MODIS Based Estimation of Forest Aboveground Biomass in China.
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Guodong Yin
Full Text Available Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS dataset in a machine learning algorithm (the model tree ensemble, MTE. We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.
MODIS Based Estimation of Forest Aboveground Biomass in China
Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong
2015-01-01
Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha−1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y−1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y−1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y−1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests. PMID:26115195
MODIS Based Estimation of Forest Aboveground Biomass in China.
Yin, Guodong; Zhang, Yuan; Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong
2015-01-01
Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.
Estimating forest and woodland aboveground biomass using active and passive remote sensing
Wu, Zhuoting; Dye, Dennis G.; Vogel, John M.; Middleton, Barry R.
2016-01-01
Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States.
Loss of aboveground forest biomass and landscape biomass variability in Missouri, US
Brice B. Hanberry; Hong S. He; Stephen R. Shifley
2016-01-01
Disturbance regimes and forests have changed over time in the eastern United States. We examined effects of historical disturbance (circa 1813 to 1850) compared to current disturbance (circa 2004 to 2008) on aboveground, live tree biomass (for trees with diameters â¥13 cm) and landscape variation of biomass in forests of the Ozarks and Plains landscapes in Missouri, USA...
Aboveground Biomass and Litterfall Dynamics in Secondary Forest ...
African Journals Online (AJOL)
The differences in aboveground biomass, litterfall patterns and the seasonality of litterfall in three secondary forest fields aged 1, 5 and 10 years of age regenerating from degraded abandoned rubber plantation and a mature forest were studied in southern Nigeria. This is with a view to understanding the possibility of ...
Li, Shuaifeng; Lang, Xuedong; Liu, Wande; Ou, Guanglong; Xu, Hui; Su, Jianrong
2018-01-01
The relationship between biodiversity and biomass is an essential element of the natural ecosystem functioning. Our research aims at assessing the effects of species richness on the aboveground biomass and the ecological driver of this relationship in a primary Pinus kesiya forest. We sampled 112 plots of the primary P. kesiya forests in Yunnan Province. The general linear model and the structural equation model were used to estimate relative effects of multivariate factors among aboveground biomass, species richness and the other explanatory variables, including climate moisture index, soil nutrient regime and stand age. We found a positive linear regression relationship between the species richness and aboveground biomass using ordinary least squares regressions. The species richness and soil nutrient regime had no direct significant effect on aboveground biomass. However, the climate moisture index and stand age had direct effects on aboveground biomass. The climate moisture index could be a better link to mediate the relationship between species richness and aboveground biomass. The species richness affected aboveground biomass which was mediated by the climate moisture index. Stand age had direct and indirect effects on aboveground biomass through the climate moisture index. Our results revealed that climate moisture index had a positive feedback in the relationship between species richness and aboveground biomass, which played an important role in a link between biodiversity maintenance and ecosystem functioning. Meanwhile, climate moisture index not only affected positively on aboveground biomass, but also indirectly through species richness. The information would be helpful in understanding the biodiversity-aboveground biomass relationship of a primary P. kesiya forest and for forest management.
Ali, Arshad; Yan, En-Rong; Chang, Scott X; Cheng, Jun-Yang; Liu, Xiang-Yu
2017-01-01
Subtropical forests are globally important in providing ecological goods and services, but it is not clear whether functional diversity and composition can predict aboveground biomass in such forests. We hypothesized that high aboveground biomass is associated with high functional divergence (FDvar, i.e., niche complementarity) and community-weighted mean (CWM, i.e., mass ratio; communities dominated by a single plant strategy) of trait values. Structural equation modeling was employed to determine the direct and indirect effects of stand age and the residual effects of CWM and FDvar on aboveground biomass across 31 plots in secondary forests in subtropical China. The CWM model accounted for 78, 20, 6 and 2% of the variation in aboveground biomass, nitrogen concentration in young leaf, plant height and specific leaf area of young leaf, respectively. The FDvar model explained 74, 13, 7 and 0% of the variation in aboveground biomass, plant height, twig wood density and nitrogen concentration in young leaf, respectively. The variation in aboveground biomass, CWM of leaf nitrogen concentration and specific leaf area, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf explained by the joint model was 86, 20, 13, 7, 2 and 0%, respectively. Stand age had a strong positive direct effect but low indirect positive effects on aboveground biomass. Aboveground biomass was negatively related to CWM of nitrogen concentration in young leaf, but positively related to CWM of specific leaf area of young leaf and plant height, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf. Leaf and wood economics spectra are decoupled in regulating the functionality of forests, communities with diverse species but high nitrogen conservative and light acquisitive strategies result in high aboveground biomass, and hence, supporting both the mass ratio and niche complementarity hypotheses in secondary subtropical forests
Nicholas S. Skowronski; Kenneth L. Clark; Michael Gallagher; Richard A. Birdsey; John L. Hom
2014-01-01
We estimated aboveground tree biomass and change in aboveground tree biomass using repeated airborne laser scanner (ALS) acquisitions and temporally coincident ground observations of forest biomass, for a relatively undisturbed period (2004-2007; ∇07-04), a contrasting period of disturbance (2007-2009; ∇09-07...
Coronado-Molina, C.; Day, J.W.; Reyes, E.; Perez, B.C.
2004-01-01
The structure and standing crop biomass of a dwarf mangrove forest, located in the salinity transition zone ofTaylor River Slough in the Everglades National Park, were studied. Although the four mangrove species reported for Florida occurred at the study site, dwarf Rhizophora mangle trees dominated the forest. The structural characteristics of the mangrove forest were relatively simple: tree height varied from 0.9 to 1.2 meters, and tree density ranged from 7062 to 23 778 stems haa??1. An allometric relationship was developed to estimate leaf, branch, prop root, and total aboveground biomass of dwarf Rhizophora mangle trees. Total aboveground biomass and their components were best estimated as a power function of the crown area times number of prop roots as an independent variable (Y = B ?? Xa??0.5083). The allometric equation for each tree component was highly significant (pRhizophora mangle contributed 85% of total standing crop biomass. Conocarpus erectus, Laguncularia racemosa, and Avicennia germinans contributed the remaining biomass. Average aboveground biomass allocation was 69% for prop roots, 25% for stem and branches, and 6% for leaves. This aboveground biomass partitioning pattern, which gives a major role to prop roots that have the potential to produce an extensive root system, may be an important biological strategy in response to low phosphorus availability and relatively reduced soils that characterize mangrove forests in South Florida.
Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P R
2016-01-01
Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.
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Vu Thanh Nam
Full Text Available Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB and root biomass (RB based on 300 (of 45 species and 40 (of 25 species sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH and tree height (H, wood density (WD was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.
Selaya, N.G.; Anten, N.P.R.; Oomen, R.J.; Matthies, M.; Werger, M.J.A.
2007-01-01
Background and Aims Crown structure and above-ground biomass investment was studied in relation to light interception of trees and lianas growing in a 6-month-old regenerating forest. Methods The vertical distribution of total above-ground biomass, height, diameter, stem density, leaf angles and
Callie Schweitzer; Dawn Lemke; Wubishet Tadesse; Yong Wang
2015-01-01
Forests contain a large amount of carbon (C) stored as tree biomass (above and below ground), detritus, and soil organic material. The aboveground tree biomass is the most rapid change component in this forest C pool. Thus, management of forest resources can influence the net C exchange with the atmosphere by changing the amount of C stored, particularly in landscapes...
ALLOMETRIC EQUATIONS FOR ESTIMATING ABOVEGROUND BIOMASS IN PAPUA TROPICAL FOREST
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Sandhi Imam Maulana
2014-10-01
Full Text Available Allometric equations can be used to estimate biomass and carbon stock of the forest. However, so far the allometric equations for commercial species in Papua tropical forests have not been appropriately developed. In this research, allometric equations are presented based on the genera of commercial species. Few equations have been developed for the commercial species of Intsia, Pometia, Palaquium and Vatica genera and an equation of a mix of these genera. The number of trees sampled in this research was 49, with diameters (1.30 m above-ground or above buttresses ranging from 5 to 40 cm. Destructive sampling was used to collect the samples where Diameter at Breast Height (DBH and Wood Density (WD were used as predictors for dry weight of Total Above-Ground Biomass (TAGB. Model comparison and selection were based on the values of F-statistics, R-sq, R-sq (adj, and average deviation. Based on these statistical indicators, the most suitable model for Intsia, Pometia, Palaquium and Vatica genera respectively are Log(TAGB = -0.76 + 2.51Log(DBH, Log(TAGB = -0.84 + 2.57Log(DBH, Log(TAGB = -1.52 + 2.96Log(DBH, and Log(TAGB = -0.09 + 2.08Log(DBH. Additional explanatory variables such as Commercial Bole Height (CBH do not really increase the indicators’ goodness of fit for the equation. An alternative model to incorporate wood density should be considered for estimating the above-ground biomass for mixed genera. Comparing the presented mixed-genera equation; Log(TAGB = 0.205 + 2.08Log(DBH + 1.75Log(WD, R-sq: 97.0%, R-sq (adj: 96.9%, F statistics 750.67, average deviation: 3.5%; to previously published datashows that this local species specific equation differs substantially from previously published equations and this site-specific equation is considered to give a better estimation of biomass.
Daolan Zheng; Linda S. Heath; Mark J. Ducey
2008-01-01
We combined satellite (Landsat 7 and Moderate Resolution Imaging Spectrometer) and U.S. Department of Agriculture forest inventory and analysis (FIA) data to estimate forest aboveground biomass (AGB) across New England, USA. This is practical for large-scale carbon studies and may reduce uncertainty of AGB estimates. We estimate that total regional forest AGB was 1,867...
Landscape-level effects on aboveground biomass of tropical forests: A conceptual framework.
Melito, Melina; Metzger, Jean Paul; de Oliveira, Alexandre A
2018-02-01
Despite the general recognition that fragmentation can reduce forest biomass through edge effects, a systematic review of the literature does not reveal a clear role of edges in modulating biomass loss. Additionally, the edge effects appear to be constrained by matrix type, suggesting that landscape composition has an influence on biomass stocks. The lack of empirical evidence of pervasive edge-related biomass losses across tropical forests highlights the necessity for a general framework linking landscape structure with aboveground biomass. Here, we propose a conceptual model in which landscape composition and configuration mediate the magnitude of edge effects and seed-flux among forest patches, which ultimately has an influence on biomass. Our model hypothesizes that a rapid reduction of biomass can occur below a threshold of forest cover loss. Just below this threshold, we predict that changes in landscape configuration can strongly influence the patch's isolation, thus enhancing biomass loss. Moreover, we expect a synergism between landscape composition and patch attributes, where matrix type mediates the effects of edges on species decline, particularly for shade-tolerant species. To test our conceptual framework, we propose a sampling protocol where the effects of edges, forest amount, forest isolation, fragment size, and matrix type on biomass stocks can be assessed both collectively and individually. The proposed model unifies the combined effects of landscape and patch structure on biomass into a single framework, providing a new set of main drivers of biomass loss in human-modified landscapes. We argue that carbon trading agendas (e.g., REDD+) and carbon-conservation initiatives must go beyond the effects of forest loss and edges on biomass, considering the whole set of effects on biomass related to changes in landscape composition and configuration. © 2017 John Wiley & Sons Ltd.
Chen, Han Y H; Luo, Yong
2015-10-01
Biomass change of the world's forests is critical to the global carbon cycle. Despite storing nearly half of global forest carbon, the boreal biome of diverse forest types and ages is a poorly understood component of the carbon cycle. Using data from 871 permanent plots in the western boreal forest of Canada, we examined net annual aboveground biomass change (ΔAGB) of four major forest types between 1958 and 2011. We found that ΔAGB was higher for deciduous broadleaf (DEC) (1.44 Mg ha(-1) year(-1) , 95% Bayesian confidence interval (CI), 1.22-1.68) and early-successional coniferous forests (ESC) (1.42, CI, 1.30-1.56) than mixed forests (MIX) (0.80, CI, 0.50-1.11) and late-successional coniferous (LSC) forests (0.62, CI, 0.39-0.88). ΔAGB declined with forest age as well as calendar year. After accounting for the effects of forest age, ΔAGB declined by 0.035, 0.021, 0.032 and 0.069 Mg ha(-1) year(-1) per calendar year in DEC, ESC, MIX and LSC forests, respectively. The ΔAGB declines resulted from increased tree mortality and reduced growth in all forest types except DEC, in which a large biomass loss from mortality was accompanied with a small increase in growth. With every degree of annual temperature increase, ΔAGB decreased by 1.00, 0.20, 0.55 and 1.07 Mg ha(-1) year(-1) in DEC, ESC, MIX and LSC forests, respectively. With every cm decrease of annual climatic moisture availability, ΔAGB decreased 0.030, 0.045 and 0.17 Mg ha(-1) year(-1) in ESC, MIX and LSC forests, but changed little in DEC forests. Our results suggest that persistent warming and decreasing water availability have profound negative effects on forest biomass in the boreal forests of western Canada. Furthermore, our results indicate that forest responses to climate change are strongly dependent on forest composition with late-successional coniferous forests being most vulnerable to climate changes in terms of aboveground biomass. © 2015 John Wiley & Sons Ltd.
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Behera, Soumit K.; Misra, Malaya K. [Ecology and Floristic Laboratory, Department of Botany, Berhampur University, Berhampur 760 007, Orissa (India)
2006-06-15
Aboveground biomass of individual tree species by component and total biomass per unit area for four different stages of a recovering tropical dry deciduous forest stands, dominated by sal (Shorea robusta Gaertn. f.) of the Eastern Ghats, India were investigated during 2001-2002. Different periods of recovering (2, 4, 6, and 10-year) forest stands (84{sup o}13'E, 20{sup o}29'N) were selected in the Kandhamal district of Orissa, India and sample trees of all species were harvested. Tree species diversity was 23, 23, 21 and 22 in 2, 4, 6, and 10-year recovering stands, respectively. Species-wise Ixora pavetta showed the highest biomass in 2 and 4-year stands while Shorea robusta in 6 and 10-year stands. Component-wise, in all species, bole-wood contribution ranged between 22.6% and 60.9%. Aboveground tree biomass, in all the stands, was dominated by Shorea robusta, which ranged between 12.68 and 231.91Mgha{sup -1}. Total aboveground tree biomass was 30.12, 49.21, 107.54 and 261.08Mgha{sup -1} in 2, 4, 6 and 10-year stands, respectively. (author)
Remote Sensing of Aboveground Biomass in Tropical Secondary Forests: A Review
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J. M. Barbosa
2014-01-01
Full Text Available Tropical landscapes are, in general, a mosaic of pasture, agriculture, and forest undergoing various stages of succession. Forest succession is comprised of continuous structural changes over time and results in increases in aboveground biomass (AGB. New remote sensing methods, including sensors, image processing, statistical methods, and uncertainty evaluations, are constantly being developed to estimate biophysical forest changes. We review 318 peer-reviewed studies related to the use of remotely sensed AGB estimations in tropical forest succession studies and summarize their geographic distribution, sensors and methods used, and their most frequent ecological inferences. Remotely sensed AGB is broadly used in forest management studies, conservation status evaluations, carbon source and sink investigations, and for studies of the relationships between environmental conditions and forest structure. Uncertainties in AGB estimations were found to be heterogeneous with biases related to sensor type, processing methodology, ground truthing availability, and forest characteristics. Remotely sensed AGB of successional forests is more reliable for the study of spatial patterns of forest succession and over large time scales than that of individual stands. Remote sensing of temporal patterns in biomass requires further study, in particular, as it is critical for understanding forest regrowth at scales useful for regional or global analyses.
Some metals in aboveground biomass of Scots pine in Lithuania
DEFF Research Database (Denmark)
Varnagiryte-Kabašinskiene, Iveta; Armolaitis, Kestutis; Stupak, Inge
2014-01-01
with stemwood and living branches. However, metal export with aboveground biomass represented relatively small proportion of metals in mineral sandy soil. The annual inputs of Fe and Zn with atmospheric deposition were over 10 times higher than the mean annual removals with total aboveground biomass....... The content of metals in forest biomass fuel ash was relatively small to compare with their total removals. The findings of this study have an important implications for future practice, i.e. the recommended maximum forest biomass fuel ash dose for the compensating fertilising could be increased with respect...... to balanced output - input in Lithuania....
CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.
2013-12-01
Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily
Luo, Xu; Wang, Yu Li; Zhang, Jin Quan
2018-03-01
Predicting the effects of climate warming and fire disturbance on forest aboveground biomass is a central task of studies in terrestrial ecosystem carbon cycle. The alteration of temperature, precipitation, and disturbance regimes induced by climate warming will affect the carbon dynamics of forest ecosystem. Boreal forest is an important forest type in China, the responses of which to climate warming and fire disturbance are increasingly obvious. In this study, we used a forest landscape model LANDIS PRO to simulate the effects of climate change on aboveground biomass of boreal forests in the Great Xing'an Mountains, and compared direct effects of climate warming and the effects of climate warming-induced fires on forest aboveground biomass. The results showed that the aboveground biomass in this area increased under climate warming scenarios and fire disturbance scenarios with increased intensity. Under the current climate and fire regime scenario, the aboveground biomass in this area was (97.14±5.78) t·hm -2 , and the value would increase up to (97.93±5.83) t·hm -2 under the B1F2 scenario. Under the A2F3 scenario, aboveground biomass at landscape scale was relatively higher at the simulated periods of year 100-150 and year 150-200, and the value were (100.02±3.76) t·hm -2 and (110.56±4.08) t·hm -2 , respectively. Compared to the current fire regime scenario, the predicted biomass at landscape scale was increased by (0.56±1.45) t·hm -2 under the CF2 scenario (fire intensity increased by 30%) at some simulated periods, and the aboveground biomass was reduced by (7.39±1.79) t·hm -2 in CF3 scenario (fire intensity increased by 230%) at the entire simulation period. There were significantly different responses between coniferous and broadleaved species under future climate warming scenarios, in that the simulated biomass for both Larix gmelinii and Betula platyphylla showed decreasing trend with climate change, whereas the simulated biomass for Pinus
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Sylvanus Mensah
2016-04-01
Full Text Available Biomass and carbon stocks are key information criteria to understand the role of forests in regulating global climate. However, for a bio-rich continent like Africa, ground-based measurements for accurate estimation of carbon are scarce, and the variables affecting the forest carbon are not well understood. Here, we present the first biomass study conducted in South Africa Mistbelt forests. Using data from a non-destructive sampling of 59 trees of four species, we (1 evaluated the accuracy of multispecies aboveground biomass (AGB models, using predictors such as diameter at breast height (DBH, total height (H and wood density; (2 estimated the amount of biomass and carbon stored in the aboveground compartment of Mistbelt forests and (3 explored the variation of aboveground carbon (AGC in relation to tree species diversity and structural variables. We found significant effects of species on wood density and AGB. Among the candidate models, the model that incorporated DBH and H as a compound variable (DBH2 × H was the best fitting. AGB and AGC values were highly variable across all plots, with average values of 358.1 Mg·ha−1 and 179.0 Mg·C·ha−1, respectively. Few species contributed 80% of AGC stock, probably as a result of selection effect. Stand basal area, basal area of the ten most important species and basal area of the largest trees were the most influencing variables. Tree species richness was also positively correlated with AGC, but the basal area of smaller trees was not. These results enable insights into the role of biodiversity in maintaining carbon storage and the possibilities for sustainable strategies for timber harvesting without risk of significant biomass decline.
Liu, Feng; Tan, Chang; Lei, Pi-Feng
2014-11-01
Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.
Yadav, Bechu K V; Nandy, S
2015-05-01
Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.
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Katsuto Shimizu
2014-11-01
Full Text Available The objectives of this study are to: (1 evaluate accuracy of tree height measurements of manual stereo viewing on a computer display using digital aerial photographs compared with airborne LiDAR height measurements; and (2 develop an empirical model to estimate stand-level aboveground biomass with variables derived from manual stereo viewing on the computer display in a Cambodian tropical seasonal forest. We evaluate observation error of tree height measured from the manual stereo viewing, based on field measurements. RMSEs of tree height measurement with manual stereo viewing and LiDAR were 1.96 m and 1.72 m, respectively. Then, stand-level aboveground biomass is regressed against tree height indices derived from the manual stereo viewing. We determined the best model to estimate aboveground biomass in terms of the Akaike’s information criterion. This was a model of mean tree height of the tallest five trees in each plot (R2 = 0.78; RMSE = 58.18 Mg/ha. In conclusion, manual stereo viewing on the computer display can measure tree height accurately and is useful to estimate aboveground stand biomass.
Biomass resilience of Neotropical secondary forests.
Poorter, Lourens; Bongers, Frans; Aide, T Mitchell; Almeyda Zambrano, Angélica M; Balvanera, Patricia; Becknell, Justin M; Boukili, Vanessa; Brancalion, Pedro H S; Broadbent, Eben N; Chazdon, Robin L; Craven, Dylan; de Almeida-Cortez, Jarcilene S; Cabral, George A L; de Jong, Ben H J; Denslow, Julie S; Dent, Daisy H; DeWalt, Saara J; Dupuy, Juan M; Durán, Sandra M; Espírito-Santo, Mario M; Fandino, María C; César, Ricardo G; Hall, Jefferson S; Hernandez-Stefanoni, José Luis; Jakovac, Catarina C; Junqueira, André B; Kennard, Deborah; Letcher, Susan G; Licona, Juan-Carlos; Lohbeck, Madelon; Marín-Spiotta, Erika; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R F; Ochoa-Gaona, Susana; de Oliveira, Alexandre A; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A; Piotto, Daniel; Powers, Jennifer S; Rodríguez-Velázquez, Jorge; Romero-Pérez, I Eunice; Ruíz, Jorge; Saldarriaga, Juan G; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B; Steininger, Marc K; Swenson, Nathan G; Toledo, Marisol; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D M; Vester, Hans F M; Vicentini, Alberto; Vieira, Ima C G; Bentos, Tony Vizcarra; Williamson, G Bruce; Rozendaal, Danaë M A
2016-02-11
Land-use change occurs nowhere more rapidly than in the tropics, where the imbalance between deforestation and forest regrowth has large consequences for the global carbon cycle. However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates are influenced by climate, landscape, and prior land use. Here we analyse aboveground biomass recovery during secondary succession in 45 forest sites and about 1,500 forest plots covering the major environmental gradients in the Neotropics. The studied secondary forests are highly productive and resilient. Aboveground biomass recovery after 20 years was on average 122 megagrams per hectare (Mg ha(-1)), corresponding to a net carbon uptake of 3.05 Mg C ha(-1) yr(-1), 11 times the uptake rate of old-growth forests. Aboveground biomass stocks took a median time of 66 years to recover to 90% of old-growth values. Aboveground biomass recovery after 20 years varied 11.3-fold (from 20 to 225 Mg ha(-1)) across sites, and this recovery increased with water availability (higher local rainfall and lower climatic water deficit). We present a biomass recovery map of Latin America, which illustrates geographical and climatic variation in carbon sequestration potential during forest regrowth. The map will support policies to minimize forest loss in areas where biomass resilience is naturally low (such as seasonally dry forest regions) and promote forest regeneration and restoration in humid tropical lowland areas with high biomass resilience.
Finegan, B.; Pena Claros, M.; Silva de Oliveira, A.; Ascarrunz, N.; Bret-Harte, M.S.; Carreño Rocabado, I.G.; Casanoves, F.; Diaz, S.; Eguiguren Velepucha, P.; Fernandez, F.; Licona, J.C.; Lorenzo, L.; Salgado Negret, B.; Vaz, M.; Poorter, L.
2014-01-01
1. Tropical forests are globally important, but it is not clear whether biodiversity enhances carbon storage and sequestration in them. We tested this relationship focusing on components of functional trait biodiversity as predictors. 2. Data are presented for three rain forests in Bolivia, Brazil and Costa Rica. Initial above-ground biomass and biomass increments of survivors, recruits and survivors + recruits (total) were estimated for trees ≥10 cm d.b.h. in 62 and 21 1.0-ha plots, respecti...
Estimating Stand Volume and Above-Ground Biomass of Urban Forests Using LiDAR
Directory of Open Access Journals (Sweden)
Vincenzo Giannico
2016-04-01
Full Text Available Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR. In this study we assessed forest stand volume and above-ground biomass (AGB in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA and mean stand height (H from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first (proxy of BA and the 95th percentile of the distribution of all first returns (proxy of H. The R2 were 0.81 (p < 0.01 for the stand volume model and 0.77 (p < 0.01 for the AGB model with a RMSE of 23.66 m3·ha−1 (23.3% and 19.59 Mg·ha−1 (23.9%, respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H, which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods.
Satellite detection of land-use change and effects on regional forest aboveground biomass estimates
Daolan Zheng; Linda S. Heath; Mark J. Ducey
2008-01-01
We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...
Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon
Longo, Marcos; Keller, Michael; Dos-Santos, Maiza N.; Leitold, Veronika; Pinage, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.
2016-01-01
Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).
Energy Technology Data Exchange (ETDEWEB)
Lee Spangler; Lee A. Vierling; Eva K. Stand; Andrew T. Hudak; Jan U.H. Eitel; Sebastian Martinuzzi
2012-04-01
Sound policy recommendations relating to the role of forest management in mitigating atmospheric carbon dioxide (CO{sub 2}) depend upon establishing accurate methodologies for quantifying forest carbon pools for large tracts of land that can be dynamically updated over time. Light Detection and Ranging (LiDAR) remote sensing is a promising technology for achieving accurate estimates of aboveground biomass and thereby carbon pools; however, not much is known about the accuracy of estimating biomass change and carbon flux from repeat LiDAR acquisitions containing different data sampling characteristics. In this study, discrete return airborne LiDAR data was collected in 2003 and 2009 across {approx}20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho, USA. Forest inventory plots, established via a random stratified sampling design, were established and sampled in 2003 and 2009. The Random Forest machine learning algorithm was used to establish statistical relationships between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level. Over this 6-year period, we found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). In these non-harvested areas, we found a significant difference in biomass increase among forest successional stages, with a higher biomass increase in mature and old forest compared to stand initiation and young forest. Approximately 20% of the landscape had been disturbed by harvest activities during the six-year time period, representing a biomass loss of >70 Mg/ha in these areas. During the study period, these harvest activities outweighed growth at the landscape scale, resulting in an overall loss in aboveground carbon at this site. The 30-fold increase in sampling density
Lü, Xiao-Tao; Tang, Jian-Wei; Feng, Zhi-Li; Li, Mai-He
2009-01-01
Lianas are important components of tropical forests and have significant impacts on the diversity, structure and dynamics of tropical forests. The present study documented the liana flora in a Chinese tropical region. Species richness, abundance, size-class distribution and spatial patterns of lianas were investigated in three 1-ha plots in tropical seasonal rain forests in Xishuangbanna, SW China. All lianas with > or = 2 cm diameter at breast height (dbh) were measured, tagged and identified. A total of 458 liana stems belonging to 95 species (ranging from 38 to 50 species/ha), 59 genera and 32 families were recorded in the three plots. The most well-represented families were Loganiaceae, Annonceae, Papilionaceae, Apocynaceae and Rhamnaceae. Papilionaceae (14 species recorded) was the most important family in the study forests. The population density, basal area and importance value index (IVI) varied greatly across the three plots. Strychnos cathayensis, Byttneria grandifolia and Bousigonia mekongensis were the dominant species in terms of IVI across the three plots. The mean aboveground biomass of lianas (3 396 kg/ha) accounted for 1.4% of the total community above-ground biomass. The abundance, diversity and biomass of lianas in Xishuangbanna tropical seasonal rain forests are lower than those in tropical moist and wet forests, but higher than those in tropical dry forests. This study provides new data on lianas from a geographical region that has been little-studied. Our findings emphasize that other factors beyond the amount and seasonality of precipitation should be included when considering the liana abundance patterns across scales.
Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann
2010-01-01
Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...
H. Viana; J. Aranha; D. Lopes; Warren B. Cohen
2012-01-01
Spatially crown biomass of Pinus pinaster stands and shrubland above-ground biomass (AGB) estimation was carried-out in a region located in Centre-North Portugal, by means of different approaches including forest inventory data, remotely sensed imagery and spatial prediction models. Two cover types (pine stands and shrubland) were inventoried and...
Kevin M. Potter; Christopher W. Woodall
2014-01-01
Biodiversity conveys numerous functional benefits to forested ecosystems, including community stability and resilience. In the context of managing forests for climate change mitigation/adaptation, maximizing and/or maintaining aboveground biomass will require understanding the interactions between tree biodiversity, site productivity, and the stocking of live trees....
Christopher W. Woodall; Linda S. Heath; Grant M. Domke; Michael C. Nichols
2011-01-01
The U.S. Forest Service, Forest Inventory and Analysis (FIA) program uses numerous models and associated coefficients to estimate aboveground volume, biomass, and carbon for live and standing dead trees for most tree species in forests of the United States. The tree attribute models are coupled with FIA's national inventory of sampled trees to produce estimates of...
Dai, Er Fu; Zhou, Heng; Wu, Zhuo; Wang, Xiao-Fan; Xi, Wei Min; Zhu, Jian Jia
2016-10-01
Global climate warming has significant effect on territorial ecosystem, especially on forest ecosystem. The increase in temperature and radiative forcing will significantly alter the structure and function of forest ecosystem. The southern plantation is an important part of forests in China, its response to climate change is getting more and more intense. In order to explore the responses of southern plantation to climate change under future climate scenarios and to reduce the losses that might be caused by climate change, we used climatic estimated data under three new emission scenarios, representative concentration pathways (RCPs) scenarios (RCP2.6 scenario, RCP4.5 scenario, and RCP8.5 scenario). We used the spatially dynamic forest landscape model LANDIS-2, coupled with a forest ecosystem process model PnET-2, to simulate the impact of climate change on aboveground net primary production (ANPP), species' establishment probability (SEP) and aboveground biomass of Moshao forest farm in Huitong Ecological Station, which located in Hunan Province during the period of 2014-2094. The results showed that there were obvious differences in SEP and ANPP among different forest types under changing climate. The degrees of response of SEP to climate change for different forest types were shown as: under RCP2.6 and RCP4.5, artificial coniferous forest>natural broadleaved forest>artificial broadleaved forest. Under RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The degrees of response of ANPP to climate change for different forest types were shown as: under RCP2.6, artificial broadleaved forest> natural broadleaved forest>artificial coniferous forest. Under RCP4.5 and RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The aboveground biomass of the artificial coniferous forest would decline at about 2050, but the natural broadleaved forest and artificial broadleaved forest showed a
Canada's forest biomass resources: deriving estimates from Canada's forest inventory
International Nuclear Information System (INIS)
Penner, M.; Power, K.; Muhairwe, C.; Tellier, R.; Wang, Y.
1997-01-01
A biomass inventory for Canada was undertaken to address the data needs of carbon budget modelers, specifically to provide estimates of above-ground tree components and of non-merchantable trees in Canadian forests. The objective was to produce a national method for converting volume estimates to biomass that was standardized, repeatable across the country, efficient and well documented. Different conversion methods were used for low productivity forests (productivity class 1) and higher productivity forests (productivity class 2). The conversion factors were computed by constructing hypothetical stands for each site, age, species and province combination, and estimating the merchantable volume and all the above-ground biomass components from suitable published equations. This report documents the procedures for deriving the national biomass inventory, and provides illustrative examples of the results. 46 refs., 9 tabs., 5 figs
Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.
2017-12-01
The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement
Aboveground Tree Biomass for Pinus ponderosa in Northeastern California
Directory of Open Access Journals (Sweden)
Todd A. Hamilton
2013-03-01
Full Text Available Forest managers need accurate biomass equations to plan thinning for fuel reduction or energy production. Estimates of carbon sequestration also rely upon such equations. The current allometric equations for ponderosa pine (Pinus ponderosa commonly employed for California forests were developed elsewhere, and are often applied without consideration potential for spatial or temporal variability. Individual-tree aboveground biomass allometric equations are presented from an analysis of 79 felled trees from four separate management units at Blacks Mountain Experimental Forest: one unthinned and three separate thinned units. A simultaneous set of allometric equations for foliage, branch and bole biomass were developed as well as branch-level equations for wood and foliage. Foliage biomass relationships varied substantially between units while branch and bole biomass estimates were more stable across a range of stand conditions. Trees of a given breast height diameter and crown ratio in thinned stands had more foliage biomass, but slightly less branch biomass than those in an unthinned stand. The observed variability in biomass relationships within Blacks Mountain Experimental Forest suggests that users should consider how well the data used to develop a selected model relate to the conditions in any given application.
Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.
2017-07-01
Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.
Forest biomass variation in Southernmost Brazil: the impact of Araucaria trees.
Rosenfield, Milena Fermina; Souza, Alexandre F
2014-03-01
A variety of environmental and biotic factors determine vegetation growth and affect plant biomass accumulation. From temperature to species composition, aboveground biomass storage in forest ecosystems is influenced by a number of variables and usually presents a high spatial variability. With this focus, the aim of the study was to evaluate the variables affecting live aboveground forest biomass (AGB) in Subtropical Moist Forests of Southern Brazil, and to analyze the spatial distribution of biomass estimates. Data from a forest inventory performed in the State of Rio Grande do Sul, Southern Brazil, was used in the present study. Thirty-eight 1-ha plots were sampled and all trees with DBH > or = 9.5cm were included for biomass estimation. Values for aboveground biomass were obtained using published allometric equations. Environmental and biotic variables (elevation, rainfall, temperature, soils, stem density and species diversity) were obtained from the literature or calculated from the dataset. For the total dataset, mean AGB was 195.2 Mg/ha. Estimates differed between Broadleaf and Mixed Coniferous-Broadleaf forests: mean AGB was lower in Broadleaf Forests (AGB(BF)=118.9 Mg/ha) when compared to Mixed Forests (AGB(MF)=250.3 Mg/ha). There was a high spatial and local variability in our dataset, even within forest types. This condition is normal in tropical forests and is usually attributed to the presence of large trees. The explanatory multiple regressions were influenced mainly by elevation and explained 50.7% of the variation in AGB. Stem density, diversity and organic matter also influenced biomass variation. The results from our study showed a positive relationship between aboveground biomass and elevation. Therefore, higher values of AGB are located at higher elevations and subjected to cooler temperatures and wetter climate. There seems to be an important contribution of the coniferous species Araucaria angustifolia in Mixed Forest plots, as it presented
Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh
2017-09-01
Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates
Estimates of forest canopy height and aboveground biomass using ICESat.
Michael A. Lefsky; David J. Harding; Michael Keller; Warren B. Cohen; Claudia C. Carabajal; Fernando Del Bom; Maria O. Hunter; Raimundo Jr. de Oliveira
2005-01-01
Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land...
Environmental and biotic controls over aboveground biomass throughout a tropical rainforest
G.P. Asner; R.F. Hughes; T.A. Varga; D.E. Knapp; T. Kennedy-Bowdoin
2009-01-01
The environmental and biotic factors affecting spatial variation in canopy three-dimensional (3-D) structure and aboveground tree biomass (AGB) are poorly understood in tropical rain forests. We combined field measurements and airborne light detection and ranging (lidar) to quantify 3-D structure and AGB across a 5,016 ha rain forest reserve on the...
Demographic controls of aboveground forest biomass across North America.
Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W
2016-04-01
Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). © 2016 John Wiley & Sons Ltd/CNRS.
Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data
Narine, L.; Popescu, S. C.; Neuenschwander, A. L.
2017-12-01
The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.
Aboveground Biomass Monitoring over Siberian Boreal Forest Using Radar Remote Sensing Data
Stelmaszczuk-Gorska, M. A.; Thiel, C. J.; Schmullius, C.
2014-12-01
Aboveground biomass (AGB) plays an essential role in ecosystem research, global cycles, and is of vital importance in climate studies. AGB accumulated in the forests is of special monitoring interest as it contains the most of biomass comparing with other land biomes. The largest of the land biomes is boreal forest, which has a substantial carbon accumulation capability; carbon stock estimated to be 272 +/-23 Pg C (32%) [1]. Russian's forests are of particular concern, due to the largest source of uncertainty in global carbon stock calculations [1], and old inventory data that have not been updated in the last 25 years [2]. In this research new empirical models for AGB estimation are proposed. Using radar L-band data for AGB retrieval and optical data for an update of in situ data the processing scheme was developed. The approach was trained and validated in the Asian part of the boreal forest, in southern Russian Central Siberia; two Siberian Federal Districts: Krasnoyarsk Kray and Irkutsk Oblast. Together the training and testing forest territories cover an area of approximately 3,500 km2. ALOS PALSAR L-band single (HH - horizontal transmitted and received) and dual (HH and HV - horizontal transmitted, horizontal and vertical received) polarizations in Single Look Complex format (SLC) were used to calculate backscattering coefficient in gamma nought and coherence. In total more than 150 images acquired between 2006 and 2011 were available. The data were obtained through the ALOS Kyoto and Carbon Initiative Project (K&C). The data were used to calibrate a randomForest algorithm. Additionally, a simple linear and multiple-regression approach was used. The uncertainty of the AGB estimation at pixel and stand level were calculated approximately as 35% by validation against an independent dataset. The previous studies employing ALOS PALSAR data over boreal forests reported uncertainty of 39.4% using randomForest approach [2] or 42.8% using semi-empirical approach [3].
Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA)...
Final Harvest of Above-Ground Biomass and Allometric Analysis of the Aspen FACE Experiment
Energy Technology Data Exchange (ETDEWEB)
Mark E. Kubiske
2013-04-15
The Aspen FACE experiment, located at the US Forest Service Harshaw Research Facility in Oneida County, Wisconsin, exposes the intact canopies of model trembling aspen forests to increased concentrations of atmospheric CO2 and O3. The first full year of treatments was 1998 and final year of elevated CO2 and O3 treatments is scheduled for 2009. This proposal is to conduct an intensive, analytical harvest of the above-ground parts of 24 trees from each of the 12, 30 m diameter treatment plots (total of 288 trees) during June, July & August 2009. This above-ground harvest will be carefully coordinated with the below-ground harvest proposed by D.F. Karnosky et al. (2008 proposal to DOE). We propose to dissect harvested trees according to annual height growth increment and organ (main stem, branch orders, and leaves) for calculation of above-ground biomass production and allometric comparisons among aspen clones, species, and treatments. Additionally, we will collect fine root samples for DNA fingerprinting to quantify biomass production of individual aspen clones. This work will produce a thorough characterization of above-ground tree and stand growth and allocation above ground, and, in conjunction with the below ground harvest, total tree and stand biomass production, allocation, and allometry.
Robert M. Hubbard; James M. Vose; Barton D. Clinton; Katherine J. Elliott; Jennifer D. Knoepp
2004-01-01
Understory prescribed burning is being suggested as a viable management tool for restoring degraded oakâpine forest communities in the southern Appalachians yet information is lacking on how this will affect ecosystem processes. Our objectives in this study were to evaluate the watershed scale effects of understory burning on total aboveground biomass, and the carbon...
Modeling loblolly pine aboveground live biomass in a mature pine-hardwood stand: a cautionary tale
D. C. Bragg
2011-01-01
Carbon sequestration in forests is a growing area of interest for researchers and land managers. Calculating the quantity of carbon stored in forest biomass seems to be a straightforward task, but it is highly dependent on the function(s) used to construct the stand. For instance, there are a number of possible equations to predict aboveground live biomass for loblolly...
Meyer, Victoria; Saatchi, Sassan; Clark, David B.; Keller, Michael; Vincent, Grégoire; Ferraz, António; Espírito-Santo, Fernando; d'Oliveira, Marcus V. N.; Kaki, Dahlia; Chave, Jérôme
2018-06-01
Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (˜ 25-30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha-1, bias = -0.63 Mg ha-1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA-AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.
Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles
In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such
Salinas-Melgoza, Miguel A.; Skutsch, Margaret; Lovett, Jon C.
2018-01-01
Topographic variables such as slope and elevation partially explain spatial variations in aboveground biomass (AGB) within landscapes. Human activities that impact vegetation, such as cattle grazing and shifting cultivation, often follow topographic features and also play a key role in determining
Evaluating lidar point densities for effective estimation of aboveground biomass
Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason M.; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.
2016-01-01
The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.
Sakici, Oytun Emre; Kucuk, Omer; Ashraf, Muhammad Irfan
2018-04-15
Small trees and saplings are important for forest management, carbon stock estimation, ecological modeling, and fire management planning. Turkish pine (Pinus brutia Ten.) is a common coniferous species and comprises 25.1% of total forest area of Turkey. Turkish pine is also important due to its flammable fuel characteristics. In this study, compatible above-ground biomass equations were developed to predict needle, branch, stem wood, and above-ground total biomass, and carbon stock assessment was also described for Turkish pine which is smaller than 8 cm diameter at breast height or shorter than breast height. Compatible biomass equations are useful for biomass prediction of small diameter individuals of Turkish pine. These equations will also be helpful in determining fire behavior characteristics and calculating their carbon stock. Overall, present study will be useful for developing ecological models, forest management plans, silvicultural plans, and fire management plans.
Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall
2017-01-01
Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...
Siberian Boreal Forest Aboveground Biomass and Fire Scar Maps, Russia, 1969-2007
National Aeronautics and Space Administration — This data set provides 30-meter resolution mapped estimates of Cajander larch (Larix cajanderi) aboveground biomass (AGB), circa 2007, and a map of burn perimeters...
Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon
Marcos Longo; Michael Keller; Maiza N. dos-Santos; Veronika Leitold; Ekena R. Pinagé; Alessandro Baccini; Sassan Saatchi; Euler M. Nogueira; Mateus Batistella; Douglas C. Morton
2016-01-01
Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha)...
Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska
Ji, Lei; Wylie, Bruce K.; Brown, Dana R. N.; Peterson, Birgit E.; Alexander, Heather D.; Mack, Michelle C.; Rover, Jennifer R.; Waldrop, Mark P.; McFarland, Jack W.; Chen, Xuexia; Pastick, Neal J.
2015-01-01
Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.
ROOT BIOMASS ALLOCATION IN THE WORLD'S UPLAND FORESTS
Because the world's forests play a major role in regulating nutrient and carbon cycles, there is much interest in estimating their biomass. Estimates of aboveground biomass based on well-established methods are relatively abundant; estimates of root biomass based on standard meth...
Non-Destructive, Laser-Based Individual Tree Aboveground Biomass Estimation in a Tropical Rainforest
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Muhammad Zulkarnain Abd Rahman
2017-03-01
Full Text Available Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been driven by advances in remote sensing technology. The conventional approach to biomass estimation heavily relies on the tree species and site-specific allometric equations, which are based on destructive methods. This paper introduces a non-destructive, laser-based approach (terrestrial laser scanner for individual tree aboveground biomass estimation in the Royal Belum forest reserve, Perak, Malaysia. The study area is in the state park, and it is believed to be one of the oldest rainforests in the world. The point clouds generated for 35 forest plots, using the terrestrial laser scanner, were geo-rectified and cleaned to produce separate point clouds for individual trees. The volumes of tree trunks were estimated based on a cylinder model fitted to the point clouds. The biomasses of tree trunks were calculated by multiplying the volume and the species wood density. The biomasses of branches and leaves were also estimated based on the estimated volume and density values. Branch and leaf volumes were estimated based on the fitted point clouds using an alpha-shape approach. The estimated individual biomass and the total above ground biomass were compared with the aboveground biomass (AGB value estimated using existing allometric equations and individual tree census data collected in the field. The results show that the combination of a simple single-tree stem reconstruction and wood density can be used to estimate stem biomass comparable to the results usually obtained through existing allometric equations. However, there are several issues associated with the data and method used for branch and leaf biomass estimations, which need further improvement.
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Tianyu Hu
2016-07-01
Full Text Available As a large carbon pool, global forest ecosystems are a critical component of the global carbon cycle. Accurate estimations of global forest aboveground biomass (AGB can improve the understanding of global carbon dynamics and help to quantify anthropogenic carbon emissions. Light detection and ranging (LiDAR techniques have been proven that can accurately capture both horizontal and vertical forest structures and increase the accuracy of forest AGB estimation. In this study, we mapped the global forest AGB density at a 1-km resolution through the integration of ground inventory data, optical imagery, Geoscience Laser Altimeter System/Ice, Cloud, and Land Elevation Satellite data, climate surfaces, and topographic data. Over 4000 ground inventory records were collected from published literatures to train the forest AGB estimation model and validate the resulting global forest AGB product. Our wall-to-wall global forest AGB map showed that the global forest AGB density was 210.09 Mg/ha on average, with a standard deviation of 109.31 Mg/ha. At the continental level, Africa (333.34 ± 63.80 Mg/ha and South America (301.68 ± 67.43 Mg/ha had higher AGB density. The AGB density in Asia, North America and Europe were 172.28 ± 94.75, 166.48 ± 84.97, and 132.97 ± 50.70 Mg/ha, respectively. The wall-to-wall forest AGB map was evaluated at plot level using independent plot measurements. The adjusted coefficient of determination (R2 and root-mean-square error (RMSE between our predicted results and the validation plots were 0.56 and 87.53 Mg/ha, respectively. At the ecological zone level, the R2 and RMSE between our map and Intergovernmental Panel on Climate Change suggested values were 0.56 and 101.21 Mg/ha, respectively. Moreover, a comprehensive comparison was also conducted between our forest AGB map and other published regional AGB products. Overall, our forest AGB map showed good agreements with these regional AGB products, but some of the regional
Motlagh, Mohadeseh Ghanbari; Kafaky, Sasan Babaie; Mataji, Asadollah; Akhavan, Reza
2018-05-21
Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.
Xiaoping Zhou; Miles A. Hemstrom
2009-01-01
Live tree biomass estimates are essential for carbon accounting, bioenergy feasibility studies, and other analyses. Several models are currently used for estimating tree biomass. Each of these incorporates different calculation methods that may significantly impact the estimates of total aboveground tree biomass, merchantable biomass, and carbon pools. Consequently,...
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Andreas Langner
2015-08-01
Full Text Available This study investigates how two existing pan-tropical above-ground biomass (AGB maps (Saatchi 2011, Baccini 2012 can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5% leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest and lowest AGB values (305.8 t/ha and 136.5 t/ha respectively. The AGB of all natural forests amounts to 10.8 Gt mainly stemming from lowland dipterocarp (66.4%, upper dipterocarp (10.9% and peat swamp forests (10.2%. Degraded forests account for another 2.1 Gt of AGB. One main advantage of our approach is that, once the best fitting data-fusion model is selected, no further AGB reference dataset is required for implementing the data-fusion process. Furthermore, the local harmonization of AGB datasets leads to more spatially precise maps. This approach can easily be extended to other areas in Southeast Asia which are dominated by lowland dipterocarp forest, and can be repeated when newer or more accurate AGB maps become available.
Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto
2017-09-08
Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.
Thomas J. Brandeis; Maria Del Rocio; Suarez Rozo
2005-01-01
Total aboveground live tree biomass in Puerto Rican lower montane wet, subtropical wet, subtropical moist and subtropical dry forests was estimated using data from two forest inventories and published regression equations. Multiple potentially-applicable published biomass models existed for some forested life zones, and their estimates tended to diverge with increasing...
Tree height and tropical forest biomass estimation
M.O. Hunter; M. Keller; D. Vitoria; D.C. Morton
2013-01-01
Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass....
Biomass and nutrient dynamics associated with slash fires in neotropical dry forests
International Nuclear Information System (INIS)
Kauffman, J.B.; Cummings, D.L.; Sanford, R.L. Jr.; Salcedo, I.H.; Sampaio, E.V.S.B.
1993-01-01
Unprecedented rates of deforestation and biomass burning in tropical dry forests are dramatically influencing biogeochemical cycles, resulting in resource depletion, declines in biodiversity, and atmospheric pollution. We quantified the effects of deforestation and varying levels of slash-fire severity on nutrient losses and redistribution in a second-growth tropical dry forest (open-quotes Caatingaclose quotes) near Serra Talhada, Pernambuco, Brazil. Total aboveground biomass prior to burning was ∼74 Mg/ha. Nitrogen and phosphorus concentrations were highest in litter, leaves attached to slash, and fine wood debris (< O.64 cm diameter). While these components comprised only 30% of the prefire aboveground biomass, they accounted for ∼60% of the aboveground pools of N and P. Three experimental fires were conducted during the 1989 burning season. Consumption was 78, 88, and 95% of the total aboveground biomass. As much as 96% of the prefire aboveground N and C pools and 56% of the prefire aboveground P pool was lost. Nitrogen losses exceeded 500 kg/ha and P losses exceeded 20 kg/ha in the fires of the greatest severity. With increasing fire severity, the concentrations of N and P in ash decreased while the concentration of Ca increased. Greater ecosystem losses of these nutrients occurred with increasing fire severity. Following fire, up to 47% of the residual aboveground N and 84% of the residual aboveground P were in the form of ash, quickly lost from the site via wind erosion. Fires appeared to have a minor immediate effect on total N, C, or P in the soils. However, soils in forests with no history of cultivation had significantly higher concentrations of C and P than second-growth forests. It would likely require a century or more of fallow for reaccumulation to occur. However, current fallow periods in this region are 15 yr or less. 38 refs., 2 figs., 7 tabs
Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys
Andrew T. Hudak; Eva K. Strand; Lee A. Vierling; John C. Byrne; Jan U. H. Eitel; Sebastian Martinuzzi; Michael J. Falkowski
2012-01-01
Sound forest policy and management decisions to mitigate rising atmospheric CO2 depend upon accurate methodologies to quantify forest carbon pools and fluxes over large tracts of land. LiDAR remote sensing is a rapidly evolving technology for quantifying aboveground biomass and thereby carbon pools; however, little work has evaluated the efficacy of repeat LiDAR...
Ali, Arshad; Mattsson, Eskil
2017-01-01
Individual tree size variation, which is generally quantified by variances in tree diameter at breast height (DBH) and height in isolation or conjunction, plays a central role in ecosystem functioning in both controlled and natural environments, including forests. However, none of the studies have been conducted in homegarden agroforestry systems. In this study, aboveground biomass, stand quality, cation exchange capacity (CEC), DBH variation, and species diversity were determined across 45 homegardens in the dry zone of Sri Lanka. We employed structural equation modeling (SEM) to test for the direct and indirect effects of stand quality and CEC, via tree size inequality and species diversity, on aboveground biomass. The SEM accounted for 26, 8, and 1% of the variation in aboveground biomass, species diversity and DBH variation, respectively. DBH variation had the strongest positive direct effect on aboveground biomass (β=0.49), followed by the non-significant direct effect of species diversity (β=0.17), stand quality (β=0.17) and CEC (β=-0.05). There were non-significant direct effects of CEC and stand quality on DBH variation and species diversity. Stand quality and CEC had also non-significant indirect effects, via DBH variation and species diversity, on aboveground biomass. Our study revealed that aboveground biomass substantially increased with individual tree size variation only, which supports the niche complementarity mechanism. However, aboveground biomass was not considerably increased with species diversity, stand quality and soil fertility, which might be attributable to the adaptation of certain productive species to the local site conditions. Stand structure shaped by few productive species or independent of species diversity is a main determinant for the variation in aboveground biomass in the studied homegardens. Maintaining stand structure through management practices could be an effective approach for enhancing aboveground biomass in these dry
Jana, Bipal K; Biswas, Soumyajit; Majumder, Mrinmoy; Roy, Pankaj K; Mazumdar, Asis
2011-07-01
Carbon is sequestered by the plant photosynthesis and stored as biomass in different parts of the tree. Carbon sequestration rate has been measured for young species (6 years age) of Shorea robusta at Chadra forest in Paschim Medinipur district, Albizzia lebbek in Indian Botanic Garden in Howrah district and Artocarpus integrifolia at Banobitan within Kolkata in the lower Gangetic plain of West Bengal in India by Automated Vaisala Made Instrument GMP343 and aboveground biomass carbon has been analyzed by CHN analyzer. The specific objective of this paper is to measure carbon sequestration rate and aboveground biomass carbon potential of three young species of Shorea robusta, Albizzia lebbek and Artocarpus integrifolia. The carbon sequestration rate (mean) from the ambient air during winter season as obtained by Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 11.13 g/h, 14.86 g/h and 4.22g/h, respectively. The annual carbon sequestration rate from ambient air were estimated at 8.97 t C ha(-1) by Shorea robusta, 11.97 t C ha(-1) by Albizzia lebbek and 3.33 t C ha(-1) by Artocarpus integrifolia. The percentage of carbon content (except root) in the aboveground biomass of Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 47.45, 47.12 and 43.33, respectively. The total aboveground biomass carbon stock per hectare as estimated for Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 5.22 t C ha(-1) , 6.26 t C ha(-1) and 7.28 t C ha(-1), respectively in these forest stands.
Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics
Slik, J.W.F.; Paoli, G.; McGuire, K.; Amaral, I.; Barroso, J.; Bongers, F.; Poorter, L.
2013-01-01
Aim - Large trees (d.b.h.¿=¿70¿cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore
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Nicola Clerici
2016-07-01
Full Text Available Periurban forests are key to offsetting anthropogenic carbon emissions, but they are under constant threat from urbanization. In particular, secondary Neotropical forest types in Andean periurban areas have a high potential to store carbon, but are currently poorly characterized. To address this lack of information, we developed a method to estimate periurban aboveground biomass (AGB—a proxy for multiple ecosystem services—of secondary Andean forests near Bogotá, Colombia, based on very high resolution (VHR GeoEye-1, Pleiades-1A imagery and field-measured plot data. Specifically, we tested a series of different pre-processing workflows to derive six vegetation indices that were regressed against in situ estimates of AGB. Overall, the coupling of linear models and the Ratio Vegetation Index produced the most satisfactory results. Atmospheric and topographic correction proved to be key in improving model fit, especially in high aerosol and rugged terrain such as the Andes. Methods and findings provide baseline AGB and carbon stock information for little studied periurban Andean secondary forests. The methodological approach can also be used for integrating limited forest monitoring plot AGB data with very high resolution imagery for cost-effective modelling of ecosystem service provision from forests, monitoring reforestation and forest cover change, and for carbon offset assessments.
Alsumaiti, Tareefa Saad Sultan
Mangrove forests are national treasures of the United Arab Emirates (UAE) and other arid countries with limited forested areas. Mangroves form a crucial part of the coastal ecosystem and provide numerous benefits to society, economy, and especially the environment. Mangrove trees, specifically Avicennia marina, are studied in their native habitat in order to characterize their population structure, aboveground biomass, and soil properties. This study focused on Eastern Mangrove Lagoon National Park in Abu Dhabi, which was the first mangrove protected area to be designated in UAE. In situ measurements were collected to estimate Avicennia marina status, mortality rate (%), height (m), crown spread (m), stem number, diameter at breast height (cm), basal area (m), and aboveground biomass (t ha-1 ). Small-footprint aerial light detection and ranging (LIDAR) data acquired by UAE were processed to characterize mangrove canopy height and aboveground biomass density. This included extraction of LIDAR-derived height percentile statistics, segmentation of the forest into structurally homogenous units, and development of regression relationships between in situ reference and remote sensing data using a machine learning approach. An in situ soil survey was conducted to examine the soils' physical and chemical properties, fertility status, and organic matter. The data of soil survey were used to create soil maps to evaluate key characteristics of soils, and their influence on Avicennia marina in Eastern Mangrove Lagoon National Park. The results of this study provide new insights into Avicennia marina canopy population, structure, aboveground biomass, and soil properties in Abu Dhabi, as data in such arid environments is lacking. This valuable information can help in managing and preserving this unique ecosystem.
Tree height integrated into pantropical forest biomass estimates
Feldpausch, T.R.; Lloyd, J.; Lewis, S.L.; Brienen, R.J.W.; Gloor, M.; Montegudo Mendoza, A.; Arets, E.J.M.M.
2012-01-01
Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer
Allometric models for estimating the aboveground biomass of the mangrove Rhizophora mangle
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Heide Vanessa Souza Santos
Full Text Available Abstract The development of species-specific allometric models is critical to the improvement of aboveground biomass estimates, as well as to the estimation of carbon stock and sequestration in mangrove forests. This study developed allometric equations for estimating aboveground biomass of Rhizophora mangle in the mangroves of the estuary of the São Francisco River, in northeastern Brazil. Using a sample of 74 trees, simple linear regression analysis was used to test the dependence of biomass (total and per plant part on size, considering both transformed (ln and not-transformed data. Best equations were considered as those with the lowest standard error of estimation (SEE and highest adjusted coefficient of determination (R2a. The ln-transformed equations showed better results, with R2a near 0.99 in most cases. The equations for reproductive parts presented low R2a values, probably attributed to the seasonal nature of this compartment. "Basal Area2 × Height" showed to be the best predictor, present in most of the best-fitted equations. The models presented here can be considered reliable predictors of the aboveground biomass of R. mangle in the NE-Brazilian mangroves as well as in any site were this widely distributed species present similar architecture to the trees used in the present study.
Jennifer C. Jenkins; Richard A. Birdsey
2000-01-01
As interest grows in the role of forest growth in the carbon cycle, and as simulation models are applied to predict future forest productivity at large spatial scales, the need for reliable and field-based data for evaluation of model estimates is clear. We created estimates of potential forest biomass and annual aboveground production for the Chesapeake Bay watershed...
Carbon stocks in tree biomass and soils of German forests
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Wellbrock Nicole
2017-06-01
Full Text Available Close to one third of Germany is forested. Forests are able to store significant quantities of carbon (C in the biomass and in the soil. Coordinated by the Thünen Institute, the German National Forest Inventory (NFI and the National Forest Soil Inventory (NFSI have generated data to estimate the carbon storage capacity of forests. The second NFI started in 2002 and had been repeated in 2012. The reporting time for the NFSI was 1990 to 2006. Living forest biomass, deadwood, litter and soils up to a depth of 90 cm have stored 2500 t of carbon within the reporting time. Over all 224 t C ha-1 in aboveground and belowground biomass, deadwood and soil are stored in forests. Specifically, 46% stored in above-ground and below-ground biomass, 1% in dead wood and 53% in the organic layer together with soil up to 90 cm. Carbon stocks in mineral soils up to 30 cm mineral soil increase about 0.4 t C ha-1 yr-1 stocks between the inventories while the carbon pool in the organic layers declined slightly. In the living biomass carbon stocks increased about 1.0 t C ha-1 yr-1. In Germany, approximately 58 mill. tonnes of CO2 were sequestered in 2012 (NIR 2017.
Above-ground biomass of mangrove species. I. Analysis of models
Soares, Mário Luiz Gomes; Schaeffer-Novelli, Yara
2005-10-01
This study analyzes the above-ground biomass of Rhizophora mangle and Laguncularia racemosa located in the mangroves of Bertioga (SP) and Guaratiba (RJ), Southeast Brazil. Its purpose is to determine the best regression model to estimate the total above-ground biomass and compartment (leaves, reproductive parts, twigs, branches, trunk and prop roots) biomass, indirectly. To do this, we used structural measurements such as height, diameter at breast-height (DBH), and crown area. A combination of regression types with several compositions of independent variables generated 2.272 models that were later tested. Subsequent analysis of the models indicated that the biomass of reproductive parts, branches, and prop roots yielded great variability, probably because of environmental factors and seasonality (in the case of reproductive parts). It also indicated the superiority of multiple regression to estimate above-ground biomass as it allows researchers to consider several aspects that affect above-ground biomass, specially the influence of environmental factors. This fact has been attested to the models that estimated the biomass of crown compartments.
Biotic and abiotic controls on the distribution of tropical forest aboveground biomass
Saatchi, S. S.; Schimel, D.; Keller, M. M.; Chambers, J. Q.; Dubayah, R.; Duffy, P.; Yu, Y.; Robinson, C. M.; Chowdhury, D.; Yang, Y.
2013-12-01
AUTHOR: Sassan Saatchi1,2, Yan Yang2, Diya Chowdhury2, Yifan Yu2, Chelsea Robinson2, David Schimel1, Paul Duffy3, Michael Keller4, Ralph Dubayah5, Jeffery Chambers6 1. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA USA 2. Institute of Environment and Sustainability, University of California, Los Angeles, CA, USA 3. Neptune and Company, Inc. Denver, CO, USA 4. International Institute of Tropical Forestry & International Programs, USDA Forest Service, Campinas, Brazil 5. Department of Geography, University of Maryland, College Park, MD, USA 6. Department of Geography, University of California, Berkeley, CA, USA ABSTRACT BODY: In recent years, climate change policies and scientific research created a widespread interest in quantify the carbon stock and changes of global tropical forests extending from forest patches to national and regional scales. Using a combination of inventory data from field plots and forest structure from spaceborne Lidar data, we examine the main controls on the distribution of tropical forest biomass. Here, we concentrate on environmental and landscape variables (precipitation, temperature, topography, and soil), and biotic variables such as functional traits (density of large trees, and wood specific gravity). The analysis is performed using global bioclimatic variables for precipitation and temperature, SRTM data for topographical variables (elevation and ruggedness), and global harmonized soil data for soil type and texture. For biotic variables, we use the GLAS Lidar data to quantify the distribution of large trees, a combined field and remote sensing data for distribution of tree wood specific gravity. The results show that climate variables such as precipitation of dry season can explain the heterogeneity of forest biomass over the landscape but cannot predict the biomass variability significantly and particularly for high biomass forests. Topography such as elevation and ruggedness along with temperature can
Tropical forest biomass estimation from truncated stand tables.
A. J. R. Gillespie; S. Brown; A. E. Lugo
1992-01-01
Total aboveground forest biomass may be estimated through a variety of techniques based on commercial inventory stand and stock tables. Stand and stock tables from tropical countries commonly omit trees bellow a certain commercial limit.
Katherine J. Elliott; Lindsay R. Boring; Wayne T. Swank
2002-01-01
In 1975, we initiated a long-term interdisciplinary study of forest watershed ecosystem response to clear- cutting and cable logging in watershed 7 at the Coweeta Hydrologic Laboratory in the southern Appalachian Mountains of North Carolina. This paper describes ~20 years of change in species composition, aboveground biomass, leaf area index (LAI),...
Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon
2015-07-31
The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE's, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development.
Secondary Forest Age and Tropical Forest Biomass Estimation Using TM
Nelson, R. F.; Kimes, D. S.; Salas, W. A.; Routhier, M.
1999-01-01
The age of secondary forests in the Amazon will become more critical with respect to the estimation of biomass and carbon budgets as tropical forest conversion continues. Multitemporal Thematic Mapper data were used to develop land cover histories for a 33,000 Square kM area near Ariquemes, Rondonia over a 7 year period from 1989-1995. The age of the secondary forest, a surrogate for the amount of biomass (or carbon) stored above-ground, was found to be unimportant in terms of biomass budget error rates in a forested TM scene which had undergone a 20% conversion to nonforest/agricultural cover types. In such a situation, the 80% of the scene still covered by primary forest accounted for over 98% of the scene biomass. The difference between secondary forest biomass estimates developed with and without age information were inconsequential relative to the estimate of biomass for the entire scene. However, in futuristic scenarios where all of the primary forest has been converted to agriculture and secondary forest (55% and 42% respectively), the ability to age secondary forest becomes critical. Depending on biomass accumulation rate assumptions, scene biomass budget errors on the order of -10% to +30% are likely if the age of the secondary forests are not taken into account. Single-date TM imagery cannot be used to accurately age secondary forests into single-year classes. A neural network utilizing TM band 2 and three TM spectral-texture measures (bands 3 and 5) predicted secondary forest age over a range of 0-7 years with an RMSE of 1.59 years and an R(Squared) (sub actual vs predicted) = 0.37. A proposal is made, based on a literature review, to use satellite imagery to identify general secondary forest age groups which, within group, exhibit relatively constant biomass accumulation rates.
Köhler, P.; Huth, A.
2010-05-01
The canopy height of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or lidar. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI). The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. It is found that for undisturbed forest and a variety of disturbed forests situations AGB can be expressed as a power-law function of canopy height h (AGB=a·hb) with an r2~60% for a spatial resolution of 20 m×20 m (0.04 ha, also called plot size). The regression is becoming significant better for the hectare wide analysis of the disturbed forest sites (r2=91%). There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2~60%) between AGB and the area fraction in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot data from the same region and with the large-scale forest inventory in Lambir. We conclude that the spaceborne remote sensing techniques have the potential to
Manninen, Sirkku; Zverev, Vitali; Bergman, Igor; Kozlov, Mikhail V
2015-12-01
Boreal coniferous forests act as an important sink for atmospheric carbon dioxide. The overall tree carbon (C) sink in the forests of Europe has increased during the past decades, especially due to management and elevated nitrogen (N) deposition; however, industrial atmospheric pollution, primarily sulphur dioxide and heavy metals, still negatively affect forest biomass production at different spatial scales. We report local and regional changes in forest aboveground biomass, C and N concentrations in plant tissues, and C and N pools caused by long-term atmospheric emissions from a large point source, the nickel-copper smelter in Monchegorsk, in north-western Russia. An increase in pollution load (assessed as Cu concentration in forest litter) caused C to increase in foliage but C remained unchanged in wood, while N decreased in foliage and increased in wood, demonstrating strong effects of pollution on resource translocation between green and woody tissues. The aboveground C and N pools were primarily governed by plant biomass, which strongly decreased with an increase in pollution load. In our study sites (located 1.6-39.7 km from the smelter) living aboveground plant biomass was 76 to 4888 gm(-2), and C and N pools ranged 35-2333 g C m(-2) and 0.5-35.1 g N m(-2), respectively. We estimate that the aboveground plant biomass is reduced due to chronic exposure to industrial air pollution over an area of about 107,200 km2, and the total (aboveground and belowground) loss of phytomass C stock amounts to 4.24×10(13) g C. Our results emphasize the need to account for the overall impact of industrial polluters on ecosystem C and N pools when assessing the C and N dynamics in northern boreal forests because of the marked long-term negative effects of their emissions on structure and productivity of plant communities. Copyright © 2015 Elsevier B.V. All rights reserved.
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E. M. Veenendaal
2015-05-01
Full Text Available Through interpretations of remote-sensing data and/or theoretical propositions, the idea that forest and savanna represent "alternative stable states" is gaining increasing acceptance. Filling an observational gap, we present detailed stratified floristic and structural analyses for forest and savanna stands located mostly within zones of transition (where both vegetation types occur in close proximity in Africa, South America and Australia. Woody plant leaf area index variation was related to tree canopy cover in a similar way for both savanna and forest with substantial overlap between the two vegetation types. As total woody plant canopy cover increased, so did the relative contribution of middle and lower strata of woody vegetation. Herbaceous layer cover declined as woody cover increased. This pattern of understorey grasses and herbs progressively replaced by shrubs as the canopy closes over was found for both savanna and forests and on all continents. Thus, once subordinate woody canopy layers are taken into account, a less marked transition in woody plant cover across the savanna–forest-species discontinuum is observed compared to that inferred when trees of a basal diameter > 0.1 m are considered in isolation. This is especially the case for shrub-dominated savannas and in taller savannas approaching canopy closure. An increased contribution of forest species to the total subordinate cover is also observed as savanna stand canopy closure occurs. Despite similarities in canopy-cover characteristics, woody vegetation in Africa and Australia attained greater heights and stored a greater amount of above-ground biomass than in South America. Up to three times as much above-ground biomass is stored in forests compared to savannas under equivalent climatic conditions. Savanna–forest transition zones were also found to typically occur at higher precipitation regimes for South America than for Africa. Nevertheless, consistent across all three
Carbon stock in forest aboveground biomass –comparison based on Landsat data
Czech Academy of Sciences Publication Activity Database
Pechanec, V.; Stržínek, F.; Purkyt, Jan; Štěrbová, Lenka; Cudlín, Pavel
2017-01-01
Roč. 63, 2-3 (2017), s. 126-132 ISSN 2454-0358 R&D Projects: GA MŠk(CZ) LO1415 Grant - others:EHP,MF ČR(CZ) EHP-CZ02-OV-1-014-2014 Program:CZ02 Institutional support: RVO:67179843 Keywords : aboveground biomass * carbon stock * remote sensing data * vegetation indices * Czech Republic Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7)
E. H. Helmer; M. A. Lefsky; D. A. Roberts
2009-01-01
We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975â2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age...
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Xiao-Tao Lü
2009-06-01
Full Text Available Lianas are important components of tropical forests and have significant impacts on the diversity, structure and dynamics of tropical forests. The present study documented the liana flora in a Chinese tropical region. Species richness, abundance, size-class distribution and spatial patterns of lianas were investigated in three 1-ha plots in tropical seasonal rain forests in Xishuangbanna, SW China. All lianas with = 2 cm diameter at breast height (dbh were measured, tagged and identified. A total of 458 liana stems belonging to 95 species (ranging from 38 to 50 species/ha, 59 genera and 32 families were recorded in the three plots. The most well-represented families were Loganiaceae, Annonceae, Papilionaceae, Apocynaceae and Rhamnaceae. Papilionaceae (14 species recorded was the most important family in the study forests. The population density, basal area and importance value index (IVI varied greatly across the three plots. Strychnos cathayensis, Byttneria grandifolia and Bousigonia mekongensis were the dominant species in terms of IVI across the three plots. The mean aboveground biomass of lianas (3 396 kg/ha accounted for 1.4% of the total community aboveground biomass. The abundance, diversity and biomass of lianas in Xishuangbanna tropical seasonal rain forests are lower than those in tropical moist and wet forests, but higher than those in tropical dry forests. This study provides new data on lianas from a geographical region that has been little-studied. Our findings emphasize that other factors beyond the amount and seasonality of precipitation should be included when considering the liana abundance patterns across scales. Rev. Biol. Trop. 57 (1-2: 211-222. Epub 2009 June 30.Las lianas son componentes importantes de los bosques tropicales y tienen importantes impactos en la diversidad, la estructura y la dinámica de los bosques tropicales. El presente estudio documenta la flora de lianas en una región tropical estacional china. La
The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates
Houghton, R. A.; Lawrence, J. L.; Hackler, J. L.; Brown, S.
2001-01-01
The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. We compared several estimates of forest biomass for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. We asked three questions. First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? Amazonian forests (including dead and below-ground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modeling of forest recovery following observed stand-replacing disturbances (the approach used in this research), and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.
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Songqiu Deng
2014-08-01
Full Text Available Enhanced methods are required for mapping the forest aboveground biomass (AGB over a large area in Chinese forests. This study attempted to develop an improved approach to retrieving biomass by combining PALSAR (Phased Array type L-band Synthetic Aperture Radar and WorldView-2 data. A total of 33 variables with potential correlations with forest biomass were extracted from the above data. However, these parameters had poor fits to the observed biomass. Accordingly, the synergies of several variables were explored to identify improved relationships with the AGB. Using principal component analysis and multivariate linear regression (MLR, the accuracies of the biomass estimates obtained using PALSAR and WorldView-2 data were improved to approximately 65% to 71%. In addition, using the additional dataset developed from the fusion of FBD (fine beam dual-polarization and WorldView-2 data improved the performance to 79% with an RMSE (root mean square error of 35.13 Mg/ha when using the MLR method. Moreover, a further improvement (R2 = 0.89, relative RMSE = 17.08% was obtained by combining all the variables mentioned above. For the purpose of comparison with MLR, a neural network approach was also used to estimate the biomass. However, this approach did not produce significant improvements in the AGB estimates. Consequently, the final MLR model was recommended to map the AGB of the study area. Finally, analyses of estimated error in distinguishing forest types and vertical structures suggested that the RMSE decreases gradually from broad-leaved to coniferous to mixed forest. In terms of different vertical structures (VS, VS3 has a high error because the forest lacks undergrowth trees, while VS4 forest, which has approximately the same amounts of stems in each of the three DBH (diameter at breast height classes (DBH > 20, 10 ≤ DBH ≤ 20, and DBH < 10 cm, has the lowest RMSE. This study demonstrates that the combination of PALSAR and WorldView-2 data
Ross Nelson; Hank Margolis; Paul Montesano; Guoqing Sun; Bruce Cook; Larry Corp; Hans-Erik Andersen; Ben deJong; Fernando Paz Pellat; Thaddeus Fickel; Jobriath Kauffman; Stephen Prisley
2017-01-01
Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar...
Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR
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J. Jubanski
2013-06-01
Full Text Available Quantification of tropical forest above-ground biomass (AGB over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+ projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia through correlating airborne light detection and ranging (LiDAR to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52. Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.
Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.
2017-08-01
The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest
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Fang Zhang
2012-01-01
Full Text Available This study focuses on the influence of the 2008 ice storm in China and subsequent forest rehabilitation dynamics up until 2011. All seven plots studied exhibited significant damage, with the total number of damaged trees varying between 63 and 92%. In addition, most trees suffered stem bending in 2008 and the extent of damage varied with tree diameter at breast high (DBH. Relationships between loss of biomass as dead trees and stand characteristics were analyzed by multiple stepwise regression. The results showed that the decrease in biomass (Y could be related to altitude (X1, slope (X2, and aboveground biomass (AGB in 2008 (X5 according to the following formula: Y=−0.02456X1+0.2815X5−1.480X2+51.23. After 2 to 3 years, tree numbers had declined in all seven plots. The mean increase in AGB (4.9 t ha−1 for six of the plots was less than the biomass loss as dead trees (9.4 t ha−1 over the 3 year periods. This corresponds to a release of CO2 to the atmosphere for each plot. Therefore, the forests of Lechang in the Nanling Montains have probably acted as a carbon source to the atmosphere for a short period after the 2008 ice storm.
Amazonian landscapes and the bias in field studies of forest structure and biomass.
Marvin, David C; Asner, Gregory P; Knapp, David E; Anderson, Christopher B; Martin, Roberta E; Sinca, Felipe; Tupayachi, Raul
2014-12-02
Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9-98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy.
Assessing biomass accumulation in second growth forests of Puerto Rico using airborne lidar
Martinuzzi, S.; Cook, B.; Corp, L. A.; Morton, D. C.; Helmer, E.; Keller, M.
2017-12-01
Degraded and second growth tropical forests provide important ecosystem services, such as carbon sequestration and soil stabilization. Lidar data measure the three-dimensional structure of forest canopies and are commonly used to quantify aboveground biomass in temperate forest landscapes. However, the ability of lidar data to quantify second growth forest biomass in complex, tropical landscapes is less understood. Our goal was to evaluate the use of airborne lidar data to quantify aboveground biomass in a complex tropical landscape, the Caribbean island of Puerto Rico. Puerto Rico provides an ideal place for studying biomass accumulation because of the abundance of second growth forests in different stages of recovery, and the high ecological heterogeneity. Puerto Rico was almost entirely deforested for agriculture until the 1930s. Thereafter, agricultural abandonment resulted in a mosaic of second growth forests that have recovered naturally under different types of climate, land use, topography, and soil fertility. We integrated forest plot data from the US Forest Service, Forest Inventory and Analysis (FIA) Program with recent lidar data from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) airborne imager to quantify forest biomass across the island's landscape. The G-LiHT data consisted on targeted acquisitions over the FIA plots and other forested areas representing the environmental heterogeneity of the island. To fully assess the potential of the lidar data, we compared the ability of lidar-derived canopy metrics to quantify biomass alone, and in combination with intensity and topographic metrics. The results presented here are a key step for improving our understanding of the patterns and drivers of biomass accumulation in tropical forests.
Ali, Arshad; Mattsson, Eskil
2017-11-15
The biodiversity - aboveground biomass relationship has been intensively studied in recent decades. However, no consensus has been arrived to consider the interplay of species diversity, and intraspecific and interspecific tree size variation in driving aboveground biomass, after accounting for the effects of plot size heterogeneity, soil fertility and stand quality in natural forest including agroforests. We tested the full, partial and no mediations effects of species diversity, and intraspecific and interspecific tree size variation on aboveground biomass by employing structural equation models (SEMs) using data from 45 homegarden agroforestry systems in Sri Lanka. The full mediation effect of either species diversity or intraspecific and interspecific tree size variation was rejected, while the partial and no mediation effects were accepted. In the no mediation SEM, homegarden size had the strongest negative direct effect (β=-0.49) on aboveground biomass (R 2 =0.65), followed by strong positive direct effect of intraspecific tree size variation (β=0.32), species diversity (β=0.29) and interspecific tree size variation (β=0.28). Soil fertility had a negative direct effect on interspecific tree size variation (β=-0.31). Stand quality had a significant positive total effect on aboveground biomass (β=0.28), but homegarden size had a significant negative total effect (β=-0.62), while soil fertility had a non-significant total effect on aboveground biomass. Similar to the no mediation SEM, the partial mediation SEMs had explained almost similar variation in aboveground biomass because species diversity, and intraspecific and interspecific tree size variation had non-significant indirect effects on aboveground biomass via each other. Our results strongly suggest that a multilayered tree canopy structure, due to high intraspecific and interspecific tree size variation, increases light capture and efficient utilization of resources among component species, and
Xiaoping Zhou; Miles A. Hemstrom
2010-01-01
Timber availability, aboveground tree biomass, and changes in aboveground carbon pools are important consequences of landscape management. There are several models available for calculating tree volume and aboveground tree biomass pools. This paper documents species-specific regional equations for tree volume and aboveground live tree biomass estimation that might be...
The role of gap phase processes in the biomass dynamics of tropical forests
Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M.N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme
2007-01-01
The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four ‘old-growth’ tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr−1) and decreased at HKK (−0.56% yr−1) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget. PMID:17785266
Viers, J. H.
2013-12-01
Integrating citizen scientists into ecological informatics research can be difficult due to limited opportunities for meaningful engagement given vast data streams. This is particularly true for analysis of remotely sensed data, which are increasingly being used to quantify ecosystem services over space and time, and to understand how land uses deliver differing values to humans and thus inform choices about future human actions. Carbon storage and sequestration are such ecosystem services, and recent environmental policy advances in California (i.e., AB 32) have resulted in a nascent carbon market that is helping fuel the restoration of riparian forests in agricultural landscapes. Methods to inventory and monitor aboveground carbon for market accounting are increasingly relying on hyperspatial remotely sensed data, particularly the use of light detection and ranging (LiDAR) technologies, to estimate biomass. Because airborne discrete return LiDAR can inexpensively capture vegetation structural differences at high spatial resolution ( 1000 ha), its use is rapidly increasing, resulting in vast stores of point cloud and derived surface raster data. While established algorithms can quantify forest canopy structure efficiently, the highly complex nature of native riparian forests can result in highly uncertain estimates of biomass due to differences in composition (e.g., species richness, age class) and structure (e.g., stem density). This study presents the comparative results of standing carbon estimates refined with field data collected by citizen scientists at three different sites, each capturing a range of agricultural, remnant forest, and restored forest cover types. These citizen science data resolve uncertainty in composition and structure, and improve allometric scaling models of biomass and thus estimates of aboveground carbon. Results indicate that agricultural land and horticulturally restored riparian forests store similar amounts of aboveground carbon
Liang, Bei; Di, Li; Zhao, Chuan-Yan; Peng, Shou-Zhang; Peng, Huan-Hua; Wang, Chao
2014-02-01
This study estimated the spatial distribution of the aboveground biomass of shrubs in the Tianlaochi catchment of Qilian Mountains based on the field survey and remote sensing data. A relationship model of the aboveground biomass and its feasibly measured factors (i. e. , canopy perimeter and plant height) was built. The land use was classified by object-oriented technique with the high resolution image (GeoEye-1) of the study area, and the distribution of shrub coverage was extracted. Then the total aboveground biomass of shrubs in the study area was estimated by the relationship model with the distribution of shrub coverage. The results showed that the aboveground biomass of shrubs in the study area was 1.8 x 10(3) t and the aboveground biomass per unit area was 1598.45 kg x m(-2). The distribution of shrubs mainly was at altitudes of 3000-3700 m, and the aboveground biomass of shrubs on the sunny slope (1.15 x 10(3) t) was higher than that on the shady slope (0.65 x 10(3) t).
Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume
Thomas J. Brandeis; Matthew Delaney; Bernard R. Parresol; Larry Royer
2006-01-01
Carbon accounting, forest health monitoring and sustainable management of the subtropical dry forests of Puerto Rico and other Caribbean Islands require an accurate assessment of forest aboveground biomass (AGB) and stem volume. One means of improving assessment accuracy is the development of predictive equations derived from locally collected data. Forest inventory...
Waveform LiDAR across forest biomass gradients
Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.
2011-12-01
Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.
Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon
Nelson, Ross
2008-01-01
ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.
Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests.
Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom
2015-07-01
Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved
Luo, Yunjian; Zhang, Xiaoquan; Wang, Xiaoke; Ren, Yin
2014-01-01
Biomass conversion factors (BCFs, defined as the ratios of tree components (i.e. stem, branch, foliage and root), as well as aboveground and whole biomass of trees to growing stock volume, Mg m-3) are considered as important parameters in large-scale forest biomass carbon estimation. To date, knowledge of possible sources of the variation in BCFs is still limited at large scales. Using our compiled forest biomass dataset of China, we presented forest type-specific values of BCFs, and examined the variation in BCFs in relation to forest type, stand development and environmental factors (climate and soil fertility). BCFs exhibited remarkable variation across forest types, and also were significantly related to stand development (especially growing stock volume). BCFs (except Stem BCF) had significant relationships with mean annual temperature (MAT) and mean annual precipitation (MAP) (Pforest carbon estimates, we should apply values of BCFs for a specified forest type, and also consider climatic and edaphic effects, especially climatic effect, in developing predictive models of BCFs (except Stem BCF).
Singh, J.; Kumar, S.; Kushwaha, S. P. S.
2015-04-01
Forests cover 30% of the world's land surface, and are home to around 90% of the world's flora and fauna. They serve as one of the world's largest carbon sinks, absorbing 2.4 million tons of CO2 each year and storing billions more in form of biomass. Around 6 million hectares of forest is lost or changed each year and as much as a fifth of global emissions are estimated to come from deforestation. Hence accurate estimation of forest biophysical variables is necessary as it is a key parameter in determination of forest inventories, vegetation modeling and global carbon cycle. SAR Remote sensing technique is capable of providing accurate and reliable information about forest parameters. The present work aims to explore the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolinSAR) technique for developing a relationship between complex coherence and forest aboveground biomass (t/ha). In order to attain our objective Radarsat-2 satellite interferometric pair of 4th March 2013(master image) and 28th March 2013(slave image) were acquired for Barkot Reserve Forest, Dehradun, India. Field inventory was done for 30 plots (31.62m x 31.62m) and tree height and stem diameter were procured for each plot which were later utilized in calculation of aboveground biomass(AGB).Work emphasizes on the application of PolinSAR coherence instead of using SAR backscatter which saturates after a certain value of biomass content. Complex coherence values for different polarization channels were computed with the help of polarimetric interferometric coherence matrix. Retrieved complex coherences were investigated individually and then regression analysis was carried with the field estimated aboveground biomass. R2 value of HV+VH complex coherence component was found to be relatively higher than other polarization channel components
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Santa Pandit
2018-04-01
Full Text Available Accurate assessment of above-ground biomass (AGB is important for the sustainable management of forests, especially buffer zone (areas within the protected area, where restrictions are placed upon resource use and special measure are undertaken to intensify the conservation value of protected area areas with a high dependence on forest products. This study presents a new AGB estimation method and demonstrates the potential of medium-resolution Sentinel-2 Multi-Spectral Instrument (MSI data application as an alternative to hyperspectral data in inaccessible regions. Sentinel-2 performance was evaluated for a buffer zone community forest in Parsa National Park, Nepal, using field-based AGB as a dependent variable, as well as spectral band values and spectral-derived vegetation indices as independent variables in the Random Forest (RF algorithm. The 10-fold cross-validation was used to evaluate model effectiveness. The effect of the input variable number on AGB prediction was also investigated. The model using all extracted spectral information plus all derived spectral vegetation indices provided better AGB estimates (R2 = 0.81 and RMSE = 25.57 t ha−1. Incorporating the optimal subset of key variables did not improve model variance but reduced the error slightly. This result is explained by the technically-advanced nature of Sentinel-2, which includes fine spatial resolution (10, 20 m and strategically-positioned bands (red-edge, conducted in flat topography with an advanced machine learning algorithm. However, assessing its transferability to other forest types with varying altitude would enable future performance and interpretability assessments of Sentinel-2.
Multi-decade biomass dynamics in an old-growth hemlock-northern hardwood forest, Michigan, USA
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Kerry D. Woods
2014-09-01
Full Text Available Trends in living aboveground biomass and inputs to the pool of coarse woody debris (CWD in an undisturbed, old-growth hemlock-northern hardwood forest in northern MI were estimated from multi-decade observations of permanent plots. Growth and demographic data from seven plot censuses over 47 years (1962–2009, combined with one-time measurement of CWD pools, help assess biomass/carbon status of this landscape. Are trends consistent with traditional notions of late-successional forests as equilibrial ecosystems? Specifically, do biomass pools and CWD inputs show consistent long-term trends and relationships, and can living and dead biomass pools and trends be related to forest composition and history? Aboveground living biomass densities, estimated using standard allometric relationships, range from 360–450 Mg/ha among sampled stands and types; these values are among the highest recorded for northeastern North American forests. Biomass densities showed significant decade-scale variation, but no consistent trends over the full study period (one stand, originating following an 1830 fire, showed an aggrading trend during the first 25 years of the study. Even though total above-ground biomass pools are neither increasing nor decreasing, they have been increasingly dominated, over the full study period, by very large (>70 cm dbh stems and by the most shade-tolerant species (Acer saccharum and Tsuga canadensis.CWD pools measured in 2007 averaged 151 m3/ha, with highest values in Acer-dominated stands. Snag densities averaged 27/ha, but varied nearly ten-fold with canopy composition (highest in Tsuga-dominated stands, lowest in Acer-dominated; snags constituted 10–50% of CWD biomass. Annualized CWD inputs from tree mortality over the full study period averaged 1.9–3.2 Mg/ha/yr, depending on stand and species composition. CWD input rates tended to increase over the course of the study. Input rates may be expected to increase over longer
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Minerva Singh
2015-04-01
Full Text Available This study develops a modelling framework for utilizing very high-resolution (VHR aerial imagery for monitoring stocks of above-ground biomass (AGB in a tropical forest in Southeast Asia. Three different texture-based methods (grey level co-occurrence metric (GLCM, Gabor wavelets and Fourier-based textural ordination (FOTO were used in conjunction with two different machine learning (ML-based regression techniques (support vector regression (SVR and random forest (RF regression. These methods were implemented on both 50-cm resolution Digital Globe data extracted from Google Earth™ (GE and 8-cm commercially obtained VHR imagery. This study further examines the role of forest biophysical parameters, such as ground-measured canopy cover and vertical canopy height, in explaining AGB distribution. Three models were developed using: (i horizontal canopy variables (i.e., canopy cover and texture variables plus vertical canopy height; (ii horizontal variables only; and (iii texture variables only. AGB was variable across the site, ranging from 51.02 Mg/ha to 356.34 Mg/ha. GE-based AGB estimates were comparable to those derived from commercial aerial imagery. The findings demonstrate that novel use of this array of texture-based techniques with GE imagery can help promote the wider use of freely available imagery for low-cost, fine-resolution monitoring of forests parameters at the landscape scale.
Foliage biomass qualitative indices of selected forest forming tree species in Ukrainian Steppe
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Sytnyk Svitlana
2017-06-01
Full Text Available Our study objective was research on the assimilation component of aboveground biomass of trees and its correlation with mensurational indices of trees (age, diameter and height in stands of the main forest forming species in the Ukrainian Northern Steppe zone - Pinus sylvestris L. (Scots pine and Robinia pseudoacacia L. (Black locust. The research was carried out in forest stands subordinated to the State Agency of Forest Resources of Ukraine. We used experimental data collected on sample plots established during years 2014-2016. The main research results prove that the foliage share in the tree greenery biomass structure had a wide range of values. For both investigated species, a positive correlation was found between the dry matter content in the tree foliage and the tree age, height and diameter. The foliage share in tree greenery biomass decreased with increasing mensurational index values. Correlation analysis revealed linear relationships between the mensurational indices and the discussed aboveground live biomass parameters. The closest correlation was observed between the stand age, mean stand diameter, mean stand height and dry matter content in the foliage.
Bioenergy production potential for aboveground biomass from a subtropical constructed wetland
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Wang, Yi-Chung [Department of Forestry and Nature Conservation, Chinese Culture University, Taipei 11114 (China); Ko, Chun-Han [School of Forestry and Resource Conservation, National Taiwan University, Taipei 10617 (China); Bioenergy Research Center, National Taiwan University, Taipei 10617 (China); Chang, Fang-Chih [The Instrument Center, National Cheng Kung University, No.1, University Road, Tainan City 70101 (China); Chen, Pen-Yuan [Department of Landscape Architecture, National Chiayi University, Chiayi City 60004 (China); Liu, Tzu-Fen [School of Forestry and Resource Conservation, National Taiwan University, Taipei 10617 (China); Sheu, Yiong-Shing [Department of Water Quality Protection, Environmental Protection Administration, Executive Yuan, Taipei 10042 (China); Shih, Tzenge-Lien [Department of Chemistry, Tamkang University, Tamsui, Taipei 25137 (China); Teng, Chia-Ji [Environmental Protection Bureau, Taipei County Government, Taipei 22001 (China)
2011-01-15
Wetland biomass has potentials for bioenergy production and carbon sequestration. Planted with multiple species macrophytes to promote biodiversity, the 3.29 ha constructed wetland has been treated 4000 cubic meter per day (CMD) domestic wastewater and urban runoff. This study investigated the seasonal variations of aboveground biomass of the constructed wetland, from March 2007 to March 2008. The overall aboveground biomass was 16,737 kg and total carbon content 6185 kg at the peak of aboveground accumulation for the system emergent macrophyte at September 2007. Typhoon Korsa flood this constructed wetland at October 2007, however, significant recovery for emergent macrophyte was observed without human intervention. Endemic Ludwigia sp. recovered much faster, compared to previously dominated typha. Self-recovery ability of the macrophyte community after typhoon validated the feasibility of biomass harvesting. Incinerating of 80% biomass harvested of experimental area in a nearby incineration plant could produce 11,846 kWh for one month. (author)
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P. Köhler
2010-08-01
Full Text Available The canopy height h of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB (and thus carbon content of vegetation and leaf area index (LAI and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model FORMIND2.0 was applied to simulate (a undisturbed forest growth and (b a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height h (AGB = a · hb with an r2 ~ 60% if data are analysed in a spatial resolution of 20 m × 20 m (0.04 ha, also called plot size. The correlation coefficient of the regression is becoming significant better in the disturbed forest sites (r2 = 91% if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2 ~ 60% between AGB and the area fraction of gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a
Köhler, P.; Huth, A.
2010-08-01
The canopy height h of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI) and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height h (AGB = a · hb) with an r2 ~ 60% if data are analysed in a spatial resolution of 20 m × 20 m (0.04 ha, also called plot size). The correlation coefficient of the regression is becoming significant better in the disturbed forest sites (r2 = 91%) if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2 ~ 60%) between AGB and the area fraction of gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot (PSP) data from the same region and with the
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Norris, M. D.; Blair, J. M.; Johnson, L. C. [Kansas State Univ., Manhattan, KS (United States); McKane, R. B. [Environmental Protection Agency, Western Ecology Division, Corvallis, OR (United States)
2001-11-01
The objective of this study was to assess changes in plant productivity and above-ground plant biomass associated with red cedar forest expansion into areas formerly dominated by tallgrass prairie. Regionally appropriate allometric biomass regression equations were developed for the nondestructive estimation of red cedar biomass in eastern Kansas, followed by quantification of the carbon and nitrogen content of selected biomass components. The equations were applied, along with measurements of leaf litter production, to selected local stands of mature closed-canopy red cedars to estimate above-ground biomass, standing stocks of carbon and nitrogen and annual above-ground net primary productivity. Above-ground plant biomass for these red cedar-dominated sites ranged from 114,100 kg/ha for the youngest stand to 210,700 kg/ha for the oldest. Annual above-ground net primary productivity (ANPP) ranged from 7,250 to 10,440 kg/ha/yr for the oldest and younger red cedar stands respectively. The ANPP in comparable tallgrass prairie sites in this region averages 3,690 k/ha/yr, indicating a large increase in carbon uptake and above-ground storage as a result of the change from prairie to red cedar forests. Comparing these results with similar published data from other sites led to the conclusion that the widespread change from tallgrass to red cedars across the woodland-prairie ecotone has important consequences for regional carbon storage.37 refs., 3 tabs., 3 figs.
Heather D. Vance-Chalcraft; Michael R. Willig; Stephen B. Cox; Ariel E. Lugo; Frederick N. Scatena
2010-01-01
Anthropogenic activities have accelerated the rate of global loss of biodiversity, making it more important than ever to understand the structure of biodiversity hotspots. One current focus is the relationship between species richness and aboveground biomass (AGB) in a variety of ecosystems. Nonetheless, species diversity, evenness, rarity, or dominance represent other...
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Dengsheng Lu
2012-01-01
Full Text Available Landsat Thematic mapper (TM image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR can overcome TM’s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints. The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation. With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors. A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data.
Above-ground biomass equations for Pinus radiata D. Don in Asturias
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E. Canga
2013-12-01
Full Text Available Aim of the study: The aim of this study was to develop a model for above-ground biomass estimation for Pinus radiata D. Don in Asturias.Area of study: Asturias (NE of Spain.Material and methods: Different models were fitted for the different above-ground components and weighted regression was used to correct heteroscedasticity. Finally, all the models were refitted simultaneously by use of Nonlinear Seemingly Unrelated Regressions (NSUR to ensure the additivity of biomass equations.Research highlights: A system of four biomass equations (wood, bark, crown and total biomass was develop, such that the sum of the estimations of the three biomass components is equal to the estimate of total biomass. Total and stem biomass equations explained more than 92% of observed variability, while crown and bark biomass equations explained 77% and 89% respectively.Keywords: radiata pine; plantations; biomass.
Spaceborne Applications of P Band Imaging Radars for Measuring Forest Biomass
Rignot, Eric J.; Zimmermann, Reiner; vanZyl, Jakob J.
1995-01-01
In three sites of boreal and temperate forests, P band HH, HV, and VV polarization data combined estimate total aboveground dry woody biomass within 12 to 27% of the values derived from allometric equations, depending on forest complexity. Biomass estimates derived from HV-polarization data only are 2 to 14% less accurate. When the radar operates at circular polarization, the errors exceed 100% over flooded forests, wet or damaged trees and sparse open tall forests because double-bounce reflections of the radar signals yield radar signatures similar to that of tall and massive forests. Circular polarizations, which minimize the effect of Faraday rotation in spaceborne applications, are therefore of limited use for measuring forest biomass. In the tropical rain forest of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 50 kg/sq m in old, undisturbed floodplain stands, the P band horizontal and vertical polarization data combined separate biomass classes in good agreement with forest inventory estimates. The worldwide need for large scale, updated, biomass estimates, achieved with a uniformly applied method, justifies a more in-depth exploration of multi-polarization long wavelength imaging radar applications for tropical forests inventories.
Evangelista, P.; Kumar, S.; Stohlgren, T.J.; Crall, A.W.; Newman, G.J.
2007-01-01
Predictive models of aboveground biomass of nonnative Tamarix ramosissima of various sizes were developed using destructive sampling techniques on 50 individuals and four 100-m2 plots. Each sample was measured for average height (m) of stems and canopy area (m2) prior to cutting, drying, and weighing. Five competing regression models (P < 0.05) were developed to estimate aboveground biomass of T. ramosissima using average height and/or canopy area measurements and were evaluated using Akaike's Information Criterion corrected for small sample size (AICc). Our best model (AICc = -148.69, ??AICc = 0) successfully predicted T. ramosissima aboveground biomass (R2 = 0.97) and used average height and canopy area as predictors. Our 2nd-best model, using the same predictors, was also successful in predicting aboveground biomass (R2 = 0.97, AICc = -131.71, ??AICc = 16.98). A 3rd model demonstrated high correlation between only aboveground biomass and canopy area (R2 = 0.95), while 2 additional models found high correlations between aboveground biomass and average height measurements only (R2 = 0.90 and 0.70, respectively). These models illustrate how simple field measurements, such as height and canopy area, can be used in allometric relationships to accurately predict aboveground biomass of T. ramosissima. Although a correction factor may be necessary for predictions at larger scales, the models presented will prove useful for many research and management initiatives.
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Asep S. Suntana
2012-01-01
Full Text Available Biomass conversion technologies that produce energy and reduce carbon emissions have become more feasible to develop. This paper analyzes the potential of converting biomass into biomethanol at forest management units experiencing three forest management practices (community-based forest management (CBFM, plantation forest (PF, and natural production forest (NPF. Dry aboveground biomass collected varied considerably: 0.26–2.16 Mg/ha/year (CBFM, 8.08–8.35 Mg/ha/year (NPF, and 36.48–63.55 Mg/ha/year (PF. If 5% of the biomass was shifted to produce biomethanol for electricity production, the NPF and PF could provide continuous power to 138 and 2,762 households, respectively. Dedicating 5% of the biomass was not a viable option from one CBFM unit. However, if all biomasses were converted, the CBFM could provide electricity to 19–27 households. If 100% biomass from two selected PF was dedicated to biomethanol production: (1 52,200–72,600 households could be provided electricity for one year; (2 142–285% of the electricity demand in Jambi province could be satisfied; (3 all gasoline consumed in Jambi, in 2009, would be replaced. The net carbon emissions avoided could vary from 323 to 8,503 Mg when biomethanol was substituted for the natural gas methanol in fuel cells and from 294 to 7,730 Mg when it was used as a gasoline substitute.
Yan, S.; Bruckman, V. J.; Glatzel, G.; Hochbichler, E.
2012-04-01
As one of the renewable energy forms, bio-energy could help to relieve the pressure which is caused by growing global energy demand. In Austria, large area of forests, traditional utilization of biomass and people's desire to live in a sound environment have supported the positive development of bio-energy. Soil nutrient status is in principle linked with the productivity of the aboveground biomass. This study focuses on K, Ca and Mg pools in soils and aboveground biomass in order to learn more on the temporal dynamics of plant nutrients as indicators for biomass potentials in Quercus dominated forests in northeastern Austria. Three soil types (according to WRB: eutric cambisol, calcic chernozem and haplic luvisol) were considered representative for the area and sampled. We selected nine Quercus petraea dominated permanent plots for this study. Exchangeable cations K, Ca and Mg in the soils were quantified in our study plots. Macronutrients pools of K, Ca and Mg in aboveground biomass were calculated according to inventory data and literature review. The exchangeable cations pool in the top 50 cm of the soil were 882 - 1,652 kg ha-1 for K, 2,661 to 16,510 kg ha-1 for Ca and 320 - 1,850 kg ha-1 for Mg. The nutrient pool in aboveground biomass ranged from 29 to 181 kg ha-1 for K, from 56 to 426 kg ha-1 for Ca and from 4 to 26 kg ha-1 for Mg. The underground exchangeable pools of K, Ca and Mg are generally 10, 22 and 58 times higher than aboveground biomass nutrient pools. Our results showed that the nutrient pools in the mineral soil are sufficient to support the tree growth. The levels of soil nutrients in particular K, Ca and Mg in our study areas are reasonably high and do not indicate the necessity for additional fertilization under current silvicultural practices and biomass extraction rate. The forest in our study areas is in favorable condition to supply biomass as raw material for energy utilization.
Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion
Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri
2010-01-01
Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P forests (R2 = 0.93, P forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.
Tropical-forest biomass estimation at X-Band from the spaceborne TanDEM-X interferometer
R. Treuhaft; F. Goncalves; J.R. dos Santos; M. Keller; M. Palace; S.N. Madsen; F. Sullivan; P.M.L.A. Graca
2014-01-01
This letter reports the sensitivity of X-band interferometric synthetic aperture radar (InSAR) data from the first dual-spacecraft radar interferometer, TanDEM-X, to variations in tropical-forest aboveground biomass (AGB). It also reports the first tropical-forest AGB estimates fromTanDEM-X data. Tropical forests account for...
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Pablito M. López-Serrano
2016-04-01
Full Text Available Solar radiation is affected by absorption and emission phenomena during its downward trajectory from the Sun to the Earth’s surface and during the upward trajectory detected by satellite sensors. This leads to distortion of the ground radiometric properties (reflectance recorded by satellite images, used in this study to estimate aboveground forest biomass (AGB. Atmospherically-corrected remote sensing data can be used to estimate AGB on a global scale and with moderate effort. The objective of this study was to evaluate four atmospheric correction algorithms (for surface reflectance, ATCOR2 (Atmospheric Correction for Flat Terrain, COST (Cosine of the Sun Zenith Angle, FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes and 6S (Second Simulation of Satellite Signal in the Solar, and one radiometric correction algorithm (for reflectance at the sensor ToA (Apparent Reflectance at the Top of Atmosphere to estimate AGB in temperate forest in the northeast of the state of Durango, Mexico. The AGB was estimated from Landsat 5 TM imagery and ancillary information from a digital elevation model (DEM using the non-parametric multivariate adaptive regression splines (MARS technique. Field reference data for the model training were collected by systematic sampling of 99 permanent forest growth and soil research sites (SPIFyS established during the winter of 2011. The following predictor variables were identified in the MARS model: Band 7, Band 5, slope (β, Wetness Index (WI, NDVI and MSAVI2. After cross-validation, 6S was found to be the optimal model for estimating AGB (R2 = 0.71 and RMSE = 33.5 Mg·ha−1; 37.61% of the average stand biomass. We conclude that atmospheric and radiometric correction of satellite images can be used along with non-parametric techniques to estimate AGB with acceptable accuracy.
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Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.; Shugart, Herman H.
2017-01-01
Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model -based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes, manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the
Ni, W.; Zhang, Z.; Sun, G.
2017-12-01
Several large-scale maps of forest AGB have been released [1] [2] [3]. However, these existing global or regional datasets were only approximations based on combining land cover type and representative values instead of measurements of actual forest aboveground biomass or forest heights [4]. Rodríguez-Veiga et al[5] reported obvious discrepancies of existing forest biomass stock maps with in-situ observations in Mexico. One of the biggest challenges to the credibility of these maps comes from the scale gaps between the size of field sampling plots used to develop(or validate) estimation models and the pixel size of these maps and the availability of field sampling plots with sufficient size for the verification of these products [6]. It is time-consuming and labor-intensive to collect sufficient number of field sampling data over the plot size of the same as resolutions of regional maps. The smaller field sampling plots cannot fully represent the spatial heterogeneity of forest stands as shown in Figure 1. Forest AGB is directly determined by forest heights, diameter at breast height (DBH) of each tree, forest density and tree species. What measured in the field sampling are the geometrical characteristics of forest stands including the DBH, tree heights and forest densities. The LiDAR data is considered as the best dataset for the estimation of forest AGB. The main reason is that LiDAR can directly capture geometrical features of forest stands by its range detection capabilities.The remotely sensed dataset, which is capable of direct measurements of forest spatial structures, may serve as a ladder to bridge the scale gaps between the pixel size of regional maps of forest AGB and field sampling plots. Several researches report that TanDEM-X data can be used to characterize the forest spatial structures [7, 8]. In this study, the forest AGB map of northeast China were produced using ALOS/PALSAR data taking TanDEM-X data as a bridges. The TanDEM-X InSAR data used in
Schuster, W S F; Griffin, K L; Roth, H; Turnbull, M H; Whitehead, D; Tissue, D T
2008-04-01
We sought to quantify changes in tree species composition, forest structure and aboveground forest biomass (AGB) over 76 years (1930-2006) in the deciduous Black Rock Forest in southeastern New York, USA. We used data from periodic forest inventories, published floras and a set of eight long-term plots, along with species-specific allometric equations to estimate AGB and carbon content. Between the early 1930s and 2000, three species were extirpated from the forest (American elm (Ulmus americana L.), paper birch (Betula papyrifera Marsh.) and black spruce (Picea mariana (nigra) (Mill.) BSP)) and seven species invaded the forest (non-natives tree-of-heaven (Ailanthus altissima (Mill.) Swingle) and white poplar (Populus alba L.) and native, generally southerly distributed, southern catalpa (Catalpa bignonioides Walt.), cockspur hawthorn (Crataegus crus-galli L.), red mulberry (Morus rubra L.), eastern cottonwood (Populus deltoides Bartr.) and slippery elm (Ulmus rubra Muhl.)). Forest canopy was dominated by red oak and chestnut oak, but the understory tree community changed substantially from mixed oak-maple to red maple-black birch. Density decreased from an average of 1500 to 735 trees ha(-1), whereas basal area doubled from less than 15 m(2) ha(-1) to almost 30 m(2) ha(-1) by 2000. Forest-wide mean AGB from inventory data increased from about 71 Mg ha(-1) in 1930 to about 145 Mg ha(-1) in 1985, and mean AGB on the long-term plots increased from 75 Mg ha(-1) in 1936 to 218 Mg ha(-1) in 1998. Over 76 years, red oak (Quercus rubra L.) canopy trees stored carbon at about twice the rate of similar-sized canopy trees of other species. However, there has been a significant loss of live tree biomass as a result of canopy tree mortality since 1999. Important constraints on long-term biomass increment have included insect outbreaks and droughts.
Changes in vegetation structure and aboveground biomass in ...
African Journals Online (AJOL)
Changes in vegetation structure and aboveground biomass in response to traditional rangeland management practices in Borana, southern Ethiopia. ... managed by prescribed fire for five years and grazed only post-fire during dry seasons.
Topographically mediated controls on aboveground biomass across a mediterranean-type landscape
Dahlin, K.; Asner, G. P.; Field, C. B.
2009-12-01
Aboveground biomass accumulation is a useful metric for evaluating habitat restoration and ecosystem services projects, in addition to being a robust measure of carbon sequestration. However, at the landscape scale non-anthropogenic controls on biomass accumulation are poorly understood. In this study we combined field measurements, high resolution data from the NASA JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Carnegie Airborne Observatory (CAO) airborne light detection and ranging (lidar) system to create a comprehensive map of aboveground biomass across a patchy mediterranean-type landscape (Jasper Ridge Biological Preserve, Stanford, CA). Candidate explanatory variables (e.g. slope, elevation, incident solar radiation) were developed using a geologic map and a digital elevation model derived from the lidar data. Finally, candidate variables were tested, and a model was produced to predict aboveground biomass from environmental data. Though many of the explanatory variables have only indirect effects on plant growth, the model permits inferences to be made about the relative importance of light, water, temperature, and edaphic characteristics on carbon accumulation in mediterranean-type systems.
Johnson, Michelle O; Galbraith, David; Gloor, Manuel; De Deurwaerder, Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; von Randow, Celso; Monteagudo, Abel; Phillips, Oliver L; Brienen, Roel J W; Feldpausch, Ted R; Lopez Gonzalez, Gabriela; Fauset, Sophie; Quesada, Carlos A; Christoffersen, Bradley; Ciais, Philippe; Sampaio, Gilvan; Kruijt, Bart; Meir, Patrick; Moorcroft, Paul; Zhang, Ke; Alvarez-Davila, Esteban; Alves de Oliveira, Atila; Amaral, Ieda; Andrade, Ana; Aragao, Luiz E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Arroyo, Luzmila; Aymard, Gerardo A; Baraloto, Christopher; Barroso, Jocely; Bonal, Damien; Boot, Rene; Camargo, Jose; Chave, Jerome; Cogollo, Alvaro; Cornejo Valverde, Fernando; Lola da Costa, Antonio C; Di Fiore, Anthony; Ferreira, Leandro; Higuchi, Niro; Honorio, Euridice N; Killeen, Tim J; Laurance, Susan G; Laurance, William F; Licona, Juan; Lovejoy, Thomas; Malhi, Yadvinder; Marimon, Bia; Marimon, Ben Hur; Matos, Darley C L; Mendoza, Casimiro; Neill, David A; Pardo, Guido; Peña-Claros, Marielos; Pitman, Nigel C A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Roopsind, Anand; Rudas, Agustin; Salomao, Rafael P; Silveira, Marcos; Stropp, Juliana; Ter Steege, Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van der Heijden, Geertje M F; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A; Baker, Timothy R
2016-12-01
Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Dispersal limitation induces long-term biomass collapse in overhunted Amazonian forests.
Peres, Carlos A; Emilio, Thaise; Schietti, Juliana; Desmoulière, Sylvain J M; Levi, Taal
2016-01-26
Tropical forests are the global cornerstone of biological diversity, and store 55% of the forest carbon stock globally, yet sustained provisioning of these forest ecosystem services may be threatened by hunting-induced extinctions of plant-animal mutualisms that maintain long-term forest dynamics. Large-bodied Atelinae primates and tapirs in particular offer nonredundant seed-dispersal services for many large-seeded Neotropical tree species, which on average have higher wood density than smaller-seeded and wind-dispersed trees. We used field data and models to project the spatial impact of hunting on large primates by ∼ 1 million rural households throughout the Brazilian Amazon. We then used a unique baseline dataset on 2,345 1-ha tree plots arrayed across the Brazilian Amazon to model changes in aboveground forest biomass under different scenarios of hunting-induced large-bodied frugivore extirpation. We project that defaunation of the most harvest-sensitive species will lead to losses in aboveground biomass of between 2.5-5.8% on average, with some losses as high as 26.5-37.8%. These findings highlight an urgent need to manage the sustainability of game hunting in both protected and unprotected tropical forests, and place full biodiversity integrity, including populations of large frugivorous vertebrates, firmly in the agenda of reducing emissions from deforestation and forest degradation (REDD+) programs.
Robinson, C. M.; Saatchi, S. S.; Clark, D.; Fricker, G. A.; Wolf, J.; Gillespie, T. W.; Rovzar, C. M.; Andelman, S.
2012-12-01
This research sought to understand how alpha and beta diversity of plants vary and relate to the three-dimensional vegetation structure and aboveground biomass along environmental gradients in the tropical montane forests of Braulio Carrillo National Park in Costa Rica. There is growing evidence that ecosystem structure plays an important role in defining patterns of species diversity and along with abiotic factors (climate and edaphic) control the phenotypic and functional variations across landscapes. It is well documented that strong subdivisions at local and regional scales are found mainly on geologic or climate gradients. These general determinants of biodiversity are best demonstrated in regions with natural gradients such as tropical montane forests. Altitudinal gradients provide a landscape scale changes through variations in topography, climate, and edaphic conditions on which we tested several theoretical and biological hypotheses regarding drivers of biodiversity. The study was performed by using forest inventory and botanical data from nine 1-ha plots ranging from 100 m to 2800 m above sea level and remote sensing data from airborne lidar and radar sensors to quantify variations in forest structure. In this study we report on the effectiveness of relating patterns of tree taxonomic alpha diversity to three-dimensional structure of a tropical montane forest using lidar and radar observations of forest structure and biomass. We assessed alpha and beta diversity at the species, genus, and family levels utilizing datasets provided by the Terrestrial Ecology Assessment and Monitoring (TEAM) Network. Through the comparison to active remote sensing imagery, our results show that there is a strong relationship between forest 3D-structure, and alpha and beta diversity controlled by variations in abiotic factors along the altitudinal gradient. Using spatial analysis with the aid of remote sensing data, we find distinct patterns along the environmental gradients
Directory of Open Access Journals (Sweden)
Nadir C. Pallqui
2014-12-01
Full Text Available In this study we evaluated the floristic composition and changes in stored biomass and dynamics over time in 9 permanent plots monitored by RAINFOR (Amazon Forest Inventory Network and located in the lowland Amazon rainforest of the Tambopata National Reserve. Data were acquired in the field using the standardized methodology of RAINFOR. The biomass was estimated using the equation for tropical moist forests of Chave et al. (2005. Biomass dynamics were analyzed, in three separated periods from 2003 to 2011. 64 families, 219 genera and 531 species were recorded. The tree floristic composition is very similar in all plots except for one swamp plot, although but it is also evident that two slightly different forest communities exist in the rest of landscape, apparently related to the age of the ancient river terraces in the area. Mortality and recruitment of individuals averaged 2.12 ± 0.52% and 1.92 ± 0.49%, respectively. The turnover rate is 2.02% per year. Aboveground biomass stored in these forests averages 296.2 ± 33.9 t ha-1. The biomass dynamics show a total net gain of 1.96, 1.69 and –1.23 t ha-1 for period respectively. Prior to the drought of 2010 a change in biomass was found 1.88 t ha-1 yr-1 and post drought was -0.18 t ha-1 yr-1 on average, though the difference is not significant. Demographic analysis suggests a dynamic equilibrium in the plots. The negative balance of biomass observed for the period 2008 – 2011 may be due to the drought of 2010, in which half of the monitored plots experienced negative net biomass change due to mortality of individuals selectively affecting the floristic composition.
Bringing Together Users and Developers of Forest Biomass Maps
Brown, Molly Elizabeth; Macauley, Molly K.
2012-01-01
Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the
Dai, Erfu; Wu, Zhuo; Ge, Quansheng; Xi, Weimin; Wang, Xiaofan
2016-11-01
In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS-II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET-II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010-2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad-leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad-leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types. © 2016
Directory of Open Access Journals (Sweden)
Martin Rutzinger
2010-12-01
Full Text Available In this study, a semi-empirical model that was originally developed for stem volume estimation is used for aboveground biomass (AGB estimation of a spruce dominated alpine forest. The reference AGB of the available sample plots is calculated from forest inventory data by means of biomass expansion factors. Furthermore, the semi-empirical model is extended by three different canopy transparency parameters derived from airborne LiDAR data. These parameters have not been considered for stem volume estimation until now and are introduced in order to investigate the behavior of the model concerning AGB estimation. The developed additional input parameters are based on the assumption that transparency of vegetation can be measured by determining the penetration of the laser beams through the canopy. These parameters are calculated for every single point within the 3D point cloud in order to consider the varying properties of the vegetation in an appropriate way. Exploratory Data Analysis (EDA is performed to evaluate the influence of the additional LiDAR derived canopy transparency parameters for AGB estimation. The study is carried out in a 560 km2 alpine area in Austria, where reference forest inventory data and LiDAR data are available. The investigations show that the introduction of the canopy transparency parameters does not change the results significantly according to R2 (R2 = 0.70 to R2 = 0.71 in comparison to the results derived from, the semi-empirical model, which was originally developed for stem volume estimation.
Singh, Minerva; Malhi, Yadvinder; Bhagwat, Shonil
2014-01-01
The focus of this study is to assess the efficacy of using optical remote sensing (RS) in evaluating disparities in forest composition and aboveground biomass (AGB). The research was carried out in the East Sabah region, Malaysia, which constitutes a disturbance gradient ranging from pristine old growth forests to forests that have experienced varying levels of disturbances. Additionally, a significant proportion of the area consists of oil palm plantations. In accordance with local laws, riparian forest (RF) zones have been retained within oil palm plantations and other forest types. The RS imagery was used to assess forest stand structure and AGB. Band reflectance, vegetation indicators, and gray-level co-occurrence matrix (GLCM) consistency features were used as predictor variables in regression analysis. Results indicate that the spectral variables were limited in their effectiveness in differentiating between forest types and in calculating biomass. However, GLCM based variables illustrated strong correlations with the forest stand structures as well as with the biomass of the various forest types in the study area. The present study provides new insights into the efficacy of texture examination methods in differentiating between various land-use types (including small, isolated forest zones such as RFs) as well as their AGB stocks.
Saatchi, Sasan; Rignot, Eric; Vanzyl, Jakob
1995-01-01
In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR
Does species richness affect fine root biomass and production in young forest plantations?
DEFF Research Database (Denmark)
Domisch, Timo; Finér, Leena; Dawud, Seid Muhie
2015-01-01
Tree species diversity has been reported to increase forest ecosystem above-ground biomass and productivity, but little is known about below-ground biomass and production in diverse mixed forests compared to single-species forests. For testing whether species richness increases below-ground biomass...... and production and thus complementarity between forest tree species in young stands, we determined fine root biomass and production of trees and ground vegetation in two experimental plantations representing gradients in tree species richness. Additionally, we measured tree fine root length and determined...... be that these stands were still young, and canopy closure had not always taken place, i.e. a situation where above- or below-ground competition did not yet exist. Another reason could be that the rooting traits of the tree species did not differ sufficiently to support niche differentiation. Our results suggested...
Dengsheng Lu; Qi Chen; Guangxing Wang; Emilio Moran; Mateus Batistella; Maozhen Zhang; Gaia Vaglio Laurin; David Saah
2012-01-01
Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonst...
Fernández-Manso, O.; Fernández-Manso, A.; Quintano, C.
2014-09-01
Aboveground biomass (AGB) estimation from optical satellite data is usually based on regression models of original or synthetic bands. To overcome the poor relation between AGB and spectral bands due to mixed-pixels when a medium spatial resolution sensor is considered, we propose to base the AGB estimation on fraction images from Linear Spectral Mixture Analysis (LSMA). Our study area is a managed Mediterranean pine woodland (Pinus pinaster Ait.) in central Spain. A total of 1033 circular field plots were used to estimate AGB from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) optical data. We applied Pearson correlation statistics and stepwise multiple regression to identify suitable predictors from the set of variables of original bands, fraction imagery, Normalized Difference Vegetation Index and Tasselled Cap components. Four linear models and one nonlinear model were tested. A linear combination of ASTER band 2 (red, 0.630-0.690 μm), band 8 (short wave infrared 5, 2.295-2.365 μm) and green vegetation fraction (from LSMA) was the best AGB predictor (Radj2=0.632, the root-mean-squared error of estimated AGB was 13.3 Mg ha-1 (or 37.7%), resulting from cross-validation), rather than other combinations of the above cited independent variables. Results indicated that using ASTER fraction images in regression models improves the AGB estimation in Mediterranean pine forests. The spatial distribution of the estimated AGB, based on a multiple linear regression model, may be used as baseline information for forest managers in future studies, such as quantifying the regional carbon budget, fuel accumulation or monitoring of management practices.
Memiaghe, Hervé R; Lutz, James A; Korte, Lisa; Alonso, Alfonso; Kenfack, David
2016-01-01
Tropical forests have long been recognized for their biodiversity and ecosystem services. Despite their importance, tropical forests, and particularly those of central Africa, remain understudied. Until recently, most forest inventories in Central Africa have focused on trees ≥10 cm in diameter, even though several studies have shown that small-diameter tree population may be important to demographic rates and nutrient cycling. To determine the ecological importance of small-diameter trees in central African forests, we used data from a 25-ha permanent plot that we established in the rainforest of Gabon to study the diversity and dynamics of these forests. Within the plot, we censused 175,830 trees ≥1 cm dbh from 54 families, 192 genera, and 345 species. Average tree density was 7,026 trees/ha, basal area 31.64 m2/ha, and above-ground biomass 369.40 Mg/ha. Fabaceae, Ebenaceae and Euphorbiaceae were the most important families by basal area, density and above-ground biomass. Small-diameter trees (1 cm ≥ dbh tree population, 16.5% of basal area, and 4.8% of the above-ground biomass. They also had diversity 18% higher at family level, 34% higher at genus level, and 42% higher at species level than trees ≥10 cm dbh. Although the relative contribution of small-diameter trees to biomass was comparable to other forests globally, their contribution to forest density, and diversity was disproportionately higher. The high levels of diversity within small-diameter classes may give these forests high levels of structural resilience to anthropogenic/natural disturbance and a changing climate.
Mitchard, Edward TA; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra
2013-01-01
BackgroundMapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m – 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by t...
an expansion of the aboveground biomass quantification model for ...
African Journals Online (AJOL)
Research Note BECVOL 3: an expansion of the aboveground biomass quantification model for ... African Journal of Range and Forage Science ... encroachment and estimation of food to browser herbivore species, was proposed during 1989.
Chen, Xuexia; Liu, Shuguang; Zhu, Zhiliang; Vogelmann, James E.; Li, Zhengpeng; Ohlen, Donald O.
2011-01-01
The concentrations of CO2 and other greenhouse gases in the atmosphere have been increasing and greatly affecting global climate and socio-economic systems. Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High
Directory of Open Access Journals (Sweden)
Sandra Eckert
2012-03-01
Full Text Available Accurate estimation of aboveground biomass and carbon stock has gained importance in the context of the United Nations Framework Convention on Climate Change (UNFCCC and the Kyoto Protocol. In order to develop improved forest stratum–specific aboveground biomass and carbon estimation models for humid rainforest in northeast Madagascar, this study analyzed texture measures derived from WorldView-2 satellite data. A forest inventory was conducted to develop stratum-specific allometric equations for dry biomass. On this basis, carbon was calculated by applying a conversion factor. After satellite data preprocessing, vegetation indices, principal components, and texture measures were calculated. The strength of their relationships with the stratum-specific plot data was analyzed using Pearson’s correlation. Biomass and carbon estimation models were developed by performing stepwise multiple linear regression. Pearson’s correlation coefficients revealed that (a texture measures correlated more with biomass and carbon than spectral parameters, and (b correlations were stronger for degraded forest than for non-degraded forest. For degraded forest, the texture measures of Correlation, Angular Second Moment, and Contrast, derived from the red band, contributed to the best estimation model, which explained 84% of the variability in the field data (relative RMSE = 6.8%. For non-degraded forest, the vegetation index EVI and the texture measures of Variance, Mean, and Correlation, derived from the newly introduced coastal blue band, both NIR bands, and the red band, contributed to the best model, which explained 81% of the variability in the field data (relative RMSE = 11.8%. These results indicate that estimation of tropical rainforest biomass/carbon, based on very high resolution satellite data, can be improved by (a developing and applying forest stratum–specific models, and (b including textural information in addition to spectral information.
Safari, A.; Sohrabi, H.
2016-06-01
The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics
Directory of Open Access Journals (Sweden)
Rocio Urrutia-Jalabert
Full Text Available Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP, carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA in the Andean Cordillera. Aboveground live biomass was 113-114 Mg C ha(-1 and 448-517 Mg C ha(-1 in AC and AA, respectively. Aboveground productivity was 3.35-3.36 Mg C ha(-1 year(-1 in AC and 2.22-2.54 Mg C ha(-1 year(-1 in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21-4.24 and 3.78-4.10 Mg C ha(-1 year(-1 in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539-640 years for the whole forest in the Andes and 1368-1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia.
Urrutia-Jalabert, Rocio; Malhi, Yadvinder; Lara, Antonio
2015-01-01
Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP), carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC) in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA) in the Andean Cordillera. Aboveground live biomass was 113-114 Mg C ha(-1) and 448-517 Mg C ha(-1) in AC and AA, respectively. Aboveground productivity was 3.35-3.36 Mg C ha(-1) year(-1) in AC and 2.22-2.54 Mg C ha(-1) year(-1) in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21-4.24 and 3.78-4.10 Mg C ha(-1) year(-1) in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539-640 years for the whole forest in the Andes and 1368-1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia.
Wen J. Wang; Hong S. He; Frank R. Thompson; Jacob S. Fraser; William D. Dijak
2016-01-01
Context. Forests in the northeastern United States are currently in early- and mid-successional stages recovering from historical land use. Climate change will affect forest distribution and structure and have important implications for biodiversity, carbon dynamics, and human well-being. Objective. We addressed how aboveground biomass (AGB) and...
Directory of Open Access Journals (Sweden)
ROBSON B. DE LIMA
2017-08-01
Full Text Available ABSTRACT Dry tropical forests are a key component in the global carbon cycle and their biomass estimates depend almost exclusively of fitted equations for multi-species or individual species data. Therefore, a systematic evaluation of statistical models through validation of estimates of aboveground biomass stocks is justifiable. In this study was analyzed the capacity of generic and specific equations obtained from different locations in Mexico and Brazil, to estimate aboveground biomass at multi-species levels and for four different species. Generic equations developed in Mexico and Brazil performed better in estimating tree biomass for multi-species data. For Poincianella bracteosa and Mimosa ophthalmocentra, only the Sampaio and Silva (2005 generic equation was the most recommended. These equations indicate lower tendency and lower bias, and biomass estimates for these equations are similar. For the species Mimosa tenuiflora, Aspidosperma pyrifolium and for the genus Croton the specific regional equations are more recommended, although the generic equation of Sampaio and Silva (2005 is not discarded for biomass estimates. Models considering gender, families, successional groups, climatic variables and wood specific gravity should be adjusted, tested and the resulting equations should be validated at both local and regional levels as well as on the scales of tropics with dry forest dominance.
Lima, Robson B DE; Alves, Francisco T; Oliveira, Cinthia P DE; Silva, José A A DA; Ferreira, Rinaldo L C
2017-01-01
Dry tropical forests are a key component in the global carbon cycle and their biomass estimates depend almost exclusively of fitted equations for multi-species or individual species data. Therefore, a systematic evaluation of statistical models through validation of estimates of aboveground biomass stocks is justifiable. In this study was analyzed the capacity of generic and specific equations obtained from different locations in Mexico and Brazil, to estimate aboveground biomass at multi-species levels and for four different species. Generic equations developed in Mexico and Brazil performed better in estimating tree biomass for multi-species data. For Poincianella bracteosa and Mimosa ophthalmocentra, only the Sampaio and Silva (2005) generic equation was the most recommended. These equations indicate lower tendency and lower bias, and biomass estimates for these equations are similar. For the species Mimosa tenuiflora, Aspidosperma pyrifolium and for the genus Croton the specific regional equations are more recommended, although the generic equation of Sampaio and Silva (2005) is not discarded for biomass estimates. Models considering gender, families, successional groups, climatic variables and wood specific gravity should be adjusted, tested and the resulting equations should be validated at both local and regional levels as well as on the scales of tropics with dry forest dominance.
DEFF Research Database (Denmark)
Hu, Teng; Sørensen, Peter; Wahlström, Ellen Margrethe
2018-01-01
and management factors may affect this allometric relationship making such estimates uncertain and biased. Therefore, we aimed to explore how root biomass for typical cereal crops, catch crops and weeds could most reliably be estimated. Published and unpublished data on aboveground and root biomass (corrected...
Biomass is the main driver of changes in ecosystem process rates during tropical forest succession.
Lohbeck, Madelon; Poorter, Lourens; Martínez-Ramos, Miguel; Bongers, Frans
2015-05-01
Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity, actual litter decomposition, and potential litter decomposition) during secondary succession after shifting cultivation in wet tropical forest of Mexico. We test the importance of three alternative drivers of ecosystem processes: vegetation biomass (vegetation quantity hypothesis), community-weighted trait mean (mass ratio hypothesis), and functional diversity (niche complementarity hypothesis) using structural equation modeling. This allows us to infer the relative importance of different mechanisms underlying ecosystem process recovery. Ecosystem process rates changed during succession, and the strongest driver was aboveground biomass for each of the processes. Productivity of aboveground stem biomass and leaf litter as well as actual litter decomposition increased with initial standing vegetation biomass, whereas potential litter decomposition decreased with standing biomass. Additionally, biomass productivity was positively affected by community-weighted mean of specific leaf area, and potential decomposition was positively affected by functional divergence, and negatively by community-weighted mean of leaf dry matter content. Our empirical results show that functional diversity and community-weighted means are of secondary importance for explaining changes in ecosystem process rates during tropical forest succession. Instead, simply, the amount of vegetation in a site is the major driver of changes, perhaps because there is a steep biomass buildup during succession that overrides more subtle effects of community functional properties on ecosystem processes. We recommend future studies in the field of biodiversity and ecosystem functioning to separate the effects of
Forest biomass estimated from MODIS and FIA data in the Lake States: MN, WI and MI, USA
Daolan Zheng; Linda S. Heath; Mark J. Ducey
2007-01-01
This study linked the Moderate Resolution Imaging Spectrometer and USDA Forest Service, Forest Inventory and Analysis (FIA) data through empirical models established using high-resolution Landsat Enhanced Thematic Mapper Plus observations to estimate aboveground biomass (AGB) in three Lake States in the north-central USA. While means obtained from larger sample sizes...
Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon
Nelson, Ross F.
2010-01-01
Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.
Mitchard, Edward Ta; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra
2013-10-26
Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m - 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO's Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide
Impact of deforestation and climate on the Amazon Basin's above-ground biomass during 1993-2012.
Exbrayat, Jean-François; Liu, Yi Y; Williams, Mathew
2017-11-15
Since the 1960s, large-scale deforestation in the Amazon Basin has contributed to rising global CO 2 concentrations and to climate change. Recent advances in satellite observations enable estimates of gross losses of above-ground biomass (AGB) stocks due to deforestation. However, because of simultaneous regrowth, the net contribution of deforestation emissions to rising atmospheric CO 2 concentrations is poorly quantified. Climate change may also reduce the potential for forest regeneration in previously disturbed regions. Here, we address these points of uncertainty with a machine-learning approach that combines satellite observations of AGB with climate data across the Amazon Basin to reconstruct annual maps of potential AGB during 1993-2012, the above-ground C storage potential of the undisturbed landscape. We derive a 2.2 Pg C loss of AGB over the study period, and, for the regions where these losses occur, we estimate a 0.7 Pg C reduction in potential AGB. Thus, climate change has led to a decline of ~1/3 in the capacity of these disturbed forests to recover and recapture the C lost in disturbances during 1993-2012. Our approach further shows that annual variations in land use change mask the natural relationship between the El Niño/Southern Oscillation and AGB stocks in disturbed regions.
Mukul, Sharif A; Herbohn, John; Firn, Jennifer
2016-03-08
In the tropics, shifting cultivation has long been attributed to large scale forest degradation, and remains a major source of uncertainty in forest carbon accounting. In the Philippines, shifting cultivation, locally known as kaingin, is a major land-use in upland areas. We measured the distribution and recovery of aboveground biomass carbon along a fallow gradient in post-kaingin secondary forests in an upland area in the Philippines. We found significantly higher carbon in the aboveground total biomass and living woody biomass in old-growth forest, while coarse dead wood biomass carbon was higher in the new fallow sites. For young through to the oldest fallow secondary forests, there was a progressive recovery of biomass carbon evident. Multivariate analysis indicates patch size as an influential factor in explaining the variation in biomass carbon recovery in secondary forests after shifting cultivation. Our study indicates secondary forests after shifting cultivation are substantial carbon sinks and that this capacity to store carbon increases with abandonment age. Large trees contribute most to aboveground biomass. A better understanding of the relative contribution of different biomass sources in aboveground total forest biomass, however, is necessary to fully capture the value of such landscapes from forest management, restoration and conservation perspectives.
Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass
Laurance, William F.
2004-01-01
This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.
Hughes, R F; Kauffman, J B; Cummings, D L
2000-09-01
Regenerating forests have become a common land-cover type throughout the Brazilian Amazon. However, the potential for these systems to accumulate and store C and nutrients, and the fluxes resulting from them when they are cut, burned, and converted back to croplands and pastures have not been well quantified. In this study, we quantified pre- and post-fire pools of biomass, C, and nutrients, as well as the emissions of those elements, at a series of second- and third-growth forests located in the states of Pará and Rondônia, Brazil. Total aboveground biomass (TAGB) of second- and third-growth forests averaged 134 and 91 Mg ha -1 , respectively. Rates of aboveground biomass accumulation were rapid in these systems, but were not significantly different between second- and third-growth forests, ranging from 9 to 16 Mg ha -1 year -1 . Residual pools of biomass originating from primary forest vegetation accounted for large portions of TAGB in both forest types and were primarily responsible for TAGB differences between the two forest types. In second-growth forests this pool (82 Mg ha -1 ) represented 58% of TAGB, and in third-growth forests (40 Mg ha -1 ) it represented 40% of TAGB. Amounts of TAGB consumed by burning of second- and third-growth forests averaged 70 and 53 Mg ha -1 , respectively. Aboveground pre-fire pools in second- and third-growth forests averaged 67 and 45 Mg C ha -1 , 821 and 707 kg N ha -1 , 441 and 341 kg P ha -1 , and 46 and 27 kg Ca ha -1 , respectively. While pre-fire pools of C, N, S and K were not significantly different between second- and third-growth forests, pools of both P and Ca were significantly higher in second-growth forests. This suggests that increasing land use has a negative impact on these elemental pools. Site losses of elements resulting from slashing and burning these sites were highly variable: losses of C ranged from 20 to 47 Mg ha -1 ; N losses ranged from 306 to 709 kg ha -1 ; Ca losses ranged from 10 to 145 kg ha -1
DEFF Research Database (Denmark)
Nord-Larsen, Thomas; Schumacher, Johannes
2012-01-01
Airborne laser scanning may provide a means for assessing local forest biomass resources. In this study, national forest inventory (NFI) data was used as reference data for modeling forest basal area, volume, aboveground biomass, and total biomass from laser scanning data obtained in a countrywid...
Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico
2018-04-01
Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0
Does species richness affect fine root biomass and production in young forest plantations?
Domisch, Timo; Finér, Leena; Dawud, Seid Muhie; Vesterdal, Lars; Raulund-Rasmussen, Karsten
2015-02-01
Tree species diversity has been reported to increase forest ecosystem above-ground biomass and productivity, but little is known about below-ground biomass and production in diverse mixed forests compared to single-species forests. For testing whether species richness increases below-ground biomass and production and thus complementarity between forest tree species in young stands, we determined fine root biomass and production of trees and ground vegetation in two experimental plantations representing gradients in tree species richness. Additionally, we measured tree fine root length and determined species composition from fine root biomass samples with the near-infrared reflectance spectroscopy method. We did not observe higher biomass or production in mixed stands compared to monocultures. Neither did we observe any differences in tree root length or fine root turnover. One reason for this could be that these stands were still young, and canopy closure had not always taken place, i.e. a situation where above- or below-ground competition did not yet exist. Another reason could be that the rooting traits of the tree species did not differ sufficiently to support niche differentiation. Our results suggested that functional group identity (i.e. conifers vs. broadleaved species) can be more important for below-ground biomass and production than the species richness itself, as conifers seemed to be more competitive in colonising the soil volume, compared to broadleaved species.
He, Huaijiang; Zhang, Chunyu; Zhao, Xiuhai; Fousseni, Folega; Wang, Jinsong; Dai, Haijun; Yang, Song; Zuo, Qiang
2018-01-01
Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9-12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China.
Directory of Open Access Journals (Sweden)
Francisca Rocha de Souza Pereira
2018-04-01
Full Text Available Remote sensing techniques offer useful tools for estimating forest biomass to large extent, thereby contributing to the monitoring of land use and landcover dynamics and the effectiveness of environmental policies. The main goal of this study was to investigate the potential use of discrete return light detection and ranging (lidar data to produce accurate aboveground biomass (AGB maps of mangrove forests. AGB was estimated in 34 small plots scatted over a 50 km2 mangrove forest in Rio de Janeiro, Brazil. Plot AGB was computed using either species-specific or non-species-specific allometric models. A total of 26 descriptive lidar metrics were extracted from the normalized height of the lidar point cloud data, and various model forms (random forest and partial least squares regression with backward selection of predictors (Auto-PLS were tested to predict the recorded AGB. The models developed using species-specific allometric models were distinctly more accurate (R2(calibration = 0.89, R2(validation = 0.80, root-mean-square error (RMSE, calibration = 11.20 t·ha−1, and RMSE(validation = 14.80 t·ha−1. The use of non-species-specific allometric models yielded large errors on a landscape scale (+14% or −18% bias depending on the allometry considered, indicating that using poor quality training data not only results in low precision but inaccuracy at all scales. It was concluded that under suitable sampling pattern and provided that accurate field data are used, discrete return lidar can accurately estimate and map the AGB in mangrove forests. Conversely this study underlines the potential bias affecting the estimates of AGB in other forested landscapes where only non-species-specific allometric equations are available.
Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012
International Nuclear Information System (INIS)
Tyukavina, A; Hansen, M C; Potapov, P V; Krylov, A M; Turubanova, S; Baccini, A; Houghton, R A; Goetz, S J; Stehman, S V
2015-01-01
Tropical forests provide global climate regulation ecosystem services and their clearing is a significant source of anthropogenic greenhouse gas (GHG) emissions and resultant radiative forcing of climate change. However, consensus on pan-tropical forest carbon dynamics is lacking. We present a new estimate that employs recommended good practices to quantify gross tropical forest aboveground carbon (AGC) loss from 2000 to 2012 through the integration of Landsat-derived tree canopy cover, height, intactness and forest cover loss and GLAS-lidar derived forest biomass. An unbiased estimate of forest loss area is produced using a stratified random sample with strata derived from a wall-to-wall 30 m forest cover loss map. Our sample-based results separate the gross loss of forest AGC into losses from natural forests (0.59 PgC yr −1 ) and losses from managed forests (0.43 PgC yr −1 ) including plantations, agroforestry systems and subsistence agriculture. Latin America accounts for 43% of gross AGC loss and 54% of natural forest AGC loss, with Brazil experiencing the highest AGC loss for both categories at national scales. We estimate gross tropical forest AGC loss and natural forest loss to account for 11% and 6% of global year 2012 CO 2 emissions, respectively. Given recent trends, natural forests will likely constitute an increasingly smaller proportion of tropical forest GHG emissions and of global emissions as fossil fuel consumption increases, with implications for the valuation of co-benefits in tropical forest conservation. (letter)
Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data
Directory of Open Access Journals (Sweden)
Xiaohuan Xi
2016-03-01
Full Text Available Forest biomass is an important parameter for quantifying and understanding biological and physical processes on the Earth’s surface. Rapid, reliable, and objective estimations of forest biomass are essential to terrestrial ecosystem research. The Geoscience Laser Altimeter System (GLAS produced substantial scientific data for detecting the vegetation structure at the footprint level. This study combined GLAS data with MODIS/BRDF (Bidirectional Reflectance Distribution Function and ASTER GDEM data to estimate forest aboveground biomass (AGB in Xishuangbanna, Yunnan Province, China. The GLAS waveform characteristic parameters were extracted using the wavelet method. The ASTER DEM was used to compute the terrain index for reducing the topographic influence on the GLAS canopy height estimation. A neural network method was applied to assimilate the MODIS BRDF data with the canopy heights for estimating continuous forest heights. Forest leaf area indices (LAIs were derived from Landsat TM imagery. A series of biomass estimation models were developed and validated using regression analyses between field-estimated biomass, canopy height, and LAI. The GLAS-derived canopy heights in Xishuangbanna correlated well with the field-estimated AGB (R2 = 0.61, RMSE = 52.79 Mg/ha. Combining the GLAS estimated canopy heights and LAI yielded a stronger correlation with the field-estimated AGB (R2 = 0.73, RMSE = 38.20 Mg/ha, which indicates that the accuracy of the estimated biomass in complex terrains can be improved significantly by integrating GLAS and optical remote sensing data.
Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar
Chen, Qi
2015-08-01
Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.
Smallman, T. L.; Exbrayat, J.-F.; Mencuccini, M.; Bloom, A. A.; Williams, M.
2017-03-01
Forest carbon sink strengths are governed by plant growth, mineralization of dead organic matter, and disturbance. Across landscapes, remote sensing can provide information about aboveground states of forests and this information can be linked to models to estimate carbon cycling in forests close to steady state. For aggrading forests this approach is more challenging and has not been demonstrated. Here we apply a Bayesian approach, linking a simple model to a range of data, to evaluate their information content, for two aggrading forests. We compare high information content analyses using local observations with retrievals using progressively sparser remotely sensed information (repeated, single, and no woody biomass observations). The net biome productivity of both forests is constrained to be a net sink with litter dynamics at one forest, while at the second forest total dead organic matter estimates are within observational uncertainty. The uncertainty of retrieved ecosystem traits in the repeated biomass analysis is reduced by up to 50% compared to analyses with less biomass information. This study quantifies the importance of repeated woody observations in constraining the dynamics of both wood and dead organic matter, highlighting the benefit of proposed remote sensing missions.
Forest biomass mapping from fusion of GEDI Lidar data and TanDEM-X InSAR data
Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.
2017-12-01
Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910
International Nuclear Information System (INIS)
Risio, Lucia; Herrero, Celia; Bogino, Stella M.; Bravo, Felipe
2014-01-01
The woodlands in the south-west of the Argentinean pampas are dominated by Prosopis Caldenia Burkart (calden). The current deforestation rate of this woodlands is 0.82% per year. Different compensation initiatives have begun that recognize the role of forests as environmental service providers. The financial incentives they offer make it necessary to quantify the amount of carbon stored in the forest biomass. A model for estimating calden biomass was developed. Thirty-eight trees were selected, felled and divided into sections. An equation system was fitted using joint generalized regression to ensure the additivity property. A weighted regression was used to avoid heteroscedasticity. In these woodlands fire is the main disturbance and it can modify tree allometry, due this all models included the area of the base of the stem and tree height as independent variables since it indirectly collects this variability. Total biomass and the stem fraction had the highest R2 A dj. values (0.75), while branches with a diameter less than 7 cm had the lowest (0.58). Tree biomass was also analyzed by partitioning into the basic fractions of stem, crown, roots, and the root/shoot ratio. Biomass allocation was greatest in the crown fraction and the mean root/shoot ratio was 0.58. The carbon stock of the caldenales considering only calden tree biomass is 20.2 Mg ha −1 . While the overall carbon balance of the region is negative (deforestation and biomass burning, the remnant forested area has increased their calden density and in an indirect way his carbon sequestration capacity could also be increased. - Highlights: • A model for estimating aboveground and belowground Prosopis caldenia biomass was developed. • Biomass allocation into the tree and the root/shoot ratio were analyzed. • The equation systems presented had made it possible to more accurately estimate the biomass stored in calden woodlands
Deadwood biomass: an underestimated carbon stock in degraded tropical forests?
Pfeifer, Marion; Lefebvre, Veronique; Turner, Edgar; Cusack, Jeremy; Khoo, MinSheng; Chey, Vun K.; Peni, Maria; Ewers, Robert M.
2015-04-01
Despite a large increase in the area of selectively logged tropical forest worldwide, the carbon stored in deadwood across a tropical forest degradation gradient at the landscape scale remains poorly documented. Many carbon stock studies have either focused exclusively on live standing biomass or have been carried out in primary forests that are unaffected by logging, despite the fact that coarse woody debris (deadwood with ≥10 cm diameter) can contain significant portions of a forest’s carbon stock. We used a field-based assessment to quantify how the relative contribution of deadwood to total above-ground carbon stock changes across a disturbance gradient, from unlogged old-growth forest to severely degraded twice-logged forest, to oil palm plantation. We measured in 193 vegetation plots (25 × 25 m), equating to a survey area of >12 ha of tropical humid forest located within the Stability of Altered Forest Ecosystems Project area, in Sabah, Malaysia. Our results indicate that significant amounts of carbon are stored in deadwood across forest stands. Live tree carbon storage decreased exponentially with increasing forest degradation 7-10 years after logging while deadwood accounted for >50% of above-ground carbon stocks in salvage-logged forest stands, more than twice the proportion commonly assumed in the literature. This carbon will be released as decomposition proceeds. Given the high rates of deforestation and degradation presently occurring in Southeast Asia, our findings have important implications for the calculation of current carbon stocks and sources as a result of human-modification of tropical forests. Assuming similar patterns are prevalent throughout the tropics, our data may indicate a significant global challenge to calculating global carbon fluxes, as selectively-logged forests now represent more than one third of all standing tropical humid forests worldwide.
Yan, Tao; Zhu, Jiao-Jun; Yang, Kai; Yu, Li-Zhong
2014-10-01
Larch is the main timber species of forest plantations in North China. Imbalance in nutrient cycling in soil emerged due to single species composition and mono system structure of plantation. Thus it is necessary to grasp its biomass and nutrients allocation for scientific management and nutrient cycling studies of larch plantation. We measured aboveground biomass (stem, branch, bark and leaf) and nutrient concentrations (C, N, P, K, Ca, Mg, Fe, Mn, Cu and Zn), and analyzed the patterns of accumulation and distribution of 19-year-old larch plantation with diameter at breast height of 12. 8 cm, tree height of 15. 3 m, and density of 2308 trees · hm(-2), in a montane region of eastern Liaoning Province, China. The results showed that aboveground biomass values were 70.26 kg and 162.16 t · hm(-2) for the individual tree of larch and the stand, respectively. There was a significant difference between biomass of the organs, and decreased in the order of stem > branch > bark > leaf. Nutrient accumulation was 749.94 g and 1730.86 kg · hm(-2) for the individual tree of larch and the stand, respectively. Nutrient accumulation of stem was significantly higher than that of branch, bark and leaf, whether it was macro-nutrient or micro-nutrient. Averagely, 749.94 g nutrient elements would be removed from the system when a 19-year-old larch tree was harvested. If only the stem part was removed from the system, the removal of nutrient elements could be reduced by 40.7%.
Sparse Density, Leaf-Off Airborne Laser Scanning Data in Aboveground Biomass Component Prediction
Directory of Open Access Journals (Sweden)
Ville Kankare
2015-05-01
Full Text Available The demand for cost-efficient forest aboveground biomass (AGB prediction methods is growing worldwide. The National Land Survey of Finland (NLS began collecting airborne laser scanning (ALS data throughout Finland in 2008 to provide a new high-detailed terrain elevation model. Similar data sets are being collected in an increasing number of countries worldwide. These data sets offer great potential in forest mapping related applications. The objectives of our study were (i to evaluate the AGB component prediction accuracy at a resolution of 300 m2 using sparse density, leaf-off ALS data (collected by NLS derived metrics as predictor variables; (ii to compare prediction accuracies with existing large-scale forest mapping techniques (Multi-source National Forest Inventory, MS-NFI based on Landsat TM satellite imagery; and (iii to evaluate the accuracy and effect of canopy height model (CHM derived metrics on AGB component prediction when ALS data were acquired with multiple sensors and varying scanning parameters. Results showed that ALS point metrics can be used to predict component AGBs with an accuracy of 29.7%–48.3%. AGB prediction accuracy was slightly improved using CHM-derived metrics but CHM metrics had a more clear effect on the estimated bias. Compared to the MS-NFI, the prediction accuracy was considerably higher, which was caused by differences in the remote sensing data utilized.
Light Use Efficiency of Aboveground Biomass Production of Norway Spruce Stands
Czech Academy of Sciences Publication Activity Database
Bellan, Michal; Marková, I.; Zaika, A.; Krejza, Jan
2017-01-01
Roč. 65, č. 1 (2017), s. 9-16 ISSN 1211-8516 R&D Projects: GA TA ČR TA02010945 Institutional support: RVO:67179843 Keywords : absorbed photosynthetically active radiation * aboveground biomass increment * allometric relation Subject RIV: GC - Agronomy OBOR OECD: Agronomy, plant breeding and plant protection
Dar, Javid Ahmad; Sundarapandian, Somaiah
2015-02-01
An accurate characterization of tree, understory, deadwood, floor litter, and soil organic carbon (SOC) pools in temperate forest ecosystems is important to estimate their contribution to global carbon (C) stocks. However, this information on temperate forests of the Himalayas is lacking and fragmented. In this study, we measured C stocks of tree (aboveground and belowground biomass), understory (shrubs and herbaceous), deadwood (standing and fallen trees and stumps), floor litter, and soil from 111 plots of 50 m × 50 m each, in seven forest types: Populus deltoides (PD), Juglans regia (JR), Cedrus deodara (CD), Pinus wallichiana (PW), mixed coniferous (MC), Abies pindrow (AP), and Betula utilis (BU) in temperate forests of Kashmir Himalaya, India. The main objective of the present study is to quantify the ecosystem C pool in these seven forest types. The results showed that the tree biomass ranged from 100.8 Mg ha(-1) in BU forest to 294.8 Mg ha(-1) for the AP forest. The understory biomass ranged from 0.16 Mg ha(-1) in PD forest to 2.36 Mg ha(-1) in PW forest. Deadwood biomass ranged from 1.5 Mg ha(-1) in PD forest to 14.9 Mg ha(-1) for the AP forest, whereas forest floor litter ranged from 2.5 Mg ha(-1) in BU and JR forests to 3.1 Mg ha(-1) in MC forest. The total ecosystem carbon stocks varied from 112.5 to 205.7 Mg C ha(-1) across all the forest types. The C stocks of tree, understory, deadwood, litter, and soil ranged from 45.4 to 135.6, 0.08 to 1.18, 0.7 to 6.8, 1.1 to 1.4, and 39.1-91.4 Mg ha(-1), respectively, which accounted for 61.3, 0.2, 1.4, 0.8, and 36.3 % of the total carbon stock. BU forest accounted 65 % from soil C and 35 % from biomass, whereas PD forest contributed only 26 % from soil C and 74 % from biomass. Of the total C stock in the 0-30-cm soil, about 55 % was stored in the upper 0-10 cm. Soil C stocks in BU forest were significantly higher than those in other forests. The variability of C pools of different ecosystem components is
Forest Biomass Mapping From Lidar and Radar Synergies
Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.
2011-01-01
The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the
Directory of Open Access Journals (Sweden)
S. Sandeep
2015-09-01
Full Text Available The use of suitable tree biomass allometric equations is crucial for making precise and non- destructive estimation of carbon storage and biomass energy values. The aim of this research was to evaluate the accuracy of the most commonly used pantropical allometric models and site-specific models to estimate the above-ground biomass (AGB in different aged teak plantations of Southern Western Ghats of India. For this purpose, the AGB data measured for 70 trees with diameter >10 cm from different aged teak plantations in Kerala part of Southern Western Ghats following destructive procedure was used. The results show that site specific models based on a single predictor variable diameter at breast height (dbh, though simple, may grossly increase the uncertainty across sites. Hence, a generic model encompassing dbh, height and wood specific gravity with sufficient calibration taking into account different forest types is advised for the tropical forest systems. The study also suggests that the commonly used pantropical models should be evaluated for different ecosystems prior to their application at national or regional scales.
Above-ground tree outside forest (TOF) phytomass and carbon ...
Indian Academy of Sciences (India)
to classify TOF, to estimate above-ground TOF phytomass and the carbon content ... eral, trees outside forests (TOF) mean the trees ..... have been used to stratify the area, based on the ... The optimum plot size and num- .... population centres.
CSIR Research Space (South Africa)
Rutherford, MC
1979-01-01
Full Text Available Aboveground peak season biomass is given for 11 woody species in each of five belt transects under study. Mean aerial biomass for all species was 16 273 kg ha, made up of 14 937 kg ha wood, 236 kg ha current season's twigs and 1 100 kg ha leaves...
[Aboveground biomass of Tamarix on piedmont plain of Tianshan Mountains south slope].
Zhao, Zhenyong; Wang, Ranghui; Zhang, Huizhi; Wang, Lei
2006-09-01
Based on the geo-morphological and hydro-geological characteristics, the piedmont plain of Tianshan Mountains south slope was classified into 4 geo-morphological belts, i.e., flood erosion belt, groundwater spill belt, delta belt, and the joining belt of piedmont plain and Tarim floodplain. A field investigation on the Tamarix shrub in this region showed that there was a significant difference in its aboveground biomass among the four belts, ranged from 1428.53 kg x hm(-2) at groundwater spill belt to 111.18 kg x hm(-2) at the joining belt of piedmont plain and Tarim floodplain. The main reason for such a big difference might be the different density of Tamarix shrub on different belts. Both the Tamarix aboveground biomass and the topsoil's salinity were decreased with increasing groundwater level. Groundwater level was the main factor limiting Tamarix growth, while soil salinity was not.
Couto-Santos, F. R.; Luizao, F. J.
2014-12-01
The forests-savanna advancement/retraction process seems to play an important role in the global carbon cycle and in the climate-vegetation balance maintenance in the Amazon. To contribute with long term carbon dynamics and assess effectiveness of a protected area in reduce carbon emissions in Brazilian Amazon transitional areas, variations in forest-savanna mosaics biomass and carbon stock within Maraca Ecological Station (MES), Roraima/Brazil, and its outskirts non-protected areas were compared. Composite surface soil samples and indirect methods based on regression models were used to estimate aboveground tree biomass accumulation and assess vegetation and soil carbon stock along eleven 0.6 ha transects perpendicular to the forest-savanna limits. Aboveground biomass and carbon accumulation were influenced by vegetation structure, showing higher values within protected area, with great contribution of trees above 40 cm in diameter. In the savanna environments of protected areas, a higher tree density and carbon stock up to 30 m from the border confirmed a forest encroachment. This pointed that MES acts as carbon sink, even under variations in soil fertility gradient, with a potential increase of the total carbon stock from 9 to 150 Mg C ha-1. Under 20 years of fire and disturbance management, the results indicated the effectiveness of this protected area to reduce carbon emissions and mitigate greenhouse and climate change effects in a forest-savanna transitional area in Brazilian Northern Amazon. The contribution of this study in understanding rates and reasons for biomass and carbon variation, under different management strategies, should be considered the first approximation to assist policies of reducing emissions from deforestation and forest degradation (REDD) from underresearched Amazonian ecotone; despite further efforts in this direction are still needed. FINANCIAL SUPPORT: Boticário Group Foundation (Fundação Grupo Boticário); National Council for
Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin
2017-01-19
Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass ( R ² = 0.340, root-mean-square error (RMSE) = 81.89 g·m -2 , and relative error of 14.1%). The improvement of multiple regressions to the R ² and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (lidar returns.
Peng, Shou-Zhang; Zhao, Chuan-Yan; Peng, Huan-Hua; Zheng, Xiang-Lin; Xu, Zhong-Lin
2010-08-01
Based on the field observation on the Tamarix ramosissima populations in the lower reaches of Heihe River, the relationship models between the aboveground biomass of T. ramosissima and its morphological features (basal diameter, height, and canopy perimeter) were built. In the mean time, the land use/cover of the study area was classified by the decision tree classification with high resolution image (QuickBird), the distribution of T. ramosissima was extracted from classification map, and the morphological feature (canopy perimeter) of T. ramosissima was calculated with ArcGIS 9.2. On the bases of these, the spatial distribution of T. ramosissima aboveground biomass in the study area was estimated. Finally, the spatial distribution of the water consumption of T. ramosissima in the study area was calculated by the transpiration coefficient (300) and the aboveground biomass. The results showed that the aboveground biomass of T. ramosissima was 69644.7 t, and the biomass per unit area was 0.78 kg x m(-2). Spatially, the habitats along the banks of Heihe River were suitable for T. ramosissima, and thus, this tree species had a high biomass. The total amount of water consumption of T. ramosissima in the study area was 2.1 x 10(7) m3, and the annual mean water consumption of T. ramosissima ranged from 30 mm to 386 mm.
Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass
Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.
2014-12-01
Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation
Fertile forests produce biomass more efficiently
Vicca, S.; Luyssaert, S.; Peñuelas, J.; Campioli, M.; Chapin, F.S. III; Ciais, P.; Heinemeyer, A.; Högberg, P.; Kutsch, W.L.; Law, Beverly E.; Malhi, Y.; Papale, D.; Piao, S.L.; Reichstein, M.; Schulze, E.D.; Janssens, Ivan A.
Trees with sufficient nutrition are known to allocate carbon preferentially to aboveground plant parts. Our global study of 49 forests revealed an even more fundamental carbon allocation response to nutrient availability: forests with high-nutrient availability use 58±3% (mean±SE; 17 forests) of
Patterns of covariance between forest stand and canopy structure in the Pacific Northwest.
Michael A. Lefsky; Andrew T. Hudak; Warren B. Cohen; S.A. Acker
2005-01-01
In the past decade, LIDAR (light detection and ranging) has emerged as a powerful tool for remotely sensing forest canopy and stand structure, including the estimation of aboveground biomass and carbon storage. Numerous papers have documented the use of LIDAR measurements to predict important aspects of forest stand structure, including aboveground biomass. Other...
Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.
2018-04-01
Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.
Directory of Open Access Journals (Sweden)
Karis Tenneson
2018-03-01
Full Text Available Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing the cost of forest-fire management and reintroducing fire to the landscape without negative impact depends on detailed knowledge of stand composition, in particular, above-ground biomass (AGB. Lidar-based modeling techniques provide opportunities to increase ability of managers to monitor AGB and other forest metrics at reduced cost. We developed a regional lidar-based statistical model to estimate AGB for Ponderosa pine and mixed conifer forest systems of the southwestern USA, using previously collected field data. Model selection was performed using Bayesian model averaging (BMA to reduce researcher bias, fully explore the model space, and avoid overfitting. The selected model includes measures of canopy height, canopy density, and height distribution. The model selected with BMA explains 71% of the variability in field-estimates of AGB, and the RMSE of the two independent validation data sets are 23.25 and 32.82 Mg/ha. The regional model is structured in accordance with previously described local models, and performs equivalently to these smaller scale models. We have demonstrated the effectiveness of lidar for developing cost-effective, robust regional AGB models for monitoring and planning adaptively at the landscape scale.
Zhao, Jinlong; Kang, Fengfeng; Wang, Luoxin; Yu, Xiaowen; Zhao, Weihong; Song, Xiaoshuai; Zhang, Yanlei; Chen, Feng; Sun, Yu; He, Tengfei; Han, Hairong
2014-01-01
Patterns of biomass and carbon (C) storage distribution across Chinese pine (Pinus tabulaeformis) natural secondary forests are poorly documented. The objectives of this study were to examine the biomass and C pools of the major ecosystem components in a replicated age sequence of P. tabulaeformis secondary forest stands in Northern China. Within each stand, biomass of above- and belowground tree, understory (shrub and herb), and forest floor were determined from plot-level investigation and destructive sampling. Allometric equations using the diameter at breast height (DBH) were developed to quantify plant biomass. C stocks in the tree and understory biomass, forest floor, and mineral soil (0-100 cm) were estimated by analyzing the C concentration of each component. The results showed that the tree biomass of P. tabulaeformis stands was ranged from 123.8 Mg·ha-1 for the young stand to 344.8 Mg·ha-1 for the mature stand. The understory biomass ranged from 1.8 Mg·ha-1 in the middle-aged stand to 3.5 Mg·ha-1 in the young stand. Forest floor biomass increased steady with stand age, ranging from 14.9 to 23.0 Mg·ha-1. The highest mean C concentration across the chronosequence was found in tree branch while the lowest mean C concentration was found in forest floor. The observed C stock of the aboveground tree, shrub, forest floor, and mineral soil increased with increasing stand age, whereas the herb C stock showed a decreasing trend with a sigmoid pattern. The C stock of forest ecosystem in young, middle-aged, immature, and mature stands were 178.1, 236.3, 297.7, and 359.8 Mg C ha-1, respectively, greater than those under similar aged P. tabulaeformis forests in China. These results are likely to be integrated into further forest management plans and generalized in other contexts to evaluate C stocks at the regional scale.
Directory of Open Access Journals (Sweden)
Jinlong Zhao
Full Text Available Patterns of biomass and carbon (C storage distribution across Chinese pine (Pinus tabulaeformis natural secondary forests are poorly documented. The objectives of this study were to examine the biomass and C pools of the major ecosystem components in a replicated age sequence of P. tabulaeformis secondary forest stands in Northern China. Within each stand, biomass of above- and belowground tree, understory (shrub and herb, and forest floor were determined from plot-level investigation and destructive sampling. Allometric equations using the diameter at breast height (DBH were developed to quantify plant biomass. C stocks in the tree and understory biomass, forest floor, and mineral soil (0-100 cm were estimated by analyzing the C concentration of each component. The results showed that the tree biomass of P. tabulaeformis stands was ranged from 123.8 Mg·ha-1 for the young stand to 344.8 Mg·ha-1 for the mature stand. The understory biomass ranged from 1.8 Mg·ha-1 in the middle-aged stand to 3.5 Mg·ha-1 in the young stand. Forest floor biomass increased steady with stand age, ranging from 14.9 to 23.0 Mg·ha-1. The highest mean C concentration across the chronosequence was found in tree branch while the lowest mean C concentration was found in forest floor. The observed C stock of the aboveground tree, shrub, forest floor, and mineral soil increased with increasing stand age, whereas the herb C stock showed a decreasing trend with a sigmoid pattern. The C stock of forest ecosystem in young, middle-aged, immature, and mature stands were 178.1, 236.3, 297.7, and 359.8 Mg C ha-1, respectively, greater than those under similar aged P. tabulaeformis forests in China. These results are likely to be integrated into further forest management plans and generalized in other contexts to evaluate C stocks at the regional scale.
Directory of Open Access Journals (Sweden)
Shem Kuyah
2016-02-01
Full Text Available The miombo woodland is the most extensive dry forest in the world, with the potential to store substantial amounts of biomass carbon. Efforts to obtain accurate estimates of carbon stocks in the miombo woodlands are limited by a general lack of biomass estimation models (BEMs. This study aimed to evaluate the accuracy of most commonly employed allometric models for estimating aboveground biomass (AGB in miombo woodlands, and to develop new models that enable more accurate estimation of biomass in the miombo woodlands. A generalizable mixed-species allometric model was developed from 88 trees belonging to 33 species ranging in diameter at breast height (DBH from 5 to 105 cm using Bayesian estimation. A power law model with DBH alone performed better than both a polynomial model with DBH and the square of DBH, and models including height and crown area as additional variables along with DBH. The accuracy of estimates from published models varied across different sites and trees of different diameter classes, and was lower than estimates from our model. The model developed in this study can be used to establish conservative carbon stocks required to determine avoided emissions in performance-based payment schemes, for example in afforestation and reforestation activities.
Combining Lidar and Synthetic Aperture Radar Data to Estimate Forest Biomass: Status and Prospects
Directory of Open Access Journals (Sweden)
Sanna Kaasalainen
2015-01-01
Full Text Available Research activities combining lidar and radar remote sensing have increased in recent years. The main focus in combining lidar-radar forest remote sensing has been on the retrieval of the aboveground biomass (AGB, which is a primary variable related to carbon cycle in land ecosystems, and has therefore been identified as an essential climate variable. In this review, we summarize the studies combining lidar and radar in estimating forest AGB. We discuss the complementary use of lidar and radar according to the relevance of the added value. The most promising prospects for combining lidar and radar data are in the use of lidar-derived ground elevations for improving large-area biomass estimates from radar, and in upscaling of lidar-based AGB data across large areas covered by spaceborne radar missions.
J.W. Raich; D.A. Clark; L. Schwendenmann; Tana Wood
2014-01-01
Young secondary forests and plantations in the moist tropics often have rapid rates of biomass accumulation and thus sequester large amounts of carbon. Here, we compare results from mature forest and nearby 15â20 year old tree plantations in lowland Costa Rica to evaluate differences in allocation of carbon to aboveground production and root systems. We found that the...
Carlos Alberto Silva; Andrew Thomas Hudak; Lee Alexander Vierling; Carine Klauberg; Mariano Garcia; Antonio Ferraz; Michael Keller; Jan Eitel; Sassan Saatchi
2017-01-01
Airborne lidar has become a well-suited technology for predicting and mapping many tropical forest attributes, including aboveground biomass (AGB). However, trade-offs exist between lidar pulse density and acquisition cost. The aim of this study was to evaluate the influence of lidar pulse density on AGB change predictions using airborne lidar and field plot data in a...
International Nuclear Information System (INIS)
Zewdie, Mulugeta; Olsson, Mats; Verwijst, Theo
2009-01-01
Eucalyptus plantations are extensively managed for wood production in the central highlands of Ethiopia. Nevertheless, little is known about their biomass (dry matter) production, partitioning and dynamics over time. Data from 10 different Eucalyptus globulus stands, with a plantation age ranging from 11 to 60 years and with a coppice-shoot age ranging from 1 to 9 years were collected and analyzed. Above-ground tree biomass of 7-10 sampled trees per stand was determined destructively. Dry weights of tree components (W c ; leaves, twigs, branches, stembark, and stemwood) and total above-ground biomass (W a ) were estimated as a function of diameter above stump (D), tree height (H) and a combination of these. The best fits were obtained, using combinations of D and H. When only one explanatory variable was used, D performed better than H. Total above-ground biomass was linearly related to coppice-shoot age. In contrast a negative relation was observed between the above-ground biomass production and total plantation age (number of cutting cycles). Total above-ground biomass increased from 11 t ha -1 at a stand age of 1 year to 153 t ha -1 at 9 years. The highest dry weight was allocated to stemwood and decreased in the following order: stemwood > leaves > stembark > twigs > branches. The equations developed in this study to estimate biomass components can be applied to other Eucalyptus plantations under the assumption that the populations being studied are similar with regard to density and tree size to those for which the relationships were developed
Energy Technology Data Exchange (ETDEWEB)
Zewdie, Mulugeta; Olsson, Mats; Verwijst, Theo [Swedish University of Agricultural Sciences, Department of Crop Production Ecology, P.O. Box 7043, 75007 Uppsala (Sweden)
2009-03-15
Eucalyptus plantations are extensively managed for wood production in the central highlands of Ethiopia. Nevertheless, little is known about their biomass (dry matter) production, partitioning and dynamics over time. Data from 10 different Eucalyptus globulus stands, with a plantation age ranging from 11 to 60 years and with a coppice-shoot age ranging from 1 to 9 years were collected and analyzed. Above-ground tree biomass of 7-10 sampled trees per stand was determined destructively. Dry weights of tree components (W{sub c}; leaves, twigs, branches, stembark, and stemwood) and total above-ground biomass (W{sub a}) were estimated as a function of diameter above stump (D), tree height (H) and a combination of these. The best fits were obtained, using combinations of D and H. When only one explanatory variable was used, D performed better than H. Total above-ground biomass was linearly related to coppice-shoot age. In contrast a negative relation was observed between the above-ground biomass production and total plantation age (number of cutting cycles). Total above-ground biomass increased from 11 t ha{sup -1} at a stand age of 1 year to 153 t ha{sup -1} at 9 years. The highest dry weight was allocated to stemwood and decreased in the following order: stemwood > leaves > stembark > twigs > branches. The equations developed in this study to estimate biomass components can be applied to other Eucalyptus plantations under the assumption that the populations being studied are similar with regard to density and tree size to those for which the relationships were developed. (author)
Austrheim, Gunnar; Speed, James David Mervyn; Martinsen, Vegard; Mulder, Jan; Mysterud, Atle
2014-01-01
Herbivores may increase or decrease aboveground plant productivity depending on factors such as herbivore density and habitat productivity. The grazing optimization hypothesis predicts a peak in plant production at intermediate herbivore densities, but has rarely been tested experimentally in an alpine field setting. In an experimental design with three densities of sheep (high, low, and no sheep), we harvested aboveground plant biomass in alpine grasslands prior to treatment and after five y...
Developing a Carbon Monitoring System For Pinyon-juniper Forests and Woodlands
Falkowski, M. J.; Hudak, A. T.; Fekety, P.; Filippelli, S.
2017-12-01
Pinyon-juniper (PJ) forests and woodlands are the third largest vegetation type in the United States. They cover over 40 million hectares across the western US, representing 40% of the total forest and woodland area in the Intermountain West. Although the density of carbon stored in these ecosystems is relatively low compared to other forest types, the vast area of short stature forests and woodlands (both nationally and globally) make them critical components of regional, national, and global carbon budgets. The overarching goal of this research is to prototype a carbon monitoring, reporting, and verification (MRV) system for characterizing total aboveground biomass stocks and flux across the PJ vegetation gradient in the western United States. We achieve this by combining in situ forest measurements and novel allometric equations with tree measurements derived from high resolution airborne imagery to map aboveground biomass across 500,000 km2 in the Western US. These high-resolution maps of aboveground biomass are then leveraged as training data to predict biomass flux through time from Landsat time-series data. The results from this research highlight the potential in mapping biomass stocks and flux in open forests and woodlands, and could be easily adopted into an MRV framework.
Necromass in forests of Madre de Dios, Peru: a comparison between terra firme and lowland forests
Directory of Open Access Journals (Sweden)
Alejandro Araujo-Murakami
2011-06-01
Full Text Available Stocks of dead wood or necromass represent an important portion of biomass and nutrients in tropical forests. The objectives of this study were: 1 to evaluate and compare the necromass of “terra firme” and lowlands forests, (2 to study the relationship between necromass, above-ground biomass and wood density, and (3 to estimate the necromass of the department of Madre de Dios, Peru. Stocks of necromass and above-ground biomass were estimated at three different locations using permanent plots and line intercept transects. The average volume of necromass for the three sites was 72.9 m3 ha-1 with an average weight varying between 24.8 and 30.7 Mg ha-1, depending on the estimations of dead wood density used for the calculations. Terra firme forests had significantly higher stocks of necromass than lowland forests. The amount of necromass was 11% of the total above-ground biomass in Madre de Dios forests. The total stock of carbon stored in dead wood for the entire department of Madre de Dios was estimated to be approximately 100 mega tonnes of carbon. This is ten times more than the annual fossil fuel emissions of Peru between 2000 and 2008. The substantial stocks of necromass emphasize the importance of these types of field studies, considering that this component of tropical forest carbon cannot be detected using other methods such as satellite remote sensing.
Long-term above-ground biomass production in a red oak-pecan agroforestry system
Agroforestry systems have widely been recognized for their potential to foster long-term carbon sequestration in woody perennials. This study aims to determine the above-ground biomass in a 16-year-old red oak (Quercus rubra) - pecan (Carya illinoinensis) silvopastoral planting (141 and 53 trees ha-...
Jimenez-Berni, Jose A; Deery, David M; Rozas-Larraondo, Pablo; Condon, Anthony Tony G; Rebetzke, Greg J; James, Richard A; Bovill, William D; Furbank, Robert T; Sirault, Xavier R R
2018-01-01
Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR ( r 2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association ( r 2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass ( r 2 = 0.93 and r 2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new
Annual Removal of Aboveground Plant Biomass Alters Soil Microbial Responses to Warming
Directory of Open Access Journals (Sweden)
Kai Xue
2016-09-01
Full Text Available Clipping (i.e., harvesting aboveground plant biomass is common in agriculture and for bioenergy production. However, microbial responses to clipping in the context of climate warming are poorly understood. We investigated the interactive effects of grassland warming and clipping on soil properties and plant and microbial communities, in particular, on microbial functional genes. Clipping alone did not change the plant biomass production, but warming and clipping combined increased the C4 peak biomass by 47% and belowground net primary production by 110%. Clipping alone and in combination with warming decreased the soil carbon input from litter by 81% and 75%, respectively. With less carbon input, the abundances of genes involved in degrading relatively recalcitrant carbon increased by 38% to 137% in response to either clipping or the combined treatment, which could weaken long-term soil carbon stability and trigger positive feedback with respect to warming. Clipping alone also increased the abundance of genes for nitrogen fixation, mineralization, and denitrification by 32% to 39%. Such potentially stimulated nitrogen fixation could help compensate for the 20% decline in soil ammonium levels caused by clipping alone and could contribute to unchanged plant biomass levels. Moreover, clipping tended to interact antagonistically with warming, especially with respect to effects on nitrogen cycling genes, demonstrating that single-factor studies cannot predict multifactorial changes. These results revealed that clipping alone or in combination with warming altered soil and plant properties as well as the abundance and structure of soil microbial functional genes. Aboveground biomass removal for biofuel production needs to be reconsidered, as the long-term soil carbon stability may be weakened.
Castanho, A. D.; Zhang, K.; Coe, M. T.; Costa, M. H.; Moorcroft, P. R.
2012-12-01
Field observations from undisturbed old-growth Amazonian forest plots have recently reported on the temporal variation of many of the physical and chemical characteristics such as: physiological properties of leaves, above ground live biomass, above ground productivity, mortality and turnover rates. However, although this variation has been measured, it is still not well understood what mechanisms control the observed temporal variability. The observed changes in time are believed to be a result of a combination of increasing atmospheric CO2 concentration, climate variability, recovery from natural disturbance (drought, wind blow, flood), and increase of nutrient availability. The time and spatial variability of the fertilization effect of CO2 on above ground biomass will be explored in more detail in this work. A precise understanding of the CO2 effect on the vegetation is essential for an accurate prediction of the future response of the forest to climate change. To address this issue we simultaneously explore the effects of climate variability, historical CO2 and land-use change on total biomass and productivity using two different Dynamic Global Vegetation Models (DGVM). We use the Integrated Biosphere Simulator (IBIS) and the Ecosystem Demography Model 2.1 (ED2.1). Using land use changes database from 1700 - 2008 we reconstruct the total carbon balance in the Amazonian forest in space and time and present how the models predict the forest as carbon sink or source and explore why the model and field data diverge from each other. From 1970 to 2005 the Amazonian forest has been exposed to an increase of approximately 50 ppm in the atmospheric CO2 concentration. Preliminary analyses with the IBIS and ED2.1 dynamic vegetation model shows the CO2 fertilization effect could account for an increase in above ground biomass of 0.03 and 0.04 kg-C/m2/yr on average for the Amazon basin, respectively. The annual biomass change varies temporally and spatially from about 0
Directory of Open Access Journals (Sweden)
Benedicto Vargas-Larreta
2017-07-01
Full Text Available This paper presents new equations for estimating above-ground biomass (AGB and biomass components of seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. The generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. In addition, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The results of cross-validation indicated that the fitted equations accounted for on average 91%, 82%, 83% and 76% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of total height (h or diameter at breast height2 × total height (d2h as a predictor in the d-only based equations systems slightly improved estimates for stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The predictive power of the proposed equations is higher than that of existing models for the study area. The fitted equations were used to estimate stand level AGB stocks from data on growing stock in 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were used to map the AGB and carbon distributions in the study area, for which mean values of respectively 129.84 Mg ha−1 and 63.80 Mg ha−1 were obtained.
Owers, Christopher J.; Rogers, Kerrylee; Woodroffe, Colin D.
2018-05-01
Above-ground biomass represents a small yet significant contributor to carbon storage in coastal wetlands. Despite this, above-ground biomass is often poorly quantified, particularly in areas where vegetation structure is complex. Traditional methods for providing accurate estimates involve harvesting vegetation to develop mangrove allometric equations and quantify saltmarsh biomass in quadrats. However broad scale application of these methods may not capture structural variability in vegetation resulting in a loss of detail and estimates with considerable uncertainty. Terrestrial laser scanning (TLS) collects high resolution three-dimensional point clouds capable of providing detailed structural morphology of vegetation. This study demonstrates that TLS is a suitable non-destructive method for estimating biomass of structurally complex coastal wetland vegetation. We compare volumetric models, 3-D surface reconstruction and rasterised volume, and point cloud elevation histogram modelling techniques to estimate biomass. Our results show that current volumetric modelling approaches for estimating TLS-derived biomass are comparable to traditional mangrove allometrics and saltmarsh harvesting. However, volumetric modelling approaches oversimplify vegetation structure by under-utilising the large amount of structural information provided by the point cloud. The point cloud elevation histogram model presented in this study, as an alternative to volumetric modelling, utilises all of the information within the point cloud, as opposed to sub-sampling based on specific criteria. This method is simple but highly effective for both mangrove (r2 = 0.95) and saltmarsh (r2 > 0.92) vegetation. Our results provide evidence that application of TLS in coastal wetlands is an effective non-destructive method to accurately quantify biomass for structurally complex vegetation.
Importance of tree basic density in biomass estimation and associated uncertainties
DEFF Research Database (Denmark)
Njana, Marco Andrew; Meilby, Henrik; Eid, Tron
2016-01-01
Key message Aboveground and belowground tree basic densities varied between and within the three mangrove species. If appropriately determined and applied, basic density may be useful in estimation of tree biomass. Predictive accuracy of the common (i.e. multi-species) models including aboveground...... of sustainable forest management, conservation and enhancement of carbon stocks (REDD+) initiatives offer an opportunity for sustainable management of forests including mangroves. In carbon accounting for REDD+, it is required that carbon estimates prepared for monitoring reporting and verification schemes...... and examine uncertainties in estimation of tree biomass using indirect methods. Methods This study focused on three dominant mangrove species (Avicennia marina (Forssk.) Vierh, Sonneratia alba J. Smith and Rhizophora mucronata Lam.) in Tanzania. A total of 120 trees were destructively sampled for aboveground...
D'Amato, Anthony W; Orwig, David A; Foster, David R; Barker Plotkin, Audrey; Schoonmaker, Peter K; Wagner, Maggie R
2017-03-01
The development of old-growth forests in northeastern North America has largely been within the context of gap-scale disturbances given the rarity of stand-replacing disturbances. Using the 10-ha old-growth Harvard Tract and its associated 90-year history of measurements, including detailed surveys in 1989 and 2009, we document the long-term structural and biomass development of an old-growth Tsuga canadensis-Pinus strobus forest in southern New Hampshire, USA following a stand-replacing hurricane in 1938. Measurements of aboveground biomass pools were integrated with data from second- and old-growth T. canadensis forests to evaluate long-term patterns in biomass development following this disturbance. Ecosystem structure across the Tract prior to the hurricane exhibited a high degree of spatial heterogeneity with the greatest levels of live tree basal area (70-129 m 2 /ha) on upper west-facing slopes where P. strobus was dominant and intermixed with T. canadensis. Live-tree biomass estimates for these stratified mixtures ranged from 159 to 503 Mg/ha at the localized, plot scale (100 m 2 ) and averaged 367 Mg/ha across these portions of the landscape approaching the upper bounds for eastern forests. Live-tree biomass 71 years after the hurricane is more uniform and lower in magnitude, with T. canadensis currently the dominant overstory tree species throughout much of the landscape. Despite only one living P. strobus stem in the 2009 plots (and fewer than five stems known across the entire 10-ha area), the detrital legacy of this species is pronounced with localized accumulations of coarse woody debris exceeding 237.7-404.2 m 3 /ha where this species once dominated the canopy. These patterns underscore the great sizes P. strobus attained in pre-European landscapes and its great decay resistance relative to its forest associates. Total aboveground biomass pools in this 71-year-old forest (255 Mg/ha) are comparable to those in modern old-growth ecosystems
Evaluation of sampling strategies to estimate crown biomass
Krishna P Poudel; Hailemariam Temesgen; Andrew N Gray
2015-01-01
Depending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire...
Zuo, Shu-di; Ren, Yin; Weng, Xian; Ding, Hong-feng; Luo, Yun-jian
2015-02-01
Biomass allometric equation (BAE) considered as a simple and reliable method in the estimation of forest biomass and carbon was used widely. In China, numerous studies focused on the BAEs for coniferous forest and pure broadleaved forest, and generalized BAEs were frequently used to estimate the biomass and carbon of mixed broadleaved forest, although they could induce large uncertainty in the estimates. In this study, we developed the species-specific and generalized BAEs using biomass measurement for 9 common broadleaved trees (Castanopsis fargesii, C. lamontii, C. tibetana, Lithocarpus glaber, Sloanea sinensis, Daphniphyllum oldhami, Alniphyllum fortunei, Manglietia yuyuanensis, and Engelhardtia fenzlii) of subtropical evergreen broadleaved forest, and compared differences in species-specific and generalized BAEs. The results showed that D (diameter at breast height) was a better independent variable in estimating the biomass of branch, leaf, root, aboveground section and total tree than a combined variable (D2 H) of D and H (tree height) , but D2H was better than D in estimating stem biomass. R2 (coefficient of determination) values of BAEs for 6 species decreased when adding H as the second independent variable into D- only BAEs, where R2 value for S. sinensis decreased by 5.6%. Compared with generalized D- and D2H-based BAEs, standard errors of estimate (SEE) of BAEs for 8 tree species decreased, and similar decreasing trend was observed for different components, where SEEs of the branch decreased by 13.0% and 20.3%. Therefore, the biomass carbon storage and its dynamic estimates were influenced largely by tree species and model types. In order to improve the accuracy of the estimates of biomass and carbon, we should consider the differences in tree species and model types.
Puerto Rico Above Ground Biomass Map, 2000
U.S. Environmental Protection Agency — This image dataset details the U.S. Commonwealth of Puerto Rico above-ground forest biomass (AGB) (baseline 2000) developed by the United States (US) Environmental...
Schnell, Sebastian; Altrell, Dan; Ståhl, Göran; Kleinn, Christoph
2015-01-01
In contrast to forest trees, trees outside forests (TOF) often are not included in the national monitoring of tree resources. Consequently, data about this particular resource is rare, and available information is typically fragmented across the different institutions and stakeholders that deal with one or more of the various TOF types. Thus, even if information is available, it is difficult to aggregate data into overall national statistics. However, the National Forest Monitoring and Assessment (NFMA) programme of FAO offers a unique possibility to study TOF resources because TOF are integrated by default into the NFMA inventory design. We have analysed NFMA data from 11 countries across three continents. For six countries, we found that more than 10% of the national above-ground tree biomass was actually accumulated outside forests. The highest value (73%) was observed for Bangladesh (total forest cover 8.1%, average biomass per hectare in forest 33.4 t ha(-1)) and the lowest (3%) was observed for Zambia (total forest cover 63.9%, average biomass per hectare in forest 32 t ha(-1)). Average TOF biomass stocks were estimated to be smaller than 10 t ha(-1). However, given the large extent of non-forest areas, these stocks sum up to considerable quantities in many countries. There are good reasons to overcome sectoral boundaries and to extend national forest monitoring programmes on a more systematic basis that includes TOF. Such an approach, for example, would generate a more complete picture of the national tree biomass. In the context of climate change mitigation and adaptation, international climate mitigation programmes (e.g. Clean Development Mechanism and Reduced Emission from Deforestation and Degradation) focus on forest trees without considering the impact of TOF, a consideration this study finds crucial if accurate measurements of national tree biomass and carbon pools are required.
Li, Aihua; Dhakal, Shital; Glenn, Nancy F.; Spaete, Luke P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan
2017-01-01
Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure
Vegetation in karst terrain of southwestern China allocates more biomass to roots
Ni, J.; Luo, D. H.; Xia, J.; Zhang, Z. H.; Hu, G.
2015-07-01
In mountainous areas of southwestern China, especially Guizhou province, continuous, broadly distributed karst landscapes with harsh and fragile habitats often lead to land degradation. Research indicates that vegetation located in karst terrains has low aboveground biomass and land degradation that reduces vegetation biomass, but belowground biomass measurements are rarely reported. Using the soil pit method, we investigated the root biomass of karst vegetation in five land cover types: grassland, grass-scrub tussock, thorn-scrub shrubland, scrub-tree forest, and mixed evergreen and deciduous forest in Maolan, southern Guizhou province, growing in two different soil-rich and rock-dominated habitats. The results show that roots in karst vegetation, especially the coarse roots, and roots in rocky habitats are mostly distributed in the topsoil layers (89 % on the surface up to 20 cm depth). The total root biomass in all habitats of all vegetation degradation periods is 18.77 Mg ha-1, in which roots in rocky habitat have higher biomass than in earthy habitat, and coarse root biomass is larger than medium and fine root biomass. The root biomass of mixed evergreen and deciduous forest in karst habitat (35.83 Mg ha-1) is not greater than that of most typical, non-karst evergreen broad-leaved forests in subtropical regions of China, but the ratio of root to aboveground biomass in karst forest (0.37) is significantly greater than the mean ratio (0.26 ± 0.07) of subtropical evergreen forests. Vegetation restoration in degraded karst terrain will significantly increase the belowground carbon stock, forming a potential regional carbon sink.
Developing a generalized allometric equation for aboveground biomass estimation
Xu, Q.; Balamuta, J. J.; Greenberg, J. A.; Li, B.; Man, A.; Xu, Z.
2015-12-01
A key potential uncertainty in estimating carbon stocks across multiple scales stems from the use of empirically calibrated allometric equations, which estimate aboveground biomass (AGB) from plant characteristics such as diameter at breast height (DBH) and/or height (H). The equations themselves contain significant and, at times, poorly characterized errors. Species-specific equations may be missing. Plant responses to their local biophysical environment may lead to spatially varying allometric relationships. The structural predictor may be difficult or impossible to measure accurately, particularly when derived from remote sensing data. All of these issues may lead to significant and spatially varying uncertainties in the estimation of AGB that are unexplored in the literature. We sought to quantify the errors in predicting AGB at the tree and plot level for vegetation plots in California. To accomplish this, we derived a generalized allometric equation (GAE) which we used to model the AGB on a full set of tree information such as DBH, H, taxonomy, and biophysical environment. The GAE was derived using published allometric equations in the GlobAllomeTree database. The equations were sparse in details about the error since authors provide the coefficient of determination (R2) and the sample size. A more realistic simulation of tree AGB should also contain the noise that was not captured by the allometric equation. We derived an empirically corrected variance estimate for the amount of noise to represent the errors in the real biomass. Also, we accounted for the hierarchical relationship between different species by treating each taxonomic level as a covariate nested within a higher taxonomic level (e.g. species contribution of each different covariate in estimating the AGB of trees. Lastly, we applied the GAE to an existing vegetation plot database - Forest Inventory and Analysis database - to derive per-tree and per-plot AGB estimations, their errors, and how
Paul, Keryn I; Roxburgh, Stephen H; Chave, Jerome; England, Jacqueline R; Zerihun, Ayalsew; Specht, Alison; Lewis, Tom; Bennett, Lauren T; Baker, Thomas G; Adams, Mark A; Huxtable, Dan; Montagu, Kelvin D; Falster, Daniel S; Feller, Mike; Sochacki, Stan; Ritson, Peter; Bastin, Gary; Bartle, John; Wildy, Dan; Hobbs, Trevor; Larmour, John; Waterworth, Rob; Stewart, Hugh T L; Jonson, Justin; Forrester, David I; Applegate, Grahame; Mendham, Daniel; Bradford, Matt; O'Grady, Anthony; Green, Daryl; Sudmeyer, Rob; Rance, Stan J; Turner, John; Barton, Craig; Wenk, Elizabeth H; Grove, Tim; Attiwill, Peter M; Pinkard, Elizabeth; Butler, Don; Brooksbank, Kim; Spencer, Beren; Snowdon, Peter; O'Brien, Nick; Battaglia, Michael; Cameron, David M; Hamilton, Steve; McAuthur, Geoff; Sinclair, Jenny
2016-06-01
Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species
Qi Chen; Dengsheng Lu; Michael Keller; Maiza dos-Santos; Edson Bolfe; Yunyun Feng; Changwei Wang
2015-01-01
Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems...
Colgan, M.; Asner, G. P.; Swemmer, A. M.
2011-12-01
The accurate estimation of carbon stored in a tree is essential to accounting for the carbon emissions due to deforestation and degradation. Airborne LiDAR (Light Detection and Ranging) has been successful in estimating aboveground carbon density (ACD) by correlating airborne metrics, such as canopy height, to field-estimated biomass. This latter step is reliant on field allometry which is applied to forest inventory quantities, such as stem diameter and height, to predict the biomass of a given tree stem. Constructing such allometry is expensive, time consuming, and requires destructive sampling. Consequently, the sample sizes used to construct such allometry are often small, and the largest tree sampled is often much smaller than the largest in the forest population. The uncertainty resulting from these sampling errors can lead to severe biases when the allometry is applied to stems larger than those harvested to construct the allometry, which is then subsequently propagated to airborne ACD estimates. The Kruger National Park (KNP) mission of maintaining biodiversity coincides with preserving ecosystem carbon stocks. However, one hurdle to accurately quantifying carbon density in savannas is that small stems are typically harvested to construct woody biomass allometry, yet they are not representative of Kruger's distribution of biomass. Consequently, these equations inadequately capture large tree variation in sapwood/hardwood composition, root/shoot/leaf allocation, branch fall, and stem rot. This study eliminates the "middleman" of field allometry by directly measuring, or harvesting, tree biomass within the extent of airborne LiDAR. This enables comparisons of field and airborne ACD estimates, and also enables creation of new airborne algorithms to estimate biomass at the scale of individual trees. A field campaign was conducted at Pompey Silica Mine 5km outside Kruger National Park, South Africa, in Mar-Aug 2010 to harvest and weigh tree mass. Since
International Nuclear Information System (INIS)
Abino, A.C.; Lee, Y.J.; Castillo, J.A.A
2014-01-01
Philippines claims international recognition for its mangrove-rich ecosystem which play significant functions from the viewpoint of ecosystem services and climate change mitigation. In this study, we assessed the species diversity of the natural mangrove forest of Bahile, Puerto Princesa City, Palawan and evaluated its potential to sequester and store carbon. Sixteen plots with a size of 10 m * 10 m were established using quadrat sampling technique to identify, record, and measure the trees. Diversity index and allometric equations were utilized to determine species diversity, and biomass and carbon stocks. Sediment samples in undisturbed portions using a 30 cm high and 5 cm diameter corer were collected in all plots to determine near-surface sediment carbon. The diversity index (H = 0.9918) was very low having a total of five true mangrove species identified dominated by Rhizophora apiculata Bl. with an importance value index of 148.1%. Among the stands, 74% of the total biomass was attributed to the above-ground (561.2 t ha-1) while 26% was credited to the roots (196.5 t ha-1). The total carbon sequestered and stored in the above-ground and root biomass were 263.8 t C ha-1 (50%) and 92.3 t C ha-1 (17%), respectively. Sediments contained 33% (173.75 t C ha-1) of the mangrove C-stocks. Stored carbon was equivalent to 1944.5 t CO/sub 2/ ha-1. These values suggest that Bahile natural mangrove forest has a potential to sequester and store substantial amounts of atmospheric carbon, hence the need for sustainable management and protection of this important coastal ecosystem. (author)
Li, T.; Wang, Z.; Peng, J.
2018-04-01
Aboveground biomass (AGB) estimation is critical for quantifying carbon stocks and essential for evaluating carbon cycle. In recent years, airborne LiDAR shows its great ability for highly-precision AGB estimation. Most of the researches estimate AGB by the feature metrics extracted from the canopy height distribution of the point cloud which calculated based on precise digital terrain model (DTM). However, if forest canopy density is high, the probability of the LiDAR signal penetrating the canopy is lower, resulting in ground points is not enough to establish DTM. Then the distribution of forest canopy height is imprecise and some critical feature metrics which have a strong correlation with biomass such as percentiles, maximums, means and standard deviations of canopy point cloud can hardly be extracted correctly. In order to address this issue, we propose a strategy of first reconstructing LiDAR feature metrics through Auto-Encoder neural network and then using the reconstructed feature metrics to estimate AGB. To assess the prediction ability of the reconstructed feature metrics, both original and reconstructed feature metrics were regressed against field-observed AGB using the multiple stepwise regression (MS) and the partial least squares regression (PLS) respectively. The results showed that the estimation model using reconstructed feature metrics improved R2 by 5.44 %, 18.09 %, decreased RMSE value by 10.06 %, 22.13 % and reduced RMSEcv by 10.00 %, 21.70 % for AGB, respectively. Therefore, reconstructing LiDAR point feature metrics has potential for addressing AGB estimation challenge in dense canopy area.
Kilbride, J. B.; Fraver, S.; Ayrey, E.; Weiskittel, A.; Braaten, J.; Hughes, J. M.; Hayes, D. J.
2017-12-01
Forests within the New England states and Canadian Maritime provinces, here described as the Acadian New England (ANE) forests, have undergone substantial disturbances due to insect, fire, and anthropogenic factors. Through repeated satellite observations captures by USGS's Landsat program, 45 years of disturbance information can be incorporated into modeling efforts to better understand the spatial and temporal trends in forest above ground biomass (AGB). Using Google's Earth Engine, annual mosaics were developed for the ANE study area and then disturbance and recovery metrics were developed using the temporal segmentation algorithm VeRDET. Normalization procedures were developed to incorporate the Landsat Multispectral Scanner (MSS, 1972 - 1985) data alongside the modern era of Landsat Thematic Mapper (TM, 1984-2013), Enhanced Thematic Mapper plus (ETM+, 1999 - present), and Operational Land Imager (OLI, 2013- present) data products. This has enabled the creation of a dataset with an unprecedented spatial and temporal view of forest landscape change. Model training was performed using was the Forest Inventory Analysis (FIA) and New Brunswick Permanent Sample Plot data datasets. Modeling was performed using parametric techniques such as mixed effects models and non-parametric techniques such as k-NN imputation and generalized boosted regression. We compare the biomass estimate and model accuracy to other inventory and modeling studies produced within this study area. The spatial and temporal patterns of stock changes are analyzed against resource policy, land ownership changes, and forest management.
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Sebastian Doetterl
Full Text Available African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors.Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock were only half compared to an area with lower tree height (= smaller aboveground carbon stock. This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system.We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget.
Doetterl, Sebastian; Kearsley, Elizabeth; Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal
2015-01-01
African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget.
Low Tree-Growth Elasticity of Forest Biomass Indicated by an Individual-Based Model
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Robbie A. Hember
2018-01-01
Full Text Available Environmental conditions and silviculture fundamentally alter the metabolism of individual trees and, therefore, need to be studied at that scale. However, changes in forest biomass density (Mg C ha−1 may be decoupled from changes in growth (kg C year−1 when the latter also accelerates the life cycle of trees and strains access to light, nutrients, and water. In this study, we refer to an individual-based model of forest biomass dynamics to constrain the magnitude of system feedbacks associated with ontogeny and competition and estimate the scaling relationship between changes in tree growth and forest biomass density. The model was driven by fitted equations of annual aboveground biomass growth (Gag, probability of recruitment (Pr, and probability of mortality (Pm parameterized against field observations of black spruce (Picea mariana (Mill. BSP, interior Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn. Franco, and western hemlock (Tsuga heterophylla (Raf. Sarg.. A hypothetical positive step-change in mean tree growth was imposed half way through the simulations and landscape-scale responses were then evaluated by comparing pre- and post-stimulus periods. Imposing a 100% increase in tree growth above calibrated predictions (i.e., contemporary rates only translated into 36% to 41% increases in forest biomass density. This corresponded with a tree-growth elasticity of forest biomass (εG,SB ranging from 0.33 to 0.55. The inelastic nature of stand biomass density was attributed to the dependence of mortality on intensity of competition and tree size, which decreased stand density by 353 to 495 trees ha−1, and decreased biomass residence time by 10 to 23 years. Values of εG,SB depended on the magnitude of the stimulus. For example, a retrospective scenario in which tree growth increased from 50% below contemporary rates up to contemporary rates indicated values of εG,SB ranging from 0.66 to 0.75. We conclude that: (1 effects of
Theme E: Forest Biomass and Bioenergy
DEFF Research Database (Denmark)
Bentsen, Niclas Scott; Stupak, Inge; Smith, C
2014-01-01
Several countries in the world have policies for increased use of biomass for energy and biomaterials. It is likely that such policies will lead to increased international demand for wood and increased pressure on the world’s forests. Concerns for forest sustainability have been expressed, especi...... challenges in the different regions for consideration by institutions developing energy biomass sourcing polices and biomass sustainability criteria in the public and private sector......., especially in the EU and its biomass importing countries. As countries and companies search worldwide for new biomass sourcing areas, there is a need to review and compare the biomass potentials in different regions and the associated forest sustainability challenges. We reviewed the literature to assess...
DEFF Research Database (Denmark)
Blue, Jarrod D.; Souza, Lara; Classen, Aimée T.
2011-01-01
in an old-field ecosystem. In 2004, we established 36 experimental plots in which we manipulated soil nitrogen (N) availability and insect abundance in a completely randomized plot design. In 2009, after 6 years of treatments, we measured aboveground biomass and assessed root production at peak growth...... not be limiting primary production in this ecosystem. Insects reduced the aboveground biomass of subdominant plant species and decreased coarse root production. We found no statistical interactions between N availability and insect herbivory for any response variable. Overall, the results of 6 years of nutrient...
Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment
S. C. Stark; V. Leitold; J. L. Wu; M. O. Hunter; C. V. de Castilho; F. R. C. Costa; S. M. McMahon; G. G. Parker; M. Takako Shimabukuro; M. A. Lefsky; M. Keller; L. F. Alves; J. Schietti; Y. E. Shimabukuro; D. O. Brandao; T. K. Woodcock; N. Higuchi; P. B de Camargo; R. C. de Oliveira; S. R. Saleska
2012-01-01
Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) â remotely estimated from LiDAR â control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth...
Energy Technology Data Exchange (ETDEWEB)
Suntana, Asep S. [Forest Systems and Bio-Energy Program, College of Forest Resources, University of Washington, Box 352100, Seattle, WA 98195-2100 (United States); Indonesian Ecolabeling Institute/Lembaga Ekolabel Indonesia (LEI), Taman Bogor Baru Blok BIV No. 12, Bogor 16152 (Indonesia); Vogt, Kristiina A. [Forest Systems and Bio-Energy Program, College of Forest Resources, University of Washington, Box 352100, Seattle, WA 98195-2100 (United States); Interforest LLC, Holderness, NH 03245 (United States); Renewol LLC, 63260 Overtree Road, Bend, OR 97701 (United States); Turnblom, Eric C. [Forest Biometrics Program, College of Forest Resources, University of Washington, Box 352100, WA 98195-2100 (United States); Upadhye, Ravi [ARU Associates, Pleasanton, CA 94566 (United States)
2009-11-15
Since Indonesia has significant land area in different forest types that could be used to produce biofuels, the potential to sustainably collect and convert forest materials to methanol for use in energy production was examined. Using the annually available aboveground forest biomass, from 40 to 168 billion l of bio-methanol could be produced for use as a transportation fuel and/or to supply fuel cells to produce electricity. When a lower forest biomass availability estimate was used to determine how much electricity (methanol fed into fuel cells) could be produced in Indonesia, more than 10 million households or about 12,000 villages (20% of the total rural villages in Indonesia) would be supplied annually with electricity. Collecting forest biomass at the higher end of the estimated available biomass and converting it to methanol to supply fuel cells could provide electricity to more than 42 million households annually. This would be approximately 52,000 villages, or 86% of the total rural villages in Indonesian. When electricity is produced with bio-methanol/fuel cells, it could potentially supply from half to all of the current electricity consumed in Indonesia. By generating electricity using bio-methanol/fuel cells instead of from fossil fuels, from 9 to 38% of the total carbon currently emitted each year in Indonesia could be avoided. In contrast, substituting this same amount of bio-methanol for gasoline could provide all of the annual gasoline needs of Indonesia and contribute towards reducing their carbon emissions by about 8-35%. (author)
Forest structure in low-diversity tropical forests: a study of Hawaiian wet and dry forests.
Ostertag, Rebecca; Inman-Narahari, Faith; Cordell, Susan; Giardina, Christian P; Sack, Lawren
2014-01-01
The potential influence of diversity on ecosystem structure and function remains a topic of significant debate, especially for tropical forests where diversity can range widely. We used Center for Tropical Forest Science (CTFS) methodology to establish forest dynamics plots in montane wet forest and lowland dry forest on Hawai'i Island. We compared the species diversity, tree density, basal area, biomass, and size class distributions between the two forest types. We then examined these variables across tropical forests within the CTFS network. Consistent with other island forests, the Hawai'i forests were characterized by low species richness and very high relative dominance. The two Hawai'i forests were floristically distinct, yet similar in species richness (15 vs. 21 species) and stem density (3078 vs. 3486/ha). While these forests were selected for their low invasive species cover relative to surrounding forests, both forests averaged 5->50% invasive species cover; ongoing removal will be necessary to reduce or prevent competitive impacts, especially from woody species. The montane wet forest had much larger trees, resulting in eightfold higher basal area and above-ground biomass. Across the CTFS network, the Hawaiian montane wet forest was similar to other tropical forests with respect to diameter distributions, density, and aboveground biomass, while the Hawai'i lowland dry forest was similar in density to tropical forests with much higher diversity. These findings suggest that forest structural variables can be similar across tropical forests independently of species richness. The inclusion of low-diversity Pacific Island forests in the CTFS network provides an ∼80-fold range in species richness (15-1182 species), six-fold variation in mean annual rainfall (835-5272 mm yr(-1)) and 1.8-fold variation in mean annual temperature (16.0-28.4°C). Thus, the Hawaiian forest plots expand the global forest plot network to enable testing of ecological theory for
Forest structure in low-diversity tropical forests: a study of Hawaiian wet and dry forests.
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Rebecca Ostertag
Full Text Available The potential influence of diversity on ecosystem structure and function remains a topic of significant debate, especially for tropical forests where diversity can range widely. We used Center for Tropical Forest Science (CTFS methodology to establish forest dynamics plots in montane wet forest and lowland dry forest on Hawai'i Island. We compared the species diversity, tree density, basal area, biomass, and size class distributions between the two forest types. We then examined these variables across tropical forests within the CTFS network. Consistent with other island forests, the Hawai'i forests were characterized by low species richness and very high relative dominance. The two Hawai'i forests were floristically distinct, yet similar in species richness (15 vs. 21 species and stem density (3078 vs. 3486/ha. While these forests were selected for their low invasive species cover relative to surrounding forests, both forests averaged 5->50% invasive species cover; ongoing removal will be necessary to reduce or prevent competitive impacts, especially from woody species. The montane wet forest had much larger trees, resulting in eightfold higher basal area and above-ground biomass. Across the CTFS network, the Hawaiian montane wet forest was similar to other tropical forests with respect to diameter distributions, density, and aboveground biomass, while the Hawai'i lowland dry forest was similar in density to tropical forests with much higher diversity. These findings suggest that forest structural variables can be similar across tropical forests independently of species richness. The inclusion of low-diversity Pacific Island forests in the CTFS network provides an ∼80-fold range in species richness (15-1182 species, six-fold variation in mean annual rainfall (835-5272 mm yr(-1 and 1.8-fold variation in mean annual temperature (16.0-28.4°C. Thus, the Hawaiian forest plots expand the global forest plot network to enable testing of ecological
Litterfall in the hardwood forest of a minor alluvial-floodplain
Calvin E. Meier; John A. Stanturf; Emile S. Gardiner
2006-01-01
within mature deciduous forests, annual development of foliar biomass is a major component of aboveground net primary production and nutrient demand. As litterfall, this same foliage becomes a dominant annual transfer of biomass and nutrients to the detritus pathway. We report litterfall transfers of a mature bottomland hardwood forest in a minor alluvial-floodplain...
Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik
2015-12-01
Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.
Mapping Forest Biomass Using Remote Sensing and National Forest Inventory in China
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Ling Du
2014-06-01
Full Text Available Quantifying the spatial pattern of large-scale forest biomass can provide a general picture of the carbon stocks within a region and is of great scientific and political importance. The combination of the advantages of remote sensing data and field survey data can reduce uncertainty as well as demonstrate the spatial distribution of forest biomass. In this study, the seventh national forest inventory statistics (for the period 2004–2008 and the spatially explicit MODIS Land Cover Type product (MCD12C1 were used together to quantitatively estimate the spatially-explicit distribution of forest biomass in China (with a resolution of 0.05°, ~5600 m. Our study demonstrated that the calibrated forest cover proportion maps allow proportionate downscaling of regional forest biomass statistics to forest cover pixels to produce a relatively fine-resolution biomass map. The total stock of forest biomass in China was 11.9 Pg with an average of 76.3 Mg ha−1 during the study period; the high values were located in mountain ranges in northeast, southwest and southeast China and were strongly correlated with forest age and forest density.
Lou, Yanjing; Pan, Yanwen; Gao, Chuanyu; Jiang, Ming; Lu, Xianguo; Xu, Y Jun
2016-01-01
Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region.
Wisconsin's forest resources in 2004
Charles H. Perry
2006-01-01
Results of the 2000-2004 annual inventory of Wisconsin show about 16.0 million acres of forest land, more than 22.1 billion cubic feet of live volume on forest land, and nearly 593 million dry tons of all live aboveground tree biomass on timberland. Populations of jack pine budworm are increasing, and it remains a significant pest in Wisconsin forests. A complete...
Xu, Bing; Guo, ZhaoDi; Piao, ShiLong; Fang, JingYun
2010-07-01
China's forests are characterized by young forest age, low carbon density and a large area of planted forests, and thus have high potential to act as carbon sinks in the future. Using China's national forest inventory data during 1994-1998 and 1999-2003, and direct field measurements, we investigated the relationships between forest biomass density and forest age for 36 major forest types. Statistical approaches and the predicted future forest area from the national forestry development plan were applied to estimate the potential of forest biomass carbon storage in China during 2000-2050. Under an assumption of continuous natural forest growth, China's existing forest biomass carbon (C) stock would increase from 5.86 Pg C (1 Pg=10(15) g) in 1999-2003 to 10.23 Pg C in 2050, resulting in a total increase of 4.37 Pg C. Newly planted forests through afforestation and reforestation will sequestrate an additional 2.86 Pg C in biomass. Overall, China's forests will potentially act as a carbon sink for 7.23 Pg C during the period 2000-2050, with an average carbon sink of 0.14 Pg C yr(-1). This suggests that China's forests will be a significant carbon sink in the next 50 years.
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Qiang Wang
Full Text Available Hydrological alternation can dramatically influence riparian environments and shape riparian vegetation zonation. However, it was difficult to predict the status in the drawdown area of the Three Gorges Reservoir (TGR, because the hydrological regime created by the dam involves both short periods of summer flooding and long-term winter impoundment for half a year. In order to examine the effects of hydrological alternation on plant diversity and biomass in the drawdown area of TGR, twelve sites distributed along the length of the drawdown area of TGR were chosen to explore the lateral pattern of plant diversity and above-ground biomass at the ends of growing seasons in 2009 and 2010. We recorded 175 vascular plant species in 2009 and 127 in 2010, indicating that a significant loss of vascular flora in the drawdown area of TGR resulted from the new hydrological regimes. Cynodon dactylon and Cyperus rotundus had high tolerance to short periods of summer flooding and long-term winter flooding. Almost half of the remnant species were annuals. Species richness, Shannon-Wiener Index and above-ground biomass of vegetation exhibited an increasing pattern along the elevation gradient, being greater at higher elevations subjected to lower submergence stress. Plant diversity, above-ground biomass and species distribution were significantly influenced by the duration of submergence relative to elevation in both summer and previous winter. Several million tonnes of vegetation would be accumulated on the drawdown area of TGR in every summer and some adverse environmental problems may be introduced when it was submerged in winter. We conclude that vascular flora biodiversity in the drawdown area of TGR has dramatically declined after the impoundment to full capacity. The new hydrological condition, characterized by long-term winter flooding and short periods of summer flooding, determined vegetation biodiversity and above-ground biomass patterns along the
Lidar remote sensing of above-ground biomass in three biomes.
Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas. Gower
2002-01-01
Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...
Directory of Open Access Journals (Sweden)
Bosco Kidake Kisambo
2016-12-01
Full Text Available Leaf Area Index (LAI dynamics and aboveground biomass of a semi-arid grassland region in Southern Ethiopia were determined over a long rain season. The vegetation was categorized into four distinct vegetation types namely Grassland (G, Tree-Grassland (TG, Bushed-Grassland (BG and Bush-Tree grassland (BT. LAI was measured using a Plant Canopy Analyzer (LAI2000. Biomass dynamics of litter and herbaceous components were determined through clipping while the above ground biomass of trees and shrubs were estimated using species-specific allometric equations from literature. LAI showed a seasonal increase over the season with the maximum recorded in the BG vegetation (2.52. Total aboveground biomass for the different vegetation types ranged from 0.61 ton C/ha in areas where trees were non-existent to 8.80 ± 3.81ton C/ha in the Tree-Grassland vegetation in the study site. A correlation of LAI and AGB yielded a positive relationship with an R2 value of 0.55. The results demonstrate the importance of tropical semi-arid grasslands as carbon sinks hence their potential in mitigation of climate change.
Changes in forest biomass and linkage to climate and forest disturbances over Northeastern China.
Zhang, Yuzhen; Liang, Shunlin
2014-08-01
The forests of northeastern China store nearly half of the country's total biomass carbon stocks. In this study, we investigated the changes in forest biomass by using satellite observations and found that a significant increase in forest biomass took place between 2001 and 2010. To determine the possible reasons for this change, several statistical methods were used to analyze the correlations between forest biomass dynamics and forest disturbances (i.e. fires, insect damage, logging, and afforestation and reforestation), climatic factors, and forest development. Results showed that forest development was the most important contributor to the increasing trend of forest biomass from 2001 to 2010, and climate controls were the secondary important factor. Among the four types of forest disturbance considered in this study, forest recovery from fires, and afforestation and reforestation during the past few decades played an important role in short-term biomass dynamics. This study provided observational evidence and valuable information for the relationships between forest biomass and climate as well as forest disturbances. © 2014 John Wiley & Sons Ltd.
Kotowska, Martyna M; Leuschner, Christoph; Triadiati, Triadiati; Meriem, Selis; Hertel, Dietrich
2015-10-01
Natural forests in South-East Asia have been extensively converted into other land-use systems in the past decades and still show high deforestation rates. Historically, lowland forests have been converted into rubber forests, but more recently, the dominant conversion is into oil palm plantations. While it is expected that the large-scale conversion has strong effects on the carbon cycle, detailed studies quantifying carbon pools and total net primary production (NPPtotal ) in above- and belowground tree biomass in land-use systems replacing rainforest (incl. oil palm plantations) are rare so far. We measured above- and belowground carbon pools in tree biomass together with NPPtotal in natural old-growth forests, 'jungle rubber' agroforests under natural tree cover, and rubber and oil palm monocultures in Sumatra. In total, 32 stands (eight plot replicates per land-use system) were studied in two different regions. Total tree biomass in the natural forest (mean: 384 Mg ha(-1) ) was more than two times higher than in jungle rubber stands (147 Mg ha(-1) ) and >four times higher than in monoculture rubber and oil palm plantations (78 and 50 Mg ha(-1) ). NPPtotal was higher in the natural forest (24 Mg ha(-1) yr(-1) ) than in the rubber systems (20 and 15 Mg ha(-1) yr(-1) ), but was highest in the oil palm system (33 Mg ha(-1) yr(-1) ) due to very high fruit production (15-20 Mg ha(-1) yr(-1) ). NPPtotal was dominated in all systems by aboveground production, but belowground productivity was significantly higher in the natural forest and jungle rubber than in plantations. We conclude that conversion of natural lowland forest into different agricultural systems leads to a strong reduction not only in the biomass carbon pool (up to 166 Mg C ha(-1) ) but also in carbon sequestration as carbon residence time (i.e. biomass-C:NPP-C) was 3-10 times higher in the natural forest than in rubber and oil palm plantations. © 2015 John Wiley & Sons Ltd.
Mapping Russian forest biomass with data from satellites and forest inventories
International Nuclear Information System (INIS)
Houghton, R A; Butman, D; Bunn, A G; Krankina, O N; Schlesinger, P; Stone, T A
2007-01-01
The forests of Russia cover a larger area and hold more carbon than the forests of any other nation and thus have the potential for a major role in global warming. Despite a systematic inventory of these forests, however, estimates of total carbon stocks vary, and spatial variations in the stocks within large aggregated units of land are unknown, thus hampering measurement of sources and sinks of carbon. We mapped the distribution of living forest biomass for the year 2000 by developing a relationship between ground measurements of wood volume at 12 sites throughout the Russian Federation and data from the MODIS satellite bidirectional reflectance distribution function (BRDF) product (MOD43B4). Based on the results of regression-tree analyses, we used the MOD43B4 product to assign biomass values to individual 500 m x 500 m cells in areas identified as forest by two satellite-based maps of land cover. According to the analysis, the total living biomass varied between 46 and 67 Pg, largely because of different estimates of forest area. Although optical data are limited in distinguishing differences in biomass in closed canopy forests, the estimates of total living biomass obtained here varied more in response to different definitions of forest than to saturation of the optical sensing of biomass
Mapping Russian forest biomass with data from satellites and forest inventories
Energy Technology Data Exchange (ETDEWEB)
Houghton, R A [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States); Butman, D [Yale School of Forestry and Environmental Science, Yale University, New Haven, CT 06511 (United States); Bunn, A G [Department of Environmental Sciences, Huxley College of the Environment, Western Washington University, 516 High Street, Bellingham, WA 98225-9181 (United States); Krankina, O N [Department of Forest Science, Oregon State University, 202 Richardson Hall, Corvallis, OR 97331-5752 (United States); Schlesinger, P [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States); Stone, T A [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States)
2007-10-15
The forests of Russia cover a larger area and hold more carbon than the forests of any other nation and thus have the potential for a major role in global warming. Despite a systematic inventory of these forests, however, estimates of total carbon stocks vary, and spatial variations in the stocks within large aggregated units of land are unknown, thus hampering measurement of sources and sinks of carbon. We mapped the distribution of living forest biomass for the year 2000 by developing a relationship between ground measurements of wood volume at 12 sites throughout the Russian Federation and data from the MODIS satellite bidirectional reflectance distribution function (BRDF) product (MOD43B4). Based on the results of regression-tree analyses, we used the MOD43B4 product to assign biomass values to individual 500 m x 500 m cells in areas identified as forest by two satellite-based maps of land cover. According to the analysis, the total living biomass varied between 46 and 67 Pg, largely because of different estimates of forest area. Although optical data are limited in distinguishing differences in biomass in closed canopy forests, the estimates of total living biomass obtained here varied more in response to different definitions of forest than to saturation of the optical sensing of biomass.
Does nitrogen and sulfur deposition affect forest productivity?
Brittany A. Johnson; Kathryn B. Piatek; Mary Beth Adams; John R. Brooks
2010-01-01
We studied the effects of atmospheric nitrogen and sulfur deposition on forest productivity in a 10-year-old, aggrading forest stand at the Fernow Experimental Forest in Tucker County, WV. Forest productivity was expressed as total aboveground wood biomass, which included stem and branch weight of standing live trees. Ten years after stand regeneration and treatment...
Alamgir, Mohammed; Campbell, Mason J; Turton, Stephen M; Pert, Petina L; Edwards, Will; Laurance, William F
2016-07-20
Tropical forests are major contributors to the terrestrial global carbon pool, but this pool is being reduced via deforestation and forest degradation. Relatively few studies have assessed carbon storage in degraded tropical forests. We sampled 37,000 m(2) of intact rainforest, degraded rainforest and sclerophyll forest across the greater Wet Tropics bioregion of northeast Australia. We compared aboveground biomass and carbon storage of the three forest types, and the effects of forest structural attributes and environmental factors that influence carbon storage. Some degraded forests were found to store much less aboveground carbon than intact rainforests, whereas others sites had similar carbon storage to primary forest. Sclerophyll forests had lower carbon storage, comparable to the most heavily degraded rainforests. Our findings indicate that under certain situations, degraded forest may store as much carbon as intact rainforests. Strategic rehabilitation of degraded forests could enhance regional carbon storage and have positive benefits for tropical biodiversity.
Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics
Chazdon, R.L.; Broadbent, E.N.; Rozendaal, Danae; Bongers, F.; Jakovac, A.C.; Braga Junqueira, A.; Lohbeck, M.W.M.; Pena Claros, M.; Poorter, L.
2016-01-01
Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We
Lou, Yanjing; Pan, Yanwen; Gao, Chuanyu; Jiang, Ming; Lu, Xianguo; Xu, Y. Jun
2016-01-01
Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region. PMID:27097325
Nizami, Syed Moazzam; Yiping, Zhang; Zheng, Zheng; Zhiyun, Lu; Guoping, Yang; Liqing, Sha
2017-03-01
Very old natural forests comprising the species of Fagaceae (Lithocarpus xylocarpus, Castanopsis wattii, Lithocarpus hancei) have been prevailing since years in the Ailaoshan Mountain Nature Reserve (AMNR) SW China. Within these forest trees, density is quite variable. We studied the forest structure, stand dynamics and carbon density at two different sites to know the main factors which drives carbon sequestration process in old forests by considering the following questions: How much is the carbon density in these forest trees of different DBH (diameter at breast height)? How much carbon potential possessed by dominant species of these forests? How vegetation carbon is distributed in these forests? Which species shows high carbon sequestration? What are the physiochemical properties of soil in these forests? Five-year (2005-2010) tree growth data from permanently established plots in the AMNR was analysed for species composition, density, stem diameter (DBH), height and carbon (C) density both in aboveground and belowground vegetation biomass. Our study indicated that among two comparative sites, overall 54 species of 16 different families were present. The stem density, height, C density and soil properties varied significantly with time among the sites showing uneven distribution across the forests. Among the dominant species, L. xylocarpus represents 30% of the total carbon on site 1 while C. wattii represents 50% of the total carbon on site 2. The average C density ranged from 176.35 to 243.97 t C ha -1 . The study emphasized that there is generous degree to expand the carbon stocking in this AMNR through scientific management gearing towards conservation of old trees and planting of potentially high carbon sequestering species on good site quality areas.
Wenchi Jin; Hong S. He; Frank R. Thompson; Wen J. Wang; Jacob S. Fraser; Stephen R. Shifley; Brice B. Hanberry; William D. Dijak
2017-01-01
The Central Hardwood Forest (CHF) in the United States is currently a major carbon sink, there are uncertainties in how long the current carbon sink will persist and if the CHF will eventually become a carbon source. We used a multi-model ensemble to investigate aboveground carbon density of the CHF from 2010 to 2300 under current climate. Simulations were done using...
David C. Chojnacky; Jennifer C. Jenkins; Amanda K. Holland
2009-01-01
Thousands of published equations purport to estimate biomass of individual trees. These equations are often based on very small samples, however, and can provide widely different estimates for trees of the same species. We addressed this issue in a previous study by devising 10 new equations that estimated total aboveground biomass for all species in North America (...
Potentials for forest woody biomass production in Serbia
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Vasiljević Aleksandar Lj.
2015-01-01
Full Text Available The paper presents the analysis of possible potentials for the production of forest biomass in Serbia taking into consideration the condition of forests, present organizational and technical capacities as well as the needs and situation on the firewood market. Starting point for the estimation of production potentials for forest biomass is the condition of forests which is analyzed based on the available planning documents on all levels. Potentials for biomass production and use refer to initial periods in the production and use of forest biomass in Serbia.
Estimating Forest Carbon Stock in Alpine and Arctic Ecotones of the Urals
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V. A. Usoltsev
2014-10-01
Full Text Available This paper reports on measured carbon stocks in the forests of two tree line ecotones of the Ural region where climate change might improve growing conditions. The first is an alpine ecotone that is represented by an altitudinal gradient of the spruce-dominated forests on the Western slope of the Tylaiskii Kamen Mountain (Western part of the Konzhakovskii-Tylaiskii-Serebryanskii Mountain system, 59°30′N, 59°00′E, at the alpine timber line that has risen from 864 to 960 m above sea level in the course of the last 100 years. The second is an arctic ecotone in larch-dominated forests at the lower course of the Pur river (67°N, 78°E, at the transition zone between closed floodplain forests and open or island-like communities of upland forests on tundra permafrost. According to our results, there are large differences in the carbon of the aboveground biomass of both ecotones across environmental gradients. In the alpine tree line ecotone, a 19-fold drop of the carbon stocks was detected between the lower and higher altitudinal levels. In the arctic ecotone the aboveground biomass carbon stock of forests of similar densities (1300 to 1700 trees per ha was 7 times as much in the river flood bed, and 5 times as much in mature, dense forests as the low density forests at higher elevations. Twelve regression equations describing dependencies of the aboveground tree biomass (stems, branches, foliage, total aboveground part upon stem diameter of the tree are proposed, which can be used to estimating the biological productivity (carbon of spruce and larch forests on Tylaiskii Kamen Mountain and the lower Pur river and on surrounding areas on the base of traditional forest mensuration have been proposed. In order to reduce the labor intensity of a coming determination of forest biomass the average values of density and dry matter content in the biomass fractions are given that were obtained by taking our sample trees.The results can be useful in
Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane
2018-02-21
Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated
Below- and above-ground effects of deadwood and termites in plantation forests
Michael D. Ulyshen; Richard Shefferson; Scott Horn; Melanie K. Taylor; Bryana Bush; Cavell Brownie; Sebastian Seibold; Michael S. Strickland
2017-01-01
Deadwood is an important legacy structure in managed forests, providing continuity in shelter and resource availability for many organisms and acting as a vehicle by which nutrients can be passed from one stand to the next following a harvest. Despite existing at the interface between below- and above-ground systems, however, much remains unknown about the role woody...
Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René
2018-03-01
Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.
Liu, Daijun; Ogaya, Romà; Barbeta, Adrià; Yang, Xiaohong; Peñuelas, Josep
2015-11-01
Climate change is predicted to increase the aridity in the Mediterranean Basin and severely affect forest productivity and composition. The responses of forests to different timescales of drought, however, are still poorly understood because extreme and persistent moderate droughts can produce nonlinear responses in plants. We conducted a rainfall-manipulation experiment in a Mediterranean forest dominated by Quercus ilex, Phillyrea latifolia, and Arbutus unedo in the Prades Mountains in southern Catalonia from 1999 to 2014. The experimental drought significantly decreased forest aboveground-biomass increment (ABI), tended to increase the litterfall, and decreased aboveground net primary production throughout the 15 years of the study. The responses to the experimental drought were highly species-specific. A. unedo suffered a significant reduction in ABI, Q. ilex experienced a decrease during the early experiment (1999-2003) and in the extreme droughts of 2005-2006 and 2011-2012, and P. latifolia was unaffected by the treatment. The drought treatment significantly increased branch litterfall, especially in the extremely dry year of 2011, and also increased overall leaf litterfall. The drought treatment reduced the fruit production of Q. ilex, which affected seedling recruitment. The ABIs of all species were highly correlated with SPEI in early spring, whereas the branch litterfalls were better correlated with summer SPEIs and the leaf and fruit litterfalls were better correlated with autumn SPEIs. These species-specific responses indicated that the dominant species (Q. ilex) could be partially replaced by the drought-resistant species (P. latifolia). However, the results of this long-term study also suggest that the effect of drought treatment has been dampened over time, probably due to a combination of demographic compensation, morphological and physiological acclimation, and epigenetic changes. However, the structure of community (e.g., species composition
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Gaia Vaglio Laurin
2016-12-01
Full Text Available Remote sensing supports carbon estimation, allowing the upscaling of field measurements to large extents. Lidar is considered the premier instrument to estimate above ground biomass, but data are expensive and collected on-demand, with limited spatial and temporal coverage. The previous JERS and ALOS SAR satellites data were extensively employed to model forest biomass, with literature suggesting signal saturation at low-moderate biomass values, and an influence of plot size on estimates accuracy. The ALOS2 continuity mission since May 2014 produces data with improved features with respect to the former ALOS, such as increased spatial resolution and reduced revisit time. We used ALOS2 backscatter data, testing also the integration with additional features (SAR textures and NDVI from Landsat 8 data together with ground truth, to model and map above ground biomass in two mixed forest sites: Tahoe (California and Asiago (Alps. While texture was useful to improve the model performance, the best model was obtained using joined SAR and NDVI (R2 equal to 0.66. In this model, only a slight saturation was observed, at higher levels than what usually reported in literature for SAR; the trend requires further investigation but the model confirmed the complementarity of optical and SAR datatypes. For comparison purposes, we also generated a biomass map for Asiago using lidar data, and considered a previous lidar-based study for Tahoe; in these areas, the observed R2 were 0.92 for Tahoe and 0.75 for Asiago, respectively. The quantitative comparison of the carbon stocks obtained with the two methods allows discussion of sensor suitability. The range of local variation captured by lidar is higher than those by SAR and NDVI, with the latter showing overestimation. However, this overestimation is very limited for one of the study areas, suggesting that when the purpose is the overall quantification of the stored carbon, especially in areas with high carbon
Goring, Simon; Mladenoff, David J.; Cogbill, Charles; Record, Sydne; Paciorek, Christopher J.; Dietze, Michael C.; Dawson, Andria; Matthes, Jaclyn; McLachlan, Jason S.; Williams, John W.
2016-01-01
EuroAmerican land-use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection.
Leitold, Veronika; Keller, Michael; Morton, Douglas C; Cook, Bruce D; Shimabukuro, Yosio E
2015-12-01
Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (~20 returns m -2 ) data was highly accurate (mean signed error of 0.19 ± 0.97 m), while those derived from reduced-density datasets (8 m -2 , 4 m -2 , 2 m -2 and 1 m -2 ) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4 m -2 , the bias in height estimates translated into errors of 80-125 Mg ha -1 in predicted aboveground biomass. Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.
An empirical, integrated forest biomass monitoring system
Kennedy, Robert E.; Ohmann, Janet; Gregory, Matt; Roberts, Heather; Yang, Zhiqiang; Bell, David M.; Kane, Van; Hughes, M. Joseph; Cohen, Warren B.; Powell, Scott; Neeti, Neeti; Larrue, Tara; Hooper, Sam; Kane, Jonathan; Miller, David L.; Perkins, James; Braaten, Justin; Seidl, Rupert
2018-02-01
The fate of live forest biomass is largely controlled by growth and disturbance processes, both natural and anthropogenic. Thus, biomass monitoring strategies must characterize both the biomass of the forests at a given point in time and the dynamic processes that change it. Here, we describe and test an empirical monitoring system designed to meet those needs. Our system uses a mix of field data, statistical modeling, remotely-sensed time-series imagery, and small-footprint lidar data to build and evaluate maps of forest biomass. It ascribes biomass change to specific change agents, and attempts to capture the impact of uncertainty in methodology. We find that: • A common image framework for biomass estimation and for change detection allows for consistent comparison of both state and change processes controlling biomass dynamics. • Regional estimates of total biomass agree well with those from plot data alone. • The system tracks biomass densities up to 450-500 Mg ha-1 with little bias, but begins underestimating true biomass as densities increase further. • Scale considerations are important. Estimates at the 30 m grain size are noisy, but agreement at broad scales is good. Further investigation to determine the appropriate scales is underway. • Uncertainty from methodological choices is evident, but much smaller than uncertainty based on choice of allometric equation used to estimate biomass from tree data. • In this forest-dominated study area, growth and loss processes largely balance in most years, with loss processes dominated by human removal through harvest. In years with substantial fire activity, however, overall biomass loss greatly outpaces growth. Taken together, our methods represent a unique combination of elements foundational to an operational landscape-scale forest biomass monitoring program.
Validating Community-Led Forest Biomass Assessments.
Venter, Michelle; Venter, Oscar; Edwards, Will; Bird, Michael I
2015-01-01
The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha(-1), which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50 cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees.
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T. Takayama
2016-06-01
Full Text Available Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.
Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests
Fatoyinbo, Temilola E.
2010-01-01
Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation
Model-Assisted Estimation of Tropical Forest Biomass Change: A Comparison of Approaches
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Nikolai Knapp
2018-05-01
Full Text Available Monitoring of changes in forest biomass requires accurate transfer functions between remote sensing-derived changes in canopy height (ΔH and the actual changes in aboveground biomass (ΔAGB. Different approaches can be used to accomplish this task: direct approaches link ΔH directly to ΔAGB, while indirect approaches are based on deriving AGB stock estimates for two points in time and calculating the difference. In some studies, direct approaches led to more accurate estimations, while, in others, indirect approaches led to more accurate estimations. It is unknown how each approach performs under different conditions and over the full range of possible changes. Here, we used a forest model (FORMIND to generate a large dataset (>28,000 ha of natural and disturbed forest stands over time. Remote sensing of forest height was simulated on these stands to derive canopy height models for each time step. Three approaches for estimating ΔAGB were compared: (i the direct approach; (ii the indirect approach and (iii an enhanced direct approach (dir+tex, using ΔH in combination with canopy texture. Total prediction accuracies of the three approaches measured as root mean squared errors (RMSE were RMSEdirect = 18.7 t ha−1, RMSEindirect = 12.6 t ha−1 and RMSEdir+tex = 12.4 t ha−1. Further analyses revealed height-dependent biases in the ΔAGB estimates of the direct approach, which did not occur with the other approaches. Finally, the three approaches were applied on radar-derived (TanDEM-X canopy height changes on Barro Colorado Island (Panama. The study demonstrates the potential of forest modeling for improving the interpretation of changes observed in remote sensing data and for comparing different methodologies.
Forest biomass observation: current state and prospective
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D. G. Schepaschenko
2017-08-01
Full Text Available With this article, we provide an overview of the methods, instruments and initiatives for forest biomass observation at global scale. We focus on the freely available information, provided by both remote and in-situ observations. The advantages and limitation of various space borne methods, including optical, radar (C, L and P band and LiDAR, as well as respective instruments available on the orbit (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2 , ALOS PALSAR, Envisat ASAR or expecting (BIOMASS, GEDI, NISAR, SAOCOM-CS are discussed. We emphasize the role of in-situ methods in the development of a biomass models, providing calibration and validation of remote sensing data. We focus on freely available forest biomass maps, databases and empirical models. We describe the functionality of Biomass.Geo-Wiki.org portal, which provides access to a collection of global and regional biomass maps in full resolution with unified legend and units overplayed with high-resolution imagery. The Forest-Observation-System.net is announced as an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. Prospects of unmanned aerial vehicles in the forest inventory are briefly discussed. The work was partly supported by ESA IFBN project (contract 4000114425/15/NL/FF/gp.
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Maria J. Vasconcelos
2013-03-01
Full Text Available The quantification of forest above-ground biomass (AGB is important for such broader applications as decision making, forest management, carbon (C stock change assessment and scientific applications, such as C cycle modeling. However, there is a great uncertainty related to the estimation of forest AGB, especially in the tropics. The main goal of this study was to test a combination of field data and Advanced Land Observing Satellite (ALOS Phased Array L-band Synthetic Aperture Radar (PALSAR backscatter intensity data to reduce the uncertainty in the estimation of forest AGB in the Miombo savanna woodlands of Mozambique (East Africa. A machine learning algorithm, based on bagging stochastic gradient boosting (BagSGB, was used to model forest AGB as a function of ALOS PALSAR Fine Beam Dual (FBD backscatter intensity metrics. The application of this method resulted in a coefficient of correlation (R between observed and predicted (10-fold cross-validation forest AGB values of 0.95 and a root mean square error of 5.03 Mg·ha−1. However, as a consequence of using bootstrap samples in combination with a cross validation procedure, some bias may have been introduced, and the reported cross validation statistics could be overoptimistic. Therefore and as a consequence of the BagSGB model, a measure of prediction variability (coefficient of variation on a pixel-by-pixel basis was also produced, with values ranging from 10 to 119% (mean = 25% across the study area. It provides additional and complementary information regarding the spatial distribution of the error resulting from the application of the fitted model to new observations.
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Yuanqi Chen
2015-03-01
Full Text Available In order to understand how carbon storage and allocation patterns vary among plantation types, we estimated carbon allocation between above- and below-ground compartments in four subtropical plantations and a naturally recovered shrubland (as a control. Results indicated that the carbon storage and allocation pattern varied greatly among forest types and was highly dependent on specific traits of trees and understory vegetation. The fast-growing species, such as Eucalyptus urophylla, accumulated more carbon in plant biomass. The biomass carbon was about 1.9- and 2.2-times greater than the 10-species mixed plantation and Castanopsis hystrix plantations, respectively. Meanwhile, the plantations sequestered 1.5- to 3-times more carbon in biomass than naturally recovered shrubland. The carbon allocation pattern between above- and below-ground compartments also varied with plantation type and stand age. The ratio of tree root carbon to tree aboveground carbon decreased with stand age for Eucalyptus urophylla and the 10-species mixed plantation. In contrast, the ratio increased for Acacia crassicarpa. Our data suggested that planting the fast-growing species in the degraded land of subtropical China was an effective choice in terms of carbon sequestration. The information about carbon allocation patterns was also valuable for decision making in sustainable forest management and climate change mitigation.
Volume and aboveground biomass models for dry Miombo woodland in Tanzania
DEFF Research Database (Denmark)
Mwakalukwa, Ezekiel Edward; Meilby, Henrik; Treue, Thorsten
2014-01-01
Tools to accurately estimate tree volume and biomass are scarce for most forest types in East Africa, including Tanzania. Based on a sample of 142 trees and 57 shrubs from a 6,065 ha area of dry miombo woodland in Iringa rural district in Tanzania, regression models were developed for volume...... and biomass of three important species, Brachystegia spiciformis Benth. (n=40), Combretum molle G. Don (n=41), and Dalbergia arbutifolia Baker (n=37) separately, and for broader samples of trees (28 species, n=72), shrubs (16 species, n=31), and trees and shrubs combined (44 species, n=104). Applied...... of the predictions tended to increase from general to species-specific models. Except for a few volume and biomass models developed for shrubs, all models had R2 values of 96–99%. Thus, the models appear robust and should be applicable to forests with similar site conditions, species, and diameter ranges....
Temperate forest dynamics and carbon storage: A 26-year case ...
African Journals Online (AJOL)
Overall, these results suggest that the forest is in a post-disturbance recovery phase, although favourable climatic conditions over the last three decades may also have had an influence on AGB accumulation. Keywords: aboveground biomass, carbon sequestration, forest conservation, long-term monitoring, succession ...
Liu, Liangyun; Peng, Dailiang; Wang, Zhihui; Hu, Yong
2014-11-01
China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.
Cintra, B. B. L.; Schietti, J.; Emillio, T.; Martins, D.; Moulatlet, G.; Souza, P.; Levis, C.; Quesada, C. A.; Schöngart, J.
2013-04-01
The ongoing demand for information on forest productivity has increased the number of permanent monitoring plots across the Amazon. Those plots, however, do not comprise the whole diversity of forest types in the Amazon. The complex effects of soil, climate and hydrology on the productivity of seasonally waterlogged interfluvial wetland forests are still poorly understood. The presented study is the first field-based estimate for tree ages and wood biomass productivity in the vast interfluvial region between the Purus and Madeira rivers. We estimate stand age and wood biomass productivity by a combination of tree-ring data and allometric equations for biomass stocks of eight plots distributed along 600 km in the Purus-Madeira interfluvial area that is crossed by the BR-319 highway. We relate stand age and wood biomass productivity to hydrological and edaphic conditions. Mean productivity and stand age were 5.6 ± 1.1 Mg ha-1 yr-1 and 102 ± 18 yr, respectively. There is a strong relationship between tree age and diameter, as well as between mean diameter increment and mean wood density within a plot. Regarding the soil hydromorphic properties we find a positive correlation with wood biomass productivity and a negative relationship with stand age. Productivity also shows a positive correlation with the superficial phosphorus concentration. In addition, superficial phosphorus concentration increases with enhanced soil hydromorphic condition. We raise three hypotheses to explain these results: (1) the reduction of iron molecules on the saturated soils with plinthite layers close to the surface releases available phosphorous for the plants; (2) the poor structure of the saturated soils creates an environmental filter selecting tree species of faster growth rates and shorter life spans and (3) plant growth on saturated soil is favored during the dry season, since there should be low restrictions for soil water availability.
Janaki R. R. Alavalapati; Pankaj Lal; Andres Susaeta; Robert C. Abt; David N. Wear
2013-01-01
Key FindingsHarvesting woody biomass for use as bioenergy is projected to range from 170 million to 336 million green tons by 2050, an increase of 54 to 113 percent over current levels.Consumption projections for forest biomass-based energy, which are based on Energy Information Administration projections, have a high level of...
Biomass and Carbon Stocks of Sofala Bay Mangrove Forests
Directory of Open Access Journals (Sweden)
Almeida A. Sitoe
2014-08-01
Full Text Available Mangroves could be key ecosystems in strategies addressing the mitigation of climate changes through carbon storage. However, little is known regarding the carbon stocks of these ecosystems, particularly below-ground. This study was carried out in the mangrove forests of Sofala Bay, Central Mozambique, with the aim of quantifying carbon stocks of live and dead plant and soil components. The methods followed the procedures developed by the Center for International Forestry Research (CIFOR for mangrove forests. In this study, we developed a general allometric equation to estimate individual tree biomass and soil carbon content (up to 100 cm depth. We estimated the carbon in the whole mangrove ecosystem of Sofala Bay, including dead trees, wood debris, herbaceous, pneumatophores, litter and soil. The general allometric equation for live trees derived was [Above-ground tree dry weight (kg = 3.254 × exp(0.065 × DBH], root mean square error (RMSE = 4.244, and coefficient of determination (R2 = 0.89. The average total carbon storage of Sofala Bay mangrove was 218.5 Mg·ha−1, of which around 73% are stored in the soil. Mangrove conservation has the potential for REDD+ programs, especially in regions like Mozambique, which contains extensive mangrove areas with high deforestation and degradation rates.
Directory of Open Access Journals (Sweden)
Kai Liu
2018-04-01
Full Text Available Temperate forests in Northeast China have been severely exploited by timber harvesting in the last century. To reverse this trend, China implemented the Classified Forest Management policy in the Natural Forest Conservation Program in 1998 to protect forests from excessive harvesting. However, the policy was unable to meet the 2020 commitment of increasing growing stock (set in the Kyoto Protocol because of high-intensity harvesting. Accordingly, China banned all commercial harvesting in Northeast China in 2014. In this study, we investigated the long-term impacts of the no commercial harvest (NCH policy on ecosystem services and biodiversity using a forest landscape model, LANDIS PRO 7.0, in the temperate forests of the Small Khingan Mountains, Northeast China. We designed three management scenarios: The H scenario (the Classified Forest Management policy used in the past, the NCH scenario (the current Commercial Harvest Exclusion policy, and the LT scenario (mitigation management, i.e., light thinning. We compared total aboveground forest biomass, biomass by tree species, abundance of old-growth forests, and diversity of tree species and age class in three scenarios from 2010 to 2100. We found that compared with the H scenario, the NCH scenario increased aboveground forest biomass, abundance of old-growth forests, and biomass of most timber species over time; however, it decreased the biomass of rare and protected tree species and biodiversity. We found that the LT scenario increased the biomass of rare and protected tree species and biodiversity in comparison with the NCH scenario, while it maintained aboveground forest biomass and abundance of old-growth forests at a high level (slightly less than the NCH scenario. We concluded there was trade-off between carbon storage and biodiversity. We also concluded that light thinning treatment was able to regulate the trade-off and alleviate the negative effects associated with the NCH policy. Our
Annual measurements of gain and loss in aboveground carbon density
Baccini, A.; Walker, W. S.; Carvalho, L.; Farina, M.; Sulla-menashe, D. J.; Houghton, R. A.
2017-12-01
Tropical forests hold large stores of carbon, but their net carbon balance is uncertain. Land use and land-cover change (LULCC) are believed to release between 0.81 and 1.14 PgC yr-1, while intact native forests are thought to be a net carbon sink of approximately the same magnitude. Reducing the uncertainty of these estimates is not only fundamental to the advancement of carbon cycle science but is also of increasing relevance to national and international policies designed to reduce emissions from deforestation and forest degradation (e.g., REDD+). Contemporary approaches to estimating the net carbon balance of tropical forests rely on changes in forest area between two periods, typically derived from satellite data, together with information on average biomass density. These approaches tend to capture losses in biomass due to deforestation (i.e., wholesale stand removals) but are limited in their sensitivity to forest degradation (e.g., selective logging or single-tree removals), which can account for additional biomass losses on the order of 47-75% of deforestation. Furthermore, while satellite-based estimates of forest area loss have been used successfully to estimate associated carbon losses, few such analyses have endeavored to determine the rate of carbon sequestration in growing forests. Here we use 12 years (2003-2014) of pantropical satellite data to quantify net annual changes in the aboveground carbon density of woody vegetation (MgC ha-1yr-1), providing direct, measurement-based evidence that the world's tropical forests are a net carbon source of 425.2 ± 92.0 Tg C yr-1. This net release of carbon consists of losses of 861.7 ± 80.2 Tg C yr-1 and gains of -436.5 ± 31.0 Tg C yr-1 . Gains result from forest growth; losses result from reductions in forest area due to deforestation and from reductions in biomass density within standing forests (degradation), with the latter accounting for 68.9% of overall losses. Our findings advance previous research
Height-diameter allometry of tropical forest trees
T.R. Feldpausch; L. Banin; O.L. Phillips; T.R. Baker; S.L. Lewis; C.A. Quesada; K. Affum-Baffoe; E.J.M.M. Arets; N.J. Berry; M. Bird; E.S. Brondizio; P de Camargo; J. Chave; G. Djagbletey; T.F. Domingues; M. Drescher; P.M. Fearnside; M.B. Franca; N.M. Fyllas; G. Lopez-Gonzalez; A. Hladik; N. Higuchi; M.O. Hunter; Y. Iida; K.A. Salim; A.R. Kassim; M. Keller; J. Kemp; D.A. King; J.C. Lovett; B.S. Marimon; B.H. Marimon-Junior; E. Lenza; A.R. Marshall; D.J. Metcalfe; E.T.A. Mitchard; E.F. Moran; B.W. Nelson; R. Nilus; E.M. Nogueira; M. Palace; S. Patiño; K.S.-H. Peh; M.T. Raventos; J.M. Reitsma; G. Saiz; F. Schrodt; B. Sonke; H.E. Taedoumg; S. Tan; L. White; H. Woll; J. Lloyd
2011-01-01
Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical...
[Estimation of Shenyang urban forest green biomass].
Liu, Chang-fu; He, Xing-yuan; Chen, Wei; Zhao, Gui-ling; Xu, Wen-duo
2007-06-01
Based on ARC/GIS and by using the method of "planar biomass estimation", the green biomass (GB) of Shenyang urban forests was measured. The results demonstrated that the GB per unit area was the highest (3.86 m2.m(-2)) in landscape and relaxation forest, and the lowest (2.27 m2.m(-2)) in ecological and public welfare forest. The GB per unit area in urban forest distribution area was 2.99 m2.m(-2), and that of the whole Shenyang urban area was 0.25 m2.m(-2). The total GB of Shenyang urban forests was about 1.13 x 10(8) m2, among which, subordinated forest, ecological and public welfare forest, landscape and relaxation forest, road forest, and production and management forest accounted for 36.64% , 23.99% , 19.38% , 16.20% and 3.79%, with their GB being 4. 15 x 10(7), 2.72 x 10(7), 2.20 x 10(7), 1.84 x 10(7) and 0.43 x 10(7) m2, respectively. The precision of the method "planar biomass estimation" was 91.81% (alpha = 0.05) by credit test.
Airborne S-Band SAR for Forest Biophysical Retrieval in Temperate Mixed Forests of the UK
Directory of Open Access Journals (Sweden)
Ramesh K. Ningthoujam
2016-07-01
Full Text Available Radar backscatter from forest canopies is related to forest cover, canopy structure and aboveground biomass (AGB. The S-band frequency (3.1–3.3 GHz lies between the longer L-band (1–2 GHz and the shorter C-band (5–6 GHz and has been insufficiently studied for forest applications due to limited data availability. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest biophysical properties. To understand the scattering mechanisms in forest canopies at S-band the Michigan Microwave Canopy Scattering (MIMICS-I radiative transfer model was used. S-band backscatter was found to have high sensitivity to the forest canopy characteristics across all polarisations and incidence angles. This sensitivity originates from ground/trunk interaction as the dominant scattering mechanism related to broadleaved species for co-polarised mode and specific incidence angles. The study was carried out in the temperate mixed forest at Savernake Forest and Wytham Woods in southern England, where airborne S-band SAR imagery and field data are available from the recent AirSAR campaign. Field data from the test sites revealed wide ranges of forest parameters, including average canopy height (6–23 m, diameter at breast-height (7–42 cm, basal area (0.2–56 m2/ha, stem density (20–350 trees/ha and woody biomass density (31–520 t/ha. S-band backscatter-biomass relationships suggest increasing backscatter sensitivity to forest AGB with least error between 90.63 and 99.39 t/ha and coefficient of determination (r2 between 0.42 and 0.47 for the co-polarised channel at 0.25 ha resolution. The conclusion is that S-band SAR data such as from NovaSAR-S is suitable for monitoring forest aboveground biomass less than 100 t/ha at 25 m resolution in low to medium incidence angle range.
Estimating forest characteristics using NAIP imagery and ArcObjects
John S Hogland; Nathaniel M. Anderson; Woodam Chung; Lucas Wells
2014-01-01
Detailed, accurate, efficient, and inexpensive methods of estimating basal area, trees, and aboveground biomass per acre across broad extents are needed to effectively manage forests. In this study we present such a methodology using readily available National Agriculture Imagery Program imagery, Forest Inventory Analysis samples, a two stage classification and...
Energy of forest biomass in Croatia
International Nuclear Information System (INIS)
Cupin, N.; Krivak, B.; Dundovic, J.
2005-01-01
Forest biomass is organic substance raised in forest ecosystem, consisting of trees and bushes which are used for mechanical processing and thermal use. Croatia, with 44 percent of surface under forests, has the renewable energy potential in forest biomass that could cover as much as about 50 percent of the current heating consumption. The existence of an appropriate heating consume and district heating are a prerequisite for exploitation of the mentioned potential. At the same time, heating consumption enables the utilization of cogeneration plants and the paper gives examples of such possibilities in industry, community and special facilities (sport centres, hotels, hospitals etc.). Among them, the so called 'Croatian energy absurdum' is mentioned. The paper underlines the feasibility of exploitation of forest biomass at the national level and suggests that, in order to promote and accelerate the development of cogeneration plants, the HED expert group should be established. The task of the expert group would be to draft proposal for appropriate measures in this regard and submit it to the Government for consideration.(author)
Mallon, E. E.; Turetsky, M.; Thompson, I.; Noland, T. L.; Wiebe, P.
2013-12-01
Disturbance is known to play an important role in maintaining the productivity and biodiversity of boreal forest ecosystems. Moderate to low frequency disturbance is responsible for regeneration opportunities creating a mosaic of habitats and successional trajectories. However, large-scale deforestation and increasing wildfire frequencies exacerbate habitat loss and influence biogeochemical cycles. This has raised concern about the quality of the under-story vegetation post-disturbance and whether this may impact herbivores, especially those vulnerable to change. Forest-dwelling caribou (Rangifer tarandus caribou) are declining in several regions of Canada and are currently listed as a species at risk by COSEWIC. Predation and landscape alteration are viewed as the two main threats to woodland caribou. This has resulted in caribou utilizing low productivity peatlands as refuge and the impact of this habitat selection on their diet quality is not well understood. Therefore there are two themes in the study, 1) Forage quantity: above-ground biomass and productivity and 2) Forage quality: foliar N and C to N ratios and % fiber. The themes are addressed in three questions: 1) How does forage quantity and quality vary between upland forests and peatlands? 2) How does wildfire affect the availability and nutritional quality of forage items? 3) How does forage quality vary between sites recovering from wildfire versus timber harvest? Research sites were located in the Auden region north of Geraldton, ON. This landscape was chosen because it is known woodland caribou habitat and has thorough wildfire and silviculture data from the past 7 decades. Plant diversity, above-ground biomass, vascular green area and seasonal foliar fiber and C to N ratios were collected across a matrix of sites representing a chronosequence of time since disturbance in upland forests and peatlands. Preliminary findings revealed productivity peaked in early age stands (0-30 yrs) and biomass peaked
Forest biomass and energy-wood potential in the southern United States
Energy Technology Data Exchange (ETDEWEB)
Saucier, J.R. [Forestry Sciences Lab., Athens, GA (United States)
1993-12-31
Timber resource data were compiled from the most recent USDA Forest Service inventory data for the 12 Southern States from Virginia to Texas. Timber resource inventories traditionally include only trees 5 inches dbh and greater and their volumes to the prevailing merchantable top diameter expressed in cubic feet, board feet, or cords. For this paper, conversion factors were developed to express timber inventories in weight and to expand the inventories to include the crowns of merchantable trees and trees less than 5 inches dbh. By so doing, the total aboveground biomass is estimated for the timberlands in the South. The region contains 185 million acres of timberland. Some 14.6 billion green tons of woody biomass are present on southern timberland -- about 79 tons per acre. When mature stands are harvested, the average acre in the South has 22.2 tons of woody material left in crowns and sapling, and 5.1 tons in cull stems. Thus, an average of 27.3 green tons per acre of potential energy wood are left after conventional harvests. Conversion factors that are presented permit estimates for specific tracts, areas, counties, or states.
International Nuclear Information System (INIS)
Tyukavina, A; Potapov, P V; Turubanova, S A; Hansen, M C; Stehman, S V; Baccini, A; Goetz, S J; Laporte, N T; Houghton, R A
2013-01-01
Recent advances in remote sensing enable the mapping and monitoring of carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where national forest inventories (NFI) are either non-existent or out of date. Here we demonstrate a method for estimating national-scale gross forest aboveground carbon (AGC) loss and associated uncertainties using remotely sensed-derived forest cover loss and biomass carbon density data. Lidar data were used as a surrogate for NFI plot measurements to estimate carbon stocks and AGC loss based on forest type and activity data derived using time-series multispectral imagery. Specifically, DRC forest type and loss from the FACET (Forêts d’Afrique Centrale Evaluées par Télédétection) product, created using Landsat data, were related to carbon data derived from the Geoscience Laser Altimeter System (GLAS). Validation data for FACET forest area loss were created at a 30-m spatial resolution and compared to the 60-m spatial resolution FACET map. We produced two gross AGC loss estimates for the DRC for the last decade (2000–2010): a map-scale estimate (53.3 ± 9.8 Tg C yr −1 ) accounting for whole-pixel classification errors in the 60-m resolution FACET forest cover change product, and a sub-grid estimate (72.1 ± 12.7 Tg C yr −1 ) that took into account 60-m cells that experienced partial forest loss. Our sub-grid forest cover and AGC loss estimates, which included smaller-scale forest disturbances, exceed published assessments. Results raise the issue of scale in forest cover change mapping and validation, and subsequent impacts on remotely sensed carbon stock change estimation, particularly for smallholder dominated systems such as the DRC. (letter)
Detrital carbon pools in temperate forests: magnitude and potential for landscape-scale assessment
John Bradford; Peter Weishampel; Marie-Louise Smith; Randall Kolka; Richard A. Birdsey; Scott V. Ollinger; Michael G. Ryan
2009-01-01
Reliably estimating carbon storage and cycling in detrital biomass is an obstacle to carbon accounting. We examined carbon pools and fluxes in three small temperate forest landscapes to assess the magnitude of carbon stored in detrital biomass and determine whether detrital carbon storage is related to stand structural properties (leaf area, aboveground biomass,...
Hyperspectral sensing of forests
Goodenough, David G.; Dyk, Andrew; Chen, Hao; Hobart, Geordie; Niemann, K. Olaf; Richardson, Ash
2007-11-01
Canada contains 10% of the world's forests covering an area of 418 million hectares. The sustainable management of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of new and improved information products to resource managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory, forest health, foliar biochemistry, biomass, and aboveground carbon than are currently available. This paper surveys recent methods and results in hyperspectral sensing of forests and describes space initiatives for hyperspectral sensing.
Czech Academy of Sciences Publication Activity Database
Fiala, Karel; Tůma, Ivan; Holub, Petr
2011-01-01
Roč. 66, č. 2 (2011), s. 275-281 ISSN 0006-3088 R&D Projects: GA ČR(CZ) GA526/06/0556 Institutional research plan: CEZ:AV0Z60050516 Keywords : nitrogen * drought * above-ground biomass Subject RIV: EF - Botanics Impact factor: 0.557, year: 2011
Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis
Zolkos, S. G.; Goetz, S. J.; Dubayah, R.
2012-12-01
Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.
A first map of tropical Africa's above-ground biomass derived from satellite imagery
International Nuclear Information System (INIS)
Baccini, A; Laporte, N; Goetz, S J; Sun, M; Dong, H
2008-01-01
Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha -1 for a range of biomass between 0 and 454 Mg ha -1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R 2 = 0.90) between the GLAS height metrics and predicted AGB.
Hadley, Brian Christopher
This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.
Estimates of grassland biomass and turnover time on the Tibetan Plateau
Xia, Jiangzhou; Ma, Minna; Liang, Tiangang; Wu, Chaoyang; Yang, Yuanhe; Zhang, Li; Zhang, Yangjian; Yuan, Wenping
2018-01-01
The grassland of the Tibetan Plateau forms a globally significant biome, which represents 6% of the world’s grasslands and 44% of China’s grasslands. However, large uncertainties remain concerning the vegetation carbon storage and turnover time in this biome. In this study, we quantified the pool size of both the aboveground and belowground biomass and turnover time of belowground biomass across the Tibetan Plateau by combining systematic measurements taken from a substantial number of surveys (i.e. 1689 sites for aboveground biomass, 174 sites for belowground biomass) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is effective tool for upscaling local biomass observations to the regional scale, and for producing continuous biomass estimates of the Tibetan Plateau. On average, the models estimated 46.57 Tg (1 Tg = 1012g) C of aboveground biomass and 363.71 Tg C of belowground biomass in the Tibetan grasslands covering an area of 1.32 × 106 km2. The turnover time of belowground biomass demonstrated large spatial heterogeneity, with a median turnover time of 4.25 years. Our results also demonstrated large differences in the biomass simulations among the major ecosystem models used for the Tibetan Plateau, largely because of inadequate model parameterization and validation. This study provides a spatially continuous measure of vegetation carbon storage and turnover time, and provides useful information for advancing ecosystem models and improving their performance.
Family forest owner preferences for biomass harvesting in Massachusetts
Marla Markowski-Lindsay; Thomas Stevens; David B. Kittredge; Brett J. Butler; Paul Catanzaro; David Damery
2012-01-01
U.S. forests, including family-owned forests, are a potential source of biomass for renewable energy. Family forest owners constitute a significant portion of the overall forestland in the U.S., yet little is known about family forest owners' preferences for supplying wood-based biomass. The goal of this study is to understand how Massachusetts family forest...
Monitoring coniferous forest biomass change using a Landsat trajectory-based approach
Magdalena Main-Knorn; Warren B. Cohen; Robert E. Kennedy; Wojciech Grodzki; Dirk Pflugmacher; Patrick Griffiths; Patrick Hostert
2013-01-01
Forest biomass is a major store of carbon and thus plays an important role in the regional and global carbon cycle. Accurate forest carbon sequestration assessment requires estimation of both forest biomass and forest biomass dynamics over time. Forest dynamics are characterized by disturbances and recovery, key processes affecting site productivity and the forest...
Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics.
Chazdon, Robin L; Broadbent, Eben N; Rozendaal, Danaë M A; Bongers, Frans; Zambrano, Angélica María Almeyda; Aide, T Mitchell; Balvanera, Patricia; Becknell, Justin M; Boukili, Vanessa; Brancalion, Pedro H S; Craven, Dylan; Almeida-Cortez, Jarcilene S; Cabral, George A L; de Jong, Ben; Denslow, Julie S; Dent, Daisy H; DeWalt, Saara J; Dupuy, Juan M; Durán, Sandra M; Espírito-Santo, Mario M; Fandino, María C; César, Ricardo G; Hall, Jefferson S; Hernández-Stefanoni, José Luis; Jakovac, Catarina C; Junqueira, André B; Kennard, Deborah; Letcher, Susan G; Lohbeck, Madelon; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R F; Ochoa-Gaona, Susana; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A; Piotto, Daniel; Powers, Jennifer S; Rodríguez-Velazquez, Jorge; Romero-Pérez, Isabel Eunice; Ruíz, Jorge; Saldarriaga, Juan G; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B; Steininger, Marc K; Swenson, Nathan G; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D M; Vester, Hans; Vieira, Ima Celia G; Bentos, Tony Vizcarra; Williamson, G Bruce; Poorter, Lourens
2016-05-01
Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km(2) of land (28.1% of the total study area). Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from 1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forest management, natural regeneration of second-growth forests provides a low-cost mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services.
Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics
Chazdon, Robin L.; Broadbent, Eben N.; Rozendaal, Danaë M. A.; Bongers, Frans; Zambrano, Angélica María Almeyda; Aide, T. Mitchell; Balvanera, Patricia; Becknell, Justin M.; Boukili, Vanessa; Brancalion, Pedro H. S.; Craven, Dylan; Almeida-Cortez, Jarcilene S.; Cabral, George A. L.; de Jong, Ben; Denslow, Julie S.; Dent, Daisy H.; DeWalt, Saara J.; Dupuy, Juan M.; Durán, Sandra M.; Espírito-Santo, Mario M.; Fandino, María C.; César, Ricardo G.; Hall, Jefferson S.; Hernández-Stefanoni, José Luis; Jakovac, Catarina C.; Junqueira, André B.; Kennard, Deborah; Letcher, Susan G.; Lohbeck, Madelon; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A.; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R. F.; Ochoa-Gaona, Susana; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A.; Piotto, Daniel; Powers, Jennifer S.; Rodríguez-Velazquez, Jorge; Romero-Pérez, Isabel Eunice; Ruíz, Jorge; Saldarriaga, Juan G.; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B.; Steininger, Marc K.; Swenson, Nathan G.; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D. M.; Vester, Hans; Vieira, Ima Celia G.; Bentos, Tony Vizcarra; Williamson, G. Bruce; Poorter, Lourens
2016-01-01
Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km2 of land (28.1% of the total study area). Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from 1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forest management, natural regeneration of second-growth forests provides a low-cost mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services. PMID:27386528
Gandhi, Durai Sanjay; Sundarapandian, Somaiah
2017-04-01
Tropical dry forests are one of the most widely distributed ecosystems in tropics, which remain neglected in research, especially in the Eastern Ghats. Therefore, the present study was aimed to quantify the carbon storage in woody vegetation (trees and lianas) on large scale (30, 1 ha plots) in the dry deciduous forest of Sathanur reserve forest of Eastern Ghats. Biomass of adult (≥10 cm DBH) trees was estimated by species-specific allometric equations using diameter and wood density of species whereas in juvenile tree population and lianas, their respective general allometric equations were used to estimate the biomass. The fractional value 0.4453 was used to convert dry biomass into carbon in woody vegetation of tropical dry forest. The mean aboveground biomass value of juvenile tree population was 1.86 Mg/ha. The aboveground biomass of adult trees ranged from 64.81 to 624.96 Mg/ha with a mean of 245.90 Mg/ha. The mean aboveground biomass value of lianas was 7.98 Mg/ha. The total biomass of woody vegetation (adult trees + juvenile population of trees + lianas) ranged from 85.02 to 723.46 Mg/ha, with a mean value of 295.04 Mg/ha. Total carbon accumulated in woody vegetation in tropical dry deciduous forest ranged from 37.86 to 322.16 Mg/ha with a mean value of 131.38 Mg/ha. Adult trees accumulated 94.81% of woody biomass carbon followed by lianas (3.99%) and juvenile population of trees (1.20%). Albizia amara has the greatest biomass and carbon stock (58.31%) among trees except for two plots (24 and 25) where Chloroxylon swietenia contributed more to biomass and carbon stock. Similarly, Albizia amara (52.4%) showed greater carbon storage in juvenile population of trees followed by Chloroxylon swietenia (21.9%). Pterolobium hexapetalum (38.86%) showed a greater accumulation of carbon in liana species followed by Combretum albidum (33.04%). Even though, all the study plots are located within 10 km radius, they show a significant spatial variation among
Directory of Open Access Journals (Sweden)
Su Li
2017-11-01
Full Text Available Epiphytic lichens are an important component in subtropical forests and contribute greatly to forest biodiversity and biomass. However, information on epiphytic lichens still remains scarce in forest conservation owing to the difficulty of accessing all canopy layers for direct observation. Here, epiphytic lichens were quantified on 73 whole trees in five forest types in Southwest China to clarify the vertical stratification of their biomass in subtropical forests. Lichen biomass was significantly influenced by forest type and host attributes, varying from 187.11 to 8.55 g∙tree−1 among forest types and from 289.81 to <0.01 g∙tree−1 among tree species. The vertical stratification of lichen biomass was also determined by forest type, which peaked at the top in primary Lithocarpus forest and middle-aged oak secondary forest and in the middle upper heights in other forests. Overall, the proportion of lichen biomass accounted for 73.17–100.00% of total lichen biomass on branches and 0.00–26.83% on trunks in five forests, and 64.53–100.00% and 0.00–35.47% on eight host species. Seven functional groups showed marked and various responses to tree height between and among forest types. This information improves our understanding of the distribution of epiphytic lichens in forest ecosystems and the promotion of forest management in subtropical China.
Holmquist, J. R.; Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Windham-Myers, L.; Thomas, N.
2017-12-01
Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our goal was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). To meet this objective we developed the first national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest algorithm we tested Sentinel-1 radar backscatter metrics and Landsat vegetation indices as predictors of biomass. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n=409, RMSE=310 g/m2, 10.3% normalized RMSE), successfully predicted biomass and carbon for a range of marsh plant functional types defined by height, leaf angle and growth form. Model error was reduced by scaling field measured biomass by Landsat fraction green vegetation derived from object-based classification of National Agriculture Imagery Program imagery. We generated 30m resolution biomass maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map for each region. With a mean plant %C of 44.1% (n=1384, 95% C.I.=43.99% - 44.37%) we estimated mean aboveground carbon densities (Mg/ha) and total carbon stocks for each wetland type for each region. Louisiana palustrine emergent marshes had the highest C density (2.67 ±0.08 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ±0.06 Mg/ha). This modeling and data synthesis effort will allow for aboveground
Directory of Open Access Journals (Sweden)
Harley Quinto Mosquera
2011-06-01
Full Text Available El estudio de la biomasa aérea (BA de los bosques tropicales es fundamental para entender el balance del C global en el contexto del cambio climático. La BA se cuantificó en un bosque maduro de Salero (Chocó Biogeográfico, mediante ecuaciones diseñadas para bosques húmedos tropicales, a partir de datos de densidad de madera, diámetro (DAP y altura de árboles (con DAP = 10 cm medidos en dos sub-parcelas permanentes ("E" y "U" de 1 ha, las cuales se monitorearon en los años 1998, 2005 y 2008. La BA fue 237,31 t·ha-1, 259,99 t·ha-1 y 217,97 t·ha-1 respectivamente en la sub-parcela "E". Mientras que en la "U" fue de 178,94 t·ha-1y 179,17 t·ha-1 en los años 2005 y 2008; las diferencias de BA a través del tiempo fueron no significativas. Los incrementos promedios anuales de BA de sobrevivientes fueron 4,42 y 3,18 t·ha-1 año-1 en las sub-parcelas "E" y "U" respectivamente. Además, en sub-parcela "E" en condiciones imperturbadas, se presentó una tasa de incremento neto de la BA (TINBA de 2,61 t·ha-1 año-1, en concordancia con la hipótesis del incremento en la BA en los bosques húmedos tropicales. La productividad primaria neta aérea (PPNA en Salero de carbono fue de 5,21 t· ha-1 año-1, por lo tanto los resultados no apoyaron la hipótesis de la disminución en la productividad de los bosques tropicales con el incremento en la precipitación.The study of the aboveground biomass (AB of tropical forests is fundamental to understand the balance of the global C in the context of the climatic change. We quantified the AB in a mature forest of Salero (Chocó Biogeográfico, by means of equations designed for tropical humid forests, starting from data of wooden density, diameter (D and height of trees (with D = 10 cm measured in two permanent sub-parcels (E and U of 1 hectare (ha, which were measured in the years 1998, 2005 and 2008. Inthis years the AB was of 237.31 t·ha-1, 259.99 t·ha-1 and 217.97 t·ha-1 respectively in the E
Li, Hai-Feng; Zeng, Fan-Jiang; Gui, Dong-Wei; An, Gui-Xiang; Liu, Zhen; Zhang, Li-Gang; Liu, Bo
2012-01-01
Taking Cele oasis at the southern fringe of Taklimakan Desert as a case, this paper studied the effects of different disturbances (burning in spring, cutting in spring, and cutting in fall) on the morphological characteristics and aboveground biomass of natural vegetation Alhagi sparsifolia in the ecotone of oasis-desert. Burning in spring decreased the A. sparsifolia plant height, crown width, and biomass significantly, being harmful to the regeneration and growth of the vegetation. Cutting in spring decreased the A. sparsifolia plant height, crown width, and biomass but increased the leaf biomass, thorn length, and thorn diameter, whereas cutting in fall decreased the plant height and crown width but increased the ramification amount and biomass of A. sparsifolia. Moderate cutting in fall could benefit the protection of A. sparsifolia at the southern fringe of Taklimakan Desert.
Lidar-based biomass assessment for the Yukon River Basin
Peterson, B.; Wylie, B. K.; Stoker, J.; Nossov, D.
2010-12-01
lidar data set and are expected to result in improved biomass products for the YRB as they have been shown to be highly predictive of biomass in other biomes. The results of this project represent the first step in a larger effort to collect lidar and field data for various study sites across the YRB for biomass estimations to train large-scale mapping efforts using Landsat imagery and radar data. Bond-Lamberty, B., C. Wang, and S.T. Gower. 2002. Aboveground and belowground biomass and sapwood area allometric equations for six boreal tree species of northern Manitoba. Canadian Journal of Forest Research 32: 1441-1450. Mack, M., K. Treseder, K. Manies, J. Harden, E. Schuur, J. Vogel, J. Randerson, and F.S. Chapin III. 2008. Recovery of Aboveground Plant Biomass and Productivity After Fire in Mesic and Dry Black Spruce Forests of Interior Alaska, Ecosystems v.11:209-225. Yarie, J., E. Kane, and M. Mack. 2007. Aboveground Biomass Equations for the Trees of Interior Alaska. AFES Bulletin 115.
Thapa, R. B.; Watanabe, M.; Motohka, T.; Shiraishi, T.; shimada, M.
2013-12-01
Tropical forests are providing environmental goods and services including carbon sequestration, energy regulation, water fluxes, wildlife habitats, fuel, and building materials. Despite the policy attention, the tropical forest reserve in Southeast Asian region is releasing vast amount of carbon to the atmosphere due to deforestation. Establishing quality forest statistics and documenting aboveground forest carbon stocks (AFCS) are emerging in the region. Airborne and satellite based large area monitoring methods are developed to compliment conventional plot based field measurement methods as they are costly, time consuming, and difficult to implement for large regions. But these methods still require adequate ground measurements for calibrating accurate AFCS model. Furthermore, tropical region comprised of varieties of natural and plantation forests capping higher variability of forest structures and biomass volumes. To address this issue and the needs for ground data, we propose the systematic collection of ground data integrated with airborne light detection and ranging (LiDAR) data. Airborne LiDAR enables accurate measures of vertical forest structure, including canopy height and volume demanding less ground measurement plots. Using an appropriate forest type based LiDAR sampling framework, structural properties of forest can be quantified and treated similar to ground measurement plots, producing locally relevant information to use independently with satellite data sources including synthetic aperture radar (SAR). In this study, we examined LiDAR derived forest parameters with field measured data and developed general and specific AFCS models for tropical forests in central Sumatra. The general model is fitted for all types of natural and plantation forests while the specific model is fitted to the specific forest type. The study region consists of natural forests including peat swamp and dry moist forests, regrowth, and mangrove and plantation forests
Forest biomass carbon stocks and variation in Tibet's carbon-dense forests from 2001 to 2050.
Sun, Xiangyang; Wang, Genxu; Huang, Mei; Chang, Ruiying; Ran, Fei
2016-10-05
Tibet's forests, in contrast to China's other forests, are characterized by primary forests, high carbon (C) density and less anthropogenic disturbance, and they function as an important carbon pool in China. Using the biomass C density data from 413 forest inventory sites and a spatial forest age map, we developed an allometric equation for the forest biomass C density and forest age to assess the spatial biomass C stocks and variation in Tibet's forests from 2001 to 2050. The results indicated that the forest biomass C stock would increase from 831.1 Tg C in 2001 to 969.4 Tg C in 2050, with a net C gain of 3.6 Tg C yr -1 between 2001 and 2010 and a decrease of 1.9 Tg C yr -1 between 2040 and 2050. Carbon tends to allocate more in the roots of fir forests and less in the roots of spruce and pine forests with increasing stand age. The increase of the biomass carbon pool does not promote significant augmentation of the soil carbon pool. Our findings suggest that Tibet's mature forests will remain a persistent C sink until 2050. However, afforestation or reforestation, especially with the larger carbon sink potential forest types, such as fir and spruce, should be carried out to maintain the high C sink capacity.
ROE Carbon Storage - Forest Biomass
This polygon dataset depicts the density of forest biomass in counties across the United States, in terms of metric tons of carbon per square mile of land area. These data were provided in spreadsheet form by the U.S. Department of Agriculture (USDA) Forest Service. To produce the Web mapping application, EPA joined the spreadsheet with a shapefile of U.S. county (and county equivalent) boundaries downloaded from the U.S. Census Bureau. EPA calculated biomass density based on the area of each county polygon. These data sets were converted into a single polygon feature class inside a file geodatabase.
Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie
2018-05-01
Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%-44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all
Understanding forest-derived biomass supply with GIS modelling
DEFF Research Database (Denmark)
Hock, B. K.; Blomqvist, L.; Hall, P.
2012-01-01
distribution, and the cost of delivery as forests are frequently remote from energy users. A GIS-based model was developed to predict supply curves of forest biomass material for a site or group of sites, both now and in the future. The GIS biomass supply model was used to assist the New Zealand Energy...... Efficiency and Conservation Authority's development of a national target for biomass use for industrial heat production, to determine potential forest residue volumes for industrial heat and their delivery costs for 19 processing plants of the dairy company Fonterra, and towards investigating options...
Sustainable use of forest biomass for energy
International Nuclear Information System (INIS)
Stupak Moeller, Inge
2005-01-01
The substitution of biomass for fossil fuels in energy consumption is a measure to mitigate global warming, and political action plans at European and national levels exist for an increased use. The use of forest biomass for energy can imply different economic and environmental advantages and disadvantages for the society, the energy sector and forestry. For the achievement of an increased and sustainable use of forest biomass for energy, the EU 5th Framework project WOOD-EN-MAN aimed at synthesising current knowledge and creating new knowledge within the field
Harvested wood products and carbon sink in a young beech high forest
Directory of Open Access Journals (Sweden)
Pilli R
2008-03-01
Full Text Available According to art. 3.4 of the Kyoto Protocol (KP, Italy has elected forest management as additional human-induced activity to attain the goal of reduction in greenhouse gas emissions. The whole forest area not subjected to afforestation, reforestation or deforestation processes since 1990 will be considered as managed forest. In order to analyse different management strategies, the Carbon-Pro Project, involving 9 partners of the European CADSES area, considered a young beech high forest (ex-coppice, defined as "transitory silvicultural system" as a common case study for the Pre-alps region. Using data collected with forest plans during the period 1983 - 2005, aboveground and belowground forest carbon stock and sink of a specific forest compartment were estimated by the Carbon Stock Method proposed by the IPCC Guidelines. In order to apply this approach 41 trees were cut and a species-specific allometric equation was developed. Considering the aboveground tree biomass, the carbon sink amounts to 1.99 and 1.84 Mg C ha-1 y-1 for the period 1983 - 1994 and 1994 - 2005 respectively. Adding the belowground tree biomass, the estimated sink amounts to 2.59 and 2.39 Mg C ha-1 y-1 for each period. Taking the harvested wood products (firewood, the total carbon sequestration during the second period is 0.16 Mg C ha-1 y-1. The case study highlights the possible rules for the different management strategies. In effect, the utilisation of the entire increase in aboveground biomass as firewood gives an energy substitution effect but, according to the Marrakesh Accords, it cannot be accounted for the KP. On the other hand, an accumulation strategy gives the maximum possible carbon absorption and retention.
Where did the US forest biomass/carbon go?
Christopher William. Woodall
2012-01-01
In Apr. 2012, with the submission of the 1990-2010 US Greenhouse Gas (GHG) Inventory to the United Nations Framework Convention on Climate Change (UNFCCC), the official estimates of aboveground live tree carbon stocks within managed forests of the United States will drop by approximately 14%, compared with last year's inventory. It does not stop there, dead wood...
Directory of Open Access Journals (Sweden)
Tomotsugu Yazaki
2016-11-01
Full Text Available Quantitative evaluations of biomass accumulation after disturbances in forests are crucially important for elucidating and predicting forest carbon dynamics in order to understand the carbon sink/source activities. During early secondary succession, understory vegetation often affects sapling growth. However, reports on biomass recovery in naturally-regenerating sites are limited in Japan. Therefore, we traced annual or biennial changes in plant species, biomass, and net primary production (NPP in a naturally regenerating site in Japan after windthrow and salvage-logging plantation for nine years. The catastrophic disturbance depleted the aboveground biomass (AGB from 90.6 to 2.7 Mg·ha−1, changing understory dominant species from Dryopteris spp. to Rubus idaeus. The mean understory AGB recovered to 4.7 Mg·ha−1 in seven years with the dominant species changing to invasive Solidago gigantea. Subsequently, patches of deciduous trees (mainly Betula spp. recovered whereas the understory AGB decreased. Mean understory NPP increased to 272 g·C·m−2·year−1 within seven years after the disturbance, but decreased thereafter to 189 g·C·m−2·year−1. Total NPP stagnated despite increasing overstory NPP. The biomass accumulation is similar to that of naturally regenerating sites without increase of trees in boreal and temperate regions. Dense ground vegetation and low water and nutrient availability of the soil in the study site restrict the recovery of canopy-forming trees and eventually influence the biomass accumulation.
Torano Caicoya, Astor; Kugler, Florian; Papathanassiou, Kostas; Biber, Peter; Pretzsch, Hans
2010-01-01
One common method to estimate biomass is measuring forest height and applying allometric equations to get forest biomass. Conditions like changing forest density or changing forest structure bias the allometric relations or biomass estimation fails completely. Remote sensing systems like SAR or LIDAR allow to measure vertical structure of forests. In this paper it is investigated whether vertical structure is sensitive to biomass. For this purpose vertical biomass profiles were calculated usi...
Volume and Aboveground Biomass Models for Dry Miombo Woodland in Tanzania
Directory of Open Access Journals (Sweden)
Ezekiel Edward Mwakalukwa
2014-01-01
Full Text Available Tools to accurately estimate tree volume and biomass are scarce for most forest types in East Africa, including Tanzania. Based on a sample of 142 trees and 57 shrubs from a 6,065 ha area of dry miombo woodland in Iringa rural district in Tanzania, regression models were developed for volume and biomass of three important species, Brachystegia spiciformis Benth. (n = 40, Combretum molle G. Don (n = 41, and Dalbergia arbutifolia Baker (n = 37 separately, and for broader samples of trees (28 species, n = 72, shrubs (16 species, n = 32, and trees and shrubs combined (44 species, n = 104. Applied independent variables were log-transformed diameter, height, and wood basic density, and in each case a range of different models were tested. The general tendency among the final models is that the fit improved when height and wood basic density were included. Also the precision and accuracy of the predictions tended to increase from general to species-specific models. Except for a few volume and biomass models developed for shrubs, all models had R2 values of 96–99%. Thus, the models appear robust and should be applicable to forests with similar site conditions, species, and diameter ranges.
Forest biomass carbon stocks and variation in Tibet’s carbon-dense forests from 2001 to 2050
Sun, Xiangyang; Wang, Genxu; Huang, Mei; Chang, Ruiying; Ran, Fei
2016-01-01
Tibet’s forests, in contrast to China’s other forests, are characterized by primary forests, high carbon (C) density and less anthropogenic disturbance, and they function as an important carbon pool in China. Using the biomass C density data from 413 forest inventory sites and a spatial forest age map, we developed an allometric equation for the forest biomass C density and forest age to assess the spatial biomass C stocks and variation in Tibet’s forests from 2001 to 2050. The results indicated that the forest biomass C stock would increase from 831.1 Tg C in 2001 to 969.4 Tg C in 2050, with a net C gain of 3.6 Tg C yr−1 between 2001 and 2010 and a decrease of 1.9 Tg C yr−1 between 2040 and 2050. Carbon tends to allocate more in the roots of fir forests and less in the roots of spruce and pine forests with increasing stand age. The increase of the biomass carbon pool does not promote significant augmentation of the soil carbon pool. Our findings suggest that Tibet’s mature forests will remain a persistent C sink until 2050. However, afforestation or reforestation, especially with the larger carbon sink potential forest types, such as fir and spruce, should be carried out to maintain the high C sink capacity. PMID:27703215
Czech Academy of Sciences Publication Activity Database
Novotná, Kateřina; Klem, Karel; Holub, Petr; Rapantová, Barbora; Urban, Otmar
2016-01-01
Roč. 9, 1-2 (2016), s. 21-30 ISSN 1803-2451 R&D Projects: GA MŠk(CZ) LO1415 Institutional support: RVO:67179843 Keywords : above-ground biomass * drought stress * grassland * UV radiation * precipitation * spectral reflectance * thermal imaging Subject RIV: EH - Ecology, Behaviour
Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates
Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.
2010-12-01
There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.
(abstract) Sensitivity to Forest Biomass Based on Analysis of Scattering Mechanism
Way, JoBea; Bachman, Jennifer E.; Paige, David A.
1993-01-01
The estimation of forest biomass on a global scale is an important input to global climate and carbon cycle models. Remote sensing using synthetic aperture radar offers a means to obtain such a data set. Although it has been clear for some time that radar signals penetrate forest canopies, only recently has it been demonstrated that these signals are indeed sensitive to biomass. Inasmuch as the majority of a forest's biomass is in the trunks, it is important that the radar is sensing the trunk biomass as opposed to the branch or leaf biomass. In this study we use polarimetric AIRSAR P- and L-band data from a variety of forests to determine if the radar penetrates to the trunk by examining the scattering mechanism as determined using van Zyl's scattering interaction model, and the levels at which saturation occurs with respect to sensitivity of radar backscatter to total biomass. In particular, the added sensitivity of P-band relative to L-band is addressed. Results using data from the Duke Forest in North Carolina, the Bonanza Creek Experimental Forest in Alaska, Shasta Forest in California, the Black Forest in Germany, the temporate/boreal transition forests in northern Michigan, and coastal forests along the Oregon Transect will be presented.
Montané, Francesc; Fox, Andrew M.; Arellano, Avelino F.; MacBean, Natasha; Alexander, M. Ross; Dye, Alex; Bishop, Daniel A.; Trouet, Valerie; Babst, Flurin; Hessl, Amy E.; Pederson, Neil; Blanken, Peter D.; Bohrer, Gil; Gough, Christopher M.; Litvak, Marcy E.; Novick, Kimberly A.; Phillips, Richard P.; Wood, Jeffrey D.; Moore, David J. P.
2017-09-01
How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.-iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m-2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m-2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C-LAI relationship in the model did not match the observed leaf C
Veronika Leitold; Michael Keller; Douglas C Morton; Bruce D Cook; Yosio E Shimabukuro
2015-01-01
Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas...
D.C. Bragg; K.M. McElligott
2013-01-01
Sequestration by Arkansas forests removes carbon dioxide from the atmosphere, storing this carbon in biomass that fills a number of critical ecological and socioeconomic functions. We need a better understanding of the contribution of forests to the carbon cycle, including the accurate quantification of tree biomass. Models have long been developed to predict...
Directory of Open Access Journals (Sweden)
Sasan Vafaei
2018-01-01
Full Text Available The main objective of this research is to investigate the potential combination of Sentinel-2A and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite -2 Phased Array type L-band Synthetic Aperture Radar-2 imagery for improving the accuracy of the Aboveground Biomass (AGB measurement. According to the current literature, this kind of investigation has rarely been conducted. The Hyrcanian forest area (Iran is selected as the case study. For this purpose, a total of 149 sample plots for the study area were documented through fieldwork. Using the imagery, three datasets were generated including the Sentinel-2A dataset, the ALOS-2 PALSAR-2 dataset, and the combination of the Sentinel-2A dataset and the ALOS-2 PALSAR-2 dataset (Sentinel-ALOS. Because the accuracy of the AGB estimation is dependent on the method used, in this research, four machine learning techniques were selected and compared, namely Random Forests (RF, Support Vector Regression (SVR, Multi-Layer Perceptron Neural Networks (MPL Neural Nets, and Gaussian Processes (GP. The performance of these AGB models was assessed using the coefficient of determination (R2, the root-mean-square error (RMSE, and the mean absolute error (MAE. The results showed that the AGB models derived from the combination of the Sentinel-2A and the ALOS-2 PALSAR-2 data had the highest accuracy, followed by models using the Sentinel-2A dataset and the ALOS-2 PALSAR-2 dataset. Among the four machine learning models, the SVR model (R2 = 0.73, RMSE = 38.68, and MAE = 32.28 had the highest prediction accuracy, followed by the GP model (R2 = 0.69, RMSE = 40.11, and MAE = 33.69, the RF model (R2 = 0.62, RMSE = 43.13, and MAE = 35.83, and the MPL Neural Nets model (R2 = 0.44, RMSE = 64.33, and MAE = 53.74. Overall, the Sentinel-2A imagery provides a reasonable result while the ALOS-2 PALSAR-2 imagery provides a poor result of the forest AGB estimation. The combination of the Sentinel-2A imagery and the ALOS-2 PALSAR-2
Spatial variation and prediction of forest biomass in a heterogeneous landscape
Institute of Scientific and Technical Information of China (English)
S.Lamsal; D.M.Rizzo; R.K.Meentemeyer
2012-01-01
Large areas assessments of forest biomass distribution are a challenge in heterogeneous landscapes,where variations in tree growth and species composition occur over short distances.In this study,we use statistical and geospatial modeling on densely sampled forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur,California.We estimated biomass in 280 forest plots (one plot per 2.85 km2) and measured an array of ecological (vegetation community type,distance to edge,amount of surrounding non-forest vegetation,soil properties,fire history) and physiographic drivers (elevation,potential soil moisture and solar radiation,proximity to the coast) of tree growth at each plot location.Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 km.Regression tree (RT) models showed that both physiographic and ecological factors influenced biomass distribution.Across randomly selected sample densities (sample size 112 to 280),ecological effects of vegetation community type and distance to forest edge,and physiographic effects of elevation,potentialsoil moisture and solar radiation were the most consistent predictors of biomass.Topographic moisture index and potential solar radiation had a positive effect on biomass,indicating the importance of topographicallymediated energy and moisture on plant growth and biomass accumulation.RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals.Regression kriging model,developed from RT combined with kriging of regression residuals,was used to map biomass across the Big Sur.This study demonstrates how statistical and geospatial modeling can be used to discriminate the relative importance of physiographic and ecologic effects on forest biomass and develop
Forest biomass and Armington elasticities in Europe
International Nuclear Information System (INIS)
Lundmark, Robert; Shahrammehr, Shima
2011-01-01
The purpose of this paper is to provide estimated Armington elasticities for selected European countries and for three forest biomass commodities of main interest in many energy models: roundwood, chips and particles and wood residues. The Armington elasticity is based on the assumption that a specific forest biomass commodity is differentiated by its origin. The statistically significant estimated Armington elasticities range from 0.52 for roundwood in Hungary to approximately 4.53 for roundwood in Estonia. On average, the statistically significant Armington elasticity for chips and particles over all countries is 1.7 and for wood residues and roundwood 1.3 and 1.5, respectively. These elasticities can provide benchmark values for simulation models trying to assess trade patterns of forest biomass commodities and energy policy effects for European countries or for the EU as a whole.
Samec, Pavel; Caha, Jan; Zapletal, Miloš; Tuček, Pavel; Cudlín, Pavel; Kučera, Miloš
2017-12-01
Forest decline is either caused by damage or else by vulnerability due to unfavourable growth conditions or due to unnatural silvicultural systems. Here, we assess forest decline in the Czech Republic (Central Europe) using fuzzy functions, fuzzy sets and fuzzy rating of ecosystem properties over a 1×1km grid. The model was divided into fuzzy functions of the abiotic predictors of growth conditions (F pred including temperature, precipitation, acid deposition, soil data and relative site insolation) and forest biomass receptors (F rec including remote sensing data, density and volume of aboveground biomass, and surface humus chemical data). Fuzzy functions were designed at the limits of unfavourable, undetermined or favourable effects on the forest ecosystem health status. Fuzzy sets were distinguished through similarity in a particular membership of the properties at the limits of the forest status margins. Fuzzy rating was obtained from the least difference of F pred -F rec . Unfavourable F pred within unfavourable F rec indicated chronic damage, favourable F pred within unfavourable F rec indicated acute damage, and unfavourable F pred within favourable F rec indicated vulnerability. The model in the 1×1km grid was validated through spatial intersection with a point field of uniform forest stands. Favourable status was characterised by soil base saturation (BS)>50%, BCC/Al>1, C org >1%, MgO>6g/kg, and nitrogen depositionforests had BS humus 46-60%, BCC/Al 9-20 and NDVI≈0.42. Chronic forest damage occurs in areas with low temperatures, high nitrogen deposition, and low soil BS and C org levels. In the Czech Republic, 10% of forests were considered non-damaged and 77% vulnerable, with damage considered acute in 7% of forests and chronic in 5%. The fuzzy model used suggests that improvement in forest health will depend on decreasing environmental load and restoration concordance between growth conditions and tree species composition. Copyright © 2017 Elsevier
Using aerial photography to estimate wood suitable for charcoal in managed oak forests
Ramírez-Mejía, D.; Gómez-Tagle, A.; Ghilardi, A.
2018-02-01
Mexican oak forests (genus Quercus) are frequently used for traditional charcoal production. Appropriate management programs are needed to ensure their long-term use, while conserving the biodiversity and ecosystem services, and associated benefits. A key variable needed to design these programs is the spatial distribution of standing woody biomass. A state-of-the-art methodology using small format aerial photographs was developed to estimate the total aboveground biomass (AGB) and aboveground woody biomass suitable for charcoal making (WSC) in intensively managed oak forests. We used tree crown area (CAap) measurements from very high-resolution (30 cm) orthorectified small format digital aerial photographs as the predictive variable. The CAap accuracy was validated using field measurements of the crown area (CAf). Allometric relationships between: (a) CAap versus AGB, and (b) CAap versus WSC had a high significance level (R 2 > 0.91, p < 0.0001). This approach shows that it is possible to obtain sound biomass estimates as a function of the crown area derived from digital small format aerial photographs.
Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie
2018-01-01
Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%–44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had
Simulation of the biomass dynamics of Masson pine forest under different management
Institute of Scientific and Technical Information of China (English)
ZHANG Gui-lian; WANG Kai-yun; LIU Xin-wei; PENG Shao-lin
2006-01-01
TREE submodel affiliated with TREEDYN was used to simulate biomass dynamics of Masson pine (Pinus massoniana) forest under different managements (including thinning, clear cutting, combining thinning with clear cutting). The purpose was to represent biomass dynamics involved in its development, which can provide scientific arguments for management of Masson pine forest. The results showed the scenario that 10% or 20% of biomass of the previous year was thinned every five years from 15 to 40 years made total biomass of pine forest increase slowly and it took more time to reach a mature community; If clear cutting and thinning were combined, the case C (clear cutting at 20 years of forest age, thinning 50% of remaining biomass at 30 years of forest age, and thinning 50% of remaining biomass again at 40 years of forest age) was the best scenario which can accelerate speed of development of Masson pine forest and gained better economic values.
Fatoyinbo, Temilola; Feliciano, Emanuelle A.; Lagomasino, David; Kuk Lee, Seung; Trettin, Carl
2018-02-01
Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R 2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha-1 up to 252 Mg ha-1. We suggest the best model
Sean P. Healey; Paul L. Patterson; Sassan S. Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman
2012-01-01
Lidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform "shots," which have been shown to be strongly correlated with aboveground forest...
A dataset of forest biomass structure for Eurasia.
Schepaschenko, Dmitry; Shvidenko, Anatoly; Usoltsev, Vladimir; Lakyda, Petro; Luo, Yunjian; Vasylyshyn, Roman; Lakyda, Ivan; Myklush, Yuriy; See, Linda; McCallum, Ian; Fritz, Steffen; Kraxner, Florian; Obersteiner, Michael
2017-05-16
The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.
Forest biomass as an energy source
P.E. Laks; R.W. Hemingway; A. Conner
1979-01-01
The Task Force on Forest Biomass as an Energy Source was chartered by the Society of American Foresters on September 26, 1977, and took its present form following an amendment to the charter on October 5, 1977. It built upon the findings of two previous task forces, the Task Force on Energy and Forest Resources and the Task Force for Evaluation of the CORRIM Report (...
Keith, Heather; Mackey, Brendan G; Lindenmayer, David B
2009-07-14
From analysis of published global site biomass data (n = 136) from primary forests, we discovered (i) the world's highest known total biomass carbon density (living plus dead) of 1,867 tonnes carbon per ha (average value from 13 sites) occurs in Australian temperate moist Eucalyptus regnans forests, and (ii) average values of the global site biomass data were higher for sampled temperate moist forests (n = 44) than for sampled tropical (n = 36) and boreal (n = 52) forests (n is number of sites per forest biome). Spatially averaged Intergovernmental Panel on Climate Change biome default values are lower than our average site values for temperate moist forests, because the temperate biome contains a diversity of forest ecosystem types that support a range of mature carbon stocks or have a long land-use history with reduced carbon stocks. We describe a framework for identifying forests important for carbon storage based on the factors that account for high biomass carbon densities, including (i) relatively cool temperatures and moderately high precipitation producing rates of fast growth but slow decomposition, and (ii) older forests that are often multiaged and multilayered and have experienced minimal human disturbance. Our results are relevant to negotiations under the United Nations Framework Convention on Climate Change regarding forest conservation, management, and restoration. Conserving forests with large stocks of biomass from deforestation and degradation avoids significant carbon emissions to the atmosphere, irrespective of the source country, and should be among allowable mitigation activities. Similarly, management that allows restoration of a forest's carbon sequestration potential also should be recognized.
Re-evaluation of forest biomass carbon stocks and lessons from the world's most carbon-dense forests
Keith, Heather; Mackey, Brendan G.; Lindenmayer, David B.
2009-01-01
From analysis of published global site biomass data (n = 136) from primary forests, we discovered (i) the world's highest known total biomass carbon density (living plus dead) of 1,867 tonnes carbon per ha (average value from 13 sites) occurs in Australian temperate moist Eucalyptus regnans forests, and (ii) average values of the global site biomass data were higher for sampled temperate moist forests (n = 44) than for sampled tropical (n = 36) and boreal (n = 52) forests (n is number of sites per forest biome). Spatially averaged Intergovernmental Panel on Climate Change biome default values are lower than our average site values for temperate moist forests, because the temperate biome contains a diversity of forest ecosystem types that support a range of mature carbon stocks or have a long land-use history with reduced carbon stocks. We describe a framework for identifying forests important for carbon storage based on the factors that account for high biomass carbon densities, including (i) relatively cool temperatures and moderately high precipitation producing rates of fast growth but slow decomposition, and (ii) older forests that are often multiaged and multilayered and have experienced minimal human disturbance. Our results are relevant to negotiations under the United Nations Framework Convention on Climate Change regarding forest conservation, management, and restoration. Conserving forests with large stocks of biomass from deforestation and degradation avoids significant carbon emissions to the atmosphere, irrespective of the source country, and should be among allowable mitigation activities. Similarly, management that allows restoration of a forest's carbon sequestration potential also should be recognized. PMID:19553199
Kuznetsova, Tatjana; Tilk, Mari; Pärn, Henn; Lukjanova, Aljona; Mandre, Malle
2011-12-01
The investigation was carried out in 8-year-old Scots pine (Pinus sylvestris L.) and lodgepole pine (Pinus contorta var. latifolia Engelm.) plantations on post-mining area, Northeast Estonia. The aim of the study was to assess the suitability of lodgepole pine for restoration of degraded lands by comparing the growth, biomass, and nutrient concentration of studied species. The height growth of trees was greater in the Scots pine stand, but the tree aboveground biomass was slightly larger in the lodgepole pine stand. The aboveground biomass allocation to the compartments did not differ significantly between species. The vertical distribution of compartments showed that 43.2% of the Scots pine needles were located in the middle layer of the crown, while 58.5% of the lodgepole pine needles were in the lowest layer of the crown. The largest share of the shoots and stem of both species was allocated to the lowest layer of the crown. For both species, the highest NPK concentrations were found in the needles and the lowest in the stems. On the basis of the present study results, it can be concluded that the early growth of Scots pine and lodgepole pine on oil shale post-mining landscapes is similar.
Ngoma, Justine; Moors, Eddy; Kruijt, Bart; Speer, James H.; Vinya, Royd; Chidumayo, Emmanuel N.; Leemans, Rik
2018-02-01
Understanding carbon (C) stocks or biomass in forests is important to examine how forests mitigate climate change. To estimate biomass in stems, branches and roots takes intensive fieldwork to uproot, cut and weigh the mass of each component. Different models or equations are also required. Our research focussed on the dry tropical Zambezi teak forests and we studied their structure at three sites following a rainfall gradient in Zambia. We sampled 3558 trees at 42 plots covering a combined area of 15ha. Using data from destructive tree samples, we developed mixed-species biomass models to estimate above ground biomass for small (forests, thereby adversely affecting their mitigating role in climate change.
James E. Smith; Linda S. Heath
2015-01-01
Our approach is based on a collection of models that convert or augment the USDA Forest Inventory and Analysis program survey data to estimate all forest carbon component stocks, including live and standing dead tree aboveground and belowground biomass, forest floor (litter), down deadwood, and soil organic carbon, for each inventory plot. The data, which include...
Stakeholder perspectives on converting forest biomass to energy in Oregon, USA
Energy Technology Data Exchange (ETDEWEB)
Stidham, Melanie; Simon-Brown, Viviane [Department of Forest Ecosystems and Society, College of Forestry, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 (United States)
2011-01-15
Within the state of Oregon, USA, there is considerable interest in the possibility of converting forest biomass to energy. A number of studies have assessed the technical feasibility of forest biomass energy, but few have focused on social aspects, an important consideration in projects involving public forests. This study explores the social context of converting forest biomass to energy, using qualitative research methods. Semi-structured interviews were conducted with forty individuals representing nine different stakeholder groups. Information gained through interviews was used to understand stakeholder views on forest biomass energy, including their perspectives on potential barriers and opportunities in Oregon. Findings indicate the most challenging barrier will be access to long-term, consistent supply. A related challenge is the long history of contention between parties over forest products coming from public lands. However, findings also show that there are many areas of common ground between these groups that have historically been at odds, such as agreement on the necessity of restoration treatments in certain forest types, the by-product of which could be used for biomass generation. Potential conflicts still exist, for instance over projects in mixed conifer forests. Development of policies and projects through inclusive, collaborative approaches could alleviate controversies, potentially allowing more activities to move forward. Information provided by this research creates a foundation for discussions as forest biomass energy becomes an increasingly prominent issue in Oregon, the western USA, and other regions of the world. (author)
Energy Technology Data Exchange (ETDEWEB)
Patrick Gonzalez; Benjamin Kroll; Carlos R. Vargas
2006-01-10
Conversion of tropical forest to agricultural land and pasture has reduced forest extent and the provision of ecosystem services, including watershed protection, biodiversity conservation, and carbon sequestration. Forest conservation and reforestation can restore those ecosystem services. We have assessed forest species patterns, quantified deforestation and reforestation rates, and projected future baseline carbon emissions and removal in Amazon tropical rainforest at La Selva Central, Peru. The research area is a 4800 km{sup 2} buffer zone around the Parque Nacional Yanachaga-Chemillen, Bosque de Proteccion San Matias-San Carlos, and the Reserva Comunal Yanesha. A planned project for the period 2006-2035 would conserve 4000 ha of forest in a proposed 7000 ha Area de Conservacion Municipale de Chontabamba and establish 5600 ha of natural regeneration and 1400 ha of native species plantations, laid out in fajas de enriquecimiento (contour plantings), to reforest 7000 ha of agricultural land. Forest inventories of seven sites covering 22.6 ha in primary forest and 17 sites covering 16.5 ha in secondary forest measured 17,073 trees of diameter {ge} 10 cm. The 24 sites host trees of 512 species, 267 genera, and 69 families. We could not identify the family of 7% of the trees or the scientific species of 21% of the trees. Species richness is 346 in primary forest and 257 in the secondary forest. In primary forest, 90% of aboveground biomass resides in old-growth species. Conversely, in secondary forest, 66% of aboveground biomass rests in successional species. The density of trees of diameter {ge} 10 cm is 366 trees ha{sup -1} in primary forest and 533 trees ha{sup -1} in secondary forest, although the average diameter is 24 {+-} 15 cm in primary forest and 17 {+-} 8 cm in secondary forest. Using Amazon forest biomass equations and wood densities for 117 species, aboveground biomass is 240 {+-} 30 t ha{sup -1} in the primary sites and 90 {+-} 10 t ha{sup -1} in the
ROE Carbon Storage - Forest Biomass
U.S. Environmental Protection Agency — This polygon dataset depicts the density of forest biomass in counties across the United States, in terms of metric tons of carbon per square mile of land area....
Biogeographical patterns of biomass allocation in leaves, stems, and roots in China's forests.
Zhang, Hao; Wang, Kelin; Xu, Xianli; Song, Tongqing; Xu, Yanfang; Zeng, Fuping
2015-11-03
To test whether there are general patterns in biomass partitioning in relation to environmental variation when stand biomass is considered, we investigated biomass allocation in leaves, stems, and roots in China's forests using both the national forest inventory data (2004-2008) and our field measurements (2011-2012). Distribution patterns of leaf, stem, and root biomass showed significantly different trends according to latitude, longitude, and altitude, and were positively and significantly correlated with stand age and mean annual precipitation. Trade-offs among leaves, stems, and roots varied with forest type and origin and were mainly explained by stand biomass. Based on the constraints of stand biomass, biomass allocation was also influenced by forest type, origin, stand age, stand density, mean annual temperature, precipitation, and maximum temperature in the growing season. Therefore, after stand biomass was accounted for, the residual variation in biomass allocation could be partially explained by stand characteristics and environmental factors, which may aid in quantifying carbon cycling in forest ecosystems and assessing the impacts of climate change on forest carbon dynamics in China.
Directory of Open Access Journals (Sweden)
Diane Fielding
2012-01-01
Full Text Available Woody biomass has been identified as an important renewable energy source capable of offsetting fossil fuel use. The potential environmental impacts associated with using woody biomass for energy have spurred development of biomass harvesting guidelines (BHGs in some states and proposals for BHGs in others. We examined stakeholder opinions about BHGs through 60 semistructured interviews with key participants in the North Carolina, USA, forest business sector—forest managers, loggers, and forest landowners. Respondents generally opposed requirements for new BHGs because guidelines added to best management practices (BMPs. Most respondents believed North Carolina’s current BMPs have been successful and sufficient in protecting forest health; biomass harvesting is only an additional component to harvesting with little or no modification to conventional harvesting operations; and scientific research does not support claims that biomass harvesting negatively impacts soil, water quality, timber productivity, or wildlife habitat. Some respondents recognized possible benefits from the implementation of BHGs, which included reduced site preparation costs and increases in proactive forest management, soil quality, and wildlife habitat. Some scientific literature suggests that biomass harvests may have adverse site impacts that require amelioration. The results suggest BHGs will need to be better justified for practitioners based on the scientific literature or linked to demand from new profitable uses or subsidies to offset stakeholder perceptions that they create unnecessary costs.
Directory of Open Access Journals (Sweden)
F. Montané
2017-09-01
Full Text Available How carbon (C is allocated to different plant tissues (leaves, stem, and roots determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI measurements to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM, the Community Land Model (CLM4.5. We ran CLM4.5 for nine temperate (including evergreen and deciduous forests in North America between 1980 and 2013 using four different C allocation schemes: i. dynamic C allocation scheme (named "D-CLM4.5" with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP; ii. an alternative dynamic C allocation scheme (named "D-Litton", where, similar to (i, C allocation is a dynamic function of annual NPP, but unlike (i includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen" and the other of observations in deciduous forests (named "F-Deciduous". D-CLM4.5 generally overestimated gross primary production (GPP and ecosystem respiration, and underestimated net ecosystem exchange (NEE. In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m−2 for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011 was highly underestimated (between 1222 and 7557 g C m−2 for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the
Yang, Da; He, Hong-shi; Wu, Zhi-wei; Liang, Yu; Huang, Chao; Luo, Xu; Xiao, Jiang-tao; Zhang, Qing-long
2015-02-01
Based on the field inventory data, the aboveground deadwood debris carbon storage under different fire severities was analyzed in Huzhong forest region of Great Xing' an Mountains. The results showed that the fire severity had a significant effect on aboveground deadwood debris carbon storage. The deadwood debris carbon storage was in the order of high-severity > low-severity > unburned in Larix gmelinii stands, and mixed conifer-broadleaf stands ( L. gmelinii and Betula platyphylla), and in the order of high severity > unburned > low-severity in B. platyphylla stands. Fire disturbance significantly changed the component percentage of the deadwood debris carbon storage. The component percentage of snags increased and litter decreased with the increasing fire severity. Logs and stumps did not change significantly with the increasing fire severity. The spatial variation of deadwood debris carbon storage in forests burned with low-severity fire was higher than that in unburned forests. The spatial variation of deadwood debris carbon storage with high-severity fires was lowest. This spatial variation needed to be accounted when calculating forest deadwood debris carbon storage.
Fang, Jingyun; Guo, Zhaodi; Hu, Huifeng; Kato, Tomomichi; Muraoka, Hiroyuki; Son, Yowhan
2014-06-01
Forests play an important role in regional and global carbon (C) cycles. With extensive afforestation and reforestation efforts over the last several decades, forests in East Asia have largely expanded, but the dynamics of their C stocks have not been fully assessed. We estimated biomass C stocks of the forests in all five East Asian countries (China, Japan, North Korea, South Korea, and Mongolia) between the 1970s and the 2000s, using the biomass expansion factor method and forest inventory data. Forest area and biomass C density in the whole region increased from 179.78 × 10(6) ha and 38.6 Mg C ha(-1) in the 1970s to 196.65 × 10(6) ha and 45.5 Mg C ha(-1) in the 2000s, respectively. The C stock increased from 6.9 Pg C to 8.9 Pg C, with an averaged sequestration rate of 66.9 Tg C yr(-1). Among the five countries, China and Japan were two major contributors to the total region's forest C sink, with respective contributions of 71.1% and 32.9%. In China, the areal expansion of forest land was a larger contributor to C sinks than increased biomass density for all forests (60.0% vs. 40.0%) and for planted forests (58.1% vs. 41.9%), while the latter contributed more than the former for natural forests (87.0% vs. 13.0%). In Japan, increased biomass density dominated the C sink for all (101.5%), planted (91.1%), and natural (123.8%) forests. Forests in South Korea also acted as a C sink, contributing 9.4% of the total region's sink because of increased forest growth (98.6%). Compared to these countries, the reduction in forest land in both North Korea and Mongolia caused a C loss at an average rate of 9.0 Tg C yr(-1), equal to 13.4% of the total region's C sink. Over the last four decades, the biomass C sequestration by East Asia's forests offset 5.8% of its contemporary fossil-fuel CO2 emissions. © 2014 John Wiley & Sons Ltd.
Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data
Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.
2016-01-01
Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.
Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II
DeJager, Nathan R.; Drohan, Patrick J.; Miranda, Brian M.; Sturtevant, Brian R.; Stout, Susan L.; Royo, Alejandro; Gustafson, Eric J.; Romanski, Mark C.
2017-01-01
Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.
International Nuclear Information System (INIS)
Vang Rasmussen, Laura; Rasmussen, Kjeld; Birch-Thomsen, Torben; Kristensen, Søren B.P.; Traoré, Oumar
2012-01-01
Increasing energy use and the need to mitigate climate change make production of liquid biofuels a high priority. Farmers respond worldwide to this increasing demand by converting forests and grassland into biofuel crops, but whether biofuels offer carbon savings depends on the carbon emissions that occur when land use is changed to biofuel crops. This paper reports the results of a study on cassava-based bioethanol production undertaken in the Sikasso region in Southern Mali. The paper outlines the estimated impacts on above-ground carbon stocks when land use is changed to increase cassava production. The results show that expansion of cassava production for bioethanol will most likely lead to the conversion of fallow areas to cassava. A land use change from fallow to cassava creates a reduction in the above-ground carbon stocks in the order of 4–13 Mg C ha −1 , depending on (a) the age of the fallow, (b) the allometric equation used and (c) whether all trees are removed or the larger, useful trees are preserved. This ‘carbon debt’ associated with the above-ground biomass loss would take 8–25 years to repay if fossil fuels are replaced with cassava-based bioethanol. - Highlights: ► Demands for biofuels make production of cassava-based bioethanol a priority. ► Farmers in Southern Mali are likely to convert fallow areas to cassava production. ► Converting fallow to cassava creates reductions in above-ground carbon stocks. ► Estimates of carbon stock reductions include that farmers preserve useful trees. ► The carbon debt associated with above-ground biomass loss takes 8–25 years to repay.
Biomass and carbon pools of disturbed riparian forests
Laura A. B. Giese; W. M. Aust; Randall K. Kolka; Carl C. Trettin
2003-01-01
Quantification of carbon pools as affected by forest age/development can facilitate riparian restoration and increase awareness of the potential for forests to sequester global carbon. Riparian forest biomass and carbon pools were quantified for four riparian forests representing different seral stages in the South Carolina Upper Coastal Plain. Three of the riparian...
Spatio-temporal changes in biomass carbon sinks in China's forests from 1977 to 2008.
Guo, Zhaodi; Hu, Huifeng; Li, Pin; Li, Nuyun; Fang, Jingyun
2013-07-01
Forests play a leading role in regional and global carbon (C) cycles. Detailed assessment of the temporal and spatial changes in C sinks/sources of China's forests is critical to the estimation of the national C budget and can help to constitute sustainable forest management policies for climate change. In this study, we explored the spatio-temporal changes in forest biomass C stocks in China between 1977 and 2008, using six periods of the national forest inventory data. According to the definition of the forest inventory, China's forest was categorized into three groups: forest stand, economic forest, and bamboo forest. We estimated forest biomass C stocks for each inventory period by using continuous biomass expansion factor (BEF) method for forest stands, and the mean biomass density method for economic and bamboo forests. As a result, China's forests have accumulated biomass C (i.e., biomass C sink) of 1896 Tg (1 Tg=10(12) g) during the study period, with 1710, 108 and 78 Tg C in forest stands, and economic and bamboo forests, respectively. Annual forest biomass C sink was 70.2 Tg C a(-1), offsetting 7.8% of the contemporary fossil CO2 emissions in the country. The results also showed that planted forests have functioned as a persistent C sink, sequestrating 818 Tg C and accounting for 47.8% of total C sink in forest stands, and that the old-, mid- and young-aged forests have sequestrated 930, 391 and 388 Tg C from 1977 to 2008. Our results suggest that China's forests have a big potential as biomass C sink in the future because of its large area of planted forests with young-aged growth and low C density.
The relative contributions of forest growth and areal expansion to forest biomass carbon
P. Li; J. Zhu; H. Hu; Z. Guo; Y. Pan; R. Birdsey; J. Fang
2016-01-01
Forests play a leading role in regional and global terrestrial carbon (C) cycles. Changes in C sequestration within forests can be attributed to areal expansion (increase in forest area) and forest growth (increase in biomass density). Detailed assessment of the relative contributions of areal expansion and forest growth to C sinks is crucial to reveal the mechanisms...
Babst, Flurin; Bouriaud, Olivier; Papale, Dario; Gielen, Bert; Janssens, Ivan A; Nikinmaa, Eero; Ibrom, Andreas; Wu, Jian; Bernhofer, Christian; Köstner, Barbara; Grünwald, Thomas; Seufert, Günther; Ciais, Philippe; Frank, David
2014-03-01
• Attempts to combine biometric and eddy-covariance (EC) quantifications of carbon allocation to different storage pools in forests have been inconsistent and variably successful in the past. • We assessed above-ground biomass changes at five long-term EC forest stations based on tree-ring width and wood density measurements, together with multiple allometric models. Measurements were validated with site-specific biomass estimates and compared with the sum of monthly CO₂ fluxes between 1997 and 2009. • Biometric measurements and seasonal net ecosystem productivity (NEP) proved largely compatible and suggested that carbon sequestered between January and July is mainly used for volume increase, whereas that taken up between August and September supports a combination of cell wall thickening and storage. The inter-annual variability in above-ground woody carbon uptake was significantly linked with wood production at the sites, ranging between 110 and 370 g C m(-2) yr(-1) , thereby accounting for 10-25% of gross primary productivity (GPP), 15-32% of terrestrial ecosystem respiration (TER) and 25-80% of NEP. • The observed seasonal partitioning of carbon used to support different wood formation processes refines our knowledge on the dynamics and magnitude of carbon allocation in forests across the major European climatic zones. It may thus contribute, for example, to improved vegetation model parameterization and provides an enhanced framework to link tree-ring parameters with EC measurements. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.
Boreal forest biomass classification with TanDEM-X
Torano Caicoya, Astor; Kugler, Florian; Papathanassiou, Kostas; Hajnsek, Irena
2013-01-01
High spatial resolution X-band interferometric SAR data from the TanDEM-X, in the operational DEM generation mode, are sensitive to forest structure and can therefore be used for thematic boreal forest classification of forest environments. The interferometric coherence in absence of temporal decorrelation depends strongly on forest height and structure. Due to the rather homogenous structure of boreal forest, forest biomass can be derived from forest height, on the basis of allometric equati...
Price, B; Gomez, A; Mathys, L; Gardi, O; Schellenberger, A; Ginzler, C; Thürig, E
2017-03-01
Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R 2 of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.
Hyperspectral forest monitoring and imaging implications
Goodenough, David G.; Bannon, David
2014-05-01
The forest biome is vital to the health of the earth. Canada and the United States have a combined forest area of 4.68 Mkm2. The monitoring of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of improved information products to land managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory (major forest species), forest health, foliar biochemistry, biomass, and aboveground carbon. Operationally there is a requirement for a mix of airborne and satellite approaches. This paper surveys some methods and results in hyperspectral sensing of forests and discusses the implications for space initiatives with hyperspectral sensing
Tropical forest plantation biomass estimation using RADARSAT-SAR and TM data of south china
Wang, Chenli; Niu, Zheng; Gu, Xiaoping; Guo, Zhixing; Cong, Pifu
2005-10-01
Forest biomass is one of the most important parameters for global carbon stock model yet can only be estimated with great uncertainties. Remote sensing, especially SAR data can offers the possibility of providing relatively accurate forest biomass estimations at a lower cost than inventory in study tropical forest. The goal of this research was to compare the sensitivity of forest biomass to Landsat TM and RADARSAT-SAR data and to assess the efficiency of NDVI, EVI and other vegetation indices in study forest biomass based on the field survey date and GIS in south china. Based on vegetation indices and factor analysis, multiple regression and neural networks were developed for biomass estimation for each species of the plantation. For each species, the better relationships between the biomass predicted and that measured from field survey was obtained with a neural network developed for the species. The relationship between predicted and measured biomass derived from vegetation indices differed between species. This study concludes that single band and many vegetation indices are weakly correlated with selected forest biomass. RADARSAT-SAR Backscatter coefficient has a relatively good logarithmic correlation with forest biomass, but neither TM spectral bands nor vegetation indices alone are sufficient to establish an efficient model for biomass estimation due to the saturation of bands and vegetation indices, multiple regression models that consist of spectral and environment variables improve biomass estimation performance. Comparing with TM, a relatively well estimation result can be achieved by RADARSAT-SAR, but all had limitations in tropical forest biomass estimation. The estimation results obtained are not accurate enough for forest management purposes at the forest stand level. However, the approximate volume estimates derived by the method can be useful in areas where no other forest information is available. Therefore, this paper provides a better
Aboveground stock of biomass and organic carbon in stands of Pinus taeda L.
Directory of Open Access Journals (Sweden)
Luciano Farinha Watzlawick
2013-09-01
Full Text Available This study aimed to estimate biomass and organic carbon in stands of Pinus taeda L. at different ages (14, 16, 19, 21, 22, 23 and 32 years and located in the municipality of General Carneiro (PR. In order to estimate biomass and organic carbon in different tree components (needles, live branches, dead branches, bark and stem wood, the destructive quantification method was used in which seven trees from each age category were randomly sampled across the stand. Stocks of biomass and organic carbon were found to vary between the different age categories, mainly as a result of existing dissimilarities between ages in association with forest management practices such as thinning, pruning and tree density per hectare.
El Masri, Bassil
2011-12-01
Modeling terrestrial ecosystem functions and structure has been a subject of increasing interest because of the importance of the terrestrial carbon cycle in global carbon budget and climate change. In this study, satellite data were used to estimate gross primary production (GPP), evapotranspiration (ET) for two deciduous forests: Morgan Monroe State forest (MMSF) in Indiana and Harvard forest in Massachusetts. Also, above-ground biomass (AGB) was estimated for the MMSF and the Howland forest (mixed forest) in Maine. Surface reflectance and temperature, vegetation indices, soil moisture, tree height and canopy area derived from the Moderate Resolution Imagining Spectroradiometer (MODIS), the Advanced Microwave Scanning Radiometer (AMRS-E), LIDAR, and aerial imagery respectively, were used for this purpose. These variables along with others derived from remotely sensed data were used as inputs variables to process-based models which estimated GPP and ET and to a regression model which estimated AGB. The process-based models were BIOME-BGC and the Penman-Monteith equation. Measured values for the carbon and water fluxes obtained from the Eddy covariance flux tower were compared to the modeled GPP and ET. The data driven methods produced good estimation of GPP and ET with an average root mean square error (RMSE) of 0.17 molC/m2 and 0.40 mm/day, respectively for the MMSF and the Harvard forest. In addition, allometric data for the MMSF were used to develop the regression model relating AGB with stem volume. The performance of the AGB regression model was compared to site measurements using remotely sensed data for the MMSF and the Howland forest where the model AGB RMSE ranged between 2.92--3.30 Kg C/m2. Sensitivity analysis revealed that improvement in maintenance respiration estimation and remotely sensed maximum photosynthetic activity as well as accurate estimate of canopy resistance will result in improved GPP and ET predictions. Moreover, AGB estimates were
High-biomass forests of the Pacific Northwest: who manages them and how much is protected?
Krankina, Olga N; DellaSala, Dominick A; Leonard, Jessica; Yatskov, Mikhail
2014-07-01
To examine ownership and protection status of forests with high-biomass stores (>200 Mg/ha) in the Pacific Northwest (PNW) region of the United States, we used the latest versions of publicly available datasets. Overlay, aggregation, and GIS-based computation of forest area in broad biomass classes in the PNW showed that the National Forests contained the largest area of high-biomass forests (48.4 % of regional total), but the area of high-biomass forest on private lands was important as well (22.8 %). Between 2000 and 2008, the loss of high-biomass forests to fire on the National Forests was 7.6 % (236,000 ha), while the loss of high-biomass forest to logging on private lands (364,000 ha) exceeded the losses to fire across all ownerships. Many remaining high-biomass forest stands are vulnerable to future harvest as only 20 % are strictly protected from logging, while 26 % are not protected at all. The level of protection for high-biomass forests varies by state, for example, 31 % of all high-biomass federal forests in Washington are in high-protection status compared to only 9 % in Oregon. Across the conterminous US, high-biomass forest covers forest land and the PNW region holds 56.8 % of this area or 5.87 million ha. Forests with high-biomass stores are important to document and monitor as they are scarce, often threatened by harvest and development, and their disturbance including timber harvest results in net C losses to the atmosphere that can take a new generation of trees many decades or centuries to offset.
BIOMASS AND MICROBIAL ACTIVITY UNDER DIFFERENT FOREST COVERS
Directory of Open Access Journals (Sweden)
Rafael Malfitano Braga
2016-06-01
Full Text Available This study evaluated the soil fertility, biomass and microbial activity of the soil under forest cover of Eucalyptus grandis, Eucalyptus pilularis, Eucalyptus cloeziana and Corymbia maculata; Pinus Caribbean var. hondurensis, 40 years old, and a fragment of Semideciduous Forest, located on the campus of the Federal University of Lavras. In soil samples collected in the 0-5 cm layer were determined fertility parameters, basal respiration and microbial biomass carbon. The results showed that for the species E. grandis and E. cloeziana the carbon of biomass microbial content was higher than for any other ecosystem evaluated, and equal to those observed under native forest. In contrast, the ground under Pinus had the lowest microbiological indexes. Under C. maculata and E. pilularis the contents were intermediate for this parameter. The basal respiration of all ecosystems was equal. The fertility level was very low in all types of evaluated vegetation.
Biomass estimation in forest ecosystems - a review | Wakawa ...
African Journals Online (AJOL)
Forest ecosystems plays an important role in global warming serving as both sink and source of one of the prominent green house gases, carbon dioxide (CO2). Biomass estimation in forest ecosystems is an important aspect of forest management processes aimed at ensuring sustainability. The choice of appropriate ...
Economic approach to assess the forest carbon implications of biomass energy.
Daigneault, Adam; Sohngen, Brent; Sedjo, Roger
2012-06-05
There is widespread concern that biomass energy policy that promotes forests as a supply source will cause net carbon emissions. Most of the analyses that have been done to date, however, are biological, ignoring the effects of market adaptations through substitution, net imports, and timber investments. This paper uses a dynamic model of forest and land use management to estimate the impact of United States energy policies that emphasize the utilization of forest biomass on global timber production and carbon stocks over the next 50 years. We show that when market factors are included in the analysis, expanded demand for biomass energy increases timber prices and harvests, but reduces net global carbon emissions because higher wood prices lead to new investments in forest stocks. Estimates are sensitive to assumptions about whether harvest residues and new forestland can be used for biomass energy and the demand for biomass. Restricting biomass energy to being sourced only from roundwood on existing forestland can transform the policy from a net sink to a net source of emissions. These results illustrate the importance of capturing market adjustments and a large geographic scope when measuring the carbon implications of biomass energy policies.
Biogeographical patterns of biomass allocation in leaves, stems, and roots in China’s forests
Zhang, Hao; Wang, Kelin; Xu, Xianli; Song, Tongqing; Xu, Yanfang; Zeng, Fuping
2015-01-01
To test whether there are general patterns in biomass partitioning in relation to environmental variation when stand biomass is considered, we investigated biomass allocation in leaves, stems, and roots in China’s forests using both the national forest inventory data (2004–2008) and our field measurements (2011–2012). Distribution patterns of leaf, stem, and root biomass showed significantly different trends according to latitude, longitude, and altitude, and were positively and significantly correlated with stand age and mean annual precipitation. Trade-offs among leaves, stems, and roots varied with forest type and origin and were mainly explained by stand biomass. Based on the constraints of stand biomass, biomass allocation was also influenced by forest type, origin, stand age, stand density, mean annual temperature, precipitation, and maximum temperature in the growing season. Therefore, after stand biomass was accounted for, the residual variation in biomass allocation could be partially explained by stand characteristics and environmental factors, which may aid in quantifying carbon cycling in forest ecosystems and assessing the impacts of climate change on forest carbon dynamics in China. PMID:26525117
Estimating forest biomass and volume using airborne laser data
Nelson, Ross; Krabill, William; Tonelli, John
1988-01-01
An airborne pulsed laser system was used to obtain canopy height data over a southern pine forest in Georgia in order to predict ground-measured forest biomass and timber volume. Although biomass and volume estimates obtained from the laser data were variable when compared with the corresponding ground measurements site by site, the present models are found to predict mean total tree volume within 2.6 percent of the ground value, and mean biomass within 2.0 percent. The results indicate that species stratification did not consistently improve regression relationships for four southern pine species.
Estimating above-ground biomass on mountain meadows and pastures through remote sensing
Barrachina, M.; Cristóbal, J.; Tulla, A. F.
2015-06-01
Extensive stock-breeding systems developed in mountain areas like the Pyrenees are crucial for local farming economies and depend largely on above-ground biomass (AGB) in the form of grass produced on meadows and pastureland. In this study, a multiple linear regression analysis technique based on in-situ biomass collection and vegetation and wetness indices derived from Landsat-5 TM data is successfully applied in a mountainous Pyrenees area to model AGB. Temporal thoroughness of the data is ensured by using a large series of images. Results of on-site AGB collection show the importance for AGB models to capture the high interannual and intraseasonal variability that results from both meteorological conditions and farming practices. AGB models yield best results at midsummer and end of summer before mowing operations by farmers, with a mean R2, RMSE and PE for 2008 and 2009 midsummer of 0.76, 95 g m-2 and 27%, respectively; and with a mean R2, RMSE and PE for 2008 and 2009 end of summer of 0.74, 128 g m-2 and 36%, respectively. Although vegetation indices are a priori more related with biomass production, wetness indices play an important role in modeling AGB, being statistically selected more frequently (more than 50%) than other traditional vegetation indexes (around 27%) such as NDVI. This suggests that middle infrared bands are crucial descriptors of AGB. The methodology applied in this work compares favorably with other works in the literature, yielding better results than those works in mountain areas, owing to the ability of the proposed methodology to capture natural and anthropogenic variations in AGB which are the key to increasing AGB modeling accuracy.
Ouimette, A.; Ollinger, S. V.; Hobbie, E. A.; Lepine, L. C.; Stephens, R.; Rowe, R.; Vadeboncoeur, M. A.; Tumber-Davila, S. J.
2017-12-01
Species composition and resource availability exert a strong influence on the dynamics of carbon allocation among different forest ecosystem components. Recent work in temperate forests has highlighted a tradeoff between carbon allocation to aboveground woody tissues (access to light), and belowground to fine roots (access to soil nutrients). Although root-associated mycorrhizal fungi are crucial for N acquisition and can receive 20% or more of annual net primary production, most studies fail to explicitly include carbon allocation to mycorrhizal fungi. In part, this is due to the inherent difficulties in accurately quantifying fungal production. We took several approaches to quantify production of mycorrhizal fungi, including a carbon budget approach and isotopic techniques. Here we present data on patterns of carbon allocation to aboveground (wood and foliar production), and belowground components (production of fine roots and mycorrhizal fungi), across temperate forest stands spanning a range of nitrogen availability and species composition. We found that as the proportion of conifer species decreased, and stand nitrogen availability increased, both the absolute amount and the fraction of net primary production increased for foliage, aboveground wood, and fine roots ("a rising tide lifts all boats"). While allocation to plant pools increased, allocation to mycorrhizal fungi significantly decreased with decreasing conifer dominance and increasing soil nitrogen availability. We did not find a strong trade-off between carbon allocation to fine roots and aboveground wood or foliage. Instead, a negative relationship is seen between allocation to mycorrhizal fungi and other plant pools. Effort to estimate carbon allocation to mycorrhizal fungi is important for gaining a more complete understanding of how ecosystems respond to changes in growth-limiting resources.
Directory of Open Access Journals (Sweden)
Razi Ahmed
2013-06-01
Full Text Available Estimates of above ground biomass density in forests are crucial for refining global climate models and understanding climate change. Although data from field studies can be aggregated to estimate carbon stocks on global scales, the sparsity of such field data, temporal heterogeneity and methodological variations introduce large errors. Remote sensing measurements from spaceborne sensors are a realistic alternative for global carbon accounting; however, the uncertainty of such measurements is not well known and remains an active area of research. This article describes an effort to collect field data at the Harvard and Howland Forest sites, set in the temperate forests of the Northeastern United States in an attempt to establish ground truth forest biomass for calibration of remote sensing measurements. We present an assessment of the quality of ground truth biomass estimates derived from three different sets of diameter-based allometric equations over the Harvard and Howland Forests to establish the contribution of errors in ground truth data to the error in biomass estimates from remote sensing measurements.
Forest biomass resources and utilization in China
African Journals Online (AJOL)
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environmental benefits may result from using forest biomass for energy rather than fossil fuels. ... nuclear energy. Therefore, one of the most urgent pro- blems the Chinese government faces is to build a safe, economic, clean and sustainable energy supply system, ... Forest bioenergy is the use of renewable forestry.
Wenli Huang; Anu Swatantran; Kristofer Johnson; Laura Duncanson; Hao Tang; Jarlath O' Neil Dunne; George Hurtt; Ralph Dubayah
2015-01-01
Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-...
Forest biomass and wood waste resources
K. Skog; P. Lebow; D.. Dykstra; P.. Miles; B.J. Stokes; R.D. Perlack; M. Buford; J. Barbour; D. McKeever
2011-01-01
This chapter provides estimates of forest biomass and wood waste quantities, as well as roadside costs (i.e., supply curves) for each county in the contiguous United States. Roadside price is the price a buyer pays for wood chips at a roadside in the forest, at a processing mill location in the case of mill residue, or at a landfill for urban wood wastes prior to any...
Exploration of factors limiting biomass estimation by polarimetric radar in tropical forests
Quiñones Fernández, M.J.; Hoekman, D.H.
2004-01-01
Direct inversion of radar return signals for forest biomass estimation is limited by signal saturation at medium biomass levels (roughly 150 ton/ha for P-band). Disturbing factors such as forest structural differences-and, notably, at low biomass levels, terrain roughness, and soil moisture
Inference for lidar-assisted estimation of forest growing stock volume
Ronald E. McRoberts; Erik Næsset; Terje. Gobakken
2013-01-01
Estimates of growing stock volume are reported by the national forest inventories (NFI) of most countries and may serve as the basis for aboveground biomass and carbon estimates as required by an increasing number of international agreements. The probability-based (design-based) statistical estimators traditionally used by NFIs to calculate estimates are generally...
Energy Technology Data Exchange (ETDEWEB)
Shanmughavel, P.; Zheng Zheng; Sha Liqing; Cao Min [Chinese Academy of Sciences, Kunming (China). Dept. of Forest Ecology
2001-07-01
The aim of this research was to study the forest community structure, tree species diversity and biomass production of a tropical seasonal rain forest in Xishuangbanna, southwest China. The community structure showed a diversified species composition and supported many species of economic significance. This tropical rain forest in closely related to Malaysian forests. The biomass and its distribution were studied using standard regression analysis and the clear-cut method for shrubs and herbs. The total biomass was 360.9 t/ha and its allocation in different layers was: tree layer 352.5 t/ha, shrub layer 4.7 t/ha, liana 3.1 t/ha and herb layer 0.5 t/ha. Most of the biomass was concentrated in the trees: stem 241.2 t/ha, root 69.6 t/ha, branch 37.2 t/ha and leaves 4.3 t/ha. The DBH class allocation of the tree biomass was concentrated in the middle DBH class. The biomass of six DBH classes from 20 to 80 cm was 255.4 t/ha. There are twenty-six species with biomass over 0.5% of the total biomass of the tree layer, and three species with biomass over 5%, i.e., Pometia tomentosa, Barringtonia macrostachya (5.4%) and Terminalia myriocarpa (5.2%). Data on stem, branch, leaves and root of the individual tree species were used to develop regression models. D{sup 2}H was found to be the best estimator of the biomass in this tropical rain forest. However, higher biomass figures have been reported from tropical forests elsewhere e.g., 415-520 t/ha in the tropical forests of Cambodia, the tropical moist mixed dipterocarp forests, and the tropical moist logged moist evergreen-high, medium, and low yield forests of Sri Lanka. In some forests, lower accumulation of biomass was reported, e.g., 10-295 t/ha in the tropical moist forests of Bangladesh, the tropical moist dense forest of Cambodia, the tropical dry forests of India, the tropical moist forests of Peninsular-Malaysia, the tropical moist mixed dipterocarp forests of Sarawak-Malaysia, the tropical evergreen forests of
Duveneck, Matthew J; Scheller, Robert M
2015-09-01
Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000-2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-as-usual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have
Grassland Aboveground Biomass in Inner Mongolia: Dynamics (2001-2016) and Driving force
Li, F.; Zeng, Y.; Chen, J.; Wu, B.
2017-12-01
Plant biomass is the most critical measure of carbon stored in an ecosystem, yet it remains imprecisely modeled for many terrestrial biomes. This lack of modeling capacity for biomass and its change through time and space has impeded scientists from making headway concerning issues in the geographic and social sciences. Satellite remote sensing techniques excel at detecting changes in the Earth's surface; however, accurate estimates of biomass for the heterogeneous biome landscapes based on remote sensing techniques are few and far between, which has led to many repetitive studies. Here, we argued that our ability to assess biomass in a heterogeneous landscape using satellite remote sensing techniques would be effectively enhanced through a stratification of landscapes, i.e homogenizing landscapes. Specifically, above-ground biomass (AGB) for an extended heterogeneous grassland biome over the entirety of Inner Mongolia during the past 16 years (2001-2016) was explored using remote sensing time series data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Massive and extensive in-situ measurement AGB data and pure vegetation index (PVI) models, developed from normal remote sensing vegetation indices such as the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI), were highlighted in the accomplishment of this study. Taking into full consideration the landscape heterogeneity for the grassland biome over Inner Mongolia, we achieved a series of AGB models with high R2 (>0.85) and low RMSE ( 20.85 g/m2). The total average amount of fresh AGB for the entirety of Inner Mongolia grasslands over the past 16 years was estimated as 87 Tg with an inter-annual standard deviation of 9 Tg. Overall, the grassland AGB for Inner Mongolia increased sporadically. We found that the dynamics of AGB in the grassland biome of Inner Mongolia were substantially dominated by variation in precipitation despite the accommodation of a huge
Woodam Chung; Paul Evangelista; Nathaniel Anderson; Anthony Vorster; Hee Han; Krishna Poudel; Robert Sturtevant
2017-01-01
The recent mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic has affected millions of hectares of conifer forests in the Rocky Mountains. Land managers are interested in using biomass from beetle-killed trees for bioenergy and biobased products, but they lack adequate information to accurately estimate biomass in stands with heavy mortality. We...
Forest succession in the Upper Rio Negro of Colombia and Venezuela
International Nuclear Information System (INIS)
Saldarriaga, J.G.; West, D.C.; Tharp, M.L.
1986-11-01
Woody vegetation from 23 forest stands along the Upper Rio Negro of Venezuela and Colombia was sampled in 1982 to examine the hypothesis that the Amazon forest has been largely undisturbed since the Pleistocene, to quantify vegetation development during different stages of succession following agricultural development, and to determine the time required for a successional stand to become a mature forest. The ubiquitousness of charcoal in the tierra firme forest indicated the presence of fire associated with extreme dry periods and human disturbances. Changes in species composition, vegetation structure, and woody biomass were studied on 19 abandoned farms and four mature forest stands. Living and dead biomass for the tress and their components was determined by regression equations developed from measurements of harvested trees. The rate of recovery of floristic composition, structure, and biomass following disturbance is relatively slow. Aboveground dead biomass remained high 14 years after the forest was disturbed by the agricultural practices. The lowest dead biomass is reached 20 years after abandonment, and the largest values are found in mature forests. Data analysis of 80-year-old stands showed that the species composition approached that of a mature forest. Approximately 140 to 200 years was required for an abandoned farm to attain the basal area and biomass values comparable to those of a mature forest. The results of this study indicate that recovery is five to seven times longer in the Upper Rio Negro than it is in other tropical areas in South America
Forest succession in the Upper Rio Negro of Colombia and Venezuela
Energy Technology Data Exchange (ETDEWEB)
Saldarriaga, J.G.; West, D.C.; Tharp, M.L.
1986-11-01
Woody vegetation from 23 forest stands along the Upper Rio Negro of Venezuela and Colombia was sampled in 1982 to examine the hypothesis that the Amazon forest has been largely undisturbed since the Pleistocene, to quantify vegetation development during different stages of succession following agricultural development, and to determine the time required for a successional stand to become a mature forest. The ubiquitousness of charcoal in the tierra firme forest indicated the presence of fire associated with extreme dry periods and human disturbances. Changes in species composition, vegetation structure, and woody biomass were studied on 19 abandoned farms and four mature forest stands. Living and dead biomass for the tress and their components was determined by regression equations developed from measurements of harvested trees. The rate of recovery of floristic composition, structure, and biomass following disturbance is relatively slow. Aboveground dead biomass remained high 14 years after the forest was disturbed by the agricultural practices. The lowest dead biomass is reached 20 years after abandonment, and the largest values are found in mature forests. Data analysis of 80-year-old stands showed that the species composition approached that of a mature forest. Approximately 140 to 200 years was required for an abandoned farm to attain the basal area and biomass values comparable to those of a mature forest. The results of this study indicate that recovery is five to seven times longer in the Upper Rio Negro than it is in other tropical areas in South America.
Luo, Shezhou; Wang, Cheng; Xi, Xiaohuan; Pan, Feifei; Qian, Mingjie; Peng, Dailiang; Nie, Sheng; Qin, Haiming; Lin, Yi
2017-06-01
Wetland biomass is essential for monitoring the stability and productivity of wetland ecosystems. Conventional field methods to measure or estimate wetland biomass are accurate and reliable, but expensive, time consuming and labor intensive. This research explored the potential for estimating wetland reed biomass using a combination of airborne discrete-return Light Detection and Ranging (LiDAR) and hyperspectral data. To derive the optimal predictor variables of reed biomass, a range of LiDAR and hyperspectral metrics at different spatial scales were regressed against the field-observed biomasses. The results showed that the LiDAR-derived H_p99 (99th percentile of the LiDAR height) and hyperspectral-calculated modified soil-adjusted vegetation index (MSAVI) were the best metrics for estimating reed biomass using the single regression model. Although the LiDAR data yielded a higher estimation accuracy compared to the hyperspectral data, the combination of LiDAR and hyperspectral data produced a more accurate prediction model for reed biomass (R2 = 0.648, RMSE = 167.546 g/m2, RMSEr = 20.71%) than LiDAR data alone. Thus, combining LiDAR data with hyperspectral data has a great potential for improving the accuracy of aboveground biomass estimation.
Tropical forests are a net carbon source based on aboveground measurements of gain and loss
Baccini, A.; Walker, W.; Carvalho, L.; Farina, M.; Sulla-Menashe, D.; Houghton, R. A.
2017-10-01
The carbon balance of tropical ecosystems remains uncertain, with top-down atmospheric studies suggesting an overall sink and bottom-up ecological approaches indicating a modest net source. Here we use 12 years (2003 to 2014) of MODIS pantropical satellite data to quantify net annual changes in the aboveground carbon density of tropical woody live vegetation, providing direct, measurement-based evidence that the world’s tropical forests are a net carbon source of 425.2 ± 92.0 teragrams of carbon per year (Tg C year-1). This net release of carbon consists of losses of 861.7 ± 80.2 Tg C year-1 and gains of 436.5 ± 31.0 Tg C year-1. Gains result from forest growth; losses result from deforestation and from reductions in carbon density within standing forests (degradation or disturbance), with the latter accounting for 68.9% of overall losses.
Biomass production efficiency controlled by management in temperate and boreal ecosystems
Campioli, M.; Vicca, S.; Luyssaert, S.; Bilcke, J.; Ceschia, E.; Chapin, F. S., III; Ciais, P.; Fernández-Martínez, M.; Malhi, Y.; Obersteiner, M.; Olefeldt, D.; Papale, D.; Piao, S. L.; Peñuelas, J.; Sullivan, P. F.; Wang, X.; Zenone, T.; Janssens, I. A.
2015-11-01
Plants acquire carbon through photosynthesis to sustain biomass production, autotrophic respiration and production of non-structural compounds for multiple purposes. The fraction of photosynthetic production used for biomass production, the biomass production efficiency, is a key determinant of the conversion of solar energy to biomass. In forest ecosystems, biomass production efficiency was suggested to be related to site fertility. Here we present a database of biomass production efficiency from 131 sites compiled from individual studies using harvest, biometric, eddy covariance, or process-based model estimates of production. The database is global, but dominated by data from Europe and North America. We show that instead of site fertility, ecosystem management is the key factor that controls biomass production efficiency in terrestrial ecosystems. In addition, in natural forests, grasslands, tundra, boreal peatlands and marshes, biomass production efficiency is independent of vegetation, environmental and climatic drivers. This similarity of biomass production efficiency across natural ecosystem types suggests that the ratio of biomass production to gross primary productivity is constant across natural ecosystems. We suggest that plant adaptation results in similar growth efficiency in high- and low-fertility natural systems, but that nutrient influxes under managed conditions favour a shift to carbon investment from the belowground flux of non-structural compounds to aboveground biomass.
A spatial evaluation of forest biomass usage using GIS
Energy Technology Data Exchange (ETDEWEB)
Kinoshita, Tsuguki; Yamagata, Yoshiki [National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba-shi, Ibaraki-ken 305-8506 (Japan); Inoue, Keisuke; Kagemoto, Hiroshi [The University of Tokyo (Japan); Iwao, Koki [National Institute of Advanced Industrial Science and Technology (Japan)
2009-01-15
We conducted a spatial evaluation of forest biomass usage using a geographic information system (GIS) for the Japanese town of Yusuhara. In Japan, over 60% of the land is covered with forest, of which at least 40% is artificial forest. However, because of high labor costs, the profitability of forestry is decreasing, so timber cultivation is not done to the extent that it could be, and thinning has to be subsidized. Under these circumstances, much of the forest is deteriorating. Most of the thinning is accounted for by throwaway thinning, in which the resulting wood is not used. However, with the steep rise in oil prices and the intensification of global warming concerns, expectations are rising for the use of biomass energy from thinned timber that has previously been discarded. If thinned timber, logging residues, and offcuts are utilized for biomass energy and their economic value becomes apparent, profitability will improve for both final cutting and thinning. And in addition to forestry activities being invigorated, it will be possible for some of the deteriorating forests (which have associated dangers such as landslides) to recover. However, using thinned timber and logging residues is problematic in that profitability is affected by harvesting costs. Harvesting costs are largely determined by geographic factors and are higher for more distant stands. Accordingly, in this article, operational costs for different stands are calculated using GIS and matched with total demand in the subject region. In addition, stands with lower operational costs are identified and an investigation of a highly feasible use of forest biomass is carried out. (author)
Santos, João. R.; Silva, Camila V. d. J.; Galvão, Lênio S.; Treuhaft, Robert; Mura, José C.; Madsen, Soren; Gonçalves, Fábio G.; Keller, Michael M.
2014-08-01
Secondary succession is an important process in the Amazonian region with implications for the global carbon cycle and for the sustainable regional agricultural and pasture activities. In order to better discriminate the secondary succession and to characterize and estimate the aboveground biomass (AGB), backscatter and interferometric SAR data generally have been analyzed through empirical-based statistical modeling. The objective of this study is to verify the capability of the full polarimetric PALSAR/ALOS (L-band) attributes, when combined with the interferometric (InSAR) coherence from the TanDEM-X (X-band), to improve the AGB estimates of the succession chronosequence located in the Brazilian Tapajós region. In order to perform this study, we carried out multivariate regression using radar attributes and biophysical parameters acquired during a field inventory. A previous floristic-structural analysis was performed to establish the chronosequence in three stages: initial vegetation regrowth, intermediate, and advanced regrowth. The relationship between PALSAR data and AGB was significant (p<0.001) and results suggested that the "volumetric scattering" (Pv) and "anisotropy" (A) attributes were important to explain the biomass content of the successional chronosequence (R2adjusted = 0.67; RMSE = 32.29 Mg.ha-1). By adding the TanDEM-derived interferometric coherence (Υi) into the regression modeling, better results were obtained (R2adjusted = 0.75; RMSE = 28.78Mg.ha-1). When we used both the L- and X-band attributes, the stock density prediction improved to 10.8 % for the secondary succession stands.
Feedstock quality : an important consideration in forest biomass supply
Energy Technology Data Exchange (ETDEWEB)
Ryans, M. [FP Innovations, Vancouver, BC (Canada). FERIC
2009-07-01
The move to forest-based sources of biomass requires an emphasis on the quality of forest residues. Customers set the feedstock requirements, and demand homogeneous and predictable quality. The top quality factors are appropriate moisture content, consistent particle size, chlorine content, and clean material. The seasonal variability of the resource means that suppliers must determine how to deliver a year-round supply with appropriate moisture content. Methods such as pre-piling and covering with a tarp are being tested. Although mills tailored for biomass deliveries have modernized boilers capable of burning a variety of biomass feedstocks at varying moisture contents, a 10 per cent reduction in moisture content can offer a good return on investment because suppliers could transports more energy content and less water per tonne of biomass. This presentation also discussed the range of equipment choices available for delivering the right-sized biomass, and outlined the right and wrong practices that influence biomass quality along the supply chain. figs.
African savanna-forest boundary dynamics
DEFF Research Database (Denmark)
Cuni Sanchez, Aida; White, Lee J. T.; Calders, Kim
2016-01-01
-term inventory plots we quantify changes in vegetation structure, above-ground biomass (AGB) and biodiversity of trees ≥10 cm diameter over 20 years for five vegetation types: savanna; colonising forest (F1), monodominant Okoume forest (F2); young Marantaceae forest (F3); and mixed Marantaceae forest (F4...... substantially in structure, AGB or diversity. Critically, the stability of the F3 stage implies that this stage may be maintained for long periods. Soil carbon was low, and did not show a successional gradient as for AGB and diversity. TLS vertical plant profiles showed distinctive differences amongst...... the vegetation types, indicating that this technique can improve ecological understanding. We highlight two points: (i) as forest colonises, changes in biodiversity are much slower than changes in forest structure or AGB; and (ii) all forest types store substantial quantities of carbon. Multidecadal monitoring...
[Structural recovering in Andean successional forests from Porce (Antioquia, Colombia)].
Yepes, Adriana P; del Valle, Jorge I; Jaramillo, Sandra L; Orrego, Sergio A
2010-03-01
Places subjected to natural or human disturbance can recover forest through an ecological process called secondary succession. Tropical succession is affected by factors such as disturbances, distance from original forest, surface configuration and local climate. These factors determine the composition of species and the time trend of the succession itself. We studied succession in soils used for cattle ranching over various decades in the Porce Region of Colombia (Andean Colombian forests). A set of twenty five permanent plots was measured, including nine plots (20 x 50 m) in primary forests and sixteen (20 x 25 m) in secondary forests. All trees with diameter > or =1.0 cm were measured. We analyzed stem density, basal area, above-ground biomass and species richness, in a successional process of ca. 43 years, and in primary forests. The secondary forests' age was estimated in previous studies, using radiocarbon dating, aerial photographs and a high-resolution satellite image analysis (7 to >43 years). In total, 1,143 and 1,766 stems were measured in primary and secondary forests, respectively. Basal area (5.7 to 85.4 m2 ha(-1)), above-ground biomass (19.1 to 1,011.5 t ha(-1)) and species richness (4 to 69) directly increased with site age, while steam density decreased (3,180 to 590). Diametric distributions were "J-inverted" for primary forests and even-aged size-class structures for secondary forests. Three species of palms were abundant and exclusive in old secondary forests and primary forests: Oenocarpus mapora, Euterpe precatoria and Oenocarpus bataua. These palms happened in cohorts after forest disturbances. Secondary forest structure was 40% in more than 43 years of forest succession and indicate that many factors are interacting and affecting the forests succession in the area (e.g. agriculture, cattle ranching, mining, etc.).
EXPLAINING FOREST COMPOSITION AND BIOMASS ACROSS MULTIPLE BIOGEOGRAPHIC REGIONS
Current scientific concerns regarding the impacts of global change include the responses of forest composition and biomass to rapid changes in climate, and forest gap models, have often been used to address this issue. These models reflect the concept that forest composition and...
Wang, Xinchuang; Shao, Guofan; Chen, Hua; Lewis, Bernard J; Qi, Guang; Yu, Dapao; Zhou, Li; Dai, Limin
2013-09-01
Monitoring the dynamics of forest biomass at various spatial scales is important for better understanding the terrestrial carbon cycle as well as improving the effectiveness of forest policies and forest management activities. In this article, field data and Landsat image data acquired in 1999 and 2007 were utilized to quantify spatiotemporal changes of forest biomass for Dongsheng Forestry Farm in Changbai Mountain region of northeastern China. We found that Landsat TM band 4 and Difference Vegetation Index with a 3 × 3 window size were the best predictors associated with forest biomass estimations in the study area. The inverse regression model with Landsat TM band 4 predictor was found to be the best model. The total forest biomass in the study area decreased slightly from 2.77 × 10(6) Mg in 1999 to 2.73 × 10(6) Mg in 2007, which agreed closely with field-based model estimates. The area of forested land increased from 17.9 × 10(3) ha in 1999 to 18.1 × 10(3) ha in 2007. The stabilization of forest biomass and the slight increase of forested land occurred in the period following implementations of national forest policies in China in 1999. The pattern of changes in both forest biomass and biomass density was altered due to different management regimes adopted in light of those policies. This study reveals the usefulness of the remote sensing-based approach for detecting and monitoring quantitative changes in forest biomass at a landscape scale.
Directory of Open Access Journals (Sweden)
Timothy Dube
2014-08-01
Full Text Available The quantification of aboveground biomass using remote sensing is critical for better understanding the role of forests in carbon sequestration and for informed sustainable management. Although remote sensing techniques have been proven useful in assessing forest biomass in general, more is required to investigate their capabilities in predicting intra-and-inter species biomass which are mainly characterised by non-linear relationships. In this study, we tested two machine learning algorithms, Stochastic Gradient Boosting (SGB and Random Forest (RF regression trees to predict intra-and-inter species biomass using high resolution RapidEye reflectance bands as well as the derived vegetation indices in a commercial plantation. The results showed that the SGB algorithm yielded the best performance for intra-and-inter species biomass prediction; using all the predictor variables as well as based on the most important selected variables. For example using the most important variables the algorithm produced an R2 of 0.80 and RMSE of 16.93 t·ha−1 for E. grandis; R2 of 0.79, RMSE of 17.27 t·ha−1 for P. taeda and R2 of 0.61, RMSE of 43.39 t·ha−1 for the combined species data sets. Comparatively, RF yielded plausible results only for E. dunii (R2 of 0.79; RMSE of 7.18 t·ha−1. We demonstrated that although the two statistical methods were able to predict biomass accurately, RF produced weaker results as compared to SGB when applied to combined species dataset. The result underscores the relevance of stochastic models in predicting biomass drawn from different species and genera using the new generation high resolution RapidEye sensor with strategically positioned bands.
Forest Biomass for Climate Change Mitigation
DEFF Research Database (Denmark)
Nielsen, Anders Tærø
Awareness of elevated CO2 levels in the atmosphere and resulting climate change has increased focus on renewable energy sources during recent decades. Biomass for energy has been predicted to have the greatest potential for CO2 reductions in the short term and the IPCC assumes that the use...... of biomass for energy is CO2 neutral. Several studies have however criticized this CO2 neutrality assumption and questioned whether CO2 reductions actually are achieved through use of biomass for energy. The purpose of this thesis is to investigate the biomass production potential of poplar plantations...... on southern Scandinavian sites, managed under different systems both in agriculture and in forests. In addition, the objective is to assess the potential of the poplar plantations to mitigate climate change by using poplar biomass for substitution of fossil fuels in comparison to a traditional product...
Sustainable Biofuels from Forests: Woody Biomass
Directory of Open Access Journals (Sweden)
Edwin H. White
2011-11-01
Full Text Available The use of woody biomass feedstocks for bioenergy and bioproducts involves multiple sources of material that together create year round supplies. The main sources of woody biomass include residues from wood manufacturing industries, low value trees including logging slash in forests that are currently underutilized and dedicated short-rotation woody crops. Conceptually a ton of woody biomass feedstocks can replace a barrel of oil as the wood is processed (refined through a biorefinery. As oil is refined only part of the barrel is used for liquid fuel, e.g., gasoline, while much of the carbon in oil is refined into higher value chemical products-carbon in woody biomass can be refined into the same value-added products.
Emissions tradeoffs associated with cofiring forest biomass with coal: A case study in Colorado, USA
International Nuclear Information System (INIS)
Loeffler, Dan; Anderson, Nathaniel
2014-01-01
Highlights: • Case study using audited fuel consumption and emissions data from a coal mine and power plant. • Model emissions tradeoffs of cofiring forest biomass with coal up to 20% by heat input value. • Substituting forest biomass with coal displaces fossil energy with an otherwise waste material. • Substantially less system emissions overall are generated when cofiring forest biomass. • Cofiring forest biomass has positive global and local greenhouse gas and human health implications. - Abstract: Cofiring forest biomass residues with coal to generate electricity is often cited for its potential to offset fossil fuels and reduce greenhouse gas emissions, but the extent to which cofiring achieves these objectives is highly dependent on case specific variables. This paper uses facility and forest specific data to examine emissions from cofiring forest biomass with coal ranging up to 20% substitution by heat value in southwest Colorado, USA. Calculations for net system emissions include five emissions sources: coal mining, power plant processes, forest biomass processes, boiler emissions, and forest biomass disposal. At the maximum displacement of 20% of heat demand using 120,717 t of forest biomass per year, total system emissions are projected to decrease by 15% for CO 2 , 95% for CH 4 , 18% for NO X , 82% for PM 10 , and 27% for SO X . PM 10 and CH 4 emissions benefits are closely tied to reducing open burning for residue disposal. At maximum displacement, 189,240 t of CO 2 emissions equivalent to the annual CO 2 emissions from 36,200 passenger vehicles, 440,000 barrels of oil, or nearly 990 railcars of coal are avoided. When forest biomass is not cofired, emissions equivalent to144,200 t of CO 2 are emitted from open burning. In addition to exploring the details of this case, we provide a methodology for assessing the emissions tradeoffs related to using forest biomass for cogeneration that incorporates the operational aspects of managing forest
Shifts in tree functional composition amplify the response of forest biomass to climate.
Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W
2018-04-05
Forests have a key role in global ecosystems, hosting much of the world's terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.
Shifts in tree functional composition amplify the response of forest biomass to climate
Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W.
2018-04-01
Forests have a key role in global ecosystems, hosting much of the world’s terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.
Ningthoujam, Ramesh K.; Joshi, P. K.; Roy, P. S.
2018-07-01
Tropical forest is an important ecosystem rich in biodiversity and structural complexity with high woody biomass content. Longer wavelength radar data at L-band sensor provides improved forest biomass (AGB) information due to its higher penetration level and sensitivity to canopy structure. The study presents a regression based woody biomass estimation for tropical deciduous mixed forest dominated by Shorea robusta using ALOS PALSAR mosaic (HH, HV) and field data at the lower Himalayan belt of Northern India. For the purpose of understanding the scattering mechanisms at L-band from this forest type, Michigan Microwave Canopy Scattering model (MIMICS-I) was parameterized with field data to simulate backscatter across polarization and incidence range. Regression analysis between field measured forest biomass and L-band backscatter data from PALSAR mosaic show retrieval of woody biomass up to 100 Mg ha-1 with error between 92 and 94 Mg ha-1 and coefficient of determination (r2) between 0.53 and 0.55 for HH and HH + HV polarized channel at 0.25 ha resolution. This positive relationship could be due to strong volume scattering from ground/trunk interaction at HH-polarized while in combination with direct canopy scattering for HV-polarization at ALOS specific incidence angles as predicted by MIMICS-I model. This study has found that L-band SAR data from currently ALOS-1/-2 and upcoming joint NASA-ISRO SAR (NISAR) are suitable for mapping forest biomass ≤100 Mg ha-1 at 25 m resolution in far incidence range in dense deciduous mixed forest of Northern India.
Remote Sensing-based estimates of herbaceous aboveground biomass on the Mongolian Plateau
John, R.; Chen, J.; Kim, Y.; Ouyang, Z.; Park, H.; Shao, C.
2015-12-01
Grasslands comprise most of the land area on the Mongolian Plateau, which includes Mongolia (MG), and the province of Inner Mongolia (IM). Substantial land cover/use change in the recent past, driven by a combination of post-liberalization, socio-economic changes as well as extreme climatic events has resulted in degradation of grasslands in structure and function, for e.g., their carbon sequestration ability. Hence there is a need for precise estimation of above-ground biomass (AGB). In this study, we collected surface reflectance spectra from field radiometry and quadrats and line transects, which include percentage of ground cover, vegetation height, above ground biomass, and species richness, during the growing season, between the periods, 2006-2011 in IM and 2011-2015 in MG. The field sampling was stratified by the dominant vegetation types on the plateau, including the meadow steppe, typical steppe, and the desert steppe. These sampling data were used as training and validation data for developing and testing predictive models for total herbaceous vegetation, and AGB, using Landsat and MODIS-surface reflectance bands and derived vegetation indices optimized for low cover conditions. Our results show that the independent ground sampling data were significantly correlated with remotely sensed estimates. In addition to providing measures of carbon sequestration to the community, these predictive models offer decision makers and rangeland managers the ability to accurately monitor grassland dynamics, control livestock stocking rates in these remote and extensive grasslands.
Treuhaft, R. N.; Baccini, A.; Goncalves, F. G.; Lei, Y.; Keller, M.; Walker, W. S.
2017-12-01
Tropical forests account for about 50% of the world's forested biomass, and play a critical role in the control of atmospheric carbon dioxide. Large-scale (1000's of km) changes in forest structure and biomass bear on global carbon source-sink dynamics, while small-scale (phase-height observation, we show forest phase-height time series from the TanDEM-X radar interferometer at X-band (3 cm), taken with monthly and sub-hectare temporal and spatial resolution, respectively. The measurements were taken with more than 30 TanDEM-X passes over Tapajós National Forest in the Brazilian Amazon between 2011 and 2014. The transformation of phase-height rates into aboveground biomass (AGB) rates is based on the idea that the change in AGB due to a change in phase-height depends on the plot's AGB. Plots with higher AGB will produce more AGB for a given increase in height or phase-height. Postulating a power-law dependence of plot-level mass density on physical height, we previously found that the best conversion factors for transforming phase-height rate to AGB rate were indeed dependent on AGB. For 78 plots, we demonstrated AGB rates from InSAR phase-height rates using AGB from field measurements. For regional modeling of the Amazon Basin, field measurements of AGB, to specify the conversion factors, is impractical. Conversion factors from InSAR phase-height rate to AGB rate in this talk will be based on AGB derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). AGB measurement from MODIS is based on the spectral reflectance of 7 bands from the visible to short wave infrared, and auxiliary metrics describing the variance in reflectance. The mapping of MODIS reflectance to AGB is enabled by training a machine learning algorithm with lidar-derived AGB data, which are in turn trained by field measurements for small areas. The performance of TanDEM-X AGB rate from MODIS-derived conversion factors will be compared to that derived from field-based conversion
Costanza, Jennifer; Abt, Robert C.; McKerrow, Alexa; Collazo, Jaime
2015-01-01
We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.
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Jennifer K. Costanza
2015-03-01
Full Text Available We linked state-and-transition simulation models (STSMs with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.
Evaluating kriging as a tool to improve moderate resolution maps of forest biomass
Elizabeth A. Freeman; Gretchen G. Moisen
2007-01-01
The USDA Forest Service, Forest Inventory and Analysis program (FIA) recently produced a nationwide map of forest biomass by modeling biomass collected on forest inventory plots as nonparametric functions of moderate resolution satellite data and other environmental variables using Cubist software. Efforts are underway to develop methods to enhance this initial map. We...
The importance of forest structure for carbon fluxes of the Amazon rainforest
Rödig, Edna; Cuntz, Matthias; Rammig, Anja; Fischer, Rico; Taubert, Franziska; Huth, Andreas
2018-05-01
Precise descriptions of forest productivity, biomass, and structure are essential for understanding ecosystem responses to climatic and anthropogenic changes. However, relations between these components are complex, in particular for tropical forests. We developed an approach to simulate carbon dynamics in the Amazon rainforest including around 410 billion individual trees within 7.8 million km2. We integrated canopy height observations from space-borne LIDAR in order to quantify spatial variations in forest state and structure reflecting small-scale to large-scale natural and anthropogenic disturbances. Under current conditions, we identified the Amazon rainforest as a carbon sink, gaining 0.56 GtC per year. This carbon sink is driven by an estimated mean gross primary productivity (GPP) of 25.1 tC ha‑1 a‑1, and a mean woody aboveground net primary productivity (wANPP) of 4.2 tC ha‑1 a‑1. We found that successional states play an important role for the relations between productivity and biomass. Forests in early to intermediate successional states are the most productive, and woody above-ground carbon use efficiencies are non-linear. Simulated values can be compared to observed carbon fluxes at various spatial resolutions (>40 m). Notably, we found that our GPP corresponds to the values derived from MODIS. For NPP, spatial differences can be observed due to the consideration of forest successional states in our approach. We conclude that forest structure has a substantial impact on productivity and biomass. It is an essential factor that should be taken into account when estimating current carbon budgets or analyzing climate change scenarios for the Amazon rainforest.
Characterization of biomass burning aerosols from forest fire in Indonesia
Fujii, Y.; Iriana, W.; Okumura, M.; Lestari, P.; Tohno, S.; Akira, M.; Okuda, T.
2012-12-01
Biomass burning (forest fire, wild fire) is a major source of pollutants, generating an estimate of 104 Tg per year of aerosol particles worldwide. These particles have adverse human health effects and can affect the radiation budget and climate directly and indirectly. Eighty percent of biomass burning aerosols are generated in the tropics and about thirty percent of them originate in the tropical regions of Asia (Andreae, 1991). Several recent studies have reported on the organic compositions of biomass burning aerosols in the tropical regions of South America and Africa, however, there is little data about forest fire aerosols in the tropical regions of Asia. It is important to characterize biomass burning aerosols in the tropical regions of Asia because the aerosol properties vary between fires depending on type and moisture of wood, combustion phase, wind conditions, and several other variables (Reid et al., 2005). We have characterized PM2.5 fractions of biomass burning aerosols emitted from forest fire in Indonesia. During the dry season in 2012, PM2.5 aerosols from several forest fires occurring in Riau, Sumatra, Indonesia were collected on quartz and teflon filters with two mini-volume samplers. Background aerosols in forest were sampled during transition period of rainy season to dry season (baseline period). Samples were analyzed with several analytical instruments. The carbonaceous content (organic and elemental carbon, OC and EC) of the aerosols was analyzed by a thermal optical reflectance technique using IMPROVE protocol. The metal, inorganic ion and organic components of the aerosols were analyzed by X-ray Fluorescence (XRF), ion chromatography and gas chromatography-mass spectrometry, respectively. There was a great difference of chemical composition between forest fire and non-forest fire samples. Smoke aerosols for forest fires events were composed of ~ 45 % OC and ~ 2.5 % EC. On the other hand, background aerosols for baseline periods were
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Shuman, J K; Shugart, H H
2009-01-01
Climate warming could strongly influence the structure and composition of the Eurasian boreal forest. Temperature related changes have occurred, including shifts in treelines and changes in regeneration. Dynamic vegetation models are well suited to the further exploration of the impacts that climate change may have on boreal forests. Using the individual-based gap model FAREAST, forest composition and biomass are simulated at over 2000 sites across Eurasia. Biomass output is compared to detailed forest data from a representative sample of Russian forests and a sensitivity analysis is performed to evaluate the impact that elevated temperatures and modified precipitation will have on forest biomass and composition in Eurasia. Correlations between model and forest inventory biomass are strong for several boreal tree species. A significant relationship is shown between altered precipitation and biomass. This analysis showed that a modest increase in temperature of 2 deg. C across 200 years had no significant effect on biomass; however further exploration with increased warming reflective of values measured within Siberia, or at an increased rate, are warranted. Overall, FAREAST accurately simulates forest biomass and composition at sites throughout a large geographic area with widely varying climatic conditions and produces reasonable biomass responses to simulated climatic shifts. These results indicate that this model is robust and useful in making predictions regarding the effect of future climate change on boreal forest structure across Eurasia.
Ercanli, İlker; Kahriman, Aydın
2015-03-01
We assessed the effect of stand structural diversity, including the Shannon, improved Shannon, Simpson, McIntosh, Margelef, and Berger-Parker indices, on stand aboveground biomass (AGB) and developed statistical prediction models for the stand AGB values, including stand structural diversity indices and some stand attributes. The AGB prediction model, including only stand attributes, accounted for 85 % of the total variance in AGB (R (2)) with an Akaike's information criterion (AIC) of 807.2407, Bayesian information criterion (BIC) of 809.5397, Schwarz Bayesian criterion (SBC) of 818.0426, and root mean square error (RMSE) of 38.529 Mg. After inclusion of the stand structural diversity into the model structure, considerable improvement was observed in statistical accuracy, including 97.5 % of the total variance in AGB, with an AIC of 614.1819, BIC of 617.1242, SBC of 633.0853, and RMSE of 15.8153 Mg. The predictive fitting results indicate that some indices describing the stand structural diversity can be employed as significant independent variables to predict the AGB production of the Scotch pine stand. Further, including the stand diversity indices in the AGB prediction model with the stand attributes provided important predictive contributions in estimating the total variance in AGB.
ABOVE GROUND BIOMASS MICRONUTRIENTS IN A SEASONAL SUBTROPICAL FOREST
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Hamilton Luiz Munari Vogel
2015-06-01
Full Text Available In the above ground biomass of a native forest or plantation are stored large quantities of nutrients, with few studies in the literature, especially concerning micronutrients. The present work aimed to quantify the micronutrients in above ground biomass in a Seasonal Subtropical forest in Itaara-RS, Brazil. For the above ground biomass evaluation, 20 trees of five different diameter classes were felled. The above ground biomass was separated in the following compartments: stem wood, stem bark, branches and leaves. The contents of B, Cu, Fe, Mn and Zn in the biomass samples were determined. The stock of micronutrients in the biomass for each component was obtained based on the estimated dry biomass, multiplied by the nutrient content. The total production of above ground biomass was estimated at 210.0 Mg.ha-1. The branches, stem wood, stem bark and leaves corresponded to 48.8, 43.3, 5.4 and 2.4% of the above ground biomass. The lower levels of B, Cu, Fe and Mn are in stem wood, except for Zn; in the branches and trunk wood are the largest stocks of B, Cu, Fe and Mn. In the branches, leaves and trunk bark are stored most micronutrients, pointing to the importance of these to remain on the soil.
Slik, J.W.F.; Bernard, C.S.; Beek, van M.; Breman, F.C.; Eichhorn, K.A.O.
2008-01-01
Forest fires remain a devastating phenomenon in the tropics that not only affect forest structure and biodiversity, but also contribute significantly to atmospheric CO2. Fire used to be extremely rare in tropical forests, leaving ample time for forests to regenerate to pre-fire conditions. In recent
Wijk, van M.T.; Williams, M.; Gough, L.; Hobbie, S.E.; Shaver, G.R.
2003-01-01
1 A field-experiment was used to determine how plant species might retain dominance in an arctic ecosystem receiving added nutrients. We both measured and modelled the above-ground and below-ground biomass allocation and root morphology of non-acidic tussock tundra near Toolik Lake, Alaska, after 4
Projecting demand and supply of forest biomass for heating in Norway
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Tromborg, Erik; Havskjold, Monica; Lislebo, Ole; Rorstad, Per Kristian
2011-01-01
This paper assesses the increase in demand and supply for forest biomass for heating in Norway in 2020. By then there is a political aim to double the national production of bioenergy from the level in 2008. The competitiveness of woody biomass in central and district heating is analyzed in a model selecting the least-cost heating technology and scale in municipalities given a set of constraints and under different fuels price scenarios. The supply of forest biomass from roundwood is estimated based on data of forest inventories combined with elasticities regarding price and standing volumes. The supply of biomass from harvesting residues is estimated in an engineering approach based on data from the national forest inventories and roundwood harvest. The results show how the production of bioenergy is affected by changes in energy prices and support schemes for bioenergy. One conclusion from the analyses is that the government target of 14 TWh more bioenergy by 2020 is not likely to be met by current technologies and policy incentives. The contribution of the analysis is the detailed presentation of the heat market potentials and technology choices combined with supply functions for both roundwood and harvesting residues. - Highlights: → This paper accesses the demand and supply for forest biomass for heating in Norway in 2020. → Market share for wood in central and new district heating is analyzed in a cost-minimizing model. → The supply of forest biomass includes wood chips from import, roundwood and harvesting residues. → The production of bioenergy is affected by changes in energy prices and support schemes. → The government target for bioenergy is not met by current technologies and policy incentives.
A meta-analysis of soil microbial biomass responses to forest disturbances
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Sandra Robin Holden
2013-06-01
Full Text Available Climate warming is likely to increase the frequency and severity of forest disturbances, with uncertain consequences for soil microbial communities and their contribution to ecosystem C dynamics. To address this uncertainty, we conducted a meta-analysis of 139 published soil microbial responses to forest disturbances. These disturbances included abiotic (fire, harvesting, storm and biotic (insect, pathogen disturbances. We hypothesized that soil microbial biomass would decline following forest disturbances, but that abiotic disturbances would elicit greater reductions in microbial biomass than biotic disturbances. In support of this hypothesis, across all published studies, disturbances reduced soil microbial biomass by an average of 29.4%. However, microbial responses differed between abiotic and biotic disturbances. Microbial responses were significantly negative following fires, harvest, and storms (48.7%, 19.1%, and 41.7% reductions in microbial biomass, respectively. In contrast, changes in soil microbial biomass following insect infestation and pathogen-induced tree mortality were non-significant, although biotic disturbances were poorly represented in the literature. When measured separately, fungal and bacterial responses to disturbances mirrored the response of the microbial community as a whole. Changes in microbial abundance following disturbance were significantly positively correlated with changes in microbial respiration. We propose that the differential effect of abiotic and biotic disturbances on microbial biomass may be attributable to differences in soil disruption and organic C removal from forests among disturbance types. Altogether, these results suggest that abiotic forest disturbances may significantly decrease soil microbial abundance, with corresponding consequences for microbial respiration. Further studies are needed on the effect of biotic disturbances on forest soil microbial communities and soil C dynamics.
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Sushma Tripathi
2018-01-01
Full Text Available Community forests of Nepal’s midhills have high potentiality to sequester carbon. This paper tries to analyze the biomass carbon stock in Schima-Castanopsis forest of Jaisikuna community forests of Kaski district, Nepal. Forest area was divided into two blocks and 18 sample plots (9 in each block which were laid randomly. Diameter at Breast Height (DBH and height of trees (DBH≥5cm were measured using the DBH tape and clinometer. Leaf litter, herbs, grasses and seedlings were collected from 1*1m2 plot and fresh weight was taken. For calculating carbon biomass is multiplied by default value 0.47. The AGTB carbon content of Chilaune, Katus and other species were found 19.56 t/ha, 18.66 t/ha and 3.59 t/ha respectively. The AGTB of Chilaune dominated, Katus dominated and whole forest was found 43.78 t/ha, 39.83 t/ha and 41.81 t/ha respectively. Carbon content at leaf litter, herbs, grasses and seedlings was found 2.73 t/ha. Below ground biomass carbon at whole forest was found 6.27 t/ha. Total biomass and carbon of the forest was found 108.09 t/ha and 50.80 t/ha respectively. Difference in biomass and carbon content at Chilaune dominated block and Katus dominated block was found insignificant. This study record very low biomass carbon content than average of Nepal's forest but this variation in carbon stock is not necessarily due to dominant species present in the forest. Carbon estimation at forest of different elevation, aspect and location are recommended for further research. International Journal of EnvironmentVolume-6, Issue-4, Sep-Nov 2017, page: 72-84
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Nurlita Indah Wahyuni
2014-12-01
Full Text Available The development of remote sensing technology makes it possible to utilize its data in many sectors including forestry. Remote sensing image has been used to map land cover and monitor deforestation. This paper presents utilization of ALOS PALSAR image to estimate and map aboveground biomass at natural forest of Bogani Nani Wartabone National Park especially SPTN II Doloduo and SPTN III Maelang. We used modeling method between biomass value from direct measurement and digital number of satellite image. There are two maps which present the distribution of biomass and carbon from ALOS PALSAR image with 50 m spatial resolution. These maps were built based on backscatter polarization of HH and HV bands. The maps indicate most research area dominated with biomass stock 0-5.000 ton/ha.
Forest soil carbon is threatened by intensive biomass harvesting.
Achat, David L; Fortin, Mathieu; Landmann, Guy; Ringeval, Bruno; Augusto, Laurent
2015-11-04
Forests play a key role in the carbon cycle as they store huge quantities of organic carbon, most of which is stored in soils, with a smaller part being held in vegetation. While the carbon storage capacity of forests is influenced by forestry, the long-term impacts of forest managers' decisions on soil organic carbon (SOC) remain unclear. Using a meta-analysis approach, we showed that conventional biomass harvests preserved the SOC of forests, unlike intensive harvests where logging residues were harvested to produce fuelwood. Conventional harvests caused a decrease in carbon storage in the forest floor, but when the whole soil profile was taken into account, we found that this loss in the forest floor was compensated by an accumulation of SOC in deeper soil layers. Conversely, we found that intensive harvests led to SOC losses in all layers of forest soils. We assessed the potential impact of intensive harvests on the carbon budget, focusing on managed European forests. Estimated carbon losses from forest soils suggested that intensive biomass harvests could constitute an important source of carbon transfer from forests to the atmosphere (142-497 Tg-C), partly neutralizing the role of a carbon sink played by forest soils.
Impact of Precipitation Patterns on Biomass and Species Richness of Annuals in a Dry Steppe
Yan, Hong; Liang, Cunzhu; Li, Zhiyong; Liu, Zhongling; Miao, Bailing; He, Chunguang; Sheng, Lianxi
2015-01-01
Annuals are an important component part of plant communities in arid and semiarid grassland ecosystems. Although it is well known that precipitation has a significant impact on productivity and species richness of community or perennials, nevertheless, due to lack of measurements, especially long-term experiment data, there is little information on how quantity and patterns of precipitation affect similar attributes of annuals. This study addresses this knowledge gap by analyzing how quantity and temporal patterns of precipitation affect aboveground biomass, interannual variation aboveground biomass, relative aboveground biomass, and species richness of annuals using a 29-year dataset from a dry steppe site at the Inner Mongolia Grassland Ecosystem Research Station. Results showed that aboveground biomass and relative aboveground biomass of annuals increased with increasing precipitation. The coefficient of variation in aboveground biomass of annuals decreased significantly with increasing annual and growing-season precipitation. Species richness of annuals increased significantly with increasing annual precipitation and growing-season precipitation. Overall, this study highlights the importance of precipitation for aboveground biomass and species richness of annuals. PMID:25906187
Composite materials from forest biomass : a review of current practices, science, and technology
Roger M. Rowell
2007-01-01
Renewable and sustainable composite materials can be produced using forest biomass if we maintain healthy forests. Small diameter trees and other forest biomass can be processed in the forest into small solid wood pieces, sliced veneers, strands, flakes, chips, particles and fiber that can be used to make construction composite products such as glued-laminated lumber,...
Aboveground dry biomass partitioning and nitrogen accumulation in early maturing soybean ‘Merlin’
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Tadeusz Zając
2017-12-01
Full Text Available The aim of the study was to determine the biomass and nitrogen accumulation in early maturing soybean plants experiencing contrasting weather conditions. Soybean (Glycine max is a species of agricultural crop plant that is widely described in scientific publications. During 2014–2016, a field experiment with early maturing soybean ‘Merlin’ was carried out at Grodziec Śląski, Poland (49°48'01" N, 18°52'04" E. Results showed that the morphological traits of the plants, the yield of individual plants, and the soybean crop were all closely related to the climatic conditions. A high amount of precipitation stimulated seed development, resulting in a high production potential. The harvest index calculated for soybean ‘Merlin’ was high and exceeded 0.5 g g−1. The nitrogen content of the aboveground biomass increased during ontogenesis. The maximum yield of dry matter was noted at the green maturity phase, which subsequently decreased at the full maturity phase because of the loss of the leaf fraction. The variation in the effectiveness of nitrogen accumulation in seeds between 2015 and 2016 was 30%. The nitrogen harvest index values were high in each year of the experiment and exceeded 0.92 g−1. For the production of 1 ton of seeds with an adequate amount of soybean straw, plants needed, on average, 68 kg of nitrogen.
Estimate of biomass and carbon pools in disturbed and undisturbed oak forests in Tunisia
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Zribi, L.; Chaar, H.; Khaldi, A.; Henchi, B.; Mouillot, F.; Gharbi, F.
2016-07-01
Aim of the study. To estimate biomass and carbon accumulation in a young and disturbed forest (regenerated after a tornado) and an aged cork oak forest (undisturbed forest) as well as its distribution among the different pools (tree, litter and soil). Area of study. The north west of Tunisia. Material and methods. Carbon stocks were evaluated in the above and belowground cork oak trees, the litter and the 150 cm of the soil. Tree biomass was estimated in both young and aged forests using allometric biomass equations developed for wood stem, cork stem, wood branch, cork branch, leaves, roots and total tree biomass based on combinations of diameter at breast height, total height and crown length as independent variables. Main results. Total tree biomass in forests was 240.58 Mg ha-1 in the young forest and 411.30 Mg ha-1 in the aged forest with a low root/shoot ratio (0.41 for young forest and 0.31 for aged forest). Total stored carbon was 419.46 Mg C ha-1 in the young forest and 658.09 Mg C ha-1 in the aged forest. Carbon stock (Mg C ha-1) was estimated to be113.61(27.08%) and 194.08 (29.49%) in trees, 3.55 (0.85%) and 5.73 (0.87%) in litter and 302.30 (72.07%) and 458.27 (69.64%) in soil in the young and aged forests, respectively. Research highlights. Aged undisturbed forest had the largest tree biomass but a lower potential for accumulation of carbon in the future; in contrast, young disturbed forest had both higher growth and carbon storage potential. (Author)
Extensive Sampling of Forest Carbon using High Density Power Line Lidar
Hampton, H. M.; Chen, Q.; Dye, D. G.; Hungate, B. A.
2013-12-01
Estimating carbon sequestration and greenhouse gas emissions from forest management, natural processes, and disturbance is of growing interest for mitigating global warming. Ponderosa pine is common at mid-elevations throughout the western United States and is a dominant tree species in southwestern forests. Existing unmanaged "relict" sites and stand reconstructions of southwestern ponderosa pine forests from before European settlement (late 1800s) provide evidence of forests of larger trees of lower density and less vulnerability to severe fires than today's typical conditions of high densities of small trees that have resulted from a century of fire suppression. Forest treatments to improve forest health in the region include tree cutting focused on small-diameter trees (thinning), low-intensity prescribed burning, and monitoring rather than suppressing wildfires. Stimulated by several uncharacteristically-intense fires in the last decade, a collaborative process found strong stakeholder agreement to accelerate forest treatments to reduce fire risk and restore ecological conditions. Land use planning to ramp up management is underway and could benefit from quick and inexpensive techniques to inventory tree-level carbon because existing inventory data are not adequate to capture the range of forest structural conditions. Our approach overcomes these shortcomings by employing recent breakthroughs in estimating aboveground biomass from high resolution light detection and ranging (lidar) remote sensing. Lidar is an active remote sensing technique, analogous to radar, which measures the time required for a transmitted pulse of laser light to return to the sensor after reflection from a target. Lidar data can capture 3-dimensional forest structure with greater detail and broader spatial coverage than is feasible with conventional field measurements. We developed a novel methodology for extensive sampling and field validation of forest carbon, applicable to managed and
Freschet, Grégoire T; Ostlund, Lars; Kichenin, Emilie; Wardle, David A
2014-04-01
Human activities that involve land-use change often cause major transformations to community and ecosystem properties both aboveground and belowground, and when land use is abandoned, these modifications can persist for extended periods. However, the mechanisms responsible for rapid recovery vs. long-term maintenance of ecosystem changes following abandonment remain poorly understood. Here, we examined the long-term ecological effects of two remote former settlements, regularly visited for -300 years by reindeer-herding Sami and abandoned -100 years ago, within an old-growth boreal forest that is considered one of the most pristine regions in northern Scandinavia. These human legacies were assessed through measurements of abiotic and biotic soil properties and vegetation characteristics at the settlement sites and at varying distances from them. Low-intensity land use by Sami is characterized by the transfer of organic matter towards the settlements by humans and reindeer herds, compaction of soil through trampling, disappearance of understory vegetation, and selective cutting of pine trees for fuel and construction. As a consequence, we found a shift towards early successional plant species and a threefold increase in soil microbial activity and nutrient availability close to the settlements relative to away from them. These changes in soil fertility and vegetation contributed to 83% greater total vegetation productivity, 35% greater plant biomass, and 23% and 16% greater concentrations of foliar N and P nearer the settlements, leading to a greater quantity and quality of litter inputs. Because decomposer activity was also 40% greater towards the settlements, soil organic matter cycling and nutrient availability were further increased, leading to likely positive feedbacks between the aboveground and belowground components resulting from historic land use. Although not all of the activities typical of Sami have left visible residual traces on the ecosystem after
Changing Amazon biomass and the role of atmospheric CO2 concentration, climate, and land use
de Almeida Castanho, Andrea D.; Galbraith, David; Zhang, Ke; Coe, Michael T.; Costa, Marcos H.; Moorcroft, Paul
2016-01-01
The Amazon tropical evergreen forest is an important component of the global carbon budget. Its forest floristic composition, structure, and function are sensitive to changes in climate, atmospheric composition, and land use. In this study biomass and productivity simulated by three dynamic global vegetation models (Integrated Biosphere Simulator, Ecosystem Demography Biosphere Model, and Joint UK Land Environment Simulator) for the period 1970-2008 are compared with observations from forest plots (Rede Amazónica de Inventarios Forestales). The spatial variability in biomass and productivity simulated by the DGVMs is low in comparison to the field observations in part because of poor representation of the heterogeneity of vegetation traits within the models. We find that over the last four decades the CO2 fertilization effect dominates a long-term increase in simulated biomass in undisturbed Amazonian forests, while land use change in the south and southeastern Amazonia dominates a reduction in Amazon aboveground biomass, of similar magnitude to the CO2 biomass gain. Climate extremes exert a strong effect on the observed biomass on short time scales, but the models are incapable of reproducing the observed impacts of extreme drought on forest biomass. We find that future improvements in the accuracy of DGVM predictions will require improved representation of four key elements: (1) spatially variable plant traits, (2) soil and nutrients mediated processes, (3) extreme event mortality, and (4) sensitivity to climatic variability. Finally, continued long-term observations and ecosystem-scale experiments (e.g. Free-Air CO2 Enrichment experiments) are essential for a better understanding of the changing dynamics of tropical forests.
Temperature drives global patterns in forest biomass distribution in leaves, stems, and roots.
Reich, Peter B; Luo, Yunjian; Bradford, John B; Poorter, Hendrik; Perry, Charles H; Oleksyn, Jacek
2014-09-23
Whether the fraction of total forest biomass distributed in roots, stems, or leaves varies systematically across geographic gradients remains unknown despite its importance for understanding forest ecology and modeling global carbon cycles. It has been hypothesized that plants should maintain proportionally more biomass in the organ that acquires the most limiting resource. Accordingly, we hypothesize greater biomass distribution in roots and less in stems and foliage in increasingly arid climates and in colder environments at high latitudes. Such a strategy would increase uptake of soil water in dry conditions and of soil nutrients in cold soils, where they are at low supply and are less mobile. We use a large global biomass dataset (>6,200 forests from 61 countries, across a 40 °C gradient in mean annual temperature) to address these questions. Climate metrics involving temperature were better predictors of biomass partitioning than those involving moisture availability, because, surprisingly, fractional distribution of biomass to roots or foliage was unrelated to aridity. In contrast, in increasingly cold climates, the proportion of total forest biomass in roots was greater and in foliage was smaller for both angiosperm and gymnosperm forests. These findings support hypotheses about adaptive strategies of forest trees to temperature and provide biogeographically explicit relationships to improve ecosystem and earth system models. They also will allow, for the first time to our knowledge, representations of root carbon pools that consider biogeographic differences, which are useful for quantifying whole-ecosystem carbon stocks and cycles and for assessing the impact of climate change on forest carbon dynamics.
Relating multifrequency radar backscattering to forest biomass: Modeling and AIRSAR measurement
Sun, Guo-Qing; Ranson, K. Jon
1992-01-01
During the last several years, significant efforts in microwave remote sensing were devoted to relating forest parameters to radar backscattering coefficients. These and other studies showed that in most cases, the longer wavelength (i.e. P band) and cross-polarization (HV) backscattering had higher sensitivity and better correlation to forest biomass. This research examines this relationship in a northern forest area through both backscatter modeling and synthetic aperture radar (SAR) data analysis. The field measurements were used to estimate stand biomass from forest weight tables. The backscatter model described by Sun et al. was modified to simulate the backscattering coefficients with respect to stand biomass. The average number of trees per square meter or radar resolution cell, and the average tree height or diameter breast height (dbh) in the forest stand are the driving parameters of the model. The rest of the soil surface, orientation, and size distributions of leaves and branches, remain unchanged in the simulations.
Relating P-band AIRSAR backscatter to forest stand parameters
Wang, Yong; Melack, John M.; Davis, Frank W.; Kasischke, Eric S.; Christensen, Norman L., Jr.
1993-01-01
As part of research on forest ecosystems, the Jet Propulsion Laboratory (JPL) and collaborating research teams have conducted multi-season airborne synthetic aperture radar (AIRSAR) experiments in three forest ecosystems including temperate pine forest (Duke, Forest, North Carolina), boreal forest (Bonanza Creek Experimental Forest, Alaska), and northern mixed hardwood-conifer forest (Michigan Biological Station, Michigan). The major research goals were to improve understanding of the relationships between radar backscatter and phenological variables (e.g. stand density, tree size, etc.), to improve radar backscatter models of tree canopy properties, and to develop a radar-based scheme for monitoring forest phenological changes. In September 1989, AIRSAR backscatter data were acquired over the Duke Forest. As the aboveground biomass of the loblolly pine forest stands at Duke Forest increased, the SAR backscatter at C-, L-, and P-bands increased and saturated at different biomass levels for the C-band, L-band, and P-band data. We only use the P-band backscatter data and ground measurements here to study the relationships between the backscatter and stand density, the backscatter and mean trunk dbh (diameter at breast height) of trees in the stands, and the backscatter and stand basal area.
Cost structure of and competition for forest-based biomass
International Nuclear Information System (INIS)
Lundmark, Robert
2007-01-01
Biomass has become a popular alternative to satisfy expanding energy demand and as a substitute for fossil fuels and phased-out nuclear energy in Europe. The European Union White Paper stipulates that the utilization of biomass shall increase to 1566 TWh by 2010. However it is often overlooked that the forest resources are already, to a large extent, used by the forest industries. When promoting biomass for energy generation the consequences for the forest industries also need to be considered. Sweden is an excellent case study, as there are vast quantities of forest resources, nuclear power is starting to be phased out, there are restrictions on expanding hydropower and the political desire exists to 'set an example' with respect to carbon dioxide emissions. This paper attempts to estimate and analyse the supply of two types of forest resource, namely, roundwood and harvesting residues derived from final harvesting and commercial thinnings. Two separate supply curves are estimated: one for roundwood and one for harvesting residues. The cost structure is based on an economic-engineering approach where the separate cost components are constructed from the lowest cost element into aggregates for labour, capital, materials and overhead costs for each forest resource. The results indicate an unutilized economic supply of 12 TWh of harvesting residues in Sweden. However, after these 12 TWh have been recovered it becomes more profitable to use roundwood for energy purposes than to continue extracting further amounts of harvesting residues
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EVA PADRÓN
2007-03-01
Full Text Available The significance of field work in remote sensing studies when applied to large areas has often been underestimated. The combination of specific forest inventories for the estimation of aboveground biomass in large dry tropical forest areas with remote sensor data has scarcely been explored to date. In this work, a systematic, stratified forest inventory involving 100 X 100 m square plots in an area of Peruvian Prosopis pallida dry forest, roughly one million hectares in size in the Piura province (Peru has been compiled. The inventory encompassed the principal silvicultural variables defining the ecosystem studied, which were used in allometric equations for the different species, genera and plant associations in the area in order to estimate the amount of aboveground biomass present in each plot. Field data were related to a Landsat 7 ETM+ image by using six different vegetation indices derived from an image mosaic for the area. Two regression equations (relating the amount of aboveground phytomass to the different vegetation indices provided reasonably acceptable phytomass predictions for the type of ecosystem concerned (R² between 0.72 and 0.52La importancia del trabajo de campo en estudios de teledetección radica en la necesidad de proveer una validación a los valores de reflectividad incluidos en los datos de los sensores remotos. La diversidad ecológica del medio forestal y la evaluación de grandes superficies de difícil acceso hacen de la combinación del inventario forestal y de la teledetección una herramienta compleja y útil en el análisis del medio terrestre. El presente trabajo muestra la aplicación de un inventario sistemático estratificado sobre un millón de hectáreas de bosque tropical seco de Prosopis pallida en el Departamento de Piura (Perú en la validación de diferentes tipos de clasificación realizadas sobre dicho ecosistema mediante el uso de imágenes Landsat ETM+. El inventario recoge las principales
Dead wood biomass and turnover time, measured by radiocarbon, along a subalpine elevation gradient.
Kueppers, Lara M; Southon, John; Baer, Paul; Harte, John
2004-12-01
Dead wood biomass can be a substantial fraction of stored carbon in forest ecosystems, and coarse woody debris (CWD) decay rates may be sensitive to climate warming. We used an elevation gradient in Colorado Rocky Mountain subalpine forest to examine climate and species effects on dead wood biomass, and on CWD decay rate. Using a new radiocarbon approach, we determined that the turnover time of lodgepole pine CWD (340+/-130 years) was roughly half as long in a site with 2.5-3 degrees C warmer air temperature, as that of pine (630+/-400 years) or Engelmann spruce CWD (800+/-960 and 650+/-410 years) in cooler sites. Across all sites and both species, CWD age ranged from 2 to 600 years, and turnover time was 580+/-180 years. Total standing and fallen dead wood biomass ranged from 4.7+/-0.2 to 54+/-1 Mg ha(-1), and from 2.8 to 60% of aboveground live tree biomass. Dead wood biomass increased 75 kg ha(-1) per meter gain in elevation and decreased 13 Mg ha(-1) for every degree C increase in mean air temperature. Differences in biomass and decay rates along the elevation gradient suggest that climate warming will lead to a loss of dead wood carbon from subalpine forest.
Sadeghi, Yaser; St-Onge, Benoît; Leblon, Brigitte; Prieur, Jean-François; Simard, Marc
2018-06-01
We propose a method for mapping above-ground biomass (AGB) (Mg ha-1) in boreal forests based predominantly on Landsat 8 images and on canopy height models (CHM) generated using interferometric synthetic aperture radar (InSAR) from the Shuttle Radar Topographic Mission (SRTM) and the TanDEM-X mission. The original SRTM digital elevation model (DEM) was corrected by modelling the respective effects of landform and land cover on its errors and then subtracted from a TanDEM-X DSM to produce a SAR CHM. Among all the landform factors, the terrain curvature had the largest effect on SRTM elevation errors, with a r2 of 0.29. The NDSI was the best predictor of the residual SRTM land cover error, with a r2 of 0.30. The final SAR CHM had a RMSE of 2.45 m, with a bias of 0.07 m, compared to a lidar-based CHM. An AGB prediction model was developed based on a combination of the SAR CHM, TanDEM-X coherence, Landsat 8 NDVI, and other vegetation indices of RVI, DVI, GRVI, EVI, LAI, GNDVI, SAVI, GVI, Brightness, Greenness, and Wetness. The best results were obtained using a Random forest regression algorithm, at the stand level, yielding a RMSE of 26 Mg ha-1 (34% of average biomass), with a r2 of 0.62. This method has the potential of creating spatially continuous biomass maps over entire biomes using only spaceborne sensors and requiring only low-intensity calibration.
Impact of biomass harvesting on forest soil productivity in the northern Rocky Mountains
Woongsoon Jang; Christopher R. Keyes; Deborah Page-Dumroese
2015-01-01
Biomass harvesting extracts an increased amount of organic matter from forest ecosystems over conventional harvesting. Since organic matter plays a critical role in forest productivity, concerns of potential negative long-term impacts of biomass harvesting on forest productivity (i.e., changing nutrient/water cycling, aggravating soil properties, and compaction) have...
Basuki, T.M.; Skidmore, A.K.; Laake, van P.E.; Duren, van I.C.; Hussin, Y.A.
2012-01-01
A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models
Kotowska, Martyna M; Leuschner, Christoph; Triadiati, Triadiati; Hertel, Dietrich
2016-02-01
Tropical landscapes are not only rapidly transformed by ongoing land-use change, but are additionally confronted by increasing seasonal climate variation. There is an increasing demand for studies analyzing the effects and feedbacks on ecosystem functioning of large-scale conversions of tropical natural forest into intensively managed cash crop agriculture. We analyzed the seasonality of aboveground litterfall, fine root litter production, and aboveground woody biomass production (ANPP(woody)) in natural lowland forests, rubber agroforests under natural tree cover ("jungle rubber"), rubber and oil palm monocultures along a forest-to-agriculture transformation gradient in Sumatra. We hypothesized that the temporal fluctuation of litter production increases with increasing land-use intensity, while the associated nutrient fluxes and nutrient use efficiency (NUE) decrease. Indeed, the seasonal variation of aboveground litter production and ANPP(woody) increased from the natural forest to the plantations, while aboveground litterfall generally decreased. Nutrient return through aboveground litter was mostly highest in the natural forest; however, it was significantly lower only in rubber plantations. NUE of N, P and K was lowest in the oil palm plantations, with natural forest and the rubber systems showing comparably high values. Root litter production was generally lower than leaf litter production in all systems, while the root-to-leaf ratio of litter C flux increased along the land-use intensity gradient. Our results suggest that nutrient and C cycles are more directly affected by climate seasonality in species-poor agricultural systems than in species-rich forests, and therefore might be more susceptible to inter-annual climate fluctuation and climate change.
Net primary production of forest-forming species in climatic gradients of Eurasia
Directory of Open Access Journals (Sweden)
V. A. Usoltsev
2018-04-01
Full Text Available When using biomass and net primary production (NPP databases compiled by the authors for 6 forest-forming species in a number of 6694 and 2192 sample plots correspondingly, a system of regression models of their NPP is designed and some species-specific regularities of NPP distribution in two climatic gradients (natural zonality and climate continentality are stated. It is found that according to a zonal gradient, aboveground and total NPP in 2-needled pine and spruce-fir forests are monotonically increasing in the direction from the northern to the southern tip of the continent, while larch and birch have the maximum in the southern moderate, and aspen and poplar – in the northern moderate zone, but oak forests do not show any significant pattern. Within a single zonal belt, the aboveground and total NPP of coniferous and deciduous are monotonically decreasing in direction from the Atlantic and Pacific coasts to the continentality pole in Yakutia. The understory NPP of all the species, except oak, monotonically increase towards the subequatorial zone. For oak forests, any clear regularity is not revealed. Within a single zonal belt, when approaching continentality pole, Pinus and Quercus NPP monotonically decreases and in other species, increases. Species-specific patterns in changing the relative indices of NPP (forest stand underground NPP to aboveground one and forest understory NPP to total forest stand one in gradients of the natural zonality and climate continentality are established.
Forest Biomass Energy Resources in China: Quantity and Distribution
Directory of Open Access Journals (Sweden)
Caixia Zhang
2015-11-01
Full Text Available As one of the most important renewable and sustainable energy sources, the forest biomass energy resource has always been the focus of attention of scholars and policy makers. However, its potential is still uncertain in China, especially with respect to its spatial distribution. In this paper, the quantity and distribution of Chinese forest biomass energy resources are explored based mainly on forestry statistics data rather than forest resource inventory data used by most previous studies. The results show that the forest biomass energy resource in China was 169 million tons in 2010, of which wood felling and bucking residue (WFBR,wood processing residue (WPR, bamboo processing residue, fuel wood and firewood used by farmers accounted for 38%, 37%, 6%, 4% and 15%, respectively. The highest resource was located in East China, accounting for nearly 39.0% of the national amount, followed by the Southwest and South China regions, which accounted for 17.4% and 16.3%, respectively. At the provincial scale, Shandong has the highest distribution, accounting for 11.9% of total resources, followed by Guangxi and Fujian accounting for 10.3% and 10.2%, respectively. The actual wood-processing residue (AWPR estimated from the actual production of different wood products (considering the wood transferred between regions showed apparent differences from the local wood processing residue (LWPR, which assumes that no wood has been transferredbetween regions. Due to the large contribution of WPR to total forestry bioenergy resources, the estimation of AWPR will provide a more accurate evaluation of the total amount and the spatial distribution of forest biomass energy resources in China.
Cheng, Dongliang; Zhong, Quanlin; Niklas, Karl J; Ma, Yuzhu; Yang, Yusheng; Zhang, Jianhua
2015-02-01
Empirical studies and allometric partitioning (AP) theory indicate that plant above-ground biomass (MA) scales, on average, one-to-one (isometrically) with below-ground biomass (MR) at the level of individual trees and at the level of entire forest communities. However, the ability of the AP theory to predict the biomass allocation patterns of understorey plants has not been established because most previous empirical tests have focused on canopy tree species or very large shrubs. In order to test the AP theory further, 1586 understorey sub-tropical forest plants from 30 sites in south-east China were harvested and examined. The numerical values of the scaling exponents and normalization constants (i.e. slopes and y-intercepts, respectively) of log-log linear MA vs. MR relationships were determined for all individual plants, for each site, across the entire data set, and for data sorted into a total of 19 sub-sets of forest types and successional stages. Similar comparisons of MA/MR were also made. The data revealed that the mean MA/MR of understorey plants was 2·44 and 1·57 across all 1586 plants and for all communities, respectively, and MA scaled nearly isometrically with respect to MR, with scaling exponents of 1·01 for all individual plants and 0·99 for all communities. The scaling exponents did not differ significantly among different forest types or successional stages, but the normalization constants did, and were positively correlated with MA/MR and negatively correlated with scaling exponents across all 1586 plants. The results support the AP theory's prediction that MA scales nearly one-to-one with MR (i.e. MA ∝ MR (≈1·0)) and that plant biomass partitioning for individual plants and at the community level share a strikingly similar pattern, at least for the understorey plants examined in this study. Furthermore, variation in environmental conditions appears to affect the numerical values of normalization constants, but not the scaling exponents
Potential of native forests for the mitigation of greenhouse gases in Salta, Argentina
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Manrique, Silvina; Franco, Judith; Nunez, Virgilio; Seghezzo, Lucas
2011-01-01
Carbon stocks were assessed in three archetypal forest ecosystems in the province of Salta, Argentina, namely Yungas, Chaco, and shrublands located around Chaco. Over a total area of about 7000 m 2 , detailed measurements of woody biomass were conducted using structural information such as diameter at breast height (dbh), total height, and stem height. At the same time, the wet weight of herbaceous, shrubs, and litter was registered within that area. Soil samples were also collected to determine parameters such as bulk density and organic carbon. The above-ground tree biomass (AGB) was quantified by two non-destructive methods. This biomass was expressed from each reservoir studied in t.ha -1 and the carbon content was then calculated using a factor of 0.5. Carbon stocks in the ecosystems studied were 162, 92, and 48 tC.ha -1 for Yungas, Chaco, and shrublands, respectively. Our results show that carbon is concentrated in the soil or as AGB. The latter is the most important reservoir in Yungas, while the soil plays this role in the other two, drier environments. In the province of Salta, native forests play a significant role in the mitigation of greenhouse gases. Our results reveal the magnitude of carbon stocks in some characteristic regional native forests, and estimate their carbon sequestration potential. These results could be useful to inform policy makers in charge of negotiations related to conservation and sustainable management of native forests, and be a relevant input for the formulation of more comprehensive land use planning processes in the region. -- Highlights: → We assessed carbon stocks in forest ecosystems in the province of Salta, Argentina. → The studied areas are located within ecosystems called Yungas, Chaco and shrublands. → Main carbon reservoirs in all ecosystems were found in above-ground tree biomass and soil. → Carbon stocks could be restored, maintained or increased with forest management. → We conclude that the studied
Melvin, April M.; Mack, Michelle C.; Johnstone, Jill F.; McGuire, A. David; Genet, Helene; Schuur, Edward A.G.
2015-01-01
In the boreal forest of Alaska, increased fire severity associated with climate change is expanding deciduous forest cover in areas previously dominated by black spruce (Picea mariana). Needle-leaf conifer and broad-leaf deciduous species are commonly associated with differences in tree growth, carbon (C) and nutrient cycling, and C accumulation in soils. Although this suggests that changes in tree species composition in Alaska could impact C and nutrient pools and fluxes, few studies have measured these linkages. We quantified C, nitrogen, phosphorus, and base cation pools and fluxes in three stands of black spruce and Alaska paper birch (Betula neoalaskana) that established following a single fire event in 1958. Paper birch consistently displayed characteristics of more rapid C and nutrient cycling, including greater aboveground net primary productivity, higher live foliage and litter nutrient concentrations, and larger ammonium and nitrate pools in the soil organic layer (SOL). Ecosystem C stocks (aboveground + SOL + 0–10 cm mineral soil) were similar for the two species; however, in black spruce, 78% of measured C was found in soil pools, primarily in the SOL, whereas aboveground biomass dominated ecosystem C pools in birch forest. Radiocarbon analysis indicated that approximately one-quarter of the black spruce SOL C accumulated prior to the 1958 fire, whereas no pre-fire C was observed in birch soils. Our findings suggest that tree species exert a strong influence over C and nutrient cycling in boreal forest and forest compositional shifts may have long-term implications for ecosystem C and nutrient dynamics.
Estimating carbon stock in secondary forests
DEFF Research Database (Denmark)
Breugel, Michiel van; Ransijn, Johannes; Craven, Dylan
2011-01-01
of trees and species for destructive biomass measurements. We assess uncertainties associated with these decisions using data from 94 secondary forest plots in central Panama and 244 harvested trees belonging to 26 locally abundant species. AGB estimates from species-specific models were used to assess...... is the use of allometric regression models to convert forest inventory data to estimates of aboveground biomass (AGB). The use of allometric models implies decisions on the selection of extant models or the development of a local model, the predictor variables included in the selected model, and the number...... relative errors of estimates from multispecies models. To reduce uncertainty in the estimation of plot AGB, including wood specific gravity (WSG) in the model was more important than the number of trees used for model fitting. However, decreasing the number of trees increased uncertainty of landscape...
Evaluation of total aboveground biomass and total merchantable biomass in Missouri
Michael E. Goerndt; David R. Larsen; Charles D. Keating
2014-01-01
In recent years, the state of Missouri has been converting to biomass weight rather than volume as the standard measurement of wood for buying and selling sawtimber. Therefore, there is a need to identify accurate and precise methods of estimating whole tree biomass and merchantable biomass of harvested trees as well as total standing biomass of live timber for...
Retrieval of pine forest biomass using JPL AIRSAR data
Beaudoin, A.; Letoan, T.; Zagolski, F.; Hsu, C. C.; Han, H. C.; Kong, J. A.
1992-01-01
The analysis of Jet Propulsion Laboratory (JPL) Airborne Synthetic Aperture Radar (AIRSAR) data over the Landes forest in South-West France revealed strong correlation between L- and especially P-band sigma degrees and the pine forest biomass. To explain the physical link of radar backscatter to biomass, a polarimetric backscattering model was developed and validated. Then the model was used in a simulation study to predict sigma degree sensitivity to undesired canopy and environmental parameters. Main results concerning the data analysis, modeling, and simulation at P-band are reported.
Becker, Joscha; Gütlein, Adrian; Sierra Cornejo, Natalia; Kiese, Ralf; Hertel, Dietrich; Kuzyakov, Yakov
2015-04-01
The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation in this area consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. Canopy structure is known to affect microclimate, throughfall and evapotranspiration and thereby controls soil moisture conditions. Consequently, the canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine trends and changes of soil parameters and relate their spatial variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. Distances were calculated in relation to the crown radius. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass carbon C and N, soil respiration as well as root biomass and -density, soil temperature and soil water content. Each tree was characterized by crown spread, leaf area index and basal area. Preliminary results show that C and N stocks decreased about 50% with depth independently of distance to the tree. Soil water content under the tree crown increased with depth while it decreased under grass cover. Microbial
Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems
Saatchi, Sassan; Moghaddam, Mahta
1995-01-01
In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.
Tropical forests are a net carbon source based on aboveground measurements of gain and loss.
Baccini, A; Walker, W; Carvalho, L; Farina, M; Sulla-Menashe, D; Houghton, R A
2017-10-13
The carbon balance of tropical ecosystems remains uncertain, with top-down atmospheric studies suggesting an overall sink and bottom-up ecological approaches indicating a modest net source. Here we use 12 years (2003 to 2014) of MODIS pantropical satellite data to quantify net annual changes in the aboveground carbon density of tropical woody live vegetation, providing direct, measurement-based evidence that the world's tropical forests are a net carbon source of 425.2 ± 92.0 teragrams of carbon per year (Tg C year -1 ). This net release of carbon consists of losses of 861.7 ± 80.2 Tg C year -1 and gains of 436.5 ± 31.0 Tg C year -1 Gains result from forest growth; losses result from deforestation and from reductions in carbon density within standing forests (degradation or disturbance), with the latter accounting for 68.9% of overall losses. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.
2015-01-01
Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.
Directory of Open Access Journals (Sweden)
Gianluca Grilli
2015-06-01
Full Text Available Background and Purpose: In the EU political agenda, the use of forest biomass for energy has grown rapidly and significantly, in order to mitigate carbon dioxide emissions and reduce the energy dependence on fossil fuels of European member countries. The target of the EU climate and energy package is to raise the share of renewable energy consumption produced from renewable resources to 20% in 2020 (Directive 2009/28/EC. With regards to biomass energy, the supply of forest wood biomass is expected to rise by 45% (reference period: 2006-2020, in response to increasing demand for renewable sources. The increase of forest biomass supply could have both positive and negative effects on several forest ecosystem services (ESs and local development. These effects should be assessed in a proper manner and taken into account when formulating management strategies. The aim of the paper is to assess the environmental, economic and social sustainability of forest biomass harvesting for energy, using the Figure of Merit (FoM approach. Materials and Methods: Sustainability was assessed through a set of four indicators: two focused on experts’ opinions regarding the effects of forest biomass harvesting and the other two focused on the cost-benefit analysis (potential energy obtained and costs for wood chips. The research was developed through four case studies located in the Alpine Region. A semi-structured questionnaire was administered face-to-face to 32 selected experts. The perceived effects of forest biomass harvesting for energy on ESs and local development were evaluated by experts using a 5-point Likert scale (from “quite negative effect” to “quite positive effect”. Results: All experts agree that forest biomass harvesting has a positive effect on forest products provision and local economic development (employment of local workforce, local entrepreneurship and market diversification, while the effects on other ESs are controversial (e
Ecological Importance of Large-Diameter Trees in a Temperate Mixed-Conifer Forest
Lutz, James A.; Larson, Andrew J.; Swanson, Mark E.; Freund, James A.
2012-01-01
Large-diameter trees dominate the structure, dynamics and function of many temperate and tropical forests. Although both scaling theory and competition theory make predictions about the relative composition and spatial patterns of large-diameter trees compared to smaller diameter trees, these predictions are rarely tested. We established a 25.6 ha permanent plot within which we tagged and mapped all trees ≥1 cm dbh, all snags ≥10 cm dbh, and all shrub patches ≥2 m2. We sampled downed woody debris, litter, and duff with line intercept transects. Aboveground live biomass of the 23 woody species was 507.9 Mg/ha, of which 503.8 Mg/ha was trees (SD = 114.3 Mg/ha) and 4.1 Mg/ha was shrubs. Aboveground live and dead biomass was 652.0 Mg/ha. Large-diameter trees comprised 1.4% of individuals but 49.4% of biomass, with biomass dominated by Abies concolor and Pinus lambertiana (93.0% of tree biomass). The large-diameter component dominated the biomass of snags (59.5%) and contributed significantly to that of woody debris (36.6%). Traditional scaling theory was not a good model for either the relationship between tree radii and tree abundance or tree biomass. Spatial patterning of large-diameter trees of the three most abundant species differed from that of small-diameter conspecifics. For A. concolor and P. lambertiana, as well as all trees pooled, large-diameter and small-diameter trees were spatially segregated through inter-tree distances trees and spatial relationships between large-diameter and small-diameter trees. Long-term observations may reveal regulation of forest biomass and spatial structure by fire, wind, pathogens, and insects in Sierra Nevada mixed-conifer forests. Sustaining ecosystem functions such as carbon storage or provision of specialist species habitat will likely require different management strategies when the functions are performed primarily by a few large trees as opposed to many smaller trees. PMID:22567132
Potter, Christopher; Malhi, Yadvinder
2004-01-01
Ever more detailed representations of above-ground biomass and soil carbon pools have been developed during the LBA project. Environmental controls such as regional climate, land cover history, secondary forest regrowth, and soil fertility are now being taken into account in regional inventory studies. This paper will review the evolution of measurement-extrapolation approaches, remote sensing, and simulation modeling techniques for biomass and soil carbon pools, which together help constrain regional carbon budgets and enhance in our understanding of uncertainty at the regional level.
Katherine Heckman; John L. Campbell; Heath Powers; Beverly E. Law; Chris Swanston
2013-01-01
Forest fires contribute a significant amount of CO2 to the atmosphere each year, and CO2 emissions from fires are likely to increase under projected conditions of global climate change. In addition to volatilizing aboveground biomass and litter layers, forest fires have a profound effect on belowground carbon (C) pools and the cycling of soil organic matter as a whole...
Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying
2006-09-01
Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.
A review of forest and tree plantation biomass equations in Indonesia
Anitha, Kamalakumari; Verchot, Louis V.; Joseph, Shijo; Herold, Martin; Manuri, Solichin; Avitabile, Valerio
2015-01-01
Key message: We compiled 2,458 biomass equations from 168 destructive sampling studies in Indonesia. Unpublished academic theses contributed the largest share of the biomass equations. The availability of the biomass equations was skewed to certain regions, forest types, and species. Further
Wang, Xiao-Li; Chang, Yu; Chen, Hong-Wei; Hu, Yuan-Man; Jiao, Lin-Lin; Feng, Yu-Ting; Wu, Wen; Wu, Hai-Feng
2014-04-01
Based on field inventory data and vegetation index EVI (enhanced vegetation index), the spatial pattern of the forest biomass in the Great Xing'an Mountains, Heilongjiang Province was quantitatively analyzed. Using the spatial analysis and statistics tools in ArcGIS software, the impacts of climatic zone, elevation, slope, aspect and vegetation type on the spatial pattern of forest biomass were explored. The results showed that the forest biomass in the Great Xing'an Mountains was 350 Tg and spatially aggregated with great increasing potentials. Forest biomass density in the cold temperate humid zone (64.02 t x hm(-2)) was higher than that in the temperate humid zone (60.26 t x hm(-2)). The biomass density of each vegetation type was in the order of mixed coniferous forest (65.13 t x hm(-2)) > spruce-fir forest (63.92 t x hm(-2)) > Pinus pumila-Larix gmelinii forest (63.79 t x hm(-2)) > Pinus sylvestris var. mongolica forest (61.97 t x hm(-2)) > Larix gmelinii forest (61.40 t x hm(-2)) > deciduous broadleaf forest (58.96 t x hm(-2)). With the increasing elevation and slope, the forest biomass density first decreased and then increased. The forest biomass density in the shady slopes was greater than that in the sunny slopes. The spatial pattern of forest biomass in the Great Xing' an Mountains exhibited a heterogeneous pattern due to the variation of climatic zone, vegetation type and topographical factor. This spatial heterogeneity needs to be accounted when evaluating forest biomass at regional scales.
Directory of Open Access Journals (Sweden)
M. Kröhnert
2018-05-01
Full Text Available Grassland ecology experiments in remote locations requiring quantitative analysis of the biomass in defined plots are becoming increasingly widespread, but are still limited by manual sampling methodologies. To provide a cost-effective automated solution for biomass determination, several photogrammetric techniques are examined to generate 3D point cloud representations of plots as a basis, to estimate aboveground biomass on grassland plots, which is a key ecosystem variable used in many experiments. Methods investigated include Structure from Motion (SfM techniques for camera pose estimation with posterior dense matching as well as the usage of a Time of Flight (TOF 3D camera, a laser light sheet triangulation system and a coded light projection system. In this context, plants of small scales (herbage and medium scales are observed. In the first pilot study presented here, the best results are obtained by applying dense matching after SfM, ideal for integration into distributed experiment networks.
Lasky, Jesse R; Uriarte, María; Boukili, Vanessa K; Erickson, David L; John Kress, W; Chazdon, Robin L
2014-09-01
Theory predicts shifts in the magnitude and direction of biodiversity effects on ecosystem function (BEF) over succession, but this theory remains largely untested. We studied the relationship between aboveground tree biomass dynamics (Δbiomass) and multiple dimensions of biodiversity over 8-16 years in eight successional rainforests. We tested whether successional changes in diversity-Δbiomass correlations reflect predictions of niche theories. Diversity-Δbiomass correlations were positive early but weak later in succession, suggesting saturation of niche space with increasing diversity. Early in succession, phylogenetic diversity and functional diversity in two leaf traits exhibited the strongest positive correlations with Δbiomass, indicating complementarity or positive selection effects. In mid-successional stands, high biodiversity was associated with greater mortality-driven biomass loss, i.e. negative selection effects, suggesting successional niche trade-offs and loss of fast-growing pioneer species. Our results demonstrate that BEF relationships are dynamic across succession, thus successional context is essential to understanding BEF in a given system. © 2014 John Wiley & Sons Ltd/CNRS.
International Nuclear Information System (INIS)
Kueh, J.H.R.; Majid, N.M.A.; Seca, G.; Ahmed, O.H.
2013-01-01
Forest degradation and deforestation are some of the major global concerns as it can reduce forest carbon storage and sequestration capacity. Forest rehabilitation on degraded forest areas has the potential to improve carbon stock, hence mitigate greenhouse gases emission. However, the carbon storage and sequestration potential in a rehabilitated tropical forest remains unclear due to the lack of information. This paper reports an initiative to estimate biomass-carbon partitioning, storage and sequestration in a rehabilitated forest. The study site was at the UPM-Mitsubishi Corporation Forest Rehabilitation Project, UPM Bintulu Sarawak Campus, Bintulu, Sarawak. A plot of 20 x 20 m 2 was established each in site 1991 (Plot 1991), 1999 (Plot 1999) and 2008 (Plot 2008). An adjacent natural regenerating secondary forest plot (Plot NF) was also established for comparison purposes. The results showed that the contribution of tree component biomass/ carbon to total biomass/ carbon was in the order of main stem > branch > leaf. As most of the trees were concentrated in diameter size class = 10 cm for younger rehabilitated forests, the total above ground biomass/ carbon was from this class. These observations suggest that the forests are in the early successional stage. The total above ground biomass obtained for the rehabilitated forest ranged from 4.3 to 4,192.3 kg compared to natural regenerating secondary forest of 3,942.3 kg while total above ground carbon ranged from 1.9 to 1,927.9 kg and 1,820.4 kg, respectively. The mean total above ground biomass accumulated ranged from 1.3 x 10 -2 to 20.5 kg/ 0.04 ha and mean total carbon storage ranged from 5.9 x 10 -3 to 9.4 kg/ 0.04 ha. The total CO 2 sequestrated in rehabilitated forest ranged from 6.9 to 7,069.1 kg CO 2 / 0.04 ha. After 19 years, the rehabilitated forest had total above ground biomass and carbon storage comparable to the natural regeneration secondary forest. The forest rehabilitated activities have the
Green electricity externalities: Forest biomass in an Atlantic European Region
International Nuclear Information System (INIS)
Solino, M.; Prada, A.; Vazquez, M.X.
2009-01-01
Renewable energy sources are expected to represent a growing proportion of the primary energy sources for the production of electricity. Environmental and social reasons support this tendency. European and Spanish energy plans assign a role of primary importance to biomass in general and, especially, to forest biomass for the period up to 2010. This paper reviews, organises and quantifies the potentials and values of this renewable resource in the foremost Spanish Region in terms of silviculture. The non-market externalities (environmental, economic and social) are classified, and some of them are quantified to present a synthesis of the benefits of a partial substitution of fossil fuels by forest biomass for electricity generation. (author)
O’Halloran, Lydia R.; Borer, Elizabeth T.; Seabloom, Eric W.; MacDougall, Andrew S.; Cleland, Elsa E.; McCulley, Rebecca L.; Hobbie, Sarah; Harpole, W. Stan; DeCrappeo, Nicole M.; Chu, Cheng-Jin; Bakker, Jonathan D.; Davies, Kendi F.; Du, Guozhen; Firn, Jennifer; Hagenah, Nicole; Hofmockel, Kirsten S.; Knops, Johannes M.H.; Li, Wei; Melbourne, Brett A.; Morgan, John W.; Orrock, John L.; Prober, Suzanne M.; Stevens, Carly J.
2013-01-01
Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.
Scolforo, Henrique Ferraco; Scolforo, Jose Roberto Soares; Mello, Carlos Rogerio; Mello, Jose Marcio; Ferraz Filho, Antonio Carlos
2015-01-01
The objective of this study was to map the spatial distribution of aboveground carbon stock (using Regression-kriging) of arboreal plants in the Atlantic Forest, Semi-arid woodland, and Savanna Biomes in Minas Gerais State, southeastern Brazil. The database used in this study was obtained from 163 forest fragments, totaling 4,146 plots of 1,000 m2 distributed in these Biomes. A geographical model for carbon stock estimation was parameterized as a function of Biome, latitude and altitude. This model was applied over the samples and the residuals generated were mapped based on geostatistical procedures, selecting the exponential semivariogram theoretical model for conducting ordinary Kriging. The aboveground carbon stock was found to have a greater concentration in the north of the State, where the largest contingent of native vegetation is located, mainly the Savanna Biome, with Wooded Savanna and Shrub Savanna phytophysiognomes. The largest weighted averages of carbon stock per hectare were found in the south-center region (48.6 Mg/ha) and in the southern part of the eastern region (48.4 Mg/ha) of Minas Gerais State, due to the greatest predominance of Atlantic Forest Biome forest fragments. The smallest weighted averages per hectare were found in the central (21.2 Mg/ha), northern (20.4 Mg/ha), and northwestern (20.7 Mg/ha) regions of Minas Gerais State, where Savanna Biome fragments are predominant, in the phytophysiognomes Wooded Savanna and Shrub Savanna.
Spaceborne Radar for Mapping Forest and Land Use Changes
DEFF Research Database (Denmark)
Joshi, Neha Pankaj
Degradation (REDD+). The implementation and effectiveness of such mechanisms relies partially on continuous observations of forests using satellite technology and partially on ground-based measurements of forest aboveground volume/biomass (AGV/AGB), carbon density and changes therein. Together, these means...... of forest monitoring enable the development of policies and measures to alter current trends in global forest and biodiversity loss. This thesis investigates the use of long wavelength (~23 cm, L-band) spaceborne radar, which has all-weather and canopy-penetration capabilities, acquired by the Advanced Land...... Observing Satellite (ALOS) for forest monitoring. Using a combination of local expert knowledge, plot inventories, and data from lidar and optical sensors, it aims to understand (1) whether forest disturbance dynamics may be detected with radar, and (2) what physical and macroecological properties influence...
Dynamics of aboveground phytomass of the circumpolar Arctic tundra during the past three decades
International Nuclear Information System (INIS)
Epstein, Howard E; Raynolds, Martha K; Walker, Donald A; Bhatt, Uma S; Tucker, Compton J; Pinzon, Jorge E
2012-01-01
Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982–2010). We found that the southernmost tundra subzones (C–E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field. (letter)
Dynamics of Aboveground Phytomass of the Circumpolar Arctic Tundra During the Past Three Decades
Epstein, Howard E.; Raynolds, Martha K.; Walker, Donald A.; Bhatt, Uma S.; Tucker, Compton J.; Pinzon, Jorge E.
2012-01-01
Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.
Jaramillo, Fernando; Cory, Neil; Arheimer, Berit; Laudon, Hjalmar; van der Velde, Ype; Hasper, Thomas B.; Teutschbein, Claudia; Uddling, Johan
2018-01-01
During the last 6 decades, forest biomass has increased in Sweden mainly due to forest management, with a possible increasing effect on evapotranspiration. However, increasing global CO2 concentrations may also trigger physiological water-saving responses in broadleaf tree species, and to a lesser degree in some needleleaf conifer species, inducing an opposite effect. Additionally, changes in other forest attributes may also affect evapotranspiration. In this study, we aimed to detect the dominating effect(s) of forest change on evapotranspiration by studying changes in the ratio of actual evapotranspiration to precipitation, known as the evaporative ratio, during the period 1961-2012. We first used the Budyko framework of water and energy availability at the basin scale to study the hydroclimatic movements in Budyko space of 65 temperate and boreal basins during this period. We found that movements in Budyko space could not be explained by climatic changes in precipitation and potential evapotranspiration in 60 % of these basins, suggesting the existence of other dominant drivers of hydroclimatic change. In both the temperate and boreal basin groups studied, a negative climatic effect on the evaporative ratio was counteracted by a positive residual effect. The positive residual effect occurred along with increasing standing forest biomass in the temperate and boreal basin groups, increasing forest cover in the temperate basin group and no apparent changes in forest species composition in any group. From the three forest attributes, standing forest biomass was the one that could explain most of the variance of the residual effect in both basin groups. These results further suggest that the water-saving response to increasing CO2 in these forests is either negligible or overridden by the opposite effect of the increasing forest biomass. Thus, we conclude that increasing standing forest biomass is the dominant driver of long-term and large-scale evapotranspiration
Energy Technology Data Exchange (ETDEWEB)
Martinez Sanchez, R.; Ayala Schraemili, F.
2008-07-01
This paper is about developing a logistic for the treatment of the forest prunes, including specific machines so far. Collecting, treatment, and transportation of forest biomass residues to valuation energy plant. Key words: collecting, treatment, transportation of forest prunes. (Author)
The Role of Remote Sensing in Assessing Forest Biomass in Appalachian South Carolina
Shain, W.; Nix, L.
1982-01-01
Information is presented on the use of color infrared aerial photographs and ground sampling methods to quantify standing forest biomass in Appalachian South Carolina. Local tree biomass equations are given and subsequent evaluation of stand density and size classes using remote sensing methods is presented. Methods of terrain analysis, environmental hazard rating, and subsequent determination of accessibility of forest biomass are discussed. Computer-based statistical analyses are used to expand individual cover-type specific ground sample data to area-wide cover type inventory figures based on aerial photographic interpretation and area measurement. Forest biomass data are presented for the study area in terms of discriminant size classes, merchantability limits, accessibility (as related to terrain and yield/harvest constraints), and potential environmental impact of harvest.
Meggio, Franco; Vendrame, Nadia; Maniero, Giovanni; Pitacco, Andrea
2014-05-01
In the current climate change scenarios, both agriculture and forestry inherently may act as carbon sinks and consequently can play a key role in limiting global warming. An urgent need exists to understand which land uses and land resource types have the greatest potential to mitigate greenhouse gas (GHG) emissions contributing to global change. A common believe is that agricultural fields cannot be net carbon sinks due to many technical inputs and repeated disturbances of upper soil layers that all contribute to a substantial loss both of the old and newly-synthesized organic matter. Perennial tree crops (vineyards and orchards), however, can behave differently: they grow a permanent woody structure, stand undisturbed in the same field for decades, originate a woody pruning debris, and are often grass-covered. In this context, reliable methods for quantifying and modelling emissions and carbon sequestration are required. Carbon stock changes are calculated by multiplying the difference in oven dry weight of biomass increments and losses with the appropriate carbon fraction. These data are relatively scant, and more information is needed on vineyard management practices and how they impact vineyard C sequestration and GHG emissions in order to generate an accurate vineyard GHG footprint. During the last decades, research efforts have been made for estimating the vineyard carbon budget and its allocation pattern since it is crucial to better understand how grapevines control the distribution of acquired resources in response to variation in environmental growth conditions and agronomic practices. The objective of the present study was to model and compare the dynamics of current year's above-ground biomass among four grapevine varieties. Trials were carried out over three growing seasons in field conditions. The non-linear extra-sums-of-squares method demonstrated to be a feasible way of growth models comparison to statistically assess significant differences among
Evaluation of Sentinel-1A Data For Above Ground Biomass Estimation in Different Forests in India
Vadrevu, Krishna Prasad
2017-01-01
Use of remote sensing data for mapping and monitoring of forest biomass across large spatial scales can aid in addressing uncertainties in carbon cycle. Earlier, several researchers reported on the use of Synthetic Aperture Radar (SAR) data for characterizing forest structural parameters and the above ground biomass estimation. However, these studies cannot be generalized and the algorithms cannot be applied to all types of forests without additional information on the forest physiognomy, stand structure and biomass characteristics. The radar backscatter signal also saturates as forest parameters such as biomass and the tree height increase. It is also not clear how different polarizations (VV versus VH) impact the backscatter retrievals in different forested regions. Thus, it is important to evaluate the potential of SAR data in different landscapes for characterizing forest structural parameters. In this study, the SAR data from Sentinel-1A has been used to characterize forest structural parameters including the above ground biomass from tropical forests of India. Ground based data on tree density, basal area and above ground biomass data from thirty-eight different forested sites has been collected to relate to SAR data. After the pre-processing of Sentinel 1-A data for radiometric calibration, geo-correction, terrain correction and speckle filtering, the variability in the backscatter signal in relation tree density, basal area and above biomass density has been investigated. Results from the curve fitting approach suggested exponential model between the Sentinel-1A backscatter versus tree density and above ground biomass whereas the relationship was almost linear with the basal area in the VV polarization mode. Of the different parameters, tree density could explain most of the variations in backscatter. Both VV and VH backscatter signals could explain only thirty and thirty three percent of variation in above biomass in different forest sites of India
Regional biomass stores and dynamics in forests of coastal Alaska
Mikhaill A. Yatskov; Mark E. Harmon; Olga N. Krankina; Tara M. Barrett; Kevin R. Dobelbower; Andrew N. Gray; Becky Fasth; Lori Trummer; Toni L. Hoyman; Chana M. Dudoit
2015-01-01
Coastal Alaska is a vast forested region (6.2 million ha) with the potential to store large amounts of carbon in live and dead biomass thus influencing continental and global carbon dynamics. The main objectives of this study were to assess regional biomass stores, examine the biomass partitioning between live and dead pools, and evaluate the effect of disturbance on...
Verkerk, P.J.; Mavsar, R.; Giergiczny, M.; Lindner, M.; Edwards, D.; Schelhaas, M.J.
2014-01-01
To develop viable strategies for intensifying the use of forest biomass and for increasing forest protection, impacts on ecosystem services need to be assessed. We investigated the biophysical and economic impacts of increased forest biomass production and biodiversity protection on forest ecosystem
Shiloh Sundstrom; Max Nielsen-Pincus; Cassandra Moseley; Sarah. McCaffrey
2012-01-01
The use of woody biomass is being promoted across the United States as a means of increasing energy independence, mitigating climate change, and reducing the cost of hazardous fuels reduction treatments and forest restoration projects. The opportunities and challenges for woody biomass use on the national forest system are unique. In addition to making woody biomass...
International Nuclear Information System (INIS)
French, Sean B.; Christensen, Candace; Jennings, Terry L.; Jaros, Christopher L.; Wykoff, David S.; Crowell, Kelly J.; Shuman, Rob
2008-01-01
Low-level radioactive waste (LLW) generated at the Los Alamos National Laboratories (LANL) is disposed of at LANL's Technical Area (T A) 54, Material Disposal Area (MDA) G. The ability of MDA G to safely contain radioactive waste during current and post-closure operations is evaluated as part of the facility's ongoing performance assessment (PA) and composite analysis (CA). Due to the potential for uptake and incorporation of radio nuclides into aboveground plant material, the PA and CA project that plant roots penetrating into buried waste may lead to releases of radionuclides into the accessible environment. The potential amount ofcontamination deposited on the ground surface due to plant intrusion into buried waste is a function of the quantity of litter generated by plants, as well as radionuclide concentrations within the litter. Radionuclide concentrations in plant litter is dependent on the distribution of root mass with depth and the efficiency with which radionuclides are extracted from contaminated soils by the plant's roots. In order to reduce uncertainties associated with the PA and CA for MDA G, surveys are being conducted to assess aboveground biomass, plant litter production rates, and root mass with depth for the four prominent vegetation types (grasses, forbs, shrubs and trees). The collection of aboveground biomass for grasses and forbs began in 2007. Additional sampling was conducted in October 2008 to measure root mass with depth and to collect additional aboveground biomass data for the types of grasses, forbs, shrubs, and trees that may become established at MDA G after the facility undergoes final closure, Biomass data will be used to estimate the future potential mass of contaminated plant litter fall, which could act as a latent conduit for radionuclide transport from the closed disposal area. Data collected are expected to reduce uncertainties associated with the PA and CA for MDA G and ultimately aid in the assessment and subsequent
Matthew D. Wallenstein; Steven McNulty; Ivan J. Fernandez; Johnny Boggs; William H. Schlesinger
2006-01-01
We examined the effects of N fertilization on forest soil fungal and bacterial biomass at three long-term experiments in New England (Harvard Forest, MA; Mt. Ascutney, VT; Bear Brook, ME). At Harvard Forest, chronic N fertilization has decreased organic soil microbial biomass C (MBC) by an average of 54% and substrate induced respiration (SIR) was decreased by an...
Directory of Open Access Journals (Sweden)
Katherine Sinacore
Full Text Available The potential benefits of planting trees have generated significant interest with respect to sequestering carbon and restoring other forest based ecosystem services. Reliable estimates of carbon stocks are pivotal for understanding the global carbon balance and for promoting initiatives to mitigate CO2 emissions through forest management. There are numerous studies employing allometric regression models that convert inventory into aboveground biomass (AGB and carbon (C. Yet the majority of allometric regression models do not consider the root system nor do these equations provide detail on the architecture and shape of different species. The root system is a vital piece toward understanding the hidden form and function roots play in carbon accumulation, nutrient and plant water uptake, and groundwater infiltration. Work that estimates C in forests as well as models that are used to better understand the hydrologic function of trees need better characterization of tree roots. We harvested 40 trees of six different species, including their roots down to 2 mm in diameter and created species-specific and multi-species models to calculate aboveground (AGB, coarse root belowground biomass (BGB, and total biomass (TB. We also explore the relationship between crown structure and root structure. We found that BGB contributes ~27.6% of a tree's TB, lateral roots extend over 1.25 times the distance of crown extent, root allocation patterns varied among species, and that AGB is a strong predictor of TB. These findings highlight the potential importance of including the root system in C estimates and lend important insights into the function roots play in water cycling.
Stas, Suzanne M.; Rutishauser, Ervan; Chave, Jérôme; Anten, Niels P.R.; Laumonier, Yves
2017-01-01
Deforestation and forest degradation are widespread in Indonesia and pose serious threats to biodiversity and other ecosystem services. The Indonesian government is implementing several Reduction of Emissions from Deforestation and Forest Degradation (REDD+) initiatives to help support the
Sader, Steven A.
1987-01-01
The effect of forest biomass, canopy structure, and species composition on L-band synthetic aperature radar data at 44 southern Mississippi bottomland hardwood and pine-hardwood forest sites was investigated. Cross-polarization mean digital values for pine forests were significantly correlated with green weight biomass and stand structure. Multiple linear regression with five forest structure variables provided a better integrated measure of canopy roughness and produced highly significant correlation coefficients for hardwood forests using HV/VV ratio only. Differences in biomass levels and canopy structure, including branching patterns and vertical canopy stratification, were important sources of volume scatter affecting multipolarization radar data. Standardized correction techniques and calibration of aircraft data, in addition to development of canopy models, are recommended for future investigations of forest biomass and structure using synthetic aperture radar.
Impact of biogas interventions on forest biomass and regeneration in southern India
Directory of Open Access Journals (Sweden)
M. Agarwala
2017-07-01
Full Text Available Programs to provide alternative energy sources such as biogas improve indoor air quality and potentially reduce pressure on forests from fuelwood collection. This study tests whether biogas intervention is associated with higher forest biomass and forest regeneration in degraded forests in Chikkaballapur district in Southern India. Using propensity score matching, we find that forest plots in proximity to villages with biogas interventions (treatment had greater forest biomass than comparable plots around villages without biogas (control. We also found significantly higher sapling abundance and diversity in treatment than control plots despite no significant difference in seedling abundances and diversity in treatment forests, suggesting that plants have a higher probability of reaching sapling stage. These results indicate the potential for alternative energy sources that reduce dependence on fuelwood to promote regeneration of degraded forests. However, forest regrowth is not uniform across treatments and is limited by soil nutrients and biased towards species that are light demanding, fire-resistant and can thrive in poor soil conditions.
Directory of Open Access Journals (Sweden)
Victor Onyango Odipo
2016-11-01
Full Text Available The use of optical remote sensing data for savanna vegetation structure mapping is hindered by sparse and heterogeneous distribution of vegetation canopy, leading to near-similar spectral signatures among lifeforms. An additional challenge to optical sensors is the high cloud cover and unpredictable weather conditions. Longwave microwave data, with its low sensitivity to clouds addresses some of these problems, but many space borne studies are still limited by low quality structural reference data. Terrestrial laser scanning (TLS derived canopy cover and height metrics can improve aboveground biomass (AGB prediction at both plot and landscape level. To date, few studies have explored the strength of TLS for vegetation structural mapping, and particularly few focusing on savannas. In this study, we evaluate the potential of high resolution TLS-derived canopy cover and height metrics to estimate plot-level aboveground biomass, and to extrapolate to a landscape-wide biomass estimation using multi-temporal L-band Synthetic Aperture Radar (SAR within a 9 km2 area savanna in Kruger National Park (KNP. We inventoried 42 field plots in the wet season and computed AGB for each plot using site-specific allometry. Canopy cover, canopy height, and their product were regressed with plot-level AGB over the TLS-footprint, while SAR backscatter was used to model dry season biomass for the years 2007, 2008, 2009, and 2010 for the study area. The results from model validation showed a significant linear relationship between TLS-derived predictors with field biomass, p < 0.05 and adjusted R2 ranging between 0.56 for SAR to 0.93 for the TLS-derived canopy cover and height. Log-transformed AGB yielded lower errors with TLS metrics compared with non-transformed AGB. An assessment of the backscatter based on root mean square error (RMSE showed better AGB prediction with cross-polarized (RMSE = 6.6 t/ha as opposed to co-polarized data (RMSE = 6.7 t/ha, attributed to
Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, Armond T.
1989-01-01
Forest stand structure and biomass data were collected using conventional forest inventory techniques in tropical, subtropical, and warm temperate forest biomes. The feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated. The Normalized Difference Vegetation Index (NDVI) calculated from Landsat-TM data were not significantly correlated with forest regeneration age classes in the mountain terrain of the Luquillo Experimental Forest, Puerto Rico. The low sun angle and shadows cast on steep north and west facing slopes reduced spectral reflectance values recorded by TM orbital altitude. The NDVI, calculated from low altitude aircraft scanner data, was significatly correlated with forest age classes. However, analysis of variance suggested that NDVI differences were not detectable for successional forests older than approximately 15-20 years. Also, biomass differences in young successional tropical forest were not detectable using the NDVI. The vegetation index does not appear to be a good predictor of stand structure variables (e.g., height, diameter of main stem) or total biomass in uneven age, mixed broadleaf forest. Good correlation between the vegetation index and low biomass in even age pine plantations were achieved for a warm temperate study site. The implications of the study for the use of NDVI for forest structure and biomass estimation are discussed.
Tian, Di; Li, Peng; Fang, Wenjing; Xu, Jun; Luo, Yongkai; Yan, Zhengbing; Zhu, Biao; Wang, Jingjing; Xu, Xiaoniu; Fang, Jingyun
2017-07-01
Reactive nitrogen (N) increase in the biosphere has been a noteworthy aspect of global change, producing considerable ecological effects on the functioning and dynamics of the terrestrial ecosystems. A number of observational studies have explored responses of plants to experimentally simulated N enrichment in boreal and temperate forests. Here we investigate how the dominant trees and different understory plants respond to experimental N enrichment in a subtropical forest in China. We conducted a 3.4-year N fertilization experiment in an old-aged subtropical evergreen broad-leaved forest in eastern China with three treatment levels applied to nine 20 m × 20 m plots and replicated in three blocks. We divided the plants into trees, saplings, shrubs (including tree seedlings), and ground-cover plants (ferns) according to the growth forms, and then measured the absolute and relative basal area increments of trees and saplings and the aboveground biomass of understory shrubs and ferns. We further grouped individuals of the dominant tree species, Castanopsis eyrei, into three size classes to investigate their respective growth responses to the N fertilization. Our results showed that the plot-averaged absolute and relative growth rates of basal area and aboveground biomass of trees were not affected by N fertilization. Across the individuals of C. eyrei, the small trees with a DBH (diameter at breast height) of 5-10 cm declined by 66.4 and 59.5 %, respectively, in N50 (50 kg N ha-1 yr-1) and N100 fertilized plots (100 kg N ha-1 yr-1), while the growth of median and large trees with a DBH of > 10 cm did not significantly change with the N fertilization. The growth rate of small trees, saplings, and the aboveground biomass of understory shrubs and ground-cover ferns decreased significantly in the N-fertilized plots. Our findings suggested that N might not be a limiting nutrient in this mature subtropical forest, and that the limitation of other nutrients in the forest
Directory of Open Access Journals (Sweden)
D. Tian
2017-07-01
Full Text Available Reactive nitrogen (N increase in the biosphere has been a noteworthy aspect of global change, producing considerable ecological effects on the functioning and dynamics of the terrestrial ecosystems. A number of observational studies have explored responses of plants to experimentally simulated N enrichment in boreal and temperate forests. Here we investigate how the dominant trees and different understory plants respond to experimental N enrichment in a subtropical forest in China. We conducted a 3.4-year N fertilization experiment in an old-aged subtropical evergreen broad-leaved forest in eastern China with three treatment levels applied to nine 20 m × 20 m plots and replicated in three blocks. We divided the plants into trees, saplings, shrubs (including tree seedlings, and ground-cover plants (ferns according to the growth forms, and then measured the absolute and relative basal area increments of trees and saplings and the aboveground biomass of understory shrubs and ferns. We further grouped individuals of the dominant tree species, Castanopsis eyrei, into three size classes to investigate their respective growth responses to the N fertilization. Our results showed that the plot-averaged absolute and relative growth rates of basal area and aboveground biomass of trees were not affected by N fertilization. Across the individuals of C. eyrei, the small trees with a DBH (diameter at breast height of 5–10 cm declined by 66.4 and 59.5 %, respectively, in N50 (50 kg N ha−1 yr−1 and N100 fertilized plots (100 kg N ha−1 yr−1, while the growth of median and large trees with a DBH of > 10 cm did not significantly change with the N fertilization. The growth rate of small trees, saplings, and the aboveground biomass of understory shrubs and ground-cover ferns decreased significantly in the N-fertilized plots. Our findings suggested that N might not be a limiting nutrient in this mature subtropical
Forest harvesting reduces the soil metagenomic potential for biomass decomposition.
Cardenas, Erick; Kranabetter, J M; Hope, Graeme; Maas, Kendra R; Hallam, Steven; Mohn, William W
2015-11-01
Soil is the key resource that must be managed to ensure sustainable forest productivity. Soil microbial communities mediate numerous essential ecosystem functions, and recent studies show that forest harvesting alters soil community composition. From a long-term soil productivity study site in a temperate coniferous forest in British Columbia, 21 forest soil shotgun metagenomes were generated, totaling 187 Gb. A method to analyze unassembled metagenome reads from the complex community was optimized and validated. The subsequent metagenome analysis revealed that, 12 years after forest harvesting, there were 16% and 8% reductions in relative abundances of biomass decomposition genes in the organic and mineral soil layers, respectively. Organic and mineral soil layers differed markedly in genetic potential for biomass degradation, with the organic layer having greater potential and being more strongly affected by harvesting. Gene families were disproportionately affected, and we identified 41 gene families consistently affected by harvesting, including families involved in lignin, cellulose, hemicellulose and pectin degradation. The results strongly suggest that harvesting profoundly altered below-ground cycling of carbon and other nutrients at this site, with potentially important consequences for forest regeneration. Thus, it is important to determine whether these changes foreshadow long-term changes in forest productivity or resilience and whether these changes are broadly characteristic of harvested forests.
Are double trailers cost effective for transporting forest biomass on steep terrain?
Directory of Open Access Journals (Sweden)
Rene Zamora-Cristales
2015-07-01
Full Text Available Transportation of forest biomass on steep terrain involves logistical challenges. Trucks with large single trailers are often unable to travel on forest roads due to their narrowness, tight curves, adverse grades and limited areas to turn around. A shorter trailer must be used but then transportation capacity is limited by the trailer volume due to the low bulk density of the processed biomass, particularly when the biomass is dry. With double trailers, transportation capacity can be limited by allowable legal weight based on axle number and spacing. We developed a simulation model that explores the economic feasibility of using double-trailer configurations to transport forest biomass to a bioenergy facility from the grinder at a landing or from a centralized yard in Washington, Oregon and California. Results show that double trailers can be a cost effective alternative to single trailers under limited conditions in Oregon and Washington, but they are not a competitive option in California due to the state's transportation regulations.
L. R. Iverson; S. Brown; A. Prasad; H. Mitasova; A. J. R. Gillespie; A. E. Lugo
1994-01-01
A geographic information system (GIS) was used to estimate total biomass and biomass density of the tropical forest in south and southeast Asia because available data from forest inventories were insufficient to extrapolate biomass-density estimates across the region.
Directory of Open Access Journals (Sweden)
N. Galia Selaya
2017-06-01
Full Text Available Tree species in tropical forests provide economically important goods and ecosystem services. In submontane forests of southwestern Amazonia, we investigated the degree to which tree species important for subsistence and trade contribute to aboveground carbon storage (AGC. We used 41 1-hectare plots to determine the species abundance, basal area, and AGC of stems > 10 cm diameter at breast height (dbh. Economically important taxa were classified using ethnobotanical studies and according to their stem density. These taxa (n = 263 accounted for 45% of total stems, 53% of total basal area, and 56% of total AGC, significantly more than taxa with minor or unknown uses (Welch test at p 40 cm and few stems in regeneration classes of dbh < 10 to 20 cm (e.g., Bertholletia excelsa, Cariniana spp., Cedrelinga spp., Ceiba spp., Dipteryx spp., whereas dominant Tetragastris spp., and Pseudolmedia spp. had most stems in low diameter classes and a median diameter of < 30 cm. Bertholletia excelsa, with 1.5 stems per hectare, showed the highest basal area of any species and accounted for 9% of AGC (11 Mg/ha, twice that of the second-ranking species. Our study shows that economic importance and carbon stocks in trees are closely linked in southwestern Amazonia. Unplanned harvests can disrupt synergistic dual roles altering carbon stocks temporally or permanently. Precautionary measures based on species ecology, demography, and regeneration traits should be at the forefront of REDD+ to reconcile maximum harvesting limits, biodiversity conservation, and sustainable forest management.
Tree Productivity Enhanced with Conversion from Forest to Urban Land Covers.
Briber, Brittain M; Hutyra, Lucy R; Reinmann, Andrew B; Raciti, Steve M; Dearborn, Victoria K; Holden, Christopher E; Dunn, Allison L
2015-01-01
Urban areas are expanding, changing the structure and productivity of landscapes. While some urban areas have been shown to hold substantial biomass, the productivity of these systems is largely unknown. We assessed how conversion from forest to urban land uses affected both biomass structure and productivity across eastern Massachusetts. We found that urban land uses held less than half the biomass of adjacent forest expanses with a plot level mean biomass density of 33.5 ± 8.0 Mg C ha(-1). As the intensity of urban development increased, the canopy cover, stem density, and biomass decreased. Analysis of Quercus rubra tree cores showed that tree-level basal area increment nearly doubled following development, increasing from 17.1 ± 3.0 to 35.8 ± 4.7 cm(2) yr(-1). Scaling the observed stem densities and growth rates within developed areas suggests an aboveground biomass growth rate of 1.8 ± 0.4 Mg C ha(-1) yr(-1), a growth rate comparable to nearby, intact forests. The contrasting high growth rates and lower biomass pools within urban areas suggest a highly dynamic ecosystem with rapid turnover. As global urban extent continues to grow, cities consider climate mitigation options, and as the verification of net greenhouse gas emissions emerges as critical for policy, quantifying the role of urban vegetation in regional-to-global carbon budgets will become ever more important.
Production of bio-oil from underutilized forest biomass using an auger reactor
H. Ravindran; S. Thangalzhy-Gopakumar; S. Adhikari; O. Fasina; M. Tu; B. Via; E. Carter; S. Taylor
2015-01-01
Conversion of underutilized forest biomass to bio-oil could be a niche market for energy production. In this work, bio-oil was produced from underutilized forest biomass at selected temperatures between 425â500°C using an auger reactor. Physical properties of bio-oil, such as pH, density, heating value, ash, and water, were analyzed and compared with an ASTM standard...
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Laihanen, M.; Karhunen, A.; Ranta, T.
2011-07-01
Rising demand of forest biomass in South-East Finland has created need to evaluate the impact for different energy users and producers. The aim of this study is to settle the current demand and availability of forest biomass and to evaluate the opportunities the growth offers. Initial data of study base on current structure of energy supply and on current energy demand. The information can be used as a guideline when evaluating local sufficiency of energy wood and business opportunities for local actors such as energy producers and forest fuel suppliers. Main aim of the study is to create prosperity and entrepreneurship to South-East Finland. Analysis included following tasks: gathering data about the current and potential use and users of forest biomass (logging residues, stumps and small diameter energy wood), settling local availability of forest fuels, creating forest biomass balance to indicate the sufficiency of local resources and to identify the effects of current business opportunities around forest biomass sector. Results of the study illustrate local balance between use and availability of energy wood, need for labor and revenue of forest biomass supply in South-East Finland. Evaluation analysis constructed for regional and local needs combine the current and potential use of forest biomass with local availability. Analysis represents model for evaluating local possibilities of utilization of forest biomass. Co-operation with Forestry Centre of South-East Finland was productive through entire study. (orig.)
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F. Jaramillo
2018-01-01
Full Text Available During the last 6 decades, forest biomass has increased in Sweden mainly due to forest management, with a possible increasing effect on evapotranspiration. However, increasing global CO2 concentrations may also trigger physiological water-saving responses in broadleaf tree species, and to a lesser degree in some needleleaf conifer species, inducing an opposite effect. Additionally, changes in other forest attributes may also affect evapotranspiration. In this study, we aimed to detect the dominating effect(s of forest change on evapotranspiration by studying changes in the ratio of actual evapotranspiration to precipitation, known as the evaporative ratio, during the period 1961–2012. We first used the Budyko framework of water and energy availability at the basin scale to study the hydroclimatic movements in Budyko space of 65 temperate and boreal basins during this period. We found that movements in Budyko space could not be explained by climatic changes in precipitation and potential evapotranspiration in 60 % of these basins, suggesting the existence of other dominant drivers of hydroclimatic change. In both the temperate and boreal basin groups studied, a negative climatic effect on the evaporative ratio was counteracted by a positive residual effect. The positive residual effect occurred along with increasing standing forest biomass in the temperate and boreal basin groups, increasing forest cover in the temperate basin group and no apparent changes in forest species composition in any group. From the three forest attributes, standing forest biomass was the one that could explain most of the variance of the residual effect in both basin groups. These results further suggest that the water-saving response to increasing CO2 in these forests is either negligible or overridden by the opposite effect of the increasing forest biomass. Thus, we conclude that increasing standing forest biomass is the dominant driver of long-term and large
Modelling tree biomasses in Finland
Energy Technology Data Exchange (ETDEWEB)
Repola, J.
2013-06-01
Biomass equations for above- and below-ground tree components of Scots pine (Pinus sylvestris L), Norway spruce (Picea abies [L.] Karst) and birch (Betula pendula Roth and Betula pubescens Ehrh.) were compiled using empirical material from a total of 102 stands. These stands (44 Scots pine, 34 Norway spruce and 24 birch stands) were located mainly on mineral soil sites representing a large part of Finland. The biomass models were based on data measured from 1648 sample trees, comprising 908 pine, 613 spruce and 127 birch trees. Biomass equations were derived for the total above-ground biomass and for the individual tree components: stem wood, stem bark, living and dead branches, needles, stump, and roots, as dependent variables. Three multivariate models with different numbers of independent variables for above-ground biomass and one for below-ground biomass were constructed. Variables that are normally measured in forest inventories were used as independent variables. The simplest model formulations, multivariate models (1) were mainly based on tree diameter and height as independent variables. In more elaborated multivariate models, (2) and (3), additional commonly measured tree variables such as age, crown length, bark thickness and radial growth rate were added. Tree biomass modelling includes consecutive phases, which cause unreliability in the prediction of biomass. First, biomasses of sample trees should be determined reliably to decrease the statistical errors caused by sub-sampling. In this study, methods to improve the accuracy of stem biomass estimates of the sample trees were developed. In addition, the reliability of the method applied to estimate sample-tree crown biomass was tested, and no systematic error was detected. Second, the whole information content of data should be utilized in order to achieve reliable parameter estimates and applicable and flexible model structure. In the modelling approach, the basic assumption was that the biomasses of
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Richard B. Hall
2013-07-01
Full Text Available Hybrid poplars have demonstrated high productivity as short rotation woody crops (SRWC in the Midwest USA, and the hybrid aspen “Crandon” (Populus alba L. × P. grandidenta Michx. has exhibited particularly promising yields on marginal lands. However, a key obstacle for wider deployment is the lack of economic returns early in the rotation. Alleycropping has the potential to address this issue, especially when paired with crops such as winter triticale which complete their growth cycle early in the summer and therefore are expected to exert minimal competition on establishing trees. In addition, well-placed fertilizer in low rates at planting has the potential to improve tree establishment and shorten the rotation, which is also economically desirable. To test the potential productivity of “Crandon” alleycropped with winter triticale, plots were established on five topographic positions with four different rates of fertilizer placed in the planting hole. Trees were then harvested from the plots after each of the first three growing seasons. Fertilization resulted in significant increases in branch, stem, and total aboveground biomass across all years, whereas the effects of topographic position varied by year. Allocation between branches and stems was found to be primarily a function of total aboveground biomass.
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Christopher Morhart
2016-02-01
Full Text Available Background: The global search for new ways to sequester carbon has already reached agricultural lands. Such land constitutes a major potential carbon sink. The production of high value timber within agroforestry systems can facilitate an in-situ carbon storage function. This is followed by a potential long term ex- situ carbon sinkwithin long lasting products such as veneer and furniture. For this purpose wild cherry (Prunus avium L. is an interesting option for middle Europe, yielding high prices on the timber market. Methods: A total number of 39 wild cherry were sampled in 2012 and 2013 to assess the leafless above ground biomass. The complete trees including stem and branches were separated into 1 cm diameter classes. Wood and bark from sub-samples were analysed separately and nutrient content was derived. Models for biomass estimation were constructed for all tree compartments. Results: The smallest diameter classes possess the highest proportion of bark due to smaller cross sectional area. Tree boles with a greater amount of stem wood above 10 cm in diameter will have a more constant bark proportion. Total branch bark proportion also remains relatively constant above d1.3m measurements of 8 cm. A balance is evident between the production of new branches with a low diameter and high bark proportion offset by the thickening and a relative reduction in bark proportion in larger branches. The results show that a single tree with an age of 17 and 18 years can store up to 85 kg of carbon within the aboveground biomass portion, an amount that will increase as the tree matures. Branches display greater nutrient content than stem sections per volume unit which can be attributed to a greater bark proportion. Conclusions: Using the derived models the carbon and the nutrient content of above-ground woody biomass of whole trees can be calculated. Suggested values for carbon with other major and minor nutrients held within relatively immature trees
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Sathre, Roger [Ecotechnology, Mid Sweden University, Ostersund (Sweden); Gustavsson, Leif [Ecotechnology, Mid Sweden University, Ostersund (Sweden); Bergh, Johan [Ecotechnology, Mid Sweden University, Ostersund (Sweden); Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp (Sweden)
2010-04-15
In this study we analyze the primary energy and greenhouse gas (GHG) implications of increasing biomass production by fertilizing 10% of Swedish forest land. We estimate the primary energy use and GHG emissions from forest management including production and application of N and NPK fertilizers. Based on modelled growth response, we then estimate the net primary energy and GHG benefits of using biomaterials and biofuels obtained from the increased forest biomass production. The results show an increased annual biomass harvest of 7.4 million t dry matter, of which 41% is large-diameter stemwood. About 6.9 PJ/year of additional primary energy input is needed for fertilizer production and forest management. Using the additional biomass for fuel and material substitution can reduce fossil primary energy use by 150 or 164 PJ/year if the reference fossil fuel is fossil gas or coal, respectively. About 22% of the reduced fossil energy use is due to material substitution and the remainder is due to fuel substitution. The net annual primary energy benefit corresponds to about 7% of Sweden's total primary energy use. The resulting annual net GHG emission reduction is 11.9 million or 18.1 million tCO{sub 2equiv} if the reference fossil fuel is fossil gas or coal, respectively, corresponding to 18% or 28% of the total Swedish GHG emissions in 2007. A significant one-time carbon stock increase also occurs in wood products and forest tree biomass. These results suggest that forest fertilization is an attractive option for increasing energy security and reducing net GHG emission.
International Nuclear Information System (INIS)
Sathre, Roger; Gustavsson, Leif; Bergh, Johan
2010-01-01
In this study we analyze the primary energy and greenhouse gas (GHG) implications of increasing biomass production by fertilizing 10% of Swedish forest land. We estimate the primary energy use and GHG emissions from forest management including production and application of N and NPK fertilizers. Based on modelled growth response, we then estimate the net primary energy and GHG benefits of using biomaterials and biofuels obtained from the increased forest biomass production. The results show an increased annual biomass harvest of 7.4 million t dry matter, of which 41% is large-diameter stemwood. About 6.9 PJ/year of additional primary energy input is needed for fertilizer production and forest management. Using the additional biomass for fuel and material substitution can reduce fossil primary energy use by 150 or 164 PJ/year if the reference fossil fuel is fossil gas or coal, respectively. About 22% of the reduced fossil energy use is due to material substitution and the remainder is due to fuel substitution. The net annual primary energy benefit corresponds to about 7% of Sweden's total primary energy use. The resulting annual net GHG emission reduction is 11.9 million or 18.1 million tCO 2equiv if the reference fossil fuel is fossil gas or coal, respectively, corresponding to 18% or 28% of the total Swedish GHG emissions in 2007. A significant one-time carbon stock increase also occurs in wood products and forest tree biomass. These results suggest that forest fertilization is an attractive option for increasing energy security and reducing net GHG emission.
Energy Technology Data Exchange (ETDEWEB)
Sathre, Roger; Gustavsson, Leif [Ecotechnology, Mid Sweden University, Oestersund (Sweden); Bergh, Johan [Ecotechnology, Mid Sweden University, Oestersund (Sweden); Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp (Sweden)
2010-04-15
In this study we analyze the primary energy and greenhouse gas (GHG) implications of increasing biomass production by fertilizing 10% of Swedish forest land. We estimate the primary energy use and GHG emissions from forest management including production and application of N and NPK fertilizers. Based on modelled growth response, we then estimate the net primary energy and GHG benefits of using biomaterials and biofuels obtained from the increased forest biomass production. The results show an increased annual biomass harvest of 7.4 million t dry matter, of which 41% is large-diameter stemwood. About 6.9 PJ/year of additional primary energy input is needed for fertilizer production and forest management. Using the additional biomass for fuel and material substitution can reduce fossil primary energy use by 150 or 164 PJ/year if the reference fossil fuel is fossil gas or coal, respectively. About 22% of the reduced fossil energy use is due to material substitution and the remainder is due to fuel substitution. The net annual primary energy benefit corresponds to about 7% of Sweden's total primary energy use. The resulting annual net GHG emission reduction is 11.9 million or 18.1 million tCO{sub 2equiv} if the reference fossil fuel is fossil gas or coal, respectively, corresponding to 18% or 28% of the total Swedish GHG emissions in 2007. A significant one-time carbon stock increase also occurs in wood products and forest tree biomass. These results suggest that forest fertilization is an attractive option for increasing energy security and reducing net GHG emission. (author)
Hickey, S. M.; Callow, N. J.; Phinn, S.; Lovelock, C. E.; Duarte, C. M.
2018-01-01
Mangroves are integral to ecosystem services provided by the coastal zone, in particular carbon (C) sequestration and storage. Allometric relationships linking mangrove height to estimated biomass and C stocks have been developed from field sampling, while various forms of remote sensing has been used to map vegetation height and biomass. Here we combine both these approaches to investigate spatial patterns in living biomass of mangrove forests in a small area of mangrove in north-west Australia. This study used LiDAR data and Landsat 8 OLI (Operational Land Imager) with allometric equations to derive mangrove height, biomass, and C stock estimates. We estimated the study site, Mangrove Bay, a semi-arid site in north-western Australia, contained 70 Mg ha-1 biomass and 45 Mg C ha-1 organic C, with total stocks of 2417 Mg biomass and 778 Mg organic C. Using spatial statistics to identify the scale of clustering of mangrove pixels, we found that living biomass and C stock declined with increasing distance from hydrological features (creek entrance: 0-150 m; y = -0.00041x + 0.9613, R2 = 0.96; 150-770 m; y = -0.0008x + 1.6808, R2 = 0.73; lagoon: y = -0.0041x + 3.7943, R2 = 0.78). Our results illustrate a set pattern of living C distribution within the mangrove forest, and then highlight the role hydrologic features play in determining C stock distribution in the arid zone.
Shchepashchenko, D.; Chave, J.; Phillips, O. L.; Davies, S. J.; Lewis, S. L.; Perger, C.; Dresel, C.; Fritz, S.; Scipal, K.
2017-12-01
Forest monitoring is high on the scientific and political agenda. Global measurements of forest height, biomass and how they change with time are urgently needed as essential climate and ecosystem variables. The Forest Observation System - FOS (http://forest-observation-system.net/) is an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. FOS aims to link the Remote Sensing (RS) community with ecologists who measure forest biomass and estimating biodiversity in the field for a common benefit. The benefit of FOS for the RS community is the partnering of the most established teams and networks that manage permanent forest plots globally; to overcome data sharing issues and introduce a standard biomass data flow from tree level measurement to the plot level aggregation served in the most suitable form for the RS community. Ecologists benefit from the FOS with improved access to global biomass information, data standards, gap identification and potential improved funding opportunities to address the known gaps and deficiencies in the data. FOS closely collaborate with the Center for Tropical Forest Science -CTFS-ForestGEO, the ForestPlots.net (incl. RAINFOR, AfriTRON and T-FORCES), AusCover, Tropical managed Forests Observatory and the IIASA network. FOS is an open initiative with other networks and teams most welcome to join. The online database provides open access for both metadata (e.g. who conducted the measurements, where and which parameters) and actual data for a subset of plots where the authors have granted access. A minimum set of database values include: principal investigator and institution, plot coordinates, number of trees, forest type and tree species composition, wood density, canopy height and above ground biomass of trees. Plot size is 0.25 ha or large. The database will be essential for validating and calibrating
Imani, Gérard; Boyemba, Faustin; Lewis, Simon; Nabahungu, Nsharwasi Léon; Calders, Kim; Zapfack, Louis; Riera, Bernard; Balegamire, Clarisse; Cuni-Sanchez, Aida
2017-01-01
Tropical montane forests provide an important natural laboratory to test ecological theory. While it is well-known that some aspects of forest structure change with altitude, little is known on the effects of altitude on above ground biomass (AGB), particularly with regard to changing height-diameter allometry. To address this we investigate (1) the effects of altitude on height-diameter allometry, (2) how different height-diameter allometric models affect above ground biomass estimates; and (3) how other forest structural, taxonomic and environmental attributes affect above ground biomass using 30 permanent sample plots (1-ha; all trees ≥ 10 cm diameter measured) established between 1250 and 2600 m asl in Kahuzi Biega National Park in eastern Democratic Republic of Congo. Forest structure and species composition differed with increasing altitude, with four forest types identified. Different height-diameter allometric models performed better with the different forest types, as trees got smaller with increasing altitude. Above ground biomass ranged from 168 to 290 Mg ha-1, but there were no significant differences in AGB between forests types, as tree size decreased but stem density increased with increasing altitude. Forest structure had greater effects on above ground biomass than forest diversity. Soil attributes (K and acidity, pH) also significantly affected above ground biomass. Results show how forest structural, taxonomic and environmental attributes affect above ground biomass in African tropical montane forests. They particularly highlight that the use of regional height-diameter models introduces significant biases in above ground biomass estimates, and that different height-diameter models might be preferred for different forest types, and these should be considered in future studies.
Forest dynamics in the temperate rainforests of Alaska: from individual tree to regional scales
Tara M. Barrett
2015-01-01
Analysis of remeasurement data from 1079 Forest Inventory and Analysis (FIA) plots revealed multi-scale change occurring in the temperate rainforests of southeast Alaska. In the western half of the region, including Prince William Sound, aboveground live tree biomass and carbon are increasing at a rate of 8 ( ± 2 ) percent per decade, driven by an increase in Sitka...
Nguyen, Ha Thanh
Tropical peatlands have some of the highest carbon densities of any ecosystem and are under enormous development pressure. This dissertation aimed to provide better estimates of the scales and trends of ecological impacts from tropical peatland deforestation and degradation across more than 7,000 hectares of both intact and disturbed peatlands in northwestern Borneo. We combined direct field sampling and airborne Light Detection And Ranging (LiDAR) data to empirically quantify forest structures and aboveground live biomass across a largely intact tropical peat dome. The observed biomass density of 217.7 +/- 28.3 Mg C hectare-1 was very high, exceeding many other tropical rainforests. The canopy trees were 65m in height, comprising 81% of the aboveground biomass. Stem density was observed to increase across the 4m elevational gradient from the dome margin to interior with decreasing stem height, crown area and crown roughness. We also developed and implemented a multi-temporal, Landsat resolution change detection algorithm for identify disturbance events and assessing forest trends in aseasonal tropical peatlands. The final map product achieved more than 92% user's and producer's accuracy, revealing that after more than 25 years of management and disturbances, only 40% of the area was intact forest. Using a chronosequence approach, with a space for time substitution, we then examined the temporal dynamics of peatlands and their recovery from disturbance. We observed widespread arrested succession in previously logged peatlands consistent with hydrological limits on regeneration and degraded peat quality following canopy removal. We showed that clear-cutting, selective logging and drainage could lead to different modes of regeneration and found that statistics of the Enhanced Vegetation Index and LiDAR height metrics could serve as indicators of harvesting intensity, impacts, and regeneration stage. Long-term, continuous monitoring of the hydrology and ecology of