WorldWideScience

Sample records for aboveground biomass estimation

  1. MODIS Based Estimation of Forest Aboveground Biomass in China

    Science.gov (United States)

    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

  2. MODIS Based Estimation of Forest Aboveground Biomass in China.

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    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.

  3. 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.

  4. Timber volume and aboveground live tree biomass estimations for landscape analyses in the Pacific Northwest

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    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...

  5. Evaluating lidar point densities for effective estimation of aboveground biomass

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    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.

  6. Root biomass in cereals, catch crops and weeds can be reliably estimated without considering aboveground biomass

    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...

  7. 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.

  8. Developing a generalized allometric equation for aboveground biomass estimation

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    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

  9. Estimating aboveground tree biomass on forest land in the Pacific Northwest: a comparison of approaches

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    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,...

  10. Estimates of forest canopy height and aboveground biomass using ICESat.

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    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...

  11. Estimating forest and woodland aboveground biomass using active and passive remote sensing

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    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.

  12. Airborne laser scanner-assisted estimation of aboveground biomass change in a temperate oak-pine forest

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    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...

  13. Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam.

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    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.

  14. Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest 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.

  15. Estimation of Aboveground Biomass Using Manual Stereo Viewing of Digital Aerial Photographs in Tropical Seasonal Forest

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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.

  16. 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.

  17. 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.

  18. Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

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    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.

  19. Allometric Models Based on Bayesian Frameworks Give Better Estimates of Aboveground Biomass in the Miombo Woodlands

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    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.

  20. Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales

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    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

  1. Spatial distribution of forest aboveground biomass estimated from remote sensing and forest inventory data in New England, USA

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    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...

  2. Methods and equations for estimating aboveground volume, biomass, and carbon for trees in the U.S. forest inventory, 2010

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    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...

  3. Validation databases for simulation models: aboveground biomass and net primary productive, (NPP) estimation using eastwide FIA data

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    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...

  4. Estimating Stand Volume and Above-Ground Biomass of Urban Forests Using LiDAR

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    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.

  5. Remote Sensing-based estimates of herbaceous aboveground biomass on the Mongolian Plateau

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    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.

  6. Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations

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    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...

  7. Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

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    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...

  8. Estimation of crown biomass of Pinus pinaster stands and shrubland above-ground biomass using forest inventory data, remotely sensed imagery and spatial prediction models

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    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...

  9. Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis

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    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.

  10. Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.).

    Science.gov (United States)

    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.

  11. Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor.

    Science.gov (United States)

    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.

  12. Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

    Science.gov (United States)

    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.

  13. Estimating Aboveground Biomass and Carbon Stocks in Periurban Andean Secondary Forests Using Very High Resolution Imagery

    Directory of Open Access Journals (Sweden)

    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.

  14. Estimation of aboveground biomass in Mediterranean forests by statistical modelling of ASTER fraction images

    Science.gov (United States)

    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.

  15. [Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

    Science.gov (United States)

    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.

  16. Estimating above-ground biomass on mountain meadows and pastures through remote sensing

    Science.gov (United States)

    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.

  17. Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska

    Science.gov (United States)

    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.

  18. Allometric equations for estimating aboveground biomass for common shrubs in northeastern California

    Science.gov (United States)

    Steve Huff; Martin Ritchie; H. Temesgen

    2017-01-01

    Selected allometric equations and fitting strategies were evaluated for their predictive abilities for estimating above ground biomass for seven species of shrubs common to northeastern California. Size classes for woody biomass were categorized as 1-h fuels (0.1–0.6 cm), 10-h fuels (0.6–2.5 cm), 100-h fuels (2.5–7.6 cm), and 1000-h fuels (greater than 7.7 cm in...

  19. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

    Directory of Open Access Journals (Sweden)

    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.

  20. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

    OpenAIRE

    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...

  1. 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.

  2. A Comparison of Two Above-Ground Biomass Estimation Techniques Integrating Satellite-Based Remotely Sensed Data and Ground Data for Tropical and Semiarid Forests in Puerto Rico

    Science.gov (United States)

    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)...

  3. Improving estimation of tree carbon stocks by harvesting aboveground woody biomass within airborne LiDAR flight areas

    Science.gov (United States)

    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

  4. Aboveground Biomass Estimation Using Reconstructed Feature of Airborne Discrete-Return LIDAR by Auto-Encoder Neural Network

    Science.gov (United States)

    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.

  5. Evaluation of Radiometric and Atmospheric Correction Algorithms for Aboveground Forest Biomass Estimation Using Landsat 5 TM Data

    Directory of Open Access Journals (Sweden)

    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.

  6. [Tree above-ground biomass allometries for carbon stocks estimation in the Caribbean mangroves in Colombia].

    Science.gov (United States)

    Yepes, Adriana; Zapata, Mauricio; Bolivar, Jhoanata; Monsalve, Alejandra; Espinosa, Sandra Milena; Sierra-Correa, Paula Cristina; Sierra, Andrés

    2016-06-01

    The distribution of carbon in “Blue Carbon” ecosystems such as mangroves is little known, when compared with the highly known terrestrial forests, despite its particular and recognized high productivity and carbon storage capacity. The objective of this study was to analyze the above ground biomass (AGB) of the species Rhizophora mangle and Avicennia germinans from the Marine Protected Area of Distrito de Manejo Integrado (DMI), Cispatá-Tinajones-La Balsa, Caribbean Colombian coast. With official authorization, we harvested and studied 30 individuals of each species, and built allometric models in order to estimate AGB. Our AGB results indicated that the studied mangrove forests of the DMI Colombian Caribbean was of 129.69 ± 20.24 Mg/ha, equivalent to 64.85 ± 10.12 MgC/ha. The DMI has an area of 8 570.9 ha in mangrove forests, and we estimated that the total carbon potential stored was about 555 795.93 Mg C. The equations generated in this study can be considered as an alternative for the assessment of carbon stocks in AGB of mangrove forests in Colombia; as other available AGB allometric models do not discriminate mangrove forests, despite being particular ecosystems. They can be used for analysis at a more detailed scale and are considered useful to determine the carbon storage potential of mangrove forests, as a country alternative to support forest conservation and emission reduction strategies. In general, the potential of carbon storage from Colombian Caribbean mangrove forests is important and could promote the country leadership of the “blue carbon” stored.

  7. Mixed-species allometric equations and estimation of aboveground biomass and carbon stocks in restoring degraded landscape in northern Ethiopia

    Science.gov (United States)

    Mokria, Mulugeta; Mekuria, Wolde; Gebrekirstos, Aster; Aynekulu, Ermias; Belay, Beyene; Gashaw, Tadesse; Bräuning, Achim

    2018-02-01

    Accurate biomass estimation is critical to quantify the changes in biomass and carbon stocks following the restoration of degraded landscapes. However, there is lack of site-specific allometric equations for the estimation of aboveground biomass (AGB), which consequently limits our understanding of the contributions of restoration efforts in mitigating climate change. This study was conducted in northwestern Ethiopia to develop a multi-species allometric equation and investigate the spatial and temporal variation of C-stocks following the restoration of degraded landscapes. We harvested and weighed 84 trees from eleven dominant species from six grazing exclosures and adjacent communal grazing land. We observed that AGB correlates significantly with diameter at stump height D 30 (R 2 = 0.78 P < 0.01), and tree height H (R 2 = 0.41, P < 0.05). Our best model, which includes D 30 and H as predictors explained 82% of the variations in AGB. This model produced the lowest bias with narrow ranges of errors across different diameter classes. Estimated C-stock showed a significant positive correlation with stem density (R 2 = 0.80, P < 0.01) and basal area (R 2 = 0.84, P < 0.01). At the watershed level, the mean C-stock was 3.8 (±0.5) Mg C ha-1. Plot-level C-stocks varied between 0.1 and 13.7 Mg C ha-1. Estimated C-stocks in three- and seven-year-old exclosures exceeded estimated C-stock in the communal grazing land by 50%. The species that contribute most to C-stocks were Leucaena sp. (28%), Calpurnia aurea (21%), Euclea racemosa (20.9%), and Dodonaea angustifolia (15.8%). The equations developed in this study allow monitoring changes in C-stocks and C-sequestration following the implementation of restoration practices in northern Ethiopia over space and time. The estimated C-stocks can be used as a reference against which future changes in C-stocks can be compared.

  8. Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta

    Science.gov (United States)

    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

  9. Estimating Above-Ground Biomass in Sub-Tropical Buffer Zone Community Forests, Nepal, Using Sentinel 2 Data

    Directory of Open Access Journals (Sweden)

    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.

  10. A Comparison of Regression Techniques for Estimation of Above-Ground Winter Wheat Biomass Using Near-Surface Spectroscopy

    Directory of Open Access Journals (Sweden)

    Jibo Yue

    2018-01-01

    Full Text Available Above-ground biomass (AGB provides a vital link between solar energy consumption and yield, so its correct estimation is crucial to accurately monitor crop growth and predict yield. In this work, we estimate AGB by using 54 vegetation indexes (e.g., Normalized Difference Vegetation Index, Soil-Adjusted Vegetation Index and eight statistical regression techniques: artificial neural network (ANN, multivariable linear regression (MLR, decision-tree regression (DT, boosted binary regression tree (BBRT, partial least squares regression (PLSR, random forest regression (RF, support vector machine regression (SVM, and principal component regression (PCR, which are used to analyze hyperspectral data acquired by using a field spectrophotometer. The vegetation indexes (VIs determined from the spectra were first used to train regression techniques for modeling and validation to select the best VI input, and then summed with white Gaussian noise to study how remote sensing errors affect the regression techniques. Next, the VIs were divided into groups of different sizes by using various sampling methods for modeling and validation to test the stability of the techniques. Finally, the AGB was estimated by using a leave-one-out cross validation with these powerful techniques. The results of the study demonstrate that, of the eight techniques investigated, PLSR and MLR perform best in terms of stability and are most suitable when high-accuracy and stable estimates are required from relatively few samples. In addition, RF is extremely robust against noise and is best suited to deal with repeated observations involving remote-sensing data (i.e., data affected by atmosphere, clouds, observation times, and/or sensor noise. Finally, the leave-one-out cross-validation method indicates that PLSR provides the highest accuracy (R2 = 0.89, RMSE = 1.20 t/ha, MAE = 0.90 t/ha, NRMSE = 0.07, CV (RMSE = 0.18; thus, PLSR is best suited for works requiring high

  11. Potential of ALOS2 and NDVI to Estimate Forest Above-Ground Biomass, and Comparison with Lidar-Derived Estimates

    Directory of Open Access Journals (Sweden)

    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

  12. Estimating aboveground tree biomass for beetle-killed lodgepole pine in the Rocky Mountains of northern Colorado

    Science.gov (United States)

    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...

  13. Towards ground-truthing of spaceborne estimates of above-ground biomass and leaf area index in tropical rain forests

    Science.gov (United States)

    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

  14. Evaluating Generic Pantropical Allometric Models for the Estimation of Above-Ground Biomass in the Teak Plantations of Southern Western Ghats, India

    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.

  15. Estimating Forest Aboveground Biomass by Combining ALOS PALSAR and WorldView-2 Data: A Case Study at Purple Mountain National Park, Nanjing, China

    Directory of Open Access Journals (Sweden)

    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

  16. Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

    Science.gov (United States)

    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.

  17. Estimation of Aboveground Biomass in Alpine Forests: A Semi-Empirical Approach Considering Canopy Transparency Derived from Airborne LiDAR Data

    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.

  18. Siberian Boreal Forest Aboveground Biomass and Fire Scar Maps, Russia, 1969-2007

    Data.gov (United States)

    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...

  19. 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.

  20. Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

    Science.gov (United States)

    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

  1. Estimating aboveground forest biomass carbon and fire consumption in the U.S. Utah High Plateaus using data from the Forest Inventory and Analysis program, Landsat, and LANDFIRE

    Science.gov (United States)

    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

  2. Modeling aboveground biomass of Tamarix ramosissima in the Arkansas River Basin of Southeastern Colorado, USA

    Science.gov (United States)

    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.

  3. Above-ground biomass equations for Pinus radiata D. Don in Asturias

    Directory of Open Access Journals (Sweden)

    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.

  4. 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.

  5. [Spatial distribution of aboveground biomass of shrubs in Tianlaochi catchment of the Qilian Mountains].

    Science.gov (United States)

    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).

  6. Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

    Science.gov (United States)

    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

  7. 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....

  8. Estimating the Above-Ground Biomass in Miombo Savanna Woodlands (Mozambique, East Africa Using L-Band Synthetic Aperture Radar Data

    Directory of Open Access Journals (Sweden)

    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.

  9. Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico.

    Science.gov (United States)

    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

  10. The relationship between species richness and aboveground biomass in a primary Pinus kesiya forest of Yunnan, southwestern China.

    Science.gov (United States)

    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.

  11. Determining Optimal New Generation Satellite Derived Metrics for Accurate C3 and C4 Grass Species Aboveground Biomass Estimation in South Africa

    Directory of Open Access Journals (Sweden)

    Cletah Shoko

    2018-04-01

    Full Text Available While satellite data has proved to be a powerful tool in estimating C3 and C4 grass species Aboveground Biomass (AGB, finding an appropriate sensor that can accurately characterize the inherent variations remains a challenge. This limitation has hampered the remote sensing community from continuously and precisely monitoring their productivity. This study assessed the potential of a Sentinel 2 MultiSpectral Instrument, Landsat 8 Operational Land Imager, and WorldView-2 sensors, with improved earth imaging characteristics, in estimating C3 and C4 grasses AGB in the Cathedral Peak, South Africa. Overall, all sensors have shown considerable potential in estimating species AGB; with the use of different combinations of the derived spectral bands and vegetation indices producing better accuracies. However, WorldView-2 derived variables yielded better predictive accuracies (R2 ranging between 0.71 and 0.83; RMSEs between 6.92% and 9.84%, followed by Sentinel 2, with R2 between 0.60 and 0.79; and an RMSE 7.66% and 14.66%. Comparatively, Landsat 8 yielded weaker estimates, with R2 ranging between 0.52 and 0.71 and high RMSEs ranging between 9.07% and 19.88%. In addition, spectral bands located within the red edge (e.g., centered at 0.705 and 0.745 µm for Sentinel 2, SWIR, and NIR, as well as the derived indices, were found to be very important in predicting C3 and C4 AGB from the three sensors. The competence of these bands, especially of the free-available Landsat 8 and Sentinel 2 dataset, was also confirmed from the fusion of the datasets. Most importantly, the three sensors managed to capture and show the spatial variations in AGB for the target C3 and C4 grassland area. This work therefore provides a new horizon and a fundamental step towards C3 and C4 grass productivity monitoring for carbon accounting, forage mapping, and modelling the influence of environmental changes on their productivity.

  12. Above-ground biomass of mangrove species. I. Analysis of models

    Science.gov (United States)

    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.

  13. Standing crop and aboveground biomass partitioning of a dwarf mangrove forest in Taylor River Slough, Florida

    Science.gov (United States)

    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.

  14. 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 ...

  15. Does functional trait diversity predict aboveground biomass and productivity of tropical forests? Testing three alternative hypotheses

    OpenAIRE

    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...

  16. Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests

    Directory of Open Access Journals (Sweden)

    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

  17. Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests

    Science.gov (United States)

    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

  18. Loss of aboveground forest biomass and landscape biomass variability in Missouri, US

    Science.gov (United States)

    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 ≥13 cm) and landscape variation of biomass in forests of the Ozarks and Plains landscapes in Missouri, USA...

  19. Carbon sequestration rate and aboveground biomass carbon potential of three young species in lower Gangetic plain.

    Science.gov (United States)

    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.

  20. Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar.

    Science.gov (United States)

    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.

  1. Terrestrial laser scanning to quantify above-ground biomass of structurally complex coastal wetland vegetation

    Science.gov (United States)

    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.

  2. [Spatial distribution of Tamarix ramosissima aboveground biomass and water consumption in the lower reaches of Heihe River, Northwest China].

    Science.gov (United States)

    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.

  3. Tropical forest biomass estimation from truncated stand tables.

    Science.gov (United States)

    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.

  4. Evaluation of total aboveground biomass and total merchantable biomass in Missouri

    Science.gov (United States)

    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...

  5. Comparative analysis of spectral unmixing and neural networks for estimating small diameter tree above-ground biomass in the State of Mississippi

    Science.gov (United States)

    Moham P. Tiruveedhula; Joseph Fan; Ravi R. Sadasivuni; Surya S. Durbha; David L. Evans

    2010-01-01

    The accumulation of small diameter trees (SDTs) is becoming a nationwide concern. Forest management practices such as fire suppression and selective cutting of high grade timber have contributed to an overabundance of SDTs in many areas. Alternative value-added utilization of SDTs (for composite wood products and biofuels) has prompted the need to estimate their...

  6. Evaluation of sampling strategies to estimate crown biomass

    Science.gov (United States)

    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...

  7. Tree height integrated into pantropical forest biomass estimates

    NARCIS (Netherlands)

    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

  8. Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar

    Science.gov (United States)

    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.

  9. Bioenergy production potential for aboveground biomass from a subtropical constructed wetland

    Energy Technology Data Exchange (ETDEWEB)

    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)

  10. Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran

    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

  11. Dynamics, aboveground biomass and composition on permanent plots, Tambopata National Reserve. Madre de Dios, Peru

    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.

  12. Modeling loblolly pine aboveground live biomass in a mature pine-hardwood stand: a cautionary tale

    Science.gov (United States)

    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...

  13. Aboveground biomass subdivisions in woody species of the savanna ecosystem project study area, Nylsvley

    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...

  14. Experimental effects of herbivore density on above-ground plant biomass in an alpine grassland ecosystem

    OpenAIRE

    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...

  15. Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon

    Science.gov (United States)

    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+).

  16. Remote Sensing of Aboveground Biomass in Tropical Secondary Forests: A Review

    Directory of Open Access Journals (Sweden)

    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.

  17. High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.

    Science.gov (United States)

    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

  18. Above-ground biomass investments and light interception of tropical forest trees and lianas early in succession

    NARCIS (Netherlands)

    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

  19. Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

    Science.gov (United States)

    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.

  20. Decomposition of aboveground biomass of a herbaceous wetland stand

    OpenAIRE

    KLIMOVIČOVÁ, Lucie

    2010-01-01

    The master?s thesis is part of the project GA ČR č. P504/11/1151- Role of plants in the greenhouse gas budget of a sedge fen. This thesis deals with the decomposition of aboveground vegetation in a herbaceous wetland. The decomposition rate was established on the flooded part of the Wet Meadows near Třeboň. The rate of the decomposition processes was evaluated using the litter-bag method. Mesh bags filled with dry plant matter were located in the vicinity of the automatic meteorological stati...

  1. Structure, Aboveground Biomass, and Soil Characterization of Avicennia marina in Eastern Mangrove Lagoon National Park, Abu Dhabi

    Science.gov (United States)

    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.

  2. Relationship between aboveground biomass and multiple measures of biodiversity in subtropical forest of Puerto Rico

    Science.gov (United States)

    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...

  3. Predicting aboveground forest biomass with topographic variables in human-impacted tropical dry forest landscapes

    NARCIS (Netherlands)

    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

  4. Environmental and biotic controls over aboveground biomass throughout a tropical rainforest

    Science.gov (United States)

    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...

  5. Aboveground biomass and nutrient accumulation 20 years after clear-cutting a southern Appalachian watershed

    Science.gov (United States)

    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),...

  6. Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data

    Science.gov (United States)

    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...

  7. Long-term above-ground biomass production in a red oak-pecan agroforestry system

    Science.gov (United States)

    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-...

  8. 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

  9. Aboveground Biomass and Carbon in a South African Mistbelt Forest and the Relationships with Tree Species Diversity and Forest Structures

    Directory of Open Access Journals (Sweden)

    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.

  10. Demographic controls of aboveground forest biomass across North America.

    Science.gov (United States)

    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.

  11. Tundra plant above-ground biomass and shrub dominance mapped across the North Slope of Alaska

    Science.gov (United States)

    Berner, Logan T.; Jantz, Patrick; Tape, Ken D.; Goetz, Scott J.

    2018-03-01

    Arctic tundra is becoming greener and shrubbier due to recent warming. This is impacting climate feedbacks and wildlife, yet the spatial distribution of plant biomass in tundra ecosystems is uncertain. In this study, we mapped plant and shrub above-ground biomass (AGB; kg m-2) and shrub dominance (%; shrub AGB/plant AGB) across the North Slope of Alaska by linking biomass harvests at 28 field sites with 30 m resolution Landsat satellite imagery. We first developed regression models (p plant AGB (r 2 = 0.79) and shrub AGB (r 2 = 0.82) based on the normalized difference vegetation index (NDVI) derived from imagery acquired by Landsat 5 and 7. We then predicted regional plant and shrub AGB by combining these regression models with a regional Landsat NDVI mosaic built from 1721 summer scenes acquired between 2007 and 2016. Our approach employed a Monte Carlo uncertainty analysis that propagated sampling and sensor calibration errors. We estimated that plant AGB averaged 0.74 (0.60, 0.88) kg m-2 (95% CI) and totaled 112 (91, 135) Tg across the region, with shrub AGB accounting for ~43% of regional plant AGB. The new maps capture landscape variation in plant AGB visible in high resolution satellite and aerial imagery, notably shrubby riparian corridors. Modeled shrub AGB was strongly correlated with field measurements of shrub canopy height at 25 sites (rs  = 0.88) and with a regional map of shrub cover (rs  = 0.76). Modeled plant AGB and shrub dominance were higher in shrub tundra than graminoid tundra and increased between areas with the coldest and warmest summer air temperatures, underscoring the fact that future warming has the potential to greatly increase plant AGB and shrub dominance in this region. These new biomass maps provide a unique source of ecological information for a region undergoing rapid environmental change.

  12. 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.

  13. Reducing Uncertainty in Mapping of Mangrove Aboveground Biomass Using Airborne Discrete Return Lidar Data

    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.

  14. LEAF AREA DYNAMICS AND ABOVEGROUND BIOMASS OF SPECIFIC VEGETATION TYPES OF A SEMI-ARID GRASSLAND IN SOUTHERN ETHIOPIA

    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.

  15. Community-weighted mean of leaf traits and divergence of wood traits predict aboveground biomass in secondary subtropical forests.

    Science.gov (United States)

    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

  16. Individual tree size inequality enhances aboveground biomass in homegarden agroforestry systems in the dry zone of Sri Lanka.

    Science.gov (United States)

    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

  17. Improving North American forest biomass estimates from literature synthesis and meta-analysis of existing biomass equations

    Science.gov (United States)

    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 (...

  18. Above-ground biomass production and allometric relations of Eucalyptus globulus Labill. coppice plantations along a chronosequence in the central highlands of Ethiopia

    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

  19. Above-ground biomass production and allometric relations of Eucalyptus globulus Labill. coppice plantations along a chronosequence in the central highlands of Ethiopia

    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)

  20. Aboveground and belowground biomass allocation in native Prosopis caldenia Burkart secondaries woodlands in the semi-arid Argentinean pampas

    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

  1. Grassland Aboveground Biomass in Inner Mongolia: Dynamics (2001-2016) and Driving force

    Science.gov (United States)

    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

  2. Aboveground Biomass Monitoring over Siberian Boreal Forest Using Radar Remote Sensing Data

    Science.gov (United States)

    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].

  3. Topographically mediated controls on aboveground biomass across a mediterranean-type landscape

    Science.gov (United States)

    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.

  4. Allometric Scaling and Resource Limitations Model of Total Aboveground Biomass in Forest Stands: Site-scale Test of Model

    Science.gov (United States)

    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

  5. QUANTIFYING FOREST ABOVEGROUND CARBON POOLS AND FLUXES USING MULTI-TEMPORAL LIDAR A report on field monitoring, remote sensing MMV, GIS integration, and modeling results for forestry field validation test to quantify aboveground tree biomass and carbon

    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

  6. [Aboveground biomass of Tamarix on piedmont plain of Tianshan Mountains south slope].

    Science.gov (United States)

    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.

  7. 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)

  8. 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

  9. 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.

  10. Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes

    Science.gov (United States)

    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.

  11. Landscape-level effects on aboveground biomass of tropical forests: A conceptual framework.

    Science.gov (United States)

    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.

  12. CMS: Estimated Deforested Area Biomass, Tropical America, Africa, and Asia, 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides estimates of pre-deforestation aboveground live woody biomass (AGLB) at 30-m resolution for deforested areas of tropical America, tropical...

  13. Modelling Growth and Partitioning of Annual Above-Ground Vegetative and Reproductive Biomass of Grapevine

    Science.gov (United States)

    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

  14. Assessment of forest management influences on total live aboveground tree biomass in William B Bankhead National Forest, Alabama

    Science.gov (United States)

    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...

  15. 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.

  16. Impact of deforestation and climate on the Amazon Basin's above-ground biomass during 1993-2012.

    Science.gov (United States)

    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.

  17. 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.

  18. Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data

    Directory of Open Access Journals (Sweden)

    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

  19. Retrieving aboveground biomass of wetland Phragmites australis (common reed) using a combination of airborne discrete-return LiDAR and hyperspectral data

    Science.gov (United States)

    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.

  20. Testing the generality of above-ground biomass allometry across plant functional types at the continent scale.

    Science.gov (United States)

    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

  1. Diversity and aboveground biomass of lianas in the tropical seasonal rain forests of Xishuangbanna, SW China.

    Science.gov (United States)

    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.

  2. Estimating Swedish biomass energy supply

    International Nuclear Information System (INIS)

    Johansson, J.; Lundqvist, U.

    1999-01-01

    Biomass is suggested to supply an increasing amount of energy in Sweden. There have been several studies estimating the potential supply of biomass energy, including that of the Swedish Energy Commission in 1995. The Energy Commission based its estimates of biomass supply on five other analyses which presented a wide variation in estimated future supply, in large part due to differing assumptions regarding important factors. In this paper, these studies are assessed, and the estimated potential biomass energy supplies are discusses regarding prices, technical progress and energy policy. The supply of logging residues depends on the demand for wood products and is limited by ecological, technological, and economic restrictions. The supply of stemwood from early thinning for energy and of straw from cereal and oil seed production is mainly dependent upon economic considerations. One major factor for the supply of willow and reed canary grass is the size of arable land projected to be not needed for food and fodder production. Future supply of biomass energy depends on energy prices and technical progress, both of which are driven by energy policy priorities. Biomass energy has to compete with other energy sources as well as with alternative uses of biomass such as forest products and food production. Technical progress may decrease the costs of biomass energy and thus increase the competitiveness. Economic instruments, including carbon taxes and subsidies, and allocation of research and development resources, are driven by energy policy goals and can change the competitiveness of biomass energy

  3. Spatial effects of aboveground biomass on soil ecological parameters and trace gas fluxes in a savannah ecosystem of Mount Kilimanjaro

    Science.gov (United States)

    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

  4. Effect of nitrogen addition and drought on above-ground biomass of expanding tall grasses Calamagrostis epigejos and Arrhenatherum elatius

    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

  5. Does biodiversity make a difference? Relationships between species richness, evolutionary diversity, and aboveground live tree biomass across US forests

    Science.gov (United States)

    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....

  6. Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates

    Science.gov (United States)

    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.

  7. WATCHING GRASS GROW- A PILOT STUDY ON THE SUITABILITY OF PHOTOGRAMMETRIC TECHNIQUES FOR QUANTIFYING CHANGE IN ABOVEGROUND BIOMASS IN GRASSLAND EXPERIMENTS

    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.

  8. Aboveground dry biomass partitioning and nitrogen accumulation in early maturing soybean ‘Merlin’

    Directory of Open Access Journals (Sweden)

    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.

  9. [Simulation study on the effects of climate change on aboveground biomass of plantation in southern China: Taking Moshao forest farm in Huitong Ecological Station as an example].

    Science.gov (United States)

    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

  10. Aboveground tree biomass in a recovering tropical sal (Shorea robusta Gaertn. f.) forest of Eastern Ghats, India

    Energy Technology Data Exchange (ETDEWEB)

    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)

  11. Tree height and tropical forest biomass estimation

    Science.gov (United States)

    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....

  12. Lidar remote sensing of above-ground biomass in three biomes.

    Science.gov (United States)

    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...

  13. Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran).

    Science.gov (United States)

    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.

  14. Ability of LANDSAT-8 Oli Derived Texture Metrics in Estimating Aboveground Carbon Stocks of Coppice Oak Forests

    Science.gov (United States)

    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

  15. Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

    Science.gov (United States)

    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.

  16. Taxonomic and Functional Responses of Soil Microbial Communities to Annual Removal of Aboveground Plant Biomass

    Science.gov (United States)

    Guo, Xue; Zhou, Xishu; Hale, Lauren; Yuan, Mengting; Feng, Jiajie; Ning, Daliang; Shi, Zhou; Qin, Yujia; Liu, Feifei; Wu, Liyou; He, Zhili; Van Nostrand, Joy D.; Liu, Xueduan; Luo, Yiqi; Tiedje, James M.; Zhou, Jizhong

    2018-01-01

    Clipping, removal of aboveground plant biomass, is an important issue in grassland ecology. However, few studies have focused on the effect of clipping on belowground microbial communities. Using integrated metagenomic technologies, we examined the taxonomic and functional responses of soil microbial communities to annual clipping (2010–2014) in a grassland ecosystem of the Great Plains of North America. Our results indicated that clipping significantly (P microbial respiration rates. Annual temporal variation within the microbial communities was much greater than the significant changes introduced by clipping, but cumulative effects of clipping were still observed in the long-term scale. The abundances of some bacterial and fungal lineages including Actinobacteria and Bacteroidetes were significantly (P microbial communities were significantly correlated with soil respiration and plant productivity. Intriguingly, clipping effects on microbial function may be highly regulated by precipitation at the interannual scale. Altogether, our results illustrated the potential of soil microbial communities for increased soil organic matter decomposition under clipping land-use practices. PMID:29904372

  17. [Effects of different disturbance modes on the morphological characteristics and aboveground biomass of Alhagi sparsifolia in oasis-desert ecotone].

    Science.gov (United States)

    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.

  18. Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

    Science.gov (United States)

    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

  19. 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.

  20. Estimates of grassland biomass and turnover time on the Tibetan Plateau

    Science.gov (United States)

    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.

  1. Response of Plant Height, Species Richness and Aboveground Biomass to Flooding Gradient along Vegetation Zones in Floodplain Wetlands, Northeast China.

    Science.gov (United States)

    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.

  2. Response of Plant Height, Species Richness and Aboveground Biomass to Flooding Gradient along Vegetation Zones in Floodplain Wetlands, Northeast China

    Science.gov (United States)

    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

  3. Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

    Directory of Open Access Journals (Sweden)

    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.

  4. Tropical Africa: Land use, biomass, and carbon estimates for 1980

    Energy Technology Data Exchange (ETDEWEB)

    Brown, S. [Environmental Protection Agency, Corvallis, OR (United States). Western Ecology Division; Gaston, G. [Environmental Protection Agency, Corvallis, OR (United States). National Research Council; Daniels, R.C. [ed.] [Oak Ridge National Lab., TN (United States)

    1996-06-01

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980 and describes a methodology that may be used to extend this data set to 1990 and beyond based on population and land cover data. The biomass data and carbon estimates are for woody vegetation in Tropical Africa. These data were collected to reduce the uncertainty associated with the possible magnitude of historical releases of carbon from land use change. Tropical Africa is defined here as encompassing 22.7 x 10{sup 6} km{sup 2} of the earth`s land surface and includes those countries that for the most part are located in Tropical Africa. Countries bordering the Mediterranean Sea and in southern Africa (i.e., Egypt, Libya, Tunisia, Algeria, Morocco, South Africa, Lesotho, Swaziland, and Western Sahara) have maximum potential biomass and land cover information but do not have biomass or carbon estimate. The database was developed using the GRID module in the ARC/INFO{sup TM} geographic information system. Source data were obtained from the Food and Agriculture Organization (FAO), the U.S. National Geophysical Data Center, and a limited number of biomass-carbon density case studies. These data were used to derive the maximum potential and actual (ca. 1980) aboveground biomass-carbon values at regional and country levels. The land-use data provided were derived from a vegetation map originally produced for the FAO by the International Institute of Vegetation Mapping, Toulouse, France.

  5. Diversity and aboveground biomass of lianas in the tropical seasonal rain forests of Xishuangbanna, SW China

    Directory of Open Access Journals (Sweden)

    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

  6. Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth

    Directory of Open Access Journals (Sweden)

    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.

  7. Spatiotemporal dynamics of grassland aboveground biomass on the Qinghai-Tibet Plateau based on validated MODIS NDVI.

    Science.gov (United States)

    Liu, Shiliang; Cheng, Fangyan; Dong, Shikui; Zhao, Haidi; Hou, Xiaoyun; Wu, Xue

    2017-06-23

    Spatiotemporal dynamics of aboveground biomass (AGB) is a fundamental problem for grassland environmental management on the Qinghai-Tibet Plateau (QTP). Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data can feasibly be used to estimate AGB at large scales, and their precise validation is necessary to utilize them effectively. In our study, the clip-harvest method was used at 64 plots in QTP grasslands to obtain actual AGB values, and a handheld hyperspectral spectrometer was used to calculate field-measured NDVI to validate MODIS NDVI. Based on the models between NDVI and AGB, AGB dynamics trends during 2000-2012 were analyzed. The results showed that the AGB in QTP grasslands increased during the study period, with 70% of the grasslands undergoing increases mainly in the Qinghai Province. Also, the meadow showed a larger increasing trend than steppe. Future AGB dynamic trends were also investigated using a combined analysis of the slope values and the Hurst exponent. The results showed high sustainability of AGB dynamics trends after the study period. Predictions indicate 60% of the steppe and meadow grasslands would continue to increase in AGB, while 25% of the grasslands would remain in degradation, with most of them distributing in Tibet.

  8. Effects of model choice and forest structure on inventory-based estimations of Puerto Rican forest biomass

    Science.gov (United States)

    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...

  9. Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps

    Directory of Open Access Journals (Sweden)

    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.

  10. Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

    Science.gov (United States)

    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

  11. Disentangling the effects of species diversity, and intraspecific and interspecific tree size variation on aboveground biomass in dry zone homegarden agroforestry systems.

    Science.gov (United States)

    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

  12. 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....

  13. The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates

    Science.gov (United States)

    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.

  14. Seeing the Forest through the Trees: Citizen Scientists Provide Critical Data to Refine Aboveground Carbon Estimates in Restored Riparian Forests

    Science.gov (United States)

    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

  15. 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...

  16. Estimating patterns in Spartina alterniflora belowground biomass within salt marshes

    Science.gov (United States)

    O'Connell, J. L.; Mishra, D. R.; Alber, M.; Byrd, K. B.

    2017-12-01

    Belowground biomass of marsh plants, such as Spartina alterniflora, help prevent marsh loss because they promote soil accretion, stabilize soils and add organic matter. However, site-wide estimates of belowground biomass are difficult to obtain because root:shoot ratios vary considerably both within species and across sites. We are working to develop a data fusion tool that can predict key characteristics of S. alterniflora, including belowground biomass and plant canopy N, based on satellite imagery. We used field observations from four salt marsh locations along the Georgia Coast, including one that is studied as part of the Georgia Coastal Ecosystems LTER project. From field and remote-sensing data, we developed a hybrid modeling approach to estimate % foliar N (a surrogate for plant assimilated nutrients). Partial Least squares (PLS) regression analysis of Landsat-8 spectral bands could predict variation in foliar N and belowground biomass, suggesting this public data source might be utilized for site-wide assessment of plant biophysical variables in salt marshes. Spectrally estimated foliar N and aboveground biomass were associated with belowground biomass and root:shoot ratio in S. alterniflora. This mirrors results from a previous study from the Sacramento-San Joaquin Delta, CA, on Scheonoplectus acutus, a marsh plant found in some tidal freshwater marshes. Therefore remote sensing may be a useful tool for measuring whole plant productivity among multiple coastal marsh species.

  17. Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

    Science.gov (United States)

    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.

  18. The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass

    NARCIS (Netherlands)

    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

  19. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    Science.gov (United States)

    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

  20. Secondary Forest Age and Tropical Forest Biomass Estimation Using TM

    Science.gov (United States)

    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.

  1. Bridging scale gaps between regional maps of forest aboveground biomass and field sampling plots using TanDEM-X data

    Science.gov (United States)

    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

  2. Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

    Science.gov (United States)

    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...

  3. 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.

  4. Evaluation of sampling strategies to estimate crown biomass

    Directory of Open Access Journals (Sweden)

    Krishna P Poudel

    2015-01-01

    Full Text Available Background 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 modeling. However, crown biomass is difficult to predict because of the variability within and among species and sites. Thus the allometric equations used for predicting crown biomass should be based on data collected with precise and unbiased sampling strategies. In this study, we evaluate the performance different sampling strategies to estimate crown biomass and to evaluate the effect of sample size in estimating crown biomass. Methods Using data collected from 20 destructively sampled trees, we evaluated 11 different sampling strategies using six evaluation statistics: bias, relative bias, root mean square error (RMSE, relative RMSE, amount of biomass sampled, and relative biomass sampled. We also evaluated the performance of the selected sampling strategies when different numbers of branches (3, 6, 9, and 12 are selected from each tree. Tree specific log linear model with branch diameter and branch length as covariates was used to obtain individual branch biomass. Results Compared to all other methods stratified sampling with probability proportional to size estimation technique produced better results when three or six branches per tree were sampled. However, the systematic sampling with ratio estimation technique was the best when at least nine branches per tree were sampled. Under the stratified sampling strategy, selecting unequal number of branches per stratum produced approximately similar results to simple random sampling, but it further decreased RMSE when information on branch diameter is used in the design and estimation phases. Conclusions Use of

  5. Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon

    Science.gov (United States)

    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)...

  6. Predictive modeling of hazardous waste landfill total above-ground biomass using passive optical and LIDAR remotely sensed data

    Science.gov (United States)

    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.

  7. [Aboveground biomass and nutrient distribution patterns of larch plantation in a montane region of eastern Liaoning Province, China].

    Science.gov (United States)

    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%.

  8. Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

    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

  9. Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics

    NARCIS (Netherlands)

    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

  10. The variable effects of soil nitrogen availability and insect herbivory on aboveground and belowground plant biomass in an old-field ecosystem

    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...

  11. Influence of an Ice Storm on Aboveground Biomass of Subtropical Evergreen Broadleaf Forest in Lechang, Nanling Mountains of Southern China

    Directory of Open Access Journals (Sweden)

    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.

  12. Above-ground woody biomass allocation and within tree carbon and nutrient distribution of wild cherry (Prunus avium L. – a case study

    Directory of Open Access Journals (Sweden)

    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

  13. Net aboveground biomass declines of four major forest types with forest ageing and climate change in western Canada's boreal forests.

    Science.gov (United States)

    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.

  14. Estimates of US biomass energy consumption 1992

    International Nuclear Information System (INIS)

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large

  15. Estimates of US biomass energy consumption 1992

    Energy Technology Data Exchange (ETDEWEB)

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  16. Evaluating land use and aboveground biomass dynamics in an oil palm-dominated landscape in Borneo using optical remote sensing

    Science.gov (United States)

    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.

  17. Estimating Biomass of Barley Using Crop Surface Models (CSMs Derived from UAV-Based RGB Imaging

    Directory of Open Access Journals (Sweden)

    Juliane Bendig

    2014-10-01

    Full Text Available Crop monitoring is important in precision agriculture. Estimating above-ground biomass helps to monitor crop vitality and to predict yield. In this study, we estimated fresh and dry biomass on a summer barley test site with 18 cultivars and two nitrogen (N-treatments using the plant height (PH from crop surface models (CSMs. The super-high resolution, multi-temporal (1 cm/pixel CSMs were derived from red, green, blue (RGB images captured from a small unmanned aerial vehicle (UAV. Comparison with PH reference measurements yielded an R2 of 0.92. The test site with different cultivars and treatments was monitored during “Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie” (BBCH Stages 24–89. A high correlation was found between PH from CSMs and fresh biomass (R2 = 0.81 and dry biomass (R2 = 0.82. Five models for above-ground fresh and dry biomass estimation were tested by cross-validation. Modelling biomass between different N-treatments for fresh biomass produced the best results (R2 = 0.71. The main limitation was the influence of lodging cultivars in the later growth stages, producing irregular plant heights. The method has potential for future application by non-professionals, i.e., farmers.

  18. Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests.

    Science.gov (United States)

    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

  19. Evaluation of drought and UV radiation impacts on above-ground biomass of mountain grassland by spectral reflectance and thermal imaging techniques

    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

  20. Luxury consumption of soil nutrients: a possible competitive strategy in above-ground and below-ground biomass allocation and root morphology for slow-growing arctic vegetation?

    NARCIS (Netherlands)

    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

  1. Stand restoration burning in oak-pine forests in the southern Applachians: effects on aboveground biomass and carbon and nitrogen cycling

    Science.gov (United States)

    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 oak–pine 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...

  2. Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

    Science.gov (United States)

    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-...

  3. National-scale estimation of gross forest aboveground carbon loss: a case study of the Democratic Republic of the Congo

    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)

  4. Generalized allometric regression to estimate biomass of Populus in short-rotation coppice

    Energy Technology Data Exchange (ETDEWEB)

    Ben Brahim, Mohammed; Gavaland, Andre; Cabanettes, Alain [INRA Centre de Toulouse, Castanet-Tolosane Cedex (France). Unite Agroforesterie et Foret Paysanne

    2000-07-01

    Data from four different stands were combined to establish a single generalized allometric equation to estimate above-ground biomass of individual Populus trees grown on short-rotation coppice. The generalized model was performed using diameter at breast height, the mean diameter and the mean height of each site as dependent variables and then compared with the stand-specific regressions using F-test. Results showed that this single regression estimates tree biomass well at each stand and does not introduce bias with increasing diameter.

  5. Effect of growth regulator Kelpak SL on the formation of aboveground biomass of Festulolium braunii (K. Richt. A. Camus

    Directory of Open Access Journals (Sweden)

    Jacek Sosnowski

    2013-07-01

    Full Text Available A study on the cultivation of Festulolium braunii cv. 'Felopa' was carried out using polyurethane rings with a diameter of 36 cm and a height of 40 cm, which were sunk into the ground to a depth of 30 cm and filled with soil material. In this experiment, Kelpak SL was used as a bioregulator. It consists of natural plant hormones such as auxins (11 mg in dm3 and cytokinins (0.03 mg in dm3. The experimental factors were as follows: A1-control; A2 – 20% solution of the growth regulator; A3 – 40% solution; and A4 – 60% solution. The preparation was applied to all three regrowths in the form of spray, at a rate of 3 cm3 ring-1, at the stem elongation stage. The full period of this experiment was in the years 2010–2011. During this time, detailed investigations were carried out on aboveground biomass yield (g DM ring-1, number of shoots (pcs ring-1, leaf blade length (cm, width of the leaf blade base (mm, leaf greenness index (SPAD. The study showed a significant effect of the growth regulator on the formation of Festulolium braunii biomass. However, its highest effectiveness was observed when the 60% solution was applied.

  6. A tree biomass and carbon estimation system

    Science.gov (United States)

    Emily B. Schultz; Thomas G. Matney; Donald L. Grebner

    2013-01-01

    Appropriate forest management decisions for the developing woody biofuel and carbon credit markets require inventory and growth-and-yield systems reporting component tree dry weight biomass estimates. We have developed an integrated growth-and-yield and biomass/carbon calculator. The objective was to provide Mississippi’s State inventory system with bioenergy economic...

  7. Biotic and abiotic controls on the distribution of tropical forest aboveground biomass

    Science.gov (United States)

    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

  8. Tropical-forest biomass estimation at X-Band from the spaceborne TanDEM-X interferometer

    Science.gov (United States)

    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...

  9. Forest biomass estimated from MODIS and FIA data in the Lake States: MN, WI and MI, USA

    Science.gov (United States)

    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...

  10. Aboveground biomass equations for 7-year-old Acacia mangium Willd in Botucatu, Brazil

    Science.gov (United States)

    Ricardo A. A. Veiga; Maria A. M. Brasil; Carlos M. Carvalho

    2000-01-01

    The biomass of steins, leaves, and branches was determined for 152 sample trees of Acacia mangium Willd were in a 7-year-old experimental plantation in Botucatu, Sao Paulo State, Brazil. After felling, dimensional measurements were taken from each tree. Cross sections were collected in 125 sample trees at ground level (0 percent), 25 percent, 50...

  11. Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

    Science.gov (United States)

    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.

  12. Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

    Science.gov (United States)

    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.

  13. Field note: comparative efficacy of a woody evapotranspiration landfill cover following the removal of aboveground biomass.

    Science.gov (United States)

    Schnabel, William; Munk, Jens; Byrd, Amanda

    2015-01-01

    Woody vegetation cultivated for moisture management on evapotranspiration (ET) landfill covers could potentially serve a secondary function as a biomass crop. However, research is required to evaluate the extent to which trees could be harvested from ET covers without significantly impacting their moisture management function. This study investigated the drainage through a six-year-old, primarily poplar/cottonwood ET test cover for a period of one year following the harvest of all woody biomass exceeding a height of 30 cm above ground surface. Results were compared to previously reported drainage observed during the years leading up to the coppice event. In the first year following coppice, the ET cover was found to be 93% effective at redirecting moisture during the spring/summer season, and 95% effective during the subsequent fall/winter season. This was slightly lower than the 95% and 100% efficacy observed in the spring/summer and fall/winter seasons, respectively, during the final measured year prior to coppice. However, the post-coppice efficacy was higher than the efficacy observed during the first three years following establishment of the cover. While additional longer-term studies are recommended, this project demonstrated that woody ET covers could potentially produce harvestable biomass while still effectively managing aerial moisture.

  14. Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models.

    Science.gov (United States)

    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.

  15. Changes in composition, structure and aboveground biomass over seventy-six years (1930-2006) in the Black Rock Forest, Hudson Highlands, southeastern New York State.

    Science.gov (United States)

    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.

  16. Influence of water level fluctuation on the mortality and aboveground biomass of the aquatic macrophyte Eleocharis interstincta (VAHL roemer et schults

    Directory of Open Access Journals (Sweden)

    Santos Anderson Medeiros dos

    2004-01-01

    Full Text Available The goal of this study was to study the biometric alterations of Eleocharis interstincta in response to water level fluctuations in Cabiúnas Lagoon, located on the northern coast of the state of Rio de Janeiro, in the municipality of Macaé. Three quadrats of 0.0625 m² were harvested every two weeks from June/1997 to June/1998; samples were separated into stems, dead stems (detritus and rhizome; lenghted, dried and weighted. The water level fluctuated seasonally in the macrophyte stand with two periods of drawdown. The first period occurred naturally at the end of winter and beginning of spring, when rainfall in the area was normally lowest. The second period of drawdown was the result of an artificial breaching of the sandbar that isolate the lagoon from the sea. The breach was made in the summer, at the time of highest rainfall, when the water level in the lagoon reached the maximum value recorded during the study (1.35 m. There was a strongly positive correlation of the water level with stems mean height and aboveground biomass, indicating that water level played an important role in the determination of these parameters. There was a significant difference between stem height (ANOVA; p < 0.001 and biomass (ANOVA; p < 0.001 in each sampling period, ranging from 143.9 cm and 338.8 g dry wt.m-2, before the sandbar opening, to 16.3 cm and 20.2 g dry wt.m-2 respectively after the sandbar breaching. The drastic variation of the water level, leading mass mortality of the stems, together with the lowest mean biomass/stem (0.057 g dry wt.individual-1, recorded after the sandbar breaching, did not represent a strong disturbance for E. interstincta, since the resilience time estimated for this population was about 30 days.

  17. Diversity and above-ground biomass patterns of vascular flora induced by flooding in the drawdown area of China's Three Gorges Reservoir.

    Directory of Open Access Journals (Sweden)

    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

  18. Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains

    Science.gov (United States)

    Abercrombie, H. H.; Meier, C. L.; Spencer, J. J.

    2013-12-01

    with LAI and clip harvest data to determine whether LAI can be used as a suitable proxy for aboveground standing biomass. We also compared optimal sample sizes derived from LAI data, and clip-harvest data from two different size clip harvest areas (0.1m by 1m vs. 0.1m by 2m). Sample sizes were calculated in order to estimate the mean to within a standardized level of uncertainty that will be used to guide sampling effort across all vegetation types (i.e. estimated within × 10% with 95% confidence). Finally, we employed a Semivariogram approach to determine optimal sample size and spacing.

  19. The effect of air elevated [CO2] on crown architecture and aboveground biomass in Norway spruce

    Czech Academy of Sciences Publication Activity Database

    Pokorný, Radek; Tomášková, Ivana; Slípková, Romana

    2012-01-01

    Roč. 18, č. 1 (2012), s. 2-11 ISSN 1392-1355 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073; GA MŽP(CZ) SP/2D1/70/08; GA MŽP(CZ) SP/2D1/93/07; GA AV ČR IAA600870701; GA MŠk(CZ) EE2.4.31.0056 Institutional research plan: CEZ:AV0Z60870520 Keywords : thinning * secondary shoots * biomass allocation * long-term experiment * dendrometry Subject RIV: EH - Ecology, Behaviour Impact factor: 0.379, year: 2012

  20. [Simulating the effects of climate change and fire disturbance on aboveground biomass of boreal forests in the Great Xing'an Mountains, Northeast China].

    Science.gov (United States)

    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

  1. Using basal area to estimate aboveground carbon stocks in forests: La Primavera Biosphere's Reserve, Mexico

    NARCIS (Netherlands)

    Balderas Torres, Arturo; Lovett, Jonathan Cranidge

    2012-01-01

    Increasing use of woody plants for greenhouse gas mitigation has led to demand for rapid, cost-effective estimation of forest carbon stocks. Bole diameter is readily measured and basal area can be correlated to biomass and carbon through application of allometric equations. We explore different

  2. Determining aboveground biomass of the forest successional chronosequence in a test-site of Brazilian Amazon through X- and L-band data analysis

    Science.gov (United States)

    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.

  3. Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon

    Science.gov (United States)

    Yunyun Feng; Dengsheng Lu; Qi Chen; Michael Keller; Emilio Moran; Maiza Nara dos-Santos; Edson Luis Bolfe; Mateus Batistella

    2017-01-01

    Previous research has explored the potential to integrate lidar and optical data in aboveground biomass (AGB) estimation, but how different data sources, vegetation types, and modeling algorithms influence AGB estimation is poorly understood. This research conducts a comparative analysis of different data sources and modeling approaches in improving AGB estimation....

  4. The evaluation of different forest structural indices to predict the stand aboveground biomass of even-aged Scotch pine (Pinus sylvestris L.) forests in Kunduz, Northern Turkey.

    Science.gov (United States)

    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.

  5. Estimating shrub biomass from basal stem diameters

    Energy Technology Data Exchange (ETDEWEB)

    Brown, J K

    1976-01-01

    Stem lengths and oven dry wt of stemwood and foilage were determined for shrubs in dia classes of 0 to 0.5 cm, 0.5 to 2 cm and 2 to 5 cm in various habitat types in Idaho and Montana. The logarithm of basal stem dia was closely correlated with the logarithm of wt. Regression components are presented for estimating leaf wt and total above-ground wt of 25 woody shrub species using a linear equation relating these 2 variables. Percentage stemwood wt is given for the 3 dia classes. Dia distributions for the smallest dia class were normal except for a few species with fine twigs; distributions for the other classes were positively skewed. Applications to forest fuel studies are briefly discussed.

  6. Estimating shrub biomass from basal stem diameters

    Energy Technology Data Exchange (ETDEWEB)

    Brown, J K

    1976-01-01

    Stem lengths and oven dry wt of stemwood and foilage were determined for shrubs in dia classes of 0 to 0.5 cm, 0.5 to 2 cm and 2 to 5 cm in various habitat types in Idaho and Montana. The logarithm of basal stem dia was closely correlated with the logarithm of wt. Regression components are presented for estimating leaf wt and total above-ground wt of 25 woody shrub species using a linear equation relating these 2 variables. Percentage stemwood wt is given for the 3 dia classes. Dia distributions for the smallest dia class were normal except for a few species with fine twigs: distributions for the other classes were positively skewed. Applications to forest fuel studies are briefly discussed.

  7. Potential for post-closure radionuclide redistribution due to biotic intrusion: aboveground biomass, litter production rates, and the distribution of root mass with depth at material disposal area G, Los Alamos National Laboratory

    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

  8. Mapping Above-Ground Biomass of Winter Oilseed Rape Using High Spatial Resolution Satellite Data at Parcel Scale under Waterlogging Conditions

    Directory of Open Access Journals (Sweden)

    Jiahui Han

    2017-03-01

    Full Text Available Oilseed rape (Brassica napus L. is one of the three most important oil crops in China, and is regarded as a drought-tolerant oilseed crop. However, it is commonly sensitive to waterlogging, which usually refers to an adverse environment that limits crop development. Moreover, crop growth and soil irrigation can be monitored at a regional level using remote sensing data. High spatial resolution optical satellite sensors are very useful to capture and resist unfavorable field conditions at the sub-field scale. In this study, four different optical sensors, i.e., Pleiades-1A, Worldview-2, Worldview-3, and SPOT-6, were used to estimate the dry above-ground biomass (AGB of oilseed rape and track the seasonal growth dynamics. In addition, three different soil water content field experiments were carried out at different oilseed rape growth stages from November 2014 to May 2015 in Northern Zhejiang province, China. As a significant indicator of crop productivity, AGB was measured during the seasonal growth stages of the oilseed rape at the experimental plots. Several representative vegetation indices (VIs obtained from multiple satellite sensors were compared with the simultaneously-collected oilseed rape AGB. Results showed that the estimation model using the normalized difference vegetation index (NDVI with a power regression model performed best through the seasonal growth dynamics, with the highest coefficient of determination (R2 = 0.77, the smallest root mean square error (RMSE = 104.64 g/m2, and the relative RMSE (rRMSE = 21%. It is concluded that the use of selected VIs and high spatial multiple satellite data can significantly estimate AGB during the winter oilseed rape growth stages, and can be applied to map the variability of winter oilseed rape at the sub-field level under different waterlogging conditions, which is very promising in the application of agricultural irrigation and precision agriculture.

  9. Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

    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.

  10. Allometric equations for estimating standing biomass of Avicennia marina in Bushehr of Iran

    Directory of Open Access Journals (Sweden)

    Akbar Ghasemi

    2016-07-01

    Full Text Available Today, it is important to use of ecological indicators, such as biomass for recognizing the special status of ecosystems, such as mangrove forests and also monitoring and evaluating changes through a specific period. Because using the direct method of evaluating biomass would be destructive, it is common in all similar area to use determine exact Allometric equations by using the statistical relationship between the structural characteristics of trees and their biomass and use these equations to estimate the biomass of trees. The aim of this study is estimate the aboveground biomass of mangroves and determine Allometric models for Nayband area in Bushehr, located in southern Iran. A number of mangrove trees were randomly selected. Collar diameter, crown diameter and tree height of standing trees were measured. After logging and weighing fresh weight, dry weight, trunk and branches were obtained in laboratory and biomass of components was calculated. The relationship between quantities feature of trees and biomass for determination of allometric equation was studied by using linear, power and exponential regression. The equations were compared with each other based on the different modeling parameters. The highest significant correlation was found between crown diameters and dry weight (R > 0.90. The best equations were obtained by means of an exponential and power regression models (R2adj> 0.90. The models were obtained from explained factor, suggests that there might be a relationship between the characteristics of mangrove trees and biomass.

  11. Efficient Methods of Estimating Switchgrass Biomass Supplies

    Science.gov (United States)

    Switchgrass (Panicum virgatum L.) is being developed as a biofuel feedstock for the United States. Efficient and accurate methods to estimate switchgrass biomass feedstock supply within a production area will be required by biorefineries. Our main objective was to determine the effectiveness of in...

  12. Mapping forest aboveground biomass using airborne hyperspectral and LiDAR data in the mountainous conditions of Central Europe

    Czech Academy of Sciences Publication Activity Database

    Brovkina, Olga; Novotný, Jan; Cienciala, E.; Zemek, František; Russ, R.

    2017-01-01

    Roč. 100, Mar (2017), s. 219-230 ISSN 0925-8574 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk OC09001 Institutional support: RVO:67179843 Keywords : biomass estimation * spruce * beech * airborne remote sensing * tree level * plot level Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 2.914, year: 2016

  13. Intermediate herbivory intensity of an aboveground pest promotes soil labile resources and microbial biomass via modifying rice growth

    NARCIS (Netherlands)

    Huang, J.; Liu, M.; Chen, X.; Chen, J.; Chen, F.; Li, H.; Hu, F.

    2013-01-01

    The importance of aboveground herbivores for modifying belowground ecosystems has prompted numerous studies; however, studies can be biased by context dependent conditions which lead to extremely inconsistent results. So far, the impacts of herbivory inte

  14. Development of a data driven process-based model for remote sensing of terrestrial ecosystem productivity, evapotranspiration, and above-ground biomass

    Science.gov (United States)

    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

  15. Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China.

    Science.gov (United States)

    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

  16. Growth, aboveground biomass, and nutrient concentration of young Scots pine and lodgepole pine in oil shale post-mining landscapes in Estonia.

    Science.gov (United States)

    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.

  17. Allometric Models to Predict Aboveground Woody Biomass of Black Locust (Robinia pseudoacacia L. in Short Rotation Coppice in Previous Mining and Agricultural Areas in Germany

    Directory of Open Access Journals (Sweden)

    Christin Carl

    2017-09-01

    Full Text Available Black locust is a drought-resistant tree species with high biomass productivity during juvenility; it is able to thrive on wastelands, such as former brown coal fields and dry agricultural areas. However, research conducted on this species in such areas is limited. This paper aims to provide a basis for predicting tree woody biomass for black locust based on tree, competition, and site variables at 14 sites in northeast Germany that were previously utilized for mining or agriculture. The study areas, which are located in an area covering 320 km × 280 km, are characterized by a variety of climatic and soil conditions. Influential variables, including tree parameters, competition, and climatic parameters were considered. Allometric biomass models were employed. The findings show that the most important parameters are tree and competition variables. Different former land utilizations, such as mining or agriculture, as well as growth by cores or stumps, significantly influenced aboveground woody biomass production. The new biomass models developed as part of this study can be applied to calculate woody biomass production and carbon sequestration of Robinia pseudoacacia L. in short rotation coppices in previous mining and agricultural areas.

  18. Characterizing the spatio-temporal variations of C3 and C4 dominated grasslands aboveground biomass in the Drakensberg, South Africa

    Science.gov (United States)

    Shoko, Cletah; Mutanga, Onisimo; Dube, Timothy; Slotow, Rob

    2018-06-01

    C3 and C4 grass species composition, with different physiological, morphological and most importantly phenological characteristics, influence Aboveground Biomass (AGB) and their ability to provide ecosystem goods and services, over space and time. For decades, the lack of appropriate remote sensing data sources compromised C3 and C4 grasses AGB estimation, over space and time. This resulted in uncertainties in understanding their potential and contribution to the provision of services. This study therefore examined the utility of the new multi-temporal Sentinel 2 to estimate and map C3 and C4 grasses AGB over time, using the advanced Sparse Partial Least Squares Regression (SPLSR) model. Overall results have shown the variability in AGB between C3 and C4 grasses, estimation accuracies and the performance of the SPLSR model, over time. Themeda (C4) produced higher AGB from February to April, whereas from May to September, Festuca produced higher AGB. Both species also showed a decrease in AGB in August and September, although this was most apparent for Themeda than its counterpart. Spectral bands information predicted species AGB with lowest accuracies and an improvement was observed when both spectral bands and vegetation indices were applied. For instance, in the month of May, spectral bands predicted species AGB with lowest accuracies for Festuca (R2 = 0.57; 31.70% of the mean), Themeda (R2 = 0.59; 24.02% of the mean) and combined species (R2 = 0.61; 15.64% of the mean); the use of spectral bands and vegetation indices yielded 0.77; (18.64%), 0.75 (14.27%) and 0.73 (16.47%), for Festuca, Themeda and combined species, respectively. The red edge (at 0.705 and 0.74 μm) and derived indices, NIR and SWIR 2 (2.19 μm) were found to contribute more to grass species AGB estimation, over time. Findings have also revealed the potential of the SPLSR model in estimating C3 and C4 grasses AGB using Sentinel 2 images, over time. The AGB spatial variability maps produced in

  19. [Estimation of Shenyang urban forest green biomass].

    Science.gov (United States)

    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.

  20. Establishment of Alleycropped Hybrid Aspen “Crandon” in Central Iowa, USA: Effects of Topographic Position and Fertilizer Rate on Aboveground Biomass Production and Allocation

    Directory of Open Access Journals (Sweden)

    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.

  1. 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.

  2. Analyzing spatial and temporal trends in Aboveground Biomass within the Acadian New England Forests using the complete Landsat Archive

    Science.gov (United States)

    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.

  3. Comparing aboveground biomass predictions for an uneven-aged pine-dominated stand using local, regional, and national models

    Science.gov (United States)

    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...

  4. Biomass of Sacrificed Spruce/Aspen (SNF)

    Data.gov (United States)

    National Aeronautics and Space Administration — Dimension analysis (diameter at breast high, tree height, depth of crown), estimated leaf area, and total aboveground biomass for sacrificed spruce and aspens in...

  5. Above-ground biomass models for Seabuckthorn (Hippophae salicifolia) in Mustang District, Nepal

    DEFF Research Database (Denmark)

    Rajchal, Rajesh; Meilby, Henrik

    2013-01-01

    weight of fruit and oven-dry weight of wood (stem and branches) and leaves were measured and used as a basis for developing biomass models. Diameters of the trees were measured at 30 cm above ground whereas the heights were measured in terms of the total tree height (m). Among several models tested......, the models suggested for local use were: ln(woody biomass, oven-dry, kg) = -3.083 + 2.436 ln(diameter, cm), ln (fruit biomass, fresh, kg) = -3.237 + 1.346 ln(diameter, cm) and ln(leaf biomass, oven-dry, kg) = -4.013 + 1.403 ln(Diameter, cm) with adjusted coefficients of determination of 0.99, 0.73 and 0.......91 for wood, fruit, and leaves, respectively. The models suggested for a slightly broader range of environmental conditions were: ln (woody biomass, oven-dry, kg) = -3.277 + 0.924 ln(diameter2 × height), ln(Fruit biomass, fresh, kg) = -3.146 + 0.485 ln(diameter2 × height) and ln(leaf biomass, oven-dry, kg...

  6. Estimating Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations

    Directory of Open Access Journals (Sweden)

    Bradley C. Reed

    2013-02-01

    Full Text Available Winter annual plants in southwestern North America influence fire regimes, provide forage, and help prevent erosion. Exotic annuals may also threaten native species. Monitoring winter annuals is difficult because of their ephemeral nature, making the development of a satellite monitoring tool valuable. We mapped winter annual aboveground biomass in the Desert Southwest from satellite observations, evaluating 18 algorithms using time-series vegetation indices (VI. Field-based biomass estimates were used to calibrate and evaluate each algorithm. Winter annual biomass was best estimated by calculating a base VI across the period of record and subtracting it from the peak VI for each winter season (R2 = 0.92. The normalized difference vegetation index (NDVI derived from 8-day reflectance data provided the best estimate of winter annual biomass. It is important to account for the timing of peak vegetation when relating field-based estimates to satellite VI data, since post-peak field estimates may indicate senescent biomass which is inaccurately represented by VI-based estimates. Images generated from the best-performing algorithm show both spatial and temporal variation in winter annual biomass. Efforts to manage this variable resource would be enhanced by a tool that allows the monitoring of changes in winter annual resources over time.

  7. Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach

    KAUST Repository

    Hickey, S.M.; Callow, N.J.; Phinn, S.; Lovelock, C.E.; Duarte, Carlos M.

    2017-01-01

    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

  8. Allometric Equations for Estimating Biomass and Carbon Stocks in the Temperate Forests of North-Western Mexico

    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.

  9. ROOT BIOMASS ALLOCATION IN THE WORLD'S UPLAND FORESTS

    Science.gov (United States)

    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...

  10. Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach

    Science.gov (United States)

    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.

  11. Contrasting impacts of continuous moderate drought and episodic severe droughts on the aboveground-biomass increment and litterfall of three coexisting Mediterranean woody species.

    Science.gov (United States)

    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

  12. The influences of CO2 fertilization and land use change on the total aboveground biomass in Amazonian tropical forest

    Science.gov (United States)

    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

  13. The weight of nations: an estimation of adult human biomass

    Directory of Open Access Journals (Sweden)

    Walpole Sarah

    2012-06-01

    Full Text Available Abstract Background The energy requirement of species at each trophic level in an ecological pyramid is a function of the number of organisms and their average mass. Regarding human populations, although considerable attention is given to estimating the number of people, much less is given to estimating average mass, despite evidence that average body mass is increasing. We estimate global human biomass, its distribution by region and the proportion of biomass due to overweight and obesity. Methods For each country we used data on body mass index (BMI and height distribution to estimate average adult body mass. We calculated total biomass as the product of population size and average body mass. We estimated the percentage of the population that is overweight (BMI > 25 and obese (BMI > 30 and the biomass due to overweight and obesity. Results In 2005, global adult human biomass was approximately 287 million tonnes, of which 15 million tonnes were due to overweight (BMI > 25, a mass equivalent to that of 242 million people of average body mass (5% of global human biomass. Biomass due to obesity was 3.5 million tonnes, the mass equivalent of 56 million people of average body mass (1.2% of human biomass. North America has 6% of the world population but 34% of biomass due to obesity. Asia has 61% of the world population but 13% of biomass due to obesity. One tonne of human biomass corresponds to approximately 12 adults in North America and 17 adults in Asia. If all countries had the BMI distribution of the USA, the increase in human biomass of 58 million tonnes would be equivalent in mass to an extra 935 million people of average body mass, and have energy requirements equivalent to that of 473 million adults. Conclusions Increasing population fatness could have the same implications for world food energy demands as an extra half a billion people living on the earth.

  14. Structural, physiognomic and above-ground biomass variation in savanna–forest transition zones on three continents – how different are co-occurring savanna and forest formations?

    Directory of Open Access Journals (Sweden)

    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

  15. Estimating the aboveground biomass in an old secondary forest on limestone in the Moluccas, Indonesia

    NARCIS (Netherlands)

    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

  16. Development of a Regional Lidar-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA

    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.

  17. Sampling strategies for efficient estimation of tree foliage biomass

    Science.gov (United States)

    Hailemariam Temesgen; Vicente Monleon; Aaron Weiskittel; Duncan Wilson

    2011-01-01

    Conifer crowns can be highly variable both within and between trees, particularly with respect to foliage biomass and leaf area. A variety of sampling schemes have been used to estimate biomass and leaf area at the individual tree and stand scales. Rarely has the effectiveness of these sampling schemes been compared across stands or even across species. In addition,...

  18. Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach

    KAUST Repository

    Hickey, S.M.

    2017-11-10

    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 arid zone.

  19. Assessment of variations in taxonomic diversity, forest structure, and aboveground biomass using remote sensing along an altitudinal gradient in tropical montane forest of Costa Rica

    Science.gov (United States)

    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

  20. Biomass models to estimate carbon stocks for hardwood tree species

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz-Peinado, R.; Montero, G.; Rio, M. del

    2012-11-01

    To estimate forest carbon pools from forest inventories it is necessary to have biomass models or biomass expansion factors. In this study, tree biomass models were developed for the main hardwood forest species in Spain: Alnus glutinosa, Castanea sativa, Ceratonia siliqua, Eucalyptus globulus, Fagus sylvatica, Fraxinus angustifolia, Olea europaea var. sylvestris, Populus x euramericana, Quercus canariensis, Quercus faginea, Quercus ilex, Quercus pyrenaica and Quercus suber. Different tree biomass components were considered: stem with bark, branches of different sizes, above and belowground biomass. For each species, a system of equations was fitted using seemingly unrelated regression, fulfilling the additivity property between biomass components. Diameter and total height were explored as independent variables. All models included tree diameter whereas for the majority of species, total height was only considered in the stem biomass models and in some of the branch models. The comparison of the new biomass models with previous models fitted separately for each tree component indicated an improvement in the accuracy of the models. A mean reduction of 20% in the root mean square error and a mean increase in the model efficiency of 7% in comparison with recently published models. So, the fitted models allow estimating more accurately the biomass stock in hardwood species from the Spanish National Forest Inventory data. (Author) 45 refs.

  1. A comparative analysis of extended water cloud model and backscatter modelling for above-ground biomass assessment in Corbett Tiger Reserve

    Science.gov (United States)

    Kumar, Yogesh; Singh, Sarnam; Chatterjee, R. S.; Trivedi, Mukul

    2016-04-01

    Forest biomass acts as a backbone in regulating the climate by storing carbon within itself. Thus the assessment of forest biomass is crucial in understanding the dynamics of the environment. Traditionally the destructive methods were adopted for the assessment of biomass which were further advanced to the non-destructive methods. The allometric equations developed by destructive methods were further used in non-destructive methods for the assessment, but they were mostly applied for woody/commercial timber species. However now days Remote Sensing data are primarily used for the biomass geospatial pattern assessment. The Optical Remote Sensing data (Landsat8, LISS III, etc.) are being used very successfully for the estimation of above ground biomass (AGB). However optical data is not suitable for all atmospheric/environmental conditions, because it can't penetrate through clouds and haze. Thus Radar data is one of the alternate possible ways to acquire data in all-weather conditions irrespective of weather and light. The paper examines the potential of ALOS PALSAR L-band dual polarisation data for the estimation of AGB in the Corbett Tiger Reserve (CTR) covering an area of 889 km2. The main focus of this study is to explore the accuracy of Polarimetric Scattering Model (Extended Water Cloud Model (EWCM) with respect to Backscatter model in the assessment of AGB. The parameters of the EWCM were estimated using the decomposition components (Raney Decomposition) and the plot level information. The above ground biomass in the CTR ranges from 9.6 t/ha to 322.6 t/ha.

  2. DUE GlobBiomass - Estimates of Biomass on a Global Scale

    Science.gov (United States)

    Eberle, J.; Schmullius, C.

    2017-12-01

    For the last three years, a new ESA Data User Element (DUE) project had focussed on creating improved knowledge about the Essential Climate Variable Biomass. The main purpose of the DUE GlobBiomass project is to better characterize and to reduce uncertainties of AGB estimates by developing an innovative synergistic mapping approach in five regional sites (Sweden, Poland, Mexico, Kalimantan, South Africa) for the epochs 2005, 2010 and 2015 and for one global map for the year 2010. The project team includes leading Earth Observation experts of Europe and is linked through Partnership Agreements with further national bodies from Brazil, Canada, China, Russia and South Africa. GlobBiomass has demonstrated how EO observation data can be integrated with in situ measurements and ecological understanding to provide improved biomass estimates that can be effectively exploited by users. The target users had mainly be drawn from the climate and carbon cycle modelling communities and included users concerned with carbon emissions and uptake due to biomass changes within initiatives such as REDD+. GlobBiomass provided a harmonised structure that can be exploited to address user needs for biomass information, but will be capable of being progressively refined as new data and methods become available. This presentation will give an overview of the technical prerequisites and final results of the GlobBiomass project.

  3. Estimates of global cyanobacterial biomass and its distribution

    Science.gov (United States)

    Garcia-Pichel, Ferran; Belnap, Jayne; Neuer, Susanne; Schanz, Ferdinand

    2003-01-01

    We estimated global cyanobacterial biomass in the main reservoirs of cyanobacteria on Earth: marine and freshwater plankton, arid land soil crusts, and endoliths. Estimates were based on typical population density values as measured during our research, or as obtained from literature surveys, which were then coupled with data on global geographical area coverage. Among the marine plankton, the global biomass of Prochlorococcus reaches 120 × 1012 grams of carbon (g C), and that of Synechoccus some 43 × 1012 g C. This makes Prochlorococcus and Synechococcus, in that order, the most abundant cyanobacteria on Earth. Tropical marine blooms of Trichodesmium account for an additional 10 × 1012 g C worldwide. In terrestrial environments, the mass of cyanobacteria in arid land soil crusts is estimated to reach 54 × 1012 g C and that of arid land endolithic communities an additional 14 × 1012 g C. The global biomass of planktic cyanobacteria in lakes is estimated to be around 3 × 1012 g C. Our conservative estimates, which did not include some potentially significant biomass reservoirs such as polar and subarctic areas, topsoils in subhumid climates, and shallow marine and freshwater benthos, indicate that the total global cyanobacterial biomass is in the order of 3 × 1014 g C, surpassing a thousand million metric tons (1015 g) of wet biomass.

  4. On-line Biomass Estimation in a Batch Biotechnological Process: Bacillus thuringiensis δ - endotoxins production.

    OpenAIRE

    Amicarelli, Adriana

    2010-01-01

    In this Chapter it has been addressed the problem of the biomass estimation in a batch biotechnological process: the Bacillus thuringiensis (Bt) δ-endotoxins production process. Different alternatives that can be successfully used in this sense were presented. It has been exposed the design of various biomass estimators, namely: a phenomenological biomass estimator, a standard EKF biomass estimator, a biomass estimator based on ANN, a decentralized Kalman Filter, and a biomass concentration ...

  5. Evaluation of SPOT imagery for the estimation of grassland biomass

    Science.gov (United States)

    Dusseux, P.; Hubert-Moy, L.; Corpetti, T.; Vertès, F.

    2015-06-01

    In many regions, a decrease in grasslands and change in their management, which are associated with agricultural intensification, have been observed in the last half-century. Such changes in agricultural practices have caused negative environmental effects that include water pollution, soil degradation and biodiversity loss. Moreover, climate-driven changes in grassland productivity could have serious consequences for the profitability of agriculture. The aim of this study was to assess the ability of remotely sensed data with high spatial resolution to estimate grassland biomass in agricultural areas. A vegetation index, namely the Normalized Difference Vegetation Index (NDVI), and two biophysical variables, the Leaf Area Index (LAI) and the fraction of Vegetation Cover (fCOVER) were computed using five SPOT images acquired during the growing season. In parallel, ground-based information on grassland growth was collected to calculate biomass values. The analysis of the relationship between the variables derived from the remotely sensed data and the biomass observed in the field shows that LAI outperforms NDVI and fCOVER to estimate biomass (R2 values of 0.68 against 0.30 and 0.50, respectively). The squared Pearson correlation coefficient between observed and estimated biomass using LAI derived from SPOT images reached 0.73. Biomass maps generated from remotely sensed data were then used to estimate grass reserves at the farm scale in the perspective of operational monitoring and forecasting.

  6. Estimating forest biomass and volume using airborne laser data

    Science.gov (United States)

    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.

  7. Use of GIS for estimating potential and actual forest biomass for continental South and Southeast Asia.

    Science.gov (United States)

    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.

  8. Visual obstruction as a method to quantify herbaceous biomass in ...

    African Journals Online (AJOL)

    Biomass of aboveground vegetation is a useful descriptor for studies of grazing, fire and wildlife habitat use in grassland systems. The traditional method to estimate biomass, hand-clipping, is time intensive and other indices of biomass have been used successfully. In southern Africa, the disc pasture meter has been the ...

  9. OPTIMAL WAVELENGTH SELECTION ON HYPERSPECTRAL DATA WITH FUSED LASSO FOR BIOMASS ESTIMATION OF TROPICAL RAIN FOREST

    Directory of Open Access Journals (Sweden)

    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.

  10. Productivity of aboveground coarse wood biomass and stand age related to soil hydrology of Amazonian forests in the Purus-Madeira interfluvial area

    Science.gov (United States)

    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.

  11. Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

    Science.gov (United States)

    Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

    2013-04-01

    The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the

  12. Estimation of energy potential of agricultural enterprise biomass

    Directory of Open Access Journals (Sweden)

    Lypchuk Vasyl

    2017-01-01

    Full Text Available Bioenergetics (obtaining of energy from biomass is one of innovative directions in energy branch of Ukraine. Correct and reliable estimation of biomass potential is essential for efficient use of it. The article reveals the issue of estimation of potential of biomass, obtained from byproducts of crop production and animal breeding, which can be used for power supply of agricultural enterprises. The given analysis was carried with application of common methodological fundamentals, revealed in the estimation of production structure of agricultural enterprises, structure of land employment, efficiency of crops growing, indicators of output of main and by-products, as well as normative (standard parameters of power output of energy raw material in relation to the chosen technology of its utilization. Results of the research prove high energy potential of byproducts of crop production and animal breeding at all of the studied enterprises, which should force its practical use.

  13. Estimating Aboveground Forest Carbon Stock of Major Tropical Forest Land Uses Using Airborne Lidar and Field Measurement Data in Central Sumatra

    Science.gov (United States)

    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

  14. Model-Assisted Estimation of Tropical Forest Biomass Change: A Comparison of Approaches

    Directory of Open Access Journals (Sweden)

    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.

  15. Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review

    Energy Technology Data Exchange (ETDEWEB)

    Ruth, M.

    2011-10-01

    This independent review is the conclusion arrived at from data collection, document reviews, interviews and deliberation from December 2010 through April 2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification. The Panel reviewed the current H2A case (Version 2.12, Case 01D) for hydrogen production via biomass gasification and identified four principal components of hydrogen levelized cost: CapEx; feedstock costs; project financing structure; efficiency/hydrogen yield. The panel reexamined the assumptions around these components and arrived at new estimates and approaches that better reflect the current technology and business environments.

  16. Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

    Science.gov (United States)

    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.

  17. Methyl halide emission estimates from domestic biomass burning in Africa

    Science.gov (United States)

    Mead, M. I.; Khan, M. A. H.; White, I. R.; Nickless, G.; Shallcross, D. E.

    Inventories of methyl halide emissions from domestic burning of biomass in Africa, from 1950 to the present day and projected to 2030, have been constructed. By combining emission factors from Andreae and Merlet [2001. Emission of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955-966], the biomass burning estimates from Yevich and Logan [2003. An assessment of biofuel use and burning of agricultural waste in the developing world. Global Biogeochemical Cycles 17(4), 1095, doi:10.1029/2002GB001952] and the population data from the UN population division, the emission of methyl halides from domestic biomass usage in Africa has been estimated. Data from this study suggest that methyl halide emissions from domestic biomass burning have increased by a factor of 4-5 from 1950 to 2005 and based on the expected population growth could double over the next 25 years. This estimated change has a non-negligible impact on the atmospheric budgets of methyl halides.

  18. Allometric Equations for Estimating Biomass of Euterpe precatoria, the Most Abundant Palm Species in the Amazon

    Directory of Open Access Journals (Sweden)

    Fernando Da Silva

    2015-02-01

    Full Text Available Allometric models to estimate biomass components such as stem mass Ms, foliage mass Ml, root mass Mr and aboveground mass Ma, were developed for the palm species Euterpe precatoria Mart., which is the most abundant tree species in the Amazon. We harvested twenty palms including above- and below-ground parts in an old growth Amazonian forest in Brazil. The diameter at breast height D ranged from 3.9–12.7 cm, and the stem height H ranged from 2.3–16.4 m. The D, diameter at ground basis D0, crown diameter CD, H, stem specific gravity ρ, and number of fronds Nf were considered as independent variables and incorporated into a power function model. The best predictors were D2Hρ for Ms and Ma, D2HNf for Ml, and D for Mr. Slender index (H/D ranged from 0.56–1.46 m·cm−1, and the D-H relationship suggested that the stem shape becomes more slender with increasing D. On the other hand, ρ increased with D implying a stiffening of stem tissue. The average root/shoot ratio was estimated as 0.29 which was higher than that reported for the non-palm tree species in the Amazon. Comparisons of several models to estimate Ma of different palm species, suggested that the variations of the D-H relationship and ρ should be considered to develop allometric models for estimating biomass in palm species. In particular the ρ largely varied depending on individual size, which should be important to consider, when developing the allometric models for palms.

  19. Non-destructive estimation of Oecophylla smaragdina colony biomass

    DEFF Research Database (Denmark)

    Pinkalski, Christian Alexander Stidsen; Offenberg, Joachim; Jensen, Karl-Martin Vagn

    in mango plantations in Darwin, Australia. The total nest volume of O. smaragdina colonies in a tree was related to the activity of the ants (R2=0.85), estimated as the density of ant trails in the tree. Subsequently, the relation between nest volume and ant biomass (R2=0.70) was added to enable...... a prediction of ant biomass directly from ant activity. With this combined regression the ant biomass in a tree equaled 244.5 g fresh mass*ant activity. Similarly, the number of workers in trees was estimated using the relationship between nest volume and worker numbers (R2=0.84). Based on the model, five O...

  20. 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 ...

  1. Estimating annual bole biomass production using uncertainty analysis

    Science.gov (United States)

    Travis J. Woolley; Mark E. Harmon; Kari B. O' Connell

    2007-01-01

    Two common sampling methodologies coupled with a simple statistical model were evaluated to determine the accuracy and precision of annual bole biomass production (BBP) and inter-annual variability estimates using this type of approach. We performed an uncertainty analysis using Monte Carlo methods in conjunction with radial growth core data from trees in three Douglas...

  2. Biomass burning losses of carbon estimated from ecosystem modeling and satellite data analysis for the Brazilian Amazon region

    Science.gov (United States)

    Potter, Christopher; Brooks Genovese, Vanessa; Klooster, Steven; Bobo, Matthew; Torregrosa, Alicia

    To produce a new daily record of gross carbon emissions from biomass burning events and post-burning decomposition fluxes in the states of the Brazilian Legal Amazon (Instituto Brasileiro de Geografia e Estatistica (IBGE), 1991. Anuario Estatistico do Brasil, Vol. 51. Rio de Janeiro, Brazil pp. 1-1024). We have used vegetation greenness estimates from satellite images as inputs to a terrestrial ecosystem production model. This carbon allocation model generates new estimates of regional aboveground vegetation biomass at 8-km resolution. The modeled biomass product is then combined for the first time with fire pixel counts from the advanced very high-resolution radiometer (AVHRR) to overlay regional burning activities in the Amazon. Results from our analysis indicate that carbon emission estimates from annual region-wide sources of deforestation and biomass burning in the early 1990s are apparently three to five times higher than reported in previous studies for the Brazilian Legal Amazon (Houghton et al., 2000. Nature 403, 301-304; Fearnside, 1997. Climatic Change 35, 321-360), i.e., studies which implied that the Legal Amazon region tends toward a net-zero annual source of terrestrial carbon. In contrast, our analysis implies that the total source fluxes over the entire Legal Amazon region range from 0.2 to 1.2 Pg C yr -1, depending strongly on annual rainfall patterns. The reasons for our higher burning emission estimates are (1) use of combustion fractions typically measured during Amazon forest burning events for computing carbon losses, (2) more detailed geographic distribution of vegetation biomass and daily fire activity for the region, and (3) inclusion of fire effects in extensive areas of the Legal Amazon covered by open woodland, secondary forests, savanna, and pasture vegetation. The total area of rainforest estimated annually to be deforested did not differ substantially among the previous analyses cited and our own.

  3. FIA's volume-to-biomass conversion method (CRM) generally underestimates biomass in comparison to published equations

    Science.gov (United States)

    David. C. Chojnacky

    2012-01-01

    An update of the Jenkins et al. (2003) biomass estimation equations for North American tree species resulted in 35 generalized equations developed from published equations. These 35 equations, which predict aboveground biomass of individual species grouped according to a taxa classification (based on genus or family and sometimes specific gravity), generally predicted...

  4. Scenario uncertainties in estimating direct land-use change emissions in biomass-to-energy life cycle assessment

    International Nuclear Information System (INIS)

    Curtright, Aimee E.; Johnson, David R.; Willis, Henry H.; Skone, Timothy

    2012-01-01

    The use of biomass for energy production has increasingly been encouraged in the United States, in part motivated by the potential to reduce greenhouse gas (GHG) emissions relative to fossil fuels. However, the GHG-intensity of biomass-derived energy is highly dependent on how the biomass is obtained and used. We explore scenario uncertainty in GHG estimates in the Calculating Uncertainty in Biomass Emissions (CUBE) model and find that direct land-use change emissions that result during the biomass production often dominate the total “farm-to-hopper” GHGs. CUBE represents each land-use change decision as a conversion of land from one of four specified baseline ecosystem to produce one of seven feedstock crops, both distinct by geographic region, and then determines the implied changes in soil organic carbon, root carbon, and above-ground biomass. CUBE therefore synthesizes and organizes the existing literature to represent direct land-use change emissions in a way that can be more readily incorporated into life cycle assessment. Our approach to representing direct land-use change literature has been applied to a specific set of data and offers immediate implications for decisionmakers, but it can also be generalized and replicated in the future, making use of improved scientific data on the magnitude and rates of direct land-use change emissions as it becomes available. -- Highlights: ► The GHG-intensity of bioenergy depends on how the biomass is obtained and used. ► Total GHG emissions may be dominated by direct land-use change emissions. ► There is significant scenario uncertainty in emissions based on the location of production. ► Emissions vary based on time elapsed since land-use change conversions. ► Our approach can be generalized to use improved scientific data in the future.

  5. A hyperspectral approach to estimating biomass and plant production in a heterogeneous restored temperate peatland

    Science.gov (United States)

    Byrd, K. B.; Schile, L. M.; Windham-Myers, L.; Kelly, M.; Hatala, J.; Baldocchi, D. D.

    2012-12-01

    Restoration of drained peatlands that are managed to reverse subsidence through organic accretion holds significant potential for large-scale carbon storage and sequestration. This potential has been demonstrated in an experimental wetland restoration site established by the U.S. Geological Survey in 1997 on Twitchell Island in the Sacramento-San Joaquin River Delta, where soil carbon storage is up to 1 kg C m-2 and root and rhizome production can reach over 7 kg m-2 annually. Remote sensing-based estimation of biomass and productivity over a large spatial extent helps to monitor carbon storage potential of these restored peatlands. Extensive field measurements of plant biophysical characteristics such as biomass, leaf area index, and the fraction of absorbed photosynthetically active radiation (fAPAR) [an important variable in light-use efficiency (LUE) models] have been collected for agricultural systems and forests. However the small size and local spatial variability of U.S. Pacific Coast wetlands pose new challenges for measuring these variables in the field and generating estimates through remote sensing. In particular background effects of non-photosynthetic vegetation (NPV), floating aquatic vegetation, and inundation of wetland vegetation influence the relationship between field measurements and multispectral or hyperspectral indices. Working at the USGS experimental wetland site, characterized by variable water depth and substantial NPV, or thatch, we collected field data on hardstem bulrush (Schoenoplectus acutus) and cattail (Typha spp.) coupled with reflectance data from a field spectrometer (350-2500 nm) every two to three weeks during the summers of 2011 and 2012. We calculated aboveground biomass with existing allometric relationships, and fAPAR was measured with line and point quantum sensors. We analyzed reflectance data to develop hyperspectral and multispectral indices that predict biomass and fAPAR and account for background effects of water

  6. Crop resistance traits modify the effects of an aboveground herbivore, brown planthopper, on soil microbial biomass and nematode community via changes to plant performance.

    NARCIS (Netherlands)

    Huang, J.; Liu, M.; Chen, F.; Griffiths, B.S.; Chen, X.; Johnson, S.N.; Hu, F.

    2012-01-01

    Plant-mediated effects of aboveground herbivory on the belowground ecosystem are well documented, but less attention has been paid to agro-ecosystems and in particular how crop cultivars with different traits (i.e. resistance to pests) shape such interactions. A fully factorial experiment was

  7. 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)

  8. Dynamics of Aboveground Phytomass of the Circumpolar Arctic Tundra During the Past Three Decades

    Science.gov (United States)

    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.

  9. [Compatible biomass models of natural spruce (Picea asperata)].

    Science.gov (United States)

    Wang, Jin Chi; Deng, Hua Feng; Huang, Guo Sheng; Wang, Xue Jun; Zhang, Lu

    2017-10-01

    By using nonlinear measurement error method, the compatible tree volume and above ground biomass equations were established based on the volume and biomass data of 150 sampling trees of natural spruce (Picea asperata). Two approaches, controlling directly under total aboveground biomass and controlling jointly from level to level, were used to design the compatible system for the total aboveground biomass and the biomass of four components (stem, bark, branch and foliage), and the total ground biomass could be estimated independently or estimated simultaneously in the system. The results showed that the R 2 of the one variable and bivariate compatible tree volume and aboveground biomass equations were all above 0.85, and the maximum value reached 0.99. The prediction effect of the volume equations could be improved significantly when tree height was included as predictor, while it was not significant in biomass estimation. For the compatible biomass systems, the one variable model based on controlling jointly from level to level was better than the model using controlling directly under total above ground biomass, but the bivariate models of the two methods were similar. Comparing the imitative effects of the one variable and bivariate compatible biomass models, the results showed that the increase of explainable variables could significantly improve the fitness of branch and foliage biomass, but had little effect on other components. Besides, there was almost no difference between the two methods of estimation based on the comparison.

  10. Estimating externalities of biomass fuel cycles, Report 7

    Energy Technology Data Exchange (ETDEWEB)

    Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.

    1998-01-01

    This report documents the analysis of the biomass fuel cycle, in which biomass is combusted to produce electricity. The major objectives of this study were: (1) to implement the methodological concepts which were developed in the Background Document (ORNL/RFF 1992) as a means of estimating the external costs and benefits of fuel cycles, and by so doing, to demonstrate their application to the biomass fuel cycle; (2) to develop, given the time and resources, a range of estimates of marginal (i.e., the additional or incremental) damages and benefits associated with selected impact-pathways from a new wood-fired power plant, using a representative benchmark technology, at two reference sites in the US; and (3) to assess the state of the information available to support energy decision making and the estimation of externalities, and by so doing, to assist in identifying gaps in knowledge and in setting future research agendas. The demonstration of methods, modeling procedures, and use of scientific information was the most important objective of this study. It provides an illustrative example for those who will, in the future, undertake studies of actual energy options and sites. As in most studies, a more comprehensive analysis could have been completed had budget constraints not been as severe. Particularly affected were the air and water transport modeling, estimation of ecological impacts, and economic valuation. However, the most important objective of the study was to demonstrate methods, as a detailed example for future studies. Thus, having severe budget constraints was appropriate from the standpoint that these studies could also face similar constraints. Consequently, an important result of this study is an indication of what can be done in such studies, rather than the specific numerical estimates themselves.

  11. A hybrid model for mapping relative differences in belowground biomass and root: Shoot ratios using spectral reflectance, foliar N and plant biophysical data within coastal marsh

    Science.gov (United States)

    Jessica L. O'Connell,; Byrd, Kristin B.; Maggi Kelly,

    2015-01-01

    Broad-scale estimates of belowground biomass are needed to understand wetland resiliency and C and N cycling, but these estimates are difficult to obtain because root:shoot ratios vary considerably both within and between species. We used remotely-sensed estimates of two aboveground plant characteristics, aboveground biomass and % foliar N to explore biomass allocation in low diversity freshwater impounded peatlands (Sacramento-San Joaquin River Delta, CA, USA). We developed a hybrid modeling approach to relate remotely-sensed estimates of % foliar N (a surrogate for environmental N and plant available nutrients) and aboveground biomass to field-measured belowground biomass for species specific and mixed species models. We estimated up to 90% of variation in foliar N concentration using partial least squares (PLS) regression of full-spectrum field spectrometer reflectance data. Landsat 7 reflectance data explained up to 70% of % foliar N and 67% of aboveground biomass. Spectrally estimated foliar N or aboveground biomass had negative relationships with belowground biomass and root:shoot ratio in both Schoenoplectus acutus and Typha, consistent with a balanced growth model, which suggests plants only allocate growth belowground when additional nutrients are necessary to support shoot development. Hybrid models explained up to 76% of variation in belowground biomass and 86% of variation in root:shoot ratio. Our modeling approach provides a method for developing maps of spatial variation in wetland belowground biomass.

  12. Estimation of alewife biomass in Lake Michigan, 1967-1978

    Science.gov (United States)

    Hatch, Richard W.; Haack, Paul M.; Brown, Edward H.

    1981-01-01

    The buildup of salmonid populations in Lake Michigan through annual stockings of hatchery-reared fish may become limited by the quantity of forage fish, mainly alewives Alosa pseudoharengus, available for food. As a part of a continuing examination of salmonid predator-prey relations in Lake Michigan, we traced changes in alewife biomass estimated from bottom-trawl surveys conducted in late October and early November 1967–1978. Weight of adult alewives trawled per 0.5 hectare of bottom (10-minute drag) at 16 depths along eight transects between 1973 and 1977 formed a skewed distribution: 72 of 464 drags caught no alewives; 89 drags caught less than 1 kg; and 2 drags caught more than 100 kg (maximum 159 kg). Analysis of variance in normalized catch per tow indicated highly significant differences between the main effects of years and depths, and highly significant differences in the interactions of years and transects, years and depths, and transects and depths. Five geographic and depth strata, formed by combining parts of transects wherein mean catch rate did not differ significantly, were the basis for calculating annual estimates of adult alewife biomass (with 90% confidence intervals). Estimated biomass of alewives (±90% confidence limits) in Lake Michigan proper (Green Bay and Grand Traverse Bay excluded) rose gradually from 46,000 (±9,000) t in 1967 to 114,000 (±17,000) t in 1973, declined to 45,000 (±8,000) t in 1977, and rose to 77,000 (±19,000) t in 1978.

  13. Biomass estimation by allometric relationships, nutrients, and carbon associated to heart-of-palm plantations in Costa Rica

    International Nuclear Information System (INIS)

    Ares, A.; Boniche, Y.; Quesada, J.P.; Yost, R.; Molina, E.; Smyth, T.J.

    2002-01-01

    Peach palm (Bactris gasipaes) agroecosystems constitute a productive and sustainable land use for the humid tropics. Allometric methods allow to predict biomass non-destructively at any time and, subsequently, to determine the span of growth phases, biomass and nutrient pools, and economic yields. The overall goals of this study were to obtain and validate predictive functions of aboveground dry biomass, and to relate standing biomass with heart-of-palm yields as well. Towards this purpose, peach palm shoots were harvested and separated into components: foliage, petiole and stem, in the Atlantic region of Costa Rica. A non-linear seemingly unrelated regression (NSUR) procedure, which simultaneously fits the component equations that predict leaf, petiole and stem in order to assure biomass additivity, was used to generate the allometric equations. Basal diameter (BD) was a more effective predictor of biomass than height to the fork between the spear leaf and the first fully expanded leaf, total height and number of leaves. Regression models explained 70-89% of the variance in biomass components (foliage, petiole and stem) or total shoot biomass. Three growth stages were identified: establishment (0-1 years), fast growth (1-3 or 1-8 years depending on plant density) and maturity (> 8 years). Nutrient contents associated to above- and below-ground biomass were measured. For above-ground biomass nutrient contents were N (up to 150 kg ha-1)>K (up to 119 kg ha-1)>Ca (up to 45 kg ha-1)>Mg=S=P (between 15-17 kg ha-1). The below-ground biomass: above-ground biomass ratio increased with the plantation age [es

  14. Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods

    Science.gov (United States)

    Zhaodi Guo; Jingyun Fang; Yude Pan; Richard. Birdsey

    2010-01-01

    Several studies have reported different estimates for forest biomass carbon (C) stocks in China. The discrepancy among these estimates may be largely attributed to the methods used. In this study, we used three methods [mean biomass density method (MBM), mean ratio method (MRM), and continuous biomass expansion factor (BEF) method (abbreviated as CBM)] applied to...

  15. COMBINING LIDAR ESTIMATES OF BIOMASS AND LANDSAT ESTIMATES OF STAND AGE FOR SPATIALLY EXTENSIVE VALIDATION OF MODELED FOREST PRODUCTIVITY. (R828309)

    Science.gov (United States)

    Extensive estimates of forest productivity are required to understand the relationships between shifting land use, changing climate and carbon storage and fluxes. Aboveground net primary production of wood (NPPAw) is a major component of total NPP and...

  16. A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)

    Science.gov (United States)

    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...

  17. Impacts of airborne lidar pulse density on estimating biomass stocks and changes in a selectively logged tropical forest

    Science.gov (United States)

    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...

  18. Partitioning Uncertainty In Aboveground Carbon Density Estimates: Relative Contributions From Lidar and Forest Inventory In The Brazilian Amazon.

    Science.gov (United States)

    Duffy, P.; Keller, M. M.; Morton, D. C.

    2016-12-01

    Carbon accounting for REDD+ requires knowledge of deforestation, degradation, and associated changes in forest carbon stocks. Degradation is more difficult to detect than deforestation so SilvaCarbon, an US inter-agency effort, has set a priority to better characterize forest degradation effects on carbon loss. By combining information from forest inventory and lidar data products, impacts of deforestation, degradation, and associated changes in forest carbon stocks can be more accurately characterized across space. Our approach employs a hierarchical Bayesian modeling (HBM) framework where the assimilation of information from multiple sources is accomplished using a change of support (COS) technique. The COS formulation allows data from multiple spatial resolutions to be assimilated into an intermediate resolution. This approach is being applied in Paragominas, a jurisdiction in the eastern Brazilian Amazon with a high proportion of logged and burned degraded forests where political change has opened the way for REDD+. We build on a long history of research including our extensive studies of logging damage. Our primary objective is to quantify above-ground carbon stocks and corresponding uncertainty in a spatially explicit manner. A secondary objective is to quantify the relative contribution of lower level data products to the overall uncertainty, allowing for more focused subsequent data collection in the context of uncertainty reduction. This approach provides a mechanism to assimilate information from multiple sources to produce spatially-explicit maps of carbon stocks and changes with corresponding spatially explicit maps of uncertainty. Importantly, this approach also provides a mechanism that can be used to assess the value of information from specific data products.

  19. Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands

    Science.gov (United States)

    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.

  20. Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks.

    Science.gov (United States)

    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.

  1. ESTIMATION OF BIOMASS COMMERCIAL SPROUTS OF Ilex paraguariensis A.ST.-HIL

    Directory of Open Access Journals (Sweden)

    Elisabete Vuaden

    2009-10-01

    Full Text Available This study aimed at developing some models that allow estimating the biomass of commercial green shoots of Ilex paraguariensis after pruning, at 10 years-old. In September 2007, 40 Ilex paraguariensis were pruned. One year after the first pruning, in 2008, they were evaluated dendrometrically and their biomass was determined from the commercial harvest of 16 individuals. To the others, the commercial biomass was estimated by the sum of the biomass of shoots.  The result obtained is that the biomass of commercial sprouts can be estimated as a function of the length of the rolls sprouting, with specific models for sprouts short, simple and compound average sprouts and long sprouts compounds. The models used to estimate the biomass of commercial sprouts using the length sum rolls and rolls of the length as independent variables underestimate the values of biomass with a margin of error of only 2.6%.

  2. Estimating the Heat of Formation of Foodstuffs and Biomass

    Energy Technology Data Exchange (ETDEWEB)

    Burnham, Alan K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2010-11-23

    Calorie estimates for expressing the energy content of food are common, however they are inadequate for the purpose of estimating the chemically defined heat of formation of foodstuffs for two reasons. First, they assume utilization factors by the body.1,2,3 Second, they are usually based on average values for their components. The best way to solve this problem would be to measure the heat of combustion of each material of interest. The heat of formation can then be calculated from the elemental composition and the heats of formation of CO2, H2O, and SO2. However, heats of combustion are not always available. Sometimes elemental analysis only is available, or in other cases, a breakdown into protein, carbohydrates, and lipids. A simple way is needed to calculate the heat of formation from various sorts of data commonly available. This report presents improved correlations for relating the heats of combustion and formation to the elemental composition, moisture content, and ash content. The correlations are also able to calculate heats of combustion of carbohydrates, proteins, and lipids individually, including how they depend on elemental composition. The starting point for these correlations are relationships commonly used to estimate the heat of combustion of fossil fuels, and they have been modified slightly to agree better with the ranges of chemical structures found in foodstuffs and biomass.

  3. Exploration of factors limiting biomass estimation by polarimetric radar in tropical forests

    NARCIS (Netherlands)

    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

  4. Estimating root biomass and distribution after fire in a Great Basin woodland using cores and pits

    Science.gov (United States)

    Benjamin M. Rau; Dale W. Johnson; Jeanne C. Chambers; Robert R. Blank; Annmarie Lucchesi

    2009-01-01

    Quantifying root biomass is critical to an estimation and understanding of ecosystem net primary production, biomass partitioning, and belowground competition. We compared 2 methods for determining root biomass: a new soil-coring technique and traditional excavation of quantitative pits. We conducted the study in an existing Joint Fire Sciences demonstration area in...

  5. The Utilization of ALOS PALSAR Image to Estimate Natural Forest Biomass: Case Study at Bogani Nani Wartabone National Park (Pemanfaatan Citra ALOS PALSAR dalam Menduga Biomasa Hutan Alam: Studi Kasus di Taman Nasional Bogani Nani Wartabone

    Directory of Open Access Journals (Sweden)

    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.

  6. Estimation of aerial biomass of Lychnophora ericoides (Mart.

    Directory of Open Access Journals (Sweden)

    Brunno Santana de Andrade

    2007-07-01

    Full Text Available For sustainable use of native plant species, knowledge of the amount of harvestable biomass is necessary. This study presents data on allometric relationships of Lychnophora ericoides Mart. (Asteraceae, an extractive resource in the Cerrado region of Brazil. On the Fazenda Água Limpa (15º 45'S, 47º 57'W of the Universidade de Brasilia, 38 individuals of this species were measured in the field, the parts above ground were harvested, separated into components and oven dried. The best regression equations to estimate biomass were geometric and the best fit was between total height and total biomass (r² = 0.923. The economically useful portions, the leaves and branches accounted for approximately 20% of total above ground dry weight, but when used as the dependent variable, the strength of the relationship decreased (r² = 0.694. The relationship between branch diameter and leaf biomass was similar to that between height and leaf dry weight (r² = 0.600. The relation between the number of leaves and their biomass was linear but weak. The development of these equations is the first step towards the implementation of plans for sustainable use of this species.Para o uso sustentável das espécies vegetais nativas o conhecimento da quantidade de biomassa disponível é necessário. O objetivo deste estudo foi verificar as relações alométricas para Lychnophora ericoides Mart., um recurso extrativista importante na região dos Cerrados. Na Fazenda Água Limpa da Universidade de Brasília, 38 indivíduos desta espécie foram medidas no campo, a parte aérea foi cortada, separada em componentes de folhas, galhos e tronco e estas componentes foram secas e pesadas. As melhores equações de regressão para estimar a biomassa foram geométricas e o melhor ajuste foi entre altura total e biomassa total (r² = 0,923. As partes economicamente exploradas, as folhas e ramos, contribuíram com aproximadamente 20% do peso seco total desta espécie, mas a equa

  7. Effect of culture and density on aboveground biomass allocation of 12 years old loblolly pine trees in the upper coastal plain and piedmont of Georgia and Alabama

    Science.gov (United States)

    Santosh Subedi; Dr. Michael Kane; Dr. Dehai Zhao; Dr. Bruce Borders; Dr. Dale Greene

    2012-01-01

    We destructively sampled a total of 192 12-year-old loblolly pine trees from four installations established by the Plantation Management Research Cooperative (PMRC) to analyze the effects of planting density and cultural intensity on tree level biomass allocation in the Piedmont and Upper Coastal Plain of Georgia and Alabama. Each installation had 12 plots, each plot...

  8. Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications.

    Directory of Open Access Journals (Sweden)

    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.

  9. Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications.

    Science.gov (United States)

    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.

  10. Tropical forest plantation biomass estimation using RADARSAT-SAR and TM data of south china

    Science.gov (United States)

    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

  11. The effect of wildfire and clear-cutting on above-ground biomass, foliar C to N ratios and fiber content throughout succession: Implications for forage quality in woodland caribou (Rangifer tarandus caribou)

    Science.gov (United States)

    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

  12. Assessing changes in biomass, productivity, and C and N stores following Juniperus virginiana forest expansion into tallgrass prairie

    Energy Technology Data Exchange (ETDEWEB)

    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.

  13. Estimating volume, biomass, and potential emissions of hand-piled fuels

    Science.gov (United States)

    Clinton S. Wright; Cameron S. Balog; Jeffrey W. Kelly

    2009-01-01

    Dimensions, volume, and biomass were measured for 121 hand-constructed piles composed primarily of coniferous (n = 63) and shrub/hardwood (n = 58) material at sites in Washington and California. Equations using pile dimensions, shape, and type allow users to accurately estimate the biomass of hand piles. Equations for estimating true pile volume from simple geometric...

  14. Comparing algorithms for estimating foliar biomass of conifers in the Pacific Northwest

    Science.gov (United States)

    Crystal L. Raymond; Donald. McKenzie

    2013-01-01

    Accurate estimates of foliar biomass (FB) are important for quantifying carbon storage in forest ecosystems, but FB is not always reported in regional or national inventories. Foliar biomass also drives key ecological processes in ecosystem models. Published algorithms for estimating FB in conifer species of the Pacific Northwest can yield signifi cantly different...

  15. Estimation and mapping of above ground biomass and carbon of ...

    African Journals Online (AJOL)

    USER

    1Department of Geomatics and Land Management, Makerere University, P.O. Box 7062 ... Biomass is an important parameter for bioenergy modelling, food security, ... –Kyoto climate change agreement on reducing emissions from deforestation and ... the nature of terrain can also affect the amounts of biomass and carbon ...

  16. SAFARI 2000 1-Degree Estimates of Burned Biomass, Area, and Emissions, 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — A new method is used to generate spatial estimates of monthly averaged biomass burned area and spatial and temporal estimates of trace gas and aerosol emissions from...

  17. Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations

    Science.gov (United States)

    Babcock, Chad; Finley, Andrew O.; Andersen, Hans-Erik; Pattison, Robert; Cook, Bruce D.; Morton, Douglas C.; Alonzo, Michael; Nelson, Ross; Gregoire, Timothy; Ene, Liviu; Gobakken, Terje; Næsset, Erik

    2018-06-01

    The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip samples of airborne lidar and Landsat-based remote sensing data products to predict aboveground biomass (AGB) in interior Alaska's Tanana Valley. The proposed modeling strategy facilitates pixel-level mapping of AGB density predictions across the entire spatial domain. Additionally, the coregionalization framework allows for statistically sound estimation of total AGB for arbitrary areal units within the study area---a key advance to support diverse management objectives in interior Alaska. This research focuses on appropriate characterization of prediction uncertainty in the form of posterior predictive coverage intervals and standard deviations. Using the framework detailed here, it is possible to quantify estimation uncertainty for any spatial extent, ranging from pixel-level predictions of AGB density to estimates of AGB stocks for the full domain. The lidar-informed coregionalization models consistently outperformed their counterpart lidar-free models in terms of point-level predictive performance and total AGB precision. Additionally, the inclusion of Landsat-derived forest cover as a covariate further improved estimation precision in regions with lower lidar sampling intensity. Our findings also demonstrate that model-based approaches that do not explicitly account for residual spatial dependence can grossly underestimate uncertainty, resulting in falsely precise estimates of AGB. On the other hand, in a geostatistical setting, residual spatial structure can be modeled within a Bayesian hierarchical framework to obtain statistically defensible assessments of uncertainty for AGB estimates.

  18. 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

  19. Non-Destructive Lichen Biomass Estimation in Northwestern Alaska: A Comparison of Methods

    Science.gov (United States)

    Rosso, Abbey; Neitlich, Peter; Smith, Robert J.

    2014-01-01

    Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa “community” samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m−2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska. PMID:25079228

  20. Non-destructive lichen biomass estimation in northwestern Alaska: a comparison of methods.

    Directory of Open Access Journals (Sweden)

    Abbey Rosso

    Full Text Available Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa "community" samples, n = 144 at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count, among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4% using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m-2. Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

  1. Non-destructive lichen biomass estimation in northwestern Alaska: a comparison of methods.

    Science.gov (United States)

    Rosso, Abbey; Neitlich, Peter; Smith, Robert J

    2014-01-01

    Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa "community" samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m-2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

  2. Mapping and estimating the total living biomass and carbon in low-biomass woodlands using Landsat 8 CDR data

    Directory of Open Access Journals (Sweden)

    Belachew Gizachew

    2016-06-01

    Full Text Available Abstract Background A functional forest carbon measuring, reporting and verification (MRV system to support climate change mitigation policies, such as REDD+, requires estimates of forest biomass carbon, as an input to estimate emissions. A combination of field inventory and remote sensing is expected to provide those data. By linking Landsat 8 and forest inventory data, we (1 developed linear mixed effects models for total living biomass (TLB estimation as a function of spectral variables, (2 developed a 30 m resolution map of the total living carbon (TLC, and (3 estimated the total TLB stock of the study area. Inventory data consisted of tree measurements from 500 plots in 63 clusters in a 15,700 km2 study area, in miombo woodlands of Tanzania. The Landsat 8 data comprised two climate data record images covering the inventory area. Results We found a linear relationship between TLB and Landsat 8 derived spectral variables, and there was no clear evidence of spectral data saturation at higher biomass values. The root-mean-square error of the values predicted by the linear model linking the TLB and the normalized difference vegetation index (NDVI is equal to 44 t/ha (49 % of the mean value. The estimated TLB for the study area was 140 Mt, with a mean TLB density of 81 t/ha, and a 95 % confidence interval of 74–88 t/ha. We mapped the distribution of TLC of the study area using the TLB model, where TLC was estimated at 47 % of TLB. Conclusion The low biomass in the miombo woodlands, and the absence of a spectral data saturation problem suggested that Landsat 8 derived NDVI is suitable auxiliary information for carbon monitoring in the context of REDD+, for low-biomass, open-canopy woodlands.

  3. Developing in situ non-destructive estimates of crop biomass to address issues of scale in remote sensing

    Science.gov (United States)

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Ground-based estimates of aboveground wet (fresh) biomass (AWB) are an important input for crop growth models. In this study, we developed empirical equations of AWB for rice, maize, cotton, and alfalfa, by combining several in situ non-spectral and spectral predictors. The non-spectral predictors included: crop height (H), fraction of absorbed photosynthetically active radiation (FAPAR), leaf area index (LAI), and fraction of vegetation cover (FVC). The spectral predictors included 196 hyperspectral narrowbands (HNBs) from 350 to 2500 nm. The models for rice, maize, cotton, and alfalfa included H and HNBs in the near infrared (NIR); H, FAPAR, and HNBs in the NIR; H and HNBs in the visible and NIR; and FVC and HNBs in the visible; respectively. In each case, the non-spectral predictors were the most important, while the HNBs explained additional and statistically significant predictors, but with lower variance. The final models selected for validation yielded an R2 of 0.84, 0.59, 0.91, and 0.86 for rice, maize, cotton, and alfalfa, which when compared to models using HNBs alone from a previous study using the same spectral data, explained an additional 12%, 29%, 14%, and 6% in AWB variance. These integrated models will be used in an up-coming study to extrapolate AWB over 60 × 60 m transects to evaluate spaceborne multispectral broad bands and hyperspectral narrowbands.

  4. Developing in situ Non-Destructive Estimates of Crop Biomass to Address Issues of Scale in Remote Sensing

    Directory of Open Access Journals (Sweden)

    Michael Marshall

    2015-01-01

    Full Text Available Ground-based estimates of aboveground wet (fresh biomass (AWB are an important input for crop growth models. In this study, we developed empirical equations of AWB for rice, maize, cotton, and alfalfa, by combining several in situ non-spectral and spectral predictors. The non-spectral predictors included: crop height (H, fraction of absorbed photosynthetically active radiation (FAPAR, leaf area index (LAI, and fraction of vegetation cover (FVC. The spectral predictors included 196 hyperspectral narrowbands (HNBs from 350 to 2500 nm. The models for rice, maize, cotton, and alfalfa included H and HNBs in the near infrared (NIR; H, FAPAR, and HNBs in the NIR; H and HNBs in the visible and NIR; and FVC and HNBs in the visible; respectively. In each case, the non-spectral predictors were the most important, while the HNBs explained additional and statistically significant predictors, but with lower variance. The final models selected for validation yielded an R2 of 0.84, 0.59, 0.91, and 0.86 for rice, maize, cotton, and alfalfa, which when compared to models using HNBs alone from a previous study using the same spectral data, explained an additional 12%, 29%, 14%, and 6% in AWB variance. These integrated models will be used in an up-coming study to extrapolate AWB over 60 × 60 m transects to evaluate spaceborne multispectral broad bands and hyperspectral narrowbands.

  5. Aboveground biomass in Prosopis pallida (Humb. and Bonpl. ex Willd. H. B. K. ecosystems using Landsat 7 ETM+ images Biomasa aérea en ecosistemas de Prosopis pallida (Humb. and Bonpl. ex Willd. H. B. K. usando imágenes Landsat 7 ETM+

    Directory of Open Access Journals (Sweden)

    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

  6. Method for calculating the variance and prediction intervals for biomass estimates obtained from allometric equations

    CSIR Research Space (South Africa)

    Kirton, A

    2010-08-01

    Full Text Available for calculating the variance and prediction intervals for biomass estimates obtained from allometric equations A KIRTON B SCHOLES S ARCHIBALD CSIR Ecosystem Processes and Dynamics, Natural Resources and the Environment P.O. BOX 395, Pretoria, 0001, South... intervals (confidence intervals for predicted values) for allometric estimates can be obtained using an example of estimating tree biomass from stem diameter. It explains how to deal with relationships which are in the power function form - a common form...

  7. Novel and lost forests in the Upper Midwestern United States, from new estimates of settlement-era composition, stem density, and biomass

    Science.gov (United States)

    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.

  8. TREE STEM AND CANOPY BIOMASS ESTIMATES FROM TERRESTRIAL LASER SCANNING DATA

    Directory of Open Access Journals (Sweden)

    K. Olofsson

    2017-10-01

    Full Text Available In this study an automatic method for estimating both the tree stem and the tree canopy biomass is presented. The point cloud tree extraction techniques operate on TLS data and models the biomass using the estimated stem and canopy volume as independent variables. The regression model fit error is of the order of less than 5 kg, which gives a relative model error of about 5 % for the stem estimate and 10–15 % for the spruce and pine canopy biomass estimates. The canopy biomass estimate was improved by separating the models by tree species which indicates that the method is allometry dependent and that the regression models need to be recomputed for different areas with different climate and different vegetation.

  9. Quantitative Estimation of Above Ground Crop Biomass using Ground-based, Airborne and Spaceborne Low Frequency Polarimetric Synthetic Aperture Radar

    Science.gov (United States)

    Koyama, C.; Watanabe, M.; Shimada, M.

    2016-12-01

    Estimation of crop biomass is one of the important challenges in environmental remote sensing related to agricultural as well as hydrological and meteorological applications. Usually passive optical data (photographs, spectral data) operating in the visible and near-infrared bands is used for such purposes. The virtue of optical remote sensing for yield estimation, however, is rather limited as the visible light can only provide information about the chemical characteristics of the canopy surface. Low frequency microwave signals with wavelength longer 20 cm have the potential to penetrate through the canopy and provide information about the whole vertical structure of vegetation from the top of the canopy down to the very soil surface. This phenomenon has been well known and exploited to detect targets under vegetation in the military radar application known as FOPEN (foliage penetration). With the availability of polarimetric interferometric SAR data the use PolInSAR techniques to retrieve vertical vegetation structures has become an attractive tool. However, PolInSAR is still highly experimental and suitable data is not yet widely available. In this study we focus on the use of operational dual-polarization L-band (1.27 GHz) SAR which is since the launch of Japan's Advanced Land Observing Satellite (ALOS, 2006-2011) available worldwide. Since 2014 ALOS-2 continues to deliver such kind of partial polarimetric data for the entire land surface. In addition to these spaceborne data sets we use airborne L-band SAR data acquired by the Japanese Pi-SAR-L2 as well as ultra-wideband (UWB) ground based SAR data operating in the frequency range from 1-4 GHz. By exploiting the complex dual-polarization [C2] Covariance matrix information, the scattering contributions from the canopy can be well separated from the ground reflections allowing for the establishment of semi-empirical relationships between measured radar reflectivity and the amount of fresh-weight above-ground

  10. Biomass estimation as a function of vertical forest structure and forest height: potential and limitations for radar remote sensing

    OpenAIRE

    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...

  11. A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area

    Science.gov (United States)

    Donald Gagliasso; Susan Hummel; Hailemariam. Temesgen

    2014-01-01

    Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...

  12. Is biomass a reliable estimate of plant fitness?

    Czech Academy of Sciences Publication Activity Database

    Younginger, B.S.; Sirová, Dagmara; Cruzan, M.B.; Ballhorn, D.J.

    2017-01-01

    Roč. 5, č. 2 (2017), č. článku 1600094. ISSN 2168-0450 Institutional support: RVO:60077344 Keywords : biomass * fecundity * fitness * plant performance * selection Subject RIV: EH - Ecology, Behaviour OBOR OECD: Plant sciences, botany Impact factor: 1.492, year: 2016

  13. Estimation and mapping of above ground biomass and carbon of ...

    African Journals Online (AJOL)

    In addition, field data from 35 sample plots comprising of the Diameter at Breast Height (DBH), co-ordinates of centroids and angles to the top and bottom of the individual trees was used for the analysis. The relationship between biomass and radar backscatter for selected sample plots was established using pairwise ...

  14. Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

    Directory of Open Access Journals (Sweden)

    Nora Tilly

    2015-09-01

    Full Text Available Plant biomass is an important parameter for crop management and yield estimation. However, since biomass cannot be determined non-destructively, other plant parameters are used for estimations. In this study, plant height and hyperspectral data were used for barley biomass estimations with bivariate and multivariate models. During three consecutive growing seasons a terrestrial laser scanner was used to establish crop surface models for a pixel-wise calculation of plant height and manual measurements of plant height confirmed the results (R2 up to 0.98. Hyperspectral reflectance measurements were conducted with a field spectrometer and used for calculating six vegetation indices (VIs, which have been found to be related to biomass and LAI: GnyLi, NDVI, NRI, RDVI, REIP, and RGBVI. Furthermore, biomass samples were destructively taken on almost the same dates. Linear and exponential biomass regression models (BRMs were established for evaluating plant height and VIs as estimators of fresh and dry biomass. Each BRM was established for the whole observed period and pre-anthesis, which is important for management decisions. Bivariate BRMs supported plant height as a strong estimator (R2 up to 0.85, whereas BRMs based on individual VIs showed varying performances (R2: 0.07–0.87. Fused approaches, where plant height and one VI were used for establishing multivariate BRMs, yielded improvements in some cases (R2 up to 0.89. Overall, this study reveals the potential of remotely-sensed plant parameters for estimations of barley biomass. Moreover, it is a first step towards the fusion of 3D spatial and spectral measurements for improving non-destructive biomass estimations.

  15. DINÁMICA DE LA BIOMASA AÉREA EN UN BOSQUE PLUVIAL TROPICAL DEL CHOCÓ BIOGEOGRÁFICO DYNAMICS OF TREE ABOVEGROUND BIOMASS IN A TROPICAL RAIN FOREST OF THE CHOCÓ BIOGEOGRÁFICO

    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

  16. Estimation of optimal biomass fraction measuring cycle formunicipal solid waste incineration facilities in Korea.

    Science.gov (United States)

    Kang, Seongmin; Cha, Jae Hyung; Hong, Yoon-Jung; Lee, Daekyeom; Kim, Ki-Hyun; Jeon, Eui-Chan

    2018-01-01

    This study estimates the optimum sampling cycle using a statistical method for biomass fraction. More than ten samples were collected from each of the three municipal solid waste (MSW) facilities between June 2013 and March 2015 and the biomass fraction was analyzed. The analysis data were grouped into monthly, quarterly, semi-annual, and annual intervals and the optimum sampling cycle for the detection of the biomass fraction was estimated. Biomass fraction data did not show a normal distribution. Therefore, the non-parametric Kruskal-Wallis test was applied to compare the average values for each sample group. The Kruskal-Wallis test results showed that the average monthly, quarterly, semi-annual, and annual values for all three MSW incineration facilities were equal. Therefore, the biomass fraction at the MSW incineration facilities should be calculated on a yearly cycle which is the longest period of the temporal cycles tested. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Biomass

    Science.gov (United States)

    Bernard R. Parresol

    2001-01-01

    Biomass, the contraction for biological mass, is the amount of living material provided by a given area or volume of the earth's surface, whether terrestrial or aquatic. Biomass is important for commercial uses (e.g., fuel and fiber) and for national development planning, as well as for scientific studies of ecosystem productivity, energy and nutrient flows, and...

  18. Aboveground storage tanks

    International Nuclear Information System (INIS)

    Rizzo, J.A.

    1992-01-01

    With the 1988 promulgation of the comprehensive Resource Conservation and Recovery Act (RCRA) regulations for underground storage of petroleum and hazardous substances, many existing underground storage tank (UST) owners have been considering making the move to aboveground storage. While on the surface, this may appear to be the cure-all to avoiding the underground leakage dilemma, there are many other new and different issues to consider with aboveground storage. The greatest misconception is that by storing materials above ground, there is no risk of subsurface environmental problems. it should be noted that with the aboveground storage tank (AGST) systems, there is still considerable risk of environmental contamination, either by the failure of onground tank bottoms or the spillage of product onto the ground surface where it subsequently finds its way to the ground water. In addition, there are added safety concerns that must be addressed. So what are the other specific areas of concern besides environmental to be addressed when making the decision between underground and aboveground tanks? The primary issues that will be addressed in this paper are: Safety, Product Losses, Cost Comparison of USTs vs AGSTs, Space Availability/Accessibility, Precipitation Handling, Aesthetics and Security, Pending and Existing Regulations

  19. Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

    Science.gov (United States)

    Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

    2010-12-01

    Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.

  20. Estimating Terrestrial Wood Biomass from Observed Concentrations of Atmospheric Carbon Dioxide

    NARCIS (Netherlands)

    Schaefer, K. M.; Peters, W.; Carvalhais, N.; van der Werf, G.; Miller, J.

    2008-01-01

    We estimate terrestrial disequilibrium state and wood biomass from observed concentrations of atmospheric CO2 using the CarbonTracker system coupled to the SiBCASA biophysical model. Starting with a priori estimates of carbon flux from the land, ocean, and fossil fuels, CarbonTracker estimates net

  1. From a tree to a stand in Finnish boreal forests - biomass estimation and comparison of methods

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Chunjiang

    2009-07-01

    There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61deg50' N, 24deg22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg yr-1 for understorey spruce to 7 kg yr-1 for dominant pine) when the trees were 100 years old). Tree biomass was estimated to be about 70 Mg ha-1 in Young-Stand and about 220 Mg ha-1 in Mature-Stand. In the region (58.00-62.13 degN, 14-34 degE, <= 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg ha-1 at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg ha-1 with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg ha-1. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach. (orig.)

  2. A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

    Science.gov (United States)

    Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

    2018-05-01

    estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.

  3. National scale biomass estimators for United States tree species

    Science.gov (United States)

    Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

    2003-01-01

    Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...

  4. The utilization of false color aerial photography for macrophyte biomass estimation in the Oosterschelde (the Netherlands)

    Science.gov (United States)

    Meulstee, C.; Vanstokkom, H.

    1985-01-01

    The correlation between the biomass of sea grass and seaweed samples in a sidebranch of the Oosterschelde delta (Netherlands) and density ratios of this area on color infrared aerial photographs was investigated. As the Oosterschelde will become more divided from the North Sea after pier dam completion, an increase of macrophytes is expected. In an area where the weeds Ulva, Cheatomorpha, Entermorpha, Cladophora, Fucus vesuculosis, and the grasses Zostera noltii and Zostera marina are found, 53 biomass samples of a 0.054 sq m surface each were collected. The relation between covering degree and biomass was estimated. Using a transmission-densitometer adjusted to 3 to 1 mm, densities on 1:10,000 and 1:20,000 scale photographs were measured. A gage line was determined in a density-biomass diagram. The method is shown to be useful for an efficient, accurate biomass determination in the Oosterschelde.

  5. Consequences of long-term severe industrial pollution for aboveground carbon and nitrogen pools in northern taiga forests at local and regional scales.

    Science.gov (United States)

    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.

  6. Estimation of the biomass of arbuscular mycorrhizal fungi in a linseed field

    DEFF Research Database (Denmark)

    Olsson, P.A.; Thingstrup, I.; Jakobsen, I.

    1999-01-01

    -organisms was estimated 28, 51 and 72 d after sowing based on amounts of certain fatty acids extracted from the soil. Dazomet application strongly suppressed colonisation of the linseed roots by AM fungi throughout the experiment. In plots with no dazomet application, root colonisation by the AM fungi increased from...... that the biomass of the extraradical mycelium of AM fungi was about 10 times as high as the biomass of intraradical mycelium and that the extraradical mycelium constituted the largest fraction of the soil microbial biomass. Dazomet application also decreased the biomass of saprophytic fungi in the soil...... harvests 1 to 3 as judged both from microscopical estimates and from quantitative analysis of the AM fungal indicative fatty acid 16.1 omega 5. These methods also revealed that AM formation was reduced in P-fertilised plots. The phospholipid fatty acid (PLFA) 16:1 omega 5 decreased in dazomet-treated soil...

  7. From a tree to a stand in Finnish boreal forests: biomass estimation and comparison of methods

    OpenAIRE

    Liu, Chunjiang

    2009-01-01

    There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61º50' N, 24º22' E). In particular, a comparison of the results of different estimati...

  8. The effect of cassava-based bioethanol production on above-ground carbon stocks: A case study from Southern Mali

    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.

  9. Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Silva

    2017-10-01

    Full Text Available Airborne lidar is a technology well-suited for mapping many forest attributes, including aboveground biomass (AGB stocks and changes in selective logging in tropical forests. However, trade-offs still exist between lidar pulse density and accuracy of AGB estimates. We assessed the impacts of lidar pulse density on the estimation of AGB stocks and changes using airborne lidar and field plot data in a selectively logged tropical forest located near Paragominas, Pará, Brazil. Field-derived AGB was computed at 85 square 50 × 50 m plots in 2014. Lidar data were acquired in 2012 and 2014, and for each dataset the pulse density was subsampled from its original density of 13.8 and 37.5 pulses·m−2 to lower densities of 12, 10, 8, 6, 4, 2, 0.8, 0.6, 0.4 and 0.2 pulses·m−2. For each pulse density dataset, a power-law model was developed to estimate AGB stocks from lidar-derived mean height and corresponding changes between the years 2012 and 2014. We found that AGB change estimates at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg·ha−1 when pulse density decreased from 12 to 0.2 pulses·m−2. The effects of pulse density were more pronounced in areas of steep slope, especially when the digital terrain models (DTMs used in the lidar derived forest height were created from reduced pulse density data. In particular, when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and the estimated AGB stock and changes did not exceed 20 Mg·ha−1. The results suggest that AGB change can be monitored in selective logging in tropical forests with reasonable accuracy and low cost with low pulse density lidar surveys if a baseline high-quality DTM is available from at least one lidar survey. We recommend the results of this study to be considered in developing projects and national

  10. Methodology for estimating biomass energy potential and its application to Colombia

    International Nuclear Information System (INIS)

    Gonzalez-Salazar, Miguel Angel; Morini, Mirko; Pinelli, Michele; Spina, Pier Ruggero; Venturini, Mauro; Finkenrath, Matthias; Poganietz, Witold-Roger

    2014-01-01

    Highlights: • Methodology to estimate the biomass energy potential and its uncertainty at a country level. • Harmonization of approaches and assumptions in existing assessment studies. • The theoretical and technical biomass energy potential in Colombia are estimated in 2010. - Abstract: This paper presents a methodology to estimate the biomass energy potential and its associated uncertainty at a country level when quality and availability of data are limited. The current biomass energy potential in Colombia is assessed following the proposed methodology and results are compared to existing assessment studies. The proposed methodology is a bottom-up resource-focused approach with statistical analysis that uses a Monte Carlo algorithm to stochastically estimate the theoretical and the technical biomass energy potential. The paper also includes a proposed approach to quantify uncertainty combining a probabilistic propagation of uncertainty, a sensitivity analysis and a set of disaggregated sub-models to estimate reliability of predictions and reduce the associated uncertainty. Results predict a theoretical energy potential of 0.744 EJ and a technical potential of 0.059 EJ in 2010, which might account for 1.2% of the annual primary energy production (4.93 EJ)

  11. Appendix C: Biomass Program inputs for FY 2008 benefits estimates

    Energy Technology Data Exchange (ETDEWEB)

    None, None

    2009-01-18

    Document summarizes the results of the benefits analysis of EERE’s programs, as described in the FY 2008 Budget Request. EERE estimates benefits for its overall portfolio and nine Research, Development, Demonstration, and Deployment (RD3) programs.

  12. Inference for lidar-assisted estimation of forest growing stock volume

    Science.gov (United States)

    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...

  13. The Use of Fire Radiative Power to Estimate the Biomass Consumption Coefficient for Temperate Grasslands in the Atlantic Forest Biome

    Directory of Open Access Journals (Sweden)

    Bibiana Salvador Cabral da Costa

    Full Text Available Abstract Every year, many active fire spots are identified in the satellite images of the southern Brazilian grasslands in the Atlantic Forest biome and Pampa biome. Fire Radiative Power (FRP is a technique that uses remotely sensed data to quantify burned biomass. FRP measures the radiant energy released per time unit by burning vegetation. This study aims to use satellite and field data to estimate the biomass consumption rate and the biomass consumption coefficient for the southern Brazilian grasslands. Three fire points were identified in satellite FRP products. These data were combined with field data, collected through literature review, to calculate the biomass consumption coefficient. The type of vegetation is an important variable in the estimation of the biomass consumption coefficient. The biomass consumption rate was estimated to be 2.237 kg s-1 for the southern Brazilian grasslands in Atlantic Forest biome, and the biomass consumption coefficient was estimated to be 0.242 kg MJ-1.

  14. Landsat Imagery-Based Above Ground Biomass Estimation and Change Investigation Related to Human Activities

    Directory of Open Access Journals (Sweden)

    Chaofan Wu

    2016-02-01

    Full Text Available Forest biomass is a significant indicator for substance accumulation and forest succession, and a spatiotemporal biomass map would provide valuable information for forest management and scientific planning. In this study, Landsat imagery and field data cooperated with a random forest regression approach were used to estimate spatiotemporal Above Ground Biomass (AGB in Fuyang County, Zhejiang Province of East China. As a result, the AGB retrieval showed an increasing trend for the past decade, from 74.24 ton/ha in 2004 to 99.63 ton/ha in 2013. Topography and forest management were investigated to find their relationships with the spatial distribution change of biomass. In general, the simulated AGB increases with higher elevation, especially in the range of 80–200 m, wherein AGB acquires the highest increase rate. Moreover, the forest policy of ecological forest has a positive effect on the AGB increase, particularly within the national level ecological forest. The result in this study demonstrates that human activities have a great impact on biomass distribution and change tendency. Furthermore, Landsat image-based biomass estimates would provide illuminating information for forest policy-making and sustainable development.

  15. REGIONAL ESTIMATION OF CURRENT AND FUTURE FOREST BIOMASS. (R828785)

    Science.gov (United States)

    The 90,674 wildland fires that burned 2.9 million ha at an estimated suppression cost of $1.6 billion in the United States during the 2000 fire season demonstrated that forest fuel loading has become a hazard to life, property, and ecosystem health as a result of past fire exc...

  16. Estimation of arboreal lichen biomass available to woodland caribou in Hudson Bay lowland black spruce sites

    Directory of Open Access Journals (Sweden)

    Sarah K. Proceviat

    2003-04-01

    Full Text Available An arboreal lichen index to be utilized in assessing woodland caribou habitat throughout northeastern Ontario was developed. The "index" was comprised of 5 classes, which differentiated arboreal lichen biomass on black spruce trees, ranging from maximal quantities of arboreal lichen (class 5 to minimal amounts of arboreal lichen (class 1. This arboreal lichen index was subsequently used to estimate the biomass of arboreal lichen available to woodland caribou on lowland black spruce sites ranging in age from 1 year to 150 years post-harvest. A total of 39 sites were assessed and significant differences in arboreal lichen biomass were found, with a positive linear relationship between arboreal lichen biomass and forest age. It is proposed that the index be utilized by government and industry as a means of assessing the suitability of lowland black spruce habitat for woodland caribou in this region.

  17. Estimation of Biomass and Canopy Height in Bermudagrass, Alfalfa, and Wheat Using Ultrasonic, Laser, and Spectral Sensors

    Directory of Open Access Journals (Sweden)

    Jeremy Joshua Pittman

    2015-01-01

    Full Text Available Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L., bermudagrass [Cynodon dactylon (L. Pers.], and wheat (Triticum aestivum L. were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral as compared to physical measurements (plate meter and meter stick and the traditional harvest method (clipping. Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha−1, respectively, except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass < 0.79 t·ha−1 and greatest measured biomass (average percent error of 18% for harvester and quad harvested biomass >6.4 t·ha−1. These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation.

  18. 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.

  19. Evaluation of the reference unit method for herbaceous biomass estimation in native grasslands of southwestern South Dakota

    Science.gov (United States)

    Eric D. Boyda

    2013-01-01

    The high costs associated with physically harvesting plant biomass may prevent sufficient data collection, which is necessary to account for the natural variability of vegetation at a landscape scale. A biomass estimation technique was previously developed using representative samples or "reference units", which eliminated the need to harvest biomass from all...

  20. Estimating GHG emission mitigation supply curves of large-scale biomass use on a country level

    International Nuclear Information System (INIS)

    Dornburg, Veronika; Dam, Jinke van; Faaij, Andre

    2007-01-01

    This study evaluates the possible influences of a large-scale introduction of biomass material and energy systems and their market volumes on land, material and energy market prices and their feedback to greenhouse gas (GHG) emission mitigation costs. GHG emission mitigation supply curves for large-scale biomass use were compiled using a methodology that combines a bottom-up analysis of biomass applications, biomass cost supply curves and market prices of land, biomaterials and bioenergy carriers. These market prices depend on the scale of biomass use and the market volume of materials and energy carriers and were estimated using own-price elasticities of demand. The methodology was demonstrated for a case study of Poland in the year 2015 applying different scenarios on economic development and trade in Europe. For the key technologies considered, i.e. medium density fibreboard, poly lactic acid, electricity and methanol production, GHG emission mitigation costs increase strongly with the scale of biomass production. Large-scale introduction of biomass use decreases the GHG emission reduction potential at costs below 50 Euro /Mg CO 2eq with about 13-70% depending on the scenario. Biomaterial production accounts for only a small part of this GHG emission reduction potential due to relatively small material markets and the subsequent strong decrease of biomaterial market prices at large scale of production. GHG emission mitigation costs depend strongly on biomass supply curves, own-price elasticity of land and market volumes of bioenergy carriers. The analysis shows that these influences should be taken into account for developing biomass implementations strategies

  1. Indirect methods of tree biomass estimation and their uncertainties ...

    African Journals Online (AJOL)

    Depending on data availability (dbh only or both dbh and total tree height) either of the models may be applied to generate satisfactory estimates of tree volume needed for planning and decision-making in management of mangrove forests. The study found an overall mean FF value of 0.65 ± 0.03 (SE), 0.56 ± 0.03 (SE) and ...

  2. Extension of biomass estimates to pre-assessment periods using density dependent surplus production approach.

    Directory of Open Access Journals (Sweden)

    Jan Horbowy

    Full Text Available Biomass reconstructions to pre-assessment periods for commercially important and exploitable fish species are important tools for understanding long-term processes and fluctuation on stock and ecosystem level. For some stocks only fisheries statistics and fishery dependent data are available, for periods before surveys were conducted. The methods for the backward extension of the analytical assessment of biomass for years for which only total catch volumes are available were developed and tested in this paper. Two of the approaches developed apply the concept of the surplus production rate (SPR, which is shown to be stock density dependent if stock dynamics is governed by classical stock-production models. The other approach used a modified form of the Schaefer production model that allows for backward biomass estimation. The performance of the methods was tested on the Arctic cod and North Sea herring stocks, for which analytical biomass estimates extend back to the late 1940s. Next, the methods were applied to extend biomass estimates of the North-east Atlantic mackerel from the 1970s (analytical biomass estimates available to the 1950s, for which only total catch volumes were available. For comparison with other methods which employs a constant SPR estimated as an average of the observed values, was also applied. The analyses showed that the performance of the methods is stock and data specific; the methods that work well for one stock may fail for the others. The constant SPR method is not recommended in those cases when the SPR is relatively high and the catch volumes in the reconstructed period are low.

  3. Incorporating uncertainty analysis into life cycle estimates of greenhouse gas emissions from biomass production

    International Nuclear Information System (INIS)

    Johnson, David R.; Willis, Henry H.; Curtright, Aimee E.; Samaras, Constantine; Skone, Timothy

    2011-01-01

    Before further investments are made in utilizing biomass as a source of renewable energy, both policy makers and the energy industry need estimates of the net greenhouse gas (GHG) reductions expected from substituting biobased fuels for fossil fuels. Such GHG reductions depend greatly on how the biomass is cultivated, transported, processed, and converted into fuel or electricity. Any policy aiming to reduce GHGs with biomass-based energy must account for uncertainties in emissions at each stage of production, or else it risks yielding marginal reductions, if any, while potentially imposing great costs. This paper provides a framework for incorporating uncertainty analysis specifically into estimates of the life cycle GHG emissions from the production of biomass. We outline the sources of uncertainty, discuss the implications of uncertainty and variability on the limits of life cycle assessment (LCA) models, and provide a guide for practitioners to best practices in modeling these uncertainties. The suite of techniques described herein can be used to improve the understanding and the representation of the uncertainties associated with emissions estimates, thus enabling improved decision making with respect to the use of biomass for energy and fuel production. -- Highlights: → We describe key model, scenario and data uncertainties in LCAs of biobased fuels. → System boundaries and allocation choices should be consistent with study goals. → Scenarios should be designed around policy levers that can be controlled. → We describe a new way to analyze the importance of covariance between inputs.

  4. A forward-looking, national-scale remote sensing-based model of tidal marsh aboveground carbon stocks

    Science.gov (United States)

    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

  5. Evaluation of the Environmental DNA Method for Estimating Distribution and Biomass of Submerged Aquatic Plants.

    Science.gov (United States)

    Matsuhashi, Saeko; Doi, Hideyuki; Fujiwara, Ayaka; Watanabe, Sonoko; Minamoto, Toshifumi

    2016-01-01

    The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants.

  6. Benchmarking electrical methods for rapid estimation of root biomass.

    Science.gov (United States)

    Postic, François; Doussan, Claude

    2016-01-01

    To face climate change and subsequent rainfall instabilities, crop breeding strategies now include root traits phenotyping. Rapid estimation of root traits in controlled conditions can be achieved by using parallel electrical capacitance and its linear correlation with root dry mass. The aim of the present study was to improve robustness and efficiency of methods based on capacitance and other electrical variables, such as serial/parallel resistance, conductance, impedance or reactance. Using different electrode configurations and stem contact electrodes, we have measured the electrical impedance spectra of wheat plants grown in pots filled with three types of soil. For each configuration, parallel capacitance and other linearly independent electrical variables were computed and their quality as root dry mass estimator was evaluated by a 'sensitivity score' that we derived from Pearson's correlation coefficient r and linear regression parameters. The highest sensitivity score was obtained by parallel capacitance at an alternating current frequency of 116 Hz in three-terminal configuration. Using a clamp, instead of a needle, as a stem electrode did not significantly affect the capacitance measurements. Finally, in handheld LCR meter equivalent conditions, capacitance had the highest sensitivity score and determination coefficient (r (2) = 0.52) at 10 kHz frequency. Our benchmarking of linear correlations between different electrical variables and root dry mass enables to determine more coherent practices for ensuring a sensitive and robust root dry mass estimation, including in handheld LCR meter conditions. This would enhance the value of electrical capacitance as a tool for screening crops in relation with root systems in breeding programs.

  7. [Fungal biomass estimation in soils from southwestern Buenos Aires province (Argentina) using calcofluor white stain].

    Science.gov (United States)

    Vázquez, María B; Amodeo, Martín R; Bianchinotti, María V

    Soil microorganisms are vital for ecosystem functioning because of the role they play in soil nutrient cycling. Agricultural practices and the intensification of land use have a negative effect on microbial activities and fungal biomass has been widely used as an indicator of soil health. The aim of this study was to analyze fungal biomass in soils from southwestern Buenos Aires province using direct fluorescent staining and to contribute to its use as an indicator of environmental changes in the ecosystem as well as to define its sensitivity to weather conditions. Soil samples were collected during two consecutive years. Soil smears were prepared and stained with two different concentrations of calcofluor, and the fungal biomass was estimated under an epifluorescence microscope. Soil fungal biomass varied between 2.23 and 26.89μg fungal C/g soil, being these values in the range expected for the studied soil type. The fungal biomass was positively related to temperature and precipitations. The methodology used was reliable, standardized and sensitive to weather conditions. The results of this study contribute information to evaluate fungal biomass in different soil types and support its use as an indicator of soil health for analyzing the impact of different agricultural practices. Copyright © 2016 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

  8. Estimating leaf area and leaf biomass of open-grown deciduous urban trees

    Science.gov (United States)

    David J. Nowak

    1996-01-01

    Logarithmic regression equations were developed to predict leaf area and leaf biomass for open-grown deciduous urban trees based on stem diameter and crown parameters. Equations based on crown parameters produced more reliable estimates. The equations can be used to help quantify forest structure and functions, particularly in urbanizing and urban/suburban areas.

  9. Wood Specific Gravity Variation with Height and Its Implications for Biomass Estimation

    Science.gov (United States)

    Michael C. Wiemann; G. Bruce Williamson

    2014-01-01

    Wood specific gravity (SG) is widely employed by ecologists as a key variable in estimates of biomass. When it is important to have nondestructive methods for sampling wood for SG measurements, cores are extracted with an increment borer. While boring is a relatively difficult task even at breast height sampling, it is impossible at ground level and arduous at heights...

  10. Uncertainty of Forest Biomass Estimates in North Temperate Forests Due to Allometry: Implications for Remote Sensing

    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.

  11. Top-down estimates of biomass burning emissions of black carbon in the western United States

    Science.gov (United States)

    Y. H. Mao; Q. B. Li; D. Chen; L. Zhang; W. -M. Hao; K.-N. Liou

    2014-01-01

    We estimate biomass burning and anthropogenic emissions of black carbon (BC) in the western US for May-October 2006 by inverting surface BC concentrations from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using a global chemical transport model. We first use active fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS...

  12. Allometric equations for estimating tree biomass in restored mixed-species Atlantic Forest stands

    Science.gov (United States)

    Lauro Rodrigues Nogueira; Vera Lex Engel; John A. Parrotta; Antonio Carlos Galvão de Melo; Danilo Scorzoni Ré

    2014-01-01

    Restoration of Atlantic Forests is receiving increasing attention because of its role in both biodiversity conservation and carbon sequestration for global climate change mitigation. This study was carried out in an Atlantic Forest restoration project in the south-central region of São Paulo State – Brazil to develop allometric equations to estimate tree biomass of...

  13. Using endmembers in AVIRIS images to estimate changes in vegetative biomass

    Science.gov (United States)

    Smith, Milton O.; Adams, John B.; Ustin, Susan L.; Roberts, Dar A.

    1992-01-01

    Field techniques for estimating vegetative biomass are labor intensive, and rarely are used to monitor changes in biomass over time. Remote-sensing offers an attractive alternative to field measurements; however, because there is no simple correspondence between encoded radiance in multispectral images and biomass, it is not possible to measure vegetative biomass directly from AVIRIS images. Ways to estimate vegetative biomass by identifying community types and then applying biomass scalars derived from field measurements are investigated. Field measurements of community-scale vegetative biomass can be made, at least for local areas, but it is not always possible to identify vegetation communities unambiguously using remote measurements and conventional image-processing techniques. Furthermore, even when communities are well characterized in a single image, it typically is difficult to assess the extent and nature of changes in a time series of images, owing to uncertainties introduced by variations in illumination geometry, atmospheric attenuation, and instrumental responses. Our objective is to develop an improved method based on spectral mixture analysis to characterize and identify vegetative communities, that can be applied to multi-temporal AVIRIS and other types of images. In previous studies, multi-temporal data sets (AVIRIS and TM) of Owens Valley, CA were analyzed and vegetation communities were defined in terms of fractions of reference (laboratory and field) endmember spectra. An advantage of converting an image to fractions of reference endmembers is that, although fractions in a given pixel may vary from image to image in a time series, the endmembers themselves typically are constant, thus providing a consistent frame of reference.

  14. First-order estimate of the planktic foraminifer biomass in the modern ocean

    Directory of Open Access Journals (Sweden)

    R. Schiebel

    2012-09-01

    Full Text Available Planktic foraminifera are heterotrophic mesozooplankton of global marine abundance. The position of planktic foraminifers in the marine food web is different compared to other protozoans and ranges above the base of heterotrophic consumers. Being secondary producers with an omnivorous diet, which ranges from algae to small metazoans, planktic foraminifers are not limited to a single food source, and are assumed to occur at a balanced abundance displaying the overall marine biological productivity at a regional scale. With a new non-destructive protocol developed from the bicinchoninic acid (BCA method and nano-photospectrometry, we have analysed the protein-biomass, along with test size and weight, of 754 individual planktic foraminifers from 21 different species and morphotypes. From additional CHN analysis, it can be assumed that protein-biomass equals carbon-biomass. Accordingly, the average individual planktic foraminifer protein- and carbon-biomass amounts to 0.845 μg. Samples include symbiont bearing and symbiont-barren species from the sea surface down to 2500 m water depth. Conversion factors between individual biomass and assemblage-biomass are calculated for test sizes between 72 and 845 μm (minimum test diameter. Assemblage-biomass data presented here include 1128 sites and water depth intervals. The regional coverage of data includes the North Atlantic, Arabian Sea, Red Sea, and Caribbean as well as literature data from the eastern and western North Pacific, and covers a wide range of oligotrophic to eutrophic waters over six orders of magnitude of planktic-foraminifer assemblage-biomass (PFAB. A first order estimate of the average global planktic foraminifer biomass production (>125 μm ranges from 8.2–32.7 Tg C yr−1 (i.e. 0.008–0.033 Gt C yr−1, and might be more than three times as high including neanic and juvenile individuals adding up to 25–100 Tg C yr−1. However, this is a first

  15. Estimating the fuel moisture content to control the reciprocating grate furnace firing wet woody biomass

    International Nuclear Information System (INIS)

    Striūgas, N.; Vorotinskienė, L.; Paulauskas, R.; Navakas, R.; Džiugys, A.; Narbutas, L.

    2017-01-01

    Highlights: • Combustion of biomass with varying moisture content might lead to unstable operation of a furnace. • Method for automatic control of a furnace fired with wet biomass was developed. • Fuel moisture is estimated by cost-effective indirect method for predictive control. • Fuel moisture estimation methods and furnace control algorithm were validated in an industrial boiler. - Abstract: In small countries like Lithuania with a widespread district heating system, 5–10 MW moving grate biomass furnaces equipped with water boilers and condensing economisers are widely used. Such systems are designed for firing biomass fuels; however, varying fuel moisture, mostly in the range from 30% to 60%, complicates the automated operation. Without manual adjustment of the grate motion mode and other parameters, unstable operation or even extinction of the furnace is possible. To ensure stable furnace operation with moist fuel, the indirect method to estimate the fuel moisture content was developed based on the heat balance of the flue gas condensing economiser. The developed method was implemented into the automatic control unit of the furnace to estimate the moisture content in the feedstock and predictively adjust the furnace parameters for optimal fuel combustion. The indirect method based on the economiser heat balance was experimentally validated in a 6 MW grate-fired furnace fuelled by biomass with moisture contents of 37, 46, 50, 54 and 60%. The analysis shows that the estimated and manually measured values of the fuel moisture content do not differ by more than 3%. This deviation indicates that the indirect fuel moisture calculation method is sufficiently precise and the calculated moisture content varies proportionally to changes in the thermal capacity of the economiser. By smoothing the data using sliding weighted averaging, the oscillations of the fuel moisture content were identified.

  16. Estimates of Forest Biomass Carbon Storage in Liaoning Province of Northeast China: A Review and Assessment

    Science.gov (United States)

    Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J.; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

    2014-01-01

    Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha−1 in 1980 to 31.0 Mg ha−1 in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations. PMID:24586881

  17. Estimate of biomass and carbon pools in disturbed and undisturbed oak forests in Tunisia

    Energy Technology Data Exchange (ETDEWEB)

    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)

  18. Estimates of biomass burning emissions in tropical Asia based on satellite-derived data

    OpenAIRE

    D. Chang; Y. Song

    2009-01-01

    Biomass burning in tropical Asia emits large amounts of trace gases and particulate matter into the atmosphere, which has significant implications for atmospheric chemistry and climatic change. In this study, emissions from open biomass burning over tropical Asia were evaluated during seven fire years from 2000 to 2006 (1 March 2000–31 February 2007). The size of the burned areas was estimated from newly published 1-km L3JRC and 500-m MODIS burned area products (MCD45A1). Available fuel loads...

  19. A Simultaneous Density-Integral System for Estimating Stem Profile and Biomass: Slash Pine and Willow Oak

    Science.gov (United States)

    Bernard R. Parresol; Charles E. Thomas

    1996-01-01

    In the wood utilization industry, both stem profile and biomass are important quantities. The two have traditionally been estimated separately. The introduction of a density-integral method allows for coincident estimation of stem profile and biomass, based on the calculus of mass theory, and provides an alternative to weight-ratio methodology. In the initial...

  20. Dry season biomass estimation as an indicator of rangeland quantity using multi-scale remote sensing data

    CSIR Research Space (South Africa)

    Ramoelo, Abel

    2014-10-01

    Full Text Available vegetation is green and photosynthetic active. During dry season, biomass estimation is always not plausible using vegetation indices. The aim of this study is to estimate dry biomass using the multi-scale remote sensing data in the savanna ecosystem. Field...

  1. Evaluation of Sentinel-1A Data For Above Ground Biomass Estimation in Different Forests in India

    Science.gov (United States)

    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

  2. Propagation of measurement accuracy to biomass soft-sensor estimation and control quality.

    Science.gov (United States)

    Steinwandter, Valentin; Zahel, Thomas; Sagmeister, Patrick; Herwig, Christoph

    2017-01-01

    In biopharmaceutical process development and manufacturing, the online measurement of biomass and derived specific turnover rates is a central task to physiologically monitor and control the process. However, hard-type sensors such as dielectric spectroscopy, broth fluorescence, or permittivity measurement harbor various disadvantages. Therefore, soft-sensors, which use measurements of the off-gas stream and substrate feed to reconcile turnover rates and provide an online estimate of the biomass formation, are smart alternatives. For the reconciliation procedure, mass and energy balances are used together with accuracy estimations of measured conversion rates, which were so far arbitrarily chosen and static over the entire process. In this contribution, we present a novel strategy within the soft-sensor framework (named adaptive soft-sensor) to propagate uncertainties from measurements to conversion rates and demonstrate the benefits: For industrially relevant conditions, hereby the error of the resulting estimated biomass formation rate and specific substrate consumption rate could be decreased by 43 and 64 %, respectively, compared to traditional soft-sensor approaches. Moreover, we present a generic workflow to determine the required raw signal accuracy to obtain predefined accuracies of soft-sensor estimations. Thereby, appropriate measurement devices and maintenance intervals can be selected. Furthermore, using this workflow, we demonstrate that the estimation accuracy of the soft-sensor can be additionally and substantially increased.

  3. An integrated pan-tropical biomass map using multiple reference datasets

    OpenAIRE

    Avitabile, V.; Herold, M.; Heuvelink, G. B. M.; Lewis, S. L.; Phillips, O. L.; Asner, G. P.; Armston, J.; Ashton, P. S.; Banin, L.; Bayol, N.; Berry, N. J.; Boeckx, P.; de Jong, B. H. J.; DeVries, B.; Girardin, C. A. J.

    2016-01-01

    We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging...

  4. Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

    Science.gov (United States)

    Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.

    2015-03-01

    Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.

  5. Precise plant height monitoring and biomass estimation with Terrestrial Laser Scanning in paddy rice

    Directory of Open Access Journals (Sweden)

    N. Tilly

    2013-10-01

    Full Text Available Optimizing crop management is a major topic in the field of precision agriculture as the growing world population puts pressure on the efficiency of field production. Accordingly, methods to measure plant parameters with the needed precision and within-field resolution are required. Studies show that Terrestrial Laser Scanning (TLS is a suitable method to capture small objects like crop plants. In this contribution, the results of multi-temporal surveys on paddy rice fields with the TLS system Riegl LMS-Z420i are presented. Three campaigns were carried out during the key vegetative stage of rice plants in the growing period 2012 to monitor the plant height. The TLS-derived point clouds are interpolated to visualize plant height above ground as crop surface models (CSMs with a high resolution of 0.01 m. Spatio-temporal differences within the data of one campaign and between consecutive campaigns can be detected. The results were validated against manually measured plant heights with a high correlation (R2 = 0.71. Furthermore, the dependence of actual biomass from plant height was evaluated. To the present, no method for the non-destructive determination of biomass is found yet. Thus, plant parameters, like the height, have to be used for biomass estimations. The good correlation (R2 = 0.66 leads to the assumption that biomass can be estimated from plant height measurements. The results show that TLS can be considered as a very promising tool for precision agriculture.

  6. Annual measurements of gain and loss in aboveground carbon density

    Science.gov (United States)

    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

  7. Relative contributions of sampling effort, measuring, and weighing to precision of larval sea lamprey biomass estimates

    Science.gov (United States)

    Slade, Jeffrey W.; Adams, Jean V.; Cuddy, Douglas W.; Neave, Fraser B.; Sullivan, W. Paul; Young, Robert J.; Fodale, Michael F.; Jones, Michael L.

    2003-01-01

    We developed two weight-length models from 231 populations of larval sea lampreys (Petromyzon marinus) collected from tributaries of the Great Lakes: Lake Ontario (21), Lake Erie (6), Lake Huron (67), Lake Michigan (76), and Lake Superior (61). Both models were mixed models, which used population as a random effect and additional environmental factors as fixed effects. We resampled weights and lengths 1,000 times from data collected in each of 14 other populations not used to develop the models, obtaining a weight and length distribution from reach resampling. To test model performance, we applied the two weight-length models to the resampled length distributions and calculated the predicted mean weights. We also calculated the observed mean weight for each resampling and for each of the original 14 data sets. When the average of predicted means was compared to means from the original data in each stream, inclusion of environmental factors did not consistently improve the performance of the weight-length model. We estimated the variance associated with measures of abundance and mean weight for each of the 14 selected populations and determined that a conservative estimate of the proportional contribution to variance associated with estimating abundance accounted for 32% to 95% of the variance (mean = 66%). Variability in the biomass estimate appears more affected by variability in estimating abundance than in converting length to weight. Hence, efforts to improve the precision of biomass estimates would be aided most by reducing the variability associated with estimating abundance.

  8. Plot size recommendations for biomass estimation in a midwestern old-growth forest

    Science.gov (United States)

    Martin A. Spetich; George R Parker

    1998-01-01

    The authors examine the relationship between disturbance regime and plot size for woody biomass estimation in a midwestern old-growth deciduous forest from 1926 to 1992. Analysis was done on the core 19.6 ac of a 50.1 ac forest in which every tree 4 in. d.b.h. and greater has been tagged and mapped since 1926. Five windows of time are compared—1926, 1976, 1981, 1986...

  9. Forest biomass variation in Southernmost Brazil: the impact of Araucaria trees.

    Science.gov (United States)

    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

  10. Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA

    Science.gov (United States)

    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-...

  11. Modeling mangrove biomass using remote sensing based age and growth estimates

    Science.gov (United States)

    Lagomasino, D.; Fatoyinbo, T. E.; Feliciano, E. A.; Lee, S. K.; Trettin, C.; Mangora, M.; Rahman, M.

    2016-12-01

    Mangroves are highly regarded coastal forests because of their ecosystem services and high carbon storage potential. In addition, these forests can develop rapidly in locations where congenial environmental conditions and sediment supply are available. Monitoring the growth and age of developing mangrove forests is crucial for sustainable management and estimating carbon stocks. Combining imagery from radar and optical satellites (e.g., TanDEM-X and Landsat), we can estimate young mangrove growth and age at regional and continental scales. We used TanDEM-X radar interferometry for modeling canopy height in 2013 and Landsat to measure land cover change from 1990 to 2013. Annual NDVI composites were determined for each calendar year between 1990 and 2013. New land areas gained from the transition of water to vegetation were determined by the differences in annual NDVI composites and the reference year 2013. The year of the greatest NDVI difference that met the threshold criteria was used as the initial tree height (0 m). Annual canopy height growth rates were estimated by the duration between land generation times and 2013 canopy height models derived from TanDEM-X and very-high resolution optical data. In this presentation, we compare growth rates and biomass accumulation in mangrove forests at four river deltas; the Zambezi (Mozambique), Rufiji (Tanzania), Ganges (Bangladesh), and Mekong (Vietnam). The spatial patterns of growth rates coincided with characteristic successional paradigms and stream morphology, where the maximum growth rates typically occurred along prograding creek banks. Initial comparisons between height-only and growth-age biomass indicate that the latter tend to overestimate biomass for younger forest stands of similar height. Both the vertical (e.g., canopy height) and horizontal (e.g., expansion) growth rates measured from remote sensing can garner important information regarding mangrove succession and primary productivity. Continued research

  12. A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models

    Science.gov (United States)

    Hailemariam Temesgen; David Affleck; Krishna Poudel; Andrew Gray; John Sessions

    2015-01-01

    Accurate biomass measurements and analyses are critical components in quantifying carbon stocks and sequestration rates, assessing potential impacts due to climate change, locating bio-energy processing plants, and mapping and planning fuel treatments. To this end, biomass equations will remain a key component of future carbon measurements and estimation. As...

  13. Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon Explorando texturas de imagens TM e suas relações com estimativas de biomassa em Rondônia

    Directory of Open Access Journals (Sweden)

    Dengsheng Lu

    2005-06-01

    Full Text Available Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation, associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25, and five TM bands (TM 2, 3, 4, 5, and 7 were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.Muitas medidas de textura têm sido desenvolvidas e utilizadas para melhorar a acurácia de classificações de cobertura das terras, mas raramente têm-se avaliado a importância dessas medidas em estimativas de biomassa. Este trabalho utilizou dados Landsat TM para explorar as relações entre texturas de imagens TM e biomassa em Rondônia, Amazônia. Foram analisadas oito medidas de textura baseadas em matrizes de co-ocorrência de tons de cinza (i.e., média, variância, homogeneidade, contraste, dissimilaridade, entropia, segundo momento e correlação, associadas com sete diferentes tamanhos de janela (5x5, 7x7

  14. Estimating forest characteristics using NAIP imagery and ArcObjects

    Science.gov (United States)

    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...

  15. Impact of biomass burning on urban air quality estimated by organic tracers: Guangzhou and Beijing as cases

    International Nuclear Information System (INIS)

    Qiaoqiao Wang; Min Shao; Ying Liu; Kuster, William; Goldan, Paul; Xiaohua Li; Yuan Liu; Sihua Lu

    2007-01-01

    The impacts of biomass burning have not been adequately studied in China. In this work, chemical compositions of volatile organic compounds and particulate organic matters were measured in August 2005 in Beijing and in October 2004 in Guangzhou city. The performance of several possible tracers for biomass burning is compared by using acetonitrile as a reference compound. The correlations between the possible tracers and acetonitrile show that the use of K + as a tracer could result in bias because of the existence of other K+ sources in urban areas, while chloromethane is not reliable due to its wide use as industrial chemical. The impact of biomass burning on air quality is estimated using acetonitrile and levoglucosan as tracers. The results show that the impact of biomass burning is ubiquitous in both suburban and urban Guangzhou, and the frequencies of air pollution episodes significantly influenced by biomass burning were 100% for Xinken and 58% for downtown Guangzhou city. Fortunately, the air quality in only 2 out of 22 days was partly impacted by biomass burning in August in Beijing, the month that 2008 Olympic games will take place. The quantitative contribution of biomass burning to ambient PM 2.5 concentrations in Guangzhou city was also estimated by the ratio of levoglocusan to PM 2.5 in both the ambient air and biomass burning plumes. The results show that biomass burning contributes 3.02013;16.8% and 4.02013;19.0% of PM 2.5 concentrations in Xinken and Guangzhou downtown, respectively. (Author)

  16. Evaluation of Above Ground Biomass Estimation Accuracy for Alpine Meadow Based on MODIS Vegetation Indices

    Directory of Open Access Journals (Sweden)

    Meng Bao-Ping

    2017-01-01

    Full Text Available Animal husbandry is the main agricultural type over the Tibetan Plateau, above ground biomass (AGB is very important to monitor the productivity for administration of grassland resources and grazing balance. The MODIS vegetation indices have been successfully used in numerous studies on grassland AGB estimation in the Tibetan Plateau area. However, there are considerable differences of AGB estimation models both in the form of the models and the accuracy of estimation. In this study, field measurements of AGB data at Sangke Town, Gansu Province, China in four years (2013-2016 and MODIS indices (NDVI and EVI are combined to construct AGB estimation models of alpine meadow grassland. The field measured AGB are also used to evaluate feasibility of models developed for large scale in applying to small area. The results show that (1 the differences in biomass were relatively large among the 5 sample areas of alpine meadow grassland in the study area during 2013-2016, with the maximum and minimum biomass values of 3,963 kg DW/ha and 745.5 kg DW/ha, respectively, and mean value of 1,907.7 kg DW/ha; the mean of EVI value range (0.42-0.60 are slightly smaller than the NDVI’s (0.59-0.75; (2 the optimum estimation model of grassland AGB in the study area is the exponential model based on MODIS EVI, with root mean square error of 656.6 kg DW/ha and relative estimation errors (REE of 36.3%; (3 the estimation errors of grassland AGB models previously constructed at different spatial scales (the Tibetan Plateau, the Gannan Prefecture, and Xiahe County are higher than those directly constructed based on the small area of this study by 9.5%–31.7%, with the increase of the modeling study area scales, the REE increasing as well. This study presents an improved monitoring algorithm of alpine natural grassland AGB estimation and provides a clear direction for future improvement of the grassland AGB estimation and grassland productivity from remote sensing

  17. Estimation of Viable Biomass In Wastewater And Activated Sludge By Determination of ATP, Oxygen Utilization Rate And FDA Hydrolysis

    DEFF Research Database (Denmark)

    Jørgensen, Poul-Erik; Eriksen, T.; Jensen, B.K.

    1992-01-01

    ATP content, oxygen utilization rate (OUR) and fluorescein diacetate (FDA) hydrolysis were tested for the ability to express the amount of viable biomass in wastewater and activated sludge. The relationship between biomass and these activity parameters was established in growth cultures made...... with biomass, while FDA hydrolysis in the sludge failed to show any such correlation. Conversion factors of 3 mg ATP/g dw, 300 mg O2/h g dw and 0.4 A/h (mg dw/ml) for ATP, OUR and FDA methods, respectively, were calculated. When the methods were applied for in situ determinations in four different wastewater...... plants, it was found that ATP content and respiration rate estimated viable biomass to range from 81 to 293 mg dw/g SS for raw wastewater and from 67 to 187 mg dw/g SS for activated sludge with a rather weak correlation between ATP and respiration measurements. The FDA hydrolysis estimated viable biomass...

  18. Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System

    Science.gov (United States)

    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 (1975–2003) 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...

  19. The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient

    Science.gov (United States)

    Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R. F.; Dubayah, R. O.; Ranson, K. J.; Kharuk, V.

    2014-01-01

    The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model

  20. Estimating the aboveground biomass in an old secondary forest on limestone in the Moluccas, Indonesia : Comparing locally developed versus existing allometric models

    NARCIS (Netherlands)

    Stas, Suzanne M.; Rutishauser, Ervan; Chave, Jérôme; Anten, Niels P.R.|info:eu-repo/dai/nl/138797862; 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

  1. Estimation of potential biomass resource and biogas production from aquatic plants in Argentina

    Science.gov (United States)

    Fitzsimons, R. E.; Laurino, C. N.; Vallejos, R. H.

    1982-08-01

    The use of aquatic plants in artificial lakes as a biomass source for biogas and fertilizer production through anaerobic fermentation is evaluated, and the magnitude of this resource and the potential production of biogas and fertilizer are estimated. The specific case considered is the artificial lake that will be created by the construction of Parana Medio Hydroelectric Project on the middle Parana River in Argentina. The growth of the main aquatic plant, water hyacinth, on the middle Parana River has been measured, and its conversion to methane by anaerobic fermentation is determined. It is estimated that gross methane production may be between 1.0-4.1 x 10 to the 9th cu cm/year. The fermentation residue can be used as a soil conditioner, and it is estimated production of the residue may represent between 54,900-221,400 tons of nitrogen/year, a value which is 2-8 times the present nitrogen fertilizer demand in Argentina.

  2. Hydroacoustic estimates of fish biomass and spatial distributions in shallow lakes

    Science.gov (United States)

    Lian, Yuxi; Huang, Geng; Godlewska, Małgorzata; Cai, Xingwei; Li, Chang; Ye, Shaowen; Liu, Jiashou; Li, Zhongjie

    2018-03-01

    We conducted acoustical surveys with a horizontal beam transducer to detect fish and with a vertical beam transducer to detect depth and macrophytes in two typical shallow lakes along the middle and lower reaches of the Changjiang (Yangtze) River in November 2013. Both lakes are subject to active fish management with annual stocking and removal of large fish. The purpose of the study was to compare hydroacoustic horizontal beam estimates with fish landings. The preliminary results show that the fish distribution patterns differed in the two lakes and were affected by water depth and macrophyte coverage. The hydroacoustically estimated fish biomass matched the commercial catch very well in Niushan Lake, but it was two times higher in Kuilei Lake. However, acoustic estimates included all fish, whereas the catch included only fish >45 cm (smaller ones were released). We were unable to determine the proper regression between acoustic target strength and fish length for the dominant fish species in the two lakes.

  3. BOREAS RSS-15 SIR-C and Landsat TM Biomass and Landcover Maps of the NSA

    Science.gov (United States)

    Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Ranson, K. Jon

    2000-01-01

    As part of BOREAS, the RSS-15 team conducted an investigation using SIR-C, X-SAR, and Landsat TM data for estimating total above-ground dry biomass for the SSA and NSA modeling grids and component biomass for the SSA. Relationships of backscatter to total biomass and total biomass to foliage, branch, and bole biomass were used to estimate biomass density across the landscape. The procedure involved image classification with SAR and Landsat TM data and development of simple mapping techniques using combinations of SAR channels. For the SSA, the SIR-C data used were acquired on 06-Oct-1994, and the Landsat TM data used were acquired on 02-Sep-1995. The maps of the NSA were developed from SIR-C data acquired on 13-Apr-1994. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

  4. Predicting of biomass in Brazilian tropical dry forest: a statistical evaluation of generic equations

    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.

  5. Predicting of biomass in Brazilian tropical dry forest: a statistical evaluation of generic equations.

    Science.gov (United States)

    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.

  6. Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

    Science.gov (United States)

    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...

  7. A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

    Science.gov (United States)

    Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

    2018-01-01

    the highest C density of all estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.

  8. Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

    Science.gov (United States)

    Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

    2018-05-01

    Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide

  9. Aboveground persistence of vascular plants in relationship to the levels of airborne nutrient deposition

    NARCIS (Netherlands)

    Hendriks, R.J.J.; Ozinga, W.A.; Berg, van den L.J.L.; Noordwijk, E.; Schaminee, J.H.J.; Groenendael, van J.M.

    2014-01-01

    This paper examines whether high atmospheric nitrogen deposition affects aboveground persistence of vascular plants. We combined information on local aboveground persistence of vascular plants in 245 permanent plots in the Netherlands with estimated level of nitrogen deposition at the time of

  10. Evaluation of alternative approaches for landscape-scale biomass estimation in a mixed-species northern forest

    Science.gov (United States)

    Coeli M. Hoover; Mark J. Ducey; R. Andy Colter; Mariko Yamasaki

    2018-01-01

    There is growing interest in estimating and mapping biomass and carbon content of forests across large landscapes. LiDAR-based inventory methods are increasingly common and have been successfully implemented in multiple forest types. Asner et al. (2011) developed a simple universal forest carbon estimation method for tropical forests that reduces the amount of required...

  11. Integrating field plots, lidar, and landsat time series to provide temporally consistent annual estimates of biomass from 1990 to present

    Science.gov (United States)

    Warren B. Cohen; Hans-Erik Andersen; Sean P. Healey; Gretchen G. Moisen; Todd A. Schroeder; Christopher W. Woodall; Grant M. Domke; Zhiqiang Yang; Robert E. Kennedy; Stephen V. Stehman; Curtis Woodcock; Jim Vogelmann; Zhe Zhu; Chengquan. Huang

    2015-01-01

    We are developing a system that provides temporally consistent biomass estimates for national greenhouse gas inventory reporting to the United Nations Framework Convention on Climate Change. Our model-assisted estimation framework relies on remote sensing to scale from plot measurements to lidar strip samples, to Landsat time series-based maps. As a demonstration, new...

  12. Statistical properties of mean stand biomass estimators in a LIDAR-based double sampling forest survey design.

    Science.gov (United States)

    H.E. Anderson; J. Breidenbach

    2007-01-01

    Airborne laser scanning (LIDAR) can be a valuable tool in double-sampling forest survey designs. LIDAR-derived forest structure metrics are often highly correlated with important forest inventory variables, such as mean stand biomass, and LIDAR-based synthetic regression estimators have the potential to be highly efficient compared to single-stage estimators, which...

  13. Estimation of black carbon content for biomass burning aerosols from multi-channel Raman lidar data

    Science.gov (United States)

    Talianu, Camelia; Marmureanu, Luminita; Nicolae, Doina

    2015-04-01

    Biomass burning due to natural processes (forest fires) or anthropical activities (agriculture, thermal power stations, domestic heating) is an important source of aerosols with a high content of carbon components (black carbon and organic carbon). Multi-channel Raman lidars provide information on the spectral dependence of the backscatter and extinction coefficients, embedding information on the black carbon content. Aerosols with a high content of black carbon have large extinction coefficients and small backscatter coefficients (strong absorption), while aerosols with high content of organic carbon have large backscatter coefficients (weak absorption). This paper presents a method based on radiative calculations to estimate the black carbon content of biomass burning aerosols from 3b+2a+1d lidar signals. Data is collected at Magurele, Romania, at the cross-road of air masses coming from Ukraine, Russia and Greece, where burning events are frequent during both cold and hot seasons. Aerosols are transported in the free troposphere, generally in the 2-4 km altitude range, and reaches the lidar location after 2-3 days. Optical data are collected between 2011-2012 by a multi-channel Raman lidar and follows the quality assurance program of EARLINET. Radiative calculations are made with libRadTran, an open source radiative model developed by ESA. Validation of the retrievals is made by comparison to a co-located C-ToF Aerosol Mass Spectrometer. Keywords: Lidar, aerosols, biomass burning, radiative model, black carbon Acknowledgment: This work has been supported by grants of the Romanian National Authority for Scientific Research, Programme for Research- Space Technology and Advanced Research - STAR, project no. 39/2012 - SIAFIM, and by Romanian Partnerships in priority areas PNII implemented with MEN-UEFISCDI support, project no. 309/2014 - MOBBE

  14. Impact of biomass burning on urban air quality estimated by organic tracers: Guangzhou and Beijing as cases

    Energy Technology Data Exchange (ETDEWEB)

    Qiaoqiao Wang; Min Shao; Ying Liu [State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing 100871, (China); Kuster, William; Goldan, Paul [Earth System Research Laboratory, U.S. Department of Commerce, Boulder, CO 80305, (United States); Xiaohua Li; Yuan Liu; Sihua Lu [State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing 100871, (China)

    2007-12-15

    The impacts of biomass burning have not been adequately studied in China. In this work, chemical compositions of volatile organic compounds and particulate organic matters were measured in August 2005 in Beijing and in October 2004 in Guangzhou city. The performance of several possible tracers for biomass burning is compared by using acetonitrile as a reference compound. The correlations between the possible tracers and acetonitrile show that the use of K{sup +} as a tracer could result in bias because of the existence of other K+ sources in urban areas, while chloromethane is not reliable due to its wide use as industrial chemical. The impact of biomass burning on air quality is estimated using acetonitrile and levoglucosan as tracers. The results show that the impact of biomass burning is ubiquitous in both suburban and urban Guangzhou, and the frequencies of air pollution episodes significantly influenced by biomass burning were 100% for Xinken and 58% for downtown Guangzhou city. Fortunately, the air quality in only 2 out of 22 days was partly impacted by biomass burning in August in Beijing, the month that 2008 Olympic games will take place. The quantitative contribution of biomass burning to ambient PM{sub 2.5} concentrations in Guangzhou city was also estimated by the ratio of levoglocusan to PM{sub 2.5} in both the ambient air and biomass burning plumes. The results show that biomass burning contributes 3.02013;16.8% and 4.02013;19.0% of PM{sub 2.5} concentrations in Xinken and Guangzhou downtown, respectively. (Author)

  15. Impact of biomass burning on urban air quality estimated by organic tracers: Guangzhou and Beijing as cases

    Energy Technology Data Exchange (ETDEWEB)

    Qiaoqiao Wang; Min Shao; Ying Liu [State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing 100871, (China); Kuster, William; Goldan, Paul [Earth System Research Laboratory, U.S. Department of Commerce, Boulder, CO 80305, (United States); Xiaohua Li; Yuan Liu; Sihua Lu [State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing 100871, (China)

    2007-12-15

    The impacts of biomass burning have not been adequately studied in China. In this work, chemical compositions of volatile organic compounds and particulate organic matters were measured in August 2005 in Beijing and in October 2004 in Guangzhou city. The performance of several possible tracers for biomass burning is compared by using acetonitrile as a reference compound. The correlations between the possible tracers and acetonitrile show that the use of K{sup +} as a tracer could result in bias because of the existence of other K+ sources in urban areas, while chloromethane is not reliable due to its wide use as industrial chemical. The impact of biomass burning on air quality is estimated using acetonitrile and levoglucosan as tracers. The results show that the impact of biomass burning is ubiquitous in both suburban and urban Guangzhou, and the frequencies of air pollution episodes significantly influenced by biomass burning were 100% for Xinken and 58% for downtown Guangzhou city. Fortunately, the air quality in only 2 out of 22 days was partly impacted by biomass burning in August in Beijing, the month that 2008 Olympic games will take place. The quantitative contribution of biomass burning to ambient PM{sub 2.5} concentrations in Guangzhou city was also estimated by the ratio of levoglocusan to PM{sub 2.5} in both the ambient air and biomass burning plumes. The results show that biomass burning contributes 3.02013;16.8% and 4.02013;19.0% of PM{sub 2.5} concentrations in Xinken and Guangzhou downtown, respectively. (Author).

  16. Reduced biomass burning emissions reconcile conflicting estimates of the post-2006 atmospheric methane budget.

    Science.gov (United States)

    Worden, John R; Bloom, A Anthony; Pandey, Sudhanshu; Jiang, Zhe; Worden, Helen M; Walker, Thomas W; Houweling, Sander; Röckmann, Thomas

    2017-12-20

    Several viable but conflicting explanations have been proposed to explain the recent ~8 p.p.b. per year increase in atmospheric methane after 2006, equivalent to net emissions increase of ~25 Tg CH 4 per year. A concurrent increase in atmospheric ethane implicates a fossil source; a concurrent decrease in the heavy isotope content of methane points toward a biogenic source, while other studies propose a decrease in the chemical sink (OH). Here we show that biomass burning emissions of methane decreased by 3.7 (±1.4) Tg CH 4 per year from the 2001-2007 to the 2008-2014 time periods using satellite measurements of CO and CH 4 , nearly twice the decrease expected from prior estimates. After updating both the total and isotopic budgets for atmospheric methane with these revised biomass burning emissions (and assuming no change to the chemical sink), we find that fossil fuels contribute between 12-19 Tg CH 4 per year to the recent atmospheric methane increase, thus reconciling the isotopic- and ethane-based results.

  17. Geostationary satellite estimation of biomass burning in Amazonia during BASE-A

    International Nuclear Information System (INIS)

    Menzel, W.P.; Cutrim, E.C.; Prins, E.M.

    1991-01-01

    This chapter presents the results of using Geostationary Operational Environmental Satellite (GOES) Visible Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) infrared window (3.9 and 11.2 microns) data to monitor biomass burning several times per day in Amazonia. The technique of Matson and Dozier using two window channels was adapted to GOES VAS infrared data to estimate the size and temperature of fires associated with deforestation in the vicinity of Alta Floresta, Brazil, during the Biomass Burning Airborne and Spaceborne Experiment - Amazonia (BASE-A). Although VAS data do not offer the spatial resolution available with AVHRR data 97 km versus 1 km, respectively, this decreased resolution does not seem to hinder the ability of the VAS instrument to detect fires; in some cases it proves to be advantageous in that saturation does not occur as often. VAS visible data are additionally helpful in verifying that the hot spots sensed in the infrared are actually related to fires. Furthermore, the fire plumes can be tracked in time to determine their motion and extent. In this way, the GOES satellite offers a unique ability to monitor diurnal variations in fire activity and transport of related aerosols

  18. A generic model for estimating biomass accumulation and greenhouse gas emissions from perennial crops

    Science.gov (United States)

    Ledo, Alicia; Heathcote, Richard; Hastings, Astley; Smith, Pete; Hillier, Jonathan

    2017-04-01

    -models presented in this paper can be parametrized for different crops. Quantifying CO2 capture by plants and biomass accumulation and changes in soil carbon, are key in evaluating the impacts of perennial crops in life cycle analysis. We then use this model to illustrate the importance of biomass in the overall GHG estimation from four important perennial crops - sugarcane, Miscanthus, coffee, and apples - which were chosen to cover tropical and temperate regions, trees and grasses, and energy and food supply.

  19. Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum

    Science.gov (United States)

    Wagle, Pradeep; Bhattarai, Nishan; Gowda, Prasanna H.; Kakani, Vijaya G.

    2017-06-01

    Robust evapotranspiration (ET) models are required to predict water usage in a variety of terrestrial ecosystems under different geographical and agrometeorological conditions. As a result, several remote sensing-based surface energy balance (SEB) models have been developed to estimate ET over large regions. However, comparison of the performance of several SEB models at the same site is limited. In addition, none of the SEB models have been evaluated for their ability to predict ET in rain-fed high biomass sorghum grown for biofuel production. In this paper, we evaluated the performance of five widely used single-source SEB models, namely Surface Energy Balance Algorithm for Land (SEBAL), Mapping ET with Internalized Calibration (METRIC), Surface Energy Balance System (SEBS), Simplified Surface Energy Balance Index (S-SEBI), and operational Simplified Surface Energy Balance (SSEBop), for estimating ET over a high biomass sorghum field during the 2012 and 2013 growing seasons. The predicted ET values were compared against eddy covariance (EC) measured ET (ETEC) for 19 cloud-free Landsat image. In general, S-SEBI, SEBAL, and SEBS performed reasonably well for the study period, while METRIC and SSEBop performed poorly. All SEB models substantially overestimated ET under extremely dry conditions as they underestimated sensible heat (H) and overestimated latent heat (LE) fluxes under dry conditions during the partitioning of available energy. METRIC, SEBAL, and SEBS overestimated LE regardless of wet or dry periods. Consequently, predicted seasonal cumulative ET by METRIC, SEBAL, and SEBS were higher than seasonal cumulative ETEC in both seasons. In contrast, S-SEBI and SSEBop substantially underestimated ET under too wet conditions, and predicted seasonal cumulative ET by S-SEBI and SSEBop were lower than seasonal cumulative ETEC in the relatively wetter 2013 growing season. Our results indicate the necessity of inclusion of soil moisture or plant water stress

  20. Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network

    Directory of Open Access Journals (Sweden)

    Vitor Badiale Furlong

    2013-02-01

    Full Text Available In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulans from initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days, number of clusters (10, 30 and 50 clusters and internal weight softening parameter (Sigma (0.30, 0.45 and 0.60. These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A and 18 (B days of culture growth. The validations demonstrated that in long-term experiments (Validation A the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B, Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth.

  1. Puerto Rico Above Ground Biomass Map, 2000

    Data.gov (United States)

    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...

  2. Floristic, structural, and allometric equations to estimate arboreal volume and biomass in a cerradão site

    Directory of Open Access Journals (Sweden)

    Eder Pereira Miguel

    2017-08-01

    Full Text Available This objective of this study was to characterize the floristic, structural, and ecological groups and to estimate the arboreal volume and biomass of a cerradão site in Palmas, Tocantins, Brazil. A forest inventory was conducted on 10.15 ha of the study area. Plots of 400-m2 were used for systematic sampling. All standing trees (dead or alive with a breast-height diameter (DHB greater than 5 cm were identified and measured. Floristic diversity and horizontal structure were assessed using the Shannon and importance value indices, respectively. Forest vertical structure was classified into three stratata and the tree species were categorized into ecological groups. Ninety tree volumes were rigorously cubed and weighed. Fresh- and dry biomass were sampled and estimated. Mathematical models were applied and adjusted to estimate tree volume and biomass. It was observed that the species Myrcia splendens and Emmotum nitens and the families Fabaceae and Chrysobalanaceae were dominant in our study site. The pioneer (613 individuals ha-1 and climax (530 individuals ha-1 tree species group predominated. The floristic diversity index was estimated as 3.35 nats ind- 1. The vertical structure analysis indicated fewer individuals in the superior stratum (13% compared to the medium (63% and inferior (24% stratum. The Schumacher and Hall model showed better results with regard to estimated forest production. Forest volume and biomass estimates were 126.71 m³ ha-1 and 61.67 Mg ha-1, respectively. The studied cerradão area had high floristic diversity and climax species predominated. Since this cerradão is in close proximity to the Amazon biome, its volume and biomass stocks were higher than those estimated for other cerradão and forest formations within the Cerrado biome.

  3. Carbon stocks in tree biomass and soils of German forests

    Directory of Open Access Journals (Sweden)

    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.

  4. Estimate of the dry branches biomass in plantations of Pinus maestrensis Bisse in the Granma province, Cuba

    Directory of Open Access Journals (Sweden)

    Hector Barrero-Medel

    2015-06-01

    Full Text Available This study aimed to estimate the biomass of dry branches of Pinus plantations maestrensis Bisse inGranma province. To which 138 trees were felled types selected from the execution of a simple random sample of 40 stands; which were pruned and defoliated, carrying out weighing separately biomass branches of each of the same, determined from the moisture content of representative samples of the branches taken at random and dried in stove at 105 ° C until bring to constant weight, and then convert the values to dry weight. To estimate biomass of dry branches four regression models, where the model presented better goodness of fit was logarithmic, with coefficient of determination and adjusted coefficient of determination of 94.4 and 94.3%, highly significant parameters were evaluated (P 0.001 and lower index value Furnival.

  5. Top-down Estimates of Biomass Burning Emissions of Black Carbon in the Western United States

    Science.gov (United States)

    Mao, Y.; Li, Q.; Randerson, J. T.; CHEN, D.; Zhang, L.; Liou, K.

    2012-12-01

    We apply a Bayesian linear inversion to derive top-down estimates of biomass burning emissions of black carbon (BC) in the western United States (WUS) for May-November 2006 by inverting surface BC concentrations from the IMPROVE network using the GEOS-Chem chemical transport model. Model simulations are conducted at both 2°×2.5° (globally) and 0.5°×0.667° (nested over North America) horizontal resolutions. We first improve the spatial distributions and seasonal and interannual variations of the BC emissions from the Global Fire Emissions Database (GFEDv2) using MODIS 8-day active fire counts from 2005-2007. The GFEDv2 emissions in N. America are adjusted for three zones: boreal N. America, temperate N. America, and Mexico plus Central America. The resulting emissions are then used as a priori for the inversion. The a posteriori emissions are 2-5 times higher than the a priori in California and the Rockies. Model surface BC concentrations using the a posteriori estimate provide better agreement with IMPROVE observations (~50% increase in the Taylor skill score), including improved ability to capture the observed variability especially during June-September. However, model surface BC concentrations are still biased low by ~30%. Comparisons with the Fire Locating and Modeling of Burning Emissions (FLAMBE) are included.

  6. Evaluating derived vegetation indices and cover fraction to estimate ...

    African Journals Online (AJOL)

    Nahom

    This study was conducted to assess satellite data for quantifying and mapping the ... aboveground biomass using regression models of the sample aboveground ... especially in the context of drought, land degradation risk assessment and.

  7. Urban forest biomass estimates: is it important to use allometric relationships developed specifically for urban trees? 

    Science.gov (United States)

    M.R. McHale; I.C. Burke; M.A. Lefsky; P.J. Peper; E.G. McPherson

    2009-01-01

    Many studies have analyzed the benefits, costs, and carbon storage capacity associated with urban trees. These studies have been limited by a lack of research on urban tree biomass, such that estimates of carbon storage in urban systems have relied upon allometric relationships developed in traditional forests. As urbanization increases globally, it is becoming...

  8. Estimating grass nutrients and biomass as an indicator of rangeland (forage) quality and quantity using remote sensing in Savanna ecosystems

    CSIR Research Space (South Africa)

    Ramoelo, Abel

    2012-10-01

    Full Text Available and grass quantity, respectively. The objective of the study is to estimate and map leaf N and biomass as an indicator of rangeland quality and quantity using vegetation indices derived from one RapidEye image taken at peak productivity. The study...

  9. Estimation of above ground biomass by using multispectral data for Evergreen Forest in Phu Hin Rong Kla National Park, Thailand

    International Nuclear Information System (INIS)

    Suwanprasit, C.

    2010-01-01

    Tropical forest is the most important and largest source for stocking CO 2 from the atmosphere which might be one of the main sources of carbon emission, global warming and climate change in recent decades. There are two main objectives of this study. The first one is to establish a relationship between above ground biomass and vegetation indices and the other is to evaluate above ground biomass and carbon sequestration for evergreen forest areas in Phu Hin Rong Kla National park, Thailand. Random sampling design based was applied for calculating the above ground biomass at stand level in the selected area by using Brown and Tsutsumi allometric equations. Landsat 7 ETM+ data in February 2009 was used. Support Vector Machine (SVM) was applied for identifying evergreen forest area. Forty-three of vegetation indices and image transformations were used for finding the best correlation with forest stand biomass. Regression analysis was used to investigate the relationship between the biomass volume at stand level and digital data from the satellite image. TM51 which derived from Tsutsumi allometric equation was the highest correlation with stand biomass. Normalized Difference Vegetation Index (NDVI) was not the best correlation in this study. The best biomass estimation model was from TM51 and ND71 (R2 =0.658). The totals of above ground biomass and carbon sequestration were 112,062,010 ton and 56,031,005 ton respectively. The application of this study would be quite useful for understanding the terrestrial carbon dynamics and global climate change. (author)

  10. Measuring and modeling carbon stock change estimates for US forests and uncertainties from apparent inter-annual variability

    Science.gov (United States)

    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...

  11. Thermal efficiency and particulate pollution estimation of four biomass fuels grown on wasteland

    Energy Technology Data Exchange (ETDEWEB)

    Kandpal, J.B.; Madan, M. [Indian Inst. of Tech., New Delhi (India). Centre for Rural Development and Technology

    1996-10-01

    The thermal performance and concentration of suspended particulate matter were studied for 1-hour combustion of four biomass fuels, namely Acacia nilotica, Leucaena leucocepholea, Jatropha curcus, and Morus alba grown in wasteland. Among the four biomass fuels, the highest thermal efficiency was achieved with Acacia nilotica. The suspended particulate matter concentration for 1-hour combustion of four biomass fuels ranged between 850 and 2,360 {micro}g/m{sup 3}.

  12. Estimates of forest biomass carbon storage inLiaoning Province of Northeast China: a review and assessment.

    Science.gov (United States)

    Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

    2014-01-01

    Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha(-1) in 1980 to 31.0 Mg ha(-1) in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations.

  13. Aboveground tree growth varies with belowground carbon allocation in a tropical rainforest environment

    Science.gov (United States)

    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 15–20 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...

  14. Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

    Science.gov (United States)

    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...

  15. Estimating vegetation biomass and cover across large plots in shrub and grass dominated drylands using terrestrial lidar and machine learning

    Science.gov (United States)

    Anderson, Kyle E.; Glenn, Nancy F.; Spaete, Lucas P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan; Derryberry, DeWayne R.

    2018-01-01

    Terrestrial laser scanning (TLS) has been shown to enable an efficient, precise, and non-destructive inventory of vegetation structure at ranges up to hundreds of meters. We developed a method that leverages TLS collections with machine learning techniques to model and map canopy cover and biomass of several classes of short-stature vegetation across large plots. We collected high-definition TLS scans of 26 1-ha plots in desert grasslands and big sagebrush shrublands in southwest Idaho, USA. We used the Random Forests machine learning algorithm to develop decision tree models predicting the biomass and canopy cover of several vegetation classes from statistical descriptors of the aboveground heights of TLS points. Manual measurements of vegetation characteristics collected within each plot served as training and validation data. Models based on five or fewer TLS descriptors of vegetation heights were developed to predict the canopy cover fraction of shrubs (R2 = 0.77, RMSE = 7%), annual grasses (R2 = 0.70, RMSE = 21%), perennial grasses (R2 = 0.36, RMSE = 12%), forbs (R2 = 0.52, RMSE = 6%), bare earth or litter (R2 = 0.49, RMSE = 19%), and the biomass of shrubs (R2 = 0.71, RMSE = 175 g) and herbaceous vegetation (R2 = 0.61, RMSE = 99 g) (all values reported are out-of-bag). Our models explained much of the variability between predictions and manual measurements, and yet we expect that future applications could produce even better results by reducing some of the methodological sources of error that we encountered. Our work demonstrates how TLS can be used efficiently to extend manual measurement of vegetation characteristics from small to large plots in grasslands and shrublands, with potential application to other similarly structured ecosystems. Our method shows that vegetation structural characteristics can be modeled without classifying and delineating individual plants, a challenging and time-consuming step common in previous

  16. Estimation of methane and nitrous oxide emissions from biomass waste in China:A case study in Hebei Province

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Crop residue,animal manure and MSW are selected as representative biomass waste.Greenhouse gas emissions from treatment and disposal process of biomass waste in Hebei province are estimated for the period from 2002 to 2007,using the methodologies recommended by the Intergovernmental Panel on Climate Change.Greenhouse gas emission was about 10 Mt CO2-equivalent annually.About 6% of greenhouse gas emission came from open burning of crop residue,74% from management system of animal manure,and 20% from MSW disposal.Among all the greenhouse gas sources,landfill is the most concentrated one,and has significant potential of emission reduction.

  17. Using Landsat TM and NFI data to estimate wood volume, tree biomass and stand age in Dalarna

    Energy Technology Data Exchange (ETDEWEB)

    Reese, Heather; Nilsson, Mats

    1999-10-01

    As part of the `Monitoring of forest ecosystems` project, within the MISTRA program Remote Sensing for the Environment (RESE), and also with funding from the County Administration Board of Dalarna, a demonstration project was undertaken to estimate forest stand parameters in Dalarna with the use of satellite data. Using two full scenes of Landsat Thematic Mapper data and sample plot data from the Swedish National Forest Inventory, estimations of above ground tree biomass, age, total wood volume, and separate tree species volumes were made using the `k Nearest Neighbor` method. Accuracy assessment results at the single pixel level for total wood volume are consistent with results from previous kNN estimations, with an overall relative RMSE of 75% for the western scene, and 58% overall relative RMSE for the eastern scene. Validation data show a bias of the estimate toward the mean value of the estimation data. The pixel level estimates of above ground tree biomass and age had similar validation results to those for total wood volume. Biomass estimates had a 77% relative RMSE for the western scene, and 69% for the eastern scene. Age estimates had a relative RMSE of 60% in the western scene and 57% in the eastern scene. The results may suggest the need to incorporate a geographic limitation on the plots used in the estimation, and to further investigate the co-registration between the satellite and plot data. While pixel lever errors are high, an aggregation of the estimates to larger (compartment-sized) areas could decrease the error significantly. Previous similar studies have shown that an RMSE of 10% for total wood volume can be obtained for as small areas as 100 to 450 hectares. The estimates from this study will be evaluated for use by the County Administration Board of Dalarna to find areas of ecological interest and to assist in planning 14 refs, 4 figs, 4 tabs

  18. Sustainability of biomass electricity systems. An estimate of costs, macro-economic and environmental impacts

    International Nuclear Information System (INIS)

    Van den Broek, R

    2001-01-01

    Since the 1990s there has been a renewal of interest in the possibility of sustainable generating energy from biomass, an interest driven in part by the climate issue. Other motives are the search for alternatives for parts of Western agriculture and progress in the technological feasibility of efficiently producing high-quality energy from biomass. World-wide this renewed interest has led to a clear increase in research, demonstration and commercial implementation of biomass energy systems. A recent thesis concludes that biomass can contribute to all aspects of sustainability. In the context of sustainable development (often viewed as a concept having economic, social and ecological dimensions), the central question asked by this Ph.D. research is: How do biomass electricity systems compare to fossil-fuel systems and to the land-use that they may replace, in terms of costs, macro-economic and environmental impacts. This article presents a number of conclusions

  19. [Models for biomass estimation of four shrub species planted in urban area of Xi'an city, Northwest China].

    Science.gov (United States)

    Yao, Zheng-Yang; Liu, Jian-Jun

    2014-01-01

    Four common greening shrub species (i. e. Ligustrum quihoui, Buxus bodinieri, Berberis xinganensis and Buxus megistophylla) in Xi'an City were selected to develop the highest correlation and best-fit estimation models for the organ (branch, leaf and root) and total biomass against different independent variables. The results indicated that the organ and total biomass optimal models of the four shrubs were power functional model (CAR model) except for the leaf biomass model of B. megistophylla which was logarithmic functional model (VAR model). The independent variables included basal diameter, crown diameter, crown diameter multiplied by height, canopy area and canopy volume. B. megistophylla significantly differed from the other three shrub species in the independent variable selection, which were basal diameter and crown-related factors, respectively.

  20. Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

    Science.gov (United States)

    Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

    2014-01-01

    Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

  1. Linking aboveground and belowground inducible plant resistance

    NARCIS (Netherlands)

    Bezemer, T.M.

    2009-01-01

    Induced resistance of plants against pests and diseases via plant defense responses is well documented and can occur aboveground, in the leaves, and belowground in the roots. A number of recent studies have shown that soil-borne pests can also induce plant resistance aboveground and vice versa.

  2. 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.

  3. Ciclagem de nutrientes em Acacia mearnsii de wild. V. Quantificação do conteúdo de nutrientes na biomassa aérea de Acacia mearnsii de wild. Procedência australiana Nutrient cycling in Acacia mearnsii de wild. V. Quantification of nutrient contents in the above-ground biomass of australian provenance of Acacia mearnsii de wild

    Directory of Open Access Journals (Sweden)

    Marcos Vinicius Winckler Caldeira

    2000-12-01

    Full Text Available No presente trabalho foi quantificado o conteúdo de nutrientes na procedência Australiana Bodalla de Acácia-negra (Acacia mearnsii De Wild., aos 2,4 anos de idade. A procedência encontra-se estabelecida em solo de baixa fertilidade, com acidez elevada e localizado na Fazenda Menezes, no Distrito de Capão Comprido, município de Butiá-RS, pertencente à Empresa Florestal Agroseta S.A.. Foi selecionado um total de nove árvores para comporem as amostras. A amostragem destrutiva constituiu na individualização dos compartimentos da biomassa aérea (folhas, galhos vivos, galhos mortos, casca e madeira visando à determinação da matéria seca e do conteúdo de nutrientes. As quantidades de nutrientes contidos na biomassa aérea total da procedência Bodalla foram de 182,1kg ha-1 de N; 8,2kg ha-1 de P; 104,4kg ha-1 de K; 66,7kg ha-1 de Ca; 16,1kg ha-1 de Mg e 10,0kg ha-1 de S. Na procedência Bodalla, 57,4% da matéria seca foi alocada para folhas, galhos vivos e galhos mortos, contento 74% do N; 72,1% do P; 63% do K; 68,5% do Ca, 69,3% do Mg e 74,1% do S do total existente na parte aérea. O componente fuste ( casca e madeira acumulou 26% do N; 27,9% do P; 37% do K; 31,5% do Ca; 30,7% do Mg e 25,8% do S.Nutrient contents of 2.4 years old black wattle (., from Bodalla Australian provenance, were quantified. This provenance was established on soils of low fertility and high acidity, at Menezes Farm of Agroseta S.A. Forest CompAcacia mearnsii De Wildany in the Capão Comprido District, municipality of Butiá-RS. A total of nine trees were selected to form the sample. The destructive sampling was constituted in the individualization of compartments of above-ground biomass (leaves, live branches, dead branches, bark and wood to determine dry matter and nutrient contents. The quantity of total nutrients in the above-ground biomass from Bodalla provenance was 182.1kg ha-1 of N; 8.2kg ha-1 of P; 104.4kg ha-1 of K; 66.7kg ha-1 of Ca; 16.1kg ha-1 of

  4. Estimation of lichen biomass with emphasis on reindeer winter pastures at Hardangervidda, S Norway

    OpenAIRE

    Arvid Odland; Sylvi M. Sandvik; Dag K. Bjerketvedt; Linn L. Myrvold

    2014-01-01

    Quantification of lichen abundance is important for management of reindeer populations. We measured dry lichen biomass in 876 micro plots (16.5 cm × 16.5 cm) systematically sampled within 219 vegetation plots (2 m × 2 m) from 7 different areas in S Norway. Lichen biomass was quantified as: (a) dry weight in g m-2, (b) lichen height in cm, (c) lichen cover, and (d) lichen volume (lichen height × lichen cover). Lichen biomass decreased with increasing precipitation and increasing altitude. On l...

  5. Seasonal and diel effects on acoustic fish biomass estimates: application to a shallow reservoir with untargeted common carp (Cyprinus carpio)

    Science.gov (United States)

    Djemali, Imed; Yule, Daniel; Guillard, Jean

    2016-01-01

    The aim of the present study was to understand how seasonal fish distributions affect acoustically derived fish biomass estimates in a shallow reservoir in a semi-arid country (Tunisia). To that end, sampling events were performed during four seasons (spring (June), summer (September), autumn (December) and winter (March)) that included day and night surveys. A Simrad EK60 echosounder, equipped with two 120-kHz split-beam transducers for simultaneous horizontal and vertical beaming, was used to sample the entire water column. Surveys during spring and summer and daytime hours of winter were deemed unusable owing to high methane flux from the sediment, and during the day survey of autumn, fish were close to the reservoir bottom leading to low detectability. It follows that acoustic surveys should be conducted only at night during the cold season (December–March) for shallow reservoirs having carp Cyprinus carpio (L.) as the dominant species. Further, night-time biomass estimates during the cold season declined significantly (P < 0.001) from autumn to winter. Based on our autumn night-time survey, overall fish biomass in the Bir-Mcherga Reservoir was high (mean (± s.d.) 185 ± 98 tonnes (Mg)), but annual fishery exploitation is low (19.3–24.1 Mg) because the fish biomass is likely dominated by invasive carp not targeted by fishers. The results suggest that controlling carp would help improve the fishery.

  6. Estimates of global biomass burning emissions for reactive greenhouse gases (CO, NMHCs, and NOx) and CO2

    Science.gov (United States)

    Jain, Atul K.; Tao, Zhining; Yang, Xiaojuan; Gillespie, Conor

    2006-03-01

    Open fire biomass burning and domestic biofuel burning (e.g., cooking, heating, and charcoal making) algorithms have been incorporated into a terrestrial ecosystem model to estimate CO2 and key reactive GHGs (CO, NOx, and NMHCs) emissions for the year 2000. The emissions are calculated over the globe at a 0.5° × 0.5° spatial resolution using tree density imagery, and two separate sets of data each for global area burned and land clearing for croplands, along with biofuel consumption rate data. The estimated global and annual total dry matter (DM) burned due to open fire biomass burning ranges between 5221 and 7346 Tg DM/yr, whereas the resultant emissions ranges are 6564-9093 Tg CO2/yr, 438-568 Tg CO/yr, 11-16 Tg NOx/yr (as NO), and 29-40 Tg NMHCs/yr. The results indicate that land use changes for cropland is one of the major sources of biomass burning, which amounts to 25-27% (CO2), 25 -28% (CO), 20-23% (NO), and 28-30% (NMHCs) of the total open fire biomass burning emissions of these gases. Estimated DM burned associated with domestic biofuel burning is 3,114 Tg DM/yr, and resultant emissions are 4825 Tg CO2/yr, 243 Tg CO/yr, 3 Tg NOx/yr, and 23 Tg NMHCs/yr. Total emissions from biomass burning are highest in tropical regions (Asia, America, and Africa), where we identify important contributions from primary forest cutting for croplands and domestic biofuel burning.

  7. Acoustic Estimates of Distribution and Biomass of Different Acoustic Scattering Types Between the New England Shelf Break and Slope Waters

    KAUST Repository

    McLaren, Alexander

    2011-11-01

    Due to their great ecological significance, mesopelagic fishes are attracting a wider audience on account of the large biomass they represent. Data from the National Marine Fisheries Service (NMFS) provided the opportunity to explore an unknown region of the North-West Atlantic, adjacent to one of the most productive fisheries in the world. Acoustic data collected during the cruise required the identification of acoustically distinct scattering types to make inferences on the migrations, distributions and biomass of mesopelagic scattering layers. Six scattering types were identified by the proposed method in our data and traces their migrations and distributions in the top 200m of the water column. This method was able to detect and trace the movements of three scattering types to 1000m depth, two of which can be further subdivided. This process of identification enabled the development of three physically-derived target-strength models adapted to traceable acoustic scattering types for the analysis of biomass and length distribution to 1000m depth. The abundance and distribution of acoustic targets varied closely in relation to varying physical environments associated with a warm core ring in the New England continental Shelf break region. The continental shelf break produces biomass density estimates that are twice as high as the warm core ring and the surrounding continental slope waters are an order of magnitude lower than either estimate. Biomass associated with distinct layers is assessed and any benefits brought about by upwelling at the edge of the warm core ring are shown not to result in higher abundance of deepwater species. Finally, asymmetric diurnal migrations in shelf break waters contrasts markedly with the symmetry of migrating layers within the warm ring, both in structure and density estimates, supporting a theory of predatorial and nutritional constraints to migrating pelagic species.

  8. Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

    Science.gov (United States)

    Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

    2012-01-01

    The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized

  9. 3D Ground Penetrating Radar to Detect Tree Roots and Estimate Root Biomass in the Field

    Directory of Open Access Journals (Sweden)

    Shiping Zhu

    2014-06-01

    Full Text Available The objectives of this study were to detect coarse tree root and to estimate root biomass in the field by using an advanced 3D Ground Penetrating Radar (3D GPR system. This study obtained full-resolution 3D imaging results of tree root system using 500 MHz and 800 MHz bow-tie antennas, respectively. The measurement site included two larch trees, and one of them was excavated after GPR measurements. In this paper, a searching algorithm, based on the continuity of pixel intensity along the root in 3D space, is proposed, and two coarse roots whose diameters are more than 5 cm were detected and delineated correctly. Based on the detection results and the measured root biomass, a linear regression model is proposed to estimate the total root biomass in different depth ranges, and the total error was less than 10%. Additionally, based on the detected root samples, a new index named “magnitude width” is proposed to estimate the root diameter that has good correlation with root diameter compared with other common GPR indexes. This index also provides direct measurement of the root diameter with 13%–16% error, providing reasonable and practical root diameter estimation especially in the field.

  10. Biomass production efficiency controlled by management in temperate and boreal ecosystems

    Science.gov (United States)

    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.

  11. Optically-derived estimates of phytoplankton size class and taxonomic group biomass in the Eastern Subarctic Pacific Ocean

    Science.gov (United States)

    Zeng, Chen; Rosengard, Sarah Z.; Burt, William; Peña, M. Angelica; Nemcek, Nina; Zeng, Tao; Arrigo, Kevin R.; Tortell, Philippe D.

    2018-06-01

    We evaluate several algorithms for the estimation of phytoplankton size class (PSC) and functional type (PFT) biomass from ship-based optical measurements in the Subarctic Northeast Pacific Ocean. Using underway measurements of particulate absorption and backscatter in surface waters, we derived estimates of PSC/PFT based on chlorophyll-a concentrations (Chl-a), particulate absorption spectra and the wavelength dependence of particulate backscatter. Optically-derived [Chl-a] and phytoplankton absorption measurements were validated against discrete calibration samples, while the derived PSC/PFT estimates were validated using size-fractionated Chl-a measurements and HPLC analysis of diagnostic photosynthetic pigments (DPA). Our results showflo that PSC/PFT algorithms based on [Chl-a] and particulate absorption spectra performed significantly better than the backscatter slope approach. These two more successful algorithms yielded estimates of phytoplankton size classes that agreed well with HPLC-derived DPA estimates (RMSE = 12.9%, and 16.6%, respectively) across a range of hydrographic and productivity regimes. Moreover, the [Chl-a] algorithm produced PSC estimates that agreed well with size-fractionated [Chl-a] measurements, and estimates of the biomass of specific phytoplankton groups that were consistent with values derived from HPLC. Based on these results, we suggest that simple [Chl-a] measurements should be more fully exploited to improve the classification of phytoplankton assemblages in the Northeast Pacific Ocean.

  12. Hydroacoustic estimation of fish biomass in the Gulf of Nicoya, Costa Rica

    Directory of Open Access Journals (Sweden)

    John Hedgepeth

    2000-06-01

    Full Text Available A stratified sampling design was used for a hydroacoustic survey of the inner parts of the Gulf of Nicoya in 1987 and 1988. The bottom topography of the inner Gulf was modeled by introducing the concept of a topographical basin model, as the basis for the projection of the sample survey estimates to the entire inner gulf. The bottom depth contours and volumes for the basin model were constructed from nautical charts. The estimates of sample abundance were made for the fish in the inner Gulf using the acoustic methods, EMS (Expectation Maximization and Smoothing and echo integration. The estimates of population were made by the multiplication of the topographic model's estimate of water volume and a model of fish density dependent on bottom depth. The results showed a general decrease in fish density biomass with bottom depth, and a simultaneous tendency for maximum concentrations over bottom depths of about four meters. The four meter bottom depth includes a broad expanse of the inner Gulf located south of Isla Chira. Overall estimates of volumetric density (0.269 fish/m³ and of areal densities (1.88 fish/m² are comparable to other estuarine shallow water environments.Se utilizó un diseño muestral estratificado para llevar a cabo una evaluación hidroacústica de la sección interior del Golfo de Nicoya. La topografía submarina fue modelada introduciendo el concepto topográfico de la cuenca, como una forma de proyectar los estimados del muestreo a todo el Golfo interno. Las isobatas y volúmenes de la cuenca del Golfo fueron construidos a partir de cartas náuticas. Los estimados de abundancia en las muestras se hicieron para los peces en la parte interna del Golfo utilizando los métodos acústicos conocidos como EMS (Expectation, Maximitation and Smoothing y ecointegración. Los estimados de población se obtuvieron a partir de la multiplicación de los estimados del modelo topográfico de volúmen acuático y un modelo de densidad de

  13. Generic biomass functions for Norway spruce in Central Europe--a meta-analysis approach toward prediction and uncertainty estimation.

    Science.gov (United States)

    Wirth, Christian; Schumacher, Jens; Schulze, Ernst-Detlef

    2004-02-01

    To facilitate future carbon and nutrient inventories, we used mixed-effect linear models to develop new generic biomass functions for Norway spruce (Picea abies (L.) Karst.) in Central Europe. We present both the functions and their respective variance-covariance matrices and illustrate their application for biomass prediction and uncertainty estimation for Norway spruce trees ranging widely in size, age, competitive status and site. We collected biomass data for 688 trees sampled in 102 stands by 19 authors. The total number of trees in the "base" model data sets containing the predictor variables diameter at breast height (D), height (H), age (A), site index (SI) and site elevation (HSL) varied according to compartment (roots: n = 114, stem: n = 235, dry branches: n = 207, live branches: n = 429 and needles: n = 551). "Core" data sets with about 40% fewer trees could be extracted containing the additional predictor variables crown length and social class. A set of 43 candidate models representing combinations of lnD, lnH, lnA, SI and HSL, including second-order polynomials and interactions, was established. The categorical variable "author" subsuming mainly methodological differences was included as a random effect in a mixed linear model. The Akaike Information Criterion was used for model selection. The best models for stem, root and branch biomass contained only combinations of D, H and A as predictors. More complex models that included site-related variables resulted for needle biomass. Adding crown length as a predictor for needles, branches and roots reduced both the bias and the confidence interval of predictions substantially. Applying the best models to a test data set of 17 stands ranging in age from 16 to 172 years produced realistic allocation patterns at the tree and stand levels. The 95% confidence intervals (% of mean prediction) were highest for crown compartments (approximately +/- 12%) and lowest for stem biomass (approximately +/- 5%), and

  14. Novel and Lost Forests in the Upper Midwestern United States, from New Estimates of Settlement-Era Composition, Stem Density, and Biomass.

    Science.gov (United States)

    Goring, Simon J; Mladenoff, David J; Cogbill, Charles V; Record, Sydne; Paciorek, Christopher J; Jackson, Stephen T; Dietze, Michael C; Dawson, Andria; Matthes, Jaclyn Hatala; 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. We compare pre-settlement to modern forests using US Forest Service Forest Inventory and Analysis (FIA) data to show the prevalence of lost forests (pre-settlement forests with no current analog), and novel forests (modern forests with no past analogs). Differences between pre-settlement and modern forests are spatially structured owing to differences in land-use impacts and accompanying ecological responses. Modern forests are more homogeneous, and ecotonal gradients are more diffuse today than in the past. Novel forest assemblages represent 28% of all FIA cells, and 28% of pre-settlement forests no longer exist in a modern context. Lost forests include tamarack forests in northeastern Minnesota, hemlock and cedar dominated forests in north-central Wisconsin and along the Upper Peninsula of Michigan, and elm, oak, basswood and ironwood forests along the forest-prairie boundary in south central Minnesota and eastern Wisconsin. Novel FIA forest assemblages are distributed evenly across the region, but novelty shows a strong relationship to spatial distance from remnant forests in the upper Midwest, with novelty predicted at between 20 to 60km from remnants, depending on historical forest

  15. Novel and Lost Forests in the Upper Midwestern United States, from New Estimates of Settlement-Era Composition, Stem Density, and Biomass.

    Directory of Open Access Journals (Sweden)

    Simon J Goring

    Full Text Available 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.We compare pre-settlement to modern forests using US Forest Service Forest Inventory and Analysis (FIA data to show the prevalence of lost forests (pre-settlement forests with no current analog, and novel forests (modern forests with no past analogs. Differences between pre-settlement and modern forests are spatially structured owing to differences in land-use impacts and accompanying ecological responses. Modern forests are more homogeneous, and ecotonal gradients are more diffuse today than in the past. Novel forest assemblages represent 28% of all FIA cells, and 28% of pre-settlement forests no longer exist in a modern context. Lost forests include tamarack forests in northeastern Minnesota, hemlock and cedar dominated forests in north-central Wisconsin and along the Upper Peninsula of Michigan, and elm, oak, basswood and ironwood forests along the forest-prairie boundary in south central Minnesota and eastern Wisconsin. Novel FIA forest assemblages are distributed evenly across the region, but novelty shows a strong relationship to spatial distance from remnant forests in the upper Midwest, with novelty predicted at between 20 to 60km from remnants, depending on historical

  16. Descendant root volume varies as a function of root type: estimation of root biomass lost during uprooting in Pinus pinaster

    OpenAIRE

    Danjon, Frédéric; Caplan, Joshua S.; Fortin, Mathieu; Meredieu, Céline

    2013-01-01

    Root systems of woody plants generally display a strong relationship between the cross-sectional area or cross-sectional diameter (CSD) of a root and the dry weight of biomass (DWd) or root volume (Vd) that has grown (i.e., is descendent) from a point. Specification of this relationship allows one to quantify root architectural patterns and estimate the amount of material lost when root systems are extracted from the soil. However, specifications of this relationship generally do not account ...

  17. Examination of Abiotic Drivers and Their Influence on Spartina alterniflora Biomass over a Twenty-Eight Year Period Using Landsat 5 TM Satellite Imagery of the Central Georgia Coast

    Directory of Open Access Journals (Sweden)

    John P. R. O’Donnell

    2016-06-01

    Full Text Available We examined the influence of abiotic drivers on inter-annual and phenological patterns of aboveground biomass for Marsh Cordgrass, Spartina alterniflora, on the Central Georgia Coast. The linkages between drivers and plant response via soil edaphic factors are captured in our graphical conceptual model. We used geospatial techniques to scale up in situ measurements of aboveground S. alterniflora biomass to landscape level estimates using 294 Landsat 5 TM scenes acquired between 1984 and 2011. For each scene we extracted data from the same 63 sampling polygons, containing 1222 pixels covering about 1.1 million m2. Using univariate and multiple regression tests, we compared Landsat derived biomass estimates for three S. alterniflora size classes against a suite of abiotic drivers. River discharge, total precipitation, minimum temperature, and mean sea level had positive relationships with and best explained biomass for all dates. Additional results, using seasonally binned data, indicated biomass was responsive to changing combinations of variables across the seasons. Our 28-year analysis revealed aboveground biomass declines of 33%, 35%, and 39% for S. alterniflora tall, medium, and short size classes, respectively. This decline correlated with drought frequency and severity trends and coincided with marsh die-backs events and increased snail herbivory in the second half of the study period.

  18. Energy values and estimation of power generation potentials of some non-woody biomass species

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, M; Patel, S K [National Institute of Technology, Rourkela (India)

    2008-07-01

    In view of high energy potentials in non-woody biomass species and an increasing interest in their utilization for power generation, an attempt has been made in this study to assess the proximate analysis and energy content of different components of Ocimum canum and Tridax procumbens biomass species (both non-woody), and their impact on power generation and land requirement for energy plantations. The net energy content in Ocimum canum was found to be slightly higher than that in Tridax procumbens. In spite of having higher ash contents, the barks from both the plant species exhibited higher calorific values. The results have shown that approximately 650 and 1,270 hectares of land are required to generate 20,000 kWh/day electricity from Ocimum canum and Tridax procumbens biomass species. Coal samples, obtained from six different local mines, were also examined for their qualities, and the results were compared with those of studied biomass materials. This comparison reveals much higher power output with negligible emission of suspended particulate matters (SPM) from biomass materials.

  19. 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)

  20. Estimation of the fraction of biologically active methyl tert-butyl ether degraders in a heterogeneous biomass sample

    DEFF Research Database (Denmark)

    Waul, Christopher Kevin; Arvin, Erik; Schmidt, Jens Ejbye

    2008-01-01

    The fraction of biologically active methyl tert-butyl ether degraders in reactors is just as important for prediction of removal rates as knowledge of the kinetic parameters. The fraction of biologically active methyl tert-butyl ether degraders in a heterogeneous biomass sample, taken from a packed...... bed reactor, was determined using a batch kinetic based approach. The procedure involved modeling of methyl tert-butyl ether removal rates from batch experiments followed by parameter estimations. It was estimated to be 5-14% (w/w) of the measured volatile suspended solids concentration in the reactor....

  1. Semi-empirical modelling for forest above ground biomass estimation using hybrid and fully PolSAR data

    Science.gov (United States)

    Tomar, Kiledar S.; Kumar, Shashi; Tolpekin, Valentyn A.; Joshi, Sushil K.

    2016-05-01

    Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m-alpha and Yamaguchi decomposition modelling were extracted. The R2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha-1) and 73.424 (t ha-1) respectively. On the basis of RMSE and R2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering

  2. Biomass burning emissions of reactive gases estimated from satellite data analysis and ecosystem modeling for the Brazilian Amazon region

    Science.gov (United States)

    Potter, Christopher; Brooks-Genovese, Vanessa; Klooster, Steven; Torregrosa, Alicia

    2002-10-01

    To produce a new daily record of trace gas emissions from biomass burning events for the Brazilian Legal Amazon, we have combined satellite advanced very high resolution radiometer (AVHRR) data on fire counts together for the first time with vegetation greenness imagery as inputs to an ecosystem biomass model at 8 km spatial resolution. This analysis goes beyond previous estimates for reactive gas emissions from Amazon fires, owing to a more detailed geographic distribution estimate of vegetation biomass, coupled with daily fire activity for the region (original 1 km resolution), and inclusion of fire effects in extensive areas of the Legal Amazon (defined as the Brazilian states of Acre, Amapá, Amazonas, Maranhao, Mato Grosso, Pará, Rondônia, Roraima, and Tocantins) covered by open woodland, secondary forests, savanna, and pasture vegetation. Results from our emissions model indicate that annual emissions from Amazon deforestation and biomass burning in the early 1990s total to 102 Tg yr-1 carbon monoxide (CO) and 3.5 Tg yr-1 nitrogen oxides (NOx). Peak daily burning emissions, which occurred in early September 1992, were estimated at slightly more than 3 Tg d-1for CO and 0.1 Tg d-1for NOx flux to the atmosphere. Other burning source fluxes of gases with relatively high emission factors are reported, including methane (CH4), nonmethane hydrocarbons (NMHC), and sulfur dioxide (SO2), in addition to total particulate matter (TPM). We estimate the Brazilian Amazon region to be a source of between one fifth and one third for each of these global emission fluxes to the atmosphere. The regional distribution of burning emissions appears to be highest in the Brazilian states of Maranhao and Tocantins, mainly from burning outside of moist forest areas, and in Pará and Mato Grosso, where we identify important contributions from primary forest cutting and burning. These new daily emission estimates of reactive gases from biomass burning fluxes are designed to be used as

  3. Aboveground Net Primary Production of tree cover at the post-disturbance area in the Tatra National Park, Slovakia

    Directory of Open Access Journals (Sweden)

    Konôpka Bohdan

    2015-09-01

    Full Text Available Large-scale disturbances under the conditions of Slovakia, caused especially by storm and bark beetle, bring dramatic decline in carbon budget of the country, besides other negative consequences. The largest disturbance in modern history of the Slovak forestry was the storm damage that occurred in November 2004. The Tatra National Park (TNP was one of the most affected regions. Thus, in this territory, two transects (T1 – the Danielov dom site and T2 – near the Horný Smokovec village were established to survey basic dendrometric properties of trees in young stands established after the disaster. The standing stock of aboveground biomass in tree cover for the spring and autumn 2014 was calculated using the recorded variables, i.e. tree height and diameter measured at the stem base, together with the region-specific allometric relations. Then, the Aboveground Net Primary Production (ANPP in tree cover was estimated with respect to its components (stem, branches and foliage. ANPP was 315 g m−2 per year (Transect T1, and 391 g m−2 per year (Transect T2. The differences in the structure of ANPP, i.e. contribution of tree components, were found between transects T1 and T2. They were caused by the contrasting tree species composition, specifically the ratios between Norway spruce and broadleaved species. Broadleaves allocated more biomass production to foliage than spruce. This phenomenon together with higher turnover (once a year of foliage caused that broadleaves manifest higher share of fast-cycling carbon in comparison to the amount of carbon sequestrated in woody parts (stem and branches. High variability of ANPP was found within the transects, i.e. among the plots (microsites. As for the representative estimation of the standing stock of aboveground part of tree cover as well as ANPP at the post-disturbance area in the TNP territory, the survey should be performed on a net of research plots. Only this approach enables reliable estimates

  4. Beak measurements of octopus ( Octopus variabilis) in Jiaozhou Bay and their use in size and biomass estimation

    Science.gov (United States)

    Xue, Ying; Ren, Yiping; Meng, Wenrong; Li, Long; Mao, Xia; Han, Dongyan; Ma, Qiuyun

    2013-09-01

    Cephalopods play key roles in global marine ecosystems as both predators and preys. Regressive estimation of original size and weight of cephalopod from beak measurements is a powerful tool of interrogating the feeding ecology of predators at higher trophic levels. In this study, regressive relationships among beak measurements and body length and weight were determined for an octopus species ( Octopus variabilis), an important endemic cephalopod species in the northwest Pacific Ocean. A total of 193 individuals (63 males and 130 females) were collected at a monthly interval from Jiaozhou Bay, China. Regressive relationships among 6 beak measurements (upper hood length, UHL; upper crest length, UCL; lower hood length, LHL; lower crest length, LCL; and upper and lower beak weights) and mantle length (ML), total length (TL) and body weight (W) were determined. Results showed that the relationships between beak size and TL and beak size and ML were linearly regressive, while those between beak size and W fitted a power function model. LHL and UCL were the most useful measurements for estimating the size and biomass of O. variabilis. The relationships among beak measurements and body length (either ML or TL) were not significantly different between two sexes; while those among several beak measurements (UHL, LHL and LBW) and body weight (W) were sexually different. Since male individuals of this species have a slightly greater body weight distribution than female individuals, the body weight was not an appropriate measurement for estimating size and biomass, especially when the sex of individuals in the stomachs of predators was unknown. These relationships provided essential information for future use in size and biomass estimation of O. variabilis, as well as the estimation of predator/prey size ratios in the diet of top predators.

  5. Biomass resilience of Neotropical secondary forests.

    Science.gov (United States)

    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.

  6. The feasibility of remotely sensed data to estimate urban tree dimensions and biomass

    Science.gov (United States)

    Jun-Hak Lee; Yekang Ko; E. Gregory McPherson

    2016-01-01

    Accurately measuring the biophysical dimensions of urban trees, such as crown diameter, stem diameter, height, and biomass, is essential for quantifying their collective benefits as an urban forest. However, the cost of directly measuring thousands or millions of individual trees through field surveys can be prohibitive. Supplementing field surveys with remotely sensed...

  7. Evaluating the remote sensing and inventory-based estimation of biomass in the western Carpathians

    Science.gov (United States)

    Magdalena Main-Knorn; Gretchen G. Moisen; Sean P. Healey; William S. Keeton; Elizabeth A. Freeman; Patrick Hostert

    2011-01-01

    Understanding the potential of forest ecosystems as global carbon sinks requires a thorough knowledge of forest carbon dynamics, including both sequestration and fluxes among multiple pools. The accurate quantification of biomass is important to better understand forest productivity and carbon cycling dynamics. Stand-based inventories (SBIs) are widely used for...

  8. Impacts of communal fuelwood extraction on lidar-estimated biomass patterns of savanna woodlands

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2012-07-01

    Full Text Available Approximately 54% of rural households in South Africa continue to use wood as their main source of energy, mainly for cooking and heating. The provision of biomass by savanna woodlands is thus of considerable value to rural households and therefore...

  9. Validity of zooplankton biomass estimates and energy equivalent in the Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Dalal, S.G.; Parulekar, A.H.

    , as deduced from the data on biochemical composition and energy content, it is evident that zooplankton of the Indian Ocean contains on an average 2.7% organic carbon, rather than the widely quoted value of 6.5%. The biomass production in terms of organic...

  10. Comparison of different approaches of radiation use efficiency of biomass formation estimation in Mountain Norway spruce

    Czech Academy of Sciences Publication Activity Database

    Krupková, Lenka; Marková, I.; Havránková, Kateřina; Pokorný, Radek; Urban, Otmar; Šigut, Ladislav; Pavelka, Marian; Cienciala, E.; Marek, Michal V.

    2017-01-01

    Roč. 31, č. 1 (2017), s. 325-337 ISSN 0931-1890 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk(CZ) LM2015061 Institutional support: RVO:67179843 Keywords : Solar radiation * Biomass increment * Carbon flux * light use efficiency Subject RIV: GK - Forestry OBOR OECD: Forestry Impact factor: 1.842, year: 2016

  11. Above-ground biomass and nutrient accumulation in the tropical ...

    African Journals Online (AJOL)

    This means that the impact of logging in the Ebom rainforest remains low. However, additional research is needed on nutrient input in the forest from outside as well as on the impact of logging on nutrient leaching in order to get a complete picture of the nutrient cycles. Key-words: phytomass, nutrient pools, logging, ...

  12. Above-ground woody carbon sequestration measured from tree rings is coherent with net ecosystem productivity at five eddy-covariance sites.

    Science.gov (United States)

    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.

  13. Use of in vivo chlorophyll fluorescence to estimate photosynthetic activity and biomass productivity in microalgae grown in different culture systems

    Directory of Open Access Journals (Sweden)

    Félix L Figueroa

    2013-11-01

    Full Text Available In vivo chlorophyll fluorescence associated to Photosystem II is being used to evaluate photosynthetic activity of microalgae grown in different types of photobioreactors; however, controversy on methodology is usual. Several recommendations on the use of chlorophyll fluorescence to estimate electron transport rate and productivity of microalgae grown in thin-layer cascade cultivators and methacrylate cylindrical vessels are included. Different methodologies related to the measure of photosynthetic activity in microalgae are discussed: (1 measurement of light absorption, (2 determination of electron transport rates versus irradiance and (3 use of simplified devices based on pulse amplitude modulated (PAM fluorescence as Junior PAM or Pocket PAM with optical fiber and optical head as measuring units, respectively. Data comparisons of in vivo chlorophyll fluorescence by using these devices and other PAM fluorometers as Water-PAM in the microalga Chlorella sp. (Chlorophyta are presented. Estimations of carbon production and productivity by transforming electron transport rate to gross photosynthetic rate (as oxygen evolution using reported oxygen produced per photons absorbed values and carbon photosynthetic yield based on reported oxygen/carbon ratio are also shown. The limitation of ETR as estimator of photosynthetic and biomass productivity is discussed. Low cost:quality PAMs can promote monitoring of chlorophyll fluorescence in algal biotechnology to estimate the photosynthetic activity and biomass productivity.

  14. Spatio-Temporal Patterns and Climate Variables Controlling of Biomass Carbon Stock of Global Grassland Ecosystems from 1982 to 2006

    Directory of Open Access Journals (Sweden)

    Jiangzhou Xia

    2014-02-01

    Full Text Available Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production. The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

  15. Biomass estimates of freshwater zooplankton from length-carbon regression equations

    Directory of Open Access Journals (Sweden)

    Patrizia COMOLI

    2000-02-01

    Full Text Available We present length/carbon regression equations of zooplankton species collected from Lake Maggiore (N. Italy during 1992. The results are discussed in terms of the environmental factors, e.g. food availability, predation, controlling biomass production of particle- feeders and predators in the pelagic system of lakes. The marked seasonality in the length-standardized carbon content of Daphnia, and its time-specific trend suggest that from spring onward food availability for Daphnia population may be regarded as a simple decay function. Seasonality does not affect the carbon content/unit length of the two predator Cladocera Leptodora kindtii and Bythotrephes longimanus. Predation is probably the most important regulating factor for the seasonal dynamics of their carbon biomass. The existence of a constant factor to convert the diameter of Conochilus colonies into carbon seems reasonable for an organism whose population comes on quickly and just as quickly disappears.

  16. Bioenergy in Australia: An improved approach for estimating spatial availability of biomass resources in the agricultural production zones

    International Nuclear Information System (INIS)

    Herr, Alexander; Dunlop, Michael

    2011-01-01

    Bioenergy production from crops and agricultural residues has a greenhouse gas mitigation potential. However, there is considerable debate about the size of this potential. This is partly due to difficulties in estimating the feedstock resource base accurately and with good spatial resolution. Here we provide two techniques for spatially estimating crop-based bioenergy feedstocks in Australia using regional agricultural statistics and national land use maps. The approach accommodates temporal variability by estimating ranges of feedstock availability and the shifting nature of zones of the highest spatial concentration of feedstocks. The techniques are applicable to biomass production from forestry, agricultural residues or oilseeds, all of which have been proposed as biofuel feedstocks. -- Highlights: → Dasymetric mapping appoach for producing spatial and temporal variation maps in feedstock production.→ Combines land use and crop statistics to produce regionally precise feedstock maps. → Feedstock concentrations and feedstock density maps enable identification of feedstock concentration spatially and comparison of yearly variation in production.