WorldWideScience

Sample records for modeling forest biomass

  1. Understanding forest-derived biomass supply with GIS modelling

    DEFF Research Database (Denmark)

    Hock, B. K.; Blomqvist, L.; Hall, P.

    2012-01-01

    distribution, and the cost of delivery as forests are frequently remote from energy users. A GIS-based model was developed to predict supply curves of forest biomass material for a site or group of sites, both now and in the future. The GIS biomass supply model was used to assist the New Zealand Energy...

  2. Forest biomass allometry in global land surface models

    Science.gov (United States)

    Wolf, Adam; Ciais, Philippe; Bellassen, Valentin; Delbart, Nicolas; Field, Christopher B.; Berry, Joseph A.

    2011-09-01

    A number of global land surface models simulate photosynthesis, respiration, and disturbance, important flows in the carbon cycle that are widely tested against flux towers and CO2 concentration gradients. The resulting forest biomass is examined in this paper for its resemblance to realistic stands, which are characterized using allometric theory. The simulated biomass pools largely do not conform to widely observed allometry, particularly for young stands. The best performing models had an explicit treatment of stand-thinning processes, which brought the slope of the allometry of these models closer to observations. Additionally, models that had relatively shorter wood turnover times performed were generally closer to observed allometries. The discrepancy between the pool distribution between models and data suggests estimates of NEE have biases when integrated over the long term, as compared to observed biomass data, and could therefore compromise long-term predictions of land carbon sources and sinks. We think that this presents a practical obstacle for improving models by informing them better with data. The approach taken in this paper, examining biomass pools allometrically, offers a simple approach to improving the characteristic behaviors of global models with the relatively sparse data that is available globally by forest inventory.

  3. Modeling forest aboveground biomass by combining spectrum, textures and topographic features

    Institute of Scientific and Technical Information of China (English)

    Mingshi LI; Ying TAN; Jie PAN; Shikui PENG

    2008-01-01

    Many textural measures have been developed and used for improving land cover classification accu-racy, but they rarely examined the role of textures in improving the performance of forest aboveground biomass estimations. The relationship between texture and biomass is poorly understood. In this paper, SPOT5 HRG datasets were ortho-rectified and atmospherically calibrated. Then the transform of spectral features is introduced, and the extraction of textural measures based on the Gray Level Co-occurrence Matrix is also implemented in accordance with four different directions (0°, 45°, 90o and 135°) and various moving window sizes, ranging from 3 x 3 to 51 x 51. Thus, a variety of textures were generated. Combined with derived topo-graphic features, the forest aboveground biomass estima-tion models for five predominant forest types in the scenic spot of the Mausoleum of Sun Yat-Sen, Nanjing, are identified and constructed, and the estimation accuracies exhibited by these models are also validated and evaluated respectively. The results indicate that: 1) Most textures are weakly correlated with forest biomass, but minority textural measures such as ME, CR and VA play a significantly effective and critical role in estimating forest biomass; 2) The textures of coniferous forest appear preferable to those of broad-leaved forest and mixed forest in representing the spatial configurations of forests;and 3) Among the topographic features including slope,aspect and elevation,aspect has the lowest correlation with the biomass of a forest in this study.

  4. Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

    Directory of Open Access Journals (Sweden)

    Jennifer K. Costanza

    2015-03-01

    Full Text Available We linked state-and-transition simulation models (STSMs with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.

  5. Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

    Science.gov (United States)

    Costanza, Jennifer; Abt, Robert C.; McKerrow, Alexa; Collazo, Jaime

    2015-01-01

    We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.

  6. Tree biomass in the Swiss landscape: nationwide modelling for improved accounting for forest and non-forest trees.

    Science.gov (United States)

    Price, B; Gomez, A; Mathys, L; Gardi, O; Schellenberger, A; Ginzler, C; Thürig, E

    2017-03-01

    Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R (2) of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.

  7. An Optimization-Based System Model of Disturbance-Generated Forest Biomass Utilization

    Science.gov (United States)

    Curry, Guy L.; Coulson, Robert N.; Gan, Jianbang; Tchakerian, Maria D.; Smith, C. Tattersall

    2008-01-01

    Disturbance-generated biomass results from endogenous and exogenous natural and cultural disturbances that affect the health and productivity of forest ecosystems. These disturbances can create large quantities of plant biomass on predictable cycles. A systems analysis model has been developed to quantify aspects of system capacities (harvest,…

  8. 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.

  9. Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model

    Science.gov (United States)

    V V L, P. A.

    2015-12-01

    In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have

  10. Allometry in global models: an important reality check on the growth and biomass of forests

    Science.gov (United States)

    Wolf, A.; Berry, J. A.

    2009-12-01

    Data assimilation incorporates information into a model of nature, and regardless of the algorithm employed the success of DA rests heavily on the quality of both the data and the model. Here we ask the question: if would could assimilate biomass from remote sensing or direct observation, could the models accommodate this information? We find that the state variables that are simulated by land surface models, such as biomass per unit area, are not amenable to developing an "observation operator" necessary for comparison with data. That is, lidar, radar, and multi-angle observations are sensitive to the size and shape of individual trees, whereas most land surface models have no representation of an individual. In addition, most land surface models make no distinction between aboveground and belowground woody biomass. We used the Cannell (1982) forest inventory database to individuate the biomass simulated in land surface models and found that the scaling of biomass pools - leaves, stem, coarse and fine roots - do not obey widely observed empirical and theoretical allometric constraints that are observed for individual trees (Enquist and Niklas, 2002), suggesting that the fractional allocation to these pools and their characteristic turnover times are in error. This discrepancy represents a gap in the translation of research on individual-based allocation to the stand level, where self-pruning and competition are manifest in the observed fluxes and biomass pools per unit area. We develop an approach to synthesize individual-based allocation with area-based flux models using a recent database of component flux and biomass compiled from Fluxnet sites (Luyssaert et al., 2008). We present the size-dependent pattern of allocation and turnover time for forest biomass pools at the spatial scale appropriate for land surface models. We discuss the implications of these results at the global scale for forests with changing size and age structure.

  11. Modeling belowground biomass of black cohosh, a medicinal forest product.

    Science.gov (United States)

    James Chamberlain; Gabrielle Ness; Christine Small; Simon Bonner; Elizabeth Hiebert

    2014-01-01

    Tens of thousands of kilograms of rhizomes and roots of Actaea racemosa L., a native Appalachian forest perennial, are harvested every year and used for the treatment of menopausal conditions. Sustainable management of this and other wild-harvested non-timber forest products requires the ability to effectively and reliably inventory marketable plant...

  12. Detecting forest structure and biomass with C-band multipolarization radar - Physical model and field tests

    Science.gov (United States)

    Westman, Walter E.; Paris, Jack F.

    1987-01-01

    The ability of C-band radar (4.75 GHz) to discriminate features of forest structure, including biomass, is tested using a truck-mounted scatterometer for field tests on a 1.5-3.0 m pygmy forest of cypress (Cupressus pygmaea) and pine (Pinus contorta ssp, Bolanderi) near Mendocino, CA. In all, 31 structural variables of the forest are quantified at seven sites. Also measured was the backscatter from a life-sized physical model of the pygmy forest, composed of nine wooden trees with 'leafy branches' of sponge-wrapped dowels. This model enabled independent testing of the effects of stem, branch, and leafy branch biomass, branch angle, and moisture content on radar backscatter. Field results suggested that surface area of leaves played a greater role in leaf scattering properties than leaf biomass per se. Tree leaf area index was strongly correlated with vertically polarized power backscatter (r = 0.94; P less than 0.01). Field results suggested that the scattering role of leaf water is enhanced as leaf surface area per unit leaf mass increases; i.e., as the moist scattering surfaces become more dispersed. Fog condensate caused a measurable rise in forest backscatter, both from surface and internal rises in water content. Tree branch mass per unit area was highly correlated with cross-polarized backscatter in the field (r = 0.93; P less than 0.01), a result also seen in the physical model.

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

    Science.gov (United States)

    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.

  14. Validation of modelled forest biomass in Germany using BETHY/DLR

    Directory of Open Access Journals (Sweden)

    M. Tum

    2011-07-01

    Full Text Available We present a new approach to the validation of modelled forest Net Primary Productivity (NPP, using empirical data on the mean annual increment, or MAI, in above-ground forest stock. The dynamic biomass model BETHY/DLR is used to estimate the NPP of forest areas in Germany, driven by remote sensing data from VEGETATION, meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF, and additional tree coverage information from the MODIS Vegetation Continuous Field (VCF. The output of BETHY/DLR, Gross Primary Productivity (GPP, is converted to NPP by subtracting the cumulative plant maintenance and growth respiration, and then validated against MAI data derived from German forestry inventories. Validation is conducted for 2000 and 2001 by converting modelled NPP to stem volume at a regional level. Our analysis shows that the presented method fills an important gap in methods for validating modelled NPP against empirically derived data. In addition, we examine theoretical energy potentials calculated from the modelled and validated NPP, assuming sustainable forest management and using species-specific tree heating values. Such estimated forest biomass energy potentials play an important role in the sustainable energy debate.

  15. Specific and generic stem biomass and volume models of tree species in a West African tropical semi-deciduous forest

    DEFF Research Database (Denmark)

    Goussanou, Cédric A.; Guendehou, Sabin; Assogbadjo, Achille E.

    2016-01-01

    The quantification of the contribution of tropical forests to global carbon stocks and climate change mitigation requires availability of data and tools such as allometric equations. This study made available volume and biomass models for eighteen tree species in a semi-deciduous tropical forest...... in West Africa. Generic models were also developed for the forest ecosystem, and basic wood density determined for the tree species. Non-destructive sampling approach was carried out on five hundred and one sample trees to analyse stem volume and biomass. From the modelling of volume and biomass...... predictive ability for biomass. Given tree species richness of tropical forests, the study demonstrated the hypothesis that species-specific models are preferred to generic models, and concluded that further research should be oriented towards development of specific models to cover the full range...

  16. Aboveground Biomass Modeling from Field and LiDAR Data in Brazilian Amazon Tropical Rain Forest

    Science.gov (United States)

    Silva, C. A.; Hudak, A. T.; Vierling, L. A.; Keller, M. M.; Klauberg Silva, C. K.

    2015-12-01

    Tropical forests are an important component of global carbon stocks, but tropical forest responses to climate change are not sufficiently studied or understood. Among remote sensing technologies, airborne LiDAR (Light Detection and Ranging) may be best suited for quantifying tropical forest carbon stocks. Our objective was to estimate aboveground biomass (AGB) using airborne LiDAR and field plot data in Brazilian tropical rain forest. Forest attributes such as tree density, diameter at breast height, and heights were measured at a combination of square plots and linear transects (n=82) distributed across six different geographic zones in the Amazon. Using previously published allometric equations, tree AGB was computed and then summed to calculate total AGB at each sample plot. LiDAR-derived canopy structure metrics were also computed at each sample plot, and random forest regression modelling was applied to predict AGB from selected LiDAR metrics. The LiDAR-derived AGB model was assessed using the random forest explained variation, adjusted coefficient of determination (Adj. R²), root mean square error (RMSE, both absolute and relative) and BIAS (both absolute and relative). Our findings showed that the 99th percentile of height and height skewness were the best LiDAR metrics for AGB prediction. The AGB model using these two best predictors explained 59.59% of AGB variation, with an Adj. R² of 0.92, RMSE of 33.37 Mg/ha (20.28%), and bias of -0.69 (-0.42%). This study showed that LiDAR canopy structure metrics can be used to predict AGC stocks in Tropical Forest with acceptable precision and accuracy. Therefore, we conclude that there is good potential to monitor carbon sequestration in Brazilian Tropical Rain Forest using airborne LiDAR data, large field plots, and the random forest algorithm.

  17. Validation of modelled forest biomass in Germany using BETHY/DLR

    Directory of Open Access Journals (Sweden)

    M. Tum

    2011-11-01

    Full Text Available We present a new approach to the validation of modelled forest Net Primary Productivity (NPP, using empirical data on the mean annual increment, or MAI, in above-ground forest stock. The soil-vegetation-atmosphere-transfer model BETHY/DLR is used, with a particular focus on a detailed parameterization of photosynthesis, to estimate the NPP of forest areas in Germany, driven by remote sensing data from VEGETATION, meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF, and additional tree coverage information from the MODIS Vegetation Continuous Field (VCF. The output of BETHY/DLR, Gross Primary Productivity (GPP, is converted to NPP by subtracting the cumulative plant maintenance and growth respiration, and then validated against MAI data that was calculated from German forestry inventories. Validation is conducted for 2000 and 2001 by converting modelled NPP to stem volume at a regional level. Our analysis shows that the presented method fills an important gap in methods for validating modelled NPP against empirically derived data. In addition, we examine theoretical energy potentials calculated from the modelled and validated NPP, assuming sustainable forest management and using species-specific tree heating values. Such estimated forest biomass energy potentials play an important role in the sustainable energy debate.

  18. [Transferability of remote sensing-based models for estimating moso bamboo forest aboveground biomass].

    Science.gov (United States)

    Yu, Chao-Lin; Du, Hua-Qiang; Zhou, Guo-Mo; Xu, Xiao-Jun; Gui, Zu-Yun

    2012-09-01

    Taking the moso bamboo production areas Lin'an, Anji, and Longquan in Zhejiang Province of East China as study areas, and based on the integration of field survey data and Landsat 5 Thematic Mappr images, five models for estimating the moso bamboo (Phyllostachys heterocycla var. pubescens) forest biomass were constructed by using linear, nonlinear, stepwise regression, multiple regression, and Erf-BP neural network, and the models were evaluated. The models with higher precision were then transferred to the study areas for examining the model's transferability. The results indicated that for the three moso bamboo production areas, Erf-BP neural network model presented the highest precision, followed by stepwise regression and nonlinear models. The Erf-BP neural network model had the best transferability. Model type and independent variables had relatively high effects on the transferability of statistical-based models.

  19. Sustainable Biomass Energy and Indigenous Cultural Models of Well-being in an Alaska Forest Ecosystem

    Directory of Open Access Journals (Sweden)

    Munish Sikka

    2013-09-01

    Full Text Available Oil-dependent indigenous communities in remote regions of Alaska and elsewhere are facing an unprecedented crisis. With the cost of fuel and transport skyrocketing, energy costs are crippling local economies, leading to increasing outmigration and concern for their very existence in the future. What can be done to address this energy crisis, and promote energy security, sustainability and resilience in rural forest communities? We examine the potential of developing a sustainable biomass-energy industry in Southeast Alaska, home to nearly 16,000 Alaska Natives in a dozen rural and two urban communities within the United States’ largest national forest: The Tongass. Although the potential for biomass energy has long been touted, realization of the opportunity has been catalyzed only recently as part of a model of sustainable development being enacted by the region’s largest Native corporation, Sealaska, and its subsidiary, Haa Aaní (“Our Land” L.L.C. In this paper we examine the unique nature of Alaska Native corporations and their potential as engines of sustainable development, particularly through Sealaska’s emerging cultural model of sustainability in relation to social-ecological well-being. We assess the economic, ecological, and atmospheric emissions parameters of a wood-biomass energy industry at various scales according to the “triple bottom line” of sustainability. Finally, we address what additional policy and support measures may be necessary to nurture the successful transition to biomass energy at a sustainable scale to support rural indigenous communities, a more resilient, renewable energy system, and a lower carbon footprint.

  20. 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

  1. 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

  2. Developing synergy regression models with space-borne ALOS PALSAR and Landsat TM sensors for retrieving tropical forest biomass

    Indian Academy of Sciences (India)

    Suman Sinha; C Jeganathan; L K L K Sharma; M S Nathawat; Anup K Das; Shiv Mohan

    2016-06-01

    Forest stand biomass serves as an effective indicator for monitoring REDD (reducing emissions fromdeforestation and forest degradation). Optical remote sensing data have been widely used to derive forestbiophysical parameters inspite of their poor sensitivity towards the forest properties. Microwave remotesensing provides a better alternative owing to its inherent ability to penetrate the forest vegetation.This study aims at developing optimal regression models for retrieving forest above-ground bole biomass(AGBB) utilising optical data from Landsat TM and microwave data from L-band of ALOS PALSARdata over Indian subcontinental tropical deciduous mixed forests located in Munger (Bihar, India). Spatialbiomass models were developed. The results using Landsat TM showed poor correlation (R^2 =0.295and RMSE=35 t/ha) when compared to HH polarized L-band SAR (R^2 =0.868 and RMSE=16.06 t/ha).However, the prediction model performed even better when both the optical and SAR were used simultaneously(R^2 =0.892 and RMSE=14.08 t/ha). The addition of TM metrics has positively contributed inimproving PALSAR estimates of forest biomass. Hence, the study recommends the combined use of bothoptical and SAR sensors for better assessment of stand biomass with significant contribution towardsoperational forestry.

  3. Regional applicability of forest height and aboveground biomass models for the Geoscience Laser Altimeter System

    Science.gov (United States)

    Dirk Pflugmacher; Warren B. Cohen; Robert E. Kennedy; Michael. Lefsky

    2008-01-01

    Accurate estimates of forest aboveground biomass are needed to reduce uncertainties in global and regional terrestrial carbon fluxes. In this study we investigated the utility of the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite for large-scale biomass inventories. GLAS is the first spaceborne lidar sensor that will...

  4. 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

  5. ROE Carbon Storage - Forest Biomass

    Data.gov (United States)

    U.S. Environmental Protection Agency — This polygon dataset depicts the density of forest biomass in counties across the United States, in terms of metric tons of carbon per square mile of land area....

  6. Forest biomass observation: current state and prospective

    Directory of Open Access Journals (Sweden)

    D. G. Schepaschenko

    2017-08-01

    Full Text Available With this article, we provide an overview of the methods, instruments and initiatives for forest biomass observation at global scale. We focus on the freely available information, provided by both remote and in-situ observations. The advantages and limitation of various space borne methods, including optical, radar (C, L and P band and LiDAR, as well as respective instruments available on the orbit (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2 , ALOS PALSAR, Envisat ASAR or expecting (BIOMASS, GEDI, NISAR, SAOCOM-CS are discussed. We emphasize the role of in-situ methods in the development of a biomass models, providing calibration and validation of remote sensing data. We focus on freely available forest biomass maps, databases and empirical models. We describe the functionality of Biomass.Geo-Wiki.org portal, which provides access to a collection of global and regional biomass maps in full resolution with unified legend and units overplayed with high-resolution imagery. The Forest-Observation-System.net is announced as an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. Prospects of unmanned aerial vehicles in the forest inventory are briefly discussed. The work was partly supported by ESA IFBN project (contract 4000114425/15/NL/FF/gp.

  7. Forest biomass-based energy

    Science.gov (United States)

    Janaki R. R. Alavalapati; Pankaj Lal; Andres Susaeta; Robert C. Abt; David N. Wear

    2013-01-01

    Key FindingsHarvesting woody biomass for use as bioenergy is projected to range from 170 million to 336 million green tons by 2050, an increase of 54 to 113 percent over current levels.Consumption projections for forest biomass-based energy, which are based on Energy Information Administration projections, have a high level of...

  8. LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

    Science.gov (United States)

    Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

    2015-01-01

    Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

  9. Robustness of model-based high-resolution prediction of forest biomass against different field plot designs.

    Science.gov (United States)

    Junttila, Virpi; Gautam, Basanta; Karky, Bhaskar Singh; Maguya, Almasi; Tegel, Katri; Kauranne, Tuomo; Gunia, Katja; Hämäläinen, Jarno; Latva-Käyrä, Petri; Nikolaeva, Ekaterina; Peuhkurinen, Jussi

    2015-12-01

    Participatory forest monitoring has been promoted as a means to engage local forest-dependent communities in concrete climate mitigation activities as it brings a sense of ownership to the communities and hence increases the likelihood of success of forest preservation measures. However, sceptics of this approach argue that local community forest members will not easily attain the level of technical proficiency that accurate monitoring needs. Thus it is interesting to establish if local communities can attain such a level of technical proficiency. This paper addresses this issue by assessing the robustness of biomass estimation models based on air-borne laser data using models calibrated with two different field sample designs namely, field data gathered by professional forester teams and field data collected by local communities trained by professional foresters in two study sites in Nepal. The aim is to find if the two field sample data sets can give similar results (LiDAR models) and whether the data can be combined and used together in estimating biomass. Results show that even though the sampling designs and principles of both field campaigns were different, they produced equivalent regression models based on LiDAR data. This was successful in one of the sites (Gorkha). At the other site (Chitwan), however, major discrepancies remained in model-based estimates that used different field sample data sets. This discrepancy can be attributed to the complex terrain and dense forest in the site which makes it difficult to obtain an accurate digital elevation model (DTM) from LiDAR data, and neither set of data produced satisfactory results. Field sample data produced by professional foresters and field sample data produced by professionally trained communities can be used together without affecting prediction performance provided that the correlation between LiDAR predictors and biomass estimates is good enough.

  10. 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.

  11. 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 < 0.05, RMSE = 2.20 kg/m²) and 85% (n = 100, p < 0.01, RMSE = 1.71 kg/m²) of variation in field- and ALS-based 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.

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

    Science.gov (United States)

    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.

  13. Random forest regression modelling for forest aboveground biomass estimation using RISAT-1 PolSAR and terrestrial LiDAR data

    Science.gov (United States)

    Mangla, Rohit; Kumar, Shashi; Nandy, Subrata

    2016-05-01

    SAR and LiDAR remote sensing have already shown the potential of active sensors for forest parameter retrieval. SAR sensor in its fully polarimetric mode has an advantage to retrieve scattering property of different component of forest structure and LiDAR has the capability to measure structural information with very high accuracy. This study was focused on retrieval of forest aboveground biomass (AGB) using Terrestrial Laser Scanner (TLS) based point clouds and scattering property of forest vegetation obtained from decomposition modelling of RISAT-1 fully polarimetric SAR data. TLS data was acquired for 14 plots of Timli forest range, Uttarakhand, India. The forest area is dominated by Sal trees and random sampling with plot size of 0.1 ha (31.62m*31.62m) was adopted for TLS and field data collection. RISAT-1 data was processed to retrieve SAR data based variables and TLS point clouds based 3D imaging was done to retrieve LiDAR based variables. Surface scattering, double-bounce scattering, volume scattering, helix and wire scattering were the SAR based variables retrieved from polarimetric decomposition. Tree heights and stem diameters were used as LiDAR based variables retrieved from single tree vertical height and least square circle fit methods respectively. All the variables obtained for forest plots were used as an input in a machine learning based Random Forest Regression Model, which was developed in this study for forest AGB estimation. Modelled output for forest AGB showed reliable accuracy (RMSE = 27.68 t/ha) and a good coefficient of determination (0.63) was obtained through the linear regression between modelled AGB and field-estimated AGB. The sensitivity analysis showed that the model was more sensitive for the major contributed variables (stem diameter and volume scattering) and these variables were measured from two different remote sensing techniques. This study strongly recommends the integration of SAR and LiDAR data for forest AGB estimation.

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

    NARCIS (Netherlands)

    Johnson, Michelle O.; Galbraith, David; Gloor, Manuel; Deurwaerder, De Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; Randow, Von 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.; Fiore, Di 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; Steege, Ter Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; Heijden, van der Geertje M.F.; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A.; Baker, Timothy R.

    2016-01-01

    Understanding the processes that determine aboveground 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

  15. Theme E: Forest Biomass and Bioenergy

    DEFF Research Database (Denmark)

    Bentsen, Niclas Scott; Stupak, Inge; Smith, C

    2014-01-01

    , evaluate and compare forest biomass sourcing potentials and associated forest sustainability challenges in Europe, Russia, Africa, North and South America, under a scenario where international demand for energy wood continue to increase. We focused on environmental sustainability criteria (GHG emission......Several countries in the world have policies for increased use of biomass for energy and biomaterials. It is likely that such policies will lead to increased international demand for wood and increased pressure on the world’s forests. Concerns for forest sustainability have been expressed...... challenges in the different regions for consideration by institutions developing energy biomass sourcing polices and biomass sustainability criteria in the public and private sector....

  16. 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.

  17. 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).

  18. Allometric models of tree biomass for airborne laser scanning and ground inventory of carbon pool in the forests of Eurasia: Comparative analysis

    Directory of Open Access Journals (Sweden)

    V. A. Usoltsev

    2016-08-01

    Full Text Available For the main tree species in North America, Europe and Japan, a number of thousands of allometric equations for single-tree biomass estimation using mostly tree height and stem diameter at breast height are designed that are intended for terrestrial forest mensuration. However, an innovative airborne laser method of the forest canopy sensing allows processing of on-line a number of morphological indices of trees, to combine them with the biomass allometric models and to evaluate the forest carbon pools. The database of 28 wood and shrub species containing 2.4 thousand definitions is compiled for the first time in the forests of Eurasia, and on its basis, the allometric transcontinental models of fractional structure of biomass of two types and dual use are developed. The first of them include as regressors the tree height and crown diameter and are intended for airborne laser location, while the latter have a traditional appointment for terrestrial forest biomass taxation using tree height and stem diameter. Those and others explain, in most cases, more than 90 % of tree biomass variability. Processing speed of laser location, incommensurable with the terrestrial mensuration, gives the possibility of assessing the change of carbon pool of forests on some territories during periodic overflights. The proposed information can be useful when implementing activities on climate stabilization, as well as in the validation of the simulation results when evaluating the carbon depositing capacity of forests.

  19. 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.

  20. Mortality as a key driver of the spatial distribution of aboveground biomass in Amazonian forest: results from a dynamic vegetation model

    Directory of Open Access Journals (Sweden)

    N. Delbart

    2010-10-01

    Full Text Available Dynamic Vegetation Models (DVMs simulate energy, water and carbon fluxes between the ecosystem and the atmosphere, between the vegetation and the soil, and between plant organs. They also estimate the potential biomass of a forest in equilibrium having grown under a given climate and atmospheric CO2 level. In this study, we evaluate the Above Ground Woody Biomass (AGWB and the above ground woody Net Primary Productivity (NPPAGW simulated by the DVM ORCHIDEE across Amazonian forests, by comparing the simulation results to a large set of ground measurements (220 sites for biomass, 104 sites for NPPAGW. We found that the NPPAGW is on average overestimated by 63%. We also found that the fraction of biomass that is lost through mortality is 85% too high. These model biases nearly compensate each other to give an average simulated AGWB close to the ground measurement average. Nevertheless, the simulated AGWB spatial distribution differs significantly from the observations. Then, we analyse the discrepancies in biomass with regards to discrepancies in NPPAGW and those in the rate of mortality. When we correct for the error in NPPAGW, the errors on the spatial variations in AGWB are exacerbated, showing clearly that a large part of the misrepresentation of biomass comes from a wrong modelling of mortality processes.

    Previous studies showed that Amazonian forests with high productivity have a higher mortality rate than forests with lower productivity. We introduce this relationship, which results in strongly improved modelling of biomass and of its spatial variations. We discuss the possibility of modifying the mortality modelling in ORCHIDEE, and the opportunity to improve forest productivity modelling through the integration of biomass measurements, in particular from remote sensing.

  1. Modelling and prediction of air pollutant transport during the 2014 biomass burning and forest fires in peninsular Southeast Asia.

    Science.gov (United States)

    Duc, Hiep Nguyen; Bang, Ho Quoc; Quang, Ngo Xuan

    2016-02-01

    During the dry season, from November to April, agricultural biomass burning and forest fires especially from March to late April in mainland Southeast Asian countries of Myanmar, Thailand, Laos and Vietnam frequently cause severe particulate pollution not only in the local areas but also across the whole region and beyond due to the prevailing meteorological conditions. Recently, the BASE-ASIA (Biomass-burning Aerosols in South East Asia: Smoke Impact Assessment) and 7-SEAS (7-South-East Asian Studies) studies have provided detailed analysis and important understandings of the transport of pollutants, in particular, the aerosols and their characteristics across the region due to biomass burning in Southeast Asia (SEA). Following these studies, in this paper, we study the transport of particulate air pollution across the peninsular region of SEA and beyond during the March 2014 burning period using meteorological modelling approach and available ground-based and satellite measurements to ascertain the extent of the aerosol pollution and transport in the region of this particular event. The results show that the air pollutants from SEA biomass burning in March 2014 were transported at high altitude to southern China, Hong Kong, Taiwan and beyond as has been highlighted in the BASE-ASIA and 7-SEAS studies. There are strong evidences that the biomass burning in SEA especially in mid-March 2014 has not only caused widespread high particle pollution in Thailand (especially the northern region where most of the fires occurred) but also impacted on the air quality in Hong Kong as measured at the ground-based stations and in LulinC (Taiwan) where a remote background monitoring station is located.

  2. Estimating biomass of mixed and uneven-aged forests using spectral data and a hybrid model combining regression trees and linear models

    Directory of Open Access Journals (Sweden)

    López-Serrano PM

    2016-04-01

    Full Text Available The Sierra Madre Occidental mountain range (Durango, Mexico is of great ecological interest because of the high degree of environmental heterogeneity in the area. The objective of the present study was to estimate the biomass of mixed and uneven-aged forests in the Sierra Madre Occidental by using Landsat-5 TM spectral data and forest inventory data. We used the ATCOR3® atmospheric and topographic correction module to convert remotely sensed imagery digital signals to surface reflectance values. The usual approach of modeling stand variables by using multiple linear regression was compared with a hybrid model developed in two steps: in the first step a regression tree was used to obtain an initial classification of homogeneous biomass groups, and multiple linear regression models were then fitted to each node of the pruned regression tree. Cross-validation of the hybrid model explained 72.96% of the observed stand biomass variation, with a reduction in the RMSE of 25.47% with respect to the estimates yielded by the linear model fitted to the complete database. The most important variables for the binary classification process in the regression tree were the albedo, the corrected readings of the short-wave infrared band of the satellite (2.08-2.35 µm and the topographic moisture index. We used the model output to construct a map for estimating biomass in the study area, which yielded values of between 51 and 235 Mg ha-1. The use of regression trees in combination with stepwise regression of corrected satellite imagery proved a reliable method for estimating forest biomass.

  3. Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

    Science.gov (United States)

    J. A. Blackard; M. V. Finco; E. H. Helmer; G. R. Holden; M. L. Hoppus; D.M. Jacobs; A. J. Lister; G. G. Moisen; M. D. Nelson; R. Riemann; B. Ruefenacht; D. Salajanu; D. L. Weyermann; K. C. Winterberger; T. J. Brandeis; R. L. Czaplewski; R. E. McRoberts; P. L. Patterson; R. P. Tymcio

    2008-01-01

    A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes...

  4. Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest

    Directory of Open Access Journals (Sweden)

    Ryan D. Sheridan

    2014-12-01

    Full Text Available The United States Forest Service Forest Inventory and Analysis (FIA Program provides a diverse selection of data used to assess the status of the nation’s forests using sample locations dispersed throughout the country. Airborne laser scanning (ALS systems are capable of producing accurate measurements of individual tree dimensions and also possess the ability to characterize forest structure in three dimensions. This study investigates the potential of discrete return ALS data for modeling forest aboveground biomass (AGBM and gross volume (gV at FIA plot locations in the Malheur National Forest, eastern Oregon utilizing three analysis levels: (1 individual subplot (r = 7.32 m; (2 plot, comprising four clustered subplots; and (3 hectare plot (r = 56.42 m. A methodology for the creation of three point cloud-based airborne LiDAR metric sets is presented. Models for estimating AGBM and gV based on LiDAR-derived height metrics were built and validated utilizing FIA estimates of AGBM and gV derived using regional allometric equations. Simple linear regression models based on the plot-level analysis out performed subplot-level and hectare-level models, producing R2 values of 0.83 and 0.81 for AGBM and gV, utilizing mean height and the 90th height percentile as predictors, respectively. Similar results were found for multiple regression models, where plot-level analysis produced models with R2 values of 0.87 and 0.88 for AGBM and gV, utilizing multiple height percentile metrics as predictor variables. Results suggest that the current FIA plot design can be used with dense airborne LiDAR data to produce area-based estimates of AGBM and gV, and that the increased spatial scale of hectare plots may be inappropriate for modeling AGBM of gV unless exhaustive tree tallies are available. Overall, this study demonstrates that ALS data can be used to create models that describe the AGBM and gV of Pacific Northwest FIA plots and highlights the potential of

  5. Assessing aboveground tropical forest biomass using Google Earth canopy images.

    Science.gov (United States)

    Ploton, Pierre; Pélissier, Raphaël; Proisy, Christophe; Flavenot, Théo; Barbier, Nicolas; Rai, S N; Couteron, Pierre

    2012-04-01

    Reducing Emissions from Deforestation and Forest Degradation (REDD) in efforts to combat climate change requires participating countries to periodically assess their forest resources on a national scale. Such a process is particularly challenging in the tropics because of technical difficulties related to large aboveground forest biomass stocks, restricted availability of affordable, appropriate remote-sensing images, and a lack of accurate forest inventory data. In this paper, we apply the Fourier-based FOTO method of canopy texture analysis to Google Earth's very-high-resolution images of the wet evergreen forests in the Western Ghats of India in order to (1) assess the predictive power of the method on aboveground biomass of tropical forests, (2) test the merits of free Google Earth images relative to their native commercial IKONOS counterparts and (3) highlight further research needs for affordable, accurate regional aboveground biomass estimations. We used the FOTO method to ordinate Fourier spectra of 1436 square canopy images (125 x 125 m) with respect to a canopy grain texture gradient (i.e., a combination of size distribution and spatial pattern of tree crowns), benchmarked against virtual canopy scenes simulated from a set of known forest structure parameters and a 3-D light interception model. We then used 15 1-ha ground plots to demonstrate that both texture gradients provided by Google Earth and IKONOS images strongly correlated with field-observed stand structure parameters such as the density of large trees, total basal area, and aboveground biomass estimated from a regional allometric model. Our results highlight the great potential of the FOTO method applied to Google Earth data for biomass retrieval because the texture-biomass relationship is only subject to 15% relative error, on average, and does not show obvious saturation trends at large biomass values. We also provide the first reliable map of tropical forest aboveground biomass predicted

  6. Forest biomass estimation with hemispherical photography for multiple forest types and various atmospheric conditions

    Science.gov (United States)

    Clark, Joshua Andrew

    The importance of accurately identifying inventories of domestic energy, including forest biomass, has increasingly become a priority of the US government and its citizens as the cost of fossil fuels has risen. It is useful to identify which of these resources can be processed and transported at the lowest cost for both private and public landowners. Accurate spatial inventories of forest biomass can help landowners allocate resources to maximize forest biomass utilization and provide information regarding current forest health (e.g., forest fire potential, insect susceptibility, wildlife habitat range). This research has indicated that hemispherical photography (HP) may be an accurate and low cost sensing technique for forest biomass measurements. In this dissertation: (1) It is shown that HP gap fraction measurements and both above ground biomass and crown biomass have a linear relationship. (2) It is demonstrated that careful manipulation of images improves gap fraction estimates, even under unfavorable atmospheric conditions. (3) It is shown that estimates of Leaf Area Index (LAI), based on transformations of gap fraction measurements, are the best estimator for both above ground forest biomass and crown biomass. (4) It is shown that many factors negatively influence the utility of HP for biomass estimation. (5) It is shown that biomass of forests stands with regular spacing is not modeled well using HP. As researchers continue to explore different methods for forest biomass estimation, HP is likely to remain as a viable technique, especially if LAI can be accurately estimated. However, other methods should be compared with HP, particularly for stands where LAI is poorly estimated by HP.

  7. [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.

  8. Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR.

    Science.gov (United States)

    Garcia, Mariano; Saatchi, Sassan; Ferraz, Antonio; Silva, Carlos Alberto; Ustin, Susan; Koltunov, Alexander; Balzter, Heiko

    2017-12-01

    Accurate estimation of aboveground forest biomass (AGB) and its dynamics is of paramount importance in understanding the role of forest in the carbon cycle and the effective implementation of climate change mitigation policies. LiDAR is currently the most accurate technology for AGB estimation. LiDAR metrics can be derived from the 3D point cloud (echo-based) or from the canopy height model (CHM). Different sensors and survey configurations can affect the metrics derived from the LiDAR data. We evaluate the ability of the metrics derived from the echo-based and CHM data models to estimate AGB in three different biomes, as well as the impact of point density on the metrics derived from them. Our results show that differences among metrics derived at different point densities were significantly different from zero, with a larger impact on CHM-based than echo-based metrics, particularly when the point density was reduced to 1 point m(-2). Both data models-echo-based and CHM-performed similarly well in estimating AGB at the three study sites. For the temperate forest in the Sierra Nevada Mountains, California, USA, R(2) ranged from 0.79 to 0.8 and RMSE (relRMSE) from 69.69 (35.59%) to 70.71 (36.12%) Mg ha(-1) for the echo-based model and from 0.76 to 0.78 and 73.84 (37.72%) to 128.20 (65.49%) Mg ha(-1) for the CHM-based model. For the moist tropical forest on Barro Colorado Island, Panama, the models gave R(2) ranging between 0.70 and 0.71 and RMSE between 30.08 (12.36%) and 30.32 (12.46) Mg ha(-1) [between 0.69-0.70 and 30.42 (12.50%) and 61.30 (25.19%) Mg ha(-1)] for the echo-based [CHM-based] models. Finally, for the Atlantic forest in the Sierra do Mar, Brazil, R(2) was between 0.58-0.69 and RMSE between 37.73 (8.67%) and 39.77 (9.14%) Mg ha(-1) for the echo-based model, whereas for the CHM R(2) was between 0.37-0.45 and RMSE between 45.43 (10.44%) and 67.23 (15.45%) Mg ha(-1). Metrics derived from the CHM show a higher dependence on point density than

  9. Commodity chemicals from forest biomass - Bioforest

    Energy Technology Data Exchange (ETDEWEB)

    Granstrom, T. [Aalto University, Espoo (Finland)], email: tom.granstrom@aalto.fi

    2012-07-01

    To develop an economic process for production of commodity chemicals from mixed forest biomass (tree tops, limbs, twigs and stumps from softwoods and hardwoods) and recycled fibers within an integrated forest products complex. The chemicals that will be produced are: butanol, isopropanol and ethanol.

  10. Biomass resilience of Neotropical secondary forests

    NARCIS (Netherlands)

    Poorter, Lourens; Bongers, Frans; Aide, T.M.; Almeyda Zambrano, A.M.; Balvanera, Patricia; Jakovac, C.C.; Braga Junqueira, A.; Lohbeck, Madelon; Penã-Claros, Marielos; Rozendaal, D.M.A.

    2016-01-01

    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

  11. Biomass resilience of Neotropical secondary forests

    NARCIS (Netherlands)

    Poorter, L.; Bongers, F.; Aide, T.M.; Almeyda Zambrano, A.M.; Balvanera, P.; Becknell, J.M.; Boukill, V.; Brancalion, P.H.S.; Jakovac, A.C.; Braga Junqueira, A.; Lohbeck, M.W.M.; Pena Claros, M.; Rozendaal, Danae

    2016-01-01

    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 cycle1. However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates a

  12. Biomass resilience of Neotropical secondary forests

    NARCIS (Netherlands)

    Poorter, Lourens; Bongers, Frans; Aide, T.M.; Almeyda Zambrano, A.M.; Balvanera, Patricia; Jakovac, C.C.; Braga Junqueira, A.; Lohbeck, Madelon; Penã-Claros, Marielos; Rozendaal, D.M.A.

    2016-01-01

    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

  13. Biomass resilience of Neotropical secondary forests

    NARCIS (Netherlands)

    Poorter, L.; Bongers, F.; Aide, T.M.; Almeyda Zambrano, A.M.; Balvanera, P.; Becknell, J.M.; Boukill, V.; Brancalion, P.H.S.; Jakovac, A.C.; Braga Junqueira, A.; Lohbeck, M.W.M.; Pena Claros, M.; Rozendaal, Danae

    2016-01-01

    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 cycle1. However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates a

  14. GIS Methodology for Location of Biomass Power Plants Via Multi -Criteria Evaluation and Network Analysis. Location-Allocation Models for Forest Biomass Use; Metodologia SIG para la Localizacion de Centrales de Biomasa mediante Evaluacion Multicriterio y Analisis de Redes. Modelos de Localizacion-Asignacion para el Aprovechamiento de Biomasa Forestal

    Energy Technology Data Exchange (ETDEWEB)

    Paz, C. de la; Dominguez, J.; Perez, M. E.

    2013-02-01

    The main purpose of this study is to find optimal areas for the installation of Biomass Plants for electric generation and grid connected. In order to achieve this goal, a methodology based on Multi-Criteria Evaluation (MCE) and implemented by means a Geographic Information System (GIS) has been developed. Factors and restrictions for biomass resource and power plants location of biomass have been obtained through the dataset. The methodology output includes maps of greater aptitude areas for resource use (forest biomass available), as well as suitable locations for the placement of Forest Biomass facilities. Both cartographic products have been related by means Network Analysis. It generates Location-Allocation Models which allows locating Forest Biomass Facilities according with an optimization of the supply chain from the resource areas. (Author)

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

    NARCIS (Netherlands)

    Johnson, Michelle O.; Galbraith, David; Gloor, Manuel; Deurwaerder, De Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; Randow, Von 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.; Fiore, Di 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; Steege, Ter Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; Heijden, van der Geertje M.F.; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A.; Baker, Timothy R.

    2016-01-01

    Understanding the processes that determine aboveground 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 producti

  16. Forest biomass as an energy source

    Science.gov (United States)

    P.E. Laks; R.W. Hemingway; A. Conner

    1979-01-01

    The Task Force on Forest Biomass as an Energy Source was chartered by the Society of American Foresters on September 26, 1977, and took its present form following an amendment to the charter on October 5, 1977. It built upon the findings of two previous task forces, the Task Force on Energy and Forest Resources and the Task Force for Evaluation of the CORRIM Report (...

  17. Polyhydroxyalkanoate copolymers from forest biomass.

    Science.gov (United States)

    Keenan, Thomas M; Nakas, James P; Tanenbaum, Stuart W

    2006-07-01

    The potential for the use of woody biomass in poly-beta-hydroxyalkanoate (PHA) biosynthesis is reviewed. Based on previously cited work indicating incorporation of xylose or levulinic acid (LA) into PHAs by several bacterial strains, we have initiated a study for exploring bioconversion of forest resources to technically relevant copolymers. Initially, PHA was synthesized in shake-flask cultures of Burkholderia cepacia grown on 2.2% (w/v) xylose, periodically amended with varying concentrations of levulinic acid [0.07-0.67% (w/v)]. Yields of poly(beta-hydroxybutyrate-co-beta-hydroxyvalerate) [P(3HB-co-3HV)] from 1.3 to 4.2 g/l were obtained and could be modulated to contain from 1.0 to 61 mol% 3-hydroxyvalerate (3HV), as determined by 1H and 13C NMR analyses. No evidence for either the 3HB or 4HV monomers was found. Characterization of these P(3HB-co-3HV) samples, which ranged in molecular mass (viscometric, Mv) from 511-919 kDa, by differential scanning calorimetry and thermogravimetric analyses (TGA) provided data which were in agreement for previously reported P(3HB-co-3HV) copolymers. For these samples, it was noted that melting temperature (Tm) and glass transition temperature (Tg) decreased as a function of 3HVcontent, with Tm demonstrating a pseudoeutectic profile as a function of mol% 3HV content. In order to extend these findings to the use of hemicellulosic process streams as an inexpensive carbon source, a detoxification procedure involving sequential overliming and activated charcoal treatments was developed. Two such detoxified process hydrolysates (NREL CF: aspen and CESF: maple) were each fermented with appropriate LA supplementation. For the NREL CF hydrolysate-based cultures amended with 0.25-0.5% LA, P(3HB-co-3HV) yields, PHA contents (PHA as percent of dry biomass), and mol% 3HV compositions of 2.0 g/l, 40% (w/w), and 16-52 mol% were obtained, respectively. Similarly, the CESF hydrolysate-based shake-flask cultures yielded 1.6 g/l PHA, 39% (w

  18. Validating Community-Led Forest Biomass Assessments.

    Science.gov (United States)

    Venter, Michelle; Venter, Oscar; Edwards, Will; Bird, Michael I

    2015-01-01

    The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha(-1), which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50 cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees.

  19. Tree height integrated into pan-tropical forest biomass estimates

    Directory of Open Access Journals (Sweden)

    T. R. Feldpausch

    2012-03-01

    Full Text Available Above-ground tropical tree biomass and carbon storage estimates commonly ignore tree height. We estimate the effect of incorporating height (H on forest biomass estimates using 37 625 concomitant H and diameter measurements (n = 327 plots and 1816 harvested trees (n = 21 plots tropics-wide to answer the following questions:

    1. For trees of known biomass (from destructive harvests which H-model form and geographic scale (plot, region, and continent most reduces biomass estimate uncertainty?

    2. How much does including H relationship estimates derived in (1 reduce uncertainty in biomass estimates across 327 plots spanning four continents?

    3. What effect does the inclusion of H in biomass estimates have on plot- and continental-scale forest biomass estimates?

    The mean relative error in biomass estimates of the destructively harvested trees was half (mean 0.06 when including H, compared to excluding H (mean 0.13. The power- and Weibull-H asymptotic model provided the greatest reduction in uncertainty, with the regional Weibull-H model preferred because it reduces uncertainty in smaller-diameter classes that contain the bulk of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows errors are reduced from 41.8 Mg ha−1 (range 6.6 to 112.4 to 8.0 Mg ha−1 (−2.5 to 23.0 when including $H$. For all plots, above-ground live biomass was 52.2±17.3 Mg ha−1 lower when including H estimates (13%, with the greatest reductions in estimated biomass in Brazilian Shield forests and relatively no change in the Guyana Shield, central Africa and southeast Asia. We show fundamentally different stand structure across the four forested tropical continents, which affects biomass reductions due to $H

  20. Conservative species drive biomass productivity in tropical dry forests

    NARCIS (Netherlands)

    Prado-Junior, Jamir A.; Schiavini, Ivan; Vale, Vagner S.; Sande, van der Masha T.; Lohbeck, Madelon; Poorter, Lourens

    2016-01-01

    Forests account for a substantial part of the terrestrial biomass storage and productivity. To better understand forest productivity, we need to disentangle the processes underlying net biomass change. We tested how above-ground net biomass change and its underlying biomass dynamics (biomass recr

  1. Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data

    Science.gov (United States)

    Ramoelo, Abel; Cho, M. A.; Mathieu, R.; Madonsela, S.; van de Kerchove, R.; Kaszta, Z.; Wolff, E.

    2015-12-01

    Land use and climate change could have huge impacts on food security and the health of various ecosystems. Leaf nitrogen (N) and above-ground biomass are some of the key factors limiting agricultural production and ecosystem functioning. Leaf N and biomass can be used as indicators of rangeland quality and quantity. Conventional methods for assessing these vegetation parameters at landscape scale level are time consuming and tedious. Remote sensing provides a bird-eye view of the landscape, which creates an opportunity to assess these vegetation parameters over wider rangeland areas. Estimation of leaf N has been successful during peak productivity or high biomass and limited studies estimated leaf N in dry season. The estimation of above-ground biomass has been hindered by the signal saturation problems using conventional vegetation indices. The objective of this study is to monitor leaf N and above-ground biomass as an indicator of rangeland quality and quantity using WorldView-2 satellite images and random forest technique in the north-eastern part of South Africa. Series of field work to collect samples for leaf N and biomass were undertaken in March 2013, April or May 2012 (end of wet season) and July 2012 (dry season). Several conventional and red edge based vegetation indices were computed. Overall results indicate that random forest and vegetation indices explained over 89% of leaf N concentrations for grass and trees, and less than 89% for all the years of assessment. The red edge based vegetation indices were among the important variables for predicting leaf N. For the biomass, random forest model explained over 84% of biomass variation in all years, and visible bands including red edge based vegetation indices were found to be important. The study demonstrated that leaf N could be monitored using high spatial resolution with the red edge band capability, and is important for rangeland assessment and monitoring.

  2. 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

  3. Harvesting natural forests for biomass in the Lake States: Using a landscape disturbance and succession model to evaluate long-term carbon, nitrogen and species composition change

    Science.gov (United States)

    La Puma, I. P.; Mladenoff, D.; Bradford, J.; Forrester, J. A.; D'Amato, A.

    2013-12-01

    We used the LANDIS-II spatial forest landscape disturbance and succession model with a modified Century carbon and nitrogen cycling model to investigate how the harvest of branches for biomass will affect above and below-ground carbon and nitrogen allocations under several long term harvest scenarios. We focused on aspen/birch sites along climate and soil composition gradients in the Lake States in order to understand how state guidelines for biomass harvesting may affect long term forest ecosystem sustainability and composition across the landscape. Preliminary results suggest that above-ground biomass does not differ significantly between bole-only and whole-tree harvest over 280 years with 40 year harvest intervals for aspen birch forests. However, differences in above-ground biomass at year 280 between harvest and no harvest scenarios are two-fold. Additionally, aspen dominated sites succeed to maple and pine dominated composition for non-harvest scenarios. Simulations are most sensitive to species physiological traits, and small changes in these parameters strongly affect model results. Our results suggest that details of species specific physiological traits may be important in understanding landscape level changes in carbon sequestration and ecosystem sustainability.

  4. Family forest owner preferences for biomass harvesting in Massachusetts

    Science.gov (United States)

    Marla Markowski-Lindsay; Thomas Stevens; David B. Kittredge; Brett J. Butler; Paul Catanzaro; David Damery

    2012-01-01

    U.S. forests, including family-owned forests, are a potential source of biomass for renewable energy. Family forest owners constitute a significant portion of the overall forestland in the U.S., yet little is known about family forest owners' preferences for supplying wood-based biomass. The goal of this study is to understand how Massachusetts family forest...

  5. Forest volume-to-biomass models and estimates of mass for live and standing dead trees of U.S. forests.

    Science.gov (United States)

    James E. Smith; Linda S. Heath; Jennifer C. Jenkins

    2003-01-01

    Includes methods and equations for nationally consistent estimates of tree-mass density at the stand level (Mg/ha) as predicted by growing-stock volumes reported by the USDA Forest Service for forests of the conterminous United States. Developed for use in FORCARB, a carbon budget model for U.S. forests, the equations also are useful for converting plot-, stand- and...

  6. Forest Biomass for Climate Change Mitigation

    DEFF Research Database (Denmark)

    Nielsen, Anders Tærø

    Awareness of elevated CO2 levels in the atmosphere and resulting climate change has increased focus on renewable energy sources during recent decades. Biomass for energy has been predicted to have the greatest potential for CO2 reductions in the short term and the IPCC assumes that the use...... of biomass for energy is CO2 neutral. Several studies have however criticized this CO2 neutrality assumption and questioned whether CO2 reductions actually are achieved through use of biomass for energy. The purpose of this thesis is to investigate the biomass production potential of poplar plantations...... on southern Scandinavian sites, managed under different systems both in agriculture and in forests. In addition, the objective is to assess the potential of the poplar plantations to mitigate climate change by using poplar biomass for substitution of fossil fuels in comparison to a traditional product...

  7. Detecting tropical forest biomass dynamics from repeated airborne lidar measurements

    Directory of Open Access Journals (Sweden)

    V. Meyer

    2013-08-01

    Full Text Available Reducing uncertainty of terrestrial carbon cycle depends strongly on the accurate estimation of changes of global forest carbon stock. However, this is a challenging problem from either ground surveys or remote sensing techniques in tropical forests. Here, we examine the feasibility of estimating changes of tropical forest biomass from two airborne lidar measurements of forest height acquired about 10 yr apart over Barro Colorado Island (BCI, Panama. We used the forest inventory data from the 50 ha Center for Tropical Forest Science (CTFS plot collected every 5 yr during the study period to calibrate the estimation. We compared two approaches for detecting changes in forest aboveground biomass (AGB: (1 relating changes in lidar height metrics from two sensors directly to changes in ground-estimated biomass; and (2 estimating biomass from each lidar sensor and then computing changes in biomass from the difference of two biomass estimates, using two models, namely one model based on five relative height metrics and the other based only on mean canopy height (MCH. We performed the analysis at different spatial scales from 0.04 ha to 10 ha. Method (1 had large uncertainty in directly detecting biomass changes at scales smaller than 10 ha, but provided detailed information about changes of forest structure. The magnitude of error associated with both the mean biomass stock and mean biomass change declined with increasing spatial scales. Method (2 was accurate at the 1 ha scale to estimate AGB stocks (R2 = 0.7 and RMSEmean = 27.6 Mg ha−1. However, to predict biomass changes, errors became comparable to ground estimates only at a spatial scale of about 10 ha or more. Biomass changes were in the same direction at the spatial scale of 1 ha in 60 to 64% of the subplots, corresponding to p values of respectively 0.1 and 0.033. Large errors in estimating biomass changes from lidar data resulted from the uncertainty in detecting changes at 1 ha from ground

  8. Forest biodiversity and woody biomass harvesting

    Science.gov (United States)

    Deahn M. Donner; T. Bently Wigley; Darren A. Miller

    2017-01-01

    With the expected increase in demand for woody biomass to help meet renewable energy needs, one principal sustainability question has been whether this material can be removed from forest stands while still conserving biological diversity and retaining ecosystem functioning (Hecht et al. 2009; Berch, Morris, and Malcolm 2011; Ridley et al. 2013). In general,...

  9. Forest Biomass Mapping From Lidar and Radar Synergies

    Science.gov (United States)

    Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.

    2011-01-01

    The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the

  10. Mapping aboveground forest biomass combining dendrometric data and spectral signature of forest species

    Science.gov (United States)

    Avocat, H.; Tourneux, F.

    2013-12-01

    Accurate measures and explicit spatial representations of forest biomass compose an important aspect to model the forest productivity and crops, and to implement sustainable forest management. Several methods have been developed to estimate and to map forest biomass, combining point-sources measurements of biophysical variables such as diameter-at-breast height (DBH), tree height, crown size, crown length, crown volume and remote sensing data (spectral vegetation index values). In this study, we propose a new method for aboveground biomass (AGB) mapping of forests and isolated trees. This method is tested on a 1100 km2 area located in the eastern France. In contrast to most of studies, our model is not calibrated using field plot measurements or point-source inventory data. The primary goal of this model is to propose an accessible and reproducible method for AGB mapping of temperate forests, by combining standard biomass values coming from bibliography and remotely sensed data. This method relies on three steps. (1) The first step consists of produce a map of wooded areas including small woods and isolated trees, and to identify the major forest stands. To do this, we use an unsupervised classification of a Landsat 7 ETM+ image. Results are compared and improved with various land cover data. (2) The second step consists of extract the normalized difference vegetation index (NDVI) values of main forest stands. (3) Finally, these values are combined with standard AGB values provided by bibliography, to calibrate four AGB estimation models of different forest types (broadleaves, coniferous, coppices, and mixed stands). This method provides a map of aboveground biomass for forests and isolated trees with a 30 meters spatial resolution. Results demonstrate that 71 % of AGB values for hardwoods vary between 143 and 363 t.ha-1, i.e. × 1 standard deviation around the average. For coniferous stands, most of values of AGB range from 167 to 256 t.ha-1.

  11. Tree height integrated into pantropical forest biomass estimates

    Directory of Open Access Journals (Sweden)

    T. R. Feldpausch

    2012-08-01

    Full Text Available 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 the following questions:

    1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass?

    2. To what extent does including H estimates derived in (1 reduce uncertainty in biomass estimates across all 327 plots?

    3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates?

    The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06, was half that when excluding H (mean 0.13. Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4 to 8.0 Mg ha−1 (−2.5 to 23.0. For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI, or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly

  12. Sustainable Biofuels from Forests: Woody Biomass

    Directory of Open Access Journals (Sweden)

    Edwin H. White

    2011-11-01

    Full Text Available The use of woody biomass feedstocks for bioenergy and bioproducts involves multiple sources of material that together create year round supplies. The main sources of woody biomass include residues from wood manufacturing industries, low value trees including logging slash in forests that are currently underutilized and dedicated short-rotation woody crops. Conceptually a ton of woody biomass feedstocks can replace a barrel of oil as the wood is processed (refined through a biorefinery. As oil is refined only part of the barrel is used for liquid fuel, e.g., gasoline, while much of the carbon in oil is refined into higher value chemical products-carbon in woody biomass can be refined into the same value-added products.

  13. Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part II: sensitivity studies

    Directory of Open Access Journals (Sweden)

    G. Luderer

    2006-01-01

    Full Text Available The Chisholm forest fire that burned in Alberta, Canada, in May 2001 resulted in injection of substantial amounts of smoke into the lower stratosphere. We used the cloud-resolving plume model ATHAM (Active Tracer High resolution Atmospheric Model to investigate the importance of different contributing factors to the severe intensification of the convection induced by the Chisholm fire and the subsequent injection of biomass smoke into the lower stratosphere. The simulations show strong sensitivity of the pyro-convection to background meteorology. This explains the observed coincidence of the convective blow-up of the fire plume and the passage of a synoptic cold front. Furthermore, we performed model sensitivity studies to the rate of release of sensible heat and water vapor from the fire. The release of sensible heat by the fire plays a dominant role for the dynamic development of the pyro-cumulonimbus cloud (pyroCb and the height to which smoke is transported. The convection is very sensitive to the heat flux from the fire. The emissions of water vapor play a less significant role for the injection height but enhance the amount of smoke transported beyond the tropopause level. The aerosol burden in the plume has a strong impact on the microphysical structure of the resulting convective cloud. The dynamic evolution of the pyroCb, however, is only weakly sensitive to the abundance of cloud condensation nuclei (CCN from the fire. In contrast to previous findings by other studies of convective clouds, we found that fire CCN have a negative effect on the convection dynamics because they give rise to a delay in the freezing of cloud droplets. Even in a simulation without fire CCN, there is no precipitation formation within the updraft region of the pyroCb. Enhancement of convection by aerosols as reported from studies of other cases of convection is therefore not found in our study.

  14. Chemicals from biomass - BioForest

    Energy Technology Data Exchange (ETDEWEB)

    Heiningen, A. van (Aalto University School of Chemical Technology, Espoo (Finland), Dept. of Forest Products Technology), e-mail: adriaan.vanheiningen@aalto.fi; Granstroem, T. (Aalto University School of Chemical Technology, Espoo (Finland), Dept.of Biotechnology and Chemical Technology), e-mail: tom.granstrom@aalto.fi

    2011-11-15

    The objective of the BioForest project is to develop the science and technology of a series of integrated processing steps which economically convert mixed hardwood and softwood biomass and recycled fibers into commodity chemicals at an existing forest products complex which also produces wood and/or pulp and paper. The commodity products will be produced from the biomass carbohydrates using a novel biomass fractionation process, a modified ABE (Acetone- Butanol-Ethanol) fermentation process, and a novel continuous solvent recovery method from the fermentation liquid. The mixture of solvents produced by the modified ABE process consists of isopropanol, butanol and ethanol. The key technological barriers which have been accomplished in the Bioforest project are following: 1. Fundamental understanding of the kinetics of delignification, hemicellulose dissolution and cellulose degradation during SEW fractionation of softwood and hardwood 2. Optimization of SEW fractionation of softwood biomass with a total treatment time as short as 30 minutes 3. Simultaneous SEW fractionation of hardwood and softwood biomass 4. Production of a high concentration (> 100 g/L) hemicellulose monosugar solution from SEW spent fractionation liquor at a sugar yield larger than 85% by multistep conditioning 5. Construction of E.coli strain harboring isopropanol dehydrogenase gene capable of acetone conversion to isopropanol 6. Successful fermentation of the conditioned hemicellulose monosugar solution to ABE (Acetone, Butanol, Ethanol) solvents using advanced column technology (patent pending) or semi-solid pulp fermentations with the volumetric productivities of 5.5 and 13.5 g/L h respectively. (orig.)

  15. Forest Biomass for Climate Change Mitigation

    DEFF Research Database (Denmark)

    Nielsen, Anders Tærø

    on southern Scandinavian sites, managed under different systems both in agriculture and in forests. In addition, the objective is to assess the potential of the poplar plantations to mitigate climate change by using poplar biomass for substitution of fossil fuels in comparison to a traditional product......Awareness of elevated CO2 levels in the atmosphere and resulting climate change has increased focus on renewable energy sources during recent decades. Biomass for energy has been predicted to have the greatest potential for CO2 reductions in the short term and the IPCC assumes that the use...

  16. Predicting tree heights for biomass estimates in tropical forests

    Directory of Open Access Journals (Sweden)

    Q. Molto

    2013-05-01

    Full Text Available The recent development of REDD+ mechanisms require reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even if tree height is a crucial variable to compute the above-ground forest biomass, tree heights are rarely measured in large-scale forest census because it requires consequent extra-effort. Tree height have thus to be predicted thanks to height models. Height and diameter of all trees above 10 cm of diameter were measured in thirty-three half-ha plots and nine one-ha plots throughout the northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis–Menten shape was the most appropriate for the tree biomass prediction. Model parameters values were significantly different from one forest plot to another and neglecting these differences would lead to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of the plot-to-plot variations of the height model parameters to affect the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The above-ground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrates the feasibility and the importance of height modeling in tropical forest for carbon mapping. Tree height is definitely an important variable for AGB estimations. When the tree heights are not measured in an inventory, they can be predicted with a height-diameter model. This model can account for plot-to plot variations in height-diameter relationship thank to variables describing the plots. The variables describing the stand structure of the plots are efficient for

  17. Estimation of above ground biomass in boreal forest using ground-based Lidar

    Science.gov (United States)

    Taheriazad, L.; Moghadas, H.; Sanchez-Azofeifa, A.

    2017-05-01

    Assessing above ground biomass of forest is important for carbon storage monitoring in boreal forest. In this study, a new model is developed to estimate the above ground biomass using ground based Lidar data. 21 trees were measured and scanned across the plot area study in boreal forests of Alberta, Canada. The study area was scanned in the summer season 2014 to quantify the green biomass. The average of total crown biomass and green biomass in this study was 377 kg (standard deviation, S.D. = 243 kg) and 6.42 kg (S.D. = 2.69 m), respectively.

  18. Modeling integrated biomass gasification business concepts

    Science.gov (United States)

    Peter J. Ince; Ted Bilek; Mark A. Dietenberger

    2011-01-01

    Biomass gasification is an approach to producing energy and/or biofuels that could be integrated into existing forest product production facilities, particularly at pulp mills. Existing process heat and power loads tend to favor integration at existing pulp mills. This paper describes a generic modeling system for evaluating integrated biomass gasification business...

  19. Chemicals from biomass - BioForest

    Energy Technology Data Exchange (ETDEWEB)

    van Heiningen, A. (Aalto Univ., Espoo (Finland). Dept. of Forest products Technology), Email: adriaan.vanheiningen@tkk.fi; Granstroem, T. (Aalto Univ. , Espoo (Finland). Dept. of Biotechnology and Chemical Technology), Email: tom.granstrom@tkk.fi

    2010-10-15

    The objective of the BioForest project is to develop the science and technology of a series of integrated processing steps which economically convert mixed hardwood and softwood biomass and recycled fibers into commodity chemicals at an existing forest products complex which produces wood and/or pulp and paper. The commodity products will be produced from the biomass carbohydrates using a novel biomass fractionation process, a modified ABE (Acetone-Butanol-Ethanol) fermentation process, and a novel continuous solvent recovery method from the fermentation liquid. The mixture of solvents produced by the modified ABE process consists of isopropanol, butanol and ethanol. The key technological barriers which will be addressed in the present project are: 1. Production of a high concentration (> 100 g/L) mono sugar solution without costly pretreatment and enzymatic hydrolysis of the biomass, 2. Generation of the modified ABE solvent mixture at high concentration (> 20 g/L) and a fermentation time of 40?60 hours or 4 g/L h productivity, 3. Continuous removal of the ABE solvent mixture from the fermentation broth to overcome the high concentration toxicity of butanol to the Clostridia fermentation strain, and 4. Pretreatment and utilization of recycled fibers for fermentation to ABE solvents. (orig.)

  20. Chemical from biomass - BioForest

    Energy Technology Data Exchange (ETDEWEB)

    Van Heiningen, A. (Helsinki Univ. of Technology, Dept. of Forest Products Technology, Espoo (Finland)), email: adriaan.vanheiningen@tkk.fi; Granstroem, T. (Helsinki Univ. of Technology, Dept. of Biotechnology and Chemical Technology, Espoo (Finland)), email: tom.granstrom@tkk.fi

    2009-10-15

    The objective of the BioForest project is to develop the science and technology of a series of integrated processing steps which economically convert mixed hardwood and softwood biomass and recycled fibers into commodity chemicals at an existing forest products complex which produces wood and/or pulp and paper. The commodity products will be produced from the biomass carbohydrates using a novel biomass fractionation process, a modified ABE (Acetone-Butanol-Ethanol) fermentation process, and a novel continuous solvent recovery method from the fermentation liquid. The mixture of solvents produced by the modified ABE-process consists of isopropanol, butanol and ethanol. The key technological barriers which will be addressed in the present project are: (1) Production of a high concentration (> 100 g/L) mono sugar solution without costly pretreatment and enzymatic hydrolysis of the biomass, (2) Generation of the modified ABE solvent mixture at high concentration (>20 g/L) and a fermentation time of 40-60 hours, Continuous removal of the ABE solvent mixture from the fermentation broth to overcome the high concentration toxicity of butanol to the Clostridia fermentation strain, and (4) Pretreatment and utilization of recycled fibers for fermentation to ABE solvents. (orig.)

  1. Monitoring and Modeling of Large-Scale Pattern of Forest Height and Biomass based on the Metabolic Scaling Theory and Water-Energy Balance Equation

    Science.gov (United States)

    CHOI, S.; Myneni, R. B.; Knyazikhin, Y.; Park, T.

    2015-12-01

    This study applies the metabolic scaling theory (MST) and water-energy balance equation (PM: Penman-Monteith) to monitor and model the large-scale pattern of forest height and biomass. The WBE and PM theories grant a generalized mechanistic understanding of relationships between the forest structure and multiple geospatial predictors including topography and climatic variables. We successfully expanded the average trend and predictions of the MST and PM by including eco-regional and plant functional type variations. Our model now accounts for plant interaction, self-competition and disturbance effects to alleviate known limitations of the MST. The topographic heterogeneity and climate seasonality are additionally incorporated in the model predictions. A simple and clear mechanistic understanding in the model is promising for prognostic applications in contrast to conventional black-box approaches. This study provides baseline maps (circa 2005; 1-km2 grids) of the maximum forest canopy heights and aboveground biomass over the continental USA. Their future projections are also delivered using various climate scenarios. The NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset is used in this task.

  2. A dataset of forest biomass structure for Eurasia

    Science.gov (United States)

    Schepaschenko, Dmitry; Shvidenko, Anatoly; Usoltsev, Vladimir; Lakyda, Petro; Luo, Yunjian; Vasylyshyn, Roman; Lakyda, Ivan; Myklush, Yuriy; See, Linda; McCallum, Ian; Fritz, Steffen; Kraxner, Florian; Obersteiner, Michael

    2017-05-01

    The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

  3. Potentials for forest woody biomass production in Serbia

    Directory of Open Access Journals (Sweden)

    Vasiljević Aleksandar Lj.

    2015-01-01

    Full Text Available The paper presents the analysis of possible potentials for the production of forest biomass in Serbia taking into consideration the condition of forests, present organizational and technical capacities as well as the needs and situation on the firewood market. Starting point for the estimation of production potentials for forest biomass is the condition of forests which is analyzed based on the available planning documents on all levels. Potentials for biomass production and use refer to initial periods in the production and use of forest biomass in Serbia.

  4. Climate-related large-scale variation in forest carbon turnover rate - Evaluating global vegetation models using remote sensing products of biomass and NPP

    Science.gov (United States)

    Thurner, Martin; Beer, Christian; Carvalhais, Nuno; Ciais, Philippe; Forkel, Matthias; Friend, Andrew; Ito, Akihiko; Kleidon, Axel; Lomas, Mark; Quegan, Shaun; Tito Rademacher, Tim; Santoro, Maurizio; Schaphoff, Sibyll; Schmullius, Christiane; Tum, Markus; Wiltshire, Andy

    2017-04-01

    Vegetation carbon turnover, in terms of its spatial variation and its response to climate change, is one of the most important, but also most uncertain carbon fluxes in terrestrial ecosystems. Its measurement is hardly possible by inventory studies alone, due to several reasons: First, vegetation carbon turnover involves a variety of processes, including litterfall, background mortality, and mortality by all kinds of disturbances, affecting single biomass compartments, individual trees or even whole ecosystems. Second, these processes act on very different timescales, involving short-term extreme events and long-term responses, and spatial scales, from local extremes to global impacts. In order to capture this variety of processes, spatial scales and timescales, here we estimate forest carbon turnover rate from novel remote sensing products of NPP and biomass. These products allow investigating the spatial variation in long-term mean turnover rate at 0.5° resolution across northern boreal and temperate forest ecosystems and its relation to climate variables. We observe an increase in turnover rate with colder and longer winters in boreal forests, whereas in temperate forests the spatial gradients in turnover rate are related to the length of both warm and dry periods. Thus, we hypothesize that the spatial variation in turnover rate can be explained by direct and indirect frost damage effects on mortality in boreal forests but drought and insect outbreaks in temperate forests. An evaluation of a set of global vegetation models (GVMs) participating in the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP; including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, VISIT) shows that those models are able to reproduce the observation-based spatial relationships only to a limited extent. Deviations from the observation-based turnover rates can be mostly attributed to severe overestimations of biomass, however also important differences in the simulated spatial

  5. Variation of biomass and carbon pools with forest type in temperate forests of Kashmir Himalaya, India.

    Science.gov (United States)

    Dar, Javid Ahmad; Sundarapandian, Somaiah

    2015-02-01

    influenced by vegetation type, stand structure, management history, and altitude. Our results reveal that a higher percentage (63 %) of C is stored in biomass and less in soil in these temperate forests except at the higher elevation broad-leaved BU forest. Results from this study will enhance our ability to evaluate the role of these forests in regional and global C cycles and have great implications for planning strategies for conservation. The study provides important data for developing and validating C cycling models for temperate forests.

  6. Forest biomass supply for bioenergy in the southeast: Evaluating assessment scale

    Science.gov (United States)

    Christopher S. Galik; Robert C. Abt

    2012-01-01

    This study evaluates the potential impacts of expanded forest biomass use in the Southeast from present year through 2036, focusing on the forest supply, industrial, and GHG emissions implications of maximizing biomass co-firing with coal. We model demand scenarios at the state, subregional, and regional levels, and assess the influence of study scale on the observed...

  7. 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.

  8. Spatial variation and prediction of forest biomass in a heterogeneous landscape

    Institute of Scientific and Technical Information of China (English)

    S.Lamsal; D.M.Rizzo; R.K.Meentemeyer

    2012-01-01

    Large areas assessments of forest biomass distribution are a challenge in heterogeneous landscapes,where variations in tree growth and species composition occur over short distances.In this study,we use statistical and geospatial modeling on densely sampled forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur,California.We estimated biomass in 280 forest plots (one plot per 2.85 km2) and measured an array of ecological (vegetation community type,distance to edge,amount of surrounding non-forest vegetation,soil properties,fire history) and physiographic drivers (elevation,potential soil moisture and solar radiation,proximity to the coast) of tree growth at each plot location.Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 km.Regression tree (RT) models showed that both physiographic and ecological factors influenced biomass distribution.Across randomly selected sample densities (sample size 112 to 280),ecological effects of vegetation community type and distance to forest edge,and physiographic effects of elevation,potentialsoil moisture and solar radiation were the most consistent predictors of biomass.Topographic moisture index and potential solar radiation had a positive effect on biomass,indicating the importance of topographicallymediated energy and moisture on plant growth and biomass accumulation.RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals.Regression kriging model,developed from RT combined with kriging of regression residuals,was used to map biomass across the Big Sur.This study demonstrates how statistical and geospatial modeling can be used to discriminate the relative importance of physiographic and ecologic effects on forest biomass and develop

  9. Biomass Scenario Model

    Energy Technology Data Exchange (ETDEWEB)

    2015-09-01

    The Biomass Scenario Model (BSM) is a unique, carefully validated, state-of-the-art dynamic model of the domestic biofuels supply chain which explicitly focuses on policy issues, their feasibility, and potential side effects. It integrates resource availability, physical/technological/economic constraints, behavior, and policy. The model uses a system dynamics simulation (not optimization) to model dynamic interactions across the supply chain.

  10. Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

    Science.gov (United States)

    Fatoyinbo, Temilola E.

    2010-01-01

    Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation

  11. (abstract) Sensitivity to Forest Biomass Based on Analysis of Scattering Mechanism

    Science.gov (United States)

    Way, JoBea; Bachman, Jennifer E.; Paige, David A.

    1993-01-01

    The estimation of forest biomass on a global scale is an important input to global climate and carbon cycle models. Remote sensing using synthetic aperture radar offers a means to obtain such a data set. Although it has been clear for some time that radar signals penetrate forest canopies, only recently has it been demonstrated that these signals are indeed sensitive to biomass. Inasmuch as the majority of a forest's biomass is in the trunks, it is important that the radar is sensing the trunk biomass as opposed to the branch or leaf biomass. In this study we use polarimetric AIRSAR P- and L-band data from a variety of forests to determine if the radar penetrates to the trunk by examining the scattering mechanism as determined using van Zyl's scattering interaction model, and the levels at which saturation occurs with respect to sensitivity of radar backscatter to total biomass. In particular, the added sensitivity of P-band relative to L-band is addressed. Results using data from the Duke Forest in North Carolina, the Bonanza Creek Experimental Forest in Alaska, Shasta Forest in California, the Black Forest in Germany, the temporate/boreal transition forests in northern Michigan, and coastal forests along the Oregon Transect will be presented.

  12. 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.

  13. Relationships among the Stem,Aboveground and Total Biomass across Chinese Forests

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Forest biomass plays a key role in the global carbon cycle.In the present study,a general allometric model was derived to predict the relationships among the stem biomass Ms,aboveground biomass MA and total biomass Mr.based on previously developed scaling relationships for leaf,stem and root standing biomass.The model predicted complex scaling exponents for MT and/or MA with respect to MS.Because annual biomass accumulation in the stem,root and branch far exceeded the annual increase in standing leaf biomass,we can predict that MT∝MA∝Ms as a simple result of the model.Although slight variations existed in different phyletic affiliations(I.e.conifers versus angiosperms),empirical results using Model Type Ⅱ (reduced major axis) regression supported the model's predictions.The predictive formulas among stem,aboveground and total biomass were obtained using Model Type Ⅰ(ordinary least squares) regression to estimate forest biomass.Given the low mean percentage prediction errors for aboveground(and total biomass) based on the stem biomass.the results provided a reasonable method to estimate the biomass of forests at the individual level.which was insensitive to the variation in local environmental conditions (e.g.precipitation,tempereture,etc.).

  14. Global patterns and predictions of seafloor biomass using random forests.

    Directory of Open Access Journals (Sweden)

    Chih-Lin Wei

    Full Text Available A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM, seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes. Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.

  15. Natural Forest Biomass Estimation Based on Plantation Information Using PALSAR Data

    Science.gov (United States)

    Avtar, Ram; Suzuki, Rikie; Sawada, Haruo

    2014-01-01

    Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ0) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ0 showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ0 were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE  = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal. PMID:24465908

  16. Translating Forest Change to Carbon Emissions and Removals By Linking Disturbance Products, Biomass Maps, and Carbon Cycle Modeling in a Comprehensive Carbon Monitoring Framework for the Conterminous US Forests

    Science.gov (United States)

    Williams, C. A.; Gu, H.

    2016-12-01

    Protecting forest carbon stores and uptake is central to national and international policies aimed at mitigating climate change. The success of such polices relies on high quality, accurate reporting (Tier 3) that earns the greatest financial value of carbon credits and hence incentivizes forest conservation and protection. Methods for Tier 3 Measuring, Reporting, and Verification (MRV) are still in development, generally involving some combination of direct remote sensing, ground based inventorying, and computer modeling, but have tended to emphasize assessments of live aboveground carbon stocks with a less clear connection to the real target of MRV which is carbon emissions and removals. Most existing methods are also ambiguous as to the mechanisms that underlie carbon accumulation, and any have limited capacity for forecasting carbon dynamics over time. This paper reports on the design and implementation of a new method for Tier 3 MRV, decision support, and forecasting that is being applied to assess forest carbon dynamics across the conterminous US. The method involves parameterization of a carbon cycle model (CASA) to match yield data from the US forest inventory (FIA). A range of disturbance types and severities are imposed in the model to estimate resulting carbon emissions, carbon uptake, and carbon stock changes post-disturbance. Resulting trajectories are then applied to landscapes at the 30-m pixel level based on two remote-sensing based data products. One documents the year, type, and severity of disturbance in recent decades. The second documents aboveground biomass which is used to estimate time since disturbance and associated carbon fluxes and stocks. Results will highlight high-resolution (30 m) annual carbon stocks and fluxes from 1990 to 2010 for select regions of interest across the US. Spatial analyses reveal regional patterns in US forest carbon stocks and fluxes as they respond to forest types, climate, and disturbances. Temporal analyses

  17. Estimating forest aboveground biomass using HJ-1 Satellite CCD and ICESat GLAS waveform data

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance.Forest aboveground biomass(AGB) is an important component in the land surface carbon cycle.In this study,using forest inventory data and forest distribution data,the AGB was estimated for forest in Daxinganlin in northeastern China by combining charge-coupled device(CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast(HJ-1) and Geoscience Laser Altimeter System(GLAS) waveform data from the Ice,Cloud and land Elevation Satellite(ICESat).The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing(CQ) Forest Center,which was calculated from forest inventory data.The resulted statistical regression models have a R2=0.68 for conifer and R2=0.71 for broadleaf forests.These models were used to estimate biomass for all GLAS footprints of forest located in the study area.All GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models(R2=0.55 and R2=0.52 for needle and broadleaf respectively).Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 data.Biomass data obtained from forest inventory data of the Zhuanglin(ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data(R2=0.71).About 80% of biomass samples had an error less than 20 t ha-1,and the mean error of all validation samples is 5.74 t ha-1.The pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this area.It was found that HJ-1 wide-swath data and GLAS waveform data can be combined to

  18. National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China

    Directory of Open Access Journals (Sweden)

    Hong Chi

    2015-05-01

    Full Text Available Forest aboveground biomass (AGB was mapped throughout China using large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat, Moderate Resolution Imaging Spectro-radiometer (MODIS imagery and forest inventory data. The entire land of China was divided into seven zones according to the geographic characteristics of the forests. The forest AGB prediction models were separately developed for different forest types in each of the seven forest zones at GLAS footprint level from GLAS waveform parameters and biomass derived from height and diameter at breast height (DBH field observation. Some waveform parameters used in the prediction models were able to reduce the effects of slope on biomass estimation. The models of GLAS-based biomass estimates were developed by using GLAS footprints with slopes less than 20° and slopes ≥ 20°, respectively. Then, all GLAS footprint biomass and MODIS data were used to establish Random Forest regression models for extrapolating footprint AGB to a nationwide scale. The total amount of estimated AGB in Chinese forests around 2006 was about 12,622 Mt vs. 12,617 Mt derived from the seventh national forest resource inventory data. Nearly half of all provinces showed a relative error (% of less than 20%, and 80% of total provinces had relative errors less than 50%.

  19. Regional biomass stores and dynamics in forests of coastal Alaska

    Science.gov (United States)

    Mikhaill A. Yatskov; Mark E. Harmon; Olga N. Krankina; Tara M. Barrett; Kevin R. Dobelbower; Andrew N. Gray; Becky Fasth; Lori Trummer; Toni L. Hoyman; Chana M. Dudoit

    2015-01-01

    Coastal Alaska is a vast forested region (6.2 million ha) with the potential to store large amounts of carbon in live and dead biomass thus influencing continental and global carbon dynamics. The main objectives of this study were to assess regional biomass stores, examine the biomass partitioning between live and dead pools, and evaluate the effect of disturbance on...

  20. 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...

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

    DEFF Research Database (Denmark)

    Slik, J.W.Ferry; Paoli, Gary; McGuire, Krista

    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...

  2. Modernization of forest biomass operations research : powered by the EU

    Energy Technology Data Exchange (ETDEWEB)

    Roser, D. [Finnish Forest Research Inst., Joensuu (Finland)

    2010-07-01

    The European Union (EU) COST framework to support the modernization of forest biomass operations research in Europe was discussed along with the commitment to strengthen Europe's role as a world leader in forest biomass energy production and use. Initiated in 2009, the COST action aims to harmonize forest energy terminologies, methodologies, and biomass availability calculations by supporting technology transfer and research capacity related to the biomass procurement chain and sustainable forest management practices. The action will develop best practice guidelines, standard measurement and sampling methods, and a format for cost calculations. The action will allow scientists from Europe as well as other countries to communicate and exchange knowledge of topics related to the biomass industry. An electronic peer-reviewed online journal will also be established to improve the availability of research to all stakeholders.

  3. Monitoring coniferous forest biomass change using a Landsat trajectory-based approach

    Science.gov (United States)

    Magdalena Main-Knorn; Warren B. Cohen; Robert E. Kennedy; Wojciech Grodzki; Dirk Pflugmacher; Patrick Griffiths; Patrick Hostert

    2013-01-01

    Forest biomass is a major store of carbon and thus plays an important role in the regional and global carbon cycle. Accurate forest carbon sequestration assessment requires estimation of both forest biomass and forest biomass dynamics over time. Forest dynamics are characterized by disturbances and recovery, key processes affecting site productivity and the forest...

  4. Modeling below-ground biomass to improve sustainable management of Actaea racemosa, a globally important medicinal forest product

    Science.gov (United States)

    James L. Chamberlain; Gabrielle Ness; Christine J. Small; Simon J. Bonner; Elizabeth B. Hiebert

    2013-01-01

    Non-timber forest products, particularly herbaceous understory plants, support a multi-billion dollar industry and are extracted from forests worldwide for their therapeutic value. Tens of thousands of kilograms of rhizomes and roots of Actaea racemosa L., a native Appalachian forest perennial, are harvested every year and used for the treatment of...

  5. Biomass distribution patterns of ecotones between forest and swamp in Changbai Mountain

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper studied the biomass distribution patterns of Larix olgensis/swamp ecotones and Betula platyphlla/swamp ecotones in Changbai Mountain so as to provide theory foundation for the management of these nature resources, by setting up sample belts, investigating initial data along the environmental gradients change, and establishing regression models. By means of regression models, the biomass of communities, layers, tree species and organs was calculated. In this system, it was found that the community biomass increased gradually along the environmental gradients change from swamp to forest in Changbai Mountain. Furthermore, the ecotoneal biomass distributed mainly over tree layer. The tree biomass distributed mainly in two or three dominate tree species.

  6. Use of forest inventories and geographic information systems to estimate biomass density of tropical forests: Application to tropical Africa.

    Science.gov (United States)

    Brown, S; Gaston, G

    1995-01-01

    One of the most important databases needed for estimating emissions of carbon dioxide resulting from changes in the cover, use, and management of tropical forests is the total quantity of biomass per unit area, referred to as biomass density. Forest inventories have been shown to be valuable sources of data for estimating biomass density, but inventories for the tropics are few in number and their quality is poor. This lack of reliable data has been overcome by use of a promising approach that produces geographically referenced estimates by modeling in a geographic information system (GIS). This approach has been used to produce geographically referenced, spatial distributions of potential and actual (circa 1980) aboveground biomass density of all forests types in tropical Africa. Potential and actual biomass density estimates ranged from 33 to 412 Mg ha(-1) (10(6)g ha(-1)) and 20 to 299 Mg ha(-1), respectively, for very dry lowland to moist lowland forests and from 78 to 197 Mg ha(-1) and 37 to 105 Mg ha(-1), respectively, for montane-seasonal to montane-moist forests. Of the 37 countries included in this study, more than half (51%) contained forests that had less than 60% of their potential biomass. Actual biomass density for forest vegetation was lowest in Botswana, Niger, Somalia, and Zimbabwe (about 10 to 15 Mg ha(-1)). Highest estimates for actual biomass density were found in Congo, Equatorial Guinea, Gabon, and Liberia (305 to 344 Mg ha(-1)). Results from this research effort can contribute to reducing uncertainty in the inventory of country-level emission by providing consistent estimates of biomass density at subnational scales that can be used with other similarly scaled databases on change in land cover and use.

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

    Science.gov (United States)

    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.

  8. 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

  9. 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.

  10. Forest biomass supply logistics for a power plant using the discrete-event simulation approach

    Energy Technology Data Exchange (ETDEWEB)

    Mobini, Mahdi [Industrial Engineering Group, Department of Wood Science, University of British Columbia, 2943-2424 Main Mall, Vancouver, BC V6T-1Z4 (Canada); Sowlati, Taraneh [Department of Wood Science, University of British Columbia, 2931-2424 Main Mall, Vancouver, BC V6T-1Z4 (Canada); Sokhansanj, Shahab [Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall, Vancouver, BC V6T 1Z3 (Canada); Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

    2011-04-15

    This study investigates the logistics of supplying forest biomass to a potential power plant. Due to the complexities in such a supply logistics system, a simulation model based on the framework of Integrated Biomass Supply Analysis and Logistics (IBSAL) is developed in this study to evaluate the cost of delivered forest biomass, the equilibrium moisture content, and carbon emissions from the logistics operations. The model is applied to a proposed case of 300 MW power plant in Quesnel, BC, Canada. The results show that the biomass demand of the power plant would not be met every year. The weighted average cost of delivered biomass to the gate of the power plant is about C$ 90 per dry tonne. Estimates of equilibrium moisture content of delivered biomass and CO{sub 2} emissions resulted from the processes are also provided. (author)

  11. Forest biomass supply logistics for a power plant using the discrete-event simulation approach

    Energy Technology Data Exchange (ETDEWEB)

    Mobini, Mahdi [University of British Columbia, Vancouver; Sowlati, T. [University of British Columbia, Vancouver; Sokhansanj, Shahabaddine [ORNL

    2011-04-01

    This study investigates the logistics of supplying forest biomass to a potential power plant. Due to the complexities in such a supply logistics system, a simulation model based on the framework of Integrated Biomass Supply Analysis and Logistics (IBSAL) is developed in this study to evaluate the cost of delivered forest biomass, the equilibrium moisture content, and carbon emissions from the logistics operations. The model is applied to a proposed case of 300 MW power plant in Quesnel, BC, Canada. The results show that the biomass demand of the power plant would not be met every year. The weighted average cost of delivered biomass to the gate of the power plant is about C$ 90 per dry tonne. Estimates of equilibrium moisture content of delivered biomass and CO2 emissions resulted from the processes are also provided.

  12. Forest biomass carbon stocks and variation in Tibet's carbon-dense forests from 2001 to 2050.

    Science.gov (United States)

    Sun, Xiangyang; Wang, Genxu; Huang, Mei; Chang, Ruiying; Ran, Fei

    2016-10-05

    Tibet's forests, in contrast to China's other forests, are characterized by primary forests, high carbon (C) density and less anthropogenic disturbance, and they function as an important carbon pool in China. Using the biomass C density data from 413 forest inventory sites and a spatial forest age map, we developed an allometric equation for the forest biomass C density and forest age to assess the spatial biomass C stocks and variation in Tibet's forests from 2001 to 2050. The results indicated that the forest biomass C stock would increase from 831.1 Tg C in 2001 to 969.4 Tg C in 2050, with a net C gain of 3.6 Tg C yr(-1) between 2001 and 2010 and a decrease of 1.9 Tg C yr(-1) between 2040 and 2050. Carbon tends to allocate more in the roots of fir forests and less in the roots of spruce and pine forests with increasing stand age. The increase of the biomass carbon pool does not promote significant augmentation of the soil carbon pool. Our findings suggest that Tibet's mature forests will remain a persistent C sink until 2050. However, afforestation or reforestation, especially with the larger carbon sink potential forest types, such as fir and spruce, should be carried out to maintain the high C sink capacity.

  13. The Biomass mission: a step forward in quantifying forest biomass and structure

    Science.gov (United States)

    LE Toan, T.

    2015-12-01

    The primary aim of the ESA BIOMASS mission is to determine, for the first time and in a consistent manner, the global distribution of above-ground forest biomass (AGB) in order to provide greatly improved quantification of the size and distribution of the terrestrial carbon pool, and improved estimates of terrestrial carbon fluxes. Specifically, BIOMASS will measure forest carbon stock, as well as forest height, from data provided by a single satellite giving a biomass map covering tropical, temperate and boreal forests at a resolution of around 200 m every 6 months throughout the five years of the mission. BIOMASS will use a long wavelength SAR (P-band) providing three mutually supporting measurement techniques, namely polarimetric SAR (PolSAR), polarimetric interferometric SAR (PolInSAR) and tomographic SAR (TomoSAR). The combination of these techniques will significantly reduce the uncertainties in biomass retrievals by yielding complementary information on biomass properties. Horizontal mapping: For a forest canopy, the P-band radar waves penetrate deep into the canopy, and their interaction with the structure of the forest will be exploited to map above ground biomass (AGB), as demonstrated from airborne data for temperate, boreal forests and tropical forest. Height mapping: By repeat revisits to the same location, the PolInSAR measurements will be used to estimate the height of scattering in the forest canopy. The long wavelength used by BIOMASS is crucial for the temporal coherence to be preserved over much longer timescales than at L-band, for example. 3D mapping: The P-band frequency used by BIOMASS is low enough to ensure penetration through the entire canopy, even in dense tropical forests. As a consequence, resolution of the vertical structure of the forest will be possible using tomographic methods from the multi-baseline acquisitions. This is the concept of SAR tomography, which will be implemented in the BIOMASS mission. The improvement in the

  14. 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

  15. The relative contributions of forest growth and areal expansion to forest biomass carbon sinks in China

    Directory of Open Access Journals (Sweden)

    P. Li

    2015-06-01

    Full Text Available Forests play a leading role in regional and global terrestrial carbon (C cycles. Changes in C sequestration within forests can be attributed to areal expansion (increase in forest area and forest growth (increase in biomass density. Detailed assessment of the relative contributions of areal expansion and forest growth to C sinks is crucial to reveal the mechanisms that control forest C sinks and is helpful for developing sustainable forest management policies in the face of climate change. Using the Forest Identity concept and forest inventory data, this study quantified the spatial and temporal changes in the relative contributions of forest areal expansion and increased biomass growth to China's forest C sinks from 1977 to 2008. Over the last 30 years, the areal expansion of forests was a larger contributor to C sinks than forest growth for all forests and planted forests in China (74.6 vs. 25.4 % for all forests, and 62.4 vs. 37.8 % for plantations. However, for natural forests, forest growth made a larger contribution than areal expansion (60.4 vs. 39.6 %. The relative contribution of forest growth of planted forests showed an increasing trend from an initial 25.3 to 61.0 % in the later period of 1998 to 2003, but for natural forests, the relative contributions were variable without clear trends owing to the drastic changes in forest area and biomass density over the last 30 years. Our findings suggest that afforestation can continue to increase the C sink of China's forests in the future subject to persistently-increasing forest growth after establishment of plantation.

  16. Tree species richness affecting fine root biomass in European forests

    Science.gov (United States)

    Finér, Leena; Domisch, Timo; Vesterdal, Lars; Dawud, Seid M.; Raulund-Rasmussen, Karsten

    2016-04-01

    Fine roots are an important factor in the forest carbon cycle, contributing significantly to below-ground biomass and soil carbon storage. Therefore it is essential to understand the role of the forest structure, indicated by tree species diversity in controlling below-ground biomass and managing the carbon pools of forest soils. We studied how tree species richness would affect fine root biomass and its distribution in the soil profile and biomass above- and below-ground allocation patterns of different tree species. Our main hypothesis was that increasing tree species richness would lead to below-ground niche differentiation and more efficient soil exploitation by the roots, resulting in a higher fine root biomass in the soil. We sampled fine roots of trees and understorey vegetation in six European forest types in Finland, Poland, Germany, Romania, Italy and Spain, representing boreal, temperate and Mediterranean forests, established within the FunDivEUROPE project for studying the effects of tree species diversity on forest functioning. After determining fine root biomasses, we identified the percentages of different tree species in the fine root samples using the near infrared reflectance spectroscopy (NIRS) method. Opposite to our hypothesis we did not find any general positive relationship between tree species richness and fine root biomass. A weak positive response found in Italy and Spain seemed to be related to dry environmental conditions during Mediterranean summers. At the Polish site where we could sample deeper soil layers (down to 40 cm), we found more tree fine roots in the deeper layers under species-rich forests, as compared to the monocultures, indicating the ability of trees to explore more resources and to increase soil carbon stocks. Tree species richness did not affect biomass allocation patterns between above- and below-ground parts of the trees.

  17. Preliminary results of the global forest biomass survey

    Science.gov (United States)

    S. Healey; E. Lindquist

    2014-01-01

    Many countries do not yet have well-established national forest inventories, and among those that do, significant methodological differences exist, particularly in the estimation of standing forest biomass. Global space-based LiDAR (Light Detection and Ranging) from NASA’s now-completed ICESat mission provided consistent, high-quality measures of canopy height and...

  18. Sustainable utilisation of forest biomass for energy - Possibilities and problems

    DEFF Research Database (Denmark)

    Stupak, I.; Asikainen, A.; Jonsell, M.;

    2007-01-01

    The substitution of biomass for fossil fuels in energy consumption is a measure to mitigate global warming, as well as having other advantages. Political action plans for increased use exist at both European and national levels. This paper briefly reviews the contents of recommendations. guidelines....... and other synthesis publications on Sustainable use of forest biomass for energy. Topics are listed and an overview of advantages. disadvantages, and trade-offs between them is given, from the viewpoint of society in general and the forestry or the Nordic and Baltic countries, the paper also identifies...... the extent to which wood for energy is and energy sectors in particular. F included in forest legislation and forest certification standards under the "Programme for the Endorsement of Forest Certification" (PEFC) and the "Forest Stewardship Council" (FSC) schemes. Energy and forest policies at EU...

  19. Nontraditional Use of Biomass at Certified Forest Management Units: Forest Biomass for Energy Production and Carbon Emissions Reduction in Indonesia

    Directory of Open Access Journals (Sweden)

    Asep S. Suntana

    2012-01-01

    Full Text Available Biomass conversion technologies that produce energy and reduce carbon emissions have become more feasible to develop. This paper analyzes the potential of converting biomass into biomethanol at forest management units experiencing three forest management practices (community-based forest management (CBFM, plantation forest (PF, and natural production forest (NPF. Dry aboveground biomass collected varied considerably: 0.26–2.16 Mg/ha/year (CBFM, 8.08–8.35 Mg/ha/year (NPF, and 36.48–63.55 Mg/ha/year (PF. If 5% of the biomass was shifted to produce biomethanol for electricity production, the NPF and PF could provide continuous power to 138 and 2,762 households, respectively. Dedicating 5% of the biomass was not a viable option from one CBFM unit. However, if all biomasses were converted, the CBFM could provide electricity to 19–27 households. If 100% biomass from two selected PF was dedicated to biomethanol production: (1 52,200–72,600 households could be provided electricity for one year; (2 142–285% of the electricity demand in Jambi province could be satisfied; (3 all gasoline consumed in Jambi, in 2009, would be replaced. The net carbon emissions avoided could vary from 323 to 8,503 Mg when biomethanol was substituted for the natural gas methanol in fuel cells and from 294 to 7,730 Mg when it was used as a gasoline substitute.

  20. Mapping Forest Biomass Using Remote Sensing and National Forest Inventory in China

    Directory of Open Access Journals (Sweden)

    Ling Du

    2014-06-01

    Full Text Available Quantifying the spatial pattern of large-scale forest biomass can provide a general picture of the carbon stocks within a region and is of great scientific and political importance. The combination of the advantages of remote sensing data and field survey data can reduce uncertainty as well as demonstrate the spatial distribution of forest biomass. In this study, the seventh national forest inventory statistics (for the period 2004–2008 and the spatially explicit MODIS Land Cover Type product (MCD12C1 were used together to quantitatively estimate the spatially-explicit distribution of forest biomass in China (with a resolution of 0.05°, ~5600 m. Our study demonstrated that the calibrated forest cover proportion maps allow proportionate downscaling of regional forest biomass statistics to forest cover pixels to produce a relatively fine-resolution biomass map. The total stock of forest biomass in China was 11.9 Pg with an average of 76.3 Mg ha−1 during the study period; the high values were located in mountain ranges in northeast, southwest and southeast China and were strongly correlated with forest age and forest density.

  1. Forest biomass density, utilization and production dynamics in a western Himalayan watershed

    Institute of Scientific and Technical Information of China (English)

    Rakesh Kumar Sharma; Prem Lall Sankhayan; Ole Hofstad

    2008-01-01

    There is enough evidence to show that the forest biomass has decreased significantly in the Indian Himalayan state of Himachal Pradesh. The government has responded through restrictive measures to check this decline. Using tree biomass as proxy for degradation, we assessed the current state of biomass within dominant land use types and examined its implications for sustainability. The highest above-ground mean tree biomass density of 1158 t·ha-1 was recorded for the reserved forest followed by 728, 13, 11, 8, 5 and 3 t·ha-1 in the protected forest, fallow land, cultivated-unirrigated land, grassland, orchard land and cultivated-irrigated land respectively. Of the total accessible biomass, only 0.31% was extracted annually by the local people for fuel, fodder and other uses. Though, the current level of extraction may be sustainable in the short run, insufficient regeneration is observed for long term sustainability. Forest biomass production was simulated for the next 30 years with a logistic growth model and the relative significance of input variables in influencing system behaviour was analysed through sensitivity analysis. The model results highlighted the declining forest resources in the long run. Positive response through appropriate government policies can, however, change the scenario for the better.

  2. 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

  3. Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass

    Science.gov (United States)

    Laurance, William F.

    2004-01-01

    This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.

  4. Mapping Russian forest biomass with data from satellites and forest inventories

    Energy Technology Data Exchange (ETDEWEB)

    Houghton, R A [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States); Butman, D [Yale School of Forestry and Environmental Science, Yale University, New Haven, CT 06511 (United States); Bunn, A G [Department of Environmental Sciences, Huxley College of the Environment, Western Washington University, 516 High Street, Bellingham, WA 98225-9181 (United States); Krankina, O N [Department of Forest Science, Oregon State University, 202 Richardson Hall, Corvallis, OR 97331-5752 (United States); Schlesinger, P [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States); Stone, T A [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States)

    2007-10-15

    The forests of Russia cover a larger area and hold more carbon than the forests of any other nation and thus have the potential for a major role in global warming. Despite a systematic inventory of these forests, however, estimates of total carbon stocks vary, and spatial variations in the stocks within large aggregated units of land are unknown, thus hampering measurement of sources and sinks of carbon. We mapped the distribution of living forest biomass for the year 2000 by developing a relationship between ground measurements of wood volume at 12 sites throughout the Russian Federation and data from the MODIS satellite bidirectional reflectance distribution function (BRDF) product (MOD43B4). Based on the results of regression-tree analyses, we used the MOD43B4 product to assign biomass values to individual 500 m x 500 m cells in areas identified as forest by two satellite-based maps of land cover. According to the analysis, the total living biomass varied between 46 and 67 Pg, largely because of different estimates of forest area. Although optical data are limited in distinguishing differences in biomass in closed canopy forests, the estimates of total living biomass obtained here varied more in response to different definitions of forest than to saturation of the optical sensing of biomass.

  5. 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.

  6. Temperature drives global patterns in forest biomass distribution in leaves, stems, and roots.

    Science.gov (United States)

    Reich, Peter B; Luo, Yunjian; Bradford, John B; Poorter, Hendrik; Perry, Charles H; Oleksyn, Jacek

    2014-09-23

    Whether the fraction of total forest biomass distributed in roots, stems, or leaves varies systematically across geographic gradients remains unknown despite its importance for understanding forest ecology and modeling global carbon cycles. It has been hypothesized that plants should maintain proportionally more biomass in the organ that acquires the most limiting resource. Accordingly, we hypothesize greater biomass distribution in roots and less in stems and foliage in increasingly arid climates and in colder environments at high latitudes. Such a strategy would increase uptake of soil water in dry conditions and of soil nutrients in cold soils, where they are at low supply and are less mobile. We use a large global biomass dataset (>6,200 forests from 61 countries, across a 40 °C gradient in mean annual temperature) to address these questions. Climate metrics involving temperature were better predictors of biomass partitioning than those involving moisture availability, because, surprisingly, fractional distribution of biomass to roots or foliage was unrelated to aridity. In contrast, in increasingly cold climates, the proportion of total forest biomass in roots was greater and in foliage was smaller for both angiosperm and gymnosperm forests. These findings support hypotheses about adaptive strategies of forest trees to temperature and provide biogeographically explicit relationships to improve ecosystem and earth system models. They also will allow, for the first time to our knowledge, representations of root carbon pools that consider biogeographic differences, which are useful for quantifying whole-ecosystem carbon stocks and cycles and for assessing the impact of climate change on forest carbon dynamics.

  7. Temperature drives global patterns in forest biomass distribution in leaves, stems, and roots

    Science.gov (United States)

    Reich, Peter B.; Lou, Yunjian; Bradford, John B.; Poorter, Hendrik; Perry, Charles H.; Oleksyn, Jacek

    2014-01-01

    Whether the fraction of total forest biomass distributed in roots, stems, or leaves varies systematically across geographic gradients remains unknown despite its importance for understanding forest ecology and modeling global carbon cycles. It has been hypothesized that plants should maintain proportionally more biomass in the organ that acquires the most limiting resource. Accordingly, we hypothesize greater biomass distribution in roots and less in stems and foliage in increasingly arid climates and in colder environments at high latitudes. Such a strategy would increase uptake of soil water in dry conditions and of soil nutrients in cold soils, where they are at low supply and are less mobile. We use a large global biomass dataset (>6,200 forests from 61 countries, across a 40 °C gradient in mean annual temperature) to address these questions. Climate metrics involving temperature were better predictors of biomass partitioning than those involving moisture availability, because, surprisingly, fractional distribution of biomass to roots or foliage was unrelated to aridity. In contrast, in increasingly cold climates, the proportion of total forest biomass in roots was greater and in foliage was smaller for both angiosperm and gymnosperm forests. These findings support hypotheses about adaptive strategies of forest trees to temperature and provide biogeographically explicit relationships to improve ecosystem and earth system models. They also will allow, for the first time to our knowledge, representations of root carbon pools that consider biogeographic differences, which are useful for quantifying whole-ecosystem carbon stocks and cycles and for assessing the impact of climate change on forest carbon dynamics.

  8. 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.

  9. Economic approach to assess the forest carbon implications of biomass energy.

    Science.gov (United States)

    Daigneault, Adam; Sohngen, Brent; Sedjo, Roger

    2012-06-05

    There is widespread concern that biomass energy policy that promotes forests as a supply source will cause net carbon emissions. Most of the analyses that have been done to date, however, are biological, ignoring the effects of market adaptations through substitution, net imports, and timber investments. This paper uses a dynamic model of forest and land use management to estimate the impact of United States energy policies that emphasize the utilization of forest biomass on global timber production and carbon stocks over the next 50 years. We show that when market factors are included in the analysis, expanded demand for biomass energy increases timber prices and harvests, but reduces net global carbon emissions because higher wood prices lead to new investments in forest stocks. Estimates are sensitive to assumptions about whether harvest residues and new forestland can be used for biomass energy and the demand for biomass. Restricting biomass energy to being sourced only from roundwood on existing forestland can transform the policy from a net sink to a net source of emissions. These results illustrate the importance of capturing market adjustments and a large geographic scope when measuring the carbon implications of biomass energy policies.

  10. 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; Pinagé, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.

    2016-11-01

    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) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained 70% 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-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 nearly 15 years ago had between 4.1 ± 0.5 and 6.8 ± 0.3 kg C m-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-2 (4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pantropical products consistently overestimated ACD in degraded forests, underestimated ACD in intact forests, and showed little sensitivity to fires 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+).

  11. Estimating aboveground biomass of broadleaved woody plants in the understory of Florida Keys pine forests

    Science.gov (United States)

    Sah, J.P.; Ross, M.S.; Koptur, S.; Snyder, J.R.

    2004-01-01

    Species-specific allometric equations that provide estimates of biomass from measured plant attributes are currently unavailable for shrubs common to South Florida pine rocklands, where fire plays an important part in shaping the structure and function of ecosystems. We developed equations to estimate total aboveground biomass and fine fuel of 10 common hardwood species in the shrub layer of pine forests of the lower Florida Keys. Many equations that related biomass categories to crown area and height were significant (p aboveground shrub biomass and shrub fine fuel increased with time since last fire, but the relationships were non-linear. The relative proportion of biomass constituted by the major species also varied with stand age. Estimates based on mixed-species regressions differed slightly from estimates based on species-specific models, but the former could provide useful approximations in similar forests where species-specific regressions are not yet available. ?? 2004 Elsevier B.V. All rights reserved.

  12. Height-diameter allometry and above ground biomass in tropical montane forests: Insights from the Albertine Rift in Africa

    Science.gov (United States)

    Boyemba, Faustin; Lewis, Simon; Nabahungu, Nsharwasi Léon; Calders, Kim; Zapfack, Louis; Riera, Bernard; Balegamire, Clarisse; Cuni-Sanchez, Aida

    2017-01-01

    Tropical montane forests provide an important natural laboratory to test ecological theory. While it is well-known that some aspects of forest structure change with altitude, little is known on the effects of altitude on above ground biomass (AGB), particularly with regard to changing height-diameter allometry. To address this we investigate (1) the effects of altitude on height-diameter allometry, (2) how different height-diameter allometric models affect above ground biomass estimates; and (3) how other forest structural, taxonomic and environmental attributes affect above ground biomass using 30 permanent sample plots (1-ha; all trees ≥ 10 cm diameter measured) established between 1250 and 2600 m asl in Kahuzi Biega National Park in eastern Democratic Republic of Congo. Forest structure and species composition differed with increasing altitude, with four forest types identified. Different height-diameter allometric models performed better with the different forest types, as trees got smaller with increasing altitude. Above ground biomass ranged from 168 to 290 Mg ha-1, but there were no significant differences in AGB between forests types, as tree size decreased but stem density increased with increasing altitude. Forest structure had greater effects on above ground biomass than forest diversity. Soil attributes (K and acidity, pH) also significantly affected above ground biomass. Results show how forest structural, taxonomic and environmental attributes affect above ground biomass in African tropical montane forests. They particularly highlight that the use of regional height-diameter models introduces significant biases in above ground biomass estimates, and that different height-diameter models might be preferred for different forest types, and these should be considered in future studies. PMID:28617841

  13. Height-diameter allometry and above ground biomass in tropical montane forests: Insights from the Albertine Rift in Africa.

    Science.gov (United States)

    Imani, Gérard; Boyemba, Faustin; Lewis, Simon; Nabahungu, Nsharwasi Léon; Calders, Kim; Zapfack, Louis; Riera, Bernard; Balegamire, Clarisse; Cuni-Sanchez, Aida

    2017-01-01

    Tropical montane forests provide an important natural laboratory to test ecological theory. While it is well-known that some aspects of forest structure change with altitude, little is known on the effects of altitude on above ground biomass (AGB), particularly with regard to changing height-diameter allometry. To address this we investigate (1) the effects of altitude on height-diameter allometry, (2) how different height-diameter allometric models affect above ground biomass estimates; and (3) how other forest structural, taxonomic and environmental attributes affect above ground biomass using 30 permanent sample plots (1-ha; all trees ≥ 10 cm diameter measured) established between 1250 and 2600 m asl in Kahuzi Biega National Park in eastern Democratic Republic of Congo. Forest structure and species composition differed with increasing altitude, with four forest types identified. Different height-diameter allometric models performed better with the different forest types, as trees got smaller with increasing altitude. Above ground biomass ranged from 168 to 290 Mg ha-1, but there were no significant differences in AGB between forests types, as tree size decreased but stem density increased with increasing altitude. Forest structure had greater effects on above ground biomass than forest diversity. Soil attributes (K and acidity, pH) also significantly affected above ground biomass. Results show how forest structural, taxonomic and environmental attributes affect above ground biomass in African tropical montane forests. They particularly highlight that the use of regional height-diameter models introduces significant biases in above ground biomass estimates, and that different height-diameter models might be preferred for different forest types, and these should be considered in future studies.

  14. Exploring multi-scale forest above ground biomass estimation with optical remote sensing imageries

    Science.gov (United States)

    Koju, U.; Zhang, J.; Gilani, H.

    2017-02-01

    Forest shares 80% of total exchange of carbon between the atmosphere and the terrestrial ecosystem. Due to this monitoring of forest above ground biomass (as carbon can be calculated as 0.47 part of total biomass) has become very important. Forest above ground biomass as being the major portion of total forest biomass should be given a very careful consideration in its estimation. It is hoped to be useful in addressing the ongoing problems of deforestation and degradation and to gain carbon mitigation benefits through mechanisms like Reducing Emissions from Deforestation and Forest Degradation (REDD+). Many methods of above ground biomass estimation are in used ranging from use of optical remote sensing imageries of very high to very low resolution to SAR data and LIDAR. This paper describes a multi-scale approach for assessing forest above ground biomass, and ultimately carbon stocks, using very high imageries, open source medium resolution and medium resolution satellite datasets with a very limited number of field plots. We found this method is one of the most promising method for forest above ground biomass estimation with higher accuracy and low cost budget. Pilot study was conducted in Chitwan district of Nepal on the estimation of biomass using this technique. The GeoEye-1 (0.5m), Landsat (30m) and Google Earth (GE) images were used remote sensing imageries. Object-based image analysis (OBIA) classification technique was done on Geo-eye imagery for the tree crown delineation at the watershed level. After then, crown projection area (CPA) vs. biomass model was developed and validated at the watershed level. Open source GE imageries were used to calculate the CPA and biomass from virtual plots at district level. Using data mining technique, different parameters from Landsat imageries along with the virtual sample biomass were used for upscaling biomass estimation at district level. We found, this approach can considerably reduce field data requirements for

  15. ALLOMETRIC EQUATIONS FOR ESTIMATING ABOVEGROUND BIOMASS IN PAPUA TROPICAL FOREST

    Directory of Open Access Journals (Sweden)

    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.

  16. Tropical Forest Biomass Estimation from Vertical Fourier Transforms of Lidar and InSAR Profiles

    Science.gov (United States)

    Treuhaft, R. N.; Goncalves, F.; Drake, J.; Hensley, S.; Chapman, B. D.; Michel, T.; Dos Santos, J. R.; Dutra, L.; Graca, P. A.

    2010-12-01

    Structural forest biomass estimation from lidar or interferometric SAR (InSAR) has demonstrated better performance than radar-power-based approaches for the higher biomasses (>150 Mg/ha) found in tropical forests. Structural biomass estimation frequently regresses field biomass to some function of forest height. With airborne, 25-m footprint lidar data and fixed-baseline C-band InSAR data over tropical wet forests of La Selva Biological Station, Costa Rica, we compare the use of Fourier transforms of vertical profiles at a few frequencies to the intrinsically low-frequency “average height”. RMS scatters of Fourier-estimated biomass about field-measured biomass improved by 40% and 20% over estimates base on average height from lidar and fixed-baseline InSAR, respectively. Vertical wavelengths between 14 and 100 m were found to best estimate biomass. The same airborne data acquisition over La Selva was used to generate many 10’s of repeat-track L-band InSAR baselines with time delays of 1-72 hours, and vertical wavelengths of 5-100 m. We will estimate biomass from the Fourier transforms of L-band radar power profiles (InSAR complex coherence). The effects of temporal decorrelation will be modeled in the Fourier domain to try to model and reduce their impact. Using L-band polarimetric interferometry, average heights will be estimated as well and biomass regression performance compared to the Fourier transform approach. The more traditional approach of using L-band radar polarimetry will also be compared to structural biomass estimation.

  17. BIOMASS AND MICROBIAL ACTIVITY UNDER DIFFERENT FOREST COVERS

    Directory of Open Access Journals (Sweden)

    Rafael Malfitano Braga

    2016-06-01

    Full Text Available This study evaluated the soil fertility, biomass and microbial activity of the soil under forest cover of Eucalyptus grandis, Eucalyptus pilularis, Eucalyptus cloeziana and Corymbia maculata; Pinus Caribbean var. hondurensis, 40 years old, and a fragment of Semideciduous Forest, located on the campus of the Federal University of Lavras. In soil samples collected in the 0-5 cm layer were determined fertility parameters, basal respiration and microbial biomass carbon. The results showed that for the species E. grandis and E. cloeziana the carbon of biomass microbial content was higher than for any other ecosystem evaluated, and equal to those observed under native forest. In contrast, the ground under Pinus had the lowest microbiological indexes. Under C. maculata and E. pilularis the contents were intermediate for this parameter. The basal respiration of all ecosystems was equal. The fertility level was very low in all types of evaluated vegetation.

  18. Water Quality Response to Forest Biomass Utilization

    Science.gov (United States)

    Benjamin Rau; Augustine Muwamba; Carl Trettin; Sudhanshu Panda; Devendra Amatya; Ernest Tollner

    2017-01-01

    Forested watersheds provide approximately 80% of freshwater drinking resources in the United States (Fox et al. 2007). The water originating from forested watersheds is typically of high quality when compared to agricul¬tural watersheds, and concentrations of nitrogen and phosphorus are nine times higher, on average, in agricultur¬al watersheds when compared to...

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

    NARCIS (Netherlands)

    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 a

  20. Allometric equations for aboveground and belowground biomass estimations in an evergreen forest in Vietnam

    NARCIS (Netherlands)

    Nam, Vu Thanh; Kuijk, Van 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 fo

  1. [Selection of biomass estimation models for Chinese fir plantation].

    Science.gov (United States)

    Li, Yan; Zhang, Jian-guo; Duan, Ai-guo; Xiang, Cong-wei

    2010-12-01

    A total of 11 kinds of biomass models were adopted to estimate the biomass of single tree and its organs in young (7-year-old), middle-age (16-year-old), mature (28-year-old), and mixed-age Chinese fir plantations. There were totally 308 biomass models fitted. Among the 11 kinds of biomass models, power function models fitted best, followed by exponential models, and then polynomial models. Twenty-one optimal biomass models for individual organ and single tree were chosen, including 18 models for individual organ and 3 models for single tree. There were 7 optimal biomass models for the single tree in the mixed-age plantation, containing 6 for individual organ and 1 for single tree, and all in the form of power function. The optimal biomass models for the single tree in different age plantations had poor generality, but the ones for that in mixed-age plantation had a certain generality with high accuracy, which could be used for estimating the biomass of single tree in different age plantations. The optimal biomass models for single Chinese fir tree in Shaowu of Fujin Province were used to predict the single tree biomass in mature (28-year-old) Chinese fir plantation in Jiangxi Province, and it was found that the models based on a large sample of forest biomass had a relatively high accuracy, being able to be applied in large area, whereas the regional models with small sample were limited to small area.

  2. Forest-fire models

    Science.gov (United States)

    Haiganoush Preisler; Alan Ager

    2013-01-01

    For applied mathematicians forest fire models refer mainly to a non-linear dynamic system often used to simulate spread of fire. For forest managers forest fire models may pertain to any of the three phases of fire management: prefire planning (fire risk models), fire suppression (fire behavior models), and postfire evaluation (fire effects and economic models). In...

  3. Biomass functions for young scots pine-dominated forest

    Energy Technology Data Exchange (ETDEWEB)

    Ahnlund Ulvcrona, K. (Vindeln Experimental Forests, Svartberet Research Station, Swedish Univ. of Agricultural Science, Vindeln (Sweden)), e-mail: Kristina.ulvcrona@esf.slu.se; Nilsson, U. (Southern Swedish Forest Research centre, Swedish Univ. of Agricultural Science, Alnarp (Sweden)); Lundmark, T. (Forest Ecology and Management, Swedish Univ. of Agricultural Science, Umeaa (Sweden))

    2010-07-15

    The aim of this study was to develop predictive biomass functions for young stands of Scots pine-dominated forests in northern Sweden. Above ground biomass was destructively sampled, and biomass functions for all tree fractions (e.g. stem including bark, branch and foliage) were developed, based on independent variables. Functions to estimate dry weight of the whole tree were also developed. No significant regressions could be found for the dead branch fraction. DBH for sampled trees in this study was in the range of 11 - 136 mm (Pinus sylvestris), 10 - 121 mm (Picea abies L. Karst) and 9 - 113 mm (Betula spp.)

  4. Login wood. Logistic for the Treatment of Forest Biomass; Loginwood. Logistica para el tratamiento de biomasa forestal

    Energy Technology Data Exchange (ETDEWEB)

    Martinez Sanchez, R.; Ayala Schraemili, F.

    2008-07-01

    This paper is about developing a logistic for the treatment of the forest prunes, including specific machines so far. Collecting, treatment, and transportation of forest biomass residues to valuation energy plant. Key words: collecting, treatment, transportation of forest prunes. (Author)

  5. The biomass and aboveground net primary productivity of Schima superba-Castanopsis carlesii forests in east China

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The biomass and productivity of Schima superba-Castanopsis carlesii forests in Tiantong,Zhejiang Province,were determined using overlapping quadrants and stem analyses.The total community biomass was(225.3±30.1) t hm-2,of which the aboveground parts accounted for 72.0% and the underground parts accounted for 28.0%.About 87.2% of biomass existed in the tree layer.The resprouting biomass was small,of which over 95.0% occurred in the shrub layer.The productivity of the aboveground parts of the community was(386.8±98.9) g m-2a-1,in which more than 96.0% was present at the tree level.The trunk’s contribution to productivity was the greatest,while that of leaves was the smallest.In China,the community biomass of subtropical evergreen broadleaved forests differs significantly with the age of the forest.The community biomass of the 52-year-old S.superba-C.carlesii forests in this study was lower than the average biomass of subtropical evergreen broadleaved forests in China,and was lower than the biomass of other subtropical evergreen broadleaved forests elsewhere in the world.Moreover,its productivity was lower than the model estimate,indicating that without disturbance,this community has great developmental potential in terms of community biomass and productivity.

  6. The biomass and aboveground net primary productivity of Schima superba-Castanopsis carlesii forests in east China.

    Science.gov (United States)

    Yang, TongHui; Song, Kun; Da, LiangJun; Li, XiuPeng; Wu, JianPing

    2010-07-01

    The biomass and productivity of Schima superba-Castanopsis carlesii forests in Tiantong, Zhejiang Province, were determined using overlapping quadrants and stem analyses. The total community biomass was (225.3+/-30.1) t hm(-2), of which the aboveground parts accounted for 72.0% and the underground parts accounted for 28.0%. About 87.2% of biomass existed in the tree layer. The resprouting biomass was small, of which over 95.0% occurred in the shrub layer. The productivity of the aboveground parts of the community was (386.8+/-98.9) g m(-2)a(-1), in which more than 96.0% was present at the tree level. The trunk's contribution to productivity was the greatest, while that of leaves was the smallest. In China, the community biomass of subtropical evergreen broadleaved forests differs significantly with the age of the forest. The community biomass of the 52-year-old S. superba-C. carlesii forests in this study was lower than the average biomass of subtropical evergreen broadleaved forests in China, and was lower than the biomass of other subtropical evergreen broadleaved forests elsewhere in the world. Moreover, its productivity was lower than the model estimate, indicating that without disturbance, this community has great developmental potential in terms of community biomass and productivity.

  7. An Evaluation of Site-specific and Generalized Spatial Models of Aboveground Forest Biomass Based on Landsat Time-series and LiDAR Strip Samples in the Eastern U.S.A.

    Science.gov (United States)

    Deo, R. K.; Domke, G. M.; Russell, M.; Andersen, H. E.; Cohen, W. B.

    2016-12-01

    Aboveground forest biomass (AGB) contributes a large part of the terrestrial carbon and varies with forest types. While forest disturbance and land use changes significantly influence greenhouse gas (GHG) emissions, international conventions on climate change mitigation have identified forest conservation and management as an efficient mechanism for enhancing carbon storage in live plant biomass to offset the emissions. Regional or national scale assessment of AGB on forest lands facilitates strategic plans such as the national GHG inventory per the requirement of the United Nations Framework Convention on Climate Change (UNFCCC). Large area inventory of AGB can be efficiently carried out by using remotely sensed data and a generalized statistical model in contrast to using only field measurements and site-specific models. In this study, we have integrated specialized forest inventory plot data with spatial predictors derived from time-series Landsat imagery and LiDAR strip samples in four sites across the eastern U.S.A.- Minnesota (MN), Maine (ME), Pennsylvania-New Jersey (PANJ) and South Carolina (SC) - to formulate statistical models. Pixel-level polynomial curve fit was applied to the time-series Landsat variables to obtain projected metrics in the target year 2014. Two forms of models based on ordinary least-squares regression (OLR) and the random forest (RF) algorithm were developed for each site and with the pooled (generalized) dataset. The site-specific models were tested with the national forest inventory (NFI) data as well as specialized plot data of the other sites while the generalized models were tested with the NFI data only. We observed similar level of accuracies with the OLR and RF models at the same site. Although the RF models yielded larger values for the amount of explained variance (i.e., pseudo R2) in the site-specific models, the generalized model was also promising. The amount of variance explained with the site-site specific models were

  8. Ashes from fluidized bed combustion of residual forest biomass

    NARCIS (Netherlands)

    Cruz, Nuno C.; Rodrigues, Sónia M.; Carvalho, Lina; Duarte, Armando C.; Pereira, Eduarda; Romkens, Paul; Tarelho, Luís A.C.

    2017-01-01

    Although bottom ash (BA) [or mixtures of bottom and fly ash (FA)] from clean biomass fuels is currently used as liming agent, additive for compost, and fertilizer on agricultural and forest soils in certain European countries, in several other countries most of the ashes are currently disposed in la

  9. Forest biomass at Xiaolong Mountain in Gansu Province,China

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In order to accurately estimate the size of the carbon pool and the capacity of the carbon sink in the forested areas of Xiaolong Mountain in Gansu Province,we have established regression equations of organ biomass of eight tree species.We measured and investigated the biomass of different forest stand types based on data from 1259 standard sample plots and 836 standard sample trees.for eight types of forest stands on Xiaolong Mountain,are as follows:Quercus aliena var.acuteserrata 84.05,Pinus tabulaeformis 62.44,Quercus variabilis 81.77,Populus sp.and Betula sp.combined 77.44,Larix sp.69.00,Pinus armandii 70.07,Picea sp.96.49 and Abies sp.98.72.We also looked at other broad-leaved mixed forests.Our study shows that the biomass of a single tree of each tree species is closely related to the diameter at breast height (DBH) and to tree height.The biomass of single trees as well as stand volumes is closely related to average DBH,average tree height and to stand density.

  10. Biomass publications of the forest operations research unit: A synthesis

    Science.gov (United States)

    Dana Mitchell; Renee Ayala; [Compilers

    2005-01-01

    The Forest Operations Unit of the Southern Research Station has been studying biomass-related topics since 1977. This CD aids the reader by organizing these publications in one easy-to-use CD. This CD is comprised of an executive summary, two bibliographies, individual publications (in PDF format), and a keyword listing. The types of publications included on this CD...

  11. ESTIMATION OF TROPICAL FOREST STRUCTURE AND BIOMASS FROM FUSION OF RADAR AND LIDAR MEASUREMENTS (Invited)

    Science.gov (United States)

    Saatchi, S. S.; Dubayah, R.; Clark, D. B.; Chazdon, R.

    2009-12-01

    Radar and Lidar instruments are active remote sensing sensors with the potential of measuring forest vertical and horizontal structure and the aboveground biomass (AGB). In this paper, we present the analysis of radar and lidar data acquired over the La Selva Biological Station in Costa Rica. Radar polarimetry at L-band (25 cm wavelength), P-band (70 cm wavelength) and interferometry at C-band (6 cm wavelength) and VV polarization were acquired by the NASA/JPL airborne synthetic aperture radar (AIRSAR) system. Lidar images were provided by a large footprint airborne scanning Lidar known as the Laser Vegetation Imaging Sensor (LVIS). By including field measurements of structure and biomass over a variety of forest types, we examined: 1) sensitivity of radar and lidar measurements to forest structure and biomass, 2) accuracy of individual sensors for AGB estimation, and 3) synergism of radar imaging measurements with lidar imaging and sampling measurements for improving the estimation of 3-dimensional forest structure and AGB. The results showed that P-band radar combined with any interformteric measurement of forest height can capture approximately 85% of the variation of biomass in La Selva at spatial scales larger than 1 hectare. Similar analysis at L-band frequency captured only 70% of the variation. However, combination of lidar and radar measurements improved estimates of forest three-dimensional structure and biomass to above 90% for all forest types. We present a novel data fusion approach based on a Baysian estimation model with the capability of incorporating lidar samples and radar imagery. The model was used to simulate the potential of data fusion in future satellite mission scenarios as in BIOMASS (planned by ESA) at P-band and DESDynl (planned by NASA) at L-band. The estimation model was also able to quantify errors and uncertainties associated with the scale of measurements, spatial variability of forest structure, and differences in radar and lidar

  12. Modeling the spatial distribution of forest crown biomass and effects on fire behavior with FUEL3D and WFDS

    Science.gov (United States)

    Russell A. Parsons; William Mell; Peter McCauley

    2010-01-01

    Crown fire poses challenges to fire managers and can endanger fire fighters. Understanding of how fire interacts with tree crowns is essential to informed decisions about crown fire. Current operational crown fire predictions in the United States assume homogeneous crown fuels. While a new class of research fire models, which model fire behavior with computational...

  13. Phytosociology and standing crop biomass of five different forest types of East Dehra Dun Forest Division

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, O.M.; Vasistha, H.B.; Soni, P.

    1984-08-01

    Different types of forests have varying efficiency of production depending upon a number of factors such as microclimate, altitude, latitude, soil type, etc. The standing biomass and floristic composition were determined for five forest types of India, and the productivity was compared. 8 tables.

  14. Forest volume and biomass estimation using small-footprint lidar-distributional parameters on a per-segment basis

    CSIR Research Space (South Africa)

    Van Aardt, JAN

    2006-05-01

    Full Text Available This study assessed a lidar-based, object-oriented (segmentation) approach to forest volume and aboveground biomass modeling. The study area in the Piedmont physiographic region of Virginia is composed of temperate coniferous, deciduous, and mixed...

  15. Allometric models for estimating biomass and carbon in Alnus acuminata

    Directory of Open Access Journals (Sweden)

    William Fonseca

    2013-12-01

    Full Text Available In order to quantify the climate change mitigation potential of forest plantations, information on total biomass and its growth rate is required. Depending on the method used, the study of the biomass behavior can be a complex and expensive activity. The main objective of this research was to develop allometric models to estimate biomass for different tree components (leaves, branches, stem and root and total tree biomass in Alnus acuminata (Kunth in Costa Rica. Additionally, models were developed to estimate biomass and carbon in trees per hectare and for total plant biomass per hectare (trees + herbaceous vegetation + necromass. To construct the tree models, 41 sampling plots were evaluated in seven sites from which 47 trees with a diametric from 4.5 to 44.5 cm were selected to be harvested. In the selected models for the stem, root and total tree biomass, a r 2 >93.87 % was accomplished, while the r 2aj for leaves and branches was 88 %. For the biomass and carbon models for total trees and total plant biomass per hectare the r2 was >99 %. Average biomass expansion factor was 1.22 for aboveground and 1.43 for total biomass (when the root was included. The carbon fraction in plant biomass varied between 32.9 and 46.7 % and the percentage of soil carbon was 3 %.

  16. Deadwood biomass: an underestimated carbon stock in degraded tropical forests?

    Science.gov (United States)

    Pfeifer, Marion; Lefebvre, Veronique; Turner, Edgar; Cusack, Jeremy; Khoo, MinSheng; Chey, Vun K.; Peni, Maria; Ewers, Robert M.

    2015-04-01

    Despite a large increase in the area of selectively logged tropical forest worldwide, the carbon stored in deadwood across a tropical forest degradation gradient at the landscape scale remains poorly documented. Many carbon stock studies have either focused exclusively on live standing biomass or have been carried out in primary forests that are unaffected by logging, despite the fact that coarse woody debris (deadwood with ≥10 cm diameter) can contain significant portions of a forest’s carbon stock. We used a field-based assessment to quantify how the relative contribution of deadwood to total above-ground carbon stock changes across a disturbance gradient, from unlogged old-growth forest to severely degraded twice-logged forest, to oil palm plantation. We measured in 193 vegetation plots (25 × 25 m), equating to a survey area of >12 ha of tropical humid forest located within the Stability of Altered Forest Ecosystems Project area, in Sabah, Malaysia. Our results indicate that significant amounts of carbon are stored in deadwood across forest stands. Live tree carbon storage decreased exponentially with increasing forest degradation 7-10 years after logging while deadwood accounted for >50% of above-ground carbon stocks in salvage-logged forest stands, more than twice the proportion commonly assumed in the literature. This carbon will be released as decomposition proceeds. Given the high rates of deforestation and degradation presently occurring in Southeast Asia, our findings have important implications for the calculation of current carbon stocks and sources as a result of human-modification of tropical forests. Assuming similar patterns are prevalent throughout the tropics, our data may indicate a significant global challenge to calculating global carbon fluxes, as selectively-logged forests now represent more than one third of all standing tropical humid forests worldwide.

  17. Projecting demand and supply of forest biomass for heating in Norway

    Energy Technology Data Exchange (ETDEWEB)

    Tromborg, Erik, E-mail: erik.tromborg@umb.no [Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 As (Norway); Havskjold, Monica; Lislebo, Ole [Xrgia as, P.O. Box 329, NO-1301, Sandvika (Norway); Rorstad, Per Kristian [Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 As (Norway)

    2011-11-15

    This paper assesses the increase in demand and supply for forest biomass for heating in Norway in 2020. By then there is a political aim to double the national production of bioenergy from the level in 2008. The competitiveness of woody biomass in central and district heating is analyzed in a model selecting the least-cost heating technology and scale in municipalities given a set of constraints and under different fuels price scenarios. The supply of forest biomass from roundwood is estimated based on data of forest inventories combined with elasticities regarding price and standing volumes. The supply of biomass from harvesting residues is estimated in an engineering approach based on data from the national forest inventories and roundwood harvest. The results show how the production of bioenergy is affected by changes in energy prices and support schemes for bioenergy. One conclusion from the analyses is that the government target of 14 TWh more bioenergy by 2020 is not likely to be met by current technologies and policy incentives. The contribution of the analysis is the detailed presentation of the heat market potentials and technology choices combined with supply functions for both roundwood and harvesting residues. - Highlights: > This paper accesses the demand and supply for forest biomass for heating in Norway in 2020. > Market share for wood in central and new district heating is analyzed in a cost-minimizing model. > The supply of forest biomass includes wood chips from import, roundwood and harvesting residues. > The production of bioenergy is affected by changes in energy prices and support schemes. > The government target for bioenergy is not met by current technologies and policy incentives.

  18. Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part I: reference simulation

    Directory of Open Access Journals (Sweden)

    J. Trentmann

    2006-01-01

    Full Text Available Wildland fires in boreal regions have the potential to initiate deep convection, so-called pyro-convection, due to their release of sensible heat. Under favorable atmospheric conditions, large fires can result in pyro-convection that transports the emissions into the upper troposphere and the lower stratosphere. Here, we present three-dimensional model simulations of the injection of fire emissions into the lower stratosphere by pyro-convection. These model simulations are constrained and evaluated with observations obtained from the Chisholm fire in Alberta, Canada, in 2001. The active tracer high resolution atmospheric model (ATHAM is initialized with observations obtained by radiosonde. Information on the fire forcing is obtained from ground-based observations of the mass and moisture of the burned fuel. Based on radar observations, the pyro-convection reached an altitude of about 13 km, well above the tropopause, which was located at about 11.2 km. The model simulation yields a similarly strong convection with an overshoot of the convection above the tropopause. The main outflow from the pyro-convection occurs at about 10.6 km, but a significant fraction (about 8% of the emitted mass of the smoke aerosol is transported above the tropopause. In contrast to regular convection, the region with maximum updraft velocity in the pyro-convection is located close to the surface above the fire. This results in high updraft velocities >10 m s−1 at cloud base. The temperature anomaly in the plume decreases rapidly with height from values above 50 K at the fire to about 5 K at about 3000 m above the fire. While the sensible heat released from the fire is responsible for the initiation of convection in the model, the release of latent heat from condensation and freezing dominates the overall energy budget. Emissions of water vapor from the fire do not significantly contribute to the energy budget of the convection.

  19. Mapping woody-biomass supply costs using forest inventory and competing industry data

    Energy Technology Data Exchange (ETDEWEB)

    Stasko, Timon H.; Conrado, Robert J.; Labatut, Rodrigo; Tasseff, Ryan; Mannion, John T.; Gao, H. Oliver [College of Engineering, Cornell University, Ithaca, NY 14853 (United States); Wankerl, Andreas [Innovation Interface, 126 Reach Run, Ithaca, NY 14850 (United States); Sanborn, Stephen D.; Knott, Gregory [General Electric Global Research, 1 Research Circle, Niskayuna, NY 12309 (United States)

    2011-01-15

    The goals of energy independence and sustainability have motivated many countries to consider biomass-based energy sources. The United States has substantial and increasing forest resources that could be used to produce both electricity and liquid fuel. However, these forest resources are highly heterogeneous in terms of the wood's properties, the logging cost, the spatial distribution, and the value to other industries. These factors make predicting costs and selecting plant locations particularly challenging. When dealing with forest biomass, feedstock cost and location have frequently been highly simplified in previous studies. This paper presents a methodology for combining highly resolved forest inventory and price data with records of competing industries to develop detailed maps of feedstock availability. The feedstock sourcing strategy of the proposed bioenergy plants is modeled by a cost-minimizing linear program, as is the feedstock selection of the competing mills. A case study is performed on the southeast United States. (author)

  20. Measuring Forest Height and Biomass from Space

    Science.gov (United States)

    Agueh, Temilola Elisabeth Fato

    2013-01-01

    Talk about doing earth science at NASA and how what we do is focus on the biosphere- that is the living portion of the earth.In particular, we are interested in looking at forests-quantifying deforestation, regrowth, change in general and helping develop new cutting-edge technologies and instruments to be able to measure these changes in land use, land cover and quality more accurately.

  1. 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.

  2. Composite materials from forest biomass : a review of current practices, science, and technology

    Science.gov (United States)

    Roger M. Rowell

    2007-01-01

    Renewable and sustainable composite materials can be produced using forest biomass if we maintain healthy forests. Small diameter trees and other forest biomass can be processed in the forest into small solid wood pieces, sliced veneers, strands, flakes, chips, particles and fiber that can be used to make construction composite products such as glued-laminated lumber,...

  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. Changes in tree functional composition amplify the response of forest biomass to climate variability

    Science.gov (United States)

    Lichstein, Jeremy; Zhang, Tao; Niinemets, Ulo; Sheffield, Justin

    2017-04-01

    The response of forest carbon storage to climate change is highly uncertain, contributing substantially to the divergence among global climate model projections. Numerous studies have documented responses of forest ecosystems to climate change and variability, including drought-induced increases in tree mortality rates. However, the sensitivity of forests to climate variability - in terms of both biomass carbon storage and functional components of tree species composition - has yet to be quantified across a large region using systematically sampled data. Here, we combine systematic forest inventories across the eastern USA with a species-level drought-tolerance index, derived from a meta-analysis of published literature, to quantify changes in forest biomass and community-mean-drought-tolerance in one-degree grid cells from the 1980s to 2000s. We show that forest biomass responds to decadal-scale changes in water deficit and that this biomass response is amplified by concurrent changes in community-mean-drought-tolerance. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards more drought-tolerant but lower-biomass species. Multiple plant functional traits are correlated with the above species-level drought-tolerance index, and likely contribute to the decrease in biomass with increasing drought-tolerance. These traits include wood density and P50 (the xylem water potential at which a plant loses 50% of its hydraulic conductivity). Simulations with a trait- and competition-based dynamic global vegetation model suggest that species differences in plant carbon allocation to wood, leaves, and fine roots also likely contribute to the observed decrease in biomass with increasing drought-tolerance, because competition drives plants to over-invest in fine roots when water is limiting. Thus, the most competitive species under dry conditions have greater root allocation but

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

    Science.gov (United States)

    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...

  6. 林分生物量碳计量模型的比较研究%Comparative studies on biomass-carbon accounting models at forest stand scale

    Institute of Scientific and Technical Information of China (English)

    胡砚秋; 苏志尧; 李佩瑗; 李文斌

    2015-01-01

    选取3个天然林群落作为研究对象,利用3种包含不同计量参数的生物量碳计量模型,即生物量因子法、异速生长方程法及材积源生物量法,分别计算林分碳储量并比较分析各模型计量结果的差异。结果表明:生物量因子法与材积源生物量法计算所得林分平均碳密度相近,分别为155.56和152.82 Mg·hm-2,异速生长方程法的结果偏低,为118.44 Mg·hm-2,生物量因子法计算的不同群落的林分碳储量比异速生长方程法的高22.11%~43.02%;各群落的立木结构及物种组成存在显著差异,均方根误差分析显示生物量因子法对群落碳密度的差异反应最为敏感,计量精度最高;各方法计量结果均显示中、大径级立木是林分碳储量的主要贡献者,中径级立木与大径级立木中计量精度较高的模型分别是异速生长方程法与生物量因子法。综合考虑计量精度及参数获取的便利性,3种计量模型各有优势,在实际应用中可以根据具体情况选择较为适合的模型,一般情况下可使用材积源生物量法,能便利地获得与采用包含木材密度参数的生物量因子法最接近的计量结果。%To calculate the differences among carbon accounting models, the stand carbon storages in three natural evergreen forest communities were measured and compared by three biomass-carbon accounting models with different parameters, including biomass factor method (BFM) containing wood density, allometric equation method (AEM) and biomass-volume method (BVM). The results show that the average community carbon density calculated by BFM (155.56 Mg·hm-2) and BVM (152.82 Mg·hm-2) were close each other, while the value of AGM (118.44 Mg·hm-2) was relatively lower, Carbon storage determined by BFM was 22.11%~ 43.02% higher than AGM in each community; Stand structure and species composition of the communities were significantly different, and the

  7. Bringing Together Users and Developers of Forest Biomass Maps

    Science.gov (United States)

    Brown, Molly Elizabeth; Macauley, Molly K.

    2012-01-01

    Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the

  8. Forest Biomass Energy Resources in China: Quantity and Distribution

    Directory of Open Access Journals (Sweden)

    Caixia Zhang

    2015-11-01

    Full Text Available As one of the most important renewable and sustainable energy sources, the forest biomass energy resource has always been the focus of attention of scholars and policy makers. However, its potential is still uncertain in China, especially with respect to its spatial distribution. In this paper, the quantity and distribution of Chinese forest biomass energy resources are explored based mainly on forestry statistics data rather than forest resource inventory data used by most previous studies. The results show that the forest biomass energy resource in China was 169 million tons in 2010, of which wood felling and bucking residue (WFBR,wood processing residue (WPR, bamboo processing residue, fuel wood and firewood used by farmers accounted for 38%, 37%, 6%, 4% and 15%, respectively. The highest resource was located in East China, accounting for nearly 39.0% of the national amount, followed by the Southwest and South China regions, which accounted for 17.4% and 16.3%, respectively. At the provincial scale, Shandong has the highest distribution, accounting for 11.9% of total resources, followed by Guangxi and Fujian accounting for 10.3% and 10.2%, respectively. The actual wood-processing residue (AWPR estimated from the actual production of different wood products (considering the wood transferred between regions showed apparent differences from the local wood processing residue (LWPR, which assumes that no wood has been transferredbetween regions. Due to the large contribution of WPR to total forestry bioenergy resources, the estimation of AWPR will provide a more accurate evaluation of the total amount and the spatial distribution of forest biomass energy resources in China.

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

    Directory of Open Access Journals (Sweden)

    Vincenzo Giannico

    2016-04-01

    Full Text Available Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR. In this study we assessed forest stand volume and above-ground biomass (AGB in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA and mean stand height (H from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first (proxy of BA and the 95th percentile of the distribution of all first returns (proxy of H. The R2 were 0.81 (p < 0.01 for the stand volume model and 0.77 (p < 0.01 for the AGB model with a RMSE of 23.66 m3·ha−1 (23.3% and 19.59 Mg·ha−1 (23.9%, respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H, which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods.

  10. Forest biomass carbon sinks in East Asia, with special reference to the relative contributions of forest expansion and forest growth.

    Science.gov (United States)

    Fang, Jingyun; Guo, Zhaodi; Hu, Huifeng; Kato, Tomomichi; Muraoka, Hiroyuki; Son, Yowhan

    2014-06-01

    Forests play an important role in regional and global carbon (C) cycles. With extensive afforestation and reforestation efforts over the last several decades, forests in East Asia have largely expanded, but the dynamics of their C stocks have not been fully assessed. We estimated biomass C stocks of the forests in all five East Asian countries (China, Japan, North Korea, South Korea, and Mongolia) between the 1970s and the 2000s, using the biomass expansion factor method and forest inventory data. Forest area and biomass C density in the whole region increased from 179.78 × 10(6) ha and 38.6 Mg C ha(-1) in the 1970s to 196.65 × 10(6) ha and 45.5 Mg C ha(-1) in the 2000s, respectively. The C stock increased from 6.9 Pg C to 8.9 Pg C, with an averaged sequestration rate of 66.9 Tg C yr(-1). Among the five countries, China and Japan were two major contributors to the total region's forest C sink, with respective contributions of 71.1% and 32.9%. In China, the areal expansion of forest land was a larger contributor to C sinks than increased biomass density for all forests (60.0% vs. 40.0%) and for planted forests (58.1% vs. 41.9%), while the latter contributed more than the former for natural forests (87.0% vs. 13.0%). In Japan, increased biomass density dominated the C sink for all (101.5%), planted (91.1%), and natural (123.8%) forests. Forests in South Korea also acted as a C sink, contributing 9.4% of the total region's sink because of increased forest growth (98.6%). Compared to these countries, the reduction in forest land in both North Korea and Mongolia caused a C loss at an average rate of 9.0 Tg C yr(-1), equal to 13.4% of the total region's C sink. Over the last four decades, the biomass C sequestration by East Asia's forests offset 5.8% of its contemporary fossil-fuel CO2 emissions. © 2014 John Wiley & Sons Ltd.

  11. Dispersal limitation induces long-term biomass collapse in overhunted Amazonian forests.

    Science.gov (United States)

    Peres, Carlos A; Emilio, Thaise; Schietti, Juliana; Desmoulière, Sylvain J M; Levi, Taal

    2016-01-26

    Tropical forests are the global cornerstone of biological diversity, and store 55% of the forest carbon stock globally, yet sustained provisioning of these forest ecosystem services may be threatened by hunting-induced extinctions of plant-animal mutualisms that maintain long-term forest dynamics. Large-bodied Atelinae primates and tapirs in particular offer nonredundant seed-dispersal services for many large-seeded Neotropical tree species, which on average have higher wood density than smaller-seeded and wind-dispersed trees. We used field data and models to project the spatial impact of hunting on large primates by ∼ 1 million rural households throughout the Brazilian Amazon. We then used a unique baseline dataset on 2,345 1-ha tree plots arrayed across the Brazilian Amazon to model changes in aboveground forest biomass under different scenarios of hunting-induced large-bodied frugivore extirpation. We project that defaunation of the most harvest-sensitive species will lead to losses in aboveground biomass of between 2.5-5.8% on average, with some losses as high as 26.5-37.8%. These findings highlight an urgent need to manage the sustainability of game hunting in both protected and unprotected tropical forests, and place full biodiversity integrity, including populations of large frugivorous vertebrates, firmly in the agenda of reducing emissions from deforestation and forest degradation (REDD+) programs.

  12. Spatio-temporal changes in biomass carbon sinks in China's forests from 1977 to 2008.

    Science.gov (United States)

    Guo, Zhaodi; Hu, Huifeng; Li, Pin; Li, Nuyun; Fang, Jingyun

    2013-07-01

    Forests play a leading role in regional and global carbon (C) cycles. Detailed assessment of the temporal and spatial changes in C sinks/sources of China's forests is critical to the estimation of the national C budget and can help to constitute sustainable forest management policies for climate change. In this study, we explored the spatio-temporal changes in forest biomass C stocks in China between 1977 and 2008, using six periods of the national forest inventory data. According to the definition of the forest inventory, China's forest was categorized into three groups: forest stand, economic forest, and bamboo forest. We estimated forest biomass C stocks for each inventory period by using continuous biomass expansion factor (BEF) method for forest stands, and the mean biomass density method for economic and bamboo forests. As a result, China's forests have accumulated biomass C (i.e., biomass C sink) of 1896 Tg (1 Tg=10(12) g) during the study period, with 1710, 108 and 78 Tg C in forest stands, and economic and bamboo forests, respectively. Annual forest biomass C sink was 70.2 Tg C a(-1), offsetting 7.8% of the contemporary fossil CO2 emissions in the country. The results also showed that planted forests have functioned as a persistent C sink, sequestrating 818 Tg C and accounting for 47.8% of total C sink in forest stands, and that the old-, mid- and young-aged forests have sequestrated 930, 391 and 388 Tg C from 1977 to 2008. Our results suggest that China's forests have a big potential as biomass C sink in the future because of its large area of planted forests with young-aged growth and low C density.

  13. Live above- and belowground biomass of a Mozambican evergreen forest: a comparison of estimates based on regression equations and biomass expansion factors

    Directory of Open Access Journals (Sweden)

    Tarquinio Mateus Magalhães

    2015-10-01

    Full Text Available Background Biomass regression equations are claimed to yield the most accurate biomass estimates than biomass expansion factors (BEFs. Yet, national and regional biomass estimates are generally calculated based on BEFs, especially when using national forest inventory data. Comparison of regression equations based and BEF-based biomass estimates are scarce. Thus, this study was intended to compare these two commonly used methods for estimating tree and forest biomass with regard to errors and biases. Methods The data were collected in 2012 and 2014. In 2012, a two-phase sampling design was used to fit tree component biomass regression models and determine tree BEFs. In 2014, additional trees were felled outside sampling plots to estimate the biases associated with regression equation based and BEF-based biomass estimates; those estimates were then compared in terms of the following sources of error: plot selection and variability, biomass model, model parameter estimates, and residual variability around model prediction. Results The regression equation based below-, aboveground and whole tree biomass stocks were, approximately, 7.7, 8.5 and 8.3 % larger than the BEF-based ones. For the whole tree biomass stock, the percentage of the total error attributed to first phase (random plot selection and variability was 90 and 88 % for regression- and BEF-based estimates, respectively, being the remaining attributed to biomass models (regression and BEF models, respectively. The percent bias of regression equation based and BEF-based biomass estimates for the whole tree biomass stock were −2.7 and 5.4 %, respectively. The errors due to model parameter estimates, those due to residual variability around model prediction, and the percentage of the total error attributed to biomass model were larger for BEF models (than for regression models, except for stem and stem wood components. Conclusions The regression equation based biomass stocks were found to

  14. Primary energy and greenhouse gas implications of increasing biomass production through forest fertilization

    Energy Technology Data Exchange (ETDEWEB)

    Sathre, Roger; Gustavsson, Leif [Ecotechnology, Mid Sweden University, Oestersund (Sweden); Bergh, Johan [Ecotechnology, Mid Sweden University, Oestersund (Sweden); Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Alnarp (Sweden)

    2010-04-15

    In this study we analyze the primary energy and greenhouse gas (GHG) implications of increasing biomass production by fertilizing 10% of Swedish forest land. We estimate the primary energy use and GHG emissions from forest management including production and application of N and NPK fertilizers. Based on modelled growth response, we then estimate the net primary energy and GHG benefits of using biomaterials and biofuels obtained from the increased forest biomass production. The results show an increased annual biomass harvest of 7.4 million t dry matter, of which 41% is large-diameter stemwood. About 6.9 PJ/year of additional primary energy input is needed for fertilizer production and forest management. Using the additional biomass for fuel and material substitution can reduce fossil primary energy use by 150 or 164 PJ/year if the reference fossil fuel is fossil gas or coal, respectively. About 22% of the reduced fossil energy use is due to material substitution and the remainder is due to fuel substitution. The net annual primary energy benefit corresponds to about 7% of Sweden's total primary energy use. The resulting annual net GHG emission reduction is 11.9 million or 18.1 million tCO{sub 2equiv} if the reference fossil fuel is fossil gas or coal, respectively, corresponding to 18% or 28% of the total Swedish GHG emissions in 2007. A significant one-time carbon stock increase also occurs in wood products and forest tree biomass. These results suggest that forest fertilization is an attractive option for increasing energy security and reducing net GHG emission. (author)

  15. Mapping Aboveground Biomass using Texture Indices from Aerial Photos in a Temperate Forest of Northeastern China

    Directory of Open Access Journals (Sweden)

    Shili Meng

    2016-03-01

    Full Text Available Optical remote sensing data have been considered to display signal saturation phenomena in regions of high aboveground biomass (AGB and multi-storied forest canopies. However, some recent studies using texture indices derived from optical remote sensing data via the Fourier-based textural ordination (FOTO approach have provided promising results without saturation problems for some tropical forests, which tend to underestimate AGB predictions. This study was applied to the temperate mixed forest of the Liangshui National Nature Reserve in Northeastern China and demonstrated the capability of FOTO texture indices to obtain a higher prediction quality of forest AGB. Based on high spatial resolution aerial photos (1.0 m spatial resolution acquired in September 2009, the relationship between FOTO texture indices and field-derived biomass measurements was calibrated using a support vector regression (SVR algorithm. Ten-fold cross-validation was used to construct a robust prediction model, which avoided the over-fitting problem. By further comparison the performance of the model estimates for greater coverage, the predicted results were compared with a reference biomass map derived from LiDAR metrics. This study showed that the FOTO indices accounted for 88.3% of the variance in ground-based AGB; the root mean square error (RMSE was 34.35 t/ha, and RMSE normalized by the mean value of the estimates was 22.31%. This novel texture-based method has great potential for forest AGB estimation in other temperate regions.

  16. LiDAR-Assisted Multi-Source Program (LAMP for Measuring Above Ground Biomass and Forest Carbon

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    Tuomo Kauranne

    2017-02-01

    Full Text Available Forest measurement for purposes like harvesting planning, biomass estimation and mitigating climate change through carbon capture by forests call for increasingly frequent forest measurement campaigns that need to balance cost with accuracy and precision. Often this implies the use of remote sensing based measurement methods. For any remote-sensing based methods to be accurate, they must be validated against field data. We present a method that combines field measurements with two layers of remote sensing data: sampling of forests by airborne laser scanning (LiDAR and Landsat imagery. The Bayesian model-based framework presented here is called Lidar-Assisted Multi-source Programme—or LAMP—for Above Ground Biomass estimation. The method has two variants: LAMP2 which splits the biomass estimation task into two separate stages: forest type stratification from Landsat imagery and mean biomass density estimation of each forest type by LiDAR models calibrated on field plots. LAMP3, on the other hand, estimates first the biomass on a LiDAR sample using models calibrated with field plots and then uses these LiDAR-based models to generate biomass density estimates on thousands of surrogate plots, with which a satellite image based model is calibrated and subsequently used to estimate biomass density on the entire forest area. Both LAMP methods have been applied to a 2 million hectare area in Southern Nepal, the Terai Arc Landscape or TAL to calculate the emission Reference Levels (RLs that are required for the UN REDD+ program that was accepted as part of the Paris Climate Agreement. The uncertainty of these estimates is studied with error variance estimation, cross-validation and Monte Carlo simulation. The relative accuracy of activity data at pixel level was found to be 14 per cent at 95 per cent confidence level and the root mean squared error of biomass estimates to be between 35 and 39 per cent at 1 ha resolution.

  17. Review of Methods for the Monitoring of Biomass and Vegetal Carbon in Tropical Forest Ecosystems

    Directory of Open Access Journals (Sweden)

    William Fonseca

    2017-06-01

    Full Text Available The quantification of vegetal biomass is the key to know the carbon that forest ecosystems store, and therefore, its capacity to mitigate climatic change. There is a variety of methods to estimate biomass, many with small variations, such as size and shape of sampling units, inclusion or not of any reservoir component (leaves, branches, roots, necromasses, minimum diameter inventoried, among others. The objective of the paper is to explain the most important aspects to be considered in the inventory of removals, based on the inventory design (statistical design, size and shape of the sampling units, components of the biomass to be evaluated. A second point deals with the determination of aerial biomass and roots, referring to the direct or destructive method, and indirect methods, especially to the use of mathematical models for their easy application and low cost; besides, some models for natural forest and plantations are noted. Reference is also made to the study of carbon in soils, biomass expansion factors, and how to determine carbon in biomass. We hope that these notes will facilitate the understanding of the topic and be a reference for the establishment of monitoring, reporting and verification schemes.

  18. Biomass carbon stocks in China’s forests between 2000 and 2050:A prediction based on forest biomass-age relationships

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    China’s forests are characterized by young forest age,low carbon density and a large area of planted forests,and thus have high potential to act as carbon sinks in the future.Using China’s national forest inventory data during 1994-1998 and 1999-2003,and direct field measurements,we investigated the relationships between forest biomass density and forest age for 36 major forest types.Statistical approaches and the predicted future forest area from the national forestry development plan were applied to estimate the potential of forest biomass carbon storage in China during 2000-2050.Under an assumption of continuous natural forest growth,China’s existing forest biomass carbon(C) stock would increase from 5.86 Pg C(1 Pg=1015 g) in 1999-2003 to 10.23 Pg C in 2050,resulting in a total increase of 4.37 Pg C.Newly planted forests through afforestation and reforestation will sequestrate an additional 2.86 Pg C in biomass.Overall,China’s forests will potentially act as a carbon sink for 7.23 Pg C during the period 2000-2050,with an average carbon sink of 0.14 Pg C yr-1.This suggests that China’s forests will be a significant carbon sink in the next 50 years.

  19. Simulation of the biomass dynamics of Masson pine forest under different management

    Institute of Scientific and Technical Information of China (English)

    ZHANG Gui-lian; WANG Kai-yun; LIU Xin-wei; PENG Shao-lin

    2006-01-01

    TREE submodel affiliated with TREEDYN was used to simulate biomass dynamics of Masson pine (Pinus massoniana) forest under different managements (including thinning, clear cutting, combining thinning with clear cutting). The purpose was to represent biomass dynamics involved in its development, which can provide scientific arguments for management of Masson pine forest. The results showed the scenario that 10% or 20% of biomass of the previous year was thinned every five years from 15 to 40 years made total biomass of pine forest increase slowly and it took more time to reach a mature community; If clear cutting and thinning were combined, the case C (clear cutting at 20 years of forest age, thinning 50% of remaining biomass at 30 years of forest age, and thinning 50% of remaining biomass again at 40 years of forest age) was the best scenario which can accelerate speed of development of Masson pine forest and gained better economic values.

  20. Countrywide Forest Biomass Estimates from PALSAR L-Band Backscatter to Improve Greenhouse Gas Inventory in Estonia

    Science.gov (United States)

    Olesk, A.; Voormansik, K.; Luud, Aarne; Renne, M.; Zalite, K.; Noorma, M.; Reinart, A.

    2013-08-01

    Accurately estimated forest biomass and its distribution is a key parameter for forest inventories, vegetation modeling and understanding the global carbon cycle. It is also required by the United Nations and Intergovernmental Panel on Climate Change (IPCC) to provide a comprehensive analysis on estimates of terrestrial carbon fluxes for climate change reports. To improve the understanding of the carbon balance in Estonia, where forests cover over half of the land, a methodology has been worked out to map the changes in the forest biomass in yearly basis using satellite and forest inventory data. To assess the above-ground biomass in temperate deciduous, coniferous and mixed forest of Estonia, measurements and imagery from dual polarimetric L-band SAR (Synthetic Aperature Radar) and optical remote sensing satellites were used. A country-specific model allows easily regenerating the forest biomass estimations with the newest satellite data and producing up-to-date biomass maps that can be used to assist the national inventory reporting under the Intergovernmental Negotiating Committee for a Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol.

  1. Impact of biomass harvesting on forest soil productivity in the northern Rocky Mountains

    Science.gov (United States)

    Woongsoon Jang; Christopher R. Keyes; Deborah Page-Dumroese

    2015-01-01

    Biomass harvesting extracts an increased amount of organic matter from forest ecosystems over conventional harvesting. Since organic matter plays a critical role in forest productivity, concerns of potential negative long-term impacts of biomass harvesting on forest productivity (i.e., changing nutrient/water cycling, aggravating soil properties, and compaction) have...

  2. Evaluating forest biomass utilization in the Appalachians: A review of potential impacts and guidelines for management

    Science.gov (United States)

    Michael R. Vanderberg; Mary Beth Adams; Mark S. Wiseman

    2012-01-01

    Forests are important economic and ecological resources for both the Appalachian hardwood forest region and the country. Increased demand for woody biomass can be met, at least in part, by improved utilization of these resources. However, concerns exist about the impacts of increased intensity of woody biomass removal on the sustainability of forest ecosystems....

  3. Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality

    Science.gov (United States)

    Foster, Jane R.; D'Amato, Anthony W.; Bradford, John B.

    2014-01-01

    Forest biomass growth is almost universally assumed to peak early in stand development, near canopy closure, after which it will plateau or decline. The chronosequence and plot remeasurement approaches used to establish the decline pattern suffer from limitations and coarse temporal detail. We combined annual tree ring measurements and mortality models to address two questions: first, how do assumptions about tree growth and mortality influence reconstructions of biomass growth? Second, under what circumstances does biomass production follow the model that peaks early, then declines? We integrated three stochastic mortality models with a census tree-ring data set from eight temperate forest types to reconstruct stand-level biomass increments (in Minnesota, USA). We compared growth patterns among mortality models, forest types and stands. Timing of peak biomass growth varied significantly among mortality models, peaking 20–30 years earlier when mortality was random with respect to tree growth and size, than when mortality favored slow-growing individuals. Random or u-shaped mortality (highest in small or large trees) produced peak growth 25–30 % higher than the surviving tree sample alone. Growth trends for even-aged, monospecific Pinus banksiana or Acer saccharum forests were similar to the early peak and decline expectation. However, we observed continually increasing biomass growth in older, low-productivity forests of Quercus rubra, Fraxinus nigra, and Thuja occidentalis. Tree-ring reconstructions estimated annual changes in live biomass growth and identified more diverse development patterns than previous methods. These detailed, long-term patterns of biomass development are crucial for detecting recent growth responses to global change and modeling future forest dynamics.

  4. Looking for age-related growth decline in natural forests: unexpected biomass patterns from tree rings and simulated mortality.

    Science.gov (United States)

    Foster, Jane R; D'Amato, Anthony W; Bradford, John B

    2014-05-01

    Forest biomass growth is almost universally assumed to peak early in stand development, near canopy closure, after which it will plateau or decline. The chronosequence and plot remeasurement approaches used to establish the decline pattern suffer from limitations and coarse temporal detail. We combined annual tree ring measurements and mortality models to address two questions: first, how do assumptions about tree growth and mortality influence reconstructions of biomass growth? Second, under what circumstances does biomass production follow the model that peaks early, then declines? We integrated three stochastic mortality models with a census tree-ring data set from eight temperate forest types to reconstruct stand-level biomass increments (in Minnesota, USA). We compared growth patterns among mortality models, forest types and stands. Timing of peak biomass growth varied significantly among mortality models, peaking 20-30 years earlier when mortality was random with respect to tree growth and size, than when mortality favored slow-growing individuals. Random or u-shaped mortality (highest in small or large trees) produced peak growth 25-30% higher than the surviving tree sample alone. Growth trends for even-aged, monospecific Pinus banksiana or Acer saccharum forests were similar to the early peak and decline expectation. However, we observed continually increasing biomass growth in older, low-productivity forests of Quercus rubra, Fraxinus nigra, and Thuja occidentalis. Tree-ring reconstructions estimated annual changes in live biomass growth and identified more diverse development patterns than previous methods. These detailed, long-term patterns of biomass development are crucial for detecting recent growth responses to global change and modeling future forest dynamics.

  5. Lidar Estimation of Aboveground Biomass in a Tropical Coastal Forest of Gabon

    Science.gov (United States)

    Meyer, V.; Saatchi, S. S.; Poulsen, J.; Clark, C.; Lewis, S.; White, L.

    2012-12-01

    Estimation of tropical forest carbon stocks is a critical yet challenging problem from both ground surveys and remote sensing measurements. However, with its increasing importance in global climate mitigation and carbon cycle assessment, there is a need to develop new techniques to measure forest carbon stocks at landscape scales. Progresses have been made in terms of above ground biomass (AGB) monitoring techniques using ground measurements, with the development of tree allometry techniques. Besides, studies have shown that new remote sensing technologies such as Lidar can give accurate information on tree height and forest structure at a landscape level and can be very useful to estimate AGB. This study examines the ability of small footprint Lidar to estimate above ground biomass in Mondah forest, Gabon. Mondah forest is a coastal tropical forest that is partially flooded and includes areas of mangrove. Its mean annual temperature is 18.8C and mean annual precipitation is 2631mm/yr. Its proximity to the capital of Gabon, Libreville, makes it particularly subject to environmental pressure. The analysis is based on small footprint Lidar waveform information and relative height (RH) metrics that correspond to the percentiles of energy of the signal (25%, 50%, 75% and 100%). AGB estimation is calibrated with ground measurements. Ground-estimated AGB is calculated using allometric equations based on tree diameter, wood density and tree height. Lidar-derived AGB is calculated using a linear regression model between the four Lidar RH metrics and ground-estimated AGB and using available models developed in other tropical regions that use one height metric, average wood density, and tree stocking number. We present uncertainty of different approaches and discuss the universality of lidar biomass estimation models in tropical forests.

  6. VT0005 In Action: National Forest Biomass Inventory Using Airborne Lidar Sampling

    Science.gov (United States)

    Saatchi, S. S.; Xu, L.; Meyer, V.; Ferraz, A.; Yang, Y.; Shapiro, A.; Bastin, J. F.

    2016-12-01

    Tropical countries are required to produce robust and verifiable estimates of forest carbon stocks for successful implementation of climate change mitigation. Lack of systematic national inventory data due to access, cost, and infrastructure, has impacted the capacity of most tropical countries to accurately report the GHG emissions to the international community. Here, we report on the development of the aboveground forest carbon (AGC) map of Democratic Republic of Congo (DRC) by using the VCS (Verified Carbon Standard) methodology developed by Sassan Saatchi (VT0005) using high-resolution airborne LiDAR samples. The methodology provides the distribution of the carbon stocks in aboveground live trees of more than 150 million ha of forests at 1-ha spatial resolution in DRC using more than 430, 000 ha of systematic random airborne Lidar inventory samples of forest structure. We developed a LIDAR aboveground biomass allometry using more than 100 1-ha plots across forest types and power-law model with LIDAR height metrics and average landscape scale wood density. The methodology provided estimates of forest biomass over the entire country using two approaches: 1) mean, variance, and total carbon estimates for each forest type present in DRC using inventory statistical techniques, and 2) a wall-to-wall map of the forest biomass extrapolated using satellite radar (ALOS PALSAR), surface topography from SRTM, and spectral information from Landsat (TM) and machine learning algorithms. We present the methodology, the estimates of carbon stocks and the spatial uncertainty over the entire country. AcknowledgementsThe theoretical research was carried out partially at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration, and the design and implementation in the Democratic Republic of Congo was carried out at the Institute of Environment and Sustainability at University of California Los

  7. Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar

    Directory of Open Access Journals (Sweden)

    Cédric Véga

    2015-08-01

    Full Text Available Light Detection and Ranging (Lidar is a state of the art technology to assess forest aboveground biomass (AGB. To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level using point distributional approach (DM, canopy volume profile approach (CVP, 2D canopy grain approach (FOTO, and further evaluated the potential of a topographical complexity index (TCI to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP and horizontal (FOTO structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure.

  8. Inventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods

    Directory of Open Access Journals (Sweden)

    X. Tang

    2016-12-01

    Full Text Available Several comparative studies have reported that there can be great discrepancies between different methods used to estimate forest biomass. With the development of carbon markets, an accurate estimation at the regional scale (i.e. county level is becoming increasingly important for local government. In this study, we applied five methodologies [continuous biomass expansion factor (CBEF approach, mean biomass density (MB approach, mean biomass expansion factor (MBEF approach, national continuous biomass expansion factors (NCBEF proposed by Fang et al (2002, standard IPCC approach] to estimate the total biomass for Shitai County, China. The CBEF is generally considered to provide the most realistic estimates in term of regional biomass because CBEF reflects the change of BEF to stand density, stand age and site conditions. The forests of the whole county were divided into four forest types, namely Chinese fir plantations (CF, hardwood broadleaved forests (HB, softwood–broadleaved forests (SB and mason pine forests (MP according to the local forest management inventory of 2004. Generally, the MBEF approach overestimated forest biomass while the IPCC approach underestimated forest biomass for all forest types when CBEF derived biomass was used as a control. The MB approach provided the most similar biomass estimates for all forest types and could be an alternative approach when a CBEF equation is lacking in the study area. The total biomass derived from MBEF was highest at 1.44×107 t, followed by 1.32 ×107 t from CBEF, 1.31 ×107 t from NCBEF, 1.25 ×107 t from MB and 1.16 ×107 t from IPCC. Our results facilitate method selection for regional forest biomass estimation and provide statistical evidence for local government planning to enter the potential carbon market.

  9. Inventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods

    Directory of Open Access Journals (Sweden)

    X. Tang

    2016-12-01

    Full Text Available Several comparative studies have reported that there can be great discrepancies between different methods used to estimate forest biomass. With the development of carbon markets, an accurate estimation at the regional scale (i.e. county level is becoming increasingly important for local government. In this study, we applied five methodologies [continuous biomass expansion factor (CBEF approach, mean biomass density (MB approach, mean biomass expansion factor (MBEF approach, national continuous biomass expansion factors (NCBEF proposed by Fang et al (2002, standard IPCC approach] to estimate the total biomass for Shitai County, China. The CBEF is generally considered to provide the most realistic estimates in term of regional biomass because CBEF reflects the change of BEF to stand density, stand age and site conditions. The forests of the whole county were divided into four forest types, namely Chinese fir plantations (CF, hardwood broadleaved forests (HB, softwood–broadleaved forests (SB and mason pine forests (MP according to the local forest management inventory of 2004. Generally, the MBEF approach overestimated forest biomass while the IPCC approach underestimated forest biomass for all forest types when CBEF derived biomass was used as a control. The MB approach provided the most similar biomass estimates for all forest types and could be an alternative approach when a CBEF equation is lacking in the study area. The total biomass derived from MBEF was highest at 1.44×107 t, followed by 1.32 ×107 t from CBEF, 1.31 ×107 t from NCBEF, 1.25 ×107 t from MB and 1.16 ×107 t from IPCC. Our results facilitate method selection for regional forest biomass estimation and provide statistical evidence for local government planning to enter the potential carbon market.

  10. Forest biomass carbon stocks and variation in Tibet’s carbon-dense forests from 2001 to 2050

    Science.gov (United States)

    Sun, Xiangyang; Wang, Genxu; Huang, Mei; Chang, Ruiying; Ran, Fei

    2016-01-01

    Tibet’s forests, in contrast to China’s other forests, are characterized by primary forests, high carbon (C) density and less anthropogenic disturbance, and they function as an important carbon pool in China. Using the biomass C density data from 413 forest inventory sites and a spatial forest age map, we developed an allometric equation for the forest biomass C density and forest age to assess the spatial biomass C stocks and variation in Tibet’s forests from 2001 to 2050. The results indicated that the forest biomass C stock would increase from 831.1 Tg C in 2001 to 969.4 Tg C in 2050, with a net C gain of 3.6 Tg C yr−1 between 2001 and 2010 and a decrease of 1.9 Tg C yr−1 between 2040 and 2050. Carbon tends to allocate more in the roots of fir forests and less in the roots of spruce and pine forests with increasing stand age. The increase of the biomass carbon pool does not promote significant augmentation of the soil carbon pool. Our findings suggest that Tibet’s mature forests will remain a persistent C sink until 2050. However, afforestation or reforestation, especially with the larger carbon sink potential forest types, such as fir and spruce, should be carried out to maintain the high C sink capacity. PMID:27703215

  11. Pattern and dynamics of biomass stock in old growth forests: The role of habitat and tree size

    Science.gov (United States)

    Yuan, Zuoqiang; Gazol, Antonio; Wang, Xugao; Lin, Fei; Ye, Ji; Zhang, Zhaochen; Suo, YanYan; Kuang, Xu; Wang, Yunyun; Jia, Shihong; Hao, Zhanqing

    2016-08-01

    Forest ecosystems play a fundamental role in the global carbon cycle. However, how stand-level changes in tree age and structure influence biomass stock and dynamics in old-growth forests is a question that remains unclear. In this study, we quantified the aboveground biomass (AGB) standing stock, the coarse woody productivity (CWP), and the change in biomass over ten years (2004-2014) in a 25 ha unmanaged broad-leaved Korean pine mixed forest in northeastern China. In addition, we quantified how AGB stock and change (tree growth, recruitment and mortality) estimations are influenced by the variation in habitat heterogeneity, tree size structure and subplot size. Our analysis indicated that Changbai forest had AGB of 265.4 Mg ha-1 in 2004, and gained1.36 Mg ha-1 y-1 between 2004 and 2014. Despite recruitment having better performance in nutrient rich habitat, we found that there is a directional tree growth trend independent of habitat heterogeneity for available nutrients in this old growth forest. The observed increases in AGB stock (∼70%) are mainly attributed to the growth of intermediate size trees (30-70 cm DBH), indicating that this forest is still reaching its mature stage. Meanwhile, we indicated that biomass loss due to mortality reduces living biomass, not increment, may be the primary factor to affect forest biomass dynamics in this area. Also, spatial variation in forest dynamics is large for small sizes (i.e. coefficient of variation in 20 × 20 m subplots is 53.2%), and more than 90 percent of the inherent variability of these coefficients was predicted by a simple model including plot size. Our result provides a mean by which to estimate within-plot variability at a local scale before inferring any directional change in forest dynamics at a regional scale, and information about the variability of forest structure and dynamics are fundamental to design effective sampling strategies in future study.

  12. Mapping landscape scale variations of forest structure, biomass, and productivity in Amazonia

    Directory of Open Access Journals (Sweden)

    S. Saatchi

    2009-06-01

    Full Text Available Landscape and environmental variables such as topography, geomorphology, soil types, and climate are important factors affecting forest composition, structure, productivity, and biomass. Here, we combine a network of forest inventories with recently developed global data products from satellite observations in modeling the potential distributions of forest structure and productivity in Amazonia and examine how geomorphology, soil, and precipitation control these distributions. We use the RAINFOR network of forest plots distributed in lowland forests across Amazonia, and satellite observations of tree cover, leaf area index, phenology, moisture, and topographical variations. A maximum entropy estimation (Maxent model is employed to predict the spatial distribution of several key forest structure parameters: basal area, fraction of large trees, fraction of palms, wood density, productivity, and above-ground biomass at 5 km spatial resolution. A series of statistical tests at selected thresholds as well as across all thresholds and jackknife analysis are used to examine the accuracy of distribution maps and the relative contributions of environmental variables. The final maps were interpreted using soil, precipitation, and geomorphological features of Amazonia and it was found that the length of dry season played a key role in impacting the distribution of all forest variables except the wood density. Soil type had a significant impact on the wood productivity. Most high productivity forests were distributed either on less infertile soils of western Amazonia and Andean foothills, on crystalline shields, and younger alluvial deposits. Areas of low elevation and high density of small rivers of Central Amazonia showed distinct features, hosting mainly forests with low productivity and smaller trees.

  13. Problems in the inventory of the belowground forest biomass carbon stocks

    Directory of Open Access Journals (Sweden)

    Lasserre B

    2006-01-01

    Full Text Available Signatory countries of Kyoto Protocol are engaged in carrying out national inventories to quantify greenhouse gas emission and potentiality of C sinks. Forests represent the terrestrial ecosystem with the highest C sequestration capacity taking up CO2 from the atmosphere and fixing it in vegetal biomass through photosynthesis process; C stocks can be divided in aboveground and belowground ones. In inventorial processes, root biomass is empirically extrapolated from aboveground biomass using a 0.2 factor, which underestimate the real value. Some authors suggest that total underground C allocation can be assessed from the difference between annual respiration rate and litter fall. Belowground biomass can be divided in permanent biomass (structural roots and temporary one (fine roots. Models allow a valuation of structural roots biomass from stand dendrometrical characteristics. Literature reveals that underground biomass, as fine roots than structural ones, highly varies with local conditions. The development of models that take into account these station parameters and therefore able to reproduce this variability seems to be obligatory to deal with inventory processes with an acceptable precision.

  14. Estimation of biomass in wheat using random forest regression algorithm and remote sensing data

    Institute of Scientific and Technical Information of China (English)

    Li'ai Wang; Xudong Zhou; Xinkai Zhu; Zhaodi Dong; Wenshan Guo

    2016-01-01

    Wheat biomass can be estimated using appropriate spectral vegetation indices. However, the accuracy of estimation should be further improved for on-farm crop management. Previous studies focused on developing vegetation indices, however limited research exists on modeling algorithms. The emerging Random Forest (RF) machine-learning algorithm is regarded as one of the most precise prediction methods for regression modeling. The objectives of this study were to (1) investigate the applicability of the RF regression algorithm for remotely estimating wheat biomass, (2) test the performance of the RF regression model, and (3) compare the performance of the RF algorithm with support vector regression (SVR) and artificial neural network (ANN) machine-learning algorithms for wheat biomass estimation. Single HJ-CCD images of wheat from test sites in Jiangsu province were obtained during the jointing, booting, and anthesis stages of growth. Fifteen vegetation indices were calculated based on these images. In-situ wheat above-ground dry biomass was measured during the HJ-CCD data acquisition. The results showed that the RF model produced more accurate estimates of wheat biomass than the SVR and ANN models at each stage, and its robustness is as good as SVR but better than ANN. The RF algorithm provides a useful exploratory and predictive tool for estimating wheat biomass on a large scale in Southern China.

  15. Estimation of biomass in wheat using random forest regression algorithm and remote sensing data

    Institute of Scientific and Technical Information of China (English)

    Li’ai Wang; Xudong Zhou; Xinkai Zhu; Zhaodi Dong; Wenshan Guo

    2016-01-01

    Wheat biomass can be estimated using appropriate spectral vegetation indices.However,the accuracy of estimation should be further improved for on-farm crop management.Previous studies focused on developing vegetation indices,however limited research exists on modeling algorithms.The emerging Random Forest(RF) machine-learning algorithm is regarded as one of the most precise prediction methods for regression modeling.The objectives of this study were to(1) investigate the applicability of the RF regression algorithm for remotely estimating wheat biomass,(2) test the performance of the RF regression model,and(3) compare the performance of the RF algorithm with support vector regression(SVR) and artificial neural network(ANN) machine-learning algorithms for wheat biomass estimation.Single HJ-CCD images of wheat from test sites in Jiangsu province were obtained during the jointing,booting,and anthesis stages of growth.Fifteen vegetation indices were calculated based on these images.In-situ wheat above-ground dry biomass was measured during the HJ-CCD data acquisition.The results showed that the RF model produced more accurate estimates of wheat biomass than the SVR and ANN models at each stage,and its robustness is as good as SVR but better than ANN.The RF algorithm provides a useful exploratory and predictive tool for estimating wheat biomass on a large scale in Southern China.

  16. A Spatial Model of the Biomass to Energy Cycle

    DEFF Research Database (Denmark)

    Möller, Bernd

    2003-01-01

    by location. This paper aims to contribute to the development of a biomass to energy evaluation and mapping system, using geographical information systems (GIS). A GIS-based in-forest residue model considers forest growth and choice of harvest method. Data from a sawmill survey is used to assess sawmill resi...... and the costs of accumulated amounts of wood residues can now be calculated almost instantly for each location in the country. It is assumed that this approach will facilitate the assessment of future biomass markets....

  17. Comparative of remote sensing estimation models of winter wheat biomass based on random forest algorithm%基于随机森林算法的冬小麦生物量遥感估算模型对比

    Institute of Scientific and Technical Information of China (English)

    岳继博; 杨贵军; 冯海宽

    2016-01-01

    为了寻求高效的冬小麦生物量估算方法,该研究获取了2014年陕西省杨凌区拔节期、抽穗期和灌浆期的冬小麦生物量和对应的RADARSAT-2全极化雷达、GF1-WFV多光谱数据,并利用随机森林算法(random forest,RF)将光谱、雷达后向散射、光学植被指数和雷达植被指数结合进行冬小麦生物量回归建模。将相关系数分析(correlation coefficient, r)、袋外数据(out-of-bag data,OOB)重要性和灰色关联分析(grey relational analysis, GRA)与随机森林算法(RF)进行整合,构建了3种冬小麦生物量估算模型:r-RF、OOB-RF和GRA-RF,并分别利用3种估算模型对冬小麦生物量进行了估算。结果表明:r-RF、OOB-RF和GRA-RF3种模型分别采用3、4、10组数据时,验证决定系数分别为0.70、0.70和0.65,平均绝对误差分别为0.162、0.164和0.172 kg/m2,均方根误差分别为0.218、0.221和0.236 kg/m2,r-RF和OOB-RF比GRA-RF对冬小麦生物量有更好而的预测能力。研究结果证实了随机森林算法对冬小麦生物量进行遥感估算的潜力。%Biomass is one of important agricultural crop parameters, and has significant meanings in agriculture production management and decision-making. The estimated of biomass by remote sensing is of great importance for the real-time and dynamic crop information and can be acquired by remote sensing detection technology. The random forest algorithm (RF), from which machine learning is used, shows considerable potential for estimated crop parameters. However, there has been little study on estimation of crop parameters by RF model, especially using a combined of optical and SAR Data. In this study, we focused on analyzing different RF models data selection impact on the accuracy of estimation winter wheat biomass using spectral reflectance, radar backscatter, spectral Vis (Vegetation Indices) and radar Vis. In this paper, RF model, optical and SAR data were

  18. Carbon, energy and forest biomass: new opportunities and needs for forest management in Italy

    Directory of Open Access Journals (Sweden)

    2005-01-01

    Full Text Available Forest biomass provides a relevant fraction of world energy needs, not only in developing Countries. In Italy, several factors are presently contributing to a new interest for this resource, ranging from regulatory quotas for renewables to the increasing price of fossil fuel to the emergence of a European carbon stock exchange. This focus on renewable resources constitutes an important opportunity for the forest sector and for society by and large, but because of the potential dimensions of the emerging market it also requires new planning instruments, in order to avoid a sudden and widespread resumption of coppice management and a reduction of standing carbon stock in forest ecosystems, which would run contrary to the objectives of the Kyoto Protocol. An example of the future demand for biomasses in Central Italy is presented, based on the possible use of fuelwood in new coal-fired power plants by the 'co-firing' technology.

  19. 基于生态过程模型和森林清查数据的森林生长量估算对比研究%Comparison of estimated forest biomass increment rate based on a process-based ecological model and forest inventory data

    Institute of Scientific and Technical Information of China (English)

    李登秋; 居为民; 郑光; 柳艺博; 昝梅; 张春华; 黄金龙

    2013-01-01

    Based on a remote sensing driven, processed-based ecological model (Boreal Ecosystem Productivity Simulator, BEPS), National Forest Continues Inventory (NFCI) data (surveyed in 2001 and 2006) and Forest Management Inventory (FMI) data (surveyed in 2003 and 2009), the forest annual biomass increment rate in Ji’an city was calculated, respectively. The differences among the forest biomass increment rates estimated using these three different methods were analyzed for various spatial scales and forest types. Our results showed that at the plot scale the forest biomass increment rate (4.18 Mg·hm-2·a-1) simulated by the BEPS model was close to the overstory biomass increment rate (OBIR, 4.29 Mg·hm-2·a-1), and lower than the biome biomass increment rate (BBIR, 5.86 Mg·hm-2·a-1) estimated using the NFCI data. The R2 of OBIR and BBIR simulated by the BEPS model against estimates with the NFCI data were 0.43 and 0.48, respectively. The regional mean forest biomass increment rate simulated by the BEPS model was 4.65 Mg·hm-2·a-1 while the OBIR and BBIR estimated using the FMI data were 4.36 and 3.34 Mg·hm-2·a-1, respectively. The R2 values of county-level forest biomass increment rate simulated by the BEPS model against OBIR and BBIR were 0.84 (p<0.01) and 0.83 (p<0.01), respectively. The OBIR and BBIR estimated using the NFCI data were higher than those estimated using the FMI data. The forest biomass increment rate simulated by BEPS modeled was close to the OBIR value based on NFCI and the CBIR value based on FMI. As to two dominant forest types, evergreen broadleaf forests grow faster than evergreen coniferous forests. The agreement between simulated and estimated forest biomass increment rate is better for evergreen coniferous forests than for evergreen broadleaf forests. This study confirms that the output from BEPS can be used for updating forest biomass.%利用遥感驱动的生态过程模型-Boreal Ecosystem Productivity Simulator (BEPS)、2001-2006年

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

    Science.gov (United States)

    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.

  1. Modelling in forest management

    Science.gov (United States)

    Mark J. Twery

    2004-01-01

    Forest management has traditionally been considered management of trees for timber. It really includes vegetation management and land management and people management as multiple objectives. As such, forest management is intimately linked with other topics in this volume, most especially those chapters on ecological modelling and human dimensions. The key to...

  2. 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

  3. 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.

  4. Estimation of LAI and above-ground biomass in deciduous forests: Western Ghats of Karnataka, India

    Science.gov (United States)

    Madugundu, Rangaswamy; Nizalapur, Vyjayanthi; Jha, Chandra Shekhar

    2008-06-01

    This study demonstrates the potentials of IRS P6 LISS-IV high-resolution multispectral sensor (IGFOV ˜ 6 m)-based estimation of biomass in the deciduous forests in the Western Ghats of Karnataka, India. Regression equations describing the relationship between IRS P6 LISS-IV data-based vegetation index (NDVI) and field measured leaf area index (ELAI) and estimated above-ground biomass (EAGB) were derived. Remote sensing (RS) data-based leaf area index (PLAI) image is generated using regression equation based on NDVI and ELAI ( r2 = 0.68, p ≤ 0.05). RS-based above-ground biomass (PAGB) image was generated based on regression equation developed between PLAI and EAGB ( r2 = 0.63, p ≤ 0.05). The mean value of estimated above-ground biomass and RS-based above-ground biomass in the study area are 280(±72.5) and 297.6(±55.2) Mg ha -1, respectively. The regression models generated in the study between NDVI and LAI; LAI and biomass can also help in generating spatial biomass map using RS data alone. LISS-IV-based estimation of biophysical parameters can also be used for the validation of various coarse resolution satellite products derived from the ground-based measurements alone.

  5. Closing a gap in tropical forest biomass estimation: accounting for crown mass variation in pantropical allometries

    Science.gov (United States)

    Ploton, P.; Barbier, N.; Momo, S. T.; Réjou-Méchain, M.; Boyemba Bosela, F.; Chuyong, G.; Dauby, G.; Droissart, V.; Fayolle, A.; Goodman, R. C.; Henry, M.; Kamdem, N. G.; Katembo Mukirania, J.; Kenfack, D.; Libalah, M.; Ngomanda, A.; Rossi, V.; Sonké, B.; Texier, N.; Thomas, D.; Zebaze, D.; Couteron, P.; Berger, U.; Pélissier, R.

    2015-12-01

    Accurately monitoring tropical forest carbon stocks is an outstanding challenge. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference in the coming years. However, this reference model shows a systematic bias for the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass dataset on 673 trees measured in five tropical countries (101 trees > 100 cm in diameter) and an original dataset of 130 forest plots (1 ha) from central Africa to quantify the error of biomass allometric models at the individual and plot levels when explicitly accounting or not accounting for crown mass variations. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees Accounting for a crown mass proxy in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error from -23-16 to 0-10 %. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by accounting for a crown mass proxy for the largest trees in a stand, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

  6. Transport and supply logistics of biomass fuels: Vol. 2. Biomass and strategic modelling

    Energy Technology Data Exchange (ETDEWEB)

    Allen, J.; Browne, M.; Cook, A.; Wicks, N.; Palmer, H.; Hunter, A.; Boyd, J.

    1996-10-01

    This document forms part of the United Kingdom Department of Trade and Industry project ''Transport and Logistics of Biomass Fuels'', which aimed to describe the distribution of existing and potential biomass resources in terms of their supply potential for power stations. Fixed areas of supply, or catchments, have been identified on colour maps of Britain showing the distribution of forest fuel, short rotation coppices, and various types of straw and animal slurry, using a specially written strategic modelling program. Adequate supplies of biomass resources are shown to exist in Britain, but siting of power stations to exploit these resources, will depend on transport and economic considerations appropriate at the time of construction. Biomass power stations in the megawatt capacity range could be resourced. (UK)

  7. Portable in-woods pyrolysis: Using forest biomass to reduce forest fuels, increase soil productivity, and sequester carbon

    Science.gov (United States)

    Deborah Page-Dumroese; Mark Coleman; Greg Jones; Tyron Venn; R. Kasten Dumroese; Nathanial Anderson; Woodam Chung; Dan Loeffler; Jim Archuleta; Mark Kimsey; Phil Badger; Terry Shaw; Kristin McElligott

    2009-01-01

    We describe the use of an in-woods portable pyrolysis unit that converts forest biomass to bio-oil and the application of the byproduct bio-char in a field trial. We also discuss how in-woods processing may reduce the need for long haul distances of lowvalue woody biomass and eliminate open, currently wasteful burning of forest biomass. If transportation costs can be...

  8. Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica

    Science.gov (United States)

    Dubayah, R. O.; Sheldon, S. L.; Clark, D. B.; Hofton, M. A.; Blair, J. B.; Hurtt, G. C.; Chazdon, R. L.

    2010-06-01

    In this paper we present the results of an experiment to measure forest structure and biomass dynamics over the tropical forests of La Selva Biological Station in Costa Rica using a medium resolution lidar. Our main objective was to observe changes in forest canopy height, related height metrics, and biomass, and from these map sources and sinks of carbon across the landscape. The Laser Vegetation Imaging Sensor (LVIS) measured canopy structure over La Selva in 1998 and again in 2005. Changes in waveform metrics were related to field-derived changes in estimated aboveground biomass from a series of old growth and secondary forest plots. Pairwise comparisons of nearly coincident lidar footprints between years showed canopy top height changes that coincided with expected changes based on land cover types. Old growth forests had a net loss in height of -0.33 m, while secondary forests had net gain of 2.08 m. Multiple linear regression was used to relate lidar metrics with biomass changes for combined old growth and secondary forest plots, giving an r2 of 0.65 and an RSE of 10.5 Mg/ha, but both parametric and bootstrapped confidence intervals were wide, suggesting weaker model performance. The plot level relationships were then used to map biomass changes across La Selva using LVIS at a 1 ha scale. The spatial patterns of biomass changes matched expected patterns given the distribution of land cover types at La Selva, with secondary forests showing a gain of 25 Mg/ha and old growth forests showing little change (2 Mg/ha). Prediction intervals were calculated to assess uncertainty for each 1 ha cell to ascertain whether the data and methods used could confidently estimate the sign (source or sink) of the biomass changes. The resulting map showed most of the old growth areas as neutral (no net biomass change), with widely scattered and isolated sources and sinks. Secondary forests in contrast were mostly sinks or neutral, but were never sources. By quantifying both the

  9. Carbon Sequestration Potential in Aboveground Biomass of Hybrid Eucalyptus Plantation Forest

    Directory of Open Access Journals (Sweden)

    Siti Latifah

    2013-04-01

    Full Text Available Forests are a significant part of the global carbon cycle. Forests sequester carbon by conducting photosynthesis, which is the process of converting light energy to chemical energy and storing it in the chemical bonds of sugar. Carbon sequestration through forestry has the potential to play a significant role in ameliorating global environmental problems such as atmospheric accumulation of GHG's and climate change.  The present investigation was carried out to determine carbon sequestration potential of hybrid Eucalyptus. This study was conducted primarily to develop a prediction model of carbon storage capacity for plantation forest of hybrid Eucalyptus in Aek Nauli, Simalungun District, North Sumatera. Models were tested and assessed for statistical validity and accuracy in predicting biomass and carbon, based on determination coefficient (R and correlation coefficient (r, aggregative deviation percentage (AgD, and the average deviation percentage (AvD. The best general model to estimate the biomass of hybrid Eucalyptus was Y = 1351,09x^0,876. e^(0,094.  Results showed that hybrid Eucalyptus had an average above-ground biomass in year 0 (the land without the eucalyptus trees up to year 3 as large as 1.36, 11.56, 43.18, and 63.84 t ha. The carbon content of hybrid Eucalyptus were 0.61, 5.2, 19.43 t^(-1, and 28,73  t^(-1 C ha while the carbon sequestration potential were 2.23, 19.08, 71.31, and 105.43 t^(-1 CO  ha^(-1 respectively.Keywords: biomass, carbon stock, model, hybrid Eucalyptus, plantation forest

  10. Closing a gap in tropical forest biomass estimation: accounting for crown mass variation in pantropical allometries

    Directory of Open Access Journals (Sweden)

    P. Ploton

    2015-12-01

    Full Text Available Accurately monitoring tropical forest carbon stocks is an outstanding challenge. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference in the coming years. However, this reference model shows a systematic bias for the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass dataset on 673 trees measured in five tropical countries (101 trees > 100 cm in diameter and an original dataset of 130 forest plots (1 ha from central Africa to quantify the error of biomass allometric models at the individual and plot levels when explicitly accounting or not accounting for crown mass variations. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees 1 Mg and reduced the range of plot-level error from −23–16 to 0–10 %. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by accounting for a crown mass proxy for the largest trees in a stand, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

  11. The potential of random forest and neural networks for biomass and recombinant protein modeling in Escherichia coli fed-batch fermentations.

    Science.gov (United States)

    Melcher, Michael; Scharl, Theresa; Spangl, Bernhard; Luchner, Markus; Cserjan, Monika; Bayer, Karl; Leisch, Friedrich; Striedner, Gerald

    2015-09-01

    Product quality assurance strategies in production of biopharmaceuticals currently undergo a transformation from empirical "quality by testing" to rational, knowledge-based "quality by design" approaches. The major challenges in this context are the fragmentary understanding of bioprocesses and the severely limited real-time access to process variables related to product quality and quantity. Data driven modeling of process variables in combination with model predictive process control concepts represent a potential solution to these problems. The selection of statistical techniques best qualified for bioprocess data analysis and modeling is a key criterion. In this work a series of recombinant Escherichia coli fed-batch production processes with varying cultivation conditions employing a comprehensive on- and offline process monitoring platform was conducted. The applicability of two machine learning methods, random forest and neural networks, for the prediction of cell dry mass and recombinant protein based on online available process parameters and two-dimensional multi-wavelength fluorescence spectroscopy is investigated. Models solely based on routinely measured process variables give a satisfying prediction accuracy of about ± 4% for the cell dry mass, while additional spectroscopic information allows for an estimation of the protein concentration within ± 12%. The results clearly argue for a combined approach: neural networks as modeling technique and random forest as variable selection tool.

  12. Potential aboveground biomass in drought-prone forest used for rangeland pastoralism.

    Science.gov (United States)

    Fensham, R J; Fairfax, R J; Dwyer, J M

    2012-04-01

    The restoration of cleared dry forest represents an important opportunity to sequester atmospheric carbon. In order to account for this potential, the influences of climate, soils, and disturbance need to be deciphered. A data set spanning a region defined the aboveground biomass of mulga (Acacia aneura) dry forest and was analyzed in relation to climate and soil variables using a Bayesian model averaging procedure. Mean annual rainfall had an overwhelmingly strong positive effect, with mean maximum temperature (negative) and soil depth (positive) also important. The data were collected after a recent drought, and the amount of recent tree mortality was weakly positively related to a measure of three-year rainfall deficit, and maximum temperature (positive), soil depth (negative), and coarse sand (negative). A grazing index represented by the distance of sites to watering points was not incorporated by the models. Stark management contrasts, including grazing exclosures, can represent a substantial part of the variance in the model predicting biomass, but the impact of management was unpredictable and was insignificant in the regional data set. There was no evidence of density-dependent effects on tree mortality. Climate change scenarios represented by the coincidence of historical extreme rainfall deficit with extreme temperature suggest mortality of 30.1% of aboveground biomass, compared to 21.6% after the recent (2003-2007) drought. Projections for recovery of forest using a mapping base of cleared areas revealed that the greatest opportunities for restoration of aboveground biomass are in the higher-rainfall areas, where biomass accumulation will be greatest and droughts are less intense. These areas are probably the most productive for rangeland pastoralism, and the trade-off between pastoral production and carbon sequestration will be determined by market forces and carbon-trading rules.

  13. Near isometric biomass partitioning in forest ecosystems of China.

    Science.gov (United States)

    Hui, Dafeng; Wang, Jun; Shen, Weijun; Le, Xuan; Ganter, Philip; Ren, Hai

    2014-01-01

    Based on the isometric hypothesis, belowground plant biomass (MB) should scale isometrically with aboveground biomass (MA) and the scaling exponent should not vary with environmental factors. We tested this hypothesis using a large forest biomass database collected in China. Allometric scaling functions relating MB and MA were developed for the entire database and for different groups based on tree age, diameter at breast height, height, latitude, longitude or elevation. To investigate whether the scaling exponent is independent of these biotic and abiotic factors, we analyzed the relationship between the scaling exponent and these factors. Overall MB was significantly related to MA with a scaling exponent of 0.964. The scaling exponent of the allometric function did not vary with tree age, density, latitude, or longitude, but varied with diameter at breast height, height, and elevation. The mean of the scaling exponent over all groups was 0.986. Among 57 scaling relationships developed, 26 of the scaling exponents were not significantly different from 1. Our results generally support the isometric hypothesis. MB scaled near isometrically with MA and the scaling exponent did not vary with tree age, density, latitude, or longitude, but increased with tree size and elevation. While fitting a single allometric scaling relationship may be adequate, the estimation of MB from MA could be improved with size-specific scaling relationships.

  14. Development of a Methodology for Mapping Forest Height and Biomass Using Satellite Based SAR and Lidar Data

    Science.gov (United States)

    Hilbert, Claudia; Schmullius, Christiane

    2010-12-01

    This paper presents first results of a study investigating satellite, multifrequent radar and lidar data for characterising the three-dimensional forest structure. Biomass is an important structural parameter to asses the carbon pool of forests. The synergy of lidar and SAR data for forest biomass mapping is promising. The study introduced here aims to combine TerraSAR-X, ALOS PALSAR and ICESat/GLAS data. Some preliminary results for the test site in Thuringian Forest, a low mountain range in eastern Germany, with a focus on the GLAS data will be described. Two methods for filtering invalid GLAS shots are investigated. Moreover, different ICESat/GLAS waveforms parameters were calculated and compared to an airborne lidar based Digital Height Model (DHM) and a forest inventory data base.

  15. Development of Allometric Equations for Estimating Above-Ground Liana Biomass in Tropical Primary and Secondary Forests, Malaysia

    Directory of Open Access Journals (Sweden)

    Patrick Addo-Fordjour

    2013-01-01

    Full Text Available The study developed allometric equations for estimating liana stem and total above-ground biomass in primary and secondary forests in the Penang National Park, Penang, Malaysia. Using biomass-diameter-length data of 60 liana individuals representing 15 species, allometric equations were developed for liana stem biomass and total above-ground biomass (TAGB. Three types of allometric equations were developed: models fitted to untransformed, weighted, and log-transformed (log10 data. There was a significant linear relationship between biomass and the predictors (diameter, length, and/or their combinations. The same set of models was developed for primary and secondary forests due to absence of differences in regression line slopes of the forests (ANCOVA: . The coefficients of determination values of the models were high (stem: 0.861 to 0.990; TAGB: 0.900 to 0.992. Generally, log-transformed models showed better fit (Furnival's index, FI 0.5. A comparison of the best TAGB model in this study (based on FI with previously published equations indicated that most of the equations significantly ( overestimated TAGB of lianas. However, a previous equation from Southeast Asia estimated TAGB similar to that of the current equation (. Therefore, regional or intracontinental equations should be preferred to intercontinental equations when estimating liana biomass.

  16. 异速模型评估森林植被生物量有机碳储量%Allometric models to estimate biomass organic carbon stock in forest vegetation

    Institute of Scientific and Technical Information of China (English)

    Mohammed Alamgir; M. Al-Amin

    2008-01-01

    在孟加拉的吉大港南部森林地区,利用异速模型评估森林植被的有机碳的储量.异速模型被分别应用测试树木(被划分两个胸高直径级)、灌木和草本植物.采用基部面积估算胸高直径级为从> 5 cm 到 ≤ 15 cm 和> 15 cm树木的生物量有机碳储量模型最好,分别有很高的决定系数(胸高直径级> 5 cm 到 ≤ 15 cm 的r2 为0.73697,胸高直径级> 15 cm 的r2为0.87703),且回归系数(P = 0.000)显著.其它模型(包括采用树高,胸高直径,树高和胸高直径,以及综合树高、胸高直径和木材密度)的线性和对数关系都表现出很低的决定系数.分别建立了20种优势树种的异速模型,采用树木基部面积的模型都得到很高的决定系数值.单独采用灌木和草本植物总生物量的异速模型有较高的决定系数(灌木的r2 为0.87948,草本植物的r2 为0.87325),且回归(系数)性显著(P = 0.000).生物量有机碳的评估是复杂的和耗时的研究,本研究所建立的异速模型可以应用于孟加拉和其它热带(地区)国家的森林植被的有机碳储量的测算.%A study was conducted in the forest area of Chittagong (South) Forest Division, Chittagong, Bangladesh for developing allometric models to estimate biomass organic carbon stock in the forest vegetation. Allometric models were tested separately for trees (divided into two DBH classes), shrubs, herbs and grasses. Model using basal area alone was found to be the best predictor of biomass organic carbon stock in trees because of high coefficient of determination (r2 is 0.73697 and 0.87703 for > 5 cm to ≤ 15 cm and > 15 cm DBH (diameter at breast height) rang, respectively) and significance of regression (P is 0.000 for each DBH range) coefficients for both DBH range. The other models using height alone; DBH alone; height and DBH together; height, DBH and wood density; with liner and logarithmic relations produced relatively poor coefficient of determination

  17. Demographic Drivers of Aboveground Biomass Dynamics During Secondary Succession in Neotropical Dry and Wet Forests

    NARCIS (Netherlands)

    Rozendaal, Danaë M.A.; Chazdon, Robin L.; Arreola-Villa, Felipe; Balvanera, Patricia; Bentos, Tony V.; Dupuy, Juan M.; Hernández-Stefanoni, J.L.; Jakovac, Catarina C.; Lebrija-Trejos, Edwin E.; Lohbeck, Madelon; Martínez-Ramos, Miguel; Massoca, Paulo E.S.; Meave, Jorge A.; Mesquita, Rita C.G.; Mora, Francisco; Pérez-García, Eduardo A.; Romero-Pérez, I.E.; Saenz-Pedroza, Irving; Breugel, van Michiel; Williamson, G.B.; Bongers, Frans

    2016-01-01

    The magnitude of the carbon sink in second-growth forests is expected to vary with successional biomass dynamics resulting from tree growth, recruitment, and mortality, and with the effects of climate on these dynamics. We compare aboveground biomass dynamics of dry and wet Neotropical forests, b

  18. Stand density index as a tool to assess the maximization of forest carbon and biomass

    Science.gov (United States)

    Christopher W. Woodall; Anthony W. D’Amato; John B. Bradford; Andrew O. Finley

    2012-01-01

    Given the ability of forests to mitigate greenhouse gas emissions and provide feedstocks to energy utilities, there is an emerging need to assess forest biomass/carbon accretion opportunities over large areas. Techniques for objectively quantifying stand stocking of biomass/carbon are lacking for large areas given the complexity of tree species composition in the U.S....

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

    Directory of Open Access Journals (Sweden)

    Lobna Zribi

    2016-07-01

    Full Text Available 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. Keywords: Tree biomass; disturbance; allometry; cork oak forests; soil organic carbon stock.

  20. National-scale estimates of forest root biomass carbon stocks and associated carbon fluxes in Canada

    Science.gov (United States)

    Smyth, C. E.; Kurz, W. A.; Neilson, E. T.; Stinson, G.

    2013-12-01

    forests play an important role in the global carbon cycle through carbon (C) storage and C exchange with the atmosphere. While estimates of aboveground biomass have been improving, little is known about belowground C storage in root biomass. Here we estimated the contribution of roots to the C budget of Canada's 2.3 × 106 km2 managed forests from 1990 to 2008 using the empirical modeling approach of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) driven by detailed forestry data sets from the National Forest C Monitoring, Accounting and Reporting System. The estimated average net primary production (NPP) during this period was 809 Tg C yr-1 (352 g C m2 yr-1) with root growth and replacement of turnover contributing 39.8 % of NPP. Average heterotrophic respiration (Rh) was 738 Tg C yr-1 (321 g C m-2 yr-1), which resulted in a net ecosystem production (NEP) value of 31 g C m-2 yr-1(71 Tg C yr-1), and on average only 8.7% of NPP remained in the system as NEP. Estimated average root C stocks were 2.38 Pg (1235 g C m-2), mostly in coarse roots (≥ 5 mm diameter), and had an average root to shoot percentage (belowground to aboveground biomass) of 25.6%. Detailed monitoring of C exchange between forests and the atmosphere and an improved understanding of the belowground processes and their response to environmental changes are needed to improve our understanding of the terrestrial C budget.

  1. Reclamation of coppice forests in order to increase the potential of woody biomass in Serbia

    Science.gov (United States)

    Bjelanovic, I.; Krstic, M.

    2012-04-01

    Biomass makes 63% of the total renewable energy potential of Serbia. Here, the biomass from forests together with wood processing industry waste represent the second most important renewable source for energy production. The Action Plan for Biomass of Serbia (2010) shows that the technically exploitable biomass in the Republic of Serbia amounts annually 2.7 Mtoe. Here, the woody biomass (fuelwood, forest residue, wood processing industry residue, wood from trees outside the forest) accounts for 1.0 Mtoe while the rest originates from agricultural sources. According to the national forest inventory (2008), forest cover in Serbia accounts for 29% of the country area, having standing volume of 362.5 mil. m3 and annual increment of 9.1 mil. m3. More than half is state-owned and the rest 47% is in the private ownership. Coppice forests dominate in the forest stock (65%). According to Glavonjić (2010), northeastern and southwestern Serbia are the regions with greatest spatial forest distribution. The general forest condition is characterised by insufficient production volume, unsatisfactory stock density and forest cover, high percentage of degraded forests, unfavorable age structure, unfavorable health condition and weeded areas. Herewith, the basic measures for the improvement of forest fund (Forestry Development Strategy for Serbia, 2006) represent conversion of coppice forests, increase of forest cover and productivity of forest ecosystems by the ecologically, economically and socially acceptable methods. The actions include reclamation of degraded forests, re- and afforestation activities on abandoned agricultural, degraded and other treeless lands. The average standing volume of high forests is 254 m3·ha-1 with an annual increment of 5.5 m3·ha-1. On the contrary, coppice forests dispose 124 m3·ha-1 of standing volume, having an annual increment of 3.1 m3·ha-1. Here, estimated losses from coppice forests amount up to 3.5 mil. m3 wood annually. These data

  2. Does species richness affect fine root biomass and production in young forest plantations?

    DEFF Research Database (Denmark)

    Domisch, Timo; Finér, Leena; Dawud, Seid Muhie;

    2015-01-01

    species composition from fine root biomass samples with the near-infrared reflectance spectroscopy method. We did not observe higher biomass or production in mixed stands compared to monocultures. Neither did we observe any differences in tree root length or fine root turnover. One reason for this could......Tree species diversity has been reported to increase forest ecosystem above-ground biomass and productivity, but little is known about below-ground biomass and production in diverse mixed forests compared to single-species forests. For testing whether species richness increases below-ground biomass...... and production and thus complementarity between forest tree species in young stands, we determined fine root biomass and production of trees and ground vegetation in two experimental plantations representing gradients in tree species richness. Additionally, we measured tree fine root length and determined...

  3. Logistics of supplying biomass from a mountain pine beetle-infested forest to a power plant in British Columbia

    Energy Technology Data Exchange (ETDEWEB)

    Mahmoudi, Mohammadhossein; Sowlati, Taraneh (Depts. of Wood Science, Univ. of British Columbia, Vancouver (Canada)); Sokhansanj, Shahab (Chemical and Biological Engineering, Univ. of British Columbia, Vancouver (Canada))

    2009-03-15

    The search for alternative energy sources has increased the interest in forest biomass. During the past few years, the severe infestation of the mountain pine beetle (MPB) within the forests of interior British Columbia (BC) has led to huge volumes of dead wood that exceed the capacity of the lumber industry. One way to make the most value of the surplus wood is to use it as the feedstock for bioenergy. The high costs associated with harvest and transport, and uncertainty in supply logistics are issues related to forest biomass utilization. This paper presents the development of a forest biomass supply logistics simulation model and its application to a case of supplying MPB-killed biomass from Quesnel timber supply area (one of the most infested areas in the interior BC) to a potential 300 MW power plant adjacent to the city of Quesnel. It provides values of quantity, cost and moisture content of biomass which are important factors in feasibility study of bioenergy projects. In the case of a conventional harvesting system, the biomass recovered from roadside residues in 1 year will meet only about 30% of the annual demand of the power plant with an estimated delivered cost of Can $45 per oven-dry tonne of woodchips. Sensitivity analyses were also performed

  4. Review and analysis of biomass gasification models

    DEFF Research Database (Denmark)

    Puig Arnavat, Maria; Bruno, Joan Carles; Coronas, Alberto

    2010-01-01

    The use of biomass as a source of energy has been further enhanced in recent years and special attention has been paid to biomass gasification. Due to the increasing interest in biomass gasification, several models have been proposed in order to explain and understand this complex process, and th...

  5. The Potential of Forest Biomass Inversion Based on Vegetation Indices Using Multi-Angle CHRIS/PROBA Data

    Directory of Open Access Journals (Sweden)

    Qiang Wang

    2016-10-01

    Full Text Available Multi-angle remote sensing can either be regarded as an added source of uncertainty for variable retrieval, or as a source of additional information, which enhances variable retrieval compared to traditional single-angle observation. However, the magnitude of these angular and band effects for forest structure parameters is difficult to quantify. We used the Discrete Anisotropic Radiative Transfer (DART model and the Zelig model to simulate the forest canopy Bidirectional Reflectance Distribution Factor (BRDF in order to build a look-up table, and eight vegetation indices were used to assess the relationship between BRDF and forest biomass in order to find the sensitive angles and bands. Further, the European Space Agency (ESA mission, Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy (CHRIS-PROBA and field sample measurements, were selected to test the angular and band effects on forest biomass retrieval. The results showed that the off-nadir vegetation indices could predict the forest biomass more accurately than the nadir. Additionally, we found that the viewing angle effect is more important, but the band effect could not be ignored, and the sensitive angles for extracting forest biomass are greater viewing angles, especially around the hot and dark spot directions. This work highlighted the combination of angles and bands, and found a new index based on the traditional vegetation index, Atmospherically Resistant Vegetation Index (ARVI, which is calculated by combining sensitive angles and sensitive bands, such as blue band 490 nm/−55°, green band 530 nm/55°, and the red band 697 nm/55°, and the new index was tested to improve the accuracy of forest biomass retrieval. This is a step forward in multi-angle remote sensing applications for mining the hidden relationship between BRDF and forest structure information, in order to increase the utilization efficiency of remote sensing data.

  6. Evaluation of forest structure, biomass and carbon sequestration in subtropical pristine forests of SW China.

    Science.gov (United States)

    Nizami, Syed Moazzam; Yiping, Zhang; Zheng, Zheng; Zhiyun, Lu; Guoping, Yang; Liqing, Sha

    2017-03-01

    Very old natural forests comprising the species of Fagaceae (Lithocarpus xylocarpus, Castanopsis wattii, Lithocarpus hancei) have been prevailing since years in the Ailaoshan Mountain Nature Reserve (AMNR) SW China. Within these forest trees, density is quite variable. We studied the forest structure, stand dynamics and carbon density at two different sites to know the main factors which drives carbon sequestration process in old forests by considering the following questions: How much is the carbon density in these forest trees of different DBH (diameter at breast height)? How much carbon potential possessed by dominant species of these forests? How vegetation carbon is distributed in these forests? Which species shows high carbon sequestration? What are the physiochemical properties of soil in these forests? Five-year (2005-2010) tree growth data from permanently established plots in the AMNR was analysed for species composition, density, stem diameter (DBH), height and carbon (C) density both in aboveground and belowground vegetation biomass. Our study indicated that among two comparative sites, overall 54 species of 16 different families were present. The stem density, height, C density and soil properties varied significantly with time among the sites showing uneven distribution across the forests. Among the dominant species, L. xylocarpus represents 30% of the total carbon on site 1 while C. wattii represents 50% of the total carbon on site 2. The average C density ranged from 176.35 to 243.97 t C ha(-1). The study emphasized that there is generous degree to expand the carbon stocking in this AMNR through scientific management gearing towards conservation of old trees and planting of potentially high carbon sequestering species on good site quality areas.

  7. Synthesis and analysis of biomass and net primary productivity in Chinese forests

    OpenAIRE

    Ni, Jian; Zhang, Xin-Shi; Scurlock, Jonathan

    2001-01-01

    International audience; An extant dataset is presented on biomass and net primary productivity (NPP) of 6 forest biomes, including 690 stands from 17 forest types of China. Data on latitude, longitude, elevation, field measurements of stand age, leaf area index (LAI) and total biomass were collected for 29 provinces from forestry inventory data of the Forestry Ministry of China, as well as a wide range of published literature. The individual site-based NPP was estimated from field biomass mea...

  8. Tree diversity, composition, forest structure and aboveground biomass dynamics after single and repeated fire in a Bornean rain forest.

    Science.gov (United States)

    Slik, J W Ferry; Bernard, Caroline S; Van Beek, Marloes; Breman, Floris C; Eichhorn, Karl A O

    2008-12-01

    Forest fires remain a devastating phenomenon in the tropics that not only affect forest structure and biodiversity, but also contribute significantly to atmospheric CO2. Fire used to be extremely rare in tropical forests, leaving ample time for forests to regenerate to pre-fire conditions. In recent decades, however, tropical forest fires occur more frequently and at larger spatial scales than they used to. We studied forest structure, tree species diversity, tree species composition, and aboveground biomass during the first 7 years since fire in unburned, once burned and twice burned forest of eastern Borneo to determine the rate of recovery of these forests. We paid special attention to changes in the tree species composition during burned forest regeneration because we expect the long-term recovery of aboveground biomass and ecosystem functions in burned forests to largely depend on the successful regeneration of the pre-fire, heavy-wood, species composition. We found that forest structure (canopy openness, leaf area index, herb cover, and stem density) is strongly affected by fire but shows quick recovery. However, species composition shows no or limited recovery and aboveground biomass, which is greatly reduced by fire, continues to be low or decline up to 7 years after fire. Consequently, large amounts of the C released to the atmosphere by fire will not be recaptured by the burned forest ecosystem in the near future. We also observed that repeated fire, with an inter-fire interval of 15 years, does not necessarily lead to a huge deterioration in the regeneration potential of tropical forest. We conclude that burned forests are valuable and should be conserved and that long-term monitoring programs in secondary forests are necessary to determine their recovery rates, especially in relation to aboveground biomass accumulation.

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

    OpenAIRE

    Köhler, P.; Huth, A.

    2010-01-01

    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 degr...

  10. 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.

  11. Stakeholder perspectives on converting forest biomass to energy in Oregon, USA

    Energy Technology Data Exchange (ETDEWEB)

    Stidham, Melanie; Simon-Brown, Viviane [Department of Forest Ecosystems and Society, College of Forestry, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331 (United States)

    2011-01-15

    Within the state of Oregon, USA, there is considerable interest in the possibility of converting forest biomass to energy. A number of studies have assessed the technical feasibility of forest biomass energy, but few have focused on social aspects, an important consideration in projects involving public forests. This study explores the social context of converting forest biomass to energy, using qualitative research methods. Semi-structured interviews were conducted with forty individuals representing nine different stakeholder groups. Information gained through interviews was used to understand stakeholder views on forest biomass energy, including their perspectives on potential barriers and opportunities in Oregon. Findings indicate the most challenging barrier will be access to long-term, consistent supply. A related challenge is the long history of contention between parties over forest products coming from public lands. However, findings also show that there are many areas of common ground between these groups that have historically been at odds, such as agreement on the necessity of restoration treatments in certain forest types, the by-product of which could be used for biomass generation. Potential conflicts still exist, for instance over projects in mixed conifer forests. Development of policies and projects through inclusive, collaborative approaches could alleviate controversies, potentially allowing more activities to move forward. Information provided by this research creates a foundation for discussions as forest biomass energy becomes an increasingly prominent issue in Oregon, the western USA, and other regions of the world. (author)

  12. Mixed multi-scalar methods to assess wood biomass availability on family forests in Virginia's Southside

    Science.gov (United States)

    M. D. Brinckman; J. F. Munsell

    2009-01-01

    Interest in wood-based bio-energy production systems is increasing. Multiscalar, mixed-method approaches focusing on both biophysical and social aspects of procurable feedstock are needed. Family forests will likely play an important role in supplying forest-based biomass. However, access depends in large part on the management trends among family forest owners. This...

  13. Biomass and Carbon Stocks of Sofala Bay Mangrove Forests

    Directory of Open Access Journals (Sweden)

    Almeida A. Sitoe

    2014-08-01

    Full Text Available Mangroves could be key ecosystems in strategies addressing the mitigation of climate changes through carbon storage. However, little is known regarding the carbon stocks of these ecosystems, particularly below-ground. This study was carried out in the mangrove forests of Sofala Bay, Central Mozambique, with the aim of quantifying carbon stocks of live and dead plant and soil components. The methods followed the procedures developed by the Center for International Forestry Research (CIFOR for mangrove forests. In this study, we developed a general allometric equation to estimate individual tree biomass and soil carbon content (up to 100 cm depth. We estimated the carbon in the whole mangrove ecosystem of Sofala Bay, including dead trees, wood debris, herbaceous, pneumatophores, litter and soil. The general allometric equation for live trees derived was [Above-ground tree dry weight (kg = 3.254 × exp(0.065 × DBH], root mean square error (RMSE = 4.244, and coefficient of determination (R2 = 0.89. The average total carbon storage of Sofala Bay mangrove was 218.5 Mg·ha−1, of which around 73% are stored in the soil. Mangrove conservation has the potential for REDD+ programs, especially in regions like Mozambique, which contains extensive mangrove areas with high deforestation and degradation rates.

  14. Optimal Wavelength Selection on Hyperspectral Data with Fused Lasso for Biomass Estimation of Tropical Rain Forest

    Science.gov (United States)

    Takayama, T.; Iwasaki, A.

    2016-06-01

    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.

  15. 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.

  16. 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)

  17. The Price of Precision: Large-Scale Mapping of Forest Structure and Biomass Using Airborne Lidar

    Science.gov (United States)

    Dubayah, R.

    2015-12-01

    Lidar remote sensing provides one of the best means for acquiring detailed information on forest structure. However, its application over large areas has been limited largely because of its expense. Nonetheless, extant data exist over many states in the U.S., funded largely by state and federal consortia and mainly for infrastructure, emergency response, flood plain and coastal mapping. These lidar data are almost always acquired in leaf-off seasons, and until recently, usually with low point count densities. Even with these limitations, they provide unprecedented wall-to-wall mappings that enable development of appropriate methodologies for large-scale deployment of lidar. In this talk we summarize our research and lessons learned in deriving forest structure over regional areas as part of NASA's Carbon Monitoring System (CMS). We focus on two areas: the entire state of Maryland and Sonoma County, California. The Maryland effort used low density, leaf-off data acquired by each county in varying epochs, while the on-going Sonoma work employs state-of-the-art, high density, wall-to-wall, leaf-on lidar data. In each area we combine these lidar coverages with high-resolution multispectral imagery from the National Agricultural Imagery Program (NAIP) and in situ plot data to produce maps of canopy height, tree cover and biomass, and compare our results against FIA plot data and national biomass maps. Our work demonstrates that large-scale mapping of forest structure at high spatial resolution is achievable but products may be complex to produce and validate over large areas. Furthermore, fundamental issues involving statistical approaches, plot types and sizes, geolocation, modeling scales, allometry, and even the definitions of "forest" and "non-forest" must be approached carefully. Ultimately, determining the "price of precision", that is, does the value of wall-to-wall forest structure data justify their expense, should consider not only carbon market applications

  18. 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

  19. Discrimination between acute and chronic decline of Central European forests using map algebra of the growth condition and forest biomass fuzzy sets: A case study.

    Science.gov (United States)

    Samec, Pavel; Caha, Jan; Zapletal, Miloš; Tuček, Pavel; Cudlín, Pavel; Kučera, Miloš

    2017-12-01

    Forest decline is either caused by damage or else by vulnerability due to unfavourable growth conditions or due to unnatural silvicultural systems. Here, we assess forest decline in the Czech Republic (Central Europe) using fuzzy functions, fuzzy sets and fuzzy rating of ecosystem properties over a 1×1km grid. The model was divided into fuzzy functions of the abiotic predictors of growth conditions (Fpred including temperature, precipitation, acid deposition, soil data and relative site insolation) and forest biomass receptors (Frec including remote sensing data, density and volume of aboveground biomass, and surface humus chemical data). Fuzzy functions were designed at the limits of unfavourable, undetermined or favourable effects on the forest ecosystem health status. Fuzzy sets were distinguished through similarity in a particular membership of the properties at the limits of the forest status margins. Fuzzy rating was obtained from the least difference of Fpred-Frec. Unfavourable Fpred within unfavourable Frec indicated chronic damage, favourable Fpred within unfavourable Frec indicated acute damage, and unfavourable Fpred within favourable Frec indicated vulnerability. The model in the 1×1km grid was validated through spatial intersection with a point field of uniform forest stands. Favourable status was characterised by soil base saturation (BS)>50%, BCC/Al>1, Corg>1%, MgO>6g/kg, and nitrogen deposition<1200mol(H(+))/ha·year. Vulnerable forests had BShumus 46-60%, BCC/Al 9-20 and NDVI≈0.42. Chronic forest damage occurs in areas with low temperatures, high nitrogen deposition, and low soil BS and Corg levels. In the Czech Republic, 10% of forests were considered non-damaged and 77% vulnerable, with damage considered acute in 7% of forests and chronic in 5%. The fuzzy model used suggests that improvement in forest health will depend on decreasing environmental load and restoration concordance between growth conditions and tree species composition

  20. Hydrological modelling in forested systems

    Science.gov (United States)

    This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological p...

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Total aboveground biomass (TAGB) estimation using IFSAR: speckle noise effect on TAGB in tropical forest

    Science.gov (United States)

    Misbari, S.; Hashim, M.

    2014-02-01

    Total Aboveground Biomass (TAGB) estimation is critically important to enhance understanding of dynamics of carbon fluxes between atmosphere and terrestrial ecosystem. For humid tropical forest, it is a challenging task for researchers due to complex canopy structure and predominant cloud cover. Optical sensors are only able to sense canopy crown. In contrast, radar technology is able to sense sub-canopy structure of the forest with penetration ability through the cloud for precise biomass estimation with validation from field data including diameter at breast height (DBH) of trees. This study is concerned about estimation of TAGB through the utilization of Interferometry Synthetic Aperture Radar (IFSAR). Based on this study, it is found that the stand parameters such as DBH and backscattered on IFSAR image has high correlation, R2=0.6411. The most suitable model for TAGB estimation on IFSAR is Chave Model with R2=0.9139. This study analyzes the impact brought by speckle noises on IFSAR image. It is found that filtering process has improves TAGB estimation about +30% using several filtering schemes especially Gamma filter for 11×11 window size. Using field data obtained from a primary tropical forest at Gerik, Perak, TAGBestimation can be validated and the assessment has been carried out.

  3. Low-Density LiDAR and Optical Imagery for Biomass Estimation over Boreal Forest in Sweden

    Directory of Open Access Journals (Sweden)

    Iurii Shendryk

    2014-05-01

    Full Text Available Knowledge of the forest biomass and its change in time is crucial to understanding the carbon cycle and its interactions with climate change. LiDAR (Light Detection and Ranging technology, in this respect, has proven to be a valuable tool, providing reliable estimates of aboveground biomass (AGB. The overall goal of this study was to develop a method for assessing AGB using a synergy of low point density LiDAR-derived point cloud data and multi-spectral imagery in conifer-dominated forest in the southwest of Sweden. Different treetop detection algorithms were applied for forest inventory parameter extraction from a LiDAR-derived canopy height model. Estimation of AGB was based on the power functions derived from tree parameters measured in the field, while vegetation classification of a multi-spectral image (SPOT-5 was performed in order to account for dependences of AGB estimates on vegetation types. Linear regression confirmed good performance of a newly developed grid-based approach for biomass estimation (R2 = 0.80. Results showed AGB to vary from below 1 kg/m2 in very young forests to 94 kg/m2 in mature spruce forests, with RMSE of 4.7 kg/m2. These AGB estimates build a basis for further studies on carbon stocks as well as for monitoring this forest ecosystem in respect of disturbance and change in time. The methodology developed in this study can be easily adopted for assessing biomass of other conifer-dominated forests on the basis of low-density LiDAR and multispectral imagery. This methodology is hence of much wider applicability than biomass derivation based on expensive and currently still scarce high-density LiDAR data.

  4. Integration of biomass data in the dynamic vegetation model ORCHIDEE

    Science.gov (United States)

    Delbart, N.; Viovy, N.; Ciais, P.; Le Toan, T.

    2009-04-01

    Dynamic vegetation models (DVMs) are aimed at estimating exchanges between the terrestrial vegetated surface and the atmosphere, and the spatial distribution of natural vegetation types. For this purpose, DVMs use the climatic data alone to feed the vegetation process equations. As dynamic models, they can also give predictions under the current and the future climatic conditions. However, they currently lack accuracy in locating carbon stocks, sinks and sources, and in getting the correct magnitude. Consequently they have been essentially used to compare the vegetation responses under different scenarii. The assimilation of external data such as remote sensing data has been shown to improve the simulations. For example, the land cover maps are used to force the correct distribution of plant functional types (PFTs), and the leaf area index data is used to force the photosynthesis processes. This study concerns the integration of biomass data within the DVM ORCHIDEE. The objective here is to have the living carbon stocks with the correct magnitude and the correct location. Carbon stocks depend on interplay of carbon assimilated by photosynthesis, and carbon lost by respiration, mortality and disturbance. Biomass data can therefore be used as one essential constraint on this interplay. In this study, we use a large database provided by in-situ measurements of carbon stocks and carbon fluxes of old growth forests to constraint this interplay. For each PFT, we first adjust the simulated photosynthesis by reducing the mean error with the in situ measurements. Then we proceed similarly to adjust the autotrophic respiration. We then compare the biomass measured, and adjust the mortality processes in the model. Second, when processes are adjusted for each PFT to minimize the mean error on the carbon stock, biomass measurements can be assimilated. This assimilation is based on the hypothesis that the main variable explaining the biomass level at a given location is the age

  5. Does the disturbance hypothesis explain the biomass increase in basin-wide Amazon forest plot data?

    OpenAIRE

    Gloor, M.; Phillips, Oliver L.; Lloyd, J.; Lewis, Simon L.; Malhi, Y; Baker, T. R.; Lopez Gonzalez, G.; J. Peacock; Almeida, S; Alves de Oliveira, Atila Cristina; Alvarez, E; Amaral, Ieda; Arroyo, L.; Aymard, Gerardo; Banki, Olaf

    2009-01-01

    Positive aboveground biomass trends have been reported from old-growth forests across the Amazon basin and hypothesized to reflect a large-scale response to exterior forcing. The result could, however, be an artefact due to a sampling bias induced by the nature of forest growth dynamics. Here, we characterize statistically the disturbance process in Amazon old-growth forests as recorded in 135 forest plots of the RAINFOR network up to 2006, and other independent research programmes, and explo...

  6. 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...

  7. A novel statistical methodology to overcome sampling irregularities in the forest inventory data and to model forest changes under dynamic disturbance regimes

    Science.gov (United States)

    Nikolay Strigul; Jean. Lienard

    2015-01-01

    Forest inventory datasets offer unprecedented opportunities to model forest dynamics under evolving environmental conditions but they are analytically challenging due to irregular sampling time intervals of the same plot, across the years. We propose here a novel method to model dynamic changes in forest biomass and basal area using forest inventory data. Our...

  8. Harvesting forest biomass for energy in Minnesota: An assessment of guidelines, costs and logistics

    Science.gov (United States)

    Saleh, Dalia El Sayed Abbas Mohamed

    The emerging market for renewable energy in Minnesota has generated a growing interest in utilizing more forest biomass for energy. However, this growing interest is paralleled with limited knowledge of the environmental impacts and cost effectiveness of utilizing this resource. To address environmental and economic viability concerns, this dissertation has addressed three areas related to biomass harvest: First, existing biomass harvesting guidelines and sustainability considerations are examined. Second, the potential contribution of biomass energy production to reduce the costs of hazardous fuel reduction treatments in these trials is assessed. Third, the logistics of biomass production trials are analyzed. Findings show that: (1) Existing forest related guidelines are not sufficient to allow large-scale production of biomass energy from forest residue sustainably. Biomass energy guidelines need to be based on scientific assessments of how repeated and large scale biomass production is going to affect soil, water and habitat values, in an integrated and individual manner over time. Furthermore, such guidelines would need to recommend production logistics (planning, implementation, and coordination of operations) necessary for a potential supply with the least site and environmental impacts. (2) The costs of biomass production trials were assessed and compared with conventional treatment costs. In these trials, conventional mechanical treatment costs were lower than biomass energy production costs less income from biomass sale. However, a sensitivity analysis indicated that costs reductions are possible under certain site, prescriptions and distance conditions. (3) Semi-structured interviews with forest machine operators indicate that existing fuel reduction prescriptions need to be more realistic in making recommendations that can overcome operational barriers (technical and physical) and planning and coordination concerns (guidelines and communications

  9. Forest feedstocks : systems for recovery of residual biomass

    Energy Technology Data Exchange (ETDEWEB)

    MacDonald, J. [FP Innovations, Vancouver, BC (Canada). FERIC Div.

    2007-07-01

    Interest in forest feedstock is growing due to high energy costs, the need for energy self-sufficiency and climate change issues. The Mountain Pine Beetle (MPB) epidemic in British Columbia has also contributed to the growing interest in forest feedstock. This presentation discussed the potential for wood to be used for liquid fuels conversion, pellets and biorefineries. The extraction of energy from residue biomass was reviewed with reference to traditional sources such as hog fuel and black liquor, as well as new sources that consider the changing landscape. These include harvest residues, MPB-killed stands, burned stands, non-merchantable stands, and stumps. Early thinning and FireSmart treatments were outlined along with the value of purpose-grown energy plantations. The variety of available recovery methods and equipment was demonstrated, including whole-tree chippers; disc and drum chippers; grinders and shredders; overhead conveyor systems; blower attachments; and, wheel-mounted equipment. The performance of each method and equipment was reviewed along with challenges regarding the transportation of a low-value, low bulk-density material over long distances. Although residue bundlers have been developed, it was suggested that it may be more cost effective to convert the feedstock in the field using a mobile biorefinery, and then transport the denser fuel. It was shown that although a range of equipment is available, nothing has been designed specifically for full-tree residue. It was noted that coordination with conventional harvesting is desirable, but may not be possible in all cases. Lessons from studies have indicated that the distance from the mill is a major cost factor and that the debris should be prepared in advance to shipping. tabs., figs.

  10. Environmental and economic suitability of forest biomass-based bioenergy production in the Southern United States

    Science.gov (United States)

    Dwivedi, Puneet

    This study attempts to ascertain the environmental and economic suitability of utilizing forest biomass for cellulosic ethanol production in the Southern United States. The study is divided into six chapters. The first chapter details the background and defines the relevance of the study along with objectives. The second chapter reviews the existing literature to ascertain the present status of various existing conversion technologies. The third chapter assesses the net energy ratio and global warming impact of ethanol produced from slash pine (Pinus elliottii Engelm.) biomass. A life-cycle assessment was applied to achieve the task. The fourth chapter assesses the role of emerging bioenergy and voluntary carbon markets on the profitability of non-industrial private forest (NIPF) landowners by combining the Faustmann and Hartmann models. The fifth chapter assesses perceptions of four stakeholder groups (Non-Government Organization, Academics, Industries, and Government) on the use of forest biomass for bioenergy production in the Southern United States using the SWOT-AHP (Strength, Weakness, Opportunity, and Threat-Analytical Hierarchy Process) technique. Finally, overall conclusions are made in the sixth chapter. Results indicate that currently the production of cellulosic ethanol is limited as the production cost of cellulosic ethanol is higher than the production cost of ethanol derived from corn. However, it is expected that the production cost of cellulosic ethanol will come down in the future from its current level due to ongoing research efforts. The total global warming impact of E85 fuel (production and consumption) was found as 10.44 tons where as global warming impact of an equivalent amount of gasoline (production and consumption) was 21.45 tons. This suggests that the production and use of ethanol derived from slash pine biomass in the form of E85 fuel in an automobile saves about 51% of carbon emissions when compared to gasoline. The net energy ratio

  11. Impact of forest biomass residues to the energy supply chain on regional air quality.

    Science.gov (United States)

    Rafael, S; Tarelho, L; Monteiro, A; Sá, E; Miranda, A I; Borrego, C; Lopes, M

    2015-02-01

    The increase of the share of renewable energy in Portugal can be met from different sources, of which forest biomass residues (FBR) can play a main role. Taking into account the demand for information about the strategy of FBR to energy, and its implications on the Portuguese climate policy, the impact of energy conversion of FBR on air quality is evaluated. Three emission scenarios were defined and a numerical air quality model was selected to perform this evaluation. The results reveal that the biomass thermal plants contribute to an increment of the pollutant concentrations in the atmosphere, however restricted to the surrounding areas of the thermal plants, and most significant for NO₂ and O₃. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data

    CSIR Research Space (South Africa)

    Ramoelo, Abel

    2015-12-01

    Full Text Available and biomass can be used as indicators of rangeland quality and quantity. Conventional methods for assessing these vegetation parameters at landscape scale level is time consuming and tedious. Remote sensing provides a bird-eye view of the landscape, which...

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

    Science.gov (United States)

    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...

  14. Interest of Integrating Spaceborne LiDAR Data to Improve the Estimation of Biomass in High Biomass Forested Areas

    Directory of Open Access Journals (Sweden)

    Mohammad El Hajj

    2017-02-01

    Full Text Available Mapping forest AGB (Above Ground Biomass is of crucial importance to estimate the carbon emissions associated with tropical deforestation. This study proposes a method to overcome the saturation at high AGB values of existing AGB map (Vieilledent’s AGB map by using a map of correction factors generated from GLAS (Geoscience Laser Altimeter System spaceborne LiDAR data. The Vieilledent’s AGB map of Madagascar was established using optical images, with parameters calculated from the SRTM Digital Elevation Model, climatic variables, and field inventories. In the present study, first, GLAS LiDAR data were used to obtain a spatially distributed (GLAS footprints geolocation estimation of AGB (GLAS AGB covering Madagascar forested areas, with a density of 0.52 footprint/km2. Second, the difference between the AGB from the Vieilledent’s AGB map and GLAS AGB at each GLAS footprint location was calculated, and additional spatially distributed correction factors were obtained. Third, an ordinary kriging interpolation was thus performed by taking into account the spatial structure of these additional correction factors to provide a continuous correction factor map. Finally, the existing and the correction factor maps were summed to improve the Vieilledent’s AGB map. The results showed that the integration of GLAS data improves the precision of Vieilledent’s AGB map by approximately 7 t/ha. By integrating GLAS data, the RMSE on AGB estimates decreases from 81 t/ha (R2 = 0.62 to 74.1 t/ha (R2 = 0.71. Most importantly, we showed that this approach using LiDAR data avoids underestimating high biomass values (new maximum AGB of 650 t/ha compared to 550 t/ha with the first approach.

  15. Species-specific fine root biomass distribution alters competition in mixed forests under climate change

    Science.gov (United States)

    Reyer, Christopher; Gutsch, Martin; Lasch, Petra; Suckow, Felicitas; Sterck, Frank; Mohren, Frits

    2010-05-01

    The importance of mixed forests in European silviculture has increased due to forest conversion policies and multifunctional forest management. Concurrently, evidences for substantial impacts of climate change on forest ecosystems accumulate. Projected drier and warmer conditions alter the water relations of tree species, their growth and ultimately their inter-specific competition in mixed stands. Process-based models are scientific tools to study the impact of climate change on and to deepen the understanding of the functioning of these systems based on ecological mechanisms. They allow for long-term, stand-level studies of forest dynamics which could only be addressed with great difficulty in an experimental or empirical setup. We used the process-based forest model 4C to simulate inter-specific competition in mixed stands of Douglas-fir (Pseudotsuga menziesii) and Common beech (Fagus sylvatica) as well as Scots pine (Pinus sylvestris) and Sessile / Pedunculate oak (Quercus petraea and Quercus robur) under a) historical climate for model verification and b) under climate change scenario realizations of the climate model STAR 2.0 in Brandenburg, Germany. Some of the climate change scenario realizations feature a substantially drier and warmer summer climate which decreases the climatic water balance during the growing season. We assumed species-specific fine root biomass distributions which feature broadleaved fine roots in deeper soil layers and coniferous fine roots in upper soil layers according to several root excavation studies from mixed stands. The stands themselves were constructed from yield tables of the contributing species. The model verification provided good results for the basal area predictions under the historical climate. Under climate change, the number of days when the tree water demand exceeded the soil water supply was higher for the coniferous species than for broadleaved species. Furthermore, after 45 simulation years the basal area

  16. Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China

    Directory of Open Access Journals (Sweden)

    Zhenfeng Shao

    2016-06-01

    Full Text Available Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively dense vegetation areas, and microwave backscattering is significantly influenced by the underlying soil when the vegetation coverage is low. Both of these conditions decrease the estimation accuracy of forest biomass. A new optical and microwave integrated vegetation index (VI was proposed based on observations from both field experiments and satellite (Landsat 8 Operational Land Imager (OLI and RADARSAT-2 data. According to the difference in interaction between the multispectral reflectance and microwave backscattering signatures with biomass, the combined VI (COVI was designed using the weighted optical optimized soil-adjusted vegetation index (OSAVI and microwave horizontally transmitted and vertically received signal (HV to overcome the disadvantages of both data types. The performance of the COVI was evaluated by comparison with those of the sole optical data, Synthetic Aperture Radar (SAR data, and the simple combination of independent optical and SAR variables. The most accurate performance was obtained by the models based on the COVI and optical and microwave optimal variables excluding OSAVI and HV, in combination with a random forest algorithm and the largest number of reference samples. The results also revealed that the predictive accuracy depended highly on the statistical method and the number of sample units. The validation indicated that this integrated method of determining the new VI is a good synergistic way to combine both optical and microwave information for the accurate estimation of forest biomass.

  17. Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China.

    Science.gov (United States)

    Shao, Zhenfeng; Zhang, Linjing

    2016-06-07

    Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively dense vegetation areas, and microwave backscattering is significantly influenced by the underlying soil when the vegetation coverage is low. Both of these conditions decrease the estimation accuracy of forest biomass. A new optical and microwave integrated vegetation index (VI) was proposed based on observations from both field experiments and satellite (Landsat 8 Operational Land Imager (OLI) and RADARSAT-2) data. According to the difference in interaction between the multispectral reflectance and microwave backscattering signatures with biomass, the combined VI (COVI) was designed using the weighted optical optimized soil-adjusted vegetation index (OSAVI) and microwave horizontally transmitted and vertically received signal (HV) to overcome the disadvantages of both data types. The performance of the COVI was evaluated by comparison with those of the sole optical data, Synthetic Aperture Radar (SAR) data, and the simple combination of independent optical and SAR variables. The most accurate performance was obtained by the models based on the COVI and optical and microwave optimal variables excluding OSAVI and HV, in combination with a random forest algorithm and the largest number of reference samples. The results also revealed that the predictive accuracy depended highly on the statistical method and the number of sample units. The validation indicated that this integrated method of determining the new VI is a good synergistic way to combine both optical and microwave information for the accurate estimation of forest biomass.

  18. Modelling of biomass utilization for energy purpose

    Energy Technology Data Exchange (ETDEWEB)

    Grzybek, Anna (ed.)

    2010-07-01

    the overall farms structure, farms land distribution on several separate subfields for one farm, villages' overpopulation and very high employment in agriculture (about 27% of all employees in national economy works in agriculture). Farmers have low education level. In towns 34% of population has secondary education and in rural areas - only 15-16%. Less than 2% inhabitants of rural areas have higher education. The structure of land use is as follows: arable land 11.5%, meadows and pastures 25.4%, forests 30.1%. Poland requires implementation of technical and technological progress for intensification of agricultural production. The reason of competition for agricultural land is maintenance of the current consumption level and allocation of part of agricultural production for energy purposes. Agricultural land is going to be key factor for biofuels production. In this publication research results for the Project PL0073 'Modelling of energetical biomass utilization for energy purposes' have been presented. The Project was financed from the Norwegian Financial Mechanism and European Economic Area Financial Mechanism. The publication is aimed at moving closer and explaining to the reader problems connected with cultivations of energy plants and dispelling myths concerning these problems. Exchange of fossil fuels by biomass for heat and electric energy production could be significant input in carbon dioxide emission reduction. Moreover, biomass crop and biomass utilization for energetical purposes play important role in agricultural production diversification in rural areas transformation. Agricultural production widening enables new jobs creation. Sustainable development is going to be fundamental rule for Polish agriculture evolution in long term perspective. Energetical biomass utilization perfectly integrates in the evolution frameworks, especially on local level. There are two facts. The fist one is that increase of interest in energy crops in Poland

  19. Modelling of biomass utilization for energy purpose

    Energy Technology Data Exchange (ETDEWEB)

    Grzybek, Anna (ed.)

    2010-07-01

    the overall farms structure, farms land distribution on several separate subfields for one farm, villages' overpopulation and very high employment in agriculture (about 27% of all employees in national economy works in agriculture). Farmers have low education level. In towns 34% of population has secondary education and in rural areas - only 15-16%. Less than 2% inhabitants of rural areas have higher education. The structure of land use is as follows: arable land 11.5%, meadows and pastures 25.4%, forests 30.1%. Poland requires implementation of technical and technological progress for intensification of agricultural production. The reason of competition for agricultural land is maintenance of the current consumption level and allocation of part of agricultural production for energy purposes. Agricultural land is going to be key factor for biofuels production. In this publication research results for the Project PL0073 'Modelling of energetical biomass utilization for energy purposes' have been presented. The Project was financed from the Norwegian Financial Mechanism and European Economic Area Financial Mechanism. The publication is aimed at moving closer and explaining to the reader problems connected with cultivations of energy plants and dispelling myths concerning these problems. Exchange of fossil fuels by biomass for heat and electric energy production could be significant input in carbon dioxide emission reduction. Moreover, biomass crop and biomass utilization for energetical purposes play important role in agricultural production diversification in rural areas transformation. Agricultural production widening enables new jobs creation. Sustainable development is going to be fundamental rule for Polish agriculture evolution in long term perspective. Energetical biomass utilization perfectly integrates in the evolution frameworks, especially on local level. There are two facts. The fist one is that increase of interest in energy crops in Poland

  20. 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; L. Poorter

    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...

  1. Database of 478 allometric equations to estimate biomass for Mexican trees and forests

    OpenAIRE

    Rojas-García, Fabiola; Bernardus H. J. De Jong; Martínez-Zurimendí, Pablo; Paz-Pellat, Fernando

    2015-01-01

    International audience; Key messageWe present a comprehensive database of 478 allometric equations to estimate biomass of trees and other life forms in Mexican forest and scrubland ecosystems.ContextAccurate estimation of standing biomass in forests is a prerequisite for any approach to carbon storage and a number of additional applications.AimsTo provide a comprehensive database with allometric equations applicable to a large number of tree and shrub species of Mexico.MethodsAn intensive lit...

  2. Forest Structure, Composition and Above Ground Biomass of Tree Community in Tropical Dry Forests of Eastern Ghats, India

    Directory of Open Access Journals (Sweden)

    Sudam Charan SAHU

    2016-03-01

    Full Text Available The study of biomass, structure and composition of tropical forests implies also the investigation of forest productivity, protection of biodiversity and removal of CO2 from the atmosphere via C-stocks. The hereby study aimed at understanding the forest structure, composition and above ground biomass (AGB of tropical dry deciduous forests of Eastern Ghats, India, where as a total of 128 sample plots (20 x 20 meters were laid. The study showed the presence of 71 tree species belonging to 57 genera and 30 families. Dominant tree species was Shorea robusta with an importance value index (IVI of 40.72, while Combretaceae had the highest family importance value (FIV of 39.01. Mean stand density was 479 trees ha-1 and a basal area of 15.20 m2 ha-1. Shannon’s diversity index was 2.01 ± 0.22 and Simpson’s index was 0.85 ± 0.03. About 54% individuals were in the size between 10 and 20 cm DBH, indicating growing forests. Mean above ground biomass value was 98.87 ± 68.8 Mg ha-1. Some of the dominant species that contributed to above ground biomass were Shorea robusta (17.2%, Madhuca indica (7.9%, Mangifera indica (6.9%, Terminalia alata (6.9% and Diospyros melanoxylon (4.4%, warranting extra efforts for their conservation. The results suggested that C-stocks of tropical dry forests can be enhanced by in-situ conserving the high C-density species and also by selecting these species for afforestation and stand improvement programs. Correlations were computed to understand the relationship between above ground biomass, diversity indices, density and basal area, which may be helpful for implementation of REDD+ (reduce emissions from deforestation and forest degradation, and foster conservation, sustainable management of forests and enhancement of forest carbon stocks scheme.

  3. 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.

  4. Cross-Sectoral Resource Management: How Forest Management Alternatives Affect the Provision of Biomass and Other Ecosystem Services

    Directory of Open Access Journals (Sweden)

    Susanne Frank

    2015-02-01

    Full Text Available Integrated forest management is faced with the challenge that the contribution of forests to economic and ecological planning targets must be assessed in a socio-ecological system context. This paper introduces a way to model spatio-temporal dynamics of biomass production at a regional scale in order to derive land use strategies that enhance biomass provision and avoid trade-offs for other ecosystem services. The software platform GISCAME was employed to bridge the gap between local land management decisions and regional planning by linking growth and yield models with an integrative mesoscale modeling and assessment approach. The model region is located in Saxony, Germany. Five scenarios were simulated, which aimed at testing different alternatives for adapted land use in the context of climate change and increasing biomass demand. The results showed, for example, that forest conversion towards climate-change-adapted forest types had positive effects on ecological integrity and landscape aesthetics. In contrast, negative impacts on landscape aesthetics must be expected if agricultural sites were converted into short rotation coppices. Uncertainties with stem from assumptions regarding growth and yield models were discussed. Future developmental steps which consider, for example, accessibility of the resources were identified.

  5. Northern Forest Ecosystem Dynamics Using Coupled Models and Remote Sensing

    Science.gov (United States)

    Ranson, K. J.; Sun, G.; Knox, R. G.; Levine, E. R.; Weishampel, J. F.; Fifer, S. T.

    1999-01-01

    Forest ecosystem dynamics modeling, remote sensing data analysis, and a geographical information system (GIS) were used together to determine the possible growth and development of a northern forest in Maine, USA. Field measurements and airborne synthetic aperture radar (SAR) data were used to produce maps of forest cover type and above ground biomass. These forest attribute maps, along with a conventional soils map, were used to identify the initial conditions for forest ecosystem model simulations. Using this information along with ecosystem model results enabled the development of predictive maps of forest development. The results obtained were consistent with observed forest conditions and expected successional trajectories. The study demonstrated that ecosystem models might be used in a spatial context when parameterized and used with georeferenced data sets.

  6. [Biomass and carbon storage of ground bryophytes under six types of young coniferous forest plantations].

    Science.gov (United States)

    Bao, Weikai; Lei, Bo; Leng, Li

    2005-10-01

    This paper studied the biomass and carbon storage of the ground bryophytes under young Picea balfouriana (P), Pinus tabulaeformis (Y), Pinus armandii (H), Larix kaempferi (L), Picea balfouriana-Pinus tabulaeformis (P-Y), and Pinus tabulaeformis-Pinus armandii (Y-H) forest plantations in the upper reach of Minjiang River, Sichuan Province. The results showed that total biomass and carbon storage of ground bryophytes were relatively low, being 3.11 - 460.36 kg x hm(-2) and 1.12 +/- 0.03 x 168.95 +/- 0.92 kg x hm(-2), respectively. On plot level, only the bryophyte biomass between forest P and others, and the carbon storage between forest L and others were significantly different. The ground bryophyte had the highest biomass and carbon storage under forest P, while the lowest ones under forest H. Comprehensive analysis suggested that forest type and its structural feature might be the important factors determining the biomass and carbon storage of ground bryophytes, and thinning was an important measure to improve ground bryophyte growth and biomass production.

  7. Building mixed effect models of stand biomass for Simao pine (Pinus kesiya var. langbianensis) natural forest%思茅松天然林林分生物量混合效应模型构建

    Institute of Scientific and Technical Information of China (English)

    欧光龙; 胥辉; 王俊峰; 肖义发; 陈科屹; 郑海妹

    2015-01-01

    本研究以云南省普洱市的思茅松天然林为对象,调查了3个位点45块样地的林分地上、根系和总生物量。以幂函数模型为基础构建林分生物量的基本模型;采用混合效应模型技术,考虑区域效应随机效应,选择基本混合效应模型,并分析模型的方差和协方差结构,分别构建3个维量的区域效应随机效应的混合效应模型;考虑林分因子、地形因子和气象因子固定效应,构建含环境因子固定效应和区域效应随机效应的林分生物量混合效应模型。所有模型均采用拟合指标和独立检验指标进行评价。结果表明:1)从模型拟合情况看,考虑区域效应的随机效应模型均能显著提高一般回归模型的精度;在3类含环境因子固定效应模型中,含地形因子固定效应的区域混合效应模型均具有最低的AIC和BIC值,表现最好;2)就模型独立性检验看,除地形因子固定效应的林分根系混合效应模型外,其余模型均优于一般回归模型;考虑环境因子固定效应的混合效应模型与普通区域效应混合模型相比,各个维量模型的独立性检验指标表现不一,但总体上差异不大;3)综合考虑模型拟合和独立性检验结果,除林分根系生物量选择普通区域效应混合模型外,另2个维量均选择含地形因子固定效应和区域效应随机效应的混合效应模型。%In this paper we took natural Simao pine ( Pinus kesiya var. langbianensis) forest as the research object, and investigated the aboveground, root and total biomass of 45 plots of at three typical sites ( Tongguan town of Mojiang County, Yunxian town of Simao District, and Nuofu town of Lancang County) in Pu'er City, Yunnan Province. Firstly, we chose the best power function to the basic model. Secondly, considering random effect of the regional effect we constructed the mixed effects models of the biomass components of stand

  8. Quantifying variation in forest disturbance, and its effects on aboveground biomass dynamics, across the eastern United States.

    Science.gov (United States)

    Vanderwel, Mark C; Coomes, David A; Purves, Drew W

    2013-05-01

    The role of tree mortality in the global carbon balance is complicated by strong spatial and temporal heterogeneity that arises from the stochastic nature of carbon loss through disturbance. Characterizing spatio-temporal variation in mortality (including disturbance) and its effects on forest and carbon dynamics is thus essential to understanding the current global forest carbon sink, and to predicting how it will change in future. We analyzed forest inventory data from the eastern United States to estimate plot-level variation in mortality (relative to a long-term background rate for individual trees) for nine distinct forest regions. Disturbances that produced at least a fourfold increase in tree mortality over an approximately 5 year interval were observed in 1-5% of plots in each forest region. The frequency of disturbance was lowest in the northeast, and increased southwards along the Atlantic and Gulf coasts as fire and hurricane disturbances became progressively more common. Across the central and northern parts of the region, natural disturbances appeared to reflect a diffuse combination of wind, insects, disease, and ice storms. By linking estimated covariation in tree growth and mortality over time with a data-constrained forest dynamics model, we simulated the implications of stochastic variation in mortality for long-term aboveground biomass changes across the eastern United States. A geographic gradient in disturbance frequency induced notable differences in biomass dynamics between the least- and most-disturbed regions, with variation in mortality causing the latter to undergo considerably stronger fluctuations in aboveground stand biomass over time. Moreover, regional simulations showed that a given long-term increase in mean mortality rates would support greater aboveground biomass when expressed through disturbance effects compared with background mortality, particularly for early-successional species. The effects of increased tree mortality on

  9. How to Avoid Errors in Error Propagation: Prediction Intervals and Confidence Intervals in Forest Biomass

    Science.gov (United States)

    Lilly, P.; Yanai, R. D.; Buckley, H. L.; Case, B. S.; Woollons, R. C.; Holdaway, R. J.; Johnson, J.

    2016-12-01

    Calculations of forest biomass and elemental content require many measurements and models, each contributing uncertainty to the final estimates. While sampling error is commonly reported, based on replicate plots, error due to uncertainty in the regression used to estimate biomass from tree diameter is usually not quantified. Some published estimates of uncertainty due to the regression models have used the uncertainty in the prediction of individuals, ignoring uncertainty in the mean, while others have propagated uncertainty in the mean while ignoring individual variation. Using the simple case of the calcium concentration of sugar maple leaves, we compare the variation among individuals (the standard deviation) to the uncertainty in the mean (the standard error) and illustrate the declining importance in the prediction of individual concentrations as the number of individuals increases. For allometric models, the analogous statistics are the prediction interval (or the residual variation in the model fit) and the confidence interval (describing the uncertainty in the best fit model). The effect of propagating these two sources of error is illustrated using the mass of sugar maple foliage. The uncertainty in individual tree predictions was large for plots with few trees; for plots with 30 trees or more, the uncertainty in individuals was less important than the uncertainty in the mean. Authors of previously published analyses have reanalyzed their data to show the magnitude of these two sources of uncertainty in scales ranging from experimental plots to entire countries. The most correct analysis will take both sources of uncertainty into account, but for practical purposes, country-level reports of uncertainty in carbon stocks, as required by the IPCC, can ignore the uncertainty in individuals. Ignoring the uncertainty in the mean will lead to exaggerated estimates of confidence in estimates of forest biomass and carbon and nutrient contents.

  10. 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 (paboveground biomass that ranged from 7.9 to 23.2 ton haa??1. Rhizophora 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.

  11. Biomass from the Brazilian raining forest; Biomassa das florestas amazonicas brasileiras

    Energy Technology Data Exchange (ETDEWEB)

    Fearnside, Philip M. [Instituto Nacional de Pesquisas da Amazonia (INPA), Manaus, AM (Brazil)

    1994-12-31

    This work summarizes the existing knowledge about biomass in the Brazilian area of the Amazon jungle and presents a calculation for the average total biomass in virgin forests. The results are presented. The results are higher than those presently accepted. The reasons for the discrepancy in the calculated and presently used value are presented and discussed 64 refs., 8 tabs.

  12. Quantifying Post-Fire Forest Biomass Recovery in Northeastern Siberia using Hierarchical Multi-Sensor Satellite Imagery and Field Measurements

    Science.gov (United States)

    Berner, L.; Beck, P. S.; Loranty, M. M.; Alexander, H. D.; Mack, M. C.; Goetz, S. J.

    2011-12-01

    Russian forests are the largest vegetation carbon pool outside of the tropics, with larch dominating northeastern Siberia where extreme temperatures, permafrost and wildfire currently limit persistence of other tree species. These ecosystems have experienced rapid climate warming over the past century and model simulations suggest that they will undergo profound changes by the end of the century if warming continues. Understanding the responses of these unique deciduous-conifer ecosystems to current and future climate is important given the potential changes in disturbance regimes and other climate feedbacks. The climate implications of changes in fire severity and return interval, as predicted under a warmer and drier climate, are not well understood given the trade-off between storage of C in forest biomass and post-fire surface albedo. We examined forest biomass recovery across a burn chronosequence near Cherskii, Sakha Republic, in far northeastern Siberia. We used high-quality Landsat imagery to date and map fires that occurred between 1972 and 2009, then complemented this data set using tree ring measurements to map older fires. A three stage approach was taken to map current biomass distribution. First, tree shadows were mapped from 50 cm panchromatic WorldView 1 imagery covering a portion of the region. Secondly, the tree shadow map was aggregated to 30 m resolution and used to train a regression-tree model that ingested mosaiced Landsat data. The model output correlated with allometry-based field estimates of biomass, allowing us to transform the model output to a map of regional aboveground biomass using a regression model. When combined with the fire history data, the new biomass map revealed a chronosequence of forest regrowth and carbon sequestration in aboveground biomass after fire. We discuss the potential for future carbon emissions from fires in northeastern Siberia, as well as carbon sequestration during recovery based on the observed biomass

  13. Experts’ Perceptions of the Effects of Forest Biomass Harvesting on Sustainability in the Alpine Region

    Directory of Open Access Journals (Sweden)

    Gianluca Grilli

    2015-06-01

    Full Text Available Background and Purpose: In the EU political agenda, the use of forest biomass for energy has grown rapidly and significantly, in order to mitigate carbon dioxide emissions and reduce the energy dependence on fossil fuels of European member countries. The target of the EU climate and energy package is to raise the share of renewable energy consumption produced from renewable resources to 20% in 2020 (Directive 2009/28/EC. With regards to biomass energy, the supply of forest wood biomass is expected to rise by 45% (reference period: 2006-2020, in response to increasing demand for renewable sources. The increase of forest biomass supply could have both positive and negative effects on several forest ecosystem services (ESs and local development. These effects should be assessed in a proper manner and taken into account when formulating management strategies. The aim of the paper is to assess the environmental, economic and social sustainability of forest biomass harvesting for energy, using the Figure of Merit (FoM approach. Materials and Methods: Sustainability was assessed through a set of four indicators: two focused on experts’ opinions regarding the effects of forest biomass harvesting and the other two focused on the cost-benefit analysis (potential energy obtained and costs for wood chips. The research was developed through four case studies located in the Alpine Region. A semi-structured questionnaire was administered face-to-face to 32 selected experts. The perceived effects of forest biomass harvesting for energy on ESs and local development were evaluated by experts using a 5-point Likert scale (from “quite negative effect” to “quite positive effect”. Results: All experts agree that forest biomass harvesting has a positive effect on forest products provision and local economic development (employment of local workforce, local entrepreneurship and market diversification, while the effects on other ESs are controversial (e

  14. Predicting biomass of hyperdiverse and structurally complex central Amazonian forests - a virtual approach using extensive field data

    Science.gov (United States)

    Magnabosco Marra, Daniel; Higuchi, Niro; Trumbore, Susan E.; Ribeiro, Gabriel H. P. M.; dos Santos, Joaquim; Carneiro, Vilany M. C.; Lima, Adriano J. N.; Chambers, Jeffrey Q.; Negrón-Juárez, Robinson I.; Holzwarth, Frederic; Reu, Björn; Wirth, Christian

    2016-03-01

    Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha-1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha-1) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express

  15. Biomass and carbon stocks of the natural forests at Me Linh biodiversity station, Vinh Phuc province, Vietnam

    OpenAIRE

    Dang, Thi Thu Huong; Do, Huu Thu

    2015-01-01

    Biomass and carbon stock of the natural forests in Vietnam are still not clear due to limitation of knowledge and financial. In this paper, the results of estimating biomass and carbon stocks of the natural forests at Me Linh Biodiversity Station are shown. There are two forest types in this study: the forest vegetation restored after shifting cultivation (vegetation type I) and the forest vegetation restored after clear cutting exploitation (vegetation type II). As the results, the estimated...

  16. 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.

  17. Power production from radioactively contaminated biomass and forest litter in Belarus - Phase 1b

    DEFF Research Database (Denmark)

    Roed, Jørn; Andersson, Kasper Grann; Fogh, C.L.

    2000-01-01

    The Chernobyl accident has led to radioactive contamination of vast Belarussian forest areas. A total scheme for remediation of contaminated forest areas and utilisation of the removed biomass in safe energy production is being investigated in aBelarussian-American-Danish collaborative project. H...... from the stream by using a combination of a cyclone and a baghouse filter....

  18. Allometry, biomass, and chemical content of novel African Tulip Tree (Spathodea campanulata) forests in Puerto Rico

    Science.gov (United States)

    Ariel E. Lugo; Oscar J. Abelleira; Alexander Collado; Christian A. Viera; Cynthia Santiago; Diego O. Velez; Emilio Soto; Giovanni Amaro; Graciela Charon; Jr. Colon; Jennifer Santana; Jose L. Morales; Katherine Rivera; Luis Ortiz; Luis Rivera; Mianel Maldonado; Natalia Rivera; Norelis J. Vazquez

    2011-01-01

    The African tulip tree, Spathodea campanulata, the most common tree in Puerto Rico, forms novel forest types with mixtures of native and other introduced tree species. Novel forests increase in area in response to human activity and there is no information about their biomass accumulation and nutrient cycling. We established allometric relationships and chemically...

  19. Increasing liana abundance and biomass in tropical forests: emerging patterns and putative mechanisms.

    NARCIS (Netherlands)

    Schnitzer, S.A.; Bongers, F.

    2011-01-01

    Tropical forests are experiencing large-scale structural changes, the most apparent of which may be the increase in liana (woody vine) abundance and biomass. Lianas permeate most lowland tropical forests, where they can have a huge effect on tree diversity, recruitment, growth and survival, which, i

  20. Forest biomass diversion in the Sierra Nevada: Energy, economics and emissions

    Science.gov (United States)

    Bruce Springsteen; Thomas Christofk; Robert A. York; Tad Mason; Stephen Baker; Emily Lincoln; Bruce Hartsough; Takuyuki Yoshioka

    2015-01-01

    As an alternative to open pile burning, use of forest wastes from fuel hazard reduction projects at Blodgett Forest Research Station for electricity production was shown to produce energy and emission benefits: energy (diesel fuel) expended for processing and transport was 2.5% of the biomass fuel (energy equivalent); based on measurements from a large pile...

  1. Biomass is the main driver of changes in ecosystem process rates during tropical forest succession

    NARCIS (Netherlands)

    Lohbeck, M.W.M.; Poorter, L.; Martinez-Ramos, M.; Bongers, F.

    2015-01-01

    Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity, actu

  2. Biomass is the main driver of changes in ecosystem process rates during tropical forest succession

    NARCIS (Netherlands)

    Lohbeck, M.W.M.; Poorter, L.; Martinez-Ramos, M.; Bongers, F.

    2015-01-01

    Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity,

  3. Additive Stand-Level Biomass Models for Natural Larch Forest in the East of Daxing’an Mountains%大兴安岭东部天然落叶松林可加性林分生物量估算模型

    Institute of Scientific and Technical Information of China (English)

    董利虎; 李凤日

    2016-01-01

    【目的】探讨林分乔木层生物量的估算方法,为大区域、大尺度森林生物量的估算提供理论依据。【方法】利用1990—2010年5期大兴安岭东部天然落叶松林固定样地数据,选择基于林分变量的林分生物量模型和基于林分蓄积量的林分生物量模型作为林分乔木层生物量估算的方法,利用似然分析法去判断2种模型的误差结构(相加型和相乘型),并采用聚合型可加性生物量模型建立其林分生物量模型,模型参数估计采用非线性似乎不相关回归模型方法。采用“刀切法”评价所建立的林分生物量模型。【结果】经似然分析法判断,2种模型的误差结构是相乘型的,对数转换的线性回归更适合用来拟合林分生物量数据;2种模型的调整后确定系数 R2a >0.94,平均相对误差 ME为0%~5%,平均相对误差绝对值 MAE<15%;所建立的2种可加性林分生物量模型的预测精度在98%以上。【结论】虽然基于林分蓄积量的林分生物量和基于林分变量的林分生物量模型形式不同,但二者都具有较好的预测精度;就本研究而言,2种估算林分生物量的方法都能对大兴安岭东部天然落叶松林林分生物量进行很好地估算。%Objective]The traditional method based on forest inventory data plays an import role in assessment of forest biomass at regional scale and its dynamics and verification of the remote-sensing based model and improvement of its prediction precision. The forest biomass methods at regional scale have attracted most attention of researchers,developing the stand-level biomass model has become a new trend. Based on 1990—2010 forestry inventory data (the 5th inventory) of natural larch forest in the east of Daxing’an Mountains,we studied how to use two methods ( i. e. ,stand biomass models respectively based on stand variables and stand volume ) to establish the additive system of stand

  4. [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.

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

    Directory of Open Access Journals (Sweden)

    J. Jubanski

    2012-08-01

    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 meter of 2–4 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 46%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong 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.

  6. STATUS OF SOIL MICROBIAL POPULATION, ENZYMATIC ACTIVITY AND BIOMASS OF SELECTED NATURAL, SECONDARY AND REHABILITATED FORESTS

    Directory of Open Access Journals (Sweden)

    K. S. Daljit Singh

    2013-01-01

    Full Text Available Substantial clearance of forests and conversion of forest into various land use types contribute to deterioration of soil fertility and associated nutrients loss. Soils from natural and rehabilitated forest in Chikus Forest Reserve and also enrichment planting forest and secondary forest of Tapah Hill Forest Reserve, Perak, Malaysia were selected in order to assess the influence of land use change on biological properties. This study was carried out to provide fundamental information on soil biological properties and also to compare the differences between natural forest, mono-rehabilitated forest, mixed planting forest and natural regenerated forest (secondary forest. Six subplots (20×20 m were established at each study plot and soil samples were collected at the depths of 0-15 cm (topsoil and 15-30 cm (subsoil. Soil microbial population was determined using spread-plate technique. Fluorescein Diacetate (FDA hydrolysis was used to assess the amount of microbial enzymatic activity for each forest plot. Soil Microbial Biomass C (MBC and N (MBN were extracted using chloroform fumigation extraction technique and the amount of MBC was determined by dichromate digestion, while MBN via Kjeldahl digestion technique. Soil acidity was determined by pH meter and moisture content was elucidated using gravimetric method. The levels of microbial population of bacterial and fungal at natural significantly exceeded the corresponding values of rehabilitated and secondary forest. However, microbial population is much higher in rehabilitated forest of Tapah Hill compared to that of secondary forest and also Chikus Forest Reserve planted forest which proves that rehabilitation activities do help increase the level of microbial community in the soils. Longer period of time after planting as in enrichment planting compared to mono planting of S. leprosula plantation showed that restoring and recovery of the planted forest needed time. Deforestation activities

  7. Historical, ecological, and governance aspects of intensive forest biomass harvesting in Denmark

    DEFF Research Database (Denmark)

    Stupak, Inge; Raulund-Rasmussen, Karsten

    2016-01-01

    Intensive forest harvesting has increased in Fennoscandia over the last few decades. Similar developments may follow throughout Europe as renewable energy replaces fossil fuels. The international literature suggests that intensive harvesting could increase ecological risks to yield, carbon stores...... forest management impacts and conservation of light-demanding biodiversity associated with historic coppicing and grazing than on intensive harvesting. The energy sector drives the development of new governance to verify forest biomass sustainability, but the national knowledge base for such verification...

  8. Predictive models of forest dynamics.

    Science.gov (United States)

    Purves, Drew; Pacala, Stephen

    2008-06-13

    Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

  9. From monitoring to modeling: using biomass observation for benchmarking terrestrial carbon cycle models

    Science.gov (United States)

    Poulter, B.; Ciais, P.; Chevallier, F.; Delbart, N.; Lafont, S.; Maignan, F.; Saatchi, S.; Sitch, S.

    2012-04-01

    Biomass is a key ecosystem property linking biogeochemical fluxes with the accumulation of carbon in terrestrial ecosystems. The spatial and temporal distribution of aboveground biomass has implications for climate stability and other ecosystem services, including timber supplies. Globally, terrestrial forest ecosystems store ~380 Pg C in aboveground biomass, which is about 45% compared to the amount of carbon in the atmosphere as CO2. Model-data comparisons of aboveground biomass have so far been limited because of a lack of wall-to-wall coverage of observations, which has recently been resolved from satellite remote sensing and an intensification of forest inventory networks. Here, we compare aboveground biomass estimates among an ensemble of terrestrial carbon cycle models, and benchmark these estimates with inventory and satellite-based estimates. We then use the distribution of biomass estimates to evaluate bias in net ecosystem exchange caused by uncertainty from carbon turnover rates. By identifying model structure and the parameters linked to carbon turnover, improvements can be made to more realistically simulate aboveground biomass.

  10. Temperature Modelling of the Biomass Pretreatment Process

    DEFF Research Database (Denmark)

    2012-01-01

    In a second generation biorefinery, the biomass pretreatment stage has an important contribution to the efficiency of the downstream processing units involved in biofuel production. Most of the pretreatment process occurs in a large pressurized thermal reactor that presents an irregular temperature...... distribution. Therefore, an accurate temperature model is critical for observing the biomass pretreatment. More than that, the biomass is also pushed with a constant horizontal speed along the reactor in order to ensure a continuous throughput. The goal of this paper is to derive a temperature model...

  11. BIOMASS REBURNING - MODELING/ENGINEERING STUDIES

    Energy Technology Data Exchange (ETDEWEB)

    Vladimir Zamansky; Chris Lindsey; Vitali Lissianski

    2000-01-28

    This project is designed to develop engineering and modeling tools for a family of NO{sub x} control technologies utilizing biomass as a reburning fuel. During the ninth reporting period (September 27--December 31, 1999), EER prepared a paper Kinetic Model of Biomass Reburning and submitted it for publication and presentation at the 28th Symposium (International) on Combustion, University of Edinburgh, Scotland, July 30--August 4, 2000. Antares Group Inc, under contract to Niagara Mohawk Power Corporation, evaluated the economic feasibility of biomass reburning options for Dunkirk Station. A preliminary report is included in this quarterly report.

  12. Changes in Forest Production, Biomass and Carbon: Results From the 2015 UN FAO Global Forest Resource Assessment

    Science.gov (United States)

    Navar, J.

    2015-12-01

    Forests are important sources of livelihoods to millions of people and contribute to national economic development of many countries. In addition, they are vital sources and sinks of carbon and contribute to the rate of climate change. The UN Food and Agriculture Organization has been collecting and presenting data on global forest resources and forest cover since 1948. This paper builds on data from FAO's 2015 Global Forest Resource Assessment (FRA) and presents information on growing stock, biomass, carbon stock, wood removals, and changes of forest area primarily designated for production and multiple use of the world's forests. Between 1990 and 2015, the total growing stock volume has increased in East Asia, Caribbean, Western and Central Asia, North America, Europe (including the Russian Federation), and Oceania with the highest relative increase in East Asia and the Caribbean. In all other subregions the total growing stock volume decreased. North and Central America, Europe and Asia report forest C stock increases while South America and Africa report strong decreases and Oceania reports stable forest C stocks. The annual rate of decrease of forest C stock weakened between 1990 and 2015. The total volume of annual wood removals including wood fuel removals increased between 1990 and 2011, but shows a remarkable decline during the 2008-2009 economic crisis. Forest areas designated for production purposes differ considerably between subregions. The percentage of production area out of total forest area ranges between 16 percent in South America and 53 percent in Europe. Globally about one quarter of the forest area is designated to multiple use forestry. The balance between biomass growth and removals shows considerable sub-regional differences and related implications for the sustainable use of forests.

  13. Does species richness affect fine root biomass and production in young forest plantations?

    Science.gov (United States)

    Domisch, Timo; Finér, Leena; Dawud, Seid Muhie; Vesterdal, Lars; Raulund-Rasmussen, Karsten

    2015-02-01

    Tree species diversity has been reported to increase forest ecosystem above-ground biomass and productivity, but little is known about below-ground biomass and production in diverse mixed forests compared to single-species forests. For testing whether species richness increases below-ground biomass and production and thus complementarity between forest tree species in young stands, we determined fine root biomass and production of trees and ground vegetation in two experimental plantations representing gradients in tree species richness. Additionally, we measured tree fine root length and determined species composition from fine root biomass samples with the near-infrared reflectance spectroscopy method. We did not observe higher biomass or production in mixed stands compared to monocultures. Neither did we observe any differences in tree root length or fine root turnover. One reason for this could be that these stands were still young, and canopy closure had not always taken place, i.e. a situation where above- or below-ground competition did not yet exist. Another reason could be that the rooting traits of the tree species did not differ sufficiently to support niche differentiation. Our results suggested that functional group identity (i.e. conifers vs. broadleaved species) can be more important for below-ground biomass and production than the species richness itself, as conifers seemed to be more competitive in colonising the soil volume, compared to broadleaved species.

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Hieu Cong Nguyen

    2015-07-01

    Full Text Available 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.

  16. Relationship between species richness and biomass on environmental gradient in natural forest communities on Mt. Xiaolongshan, northwest China

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    We analyzed the relationship between species richness and biomass in natural forest communities at two similar sites on Mt. Xiaoiongshan, northwest China. At both sites, a wide range of tree layer biomass levels was available by local biomass estima-tion models. In order to identify underlying mechanism of the species richness-biomass relationship, we included different water resource levels and number of individuals in each plot in our analysis. We sampled 15 and 20 plots (20 m x 20 m), respectively, at both two sites. These plots were sampled equally on the sunny slope and the shady slope. Species richness, number of individuals of each species and diameter at breast height (DBH) as a substitute of biomass of tree layer were recorded in each sample. At one site,the relationship between species richness and biomass was significant on the sunny slope, and this relationship disappeared on the shady slope due to more environmental factors. The relations between species richness and number of individuals and between num-ber of individuals and biomass paralleled the species richness-biomass relation on both slopes. The difference in number of individu-als-biomass relationships on the sunny slope and the shady slope revealed "interspecific competitive exclusion" even though the species richness-biomass relationships were not hump-shaped. At the other site, species richness was not related to biomass or to number of individuals. Our study demonstrated the importance of environmental stress and succession of community in the under-standing of species diversity-productivity patterns.

  17. Modeling future U.S. forest sector market and trade impacts of expansion in wood energy consumption

    Science.gov (United States)

    Peter J. Ince; Andrew D. Kramp; Kenneth E. Skog; Do-il Yoo; V. Alaric Sample

    2011-01-01

    This paper describes an approach to modeling U.S. forest sector market and trade impacts of expansion in domestic wood energy consumption under hypothetical future U.S. wood biomass energy policy scenarios. The U.S. Forest Products Module (USFPM) was created to enhance the modeling of the U.S. forest sector within the Global Forest Products Model (GFPM), providing a...

  18. Implication of Forest-Savanna Dynamics on Biomass and Carbon Stock: Effectiveness of an Amazonian Ecological Station

    Science.gov (United States)

    Couto-Santos, F. R.; Luizao, F. J.

    2014-12-01

    The forests-savanna advancement/retraction process seems to play an important role in the global carbon cycle and in the climate-vegetation balance maintenance in the Amazon. To contribute with long term carbon dynamics and assess effectiveness of a protected area in reduce carbon emissions in Brazilian Amazon transitional areas, variations in forest-savanna mosaics biomass and carbon stock within Maraca Ecological Station (MES), Roraima/Brazil, and its outskirts non-protected areas were compared. Composite surface soil samples and indirect methods based on regression models were used to estimate aboveground tree biomass accumulation and assess vegetation and soil carbon stock along eleven 0.6 ha transects perpendicular to the forest-savanna limits. Aboveground biomass and carbon accumulation were influenced by vegetation structure, showing higher values within protected area, with great contribution of trees above 40 cm in diameter. In the savanna environments of protected areas, a higher tree density and carbon stock up to 30 m from the border confirmed a forest encroachment. This pointed that MES acts as carbon sink, even under variations in soil fertility gradient, with a potential increase of the total carbon stock from 9 to 150 Mg C ha-1. Under 20 years of fire and disturbance management, the results indicated the effectiveness of this protected area to reduce carbon emissions and mitigate greenhouse and climate change effects in a forest-savanna transitional area in Brazilian Northern Amazon. The contribution of this study in understanding rates and reasons for biomass and carbon variation, under different management strategies, should be considered the first approximation to assist policies of reducing emissions from deforestation and forest degradation (REDD) from underresearched Amazonian ecotone; despite further efforts in this direction are still needed. FINANCIAL SUPPORT: Boticário Group Foundation (Fundação Grupo Boticário); National Council for

  19. A Forest Biomass Survey by Bitterlich Method With an Electronic Relascope for Satellite Data Validation

    Science.gov (United States)

    Suzuki, R.; Ishii, R.; Takao, G.; Nakano, T.; Yasuda, T.

    2006-12-01

    For the better understanding of the carbon cycle in the global ecosystem, an investigation on the spatio- temporal variation of the carbon stock which is stored as vegetation biomass should be important. "PALSAR (Phased Array type L-band Synthetic Aperture Radar)", an onboard sensor of the polar orbiting satellite "ALOS (Advanced Land Observing Satellite)" launched in January 2006, provides the information which can be used for the above-ground biomass estimation. It is expected that ALOS/PALSAR provides us a great opportunity to analyze the biomass dynamics over extensive regions. To derive the biomass from the ALOS/PALSAR measurement, it is inevitable to acquire in situ biomass measurement by ground-based forest surveys. Moreover, it is required to obtain such ground-based information at as possible many sites, because the region targeted by satellite remote sensing is extensive and the forest structure in that region is various. Therefore, a quick forest survey will be required to measure the biomass at as possible many sites. For the quick measurement of the forest above-ground biomass, we propose a way that is a combination of Bitterlich angle count sampling method and sampled-tree measuring method. First, a tree which has wider trunk than the basal area factor (BAF) angle is identified by the relascope from a representative point in the target forest. Next, the tree height and the breast height diameter (DBH) of the sampled tree are measured. The biomass of the tree is estimate by the allometric equation with the tree height and DBH measurements. Through these processes, the biomass density of the sampled tree per the forest area defined by the BAF is estimated. By sampling and measuring all trees (usually around 20 trees), the biomass of the forest can be estimate. A brand-new electronic relascope (Criterion RD 1000, Laser Technology Inc.) and laser range finder (TruPulse 200, Laser Technology Inc.) are used for the tree height and DBH measurements to

  20. Effect of disturbance on biomass, production and carbon dynamics in moist tropical forest of eastern Nepal

    Directory of Open Access Journals (Sweden)

    Tilak Prasad Gautam

    2016-04-01

    Full Text Available Background: Forest biomass is helpful to assess its productivity and carbon (C sequestration capacity. Several disturbance activities in tropical forests have reduced the biomass and net primary production (NPP leading to climate change. Therefore, an accurate estimation of forest biomass and C cycling in context of disturbances is required for implementing REDD (Reducing Emissions from Deforestation and Forest Degradation policy. Methods: Biomass and NPP of trees and shrubs were estimated by using allometric equations while herbaceous biomass was estimated by harvest method. Fine root biomass was determined from soil monolith. The C stock in vegetation was calculated by multiplying C concentration to dry weight. Results: Total stand biomass (Mg∙ha–1 in undisturbed forest stand (US was 960.4 while in disturbed forest stand (DS it was 449.1. The biomass (Mg∙ha–1 of trees, shrubs and herbs in US was 948.0, 4.4 and 1.4, respectively, while in DS they were 438.4, 6.1 and 1.2, respectively. Total NPP (Mg∙ha–1∙yr–1 was 26.58 (equivalent to 12.26 Mg C∙ha–1∙yr–1 in US and 14.91 (6.88 Mg C∙ha–1∙yr–1 in DS. Total C input into soil through litter plus root turnover was 6.78 and 3.35 Mg∙ha–1∙yr–1 in US and DS, respectively. Conclusions: Several disturbance activities resulted in the significant loss in stand biomass (53 %, NPP (44 %, and C sequestration capacity of tropical forest in eastern Nepal. The net uptake of carbon by the vegetation is far greater than that returned to the soil by the turnover of fine root and litter. Therefore, both stands of present forest act as carbon accumulating systems. Moreover, disturbance reflects higher C emissions which can be reduced by better management. Keywords: Tropical forest, Disturbance, Biomass, Production, Carbon cycling, Nepal

  1. Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation

    Directory of Open Access Journals (Sweden)

    Panpan Zhao

    2016-06-01

    Full Text Available The data saturation problem in Landsat imagery is well recognized and is regarded as an important factor resulting in inaccurate forest aboveground biomass (AGB estimation. However, no study has examined the saturation values for different vegetation types such as coniferous and broadleaf forests. The objective of this study is to estimate the saturation values in Landsat imagery for different vegetation types in a subtropical region and to explore approaches to improving forest AGB estimation. Landsat Thematic Mapper imagery, digital elevation model data, and field measurements in Zhejiang province of Eastern China were used. Correlation analysis and scatterplots were first used to examine specific spectral bands and their relationships with AGB. A spherical model was then used to quantitatively estimate the saturation value of AGB for each vegetation type. A stratification of vegetation types and/or slope aspects was used to determine the potential to improve AGB estimation performance by developing a specific AGB estimation model for each category. Stepwise regression analysis based on Landsat spectral signatures and textures using grey-level co-occurrence matrix (GLCM was used to develop AGB estimation models for different scenarios: non-stratification, stratification based on either vegetation types, slope aspects, or the combination of vegetation types and slope aspects. The results indicate that pine forest and mixed forest have the highest AGB saturation values (159 and 152 Mg/ha, respectively, Chinese fir and broadleaf forest have lower saturation values (143 and 123 Mg/ha, respectively, and bamboo forest and shrub have the lowest saturation values (75 and 55 Mg/ha, respectively. The stratification based on either vegetation types or slope aspects provided smaller root mean squared errors (RMSEs than non-stratification. The AGB estimation models based on stratification of both vegetation types and slope aspects provided the most

  2. 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, X.; Liu, S.; Zhu, Z.; Vogelmann, J.; Li, Z.; Ohlen, D.

    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 fireinduced 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

  3. Effects of increased biomass removal on the biogeochemistry of two Norwegian forest ecosystems

    Science.gov (United States)

    Lange, H.; Clarke, N.; Kjønaas, O. J.; Aas, W.; Andreassen, K.; Børja, I.; Bratli, H.; Eich-Greatorex, S.; Eldhuset, T.; Holt-Hanssen, K.

    2009-04-01

    quantified post harvest. Soil water at 30 cm soil depth will be analysed for nutrients, and element fluxes will be estimated to provide information about nutrient leaching. Soil respiration will be measured, along with lab decomposition studies under different temperature and moisture regimes. Long term in situ decomposition studies will be carried out in the WTH plots using three different tree compartments (needles, coarse twigs, fine roots) decomposing in litter bags, in order to determine their limit value. The structure of the fungal community will be determined by soil core sampling and molecular techniques. Understory vegetation will be sampled to determine its biomass, and the frequency of all vascular plants, bryophytes and lichens will be estimated. After harvesting, replanting will be carried out. Seedling survival, causes of mortality and potential damage, growth, and needle nutrients will be monitored. Results from these studies will be used to identify key processes explaining trends observed in two series of ongoing long-term whole-tree thinning trials. We shall combine knowledge obtained using field experiments with results of modelling and data from the Norwegian Monitoring Programme for Forest Damage and the National Forest Inventory. The overall project aim is to predict and map the ecologically most suitable areas for increased harvesting of branches and tops on a regional scale, and to identify uncertainties and additional knowledge needed to improve current predictions.

  4. Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests

    Science.gov (United States)

    Vaglio Laurin, Gaia; Puletti, Nicola; Chen, Qi; Corona, Piermaria; Papale, Dario; Valentini, Riccardo

    2016-10-01

    Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment.

  5. Salamander populations and biomass in the Hubbard Brook Experimental Forest, New Hampshire

    Energy Technology Data Exchange (ETDEWEB)

    Burton, T.M.; Likens, G.E.

    1975-01-01

    There were about 2950 salamanders per ha (1770 g/ha wet wt) in the Hubbard Brook Experimental Forest in New Hampshire. The terrestrial species, Plethodon cinereus, accounted for about 93.5% of the total biomass while the streamside species, Desmognathus fuscus, Eurycea bislineata and Gyrinophilus porphyriticus, accounted for the remaining 6.5%. Notophthalmus viridescens was present, but was rare and insignificant in the biomass calculations. The population size of salamanders at Hubbard Brook appears to be stable. The biomass of salamanders is about twice that of birds during the bird's peak (breeding) season and is about equal to the biomass of small mammals.

  6. Predicting biomass of hyperdiverse and structurally complex Central Amazon forests - a virtual approach using extensive field data

    Science.gov (United States)

    Magnabosco Marra, D.; Higuchi, N.; Trumbore, S. E.; Ribeiro, G. H. P. M.; dos Santos, J.; Carneiro, V. M. C.; Lima, A. J. N.; Chambers, J. Q.; Negrón-Juárez, R. I.; Holzwarth, F.; Reu, B.; Wirth, C.

    2015-09-01

    Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total AGB above-ground biomass in tropical forests and AGB estimation models are crucial for forest management and conservation. In the Central Amazon, predicting AGB at large spatial-scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this dataset we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape-level across successional gradients. We found that good individual tree model fits do not necessarily translate into good predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with RMSE root-mean-square error values of up to 130 Mg ha-1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha-1) when applied over scenarios. Predicting biomass correctly at the landscape-level in complex tropical forests, especially allowing good performance at the margins of data availability for model parametrization, requires the inclusion of predictors related to species architecture. The model of interest should comprise the floristic composition and size

  7. 贺兰山东麓不同种植年限酿酒葡萄林生物量分配及估算模型%Biomass allocation and estimation model at different planting ages of wine grape forest in east Helan Mountain

    Institute of Scientific and Technical Information of China (English)

    吴旭东; 谢应忠; 徐坤; 汪诗平; 张晓娟

    2012-01-01

    The biomass and morphological indexes of different planting ages of wine grape forest (1~12 years) were investigated by analyzing biomass distributions in different organs of varying-age stands and the relationships of biomass with component factors in east Helan Mountain. The study then established biomass prediction models for wine grape forests in the region. The results showed that plant height (H), stem height (SH), young shoot height (YSH), branch number (BN) and stem diameter (D) gradually increased with increasing planting age. Also different aboveground organs biomass increased with increasing forest age. The distribution of aboveground biomass showed an order of leaf > young shoot > stem for forest of ages 1~4 years. Although leaf formed a principal component of aboveground biomass, stem biomass was greater than young shoot biomass which was in turn greater than leaf biomass for forest of ages 4~12 years. Aboveground biomass gradually transformed into stem and young shoot. Belowground and aboveground biomasses significantly increased for ages 1~12 years. Biomass allocation was in the order as follows: aboveground biomass > belowground biomass for forest ages of 2~12 years. The pattern of relationship between biomasses of different plant organs and D2H was uniform with age structures. The optimal biomass models were the power function models of the form W=a×(D2H)b. The relationship between leaf biomass and D2H fitted the form W=12.909×(D2H)0.8259 (R2=0.849 9, P=0.000); that between shoot biomass and D2H fitted the form W=3.963 4x( >2H)134A 9 (R2=0.938 1, P=0.000); also that between young shoot biomass and D2H fitted the form W=6.190 6×(D2H)1.0517 (R2=0.804 7, P=0.000); next that between aboveground biomass and D2H fitted the form W=23.017×(JD2H)1.0766(A2=0.938 5, P=0.000); and the relationship between belowground biomass and D2H fitted the form W=27.126×(D2H)0.689(R2=0.892 4, P=0.000). The optimal wine grape biomass models at different planting ages

  8. Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

    Science.gov (United States)

    Ploton, Pierre; Barbier, Nicolas; Takoudjou Momo, Stéphane; Réjou-Méchain, Maxime; Boyemba Bosela, Faustin; Chuyong, Georges; Dauby, Gilles; Droissart, Vincent; Fayolle, Adeline; Calisto Goodman, Rosa; Henry, Matieu; Kamdem, Narcisse Guy; Katembo Mukirania, John; Kenfack, David; Libalah, Moses; Ngomanda, Alfred; Rossi, Vivien; Sonké, Bonaventure; Texier, Nicolas; Thomas, Duncan; Zebaze, Donatien; Couteron, Pierre; Berger, Uta; Pélissier, Raphaël

    2016-03-01

    Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [-23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

  9. Above ground biomass estimation from lidar and hyperspectral airbone data in West African moist forests.

    Science.gov (United States)

    Vaglio Laurin, Gaia; Chen, Qi; Lindsell, Jeremy; Coomes, David; Cazzolla-Gatti, Roberto; Grieco, Elisa; Valentini, Riccardo

    2013-04-01

    The development of sound methods for the estimation of forest parameters such as Above Ground Biomass (AGB) and the need of data for different world regions and ecosystems, are widely recognized issues due to their relevance for both carbon cycle modeling and conservation and policy initiatives, such as the UN REDD+ program (Gibbs et al., 2007). The moist forests of the Upper Guinean Belt are poorly studied ecosystems (Vaglio Laurin et al. 2013) but their role is important due to the drier condition expected along the West African coasts according to future climate change scenarios (Gonzales, 2001). Remote sensing has proven to be an effective tool for AGB retrieval when coupled with field data. Lidar, with its ability to penetrate the canopy provides 3D information and best results. Nevertheless very limited research has been conducted in Africa tropical forests with lidar and none to our knowledge in West Africa. Hyperspectral sensors also offer promising data, being able to evidence very fine radiometric differences in vegetation reflectance. Their usefulness in estimating forest parameters is still under evaluation with contrasting findings (Andersen et al. 2008, Latifi et al. 2012), and additional studies are especially relevant in view of forthcoming satellite hyperspectral missions. In the framework of the EU ERC Africa GHG grant #247349, an airborne campaign collecting lidar and hyperspectral data has been conducted in March 2012 over forests reserves in Sierra Leone and Ghana, characterized by different logging histories and rainfall patterns, and including Gola Rainforest National Park, Ankasa National Park, Bia and Boin Forest Reserves. An Optech Gemini sensor collected the lidar dataset, while an AISA Eagle sensor collected hyperspectral data over 244 VIS-NIR bands. The lidar dataset, with a point density >10 ppm was processed using the TIFFS software (Toolbox for LiDAR Data Filtering and Forest Studies)(Chen 2007). The hyperspectral dataset, geo

  10. The role of forest age in earth system models

    Science.gov (United States)

    Poulter, B.; Bellassen, V.; Lin, X.; Luyssaert, S.; Nachin, B.; Pederson, N.; Shchepashchenko, D.; Shvidenko, A.; Ciais, P.

    2012-12-01

    The age of a forest has a principal role in determining the magnitude of carbon stocks and fluxes. As forests grow older, carbon tends to accumulate in above and belowground biomass causing changes in forest canopy complexity, nutrient pools, and the balance between carbon uptake and release. While age is a standard variable for forestry models, the present generation of earth system models neglects a representation of forest age for several reasons. These include the challenge in representing sub-grid cell ecosystem heterogeneity, a poor understanding of how ecosystem processes evolve with age, and because of a lack of forest age data with which to initialize models. Here we present a globally gridded forest age distribution dataset that is derived from National Forest Inventory data and from satellite-derived disturbance frequencies. This gridded dataset is developed at 0.5° spatial resolution at the plant functional types classification level, one that is commonly used in dynamic global vegetation models. We find large national-scale differences in forest age distributions, for example, with a peak age-area for young forests in China, and more mature forests across Canada and in Russia. Comparing simulated forest carbon stocks and fluxes from three DGVM models (LPJ, ORCHIDEE, and ORCHIDEE-Forest Management) with a global forest database, we illustrate the importance of accounting for structural development as forests develop. With over half the world's forests modified by human activities, or influenced by natural disturbance, spatial patterns of forest age distributions are a necessary feature of forward models for closing the global carbon budget within a consistent modeling framework.

  11. Interactions between Canopy Structure and Herbaceous Biomass along Environmental Gradients in Moist Forest and Dry Miombo Woodland of Tanzania.

    Directory of Open Access Journals (Sweden)

    Deo D Shirima

    Full Text Available We have limited understanding of how tropical canopy foliage varies along environmental gradients, and how this may in turn affect forest processes and functions. Here, we analyse the relationships between canopy leaf area index (LAI and above ground herbaceous biomass (AGBH along environmental gradients in a moist forest and miombo woodland in Tanzania. We recorded canopy structure and herbaceous biomass in 100 permanent vegetation plots (20 m × 40 m, stratified by elevation. We quantified tree species richness, evenness, Shannon diversity and predominant height as measures of structural variability, and disturbance (tree stumps, soil nutrients and elevation as indicators of environmental variability. Moist forest and miombo woodland differed substantially with respect to nearly all variables tested. Both structural and environmental variables were found to affect LAI and AGBH, the latter being additionally dependent on LAI in moist forest but not in miombo, where other factors are limiting. Combining structural and environmental predictors yielded the most powerful models. In moist forest, they explained 76% and 25% of deviance in LAI and AGBH, respectively. In miombo woodland, they explained 82% and 45% of deviance in LAI and AGBH. In moist forest, LAI increased non-linearly with predominant height and linearly with tree richness, and decreased with soil nitrogen except under high disturbance. Miombo woodland LAI increased linearly with stem density, soil phosphorous and nitrogen, and decreased linearly with tree species evenness. AGBH in moist forest decreased with LAI at lower elevations whilst increasing slightly at higher elevations. AGBH in miombo woodland increased linearly with soil nitrogen and soil pH. Overall, moist forest plots had denser canopies and lower AGBH compared with miombo plots. Further field studies are encouraged, to disentangle the direct influence of LAI on AGBH from complex interrelationships between stand

  12. Forest Biomass, Carbon Stocks, and Macrofungal Dynamics: A Case Study in Costa Rica

    Directory of Open Access Journals (Sweden)

    Carlos Rojas

    2014-01-01

    Full Text Available There are few published studies providing information about macrofungal biology in a context of forest dynamics in tropical areas. For this study, a characterization of above-ground standing tree biomass and carbon stocks was performed for four different forest subtypes within two life zones in Costa Rica. Fungal productivity and reproductive success were estimated and analyzed in the context of the forest systems studied and results showed fungal dynamics to be a complex and challenging topic. In the present study, fungal productivity was higher in forest patches with more tree density but independent from life zones, whereas fungal biomass was higher in premontane areas with ectomycorrhizal dominant trees. Even though some observed patterns could be explained in terms of climatic differences and biotic relationships, the high fungal productivity observed in dry forests was an interesting finding and represents a topic for further studies.

  13. Impact of logging on aboveground biomass stocks in lowland rain forest, Papua New Guinea.

    Science.gov (United States)

    Bryan, Jane; Shearman, Phil; Ash, Julian; Kirkpatrick, J B

    2010-12-01

    Greenhouse-gas emissions resulting from logging are poorly quantified across the tropics. There is a need for robust measurement of rain forest biomass and the impacts of logging from which carbon losses can be reliably estimated at regional and global scales. We used a modified Bitterlich plotless technique to measure aboveground live biomass at six unlogged and six logged rain forest areas (coupes) across two approximately 3000-ha regions at the Makapa concession in lowland Papua New Guinea. "Reduced-impact logging" is practiced at Makapa. We found the mean unlogged aboveground biomass in the two regions to be 192.96 +/- 4.44 Mg/ha and 252.92 +/- 7.00 Mg/ha (mean +/- SE), which was reduced by logging to 146.92 +/- 4.58 Mg/ha and 158.84 +/- 4.16, respectively. Killed biomass was not a fixed proportion, but varied with unlogged biomass, with 24% killed in the lower-biomass region, and 37% in the higher-biomass region. Across the two regions logging resulted in a mean aboveground carbon loss of 35 +/- 2.8 Mg/ha. The plotless technique proved efficient at estimating mean aboveground biomass and logging damage. We conclude that substantial bias is likely to occur within biomass estimates derived from single unreplicated plots.

  14. The Penetration Depth Derived from the Synthesis of ALOS/PALSAR InSAR Data and ASTER GDEM for the Mapping of Forest Biomass

    Directory of Open Access Journals (Sweden)

    Wenjian Ni

    2014-08-01

    Full Text Available The Global Digital Elevation Model produced from stereo images of Advanced Spaceborne Thermal Emission and Reflection Radiometer data (ASTER GDEM covers land surfaces between latitudes of 83°N and 83°S. The Phased Array type L-band Synthetic Aperture Radar (PALSAR onboard Advanced Land Observing Satellite (ALOS collected many SAR images since it was launched on 24 January 2006. The combination of ALOS/PALSAR interferometric data and ASTER GDEM should provide the penetration depth of SAR data assuming ASTER GDEM was the elevation of vegetation canopy top. It would be correlated with forest biomass because penetration depth could be affected by forest density and forest canopy height. Their combination held great promises for the forest biomass mapping over large area. The feasibility of forest biomass mapping through the data synthesis of ALOS/PALSAR InSAR data and ASTER GDEM was investigated in this study. A procedure for the extraction of penetration depth was firstly proposed. Then three models were built for biomass estimation: (I model only using backscattering coefficients of ALOS/PALSAR data; (II model only using penetration depth; (III model using both of them. The biomass estimated from Lidar data was taken as reference data to evaluate the three different models. The results showed that the combination of backscattering coefficients and penetration depth gave the best accuracy. The forest disturbance has to be considered in forest biomass estimation because of the long time span of ASTER data for generating ASTER GDEM. The spatial homogeneity could be used to improve estimation accuracy.

  15. 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.

  16. Patterns of biomass and carbon distribution across a chronosequence of Chinese pine (Pinus tabulaeformis forests.

    Directory of Open Access Journals (Sweden)

    Jinlong Zhao

    Full Text Available Patterns of biomass and carbon (C storage distribution across Chinese pine (Pinus tabulaeformis natural secondary forests are poorly documented. The objectives of this study were to examine the biomass and C pools of the major ecosystem components in a replicated age sequence of P. tabulaeformis secondary forest stands in Northern China. Within each stand, biomass of above- and belowground tree, understory (shrub and herb, and forest floor were determined from plot-level investigation and destructive sampling. Allometric equations using the diameter at breast height (DBH were developed to quantify plant biomass. C stocks in the tree and understory biomass, forest floor, and mineral soil (0-100 cm were estimated by analyzing the C concentration of each component. The results showed that the tree biomass of P. tabulaeformis stands was ranged from 123.8 Mg·ha-1 for the young stand to 344.8 Mg·ha-1 for the mature stand. The understory biomass ranged from 1.8 Mg·ha-1 in the middle-aged stand to 3.5 Mg·ha-1 in the young stand. Forest floor biomass increased steady with stand age, ranging from 14.9 to 23.0 Mg·ha-1. The highest mean C concentration across the chronosequence was found in tree branch while the lowest mean C concentration was found in forest floor. The observed C stock of the aboveground tree, shrub, forest floor, and mineral soil increased with increasing stand age, whereas the herb C stock showed a decreasing trend with a sigmoid pattern. The C stock of forest ecosystem in young, middle-aged, immature, and mature stands were 178.1, 236.3, 297.7, and 359.8 Mg C ha-1, respectively, greater than those under similar aged P. tabulaeformis forests in China. These results are likely to be integrated into further forest management plans and generalized in other contexts to evaluate C stocks at the regional scale.

  17. Patterns of Biomass and Carbon Distribution across a Chronosequence of Chinese Pine (Pinus tabulaeformis) Forests

    Science.gov (United States)

    Wang, Luoxin; Yu, Xiaowen; Zhao, Weihong; Song, Xiaoshuai; Zhang, Yanlei; Chen, Feng; Sun, Yu; He, Tengfei; Han, Hairong

    2014-01-01

    Patterns of biomass and carbon (C) storage distribution across Chinese pine (Pinus tabulaeformis) natural secondary forests are poorly documented. The objectives of this study were to examine the biomass and C pools of the major ecosystem components in a replicated age sequence of P. tabulaeformis secondary forest stands in Northern China. Within each stand, biomass of above- and belowground tree, understory (shrub and herb), and forest floor were determined from plot-level investigation and destructive sampling. Allometric equations using the diameter at breast height (DBH) were developed to quantify plant biomass. C stocks in the tree and understory biomass, forest floor, and mineral soil (0–100 cm) were estimated by analyzing the C concentration of each component. The results showed that the tree biomass of P. tabulaeformis stands was ranged from 123.8 Mg·ha–1 for the young stand to 344.8 Mg·ha–1 for the mature stand. The understory biomass ranged from 1.8 Mg·ha–1 in the middle-aged stand to 3.5 Mg·ha–1 in the young stand. Forest floor biomass increased steady with stand age, ranging from 14.9 to 23.0 Mg·ha–1. The highest mean C concentration across the chronosequence was found in tree branch while the lowest mean C concentration was found in forest floor. The observed C stock of the aboveground tree, shrub, forest floor, and mineral soil increased with increasing stand age, whereas the herb C stock showed a decreasing trend with a sigmoid pattern. The C stock of forest ecosystem in young, middle-aged, immature, and mature stands were 178.1, 236.3, 297.7, and 359.8 Mg C ha–1, respectively, greater than those under similar aged P. tabulaeformis forests in China. These results are likely to be integrated into further forest management plans and generalized in other contexts to evaluate C stocks at the regional scale. PMID:24736660

  18. The Forest Biomass Resource of the United States

    Science.gov (United States)

    Noel D. Cost; James O. Howard; Bert Mead; William H. McWilliams; W. Brad Smith; Dwane D. van Hooser; Eric H. Wharton

    1990-01-01

    Over the last decade, biomass statistics have been published for most states. However, the existing aggregate data are either limited or out of date. The most recent statistics on biomass were for 1980 (U.S. Department of Agriculture 1981). The development of such data continues to lag even though user interest is high. This study was initiated to provide current...

  19. Regional Mapping, Modelling, and Monitoring of Tree Aboveground Biomass Carbon

    Science.gov (United States)

    Hudak, Andrew

    2016-04-01

    Airborne lidar collections are preferred for mapping aboveground biomass carbon (AGBC), while historical Landsat imagery are preferred for monitoring decadal scale forest cover change. Our modelling approach tracks AGBC change regionally using Landsat time series metrics; training areas are defined by airborne lidar extents within which AGBC is accurately mapped with high confidence. Geospatial topographic and climate layers are also included in the predictive model. Validation is accomplished using systematically sampled Forest Inventory and Analysis (FIA) plot data that have been independently collected, processed and summarized at the county level. Our goal is to demonstrate that spatially and temporally aggregated annual AGBC map predictions show no bias when compared to annual county-level summaries across the Northwest USA. A prominent source of bias is trees outside forest; much of the more arid portions of our study area meet the FIA definition of non-forest because the tree cover does not exceed their minimum tree cover threshold. We employ detailed tree cover maps derived from high-resolution aerial imagery to extend our AGBC predictions into non-forest areas. We also employ Landsat-derived annual disturbance maps into our mapped AGBC predictions prior to aggregation and validation.

  20. Topographic variation in aboveground biomass in a subtropical evergreen broad-leaved forest in China.

    Science.gov (United States)

    Lin, Dunmei; Lai, Jiangshan; Muller-Landau, Helene C; Mi, Xiangcheng; Ma, Keping

    2012-01-01

    The subtropical forest biome occupies about 25% of China, with species diversity only next to tropical forests. Despite the recognized importance of subtropical forest in regional carbon storage and cycling, uncertainties remain regarding the carbon storage of subtropical forests, and few studies have quantified within-site variation of biomass, making it difficult to evaluate the role of these forests in the global and regional carbon cycles. Using data for a 24-ha census plot in east China, we quantify aboveground biomass, characterize its spatial variation among different habitats, and analyse species relative contribution to the total aboveground biomass of different habitats. The average aboveground biomass was 223.0 Mg ha(-1) (bootstrapped 95% confidence intervals [217.6, 228.5]) and varied substantially among four topographically defined habitats, from 180.6 Mg ha(-1) (bootstrapped 95% CI [167.1, 195.0]) in the upper ridge to 245.9 Mg ha(-1) (bootstrapped 95% CI [238.3, 253.8]) in the lower ridge, with upper and lower valley intermediate. In consistent with our expectation, individual species contributed differently to the total aboveground biomass of different habitats, reflecting significant species habitat associations. Different species show differently in habitat preference in terms of biomass contribution. These patterns may be the consequences of ecological strategies difference among different species. Results from this study enhance our ability to evaluate the role of subtropical forests in the regional carbon cycle and provide valuable information to guide the protection and management of subtropical broad-leaved forest for carbon sequestration and carbon storage.

  1. Topographic variation in aboveground biomass in a subtropical evergreen broad-leaved forest in China.

    Directory of Open Access Journals (Sweden)

    Dunmei Lin

    Full Text Available The subtropical forest biome occupies about 25% of China, with species diversity only next to tropical forests. Despite the recognized importance of subtropical forest in regional carbon storage and cycling, uncertainties remain regarding the carbon storage of subtropical forests, and few studies have quantified within-site variation of biomass, making it difficult to evaluate the role of these forests in the global and regional carbon cycles. Using data for a 24-ha census plot in east China, we quantify aboveground biomass, characterize its spatial variation among different habitats, and analyse species relative contribution to the total aboveground biomass of different habitats. The average aboveground biomass was 223.0 Mg ha(-1 (bootstrapped 95% confidence intervals [217.6, 228.5] and varied substantially among four topographically defined habitats, from 180.6 Mg ha(-1 (bootstrapped 95% CI [167.1, 195.0] in the upper ridge to 245.9 Mg ha(-1 (bootstrapped 95% CI [238.3, 253.8] in the lower ridge, with upper and lower valley intermediate. In consistent with our expectation, individual species contributed differently to the total aboveground biomass of different habitats, reflecting significant species habitat associations. Different species show differently in habitat preference in terms of biomass contribution. These patterns may be the consequences of ecological strategies difference among different species. Results from this study enhance our ability to evaluate the role of subtropical forests in the regional carbon cycle and provide valuable information to guide the protection and management of subtropical broad-leaved forest for carbon sequestration and carbon storage.

  2. Silica uptake and release in live and decaying biomass in a northern hardwood forest.

    Science.gov (United States)

    Clymans, Wim; Conley, Daniel J; Battles, John J; Frings, Patrick J; Koppers, Mary Margaret; Likens, Gene E; Johnson, Chris E

    2016-11-01

    In terrestrial ecosystems, a large portion (20-80%) of the dissolved Si (DSi) in soil solution has passed through vegetation. While the importance of this "terrestrial Si filter" is generally accepted, few data exist on the pools and fluxes of Si in forest vegetation and the rate of release of Si from decomposing plant tissues. We quantified the pools and fluxes of Si through vegetation and coarse woody debris (CWD) in a northern hardwood forest ecosystem (Watershed 6, W6) at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA. Previous work suggested that the decomposition of CWD may have significantly contributed to an excess of DSi reported in stream-waters following experimental deforestation of Watershed 2 (W2) at the HBEF. We found that woody biomass (wood + bark) and foliage account for approximately 65% and 31%, respectively, of the total Si in biomass at the HBEF. During the decay of American beech (Fagus grandifolia) boles, Si loss tracked the whole-bole mass loss, while yellow birch (Betula alleghaniensis) and sugar maple (Acer saccharum) decomposition resulted in a preferential Si retention of up to 30% after 16 yr. A power-law model for the changes in wood and bark Si concentrations during decomposition, in combination with an exponential model for whole-bole mass loss, successfully reproduced Si dynamics in decaying boles. Our data suggest that a minimum of 50% of the DSi annually produced in the soil of a biogeochemical reference watershed (W6) derives from biogenic Si (BSi) dissolution. The major source is fresh litter, whereas only ~2% comes from the decay of CWD. Decay of tree boles could only account for 9% of the excess DSi release observed following the experimental deforestation of W2. Therefore, elevated DSi concentrations after forest disturbance are largely derived from other sources (e.g., dissolution of BSi from forest floor soils and/or mineral weathering). © 2016 The Authors. Ecology, published by Wiley Periodicals

  3. Space-time dynamics of fine root biomass of six forests in the Maoershan forest region,northeast China

    Institute of Scientific and Technical Information of China (English)

    ZHOU Biao; ZHU Shengying; MAO Zijun; WANG Xiuwei; ZHAO Xizhu; SUN Yuanfa

    2007-01-01

    The Maoershan forestry centre is situated in the Zhangguangcai Mountain of the Changbai mountain range.The main forest types in the Maoershan region are plantation (Pinus sylvestris var.mongolica,Pinus koraiensis and Larix gmelinii) and natural secondary forests (Fraxinus mandshurica,Quercus mongolica and Populus davidiana).Fine roots have enormous surface areas,growing and turning over quickly,which plays an important role in terms of substance cycling and energy flow in the forest ecosystem.This study deals with the dynamics of live,dead,and total fine roots (≤ mm) biomass in the 0-30 cm soil layer using the soil core method.Differences between the six stands in the Maoershan region showed the following results:1) the fine root biomass in the various stands showed obvious differences.The total fine root biomass of six stands from high to low were F.mandshurica (1,030.0 g/m2) > Q.mongolica (973.4 g/m2) > Pinus koraiensis (780.9 g/m2) >L.gmelinii (718.2 g/m2) > Populusdavidiana(709.1 g/m2) > Pinus sylvestris var.mongolica (470.4 g/m2);2) except for L.gmelinii,the development of live fine root biomass agreed with the trend of total fine root biomass.The maximum biomass of live fine roots in Pinus koraiensis or L.gmelinii stand appeared in May,others in June;in the F.mandshurica stand,the minimum biomass of live fine roots occurred in September,others in July or August;3) the proportions of dead fine root biomass varied in different stands;4) the vertical distribution of fine roots was affected by temperature,water,and nutrients;the proportion of fine root biomass was concentrated in the 0-10 cm soil layer.The fine root biomass of six stands in the 0-10 cm soil layer was over 40% of the total fine root biomass;this proportion was 60.3% in F.mandshurica. Space-time dynamics of the various stands had different characteristics.When investigating the substance cycling and energy flows of all forest ecosystems,we should consider the characteristics of

  4. Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure

    Science.gov (United States)

    Frolking, S.; Palace, M. W.; Clark, D. B.; Chambers, J. Q.; Shugart, H. H.; Hurtt, G. C.

    2009-07-01

    Abrupt forest disturbances generating gaps >0.001 km2 impact roughly 0.4-0.7 million km2 a-1. Fire, windstorms, logging, and shifting cultivation are dominant disturbances; minor contributors are land conversion, flooding, landslides, and avalanches. All can have substantial impacts on canopy biomass and structure. Quantifying disturbance location, extent, severity, and the fate of disturbed biomass will improve carbon budget estimates and lead to better initialization, parameterization, and/or testing of forest carbon cycle models. Spaceborne remote sensing maps large-scale forest disturbance occurrence, location, and extent, particularly with moderate- and fine-scale resolution passive optical/near-infrared (NIR) instruments. High-resolution remote sensing (e.g., ˜1 m passive optical/NIR, or small footprint lidar) can map crown geometry and gaps, but has rarely been systematically applied to study small-scale disturbance and natural mortality gap dynamics over large regions. Reducing uncertainty in disturbance and recovery impacts on global forest carbon balance requires quantification of (1) predisturbance forest biomass; (2) disturbance impact on standing biomass and its fate; and (3) rate of biomass accumulation during recovery. Active remote sensing data (e.g., lidar, radar) are more directly indicative of canopy biomass and many structural properties than passive instrument data; a new generation of instruments designed to generate global coverage/sampling of canopy biomass and structure can improve our ability to quantify the carbon balance of Earth's forests. Generating a high-quality quantitative assessment of disturbance impacts on canopy biomass and structure with spaceborne remote sensing requires comprehensive, well designed, and well coordinated field programs collecting high-quality ground-based data and linkages to dynamical models that can use this information.

  5. The importance of biomass net uptake for a trace metal budget in a forest stand in north-eastern France

    Energy Technology Data Exchange (ETDEWEB)

    Gandois, L. [Universite de Toulouse, UPS, INP, EcoLab - Laboratoire d' ecologie fonctionnelle, ENSAT, Avenue de l' Agrobiopole, F-31326 Castanet-Tolosan (France); CNRS, EcoLab, F-31326 Castanet-Tolosan (France); Nicolas, M. [ONF, Direction technique RENECOFOR, Bd de Constance 77300 Fontainebleau (France); VanderHeijden, G. [INRA, centre de Nancy, Equipe BEF, 54280 Champenoux (France); Probst, A., E-mail: anne.probst@ensat.fr [Universite de Toulouse, UPS, INP, EcoLab -Laboratoire d' ecologie fonctionnelle, ENSAT, Avenue de l' Agrobiopole, F-31326 Castanet-Tolosan (France); CNRS, EcoLab, F-31326 Castanet-Tolosan (France)

    2010-11-01

    The trace metal (TM: Cd, Cu, Ni, Pb and Zn) budget (stocks and annual fluxes) was evaluated in a forest stand (silver fir, Abies alba Miller) in north-eastern France. Trace metal concentrations were measured in different tree compartments in order to assess TM partitioning and dynamics in the trees. Inputs included bulk deposition, estimated dry deposition and weathering. Outputs were leaching and biomass exportation. Atmospheric deposition was the main input flux. The estimated dry deposition accounted for about 40% of the total trace metal deposition. The relative importance of leaching (estimated by a lumped parameter water balance model, BILJOU) and net biomass uptake (harvesting) for ecosystem exportation depended on the element. Trace metal distribution between tree compartments (stem wood and bark, branches and needles) indicated that Pb was mainly stored in the stem, whereas Zn and Ni, and to a lesser extent Cd and Cu, were translocated to aerial parts of the trees and cycled in the ecosystem. For Zn and Ni, leaching was the main output flux (> 95% of the total output) and the plot budget (input-output) was negative, whereas for Pb the biomass net exportation represented 60% of the outputs and the budget was balanced. Cadmium and Cu had intermediate behaviours, with 18% and 30% of the total output relative to biomass exportation, respectively, and the budgets were negative. The net uptake by biomass was particularly important for Pb budgets, less so for Cd and Cu and not very important for Zn and Ni in such forest stands.

  6. Modeling and analysis of biomass production systems

    Energy Technology Data Exchange (ETDEWEB)

    Mishoe, J.W.; Lorber, M.N.; Peart, R.M.; Fluck, R.C.; Jones, J.W.

    1984-01-01

    BIOMET is an interactive simulation model that is used to analyze specific biomass and methane production systems. The system model is composed of crop growth models, harvesting, transportation, conversion and economic submodels. By use of menus the users can configure the structure and set selected parameters of the system to analyze the effects of variables within the component models. For example, simulations of a water hyacinth system resulted in yields of 63, 48 and 37 mg/ha/year for different harvest schedules. For napier grass, unit methane costs were $3.04, $2.86 and $2.98 for various yields of biomass. 10 references.

  7. Allometric models for estimating biomass and carbon in Alnus acuminata

    National Research Council Canada - National Science Library

    William Fonseca; Laura Ruíz; Marylin Rojas; Federico Allice

    2013-01-01

    ... (leaves, branches, stem and root) and total tree biomass in Alnus acuminata (Kunth) in Costa Rica. Additionally, models were developed to estimate biomass and carbon in trees per hectare and for total plant biomass per hectare...

  8. Using LiDAR data to measure the 3D green biomass of Beijing urban forest in China.

    Science.gov (United States)

    He, Cheng; Convertino, Matteo; Feng, Zhongke; Zhang, Siyu

    2013-01-01

    The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired'Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m(3), of which coniferous was 28.7871 million m(3) and broad-leaf was 370.3424 million m(3). The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities.

  9. Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

    Science.gov (United States)

    Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.; Shugart, Herman H.

    2017-02-01

    Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model-based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes, manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the

  10. Climate change-associated trends in net biomass change are age dependent in western boreal forests of Canada.

    Science.gov (United States)

    Chen, Han Y H; Luo, Yong; Reich, Peter B; Searle, Eric B; Biswas, Shekhar R

    2016-09-01

    The impacts of climate change on forest net biomass change are poorly understood but critical for predicting forest's contribution to the global carbon cycle. Recent studies show climate change-associated net biomass declines in mature forest plots. The representativeness of these plots for regional forests, however, remains uncertain because we lack an assessment of whether climate change impacts differ with forest age. Using data from plots of varying ages from 17 to 210 years, monitored from 1958 to 2011 in western Canada, we found that climate change has little effect on net biomass change in forests ≤ 40 years of age due to increased growth offsetting increased mortality, but has led to large decreases in older forests due to increased mortality accompanying little growth gain. Our analysis highlights the need to incorporate forest age profiles in examining past and projecting future forest responses to climate change.

  11. 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

  12. Forest Aboveground Biomass Estimation in the Greater Mekong, Subregion and Russian Siberia

    Science.gov (United States)

    Pang, Yong; Li, Zengyuan; Sun, Gouqing; Zhang, Zhiyu; Schmullius, Christiane; Meng, Shili; Ma, Zhenyu; Lu, Hao; Li, Shiming; Liu, Qingwang; Bai, Lina; Tian, Xin

    2016-08-01

    Forests play a vital role in sustainable development and provide a range of economic, social and environmental benefits, including essential ecosystem services such as climate change mitigation and adaptation. We summarized works in forest aboveground biomass estimation in Greater Mekong Subregion (GMS) and Russian Siberia (RuS). Both regions are rich in forest resources. These mapping and estimation works were based on multiple-source remote sensing data and some field measurements. Biomass maps were generated at 500 m and 30 m pixel size for RuS and GMS respectively. With the available of the 2015 PALSAR-2 mosaic at 25 m spacing, Sentinel-2 data at 20 m, we will work on the biomass mapping and dynamic study at higher spatial resolution.

  13. Impact of biogas interventions on forest biomass and regeneration in southern India

    Directory of Open Access Journals (Sweden)

    M. Agarwala

    2017-07-01

    Full Text Available Programs to provide alternative energy sources such as biogas improve indoor air quality and potentially reduce pressure on forests from fuelwood collection. This study tests whether biogas intervention is associated with higher forest biomass and forest regeneration in degraded forests in Chikkaballapur district in Southern India. Using propensity score matching, we find that forest plots in proximity to villages with biogas interventions (treatment had greater forest biomass than comparable plots around villages without biogas (control. We also found significantly higher sapling abundance and diversity in treatment than control plots despite no significant difference in seedling abundances and diversity in treatment forests, suggesting that plants have a higher probability of reaching sapling stage. These results indicate the potential for alternative energy sources that reduce dependence on fuelwood to promote regeneration of degraded forests. However, forest regrowth is not uniform across treatments and is limited by soil nutrients and biased towards species that are light demanding, fire-resistant and can thrive in poor soil conditions.

  14. The amount of carbon in the undergrowth biomass of main types of forests stands in Poland

    Directory of Open Access Journals (Sweden)

    Janyszek Sławomir

    2015-12-01

    Full Text Available The sequestration of carbon in biomass of herb and moss layers of forest ecosystems is relatively less studied, than analogical processes in trees biomass and soil organic mass. The paper presents mean values of carbon concentration and mean amounts of dry mass of plant material in the herb and moss layer of phytocoenoses formed under canopy of stands of main forest-forming species of trees in Poland. The parameters were studied for beech, birch, oak, alder, pine, fir and spruce forest stands, for most of the particular age classes. The studied plots were contained in following plant associations and communities: Ribo nigri-Alnetum, Fraxino-Alnetum, Galio odorati-Fagetum, Luzulo luzuloidis-Fagetum, Molinio caeruleae-Quercetum roboris, Calamagrostio-Quercetum petraeae, Abietetum polonicum, Abieti-Piceetum montanum, Calamagrostio villosae-Piceetum, as well as anthropogenic communities: Betula pendula comm. on Leucobryo-Pinetum habitat, Larix decidua comm. on Tilio-Carpinetum habitat, Pinus sylvestris comm. on Tilio-Carpinetum habitat, Picea abies comm. on Luzulo pilosae-Fagetum habitat (in lowland and Picea abies comm. on Luzulo luzuloidis-Fagetum habitat (in lower mountain localities. The relatively highest carbon amount was observed in oak forests, pine forests and in older age classes of lowland beech forest, where the carbon concentration in dry mass reaches from 60 to 81%. The lowest concentrations were determined for lowland spruce forests, highland fir forests and for alder forests. The carbon concentration reached in these types of ecosystems from 39 to 41%.

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

    Science.gov (United States)

    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...

  16. Effects Of Very Intensive Forest Biomass Harvesting On Short And Long Term Site Productivity

    DEFF Research Database (Denmark)

    Clarke, Nicholas; Callesen, Ingeborg; Helmisaari, Heljä-Sisko

    2008-01-01

    of the nutrient export and to the soil nutrient release capability. We suggest distinction of sensitive and robust soils. Six case studies are used to exemplify the approach and illustrate the importance of deposition, harvesting and soil properties. The distinction of sites and the quantification of nutrient......Intensified forest biomass utilisation causes export of substantial amounts of nutrients from the forest ecosystem. Compared to conventional stems-only harvesting, the most intensive biomass sce nario causes increases in nutrient exports of up to 6-7 times whereas the biomass export increases only...... up to 2 times (Stupak et al. 2007a). High concentrations of nutrients in small branches, twigs, and leaves compared to stems are the main reason. The extensive export of nutrients related to intensive biomass extraction have for many years caused concern for the long-term fertility of the system...

  17. 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.

  18. Biomass Equations for Tropical Forest Tree Species in Mozambique

    Directory of Open Access Journals (Sweden)

    Rosta Mate

    2014-03-01

    Full Text Available Chanfuta (Afzelia quanzensis Welw., Jambire (Millettia stuhlmannii Taub. and Umbila (Pterocarpus angolensis D.C. are, among others, three of the main tropical tree species producing commercial timber in Mozambique. The present study employed destructive biomass estimation methods at three localities in Mozambique (Inhaminga, Mavume, and Tome to acquire data on the mean diameter at breast height (DBH, and height of trees sampled in 21 stands each of Chanfuta and Jambire, and 15 stands of Umbila. Mean diameter at breast height (DBH (ob for Chanfuta, Jambire, and Umbila was: 33.8 ± 12.6 (range 13.5–61.1, 33.4 ± 7.4 (range 21.0–52.2, and 27.0 ± 9.5 (range 14.0–46.5 cm. The mean total values for biomass (kg of trees of Chanfuta, Jambire, and Umbila trees were 864, 1016, and 321 respectively. The mean percentages of total tree biomass as stem, branch and leaf respectively were 54, 43, and 3 for Chanfuta; 77, 22, and 1 for Jambire; and 46, 51, and 3 for Umbila. The best fit species-specific equation for estimating total above ground biomass (AGB was the power equation with only DBH considered as independent variable yielding coefficient of determination (R2 ranging from 0.89 to 0.97. At stand level, a total mean of 27.3 tons ha−1 biomass was determined of which studied species represented 94.6%. At plot level, total mean biomass for Jambire was 11.8 tons ha−1, Chanfuta and Umbila 9.9 and 4.1 tons ha−1 respectively. The developed power equation fitted total and stem biomass data well and could be used for biomass prediction of the studied species in Mozambique.

  19. A meta-analysis of soil microbial biomass responses to forest disturbances

    Directory of Open Access Journals (Sweden)

    Sandra Robin Holden

    2013-06-01

    Full Text Available Climate warming is likely to increase the frequency and severity of forest disturbances, with uncertain consequences for soil microbial communities and their contribution to ecosystem C dynamics. To address this uncertainty, we conducted a meta-analysis of 139 published soil microbial responses to forest disturbances. These disturbances included abiotic (fire, harvesting, storm and biotic (insect, pathogen disturbances. We hypothesized that soil microbial biomass would decline following forest disturbances, but that abiotic disturbances would elicit greater reductions in microbial biomass than biotic disturbances. In support of this hypothesis, across all published studies, disturbances reduced soil microbial biomass by an average of 29.4%. However, microbial responses differed between abiotic and biotic disturbances. Microbial responses were significantly negative following fires, harvest, and storms (48.7%, 19.1%, and 41.7% reductions in microbial biomass, respectively. In contrast, changes in soil microbial biomass following insect infestation and pathogen-induced tree mortality were non-significant, although biotic disturbances were poorly represented in the literature. When measured separately, fungal and bacterial responses to disturbances mirrored the response of the microbial community as a whole. Changes in microbial abundance following disturbance were significantly positively correlated with changes in microbial respiration. We propose that the differential effect of abiotic and biotic disturbances on microbial biomass may be attributable to differences in soil disruption and organic C removal from forests among disturbance types. Altogether, these results suggest that abiotic forest disturbances may significantly decrease soil microbial abundance, with corresponding consequences for microbial respiration. Further studies are needed on the effect of biotic disturbances on forest soil microbial communities and soil C dynamics.

  20. Empowerment model of biomass in west java

    Science.gov (United States)

    Mulyana, C.; Fitriani, N. I.; Saad, A.; Yuliah, Y.

    2017-06-01

    Scarcity of fossil energy accelerates the search of renewable energy sources as the substitution. In West Java, biomass has potential to be developed into bio-briquette because the resources are abundant. The objectives of this research are mapping the potency of biomass as bio-briquette in West Java, and making the model of the empowerment biomass potential involving five fundamental step which are raw material, pre-processing process, conversion mechanism, products, and end user. The main object of this model focused on 3 forms which are solid, liquid, and gas which was made by involving the community component as the owner biomass, district government, academics and researcher communities, related industries as users of biomass, and the central government as the policy holders and investors as a funder. In the model was described their respective roles and mutual relationship one with another so that the bio-briquette as a substitute of fossil fuels can be realized. Application of this model will provide the benefits in renewability energy sources, environmental, socio economical and energy security.

  1. Modeling the impact of forest biomass change on the subsequent ground level solar energy to enhance the understanding of ecosystem service tradeoffs

    Science.gov (United States)

    Background/Question/Methods Solar radiation is a significant environmental driver that impacts the quality and resilience of terrestrial and aquatic habitats, yet its spatiotemporal variations are complicated to model accurately at high resolution over large, complex watersheds. ...

  2. Soil properties and understory herbaceous biomass in forests of three species of Quercus in Northeast Portugal

    Directory of Open Access Journals (Sweden)

    Marina Castro

    2014-12-01

    Full Text Available Aim of study: This paper aims to characterize some soil properties within the first 25 cm of the soil profile and the herbaceous biomass in Quercus forests, and the possible relationships between soil properties and understory standing biomass.Area of study: Three monoespecific Quercus forests (Q. suber L., Q. ilex subsp. rotundifolia Lam. and Q. pyrenaica Willd in NE Portugal.Material and methods: During 1999 and 2000 soil properties (pH-KCl, total soil nitrogen (N, soil organic carbon (SOC, C/N ratio, available phosphorus (P, and available potassium (K and herbaceous biomass production of three forest types: Quercus suber L., Quercus ilex subsp. rotundifolia Lam. and Quercus pyrenaica Willd were studied.Main results: The results showed a different pattern of soil fertility (N, SOC, P, K in Quercus forests in NE of Portugal. The C/N ratio and the herbaceous biomass confirmed this pattern. Research highlights: There is a pattern of Quercus sp. distribution that correlates with different soil characteristics by soil characteristics in NE Portugal. Q. pyrenaica ecosystems were found in more favoured areas (mesic conditions; Q. rotundifolia developed in nutrient-poor soils (oligotrophic conditions; and Q. suber were found in intermediate zones.Keywords: fertility; biomass; C/N ratio; cork oak; holm oak; pyrenean oak.

  3. Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data

    Science.gov (United States)

    Fayad, Ibrahim; Baghdadi, Nicolas; Guitet, Stéphane; Bailly, Jean-Stéphane; Hérault, Bruno; Gond, Valéry; El Hajj, Mahmoud; Tong Minh, Dinh Ho

    2016-10-01

    Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain "wall-to-wall" AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS

  4. Post-Fire Changes in Forest Biomass Retrieved by Airborne LiDAR in Amazonia

    Directory of Open Access Journals (Sweden)

    Luciane Yumie Sato

    2016-10-01

    Full Text Available Fire is one of the main factors directly impacting Amazonian forest biomass and dynamics. Because of Amazonia’s large geographical extent, remote sensing techniques are required for comprehensively assessing forest fire impacts at the landscape level. In this context, Light Detection and Ranging (LiDAR stands out as a technology capable of retrieving direct measurements of vegetation vertical arrangement, which can be directly associated with aboveground biomass. This work aims, for the first time, to quantify post-fire changes in forest canopy height and biomass using airborne LiDAR in western Amazonia. For this, the present study evaluated four areas located in the state of Acre, called Rio Branco, Humaitá, Bonal and Talismã. Rio Branco and Humaitá burned in 2005 and Bonal and Talismã burned in 2010. In these areas, we inventoried a total of 25 plots (0.25 ha each in 2014. Humaitá and Talismã are located in an open forest with bamboo and Bonal and Rio Branco are located in a dense forest. Our results showed that even ten years after the fire event, there was no complete recovery of the height and biomass of the burned areas (p < 0.05. The percentage difference in height between control and burned sites was 2.23% for Rio Branco, 9.26% for Humaitá, 10.03% for Talismã and 20.25% for Bonal. All burned sites had significantly lower biomass values than control sites. In Rio Branco (ten years after fire, Humaitá (nine years after fire, Bonal (four years after fire and Talismã (five years after fire biomass was 6.71%, 13.66%, 17.89% and 22.69% lower than control sites, respectively. The total amount of biomass lost for the studied sites was 16,706.3 Mg, with an average loss of 4176.6 Mg for sites burned in 2005 and 2890 Mg for sites burned in 2010, with an average loss of 3615 Mg. Fire impact associated with tree mortality was clearly detected using LiDAR data up to ten years after the fire event. This study indicates that fire disturbance

  5. Emergent Patterns of Forest Biomass Production from Across and within a Micro-Network

    Science.gov (United States)

    Pederson, N.; Martin Benito, D.; Bishop, D. A.; Dawson, A.; Dietze, M.; Druckenbrod, D.; Dye, A.; Gonzalez, A. C.; Hessl, A. E.; Martin Fernandez, J.; McLachlan, J. S.; Paciorek, C. J.; Poulter, B.; Williams, J. W.

    2014-12-01

    Many factors drive short- and long-term trends in forest biomass production. Replication at multiple scales, from within individual trees up to continental scales, is necessary to determine factors of growth and at what scale they are most important. Here we report on patterns of biomass production from within and across a micro-network of three forests in the northeastern US. Each forest has different histories and species composition, but each is within a similar climatological setting, which gives insight on important factors of short- and long-term patterns of forest production. One emergent pattern is that two forests are showing a large uptick in production over the last decade. Coincident to this uptick, late-season biomass production is showing a significant increase, even among 150-200+ year old trees. The third forest experienced a severe ice storm in the early-Aughts that paused a three-decade trend of increasing production. In the least diverse forest, the most dominant species drives most of the annual to decadal trend in production. In the most diverse forest, no one species appears to be driving landscape-level production, yet the emergent pattern of production reflects not only drought and pluvial events, but the impact of invasive species and the ice storm. Variation in annual biomass production for most species is strongly related to annual variations in soil moisture. Interestingly at the species level, coherency of growth among yellow birch is lower in the oldest forest in which is it is common versus the youngest forest. Differences in coherency suggest different drivers operating at different scales. Growth of red maple is also driven by moisture, but competition appears to be driving a long-term decline of individuals below the canopy. The decline begins soon after a severe defoliation event. In this same forest, however, significant wetting and warming over the last two decades appears to have reduced some of the climatic constraints on red

  6. A GIS approach for the quantification of forest and agricultural biomass in the Basilicata region

    Directory of Open Access Journals (Sweden)

    D. Statuto

    2013-09-01

    Full Text Available In this paper the attention has been focused on the energy from biomass by-product, including forest biomass and agricultural production, waste and other sources of renewable energy, available in the Basilicata Region. In order to determine the quantity of extractable biomass from the forests of the region data from plans for forest management were used. These data were imported in a Geographic Information System, in order to determine in which part of the Region there is the possibility to find greater quantity of biomass. As for the determination of the quantities of agricultural biomass, the energy crops and the agricultural waste (such as crop residues, grass cuttings, pruning, manure, waste coming from agro-food industries, etc. were considered too. The reuse and exploitation of these wastes, while contributing to the solution of problems related to their disposal, promote their recovery as a primary source of energy. Once estimated the annual amount of biomass, the percentage of the annual energy contribution which this kind of by-product is able to ensure was determined; this renewable energy source may therefore significantly contribute to the development of the agro-forestry sector.

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

    Science.gov (United States)

    Zheng, Daolan; Heath, Linda S; Ducey, Mark J

    2008-09-01

    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 and land-cover map (University of Maryland) from Advanced Very High Resolution Radiometer (AVHRR) and 2001 products from Moderate Resolution Imaging Spectroradiometer (MODIS) at 1-km resolution for the region; and 30-m resolution land-cover maps from the National Land Cover Data (NLCD) for a subarea to conduct nine simulations to address our questions. Sensitivity analysis showed that (1) AVHRR data tended to underestimate AGB density by 11%, on average, compared to that estimated using MODIS data; (2) regional mean AGB density increased slightly from 124 (1992) to 126 Mg ha(-1) (2001) by 1.6%; (3) a substantial decrease in total forest AGB across the region was detected, from 2,507 (1992) to 1,961 Tg (2001), an annual rate of -2.4%; and (4) in the subarea, while NLCD-based estimates suggested a 26% decrease in total AGB from 1992 to 2001, AVHRR/MODIS-based estimates indicated a 36% increase. The major source of uncertainty in change detection of total forest AGB over large areas was due to area differences from using land-cover maps produced by different sources. Scaling up 30-m land-cover map to 1-km resolution caused a mean difference of 8% (in absolute value) in forest area estimates at the county-level ranging from 0 to 17% within a 95% confidence interval.

  8. Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.

    Science.gov (United States)

    Guangyi, Mei; Yujun, Sun; Saeed, Sajjad

    2017-01-01

    Using existing equations to estimate the biomass of a single tree or a forest stand still involves large uncertainties. In this study, we developed individual-tree biomass models for Chinese Fir (Cunninghamia lanceolata.) stands in Fujian Province, southeast China, by using 74 previously established models that have been most commonly used to estimate tree biomass. We selected the best fit models and modified them. The results showed that the published model ln(B(Biomass)) = a + b * ln(D) + c * (ln(H))2 + d * (ln(H))3 + e * ln(WD) had the best fit for estimating the tree biomass of Chinese Fir stands. Furthermore, we observed that variables D(diameter at breast height), H (height), and WD(wood density)were significantly correlated with the total tree biomass estimation model. As a result, a natural logarithm structure gave the best estimates for the tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the tree biomass model with Tree volume(TV), WD and biomass wood density conversion factor (BECF),achieved the highest simulation accuracy, expressed as ln(TB) = -0.0703 + 0.9780 * ln(TV) + 0.0213 * ln(WD) + 1.0166 * ln(BECF). Therefore, when TV, WD and BECF were combined with tree biomass volume coefficient bi for Chinese Fir, the stand biomass (SB)model included both volume(SV) and coefficient bi variables of the stand as follows: bi = Exp(-0.0703+0.9780*ln(TV)+0.0213 * ln(WD)+1.0166*ln(BECF)). The stand biomass model is SB = SV/TV * bi.

  9. Changes in forest biomass carbon stock in the Pearl River Delta between 1989 and 2003

    Institute of Scientific and Technical Information of China (English)

    YANG Kun; GUAN Dongsheng

    2008-01-01

    Forest ecosystems play a significant role in maintaining climate stability at the regional and global scales as an important carbon sink. Regional forest carbon storage and its dynamic changes in the Pearl River Delta have been estimated using the continuous biomass expansion factor (BEF) method based on field measurements of forests plots in different age classes and forest inventory data of three periods (1989-1993, 1994-1998, 1999-2003). The results show that regional carbon storage increased by 16.76%, from 48.57×106 to 56.71×106 tons, 80% of which was stored in forest stands. Carbon storage of other types of vegetation, with the exception of shrubland and woodland, increased. Carbon density of the regional forest increased by 14.31%, from 19.08 to 21.81 ton/hm2. Potential carbon storage of the regional forest may reach 39.96×107 tons when the forest biomass peaks with succession.

  10. Are forestation, bio-char and landfilled biomass adequate offsets for the climate effects of burning fossil fuels?

    NARCIS (Netherlands)

    Reijnders, L.

    2009-01-01

    Forestation and landfilling purpose-grown biomass are not adequate offsets for the CO2 emission from burning fossil fuels. Their permanence is insufficiently guaranteed and landfilling purpose-grown biomass may even be counterproductive. As to permanence, bio-char may do better than forests or

  11. Are forestation, bio-char and landfilled biomass adequate offsets for the climate effects of burning fossil fuels?

    NARCIS (Netherlands)

    Reijnders, L.

    2009-01-01

    Forestation and landfilling purpose-grown biomass are not adequate offsets for the CO2 emission from burning fossil fuels. Their permanence is insufficiently guaranteed and landfilling purpose-grown biomass may even be counterproductive. As to permanence, bio-char may do better than forests or landf

  12. 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

  13. Mapping tropical forest biomass with radar and spaceborne LiDAR: overcoming problems of high biomass and persistent cloud

    Directory of Open Access Journals (Sweden)

    E. T. A. Mitchard

    2011-08-01

    Full Text Available Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional to national level. The production of such maps across wide areas will become increasingly necessary as international efforts to protect primary forests, such as the REDD+ (Reducing Emissions from Deforestation and forest Degradation mechanism, come into effect, alongside their use for management and research more generally. However, mapping biomass over high-biomass tropical forest is challenging as (1 direct regressions with optical and radar data saturate, (2 much of the tropics is persistently cloud-covered, reducing the availability of optical data, (3 many regions include steep topography, making the use of radar data complex, (4 while LiDAR data does not suffer from saturation, expensive aircraft-derived data are necessary for complete coverage.

    We present a solution to the problems, using a combination of terrain-corrected L-band radar data (ALOS PALSAR, spaceborne LiDAR data (ICESat GLAS and ground-based data. We map Gabon's Lopé National Park (5000 km2 because it includes a range of vegetation types from savanna to closed-canopy tropical forest, is topographically complex, has no recent cloud-free high-resolution optical data, and the dense forest is above the saturation point for radar. Our 100 m resolution biomass map is derived from fusing spaceborne LiDAR (7142 ICESat GLAS footprints, 96 ground-based plots (average size 0.8 ha and an unsupervised classification of terrain-corrected ALOS PALSAR radar data, from which we derive the aboveground biomass stocks of the park to be 78 Tg C (173 Mg C ha−1. This value is consistent with our field data average of 181 Mg C ha−1, from the field plots measured in 2009 covering a total of 78 ha, and which are independent as they were not used for the GLAS-biomass estimation. We estimate an uncertainty of ± 25 % on our

  14. Allometric models for aboveground biomass of ten tree species in northeast China

    Directory of Open Access Journals (Sweden)

    Shuo Cai

    2013-05-01

    Full Text Available China contains 119 million hectares of natural forest, much of whichis secondary forest. An accurate estimation of the biomass of these forests is imperative because many studies conducted in northeast China have only used primary forest and this may have resulted in biased estimates. This study analyzed secondary forest in the area using information from a forest inventory to develop allometric models of the aboveground biomass (AGB. The parameter values of the diameter at breast height (DBH, tree height (H, and crown length (CL were derived from a forest inventory of 2,733 trees in a 3.5 ha plot. The wood-specific gravity (WSG was determined for 109 trees belonging to ten species. A partial sampling method was also used to determine the biomass of branches (including stem, bark and foliage in 120 trees, which substantially ease the field works. The mean AGB was110,729 kg ha–1. We developed four allometric models from the investigation and evaluated the utility of other 19 published ones for AGB in the ten tree species. Incorporation of full range of variables with WSG-DBH-H-CL, significantly improved the precision of the models. Some of models were chosen that best fitted each tree species with high precision (R2 ≥ 0.939, SEE 0.167. At the latitude level, the estimated AGB of secondary forest was lower than that in mature primary forests, but higher than that in primary broadleaf forest and the average level in other types of forest likewise.

  15. Allometric models for aboveground biomass of ten tree species in northeast China

    Directory of Open Access Journals (Sweden)

    Shuo Cai

    2013-07-01

    Full Text Available China contains 119 million hectares of natural forest, much of which is secondary forest. An accurate estimation of the biomass of these forests is imperative because many studies conducted in northeast China have only used primary forest and this may have resulted in biased estimates. This study analyzed secondary forest in the area using information from a forest inventory to develop allometric models of the aboveground biomass (AGB. The parameter values of the diameter at breast height (DBH, tree height (H, and crown length (CL were derived from a forest inventory of 2,733 trees in a 3.5 ha plot. The wood-specific gravity (WSG was determined for 109 trees belonging to ten species. A partial sampling method was also used to determine the biomass of branches (including stem, bark and foliage in 120 trees, which substantially easy the field works. The mean AGB was 110,729 kg ha–1. We developed four allometric models from the investigation and evaluated the utility of other 19 published ones for AGB in the ten tree species. Incorporation of full range of variables with WSG-DBH-H-CL, significantly improved the precision of the models. Some of models were chosen that best fitted each tree species with high precision (R2 = 0.939, SEE 0.167. At the latitude level, the estimated AGBof secondary forest was lower than that in mature primary forests, but higher than that in primary broadleaf forest and the average level in other types of forest likewise. 

  16. Carbon carry capacity and carbon sequestration potential in China based on an integrated analysis of mature forest biomass.

    Science.gov (United States)

    Liu, YingChun; Yu, GuiRui; Wang, QiuFeng; Zhang, YangJian; Xu, ZeHong

    2014-12-01

    Forests play an important role in acting as a carbon sink of terrestrial ecosystem. Although global forests have huge carbon carrying capacity (CCC) and carbon sequestration potential (CSP), there were few quantification reports on Chinese forests. We collected and compiled a forest biomass dataset of China, a total of 5841 sites, based on forest inventory and literature search results. From the dataset we extracted 338 sites with forests aged over 80 years, a threshold for defining mature forest, to establish the mature forest biomass dataset. After analyzing the spatial pattern of the carbon density of Chinese mature forests and its controlling factors, we used carbon density of mature forests as the reference level, and conservatively estimated the CCC of the forests in China by interpolation methods of Regression Kriging, Inverse Distance Weighted and Partial Thin Plate Smoothing Spline. Combining with the sixth National Forest Resources Inventory, we also estimated the forest CSP. The results revealed positive relationships between carbon density of mature forests and temperature, precipitation and stand age, and the horizontal and elevational patterns of carbon density of mature forests can be well predicted by temperature and precipitation. The total CCC and CSP of the existing forests are 19.87 and 13.86 Pg C, respectively. Subtropical forests would have more CCC and CSP than other biomes. Consequently, relying on forests to uptake carbon by decreasing disturbance on forests would be an alternative approach for mitigating greenhouse gas concentration effects besides afforestation and reforestation.

  17. Carbon dynamics in aboveground coarse wood biomass of wetland forests in the northern Pantanal, Brazil

    Science.gov (United States)

    Schöngart, J.; Arieira, J.; Felfili Fortes, C.; Cezarine de Arruda, E.; Nunes da Cunha, C.

    2008-05-01

    This is the first estimation on carbon dynamics in the aboveground coarse wood biomass (AGWB) of wetland forests in the Pantanal, located in Central Southern America. In four 1-ha plots in stands characterized by the pioneer species Vochysia divergens Pohl (Vochysiaceae) forest inventories (trees ≥10 cm diameter at breast height, DBH) have been performed and converted to predictions of AGWB by five different allometric models using two or three predicting parameters (DBH, tree height, wood density). Best prediction has been achieved using allometric equations with three independent variables. Carbon stocks (50% of AGWB) vary from 7.4 to 100.9 Mg C ha-1 between the four stands. Carbon sequestration differs 0.50-4.24 Mg C ha-1 yr-1 estimated by two growth models derived from tree-ring analysis describing the relationships between age and DBH for V. divergens and other tree species. We find a close correlation between estimated tree age and C-stock, C-sequestration and C-turnover (mean residence of C in AGWB).

  18. Accounting for biomass carbon stock change due to wildfire in temperate forest landscapes in Australia.

    Science.gov (United States)

    Keith, Heather; Lindenmayer, David B; Mackey, Brendan G; Blair, David; Carter, Lauren; McBurney, Lachlan; Okada, Sachiko; Konishi-Nagano, Tomoko

    2014-01-01

    Carbon stock change due to forest management and disturbance must be accounted for in UNFCCC national inventory reports and for signatories to the Kyoto Protocol. Impacts of disturbance on greenhouse gas (GHG) inventories are important for many countries with large forest estates prone to wildfires. Our objective was to measure changes in carbon stocks due to short-term combustion and to simulate longer-term carbon stock dynamics resulting from redistribution among biomass components following wildfire. We studied the impacts of a wildfire in 2009 that burnt temperate forest of tall, wet eucalypts in south-eastern Australia. Biomass combusted ranged from 40 to 58 tC ha(-1), which represented 6-7% and 9-14% in low- and high-severity fire, respectively, of the pre-fire total biomass carbon stock. Pre-fire total stock ranged from 400 to 1040 tC ha(-1) depending on forest age and disturbance history. An estimated 3.9 TgC was emitted from the 2009 fire within the forest region, representing 8.5% of total biomass carbon stock across the landscape. Carbon losses from combustion were large over hours to days during the wildfire, but from an ecosystem dynamics perspective, the proportion of total carbon stock combusted was relatively small. Furthermore, more than half the stock losses from combustion were derived from biomass components with short lifetimes. Most biomass remained on-site, although redistributed from living to dead components. Decomposition of these components and new regeneration constituted the greatest changes in carbon stocks over ensuing decades. A critical issue for carbon accounting policy arises because the timeframes of ecological processes of carbon stock change are longer than the periods for reporting GHG inventories for national emissions reductions targets. Carbon accounts should be comprehensive of all stock changes, but reporting against targets should be based on human-induced changes in carbon stocks to incentivise mitigation activities.

  19. Accounting for biomass carbon stock change due to wildfire in temperate forest landscapes in Australia.

    Directory of Open Access Journals (Sweden)

    Heather Keith

    Full Text Available Carbon stock change due to forest management and disturbance must be accounted for in UNFCCC national inventory reports and for signatories to the Kyoto Protocol. Impacts of disturbance on greenhouse gas (GHG inventories are important for many countries with large forest estates prone to wildfires. Our objective was to measure changes in carbon stocks due to short-term combustion and to simulate longer-term carbon stock dynamics resulting from redistribution among biomass components following wildfire. We studied the impacts of a wildfire in 2009 that burnt temperate forest of tall, wet eucalypts in south-eastern Australia. Biomass combusted ranged from 40 to 58 tC ha(-1, which represented 6-7% and 9-14% in low- and high-severity fire, respectively, of the pre-fire total biomass carbon stock. Pre-fire total stock ranged from 400 to 1040 tC ha(-1 depending on forest age and disturbance history. An estimated 3.9 TgC was emitted from the 2009 fire within the forest region, representing 8.5% of total biomass carbon stock across the landscape. Carbon losses from combustion were large over hours to days during the wildfire, but from an ecosystem dynamics perspective, the proportion of total carbon stock combusted was relatively small. Furthermore, more than half the stock losses from combustion were derived from biomass components with short lifetimes. Most biomass remained on-site, although redistributed from living to dead components. Decomposition of these components and new regeneration constituted the greatest changes in carbon stocks over ensuing decades. A critical issue for carbon accounting policy arises because the timeframes of ecological processes of carbon stock change are longer than the periods for reporting GHG inventories for national emissions reductions targets. Carbon accounts should be comprehensive of all stock changes, but reporting against targets should be based on human-induced changes in carbon stocks to incentivise

  20. Accounting for Biomass Carbon Stock Change Due to Wildfire in Temperate Forest Landscapes in Australia

    Science.gov (United States)

    Keith, Heather; Lindenmayer, David B.; Mackey, Brendan G.; Blair, David; Carter, Lauren; McBurney, Lachlan; Okada, Sachiko; Konishi-Nagano, Tomoko

    2014-01-01

    Carbon stock change due to forest management and disturbance must be accounted for in UNFCCC national inventory reports and for signatories to the Kyoto Protocol. Impacts of disturbance on greenhouse gas (GHG) inventories are important for many countries with large forest estates prone to wildfires. Our objective was to measure changes in carbon stocks due to short-term combustion and to simulate longer-term carbon stock dynamics resulting from redistribution among biomass components following wildfire. We studied the impacts of a wildfire in 2009 that burnt temperate forest of tall, wet eucalypts in south-eastern Australia. Biomass combusted ranged from 40 to 58 tC ha−1, which represented 6–7% and 9–14% in low- and high-severity fire, respectively, of the pre-fire total biomass carbon stock. Pre-fire total stock ranged from 400 to 1040 tC ha−1 depending on forest age and disturbance history. An estimated 3.9 TgC was emitted from the 2009 fire within the forest region, representing 8.5% of total biomass carbon stock across the landscape. Carbon losses from combustion were large over hours to days during the wildfire, but from an ecosystem dynamics perspective, the proportion of total carbon stock combusted was relatively small. Furthermore, more than half the stock losses from combustion were derived from biomass components with short lifetimes. Most biomass remained on-site, although redistributed from living to dead components. Decomposition of these components and new regeneration constituted the greatest changes in carbon stocks over ensuing decades. A critical issue for carbon accounting policy arises because the timeframes of ecological processes of carbon stock change are longer than the periods for reporting GHG inventories for national emissions reductions targets. Carbon accounts should be comprehensive of all stock changes, but reporting against targets should be based on human-induced changes in carbon stocks to incentivise mitigation activities

  1. Allometric Equations for Estimating Tree Aboveground Biomass in Tropical Dipterocarp Forests of Vietnam

    Directory of Open Access Journals (Sweden)

    Bao Huy

    2016-08-01

    Full Text Available There are few allometric equations available for dipterocarp forests, despite the fact that this forest type covers extensive areas in tropical Southeast Asia. This study aims to develop a set of equations to estimate tree aboveground biomass (AGB in dipterocarp forests in Vietnam and to validate and compare their predictive performance with allometric equations used for dipterocarps in Indonesia and pantropical areas. Diameter at breast height (DBH, total tree height (H, and wood density (WD were used as input variables of the nonlinear weighted least square models. Akaike information criterion (AIC and residual plots were used to select the best models; while percent bias, root mean square percentage error, and mean absolute percent error were used to compare their performance to published models. For mixed-species, the best equation was AGB = 0.06203 × DBH 2.26430 × H 0.51415 × WD 0.79456 . When applied to a random independent validation dataset, the predicted values from the generic equations and the dipterocarp equations in Indonesia overestimated the AGB for different sites, indicating the need for region-specific equations. At the genus level, the selected equations were AGB = 0.03713 × DBH 2.73813 and AGB = 0.07483 × DBH 2.54496 for two genera, Dipterocarpus and Shorea, respectively, in Vietnam. Compared to the mixed-species equations, the genus-specific equations improved the accuracy of the AGB estimates. Additionally, the genus-specific equations showed no significant differences in predictive performance in different regions (e.g., Indonesia, Vietnam of Southeast Asia.

  2. Building generalized tree mass/volume component models for improved estimation of forest stocks and utilization potential

    Science.gov (United States)

    David W. MacFarlane

    2015-01-01

    Accurately assessing forest biomass potential is contingent upon having accurate tree biomass models to translate data from forest inventories. Building generality into these models is especially important when they are to be applied over large spatial domains, such as regional, national and international scales. Here, new, generalized whole-tree mass / volume...

  3. Biomass consumption and CO2, CO and main hydrocarbon gas emissions in an Amazonian forest clearing fire

    Science.gov (United States)

    T. G. Soares Neto; J. A. Carvalho; C. A. G. Veras; E. C. Alvarado; R. Gielow; E. N. Lincoln; T. J. Christian; R. J. Yokelson; J. C. Santos

    2009-01-01

    Biomass consumption and CO2, CO and hydrocarbon gas emissions in an Amazonian forest clearing fire are presented and discussed. The experiment was conducted in the arc of deforestation, near the city of Alta Floresta, state of Mato Grosso, Brazil. The average carbon content of dry biomass was 48% and the estimated average moisture content of fresh biomass was 42% on...

  4. Challenges and Opportunities for International Trade in Forest Biomass

    NARCIS (Netherlands)

    Lamers, P.; Mai-Moulin, T.|info:eu-repo/dai/nl/412461021; Junginger, H.M.|info:eu-repo/dai/nl/202130703

    2016-01-01

    In an effort to reduce fossil fuel consumption, the use of woody biomass for heat and power generation is growing. Key destination markets will be countries within the European Union, particularly the United Kingdom, the Netherlands, Denmark and Belgium. While demand from Asia (particularly South Ko

  5. Ozone Tendency in Biomass Burning Plumes: Influence of Biogenic and Anthropogenic Emissions Downwind of Forest Fires

    Science.gov (United States)

    Finch, D.; Palmer, P. I.

    2015-12-01

    Forest fires emit pollutants that can influence downwind surface concentrations of ozone, with potential implications for exceeding air quality regulations. The influence of emissions from biogenic and anthropogenic sources that are mixed into a biomass burning plume as it travels downwind is not well understood. Using the GEOS-Chem atmospheric chemistry transport model and a novel method to track the centre of biomass burning plumes, we identify the chemical reactions that determine ozone production and loss along the plume trajectory. Using a series of sensitivity runs, we quantify the role of biogenic and anthropogenic emissions on the importance of individual chemical reactions. We illustrate the method using data collected during the BORTAS aircraft campaign over eastern Canada during summer 2011. We focus on two contrasting plume trajectories originating from the same multi-day fire in Ontario. The first plume trajectory on 16th July 2011 travels eastward from the fire and eventually mixes with anthropogenic emissions travelling up the east coast of the United States before outflow over the North Atlantic. The second plume trajectory we follow is three days later and travels eastward with a strong northeast component away from large anthropogenic sources. Both trajectories are influenced by downwind biogenic emissions. We generate a chemical reaction narrative for each plume trajectory, allowing is to quantify how mixing pyrogenic, biogenic and anthropogenic emissions influences downwind ozone photochemistry.

  6. Economics, Environmental Impacts, and Supply Chain Analysis of Cellulosic Biomass for Biofuels in the Southern US: Pine, Eucalyptus, Unmanaged Hardwoods, Forest Residues, Switchgrass, and Sweet Sorghum

    Directory of Open Access Journals (Sweden)

    Jesse Daystar

    2013-11-01

    Full Text Available The production of six regionally important cellulosic biomass feedstocks, including pine, eucalyptus, unmanaged hardwoods, forest residues, switchgrass, and sweet sorghum, was analyzed using consistent life cycle methodologies and system boundaries to identify feedstocks with the lowest cost and environmental impacts. Supply chain analysis was performed for each feedstock, calculating costs and supply requirements for the production of 453,592 dry tonnes of biomass per year. Cradle-to-gate environmental impacts from these modeled supply systems were quantified for nine mid-point indicators using SimaPro 7.2 LCA software. Conversion of grassland to managed forest for bioenergy resulted in large reductions in GHG emissions due to carbon uptake associated with direct land use change. By contrast, converting forests to cropland resulted in large increases in GHG emissions. Production of forest-based feedstocks for biofuels resulted in lower delivered cost, lower greenhouse gas (GHG emissions, and lower overall environmental impacts than the agricultural feedstocks studied. Forest residues had the lowest environmental impact and delivered cost per dry tonne. Using forest-based biomass feedstocks instead of agricultural feedstocks would result in lower cradle-to-gate environmental impacts and delivered biomass costs for biofuel production in the southern U.S.

  7. Influence of windthrows and tree species on forest soil plant biomass and carbon stocks

    Science.gov (United States)

    Veselinovic, B.; Hager, H.

    2012-04-01

    The role of forests has generally been recognized in climate change mitigation and adaptation strategies and policies (e.g. Kyoto Protocol within articles 3.3 and 3.4, RES-E Directive of EU, Country Biomass Action Plans etc.). Application of mitigation actions, to decrease of CO2-emissions and, as the increase of carbon(C)-stocks and appropriate GHG-accounting has been hampered due to a lack of reliable data and good statistical models for the factors influencing C-sequestration in and its release from these systems (e.g. natural and human induced disturbances). Highest uncertainties are still present for estimation of soil C-stocks, which is at the same time the second biggest C-reservoir on earth. Spruce monocultures have been a widely used management practice in central Europe during the past century. Such stands are in lower altitudes (e.g. submontane to lower montane elevation zone) and on heavy soils unstable and prone to disturbances, especially on blowdown. As the windthrow-areas act as CO2-source, we hypothesize that conversion to natural beech and oak forests will provide sustainable wood supply and higher stability of stands against blowdown, which simultaneously provides the long-term belowground C-sequestration. This work focuses on influence of Norway spruce, Common beech and Oak stands on belowground C-dynamics (mineral soil, humus and belowground biomass) taking into consideration the increased impact of windthrows on spruce monocultures as a result of climate change. For this purpose the 300-700m altitude and pseudogley (planosols/temporally logged) soils were chosen in order to evaluate long-term impacts of the observed tree species on belowground C-dynamics and human induced disturbances on secondary spruce stands. Using the false chronosequence approach, the C-pools have been estimated for different compartments and age classes. The sampling of forest floor and surface vegetation was done using 30x30 (homogenous plots) and 50x50cm (inhomogeneous

  8. Aboveground biomass, wood volume, nutrient stocks and leaf litter in novel forests compared to native forests and tree plantations in Puerto Rico

    Science.gov (United States)

    A.E. Lugo; O. Abelleira Martínez; J. Fonseca da Silva

    2012-01-01

    The article presents comparative data for aboveground biomass, wood volume, nutirent stocks (N, P, K) and leaf litter in different types of forests in Puerto Rico. The aim of the study is to assess how novel forests of Castilla elastica, Panama Rubber Tree, and Spathodea campanulata, African Tulip Tree, compare with tree plantations and native historical forests (both...

  9. Tropical-Forest Structure and Biomass Dynamics from TanDEM-X Radar Interferometry

    Science.gov (United States)

    Robert Treuhaft; Yang Lei; Fabio Gonçalves; Michael Keller; João Santos; Maxim Neumann; André Almeida

    2017-01-01

    Changes in tropical-forest structure and aboveground biomass (AGB) contribute directly to atmospheric changes in CO2, which, in turn, bear on global climate. This paper demonstrates the capability of radar-interferometric phase-height time series at X-band (wavelength = 3 cm) to monitor changes in vertical structure and AGB, with sub-hectare and monthly spatial and...

  10. Biomass and carbon attributes of downed woody materials in forests of the United States

    Science.gov (United States)

    C.W. Woodall; B.F. Walters; S.N. Oswalt; G.M. Domke; C. Toney; A.N. Gray

    2013-01-01

    Due to burgeoning interest in the biomass/carbon attributes of forest downed and dead woody materials (DWMs) attributable to its fundamental role in the carbon cycle, stand structure/diversity, bioenergy resources, and fuel loadings, the U.S. Department of Agriculture has conducted a nationwide field-based inventory of DWM. Using the national DWM inventory, attributes...

  11. Biomass removal study on the George Washington and Jefferson National Forests

    Science.gov (United States)

    Dana Mitchell; John Klepac

    2017-01-01

    A study was installed on the George Washington National Forest to gather hardwood arvesting production data. The silvicultural prescription for the harvested unit was shelterwood with reserves. There was no biomass removal component included in this study. One purpose of this study was to gather baseline harvesting data for future comparisons of production impacts from...

  12. Effects of fine root length density and root biomass on soil preferential flow in forest ecosystems

    Directory of Open Access Journals (Sweden)

    Yinghu Zhang

    2015-04-01

    Full Text Available Aim of study: The study was conducted to characterize the impacts of plant roots systems (e.g., root length density and root biomass on soil preferential flow in forest ecosystems. Area of study: The study was carried out in Jiufeng National Forest Park, Beijing, China. Material and methods: The flow patterns were measured by field dye tracing experiments. Different species (Sophora japonica Linn,Platycladus orientalis Franco, Quercus dentata Thunbwere quantified in two replicates, and 12 soil depth were applied. Plant roots were sampled in the sieving methods. Root length density and root biomass were measured by WinRHIZO. Dye coverage was implied in the image analysis, and maximum depth of dye infiltration by direct measurement. Main results: Root length density and root biomass decreased with the increasing distance from soil surface, and root length density was 81.6% higher in preferential pathways than in soil matrix, and 66.7% for root biomass with respect to all experimental plots. Plant roots were densely distributed in the upper soil layers. Dye coverage was almost 100% in the upper 5-10 cm, but then decreased rapidly with soil depth. Root length density and root biomass were different from species: Platycladus orientalis Franco > Quercus dentata Thunb > Sophora japonica Linn. Research highlights: The results indicated that fine roots systems had strong effects on soil preferential flow, particularly root channels enhancing nutrition transport across soil profiles in forest dynamics.

  13. Plant biomass and nutrient flux in a managed mangrove forest in Malaysia

    Science.gov (United States)

    Gong, Wooi-Khoon; Ong, Jin-Eong

    1990-11-01

    This paper summarizes previously reported and new data. Data on biomass and nutrient content in different components of the mangrove trees are presented and estimates of the flux of these are attempted. As a first step to determining the quantitative relationship between the export of material and the areal extent of mangroves, the biomass and nutrients contained in the mangrove trees and the release of these to the ecosystem annually were determined for the 40 800-ha Matang Mangrove Forest Reserve—a managed mangrove forest in Malaysia. The total standing biomass of the Matang Mangrove Forest is estimated to be 8·26 milion tonnes (of dry matter). Biomass released annually from the mangrove trees in the Matang system is 1 015 980 tonnes. Of these, 559 500 tonnes or 55% is in the form of dead trees, 396 840 tonnes (39%) is in the form of small litter and 59 640 (6%) in the slash left behind after thinning and harvesting. The amounts of macro-nutrients (N,P,K, Ca, Mg and Na) released annually are 12 210, 11 870 and 2690 tonnes through litter, dead trees and slash respectively. The fate of these materials is discussed. Using the figure of 50% export, the export of biomass and nutrients from the Matang Mangroves through leaf litter alone is estimated as 158 300 and 5100 tonnes annually or 3·9 and 0·1 tonne ha -1 year -1 respectively.

  14. Woody biomass production lags stem-girth increase by over one month in coniferous forests.

    Science.gov (United States)

    Cuny, Henri E; Rathgeber, Cyrille B K; Frank, David; Fonti, Patrick; Mäkinen, Harri; Prislan, Peter; Rossi, Sergio; Del Castillo, Edurne Martinez; Campelo, Filipe; Vavrčík, Hanuš; Camarero, Jesus Julio; Bryukhanova, Marina V; Jyske, Tuula; Gričar, Jožica; Gryc, Vladimír; De Luis, Martin; Vieira, Joana; Čufar, Katarina; Kirdyanov, Alexander V; Oberhuber, Walter; Treml, Vaclav; Huang, Jian-Guo; Li, Xiaoxia; Swidrak, Irene; Deslauriers, Annie; Liang, Eryuan; Nöjd, Pekka; Gruber, Andreas; Nabais, Cristina; Morin, Hubert; Krause, Cornelia; King, Gregory; Fournier, Meriem

    2015-10-26

    Wood is the main terrestrial biotic reservoir for long-term carbon sequestration(1), and its formation in trees consumes around 15% of anthropogenic carbon dioxide emissions each year(2). However, the seasonal dynamics of woody biomass production cannot be quantified from eddy covariance or satellite observations. As such, our understanding of this key carbon cycle component, and its sensitivity to climate, remains limited. Here, we present high-resolution cellular based measurements of wood formation dynamics in three coniferous forest sites in northeastern France, performed over a period of 3 years. We show that stem woody biomass production lags behind stem-girth increase by over 1 month. We also analyse more general phenological observations of xylem tissue formation in Northern Hemisphere forests and find similar time lags in boreal, temperate, subalpine and Mediterranean forests. These time lags question the extension of the equivalence between stem size increase and woody biomass production to intra-annual time scales(3, 4, 5, 6). They also suggest that these two growth processes exhibit differential sensitivities to local environmental conditions. Indeed, in the well-watered French sites the seasonal dynamics of stem-girth increase matched the photoperiod cycle, whereas those of woody biomass production closely followed the seasonal course of temperature. We suggest that forecasted changes in the annual cycle of climatic factors(7) may shift the phase timing of stem size increase and woody biomass production in the future.

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

    OpenAIRE

    Köhler, P.; Huth, A.

    2010-01-01

    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...

  16. 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....

  17. Where did the US forest biomass/carbon go?

    Science.gov (United States)

    Christopher William. Woodall

    2012-01-01

    In Apr. 2012, with the submission of the 1990-2010 US Greenhouse Gas (GHG) Inventory to the United Nations Framework Convention on Climate Change (UNFCCC), the official estimates of aboveground live tree carbon stocks within managed forests of the United States will drop by approximately 14%, compared with last year's inventory. It does not stop there, dead wood...

  18. Modeling biomass gasification in circulating fluidized beds

    Science.gov (United States)

    Miao, Qi

    In this thesis, the modeling of biomass gasification in circulating fluidized beds was studied. The hydrodynamics of a circulating fluidized bed operating on biomass particles were first investigated, both experimentally and numerically. Then a comprehensive mathematical model was presented to predict the overall performance of a 1.2 MWe biomass gasification and power generation plant. A sensitivity analysis was conducted to test its response to several gasifier operating conditions. The model was validated using the experimental results obtained from the plant and two other circulating fluidized bed biomass gasifiers (CFBBGs). Finally, an ASPEN PLUS simulation model of biomass gasification was presented based on minimization of the Gibbs free energy of the reaction system at chemical equilibrium. Hydrodynamics plays a crucial role in defining the performance of gas-solid circulating fluidized beds (CFBs). A 2-dimensional mathematical model was developed considering the hydrodynamic behavior of CFB gasifiers. In the modeling, the CFB riser was divided into two regions: a dense region at the bottom and a dilute region at the top of the riser. Kunii and Levenspiel (1991)'s model was adopted to express the vertical solids distribution with some other assumptions. Radial distributions of bed voidage were taken into account in the upper zone by using Zhang et al. (1991)'s correlation. For model validation purposes, a cold model CFB was employed, in which sawdust was transported with air as the fluidizing agent. A comprehensive mathematical model was developed to predict the overall performance of a 1.2 MWe biomass gasification and power generation demonstration plant in China. Hydrodynamics as well as chemical reaction kinetics were considered. The fluidized bed riser was divided into two distinct sections: (a) a dense region at the bottom of the bed where biomass undergoes mainly heterogeneous reactions and (b) a dilute region at the top where most of homogeneous

  19. Contribution of aboveground biomass uncertainty to bias in modeled global net ecosystem exchange

    Science.gov (United States)

    Poulter, B.; Delbart, N.; Maignan, F.; Saatchi, S. S.; Sitch, S.; Ciais, P.

    2011-12-01

    Biomass is a key ecosystem property that links biogeochemical fluxes with the accumulation of carbon. The spatial and temporal dynamics of biomass have implications for climate stability and other ecosystem services. Globally, terrestrial forest ecosystems store approximately 383 Pg C in aboveground biomass, about 45% compared to the amount of carbon in the atmosphere. Model-data comparisons of aboveground biomass have so far been limited by a lack of wall-to-wall coverage, which has recently been resolved from satellite remote sensing. These recent satellite products use lidar to measure forest structure directly or have developed novel data-fusion techniques. Here, we compare biomass estimates among terrestrial carbon cycle models, and benchmark these estimates with inventory and satellite-based estimates. Using an ensemble of dynamic global vegetation model simulations from the TRENDY archive, we then use the distribution of biomass estimates to evaluate bias in net ecosystem exchange caused by uncertainty from carbon turnover. By identifying detailed model structure and parameters that are linked to carbon turnover, targeted improvements can be made to more realistically simulate aboveground biomass.

  20. Quantifying above- and belowground biomass carbon loss with forest conversion in tropical lowlands of Sumatra (Indonesia).

    Science.gov (United States)

    Kotowska, Martyna M; Leuschner, Christoph; Triadiati, Triadiati; Meriem, Selis; Hertel, Dietrich

    2015-10-01

    Natural forests in South-East Asia have been extensively converted into other land-use systems in the past decades and still show high deforestation rates. Historically, lowland forests have been converted into rubber forests, but more recently, the dominant conversion is into oil palm plantations. While it is expected that the large-scale conversion has strong effects on the carbon cycle, detailed studies quantifying carbon pools and total net primary production (NPPtotal ) in above- and belowground tree biomass in land-use systems replacing rainforest (incl. oil palm plantations) are rare so far. We measured above- and belowground carbon pools in tree biomass together with NPPtotal in natural old-growth forests, 'jungle rubber' agroforests under natural tree cover, and rubber and oil palm monocultures in Sumatra. In total, 32 stands (eight plot replicates per land-use system) were studied in two different regions. Total tree biomass in the natural forest (mean: 384 Mg ha(-1) ) was more than two times higher than in jungle rubber stands (147 Mg ha(-1) ) and >four times higher than in monoculture rubber and oil palm plantations (78 and 50 Mg ha(-1) ). NPPtotal was higher in the natural forest (24 Mg ha(-1)  yr(-1) ) than in the rubber systems (20 and 15 Mg ha(-1)  yr(-1) ), but was highest in the oil palm system (33 Mg ha(-1)  yr(-1) ) due to very high fruit production (15-20 Mg ha(-1)  yr(-1) ). NPPtotal was dominated in all systems by aboveground production, but belowground productivity was significantly higher in the natural forest and jungle rubber than in plantations. We conclude that conversion of natural lowland forest into different agricultural systems leads to a strong reduction not only in the biomass carbon pool (up to 166 Mg C ha(-1) ) but also in carbon sequestration as carbon residence time (i.e. biomass-C:NPP-C) was 3-10 times higher in the natural forest than in rubber and oil palm plantations. © 2015 John Wiley & Sons Ltd.

  1. 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...

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

    Directory of Open Access Journals (Sweden)

    Dapao Yu

    Full Text Available 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.

  3. 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.

  4. Biochar as a possible solution to shortcomings of traditional forest biomass utilization in Finland

    Science.gov (United States)

    Köster, Egle; Berninger, Frank; Pumpanen, Jukka; Palviainen, Marjo; Köster, Kajar

    2017-04-01

    The removal of biomass is reducing C stocks in forests and implies a large removal of nitrogen. Current studies show more than 10% decreases in tree growth and biomass removal seems to be the reason. If some of harvested nutrients could be returned to the ecosystem, the observed reductions in growth might be avoided. The use of biochar has been proposed as a solution to shortcomings of forest biomass use. If the biochar is buried into the soil it will stay there for thousands of years, keeping the C out of the atmosphere, and nourishing the soil. Preferably the origin of the biochar used in forest ecosystems should be also the forest. However, for forest ecosystems studies are rare and it is not clear if biochar applications to the boreal forest would lead to larger biomass production or C neutrality. Furthermore it is not clear how much the source of biochar influences the nutrient content of the final product. We have tried to access and categorize the nutrient contents of biochar from different stocks with an emphasis on wood. We received samples of wood and produced biochar from biochar producers of Finland and one producer from Switzerland. Wooden feed stocks under analysis were birch, willow and spruce. Gained samples of biochar and feed stock have been analyzed for their nutrient contents. Nutrient differences in feed stocks and biochar have been accessed using production data collected from the producers and based on this the ratios between the mass of feed stock and the mass of biochar has been calculated. Data analysis are still in process, but our preliminary results showed that the temperature and time of pyrolysis were positively correlated with the contents of studied nutrients. Overall nutrient contents of biochar produced from spruce were much higher than ones observed in hardwoods.

  5. Aboveground biomass and carbon stocks modelling using non-linear regression model

    Science.gov (United States)

    Ain Mohd Zaki, Nurul; Abd Latif, Zulkiflee; Nazip Suratman, Mohd; Zainee Zainal, Mohd

    2016-06-01

    Aboveground biomass (AGB) is an important source of uncertainty in the carbon estimation for the tropical forest due to the variation biodiversity of species and the complex structure of tropical rain forest. Nevertheless, the tropical rainforest holds the most extensive forest in the world with the vast diversity of tree with layered canopies. With the usage of optical sensor integrate with empirical models is a common way to assess the AGB. Using the regression, the linkage between remote sensing and a biophysical parameter of the forest may be made. Therefore, this paper exemplifies the accuracy of non-linear regression equation of quadratic function to estimate the AGB and carbon stocks for the tropical lowland Dipterocarp forest of Ayer Hitam forest reserve, Selangor. The main aim of this investigation is to obtain the relationship between biophysical parameter field plots with the remotely-sensed data using nonlinear regression model. The result showed that there is a good relationship between crown projection area (CPA) and carbon stocks (CS) with Pearson Correlation (p < 0.01), the coefficient of correlation (r) is 0.671. The study concluded that the integration of Worldview-3 imagery with the canopy height model (CHM) raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the lowland Dipterocarp forest.

  6. Overview of the Biomass Scenario Model

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, Steve [Lexidyne, LLC, Colorado Springs, CO (United States)

    2015-09-01

    This report describes the structure of the October 2012 version of the Biomass Scenario Model (BSM) in considerable detail, oriented towards readers with a background or interest in the underlying modeling structures. Readers seeking a less-detailed summary of the BSM may refer to Peterson (2013). BSM aims to provide a framework for exploring the potential contribution of biofuel technologies to the transportation energy supply for the United States over the next several decades. The model has evolved significantly from the prototype developed as part of the Role of Biomass in America" tm s Energy Future (RBAEF) project. BSM represents the supply chain surrounding conversion pathways for multiple fuel products, including ethanol, butanol, and infrastructure-compatible biofuels such as diesel, jet fuel, and gasoline.

  7. Forest-management modelling

    Science.gov (United States)

    Mark J. Twery; Aaron R. Weiskittel

    2013-01-01

    Forests are complex and dynamic ecosystems comprising individual trees that can vary in both size and species. In comparison to other organisms, trees are relatively long lived (40-2000 years), quite plastic in terms of their morphology and ecological niche, and adapted to a wide variety of habitats, which can make predicting their behaviour exceedingly difficult....

  8. Modeling Woody Biomass Procurement for Bioenergy Production at the Atikokan Generating Station in Northwestern Ontario, Canada

    Directory of Open Access Journals (Sweden)

    Thakur Upadhyay

    2012-12-01

    Full Text Available Efficient procurement and utilization of woody biomass for bioenergy production requires a good understanding of biomass supply chains. In this paper, a dynamic optimization model has been developed and applied to estimate monthly supply and procurement costs of woody biomass required for the Atikokan Generating Station (AGS in northwestern Ontario, based on its monthly electricity production schedule. The decision variables in the model are monthly harvest levels of two types of woody biomass, forest harvest residues and unutilized biomass, from 19,315 forest depletion cells (each 1 km2 for a one year planning horizon. Sixteen scenarios are tested to examine the sensitivity of the cost minimization model to changing economic and technological parameters. Reduction in moisture content and improvement of conversion efficiency showed relatively higher reductions in monthly and total costs of woody biomass feedstock for the AGS. The results of this study help in understanding and designing decision support systems for optimal biomass supply chains under dynamic operational frameworks.

  9. Aboveground biomass and net primary production of semi-evergreen tropical forest of Manipur, north-eastern India

    Institute of Scientific and Technical Information of China (English)

    L.Supriya Devi; P.S Yadava

    2009-01-01

    The aboveground biomass dynamics and net primary productivity were investigated to assess the productive potential of Dipterocarpus forest in Manipur, Northeast India. Two forest stands (stand I and II) were earmarked randomly in the study site for the evaluation of biomass in the different girth classes of tree species by harvest method. The total biomass was 22.50 t·ha-1 and 18.27 t·ha-1 in forest stand I and II respectively. Annual aboveground net primary production varied from 8.86 to 10.43 t·ha-1 respectively in two forest stands (stand I and II). In the present study, the values of production efficiency and the biomass accumulation ratio indicate that the forest is at succession stage with high productive potential.

  10. 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.

  11. Relasphone—Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping

    Directory of Open Access Journals (Sweden)

    Matthieu Molinier

    2016-10-01

    Full Text Available Due to the high cost of traditional forest plot measurements, the availability of up-to-date in situ forest inventory data has been a bottleneck for remote sensing image analysis in support of the important global forest biomass mapping. Capitalizing on the proliferation of smartphones, citizen science is a promising approach to increase spatial and temporal coverages of in situ forest observations in a cost-effective way. Digital cameras can be used as a relascope device to measure basal area, a forest density variable that is closely related to biomass. In this paper, we present the Relasphone mobile application with extensive accuracy assessment in two mixed forest sites from different biomes. Basal area measurements in Finland (boreal zone were in good agreement with reference forest inventory plot data on pine ( R 2 = 0 . 75 , R M S E = 5 . 33 m 2 /ha, spruce ( R 2 = 0 . 75 , R M S E = 6 . 73 m 2 /ha and birch ( R 2 = 0 . 71 , R M S E = 4 . 98 m 2 /ha, with total relative R M S E ( % = 29 . 66 % . In Durango, Mexico (temperate zone, Relasphone stem volume measurements were best for pine ( R 2 = 0 . 88 , R M S E = 32 . 46 m 3 /ha and total stem volume ( R 2 = 0 . 87 , R M S E = 35 . 21 m 3 /ha. Relasphone data were then successfully utilized as the only reference data in combination with optical satellite images to produce biomass maps. The Relasphone concept has been validated for future use by citizens in other locations.

  12. Biomass removal, retention, and costs associated with biomass harvesting in the partial harvest systems of Ontario's Great Lakes-Saint Lawrence forest region : preliminary results

    Energy Technology Data Exchange (ETDEWEB)

    Wolf, D. [Toronto Univ., ON (Canada). Faculty of Forestry

    2010-07-01

    Recent bioenergy policy developments in Ontario have increased interest in forest biomass supply research. Biomass harvested from clearcut and partial harvest system in the Great Lakes-Saint Lawrence (GLSL) region can be used to supply centralized pellet plants or directly to forest mill-based conversion facilities for electricity generation. Preliminary results from a biomass harvesting trial conducted in the GLSL have confirmed that whole-tree harvesting (WTH) and the removal of skid trail results in increased biomass removal and improved operational productivity relative to conventional cut-to-length methods. Biomass removals can be increased through the imposition of smaller minimum topping diameters and the harvesting of unmerchantable trees. The results of a study conducted to evaluate the difference between conventional and biomass harvesting in a shelterwood and selection system in the GLSL has indicated that increases in the amount of firewood and small, irregular blocks of wood recovered from biomass harvests are negligible compared with conventional harvesting practices. Biomass harvesting trials are currently being conducted to determine biomass removal and operational productivity calculations for determining the overall economic feasibility of biomass harvesting for energy in the region.

  13. Forest aboveground biomass estimation in Zhejiang Province using the integration of Landsat TM and ALOS PALSAR data

    Science.gov (United States)

    Zhao, Panpan; Lu, Dengsheng; Wang, Guangxing; Liu, Lijuan; Li, Dengqiu; Zhu, Jinru; Yu, Shuquan

    2016-12-01

    In remote sensing-based forest aboveground biomass (AGB) estimation research, data saturation in Landsat and radar data is well known, but how to reduce this problem for improving AGB estimation has not been fully examined. Different vegetation types have their own species composition and stand structure, thus they have different data saturation values in Landsat or radar data. Optical and radar data also have different characteristics in representing forest stand structures, thus effective use of their features may improve AGB estimation. This research examines the effects of Landsat Thematic Mapper (TM) and ALOS PALSAR L-band data and their integrations in forest AGB estimation of Zhejiang Province, China, and the roles of textural images from both datasets. The linear regression models of AGB were conducted by using (1) Landsat TM alone, (2) ALOS PALSAR data alone, (3) their combination as extra bands, and (4) their data fusion, based on non-stratification and stratification of vegetation types, respectively. The results show that (1) overall, Landsat TM data perform better than PALSAR data, but the latter can produce more accurate estimates for bamboo and shrub, and for forests with AGB values less than 60 Mg/ha; (2) the combination of TM and PALSAR data as extra bands can greatly improve AGB estimation performance, but their fusion using the modified high-pass filter resolution-merging technique cannot; (3) textures are indeed valuable in AGB estimation, especially for forests with complex stand structures such as mixed forests and pine forests with understories of broadleaf species; (4) stratification of vegetation types can improve AGB estimation performance; and (5) the results from the linear regression models are characterized by overestimation and underestimation for the smaller and larger AGB values, respectively, and thus, selecting non-linear models or non-parametric algorithms may be needed in future research.

  14. Analysis of results of biomass forest inventory in northeastern Amazon for development of REDD+ carbon project

    Directory of Open Access Journals (Sweden)

    LEONEL N.C. MELLO

    2016-03-01

    Full Text Available ABSTRACT In Brazil, a significant reduction in deforestation rates occurred during the last decade. In spite of that fact, the average annual rates are still too high, approximately 400.000 ha/year (INPE/Prodes. The projects of emissions reduction through avoided deforestation (REED+ are an important tool to reduce deforestation rates in Brazil. Understanding the amazon forest structure, in terms of biomass stock is key to design avoided deforestation strategies. In this work, we analyze data results from aboveground biomass of 1,019.346,27 hectares in the state of Pará. It was collected data from 16,722 trees in 83 random independent plots. It was tested 4 allometric equations, for DBH > 10cm: Brown et al. (1989, Brown and Lugo (1999, Chambers et al. (2000, Higuchi et al. (1998. It revealed that the biggest carbon stock of above ground biomass is stocked on the interval at DBH between 30cm and 80cm. This biomass compartment stocks 75.70% of total biomass in Higuchi et al. (1998 equation, 75.56% of total biomass in Brown et al. (1989 equation, 78.83% of total biomass in Chambers et al. (2000 equation, and 73.22% in Brown and Lugo (1999 equation.

  15. Above-ground biomass and structure of 260 African tropical forests

    Science.gov (United States)

    Lewis, Simon L.; Sonké, Bonaventure; Sunderland, Terry; Begne, Serge K.; Lopez-Gonzalez, Gabriela; van der Heijden, Geertje M. F.; Phillips, Oliver L.; Affum-Baffoe, Kofi; Baker, Timothy R.; Banin, Lindsay; Bastin, Jean-François; Beeckman, Hans; Boeckx, Pascal; Bogaert, Jan; De Cannière, Charles; Chezeaux, Eric; Clark, Connie J.; Collins, Murray; Djagbletey, Gloria; Djuikouo, Marie Noël K.; Droissart, Vincent; Doucet, Jean-Louis; Ewango, Cornielle E. N.; Fauset, Sophie; Feldpausch, Ted R.; Foli, Ernest G.; Gillet, Jean-François; Hamilton, Alan C.; Harris, David J.; Hart, Terese B.; de Haulleville, Thales; Hladik, Annette; Hufkens, Koen; Huygens, Dries; Jeanmart, Philippe; Jeffery, Kathryn J.; Kearsley, Elizabeth; Leal, Miguel E.; Lloyd, Jon; Lovett, Jon C.; Makana, Jean-Remy; Malhi, Yadvinder; Marshall, Andrew R.; Ojo, Lucas; Peh, Kelvin S.-H.; Pickavance, Georgia; Poulsen, John R.; Reitsma, Jan M.; Sheil, Douglas; Simo, Murielle; Steppe, Kathy; Taedoumg, Hermann E.; Talbot, Joey; Taplin, James R. D.; Taylor, David; Thomas, Sean C.; Toirambe, Benjamin; Verbeeck, Hans; Vleminckx, Jason; White, Lee J. T.; Willcock, Simon; Woell, Hannsjorg; Zemagho, Lise

    2013-01-01

    We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha−1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha−1) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha−1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes. PMID:23878327

  16. Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests.

    Science.gov (United States)

    Ma, Zhihai; Peng, Changhui; Zhu, Qiuan; Chen, Huai; Yu, Guirui; Li, Weizhong; Zhou, Xiaolu; Wang, Weifeng; Zhang, Wenhua

    2012-02-14

    The boreal forests, identified as a critical "tipping element" of the Earth's climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canada's boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canada's boreal forests may become net carbon sources if the climate change-induced droughts continue to intensify.

  17. Estimating aboveground biomass in the boreal forests of the Yukon River Basin, Alaska

    Science.gov (United States)

    Ji, L.; Wylie, B. K.; Nossov, D.; Peterson, B.; Waldrop, M. P.; McFarland, J.; Alexander, H. D.; Mack, M. C.; Rover, J. A.; Chen, X.

    2011-12-01

    Quantification of aboveground biomass (AGB) in Alaska's boreal forests is essential to accurately evaluate terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. However, regional AGB datasets with spatially detailed information (1 m tall), which were converted to plot-level AGB using allometric equations. We acquired Landsat Enhanced Thematic Mapper Plus (ETM+) images from the Web Enabled Landsat Data (WELD) that provides multi-date composites of top-of-atmosphere reflectance and brightness temperature for Alaska. From the WELD images, we generated a three-year (2008 - 2010) image composite for the Yukon River Basin using a series of compositing criteria including non-saturation, non-cloudiness, maximal normalize difference vegetation index (NDVI), and maximal brightness temperature. Airborne lidar datasets were acquired for two sub-regions in the central basin in 2009, which were converted to vegetation height datasets using the bare-earth digital surface model (DSM) and the first-return DSM. We created a multiple regression model in which the response variable was the field-observed AGB and the predictor variables were Landsat-derived reflectance, brightness temperature, and spectral vegetation indices including NDVI, soil adjusted vegetation index (SAVI), enhanced vegetation index (EVI), normalized difference infrared index (NDII), and normalized difference water index (NDWI). Principal component analysis was incorporated in the regression model to remedy the multicollinearity problems caused by high correlations between predictor variables. The model fitted the observed data well with an R-square of 0.62, mean absolute error of 29.1 Mg/ha, and mean bias error of 3.9 Mg/ha. By applying this model to the Landsat mosaic, we generated a 30-m AGB map for the boreal forests in the Yukon River Basin. Validation of the Landsat-derived AGB using the lidar dataset indicated a significant correlation between the AGB estimates and the lidar

  18. Tissue culture and micropropagation for forest biomass production

    Energy Technology Data Exchange (ETDEWEB)

    Mason, E.; Maine, F.W.

    1984-09-01

    An increase in forest production will be necessary in the future when wood becomes a major renewable source of energy and chemicals along with its traditional role of fibre source. This increase could eventually by achieved be proper selection and breeding of trees. Clonal forestry by vegetative propagation of cuttings is becoming a viable alternative to a seedling-based forestry with many advantages, and cutting could be used to quickly propagate large numbers of clones of control-pollinated seedlings. Most forest trees are propagated sexually and seed orchards were started in the US and Canada in the last 40-50 years for breeding purposes. Forests could ultimately be established with improved seedlings instead of from seed with unknown genetic potential, or by natural regeneration. Micropropagation is the term used to refer to the propagation of plants raised by tissue culture methods rather than from seeds or cuttings. Many clonal plantlets could be regenerated asexually in the laboratory and eventually transplanted to permanent sites. In addition the technology could be developed to produce new variants from somatic cells. Tissue culture is a technique which may be useful for plant propagation where conventional methods are inadequate or unsuitable. However, traditional studies of field planting observed over long periods of time would still be necessary. This document has the object of informing those who may wish to know more about these techniques in relation to practical application, and require a general overview rather than experimental details, which are given in an annotated bilbiography. 274 refs., 2 figs., 1 tab.

  19. [Aboveground biomass input of Myristicaceae tree species in the Amazonian Forest in Peru].

    Science.gov (United States)

    Ureta Adrianzén, Marisabel

    2015-03-01

    Amazonian forests are a vast storehouse of biodiversity and function as carbon sinks from biomass that accumulates in various tree species. In these forests, the taxa with the greatest contribution of biomass cannot be precisely defined, and the representative distribution of Myristicaceae in the Peruvian Amazon was the starting point for designing the present study, which aimed to quantify the biomass contribution of this family. For this, I analyzed the databases that corresponded to 38 sample units that were previously collected and that were provided by the TeamNetwork and RAINFOR organizations. The analysis consisted in the estimation of biomass using pre-established allometric equations, Kruskal-Wallis sample comparisons, interpolation-analysis maps, and nonparametric multidimensional scaling (NMDS). The results showed that Myristicaceae is the fourth most important biomass contributor with 376.97 Mg/ha (9.92 Mg/ha in average), mainly due to its abundance. Additionally, the family shows a noticeable habitat preference for certain soil conditions in the physiographic units, such is the case of Virola pavonis in "varillales", within "floodplain", or Iryanthera tessmannii and Virola loretensis in sewage flooded areas or "igapo" specifically, and the preference of Virola elongata and irola surinamensis for white water flooded areas or "varzea" edaphic conditions of the physiographic units taken in the study.

  20. The paradox of inverted biomass pyramids in kelp forest fish communities.

    Science.gov (United States)

    Trebilco, Rowan; Dulvy, Nicholas K; Anderson, Sean C; Salomon, Anne K

    2016-06-29

    Theory predicts that bottom-heavy biomass pyramids or 'stacks' should predominate in real-world communities if trophic-level increases with body size (mean predator-to-prey mass ratio (PPMR) more than 1). However, recent research suggests that inverted biomass pyramids (IBPs) characterize relatively pristine reef fish communities. Here, we estimated the slope of a kelp forest fish community biomass spectrum from underwater visual surveys. The observed biomass spectrum slope is strongly positive, reflecting an IBP. This is incongruous with theory because this steep positive slope would only be expected if trophic position decreased with increasing body size (consumer-to-resource mass ratio, less than 1). We then used δ(15)N signatures of fish muscle tissue to quantify the relationship between trophic position and body size and instead detected strong evidence for the opposite, with PPMR ≈ 1650 (50% credible interval 280-12 000). The natural history of kelp forest reef fishes suggests that this paradox could arise from energetic subsidies in the form of movement of mobile consumers across habitats, and from seasonally pulsed production inputs at small body sizes. There were four to five times more biomass at large body sizes (1-2 kg) than would be expected in a closed steady-state community providing a measure of the magnitude of subsidies.

  1. Effects of forest canopy gap on biomass of Abies faxoniana seedlings and its allocation in subalpine coniferous forests of western Sichuan

    Institute of Scientific and Technical Information of China (English)

    Junren XIAN; Tingxing HU; Yuanbin ZHANG; Kaiyun WANG

    2008-01-01

    Using a strip transect sampling method, the density, height (≤ 100 cm), basal diameter and compo-nents of biomass of Abiesfaxoniana seedlings, living in a forest gap (FG) and under the forest canopy (FC) of sub-alpine natural coniferous forests in western Sichuan, were investigated and the relationships among different com-ponents of biomass analyzed. The results indicated that the density and average height (H) of A. faxoniana seed-lings were significantly different in the FG and under the FC, with the values being 12903 and 2017 per hm2, and 26.6 and 24.3 cm. No significant differences were found in the average basal diameter (D) and biomass. The biomass allocation in seedling components was significantly affec-ted by forest gap. In the FG, the biomass ratio of branch to stem reached a maximum of 1.54 at age 12 and then declined and fluctuated around 0.69. Under the FC, the biomass ratio of branch to stem increased with seedling growth and exceeded 1.0 at about age 15. The total bio-mass and the biomass of leaves, stems, shoots and roots grown in the FG and under the FC were significantly correlated with D2H. There were significant and positive correlations among the biomass of different components.

  2. Effects of phosphorus addition on soil microbial biomass and community composition in three forest types in tropical China

    DEFF Research Database (Denmark)

    Liu, Lei; Gundersen, Per; Zhang, Tao;

    2012-01-01

    Elevated nitrogen (N) deposition in humid tropical regions may aggravate phosphorus (P) deficiency in forest on old weathered soil found in these regions. From January 2007 to August 2009, we studied the responses of soil microbial biomass and community composition to P addition (in two monthly...... portions at level of 15 g P m-2 yr-1) in three tropical forests in southern China. The forests were an old-growth forest and two disturbed forests (mixed species and pine dominated). The objective was to test the hypothesis that P addition would increase microbial biomass and change the composition...... of the microbial community, and that the old-growth forests would be more sensitive to P addition due to its higher soil N availability. Microbial biomass C (MBC) was estimated twice a year and the microbial community structure was quantified by phospholipid fatty acid (PLFA) analysis at the end of the experiment...

  3. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

    Directory of Open Access Journals (Sweden)

    M. Réjou-Méchain

    2014-04-01

    Full Text Available Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+. Though broad scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass (AGB at spatial grains ranging from 5 to 250 m (0.025–6.25 ha, and we evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that the spatial sampling error in AGB is large for standard plot sizes, averaging 46.3% for 0.1 ha subplots and 16.6% for 1 ha subplots. Topographically heterogeneous sites showed positive spatial autocorrelation in AGB at scales of 100 m and above; at smaller scales, most study sites showed negative or nonexistent spatial autocorrelation in AGB. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGB leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with current statistical methods. Overall, our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

  4. Biomass thermochemical gasification: Experimental studies and modeling

    Science.gov (United States)

    Kumar, Ajay

    The overall goals of this research were to study the biomass thermochemical gasification using experimental and modeling techniques, and to evaluate the cost of industrial gas production and combined heat and power generation. This dissertation includes an extensive review of progresses in biomass thermochemical gasification. Product gases from biomass gasification can be converted to biopower, biofuels and chemicals. However, for its viable commercial applications, the study summarizes the technical challenges in the gasification and downstream processing of product gas. Corn stover and dried distillers grains with solubles (DDGS), a non-fermentable byproduct of ethanol production, were used as the biomass feedstocks. One of the objectives was to determine selected physical and chemical properties of corn stover related to thermochemical conversion. The parameters of the reaction kinetics for weight loss were obtained. The next objective was to investigate the effects of temperature, steam to biomass ratio and equivalence ratio on gas composition and efficiencies. DDGS gasification was performed on a lab-scale fluidized-bed gasifier with steam and air as fluidizing and oxidizing agents. Increasing the temperature resulted in increases in hydrogen and methane contents and efficiencies. A model was developed to simulate the performance of a lab-scale gasifier using Aspen Plus(TM) software. Mass balance, energy balance and minimization of Gibbs free energy were applied for the gasification to determine the product gas composition. The final objective was to optimize the process by maximizing the net energy efficiency, and to estimate the cost of industrial gas, and combined heat and power (CHP) at a biomass feedrate of 2000 kg/h. The selling price of gas was estimated to be 11.49/GJ for corn stover, and 13.08/GJ for DDGS. For CHP generation, the electrical and net efficiencies were 37 and 86%, respectively for corn stover, and 34 and 78%, respectively for DDGS. For

  5. Biomass of Secondary Evergreen and Deciduous Broadleaved Mixed Forest in Plateau-type Karst Terrain of Guizhou Province, SW China

    Science.gov (United States)

    Liu, L.

    2014-12-01

    Using allometric functions, harvest and soil column methods, we investigated the biomass of a secondary evergreen and deciduous broadleaved mixed forest in Tianlongshan permanent monitoring plot (a horizontally-projected area of 2 hectares) of Puding Karst Ecosystem Research Station, Guizhou Province, southwestern China. Results showed that the total biomass of the forest is 165.4 Mg·hm-2. The aboveground biomass and root biomass are 137.7 Mg·hm-2 and 27.7 Mg·hm-2, respectively. Among the aboveground biomass, the tree layer accounts for 97.76%, which is obviously greater than the shrub layer and herb layer. Larger trees (the diameter at breast height, DBH is between 5 cm and 20 cm) occupies 76.85% of the aboveground biomass, especially the five dominant species(Lithocarpus confinis, Platycarya longipes, Itea yunnanensis, Machilus cavaleriei and Carpinus pubescens). Shrubs and lianas (DBH = 1 cm) account for more than 30% of total shrub and liana biomass, although their individuals are less than 2% of total shrub individuals and 1% of total liana individuals, respectively. The root biomass differs in root diameters, i.e. coarse root > medium root > fine root. Root biomass decreases with the increase of soil depth. Within soil depth of 20 cm, the root biomass is 20.1 Mg·hm-2, which is more than 70% of total root biomass. Within soil depth of 50 cm, the root biomass is 26.7 Mg·hm-2, which is 96.39% of total root biomass. Compared with non-karst forests in the same climate zone, karst forest has lower biomass and carbon stock, but it further has greater potential of carbon sink.

  6. Hydrological modeling in forested systems

    Science.gov (United States)

    H.E. Golden; G.R. Evenson; S. Tian; Devendra Amatya; Ge Sun

    2015-01-01

    Characterizing and quantifying interactions among components of the forest hydrological cycle is complex and usually requires a combination of field monitoring and modelling approaches (Weiler and McDonnell, 2004; National Research Council, 2008). Models are important tools for testing hypotheses, understanding hydrological processes and synthesizing experimental data...

  7. Investigating Appropriate Sampling Design for Estimating Above-Ground Biomass in Bruneian Lowland Mixed Dipterocarp Forest

    Science.gov (United States)

    Lee, S.; Lee, D.; Abu Salim, K.; Yun, H. M.; Han, S.; Lee, W. K.; Davies, S. J.; Son, Y.

    2014-12-01

    Mixed tropical forest structure is highly heterogeneous unlike plantation or mixed temperate forest structure, and therefore, different sampling approaches are required. However, the appropriate sampling design for estimating the above-ground biomass (AGB) in Bruneian lowland mixed dipterocarp forest (MDF) has not yet been fully clarified. The aim of this study was to provide supportive information in sampling design for Bruneian forest carbon inventory. The study site was located at Kuala Belalong lowland MDF, which is part of the Ulu Tembulong National Park, Brunei Darussalam. Six 60 m × 60 m quadrats were established, separated by a distance of approximately 100 m and each was subdivided into quadrats of 10 m × 10 m, at an elevation between 200 and 300 m above sea level. At each plot all free-standing trees with diameter at breast height (dbh) ≥ 1 cm were measured. The AGB for all trees with dbh ≥ 10 cm was estimated by allometric models. In order to analyze changes in the diameter-dependent parameters used for estimating the AGB, different quadrat areas, ranging from 10 m × 10 m to 60 m × 60 m, were used across the study area, starting at the South-West end and moving towards the North-East end. The derived result was as follows: (a) Big trees (dbh ≥ 70 cm) with sparse distribution have remarkable contribution to the total AGB in Bruneian lowland MDF, and therefore, special consideration is required when estimating the AGB of big trees. Stem number of trees with dbh ≥ 70 cm comprised only 2.7% of all trees with dbh ≥ 10 cm, but 38.5% of the total AGB. (b) For estimating the AGB of big trees at the given acceptable limit of precision (p), it is more efficient to use large quadrats than to use small quadrats, because the total sampling area decreases with the former. Our result showed that 239 20 m × 20 m quadrats (9.6 ha in total) were required, while 15 60 m × 60 m quadrats (5.4 ha in total) were required when estimating the AGB of the trees

  8. Aboveground Biomass Estimation of Individual Trees in a Coastal Planted Forest Using Full-Waveform Airborne Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Lin Cao

    2016-09-01

    Full Text Available The accurate estimation of individual tree level aboveground biomass (AGB is critical for understanding the carbon cycle, detecting potential biofuels and managing forest ecosystems. In this study, we assessed the capability of the metrics of point clouds, extracted from the full-waveform Airborne Laser Scanning (ALS data, and of composite waveforms, calculated based on a voxel-based approach, for estimating tree level AGB individually and in combination, over a planted forest in the coastal region of east China. To do so, we investigated the importance of point cloud and waveform metrics for estimating tree-level AGB by all subsets models and relative weight indices. We also assessed the capability of the point cloud and waveform metrics based models and combo model (including the combination of both point cloud and waveform metrics for tree-level AGB estimation and evaluated the accuracies of these models. The results demonstrated that most of the waveform metrics have relatively low correlation coefficients (<0.60 with other metrics. The combo models (Adjusted R2 = 0.78–0.89, including both point cloud and waveform metrics, have a relatively higher performance than the models fitted by point cloud metrics-only (Adjusted R2 = 0.74–0.86 and waveform metrics-only (Adjusted R2 = 0.72–0.84, with the mostly selected metrics of the 95th percentile height (H95, mean of height of median energy (HOMEμ and mean of the height/median ratio (HTMRμ. Based on the relative weights (i.e., the percentage of contribution for R2 of the mostly selected metrics for all subsets, the metric of 95th percentile height (H95 has the highest relative importance for AGB estimation (19.23%, followed by 75th percentile height (H75 (18.02% and coefficient of variation of heights (Hcv (15.18% in the point cloud metrics based models. For the waveform metrics based models, the metric of mean of height of median energy (HOMEμ has the highest relative importance for AGB

  9. A semi-empirical model for pressurised air-blown fluidized-bed gasification of biomass.

    Science.gov (United States)

    Hannula, Ilkka; Kurkela, Esa

    2010-06-01

    A process model for pressurised fluidized-bed gasification of biomass was developed using Aspen Plus simulation software. Eight main blocks were used to model the fluidized-bed gasifier, complemented with FORTRAN subroutines nested in the programme to simulate hydrocarbon and NH(3) formation as well as carbon conversion. The model was validated with experimental data derived from a PDU-scale test rig operated with various types of biomass. The model was shown to be suitable for simulating the gasification of pine sawdust, pine and eucalyptus chips as well as forest residues, but not for pine bark or wheat straw.

  10. Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity.

    Directory of Open Access Journals (Sweden)

    Jos Barlow

    Full Text Available Fire has become an increasingly important disturbance event in south-western Amazonia. We conducted the first assessment of the ecological impacts of these wildfires in 2008, sampling forest structure and biodiversity along twelve 500 m transects in the Chico Mendes Extractive Reserve, Acre, Brazil. Six transects were placed in unburned forests and six were in forests that burned during a series of forest fires that occurred from August to October 2005. Normalized Burn Ratio (NBR calculations, based on Landsat reflectance data, indicate that all transects were similar prior to the fires. We sampled understorey and canopy vegetation, birds using both mist nets and point counts, coprophagous dung beetles and the leaf-litter ant fauna. Fire had limited influence upon either faunal or floral species richness or community structure responses, and stems <10 cm DBH were the only group to show highly significant (p = 0.001 community turnover in burned forests. Mean aboveground live biomass was statistically indistinguishable in the unburned and burned plots, although there was a significant increase in the total abundance of dead stems in burned plots. Comparisons with previous studies suggest that wildfires had much less effect upon forest structure and biodiversity in these south-western Amazonian forests than in central and eastern Amazonia, where most fire research has been undertaken to date. We discuss potential reasons for the apparent greater resilience of our study plots to wildfire, examining the role of fire intensity, bamboo dominance, background rates of disturbance, landscape and soil conditions.

  11. Modeling forest disturbance and recovery in secondary subtropical dry forests of Puerto Rico

    Science.gov (United States)

    Holm, J. A.; Shugart, H. H., Jr.; Van Bloem, S. J.

    2015-12-01

    Because of human pressures, the need to understand and predict the long-term dynamics of subtropical dry forests is urgent. Through modifications to the ZELIG vegetation demographic model, including the development of species- and site-specific parameters and internal modifications, the capability to predict forest change within the Guanica State Forest in Puerto Rico can now be accomplished. One objective was to test the capability of this new model (i.e. ZELIG-TROP) to predict successional patterns of secondary forests across a gradient of abandoned fields currently being reclaimed as forests. Model simulations found that abandoned fields that are on degraded lands have a delayed response to fully recover and reach a mature forest status during the simulated time period; 200 years. The forest recovery trends matched predictions published in other studies, such that attributes involving early resource acquisition (i.e. canopy height, canopy coverage, density) were the fastest to recover, but attributes used for structural development (i.e. biomass, basal area) were relatively slow in recovery. Biomass and basal area, two attributes that tend to increase during later successional stages, are significantly lower during the first 80-100 years of recovery compared to a mature forest, suggesting that the time scale of resilience in subtropical dry forests needs to be partially redefined. A second objective was to investigate the long and short-term effects of increasing hurricane disturbances on vegetation structure and dynamics, due to hurricanes playing an important role in maintaining dry forest structure in Puerto Rico. Hurricane disturbance simulations within ZELIG-TROP predicted that increasing hurricane intensity (i.e. up to 100% increase) did not lead to a large shift in long-term AGB or NPP. However, increased hurricane frequency did lead to a 5-40% decrease in AGB, and 32-50% increase in NPP, depending on the treatment. In addition, the modeling approach used

  12. 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.

  13. Storage of caatinga forest biomass to improve the quality of wood for energy

    Directory of Open Access Journals (Sweden)

    Martha Andreia Brand

    2016-07-01

    Full Text Available ABSTRACT: This study aimed to evaluate the quality of forest biomass energy, coming from the Caatinga, for different storage times in the field. The study was conducted in southern Piauí, between January and February (rainy season. Samples were collected containing branches and trunks of various species, and samples of branches and trunks separately in 5 sample units of 20x20m. Samples were evaluated in the general state freshly harvested and samples of branches and logs after 15 and 30 days of storage in piles in the field. The analyzes carried out were: moisture content on wet basis, ash content and calorific value. Moisture content of freshly harvested biomass ranged from 39% with two days after cutting to 79% in biomass cut and left distributed in the field for 10 days. After storage in piles for 15 days, branches showed moisture content of 18% and the logs 21%, and net calorific value of 3432kcal kg-1 and 3274kcal kg-1, respectively. After 30 days, moisture content for branches was 13% and the logs 21%, and net calorific value of 3672kcal kg-1 and 3240kcal kg-1, respectively. Ash content of the biomass was low. Cutting trees in the rainy season, with maintenance of biomass in the field for 10 days, resulted in an increment of moisture content. Branches had the best behaviour during the storage. Fifteen days of storage are sufficient for the caatinga biomass to achieve high-quality energy.

  14. Experimental and Modelling Studies of Biomass Pyrolysis

    Institute of Scientific and Technical Information of China (English)

    Ka Leung Lam; Adetoyese Olajire Oyedu~; Chi Wai Hui

    2012-01-01

    The analysis on the feedstock pyrolysis characteristic and the impacts of process parameters on pyrolysis outcomes can assist in the designing, operating and optimizing pyrolysis processes. This work aims to utilize both experimental and modelling approaches to perform the analysis on three biomass feedstocks--wood sawdust, bamboo shred and Jatropha Curcas seed cake residue, and to provide insights for the design_and operation of pyro-lysis processes. For the experimental part, the study investigated the effect of heating rate, final pyrolysis tempera- ture and sample size on pyrolysis using common thermal analysis techniques. For the modelling part, a transient mathematical model that integrates the feedstock characteristic from the experimental study was used to simulate the pyrolysis progress of selected biomass feedstock particles for reactor scenarios. The model composes of several sub-models that describe pyrolysis kinetic and heat flow, particle heat transfer, particle shrinking and reactor opera-tion. With better understanding of the effects of process conditions and feedstock characteristics on pyrolysis through both experimental and modelling studies, this work discusses on the considerations of and interrelation between feedstock size, pyrolysis energy usage, processing time and product quality for the design and operation of pyrolysis processes.

  15. Biomass Scenario Model Documentation: Data and References

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Y.; Newes, E.; Bush, B.; Peterson, S.; Stright, D.

    2013-05-01

    The Biomass Scenario Model (BSM) is a system dynamics model that represents the entire biomass-to-biofuels supply chain, from feedstock to fuel use. The BSM is a complex model that has been used for extensive analyses; the model and its results can be better understood if input data used for initialization and calibration are well-characterized. It has been carefully validated and calibrated against the available data, with data gaps filled in using expert opinion and internally consistent assumed values. Most of the main data sources that feed into the model are recognized as baseline values by the industry. This report documents data sources and references in Version 2 of the BSM (BSM2), which only contains the ethanol pathway, although subsequent versions of the BSM contain multiple conversion pathways. The BSM2 contains over 12,000 total input values, with 506 distinct variables. Many of the variables are opportunities for the user to define scenarios, while others are simply used to initialize a stock, such as the initial number of biorefineries. However, around 35% of the distinct variables are defined by external sources, such as models or reports. The focus of this report is to provide insight into which sources are most influential in each area of the supply chain.

  16. The contribution of trees outside forests to national tree biomass and carbon stocks--a comparative study across three continents.

    Science.gov (United States)

    Schnell, Sebastian; Altrell, Dan; Ståhl, Göran; Kleinn, Christoph

    2015-01-01

    In contrast to forest trees, trees outside forests (TOF) often are not included in the national monitoring of tree resources. Consequently, data about this particular resource is rare, and available information is typically fragmented across the different institutions and stakeholders that deal with one or more of the various TOF types. Thus, even if information is available, it is difficult to aggregate data into overall national statistics. However, the National Forest Monitoring and Assessment (NFMA) programme of FAO offers a unique possibility to study TOF resources because TOF are integrated by default into the NFMA inventory design. We have analysed NFMA data from 11 countries across three continents. For six countries, we found that more than 10% of the national above-ground tree biomass was actually accumulated outside forests. The highest value (73%) was observed for Bangladesh (total forest cover 8.1%, average biomass per hectare in forest 33.4 t ha(-1)) and the lowest (3%) was observed for Zambia (total forest cover 63.9%, average biomass per hectare in forest 32 t ha(-1)). Average TOF biomass stocks were estimated to be smaller than 10 t ha(-1). However, given the large extent of non-forest areas, these stocks sum up to considerable quantities in many countries. There are good reasons to overcome sectoral boundaries and to extend national forest monitoring programmes on a more systematic basis that includes TOF. Such an approach, for example, would generate a more complete picture of the national tree biomass. In the context of climate change mitigation and adaptation, international climate mitigation programmes (e.g. Clean Development Mechanism and Reduced Emission from Deforestation and Degradation) focus on forest trees without considering the impact of TOF, a consideration this study finds crucial if accurate measurements of national tree biomass and carbon pools are required.

  17. Forest biomass flow for fuel wood, fodder and timber security among tribal communities of Jharkhand.

    Science.gov (United States)

    Islam, M A; Quli, S M S; Rai, R; Ali, Angrej; Gangoo, S A

    2015-01-01

    The study investigated extraction and consumption pattern of fuel wood, fodder and timber and forest biomass flow for fuel wood, fodder and timber security among tribal communities in Bundu block of Ranchi district in Jharkhand (India). The study is based on personal interviews of the selected respondents through structured interview schedule, personal observations and participatory rural appraisal tools i.e. key informant interviews and focus group discussions carried out in the sample villages, using multi-stage random sampling technique. The study revealed that the total extraction of fuel wood from different sources in villages was 2978.40 tons annum(-1), at the rate of 0.68 tons per capita annum(-1), which was mostly consumed in cooking followed by cottage industries, heating, community functions and others. The average fodder requirement per household was around 47.77 kg day(-1) with a total requirement of 14227.34 tons annum(-1). The average timber requirement per household was computed to be 0.346 m3 annum(-1) accounting for a total timber demand of 282.49 m3 annum(-1), which is mostly utilized in housing, followed by agricultural implements, rural furniture, carts and carriages, fencing, cattle shed/ store house and others. Forest biomass is the major source of fuel wood, fodder and timber for the primitive societies of the area contributing 1533.28 tons annum(-1) (51.48%) of the total fuel wood requirement, 6971.55 tons annum(-1) (49.00%) of the total fodder requirement and 136.36 m3 annum(-1) (48.27%) of the total timber requirement. The forest biomass is exposed to enormous pressure for securing the needs by the aboriginal people, posing great threat to biodiversity and environment of the region. Therefore, forest biomass conservation through intervention of alternative avenues is imperative to keep pace with the current development and future challenges in the area.

  18. Biomass and nutrient dynamics associated with slash fires in neotropical dry forests

    Energy Technology Data Exchange (ETDEWEB)

    Kauffman, J.B.; Cummings, D.L. (Oregon State Univ., Corvallis (United States)); Sanford, R.L. Jr. (Univ. of Denver, CO (United States)); Salcedo, I.H.; Sampaio, E.V.S.B. (Universidade Federal do Pernambuco, Recife (Brazil))

    1993-01-01

    Unprecedented rates of deforestation and biomass burning in tropical dry forests are dramatically influencing biogeochemical cycles, resulting in resource depletion, declines in biodiversity, and atmospheric pollution. We quantified the effects of deforestation and varying levels of slash-fire severity on nutrient losses and redistribution in a second-growth tropical dry forest ([open quotes]Caatinga[close quotes]) near Serra Talhada, Pernambuco, Brazil. Total aboveground biomass prior to burning was [approx]74 Mg/ha. Nitrogen and phosphorus concentrations were highest in litter, leaves attached to slash, and fine wood debris (biomass, they accounted for [approx]60% of the aboveground pools of N and P. Three experimental fires were conducted during the 1989 burning season. Consumption was 78, 88, and 95% of the total aboveground biomass. As much as 96% of the prefire aboveground N and C pools and 56% of the prefire aboveground P pool was lost. Nitrogen losses exceeded 500 kg/ha and P losses exceeded 20 kg/ha in the fires of the greatest severity. With increasing fire severity, the concentrations of N and P in ash decreased while the concentration of Ca increased. Greater ecosystem losses of these nutrients occurred with increasing fire severity. Following fire, up to 47% of the residual aboveground N and 84% of the residual aboveground P were in the form of ash, quickly lost from the site via wind erosion. Fires appeared to have a minor immediate effect on total N, C, or P in the soils. However, soils in forests with no history of cultivation had significantly higher concentrations of C and P than second-growth forests. It would likely require a century or more of fallow for reaccumulation to occur. However, current fallow periods in this region are 15 yr or less. 38 refs., 2 figs., 7 tabs.

  19. Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran

    Directory of Open Access Journals (Sweden)

    Sara Attarchi

    2014-04-01

    Full Text Available The objective of this study is to develop models based on both optical and L-band Synthetic Aperture Radar (SAR data for above ground dry biomass (hereafter AGB estimation in mountain forests. We chose the site of the Loveh forest, a part of the Hyrcanian forest for which previous attempts to estimate AGB have proven difficult. Uncorrected ETM+ data allow a relatively poor AGB estimation, because topography can hinder AGB estimation in mountain terrain. Therefore, we focused on the use of atmospherically and topographically corrected multispectral Landsat ETM+ and Advanced Land-Observing Satellite/Phased Array L-band Synthetic Aperture Radar (ALOS/PALSAR to estimate forest AGB. We then evaluated 11 different multiple linear regression models using different combinations of corrected spectral and PolSAR bands and their derived features. The use of corrected ETM+ spectral bands and GLCM textures improves AGB estimation significantly (adjusted R2 = 0.59; RMSE = 31.5 Mg/ha. Adding SAR backscattering coefficients as well as PolSAR features and textures increase substantially the accuracy of AGB estimation (adjusted R2 = 0.76; RMSE = 25.04 Mg/ha. Our results confirm that topographically and atmospherically corrected data are indispensable for the estimation of mountain forest’s physical properties. We also demonstrate that only the joint use of PolSAR and multispectral data allows a good estimation of AGB in those regions.

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

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    Minerva Singh

    2015-04-01

    Full Text Available This study develops a modelling framework for utilizing very high-resolution (VHR aerial imagery for monitoring stocks of above-ground biomass (AGB in a tropical forest in Southeast Asia. Three different texture-based methods (grey level co-occurrence metric (GLCM, Gabor wavelets and Fourier-based textural ordination (FOTO were used in conjunction with two different machine learning (ML-based regression techniques (support vector regression (SVR and random forest (RF regression. These methods were implemented on both 50-cm resolution Digital Globe data extracted from Google Earth™ (GE and 8-cm commercially obtained VHR imagery. This study further examines the role of forest biophysical parameters, such as ground-measured canopy cover and vertical canopy height, in explaining AGB distribution. Three models were developed using: (i horizontal canopy variables (i.e., canopy cover and texture variables plus vertical canopy height; (ii horizontal variables only; and (iii texture variables only. AGB was variable across the site, ranging from 51.02 Mg/ha to 356.34 Mg/ha. GE-based AGB estimates were comparable to those derived from commercial aerial imagery. The findings demonstrate that novel use of this array of texture-based techniques with GE imagery can help promote the wider use of freely available imagery for low-cost, fine-resolution monitoring of forests parameters at the landscape scale.

  1. DEVELOPMENT OF LOCAL ALLOMETRIC EQUATION TO ESTIMATE TOTAL ABOVEGROUND BIOMASS IN PAPUA TROPICAL FOREST

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    Sandhi Imam Maulana

    2016-10-01

    Full Text Available Recently, pantropical allometric equations  have been commonly used across the globe to  estimate the aboveground biomass of the forests, including in Indonesia. However, in relation to regional differences in diameter, height and wood density, the lack of data measured, particularly from eastern part of Indonesia, may raise the question on  accuracy of pantropical allometric in such area. Hence, this paper examines  the differences of local allometric equations of Papua Island with equations developed by Chave and his research groups.. Measurements of biomass in this study were conducted directly based on weighing and destructive samplings. Results show that the most appropriate local equation to estimate total aboveground biomass in Papua tropical forest is Log(TAGB = -0.267 + 2.23 Log(DBH +0.649 Log(WD (CF=1.013; VIF=1.6; R2= 95%; R2-adj= 95.1%; RMSE= 0.149; P<0.001. This equation is also a better option in comparison to those of previously published pantropical equations with only 6.47% average deviation and 5.37 points of relative bias. This finding implies that the locally developed equation should be a better option to produce more accurate site specific total aboveground biomass estimation.

  2. Considerations for Sustainable Biomass Production in Quercus-Dominated Forest Ecosystems

    Science.gov (United States)

    Bruckman, Viktor; Yan, Shuai; Hochbichler, Eduard

    2013-04-01

    Our current energy system is mainly based on carbon (C) intensive metabolisms, resulting in great effects on the earth's biosphere. The majority of the energy sources are fossil (crude oil, coal, natural gas) and release CO2 in the combustion (oxidation) process which takes place during utilization of the energy. C released to the atmosphere was once sequestered by biomass over a time span of millions of years and is now being released back into the atmosphere within a period of just decades. In the context of green and CO2 neutral Energy, there is an on-going debate regarding the potentials of obtaining biomass from forests on multiple scales, from stand to international levels. Especially in the context of energy, it is highlighted that biomass is an entirely CO2 neutral feedstock since the carbon stored in wood originates from the atmospheric CO2 pool and it was taken up during plant growth. It needs systems approaches in order to justify this statement and ensure sustainability covering the whole life-cycle from biomass production to (bio)energy consumption. There are a number of Quercus woodland management systems focussing solely on woody biomass production for energetic utilization or a combination with traditional forestry and high quality timber production for trades and industry. They have often developed regionally as a consequence of specific demands and local production capacities, which are mainly driven by environmental factors such as climate and soil properties. We assessed the nutritional status of a common Quercus-dominated forest ecosystem in northern Austria, where we compared biomass- with belowground C and nutrient pools in order to identify potential site limits if the management shifts towards systems with a higher level of nutrient extraction. Heterogeneity of soils, and soil processes are considered, as well as other, growth-limiting factors (e.g. precipitation) and species-specific metabolisms and element translocation.

  3. Impacts of Frequent Burning on Live Tree Carbon Biomass and Demography in Post-Harvest Regrowth Forest

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    Luke Collins

    2014-04-01

    Full Text Available The management of forest ecosystems to increase carbon storage is a global concern. Fire frequency has the potential to shift considerably in the future. These shifts may alter demographic processes and growth of tree species, and consequently carbon storage in forests. Examination of the sensitivity of forest carbon to the potential upper and lower extremes of fire frequency will provide crucial insight into the magnitude of possible change in carbon stocks associated with shifts in fire frequency. This study examines how tree biomass and demography of a eucalypt forest regenerating after harvest is affected by two experimentally manipulated extremes in fire frequency (i.e., ~3 year fire intervals vs. unburnt sustained over a 23 year period. The rate of post-harvest biomass recovery of overstorey tree species, which constituted ~90% of total living tree biomass, was lower within frequently burnt plots than unburnt plots, resulting in approximately 20% lower biomass in frequently burnt plots by the end of the study. Significant differences in carbon biomass between the two extremes in frequency were only evident after >15–20 years of sustained treatment. Reduced growth rates and survivorship of smaller trees on the frequently burnt plots compared to unburnt plots appeared to be driving these patterns. The biomass of understorey trees, which constituted ~10% of total living tree biomass, was not affected by frequent burning. These findings suggest that future shifts toward more frequent fire will potentially result in considerable reductions in carbon sequestration across temperate forest ecosystems in Australia.

  4. Allometric models and aboveground biomass stocks of a West African Sudan Savannah watershed in Benin.

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    Chabi, Adéyèmi; Lautenbach, Sven; Orekan, Vincent Oladokoun Agnila; Kyei-Baffour, Nicholas

    2016-12-01

    The estimation of forest biomass changes due to land-use change is of significant importance for estimates of the global carbon budget. The accuracy of biomass density maps depends on the availability of reliable allometric models used in combination with data derived from satellites images and forest inventory data. To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on allometric equations and the spatial distribution of aboveground biomass stocks in each land use/land cover (LULC) class is needed for the different ecological zones. Such information has been sparse for the West African Sudan Savannah zone. This paper provides new data and results for this important zone. The analysis combines satellite images and locally derived allometric models based on non-destructive measurements to estimate aboveground biomass stocks at the watershed level in the Sudan Savannah zone in Benin. We compared three types of empirically fitted allometric models of varying model complexity with respect to the number of input parameters that are easy to measure at the ground: model type I based only on the diameter at breast height (DBH), type II which used DBH and tree height and model type III which used DBH, tree height and wood density as predictors. While for most LULC classes model III outperformed the other models even the simple model I showed a good performance. The estimated mean dry biomass density values and attached standard error for the different LULC class were 3.28 ± 0.31 (for cropland and fallow), 3.62 ± 0.36 (for Savanna grassland), 4.86 ± 1.03 (for Settlements), 14.05 ± 0.72 (for Shrub savanna), 45.29 ± 2.51 (for Savanna Woodland), 46.06 ± 14.40 (for Agroforestry), 94.58 ± 4.98 (for riparian forest and woodland), 162 ± 64.88 (for Tectona grandis plantations), 179.62 ± 57.61 (for Azadirachta indica plantations), 25.17 ± 7.46 (for Gmelina arborea plantations

  5. Sensitivity of L-Band SAR Backscatter to Aboveground Biomass of Global Forests

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    Yifan Yu

    2016-06-01

    Full Text Available Synthetic Aperture Radar (SAR backscatter measurements are sensitive to forest aboveground biomass (AGB, and the observations from space can be used for mapping AGB globally. However, the radar sensitivity saturates at higher AGB values depending on the wavelength and geometry of radar measurements, and is influenced by the structure of the forest and environmental conditions. Here, we examine the sensitivity of SAR at the L-band frequency (~25 cm wavelength to AGB in order to examine the performance of future joint National Aeronautics and Space Administration, Indian Space Research Organisation NASA-ISRO SAR mission in mapping the AGB of global forests. For SAR data, we use the Phased Array L-Band SAR (PALSAR backscatter from the Advanced Land Observing Satellite (ALOS aggregated at a 100-m spatial resolution; and for AGB data, we use more than three million AGB values derived from the Geoscience Laser Altimeter System (GLAS LiDAR height metrics at about 0.16–0.25 ha footprints across eleven different forest types globally. The results from statistical analysis show that, over all eleven forest types, saturation level of L-band radar at HV polarization on average remains ≥100 Mg·ha−1. Fresh water swamp forests have the lowest saturation with AGB at ~80 Mg·ha−1, while needleleaf forests have the highest saturation at ~250 Mg·ha−1. Swamp forests show a strong backscatter from the vegetation-surface specular reflection due to inundation that requires to be treated separately from those on terra firme. Our results demonstrate that L-Band backscatter relations to AGB can be significantly different depending on forest types and environmental effects, requiring multiple algorithms to map AGB from time series of satellite radar observations globally.

  6. Nisqually Community Forest VELMA modeling

    Science.gov (United States)

    We developed a set of modeling tools to support community-based forest management and salmon-recovery planning in Pacific Northwest watersheds. Here we describe how these tools are being applied to the Mashel River Watershed in collaboration with the Board of Directors of the Nis...

  7. Long-term effects of fuel treatments on aboveground biomass accumulation in ponderosa pine forests of the northern Rocky Mountains

    Science.gov (United States)

    Kate A. Clyatt; Christopher R. Keyes; Sharon M. Hood

    2017-01-01

    Fuel treatments in ponderosa pine forests of the northern Rocky Mountains are commonly used to modify fire behavior, but it is unclear how different fuel treatments impact the subsequent production and distribution of aboveground biomass, especially in the long term. This research evaluated aboveground biomass responses 23 years after treatment in two silvicultural...