Science.gov

Sample records for aboveground biomass estimates

  1. MODIS Based Estimation of Forest Aboveground Biomass in China

    PubMed Central

    Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong

    2015-01-01

    Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha−1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y−1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y−1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y−1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests. PMID:26115195

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

    PubMed

    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. PMID:26115195

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

    PubMed

    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.

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

    USGS Publications Warehouse

    Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.

    2016-01-01

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

  5. Stratified aboveground forest biomass estimation by remote sensing data

    NASA Astrophysics Data System (ADS)

    Latifi, Hooman; Fassnacht, Fabian E.; Hartig, Florian; Berger, Christian; Hernández, Jaime; Corvalán, Patricio; Koch, Barbara

    2015-06-01

    Remote sensing-assisted estimates of aboveground forest biomass are essential for modeling carbon budgets. It has been suggested that estimates can be improved by building species- or strata-specific biomass models. However, few studies have attempted a systematic analysis of the benefits of such stratification, especially in combination with other factors such as sensor type, statistical prediction method and sampling design of the reference inventory data. We addressed this topic by analyzing the impact of stratifying forest data into three classes (broadleaved, coniferous and mixed forest). We compare predictive accuracy (a) between the strata (b) to a case without stratification for a set of pre-selected predictors from airborne LiDAR and hyperspectral data obtained in a managed mixed forest site in southwestern Germany. We used 5 commonly applied algorithms for biomass predictions on bootstrapped subsamples of the data to obtain cross validated RMSE and r2 diagnostics. Those values were analyzed in a factorial design by an analysis of variance (ANOVA) to rank the relative importance of each factor. Selected models were used for wall-to-wall mapping of biomass estimates and their associated uncertainty. The results revealed marginal advantages for the strata-specific prediction models over the unstratified ones, which were more obvious on the wall-to-wall mapped area-based predictions. Yet further tests are necessary to establish the generality of these results. Input data type and statistical prediction method are concluded to remain the two most crucial factors for the quality of remote sensing-assisted biomass models.

  6. Developing a generalized allometric equation for aboveground biomass estimation

    NASA Astrophysics Data System (ADS)

    Xu, Q.; Balamuta, J. J.; Greenberg, J. A.; Li, B.; Man, A.; Xu, Z.

    2015-12-01

    A key potential uncertainty in estimating carbon stocks across multiple scales stems from the use of empirically calibrated allometric equations, which estimate aboveground biomass (AGB) from plant characteristics such as diameter at breast height (DBH) and/or height (H). The equations themselves contain significant and, at times, poorly characterized errors. Species-specific equations may be missing. Plant responses to their local biophysical environment may lead to spatially varying allometric relationships. The structural predictor may be difficult or impossible to measure accurately, particularly when derived from remote sensing data. All of these issues may lead to significant and spatially varying uncertainties in the estimation of AGB that are unexplored in the literature. We sought to quantify the errors in predicting AGB at the tree and plot level for vegetation plots in California. To accomplish this, we derived a generalized allometric equation (GAE) which we used to model the AGB on a full set of tree information such as DBH, H, taxonomy, and biophysical environment. The GAE was derived using published allometric equations in the GlobAllomeTree database. The equations were sparse in details about the error since authors provide the coefficient of determination (R2) and the sample size. A more realistic simulation of tree AGB should also contain the noise that was not captured by the allometric equation. We derived an empirically corrected variance estimate for the amount of noise to represent the errors in the real biomass. Also, we accounted for the hierarchical relationship between different species by treating each taxonomic level as a covariate nested within a higher taxonomic level (e.g. species < genus). This approach provides estimation under incomplete tree information (e.g. missing species) or blurred information (e.g. conjecture of species), plus the biophysical environment. The GAE allowed us to quantify contribution of each different

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

    USGS Publications Warehouse

    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.

  8. Range vegetation type mapping and above-ground green biomass estimations using multispectral imagery. [Wyoming

    NASA Technical Reports Server (NTRS)

    Houston, R. S. (Principal Investigator); Gordon, R. C.

    1974-01-01

    The author has identified the following significant results. Range vegetation types have been successfully mapped on a portion of the 68,000 acre study site located west of Baggs, Wyoming, using ERTS-1 imagery. These types have been ascertained from field transects over a five year period. Comparable studies will be made with EREP imagery. Above-ground biomass estimation studies are being conducted utilizing double sampling techniques on two similar study sites. Information obtained will be correlated with percent relative reflectance measurements obtained on the ground which will be related to image brightness levels. This will provide an estimate of above-ground green biomass with multispectral imagery.

  9. Are Inventory Based and Remotely Sensed Above-Ground Biomass Estimates Consistent?

    PubMed Central

    Hill, Timothy C.; Williams, Mathew; Bloom, A. Anthony; Mitchard, Edward T. A.; Ryan, Casey M.

    2013-01-01

    Carbon emissions resulting from deforestation and forest degradation are poorly known at local, national and global scales. In part, this lack of knowledge results from uncertain above-ground biomass estimates. It is generally assumed that using more sophisticated methods of estimating above-ground biomass, which make use of remote sensing, will improve accuracy. We examine this assumption by calculating, and then comparing, above-ground biomass area density (AGBD) estimates from studies with differing levels of methodological sophistication. We consider estimates based on information from nine different studies at the scale of Africa, Mozambique and a 1160 km2 study area within Mozambique. The true AGBD is not known for these scales and so accuracy cannot be determined. Instead we consider the overall precision of estimates by grouping different studies. Since an the accuracy of an estimate cannot exceed its precision, this approach provides an upper limit on the overall accuracy of the group. This reveals poor precision at all scales, even between studies that are based on conceptually similar approaches. Mean AGBD estimates for Africa vary from 19.9 to 44.3 Mg ha−1, for Mozambique from 12.7 to 68.3 Mg ha−1, and for the 1160 km2 study area estimates range from 35.6 to 102.4 Mg ha−1. The original uncertainty estimates for each study, when available, are generally small in comparison with the differences between mean biomass estimates of different studies. We find that increasing methodological sophistication does not appear to result in improved precision of AGBD estimates, and moreover, inadequate estimates of uncertainty obscure any improvements in accuracy. Therefore, despite the clear advantages of remote sensing, there is a need to improve remotely sensed AGBD estimates if they are to provide accurate information on above-ground biomass. In particular, more robust and comprehensive uncertainty estimates are needed. PMID:24069275

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

    PubMed Central

    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. PMID:27309718

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

    PubMed

    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. PMID:27309718

  12. Improved allometric models to estimate the aboveground biomass of tropical trees.

    PubMed

    Chave, Jérôme; Réjou-Méchain, Maxime; Búrquez, Alberto; Chidumayo, Emmanuel; Colgan, Matthew S; Delitti, Welington B C; Duque, Alvaro; Eid, Tron; Fearnside, Philip M; Goodman, Rosa C; Henry, Matieu; Martínez-Yrízar, Angelina; Mugasha, Wilson A; Muller-Landau, Helene C; Mencuccini, Maurizio; Nelson, Bruce W; Ngomanda, Alfred; Nogueira, Euler M; Ortiz-Malavassi, Edgar; Pélissier, Raphaël; Ploton, Pierre; Ryan, Casey M; Saldarriaga, Juan G; Vieilledent, Ghislain

    2014-10-01

    Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development. PMID:24817483

  13. Improved allometric models to estimate the aboveground biomass of tropical trees.

    PubMed

    Chave, Jérôme; Réjou-Méchain, Maxime; Búrquez, Alberto; Chidumayo, Emmanuel; Colgan, Matthew S; Delitti, Welington B C; Duque, Alvaro; Eid, Tron; Fearnside, Philip M; Goodman, Rosa C; Henry, Matieu; Martínez-Yrízar, Angelina; Mugasha, Wilson A; Muller-Landau, Helene C; Mencuccini, Maurizio; Nelson, Bruce W; Ngomanda, Alfred; Nogueira, Euler M; Ortiz-Malavassi, Edgar; Pélissier, Raphaël; Ploton, Pierre; Ryan, Casey M; Saldarriaga, Juan G; Vieilledent, Ghislain

    2014-10-01

    Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.

  14. Estimating aboveground biomass for broadleaf woody plants and young conifers in Sierra Nevada, California forests.

    USGS Publications Warehouse

    McGinnis, Thomas W.; Shook, Christine D.; Keeley, Jon E.

    2010-01-01

    Quantification of biomass is fundamental to a wide range of research and natural resource management goals. An accurate estimation of plant biomass is essential to predict potential fire behavior, calculate carbon sequestration for global climate change research, assess critical wildlife habitat, and so forth. Reliable allometric equations from simple field measurements are necessary for efficient evaluation of plant biomass. However, allometric equations are not available for many common woody plant taxa in the Sierra Nevada. In this report, we present more than 200 regression equations for the Sierra Nevada western slope that relate crown diameter, plant height, crown volume, stem diameter, and both crown diameter and height to the dry weight of foliage, branches, and entire aboveground biomass. Destructive sampling methods resulted in regression equations that accurately predict biomass from one or two simple, nondestructive field measurements. The tables presented here will allow researchers and natural resource managers to easily choose the best equations to fit their biomass assessment needs.

  15. Estimating aboveground biomass for broadleaf woody plants and young conifers in Sierra Nevada, California, forests

    USGS Publications Warehouse

    McGinnis, T.W.; Shook, C.D.; Keeley, J.E.

    2010-01-01

    Quantification of biomass is fundamental to a wide range of research and natural resource management goals. An accurate estimation of plant biomass is essential to predict potential fire behavior, calculate carbon sequestration for global climate change research, assess critical wildlife habitat, and so forth. Reliable allometric equations from simple field measurements are necessary for efficient evaluation of plant biomass. However, allometric equations are not available for many common woody plant taxa in the Sierra Nevada. In this report, we present more than 200 regression equations for the Sierra Nevada western slope that relate crown diameter, plant height, crown volume, stem diameter, and both crown diameter and height to the dry weight of foliage, branches, and entire aboveground biomass. Destructive sampling methods resulted in regression equations that accurately predict biomass from one or two simple, nondestructive field measurements. The tables presented here will allow researchers and natural resource managers to easily choose the best equations to fit their biomass assessment needs.

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

    USGS Publications Warehouse

    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 < 0.05), but the form and variables comprising the best model varied among species. We applied the best-fit regression models to structural information from the shrub stratum in 18 plots on Big Pine Key, the most extensive pine forest in the Keys. Estimates based on species-specific equations indicated clearly that total 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.

  17. Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing

    NASA Astrophysics Data System (ADS)

    Ni-Meister, Wenge; Lee, Shihyan; Strahler, Alan H.; Woodcock, Curtis E.; Schaaf, Crystal; Yao, Tian; Ranson, K. Jon; Sun, Guoqing; Blair, J. Bryan

    2010-06-01

    Lidar-based aboveground biomass is derived based on the empirical relationship between lidar-measured vegetation height and aboveground biomass, often leading to large uncertainties of aboveground biomass estimates at large scales. This study investigates whether the use of any additional lidar-derived vegetation structure parameters besides height improves aboveground biomass estimation. The analysis uses data collected in the field and with the Laser Vegetation Imaging Sensor (LVIS), and the Echidna® validation instrument (EVI), a ground-based hemispherical-scanning lidar data in New England in 2003 and 2007. Our field data analysis shows that using wood volume (approximated by the product of basal area and top 10% tree height) and vegetation type (conifer/softwood or deciduous/hardwood forests, providing wood density) has the potential to improve aboveground biomass estimates at large scales. This result is comparable to previous individual-tree based analyses. Our LVIS data analysis indicates that structure parameters that combine height and gap fraction, such as RH100*cover and RH50*cover, are closely related to wood volume and thus biomass particularly for conifer forests. RH100*cover and RH50*cover perform similarly or even better than RH50, a good biomass predictor found in previous study. This study shows that the use of structure parameters that combine height and gap fraction (rather than height alone) improves the aboveground biomass estimate, and that the fusion of lidar and optical remote sensing (to provide vegetation type) will provide better aboveground biomass estimates than using lidar alone. Our ground lidar analysis shows that EVI provides good estimates of wood volume, and thus accurate estimates of aboveground biomass particularly at the stand level.

  18. Assessing General Relationships Between Above-Ground Biomass and Vegetation Structure Parameters for Improved Carbon Estimate from Lidar Remote Sensing

    NASA Astrophysics Data System (ADS)

    Ni-Meister, W.; Lee, S.; Strahler, A. H.; Woodcock, C. E.; Schaaf, C.; Yao, T.; Ranson, J.; Sun, G.; Blair, J. B.

    2009-12-01

    Lidar remote sensing uses vegetation height to estimate large-scale above-ground biomass. However, lidar height and biomass relationships are empirical and thus often lead to large uncertainties in above-ground biomass estimates. This study uses vegetation structure measurements from field: an airborne lidar (Laser Vegetation Imaging Sensor, LVIS)) and a full wave form ground-based lidar (Echidna® validation instrument, EVI) collected in the New England region in 2003 and 2007, to investigate using additional vegetation structure parameters besides height for improved above-ground biomass estimation from lidar. Our field data analysis shows that using woody volume (approximated by the product of basal area and top 10% tree height) and vegetation type (conifer/softwood or deciduous/hardwood forests, providing wood density) has the potential to improve above-ground biomass estimates at large scale. This result is comparable to previous work by Chave et al. (2005), which focused on individual trees. However this study uses a slightly different approach, and our woody volume is estimated differently from Chave et al. (2005). Previous studies found that RH50 is a good predictor of above-ground biomass (Drake et al., 2002; 2003). Our LVIS data analysis shows that structure parameters that combine height and gap fraction, such as RH100*cover and RH50*cover, perform similarly or even better than RH50. We also found that the close relationship of RH100*cover and RH50*cover with woody volume explains why they are good predictors of above-ground biomass. RH50 is highly related to RH100*cover, and this explains why RH50 is a better predictor of biomass than RH100. This study shows that using structure parameters combining height and gap fraction improve above-ground biomass estimate compared to height alone, and fusion of lidar and optical remote sensing (to provide vegetation type) will provide better above-ground biomass estimates than lidar alone. Ground lidar analysis

  19. Estimation of aboveground biomass in forests using multi-sensor (LIDAR, IFSAR, ETM+) fusion

    NASA Astrophysics Data System (ADS)

    Hyde, P.; Dubuyah, R.; Blair, B.; Hofton, M.; Hunsaker, C.; Pierce, L.; Walker, W.

    2002-05-01

    Aboveground biomass in forests, or the dry weight of standing trees, is a key ecosystem parameter for carbon dynamics, fire modeling, and biodiversity studies. Field-based assessments are expensive and methods to scale from field plots to landscapes are not generally accepted. Remote sensing potentially provides a cost-effective alternative, but no single sensor has yet to provide accurate, consistent estimates in all biomes. Passive optical sensors and synthetic aperture radar (SAR) have been proven effective only in young, structurally simple forests. Light detecting and ranging (LIDAR) has been effective in old-growth, structurally complex forests, but data are not widely available. Combining information from these sensors will leverage the high information content, high cost LIDAR data with lower cost, more widely available SAR and passive optical data. In this study, Landsat ETM+, x-band interferometric SAR, and airborne LIDAR from the Laser Vegetation Imaging Sensor (LVIS) were statistically fused using a decision tree classifier and compared to field-based estimates of biomass in Sierra National Forest, CA, USA. Biomass estimates derived from all sensors combined were more accurate than those derived from any single sensor.

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

    NASA Astrophysics Data System (ADS)

    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.

  1. Estimating aboveground biomass in interior Alaska with Landsat data and field measurements

    USGS Publications Warehouse

    Ji, Lei; Wylie, Bruce K.; Nossov, Dana R.; Peterson, Birgit E.; Waldrop, Mark P.; McFarland, Jack W.; Rover, Jennifer R.; Hollingsworth, Teresa N.

    2012-01-01

    Terrestrial plant biomass is a key biophysical parameter required for understanding ecological systems in Alaska. An accurate estimation of biomass at a regional scale provides an important data input for ecological modeling in this region. In this study, we created an aboveground biomass (AGB) map at 30-m resolution for the Yukon Flats ecoregion of interior Alaska using Landsat data and field measurements. Tree, shrub, and herbaceous AGB data in both live and dead forms were collected in summers and autumns of 2009 and 2010. Using the Landsat-derived spectral variables and the field AGB data, we generated a regression model and applied this model to map AGB for the ecoregion. A 3-fold cross-validation indicated that the AGB estimates had a mean absolute error of 21.8 Mg/ha and a mean bias error of 5.2 Mg/ha. Additionally, we validated the mapping results using an airborne lidar dataset acquired for a portion of the ecoregion. We found a significant relationship between the lidar-derived canopy height and the Landsat-derived AGB (R2 = 0.40). The AGB map showed that 90% of the ecoregion had AGB values ranging from 10 Mg/ha to 134 Mg/ha. Vegetation types and fires were the primary factors controlling the spatial AGB patterns in this ecoregion.

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

    PubMed

    Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

    2015-01-01

    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. PMID:26263996

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

    PubMed Central

    Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

    2015-01-01

    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. PMID:26263996

  4. Estimating aboveground biomass in Avicennia marina plantation in Indian Sundarbans using high-resolution satellite data

    NASA Astrophysics Data System (ADS)

    Manna, Sudip; Nandy, Subrata; Chanda, Abhra; Akhand, Anirban; Hazra, Sugata; Dadhwal, Vinay Kumar

    2014-01-01

    Mangroves are active carbon sequesters playing a crucial role in coastal ecosystems. In the present study, aboveground biomass (AGB) was estimated in a 5-year-old Avicennia marina plantation (approximate area ≈190 ha) of Indian Sundarbans using high-resolution satellite data in order to assess its carbon sequestration potential. The reflectance values of each band of LISS IV satellite data and the vegetation indices, viz., normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), and transformed difference vegetation index (TDVI), derived from the satellite data, were correlated with the AGB. OSAVI showed the strongest positive linear relationship with the AGB and hence carbon content of the stand. OSAVI was found to predict the AGB to a great extent (r=0.72) as it is known to nullify the background soil reflectance effect added to vegetation reflectance. The total AGB of the entire plantation was estimated to be 236 metric tons having a carbon stock of 54.9 metric tons, sequestered within a time span of 5 years. Integration of this technique for monitoring and management of young mangrove plantations will give time and cost effective results.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Applying ICESat/GLAS data to estimate forest aboveground biomass on Hokkaido, Japan

    NASA Astrophysics Data System (ADS)

    Hayashi, M.; Saigusa, N.; Oguma, H.; Yamao, Y.; Yamagata, Y.; Takao, G.

    2013-12-01

    Spaceborne Light Detection And Ranging (LiDAR) has an ability to measure forest resources with high accuracy, therefore, it will contribute to evaluating global carbon cycle or addressing climate change. We then evaluated the potential of spaceborne LiDAR to measure forest resources, and used Geoscience Laser Altimeter System (GLAS) data obtained with the Ice, Cloud, and land Elevation Satellite (ICESat) to develop an estimation methodology for forest biomass. The study area was the island of Hokkaido, Japan. We compared two estimation methods: (i) a direct method that uses some of the GLAS waveform parameters to estimate aboveground biomass (AGB) directly, and (ii) an allometric method that uses an allometric equation to estimate AGB from the canopy height estimated from the GLAS waveform. We used two kinds of ground truth data: (i) field survey data in situ measurements of AGB by the Bitterlich method at 106 points within GLAS footprints, and (ii) airborne LiDAR data from maximum canopy height measurements at 481 points within GLAS footprints. We then used the field survey data to develop the AGB estimation equation of the direct method by carrying out a multiple regression analysis that related GLAS waveform parameters to AGB. For the allometric method, we also carried out a multiple regression analysis using the airborne LiDAR data to estimate canopy height from GLAS data. Two parameters were used as the explanatory variables: a 'terrain index' calculated from the ground elevation difference within a GLAS footprint, and a 'GLAS waveform extent'. The root mean square error (RMSE) of the canopy height estimates was 4.1 m. We used the allometric equation determined from the field survey data to relate canopy height to AGB and then estimated the AGB from the GLAS estimates of canopy height. The accuracy of the AGB estimates obtained by these two estimation methods was determined by comparison with the field survey data. The RMSEs of the direct and allometric

  7. Toward Aboveground Biomass Estimation with RADAR, Lidar and Optical Remote Sensing Data in Southern Mexico

    NASA Astrophysics Data System (ADS)

    Urbazaev, M.; Thiel, C. J.; Schmullius, C.

    2014-12-01

    Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed (1) for understanding and managing the processes involved in the carbon cycle, and (2) supporting international policies for climate change mitigation and adaption. Using remote sensing techniques it is possible to provide spatially explicit information of AGB from local to global scales. In this work we present the first results on the use of multi-sensor remote sensing data to estimate AGB over three test sites in southern Mexico. In order to develop a set of AGB retrieval algorithms, we firstly compared different SAR parameters (e.g. multi-polarized backscatter intensities and interferometric coherence) obtained from ALOS PALSAR sensor and Landsat imagery with field-based AGB estimates using empirical regressions and analyzed the relationships between them. The next steps of the work will be development of a two-stage up-scaling approach: firstly, to enlarge the cal/val data, we propose to estimate AGB along airborne LiDAR (from G-LiHT sensor) transects using field-based AGB and LiDAR height metrics. With LiDAR-based AGB we will then calibrate SAR parameters in a non-parametric model (e.g., randomForest) to create AGB maps over the study areas. An overall aim of the study is the analysis of capabilities and limitations of SAR data for AGB mapping and the investigation of the potential synergistic use of SAR, LiDAR and optical systems.The proposed monitoring tool will facilitate quantitative estimations in loss of carbon storage and support the selection of terrestrial (e.g. tropical dry forests, shrublands) sites for conservation priorities with high value for the national carbon budget.

  8. Quantification of uncertainty in aboveground biomass estimates derived from small-footprint LiDAR data

    NASA Astrophysics Data System (ADS)

    Xu, Q.; Greenberg, J. A.; Li, B.; Ramirez, C.; Balamuta, J. J.; Evans, K.; Man, A.; Xu, Z.

    2015-12-01

    A promising approach to determining aboveground biomass (AGB) in forests comes through the use of individual tree crown delineation (ITCD) techniques applied to small-footprint LiDAR data. These techniques, when combined with allometric equations, can produce per-tree estimates of AGB. At this scale, AGB estimates can be quantified in a manner similar to how ground-based forest inventories are produced. However, these approaches have significant uncertainties that are rarely described in full. Allometric equations are often based on species-specific diameter-at-breast height (DBH) relationships, but neither DBH nor species can be reliably determined using remote sensing analysis. Furthermore, many approaches to ITCD only delineate trees appearing in the upper canopy so subcanopy trees are often missing from the inventories. In this research, we performed a propagation-of-error analysis to determine the spatially varying uncertainties in AGB estimates at the individual plant and stand level for a large collection of LiDAR acquisitions covering a large portion of California. Furthermore, we determined the relative contribution of various aspects of the analysis towards the uncertainty, including errors in the ITCD results, the allometric equations, the taxonomic designation, and the local biophysical environment. Watershed segmentation was used to obtain the preliminary crown segments. Lidar points within the preliminary segments were extracted to form profiling data of the segments, and then mode detection algorithms were applied to identify the tree number and tree heights within each segment. As part of this analysis, we derived novel "remote sensing aware" allometric equations and their uncertainties based on three-dimensional morphological metrics that can be accurately derived from LiDAR data.

  9. Estimation of aboveground woody biomass using HJ-1 and Radarsat-2 data for deciduous forests in Daxing'anling, China

    NASA Astrophysics Data System (ADS)

    Liu, Qian; Yang, Le; Liu, Qinhuo; Li, Jing

    2014-11-01

    Accurate estimation of forest aboveground biomass is important for global carbon budgets and ecosystem change studies. Most algorithms for regional or global aboveground biomass estimation using optical and microwave remote sensing data are based on empirical regression and non-parametric training methods, which require large amount of ground measurements for training and are lacking of explicit interaction mechanisms between electromagnetic wave and vegetation. In this study, we proposed an optical/microwave synergy method based on a coherent polarimetric SAR model to estimate woody biomass. The study area is sparse deciduous forest dominated by birch with understory of shrubs and herbs in Daxing'anling, China. HJ-1, Radarsat-2 images, and field LAI were collected during May to August in 2013, tree biophysical parameters were measured at the field campaign during August to September in 2012. The effects of understory and wet ground were evaluated by introducing the NDVI derived from HJ-1 image and rain rate. Field measured LAI was used as an input to the SAR model to define the scattering and attenuation of the green canopy to the total backscatter. Finally, an logarithmic equation between the backscatter coefficient of direct forest scattering mechanism and woody biomass was generated (R2=0.582). The retrieval results were validated with the ground biomass measurements (RMSE=29.01ton/ha). The results indicated the synergy of optical and microwave remote sensing data based on SAR model has the potential to improve the accuracy of woody biomass estimation.

  10. Investigating Appropriate Sampling Design for Estimating Above-Ground Biomass in Bruneian Lowland Mixed Dipterocarp Forest

    NASA Astrophysics Data System (ADS)

    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

  11. A RAPID NON-DESTRUCTIVE METHOD FOR ESTIMATING ABOVEGROUND BIOMASS OF SALT MARSH GRASSES

    EPA Science Inventory

    Understanding the primary productivity of salt marshes requires accurate estimates of biomass. Unfortunately, these estimates vary enough within and among salt marshes to require large numbers of replicates if the averages are to be statistically meaningful. Large numbers of repl...

  12. Estimating aboveground biomass in the boreal forests of the Yukon River Basin, Alaska

    NASA Astrophysics Data System (ADS)

    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 (<500 m) are not available for this extensive and remote area. Our goal was to map AGB at 30-m resolution for the boreal forests in the Yukon River Basin of Alaska using recent Landsat data and ground measurements. We collected field data in the Yukon River Basin from 2008 to 2010. Ground measurements included diameter at breast height (DBH) or basal diameter (BD) for live and dead trees and shrubs (>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

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

    PubMed

    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.

  14. Rapid assessment of above-ground biomass of Giant Reed using visibility estimates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A method for the rapid estimation of biomass and density of giant reed (Arundo donax L.) was developed using estimates of visibility as a predictive tool. Visibility estimates were derived by capturing digital images of a 0.25 m2 polystyrene whiteboard placed a set distance (1m) from the edge of gia...

  15. Above-ground biomass estimation of tuberous bulrush ( Bolboschoenus planiculmis) in mudflats using remotely sensed multispectral image

    NASA Astrophysics Data System (ADS)

    Kim, Ji Yoon; Im, Ran-Young; Do, Yuno; Kim, Gu-Yeon; Joo, Gea-Jae

    2016-03-01

    We present a multivariate regression approach for mapping the spatial distribution of above-ground biomass (AGB) of B. planiculmis using field data and coincident moderate spatial resolution satellite imagery. A total of 232 ground sample plots were used to estimate the biomass distribution in the Nakdong River estuary. Field data were overlain and correlated with digital values from an atmospherically corrected multispectral image (Landsat 8). The AGB distribution was derived using empirical models trained with field-measured AGB data. The final regression model for AGB estimation was composed using the OLI3, OLI4, and OLI7 spectral bands. The Pearson correlation between the observed and predicted biomass was significant (R = 0.84, p < 0.0001). OLI3 made the largest contribution to the final model (relative coefficient value: 53.4%) and revealed a negative relationship with the AGB biomass. The total distribution area of B. planiculmis was 1,922,979 m2. Based on the model estimation, the total AGB had a dry weight (DW) of approximately 298.2 tons. The distribution of high biomass stands (> 200 kg DW/900 m2) constituted approximately 23.91% of the total vegetated area. Our findings suggest the expandability of remotely sensed products to understand the distribution pattern of estuarine plant productivity at the landscape level.

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

    USGS Publications Warehouse

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Exploring the possibility of estimating the aboveground biomass of Vallisneria spiralis L. using Landsat TM image in Dahuchi, Jiangxi Province, China

    NASA Astrophysics Data System (ADS)

    Wu, Guofeng; de Leeuw, Jan; Skidmore, Andrew K.; Prins, Herbert H. T.; Liu, Yaolin

    2005-10-01

    The provision of food to breeding and migrating waterfowl is one of the major functions of submerged aquatic vegetation in shallow lakes. Vallisneria spiralis L. is a submerged aquatic plant species widely distributed within Jiangxi Poyang Lake National Nature Reserve, China. More than 95% of the world population of the endangered Siberian crane as well as significant numbers of Bewick's swan and swan goose over winter in this area, while foraging on the tubers of Vallisneria. The objective of this paper was to explore the possibility of estimating the aboveground biomass of Vallisneria in Dahuchi Lake using Landsat TM image. The relations between aboveground biomass and the bands of a Landsat TM image and their derived variables were investigated using uni- and multivariate linear and non-linear regression models. The results revealed significant but very weak relations between aboveground biomass and the remotely sensed variables. Hence Landsat TM imagery offered little potential to predict aboveground biomass of Vallisneria in this particular region. Possible reasons which could have caused these results were discussed, including: 1) the possible influence of suspended matter in the water; 2) the less accurate field sampling; 3) the limitations of spatial and spectral resolutions of Landsat TM image; 4) the methods used are not appropriate; 5) the homogeneously spatial distribution of aboveground biomass. We propose considering two alternative methods to improve the estimation of aboveground biomass of Vallisneria. First of all, results might be improved while combining alternative data sources (hyperspectral or high spatial resolution images) with innovative methods and more accurate sampling data; Secondly we propose assessing aboveground biomass while using productivity simulation models of submerged aquatic vegetation integrated with geographic information system (GIS) and remote sensing.

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

    PubMed

    Shao, Zhenfeng; Zhang, Linjing

    2016-01-01

    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. PMID:27338378

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

    PubMed Central

    Shao, Zhenfeng; Zhang, Linjing

    2016-01-01

    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. PMID:27338378

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

    NASA Astrophysics Data System (ADS)

    Colgan, M.; Asner, G. P.; Swemmer, A. M.

    2011-12-01

    The accurate estimation of carbon stored in a tree is essential to accounting for the carbon emissions due to deforestation and degradation. Airborne LiDAR (Light Detection and Ranging) has been successful in estimating aboveground carbon density (ACD) by correlating airborne metrics, such as canopy height, to field-estimated biomass. This latter step is reliant on field allometry which is applied to forest inventory quantities, such as stem diameter and height, to predict the biomass of a given tree stem. Constructing such allometry is expensive, time consuming, and requires destructive sampling. Consequently, the sample sizes used to construct such allometry are often small, and the largest tree sampled is often much smaller than the largest in the forest population. The uncertainty resulting from these sampling errors can lead to severe biases when the allometry is applied to stems larger than those harvested to construct the allometry, which is then subsequently propagated to airborne ACD estimates. The Kruger National Park (KNP) mission of maintaining biodiversity coincides with preserving ecosystem carbon stocks. However, one hurdle to accurately quantifying carbon density in savannas is that small stems are typically harvested to construct woody biomass allometry, yet they are not representative of Kruger's distribution of biomass. Consequently, these equations inadequately capture large tree variation in sapwood/hardwood composition, root/shoot/leaf allocation, branch fall, and stem rot. This study eliminates the "middleman" of field allometry by directly measuring, or harvesting, tree biomass within the extent of airborne LiDAR. This enables comparisons of field and airborne ACD estimates, and also enables creation of new airborne algorithms to estimate biomass at the scale of individual trees. A field campaign was conducted at Pompey Silica Mine 5km outside Kruger National Park, South Africa, in Mar-Aug 2010 to harvest and weigh tree mass. Since

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

    EPA Science Inventory

    Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA)...

  3. Reducing Uncertainties in Satellite-derived Forest Aboveground Biomass Estimates using a High Resolution Forest Cover Map

    NASA Astrophysics Data System (ADS)

    Zhang, G.; Ganguly, S.; Nemani, R. R.; Milesi, C.; Basu, S.; Kumar, U.

    2014-12-01

    Several studies to date have provided an extensive knowledge base for estimating forest aboveground biomass (AGB) and recent advances in space-based modeling of the 3-D canopy structure, combined with canopy reflectance measured by passive optical sensors and radar backscatter, are providing improved satellite-derived AGB density mapping for large scale carbon monitoring applications. A key limitation in forest AGB estimation from remote sensing, however, is the large uncertainty in forest cover estimates from the coarse-to-medium resolution satellite-derived land cover maps (present resolution is limited to 30-m of the USGS NLCD Program). The uncertainties in forest cover estimates at the Landsat scale result in high uncertainties for AGB estimation, predominantly in heterogeneous forest and urban landscapes. We have successfully developed an approach using a machine learning algorithm and High-Performance-Computing with NAIP air-borne imagery data for mapping tree cover at 1-m over California and Maryland. In a comparison with high resolution LiDAR data available over selected regions in the two states, we found our results to be promising both in terms of accuracy as well as our ability to scale nationally. The generated 1-m forest cover map will be aggregated to the Landsat spatial grid to demonstrate differences in AGB estimates (pixel-level AGB density, total AGB at aggregated scales like ecoregions and counties) when using a native 30-m forest cover map versus a 30-m map derived from a higher resolution dataset. The process will also be complemented with a LiDAR derived AGB estimate at the 30-m scale to aid in true validation.

  4. Using LiDAR to Estimate Total Aboveground Biomass of Redwood Stands in the Jackson Demonstration State Forest, Mendocino, California

    NASA Astrophysics Data System (ADS)

    Rao, M.; Vuong, H.

    2013-12-01

    The overall objective of this study is to develop a method for estimating total aboveground biomass of redwood stands in Jackson Demonstration State Forest, Mendocino, California using airborne LiDAR data. LiDAR data owing to its vertical and horizontal accuracy are increasingly being used to characterize landscape features including ground surface elevation and canopy height. These LiDAR-derived metrics involving structural signatures at higher precision and accuracy can help better understand ecological processes at various spatial scales. Our study is focused on two major species of the forest: redwood (Sequoia semperirens [D.Don] Engl.) and Douglas-fir (Pseudotsuga mensiezii [Mirb.] Franco). Specifically, the objectives included linear regression models fitting tree diameter at breast height (dbh) to LiDAR derived height for each species. From 23 random points on the study area, field measurement (dbh and tree coordinate) were collected for more than 500 trees of Redwood and Douglas-fir over 0.2 ha- plots. The USFS-FUSION application software along with its LiDAR Data Viewer (LDV) were used to to extract Canopy Height Model (CHM) from which tree heights would be derived. Based on the LiDAR derived height and ground based dbh, a linear regression model was developed to predict dbh. The predicted dbh was used to estimate the biomass at the single tree level using Jenkin's formula (Jenkin et al 2003). The linear regression models were able to explain 65% of the variability associated with Redwood's dbh and 80% of that associated with Douglas-fir's dbh.

  5. Sensitivity of Above-Ground Biomass Estimates to Height-Diameter Modelling in Mixed-Species West African Woodlands

    PubMed Central

    Aynekulu, Ermias; Pitkänen, Sari; Packalen, Petteri

    2016-01-01

    It has been suggested that above-ground biomass (AGB) inventories should include tree height (H), in addition to diameter (D). As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0) AGB estimations from D-only; (B1) involving also H obtained from a fixed-effects H-D model; (B2) involving also species; (B3) including also between-plot variability as random effects; and (B4) involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E), which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the general H-D relation was relevant to modify. Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance. PMID:27367857

  6. Sensitivity of Above-Ground Biomass Estimates to Height-Diameter Modelling in Mixed-Species West African Woodlands.

    PubMed

    Valbuena, Rubén; Heiskanen, Janne; Aynekulu, Ermias; Pitkänen, Sari; Packalen, Petteri

    2016-01-01

    It has been suggested that above-ground biomass (AGB) inventories should include tree height (H), in addition to diameter (D). As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0) AGB estimations from D-only; (B1) involving also H obtained from a fixed-effects H-D model; (B2) involving also species; (B3) including also between-plot variability as random effects; and (B4) involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E), which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the general H-D relation was relevant to modify. Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance.

  7. Sensitivity of Above-Ground Biomass Estimates to Height-Diameter Modelling in Mixed-Species West African Woodlands.

    PubMed

    Valbuena, Rubén; Heiskanen, Janne; Aynekulu, Ermias; Pitkänen, Sari; Packalen, Petteri

    2016-01-01

    It has been suggested that above-ground biomass (AGB) inventories should include tree height (H), in addition to diameter (D). As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0) AGB estimations from D-only; (B1) involving also H obtained from a fixed-effects H-D model; (B2) involving also species; (B3) including also between-plot variability as random effects; and (B4) involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E), which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the general H-D relation was relevant to modify. Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance. PMID:27367857

  8. Adjusting lidar-derived digital terrain models in coastal marshes based on estimated aboveground biomass density

    SciTech Connect

    Medeiros, Stephen; Hagen, Scott; Weishampel, John; Angelo, James

    2015-03-25

    Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three-class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer to true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.

  9. Adjusting lidar-derived digital terrain models in coastal marshes based on estimated aboveground biomass density

    DOE PAGES

    Medeiros, Stephen; Hagen, Scott; Weishampel, John; Angelo, James

    2015-03-25

    Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three-class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer tomore » true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.« less

  10. Spatial distribution of forest aboveground biomass in China: estimation through combination of spaceborne lidar, optical imagery, and forest inventory data

    NASA Astrophysics Data System (ADS)

    Xue, B. L.; Su, Y.; Guo, Q.; Hu, T.; Alvarez, O.; Tao, S.; Fang, J.

    2015-12-01

    The global forest ecosystem, which acts as a large carbon sink, plays an important role in modeling the global carbon balance. An accurate estimation of the total forest carbon stock in the aboveground biomass (AGB) is therefore necessary to improve our understanding of carbon dynamics, especially against the background of global climate change. The forest area of China is among the top five globally. However, because of limitations in forest AGB mapping methods and the availability of ground inventory data, there is still a lack in nationwide wall-to-wall forest AGB estimation map for China. In this study, we collected over 8000 ground inventory data from the literature, and developed an AGB mapping method using a combination of these ground inventory data, Geoscience Laser Altimeter System (GLAS)/Ice, Cloud, and Land Elevation Satellite (ICESat) data, optical imagery, climate surfaces, and topographic data. An uncertainty field model was introduced into the forest AGB mapping model to minimize the influence of plot locality uncertainty. Our nationwide wall-to-wall forest AGB mapping results show that the forest AGB density in China is 120 Mg/ha on average, with a standard deviation of 61 Mg/ha. Evaluation with an independent ground inventory dataset showed that our proposed method can accurately map wall-to-wall forest AGB across a large landscape. The coefficient of determination (R2) and root-mean-square error between our predicted results and the validation dataset were 0.75 and 42.39 Mg/ha, respectively. This new method and the resulting nationwide wall-to-wall AGB map will help to improve the accuracy of carbon dynamic predictions in China.

  11. China Forest Aboveground Biomass Estimation by Fusion of Inventory and Remote Sensing Data: 1st results from Heilongjiang Province and Yunnan Province

    NASA Astrophysics Data System (ADS)

    Pang, Y.; Li, Z.; Huang, G.; Sun, G.; Cheng, Z.; Zhang, Z.; Zhang, G.

    2013-12-01

    Forests play an irreplaceable role in maintaining regional ecological environment, global carbon balance and mitigating global climate change. Forest aboveground biomass (AGB) is an important indicator of forest carbon stocks. Estimating forest aboveground biomass accurately could significantly reduce the uncertainties in terrestrial ecosystem carbon cycle. LIDAR provides accurate information on the vertical structure of forests (Lefsky et al., 2007; Naesset et al., 2004; Pang et al., 2008). Combining airborne LiDAR and spaceborne LiDAR for regional forest biomass retrieval could provide a more reliable and accurate quantitative information in regional forest biomass estimate (Boudreau et al., 2008; Nelson et al., 2009; Pang et al., 2011; Saatchi et al., 2011). The Heilongjiang Province and Yunnan Province are rich in forest resources and suffers intensive forest management activities for timber products. The Heilongjiang Province is typical in temperate forest and the Yunnan Province contains multiple forest types including tropical forest. These two provinces also have good ground inventory system with thousands of permanent field plots. Two campaign consists of in-situ measurement, airborne Lidar data and spaceborne data fusion were designed and implemented. First results show that i). Both spaceborne lidar and forest inventory data are useful for AGB mapping at province level. ii). The combination of spaceborne lidar and forest inventory data gave better biomass estimation with less bias. iii). A pixel level bias mapping was also proposed and gave spatial explicit map of estimation uncertainties. This method will be investigated further with more reference data and tested in other area.

  12. Estimation of Regional Forest Aboveground Biomass Combining Icesat-Glas Waveforms and HJ-1A/HSI Hyperspectral Imageries

    NASA Astrophysics Data System (ADS)

    Xing, Yanqiu; Qiu, Sai; Ding, Jianhua; Tian, Jing

    2016-06-01

    Estimation of forest aboveground biomass (AGB) is a critical challenge for understanding the global carbon cycle because it dominates the dynamics of the terrestrial carbon cycle. Light Detection and Ranging (LiDAR) system has a unique capability for estimating accurately forest canopy height, which has a direct relationship and can provide better understanding to the forest AGB. The Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) is the first polarorbiting LiDAR instrument for global observations of Earth, and it has been widely used for extracting forest AGB with footprints of nominally 70 m in diameter on the earth's surface. However, the GLAS footprints are discrete geographically, and thus it has been restricted to produce the regional full coverage of forest AGB. To overcome the limit of discontinuity, the Hyper Spectral Imager (HSI) of HJ-1A with 115 bands was combined with GLAS waveforms to predict the regional forest AGB in the study. Corresponding with the field investigation in Wangqing of Changbai Mountain, China, the GLAS waveform metrics were derived and employed to establish the AGB model, which was used further for estimating the AGB within GLAS footprints. For HSI imagery, the Minimum Noise Fraction (MNF) method was used to decrease noise and reduce the dimensionality of spectral bands, and consequently the first three of MNF were able to offer almost 98% spectral information and qualified to regress with the GLAS estimated AGB. Afterwards, the support vector regression (SVR) method was employed in the study to establish the relationship between GLAS estimated AGB and three of HSI MNF (i.e. MNF1, MNF2 and MNF3), and accordingly the full covered regional forest AGB map was produced. The results showed that the adj.R2 and RMSE of SVR-AGB models were 0.75 and 4.68 t hm-2 for broadleaf forests, 0.73 and 5.39 t hm-2 for coniferous forests and 0.71 and 6.15 t hm-2 for mixed forests respectively. The

  13. A comparison of two above-ground biomass estimation techniques integrating satellite-based remotely sensed data and ground data for tropical and semiarid forests in Puerto Rico

    NASA Astrophysics Data System (ADS)

    Iiames, J. S.; Riegel, J.; Lunetta, R.

    2013-12-01

    Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA) program. The U.S. Environmental Protection Agency (EPA) estimated above-ground forest biomass implementing methodology first posited by the Woods Hole Research Center developed for conterminous United States (National Biomass and Carbon Dataset [NBCD2000]). For EPA's effort, spatial predictor layers for above-ground biomass estimation included derived products from the U.S. Geologic Survey (USGS) National Land Cover Dataset 2001 (NLCD) (landcover and canopy density), the USGS Gap Analysis Program (forest type classification), the USGS National Elevation Dataset, and the NASA Shuttle Radar Topography Mission (tree heights). In contrast, the U.S. Forest Service (USFS) biomass product integrated FIA ground-based data with a suite of geospatial predictor variables including: (1) the Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; (2) NLCD land cover proportions; (3) topographic variables; (4) monthly and annual climate parameters; and (5) other ancillary variables. Correlations between both data sets were made at variable watershed scales to test level of agreement. Notice: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S EPA funded and conducted the research described in this paper. Although this work was reviewed by the EPA and has been approved for publication, it may not necessarily reflect official Agency policy. Mention of any trade names or commercial products does not constitute endorsement or recommendation for use.

  14. A cross-scale remote sensing approach to estimate tree cover and aboveground biomass in pinyon-juniper woodlands of the Colorado Plateau, USA

    NASA Astrophysics Data System (ADS)

    Huang, C.; Asner, G.; Martin, R.; Barger, N.; Neff, J.

    2007-12-01

    Vegetation dominated by pinyon pines and junipers (pinyon-juniper [P-J] woodlands) is one of the largest vegetation types in the North America. P-J woodlands maintain the highest level of woody biomass compared to other major dryland ecosystems. However, distributions of tree cover and biomass in the P-J woodlands of the Colorado Plateau have not been well studied. Here we developed a synoptic remote sensing approach to scale up pinyon pine and juniper cover and biomass field observations from plot to regional levels using fractional photosynthetic vegetation cover (PV) derived from airborne imaging spectroscopy and Landsat satellite data. Our results demonstrated strong correlations (p < 0.001) between field and airborne tree canopy cover estimates (r2 = 0.92), and between airborne and satellite canopy cover estimates (r2 = 0.61). Field data also indicated that P-J aboveground biomass can be estimated from canopy cover using a unified allometric equation (r2 = 0.69, p < 0.001). Using these multi-scale, cover-biomass relationships, we developed high-resolution, regional-scale maps of P-J cover and biomass for the western Colorado Plateau. The mean (± standard deviation) P-J cover was 27.4 (± 9.9)%, and the mean aboveground woody carbon (C) converted from biomass was 5.2 (± 2.0)MgC/ha. Combining our data with the southwest Regional Gap Analysis Program vegetation map, we estimated that total contemporary woody C storage for the entire Colorado Plateau P-J woodlands (113,600 km2) is 59 TgC. Our results facilitate further investigation of the processes controlling carbon stocks and fluxes across this large region, which forms a key component of the North American Carbon Program (NACP).

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

    PubMed

    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

  16. Above-ground biomass and carbon estimates of Shorea robusta and Tectona grandis forests using QuadPOL ALOS PALSAR data

    NASA Astrophysics Data System (ADS)

    Behera, M. D.; Tripathi, P.; Mishra, B.; Kumar, Shashi; Chitale, V. S.; Behera, Soumit K.

    2016-01-01

    Mechanisms to mitigate climate change in tropical countries such as India require information on forest structural components i.e., biomass and carbon for conservation steps to be implemented successfully. The present study focuses on investigating the potential use of a one time, QuadPOL ALOS PALSAR L-band 25 m data to estimate above-ground biomass (AGB) using a water cloud model (WCM) in a wildlife sanctuary in India. A significant correlation was obtained between the SAR-derived backscatter coefficient (σ°) and the field measured AGB, with the maximum coefficient of determination for cross-polarized (HV) σ° for Shorea robusta, and the weakest correlation was observed with co-polarized (HH) σ° for Tectona grandis forests. The biomass of S. robusta and that of T. grandis were estimated on the basis of field-measured data at 444.7 ± 170.4 Mg/ha and 451 ± 179.4 Mg/ha respectively. The mean biomass values estimated using the WCM varied between 562 and 660 Mg/ha for S. robusta; between 590 and 710 Mg/ha for T. grandis using various polarized data. Our results highlighted the efficacy of one time, fully polarized PALSAR data for biomass and carbon estimate in a dense forest.

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

    PubMed Central

    Jochem, Andreas; Hollaus, Markus; Rutzinger, Martin; Höfle, Bernhard

    2011-01-01

    In this study, a semi-empirical model that was originally developed for stem volume estimation is used for aboveground biomass (AGB) estimation of a spruce dominated alpine forest. The reference AGB of the available sample plots is calculated from forest inventory data by means of biomass expansion factors. Furthermore, the semi-empirical model is extended by three different canopy transparency parameters derived from airborne LiDAR data. These parameters have not been considered for stem volume estimation until now and are introduced in order to investigate the behavior of the model concerning AGB estimation. The developed additional input parameters are based on the assumption that transparency of vegetation can bemeasured by determining the penetration of the laser beams through the canopy. These parameters are calculated for every single point within the 3D point cloud in order to consider the varying properties of the vegetation in an appropriate way. Exploratory Data Analysis (EDA) is performed to evaluate the influence of the additional LiDAR derived canopy transparency parameters for AGB estimation. The study is carried out in a 560 km2 alpine area in Austria, where reference forest inventory data and LiDAR data are available. The investigations show that the introduction of the canopy transparency parameters does not change the results significantly according to R2 (R2 = 0.70 to R2 = 0.71) in comparison to the results derived from, the semi-empirical model, which was originally developed for stem volume estimation. PMID:22346577

  18. Age-related and stand-wise estimates of carbon stocks and sequestration in the aboveground coarse wood biomass of wetland forests in the northern Pantanal, Brazil

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

    In this study we use allometric models combined with tree ring analysis to estimate carbon stocks and sequestration in the aboveground coarse wood biomass (AGWB) of wetland forests in the Pantanal, located in central South America. In four 1-ha plots in stands characterized by the pioneer tree species Vochysia divergens Pohl (Vochysiaceae) forest inventories (trees ≥10 cm diameter at breast height, D) have been performed and converted to estimates of AGWB by two allometric models using three independent parameters (D, tree height H and wood density ρ). We perform a propagation of measurement errors to estimate uncertainties in the estimates of AGWB. Carbon stocks of AGWB vary from 7.8 ± 1.5 to 97.2 ± 14.4 Mg C ha-1 between the four stands. From models relating tree ages determined by dendrochronological techniques to C-stocks in AGWB we derived estimates for C-sequestration which differs from 0.50 ± 0.03 to 3.34 ± 0.31 Mg C ha-1 yr-1. Maps based on geostatistic techniques indicate the heterogeneous spatial distribution of tree ages and C-stocks of the four studied stands. This distribution is the result of forest dynamics due to the colonizing and retreating of V. divergens and other species associated with pluriannual wet and dry episodes in the Pantanal, respectively. Such information is essential for the management of the cultural landscape of the Pantanal wetlands.

  19. 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

    USGS Publications Warehouse

    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

  20. Distribution of Aboveground Live Biomass in the Amazon Basin

    NASA Technical Reports Server (NTRS)

    Saatchi, S. S.; Houghton, R. A.; DosSantos Alvala, R. C.; Soares, J. V.; Yu, Y.

    2007-01-01

    The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300Mgha(sup 1) here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300Mgha(sup 1). Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200Mgha(sup 1). The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and below ground biomass, is 86 PgC with +/- 20% uncertainty.

  1. Influence of tree size, taxonomy, and edaphic conditions on heart rot in mixed-dipterocarp Bornean rainforests: implications for aboveground biomass estimates

    NASA Astrophysics Data System (ADS)

    Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

    2015-05-01

    Fungal decay of heartwood creates hollows and areas of reduced wood density within the stems of living trees known as heart rot. Although heart rot is acknowledged as a source of error in forest aboveground biomass estimates, there are few datasets available to evaluate the environmental controls over heart rot infection and severity in tropical forests. Using legacy and recent data from drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of heart rot, and used generalized linear mixed effect models to characterize the association of heart rot with tree size, wood density, taxonomy, and edaphic conditions. Heart rot was detected in 55% of felled stems > 30 cm DBH, while the detection frequency was lower for stems of the same size evaluated by non-destructive drilling (45%) and coring (23%) methods. Heart rot severity, defined as the percent stem volume lost in infected stems, ranged widely from 0.1-82.8%. Tree taxonomy explained the greatest proportion of variance in heart rot frequency and severity among the fixed and random effects evaluated in our models. Heart rot frequency, but not severity, increased sharply with tree diameter, ranging from 56% infection across all datasets in stems > 50 cm DBH to 11% in trees 10-30 cm DBH. The frequency and severity of heart rot increased significantly in soils with low pH and cation concentrations in topsoil, and heart rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the percent of stem biomass lost to heart rot varied significantly with soil properties, and we estimate that 7% of the forest biomass is in some stage of heart rot decay. This study demonstrates not only that heart rot is a significant source of error in forest carbon estimates, but also that it strongly covaries with soil resources, underscoring the need to account for edaphic variation in

  2. Evaluation of stem rot in 339 Bornean tree species: implications of size, taxonomy, and soil-related variation for aboveground biomass estimates

    NASA Astrophysics Data System (ADS)

    Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

    2015-10-01

    Fungal decay of heart wood creates hollows and areas of reduced wood density within the stems of living trees known as stem rot. Although stem rot is acknowledged as a source of error in forest aboveground biomass (AGB) estimates, there are few data sets available to evaluate the controls over stem rot infection and severity in tropical forests. Using legacy and recent data from 3180 drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of stem rot in a total of 339 tree species, and related variation in stem rot with tree size, wood density, taxonomy, and species' soil association, as well as edaphic conditions. Predicted stem rot frequency for a 50 cm tree was 53 % of felled, 39 % of drilled, and 28 % of cored stems, demonstrating differences among methods in rot detection ability. The percent stem volume infected by rot, or stem rot severity, ranged widely among trees with stem rot infection (0.1-82.8 %) and averaged 9 % across all trees felled. Tree taxonomy explained the greatest proportion of variance in both stem rot frequency and severity among the predictors evaluated in our models. Stem rot frequency, but not severity, increased sharply with tree diameter, ranging from 13 % in trees 10-30 cm DBH to 54 % in stems ≥ 50 cm DBH across all data sets. The frequency of stem rot increased significantly in soils with low pH and cation concentrations in topsoil, and stem rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the maximum percent of stem biomass lost to stem rot varied significantly with soil properties, and we estimate that stem rot reduces total forest AGB estimates by up to 7 % relative to what would be predicted assuming all stems are composed strictly of intact wood. This study demonstrates not only that stem rot is likely to be a significant source of error in forest AGB estimation

  3. Estimation of Aboveground Biomass Change for Tropical Deciduous Forest in Bago Yoma, Myanmar between year 2000 and 2014 using Landsat Images and Ground Measurements

    NASA Astrophysics Data System (ADS)

    Kim, H. S.; Wynn, K. Z.; Ryu, Y.

    2015-12-01

    Even with recently increased awareness of the environmental conservation, the degradation of tropical forests are still one of the major sources of global carbon emission. Especially in Myanmar, the pressure to develop natural forest is growing rapidly after the change from socialism to capitalism in 2010. As the initial step of the forest conservation, the aboveground biomass(AGB) of South Zarmani Reserved Forest in Bago Yoma region were estimated using Landsat 8 OLI after the evaluation with 100 sample plot measurements. Multiple linear regression (MLR) model of band values and their principal component analysis (PCA) model were developed to estimate the AGB using the spectral reflectance from Landsat images and elevation as the input variables. The MLR model had r2 = 0.43, RMSE = 60.2 tons/ha, relative RMSE = 70.1%, Bias = -9.1 tons/ha, Bias (%) = -10.6%, and p < 0.0001, while the PCA model showed r2 = 0.45, RMSE = 55.1 tons/ha, relative RMSE = 64.1%, Bias = -8.3 tons/ha, Bias (%) = -9.7%, and p < 0.0001. The AGB maps of the study area were generated based on both MLR and PCA models. The estimated mean AGB values were 74.74±22.3 tons/ha and 73.04±17.6 tons/ha and the total AGB of the study area are about 5.7 and 5.6 million tons from MLR and PCA, respectively. Then, Landsat 7 ETM+ image acquired on 2000 was also used to compare the changing of AGB between year 2000 and 2014. The estimated mean AGB value generated from the Landsat 7 ETM+ image was 78.9±16.9 tons/ha, which is substantially decreased about 7.5% compared to year 2014. The reduction of AGB increased with closeness to village, however AGB in distant areas showed steady increases. In conclusion, we were able to generate solid regression models from Landsat 8 OLI image after ground truth and two regression models gave us very similar AGB estimation (less than 2%) of the study area. We were also able to estimate the changing of AGB from year 2000 to 2014 of South Zarmani Reserved Forest, Bago Yoma

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

    PubMed

    Liang, Bei; Di, Li; Zhao, Chuan-Yan; Peng, Shou-Zhang; Peng, Huan-Hua; Wang, Chao

    2014-02-01

    This study estimated the spatial distribution of the aboveground biomass of shrubs in the Tianlaochi catchment of Qilian Mountains based on the field survey and remote sensing data. A relationship model of the aboveground biomass and its feasibly measured factors (i. e. , canopy perimeter and plant height) was built. The land use was classified by object-oriented technique with the high resolution image (GeoEye-1) of the study area, and the distribution of shrub coverage was extracted. Then the total aboveground biomass of shrubs in the study area was estimated by the relationship model with the distribution of shrub coverage. The results showed that the aboveground biomass of shrubs in the study area was 1.8 x 10(3) t and the aboveground biomass per unit area was 1598.45 kg x m(-2). The distribution of shrubs mainly was at altitudes of 3000-3700 m, and the aboveground biomass of shrubs on the sunny slope (1.15 x 10(3) t) was higher than that on the shady slope (0.65 x 10(3) t).

  5. [Aboveground architecture and biomass distribution of Quercus variabilis].

    PubMed

    Yu, Bi-yun; Zhang, Wen-hui; Hu, Xiao-jing; Shen, Jia-peng; Zhen, Xue-yuan; Yang, Xiao-zhou

    2015-08-01

    The aboveground architecture, biomass and its allocation, and the relationship between architecture and biomass of Quercus variabilis of different diameter classes in Shangluo, south slope of Qinling Mountains were researched. The results showed that differences existed in the aboveground architecture and biomass allocation of Q. variabilis of different diameter classes. With the increase of diameter class, tree height, DBH, and crown width increased gradually. The average decline rate of each diameter class increased firstly then decreased. Q. variabilis overall bifurcation ratio and stepwise bifurcation ratio increased then declined. The specific leaf areas of Q. variabilis of all different diameter classes at vertical direction were 0.02-0.03, and the larger values of leaf mass ratio, LAI and leaf area ratio at vertical direction in diameter level I , II, III appeared in the middle and upper trunk, while in diameter level IV, V, VI, they appeared in the central trunk, with the increase of diameter class, there appeared two peaks in vertical direction, which located in the lower and upper trunk. The trunk biomass accounted for 71.8%-88.4% of Q. variabilis aboveground biomass, while the branch biomass accounted for 5.8%-19.6%, and the leaf biomass accounted for 4.2%-8.6%. With the increase of diameter class, stem biomass proportion of Q. variabilis decreased firstly then increased, while the branch and leaf biomass proportion showed a trend that increased at first then decreased, and then increased again. The aboveground biomass of Q. variabilis was significantly positively correlated to tree height, DBH, crown width and stepwise bifurcation ratio (R2:1), and positively related to the overall bifurcation ratio and stepwise bifurcation ratio (R3:2), but there was no significant correlation. Trunk biomass and total biomass aboveground were negatively related to the trunk decline rate, while branch biomass and leaf biomass were positively related to trunk decline

  6. [Aboveground architecture and biomass distribution of Quercus variabilis].

    PubMed

    Yu, Bi-yun; Zhang, Wen-hui; Hu, Xiao-jing; Shen, Jia-peng; Zhen, Xue-yuan; Yang, Xiao-zhou

    2015-08-01

    The aboveground architecture, biomass and its allocation, and the relationship between architecture and biomass of Quercus variabilis of different diameter classes in Shangluo, south slope of Qinling Mountains were researched. The results showed that differences existed in the aboveground architecture and biomass allocation of Q. variabilis of different diameter classes. With the increase of diameter class, tree height, DBH, and crown width increased gradually. The average decline rate of each diameter class increased firstly then decreased. Q. variabilis overall bifurcation ratio and stepwise bifurcation ratio increased then declined. The specific leaf areas of Q. variabilis of all different diameter classes at vertical direction were 0.02-0.03, and the larger values of leaf mass ratio, LAI and leaf area ratio at vertical direction in diameter level I , II, III appeared in the middle and upper trunk, while in diameter level IV, V, VI, they appeared in the central trunk, with the increase of diameter class, there appeared two peaks in vertical direction, which located in the lower and upper trunk. The trunk biomass accounted for 71.8%-88.4% of Q. variabilis aboveground biomass, while the branch biomass accounted for 5.8%-19.6%, and the leaf biomass accounted for 4.2%-8.6%. With the increase of diameter class, stem biomass proportion of Q. variabilis decreased firstly then increased, while the branch and leaf biomass proportion showed a trend that increased at first then decreased, and then increased again. The aboveground biomass of Q. variabilis was significantly positively correlated to tree height, DBH, crown width and stepwise bifurcation ratio (R2:1), and positively related to the overall bifurcation ratio and stepwise bifurcation ratio (R3:2), but there was no significant correlation. Trunk biomass and total biomass aboveground were negatively related to the trunk decline rate, while branch biomass and leaf biomass were positively related to trunk decline

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

    PubMed

    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. PMID:21265444

  8. Estimating Mangrove Canopy Height and Above-Ground Biomass in Everglades National Park with Airbone LiDAR and TanDEM-X Data.

    NASA Astrophysics Data System (ADS)

    Feliciano, E. A.; Wdowinski, S.; Potts, M. D.; Fatoyinbo, T. E.; Lee, S. K.

    2014-12-01

    The coastal mangroves forests of Everglades National Park (ENP) are well protected from development. Nevertheless, climate change, hurricanes and other anthropogenic disturbances have affected these intertidal ecosystems. Understanding and monitoring forest structural parameters such as canopy height and above-ground biomass (AGB) are important for the establishment of an historical database for past, present and future ecosystem comparison. Forest canopy height has a well understood and directly proportional correlation with AGB. It is possible to derive it using (1) airborne LiDAR/Laser Scanning (ALS) or (2) space-borne radar systems such as Shuttle Radar Topography Mission (SRTM) and TanDEM-X (TDX). A previous study of the mangrove canopy height and AGB in the ENP was conducted a decade ago based on ALS data acquired in 2004 in conjunction with SRTM data, which were acquired in 2000 (Simard et al. 2006). In this study we estimated canopy height and AGB using an ALS dataset acquired in 2012 and TDX data acquired during the years 2012-2014. The ALS dataset was acquired along a 16.5 x 1.5 km swath of mangrove forest with variable canopy height. The sampled areas were representative of mangrove stature and structure in the whole ENP. Analysis of the ALS dataset showed that mangrove canopy height can reach up to ~25 meters close to the coastal ENP waters. Additionally, by comparing our ALS results with those of a previous study by Simard et al. (2006) we identified areas where mangrove height changes greater than ± 3 meters occurred. To expand the study area to the full ENP mangrove ecosystem we processed single-polarization TDX data to obtain a Digital Canopy Model (DCM) that represents the mangrove canopy height. In order to obtain the true canopy height we calibrated the TDX phase center height with ALS true canopy height. Preliminary results of a corrected single-polarized (HH) TDX scene show that mangrove canopy height can reach up to ~25 meters in the western

  9. Comparing the above-ground component biomass estimates of western junipers using airborne and full-waveform terrestrial laser scanning data

    NASA Astrophysics Data System (ADS)

    Shrestha, R.; Glenn, N. F.; Spaete, L.; Hardegree, S. P.

    2012-12-01

    With the rapid expansion into shrub steppe and grassland ecosystems over the last century, western juniper (Juniperus occidentalis var. occidentalis Hook) is becoming a major component of the regional carbon pool in the Intermountain West. Understanding how biomass is allocated across individual tree components is necessary to understand the uncertainties in biomass estimates and more accurately quantify biomass and carbon dynamics in these ecosystems. Estimates of component biomass are also important for canopy fuel load assessment and predicting rangeland fire behavior. Airborne LiDAR can capture vegetation structure over larger scales, but the high crown penetration and sampling density of terrestrial laser scanner (TLS) instruments can better capture tree components. In this study, we assessed the ability of airborne LiDAR to estimate biomass of tree components of western juniper with validation data from field measured tees and a full-waveform TLS. Sixteen juniper trees (height range 1.5-10 m) were randomly selected using a double sampling strategy from different height classes in the Reynolds Creek Experimental Watershed in the Owyhee Mountains, southwestern Idaho, USA. Each tree was scanned with a full-waveform TLS, and the dry biomass of each component (foliage, branches and main stem) were measured by destructive harvesting of the trees. We compare the allometric relationships of biomass estimates of the tree components obtained from field-measured trees and TLS-based estimates with the estimates from discrete-return airborne-LiDAR based estimates.

  10. Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas

    NASA Astrophysics Data System (ADS)

    Dube, Timothy; Mutanga, Onisimo

    2015-10-01

    The successful launch of the 30-m Landsat-8 Operational Land Imager (OLI) pushbroom sensor offers a new primary data source necessary for aboveground biomass (AGB) estimation, especially in resource-limited environments. In this work, the strength and performance of Landsat-8 OLI image derived texture metrics (i.e. texture measures and texture ratios) in estimating plantation forest species AGB was investigated. It was hypothesized that the sensor's pushbroom design, coupled with the presence of refined spectral properties, enhanced radiometric resolution (i.e. from 8 bits to 12 bits) and improved signal-to-noise ratio have the potential to provide detailed spectral information necessary for significantly strengthening AGB estimation in medium-density forest canopies. The relationship between image texture metrics and measurements of forest attributes can be used to help characterize complex forests, and enhance fine vegetation biophysical properties, a difficult challenge when using spectral vegetation indices especially in closed canopies. This study examines the prospects of using Landsat-8 OLI sensor derived texture metrics for estimating AGB for three medium-density plantation forest species in KwaZulu Natal, South Africa. In order to achieve this objective, three unique data pre-processing techniques were tested (analysis I: Landsat-8 OLI raw spectral-bands vs. raw texture bands; analysis II: Landsat-8 OLI raw spectral-band ratios vs. texture band ratios and analysis III: Landsat-8 OLI derived vegetation indices vs. texture band ratios). The landsat-8 OLI derived texture parameters were examined for robustness in estimating AGB using linear regression, stepwise-multiple linear regression and stochastic gradient boosting regression models. The results of this study demonstrated that all texture parameters particularly band texture ratios calculated using a 3 × 3 window size, could enhance AGB estimation when compared to simple spectral reflectance, simple

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

    NASA Astrophysics Data System (ADS)

    Soares, Mário Luiz Gomes; Schaeffer-Novelli, Yara

    2005-10-01

    This study analyzes the above-ground biomass of Rhizophora mangle and Laguncularia racemosa located in the mangroves of Bertioga (SP) and Guaratiba (RJ), Southeast Brazil. Its purpose is to determine the best regression model to estimate the total above-ground biomass and compartment (leaves, reproductive parts, twigs, branches, trunk and prop roots) biomass, indirectly. To do this, we used structural measurements such as height, diameter at breast-height (DBH), and crown area. A combination of regression types with several compositions of independent variables generated 2.272 models that were later tested. Subsequent analysis of the models indicated that the biomass of reproductive parts, branches, and prop roots yielded great variability, probably because of environmental factors and seasonality (in the case of reproductive parts). It also indicated the superiority of multiple regression to estimate above-ground biomass as it allows researchers to consider several aspects that affect above-ground biomass, specially the influence of environmental factors. This fact has been attested to the models that estimated the biomass of crown compartments.

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

    USGS Publications Warehouse

    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 (p<0.0001), with all r2 values greater than 0.90. The allometric relationship was used to estimate total aboveground 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.

  13. Soil nutrients affect spatial patterns of aboveground biomass and emergent tree density in southwestern Borneo.

    PubMed

    Paoli, Gary D; Curran, Lisa M; Slik, J W F

    2008-03-01

    Studies on the relationship between soil fertility and aboveground biomass in lowland tropical forests have yielded conflicting results, reporting positive, negative and no effect of soil nutrients on aboveground biomass. Here, we quantify the impact of soil variation on the stand structure of mature Bornean forest throughout a lowland watershed (8-196 m a.s.l.) with uniform climate and heterogeneous soils. Categorical and bivariate methods were used to quantify the effects of (1) parent material differing in nutrient content (alluvium > sedimentary > granite) and (2) 27 soil parameters on tree density, size distribution, basal area and aboveground biomass. Trees > or =10 cm (diameter at breast height, dbh) were enumerated in 30 (0.16 ha) plots (sample area = 4.8 ha). Six soil samples (0-20 cm) per plot were analyzed for physiochemical properties. Aboveground biomass was estimated using allometric equations. Across all plots, stem density averaged 521 +/- 13 stems ha(-1), basal area 39.6 +/- 1.4 m(2) ha(-1) and aboveground biomass 518 +/- 28 Mg ha(-1) (mean +/- SE). Adjusted forest-wide aboveground biomass to account for apparent overestimation of large tree density (based on 69 0.3-ha transects; sample area = 20.7 ha) was 430 +/- 25 Mg ha(-1). Stand structure did not vary significantly among substrates, but it did show a clear trend toward larger stature on nutrient-rich alluvium, with a higher density and larger maximum size of emergent trees. Across all plots, surface soil phosphorus (P), potassium, magnesium and percentage sand content were significantly related to stem density and/or aboveground biomass (R (Pearson) = 0.368-0.416). In multiple linear regression, extractable P and percentage sand combined explained 31% of the aboveground biomass variance. Regression analyses on size classes showed that the abundance of emergent trees >120 cm dbh was positively related to soil P and exchangeable bases, whereas trees 60-90 cm dbh were negatively related to these

  14. Soil nutrients affect spatial patterns of aboveground biomass and emergent tree density in southwestern Borneo.

    PubMed

    Paoli, Gary D; Curran, Lisa M; Slik, J W F

    2008-03-01

    Studies on the relationship between soil fertility and aboveground biomass in lowland tropical forests have yielded conflicting results, reporting positive, negative and no effect of soil nutrients on aboveground biomass. Here, we quantify the impact of soil variation on the stand structure of mature Bornean forest throughout a lowland watershed (8-196 m a.s.l.) with uniform climate and heterogeneous soils. Categorical and bivariate methods were used to quantify the effects of (1) parent material differing in nutrient content (alluvium > sedimentary > granite) and (2) 27 soil parameters on tree density, size distribution, basal area and aboveground biomass. Trees > or =10 cm (diameter at breast height, dbh) were enumerated in 30 (0.16 ha) plots (sample area = 4.8 ha). Six soil samples (0-20 cm) per plot were analyzed for physiochemical properties. Aboveground biomass was estimated using allometric equations. Across all plots, stem density averaged 521 +/- 13 stems ha(-1), basal area 39.6 +/- 1.4 m(2) ha(-1) and aboveground biomass 518 +/- 28 Mg ha(-1) (mean +/- SE). Adjusted forest-wide aboveground biomass to account for apparent overestimation of large tree density (based on 69 0.3-ha transects; sample area = 20.7 ha) was 430 +/- 25 Mg ha(-1). Stand structure did not vary significantly among substrates, but it did show a clear trend toward larger stature on nutrient-rich alluvium, with a higher density and larger maximum size of emergent trees. Across all plots, surface soil phosphorus (P), potassium, magnesium and percentage sand content were significantly related to stem density and/or aboveground biomass (R (Pearson) = 0.368-0.416). In multiple linear regression, extractable P and percentage sand combined explained 31% of the aboveground biomass variance. Regression analyses on size classes showed that the abundance of emergent trees >120 cm dbh was positively related to soil P and exchangeable bases, whereas trees 60-90 cm dbh were negatively related to these

  15. Remote sensing of aboveground biomass and annual net aerial primary productivity in tidal wetlands

    SciTech Connect

    Hardisky, M.A.

    1983-01-01

    A technique was investigated for estimating biomass and net aerial primary productivity (NAPP) in Delaware tidal marshes from spectral data, describing marsh vegetation canopies. Spectral radiance data were collected with hand-held radiometers from the ground and from low altitude aircraft. Spectral wavebands corresponding to Landsat 4 thematic mapper bands 3, 4 and 5 and multispectral scanner bands 5 and 7 were employed. Spectral data, expressed as index values, were substituted into simple regression models to nondestructively compute total aboveground biomass. Dead biomass, salt crystals on plant leaves and soil background reflectance, all attenuated the spectral radiance index values. A large spectral contribution from any one of these canopy components caused an underestimate of live biomass. Biomass and annual NAPP of a S. alterniflora dominated salt marsh was estimated by traditional harvesting techniques and from ground-gathered spectral radiance data. The live and dead standing crop biomass estimates computed from spectral data were usually not significantly different from harvest biomass estimates. Spectral estimates of NAPP were usually within 10% of NAPP estimates calculated from harvest data. August live standing crop biomass estimates computed from ground-gathered spectral data for a tidal brackish marsh were generally within 10% of harvest estimates. Live biomass estimates computed from spectral data gathered from a low altitude aircraft were equally similar to harvest biomass estimates. The remote sensing technique holds much promise for rapid and accurate estimates of biomass and NAPP in tidal marshes.

  16. Carbon and Nitrogen Storage in Aboveground Biomass and Organic Layer in Natural Larix Stands in Eastern Siberia

    NASA Astrophysics Data System (ADS)

    Shibuya, M.; Saito, H.; Sawamoto, T.; Hatano, R.; Yajima, T.; Takahashi, K.; Cha, J.; Isaev, A.; Maximov, T.

    2002-12-01

    To evaluate the carbon storage capacity of natural Larix stands in eastern Siberia, aboveground biomass, carbon and nitrogen storage in the biomass and organic layer of soil, and net primary production (NPP) were estimated in relation to stand age. Stands studied were from young to mature growth stage. The aboveground biomass and carbon storage in the biomass increased sigmoidally with stand age. The asymptotes of the biomass and carbon storage were 104 t\\ha-1 and 52 tC\\ha-1, respectively. The carbon storage capacity of the aboveground biomass was considered not to be small depending on the long period during which a large biomass close to the asymptote is retained, while the annual increment of the biomass is small. Also, carbon sink efficiency of the biomass changed with stand age. NPP of the stands was small comparing with those of temperate and boreal stands. Estimated net ecosystem production was positive even in a mature stand. Siberian Larix stands studied were carbon sink irrespective of stand age. The carbon storage in organic layer of soil accounted for 80-100 % of that in the aboveground biomass and was a significant carbon sink. Nitrogen was considered as a limited nutrient for the production of the stands from its allocation pattern to aboveground tree organs and storage pattern in soil. Furthermore, the decomposition rate of litter was small and affects the accumulation of organic materials.

  17. Aboveground biomass estimation using SAR-optical (Lidar, RapidEye) and field inventory datasets in Skukuza, Kruger National Park in South Africa

    NASA Astrophysics Data System (ADS)

    Onyango Odipo, Victor; Hüttich, Christian; Luck, Wolfgang; Schmullius, Christiane

    2015-04-01

    African savanna covers approximately two-thirds of sub-saharan Africa, playing important roles as a carbon pool, habitat for mankind and wildlife, source of livelihood, an important tropical climate modifier, among other ecological roles. Sub-saharan Africa alone accounts for 25% of the tropical aboveground carbon stock (193 Gt C). Global and national level AGB estimates rely on extrapolations with regression models from few field inventories, leading in some cases, up to 100% uncertainty. Remote sensing has proven to provide reliable vegetation structural mapping, given the high spatial and temporal resolution allowing datasets to be availed in areas where ground based inventories are infeasible due to time and financial constraints. The availability of freely accessible optical remotely-sensed datasets has made this feat attainable. However, the heterogeneity of tropical savannas (co-existence of trees and grasses), coupled with erratic rainfall events and atmospheric clouds and aerosol in the tropics has made it difficult to extract biophysical properties of the savannas by solely using optical datasets. This has necessitated an assessment of synergies between active and passive remotely sensed datasets to benefit from the complementarities. In this study we assess the extent to which multi-level sub-centimeter Unmanned Aerial Vehicle (UAV) Lidar, high resolution RapidEye and microwave (ALOS PALSAR L-band and Sentinel-1 C-band) remotely sensed datasets can be used together with tree census datasets to estimate AGB within the complex southern Africa savanna ecosystem. A random forest (RF) regression model is produced which relates the Lidar canopy-height metrics (CHM) with both synthetic aperture radar (SAR) and high resolution RapidEye datasets. As a validation, we compare our results with both national and global level ABG estimates.

  18. The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa

    NASA Astrophysics Data System (ADS)

    Dube, Timothy; Mutanga, Onisimo

    2016-09-01

    Reliable and accurate mapping and extraction of key forest indicators of ecosystem development and health, such as aboveground biomass (AGB) and aboveground carbon stocks (AGCS) is critical in understanding forests contribution to the local, regional and global carbon cycle. This information is critical in assessing forest contribution towards ecosystem functioning and services, as well as their conservation status. This work aimed at assessing the applicability of the high resolution 8-band WorldView-2 multispectral dataset together with environmental variables in quantifying AGB and aboveground carbon stocks for three forest plantation species i.e. Eucalyptus dunii (ED), Eucalyptus grandis (EG) and Pinus taeda (PT) in uMgeni Catchment, South Africa. Specifically, the strength of the Worldview-2 sensor in terms of its improved imaging agilities is examined as an independent dataset and in conjunction with selected environmental variables. The results have demonstrated that the integration of high resolution 8-band Worldview-2 multispectral data with environmental variables provide improved AGB and AGCS estimates, when compared to the use of spectral data as an independent dataset. The use of integrated datasets yielded a high R2 value of 0.88 and RMSEs of 10.05 t ha-1 and 5.03 t C ha-1 for E. dunii AGB and carbon stocks; whereas the use of spectral data as an independent dataset yielded slightly weaker results, producing an R2 value of 0.73 and an RMSE of 18.57 t ha-1 and 09.29 t C ha-1. Similarly, high accurate results (R2 value of 0.73 and RMSE values of 27.30 t ha-1 and 13.65 t C ha-1) were observed from the estimation of inter-species AGB and carbon stocks. Overall, the findings of this work have shown that the integration of new generation multispectral datasets with environmental variables provide a robust toolset required for the accurate and reliable retrieval of forest aboveground biomass and carbon stocks in densely forested terrestrial ecosystems.

  19. Monitoring Changes in Aboveground Biomass in Loblolly Pine Forests Using Multichannel Synthetic Aperture Radar Data

    NASA Astrophysics Data System (ADS)

    Kasischke, Eric Stewart

    A study was conducted to evaluate using synthetic aperture radar (SAR) for estimating aboveground biomass in loblolly pine (Pinus taeda L.) forests. The data set for this experiment was a multiple-frequency (C-, L- and P-band), polarimetric SAR data set collected by the NASA/JPL AIRSAR System over the Duke University Research Forest located near Durham, North Carolina. In addition to the SAR data set, a set of ground measurements were collected to describe the tree geometry and biomass characteristics from 59 different stands consisting principally of loblolly pine within the Duke Forest. The aboveground, dry weight woody biomass in these test stands ranges from < 1 to >50 kg-m^2. The first analysis performed on this data set was to produce algorithms to estimate both dry and wet weight biomasses for each of the test stands, and to distribute this biomass amongst various tree components (e.g., boles, branches, and needles/leaves) as well as the different layers within the tree canopy (e.g., canopy, subcanopy and understory) in order to better relate biomass to the radar backscattering measurements. This was accomplished by development of allometric equations to estimate biomass for individual trees, from which stand estimates on an aerial basis were derived. The biomass estimates were then statistically correlated with radar backscatter (sigma ^circ) measurements derived from the SAR data set. It was found that sigma^ circ at a variety of radar frequencies (P, L, and C-bands) and linear-polarization combinations (HH, HV, and VV) were significantly correlated (at a level of significance of p = 0.001) to either individual biomass components (e.g., bole biomass, branch biomass, needle/leaf biomass, etc.) or multiple combinations of these components. While the correlations were significant at all linear polarizations at L- and P-bands, they were only significant in the cross -polarized channel at C-band. Finally, a two-step method was developed to estimate aboveground

  20. Regional Contingencies in the Relationship between Aboveground Biomass and Litter in the World’s Grasslands

    PubMed Central

    O’Halloran, Lydia R.; Borer, Elizabeth T.; Seabloom, Eric W.; MacDougall, Andrew S.; Cleland, Elsa E.; McCulley, Rebecca L.; Hobbie, Sarah; Harpole, W. Stan; DeCrappeo, Nicole M.; Chu, Chengjin; Bakker, Jonathan D.; Davies, Kendi F.; Du, Guozhen; Firn, Jennifer; Hagenah, Nicole; Hofmockel, Kirsten S.; Knops, Johannes M. H.; Li, Wei; Melbourne, Brett A.; Morgan, John W.; Orrock, John L.; Prober, Suzanne M.; Stevens, Carly J.

    2013-01-01

    Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex. PMID:23405103

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

    PubMed

    Jana, Bipal K; Biswas, Soumyajit; Majumder, Mrinmoy; Roy, Pankaj K; Mazumdar, Asis

    2011-07-01

    Carbon is sequestered by the plant photosynthesis and stored as biomass in different parts of the tree. Carbon sequestration rate has been measured for young species (6 years age) of Shorea robusta at Chadra forest in Paschim Medinipur district, Albizzia lebbek in Indian Botanic Garden in Howrah district and Artocarpus integrifolia at Banobitan within Kolkata in the lower Gangetic plain of West Bengal in India by Automated Vaisala Made Instrument GMP343 and aboveground biomass carbon has been analyzed by CHN analyzer. The specific objective of this paper is to measure carbon sequestration rate and aboveground biomass carbon potential of three young species of Shorea robusta, Albizzia lebbek and Artocarpus integrifolia. The carbon sequestration rate (mean) from the ambient air during winter season as obtained by Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 11.13 g/h, 14.86 g/h and 4.22g/h, respectively. The annual carbon sequestration rate from ambient air were estimated at 8.97 t C ha(-1) by Shorea robusta, 11.97 t C ha(-1) by Albizzia lebbek and 3.33 t C ha(-1) by Artocarpus integrifolia. The percentage of carbon content (except root) in the aboveground biomass of Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 47.45, 47.12 and 43.33, respectively. The total aboveground biomass carbon stock per hectare as estimated for Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 5.22 t C ha(-1) , 6.26 t C ha(-1) and 7.28 t C ha(-1), respectively in these forest stands.

  2. Shifts in Aboveground Biomass Allocation Patterns of Dominant Shrub Species across a Strong Environmental Gradient

    PubMed Central

    Kumordzi, Bright B.; Gundale, Michael J.; Nilsson, Marie-Charlotte; Wardle, David A.

    2016-01-01

    Most plant biomass allocation studies have focused on allocation to shoots versus roots, and little is known about drivers of allocation for aboveground plant organs. We explored the drivers of within-and between-species variation of aboveground biomass allocation across a strong environmental resource gradient, i.e., a long-term chronosequence of 30 forested islands in northern Sweden across which soil fertility and plant productivity declines while light availability increases. For each of the three coexisting dominant understory dwarf shrub species on each island, we estimated the fraction of the total aboveground biomass produced year of sampling that was allocated to sexual reproduction (i.e., fruits), leaves and stems for each of two growing seasons, to determine how biomass allocation responded to the chronosequence at both the within-species and whole community levels. Against expectations, within-species allocation to fruits was least on less fertile islands, and allocation to leaves at the whole community level was greatest on intermediate islands. Consistent with expectations, different coexisting species showed contrasting allocation patterns, with the species that was best adapted for more fertile conditions allocating the most to vegetative organs, and with its allocation pattern showing the strongest response to the gradient. Our study suggests that co-existing dominant plant species can display highly contrasting biomass allocations to different aboveground organs within and across species in response to limiting environmental resources within the same plant community. Such knowledge is important for understanding how community assembly, trait spectra, and ecological processes driven by the plant community vary across environmental gradients and among contrasting ecosystems. PMID:27270445

  3. Shifts in Aboveground Biomass Allocation Patterns of Dominant Shrub Species across a Strong Environmental Gradient.

    PubMed

    Kumordzi, Bright B; Gundale, Michael J; Nilsson, Marie-Charlotte; Wardle, David A

    2016-01-01

    Most plant biomass allocation studies have focused on allocation to shoots versus roots, and little is known about drivers of allocation for aboveground plant organs. We explored the drivers of within-and between-species variation of aboveground biomass allocation across a strong environmental resource gradient, i.e., a long-term chronosequence of 30 forested islands in northern Sweden across which soil fertility and plant productivity declines while light availability increases. For each of the three coexisting dominant understory dwarf shrub species on each island, we estimated the fraction of the total aboveground biomass produced year of sampling that was allocated to sexual reproduction (i.e., fruits), leaves and stems for each of two growing seasons, to determine how biomass allocation responded to the chronosequence at both the within-species and whole community levels. Against expectations, within-species allocation to fruits was least on less fertile islands, and allocation to leaves at the whole community level was greatest on intermediate islands. Consistent with expectations, different coexisting species showed contrasting allocation patterns, with the species that was best adapted for more fertile conditions allocating the most to vegetative organs, and with its allocation pattern showing the strongest response to the gradient. Our study suggests that co-existing dominant plant species can display highly contrasting biomass allocations to different aboveground organs within and across species in response to limiting environmental resources within the same plant community. Such knowledge is important for understanding how community assembly, trait spectra, and ecological processes driven by the plant community vary across environmental gradients and among contrasting ecosystems. PMID:27270445

  4. Mapping Aboveground Biomass in the Amazon Basin: Exploring Sensors, Scales, and Strategies for Optimal Data Linkage

    NASA Astrophysics Data System (ADS)

    Walker, W. S.; Baccini, A.

    2013-05-01

    encompassing the state of Acre Brazil. Through a comprehensive comparison involving nearly 50 separate analyses, we assess accuracy in aboveground biomass estimates with respect to varying (a) satellite data inputs, (b) image spatial scales, (c) and field/image data linkage strategies. Our results confirm the utility of both ALOS/PALSAR and Landsat data for the provision of accurate estimates of aboveground biomass, with accuracy increasing markedly with increasing spectral resolution, decreasing spatial resolution, and as the spatial mismatches between field and image data sources are minimized.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Landscape Patterns of Wood Density and Aboveground Biomass Along a Tropical Elevation Gradient in Costa Rica

    NASA Astrophysics Data System (ADS)

    Robinson, C. M.

    2015-12-01

    This research sought to understand how tree wood density and taxonomic diversity relate to topography and three-dimensional vegetation structure in the tropical montane forest of Braulio Carrillo National Park in Costa Rica. The study utilized forest inventory and botanical data from twenty 1-ha plots ranging from 55 m to 2800 m above sea level and remote sensing data from an airborne lidar sensor (NASA's Land, Vegetation, and Ice Sensor [LVIS]) to quantify variations in forest structure. There is growing evidence that ecosystem structure may help to control the functional variations across landscapes. This study relates patterns of tree functional wood density and alpha diversity to three-dimensional structure using remote sensing observations of forest structure. We were able to test the effect of the gradient on wood density measured from collected tree cores and on the subsequent aboveground biomass estimations. We sought to determine if there was a significant pattern of wood density across the altitudinal gradient, which has implications for conservation of both ecosystem services and biodiversity. We also wanted to determine how many random individuals could be sampled to accurately estimate aboveground biomass in a one-hectare plot. Our results indicate that there is a strong relationship between LVIS-derived forest 3D-structure and alpha diversity, likely controlled by variations in abiotic factors and topography along the elevation. Using spatial analysis with the aid of remote sensing data, we found patterns along the environmental gradients defining species composition and forest structure. Wood density values were found to vary significantly from database values for the same species. This variation in tree growth has repercussions on overall forest structure, and subsequent carbon estimates extrapolated from field measurements. Because these wood density values are directly tied to biomass estimates, it is possible that carbon storage has been

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

    NASA Astrophysics Data System (ADS)

    Chen, Qi

    2015-08-01

    Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.

  9. Estimating Aboveground Net Primary Productivity of Black Spruce along a Climatic Gradient in the Boreal Forest.

    NASA Astrophysics Data System (ADS)

    Bhatti, J.; Varem-Sanders, T.; Bouriaud, O.

    2005-12-01

    Net primary productivity (NPP) is the difference between carbon assimilation by photosynthesis and plant respiration quantifies the rate at which carbon is accumulated in the living vegetation. The ability to measure net primary productivity (NPP) over a period of years using relatively inexpensive methods can be a tremendous asset when assessing the forest response to climate change. This project investigates and evaluates a new comprehensive method of estimating multi-decadal historical black spruce productivity using biomass stocks and tree ring width measurements along a climatic gradient. Black spruce aboveground NPP was calculated for even aged stands along Boreal Forest Transect Case Study (BFTCS) with similar soil and fertility characteristics. Biomass functions were modified using local DBH-height functions to determine tree level with Dbh as the sole predictor. Above ground net primary productivity was estimated from the stand level change in biomass with measured litter production rate on these sites. Tree biomass increment and litter production increases from Central Saskatchewan at the southern limit of the boreal forest where the climate is warm and dry up to Thompson (Northern Manitoba) where the climate is wetter and colder. Aboveground NPP for mature stands ranges from 671 to 1567 kg C ha-1 yr-1. Both at the southern boreal sites and northern boreal sites, the tree productivity was highly sensitivity to climate variability. The younger mixed black spruce stands are considerably more productive than older pure stands. Litter production is a major component and accounts for 30 to 60% of aboveground NPP. Practical robust estimation of aboveground NPP using tree ring measurement offers the potential for application over large spatial and temporal scale.

  10. Ecological studies on the revegetation process of surface coal mined areas in North Dakota. 6. Relationship between cover and aboveground biomass. Final report Aug 75-Jun 82

    SciTech Connect

    Schimmelpfennig, D.K.

    1982-06-01

    Assessment of revegetation success on mined lands is a difficult, time consuming task and has been the subject of a number of controversies. Present regulations require that both plant cover and aboveground plant biomass be measured for use in making that assessment. Of these two variables, biomass is the most time consuming to measure and requires destructive sampling, a most undesirable, requirement on fragile, recently revegetated areas. A study was done to evaluate the predictability of aboveground biomass production on revegetated mined sites and adjacent native prairies using plant cover estimates made with the point frame method. A positive, statistically significant correlation was demonstrated between plant cover and aboveground biomass regardless of the community type, species composition, diversity or level of biomass production. However, the latter did have their effects on the relationship and must be accounted for in any predictive equations.

  11. Plot-level aboveground woody biomass modeling using canopy height and auxiliary remote sensing data in a heterogeneous savanna

    NASA Astrophysics Data System (ADS)

    Gwenzi, David; Lefsky, Michael Andrew

    2016-01-01

    Remote sensing studies aiming at assessing woody biomass have demonstrated a strong relationship between canopy height and plot-level aboveground biomass, but most of these studies focused on closed canopy forests. To date, a few studies have examined the strength and reliability of this relationship using large footprint lidar in savannas. Furthermore, there have been few studies of appropriate methods for the comparison of models that relate aboveground biomass to canopy height metrics without consideration of variation in species composition (generic models) to models developed for individual species composition or vegetation types. We developed generic models using the classical least-squares regression modeling approach to relate selected canopy height metrics to aboveground woody biomass in a savanna landscape. Hierarchical Bayesian analysis (HBA) was then used to explore the implications of using generic or composition-specific models. Our study used the estimates of aboveground biomass from field data, canopy height estimates from airborne discrete return lidar, and a proxy for canopy cover (the Normalized Difference Vegetation Index) from Landsat 5 Thematic Mapper data, collected from the oak savannas of Tejon Ranch Conservancy in Kern County, California. Models were developed and analyzed using estimates of canopy height and aboveground biomass calculated at the level of 50-m diameter plots, comparable with footprint diameter of existing large footprint spaceborne lidar data. The two generic models that incorporated canopy cover proxies performed better than one model that did not use canopy cover information. From the HBA, we found out that for all models both the intercept and slope had interspecific variability. The valley oak dominated plots consistently had higher slopes and intercepts, whereas the plots dominated by blue oaks had the lowest. However, the intercept and slope values of the composition-specific models did not differ much from the

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    Alsumaiti, Tareefa Saad Sultan

    Mangrove forests are national treasures of the United Arab Emirates (UAE) and other arid countries with limited forested areas. Mangroves form a crucial part of the coastal ecosystem and provide numerous benefits to society, economy, and especially the environment. Mangrove trees, specifically Avicennia marina, are studied in their native habitat in order to characterize their population structure, aboveground biomass, and soil properties. This study focused on Eastern Mangrove Lagoon National Park in Abu Dhabi, which was the first mangrove protected area to be designated in UAE. In situ measurements were collected to estimate Avicennia marina status, mortality rate (%), height (m), crown spread (m), stem number, diameter at breast height (cm), basal area (m), and aboveground biomass (t ha-1 ). Small-footprint aerial light detection and ranging (LIDAR) data acquired by UAE were processed to characterize mangrove canopy height and aboveground biomass density. This included extraction of LIDAR-derived height percentile statistics, segmentation of the forest into structurally homogenous units, and development of regression relationships between in situ reference and remote sensing data using a machine learning approach. An in situ soil survey was conducted to examine the soils' physical and chemical properties, fertility status, and organic matter. The data of soil survey were used to create soil maps to evaluate key characteristics of soils, and their influence on Avicennia marina in Eastern Mangrove Lagoon National Park. The results of this study provide new insights into Avicennia marina canopy population, structure, aboveground biomass, and soil properties in Abu Dhabi, as data in such arid environments is lacking. This valuable information can help in managing and preserving this unique ecosystem.

  14. [Spatiotemporal variations of aboveground biomass and leaf area index of typical grassland in tower flux footprint].

    PubMed

    Wang, Meng; Li, Gui-cai; Wang, Jun-bang

    2011-03-01

    By using cyclic sampling method, the aboveground biomass and leaf area index (LAI) of typical grassland in tower flux footprint were measured at three growth stages, i.e., early July (July 2-7), late July (July 20-26), and late August (Aug. 25-30), with their spatial patterns analyzed by geostatistics. At the three stages, the aboveground biomass of the grassland kept rising, while the LAI decreased after an initial increase. Both the two variables had good spatial autocorrelation, with similar spatial pattern and temporal evolution trend, and changed from stripe to patch. From early July to late August, the C0/(C0+C) of the aboveground biomass and LAI all decreased significantly, indicating that the spatial autocorrelation of the two variables changed from medium to high. The change ranges of the two variables gradually decreased, presenting the decrease of spatial continuity. The fractal dimension (D) also decreased gradually, suggesting the increase of spatial dependence. Topography and field management were the main factors affecting the spatial distribution of aboveground biomass and LAI, which induced the spatial variability of water and heat, and further, affected the grass growth. PMID:21657018

  15. Aboveground total and green biomass of dryland shrub derived from terrestrial laser scanning

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The distribution of many dryland vegetation species are expected to shift based on predictions of future increases in global temperatures. Quantifying aboveground biomass in dryland systems is important for assessing global carbon storage and monitoring the presence and distribution of these rapidl...

  16. [Spatiotemporal variations of aboveground biomass and leaf area index of typical grassland in tower flux footprint].

    PubMed

    Wang, Meng; Li, Gui-cai; Wang, Jun-bang

    2011-03-01

    By using cyclic sampling method, the aboveground biomass and leaf area index (LAI) of typical grassland in tower flux footprint were measured at three growth stages, i.e., early July (July 2-7), late July (July 20-26), and late August (Aug. 25-30), with their spatial patterns analyzed by geostatistics. At the three stages, the aboveground biomass of the grassland kept rising, while the LAI decreased after an initial increase. Both the two variables had good spatial autocorrelation, with similar spatial pattern and temporal evolution trend, and changed from stripe to patch. From early July to late August, the C0/(C0+C) of the aboveground biomass and LAI all decreased significantly, indicating that the spatial autocorrelation of the two variables changed from medium to high. The change ranges of the two variables gradually decreased, presenting the decrease of spatial continuity. The fractal dimension (D) also decreased gradually, suggesting the increase of spatial dependence. Topography and field management were the main factors affecting the spatial distribution of aboveground biomass and LAI, which induced the spatial variability of water and heat, and further, affected the grass growth.

  17. Above-ground Biomass Investments and Light Interception of Tropical Forest Trees and Lianas Early in Succession

    PubMed Central

    Selaya, N. G.; Anten, N. P. R.; Oomen, R. J.; Matthies, M.; Werger, M. J. A.

    2007-01-01

    Background and Aims Crown structure and above-ground biomass investment was studied in relation to light interception of trees and lianas growing in a 6-month-old regenerating forest. Methods The vertical distribution of total above-ground biomass, height, diameter, stem density, leaf angles and crown depth were measured for individual plants of three short-lived pioneers (SLPs), four long-lived pioneers (LLPs) and three lianas. Daily light interception per individual Φd was calculated with a canopy model. The model was then used to estimate light interception per unit of leaf mass (Φleaf mass), total above-ground mass (Φmass) and crown structure efficiency (Ea, the ratio of absorbed vs. available light). Key Results The SLPs Trema and Ochroma intercepted higher amounts of light per unit leaf mass (Φleaf mass) because they had shallower crowns, resulting in higher crown use efficiency (Ea) than the other species. These SLPs (but not Cecropia) were also taller and intercepted more light per unit leaf area (Φarea). LLPs and lianas had considerably higher amounts of leaf mass and area per unit above-ground mass (LMR and LAR, respectively) and thus attained Φmass values similar to the SLPs (Φmass=Φarea×LAR). Lianas, which were mostly self-supporting, had light interception efficiencies similar to those of the trees. Conclusions These results show how, due to the trade-off between crown structure and biomass allocation, SLPs, and LLPs and lianas intercept similar amount of light per unit mass which may contribute to the ability of the latter two groups to persist. PMID:17210607

  18. Final Harvest of Above-Ground Biomass and Allometric Analysis of the Aspen FACE Experiment

    SciTech Connect

    Mark E. Kubiske

    2013-04-15

    The Aspen FACE experiment, located at the US Forest Service Harshaw Research Facility in Oneida County, Wisconsin, exposes the intact canopies of model trembling aspen forests to increased concentrations of atmospheric CO2 and O3. The first full year of treatments was 1998 and final year of elevated CO2 and O3 treatments is scheduled for 2009. This proposal is to conduct an intensive, analytical harvest of the above-ground parts of 24 trees from each of the 12, 30 m diameter treatment plots (total of 288 trees) during June, July & August 2009. This above-ground harvest will be carefully coordinated with the below-ground harvest proposed by D.F. Karnosky et al. (2008 proposal to DOE). We propose to dissect harvested trees according to annual height growth increment and organ (main stem, branch orders, and leaves) for calculation of above-ground biomass production and allometric comparisons among aspen clones, species, and treatments. Additionally, we will collect fine root samples for DNA fingerprinting to quantify biomass production of individual aspen clones. This work will produce a thorough characterization of above-ground tree and stand growth and allocation above ground, and, in conjunction with the below ground harvest, total tree and stand biomass production, allocation, and allometry.

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

    NASA Astrophysics Data System (ADS)

    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).

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

    PubMed

    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

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

    PubMed Central

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

    2013-01-01

    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

  2. Topographic Variation in Aboveground Biomass in a Subtropical Evergreen Broad-Leaved Forest in China

    PubMed Central

    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. PMID:23118961

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

    NASA Astrophysics Data System (ADS)

    Stelmaszczuk-Gorska, M. A.; Thiel, C. J.; Schmullius, C.

    2014-12-01

    Aboveground biomass (AGB) plays an essential role in ecosystem research, global cycles, and is of vital importance in climate studies. AGB accumulated in the forests is of special monitoring interest as it contains the most of biomass comparing with other land biomes. The largest of the land biomes is boreal forest, which has a substantial carbon accumulation capability; carbon stock estimated to be 272 +/-23 Pg C (32%) [1]. Russian's forests are of particular concern, due to the largest source of uncertainty in global carbon stock calculations [1], and old inventory data that have not been updated in the last 25 years [2]. In this research new empirical models for AGB estimation are proposed. Using radar L-band data for AGB retrieval and optical data for an update of in situ data the processing scheme was developed. The approach was trained and validated in the Asian part of the boreal forest, in southern Russian Central Siberia; two Siberian Federal Districts: Krasnoyarsk Kray and Irkutsk Oblast. Together the training and testing forest territories cover an area of approximately 3,500 km2. ALOS PALSAR L-band single (HH - horizontal transmitted and received) and dual (HH and HV - horizontal transmitted, horizontal and vertical received) polarizations in Single Look Complex format (SLC) were used to calculate backscattering coefficient in gamma nought and coherence. In total more than 150 images acquired between 2006 and 2011 were available. The data were obtained through the ALOS Kyoto and Carbon Initiative Project (K&C). The data were used to calibrate a randomForest algorithm. Additionally, a simple linear and multiple-regression approach was used. The uncertainty of the AGB estimation at pixel and stand level were calculated approximately as 35% by validation against an independent dataset. The previous studies employing ALOS PALSAR data over boreal forests reported uncertainty of 39.4% using randomForest approach [2] or 42.8% using semi-empirical approach [3].

  4. Impacts of Tree Height-Dbh Allometry on Lidar-Based Tree Aboveground Biomass Modeling

    NASA Astrophysics Data System (ADS)

    Fang, R.

    2016-06-01

    Lidar has been widely used in tree aboveground biomass (AGB) estimation at plot or stand levels. Lidar-based AGB models are usually constructed with the ground AGB reference as the response variable and lidar canopy indices as predictor variables. Tree diameter at breast height (dbh) is the major variable of most allometric models for estimating reference AGB. However, lidar measurements are mainly related to tree vertical structure. Therefore, tree height-dbh allometric model residuals are expected to have a large impact on lidar-based AGB model performance. This study attempts to investigate sensitivity of lidar-based AGB model to the decreasing strength of height-dbh relationship using a Monte Carlo simulation approach. Striking decrease in R2 and increase in relative RMSE were found in lidar-based AGB model, as the variance of height-dbh model residuals grew. I, therefore, concluded that individual tree height-dbh model residuals fundamentally introduce errors to lidar-AGB models.

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

    NASA Astrophysics Data System (ADS)

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

    NASA Astrophysics Data System (ADS)

    Dahlin, K.; Asner, G. P.; Field, C. B.

    2009-12-01

    Aboveground biomass accumulation is a useful metric for evaluating habitat restoration and ecosystem services projects, in addition to being a robust measure of carbon sequestration. However, at the landscape scale non-anthropogenic controls on biomass accumulation are poorly understood. In this study we combined field measurements, high resolution data from the NASA JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Carnegie Airborne Observatory (CAO) airborne light detection and ranging (lidar) system to create a comprehensive map of aboveground biomass across a patchy mediterranean-type landscape (Jasper Ridge Biological Preserve, Stanford, CA). Candidate explanatory variables (e.g. slope, elevation, incident solar radiation) were developed using a geologic map and a digital elevation model derived from the lidar data. Finally, candidate variables were tested, and a model was produced to predict aboveground biomass from environmental data. Though many of the explanatory variables have only indirect effects on plant growth, the model permits inferences to be made about the relative importance of light, water, temperature, and edaphic characteristics on carbon accumulation in mediterranean-type systems.

  7. 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

    SciTech Connect

    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

  8. Above-ground biomass and structure of 260 African tropical forests.

    PubMed

    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

  9. Above-ground biomass and structure of 260 African tropical forests

    PubMed Central

    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

  10. Temporal variability in aboveground plant biomass decreases as spatial variability increases.

    PubMed

    McGranahan, Devan Allen; Hovick, Torre J; Elmore, R Dwayne; Engle, David M; Fuhlendorf, Samuel D; Winter, Stephen L; Miller, James R; Debinski, Diane M

    2016-03-01

    Ecological theory predicts that diversity decreases variability in ecosystem function. We predict that, at the landscape scale, spatial variability created by a mosaic of contrasting patches that differ in time since disturbance will decrease temporal variability in aboveground plant biomass. Using data from a multi-year study of seven grazed tallgrass prairie landscapes, each experimentally managed for one to eight patches, we show that increased spatial variability driven by spatially patchy fire and herbivory reduces temporal variability in aboveground plant biomass. This pattern is associated with statistical evidence for the portfolio effect and a positive relationship between temporal variability and functional group synchrony as predicted by metacommunity variability theory. As disturbance from fire and grazing interact to create a shifting mosaic of spatially heterogeneous patches within a landscape, temporal variability in aboveground plant biomass can be dampened. These results suggest that spatially heterogeneous disturbance regimes contribute to a portfolio of ecosystem functions provided by biodiversity, including wildlife habitat, fuel, and forage. We discuss how spatial patterns of disturbance drive variability within and among patches. PMID:27197382

  11. Temporal variability in aboveground plant biomass decreases as spatial variability increases.

    PubMed

    McGranahan, Devan Allen; Hovick, Torre J; Elmore, R Dwayne; Engle, David M; Fuhlendorf, Samuel D; Winter, Stephen L; Miller, James R; Debinski, Diane M

    2016-03-01

    Ecological theory predicts that diversity decreases variability in ecosystem function. We predict that, at the landscape scale, spatial variability created by a mosaic of contrasting patches that differ in time since disturbance will decrease temporal variability in aboveground plant biomass. Using data from a multi-year study of seven grazed tallgrass prairie landscapes, each experimentally managed for one to eight patches, we show that increased spatial variability driven by spatially patchy fire and herbivory reduces temporal variability in aboveground plant biomass. This pattern is associated with statistical evidence for the portfolio effect and a positive relationship between temporal variability and functional group synchrony as predicted by metacommunity variability theory. As disturbance from fire and grazing interact to create a shifting mosaic of spatially heterogeneous patches within a landscape, temporal variability in aboveground plant biomass can be dampened. These results suggest that spatially heterogeneous disturbance regimes contribute to a portfolio of ecosystem functions provided by biodiversity, including wildlife habitat, fuel, and forage. We discuss how spatial patterns of disturbance drive variability within and among patches.

  12. Tibetan alpine tundra responses to simulated changes in climate: Aboveground biomass and community responses

    SciTech Connect

    Yanqing Zhang; Welker, J.M.

    1996-05-01

    High-elevation ecosystems are predicted to be some of the terrestrial habitats most sensitive to changing climates. The ecological consequences of changes in alpine tundra environmental conditions are still unclear especially for habitats in Asia. In this study we report findings from a field experiment where an alpine tundra grassland on the Tibetan plateau (37{degrees}N, 101{degrees}E) was exposed to experimental warming, irradiance was lowered, and wind speed reduced to simulate a suite of potential changes in environmental conditions. Our warming treatment increased air temperatures by 5{degrees}C on average and soil temperatures were elevated by 3{degrees}C at 5 cm depth. Aboveground biomass of grasses responded rapidly to the warmer conditions whereby biomass was 25% greater than that of controls after only 5 wk of experimental warming. This increase was accompanied by a simultaneous decrease in forb biomass, resulting in almost no net change in community biomass after 5 wk. Lower irradiance reduced grass biomass during the same period. Under ambient conditions total aboveground community biomass increased seasonally from 161 g m{sup -2} in July to a maximum of 351 g m{sup -2} in September, declining to 285 g m{sup -2} in October. However, under warmed conditions, peak community biomass was extended into October due in part to continued growth of grasses and the postponement of senescence. Our finding indicate that while alpine grasses respond favorably to altered conditions, others may not. And, while peak community biomass may actually change very little under warmer summers, the duration of peak biomass may be extended having feedback effects on net ecosystem CO{sub 2} balances, nutrient cycling, and forage availability. 47 refs., 3 figs., 3 tabs.

  13. Simulation results of aboveground woody biomass and leaf litterfall for African tropical forest with a global terrestrial model

    NASA Astrophysics Data System (ADS)

    De Weirdt, Marjolein; Maignan, Fabienne; Peylin, Philippe; Poulter, Benjamin; Moreau, Inès; Ciais, Philippe; Defourny, Pierre; Steppe, Kathy; Verbeeck, Hans

    2014-05-01

    The response of tropical forest vegetation to global climate change could be central to predictions of future levels of atmospheric carbon dioxide. Tropical forests are believed to annually process approximately six times as much carbon via photosynthesis and respiration as humans emit from fossil fuel use. Of all tropical forests worldwide, the role of African tropical forest is not very well known and both the quantity as well as the dynamics of tropical forest carbon stocks and fluxes are very poorly quantified components of the global carbon cycle. Furthermore, African tropical forest spatial carbon stocks patterns as measured in the field are not as well represented by the global biogeochemical models as they are for temperate forests. In this study, a first simulation for the African tropical forest with the process based global terrestrial ecosystem model ORCHIDEE was done. In this work, ORCHIDEE included deep soils, seasonal leaf litterfall and phosphorus availability mechanisms for tropical evergreen forests included. The ORCHIDEE model run outputs are evaluated against reported field inventories, investigating seasonal variations in leaf litterfall and spatial variation in aboveground woody biomass. A comparison between modeled and measured leaf litterfall was made at a semi-deciduous Equatorial rainforest site in the Republic of Congo at the Biosphere reserve Dimonika south of Gabon. Also, simulated woody aboveground biomass was compared against site-level field inventories and satellite-based estimates based on a combination of MODIS imagery with field inventory data from Uganda, DRC and Cameroon. First comparison results seem promising and show that the radiation driven leaf litterfall model results correspond well with the field inventories and that the mean of the modelled aboveground woody biomass matches the available field inventory observations but there is still a need for more ground data to evaluate the model outcome over a large region like

  14. Spectroscopic Determination of Aboveground Biomass in Grasslands Using Spectral Transformations, Support Vector Machine and Partial Least Squares Regression

    PubMed Central

    Marabel, Miguel; Alvarez-Taboada, Flor

    2013-01-01

    Aboveground biomass (AGB) is one of the strategic biophysical variables of interest in vegetation studies. The main objective of this study was to evaluate the Support Vector Machine (SVM) and Partial Least Squares Regression (PLSR) for estimating the AGB of grasslands from field spectrometer data and to find out which data pre-processing approach was the most suitable. The most accurate model to predict the total AGB involved PLSR and the Maximum Band Depth index derived from the continuum removed reflectance in the absorption features between 916–1,120 nm and 1,079–1,297 nm (R2 = 0.939, RMSE = 7.120 g/m2). Regarding the green fraction of the AGB, the Area Over the Minimum index derived from the continuum removed spectra provided the most accurate model overall (R2 = 0.939, RMSE = 3.172 g/m2). Identifying the appropriate absorption features was proved to be crucial to improve the performance of PLSR to estimate the total and green aboveground biomass, by using the indices derived from those spectral regions. Ordinary Least Square Regression could be used as a surrogate for the PLSR approach with the Area Over the Minimum index as the independent variable, although the resulting model would not be as accurate. PMID:23925082

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

    NASA Astrophysics Data System (ADS)

    Meggio, Franco; Vendrame, Nadia; Maniero, Giovanni; Pitacco, Andrea

    2014-05-01

    In the current climate change scenarios, both agriculture and forestry inherently may act as carbon sinks and consequently can play a key role in limiting global warming. An urgent need exists to understand which land uses and land resource types have the greatest potential to mitigate greenhouse gas (GHG) emissions contributing to global change. A common believe is that agricultural fields cannot be net carbon sinks due to many technical inputs and repeated disturbances of upper soil layers that all contribute to a substantial loss both of the old and newly-synthesized organic matter. Perennial tree crops (vineyards and orchards), however, can behave differently: they grow a permanent woody structure, stand undisturbed in the same field for decades, originate a woody pruning debris, and are often grass-covered. In this context, reliable methods for quantifying and modelling emissions and carbon sequestration are required. Carbon stock changes are calculated by multiplying the difference in oven dry weight of biomass increments and losses with the appropriate carbon fraction. These data are relatively scant, and more information is needed on vineyard management practices and how they impact vineyard C sequestration and GHG emissions in order to generate an accurate vineyard GHG footprint. During the last decades, research efforts have been made for estimating the vineyard carbon budget and its allocation pattern since it is crucial to better understand how grapevines control the distribution of acquired resources in response to variation in environmental growth conditions and agronomic practices. The objective of the present study was to model and compare the dynamics of current year's above-ground biomass among four grapevine varieties. Trials were carried out over three growing seasons in field conditions. The non-linear extra-sums-of-squares method demonstrated to be a feasible way of growth models comparison to statistically assess significant differences among

  16. Interactions between herbivory and warming in aboveground biomass production of arctic vegetation

    PubMed Central

    Pedersen, Christian; Post, Eric

    2008-01-01

    Background Many studies investigating the ecosystem effects of global climate change have focused on arctic ecosystems because the Arctic is expected to undergo the earliest and most pronounced changes in response to increasing global temperatures, and arctic ecosystems are considerably limited by low temperatures and permafrost. In these nutrient limited systems, a warmer climate is expected to increase plant biomass production, primarily through increases in shrubs over graminoids and forbs. But, the influence of vertebrate and invertebrate herbivores has been largely absent in studies investigating the effects of vegetation responses to climate change, despite the fact that herbivory can have a major influence on plant community composition, biomass and nutrient cycling. Here, we present results from a multi-annual field experiment investigating the effects of vertebrate herbivory on plant biomass response to simulated climate warming in arctic Greenland. Results The results after four years of treatments did not give any clear evidence of increased biomass of shrubs in response climate warming. Nor did our study indicate that vertebrate grazing mediated any increased domination of shrubs over other functional plant groups in response to warming. However, our results indicate an important role of insect outbreaks on aboveground biomass. Intense caterpillar foraging from a two-year outbreak of the moth Eurois occulta during two growing seasons may have concealed any treatment effects. However, there was some evidence suggesting that vertebrate herbivores constrain the biomass production of shrubs over graminoids and forbs. Conclusion Although inconclusive, our results were likely constrained by the overwhelming influence of an unexpected caterpillar outbreak on aboveground biomass. It is likely that the role of large vertebrate herbivores in vegetation response to warming will become more evident as this experiment proceeds and the plant community recovers from

  17. Plant diversity and functional groups affect Si and Ca pools in aboveground biomass of grassland systems.

    PubMed

    Schaller, Jörg; Roscher, Christiane; Hillebrand, Helmut; Weigelt, Alexandra; Oelmann, Yvonne; Wilcke, Wolfgang; Ebeling, Anne; Weisser, Wolfgang W

    2016-09-01

    Plant diversity is an important driver of nitrogen and phosphorus stocks in aboveground plant biomass of grassland ecosystems, but plant diversity effects on other elements also important for plant growth are less understood. We tested whether plant species richness, functional group richness or the presence/absence of particular plant functional groups influences the Si and Ca concentrations (mmol g(-1)) and stocks (mmol m(-2)) in aboveground plant biomass in a large grassland biodiversity experiment (Jena Experiment). In the experiment including 60 temperate grassland species, plant diversity was manipulated as sown species richness (1, 2, 4, 8, 16) and richness and identity of plant functional groups (1-4; grasses, small herbs, tall herbs, legumes). We found positive species richness effects on Si as well as Ca stocks that were attributable to increased biomass production. The presence of particular functional groups was the most important factor explaining variation in aboveground Si and Ca stocks (mmol m(-2)). Grass presence increased the Si stocks by 140 % and legume presence increased the Ca stock by 230 %. Both the presence of specific plant functional groups and species diversity altered Si and Ca stocks, whereas Si and Ca concentration were affected mostly by the presence of specific plant functional groups. However, we found a negative effect of species diversity on Si and Ca accumulation, by calculating the deviation between mixtures and mixture biomass proportions, but in monoculture concentrations. These changes may in turn affect ecosystem processes such as plant litter decomposition and nutrient cycling in grasslands.

  18. Long-term patterns in tropical reforestation: plant community composition and aboveground biomass accumulation.

    PubMed

    Marín-Spiotta, E; Ostertag, R; Silver, W L

    2007-04-01

    Primary tropical forests are renowned for their high biodiversity and carbon storage, and considerable research has documented both species and carbon losses with deforestation and agricultural land uses. Economic drivers are now leading to the abandonment of agricultural lands, and the area in secondary forests is increasing. We know little about how long it takes for these ecosystems to achieve the structural and compositional characteristics of primary forests. In this study, we examine changes in plant species composition and aboveground biomass during eight decades of tropical secondary succession in Puerto Rico, and compare these patterns with primary forests. Using a well-replicated chronosequence approach, we sampled primary forests and secondary forests established 10, 20, 30, 60, and 80 years ago on abandoned pastures. Tree species composition in all secondary forests was different from that of primary forests and could be divided into early (10-, 20-, and 30-year) vs. late (60- and 80-year) successional phases. The highest rates of aboveground biomass accumulation occurred in the first 20 years, with rates of C sequestration peaking at 6.7 +/- 0.5 Mg C x ha(-1) x yr(-1). Reforestation of pastures resulted in an accumulation of 125 Mg C/ha in aboveground standing live biomass over 80 years. The 80 year-old secondary forests had greater biomass than the primary forests, due to the replacement of woody species by palms in the primary forests. Our results show that these new ecosystems have different species composition, but similar species richness, and significant potential for carbon sequestration, compared to remnant primary forests. PMID:17494400

  19. Plant diversity and functional groups affect Si and Ca pools in aboveground biomass of grassland systems.

    PubMed

    Schaller, Jörg; Roscher, Christiane; Hillebrand, Helmut; Weigelt, Alexandra; Oelmann, Yvonne; Wilcke, Wolfgang; Ebeling, Anne; Weisser, Wolfgang W

    2016-09-01

    Plant diversity is an important driver of nitrogen and phosphorus stocks in aboveground plant biomass of grassland ecosystems, but plant diversity effects on other elements also important for plant growth are less understood. We tested whether plant species richness, functional group richness or the presence/absence of particular plant functional groups influences the Si and Ca concentrations (mmol g(-1)) and stocks (mmol m(-2)) in aboveground plant biomass in a large grassland biodiversity experiment (Jena Experiment). In the experiment including 60 temperate grassland species, plant diversity was manipulated as sown species richness (1, 2, 4, 8, 16) and richness and identity of plant functional groups (1-4; grasses, small herbs, tall herbs, legumes). We found positive species richness effects on Si as well as Ca stocks that were attributable to increased biomass production. The presence of particular functional groups was the most important factor explaining variation in aboveground Si and Ca stocks (mmol m(-2)). Grass presence increased the Si stocks by 140 % and legume presence increased the Ca stock by 230 %. Both the presence of specific plant functional groups and species diversity altered Si and Ca stocks, whereas Si and Ca concentration were affected mostly by the presence of specific plant functional groups. However, we found a negative effect of species diversity on Si and Ca accumulation, by calculating the deviation between mixtures and mixture biomass proportions, but in monoculture concentrations. These changes may in turn affect ecosystem processes such as plant litter decomposition and nutrient cycling in grasslands. PMID:27164912

  20. Multi- and hyperspectral remote-sensing retrieval of floodplain-forest aboveground biomass using machine learning

    NASA Astrophysics Data System (ADS)

    Filippi, A. M.; Guneralp, I.; Randall, J.

    2014-12-01

    Forests within dynamic floodplain landscapes, such as meandering-river landscapes, are composed of uneven-aged trees and entail high spatial variability, which results from intersecting hydrological, fluvial, and ecological processes. Floodplain forests are an important carbon sink relative to other terrestrial ecosystems and thus serve a critical role in the global carbon cycle. Accurate, quantitative aboveground biomass (AGB) retrieval within floodplain forests is urgently needed for improved carbon-pool estimates in such areas and enhanced process understanding of river-floodplain biomorphodynamics. We perform remote AGB retrieval for a meander-bend bottomland hardwood forest, based on utilization of stochastic gradient boosting (SGB), multivariate adaptive regression splines (MARS), and Cubist algorithms and multi- and hyperspectral image-based data sets. For multispectral experiments, we use 30-m and 10-m image bands (Landsat 7 ETM+ and SPOT 5, respectively) and ancillary input vectors; for hyperspectral-based experiments, we use 30-m Hyperion bands and other input variables. Results indicate that for both the multispectral and hyperspectral experimental trials, SGB- and MARS-derived AGB are significantly more accurate than Cubist estimates. (Cubist is used for U.S. national-scale forest biomass mapping.) For the multispectral results, across all data-experiments and algorithms, at 10-m spatial resolution, SGB gives the most accurate estimates (RMSE = 22.49 tonnes/ha; coefficient of determination (R2) = 0.96) when geomorphometric data are also included. For 30-m multispectral data trials, MARS performs the best (RMSE = 29.2 tonnes/ha; R2 = 0.94) when image-derived data are also incorporated. For the hyperspectral experiments, the most accurate MARS- and SGB-based retrievals have R2 of 0.97 and 0.95, respectively; the most accurate Cubist AGB retrieval has R2 of 0.85. MARS and SGB AGB are not significantly different though for the hyperspectral experiments. The

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

    NASA Astrophysics Data System (ADS)

    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.

  2. [Vegetation above-ground biomass and its affecting factors in water/wind erosion crisscross region on Loess Plateau].

    PubMed

    Wang, Jian-guo; Fan, Jun; Wang, Quan-jiu; Wang, Li

    2011-03-01

    Field investigations were conducted in Liudaogou small watershed in late September 2009 to study the differences of vegetation above-ground biomass, soil moisture content, and soil nutrient contents under different land use patterns, aimed to approach the vegetation above-ground biomass level and related affecting factors in typical small watershed in water/wind erosion crisscross region on Loess Plateau. The above-ground dry biomass of the main vegetations in Liudaogou was 177-2207 g x m(-2), and that in corn field, millet field, abandoned farmland, artificial grassland, natural grassland, and shrub land was 2097-2207, 518-775, 248-578, 280-545, 177-396, and 372-680 g x m(-2), respectively. The mean soil moisture content in 0-100 layer was the highest (14.2%) in farmlands and the lowest (10.9%) in shrub land. The coefficient of variation of soil moisture content was the greatest (26. 7% ) in abandoned farmland, indicating the strong spatial heterogeneity of soil moisture in this kind of farmland. The mean soil water storage was in the order of farmland > artificial grassland > natural grassland > shrub land. Soil dry layer was observed in alfalfa and caragana lands. There was a significant positive correlation (r = 0.639, P < 0.05) between above-ground dry biomass and 0-100 cm soil water storage, and also, a very significant positive correlation between above-ground fresh biomass and vegetation height. The above-ground biomass of the higher vegetations could potentially better control the wind and water erosion in the water/wind erosion crisscross region. Vegetation above-ground biomass was highly correlated with soil moisture and nutrient contents, but had no significant correlations with elevation, slope gradient, slope aspect, and soil bulk density.

  3. Annual Removal of Aboveground Plant Biomass Alters Soil Microbial Responses to Warming

    PubMed Central

    Xue, Kai; Yuan, Mengting M.; Xie, Jianping; Li, Dejun; Qin, Yujia; Wu, Liyou; Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Luo, Yiqi; Tiedje, James M.

    2016-01-01

    ABSTRACT Clipping (i.e., harvesting aboveground plant biomass) is common in agriculture and for bioenergy production. However, microbial responses to clipping in the context of climate warming are poorly understood. We investigated the interactive effects of grassland warming and clipping on soil properties and plant and microbial communities, in particular, on microbial functional genes. Clipping alone did not change the plant biomass production, but warming and clipping combined increased the C4 peak biomass by 47% and belowground net primary production by 110%. Clipping alone and in combination with warming decreased the soil carbon input from litter by 81% and 75%, respectively. With less carbon input, the abundances of genes involved in degrading relatively recalcitrant carbon increased by 38% to 137% in response to either clipping or the combined treatment, which could weaken long-term soil carbon stability and trigger positive feedback with respect to warming. Clipping alone also increased the abundance of genes for nitrogen fixation, mineralization, and denitrification by 32% to 39%. Such potentially stimulated nitrogen fixation could help compensate for the 20% decline in soil ammonium levels caused by clipping alone and could contribute to unchanged plant biomass levels. Moreover, clipping tended to interact antagonistically with warming, especially with respect to effects on nitrogen cycling genes, demonstrating that single-factor studies cannot predict multifactorial changes. These results revealed that clipping alone or in combination with warming altered soil and plant properties as well as the abundance and structure of soil microbial functional genes. Aboveground biomass removal for biofuel production needs to be reconsidered, as the long-term soil carbon stability may be weakened. PMID:27677789

  4. [Effect of flooding disturbance on aboveground biomass of Leymus chinensis grassland--a preliminary study].

    PubMed

    Wang, Zhengwen; Zhu, Tingcheng

    2003-12-01

    To investigate the effect of flooding disturbance on the net primary productivity of Songnen steppe, a comparatively thorough study was conducted on Sanjiadian State-owned Rangeland in Da'an city, Jilin Province, which was partly flooded in 1998. The study site was located in the south Songnen plain of Northeastern China, dominated by Leymus chinensis grassland. An extensively mild slope with flooding gradients (from un-flooded to heavily flooded) was taken as the study site. Two flooded transects coded FL and FH which was respectively subjected to 3 and 9 months of flooding were designed, and an un-flooded one coded CK at a relatively higher elevation was set as a control. Before flooding occurred in 1998, the slope had an almost uniform soil and L. chinensis dominated vegetation. Each transect was 0.2 hm2 (100 m x 20 m) in size, and the two flooded transects were almost paralleled each other, with the longer sides of them perpendicular to the retrieving direction of floodwater. In each transect twenty 1 m2 sized quadrats were randomly chosen to survey the community structure and the aboveground biomass. Comparative analyses were made on the dynamics of soil water, soil N and P, and species composition of grassland communities that occurred in responses to flooding disturbance. The results showed that the lightly and heavily flooded transects had a significantly larger aboveground biomass than the control, with the increase of 89.54% and 113.45%, respectively. The heavily flooded transect had a slightly but insignificantly larger aboveground biomass than the lightly flooded one, indicating that on flooded sites, water was not the limiting factor of the aboveground biomass. The acute changes of soil water caused by flooding led to the changes of soil nutrients and species assemblages, which would impact community biomass. Just as the case for aboveground biomass, the soil water contents of the two flooded transects were significantly larger than that of control

  5. [Effect of flooding disturbance on aboveground biomass of Leymus chinensis grassland--a preliminary study].

    PubMed

    Wang, Zhengwen; Zhu, Tingcheng

    2003-12-01

    To investigate the effect of flooding disturbance on the net primary productivity of Songnen steppe, a comparatively thorough study was conducted on Sanjiadian State-owned Rangeland in Da'an city, Jilin Province, which was partly flooded in 1998. The study site was located in the south Songnen plain of Northeastern China, dominated by Leymus chinensis grassland. An extensively mild slope with flooding gradients (from un-flooded to heavily flooded) was taken as the study site. Two flooded transects coded FL and FH which was respectively subjected to 3 and 9 months of flooding were designed, and an un-flooded one coded CK at a relatively higher elevation was set as a control. Before flooding occurred in 1998, the slope had an almost uniform soil and L. chinensis dominated vegetation. Each transect was 0.2 hm2 (100 m x 20 m) in size, and the two flooded transects were almost paralleled each other, with the longer sides of them perpendicular to the retrieving direction of floodwater. In each transect twenty 1 m2 sized quadrats were randomly chosen to survey the community structure and the aboveground biomass. Comparative analyses were made on the dynamics of soil water, soil N and P, and species composition of grassland communities that occurred in responses to flooding disturbance. The results showed that the lightly and heavily flooded transects had a significantly larger aboveground biomass than the control, with the increase of 89.54% and 113.45%, respectively. The heavily flooded transect had a slightly but insignificantly larger aboveground biomass than the lightly flooded one, indicating that on flooded sites, water was not the limiting factor of the aboveground biomass. The acute changes of soil water caused by flooding led to the changes of soil nutrients and species assemblages, which would impact community biomass. Just as the case for aboveground biomass, the soil water contents of the two flooded transects were significantly larger than that of control

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

    Paul, Keryn I; Roxburgh, Stephen H; Chave, Jerome; England, Jacqueline R; Zerihun, Ayalsew; Specht, Alison; Lewis, Tom; Bennett, Lauren T; Baker, Thomas G; Adams, Mark A; Huxtable, Dan; Montagu, Kelvin D; Falster, Daniel S; Feller, Mike; Sochacki, Stan; Ritson, Peter; Bastin, Gary; Bartle, John; Wildy, Dan; Hobbs, Trevor; Larmour, John; Waterworth, Rob; Stewart, Hugh T L; Jonson, Justin; Forrester, David I; Applegate, Grahame; Mendham, Daniel; Bradford, Matt; O'Grady, Anthony; Green, Daryl; Sudmeyer, Rob; Rance, Stan J; Turner, John; Barton, Craig; Wenk, Elizabeth H; Grove, Tim; Attiwill, Peter M; Pinkard, Elizabeth; Butler, Don; Brooksbank, Kim; Spencer, Beren; Snowdon, Peter; O'Brien, Nick; Battaglia, Michael; Cameron, David M; Hamilton, Steve; McAuthur, Geoff; Sinclair, Jenny

    2016-06-01

    Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species

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

    PubMed

    Paul, Keryn I; Roxburgh, Stephen H; Chave, Jerome; England, Jacqueline R; Zerihun, Ayalsew; Specht, Alison; Lewis, Tom; Bennett, Lauren T; Baker, Thomas G; Adams, Mark A; Huxtable, Dan; Montagu, Kelvin D; Falster, Daniel S; Feller, Mike; Sochacki, Stan; Ritson, Peter; Bastin, Gary; Bartle, John; Wildy, Dan; Hobbs, Trevor; Larmour, John; Waterworth, Rob; Stewart, Hugh T L; Jonson, Justin; Forrester, David I; Applegate, Grahame; Mendham, Daniel; Bradford, Matt; O'Grady, Anthony; Green, Daryl; Sudmeyer, Rob; Rance, Stan J; Turner, John; Barton, Craig; Wenk, Elizabeth H; Grove, Tim; Attiwill, Peter M; Pinkard, Elizabeth; Butler, Don; Brooksbank, Kim; Spencer, Beren; Snowdon, Peter; O'Brien, Nick; Battaglia, Michael; Cameron, David M; Hamilton, Steve; McAuthur, Geoff; Sinclair, Jenny

    2016-06-01

    Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species

  9. Biomass Estimation of Dry Tropical Woody Species at Juvenile Stage

    PubMed Central

    Chaturvedi, R. K.; Raghubanshi, A. S.; Singh, J. S.

    2012-01-01

    Accurate characterization of biomass in different forest components is important to estimate their contribution to total carbon stock. Due to lack of allometric equations for biomass estimation of woody species at juvenile stage, the carbon stored in this forest component is ignored. We harvested 47 woody species at juvenile stage in a dry tropical forest and developed regression models for the estimation of above-ground biomass (AGB). The models including wood-specific gravity (ρ) exhibited higher R2 than those without ρ. The model consisting of ρ, stem diameter (D), and height (H) not only exhibited the highest R2 value but also had the lowest standard error of estimate. We suggest that ρ-based regression model is a viable option for nondestructive estimation of biomass of forest trees at juvenile stage. PMID:22448139

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

    NASA Astrophysics Data System (ADS)

    Becker, Joscha; Gütlein, Adrian; Sierra Cornejo, Natalia; Kiese, Ralf; Hertel, Dietrich; Kuzyakov, Yakov

    2015-04-01

    The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation in this area consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. Canopy structure is known to affect microclimate, throughfall and evapotranspiration and thereby controls soil moisture conditions. Consequently, the canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine trends and changes of soil parameters and relate their spatial variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. Distances were calculated in relation to the crown radius. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass carbon C and N, soil respiration as well as root biomass and -density, soil temperature and soil water content. Each tree was characterized by crown spread, leaf area index and basal area. Preliminary results show that C and N stocks decreased about 50% with depth independently of distance to the tree. Soil water content under the tree crown increased with depth while it decreased under grass cover. Microbial

  11. Landscape and forest structural controls on wood density and aboveground biomass along a tropical elevation gradient in Costa Rica

    NASA Astrophysics Data System (ADS)

    Robinson, C. M.; Saatchi, S. S.; Clark, D. B.; Gillespie, T. W.; Andelman, S.

    2014-12-01

    This research seeks to understand how tree wood density and taxonomic diversity relate to topography and three-dimensional vegetation structure in the tropical montane forest of Braulio Carrillo National Park in Costa Rica. The study utilized forest inventory and botanical data from twenty 1-ha plots ranging from 55 m to 2800 m above sea level and remote sensing data from an airborne lidar sensor (NASA's Land, Vegetation, and Ice Sensor [LVIS]) to quantify variations in forest structure. There is growing evidence that ecosystem structure plays an important role in defining patterns of species diversity and help to control the phenotypic and functional variations across landscapes. Elevation gradients along mountains provide landscape-size scales through which variations in topography, climate, and edaphic conditions as drivers of biodiversity can be tested. In this study we report on the effectiveness of relating patterns of tree wood density and alpha diversity to three-dimensional structure of a tropical montane forest using remote sensing observations of forest structure. Wood density is an important parameter for aboveground biomass and carbon estimations. Tree cores were analyzed for wood density and compared to existing database values for the same species. In this manner we were able to test the effect of the gradient on wood density and on the subsequent aboveground biomass estimations. Understanding these patterns has implications for conservation of both ecosystem services and biodiversity. Our results indicate that there is a strong relationship between LVIS-derived forest 3D-structure and alpha diversity, likely controlled controlled by variations in abiotic factors and topography along the elevation. Using spatial analysis with the aid of remote sensing data, we found distinct patterns along the environmental gradients defining species composition and forest structure. Wood density values were found to vary significantly from database values for the

  12. Carbon dynamics in aboveground biomass of co-dominant plant species: related rather to leaf life span than to species

    NASA Astrophysics Data System (ADS)

    Ostler, Ulrike; Schleip, Inga; Lattanzi, Fernando A.; Schnyder, Hans

    2016-04-01

    This study investigates the role of individual organisms in whole ecosystem carbon (C) fluxes. It is currently unknown if different plant community members share the same or different kinetics of C pools in aboveground biomass, thereby adding (or not) variability to the first steps in ecosystem C cycling. We assessed the residence times in metabolic and non-metabolic (or structural) C pools and the allocation pattern of assimilated C in aboveground plant parts of four co-existing, co-dominant species from different functional groups in a temperate grassland community. For this purpose continuous, 14-16 day long 13CO2/12CO2-labeling experiments were performed in Sept. 2006, May 2007 and Sept. 2007, and the tracer kinetics were analysed with compartmental modeling. In all experimental periods, the species shared vastly similar residence times in metabolic C (5-8 d). In contrast, the residence times in non-metabolic C ranged from 20 to 58 d (except one outlier) and the fraction of fixed C allocated to the non-metabolic pool from 7 to 45%. These variations in non-metabolic C kinetics were not systematically associated with species or experimental periods, but exhibited close relationships with (independent estimates of) leaf life span, particularly in the grasses. This adds new meaning to leaf life span as a functional trait in the leaf and plant economics spectrum and its implication for C cycle studies in grassland and also forest systems. As the four co-dominant species accounted for ~80% of total community shoot biomass, we should also expect that the observed similarities in pool kinetics and allocation will scale up to similar relationships at the community level.

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

    NASA Astrophysics Data System (ADS)

    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

  14. The estimation of microbial biomass.

    PubMed

    Harris, C M; Kell, D B

    1985-01-01

    Methods that have been used to estimate the content, and in some cases the nature, of the microbial biomass in a sample are reviewed. The methods may be categorised in terms of their principle (physical, chemical, biological or mathematical/computational), their speed (real-time or otherwise) and the amount of automation/expense involved. For sparse populations, where the output signal is to be enhanced by growth of the organisms, physical, chemical and biological approaches may be of equal merit, whilst in systems, such as laboratory and industrial fermentations, in which the microbial biomass content is high, physical methods (alone) can permit the real-time estimation of microbial biomass.

  15. Aboveground biomass and leaf area index (LAI) mapping for Niassa Reserve, northern Mozambique

    NASA Astrophysics Data System (ADS)

    Ribeiro, Natasha S.; Saatchi, Sassan S.; Shugart, Herman H.; Washington-Allen, Robert A.

    2008-09-01

    Estimations of biomass are critical in miombo woodlands because they represent the primary source of goods and services for over 80% of the population in southern Africa. This study was carried out in Niassa Reserve, northern Mozambique. The main objectives were first to estimate woody biomass and Leaf Area Index (LAI) using remotely sensed data [RADARSAT (C-band, λ = 5.7-cm)] and Landsat ETM+ derived Normalized Difference Vegetation Index (NDVI) and Simple Ratio (SR) calibrated by field measurements and, second to determine, at both landscape and plot scales, the environmental controls (precipitation, woody cover density, fire and elephants) of biomass and LAI. A land-cover map (72% overall accuracy) was derived from the June 2004 ETM+ mosaic. Field biomass and LAI were correlated with RADARSAT backscatter (rbiomass = 0.65, rLAI = 0.57, p < 0.0001) from July 2004, NDVI (rbiomass = 0.30, rLAI = 0.35; p < 0.0001) and SR (rbiomass = 0.36, rLAI = 0.40, p < 0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 + 0.074 * radarsat + 1.56 * SR, r2 = 0.55) and LAI (LAI = -0.66 + 0.01 * radarsat + 0.22 * SR, r2 = 0.45). Biomass and LAI maps were produced with an estimated peak of 18 kg m-2 and 2.80 m2 m-2, respectively. On the landscape-scale, both biomass and LAI were strongly determined by mean annual precipitation (F = 13.91, p = 0.0002). On the plot spatial scale, woody biomass was significantly determined by fire frequency, and LAI by vegetation type.

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

    NASA Astrophysics Data System (ADS)

    Safari, A.; Sohrabi, H.

    2016-06-01

    The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics

  17. Wildfires in Bamboo-Dominated Amazonian Forest: Impacts on Above-Ground Biomass and Biodiversity

    PubMed Central

    Barlow, Jos; Silveira, Juliana M.; Mestre, Luiz A. M.; Andrade, Rafael B.; Camacho D'Andrea, Gabriela; Louzada, Julio; Vaz-de-Mello, Fernando Z.; Numata, Izaya; Lacau, Sébastien; Cochrane, Mark A.

    2012-01-01

    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. PMID:22428035

  18. Relationships between functional diversity and aboveground biomass production in the Northern Tibetan alpine grasslands

    PubMed Central

    Zhu, Juntao; Jiang, Lin; Zhang, Yangjian

    2016-01-01

    Functional diversity, the extent of functional differences among species in a community, drives biodiversity–ecosystem function (BEF) relationships. Here, four species traits and aboveground biomass production (ABP) were considered. We used two community-wide measures of plant functional composition, (1) community weighted means of trait values (CWM) and (2) functional trait diversity based on Rao’s quadratic diversity (FDQ) to evaluate the effects of functional diversity on the ABP in the Northern Tibetan alpine grasslands. Both species and functional diversity were positively related to the ABP. Functional trait composition had a larger predictive power for the ABP than species diversity and FDQ, indicating a primary dependence of ecosystem property on the identity of dominant species in our study system. Multivariate functional diversity was ineffective in predicting ecosystem function due to the trade-offs among different traits or traits selection criterions. Our study contributes to a better understanding of the mechanisms driving the BEF relationships in stressed ecosystems, and especially emphasizes that abiotic and biotic factors affect the BEF relationships in alpine grasslands. PMID:27666532

  19. Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity.

    PubMed

    Barlow, Jos; Silveira, Juliana M; Mestre, Luiz A M; Andrade, Rafael B; Camacho D'Andrea, Gabriela; Louzada, Julio; Vaz-de-Mello, Fernando Z; Numata, Izaya; Lacau, Sébastien; Cochrane, Mark A

    2012-01-01

    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.

  20. Comment on 'A first map of tropical Africa's above-ground biomass derived from satellite imagery'

    NASA Astrophysics Data System (ADS)

    Mitchard, E. T. A.; Saatchi, S. S.; Lewis, S. L.; Feldpausch, T. R.; Gerard, F. F.; Woodhouse, I. H.; Meir, P.

    2011-10-01

    We present a critical evaluation of the above-ground biomass (AGB) map of Africa published in this journal by Baccini et al (2008 Environ. Res. Lett. 3 045011). We first test their map against an independent dataset of 1154 scientific inventory plots from 16 African countries, and find only weak correspondence between our field plots and the AGB value given for the surrounding 1 km pixel by Baccini et al. Separating our field data using a continental landcover classification suggests that the Baccini et al map underestimates the AGB of forests and woodlands, while overestimating the AGB of savannas and grasslands. Secondly, we compare their map to 216 000 × 0.25 ha spaceborne LiDAR footprints. A comparison between Lorey's height (basal-area-weighted average height) derived from the LiDAR data for 1 km pixels containing at least five LiDAR footprints again does not support the hypothesis that the Baccini et al map is accurate, and suggests that it significantly underestimates the AGB of higher AGB areas. We conclude that this is due to the unsuitability of some of the field data used by Baccini et al to create their map, and overfitting in their model, resulting in low accuracies outside the small areas from which their field data are drawn.

  1. Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity.

    PubMed

    Barlow, Jos; Silveira, Juliana M; Mestre, Luiz A M; Andrade, Rafael B; Camacho D'Andrea, Gabriela; Louzada, Julio; Vaz-de-Mello, Fernando Z; Numata, Izaya; Lacau, Sébastien; Cochrane, Mark A

    2012-01-01

    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. PMID:22428035

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

    NASA Astrophysics Data System (ADS)

    Jubanski, J.; Ballhorn, U.; Kronseder, K.; Franke, J.; Siegert, F.

    2013-06-01

    Quantification of tropical forest above-ground biomass (AGB) over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+) projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia) through correlating airborne light detection and ranging (LiDAR) to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52). Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC) showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG) emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

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

    PubMed Central

    Lou, Yanjing; Pan, Yanwen; Gao, Chuanyu; Jiang, Ming; Lu, Xianguo; Xu, Y. Jun

    2016-01-01

    Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region. PMID:27097325

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

    PubMed

    Lou, Yanjing; Pan, Yanwen; Gao, Chuanyu; Jiang, Ming; Lu, Xianguo; Xu, Y Jun

    2016-01-01

    Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region. PMID:27097325

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

    PubMed

    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.

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

    PubMed

    Lou, Yanjing; Pan, Yanwen; Gao, Chuanyu; Jiang, Ming; Lu, Xianguo; Xu, Y Jun

    2016-01-01

    Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region.

  7. Progress in the remote sensing of C3 and C4 grass species aboveground biomass over time and space

    NASA Astrophysics Data System (ADS)

    Shoko, Cletah; Mutanga, Onisimo; Dube, Timothy

    2016-10-01

    The remote sensing of grass aboveground biomass (AGB) has gained considerable attention, with substantial research being conducted in the past decades. Of significant importance is their photosynthetic pathways (C3 and C4), which epitomizes a fundamental eco-physiological distinction of grasses functional types. With advances in technology and the availability of remotely sensed data at different spatial, spectral, radiometric and temporal resolutions, coupled with the need for detailed information on vegetation condition, the monitoring of C3 and C4 grasses AGB has received renewed attention, especially in the light of global climate change, biodiversity and, most importantly, food security. This paper provides a detailed survey on the progress of remote sensing application in determining C3 and C4 grass species AGB. Importantly, the importance of species functional type is highlighted in conjunction with the availability and applicability of different remote sensing datasets, with refined resolutions, which provide an opportunity to monitor C3 and C4 grasses AGB. While some progress has been made, this review has revealed the need for further remote sensing studies to model the seasonal (cyclical) variability, as well as long-term AGB changes in C3 and C4 grasses, in the face of climate change and food security. Moreover, the findings of this study have shown the significance of shifting towards the application of advanced statistical models, to further improve C3 and C4 grasses AGB estimation accuracy.

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

    NASA Astrophysics Data System (ADS)

    Viers, J. H.

    2013-12-01

    Integrating citizen scientists into ecological informatics research can be difficult due to limited opportunities for meaningful engagement given vast data streams. This is particularly true for analysis of remotely sensed data, which are increasingly being used to quantify ecosystem services over space and time, and to understand how land uses deliver differing values to humans and thus inform choices about future human actions. Carbon storage and sequestration are such ecosystem services, and recent environmental policy advances in California (i.e., AB 32) have resulted in a nascent carbon market that is helping fuel the restoration of riparian forests in agricultural landscapes. Methods to inventory and monitor aboveground carbon for market accounting are increasingly relying on hyperspatial remotely sensed data, particularly the use of light detection and ranging (LiDAR) technologies, to estimate biomass. Because airborne discrete return LiDAR can inexpensively capture vegetation structural differences at high spatial resolution (< 1 m) over large areas (> 1000 ha), its use is rapidly increasing, resulting in vast stores of point cloud and derived surface raster data. While established algorithms can quantify forest canopy structure efficiently, the highly complex nature of native riparian forests can result in highly uncertain estimates of biomass due to differences in composition (e.g., species richness, age class) and structure (e.g., stem density). This study presents the comparative results of standing carbon estimates refined with field data collected by citizen scientists at three different sites, each capturing a range of agricultural, remnant forest, and restored forest cover types. These citizen science data resolve uncertainty in composition and structure, and improve allometric scaling models of biomass and thus estimates of aboveground carbon. Results indicate that agricultural land and horticulturally restored riparian forests store similar

  9. [Effects of China future land use change on aboveground vegetation biomass].

    PubMed

    Sun, Xiao-Fang; Yue, Tian-Xiang

    2012-08-01

    Land use change has significant effects on vegetation biomass via altering ecosystem structure. By adopting a spatially explicit land use change model, this paper simulated the spatiotemporal pattern of land use change in China till 2030, based on the historical scenario (in this scenario, the land use trend in 1988-2005 was extrapolated to obtain the area of each land use type in the future) and the planned scenario (in this scenario, the area of each land use type in the future was based on the national scale land use planning). On the basis of this simulation and using a biomass density approach, the spatial pattern of vegetation biomass change in China was estimated. The simulation showed that under the historical scenario, the forest area would be decreased but the forest age would be in adverse, and accordingly, the forest biomass density would have an increase. Till 2030, the overall vegetation biomass in China would be 14619 Tg, with an increase of 251.19 Tg as compared to the situation in 2005. Under the planned scenario, the forest area would be increased, and the overall vegetation biomass in 2030 would be 15468 Tg, with an increase of 1100 Tg as compared to the situation in 2005. In the planned scenario, the planted forest area would be larger while the forest age would be younger, resulting in a much lower vegetation biomass density in 2030 than that in the historical scenario, and thus, the China's vegetation in the planned scenario would have a higher potential to act as a carbon sink.

  10. [Aboveground biomass input of Myristicaceae tree species in the Amazonian Forest in Peru].

    PubMed

    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. PMID:26299130

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

    SciTech Connect

    Brown, S.; Gaston, G.; Daniels, R.C.

    1996-06-01

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

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

    NASA Technical Reports Server (NTRS)

    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.

  13. Grazing effects on aboveground primary production and root biomass of early-seral, mid-seral, and undisturbed semiarid grassland

    USGS Publications Warehouse

    Milchunas, D.G.; Vandever, M.W.

    2013-01-01

    Annual/perennial and tall/short plant species differentially dominate early to late successional shortgrass steppe communities. Plant species can have different ratios of above-/below-ground biomass distributions and this can be modified by precipitation and grazing. We compared grazing effects on aboveground production and root biomass in early- and mid-seral fields and undisturbed shortgrass steppe. Production averaged across four years and grazed and ungrazed treatments were 246, 134, and 102 g m−2 yr−1 for the early-, mid-seral, and native sites, respectively, while root biomass averaged 358, 560, and 981 g m−2, respectively. Early- and mid-seral communities provided complimentary forage supplies but at the cost of root biomass. Grazing increased, decreased, or had no effect on aboveground production in early-, mid-seral, and native communities, and had no effect on roots in any. Grazing had some negative effects on early spring forage species, but not in the annual dominated early-seral community. Dominant species increased with grazing in native communities with a long evolutionary history of grazing by large herbivores, but had no effects on the same species in mid-seral communities. Effects of grazing in native communities in a region cannot necessarily be used to predict effects at other seral stages.

  14. Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa

    NASA Astrophysics Data System (ADS)

    Dube, Timothy; Mutanga, Onisimo

    2015-03-01

    Aboveground biomass estimation is critical in understanding forest contribution to regional carbon cycles. Despite the successful application of high spatial and spectral resolution sensors in aboveground biomass (AGB) estimation, there are challenges related to high acquisition costs, small area coverage, multicollinearity and limited availability. These challenges hamper the successful regional scale AGB quantification. The aim of this study was to assess the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying AGB in a forest plantation. We applied different sets of spectral analysis (test I: spectral bands; test II: spectral vegetation indices and test III: spectral bands + spectral vegetation indices) in testing the utility of Landsat 8 OLI using two non-parametric algorithms: stochastic gradient boosting and the random forest ensembles. The results of the study show that the medium-resolution multispectral Landsat 8 OLI dataset provides better AGB estimates for Eucalyptus dunii, Eucalyptus grandis and Pinus taeda especially when using the extracted spectral information together with the derived spectral vegetation indices. We also noted that incorporating the optimal subset of the most important selected medium-resolution multispectral Landsat 8 OLI bands improved AGB accuracies. We compared medium-resolution multispectral Landsat 8 OLI AGB estimates with Landsat 7 ETM + estimates and the latter yielded lower estimation accuracies. Overall, this study demonstrates the invaluable potential and strength of applying the relatively affordable and readily available newly-launched medium-resolution Landsat 8 OLI dataset, with a large swath width (185-km) in precisely estimating AGB. This strength of the Landsat OLI dataset is crucial especially in sub-Saharan Africa where high-resolution remote sensing data availability remains a challenge.

  15. From grass to forest biomass: uncertainty estimates with lidar remote sensing (Invited)

    NASA Astrophysics Data System (ADS)

    Popescu, S. C.; Zhao, K.; Feagin, R. A.; Gatziolis, D.; Sheridan, R.; Srinivasan, S.; Ku, N.; Kulawardhana, R. W.

    2013-12-01

    Lidar remote sensing from three platforms - ground, airborne, and spaceborne - has the capability to acquire direct three-dimensional measurements of the vegetation canopy that are useful for estimating biophysical characteristics, including biomass. Each platform provides data over different spatial scales and enables biomass and carbon estimates with different levels of uncertainty. The overall goal of this presentation is to discuss error sources involved in biomass estimation with lidar remote sensing, with terrestrial, airborne, and satellite sensors, with examples of studies of coastal vegetation grasses, brush, and forests. Specific objectives will focus on the accuracy of estimating vegetation dimensions, such as height and crown widths, allometrics used to derive biomass, regression models for biomass estimation, and comparison between methods and sensors. In our studies, ICESat height variables were able to explain 80% of the variance associated with the reference forest biomass derived from airborne lidar, with an RMSE of 37.7 Mg/ha. For salt marshes, the combination of airborne lidar and multispectral variables explained 47% of the biomass variance, whereas the best models using lidar and multi-spectral data separately explained 37% and 28% of variances in live biomass measurements respectively. Terrestrial lidar was able to explain up to 81% of the variance associated with the aboveground biomass of rangeland woody plants in a semi-arid environment in Texas. With airborne lidar and a scale-invariant approach, previous work suggests that regression models can accurately predict biomass and yield consistent predictive performances across a variety of scales ranging from 80% to 95% biomass variance explained, with RMSE values from 14. 3 Mg/ha to 33.7 Mg/ha among regression models. The results of these studies demonstrate the ability of using lidar remote sensing on multiple platforms for assessing aboveground biomass and the uncertainty of estimates and

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

    NASA Technical Reports Server (NTRS)

    Nelson, Ross

    2008-01-01

    ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.

  17. [Optimized Spectral Indices Based Estimation of Forage Grass Biomass].

    PubMed

    An, Hai-bo; Li, Fei; Zhao, Meng-li; Liu, Ya-jun

    2015-11-01

    As an important indicator of forage production, aboveground biomass will directly illustrate the growth of forage grass. Therefore, Real-time monitoring biomass of forage grass play a crucial role in performing suitable grazing and management in artificial and natural grassland. However, traditional sampling and measuring are time-consuming and labor-intensive. Recently, development of hyperspectral remote sensing provides the feasibility in timely and nondestructive deriving biomass of forage grass. In the present study, the main objectives were to explore the robustness of published and optimized spectral indices in estimating biomass of forage grass in natural and artificial pasture. The natural pasture with four grazing density (control, light grazing, moderate grazing and high grazing) was designed in desert steppe, and different forage cultivars with different N rate were conducted in artificial forage fields in Inner Mongolia. The canopy reflectance and biomass in each plot were measured during critical stages. The result showed that, due to the influence in canopy structure and biomass, the canopy reflectance have a great difference in different type of forage grass. The best performing spectral index varied in different species of forage grass with different treatments (R² = 0.00-0.69). The predictive ability of spectral indices decreased under low biomass of desert steppe, while red band based spectral indices lost sensitivity under moderate-high biomass of forage maize. When band combinations of simple ratio and normalized difference spectral indices were optimized in combined datasets of natural and artificial grassland, optimized spectral indices significant increased predictive ability and the model between biomass and optimized spectral indices had the highest R² (R² = 0.72) compared to published spectral indices. Sensitive analysis further confirmed that the optimized index had the lowest noise equivalent and were the best performing index in

  18. [Optimized Spectral Indices Based Estimation of Forage Grass Biomass].

    PubMed

    An, Hai-bo; Li, Fei; Zhao, Meng-li; Liu, Ya-jun

    2015-11-01

    As an important indicator of forage production, aboveground biomass will directly illustrate the growth of forage grass. Therefore, Real-time monitoring biomass of forage grass play a crucial role in performing suitable grazing and management in artificial and natural grassland. However, traditional sampling and measuring are time-consuming and labor-intensive. Recently, development of hyperspectral remote sensing provides the feasibility in timely and nondestructive deriving biomass of forage grass. In the present study, the main objectives were to explore the robustness of published and optimized spectral indices in estimating biomass of forage grass in natural and artificial pasture. The natural pasture with four grazing density (control, light grazing, moderate grazing and high grazing) was designed in desert steppe, and different forage cultivars with different N rate were conducted in artificial forage fields in Inner Mongolia. The canopy reflectance and biomass in each plot were measured during critical stages. The result showed that, due to the influence in canopy structure and biomass, the canopy reflectance have a great difference in different type of forage grass. The best performing spectral index varied in different species of forage grass with different treatments (R² = 0.00-0.69). The predictive ability of spectral indices decreased under low biomass of desert steppe, while red band based spectral indices lost sensitivity under moderate-high biomass of forage maize. When band combinations of simple ratio and normalized difference spectral indices were optimized in combined datasets of natural and artificial grassland, optimized spectral indices significant increased predictive ability and the model between biomass and optimized spectral indices had the highest R² (R² = 0.72) compared to published spectral indices. Sensitive analysis further confirmed that the optimized index had the lowest noise equivalent and were the best performing index in

  19. Carbon dynamics in aboveground biomass of co-dominant plant species in a temperate grassland ecosystem: same or different?

    PubMed

    Ostler, Ulrike; Schleip, Inga; Lattanzi, Fernando A; Schnyder, Hans

    2016-04-01

    Understanding the role of individual organisms in whole-ecosystem carbon (C) fluxes is probably the biggest current challenge in C cycle research. Thus, it is unknown whether different plant community members share the same or different residence times in metabolic (τmetab ) and nonmetabolic (i.e. structural) (τnonmetab ) C pools of aboveground biomass and the fraction of fixed C allocated to aboveground nonmetabolic biomass (Anonmetab ). We assessed τmetab , τnonmetab and Anonmetab of co-dominant species from different functional groups (two bunchgrasses, a stoloniferous legume and a rosette dicot) in a temperate grassland community. Continuous, 14-16-d-long (13) C-labeling experiments were performed in September 2006, May 2007 and September 2007. A two-pool compartmental system, with a well-mixed metabolic and a nonmixed nonmetabolic pool, was the simplest biologically meaningful model that fitted the (13) C tracer kinetics in the whole-shoot biomass of all species. In all experimental periods, the species had similar τmetab (5-8 d), whereas τnonmetab ranged from 20 to 58 d (except for one outlier) and Anonmetab from 7 to 45%. Variations in τnonmetab and Anonmetab were not systematically associated with species or experimental periods, but exhibited relationships with leaf life span, particularly in the grasses. Similar pool kinetics of species suggested similar kinetics at the community level.

  20. The response of tundra plant biomass, above-ground production, nitrogen, and CO{sub 2} flux to experimental warming

    SciTech Connect

    Hobbie, S.E.; Chapin, F.S. III

    1998-07-01

    The authors manipulated air temperature in tussock tundra near Toolik Lake, Alaska, and determined the consequences for total plant biomass, aboveground net primary production (ANPP), ecosystem nitrogen (N) pools and N uptake, and ecosystem CO{sub 2} flux. After 3.5 growing seasons, in situ plastic greenhouses that raised air temperature during the growing season had little effect on total biomass, N content, or growing-season N uptake of the major plant and soil pools. Similarly, vascular ANPP and net ecosystem CO{sub 2} exchange did not change with warming, although net primary production of mosses decreased with warming. Such general lack of response supports the hypothesis that productivity in tundra is constrained by the indirect effects of cold temperatures rather than by cold growing-season temperatures per se. Despite no effect on net ecosystem CO{sub 2} flux, air warming stimulated early-season gross photosynthesis (GP) and ecosystem respiration (ER) throughout the growing season. This increased carbon turnover was probably associated with species-level responses to increased air temperature. Warming increased the aboveground biomass of the overstory shrub, dwarf birch (Betula nana), and caused a significant net redistribution of N from the understory evergreen shrub, Vaccinium vitis-idaea, to B. nana, despite no effects on soil temperature, total plant N, or N availability.

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

    NASA Technical Reports Server (NTRS)

    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.

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

    NASA Astrophysics Data System (ADS)

    Hadley, Brian Christopher

    This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.

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

    NASA Astrophysics Data System (ADS)

    Tyukavina, A.; Stehman, S. V.; Potapov, P. V.; Turubanova, S. A.; Baccini, A.; Goetz, S. J.; Laporte, N. T.; Houghton, R. A.; Hansen, M. C.

    2013-12-01

    Recent advances in remote sensing enable the mapping and monitoring of carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where national forest inventories (NFI) are either non-existent or out of date. Here we demonstrate a method for estimating national-scale gross forest aboveground carbon (AGC) loss and associated uncertainties using remotely sensed-derived forest cover loss and biomass carbon density data. Lidar data were used as a surrogate for NFI plot measurements to estimate carbon stocks and AGC loss based on forest type and activity data derived using time-series multispectral imagery. Specifically, DRC forest type and loss from the FACET (Forêts d’Afrique Centrale Evaluées par Télédétection) product, created using Landsat data, were related to carbon data derived from the Geoscience Laser Altimeter System (GLAS). Validation data for FACET forest area loss were created at a 30-m spatial resolution and compared to the 60-m spatial resolution FACET map. We produced two gross AGC loss estimates for the DRC for the last decade (2000-2010): a map-scale estimate (53.3 ± 9.8 Tg C yr-1) accounting for whole-pixel classification errors in the 60-m resolution FACET forest cover change product, and a sub-grid estimate (72.1 ± 12.7 Tg C yr-1) that took into account 60-m cells that experienced partial forest loss. Our sub-grid forest cover and AGC loss estimates, which included smaller-scale forest disturbances, exceed published assessments. Results raise the issue of scale in forest cover change mapping and validation, and subsequent impacts on remotely sensed carbon stock change estimation, particularly for smallholder dominated systems such as the DRC.

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

    PubMed

    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.

  5. Evaluation of non-destructive methods for estimating biomass in marshes of the upper Texas, USA coast

    USGS Publications Warehouse

    Whitbeck, M.; Grace, J.B.

    2006-01-01

    The estimation of aboveground biomass is important in the management of natural resources. Direct measurements by clipping, drying, and weighing of herbaceous vegetation are time-consuming and costly. Therefore, non-destructive methods for efficiently and accurately estimating biomass are of interest. We compared two non-destructive methods, visual obstruction and light penetration, for estimating aboveground biomass in marshes of the upper Texas, USA coast. Visual obstruction was estimated using the Robel pole method, which primarily measures the density and height of the canopy. Light penetration through the canopy was measured using a Decagon light wand, with readings taken above the vegetation and at the ground surface. Clip plots were also taken to provide direct estimates of total aboveground biomass. Regression relationships between estimated and clipped biomass were significant using both methods. However, the light penetration method was much more strongly correlated with clipped biomass under these conditions (R2 value 0.65 compared to 0.35 for the visual obstruction approach). The primary difference between the two methods in this situation was the ability of the light-penetration method to account for variations in plant litter. These results indicate that light-penetration measurements may be better for estimating biomass in marshes when plant litter is an important component. We advise that, in all cases, investigators should calibrate their methods against clip plots to evaluate applicability to their situation. ?? 2006, The Society of Wetland Scientists.

  6. Estimates of US biomass energy consumption 1992

    SciTech Connect

    Not Available

    1994-05-06

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

  7. Error propagation and scaling for tropical forest biomass estimates.

    PubMed Central

    Chave, Jerome; Condit, Richard; Aguilar, Salomon; Hernandez, Andres; Lao, Suzanne; Perez, Rolando

    2004-01-01

    The above-ground biomass (AGB) of tropical forests is a crucial variable for ecologists, biogeochemists, foresters and policymakers. Tree inventories are an efficient way of assessing forest carbon stocks and emissions to the atmosphere during deforestation. To make correct inferences about long-term changes in biomass stocks, it is essential to know the uncertainty associated with AGB estimates, yet this uncertainty is rarely evaluated carefully. Here, we quantify four types of uncertainty that could lead to statistical error in AGB estimates: (i) error due to tree measurement; (ii) error due to the choice of an allometric model relating AGB to other tree dimensions; (iii) sampling uncertainty, related to the size of the study plot; (iv) representativeness of a network of small plots across a vast forest landscape. In previous studies, these sources of error were reported but rarely integrated into a consistent framework. We estimate all four terms in a 50 hectare (ha, where 1 ha = 10(4) m2) plot on Barro Colorado Island, Panama, and in a network of 1 ha plots scattered across central Panama. We find that the most important source of error is currently related to the choice of the allometric model. More work should be devoted to improving the predictive power of allometric models for biomass. PMID:15212093

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

    PubMed

    Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom

    2015-07-01

    Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved

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

    PubMed

    Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom

    2015-07-01

    Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved

  10. Estimating phytoplankton biomass and productivity. Final report

    SciTech Connect

    Janik, J.J.; Taylor, W.D.; Lambou, V.W.

    1981-06-01

    Estimates of phytoplankton biomass and rates of production can provide a manager with some insight into questions concerning trophic state, water quality, and aesthetics. Methods for estimation of phytoplankton biomass include a gravimetric approach, microscopic enumeration, and chlorophyll analysis, Strengths and weaknesses of these and other methods are presented. Productivity estimation techniques are discussed including oxygen measurement, carbon dioxide measurements, carbon 14 measurements, and the chlorophyll method. Again, strengths and weaknesses are presented.

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

    NASA Astrophysics Data System (ADS)

    Saatchi, S. S.; Schimel, D.; Keller, M. M.; Chambers, J. Q.; Dubayah, R.; Duffy, P.; Yu, Y.; Robinson, C. M.; Chowdhury, D.; Yang, Y.

    2013-12-01

    AUTHOR: Sassan Saatchi1,2, Yan Yang2, Diya Chowdhury2, Yifan Yu2, Chelsea Robinson2, David Schimel1, Paul Duffy3, Michael Keller4, Ralph Dubayah5, Jeffery Chambers6 1. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA USA 2. Institute of Environment and Sustainability, University of California, Los Angeles, CA, USA 3. Neptune and Company, Inc. Denver, CO, USA 4. International Institute of Tropical Forestry & International Programs, USDA Forest Service, Campinas, Brazil 5. Department of Geography, University of Maryland, College Park, MD, USA 6. Department of Geography, University of California, Berkeley, CA, USA ABSTRACT BODY: In recent years, climate change policies and scientific research created a widespread interest in quantify the carbon stock and changes of global tropical forests extending from forest patches to national and regional scales. Using a combination of inventory data from field plots and forest structure from spaceborne Lidar data, we examine the main controls on the distribution of tropical forest biomass. Here, we concentrate on environmental and landscape variables (precipitation, temperature, topography, and soil), and biotic variables such as functional traits (density of large trees, and wood specific gravity). The analysis is performed using global bioclimatic variables for precipitation and temperature, SRTM data for topographical variables (elevation and ruggedness), and global harmonized soil data for soil type and texture. For biotic variables, we use the GLAS Lidar data to quantify the distribution of large trees, a combined field and remote sensing data for distribution of tree wood specific gravity. The results show that climate variables such as precipitation of dry season can explain the heterogeneity of forest biomass over the landscape but cannot predict the biomass variability significantly and particularly for high biomass forests. Topography such as elevation and ruggedness along with temperature can

  12. Response of aboveground biomass and diversity to nitrogen addition along a degradation gradient in the Inner Mongolian steppe, China

    PubMed Central

    Xu, Xiaotian; Liu, Hongyan; Song, Zhaoliang; Wang, Wei; Hu, Guozheng; Qi, Zhaohuan

    2015-01-01

    Although nitrogen addition and recovery from degradation can both promote production of grassland biomass, these two factors have rarely been investigated in combination. In this study, we established a field experiment with six N-treatment (CK, 10, 20, 30, 40, 50 g N m−2 yr−1) on five fields with different degradation levels in the Inner Mongolian steppe of China from 2011–2013. Our observations showed that while the external nitrogen increased the aboveground biomass in all five grasslands, the magnitude of the effects differed with the severity of degradation. Fields with a higher level of degradation tended to have a higher saturation value (20 g N m−2 yr−1) than those with a lower degradation level ( < 10 g N m−2 yr−1). After three years of experimentation, species richness showed little change across degradation levels. Among the four functional groups of grasses, sedges, forbs and legumes, grasses shared the most similar response patterns with those of the whole community, demonstrating the predominant role that they play in the restoration of grassland under a stimulus of nitrogen addition. PMID:26194184

  13. Recovery of aboveground plant biomass and productivity after fire in mesic and dry black spruce forests of interior Alaska

    USGS Publications Warehouse

    Mack, M.C.; Treseder, K.K.; Manies, K.L.; Harden, J.W.; Schuur, E.A.G.; Vogel, J.G.; Randerson, J.T.; Chapin, F. S.

    2008-01-01

    Plant biomass accumulation and productivity are important determinants of ecosystem carbon (C) balance during post-fire succession. In boreal black spruce (Picea mariana) forests near Delta Junction, Alaska, we quantified aboveground plant biomass and net primary productivity (ANPP) for 4 years after a 1999 wildfire in a well-drained (dry) site, and also across a dry and a moderately well-drained (mesic) chronosequence of sites that varied in time since fire (2 to ???116 years). Four years after fire, total biomass at the 1999 burn site had increased exponentially to 160 ?? 21 g m-2 (mean ?? 1SE) and vascular ANPP had recovered to 138 ?? 32 g m-2 y -1, which was not different than that of a nearby unburned stand (160 ?? 48 g m-2 y-1) that had similar pre-fire stand structure and understory composition. Production in the young site was dominated by re-sprouting graminoids, whereas production in the unburned site was dominated by black spruce. On the dry and mesic chronosequences, total biomass pools, including overstory and understory vascular and non-vascular plants, and lichens, increased logarithmically (dry) or linearly (mesic) with increasing site age, reaching a maximum of 2469 ?? 180 (dry) and 4008 ?? 233 g m-2 (mesic) in mature stands. Biomass differences were primarily due to higher tree density in the mesic sites because mass per tree was similar between sites. ANPP of vascular and non-vascular plants increased linearly over time in the mesic chronosequence to 335 ?? 68 g m-2 y -1 in the mature site, but in the dry chronosequence it peaked at 410 ?? 43 g m-2 y-1 in a 15-year-old stand dominated by deciduous trees and shrubs. Key factors regulating biomass accumulation and production in these ecosystems appear to be the abundance and composition of re-sprouting species early in succession, the abundance of deciduous trees and shrubs in intermediate aged stands, and the density of black spruce across all stand ages. A better understanding of the controls

  14. Predicting tree heights for biomass estimates in tropical forests

    NASA Astrophysics Data System (ADS)

    Molto, Q.; Hérault, B.; Boreux, J.-J.; Daullet, M.; Rousteau, A.; Rossi, V.

    2013-05-01

    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 this. We found that

  15. Lasting effects of climate disturbance on perennial grassland above-ground biomass production under two cutting frequencies.

    PubMed

    Zwicke, Marine; Alessio, Giorgio A; Thiery, Lionel; Falcimagne, Robert; Baumont, René; Rossignol, Nicolas; Soussana, Jean-François; Picon-Cochard, Catherine

    2013-11-01

    Climate extremes can ultimately reshape grassland services such as forage production and change plant functional type composition. This 3-year field research studied resistance to dehydration and recovery after rehydration of plant community and plant functional types in an upland perennial grassland subjected to climate and cutting frequency (Cut+, Cut-) disturbances by measuring green tissue percentage and above-ground biomass production (ANPP). In year 1, a climate disturbance gradient was applied by co-manipulating temperature and precipitation. Four treatments were considered: control and warming-drought climatic treatment, with or without extreme summer event. In year 2, control and warming-drought treatments were maintained without extreme. In year 3, all treatments received ambient climatic conditions. We found that the grassland community was very sensitive to dehydration during the summer extreme: aerial senescence reached 80% when cumulated climatic water balance fell to -156 mm and biomass declined by 78% at the end of summer. In autumn, canopy greenness and biomass totally recovered in control but not in the warming-drought treatment. However ANPP decreased under both climatic treatments, but the effect was stronger on Cut+ (-24%) than Cut- (-15%). This decline was not compensated by the presence of three functional types because they were negatively affected by the climatic treatments, suggesting an absence of buffering effect on grassland production. In the following 2 years, lasting effects of climate disturbance on ANPP were observable. The unexpected stressful conditions of year 3 induced a decline in grassland production in the Cut+ control treatment. The fact that this treatment cumulated higher (45%) N export over the 3 years suggests that N plays a key role in ANPP stability. As ANPP in this mesic perennial grassland did not show engineering resilience, long-term experimental manipulation is needed. Infrequent mowing appears more

  16. Lasting effects of climate disturbance on perennial grassland above-ground biomass production under two cutting frequencies.

    PubMed

    Zwicke, Marine; Alessio, Giorgio A; Thiery, Lionel; Falcimagne, Robert; Baumont, René; Rossignol, Nicolas; Soussana, Jean-François; Picon-Cochard, Catherine

    2013-11-01

    Climate extremes can ultimately reshape grassland services such as forage production and change plant functional type composition. This 3-year field research studied resistance to dehydration and recovery after rehydration of plant community and plant functional types in an upland perennial grassland subjected to climate and cutting frequency (Cut+, Cut-) disturbances by measuring green tissue percentage and above-ground biomass production (ANPP). In year 1, a climate disturbance gradient was applied by co-manipulating temperature and precipitation. Four treatments were considered: control and warming-drought climatic treatment, with or without extreme summer event. In year 2, control and warming-drought treatments were maintained without extreme. In year 3, all treatments received ambient climatic conditions. We found that the grassland community was very sensitive to dehydration during the summer extreme: aerial senescence reached 80% when cumulated climatic water balance fell to -156 mm and biomass declined by 78% at the end of summer. In autumn, canopy greenness and biomass totally recovered in control but not in the warming-drought treatment. However ANPP decreased under both climatic treatments, but the effect was stronger on Cut+ (-24%) than Cut- (-15%). This decline was not compensated by the presence of three functional types because they were negatively affected by the climatic treatments, suggesting an absence of buffering effect on grassland production. In the following 2 years, lasting effects of climate disturbance on ANPP were observable. The unexpected stressful conditions of year 3 induced a decline in grassland production in the Cut+ control treatment. The fact that this treatment cumulated higher (45%) N export over the 3 years suggests that N plays a key role in ANPP stability. As ANPP in this mesic perennial grassland did not show engineering resilience, long-term experimental manipulation is needed. Infrequent mowing appears more

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

    PubMed

    Schnabel, William; Munk, Jens; Byrd, Amanda

    2015-01-01

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

  18. Pathways of Leymus chinensis Individual Aboveground Biomass Decline in Natural Semiarid Grassland Induced by Overgrazing: A Study at the Plant Functional Trait Scale

    PubMed Central

    Wang, Zhen; Wu, Xinhong; Li, Xinle; Hu, Jing; Shi, Hongxiao; Guo, Fenghui; Zhang, Yong; Hou, Xiangyang

    2015-01-01

    Natural grassland productivity, which is based on an individual plant’s aboveground biomass (AB) and its interaction with herbivores, can obviously affect terrestrial ecosystem services and the grassland’s agricultural production. As plant traits have been linked to both AB and ecosystem success, they may provide a useful approach to understand the changes in individual plants and grassland productivity in response to grazing on a generic level. Unfortunately, the current lack of studies on how plant traits affect AB affected by herbivores leaves a major gap in our understanding of the mechanism of grassland productivity decline. This study, therefore, aims to analyze the paths of overgrazing-induced decline in the individual AB of Leymus chinensis (the dominant species of meadow-steppe grassland in northern China) on a plant functional trait scale. Using a paired-sampling approach, we compared the differences in the functional traits of L. chinensis in long-term grazing-excluded and experimental grazing grassland plots over a continuous period of approximately 20 years (located in meadow steppe lands in Hailar, Inner Mongolia, China). We found a highly significant decline in the individual height and biomass (leaf, stem, and the whole plant) of L. chinensis as a result of overgrazing. Biomass allocation and leaf mass per unit area were significantly affected by the variation in individual size. Grazing clearly enhanced the sensitivity of the leaf-to-stem biomass ratio in response to variation in individual size. Moreover, using a method of standardized major axis estimation, we found that the biomass in the leaves, stems, and the plant as a whole had highly significant allometric scaling with various functional traits. Also, the slopes of the allometric equations of these relationships were significantly altered by grazing. Therefore, a clear implication of this is that grazing promotes an asymmetrical response of different plant functional traits to variation

  19. Pathways of Leymus chinensis Individual Aboveground Biomass Decline in Natural Semiarid Grassland Induced by Overgrazing: A Study at the Plant Functional Trait Scale.

    PubMed

    Li, Xiliang; Liu, Zhiying; Wang, Zhen; Wu, Xinhong; Li, Xinle; Hu, Jing; Shi, Hongxiao; Guo, Fenghui; Zhang, Yong; Hou, Xiangyang

    2015-01-01

    Natural grassland productivity, which is based on an individual plant's aboveground biomass (AB) and its interaction with herbivores, can obviously affect terrestrial ecosystem services and the grassland's agricultural production. As plant traits have been linked to both AB and ecosystem success, they may provide a useful approach to understand the changes in individual plants and grassland productivity in response to grazing on a generic level. Unfortunately, the current lack of studies on how plant traits affect AB affected by herbivores leaves a major gap in our understanding of the mechanism of grassland productivity decline. This study, therefore, aims to analyze the paths of overgrazing-induced decline in the individual AB of Leymus chinensis (the dominant species of meadow-steppe grassland in northern China) on a plant functional trait scale. Using a paired-sampling approach, we compared the differences in the functional traits of L. chinensis in long-term grazing-excluded and experimental grazing grassland plots over a continuous period of approximately 20 years (located in meadow steppe lands in Hailar, Inner Mongolia, China). We found a highly significant decline in the individual height and biomass (leaf, stem, and the whole plant) of L. chinensis as a result of overgrazing. Biomass allocation and leaf mass per unit area were significantly affected by the variation in individual size. Grazing clearly enhanced the sensitivity of the leaf-to-stem biomass ratio in response to variation in individual size. Moreover, using a method of standardized major axis estimation, we found that the biomass in the leaves, stems, and the plant as a whole had highly significant allometric scaling with various functional traits. Also, the slopes of the allometric equations of these relationships were significantly altered by grazing. Therefore, a clear implication of this is that grazing promotes an asymmetrical response of different plant functional traits to variation in

  20. Linking Carbon Fluxes with Remotely-Sensed Vegetation Indices for Leaf Area and Aboveground Biomass Through Footprint Climatology

    NASA Astrophysics Data System (ADS)

    Wayson, C.; Clark, K.; Hollinger, D. Y.; Skowronski, N.; Schmid, H. E.

    2010-12-01

    A major challenge of bottom-up scaling is that in-situ flux observations are spatially limited. Thus, to achieve valid regional exchange rates, models are used to interpolate and extrapolate to the vegetational/spatial domain covered by these observations. To parameterize these models from flux data, efforts must be made to select data that best represents the region being modeled as well as linking the fluxes to remotely-sensed data products that can be produced from site to regional scales. Because most long-term flux stations are not in spatially extensive, homogeneous locations, this requirement is often a challenge. However, this requirement can be met by selecting observation periods whose flux footprints are statistically representative of the type of ecosystem identified in the model. The flux footprint function indicates the time-varying surface “field-of-view” (or spatial sampling window) of an eddy-flux sensor, oriented mostly in upwind direction. For each observation period, the modeled flux footprint window is overlain with a high-resolution vegetation index map to determine a footprint-weighted vegetation index for which the observation is representative. Using flux-footprint analysis to link fluxes to models using just an enhanced vegetation index (EVI) map shows a positive trend between EVI and eddy covariance measured fluxes, but the link is not strong. Leaf area is linked with carbon (C) uptake, but forests tend to maximize leaf area, as determined through remote sensing, early on with forests having similar leaf areas across a wide range of ages. Adding another remotely-sensed dataset, aboveground biomass map (AGB), helps capture the processes of lower productivity rates (as biomass increases per unit of leaf area there is a decline, due to the forest ageing) and the C losses due to respiration, both heterotrophic and autotrophic (linked to live and detrital biomass pools). Adding biomass from LIDAR and a combined EVI-biomass layer to examine

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

    PubMed

    Schuster, W S F; Griffin, K L; Roth, H; Turnbull, M H; Whitehead, D; Tissue, D T

    2008-04-01

    We sought to quantify changes in tree species composition, forest structure and aboveground forest biomass (AGB) over 76 years (1930-2006) in the deciduous Black Rock Forest in southeastern New York, USA. We used data from periodic forest inventories, published floras and a set of eight long-term plots, along with species-specific allometric equations to estimate AGB and carbon content. Between the early 1930s and 2000, three species were extirpated from the forest (American elm (Ulmus americana L.), paper birch (Betula papyrifera Marsh.) and black spruce (Picea mariana (nigra) (Mill.) BSP)) and seven species invaded the forest (non-natives tree-of-heaven (Ailanthus altissima (Mill.) Swingle) and white poplar (Populus alba L.) and native, generally southerly distributed, southern catalpa (Catalpa bignonioides Walt.), cockspur hawthorn (Crataegus crus-galli L.), red mulberry (Morus rubra L.), eastern cottonwood (Populus deltoides Bartr.) and slippery elm (Ulmus rubra Muhl.)). Forest canopy was dominated by red oak and chestnut oak, but the understory tree community changed substantially from mixed oak-maple to red maple-black birch. Density decreased from an average of 1500 to 735 trees ha(-1), whereas basal area doubled from less than 15 m(2) ha(-1) to almost 30 m(2) ha(-1) by 2000. Forest-wide mean AGB from inventory data increased from about 71 Mg ha(-1) in 1930 to about 145 Mg ha(-1) in 1985, and mean AGB on the long-term plots increased from 75 Mg ha(-1) in 1936 to 218 Mg ha(-1) in 1998. Over 76 years, red oak (Quercus rubra L.) canopy trees stored carbon at about twice the rate of similar-sized canopy trees of other species. However, there has been a significant loss of live tree biomass as a result of canopy tree mortality since 1999. Important constraints on long-term biomass increment have included insect outbreaks and droughts.

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

    NASA Technical Reports Server (NTRS)

    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.

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

    PubMed

    Wang, Qiang; Yuan, Xingzhong; Willison, J H Martin; Zhang, Yuewei; Liu, Hong

    2014-01-01

    Hydrological alternation can dramatically influence riparian environments and shape riparian vegetation zonation. However, it was difficult to predict the status in the drawdown area of the Three Gorges Reservoir (TGR), because the hydrological regime created by the dam involves both short periods of summer flooding and long-term winter impoundment for half a year. In order to examine the effects of hydrological alternation on plant diversity and biomass in the drawdown area of TGR, twelve sites distributed along the length of the drawdown area of TGR were chosen to explore the lateral pattern of plant diversity and above-ground biomass at the ends of growing seasons in 2009 and 2010. We recorded 175 vascular plant species in 2009 and 127 in 2010, indicating that a significant loss of vascular flora in the drawdown area of TGR resulted from the new hydrological regimes. Cynodon dactylon and Cyperus rotundus had high tolerance to short periods of summer flooding and long-term winter flooding. Almost half of the remnant species were annuals. Species richness, Shannon-Wiener Index and above-ground biomass of vegetation exhibited an increasing pattern along the elevation gradient, being greater at higher elevations subjected to lower submergence stress. Plant diversity, above-ground biomass and species distribution were significantly influenced by the duration of submergence relative to elevation in both summer and previous winter. Several million tonnes of vegetation would be accumulated on the drawdown area of TGR in every summer and some adverse environmental problems may be introduced when it was submerged in winter. We conclude that vascular flora biodiversity in the drawdown area of TGR has dramatically declined after the impoundment to full capacity. The new hydrological condition, characterized by long-term winter flooding and short periods of summer flooding, determined vegetation biodiversity and above-ground biomass patterns along the elevation gradient in

  4. Diversity and Above-Ground Biomass Patterns of Vascular Flora Induced by Flooding in the Drawdown Area of China's Three Gorges Reservoir

    PubMed Central

    Wang, Qiang; Yuan, Xingzhong; Willison, J.H.Martin; Zhang, Yuewei; Liu, Hong

    2014-01-01

    Hydrological alternation can dramatically influence riparian environments and shape riparian vegetation zonation. However, it was difficult to predict the status in the drawdown area of the Three Gorges Reservoir (TGR), because the hydrological regime created by the dam involves both short periods of summer flooding and long-term winter impoundment for half a year. In order to examine the effects of hydrological alternation on plant diversity and biomass in the drawdown area of TGR, twelve sites distributed along the length of the drawdown area of TGR were chosen to explore the lateral pattern of plant diversity and above-ground biomass at the ends of growing seasons in 2009 and 2010. We recorded 175 vascular plant species in 2009 and 127 in 2010, indicating that a significant loss of vascular flora in the drawdown area of TGR resulted from the new hydrological regimes. Cynodon dactylon and Cyperus rotundus had high tolerance to short periods of summer flooding and long-term winter flooding. Almost half of the remnant species were annuals. Species richness, Shannon-Wiener Index and above-ground biomass of vegetation exhibited an increasing pattern along the elevation gradient, being greater at higher elevations subjected to lower submergence stress. Plant diversity, above-ground biomass and species distribution were significantly influenced by the duration of submergence relative to elevation in both summer and previous winter. Several million tonnes of vegetation would be accumulated on the drawdown area of TGR in every summer and some adverse environmental problems may be introduced when it was submerged in winter. We conclude that vascular flora biodiversity in the drawdown area of TGR has dramatically declined after the impoundment to full capacity. The new hydrological condition, characterized by long-term winter flooding and short periods of summer flooding, determined vegetation biodiversity and above-ground biomass patterns along the elevation gradient in

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

    PubMed

    Wang, Qiang; Yuan, Xingzhong; Willison, J H Martin; Zhang, Yuewei; Liu, Hong

    2014-01-01

    Hydrological alternation can dramatically influence riparian environments and shape riparian vegetation zonation. However, it was difficult to predict the status in the drawdown area of the Three Gorges Reservoir (TGR), because the hydrological regime created by the dam involves both short periods of summer flooding and long-term winter impoundment for half a year. In order to examine the effects of hydrological alternation on plant diversity and biomass in the drawdown area of TGR, twelve sites distributed along the length of the drawdown area of TGR were chosen to explore the lateral pattern of plant diversity and above-ground biomass at the ends of growing seasons in 2009 and 2010. We recorded 175 vascular plant species in 2009 and 127 in 2010, indicating that a significant loss of vascular flora in the drawdown area of TGR resulted from the new hydrological regimes. Cynodon dactylon and Cyperus rotundus had high tolerance to short periods of summer flooding and long-term winter flooding. Almost half of the remnant species were annuals. Species richness, Shannon-Wiener Index and above-ground biomass of vegetation exhibited an increasing pattern along the elevation gradient, being greater at higher elevations subjected to lower submergence stress. Plant diversity, above-ground biomass and species distribution were significantly influenced by the duration of submergence relative to elevation in both summer and previous winter. Several million tonnes of vegetation would be accumulated on the drawdown area of TGR in every summer and some adverse environmental problems may be introduced when it was submerged in winter. We conclude that vascular flora biodiversity in the drawdown area of TGR has dramatically declined after the impoundment to full capacity. The new hydrological condition, characterized by long-term winter flooding and short periods of summer flooding, determined vegetation biodiversity and above-ground biomass patterns along the elevation gradient in

  6. Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Santos, João. R.; Silva, Camila V. d. J.; Galvão, Lênio S.; Treuhaft, Robert; Mura, José C.; Madsen, Soren; Gonçalves, Fábio G.; Keller, Michael M.

    2014-08-01

    Secondary succession is an important process in the Amazonian region with implications for the global carbon cycle and for the sustainable regional agricultural and pasture activities. In order to better discriminate the secondary succession and to characterize and estimate the aboveground biomass (AGB), backscatter and interferometric SAR data generally have been analyzed through empirical-based statistical modeling. The objective of this study is to verify the capability of the full polarimetric PALSAR/ALOS (L-band) attributes, when combined with the interferometric (InSAR) coherence from the TanDEM-X (X-band), to improve the AGB estimates of the succession chronosequence located in the Brazilian Tapajós region. In order to perform this study, we carried out multivariate regression using radar attributes and biophysical parameters acquired during a field inventory. A previous floristic-structural analysis was performed to establish the chronosequence in three stages: initial vegetation regrowth, intermediate, and advanced regrowth. The relationship between PALSAR data and AGB was significant (p<0.001) and results suggested that the "volumetric scattering" (Pv) and "anisotropy" (A) attributes were important to explain the biomass content of the successional chronosequence (R2adjusted = 0.67; RMSE = 32.29 Mg.ha-1). By adding the TanDEM-derived interferometric coherence (Υi) into the regression modeling, better results were obtained (R2adjusted = 0.75; RMSE = 28.78Mg.ha-1). When we used both the L- and X-band attributes, the stock density prediction improved to 10.8 % for the secondary succession stands.

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Tropical Africa: Land Use, Biomass, and Carbon Estimates for 1980 (NDP-055)

    SciTech Connect

    Brown, S.

    2002-04-16

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980. The biomass data and carbon estimates are associated with woody vegetation in Tropical Africa. These data were collected to reduce the uncertainty associated with estimating historical releases of carbon from land use change. Tropical Africa is defined here as encompassing 22.7 x 10{sup 6} km{sup 2} of the earth's land surface and is comprised of countries that are located in tropical Africa (Angola, Botswana, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Congo, Benin, Equatorial Guinea, Ethiopia, Djibouti, Gabon, Gambia, Ghana, Guinea, Ivory Coast, Kenya, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Nigeria, Guinea-Bissau, Zimbabwe (Rhodesia), Rwanda, Senegal, Sierra Leone, Somalia, Sudan, Tanzania, Togo, Uganda, Burkina Faso (Upper Volta), Zaire, and Zambia). The database was developed using the GRID module in the ARC/INFO{trademark} geographic information system. Source data were obtained from the Food and Agriculture Organization (FAO), the U.S. National Geophysical Data Center, and a limited number of biomass-carbon density case studies. These data were used to derive the maximum potential and actual (ca. 1980) aboveground biomass values at regional and country levels. The land-use data provided were derived from a vegetation map originally produced for the FAO by the International Institute of Vegetation Mapping, Toulouse, France.

  10. The importance of crown dimensions to improve tropical tree biomass estimates.

    PubMed

    Goodman, Rosa C; Phillips, Oliver L; Baker, Timothy R

    2014-06-01

    Tropical forests play a vital role in the global carbon cycle, but the amount of carbon they contain and its spatial distribution remain uncertain. Recent studies suggest that once tree height is accounted for in biomass calculations, in addition to diameter and wood density, carbon stock estimates are reduced in many areas. However, it is possible that larger crown sizes might offset the reduction in biomass estimates in some forests where tree heights are lower because even comparatively short trees develop large, well-lit crowns in or above the forest canopy. While current allometric models and theory focus on diameter, wood density, and height, the influence of crown size and structure has not been well studied. To test the extent to which accounting for crown parameters can improve biomass estimates, we harvested and weighed 51 trees (11-169 cm diameter) in southwestern Amazonia where no direct biomass measurements have been made. The trees in our study had nearly half of total aboveground biomass in the branches (44% +/- 2% [mean +/- SE]), demonstrating the importance of accounting for tree crowns. Consistent with our predictions, key pantropical equations that include height, but do not account for crown dimensions, underestimated the sum total biomass of all 51 trees by 11% to 14%, primarily due to substantial underestimates of many of the largest trees. In our models, including crown radius greatly improves performance and reduces error, especially for the largest trees. In addition, over the full data set, crown radius explained more variation in aboveground biomass (10.5%) than height (6.0%). Crown form is also important: Trees with a monopodial architectural type are estimated to have 21-44% less mass than trees with other growth patterns. Our analysis suggests that accounting for crown allometry would substantially improve the accuracy of tropical estimates of tree biomass and its distribution in primary and degraded forests.

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

    PubMed

    Ercanli, İlker; Kahriman, Aydın

    2015-03-01

    We assessed the effect of stand structural diversity, including the Shannon, improved Shannon, Simpson, McIntosh, Margelef, and Berger-Parker indices, on stand aboveground biomass (AGB) and developed statistical prediction models for the stand AGB values, including stand structural diversity indices and some stand attributes. The AGB prediction model, including only stand attributes, accounted for 85 % of the total variance in AGB (R (2)) with an Akaike's information criterion (AIC) of 807.2407, Bayesian information criterion (BIC) of 809.5397, Schwarz Bayesian criterion (SBC) of 818.0426, and root mean square error (RMSE) of 38.529 Mg. After inclusion of the stand structural diversity into the model structure, considerable improvement was observed in statistical accuracy, including 97.5 % of the total variance in AGB, with an AIC of 614.1819, BIC of 617.1242, SBC of 633.0853, and RMSE of 15.8153 Mg. The predictive fitting results indicate that some indices describing the stand structural diversity can be employed as significant independent variables to predict the AGB production of the Scotch pine stand. Further, including the stand diversity indices in the AGB prediction model with the stand attributes provided important predictive contributions in estimating the total variance in AGB.

  12. Spectral procedures for estimating crop biomass

    SciTech Connect

    Wanjura, D.F.; Hatfield, J.L.

    1985-05-01

    Spectral reflectance was measured semi-weekly and used to estimate leaf area and plant dry weight accumulation in cotton, soybeans, and sunflower. Integration of spectral crop growth cycle curves explained up to 95 and 91%, respectively, of the variation in cotton lint yield and dry weight. A theoretical relationship for dry weight accumulation, in which only intercepted radiation or intercepted radiation and solar energy to biomass conversion efficiency were spectrally estimated, explained 99 and 96%, respectively, of the observed plant dry weight variation of the three crops. These results demonstrate the feasibility of predicting crop biomass from spectral measurements collected frequently during the growing season. 15 references.

  13. Rangeland biomass estimation demonstration. [Texas Experimenta Ranch

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator); Boyd, W. E.; Clark, B. V.

    1982-01-01

    Because of their sensitivity to chlorophyll density, green leaf density, and leaf water density, two hand-held radiometers which have sensor bands coinciding with thematic mapper bands 3, 4, and 5 were used to calibrate green biomass to LANDSAT spectral ratios as a step towards using portable radiometers to speed up ground data acquisition. Two field reflectance panels monitored incoming radiation concurrently with sampling. Software routines were developed and used to extract data from uncorrected tapes of MSS data provided in NASA LANDSAT universal format. A LANDSAT biomass calibration curve estimated the range biomass over a four scene area and displayed this information spatially as a product in a format of use to ranchers. The regional biomass contour map is discussed.

  14. [Influence of nitrogen and phosphorus addition on the aboveground biomass in Inner Mongo- lia temperate steppe, China].

    PubMed

    He, Li-yuan; Hu, Zhong-min; Guo, Qun; Li, Sheng-gong; Bai, Wen-ming; Li, Ling-hao

    2015-08-01

    The plants in arid environment are constrained not only by water availability, but also by soil nutrient conditions. In order to clarify to what extent nutrient addition would facilitate the growth of plants in semi-arid region, we conducted a nitrogen (N) and phosphorus (P) addition experiment in Inner Mongolia temperate grassland in 2012 and 2013. In our experiment, N was added at 10 and 40 g N · m(-2) · a(-1) alone or in combination with P addition (10 g P · m(-2) · a(-1)). N addition significantly improved plant aboveground biomass (AGB) during the two study years. AGB in the treatments of 10 and 40 g · m2 · a(-1) was enhanced by 50.8% and 65.9% in 2012, and 71.6% and 93.3% in 2013, respectively. However, no significant difference in AGB enhancement was found between two N addition treatments. Compared with N addition treatments at the rates of 10 and 40 g · m(-2) · a(-1), N plus P addition improved AGB by 98.4% and 186.8% in 2012, and 111.7% and 141.4% in 2013, respectively. N addition generally increased all the three main functional types (i.e., Gramineae, Asteraceae and others) , and the three functional types contributed nearly equally to the increase of the community AGB. In comparison, Asteraceae contributed largest to the increments of AGB under the N plus P addition treatments. Our results also indicated that N and P addition remarkably increased the ground coverage, resulting in improved surface soil moisture condition, which might be one important reason that N and P addition could facilitate plant growth in arid environment.

  15. Estimation and Mapping of Coastal Mangrove Biomass Using Both Passive and Active Remote Sensing Method

    NASA Astrophysics Data System (ADS)

    Yiqiong, L.; Lu, W.; Zhou, J.; Gan, W.; Cui, X.; Lin, G., Sr.

    2015-12-01

    Mangrove forests play an important role in global carbon cycle, but carbon stocks in different mangrove forests are not easily measured at large scale. In this research, both active and passive remote sensing methods were used to estimate the aboveground biomass of dominant mangrove communities in Zhanjiang National Mangrove Nature Reserve in Guangdong, China. We set up a decision tree including spectral, texture, position and geometry indexes to achieve mangrove inter-species classification among 5 main species named Aegiceras corniculatum, Aricennia marina, Bruguiera gymnorrhiza, Kandelia candel, Sonneratia apetala by using 5.8m multispectral ZY-3 images. In addition, Lidar data were collected and used to obtain the canopy height of different mangrove species. Then, regression equations between the field measured aboveground biomass and the canopy height deduced from Lidar data were established for these mangrove species. By combining these results, we were able to establish a relatively accurate method for differentiating mangrove species and mapping their aboveground biomass distribution at the estuary scale, which could be applied to mangrove forests in other regions.

  16. Greening of the Arctic: Spatial and temporal (1982-2009) variation of circumpolar tundra NDVI and aboveground biomass

    NASA Astrophysics Data System (ADS)

    Walker, D. A.; Epstein, H. E.; Bhatt, U. S.; Raynolds, M. K.; Jia, G.; Comiso, J. C.; Pinzon, J.; Tucker, C. J.

    2010-12-01

    The Greening of the Arctic project examined the spatial and temporal variability of tundra productivity during field studies along two transects in North America and Russia and in circumpolar remote-sensing studies. Aboveground biomass of zonal vegetation was strongly correlated with summer air temperature along the North America transect (r2 > 0.8), but on the Yamal Peninsula, Russia, there was a nearly flat relationship with air temperature in the central part of the climate gradient. The more homogeneous nature of the Russian transect is caused by more consistent soil conditions, warmer than expected temperatures along the central part of the Russian transect, and the homogenizing effect of various landscape-scale disturbances including reindeer grazing and disturbances related to permafrost thawing. We examined the circumpolar spatial variability of the NDVI with respect to land temperatures and a suite of vegetation/terrain variables in a circumpolar geographic information system (GIS). Tests of sensitivity of NDVI to increases in summer temperature showed the largest percentage increases in NDVI will likely occur in northern partially-vegetated areas. A temporal analysis of maximum summer NDVI from 1982-2008 also indicated the ongoing changes have been strongest in the Far North. The percentage changes in the annual maximum NDVI were highest in the Baffin Bay, Beaufort Sea, Canadian Archipelago and Davis Strait areas (10-15% changes). The NDVI trends for most Arctic regions were highly positively correlated with the changes in summer land temperatures and negatively correlated with temporal changes in the near-shore early-summer sea-ice concentrations. Trends from these and several other lines of evidence point to a general increase in biomass across the Arctic during the period of satellite observations. The most rapid changes are occurring in the Far North. The impact of shrubification on these trends is probably greatest in the southern parts of the Arctic

  17. Non-Parametric Responses of Aboveground Biomass and NDVI to Land Surface Parameters in Arctic-Alpine Environments

    NASA Astrophysics Data System (ADS)

    Riihimäki, H. K.; Heiskanen, J.; Luoto, M.

    2015-12-01

    Aboveground biomass (AGB) is an important carbon pool and it affects various phenomena in Arctic and alpine areas, e.g. biodiversity, surface albedo and soil conditions. The growing availability of high-resolution digital elevation models (DEM) makes it possible to utilize topographical information for modeling local ground surface conditions globally. We investigated the effect of topography on field measured AGB (n = 359) and its commonly used proxy, the Normalized Difference Vegetation Index (NDVI) calculated from SPOT 5 imagery. The study area located in an Arctic-alpine treeline environment (69 °N, 21 °E). We performed the analyses with boosted regression trees method by using elevation and four land surface parameters (LSPs), derived from 10 m DEM, as predictors. The LSPs were namely Potential Incoming Solar Radiation (PISR, MJ m-2 a-1), Topographic Position Index (TPI, r = 300 m), Slope (angle in degrees) and Topographic Wetness Index (TWI). AGB varied from 0 to 5647 g m-2, while median AGB of the data was 449 g m-2. The explained deviance of the AGB and NDVI models were 53 % and 65 %, respectively. Elevation and PISR were the most important predictors. Their interaction was also significant in both cases as the highest AGB were at low-elevation, high-radiation sites, which implicates that PISR significantly improves the modelling of temperature related growing conditions. TWI had no clear effect to AGB nor to NDVI. TPI and Slope had a minor effect on AGB, but no effect to NDVI. Areas lower than their surroundings (negative TPI) had relatively high AGB. Furthermore, steeper slopes had higher AGB compared to flat sites. This is probably caused by the presence of mountain birch (Betula pubescens ssp. czerepanovii), which favors protected and steeper topography. Local topography is an important driver of the fine scale AGB patterns. Thus, DEM derived LSPs should be taken into account when modelling current and future biomass distributions in Arctic and alpine

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

    SciTech Connect

    French, Sean B; Christensen, Candace; Jennings, Terry L; Jaros, Christopher L; Wykoff, David S; Crowell, Kelly J; Shuman, Rob

    2008-01-01

    Low-level radioactive waste (LLW) generated at the Los Alamos National Laboratories (LANL) is disposed of at LANL's Technical Area (T A) 54, Material Disposal Area (MDA) G. The ability of MDA G to safely contain radioactive waste during current and post-closure operations is evaluated as part of the facility's ongoing performance assessment (PA) and composite analysis (CA). Due to the potential for uptake and incorporation of radio nuclides into aboveground plant material, the PA and CA project that plant roots penetrating into buried waste may lead to releases of radionuclides into the accessible environment. The potential amount ofcontamination deposited on the ground surface due to plant intrusion into buried waste is a function of the quantity of litter generated by plants, as well as radionuclide concentrations within the litter. Radionuclide concentrations in plant litter is dependent on the distribution of root mass with depth and the efficiency with which radionuclides are extracted from contaminated soils by the plant's roots. In order to reduce uncertainties associated with the PA and CA for MDA G, surveys are being conducted to assess aboveground biomass, plant litter production rates, and root mass with depth for the four prominent vegetation types (grasses, forbs, shrubs and trees). The collection of aboveground biomass for grasses and forbs began in 2007. Additional sampling was conducted in October 2008 to measure root mass with depth and to collect additional aboveground biomass data for the types of grasses, forbs, shrubs, and trees that may become established at MDA G after the facility undergoes final closure, Biomass data will be used to estimate the future potential mass of contaminated plant litter fall, which could act as a latent conduit for radionuclide transport from the closed disposal area. Data collected are expected to reduce uncertainties associated with the PA and CA for MDA G and ultimately aid in the assessment and subsequent

  19. Accurate Biomass Estimation via Bayesian Adaptive Sampling

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay

    2005-01-01

    The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.

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

    NASA Astrophysics Data System (ADS)

    El Masri, Bassil

    2011-12-01

    Modeling terrestrial ecosystem functions and structure has been a subject of increasing interest because of the importance of the terrestrial carbon cycle in global carbon budget and climate change. In this study, satellite data were used to estimate gross primary production (GPP), evapotranspiration (ET) for two deciduous forests: Morgan Monroe State forest (MMSF) in Indiana and Harvard forest in Massachusetts. Also, above-ground biomass (AGB) was estimated for the MMSF and the Howland forest (mixed forest) in Maine. Surface reflectance and temperature, vegetation indices, soil moisture, tree height and canopy area derived from the Moderate Resolution Imagining Spectroradiometer (MODIS), the Advanced Microwave Scanning Radiometer (AMRS-E), LIDAR, and aerial imagery respectively, were used for this purpose. These variables along with others derived from remotely sensed data were used as inputs variables to process-based models which estimated GPP and ET and to a regression model which estimated AGB. The process-based models were BIOME-BGC and the Penman-Monteith equation. Measured values for the carbon and water fluxes obtained from the Eddy covariance flux tower were compared to the modeled GPP and ET. The data driven methods produced good estimation of GPP and ET with an average root mean square error (RMSE) of 0.17 molC/m2 and 0.40 mm/day, respectively for the MMSF and the Harvard forest. In addition, allometric data for the MMSF were used to develop the regression model relating AGB with stem volume. The performance of the AGB regression model was compared to site measurements using remotely sensed data for the MMSF and the Howland forest where the model AGB RMSE ranged between 2.92--3.30 Kg C/m2. Sensitivity analysis revealed that improvement in maintenance respiration estimation and remotely sensed maximum photosynthetic activity as well as accurate estimate of canopy resistance will result in improved GPP and ET predictions. Moreover, AGB estimates were

  1. Remote sensing of submerged vegetation canopies for biomass estimation

    NASA Technical Reports Server (NTRS)

    Armstrong, Roy A.

    1993-01-01

    The visible bands of the Landsat Thematic Mapper (TM) sensor were used in an empirical assessment of seagrass biomass on shallow banks near Lee Stocking Island in the Bahamas. The TM bands were transformed to minimize the depth-dependent variance in the bottom reflectance signal. Regression analyses were performed between the transformed bands and field measurements of seagrass standing crop (above-ground biomass). Regression equations using spectral data accounted for up to 80 per cent of the variability in seagrass biomass. The unexplained variance was ascribed to variations in bottom sediment color.

  2. Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

    PubMed Central

    Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

    2015-01-01

    Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID

  3. Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome.

    PubMed

    Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

    2015-01-01

    Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.

  4. Sensitivity of Backscatter Intensity of ALOS/PALSAR to Above-ground Biomass and Other Biophysical Parameters of Boreal Forests in Alaska and Japan

    NASA Astrophysics Data System (ADS)

    Suzuki, R.; Hayashi, M.; Kim, Y.; Ishii, R.; Kobayashi, H.; Shoyama, K.; Adachi, M.; Takahashi, A.; Saigusa, N.; Ito, A.

    2012-12-01

    For the better understanding of the carbon cycle in the global environment, investigations on the spatio-temporal variation of the carbon stock which is stored as vegetation biomass is important. The backscatter intensity of "Phased Array type L-band Synthetic Aperture Radar (PALSAR)" onboard the satellite "Advanced Land Observing Satellite (ALOS)" provides us the information which is applicable to estimate the forest above-ground biomass (AGB). This study examines the sensitivity of the backscatter intensity of ALOS/PALSAR to the forest AGB and other biophysical parameters (tree height, tree diameter at breast height (DBH), and tree stand density) for boreal forests in two geographical regions of Alaska and Kushiro, northern Japan, and compares the sensitivities in two regions. In Alaska, a forest survey was executed in the south-north transect (about 300 km long) along a trans-Alaska pipeline which profiles the ecotone from the boreal forest to tundra in 2007. Forest AGBs and other biophysical parameters at 29 forests along the transect were measured by Bitterlich method. In Kushiro, a forest survey was carried out at 42 forests in 2011 and those parameters were similarly obtained by Bitterlich method. 20 and 2 scenes of ALOS/PALSAR FBD Level 1.5 data that cover the regions in Alaska and Kushiro, respectively, were collected and mosaicked. Backscatter intensities of ALOS/PALSAR in HH (horizontally polarized transmitted and horizontally polarized received) and HV (horizontally polarized transmitted and vertically polarized received) modes were compared with the forest AGB and other biophysical parameters. The intensity generally increased with the increase of those biophysical parameters in both HV and HH modes, but the intensity in HV mode generally had a stronger correlation to those parameters than in HH mode in both Alaska and Kushiro. The HV intensity had strong correlation to the forest AGB and DBH, while weak correlation to the tree stand density in Alaska

  5. Improved leaf area index based biomass estimations for Zostera marina L.

    PubMed

    Solana-Arellano, Elena; Echavarria-Heras, Hector; Gallegos Martinez, Margarita

    2003-12-01

    The application of special scanning technologies in plant population studies makes it now possible to offer reliable indirect estimations of Leaf Area Index (LAI). This has stimulated the adaptation of related biomass assessment methods and has provided a way to simplify tedious laboratory procedures whilst avoiding destructive sampling. Particularly, above-ground biomass for Zostera marina L. has been expressed depending linearly on Leaf Area Index. Nevertheless, we demonstrate that this approach produces biased estimations. It is also shown that expressing leaf dry weight by means of an allometric function of length and width can eliminate bias. Furthermore, the dominant term of the associated power series expansion becomes the aforementioned linear representation in terms of Leaf Area Index. The consistency of the estimation methods derived from the allometric model was tested using data from a Z. marina meadow. Consequently, the improved method is expected to become a valuable tool for the reduction of the uncertainty associated with the estimation of above-ground biomass through the use of Leaf Area Index.

  6. Estimating slash pine biomass using radar backscatter

    NASA Technical Reports Server (NTRS)

    Hussin, Yousif Ali; Reich, Robin M.; Hoffer, Roger M.

    1991-01-01

    L-band HV multiple-incidence-angle aircraft synthetic aperture radar (SAR) data were analyzed in relation to average stand biomass, basal area, and tree height for 55 slash pine plantations located in northern Florida. This information was used to develop a system of equations to predict average stand biomass as a function of L-band (24.5-cm) radar backscatter. The system of equations developed in this study using three-stage least-squares and combinatorial screening accounted for 97 percent of the variability observed in average stand biomass per hectare. When applied to an independent data set, the biomass equations had an average bias of less than 1 percent with a standard error of approximately 3 percent. These results indicate that future Shuttle Imaging Radar Systems (e.g., SIR-C, which will have cross-polarized radar sensors) should be able to obtain better estimates of forest biomass than were obtained with previous satellite radar missions, which utilized only HH-polarized SAR data.

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

    PubMed

    Kuznetsova, Tatjana; Tilk, Mari; Pärn, Henn; Lukjanova, Aljona; Mandre, Malle

    2011-12-01

    The investigation was carried out in 8-year-old Scots pine (Pinus sylvestris L.) and lodgepole pine (Pinus contorta var. latifolia Engelm.) plantations on post-mining area, Northeast Estonia. The aim of the study was to assess the suitability of lodgepole pine for restoration of degraded lands by comparing the growth, biomass, and nutrient concentration of studied species. The height growth of trees was greater in the Scots pine stand, but the tree aboveground biomass was slightly larger in the lodgepole pine stand. The aboveground biomass allocation to the compartments did not differ significantly between species. The vertical distribution of compartments showed that 43.2% of the Scots pine needles were located in the middle layer of the crown, while 58.5% of the lodgepole pine needles were in the lowest layer of the crown. The largest share of the shoots and stem of both species was allocated to the lowest layer of the crown. For both species, the highest NPK concentrations were found in the needles and the lowest in the stems. On the basis of the present study results, it can be concluded that the early growth of Scots pine and lodgepole pine on oil shale post-mining landscapes is similar. PMID:21374054

  8. Optimizing the number of training areas for modeling above-ground biomass with ALS and multispectral remote sensing in subtropical Nepal

    NASA Astrophysics Data System (ADS)

    Rana, Parvez; Gautam, Basanta; Tokola, Timo

    2016-07-01

    Remote sensing-based inventories of above-ground forest biomass (AGB) require a set of training plots representative of the area to be studied, the collection of which is the most expensive part of the analysis. These are time-consuming and costly because the large variety in forest conditions requires more plots to adequately capture this variability. A field campaign in general is challenging and is hampered by the complex topographic conditions, limited accessibility, steep mountainous terrains which increase labor efforts and costs. In addition it is also depend on the ratio between size of study area and number of training plots. In this study, we evaluate the number of training areas (sample size) required to estimate AGB for an area in the southern part of Nepal using airborne laser scanning (ALS), RapidEye and Landsat data. Three experiments were conducted: (i) AGB model performance, based on all the field training plots; (ii) reduction of the sample size, based on the ALS metrics and the AGB distribution; and (iii) prediction of the optimal number of training plots, based on the correlation between the remote sensing and field data. The AGB model was fitted using the sparse Bayesian method. AGB model performance was validated using an independent validation dataset. The effect of the strategies for reducing the sample size was readily apparent for the ALS-based AGB prediction, but the RapidEye and Landsat sensor data failed to capture any such effect. The results indicate that adequate coverage of the variability in tree height and density was an important condition for selecting the training plots. In addition, the ALS-based AGB prediction required the smallest number of training plots and was also quite stable with a small number of field plots.

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

    PubMed

    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. PMID:17763717

  10. Soil water content and patterns of allocation to below- and above-ground biomass in the sexes of the subdioecious plant Honckenya peploides

    PubMed Central

    Sánchez-Vilas, Julia; Bermúdez, Raimundo; Retuerto, Rubén

    2012-01-01

    Background and aims Dioecious plants often show sex-specific differences in growth and biomass allocation. These differences have been explained as a consequence of the different reproductive functions performed by the sexes. Empirical evidence strongly supports a greater reproductive investment in females. Sex differences in allocation may determine the performance of each sex in different habitats and therefore might explain the spatial segregation of the sexes described in many dimorphic plants. Here, an investigation was made of the sexual dimorphism in seasonal patterns of biomass allocation in the subdioecious perennial herb Honckenya peploides, a species that grows in embryo dunes (i.e. the youngest coastal dune formation) and displays spatial segregation of the sexes at the studied site. The water content in the soil of the male- and female-plant habitats at different times throughout the season was also examined. Methods The seasonal patterns of soil-water availability and biomass allocation were compared in two consecutive years in male and female H. peploides plants by collecting soil and plant samples in natural populations. Vertical profiles of below-ground biomass and water content were studied by sampling soil in male- and female-plant habitats at different soil depths. Key Results The sexes of H. peploides differed in their seasonal patterns of biomass allocation to reproduction. Males invested twice as much in reproduction than females early in the season, but sexual differences became reversed as the season progressed. No differences were found in above-ground biomass between the sexes, but the allocation of biomass to below-ground structures varied differently in depth for males and females, with females usually having greater below-ground biomass than males. In addition, male and female plants of H. peploides had different water-content profiles in the soil where they were growing and, when differences existed (usually in the upper layers of the

  11. Potential for radionuclide redistribution due to biotic intrusion: Aboveground biomass study at the Los Alamos National Laboratory for the closure of Material Disposal Area G

    SciTech Connect

    Beguin, K.; Pressler, R.E.; Christensen, C.; Anderson, T.; French, S.; Schuman, R.

    2008-07-01

    Low-level radioactive waste generated at the Los Alamos National Laboratories (LANL) is disposed of at Technical Area (TA) 54, Material Disposal Area (MDA) G. The ability of MDA G to safely contain radioactive waste was evaluated in the facility's performance assessment (PA) and composite analysis (CA). The PA and CA project that, due to uptake and incorporation of radionuclides into aboveground plant material, plant roots penetrating into buried waste may lead to releases of radionuclides to the accessible environment and potentially lead to the exposure to members of the public. The potential amount of contamination deposited on the ground surface, due to plant intrusion into buried waste, is a function of the quantity of litter generated by plants, as well as radionuclide concentrations within the litter. Radionuclide concentrations in plant litter is dependent on the distribution of root mass with depth and the efficiency with which radionuclides are extracted from contaminated soils by the plants roots. In order to reduce uncertainties associated with the PA and CA for MDA G, aboveground biomass surveys, plant litter production rates, and root mass with depth analyses for the four prominent vegetation types (grasses, forbs, shrubs and trees) are being conducted. Sampling occurred during the months of August and September of 2007 which measured aboveground biomass for the types of grasses and forbs that may become established at MDA G after the disposal facility undergoes final closure. Biomass data are representative of the future potential for the amount of contaminated plant litter fall, which could act as a latent conduit for radionuclide transport from the closed disposal area. Follow on work will be conducted to evaluate frequency and coverage of all growth forms, litter production rates will be measured, and root mass with depth for grasses, forbs, shrubs, and trees will be analyzed. Together, data collected are expected to reduce uncertainties

  12. Measuring bulrush culm relationships to estimate plant biomass within a southern California treatment wetland

    USGS Publications Warehouse

    Daniels, Joan S. (Thullen); Cade, Brian S.; Sartoris, James J.

    2010-01-01

    Assessment of emergent vegetation biomass can be time consuming and labor intensive. To establish a less onerous, yet accurate method, for determining emergent plant biomass than by direct measurements we collected vegetation data over a six-year period and modeled biomass using easily obtained variables: culm (stem) diameter, culm height and culm density. From 1998 through 2005, we collected emergent vegetation samples (Schoenoplectus californicus andSchoenoplectus acutus) at a constructed treatment wetland in San Jacinto, California during spring and fall. Various statistical models were run on the data to determine the strongest relationships. We found that the nonlinear relationship: CB=β0DHβ110ε, where CB was dry culm biomass (g m−2), DH was density of culms × average height of culms in a plot, and β0 and β1 were parameters to estimate, proved to be the best fit for predicting dried-live above-ground biomass of the two Schoenoplectus species. The random error distribution, ε, was either assumed to be normally distributed for mean regression estimates or assumed to be an unspecified continuous distribution for quantile regression estimates.

  13. Predicting tree heights for biomass estimates in tropical forests - a test from French Guiana

    NASA Astrophysics Data System (ADS)

    Molto, Q.; Hérault, B.; Boreux, J.-J.; Daullet, M.; Rousteau, A.; Rossi, V.

    2014-06-01

    The recent development of REDD+ mechanisms requires reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even though tree height is a crucial variable for computing aboveground forest biomass (AGB), it is rarely measured in large-scale forest censuses because it requires extra effort. Therefore, tree height has to be predicted with height models. The height and diameter of all trees over 10 cm in diameter were measured in 33 half-hectare plots and 9 one-hectare plots throughout 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 most appropriate for the tree biomass prediction. Model parameter values were significantly different from one forest plot to another, and this leads to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of plot-to-plot variations of the height model parameters to improve the quality of 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 aboveground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrated the feasibility and the importance of height modeling in tropical forests for carbon mapping. When the tree heights are not measured in an inventory, they can be predicted with a height-diameter model and incorporating forest structure descriptors may improve the predictions.

  14. Evaluating Post-fire Ecosystem Effects in Tussock Tundra of the Seward Peninsula: Characterizing Above-ground Biomass Accumulation, Soil Nutrient Pools, and Foliar Nitrogen.

    NASA Astrophysics Data System (ADS)

    Hollingsworth, T. N.; Mack, M. C.; Breen, A. L.

    2014-12-01

    Over the last century in the circumpolar north, changes in vegetation include shrub cover expansion and shifts in tree line. Invasion of tundra by trees and shrubs may be further facilitated by wildfire disturbance, which creates opportunities for establishment where recruitment is otherwise rare. Even moderate increases in warm-season temperatures are predicted to increase the likelihood of tundra fires. Understanding the consequences of a change in fire regime are complicated by the fact that there are relatively few large recent fires to study. However, the Seward Peninsula is a region that currently experiences more frequent and large fires than other tundra regions in Arctic Alaska. In this tundra region, there are areas of overlapping burns dating back to the 1970s. Using a chronosequence approach, we looked at post-fire biomass accumulation as well as foliar and soil C and N. Our experimental design incorporated sites that showed no evidence of recent burning, sites that burned in 1971, 1997, 2002, and 2011 as well as sites that burned multiple times over the last 30 years. We found that fire had a significant effect on total biomass and shrub basal area in tussock tundra. Our site that burned in 2011 had the lowest total biomass, about half of the biomass of our unburned site. However, our results indicated the site that burned in 1971 had over double the aboveground biomass and more soil N than the unburned site. We found that sites that repeatedly burned since 1971 were very similar in biomass to unburned tundra. This suggests that repeat fires keep a post-fire site at unburned levels of biomass. However, in these repeat fire sites, foliar C/N was ~25% greater and soil C and N was ~50% less than in unburned tundra. These results indicate that repeat fires are potentially causing nitrogen loss that not likely to be replenished into the system. As tundra fires become more frequent prediction of post-fire ecosystem effects is critical due to impacts on

  15. Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie-Ames-Stanford approach (CASA) model

    NASA Astrophysics Data System (ADS)

    Cao, S.; Sanchez-Azofeifa, GA; Duran, SM; Calvo-Rodriguez, S.

    2016-07-01

    Although tropical dry forests (TDFs) cover roughly 42% of all tropical ecosystems, extensive deforestation and habitat fragmentation pose important limitations for their conservation and restoration worldwide. In order to develop conservation policies for this endangered ecosystem, it is necessary to quantify their provision of ecosystems services such as carbon sequestration and primary production. In this paper we explore the potential of the Carnegie-Ames-Stanford approach (CASA) for estimating aboveground net primary productivity (ANPP) in a secondary TDF located at the Santa Rosa National Park (SRNP), Costa Rica. We calculated ANPP using the CASA model (ANPPCASA) in three successional stages (early, intermediate, and late). Each stage has a stand age of 21 years, 32 years, and 50+ years, respectively, estimated as the age since land abandonment. Our results showed that the ANPPCASA for early, intermediate, and late successional stages were 3.22 Mg C ha-1 yr-1, 8.90 Mg C ha-1 yr-1, and 7.59 Mg C ha-1 yr-1, respectively, which are comparable with rates of carbon uptake in other TDFs. Our results indicate that key variables that influence ANPP in our dry forest site were stand age and precipitation seasonality. Incident photosynthetically active radiation and temperature were not dominant in the ANPPCASA. The results of this study highlight the potential of the use of remote sensing techniques and the importance of incorporating successional stage in accurate regional TDF ANPP estimation.

  16. Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie–Ames–Stanford approach (CASA) model

    NASA Astrophysics Data System (ADS)

    Cao, S.; Sanchez-Azofeifa, GA; Duran, SM; Calvo-Rodriguez, S.

    2016-07-01

    Although tropical dry forests (TDFs) cover roughly 42% of all tropical ecosystems, extensive deforestation and habitat fragmentation pose important limitations for their conservation and restoration worldwide. In order to develop conservation policies for this endangered ecosystem, it is necessary to quantify their provision of ecosystems services such as carbon sequestration and primary production. In this paper we explore the potential of the Carnegie–Ames–Stanford approach (CASA) for estimating aboveground net primary productivity (ANPP) in a secondary TDF located at the Santa Rosa National Park (SRNP), Costa Rica. We calculated ANPP using the CASA model (ANPPCASA) in three successional stages (early, intermediate, and late). Each stage has a stand age of 21 years, 32 years, and 50+ years, respectively, estimated as the age since land abandonment. Our results showed that the ANPPCASA for early, intermediate, and late successional stages were 3.22 Mg C ha‑1 yr‑1, 8.90 Mg C ha‑1 yr‑1, and 7.59 Mg C ha‑1 yr‑1, respectively, which are comparable with rates of carbon uptake in other TDFs. Our results indicate that key variables that influence ANPP in our dry forest site were stand age and precipitation seasonality. Incident photosynthetically active radiation and temperature were not dominant in the ANPPCASA. The results of this study highlight the potential of the use of remote sensing techniques and the importance of incorporating successional stage in accurate regional TDF ANPP estimation.

  17. Correlating radar backscatter with components of biomass in loblolly pine forests

    NASA Astrophysics Data System (ADS)

    Kasischke, Eric S.; Christensen, Norman L., Jr.; Bourgeau-Chavez, Laura L.

    1995-05-01

    The relationship between radar backscatter and the aboveground biomass in loblolly pine forests was examined using a multifrequency, multipolarization airborne SAR data set. In addition, the potential of SAR to estimate aboveground biomass in these forests was also examined. The total aboveground biomass used in the tests stands ranged from less than 1-50 kg m(sup - 2). In addition to aboveground biomass, the biomass of the tree boles, branches, and needles/leaves were considered. Basing from the results obtained, it is concluded that the image intensity signatures recorded on SAR imagery have the potential to be used as the basis for the estimation of aboveground biomass in pine forests, for total stand biomass levels up to 35-40 kg m(sup - 2).

  18. Aboveground biomass allocation of ponderosa pine along an elevational gradient: An analog for response to climate change

    SciTech Connect

    Callaway, R.M.; DeLucia, E.H.; Schlesinger, W.H. Duke Univ., Durham, NC )

    1993-06-01

    Predictions of CO[sub 2]-enhanced growth for adult trees are primarily based on leaf-level assimilation responses and improved growth rates of seedlings and saplings. Plant growth may be more dependent on biomass allocation than on rates of assimilation, but predictions have not incorporated the effects of temperature on biomass reallocation among autotrophic and heterotrophic tissues and whole-plant carbon balance. We measured biomass allocation of Pinus ponderosa on hydrothermally altered andesite in montane and desert climates, thus substrate was held constant while climate varied. Trees from montane climates supported higher leaf mass per cross-sectional sapwood area (functional conducting xylem) than trees from desert climates, suggesting that a functional response to climate had occurred. Our results also indicate that sapwood mass:leaf mass ratios of P. ponderosa may increase [approx] 50% with a 5[degrees]C change. in mean growing season temperature, approximately the difference between our montane and desert sites. Such an increase in sapwood:leaf ratio may partially offset predicted CO[sub 2]-enhancement effects and substantially reduce whole-plant carbon balance. Biomass allocation responses must be incorporated into growth-response models used to predict fluctuations in forest productivity with changes in climate and atmospheric CO[sub 2] concentration.

  19. Effect of seven years of experimental drought on the aboveground biomass storage of an eastern Amazonian rainforest

    NASA Astrophysics Data System (ADS)

    da Costa, Antonio Carlos Lola; Galbraith, David; Almeida, Samuel; Fisher, Rosie; Phillips, Oliver; Metcalfe, Daniel; Levy, Peter; Portela, Bruno; da Costa, Mauricio; Meir, Patrick

    2010-05-01

    At least one climate model predicts severe reductions of rainfall over Amazonia during this century. Long-term throughfall exclusion (TFE) experiments represent the best available means to investigate the resilience of the Amazon rainforest to such droughts. Results are presented from a 7-year TFE study at Caxiuanã National Forest, eastern Amazonia. We focus on the impacts of the drought on tree mortality, wood production and aboveground carbon storage. Tree mortality in the TFE plot over the experimental period was 2.5% yr-1, compared to 1.25% yr-1 in a nearby Control plot experiencing normal rainfall. Differences in stem mortality between plots were greatest in the largest (> 40 cm dbh) size class (4.1% yr-1 in the TFE and 1.4% yr-1 in the Control). Wood production in the TFE plot was approximately 30% lower than in the Control plot. Together, these changes resulted in a loss of 37.8 ± 2.0 Mg C ha-1 (~ 20%) in the TFE plot (2002-2008), whereas the Control plot was essentially carbon neutral(change of - 0.2 ± 1.0 Mg C ha-1). These results are remarkably consistent with those from another TFE (at Tapajós National Forest), suggesting that Amazonian forests may respond to prolonged drought in a predictable manner.

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

    NASA Astrophysics Data System (ADS)

    Castanho, A. D.; Zhang, K.; Coe, M. T.; Costa, M. H.; Moorcroft, P. R.

    2012-12-01

    Field observations from undisturbed old-growth Amazonian forest plots have recently reported on the temporal variation of many of the physical and chemical characteristics such as: physiological properties of leaves, above ground live biomass, above ground productivity, mortality and turnover rates. However, although this variation has been measured, it is still not well understood what mechanisms control the observed temporal variability. The observed changes in time are believed to be a result of a combination of increasing atmospheric CO2 concentration, climate variability, recovery from natural disturbance (drought, wind blow, flood), and increase of nutrient availability. The time and spatial variability of the fertilization effect of CO2 on above ground biomass will be explored in more detail in this work. A precise understanding of the CO2 effect on the vegetation is essential for an accurate prediction of the future response of the forest to climate change. To address this issue we simultaneously explore the effects of climate variability, historical CO2 and land-use change on total biomass and productivity using two different Dynamic Global Vegetation Models (DGVM). We use the Integrated Biosphere Simulator (IBIS) and the Ecosystem Demography Model 2.1 (ED2.1). Using land use changes database from 1700 - 2008 we reconstruct the total carbon balance in the Amazonian forest in space and time and present how the models predict the forest as carbon sink or source and explore why the model and field data diverge from each other. From 1970 to 2005 the Amazonian forest has been exposed to an increase of approximately 50 ppm in the atmospheric CO2 concentration. Preliminary analyses with the IBIS and ED2.1 dynamic vegetation model shows the CO2 fertilization effect could account for an increase in above ground biomass of 0.03 and 0.04 kg-C/m2/yr on average for the Amazon basin, respectively. The annual biomass change varies temporally and spatially from about 0

  1. Biomass Estimates for Five Western States.

    SciTech Connect

    Howard, James O.

    1990-10-01

    The purpose of this report is to describe the woody biomass resource within US Department of Energy's Pacific Northwest and Alaska Regional Biomass Program, comprised of southeast Alaska, Idaho, Montana, Oregon, and Washington. In addition to the regional forest biomass assessment, information will be presented for logging residue, which represents current energy conversion opportunities. The information presented in the report is based on data and relationships already published. Regionally applicable biomass equations are generally not available for species occurring in the west. Because of this, a number of assumptions were made to develop whole-tree biomass tables. These assumptions are required to link algorithms from biomass studies to regional timber inventory data published by the Forest Inventory and Analysis Research Units (FIA), of the Pacific Northwest and Intermountain Research Stations, US Forest Service. These sources and assumptions will be identified later in this report. Tabular biomass data will be presented for 11 resource areas, identified in the FS inventory publications. This report does not include information for the vast area encompassing interior Alaska. Total tress biomass as defined in the report refers to the above ground weight of a tree above a 1.0 foot stump, and exclusive of foliage. A glossary is included that defines specific terms as used in the report. Inventory terminology is derived from forest inventory reports from Forest Inventory and Analysis units at the Intermountain and Pacific Northwest Research Stations. 39 refs., 15 figs., 23 tabs.

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

    PubMed

    Liu, Daijun; Ogaya, Romà; Barbeta, Adrià; Yang, Xiaohong; Peñuelas, Josep

    2015-11-01

    Climate change is predicted to increase the aridity in the Mediterranean Basin and severely affect forest productivity and composition. The responses of forests to different timescales of drought, however, are still poorly understood because extreme and persistent moderate droughts can produce nonlinear responses in plants. We conducted a rainfall-manipulation experiment in a Mediterranean forest dominated by Quercus ilex, Phillyrea latifolia, and Arbutus unedo in the Prades Mountains in southern Catalonia from 1999 to 2014. The experimental drought significantly decreased forest aboveground-biomass increment (ABI), tended to increase the litterfall, and decreased aboveground net primary production throughout the 15 years of the study. The responses to the experimental drought were highly species-specific. A. unedo suffered a significant reduction in ABI, Q. ilex experienced a decrease during the early experiment (1999-2003) and in the extreme droughts of 2005-2006 and 2011-2012, and P. latifolia was unaffected by the treatment. The drought treatment significantly increased branch litterfall, especially in the extremely dry year of 2011, and also increased overall leaf litterfall. The drought treatment reduced the fruit production of Q. ilex, which affected seedling recruitment. The ABIs of all species were highly correlated with SPEI in early spring, whereas the branch litterfalls were better correlated with summer SPEIs and the leaf and fruit litterfalls were better correlated with autumn SPEIs. These species-specific responses indicated that the dominant species (Q. ilex) could be partially replaced by the drought-resistant species (P. latifolia). However, the results of this long-term study also suggest that the effect of drought treatment has been dampened over time, probably due to a combination of demographic compensation, morphological and physiological acclimation, and epigenetic changes. However, the structure of community (e.g., species composition

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

    PubMed

    Liu, Daijun; Ogaya, Romà; Barbeta, Adrià; Yang, Xiaohong; Peñuelas, Josep

    2015-11-01

    Climate change is predicted to increase the aridity in the Mediterranean Basin and severely affect forest productivity and composition. The responses of forests to different timescales of drought, however, are still poorly understood because extreme and persistent moderate droughts can produce nonlinear responses in plants. We conducted a rainfall-manipulation experiment in a Mediterranean forest dominated by Quercus ilex, Phillyrea latifolia, and Arbutus unedo in the Prades Mountains in southern Catalonia from 1999 to 2014. The experimental drought significantly decreased forest aboveground-biomass increment (ABI), tended to increase the litterfall, and decreased aboveground net primary production throughout the 15 years of the study. The responses to the experimental drought were highly species-specific. A. unedo suffered a significant reduction in ABI, Q. ilex experienced a decrease during the early experiment (1999-2003) and in the extreme droughts of 2005-2006 and 2011-2012, and P. latifolia was unaffected by the treatment. The drought treatment significantly increased branch litterfall, especially in the extremely dry year of 2011, and also increased overall leaf litterfall. The drought treatment reduced the fruit production of Q. ilex, which affected seedling recruitment. The ABIs of all species were highly correlated with SPEI in early spring, whereas the branch litterfalls were better correlated with summer SPEIs and the leaf and fruit litterfalls were better correlated with autumn SPEIs. These species-specific responses indicated that the dominant species (Q. ilex) could be partially replaced by the drought-resistant species (P. latifolia). However, the results of this long-term study also suggest that the effect of drought treatment has been dampened over time, probably due to a combination of demographic compensation, morphological and physiological acclimation, and epigenetic changes. However, the structure of community (e.g., species composition

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

    EPA Science Inventory

    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...

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

    PubMed

    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.

  6. Forest Volume and Biomass estimation from SAR/LIDAR/Optical Fusion in Chile

    NASA Astrophysics Data System (ADS)

    Kellndorfer, J. M.; Walker, W. S.; Goetz, S. J.; Cormier, T.; Kirsch, K.; Gonzalez, S.; Rombach, M.

    2009-12-01

    The paper reports on research to investigate ALOS/PALSAR L-band radar and optical time series data in conjunction with airborne lidar datasets to develop advanced data fusion algorithms for biomass and ecosystem structure measurements in support of the NASA DESDynI mission. The research is based on the acquisition of ALOS/PALSAR time series data beginning in 2007 and the timely confluence of these acquisitions with other highly relevant remote sensing and ground reference data sets in forested areas in Chile. Through collaboration with Digimapas Chile, the project has access to 75,000 km2 of 1-meter resolution full-waveform small footprint lidar (SFPL) data and 0.5 m resolution digital orthophoto imagery covering the commercial forests of Arauco, one of the largest cellulose producers in Latin America. Field inventory data from Arauco are used to test terrain and environmental influences on biomass estimation from empirical regression tree based data fusion approaches. The SAR data acquisitions available from PALSAR during the project time frame will span a five year period from 2007 to 2011, allowing investigations into how L-band time series data, similar to that expected from the DESDynI SAR (backscatter and interferometric coherence), can be used to build (1) the DESDynI biomass map product to be produced at the end of the “designed mission life” (i.e., 3 and/or 5/5+ years) and (2) annual maps of aboveground biomass change.

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

    NASA Astrophysics Data System (ADS)

    Veenendaal, E. M.; Torello-Raventos, M.; Feldpausch, T. R.; Domingues, T. F.; Gerard, F.; Schrodt, F.; Saiz, G.; Quesada, C. A.; Djagbletey, G.; Ford, A.; Kemp, J.; Marimon, B. S.; Marimon-Junior, B. H.; Lenza, E.; Ratter, J. A.; Maracahipes, L.; Sasaki, D.; Sonke, B.; Zapfack, L.; Villarroel, D.; Schwarz, M.; Yoko Ishida, F.; Gilpin, M.; Nardoto, G. B.; Affum-Baffoe, K.; Arroyo, L.; Bloomfield, K.; Ceca, G.; Compaore, H.; Davies, K.; Diallo, A.; Fyllas, N. M.; Gignoux, J.; Hien, F.; Johnson, M.; Mougin, E.; Hiernaux, P.; Killeen, T.; Metcalfe, D.; Miranda, H. S.; Steininger, M.; Sykora, K.; Bird, M. I.; Grace, J.; Lewis, S.; Phillips, O. L.; Lloyd, J.

    2015-05-01

    Through interpretations of remote-sensing data and/or theoretical propositions, the idea that forest and savanna represent "alternative stable states" is gaining increasing acceptance. Filling an observational gap, we present detailed stratified floristic and structural analyses for forest and savanna stands located mostly within zones of transition (where both vegetation types occur in close proximity) in Africa, South America and Australia. Woody plant leaf area index variation was related to tree canopy cover in a similar way for both savanna and forest with substantial overlap between the two vegetation types. As total woody plant canopy cover increased, so did the relative contribution of middle and lower strata of woody vegetation. Herbaceous layer cover declined as woody cover increased. This pattern of understorey grasses and herbs progressively replaced by shrubs as the canopy closes over was found for both savanna and forests and on all continents. Thus, once subordinate woody canopy layers are taken into account, a less marked transition in woody plant cover across the savanna-forest-species discontinuum is observed compared to that inferred when trees of a basal diameter > 0.1 m are considered in isolation. This is especially the case for shrub-dominated savannas and in taller savannas approaching canopy closure. An increased contribution of forest species to the total subordinate cover is also observed as savanna stand canopy closure occurs. Despite similarities in canopy-cover characteristics, woody vegetation in Africa and Australia attained greater heights and stored a greater amount of above-ground biomass than in South America. Up to three times as much above-ground biomass is stored in forests compared to savannas under equivalent climatic conditions. Savanna-forest transition zones were also found to typically occur at higher precipitation regimes for South America than for Africa. Nevertheless, consistent across all three continents coexistence

  8. Estimating stem volume and biomass of Pinus koraiensis using LiDAR data.

    PubMed

    Kwak, Doo-Ahn; Lee, Woo-Kyun; Cho, Hyun-Kook; Lee, Seung-Ho; Son, Yowhan; Kafatos, Menas; Kim, So-Ra

    2010-07-01

    The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R (2) = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R (2) = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R (2) = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm(3)), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI). PMID:20182905

  9. Recovery and Phylogenetic Analysis of nifH Sequences from Diazotrophic Bacteria Associated with Dead Aboveground Biomass of Spartina alterniflora

    PubMed Central

    Lovell, Charles R.; Friez, Michael J.; Longshore, John W.; Bagwell, Christopher E.

    2001-01-01

    DNA was extracted from dry standing dead Spartina alterniflora stalks as well as dry Spartina wrack from the North Inlet (South Carolina) and Sapelo Island (Georgia) salt marshes. Partial nifH sequences were PCR amplified, the products were separated by denaturing gradient gel electrophoresis (DGGE), and the prominent DGGE bands were sequenced. Most sequences (109 of 121) clustered with those from α-Proteobacteria, and 4 were very similar (>99%) to that of Azospirillum brasilense. Seven sequences clustered with those from known γ-Proteobacteria and five with those from known anaerobic diazotrophs. The diazotroph assemblages associated with dead Spartina biomass in these two salt marshes were very similar, and relatively few major lineages were represented. PMID:11679360

  10. Response of aboveground biomass and diversity to nitrogen addition – a five-year experiment in semi-arid grassland of Inner Mongolia, China

    NASA Astrophysics Data System (ADS)

    He, Kejian; Qi, Yu; Huang, Yongmei; Chen, Huiying; Sheng, Zhilu; Xu, Xia; Duan, Lei

    2016-08-01

    Understanding the response of the plant community to increasing nitrogen (N) deposition is helpful for improving pasture management in semi-arid areas. We implemented a 5-year N addition experiment in a Stipa krylovii steppe of Inner Mongolia, northern China. The aboveground biomass (AGB) and species richness were measured annually. Along with the N addition levels, the species richness declined significantly, and the species composition changed noticeably. However, the total AGB did not exhibit a noticeable increase. We found that compensatory effects of the AGB occurred not only between the grasses and the forbs but also among Gramineae species. The plant responses to N addition, from the community to species level, lessened in dry years compared to wet or normal years. The N addition intensified the reduction of community productivity in dry years. Our study indicated that the compensatory effects of the AGB among the species sustained the stability of grassland productivity. However, biodiversity loss resulting from increasing N deposition might lead the semi-arid grassland ecosystem to be unsustainable, especially in dry years.

  11. Response of aboveground biomass and diversity to nitrogen addition - a five-year experiment in semi-arid grassland of Inner Mongolia, China.

    PubMed

    He, Kejian; Qi, Yu; Huang, Yongmei; Chen, Huiying; Sheng, Zhilu; Xu, Xia; Duan, Lei

    2016-01-01

    Understanding the response of the plant community to increasing nitrogen (N) deposition is helpful for improving pasture management in semi-arid areas. We implemented a 5-year N addition experiment in a Stipa krylovii steppe of Inner Mongolia, northern China. The aboveground biomass (AGB) and species richness were measured annually. Along with the N addition levels, the species richness declined significantly, and the species composition changed noticeably. However, the total AGB did not exhibit a noticeable increase. We found that compensatory effects of the AGB occurred not only between the grasses and the forbs but also among Gramineae species. The plant responses to N addition, from the community to species level, lessened in dry years compared to wet or normal years. The N addition intensified the reduction of community productivity in dry years. Our study indicated that the compensatory effects of the AGB among the species sustained the stability of grassland productivity. However, biodiversity loss resulting from increasing N deposition might lead the semi-arid grassland ecosystem to be unsustainable, especially in dry years. PMID:27573360

  12. Response of aboveground biomass and diversity to nitrogen addition – a five-year experiment in semi-arid grassland of Inner Mongolia, China

    PubMed Central

    He, Kejian; Qi, Yu; Huang, Yongmei; Chen, Huiying; Sheng, Zhilu; Xu, Xia; Duan, Lei

    2016-01-01

    Understanding the response of the plant community to increasing nitrogen (N) deposition is helpful for improving pasture management in semi-arid areas. We implemented a 5-year N addition experiment in a Stipa krylovii steppe of Inner Mongolia, northern China. The aboveground biomass (AGB) and species richness were measured annually. Along with the N addition levels, the species richness declined significantly, and the species composition changed noticeably. However, the total AGB did not exhibit a noticeable increase. We found that compensatory effects of the AGB occurred not only between the grasses and the forbs but also among Gramineae species. The plant responses to N addition, from the community to species level, lessened in dry years compared to wet or normal years. The N addition intensified the reduction of community productivity in dry years. Our study indicated that the compensatory effects of the AGB among the species sustained the stability of grassland productivity. However, biodiversity loss resulting from increasing N deposition might lead the semi-arid grassland ecosystem to be unsustainable, especially in dry years. PMID:27573360

  13. Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Naesset, Erik; Gobakken, T.; Gregoire, T.; Stahl, G.

    2009-01-01

    A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

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

    NASA Astrophysics Data System (ADS)

    Robinson, C. M.; Saatchi, S. S.; Clark, D.; Fricker, G. A.; Wolf, J.; Gillespie, T. W.; Rovzar, C. M.; Andelman, S.

    2012-12-01

    This research sought to understand how alpha and beta diversity of plants vary and relate to the three-dimensional vegetation structure and aboveground biomass along environmental gradients in the tropical montane forests of Braulio Carrillo National Park in Costa Rica. There is growing evidence that ecosystem structure plays an important role in defining patterns of species diversity and along with abiotic factors (climate and edaphic) control the phenotypic and functional variations across landscapes. It is well documented that strong subdivisions at local and regional scales are found mainly on geologic or climate gradients. These general determinants of biodiversity are best demonstrated in regions with natural gradients such as tropical montane forests. Altitudinal gradients provide a landscape scale changes through variations in topography, climate, and edaphic conditions on which we tested several theoretical and biological hypotheses regarding drivers of biodiversity. The study was performed by using forest inventory and botanical data from nine 1-ha plots ranging from 100 m to 2800 m above sea level and remote sensing data from airborne lidar and radar sensors to quantify variations in forest structure. In this study we report on the effectiveness of relating patterns of tree taxonomic alpha diversity to three-dimensional structure of a tropical montane forest using lidar and radar observations of forest structure and biomass. We assessed alpha and beta diversity at the species, genus, and family levels utilizing datasets provided by the Terrestrial Ecology Assessment and Monitoring (TEAM) Network. Through the comparison to active remote sensing imagery, our results show that there is a strong relationship between forest 3D-structure, and alpha and beta diversity controlled by variations in abiotic factors along the altitudinal gradient. Using spatial analysis with the aid of remote sensing data, we find distinct patterns along the environmental gradients

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

    NASA Astrophysics Data System (ADS)

    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

  16. Estimates of U.S. Biomass Energy Consumption 1992

    EIA Publications

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass derived primary energy used by the U.S. economy. It presents estimates of 1991 and 1992 consumption.

  17. USING DIRICHLET TESSELLATION TO HELP ESTIMATE MICROBIAL BIOMASS CONCENTRATIONS

    EPA Science Inventory

    Dirichlet tessellation was applied to estimate microbial concentrations from microscope well slides. The use of microscopy/Dirichlet tessellation to quantify biomass was illustrated with two species of morphologically distinct cyanobacteria, and validated empirically by compariso...

  18. Mortality as a key driver of the spatial distribution of aboveground biomass in Amazonian forests: results from a Dynamic Vegetation Model

    NASA Astrophysics Data System (ADS)

    Delbart, N.; Ciais, P.; Chave, J.; Viovy, N.; Malhi, Y.; Le Toan, T.

    2010-04-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Delbart, N.; Ciais, P.; Chave, J.; Viovy, N.; Malhi, Y.; Le Toan, T.

    2010-10-01

    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.

  20. Biomass Estimation for Individual Trees using Waveform LiDAR

    NASA Astrophysics Data System (ADS)

    Wang, K.; Kumar, P.; Dutta, D.

    2015-12-01

    Vegetation biomass information is important for many ecological models that include terrestrial vegetation in their simulations. Biomass has strong influences on carbon, water, and nutrient cycles. Traditionally biomass estimation requires intensive, and often destructive, field measurements. However, with advances in technology, airborne LiDAR has become a convenient tool for acquiring such information on a large scale. In this study, we use infrared full waveform LiDAR to estimate biomass information for individual trees in the Sangamon River basin in Illinois, USA. During this process, we also develop automated geolocation calibration algorithms for raw waveform LiDAR data. In the summer of 2014, discrete and waveform LiDAR data were collected over the Sangamon River basin. Field measurements commonly used in biomass equations such as diameter at breast height and total tree height were also taken for four sites across the basin. Using discrete LiDAR data, individual trees are delineated. For each tree, a voxelization methods is applied to all waveforms associated with the tree to result in a pseudo-waveform. By relating biomass extrapolated using field measurements from a training set of trees to waveform metrics for each corresponding tree, we are able to estimate biomass on an individual tree basis. The results can be especially useful as current models increase in resolution.

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

    NASA Astrophysics Data System (ADS)

    Thapa, R. B.; Watanabe, M.; Motohka, T.; Shiraishi, T.; shimada, M.

    2013-12-01

    Tropical forests are providing environmental goods and services including carbon sequestration, energy regulation, water fluxes, wildlife habitats, fuel, and building materials. Despite the policy attention, the tropical forest reserve in Southeast Asian region is releasing vast amount of carbon to the atmosphere due to deforestation. Establishing quality forest statistics and documenting aboveground forest carbon stocks (AFCS) are emerging in the region. Airborne and satellite based large area monitoring methods are developed to compliment conventional plot based field measurement methods as they are costly, time consuming, and difficult to implement for large regions. But these methods still require adequate ground measurements for calibrating accurate AFCS model. Furthermore, tropical region comprised of varieties of natural and plantation forests capping higher variability of forest structures and biomass volumes. To address this issue and the needs for ground data, we propose the systematic collection of ground data integrated with airborne light detection and ranging (LiDAR) data. Airborne LiDAR enables accurate measures of vertical forest structure, including canopy height and volume demanding less ground measurement plots. Using an appropriate forest type based LiDAR sampling framework, structural properties of forest can be quantified and treated similar to ground measurement plots, producing locally relevant information to use independently with satellite data sources including synthetic aperture radar (SAR). In this study, we examined LiDAR derived forest parameters with field measured data and developed general and specific AFCS models for tropical forests in central Sumatra. The general model is fitted for all types of natural and plantation forests while the specific model is fitted to the specific forest type. The study region consists of natural forests including peat swamp and dry moist forests, regrowth, and mangrove and plantation forests

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  3. Impacts of cattle grazing on spatio-temporal variability of soil moisture and above-ground live plant biomass in mixed grasslands

    NASA Astrophysics Data System (ADS)

    Virk, Ravinder

    Areas with relatively high spatial heterogeneity generally have more biodiversity than spatially homogeneous areas due to increased potential habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, but the nature of this impact is not well understood. Therefore this thesis studies the impacts of variation in grazing on soil moisture and biomass heterogeneity. These are not only important in terms of management of protected grasslands, but also for designing an effective grazing system from a livestock management point of view. This research is a part of the cattle grazing experiment underway in Grasslands National Park (GNP) of Canada since 2006, as part of the adaptive management process for restoring ecological integrity of the northern mixed-grass prairie region. An experimental approach using field measurements and remote sensing (Landsat) was combined with modelling (CENTURY) to examine and predict the impacts of grazing intensity on the spatial heterogeneity and patterns of above-ground live plant biomass (ALB) in experimental pastures in a mixed grassland ecosystem. The field-based research quantified the temporal patterns and spatial variability in both soil moisture (SM) and ALB, and the influence of local intra-seasonal weather variability and slope location on the spatio-temporal variability of SM and ALB at field plot scales. Significant impacts of intra-seasonal weather variability, slope position and grazing pressure on SM and ALB across a range of scales (plot and local (within pasture)) were found. Grazing intensity significantly affected the ALB even after controlling for the effect of slope position. Satellite-based analysis extended the scale of interest to full pastures and the surrounding region to assess the effects of grazing intensity on the spatio-temporal pattern of ALB in mixed grasslands. Overall, low to moderate grazing intensity showed increase in ALB heterogeneity whereas no change in ALB

  4. Structural, physiognomic and aboveground biomass variation in savanna-forest transition zones on three continents. How different are co-occurring savanna and forest formations?

    NASA Astrophysics Data System (ADS)

    Veenendaal, E. M.; Torello-Raventos, M.; Feldpausch, T. R.; Domingues, T. F.; Gerard, F.; Schrodt, F.; Saiz, G.; Quesada, C. A.; Djagbletey, G.; Ford, A.; Kemp, J.; Marimon, B. S.; Marimon-Junior, B. H.; Lenza, E.; Ratter, J. A.; Maracahipes, L.; Sasaki, D.; Sonké, B.; Zapfack, L.; Villarroel, D.; Schwarz, M.; Yoko Ishida, F.; Gilpin, M.; Nardoto, G. B.; Affum-Baffoe, K.; Arroyo, L.; Bloomfield, K.; Ceca, G.; Compaore, H.; Davies, K.; Diallo, A.; Fyllas, N. M.; Gignoux, J.; Hien, F.; Johnson, M.; Mougin, E.; Hiernaux, P.; Killeen, T.; Metcalfe, D.; Miranda, H. S.; Steininger, M.; Sykora, K.; Bird, M. I.; Grace, J.; Lewis, S.; Phillips, O. L.; Lloyd, J.

    2014-03-01

    Through interpretations of remote sensing data and/or theoretical propositions, the idea that forest and savanna represent "alternative stable states" is gaining increasing acceptance. Filling an observational gap, we present detailed stratified floristic and structural analyses for forest and savanna stands mostly located within zones of transition (where both vegetation types occur in close proximity) in Africa, South America and Australia. Woody plant leaf area index variation was related in a similar way to tree canopy cover for both savanna and forest with substantial overlap between the two vegetation types. As total woody plant canopy cover increased, so did the contribution of middle and lower strata of woody vegetation to this total. Herbaceous layer cover also declined as woody cover increased. This pattern of understorey grasses and herbs being progressively replaced by shrubs as canopy closure occurs was found for both savanna and forests and on all continents. Thus, once subordinate woody canopy layers are taken into account, a less marked transition in woody plant cover across the savanna-forest species discontinuum is observed compared to that implied when trees of a basal diameter > 0.1m are considered in isolation. This is especially the case for shrub-dominated savannas and in taller savannas approaching canopy closure. An increased contribution of forest species to the total subordinate cover is also observed as savanna stand canopy closure occurs. Despite similarities in canopy cover characteristics, woody vegetation in Africa and Australia attained greater heights and stored a greater concentration of above ground biomass than in South America. Up to three times as much aboveground biomass is stored in forests compared to savannas under equivalent climatic conditions. Savanna/forest transition zones were also found to typically occur at higher precipitation regimes for South America than for Africa. Nevertheless, coexistence was found to be

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

    NASA Astrophysics Data System (ADS)

    Cintra, B. B. L.; Schietti, J.; Emillio, T.; Martins, D.; Moulatlet, G.; Souza, P.; Levis, C.; Quesada, C. A.; Schöngart, J.

    2013-04-01

    The ongoing demand for information on forest productivity has increased the number of permanent monitoring plots across the Amazon. Those plots, however, do not comprise the whole diversity of forest types in the Amazon. The complex effects of soil, climate and hydrology on the productivity of seasonally waterlogged interfluvial wetland forests are still poorly understood. The presented study is the first field-based estimate for tree ages and wood biomass productivity in the vast interfluvial region between the Purus and Madeira rivers. We estimate stand age and wood biomass productivity by a combination of tree-ring data and allometric equations for biomass stocks of eight plots distributed along 600 km in the Purus-Madeira interfluvial area that is crossed by the BR-319 highway. We relate stand age and wood biomass productivity to hydrological and edaphic conditions. Mean productivity and stand age were 5.6 ± 1.1 Mg ha-1 yr-1 and 102 ± 18 yr, respectively. There is a strong relationship between tree age and diameter, as well as between mean diameter increment and mean wood density within a plot. Regarding the soil hydromorphic properties we find a positive correlation with wood biomass productivity and a negative relationship with stand age. Productivity also shows a positive correlation with the superficial phosphorus concentration. In addition, superficial phosphorus concentration increases with enhanced soil hydromorphic condition. We raise three hypotheses to explain these results: (1) the reduction of iron molecules on the saturated soils with plinthite layers close to the surface releases available phosphorous for the plants; (2) the poor structure of the saturated soils creates an environmental filter selecting tree species of faster growth rates and shorter life spans and (3) plant growth on saturated soil is favored during the dry season, since there should be low restrictions for soil water availability.

  6. Landscape-scale extent, height, biomass, and carbon estimation of Mozambique's mangrove forests with Landsat ETM+ and Shuttle Radar Topography Mission elevation data

    NASA Astrophysics Data System (ADS)

    Fatoyinbo, Temilola E.; Simard, Marc; Washington-Allen, Robert A.; Shugart, Herman H.

    2008-06-01

    Mangroves are salt tolerant plants that grow within the intertidal zone along tropical and subtropical coasts. They are important barriers for mitigating coastal disturbances, provide habitat for over 1300 animal species and are one of the most productive ecosystems. Mozambique's mangroves extend along 2700 km and cover one of the largest areas in Africa. The purpose of this study was to determine the countrywide mean tree height spatial distribution and biomass of Mozambique's mangrove forests using Landsat ETM+ and Shuttle Radar Topography Mission (SRTM) data. The SRTM data were calibrated using the Landsat derived land-cover map and height calibration equations. Stand-specific canopy height-biomass allometric equations developed from field measurements and published height-biomass equations were used to calculate aboveground biomass of the mangrove forests on a landscape scale. The results showed that mangrove forests covered a total of 2909 km2 in Mozambique, a 27% smaller area than previously estimated. The SRTM calibration indicated that average tree heights changed with geographical settings. Even though the coast of Mozambique spans across 16 degrees latitude, we did not find a relationship between latitude and biomass. These results confirm that geological setting has a greater influence than latitude alone on mangrove production. The total mangrove dry aboveground biomass in Mozambique was 23.6 million tons and the total carbon was 11.8 million tons.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    SciTech Connect

    none,

    2011-10-01

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

  9. Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

    NASA Technical Reports Server (NTRS)

    Saatchi, Sassan; Moghaddam, Mahta

    1995-01-01

    In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.

  10. Biomass estimation in a young stand of mesquite (Prosopis species), ironwood (Olneya tesota), pado verde (Cercidium floridium, and Parkinsonia aculeata), and leucaena (Leucaena leucocephala)

    SciTech Connect

    Felker, P.; Clark, P.R.; Osborn, J.F.; Cannell, G.H.

    1982-01-01

    Simple methods for estimating standing biomass in a stand of tree legumes containing the genera Prosopis, Cercidium, Olneya, Leucaena, and Parkinsonia are reported. Fresh and dry biomass were related to height and stem diameter measurements for 212 leguminous trees ranging in biomass from 0.04 to 17.8 kg using linear regression. The dry matter content of the above-ground biomass of these genera ranged from 40-56% and the stem dry matter percentage ranged from 70 to 96%. The best functional form of the model was log 10 dry weight (kg) = 2.55 log basal diameter (cm)-1.25, which had an r2 of 0.956 for 212 samples.

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

    NASA Astrophysics Data System (ADS)

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

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

  12. Long-term remote monitoring of salt marsh biomass

    NASA Technical Reports Server (NTRS)

    Gross, M. F.; Klemas, V.; Hardisky, M. A.

    1990-01-01

    Methods developed for monitoring salt-marsh biomass remotedly are considered in the framework of NASA's Biospheric Research Program. Satellite-derived estimates of the aboveground biomass is considered, and it is noted that a long-term program for long-term remote monitoring is only practical if the relationship between biomass and spectral data remains essentially constant from year to year. Emphasis is placed on ground-based sampling, satellite measurements of mean marsh live aboveground biomass, the spatial distribution of biomass within the marsh, and changes in marsh hydrography as seen from a satellite. Linking aboveground and belowground biomass is discussed, as well as the problem with obtaining cloud-free images and measuring dead biomass.

  13. Lidar and Ground Assessment of Diversity, Wood Density, and Aboveground Biomass Along an Elevation Gradient in Tropical Montane Forest of Costa Rica

    NASA Astrophysics Data System (ADS)

    Robinson, C. M.; Saatchi, S. S.; Clark, D.; Andelman, S.; Gillespie, T.

    2013-12-01

    This research seeks to understand how tree diversity relates to three-dimensional vegetation structure along environmental gradients in the tropical montane forest of Braulio Carrillo National Park in Costa Rica. Elevation gradients along mountains provide landscape-size scales through which variations in topography and climatic conditions can be tested as drivers of biodiversity. In this study we report on the effectiveness of relating patterns of tree alpha diversity to three-dimensional structure of a tropical montane forest using remote sensing observations of forest structure. The study was utilized forest inventory and botanical data from nine 1-ha plots ranging from 100m-2800m above sea level and remote sensing data from an airborne lidar sensor (NASA's Land, Vegetation, and Ice Sensor [LVIS]) to quantify variations in forest structure. In addition to calculating alpha diversity, we report on the variations in wood density with elevation, important for biomass and carbon estimations. Tree cores were analyzed for wood density and compared to existing database values for the same species, often collected only in the lowlands. In this manner we were able to test the effect of the gradient on effective wood density. Through the comparison to the lidar, our results show that there is a strong relationship between forest 3D structure and alpha diversity controlled by variations in abiotic factors along the elevational gradient. Using spatial analysis with the aid of remote sensing data, we found distinct patterns along the environmental gradients defining species composition. Wood density values with elevation change were found to vary significantly from database values for the same species. These wood density values are directly tied to biomass estimates, and it is possible that carbon storage has been overestimated along this gradient using prior methods. This variation in individual tree growth has repercussions on overall forest structure, as well as

  14. Biomass estimation to support pasture management in Niger

    NASA Astrophysics Data System (ADS)

    Schucknecht, A.; Meroni, M.; Kayitakire, F.; Rembold, F.; Boureima, A.

    2015-04-01

    Livestock plays a central economic role in Niger, but it is highly vulnerable due to the high inter-annual variability of rain and hence pasture production. This study aims to develop an approach for mapping pasture biomass production to support activities of the Niger Ministry of Livestock for effective pasture management. Our approach utilises the observed spatiotemporal variability of biomass production to build a predictive model based on ground and remote sensing data for the period 1998-2012. Measured biomass (63 sites) at the end of the growing season was used for the model parameterisation. The seasonal cumulative Fraction of Absorbed Photosynthetically Active Radiation (CFAPAR), calculated from 10-day image composites of SPOT-VEGETATION FAPAR, was computed as a phenology-tuned proxy of biomass production. A linear regression model was tested aggregating field data at different levels (global, department, agro-ecological zone, and intersection of agro-ecological and department units) and subjected to a cross validation (cv) by leaving one full year out. An increased complexity (i.e. spatial detail) of the model increased the estimation performances indicating the potential relevance of additional and spatially heterogeneous agro-ecological characteristics for the relationship between herbaceous biomass at the end of the season and CFAPAR. The model using the department aggregation yielded the best trade-off between model complexity and predictive power (R2 = 0.55, R2cv = 0.48). The proposed approach can be used to timely produce maps of estimated biomass at the end of the growing season before ground point measurements are made available.

  15. Estimation of old field ecosystem biomass using low altitude imagery

    NASA Technical Reports Server (NTRS)

    Nor, S. M.; Safir, G.; Burton, T. M.; Hook, J. E.; Schultink, G.

    1977-01-01

    Color-infrared photography was used to evaluate the biomass of experimental plots in an old-field ecosystem that was treated with different levels of waste water from a sewage treatment facility. Cibachrome prints at a scale of approximately 1:1,600 produced from 35 mm color infrared slides were used to analyze density patterns using prepared tonal density scales and multicell grids registered to ground panels shown on the photograph. Correlation analyses between tonal density and vegetation biomass obtained from ground samples and harvests were carried out. Correlations between mean tonal density and harvest biomass data gave consistently high coefficients ranging from 0.530 to 0.896 at the 0.001 significance level. Corresponding multiple regression analysis resulted in higher correlation coefficients. The results of this study indicate that aerial infrared photography can be used to estimate standing crop biomass on waste water irrigated old field ecosystems. Combined with minimal ground truth data, this technique could enable managers of wastewater irrigation projects to precisely time harvest of such systems for maximal removal of nutrients in harvested biomass.

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

    NASA Technical Reports Server (NTRS)

    Epstein, Howard E.; Raynolds, Martha K.; Walker, Donald A.; Bhatt, Uma S.; Tucker, Compton J.; Pinzon, Jorge E.

    2012-01-01

    Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

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

    NASA Astrophysics Data System (ADS)

    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 < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥ 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. 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

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

    NASA Astrophysics Data System (ADS)

    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

  19. Estimating forest biomass with GLAS samples and MODIS imagery in Northeastern China

    NASA Astrophysics Data System (ADS)

    Fu, Anmin; Sun, Guoqing; Guo, Zhifeng

    2009-10-01

    The forest ecosystem in Northeastern China (NEC) is approximately 25% proportion of total forested area of China, which has been undergoing dramatic changes due to massive loggings and forest fires in the last several decades and successively intensive manual afforestation and closing protective recovery since 1990s. It is a hot region for scientific research in carbon balance. In this paper, national land cover GIS data, moderate resolution imaging spectroradiometer (MODIS) imagery, and vertical waveform of Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESAT) were combined together to map forest aboveground biomass (AGB) in the NEC. Firstly, GLAS waveform has the advantage of three dimensional observations and can play the role as sampling footprints for forest biomes. The estimation algorithm was developed between field survey samples and height profile indices of GLAS waveform to predict forest AGB by neural net regression model. The correlation coefficient R2 between GLAS forest AGB and field-investigated ones was 0.73. Secondly, MODIS data affords spatially continuous images and can be used to stratify forested regions as statistical districts. one hundred of spectral clusters were derived from MODIS phenological curve of enhanced vegetation index (EVI) and near infrared (NIR) channel by K-Means method and stratified for the statistics of GLAS forest AGB samples. The result illustrates spatial pattern forest AGB and explores its total amount in the NEC.

  20. Estimation of old field ecosystem biomass using low altitude imagery

    NASA Technical Reports Server (NTRS)

    Nor, S. M.; Safir, G.; Burton, T. M.; Hook, J. E.; Schultink, G.

    1977-01-01

    Color-infrared photography was used to evaluate the biomass of experimental plots in an old-field ecosystem that was treated with different levels of waste water from a sewage treatment facility. Cibachrome prints at a scale of approximately 1:1,600 produced from 35 mm color infrared slides were used to analyze density patterns using prepared tonal density scales and multicell grids registered to ground panels shown on the photograph. Correlations between mean tonal density and harvest biomass data gave consistently high coefficients ranging from 0.530 to 0.896 at the 0.001 significance level. Corresponding multiple regression analysis resulted in higher correlation coefficients. The results indicate that aerial infrared photography can be used to estimate standing crop biomass on waste water irrigated old field ecosystems. Combined with minimal ground truth data, this technique could enable managers of waste water irrigation projects to precisely time harvest of such systems for maximal removal of nutrients in harvested biomass.

  1. New estimates of nitrous oxide emissions from biomass burning

    NASA Technical Reports Server (NTRS)

    Cofer, W. R., III; Levine, J. S.; Winstead, E. L.; Stocks, B. J.

    1991-01-01

    The recent discovery of an artifact producing increased levels of N2O in combustion gas samples collected and stored in grab bottles before chemical analysis has resulted in the downgrading of fossil-fuel combustion and the questioning of biomass burning as important sources of N2O. As almost all reported analyses of N2O produced from biomass burning have involved essentially the same collection and analysis protocols as used in the fossil-fuel studies, this source of N2O must also be reexamined. Here, measurements of N2O made over a large prescribed fire using a near real-time in situ measurement technique are reported and compared with measurements of N2O from simultaneously collected grab-bottle samples. The results from 27 small laboratory biomass test fires are also used to help clarify the validity of earlier assessments. It is concluded that biomass burning contributes about seven percent of atmospheric N2O, as opposed to earlier estimates of several times this value.

  2. Estimating externalities of biomass fuel cycles, Report 7

    SciTech Connect

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

    1998-01-01

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

  3. Single Baseline Tomography SAR for Forest Above Ground Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Li, Wenmei; Chen, Erxue; Li, Zengyuan; Wang, Xinshuang; Feng, Qi

    2013-01-01

    Single baseline tomography SAR is used for forest height estimation as its little restriction on the number of baselines and configurations of tracks in recent years. There existed two kinds of single baseline tomography SAR techniques, the polarimetric coherence tomography (PCT) and the sum of Kronecker product (SKP), algebraic synthesis (AS) and Capon spectral estimator approach (SKP-AS-Capon). Few researches on forest above ground biomass (AGB) estimation are there using single baseline tomography SAR. In this paper, PCT and SKP-AS-Capon approaches are proposed for forest AGB estimation. L-band data set acquired by E-SAR airborne system in 2003 for the forest test site in Traunstein, is used for this experiment. The result shows that single baseline polarimetric tomography SAR can obtain forest AGB in forest stand scale, and SKP-AS-Capon method has better detailed vertical structure information, while the Freeman 3-component combined PCT approach gets a homogenous vertical structure in forest stand.

  4. Regional forest biomass estimation using ICESat/GLAS spaceborne LiDAR

    NASA Astrophysics Data System (ADS)

    Hayashi, M.; Saigusa, N.; Habura, B.; Sawada, Y.; Yamagata, Y.; Hirano, T.; Ichii, K.

    2015-12-01

    Spaceborne LiDAR can observe vertical structure of forests and provide a means for accurate forest monitoring, therefore, it may meet the growing demand of forest resources monitoring on a large scale. This study aims to clarify the potential of ICESat/GLAS, which had been the only spaceborne LiDAR up to now, for forest resources monitoring on a regional scale. The study areas were three regions: Hokkaido Island in Japan (cool-temperate forest), Borneo Island (tropical forest) and Siberia (boreal forest). Firstly, we conducted field measurements at 106 points in Hokkaido and 37 points in Borneo to measure the average canopy height (Lorey's height) and the above-ground biomass (AGB) for each GLAS-footprint, then, we developed some models to estimate canopy height and AGB from the GLAS waveform parameters. Next, we applied the developed models to the GLAS data which were 14,000 points in Hokkaido, and 130,000 points in Borneo, to estimate canopy height and AGB on a regional scale. As a result, we clarified the forest condition concerning canopy height and AGB for each region, namely, the average value, the comparison between the average of each forest type, and the spatial distribution. Furthermore, we detected the AGB change over the years (forest degradation) and estimated the forest loss rate of 1.6% yr-1 in Borneo. Next, we applied the developed models in Hokkaido to the 1,600,000 points GLAS data observed in Siberia. As a result, we clarified that the average AGB in Siberia was a remarkable low value as compared with those in Hokkaido and Borneo, and that the AGB change over the years (forest degradation) was significant in the southern region of western Siberia. This study showed that spaceborne LiDAR had an ability of forest resources monitoring on a regional scale for various forests over the world.

  5. Contribution of aboveground plant respiration to carbon cycling in a Bornean tropical rainforet

    NASA Astrophysics Data System (ADS)

    Katayama, Ayumi; Tanaka, Kenzo; Ichie, Tomoaki; Kume, Tomonori; Matsumoto, Kazuho; Ohashi, Mizue; Kumagai, Tomo'omi

    2014-05-01

    Bornean tropical rainforests have a different characteristic from Amazonian tropical rainforests, that is, larger aboveground biomass caused by higher stand density of large trees. Larger biomass may cause different carbon cycling and allocation pattern. However, there are fewer studies on carbon allocation and each component in Bornean tropical rainforests, especially for aboveground plant respiration, compared to Amazonian forests. In this study, we measured woody tissue respiration and leaf respiration, and estimated those in ecosystem scale in a Bornean tropical rainforest. Then, we examined carbon allocation using the data of soil respiration and aboveground net primary production obtained from our previous studies. Woody tissue respiration rate was positively correlated with diameter at breast height (dbh) and stem growth rate. Using the relationships and biomass data, we estimated woody tissue respiration in ecosystem scale though methods of scaling resulted in different estimates values (4.52 - 9.33 MgC ha-1 yr-1). Woody tissue respiration based on surface area (8.88 MgC ha-1 yr-1) was larger than those in Amazon because of large aboveground biomass (563.0 Mg ha-1). Leaf respiration rate was positively correlated with height. Using the relationship and leaf area density data at each 5-m height, leaf respiration in ecosystem scale was estimated (9.46 MgC ha-1 yr-1), which was similar to those in Amazon because of comparable LAI (5.8 m2 m-2). Gross primary production estimated from biometric measurements (44.81 MgC ha-1 yr-1) was much higher than those in Amazon, and more carbon was allocated to woody tissue respiration and total belowground carbon flux. Large tree with dbh > 60cm accounted for about half of aboveground biomass and aboveground biomass increment. Soil respiration was also related to position of large trees, resulting in high soil respiration rate in this study site. Photosynthesis ability of top canopy for large trees was high and leaves for

  6. Estimation of methanogen biomass by quantitation of coenzyme M

    SciTech Connect

    Elias, D.A.; Krumholz, L.R.; Tanner, R.S.; Suflita, J.M.

    1999-12-01

    Determination of the role of methanogenic bacteria in an anaerobic ecosystem often requires quantitation of the organisms. Because of the extreme oxygen sensitivity of these organisms and the inherent limitations of cultural techniques, an accurate biomass value is very difficult to obtain. The authors standardized a simple method for estimating methanogen biomass in a variety of environmental matrices. In this procedure they used the thiol biomarker coenzyme M (CoM) (2-mercaptoethanesulfonic acid), which is known to be present in tall methanogenic bacteria. A high-performance liquid chromatography-based method for detecting thiols in pore water was modified in order to quantify CoM in pure cultures, sediments, and sewage water samples. The identity of the CoM derivative was verified by using liquid chromatography-mass spectroscopy. The assay was linear for CoM amounts ranging from 2 to 2,000 pmol, and the detection limit was 2 pmol of CoM/ml of sample. CoM was not adsorbed to sediments. The methanogens tested contained an average of 19.5 nmol of CoM/mg of protein and 0.39 {+-} 0.07 fmol of CoM/cell. Environmental samples contained an average of 0.41 {+-} 0.17 fmol/cell based on most-probable-number estimates. CoM was extracted by using 1% tri-(N)-butylphosphine in isopropanol. More than 90% of the CoM was recovered from pure cultures and environmental samples. The authors observed no interference from sediments in the CoM recovery process, and the method could be completed aerobically within 3 h. Freezing sediment samples resulted in 46 to 83% decreases in the amounts of detectable CoM, whereas freezing had no effect on the amounts of CoM determined in pure cultures. The method described here provides a quick and relatively simple way to estimate methanogenic biomass.

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

    USGS Publications Warehouse

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

    1981-01-01

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

  8. Spatially Explicit Large Area Biomass Estimation: Three Approaches Using Forest Inventory and Remotely Sensed Imagery in a GIS

    PubMed Central

    Wulder, Michael A.; White, Joanne C.; Fournier, Richard A.; Luther, Joan E.; Magnussen, Steen

    2008-01-01

    Forest inventory data often provide the required base data to enable the large area mapping of biomass over a range of scales. However, spatially explicit estimates of above-ground biomass (AGB) over large areas may be limited by the spatial extent of the forest inventory relative to the area of interest (i.e., inventories not spatially exhaustive), or by the omission of inventory attributes required for biomass estimation. These spatial and attributional gaps in the forest inventory may result in an underestimation of large area AGB. The continuous nature and synoptic coverage of remotely sensed data have led to their increased application for AGB estimation over large areas, although the use of these data remains challenging in complex forest environments. In this paper, we present an approach to generating spatially explicit estimates of large area AGB by integrating AGB estimates from multiple data sources; 1. using a lookup table of conversion factors applied to a non-spatially exhaustive forest inventory dataset (R2 = 0.64; RMSE = 16.95 t/ha), 2. applying a lookup table to unique combinations of land cover and vegetation density outputs derived from remotely sensed data (R2 = 0.52; RMSE = 19.97 t/ha), and 3. hybrid mapping by augmenting forest inventory AGB estimates with remotely sensed AGB estimates where there are spatial or attributional gaps in the forest inventory data. Over our 714,852 ha study area in central Saskatchewan, Canada, the AGB estimate generated from the forest inventory was approximately 40 Mega tonnes (Mt); however, the inventory estimate represents only 51% of the total study area. The AGB estimate generated from the remotely sensed outputs that overlap those made from the forest inventory based approach differ by only 2 %; however in total, the remotely sensed estimate is 30 % greater (58 Mt) than the estimate generated from the forest inventory when the entire study area is accounted for. Finally, using the hybrid approach, whereby

  9. Estimation of Tropical Forest Height and Biomass Dynamics Using Lidar Remote Sensing at La Selva, Costa Rica

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    In this paper we reexamine 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. Pair wise 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 one 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). When statistical uncertainty was included in our analysis most of the old growth areas appeared 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 magnitude of biomass changes and the sensitivity of lidar to detect them, this work will help inform the formulation of future space missions focused on

  10. Uav-Based Automatic Tree Growth Measurement for Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Karpina, M.; Jarząbek-Rychard, M.; Tymków, P.; Borkowski, A.

    2016-06-01

    Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

  11. Uncertainty estimation in integrated LiDAR- and radar-derived biomass maps at key national-level map scales

    NASA Astrophysics Data System (ADS)

    Joshi, N.; Fensholt, R.; Saatchi, S. S.; Mitchard, E. T.

    2013-12-01

    The international Reducing Emissions from Deforestation and Degradation (REDD) program requires accurate and cost-effective techniques of national-level mapping of above-ground biomass (AGB) and ground-sampling strategies. This paper explores a multi-sensor (radar and low-density airborne LiDAR) integration approach for country-wide AGB estimation and mapping in Denmark, selected as a test-country due to the unique availability of country-wide remote sensing and forest inventory data. We assess the potential use of ALOS PALSAR L-band radar and ENVISAT ASAR C-band radar in prediction and mapping of AGB with accuracies similar to LiDAR-derived AGB estimates at different map scales. We start by creating a LiDAR-based ';ground truth' map, using LiDAR-derived 95th Percentile of heights >1 m weighted by the Canopy Density ratio, together with 113 AGB plots to map AGB at a 0.25 ha resolution across the country. A leave-20%-out cross-validation indicates that the AGB estimates have a mean absolute error of 41 Mg ha-1 and a negative mean bias error of 1.7 Mg ha-1. Though the LiDAR model appears to have an overall species-specific bias for conifers and broadleaf (-5.2 Mg ha-1 and +12.3 Mg ha-1 respectively), these are found to be insignificant (p>0.05) when accounting for species sampling bias and the under-prediction of plots containing high-biomass (> 350 Mg ha-1). Using the LiDAR-derived biomass map as a ';truth-map', biomass-backscatter relations will be quantified at three map scales (0.25 ha, 1 ha and 100 ha) and using three spatial sampling frameworks (full-dataset, stratified random sampling equally representing low and high biomass pixels, clustered sampling). The approach aims to derive a minimal-sampling and mapping strategy for L- and C-band radar that achieves at least 20% accuracy in AGB estimation, along with quantified sources of error from ground-AGB estimates, scaling and sampling. It is expected that mapping techniques, uncertainty quantification and

  12. Comparison of carbon and biomass estimation methods for European forests

    NASA Astrophysics Data System (ADS)

    Neumann, Mathias; Mues, Volker; Harkonen, Sanna; Mura, Matteo; Bouriaud, Olivier; Lang, Mait; Achten, Wouter; Thivolle-Cazat, Alain; Bronisz, Karol; Merganicova, Katarina; Decuyper, Mathieu; Alberdi, Iciar; Astrup, Rasmus; Schadauer, Klemens; Hasenauer, Hubert

    2015-04-01

    National and international reporting systems as well as research, enterprises and political stakeholders require information on carbon stocks of forests. Terrestrial assessment systems like forest inventory data in combination with carbon calculation methods are often used for this purpose. To assess the effect of the calculation method used, a comparative analysis was done using the carbon calculation methods from 13 European countries and the research plots from ICP Forests (International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests). These methods are applied for five European tree species (Fagus sylvatica L., Quercus robur L., Betula pendula Roth, Picea abies (L.) Karst. and Pinus sylvestris L.) using a standardized theoretical tree dataset to avoid biases due to data collection and sample design. The carbon calculation methods use allometric biomass and volume functions, carbon and biomass expansion factors or a combination thereof. The results of the analysis show a high variation in the results for total tree carbon as well as for carbon in the single tree compartments. The same pattern is found when comparing the respective volume estimates. This is consistent for all five tree species and the variation remains when the results are grouped according to the European forest regions. Possible explanations are differences in the sample material used for the biomass models, the model variables or differences in the definition of tree compartments. The analysed carbon calculation methods have a strong effect on the results both for single trees and forest stands. To avoid misinterpretation the calculation method has to be chosen carefully along with quality checks and the calculation method needs consideration especially in comparative studies to avoid biased and misleading conclusions.

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

    USGS Publications Warehouse

    O’Halloran, Lydia R.; Borer, Elizabeth T.; Seabloom, Eric W.; MacDougall, Andrew S.; Cleland, Elsa E.; McCulley, Rebecca L.; Hobbie, Sarah; Harpole, W. Stan; DeCrappeo, Nicole M.; Chu, Cheng-Jin; Bakker, Jonathan D.; Davies, Kendi F.; Du, Guozhen; Firn, Jennifer; Hagenah, Nicole; Hofmockel, Kirsten S.; Knops, Johannes M.H.; Li, Wei; Melbourne, Brett A.; Morgan, John W.; Orrock, John L.; Prober, Suzanne M.; Stevens, Carly J.

    2013-01-01

    Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.

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

    PubMed

    Liu, Liangyun; Peng, Dailiang; Wang, Zhihui; Hu, Yong

    2014-11-01

    China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.

  15. Estimating forest biomass from LiDAR data: A comparison of the raster-based and point-cloud data approach

    NASA Astrophysics Data System (ADS)

    Garcia-Alonso, M.; Ferraz, A.; Saatchi, S. S.; Casas, A.; Koltunov, A.; Ustin, S.; Ramirez, C.; Balzter, H.

    2015-12-01

    Accurate knowledge of forest biomass and its dynamics is critical for better understanding the carbon cycle and improving forest management decisions to ensure forest sustainability. LiDAR technology provides accurate estimates of aboveground biomass in different ecosystems, minimizing the signal saturation problems that are common with other remote sensing technologies. LiDAR data processing can be based on two different approaches. The first is based on deriving structural metrics from returns classified as vegetation, while the second one is based on metrics derived from the canopy height model (CHM). The CHM is obtained by subtracting the digital elevation model (DEM) that was created from the ground returns, from the digital surface model (DSM), which was itself constructed using the maximum height within each grid cell. The former approach provides a better description of the vertical distribution of the vegetation, whereas the latter significantly reduces the computational burden involved in processing point cloud data at the expense of losing information. This study evaluates the performance of both approaches for biomass estimation over very different ecosystems, including a Mediterranean forest in the Sierra Nevada Mountains of California and a tropical forest in Barro Colorado Island (Panama). In addition, the effect of point density on the variables derived, and ultimately on the estimated biomass, will be assessed.

  16. Structure-based biomass estimation in an Amazon forest from ICESat/GLAS observations: the performance of Fourier transforms of profiles

    NASA Astrophysics Data System (ADS)

    Goncalves, F. G.; Treuhaft, R. N.; dos Santos, J. R.; Graca, P. A.; Almeida, A. Q.; Law, B. E.; Dutra, L.

    2011-12-01

    Studies of the terrestrial carbon balance have shown that global monitoring of carbon fluxes from deforestation and forest degradation is critical to projecting with confidence future changes in the Earth's climate. The use of LiDAR and interferometric SAR data for characterizing the vertical structure of tropical forests has been tested and validated in a number of studies. Nonetheless, key scientific issues still need to be addressed for transforming these structural measurements into predictions of carbon pools at required accuracies and resolutions. In this study, we exploit the analysis of space-based LiDAR observations from ICESat/GLAS, and detailed in-situ measurements of 3-D structure and aboveground biomass collected at the Tapajos National Forest, Brazil, to mature methodological approaches relevant to potential future missions such as DESDynI-Radar and ICESat-2. We show that GLAS and field-based profiles estimated for 30 stands spanning a wide range in vertical structure (7-22 m mean height) and biomass (7-419 Mg ha-1) have good qualitative and quantitative agreement, with GLAS profile-averaged mean height and standard deviation RMS errors about the field measurements of 2.8 m (17%) and 2.6 m (42%), respectively. We used regression analysis to model the relationship between aboveground biomass and the remotely sensed structure. To obtain honest estimates of the predictive ability of the models, we used cross-validation involving repeated splits of the data set into separate model training and validation sets. The best height-based model included two metrics - the height of the median energy (HOME) and the standard deviation of height (SDH) - and explained 88% of the biomass variability, with a cross-validation RMS prediction error of 50.3 Mg ha-1 (29%). A new approach to biomass estimation based on the Fourier transform of large-footprint LiDAR profiles suggested that combinations of 5-6 vertical scales, ranging from 3 to 100 m, yield optimal biomass

  17. Weed management, training, and irrigation practices for organic production of trailing blackberry: III. Accumulation and removal of aboveground biomass, carbon, and nutrients

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The effects of various production practices on biomass, C, and nutrient content, accumulation, and loss were assessed over 2 years in a mature organic trailing blackberry (Rubus L. subgenus Rubus, Watson) production system. Treatments included two irrigation options (no irrigation after harvest and ...

  18. Regional estimation of current and future forest biomass.

    PubMed

    Mickler, R A; Earnhardt, T S; Moore, J A

    2002-01-01

    The 90,674 wildland fires that burned 2.9 million ha at an estimated suppression cost of $1.6 billion in the United States during the 2000 fire season demonstrated that forest fuel loading has become a hazard to life, property, and ecosystem health as a result of past fire exclusion policies and practices. The fire regime at any given location in these regions is a result of complex interactions between forest biomass, topography, ignitions, and weather. Forest structure and biomass are important aspects in determining current and future fire regimes. Efforts to quantify live and dead forest biomass at the local to regional scale has been hindered by the uncertainty surrounding the measurement and modeling of forest ecosystem processes and fluxes. The interaction of elevated CO2 with climate, soil nutrients, and other forest management factors that affect forest growth and fuel loading will play a major role in determining future forest stand growth and the distribution of species across the southern United States. The use of satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of forest carbon. The incorporation of Landsat Thematic Mapper data coupled with a physiologically based productivity model (PnET), soil water holding capacity, and historic and projected climatic data provides an opportunity to enhance field plot based forest inventory and monitoring methodologies. We use periodic forest inventory data from the USDA Forest Service's Forest Inventory and Analysis (FIA) project to obtain estimates of forest area and type to generate estimates of carbon storage for evergreen, deciduous, and mixed forest classes for use in an assessment of remotely sensed forest cover at the regional scale for the southern United States. The displays of net primary productivity (NPP) generated from the PnET model show areas of high and low forest carbon storage

  19. High-biomass sorghum yield estimate with aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Abstract. To reach the goals laid out by the U.S. Government for displacing fossil fuels with biofuels, agricultural production of dedicated biomass crops is required. High-biomass sorghum is advantageous across wide regions because it requires less water per unit dry biomass and can produce very hi...

  20. ESTIMATION OF SURPLUS BIOMASS OF CLUPEIDS IN SMITH MOUNTAIN LAKE, VIRGINIA

    EPA Science Inventory

    Mean annual estimates of surplus biomass of alewife Alosa pseudoharengus and gizzard shad Dorosoma cepedianum in Smith Mountain Lake, Virginia, were calculated using data on the biomass, growth, and mortality of each clupeid species. Surplus biomass, defined as production over a...

  1. Estimation of crops biomass and evapotranspiration from high spatial and temporal resolutions remote sensing data

    NASA Astrophysics Data System (ADS)

    Claverie, Martin; Demarez, Valérie; Duchemin, Benoît.; Ceschia, Eric; Hagolle, Olivier; Ducrot, Danielle; Keravec, Pascal; Beziat, Pierre; Dedieu, Pierre

    2010-05-01

    Carbon and water cycles are closely related to agricultural activities. Agriculture has been indeed identified by IPCC 2007 report as one of the options to sequester carbon in soil. Concerning the water resources, their consumptions by irrigated crops are called into question in view of demographic pressure. In the prospect of an assessment of carbon production and water consumption, the use of crop models at a regional scale is a challenging issue. The recent availability of high spatial resolution (10 m) optical sensors associated to high temporal resolution (1 day) such as FORMOSAT-2 and, in the future, Venµs and SENTINEL-2 will offer new perspectives for agricultural monitoring. In this context, the objective of this work is to show how multi-temporal satellite observations acquired at high spatial resolution are useful for a regional monitoring of following crops biophysical variables: leaf area index (LAI), aboveground biomass (AGB) and evapotranspiration (ET). This study focuses on three summer crops dominant in South-West of France: maize, sunflower and soybean. A unique images data set (82 FORMOSAT-2 images over four consecutive years, 2006-2009) was acquired for this project. The experimental data set includes LAI and AGB measurements over eight agricultural fields. Two fields were intensively monitored where ET flux were measured with a 30 minutes time step using eddy correlation methods. The modelisation approach is based on FAO-56 method coupled with a vegetation functioning model based on Monteith theory: the SAFY model [5]. The model operates at a daily time step model to provide estimates of plant characteristics (LAI, AGB), soil conditions (soil water content) and water use (ET). As a key linking variable, LAI is deduced from FORMOSAT-2 reflectances images, and then introduced into the SAFY model to provide spatial and temporal estimates of these biophysical variables. Most of the SAFY parameters are crop related and have been fixed according to

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

    PubMed Central

    Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal

    2015-01-01

    Background African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Principal Findings Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. Conclusions/Significance We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to

  3. Plant biomass in the Tanana River Basin, Alaska. Forest Service research paper

    SciTech Connect

    Mead, B.R.

    1995-01-01

    Vegetation biomass tables are presented for the Tanana River Basin. Average biomass for each species of tree, shrub, grass, forb, lichen, and moss in the 13 forest and 30 nonforest vegetation types is shown. These data combined with area estimates for each vegetation type provide a tool for estimating habitat carrying capacity for many wildlife species. Tree biomass is reported for the entire aboveground tree, thereby allowing estimates of total fiber content.

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

    NASA Astrophysics Data System (ADS)

    Mallon, E. E.; Turetsky, M.; Thompson, I.; Noland, T. L.; Wiebe, P.

    2013-12-01

    Disturbance is known to play an important role in maintaining the productivity and biodiversity of boreal forest ecosystems. Moderate to low frequency disturbance is responsible for regeneration opportunities creating a mosaic of habitats and successional trajectories. However, large-scale deforestation and increasing wildfire frequencies exacerbate habitat loss and influence biogeochemical cycles. This has raised concern about the quality of the under-story vegetation post-disturbance and whether this may impact herbivores, especially those vulnerable to change. Forest-dwelling caribou (Rangifer tarandus caribou) are declining in several regions of Canada and are currently listed as a species at risk by COSEWIC. Predation and landscape alteration are viewed as the two main threats to woodland caribou. This has resulted in caribou utilizing low productivity peatlands as refuge and the impact of this habitat selection on their diet quality is not well understood. Therefore there are two themes in the study, 1) Forage quantity: above-ground biomass and productivity and 2) Forage quality: foliar N and C to N ratios and % fiber. The themes are addressed in three questions: 1) How does forage quantity and quality vary between upland forests and peatlands? 2) How does wildfire affect the availability and nutritional quality of forage items? 3) How does forage quality vary between sites recovering from wildfire versus timber harvest? Research sites were located in the Auden region north of Geraldton, ON. This landscape was chosen because it is known woodland caribou habitat and has thorough wildfire and silviculture data from the past 7 decades. Plant diversity, above-ground biomass, vascular green area and seasonal foliar fiber and C to N ratios were collected across a matrix of sites representing a chronosequence of time since disturbance in upland forests and peatlands. Preliminary findings revealed productivity peaked in early age stands (0-30 yrs) and biomass peaked

  5. Aboveground and belowground competition between willow Salix caprea its understory

    NASA Astrophysics Data System (ADS)

    Mudrák, Ondřej; Hermová, Markéta; Frouz, Jan

    2016-04-01

    The effects of aboveground and belowground competition with the willow S. caprea on its understory plant community were studied in unreclaimed post-mining sites. Belowground competition was evaluated by comparing (i) frames inserted into the soil that excluded woody roots (frame treatment), (ii) frames that initially excluded woody root growth but then allowed regrowth of the roots (open-frame treatment), and (iii) undisturbed soil (no-frame treatment). These treatments were combined with S. caprea thinning to assess the effect of aboveground competition. Three years after the start of the experiment, aboveground competition from S. caprea (as modified by thinning of the S. caprea canopy) had not affected understory biomass or species number but had affected species composition. In contrast, belowground competition significantly affected both the aboveground and belowground biomass of the understory. The aboveground biomass of the understory was greater in the frame treatment (which excluded woody roots) than in the other two treatments. The belowground biomass of the understory was greater in the frame than in the open-frame treatment. Unlike aboveground competition (light availability), belowground competition did not affect understory species composition. Our results suggest that S. caprea is an important component during plant succession on post-mining sites because it considerably modifies its understory plant community. Belowground competition is a major reason for the low cover and biomass of the herbaceous understory in S. caprea stands on post-mining sites.

  6. Harvesting tree biomass at the stand level to assess the accuracy of field and airborne biomass estimation in savannas.

    PubMed

    Colgan, Matthew S; Asner, Gregory P; Swemmer, Tony

    2013-07-01

    Tree biomass is an integrated measure of net growth and is critical for understanding, monitoring, and modeling ecosystem functions. Despite the importance of accurately measuring tree biomass, several fundamental barriers preclude direct measurement at large spatial scales, including the facts that trees must be felled to be weighed and that even modestly sized trees are challenging to maneuver once felled. Allometric methods allow for estimation of tree mass using structural characteristics, such as trunk diameter. Savanna trees present additional challenges, including limited available allometry and a prevalence of multiple stems per individual. Here we collected airborne lidar data over a semiarid savanna adjacent to the Kruger National Park, South Africa, and then harvested and weighed woody plant biomass at the plot scale to provide a standard against which field and airborne estimation methods could be compared. For an existing airborne lidar method, we found that half of the total error was due to averaging canopy height at the plot scale. This error was eliminated by instead measuring maximum height and crown area of individual trees from lidar data using an object-based method to identify individual tree crowns and estimate their biomass. The best object-based model approached the accuracy of field allometry at both the tree and plot levels, and it more than doubled the accuracy compared to existing airborne methods (17% vs. 44% deviation from harvested biomass). Allometric error accounted for less than one-third of the total residual error in airborne biomass estimates at the plot scale when using allometry with low bias. Airborne methods also gave more accurate predictions at the plot level than did field methods based on diameter-only allometry. These results provide a novel comparison of field and airborne biomass estimates using harvested plots and advance the role of lidar remote sensing in savanna ecosystems.

  7. Prospects for the Regional Assessment of Aboveground Carbon Stocks of Northern Forests Using the ICESAT-GLAS Spaceborne Sensor

    NASA Astrophysics Data System (ADS)

    Margolis, H. A.; Nelson, R. F.; Boudreau, J.; Wulder, M.; Andersen, H. E.; Beaudoin, A.; Guindon, L.

    2009-05-01

    Northern forests in North America contain a vast amount of sequestered carbon that is potentially vulnerable to climate change. Scientists from Canada and the US are working in close collaboration to assess the capacity of the GLAS lidar sensor on the ICESAT satellite to estimate the amount, spatial distribution and statistical uncertainty of aboveground tree biomass of these forests. A pilot study in the 1.2 million km2 forest region of Quebec has demonstrated the capability and precision of this spaceborne sensor and we are now applying the technique we developed to the ˜6.2 million km2 area of the boreal biome of North America, i.e. both Canada and Alaska. The biomass of ground plots located in different regions is related to tree height data collected from an airborne profiling small-footprint lidar system. The airborne data is then related to GLAS data for a sample of ICESat orbits. Finally, the full set of available GLAS data is combined with land cover and topographic data to predict aboveground tree biomass as well as the sources and magnitude of the uncertainty. Aboveground biomass for the Quebec study area averaged 39.0 ± 2.2 Mg ha-1 and totalled 4.9 ± 0.3 Pg. Biomass distributions in Quebec were 12.6% northern hardwoods, 12.6% northern mixedwood, 38.4% commercial boreal, 13% non-commercial boreal, 14.2% taiga, and 9.2% treed tundra. Non-commercial forests represented 36% of the estimated aboveground biomass, thus highlighting the importance of remote northern forests to C sequestration.

  8. Biomass estimator for NIR image with a few additional spectral band images taken from light UAS

    NASA Astrophysics Data System (ADS)

    Pölönen, Ilkka; Salo, Heikki; Saari, Heikki; Kaivosoja, Jere; Pesonen, Liisa; Honkavaara, Eija

    2012-05-01

    A novel way to produce biomass estimation will offer possibilities for precision farming. Fertilizer prediction maps can be made based on accurate biomass estimation generated by a novel biomass estimator. By using this knowledge, a variable rate amount of fertilizers can be applied during the growing season. The innovation consists of light UAS, a high spatial resolution camera, and VTT's novel spectral camera. A few properly selected spectral wavelengths with NIR images and point clouds extracted by automatic image matching have been used in the estimation. The spectral wavelengths were chosen from green, red, and NIR channels.

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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 < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥ 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into 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

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

    USGS Publications Warehouse

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

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

  15. On-line biomass estimation in biosurfactant production process by Candida lipolytica UCP 988.

    PubMed

    da Costa Albuquerque, Clarissa Daisy; de Campos-Takaki, Galba Maria; Fileti, Ana Maria Frattini

    2008-11-01

    Biomass is an important variable in biosurfactant production process. However, such bioprocess variable, usually, is collected by sampling and determined by off-line analysis, with significant time delay. Therefore, simple and reliable on-line biomass estimation procedures are highly desirable. An artificial neural network model (ANN) is presented for the on-line estimation of biomass concentration, in biosurfactant production by Candida lipolytica UCP 988, as a nonlinear function of pH and dissolved oxygen. Several configurations were evaluated while developing the optimal ANN model. The optimal ANN model consists of one hidden layer with four neurons. The performance of the ANN was checked using experimental data. The results obtained indicate a very good predictive capacity for the ANN-based software sensor with values of R2 of 0.969 and RMSE of 0.021 for biomass concentration. Estimated biomass using the ANN was proved to be a simple, robust and accurate method.

  16. Precision of sugarcane biomass estimates in pot studies using fresh and dry weights

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sugarcane (Saccharum spp.) field studies generally report fresh weight (FW) rather than dry weight (DW) due to logistical difficulties in drying large amounts of biomass. Pot studies often measure biomass of young plants with DW under the assumption that DW provides a more precise estimate of treatm...

  17. Biomass estimation of Douglas fir stands using airborne LiDAR data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Biomass is an important parameter not only for carbon cycle modeling, but also for supporting land management operations (e.g. land use policy, forest fire management). Various remote sensing data have been utilized for biomass estimation, especially in forested areas. LiDAR (Light Detection And Ran...

  18. Structural Biomass Estimation from L-band Interferometric SAR and Lidar

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    After a review of biomass estimation from interferometric SAR (InSAR) at all bands over the last 15 years, and a brief review of lidar biomass estimation, this paper discusses structure and biomass estimation from simultaneously acquired (not repeat-track) InSAR at L-band. We will briefly discuss the history of regression of biomass to InSAR raw observations (coherence and phase) and structural parameters (height, standard deviation, Fourier component). Lidar biomass estimation from functions of the waveform will be discussed. We review our structural and biomass estimation results for C-band InSAR at vertical polarization for 12-14 baselines in La Selva Biological Station, Costa Rica. C-band vertical scales were between 12 and 100 m for structure estimation, but only between 50 and 100 m for biomass estimation, due to phase calibration problems at the shorter vertical wavelengths (larger baselines). Most of the talk will be spent on L-band, simultaneously acquired multibaseline InSAR, also at La Selva, acquired at vertical polarization. Because the vertical interferometric scale is proportional to the radar altitude times the wavelength over the baseline length, the AirSAR aircraft had to be flown very low (1.2 km) to realize vertical scales at L-band of 60 m and higher. Our lidar biomass estimation suggests that vertical scales of 14 m-100 m are optimal for biomass estimation. We will try three different approaches to biomass estimation with the limited high vertical scales we have available: 1) We will regress biomass to Fourier transforms as in the C-band and lidar study, but with 60 m - 100+ m vertical scales we do not expect accuracies to be as high as for the lidar demonstration (58 Mg/ha RMS scatter of estimated about field biomass for biomasses up to 450 Mg/ha), which used Fourier vertical wavelengths of 15 m-20 m. In addition to using Fourier components, 2) we will report the use of the derivative of the InSAR complex coherence with respect to Fourier

  19. A method to estimate the biomass of Spirulina platensis cultivated on a solid medium.

    PubMed

    Pelizer, Lúcia Helena; Moraes, Iracema de Oliveira

    2014-01-01

    This paper presents a method to estimate the biomass of Spirulina cultivated on solid medium with sugarcane bagasse as a support, in view of the difficulty in determining biomass concentrations in bioprocesses, particularly those conducted in semi-solid or solid media. The genus Spirulina of the family Oscillatoriaceae comprises the group of multicellular filamentous cyanobacteria (blue-green microalgae). Spirulina is used as fish feed in aquaculture, as a food supplement, a source of vitamins, pigments, antioxidants and fatty acids. Therefore, its growth parameters are extremely important in studies of the development and optimization of bioprocesses. For studies of biomass growth, Spirulina platensis was cultured on solid medium using sugarcane bagasse as a support. The biomass thus produced was estimated by determining the protein content of the material grown during the process, based on the ratio of dry weight to protein content obtained in the surface growth experiments. The protein content of the biomass grown in Erlenmeyer flasks on surface medium was examined daily to check the influence of culture time on the protein content of the biomass. The biomass showed an average protein content of 42.2%. This methodology enabled the concentration of biomass adhering to the sugarcane bagasse to be estimated from the indirect measurement of the protein content associated with cell growth.

  20. Incorrect representation of uncertainty in the modeling of growth leads to biased estimates of future biomass.

    PubMed

    Valle, Denis

    2011-06-01

    Biomass is a fundamental measure in the natural sciences, and numerous models have been developed to forecast timber and fishery yields, forest carbon content, and other environmental services that depend on biomass estimates. We derive general results that reveal how dynamic models that simulate growth as an increase in a linear measure of size (e.g., diameter, length, height) result in biased estimates of future mean biomass when uncertainty in growth is misrepresented. Our case study shows how models of tree growth that predict the same mean diameter increment, but with alternative representations of growth uncertainty, result in almost a threefold difference in the projections of future mean tree biomass after a 20-yr simulation. These results have important implications concerning our ability to accurately predict future biomass and all the related environmental services (e.g., forest carbon content, timber and fishery yields). If the objective is to predict future biomass, we strongly recommend that: (1) ecological modelers should choose a growth model based on a variable more linearly related to biomass (e.g., tree basal area instead of tree diameter for forest models); (2) if field measurements preclude the use of variables other than the linear measure of size, both the mean and other statistical moments (e.g., covariances) should be carefully modeled; (3) careful assessment be done on models that aggregate similar individuals (i.e., cohort models) to see if neglecting autocorrelated growth from individuals leads to biased estimates of future mean biomass.

  1. A method to estimate the biomass of Spirulina platensis cultivated on a solid medium.

    PubMed

    Pelizer, Lúcia Helena; Moraes, Iracema de Oliveira

    2014-01-01

    This paper presents a method to estimate the biomass of Spirulina cultivated on solid medium with sugarcane bagasse as a support, in view of the difficulty in determining biomass concentrations in bioprocesses, particularly those conducted in semi-solid or solid media. The genus Spirulina of the family Oscillatoriaceae comprises the group of multicellular filamentous cyanobacteria (blue-green microalgae). Spirulina is used as fish feed in aquaculture, as a food supplement, a source of vitamins, pigments, antioxidants and fatty acids. Therefore, its growth parameters are extremely important in studies of the development and optimization of bioprocesses. For studies of biomass growth, Spirulina platensis was cultured on solid medium using sugarcane bagasse as a support. The biomass thus produced was estimated by determining the protein content of the material grown during the process, based on the ratio of dry weight to protein content obtained in the surface growth experiments. The protein content of the biomass grown in Erlenmeyer flasks on surface medium was examined daily to check the influence of culture time on the protein content of the biomass. The biomass showed an average protein content of 42.2%. This methodology enabled the concentration of biomass adhering to the sugarcane bagasse to be estimated from the indirect measurement of the protein content associated with cell growth. PMID:25477928

  2. A method to estimate the biomass of Spirulina platensis cultivated on a solid medium

    PubMed Central

    Pelizer, Lúcia Helena; Moraes, Iracema de Oliveira

    2014-01-01

    This paper presents a method to estimate the biomass of Spirulina cultivated on solid medium with sugarcane bagasse as a support, in view of the difficulty in determining biomass concentrations in bioprocesses, particularly those conducted in semi-solid or solid media. The genus Spirulina of the family Oscillatoriaceae comprises the group of multicellular filamentous cyanobacteria (blue-green microalgae). Spirulina is used as fish feed in aquaculture, as a food supplement, a source of vitamins, pigments, antioxidants and fatty acids. Therefore, its growth parameters are extremely important in studies of the development and optimization of bioprocesses. For studies of biomass growth, Spirulina platensis was cultured on solid medium using sugarcane bagasse as a support. The biomass thus produced was estimated by determining the protein content of the material grown during the process, based on the ratio of dry weight to protein content obtained in the surface growth experiments. The protein content of the biomass grown in Erlenmeyer flasks on surface medium was examined daily to check the influence of culture time on the protein content of the biomass. The biomass showed an average protein content of 42.2%. This methodology enabled the concentration of biomass adhering to the sugarcane bagasse to be estimated from the indirect measurement of the protein content associated with cell growth. PMID:25477928

  3. Estimating total standing herbaceous biomass production with LANDSAT MSS digital data

    NASA Technical Reports Server (NTRS)

    Richardson, A. J.; Everitt, J. H.; Wiegand, C. L. (Principal Investigator)

    1982-01-01

    Rangeland biomass data were correlated with spectral vegetation indices, derived from LANDSAT MSS data. LANDSAT data from five range and three other land use sites in Willacv and Cameron Counties were collected on October 17 and December 10, 1975, and on July 31 and September 23, 1976. The overall linear correlation of total standing herbaceous biomass with the LANDSAT derived perpendicular vegetation index was highly significant (r = 0.90**) for these four dates. The standard error of estimate was 722 kg/ha. Biomass data were recorded for two of these range sites for 8 months (March through October) during the 1976 growing season. Standing green biomass accounted for most of the increase in herbage, starting in June and ending about September and October. These results indicate that satellite data may be useful for the estimation of total standing herbaceous biomass production that could aid range managers in assessing range condition and animal carrying capacities of large and inaccessible range holdings.

  4. [Estimation models of understory shrub biomass and their applications in red soil hilly region].

    PubMed

    Zeng, Hui-Qing; Liu, Qi-Jing; Feng, Zong-Wei; Ma, Ze-Qing; Hu, Li-Le

    2007-10-01

    With 16 familiar species of understory shrub at Qianyezhou ecological experimental station in red soil hilly region under Chinese Academy of Sciences as test objects, crown area (A(c)) and projected volume (V(c)) were used as the variables for building quadratic and power allometric equations, respectively, to estimate the biomass of individual populations, and mixed-model was used to estimate the biomass of the 16 species. The best-fit models were applied to estimate the biomass of understory shrub in different forest types. The results showed that the biomass of shrub layer varied significantly among different stand types. With species-specific models, the biomass in deciduous, secondary, and coniferous forests was estimated as 4 773, 3 175 and 733 kg x hm(-2), respectively; while with mixed model, the estimation result was a little lower, being 3 946, 2 772 and 840 kg x hm(-2), respectively. Under the conditions of species-specific models being not established, mixed model was more convenient and practical in estimating the biomass of understory shrub.

  5. Zooplankton biomass estimated from digitalized images in Antarctic waters: A calibration exercise

    NASA Astrophysics Data System (ADS)

    HernáNdez-León, Santiago; Montero, Irene

    2006-05-01

    The direct measurement of zooplankton biomass following the different analytical procedures normally requires the destruction of the samples. The use of conversion factors to estimate biomass from nondestructive methods is still a challenge. The widespread use of image analyzers and optical counters in biological oceanography provides a useful tool to measure the abundance and size spectrum of zooplanktonic organisms in real or quasi-real time. Both methodologies measure the equivalent spherical diameter and/or the body area of organisms. In order to estimate biomass from the highly valuable information generated by the size spectrum of the sample, we measured the relationship between individual body area and individual biomass of the most common species and groups of zooplankton in Antarctic waters. The slope of the regression for each different species and groups of taxa was not significantly different from that obtained by pooling all taxa, thus providing a general relationship for the entire size spectrum of zooplankton. The biomass estimated from the body area spectrum of samples obtained around the Antarctic Peninsula agreed with other measurements of biomass in the region. The proposed conversion factor could provide for rapid estimates of biomass of net-collected zooplankton from imaging devices or optical plankton counters.

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

    EPA Science Inventory

    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. Reliability of biomass burning estimates from savanna fires: Biomass burning in northern Australia during the 1999 Biomass Burning and Lightning Experiment B field campaign

    NASA Astrophysics Data System (ADS)

    Russell-Smith, Jeremy; Edwards, Andrew C.; Cook, Garry D.

    2003-02-01

    This paper estimates the two-daily extent of savanna burning and consumption of fine (grass and litter) fuels from an extensive 230,000 km2 region of northern Australia during August-September 1999 encompassing the Australian continental component of the Biomass Burning and Lightning Experiment B (BIBLE B) campaign [, 2002]. The extent of burning for the study region was derived from fire scar mapping of imagery from the advanced very high resolution radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) satellite. The mapping was calibrated and verified with reference to one Landsat scene and associated aerial transect validation data. Fine fuel loads were estimated using published fuel accumulation relationships for major regional fuel types. It is estimated that more than 43,000 km2 was burnt during the 25 day study period, with about 19 Mt of fine (grass and litter) fuels. This paper examines assumptions and errors associated with these estimates. It is estimated from uncalibrated fire mapping derived from AVHRR imagery that 417,500 km2 of the northern Australian savanna was burnt in 1999, of which 136,405 km2, or 30%, occurred in the Northern Territory study region. Using generalized fuel accumulation equations, such biomass burning consumed an estimated 212.3 Mt of fine fuels, but no data are available for consumption of coarse fuels. This figure exceeds a recent estimate, based on fine fuels only, for the combined Australian savanna and temperate grassland biomass burning over the period 1990-1999 but is lower than past estimates derived from classification approaches. We conclude that (1) fire maps derived from coarse-resolution optical imagery can be applied relatively reliably to estimate the extent of savanna fires, generally with 70-80% confidence using the approach adopted here, over the major burning period in northern Australia and (2) substantial further field assessment and associated modeling of fuel accumulation

  8. Potential application of multipolarization SAR for pine-plantation biomass estimation

    NASA Technical Reports Server (NTRS)

    Wu, Shih-Tseng

    1987-01-01

    This paper presents the technique and the potential utility of multipolarization Synthetic Aperture Radar (SAR) data for pine-plantation biomass estimation. Three channels of SAR data, one from the Shuttle Imaging Radar SIR-A and the other two from the aircraft SAR, were acquired over the Baldwin County, Alabama, study area. The SIR-A data were acquired with HH polarization and the aircraft SAR data with VV and VH polarizations. Linear regression techniques are used to estimate the pine-plantation biomass, tree height, and age using 21 test plots. The results indicate that the multipolarization data are highly related to the plantation biomass. The results suggest a potential application of multipolarization SAR for pine-plantation biomass estimation.

  9. Fresh Biomass Estimation in Heterogeneous Grassland Using Hyperspectral Measurements and Multivariate Statistical Analysis

    NASA Astrophysics Data System (ADS)

    Darvishzadeh, R.; Skidmore, A. K.; Mirzaie, M.; Atzberger, C.; Schlerf, M.

    2014-12-01

    Accurate estimation of grassland biomass at their peak productivity can provide crucial information regarding the functioning and productivity of the rangelands. Hyperspectral remote sensing has proved to be valuable for estimation of vegetation biophysical parameters such as biomass using different statistical techniques. However, in statistical analysis of hyperspectral data, multicollinearity is a common problem due to large amount of correlated hyper-spectral reflectance measurements. The aim of this study was to examine the prospect of above ground biomass estimation in a heterogeneous Mediterranean rangeland employing multivariate calibration methods. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of above ground biomass for 170 sample plots. Multivariate calibrations including partial least squares regression (PLSR), principal component regression (PCR), and Least-Squared Support Vector Machine (LS-SVM) were used to estimate the above ground biomass. The prediction accuracy of the multivariate calibration methods were assessed using cross validated R2 and RMSE. The best model performance was obtained using LS_SVM and then PLSR both calibrated with first derivative reflectance dataset with R2cv = 0.88 & 0.86 and RMSEcv= 1.15 & 1.07 respectively. The weakest prediction accuracy was appeared when PCR were used (R2cv = 0.31 and RMSEcv= 2.48). The obtained results highlight the importance of multivariate calibration methods for biomass estimation when hyperspectral data are used.

  10. [Estimation of Winter Wheat Biomass Using Visible Spectral and BP Based Artificial Neural Networks].

    PubMed

    Cui, Ri-xian; Liu, Ya-dong; Fu, Jin-dong

    2015-09-01

    The objective of this study was to evaluate the feasibility of using color digital image analysis and back propagation (BP) based artificial neural networks (ANN) method to estimate above ground biomass at the canopy level of winter wheat field. Digital color images of winter wheat canopies grown under six levels of nitrogen treatments were taken with a digital camera for four times during the elongation stage and at the same time wheat plants were sampled to measure above ground biomass. Canopy cover (CC) and 10 color indices were calculated from winter wheat canopy images by using image analysis program (developed in Microsoft Visual Basic). Correlation analysis was carried out to identify the relationship between CC, 10 color indices and winter wheat above ground biomass. Stepwise multiple linear regression and BP based ANN methods were used to establish the models to estimate winter wheat above ground biomass. The results showed that CC, and two color indices had a significant cor- relation with above ground biomass. CC revealed the highest correlation with winter wheat above ground biomass. Stepwise multiple linear regression model constituting CC and color indices of NDI and b, and BP based ANN model with four variables (CC, g, b and NDI) for input was constructed to estimate winter wheat above ground biomass. The validation results indicate that the model using BP based ANN method has a better performance with higher R2 (0.903) and lower RMSE (61.706) and RRMSE (18.876) in comparation with the stepwise regression model.

  11. Converting wood volume to biomass for pinyon and juniper. Forest Service research note

    SciTech Connect

    Chojnacky, D.C.; Moisen, G.G.

    1993-03-01

    A technique was developed to convert pinyon-juniper volume equation predictions to weights. The method uses specific gravity and biomass conversion equations to obtain foliage weight and total wood weight of all stems, branches, and bark. Specific gravity data are given for several Arizona pinyon-juniper species. Biomass conversion equations are constructed from pinyon-juniper data collected in Nevada. Results provide an interim means of estimating pinyon-juniper aboveground biomass from available volume inventory data.

  12. Estimation of potential maximum biomass of trout in Wyoming streams to assist management decisions

    USGS Publications Warehouse

    Hubert, W.A.; Marwitz, T.D.; Gerow, K.G.; Binns, N.A.; Wiley, R.W.

    1996-01-01

    Fishery managers can benefit from knowledge of the potential maximum biomass (PMB) of trout in streams when making decisions on the allocation of resources to improve fisheries. Resources are most likely to he expended on streams with high PMB and with large differences between PMB and currently measured biomass. We developed and tested a model that uses four easily measured habitat variables to estimate PMB (upper 90th percentile of predicted mean bid mass) of trout (Oncorhynchus spp., Salmo trutta, and Salvelinus fontinalis) in Wyoming streams. The habitat variables were proportion of cover, elevation, wetted width, and channel gradient. The PMB model was constructed from data on 166 stream reaches throughout Wyoming and validated on an independent data set of 50 stream reaches. Prediction of PMB in combination with estimation of current biomass and information on habitat quality can provide managers with insight into the extent to which management actions may enhance trout biomass.

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

    PubMed

    Manninen, Sirkku; Zverev, Vitali; Bergman, Igor; Kozlov, Mikhail V

    2015-12-01

    Boreal coniferous forests act as an important sink for atmospheric carbon dioxide. The overall tree carbon (C) sink in the forests of Europe has increased during the past decades, especially due to management and elevated nitrogen (N) deposition; however, industrial atmospheric pollution, primarily sulphur dioxide and heavy metals, still negatively affect forest biomass production at different spatial scales. We report local and regional changes in forest aboveground biomass, C and N concentrations in plant tissues, and C and N pools caused by long-term atmospheric emissions from a large point source, the nickel-copper smelter in Monchegorsk, in north-western Russia. An increase in pollution load (assessed as Cu concentration in forest litter) caused C to increase in foliage but C remained unchanged in wood, while N decreased in foliage and increased in wood, demonstrating strong effects of pollution on resource translocation between green and woody tissues. The aboveground C and N pools were primarily governed by plant biomass, which strongly decreased with an increase in pollution load. In our study sites (located 1.6-39.7 km from the smelter) living aboveground plant biomass was 76 to 4888 gm(-2), and C and N pools ranged 35-2333 g C m(-2) and 0.5-35.1 g N m(-2), respectively. We estimate that the aboveground plant biomass is reduced due to chronic exposure to industrial air pollution over an area of about 107,200 km2, and the total (aboveground and belowground) loss of phytomass C stock amounts to 4.24×10(13) g C. Our results emphasize the need to account for the overall impact of industrial polluters on ecosystem C and N pools when assessing the C and N dynamics in northern boreal forests because of the marked long-term negative effects of their emissions on structure and productivity of plant communities. PMID:26254064

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

    PubMed

    Manninen, Sirkku; Zverev, Vitali; Bergman, Igor; Kozlov, Mikhail V

    2015-12-01

    Boreal coniferous forests act as an important sink for atmospheric carbon dioxide. The overall tree carbon (C) sink in the forests of Europe has increased during the past decades, especially due to management and elevated nitrogen (N) deposition; however, industrial atmospheric pollution, primarily sulphur dioxide and heavy metals, still negatively affect forest biomass production at different spatial scales. We report local and regional changes in forest aboveground biomass, C and N concentrations in plant tissues, and C and N pools caused by long-term atmospheric emissions from a large point source, the nickel-copper smelter in Monchegorsk, in north-western Russia. An increase in pollution load (assessed as Cu concentration in forest litter) caused C to increase in foliage but C remained unchanged in wood, while N decreased in foliage and increased in wood, demonstrating strong effects of pollution on resource translocation between green and woody tissues. The aboveground C and N pools were primarily governed by plant biomass, which strongly decreased with an increase in pollution load. In our study sites (located 1.6-39.7 km from the smelter) living aboveground plant biomass was 76 to 4888 gm(-2), and C and N pools ranged 35-2333 g C m(-2) and 0.5-35.1 g N m(-2), respectively. We estimate that the aboveground plant biomass is reduced due to chronic exposure to industrial air pollution over an area of about 107,200 km2, and the total (aboveground and belowground) loss of phytomass C stock amounts to 4.24×10(13) g C. Our results emphasize the need to account for the overall impact of industrial polluters on ecosystem C and N pools when assessing the C and N dynamics in northern boreal forests because of the marked long-term negative effects of their emissions on structure and productivity of plant communities.

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

    SciTech Connect

    None, None

    2009-01-18

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

  16. [Band depth analysis and partial least square regression based winter wheat biomass estimation using hyperspectral measurements].

    PubMed

    Fu, Yuan-Yuan; Wang, Ji-Hua; Yang, Gui-Jun; Song, Xiao-Yu; Xu, Xin-Gang; Feng, Hai-Kuan

    2013-05-01

    The major limitation of using existing vegetation indices for crop biomass estimation is that it approaches a saturation level asymptotically for a certain range of biomass. In order to resolve this problem, band depth analysis and partial least square regression (PLSR) were combined to establish winter wheat biomass estimation model in the present study. The models based on the combination of band depth analysis and PLSR were compared with the models based on common vegetation indexes from the point of view of estimation accuracy, subsequently. Band depth analysis was conducted in the visible spectral domain (550-750 nm). Band depth, band depth ratio (BDR), normalized band depth index, and band depth normalized to area were utilized to represent band depth information. Among the calibrated estimation models, the models based on the combination of band depth analysis and PLSR reached higher accuracy than those based on the vegetation indices. Among them, the combination of BDR and PLSR got the highest accuracy (R2 = 0.792, RMSE = 0.164 kg x m(-2)). The results indicated that the combination of band depth analysis and PLSR could well overcome the saturation problem and improve the biomass estimation accuracy when winter wheat biomass is large.

  17. Belowground Biomass Sampling to Estimate Fine Root Mass across NEON Sites

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Production of belowground biomass is an important and relatively uncharacterized component of the net primary productivity (NPP) of ecosystems. Fine root productivity makes up a significant portion of total belowground production because fine roots turn over rapidly, and therefore contribute disproportionately to annual estimates of belowground net primary productivity (BNPP). One of the major goals of the National Ecological Observatory Network (NEON) is to quantify above- and below-ground NPP at 60 sites within 20 different eco-climactic regions. NEON's Terrestrial Observation System will carry out belowground biomass sampling throughout the life of the observatory to estimate fine root production. However, belowground biomass sampling during NEON operations will be constrained to a maximum depth of 50cm. This limited depth range leaves the question of what proportion of total fine root mass is being collected and how to optimally characterize belowground biomass given sampling depth limitations. During the construction period, NEON is characterizing fine root biomass distribution at depth down to 2m at each site, as well as physical and chemical properties in each soil horizon. Each sampling unit is a pit (2m deep and approximately 1.5m wide), dug in the site's dominant vegetation type where fine root biomass sampling will also occur during Operations. To sample fine root biomass in each pit, soil samples of a known volume are taken from three vertical profiles down the face of the pit. Samples are then wet sieved to extract fine root mass, and roots are dried at 65°C for 48 hours and then weighed. The soil pit data are used to estimate the proportion of total fine root biomass from each site as a function of depth. Non-linear curves are fitted to the data to calculate total fine root mass at depth and to provide estimates of the proportion of the total fine root mass that is sampled at each site during NEON's 30 year operational sampling. The belowground

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

    PubMed Central

    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

  19. Quantifying the differences between Amazon forest biomass maps: uncertainty to be tackled in carbon emission estimates

    NASA Astrophysics Data System (ADS)

    Ometto, J.; Soler, L.; Assis, T.; Lapola, D.; Aguiar, A. P.; Meir, P.

    2012-12-01

    The current methods adopted to estimate the spatial variation on above- and below-ground biomass in tropical forests, in particular the Brazilian Amazon, are usually based on remote sensing and coupled with scarce and, generally poorly distributed fieldwork measurements. There are notable differences between the resulting published biomass maps and this results in high uncertainty in calculated carbon emissions from deforestation, forest degradation and other changes in the land cover. These uncertainties are particularly critical when biomass maps are coded into biomass classes referring to a specific range of values. The Brazilian Amazon is the largest continuous tropical broadleaf forest in the globe, containing a substantial amount of carbon above and below the soil surface. Analysis of land use change has shown that deforestation in the region is a patchy process, comprising different intensities and dynamics in separate and adjacent areas, such that even if when characterized by broad patterns estimates of carbon emissions can become a complicated task unless spatially accurate biomass maps are available. In this paper we analyze the differences in recently published biomass maps of the Amazon region, considering as well the official information used by the Brazilian government for its communication to the United Framework on Climate Change Convention of the United Nations. From the average biomass at deforestation areas in two different periods (1997 and 2006), maps varied from +20% to -19% in the first period and from +20% to -15% in the later, highlighting the substantial differences in the overall biomass estimate, with clear reflect on carbon emissions in the region.

  20. Natural forest biomass estimation based on plantation information using PALSAR data.

    PubMed

    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.

  1. Estimating biomass, yield, evaprotranspiration and carbon fluxes for winter wheat by using high resolution remote sensing data combined with a crop model

    NASA Astrophysics Data System (ADS)

    Veloso, A.; Ceschia, E.; Demarez, V.

    2013-12-01

    The use of crop models allows simulating plant development, growth, yield, CO2 and water fluxes under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. Besides, monitoring spatial and temporal variation in water budget and amount of carbon fixed by these crops is an ultimate goal of earth climate change studies. We propose here an approach to estimate time courses of dry aboveground biomass (DAM), yield and evapotranspiration (ETR) for winter wheat by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. This model is then coupled with a ';carbon flux module' for estimating the components of the carbon budget (gross primary production (GPP), ecosystem respiration (Reco), ...). Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. For this work, we employed a unique set of Formosat-2 and SPOT images acquired from 2006 to 2011 in southwest France. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, biomass (NPP), grain yield and ETR. The carbon flux module simulates GPP, the autotrophic respiration (Ra) that is defined as the sum of plant growth and maintenance respiration and the heterotrophic respiration (Rh

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

    EPA Science Inventory

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

  3. Use of near infrared/red radiance ratios for estimating vegetation biomass and physiological status

    NASA Technical Reports Server (NTRS)

    Tucker, C. J.

    1977-01-01

    The application of photographic infrared/red (ir/red) reflectance or radiance ratios for the estimation of vegetation biomass and physiological status were investigated by analyzing in situ spectral reflectance data from experimental grass plots. Canopy biological samples were taken for total wet biomass, total dry biomass, leaf water content, dry green biomass, dry brown biomass, and total chlorophyll content at each sampling date. Integrated red and photographic infrared radiances were regressed against the various canopy or plot variables to determine the relative significance between the red, photographic infrared, and the ir/red ratio and the canopy variables. The ir/red ratio is sensitive to the photosynthetically active or green biomass, the rate of primary production, and actually measures the interaction between the green biomass and the rate of primary production within a given species type. The ir/red ratio resulted in improved regression significance over the red or the ir/radiances taken separately. Only slight differences were found between ir/red ratio, the ir-red difference, the vegetation index, and the transformed vegetation index. The asymptotic spectral radiance properties of the ir, red, ir/red ratio, and the various transformations were evaluated.

  4. Estimation of biomass and canopy height in bermudagrass, alfalfa, and wheat using ultrasonic, laser, and spectral sensors.

    PubMed

    Pittman, Jeremy Joshua; Arnall, Daryl Brian; Interrante, Sindy M; Moffet, Corey A; Butler, Twain J

    2015-01-28

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

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

    PubMed Central

    Pittman, Jeremy Joshua; Arnall, Daryl Brian; Interrante, Sindy M.; Moffet, Corey A.; Butler, Twain J.

    2015-01-01

    Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L.), bermudagrass [Cynodon dactylon (L.) Pers.], and wheat (Triticum aestivum L.) were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral) as compared to physical measurements (plate meter and meter stick) and the traditional harvest method (clipping). Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha−1, respectively), except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass < 0.79 t·ha−1) and greatest measured biomass (average percent error of 18% for harvester and quad harvested biomass >6.4 t·ha−1). These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation. PMID:25635415

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

    PubMed Central

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

    2016-01-01

    The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants. PMID:27304876

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

    PubMed

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

    2016-01-01

    The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants. PMID:27304876

  8. Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms. [Guyton, Oklahoma and Dalhart, Texas

    NASA Technical Reports Server (NTRS)

    Rosenthal, W. D.; Mcfarland, M. J.; Theis, S. W.; Jones, C. L. (Principal Investigator)

    1982-01-01

    Agricultural crop classification models using two or more spectral regions (visible through microwave) are considered in an effort to estimate biomass at Guymon, Oklahoma Dalhart, Texas. Both grounds truth and aerial data were used. Results indicate that inclusion of C, L, and P band active microwave data, from look angles greater than 35 deg from nadir, with visible and infrared data improve crop discrimination and biomass estimates compared to results using only visible and infrared data. The microwave frequencies were sensitive to different biomass levels. The K and C band were sensitive to differences at low biomass levels, while P band was sensitive to differences at high biomass levels. Two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass. It is implied that inclusion of active microwave sensors with visible and infrared sensors on future satellites could aid in crop discrimination and biomass estimation.

  9. Crowd-Sourced Calibration: The GEDI Strategy for Empirical Biomass Estimation Using Spaceborne Lidar

    NASA Astrophysics Data System (ADS)

    Dubayah, R.

    2015-12-01

    The central task in estimating forest biomass from spaceborne sensors is the development of calibration equations that relate observed forest structure to biomass at a variety of spatial scales. Empirical methods generally rely on statistical estimation or machine learning techniques where field-based estimates of biomass at the plot level are associated with post-launch observations of variables such as canopy height and cover. For global-scale mapping the process is complex and leads to a number of questions: How many calibrations are required to capture non-stationarity in the relationships? Where does one calibration begin and another end? Should calibrations be conditioned by biome? Vegetation type? Land-use? Post-launch calibrations lead to further complications, such as the requirement to have sufficient field plot data underneath potentially sparse satellite observations, spatial and temporal mismatches in scale between field plots and pixels, and geolocation uncertainty, both in the plots and the satellite data. The Global Ecosystem Dynamics Investigation (GEDI) is under development by NASA to estimate forest biomass. GEDI will deploy a multi-beam lidar on the International Space Station and provide billions of observations of forest structure per year. Because GEDI uses relatively small footprints, about 25 m diameter, post-launch calibration is exceptionally problematic for the reasons listed earlier. Instead, GEDI will use a kind of "crowd-sourced" calibration strategy where existing lidar observations and the corresponding plot biomass will be assembled from data contributed by the science community. Through a process of continuous updating, calibrations will be refined as more data is ingested. This talk will focus on the GEDI pre-launch calibration strategy and present initial progress on its development, and how it forms the basis for meeting mission biomass requirements.

  10. Evaluating analytical approaches for estimating pelagic fish biomass using simulated fish communities

    USGS Publications Warehouse

    Yule, Daniel L.; Adams, Jean V.; Warner, David M.; Hrabik, Thomas R.; Kocovsky, Patrick M.; Weidel, Brian C.; Rudstam, Lars G.; Sullivan, Patrick J.

    2013-01-01

    Pelagic fish assessments often combine large amounts of acoustic-based fish density data and limited midwater trawl information to estimate species-specific biomass density. We compared the accuracy of five apportionment methods for estimating pelagic fish biomass density using simulated communities with known fish numbers that mimic Lakes Superior, Michigan, and Ontario, representing a range of fish community complexities. Across all apportionment methods, the error in the estimated biomass generally declined with increasing effort, but methods that accounted for community composition changes with water column depth performed best. Correlations between trawl catch and the true species composition were highest when more fish were caught, highlighting the benefits of targeted trawling in locations of high fish density. Pelagic fish surveys should incorporate geographic and water column depth stratification in the survey design, use apportionment methods that account for species-specific depth differences, target midwater trawling effort in areas of high fish density, and include at least 15 midwater trawls. With relatively basic biological information, simulations of fish communities and sampling programs can optimize effort allocation and reduce error in biomass estimates.

  11. Survey estimates of fishable biomass following a mass mortality in an Australian molluscan fishery.

    PubMed

    Mayfield, S; McGarvey, R; Gorfine, H K; Peeters, H; Burch, P; Sharma, S

    2011-04-01

    Mass mortality events are relatively uncommon in commercially fished populations, but when they occur, they reduce production and degrade ecosystems. Observing and documenting mass mortalities is simpler than quantifying the impact on stocks, monitoring or predicting recovery, and re-establishing commercial fishing. Direct survey measures of abundance, distribution and harvestable biomass provide the most tenable approach to informing decisions about future harvests in cases where stock collapses have occurred because conventional methods have been disrupted and are less applicable. Abalone viral ganglioneuritis (AVG) has resulted in high levels of mortality across all length classes of blacklip abalone, Haliotis rubra Leach, off western Victoria, Australia, since May 2006. Commercial catches in this previously valuable fishery were reduced substantially. This paper describes the integration of research surveys with commercial fishermen's knowledge to estimate the biomass of abalone on AVG-impacted reefs. Experienced commercial abalone divers provided credible information on the precise locations of historical fishing grounds within which fishery-independent surveys were undertaken. Abalone density estimates remained low relative to pre-AVG levels, and total biomass estimates were similar to historical annual catch levels, indicating that the abalone populations have yet to adequately recover. Survey biomass estimates were incorporated into harvest decision tables and used with prior accumulated knowledge of the populations to determine a conservative harvest strategy for the fishery.

  12. Intercomparison of Near-Real-Time Biomass Burning Emissions Estimates Constrained by Satellite Fire Data

    EPA Science Inventory

    We compare biomass burning emissions estimates from four different techniques that use satellite based fire products to determine area burned over regional to global domains. Three of the techniques use active fire detections from polar-orbiting MODIS sensors and one uses detec...

  13. Estimating single-tree branch biomass of Norway spruce by airborne laser scanning

    NASA Astrophysics Data System (ADS)

    Hauglin, Marius; Dibdiakova, Janka; Gobakken, Terje; Næsset, Erik

    2013-05-01

    The use of forest biomass for bioenergy purposes, directly or through refinement processes, has increased in the last decade. One example of such use is the utilization of logging residues. Branch biomass constitutes typically a considerable part of the logging residues, and should be quantified and included in future forest inventories. Airborne laser scanning (ALS) is widely used when collecting data for forest inventories, and even methods to derive information at the single-tree level has been described. Procedures for estimation of single-tree branch biomass of Norway spruce using features derived from ALS data are proposed in the present study. As field reference data the dry weight branch biomass of 50 trees were obtained through destructive sampling. Variables were further derived from the ALS echoes from each tree, including crown volume calculated from an interpolated crown surface constructed with a radial basis function. Spatial information derived from the pulse vectors were also incorporated when calculating the crown volume. Regression models with branch biomass as response variable were fit to the data, and the prediction accuracy assessed through a cross-validation procedure. Random forest regression models were compared to stepwise and simple linear least squares models. In the present study branch biomass was estimated with a higher accuracy by the best ALS-based models than by existing allometric biomass equations based on field measurements. An improved prediction accuracy was observed when incorporating information from the laser pulse vectors into the calculation of the crown volume variable, and a linear model with the crown volume as a single predictor gave the best overall results with a root mean square error of 35% in the validation.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  15. Equations for estimating biomass of herbaceous and woody vegetation in early-successional southern Appalachian pine-hardwood forests. Forest Service research note

    SciTech Connect

    Elliott, K.J.; Clinton, B.D.

    1993-03-31

    Allometric equations were developed to predict aboveground dry weight of herbaceous and woody species on prescribe-burned sites in the Southern Appalachians. Best-fit least-square regression models were developed using diameter, height, or both, as the independent variables and dry weight as the dependent variable. Coefficients of determination for the selected total biomass models ranged from 0.620 to 0.992 for herbaceous species and from 0.698 to 0.999 for the wood species. Equations for foliage biomass generally had lower coefficients of determination than did equations for either stem or total biomass of woody species.

  16. Mapping Africa Biomass with MODIS Imagery

    NASA Astrophysics Data System (ADS)

    Laporte, N.; Baccini, A.; Houghton, R.

    2006-12-01

    Central Africa contains the second largest block of tropical forest remaining in the world, and is one of the largest carbon reservoirs on Earth. The carbon dynamics of the region differ substantially from other tropical forests because most deforestation and land use is associated with selective logging and small-scale landholders practicing traditional "slash-and-burn" agriculture. Despite estimates of 1-2 PgC/yr released to the atmosphere from tropical deforestation, the amount released from Central Africa is highly uncertain relative to the amounts released from other tropical forest areas. The uncertainty in carbon fluxes results from inadequate estimates of both rates of deforestation and standing stocks of carbon (forest biomass). Here we present new results mapping above-ground forest biomass for tropical Africa using machine learning techniques to integrate MODIS 1km spectral reflectance with forest inventory measurements to calibrate an empirical relationship. The derived forest biomass at each MODIS pixel shows the spatial distribution of forest biomass over the entire tropical forest region. The model has been tested in Uganda, Mali and part of Republic of Congo where field data were available. The regression tree model based on MODIS NBAR surface reflectance for Uganda, Mali and Republic of Congo explains 94 percent of the variance in above-ground biomass with a root mean square error (RMSE) of 27 Tons/ha. The approach shows promise for use of optical remote sensing data in mapping the spatial distribution of forest biomass across the region.

  17. A BIOMASS-BASED MODEL TO ESTIMATE THE PLAUSIBILITY OF EXOPLANET BIOSIGNATURE GASES

    SciTech Connect

    Seager, S.; Bains, W.; Hu, R.

    2013-10-01

    Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H{sub 2}S, CH{sub 4}, CH{sub 3}Cl, and DMS. We have applied the models to propose NH{sub 3} as a biosignature gas on a 'cold Haber World', a planet with a N{sub 2}-H{sub 2} atmosphere, and to demonstrate why gases such as CH{sub 3}Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such as CH{sub 4}, H{sub 2}S, and N{sub 2}O) produced from life that extracts energy from chemical potential energy gradients will always have false positives because geochemistry has the same gases to work with as life does, and gases (such as DMS and CH{sub 3}Cl) produced for secondary metabolic reasons are far less likely to have false positives but because of their highly specialized origin are more likely to be produced in small quantities. The biomass model estimates are valid to one or two orders of magnitude; the goal is an independent approach to testing whether a biosignature gas is plausible rather than a precise quantification of atmospheric biosignature gases and their corresponding biomasses.

  18. Fluorometric detection and estimation of fungal biomass on cultural heritage materials.

    PubMed

    Konkol, Nick; McNamara, Christopher J; Mitchell, Ralph

    2010-02-01

    A wide variety of cultural heritage materials are susceptible to fungal deterioration. The paper, canvas, and stone constituents of our cultural heritage are subjected to harmful physical and chemical processes as they are slowly consumed by fungi. Remediation of fungal contamination can be costly and risk further damage to cultural artifacts. Early detection of fungal growth would permit the use of relatively noninvasive treatments to remediate fungal contamination before visible or lasting damage to the object has occurred. Current methods used for the detection and measurement of microbial biomass, such as colony counts, microscopic biovolume estimation, and ergosterol analysis are expensive and time consuming, or are inappropriate for use with fungi. Beta-N-acetylhexosaminidase (3.2.1.52) activity provides a reliable estimation of fungal biomass in soil and on building materials. Adapted for use on cultural heritage materials' fluorogenic 4-methylumbelliferyl (MUF) labeled substrate N-acetyl-beta-d-glucosaminide (NAG) was used to detect beta-N-acetylhexosaminidase activity in the fungus Aspergillus niger. Fluorescence increased linearly with fungal biomass and the sensitivity of the assay was comparable to other biochemical techniques. The fluorometric assay was used to monitor fungal biomass on a variety of cultural heritage materials non-destructively, and without the introduction of chemicals or solvents to the surfaces.

  19. Estimation of Biomass and Carbon Stocks in Rubber Plantation Using Thaichote Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Charoenjit, Kitsanai; Zuddas, Pierpaolo; Allemand, Pascal

    2014-05-01

    This goal of study is to improve model for estimate biomass and carbon stocks of rubber plantation (clone RRIM 600) in sub-basin of mae num prasae, East Thailand with total area is 232 Km2. We mapped 2011 of the biomass and carbon stocks with the used of integrated Thaichote satellite imagery and field data. In order to tree girth prediction and tree density population, we applied the objected based image analysis (OBIA) which include image mining and modeling by linear multiple regression, then estimate biomass and carbon stocks in rubber plantation. The image mining includes spectral, vegetation, textural and mask information for modeling construction. We found an parameters of the Global Environmental Monitoring Index (GEMI) and texture of homogeneity, dissimilarity, contrast and variance were accepted relationship of tree girt prediction with R2 0.865. The total amount of biomass and carbon stocks in study area is 2,227 Kt and 991.5 KtC respectively. For summary of study area, the annual sequestered in 2011 is 121.3 tCO2 from the atmosphere and the rubber plantation at mature age stage (25 years) had highest capacity of sequestered at 33.53 tCO2 ha-1 yr-1.

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

    USGS Publications Warehouse

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

    2003-01-01

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

  1. Rainforest burning and the global carbon budget: Biomass, combustion efficiency, and charcoal formation in the Brazilian Amazon

    SciTech Connect

    Fearnside, P.M.; Leal, N. Jr.; Fernandes, F.M.

    1993-09-20

    Biomass present before and after burning was measured in forest cleared for pasture in a cattle ranch (Fazenda Dimona) near Manaus, Amazonas, Brazil. Aboveground dry weight biomass loading averaged 265 t ha{sup {minus}1} (standard deviation (SD) = 110, n = 6 quadrats) at Fazenda Dimonas. Postburn aboveground biomass loading was evaluated by cutting and weighing of 100 m{sup 2} quadrats and by line intersect sampling. Quadrats had a mean dry weight of 187 t ha{sup {minus}1} (SD = 69, n = 10), a 29.3% reduction from the preburn mean in the same clearing. Line intersect estimates in 1.65 km of transects indicated that 265 m{sup 3} ha{sup {minus}1} (approximately 164 t ha{sup {minus}1} of aboveground dry matter) survived burning. Using carbon contents measured for different biomass components (all {approximately} 50% carbon) and assuming a carbon content of 74.8% for charcoal (from other studies near Manaus), the destructive measurements imply a 27.6% reduction of aboveground carbon pools. Charcoal composed 2.5% of the dry weight of the remains in the postburn destructive quadrats and 2.8% of the volume in the line intersect transects. Thus approximately 2.7% of the preburn aboveground carbon stock was converted to charcoal, substantially less than is generally assumed in global carbon models. The findings confirm high values for biomass in central Amazonia. High variability indicates the need for further studies in many localities and for making maximum use of less laborious indirect methods of biomass estimation. While indirect methods are essential for regional estimates of average biomass, only direct weighing such as that reported here can yield information on combustion efficiency and charcoal formation. Both high biomass and low percentage of charcoal formation suggest the significant potential contribution of forest burning to global climate changes from CO{sub 2} and trace gases. 66 refs., 6 figs., 2 tabs.

  2. Nutrient subsidies to belowground microbes impact aboveground food web interactions.

    PubMed

    Hines, Jes; Megonigal, J Patrick; Denno, Robert F

    2006-06-01

    Historically, terrestrial food web theory has been compartmentalized into interactions among aboveground or belowground communities. In this study we took a more synthetic approach to understanding food web interactions by simultaneously examining four trophic levels and investigating how nutrient (nitrogen and carbon) and detrital subsidies impact the ability of the belowground microbial community to alter the abundance of aboveground arthropods (herbivores and predators) associated with the intertidal cord grass Spartina alterniflora. We manipulated carbon, nitrogen, and detrital resources in a field experiment and measured decomposition rate, soil nitrogen pools, plant biomass and quality, herbivore density, and arthropod predator abundance. Because carbon subsidies impact plant growth only indirectly (microbial pathways), whereas nitrogen additions both directly (plant uptake) and indirectly (microbial pathways) impact plant primary productivity, we were able to assess the effect of both belowground soil microbes and nutrient availability on aboveground herbivores and their predators. Herbivore density in the field was suppressed by carbon supplements. Carbon addition altered soil microbial dynamics (net potential ammonification, litter decomposition rate, DON [dissolved organic N] concentration), which limited inorganic soil nitrogen availability and reduced plant size as well as predator abundance. Nitrogen addition enhanced herbivore density by increasing plant size and quality directly by increasing inorganic soil nitrogen pools, and indirectly by enhancing microbial nitrification. Detritus adversely affected aboveground herbivores mainly by promoting predator aggregation. To date, the effects of carbon and nitrogen subsidies on salt marshes have been examined as isolated effects on either the aboveground or the belowground community. Our results emphasize the importance of directly addressing the soil microbial community as a factor that influences

  3. Bias in acoustic biomass estimates of Euphausia superba due to diel vertical migration

    NASA Astrophysics Data System (ADS)

    Demer, David A.; Hewitt, Roger P.

    1995-04-01

    The diel vertical migration (DVM) of Antarctic krill ( Euphausia superba) can greatly bias the results of qualitative and quantitative hydroacoustic surveys which are conducted with a down-looking sonar and irrespective of the time of day. To demonstrate and quantify these negative biases on both the estimates of biomass distribution and abundance, a time-depth-density analysis was performed. Data were collected, as part of the United States Antarctic Marine Living Resources Program (AMLR), in the vicinities of Elephant Island, Antarctica, during the austral summers of 1992 and 1993. Five surveys were conducted in 1992; two covered a 105 by 105 n.mi. area centered on Elephant Island, two encompassed a 60 by 35 n.mi. area immediately to the north of the Island, and one covered a 1 n.mi. 2 area centered on a large krill swarm to the west of Seal Island. The 1993 data include repetitions of the two small-area and two large-area surveys. Average krill volume densities were calculated for each hour as well as for three daily periods: day, twilight and night. These data were normalized and presented as a probability of daily average density. With spectral analysis to identify the frequencies of migration, a four-term periodic function was fitted to the probability density function of average daily biomass versus local apparent time. This function was transformed to create a temporal compensation function (TCF) for upwardly adjusting acoustic biomass estimates. The TCF was then applied to the original 1992 survey data; the resulting biomass estimates are an average of 49.5% higher than those calculated disregarding biases due to diel vertical migration. The effect of DVM on the estimates of krill distribution are illustrated by a comparison of compensated and uncompensated density maps of two 1992 surveys. Through this technique, high density kril areas are revealed where uncompensated maps indicated low densities.

  4. Enumeration and Biomass Estimation of Bacteria in Aquifer Microcosm Studies by Flow Cytometry

    PubMed Central

    DeLeo, P. C.; Baveye, P.

    1996-01-01

    Flow cytometry was used to enumerate and characterize bacteria from a sand column microcosm simulating aquifer conditions. Pure cultures of a species of Bacillus isolated from subsurface sediments or Bacillus megaterium were first evaluated to identify these organisms' characteristic histograms. Counting was then carried out with samples from the aquifer microcosms. Enumeration by flow cytometry was compared with more-traditional acridine orange direct counting. These two techniques gave statistically similar results. However, counting by flow cytometry, in this case, surveyed a sample size 700 times greater than did acridine orange direct counting (25 (mu)l versus 0.034 (mu)l) and required 1/10 the time (2 h versus 20 h). Flow cytometry was able to distinguish the same species of bacteria grown under different nutrient conditions, and it could distinguish changes in cell growth patterns, specifically single cell growth versus chained cell growth in different regions of an aquifer microcosm. A biomass estimate was calculated by calibrating the total fluorescence of a sample from a pure culture with the dry weight of a freeze-dried volume from the original pure culture. Growth conditions significantly affected histograms and biomass estimates, so the calibration was carried out with cells grown under conditions similar to those in the aquifer microcosm. Costs associated with using flow cytometry were minimal compared with the amount of time saved in counting cells and estimating biomass. PMID:16535470

  5. Matching the best viewing angle in depth cameras for biomass estimation based on poplar seedling geometry.

    PubMed

    Andújar, Dionisio; Fernández-Quintanilla, César; Dorado, José

    2015-06-04

    In energy crops for biomass production a proper plant structure is important to optimize wood yields. A precise crop characterization in early stages may contribute to the choice of proper cropping techniques. This study assesses the potential of the Microsoft Kinect for Windows v.1 sensor to determine the best viewing angle of the sensor to estimate the plant biomass based on poplar seedling geometry. Kinect Fusion algorithms were used to generate a 3D point cloud from the depth video stream. The sensor was mounted in different positions facing the tree in order to obtain depth (RGB-D) images from different angles. Individuals of two different ages, e.g., one month and one year old, were scanned. Four different viewing angles were compared: top view (0°), 45° downwards view, front view (90°) and ground upwards view (-45°). The ground-truth used to validate the sensor readings consisted of a destructive sampling in which the height, leaf area and biomass (dry weight basis) were measured in each individual plant. The depth image models agreed well with 45°, 90° and -45° measurements in one-year poplar trees. Good correlations (0.88 to 0.92) between dry biomass and the area measured with the Kinect were found. In addition, plant height was accurately estimated with a few centimeters error. The comparison between different viewing angles revealed that top views showed poorer results due to the fact the top leaves occluded the rest of the tree. However, the other views led to good results. Conversely, small poplars showed better correlations with actual parameters from the top view (0°). Therefore, although the Microsoft Kinect for Windows v.1 sensor provides good opportunities for biomass estimation, the viewing angle must be chosen taking into account the developmental stage of the crop and the desired parameters. The results of this study indicate that Kinect is a promising tool for a rapid canopy characterization, i.e., for estimating crop biomass

  6. Matching the Best Viewing Angle in Depth Cameras for Biomass Estimation Based on Poplar Seedling Geometry

    PubMed Central

    Andújar, Dionisio; Fernández-Quintanilla, César; Dorado, José

    2015-01-01

    In energy crops for biomass production a proper plant structure is important to optimize wood yields. A precise crop characterization in early stages may contribute to the choice of proper cropping techniques. This study assesses the potential of the Microsoft Kinect for Windows v.1 sensor to determine the best viewing angle of the sensor to estimate the plant biomass based on poplar seedling geometry. Kinect Fusion algorithms were used to generate a 3D point cloud from the depth video stream. The sensor was mounted in different positions facing the tree in order to obtain depth (RGB-D) images from different angles. Individuals of two different ages, e.g., one month and one year old, were scanned. Four different viewing angles were compared: top view (0°), 45° downwards view, front view (90°) and ground upwards view (−45°). The ground-truth used to validate the sensor readings consisted of a destructive sampling in which the height, leaf area and biomass (dry weight basis) were measured in each individual plant. The depth image models agreed well with 45°, 90° and −45° measurements in one-year poplar trees. Good correlations (0.88 to 0.92) between dry biomass and the area measured with the Kinect were found. In addition, plant height was accurately estimated with a few centimeters error. The comparison between different viewing angles revealed that top views showed poorer results due to the fact the top leaves occluded the rest of the tree. However, the other views led to good results. Conversely, small poplars showed better correlations with actual parameters from the top view (0°). Therefore, although the Microsoft Kinect for Windows v.1 sensor provides good opportunities for biomass estimation, the viewing angle must be chosen taking into account the developmental stage of the crop and the desired parameters. The results of this study indicate that Kinect is a promising tool for a rapid canopy characterization, i.e., for estimating crop biomass

  7. Biomass and estimated production properties of size-fractionated zooplankton in the Yellow Sea, China

    NASA Astrophysics Data System (ADS)

    Huo, Yuanzi; Sun, Song; Zhang, Fang; Wang, Minxiao; Li, Chaolun; Yang, Bo

    2012-06-01

    The size-fractionated zooplankton biomass, taxonomic composition, and production calculated by formulas basing on Ikeda-Motoda's physiological methods were studied on the basis of samples taken from six cruises in the Yellow Sea. Zooplankton was size-fractionated using sieves into ~ 2 mm, 1-2 mm, 0.5-1 mm, 0.25-0.5 mm and 0.16-0.25 mm groups. The results showed that the average zooplankton biomass was 84.03 mg DM m- 3 in May, followed in order by September, June, March, August and December with 42.34, 38.36, 32.37, 27.17 and 21.83 mg DM m- 3, respectively. The contribution of ~ 2 mm, 1-2 mm, 0.5-1 mm, 0.25-0.5 mm and 0.16-0.25 mm groups to the total biomass was in the range of 15.2-27.4%, 13.2-29.4%, 14.7-18.2%, 15.8-22.6% and 16.3-34.2%, respectively, during the investigating period. The biomass of all size groups was all highest in May, and except that the biomass of 0.16-0.25 mm group was lowest in August, the biomass of other size groups was lowest in December. The dominant zooplankton species (or taxa) in each group were similar between six cruises. The estimated zooplankton production was highest in May with 1.97 mg C m- 3 d- 1, and was lowest in December with 0.51 mg C m- 3 d- 1, and was in the range of 0.67-1.44 mg C m- 3 d- 1 in other investigating months. The estimated annual zooplankton production was 0.37 g C m- 3 y- 1. The two smallest groups aggregately comprised 59-84% of the net-zooplankton production in the Yellow Sea. The geographical distribution of size-fractionated zooplankton biomass and production was significantly affected by the complex physical features of the Yellow Sea. When the Yellow Sea Cold Bottom Water appeared from June to September, the biomass and production of zooplankton larger than 1 mm were higher inside the cold water mass area than outside it, while the zooplankton smaller than 1 mm showed contrary results. The higher biomass and production of all zooplankton groups occurred in the southern part of the study area in

  8. Soil water content determination with cosmic-ray neutron sensor: Correcting aboveground hydrogen effects with thermal/fast neutron ratio

    NASA Astrophysics Data System (ADS)

    Tian, Zhengchao; Li, Zizhong; Liu, Gang; Li, Baoguo; Ren, Tusheng

    2016-09-01

    The cosmic-ray neutron sensor (CRNS), which estimates field scale soil water content, bridges the gap between point measurement and remote sensing. The accuracy of CRNS measurements, however, is affected by additional hydrogen pools (e.g., vegetation, snow, and rainfall interception). The objectives of this study are to: (i) evaluate the accuracy of CRNS estimates in a farmland system using depth and horizontal weighted point measurements, (ii) introduce a novel method for estimating the amounts of hydrogen from biomass and snow cover in CRNS data, and (iii) propose a simple approach for correcting the influences of aboveground hydrogen pool (expressed as aboveground water equivalent, AWE) on CRNS measurements. A field experiment was conducted in northeast China to compare soil water content results from CRNS to in-situ data with time domain reflectometry (TDR) and neutron probe (NP) in the 0-40 cm soil layers. The biomass water equivalent (BWE) and snow water equivalent (SWE) were observed to have separate linear relationships with the thermal/fast neutron ratio, and the dynamics of BWE and SWE were estimated correctly in the crop seasons and snow-covered seasons, respectively. A simple approach, which considered the AWE, AWE at calibration, and the effective measurement depth of CRNS, was introduced to correct the errors caused by BWE and SWE. After correction, the correlation coefficients between soil water contents determined by CRNS and TDR were 0.79 and 0.77 during the 2014 and 2015 crop seasons, respectively, and CRNS measurements had RMSEs of 0.028, 0.030, and 0.039 m3 m-3 in the 2014 and 2015 crop seasons and the snow-covered seasons, respectively. The experimental results also indicated that the accuracies of CRNS estimated BWE and SWE were affected by the distributions of aboveground hydrogen pools, which were related to the height of the CRNS device above ground surface.

  9. Estimation of cell volume and biomass of penicillium chrysogenum using image analysis.

    PubMed

    Packer, H L; Keshavarz-Moore, E; Lilly, M D; Thomas, C R

    1992-02-20

    A methodology for the estimation of biomass for the penicillin fermentation using image analysis is presented. Two regions of hyphae are defined to describe the growth of mycelia during fermentation: (1) the cytoplasmic region, and (2) the degenerated region including large vacuoles. The volume occupied by each of these regions in a fixed volume of sample is estimated from area measurements using image analysis. Areas are converted to volumes by treating the hyphae as solid cylinders with the hyphal diameter as the cylinder diameter. The volumes of the cytoplasmic and degenerated regions are converted into dry weight estimations using hyphal density values available from the literature. The image analysis technique is able to estimate biomass even in the presence of nondissolved solids of a concentration of up to 30 gL(-1). It is shown to estimate successfully concentrations of mycelia from 0.03 to 38 gL(-1). Although the technique has been developed for the penicillin fermentation, it should be applicable to other (nonpellected) fungal fermentations.

  10. Estimation of Forest Biomass Increment Using Tree-ring data and Hydro-Ecological Modeling in a Rugged Forested Landscape

    NASA Astrophysics Data System (ADS)

    Lee, B.; Kang, S.; Kim, E.; Kim, Y.

    2006-12-01

    Terrestrial carbon sequestration by forest biomass is an important component of global carbon cycle, which is closely related to the greenhouse effect and climate system. Many researchers have studied on how to estimate forest biomass accurately and they utilized various methods including ecological modeling, remote sensing, and field measurements. However, it is still highly uncertain to estimate the forest biomass accurately and predict the future change. In particular, where water limitation is likely expected, carbon and water relations should be considered importantly in predicting vegetation primary production. The main objective of this study is to estimate biomass increments in the Gwangneung Experimental Forest (GEF) and to compare them with the simulation results of RHESSys, a GIS-based hydro-ecological model designed to simulate water and nutrient fluxes. We measured biomass and to estimate biomass increments using tree-ring data from 1991 to 2004, and they were calculated by using the single tree biomass equation. Average biomass increment during the study period was 271.38 g C m-2yr-1. RHESSys simulations need to a certain number of years to allow carbon and nitrogen stores to stabilize (spin up), which provides initial condition of the model simulation from 1991 to 2004. The data of Leaf Area Index (LAI) and daily stream discharge were used for model calibration. In addition, the results of biomass increment measurement from 1991 to 1997 in GEF were used for model parameterization, and those from 1998 to 2004 were used for validation. Our preliminary simulation results indicated that the simulation results of RHESSys model on the biomass increment was reasonably accurate, but in order to improve the prediction accuracy of this model, we concluded that various efforts on model verification and field data collection are required. *Keyword: Biomass increment, Hydro-Ecological Model. *Acknowledgement : This work was supported by the 2nd phase Brain Korea

  11. Comparing new and conventional methods to estimate benthic algal biomass and composition in freshwaters.

    PubMed

    Kahlert, Maria; McKie, Brendan G

    2014-11-01

    We compared conventional microscope-based methods for quantifying biomass and community composition of stream benthic algae with output obtained for these parameters from a new instrument (the BenthoTorch), which measures fluorescence of algal pigments in situ. Benthic algae were studied in 24 subarctic oligotrophic (1.7-26.9, median 7.2 μg total phosphorus L(-1)) streams in Northern Sweden. Readings for biomass of the total algal mat, quantified as chlorophyll a, did not differ significantly between the BenthoTorch (median 0.52 μg chlorophyll a cm(-2)) and the conventional method (median 0.53 μg chlorophyll a cm(-2)). However, quantification of community composition of the benthic algal mat obtained using the BenthoTorch did not match those obtained from conventional methods. The BenthoTorch indicated a dominance of diatoms, whereas microscope observations showed a fairly even distribution between diatoms, blue-green algae (mostly nitrogen-fixing) and green algae (mostly large filamentous), and also detected substantial biovolumes of red algae in some streams. These results most likely reflect differences in the exact parameters quantified by the two methods, as the BenthoTorch does not account for variability in cell size and the presence of non-chlorophyll bearing biomass in estimating the proportion of different algal groups, and does not distinguish red algal chlorophyll from that of other algal groups. Our findings suggest that the BenthoTorch has utility in quantifying biomass expressed as μg chlorophyll a cm(-2), but its output for the relative contribution of different algal groups to benthic algal biomass should be used with caution. PMID:25277172

  12. First Estimates of the Radiative Forcing of Aerosols Generated from Biomass Burning using Satellite Data

    NASA Technical Reports Server (NTRS)

    Chistopher, Sundar A.; Kliche, Donna V.; Chou, Joyce; Welch, Ronald M.

    1996-01-01

    Collocated measurements from the Advanced Very High Resolution Radiometer (AVHRR) and the Earth Radiation Budget Experiment (ERBE) scanner are used to examine the radiative forcing of atmospheric aerosols generated from biomass burning for 13 images in South America. Using the AVHRR, Local Area Coverage (LAC) data, a new technique based on a combination of spectral and textural measures is developed for detecting these aerosols. Then, the instantaneous shortwave, longwave, and net radiative forcing values are computed from the ERBE instantaneous scanner data. Results for the selected samples from 13 images show that the mean instantaneous net radiative forcing for areas with heavy aerosol loading is about -36 W/sq m and that for the optically thin aerosols are about -16 W/sq m. These results, although preliminary, provide the first estimates of radiative forcing of atmospheric aerosols from biomass burning using satellite data.

  13. First Estimates of the Radiative Forcing of Aerosols Generated from Biomass Burning Using Satellite Data

    NASA Technical Reports Server (NTRS)

    Christopher, Sundar A.; Kliche, Donna A.; Chou, Joyce; Welch, Ronald M.

    1996-01-01

    Collocated measurements from the Advanced Very High Resolution Radiometer (AVHRR) and the Earth Radiation Budget Experiment (ERBE) scanner are used to examine the radiative forcing of atmospheric aerosols generated from biomass burning for 13 images in South America. Using the AVHRR, Local Area Coverage (LAC) data, a new technique based on a combination of spectral and textural measures is developed for detecting these aerosols. Then, the instantaneous shortwave, longwave, and net radiative forcing values are computed from the ERBE instantaneous scanner data. Results for the selected samples from 13 images show that the mean instantaneous net radiative forcing for areas with heavy aerosol loading is about -36 W/sq m and that for the optically thin aerosols are about -16 W/sq m. These results, although preliminary, provide the first estimates of radiative forcing of atmospheric aerosols from biomass burning using satellite data.

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

    PubMed

    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

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

    PubMed

    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

  16. Estimating Consumption to Biomass Ratio in Non-Stationary Harvested Fish Populations

    PubMed Central

    Wiff, Rodrigo; Roa-Ureta, Ruben H.; Borchers, David L.; Milessi, Andrés C.; Barrientos, Mauricio A.

    2015-01-01

    The food consumption to biomass ratio (C) is one of the most important population parameters in ecosystem modelling because its quantifies the interactions between predator and prey. Existing models for estimating C in fish populations are per-recruit cohort models or empirical models, valid only for stationary populations. Moreover, empirical models lack theoretical support. Here we develop a theory and derive a general modelling framework to estimate C in fish populations, based on length frequency data and the generalised von Bertalanffy growth function, in which models for stationary populations with a stable-age distributions are special cases. Estimates using our method are compared with estimates from per-recruit cohort models for C using simulated harvested fish populations of different lifespans. The models proposed here are also applied to three fish populations that are targets of commercial fisheries in southern Chile. Uncertainty in the estimation of C was evaluated using a resampling approach. Simulations showed that stationary and non-stationary population models produce different estimates for C and those differences depend on the lifespan, fishing mortality and recruitment variations. Estimates of C using the new model exhibited smoother inter-annual variation in comparison with a per-recruit model estimates and they were also smaller than C predicted by the empirical equations in all population assessed. PMID:26528721

  17. Estimating Consumption to Biomass Ratio in Non-Stationary Harvested Fish Populations.

    PubMed

    Wiff, Rodrigo; Roa-Ureta, Ruben H; Borchers, David L; Milessi, Andrés C; Barrientos, Mauricio A

    2015-01-01

    The food consumption to biomass ratio (C) is one of the most important population parameters in ecosystem modelling because its quantifies the interactions between predator and prey. Existing models for estimating C in fish populations are per-recruit cohort models or empirical models, valid only for stationary populations. Moreover, empirical models lack theoretical support. Here we develop a theory and derive a general modelling framework to estimate C in fish populations, based on length frequency data and the generalised von Bertalanffy growth function, in which models for stationary populations with a stable-age distributions are special cases. Estimates using our method are compared with estimates from per-recruit cohort models for C using simulated harvested fish populations of different lifespans. The models proposed here are also applied to three fish populations that are targets of commercial fisheries in southern Chile. Uncertainty in the estimation of C was evaluated using a resampling approach. Simulations showed that stationary and non-stationary population models produce different estimates for C and those differences depend on the lifespan, fishing mortality and recruitment variations. Estimates of C using the new model exhibited smoother inter-annual variation in comparison with a per-recruit model estimates and they were also smaller than C predicted by the empirical equations in all population assessed.

  18. [Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite].

    PubMed

    Yu, Chao; Chen, Liang-fu; Li, Shen-shen; Tao, Jin-hua; Su, Lin

    2015-03-01

    Biomass burning makes up an important part of both trace gases and particulate matter emissions, which can efficiently degrade air quality and reduce visibility, destabilize the global climate system at regional to global scales. Burned area is one of the primary parameters necessary to estimate emissions, and considered to be the largest source of error in the emission inventory. Satellite-based fire observations can offer a reliable source of fire occurrence data on regional and global scales, a variety of sensors have been used to detect and map fires in two general approaches: burn scar mapping and active fire detection. However, both of the two approaches have limitations. In this article, we explore the relationship between hotspot data and burned area for the Southeastern United States, where a significant amount of biomass burnings from both prescribed and wild fire took place. MODIS (Moderate resolution imaging spectrometer) data, which has high temporal-resolution, can be used to monitor ground biomass. burning in time and provided hot spot data in this study. However, pixel size of MODIS hot spot can't stand for the real ground burned area. Through analysis of the variation of vegetation band reflectance between pre- and post-burn, we extracted the burned area from Landsat-5 TM (Thematic Mapper) images by using the differential normalized burn ratio (dNBR) which is based on TM band4 (0.84 μm) and TM band 7(2.22 μm) data. We combined MODIS fire hot spot data and Landsat-5 TM burned scars data to build the burned area estimation model, results showed that the linear correlation coefficient is 0.63 and the relationships vary as a function of vegetation cover. Based on the National Land Cover Database (NLCD), we built burned area estimation model over different vegetation cover, and got effective burned area per fire pixel, values for forest, grassland, shrub, cropland and wetland are 0.69, 1.27, 0.86, 0.72 and 0.94 km2 respectively. We validated the

  19. [Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite].

    PubMed

    Yu, Chao; Chen, Liang-fu; Li, Shen-shen; Tao, Jin-hua; Su, Lin

    2015-03-01

    Biomass burning makes up an important part of both trace gases and particulate matter emissions, which can efficiently degrade air quality and reduce visibility, destabilize the global climate system at regional to global scales. Burned area is one of the primary parameters necessary to estimate emissions, and considered to be the largest source of error in the emission inventory. Satellite-based fire observations can offer a reliable source of fire occurrence data on regional and global scales, a variety of sensors have been used to detect and map fires in two general approaches: burn scar mapping and active fire detection. However, both of the two approaches have limitations. In this article, we explore the relationship between hotspot data and burned area for the Southeastern United States, where a significant amount of biomass burnings from both prescribed and wild fire took place. MODIS (Moderate resolution imaging spectrometer) data, which has high temporal-resolution, can be used to monitor ground biomass. burning in time and provided hot spot data in this study. However, pixel size of MODIS hot spot can't stand for the real ground burned area. Through analysis of the variation of vegetation band reflectance between pre- and post-burn, we extracted the burned area from Landsat-5 TM (Thematic Mapper) images by using the differential normalized burn ratio (dNBR) which is based on TM band4 (0.84 μm) and TM band 7(2.22 μm) data. We combined MODIS fire hot spot data and Landsat-5 TM burned scars data to build the burned area estimation model, results showed that the linear correlation coefficient is 0.63 and the relationships vary as a function of vegetation cover. Based on the National Land Cover Database (NLCD), we built burned area estimation model over different vegetation cover, and got effective burned area per fire pixel, values for forest, grassland, shrub, cropland and wetland are 0.69, 1.27, 0.86, 0.72 and 0.94 km2 respectively. We validated the

  20. Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms, volume 2. [Oklahoma and Texas

    NASA Technical Reports Server (NTRS)

    Rosenthal, W. D.; Mcfarland, M. J.; Theis, S. W.; Jones, C. L. (Principal Investigator)

    1982-01-01

    Agricultural crop classification models using two or more spectral regions (visible through microwave) were developed and tested and biomass was estimated by including microwave with visible and infrared data. The study was conducted at Guymon, Oklahoma and Dalhart, Texas utilizing aircraft multispectral data and ground truth soil moisture and biomass information. Results indicate that inclusion of C, L, and P band active microwave data from look angles greater than 35 deg from nadir with visible and infrared data improved crop discrimination and biomass estimates compared to results using only visible and infrared data. The active microwave frequencies were sensitive to different biomass levels. In addition, two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass.

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

    NASA Astrophysics Data System (ADS)

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

    1982-08-01

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

  2. Estimating Above Ground Biomass using LiDAR in the Northcoast Redwood Forests

    NASA Astrophysics Data System (ADS)

    Rao, M.; Stewart, E.

    2010-12-01

    In recent years, LiDAR (Light Intensity Detection Amplification and Ranging) is increasingly being used in estimating biophysical parameters related to forested environments. The main goal of the project is to estimate long-term biomass accumulation and carbon sequestration potential of the redwoods ecosystem. The project objectives are aimed at providing an assessment of carbon pools within the redwood ecosystem. Specifically, we intend to develop a relational model based on LiDAR-based canopy estimates and extensive ground-based measurements available for the old-growth redwood forest located within the Prairie Creek Redwoods State Park, CA. Our preliminary analysis involved developing a geospatial database, including LiDAR data collected in 2007 for the study site, and analyzing the data using USFS Fusion software. The study area comprised of a 12-acres section of coastal redwood (Sequoia sempervirens) in the Prairie Creek Redwoods State Park, located in Orick, CA. A series of analytical steps were executed using the USFS FUSION software to produce some intermediate data such as bare earth model, canopy height model, canopy coverage model, and canopy maxima treelist. Canopy maxima tree tops were compared to ground layer to determine height of tree tops. A total of over 1000 trees were estimated, and then with thinning (to eliminate errors due to low vegetation > 3 meters tall), a total of 950 trees were delineated. Ground measurements were imported as a point based shapefile and then compared to the treetop heights created from LiDAR data to the actual ground referenced data. The results were promising as most estimated treetops were within 1-3 meters of the ground measurements and generally within 3-5m of the actual tree height. Finally, we are in the process of applying some allometric equations to estimate above ground biomass using some of the LiDAR-derived canopy metrics.

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

    NASA Technical Reports Server (NTRS)

    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

  4. A Bayesian geostatistical estimation of biomass in semi-arid rangelands by combining airborne and terrestrial laser scanning data

    NASA Astrophysics Data System (ADS)

    Li, A.; Glenn, N. F.

    2012-12-01

    Biomass of vegetation is critical for carbon cycle research. Estimating biomass from field survey data is laborious and/or destructive and thus retrieving biomass from remote sensing data may be advantageous. Most remote sensing biomass studies have focused on forest ecosystems, while few have focused on low stature vegetation, such as grasses in semi-arid environments. Biomass estimates for grass are significant for studying wildlife habitat, assessing fuel loads, and studying climate change response in semi-arid regions. Recent research has demonstrated the ability of small footprint airborne laser scanning (ALS) data to extract sagebrush height characteristics and the ability of terrestrial laser scanning (TLS) data to estimate vegetation volume over semi-arid rangelands. ALS has somewhat lower resolution than TLS, but has improved spatial coverage over TLS. Combining ALS and TLS is a powerful tool to estimate biomass on regional scales. Bayesian geostatistics, also known as Bayesian Maximum Entropy (BME), can fuse multiple data sources across scales and provide estimation uncertainties for the integration of ALS and TLS data for grass biomass. Regression models are used to approximately delineate the relationship between field biomass measurements and TLS derived height and shape metrics. We then consider TLS plot-level data at the point scale with ALS data at the area scale. The regularization method is utilized to establish the scaling relations between TLS-derived and ALS-derived metrics. The metric maps from the ALS level are reconstructed using a BME method based on regularized variograms. We gain biomass and estimation uncertainty on the regional scale by introducing updated metrics into the model. In order to evaluate the effectiveness of the BME method, we develop simple independent regression models by assuming the TLS-derived metrics as ground reference data. Therefore, the regression model is used to correct the ALS-estimated values and we retrieve

  5. Statistical Estimates of the Long-Term Impact of Land-Use Disturbance on Woody Biomass in the Midwest (USA)

    NASA Astrophysics Data System (ADS)

    McLachlan, J. S.; Moore, D. J.; Zhu, J.; Feng, X.; Paciorek, C. J.; Williams, J. W.; Goring, S. J.; Hartfield, K. A.

    2014-12-01

    The impact on carbon balance of land-use transformations in eastern North America since the time of Euroamerican settlement is important at the global scale. And yet, our understanding of the baseline conditions of pre-settlement vegetation is generally weak. Many estimates of terrestrial carbon pools before Euroamerican settlement are based on hypothetical potential vegetation, and even data-derived estimates of biomass do not have statistical estimates of uncertainty. We fit a spatial statistical model to forest survey (PLS) data from the time of settlement across Midwesterm states from Minnesota to Indiana. Our spatial model scales diameter data from the PLS surveys by standard allometries to produce maps at 8km resolution of biomass with associated uncertainty for all major tree taxa and plant functional types and for total woody biomass. General trends in biomass are consistent with previous estimates, but fine scale heterogeneity is more revealed in our biomass product. A full accounting of uncertainty in settlement-era biomass allows us to assess the extent to which biomass has recovered across a vegetation gradient from subboreal forests to oak savannas and prairies and across land-use histories ranging from preserved old-growth forests through areas reforesting after intensive logging and agriculture to areas currently experiencing a range of intensive human activity.

  6. Satellite Estimates of the Direct Radiative Forcing of Biomass Burning Aerosols Over South America and Africa

    NASA Technical Reports Server (NTRS)

    Christopher, Sundar A.; Wang, Min; Kliche, Donna V.; Berendes, Todd; Welch, Ronald M.; Yang, S.K.

    1997-01-01

    Atmospheric aerosol particles, both natural and anthropogenic are important to the earth's radiative balance. Therefore it is important to provide adequate validation information on the spatial, temporal and radiative properties of aerosols. This will enable us to predict realistic global estimates of aerosol radiative effects more confidently. The current study utilizes 66 AVHRR LAC (Local Area Coverage) and coincident Earth Radiation Budget Experiment (ERBE) images to characterize the fires, smoke and radiative forcings of biomass burning aerosols over four major ecosystems of South America.

  7. Estimating fresh grass/herb biomass from HYMAP data using the red edge position

    NASA Astrophysics Data System (ADS)

    Cho, Moses A.; Sobhan, Istiak M.; Skidmore, Andrew K.

    2006-08-01

    Remote sensing of grass/herb quantity is essential for rangeland management of livestock and wildlife. Spectral indices such as NDVI, determined from red and near infrared bands are affected by variable soil and atmospheric conditions and saturate in dense vegetation. Alternatively, the wavelength of maximum slope in the red-NIR transition, termed the red edge position (REP) has potential to mitigate these effects. But the utility of the REP using air- and space-borne imagery is determined by the availability of narrow bands in the region of the red edge and the simplicity of the extraction method. Very recently, we proposed a simple technique for extracting the REP called the linear extrapolation method [Cho and Skidmore, Remote Sens. Environ., 101(2006)118.]. The purpose of this study was to evaluate the potential of the linear extrapolation method for estimating fresh grass/herb biomass and compare its performance with the four-point linear interpolation and three-point Lagrangian interpolation methods. The REPs were derived from atmospherically corrected HYMAP images collected over Majella National Park, Italy in July 2004. The predictive capabilities of various REP linear regression models were evaluated using leave-one-out cross validation and test set validation methods. For both validation methods, the linear extrapolation REP models produced higher correlations with grass/herb biomass and lower prediction errors compared with the linear interpolation and Lagrangian REP models. This study demonstrates the potential of REPs extracted by the linear extrapolation method using HYMAP data for estimating fresh grass/herb biomass.

  8. Density and Biomass Estimates by Removal for an Amazonian Crocodilian, Paleosuchus palpebrosus

    PubMed Central

    2016-01-01

    Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians. PMID:27224473

  9. Density and Biomass Estimates by Removal for an Amazonian Crocodilian, Paleosuchus palpebrosus.

    PubMed

    Campos, Zilca; Magnusson, William E

    2016-01-01

    Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians.

  10. Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

    NASA Technical Reports Server (NTRS)

    Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

    2013-01-01

    Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI

  11. Estimates of bacterial growth from changes in uptake rates and biomass.

    PubMed Central

    Kirchman, D; Ducklow, H; Mitchell, R

    1982-01-01

    Rates of nucleic acid synthesis have been used to examine microbiol growth in natural waters. These rates are calculated from the incorporation of [3H]adenine and [3H]thymidine for RNA and DNA syntheses, respectively. Several additional biochemical parameters must be measured or taken from the literature to estimate growth rates from the incorporation of the tritiated compounds. We propose a simple method of estimating a conversion factor which obviates measuring these biochemical parameters. The change in bacterial abundance and incorporation rates of [3H]thymidine was measured in samples from three environments. The incorporation of exogenous [3H]thymidine was closely coupled with growth and cell division as estimated from the increase in bacterial biomass. Analysis of the changes in incorporation rates and initial bacterial abundance yielded a conversion factor for calculating bacterial production rates from incorporation rates. Furthermore, the growth rate of only those bacteria incorporating the compound can be estimated. The data analysis and experimental design can be used to estimate the proportion of nondividing cells and to examine changes in cell volumes. PMID:6760812

  12. Canopy Vertical Spatial Scales which Constrain Biomass in a Tropical Forest at the Plot Level: Unifying Lidar and InSAR for Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Treuhaft, R. N.; Goncalves, F. G.; Drake, J. B.; Chapman, B. D.; Dos Santos, J. R.; Dutra, L. V.; Graca, P. M.; Purcell, G. H.

    2009-12-01

    Structural remote sensing of forest biomass, using lidar and/or interferometric synthetic aperture radar (InSAR), often involves regressing field measured biomass against remotely sensed characteristics of the vertical density profile. Because spaceborne lidar or InSAR sensors will estimate structural characteristics averaged at the plot level (0.04-1 hectare), and because tropical forests contain 40% of the Earth’s forested biomass, this study focuses on the scales of vertical characteristics which best correlate with tropical forest biomass. This work suggests that the structural characteristics used in both lidar and InSAR biomass estimation, such as mean height or total height or height of median energy, are based on the behavior of Fourier vertical frequency components of vegetation density near zero frequency; that is, they are very low-spatial frequency characteristics of the vertical vegetation distribution. In this work, we ask which other vertical Fourier frequencies in lidar- or InSAR-produced structure metrics can best correlate with field biomass. Using lidar (LVIS) data from La Selva Biological Station, Costa Rica, taken in 2005, lidar canopy observations are Fourier transformed in the vertical direction to decompose into vertical frequency components. Each baseline of an InSAR observation, the complex coherence, is this Fourier transform of the canopy, if the ground contribution can be neglected. Using the qualitative similarity in vertical profiles seen by lidar, InSAR (at C-band, from AirSAR in 2004), and field measurements in the La Selva data, we produce the equivalent many (1000’s of) InSAR baselines from the lidar data and, using the lidar-simulated InSAR, determine the optimal spatial frequencies—baselines at DESDynI orbital altitudes for InSAR—which would estimate biomass in this wet tropical forest most accurately for either technique. For biomass ranging from 39-490 Mg/ha, regressing field biomass against some function of height

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  14. Improved estimates of forest vegetation structure and biomass with a LiDAR-optimized sampling design

    NASA Astrophysics Data System (ADS)

    Hawbaker, Todd J.; Keuler, Nicholas S.; Lesak, Adrian A.; Gobakken, Terje; Contrucci, Kirk; Radeloff, Volker C.

    2009-06-01

    LiDAR data are increasingly available from both airborne and spaceborne missions to map elevation and vegetation structure. Additionally, global coverage may soon become available with NASA's planned DESDynI sensor. However, substantial challenges remain to using the growing body of LiDAR data. First, the large volumes of data generated by LiDAR sensors require efficient processing methods. Second, efficient sampling methods are needed to collect the field data used to relate LiDAR data with vegetation structure. In this paper, we used low-density LiDAR data, summarized within pixels of a regular grid, to estimate forest structure and biomass across a 53,600 ha study area in northeastern Wisconsin. Additionally, we compared the predictive ability of models constructed from a random sample to a sample stratified using mean and standard deviation of LiDAR heights. Our models explained between 65 to 88% of the variability in DBH, basal area, tree height, and biomass. Prediction errors from models constructed using a random sample were up to 68% larger than those from the models built with a stratified sample. The stratified sample included a greater range of variability than the random sample. Thus, applying the random sample model to the entire population violated a tenet of regression analysis; namely, that models should not be used to extrapolate beyond the range of data from which they were constructed. Our results highlight that LiDAR data integrated with field data sampling designs can provide broad-scale assessments of vegetation structure and biomass, i.e., information crucial for carbon and biodiversity science.

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

    NASA Astrophysics Data System (ADS)

    Talianu, Camelia; Marmureanu, Luminita; Nicolae, Doina

    2015-04-01

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

  16. Satellite Estimates of Single Scattering Albedo and Optical Depth of Biomass Burning Carbonaceous Aerosols

    NASA Technical Reports Server (NTRS)

    Torres, O.; Herman, J. R.; Bhartia, P. K.; Hsu, N. C.

    1998-01-01

    Satellite based estimates of aerosol single scattering albedo (ssa), over both land and water surfaces, have been obtained for the first time using measurements of backscattered radiation in the near ultraviolet by the Total Ozone Mapping Spectrometer (TOMS). The retrieval of ssa and aerosol optical depth is based on the strong spectral contrast in the near-UV resulting from the interaction between the particle absorption and scattering (both Rayleigh and Mie) processes. We use the multi-year data set on backscattered radiances by the TOMS family of instruments to analyze the time and space variability of biomass burning generated carbonaceous aerosols. Results of a comparative analysis of satellite derived optical depth and available sunphotometer measurements will also be presented.

  17. Subtropical Forest Biomass Estimation Using Airborne LiDAR and Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Pang, Yong; Li, Zengyuan

    2016-06-01

    Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF's (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.

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

    SciTech Connect

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

    1982-08-01

    It is expected that the future construction of the Parana Medio Hydroelectric Project on the middle Parana River in Argentina will lead to the accumulation of floating hydrophytes, mainly water hyacinth. Several problems are related to aquatic plants, and steps for efficient control of the vegetation should be taken. If mechanical control is used, the biomass must be processed, preferably in a useful way. Water hyacinth growth in the middle Parana River has been measured and its bioconversion to methane by anaerobic fermentation determined. It is estimated that gross methane production may be between 1. and 4.1 x 10/sup 9/ m/sup 3//yr. The fermentation residue production, with a potential value as soil condition, may represent between 54.9 and 221.4 x 10/sup 3/t nitrogen/year, i.e., between 2 and 8 times the present nitrogen fertilizer demand in Argentina.

  19. Use of Spectral Radiance to Estimate In-Season Biomass and Grain Yield in Nitrogen- and Water-Stressed Corn.

    PubMed

    Osborne, S. L.; Schepers, J. S.; Francis, D. D.; Schlemmer, M. R.

    2002-01-01

    Current technologies for measuring plant water status are limited, while recently remote sensing techniques for estimating N status have increased with limited research on the interaction between the two stresses. Because plant water status methods are time-consuming and require numerous observations to characterize a field, managers could benefit from remote sensing techniques to assist in irrigation and N management decisions. A 2-yr experiment was initiated to determine specific wavelengths and/or combinations of wavelengths indicative of water stress and N deficiencies, and to evaluate these wavelengths for estimating in-season biomass and corn (Zea mays L.) grain yield. The experiment was a split-plot design with three replications. The treatment structure had five N rates (0, 45, 90, 134, and 269 kg N ha(-1)) and three water treatments [dryland, 0.5 evapotranspiration (ET), and full ET]. Canopy spectral radiance measurements (350-2500 nm) were taken at various growth stages (V6-V7, V13-V16, and V14-R1). Specific wavelengths for estimating crop biomass, N concentration, grain yield, and chlorophyll meter readings changed with growth stage and sampling date. Changes in total N and biomass in the presence of a water stress were estimated using near-infrared (NIR) reflectance and the water absorption bands. Reflectance in the green and NIR regions were used to estimate total N and biomass without water stress. Reflectance at 510, 705, and 1135 nm were found for estimating chlorophyll meter readings regardless of year or sampling date.

  20. Comparison of anchovy biomass estimates measured by trawls, egg production methods and hydro-acoustics in the Chesapeake Bay and the Korea Strait

    NASA Astrophysics Data System (ADS)

    Jung, Sukgeun; Houde, Edward D.

    2014-06-01

    We compared estimates of anchovy biomass derived from trawl surveys, egg production method (EPM) and acoustic surveys, conducted in two remote regions. Biomass density of bay anchovy Anchoa mitchilli was estimated in Chesapeake Bay, USA, by trawls, EPM and acoustics from 1989 to 2000. Biomass density of Pacific anchovy Engraulis japonicus was estimated in the Korea Strait using EPM, simulation-based daily cohort analysis and acoustics from 1984 to 2006. Most of the existing estimates already had considered body-size-dependent gear selectivity, highlyvariable instantaneous natural mortality of anchovy eggs, and avoidance of trawl nets by adult anchovy. Despite great variability in the ratio of trawl to acoustic biomass estimates (0.034-8.35), annually-averaged biomass density of young-ofthe-year individuals derived by the two methods were similar for bay anchovy in Chesapeake Bay and Pacific anchovy in the Korea Strait (0.83 and 0.70 g m-3, respectively). Results suggested that, despite substantial uncertainty, anchovy biomass estimates are generally compatible between EPM and acoustics. However, reported estimates of biomass density derived from the two acoustic surveys in the Korea Strait differed by a factor of 28, suggesting that further improvements in calibrations are required to reliably estimate anchovy biomass. The comparisons suggested that all biomass estimates could be biased and will require comparison and validation by other, independent sampling methods.

  1. Changes in the relationship between tree size and aboveground respiration in field-grown hinoki cypress (Chamaecyparis obtusa) trees over three years.

    PubMed

    Yokota, Taketo; Hagihara, Akio

    1998-01-01

    Respiration measurements of aerial parts of 18-year-old hinoki cypress (Chamaecyparis obtusa (Sieb. et Zucc.) Endl.) trees were made under field conditions over three years to study changing relationships with tree age between respiration and phytomass, phytomass increment, and leaf mass. The relationship between annual respiration (r(a)) and phytomass (w(T)) was approximated by a proportional function (r(a) = aw(T)), where the proportional constant (a) decreased year by year. The effect of time on the relationship between annual respiration and phytomass of each sample tree was fitted by a power function. Respiration of the tree suppressed by the canopy decreased year by year, but respiration of the other trees increased slightly with age. The relationship between annual respiration and leaf mass was also approximated by a generalized power function. Excluding the suppressed tree, the relationship between annual respiration (r(a)) and the annual increment of aboveground phytomass (Deltaw(T)) was described by a proportional function (r(a) = 2.27Deltaw(T)), where the proportional constant, 2.27, was independent of sample tree and year, indicating that about 2.3 times of the annual aboveground phytomass increment equivalent was respired annually. For any tree, the time constant relationships between annual respiration and leaf mass and phytomass increment for different-sized trees were similar to the corresponding time continuum relationships. In contrast, the time continuum relationship between annual respiration and phytomass differed from the time constant relationship, indicating that respiration of less active woody tissue contributed significantly to aboveground respiration. Based on the relationship between tree size and annual respiration, annual aboveground stand respiration was estimated to be 25.0, 26.9, and 25.8 Mg(dm) ha(-1) year(-1) for the three consecutive years, respectively, and the corresponding aboveground stand biomass was 60.0, 69.0, and 76.8 Mg

  2. PALSAR 50 m Mosaic Data Based National Level Biomass Estimation in Cambodia for Implementation of REDD+ Mechanism

    PubMed Central

    Avtar, Ram; Suzuki, Rikie; Takeuchi, Wataru; Sawada, Haruo

    2013-01-01

    Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB) in Cambodia. AGB was estimated using a bottom-up approach based on field measured biomass and backscattering (σo) properties of PALSAR data. The relationship between the PALSAR σo HV and HH/HV with field measured biomass was strong with R2 = 0.67 and 0.56, respectively. PALSAR estimated AGB show good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation results showed a high coefficient of determination R2 = 0.61 with RMSE  = 21 Mg/ha using values up to 200 Mg/ha biomass. There were some uncertainties because of the uncertainty in the field based measurement and saturation of PALSAR data. AGB map of Cambodian forests could be useful for the implementation of forest management practices for REDD+ assessment and policies implementation at the national level. PMID:24116012

  3. PALSAR 50 m mosaic data based national level biomass estimation in Cambodia for implementation of REDD+ mechanism.

    PubMed

    Avtar, Ram; Suzuki, Rikie; Takeuchi, Wataru; Sawada, Haruo

    2013-01-01

    Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB) in Cambodia. AGB was estimated using a bottom-up approach based on field measured biomass and backscattering (σ(o)) properties of PALSAR data. The relationship between the PALSAR σ(o) HV and HH/HV with field measured biomass was strong with R(2) = 0.67 and 0.56, respectively. PALSAR estimated AGB show good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation results showed a high coefficient of determination R(2) = 0.61 with RMSE  = 21 Mg/ha using values up to 200 Mg/ha biomass. There were some uncertainties because of the uncertainty in the field based measurement and saturation of PALSAR data. AGB map of Cambodian forests could be useful for the implementation of forest management practices for REDD+ assessment and policies implementation at the national level.

  4. Estimation of Tree Height, Biomass, and Standing Carbon in Miombo Woodlands Using Radar Interferometry

    NASA Astrophysics Data System (ADS)

    Ribiero, N. S.; Washington-Allen, R. A.; Simard, M.; Shugart, H. H.

    2007-12-01

    Savannas and woodlands are a major component of the world's vegetation covering one-sixth of the global land surface and one-half of the African continent. They account for about 30% of the primary production of all terrestrial vegetation. The southern African savannas cover 54% of the sub-continent with a plant diversity of approximately 8500 species and approximately 50% endemism. Miombo covers about two thirds of Mozambique and estimations of its biomass are critical because ecosystem services provided include food, fiber, and fuel for 39 million rural peoples and another 15 million urban dwellers in southern Africa. The Shuttle Radar Topography Mission (SRTM) C-band derived digital terrain model (DTM) can be used to estimate tree height by subtracting a base-level digital elevation model (DEM) from the calibrated SRTM. SRTM C-band's wavelength is such that there is partial penetration of the tree canopy before scattering which results in an underestimate of tree height. Consequently, mean tree height data from 50 30-m x 30-m random-stratified field plots in Niassa Reserve were used to bias the SRTM data up to average tree height and thus calibrate. However, DEMs in developing countries, particularly Africa, are not usually present and have to be developed either from field survey, orthophotography, or topographic maps. We derived a bare-ground binary mask from a land cover map of Niassa Reserve in northern Mozambique. The land cover map was generated from a Landsat Enhanced Thematic Mapper (ETM+) scene and the binary mask was overlaid against the SRTM to derive ground elevations from the SRTM. The resulting point map of elevations was spatially interpolated using thin plate spines with tension to derive a base-level DEM. The DEM was then subtracted from the calibrated SRTM to get tree heights. Secondly we explored the derivation of an independent base elevation DEM using the last return of the NASA Geoscience Laser Altimeter System (GLAS) and compared this to

  5. Ocean Lidar Measurements of Beam Attenuation and a Roadmap to Accurate Phytoplankton Biomass Estimates

    NASA Astrophysics Data System (ADS)

    Hu, Yongxiang; Behrenfeld, Mike; Hostetler, Chris; Pelon, Jacques; Trepte, Charles; Hair, John; Slade, Wayne; Cetinic, Ivona; Vaughan, Mark; Lu, Xiaomei; Zhai, Pengwang; Weimer, Carl; Winker, David; Verhappen, Carolus C.; Butler, Carolyn; Liu, Zhaoyan; Hunt, Bill; Omar, Ali; Rodier, Sharon; Lifermann, Anne; Josset, Damien; Hou, Weilin; MacDonnell, David; Rhew, Ray

    2016-06-01

    Beam attenuation coefficient, c, provides an important optical index of plankton standing stocks, such as phytoplankton biomass and total particulate carbon concentration. Unfortunately, c has proven difficult to quantify through remote sensing. Here, we introduce an innovative approach for estimating c using lidar depolarization measurements and diffuse attenuation coefficients from ocean color products or lidar measurements of Brillouin scattering. The new approach is based on a theoretical formula established from Monte Carlo simulations that links the depolarization ratio of sea water to the ratio of diffuse attenuation Kd and beam attenuation C (i.e., a multiple scattering factor). On July 17, 2014, the CALIPSO satellite was tilted 30° off-nadir for one nighttime orbit in order to minimize ocean surface backscatter and demonstrate the lidar ocean subsurface measurement concept from space. Depolarization ratios of ocean subsurface backscatter are measured accurately. Beam attenuation coefficients computed from the depolarization ratio measurements compare well with empirical estimates from ocean color measurements. We further verify the beam attenuation coefficient retrievals using aircraft-based high spectral resolution lidar (HSRL) data that are collocated with in-water optical measurements.

  6. Estimates of emissions from open biomass burning in Tropical Asia during 2000-2007

    NASA Astrophysics Data System (ADS)

    Chang, D.

    2009-04-01

    Biomass burning in tropical Asia emits large amounts of trace gases and particulate matters to atmosphere, which have significant influence in climate change and atmospheric chemistry. Emissions from open biomass burning in tropical Asia are estimated during seven fire years 2000-2006 (i.e., April 1st 2000-March 31st 2007), using newly released L3JRC burned area product and MODIS burned area product (MCD45A1). Over seven fire years, both burned areas and fire emissions showed clearly spatial and inter-annual variations. The L3JRC burned areas ranged from 31.3×103 km2 for fire year 2005 to 57.5×103 km2 for 2000, while the MODIS burned areas ranged from 64.9×103 km2 for fire year 2002 to 127.0×103 km2 for 2004. We compared the total burned areas and forest burned areas derived from the two separate products with publication data for several typical countries and found that the L3JRC results were comparable to previous studies and the MODIS results showed significant overestimation. The annual average L3JRC-based emissions were 29915, 1948, 90, 30, 12, 105, and 871 Gg yr-1 for CO2, CO, CH4, NOx, BC, OC, and PM2.5 respectively, while MODIS-based emissions were 86740, 5222, 230, 83, 33, 296, and 2188 Gg yr-1, 60.2%-65.5% higher than L3JRC. Forest fires were the largest contributor to fire emissions, though burned area within forest biomes only constituted a minority of total burned area. Fire emissions were mainly concentrated in Myanmar, Cambodia and India. Furthermore, the seasonal distribution of fire emissions was in good agreement with that of total burned areas.

  7. Stand structural diversity rather than species diversity enhances aboveground carbon storage in secondary subtropical forests in Eastern China

    NASA Astrophysics Data System (ADS)

    Ali, Arshad; Yan, En-Rong; Chen, Han Y. H.; Chang, Scott X.; Zhao, Yan-Tao; Yang, Xiao-Dong; Xu, Ming-Shan

    2016-08-01

    Stand structural diversity, typically characterized by variances in tree diameter at breast height (DBH) and total height, plays a critical role in influencing aboveground carbon (C) storage. However, few studies have considered the multivariate relationships of aboveground C storage with stand age, stand structural diversity, and species diversity in natural forests. In this study, aboveground C storage, stand age, tree species, DBH and height diversity indices, were determined across 80 subtropical forest plots in Eastern China. We employed structural equation modelling (SEM) to test for the direct and indirect effects of stand structural diversity, species diversity, and stand age on aboveground C storage. The three final SEMs with different directions for the path between species diversity and stand structural diversity had a similar goodness of fit to the data. They accounted for 82 % of the variation in aboveground C storage, 55-59 % of the variation in stand structural diversity, and 0.1 to 9 % of the variation in species diversity. Stand age demonstrated strong positive total effects, including a positive direct effect (β = 0.41), and a positive indirect effect via stand structural diversity (β = 0.41) on aboveground C storage. Stand structural diversity had a positive direct effect on aboveground C storage (β = 0.56), whereas there was little total effect of species diversity as it had a negative direct association with, but had a positive indirect effect, via stand structural diversity, on aboveground C storage. The negligible total effect of species diversity on aboveground C storage in the forests under study may have been attributable to competitive exclusion with high aboveground biomass, or a historical logging preference for productive species. Our analyses suggested that stand structural diversity was a major determinant for variations in aboveground C storage in the secondary subtropical forests in Eastern China. Hence, maintaining tree DBH and

  8. Remote sensing of biomass and annual net aerial primary productivity of a salt marsh

    NASA Technical Reports Server (NTRS)

    Hardisky, M. A.; Klemas, V.; Daiber, F. C.; Roman, C. T.

    1984-01-01

    Net aerial primary productivity is the rate of storage of organic matter in above-ground plant issues exceeding the respiratory use by the plants during the period of measurement. It is pointed out that this plant tissue represents the fixed carbon available for transfer to and consumption by the heterotrophic organisms in a salt marsh or the estuary. One method of estimating annual net aerial primary productivity (NAPP) required multiple harvesting of the marsh vegetation. A rapid nondestructive remote sensing technique for estimating biomass and NAPP would, therefore, be a significant asset. The present investigation was designed to employ simple regression models, equating spectral radiance indices with Spartina alterniflora biomass to nondestructively estimate salt marsh biomass. The results of the study showed that the considered approach can be successfully used to estimate salt marsh biomass.

  9. Gas-liquid slug-flow oxygen transport and non-invasive biomass estimation in hollow-fiber reactors

    SciTech Connect

    Smith, W.J.

    1989-01-01

    Maintenance of non-limiting concentrations of dissolved gases at the surface of a particulate biocatalyst is a formidable barrier to the development of ultra-compact bioreactors. The method proposed here for supplying dissolved gases resembles the microcirculation of vertebrates. In the microcirculation, two phases, oxygen-rich hemoglobin-packed erythrocytes and nutrient-rich plasma, pass alternately through the capillaries. In slug-flow membrane bioreactors, two phases, oxygen-rich gas bubbles and slugs of aqueous nutrient medium, flow alternately on one side of a semipermeable membrane while cells grow on the opposite side. Protein synthesis rates were measured for Bacillus licheniformis 749C cultures immobilized in slug-flow hollow-fiber membrane reactors. The cultures required oxygen for growth and protein synthesis. A mathematical model of slug-flow identified the operating conditions corresponding to either continuous or periodic oxygen supply within the reactors. Synthesis rates within the slug-flow reactors were higher than those predicted by the model; the model apparently underestimated concentrations of soluble nutrients in the biomass. Non-invasive estimates of the total immobilized biomass are needed to monitor and control the biomass density, and hence the transport properties of the biomass phase. Investigators have used two non-invasive methods: in situ monitoring of an aggregate property, such as electrical conductivity; and inferential estimates based on substrate consumption and metabolic models. Techniques were developed to estimate immobilized biomass concentrations and growth rates from sulfur mass balances. Additionally, global mass balances showed that time-averaged biomass specific growth rates can be estimated from effluent concentrations of any substrate with a finite yield coefficient.

  10. Examination of high resolution rainfall products and satellite greenness indices for estimating patch and landscape forage biomass

    NASA Astrophysics Data System (ADS)

    Angerer, Jay Peter

    Assessment of vegetation productivity on rangelands is needed to assist in timely decision making with regard to management of the livestock enterprise as well as to protect the natural resource. Characterization of the vegetation resource over large landscapes can be time consuming, expensive and almost impossible to do on a near real-time basis. The overarching goal of this study was to examine available technologies for implementing near real-time systems to monitor forage biomass available to livestock on a given landscape. The primary objectives were to examine the ability of the Climate Prediction Center Morphing Product (CMORPH) and Next Generation Weather Radar (NEXRAD) rainfall products to detect and estimate rainfall at semi-arid sites in West Texas, to verify the ability of a simulation model (PHYGROW) to predict herbaceous biomass at selected sites (patches) in a semi-arid landscape using NEXRAD rainfall, and to examine the feasibility of using cokriging for integrating simulation model output and satellite greenness imagery (NDVI) for producing landscape maps of forage biomass in Mongolia's Gobi region. The comparison of the NEXRAD and CMORPH rainfall products to gage collected rainfall revealed that NEXRAD outperformed the CMORPH rainfall with lower estimation bias, lower variability, and higher estimation efficiency. When NEXRAD was used as a driving variable in PHYGROW simulations that were calibrated using gage measured rainfall, model performance for estimating forage biomass was generally poor when compared to biomass measurements at the sites. However, when model simulations were calibrated using NEXRAD rainfall, performance in estimating biomass was substantially better. A suggested reason for the improved performance was that calibration with NEXRAD adjusted the model for the general over or underestimation of rainfall by the NEXRAD product. In the Gobi region of Mongolia, the PHYGROW model performed well in predicting forage biomass except

  11. Plant-mediated links between detritivores and aboveground herbivores

    PubMed Central

    Wurst, Susanne

    2013-01-01

    Most studies on plant-mediated above–belowground interactions focus on soil biota with direct trophic links to plant roots such as root herbivores, pathogens, and symbionts. Detritivorous soil fauna, though ubiquitous and present in high abundances and biomasses in soil, are under-represented in those studies. Understanding of their impact on plants is mainly restricted to growth and nutrient uptake parameters. Detritivores have been shown to affect secondary metabolites and defense gene expression in aboveground parts of plants, with potential impacts on aboveground plant–herbivore interactions. The proposed mechanisms range from nutrient mobilization effects and impacts on soil microorganisms to defense induction by passive or active ingestion of roots. Since their negative effects (disruption or direct feeding of roots) may be counterbalanced by their overall beneficial effects (nutrient mobilization), detritivores may not harm, but rather enable plants to respond to aboveground herbivore attacks in a more efficient way. Both more mechanistic and holistic approaches are needed to better understand the involvement of detritivores in plant-mediated above–belowground interactions and their potential for sustainable agriculture. PMID:24069027

  12. Biomass carbon accumulation by Japan's forests from 1947 to 1995

    NASA Astrophysics Data System (ADS)

    Fang, Jingyun; Oikawa, Takehisa; Kato, Tomomichi; Mo, Wenhong; Wang, Zhiheng

    2005-06-01

    Forest ecosystems in the Northern Hemisphere function as carbon (C) sinks for atmospheric carbon dioxide; however, the magnitude, location, and cause of the sinks remain uncertain. A number of field measurements of forest biomass and systematic national forest inventories in Japan make it possible to quantify the C sinks and their distribution. Allometric relationships between forest biomass and stem volume were obtained for the major forest types in Japan from 945 sets of direct field measurements across the country. These relationships were used to estimate the changes in C accumulations of aboveground biomass and total living biomass from 1947 to 1995 from the national forest inventories of 1947, 1956, 1961, 1965, 1975, 1980, 1985, 1990, and 1995. The results showed that the C accumulations have significantly increased during the last 50 years. The C density (C stock per hectare) and total C stock of aboveground biomass increased from 27.6 Mg C/ha and 611.7 Tg C in 1947 to 43.2 Mg C/ha and 1027.7 Tg C in 1995, respectively, and those of total living biomass increased from 33.9 Mg C/ha and 751.8 Tg C in 1947 to 53.6 Mg C/ha and 1274.8 Tg C in 1995. These increases were remarkable during 1976-1995, with a net increase of 5.6 Mg C/ha and 369 Tg C for the C density and total living biomass. These results suggest that Japan's forest vegetation is a significant C sink. In the past 20 years, living vegetation has sequestered 18.5 Tg C annually, 14.6 Tg C of which was accumulated in aboveground biomass. The total C sink for the whole forest sector (including nonliving biomass) of Japan was estimated as 36 Tg C/yr if using the net change ratio of nonliving biomass C to living biomass C derived from the United States and Europe. On the basis of average C sink per hectare, Japan's forests have a higher sequestration rate (0.77 Mg C ha-1 yr-1) than the average of the other northern countries (0.14-0.19 Mg C ha-1 yr-1). The expansion and regrowth of planted forests are two

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

    PubMed

    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.

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

    SciTech Connect

    Kandpal, J.B.; Madan, M.

    1996-10-01

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

  15. A Bayesian approach to estimate the biomass of anchovies off the coast of Perú.

    PubMed

    Quiroz, Zaida C; Prates, Marcos O; Rue, Håvard

    2015-03-01

    The Northern Humboldt Current System (NHCS) is the world's most productive ecosystem in terms of fish. In particular, the Peruvian anchovy (Engraulis ringens) is the major prey of the main top predators, like seabirds, fish, humans, and other mammals. In this context, it is important to understand the dynamics of the anchovy distribution to preserve it as well as to exploit its economic capacities. Using the data collected by the "Instituto del Mar del Perú" (IMARPE) during a scientific survey in 2005, we present a statistical analysis that has as main goals: (i) to adapt to the characteristics of the sampled data, such as spatial dependence, high proportions of zeros and big size of samples; (ii) to provide important insights on the dynamics of the anchovy population; and (iii) to propose a model for estimation and prediction of anchovy biomass in the NHCS offshore from Perú. These data were analyzed in a Bayesian framework using the integrated nested Laplace approximation (INLA) method. Further, to select the best model and to study the predictive power of each model, we performed model comparisons and predictive checks, respectively. Finally, we carried out a Bayesian spatial influence diagnostic for the preferred model.

  16. Biomass estimation in a tropical wet forest using Fourier transforms of profiles from lidar or interferometric SAR

    NASA Astrophysics Data System (ADS)

    Treuhaft, R. N.; Gonçalves, F. G.; Drake, J. B.; Chapman, B. D.; dos Santos, J. R.; Dutra, L. V.; Graça, P. M. L. A.; Purcell, G. H.

    2010-12-01

    Tropical forest biomass estimation based on the structure of the canopy is a burgeoning and crucial remote sensing capability for balancing terrestrial carbon budgets. This paper introduces a new approach to structural biomass estimation based on the Fourier transform of vertical profiles from lidar or interferometric SAR (InSAR). Airborne and field data were used from 28 tropical wet forest stands at La Selva Biological Station, Costa Rica, with average biomass of 229 Mg-ha-1. RMS scatters of remote sensing biomass estimates about field measurements were 58.3 Mg-ha-1, 21%, and 76.1 Mg-ha-1, 26%, for lidar and InSAR, respectively. Using mean forest height, the RMS scatter was 97 Mg-ha-1, ≈34% for both lidar and InSAR. The confidence that Fourier transforms are a significant improvement over height was >99% for lidar and ≈90% for InSAR. Lidar Fourier transforms determined the useful range of vertical wavelengths to be 14 m to 100 m.

  17. Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore Tuna (Thunnus alalunga)

    NASA Astrophysics Data System (ADS)

    Lehodey, P.; Senina, I.; Dragon, A.-C.; Arrizabalaga, H.

    2014-04-01

    The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. Unlike standard stock assessment models, new state-of-the-art ecosystem models require geo-referenced fishing data with highest possible spatial resolution. This study presents an application to the north Atlantic albacore tuna stock with a careful definition and validation of a spatially explicit fishing dataset prepared from publically available sources (ICCAT) for its use in a spatial ecosystem and population dynamics model (SEAPODYM) to provide the first spatially explicit estimate of albacore density in the North Atlantic by life stage. Density distributions are provided (http://doi.pangaea.de/10.1594/PANGAEA.831499) together with the fishing data used for these estimates http://doi.pangaea.de/10.1594/PANGAEA.830797, http://doi.pangaea.de/10.15 1594/PANGAEA.828168, http://doi.pangaea.de/10.1594/PANGAEA.828170, and http://doi.pangaea.de/10.1594/PANGAEA.828171 (see section Source Data References).

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

    NASA Astrophysics Data System (ADS)

    Chang, D.; Song, Y.

    2009-09-01

    Biomass burning in tropical Asia emits large amounts of trace gases and particulate matters into the atmosphere, which has significant implications for atmospheric chemistry and climatic change. In this study, emissions from open biomass burning over tropical Asia were evaluated during seven fire years from 2000-2006 (1 April 2000-31 March 2007). Burned areas were estimated from newly published 1-km L3JRC and 500-m MODIS burned area products (MCD45A1). Available fuel loads and emission factors were assigned for each vegetation type in a GlobCover characterisation map, and fuel moisture content was taken into account when calculating combustion factors. Over the whole period, both burned areas and fire emissions clearly showed spatial and seasonal variations. The L3JRC burned areas ranged from 31 165 km2 in fire year 2005 to 57 313 km2 in 2000, while the MCD45A1 burned areas ranged from 54 260 km2 in fire year 2001 to 127 068 km2 in 2004. Comparisons of L3JRC and MCD45A1 burned areas with ground-based measurements and other satellite information were constructed in several major burning regions, and results suggested that MCD45A1 performed better in most areas than L3JRC did although with a certain degree of underestimation of burned forest areas. The average annual L3JRC-based emissions were 125, 12, 0.98, 1.91, 0.11, 0.89, 0.044, 0.022, 0.42, 3.40, and 3.68 Tg yr

  19. Bringing Together Users and Developers of Forest Biomass Maps

    NASA Technical Reports Server (NTRS)

    Brown, Molly E.; Macauley, Molly

    2011-01-01

    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.

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

    PubMed

    Yao, Zheng-Yang; Liu, Jian-Jun

    2014-01-01

    Four common greening shrub species (i. e. Ligustrum quihoui, Buxus bodinieri, Berberis xinganensis and Buxus megistophylla) in Xi'an City were selected to develop the highest correlation and best-fit estimation models for the organ (branch, leaf and root) and total biomass against different independent variables. The results indicated that the organ and total biomass optimal models of the four shrubs were power functional model (CAR model) except for the leaf biomass model of B. megistophylla which was logarithmic functional model (VAR model). The independent variables included basal diameter, crown diameter, crown diameter multiplied by height, canopy area and canopy volume. B. megistophylla significantly differed from the other three shrub species in the independent variable selection, which were basal diameter and crown-related factors, respectively. PMID:24765849

  1. Estimating pre-fire biomass for the 2013 California Rim Fire using airborne LiDAR and Landsat data

    NASA Astrophysics Data System (ADS)

    Garcia-Alonso, M.; Casas Planes, Á.; Koltunov, A.; Ustin, S.; Falk, M.; Ramirez, C.

    2014-12-01

    Accurate knowledge of the amount and distribution of fuels is critical for appropriate fire planning and management, but also to improve carbon emissions estimates resulting from both wildland and prescribed fires. Airborne LiDAR (ALS) data has shown great capability to determine the amount of biomass in different ecosystems. Nevertheless, for most incidents a pre-fire LiDAR dataset that would enable the characterization of fuels before the incident is not available. Addressing this problem, we investigated the potential of combining a post-fire ALS dataset and a pre-fire Landsat image to model the pre-fire biomass distribution for the third-largest wildfire in California history, the Rim fire. Very high density (≈ 20 points/m2) ALS data was acquired covering the burned area plus a 2 km buffer. 500+ ALS-plots were located throughout the buffer area using a stratified random sampling scheme, with the strata defined by species group (coniferous, hardwood, and mixed forests) and diametric classes (5-9.9"; 10-19.9"; 20-29.9" and >30"). In these plots, individual tree crowns were delineated by the Watershed algorithm. Crown delineation was visually refined to avoid over- and under-segmentation errors, and the tree biomass was determined based on species-specific allometric equations. The biomass estimates for correctly delineated trees were subsequently aggregated to the plot-level. The next step is to derive a model relating the plot-level biomass to plot-level ALS-derived height and intensity metrics as explanatory variables. This model will be used to map pre-fire biomass in the buffer area outside the burn. To determine pre-fire biomass inside the fire perimeter, where ALS data are not available, we will use a statistical approach based on spectral information provided by a pre-fire Landsat image and its relationships with the 2 km buffer LiDAR-derived biomass estimates. We will validate our results with field measurements collected independently, before the fire.

  2. Using simple environmental variables to estimate below-ground productivity in grasslands

    USGS Publications Warehouse

    Gill, R.A.; Kelly, R.H.; Parton, W.J.; Day, K.A.; Jackson, R.B.; Morgan, J.A.; Scurlock, J.M.O.; Tieszen, L.L.; Castle, J.V.; Ojima, D.S.; Zhang, X.S.

    2002-01-01

    In many temperate and annual grasslands, above-ground net primary productivity (NPP) can be estimated by measuring peak above-ground biomass. Estimates of below-ground net primary productivity and, consequently, total net primary productivity, are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of below-ground NPP (BNPP) requires an accounting of total root biomass, the percentage of living biomass and annual turnover of live roots. We derived a relationship using above-ground peak biomass and mean annual temperature as predictors of below-ground biomass (r2 = 0.54; P = 0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of above-ground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 = 0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2 = 0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modelled estimates of BNPP.

  3. Improved Radiometric Capabilities of Landsat 8, Coupled With Lidar, Estimate Semi-arid Rangeland Biomass and Cover

    NASA Astrophysics Data System (ADS)

    Dhakal, S.; Glenn, N. F.; Li, A.; Spaete, L.; Shinneman, D. J.; Arkle, R.; Pilliod, D.; Mcllroy, S.; Baun, C.

    2015-12-01

    Remote sensing based quantification of semi-arid rangeland vegetation provides the large scale observations necessary for monitoring native plants distribution, estimating fuel loads and measuring carbon storage. Improved signal to noise ratio and radiometric resolution of recent satellite imagery and fine scale 3-dimensional information from lidar provides opportunities for refined measurements of vegetation structure. We leverage a large number of Landsat 8 and lidar-based metrics for prediction of biomass and cover of shrubs in the semi-arid rangeland of the western United States. Time-series Landsat 8 images were used to develop 20 ratio based vegetation indices. Similarly, 35 vegetation metrics, including metrics based on numerical values (e.g. elevation, canopy height) and on density of points (e.g. canopy density) were developed from airborne lidar point clouds. These vegetation indices and metrics were trained and linked to insitu measurements (n=141) with the Random Forest regression to impute biomass and cover map across a large scale. We also validate our model with an independent data-set (n=44), explaining up to 63% of variation in cover and 53% in biomass. The preliminary results suggest that Landsat performs better in estimating vegetation cover whereas lidar performs better in estimating biomass with no significant relationship to topographic variables (e.g. slope, aspect and elevation). We further compare our results with historical fire data to show that both biomass and cover decreases with the increase of fire frequency in the study site. This study demonstrates the new opportunities of using Landsat 8 with established lidar approaches to better quantify vegetation in semiarid ecosystems.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

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

    USGS Publications Warehouse

    Djemali, Imed; Yule, Daniel; Guillard, Jean

    2016-01-01

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

  6. Twig and foliar biomass estimation equations for major plant species in the Tanana River basin of interior Alaska. Forest Service research paper

    SciTech Connect

    Yarie, J.; Mead, B.R.

    1988-09-01

    Equations are presented for estimating the twig, foliage, and combined biomass for 58 plant species in interior Alaska. The equations can be used for estimating biomass from percentage of the foliar cover of 10-centimeter layers in a vertical profile from 0 to 6 meters. Few differences were found in regressions of the same species between layers except when the ratio of foliar-to-twig biomass changed drastically between layers, for example, Rosa acicularis Lindl. Eighteen species were tested for regression differences between years. Thirteen showed no significant differences, five were different. Of these five, three were feather mosses for which live and dead biomass are easily confused when measured.

  7. Estimating the loss of C, N and microbial biomass from Biological Soil Crusts under simulated rainfall

    NASA Astrophysics Data System (ADS)

    Gommeaux, M.; Malam Issa, O.; Bouchet, T.; Valentin, C.; Rajot, J.-L.; Bertrand, I.; Alavoine, G.; Desprats, J.-F.; Cerdan, O.; Fatondji, D.

    2012-04-01

    Most areas where biological soil crusts (BSC) develop undergo a climate with heavy but sparse rainfall events. The hydrological response of the BSC, namely the amount of runoff, is highly variable. Rainfall simulation experiments were conducted in Sadoré, south-western Niger. The aim was to estimate the influence of the BSC coverage on the quantity and quality of water, particles and solutes exported during simulated rainfall events. Ten 1 m2 plots were selected based on their various degree of BSC cover (4-89%) and type of underlying physical crust (structural or erosion crusts). The plots are located on similar sandy soil with moderate slope (3-6%). The experiments consisted of two rainfall events, spaced at 22-hours interval: 60 mm/h for 20 min, and 120 mm/h for 10 min. During each experiments particles dectached and runoff water were collected and filtered in the laboratory. C and N content were determined both in water and sediments samples.. These analyses were completed by measurements of phospholipid fatty acids and chlorophyll a contents in sediments and BSC samples collected before and after the rainfall. Mineral N and microbial biomass carbon of BSC samples were also analysed. The results confirmed that BSC reduce the loss of particles and exert a protective effect on soils with regard to particle detachment by raindrop. However there is no general relationship between the BSC coverage and the loss of C and N due to runoff. Contrarily, the C and N content in the sediments is negatively correlated to their mass. The type of physical crust on which the BSC develop also has to be taken into account. These results will contribute to the region-wide modeling of the role of BSC in biogeochemical cycles.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  9. Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula, Costa Rica.

    PubMed

    Taylor, Philip; Asner, Gregory; Dahlin, Kyla; Anderson, Christopher; Knapp, David; Martin, Roberta; Mascaro, Joseph; Chazdon, Robin; Cole, Rebecca; Wanek, Wolfgang; Hofhansl, Florian; Malavassi, Edgar; Vilchez-Alvarado, Braulio; Townsend, Alan

    2015-01-01

    Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD

  10. Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula, Costa Rica.

    PubMed

    Taylor, Philip; Asner, Gregory; Dahlin, Kyla; Anderson, Christopher; Knapp, David; Martin, Roberta; Mascaro, Joseph; Chazdon, Robin; Cole, Rebecca; Wanek, Wolfgang; Hofhansl, Florian; Malavassi, Edgar; Vilchez-Alvarado, Braulio; Townsend, Alan

    2015-01-01

    Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD

  11. Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula, Costa Rica

    PubMed Central

    Taylor, Philip; Asner, Gregory; Dahlin, Kyla; Anderson, Christopher; Knapp, David; Martin, Roberta; Mascaro, Joseph; Chazdon, Robin; Cole, Rebecca; Wanek, Wolfgang; Hofhansl, Florian; Malavassi, Edgar; Vilchez-Alvarado, Braulio; Townsend, Alan

    2015-01-01

    Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD

  12. Biomass, decomposition and nutrient cycling in a SW Atlantic Sarcocornia perennis marsh

    NASA Astrophysics Data System (ADS)

    Negrin, Vanesa L.; Pratolongo, Paula D.; de Villalobos, Ana E.; Botté, Sandra E.; Marcovecchio, Jorge E.

    2015-03-01

    Biomass dynamics, decomposition and nutrient cycling were studied in a Sarcocornia perennis salt marsh in the Bahia Blanca estuary (Argentina) to achieve a better understanding of these processes and provide information about a species and a region underrepresented in the literature. Above and belowground biomass stocks and carbon (C), nitrogen (N) and phosphorus (P) concentration in plant tissues were monitored every 2 months during a year. The decomposition rate and the concentration of C, N and P during the process were also estimated in above and belowground tissues. Biomass values were low (mean of 363 ± 43 and 242 ± 27 g m- 2 for aboveground and belowground tissues, respectively), presumably associated with the high salinity of this estuary. The general trend of higher values for aboveground biomass is in agreement with other reports for this species and has an effect on nutrients pools, which are higher for aboveground tissues for C and