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Sample records for aboveground biomass map

  1. Uncertainty Analysis in Large Area Aboveground Biomass Mapping

    NASA Astrophysics Data System (ADS)

    Baccini, A.; Carvalho, L.; Dubayah, R.; Goetz, S. J.; Friedl, M. A.

    2011-12-01

    Satellite and aircraft-based remote sensing observations are being more frequently used to generate spatially explicit estimates of aboveground carbon stock of forest ecosystems. Because deforestation and forest degradation account for circa 10% of anthropogenic carbon emissions to the atmosphere, policy mechanisms are increasingly recognized as a low-cost mitigation option to reduce carbon emission. They are, however, contingent upon the capacity to accurately measures carbon stored in the forests. Here we examine the sources of uncertainty and error propagation in generating maps of aboveground biomass. We focus on characterizing uncertainties associated with maps at the pixel and spatially aggregated national scales. We pursue three strategies to describe the error and uncertainty properties of aboveground biomass maps, including: (1) model-based assessment using confidence intervals derived from linear regression methods; (2) data-mining algorithms such as regression trees and ensembles of these; (3) empirical assessments using independently collected data sets.. The latter effort explores error propagation using field data acquired within satellite-based lidar (GLAS) acquisitions versus alternative in situ methods that rely upon field measurements that have not been systematically collected for this purpose (e.g. from forest inventory data sets). A key goal of our effort is to provide multi-level characterizations that provide both pixel and biome-level estimates of uncertainties at different scales.

  2. 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.

  3. 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.

  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

    Information on the distribution and density of carbon in tropical forests is critical to decision-making on a host of globally significant issues ranging from climate stabilization and biodiversity conservation to poverty reduction and human health. Encouraged by recent progress at both the international and jurisdictional levels on the design of incentive-based policy mechanisms to compensate tropical nations for maintaining their forests intact, governments throughout the tropics are moving with urgency to implement robust national and sub-national forest monitoring systems for operationally tracking and reporting on changes in forest cover and associated carbon stocks. Monitoring systems will be required to produce results that are accurate, consistent, complete, transparent, and comparable at sub-national to pantropical scales, and satellite-based remote sensing supported by field observations is widely-accepted as the most objective and cost-effective solution. The effectiveness of any system for large-area forest monitoring will necessarily depend on the capacity of current and near-future Earth observation satellites to provide information that meets the requirements of developing monitoring protocols. However, important questions remain regarding the role that spatially explicit maps of aboveground biomass and carbon can play in IPCC-compliant forest monitoring systems, with the majority of these questions stemming from doubts about the inherit sensitivity of satellite data to aboveground forest biomass, confusion about the relationship between accuracy and resolution, and a general lack of guidance on optimal strategies for linking field reference and remote sensing data sources. Here we demonstrate the ability of a state-of-the-art satellite radar sensor, the Japanese ALOS/PALSAR, and a venerable optical platform, Landsat 5, to support large-area mapping of aboveground tropical woody biomass across a 153,000-km2 region in the southwestern Amazon

  5. 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.

  6. Statewide Mapping of Aboveground Biomass by Integrating Airborne Lidar Data and National Forestry Inventory Plots

    NASA Astrophysics Data System (ADS)

    Chen, Q.; McRoberts, R. E.

    2015-12-01

    The freely available airborne lidar data at the sub-national level in the United States provide unprecedented opportunities for mapping large-area yet accurate information about vegetation structure, biomass, and carbon. However, the challenge of processing massive lidar data and extracting useful information is huge. This study is to conduct a statewide mapping study of aboveground biomass (AGB) by integrating airborne lidar data and FIA (Forest Inventory and Analysis) plot data for the whole state of Minnesota. We will share our experience and lessons in issues including 1) automatic generation of Digital Terrain Model from point cloud, 2) classification of vegetation returns, 3) calculation of AGB from FIA plots using different allometric models, 4) statistical modeling of AGB by integrating with FIA plots, and 5) assessing the uncertainty of mapped AGB.

  7. Aboveground Live Forest Biomass Map for the US From Satellite Imagery and Inventory Data

    NASA Astrophysics Data System (ADS)

    Helmer, E.; Blackard, J.; Finco, M.; Holden, G.; Hoppus, M.; Jacobs, D.; Lister, A.; Moisen, G.; Nelson, M.; Riemann, R.; Ruefenacht, B.; Salajanu, D.; Weyermann, D.; Winterberger, K.; Czaplewski, R.; Tymcio, R.; Brandeis, T.

    2004-12-01

    A gridded map of aboveground live forest biomass for the conterminous U.S., Alaska and Puerto Rico with a 250-m cell size resulted from integrating plot-level biomass estimates, from USDA Forest Service (USFS) nation-wide forest inventory data, with satellite imagery and ancillary geospatial data. The image and other predictor layers included MOD09 8-Day surface reflectance imagery (1) from the Moderate Resolution Imaging Spectroradiometer, MODIS-derived proportional tree cover (2), Landsat image-derived proportional land cover (3-4), climate averages (5-6) and topographic variables (7). By state or mapping zone (8), plot-based aboveground live forest biomass estimates generally fell within 5 percent of map-based estimates, and the map provided previously unavailable spatial detail. Here we describe the inventory data, the modeling approach, and the error maps. We secondly compare estimates of U.S. forest carbon storage in live woody biomass from this map with other estimates. We also critically evaluate the modeling process and spatial scaling issues. (1)Vermote EF, Vermueulen A. 1999. MOD09 ATBD, Univ. of Maryland, College Park, 107 pp. (2) Hansen M, DeFries R, et al. 2003. GLCF, Univ. of Maryland, College Park (3) Vogelmann JE, Howard S, et al. 2001. Photogramm Eng Rem S 67:650 (4) Helmer E, Ramos O, et al. 2002. Caribbean J Sci 38:165 (5) Daly C, Kittel T, et al. 2000. 12th AMS Conf on Applied Climatology, Amer Meteorol Soc, Asheville (6) Daly C, Helmer E, et al. 2003. Intl J Climatology 23:1359 (7) Gesch D, Oimoen M, et al. 2002. Photogramm Eng Rem S 68:5 (8) Homer C, Huang C, et al. 2004. Photogramm Eng Rem S 70:829

  8. 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.

  9. 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. PMID:25930205

  10. Mapping 2002-2012 Aboveground Biomass Carbon from LiDAR and Landsat Time Series across Northern Idaho, USA

    NASA Astrophysics Data System (ADS)

    Hudak, A. T.; Fekety, P.; Falkowski, M. J.; Kennedy, R. E.; Crookston, N.; Smith, A. M.

    2015-12-01

    The heavy investment by public and private land management entities in commercial off-the-shelf airborne lidar provides an optimum basis for a Carbon Monitoring System due to the known sensitivity of lidar to vegetation canopy structure. The ability to accurately map aboveground carbon pools from lidar and collocated field plot data has been demonstrated in many studies. Our goal is to upscale this biomass information, mapped at 30 m resolution, to the regional level using wall-to-wall, multi-temporal Landsat imagery. We use the LandTrendr approach to transform Landsat time series into annual maps of Brightness, Greenness, and Wetness along with annual change estimates of these same tasseled cap indices. These, along with ancillary layers of canopy height (e.g., GLAS-derived), topography (e.g., insolation), and climate (e.g., mean annual precipitation) are used to predict 2002-2012 aboveground carbon annually across the northern half of Idaho, USA. Ecoregion-specific models are developed to impute aboveground biomass and forest type beneath a forest/non-forest mask. Annual maps are then summarized at the county-level and compared to publically available Forest Inventory and Analysis estimates for Monitoring, Reporting and Verification.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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. PMID:26402522

  16. 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

  17. 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

  18. [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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Wavelet analysis for aboveground biomass estimate in temperate deciduous forests

    NASA Astrophysics Data System (ADS)

    Wei, Xiao-Fang

    2008-10-01

    The ever-increasing concentration of anthropogenic greenhouse gases (CO2, CH4, and CFCs) has been identified as a likely (greater than 90% confidence) cause of the observed increase of global mean temperatures since the mid-20th century (IPCC, 2007). The effect of human-induced climate change could be unprecedented and far-reaching. Carbon sequestration into trees and forests is an effective and inexpensive way for mitigating the CO2 level in the atmosphere. Hence, accurate measurement of biomass will be of great importance to global carbon cycle and climate change. This study performed a wavelet-based forest aboveground biomass estimation approach in a temperate deciduous forest, the Hoosier National Forest, in Indiana. Wavelet analysis, specifically two-dimensional discrete wavelet transform (DWT) was applied to ASTER images to obtain wavelet coefficients (WCs), which were correlated with forest inventory data using multiple linear regression analysis to investigate the relationship. Different mother wavelets and level of decomposition were tested. Moreover, vegetation indices, RATIO, normalized difference vegetation index (NDVI), and principal component analyses (PCA) were computed and correlated with field biomass measurements. The results indicate that wavelet coefficients correlate better with field biomass data than vegetation indices. For level one decomposition, the correlation coefficients are 0.3 to 0.5, while 0.1-0.3 for vegetation indices; for level two decomposition, the overall R value increased by 0.2, and for level three, the R value can be increased to 0.6-0.7. Meanwhile, tree per acre and basal area were also examined and correlated with field measurements. This study demonstrates that wavelet-based biomass estimation could be a very promising approach for solving the uncertainty between reflectance value from satellite images and forest biomass and therefore providing better biomass estimation; however, further research is needed for identifying

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

    USGS Publications Warehouse

    Evangelista, P.; Kumar, S.; Stohlgren, T.J.; Crall, A.W.; Newman, G.J.

    2007-01-01

    Predictive models of aboveground biomass of nonnative Tamarix ramosissima of various sizes were developed using destructive sampling techniques on 50 individuals and four 100-m2 plots. Each sample was measured for average height (m) of stems and canopy area (m2) prior to cutting, drying, and weighing. Five competing regression models (P < 0.05) were developed to estimate aboveground biomass of T. ramosissima using average height and/or canopy area measurements and were evaluated using Akaike's Information Criterion corrected for small sample size (AICc). Our best model (AICc = -148.69, ??AICc = 0) successfully predicted T. ramosissima aboveground biomass (R2 = 0.97) and used average height and canopy area as predictors. Our 2nd-best model, using the same predictors, was also successful in predicting aboveground biomass (R2 = 0.97, AICc = -131.71, ??AICc = 16.98). A 3rd model demonstrated high correlation between only aboveground biomass and canopy area (R2 = 0.95), while 2 additional models found high correlations between aboveground biomass and average height measurements only (R2 = 0.90 and 0.70, respectively). These models illustrate how simple field measurements, such as height and canopy area, can be used in allometric relationships to accurately predict aboveground biomass of T. ramosissima. Although a correction factor may be necessary for predictions at larger scales, the models presented will prove useful for many research and management initiatives.

  7. 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; 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.

  8. Mid-Term Status of the Forest Dragon III: Data Collection and Regional Aboveground Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Pang, Yong; Li, Zengyuan; Liu, Luxia; Lu, Hao; Jia, Wen; Liu, Qingwang; Tian, Xin; Zhang, Ruiying; Shmullius, Christiana

    2014-11-01

    In the 1st two years of Forest Dragon 3 project, Chinese groups engaged in following activities: 1) field measurements and airborne campaigns for forest map validation, 2) regional forest aboveground biomass (AGB) estimation algorithm development and map generation. The AGB estimation by fusion multisensor fusion was investigated. Two campaigns consist of in-situ observation, airborne flight and spaceborne measurements were designed and implemented in the Heilongjiang Province and Yunnan Province of China. The Heilongjiang Province is located in Northeast China and has typical temperate forest. The Yunnan Province is located in Southwest China and contains multiple forest types including tropical forest. By using these observation data from different scales, multi-source satellite data were used to estimate spatial explicit AGB for Da Xinganling study area.

  9. [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). PMID:24830234

  10. 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

  11. A study on estimation of aboveground wet biomass based on the microwave vegetation indices

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation biomass is an important parameter in the carbon cycle study. In this paper, a new technique to estimate aboveground vegetation wet biomass based on the Microwave Vegetation Indices (MVIs), which are computed through the observed brightness temperature of AMSR-E/Aqua under two adjacent fre...

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.

    PubMed

    Riegel, Joseph B; Bernhardt, Emily; Swenson, Jennifer

    2013-01-01

    Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R(2) values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R(2) of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas. PMID:23840837

  17. Estimating Above-Ground Carbon Biomass in a Newly Restored Coastal Plain Wetland Using Remote Sensing

    PubMed Central

    Riegel, Joseph B.; Bernhardt, Emily; Swenson, Jennifer

    2013-01-01

    Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R2 values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R2 of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas. PMID:23840837

  18. Use of Radar to Estimate Above-Ground Biomass in Disturbed Tropical Landscapes

    NASA Technical Reports Server (NTRS)

    Houghton, R. A.

    1998-01-01

    The overall purpose of this work was to evaluate the use of satellite radar in distinguishing, first, different cover classes in tropical landscapes and, second, cover classes with different amounts of above-ground biomass. The work focused on Ama7onian forests around Paragominas, Para, Brazil where extensive ground data had been obtained through previous field work.

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

    NASA Astrophysics Data System (ADS)

    CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.

    2013-12-01

    Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily

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

    PubMed

    Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W

    2016-04-01

    Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). PMID:26913575

  1. 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

  2. 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

  3. 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; Alexander, Heather D.; Mack, Michelle C.; Rover, Jennifer R.; Waldrop, Mark P.; McFarland, Jack W.; Chen, Xuexia; Pastick, Neal J.

    2015-01-01

    Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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

  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. 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

  11. 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.

  12. 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.

  13. 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

  14. Pasture burning in Amazonia: Dynamics of residual biomass and the storage and release of aboveground carbon

    NASA Astrophysics Data System (ADS)

    Barbosa, Reinaldo Imbrózio; Fearnside, Philip M.

    1996-11-01

    Aboveground biomass in cattle pasture converted from tropical dense forest was studied both before and after reburning in Brazilian Amazonia. In a 7-year-old pasture studied in Apiaú, Roraima, the aboveground dry weight of biomass (live plus dead) exposed to burning consisted of 96.3 t ha-1 of original forest remains, 6.2 t ha-1 of secondary successional vegetation (woody invaders in the pasture), and 8.0 t ha-1 of pasture grass (carbon contents 48.2%, 45.4%, and 42.2%, respectively). In terms of carbon, burning efficiencies for these three categories were 13.2%, 66.7% and 94.6%, respectively. Net charcoal formation was 0.35 t C ha-1 or 0.63% of the carbon exposed to the reburn, while the total accumulated since conversion (including the initial burn) is estimated at 2.3 t ha-1 (1.82% of the predeforestation aboveground biomass carbon stock). The dynamics of the original forest remains were represented in simulations that included parameters such as charcoal formation, burning efficiency and carbon concentration in different biomass components. Releases from initial burning of the cleared forest (44.0 t C ha-1) plus releases over the course of the succeeding decade through combustion (12.5 t C ha-1) and decay (51.5 t C ha-1) total 92% of the original forest biomass carbon (126 t C ha-1). Of biomass carbon remaining after the initial burn (84.3 t C ha-1), 76.0% is released: 61.1% through decay and 14.9% through combustion in reburns, while 1.2% is net conversion to charcoal in the reburns. These results indicate an amount of charcoal accumulation that is smaller than some carbon calculations have assumed, therefore suggesting a greater impact on global warming from conversion of forest to pasture.

  15. 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

  16. Latitudinal Characteristics of Below- and Above-ground Biomass of Typha: a Modelling Approach

    PubMed Central

    ASAEDA, TAKASHI; HAI, DINH NGOC; MANATUNGE, JAGATH; WILLIAMS, DAVID; ROBERTS, JANE

    2005-01-01

    • Background and Aims The latitudinal differences in the growth characteristics of Typha are largely unknown, although a number of studies have pointed out the effects of climate on the growth and productivity of Typha. Therefore, a dynamic growth model was developed for Typha to examine the effects of latitudinal changes in temperature and radiation on partitioning of the total biomass during the growing season into rhizomes, roots, flowering and vegetative shoots, and inflorescences. • Methods After validating the model with data from growth studies of Typha found in past literature, it was used to investigate the dynamics of above- and below-ground biomasses at three latitudes: 30°, 40° and 50°. • Key Results Regardless of the initial rhizome biomass, both above- and below-ground biomass values converged to a latitude-specific equilibrium produced by the balance between the total production and respiration and mortality losses. Above-ground biomass was high from 10° to 35° latitude with sufficient radiation, despite high metabolic losses; however, it decreased markedly at higher latitudes due to a low photosynthetic rate. Below-ground biomass, on the other hand, increased with latitude up to 40° due to decreasing metabolic losses, and then markedly decreased at higher latitudes. Above-ground biomass was enhanced with an increasing number of cohorts regardless of latitude. However, although more cohorts resulted in a larger below-ground biomass at low latitudes, the largest below-ground biomass was provided by a smaller number of cohorts at high latitudes. This difference is due to low production rates of late-season cohorts in high latitudes, compared with consumption for shooting and establishing foliage. • Conclusions The model could be used to predict the potential growth of Typha in given conditions over a wide range of latitudes and is useful for practical applications such as wetland management or wastewater treatment systems using Typha

  17. Study on forest above-ground biomass synergy inversion from GLAS and HJ-1 data

    NASA Astrophysics Data System (ADS)

    Fang, Zhou; Cao, Chunxiang; Ji, Wei; Xu, Min; Chen, Wei

    2012-10-01

    The need exists to develop a systematic approach to inventory and monitor global forests, both for carbon stock evaluation and for land use change analysis. The use of freely available satellite-based data for carbon stock estimation mitigates both the cost and the spatial limitations of field-based techniques. Spaceborne lidar data have been demonstrated as useful for forest aboveground biomass (AGB) estimation over a wide range of biomass values and forest types. However, the application of these data is limited because of their spatially discrete nature. Spaceborne multispectral sensors have been used extensively to estimate AGB, but these methods have been demonstrated as inappropriate for forest structure characterization in high-biomass mature forests. This study uses an integration of ICESat Geospatial Laser Altimeter System (GLAS) lidar and HJ-1 satellites data to develop methods to estimate AGB in an area of Qilian Mountains, Northwest China. Considering the study area belongs to mountainous terrain, the difficulties of this article are how to extract canopy height from GLAS waveform metrics. Combining with HJ-1 data and ground survey data of the study area, we establish forest biomass estimation model for the GLAS data based on BP neural network model. In order to estimate AGB, the training sample data includes the canopy height extracted from GLAS, LAI, vegetation coverage and several kinds of vegetation indices from HJ-1 data. The results of forest aboveground biomass are very close to the fields measured results, and are consistent with land cover data in the spatial distribution.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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

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

    NASA Astrophysics Data System (ADS)

    Olsoy, Peter J.; Glenn, Nancy F.; Clark, Patrick E.; Derryberry, DeWayne R.

    2014-02-01

    Sagebrush (Artemisia tridentata), a dominant shrub species in the sagebrush-steppe ecosystem of the western US, is declining from its historical distribution due to feedbacks between climate and land use change, fire, and invasive species. Quantifying aboveground biomass of sagebrush is important for assessing carbon storage and monitoring the presence and distribution of this rapidly changing dryland ecosystem. Models of shrub canopy volume, derived from terrestrial laser scanning (TLS) point clouds, were used to accurately estimate aboveground sagebrush biomass. Ninety-one sagebrush plants were scanned and sampled across three study sites in the Great Basin, USA. Half of the plants were scanned and destructively sampled in the spring (n = 46), while the other half were scanned again in the fall before destructive sampling (n = 45). The latter set of sagebrush plants was scanned during both spring and fall to further test the ability of the TLS to quantify seasonal changes in green biomass. Sagebrush biomass was estimated using both a voxel and a 3-D convex hull approach applied to TLS point cloud data. The 3-D convex hull model estimated total and green biomass more accurately (R2 = 0.92 and R2 = 0.83, respectively) than the voxel-based method (R2 = 0.86 and R2 = 0.73, respectively). Seasonal differences in TLS-predicted green biomass were detected at two of the sites (p < 0.001 and p = 0.029), elucidating the amount of ephemeral leaf loss in the face of summer drought. The methods presented herein are directly transferable to other dryland shrubs, and implementation of the convex hull model with similar sagebrush species is straightforward.

  5. 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

  6. [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. PMID:21657007

  7. 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

  8. 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

  9. 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.

  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. Forest Biomass Mapping From Lidar and Radar Synergies

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  12. 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).

  13. Estimating Yellow Starthistle (Centaurea solstitialis) Leaf Area Index and Aboveground Biomass with the Use of Hyperspectral Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral remote-sensed data were obtained via a Compact Airborne Spectrographic Imager-II (CASI-II) and used to estimate leaf-area index (LAI) and aboveground biomass of a highly invasive weed species, yellow starthistle (YST). In parallel, 34 ground-based field plots were used to measure abov...

  14. Estimating leaf area index and aboveground biomass of an invasive weed (yellow starthistle, Centaurea solstitalis L.) using airborne hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral remote sensed data was obtained via a Compact Airborne Spectrographic Imager (CASI) and used to estimate leaf area index (LAI) and aboveground biomass of a highly invasive weed species, yellow starthistle (Centaurea solstitialis L.). In parallel, 34 ground-based field plots were used t...

  15. 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.

  16. Quantification of aboveground forest biomass using Quickbird imagery, topographic variables, and field data

    NASA Astrophysics Data System (ADS)

    Zhou, Jing-Jing; Zhao, Zhong; Zhao, Qingxia; Zhao, Jun; Wang, Haize

    2013-01-01

    Optical remote sensing is the most widely used method for obtaining forest biomass information. This research investigated the potential of using topographical and high-resolution optical data from Quickbird for measurement of black locust plantation aboveground biomass (AGB) grown in the hill-gully region of the Loess Plateau. Three different processing techniques, including spectral vegetation indices (SVIs), texture, and topography were evaluated, both individually and combined. Simple linear regression and stepwise multiple-linear regression models were developed to describe the relationship between image parameters obtained using these approaches and field measurements. SVI and topography-based approaches did not yield reliable AGB estimates, accounting for at best 23 and 19% of the observed variation in AGB. Texture-based methods were better, explaining up to 70% of the observed variation. A combination of SVIs, texture, and topography yielded an even better R value of 0.74 with the lowest root mean square error (17.21 t/ha) and bias (-1.85 t/ha). The results suggest that texture information from high-resolution optical data was more effective than SVIs and topography to estimate AGB. The performance of AGB estimation can be improved by adding SVIs and topography results to texture data; the best results can be obtained using a combination of these three data types.

  17. 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.

  18. 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

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

    NASA Astrophysics Data System (ADS)

    Barrachina, M.; Cristóbal, J.; Tulla, A. F.

    2015-06-01

    Extensive stock-breeding systems developed in mountain areas like the Pyrenees are crucial for local farming economies and depend largely on above-ground biomass (AGB) in the form of grass produced on meadows and pastureland. In this study, a multiple linear regression analysis technique based on in-situ biomass collection and vegetation and wetness indices derived from Landsat-5 TM data is successfully applied in a mountainous Pyrenees area to model AGB. Temporal thoroughness of the data is ensured by using a large series of images. Results of on-site AGB collection show the importance for AGB models to capture the high interannual and intraseasonal variability that results from both meteorological conditions and farming practices. AGB models yield best results at midsummer and end of summer before mowing operations by farmers, with a mean R2, RMSE and PE for 2008 and 2009 midsummer of 0.76, 95 g m-2 and 27%, respectively; and with a mean R2, RMSE and PE for 2008 and 2009 end of summer of 0.74, 128 g m-2 and 36%, respectively. Although vegetation indices are a priori more related with biomass production, wetness indices play an important role in modeling AGB, being statistically selected more frequently (more than 50%) than other traditional vegetation indexes (around 27%) such as NDVI. This suggests that middle infrared bands are crucial descriptors of AGB. The methodology applied in this work compares favorably with other works in the literature, yielding better results than those works in mountain areas, owing to the ability of the proposed methodology to capture natural and anthropogenic variations in AGB which are the key to increasing AGB modeling accuracy.

  20. Impacts of Sample Design on Estimation of Aboveground Biomass: Implications for the Assimilation of Lidar and Forest Inventory Data

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    The availability of lidar data that can be used to characterize forest structure and estimate aboveground biomass (AGB) is rapidly increasing. When lidar data are considered in conjunction with forest inventory data to estimate AGB, the order of acquisition for these data products may impact the quality of the resulting estimates. In this work, we address this question in the context of uncertainty reduction with respect to estimation of AGB in a degraded forest in Paragominas, Brazil. We have developed a simulation framework that quantitatively assesses the uncertainty associated with estimation of AGB for different sampling strategies that combine forest inventory and lidar data. We utilize a Bayesian hierarchical modeling (BHM) data assimilation framework to combine information from the forest inventory and lidar data products into a higher order data product of AGB. Spatially explicit realizations of AGB are generated under different sampling strategies. Sampling strategies are assessed using the distributional properties of the assimilated higher order data product in the context of uncertainty reduction. We consider both spatially explicit maps of uncertainty as well as the standard deviation of the posterior predictive distributions of AGB as endpoints for the quantification of uncertainty. This framework allows for the explicit characterization of important sources of uncertainty. Our results show that a significant reduction in the uncertainty associated with estimation of AGB can be realized when design optimization is utilized in this context.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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].

  9. 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

  10. 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.

  11. 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

  12. 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

  13. Using multi-frequency radar and discrete-return LiDAR measurements to estimate above-ground biomass and biomass components in a coastal temperate forest

    NASA Astrophysics Data System (ADS)

    Tsui, Olivier W.; Coops, Nicholas C.; Wulder, Michael A.; Marshall, Peter L.; McCardle, Adrian

    2012-04-01

    Height measurements from small-footprint discrete-return LiDAR and backscatter coefficients from C- and L-band radar were used independently and in combination to estimate above-ground component and total biomass for a coniferous temperate forest, located on Vancouver Island, British Columbia, Canada. Reference biomass data were obtained from plot-level data and used for comparison against the LiDAR and radar-based biomass models. For the LiDAR-only model, height metrics such as mean first return height and percentiles (e.g., 10th and 90th) of first returns correlated best to total above-ground and stem biomass. While percent of first returns above 2 m and percentiles (75th and 90th) of first returns height metrics correlated best to crown biomass. A comparison between above-ground components and total biomass indicate that stem biomass displayed the highest relationship with the LiDAR measurements while crown biomass showed the lowest relationship with relative root mean squared error ranging from 16% to 22%, respectively. Alternatively, the radar-only models indicated that for C-band radar, a combination of HH and VV backscatter demonstrated the most significant correlation with forest biomass compared to coherence based models with a relative root mean squared error of 53%. For L-band radar, a combination of HH and HV backscatter showed the most significant correlation compared to coherence based models with a relative root mean squared error of 44%. Exploring a mixture of C- and L-band backscatter and coherence based models revealed that a combination of C-HV and L-HV coherence magnitudes provided the best radar relationship with forest biomass with a relative root mean squared error of 35%. Also for all radar-based models, L- and C-band backscatter and coherence magnitudes were poorly correlated with individual biomass components when compared to total above-ground biomass. The addition of C- and L-band backscatter and coherence variables to the Li

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. Estimating grassland aboveground biomass using multitemporal MODIS data in the West Songnen Plain, China

    NASA Astrophysics Data System (ADS)

    Li, Fei; Jiang, Lei; Wang, Xufeng; Zhang, Xiaoqiang; Zheng, Jiajia; Zhao, Qianjun

    2013-01-01

    The West Songnen Plain is an ecologically fragile area. The grasslands on the plain have been seriously degraded over the past five decades and this process is continuing. The reliable estimation of grassland aboveground biomass (AGB) provides scientific data for determining the livestock stocking rate on rangeland. AGB is also of considerable significance for biodiversity and environmental protection in this region. Remote sensing is the most effective way to estimate grassland AGB on a regional scale. Multitemporal, remotely sensed data were used for grassland AGB estimation with statistical models and an artificial neural network (ANN), and the accuracy of estimation for these methods was compared. The results demonstrate that the use of multi-temporal remotely sensed data has advantages for grassland AGB estimation, whether with statistical models or ANN methods, compared with single-temporal remotely sensed data, although the ANN had a higher accuracy of estimation for grassland AGB. Finally, the grassland AGB on the Songnen Plain was estimated with the ANN using multitemporal MODIS data. The spatial distribution pattern of grassland AGB showed large variations, and grassland productivity was generally low. The maximum green weight of the grassland AGB was 927.22 g/m2 and was mainly distributed on the northeast of the West Songnen Plain. The minimum green weight of the grassland AGB was 194.82 g/m2 and was mainly distributed on the central and southwestern West Songnen Plain. Most of the areas had medium- and low-yielding grasses. The significant increases of population and livestock number were the primary and direct reasons for the decrease in grassland quality. This study will contribute to policy making for the control of grazing and for biodiversity and environmental protection.

  19. 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.

  20. 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

  1. 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.

  2. Characterizing uncertainties of the national-scale forest gross aboveground biomass (AGB) loss estimate: a case study of the Democratic Republic of the Congo

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Modern remote sensing techniques enable the mapping and monitoring of aboveground biomass (AGB) carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where a national forest inventory (NFI) has yet to be established due to a lack of infrastructure and political instability. We demonstrate a method for producing national-scale gross AGB loss estimates and quantifying uncertainty of the estimates using remotely sensed-derived forest cover loss and biomass carbon density data. Forest cover type and loss were characterized using published Landsat-based data sets and related to LIDAR-derived biomass data from the Geoscience Laser Altimeter System (GLAS). We produced two gross AGB loss estimates for the DRC for the last decade (2000-2010): a conservative estimate accounting for classification errors in the 60-m resolution FACET forest cover change product, and a maximal estimate that also took into consideration omitted change at the 30m spatial resolution. Omitted disturbances were largely related to smallholder agriculture, the detection of which is scale-dependent. The use of LIDAR data as a substitute for NFI data to estimate AGB loss based on Landsat-derived activity data was demonstrated. Comparisons of our forest cover loss and AGB estimates with published studies raise the issue of scale in forest cover change mapping and its impact on carbon stock change estimation using remotely sensed data.

  3. 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

  4. 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.

  5. [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. PMID:25898621

  6. 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.

  7. 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

  8. 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

  9. 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).

  10. 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

  11. A hyperspectral imaging system for an accurate prediction of the above-ground biomass of individual rice plants.

    PubMed

    Feng, Hui; Jiang, Ni; Huang, Chenglong; Fang, Wei; Yang, Wanneng; Chen, Guoxing; Xiong, Lizhong; Liu, Qian

    2013-09-01

    Biomass is an important component of the plant phenomics, and the existing methods for biomass estimation for individual plants are either destructive or lack accuracy. In this study, a hyperspectral imaging system was developed for the accurate prediction of the above-ground biomass of individual rice plants in the visible and near-infrared spectral region. First, the structure of the system and the influence of various parameters on the camera acquisition speed were established. Then the system was used to image 152 rice plants, which selected from the rice mini-core collection, in two stages, the tillering to elongation (T-E) stage and the booting to heading (B-H) stage. Several variables were extracted from the images. Following, linear stepwise regression analysis and 5-fold cross-validation were used to select effective variables for model construction and test the stability of the model, respectively. For the T-E stage, the R(2) value was 0.940 for the fresh weight (FW) and 0.935 for the dry weight (DW). For the B-H stage, the R(2) value was 0.891 for the FW and 0.783 for the DW. Moreover, estimations of the biomass using visible light images were also calculated. These comparisons showed that hyperspectral imaging performed better than the visible light imaging. Therefore, this study provides not only a stable hyperspectral imaging platform but also an accurate and nondestructive method for the prediction of biomass for individual rice plants. PMID:24089866

  12. 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

  13. 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

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

    NASA Astrophysics Data System (ADS)

    Singh, Minerva; Malhi, Yadvinder; Bhagwat, Shonil

    2014-01-01

    The focus of this study is to assess the efficacy of using optical remote sensing (RS) in evaluating disparities in forest composition and aboveground biomass (AGB). The research was carried out in the East Sabah region, Malaysia, which constitutes a disturbance gradient ranging from pristine old growth forests to forests that have experienced varying levels of disturbances. Additionally, a significant proportion of the area consists of oil palm plantations. In accordance with local laws, riparian forest (RF) zones have been retained within oil palm plantations and other forest types. The RS imagery was used to assess forest stand structure and AGB. Band reflectance, vegetation indicators, and gray-level co-occurrence matrix (GLCM) consistency features were used as predictor variables in regression analysis. Results indicate that the spectral variables were limited in their effectiveness in differentiating between forest types and in calculating biomass. However, GLCM based variables illustrated strong correlations with the forest stand structures as well as with the biomass of the various forest types in the study area. The present study provides new insights into the efficacy of texture examination methods in differentiating between various land-use types (including small, isolated forest zones such as RFs) as well as their AGB stocks.

  15. 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.

  16. 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

  17. 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

  18. Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps

    PubMed Central

    2013-01-01

    Background Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m – 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO’s Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. Results We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. Conclusions Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to

  19. 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)...

  20. 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...

  1. Changes in aboveground biomass and nutrient content on Walker Branch Watershed from 1967 to 1983

    SciTech Connect

    Johnson, D.W.; Henderson, G.S.; Harris, W.F.

    1987-01-01

    The increment of forest biomass and nutrient content on Walker Branch Watershed, Tennessee, from 1967 to 1983 was interrupted by two insect outbreaks. An outbreak of the southern pine beetle in the early 1970s and an outbreak of the hickory borer in the late 1970s to early 1980s killed a number of shortleaf pine (Pinus echinata) and hickory (Carya spp.), respectively. Yellow-poplar (Liriodendron tulipifera) growth increased over this 16-year period, especially in response to the mortality of shortleaf pine. The net result of these events was little change in total biomass but a substantial shift in species composition (from pine to yellow-poplar) in the Pine forest type over this period. No species has yet responded to the mortality of hickory. Due to the shift in species composition in the Pine type, calcium and magnesium accumulation rates in biomass increased but foliage biomass decreased over the inventory period. There was little change in foliage biomass or nutrient content in other forest types, despite hickory mortality, since mortality occurred primarily among large trees having low foliage-to-woody-biomass ratios. The insect attacks, combined with apparently natural self-thinning, caused a large increase in standing dead biomass and in nutrient return via tree fall. This increased rate of return will substantially alter forest floor nutrient content and availability, especially with regard to calcium (where the calcium content of standing dead currently equals forest floor calcium content) and nitrogen (where inputs of woody litter will substantially alter carbon to nitrogen ratios). 23 refs., 7 figs., 2 tabs.

  2. 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

  3. Using satellite radar backscatter to predict above-ground woody biomass: A consistent relationship across four different African landscapes

    NASA Astrophysics Data System (ADS)

    Mitchard, E. T. A.; Saatchi, S. S.; Woodhouse, I. H.; Nangendo, G.; Ribeiro, N. S.; Williams, M.; Ryan, C. M.; Lewis, S. L.; Feldpausch, T. R.; Meir, P.

    2009-12-01

    Regional-scale above-ground biomass (AGB) estimates of tropical savannas and woodlands are highly uncertain, despite their global importance for ecosystems services and as carbon stores. In response, we collated field inventory data from 253 plots at four study sites in Cameroon, Uganda and Mozambique, and examined the relationships between field-measured AGB and cross-polarized radar backscatter values derived from ALOS PALSAR, an L-band satellite sensor. The relationships were highly significant, similar among sites, and displayed high prediction accuracies up to 150 Mg ha-1 (±˜20%). AGB predictions for any given site obtained using equations derived from data from only the other three sites generated only small increases in error. The results suggest that a widely applicable general relationship exists between AGB and L-band backscatter for lower-biomass tropical woody vegetation. This relationship allows regional-scale AGB estimation, required for example by planned REDD (Reducing Emissions from Deforestation and Degradation) schemes.

  4. 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

  5. Bringing Together Users and Developers of Forest Biomass Maps

    NASA Technical Reports Server (NTRS)

    Brown, Molly Elizabeth; Macauley, Molly K.

    2012-01-01

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

  6. Aboveground Biomass Estimation in a Tidal Brackish Marsh Using Simulated Thematic Mapper Spectral Data

    NASA Technical Reports Server (NTRS)

    Hardisky, M.; Klemas, V.

    1984-01-01

    Spectral radiance data were collected from the ground and from a low altitude aircraft in an attempt to gain some insight into the potential utility of actual Thematic Mapper data for biomass estimation in wetland plant communities. No attempt was made to distinguish individual plant species within brackish marsh plant associations. Rather, it was decided to lump plant species with similar canopy morphologies and then estimate from spectral radiance data the biomass of the group. The rationale for such an approach is that plants with a similar morphology will produce a similar reflecting or absorping surface (i.e., canopy) for incoming electromagnetic radiation. Variations in observed reflectance from different plant communities with a similar canopy morphology are more likely to be a result of biomass differences than a result of differences in canopy architecture. If the hypothesis that plants with a similar morphology exhibit similar reflectance characteristics is true, then biomass can be estimated based on a model for the dominant plant morphology within a plant association and the need for species discrimination has effectively been eliminated.

  7. 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...

  8. 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., III

    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

  9. 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

  10. 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. PMID:25254294

  11. Forest structure and aboveground biomass in the southwestern United States from MODIS and MISR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Red band bidirectional reflectance factor data from the NASA MODerate resolution Imaging Spectroradiometer (MODIS) acquired over the southwestern United States were interpreted through a simple geometric–optical (GO) canopy reflectance model to provide maps of fractional crown cover (dimensionless),...

  12. 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

  13. 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.

  14. 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.

  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. 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

  17. Mapping biomass with remote sensing: a comparison of methods for the case study of Uganda

    PubMed Central

    2011-01-01

    Background Assessing biomass is gaining increasing interest mainly for bioenergy, climate change research and mitigation activities, such as reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+). In response to these needs, a number of biomass/carbon maps have been recently produced using different approaches but the lack of comparable reference data limits their proper validation. The objectives of this study are to compare the available maps for Uganda and to understand the sources of variability in the estimation. Uganda was chosen as a case-study because it presents a reliable national biomass reference dataset. Results The comparison of the biomass/carbon maps show strong disagreement between the products, with estimates of total aboveground biomass of Uganda ranging from 343 to 2201 Tg and different spatial distribution patterns. Compared to the reference map based on country-specific field data and a national Land Cover (LC) dataset (estimating 468 Tg), maps based on biome-average biomass values, such as the Intergovernmental Panel on Climate Change (IPCC) default values, and global LC datasets tend to strongly overestimate biomass availability of Uganda (ranging from 578 to 2201 Tg), while maps based on satellite data and regression models provide conservative estimates (ranging from 343 to 443 Tg). The comparison of the maps predictions with field data, upscaled to map resolution using LC data, is in accordance with the above findings. This study also demonstrates that the biomass estimates are primarily driven by the biomass reference data while the type of spatial maps used for their stratification has a smaller, but not negligible, impact. The differences in format, resolution and biomass definition used by the maps, as well as the fact that some datasets are not independent from the reference data to which they

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

    NASA Astrophysics Data System (ADS)

    Mitchard, E. T. A.; Saatchi, S. S.; White, L. J. T.; Abernethy, K. A.; Jeffery, K. J.; Lewis, S. L.; Collins, M.; Lefsky, M. A.; Leal, M. E.; Woodhouse, I. H.; Meir, P.

    2011-08-01

    Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional to national level. The production of such maps across wide areas will become increasingly necessary as international efforts to protect primary forests, such as the REDD+ (Reducing Emissions from Deforestation and forest Degradation) mechanism, come into effect, alongside their use for management and research more generally. However, mapping biomass over high-biomass tropical forest is challenging as (1) direct regressions with optical and radar data saturate, (2) much of the tropics is persistently cloud-covered, reducing the availability of optical data, (3) many regions include steep topography, making the use of radar data complex, (4) while LiDAR data does not suffer from saturation, expensive aircraft-derived data are necessary for complete coverage. We present a solution to the problems, using a combination of terrain-corrected L-band radar data (ALOS PALSAR), spaceborne LiDAR data (ICESat GLAS) and ground-based data. We map Gabon's Lopé National Park (5000 km2) because it includes a range of vegetation types from savanna to closed-canopy tropical forest, is topographically complex, has no recent cloud-free high-resolution optical data, and the dense forest is above the saturation point for radar. Our 100 m resolution biomass map is derived from fusing spaceborne LiDAR (7142 ICESat GLAS footprints), 96 ground-based plots (average size 0.8 ha) and an unsupervised classification of terrain-corrected ALOS PALSAR radar data, from which we derive the aboveground biomass stocks of the park to be 78 Tg C (173 Mg C ha-1). This value is consistent with our field data average of 181 Mg C ha-1, from the field plots measured in 2009 covering a total of 78 ha, and which are independent as they were not used for the GLAS-biomass estimation. We estimate an uncertainty of ± 25 % on our carbon stock value for the park. This error term includes

  19. 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.

  20. Regional mapping of forest canopy water content and biomass using AIRSAR images over BOREAS study area

    NASA Technical Reports Server (NTRS)

    Saatchi, Sasan; Rignot, Eric; Vanzyl, Jakob

    1995-01-01

    In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR

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

    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

  2. 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%.

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

    DOE PAGESBeta

    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

  4. Local Discrepancies in Continental Scale Biomass Maps: A Case Study over Forested and Non-Forested Landscapes in Maryland, USA

    NASA Astrophysics Data System (ADS)

    Huang, W.; Swatantran, A.; Johnson, K. D.; Duncanson, L.; Tang, H.; ONeil-Dunne, J.; Hurtt, G. C.; Dubayah, R.

    2015-12-01

    Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-derived biomass map over Maryland, USA. We conduct detailed comparisons at pixel-, county-, and state-level. Spatial patterns of biomass are broadly consistent in all maps, but there are large differences at fine scales (RMSD 48.5 Mg·ha-1-92.7 Mg·ha-1). Discrepancies reduce with aggregation and the agreement among products improves at the county level. However, continental scale maps exhibit residual negative biases in mean (33.0 Mg·ha-1-54.6 Mg·ha-1) and total biomass (3.5-5.8 Tg) when compared to the high-resolution lidar biomass map. Three of the four continental scale maps reach near-perfect agreement at ~4 km and onward but do not converge with the high-resolution biomass map even at county scale. At the State level, these maps underestimate biomass by 30-80 Tg in forested and 40-50 Tg in non-forested areas. Local discrepancies in continental scale biomass maps are caused by factors including data inputs, modeling approaches, forest / non-forest definitions and time lags. There is a net underestimation over high biomass forests and non-forested areas that could impact carbon accounting at all levels. Local, high-resolution lidar-derived biomass maps provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale maps produced in carbon monitoring systems.

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

    PubMed

    Avitabile, Valerio; Herold, Martin; Heuvelink, Gerard B M; Lewis, Simon L; Phillips, Oliver L; Asner, Gregory P; Armston, John; Ashton, Peter S; Banin, Lindsay; Bayol, Nicolas; Berry, Nicholas J; Boeckx, Pascal; de Jong, Bernardus H J; DeVries, Ben; Girardin, Cecile A J; Kearsley, Elizabeth; Lindsell, Jeremy A; Lopez-Gonzalez, Gabriela; Lucas, Richard; Malhi, Yadvinder; Morel, Alexandra; Mitchard, Edward T A; Nagy, Laszlo; Qie, Lan; Quinones, Marcela J; Ryan, Casey M; Ferry, Slik J W; Sunderland, Terry; Laurin, Gaia Vaglio; Gatti, Roberto Cazzolla; Valentini, Riccardo; Verbeeck, Hans; Wijaya, Arief; Willcock, Simon

    2016-04-01

    We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. PMID:26499288

  6. Spatial distributions of forest aboveground biomass and landscape dynamics associated with conservation status and ownership in New England, USA

    NASA Astrophysics Data System (ADS)

    Zheng, D.; Heath, L. S.; Ducey, M. J.

    2009-05-01

    We combined remote sensing derived forest aboveground biomass (AGB) estimation and the Conservation Biology Institute/World Wildlife Fund Protected Area Database using GIS techniques and spatial pattern analysis to illustrate how different conservation status and ownership could affect the landscape dynamics and spatial distributions of AGB in New England states, USA. The AGB means between all pairs of protection status and ownership categories were significantly different (P < 0.05). The highest mean AGB was observed in the protected public lands (156 Mg/ha), 44% higher than the lowest AGB mean (108 Mg/ha) observed in private regulated lands (privately owned but under the regulatory control by a state agency), or 30% higher than that in privately owned lands on average (120 Mg/ha). Seventy-seven percent of the regional forests with AGB > 200 Mg/ha, totaling about 9,300 km2, were located outside protected areas and were concentrated in western MA, southern VT, southwestern NH, and northwestern CT. The fragmentation rate in protected public lands between 1992 and 2001 was the least with greater rates were observed in privately regulated and non-regulated lands. Changing rates for the 4 representative fragmentation indices (patch density (PD), edge density (ED), landscape shape index (LSI), and mean patch size (MPS)) ranged from 1% in MPS to 6% in PD in protected public lands during the 9-year period whereas the mean changing rates ranged from 21% in LSI to 32% in PD in private lands. Thus, ownership and conservation status appears to have a strong impact on the dynamic changes of landscape structures in the region. These results indicate that if maintenance and enhancement of relatively unfragmented, high-AGB forest is a goal, expansion of protected areas appears to be an important management strategy.

  7. 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

  8. 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

  9. 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.

  10. Dynamics associated with total aboveground biomass, C, nutrient pools, and biomass burning of primary forest and pasture in Rondo‸nia, Brazil during SCAR-B

    NASA Astrophysics Data System (ADS)

    Guild, Liane S.; Kauffman, J. Boone; Ellingson, Lisa J.; Cummings, Dian L.; Castro, Elmar A.; Babbitt, Ron E.; Ward, Darold E.

    1998-12-01

    Burning of slashed tropical forests and pastures is among the most significant global sources of atmospheric emissions, yet the composition of the fuels and fires that creates these emissions is not well characterized. As part of the Smoke, Clouds, and Radiation-Brazil (SCAR-B) experiment, we measured total aboveground biomass (TAGB) as well as carbon, nitrogen, and sulfur pools in one cattle pasture and two slashed primary forests in Rondônia, Brazil. These pools were measured before and immediately after fires. From these data, we calculated the quantities of biomass and elements lost to the atmosphere during biomass burning. Prefire biomass in the pasture was 66 Mg ha-1; fire consumed 31% of this mass. Woody debris from the forest that occupied this site 12 years previously comprised 81% of the pasture prefire TAGB. Elemental inputs into the atmosphere (site losses) from the pasture fire were 9 Mg C ha-1, 88 kg N ha-1, and 5 kg S ha-1. Combining previous studies with this one, we calculate that the mean TAGB of Amazonian pastures is 74 Mg ha-1 with a mean combustion factor of 46%. Mean nutrient losses from pasture fires in Amazonia are 14 Mg C ha-1, 199 kg N ha-1, and 16 kg S ha-1. The TAGB of the two slashed primary forests before fire was 355 and 399 Mg ha-1 and following fire was 188 and 185 Mg ha-1 (i.e., a combustion factor of 47 and 54%), respectively. Combining this study with other studies of Amazon slashed primary forests, we calculate that the mean TAGB is 349 Mg ha-1 and the mean combustion factor is 48%. Total elemental losses arising from the primary forest slash fires in this study were notably higher than losses from the pasture site: 79 and 102 Mg C ha-1; 1019 and 1196 kg N ha-1; and 87 and 96 kg S ha-1. From this study combined with previous research in Rondônia and Pará, we calculate that mean nutrient losses from primary forest slash fires are 88 Mg C ha-1, 1181 kg N ha-1, and 107 kg S ha-1. As rates of deforestation are remaining high in

  11. 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

  12. 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

  13. Biomass Mapping of US forests using synergy of Synthetic Aperture Radar and optical Remote Sensing

    NASA Astrophysics Data System (ADS)

    Kellndorfer, J. M.; Baccini, A.; Bishop, J.; Cartus, O.; Cormier, T.; Walker, W. S.; Santoro, M.

    2011-12-01

    The availability of several national remote sensing datasets with 30 m resolution for ca. year 2000, i.e. the SRTM DEM, the USGS National Elevation Dataset (NED), the National Land Cover Dataset 2001 (NLCD 2001) as well as Landsat ETM+ data compiled by the Multi-Resolution Land Characteristics Consortium (MRLC), represented a unique opportunity to produce a baseline canopy height and aboveground biomass map for the US, the National Biomass and Carbon Dataset, NBCD 2000. Differentiation of the SRTM Elevations and NED allowed the estimation of the SRTM phase scattering center height within the forest canopies, which was found to be a key predictor for the actual canopy height as well as for the aboveground biomass of live woody vegetation. Together with topographic information derived from the DEM, the NLCD maps and the Landsat data, the phase scattering center heights were used as spatial predictor layers in RandomForest for predicting canopy height and biomass. Forest survey data provided by the USDA Forest Service FIA program were available under a national Memorandum of Understanding and served as response variables for model development and validation. The production of the canopy height and biomass maps was done on a mapping zone basis in which the conterminous US was split into 66 ecoregionally distinct mapping zones. A bootstrap validation at different spatial scales resulted in biomass retrieval accuracies in terms of the root mean square error, RMSE, of 55 t/ha (at plot level), 19 t/ha (at hexagon level) and 14 t/ha (at county level). In case of canopy height, the RMSE was 3.8 m at plot level. In a follow-on project, we aim at generating regional datasets of changes in carbon stocks between the years 2000 and 2007 for the Northeastern US. In order to update the NBCD biomass map, ALOS PALSAR FBD data for the years 2007/08 were ordered from ASF. For the biomass retrieval with ALOS PALSAR data, we adopted a fully automated retrieval algorithm, presented in

  14. 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

  15. Evaluation of sensor types and environmental controls on mapping biomass of coastal marsh emergent vegetation

    USGS Publications Warehouse

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

    2014-01-01

    There is a need to quantify large-scale plant productivity in coastal marshes to understand marsh resilience to sea level rise, to help define eligibility for carbon offset credits, and to monitor impacts from land use, eutrophication and contamination. Remote monitoring of aboveground biomass of emergent wetland vegetation will help address this need. Differences in sensor spatial resolution, bandwidth, temporal frequency and cost constrain the accuracy of biomass maps produced for management applications. In addition the use of vegetation indices to map biomass may not be effective in wetlands due to confounding effects of water inundation on spectral reflectance. To address these challenges, we used partial least squares regression to select optimal spectral features in situ and with satellite reflectance data to develop predictive models of aboveground biomass for common emergent freshwater marsh species, Typha spp. and Schoenoplectus acutus, at two restored marshes in the Sacramento–San Joaquin River Delta, California, USA. We used field spectrometer data to test model errors associated with hyperspectral narrowbands and multispectral broadbands, the influence of water inundation on prediction accuracy, and the ability to develop species specific models. We used Hyperion data, Digital Globe World View-2 (WV-2) data, and Landsat 7 data to scale up the best statistical models of biomass. Field spectrometer-based models of the full dataset showed that narrowband reflectance data predicted biomass somewhat, though not significantly better than broadband reflectance data [R2 = 0.46 and percent normalized RMSE (%RMSE) = 16% for narrowband models]. However hyperspectral first derivative reflectance spectra best predicted biomass for plots where water levels were less than 15 cm (R2 = 0.69, %RMSE = 12.6%). In species-specific models, error rates differed by species (Typha spp.: %RMSE = 18.5%; S. acutus: %RMSE = 24.9%), likely due to the more vertical structure and

  16. 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.

  17. Space Radar Image of Raco Biomass Map

    NASA Technical Reports Server (NTRS)

    1999-01-01

    This biomass map of the Raco, Michigan, area was produced from data acquired by the Spaceborne Imaging Radar C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) onboard space shuttle Endeavour. Biomass is the amount of plant material on an area of Earth's surface. Radar can directly sense the quantity and organizational structure of the woody biomass in the forest. Science team members at the University of Michigan used the radar data to estimate the standing biomass for this Raco site in the Upper Peninsula of Michigan. Detailed surveys of 70 forest stands will be used to assess the accuracy of these techniques. The seasonal growth of terrestrial plants, and forests in particular, leads to the temporary storage of large amounts of carbon, which could directly affect changes in global climate. In order to accurately predict future global change, scientists need detailed information about current distribution of vegetation types and the amount of biomass present around the globe. Optical techniques to determine net biomass are frustrated by chronic cloud-cover. Imaging radar can penetrate through cloud-cover with negligible signal losses. Spaceborne Imaging Radar-C and X-Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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

  3. Mapping tropical forest biomass with radar and spaceborne LiDAR in Lopé National Park, Gabon: overcoming problems of high biomass and persistent cloud

    NASA Astrophysics Data System (ADS)

    Mitchard, E. T. A.; Saatchi, S. S.; White, L. J. T.; Abernethy, K. A.; Jeffery, K. J.; Lewis, S. L.; Collins, M.; Lefsky, M. A.; Leal, M. E.; Woodhouse, I. H.; Meir, P.

    2012-01-01

    Spatially-explicit maps of aboveground biomass are essential for calculating the losses and gains in forest carbon at a regional to national level. The production of such maps across wide areas will become increasingly necessary as international efforts to protect primary forests, such as the REDD+ (Reducing Emissions from Deforestation and forest Degradation) mechanism, come into effect, alongside their use for management and research more generally. However, mapping biomass over high-biomass tropical forest is challenging as (1) direct regressions with optical and radar data saturate, (2) much of the tropics is persistently cloud-covered, reducing the availability of optical data, (3) many regions include steep topography, making the use of radar data complex, (5) while LiDAR data does not suffer from saturation, expensive aircraft-derived data are necessary for complete coverage. We present a solution to the problems, using a combination of terrain-corrected L-band radar data (ALOS PALSAR), spaceborne LiDAR data (ICESat GLAS) and ground-based data. We map Gabon's Lopé National Park (5000 km2) because it includes a range of vegetation types from savanna to closed-canopy tropical forest, is topographically complex, has no recent contiguous cloud-free high-resolution optical data, and the dense forest is above the saturation point for radar. Our 100 m resolution biomass map is derived from fusing spaceborne LiDAR (7142 ICESat GLAS footprints), 96 ground-based plots (average size 0.8 ha) and an unsupervised classification of terrain-corrected ALOS PALSAR radar data, from which we derive the aboveground biomass stocks of the park to be 78 Tg C (173 Mg C ha-1). This value is consistent with our field data average of 181 Mg C ha-1, from the field plots measured in 2009 covering a total of 78 ha, and which are independent as they were not used for the GLAS-biomass estimation. We estimate an uncertainty of ±25% on our carbon stock value for the park. This error term

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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. PMID:18244941

  13. 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

  14. 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

  15. 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. PMID:25663395

  16. 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

  17. 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

  18. Forest Biomass Mapping from Prism Triplet, Palsar and Landsat Data

    NASA Astrophysics Data System (ADS)

    Ranson, J.; Sun, G.; Ni, W.

    2014-12-01

    The loss of sensitivity at higher biomass levels is a common problem in biomass mapping using optical multi-spectral data or radar backscattering data due to the lack of information on canopy vertical structure. Studies have shown that adding implicit information of forest vertical structure improves the performance of forest biomass mapping from optical reflectance and radar backscattering data. LiDAR, InSAR and stereo imager are the data sources for obtaining forest structural information. The potential of providing information on forest vertical structure by stereoscopic imagery data has drawn attention recently due to the availability of high-resolution digital stereo imaging from space and the advances of digital stereo image processing software. The Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observation Satellite (ALOS) has acquired multiple global coverage from June 2006 to April 2011 providing a good data source for regional/global forest studies. In this study, five PRISM triplets acquired on June 14, 2008, August 19 and September 5, 2009; PALSAR dual-pol images acquired on July 12, 2008 and August 30, 2009; and LANDSAT 5 TM images acquired on September 5, 2009 and the field plot data collected in 2009 and 2010 were used to map forest biomass at 50m pixel in an area of about 4000 km2in Maine, USA ( 45.2 deg N 68.6 deg W). PRISM triplets were used to generate point cloud data at 2m pixel first and then the average height of points above NED (National Elevation Dataset) within a 50m by 50m pixel was calculated. Five images were mosaicked and used as canopy height information in the biomass estimation along with the PALSAR HH, HV radar backscattering and optical reflectance vegetation indices from L-5 TM data. A small portion of this region was covered by the Land Vegetation and Ice Sensor (LVIS) in 2009. The biomass maps from the LVIS data was used to evaluate the results from combined use of PRISM, PALSAR and

  19. Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

    NASA Astrophysics Data System (ADS)

    Thurner, Martin; Beer, Christian; Santoro, Maurizio; Carvalhais, Nuno; Wutzler, Thomas; Schepaschenko, Dmitry; Shvidenko, Anatoly; Kompter, Elisabeth; Levick, Shaun; Schmullius, Christiane

    2013-04-01

    Quantifying the state and the change of the World's forests is crucial because of their ecological, social and economic value. Concerning their ecological importance, forests provide important feedbacks on the global carbon, energy and water cycles. In addition to their influence on albedo and evapotranspiration, they have the potential to sequester atmospheric carbon dioxide and thus to mitigate global warming. The current state and inter-annual variability of forest carbon stocks remain relatively unexplored, but remote sensing can serve to overcome this shortcoming. While for the tropics wall-to-wall estimates of above-ground biomass have been recently published, up to now there was a lack of similar products covering boreal and temperate forests. Recently, estimates of forest growing stock volume (GSV) were derived from ENVISAT ASAR C-band data for latitudes above 30° N. Utilizing a wood density and a biomass compartment database, a forest carbon density map covering North-America, Europe and Asia with 0.01° resolution could be derived out of this dataset. Allometric functions between stem, branches, root and foliage biomass were fitted and applied for different leaf types (broadleaf, needleleaf deciduous, needleleaf evergreen forest). Additionally, this method enabled uncertainty estimation of the resulting carbon density map. Intercomparisons with inventory-based biomass products in Russia, Europe and the USA proved the high accuracy of this approach at a regional scale (r2 = 0.70 - 0.90). Based on the final biomass map, the forest carbon stocks and densities (excluding understorey vegetation) for three biomes were estimated across three continents. While 40.7 ± 15.7 Gt of carbon were found to be stored in boreal forests, temperate broadleaf/mixed forests and temperate conifer forests contain 24.5 ± 9.4 Gt(C) and 14.5 ± 4.8 Gt(C), respectively. In terms of carbon density, most of the carbon per area is stored in temperate conifer (62.1 ± 20.7 Mg

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. Imaging Laser Altimetry in the Amazon: Mapping Large Areas of Topography, Vegetation Height and Structure, and Biomass

    NASA Technical Reports Server (NTRS)

    Blair, J. Bryan; Nelson, B.; dosSantos, J.; Valeriano, D.; Houghton, R.; Hofton, M.; Lutchke, S.; Sun, Q.

    2002-01-01

    A flight mission of NASA GSFC's Laser Vegetation Imaging Sensor (LVIS) is planned for June-August 2003 in the Amazon region of Brazil. The goal of this flight mission is to map the vegetation height and structure and ground topography of a large area of the Amazon. This data will be used to produce maps of true ground topography, vegetation height, and estimated above-ground biomass and for comparison with and potential calibration of Synthetic Aperture Radar (SAR) data. Approximately 15,000 sq. km covering various regions of the Amazon will be mapped. The LVIS sensor has the unique ability to accurately sense the ground topography beneath even the densest of forest canopies. This is achieved by using a high signal-to-noise laser altimeter to detect the very weak reflection from the ground that is available only through small gaps in between leaves and between tree canopies. Often the amount of ground signal is 1% or less of the total returned echo. Once the ground elevation is identified, that is used as the reference surface from which we measure the vertical height and structure of the vegetation. Test data over tropical forests have shown excellent correlation between LVIS measurements and biomass, basal area, stem density, ground topography, and canopy height. Examples of laser altimetry data over forests and the relationships to biophysical parameters will be shown. Also, recent advances in the LVIS instrument will be discussed.

  9. Biomass resilience of Neotropical secondary forests

    NASA Astrophysics Data System (ADS)

    Poorter, Lourens; Bongers, Frans; Aide, T. Mitchell; Almeyda Zambrano, Angélica M.; Balvanera, Patricia; Becknell, Justin M.; Boukili, Vanessa; Brancalion, Pedro H. S.; Broadbent, Eben N.; Chazdon, Robin L.; Craven, Dylan; de Almeida-Cortez, Jarcilene S.; Cabral, George A. L.; de Jong, Ben H. J.; Denslow, Julie S.; Dent, Daisy H.; Dewalt, Saara J.; Dupuy, Juan M.; Durán, Sandra M.; Espírito-Santo, Mario M.; Fandino, María C.; César, Ricardo G.; Hall, Jefferson S.; Hernandez-Stefanoni, José Luis; Jakovac, Catarina C.; Junqueira, André B.; Kennard, Deborah; Letcher, Susan G.; Licona, Juan-Carlos; Lohbeck, Madelon; Marín-Spiotta, Erika; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A.; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R. F.; Ochoa-Gaona, Susana; de Oliveira, Alexandre A.; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A.; Piotto, Daniel; Powers, Jennifer S.; Rodríguez-Velázquez, Jorge; Romero-Pérez, I. Eunice; Ruíz, Jorge; Saldarriaga, Juan G.; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B.; Steininger, Marc K.; Swenson, Nathan G.; Toledo, Marisol; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D. M.; Vester, Hans F. M.; Vicentini, Alberto; Vieira, Ima C. G.; Bentos, Tony Vizcarra; Williamson, G. Bruce; Rozendaal, Danaë M. A.

    2016-02-01

    Land-use change occurs nowhere more rapidly than in the tropics, where the imbalance between deforestation and forest regrowth has large consequences for the global carbon cycle. However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates are influenced by climate, landscape, and prior land use. Here we analyse aboveground biomass recovery during secondary succession in 45 forest sites and about 1,500 forest plots covering the major environmental gradients in the Neotropics. The studied secondary forests are highly productive and resilient. Aboveground biomass recovery after 20 years was on average 122 megagrams per hectare (Mg ha-1), corresponding to a net carbon uptake of 3.05 Mg C ha-1 yr-1, 11 times the uptake rate of old-growth forests. Aboveground biomass stocks took a median time of 66 years to recover to 90% of old-growth values. Aboveground biomass recovery after 20 years varied 11.3-fold (from 20 to 225 Mg ha-1) across sites, and this recovery increased with water availability (higher local rainfall and lower climatic water deficit). We present a biomass recovery map of Latin America, which illustrates geographical and climatic variation in carbon sequestration potential during forest regrowth. The map will support policies to minimize forest loss in areas where biomass resilience is naturally low (such as seasonally dry forest regions) and promote forest regeneration and restoration in humid tropical lowland areas with high biomass resilience.

  10. 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

  11. Mapping High Biomass Corridors for Climate and Biodiversity Co-Benefits

    NASA Astrophysics Data System (ADS)

    Jantz, P.; Goetz, S. J.; Laporte, N. T.

    2013-12-01

    A key issue in global conservation is how climate mitigation activities can secure biodiversity co-benefits. Tropical deforestation releases significant amounts of CO2 to the atmosphere and results in widespread biodiversity loss. The dominant strategy for forest conservation has been protected area designation. However, maintaining biodiversity in protected areas requires ecological exchange with ecosystems in which they are embedded. At current funding levels, existing conservation strategies are unlikely to prevent further loss of connectivity between protected areas and surrounding landscapes. The emergence of REDD+, a mechanism for funding carbon emissions reductions from deforestation in developing countries, suggests an alignment of goals and financial resources for protecting forest carbon, maintaining biodiversity in protected areas, and minimizing loss of forest ecosystem services. Identifying, protecting and sustainably managing vegetation carbon stocks between protected areas can provide both climate mitigation benefits through avoided CO2 emissions from deforestation and biodiversity benefits through the targeted protection of forests that maintain connectivity between protected areas and surrounding ecosystems. We used a high resolution, pan-tropical map of vegetation carbon stocks derived from MODIS, GLAS lidar and field measurements to map corridors that traverse areas of highest aboveground biomass between protected areas. We mapped over 13,000 corridors containing 49 GtC, accounting for 14% of unprotected vegetation carbon stock in the tropics. In the majority of cases, carbon density in corridors was commensurate with that of the protected areas they connect, suggesting significant opportunities for achieving climate mitigation and biodiversity co-benefits. To further illustrate the utility of this approach, we conducted a multi-criteria analysis of corridors in the Brazilian Amazon, identifying high biodiversity, high vegetation carbon stock

  12. Forest Biomass Mapping from Stereo Imagery and Radar Data

    NASA Astrophysics Data System (ADS)

    Sun, G.; Ni, W.; Zhang, Z.

    2013-12-01

    Both InSAR and lidar data provide critical information on forest vertical structure, which are critical for regional mapping of biomass. However, the regional application of these data is limited by the availability and acquisition costs. Some researchers have demonstrated potentials of stereo imagery in the estimation of forest height. Most of these researches were conducted on aerial images or spaceborne images with very high resolutions (~0.5m). Space-born stereo imagers with global coverage such as ALOS/PRISM have coarser spatial resolutions (2-3m) to achieve wider swath. The features of stereo images are directly affected by resolutions and the approaches use by most of researchers need to be adjusted for stereo imagery with lower resolutions. This study concentrated on analyzing the features of point clouds synthesized from multi-view stereo imagery over forested areas. The small footprint lidar and lidar waveform data were used as references. The triplets of ALOS/PRISM data form three pairs (forward/nadir, backward/nadir and forward/backward) of stereo images. Each pair of the stereo images can be used to generate points (pixels) with 3D coordinates. By carefully co-register these points from three pairs of stereo images, a point cloud data was generated. The height of each point above ground surface was then calculated using DEM from National Elevation Dataset, USGS as the ground surface elevation. The height data were gridded into pixel of different sizes and the histograms of the points within a pixel were analyzed. The average height of the points within a pixel was used as the height of the pixel to generate a canopy height map. The results showed that the synergy of point clouds from different views were necessary, which increased the point density so the point cloud could detect the vertical structure of sparse and unclosed forests. The top layer of multi-layered forest could be captured but the dense forest prevented the stereo imagery to see through

  13. 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

  14. Putting urban biomass on the map: contrasting case studies from three climactic zones

    NASA Astrophysics Data System (ADS)

    Raciti, S. M.; Hutyra, L.; Rao, P.; McHale, M. R.

    2012-12-01

    There is evidence that urban vegetation can provide important ecosystem services, however, existing maps of vegetation biomass tend to exclude developed land uses or report them as having little or no biomass. We used field and remote sensing data from the Boston, MA, Seattle, WA, and Phoenix Arizona metropolitan areas to 1) assess the potential for predicting urban biomass from remote sensing data, 2) explore the influence of land use and climate on urban biomass, 3) generate new biomass maps that explicitly include urban land uses, and 4) compare these biomass maps to existing products. For each metropolitan area, vegetation biomass was estimated for field plots using tree/shrub species, diameter at breast height (DBH) or ground level (DGL), and allometric equations. These field data were paired with geospatial data to assess the potential for creating vegetation biomass maps for each metropolitan area. The geospatial data included land use, land cover, impervious surface fraction, population density, and two remotely-sensed vegetation indices (Normalized Difference Vegetation Index [NDVI] and Enhanced Vegetation Index [EVI]). Preliminary findings suggest that the ability to predict biomass from remote sensing data varies with land use, climate, and dominant vegetation type. Existing vegetation biomass maps may considerably underestimate biomass, particularly in regions with extensive urban land cover. Urban areas are rapidly expanding and future development patterns will have significant impacts on terrestrial carbon stocks, anthropogenic emissions, and the ecosystem services provided by remnant and regrowing vegetation.

  15. Mapping carbon storage in urban trees with multi-source remote sensing data: relationships between biomass, land use, and demographics in Boston neighborhoods.

    PubMed

    Raciti, Steve M; Hutyra, Lucy R; Newell, Jared D

    2014-12-01

    High resolution maps of urban vegetation and biomass are powerful tools for policy-makers and community groups seeking to reduce rates of urban runoff, moderate urban heat island effects, and mitigate the effects of greenhouse gas emissions. We developed a very high resolution map of urban tree biomass, assessed the scale sensitivities in biomass estimation, compared our results with lower resolution estimates, and explored the demographic relationships in biomass distribution across the City of Boston. We integrated remote sensing data (including LiDAR-based tree height estimates) and field-based observations to map canopy cover and aboveground tree carbon storage at ~1m spatial scale. Mean tree canopy cover was estimated to be 25.5±1.5% and carbon storage was 355Gg (28.8MgCha(-1)) for the City of Boston. Tree biomass was highest in forest patches (110.7MgCha(-1)), but residential (32.8MgCha(-1)) and developed open (23.5MgCha(-1)) land uses also contained relatively high carbon stocks. In contrast with previous studies, we did not find significant correlations between tree biomass and the demographic characteristics of Boston neighborhoods, including income, education, race, or population density. The proportion of households that rent was negatively correlated with urban tree biomass (R(2)=0.26, p=0.04) and correlated with Priority Planting Index values (R(2)=0.55, p=0.001), potentially reflecting differences in land management among rented and owner-occupied residential properties. We compared our very high resolution biomass map to lower resolution biomass products from other sources and found that those products consistently underestimated biomass within urban areas. This underestimation became more severe as spatial resolution decreased. This research demonstrates that 1) urban areas contain considerable tree carbon stocks; 2) canopy cover and biomass may not be related to the demographic characteristics of Boston neighborhoods; and 3) that recent advances

  16. Mapping Carbon Storage in Urban Trees with Multi-source Remote Sensing Data: Relationships between Biomass, Land Use, and Demographics in Boston Neighborhoods

    NASA Astrophysics Data System (ADS)

    Raciti, S. M.; Hutyra, L.

    2014-12-01

    High resolution maps of urban vegetation and biomass are powerful tools for policy-makers and community groups seeking to reduce rates of urban runoff, moderate urban heat island effects, and mitigate the effects of greenhouse gas emissions. We develop a very high resolution map of urban tree biomass, assess the scale sensitivities in biomass estimation, compare our results with lower resolution estimates, and explore the demographic relationships in biomass distribution across the City of Boston. We integrated remote sensing data (including LiDAR-based tree height estimates) and field-based observations to map canopy cover and aboveground tree carbon storage at ~1 m spatial scale. Mean tree canopy cover was estimated to be 25.5±1.5% and carbon storage was 355 Gg (28.8 Mg C ha-1) for the City of Boston. Tree biomass was highest in forest patches (110.7 Mg C ha-1), but residential (32.8 Mg C ha-1) and developed open (23.5 Mg C ha-1) land uses also contained relatively high carbon stocks. In contrast with previous studies, we did not find significant correlations between tree biomass and the demographic characteristics of Boston neighborhoods, including income, education, race, or population density. The proportion of households that rent was negatively correlated with urban tree biomass (R2=0.26, p=0.04) and correlated with Priority Planting Index values (R2=0.55, p=0.001), potentially reflecting differences in land management among rented and owner-occupied residential properties. We compared our very high resolution biomass map to lower resolution biomass products from other sources and found that those products consistently underestimated biomass within urban areas. This underestimation became more severe as spatial resolution decreased. This research demonstrates that 1) urban areas contain considerable tree carbon stocks; 2) canopy cover and biomass may not be related to the demographic characteristics of Boston neighborhoods; and 3) that recent advances in

  17. Yield mapping of high-biomass sorghum with aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 high biomass...

  18. 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.

  19. 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 ...

  20. Aboveground biomass of an invasive tree Melaleuca (Melaleuca quinquenervia) before and after herbivory by adventive and introduced natural enemies: a temporal case-study in Florida

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Invasive plants may respond to injury from natural enemies by altering the quantity and distribution of biomass among woody materials, foliage, fruits, and seeds. Melaleuca, an Australian tree that has naturalized in south Florida, USA, has been reunited with two natural enemies: a weevil introduce...

  1. 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.

  2. Biomass mapping using biophysical forest type characterisation of SAR polarimetric images

    NASA Astrophysics Data System (ADS)

    Quiñones, Marcela J.; Hoekman, Dirk H.

    2002-01-01

    Studies on the relationship between biomass and radar backscatter have relied on field data to construct empirical relationships with radar backscatter that can be used for biomass estimations and mapping. In general, inversion of radar data for biomass estimations is limited by the variations on backscatter produced by structural parameters and soil moisture and limited to a certain maximum biomass level dependent on the structural class. In this work we created biomass maps of two study sites at the Colombian Amazon (Guaviare and Araracuara) by using results from polarimetric classification algorithm that combines power, phase and correlation of C, L and P band of AirSAR data. Two different approaches were used. For the Guaviare site, (dry and flat) the biomass classes selected are related to Land Cover types and an empirical relationship between biomass and the average backscatter (LHV+PRR)/2) is used to create the biomass map. High consistency with the cover map is found. For the Araracuara site (hilly and flooded) a biomass map is created by reclassifying a biophysical forest structural map with biomass values obtained from field available data. Field data is used to validate maps and to study the behavior of radar polarimetric signatures according to different forest structures. A new approach of analysis is based on the description of the polarimetric coherence according to a physical explanation of the wave-object interactions. The same type of analysis is used to study systematically the influence of different forest structural parameters and soil moisture conditions on the polarimetric signatures. Simulated radar data from the UTARTCAN backscatter model is used.

  3. Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

    NASA Technical Reports Server (NTRS)

    Ranson, K. J.; Sun, Guoqing

    1992-01-01

    Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

  4. Comparing the Accuracy of Aboveground Biomass Estimates and Forest Structure Metrics at Large Footprint Level: Satellite Waveform Lidar vs. Discrete-Return Airborne Lidar

    NASA Astrophysics Data System (ADS)

    Popescu, S. C.; Zhao, K.; Gatziolis, D.

    2009-12-01

    The overall goal of this paper was to compare biomass estimates and forest structure metrics obtained by processing ICESat waveform data and spatially coincident discrete-return airborne lidar data over varied terrain conditions. For mostly flat-terrain conditions, we investigated lidar data over forests in east Texas, which are characteristics for most of the south-eastern United States, thus allowing terrain to be largely excluded as a source of error. For sloped-terrain, we used lidar data over forests in Oregon. With biomass estimates derived from waveform height metrics, we also compared ground elevation measurements and canopy parameters. Specific objectives were to: compare ground elevations and canopy height parameters derived from ICESat and airborne lidar; (2) investigate above ground biomass estimates; (3) develop a 3D ray-tracing model to simulate lidar waveforms over forests with sloped terrain; and (4) test model performance with real lidar data over terrain with varied topography. Over flat terrain, results indicated a very strong correlation for terrain elevations between ICESat and airborne lidar, with R-square values of 0.98 and sub-meter RMSE. ICESat height variables were able to explain 80% of the variance associated with the reference biomass derived from airborne lidar, with an RMSE of 37.7 Mg/ha. Most of the models for height metrics had R-square values above 0.9. Results from ongoing investigations for sloped-terrain are expected to establish practical procedures for improving analysis of waveform data in vegetation studies.

  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. 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

  7. Biomass resilience of Neotropical secondary forests.

    PubMed

    Poorter, Lourens; Bongers, Frans; Aide, T Mitchell; Almeyda Zambrano, Angélica M; Balvanera, Patricia; Becknell, Justin M; Boukili, Vanessa; Brancalion, Pedro H S; Broadbent, Eben N; Chazdon, Robin L; Craven, Dylan; de Almeida-Cortez, Jarcilene S; Cabral, George A L; de Jong, Ben H J; Denslow, Julie S; Dent, Daisy H; DeWalt, Saara J; Dupuy, Juan M; Durán, Sandra M; Espírito-Santo, Mario M; Fandino, María C; César, Ricardo G; Hall, Jefferson S; Hernandez-Stefanoni, José Luis; Jakovac, Catarina C; Junqueira, André B; Kennard, Deborah; Letcher, Susan G; Licona, Juan-Carlos; Lohbeck, Madelon; Marín-Spiotta, Erika; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R F; Ochoa-Gaona, Susana; de Oliveira, Alexandre A; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A; Piotto, Daniel; Powers, Jennifer S; Rodríguez-Velázquez, Jorge; Romero-Pérez, I Eunice; Ruíz, Jorge; Saldarriaga, Juan G; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B; Steininger, Marc K; Swenson, Nathan G; Toledo, Marisol; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D M; Vester, Hans F M; Vicentini, Alberto; Vieira, Ima C G; Bentos, Tony Vizcarra; Williamson, G Bruce; Rozendaal, Danaë M A

    2016-02-11

    Land-use change occurs nowhere more rapidly than in the tropics, where the imbalance between deforestation and forest regrowth has large consequences for the global carbon cycle. However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates are influenced by climate, landscape, and prior land use. Here we analyse aboveground biomass recovery during secondary succession in 45 forest sites and about 1,500 forest plots covering the major environmental gradients in the Neotropics. The studied secondary forests are highly productive and resilient. Aboveground biomass recovery after 20 years was on average 122 megagrams per hectare (Mg ha(-1)), corresponding to a net carbon uptake of 3.05 Mg C ha(-1) yr(-1), 11 times the uptake rate of old-growth forests. Aboveground biomass stocks took a median time of 66 years to recover to 90% of old-growth values. Aboveground biomass recovery after 20 years varied 11.3-fold (from 20 to 225 Mg ha(-1)) across sites, and this recovery increased with water availability (higher local rainfall and lower climatic water deficit). We present a biomass recovery map of Latin America, which illustrates geographical and climatic variation in carbon sequestration potential during forest regrowth. The map will support policies to minimize forest loss in areas where biomass resilience is naturally low (such as seasonally dry forest regions) and promote forest regeneration and restoration in humid tropical lowland areas with high biomass resilience. PMID:26840632

  8. Aboveground storage tank regulations

    SciTech Connect

    Geyer, W. )

    1993-01-01

    There are critical differences between the potential for environmental impact of aboveground and underground oil storage. For example, while leaks from underground storage tanks (USTs) seep into soil or aquifers, the concern with aboveground storage tanks (ASTs) is that an overfill or tank rupture can cause product to escape into a navigable stream and immediately create an oil spill pollution incident. The US Environmental Protection Agency (EPA) has very distinct programs outlining regulation parameters for each type of storage, including source of authority, regulatory cutoffs and exclusions, definitions, prevention and response requirements, and penalties, etc. Engineers considering changes or recommending a change in type of storage, particularly from a UST to an AST, need to be aware of existing federal regulations. Since the federal UST program began, remediation costs have skyrocketed as a result of the need to clean up leaking tank and piping sites, backfill and surrounding soil or groundwater. Compliance with federal and state UST regulations has not been cheap, and is expected to top $23 billion, according to some estimates. Partly as a result, market demand has shifted toward use of aboveground storage tanks, a trend that is expected to continue. Industry figures show a 100% increase in factory fabricated aboveground tank activity during the last four years.

  9. Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers

    USGS Publications Warehouse

    Esselman, Peter C.; Stevenson, R Jan; Lupi, Frank; Riseng, Catherine M.; Wiley, Michael J.

    2015-01-01

    The increased integration of ecosystem service concepts into natural resource management places renewed emphasis on prediction and mapping of fish biomass as a major provisioning service of rivers. The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity. We examined hypotheses about fish responses to total phosphorus (TP), as TP is a growth-limiting nutrient known to cause increases (subsidy response) and/or decreases (stress response) in fish biomass depending on its concentration and the species being considered. Boosted regression trees were used to define nonlinear functions that predicted the standing crops of Brook Trout Salvelinus fontinalis, Brown Trout Salmo trutta, Smallmouth Bass Micropterus dolomieu, panfishes (seven centrarchid species), and Walleye Sander vitreus by using landscape and modeled local-scale predictors. Fitted models were highly significant and explained 22–56% of the variation in validation data sets. Nonlinear and threshold responses were apparent for numerous predictors, including TP concentration, which had significant effects on all except the Walleye fishery. Brook Trout and Smallmouth Bass exhibited both subsidy and stress responses, panfish biomass exhibited a subsidy response only, and Brown Trout exhibited a stress response. Maps of reach-specific standing crop predictions showed patterns of predicted fish biomass that corresponded to spatial patterns in catchment area, water temperature, land cover, and nutrient availability. Maps illustrated predictions of higher trout biomass in coldwater streams draining glacial till in northern Michigan, higher Smallmouth Bass and panfish biomasses in warmwater systems of southern Michigan, and high Walleye biomass in large main-stem rivers throughout the state. Our results allow fisheries managers to examine the biomass

  10. 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.

  11. Biomass Thermogravimetric Analysis: Uncertainty Determination Methodology and Sampling Maps Generation

    PubMed Central

    Pazó, Jose A.; Granada, Enrique; Saavedra, Ángeles; Eguía, Pablo; Collazo, Joaquín

    2010-01-01

    The objective of this study was to develop a methodology for the determination of the maximum sampling error and confidence intervals of thermal properties obtained from thermogravimetric analysis (TG), including moisture, volatile matter, fixed carbon and ash content. The sampling procedure of the TG analysis was of particular interest and was conducted with care. The results of the present study were compared to those of a prompt analysis, and a correlation between the mean values and maximum sampling errors of the methods were not observed. In general, low and acceptable levels of uncertainty and error were obtained, demonstrating that the properties evaluated by TG analysis were representative of the overall fuel composition. The accurate determination of the thermal properties of biomass with precise confidence intervals is of particular interest in energetic biomass applications. PMID:20717532

  12. Aboveground production does not increase after ten years of elevated CO2 in the Mojave Desert

    NASA Astrophysics Data System (ADS)

    Newingham, B. A.; Vanier, C. H.; Charlet, D.; Zitzer, S. F.; Smith, S. D.

    2011-12-01

    Elevated atmospheric CO2 ([CO2]) is assumed to increase primary production, particularly in desert systems through stimulatory effects on plant water-use efficiency. We examined the effects of elevated [CO2] at the Nevada Desert FACE (Free-air CO2 Enrichment) Facility (NDFF) in an intact Mojave Desert ecosystem. At the NDFF, ambient and elevated [CO2] levels were 360 and 550 μmol mol-1 [CO2], respectively. CO2 treatments were applied continuously from 1997-2007 in intact plots 25 m in diameter. While other studies focused on soil and root responses to elevated [CO2], our study focused on aboveground production of annuals and perennial plants. In 1997, diameters and heights of all perennial individuals were recorded and mapped. In 2007, diameters and heights were re-measured and aboveground biomass was harvested for every mapped perennial individual. Harvest data were used to construct regressions for twenty perennial species to predict starting biomass based on diameters and heights. Annual plants were harvested yearly at peak biomass from permanent transects. We found no significant effect of elevated [CO2] on total perennial plant biomass or cover at the end of the experiment. Regardless of [CO2] treatment, perennial cover increased while total biomass did not change over the ten years of the experiment. Perennial biomass allocation to vegetative, twig and woody biomass was not differentially affected by elevated [CO2], although leaf area index increased under elevated [CO2]. Similarly, there was no consistent elevated [CO2] effect on yearly production of annual (ephemeral) plants, although an exotic grass (Bromus madritensis subsp. rubens) exhibited a higher relative stimulation in production at elevated [CO2] than did native dicot and grass species. Other studies in our research group have shown that increases in production are only seen in wet years during the ten-year period of CO2 treatments at the NDFF, and so future effects of rising [CO2] may primarily

  13. Combined Use of Active and Passive Remote Sensing for Mapping Distribution and Biomass of Coastal Mangroves

    NASA Astrophysics Data System (ADS)

    Aslan, A.; Rahman, A. F.; Warren, M.; Robeson, S. M.; Darusman, T.

    2014-12-01

    Remote sensing provides a potentially fast, cost-effective, and efficient tool for mapping and monitoring mangroves located in relatively inaccessible areas where field measurements are often difficult and expensive. In this study, we examined the utility of combining Landsat-8 (LDCM), ALOS-PALSAR, and SRTM satellite imagery for mapping mangrove species composition, its canopy height and biomass distribution in the Mimika District of Papua, Indonesia. Image segmentation of ALOS-PALSAR radar data were used to delineate mangrove areas, while flexible statistical expert-based classification of spectral signatures from Landsat-8 (LDCM) images were used to classify mangrove associations. The overall accuracy of mangrove mapping for the entire area was 94.38% with kappa coefficient of 0.94 when validated with field data and QuickBird image data with 2.44 m spatial resolution. Mangrove height and biomass were mapped using the SRTM-based elevation, which were calibrated with field-measured canopy height via regression models. There was a strong linear relationship between the SRTM data and field-measured vegetation height (r = 0.87 and adjusted R2 = 0.76). A bootstrap simulation of 10,000 runs with replacement resulted in an error of 3.03 m (RMSE) and 2.33 m (MAE) for mean tree height over 30 m pixels. SRTM-derived canopy height and plot-level biomass from the 22 mangrove plots showed a strong non-linear relationship with an R2=0.75. Our results showed that mangrove standing biomass in the Mimika District varies from 70.32 Mg/ha to 511.80 Mg/ha with mean biomass error of 65.23 Mg/ha (RMSE) and 58.10 Mg/ha (MAE) over a pixel of 90 m. This study explored a set of reliable methodologies which can be applied for mapping and monitoring mangrove dynamics of large areas in Indonesia.

  14. High-Resolution Regional Biomass Map of Siberia from Glas, Palsar L-Band Radar and Landsat Vcf Data

    NASA Astrophysics Data System (ADS)

    Sun, G.; Ranson, K.; Montesano, P.; Zhang, Z.; Kharuk, V.

    2015-12-01

    The Arctic-Boreal zone is known be warming at an accelerated rate relative to other biomes. The taiga or boreal forest covers over 16 x106 km2 of Arctic North America, Scandinavia, and Eurasia. A large part of the northern Boreal forests are in Russia's Siberia, as area with recent accelerated climate warming. During the last two decades we have been working on characterization of boreal forests in north-central Siberia using field and satellite measurements. We have published results of circumpolar biomass using field plots, airborne (PALS, ACTM) and spaceborne (GLAS) lidar data with ASTER DEM, LANDSAT and MODIS land cover classification, MODIS burned area and WWF's ecoregion map. Researchers from ESA and Russia have also been working on biomass (or growing stock) mapping in Siberia. For example, they developed a pan-boreal growing stock volume map at 1-kilometer scale using hyper-temporal ENVISAT ASAR ScanSAR backscatter data. Using the annual PALSAR mosaics from 2007 to 2010 growing stock volume maps were retrieved based on a supervised random forest regression approach. This method is being used in the ESA/Russia ZAPAS project for Central Siberia Biomass mapping. Spatially specific biomass maps of this region at higher resolution are desired for carbon cycle and climate change studies. In this study, our work focused on improving resolution ( 50 m) of a biomass map based on PALSAR L-band data and Landsat Vegetation Canopy Fraction products. GLAS data were carefully processed and screened using land cover classification, local slope, and acquisition dates. The biomass at remaining footprints was estimated using a model developed from field measurements at GLAS footprints. The GLAS biomass samples were then aggregated into 1 Mg/ha bins of biomass and mean VCF and PALSAR backscatter and textures were calculated for each of these biomass bins. The resulted biomass/signature data was used to train a random forest model for biomass mapping of entire region from 50o

  15. Mapping Biomass for REDD in the Largest Forest of Central Africa: the Democratic Republic of Congo

    NASA Astrophysics Data System (ADS)

    Shapiro, Aurelie; Saatchi, Sassan

    2014-05-01

    With the support of the International Climate Initiative (ICI) of the Federal Ministry of the Environment, Conservation, and Nuclear Security, the implementation of the German Development Bank KfW, the World Wide Fund for Nature (WWF) Germany, the University of California Los Angeles (UCLA) and local DRC partners will produce a national scale biomass map for the entire forest coverage of the Democratic Republic of Congo (DRC) along with feasibility assessments of different forest protection measures within a framework of a REDD+ model project. The « Carbon Map and Model (CO2M&M) » project will produce a national forest biomass map for the DRC, which will enable quantitative assessments of carbon stocks and emissions in the largest forest of the Congo Basin. This effort will support the national REDD (Reducing Emissions from Deforestation and Degradation) program in DRC, which plays a major role in sustainable development and poverty alleviation. This map will be developed from field data, complemented by airborne LiDAR (Light Detection and Ranging) and aerial photos, systematically sampled throughout the forests of the DRC and up-scaled to satellite images to accurately estimate carbon content in all forested areas. The second component of the project is to develop specific approaches for model REDD projects in key landscapes. This project represents the largest LiDAR-derived mapping effort in Africa, under unprecedented logistical constraints, which will provide one of the poorest nations in the world with the richest airborne and satellites derived datasets for analyzing forest structure, biomass and biodiversity.

  16. The impact of biomass burning on the tropospheric distribution of CO during the 1984 maps experiment

    SciTech Connect

    Saylor, R.D.; Easter, R.C.; Chapman, E.G.

    1996-12-31

    The purpose of the work reported here was to use a global, three-dimensional tropospheric chemistry model to analyze and evaluate carbon monoxide (CO) experimental data. The data was obtained from the Measurement of Air Pollution by Satellites (MAPS) program. The model was used to investigate the role of biomass burning on the global distribution of CO during early October 1984. Global simulations of CO emissions, transport, and chemistry were made using archived meteorological data. To allow direct comparison with the MAPS data, the model results were column-weighted. The model CO distribution had several similarities with the MAPS data. Major maxima of CO mixing ratios occur over southern Africa and South America in the model and in MAPS measurements. Modeled and MAPS CO values compare favorably over Europe and eastern Asia. A major difference between the modeled distribution and the MAPS data was the location of the maximum over South America. This difference may be the result of differences in actual emissions or may be due to differences in the location of modeled and actual convective activity. Another significant difference was that the model showed a distinct plume of CO emanating from eastern North America while the MAPS data does not. To further test the accuracy of the model simulation, the results were compared to three other measurements of CO data that were taken during the same time period or that should be representative of conditions in remote areas. 9 refs., 2 figs., 3 tabs.

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

    NASA Astrophysics Data System (ADS)

    Dubayah, R.

    2015-12-01

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

  18. Mapping continental-scale biomass burning and smoke palls from the space shuttle

    NASA Technical Reports Server (NTRS)

    Lulla, Kamlesh; Helfert, Michael

    1992-01-01

    Space shuttle photographs have been used to map the areal extent of Amazonian smoke palls associated with biomass burning. Areas covered with smoke have increased from approximately 300,000 sq km to continental-size smoke palls of approximately 3,000,000 sq km. The smoke palls interpreted from the STS-48 data indicate that this phenomenon is persistent. Astronaut observations of such dynamic and vital environmental phenomena indicate the possibility of intergrating the earth observation capabilities of all space platforms in future modeling of the earth's dynamic processes.

  19. Integration of Canopy Height Information Derived from Stereo Imagery with SAR Backscatter Data to Improve Biomass Mapping

    NASA Astrophysics Data System (ADS)

    Sun, G.; Ranson, J.; Montesano, P. M.; Ni, W.

    2015-12-01

    Accurate forest biomass estimation over large areas is important for studies of global climate change and the carbon cycle. Synthetic Aperture Radar (SAR) is known to be effective for assessing forest biomass. SAR penetrates farther into forest canopies than optical sensors, so SAR data from forested areas can be related to standing woody biomass, especially at longer L and P bands wavelength. The effect of forest structure on radar signature reduces its sensitivity to biomass when the biomass reaches a threshold level (e.g. ~100Mg/ha at L-band). Therefore the ability for forest biomass mapping using only backscattering coefficients is limited. However, including height data in forest biomass mapping using SAR data will improve the sensitivity beyond saturation levels. There are many ways to get information related to forest canopy height including: 1) Lidar, a direct measurement of canopy height; 2) Height of scattering phase center (HSPC) from InSAR; 3) HSPC difference from two bands of InSAR, and 4) Polarimetric Interferometric SAR, which employs the polarization-dependent coherences. Photogrammetry (or stereo imagery) is another technique for quantifying forest vertical structure and is a traditional technique for the extraction of a digital surface model. The launch of spaceborne sensors, the application of digital cameras, the maturation of photogrammetry theory and the development of fully digital and automatic image processing make the application of photogrammetric methods feasible. Our previous studies using ALOS PRISM data have shown that the canopy height derived from PRISM stereo data were highly correlated with LVIS RH50 data. In this study we have integrated this canopy height with L-band SAR imagery data to map forest biomass in our test site in Howland, Maine. The point cloud data from multi-pair stereo imageries of five PRISM scenes were co-registered and used along with the USGS NED data to calculate the mean canopy height at 30m pixels. Multi

  20. On the potential of long wavelength imaging radars for mapping vegetation types and woody biomass in tropical rain forests

    NASA Technical Reports Server (NTRS)

    Rignot, Eric J.; Zimmermann, Reiner; Oren, Ram

    1995-01-01

    In the tropical rain forests of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 100 kg/sq m in old, undisturbed floodplain stands, the P-band polarimetric radar data gathered in June of 1993 by the AIRSAR (Airborne Synthetic Aperture Radar) instrument separate most major vegetation formations and also perform better than expected in estimating woody biomass. The worldwide need for large scale, updated biomass estimates, achieved with a uniformly applied method, as well as reliable maps of land cover, justifies a more in-depth exploration of long wavelength imaging radar applications for tropical forests inventories.

  1. High-resolution mapping of biomass burning emissions in tropical regions across three continents

    NASA Astrophysics Data System (ADS)

    Shi, Yusheng; Matsunaga, Tsuneo; Saito, Makoto

    2015-04-01

    Biomass burning emissions from open vegetation fires (forest fires, savanna fires, agricultural waste burning), human waste and biofuel combustion contain large amounts of trace gases (e.g., CO2, CH4, and N2O) and aerosols (BC and OC), which significantly impact ecosystem productivity, global atmospheric chemistry, and climate . With the help of recently released satellite products, biomass density based on satellite and ground-based observation data, and spatial variable combustion factors, this study developed a new high-resolution emissions inventory for biomass burning in tropical regions across three continents in 2010. Emissions of trace gases and aerosols from open vegetation burning are estimated from burned areas, fuel loads, combustion factors, and emission factors. Burned areas were derived from MODIS MCD64A1 burned area product, fuel loads were mapped from biomass density data sets for herbaceous and tree-covered land based on satellite and ground-based observation data. To account for spatial heterogeneity in combustion factors, global fractional tree cover (MOD44B) and vegetation cover maps (MCD12Q1) were introduced to estimate the combustion factors in different regions by using their relationship with tree cover under less than 40%, between 40-60% and above 60% conditions. For emission factors, the average values for each fuel type from field measurements are used. In addition to biomass burning from open vegetation fires, the emissions from human waste (residential and dump) burning and biofuel burning in 2010 were also estimated for 76 countries in tropical regions across the three continents and then allocated into each pixel with 1 km grid based on the population density (Gridded Population of the World v3). Our total estimates for the tropical regions across the three continents in 2010 were 17744.5 Tg CO2, 730.3 Tg CO, 32.0 Tg CH4, 31.6 Tg NOx, 119.2 Tg NMOC, 6.3 Tg SO2, 9.8 NH3 Tg, 81.8 Tg PM2.5, 48.0 Tg OC, and 5.7 Tg BC, respectively. Open

  2. Mapping the in situ microscale distribution of microphytobenthic biomass in coastal sediments: a hyperspectral methodology

    NASA Astrophysics Data System (ADS)

    Chennu, A.; Volkenborn, N.; Janssen, F.; Polerecky, L.

    2012-04-01

    Microphytobenthic primary production is the fundament of the trophic food web in coastal marine sediments. The concentration of photopigments, which are a proxy for phototrophic biomass, in the surface sediment is considered as a basic environmental descriptor in benthic studies. The mechanisms that control the distribution of benthic microalgae are complex, ranging from physico-chemical drivers (e.g. tidal action, nutrient availability) to ecological drivers (e.g. grazing). Here we present a novel, field-deployable hyperspectral imaging system that allows non-invasive in situ mapping of the photosynthetic microalgal biomass distribution with a high spatial (<1mm) and temporal (minutes) resolution. Using this system, we found a remarkably heterogeneous and dynamic distribution of microalgae in surficial intertidal sediments. These distributions were tightly linked to sediment surface topography (e.g. ripples) and to the distribution and activity of benthic infauna. We hypothesize that this correlation is facilitated by the influence of these factors on the advective transport of porewater and the associated fluxes of dissolved nutrients across the sediment-water interface. We argue that the utility of the high-resolution hyperspectral imaging method overcomes the inadequate resolution of traditional methods based on sedimentary chlorophyll extraction, and significantly improves our understanding of the processes that control benthic productivity in coastal sediments.

  3. 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

  4. Above- and Belowground Biomass Allocation in Shrub Biomes across the Northeast Tibetan Plateau

    PubMed Central

    Yang, Yuanhe; Yang, Lucun; Zhou, Guoying

    2016-01-01

    Biomass partitioning has been explored across various biomes. However, the strategies of allocation in plants still remain contentious. This study investigated allocation patterns of above- and belowground biomass at the community level, using biomass survey from the Tibetan Plateau. We explored above- and belowground biomass by conducting three consecutive sampling campaigns across shrub biomes on the northeast Tibetan Plateau during 2011–2013. We then documented the above-ground biomass (AGB), below-ground biomass (BGB) and root: shoot ratio (R/S) and the relationships between R/S and environment factors using data from 201 plots surveyed from 67 sites. We further examined relationships between above-ground and below-ground biomass across various shrub types. Our results indicated that the median values of AGB, BGB, and R/S in Tibetan shrub were 1102.55, 874.91 g m-2, and 0.85, respectively. R/S showed significant trend with mean annual precipitation (MAP), while decreased with mean annual temperature (MAT). Reduced major axis analysis indicated that the slope of the log-log relationship between above- and belowground biomass revealed a significant difference from 1.0 over space, supporting the optimal hypothesis. Interestingly, the slopes of the allometric relationship between log AGB and log BGB differed significantly between alpine and desert shrub. Our findings supported the optimal theory of above- and belowground biomass partitioning in Tibetan shrub, while the isometric hypothesis for alpine shrub at the community level. PMID:27119379

  5. Estimating Above-Ground Biomass Within the Footprint of an Eddy-Covariance Flux Tower: Continuous LiDAR Based Estimates Compared With Discrete Inventory and Disturbance History Based Stratification Boundaries

    NASA Astrophysics Data System (ADS)

    Ferster, C. J.; Trofymow, J. A.; Coops, N. C.; Chen, B.; Black, T. A.

    2008-12-01

    Eddy-covariance (EC) flux towers provide data about carbon (C) exchange between land and the atmosphere at an ecosystem scale. However, important research questions need to be addressed when placing EC flux towers in complex heterogeneous forest landscapes, such as the coastal forests of Western Canada. Recently available footprint analysis, which describes the contribution function and catchment area where EC flux is being measured, can be used to relate EC flux tower measurements with the biological structure and carbon stock distributions of complex forest landscapes. In this study, above ground biomass is estimated near an EC flux tower using two approaches. In the first approach, a remote sensing based surface representing above ground biomass was estimated using small footprint, discrete return, light detection and ranging (LiDAR) data. Plot level LiDAR metrics were supplemented with metrics calculated using individual tree detection. A multiple regression model was developed to estimate above ground biomass using ground plot and LiDAR data, and then the model was applied across the EC flux footprint area to estimate the spatial distribution of above ground biomass. In the second approach, line boundaries from forest inventory, disturbance history, and site series were used to delineate discrete stratification units and the measured groundplot data assigned to the various strata. Within the heterogeneous tower footprint area, footprint weighting allows us to compare and contrast above ground biomass estimates from these two approaches. Using this methodology we then plan to compare, for the same period, ground-based measurements of ecosystem C stock changes with accumulative EC measured net ecosystem C flux.

  6. Aboveground carbon in Quebec forests: stock quantification at the provincial scale and assessment of temperature, precipitation and edaphic properties effects on the potential stand-level stocking.

    PubMed

    Duchesne, Louis; Houle, Daniel; Ouimet, Rock; Lambert, Marie-Claude; Logan, Travis

    2016-01-01

    Biological carbon sequestration by forest ecosystems plays an important role in the net balance of greenhouse gases, acting as a carbon sink for anthropogenic CO2 emissions. Nevertheless, relatively little is known about the abiotic environmental factors (including climate) that control carbon storage in temperate and boreal forests and consequently, about their potential response to climate changes. From a set of more than 94,000 forest inventory plots and a large set of spatial data on forest attributes interpreted from aerial photographs, we constructed a fine-resolution map (∼375 m) of the current carbon stock in aboveground live biomass in the 435,000 km(2) of managed forests in Quebec, Canada. Our analysis resulted in an area-weighted average aboveground carbon stock for productive forestland of 37.6 Mg ha(-1), which is lower than commonly reported values for similar environment. Models capable of predicting the influence of mean annual temperature, annual precipitation, and soil physical environment on maximum stand-level aboveground carbon stock (MSAC) were developed. These models were then used to project the future MSAC in response to climate change. Our results indicate that the MSAC was significantly related to both mean annual temperature and precipitation, or to the interaction of these variables, and suggest that Quebec's managed forests MSAC may increase by 20% by 2041-2070 in response to climate change. Along with changes in climate, the natural disturbance regime and forest management practices will nevertheless largely drive future carbon stock at the landscape scale. Overall, our results allow accurate accounting of carbon stock in aboveground live tree biomass of Quebec's forests, and provide a better understanding of possible feedbacks between climate change and carbon storage in temperate and boreal forests. PMID:26966680

  7. Aboveground carbon in Quebec forests: stock quantification at the provincial scale and assessment of temperature, precipitation and edaphic properties effects on the potential stand-level stocking

    PubMed Central

    Houle, Daniel; Ouimet, Rock; Lambert, Marie-Claude; Logan, Travis

    2016-01-01

    Biological carbon sequestration by forest ecosystems plays an important role in the net balance of greenhouse gases, acting as a carbon sink for anthropogenic CO2 emissions. Nevertheless, relatively little is known about the abiotic environmental factors (including climate) that control carbon storage in temperate and boreal forests and consequently, about their potential response to climate changes. From a set of more than 94,000 forest inventory plots and a large set of spatial data on forest attributes interpreted from aerial photographs, we constructed a fine-resolution map (∼375 m) of the current carbon stock in aboveground live biomass in the 435,000 km2 of managed forests in Quebec, Canada. Our analysis resulted in an area-weighted average aboveground carbon stock for productive forestland of 37.6 Mg ha−1, which is lower than commonly reported values for similar environment. Models capable of predicting the influence of mean annual temperature, annual precipitation, and soil physical environment on maximum stand-level aboveground carbon stock (MSAC) were developed. These models were then used to project the future MSAC in response to climate change. Our results indicate that the MSAC was significantly related to both mean annual temperature and precipitation, or to the interaction of these variables, and suggest that Quebec’s managed forests MSAC may increase by 20% by 2041–2070 in response to climate change. Along with changes in climate, the natural disturbance regime and forest management practices will nevertheless largely drive future carbon stock at the landscape scale. Overall, our results allow accurate accounting of carbon stock in aboveground live tree biomass of Quebec’s forests, and provide a better understanding of possible feedbacks between climate change and carbon storage in temperate and boreal forests. PMID:26966680

  8. Mapping afforestation and forest biomass using time-series Landsat stacks

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    Satellite data can adequately capture forest dynamics over larger areas. Firstly, the Landsat ground surface reflectance (GSR) images from 1974 to 2013 were collected and processed based on 6S atmospheric transfer code and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the dense time-series Landsat GSR images, and the afforestation age was successfully retrieved from the Landsat time-series stacks in the last forty years and shown to be consistent with the surveyed tree ages. Then, the above ground biomass (AGB) regression models were greatly improved by integrating the simple ratio vegetation index (SR) and tree age. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in six 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 forest area, 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 1 t/ha. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.

  9. Using pan-tropical biomass maps to improve IPCC Tier 1 default level emission factors - a case study for the Democratic Republic of the Congo (DRC)

    NASA Astrophysics Data System (ADS)

    Langner, Andreas; Achard, Frédéric; Grassi, Giacomo

    2014-05-01

    The IPCC proposes three Tier levels for greenhouse gas emission monitoring with a hierarchical order in terms of accuracy as well as data requirements/complexity. While Tier 1 provides default above-ground biomass (AGB) values per ecological zone and continent, Tier 2 and 3 are either based on country-specific remote sensing or permanent sample-plot data. Due to missing capacities most developing countries have to rely on Tier 1 default values, which show highest uncertainties. Furthermore, IPCC Tier 1 values lack transparency as they are based on a variety of studies that have been repeatedly updated and combined with expert opinions, thus blurring the original data sources. A possible way to increase credibility is a conservative monitoring approach, following the principle of conservativeness, thus reducing the likelihood of unjustified payments for emission reductions not reflecting reality. For the implementation of that principle knowledge about the distribution of the biomass within each ecological zone is essential. However, such information is not available for the IPCC Tier 1 values, which only provide mean values and/or AGB ranges that are not based on a common statistical analysis. Using the pan-tropical datasets of Saatchi et al (Proc Natl Acad Sci USA, 108, 9899-9904, 2011; 1km spatial resolution) and Baccini et al (Nat Climate Change, 2:182-185, 2012; 500m spatial resolution) we calculated the mean AGB values as well as their 50% confidence intervals for each ecological zone within the DRC using Globcover2009 as forest/non-forest mask and the FAO ecological zones dataset. Such analysis is more transparent while at the same time leading to "statistically improved" Tier 1 values, potentially allowing a conservative monitoring approach by selecting the lower bound of the confidence interval for emission estimation during the reference period and the higher bound for the assessment period. Within the DRC Baccini generally delivers higher AGB estimates

  10. Mapping continental-scale biomass burning and smoke palls over the Amazon basin as observed from the Space Shuttle

    NASA Technical Reports Server (NTRS)

    Helfert, Michael R.; Lulla, Kamlesh P.

    1990-01-01

    Space Shuttle and Skylab-3 photography has been used to map the areal extent of Amazonian smoke palls associated with biomass burning (1973-1988). Areas covered with smoke have increased from approximately 300,000 sq km in 1973 to continental-size smoke palls measuring approximately 3,000,000 sq km in 1985 and 1988. Mapping of these smoke palls has been accomplished using space photography mainly acquired during Space Shuttle missions. Astronaut observations of such dynamic and vital environmental phenomena indicate the possibility of integrating the earth observation capabilities of all space platforms in future Global Change research.

  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. 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.

  13. 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

  14. 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.

  15. Genome-wide association of drought-related and biomass traits with HapMap SNPs in Medicago truncatula.

    PubMed

    Kang, Yun; Sakiroglu, Muhammet; Krom, Nicholas; Stanton-Geddes, John; Wang, Mingyi; Lee, Yi-Ching; Young, Nevin D; Udvardi, Michael

    2015-10-01

    Improving drought tolerance of crop plants is a major goal of plant breeders. In this study, we characterized biomass and drought-related traits of 220 Medicago truncatula HapMap accessions. Characterized traits included shoot biomass, maximum leaf size, specific leaf weight, stomatal density, trichome density and shoot carbon-13 isotope discrimination (δ(13) C) of well-watered M. truncatula plants, and leaf performance in vitro under dehydration stress. Genome-wide association analyses were carried out using the general linear model (GLM), the standard mixed linear model (MLM) and compressed MLM (CMLM) in TASSEL, which revealed significant overestimation of P-values by CMLM. For each trait, candidate genes and chromosome regions containing SNP markers were found that are in significant association with the trait. For plant biomass, a 0.5 Mbp region on chromosome 2 harbouring a plasma membrane intrinsic protein, PIP2, was discovered that could potentially be targeted to increase dry matter yield. A protein disulfide isomerase-like protein was found to be tightly associated with both shoot biomass and leaf size. A glutamate-cysteine ligase and an aldehyde dehydrogenase family protein with Arabidopsis homologs strongly expressed in the guard cells were two of the top genes identified by stomata density genome-wide association studies analysis. PMID:25707512

  16. 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.

  17. 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

  18. 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

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

    NASA Astrophysics Data System (ADS)

    LE Toan, T.

    2015-12-01

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

  20. 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.

  1. Human and environmental controls over aboveground carbon storage in Madagascar

    PubMed Central

    2012-01-01

    Background Accurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar. Results We found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR. Conclusions High-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy. PMID:22289685

  2. Impacts of fire management on aboveground tree carbon stocks in Yosemite and Sequoia & Kings Canyon national parks.

    USGS Publications Warehouse

    Matchett, John R.; Lutz, Jamea A.; Tarnay, Leland W.; Smith, Douglas G.; Becker, Kendall M.L.; Brooks, Matthew L.

    2015-01-01

    methods, we found that vegetation type mapping error was the largest source of uncertainty, while measurement uncertainties contributed by tree diameter measurements and tree diameter–biomass allometry equations were relatively minor. For some forest types, we found differences in aboveground tree carbon densities between burned and unburned areas. For example, mean carbon density in burned red fir forests was estimated to be ~29% lower versus unburned areas. Alternative measures of fire history, such as time since fire and number of times burned, were poorly related to carbon densities. Within YOSE, we evaluated the stability of landscape carbon pools by quantifying carbon stocks in areas of varying degrees of departure from historic fire return intervals. Of the ~25 Tg of total aboveground tree carbon in YOSE, ~10 Tg is contained within relatively stable areas (the next fire is unlikely to be high severity and stand-replacing), ~10 Tg occurs in areas deemed moderately stable, and the remaining ~5 Tg within relatively unstable areas. We compared our landscape carbon estimates in YOSE to remotely-sensed carbon estimates from the NASA–CASA project and found that the two methods roughly agree. Our analysis and comparisons suggest, however, that fire severity should be integrated into future carbon mapping efforts. We illustrate this with an example using the 2013 Rim Fire, which we estimate burned an area containing over 5 Tg of aboveground tree carbon, but likely left a large fraction of that carbon on the landscape if one accounts for fire severity.

  3. Potential plant biomass estimation through field measurement and vegetation cover mapping using ALOS satellite imagery: Case study of Fujiyoshida City, Japan

    NASA Astrophysics Data System (ADS)

    Doko, T.; Chen, W.; Qazi, O.; Okabayashi, S.; Meguro, D.; Kanamori, T.; Jones, M.; Kawata, C.; Yagasaki, T.; Ichinose, T.; Sasaki, K.

    2014-03-01

    Biomass is a renewable energy source that is produced from living or recently living biological material. Vegetation type and biomass are considered important components that affect biosphere-atmosphere interactions. The ground assessment of biomass, however, has been found to be insufficient due to the limited spatial extent of surveys. This study aims to integrate field measurements with satellite remote sensing data for regional biomass mapping in Fujiyoshida City, Japan. Fujiyoshida City is situated on the northern slope of Mt. Fuji and includes a large area of forest land, named "Onshirin Forest". From 2011 to 2012, a field survey was conducted to calculate the biomass potential in situ as ground-truthed data. After fieldwork, ortho-rectified ALOS data with an AVNIR-2 scene (22 May 2008) was used to map the vegetation cover types. Japanese larch, Japanese red pine, mixed forest, other forest, grass, bare soil and roads, and buildings were identified using supervised classification. The total plant biomass was 163,252 tons. The biomass potential estimate from field measurements was extrapolated to the large forest area in Fujiyoshida City to estimate the potential plant biomass of specific vegetation cover types.

  4. Lidar-based biomass assessment for the Yukon River Basin

    NASA Astrophysics Data System (ADS)

    Peterson, B.; Wylie, B. K.; Stoker, J.; Nossov, D.

    2010-12-01

    lidar data set and are expected to result in improved biomass products for the YRB as they have been shown to be highly predictive of biomass in other biomes. The results of this project represent the first step in a larger effort to collect lidar and field data for various study sites across the YRB for biomass estimations to train large-scale mapping efforts using Landsat imagery and radar data. Bond-Lamberty, B., C. Wang, and S.T. Gower. 2002. Aboveground and belowground biomass and sapwood area allometric equations for six boreal tree species of northern Manitoba. Canadian Journal of Forest Research 32: 1441-1450. Mack, M., K. Treseder, K. Manies, J. Harden, E. Schuur, J. Vogel, J. Randerson, and F.S. Chapin III. 2008. Recovery of Aboveground Plant Biomass and Productivity After Fire in Mesic and Dry Black Spruce Forests of Interior Alaska, Ecosystems v.11:209-225. Yarie, J., E. Kane, and M. Mack. 2007. Aboveground Biomass Equations for the Trees of Interior Alaska. AFES Bulletin 115.

  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. 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

  7. Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

    Tropical forests provide global climate regulation ecosystem services and their clearing is a significant source of anthropogenic greenhouse gas (GHG) emissions and resultant radiative forcing of climate change. However, consensus on pan-tropical forest carbon dynamics is lacking. We present a new estimate that employs recommended good practices to quantify gross tropical forest aboveground carbon (AGC) loss from 2000 to 2012 through the integration of Landsat-derived tree canopy cover, height, intactness and forest cover loss and GLAS-lidar derived forest biomass. An unbiased estimate of forest loss area is produced using a stratified random sample with strata derived from a wall-to-wall 30 m forest cover loss map. Our sample-based results separate the gross loss of forest AGC into losses from natural forests (0.59 PgC yr-1) and losses from managed forests (0.43 PgC yr-1) including plantations, agroforestry systems and subsistence agriculture. Latin America accounts for 43% of gross AGC loss and 54% of natural forest AGC loss, with Brazil experiencing the highest AGC loss for both categories at national scales. We estimate gross tropical forest AGC loss and natural forest loss to account for 11% and 6% of global year 2012 CO2 emissions, respectively. Given recent trends, natural forests will likely constitute an increasingly smaller proportion of tropical forest GHG emissions and of global emissions as fossil fuel consumption increases, with implications for the valuation of co-benefits in tropical forest conservation.

  8. Measuring Forest Biomass and Height from Space - Results from the assessment of ESA's BIOMASS satellite concept

    NASA Astrophysics Data System (ADS)

    Scipal, Klaus

    2010-05-01

    Knowledge about forest above-ground biomass is of fundamental importance in quantifying the terrestrial carbon cycle, but is also crucial in assessing forest resources and the ecosystem services provided by forests, and is an essential element in assessing carbon fluxes under the United Nations Framework Convention on Climate Change. For most parts of the world, in particular the tropical forests, information on biomass is currently very limited, at very coarse scales, and subject to large and unquantified errors. In response to the urgent need for greatly improved mapping of global biomass and the lack of any current space systems capable of addressing this need, the BIOMASS mission was proposed to the European Space Agency for the third cycle of Earth Explorer Core missions and was selected for Feasibility Study (Phase A) in March 2009. Over the five-year mission lifetime, it shall map the full range of the world's above-ground biomass with accuracy and spatial resolution compatible with the needs of national scale inventory and carbon flux calculations, and will map changes in forest biomass. The mission will carry a polarimetric P-Band SAR, capable of providing both direct measurements of biomass derived from inverting intensity data, and measurements of forest height derived from polarimetric interferometry. The BIOMASS payload consists of a fully polarimetric system operated at a centre frequency of 435 MHz (P-band) with a bandwidth of 6 MHz. To enable measurements at a scale comparable to that of deforestation and forest disturbance (i.e. around 1 ha), it is envisaged that BIOMASS will provide level-1 products with around 50 m x 50 m resolution at 4 looks, so around 16 looks at a scale of 1 ha. The satellite shall fly in a sun-synchronous dawn-dusk orbit to minimise ionospheric disturbances with a controlled drift to meet the revisit requirement for forest height recovery using Pol-InSAR techniques. The revisit time will be between 25-45 days to maintain

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

    NASA Astrophysics Data System (ADS)

    Helmer, Eileen H.; Lefsky, Michael A.; Roberts, Dar A.

    2009-01-01

    We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975-2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age mapping with biomass estimates from the Geoscience Laser Altimeter System (GLAS). Though highly variable, the estimated average biomass accumulation rate of 8.4 Mg ha-1 yr-1 agrees well with ground-based studies for young secondary forests in the region. In isolating the lowland forests, we map land cover and general types of old-growth forests with decision tree classification of Landsat imagery and elevation data. We then estimate aboveground live biomass for seven classes of old-growth forest. TAMA is simple, fast, and self-calibrating. By not using between-date band or index differences or trends, it requires neither image normalization nor atmospheric correction. In addition, it uses an approach to map forest cover for the self-calibrations that is novel to forest mapping with satellite imagery; it maps humid secondary forest that is difficult to distinguish from old-growth forest in single-date imagery; it does not assume that forest age equals time since disturbance; and it incorporates Landsat Multispectral Scanner imagery. Variations on the work that we present here can be applied to other forested landscapes. Applications that use image time series will be helped by the free distribution of coregistered Landsat imagery, which began in December 2008, and of the Ice Cloud and land Elevation Satellite Vegetation Product, which simplifies the use of GLAS data. Finally, we demonstrate here for the first time how the optical imagery of fine spatial resolution that is viewable on Google Earth provides a new source of reference data for remote sensing applications related to land cover.

  10. Aboveground storage tanks: Understanding the rules

    SciTech Connect

    Kitchen, T.; McCallion, J.

    1995-10-01

    Facility owners and operators using aboveground tanks for storing or processing hazardous wastes or oils must follow Environmental Protection Agency (EPA) or Occupational Safety and Health Administration (OSHA) regulations, or they risk heavy fines and penalties. Every facility storing more than 1320 gallons of hazardous waste or oil aboveground or more than 660 gallons in a single tank are required to have a spill prevention control and countermeasures plan. Given in the article is a table of aboveground tank standards under various agencies or acts. The subject and location of these regulations from the EPA, OSHA, Resource Conservation and Recovery Act (RCRA), Underwriter`s Laboratory (UL), the American Petroleum Institute (API), and the American Society of Mechanical Engineers (ASME) cover various aspects of tank construction and safety. Understanding and complying with the codes and regulations can be arduous, but the rewards in safety and environmental stewardship and the potential savings in fines make the effort worthwhile.

  11. Uncertainty Determination Methodology, Sampling Maps Generation and Trend Studies with Biomass Thermogravimetric Analysis

    PubMed Central

    Pazó, Jose A.; Granada, Enrique; Saavedra, Ángeles; Eguía, Pablo; Collazo, Joaquín

    2010-01-01

    This paper investigates a method for the determination of the maximum sampling error and confidence intervals of thermal properties obtained from thermogravimetric analysis (TG analysis) for several lignocellulosic materials (ground olive stone, almond shell, pine pellets and oak pellets), completing previous work of the same authors. A comparison has been made between results of TG analysis and prompt analysis. Levels of uncertainty and errors were obtained, demonstrating that properties evaluated by TG analysis were representative of the overall fuel composition, and no correlation between prompt and TG analysis exists. Additionally, a study of trends and time correlations is indicated. These results are particularly interesting for biomass energy applications. PMID:21152292

  12. Biomass Accumulation Rates of Amazonian Secondary Forest and Biomass of Old-Growth Forests from Landsat Time Series and GLAS

    NASA Astrophysics Data System (ADS)

    Helmer, E.; Lefsky, M. A.; Roberts, D.

    2009-12-01

    We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975-2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age mapping with biomass estimates from the Geoscience Laser Altimeter System (GLAS). Though highly variable, the estimated average biomass accumulation rate of 8.4 Mg ha-1 yr-1 agrees well with ground-based studies for young secondary forests in the region. In isolating the lowland forests, we map land cover and general types of old-growth forests with decision tree classification of Landsat imagery and elevation data. We then estimate aboveground live biomass for seven classes of old-growth forest. TAMA is simple, fast, and self-calibrating. By not using between-date band or index differences or trends, it requires neither image normalization nor atmospheric correction. In addition, it uses an approach to map forest cover for the self-calibrations that is novel to forest mapping with satellite imagery; it maps humid secondary forest that is difficult to distinguish from old-growth forest in single-date imagery; it does not assume that forest age equals time since disturbance; and it incorporates Landsat Multispectral Scanner (MSS) imagery. Variations on the work that we present here can be applied to other forested landscapes. Applications that use image time series will be helped by the free distribution of coregistered Landsat imagery, which began in December 2008, and of the Ice Cloud and land Elevation Satellite (ICESat) Vegetation Product, which simplifies the use of GLAS data. Finally, we demonstrate here for the first time how the optical imagery of fine spatial resolution that is viewable on Google Earth provides a new source of reference data for remote sensing applications related to land cover

  13. Resource mapping and analysis of UK farm livestock manures: Assessing the opportunities for biomass-to-energy technologies

    SciTech Connect

    Dagnall, S.P.

    1995-11-01

    Livestock farms produce wastes with a high potential for pollution. Alternative, environmentally acceptable disposal routes might lie in biomass-to-energy schemes, generating revenue from the energy produced and fertiliser as a by-product; these are currently being developed, or assessed, for the UK under DTI/MAFF collaborative programmes; two options are being considered-direct combustion (12-14MW{sub e}) and centralised anaerobic digestion (0.1-1MW{sub e} CHP). One of the barriers to initiating such schemes is establishing where feedstocks are located in order that they may be exploited in a cost effective manner. Resource mapping and analysis using a Geographical Information System has been used to establish the opportunities for England and Wales. This work was carried out in two parts: produce spatially distributed resource data, of agro-industrial wastes and farm livestock manures, expressed in tonnes dry solids, from which energy production figures were derived; and develop algorithms to establish how much of this resource could be feasibly exploited. By comparing these resource data with other appropriate information (e.g., road networks, environmentally sensitive areas, grid interconnections), the optimum location and size of potential biomass-to-energy plants were determined. Whilst interest in such schemes is anticipated to grow further over the next few years, their future will be heavily dependent upon the level of concern for wider environmental issues.

  14. High-Resolution Mapping of Biomass Burning Emissions in Three Tropical Regions.

    PubMed

    Shi, Yusheng; Matsunaga, Tsuneo; Yamaguchi, Yasushi

    2015-09-15

    Biomass burning in tropical regions plays a significant role in atmospheric pollution and climate change. This study quantified a comprehensive monthly biomass burning emissions inventory with 1 km high spatial resolution, which included the burning of vegetation, human waste, and fuelwood for 2010 in three tropical regions. The estimations were based on the available burned area product MCD64A1 and statistical data. The total emissions of all gases and aerosols were 17382 Tg of CO2, 719 Tg of CO, 30 Tg of CH4, 29 Tg of NOx, 114 Tg of NMOC (nonmethane organic compounds), 7 Tg of SO2, 10 Tg of NH3, 79 Tg of PM2.5 (particulate matter), 45 Tg of OC (organic carbon), and 6 Tg of BC (black carbon). Taking CO as an example, vegetation burning accounted for 74% (530 Tg) of the total CO emissions, followed by fuelwood combustion and human waste burning. Africa was the biggest emitter (440 Tg), larger than Central and South America (113 Tg) and South and Southeast Asia (166 Tg). We also noticed that the dominant fire types in vegetation burning of these three regions were woody savanna/shrubland, savanna/grassland, and forest, respectively. Although there were some slight overestimations, our results are supported by comparisons with previously published data. PMID:26287650

  15. Climatic controls on aboveground net primary production of tropical lowland rainforests

    NASA Astrophysics Data System (ADS)

    Hofhansl, F.; Drage, S.; Poelz, E.; Richter, A.; Wanek, W.

    2012-12-01

    Aboveground net primary production (ANPP) of tropical forests is driven by soil fertility and climate, the latter receiving special attention as recent projections of global circulation models predict Mesoamerican tropics to become drier and warmer. Given the scarcity of manipulative experiments, interannual climate variations caused by El Nino Southern Oscillation have been used to assess the potential responses of tropical ANPP to projected climate change. The focus of this study was (1) to investigate how seasonal and interannual climate variations affect ANPP and the partitioning between litterfall and stem increment on three forest sites differing in soil fertility and disturbance regime in SW Costa Rica, and (2) to identify major drivers of tropical forest ANPP by integrating our results into a dataset provided by the National Center for Ecological Analysis and Synthesis (NCEAS). While forest productivity was reported to decline in areas with high precipitation and temperature, we measured among the highest stem increments and litterfall rates published to date at a site with >6000 mm mean annual precipitation (MAP) and a mean annual temperature (MAT) of 28 °C. Based on the full dataset MAP was inversely correlated with litterfall, while MAT and soil fertility promoted stem increment. Therefore the percentage of litterfall and stem increment to ANPP shifted from 80:20 in low productive tropical forests to 40:60 at forest sites with high biomass production. Our results suggest that there is a shift in the allocation of biomass towards greater nutrient conservation (i.e. production of wood biomass) in more productive tropical forests while litterfall is sustaining nutrient recycling processes in less productive forests and that this relationship is driven by climate. We finally demonstrate that both ANPP components are sensitive to seasonal and interannual climate variation at the three forest sites studied, but that the controls differ for litterfall and stem

  16. 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.

  17. Interrelated effects of mycorrhiza and free-living nitrogen fixers cascade up to aboveground herbivores

    PubMed Central

    Khaitov, Botir; Patiño-Ruiz, José David; Pina, Tatiana; Schausberger, Peter

    2015-01-01

    Aboveground plant performance is strongly influenced by belowground microorganisms, some of which are pathogenic and have negative effects, while others, such as nitrogen-fixing bacteria and arbuscular mycorrhizal fungi, usually have positive effects. Recent research revealed that belowground interactions between plants and functionally distinct groups of microorganisms cascade up to aboveground plant associates such as herbivores and their natural enemies. However, while functionally distinct belowground microorganisms commonly co-occur in the rhizosphere, their combined effects, and relative contributions, respectively, on performance of aboveground plant-associated organisms are virtually unexplored. Here, we scrutinized and disentangled the effects of free-living nitrogen-fixing (diazotrophic) bacteria Azotobacter chroococcum (DB) and arbuscular mycorrhizal fungi Glomus mosseae (AMF) on host plant choice and reproduction of the herbivorous two-spotted spider mite Tetranychus urticae on common bean plants Phaseolus vulgaris. Additionally, we assessed plant growth, and AMF and DB occurrence and density as affected by each other. Both AMF alone and DB alone increased spider mite reproduction to similar levels, as compared to the control, and exerted additive effects under co-occurrence. These effects were similarly apparent in host plant choice, that is, the mites preferred leaves from plants with both AMF and DB to plants with AMF or DB to plants grown without AMF and DB. DB, which also act as AMF helper bacteria, enhanced root colonization by AMF, whereas AMF did not affect DB abundance. AMF but not DB increased growth of reproductive plant tissue and seed production, respectively. Both AMF and DB increased the biomass of vegetative aboveground plant tissue. Our study breaks new ground in multitrophic belowground–aboveground research by providing first insights into the fitness implications of plant-mediated interactions between interrelated belowground fungi

  18. Plant genetic variation mediates an indirect ecological effect between belowground earthworms and aboveground aphids

    PubMed Central

    2014-01-01

    Background Interactions between aboveground and belowground terrestrial communities are often mediated by plants, with soil organisms interacting via the roots and aboveground organisms via the shoots and leaves. Many studies now show that plant genetics can drive changes in the structure of both above and belowground communities; however, the role of plant genetic variation in mediating aboveground-belowground interactions is still unclear. We used an earthworm-plant-aphid model system with two aphid species (Aphis fabae and Acyrthosiphon pisum) to test the effect of host-plant (Vicia faba) genetic variation on the indirect interaction between the belowground earthworms (Eisenia veneta) on the aboveground aphid populations. Results Our data shows that host-plant variety mediated an indirect ecological effect of earthworms on generalist black bean aphids (A. fabae), with earthworms increasing aphid growth rate in three plant varieties but decreasing it in another variety. We found no effect of earthworms on the second aphid species, the pea aphid (A. pisum), and no effect of competition between the aphid species. Plant biomass was increased when earthworms were present, and decreased when A. pisum was feeding on the plant (mediated by plant variety). Although A. fabae aphids were influenced by the plants and worms, they did not, in turn, alter plant biomass. Conclusions Previous work has shown inconsistent effects of earthworms on aphids, but we suggest these differences could be explained by plant genetic variation and variation among aphid species. This study demonstrates that the outcome of belowground-aboveground interactions can be mediated by genetic variation in the host-plant, but depends on the identity of the species involved. PMID:25331082

  19. 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...

  20. Mapping vegetation cover and biomass on the Qinghai-Tibet-Plateau using hyperspectral measurements and multispectral satellite images

    NASA Astrophysics Data System (ADS)

    Meyer, Hanna; Lehnert, Lukas W.; Wang, Yun; Reudenbach, Christoph; Nauss, Thomas; Bendix, Jörg

    2016-04-01

    Pastoralism is the dominant land-use on the Qinghai-Tibet-Plateau (QTP) providing the major economic resource for the local population. However, the pastures are highly supposed to be affected by ongoing degradation whose extent is still disputed. This study uses hyperspectral in situ measurements and multispectral satellite images to assess vegetation cover and above ground biomass (AGB) as proxies of pasture degradation on a regional scale. Using Random Forests in conjunction with recursive feature selection as modeling tool, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate vegetation cover and AGB. To regionalize pasture degradation proxies, the transferability of the locally derived models to high resolution multispectral satellite data is assessed. For this purpose, 1183 hyperspectral measurements and vegetation records were sampled at 18 locations on the QTP. AGB was determined on 25 0.5x0.5m plots. Proxies for pasture degradation were derived from the spectra by calculating narrow-band indices (NBI). Using the NBI as predictor variables vegetation cover and AGB were modeled. Models were calculated using the hyperspectral data as well as the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used. In contrast, errors in AGB estimations were considerably higher. Only small differences in accuracy were observed between the models based on hyper- compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite data, the results still show a

  1. 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.

  2. Amazonian landscapes and the bias in field studies of forest structure and biomass

    PubMed Central

    Marvin, David C.; Asner, Gregory P.; Knapp, David E.; Anderson, Christopher B.; Martin, Roberta E.; Sinca, Felipe; Tupayachi, Raul

    2014-01-01

    Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9–98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy. PMID:25422434

  3. Amazonian landscapes and the bias in field studies of forest structure and biomass.

    PubMed

    Marvin, David C; Asner, Gregory P; Knapp, David E; Anderson, Christopher B; Martin, Roberta E; Sinca, Felipe; Tupayachi, Raul

    2014-12-01

    Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9-98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy. PMID:25422434

  4. Deer browsing delays succession by altering aboveground vegetation and belowground seed banks.

    PubMed

    DiTommaso, Antonio; Morris, Scott H; Parker, John D; Cone, Caitlin L; Agrawal, Anurag A

    2014-01-01

    Soil seed bank composition is important to the recovery of natural and semi-natural areas from disturbance and serves as a safeguard against environmental catastrophe. White-tailed deer (Odocoileus virginianus) populations have increased dramatically in eastern North America over the past century and can have strong impacts on aboveground vegetation, but their impacts on seed bank dynamics are less known. To document the long-term effects of deer browsing on plant successional dynamics, we studied the impacts of deer on both aboveground vegetation and seed bank composition in plant communities following agricultural abandonment. In 2005, we established six 15 × 15 m fenced enclosures and paired open plots in recently followed agricultural fields near Ithaca, NY, USA. In late October of each of six years (2005-2010), we collected soil from each plot and conducted seed germination cycles in a greenhouse to document seed bank composition. These data were compared to measurements of aboveground plant cover (2005-2008) and tree density (2005-2012). The impacts of deer browsing on aboveground vegetation were severe and immediate, resulting in significantly more bare soil, reduced plant biomass, reduced recruitment of woody species, and relatively fewer native species. These impacts persisted throughout the experiment. The impacts of browsing were even stronger on seed bank dynamics. Browsing resulted in significantly decreased overall species richness (but higher diversity), reduced seed bank abundance, relatively more short-lived species (annuals and biennials), and fewer native species. Both seed bank richness and the relative abundance of annuals/biennials were mirrored in the aboveground vegetation. Thus, deer browsing has long-term and potentially reinforcing impacts on secondary succession, slowing succession by selectively consuming native perennials and woody species and favoring the persistence of short-lived, introduced species that continually recruit from an

  5. Deer Browsing Delays Succession by Altering Aboveground Vegetation and Belowground Seed Banks

    PubMed Central

    DiTommaso, Antonio; Morris, Scott H.; Parker, John D.; Cone, Caitlin L.; Agrawal, Anurag A.

    2014-01-01

    Soil seed bank composition is important to the recovery of natural and semi-natural areas from disturbance and serves as a safeguard against environmental catastrophe. White-tailed deer (Odocoileus virginianus) populations have increased dramatically in eastern North America over the past century and can have strong impacts on aboveground vegetation, but their impacts on seed bank dynamics are less known. To document the long-term effects of deer browsing on plant successional dynamics, we studied the impacts of deer on both aboveground vegetation and seed bank composition in plant communities following agricultural abandonment. In 2005, we established six 15×15 m fenced enclosures and paired open plots in recently fallowed agricultural fields near Ithaca, NY, USA. In late October of each of six years (2005–2010), we collected soil from each plot and conducted seed germination cycles in a greenhouse to document seed bank composition. These data were compared to measurements of aboveground plant cover (2005–2008) and tree density (2005–2012). The impacts of deer browsing on aboveground vegetation were severe and immediate, resulting in significantly more bare soil, reduced plant biomass, reduced recruitment of woody species, and relatively fewer native species. These impacts persisted throughout the experiment. The impacts of browsing were even stronger on seed bank dynamics. Browsing resulted in significantly decreased overall species richness (but higher diversity), reduced seed bank abundance, relatively more short-lived species (annuals and biennials), and fewer native species. Both seed bank richness and the relative abundance of annuals/biennials were mirrored in the aboveground vegetation. Thus, deer browsing has long-term and potentially reinforcing impacts on secondary succession, slowing succession by selectively consuming native perennials and woody species and favoring the persistence of short-lived, introduced species that continually recruit

  6. Impact of precipitation patterns on biomass and species richness of annuals in a dry steppe.

    PubMed

    Yan, Hong; Liang, Cunzhu; Li, Zhiyong; Liu, Zhongling; Miao, Bailing; He, Chunguang; Sheng, Lianxi

    2015-01-01

    Annuals are an important component part of plant communities in arid and semiarid grassland ecosystems. Although it is well known that precipitation has a significant impact on productivity and species richness of community or perennials, nevertheless, due to lack of measurements, especially long-term experiment data, there is little information on how quantity and patterns of precipitation affect similar attributes of annuals. This study addresses this knowledge gap by analyzing how quantity and temporal patterns of precipitation affect aboveground biomass, interannual variation aboveground biomass, relative aboveground biomass, and species richness of annuals using a 29-year dataset from a dry steppe site at the Inner Mongolia Grassland Ecosystem Research Station. Results showed that aboveground biomass and relative aboveground biomass of annuals increased with increasing precipitation. The coefficient of variation in aboveground biomass of annuals decreased significantly with increasing annual and growing-season precipitation. Species richness of annuals increased significantly with increasing annual precipitation and growing-season precipitation. Overall, this study highlights the importance of precipitation for aboveground biomass and species richness of annuals. PMID:25906187

  7. Impact of Precipitation Patterns on Biomass and Species Richness of Annuals in a Dry Steppe

    PubMed Central

    Yan, Hong; Liang, Cunzhu; Li, Zhiyong; Liu, Zhongling; Miao, Bailing; He, Chunguang; Sheng, Lianxi

    2015-01-01

    Annuals are an important component part of plant communities in arid and semiarid grassland ecosystems. Although it is well known that precipitation has a significant impact on productivity and species richness of community or perennials, nevertheless, due to lack of measurements, especially long-term experiment data, there is little information on how quantity and patterns of precipitation affect similar attributes of annuals. This study addresses this knowledge gap by analyzing how quantity and temporal patterns of precipitation affect aboveground biomass, interannual variation aboveground biomass, relative aboveground biomass, and species richness of annuals using a 29-year dataset from a dry steppe site at the Inner Mongolia Grassland Ecosystem Research Station. Results showed that aboveground biomass and relative aboveground biomass of annuals increased with increasing precipitation. The coefficient of variation in aboveground biomass of annuals decreased significantly with increasing annual and growing-season precipitation. Species richness of annuals increased significantly with increasing annual precipitation and growing-season precipitation. Overall, this study highlights the importance of precipitation for aboveground biomass and species richness of annuals. PMID:25906187

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  9. Aboveground vertebrate and invertebrate herbivore impact on net N mineralization in subalpine grasslands.

    PubMed

    Risch, Anita C; Schotz, Martin; Vandegehuchte, Martijn L; Van Der Putten, Wim H; Duyts, Henk; Raschein, Ursina; Gwiazdowicz, Dariusz J; Busse, Matt D; Page-dumroese, Deborah S; Zimmermann, Stephan

    2015-12-01

    Aboveground herbivores have strong effects on grassland nitrogen (N) cycling. They can accelerate or slow down soil net N mineralization depending on ecosystem productivity and grazing intensity. Yet, most studies only consider either ungulates or invertebrate herbivores, but not the combined effect of several functionally different vertebrate and invertebrate herbivore species or guilds. We assessed how a diverse herbivore community affects net N mineralization in subalpine grasslands. By using size-selective fences, we progressively excluded large, medium, and small mammals, as well as invertebrates from two vegetation types, and assessed how the exclosure types (ET) affected net N mineralization. The two vegetation types differed in long-term management (centuries), forage quality, and grazing history and intensity. To gain a more mechanistic understanding of how herbivores affect net N mineralization, we linked mineralization to soil abiotic (temperature; moisture; NO3-, NH4+, and total inorganic N concentrations/pools; C, N, P concentrations; pH; bulk density), soil biotic (microbial biomass; abundance of collembolans, mites, and nematodes) and plant (shoot and root biomass; consumption; plant C, N, and fiber content; plant N pool) properties. Net N mineralization differed between ET, but not between vegetation types. Thus, short-term changes in herbivore community composition and, therefore, in grazing intensity had a stronger effect on net N mineralization than long-term management and grazing history. We found highest N mineralization values when only invertebrates were present, suggesting that mammals had a negative effect on net N mineralization. Of the variables included in our analyses, only mite abundance and aboveground plant biomass explained variation in net N mineralization among ET. Abundances of both mites and leaf-sucking invertebrates were positively correlated with aboveground plant biomass, and biomass increased with progressive exclusion

  10. The Circumpolar Arctic vegetation map

    USGS Publications Warehouse

    Walker, Donald A.; Raynolds, Martha K.; Daniels, F.J.A.; Einarsson, E.; Elvebakk, A.; Gould, W.A.; Katenin, A.E.; Kholod, S.S.; Markon, C.J.; Melnikov, E.S.; Moskalenko, N.G.; Talbot, S. S.; Yurtsev, B.A.; Bliss, L.C.; Edlund, S.A.; Zoltai, S.C.; Wilhelm, M.; Bay, C.; Gudjonsson, G.; Ananjeva, G.V.; Drozdov, D.S.; Konchenko, L.A.; Korostelev, Y.V.; Ponomareva, O.E.; Matveyeva, N.V.; Safranova, I.N.; Shelkunova, R.; Polezhaev, A.N.; Johansen, B.E.; Maier, H.A.; Murray, D.F.; Fleming, Michael D.; Trahan, N.G.; Charron, T.M.; Lauritzen, S.M.; Vairin, B.A.

    2005-01-01

    Question: What are the major vegetation units in the Arctic, what is their composition, and how are they distributed among major bioclimate subzones and countries? Location: The Arctic tundra region, north of the tree line. Methods: A photo-interpretive approach was used to delineate the vegetation onto an Advanced Very High Resolution Radiometer (AVHRR) base image. Mapping experts within nine Arctic regions prepared draft maps using geographic information technology (ArcInfo) of their portion of the Arctic, and these were later synthesized to make the final map. Area analysis of the map was done according to bioclimate subzones, and country. The integrated mapping procedures resulted in other maps of vegetation, topography, soils, landscapes, lake cover, substrate pH, and above-ground biomass. Results: The final map was published at 1:7 500 000 scale map. Within the Arctic (total area = 7.11 x 106 km 2), about 5.05 ?? 106 km2 is vegetated. The remainder is ice covered. The map legend generally portrays the zonal vegetation within each map polygon. About 26% of the vegetated area is erect shrublands, 18% peaty graminoid tundras, 13% mountain complexes, 12% barrens, 11% mineral graminoid tundras, 11% prostrate-shrub tundras, and 7% wetlands. Canada has by far the most terrain in the High Arctic mostly associated with abundant barren types and prostrate dwarf-shrub tundra, whereas Russia has the largest area in the Low Arctic, predominantly low-shrub tundra. Conclusions: The CAVM is the first vegetation map of an entire global biome at a comparable resolution. The consistent treatment of the vegetation across the circumpolar Arctic, abundant ancillary material, and digital database should promote the application to numerous land-use, and climate-change applications and will make updating the map relatively easy. ?? IAVS; Opulus Press.

  11. Improvement of Rice Biomass Yield through QTL-Based Selection

    PubMed Central

    Matsubara, Kazuki; Yamamoto, Eiji; Kobayashi, Nobuya; Ishii, Takuro; Tanaka, Junichi; Tsunematsu, Hiroshi; Yoshinaga, Satoshi; Matsumura, Osamu; Yonemaru, Jun-ichi; Mizobuchi, Ritsuko; Yamamoto, Toshio; Kato, Hiroshi; Yano, Masahiro

    2016-01-01

    Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related traits in recombinant inbred lines. Phenotypic values for these traits showed a continuous distribution with transgressive segregation, suggesting that selection can affect plant weight in the progeny. Four significant QTLs were mapped for plant weight, three for grain weight, and five for stem and leaf weight (at α = 0.05); some of them overlapped. Multiple regression analysis showed that about 43% of the phenotypic variance of plant weight was significantly explained (P < 0.0001) by six of the QTLs. From F2 plants derived from the same parental cross as the recombinant inbred lines, we divergently selected lines that carried alleles with positive or negative additive effects at these QTLs, and performed successive selfing. In the resulting F6 lines and parents, plant weight significantly differed among the genotypes (at α = 0.05). These results demonstrate that QTL-based selection is effective in improving rice biomass yield. PMID:26986071

  12. Aboveground Tree Growth Varies with Belowground Carbon Allocation in a Tropical Rainforest Environment

    PubMed Central

    Raich, James W.; Clark, Deborah A.; Schwendenmann, Luitgard; Wood, Tana E.

    2014-01-01

    Young secondary forests and plantations in the moist tropics often have rapid rates of biomass accumulation and thus sequester large amounts of carbon. Here, we compare results from mature forest and nearby 15–20 year old tree plantations in lowland Costa Rica to evaluate differences in allocation of carbon to aboveground production and root systems. We found that the tree plantations, which had fully developed, closed canopies, allocated more carbon belowground - to their root systems - than did mature forest. This increase in belowground carbon allocation correlated significantly with aboveground tree growth but not with canopy production (i.e., leaf fall or fine litter production). In contrast, there were no correlations between canopy production and either tree growth or belowground carbon allocation. Enhanced allocation of carbon to root systems can enhance plant nutrient uptake, providing nutrients beyond those required for the production of short-lived tissues such as leaves and fine roots, and thus enabling biomass accumulation. Our analyses support this deduction at our site, showing that enhanced allocation of carbon to root systems can be an important mechanism promoting biomass accumulation during forest growth in the moist tropics. Identifying factors that control when, where and for how long this occurs would help us to improve models of forest growth and nutrient cycling, and to ascertain the role that young forests play in mitigating increased atmospheric carbon dioxide. PMID:24945351

  13. Moving toward a Biomass Map of Boreal Eurasia based on ICESat GLAS, ASTER GDEM, and field measurements: Amount, Spatial distribution, and Statistical Uncertainties

    NASA Astrophysics Data System (ADS)

    Neigh, C. S.; Nelson, R. F.; Sun, G.; Ranson, J.; Montesano, P. M.; Margolis, H. A.

    2011-12-01

    The Eurasian boreal forest is the largest continuous forest in the world and contains a vast quantity of carbon stock that is currently vulnerable to loss from climate change. We develop and present an approach to map the spatial distribution of above ground biomass throughout this region. Our method combines satellite measurements from the Geoscience Laser Altimeter System (GLAS) that is carried on the Ice, Cloud and land Elevation Satellite ( ICESat), with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM), and biomass field measurements collected from surveys from a number of different biomes throughout Boreal Eurasia. A slope model derived from the GDEM with quality control flags, and Moderate-resolution Imaging Spectroradiometer (MODIS) water mask was implemented to exclude poor quality GLAS shots and stratify measurements by MODIS International Geosphere Biosphere (IGBP) and World Wildlife Fund (WWF) ecozones. We derive equations from regional field measurements to estimate the spatial distribution of above ground biomass by land cover type within biome and present a map with uncertainties and limitations of this approach which can be used as a baseline for future studies.

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

    SciTech Connect

    Kasischke, E.S.; Bourgeau-Chavez, L.L.; Christensen, N.L. Jr.

    1995-05-01

    A multifrequency, multipolarization airborne SAR data set was utilized to examine the relationship between radar backscatter and the aboveground biomass in loblolly pine forests. This data set was also used to examine the potential of SAR to estimate aboveground biomass in these forests. The total aboveground biomass in the test stands used in this study ranged from <1--50 kg m{sup {minus}2}. Not only was total aboveground biomass considered, but the biomass of the tree boles, branches, and needles/leaves. Significant correlations were found in all three frequencies of radar imagery used in this study. At P- and L-bands, the greatest sensitivity to change in biomass occurred in the HH and VH polarized channels, while at C-band, the greatest sensitivity was in the VH polarized channel. The results of the correlation analyses support modeling studies which show the dominant scattering mechanisms from these pines should be double-bounce, ground-trunk scattering and canopy volume scattering. To produce equations to estimate biomass, a stepwise, multiple-linear regression approach was used, using all the radar channels as independent variables, and the log of the biomass components as the dependent variables. The authors conclude from this analysis that the image intensity signatures recorded on SAR imagery have the potential to be used as a basis for estimation of aboveground biomass in pine forests, for total stand biomass levels up to 35--40 kg m{sup {minus}2}.

  15. Corn Stover to Sustain Organic Carbon Further Constrains Biomass Supply

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sustainable aboveground crop biomass harvest estimates for cellulosic ethanol production, to date, have been limited by the need for stover or residue to control erosion. Recently, estimates of the amount of crop biomass needed to maintain soil carbon, which is responsible for favorable soil propert...

  16. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... (incorporated by reference, see § 195.3). (d) For aboveground atmospheric pressure breakout tanks constructed of... 49 Transportation 3 2014-10-01 2014-10-01 false Pressure testing aboveground breakout tanks. 195... SAFETY TRANSPORTATION OF HAZARDOUS LIQUIDS BY PIPELINE Pressure Testing § 195.307 Pressure...

  17. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... (incorporated by reference, see § 195.3). (d) For aboveground atmospheric pressure breakout tanks constructed of... 49 Transportation 3 2011-10-01 2011-10-01 false Pressure testing aboveground breakout tanks. 195... SAFETY TRANSPORTATION OF HAZARDOUS LIQUIDS BY PIPELINE Pressure Testing § 195.307 Pressure...

  18. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... (incorporated by reference, see § 195.3). (d) For aboveground atmospheric pressure breakout tanks constructed of... 49 Transportation 3 2010-10-01 2010-10-01 false Pressure testing aboveground breakout tanks. 195... SAFETY TRANSPORTATION OF HAZARDOUS LIQUIDS BY PIPELINE Pressure Testing § 195.307 Pressure...

  19. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... (incorporated by reference, see § 195.3). (d) For aboveground atmospheric pressure breakout tanks constructed of... 49 Transportation 3 2012-10-01 2012-10-01 false Pressure testing aboveground breakout tanks. 195... SAFETY TRANSPORTATION OF HAZARDOUS LIQUIDS BY PIPELINE Pressure Testing § 195.307 Pressure...

  20. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... (incorporated by reference, see § 195.3). (d) For aboveground atmospheric pressure breakout tanks constructed of... 49 Transportation 3 2013-10-01 2013-10-01 false Pressure testing aboveground breakout tanks. 195... SAFETY TRANSPORTATION OF HAZARDOUS LIQUIDS BY PIPELINE Pressure Testing § 195.307 Pressure...

  1. Modelling above-ground carbon dynamics using multi-temporal airborne lidar: insights from a Mediterranean woodland

    NASA Astrophysics Data System (ADS)

    Simonson, W.; Ruiz-Benito, P.; Valladares, F.; Coomes, D.

    2016-02-01

    Woodlands represent highly significant carbon sinks globally, though could lose this function under future climatic change. Effective large-scale monitoring of these woodlands has a critical role to play in mitigating for, and adapting to, climate change. Mediterranean woodlands have low carbon densities, but represent important global carbon stocks due to their extensiveness and are particularly vulnerable because the region is predicted to become much hotter and drier over the coming century. Airborne lidar is already recognized as an excellent approach for high-fidelity carbon mapping, but few studies have used multi-temporal lidar surveys to measure carbon fluxes in forests and none have worked with Mediterranean woodlands. We use a multi-temporal (5-year interval) airborne lidar data set for a region of central Spain to estimate above-ground biomass (AGB) and carbon dynamics in typical mixed broadleaved and/or coniferous Mediterranean woodlands. Field calibration of the lidar data enabled the generation of grid-based maps of AGB for 2006 and 2011, and the resulting AGB change was estimated. There was a close agreement between the lidar-based AGB growth estimate (1.22 Mg ha-1 yr-1) and those derived from two independent sources: the Spanish National Forest Inventory, and a tree-ring based analysis (1.19 and 1.13 Mg ha-1 yr-1, respectively). We parameterised a simple simulator of forest dynamics using the lidar carbon flux measurements, and used it to explore four scenarios of fire occurrence. Under undisturbed conditions (no fire) an accelerating accumulation of biomass and carbon is evident over the next 100 years with an average carbon sequestration rate of 1.95 Mg C ha-1 yr-1. This rate reduces by almost a third when fire probability is increased to 0.01 (fire return rate of 100 years), as has been predicted under climate change. Our work shows the power of multi-temporal lidar surveying to map woodland carbon fluxes and provide parameters for carbon

  2. Modelling above-ground carbon dynamics using multi-temporal airborne lidar: insights from a Mediterranean woodland

    NASA Astrophysics Data System (ADS)

    Simonson, W.; Ruiz-Benito, P.; Valladares, F.; Coomes, D.

    2015-09-01

    Woodlands represent highly significant carbon sinks globally, though could lose this function under future climatic change. Effective large-scale monitoring of these woodlands has a critical role to play in mitigating for, and adapting to, climate change. Mediterranean woodlands have low carbon densities, but represent important global carbon stocks due to their extensiveness and are particularly vulnerable because the region is predicted to become much hotter and drier over the coming century. Airborne lidar is already recognized as an excellent approach for high-fidelity carbon mapping, but few studies have used multi-temporal lidar surveys to measure carbon fluxes in forests and none have worked with Mediterranean woodlands. We use a multi-temporal (five year interval) airborne lidar dataset for a region of central Spain to estimate above-ground biomass (AGB) and carbon dynamics in typical mixed broadleaved/coniferous Mediterranean woodlands. Field calibration of the lidar data enabled the generation of grid-based maps of AGB for 2006 and 2011, and the resulting AGB change were estimated. There was a close agreement between the lidar-based AGB growth estimate (1.22 Mg ha-1 year-1) and those derived from two independent sources: the Spanish National Forest Inventory, and a~tree-ring based analysis (1.19 and 1.13 Mg ha-1 year-1, respectively). We parameterised a simple simulator of forest dynamics using the lidar carbon flux measurements, and used it to explore four scenarios of fire occurrence. Under undisturbed conditions (no fire occurrence) an accelerating accumulation of biomass and carbon is evident over the next 100 years with an average carbon sequestration rate of 1.95 Mg C ha-1 year-1. This rate reduces by almost a third when fire probability is increased to 0.01, as has been predicted under climate change. Our work shows the power of multi-temporal lidar surveying to map woodland carbon fluxes and provide parameters for carbon dynamics models. Space

  3. 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

  4. Fine quantitative trait loci mapping of carbon and nitrogen metabolism enzyme activities and seedling biomass in the intermated maize IBM mapping population

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Understanding the genetic basis of nitrogen and carbon metabolism will accelerate development of plant varieties with high yield and improved nitrogen use efficiency. In this study, we measured the activities of ten enzymes from carbon and nitrogen metabolism and seedling/juvenile biomass in the mai...

  5. Plant Diversity Impacts Decomposition and Herbivory via Changes in Aboveground Arthropods

    PubMed Central

    Ebeling, Anne; Meyer, Sebastian T.; Abbas, Maike; Eisenhauer, Nico; Hillebrand, Helmut; Lange, Markus; Scherber, Christoph; Vogel, Anja; Weigelt, Alexandra; Weisser, Wolfgang W.

    2014-01-01

    Loss of plant diversity influences essential ecosystem processes as aboveground productivity, and can have cascading effects on the arthropod communities in adjacent trophic levels. However, few studies have examined how those changes in arthropod communities can have additional impacts on ecosystem processes caused by them (e.g. pollination, bioturbation, predation, decomposition, herbivory). Therefore, including arthropod effects in predictions of the impact of plant diversity loss on such ecosystem processes is an important but little studied piece of information. In a grassland biodiversity experiment, we addressed this gap by assessing aboveground decomposer and herbivore communities and linking their abundance and diversity to rates of decomposition and herbivory. Path analyses showed that increasing plant diversity led to higher abundance and diversity of decomposing arthropods through higher plant biomass. Higher species richness of decomposers, in turn, enhanced decomposition. Similarly, species-rich plant communities hosted a higher abundance and diversity of herbivores through elevated plant biomass and C:N ratio, leading to higher herbivory rates. Integrating trophic interactions into the study of biodiversity effects is required to understand the multiple pathways by which biodiversity affects ecosystem functioning. PMID:25226237

  6. Improving Aboveground Carbon Estimates in Dryland Ecosystems with Airborne LiDAR and Satellite Laser Altimetry

    NASA Astrophysics Data System (ADS)

    Glenn, N. F.; Shrestha, R.; Li, A.; Spaete, L.

    2014-12-01

    Numerous studies have demonstrated the utility of ground and airborne LiDAR data to quantify ecosystem structure. In addition, data from satellite-based laser altimetry (e.g. ICESat's GLAS instrument) have been used to estimate vegetation heights, aboveground carbon, and topography in forested areas. With the upcoming ICESAT-2 satellite scheduled to launch in 2017, we have the potential to map vegetation characteristics and dynamics in other ecosystems, including semiarid and low-height ecosystems, at global and regional scales. The ICESat-2 satellite will include the Advanced Topographic Laser Altimeter System (ATLAS) with a configuration of 6 laser beams with 532 nm wavelength and photon counting detectors. We will demonstrate the potential of ICESat-2 to provide estimates of vegetation structure and topography in a dryland ecosystem by simulating the configuration of the ATLAS mission. We will also examine how airborne LiDAR can be used together with ICESat-2 and other satellite data to achieve estimates of aboveground carbon. We will explore how these data may be used for future monitoring and quantification of spatial and temporal changes in aboveground carbon and topography.

  7. Global Forest Canopy Height Maps Validation and Calibration for The Potential of Forest Biomass Estimation in The Southern United States

    NASA Astrophysics Data System (ADS)

    Ku, N. W.; Popescu, S. C.

    2015-12-01

    In the past few years, three global forest canopy height maps have been released. Lefsky (2010) first utilized the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate a global forest canopy height map in 2010. Simard et al. (2011) integrated GLAS data and other ancillary variables, such as MODIS, Shuttle Radar Topography Mission (STRM), and climatic data, to generate another global forest canopy height map in 2011. Los et al. (2012) also used GLAS data to create a vegetation height map in 2012.Several studies attempted to compare these global height maps to other sources of data., Bolton et al. (2013) concluded that Simard's forest canopy height map has strong agreement with airborne lidar derived heights. Los map is a coarse spatial resolution vegetation height map with a 0.5 decimal degrees horizontal resolution, around 50 km in the US, which is not feasible for the purpose of our research. Thus, Simard's global forest canopy height map is the primary map for this research study. The main objectives of this research were to validate and calibrate Simard's map with airborne lidar data and other ancillary variables in the southern United States. The airborne lidar data was collected between 2010 and 2012 from: (1) NASA LiDAR, Hyperspectral & Thermal Image (G-LiHT) program; (2) National Ecological Observatory Network's (NEON) prototype data sharing program; (3) NSF Open Topography Facility; and (4) the Department of Ecosystem Science and Management at Texas A&M University. The airborne lidar study areas also cover a wide variety of vegetation types across the southern US. The airborne lidar data is post-processed to generate lidar-derived metrics and assigned to four different classes of point cloud data. The four classes of point cloud data are the data with ground points, above 1 m, above 3 m, and above 5 m. The root mean square error (RMSE) and

  8. Root herbivore effects on aboveground multitrophic interactions: patterns, processes and mechanisms.

    PubMed

    Soler, Roxina; Van der Putten, Wim H; Harvey, Jeffrey A; Vet, Louise E M; Dicke, Marcel; Bezemer, T Martijn

    2012-06-01

    In terrestrial food webs, the study of multitrophic interactions traditionally has focused on organisms that share a common domain, mainly above ground. In the last two decades, it has become clear that to further understand multitrophic interactions, the barrier between the belowground and aboveground domains has to be crossed. Belowground organisms that are intimately associated with the roots of terrestrial plants can influence the levels of primary and secondary chemistry and biomass of aboveground plant parts. These changes, in turn, influence the growth, development, and survival of aboveground insect herbivores. The discovery that soil organisms, which are usually out of sight and out of mind, can affect plant-herbivore interactions aboveground raised the question if and how higher trophic level organisms, such as carnivores, could be influenced. At present, the study of above-belowground interactions is evolving from interactions between organisms directly associated with the plant roots and shoots (e.g., root feeders - plant - foliar herbivores) to interactions involving members of higher trophic levels (e.g., parasitoids), as well as non-herbivorous organisms (e.g., decomposers, symbiotic plant mutualists, and pollinators). This multitrophic approach linking above- and belowground food webs aims at addressing interactions between plants, herbivores, and carnivores in a more realistic community setting. The ultimate goal is to understand the ecology and evolution of species in communities and, ultimately how community interactions contribute to the functioning of terrestrial ecosystems. Here, we summarize studies on the effects of root feeders on aboveground insect herbivores and parasitoids and discuss if there are common trends. We discuss the mechanisms that have been reported to mediate these effects, from changes in concentrations of plant nutritional quality and secondary chemistry to defense signaling. Finally, we discuss how the traditional

  9. OBLIQUE VIEW WITH ABOVEGROUND PORTION IN THE FOREGROUND. VIEW FACING ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    OBLIQUE VIEW WITH ABOVE-GROUND PORTION IN THE FOREGROUND. VIEW FACING SOUTHWEST - U.S. Naval Base, Pearl Harbor, Ford Island 5-Inch Antiaircraft Battery, Battery Command Center, Ford Island, Pearl City, Honolulu County, HI

  10. NORTH ELEVATION WITH GRADUATED MEASURING POLE. ABOVEGROUND PORTION IS ON ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    NORTH ELEVATION WITH GRADUATED MEASURING POLE. ABOVE-GROUND PORTION IS ON THE LEFT. VIEW FACING SOUTH - U.S. Naval Base, Pearl Harbor, Ford Island 5-Inch Antiaircraft Battery, Battery Command Center, Ford Island, Pearl City, Honolulu County, HI

  11. PROVEN ALTERNATIVES FOR ABOVEGROUND TREATMENT OF ARSENIC IN GROUNDWATER

    EPA Science Inventory

    This report was prepared as an issue paper for the EPA Engineering Forum, summarizes experiences with proven aboveground treatment alternatives for arsenic in groundwater, and provides information on their relative performance and cost. The four technologies reviewed are: preci...

  12. Mapping.

    ERIC Educational Resources Information Center

    Kinney, Douglas M.; McIntosh, Willard L.

    1979-01-01

    The area of geological mapping in the United States in 1978 increased greatly over that reported in 1977; state geological maps were added for California, Idaho, Nevada, and Alaska last year. (Author/BB)

  13. Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

    NASA Technical Reports Server (NTRS)

    Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

    2010-01-01

    Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P < 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P < 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

  14. Dryland Wheat Domestication Changed the Development of Aboveground Architecture for a Well-Structured Canopy

    PubMed Central

    Li, Pu-Fang; Cheng, Zheng-Guo; Ma, Bao-Luo; Palta, Jairo A.; Kong, Hai-Yan; Mo, Fei; Wang, Jian-Yong; Zhu, Ying; Lv, Guang-Chao; Batool, Asfa; Bai, Xue; Li, Feng-Min; Xiong, You-Cai

    2014-01-01

    We examined three different-ploidy wheat species to elucidate the development of aboveground architecture and its domesticated mechanism under environment-controlled field conditions. Architecture parameters including leaf, stem, spike and canopy morphology were measured together with biomass allocation, leaf net photosynthetic rate and instantaneous water use efficiency (WUEi). Canopy biomass density was decreased from diploid to tetraploid wheat, but increased to maximum in hexaploid wheat. Population yield in hexaploid wheat was higher than in diploid wheat, but the population fitness and individual competition ability was higher in diploid wheats. Plant architecture was modified from a compact type in diploid wheats to an incompact type in tetraploid wheats, and then to a more compact type of hexaploid wheats. Biomass accumulation, population yield, harvest index and the seed to leaf ratio increased from diploid to tetraploid and hexaploid, associated with heavier specific internode weight and greater canopy biomass density in hexaploid and tetraploid than in diploid wheat. Leaf photosynthetic rate and WUEi were decreased from diploid to tetraploid and increased from tetraploid to hexaploid due to more compact leaf type in hexaploid and diploid than in tetraploid. Grain yield formation and WUEi were closely associated with spatial stance of leaves and stems. We conclude that the ideotype of dryland wheats could be based on spatial reconstruction of leaf type and further exertion of leaf photosynthetic rate. PMID:25181037

  15. Does the aboveground herbivore assemblage influence soil bacterial community composition and richness in subalpine grasslands?

    PubMed

    Hodel, Melanie; Schütz, Martin; Vandegehuchte, Martijn L; Frey, Beat; Albrecht, Matthias; Busse, Matt D; Risch, Anita C

    2014-10-01

    Grassland ecosystems support large communities of aboveground herbivores that are known to directly and indirectly affect belowground properties such as the microbial community composition, richness, or biomass. Even though multiple species of functionally different herbivores coexist in grassland ecosystems, most studies have only considered the impact of a single group, i.e., large ungulates (mostly domestic livestock) on microbial communities. Thus, we investigated how the exclusion of four groups of functionally different herbivores affects bacterial community composition, richness, and biomass in two vegetation types with different grazing histories. We progressively excluded large, medium, and small mammals as well as invertebrate herbivores using exclosures at 18 subalpine grassland sites (9 per vegetation type). We assessed the bacterial community composition using terminal restriction fragment length polymorphism (T-RFLP) at each site and exclosure type during three consecutive growing seasons (2009-2011) for rhizosphere and mineral soil separately. In addition, we determined microbial biomass carbon (MBC), root biomass, plant carbon:nitrogen ratio, soil temperature, and soil moisture. Even though several of these variables were affected by herbivore exclusion and vegetation type, against our expectations, bacterial community composition, richness, or MBC were not. Yet, bacterial communities strongly differed between the three growing seasons as well as to some extent between our study sites. Thus, our study indicates that the spatiotemporal variability in soil microclimate has much stronger effects on the soil bacterial communities than the grazing regime or the composition of the vegetation in this high-elevation ecosystem. PMID:24889285

  16. POLINSAR Coherence-Based Regression Analysis of Forest Biomass Using RADARSAT-2 Datasets

    NASA Astrophysics Data System (ADS)

    Singh, J.; Kumar, S.; Kushwaha, S. P. S.

    2014-11-01

    Forests play a pivotal role in synchronizing earth's carbon cycle by absorbing carbon from the atmosphere and storing it in the form of biomass. Researchers today are trying to understand the climatic variations, especially those occurring due to destruction of forest and its corresponding biomass loss. Hence, quantification of various forest parameters such as biomass is imperative for evaluating the carbon. The objective of this research was to exploit the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) technique for analysing the relationship between complex coherence and field-estimated aboveground biomass. Association between the backscatter and the aboveground biomass was also established in the process. To serve our objective, Radarsat-2 interferometric pair dated 4th March, 2013 (master image) and 28th March, 2013 (slave image) were procured for the Barkot Reserve Forest region of Dehradun, India. Field sampling was done for 30 plots (31.62 m x 31.62 m) and stem diameter and tree height were measured in each plot. The study emphasized on the application of POLINSAR coherence instead of using conventional method of relying on backscatter values for retrieving forest biomass. Coherence matrices were utilized for generating complex coherence values for different polarization channels and were regressed against field estimated aboveground biomass. Results indicated a negative linear relationship between complex coherence and aboveground biomass with the cross - polarized coherence showing the highest R2 value of 0.71. Further, the backscatter mechanism when studied with respect to aboveground biomass indicated a positive linear relationship between backscatter values and field estimated aboveground biomass with R2 value of 0.45 and 0.61 for slave and master image respectively. The results suggest that PolInSAR technique, in combination with different modelling approaches, can be adopted for estimating forest

  17. Shifting grassland plant community structure drives positive interactive effects of warming and diversity on aboveground net primary productivity.

    PubMed

    Cowles, Jane M; Wragg, Peter D; Wright, Alexandra J; Powers, Jennifer S; Tilman, David

    2016-02-01

    Ecosystems worldwide are increasingly impacted by multiple drivers of environmental change, including climate warming and loss of biodiversity. We show, using a long-term factorial experiment, that plant diversity loss alters the effects of warming on productivity. Aboveground primary productivity was increased by both high plant diversity and warming, and, in concert, warming (≈1.5 °C average above and belowground warming over the growing season) and diversity caused a greater than additive increase in aboveground productivity. The aboveground warming effects increased over time, particularly at higher levels of diversity, perhaps because of warming-induced increases in legume and C4 bunch grass abundances, and facilitative feedbacks of these species on productivity. Moreover, higher plant diversity was associated with the amelioration of warming-induced environmental conditions. This led to cooler temperatures, decreased vapor pressure deficit, and increased surface soil moisture in higher diversity communities. Root biomass (0-30 cm) was likewise consistently greater at higher plant diversity and was greater with warming in monocultures and at intermediate diversity, but at high diversity warming had no detectable effect. This may be because warming increased the abundance of legumes, which have lower root : shoot ratios than the other types of plants. In addition, legumes increase soil nitrogen (N) supply, which could make N less limiting to other species and potentially decrease their investment in roots. The negative warming × diversity interaction on root mass led to an overall negative interactive effect of these two global change factors on the sum of above and belowground biomass, and thus likely on total plant carbon stores. In total, plant diversity increased the effect of warming on aboveground net productivity and moderated the effect on root mass. These divergent effects suggest that warming and changes in plant diversity are likely to have both

  18. Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations

    USGS Publications Warehouse

    Gu, Yingxin; Wylie, Bruce K.

    2015-01-01

    Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.

  19. Usefulness of Skylab color photography and ERTS-1 multispectral imagery for mapping range vegetation types in southwestern Wyoming

    NASA Technical Reports Server (NTRS)

    Gordon, R. C. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. Aerial photography at scales of 1:43,400 and 1:104,500 was used to evaluate the usefulness of Skylab color photography (scales of 1:477,979 and 1:712,917) and ERTS-1 multispectral imagery (scale 1:1,000,000) for mapping range vegetation types. The project was successful in producing a range vegetation map of the 68,000 acres of salt desert shrub type in southwestern Wyoming. Techniques for estimation of above-ground green biomass have not yet been confirmed due to the mechanical failure of the photometer used in obtaining relative reflectance measurement. However, graphs of log transmittance versus above-ground green biomass indicate that production estimates may be made for some vegetation types from ERTS imagery. Other vegetation types not suitable for direct ERTS estimation of green biomass may possibly be related to those vegetation types whose production has been estimated from the multispectral imagery.

  20. How much biomass do plant communities pack per unit volume?

    PubMed Central

    Rheault, Guillaume; Bonin, Laurianne; Roca, Irene Torrecilla; Martin, Charles A.; Desrochers, Louis; Seiferling, Ian

    2015-01-01

    Aboveground production in terrestrial plant communities is commonly expressed in amount of carbon, or biomass, per unit surface. Alternatively, expressing production per unit volume allows the comparison of communities by their fundamental capacities in packing carbon. In this work we reanalyzed published data from more than 900 plant communities across nine ecosystems to show that standing dry biomass per unit volume (biomass packing) consistently averages around 1 kg/m3 and rarely exceeds 5 kg/m3 across ecosystem types. Furthermore, we examined how empirical relationships between aboveground production and plant species richness are modified when standing biomass is expressed per unit volume rather than surface. We propose that biomass packing emphasizes species coexistence mechanisms and may be an indicator of resource use efficiency in plant communities. PMID:25802814

  1. Genome Wide Association Mapping in Arabidopsis thaliana Identifies Novel Genes Involved in Linking Allyl Glucosinolate to Altered Biomass and Defense

    PubMed Central

    Francisco, Marta; Joseph, Bindu; Caligagan, Hart; Li, Baohua; Corwin, Jason A.; Lin, Catherine; Kerwin, Rachel E.; Burow, Meike; Kliebenstein, Daniel J.

    2016-01-01

    A key limitation in modern biology is the ability to rapidly identify genes underlying newly identified complex phenotypes. Genome wide association studies (GWAS) have become an increasingly important approach for dissecting natural variation by associating phenotypes with genotypes at a genome wide level. Recent work is showing that the Arabidopsis thaliana defense metabolite, allyl glucosinolate (GSL), may provide direct feedback regulation, linking defense metabolism outputs to the growth, and defense responses of the plant. However, there is still a need to identify genes that underlie this process. To start developing a deeper understanding of the mechanism(s) that modulate the ability of exogenous allyl GSL to alter growth and defense, we measured changes in plant biomass and defense metabolites in a collection of natural 96 A. thaliana accessions fed with 50 μM of allyl GSL. Exogenous allyl GSL was introduced exclusively to the roots and the compound transported to the leaf leading to a wide range of heritable effects upon plant biomass and endogenous GSL accumulation. Using natural variation we conducted GWAS to identify a number of new genes which potentially control allyl responses in various plant processes. This is one of the first instances in which this approach has been successfully utilized to begin dissecting a novel phenotype to the underlying molecular/polygenic basis. PMID:27462337

  2. What is the value of biomass remote sensing data for blue carbon inventories?

    NASA Astrophysics Data System (ADS)

    Byrd, K. B.; Simard, M.; Crooks, S.; Windham-Myers, L.

    2015-12-01

    The U.S. is testing approaches for accounting for carbon emissions and removals associated with wetland management according to 2013 IPCC Wetlands Supplement guidelines. Quality of reporting is measured from low (Tier 1) to high (Tier 3) depending upon data availability and analytical capacity. The use of satellite remote sensing data to derive carbon stocks and flux provides a practical approach for moving beyond IPCC Tier 1, the global default factor approach, to support Tier 2 or Tier 3 quantification of carbon emissions or removals. We are determining the "price of precision," or the extent to which improved satellite data will continue to increase the accuracy of "blue carbon" accounting. Tidal marsh biomass values are needed to quantify aboveground carbon stocks and stock changes, and to run process-based models of carbon accumulation. Maps of tidal marsh biomass have been produced from high resolution commercial and moderate resolution Landsat satellite data with relatively low error [percent normalized RMSE (%RMSE) from 7 to 14%]. Recently for a brackish marsh in Suisun Bay, California, we used Landsat 8 data to produce a biomass map that applied the Wide Dynamic Range Vegetation Index (WDRVI) (ρNIR*0.2 - ρR)/(ρNIR*0.2+ρR) to fully vegetated pixels and the Simple Ratio index (ρRed/ρGreen) to pixels with a mix of vegetation and water. Overall RMSE was 208 g/m2, while %RMSE = 13.7%. Also, preliminary use of airborne and spaceborne RADAR data in coastal Louisiana produced a marsh biomass map with 30% error. The integration of RADAR and LiDAR with optical remote sensing data has the potential to further reduce error in biomass estimation. In 2017, nations will report back to the U.N. Framework Convention on Climate Change on their experience in applying the Wetlands Supplement guidelines. These remote sensing efforts will mark an important step toward quantifying human impacts to wetlands within the global carbon cycle.

  3. Biomass and nutrient distributions in central Oregon second-growth ponderosa pine ecosystems. Forest Service research paper

    SciTech Connect

    Little, S.N.; Shainsky, L.J.

    1995-03-01

    We investigated the distributioin of biomass and nurtrients in second-growth ponderosa pine (Pinus ponderosa Dougl. ex Laws.) ecosystems in central Oregon. Destructive sampling of aboveground and belowground tree biomass was carried out at six sites in the Deschutes National Forest; three of these sites also were intensively sampled for biomass and nutrient concentrations of the soil, forest floor, residue, and shrub components. Tree biomass equations were developed that related component biomass to diameter at breast height and total tree height.

  4. Aboveground allometric models for freeze-affected black mangroves (Avicennia germinans): equations for a climate sensitive mangrove-marsh ecotone.

    PubMed

    Osland, Michael J; Day, Richard H; Larriviere, Jack C; From, Andrew S

    2014-01-01

    Across the globe, species distributions are changing in response to climate change and land use change. In parts of the southeastern United States, climate change is expected to result in the poleward range expansion of black mangroves (Avicennia germinans) at the expense of some salt marsh vegetation. The morphology of A. germinans at its northern range limit is more shrub-like than in tropical climes in part due to the aboveground structural damage and vigorous multi-stem regrowth triggered by extreme winter temperatures. In this study, we developed aboveground allometric equations for freeze-affected black mangroves which can be used to quantify: (1) total aboveground biomass; (2) leaf biomass; (3) stem plus branch biomass; and (4) leaf area. Plant volume (i.e., a combination of crown area and plant height) was selected as the optimal predictor of the four response variables. We expect that our simple measurements and equations can be adapted for use in other mangrove ecosystems located in abiotic settings that result in mangrove individuals with dwarf or shrub-like morphologies including oligotrophic and arid environments. Many important ecological functions and services are affected by changes in coastal wetland plant community structure and productivity including carbon storage, nutrient cycling, coastal protection, recreation, fish and avian habitat, and ecosystem response to sea level rise and extreme climatic events. Coastal scientists in the southeastern United States can use the identified allometric equations, in combination with easily obtained and non-destructive plant volume measurements, to better quantify and monitor ecological change within the dynamic, climate sensitive, and highly-productive mangrove-marsh ecotone. PMID:24971938

  5. Aboveground Allometric Models for Freeze-Affected Black Mangroves (Avicennia germinans): Equations for a Climate Sensitive Mangrove-Marsh Ecotone

    PubMed Central

    Osland, Michael J.; Day, Richard H.; Larriviere, Jack C.; From, Andrew S.

    2014-01-01

    Across the globe, species distributions are changing in response to climate change and land use change. In parts of the southeastern United States, climate change is expected to result in the poleward range expansion of black mangroves (Avicennia germinans) at the expense of some salt marsh vegetation. The morphology of A. germinans at its northern range limit is more shrub-like than in tropical climes in part due to the aboveground structural damage and vigorous multi-stem regrowth triggered by extreme winter temperatures. In this study, we developed aboveground allometric equations for freeze-affected black mangroves which can be used to quantify: (1) total aboveground biomass; (2) leaf biomass; (3) stem plus branch biomass; and (4) leaf area. Plant volume (i.e., a combination of crown area and plant height) was selected as the optimal predictor of the four response variables. We expect that our simple measurements and equations can be adapted for use in other mangrove ecosystems located in abiotic settings that result in mangrove individuals with dwarf or shrub-like morphologies including oligotrophic and arid environments. Many important ecological functions and services are affected by changes in coastal wetland plant community structure and productivity including carbon storage, nutrient cycling, coastal protection, recreation, fish and avian habitat, and ecosystem response to sea level rise and extreme climatic events. Coastal scientists in the southeastern United States can use the identified allometric equations, in combination with easily obtained and non-destructive plant volume measurements, to better quantify and monitor ecological change within the dynamic, climate sensitive, and highly-productive mangrove-marsh ecotone. PMID:24971938

  6. Aboveground allometric models for freeze-affected black mangroves (Avicennia germinans): equations for a climate sensitive mangrove-marsh ecotone

    USGS Publications Warehouse

    Osland, Michael J.; Day, Richard H.; Larriviere, Jack C.; From, Andrew S.

    2014-01-01

    Across the globe, species distributions are changing in response to climate change and land use change. In parts of the southeastern United States, climate change is expected to result in the poleward range expansion of black mangroves (Avicennia germinans) at the expense of some salt marsh vegetation. The morphology of A. germinans at its northern range limit is more shrub-like than in tropical climes in part due to the aboveground structural damage and vigorous multi-stem regrowth triggered by extreme winter temperatures. In this study, we developed aboveground allometric equations for freeze-affected black mangroves which can be used to quantify: (1) total aboveground biomass; (2) leaf biomass; (3) stem plus branch biomass; and (4) leaf area. Plant volume (i.e., a combination of crown area and plant height) was selected as the optimal predictor of the four response variables. We expect that our simple measurements and equations can be adapted for use in other mangrove ecosystems located in abiotic settings that result in mangrove individuals with dwarf or shrub-like morphologies including oligotrophic and arid environments. Many important ecological functions and services are affected by changes in coastal wetland plant community structure and productivity including carbon storage, nutrient cycling, coastal protection, recreation, fish and avian habitat, and ecosystem response to sea level rise and extreme climatic events. Coastal scientists in the southeastern United States can use the identified allometric equations, in combination with easily obtained and non-destructive plant volume measurements, to better quantify and monitor ecological change within the dynamic, climate sensitive, and highly-productive mangrove-marsh ecotone.

  7. Salinity influences on aboveground and belowground net primary productivity in tidal wetlands

    USGS Publications Warehouse

    Pierfelice, Kathryn N.; Graeme Lockaby, B.; Krauss, Ken W.; Conner, William H.; Noe, Gregory; Ricker, Matthew C.

    2015-01-01

    Tidal freshwater wetlands are one of the most vulnerable ecosystems to climate change and rising sea levels. However salinification within these systems is poorly understood, therefore, productivity (litterfall, woody biomass, and fine roots) were investigated on three forested tidal wetlands [(1) freshwater, (2) moderately saline, and (3) heavily salt-impacted] and a marsh along the Waccamaw and Turkey Creek in South Carolina. Mean aboveground (litterfall and woody biomass) production on the freshwater, moderately saline, heavily salt-impacted, and marsh, respectively, was 1,061, 492, 79, and 0  g m−2 year−1 versus belowground (fine roots) 860, 490, 620, and 2,128  g m−2 year−1. Litterfall and woody biomass displayed an inverse relationship with salinity. Shifts in productivity across saline sites is of concern because sea level is predicted to continue rising. Results from the research reported in this paper provide baseline data upon which coupled hydrologic/wetland models can be created to quantify future changes in tidal forest functions.

  8. The response of aboveground plant productivity to earlier snowmelt and summer warming in an Arctic ecosystem

    NASA Astrophysics Data System (ADS)

    Livensperger, C.; Steltzer, H.; Darrouzet-Nardi, A.; Sullivan, P.; Wallenstein, M. D.; Weintraub, M. N.

    2012-12-01

    Plant communities in the Arctic are undergoing changes in structure and function due to shifts in seasonality from changing winters and summer warming. These changes will impact biogeochemical cycling, surface energy balance, and functioning of vertebrate and invertebrate communities. To examine seasonal controls on aboveground net primary production (ANPP) in a moist acidic tundra ecosystem in northern Alaska, we shifted the growing season by accelerating snowmelt (using radiation absorbing shadecloth) and warming air and soil temperature (using 1 m2 open-top chambers), individually and in combination. After three years, we measured ANPP by harvesting up to 16 individual ramets, tillers and rhizomes for each of 7 plant species, including two deciduous shrubs, two graminoids, two evergreen shrubs and one forb during peak season. Our results show that ANPP per stem summed across the 7 species increased when snow melt occurred earlier. However, standing biomass, excluding current year growth, was also greater. The ratio of ANPP/standing biomass decreased in all treatments compared to the control. ANPP per unit standing biomass summed for the four shrub species decreases due to summer warming alone or in combination with early snowmelt; however early snowmelt alone did not lead to lower ANPP for the shrubs. ANPP per tiller or rhizome summed for the three herbaceous species increased in response to summer warming. Understanding the differential response of plants to changing seasonality will inform predictions of future Arctic plant community structure and function.

  9. Costs of jasmonic acid induced defense in aboveground and belowground parts of corn (Zea mays L.).

    PubMed

    Feng, Yuanjiao; Wang, Jianwu; Luo, Shiming; Fan, Huizhi; Jin, Qiong

    2012-08-01

    Costs of jasmonic acid (JA) induced plant defense have gained increasing attention. In this study, JA was applied continuously to the aboveground (AG) or belowground (BG) parts, or AG plus BG parts of corn (Zea mays L.) to investigate whether JA exposure in one part of the plant would affect defense responses in another part, and whether or not JA induced defense would incur allocation costs. The results indicated that continuous JA application to AG parts systemically affected the quantities of defense chemicals in the roots, and vice versa. Quantities of DIMBOA and total amounts of phenolic compounds in leaves or roots generally increased 2 or 4 wk after the JA treatment to different plant parts. In the first 2 wk after application, the increase of defense chemicals in leaves and roots was accompanied by a significant decrease of root length, root surface area, and root biomass. Four weeks after the JA application, however, no such costs for the increase of defense chemicals in leaves and roots were detected. Instead, shoot biomass and root biomass increased. The results suggest that JA as a defense signal can be transferred from AG parts to BG parts of corn, and vice versa. Costs for induced defense elicited by continuous JA application were found in the early 2 wk, while distinct benefits were observed later, i.e., 4 wk after JA treatment. PMID:22744011

  10. Biomass Burning

    Atmospheric Science Data Center

    2015-07-27

    Projects:  Biomass Burning Definition/Description:  Biomass Burning: This data set represents the geographical and temporal distribution of total amount of biomass burned. These data may be used in general circulation models (GCMs) and ...

  11. Quantifying Annual Aboveground Net Primary Production in the Intermountain West

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As part of a larger project, methods were developed to quantify current year growth on grasses, forbs, and shrubs. Annual aboveground net primary production (ANPP) data are needed for this project to calibrate results from computer simulation models and remote-sensing data. Measuring annual ANPP of ...

  12. Forecasting annual aboveground net primary production in the intermountain west

    Technology Transfer Automated Retrieval System (TEKTRAN)

    For many land manager’s annual aboveground net primary production, or plant growth, is a key factor affecting business success, profitability and each land manager's ability to successfully meet land management objectives. The strategy often utilized for forecasting plant growth is to assume every y...

  13. Biomass and energy productivity of Leucaena under humid subtropical conditions

    SciTech Connect

    Othman, A.B.; Prine, G.M.

    1984-01-01

    A table shows the amount and energy content of above-ground biomass produced in 1982 and 1983 by the 12 most productive of 62 accessions of Leucanena spp. established in 1979 at the University of Florida. Mean annual biomass production of the 12 accessions was 29.3 and 24.7 Mg/ha, with energy contents of 19,690 and 19,820 J/g, in 1982 and 1983 respectively.

  14. Height and Biomass of Mangroves in Africa from ICEsat/GLAS and SRTM

    NASA Technical Reports Server (NTRS)

    Fatoyinbo, Temilola E.; Simard, Marc

    2012-01-01

    The accurate quantification of forest 3-D structure is of great importance for studies of the global carbon cycle and biodiversity. These studies are especially relevant in Africa, where deforestation rates are high and the lack of background data is great. Mangrove forests are ecologically significant and it is important to measure mangrove canopy heights and biomass. The objectives of this study are to estimate: 1. The total area, 2. Canopy height distributions and 3. Aboveground biomass of mangrove forests in Africa. To derive mangrove 3-D structure and biomass maps, we used a combination of mangrove maps derived from Landsat ETM+, LiDAR canopy height estimates from ICEsat/GLAS (Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) and elevation data from SRTM (Shuttle Radar Topography Mission) for the African continent. More specifically, we extracted mangrove forest areas on the SRTM DEM using Landsat based landcover maps. The LiDAR (Light Detection and Ranging) measurements from the large footprint GLAS sensor were used to derive local estimates of canopy height and calibrate the Interferometric Synthetic Aperture Radar (InSAR) data from SRTM. We then applied allometric equations relating canopy height to biomass in order to estimate above ground biomass (AGB) from the canopy height product. The total mangrove area of Africa was estimated to be 25 960 square kilometers with 83% accuracy. The largest mangrove areas and greatest total biomass was 29 found in Nigeria covering 8 573 km2 with 132 x10(exp 6) Mg AGB. Canopy height across Africa was estimated with an overall root mean square error of 3.55 m. This error also includes the impact of using sensors with different resolutions and geolocation error which make comparison between measurements sensitive to canopy heterogeneities. This study provides the first systematic estimates of mangrove area, height and biomass in Africa. Our results showed that the combination of ICEsat/GLAS and

  15. 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.

  16. Modeling the spatial distribution of above-ground carbon in Mexican coniferous forests using remote sensing and a geostatistical approach

    NASA Astrophysics Data System (ADS)

    Galeana-Pizaña, J. Mauricio; López-Caloca, Alejandra; López-Quiroz, Penélope; Silván-Cárdenas, José Luis; Couturier, Stéphane

    2014-08-01

    Forest conservation is considered an option for mitigating the effect of greenhouse gases on global climate, hence monitoring forest carbon pools at global and local levels is important. The present study explores the capability of remote-sensing variables (vegetation indices and textures derived from SPOT-5; backscattering coefficient and interferometric coherence of ALOS PALSAR images) for modeling the spatial distribution of above-ground biomass in the Environmental Conservation Zone of Mexico City. Correlation and spatial autocorrelation coefficients were used to select significant explanatory variables in fir and pine forests. The correlation for interferometric coherence in HV polarization was negative, with correlations coefficients r = -0.83 for the fir and r = -0.75 for the pine forests. Regression-kriging showed the least root mean square error among the spatial interpolation methods used, with 37.75 tC/ha for fir forests and 29.15 tC/ha for pine forests. The results showed that a hybrid geospatial method, based on interferometric coherence data and a regression-kriging interpolator, has good potential for estimating above-ground biomass carbon.

  17. Species richness of arbuscular mycorrhizal fungi: associations with grassland plant richness and biomass.

    PubMed

    Hiiesalu, Inga; Pärtel, Meelis; Davison, John; Gerhold, Pille; Metsis, Madis; Moora, Mari; Öpik, Maarja; Vasar, Martti; Zobel, Martin; Wilson, Scott D

    2014-07-01

    Although experiments show a positive association between vascular plant and arbuscular mycorrhizal fungal (AMF) species richness, evidence from natural ecosystems is scarce. Furthermore, there is little knowledge about how AMF richness varies with belowground plant richness and biomass. We examined relationships among AMF richness, above- and belowground plant richness, and plant root and shoot biomass in a native North American grassland. Root-colonizing AMF richness and belowground plant richness were detected from the same bulk root samples by 454-sequencing of the AMF SSU rRNA and plant trnL genes. In total we detected 63 AMF taxa. Plant richness was 1.5 times greater belowground than aboveground. AMF richness was significantly positively correlated with plant species richness, and more strongly with below- than aboveground plant richness. Belowground plant richness was positively correlated with belowground plant biomass and total plant biomass, whereas aboveground plant richness was positively correlated only with belowground plant biomass. By contrast, AMF richness was negatively correlated with belowground and total plant biomass. Our results indicate that AMF richness and plant belowground richness are more strongly related with each other and with plant community biomass than with the plant aboveground richness measures that have been almost exclusively considered to date. PMID:24641509

  18. Potato tuber herbivory increases resistance to aboveground lepidopteran herbivores.

    PubMed

    Kumar, Pavan; Ortiz, Erandi Vargas; Garrido, Etzel; Poveda, Katja; Jander, Georg

    2016-09-01

    Plants mediate interactions between aboveground and belowground herbivores. Although effects of root herbivory on foliar herbivores have been documented in several plant species, interactions between tuber-feeding herbivores and foliar herbivores are rarely investigated. We report that localized tuber damage by Tecia solanivora (Guatemalan tuber moth) larvae reduced aboveground Spodoptera exigua (beet armyworm) and Spodoptera frugiperda (fall armyworm) performance on Solanum tuberosum (potato). Conversely, S. exigua leaf damage had no noticeable effect on belowground T. solanivora performance. Tuber infestation by T. solanivora induced systemic plant defenses and elevated resistance to aboveground herbivores. Lipoxygenase 3 (Lox3), which contributes to the synthesis of plant defense signaling molecules, had higher transcript abundance in T. solanivora-infested leaves and tubers than in equivalent control samples. Foliar expression of the hydroxycinnamoyl-CoA quinate hydroxycinnamoyl transferase (HQT) and 3-hydroxy-3-methylglutaryl CoA reductase I (HMGR1) genes, which are involved in chlorogenic acid and steroidal glycoalkaloid biosynthesis, respectively, also increased in response to tuber herbivory. Leaf metabolite profiling demonstrated the accumulation of unknown metabolites as well as the known potato defense compounds chlorogenic acid, α-solanine, and α-chaconine. When added to insect diet at concentrations similar to those found in potato leaves, chlorogenic acid, α-solanine, and α-chaconine all reduced S. exigua larval growth. Thus, despite the fact that tubers are a metabolic sink tissue, T. solanivora feeding elicits a systemic signal that induces aboveground resistance against S. exigua and S. frugiperda by increasing foliar abundance of defensive metabolites. PMID:27147449

  19. 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.

  20. 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.

  1. A cost effective and operational methodology for wall to wall Above Ground Biomass (AGB) and carbon stocks estimation and mapping: Nepal REDD+

    NASA Astrophysics Data System (ADS)

    Gilani, H., Sr.; Ganguly, S.; Zhang, G.; Koju, U. A.; Murthy, M. S. R.; Nemani, R. R.; Manandhar, U.; Thapa, G. J.

    2015-12-01

    Nepal is a landlocked country with 39% forest cover of the total land area (147,181 km2). Under the Forest Carbon Partnership Facility (FCPF) and implemented by the World Bank (WB), Nepal chosen as one of four countries best suitable for results-based payment system for Reducing Emissions from Deforestation and Forest Degradation (REDD and REDD+) scheme. At the national level Landsat based, from 1990 to 2000 the forest area has declined by 2%, i.e. by 1467 km2, whereas from 2000 to 2010 it has declined only by 0.12% i.e. 176 km2. A cost effective monitoring and evaluation system for REDD+ requires a balanced approach of remote sensing and ground measurements. This paper provides, for Nepal a cost effective and operational 30 m Above Ground Biomass (AGB) estimation and mapping methodology using freely available satellite data integrated with field inventory. Leaf Area Index (LAI) generated based on propose methodology by Ganguly et al. (2012) using Landsat-8 the OLI cloud free images. To generate tree canopy height map, a density scatter graph between the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat) estimated maximum height and Landsat LAI nearest to the center coordinates of the GLAS shots show a moderate but significant exponential correlation (31.211*LAI0.4593, R2= 0.33, RMSE=13.25 m). From the field well distributed circular (750m2 and 500m2), 1124 field plots (0.001% representation of forest cover) measured which were used for estimation AGB (ton/ha) using Sharma et al. (1990) proposed equations for all tree species of Nepal. A satisfactory linear relationship (AGB = 8.7018*Hmax-101.24, R2=0.67, RMSE=7.2 ton/ha) achieved between maximum canopy height (Hmax) and AGB (ton/ha). This cost effective and operational methodology is replicable, over 5-10 years with minimum ground samples through integration of satellite images. Developed AGB used to produce optimum fuel wood scenarios using population and road

  2. Biomass and nitrogen accumulation of hairy vetch-cereal rye cover crop mixtures as influenced by species proportions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The performance and suitability of a legume-grass cover crop mixture for specific functions may be influenced by the proportions of each species in the mixture. The objectives of this study were to: 1) evaluate aboveground biomass and species biomass proportions at different hairy vetch (Vicia villo...

  3. Responses of Plant Community Composition and Biomass Production to Warming and Nitrogen Deposition in a Temperate Meadow Ecosystem

    PubMed Central

    Gao, Song; Guo, Jixun; Sun, Wei

    2015-01-01

    Climate change has profound influences on plant community composition and ecosystem functions. However, its effects on plant community composition and biomass production are not well understood. A four-year field experiment was conducted to examine the effects of warming, nitrogen (N) addition, and their interactions on plant community composition and biomass production in a temperate meadow ecosystem in northeast China. Experimental warming had no significant effect on plant species richness, evenness, and diversity, while N addition highly reduced the species richness and diversity. Warming tended to reduce the importance value of graminoid species but increased the value of forbs, while N addition had the opposite effect. Warming tended to increase the belowground biomass, but had an opposite tendency to decrease the aboveground biomass. The influences of warming on aboveground production were dependent upon precipitation. Experimental warming had little effect on aboveground biomass in the years with higher precipitation, but significantly suppressed aboveground biomass in dry years. Our results suggest that warming had indirect effects on plant production via its effect on the water availability. Nitrogen addition significantly increased above- and below-ground production, suggesting that N is one of the most important limiting factors determining plant productivity in the studied meadow steppe. Significant interactive effects of warming plus N addition on belowground biomass were also detected. Our observations revealed that environmental changes (warming and N deposition) play significant roles in regulating plant community composition and biomass production in temperate meadow steppe ecosystem in northeast China. PMID:25874975

  4. BIOMASS UTILIZATION

    EPA Science Inventory

    The biomass utilization task consists of the evaluation of a biomass conversion technology including research and development initiatives. The project is expected to provide information on co-control of pollutants, as well as, to prove the feasibility of biomass conversion techn...

  5. Biomass pretreatment

    SciTech Connect

    Hennessey, Susan Marie; Friend, Julie; Elander, Richard T; Tucker, III, Melvin P

    2013-05-21

    A method is provided for producing an improved pretreated biomass product for use in saccharification followed by fermentation to produce a target chemical that includes removal of saccharification and or fermentation inhibitors from the pretreated biomass product. Specifically, the pretreated biomass product derived from using the present method has fewer inhibitors of saccharification and/or fermentation without a loss in sugar content.

  6. Beyond Radar Backscatter: Estimating Forest Structure and Biomass with Radar Interferometry and Lidar Remote Sensing

    NASA Astrophysics Data System (ADS)

    Lavalle, M.; Ahmed, R.

    2014-12-01

    Mapping forest structure and aboveground biomass globally is a major challenge that the remote sensing community has been facing for decades. Radar backscatter is sensitive to biomass only up to a certain amount (about 150 tons/ha at L-band and 300 tons/ha at P-band), whereas lidar remote sensing is strongly limited by poor spatial coverage. In recent years radar interferometry, including its extension to polarimetric radar interferometry (PolInSAR), has emerged as a new technique to overcome the limitations of radar backscatter. The idea of PolInSAR is to use jointly interferometric and polarimetric radar techniques to separate different scattering mechanisms and retrieve the vertical structure of forests. The advantage is to map ecosystem structure continuously over large areas and independently of cloud coverage. Experiments have shown that forest height - an important proxy for biomass - can be estimated using PolInSAR with accuracy between 15% and 20% at plot level. At AGU we will review the state-of-art of repeat-pass PolInSAR for biomass mapping, including its potential and limitations, and discuss how merging lidar data with PolInSAR data can be beneficial not only for product cross-validation but also for achieving better estimation of ecosystem properties over large areas. In particular, lidar data are expected to aid the inversion of PolInSAR models by providing (1) better identification of ground under the canopy, (2) approximate information of canopy structure in limited areas, and (3) maximum tree height useful for mapping PolInSAR temporal decorrelation. We will show our tree height and biomass maps using PolInSAR L-band JPL/UAVSAR data collected in tropical and temperate forests, and P-band ONERA/TROPISAR data acquired in French Guiana. LVIS lidar data will be used, as well as SRTM data, field measurements and inventory data to support our study. The use of two different radar frequencies and repeat-pass JPL UAVSAR data will offer also the

  7. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

    NASA Astrophysics Data System (ADS)

    Réjou-Méchain, M.; Muller-Landau, H. C.; Detto, M.; Thomas, S. C.; Le Toan, T.; Saatchi, S. S.; Barreto-Silva, J. S.; Bourg, N. A.; Bunyavejchewin, S.; Butt, N.; Brockelman, W. Y.; Cao, M.; Cárdenas, D.; Chiang, J.-M.; Chuyong, G. B.; Clay, K.; Condit, R.; Dattaraja, H. S.; Davies, S. J.; Duque, A.; Esufali, S.; Ewango, C.; Fernando, R. H. S.; Fletcher, C. D.; Gunatilleke, I. A. U. N.; Hao, Z.; Harms, K. E.; Hart, T. B.; Hérault, B.; Howe, R. W.; Hubbell, S. P.; Johnson, D. J.; Kenfack, D.; Larson, A. J.; Lin, L.; Lin, Y.; Lutz, J. A.; Makana, J.-R.; Malhi, Y.; Marthews, T. R.; McEwan, R. W.; McMahon, S. M.; McShea, W. J.; Muscarella, R.; Nathalang, A.; Noor, N. S. M.; Nytch, C. J.; Oliveira, A. A.; Phillips, R. P.; Pongpattananurak, N.; Punchi-Manage, R.; Salim, R.; Schurman, J.; Sukumar, R.; Suresh, H. S.; Suwanvecho, U.; Thomas, D. W.; Thompson, J.; Uríarte, M.; Valencia, R.; Vicentini, A.; Wolf, A. T.; Yap, S.; Yuan, Z.; Zartman, C. E.; Zimmerman, J. K.; Chave, J.

    2014-12-01

    Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha-1) at spatial scales ranging from 5 to 250 m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

  8. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

    NASA Astrophysics Data System (ADS)

    Réjou-Méchain, M.; Muller-Landau, H. C.; Detto, M.; Thomas, S. C.; Le Toan, T.; Saatchi, S. S.; Barreto-Silva, J. S.; Bourg, N. A.; Bunyavejchewin, S.; Butt, N.; Brockelman, W. Y.; Cao, M.; Cárdenas, D.; Chiang, J.-M.; Chuyong, G. B.; Clay, K.; Condit, R.; Dattaraja, H. S.; Davies, S. J.; Duque, A.; Esufali, S.; Ewango, C.; Fernando, R. H. S.; Fletcher, C. D.; Gunatilleke, I. A. U. N.; Hao, Z.; Harms, K. E.; Hart, T. B.; Hérault, B.; Howe, R. W.; Hubbell, S. P.; Johnson, D. J.; Kenfack, D.; Larson, A. J.; Lin, L.; Lin, Y.; Lutz, J. A.; Makana, J.-R.; Malhi, Y.; Marthews, T. R.; McEwan, R. W.; McMahon, S. M.; McShea, W. J.; Muscarella, R.; Nathalang, A.; Noor, N. S. M.; Nytch, C. J.; Oliveira, A. A.; Phillips, R. P.; Pongpattananurak, N.; Punchi-Manage, R.; Salim, R.; Schurman, J.; Sukumar, R.; Suresh, H. S.; Suwanvecho, U.; Thomas, D. W.; Thompson, J.; Uríarte, M.; Valencia, R.; Vicentini, A.; Wolf, A. T.; Yap, S.; Yuan, Z.; Zartman, C. E.; Zimmerman, J. K.; Chave, J.

    2014-04-01

    Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+. Though broad scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass (AGB) at spatial grains ranging from 5 to 250 m (0.025-6.25 ha), and we evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that the spatial sampling error in AGB is large for standard plot sizes, averaging 46.3% for 0.1 ha subplots and 16.6% for 1 ha subplots. Topographically heterogeneous sites showed positive spatial autocorrelation in AGB at scales of 100 m and above; at smaller scales, most study sites showed negative or nonexistent spatial autocorrelation in AGB. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGB leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with current statistical methods. Overall, our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

  9. Biomass Logistics

    SciTech Connect

    J. Richard Hess; Kevin L. Kenney; William A. Smith; Ian Bonner; David J. Muth

    2015-04-01

    Equipment manufacturers have made rapid improvements in biomass harvesting and handling equipment. These improvements have increased transportation and handling efficiencies due to higher biomass densities and reduced losses. Improvements in grinder efficiencies and capacity have reduced biomass grinding costs. Biomass collection efficiencies (the ratio of biomass collected to the amount available in the field) as high as 75% for crop residues and greater than 90% for perennial energy crops have also been demonstrated. However, as collection rates increase, the fraction of entrained soil in the biomass increases, and high biomass residue removal rates can violate agronomic sustainability limits. Advancements in quantifying multi-factor sustainability limits to increase removal rate as guided by sustainable residue removal plans, and mitigating soil contamination through targeted removal rates based on soil type and residue type/fraction is allowing the use of new high efficiency harvesting equipment and methods. As another consideration, single pass harvesting and other technologies that improve harvesting costs cause biomass storage moisture management challenges, which challenges are further perturbed by annual variability in biomass moisture content. Monitoring, sampling, simulation, and analysis provide basis for moisture, time, and quality relationships in storage, which has allowed the development of moisture tolerant storage systems and best management processes that combine moisture content and time to accommodate baled storage of wet material based upon “shelf-life.” The key to improving biomass supply logistics costs has been developing the associated agronomic sustainability and biomass quality technologies and processes that allow the implementation of equipment engineering solutions.

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

    NASA Astrophysics Data System (ADS)

    Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.

    2010-12-01

    There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.

  11. Recovery of above-ground woody biomass using operational modifications of conventional harvesting systems

    SciTech Connect

    Herschelman, J. W.; Domenech, D. W.

    1980-06-01

    Two harvesting systems were assembled during each of two summers to compare the operational efficiency of a whole tree harvesting system with a conventional harvesting system. Skidding of whole trees proved to be 27% more efficient than the skidding of primary stems because of operators habits of underutilizing skidder capacity. Although 5% more gals/hour were used by the whole tree system, there was a net gain of 21% more tons/gal. produced by this same system. A whole tree chipper was analyzed for its potential to process large hardwood trees for energy products. A comparison of five harvesting systems revealed that whole tree systems producing sawtimber, round pulpwood and energy chips proved most energy efficient and economically viable. A variety of machine/system factors were measured. It was determined that with certain modifications, whole tree chippers offer the best potential for processing logging residue for fuel. Forty-eight equations were developed predicting green and ovendry weights in summer and winter for whole tree weight, primary product weight, and the weight of limbs and tops for hardwood trees associated with the oak-hickory forest type in the Southern Appalachian Region based on diameter at breast height and whole tree length. Eight sawlog prediction equations were also developed based on log length, diameter small end outside bark and diameter large end outside bark. The energy efficiency of harvesting systems was studied by analyzing the equipment involved in manual and mechanized shortwood, longwood, and whole tree systems.

  12. Variability of aboveground litter inputs alters soil physicochemical and biological processes: a meta-analysis of litterfall-manipulation experiments

    NASA Astrophysics Data System (ADS)

    Xu, S.; Liu, L.; Sayer, E. J.

    2013-03-01

    Global change has been shown to greatly alter the amount of aboveground litter inputs to soil, which could cause substantial cascading effects on belowground biogeochemical cyling. Although having been studied extensively, there is uncertainty about how changes in aboveground litter inputs affect soil carbon and nutrient turnover and transformation. Here, we conducted a comprehensive compilation of 68 studies on litter addition or removal experiments, and used meta-analysis to assess the responses of soil physicochemical properties and carbon and nutrient cycling under changed aboveground litter inputs. Our results suggested that litter addition or removal could significantly alter soil temperature and moisture, but not soil pH. Litter inputs were more crucial in buffering soil temperature and moisture fluctuations in grassland than in forest. Soil respiration, soil microbial biomass carbon and total carbon in the mineral soil increased with increasing litter inputs, suggesting that soil acted as a~net carbon sink although carbon loss and transformation increased with increasing litter inputs. Total nitrogen and the C : N ratio in the mineral soil increased with increased litter inputs. However, there was no correlation between litter inputs and extractable inorganic nitrogen in the mineral soil. Compared to other ecosystems, tropical and subtropical forests are more sensitive to variation in litter inputs. Increased or decreased litter inputs altered the turnover and accumulation of soil carbon and nutrient in tropical and subtropical forests more substantially over a shorter time period compared to other ecosystems. Overall, our study suggested that, although the magnitude of responses differed greatly among ecosystems, increased litter inputs generally accelerated the decomposition and accumulation of carbon and nutrients in soil, and decreased litter inputs reduced them.

  13. 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

  14. Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Gu, Huan

    Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our

  15. Historical forest biomass dynamics modelled with Landsat spectral trajectories

    NASA Astrophysics Data System (ADS)

    Gómez, Cristina; White, Joanne C.; Wulder, Michael A.; Alejandro, Pablo

    2014-07-01

    Estimation of forest aboveground biomass (AGB) is informative of the role of forest ecosystems in local and global carbon budgets. There is a need to retrospectively estimate biomass in order to establish a historical baseline and enable reporting of change. In this research, we used temporal spectral trajectories to inform on forest successional development status in support of modelling and mapping of historic AGB for Mediterranean pines in central Spain. AGB generated with ground plot data from the Spanish National Forest Inventory (NFI), representing two collection periods (1990 and 2000), are linked with static and dynamic spectral data as captured by Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) sensors over a 25 year period (1984-2009). The importance of forest structural complexity on the relationship between AGB and spectral vegetation indices is revealed by the analysis of wavelet transforms. Two-dimensional (2D) wavelet transforms support the identification of spectral trajectory patterns of forest stands that in turn, are associated with traits of individual NFI plots, using a flexible algorithm sensitive to capturing time series similarity. Single-date spectral indices, temporal trajectories, and temporal derivatives associated with succession are used as input variables to non-parametric decision trees for modelling, estimation, and mapping of AGB and carbon sinks over the entire study area. Results indicate that patterns of change found in Normalized Difference Vegetation Index (NDVI) values are associated and relate well to classes of forest AGB. The Tasseled Cap Angle (TCA) index was found to be strongly related with forest density, although the related patterns of change had little relation with variability in historic AGB. By scaling biomass models through small (∼2.5 ha) spatial objects defined by spectral homogeneity, the AGB dynamics in the period 1990-2000 are mapped (70% accuracy when validated with plot values of

  16. Controls over aboveground forest carbon density on Barro Colorado Island, Panama

    NASA Astrophysics Data System (ADS)

    Mascaro, J.; Asner, G. P.; Muller-Landau, H. C.; van Breugel, M.; Hall, J.; Dahlin, K.

    2011-06-01

    Despite the importance of tropical forests to the global carbon cycle, ecological controls over landscape-level variation in live aboveground carbon density (ACD) in tropical forests are poorly understood. Here, we conducted a spatially comprehensive analysis of ACD variation for a continental tropical forest - Barro Colorado Island, Panama (BCI) - and tested site factors that may control such variation. We mapped ACD over 1256 ha of BCI using airborne Light Detection and Ranging (LiDAR), which was well-correlated with ground-based measurements of ACD in Panamanian forests of various ages (r2 = 0.84, RMSE = 17 Mg C ha-1, P < 0.0001). We used multiple regression to examine controls over LiDAR-derived ACD, including slope angle, forest age, bedrock, and soil texture. Collectively, these variables explained 14 % of the variation in ACD at 30-m resolution, and explained 33 % at 100-m resolution. At all resolutions, slope (linked to underlying bedrock variation) was the strongest driving factor; standing carbon stocks were generally higher on steeper slopes. This result suggests that physiography may be more important in controlling ACD variation in Neotropical forests than currently thought. Although BCI has been largely undisturbed by humans for a century, past land-use over approximately half of the island still influences ACD variation, with younger forests (80-130 years old) averaging ~15 % less carbon storage than old-growth forests (>400 years old). If other regions of relatively old tropical secondary forests also store less carbon aboveground than primary forests, the effects on the global carbon cycle could be substantial and difficult to detect with traditional satellite monitoring.

  17. Controls over aboveground forest carbon density on Barro Colorado Island, Panama

    NASA Astrophysics Data System (ADS)

    Mascaro, J.; Asner, G. P.; Muller-Landau, H. C.; van Breugel, M.; Hall, J.; Dahlin, K.

    2010-12-01

    Despite the importance of tropical forests to the global carbon cycle, ecological controls over landscape-level variation in live aboveground carbon density (ACD) in tropical forests are poorly understood. Here, we conducted a spatially comprehensive analysis of ACD variation for a mainland tropical forest - Barro Colorado Island, Panama (BCI) - and tested site factors that may control such variation. We mapped ACD over 98% of BCI (~1500 ha) using airborne Light Detection and Ranging (LiDAR), which was well-correlated with ground-based measurements of ACD in Panamanian forests of various ages (r2 = 0.77, RMSE = 29 Mg C ha-1, P < 0.0001). We used multiple regression to examine controls over LiDAR-derived ACD, including slope angle, bedrock, soil texture, and forest age. Collectively, these variables explained 14% of the variation in ACD at 30-m resolution, and explained 33% at 100-m resolution. At all resolutions, slope (linked to underlying bedrock variation) was the strongest driving factor; standing carbon stocks were generally higher on steeper slopes, where erosion rates tend to exceed weathering rates, compared to gentle slopes, where weathering in place produces deep, oxic soils. This result suggests that physiography may be more important in controlling ACD variation in Neotropical forests than currently thought. Although BCI has been largely undisturbed by humans for a century, past land-use over approximately half of the island still influences ACD variation, with younger forests (80-130 years old) averaging ~15% less carbon storage than old-growth forests (>400 years old). If other regions of relatively old tropical secondary forests also store less carbon aboveground than primary forests, the effects on the global carbon cycle could be substantial and difficult to detect with satellite monitoring.

  18. Closure Report for Corrective Action Unit 134: Aboveground Storage Tanks, Nevada Test Site, Nevada

    SciTech Connect

    NSTec Environmental Restoration

    2009-06-30

    Corrective Action Unit (CAU) 134 is identified in the Federal Facility Agreement and Consent Order (FFACO) as “Aboveground Storage Tanks” and consists of the following four Corrective Action Sites (CASs), located in Areas 3, 15, and 29 of the Nevada Test Site: · CAS 03-01-03, Aboveground Storage Tank · CAS 03-01-04, Tank · CAS 15-01-05, Aboveground Storage Tank · CAS 29-01-01, Hydrocarbon Stain

  19. Spatial patterns of vegetation biomass and soil organic carbon acquired from airborne lidar and hyperspectral imagery at Reynolds Creek Critical Zone Observatory

    NASA Astrophysics Data System (ADS)

    Will, R. M.; Li, A.; Glenn, N. F.; Benner, S. G.; Spaete, L.; Ilangakoon, N. T.

    2015-12-01

    Soil organic carbon distribution and the factors influencing this distribution are important for understanding carbon stores, vegetation dynamics, and the overall carbon cycle. Linking soil organic carbon (SOC) with aboveground vegetation biomass may provide a method to better understand SOC distribution in semiarid ecosystems. The Reynolds Creek Critical Zone Observatory (RC CZO) in Idaho, USA, is approximately 240 square kilometers and is situated in the semiarid Great Basin of the sagebrush-steppe ecosystem. Full waveform airborne lidar data and Next-Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-ng) collected in 2014 across the RC CZO are used to map vegetation biomass and SOC and then explore the relationships between them. Vegetation biomass is estimated by identifying vegetation species, and quantifying distribution and structure with lidar and integrating the field-measured biomass. Spectral data from AVIRIS-ng are used to differentiate non-photosynthetic vegetation (NPV) and soil, which are commonly confused in semiarid ecosystems. The information from lidar and AVIRIS-ng are then used to predict SOC by partial least squares regression (PLSR). An uncertainty analysis is provided, demonstrating the applicability of these approaches to improving our understanding of the distribution and patterns of SOC across the landscape.

  20. Aboveground insect infestation attenuates belowground Agrobacterium-mediated genetic transformation.

    PubMed

    Song, Geun Cheol; Lee, Soohyun; Hong, Jaehwa; Choi, Hye Kyung; Hong, Gun Hyong; Bae, Dong-Won; Mysore, Kirankumar S; Park, Yong-Soon; Ryu, Choong-Min

    2015-07-01

    Agrobacterium tumefaciens causes crown gall disease. Although Agrobacterium can be popularly used for genetic engineering, the influence of aboveground insect infestation on Agrobacterium induced gall formation has not been investigated. Nicotiana benthamiana leaves were exposed to a sucking insect (whitefly) infestation and benzothiadiazole (BTH) for 7 d, and these exposed plants were inoculated with a tumorigenic Agrobacterium strain. We evaluated, both in planta and in vitro, how whitefly infestation affects crown gall disease. Whitefly-infested plants exhibited at least a two-fold reduction in gall formation on both stem and crown root. Silencing of isochorismate synthase 1 (ICS1), required for salicylic acid (SA) synthesis, compromised gall formation indicating an involvement of SA in whitefly-derived plant defence against Agrobacterium. Endogenous SA content was augmented in whitefly-infested plants upon Agrobacterium inoculation. In addition, SA concentration was three times higher in root exudates from whitefly-infested plants. As a consequence, Agrobacterium-mediated transformation of roots of whitefly-infested plants was clearly inhibited when compared to control plants. These results suggest that aboveground whitefly infestation elicits systemic defence responses throughout the plant. Our findings provide new insights into insect-mediated leaf-root intra-communication and a framework to understand interactions between three organisms: whitefly, N. benthamiana and Agrobacterium. PMID:25676198

  1. Have ozone effects on carbon sequestration been overestimated? A new biomass response function for wheat

    NASA Astrophysics Data System (ADS)

    Pleijel, H.; Danielsson, H.; Simpson, D.; Mills, G.

    2014-08-01

    Elevated levels of tropospheric ozone can significantly impair the growth of crops. The reduced removal of CO2 by plants leads to higher atmospheric concentrations of CO2, enhancing radiative forcing. Ozone effects on economic yield, e.g. the grain yield of wheat (Triticum aestivum L.), are currently used to model effects on radiative forcing. However, changes in grain yield do not necessarily reflect changes in total biomass. Based on an analysis of 22 ozone exposure experiments with field-grown wheat, we investigated whether the use of effects on grain yield as a proxy for effects on biomass under- or overestimates effects on biomass. First, we confirmed that effects on partitioning and biomass loss are both of significant importance for wheat yield loss. Then we derived ozone dose response functions for biomass loss and for harvest index (the proportion of above-ground biomass converted to grain) based on 12 experiments and recently developed ozone uptake modelling for wheat. Finally, we used a European-scale chemical transport model (EMEP MSC-West) to assess the effect of ozone on biomass (-9%) and grain yield (-14%) loss over Europe. Based on yield data per grid square, we estimated above-ground biomass losses due to ozone in 2000 in Europe, totalling 22.2 million tonnes. Incorrectly applying the grain yield response function to model effects on biomass instead of the biomass response function of this paper would have indicated total above-ground biomass losses totalling 38.1 million (i.e. overestimating effects by 15.9 million tonnes). A key conclusion from our study is that future assessments of ozone-induced loss of agroecosystem carbon storage should use response functions for biomass, such as that provided in this paper, not grain yield, to avoid overestimation of the indirect radiative forcing from ozone effects on crop biomass accumulation.

  2. Rainforest burning and the global carbon budget: Biomass, combustion efficiency, and charcoal formation in the Brazilian Amazon

    NASA Astrophysics Data System (ADS)

    Fearnside, Philip M.; Leal, Niwton; Fernandes, Fernando Moreira

    1993-01-01

    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-1 (standard deviation (SD) = 110, n = 6 quadrats) at Fazenda Dimona, which corresponds to approximately 311 t ha-1 total dry weight biomass. A five-category visual classification at 200 points showed highly variable burn quality. Postburn aboveground biomass loading was evaluated by cutting and weighing of 100 m2 quadrats and by line intersect sampling. Quadrats had a mean dry weight of 187 t ha-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 m3 ha-1 (approximately 164 t ha-1 of aboveground dry matter) survived burning. Using carbon contents measured for different biomass components (all ˜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 CO2 and trace gases.

  3. Landscape-scale analysis of aboveground tree carbon stocks affected by mountain pine beetles in Idaho

    NASA Astrophysics Data System (ADS)

    Bright, B. C.; Hicke, J. A.; Hudak, A. T.

    2012-12-01

    Bark beetle outbreaks kill billions of trees in western North America, and the resulting tree mortality can significantly impact local and regional carbon cycling. However, substantial variability in mortality occurs within outbreak areas. Our objective was to quantify landscape-scale effects of beetle infestations on aboveground carbon (AGC) stocks using field observations and remotely sensed data across a 5054 ha study area that had experienced a mountain pine beetle outbreak. Tree mortality was classified using multispectral imagery that separated green, red, and gray trees, and models relating field observations of AGC to LiDAR data were used to map AGC. We combined mortality and AGC maps to quantify AGC in beetle-killed trees. Thirty-nine per cent of the forested area was killed by beetles, with large spatial variability in mortality severity. For the entire study area, 40-50% of AGC was contained in beetle-killed trees. When considered on a per-hectare basis, 75-89% of the study area had >25% AGC in killed trees and 3-6% of the study area had >75% of the AGC in killed trees. Our results show that despite high variability in tree mortality within an outbreak area, bark beetle epidemics can have a large impact on AGC stocks at the landscape scale.

  4. Mapping forest biomass from space - Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models

    NASA Astrophysics Data System (ADS)

    Kattenborn, Teja; Maack, Joachim; Faßnacht, Fabian; Enßle, Fabian; Ermert, Jörg; Koch, Barbara

    2015-03-01

    Spaceborne sensors allow for wide-scale assessments of forest ecosystems. Combining the products of multiple sensors is hypothesized to improve the estimation of forest biomass. We applied interferometric (Tandem-X) and photogrammetric (WorldView-2) based predictors, e.g. canopy height models, in combination with hyperspectral predictors (EO1-Hyperion) by using 4 different machine learning algorithms for biomass estimation in temperate forest stands near Karlsruhe, Germany. An iterative model selection procedure was used to identify the optimal combination of predictors. The most accurate model (Random Forest) reached a r2 of 0.73 with a RMSE of 14.9% (29.4 t/ha). Further results revealed that the predictive accuracy depended highly on the statistical model and the area size of the field samples. We conclude that a fusion of canopy height and spectral information allows for accurate estimations of forest biomass from space.

  5. Topo-edaphic controls over woody plant biomass in South African savannas

    NASA Astrophysics Data System (ADS)

    Colgan, M. S.; Asner, G. P.; Levick, S. R.; Martin, R. E.; Chadwick, O. A.

    2012-05-01

    The distribution of woody biomass in savannas reflects spatial patterns fundamental to ecosystem processes, such as water flow, competition, and herbivory, and is a key contributor to savanna ecosystem services, such as fuelwood supply. While total precipitation sets an upper bound on savanna woody biomass, the extent to which substrate and terrain constrain trees and shrubs below this maximum remains poorly understood, often occluded by local-scale disturbances such as fire and trampling. Here we investigate the role of hillslope topography and soil properties in controlling woody plant aboveground biomass (AGB) in Kruger National Park, South Africa. Large-area sampling with airborne Light Detection and Ranging (LiDAR) provided a means to average across local-scale disturbances, revealing an unexpectedly linear relationship between AGB and hillslope-position on basalts, where biomass levels were lowest on crests, and linearly increased toward streams (R2 = 0.91). The observed pattern was different on granite substrates, where AGB exhibited a strongly non-linear relationship with hillslope position: AGB was high on crests, decreased midslope, and then increased near stream channels (R2 = 0.87). Overall, we observed 5-to-8-fold lower AGB on clayey, basalt-derived soil than on granites, and we suggest this is due to herbivore-fire interactions rather than lower hydraulic conductivity or clay shrinkage/swelling, as previously hypothesized. By mapping AGB within and outside fire and herbivore exclosures, we found that basalt-derived soils support tenfold higher AGB in the absence of fire and herbivory, suggesting high clay content alone is not a proximal limitation on AGB. Understanding how fire and herbivory contribute to AGB heterogeneity is critical to predicting future savanna carbon storage under a changing climate.

  6. Topo-edaphic controls over woody plant biomass in South African savannas

    NASA Astrophysics Data System (ADS)

    Colgan, M. S.; Asner, G. P.; Levick, S. R.; Martin, R. E.; Chadwick, O. A.

    2012-01-01

    The distribution of woody biomass in savannas reflects spatial patterns fundamental to ecosystem processes, such as water flow, competition, and herbivory, and is a key contributor to savanna ecosystem services, such as fuelwood supply. While total precipitation sets an upper bound on savanna woody biomass, the extent to which substrate and terrain constrain trees and shrubs below this maximum remains poorly understood, often occluded by local-scale disturbances such as fire and trampling. Here we investigate the role of hillslope topography and soil properties in controlling woody plant aboveground biomass (AGB) in Kruger National Park, South Africa. Large-area sampling with airborne Light Detection and Ranging (LiDAR) provided a means to average across local-scale disturbances, revealing an unexpectedly linear relationship between AGB and hillslope-position on basalts, where biomass levels were lowest on crests, and linearly increased toward streams (R2 = 0.91). The observed pattern was different on granite substrates, where AGB exhibited a strongly non-linear relationship with hillslope position: AGB was high on crests, decreased midslope, and then increased near stream channels (R2 = 0.87). Overall, we observed 5-to-8-fold lower AGB on clayey, basalt-derived soil than on granites, and we suggest this is due to herbivore-fire interactions rather than lower hydraulic conductivity or clay shrinkage/swelling, as previously hypothesized. By mapping AGB within and outside fire and herbivore exclosures, we found that basalt-derived soils support tenfold higher AGB in the absence of fire and herbivory, suggesting high clay content alone is not a~proximal limitation on AGB. Understanding how fire and herbivory contribute to AGB heterogeneity is critical to predicting future savanna carbon storage under a changing climate.

  7. Belowground plant biomass allocation in tundra ecosystems and its relationship with temperature

    NASA Astrophysics Data System (ADS)

    Wang, Peng; Heijmans, Monique M. P. D.; Mommer, Liesje; van Ruijven, Jasper; Maximov, Trofim C.; Berendse, Frank

    2016-05-01

    Climate warming is known to increase the aboveground productivity of tundra ecosystems. Recently, belowground biomass is receiving more attention, but the effects of climate warming on belowground productivity remain unclear. Enhanced understanding of the belowground component of the tundra is important in the context of climate warming, since most carbon is sequestered belowground in these ecosystems. In this study we synthesized published tundra belowground biomass data from 36 field studies spanning a mean annual temperature (MAT) gradient from ‑20 °C to 0 °C across the tundra biome, and determined the relationships between different plant biomass pools and MAT. Our results show that the plant community biomass–temperature relationships are significantly different between above and belowground. Aboveground biomass clearly increased with MAT, whereas total belowground biomass and fine root biomass did not show a significant increase over the broad MAT gradient. Our results suggest that biomass allocation of tundra vegetation shifts towards aboveground in warmer conditions, which could impact on the carbon cycling in tundra ecosystems through altered litter input and distribution in the soil, as well as possible changes in root turnover.

  8. Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

    PubMed Central

    Goetz, Scott J; Baccini, Alessandro; Laporte, Nadine T; Johns, Tracy; Walker, Wayne; Kellndorfer, Josef; Houghton, Richard A; Sun, Mindy

    2009-01-01

    Mapping and monitoring carbon stocks in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions, and are now included in climate change negotiations. We review the potential for satellites to measure carbon stocks, specifically aboveground biomass (AGB), and provide an overview of a range of approaches that have been developed and used to map AGB across a diverse set of conditions and geographic areas. We provide a summary of types of remote sensing measurements relevant to mapping AGB, and assess the relative merits and limitations of each. We then provide an overview of traditional techniques of mapping AGB based on ascribing field measurements to vegetation or land cover type classes, and describe the merits and limitations of those relative to recent data mining algorithms used in the context of an approach based on direct utilization of remote sensing measurements, whether optical or lidar reflectance, or radar backscatter. We conclude that while satellite remote sensing has often been discounted as inadequate for the task, attempts to map AGB without satellite imagery are insufficient. Moreover, the direct remote sensing approach provided more coherent maps of AGB relative to traditional approaches. We demonstrate this with a case study focused on continental Africa and discuss the work in the context of reducing uncertainty for carbon monitoring and markets. PMID:19320965

  9. Aboveground and belowground responses to nutrient additions and herbivore exclusion in Arctic tundra ecosystems in northern Alaska

    NASA Astrophysics Data System (ADS)

    Moore, J. C.; Gough, L.; Simpson, R.; Johnson, D. R.

    2011-12-01

    The Arctic has experienced significant increased regional warming over the past 30 years. Warming generally increases tundra soil nutrient availability by creating a more favorable environment for plant growth, decomposition and nutrient mineralization. Aboveground there has been a "greening" of the Arctic with increased net primary productivity (NPP), and an increase in woody vegetation. Concurrent with the changes aboveground has been an increase in root growth at lower depths and a loss of soil organic C (40 -100 g C m-2 yr-1). Given that arctic soils contain 14% of the global soil C pool, understanding the mechanisms behind shifts of this magnitude that are changing arctic soils from a net sink to a net source of atmospheric C is critical. We took an integrated multi-trophic level approach to examine how altering soil nutrients and mammalian herbivore activity affects vegetation, soil fauna, and microbial communities as well as soil physical characteristics in moist acidic (MAT) and dry heath (DH) tundra. Our work was conducted at the Arctic LTER site in northern Alaska. We sampled the nutrient (controls and annual N+P additions) and herbivore (controls and exclosures) manipulations established in 1996 after 10 years of treatment. Models that incorporated the biomass estimates from the field were used to characterize the trophic structure of the belowground food web and to estimate carbon flux among soil organisms and C-mineralization rates. Both MAT and DH exhibited significant increases in NPP and root growth and changes in vegetation structure with transitions from a mixed community to deciduous shrubs in MAT and from lichens to grasses and shrubs in DH, with nutrient additions and herbivore exclosures. Belowground responses to the treatments were dependent on ecosystem type, but exposed alterations in trophic structure that included changes in microbial biomass, the establishment of microbivorous enchytreaids, increases in root-feeding nematodes, and

  10. Root biomass and soil δ13C in C3 and C4 grasslands along a precipitation gradient

    NASA Astrophysics Data System (ADS)

    Pau, S.; Angelo, C. L.

    2014-12-01

    Many studies have investigated the distribution of C3 and C4 grasses along climatic gradients because they illustrate complex interactions between abiotic and biotic controls on ecosystem functions. Yet few studies have examined belowground components of these distributions, which may present very different patterns compared to aboveground measures. In this study, we surveyed grass species cover and collected soil and root samples from field plots at 100 - 150 m elevation intervals along a climatic gradient in Hawai'i. We examined how the relationship between soil carbon isotopic composition (δ13C), a proxy for C4 productivity and dominance, and % C4 cover changed along a climatic gradient. Results showed that δ13C underpredicted C4 dominance in wetter sites. Indeed, the relationship between % C4 cover and soil δ13C became more negative with increasing mean annual precipitation (MAP) based on a linear mixed-effects model (F 1,34 = 12.25, P < 0.01). Soil δ13C in wetter sites indicated a larger C3 contribution than estimated by aboveground cover, which was in part due to C3 root biomass increasing (P < 0.05) whereas C4 root biomass did not change along the precipitation gradient. C3 and C4 grasses appear to allocate disproportionately belowground, thus a different understanding of C4 ecological dominance may emerge when considering both above and belowground components. Our results show that belowground allocation and interpretation of soil δ13C need to be more carefully considered in global vegetation and carbon models and paleoecological reconstructions of C4 dominance.

  11. 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

  12. LANDSAT-4 Science Characterization Early Results. Volume 4: Applications. [agriculture, soils land use, geology, hydrology, wetlands, water quality, biomass identification, and snow mapping

    NASA Technical Reports Server (NTRS)

    Barker, J. L. (Editor)

    1985-01-01

    The excellent quality of TM data allows researchers to proceed directly with applications analyses, without spending a significant amount of time applying various corrections to the data. The early results derived of TM data are discussed for the following applications: agriculture, land cover/land use, soils, geology, hydrology, wetlands biomass, water quality, and snow.

  13. Dynamics of aboveground carbon stocks in a selectively logged tropical forest.

    PubMed

    Blanc, Lilian; Echard, Marion; Herault, Bruno; Bonal, Damien; Marcon, Eric; Chave, Jérôme; Baraloto, Christopher

    2009-09-01

    The expansion of selective logging in tropical forests may be an important source of global carbon emissions. However, the effects of logging practices on the carbon cycle have never been quantified over long periods of time. We followed the fate of more than 60 000 tropical trees over 23 years to assess changes in aboveground carbon stocks in 48 1.56-ha plots in French Guiana that represent a gradient of timber harvest intensities, with and without intensive timber stand improvement (TSI) treatments to stimulate timber tree growth. Conventional selective logging led to emissions equivalent to more than a third of aboveground carbon stocks in plots without TSI (85 Mg C/ha), while plots with TSI lost more than one-half of aboveground carbon stocks (142 Mg C/ha). Within 20 years of logging, plots without TSI sequestered aboveground carbon equivalent to more than 80% of aboveground carbon lost to logging (-70.7 Mg C/ha), and our simulations predicted an equilibrium aboveground carbon balance within 45 years of logging. In contrast, plots with intensive TSI are predicted to require more than 100 years to sequester aboveground carbon lost to emissions. These results indicate that in some tropical forests aboveground carbon storage can be recovered within half a century after conventional logging at moderate harvest intensities. PMID:19769089

  14. Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps.

    PubMed

    Kimball, J. S.; Keyser, A. R.; Running, S. W.; Saatchi, S. S.

    2000-06-01

    An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km(2) portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994-1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (+/- 0.6), 1.8 (+/- 0.5) and 1.7 (+/- 0.5) Mg C ha(-1) year(-1) for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances. PMID:12651512

  15. A SPATIAL ANALYSIS OF THE FINE ROOT BIOMASS FROM STAND DATA IN THE PACIFIC NORTHWEST

    EPA Science Inventory

    High spatial variability of fine roots in natural forest stands makes accurate estimates of stand-level fine root biomass difficult and expensive to obtain by standard coring methods. This study uses aboveground tree metrics and spatial relationships to improve core-based estima...

  16. Influence of Prescribed Fire on Ecosystem Biomass, Carbon, and Nitrogen in a Pinyon Juniper Woodland

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Pinyon and juniper woodland encroachment associated with climate change and land use history in the Great Basin is thought to provide offsets for carbon emissions. However, the largest pools of carbon in arid landscapes are typically found in soils, and aboveground biomass cannot be considered long ...

  17. 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.

  18. 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.

  19. Climate, Plant Biomass, NDVI, and LAI Relationships Along The Full Arctic Bioclimate Gradient

    NASA Astrophysics Data System (ADS)

    Epstein, H. E.; Walker, D. A.; Jia, G. J.; Kelley, A. M.

    2005-12-01

    A common methodology for assessing the potential effects of terrestrial ecosystems to environmental change is to develop present-day spatial relationships between environmental variables and ecosystem properties. Spatial relationships between climate variables and ecosystem variables should of course be used cautiously when extrapolating these patterns over time, i.e. space-for-time substitutions. Nevertheless, this approach has been extremely useful along regional climate gradients, in addition to providing support for vegetation dynamics models. We are developing several datasets of latitude, temperature, aboveground plant biomass, the NDVI (normalized difference vegetation index) and LAI (leaf area index) for arctic tundra ecosystems along an 1800-km transect from the Low Arctic tundra in northern Alaska to the Polar Desert of the northern Canadian Archipelago. Another useful application of these data is the relationships between NDVI and aboveground plant biomass, which can allow for the conversion of satellite data to on-the-ground ecosystem properties. For the portion of our transect on the northern slope of Alaska, NDVI (from NOAA AVHRR data) decreased with increasing latitude, explaining 45% of the variance in LAI, 65% of aboveground biomass and 42% of shrub biomass. Along the same portion of the transect, LAI (measured from above the mosses and lichens) explained 69% of vascular plant biomass and 68% of shrub biomass. For the higher arctic portion of the transect, NDVI (measured using a handheld spectroradiometer) continued to decrease with latitude, and latitude explained 90% of the variation in NDVI. For these sites in the High Arctic, NDVI was most strongly related to the sum of moss and graminoid biomass (r2=0.60). Ultimately, our dataset will contain climate data, satellite NDVI, handheld NDVI, LAI, and various components of aboveground plant biomass for a complete synthesis along the full arctic bioclimate gradient.

  20. 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

  1. Biomass Burning

    NASA Technical Reports Server (NTRS)

    Levine, Joel S.; Cofer, Wesley R., III; Pinto, Joseph P.

    1993-01-01

    Biomass burning may be the overwhelming regional or continental-scale source of methane (CH4) as in tropical Africa and a significant global source of CH4. Our best estimate of present methane emissions from biomass burning is about 51.9 Tg/yr, or 10% of the annual methane emissions to the atmosphere. Increased frequency of fires that may result as the Earth warms up may result in increases in this source of atmospheric methane.

  2. Creating a Multi-Proxy Based Estimate of Regional Carbon Stocks from Ground-Based Biomass Measurements and Remotely Sensed Imagery

    NASA Astrophysics Data System (ADS)

    Kelsey, K.; Neff, J. C.

    2013-12-01

    Forest carbon storage and flux are rapidly changing in many parts of the world due to agents including wildfire, insect outbreaks, forest thinning and timber harvest. Quantifying changes in forest carbon storage requires characterizing the distribution of forest biomass across heterogeneous landscapes at finely resolved spatial and temporal scales. Here, we integrate information from multiple remote sensing platforms with US Forest Service ground-based biomass measurements to form a multi-proxy based estimate of forest carbon stocks and associated uncertainty in two vegetation types on San Juan National Forest, Colorado. We take advantage of US Forest Service Common Stand Exam plots that have been sampled for vegetation and biomass information in conjunction with forest management actions from the 1950's to the present. Due to their number and wide spatial distribution, Common Stand Exam data present an underutilized source of information for mapping vegetation and quantifying biomass on federal lands. Using information from 3188 Common Stand Exam plots within Ponderosa Pine and Spruce Fir vegetation types, we characterize aboveground carbon stocks using four methods: (1) simple extrapolation using regression tree approaches; (2) geostatistical interpolation (kriging); (3) regressions between biomass and vegetation indices derived from Landsat and MODIS imagery; (4) interfacing other biomass estimation methods with texture analysis preformed on one meter resolution areal imagery from the National Agriculture Imagery Program. Results from the different approaches generate a wide range of forest carbon estimates; however, combinations of information from ground-based measurements and remotely sensed images appear to yield the best estimate of forest carbon stocks in this region. A comparison of this relatively high resolution (0.1 to 1 km) analysis to larger scale estimates highlights the importance of regional information and high resolution data for constraining

  3. Biomass of Secondary Evergreen and Deciduous Broadleaved Mixed Forest in Plateau-type Karst Terrain of Guizhou Province, SW China

    NASA Astrophysics Data System (ADS)

    Liu, L.

    2014-12-01

    Using allometric functions, harvest and soil column methods, we investigated the biomass of a secondary evergreen and deciduous broadleaved mixed forest in Tianlongshan permanent monitoring plot (a horizontally-projected area of 2 hectares) of Puding Karst Ecosystem Research Station, Guizhou Province, southwestern China. Results showed that the total biomass of the forest is 165.4 Mg·hm-2. The aboveground biomass and root biomass are 137.7 Mg·hm-2 and 27.7 Mg·hm-2, respectively. Among the aboveground biomass, the tree layer accounts for 97.76%, which is obviously greater than the shrub layer and herb layer. Larger trees (the diameter at breast height, DBH is between 5 cm and 20 cm) occupies 76.85% of the aboveground biomass, especially the five dominant species(Lithocarpus confinis, Platycarya longipes, Itea yunnanensis, Machilus cavaleriei and Carpinus pubescens). Shrubs and lianas (DBH = 1 cm) account for more than 30% of total shrub and liana biomass, although their individuals are less than 2% of total shrub individuals and 1% of total liana individuals, respectively. The root biomass differs in root diameters, i.e. coarse root > medium root > fine root. Root biomass decreases with the increase of soil depth. Within soil depth of 20 cm, the root biomass is 20.1 Mg·hm-2, which is more than 70% of total root biomass. Within soil depth of 50 cm, the root biomass is 26.7 Mg·hm-2, which is 96.39% of total root biomass. Compared with non-karst forests in the same climate zone, karst forest has lower biomass and carbon stock, but it further has greater potential of carbon sink.

  4. 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.

  5. Intra-annual changes in biomass, carbon, and nitrogen dynamics at 4-year old switchgrass field trials in West Tennessee, USA

    SciTech Connect

    Garten, Jr, C. T.; Smith, Jeffery L.; Tyler, Donald D.; Amonette, James E.; Bailey, Vanessa L.; Brice, D. J.; Castro, H. F.; Graham, Robin L.; Gunderson, C. A.; Izaurralde, Roberto C.; Jardine, Philip M.; Jastrow, J. D.; Kerley, M. K.; Matamala, R.; Mayes, M. A.; Metting, F. B.; Miller, R. M.; Moran, K. K.; Post, W. M.; Sands, Ronald D.; Schadt, Christopher W.; Phillips, J. R.; Thomson, Allison M.; Vugteveen, T.; West, T. O.; Wullschleger, Stan D.

    2010-02-15

    Switchgrass is a potential bioenergy crop that could promote soil C sequestration in some environments. We compared four cultivars on a well-drained Alfisol to test for differences in biomass, C, and N dynamics during the fourth growing season. There was no difference (P > 0.05) among cultivars and no significant cultivar x time interaction in analyses of dry mass, C stocks, or N stocks in aboveground biomass and surface litter. At the end of the growing season, mean (±SE) aboveground biomass was 2.1±0.13 kg m-2, and surface litter dry mass was approximately 50% of aboveground biomass. Prior to harvest, the live root:shoot biomass ratio was 0.76. There was no difference (P > 0.05) among cultivars for total biomass, C, and N stocks belowground. Total belowground biomass (90-cm soil depth) as well as coarse (greater than or equal to 1 mm diameter) and fine (< 1 mm diameter) live root biomass increased from April to October. Dead roots were less than 7% of live root biomass to a depth of 90 cm. Net production of total belowground biomass (505 ±132 g m-2) occurred in the last half of the growing season. The increase in total live belowground biomass (426 ±139 g m-2) was more or less evenly divided among rhizomes, coarse, and fine roots. The N budget for annual switchgrass production was closely balanced with 6.3 g N m-2 removed by harvest of aboveground biomass and 6.7 g N m-2 supplied by fertilization. At the location of our study in west Tennessee, intra-annual changes in biomass, C, and N stocks belowground were of greater importance to crop management for C sequestration than were differences among cultivars.

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

    PubMed

    Babst, Flurin; Bouriaud, Olivier; Papale, Dario; Gielen, Bert; Janssens, Ivan A; Nikinmaa, Eero; Ibrom, Andreas; Wu, Jian; Bernhofer, Christian; Köstner, Barbara; Grünwald, Thomas; Seufert, Günther; Ciais, Philippe; Frank, David

    2014-03-01

    • Attempts to combine biometric and eddy-covariance (EC) quantifications of carbon allocation to different storage pools in forests have been inconsistent and variably successful in the past. • We assessed above-ground biomass changes at five long-term EC forest stations based on tree-ring width and wood density measurements, together with multiple allometric models. Measurements were validated with site-specific biomass estimates and compared with the sum of monthly CO₂ fluxes between 1997 and 2009. • Biometric measurements and seasonal net ecosystem productivity (NEP) proved largely compatible and suggested that carbon sequestered between January and July is mainly used for volume increase, whereas that taken up between August and September supports a combination of cell wall thickening and storage. The inter-annual variability in above-ground woody carbon uptake was significantly linked with wood production at the sites, ranging between 110 and 370 g C m(-2) yr(-1) , thereby accounting for 10-25% of gross primary productivity (GPP), 15-32% of terrestrial ecosystem respiration (TER) and 25-80% of NEP. • The observed seasonal partitioning of carbon used to support different wood formation processes refines our knowledge on the dynamics and magnitude of carbon allocation in forests across the major European climatic zones. It may thus contribute, for example, to improved vegetation model parameterization and provides an enhanced framework to link tree-ring parameters with EC measurements. PMID:24206564

  7. Airport, air base benefit from switch to aboveground tanks

    SciTech Connect

    1995-10-01

    The Environmental Protection Agency requires that by the end of 1998 all underground fuel tanks must comply with requirements established for tanks installed after Dec. 22, 1988. To comply with federal and state regulations, authorities at Mansfield (Mass.) Municipal Airport decided during a recent reconstruction effort to replace several 46-year-old underground fuel tanks with an 8,000-gallon, aboveground tank. After researching several types of tanks and weighing recommendations from the airport`s fueling company, officials chose to install a lightweight, double-walled tank from Aero-Power Unitized Fueler Inc., Smithtown, NY. The Fireguard{trademark} tank has a concrete-insulated lining between its two walls that can absorb aviation fuel in case of a pool fire. An outer steel wall provides secondary containment, protecting the insulating material, and resists cracking and spalling. Dobbins Air Reserve Base in Georgia recently installed two 2,000-gallon Fireguard tanks to contain diesel and unleaded fuel for a new military-vehicle refueling station.

  8. [Dry matter accumulation in rice aboveground part: quantitative simulation].

    PubMed

    Li, Yan-Da; Tang, Liang; Chen, Qing-Chun; Zhang, Yu-Ping; Cao, Wei-Xing; Zhu, Yan

    2010-06-01

    A field experiment with four rice (Oryza sativa L.) cultivars and different nitrogen application rates was conducted, with the dry matter accumulation (DMA) in the cultivars aboveground part measured at their main growth stages. The dynamic model of relative dry matter accumulation (RDMA) was established with the normalized DMA and TEP (product of thermal effectiveness and PAR) from emergence to maturity, and the temporal characteristics of DMA changes was quantitatively analyzed based on the RDMA model. The dynamic changes of the RDMA could be well described with Richards equation, i. e., RDMA = 1.0157/(1 +e(3.6329-7.5907xRTEP)) 1/0.5574 (r = 0.9938). The model was validated with independent field experiment datasets, involving different eco-sites, cultivars, and nitrogen application rates. The RMSE (root mean square error) between the simulated and observed values of DMA at varied RTEP was 0.86 t x hm(-2). According to the two inflexion points of dry matter accumulation rate equation, the whole process of dry matter accumulation could be divided into early, middle, and late phases. The maximum dry matter accumulation rate (AR(max)), relative TEP at AR(max), and relative dry matter accumulation at AR(max) were found to be 2.24, 0.56, and 0.46, respectively. PMID:20873627

  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. Biomass energy

    SciTech Connect

    Smil, V.

    1983-01-01

    This book offers a broad, interdisciplinary approach to assessing the factors that are key determinants to the use of biomass energies, stressing their limitations, complexities, uncertainties, links, and consequences. Considers photosynthesis, energy costs of nutrients, problems with monoculture, and the energy analysis of intensive tree plantations. Subjects are examined in terms of environmental and economic impact. Emphasizes the use and abuse of biomass energies in China, India, and Brazil. Topics include forests, trees for energy, crop residues, fuel crops, aquatic plants, and animal and human wastes. Recommended for environmental engineers and planners, and those involved in ecology, systematics, and forestry.

  11. Linking Topographic, Hydrologic, Climatic, and Ecologic Processes in Semi-arid Forests: an investigation of aboveground growth dynamics

    NASA Astrophysics Data System (ADS)

    Adams, H. R.; Loomis, A. K.; Barnard, H. R.

    2013-12-01

    Topography and climate play an integral role in the spatial variability and annual dynamics of aboveground carbon sequestration. Topographic, climatic, and hydrologic dynamics of a catchment interact to drive vegetation spatial distribution, growth patterns, and physiological processes in the catchment. Despite previous knowledge concerning gradient-theory influences on vegetation spatial distribution, little is known about the specific influence of complex terrain coupled with hydrologic and topo-climatic variation on aboveground biomass, especially in semi-arid forests of the Rocky Mountains. Climate change predictions for the semi-arid west, however, include increased temperatures, more frequent and extreme drought events, and decreases in snow pack all of which put forests at risk of altered species ranges and physiological processes, and susceptibility to disturbance events. In this study, we determine how species-specific tree growth patterns and water use efficiency respond to interannual variability in moisture availability (drought) through the use of dendrochronology techniques and carbon isotopes as a measure of water use efficiency with regard to topography and climate through data collection at 75 forest plots. Preliminary results suggest that tree growth and physiological processes respond directly to topographic and climatic parameters including aspect, elevation, and drought events (p < .05) and species vary in their response to these parameters (p < .05). Carbon isotope analyses indicate no significant difference appears in the water use efficiency of ponderosa pine between a drought year and a non-drought year while lodgepole pine water use efficiency increases significantly in a drought year. Both species, however, experience decreases in growth in drought years (p < .05) and, while aspect is a significant predictor of lodgepole pine tree growth in a wet year (p < .05), it becomes insignificant in a dry year. Varying responses from different

  12. Aboveground and belowground legacies of native Sami land use on boreal forest in northern Sweden 100 years after abandonment.

    PubMed

    Freschet, Grégoire T; Ostlund, Lars; Kichenin, Emilie; Wardle, David A

    2014-04-01

    Human activities that involve land-use change often cause major transformations to community and ecosystem properties both aboveground and belowground, and when land use is abandoned, these modifications can persist for extended periods. However, the mechanisms responsible for rapid recovery vs. long-term maintenance of ecosystem changes following abandonment remain poorly understood. Here, we examined the long-term ecological effects of two remote former settlements, regularly visited for -300 years by reindeer-herding Sami and abandoned -100 years ago, within an old-growth boreal forest that is considered one of the most pristine regions in northern Scandinavia. These human legacies were assessed through measurements of abiotic and biotic soil properties and vegetation characteristics at the settlement sites and at varying distances from them. Low-intensity land use by Sami is characterized by the transfer of organic matter towards the settlements by humans and reindeer herds, compaction of soil through trampling, disappearance of understory vegetation, and selective cutting of pine trees for fuel and construction. As a consequence, we found a shift towards early successional plant species and a threefold increase in soil microbial activity and nutrient availability close to the settlements relative to away from them. These changes in soil fertility and vegetation contributed to 83% greater total vegetation productivity, 35% greater plant biomass, and 23% and 16% greater concentrations of foliar N and P nearer the settlements, leading to a greater quantity and quality of litter inputs. Because decomposer activity was also 40% greater towards the settlements, soil organic matter cycling and nutrient availability were further increased, leading to likely positive feedbacks between the aboveground and belowground components resulting from historic land use. Although not all of the activities typical of Sami have left visible residual traces on the ecosystem after

  13. 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.

  14. TECHNICAL BASIS REPORT FOR LARGE FIRE ACCIDENTS INVOLVING ABOVEGROUND TANKS & VESSELS

    SciTech Connect

    MARCHESE, A.R.

    2005-03-03

    This document analyzes large fire accidents involving aboveground tanks and vessels during Demonstration Bulk Vitrification System (DBVS) operations. The fire accident scenarios are consistent with RPP-22461,''Preliminary Fire Hazard Analysis (PFHA) for DBVS''. The radiological and toxicological consequences are determined for a wide spectrum of fire sizes to bracket the range of possible consequences resulting from large fires involving aboveground tanks/vessels that are part of DBVS.

  15. Biotechnology of biomass conversion

    SciTech Connect

    Wayman, M.; Parekh, S.R.

    1990-01-01

    This book covers: An introduction to biomass crops; The microbiology of fermentation processes; The production of ethanol from biomass crops, such as sugar cane and rubbers; The energy of biomass conversion; and The economics of biomass conversion.

  16. High-resolution mapping of biogenic carbon fluxes to improve urban CO2 monitoring, reporting, and verification

    NASA Astrophysics Data System (ADS)

    Hardiman, B. S.; Hutyra, L.; Gately, C.; Raciti, S. M.

    2014-12-01

    Urban areas are home to 80% of the US population and 70% of energy related fossil fuel emissions originate from urban areas. Efforts to accurately monitor, report, and verify anthropogenic CO2 missions using atmospheric measurements require reliable partitioning of anthropogenic and biogenic sources. Anthropogenic emissions peak during the daytime, coincident with biogenic drawdown of CO2. In contrast, biogenic respiration emissions peak at night when anthropogenic emissions are lower. This temporal aliasing of fluxes requires careful modeling of both biogenic and anthropogenic fluxes for accurate source attribution through inverse modeling. Biogenic fluxes in urban regions can be a significant component of the urban carbon cycle. However, vegetation in urban areas is subject to longer growing seasons, reduced competition, higher rates of nitrogen deposition, and altered patterns of biomass inputs, all interacting to elevate C turnover rates relative to analogous non-urban ecosystems. These conditions suggest that models that ignore urban vegetation or base biogenic flux estimates on non-urban forests are likely to produce inaccurate estimates of anthropogenic CO2 emissions. Biosphere models often omit biogenic fluxes in urban areas despite potentially extensive vegetation coverage. For example, in Massachusetts, models mask out as much as 40% of land area, effectively assuming they have no biological flux. This results in a ~32% underestimate of aboveground biomass (AGB) across the state as compared to higher resolution vegetation maps. Our analysis suggests that some common biomass maps may underestimate forest biomass by ~520 Tg C within the state of Massachusetts. Moreover, omitted portions of the state have the highest population density, indicating that we know least about regions where most people live. We combine remote sensing imagery of urban vegetation cover with ground surveys of tree growth and mortality to improve estimates of aboveground biomass and

  17. Genetic variation in biomass traits among 20 diverse rice varieties.

    PubMed

    Jahn, Courtney E; Mckay, John K; Mauleon, Ramil; Stephens, Janice; McNally, Kenneth L; Bush, Daniel R; Leung, Hei; Leach, Jan E

    2011-01-01

    Biofuels provide a promising route of producing energy while reducing reliance on petroleum. Developing sustainable liquid fuel production from cellulosic feedstock is a major challenge and will require significant breeding efforts to maximize plant biomass production. Our approach to elucidating genes and genetic pathways that can be targeted for improving biomass production is to exploit the combination of genomic tools and genetic diversity in rice (Oryza sativa). In this study, we analyzed a diverse set of 20 recently resequenced rice varieties for variation in biomass traits at several different developmental stages. The traits included plant size and architecture, aboveground biomass, and underlying physiological processes. We found significant genetic variation among the 20 lines in all morphological and physiological traits. Although heritability estimates were significant for all traits, heritabilities were higher in traits relating to plant size and architecture than for physiological traits. Trait variation was largely explained by variety and breeding history (advanced versus landrace) but not by varietal groupings (indica, japonica, and aus). In the context of cellulosic biofuels development, cell wall composition varied significantly among varieties. Surprisingly, photosynthetic rates among the varieties were inversely correlated with biomass accumulation. Examining these data in an evolutionary context reveals that rice varieties have achieved high biomass production via independent developmental and physiological pathways, suggesting that there are multiple targets for biomass improvement. Future efforts to identify loci and networks underlying this functional variation will facilitate the improvement of biomass traits in other grasses being developed as energy crops. PMID:21062890

  18. Detecting tropical forest biomass dynamics from repeated airborne Lidar measurements

    NASA Astrophysics Data System (ADS)

    Meyer, V.; Saatchi, S. S.; Chave, J.; Dalling, J.; Bohlman, S.; Fricker, G. A.; Robinson, C.; Neumann, M.

    2013-02-01

    Reducing uncertainty of terrestrial carbon cycle depends strongly on the accurate estimation of changes of global forest carbon stock. However, this is a challenging problem from either ground surveys or remote sensing techniques in tropical forests. Here, we examine the feasibility of estimating changes of tropical forest biomass from two airborne Lidar measurements acquired about 10 yr apart over Barro Colorado Island (BCI), Panama from high and medium resolution airborne sensors. The estimation is calibrated with the forest inventory data over 50 ha that was surveyed every 5 yr during the study period. We estimated the aboveground forest biomass and its uncertainty for each time period at different spatial scales (0.04, 0.25, 1.0 ha) and developed a linear regression model between four Lidar height metrics and the aboveground biomass. The uncertainty associated with estimating biomass changes from both ground and Lidar data was quantified by propagating measurement and prediction errors across spatial scales. Errors associated with both the mean biomass stock and mean biomass change declined with increasing spatial scales. Biomass changes derived from Lidar and ground estimates were largely (36 out 50 plots) in the same direction at the spatial scale of 1 ha. Lidar estimation of biomass was accurate at the 1 ha scale (R2 = 0.7 and RMSEmean = 28.6 Mg ha-1). However, to predict biomass changes, errors became comparable to ground estimates only at about 10-ha or more. Our results indicate that the 50-ha BCI plot lost a~significant amount of biomass (-0.8 ± 2.2 Mg ha-1 yr-1) over the past decade (2000-2010). Over the entire island and during the same period, mean AGB change is -0.4 ± 3.7 Mg ha-1 yr-1. Old growth forests lost biomass (-0.7 ± 3.5 Mg ha-1 yr-1), whereas the secondary forests gained biomass (+0.4 ± 3.4 Mg ha-1 yr-1). Our analysis demonstrates that repeated Lidar surveys, even with two different sensors, is able to estimate biomass changes in old

  19. Biomass shock pretreatment

    DOEpatents

    Holtzapple, Mark T.; Madison, Maxine Jones; Ramirez, Rocio Sierra; Deimund, Mark A.; Falls, Matthew; Dunkelman, John J.

    2014-07-01

    Methods and apparatus for treating biomass that may include introducing a biomass to a chamber; exposing the biomass in the chamber to a shock event to produce a shocked biomass; and transferring the shocked biomass from the chamber. In some aspects, the method may include pretreating the biomass with a chemical before introducing the biomass to the chamber and/or after transferring shocked biomass from the chamber.

  20. Utilizing national agriculture imagery program data to estimate tree cover and biomass of pinyon and juniper woodlands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With the encroachment of pinyon (Pinus ssp.) and juniper (Juniperus ssp.) (P-J) woodlands into sagebrush steppe communities, there is an increasing interest in rapid, accurate, and inexpensive quantification methods to estimate tree canopy cover and aboveground biomass over large landscapes. The o...

  1. Hand-held spectral radiometer to estimate gramineous biomass. [with interfaced pocket calculator solution

    NASA Technical Reports Server (NTRS)

    Pearson, R. L.; Miller, L. D.; Tucker, C. J.

    1976-01-01

    A simple hand-held instrument has been designed and constructed to nondestructively estimate above-ground gramineous biomass using radiometric measurements. The prototype unit consists of a modified two-channel digital radiometer interfaced to a pocket calculator. A digital interface was constructed to join electronically and control the radiometer and calculator to enable the radiometer-calculator system to solve a linear conversion solution from radiometric units to estimated biomass. This instrument has been used to estimate radiometrically gramineous biomass in a more efficient fashion with a high degree of accuracy.

  2. Benchmark map of forest carbon stocks in tropical regions across three continents

    PubMed Central

    Saatchi, Sassan S.; Harris, Nancy L.; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T. A.; Salas, William; Zutta, Brian R.; Buermann, Wolfgang; Lewis, Simon L.; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

    2011-01-01

    Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a “benchmark” map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ±6% to ±53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ±5% and ca. ±1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete. PMID:21628575

  3. Benchmark map of forest carbon stocks in tropical regions across three continents.

    PubMed

    Saatchi, Sassan S; Harris, Nancy L; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T A; Salas, William; Zutta, Brian R; Buermann, Wolfgang; Lewis, Simon L; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

    2011-06-14

    Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a "benchmark" map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ± 6% to ± 53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ± 5% and ca. ± 1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete. PMID:21628575

  4. Variability of above-ground litter inputs alters soil physicochemical and biological processes: a meta-analysis of litterfall-manipulation experiments

    NASA Astrophysics Data System (ADS)

    Xu, S.; Liu, L. L.; Sayer, E. J.

    2013-11-01

    Global change has been shown to alter the amount of above-ground litter inputs to soil greatly, which could cause substantial cascading effects on below-ground biogeochemical cycling. Despite extensive study, there is uncertainty about how changes in above-ground litter inputs affect soil carbon and nutrient turnover and transformation. Here, we conducted a meta-analysis on 70 litter-manipulation experiments in order to assess how changes in above-ground litter inputs alter soil physicochemical properties, carbon dynamics and nutrient cycles. Our results demonstrated that litter removal decreased soil respiration by 34%, microbial biomass carbon in the mineral soil by 39% and total carbon in the mineral soil by 10%, whereas litter addition increased them by 31, 26 and 10%, respectively. This suggests that greater litter inputs increase the soil carbon sink despite higher rates of carbon release and transformation. Total nitrogen and extractable inorganic nitrogen in the mineral soil decreased by 17 and 30%, respectively, under litter removal, but were not altered by litter addition. Overall, litter manipulation had a significant impact upon soil temperature and moisture, but not soil pH; litter inputs were more crucial in buffering soil temperature and moisture fluctuations in grassland than in forest. Compared to other ecosystems, tropical and subtropical forests were more sensitive to variation in litter inputs, as altered litter inputs affected the turnover and accumulation of soil carbon and nutrients more substantially over a shorter time period. Our study demonstrates that although the magnitude of responses differed greatly among ecosystems, the direction of the responses was very similar across different ecosystems. Interactions between plant productivity and below-ground biogeochemical cycling need to be taken into account to predict ecosystem responses to environmental change.

  5. Aboveground insect herbivory increases plant competitive asymmetry, while belowground herbivory mitigates the effect

    PubMed Central

    Strengbom, Joachim; Viketoft, Maria; Bommarco, Riccardo

    2016-01-01

    Insect herbivores can shift the composition of a plant community, but the mechanism underlying such shifts remains largely unexplored. A possibility is that insects alter the competitive symmetry between plant species. The effect of herbivory on competition likely depends on whether the plants are subjected to aboveground or belowground herbivory or both, and also depends on soil nitrogen levels. It is unclear how these biotic and abiotic factors interactively affect competition. In a greenhouse experiment, we measured competition between two coexisting grass species that respond differently to nitrogen deposition: Dactylis glomerata L., which is competitively favoured by nitrogen addition, and Festuca rubra L., which is competitively favoured on nitrogen-poor soils. We predicted: (1) that aboveground herbivory would reduce competitive asymmetry at high soil nitrogen by reducing the competitive advantage of D. glomerata; and (2), that belowground herbivory would relax competition at low soil nitrogen, by reducing the competitive advantage of F. rubra. Aboveground herbivory caused a 46% decrease in the competitive ability of F. rubra, and a 23% increase in that of D. glomerata, thus increasing competitive asymmetry, independently of soil nitrogen level. Belowground herbivory did not affect competitive symmetry, but the combined influence of above- and belowground herbivory was weaker than predicted from their individual effects. Belowground herbivory thus mitigated the increased competitive asymmetry caused by aboveground herbivory. D. glomerata remained competitively dominant after the cessation of aboveground herbivory, showing that the influence of herbivory continued beyond the feeding period. We showed that insect herbivory can strongly influence plant competitive interactions. In our experimental plant community, aboveground insect herbivory increased the risk of competitive exclusion of F. rubra. Belowground herbivory appeared to mitigate the influence of

  6. Aboveground insect herbivory increases plant competitive asymmetry, while belowground herbivory mitigates the effect.

    PubMed

    Borgström, Pernilla; Strengbom, Joachim; Viketoft, Maria; Bommarco, Riccardo

    2016-01-01

    Insect herbivores can shift the composition of a plant community, but the mechanism underlying such shifts remains largely unexplored. A possibility is that insects alter the competitive symmetry between plant species. The effect of herbivory on competition likely depends on whether the plants are subjected to aboveground or belowground herbivory or both, and also depends on soil nitrogen levels. It is unclear how these biotic and abiotic factors interactively affect competition. In a greenhouse experiment, we measured competition between two coexisting grass species that respond differently to nitrogen deposition: Dactylis glomerata L., which is competitively favoured by nitrogen addition, and Festuca rubra L., which is competitively favoured on nitrogen-poor soils. We predicted: (1) that aboveground herbivory would reduce competitive asymmetry at high soil nitrogen by reducing the competitive advantage of D. glomerata; and (2), that belowground herbivory would relax competition at low soil nitrogen, by reducing the competitive advantage of F. rubra. Aboveground herbivory caused a 46% decrease in the competitive ability of F. rubra, and a 23% increase in that of D. glomerata, thus increasing competitive asymmetry, independently of soil nitrogen level. Belowground herbivory did not affect competitive symmetry, but the combined influence of above- and belowground herbivory was weaker than predicted from their individual effects. Belowground herbivory thus mitigated the increased competitive asymmetry caused by aboveground herbivory. D. glomerata remained competitively dominant after the cessation of aboveground herbivory, showing that the influence of herbivory continued beyond the feeding period. We showed that insect herbivory can strongly influence plant competitive interactions. In our experimental plant community, aboveground insect herbivory increased the risk of competitive exclusion of F. rubra. Belowground herbivory appeared to mitigate the influence of

  7. Biomass Inventory Using Small Footprint Lidar: Preliminary Results in Two Maryland Counties

    NASA Astrophysics Data System (ADS)

    Suárez, J.; Nelson, R. F.; Pinto, N.; Rosette, J.; Dubayah, R.; Fatoyinbo, T. E.; Cook, B. D.

    2011-12-01

    The Carbon Monitoring System (CMS) project started in September 2010 with a mandate from the U.S. Congress to NASA (NASA, 2010). The primary goal of the project is the estimation of above-ground biomass stocks and carbon fluxes, the appraisal of error budgets and the delivery of cartographic products and other geo-referenced information for selected locations at a scale that is ecologically meaningful and relevant for forest management. The project is incrementally planning to marry carbon monitoring efforts firstly at both local and federal scale and then globally. As part of the local component of this effort, small footprint LiDAR data from archive have been analysed for two counties in Maryland. LiDAR metrics, such as the percentile distribution of heights and density deciles, were generated for each National Land Cover Database (NLCD) pixel at 30 m resolution. Field data for validation and training of models consisted of variable plot sizes with BAF 10, 20 and 30. Training of models was based on a previous stratification of woodland types into evergreen, broadleaves, mixed, wetlands and non-wooded areas. The biomass models were derived by means of empirical fits between ground-measured biomass and the LiDAR metrics generated for each stratum. The results showed coefficients of determination ranging above 0.70 for all the strata with the exception of mixed woodlands (0.48). The distribution of the residuals showed a bias for plots with largest biomass levels measured in the field, due to the unintended inclusion of boundary trees. The final results were converted into a 30m raster map showing the spatial distribution of biomass in Mg ha-1. Further research within the CMS initiative will concentrate on further validation and error analysis in addition to replicating this methodology in other monitoring areas in order to ensure this methodology is consistent and widely applicable. REFERENCE NASA, 2010. NASA Carbon Monitoring System Initiative. Available online at

  8. Seasonal availability of edible underground and aboveground carbohydrate resources to human foragers on the Cape south coast, South Africa

    PubMed Central

    Cowling, Richard M.; Potts, Alastair J.; Marean, Curtis W.

    2016-01-01

    The coastal environments of South Africa’s Cape Floristic Region (CFR) provide some of the earliest and most abundant evidence for the emergence of cognitively modern humans. In particular, the south coast of the CFR provided a uniquely diverse resource base for hunter-gatherers, which included marine shellfish, game, and carbohydrate-bearing plants, especially those with Underground Storage Organs (USOs). It has been hypothesized that these resources underpinned the continuity of human occupation in the region since the Middle Pleistocene. Very little research has been conducted on the foraging potential of carbohydrate resources in the CFR. This study focuses on the seasonal availability of plants with edible carbohydrates at six-weekly intervals over a two-year period in four vegetation types on South Africa’s Cape south coast. Different plant species were considered available to foragers if the edible carbohydrate was directly (i.e. above-ground edible portions) or indirectly (above-ground indications to below-ground edible portions) visible to an expert botanist familiar with this landscape. A total of 52 edible plant species were recorded across all vegetation types. Of these, 33 species were geophytes with edible USOs and 21 species had aboveground edible carbohydrates. Limestone Fynbos had the richest flora, followed by Strandveld, Renosterveld and lastly, Sand Fynbos. The availability of plant species differed across vegetation types and between survey years. The number of available USO species was highest for a six-month period from winter to early summer (Jul–Dec) across all vegetation types. Months of lowest species’ availability were in mid-summer to early autumn (Jan–Apr); the early winter (May–Jun) values were variable, being highest in Limestone Fynbos. However, even during the late summer carbohydrate “crunch,” 25 carbohydrate bearing species were visible across the four vegetation types. To establish a robust resource landscape

  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. Aboveground and belowground effects of single-tree removals in New Zealand rain forest.

    PubMed

    Wardle, David A; Wiser, Susan K; Allen, Robert B; Doherty, James E; Bonner, Karen I; Williamson, Wendy M

    2008-05-01

    There has been considerable recent interest in how human-induced species loss affects community and ecosystem properties. These effects are particularly apparent when a commercially valuable species is harvested from an ecosystem, such as occurs through single-tree harvesting or selective logging of desired timber species in natural forests. In New Zealand mixed-species rain forests, single-tree harvesting of the emergent gymnosperm Dacrydium cupressinum, or rimu, has been widespread. This harvesting has been contentious in part because of possible ecological impacts of Dacrydium removal on the remainder of the forest, but many of these effects remain unexplored. We identified an area where an unintended 40-year "removal experiment" had been set up that involved selective extraction of individual Dacrydium trees. We measured aboveground and belowground variables at set distances from both individual live trees and stumps of trees harvested 40 years ago. Live trees had effects both above and below ground by affecting diversity and cover of several components of the vegetation (usually negatively), promoting soil C sequestration, enhancing ratios of soil C:P and N:P, and affecting community structure of soil microflora. These effects extended to 8 m from the tree base and were likely caused by poor-quality litter and humus produced by the trees. Measurements for the stumps revealed strong legacy effects of prior presence of trees on some properties (e.g., cover by understory herbs and ferns, soil C sequestration, soil C:P and N:P ratios), but not others (e.g., soil fungal biomass, soil N concentration). These results suggest that the legacy of prior presence of Dacrydium may remain for several decades or centuries, and certainly well over 40 years. They also demonstrate that, while large Dacrydium individuals (and their removal) may have important effects in their immediate proximity, within a forest, these effects should only be important in localized patches

  11. Can recent pan-tropical biomass maps be used to derive alternative Tier 1 values for reporting REDD+ activities under UNFCCC?

    NASA Astrophysics Data System (ADS)

    Langner, Andreas; Achard, Frédéric; Grassi, Giacomo

    2014-12-01

    The IPCC Guidelines propose 3 Tier levels for greenhouse gas monitoring within the forest land category with a hierarchical order in terms of accuracy, data requirements and complexity. Due to missing data and/or capacities, many developing countries, potentially interested in the reducing emissions from deforestation and forest degradation scheme, have to rely on Tier 1 default values with highest uncertainties. A possible way to increase the credibility of uncertain estimates is to apply a conservative approach, for which standard statistical information is needed. However, such information is currently not available for the IPCC values. In our study we combine a recent global forest mask, an ecological zoning map and the pan-tropical AGB datasets of Saatchi and Baccini to derive mean forest AGB values per ecological zone and continent as well as their corresponding confidence intervals. Such analysis can be considered transparent as the datasets/methodologies are well documented. Our study leads to alternative Tier 1 values and allows the application of statistically-based conservative approaches. Our AGB estimates derived from Saatchi and Baccini datasets are 35% and 24% lower respectively than the IPCC values. When restricting the analysis to intact forest landscapes resulting ABG estimates derived from Saatchi and Baccini datasets get closer to the IPCC values with 13% and 1% differences respectively (underestimation). This suggests that the IPCC default values are mainly based on plots in mature forest stands. However, as tropical forests generally consist of a mixture of intact and degraded stands, the use of IPCC values may not properly reflect the reality. Finally, we propose to use the average composite of the Saatchi and Baccini datasets to produce improved alternative IPCC Tier 1 values. The values derived from such approach can easily be updated when newer and/or improved pan-tropical AGB maps will be available.

  12. [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

  13. Belowground ABA boosts aboveground production of DIMBOA and primes induction of chlorogenic acid in maize.

    PubMed

    Erb, Matthias; Gordon-Weeks, Ruth; Flors, Victor; Camañes, Gemma; Turlings, Ted C J; Ton, Jurriaan

    2009-07-01

    Plants are important mediators between above- and belowground herbivores. Consequently, interactions between root and shoot defenses can have far-reaching impacts on entire food webs. We recently reported that infestation of maize roots by larvae of the beetle Diabrotica virgifera virgifera induced shoot resistance against herbivores and pathogens. Root herbivory also enhanced aboveground DIMBOA and primed for enhanced induction of chlorogenic acid, two secondary metabolites that have been associated with plant stress resistance. Interestingly, the plant hormone abscisic acid (ABA) emerged as a putative long-distance signal in the regulation of these systemic defenses. In this addendum, we have investigated the role of root-derived ABA in aboveground regulation of DIMBOA and the phenolic compounds chlorogenic acid, caffeic and ferulic acid. Furthermore, we discuss the relevance of ABA in relation to defense against the leaf herbivore Spodoptera littoralis. Soil-drench treatment with ABA mimicked root herbivore-induced accumulation of DIMBOA in the leaves. Similarly, ABA mimicked aboveground priming of chlorogenic acid production, causing augmented induction of this compound after subsequent shoot attack by S. littoralis caterpillars. These findings confirm our notion that ABA acts as an important signal in the regulation of aboveground defenses during belowground herbivory. However, based on our previous finding that ABA alone is not sufficient to trigger aboveground resistance against S. littoralis caterpillars, our results also suggest that the ABA-inducible effects on DIMBOA and chlorogenic acid are not solely responsible for root herbivore-induced resistance against S. littoralis. PMID:19820311

  14. Biomass energy: the scale of the potential resource.

    PubMed

    Field, Christopher B; Campbell, J Elliott; Lobell, David B

    2008-02-01

    Increased production of biomass for energy has the potential to offset substantial use of fossil fuels, but it also has the potential to threaten conservation areas, pollute water resources and decrease food security. The net effect of biomass energy agriculture on climate could be either cooling or warming, depending on the crop, the technology for converting biomass into useable energy, and the difference in carbon stocks and reflectance of solar radiation between the biomass crop and the pre-existing vegetation. The area with the greatest potential for yielding biomass energy that reduces net warming and avoids competition with food production is land that was previously used for agriculture or pasture but that has been abandoned and not converted to forest or urban areas. At the global scale, potential above-ground plant growth on these abandoned lands has an energy content representing approximately 5% of world primary energy consumption in 2006. The global potential for biomass energy production is large in absolute terms, but it is not enough to replace more than a few percent of current fossil fuel usage. Increasing biomass energy production beyond this level would probably reduce food security and exacerbate forcing of climate change. PMID:18215439

  15. Spatial Distribution of Aboveground Carbon Stock of the Arboreal Vegetation in Brazilian Biomes of Savanna, Atlantic Forest and Semi-Arid Woodland.

    PubMed

    Scolforo, Henrique Ferraco; Scolforo, Jose Roberto Soares; Mello, Carlos Rogerio; Mello, Jose Marcio; Ferraz Filho, Antonio Carlos

    2015-01-01

    The objective of this study was to map the spatial distribution of aboveground carbon stock (using Regression-kriging) of arboreal plants in the Atlantic Forest, Semi-arid woodland, and Savanna Biomes in Minas Gerais State, southeastern Brazil. The database used in this study was obtained from 163 forest fragments, totaling 4,146 plots of 1,000 m2 distributed in these Biomes. A geographical model for carbon stock estimation was parameterized as a function of Biome, latitude and altitude. This model was applied over the samples and the residuals generated were mapped based on geostatistical procedures, selecting the exponential semivariogram theoretical model for conducting ordinary Kriging. The aboveground carbon stock was found to have a greater concentration in the north of the State, where the largest contingent of native vegetation is located, mainly the Savanna Biome, with Wooded Savanna and Shrub Savanna phytophysiognomes. The largest weighted averages of carbon stock per hectare were found in the south-center region (48.6 Mg/ha) and in the southern part of the eastern region (48.4 Mg/ha) of Minas Gerais State, due to the greatest predominance of Atlantic Forest Biome forest fragments. The smallest weighted averages per hectare were found in the central (21.2 Mg/ha), northern (20.4 Mg/ha), and northwestern (20.7 Mg/ha) regions of Minas Gerais State, where Savanna Biome fragments are predominant, in the phytophysiognomes Wooded Savanna and Shrub Savanna. PMID:26066508

  16. Spatial Distribution of Aboveground Carbon Stock of the Arboreal Vegetation in Brazilian Biomes of Savanna, Atlantic Forest and Semi-Arid Woodland

    PubMed Central

    2015-01-01

    The objective of this study was to map the spatial distribution of aboveground carbon stock (using Regression-kriging) of arboreal plants in the Atlantic Forest, Semi-arid woodland, and Savanna Biomes in Minas Gerais State, southeastern Brazil. The database used in this study was obtained from 163 forest fragments, totaling 4,146 plots of 1,000 m2 distributed in these Biomes. A geographical model for carbon stock estimation was parameterized as a function of Biome, latitude and altitude. This model was applied over the samples and the residuals generated were mapped based on geostatistical procedures, selecting the exponential semivariogram theoretical model for conducting ordinary Kriging. The aboveground carbon stock was found to have a greater concentration in the north of the State, where the largest contingent of native vegetation is located, mainly the Savanna Biome, with Wooded Savanna and Shrub Savanna phytophysiognomes. The largest weighted averages of carbon stock per hectare were found in the south-center region (48.6 Mg/ha) and in the southern part of the eastern region (48.4 Mg/ha) of Minas Gerais State, due to the greatest predominance of Atlantic Forest Biome forest fragments. The smallest weighted averages per hectare were found in the central (21.2 Mg/ha), northern (20.4 Mg/ha), and northwestern (20.7 Mg/ha) regions of Minas Gerais State, where Savanna Biome fragments are predominant, in the phytophysiognomes Wooded Savanna and Shrub Savanna. PMID:26066508

  17. Aboveground predation by an American badger (Taxidea taxus) on black-tailed prairie dogs (Cynomys ludovicianus)

    USGS Publications Warehouse

    Eads, D.A.; Biggins, D.E.

    2008-01-01

    During research on black-tailed prairie dogs (Cynomys ludovicianus), we repeatedly observed a female American badger (Taxidea taxus) hunting prairie dogs on a colony in southern Phillips County, Montana. During 1-14 June 2006, we observed 7 aboveground attacks (2 successful) and 3 successful excavations of prairie dogs. The locations and circumstances of aboveground attacks suggested that the badger improved her probability of capturing prairie dogs by planning the aboveground attacks based on perceptions of speeds, angles, distances, and predicted escape responses of prey. Our observations add to previous reports on the complex and varied predatory methods and cognitive capacities of badgers. These observations also underscore the individuality of predators and support the concept that predators are active participants in predator-prey interactions.

  18. Below-ground herbivory limits induction of extrafloral nectar by above-ground herbivores

    PubMed Central

    Huang, Wei; Siemann, Evan; Carrillo, Juli; Ding, Jianqing

    2015-01-01

    Background and Aims Many plants produce extrafloral nectar (EFN), and increase production following above-ground herbivory, presumably to attract natural enemies of the herbivores. Below-ground herbivores, alone or in combination with those above ground, may also alter EFN production depending on the specificity of this defence response and the interactions among herbivores mediated through plant defences. To date, however, a lack of manipulative experiments investigating EFN production induced by above- and below-ground herbivory has limited our understanding of how below-ground herbivory mediates indirect plant defences to affect above-ground herbivores and their natural enemies. Methods In a greenhouse experiment, seedlings of tallow tree (Triadica sebifera) were subjected to herbivory by a specialist flea beetle (Bikasha collaris) that naturally co-occurs as foliage-feeding adults and root-feeding larvae. Seedlings were subjected to above-ground adults and/or below-ground larvae herbivory, and EFN production was monitored. Key Results Above- and/or below-ground herbivory significantly increased the percentage of leaves with active nectaries, the volume of EFN and the mass of soluble solids within the nectar. Simultaneous above- and below-ground herbivory induced a higher volume of EFN and mass of soluble solids than below-ground herbivory alone, but highest EFN production was induced by above-ground herbivory when below-ground herbivores were absent. Conclusions The induction of EFN production by below-ground damage suggests that systemic induction underlies some of the EFN response. The strong induction by above-ground herbivory in the absence of below-ground herbivory points to specific induction based on above- and below-ground signals that may be adaptive for this above-ground indirect defence. PMID:25681822

  19. Biomass production, nutrient cycling, and carbon fixation by Salicornia brachiata Roxb.: A promising halophyte for coastal saline soil rehabilitation.

    PubMed

    Rathore, Aditya P; Chaudhary, Doongar R; Jha, Bhavanath

    2016-08-01

    In order to increase our understanding of the interaction of soil-halophyte (Salicornia brachiata) relations and phytoremediation, we investigated the aboveground biomass, carbon fixation, and nutrient composition (N, P, K, Na, Ca, and Mg) of S. brachiata using six sampling sites with varying characteristics over one growing season in intertidal marshes. Simultaneously, soil characteristics and nutrient concentrations were also estimated. There was a significant variation in soil characteristics and nutrient contents spatially (except pH) as well as temporally. Nutrient contents in aboveground biomass of S. brachiata were also significantly differed spatially (except C and Cl) as well as temporally. Aboveground biomass of S. brachiata ranged from 2.51 to 6.07 t/ha at maturity and it was positively correlated with soil electrical conductivity and available Na, whereas negatively with soil pH. The K/Na ratio in plant was below one, showing tolerance to salinity. The aboveground C fixation values ranged from 0.77 to 1.93 C t/ha at all six sampling sites. This study provides new understandings into nutrient cycling-C fixation potential of highly salt-tolerant halophyte S. brachiata growing on intertidal soils of India. S. brachiata have a potential for amelioration of the salinity due to higher Na bioaccumulation factor. PMID:26852782

  20. Understanding cross-communication between aboveground and belowground tissues via transcriptome analysis of a sucking insect whitefly-infested pepper plants.

    PubMed

    Park, Yong-Soon; Ryu, Choong-Min

    2014-01-01

    Plants have developed defensive machinery to protect themselves against herbivore and pathogen attacks. We previously reported that aboveground whitefly (Bemisia tabaci Genn.) infestation elicited induced resistance in leaves and roots and influenced the modification of the rhizosphere microflora. In this study, to obtain molecular evidence supporting these plant fitness strategies against whitefly infestation, we performed a 300 K pepper microarray analysis using leaf and root tissues of pepper (Capsicum annuum L.) applied with whitefly, benzo-(1,2,3)-thiadiazole-7-carbothioic acid S-methyl ester (BTH), and the combination of BTH+whitefly. We defined differentially expressed genes (DEGs) as genes exhibiting more than 2-fold change (1.0 based on log2 values) in expression in leaves and roots in response to each treatment compared to the control. We identified a total of 16,188 DEGs in leaves and roots. Of these, 6685, 6752, and 4045 DEGs from leaf tissue and 6768, 7705, and 7667 DEGs from root tissue were identified in the BTH, BTH+whitefly, and whitefly treatment groups, respectively. The total number of DEGs was approximately two-times higher in roots than in whitefly-infested leaves subjected to whitefly infestation. Among DEGs, whitefly feeding induced salicylic acid and jasmonic acid/ethylene-dependent signaling pathways in leaves and roots. Several transporters and auxin-responsive genes were upregulated in roots, which can explain why biomass increase is facilitated. Using transcriptome analysis, our study provides new insights into the molecular basis of whitefly-mediated intercommunication between aboveground and belowground plant tissues and provides molecular evidence that may explain the alteration of rhizosphere microflora and root biomass by whitefly infestation. PMID:24309116

  1. Merging unmixed Landsat TM data in a semi-empirical SAR model for the assessment of herbaceous vegetation biomass in a heterogeneous environment

    NASA Astrophysics Data System (ADS)

    Svoray, T.; Shoshany, M.

    2002-01-01

    In this paper we suggest a remote sensing methodology for herbaceous Areal Aboveground Biomass (AAB) estimations in the heterogeneous Mediterranean system. The methodology developed is based on a modification of the water-cloud model to the conditions of mixed environments including shrub, dwarf shrub and herb formations. The use of the Green leaf biomass Volumetric Density (GVD) as a canopy descriptor and the use of soil and vegetation fractions from Lansat TM data facilitated improvements in the application of the water-cloud model to the study area and enabled successful reproduction of the backscatter from the Mediterranean vegetation formations and the derivation of AAB values of herbaceous vegetation. The model was applied to the entire image domain and the AAB layers achieved probe capable of representing spatio-temporal patterns of changing AAB. Based on these results, the methodology provided in this paper lays a basis for the derivation of important and more advanced ecological and range management parameters, such as primary production, carrying capacity and dominance in the areal domain. The use of satellite images for quantitative mapping of these parameters may contribute significantly to our understanding of Mediterranean to semi-arid ecosystems and could provide an efficient tool for rangeland plannars and decision makers.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Campioli, M.; Vicca, S.; Luyssaert, S.; Bilcke, J.; Ceschia, E.; Chapin, F. S., III; Ciais, P.; Fernández-Martínez, M.; Malhi, Y.; Obersteiner, M.; Olefeldt, D.; Papale, D.; Piao, S. L.; Peñuelas, J.; Sullivan, P. F.; Wang, X.; Zenone, T.; Janssens, I. A.

    2015-11-01

    Plants acquire carbon through photosynthesis to sustain biomass production, autotrophic respiration and production of non-structural compounds for multiple purposes. The fraction of photosynthetic production used for biomass production, the biomass production efficiency, is a key determinant of the conversion of solar energy to biomass. In forest ecosystems, biomass production efficiency was suggested to be related to site fertility. Here we present a database of biomass production efficiency from 131 sites compiled from individual studies using harvest, biometric, eddy covariance, or process-based model estimates of production. The database is global, but dominated by data from Europe and North America. We show that instead of site fertility, ecosystem management is the key factor that controls biomass production efficiency in terrestrial ecosystems. In addition, in natural forests, grasslands, tundra, boreal peatlands and marshes, biomass production efficiency is independent of vegetation, environmental and climatic drivers. This similarity of biomass production efficiency across natural ecosystem types suggests that the ratio of biomass production to gross primary productivity is constant across natural ecosystems. We suggest that plant adaptation results in similar growth efficiency in high- and low-fertility natural systems, but that nutrient influxes under managed conditions favour a shift to carbon investment from the belowground flux of non-structural compounds to aboveground biomass.

  4. Allometric scaling relationship between above- and below-ground biomass within and across five woody seedlings

    PubMed Central

    Cheng, Dongliang; Ma, Yuzhu; Zhong, Quanling; Xu, Weifeng

    2014-01-01

    Allometric biomass allocation theory predicts that leaf biomass (ML) scaled isometrically with stem (MS) and root (MR) biomass, and thus above-ground biomass (leaf and stem) (MA) and root (MR) scaled nearly isometrically with below-ground biomass (root) for tree seedlings across a wide diversity of taxa. Furthermore, prior studies also imply that scaling constant should vary with species. However, litter is known about whether such invariant isometric scaling exponents hold for intraspecific biomass allocation, and how variation in scaling constants influences the interspecific scaling relationship between above- and below-ground biomass. Biomass data of seedlings from five evergreen species were examined to test scaling relationships among biomass components across and within species. Model Type II regression was used to compare the numerical values of scaling exponents and constants among leaf, stem, root, and above- to below-ground biomass. The results indicated that ML and MS scaled in an isometric or a nearly isometric manner with MR, as well as MA to MR for five woody species. Significant variation was observed in the Y-intercepts of the biomass scaling curves, resulting in the divergence for intraspecific scaling and interspecific scaling relationships for ML versus MS and ML versus MR, but not for MS versus MR and MA versus MR. We conclude, therefore, that a nearly isometric scaling relationship of MA versus MR holds true within each of the studied woody species and across them irrespective the negative scaling relationship between leaf and stem. PMID:25505524

  5. Biomass torrefaction mill

    DOEpatents

    Sprouse, Kenneth M.

    2016-05-17

    A biomass torrefaction system includes a mill which receives a raw biomass feedstock and operates at temperatures above 400 F (204 C) to generate a dusty flue gas which contains a milled biomass product.

  6. Biomass Energy Research

    SciTech Connect

    Traylor, T.D.; Pitsenbarger, J.

    1996-03-01

    Biomass Energy Research announces on a bimonthly basis the current worldwide research and development (R&D) information available on biomass power systems, alternate feedstocks from biomass, and biofuels supply options.

  7. My Biomass, Your Biomass, Our Solution

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The US is pursuing an array of renewable energy sources to reduce reliance on imported fossil fuels and reduce greenhouse gas emissions. Biomass energy and biomass ethanol are key components in the pursuit. The need for biomass feedstock to produce sufficient ethanol to meet any of the numerous stat...

  8. Vegetation in karst terrain of southwestern China allocates more biomass to roots

    NASA Astrophysics Data System (ADS)

    Ni, J.; Luo, D. H.; Xia, J.; Zhang, Z. H.; Hu, G.

    2015-07-01

    In mountainous areas of southwestern China, especially Guizhou province, continuous, broadly distributed karst landscapes with harsh and fragile habitats often lead to land degradation. Research indicates that vegetation located in karst terrains has low aboveground biomass and land degradation that reduces vegetation biomass, but belowground biomass measurements are rarely reported. Using the soil pit method, we investigated the root biomass of karst vegetation in five land cover types: grassland, grass-scrub tussock, thorn-scrub shrubland, scrub-tree forest, and mixed evergreen and deciduous forest in Maolan, southern Guizhou province, growing in two different soil-rich and rock-dominated habitats. The results show that roots in karst vegetation, especially the coarse roots, and roots in rocky habitats are mostly distributed in the topsoil layers (89 % on the surface up to 20 cm depth). The total root biomass in all habitats of all vegetation degradation periods is 18.77 Mg ha-1, in which roots in rocky habitat have higher biomass than in earthy habitat, and coarse root biomass is larger than medium and fine root biomass. The root biomass of mixed evergreen and deciduous forest in karst habitat (35.83 Mg ha-1) is not greater than that of most typical, non-karst evergreen broad-leaved forests in subtropical regions of China, but the ratio of root to aboveground biomass in karst forest (0.37) is significantly greater than the mean ratio (0.26 ± 0.07) of subtropical evergreen forests. Vegetation restoration in degraded karst terrain will significantly increase the belowground carbon stock, forming a potential regional carbon sink.

  9. Vegetation in karst terrain of southwestern China allocates more biomass to roots

    NASA Astrophysics Data System (ADS)

    Ni, J.; Luo, D. H.; Xia, J.; Zhang, Z. H.; Hu, G.

    2015-03-01

    In mountainous areas of southwestern China, especially Guizhou Province, continuous, broadly distributed karst landscapes with harsh and fragile habitats often lead to land degradation. Research indicates that vegetation located in karst terrains has low aboveground biomass, and land degradation reduces vegetation biomass, but belowground biomass measurements are rarely reported. Using the soil pit method, we investigated the root biomass of karst vegetation in five degraded (successional) stages: grassland, grass-scrub tussock, thorn-scrub shrubland, scrub-tree forest, and mixed evergreen and deciduous forest in Maolan, southern Guizhou Province, growing in two different soil-rich and rock-dominated habitats. The results show that roots in karst vegetation, especially the coarse roots, and roots in rocky habitats, are mostly distributed in the topsoil layers (89% on the surface up to 20 cm depth). The total root biomass in all habitats of all vegetation degradation periods is 18.77 Mg ha-1, in which roots in rocky habitat have higher biomass than in earthy habitat, and coarse root biomass is larger than medium and fine root biomass. The root biomass of mixed evergreen and deciduous forest in karst habitat (35.83 Mg ha-1) is not greater than that of most typical, non-karst evergreen broad-leaved forests in subtropical regions of China, but the ratio of root to aboveground biomass in karst forest (0.37) is significantly greater than the mean ratio (0.26±0.07) of subtropical evergreen forests. Vegetation restoration in degraded karst terrain will significantly increase the belowground carbon stock, forming a potential regional carbon sink.

  10. Facilitation and inhibition: changes in plant nitrogen and secondary metabolites mediate interactions between aboveground and belowground herbivores

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To date, it remains unclear how herbivore-induced changes in plant primary and secondary metabolites impact aboveground and belowground herbivore interactions. Here we report the effects of aboveground (adult) and belowground (larval) feeding by Bikasha collaris on nitrogen and secondary chemicals i...

  11. Patterns of Plant Biomass Partitioning Depend on Nitrogen Source

    PubMed Central

    Cambui, Camila Aguetoni; Svennerstam, Henrik; Gruffman, Linda; Nordin, Annika; Ganeteg, Ulrika; Näsholm, Torgny

    2011-01-01

    Nitrogen (N) availability is a strong determinant of plant biomass partitioning, but the role of different N sources in this process is unknown. Plants inhabiting low productivity ecosystems typically partition a large share of total biomass to belowground structures. In these systems, organic N may often dominate plant available N. With increasing productivity, plant biomass partitioning shifts to aboveground structures, along with a shift in available N to inorganic forms of N. We tested the hypothesis that the form of N taken up by plants is an important determinant of plant biomass partitioning by cultivating Arabidopsis thaliana on different N source mixtures. Plants grown on different N mixtures were similar in size, but those supplied with organic N displayed a significantly greater root fraction. 15N labelling suggested that, in this case, a larger share of absorbed organic N was retained in roots and split-root experiments suggested this may depend on a direct incorporation of absorbed amino acid N into roots. These results suggest the form of N acquired affects plant biomass partitioning and adds new information on the interaction between N and biomass partitioning in plants. PMID:21544211

  12. Aboveground net primary production responses to water availability in the Chihuhuan Desert: importance of legacy effects

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In arid ecosystems, current year precipitation explains a small proportion of annual aboveground net primary production (ANPP). Precipitation that occurred in previous years may be responsible for the observed difference between actual and expected ANPP, a concept that we called legacy. Thus, previo...

  13. Putative linkages between below- and aboveground mutualisms during alien plant invasions.

    PubMed

    Rodríguez-Echeverría, Susana; Traveset, Anna

    2015-01-01

    Evidence of the fundamental role of below-aboveground links in controlling ecosystem processes is mostly based on studies done with soil herbivores or mutualists and aboveground herbivores. Much less is known about the links between belowground and aboveground mutualisms, which have been studied separately for decades. It has not been until recently that these mutualisms-mycorrhizas and legume-rhizobia on one hand, and pollinators and seed dispersers on the other hand-have been found to influence each other, with potential ecological and evolutionary consequences. Here we review the mechanisms that may link these two-level mutualisms, mostly reported for native plant species, and make predictions about their relevance during alien plant invasions. We propose that alien plants establishing effective mutualisms with belowground microbes might improve their reproductive success through positive interactions between those mutualists and pollinators and seed dispersers. On the other hand, changes in the abundance and diversity of soil mutualists induced by invasion can also interfere with below-aboveground links for native plant species. We conclude that further research on this topic is needed in the field of invasion ecology as it can provide interesting clues on synergistic interactions and invasional meltdowns during alien plant invasions. PMID:26034049

  14. Technical basis for the aboveground structure failure and associated represented hazardous conditions

    SciTech Connect

    MANGAN, D.

    2003-03-20

    The purpose of the Technical Basis Document is to determine the consequences and frequency of aboveground structure failures. These failures include drops of contained equipment, such as a pump, from a SST or DST, a crane failure resulting in a load drop onto a HEPA filter. These failures can result in an uncontrolled release of radiological and toxicological material.

  15. Switchgrass and intermediate wheatgrass aboveground and belowground response to nitrogen and calcium

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Optimal nutrient management will be critical in developing sustainable perennial biofeedstocks. Calcium (Ca) and nitrogen (N) treatments (2, 8, and 32 mg L-1) were investigated on aboveground and belowground growth of switchgrass (Panicum virgatum L.) and intermediate wheatgrass [Thinopyrum interme...

  16. Impact of predatory carabids on below- and aboveground pests and yield in strawberry

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The impact of adult carabid beetles on below- and above-ground pests and fruit yield was examined in a two-year strawberry field study. Plots (2 m x 2 m) enclosed with barriers were used to augment or exclude adult carabids, and compared to open control plots. Pterostichus melanarius was the predo...

  17. Putative linkages between below- and aboveground mutualisms during alien plant invasions

    PubMed Central

    Rodríguez-Echeverría, Susana; Traveset, Anna

    2015-01-01

    Evidence of the fundamental role of below–aboveground links in controlling ecosystem processes is mostly based on studies done with soil herbivores or mutualists and aboveground herbivores. Much less is known about the links between belowground and aboveground mutualisms, which have been studied separately for decades. It has not been until recently that these mutualisms—mycorrhizas and legume–rhizobia on one hand, and pollinators and seed dispersers on the other hand—have been found to influence each other, with potential ecological and evolutionary consequences. Here we review the mechanisms that may link these two-level mutualisms, mostly reported for native plant species, and make predictions about their relevance during alien plant invasions. We propose that alien plants establishing effective mutualisms with belowground microbes might improve their reproductive success through positive interactions between those mutualists and pollinators and seed dispersers. On the other hand, changes in the abundance and diversity of soil mutualists induced by invasion can also interfere with below–aboveground links for native plant species. We conclude that further research on this topic is needed in the field of invasion ecology as it can provide interesting clues on synergistic interactions and invasional meltdowns during alien plant invasions. PMID:26034049

  18. Root growth dynamics linked to aboveground growth in walnuts (Juglans regia L.)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Background and Aims: Examination of belowground plant responses to canopy and soil moisture manipulation is scant compared to that aboveground but needed to understand whole plant responses to environmental factors. Plasticity in the seasonal timing and vertical distribution of root growth in respon...

  19. Characteristics of train noise in above-ground and underground stations with side and island platforms

    NASA Astrophysics Data System (ADS)

    Shimokura, Ryota; Soeta, Yoshiharu

    2011-04-01

    Railway stations can be principally classified by their locations, i.e., above-ground or underground stations, and by their platform styles, i.e., side or island platforms. However, the effect of the architectural elements on the train noise in stations is not well understood. The aim of the present study is to determine the different acoustical characteristics of the train noise for each station style. The train noise was evaluated by (1) the A-weighted equivalent continuous sound pressure level ( LAeq), (2) the amplitude of the maximum peak of the interaural cross-correlation function (IACC), (3) the delay time ( τ1) and amplitude ( ϕ1) of the first maximum peak of the autocorrelation function. The IACC, τ1 and ϕ1 are related to the subjective diffuseness, pitch and pitch strength, respectively. Regarding the locations, the LAeq in the underground stations was 6.4 dB higher than that in the above-ground stations, and the pitch in the underground stations was higher and stronger. Regarding the platform styles, the LAeq on the side platforms was 3.3 dB higher than on the island platforms of the above-ground stations. For the underground stations, the LAeq on the island platforms was 3.3 dB higher than that on the side platforms when a train entered the station. The IACC on the island platforms of the above-ground stations was higher than that in the other stations.

  20. 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.

  1. Cadmium uptake in above-ground parts of lettuce (Lactuca sativa L.).

    PubMed

    Tang, Xiwang; Pang, Yan; Ji, Puhui; Gao, Pengcheng; Nguyen, Thanh Hung; Tong, Yan'an

    2016-03-01

    Because of its high Cd uptake and translocation, lettuce is often used in Cd contamination studies. However, there is a lack of information on Cd accumulation in the above-ground parts of lettuce during the entire growing season. In this study, a field experiment was carried out in a Cd-contaminated area. Above-ground lettuce parts were sampled, and the Cd content was measured using a flame atomic absorption spectrophotometer (AAS). The results showed that the Cd concentration in the above-ground parts of lettuce increased from 2.70 to 3.62mgkg(-1) during the seedling stage, but decreased from 3.62 to 2.40mgkg(-1) during organogenesis and from 2.40 to 1.64mgkg(-1) during bolting. The mean Cd concentration during the seedling stage was significantly higher than that during organogenesis (a=0.05) and bolting (a=0.01). The Cd accumulation in the above-ground parts of an individual lettuce plant could be described by a sigmoidal curve. Cadmium uptake during organogenesis was highest (80% of the total), whereas that during bolting was only 4.34%. This research further reveals that for Rome lettuce: (1) the highest Cd content of above-ground parts occurred at the end of the seedling phase; (2) the best harvest time with respect to Cd phytoaccumulation is at the end of the organogenesis stage; and (3) the organogenesis stage is the most suitable time to enhance phytoaccumulation efficiency by adjusting the root:shoot ratio. PMID:26685781

  2. Comparative study of above ground biomass estimates for conterminous US

    NASA Astrophysics Data System (ADS)

    Neeti, N.; Kennedy, R. E.

    2013-12-01

    Accurate estimates of forest biomass are important for carbon accounting at both regional and national scale. There are four above ground biomass (AGB) maps available for conterminous US, one from the National Aeronautics and Space Administration (NASA), two from the United States Forest Service (USFS) (Blackard and Wilson) and one from the Woods Hole Research Center (WHRC). Although all four maps are meant to represent similar quantities, spatial patterns of AGB vary considerably from map to map. To use any of these AGB maps for carbon accounting, it is important to understand sources of uncertainty in individual maps and agreement and disagreement among them. Therefore, we compared the four AGB maps at ecoregion and state level to gain understanding of map consistency, leveraging discrepancies among maps to gain insight into the method and data sources. We also developed statewide summaries to compare with FIA forest AGB estimates, which are typically reported at the state level. We examined both absolute differences among these aggregated maps, and relative differences among regions within each map. The result shows that NASA biomass estimates are highest and Blackard estimates are lowest compared to other maps at both ecoregion and state level. The AGB for WHRC and Wilson are very similar at both ecoregion and state level specifically in the lower biomass regions compared to higher biomass regions. This could be associated with the differences in the spatial resolution of the data sources uses to generate these maps. At state level, WHRC map is found to be most similar and NASA biomass estimates least similar to FIA plot data. We discuss these differences in light of the different methods and data sources used to generate the maps.