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

    Treesearch

    Qi Chen; Dengsheng Lu; Michael Keller; Maiza dos-Santos; Edson Bolfe; Yunyun Feng; Changwei Wang

    2015-01-01

    Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems...

  3. 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.

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

    2017-12-01

    The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement

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

    PubMed

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

    2015-08-01

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

  7. Aboveground tree biomass statistics for Maine: 1982

    Treesearch

    Eric H. Wharton; Thomas S. Frieswyk; Anne M. Malley

    1985-01-01

    Traditional measures of volume inadequately describe the total aboveground wood resource. The 1980-82 inventory of Maine included estimates of aboveground tree biomass on timberland. There are nearly 1,504.4 million green tons of wood and bark in all trees above the ground level, or 88.2 green tons per acre of timberland. Most of the biomass is in growing stock, but 49...

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

    NASA Astrophysics Data System (ADS)

    Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

    2017-12-01

    The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

  9. 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.

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  12. Implications of allometric model selection for county-level biomass mapping

    Treesearch

    Laura Duncanson; Wenli Huang; Kristofer Johnson; Anu Swatantran; Ronald E. McRoberts; Ralph Dubayah

    2017-01-01

    Background: Carbon accounting in forests remains a large area of uncertainty in the global carbon cycle. Forest aboveground biomass is therefore an attribute of great interest for the forest management community, but the accuracy of aboveground biomass maps depends on the accuracy of the underlying field estimates used to calibrate models. These field estimates depend...

  13. 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.

  14. [Aboveground biomass of three conifers in Qianyanzhou plantation].

    PubMed

    Li, Xuanran; Liu, Qijing; Chen, Yongrui; Hu, Lile; Yang, Fengting

    2006-08-01

    In this paper, the regressive models of the aboveground biomass of Pinus elliottii, P. massoniana and Cunninghamia lanceolata in Qianyanzhou of subtropical China were established, and the regression analysis on the dry weight of leaf biomass and total biomass against branch diameter (d), branch length (L), d3 and d2L was conducted with linear, power and exponent functions. Power equation with single parameter (d) was proved to be better than the rests for P. massoniana and C. lanceolata, and linear equation with parameter (d3) was better for P. elliottii. The canopy biomass was derived by the regression equations for all branches. These equations were also used to fit the relationships of total tree biomass, branch biomass and foliage biomass with tree diameter at breast height (D), tree height (H), D3 and D2H, respectively. D2H was found to be the best parameter for estimating total biomass. For foliage-and branch biomass, both parameters and equation forms showed some differences among species. Correlations were highly significant (P <0.001) for foliage-, branch-and total biomass, with the highest for total biomass. By these equations, the aboveground biomass and its allocation were estimated, with the aboveground biomass of P. massoniana, P. elliottii, and C. lanceolata forests being 83.6, 72. 1 and 59 t x hm(-2), respectively, and more stem biomass than foliage-and branch biomass. According to the previous studies, the underground biomass of these three forests was estimated to be 10.44, 9.42 and 11.48 t x hm(-2), and the amount of fixed carbon was 47.94, 45.14 and 37.52 t x hm(-2), respectively.

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

    NASA Astrophysics Data System (ADS)

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

    2018-03-01

    Arctic tundra is becoming greener and shrubbier due to recent warming. This is impacting climate feedbacks and wildlife, yet the spatial distribution of plant biomass in tundra ecosystems is uncertain. In this study, we mapped plant and shrub above-ground biomass (AGB; kg m-2) and shrub dominance (%; shrub AGB/plant AGB) across the North Slope of Alaska by linking biomass harvests at 28 field sites with 30 m resolution Landsat satellite imagery. We first developed regression models (p < 0.01) to predict plant AGB (r 2 = 0.79) and shrub AGB (r 2 = 0.82) based on the normalized difference vegetation index (NDVI) derived from imagery acquired by Landsat 5 and 7. We then predicted regional plant and shrub AGB by combining these regression models with a regional Landsat NDVI mosaic built from 1721 summer scenes acquired between 2007 and 2016. Our approach employed a Monte Carlo uncertainty analysis that propagated sampling and sensor calibration errors. We estimated that plant AGB averaged 0.74 (0.60, 0.88) kg m-2 (95% CI) and totaled 112 (91, 135) Tg across the region, with shrub AGB accounting for ~43% of regional plant AGB. The new maps capture landscape variation in plant AGB visible in high resolution satellite and aerial imagery, notably shrubby riparian corridors. Modeled shrub AGB was strongly correlated with field measurements of shrub canopy height at 25 sites (rs  = 0.88) and with a regional map of shrub cover (rs  = 0.76). Modeled plant AGB and shrub dominance were higher in shrub tundra than graminoid tundra and increased between areas with the coldest and warmest summer air temperatures, underscoring the fact that future warming has the potential to greatly increase plant AGB and shrub dominance in this region. These new biomass maps provide a unique source of ecological information for a region undergoing rapid environmental change.

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

    PubMed

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

    2012-04-01

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

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

    Treesearch

    Xiaoping Zhou; Miles A. Hemstrom

    2010-01-01

    Timber availability, aboveground tree biomass, and changes in aboveground carbon pools are important consequences of landscape management. There are several models available for calculating tree volume and aboveground tree biomass pools. This paper documents species-specific regional equations for tree volume and aboveground live tree biomass estimation that might be...

  18. [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).

  19. Aboveground biomass in Tibetan grasslands

    Treesearch

    Y.H. Yang; J.Y. Fang; Y.D. Pan; C.J. Ji

    2009-01-01

    This study investigated spatial patterns and environmental controls of aboveground biomass (AGB) in alpine grasslands on the Tibetan Plateau by integrating AGB data collected from 135 sites during 2001-2004 and concurrent enhanced vegetation index derived from MODIS data sets. The AGB was estimated at 68.8 gm-2, with a larger value (90.8 gm

  20. 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

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

    PubMed

    Li, Shuaifeng; Lang, Xuedong; Liu, Wande; Ou, Guanglong; Xu, Hui; Su, Jianrong

    2018-01-01

    The relationship between biodiversity and biomass is an essential element of the natural ecosystem functioning. Our research aims at assessing the effects of species richness on the aboveground biomass and the ecological driver of this relationship in a primary Pinus kesiya forest. We sampled 112 plots of the primary P. kesiya forests in Yunnan Province. The general linear model and the structural equation model were used to estimate relative effects of multivariate factors among aboveground biomass, species richness and the other explanatory variables, including climate moisture index, soil nutrient regime and stand age. We found a positive linear regression relationship between the species richness and aboveground biomass using ordinary least squares regressions. The species richness and soil nutrient regime had no direct significant effect on aboveground biomass. However, the climate moisture index and stand age had direct effects on aboveground biomass. The climate moisture index could be a better link to mediate the relationship between species richness and aboveground biomass. The species richness affected aboveground biomass which was mediated by the climate moisture index. Stand age had direct and indirect effects on aboveground biomass through the climate moisture index. Our results revealed that climate moisture index had a positive feedback in the relationship between species richness and aboveground biomass, which played an important role in a link between biodiversity maintenance and ecosystem functioning. Meanwhile, climate moisture index not only affected positively on aboveground biomass, but also indirectly through species richness. The information would be helpful in understanding the biodiversity-aboveground biomass relationship of a primary P. kesiya forest and for forest management.

  2. 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.

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

    PubMed Central

    Li, Shuaifeng; Lang, Xuedong; Liu, Wande; Ou, Guanglong; Xu, Hui

    2018-01-01

    The relationship between biodiversity and biomass is an essential element of the natural ecosystem functioning. Our research aims at assessing the effects of species richness on the aboveground biomass and the ecological driver of this relationship in a primary Pinus kesiya forest. We sampled 112 plots of the primary P. kesiya forests in Yunnan Province. The general linear model and the structural equation model were used to estimate relative effects of multivariate factors among aboveground biomass, species richness and the other explanatory variables, including climate moisture index, soil nutrient regime and stand age. We found a positive linear regression relationship between the species richness and aboveground biomass using ordinary least squares regressions. The species richness and soil nutrient regime had no direct significant effect on aboveground biomass. However, the climate moisture index and stand age had direct effects on aboveground biomass. The climate moisture index could be a better link to mediate the relationship between species richness and aboveground biomass. The species richness affected aboveground biomass which was mediated by the climate moisture index. Stand age had direct and indirect effects on aboveground biomass through the climate moisture index. Our results revealed that climate moisture index had a positive feedback in the relationship between species richness and aboveground biomass, which played an important role in a link between biodiversity maintenance and ecosystem functioning. Meanwhile, climate moisture index not only affected positively on aboveground biomass, but also indirectly through species richness. The information would be helpful in understanding the biodiversity-aboveground biomass relationship of a primary P. kesiya forest and for forest management. PMID:29324901

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

    Treesearch

    Brice B. Hanberry; Hong S. He; Stephen R. Shifley

    2016-01-01

    Disturbance regimes and forests have changed over time in the eastern United States. We examined effects of historical disturbance (circa 1813 to 1850) compared to current disturbance (circa 2004 to 2008) on aboveground, live tree biomass (for trees with diameters ≥13 cm) and landscape variation of biomass in forests of the Ozarks and Plains landscapes in Missouri, USA...

  5. Estimating Forest Canopy Heights and Aboveground Biomass with Simulated ICESat-2 Data

    NASA Astrophysics Data System (ADS)

    Malambo, L.; Narine, L.; Popescu, S. C.; Neuenschwander, A. L.; Sheridan, R.

    2016-12-01

    The Ice, Cloud and Land Elevation Satellite (ICESat) 2 is scheduled for launch in 2017 and one of its overall science objectives will be to measure vegetation heights, which can be used to estimate and monitor aboveground biomass (AGB) over large spatial scales. This study serves to develop a methodology for utilizing vegetation data collected by ICESat-2 that will be on a five-year mission from 2017, for mapping forest canopy heights and estimating aboveground forest biomass (AGB). The specific objectives are to, (1) simulate ICESat-2 photon-counting lidar (PCL) data, (2) utilize simulated PCL data to estimate forest canopy heights and propose a methodology for upscaling PCL height measurements to obtain spatially contiguous coverage and, (3) estimate and map AGB using simulated PCL data. The laser pulse from ICESat-2 will be divided into three pairs of beams spaced approximately 3 km apart, with footprints measuring approximately 14 m in diameter and with 70 cm along-track intervals. Using existing airborne lidar data (ALS) for Sam Houston National Forest (SHNF) and known ICESat-2 beam locations, footprints are generated along beam locations and PCL data are then simulated from discrete return lidar points within each footprint. By applying data processing algorithms, photons are classified into top of canopy points and ground surface elevation points to yield tree canopy height values within each ICESat-2 footprint. AGB is then estimated using simple linear regression that utilizes AGB from a biomass map generated with ALS data for SHNF and simulated PCL height metrics for 100 m segments along ICESat-2 tracks. Two approaches also investigated for upscaling AGB estimates to provide wall-to-wall coverage of AGB are (1) co-kriging and (2) Random Forest. Height and AGB maps, which are the outcomes of this study, will demonstrate how data acquired by ICESat-2 can be used to measure forest parameters and in extension, estimate forest carbon for climate change

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

    PubMed

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

    2010-12-01

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

  7. Aboveground tree biomass on productive forest land in Alaska.

    Treesearch

    John Yarie; Delbert Mead

    1982-01-01

    Total aboveground woody biomass of trees on forest land that can produce 1.4 cubic m eters per hectare per year of industrial wood in Alaska is 1.33 billion metric tons green weight. The estimated energy value of the standing woody biomass is 11.9 x 10'5 Btu's. Statewide tables of biomass and energy values for softwoods, hardwoods, and species groups are...

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

    Treesearch

    Nicholas S. Skowronski; Kenneth L. Clark; Michael Gallagher; Richard A. Birdsey; John L. Hom

    2014-01-01

    We estimated aboveground tree biomass and change in aboveground tree biomass using repeated airborne laser scanner (ALS) acquisitions and temporally coincident ground observations of forest biomass, for a relatively undisturbed period (2004-2007; ∇07-04), a contrasting period of disturbance (2007-2009; ∇09-07...

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

    USGS Publications Warehouse

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

    2012-01-01

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

  10. 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.

  11. Tropical Soil Carbon Stocks do not Reflect Aboveground Forest Biomass Across Geological and Rainfall Gradients

    NASA Astrophysics Data System (ADS)

    Cusack, D. F.; Markesteijn, L.; Turner, B. L.

    2016-12-01

    Soil organic carbon (C) dynamics present a large source of uncertainty in global C cycle models, and inhibit our ability to predict effects of climate change. Tropical wet and seasonal forests exert a disproportionate influence on the global C cycle relative to their land area because they are the most C-rich ecosystems on Earth, containing 25-40% of global terrestrial C stocks. While significant advances have been made to map aboveground C stocks in tropical forests, determining soil C stocks using remote sensing technology is still not possible for closed-canopy forests. It is unclear to what extent aboveground C stocks can be used to predict soil C stocks across tropical forests. Here we present 1-m-deep soil organic C stocks for 42 tropical forest sites across rainfall and geological gradients in Panama. We show that soil C stocks do not correspond to aboveground plant biomass or to litterfall productivity in these humid tropical forests. Rather, soil C stocks were strongly and positively predicted by fine root biomass, soil clay content, and rainfall (R2 = 0.47, p < 0.05). Fine root biomass, in turn, was most strongly predicted by total extractable soil base cations (R2 = 0.24, p < 0.05, negative relationship). Our measures of tropical soil C and its relationships with climatic and soil chemical characteristics form an important basis for improving model estimates of soil C stocks and predictions of climate change effects on tropical C storage.

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

    PubMed

    Ali, Arshad; Mattsson, Eskil

    2017-01-01

    Individual tree size variation, which is generally quantified by variances in tree diameter at breast height (DBH) and height in isolation or conjunction, plays a central role in ecosystem functioning in both controlled and natural environments, including forests. However, none of the studies have been conducted in homegarden agroforestry systems. In this study, aboveground biomass, stand quality, cation exchange capacity (CEC), DBH variation, and species diversity were determined across 45 homegardens in the dry zone of Sri Lanka. We employed structural equation modeling (SEM) to test for the direct and indirect effects of stand quality and CEC, via tree size inequality and species diversity, on aboveground biomass. The SEM accounted for 26, 8, and 1% of the variation in aboveground biomass, species diversity and DBH variation, respectively. DBH variation had the strongest positive direct effect on aboveground biomass (β=0.49), followed by the non-significant direct effect of species diversity (β=0.17), stand quality (β=0.17) and CEC (β=-0.05). There were non-significant direct effects of CEC and stand quality on DBH variation and species diversity. Stand quality and CEC had also non-significant indirect effects, via DBH variation and species diversity, on aboveground biomass. Our study revealed that aboveground biomass substantially increased with individual tree size variation only, which supports the niche complementarity mechanism. However, aboveground biomass was not considerably increased with species diversity, stand quality and soil fertility, which might be attributable to the adaptation of certain productive species to the local site conditions. Stand structure shaped by few productive species or independent of species diversity is a main determinant for the variation in aboveground biomass in the studied homegardens. Maintaining stand structure through management practices could be an effective approach for enhancing aboveground biomass in these dry

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

    PubMed

    Ali, Arshad; Yan, En-Rong; Chang, Scott X; Cheng, Jun-Yang; Liu, Xiang-Yu

    2017-01-01

    Subtropical forests are globally important in providing ecological goods and services, but it is not clear whether functional diversity and composition can predict aboveground biomass in such forests. We hypothesized that high aboveground biomass is associated with high functional divergence (FDvar, i.e., niche complementarity) and community-weighted mean (CWM, i.e., mass ratio; communities dominated by a single plant strategy) of trait values. Structural equation modeling was employed to determine the direct and indirect effects of stand age and the residual effects of CWM and FDvar on aboveground biomass across 31 plots in secondary forests in subtropical China. The CWM model accounted for 78, 20, 6 and 2% of the variation in aboveground biomass, nitrogen concentration in young leaf, plant height and specific leaf area of young leaf, respectively. The FDvar model explained 74, 13, 7 and 0% of the variation in aboveground biomass, plant height, twig wood density and nitrogen concentration in young leaf, respectively. The variation in aboveground biomass, CWM of leaf nitrogen concentration and specific leaf area, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf explained by the joint model was 86, 20, 13, 7, 2 and 0%, respectively. Stand age had a strong positive direct effect but low indirect positive effects on aboveground biomass. Aboveground biomass was negatively related to CWM of nitrogen concentration in young leaf, but positively related to CWM of specific leaf area of young leaf and plant height, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf. Leaf and wood economics spectra are decoupled in regulating the functionality of forests, communities with diverse species but high nitrogen conservative and light acquisitive strategies result in high aboveground biomass, and hence, supporting both the mass ratio and niche complementarity hypotheses in secondary subtropical forests

  14. 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

  15. Implications of allometric model selection for county-level biomass mapping.

    PubMed

    Duncanson, Laura; Huang, Wenli; Johnson, Kristofer; Swatantran, Anu; McRoberts, Ronald E; Dubayah, Ralph

    2017-10-18

    Carbon accounting in forests remains a large area of uncertainty in the global carbon cycle. Forest aboveground biomass is therefore an attribute of great interest for the forest management community, but the accuracy of aboveground biomass maps depends on the accuracy of the underlying field estimates used to calibrate models. These field estimates depend on the application of allometric models, which often have unknown and unreported uncertainties outside of the size class or environment in which they were developed. Here, we test three popular allometric approaches to field biomass estimation, and explore the implications of allometric model selection for county-level biomass mapping in Sonoma County, California. We test three allometric models: Jenkins et al. (For Sci 49(1): 12-35, 2003), Chojnacky et al. (Forestry 87(1): 129-151, 2014) and the US Forest Service's Component Ratio Method (CRM). We found that Jenkins and Chojnacky models perform comparably, but that at both a field plot level and a total county level there was a ~ 20% difference between these estimates and the CRM estimates. Further, we show that discrepancies are greater in high biomass areas with high canopy covers and relatively moderate heights (25-45 m). The CRM models, although on average ~ 20% lower than Jenkins and Chojnacky, produce higher estimates in the tallest forests samples (> 60 m), while Jenkins generally produces higher estimates of biomass in forests < 50 m tall. Discrepancies do not continually increase with increasing forest height, suggesting that inclusion of height in allometric models is not primarily driving discrepancies. Models developed using all three allometric models underestimate high biomass and overestimate low biomass, as expected with random forest biomass modeling. However, these deviations were generally larger using the Jenkins and Chojnacky allometries, suggesting that the CRM approach may be more appropriate for biomass mapping with lidar. These

  16. Family Differences Influence the Aboveground Biomass of Loblolly Pine Plantations

    Treesearch

    P.E. Pope; D.L. Graney

    1979-01-01

    We compared the aboveground biomass of 4 half-sib families of loblolly pine (Pinus taeda L.) 11 years after planting. Total dry weights differed significantly among families in plantations on the same soil type with the same site index. Differences in biomass resulted from differences in stem form and branch size. Distribution of growth -the proportion of tree weight...

  17. Methods for estimating aboveground biomass and its components for Douglas-fir and lodgepole pine trees

    Treesearch

    K.P. Poudel; H. Temesgen

    2016-01-01

    Estimating aboveground biomass and its components requires sound statistical formulation and evaluation. Using data collected from 55 destructively sampled trees in different parts of Oregon, we evaluated the performance of three groups of methods to estimate total aboveground biomass and (or) its components based on the bias and root mean squared error (RMSE) that...

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

    USGS Publications Warehouse

    Coronado-Molina, C.; Day, J.W.; Reyes, E.; Perez, B.C.

    2004-01-01

    The structure and standing crop biomass of a dwarf mangrove forest, located in the salinity transition zone ofTaylor River Slough in the Everglades National Park, were studied. Although the four mangrove species reported for Florida occurred at the study site, dwarf Rhizophora mangle trees dominated the forest. The structural characteristics of the mangrove forest were relatively simple: tree height varied from 0.9 to 1.2 meters, and tree density ranged from 7062 to 23 778 stems haa??1. An allometric relationship was developed to estimate leaf, branch, prop root, and total aboveground biomass of dwarf Rhizophora mangle trees. Total aboveground biomass and their components were best estimated as a power function of the crown area times number of prop roots as an independent variable (Y = B ?? Xa??0.5083). The allometric equation for each tree component was highly significant (p<0.0001), with all r2 values greater than 0.90. The allometric relationship was used to estimate total aboveground biomass that ranged from 7.9 to 23.2 ton haa??1. Rhizophora mangle contributed 85% of total standing crop biomass. Conocarpus erectus, Laguncularia racemosa, and Avicennia germinans contributed the remaining biomass. Average aboveground biomass allocation was 69% for prop roots, 25% for stem and branches, and 6% for leaves. This aboveground biomass partitioning pattern, which gives a major role to prop roots that have the potential to produce an extensive root system, may be an important biological strategy in response to low phosphorus availability and relatively reduced soils that characterize mangrove forests in South Florida.

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

    PubMed

    Motlagh, Mohadeseh Ghanbari; Kafaky, Sasan Babaie; Mataji, Asadollah; Akhavan, Reza

    2018-05-21

    Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.

  20. Comparison of machine-learning methods for above-ground biomass estimation based on Landsat imagery

    NASA Astrophysics Data System (ADS)

    Wu, Chaofan; Shen, Huanhuan; Shen, Aihua; Deng, Jinsong; Gan, Muye; Zhu, Jinxia; Xu, Hongwei; Wang, Ke

    2016-07-01

    Biomass is one significant biophysical parameter of a forest ecosystem, and accurate biomass estimation on the regional scale provides important information for carbon-cycle investigation and sustainable forest management. In this study, Landsat satellite imagery data combined with field-based measurements were integrated through comparisons of five regression approaches [stepwise linear regression, K-nearest neighbor, support vector regression, random forest (RF), and stochastic gradient boosting] with two different candidate variable strategies to implement the optimal spatial above-ground biomass (AGB) estimation. The results suggested that RF algorithm exhibited the best performance by 10-fold cross-validation with respect to R2 (0.63) and root-mean-square error (26.44 ton/ha). Consequently, the map of estimated AGB was generated with a mean value of 89.34 ton/ha in northwestern Zhejiang Province, China, with a similar pattern to the distribution mode of local forest species. This research indicates that machine-learning approaches associated with Landsat imagery provide an economical way for biomass estimation. Moreover, ensemble methods using all candidate variables, especially for Landsat images, provide an alternative for regional biomass simulation.

  1. Family Differences in Aboveground Biomass Allocation in Loblolly Pine

    Treesearch

    Scott D. Roberts

    2002-01-01

    The proportion of tree growth allocated to stemwood is an important economic component of growth efficiency. Differences in growth efficiency between species, or between families within species, may therefore be related to how growth is proportionally allocated between the stem and other aboveground biomass components. This study examines genetically related...

  2. 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

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

    USGS Publications Warehouse

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

    2016-01-01

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

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

    PubMed

    Mitchard, Edward Ta; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra

    2013-10-26

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

  5. 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.

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

    NASA Technical Reports Server (NTRS)

    Longo, Marcos; Keller, Michael; Dos-Santos, Maiza N.; Leitold, Veronika; Pinage, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.

    2016-01-01

    Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).

  7. 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.

  8. 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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mark E. Kubiske

    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 themore » 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.« less

  10. Remote Sensing of Miombo Woodland's Aboveground Biomass and LAI using RADARSAT and Landsat ETM+ Data

    NASA Astrophysics Data System (ADS)

    Ribeiro, N. S.; Saatchi, S. S.; Shugart, H. H.; Wshington-Allen, R. A.

    2007-05-01

    Estimations of biomass are critical in Miombo Woodlands because they represent a primary source of food, fiber, and fuel for 340 million rural peoples and another 15 million urban dwellers in southern Africa. The purpose of this study is to estimate woody aboveground biomass and Leaf Area Index (LAI) in Niassa Reserve, northern Mozambique. The objective of this study is to use optical and microwave satellite data with contemporaneous field data to estimate biomass and LAI. Fifty field plots were surveyed across the Niassa Reserve for biomass and LAI in July and December 2004, respectively. Remote sensing data consisting of RADARSAT backscatter (C- band, ë=5.6 cm) and a June 2004 Landsat ETM+ were acquired. Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), and a land-cover map (72% total accuracy) were derived from the Landsat scene. Field measurements of biomass and LAI correlated with Radarsat backscatter (Rsqbiomass=0.45, RsqLAI = 0.35, P<0.0001 ), NDVI (Rsqbiomass =0.15, RsqLAI=0.14-, p <0.0001 ) and SR (Rsqbiomass=-0.14, RsqLAI= 0.17, 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, Rsq=0.53) and LAI (LAI= -0.66+0.01*radarsat+0.22*SR, Rsq=0.45). The addition of NDVI did not improve the model. Forest biomass and LAI maps were then produced for Niassa Reserve with an estimated peak total biomass of 18 kg/hm2 and a mean LAI of 2.8 m2/m2. In the east both biomass and LAI are lower than the western Niassa Reserve.

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

    Treesearch

    Xiaoping Zhou; Miles A. Hemstrom

    2009-01-01

    Live tree biomass estimates are essential for carbon accounting, bioenergy feasibility studies, and other analyses. Several models are currently used for estimating tree biomass. Each of these incorporates different calculation methods that may significantly impact the estimates of total aboveground tree biomass, merchantable biomass, and carbon pools. Consequently,...

  12. Guidelines for sampling aboveground biomass and carbon in mature central hardwood forests

    Treesearch

    Martin A. Spetich; Stephen R. Shifley

    2017-01-01

    As impacts of climate change expand, determining accurate measures of forest biomass and associated carbon storage in forests is critical. We present sampling guidance for 12 combinations of percent error, plot size, and alpha levels by disturbance regime to help determine the optimal size of plots to estimate aboveground biomass and carbon in an old-growth Central...

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

    Several large-scale maps of forest AGB have been released [1] [2] [3]. However, these existing global or regional datasets were only approximations based on combining land cover type and representative values instead of measurements of actual forest aboveground biomass or forest heights [4]. Rodríguez-Veiga et al[5] reported obvious discrepancies of existing forest biomass stock maps with in-situ observations in Mexico. One of the biggest challenges to the credibility of these maps comes from the scale gaps between the size of field sampling plots used to develop(or validate) estimation models and the pixel size of these maps and the availability of field sampling plots with sufficient size for the verification of these products [6]. It is time-consuming and labor-intensive to collect sufficient number of field sampling data over the plot size of the same as resolutions of regional maps. The smaller field sampling plots cannot fully represent the spatial heterogeneity of forest stands as shown in Figure 1. Forest AGB is directly determined by forest heights, diameter at breast height (DBH) of each tree, forest density and tree species. What measured in the field sampling are the geometrical characteristics of forest stands including the DBH, tree heights and forest densities. The LiDAR data is considered as the best dataset for the estimation of forest AGB. The main reason is that LiDAR can directly capture geometrical features of forest stands by its range detection capabilities.The remotely sensed dataset, which is capable of direct measurements of forest spatial structures, may serve as a ladder to bridge the scale gaps between the pixel size of regional maps of forest AGB and field sampling plots. Several researches report that TanDEM-X data can be used to characterize the forest spatial structures [7, 8]. In this study, the forest AGB map of northeast China were produced using ALOS/PALSAR data taking TanDEM-X data as a bridges. The TanDEM-X InSAR data used in

  14. 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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

    Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

    2017-01-19

    Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass ( R ² = 0.340, root-mean-square error (RMSE) = 81.89 g·m -2 , and relative error of 14.1%). The improvement of multiple regressions to the R ² and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns.

  17. 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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lee Spangler; Lee A. Vierling; Eva K. Stand

    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 acrossmore » {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

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

    PubMed

    Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles

    In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P < 0.001) across a wide range of AGB levels from 26 Mg/ha to 460 Mg/ha, and was confirmed by cross validation. A high-resolution biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful

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

    PubMed

    Ali, Arshad; Mattsson, Eskil

    2017-11-15

    The biodiversity - aboveground biomass relationship has been intensively studied in recent decades. However, no consensus has been arrived to consider the interplay of species diversity, and intraspecific and interspecific tree size variation in driving aboveground biomass, after accounting for the effects of plot size heterogeneity, soil fertility and stand quality in natural forest including agroforests. We tested the full, partial and no mediations effects of species diversity, and intraspecific and interspecific tree size variation on aboveground biomass by employing structural equation models (SEMs) using data from 45 homegarden agroforestry systems in Sri Lanka. The full mediation effect of either species diversity or intraspecific and interspecific tree size variation was rejected, while the partial and no mediation effects were accepted. In the no mediation SEM, homegarden size had the strongest negative direct effect (β=-0.49) on aboveground biomass (R 2 =0.65), followed by strong positive direct effect of intraspecific tree size variation (β=0.32), species diversity (β=0.29) and interspecific tree size variation (β=0.28). Soil fertility had a negative direct effect on interspecific tree size variation (β=-0.31). Stand quality had a significant positive total effect on aboveground biomass (β=0.28), but homegarden size had a significant negative total effect (β=-0.62), while soil fertility had a non-significant total effect on aboveground biomass. Similar to the no mediation SEM, the partial mediation SEMs had explained almost similar variation in aboveground biomass because species diversity, and intraspecific and interspecific tree size variation had non-significant indirect effects on aboveground biomass via each other. Our results strongly suggest that a multilayered tree canopy structure, due to high intraspecific and interspecific tree size variation, increases light capture and efficient utilization of resources among component species, and

  20. 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.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    PubMed Central

    Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

    2017-01-01

    Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns. PMID:28106819

  4. Long-term effects of fuel treatments on aboveground biomass accumulation in ponderosa pine forests of the northern Rocky Mountains

    Treesearch

    Kate A. Clyatt; Christopher R. Keyes; Sharon M. Hood

    2017-01-01

    Fuel treatments in ponderosa pine forests of the northern Rocky Mountains are commonly used to modify fire behavior, but it is unclear how different fuel treatments impact the subsequent production and distribution of aboveground biomass, especially in the long term. This research evaluated aboveground biomass responses 23 years after treatment in two silvicultural...

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

    Treesearch

    Wenli Huang; Anu Swatantran; Kristofer Johnson; Laura Duncanson; Hao Tang; Jarlath O' Neil Dunne; George Hurtt; Ralph Dubayah

    2015-01-01

    Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-...

  6. 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.

  7. A comparison of above-ground dry-biomass estimators for trees in the Northeastern United States

    Treesearch

    James A. Westfall

    2012-01-01

    In the northeastern United States, both component and total aboveground tree dry-biomass estimates are available from several sources. In this study, comparisons were made among four methods to promote understanding of the similarities and differences in live-tree biomass estimators. The methods use various equations developed from biomass data collected in the United...

  8. 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. © 2015 John Wiley & Sons Ltd.

  9. The positive relationships between plant coverage, species richness, and aboveground biomass are ubiquitous across plant growth forms in semi-steppe rangelands.

    PubMed

    Sanaei, Anvar; Ali, Arshad; Chahouki, Mohammad Ali Zare

    2018-01-01

    The positive relationships between biodiversity and aboveground biomass are important for biodiversity conservation and greater ecosystem functioning and services that humans depend on. However, the interaction effects of plant coverage and biodiversity on aboveground biomass across plant growth forms (shrubs, forbs and grasses) in natural rangelands are poorly studied. Here, we hypothesized that, while accounting for environmental factors and disturbance intensities, the positive relationships between plant coverage, biodiversity, and aboveground biomass are ubiquitous across plant growth forms in natural rangelands. We applied structural equation models (SEMs) using data from 735 quadrats across 35 study sites in semi-steppe rangelands in Iran. The combination of plant coverage and species richness rather than Shannon's diversity or species diversity (a latent variable of species richness and evenness) substantially enhance aboveground biomass across plant growth forms. In all selected SEMs, plant coverage had a strong positive direct effect on aboveground biomass (β = 0.72 for shrubs, 0.84 for forbs and 0.80 for grasses), followed by a positive effect of species richness (β = 0.26 for shrubs, 0.05 for forbs and 0.09 for grasses), and topographic factors. Disturbance intensity had a negative effect on plant coverage, whereas it had a variable effect on species richness across plant growth forms. Plant coverage had a strong positive total effect on aboveground biomass (β = 0.84 for shrubs, 0.88 for forbs, and 0.85 for grasses), followed by a positive effect of species richness, and a negative effect of disturbance intensity across plant growth forms. Our results shed light on the management of rangelands that is high plant coverage can significantly improve species richness and aboveground biomass across plant growth forms. We also found that high disturbance intensity due to heavy grazing has a strong negative effect on plant coverage rather than species

  10. High-resolution mapping of wetland vegetation biomass and distribution with L-band radar in southeastern coastal Louisiana

    NASA Astrophysics Data System (ADS)

    Thomas, N. M.; Simard, M.; Byrd, K. B.; Windham-Myers, L.; Castaneda, E.; Twilley, R.; Bevington, A. E.; Christensen, A.

    2017-12-01

    Louisiana coastal wetlands account for approximately one third (37%) of the estuarine wetland vegetation in the conterminous United States, yet the spatial distribution of their extent and aboveground biomass (AGB) is not well defined. This knowledge is critical for the accurate completion of national greenhouse gas (GHG) inventories. We generated high-resolution baselines maps of wetland vegetation extent and biomass at the Atchafalaya and Terrebonne basins in coastal Louisiana using a multi-sensor approach. Optical satellite data was used within an object-oriented machine learning approach to classify the structure of wetland vegetation types, offering increased detail over currently available land cover maps that do not distinguish between wetland vegetation types nor account for non-permanent seasonal changes in extent. We mapped 1871 km2 of wetlands during a period of peak biomass in September 2015 comprised of flooded forested wetlands and leaf, grass and emergent herbaceous marshes. The distribution of aboveground biomass (AGB) was mapped using JPL L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). Relationships between time-series radar imagery and field data collected in May 2015 and September 2016 were derived to estimate AGB at the Wax Lake and Atchafalaya deltas. Differences in seasonal biomass estimates reflect the increased AGB in September over May, concurrent with periods of peak biomass and the onset of the vegetation growing season, respectively. This method provides a tractable means of mapping and monitoring biomass of wetland vegetation types with L-band radar, in a region threatened with wetland loss under projections of increasing sea-level rise and terrestrial subsidence. Through this, we demonstrate a method that is able to satisfy the IPCC 2013 Wetlands Supplement requirement for Tier 2/Tier 3 reporting of coastal wetland GHG inventories.

  11. Leaf mass per area, not total leaf area, drives differences in above-ground biomass distribution among woody plant functional types.

    PubMed

    Duursma, Remko A; Falster, Daniel S

    2016-10-01

    Here, we aim to understand differences in biomass distribution between major woody plant functional types (PFTs) (deciduous vs evergreen and gymnosperm vs angiosperm) in terms of underlying traits, in particular the leaf mass per area (LMA) and leaf area per unit stem basal area. We used a large compilation of plant biomass and size observations, including observations of 21 084 individuals on 656 species. We used a combination of semiparametric methods and variance partitioning to test the influence of PFT, plant height, LMA, total leaf area, stem basal area and climate on above-ground biomass distribution. The ratio of leaf mass to above-ground woody mass (MF /MS ) varied strongly among PFTs. We found that MF /MS at a given plant height was proportional to LMA across PFTs. As a result, the PFTs did not differ in the amount of leaf area supported per unit above-ground biomass or per unit stem basal area. Climate consistently explained very little additional variation in biomass distribution at a given plant size. Combined, these results demonstrate consistent patterns in above-ground biomass distribution and leaf area relationships among major woody PFTs, which can be used to further constrain global vegetation models. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

  12. Methods for estimating aboveground biomass and its components for five Pacific Northwest tree species

    Treesearch

    Krishna P. Poudel; Temesgen. Hailemariam

    2015-01-01

    Performance of three groups of methods to estimate total and/or component aboveground biomass was evaluated using the data collected from destructively sampled trees in different parts of Oregon. First group of methods used analytical approach to estimate total and component biomass using existing equations, and produced biased estimates for our dataset. The second...

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

    Treesearch

    G.P. Asner; R.F. Hughes; T.A. Varga; D.E. Knapp; T. Kennedy-Bowdoin

    2009-01-01

    The environmental and biotic factors affecting spatial variation in canopy three-dimensional (3-D) structure and aboveground tree biomass (AGB) are poorly understood in tropical rain forests. We combined field measurements and airborne light detection and ranging (lidar) to quantify 3-D structure and AGB across a 5,016 ha rain forest reserve on the...

  14. Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass

    Treesearch

    Timothy G. Gregoire; Erik Næsset; Ronald E. McRoberts; Göran Ståhl; Hans Andersen; Terje Gobakken; Liviu Ene; Ross Nelson

    2016-01-01

    For many decades remotely sensed data have been used as a source of auxiliary information when conducting regional or national surveys of forest resources. In the past decade, airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool for sample surveys aimed at improving estimation of aboveground forest biomass. This technology is now...

  15. Analysis of biophysical and anthropogenic variables and their relation to the regional spatial variation of aboveground biomass illustrated for North and East Kalimantan, Borneo.

    PubMed

    Van der Laan, Carina; Verweij, Pita A; Quiñones, Marcela J; Faaij, André Pc

    2014-12-01

    Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.

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

    Treesearch

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

    2008-01-01

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

  17. Fusion of GEDI, ICESAT2 & NISAR data for above ground biomass mapping in Sonoma County, California

    NASA Astrophysics Data System (ADS)

    Duncanson, L.; Simard, M.; Thomas, N. M.; Neuenschwander, A. L.; Hancock, S.; Armston, J.; Dubayah, R.; Hofton, M. A.; Huang, W.; Tang, H.; Marselis, S.; Fatoyinbo, T.

    2017-12-01

    Several upcoming NASA missions will collect data sensitive to forest structure (GEDI, ICESAT-2 & NISAR). The LiDAR and SAR data collected by these missions will be used in coming years to map forest aboveground biomass at various resolutions. This research focuses on developing and testing multi-sensor data fusion approaches in advance of these missions. Here, we present the first case study of a CMS-16 grant with results from Sonoma County, California. We simulate lidar and SAR datasets from GEDI, ICESAT-2 and NISAR using airborne discrete return lidar and UAVSAR data, respectively. GEDI and ICESAT-2 signals are simulated from high point density discrete return lidar that was acquired over the entire county in 2014 through a previous CMS project (Dubayah & Hurtt, CMS-13). NISAR is simulated from L-band UAVSAR data collected in 2014. These simulations are empirically related to 300 field plots of aboveground biomass as well as a 30m biomass map produced from the 2014 airborne lidar data. We model biomass independently for each simulated mission dataset and then test two fusion methods for County-wide mapping 1) a pixel based approach and 2) an object oriented approach. In the pixel-based approach, GEDI and ICESAT-2 biomass models are calibrated over field plots and applied in orbital simulations for a 2-year period of the GEDI and ICESAT-2 missions. These simulated samples are then used to calibrate UAVSAR data to produce a 0.25 ha map. In the object oriented approach, the GEDI and ICESAT-2 data are identical to the pixel-based approach, but calibrate image objects of similar L-band backscatter rather than uniform pixels. The results of this research demonstrate the estimated ability for each of these three missions to independently map biomass in a temperate, high biomass system, as well as the potential improvement expected through combining mission datasets.

  18. 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.

  19. 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

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

    Treesearch

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

    2008-01-01

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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Xue, Kai; Yuan, Mengting M.; Xie, Jianping

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

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

    DOE PAGES

    Xue, Kai; Yuan, Mengting M.; Xie, Jianping; ...

    2016-09-27

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

  3. 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).

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

    USDA-ARS?s Scientific Manuscript database

    Agroforestry systems have widely been recognized for their potential to foster long-term carbon sequestration in woody perennials. This study aims to determine the above-ground biomass in a 16-year-old red oak (Quercus rubra) - pecan (Carya illinoinensis) silvopastoral planting (141 and 53 trees ha-...

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

    PubMed Central

    Jimenez-Berni, Jose A.; Deery, David M.; Rozas-Larraondo, Pablo; Condon, Anthony (Tony) G.; Rebetzke, Greg J.; James, Richard A.; Bovill, William D.; Furbank, Robert T.; Sirault, Xavier R. R.

    2018-01-01

    Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR (r2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association (r2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass (r2 = 0.93 and r2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new opportunities to

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

    PubMed

    Jimenez-Berni, Jose A; Deery, David M; Rozas-Larraondo, Pablo; Condon, Anthony Tony G; Rebetzke, Greg J; James, Richard A; Bovill, William D; Furbank, Robert T; Sirault, Xavier R R

    2018-01-01

    Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR ( r 2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association ( r 2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass ( r 2 = 0.93 and r 2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Sakici, Oytun Emre; Kucuk, Omer; Ashraf, Muhammad Irfan

    2018-04-15

    Small trees and saplings are important for forest management, carbon stock estimation, ecological modeling, and fire management planning. Turkish pine (Pinus brutia Ten.) is a common coniferous species and comprises 25.1% of total forest area of Turkey. Turkish pine is also important due to its flammable fuel characteristics. In this study, compatible above-ground biomass equations were developed to predict needle, branch, stem wood, and above-ground total biomass, and carbon stock assessment was also described for Turkish pine which is smaller than 8 cm diameter at breast height or shorter than breast height. Compatible biomass equations are useful for biomass prediction of small diameter individuals of Turkish pine. These equations will also be helpful in determining fire behavior characteristics and calculating their carbon stock. Overall, present study will be useful for developing ecological models, forest management plans, silvicultural plans, and fire management plans.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Owers, Christopher J.; Rogers, Kerrylee; Woodroffe, Colin D.

    2018-05-01

    Above-ground biomass represents a small yet significant contributor to carbon storage in coastal wetlands. Despite this, above-ground biomass is often poorly quantified, particularly in areas where vegetation structure is complex. Traditional methods for providing accurate estimates involve harvesting vegetation to develop mangrove allometric equations and quantify saltmarsh biomass in quadrats. However broad scale application of these methods may not capture structural variability in vegetation resulting in a loss of detail and estimates with considerable uncertainty. Terrestrial laser scanning (TLS) collects high resolution three-dimensional point clouds capable of providing detailed structural morphology of vegetation. This study demonstrates that TLS is a suitable non-destructive method for estimating biomass of structurally complex coastal wetland vegetation. We compare volumetric models, 3-D surface reconstruction and rasterised volume, and point cloud elevation histogram modelling techniques to estimate biomass. Our results show that current volumetric modelling approaches for estimating TLS-derived biomass are comparable to traditional mangrove allometrics and saltmarsh harvesting. However, volumetric modelling approaches oversimplify vegetation structure by under-utilising the large amount of structural information provided by the point cloud. The point cloud elevation histogram model presented in this study, as an alternative to volumetric modelling, utilises all of the information within the point cloud, as opposed to sub-sampling based on specific criteria. This method is simple but highly effective for both mangrove (r2 = 0.95) and saltmarsh (r2 > 0.92) vegetation. Our results provide evidence that application of TLS in coastal wetlands is an effective non-destructive method to accurately quantify biomass for structurally complex vegetation.

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

    Treesearch

    D. C. Bragg

    2011-01-01

    Carbon sequestration in forests is a growing area of interest for researchers and land managers. Calculating the quantity of carbon stored in forest biomass seems to be a straightforward task, but it is highly dependent on the function(s) used to construct the stand. For instance, there are a number of possible equations to predict aboveground live biomass for loblolly...

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

    Treesearch

    H. Viana; J. Aranha; D. Lopes; Warren B. Cohen

    2012-01-01

    Spatially crown biomass of Pinus pinaster stands and shrubland above-ground biomass (AGB) estimation was carried-out in a region located in Centre-North Portugal, by means of different approaches including forest inventory data, remotely sensed imagery and spatial prediction models. Two cover types (pine stands and shrubland) were inventoried and...

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

    NASA Astrophysics Data System (ADS)

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

    2018-05-01

    Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%-44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all

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

    PubMed

    Exbrayat, Jean-François; Liu, Yi Y; Williams, Mathew

    2017-11-15

    Since the 1960s, large-scale deforestation in the Amazon Basin has contributed to rising global CO 2 concentrations and to climate change. Recent advances in satellite observations enable estimates of gross losses of above-ground biomass (AGB) stocks due to deforestation. However, because of simultaneous regrowth, the net contribution of deforestation emissions to rising atmospheric CO 2 concentrations is poorly quantified. Climate change may also reduce the potential for forest regeneration in previously disturbed regions. Here, we address these points of uncertainty with a machine-learning approach that combines satellite observations of AGB with climate data across the Amazon Basin to reconstruct annual maps of potential AGB during 1993-2012, the above-ground C storage potential of the undisturbed landscape. We derive a 2.2 Pg C loss of AGB over the study period, and, for the regions where these losses occur, we estimate a 0.7 Pg C reduction in potential AGB. Thus, climate change has led to a decline of ~1/3 in the capacity of these disturbed forests to recover and recapture the C lost in disturbances during 1993-2012. Our approach further shows that annual variations in land use change mask the natural relationship between the El Niño/Southern Oscillation and AGB stocks in disturbed regions.

  15. 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.

  16. National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

    NASA Astrophysics Data System (ADS)

    Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

    2017-12-01

    Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the

  17. 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

  18. 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.

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

    PubMed

    Luo, Xu; Wang, Yu Li; Zhang, Jin Quan

    2018-03-01

    Predicting the effects of climate warming and fire disturbance on forest aboveground biomass is a central task of studies in terrestrial ecosystem carbon cycle. The alteration of temperature, precipitation, and disturbance regimes induced by climate warming will affect the carbon dynamics of forest ecosystem. Boreal forest is an important forest type in China, the responses of which to climate warming and fire disturbance are increasingly obvious. In this study, we used a forest landscape model LANDIS PRO to simulate the effects of climate change on aboveground biomass of boreal forests in the Great Xing'an Mountains, and compared direct effects of climate warming and the effects of climate warming-induced fires on forest aboveground biomass. The results showed that the aboveground biomass in this area increased under climate warming scenarios and fire disturbance scenarios with increased intensity. Under the current climate and fire regime scenario, the aboveground biomass in this area was (97.14±5.78) t·hm -2 , and the value would increase up to (97.93±5.83) t·hm -2 under the B1F2 scenario. Under the A2F3 scenario, aboveground biomass at landscape scale was relatively higher at the simulated periods of year 100-150 and year 150-200, and the value were (100.02±3.76) t·hm -2 and (110.56±4.08) t·hm -2 , respectively. Compared to the current fire regime scenario, the predicted biomass at landscape scale was increased by (0.56±1.45) t·hm -2 under the CF2 scenario (fire intensity increased by 30%) at some simulated periods, and the aboveground biomass was reduced by (7.39±1.79) t·hm -2 in CF3 scenario (fire intensity increased by 230%) at the entire simulation period. There were significantly different responses between coniferous and broadleaved species under future climate warming scenarios, in that the simulated biomass for both Larix gmelinii and Betula platyphylla showed decreasing trend with climate change, whereas the simulated biomass for Pinus

  20. 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.

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

    USGS Publications Warehouse

    Ji, Lei; Wylie, Bruce K.; Brown, Dana R. N.; Peterson, Birgit E.; Alexander, Heather D.; Mack, Michelle C.; Rover, Jennifer R.; Waldrop, Mark P.; McFarland, Jack W.; Chen, Xuexia; Pastick, Neal J.

    2015-01-01

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

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

    Treesearch

    Katherine J. Elliott; Lindsay R. Boring; Wayne T. Swank

    2002-01-01

    In 1975, we initiated a long-term interdisciplinary study of forest watershed ecosystem response to clear- cutting and cable logging in watershed 7 at the Coweeta Hydrologic Laboratory in the southern Appalachian Mountains of North Carolina. This paper describes ~20 years of change in species composition, aboveground biomass, leaf area index (LAI),...

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

    Treesearch

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

    2008-01-01

    We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

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

    NASA Astrophysics Data System (ADS)

    Holmquist, J. R.; Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Windham-Myers, L.; Thomas, N.

    2017-12-01

    Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our goal was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). To meet this objective we developed the first national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest algorithm we tested Sentinel-1 radar backscatter metrics and Landsat vegetation indices as predictors of biomass. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n=409, RMSE=310 g/m2, 10.3% normalized RMSE), successfully predicted biomass and carbon for a range of marsh plant functional types defined by height, leaf angle and growth form. Model error was reduced by scaling field measured biomass by Landsat fraction green vegetation derived from object-based classification of National Agriculture Imagery Program imagery. We generated 30m resolution biomass maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map for each region. With a mean plant %C of 44.1% (n=1384, 95% C.I.=43.99% - 44.37%) we estimated mean aboveground carbon densities (Mg/ha) and total carbon stocks for each wetland type for each region. Louisiana palustrine emergent marshes had the highest C density (2.67 ±0.08 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ±0.06 Mg/ha). This modeling and data synthesis effort will allow for aboveground

  5. Forest biomass mapping from fusion of GEDI Lidar data and TanDEM-X InSAR data

    NASA Astrophysics Data System (ADS)

    Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.

    2017-12-01

    Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910

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

    USGS Publications Warehouse

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

    2018-01-01

    Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%–44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had

  7. Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines

    PubMed Central

    Singh, Minerva; Friess, Daniel A.; Vilela, Bruno; Alban, Jose Don T. De; Monzon, Angelica Kristina V.; Veridiano, Rizza Karen A.; Tumaneng, Roven D.

    2017-01-01

    This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species. PMID:29206228

  8. Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines.

    PubMed

    Singh, Minerva; Friess, Daniel A; Vilela, Bruno; Alban, Jose Don T De; Monzon, Angelica Kristina V; Veridiano, Rizza Karen A; Tumaneng, Roven D

    2017-01-01

    This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species.

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

    Treesearch

    Heather D. Vance-Chalcraft; Michael R. Willig; Stephen B. Cox; Ariel E. Lugo; Frederick N. Scatena

    2010-01-01

    Anthropogenic activities have accelerated the rate of global loss of biodiversity, making it more important than ever to understand the structure of biodiversity hotspots. One current focus is the relationship between species richness and aboveground biomass (AGB) in a variety of ecosystems. Nonetheless, species diversity, evenness, rarity, or dominance represent other...

  10. [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.

  11. Non-pulp utilization of above-ground biomass of mixed-species forests of small trees

    Treesearch

    P. Koch

    1982-01-01

    This soulution propose to rehabilitate annually- by clear felling, site preparation, and planting- 25,000 acres of level to rolling land averaging about490 cubic feet per acre of stemwood in small hardwood trees 5 inches in diameter at breast height (dbh) and larger, and of many species, plus all equal volume of above-ground biomass in stembark and tops, and in trees...

  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.

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

    Treesearch

    Callie Schweitzer; Dawn Lemke; Wubishet Tadesse; Yong Wang

    2015-01-01

    Forests contain a large amount of carbon (C) stored as tree biomass (above and below ground), detritus, and soil organic material. The aboveground tree biomass is the most rapid change component in this forest C pool. Thus, management of forest resources can influence the net C exchange with the atmosphere by changing the amount of C stored, particularly in landscapes...

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

    PubMed

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

    2014-01-01

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

  15. 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

  16. 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

  17. Effect of thinning on partitioning of aboveground biomass in naturally regenerated shortleaf pine (Pinus echinata mill.)

    Treesearch

    Charles O. Sabatia; Rodney E. Will; Thomas B. Lynch

    2010-01-01

    In traditional harvesting systems, yield of forest stands may increase if a greater proportion of net primary production is allocated to bole wood. However, for management related to whole-tree harvesting, carbon sequestration, biofuels, and wildland fire avoidance, assessments of biomass partitioning to all aboveground components is needed. Thinning increases bole...

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

    PubMed

    Melito, Melina; Metzger, Jean Paul; de Oliveira, Alexandre A

    2018-02-01

    Despite the general recognition that fragmentation can reduce forest biomass through edge effects, a systematic review of the literature does not reveal a clear role of edges in modulating biomass loss. Additionally, the edge effects appear to be constrained by matrix type, suggesting that landscape composition has an influence on biomass stocks. The lack of empirical evidence of pervasive edge-related biomass losses across tropical forests highlights the necessity for a general framework linking landscape structure with aboveground biomass. Here, we propose a conceptual model in which landscape composition and configuration mediate the magnitude of edge effects and seed-flux among forest patches, which ultimately has an influence on biomass. Our model hypothesizes that a rapid reduction of biomass can occur below a threshold of forest cover loss. Just below this threshold, we predict that changes in landscape configuration can strongly influence the patch's isolation, thus enhancing biomass loss. Moreover, we expect a synergism between landscape composition and patch attributes, where matrix type mediates the effects of edges on species decline, particularly for shade-tolerant species. To test our conceptual framework, we propose a sampling protocol where the effects of edges, forest amount, forest isolation, fragment size, and matrix type on biomass stocks can be assessed both collectively and individually. The proposed model unifies the combined effects of landscape and patch structure on biomass into a single framework, providing a new set of main drivers of biomass loss in human-modified landscapes. We argue that carbon trading agendas (e.g., REDD+) and carbon-conservation initiatives must go beyond the effects of forest loss and edges on biomass, considering the whole set of effects on biomass related to changes in landscape composition and configuration. © 2017 John Wiley & Sons Ltd.

  19. Above-ground biomass prediction by Sentinel-1 multitemporal data in central Italy with integration of ALOS2 and Sentinel-2 data

    NASA Astrophysics Data System (ADS)

    Laurin, Gaia Vaglio; Balling, Johannes; Corona, Piermaria; Mattioli, Walter; Papale, Dario; Puletti, Nicola; Rizzo, Maria; Truckenbrodt, John; Urban, Marcel

    2018-01-01

    The objective of this research is to test Sentinel-1 SAR multitemporal data, supported by multispectral and SAR data at other wavelengths, for fine-scale mapping of above-ground biomass (AGB) at the provincial level in a Mediterranean forested landscape. The regression results indicate good accuracy of prediction (R2=0.7) using integrated sensors when an upper bound of 400 Mg ha-1 is used in modeling. Multitemporal SAR information was relevant, allowing the selection of optimal Sentinel-1 data, as broadleaf forests showed a different response in backscatter throughout the year. Similar accuracy in predictions was obtained when using SAR multifrequency data or joint SAR and optical data. Predictions based on SAR data were more conservative, and in line with those from an independent sample from the National Forest Inventory, than those based on joint data types. The potential of S1 data in predicting AGB can possibly be improved if models are developed per specific groups (deciduous or evergreen species) or forest types and using a larger range of ground data. Overall, this research shows the usefulness of Sentinel-1 data to map biomass at very high resolution for local study and at considerable carbon density.

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

    NASA Astrophysics Data System (ADS)

    Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

    2017-07-01

    Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

  1. Species richness alters spatial nutrient heterogeneity effects on above-ground plant biomass.

    PubMed

    Xi, Nianxun; Zhang, Chunhui; Bloor, Juliette M G

    2017-12-01

    Previous studies have suggested that spatial nutrient heterogeneity promotes plant nutrient capture and growth. However, little is known about how spatial nutrient heterogeneity interacts with key community attributes to affect plant community production. We conducted a meta-analysis to investigate how nitrogen heterogeneity effects vary with species richness and plant density. Effect size was calculated using the natural log of the ratio in plant biomass between heterogeneous and homogeneous conditions. Effect sizes were significantly above zero, reflecting positive effects of spatial nutrient heterogeneity on community production. However, species richness decreased the magnitude of heterogeneity effects on above-ground biomass. The magnitude of heterogeneity effects on below-ground biomass did not vary with species richness. Moreover, we detected no modification in heterogeneity effects with plant density. Our results highlight the importance of species richness for ecosystem function. Asynchrony between above- and below-ground responses to spatial nutrient heterogeneity and species richness could have significant implications for biotic interactions and biogeochemical cycling in the long term. © 2017 The Author(s).

  2. 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.

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

    Treesearch

    Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann

    2010-01-01

    Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...

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

    PubMed

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

    2013-05-01

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

  5. 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

  6. Improving Lidar-based Aboveground Biomass Estimation with Site Productivity for Central Hardwood Forests, USA

    NASA Astrophysics Data System (ADS)

    Shao, G.; Gallion, J.; Fei, S.

    2016-12-01

    Sound forest aboveground biomass estimation is required to monitor diverse forest ecosystems and their impacts on the changing climate. Lidar-based regression models provided promised biomass estimations in most forest ecosystems. However, considerable uncertainties of biomass estimations have been reported in the temperate hardwood and hardwood-dominated mixed forests. Varied site productivities in temperate hardwood forests largely diversified height and diameter growth rates, which significantly reduced the correlation between tree height and diameter at breast height (DBH) in mature and complex forests. It is, therefore, difficult to utilize height-based lidar metrics to predict DBH-based field-measured biomass through a simple regression model regardless the variation of site productivity. In this study, we established a multi-dimension nonlinear regression model incorporating lidar metrics and site productivity classes derived from soil features. In the regression model, lidar metrics provided horizontal and vertical structural information and productivity classes differentiated good and poor forest sites. The selection and combination of lidar metrics were discussed. Multiple regression models were employed and compared. Uncertainty analysis was applied to the best fit model. The effects of site productivity on the lidar-based biomass model were addressed.

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

    Treesearch

    Jennifer C. Jenkins; Richard A. Birdsey

    2000-01-01

    As interest grows in the role of forest growth in the carbon cycle, and as simulation models are applied to predict future forest productivity at large spatial scales, the need for reliable and field-based data for evaluation of model estimates is clear. We created estimates of potential forest biomass and annual aboveground production for the Chesapeake Bay watershed...

  8. Using Landsat Time-Series and LiDAR to Inform Aboveground Forest Biomass Baselines in Northern Minnesota, USA

    Treesearch

    Ram K. Deo; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Michael J. Falkowski; Warren B. Cohen

    2017-01-01

    The publicly accessible archive of Landsat imagery and increasing regional-scale LiDAR acquisitions offer an opportunity to periodically estimate aboveground forest biomass (AGB) from 1990 to the present to alignwith the reporting needs ofNationalGreenhouseGas Inventories (NGHGIs). This study integrated Landsat time-series data, a state-wide LiDAR dataset, and a recent...

  9. 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

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

    Treesearch

    Kevin M. Potter; Christopher W. Woodall

    2014-01-01

    Biodiversity conveys numerous functional benefits to forested ecosystems, including community stability and resilience. In the context of managing forests for climate change mitigation/adaptation, maximizing and/or maintaining aboveground biomass will require understanding the interactions between tree biodiversity, site productivity, and the stocking of live trees....

  11. Modeling Above-Ground Biomass Across Multiple Circum-Arctic Tundra Sites Using High Spatial Resolution Remote Sensing

    NASA Astrophysics Data System (ADS)

    Räsänen, Aleksi; Juutinen, Sari; Aurela, Mika; Virtanen, Tarmo

    2017-04-01

    Biomass is one of the central bio-geophysical variables in Earth observation for tracking plant productivity, and flow of carbon, nutrients, and water. Most of the satellite based biomass mapping exercises in Arctic environments have been performed by using rather coarse spatial resolution data, e.g. Landsat and AVHRR which have spatial resolutions of 30 m and >1 km, respectively. While the coarse resolution images have high temporal resolution, they are incapable of capturing the fragmented nature of tundra environment and fine-scale changes in vegetation and carbon exchange patterns. Very high spatial resolution (VHSR, spatial resolution 0.5-2 m) satellite images have the potential to detect environmental variables with an ecologically sound spatial resolution. The usage of VHSR images has, nevertheless, been modest so far in biomass modeling in the Arctic. Our objectives were to use VHSR for predicting above ground biomass in tundra landscapes, evaluate whether a common predictive model can be applied across circum-Arctic tundra and peatland sites having different types of vegetation, and produce knowledge on distribution of plant functional types (PFT) in these sites. Such model development is dependent on ground-based surveys of vegetation with the same spatial resolution and extent with the VHSR images. In this study, we conducted ground-based surveys of vegetation composition and biomass in four different arctic tundra or peatland areas located in Russia, Canada, and Finland. First, we sorted species into PFTs and developed PFT-specific models to predict biomass on the basis of non-destructive measurements (cover, height). Second, we predicted overall biomass on landscape scale by combinations of single bands and vegetation indices of very high resolution satellite images (QuickBird or WorldView-2 images of the eight sites). We compared area-specific empirical regression models and common models that were applied across all sites. We found that NDVI was

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

    PubMed

    Li, Hai-Feng; Zeng, Fan-Jiang; Gui, Dong-Wei; An, Gui-Xiang; Liu, Zhen; Zhang, Li-Gang; Liu, Bo

    2012-01-01

    Taking Cele oasis at the southern fringe of Taklimakan Desert as a case, this paper studied the effects of different disturbances (burning in spring, cutting in spring, and cutting in fall) on the morphological characteristics and aboveground biomass of natural vegetation Alhagi sparsifolia in the ecotone of oasis-desert. Burning in spring decreased the A. sparsifolia plant height, crown width, and biomass significantly, being harmful to the regeneration and growth of the vegetation. Cutting in spring decreased the A. sparsifolia plant height, crown width, and biomass but increased the leaf biomass, thorn length, and thorn diameter, whereas cutting in fall decreased the plant height and crown width but increased the ramification amount and biomass of A. sparsifolia. Moderate cutting in fall could benefit the protection of A. sparsifolia at the southern fringe of Taklimakan Desert.

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

    Treesearch

    Ross Nelson; Hank Margolis; Paul Montesano; Guoqing Sun; Bruce Cook; Larry Corp; Hans-Erik Andersen; Ben deJong; Fernando Paz Pellat; Thaddeus Fickel; Jobriath Kauffman; Stephen Prisley

    2017-01-01

    Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar...

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

    Treesearch

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

    2008-01-01

    We combined satellite (Landsat 7 and Moderate Resolution Imaging Spectrometer) and U.S. Department of Agriculture forest inventory and analysis (FIA) data to estimate forest aboveground biomass (AGB) across New England, USA. This is practical for large-scale carbon studies and may reduce uncertainty of AGB estimates. We estimate that total regional forest AGB was 1,867...

  15. Spatial relationships among species, above-ground biomass, N, and P in degraded grasslands in Ordus Plateau, northwestern China

    Treesearch

    X. Cheng; S. An; J. chen; B. Li; Y. Liu; S. Liu

    2007-01-01

    We chose five communities, representing a mild to severe gradient of grassland desertification in a semi-arid area of Ordos Plateau, northwestern China, to explore the spatial relationships among plant species, above-ground biomass (AGB), and plant nutrients (N and P). Community 1 (Cl) was dominated by Stipa bungeana; community 2 (C2) by a mix of S...

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

    PubMed

    Lü, Xiao-Tao; Tang, Jian-Wei; Feng, Zhi-Li; Li, Mai-He

    2009-01-01

    Lianas are important components of tropical forests and have significant impacts on the diversity, structure and dynamics of tropical forests. The present study documented the liana flora in a Chinese tropical region. Species richness, abundance, size-class distribution and spatial patterns of lianas were investigated in three 1-ha plots in tropical seasonal rain forests in Xishuangbanna, SW China. All lianas with > or = 2 cm diameter at breast height (dbh) were measured, tagged and identified. A total of 458 liana stems belonging to 95 species (ranging from 38 to 50 species/ha), 59 genera and 32 families were recorded in the three plots. The most well-represented families were Loganiaceae, Annonceae, Papilionaceae, Apocynaceae and Rhamnaceae. Papilionaceae (14 species recorded) was the most important family in the study forests. The population density, basal area and importance value index (IVI) varied greatly across the three plots. Strychnos cathayensis, Byttneria grandifolia and Bousigonia mekongensis were the dominant species in terms of IVI across the three plots. The mean aboveground biomass of lianas (3 396 kg/ha) accounted for 1.4% of the total community above-ground biomass. The abundance, diversity and biomass of lianas in Xishuangbanna tropical seasonal rain forests are lower than those in tropical moist and wet forests, but higher than those in tropical dry forests. This study provides new data on lianas from a geographical region that has been little-studied. Our findings emphasize that other factors beyond the amount and seasonality of precipitation should be included when considering the liana abundance patterns across scales.

  17. 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.

  18. Forest biomass change estimated from height change in interferometric SAR height models.

    PubMed

    Solberg, Svein; Næsset, Erik; Gobakken, Terje; Bollandsås, Ole-Martin

    2014-12-01

    There is a need for new satellite remote sensing methods for monitoring tropical forest carbon stocks. Advanced RADAR instruments on board satellites can contribute with novel methods. RADARs can see through clouds, and furthermore, by applying stereo RADAR imaging we can measure forest height and its changes. Such height changes are related to carbon stock changes in the biomass. We here apply data from the current Tandem-X satellite mission, where two RADAR equipped satellites go in close formation providing stereo imaging. We combine that with similar data acquired with one of the space shuttles in the year 2000, i.e. the so-called SRTM mission. We derive height information from a RADAR image pair using a method called interferometry. We demonstrate an approach for REDD based on interferometry data from a boreal forest in Norway. We fitted a model to the data where above-ground biomass in the forest increases with 15 t/ha for every m increase of the height of the RADAR echo. When the RADAR echo is at the ground the estimated biomass is zero, and when it is 20 m above the ground the estimated above-ground biomass is 300 t/ha. Using this model we obtained fairly accurate estimates of biomass changes from 2000 to 2011. For 200 m 2 plots we obtained an accuracy of 65 t/ha, which corresponds to 50% of the mean above-ground biomass value. We also demonstrate that this method can be applied without having accurate terrain heights and without having former in-situ biomass data, both of which are generally lacking in tropical countries. The gain in accuracy was marginal when we included such data in the estimation. Finally, we demonstrate that logging and other biomass changes can be accurately mapped. A biomass change map based on interferometry corresponded well to a very accurate map derived from repeated scanning with airborne laser. Satellite based, stereo imaging with advanced RADAR instruments appears to be a promising method for REDD. Interferometric

  19. Multi-Scale Mapping of Vegetation Biomass

    NASA Astrophysics Data System (ADS)

    Hudak, A. T.; Fekety, P.; Falkowski, M. J.; Kennedy, R. E.; Crookston, N.; Smith, A. M.; Mahoney, P.; Glenn, N. F.; Dong, J.; Kane, V. R.; Woodall, C. W.

    2016-12-01

    Vegetation biomass mapping at multiple scales is important for carbon inventory and monitoring, reporting, and verification (MRV). Project-level lidar collections allow biomass estimation with high confidence where associated with field plot measurements. Predictive models developed from such datasets are customarily used to generate landscape-scale biomass maps. We tested the feasibility of predicting biomass in landscapes surveyed with lidar but without field plots, by withholding plot datasets from a reduced model applied to the landscapes, and found support for a generalized model in the northern Idaho ecoregion. We are also upscaling a generalized model to all forested lands in Idaho. Our regional modeling approach is to sample the 30-m biomass predictions from the landscape-scale maps and use them to train a regional biomass model, using Landsat time series, topographic derivatives, and climate variables as predictors. Our regional map validation approach is to aggregate the regional, annual biomass predictions to the county level and compare them to annual county-level biomass summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. A national-scale forest cover map generated independently from 2010 PALSAR data at 25-m resolution is being used to mask non-forest pixels from the aggregations. Effects of climate change on future regional biomass stores are also being explored, using biomass estimates projected from stand-level inventory data collected in the National Forests and comparing them to FIA plot data collected independently on public and private lands, projected under the same climate change scenarios, with disturbance trends extracted from the Landsat time series. Our ultimate goal is to demonstrate, focusing on the ecologically diverse Northwest region of the USA, a carbon monitoring system (CMS) that is accurate, objective, repeatable, and transparent.

  20. 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.

  1. The effect of topography on arctic-alpine aboveground biomass and NDVI patterns

    NASA Astrophysics Data System (ADS)

    Riihimäki, Henri; Heiskanen, Janne; Luoto, Miska

    2017-04-01

    Topography is a key factor affecting numerous environmental phenomena, including Arctic and alpine aboveground biomass (AGB) distribution. Digital Elevation Model (DEM) is a source of topographic information which can be linked to local growing conditions. Here, we investigated the effect of DEM derived variables, namely elevation, topographic position, radiation and wetness on AGB and Normalized Difference Vegetation Index (NDVI) in a Fennoscandian forest-alpine tundra ecotone. Boosted regression trees were used to derive non-parametric response curves and relative influences of the explanatory variables. Elevation and potential incoming solar radiation were the most important explanatory variables for both AGB and NDVI. In the NDVI models, the response curves were smooth compared with AGB models. This might be caused by large contribution of field and shrub layer to NDVI, especially at the treeline. Furthermore, radiation and elevation had a significant interaction, showing that the highest NDVI and biomass values are found from low-elevation, high-radiation sites, typically on the south-southwest facing valley slopes. Topographic wetness had minor influence on AGB and NDVI. Topographic position had generally weak effects on AGB and NDVI, although protected topographic position seemed to be more favorable below the treeline. The explanatory power of the topographic variables, particularly elevation and radiation demonstrates that DEM-derived land surface parameters can be used for exploring biomass distribution resulting from landform control on local growing conditions.

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

    Treesearch

    Christopher W. Woodall; Linda S. Heath; Grant M. Domke; Michael C. Nichols

    2011-01-01

    The U.S. Forest Service, Forest Inventory and Analysis (FIA) program uses numerous models and associated coefficients to estimate aboveground volume, biomass, and carbon for live and standing dead trees for most tree species in forests of the United States. The tree attribute models are coupled with FIA's national inventory of sampled trees to produce estimates of...

  3. 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

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

    PubMed

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

    2016-04-01

    Understanding the role of individual organisms in whole-ecosystem carbon (C) fluxes is probably the biggest current challenge in C cycle research. Thus, it is unknown whether different plant community members share the same or different residence times in metabolic (τmetab ) and nonmetabolic (i.e. structural) (τnonmetab ) C pools of aboveground biomass and the fraction of fixed C allocated to aboveground nonmetabolic biomass (Anonmetab ). We assessed τmetab , τnonmetab and Anonmetab of co-dominant species from different functional groups (two bunchgrasses, a stoloniferous legume and a rosette dicot) in a temperate grassland community. Continuous, 14-16-d-long (13) C-labeling experiments were performed in September 2006, May 2007 and September 2007. A two-pool compartmental system, with a well-mixed metabolic and a nonmixed nonmetabolic pool, was the simplest biologically meaningful model that fitted the (13) C tracer kinetics in the whole-shoot biomass of all species. In all experimental periods, the species had similar τmetab (5-8 d), whereas τnonmetab ranged from 20 to 58 d (except for one outlier) and Anonmetab from 7 to 45%. Variations in τnonmetab and Anonmetab were not systematically associated with species or experimental periods, but exhibited relationships with leaf life span, particularly in the grasses. Similar pool kinetics of species suggested similar kinetics at the community level. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

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

    Treesearch

    Robert M. Hubbard; James M. Vose; Barton D. Clinton; Katherine J. Elliott; Jennifer D. Knoepp

    2004-01-01

    Understory prescribed burning is being suggested as a viable management tool for restoring degraded oak–pine forest communities in the southern Appalachians yet information is lacking on how this will affect ecosystem processes. Our objectives in this study were to evaluate the watershed scale effects of understory burning on total aboveground biomass, and the carbon...

  6. 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

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

    NASA Astrophysics Data System (ADS)

    Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

    2018-04-01

    Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted

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

    PubMed

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

    2011-12-01

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

  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. Dissecting variation in biomass conversion factors across China's forests: implications for biomass and carbon accounting.

    PubMed

    Luo, Yunjian; Zhang, Xiaoquan; Wang, Xiaoke; Ren, Yin

    2014-01-01

    Biomass conversion factors (BCFs, defined as the ratios of tree components (i.e. stem, branch, foliage and root), as well as aboveground and whole biomass of trees to growing stock volume, Mg m-3) are considered as important parameters in large-scale forest biomass carbon estimation. To date, knowledge of possible sources of the variation in BCFs is still limited at large scales. Using our compiled forest biomass dataset of China, we presented forest type-specific values of BCFs, and examined the variation in BCFs in relation to forest type, stand development and environmental factors (climate and soil fertility). BCFs exhibited remarkable variation across forest types, and also were significantly related to stand development (especially growing stock volume). BCFs (except Stem BCF) had significant relationships with mean annual temperature (MAT) and mean annual precipitation (MAP) (P<0.001). Climatic data (MAT and MAP) collectively explained 10.0-25.0% of the variation in BCFs (except Stem BCFs). Moreover, stronger climatic effects were found on BCFs for functional components (i.e. branch, foliage and root) than BCFs for combined components (i.e. aboveground section and whole trees). A general trend for BCFs was observed to decrease and then increase from low to high soil fertility. When qualitative soil fertility and climatic data (MAT and MAP) were combined, they explained 14.1-29.7% of the variation in in BCFs (except Stem BCFs), adding only 4.1-4.9% than climatic data used. Therefore, to reduce the uncertainty induced by BCFs in forest carbon estimates, we should apply values of BCFs for a specified forest type, and also consider climatic and edaphic effects, especially climatic effect, in developing predictive models of BCFs (except Stem BCF).

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

    USGS Publications Warehouse

    Li, Aihua; Dhakal, Shital; Glenn, Nancy F.; Spaete, Luke P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan

    2017-01-01

    Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure

  12. 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

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

    PubMed

    Dai, Er Fu; Zhou, Heng; Wu, Zhuo; Wang, Xiao-Fan; Xi, Wei Min; Zhu, Jian Jia

    2016-10-01

    Global climate warming has significant effect on territorial ecosystem, especially on forest ecosystem. The increase in temperature and radiative forcing will significantly alter the structure and function of forest ecosystem. The southern plantation is an important part of forests in China, its response to climate change is getting more and more intense. In order to explore the responses of southern plantation to climate change under future climate scenarios and to reduce the losses that might be caused by climate change, we used climatic estimated data under three new emission scenarios, representative concentration pathways (RCPs) scenarios (RCP2.6 scenario, RCP4.5 scenario, and RCP8.5 scenario). We used the spatially dynamic forest landscape model LANDIS-2, coupled with a forest ecosystem process model PnET-2, to simulate the impact of climate change on aboveground net primary production (ANPP), species' establishment probability (SEP) and aboveground biomass of Moshao forest farm in Huitong Ecological Station, which located in Hunan Province during the period of 2014-2094. The results showed that there were obvious differences in SEP and ANPP among different forest types under changing climate. The degrees of response of SEP to climate change for different forest types were shown as: under RCP2.6 and RCP4.5, artificial coniferous forest>natural broadleaved forest>artificial broadleaved forest. Under RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The degrees of response of ANPP to climate change for different forest types were shown as: under RCP2.6, artificial broadleaved forest> natural broadleaved forest>artificial coniferous forest. Under RCP4.5 and RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The aboveground biomass of the artificial coniferous forest would decline at about 2050, but the natural broadleaved forest and artificial broadleaved forest showed a

  14. Biomass energy inventory and mapping system

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kasile, J.D.

    1993-12-31

    A four-stage biomass energy inventory and mapping system was conducted for the entire State of Ohio. The product is a set of maps and an inventory of the State of Ohio. The set of amps and an inventory of the State`s energy biomass resource are to a one kilometer grid square basis on the Universal Transverse Mercator (UTM) system. Each square kilometer is identified and mapped showing total British Thermal Unit (BTU) energy availability. Land cover percentages and BTU values are provided for each of nine biomass strata types for each one kilometer grid square. LANDSAT satellite data was usedmore » as the primary stratifier. The second stage sampling was the photointerpretation of randomly selected one kilometer grid squares that exactly corresponded to the LANDSAT one kilometer grid square classification orientation. Field sampling comprised the third stage of the energy biomass inventory system and was combined with the fourth stage sample of laboratory biomass energy analysis using a Bomb calorimeter and was then used to assign BTU values to the photointerpretation and to adjust the LANDSAT classification. The sampling error for the whole system was 3.91%.« less

  15. Dissecting Variation in Biomass Conversion Factors across China’s Forests: Implications for Biomass and Carbon Accounting

    PubMed Central

    Wang, Xiaoke; Ren, Yin

    2014-01-01

    Biomass conversion factors (BCFs, defined as the ratios of tree components (i.e. stem, branch, foliage and root), as well as aboveground and whole biomass of trees to growing stock volume, Mg m−3) are considered as important parameters in large-scale forest biomass carbon estimation. To date, knowledge of possible sources of the variation in BCFs is still limited at large scales. Using our compiled forest biomass dataset of China, we presented forest type-specific values of BCFs, and examined the variation in BCFs in relation to forest type, stand development and environmental factors (climate and soil fertility). BCFs exhibited remarkable variation across forest types, and also were significantly related to stand development (especially growing stock volume). BCFs (except Stem BCF) had significant relationships with mean annual temperature (MAT) and mean annual precipitation (MAP) (P<0.001). Climatic data (MAT and MAP) collectively explained 10.0–25.0% of the variation in BCFs (except Stem BCFs). Moreover, stronger climatic effects were found on BCFs for functional components (i.e. branch, foliage and root) than BCFs for combined components (i.e. aboveground section and whole trees). A general trend for BCFs was observed to decrease and then increase from low to high soil fertility. When qualitative soil fertility and climatic data (MAT and MAP) were combined, they explained 14.1–29.7% of the variation in in BCFs (except Stem BCFs), adding only 4.1–4.9% than climatic data used. Therefore, to reduce the uncertainty induced by BCFs in forest carbon estimates, we should apply values of BCFs for a specified forest type, and also consider climatic and edaphic effects, especially climatic effect, in developing predictive models of BCFs (except Stem BCF). PMID:24728222

  16. Large-area Mapping of Forest Cover and Biomass using ALOS PALSAR

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    In the frame of a Pantropical mapping project, we aim at producing high-resolution forest cover maps from ALOS PALSAR. The ALOS data was obtained through the Americas ALOS Data Node (AADN) at ASF. For the forest cover classification, a pan-tropical network of calibrated reference data was generated from ancillary satellite data (ICESAT GLAS). These data are used to classify PALSAR swath data to be combined to continental forest probability maps. The maps are validated with withheld training data for testing, as well as through independent operator verification with very high-resolution image. In addition, we aim at developing robust algorithms for the mapping of forest biophysical parameters like stem volume or biomass using synergy of PALSAR, optical and Lidar data. Currently we are testing different approaches for the mapping of forest biophysical parameters. 1) For the showcase scenario of Mexico, where we have access to ~1400 PALSAR FBD images as well as the 30 m Landsat Vegetation Continuous Field product, VCF, we test a traditional ground-data based approach. The PALSAR HH/HV intensity data and VCF are used as predictor layers in RandomForest for predicting aboveground forest biomass. A network of 40000 in situ biomass plots is used for model development (for each PALSAR swath) as well as for validation. With this approach a first 30 m biomass map for entire Mexico was produced. An initial validation of the map resulted in an RMSE of 41 t/ha and an R2 of 0.42. Pronounced differences between different ecozones were observed. In some areas the retrieval reached an R2 of 0.6 (e.g. pine-oak forests) whereas, for instance, in dry woodlands, the retrieval accuracy was much lower (R2 of 0.1). A major limitation of the approach was also represented by the fact that for the development of models for each ALOS swath, in some cases too few sample plots were available. 2) Chile: At a forest site in Central Chile, dominated by plantations of pinus radiata, synergy of ALOS

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    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 landmore » 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.« less

  18. 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.

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

    Treesearch

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Li, F.; Zeng, Y.; Chen, J.; Wu, B.

    2017-12-01

    Plant biomass is the most critical measure of carbon stored in an ecosystem, yet it remains imprecisely modeled for many terrestrial biomes. This lack of modeling capacity for biomass and its change through time and space has impeded scientists from making headway concerning issues in the geographic and social sciences. Satellite remote sensing techniques excel at detecting changes in the Earth's surface; however, accurate estimates of biomass for the heterogeneous biome landscapes based on remote sensing techniques are few and far between, which has led to many repetitive studies. Here, we argued that our ability to assess biomass in a heterogeneous landscape using satellite remote sensing techniques would be effectively enhanced through a stratification of landscapes, i.e homogenizing landscapes. Specifically, above-ground biomass (AGB) for an extended heterogeneous grassland biome over the entirety of Inner Mongolia during the past 16 years (2001-2016) was explored using remote sensing time series data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Massive and extensive in-situ measurement AGB data and pure vegetation index (PVI) models, developed from normal remote sensing vegetation indices such as the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI), were highlighted in the accomplishment of this study. Taking into full consideration the landscape heterogeneity for the grassland biome over Inner Mongolia, we achieved a series of AGB models with high R2 (>0.85) and low RMSE ( 20.85 g/m2). The total average amount of fresh AGB for the entirety of Inner Mongolia grasslands over the past 16 years was estimated as 87 Tg with an inter-annual standard deviation of 9 Tg. Overall, the grassland AGB for Inner Mongolia increased sporadically. We found that the dynamics of AGB in the grassland biome of Inner Mongolia were substantially dominated by variation in precipitation despite the accommodation of a huge

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

    NASA Astrophysics Data System (ADS)

    Luo, Shezhou; Wang, Cheng; Xi, Xiaohuan; Pan, Feifei; Qian, Mingjie; Peng, Dailiang; Nie, Sheng; Qin, Haiming; Lin, Yi

    2017-06-01

    Wetland biomass is essential for monitoring the stability and productivity of wetland ecosystems. Conventional field methods to measure or estimate wetland biomass are accurate and reliable, but expensive, time consuming and labor intensive. This research explored the potential for estimating wetland reed biomass using a combination of airborne discrete-return Light Detection and Ranging (LiDAR) and hyperspectral data. To derive the optimal predictor variables of reed biomass, a range of LiDAR and hyperspectral metrics at different spatial scales were regressed against the field-observed biomasses. The results showed that the LiDAR-derived H_p99 (99th percentile of the LiDAR height) and hyperspectral-calculated modified soil-adjusted vegetation index (MSAVI) were the best metrics for estimating reed biomass using the single regression model. Although the LiDAR data yielded a higher estimation accuracy compared to the hyperspectral data, the combination of LiDAR and hyperspectral data produced a more accurate prediction model for reed biomass (R2 = 0.648, RMSE = 167.546 g/m2, RMSEr = 20.71%) than LiDAR data alone. Thus, combining LiDAR data with hyperspectral data has a great potential for improving the accuracy of aboveground biomass estimation.

  2. A New Synthetic Global Biomass Carbon Map for the year 2010

    NASA Astrophysics Data System (ADS)

    Spawn, S.; Lark, T.; Gibbs, H.

    2017-12-01

    Satellite technologies have facilitated a recent boom in high resolution, large-scale biomass estimation and mapping. These data are the input into a wide range of global models and are becoming the gold standard for required national carbon (C) emissions reporting. Yet their geographical and/or thematic scope may exclude some or all parts of a given country or region. Most datasets tend to focus exclusively on forest biomass. Grasslands and shrublands generally store less C than forests but cover nearly twice as much global land area and may represent a significant portion of a given country's biomass C stock. To address these shortcomings, we set out to create synthetic, global above- and below-ground biomass maps that combine recently-released satellite based data of standing forest biomass with novel estimates for non-forest biomass stocks that are typically neglected. For forests we integrated existing publicly available regional, global and biome-specific biomass maps and modeled below ground biomass using empirical relationships described in the literature. For grasslands, we developed models for both above- and below-ground biomass based on NPP, mean annual temperature and precipitation to extrapolate field measurements across the globe. Shrubland biomass was extrapolated from existing regional biomass maps using environmental factors to generate the first global estimate of shrub biomass. Our new synthetic map of global biomass carbon circa 2010 represents an update to the IPCC Tier-1 Global Biomass Carbon Map for the Year 2000 (Ruesch and Gibbs, 2008) using the best data currently available. In the absence of a single seamless remotely sensed map of global biomass, our synthetic map provides the only globally-consistent source of comprehensive biomass C data and is valuable for land change analyses, carbon accounting, and emissions modeling.

  3. 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

  4. 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

  5. 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.

  6. 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)...

  7. 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

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

    Treesearch

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

    2009-01-01

    We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975–2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age...

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

    PubMed

    Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

    2017-09-01

    Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

  10. Estimating herbaceous biomass of grassland vegetation using the reference unit method

    Treesearch

    Eric D. Boyda; Jack L. Butler; Lan Xu

    2015-01-01

    Aboveground net primary production provides valuable information on wildlife habitat, fire fuel loads, and forage availability. Aboveground net primary production in herbaceous plant communities is typically measured by clipping aboveground biomass. However, the high costs associated with physically harvesting plant biomass may prevent collecting sufficient...

  11. 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.

  12. 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.

  13. Identifying aboveground wood fiber potentials in New York State

    Treesearch

    Eric H. Wharton

    1984-01-01

    New York forests are made up of more than just the growing stock that is measured during conventional forest inventories. A biomass inventory, completed in 1980, showed that New York commercial forest lands contain nearly 1,164.4 million green tons of aboveground tree biomass, or an average of 75.6 green tons per acre. Conventional growing stock accounted for 57...

  14. Watching Grass - a Pilot Study on the Suitability of Photogrammetric Techniques for Quantifying Change in Aboveground Biomass in Grassland Experiments

    NASA Astrophysics Data System (ADS)

    Kröhnert, M.; Anderson, R.; Bumberger, J.; Dietrich, P.; Harpole, W. S.; Maas, H.-G.

    2018-05-01

    Grassland ecology experiments in remote locations requiring quantitative analysis of the biomass in defined plots are becoming increasingly widespread, but are still limited by manual sampling methodologies. To provide a cost-effective automated solution for biomass determination, several photogrammetric techniques are examined to generate 3D point cloud representations of plots as a basis, to estimate aboveground biomass on grassland plots, which is a key ecosystem variable used in many experiments. Methods investigated include Structure from Motion (SfM) techniques for camera pose estimation with posterior dense matching as well as the usage of a Time of Flight (TOF) 3D camera, a laser light sheet triangulation system and a coded light projection system. In this context, plants of small scales (herbage) and medium scales are observed. In the first pilot study presented here, the best results are obtained by applying dense matching after SfM, ideal for integration into distributed experiment networks.

  15. Biomass Allocation Patterns across China’s Terrestrial Biomes

    PubMed Central

    Wang, Limei; Li, Longhui; Chen, Xi; Tian, Xin; Wang, Xiaoke; Luo, Geping

    2014-01-01

    Root to shoot ratio (RS) is commonly used to describe the biomass allocation between below- and aboveground parts of plants. Determining the key factors influencing RS and interpreting the relationship between RS and environmental factors is important for biological and ecological research. In this study, we compiled 2088 pairs of root and shoot biomass data across China’s terrestrial biomes to examine variations in the RS and its responses to biotic and abiotic factors including vegetation type, soil texture, climatic variables, and stand age. The median value of RS (RSm) for grasslands, shrublands, and forests was 6.0, 0.73, and 0.23, respectively. The range of RS was considerably wide for each vegetation type. RS values for all three major vegetation types were found to be significantly correlated to mean annual precipitation (MAP) and potential water deficit index (PWDI). Mean annual temperature (MAT) also significantly affect the RS for forests and grasslands. Soil texture and forest origin altered the response of RS to climatic factors as well. An allometric formula could be used to well quantify the relationship between aboveground and belowground biomass, although each vegetation type had its own inherent allometric relationship. PMID:24710503

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

    Treesearch

    Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall

    2017-01-01

    Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...

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

    PubMed

    Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

    2017-09-08

    Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p < 0.05, RMSE = 2.20 kg/m²) and 85% ( n = 100, p < 0.01, RMSE = 1.71 kg/m²) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.

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

    PubMed Central

    Lu, Xiaoman; Zheng, Guang; Miller, Colton

    2017-01-01

    Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% (n = 35, p < 0.05, RMSE = 2.20 kg/m2) and 85% (n = 100, p < 0.01, RMSE = 1.71 kg/m2) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB. PMID:28885556

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

    Treesearch

    Michael E. Goerndt; David R. Larsen; Charles D. Keating

    2014-01-01

    In recent years, the state of Missouri has been converting to biomass weight rather than volume as the standard measurement of wood for buying and selling sawtimber. Therefore, there is a need to identify accurate and precise methods of estimating whole tree biomass and merchantable biomass of harvested trees as well as total standing biomass of live timber for...

  20. 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

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

    PubMed

    Chen, Han Y H; Luo, Yong

    2015-10-01

    Biomass change of the world's forests is critical to the global carbon cycle. Despite storing nearly half of global forest carbon, the boreal biome of diverse forest types and ages is a poorly understood component of the carbon cycle. Using data from 871 permanent plots in the western boreal forest of Canada, we examined net annual aboveground biomass change (ΔAGB) of four major forest types between 1958 and 2011. We found that ΔAGB was higher for deciduous broadleaf (DEC) (1.44 Mg ha(-1)  year(-1) , 95% Bayesian confidence interval (CI), 1.22-1.68) and early-successional coniferous forests (ESC) (1.42, CI, 1.30-1.56) than mixed forests (MIX) (0.80, CI, 0.50-1.11) and late-successional coniferous (LSC) forests (0.62, CI, 0.39-0.88). ΔAGB declined with forest age as well as calendar year. After accounting for the effects of forest age, ΔAGB declined by 0.035, 0.021, 0.032 and 0.069 Mg ha(-1)  year(-1) per calendar year in DEC, ESC, MIX and LSC forests, respectively. The ΔAGB declines resulted from increased tree mortality and reduced growth in all forest types except DEC, in which a large biomass loss from mortality was accompanied with a small increase in growth. With every degree of annual temperature increase, ΔAGB decreased by 1.00, 0.20, 0.55 and 1.07 Mg ha(-1)  year(-1) in DEC, ESC, MIX and LSC forests, respectively. With every cm decrease of annual climatic moisture availability, ΔAGB decreased 0.030, 0.045 and 0.17 Mg ha(-1)  year(-1) in ESC, MIX and LSC forests, but changed little in DEC forests. Our results suggest that persistent warming and decreasing water availability have profound negative effects on forest biomass in the boreal forests of western Canada. Furthermore, our results indicate that forest responses to climate change are strongly dependent on forest composition with late-successional coniferous forests being most vulnerable to climate changes in terms of aboveground biomass. © 2015 John Wiley & Sons Ltd.

  2. Combining satellite lidar, airborne lidar, and ground plots to estimate the amount and distribution of aboveground biomass in the boreal forest of North America 1

    Treesearch

    Hank A. Margolis; Ross F. Nelson; Paul M. Montesano; André Beaudoin; Guoqing Sun; Hans-Erik Andersen; Michael A. Wulder

    2015-01-01

    We report estimates of the amount, distribution, and uncertainty of aboveground biomass (AGB) of the different ecoregions and forest land cover classes within the North American boreal forest, analyze the factors driving the error estimates, and compare our estimates with other reported values. A three-phase sampling strategy was used (i) to tie ground plot AGB to...

  3. Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data

    Treesearch

    Chad Babcock; Andrew O. Finley; Bruce D. Cook; Aaron Weiskittel; Christopher W. Woodall

    2016-01-01

    Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB...

  4. Imaging spectroscopy calibration and applications for coastal wetland species composition and biomass mapping in the Mississippi Delta

    NASA Astrophysics Data System (ADS)

    Jensen, D.; Cavanaugh, K. C.; Simard, M.

    2016-12-01

    Coastal wetlands provide a wealth of ecosystem services, including improved water quality, protection from storm surges, and wildlife habitat. Louisiana's wetlands, however, are threatened by development, pollution, and relative sea level rise (RSLR)—the combination of sea level rise and subsidence rates. Beyond causing land loss, RSLR impacts Louisiana's wetland ecosystems by altering salinity, nutrient availability, flood duration, and flood frequency in the region. Despite widespread wetland loss, areas such as the Wax Lake and Atchafalaya river deltas are in fact growing due to their sediment loads, resulting in a complex of both degradation and aggradation along the Louisiana coast. In order to understand and model how coastal wetlands are responding to RSLR, there is a need for improved vegetation distribution mapping, biomass estimation, and ecosystem change modeling. To this end, high-resolution imaging spectroscopy offers the ability to accurately develop species-level distribution maps and predictive aboveground biomass (AGB) models. AVIRIS-NG data collected over the Atchafalaya River Delta were calibrated to reduce Bidirectional Reflectance Distribution Function (BRDF) effects and mosaicked, along with other scenes that coincided with field observations. Multiple Endmember Spectral Mixture Analysis (MESMA) was used to map salt marsh at the species level across our study area. Field observations were used to parameterize and validate our MESMA based approach. AGB was then mapped for this region using a partial least squares regression (PLSR) model developed from the same imagery and field measurements. Last, the Sea Level Affecting Marshes Model was applied to predict wetland loss and changes in marsh composition due to sea level rise, which was then paired with the AGB map to estimate carbon storage change. In doing so, this study addresses key concerns for coastal regions and demonstrates the ability of imaging spectroscopy to predict those impacts.

  5. 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.

  6. Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping.

    PubMed

    Mitchell, Matthew G E; Johansen, Kasper; Maron, Martine; McAlpine, Clive A; Wu, Dan; Rhodes, Jonathan R

    2018-05-01

    Urban areas are sources of land use change and CO 2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha -1 calculated across the entire urban land area, and 110.9±19.7MgCha -1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km 2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. 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.

  8. Does Sentinel multi sensor data offer synergy in Improving Accuracy of Aboveground Biomass Estimate of Dense Tropical Forest? - Utility of Decision Tree Based Machine Learning Algorithms

    NASA Astrophysics Data System (ADS)

    Ghosh, S. M.; Behera, M. D.

    2017-12-01

    Forest aboveground biomass (AGB) is an important factor for preparation of global policy making decisions to tackle the impact of climate change. Several previous studies has concluded that remote sensing methods are more suitable for estimating forest biomass on regional scale. Among all available remote sensing data and methods, Synthetic Aperture Radar (SAR) data in combination with decision tree based machine learning algorithms has shown better promise in estimating higher biomass values. There aren't many studies done for biomass estimation of dense Indian tropical forests with high biomass density. In this study aboveground biomass was estimated for two major tree species, Sal (Shorea robusta) and Teak (Tectona grandis), of Katerniaghat Wildlife Sanctuary, a tropical forest situated in northern India. Biomass was estimated by combining C-band SAR data from Sentinel-1A satellite, vegetation indices produced using Sentinel-2A data and ground inventory plots. Along with SAR backscatter value, SAR texture images were also used as input as earlier studies had found that image texture has a correlation with vegetation biomass. Decision tree based nonlinear machine learning algorithms were used in place of parametric regression models for establishing relationship between fields measured values and remotely sensed parameters. Using random forest model with a combination of vegetation indices with SAR backscatter as predictor variables shows best result for Sal forest, with a coefficient of determination value of 0.71 and a RMSE value of 105.027 t/ha. In teak forest also best result can be found in the same combination but for stochastic gradient boosted model with a coefficient of determination value of 0.6 and a RMSE value of 79.45 t/ha. These results are mostly better than the results of other studies done for similar kind of forests. This study shows that Sentinel series satellite data has exceptional capabilities in estimating dense forest AGB and machine

  9. 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

  10. 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

  11. 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

  12. 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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    French, Sean B; Christensen, Candace; Jennings, Terry L

    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 onmore » 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

  13. Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C 4 Grasses in Hawaii

    DOE PAGES

    Youkhana, Adel H.; Ogoshi, Richard M.; Kiniry, James R.; ...

    2017-05-02

    Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C 4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewablemore » energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R 2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations

  14. 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

  15. 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

  16. 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

  17. Fusion of pan-tropical biomass maps using weighted averaging and regional calibration data

    NASA Astrophysics Data System (ADS)

    Ge, Yong; Avitabile, Valerio; Heuvelink, Gerard B. M.; Wang, Jianghao; Herold, Martin

    2014-09-01

    Biomass is a key environmental variable that influences many biosphere-atmosphere interactions. Recently, a number of biomass maps at national, regional and global scales have been produced using different approaches with a variety of input data, such as from field observations, remotely sensed imagery and other spatial datasets. However, the accuracy of these maps varies regionally and is largely unknown. This research proposes a fusion method to increase the accuracy of regional biomass estimates by using higher-quality calibration data. In this fusion method, the biases in the source maps were first adjusted to correct for over- and underestimation by comparison with the calibration data. Next, the biomass maps were combined linearly using weights derived from the variance-covariance matrix associated with the accuracies of the source maps. Because each map may have different biases and accuracies for different land use types, the biases and fusion weights were computed for each of the main land cover types separately. The conceptual arguments are substantiated by a case study conducted in East Africa. Evaluation analysis shows that fusing multiple source biomass maps may produce a more accurate map than when only one biomass map or unweighted averaging is used.

  18. Spaceborne SAR Data for Aboveground-Biomass Retrieval of Indian Tropical Forests

    NASA Astrophysics Data System (ADS)

    Khati, U.; Singh, G.; Musthafa, M.

    2017-12-01

    Forests are important and indispensable part of the terrestrial ecosystems, and have a direct impact on the global carbon cycle. Forest biophysical parameters such as forest stand height and forest above-ground biomass (AGB) are forest health indicators. Measuring the forest biomass using traditional ground survey techniques are man-power consuming and have very low spatial coverage. Satellite based remote sensing techniques provide synoptic view of the earth with continuous measurements over large, inaccessible forest regions. Satellite Synthetic Aperture Radar (SAR) data has been shown to be sensitive to these forest bio-physical parameters and have been extensively utilized over boreal and tropical forests. However, there are limited studies over Indian tropical forests due to lack of auxiliary airborne data and difficulties in manual in situ data collection. In this research work we utilize spaceborne data from TerraSAR-X/TanDEM-X and ALOS-2/PALSAR-2 and implement both Polarimetric SAR and PolInSAR techniques for retrieval of AGB of a managed tropical forest in India. The TerraSAR-X/TanDEM-X provide a single-baseline PolInSAR data robust to temporal decorrelation. This would be used to accurately estimate the forest stand height. The retrieved height would be an input parameter for modelling AGB using the L-band ALOS-2/PALSAR-2 data. The IWCM model is extensively utilized to estimate AGB from SAR observations. In this research we utilize the six component scattering power decomposition (6SD) parameters and modify the IWCM based technique for a better retrieval of forest AGB. PolInSAR data shows a high estimation accuracy with r2 of 0.8 and a RMSE of 2 m. With this accurate height provided as input to the modified model along with 6SD parameters shows promising results. The results are validated with extensive field based measurements, and are further analysed in detail.

  19. 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

  20. Above-ground biomass and structure of pristine Siberian Scots pine forests as controlled by competition and fire.

    PubMed

    Wirth, C; Schulze, E-D; Schulze, W; von Stünzner-Karbe, D; Ziegler, W; Miljukova, I M; Sogatchev, A; Varlagin, A B; Panvyorov, M; Grigoriev, S; Kusnetzova, W; Siry, M; Hardes, G; Zimmermann, R; Vygodskaya, N N

    1999-10-01

    The study presents a data set of above-ground biomass (AGB), structure, spacing and fire regime, for 24 stands of pristine Siberian Scots pine (Pinus sylvestris) forests with lichens (n = 20) or Vaccinium/mosses (n = 4) as ground cover, along four chronosequences. The stands of the "lichen" site type (LT) were stratified into three chronosequences according to stand density and fire history. Allometric equations were established from 90 sample trees for stem, coarse branch, fine branch, twig and needle biomass. The LT stands exhibited a low but sustained biomass accumulation until a stand age of 383 years. AGB reached only 6-10 kg dw  m -2 after 200 years depending on stand density and fire history compared to 20 kg dw  m -2 in the "Vaccinium" type (VT) stands. Leaf area index (LAI) in the LT stands remained at 0.5-1.5 and crown cover was 30-60%, whereas LAI reached 2.5 and crown cover was >100% in the VT stands. Although nearest-neighbour analyses suggested the existence of density-dependent mortality, fire impact turned out to have a much stronger effect on density dynamics. Fire scar dating and calculation of mean and initial fire return intervals revealed that within the LT stands differences in structure and biomass were related to the severity of fire regimes, which in turn was related to the degree of landscape fragmentation by wetlands. Self-thinning analysis was used to define the local carrying capacity for biomass. A series of undisturbed LT stands was used to characterise the upper self-thinning boundary. Stands that had experienced a moderate fire regime were positioned well below the self-thinning boundary in a distinct fire-thinning band of reduced major axis regression slope -0.26. We discuss how this downward shift resulted from alternating phases of density reduction by fire and subsequent regrowth. We conclude that biomass in Siberian Scots pine forests is strongly influenced by fire and that climate change will affect ecosystem

  1. 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.

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

    PubMed

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

    2017-10-01

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

  3. Mapping boreal forest biomass from a SRTM and TanDEM-X based on canopy height model and Landsat spectral indices

    NASA Astrophysics Data System (ADS)

    Sadeghi, Yaser; St-Onge, Benoît; Leblon, Brigitte; Prieur, Jean-François; Simard, Marc

    2018-06-01

    We propose a method for mapping above-ground biomass (AGB) (Mg ha-1) in boreal forests based predominantly on Landsat 8 images and on canopy height models (CHM) generated using interferometric synthetic aperture radar (InSAR) from the Shuttle Radar Topographic Mission (SRTM) and the TanDEM-X mission. The original SRTM digital elevation model (DEM) was corrected by modelling the respective effects of landform and land cover on its errors and then subtracted from a TanDEM-X DSM to produce a SAR CHM. Among all the landform factors, the terrain curvature had the largest effect on SRTM elevation errors, with a r2 of 0.29. The NDSI was the best predictor of the residual SRTM land cover error, with a r2 of 0.30. The final SAR CHM had a RMSE of 2.45 m, with a bias of 0.07 m, compared to a lidar-based CHM. An AGB prediction model was developed based on a combination of the SAR CHM, TanDEM-X coherence, Landsat 8 NDVI, and other vegetation indices of RVI, DVI, GRVI, EVI, LAI, GNDVI, SAVI, GVI, Brightness, Greenness, and Wetness. The best results were obtained using a Random forest regression algorithm, at the stand level, yielding a RMSE of 26 Mg ha-1 (34% of average biomass), with a r2 of 0.62. This method has the potential of creating spatially continuous biomass maps over entire biomes using only spaceborne sensors and requiring only low-intensity calibration.

  4. Vegetation, plant biomass, and net primary productivity patterns in the Canadian Arctic

    NASA Astrophysics Data System (ADS)

    Gould, W. A.; Raynolds, M.; Walker, D. A.

    2003-01-01

    We have developed maps of dominant vegetation types, plant functional types, percent vegetation cover, aboveground plant biomass, and above and belowground annual net primary productivity for Canada north of the northern limit of trees. The area mapped covers 2.5 million km2 including glaciers. Ice-free land covers 2.3 million km2 and represents 42% of all ice-free land in the Circumpolar Arctic. The maps combine information on climate, soils, geology, hydrology, remotely sensed vegetation classifications, previous vegetation studies, and regional expertise to define polygons drawn using photo-interpretation of a 1:4,000,000 scale advanced very high resolution radiometer (AVHRR) color infrared image basemap. Polygons are linked to vegetation description, associated properties, and descriptive literature through a series of lookup tables in a graphic information systems (GIS) database developed as a component of the Circumpolar Arctic Vegetation Map (CAVM) project. Polygons are classified into 20 landcover types including 17 vegetation types. Half of the region is sparsely vegetated (<50% vegetation cover), primarily in the High Arctic (bioclimatic subzones A-C). Whereas most (86%) of the estimated aboveground plant biomass (1.5 × 1015 g) and 87% of the estimated above and belowground annual net primary productivity (2.28 × 1014 g yr-1) are concentrated in the Low Arctic (subzones D and E). The maps present more explicit spatial patterns of vegetation and ecosystem attributes than have been previously available, the GIS database is useful in summarizing ecosystem properties and can be easily updated and integrated into circumpolar mapping efforts, and the derived estimates fall within the range of current published estimates.

  5. Tropical Africa: Land Use, Biomass, and Carbon Estimates for 1980 (and updated for the year 2000) (NDP-055)

    DOE Data Explorer

    Brown, Sandra [University of Illinois, Urbana, IL (USA); Winrock International, Arlington, Virginia (USA); Gaston, Greg [University of Illinois, Urbana, IL (USA); Oregon State University; Beaty, T. W. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory, Oak Ridge, TN (USA); Olsen, L. M. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory, Oak Ridge, TN (USA)

    2001-01-01

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980. 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 10E6 km2 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 (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 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.

  6. Recovery of aboveground biomass in Ohio, 1978

    Treesearch

    Eric H. Wharton

    1982-01-01

    Timber-use studies in Ohio show that multiproduct harvesting could be improved. The recovery rate from these operations, expressed as a ratio of the merchantable stem biomass estimate, is 103 percent. Although current methods of multiproduct harvesting have improved recovery of the merchantable stem, an estimated 1,539 thousand fresh tons of total residual biomass were...

  7. NGEE Arctic Plant Traits: Plant Biomass and Traits, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, beginning 2016

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Verity Salmon; Colleen Iversen; Amy Breen

    Data includes aboveground biomass and plant traits for destructive harvests performed at the Kougarok hill slope located at Kougarok Road, Mile Marker 64. Data collection began in July 2016. Aboveground biomass and aboveground plant traits are available for shrub and understory species found in vegetation plots. Paired observations of aboveground and belowground plant traits are available for select shrub species.

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

    Treesearch

    Michael A. Lefsky; David J. Harding; Michael Keller; Warren B. Cohen; Claudia C. Carabajal; Fernando Del Bom Espirito-Santo; Maria O. Hunter; Raimundo de Oliveira Jr.

    2005-01-01

    Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land...

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

    NASA Astrophysics Data System (ADS)

    Zolkos, S. G.; Goetz, S. J.; Dubayah, R.

    2012-12-01

    Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.

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

    Treesearch

    Carlos Alberto Silva; Andrew Thomas Hudak; Lee Alexander Vierling; Carine Klauberg; Mariano Garcia; Antonio Ferraz; Michael Keller; Jan Eitel; Sassan Saatchi

    2017-01-01

    Airborne lidar has become a well-suited technology for predicting and mapping many tropical forest attributes, including aboveground biomass (AGB). However, trade-offs exist between lidar pulse density and acquisition cost. The aim of this study was to evaluate the influence of lidar pulse density on AGB change predictions using airborne lidar and field plot data in a...

  11. Predicting Biomass of Understory Stems in the Miississipi and Alabama Coastal Plains

    Treesearch

    B.L. Franchi; I.W. Savelle; W.F. Watson; B.J. Stokes

    1984-01-01

    Understory forest biomass is becoming an important source of industrial fuelwood. Up to 40 tons per acre of above-ground biomass may be present in the understory of Southern pine stands. The above-ground portion is the only portion of the tree that can be harvested economically for fuel.

  12. Model analysis of grazing effect on above-ground biomass and above-ground net primary production of a Mongolian grassland ecosystem

    NASA Astrophysics Data System (ADS)

    Chen, Yuxiang; Lee, Gilzae; Lee, Pilzae; Oikawa, Takehisa

    2007-01-01

    In this study, we have analyzed the productivity of a grassland ecosystem in Kherlenbayan-Ulaan (KBU), Mongolia under non-grazing and grazing conditions using a new simulation model, Sim-CYCLE grazing. The model was obtained by integrating the Sim-CYCLE [Ito, A., Oikawa, T., 2002. A simulation model of carbon cycle in land ecosystems (Sim-CYCLE): a description based on dry-matter production theory and plot-scale validation. Ecological Modeling, 151, pp. 143-176] and a defoliation formulation [Seligman, N.G., Cavagnaro, J.B., Horno, M.E., 1992. Simulation of defoliation effects on primary production of warm-season, semiarid perennial- species grassland. Ecological Modelling, 60, pp. 45-61]. The results from the model have been validated against a set of field data obtained at KBU showing that both above-ground biomass (AB) and above-ground net primary production ( Np,a) decrease with increasing grazing intensity. The simulated maximum AB for a year maintains a nearly constant value of 1.15 Mg DM ha -1 under non-grazing conditions. The AB decreases and then reaches equilibrium under a stocking rate ( Sr) of 0.4 sheep ha -1 and 0.7 sheep ha -1. The AB decreases all the time if Sr is greater than 0.7 sheep ha -1. These results suggest that the maximum sustainable Sr is 0.7 sheep ha -1. A similar trend is also observed for the simulated Np,a. The annual Np,a is about 1.25 Mg DM ha -1 year -1 and this value is also constant under non-grazing conditions. The annual Np,a decreases and then reaches equilibrium under an Sr of 0.4 sheep ha -1 and 0.7 sheep ha -1, but the Np,a decreases all the time when Sr is greater than 0.7 sheep ha -1. It also indicates that the maximum sustainable Sr is 0.7 sheep ha -1. Transpiration ( ET) and evaporation ( EE) rates were determined by the Penman-Monteith method. Simulated results show that ET decreases with increasing Sr, while EE increases with increasing Sr. At equilibrium, the annual mean evapotranspiration ( E) is 189.11 mm year -1

  13. 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.

  14. 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

  15. 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. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

  16. 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

  17. Description and prediction of individual tree biomass on pinon (Pinus edulis) in northern New Mexico

    Treesearch

    Mark Loveall; John T. Harrington

    2008-01-01

    The purpose of this study was to gain reliable information on the distribution of aboveground biomass of an important component of the woodlands of north-central New Mexico, and to develop prediction equations that may be used to quickly compute biomass from relatively simple field measurements. Improved understanding of and ability to predict aboveground biomass...

  18. Using landsat time-series and lidar to inform aboveground carbon baseline estimation in Minnesota

    Treesearch

    Ram K. Deo; Grant M. Domke; Matthew B. Russell; Christopher W. Woodall; Michael J. Falkowski

    2015-01-01

    Landsat data has long been used to support forest monitoring and management decisions despite the limited success of passive optical remote sensing for accurate estimation of structural attributes such as aboveground biomass. The archive of publicly available Landsat images dating back to the 1970s can be used to predict historic forest biomass dynamics. In addition,...

  19. Biomass statistics for Vermont - 1983

    Treesearch

    Thomas S. Frieswyk; Anne M. Malley

    1986-01-01

    A new measure of the forest resource has been added to the fourth forest inventory of Vermont. The inventory, which was conducted in 1982-83, included estimates of aboveground tree biomass on timberland. There are approximately 413 million green tons of wood and bark in the aboveground portion of all trees, which equates to an average of 93 green tons per acre...

  20. 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

    2014-12-02

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

  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. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  4. Biomass statistics for the Northern United States

    Treesearch

    Eric H. Wharton; Gerhard K. Raile

    1984-01-01

    The USDA Forest Service now estimates biomass during periodic resource inventories. Such biomass estimates quantify more of the forest resource than do traditional volume inventories that concentrate on tree boles. More than 48 percent of the aboveground tree biomass in the northern United States can be found in woody material outside of the boles. Tree biomass in the...

  5. 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

  6. 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...

  7. 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). © 2016 John Wiley & Sons Ltd/CNRS.

  8. Biomass distribution and productivity of Pinus edulis-Juniperus monosperma woodlands of north-central Arizona

    Treesearch

    Charles C. Grier; Katherine J. Elliott; Deborah G. McCullough

    1992-01-01

    Above-ground biomass distribution, leaf area, above-ground net primary productivity and foliage characteristics were determined for 90- and 350-year-old Pinus edulis-Juniperus monosperma ecosystems on the Colorado Plateau of northern Arizona. These ecosystems have low biomass, leaf area and primary productivity compared with forests in wetter...

  9. 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

  10. 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

    2015-07-31

    The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE's, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development.

  11. 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

  12. 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.

  13. Biomass statistics for New Hampshire - 1983

    Treesearch

    Thomas S. Frieswyk; Anne M. Malley

    1986-01-01

    A new measure of the forest resource has been added to the fourth forest inventory of New Hampshire. The inventory, which was conducted in 1982-83, included estimates of aboveground tree biomass on timberland. There are approximately 502 million green tons of wood and bark in the aboveground portion of all trees, or 104 green tons per acre. Fifty-five percent or 275...

  14. Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer

    Treesearch

    Mark Chopping; Gretchen G. Moisen; Lihong Su; Andrea Laliberte; Albert Rango; John V. Martonchik; Debra P. C. Peters

    2008-01-01

    A rapid canopy reflectance model inversion experiment was performed using multi-angle reflectance data from the NASA Multi-angle Imaging Spectro-Radiometer (MISR) on the Earth Observing System Terra satellite, with the goal of obtaining measures of forest fractional crown cover, mean canopy height, and aboveground woody biomass for large parts of south-eastern Arizona...

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

    Treesearch

    David. C. Chojnacky

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Meyer, Victoria; Saatchi, Sassan; Clark, David B.; Keller, Michael; Vincent, Grégoire; Ferraz, António; Espírito-Santo, Fernando; d'Oliveira, Marcus V. N.; Kaki, Dahlia; Chave, Jérôme

    2018-06-01

    Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (˜ 25-30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha-1, bias = -0.63 Mg ha-1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA-AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.

  17. Refuse dumps from leaf-cutting ant nests reduce the intensity of above-ground competition among neighboring plants in a Patagonian steppe

    NASA Astrophysics Data System (ADS)

    Farji-Brener, Alejandro G.; Lescano, María Natalia

    2017-11-01

    In arid environments, the high availability of sunlight due to the scarcity of trees suggests that plant competition take place mainly belowground for water and nutrients. However, the occurrence of soil disturbances that increase nutrient availability and thereby promote plant growth may enhance shoot competition between neighboring plants. We conducted a greenhouse experiment to evaluate the influence of the enriched soil patches generated by the leaf-cutting ant, Acromyrmex lobicornis, on the performance of the alien forb Carduus thoermeri (Asteraceae) under different intraspecific competition scenarios. Our results showed that substrate type and competition scenario affected mainly aboveground plant growth. As expected, plants growing without neighbors and in nutrient-rich ant refuse dumps showed more aboveground biomass than plants growing with neighbors and in nutrient-poor steppe soils. However, aboveground competition was more intense in nutrient-poor substrates: plants under shoot and full competition growing in the nutrient-rich ant refuse dumps showed higher biomass than those growing on steppe soils. Belowground biomass was similar among focal plants growing under different substrate type. Our results support the traditional view that increments in resource availability reduce competition intensity. Moreover, the fact that seedlings in this sunny habitat mainly compete aboveground illustrates how limiting factors may be scale-dependent and change in importance as plants grow.

  18. 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

  19. Effects of precipitation changes on switchgrass photosynthesis, growth, and biomass: A mesocosm experiment

    PubMed Central

    Yu, Chih-Li; Deng, Qi; Dzantor, E. Kudjo; Zhou, Suping; Dennis, Sam; Sauve, Roger; Johnson, Terrance L.; Fay, Philip A.; Shen, Weijun; Luo, Yiqi

    2018-01-01

    Climate changes, including chronic changes in precipitation amounts, will influence plant physiology and growth. However, such precipitation effects on switchgrass, a major bioenergy crop, have not been well investigated. We conducted a two-year precipitation simulation experiment using large pots (95 L) in an environmentally controlled greenhouse in Nashville, TN. Five precipitation treatments (ambient precipitation, and -50%, -33%, +33%, and +50% of ambient) were applied in a randomized complete block design with lowland "Alamo" switchgrass plants one year after they were established from tillers. The growing season progression of leaf physiology, tiller number, height, and aboveground biomass were determined each growing season. Precipitation treatments significantly affected leaf physiology, growth, and aboveground biomass. The photosynthetic rates in the wet (+50% and +33%) treatments were significantly enhanced by 15.9% and 8.1%, respectively, than the ambient treatment. Both leaf biomass and plant height were largely increased, resulting in dramatically increases in aboveground biomass by 56.5% and 49.6% in the +50% and +33% treatments, respectively. Compared to the ambient treatment, the drought (-33% and -50%) treatments did not influence leaf physiology, but the -50% treatment significantly reduced leaf biomass by 37.8%, plant height by 16.3%, and aboveground biomass by 38.9%. This study demonstrated that while switchgrass in general is a drought tolerant grass, severe drought significantly reduces Alamo’s growth and biomass, and that high precipitation stimulates its photosynthesis and growth. PMID:29420600

  20. Effects of precipitation changes on switchgrass photosynthesis, growth, and biomass: A mesocosm experiment.

    PubMed

    Hui, Dafeng; Yu, Chih-Li; Deng, Qi; Dzantor, E Kudjo; Zhou, Suping; Dennis, Sam; Sauve, Roger; Johnson, Terrance L; Fay, Philip A; Shen, Weijun; Luo, Yiqi

    2018-01-01

    Climate changes, including chronic changes in precipitation amounts, will influence plant physiology and growth. However, such precipitation effects on switchgrass, a major bioenergy crop, have not been well investigated. We conducted a two-year precipitation simulation experiment using large pots (95 L) in an environmentally controlled greenhouse in Nashville, TN. Five precipitation treatments (ambient precipitation, and -50%, -33%, +33%, and +50% of ambient) were applied in a randomized complete block design with lowland "Alamo" switchgrass plants one year after they were established from tillers. The growing season progression of leaf physiology, tiller number, height, and aboveground biomass were determined each growing season. Precipitation treatments significantly affected leaf physiology, growth, and aboveground biomass. The photosynthetic rates in the wet (+50% and +33%) treatments were significantly enhanced by 15.9% and 8.1%, respectively, than the ambient treatment. Both leaf biomass and plant height were largely increased, resulting in dramatically increases in aboveground biomass by 56.5% and 49.6% in the +50% and +33% treatments, respectively. Compared to the ambient treatment, the drought (-33% and -50%) treatments did not influence leaf physiology, but the -50% treatment significantly reduced leaf biomass by 37.8%, plant height by 16.3%, and aboveground biomass by 38.9%. This study demonstrated that while switchgrass in general is a drought tolerant grass, severe drought significantly reduces Alamo's growth and biomass, and that high precipitation stimulates its photosynthesis and growth.

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

    NASA Astrophysics Data System (ADS)

    Li, T.; Wang, Z.; Peng, J.

    2018-04-01

    Aboveground biomass (AGB) estimation is critical for quantifying carbon stocks and essential for evaluating carbon cycle. In recent years, airborne LiDAR shows its great ability for highly-precision AGB estimation. Most of the researches estimate AGB by the feature metrics extracted from the canopy height distribution of the point cloud which calculated based on precise digital terrain model (DTM). However, if forest canopy density is high, the probability of the LiDAR signal penetrating the canopy is lower, resulting in ground points is not enough to establish DTM. Then the distribution of forest canopy height is imprecise and some critical feature metrics which have a strong correlation with biomass such as percentiles, maximums, means and standard deviations of canopy point cloud can hardly be extracted correctly. In order to address this issue, we propose a strategy of first reconstructing LiDAR feature metrics through Auto-Encoder neural network and then using the reconstructed feature metrics to estimate AGB. To assess the prediction ability of the reconstructed feature metrics, both original and reconstructed feature metrics were regressed against field-observed AGB using the multiple stepwise regression (MS) and the partial least squares regression (PLS) respectively. The results showed that the estimation model using reconstructed feature metrics improved R2 by 5.44 %, 18.09 %, decreased RMSE value by 10.06 %, 22.13 % and reduced RMSEcv by 10.00 %, 21.70 % for AGB, respectively. Therefore, reconstructing LiDAR point feature metrics has potential for addressing AGB estimation challenge in dense canopy area.

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

    NASA Astrophysics Data System (ADS)

    Dube, Timothy; Mutanga, Onisimo

    2015-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Xia, Jiangzhou; Ma, Minna; Liang, Tiangang; Wu, Chaoyang; Yang, Yuanhe; Zhang, Li; Zhang, Yangjian; Yuan, Wenping

    2018-01-01

    The grassland of the Tibetan Plateau forms a globally significant biome, which represents 6% of the world’s grasslands and 44% of China’s grasslands. However, large uncertainties remain concerning the vegetation carbon storage and turnover time in this biome. In this study, we quantified the pool size of both the aboveground and belowground biomass and turnover time of belowground biomass across the Tibetan Plateau by combining systematic measurements taken from a substantial number of surveys (i.e. 1689 sites for aboveground biomass, 174 sites for belowground biomass) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is effective tool for upscaling local biomass observations to the regional scale, and for producing continuous biomass estimates of the Tibetan Plateau. On average, the models estimated 46.57 Tg (1 Tg = 1012g) C of aboveground biomass and 363.71 Tg C of belowground biomass in the Tibetan grasslands covering an area of 1.32 × 106 km2. The turnover time of belowground biomass demonstrated large spatial heterogeneity, with a median turnover time of 4.25 years. Our results also demonstrated large differences in the biomass simulations among the major ecosystem models used for the Tibetan Plateau, largely because of inadequate model parameterization and validation. This study provides a spatially continuous measure of vegetation carbon storage and turnover time, and provides useful information for advancing ecosystem models and improving their performance.

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

    PubMed

    Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane

    2018-02-21

    Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated

  5. Evaluation of sampling strategies to estimate crown biomass

    Treesearch

    Krishna P Poudel; Hailemariam Temesgen; Andrew N Gray

    2015-01-01

    Depending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire...

  6. Evaluating kriging as a tool to improve moderate resolution maps of forest biomass

    Treesearch

    Elizabeth A. Freeman; Gretchen G. Moisen

    2007-01-01

    The USDA Forest Service, Forest Inventory and Analysis program (FIA) recently produced a nationwide map of forest biomass by modeling biomass collected on forest inventory plots as nonparametric functions of moderate resolution satellite data and other environmental variables using Cubist software. Efforts are underway to develop methods to enhance this initial map. We...

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

    USGS Publications Warehouse

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

    2008-01-01

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

  8. 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.

  9. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    Treesearch

    David C. Chojnacky; Jennifer C. Jenkins; Amanda K. Holland

    2009-01-01

    Thousands of published equations purport to estimate biomass of individual trees. These equations are often based on very small samples, however, and can provide widely different estimates for trees of the same species. We addressed this issue in a previous study by devising 10 new equations that estimated total aboveground biomass for all species in North America (...

  11. 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.

  12. 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

  13. Response of NDVI, biomass, and ecosystem gas exchange to long-term warming and fertilization in wet sedge tundra.

    PubMed

    Boelman, Natalie T; Stieglitz, Marc; Rueth, Heather M; Sommerkorn, Martin; Griffin, Kevin L; Shaver, Gaius R; Gamon, John A

    2003-05-01

    This study explores the relationship between the normalized difference vegetation index (NDVI), aboveground plant biomass, and ecosystem C fluxes including gross ecosystem production (GEP), ecosystem respiration (ER) and net ecosystem production. We measured NDVI across long-term experimental treatments in wet sedge tundra at the Toolik Lake LTER site, in northern Alaska. Over 13 years, N and P were applied in factorial experiments (N, P and N + P), air temperature was increased using greenhouses with and without N + P fertilizer, and light intensity (photosynthetically active photon flux density) was reduced by 50% using shade cloth. Within each treatment plot, NDVI, aboveground biomass and whole-system CO(2) flux measurements were made at the same sampling points during the peak-growing season of 2001. We found that across all treatments, NDVI is correlated with aboveground biomass ( r(2)=0.84), GEP ( r(2)=0.75) and ER ( r(2)=0.71), providing a basis for linking remotely sensed NDVI to aboveground biomass and ecosystem carbon flux.

  14. Estimating aboveground live understory vegetation carbon in the United States

    NASA Astrophysics Data System (ADS)

    Johnson, Kristofer D.; Domke, Grant M.; Russell, Matthew B.; Walters, Brian; Hom, John; Peduzzi, Alicia; Birdsey, Richard; Dolan, Katelyn; Huang, Wenli

    2017-12-01

    Despite the key role that understory vegetation plays in ecosystems and the terrestrial carbon cycle, it is often overlooked and has few quantitative measurements, especially at national scales. To understand the contribution of understory carbon to the United States (US) carbon budget, we developed an approach that relies on field measurements of understory vegetation cover and height on US Department of Agriculture Forest Service, Forest Inventory and Analysis (FIA) subplots. Allometric models were developed to estimate aboveground understory carbon. A spatial model based on stand characteristics and remotely sensed data was also applied to estimate understory carbon on all FIA plots. We found that most understory carbon was comprised of woody shrub species (64%), followed by nonwoody forbs and graminoid species (35%) and seedlings (1%). The largest estimates were found in temperate or warm humid locations such as the Pacific Northwest and southeastern US, thus following the same broad trend as aboveground tree biomass. The average understory aboveground carbon density was estimated to be 0.977 Mg ha-1, for a total estimate of 272 Tg carbon across all managed forest land in the US (approximately 2% of the total aboveground live tree carbon pool). This estimate is more than twice as low as previous FIA modeled estimates that did not rely on understory measurements, suggesting that this pool may currently be overestimated in US National Greenhouse Gas reporting.

  15. Landsat phenological metrics and their relation to aboveground carbon in the Brazilian Savanna.

    PubMed

    Schwieder, M; Leitão, P J; Pinto, J R R; Teixeira, A M C; Pedroni, F; Sanchez, M; Bustamante, M M; Hostert, P

    2018-05-15

    The quantification and spatially explicit mapping of carbon stocks in terrestrial ecosystems is important to better understand the global carbon cycle and to monitor and report change processes, especially in the context of international policy mechanisms such as REDD+ or the implementation of Nationally Determined Contributions (NDCs) and the UN Sustainable Development Goals (SDGs). Especially in heterogeneous ecosystems, such as Savannas, accurate carbon quantifications are still lacking, where highly variable vegetation densities occur and a strong seasonality hinders consistent data acquisition. In order to account for these challenges we analyzed the potential of land surface phenological metrics derived from gap-filled 8-day Landsat time series for carbon mapping. We selected three areas located in different subregions in the central Brazil region, which is a prominent example of a Savanna with significant carbon stocks that has been undergoing extensive land cover conversions. Here phenological metrics from the season 2014/2015 were combined with aboveground carbon field samples of cerrado sensu stricto vegetation using Random Forest regression models to map the regional carbon distribution and to analyze the relation between phenological metrics and aboveground carbon. The gap filling approach enabled to accurately approximate the original Landsat ETM+ and OLI EVI values and the subsequent derivation of annual phenological metrics. Random Forest model performances varied between the three study areas with RMSE values of 1.64 t/ha (mean relative RMSE 30%), 2.35 t/ha (46%) and 2.18 t/ha (45%). Comparable relationships between remote sensing based land surface phenological metrics and aboveground carbon were observed in all study areas. Aboveground carbon distributions could be mapped and revealed comprehensible spatial patterns. Phenological metrics were derived from 8-day Landsat time series with a spatial resolution that is sufficient to capture gradual

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

    Treesearch

    Marcos Longo; Michael Keller; Maiza N. dos-Santos; Veronika Leitold; Ekena R. Pinagé; Alessandro Baccini; Sassan Saatchi; Euler M. Nogueira; Mateus Batistella; Douglas C. Morton

    2016-01-01

    Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha)...

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

    Treesearch

    Andrew T. Hudak; Eva K. Strand; Lee A. Vierling; John C. Byrne; Jan U. H. Eitel; Sebastian Martinuzzi; Michael J. Falkowski

    2012-01-01

    Sound forest policy and management decisions to mitigate rising atmospheric CO2 depend upon accurate methodologies to quantify forest carbon pools and fluxes over large tracts of land. LiDAR remote sensing is a rapidly evolving technology for quantifying aboveground biomass and thereby carbon pools; however, little work has evaluated the efficacy of repeat LiDAR...

  18. 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

  19. 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

  20. Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus; hide

    2016-01-01

    Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29 +/-1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119

  1. 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

  2. Alien and endangered plants in the Brazilian Cerrado exhibit contrasting relationships with vegetation biomass and N : P stoichiometry.

    PubMed

    Lannes, Luciola S; Bustamante, Mercedes M C; Edwards, Peter J; Venterink, Harry Olde

    2012-11-01

    Although endangered and alien invasive plants are commonly assumed to persist under different environmental conditions, surprisingly few studies have investigated whether this is the case. We examined how endangered and alien species are distributed in relation to community biomass and N : P ratio in the above-ground community biomass in savanna vegetation in the Brazilian Cerrado. For 60 plots, we related the occurrence of endangered (Red List) and alien invasive species to plant species richness, vegetation biomass and N : P ratio, and soil variables. Endangered plants occurred mainly in plots with relatively low above-ground biomass and high N : P ratios, whereas alien invasive species occurred in plots with intermediate to high biomass and low N : P ratios. Occurrences of endangered or alien plants were unrelated to extractable N and P concentrations in the soil. These contrasting distributions in the Cerrado imply that alien species only pose a threat to endangered species if they are able to invade sites occupied by these species and increase the above-ground biomass and/or decrease the N : P ratio of the vegetation. We found some evidence that alien species do increase above-ground community biomass in the Cerrado, but their possible effect on N : P stoichiometry requires further study. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

  3. 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, Xuexia; Liu, Shuguang; Zhu, Zhiliang; Vogelmann, James E.; Li, Zhengpeng; Ohlen, Donald O.

    2011-01-01

    The concentrations of CO2 and other greenhouse gases in the atmosphere have been increasing and greatly affecting global climate and socio-economic systems. Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High

  4. Responses of plant community composition and biomass production to warming and nitrogen deposition in a temperate meadow ecosystem.

    PubMed

    Zhang, Tao; Guo, Rui; 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.

  5. 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

  6. 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

  7. A wood density and aboveground biomass variability assessment using pre-felling inventory data in Costa Rica.

    PubMed

    Svob, Sienna; Arroyo-Mora, J Pablo; Kalacska, Margaret

    2014-12-01

    The high spatio-temporal variability of aboveground biomass (AGB) in tropical forests is a large source of uncertainty in forest carbon stock estimation. Due to their spatial distribution and sampling intensity, pre-felling inventories are a potential source of ground level data that could help reduce this uncertainty at larger spatial scales. Further, exploring the factors known to influence tropical forest biomass, such as wood density and large tree density, will improve our knowledge of biomass distribution across tropical regions. Here, we evaluate (1) the variability of wood density and (2) the variability of AGB across five ecosystems of Costa Rica. Using forest management (pre-felling) inventories we found that, of the regions studied, Huetar Norte had the highest mean wood density of trees with a diameter at breast height (DBH) greater than or equal to 30 cm, 0.623 ± 0.182 g cm -3 (mean ± standard deviation). Although the greatest wood density was observed in Huetar Norte, the highest mean estimated AGB (EAGB) of trees with a DBH greater than or equal to 30 cm was observed in Osa peninsula (173.47 ± 60.23 Mg ha -1 ). The density of large trees explained approximately 50% of EAGB variability across the five ecosystems studied. Comparing our study's EAGB to published estimates reveals that, in the regions of Costa Rica where AGB has been previously sampled, our forest management data produced similar values. This study presents the most spatially rich analysis of ground level AGB data in Costa Rica to date. Using forest management data, we found that EAGB within and among five Costa Rican ecosystems is highly variable. Combining commercial logging inventories with ecological plots will provide a more representative ground level dataset for the calibration of the models and remotely sensed data used to EAGB at regional and national scales. Additionally, because the non-protected areas of the tropics offer the greatest opportunity to reduce

  8. 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.

  9. 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.

  10. Environmental Controls on Above-Ground Biomass in the Taita Hills, Kenya

    NASA Astrophysics Data System (ADS)

    Adhikari, H.; Heiskanen, J.; Siljander, M.; Maeda, E. E.; Heikinheimo, V.; Pellikka, P.

    2016-12-01

    Tropical forests are globally significant ecosystems which maintain high biodiversity and provide valuable ecosystem services, including carbon sink, climate change mitigation and adaptation. This ecosystem has been severely degraded for decades. However, the magnitude and spatial patterns of the above ground biomass (AGB) in the tropical forest-agriculture landscapes is highly variable, even under the same climatic condition and land use. This work aims 1) to generate wall-to-wall map of AGB density for the Taita Hills in Kenya based on field measurements and airborne laser scanning (ALS) and 2) to examine environmental controls on AGB using geospatial data sets on topography, soils, climate and land use, and statistical modelling. The study area (67000 ha) is located in the northernmost part of the Eastern Arc Mountains of Kenya and Tanzania, and the highest hilltops reach over 2200 m in elevation. Most of the forest area has been cleared for croplands and agroforestry, and hills are surrounded by the semi-arid scrublands and dry savannah at an elevation of 600-900 m a.s.l. As a result, the current land cover is a mosaic of various types of land cover and land use. The field measurements were carried out in total of 216 plots in 2013-2015 for AGB computations and ALS flights were conducted in 2014-2015. AGB map at 30 m x 30 m resolution was implemented using multiple linear regression based on ALS variables derived from the point cloud, namely canopy cover and 25 percentile height of ALS returns (R2 = 0.88). Boosted regression trees (BRT) was used for examining the relationship between AGB and explanatory variables, which were derived from ALS-based high resolution DEM (2 m resolution), soil database, downscaled climate data and land cover/use maps based on satellite image analysis. The results of these analyses will be presented in the conference.

  11. Assessment of forest nutrient pools in view of biomass potentials - a case study from Austria oak stands

    NASA Astrophysics Data System (ADS)

    Yan, S.; Bruckman, V. J.; Glatzel, G.; Hochbichler, E.

    2012-04-01

    As one of the renewable energy forms, bio-energy could help to relieve the pressure which is caused by growing global energy demand. In Austria, large area of forests, traditional utilization of biomass and people's desire to live in a sound environment have supported the positive development of bio-energy. Soil nutrient status is in principle linked with the productivity of the aboveground biomass. This study focuses on K, Ca and Mg pools in soils and aboveground biomass in order to learn more on the temporal dynamics of plant nutrients as indicators for biomass potentials in Quercus dominated forests in northeastern Austria. Three soil types (according to WRB: eutric cambisol, calcic chernozem and haplic luvisol) were considered representative for the area and sampled. We selected nine Quercus petraea dominated permanent plots for this study. Exchangeable cations K, Ca and Mg in the soils were quantified in our study plots. Macronutrients pools of K, Ca and Mg in aboveground biomass were calculated according to inventory data and literature review. The exchangeable cations pool in the top 50 cm of the soil were 882 - 1,652 kg ha-1 for K, 2,661 to 16,510 kg ha-1 for Ca and 320 - 1,850 kg ha-1 for Mg. The nutrient pool in aboveground biomass ranged from 29 to 181 kg ha-1 for K, from 56 to 426 kg ha-1 for Ca and from 4 to 26 kg ha-1 for Mg. The underground exchangeable pools of K, Ca and Mg are generally 10, 22 and 58 times higher than aboveground biomass nutrient pools. Our results showed that the nutrient pools in the mineral soil are sufficient to support the tree growth. The levels of soil nutrients in particular K, Ca and Mg in our study areas are reasonably high and do not indicate the necessity for additional fertilization under current silvicultural practices and biomass extraction rate. The forest in our study areas is in favorable condition to supply biomass as raw material for energy utilization.

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

    PubMed

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

    2017-06-23

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

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

    PubMed

    Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

    2018-03-01

    Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

  14. Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes

    NASA Astrophysics Data System (ADS)

    Halligan, K. Q.; Roberts, D. A.

    2006-12-01

    Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation

  15. 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

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

    PubMed

    Doetterl, Sebastian; Kearsley, Elizabeth; Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal

    2015-01-01

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

  17. 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

  18. 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

  19. A regression-adjusted approach can estimate competing biomass

    Treesearch

    James H. Miller

    1983-01-01

    A method is presented for estimating above-ground herbaceous and woody biomass on competition research plots. On a set of destructively-sampled plots, an ocular estimate of biomass by vegetative component is first made, after which vegetation is clipped, dried, and weighed. Linear regressions are then calculated for each component between estimated and actual weights...

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

    NASA Astrophysics Data System (ADS)

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

    2018-06-01

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

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

    Treesearch

    J.W. Raich; D.A. Clark; L. Schwendenmann; Tana Wood

    2014-01-01

    Young secondary forests and plantations in the moist tropics often have rapid rates of biomass accumulation and thus sequester large amounts of carbon. Here, we compare results from mature forest and nearby 15–20 year old tree plantations in lowland Costa Rica to evaluate differences in allocation of carbon to aboveground production and root systems. We found that the...

  2. Estimating aboveground biomass of mariola (Parthenium incanum) from plant dimensions

    Treesearch

    Carlos Villalobos

    2007-01-01

    The distribution and abundance of plant biomass in space and time are important properties of rangeland ecosystem. Land managers and researchers require reliable shrub weight estimates to evaluate site productivity, food abundance, treatment effects, and stocking rates. Rapid, nondestructive methods are needed to estimate shrub biomass in semi-arid ecosystems. Shrub...

  3. Waveform LiDAR across forest biomass gradients

    NASA Astrophysics Data System (ADS)

    Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.

    2011-12-01

    Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (< 50Mg/ha) AGB. We relate field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Garten, Jr, C. T.; Smith, Jeffery L.; Tyler, Donald 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, themore » 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.« less

  5. Quantifying the coarse-root biomass of intensively managed loblolly pine plantations

    Treesearch

    Ashley T. Miller; H. Lee Allen; Chris A. Maier

    2006-01-01

    Most of the carbon accumulation during a forest rotation is in plant biomass and the forest floor. Most of the belowground biomass in older loblolly pine (Pinus taeda L.) forests is in coarse roots, and coarse roots persist longer after harvest than aboveground biomass and fine roots. The main objective was to assess the carbon accumulation in coarse...

  6. Quantifying the coarse-root biomass of intensively managed loblolly pine plantations

    Treesearch

    Ashley T. Miller; H. Lee Allen; Chris A. Maier

    2006-01-01

    Most of the carbon accumulation during a forest rotation is in plant biomass and the forest floor. Most of the belowground biomass in older loblolly pine (Pinus taeda L.) forests is in coarse roots, and coarse roots ersist longer after harvest than aboveground biomass and fine oots. The main objective was to assess the carbon accumulation in coarse...

  7. Biomass and nutrient distributions in central Oregon second-growth ponderosa pine ecosystems.

    Treesearch

    Susan N. Little; Lauri J. Shainsky

    1995-01-01

    We investigated the distribution of biomass and nutrients 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...

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

    PubMed

    Johnson, Michelle O; Galbraith, David; Gloor, Manuel; De Deurwaerder, Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; von Randow, Celso; Monteagudo, Abel; Phillips, Oliver L; Brienen, Roel J W; Feldpausch, Ted R; Lopez Gonzalez, Gabriela; Fauset, Sophie; Quesada, Carlos A; Christoffersen, Bradley; Ciais, Philippe; Sampaio, Gilvan; Kruijt, Bart; Meir, Patrick; Moorcroft, Paul; Zhang, Ke; Alvarez-Davila, Esteban; Alves de Oliveira, Atila; Amaral, Ieda; Andrade, Ana; Aragao, Luiz E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Arroyo, Luzmila; Aymard, Gerardo A; Baraloto, Christopher; Barroso, Jocely; Bonal, Damien; Boot, Rene; Camargo, Jose; Chave, Jerome; Cogollo, Alvaro; Cornejo Valverde, Fernando; Lola da Costa, Antonio C; Di Fiore, Anthony; Ferreira, Leandro; Higuchi, Niro; Honorio, Euridice N; Killeen, Tim J; Laurance, Susan G; Laurance, William F; Licona, Juan; Lovejoy, Thomas; Malhi, Yadvinder; Marimon, Bia; Marimon, Ben Hur; Matos, Darley C L; Mendoza, Casimiro; Neill, David A; Pardo, Guido; Peña-Claros, Marielos; Pitman, Nigel C A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Roopsind, Anand; Rudas, Agustin; Salomao, Rafael P; Silveira, Marcos; Stropp, Juliana; Ter Steege, Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van der Heijden, Geertje M F; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A; Baker, Timothy R

    2016-12-01

    Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

  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 NITROGEN USE EFFICIENCY AND ...

    EPA Pesticide Factsheets

    Long-term nitrogen (N) fertilization studies suggest shifting dominance from Spartina alterniflora to Distichlis spicata, although the underlying mechanism is unclear. A limitation on our ability to predict changes is a poor understanding of resource use under ambient conditions. The present project compares growth rates and N use dynamics between two emerging salt marsh dominants, S. alterniflora and D. spicata. We hypothesize that under ambient Narragansett Bay nutrient conditions, S. alterniflora is a more efficient user of N than D. spicata. Spartina alterniflora and D. spicata cores were collected from the field and raised in a greenhouse. Heights of all stems were measured weekly to determine growth rates. To understand N movement, a pulse of 15N was added and three cores were sacrificed each subsequent week. Live aboveground biomass was separated into stems and leaves, with leaves categorized based on their position from the top of the stem. Samples were analyzed by isotope ratio mass spectrometry to trace N accumulation in different pools over time. One week after the 15N pulse, most of the aboveground 15N was bound in the stems and the youngest leaves. Efficient nutrient transfer in photosynthetic material likely provides a stronger competitive advantage for taller plants, which are able to compete better for light. Growth rates of S. alterniflora proved to be more variable over time than that of D. spicata. A better understanding of N dynamics under am

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

    PubMed Central

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

    2018-01-01

    Clipping, removal of aboveground plant biomass, is an important issue in grassland ecology. However, few studies have focused on the effect of clipping on belowground microbial communities. Using integrated metagenomic technologies, we examined the taxonomic and functional responses of soil microbial communities to annual clipping (2010–2014) in a grassland ecosystem of the Great Plains of North America. Our results indicated that clipping significantly (P < 0.05) increased root and microbial respiration rates. Annual temporal variation within the microbial communities was much greater than the significant changes introduced by clipping, but cumulative effects of clipping were still observed in the long-term scale. The abundances of some bacterial and fungal lineages including Actinobacteria and Bacteroidetes were significantly (P < 0.05) changed by clipping. Clipping significantly (P < 0.05) increased the abundances of labile carbon (C) degrading genes. More importantly, the abundances of recalcitrant C degrading genes were consistently and significantly (P < 0.05) increased by clipping in the last 2 years, which could accelerate recalcitrant C degradation and weaken long-term soil carbon stability. Furthermore, genes involved in nutrient-cycling processes including nitrogen cycling and phosphorus utilization were also significantly increased by clipping. The shifts of microbial communities were significantly correlated with soil respiration and plant productivity. Intriguingly, clipping effects on microbial function may be highly regulated by precipitation at the interannual scale. Altogether, our results illustrated the potential of soil microbial communities for increased soil organic matter decomposition under clipping land-use practices. PMID:29904372

  12. Leaf Area, Vegetation Biomass and Nutrient Content, Barrow, Alaska, 2012 - 2013

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Victoria Sloan; David McGuire; Eugenie Euskirchen

    This dataset consists of measurements of vegetation harvested from Areas A to D of Intensive Site 1 at the Next-Generation Ecosystem Experiments (NGEE) Arctic site near Barrow, Alaska. The dataset includes i) values of leaf area index, biomass, carbon (C), nitrogen (N) and phosphorus (P) content of aboveground plant parts from 0.25 m × 0.25 m clip-plots at peak growing season and ii) fine-root biomass from 5.08-cm diameter soil cores taken throughout the active layer in the same location as the clip plots in late July-early August 2012, and iii) values of aboveground biomass and nitrogen (N) content measured frommore » 0.1 m × 0.1 m clip-plots harvested at 2-week intervals throughout the 2013 growing season.« less

  13. Biomass of open-grown Virginia pine

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Madgwick, H.A.I.; Olah, F.D.; Burkhart, H.E.

    1977-03-01

    Five open-grown Pinus virginiana trees ranging from 1.05 to 15.78 m tall were destructively sampled and the data used to obtain relationships between tree size and biomass to estimate dry matter production. The ratio of foliage to above-ground woody biomass decreased with tree age from 0.4 for a 7-year-old tree to 0.05 for a 39-year-old tree. Needle longevity increased with tree age. 5 references.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

    Mangroves are integral to ecosystem services provided by the coastal zone, in particular carbon (C) sequestration and storage. Allometric relationships linking mangrove height to estimated biomass and C stocks have been developed from field sampling, while various forms of remote sensing has been used to map vegetation height and biomass. Here we combine both these approaches to investigate spatial patterns in living biomass of mangrove forests in a small area of mangrove in north-west Australia. This study used LiDAR data and Landsat 8 OLI (Operational Land Imager) with allometric equations to derive mangrove height, biomass, and C stock estimates. We estimated the study site, Mangrove Bay, a semi-arid site in north-western Australia, contained 70 Mg ha-1 biomass and 45 Mg C ha-1 organic C, with total stocks of 2417 Mg biomass and 778 Mg organic C. Using spatial statistics to identify the scale of clustering of mangrove pixels, we found that living biomass and C stock declined with increasing distance from hydrological features (creek entrance: 0-150 m; y = -0.00041x + 0.9613, R2 = 0.96; 150-770 m; y = -0.0008x + 1.6808, R2 = 0.73; lagoon: y = -0.0041x + 3.7943, R2 = 0.78). Our results illustrate a set pattern of living C distribution within the mangrove forest, and then highlight the role hydrologic features play in determining C stock distribution in the arid zone.

  16. 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

  17. 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.

  18. 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.

  19. The microcomputer scientific software series 5: the BIOMASS user's guide.

    Treesearch

    George E. Host; Stephen C. Westin; William G. Cole; Kurt S. Pregitzer

    1989-01-01

    BIOMASS is an interactive microcomputer program that uses allometric regression equations to calculate aboveground biomass of common tree species of the Lake States. The equations are species-specific and most use both diameter and height as independent variables. The program accommodates fixed area and variable radius sample designs and produces both individual tree...

  20. Environmental limitation mapping of potential biomass resources across the conterminous United States

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.

    Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic

  1. Environmental limitation mapping of potential biomass resources across the conterminous United States

    DOE PAGES

    Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.; ...

    2017-12-22

    Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic

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

    NASA Astrophysics Data System (ADS)

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

    2018-02-01

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

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

    NASA Astrophysics Data System (ADS)

    Köhler, P.; Huth, A.

    2010-05-01

    The canopy height of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or lidar. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI). The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. It is found that for undisturbed forest and a variety of disturbed forests situations AGB can be expressed as a power-law function of canopy height h (AGB=a·hb) with an r2~60% for a spatial resolution of 20 m×20 m (0.04 ha, also called plot size). The regression is becoming significant better for the hectare wide analysis of the disturbed forest sites (r2=91%). There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2~60%) between AGB and the area fraction in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot data from the same region and with the large-scale forest inventory in Lambir. We conclude that the spaceborne remote sensing techniques have the potential to

  4. Tropical forest biomass estimation from truncated stand tables.

    Treesearch

    A. J. R. Gillespie; S. Brown; A. E. Lugo

    1992-01-01

    Total aboveground forest biomass may be estimated through a variety of techniques based on commercial inventory stand and stock tables. Stand and stock tables from tropical countries commonly omit trees bellow a certain commercial limit.

  5. Stand structural diversity rather than species diversity enhances aboveground carbon storage in secondary subtropical forests in Eastern China

    NASA Astrophysics Data System (ADS)

    Ali, Arshad; Yan, En-Rong; Chen, Han Y. H.; Chang, Scott X.; Zhao, Yan-Tao; Yang, Xiao-Dong; Xu, Ming-Shan

    2016-08-01

    Stand structural diversity, typically characterized by variances in tree diameter at breast height (DBH) and total height, plays a critical role in influencing aboveground carbon (C) storage. However, few studies have considered the multivariate relationships of aboveground C storage with stand age, stand structural diversity, and species diversity in natural forests. In this study, aboveground C storage, stand age, tree species, DBH and height diversity indices, were determined across 80 subtropical forest plots in Eastern China. We employed structural equation modelling (SEM) to test for the direct and indirect effects of stand structural diversity, species diversity, and stand age on aboveground C storage. The three final SEMs with different directions for the path between species diversity and stand structural diversity had a similar goodness of fit to the data. They accounted for 82 % of the variation in aboveground C storage, 55-59 % of the variation in stand structural diversity, and 0.1 to 9 % of the variation in species diversity. Stand age demonstrated strong positive total effects, including a positive direct effect (β = 0.41), and a positive indirect effect via stand structural diversity (β = 0.41) on aboveground C storage. Stand structural diversity had a positive direct effect on aboveground C storage (β = 0.56), whereas there was little total effect of species diversity as it had a negative direct association with, but had a positive indirect effect, via stand structural diversity, on aboveground C storage. The negligible total effect of species diversity on aboveground C storage in the forests under study may have been attributable to competitive exclusion with high aboveground biomass, or a historical logging preference for productive species. Our analyses suggested that stand structural diversity was a major determinant for variations in aboveground C storage in the secondary subtropical forests in Eastern China. Hence, maintaining tree DBH and

  6. 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.

  7. Tundra plant biomass distribution and environmental constraints on the North Slope of Alaska

    NASA Astrophysics Data System (ADS)

    Berner, L. T.; Jantz, P.; Goetz, S. J.

    2017-12-01

    Rising temperatures are increasing plant productivity and biomass in the Arctic tundra, with pronounced greening having occurred in northern Alaska during recent decades. Increasing plant biomass will drive biogeochemical and biophysical feedback to regional climate; however, the amount and spatial distribution of plant biomass remains highly uncertain in these northern ecosystems. In this study, we mapped both plant aboveground biomass (AGB) and the shrub component across the North Slope of Alaska at 30 m spatial resolution by combining satellite and field measurements, and then examined how the spatial distribution of AGB was constrained by regional climate and local topography. Specifically, we developed regression models for predicting AGB based on the Normalized Difference Vegetation Index (NDVI) derived from Landsat satellite imagery. These regression models incorporated previously published field measurements from 27 tundra locations and showed strong relationships between AGB and peak summer NDVI (r2=0.75-0.80). We then predicted AGB across the study area by combining these regression models with a peak summer NDVI composite mosaic derived from over 2,000 Landsat scenes acquired between 2007 and 2016. We also created uncertainty maps using a Monte Carlo approach. The resulting biomass maps indicated that plant AGB averaged 0.72 kg m-2 (95% CI = 0.50-1.01 kg m-2) and totaled 108 Tg (75-153 Tg) across the domain, with shrub AGB accounting for about 44% of plant AGB. Plant and shrub AGB peaked in riparian areas, where permafrost active layers are generally deeper and nutrients more readily available. Plant and shrub AGB were also strongly influenced by summer temperature, with average plant AGB doubling and shrub AGB quadrupling between areas with the coldest and warmest summers. Furthermore, the contribution of shrub AGB to total plant AGB increased with increasing summer temperatures. Future warming will likely increase plant AGB and the contribution from

  8. Effectiveness of Biomass Harvesting from Stormwater Detention Areas in Reducing Phosphorus Discharges

    NASA Astrophysics Data System (ADS)

    Shukla, A.; Shukla, S.

    2014-12-01

    Stormwater Detention Areas (SDAs) in agricultural landscapes are considered to be the most important Best Management Practice by state agencies in Florida. Two main processes responsible for Phosphorus (P) retention in SDAs are soil adsorption and plant uptake. Long term pumping of agricultural drainage may saturate the SDA's soil with P which can put these systems at the risk of becoming a source of P. Given that these systems already occupy part of the farmland and are costly to build, interventions are needed to sustain SDAs as a sink of P. Soil and vegetation P content at two SDAs (SDA1 and 2) in south Florida was quantified in addition to inflow and outflow P loads. Analyses showed that soil was saturated with limited to no P adsorption capacity remaining. Negative Soil Phosphorus Storage Capacity (SPSC) indicated that soil was at a risk of P release. Given these conditions, the only avenue to remove P from SDAs without any potentially undesirable ecological impacts, was biomass harvesting. At SDA1, results showed that harvesting the aboveground biomass would result in 19% extra P retention if the current vegetation (Para grass, Brachiaria mutica) is harvested. Given that aboveground tissue P content of Para grass is very low, replacing it with another native grass (Maidencane, Panicum hemitomon) and harvesting it annually could retain most of the incoming P load. A similar analysis showed that at SDA2, almost 40% additional P could be retained by harvesting aboveground biomass of the dominant vegetation (Torpedo Grass, Panicum repens and Smartweed, Polygonum hydropiperoides). A spatial analysis in conjunction with SPSC values and aboveground plant P indicated that biomass harvesting can transform both the SDAs from a source to sink in 2 to 3 years. A fifty year net present value analysis showed that overall it is an economically feasible strategy with an average annual benefit of 3,223 and 34,825 for SDA1 and 2, respectively. Harvesting aboveground biomass

  9. Assessing biomass of diverse coastal marsh ecosystems using statistical and machine learning models

    NASA Astrophysics Data System (ADS)

    Mo, Yu; Kearney, Michael S.; Riter, J. C. Alexis; Zhao, Feng; Tilley, David R.

    2018-06-01

    The importance and vulnerability of coastal marshes necessitate effective ways to closely monitor them. Optical remote sensing is a powerful tool for this task, yet its application to diverse coastal marsh ecosystems consisting of different marsh types is limited. This study samples spectral and biophysical data from freshwater, intermediate, brackish, and saline marshes in Louisiana, and develops statistical and machine learning models to assess the marshes' biomass with combined ground, airborne, and spaceborne remote sensing data. It is found that linear models derived from NDVI and EVI are most favorable for assessing Leaf Area Index (LAI) using multispectral data (R2 = 0.7 and 0.67, respectively), and the random forest models are most useful in retrieving LAI and Aboveground Green Biomass (AGB) using hyperspectral data (R2 = 0.91 and 0.84, respectively). It is also found that marsh type and plant species significantly impact the linear model development (P < .05 in both cases). Sensors with coarser spatial resolution yield lower LAI values because the fine water networks are not detected and mixed into the vegetation pixels. The Landsat OLI-derived map shows the LAI of coastal mashes in Louisiana mostly ranges from 0 to 5.0, and is highest for freshwater marshes and for marshes in the Atchafalaya Bay delta. The CASI-derived maps show that LAI of saline marshes at Bay Batiste typically ranges from 0.9 to 1.5, and the AGB is mostly less than 900 g/m2. This study provides solutions for assessing the biomass of Louisiana's coastal marshes using various optical remote sensing techniques, and highlights the impacts of the marshes' species composition on the model development and the sensors' spatial resolution on biomass mapping, thereby providing useful tools for monitoring the biomass of coastal marshes in Louisiana and diverse coastal marsh ecosystems elsewhere.

  10. Verification of the Jenkins and FIA sapling biomass equations for hardwood species in Maine

    Treesearch

    Andrew S. Nelson; Aaron R. Weiskittel; Robert G. Wagner; Michael R. Saunders

    2012-01-01

    In 2009, the Forest Inventory and Analysis Program (FIA) updated its biomass estimation protocols by switching to the component ratio method to estimate biomass of medium and large trees. Additionally, FIA switched from using regional equations to the current FIA aboveground sapling biomass equations that predict woody sapling (2.5 to 12.4 cm d.b.h.) biomass using the...

  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 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

  12. 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

  13. Assessing the potential for biomass energy development in South Carolina

    Treesearch

    Roger C. Conner; Tim O. Adams; Tony G. Johnson

    2009-01-01

    An assessment of the potential for developing a sustainable biomass energy industry in South Carolina was conducted. Biomass as defined by Forest Inventory and Analysis is the aboveground dry weight of wood in the bole and limbs of live trees ≥1-inch diameter at breast height, and excludes tree foliage, seedlings, and understory...

  14. 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.

  15. Predicting small-diameter loblolly pine aboveground biomass in naturally regenerated stands

    Treesearch

    Kristin M. McElligott; Don C. Bragg; Jamie L. Schuler

    2015-01-01

    There is growing interest in managing southern pine forests for both carbon sequestration and bioenergy. For instance, thinning otherwise unmerchantable trees in naturally regenerated pine-dominated forests should generate biomass without conflicting with more traditional forest products. However, we lack the tools to accurately quantify the biomass in these...

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

    PubMed

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

    2015-09-01

    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

  17. Elevated CO2 enrichment induces a differential biomass response in a mixed species temperate forest plantation.

    PubMed

    Smith, Andrew R; Lukac, Martin; Hood, Robin; Healey, John R; Miglietta, Franco; Godbold, Douglas L

    2013-04-01

    In a free-air carbon dioxide (CO(2)) enrichment study (BangorFACE), Alnus glutinosa, Betula pendula and Fagus sylvatica were planted in areas of one-, two- and three-species mixtures (n = 4). The trees were exposed to ambient or elevated CO(2) (580 μmol mol(-1)) for 4 yr, and aboveground growth characteristics were measured. In monoculture, the mean effect of CO(2) enrichment on aboveground woody biomass was + 29, + 22 and + 16% for A. glutinosa, F. sylvatica and B. pendula, respectively. When the same species were grown in polyculture, the response to CO(2) switched to + 10, + 7 and 0% for A. glutinosa, B. pendula and F. sylvatica, respectively. In ambient atmosphere, our species grown in polyculture increased aboveground woody biomass from 12.9 ± 1.4 to 18.9 ± 1.0 kg m(-2), whereas, in an elevated CO(2) atmosphere, aboveground woody biomass increased from 15.2 ± 0.6 to 20.2 ± 0.6 kg m(-2). The overyielding effect of polyculture was smaller (+ 7%) in elevated CO(2) than in an ambient atmosphere (+ 18%). Our results show that the aboveground response to elevated CO(2) is affected significantly by intra- and interspecific competition, and that the elevated CO(2) response may be reduced in forest communities comprising tree species with contrasting functional traits. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  18. Biomass of singleleaf pinyon and Utah juniper

    Treesearch

    E. L. Miller; R. O. Meeuwig; J. D. Budy

    1981-01-01

    Biomass determinations in singleleaf pinyon (Pinus monophylla) - Utah juniper (Juniperus osteosperma) stands in Nevada indicate that stem diameter and average crown diameter are the tree measurements most highly correlated with ovendry weights. The equations and tables developed provide a means for estimating the total aboveground...

  19. The roles of community biomass and species pools in the regulation of plant diversity

    USGS Publications Warehouse

    Grace, J.B.

    2001-01-01

    Considerable debate has developed over the importance of community biomass and species pools in the regulation of community diversity. Attempts to explain patterns of plant diversity as a function of community biomass or productivity have been only partially successful and in general, have explained only a fraction of the observed variation in diversity. At the same time studies that have focused on the importance of species pools have led some to conclude that diversity is primarily regulated in the short term by the size of the species pool rather than by biotic interactions. In this paper, I explore how community biomass and species pools may work in combination to regulate diversity in herbaceous plant communities. To address this problem, I employ a simple model in which the dynamics of species richness are a function of aboveground community biomass and environmentally controlled gradients in species pools. Model results lead to two main predictions about the role of biomass regulation: (1) Seasonal dynamics of richness will tend to follow a regular oscillation, with richness rising to peak values during the early to middle portion of the growing season and then declining during the latter part of the season. (2.) Seasonal dieback of aboveground tissues facilitates the long-term maintenance of high levels of richness in the community. The persistence of aboveground tissues and accumulation of litter are especially important in limiting the number of species through the suppression of recruitment. Model results also lead to two main predictions about the role of species pools: (1) The height and position of peak richness relative to community biomass will be influenced by the rate at which the species pool increases as available soil resources increase. (2) Variations in nonresource environmental factors (e.g. soil pH or soil salinity) have the potential to regulate species pools in a way that is uncorrelated with aboveground biomass. Under extreme conditions

  20. 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

  1. Biomass equations for shrub species of Tamualipan thornscrub of North-Eastern Mexico

    Treesearch

    J. Navar; E. Mendez; A. Najera; J. Graciano; V. Dale; B. Parresol

    2004-01-01

    Nine additive allometric equations for computing above-ground, standing biomass were developed for the plant community and for each of 18 single species typical of the Tamaulipan thornscrub of north-eastern Mexico. Equations developed using additive procedures in seemingly unrelated linear regression provided statistical efficiency in total biomass estimates at the...

  2. Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

    DOE PAGES

    Gonçalves, Fabio; Treuhaft, Robert; Law, Beverly; ...

    2017-01-07

    Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertaintymore » that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.« less

  3. Aboveground mechanical stimuli affect belowground plant-plant communication.

    PubMed

    Elhakeem, Ali; Markovic, Dimitrije; Broberg, Anders; Anten, Niels P R; Ninkovic, Velemir

    2018-01-01

    Plants can detect the presence of their neighbours and modify their growth behaviour accordingly. But the extent to which this neighbour detection is mediated by abiotic stressors is not well known. In this study we tested the acclimation response of Zea mays L. seedlings through belowground interactions to the presence of their siblings exposed to brief mechano stimuli. Maize seedling simultaneously shared the growth solution of touched plants or they were transferred to the growth solution of previously touched plants. We tested the growth preferences of newly germinated seedlings toward the growth solution of touched (T_solution) or untouched plants (C_solution). The primary root of the newly germinated seedlings grew significantly less towards T_solution than to C_solution. Plants transferred to T_solution allocated more biomass to shoots and less to roots. While plants that simultaneously shared their growth solution with the touched plants produced more biomass. Results show that plant responses to neighbours can be modified by aboveground abiotic stress to those neighbours and suggest that these modifications are mediated by belowground interactions.

  4. Regional contingencies in the relationship between aboveground biomass and litter in the world’s grasslands

    Treesearch

    L.R. O' Halloran; E.T. Borer; E.W. Seabloom; A.S. MacDougall; E.E. Cleland; R.L. McCulley; S. Hobbie; S. Harpole; N.M. DeCrappeo; C.-J. Chu; J.D. Bakker; K.F. Davies; G. Du; J. Firn; N. Hagenah; K.S. Hofmockel; J.M.H. Knops; W. Li; B.A. Melbourne; J.W. Morgan; J.L. Orrock; S.M. Prober; C.J. Stevens

    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...

  5. Biomass Production and Nitrogen Recovery after Fertilization of Young Loblolly Pines

    Treesearch

    J. B. Baker; G. L. Switzer; L. E. Nelson

    1974-01-01

    Ammonium nitrate applied at rates of 112 and 224 kg of N/ha in successive years to different areas of a young loblolly pine (Pinus taeda L.) plantation increased aboveground biomass by 25% and N accumulation by 30%. Fertilization at plantation age 3 resulted in significantly greater biomass and N accumulations in the pine; fertilization at age 4...

  6. Developing a Carbon Monitoring System For Pinyon-juniper Forests and Woodlands

    NASA Astrophysics Data System (ADS)

    Falkowski, M. J.; Hudak, A. T.; Fekety, P.; Filippelli, S.

    2017-12-01

    Pinyon-juniper (PJ) forests and woodlands are the third largest vegetation type in the United States. They cover over 40 million hectares across the western US, representing 40% of the total forest and woodland area in the Intermountain West. Although the density of carbon stored in these ecosystems is relatively low compared to other forest types, the vast area of short stature forests and woodlands (both nationally and globally) make them critical components of regional, national, and global carbon budgets. The overarching goal of this research is to prototype a carbon monitoring, reporting, and verification (MRV) system for characterizing total aboveground biomass stocks and flux across the PJ vegetation gradient in the western United States. We achieve this by combining in situ forest measurements and novel allometric equations with tree measurements derived from high resolution airborne imagery to map aboveground biomass across 500,000 km2 in the Western US. These high-resolution maps of aboveground biomass are then leveraged as training data to predict biomass flux through time from Landsat time-series data. The results from this research highlight the potential in mapping biomass stocks and flux in open forests and woodlands, and could be easily adopted into an MRV framework.

  7. Improving LiDAR Biomass Model Uncertainty through Non-Destructive Allometry and Plot-level 3D Reconstruction with Terrestrial Laser Scanning

    NASA Astrophysics Data System (ADS)

    Stovall, A. E.; Shugart, H. H., Jr.

    2017-12-01

    Future NASA and ESA satellite missions plan to better quantify global carbon through detailed observations of forest structure, but ultimately rely on uncertain ground measurement approaches for calibration and validation. A significant amount of the uncertainty in estimating plot-level biomass can be attributed to inadequate and unrepresentative allometric relationships used to convert plot-level tree measurements to estimates of aboveground biomass. These allometric equations are known to have high errors and biases, particularly in carbon rich forests because they were calibrated with small and often biased samples of destructively harvested trees. To overcome this issue, a non-destructive methodology for estimating tree and plot-level biomass has been proposed through the use of Terrestrial Laser Scanning (TLS). We investigated the potential for using TLS as a ground validation approach in LiDAR-based biomass mapping though virtual plot-level tree volume reconstruction and biomass estimation. Plot-level biomass estimates were compared on the Virginia-based Smithsonian Conservation Biology Institute's SIGEO forest with full 3D reconstruction, TLS allometry, and Jenkins et al. (2003) allometry. On average, full 3D reconstruction ultimately provided the lowest uncertainty estimate of plot-level biomass (9.6%), followed by TLS allometry (16.9%) and the national equations (20.2%). TLS offered modest improvements to the airborne LiDAR empirical models, reducing RMSE from 16.2% to 14%. Our findings suggest TLS plot acquisitions and non-destructive allometry can play a vital role for reducing uncertainty in calibration and validation data for biomass mapping in the upcoming NASA and ESA missions.

  8. 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

  9. Mapping the above and belowground biomass in three landscapes in Cameroon, Rwanda and DRC: pilot cases in REDD+ pilot project.

    NASA Astrophysics Data System (ADS)

    Sufo Kankeu, R.

    2017-12-01

    A number of biomass/carbon maps have been recently produced using different approaches and despite their comparison there is still a gap. To fill this gap there is a need to provide accurate maps based on the field data on all types of land use and land cover. Based on the field data from plots established in three pilot projects around Virunga National park in Rwanda, Tri-national Sangha landscape in Cameroon and lac Télé-Lac Tumba landscape in DRC, this paper intend to analyse the relationship between land use change and biomass and present the variability through biomass/carbon maps. The above and belowground biomass was calculated from 95 nested plots of 20 meters radius. The value of biomass/carbon per plot were thus used to elaborate carbon maps of each study site. In the same the way the correlation between the land use and underground and above ground carbon stock were analysed using geographically weighted regression. These data have been joint with classified Spot 5 image and aggregated to come out will acceptable result. Results show that there is a strong relationship between land use in various project sites and the carbon stock related, the change of a forest cover directly impact on carbon stock/biomass.in the same way carbon map realized base on field data and IDW, Kriging or spline module show an idea on the carbon distribution but the maps are not accurate giving the distance between plots,

  10. Aboveground tree biomass for Pinus ponderosa in northeastern California

    Treesearch

    Martin W. Ritchie; Jianwei Zhang; Todd A. Hamilton

    2013-01-01

    Forest managers need accurate biomass equations to plan thinning for fuel reduction or energy production. Estimates of carbon sequestration also rely upon such equations. The current allometric equations for ponderosa pine (Pinus ponderosa) commonly employed for California forests were developed elsewhere, and are often applied without consideration potential for...

  11. Genotypic Diversity for Biomass Accumulation and Shoot-Root Allometry in the Grass Brachypodium distachyon

    NASA Astrophysics Data System (ADS)

    Jansson, C.; Handakumbura, P. P.; Fortin, D.; Stanfill, B.; Rivas-Ubach, A.

    2017-12-01

    Predicting carbon uptake, assimilation and allocation for current and future biogeographical environments, including climate, is critical for our ability to select and/or design plant genotypes to meet increasing demand for plant biomass going into food, feed and energy production, while at the same time maintain or increase soil organic matter (SOM for soil fertility and carbon storage, and reduce emission of greenhouse gasses. As has been demonstrated for several plant species allometric relationships may differ between plant genotypes. Exploring plant genotypic diversity for biomass accumulation and allometry will potentially enable selection of genotypes with high CO2 assimilation and favorable allocation of recent photosynthate into above-ground and below-ground biomass. We are investigating genotypic diversity for PFTs in natural accessions of the annual C3 grass Brachypodium distachyon under current and future climate scenarios and how genotypic diversity correlates with metabolite profiles in aboveground and below-ground biomass. In the current study, we compare effects from non-stressed and drought conditions on biomass accumulation and shoot-root allometry.

  12. Soil Moisture Limitations on Monitoring Boreal Forest Regrowth Using Spaceborne L-Band SAR Data

    NASA Technical Reports Server (NTRS)

    Kasischke, Eric S.; Tanase, Mihai A.; Bourgeau-Chavez, Laura L.; Borr, Matthew

    2011-01-01

    A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the summer/fall of 2007 and one date in the summer of 2009 were used. Significant linear correlations were found between the log of aboveground biomass (range of 0.02 to 22.2 t ha-1) and (L-HH) and (L-HV) for the data collected on each of the three dates, with the highest correlation found using the LHV data collected when soil moisture was highest. Soil moisture, however, did change the correlations between L-band and aboveground biomass, and the analyses suggest that the influence of soil moisture is biomass dependent. The results indicate that to use L-band SAR data for mapping aboveground biomass and monitoring forest regrowth will require development of approaches to account for the influence that variations in soil moisture have on L-band microwave backscatter, which can be particularly strong when low levels of aboveground biomass occur

  13. 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

  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. Tree height and tropical forest biomass estimation

    Treesearch

    M.O. Hunter; M. Keller; D. Vitoria; D.C. Morton

    2013-01-01

    Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass....

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

    NASA Astrophysics Data System (ADS)

    Köhler, P.; Huth, A.

    2010-08-01

    The canopy height h of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI) and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height h (AGB = a · hb) with an r2 ~ 60% if data are analysed in a spatial resolution of 20 m × 20 m (0.04 ha, also called plot size). The correlation coefficient of the regression is becoming significant better in the disturbed forest sites (r2 = 91%) if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2 ~ 60%) between AGB and the area fraction of gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot (PSP) data from the same region and with the

  17. 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.

  18. 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.

  19. 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.

    2017-01-01

    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.

  20. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    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.

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

    PubMed

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

    2015-11-01

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

  4. 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.

  5. Biomass yielding potential of naturally regenerated Prosopis juliflora tree stands at three varied ecosystems in southern districts of Tamil Nadu, India.

    PubMed

    Saraswathi, K; Chandrasekaran, S

    2016-05-01

    Fuel energy demand is of great concern in recent times due to the depletion of fossil fuel resources. Biomass serves as widely available primary renewable energy source. Hence, a study was performed to assess the above-ground biomass yielding capability of fuel wood tree Prosopis juliflora in three varied ecosystems viz., coastal, fallow land and riparian ecosystems in southern districts of Tamil Nadu. The results showed that the biomass production potential and above-ground net primary productivity of P. juliflora depend on the age of the tree stands and the nature of ecosystem. A higher biomass yield was observed for P. juliflora trees with 5 to 10 years old when compared to less than 5 years of their age. Among the three ecosystems, the maximum biomass production was recorded in riparian ecosystem. The stands with less than 5-year-old P. juliflora trees gave 1.40 t/ha, and 5- to 10-year-old tree stands produced 27.69 t/ha in riparian ecosystem. Above-ground net primary productivity of both the age groups was high in fallow land ecosystem. In riparian ecosystem, the wood showed high density and low sulphur content than the other two ecosystems. Hence, P. juliflora biomass can serve as an environmentally and economically feasible fuel as well as their utilization proffers an effective means to control its invasiveness.

  6. Fire and the distribution and uncertainty of carbon sequestered as above-ground tree biomass in Yosemite and Sequoia & Kings Canyon National Parks

    USGS Publications Warehouse

    Lutz, James A.; Matchett, John R.; Tarnay, Leland W.; Smith, Douglas F.; Becker, Kendall M.L.; Furniss, Tucker J.; Brooks, Matthew L.

    2017-01-01

    Fire is one of the principal agents changing forest carbon stocks and landscape level distributions of carbon, but few studies have addressed how accurate carbon accounting of fire-killed trees is or can be. We used a large number of forested plots (1646), detailed selection of species-specific and location-specific allometric equations, vegetation type maps with high levels of accuracy, and Monte Carlo simulation to model the amount and uncertainty of aboveground tree carbon present in tree species (hereafter, carbon) within Yosemite and Sequoia & Kings Canyon National Parks. We estimated aboveground carbon in trees within Yosemite National Park to be 25 Tg of carbon (C) (confidence interval (CI): 23–27 Tg C), and in Sequoia & Kings Canyon National Park to be 20 Tg C (CI: 18–21 Tg C). Low-severity and moderate-severity fire had little or no effect on the amount of carbon sequestered in trees at the landscape scale, and high-severity fire did not immediately consume much carbon. Although many of our data inputs were more accurate than those used in similar studies in other locations, the total uncertainty of carbon estimates was still greater than ±10%, mostly due to potential uncertainties in landscape-scale vegetation type mismatches and trees larger than the ranges of existing allometric equations. If carbon inventories are to be meaningfully used in policy, there is an urgent need for more accurate landscape classification methods, improvement in allometric equations for tree species, and better understanding of the uncertainties inherent in existing carbon accounting methods.

  7. Biomass, production and woody detritus in an old coast redwood (Sequoia sempervirens) forest

    USGS Publications Warehouse

    Busing, R.T.; Fujimori, T.

    2005-01-01

    We examined aboveground biomass dynamics, aboveground net primary production (ANPP), and woody detritus input in an old Sequoia sempervirens stand over a three-decade period. Our estimates of aboveground biomass ranged from 3300 to 5800 Mg ha-1. Stem biomass estimates ranged from 3000 to 5200 Mg ha-1. Stem biomass declined 7% over the study interval. Biomass dynamics were patchy, with marked declines in recent tree-fall patches <0.05 ha in size. Larger tree-fall patches approaching 0.2 ha in size were observed outside the study plot. Our estimates of ANPP ranged from 6 to 14 Mg ha -1yr-1. Estimates of 7 to 10 Mg ha-1yr -1 were considered to be relatively accurate. Thus, our estimates based on long-term data corroborated the findings of earlier short-term studies. ANPP of old, pure stands of Sequoia was not above average for temperate forests. Even though production was potentially high on a per stem basis, it was moderate at the stand level. We obtained values of 797 m3 ha -1 and 262 Mg ha-1 for coarse woody detritus volume and mass, respectively. Fine woody detritus volume and mass were estimated at 16 m3 ha-1 and 5 Mg ha-1, respectively. Standing dead trees (or snags) comprised 7% of the total coarse detritus volume and 8% of the total mass. Coarse detritus input averaged 5.7 to 6.9 Mg ha -1yr-1. Assuming steady-state input and pool of coarse detritus, we obtained a decay rate constant of 0.022 to 0.026. The old-growth stand of Sequoia studied had extremely high biomass, but ANPP was moderate and the amount of woody detritus was not exceptionally large. Biomass accretion and loss were not rapid in this stand partly because of the slow population dynamics and low canopy turnover rate of Sequoia at the old-growth stage. Nomenclature: Hickman (1993). ?? Springer 2005.

  8. Aboveground Biomass of Choctawhatchee Sand Pine in Northwest Florida

    Treesearch

    Michael A. Taras

    1980-01-01

    Choctawhatchee sand pine trees 4 to 14 inches d.b.h. were selected from a natural, uneven-aged stand in northwest Florida to determine the weight and volume of above ground biomass. On the average, 85 percent of the green weight of the total tree was wood, 11 percent bark. and 4 percent needles. The average tree sampled had 82 percent of its wood in the stem and 18...

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

    PubMed

    Lima, Robson B DE; Alves, Francisco T; Oliveira, Cinthia P DE; Silva, José A A DA; Ferreira, Rinaldo L C

    2017-01-01

    Dry tropical forests are a key component in the global carbon cycle and their biomass estimates depend almost exclusively of fitted equations for multi-species or individual species data. Therefore, a systematic evaluation of statistical models through validation of estimates of aboveground biomass stocks is justifiable. In this study was analyzed the capacity of generic and specific equations obtained from different locations in Mexico and Brazil, to estimate aboveground biomass at multi-species levels and for four different species. Generic equations developed in Mexico and Brazil performed better in estimating tree biomass for multi-species data. For Poincianella bracteosa and Mimosa ophthalmocentra, only the Sampaio and Silva (2005) generic equation was the most recommended. These equations indicate lower tendency and lower bias, and biomass estimates for these equations are similar. For the species Mimosa tenuiflora, Aspidosperma pyrifolium and for the genus Croton the specific regional equations are more recommended, although the generic equation of Sampaio and Silva (2005) is not discarded for biomass estimates. Models considering gender, families, successional groups, climatic variables and wood specific gravity should be adjusted, tested and the resulting equations should be validated at both local and regional levels as well as on the scales of tropics with dry forest dominance.

  10. 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.

  11. Biomass Retrieval from L-Band Polarimetric UAVSAR Backscatter and PRISM Stereo Imagery

    NASA Technical Reports Server (NTRS)

    Zhang, Zhiyu; Ni, Wenjian; Sun, Guoqing; Huang, Wenli; Ranson, Kenneth J.; Cook, Bruce D.; Guo, Zhifeng

    2017-01-01

    The forest above-ground biomass (AGB) and spatial distribution of vegetation elements have profound effects on the productivity and biodiversity of terrestrial ecosystems. In this paper, we evaluated biomass estimation from L-band Synthetic Aperture Radar (SAR) data acquired by National Aeronautics and Space Administration (NASA) Uninhabited Aerial Vehicle SAR (UAVSAR) and the improvement of accuracy by adding canopy height information derived from stereo imagery acquired by Japan Aerospace Exploration Agency (JAXA) Panchromatic Remote Sensing Instrument for Stereo Mapping (PRISM) on-board the Advanced Land Observing Satellite (ALOS). Various models for prediction of forest biomass from UAVSAR data were investigated at pixel sizes of 1/4 ha (50 m x 50 m) and 1 ha. The variance inflation factor (VIF) was calculated for each of the explanatory variables in multivariable regression models to assess the multi-collinearity between explanatory variables. In addition, the t-and p-values were used to interpret the significance of the coefficients of each explanatory variables. The R(exp. 2), Root Mean Square Error (RMSE), bias and Akaike information criterion (AIC), and leave-one-out cross-validation (LOOCV) and bootstrapping were used to validate models. At 1/4-ha scale, the R(exp. 2) and RMSE of biomass estimation from a model using a single track of polarimetric UAVSAR data were 0.59 and 52.08 Mg/ha. With canopy height from PRISM as additional independent variable, R(exp. 2) increased to 0.76 and RMSE decreased to 39.74 Mg/ha (28.24%). At 1-ha scale, the RMSE of biomass estimation based on UAVSAR data of a single track was 39.42 Mg/ha with a R(exp. 2) of 0.77. With the canopy height from PRISM, R(exp. 2) increased to 0.86 and RMSE decreased to 29.47 Mg/ha (20.18%). The models using UAVSAR data alone underestimated biomass at levels above approximately 150 Mg/ha showing the saturation phenomenon. Adding canopy height from PRISM stereo imagery significantly improved the

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

    USDA-ARS?s Scientific Manuscript database

    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...

  13. Carbon emissions risk map from deforestation in the tropical Amazon

    NASA Astrophysics Data System (ADS)

    Ometto, J.; Soler, L. S.; Assis, T. D.; Oliveira, P. V.; Aguiar, A. P.

    2011-12-01

    Assis, Pedro Valle This work aims to estimate the carbon emissions from tropical deforestation in the Brazilian Amazon associated to the risk assessment of future land use change. The emissions are estimated by incorporating temporal deforestation dynamics, accounting for the biophysical and socioeconomic heterogeneity in the region, as well secondary forest growth dynamic in abandoned areas. The land cover change model that supported the risk assessment of deforestation, was run based on linear regressions. This method takes into account spatial heterogeneity of deforestation as the spatial variables adopted to fit the final regression model comprise: environmental aspects, economic attractiveness, accessibility and land tenure structure. After fitting a suitable regression models for each land cover category, the potential of each cell to be deforested (25x25km and 5x5 km of resolution) in the near future was used to calculate the risk assessment of land cover change. The carbon emissions model combines high-resolution new forest clear-cut mapping and four alternative sources of spatial information on biomass distribution for different vegetation types. The risk assessment map of CO2 emissions, was obtained by crossing the simulation results of the historical land cover changes to a map of aboveground biomass contained in the remaining forest. This final map represents the risk of CO2 emissions at 25x25km and 5x5 km until 2020, under a scenario of carbon emission reduction target.

  14. Effects of Model Choice and Forest Structure on Inventory-Based Estimations of Puerto Rican Forest Biomass.

    Treesearch

    THOMAS J. BRANDEIS; MARIA DEL ROCIO SUAREZ ROZO

    2005-01-01

    Total aboveground live tree biomass in Puerto Rican lower montane wet, subtropical wet, subtropical moist and subtropical dry forests was estimated using data from two forest inventories and published regression equations. Multiple potentially-applicable published biomass models existed for some forested life zones, and their estimates tended to diverge with increasing...

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

    Treesearch

    Thomas J. Brandeis; Maria Del Rocio; Suarez Rozo

    2005-01-01

    Total aboveground live tree biomass in Puerto Rican lower montane wet, subtropical wet, subtropical moist and subtropical dry forests was estimated using data from two forest inventories and published regression equations. Multiple potentially-applicable published biomass models existed for some forested life zones, and their estimates tended to diverge with increasing...

  16. The role of gap phase processes in the biomass dynamics of tropical forests

    PubMed Central

    Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M.N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme

    2007-01-01

    The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four ‘old-growth’ tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr−1) and decreased at HKK (−0.56% yr−1) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget. PMID:17785266

  17. The role of gap phase processes in the biomass dynamics of tropical forests.

    PubMed

    Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme

    2007-11-22

    The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four 'old-growth' tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr(-1)) and decreased at HKK (-0.56% yr(-1)) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget.

  18. Mapping the change of Phragmites australis live biomass in the lower Mississippi River Delta marshes

    USGS Publications Warehouse

    Ramsey, Elijah W.; Rangoonwala, Amina

    2017-07-28

    Multiyear remote sensing mapping of the normalized difference vegetation index (NDVI) was carried out as an indicator of live biomass composition of the Phragmites australis (hereafter Phragmites) marsh in the lower Mississippi River Delta (hereafter delta) from 2014 to 2017. Maps of NDVI change showed that the Phragmites condition was fairly stable between May 2014 and July 2015. From July 2015 to April 2016 NDVI change indicated Phragmites suffered a widespread decline in the live biomass proportion.  Between April and September 2016, most marsh remained unchanged from the earlier period or showed improvement; although there were pockets of continued decline scattered throughout the lower delta. From September 2016 to May 2017 a pronounced and widely exhibited decline in the condition of Phragmites marsh again occurred throughout the lower delta. This final NDVI change mapping supported field observations of Phragmites decline during the same period.

  19. Below and above-ground carbon distribution along a rainfall gradient. A case of the Zambezi teak forests, Zambia

    NASA Astrophysics Data System (ADS)

    Ngoma, Justine; Moors, Eddy; Kruijt, Bart; Speer, James H.; Vinya, Royd; Chidumayo, Emmanuel N.; Leemans, Rik

    2018-02-01

    Understanding carbon (C) stocks or biomass in forests is important to examine how forests mitigate climate change. To estimate biomass in stems, branches and roots takes intensive fieldwork to uproot, cut and weigh the mass of each component. Different models or equations are also required. Our research focussed on the dry tropical Zambezi teak forests and we studied their structure at three sites following a rainfall gradient in Zambia. We sampled 3558 trees at 42 plots covering a combined area of 15ha. Using data from destructive tree samples, we developed mixed-species biomass models to estimate above ground biomass for small (<5 cm diameter at breast height (DBH, 1.3 m above-ground)) and large (≥5 cm DBH) trees involving 90 and 104 trees respectively, that belonged to 12 species. A below-ground biomass model was developed from seven trees of three species (16-44 cm DBH) whose complete root systems were excavated. Three stump models were also derived from these uprooted trees. Finally, we determined the C fractions from 194 trees that belonged to 12 species. The analysis revealed that DBH was the only predictor that significantly correlated to both above-ground and below-ground biomass. We found a mean root-to-shoot ratio of 0.38:0.62. The C fraction in leaves ranged from 39% to 42%, while it varied between 41% and 46% in wood. The C fraction was highest at the Kabompo site that received the highest rainfall, and lowest at the intermediate Namwala site. The C stocks varied between 15 and 36 ton C ha-1 and these stocks where highest at the wetter Kabompo site and lowest at the drier Sesheke site. Our results indicate that the projected future rainfall decrease for southern Africa, will likely reduce the C storage potential of the Zambezi teak forests, thereby adversely affecting their mitigating role in climate change.

  20. 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

  1. 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

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

    Treesearch

    Steve Huff; Martin Ritchie; H. Temesgen

    2017-01-01

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

  3. 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

  4. Equations for predicting biomass of six introduced tree species, island of Hawaii

    Treesearch

    Thomas H. Schukrt; Robert F. Strand; Thomas G. Cole; Katharine E. McDuffie

    1988-01-01

    Regression equations to predict total and stem-only above-ground dry biomass for six species (Acacia melanoxylon, Albizio falcataria, Eucalyptus globulus, E. grandis, E. robusta, and E. urophylla) were developed by felling and measuring 2- to 6-year-old...

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

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

    DOE PAGES

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

    2017-02-07

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

  8. 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.

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

    Treesearch

    Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas Gower

    2002-01-01

    Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...

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

    NASA Astrophysics Data System (ADS)

    Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

    2017-08-01

    The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest

  11. 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

  12. 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

  13. 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.

  14. 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

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

    USGS Publications Warehouse

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

    2014-01-01

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

  16. A New Method for Non-destructive Measurement of Biomass, Growth Rates, Vertical Biomass Distribution and Dry Matter Content Based on Digital Image Analysis

    PubMed Central

    Tackenberg, Oliver

    2007-01-01

    Background and Aims Biomass is an important trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive. Thus, they do not allow the development of individual plants to be followed and they require many individuals to be cultivated for repeated measurements. Non-destructive methods do not have these limitations. Here, a non-destructive method based on digital image analysis is presented, addressing not only above-ground fresh biomass (FBM) and oven-dried biomass (DBM), but also vertical biomass distribution as well as dry matter content (DMC) and growth rates. Methods Scaled digital images of the plants silhouettes were taken for 582 individuals of 27 grass species (Poaceae). Above-ground biomass and DMC were measured using destructive methods. With image analysis software Zeiss KS 300, the projected area and the proportion of greenish pixels were calculated, and generalized linear models (GLMs) were developed with destructively measured parameters as dependent variables and parameters derived from image analysis as independent variables. A bootstrap analysis was performed to assess the number of individuals required for re-calibration of the models. Key Results The results of the developed models showed no systematic errors compared with traditionally measured values and explained most of their variance (R2 ≥ 0·85 for all models). The presented models can be directly applied to herbaceous grasses without further calibration. Applying the models to other growth forms might require a re-calibration which can be based on only 10–20 individuals for FBM or DMC and on 40–50 individuals for DBM. Conclusions The methods presented are time and cost effective compared with traditional methods, especially if development or growth rates are to be measured repeatedly. Hence, they offer an alternative way of determining biomass, especially as they are non-destructive and address not only FBM and DBM, but also vertical

  17. Correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis

    PubMed Central

    Liu, Wenlan; Sun, Zhirong; Qu, Jixu; Yang, Chunning; Zhang, Xiaomin; Wei, Xinxin

    2017-01-01

    The aim of the present study was to investigate the correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis. Root respiration was determined using a biological oxygen analyzer. Respiration-related enzymes including glucose-6-phosphate dehydrogenase plus 6-phosphogluconate dehydrogenase, phosphohexose isomerase and succinate dehydrogenase, and respiratory pathways were evaluated. Biomass was determined by a drying-weighing method. In addition, the percentage of glycyrrhizic acid was detected using high-performance liquid chromatography. The association between root respiration and the levels of biomass and glycyrrhizic acid was investigated. The glycolysis pathway (EMP), tricarboxylic acid cycle (TCA) and pentose phosphate (PPP) pathway acted concurrently in the roots of G. uralensis. Grey correlation analysis showed that TCA had the strongest correlation (correlation coefficient, 0.8003) with biomass. Starch and acetyl coenzyme A had the closest association with above-ground biomass, while soluble sugar correlated less strongly with above-ground biomass. Grey correlation analysis between biochemical pathways and the intermediates showed that pyruvic acid had the strongest correlation with EMP, while acetyl coenzyme A correlated most strongly with TCA. Among the intermediates and pathways, pyruvic acid and EMP exhibited the greatest correlation with glycyrrhizic acid, while acetyl coenzyme A and TCA correlated with glycyrrhizic acid less closely. The results of this study may aid the cultivation of G. uralensis. However, these results require verification in further studies. PMID:28962162

  18. Correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis.

    PubMed

    Liu, Wenlan; Sun, Zhirong; Qu, Jixu; Yang, Chunning; Zhang, Xiaomin; Wei, Xinxin

    2017-09-01

    The aim of the present study was to investigate the correlation between root respiration and the levels of biomass and glycyrrhizic acid in Glycyrrhiza uralensis . Root respiration was determined using a biological oxygen analyzer. Respiration-related enzymes including glucose-6-phosphate dehydrogenase plus 6-phosphogluconate dehydrogenase, phosphohexose isomerase and succinate dehydrogenase, and respiratory pathways were evaluated. Biomass was determined by a drying-weighing method. In addition, the percentage of glycyrrhizic acid was detected using high-performance liquid chromatography. The association between root respiration and the levels of biomass and glycyrrhizic acid was investigated. The glycolysis pathway (EMP), tricarboxylic acid cycle (TCA) and pentose phosphate (PPP) pathway acted concurrently in the roots of G. uralensis . Grey correlation analysis showed that TCA had the strongest correlation (correlation coefficient, 0.8003) with biomass. Starch and acetyl coenzyme A had the closest association with above-ground biomass, while soluble sugar correlated less strongly with above-ground biomass. Grey correlation analysis between biochemical pathways and the intermediates showed that pyruvic acid had the strongest correlation with EMP, while acetyl coenzyme A correlated most strongly with TCA. Among the intermediates and pathways, pyruvic acid and EMP exhibited the greatest correlation with glycyrrhizic acid, while acetyl coenzyme A and TCA correlated with glycyrrhizic acid less closely. The results of this study may aid the cultivation of G. uralensis . However, these results require verification in further studies.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  1. 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.

  2. 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

  3. Terrestrial Carbon Fluxes from Deforestation in the Brazilian Amazon and Cerrado Regions Predicted from MODIS Satellite Data and Ecosystem Modeling

    NASA Astrophysics Data System (ADS)

    Klooster, S.; Potter, C.; Genovese, V.

    2008-12-01

    The NASA-CASA (Carnegie Ames Stanford Approach) simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate tropical forest and savanna (Cerrado) carbon pools for the Brazilian Amazon region over the period 2000-2004. Adjustments for mean age of forest stands were carried out across the region, resulting in a new mapping of aboveground biomass pools based on MODIS satellite data. Yearly maps of newly deforested lands from the Brazilian PRODES (Programa de calculo do desflorestamento da Amazonia ) project were combined with these NASA-CASA biomass predictions to generate seasonal budgets of potential carbon and nitrogen trace gas losses from biomass burning events. Simulations of plant residue and soil carbon decomposition were conducted in the NASA-CASA model during and following deforestation events to track the fate of aboveground biomass pools that were cut and burned each year across the region.

  4. Changes in plant biomass and species composition of alpine Kobresia meadows along altitudinal gradient on the Qinghai-Tibetan Plateau.

    PubMed

    Wang, ChangTing; Cao, GuangMin; Wang, QiLan; Jing, ZengChun; Ding, LuMing; Long, RuiJun

    2008-01-01

    Alpine Kobresia meadows are major vegetation types on the Qinghai-Tibetan Plateau. There is growing concern over their relationships among biodiversity, productivity and environments. Despite the importance of species composition, species richness, the type of different growth forms, and plant biomass structure for Kobresia meadow ecosystems, few studies have been focused on the relationship between biomass and environmental gradient in the Kobresia meadow plant communities, particularly in relation to soil moisture and edaphic gradients. We measured the plant species composition, herbaceous litter, aboveground and belowground biomass in three Kobresia meadow plant communities in Haibei Alpine Meadow Ecosystem Research Station from 2001 to 2004. Community differences in plant species composition were reflected in biomass distribution. The total biomass showed a decrease from 13196.96+/-719.69 g/m(2) in the sedge-dominated K. tibetica swamp to 2869.58+/-147.52 g/m(2) in the forb and sedge dominated K. pygmaea meadow, and to 2153.08+/-141.95 g/m(2) in the forbs and grasses dominated K. humilis along with the increase of altitude. The vertical distribution of belowground biomass is distinct in the three meadow communities, and the belowground biomass at the depth of 0-10 cm in K. tibetica swamp meadow was significantly higher than that in K. humilis and K. pygmaea meadows (P<0.01). The herbaceous litter in K. tibetica swamp was significantly higher than those in K. pygnaeca and K. humilis meadows. The effects of plant litter are enhanced when ground water and soil moisture levels are raised. The relative importance of litter and vegetation may vary with soil water availability. In the K. tibetica swamp, total biomass was negatively correlated to species richness (P<0.05); aboveground biomass was positively correlated to soil organic matter, soil moisture, and plant cover (P<0.05); belowground biomass was positively correlated with soil moisture (P<0.05). However, in

  5. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... aboveground breakout tanks. (a) For aboveground breakout tanks built into API Specification 12F and first placed in service after October 2, 2000, pneumatic testing must be in accordance with section 5.3 of API Specification 12 F (incorporated by reference, see § 195.3). (b) For aboveground breakout tanks built to API...

  6. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... aboveground breakout tanks. (a) For aboveground breakout tanks built into API Specification 12F and first placed in service after October 2, 2000, pneumatic testing must be in accordance with section 5.3 of API Specification 12 F (incorporated by reference, see § 195.3). (b) For aboveground breakout tanks built to API...

  7. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... aboveground breakout tanks. (a) For aboveground breakout tanks built into API Specification 12F and first placed in service after October 2, 2000, pneumatic testing must be in accordance with section 5.3 of API Specification 12 F (incorporated by reference, see § 195.3). (b) For aboveground breakout tanks built to API...

  8. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... aboveground breakout tanks. (a) For aboveground breakout tanks built into API Specification 12F and first placed in service after October 2, 2000, pneumatic testing must be in accordance with section 5.3 of API Specification 12 F (incorporated by reference, see § 195.3). (b) For aboveground breakout tanks built to API...

  9. Ecological linkages between aboveground and belowground biota.

    PubMed

    Wardle, David A; Bardgett, Richard D; Klironomos, John N; Setälä, Heikki; van der Putten, Wim H; Wall, Diana H

    2004-06-11

    All terrestrial ecosystems consist of aboveground and belowground components that interact to influence community- and ecosystem-level processes and properties. Here we show how these components are closely interlinked at the community level, reinforced by a greater degree of specificity between plants and soil organisms than has been previously supposed. As such, aboveground and belowground communities can be powerful mutual drivers, with both positive and negative feedbacks. A combined aboveground-belowground approach to community and ecosystem ecology is enhancing our understanding of the regulation and functional significance of biodiversity and of the environmental impacts of human-induced global change phenomena.

  10. Response of aboveground carbon balance to long-term, experimental enhancements in precipitation seasonality is contingent on plant community type in cold-desert rangelands

    USGS Publications Warehouse

    McAbee, Kathryn; Reinhardt, Keith; Germino, Matthew; Bosworth, Andrew

    2017-01-01

    Semi-arid rangelands are important carbon (C) pools at global scales. However, the degree of net C storage or release in water-limited systems is a function of precipitation amount and timing, as well as plant community composition. In northern latitudes of western North America, C storage in cold-desert ecosystems could increase with boosts in wintertime precipitation, in which climate models predict, due to increases in wintertime soil water storage that enhance summertime productivity. However, there are few long-term, manipulative field-based studies investigating how rangelands will respond to altered precipitation amount or timing. We measured aboveground C pools and fluxes at leaf, soil, and ecosystem scales over a single growing season in plots that had 200 mm of supplemental precipitation added in either winter or summer for the past 21 years, in shrub- and exotic-bunchgrass-dominated garden plots. At our cold-desert site (298 mm precipitation during the study year), we hypothesized that increased winter precipitation would stimulate the aboveground C uptake and storage relative to ambient conditions, especially in plots containing shrubs. Our hypotheses were generally supported: ecosystem C uptake and long-term biomass accumulation were greater in winter- and summer-irrigated plots compared to control plots in both vegetation communities. However, substantial increases in the aboveground biomass occurred only in winter-irrigated plots that contained shrubs. Our findings suggest that increases in winter precipitation will enhance C storage of this widespread ecosystem, and moreso in shrub- compared to grass-dominated communities.

  11. From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information?

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

    Though the relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its extent is still unknown. Due to the enormous spatial extent, remote sensing provides the only possibility to investigate pasture degradation via frequently used proxies such as vegetation cover and aboveground biomass (AGB). However, unified remote sensing approaches are still lacking. This study tests the applicability of hyper- and multispectral in situ measurements to map vegetation cover and AGB on regional scales. Using machine learning techniques, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate pasture degradation proxies. To regionalize pasture degradation proxies, the transferability of the locally derived ML-models to high resolution multispectral satellite data is assessed. 1183 hyperspectral measurements and vegetation records were performed at 18 locations on the QTP. Random Forests models with recursive feature selection were trained to estimate vegetation cover and AGB using narrow-band indices (NBI) as predictors. Separate models were calculated using NBI from hyperspectral data as well as from 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 (cross validated R2 = 0.89). In contrast, errors in AGB estimations were considerably higher (cross validated R2 = 0.32). Only small differences in accuracy were observed between the models based on hyperspectral 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

  12. Biomass Allocation of Stoloniferous and Rhizomatous Plant in Response to Resource Availability: A Phylogenetic Meta-Analysis

    PubMed Central

    Xie, Xiu-Fang; Hu, Yu-Kun; Pan, Xu; Liu, Feng-Hong; Song, Yao-Bin; Dong, Ming

    2016-01-01

    Resource allocation to different functions is central in life-history theory. Plasticity of functional traits allows clonal plants to regulate their resource allocation to meet changing environments. In this study, biomass allocation traits of clonal plants were categorized into absolute biomass for vegetative growth vs. for reproduction, and their relative ratios based on a data set including 115 species and derived from 139 published literatures. We examined general pattern of biomass allocation of clonal plants in response to availabilities of resource (e.g., light, nutrients, and water) using phylogenetic meta-analysis. We also tested whether the pattern differed among clonal organ types (stolon vs. rhizome). Overall, we found that stoloniferous plants were more sensitive to light intensity than rhizomatous plants, preferentially allocating biomass to vegetative growth, aboveground part and clonal reproduction under shaded conditions. Under nutrient- and water-poor condition, rhizomatous plants were constrained more by ontogeny than by resource availability, preferentially allocating biomass to belowground part. Biomass allocation between belowground and aboveground part of clonal plants generally supported the optimal allocation theory. No general pattern of trade-off was found between growth and reproduction, and neither between sexual and clonal reproduction. Using phylogenetic meta-analysis can avoid possible confounding effects of phylogeny on the results. Our results shown the optimal allocation theory explained a general trend, which the clonal plants are able to plastically regulate their biomass allocation, to cope with changing resource availability, at least in stoloniferous and rhizomatous plants. PMID:27200071

  13. Biomass of Yellow-Poplar in Natural Stands in Western North Carolina

    Treesearch

    Alexander Clark; James G. Schroeder

    1977-01-01

    Aboveground biomass was determined for yellow-poplar(Liriodendron tulipifera L.) trees 6 to 28 inches d. b. h. growingin natural, uneven-aged mountaincovestandsin western North Carolina.Specific gravity, moisture content, and green weight per cubic foot are presented for the total tree and its components. Tables developed from regression equations show weight and...

  14. Assessing biomass accumulation in second growth forests of Puerto Rico using airborne lidar

    NASA Astrophysics Data System (ADS)

    Martinuzzi, S.; Cook, B.; Corp, L. A.; Morton, D. C.; Helmer, E.; Keller, M.

    2017-12-01

    Degraded and second growth tropical forests provide important ecosystem services, such as carbon sequestration and soil stabilization. Lidar data measure the three-dimensional structure of forest canopies and are commonly used to quantify aboveground biomass in temperate forest landscapes. However, the ability of lidar data to quantify second growth forest biomass in complex, tropical landscapes is less understood. Our goal was to evaluate the use of airborne lidar data to quantify aboveground biomass in a complex tropical landscape, the Caribbean island of Puerto Rico. Puerto Rico provides an ideal place for studying biomass accumulation because of the abundance of second growth forests in different stages of recovery, and the high ecological heterogeneity. Puerto Rico was almost entirely deforested for agriculture until the 1930s. Thereafter, agricultural abandonment resulted in a mosaic of second growth forests that have recovered naturally under different types of climate, land use, topography, and soil fertility. We integrated forest plot data from the US Forest Service, Forest Inventory and Analysis (FIA) Program with recent lidar data from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) airborne imager to quantify forest biomass across the island's landscape. The G-LiHT data consisted on targeted acquisitions over the FIA plots and other forested areas representing the environmental heterogeneity of the island. To fully assess the potential of the lidar data, we compared the ability of lidar-derived canopy metrics to quantify biomass alone, and in combination with intensity and topographic metrics. The results presented here are a key step for improving our understanding of the patterns and drivers of biomass accumulation in tropical forests.

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

    NASA Astrophysics Data System (ADS)

    Fatoyinbo, Temilola; Feliciano, Emanuelle A.; Lagomasino, David; Kuk Lee, Seung; Trettin, Carl

    2018-02-01

    Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R 2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha-1 up to 252 Mg ha-1. We suggest the best model

  16. Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

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

    USGS Publications Warehouse

    Goring, Simon; Mladenoff, David J.; Cogbill, Charles; Record, Sydne; Paciorek, Christopher J.; Dietze, Michael C.; Dawson, Andria; Matthes, Jaclyn; McLachlan, Jason S.; Williams, John W.

    2016-01-01

    EuroAmerican land-use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection.

  18. A SPATIAL ANALYSIS OF FINE-ROOT BIOMASS FROM STAND DATA IN OREGON AND WASHINGTON

    EPA Science Inventory

    Because of the high spatial variability of fine roots in natural forest stands, accurate estimates of stand-level fine root biomass are difficult and expensive to obtain by standard coring methods. This study compares two different approaches that employ aboveground tree metrics...

  19. Responses of belowground communities to large aboveground herbivores: Meta-analysis reveals biome-dependent patterns and critical research gaps.

    PubMed

    Andriuzzi, Walter S; Wall, Diana H

    2017-09-01

    The importance of herbivore-plant and soil biota-plant interactions in terrestrial ecosystems is amply recognized, but the effects of aboveground herbivores on soil biota remain challenging to predict. To find global patterns in belowground responses to vertebrate herbivores, we performed a meta-analysis of studies that had measured abundance or activity of soil organisms inside and outside field exclosures (areas that excluded herbivores). Responses were often controlled by climate, ecosystem type, and dominant herbivore identity. Soil microfauna and especially root-feeding nematodes were negatively affected by herbivores in subarctic sites. In arid ecosystems, herbivore presence tended to reduce microbial biomass and nitrogen mineralization. Herbivores decreased soil respiration in subarctic ecosystems and increased it in temperate ecosystems, but had no net effect on microbial biomass or nitrogen mineralization in those ecosystems. Responses of soil fauna, microbial biomass, and nitrogen mineralization shifted from neutral to negative with increasing herbivore body size. Responses of animal decomposers tended to switch from negative to positive with increasing precipitation, but also differed among taxa, for instance Oribatida responded negatively to herbivores, whereas Collembola did not. Our findings imply that losses and gains of aboveground herbivores will interact with climate and land use changes, inducing functional shifts in soil communities. To conceptualize the mechanisms behind our findings and link them with previous theoretical frameworks, we propose two complementary approaches to predict soil biological responses to vertebrate herbivores, one focused on an herbivore body size gradient, and the other on a climate severity gradient. Major research gaps were revealed, with tropical biomes, protists, and soil macrofauna being especially overlooked. © 2017 John Wiley & Sons Ltd.

  20. The GEDI Strategy for Improved Mapping of Forest Biomass and Structure

    NASA Astrophysics Data System (ADS)

    Dubayah, R.

    2017-12-01

    In 2014 the Committee on Earth Observation Satellites (CEOS) published a comprehensive report on approaches to meet future requirements for space-based observations of carbon. Entitled the CEOS Strategy for Carbon Observations from Space and endorsed by its member space agencies, the report outlines carbon information needs for climate and other policy, and how these needs may be met through existing and planned satellite missions. The CEOS Strategymakes recommendations for new, high-priority measurements. Among these is that space-based measurements using lidar should have priority to provide information on height, structure and biomass, complementing the existing and planned suite of SAR missions, such as the NASA NISAR and ESA BIOMASS missions. NASA's Global Ecosystem Dynamics Investigation (GEDI) directly meets this challenge. Scheduled for launch in late 2018 for deployment on the International Space Station, GEDI will provide more than 12 billion observations of canopy height, vertical structure and topography using a 10-beam lidar optimized for ecosystem measurements. Central to the success of GEDI is the development of calibration equations that relate observed forest structure to biomass at a variety of spatial scales. GEDI creates these calibrations by combining a large data base of field plot measurements with coincident airborne lidar observations that are used to simulate GEDI lidar waveforms. GEDI uses these relatively sparse footprint estimates of structure and biomass to create lower resolution, but spatially continuous grids of structure and biomass. GEDI is also developing radar/lidar fusion algorithms to produce higher-resolution, spatially continuous estimates of canopy height and biomass in collaboration with the German Aerospace Center (DLR). In this talk we present the current status of the GEDI calibration and validation program, and its approach for fusing its observations with the next generation of SAR sensors for improved mapping of

  1. Assessing the influence of return density on estimation of lidar-based aboveground biomass in tropical peat swamp forests of Kalimantan, Indonesia

    NASA Astrophysics Data System (ADS)

    Manuri, Solichin; Andersen, Hans-Erik; McGaughey, Robert J.; Brack, Cris

    2017-04-01

    The airborne lidar system (ALS) provides a means to efficiently monitor the status of remote tropical forests and continues to be the subject of intense evaluation. However, the cost of ALS acquisition can vary significantly depending on the acquisition parameters, particularly the return density (i.e., spatial resolution) of the lidar point cloud. This study assessed the effect of lidar return density on the accuracy of lidar metrics and regression models for estimating aboveground biomass (AGB) and basal area (BA) in tropical peat swamp forests (PSF) in Kalimantan, Indonesia. A large dataset of ALS covering an area of 123,000 ha was used in this study. This study found that cumulative return proportion (CRP) variables represent a better accumulation of AGB over tree heights than height-related variables. The CRP variables in power models explained 80.9% and 90.9% of the BA and AGB variations, respectively. Further, it was found that low-density (and low-cost) lidar should be considered as a feasible option for assessing AGB and BA in vast areas of flat, lowland PSF. The performance of the models generated using reduced return densities as low as 1/9 returns per m2 also yielded strong agreement with the original high-density data. The use model-based statistical inferences enabled relatively precise estimates of the mean AGB at the landscape scale to be obtained with a fairly low-density of 1/4 returns per m2, with less than 10% standard error (SE). Further, even when very low-density lidar data was used (i.e., 1/49 returns per m2) the bias of the mean AGB estimates were still less than 10% with a SE of approximately 15%. This study also investigated the influence of different DTM resolutions for normalizing the elevation during the generation of forest-related lidar metrics using various return densities point cloud. We found that the high-resolution digital terrain model (DTM) had little effect on the accuracy of lidar metrics calculation in PSF. The accuracy of

  2. Aboveground carbon sequestration in dry temperate forests varies with climate not fire regime.

    PubMed

    Gordon, Christopher E; Bendall, Eli R; Stares, Mitchell G; Collins, Luke; Bradstock, Ross A

    2018-06-01

    The storage of carbon in plant tissues and debris has been proposed as a method to offset anthropogenic increases in atmospheric [CO 2 ]. Temperate forests represent significant above-ground carbon (AGC) "sinks" because their relatively fast growth and slow decay rates optimise carbon assimilation. Fire is a common disturbance event in temperate forests globally that should strongly influence AGC because: discrete fires consume above-ground biomass releasing carbon to the atmosphere, and the long-term application of different fire-regimes select for specific plant communities that sequester carbon at different rates. We investigated the latter process by quantifying AGC storage at 104 sites in the Sydney Basin Bioregion, Australia, relative to differences in components of the fire regime: frequency, severity and interfire interval. To predict the potential impacts of future climate change on fire/AGC interactions, we stratified our field sites across gradients of mean annual temperature and precipitation and quantified within- and between-factor interactions between the fire and climate variables. In agreement with previous studies, large trees were the primary AGC sink, accounting for ~70% of carbon at sites. Generalised additive models showed that mean annual temperature was the strongest predictor of AGC storage, with a 54% near-linear decrease predicted across the 6.1°C temperature range experienced at sites. Mean annual precipitation, fire frequency, fire severity and interfire interval were consistently poor predictors of total above-ground storage, although there were some significant relationships with component stocks. Our results show resilience of AGC to frequent and severe wildfire and suggest temperature mediated decreases in forest carbon storage under future climate change predictions. © 2018 John Wiley & Sons Ltd.

  3. Response of aboveground carbon balance to long-term, experimental enhancements in precipitation seasonality is contingent on plant community type in cold-desert rangelands.

    PubMed

    McAbee, Kathryn; Reinhardt, Keith; Germino, Matthew J; Bosworth, Andrew

    2017-03-01

    Semi-arid rangelands are important carbon (C) pools at global scales. However, the degree of net C storage or release in water-limited systems is a function of precipitation amount and timing, as well as plant community composition. In northern latitudes of western North America, C storage in cold-desert ecosystems could increase with boosts in wintertime precipitation, in which climate models predict, due to increases in wintertime soil water storage that enhance summertime productivity. However, there are few long-term, manipulative field-based studies investigating how rangelands will respond to altered precipitation amount or timing. We measured aboveground C pools and fluxes at leaf, soil, and ecosystem scales over a single growing season in plots that had 200 mm of supplemental precipitation added in either winter or summer for the past 21 years, in shrub- and exotic-bunchgrass-dominated garden plots. At our cold-desert site (298 mm precipitation during the study year), we hypothesized that increased winter precipitation would stimulate the aboveground C uptake and storage relative to ambient conditions, especially in plots containing shrubs. Our hypotheses were generally supported: ecosystem C uptake and long-term biomass accumulation were greater in winter- and summer-irrigated plots compared to control plots in both vegetation communities. However, substantial increases in the aboveground biomass occurred only in winter-irrigated plots that contained shrubs. Our findings suggest that increases in winter precipitation will enhance C storage of this widespread ecosystem, and moreso in shrub- compared to grass-dominated communities.

  4. Regional distribution of forest height and biomass from multisensor data fusion

    Treesearch

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

    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...

  5. 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...

  6. Plant community composition and biomass in Gulf Coast Chenier Plain marshes: Responses to winter burning and structural marsh management

    USGS Publications Warehouse

    Gabrey, S.W.; Afton, A.D.

    2001-01-01

    Many marshes in the Gulf Coast Chenier Plain, USA, are managed through a combination of fall or winter burning and structural marsh management (i.e., levees and water control structures; hereafter SMM). The goals of winter burning and SMM include improvement of waterfowl and furbearer habitat, maintenance of historic isohaline lines, and creation and maintenance of emergent wetlands. Although management practices are intended to influence the plant community, effects of these practices on primary productivity have not been investigated. Marsh processes, such as vertical accretion and nutrient cycles, which depend on primary productivity may be affected directly or indirectly by winter burning or SMM. We compared Chenier Plain plant community characteristics (species composition and above- and belowground biomass) in experimentally burned and unburned control plots within impounded and unimpounded marshes at 7 months (1996), 19 months (1997), and 31 months (1998) after burning. Burning and SMM did not affect number of plant species or species composition in our experiment. For all three years combined, burned plots had higher live above-ground biomass than did unburned plots. Total above-ground and dead above-ground biomasses were reduced in burned plots for two and three years, respectively, compared to those in unburned control plots. During all three years, belowground biomass was lower in impounded than in unimpounded marshes but did not differ between burn treatments. Our results clearly indicate that current marsh management practices influence marsh primary productivity and may impact other marsh processes, such as vertical accretion, that are dependent on organic matter accumulation and decay.

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

    PubMed

    Lohbeck, Madelon; Poorter, Lourens; Martínez-Ramos, Miguel; Bongers, Frans

    2015-05-01

    Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity, actual litter decomposition, and potential litter decomposition) during secondary succession after shifting cultivation in wet tropical forest of Mexico. We test the importance of three alternative drivers of ecosystem processes: vegetation biomass (vegetation quantity hypothesis), community-weighted trait mean (mass ratio hypothesis), and functional diversity (niche complementarity hypothesis) using structural equation modeling. This allows us to infer the relative importance of different mechanisms underlying ecosystem process recovery. Ecosystem process rates changed during succession, and the strongest driver was aboveground biomass for each of the processes. Productivity of aboveground stem biomass and leaf litter as well as actual litter decomposition increased with initial standing vegetation biomass, whereas potential litter decomposition decreased with standing biomass. Additionally, biomass productivity was positively affected by community-weighted mean of specific leaf area, and potential decomposition was positively affected by functional divergence, and negatively by community-weighted mean of leaf dry matter content. Our empirical results show that functional diversity and community-weighted means are of secondary importance for explaining changes in ecosystem process rates during tropical forest succession. Instead, simply, the amount of vegetation in a site is the major driver of changes, perhaps because there is a steep biomass buildup during succession that overrides more subtle effects of community functional properties on ecosystem processes. We recommend future studies in the field of biodiversity and ecosystem functioning to separate the effects of

  8. Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume

    Treesearch

    Thomas J. Brandeis; Matthew Delaney; Bernard R. Parresol; Larry Royer

    2006-01-01

    Carbon accounting, forest health monitoring and sustainable management of the subtropical dry forests of Puerto Rico and other Caribbean Islands require an accurate assessment of forest aboveground biomass (AGB) and stem volume. One means of improving assessment accuracy is the development of predictive equations derived from locally collected data. Forest inventory...

  9. Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume.

    Treesearch

    Thomas J. Brandeis; Matthew Delaney; Bernard R. Parresol; Larry Royer

    2006-01-01

    Carbon accounting, forest health monitoring and sustainable management of the subtropical dry forests of Puerto Rico and other Caribbean Islands require an accurate assessment of forest aboveground biomass (AGB) and stem volume. One means of improving assessment accuracy is the development of predictive equations derived from locally collected data. Forest inventory...

  10. Estimating plant biomass in early-successional subtropical vegetation using a visual obstruction technique

    Treesearch

    Genie M. Fleming; Joseph M. Wunderle; David N. Ewert; Joseph O' Brien

    2014-01-01

    Aim: Non-destructive methods for quantifying above-ground plant biomass are important tools in many ecological studies and management endeavours, but estimation methods can be labour intensive and particularly difficult in structurally diverse vegetation types. We aimed to develop a low-cost, but reasonably accurate, estimation technique within early-successional...

  11. Tassel Removal Positively Affects Biomass Production Coupled with Significantly Increasing Stem Digestibility in Switchgrass

    PubMed Central

    Zhao, Chunqiao; Fan, Xifeng; Hou, Xincun; Zhu, Yi; Yue, Yuesen; Zhang, Shuang; Wu, Juying

    2015-01-01

    In this study, tassels of Cave-in-Rock (upland) and Alamo (lowland) were removed at or near tassel emergence to explore its effects on biomass production and quality. Tassel-removed (TR) Cave-in-Rock and Alamo both exhibited a significant (P<0.05) increase in plant heights (not including tassel length), tiller number, and aboveground biomass dry weight (10% and 12%, 30% and 13%, 13% and 18%, respectively by variety) compared to a control (CK) treatment. Notably, total sugar yields of TR Cave-in-Rock and Alamo stems increased significantly (P<0.05 or 0.01) by 19% and 19%, 21% and 14%, 52% and 18%, respectively by variety, compared to those of control switchgrass under 3 treatments by direct enzymatic hydrolysis (DEH), enzymatic hydrolysis after 1% NaOH pretreatment (EHAL) and enzymatic hydrolysis after 1% H2SO4 pretreatment (EHAC). These differences were mainly due to significantly (P<0.05 or 0.01) higher cellulose content, lower cellulose crystallinity indexes (CrI) caused by higher arabinose (Ara) substitution in xylans, and lower S/G ratio in lignin. However, the increases of nitrogen (N) and sulphur (S) concentration negatively affects the combustion quality of switchgrass aboveground biomass. This work provides information for increasing biomass production and quality in switchgrass and also facilitates the inhibition of gene dispersal of switchgrass in China. PMID:25849123

  12. Biomass and nutrient dynamics associated with slash fires in neotropical dry forests

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kauffman, J.B.; Cummings, D.L.; Sanford, R.L. Jr.

    1993-01-01

    Unprecedented rates of deforestation and biomass burning in tropical dry forests are dramatically influencing biogeochemical cycles, resulting in resource depletion, declines in biodiversity, and atmospheric pollution. We quantified the effects of deforestation and varying levels of slash-fire severity on nutrient losses and redistribution in a second-growth tropical dry forest ([open quotes]Caatinga[close quotes]) near Serra Talhada, Pernambuco, Brazil. Total aboveground biomass prior to burning was [approx]74 Mg/ha. Nitrogen and phosphorus concentrations were highest in litter, leaves attached to slash, and fine wood debris (

  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. Efficacies of designer biochars in improving biomass and nutrient uptake of winter wheat grown in a hard setting subsoil layer.

    PubMed

    Sigua, G C; Novak, J M; Watts, D W; Johnson, M G; Spokas, K

    2016-01-01

    In the Coastal Plains region of the United States, the hard setting subsoil layer of Norfolk soils results in low water holding capacity and nutrient retention, which often limits root development. In this region, the Norfolk soils are under intensive crop production that further depletes nutrients and reduces organic carbon (C). Incorporation of pyrolyzed organic residues or "biochars" can provide an alternative recalcitrant C source. However, biochar quality and effect can be inconsistent and different biochars react differently in soils. We hypothesized that addition of different designer biochars will have variable effects on biomass and nutrient uptake of winter wheat. The objective of this study was to investigate the effects of designer biochars on biomass productivity and nutrient uptake of winter wheat (Triticum aestivum L.) in a Norfolk's hard setting subsoil layer. Biochars were added to Norfolk's hard setting subsoil layer at the rate of 40 Mg ha(-1). The different sources of biochars were: plant-based (pine chips, PC); animal-based (poultry litter, PL); 50:50 blend (50% PC:50% PL); 80:20 blend (80% PC:20% PL); and hardwood (HW). Aboveground and belowground biomass and nutrient uptake of winter wheat varied significantly (p⩽0.0001) with the different designer biochar applications. The greatest increase in the belowground biomass of winter wheat over the control was from 80:20 blend of PC:PL (81%) followed by HW (76%), PC (59%) and 50:50 blend of PC:PL (9%). However, application of PL resulted in significant reduction of belowground biomass by about 82% when compared to the control plants. The average uptake of P, K, Ca, Mg, Na, Al, Fe, Cu and Zn in both the aboveground and belowground biomass of winter wheat varied remarkably with biochar treatments. Overall, our results showed promising significance for the treatment of a Norfolk's hard setting subsoil layer since designer biochars did improve both aboveground/belowground biomass and nutrient uptake

  15. Comparing the water-use-efficiency of maize and biomass sorghum grown in the rain-fed, Midwestern US.

    NASA Astrophysics Data System (ADS)

    Roby, M.; VanLoocke, A. D.; Heaton, E.; Miguez, F.; Salas Fernandez, M.

    2015-12-01

    Uncertainty in the quantity and timing of precipitation in a changing climate, combined with an increased demand for non-grain ethanol feedstock, may necessitate expanding the production of more water-use-efficient and less drought sensitive crops for biofuel applications. Research suggests that biomass sorghum [Sorghum bicolor (L.) Moench] is more drought tolerant and can produce more biomass than maize in water-limiting environments; however, sorghum water use data are scarce for the rain-fed Midwestern US. To address this gap, a replicated (n=3) side-by-side trial was established in Ames, Iowa to determine cumulative water use and water-use-efficiency of maize and biomass sorghum throughout the 2014 and 2015 growing seasons. Latent heat flux was estimated using the residual in the energy balance technique. Continuous micrometeorological measurements were supplemented by periodic measurements of leaf area index (LAI) and above-ground biomass. Water use (WU), aboveground biomass, and water-use-efficiency (WUE) were found to be similar for both crop types in 2014; data from the 2015 growing season are currently being processed. In 2015, leaf gas exchange measurements were made with a portable photosynthesis instrument. Photosynthetic parameters from gas exchange measurements will be implemented in a semi-mechanistic crop model (BioCro) as a method for scaling WUE estimates across the rain-fed Midwestern US driven with future climate projections. This research highlights the importance of understanding the potential effects of expanding biomass sorghum production on the hydrologic cycle of the Midwestern, US.

  16. Combining LIDAR estimates of aboveground biomass and Landsat estimates of stand age for spatially extensive validation of modeled forest productivity.

    Treesearch

    M.A. Lefsky; D.P. Turner; M. Guzy; W.B. Cohen

    2005-01-01

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

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

    Treesearch

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

    2017-01-01

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

  18. 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

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

    USDA-ARS?s Scientific Manuscript database

    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 ...

  20. New geospatial approaches for efficiently mapping forest biomass logistics at high resolution over large areas

    Treesearch

    John Hogland; Nathaniel Anderson; Woodam Chung

    2018-01-01

    Adequate biomass feedstock supply is an important factor in evaluating the financial feasibility of alternative site locations for bioenergy facilities and for maintaining profitability once a facility is built. We used newly developed spatial analysis and logistics software to model the variables influencing feedstock supply and to estimate and map two components of...

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

    NASA Astrophysics Data System (ADS)

    Eberle, J.; Schmullius, C.

    2017-12-01

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

  2. The Oldest, Slowest Rainforests in the World? Massive Biomass and Slow Carbon Dynamics of Fitzroya cupressoides Temperate Forests in Southern Chile.

    PubMed

    Urrutia-Jalabert, Rocio; Malhi, Yadvinder; Lara, Antonio

    2015-01-01

    Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP), carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC) in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA) in the Andean Cordillera. Aboveground live biomass was 113-114 Mg C ha(-1) and 448-517 Mg C ha(-1) in AC and AA, respectively. Aboveground productivity was 3.35-3.36 Mg C ha(-1) year(-1) in AC and 2.22-2.54 Mg C ha(-1) year(-1) in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21-4.24 and 3.78-4.10 Mg C ha(-1) year(-1) in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539-640 years for the whole forest in the Andes and 1368-1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia.

  3. The Oldest, Slowest Rainforests in the World? Massive Biomass and Slow Carbon Dynamics of Fitzroya cupressoides Temperate Forests in Southern Chile

    PubMed Central

    Urrutia-Jalabert, Rocio; Malhi, Yadvinder; Lara, Antonio

    2015-01-01

    Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP), carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC) in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA) in the Andean Cordillera. Aboveground live biomass was 113–114 Mg C ha-1 and 448–517 Mg C ha-1 in AC and AA, respectively. Aboveground productivity was 3.35–3.36 Mg C ha-1 year-1 in AC and 2.22–2.54 Mg C ha-1 year-1 in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21–4.24 and 3.78–4.10 Mg C ha-1 year-1 in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539–640 years for the whole forest in the Andes and 1368–1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia. PMID:26353111

  4. Eliciting maize defense pathways aboveground attracts belowground biocontrol agents.

    PubMed

    Filgueiras, Camila Cramer; Willett, Denis S; Pereira, Ramom Vasconcelos; Moino Junior, Alcides; Pareja, Martin; Duncan, Larry W

    2016-11-04

    Plant defense pathways mediate multitrophic interactions above and belowground. Understanding the effects of these pathways on pests and natural enemies above and belowground holds great potential for designing effective control strategies. Here we investigate the effects of aboveground stimulation of plant defense pathways on the interactions between corn, the aboveground herbivore adult Diabrotica speciosa, the belowground herbivore larval D. speciosa, and the subterranean ento-mopathogenic nematode natural enemy Heterorhabditis amazonensis. We show that adult D. speciosa recruit to aboveground herbivory and methyl salicylate treatment, that larval D. speciosa are relatively indiscriminate, and that H. amazonensis en-tomopathogenic nematodes recruit to corn fed upon by adult D. speciosa. These results suggest that entomopathogenicnematodes belowground can be highly attuned to changes in the aboveground parts of plants and that biological control can be enhanced with induced plant defense in this and similar systems.

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

    Treesearch

    R. Treuhaft; F. Goncalves; J.R. dos Santos; M. Keller; M. Palace; S.N. Madsen; F. Sullivan; P.M.L.A. Graca

    2014-01-01

    This letter reports the sensitivity of X-band interferometric synthetic aperture radar (InSAR) data from the first dual-spacecraft radar interferometer, TanDEM-X, to variations in tropical-forest aboveground biomass (AGB). It also reports the first tropical-forest AGB estimates fromTanDEM-X data. Tropical forests account for...

  6. 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

  7. Allometric models for predicting aboveground biomass and carbon stock of tropical perennial C4 grasses in Hawaii

    USDA-ARS?s Scientific Manuscript database

    Biomass represents a promising renewable energy opportunity that mayprovide a more sustainable alternative to the use of fossil resources by minimizing the net production of greenhouse gases. Yet, allometric models that allow the prediction of biomass, biomass carbon (C) and nitrogen (N) stocks rap...

  8. Deriving biomass models for small-diameter loblolly pine on the Crossett Experimental Forest

    Treesearch

    K.M. McElligott; D.C. Bragg

    2013-01-01

    Foresters and landowners have a growing interest in carbon sequestration and cellulosic biofuels in southern pine forests, and hence need to be able to accurately predict them. To this end, we derived a set of aboveground biomass models using data from 62 small-diameter loblolly pines (Pinus taeda) sampled on the Crossett Experimental Forest in...

  9. Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data.

    PubMed

    Garcia, Mariano; Saatchi, Sassan; Casas, Angeles; Koltunov, Alexander; Ustin, Susan; Ramirez, Carlos; Garcia-Gutierrez, Jorge; Balzter, Heiko

    2017-02-01

    Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR-derived metrics over the unburned area. The selected model estimated AGB with an R 2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR-based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R 2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (10 12  g), which translate into 12.06 ± 0.06 Tg CO2 e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars.

  10. Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data

    PubMed Central

    Saatchi, Sassan; Casas, Angeles; Koltunov, Alexander; Ustin, Susan; Ramirez, Carlos; Garcia‐Gutierrez, Jorge; Balzter, Heiko

    2017-01-01

    Abstract Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR‐derived metrics over the unburned area. The selected model estimated AGB with an R 2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR‐based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R 2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (1012 g), which translate into 12.06 ± 0.06 Tg CO2e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars. PMID:28405539

  11. The Circumpolar Arctic Vegetation Map: A tool for analysis of change in permafrost regions

    NASA Astrophysics Data System (ADS)

    Walker, D. A.; Raynolds, M. K.; Maier, H. A.

    2003-12-01

    Arctic vegetation occurs beyond the northern limit of trees, in areas that have an Arctic climate and Arctic flora. Here we present an overview of the recently published Circumpolar Arctic Vegetation Map (CAVM), an area analysis of the vegetation map, and a discussion of its potential for analysis of change in the Arctic. Six countries have Arctic tundra vegetation, Canada, Greenland, Iceland, Russia, Norway (Svalbard), and the US (Total Arctic area = 7.1 million km2). Some treeless areas, such as most of Iceland and the Aluetian Islands are excluded from the map because they lack an Arctic climate. The CAVM divides the Arctic into five bioclimate subzones, A thru E (Subzone A is the coldest and Subzone E is the warmest), based on a combination of summer temperature and vegetation. Fifteen vegetation types are mapped based on the dominant plant growth forms. More detailed, plant-community-level, information is contained in the database used to construct the map. The reverse side of the vegetation map has a false-color infrared image constructed from Advanced Very-High Resolution (AVHRR) satellite-derived raster data, and maps of bioclimate subzones, elevation, landscape types, lake cover, substrate chemistry, floristic provinces, the maximum normalized difference vegetation index (NDVI), and aboveground phytomass. The vegetation map was analyzed by vegetation type and biomass for each county, bioclimate subzone, and floristic province. Biomass distribution was analyzed by means of a correlation between aboveground phytomass and the normalized difference vegetation index (NDVI), a remote-sensing index of surface greenness. Biomass on zonal surfaces roughly doubles within each successively warmer subzone, from about 50 g m-2 in Subzone A to 800 g m-2- in Subzone E. But the pattern of vegetation increase is highly variable, and depends on a number of other factors. The most important appears to be the glacial history of the landscape. Areas that were glaciated during

  12. 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.

  13. 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.

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

    USDA-ARS?s Scientific Manuscript database

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

  15. A Study on PolInSAR Coherence Based Regression Analysis of Forest Biomass (BARKOT Reserve Forest India), Using RADARSAT-2 Datasets

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Forests cover 30% of the world's land surface, and are home to around 90% of the world's flora and fauna. They serve as one of the world's largest carbon sinks, absorbing 2.4 million tons of CO2 each year and storing billions more in form of biomass. Around 6 million hectares of forest is lost or changed each year and as much as a fifth of global emissions are estimated to come from deforestation. Hence accurate estimation of forest biophysical variables is necessary as it is a key parameter in determination of forest inventories, vegetation modeling and global carbon cycle. SAR Remote sensing technique is capable of providing accurate and reliable information about forest parameters. The present work aims to explore the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolinSAR) technique for developing a relationship between complex coherence and forest aboveground biomass (t/ha). In order to attain our objective Radarsat-2 satellite interferometric pair of 4th March 2013(master image) and 28th March 2013(slave image) were acquired for Barkot Reserve Forest, Dehradun, India. Field inventory was done for 30 plots (31.62m x 31.62m) and tree height and stem diameter were procured for each plot which were later utilized in calculation of aboveground biomass(AGB).Work emphasizes on the application of PolinSAR coherence instead of using SAR backscatter which saturates after a certain value of biomass content. Complex coherence values for different polarization channels were computed with the help of polarimetric interferometric coherence matrix. Retrieved complex coherences were investigated individually and then regression analysis was carried with the field estimated aboveground biomass. R2 value of HV+VH complex coherence component was found to be relatively higher than other polarization channel components

  16. Large Footprint LiDAR Data Processing for Ground Detection and Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Zhuang, Wei

    Ground detection in large footprint waveform Light Detection And Ranging (LiDAR) data is important in calculating and estimating downstream products, especially in forestry applications. For example, tree heights are calculated as the difference between the ground peak and first returned signal in a waveform. Forest attributes, such as aboveground biomass, are estimated based on the tree heights. This dissertation investigated new metrics and algorithms for estimating aboveground biomass and extracting ground peak location in large footprint waveform LiDAR data. In the first manuscript, an accurate and computationally efficient algorithm, named Filtering and Clustering Algorithm (FICA), was developed based on a set of multiscale second derivative filters for automatically detecting the ground peak in an waveform from Land, Vegetation and Ice Sensor. Compared to existing ground peak identification algorithms, FICA was tested in different land cover type plots and showed improved accuracy in ground detections of the vegetation plots and similar accuracy in developed area plots. Also, FICA adopted a peak identification strategy rather than following a curve-fitting process, and therefore, exhibited improved efficiency. In the second manuscript, an algorithm was developed specifically for shrub waveforms. The algorithm only partially fitted the shrub canopy reflection and detected the ground peak by investigating the residual signal, which was generated by deducting a Gaussian fitting function from the raw waveform. After the deduction, the overlapping ground peak was identified as the local maximum of the residual signal. In addition, an applicability model was built for determining waveforms where the proposed PCF algorithm should be applied. In the third manuscript, a new set of metrics was developed to increase accuracy in biomass estimation models. The metrics were based on the results of Gaussian decomposition. They incorporated both waveform intensity

  17. 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.

  18. Ecological Importance of Small-Diameter Trees to the Structure, Diversity and Biomass of a Tropical Evergreen Forest at Rabi, Gabon.

    PubMed

    Memiaghe, Hervé R; Lutz, James A; Korte, Lisa; Alonso, Alfonso; Kenfack, David

    2016-01-01

    Tropical forests have long been recognized for their biodiversity and ecosystem services. Despite their importance, tropical forests, and particularly those of central Africa, remain understudied. Until recently, most forest inventories in Central Africa have focused on trees ≥10 cm in diameter, even though several studies have shown that small-diameter tree population may be important to demographic rates and nutrient cycling. To determine the ecological importance of small-diameter trees in central African forests, we used data from a 25-ha permanent plot that we established in the rainforest of Gabon to study the diversity and dynamics of these forests. Within the plot, we censused 175,830 trees ≥1 cm dbh from 54 families, 192 genera, and 345 species. Average tree density was 7,026 trees/ha, basal area 31.64 m2/ha, and above-ground biomass 369.40 Mg/ha. Fabaceae, Ebenaceae and Euphorbiaceae were the most important families by basal area, density and above-ground biomass. Small-diameter trees (1 cm ≥ dbh <10 cm) comprised 93.7% of the total tree population, 16.5% of basal area, and 4.8% of the above-ground biomass. They also had diversity 18% higher at family level, 34% higher at genus level, and 42% higher at species level than trees ≥10 cm dbh. Although the relative contribution of small-diameter trees to biomass was comparable to other forests globally, their contribution to forest density, and diversity was disproportionately higher. The high levels of diversity within small-diameter classes may give these forests high levels of structural resilience to anthropogenic/natural disturbance and a changing climate.

  19. Ecological Importance of Small-Diameter Trees to the Structure, Diversity and Biomass of a Tropical Evergreen Forest at Rabi, Gabon

    PubMed Central

    Memiaghe, Hervé R.; Lutz, James A.; Korte, Lisa; Alonso, Alfonso; Kenfack, David

    2016-01-01

    Tropical forests have long been recognized for their biodiversity and ecosystem services. Despite their importance, tropical forests, and particularly those of central Africa, remain understudied. Until recently, most forest inventories in Central Africa have focused on trees ≥10 cm in diameter, even though several studies have shown that small-diameter tree population may be important to demographic rates and nutrient cycling. To determine the ecological importance of small-diameter trees in central African forests, we used data from a 25-ha permanent plot that we established in the rainforest of Gabon to study the diversity and dynamics of these forests. Within the plot, we censused 175,830 trees ≥1 cm dbh from 54 families, 192 genera, and 345 species. Average tree density was 7,026 trees/ha, basal area 31.64 m2/ha, and above-ground biomass 369.40 Mg/ha. Fabaceae, Ebenaceae and Euphorbiaceae were the most important families by basal area, density and above-ground biomass. Small-diameter trees (1 cm ≥ dbh <10 cm) comprised 93.7% of the total tree population, 16.5% of basal area, and 4.8% of the above-ground biomass. They also had diversity 18% higher at family level, 34% higher at genus level, and 42% higher at species level than trees ≥10 cm dbh. Although the relative contribution of small-diameter trees to biomass was comparable to other forests globally, their contribution to forest density, and diversity was disproportionately higher. The high levels of diversity within small-diameter classes may give these forests high levels of structural resilience to anthropogenic/natural disturbance and a changing climate. PMID:27186658

  20. Summary of nutrient and biomass data from two aspen sites in western United States

    Treesearch

    Robert S. Johnston; Dale L. Bartos

    1977-01-01

    Summary tables are presented for aboveground biomass and nutrient concentrations for 20 aspen trees (Populus tremuloides Michx.) that were sampled at two study sites in Utah and Wyoming. Trees were divided into seven components - leaves, current twigs, old twigs, deadwood (branches), branches, bark, and bole wood. Samples from each component were analyzed for nitrogen...

  1. Changes in forest biomass and tree species distribution under climate change in the northeastern United States

    Treesearch

    Wen J. Wang; Hong S. He; Frank R. Thompson; Jacob S. Fraser; William D. Dijak

    2016-01-01

    Context. Forests in the northeastern United States are currently in early- and mid-successional stages recovering from historical land use. Climate change will affect forest distribution and structure and have important implications for biodiversity, carbon dynamics, and human well-being. Objective. We addressed how aboveground biomass (AGB) and...

  2. Estimates of biomass in logging residue and standing residual inventory following tree-harvest activity on timberland acres in the southern region

    Treesearch

    Roger C. Conner; Tony G. Johnson

    2011-01-01

    This report provides estimates of biomass (green tons) in logging residue and standing residual inventory on timberland acres with evidence of tree cutting. Biomass as defined by Forest Inventory and Analysis is the aboveground dry weight of wood in the bole and limbs of live trees ≥ 1-inch diameter at breast height (d.b.h.), and excludes tree foliage, seedlings, and...

  3. Biomass and biomass change in lodgepole pine stands in Alberta

    Treesearch

    Robert A. Monserud; Shongming Huang; Yuqing Yang

    2006-01-01

    We describe methods and results for broad-scale estimation and mapping of forest biomass for the Canadian province of Alberta. Differences over successive decades provided an estimate of biomass change. Over 1500 permanent sample plots (PSP) were analyzed from across the range of lodgepole pine (Pinus contorta var. latifolia Engelm...

  4. Mapping growing stock volume and forest live biomass: a case study of the Polissya region of Ukraine

    NASA Astrophysics Data System (ADS)

    Bilous, Andrii; Myroniuk, Viktor; Holiaka, Dmytrii; Bilous, Svitlana; See, Linda; Schepaschenko, Dmitry

    2017-10-01

    Forest inventory and biomass mapping are important tasks that require inputs from multiple data sources. In this paper we implement two methods for the Ukrainian region of Polissya: random forest (RF) for tree species prediction and k-nearest neighbors (k-NN) for growing stock volume and biomass mapping. We examined the suitability of the five-band RapidEye satellite image to predict the distribution of six tree species. The accuracy of RF is quite high: ~99% for forest/non-forest mask and 89% for tree species prediction. Our results demonstrate that inclusion of elevation as a predictor variable in the RF model improved the performance of tree species classification. We evaluated different distance metrics for the k-NN method, including Euclidean or Mahalanobis distance, most similar neighbor (MSN), gradient nearest neighbor, and independent component analysis. The MSN with the four nearest neighbors (k = 4) is the most precise (according to the root-mean-square deviation) for predicting forest attributes across the study area. The k-NN method allowed us to estimate growing stock volume with an accuracy of 3 m3 ha-1 and for live biomass of about 2 t ha-1 over the study area.

  5. NREL: International Activities - Biomass Resource Assessment

    Science.gov Websites

    Biomass Resource Assessment Map showing annual productivity of marginal lands in APEC economies . Biomass resource assessments quantify the existing or potential biomass material in a given area. Biomass biomass resources could be used to produce power, heat, transportation fuels, and various chemical

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

    PubMed

    Dai, Erfu; Wu, Zhuo; Ge, Quansheng; Xi, Weimin; Wang, Xiaofan

    2016-11-01

    In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS-II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET-II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010-2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad-leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad-leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types. © 2016

  7. Remote sensing of biomass and annual net aerial primary productivity of a salt marsh

    NASA Technical Reports Server (NTRS)

    Hardisky, M. A.; Klemas, V.; Daiber, F. C.; Roman, C. T.

    1984-01-01

    Net aerial primary productivity is the rate of storage of organic matter in above-ground plant issues exceeding the respiratory use by the plants during the period of measurement. It is pointed out that this plant tissue represents the fixed carbon available for transfer to and consumption by the heterotrophic organisms in a salt marsh or the estuary. One method of estimating annual net aerial primary productivity (NAPP) required multiple harvesting of the marsh vegetation. A rapid nondestructive remote sensing technique for estimating biomass and NAPP would, therefore, be a significant asset. The present investigation was designed to employ simple regression models, equating spectral radiance indices with Spartina alterniflora biomass to nondestructively estimate salt marsh biomass. The results of the study showed that the considered approach can be successfully used to estimate salt marsh biomass.

  8. Long-term remote monitoring of salt marsh biomass

    NASA Astrophysics Data System (ADS)

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

    1990-12-01

    An objective of NASA's Biospheric Research Program is to understand biogeochemical cycling on a global scale. Being both very biologically productive and anoxic, wetlands are major sites of carbon dioxide, mean, and sulfur gas flux on a per area basis. Biogeochemical cycling in wetlands is intricately linked to vegetation biomass production. We have been monitoring biomass dynamics of the dominant salt marsh grass Spartina alterniflora for over ten years using remote sensing. Live above ground biomass is highly correlated (r = .79) with Laridsat Thematic Mapper ('IN) and SPOT spectral data transformed into normalized difference vegetation indices. Live belowg round biomass is, in turn, highly correlated (r = .86) with live above ground biomass. Therefore, below ground biomass, a source of carbon substrates for microbial gas production, can be measured using remote sensing indirectly. These relationships have been tested over a wide latitudinal range (from Georgia to Nova Scotia). Analysis of TM and SPOT satellite images from several years has revealed substantial interannual variability in mean live aerial biomass of this species in a 580ha Delaware marsh. Additionally, interannual spatial variability in biomass distribution within the marsh is evident and seems to be linked to precipitation. The aerial biomass of high salinity areas least influenced by upland runoff is the most sensitive to precipitation, whereas marsh areas adjacent to large upland areas or freshwater creeks are the least sensitive. In summary, remote sensing is an effective tool for studying aboveground and belowground biomass in salt marshes. Once the relationship between gas flux data and vegetation biomass is better understood, satellite data could be used to estimate biomass arid gas flux over large regions of the world.

  9. 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.

  10. Deciphering Natural Allelic Variation in Switchgrass for Biomass Yield and Quality Using a Nested Association Mapping Population

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Saha, Malay C.; Brummer, E. Charles; Kaeppler, Shawn

    Switchgrass (Panicum virgatum L.) is a C4 grass with high biomass yield potential and a model species for bioenergy feedstock development. Understanding the genetic basis of quantitative traits is essential to facilitate genome-enabled breeding programs. The nested association mapping (NAM) analysis combines the best features of both bi-parental and association analyses and can provide high power and high resolution in QTL detection and will ensure significant improvements in biomass yield and quality. To develop a NAM population of switchgrass, 15 highly diverse genotypes with specific characteristics were selected from a diversity panel and crossed to a recurrent parent, AP13, amore » genotype selected for whole genome sequencing and parent of a mapping population. Ten genotypes from each of the 15 F1 families were then chain crossed. Progenies form each family were randomly selected to develop the NAM population. The switchgrass NAM population consists of a total of 2000 genotypes from 15 families. All the progenies, founder parents, F1 parents (n=2350) were evaluated in replicated field trials at Ardmore, OK and Knoxville, TN. Phenotypic data on plant height, tillering ability, regrowth, flowering time, and biomass yield were collected. Dried biomass samples were also analyzed using prediction equations of NIRS at the Noble Foundation and for lignin content, S/G ratio, and sugar release characteristics at the NREL. Genomic shotgun sequencing of 15 switchgrass NAM founder parental genomes at JGI produced 28-66 Gb high-quality sequence data. Alignment of these sequences with the reference genome, AP13 (v3.0), revealed that up to 99% of the genomic sequences mapped to the reference genome. A total of 2,149 individuals from NAM populations were sequenced by exome capture and two sets of 15 SNP matrices (one for each family) were generated. QTL associated with important traits have been identified and verified in breeding populations. The QTL detected and their

  11. Effects of height and live crown ratio imputation strategies on stand biomass estimation

    Treesearch

    Elijah J. Allensworth; Temesgen. Hailemariam

    2015-01-01

    The effects of subsample design and imputation of total height (ht) and live crown ratio (cr) on the accuracy of stand-level estimates of component and total aboveground biomass are not well investigated in the current body of literature. To assess this gap in research, this study uses a data set of 3,454 Douglas-fir trees obtained from 102 stands in southwestern...

  12. Drainage identification analysis and mapping, phase 2.

    DOT National Transportation Integrated Search

    2017-01-01

    Drainage Identification, Analysis and Mapping System (DIAMS) is a computerized database that captures and : stores relevant information associated with all aboveground and underground hydraulic structures belonging to : the New Jersey Department of T...

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

    USDA-ARS?s Scientific Manuscript database

    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...

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

    Treesearch

    Woodam Chung; Paul Evangelista; Nathaniel Anderson; Anthony Vorster; Hee Han; Krishna Poudel; Robert Sturtevant

    2017-01-01

    The recent mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic has affected millions of hectares of conifer forests in the Rocky Mountains. Land managers are interested in using biomass from beetle-killed trees for bioenergy and biobased products, but they lack adequate information to accurately estimate biomass in stands with heavy mortality. We...

  15. Effect of tree shelters on above-ground stem biomass leaf numbers and size, and height growth

    Treesearch

    Douglas O. Lantagne; Gregory Kowalewski

    1997-01-01

    Tree shelters have been tested and shown to be effective in several circumstances regarding hardwood regeneration, especially with northern red oak (Quercus rubra L.). A study was initiated to quantify how tree shelters affected quantity, size and biomass of leaves, the number of growth flushes, and the above ground stem biomass of planted northern...

  16. 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.

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

    PubMed

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

    2009-03-25

    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.

  18. Microenvironmental air quality impact of a commercial-scale biomass heating system.

    PubMed

    Tong, Zheming; Yang, Bo; Hopke, Philip K; Zhang, K Max

    2017-01-01

    Initiatives to displace petroleum and climate change mitigation have driven a recent increase in space heating with biomass combustion. However, there is ample evidence that biomass combustion emits significant quantities of health damaging pollutants. We investigated the near-source micro-environmental air quality impact of a biomass-fueled combined heat and power system equipped with an electrostatic precipitator (ESP) in Syracuse, NY. Two rooftop sampling stations with PM 2.5 and CO 2 analyzers were established in such that one could capture the plume while the other one served as the background for comparison depending on the wind direction. Four sonic anemometers were deployed around the stack to quantify spatially and temporally resolved local wind patterns. Fuel-based emission factors were derived based on near-source measurement. The Comprehensive Turbulent Aerosol Dynamics and Gas Chemistry (CTAG) model was then applied to simulate the spatial variations of primary PM 2.5 without ESP. Our analysis shows that the absence of ESP could lead to an almost 7 times increase in near-source primary PM 2.5 concentrations with a maximum concentration above 100 μg m -3 at the building rooftop. The above-ground "hotspots" would pose potential health risks to building occupants since particles could penetrate indoors via infiltration, natural ventilation, and fresh air intakes on the rooftop of multiple buildings. Our results demonstrated the importance of emission control for biomass combustion systems in urban area, and the need to take above-ground pollutant "hotspots" into account when permitting distributed generation. The effects of ambient wind speed and stack temperature, the suitability of airport meteorological data on micro-environmental air quality were explored, and the implications on mitigating near-source air pollution were discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Influence of prescribed fire on ecosystem biomass, carbon, and nitrogen in a pinyon juniper woodland

    Treesearch

    Benjamin M. Rau; Robin Tausch; Alicia Reiner; Dale W. Johnson; Jeanne C. Chambers; Robert R. Blank; Annmarrie Lucchesi

    2010-01-01

    Increases in pinyon and juniper woodland cover associated with land-use history are suggested to provide offsets for carbon emissions in arid regions. However, the largest pools of carbon in arid landscapes are typically found in soils, and aboveground biomass cannot be considered long-term storage in fire-prone ecosystems. Also, the objectives of carbon storage may...

  20. Effects of Light Regimes on the Biomass and Morphological Characteristics of 2-Year-Old Cherrybark Oak Seedlings

    Treesearch

    Yanfei Guo; Michael G. Shelton

    2004-01-01

    We used modified shadehouses to simulate the complex light conditions within forest openings and tested the effects of time of direct light exposure, the ratio of direct light to day length, and daily photosynthetically active radiation on aboveground biomass and morphological characteristics of 2-year-old cherrybark oak (Quercus pagoda Raf.)...

  1. Single tree biomass modelling using airborne laser scanning

    NASA Astrophysics Data System (ADS)

    Kankare, Ville; Räty, Minna; Yu, Xiaowei; Holopainen, Markus; Vastaranta, Mikko; Kantola, Tuula; Hyyppä, Juha; Hyyppä, Hannu; Alho, Petteri; Viitala, Risto

    2013-11-01

    Accurate forest biomass mapping methods would provide the means for e.g. detecting bioenergy potential, biofuel and forest-bound carbon. The demand for practical biomass mapping methods at all forest levels is growing worldwide, and viable options are being developed. Airborne laser scanning (ALS) is a promising forest biomass mapping technique, due to its capability of measuring the three-dimensional forest vegetation structure. The objective of the study was to develop new methods for tree-level biomass estimation using metrics derived from ALS point clouds and to compare the results with field references collected using destructive sampling and with existing biomass models. The study area was located in Evo, southern Finland. ALS data was collected in 2009 with pulse density equalling approximately 10 pulses/m2. Linear models were developed for the following tree biomass components: total, stem wood, living branch and total canopy biomass. ALS-derived geometric and statistical point metrics were used as explanatory variables when creating the models. The total and stem biomass root mean square error per cents equalled 26.3% and 28.4% for Scots pine (Pinus sylvestris L.), and 36.8% and 27.6% for Norway spruce (Picea abies (L.) H. Karst.), respectively. The results showed that higher estimation accuracy for all biomass components can be achieved with models created in this study compared to existing allometric biomass models when ALS-derived height and diameter were used as input parameters. Best results were achieved when adding field-measured diameter and height as inputs in the existing biomass models. The only exceptions to this were the canopy and living branch biomass estimations for spruce. The achieved results are encouraging for the use of ALS-derived metrics in biomass mapping and for further development of the models.

  2. Recent Progress in Measuring and Modeling Patterns of Biomass and Soil Carbon Pools Across the Amazon Basin

    NASA Technical Reports Server (NTRS)

    Potter, Christopher; Malhi, Yadvinder

    2004-01-01

    Ever more detailed representations of above-ground biomass and soil carbon pools have been developed during the LBA project. Environmental controls such as regional climate, land cover history, secondary forest regrowth, and soil fertility are now being taken into account in regional inventory studies. This paper will review the evolution of measurement-extrapolation approaches, remote sensing, and simulation modeling techniques for biomass and soil carbon pools, which together help constrain regional carbon budgets and enhance in our understanding of uncertainty at the regional level.

  3. 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

  4. Examining spectral properties of Landsat 8 OLI for predicting above-ground carbon of Labanan Forest, Berau

    NASA Astrophysics Data System (ADS)

    Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.

    2018-04-01

    Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.

  5. 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

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

    Treesearch

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

    2007-01-01

    This study linked the Moderate Resolution Imaging Spectrometer and USDA Forest Service, Forest Inventory and Analysis (FIA) data through empirical models established using high-resolution Landsat Enhanced Thematic Mapper Plus observations to estimate aboveground biomass (AGB) in three Lake States in the north-central USA. While means obtained from larger sample sizes...

  7. 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

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

    NASA Astrophysics Data System (ADS)

    Mangla, Rohit; Kumar, Shashi; Nandy, Subrata

    2016-05-01

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

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

    NASA Technical Reports Server (NTRS)

    Nelson, Ross F.

    2010-01-01

    Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.

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

    Treesearch

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

    2000-01-01

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

  11. Deciduous conifers: high n deposition and o3 exposure effects on growth and biomass allocation in ponderosa pine

    Treesearch

    Nancy Grulke; L. Balduman

    1999-01-01

    Ponderosa pines (Pinus ponderosa Dougl. ex. Laws) 21 to 60 yr old were used to assess the relative importance of environmental stressors (O3, drought) versus an enhancer (N deposition) on foliar retention, components of aboveground growth, and whole tree biomass allocation. Sites were chosen across a well-described gradient...

  12. Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of Sao Paulo, Brazil

    Treesearch

    Carlos Alberto Silva; Carine Klauberg; Samuel de Padua Chaves e Carvalho; Andrew T. Hudak; e Luiz Carlos Estraviz Rodriguez

    2014-01-01

    Fast growing plantation forests provide a low-cost means to sequester carbon for greenhouse gas abatement. The aim of this study was to evaluate airborne LiDAR (Light Detection And Ranging) to predict aboveground carbon (AGC) stocks in Eucalyptus spp. plantations. Biometric parameters (tree height (Ht) and diameter at breast height (DBH)) were collected from...

  13. Relationships of Biomass with Environmental Factors in the Grassland Area of Hulunbuir, China

    PubMed Central

    Liu, Miao; Liu, Guohua; Gong, Li; Wang, Dongbo; Sun, Jian

    2014-01-01

    Many studies have focused on the relationship between vegetation biomass and environmental factors in grassland. However, several questions remain to be answered, especially with regards to the spatial pattern of vegetation biomass. Thus, the distributed mechanism will be explored in the present study. Here, plant biomass was measured at 23 sites along a transect survey during the peak growing season in 2006. The data were analyzed with a classification and regression tree (CART) model. The structural equation modeling (SEM) was conducted to explicitly evaluate the both direct and indirect effects of these critical environmental elements on vegetation biomass. The results demonstrated that mean annual temperature (MAT) affected aboveground biomass (AGB) scored at −0.811 (P<0.05). The direct effect of MAT on belowground biomass (BGB) was −0.490 (P<0.05). The results were determined by SEM. Our results indicate that AGB and BGB in semi-arid ecosystems is strongly affected by precipitation and temperature. Future work shall attempt to take into account the integrated effects of precipitation and temperature. Meanwhile, partitioning the influences of environmental variations and vegetation types are helpful in illuminating the internal mechanism of biomass distribution. PMID:25032808

  14. Relationships of biomass with environmental factors in the grassland area of Hulunbuir, China.

    PubMed

    Liu, Miao; Liu, Guohua; Gong, Li; Wang, Dongbo; Sun, Jian

    2014-01-01

    Many studies have focused on the relationship between vegetation biomass and environmental factors in grassland. However, several questions remain to be answered, especially with regards to the spatial pattern of vegetation biomass. Thus, the distributed mechanism will be explored in the present study. Here, plant biomass was measured at 23 sites along a transect survey during the peak growing season in 2006. The data were analyzed with a classification and regression tree (CART) model. The structural equation modeling (SEM) was conducted to explicitly evaluate the both direct and indirect effects of these critical environmental elements on vegetation biomass. The results demonstrated that mean annual temperature (MAT) affected aboveground biomass (AGB) scored at -0.811 (P<0.05). The direct effect of MAT on belowground biomass (BGB) was -0.490 (P<0.05). The results were determined by SEM. Our results indicate that AGB and BGB in semi-arid ecosystems is strongly affected by precipitation and temperature. Future work shall attempt to take into account the integrated effects of precipitation and temperature. Meanwhile, partitioning the influences of environmental variations and vegetation types are helpful in illuminating the internal mechanism of biomass distribution.

  15. C3 and C4 biomass allocation responses to elevated CO2 and nitrogen: contrasting resource capture strategies

    USGS Publications Warehouse

    White, K.P.; Langley, J.A.; Cahoon, D.R.; Megonigal, J.P.

    2012-01-01

    Plants alter biomass allocation to optimize resource capture. Plant strategy for resource capture may have important implications in intertidal marshes, where soil nitrogen (N) levels and atmospheric carbon dioxide (CO2) are changing. We conducted a factorial manipulation of atmospheric CO2 (ambient and ambient + 340 ppm) and soil N (ambient and ambient + 25 g m-2 year-1) in an intertidal marsh composed of common North Atlantic C3 and C4 species. Estimation of C3 stem turnover was used to adjust aboveground C3 productivity, and fine root productivity was partitioned into C3-C4 functional groups by isotopic analysis. The results suggest that the plants follow resource capture theory. The C3 species increased aboveground productivity under the added N and elevated CO2 treatment (P 2 alone. C3 fine root production decreased with added N (P 2 (P = 0.0481). The C4 species increased growth under high N availability both above- and belowground, but that stimulation was diminished under elevated CO2. The results suggest that the marsh vegetation allocates biomass according to resource capture at the individual plant level rather than for optimal ecosystem viability in regards to biomass influence over the processes that maintain soil surface elevation in equilibrium with sea level.

  16. Multi-stage approach to estimate forest biomass in degraded area by fire and selective logging

    NASA Astrophysics Data System (ADS)

    Santos, E. G.; Shimabukuro, Y. E.; Arai, E.; Duarte, V.; Jorge, A.; Gasparini, K.

    2017-12-01

    The Amazon forest has been the target of several threats throughout the years. Anthropogenic disturbances in the region can significantly alter this environment, affecting directly the dynamics and structure of tropical forests. Monitoring these threats of forest degradation across the Amazon is of paramount to understand the impacts of disturbances in the tropics. With the advance of new technologies such as Light Detection and Ranging (LiDAR) the quantification and development of methodologies to monitor forest degradation in the Amazon is possible and may bring considerable contributions to this topic. The objective of this study was to use remote sensing data to assess and estimate the aboveground biomass (AGB) across different levels of degradation (fire and selective logging) using multi-stage approach between airborne LiDAR and orbital image. The study area is in the northern part of the state of Mato Grosso, Brazil. It is predominantly characterized by agricultural land and remnants of the Amazon Forest intact and degraded by either anthropic or natural reasons (selective logging and/or fire). More specifically, the study area corresponds to path/row 226/69 of OLI/Landsat 8 image. With a forest mask generated from the multi-resolution segmentation, agriculture and forest areas, forest biomass was calculated from LiDAR data and correlated with texture images, vegetation indices and fraction images by Linear Spectral Unmixing of OLI/Landsat 8 image and extrapolated to the entire scene 226/69 and validated with field inventories. The results showed that there is a moderate to strong correlation between forest biomass and texture data, vegetation indices and fraction images. With that, it is possible to extract biomass information and create maps using optical data, specifically by combining vegetation indices, which contain forest greening information with texture data that contains forest structure information. Then it was possible to extrapolate the biomass

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

    NASA Astrophysics Data System (ADS)

    Baccini, A.; Walker, W. S.; Carvalho, L.; Farina, M.; Sulla-menashe, D. J.; Houghton, R. A.

    2017-12-01

    Tropical forests hold large stores of carbon, but their net carbon balance is uncertain. Land use and land-cover change (LULCC) are believed to release between 0.81 and 1.14 PgC yr-1, while intact native forests are thought to be a net carbon sink of approximately the same magnitude. Reducing the uncertainty of these estimates is not only fundamental to the advancement of carbon cycle science but is also of increasing relevance to national and international policies designed to reduce emissions from deforestation and forest degradation (e.g., REDD+). Contemporary approaches to estimating the net carbon balance of tropical forests rely on changes in forest area between two periods, typically derived from satellite data, together with information on average biomass density. These approaches tend to capture losses in biomass due to deforestation (i.e., wholesale stand removals) but are limited in their sensitivity to forest degradation (e.g., selective logging or single-tree removals), which can account for additional biomass losses on the order of 47-75% of deforestation. Furthermore, while satellite-based estimates of forest area loss have been used successfully to estimate associated carbon losses, few such analyses have endeavored to determine the rate of carbon sequestration in growing forests. Here we use 12 years (2003-2014) of pantropical satellite data to quantify net annual changes in the aboveground carbon density of woody vegetation (MgC ha-1yr-1), providing direct, measurement-based evidence that the world's tropical forests are a net carbon source of 425.2 ± 92.0 Tg C yr-1. This net release of carbon consists of losses of 861.7 ± 80.2 Tg C yr-1 and gains of -436.5 ± 31.0 Tg C yr-1 . Gains result from forest growth; losses result from reductions in forest area due to deforestation and from reductions in biomass density within standing forests (degradation), with the latter accounting for 68.9% of overall losses. Our findings advance previous research

  18. Soil warming and CO2 enrichment induce biomass shifts in alpine tree line vegetation.

    PubMed

    Dawes, Melissa A; Philipson, Christopher D; Fonti, Patrick; Bebi, Peter; Hättenschwiler, Stephan; Hagedorn, Frank; Rixen, Christian

    2015-05-01

    Responses of alpine tree line ecosystems to increasing atmospheric CO2 concentrations and global warming are poorly understood. We used an experiment at the Swiss tree line to investigate changes in vegetation biomass after 9 years of free air CO2 enrichment (+200 ppm; 2001-2009) and 6 years of soil warming (+4 °C; 2007-2012). The study contained two key tree line species, Larix decidua and Pinus uncinata, both approximately 40 years old, growing in heath vegetation dominated by dwarf shrubs. In 2012, we harvested and measured biomass of all trees (including root systems), above-ground understorey vegetation and fine roots. Overall, soil warming had clearer effects on plant biomass than CO2 enrichment, and there were no interactive effects between treatments. Total plant biomass increased in warmed plots containing Pinus but not in those with Larix. This response was driven by changes in tree mass (+50%), which contributed an average of 84% (5.7 kg m(-2) ) of total plant mass. Pinus coarse root mass was especially enhanced by warming (+100%), yielding an increased root mass fraction. Elevated CO2 led to an increased relative growth rate of Larix stem basal area but no change in the final biomass of either tree species. Total understorey above-ground mass was not altered by soil warming or elevated CO2 . However, Vaccinium myrtillus mass increased with both treatments, graminoid mass declined with warming, and forb and nonvascular plant (moss and lichen) mass decreased with both treatments. Fine roots showed a substantial reduction under soil warming (-40% for all roots <2 mm in diameter at 0-20 cm soil depth) but no change with CO2 enrichment. Our findings suggest that enhanced overall productivity and shifts in biomass allocation will occur at the tree line, particularly with global warming. However, individual species and functional groups will respond differently to these environmental changes, with consequences for ecosystem structure and functioning. © 2014

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

    Treesearch

    D.C. Bragg; K.M. McElligott

    2013-01-01

    Sequestration by Arkansas forests removes carbon dioxide from the atmosphere, storing this carbon in biomass that fills a number of critical ecological and socioeconomic functions. We need a better understanding of the contribution of forests to the carbon cycle, including the accurate quantification of tree biomass. Models have long been developed to predict...

  20. Massive mortality of aspen following severe drought along the southern edge of the Canadian boreal forest

    PubMed Central

    Michaelian, Michael; Hogg, Edward H; Hall, Ronald J; Arsenault, Eric

    2011-01-01

    Drought-induced, regional-scale dieback of forests has emerged as a global concern that is expected to escalate under model projections of climate change. Since 2000, drought of unusual severity, extent, and duration has affected large areas of western North America, leading to regional-scale dieback of forests in the southwestern US. We report on drought impacts on forests in a region farther north, encompassing the transition between boreal forest and prairie in western Canada. A central question is the significance of drought as an agent of large-scale tree mortality and its potential future impact on carbon cycling in this cold region. We used a combination of plot-based, meteorological, and remote sensing measures to map and quantify aboveground, dead biomass of trembling aspen (Populus tremuloides Michx.) across an 11.5 Mha survey area where drought was exceptionally severe during 2001–2002. Within this area, a satellite-based land cover map showed that aspen-dominated broadleaf forests occupied 2.3 Mha. Aerial surveys revealed extensive patches of severe mortality (>55%) resembling the impacts of fire. Dead aboveground biomass was estimated at 45 Mt, representing 20% of the total aboveground biomass, based on a spatial interpolation of plot-based measurements. Spatial variation in percentage dead biomass showed a moderately strong correlation with drought severity. In the prairie-like, southern half of the study area where the drought was most severe, 35% of aspen biomass was dead, compared with an estimated 7% dead biomass in the absence of drought. Drought led to an estimated 29 Mt increase in dead biomass across the survey area, corresponding to 14 Mt of potential future carbon emissions following decomposition. Many recent, comparable episodes of drought-induced forest dieback have been reported from around the world, which points to an emerging need for multiscale monitoring approaches to quantify drought effects on woody biomass and carbon cycling

  1. 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

    2014-01-03

    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. Copyright © 2013 Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2016-01-01

    Tropical forests are the global cornerstone of biological diversity, and store 55% of the forest carbon stock globally, yet sustained provisioning of these forest ecosystem services may be threatened by hunting-induced extinctions of plant–animal mutualisms that maintain long-term forest dynamics. Large-bodied Atelinae primates and tapirs in particular offer nonredundant seed-dispersal services for many large-seeded Neotropical tree species, which on average have higher wood density than smaller-seeded and wind-dispersed trees. We used field data and models to project the spatial impact of hunting on large primates by ∼1 million rural households throughout the Brazilian Amazon. We then used a unique baseline dataset on 2,345 1-ha tree plots arrayed across the Brazilian Amazon to model changes in aboveground forest biomass under different scenarios of hunting-induced large-bodied frugivore extirpation. We project that defaunation of the most harvest-sensitive species will lead to losses in aboveground biomass of between 2.5–5.8% on average, with some losses as high as 26.5–37.8%. These findings highlight an urgent need to manage the sustainability of game hunting in both protected and unprotected tropical forests, and place full biodiversity integrity, including populations of large frugivorous vertebrates, firmly in the agenda of reducing emissions from deforestation and forest degradation (REDD+) programs. PMID:26811455

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

    PubMed

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

    2016-01-26

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

  4. 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.

  5. Spaceborne Applications of P Band Imaging Radars for Measuring Forest Biomass

    NASA Technical Reports Server (NTRS)

    Rignot, Eric J.; Zimmermann, Reiner; vanZyl, Jakob J.

    1995-01-01

    In three sites of boreal and temperate forests, P band HH, HV, and VV polarization data combined estimate total aboveground dry woody biomass within 12 to 27% of the values derived from allometric equations, depending on forest complexity. Biomass estimates derived from HV-polarization data only are 2 to 14% less accurate. When the radar operates at circular polarization, the errors exceed 100% over flooded forests, wet or damaged trees and sparse open tall forests because double-bounce reflections of the radar signals yield radar signatures similar to that of tall and massive forests. Circular polarizations, which minimize the effect of Faraday rotation in spaceborne applications, are therefore of limited use for measuring forest biomass. In the tropical rain forest of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 50 kg/sq m in old, undisturbed floodplain stands, the P band horizontal and vertical polarization data combined separate biomass classes in good agreement with forest inventory estimates. The worldwide need for large scale, updated, biomass estimates, achieved with a uniformly applied method, justifies a more in-depth exploration of multi-polarization long wavelength imaging radar applications for tropical forests inventories.

  6. Biomass Maps | Geospatial Data Science | NREL

    Science.gov Websites

    emissions from organic wastes Methane Generation Potential from Industrial, Institutional, and Commercial Organic Wastes Publications A Geographic Perspective on the Current Biomass Resource Availability in the

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

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

    Treesearch

    Sean P. Healey; Paul L. Patterson; Sassan S. Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman

    2012-01-01

    Lidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform "shots," which have been shown to be strongly correlated with aboveground forest...

  10. A national-scale remote sensing-based methodology for quantifying tidal marsh biomass to support "Blue Carbon" accounting

    NASA Astrophysics Data System (ADS)

    Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Thomas, N.; Windham-Myers, L.; Castaneda, E.; Kroeger, K. D.; Gonneea, M. E.; O'Keefe Suttles, J.; Megonigal, P.; Troxler, T.; Schile, L. M.; Davis, M.; Woo, I.

    2016-12-01

    According to 2013 IPCC Wetlands Supplement guidelines, tidal marsh Tier 2 or Tier 3 accounting must include aboveground biomass carbon stock changes. To support this need, we are using free satellite and aerial imagery to develop a national scale, consistent remote sensing-based methodology for quantifying tidal marsh aboveground biomass. We are determining the extent to which additional satellite data will increase the accuracy of this "blue carbon" accounting. Working in 6 U.S. estuaries (Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA), we built a tidal marsh biomass dataset (n=2404). Landsat reflectance data were matched spatially and temporally with field plots using Google Earth Engine. We quantified percent cover of green vegetation, non-vegetation, and open water in Landsat pixels using segmentation of 1m National Agriculture Imagery Program aerial imagery. Sentinel-1A C-band backscatter data were used in Chesapeake, Mississippi Delta and Puget Sound. We tested multiple Landsat vegetation indices and Sentinel backscatter metrics in 30m scale biomass linear regression models by region. Scaling biomass by fraction green vegetation significantly improved biomass estimation (e.g. Cape Cod: R2 = 0.06 vs. R2 = 0.60, n=28). The best vegetation indices differed by region, though indices based on the shortwave infrared-1 and red bands were most predictive in the Everglades and the Mississippi Delta, while the soil adjusted vegetation index was most predictive in Puget Sound and Chesapeake. Backscatter metrics significantly improved model predictions over vegetation indices alone; consistently across regions, the most significant metric was the range in backscatter values within the green vegetation segment of the Landsat pixel (e.g. Mississippi Delta: R2 = 0.47 vs. R2 = 0.59, n=15). Results support using remote sensing of biomass stock change to estimate greenhouse gas emission factors in tidal

  11. Impacts of fire management on aboveground tree carbon stocks in Yosemite and Sequoia & Kings Canyon National Parks

    USGS Publications Warehouse

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

    2015-01-01

    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.

  12. Utilizing individual fish biomass and relative abundance models to map environmental niche associations of adult and juvenile targeted fishes.

    PubMed

    Galaiduk, Ronen; Radford, Ben T; Harvey, Euan S

    2018-06-21

    Many fishes undergo ontogenetic habitat shifts to meet their energy and resource needs as they grow. Habitat resource partitioning and patterns of habitat connectivity between conspecific fishes at different life-history stages is a significant knowledge gap. Species distribution models were used to examine patterns in the relative abundance, individual biomass estimates and environmental niche associations of different life stages of three iconic West Australian fishes. Continuous predictive maps describing the spatial distribution of abundance and individual biomass of the study species were created as well predictive hotspot maps that identify possible areas for aggregation of individuals of similar life stages of multiple species (i.e. spawning grounds, fisheries refugia or nursery areas). The models and maps indicate that processes driving the abundance patterns could be different from the body size associated demographic processes throughout an individual's life cycle. Incorporating life-history in the spatially explicit management plans can ensure that critical habitat of the vulnerable stages (e.g. juvenile fish, spawning stock) is included within proposed protected areas and can enhance connectivity between various functional areas (e.g. nursery areas and adult populations) which, in turn, can improve the abundance of targeted species as well as other fish species relying on healthy ecosystem functioning.

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

    PubMed

    Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

    2015-12-01

    Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

  14. 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.

  15. Improved accuracy of aboveground biomass and carbon estimates for live trees in forests of the eastern United States

    Treesearch

    Philip Radtke; David Walker; Jereme Frank; Aaron Weiskittel; Clara DeYoung; David MacFarlane; Grant Domke; Christopher Woodall; John Coulston; James Westfall

    2017-01-01

    Accurate estimation of forest biomass and carbon stocks at regional to national scales is a key requirement in determining terrestrial carbon sources and sinks on United States (US) forest lands. To that end, comprehensive assessment and testing of alternative volume and biomass models were conducted for individual tree models employed in the component ratio method (...

  16. 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.

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

    Treesearch

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

    2017-01-01

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

  18. A preliminary aboveground live biomass model for understory hardwoods from Arkansas, Louisiana, and Mississippi

    Treesearch

    Don C. Bragg; D. Andrew. Scott

    2014-01-01

    Hardwood understories can contribute significantly to total ecosystem biomass and fuel loads, but few models are available to directly quantify this component. In part, this is due to the small size of the hardwoods. Many understory trees simply do not reach the height required to determine diameter at breast height (d.b.h.), so conventional models (e.g., the National...

  19. Aboveground and belowground net primary production

    Treesearch

    Hal O. Liechty; Mark H. Eisenbies

    2000-01-01

    The relationship among net primary productivity (NPP), hydroperiod, and fertility in forested wetlands is poorly understood (Burke and others 1999), particularly with respect to belowground NPP (Megonigal and others 1997). Although some researchers have studied aboveground and belowground primary production in depressional, forested wetland systems, e.g., Day and...

  20. Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

    NASA Technical Reports Server (NTRS)

    Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

    2016-01-01

    Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.