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Sample records for aboveground biomass agb

  1. 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

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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

  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. 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...

  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. 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...

  11. 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...

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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

  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. 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...

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. 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...

  6. 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

  7. 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.

  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. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  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. 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. 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

  17. 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.

  18. 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

  19. 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-...

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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

  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 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.

  8. 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...

  9. 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...

  10. 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.

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

    PubMed

    Ercanli, İlker; Kahriman, Aydın

    2015-03-01

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

  12. [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.

  13. 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...

  14. 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

  15. 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

  16. 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...

  17. 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...

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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

  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 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.

  5. 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.

  6. 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

  7. 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...

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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...

  17. 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

  18. 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,...

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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...

  5. 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.

  6. [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).

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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....

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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...

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

    NASA Astrophysics Data System (ADS)

    El Masri, Bassil

    2011-12-01

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

  11. 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...

  12. 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-...

  13. 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...

  14. 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),...

  15. 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...

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

    NASA Astrophysics Data System (ADS)

    Dube, Timothy; Mutanga, Onisimo

    2016-09-01

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

  17. 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.

  18. 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

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

    SciTech Connect

    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

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

    PubMed Central

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

    2013-01-01

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

  1. 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...

  2. 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

  3. 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

  4. 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

  5. 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...

  6. 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

  7. 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.

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

    PubMed Central

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

    2016-01-01

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

  9. 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.

  10. 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...

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  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. 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.

  17. 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...

  18. 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...

  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. 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

  1. 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.

  2. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    SciTech Connect

    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

  5. 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

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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).

  11. 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.

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

    PubMed

    Yadav, Bechu K V; Nandy, S

    2015-05-01

    Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

  13. 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....

  14. 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...

  15. 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...

  16. 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+).

  17. 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

  18. 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.

  19. 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

  20. 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

  1. [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.

  2. 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

  3. 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.

  4. 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...

  5. 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

  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. 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

  8. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. [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.

  17. 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...

  18. 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.

  19. 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

  20. 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)...

  1. 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...

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

    NASA Astrophysics Data System (ADS)

    Hadley, Brian Christopher

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Kilbride, J. B.; Fraver, S.; Ayrey, E.; Weiskittel, A.; Braaten, J.; Hughes, J. M.; Hayes, D. J.

    2017-12-01

    Forests within the New England states and Canadian Maritime provinces, here described as the Acadian New England (ANE) forests, have undergone substantial disturbances due to insect, fire, and anthropogenic factors. Through repeated satellite observations captures by USGS's Landsat program, 45 years of disturbance information can be incorporated into modeling efforts to better understand the spatial and temporal trends in forest above ground biomass (AGB). Using Google's Earth Engine, annual mosaics were developed for the ANE study area and then disturbance and recovery metrics were developed using the temporal segmentation algorithm VeRDET. Normalization procedures were developed to incorporate the Landsat Multispectral Scanner (MSS, 1972 - 1985) data alongside the modern era of Landsat Thematic Mapper (TM, 1984-2013), Enhanced Thematic Mapper plus (ETM+, 1999 - present), and Operational Land Imager (OLI, 2013- present) data products. This has enabled the creation of a dataset with an unprecedented spatial and temporal view of forest landscape change. Model training was performed using was the Forest Inventory Analysis (FIA) and New Brunswick Permanent Sample Plot data datasets. Modeling was performed using parametric techniques such as mixed effects models and non-parametric techniques such as k-NN imputation and generalized boosted regression. We compare the biomass estimate and model accuracy to other inventory and modeling studies produced within this study area. The spatial and temporal patterns of stock changes are analyzed against resource policy, land ownership changes, and forest management.

  5. 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

  6. 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...

  7. 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...

  8. 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...

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

    SciTech Connect

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

    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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  11. 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

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

    PubMed

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  14. 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

    usually the highest scoring spectral indices in explaining biomass distribution with good explanatory power. Furthermore, models which had more than one explanatory variable had higher explanatory power than models with a single index. The dissimilarity between common and site-specific model estimates was, however, high and data indicates that variation in vegetation properties and its impact on spectral reflectance needs to be acknowledged. Our work produced knowledge on above-ground biomass distribution and contribution of PFTs across circum-Arctic low-growth landscapes and will contribute to developing space-borne vegetation monitoring schemes utilizing VHSR satellite images.

  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. 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

  17. 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

  18. 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...

  19. 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...

  20. 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)...

  1. 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.

  2. 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...

  3. 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

  4. 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...

  5. 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

  6. 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...

  7. 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...

  8. 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.

  9. 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...

  10. 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...

  11. Time Series of Tropical-Forest Structure from TanDEM-X, Transformed to Time Series of Biomass by MODIS

    NASA Astrophysics Data System (ADS)

    Treuhaft, R. N.; Baccini, A.; Goncalves, F. G.; Lei, Y.; Keller, M.; Walker, W. S.

    2017-12-01

    Tropical forests account for about 50% of the world's forested biomass, and play a critical role in the control of atmospheric carbon dioxide. Large-scale (1000's of km) changes in forest structure and biomass bear on global carbon source-sink dynamics, while small-scale (< 100 m) changes bear on deforestation and degradation monitoring. After describing the interferometric SAR (InSAR) phase-height observation, we show forest phase-height time series from the TanDEM-X radar interferometer at X-band (3 cm), taken with monthly and sub-hectare temporal and spatial resolution, respectively. The measurements were taken with more than 30 TanDEM-X passes over Tapajós National Forest in the Brazilian Amazon between 2011 and 2014. The transformation of phase-height rates into aboveground biomass (AGB) rates is based on the idea that the change in AGB due to a change in phase-height depends on the plot's AGB. Plots with higher AGB will produce more AGB for a given increase in height or phase-height. Postulating a power-law dependence of plot-level mass density on physical height, we previously found that the best conversion factors for transforming phase-height rate to AGB rate were indeed dependent on AGB. For 78 plots, we demonstrated AGB rates from InSAR phase-height rates using AGB from field measurements. For regional modeling of the Amazon Basin, field measurements of AGB, to specify the conversion factors, is impractical. Conversion factors from InSAR phase-height rate to AGB rate in this talk will be based on AGB derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). AGB measurement from MODIS is based on the spectral reflectance of 7 bands from the visible to short wave infrared, and auxiliary metrics describing the variance in reflectance. The mapping of MODIS reflectance to AGB is enabled by training a machine learning algorithm with lidar-derived AGB data, which are in turn trained by field measurements for small areas. The performance of Tan

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

    PubMed

    Schnabel, William; Munk, Jens; Byrd, Amanda

    2015-01-01

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

  13. 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

  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. 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

  16. [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

  17. 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.

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

    DOE PAGES

    Medeiros, Stephen; Hagen, Scott; Weishampel, John; ...

    2015-03-25

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

  19. [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

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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...

  7. On the Correlation Between Biomass and the P-Band Polarisation Phase Difference, and Its Potential for Biomass and Tree Number Density Estimation

    NASA Astrophysics Data System (ADS)

    Soja, Maciej J.; Blomberg, Erik; Ulander, Lars M. H.

    2015-04-01

    In this paper, a significant correlation between the HH/VV phase difference (polarisation phase difference, PPD) and the above-ground biomass (AGB) is observed for incidence angles above 30° in airborne P-band SAR data acquired over two boreal test sites in Sweden. A geometric model is used to explain the dependence of the AGB on tree height, stem radius, and tree number density, whereas a cylinder-over-ground model is used to explain the dependence of the PPD on the same three forest parameters. The models show that forest anisotropy need to be accounted for at P-band in order to obtain a linear relationship between the PPD and the AGB. An approach to the estimation of tree number density is proposed, based on a comparison between the modelled and observed PPDs.

  8. 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...

  9. 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...

  10. 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 (...

  11. 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...

  12. 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.

  13. 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

  14. AGB and post-AGB objects in the outer Galaxy

    NASA Astrophysics Data System (ADS)

    Szczerba, Ryszard; Yung, Bosco H. K.; Sewiło, Marta; Siódmiak, Natasza; Karska, Agata

    2017-10-01

    We present the results of our search for low- and intermediate mass evolved stars in the outer Galaxy using AllWISE catalogue photometry. We show that the [3.4]-[12] vs. [4.6]-[22] colour-colour diagram is most suitable for separating C-rich/O-rich AGB and post-AGB star candidates. We are able to select 2,510 AGB and 24,821 post-AGB star candidates. However, the latter are severely mixed with the known young stellar objects in this diagram.

  15. 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

  16. 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

  17. 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

  18. Applying inventory methods to estimate aboveground biomass from satellite light detection and ranging (LiDAR) forest height data

    Treesearch

    Sean P. Healey; Paul L. Patterson; Sassan Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman; Gretchen G. Moisen

    2012-01-01

    Light Detection and Ranging (LiDAR) returns from the spaceborne Geoscience Laser Altimeter (GLAS) sensor may offer an alternative to solely field-based forest biomass sampling. Such an approach would rely upon model-based inference, which can account for the uncertainty associated with using modeled, instead of field-collected, measurements. Model-based methods have...

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  20. 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.

  1. 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.

  2. 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

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

    NASA Astrophysics Data System (ADS)

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

    2018-06-01

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

  4. 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

  5. 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

  6. 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

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

    SciTech Connect

    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

  8. Environmental filtering and land-use history drive patterns in biomass accumulation in a mediterranean-type landscape.

    PubMed

    Dahlin, Kyla M; Asner, Gregory P; Field, Christopher B

    2012-01-01

    Aboveground biomass (AGB) reflects multiple and often undetermined ecological and land-use processes, yet detailed landscape-level studies of AGB are uncommon due to the difficulty in making consistent measurements at ecologically relevant scales. Working in a protected mediterranean-type landscape (Jasper Ridge Biological Preserve, California, USA), we combined field measurements with remotely sensed data from the Carnegie Airborne Observatory's light detection and ranging (lidar) system to create a detailed AGB map. We then developed a predictive model using a maximum of 56 explanatory variables derived from geologic and historic-ownership maps, a digital elevation model, and geographic coordinates to evaluate possible controls over currently observed AGB patterns. We tested both ordinary least-squares regression (OLS) and autoregressive approaches. OLS explained 44% of the variation in AGB, and simultaneous autoregression with a 100-m neighborhood improved the fit to an r2 = 0.72, while reducing the number of significant predictor variables from 27 variables in the OLS model to 11 variables in the autoregressive model. We also compared the results from these approaches to a more typical field-derived data set; we randomly sampled 5% of the data 1000 times and used the same OLS approach each time. Environmental filters including incident solar radiation, substrate type, and topographic position were significant predictors of AGB in all models. Past ownership was a minor but significant predictor, despite the long history of conservation at the site. The weak predictive power of these environmental variables, and the significant improvement when spatial autocorrelation was incorporated, highlight the importance of land-use history, disturbance regime, and population dynamics as controllers of AGB.

  9. Environmental Humidity Regulates Effects of Experimental Warming on Vegetation Index and Biomass Production in an Alpine Meadow of the Northern Tibet

    PubMed Central

    Fu, Gang; Shen, Zhen Xi

    2016-01-01

    Uncertainty about responses of vegetation index, aboveground biomass (AGB) and gross primary production (GPP) limits our ability to predict how climatic warming will influence plant growth in alpine regions. A field warming experiment was conducted in an alpine meadow at a low (4313 m), mid- (4513 m) and high elevation (4693 m) in the Northern Tibet since May 2010. Growing season vapor pressure deficit (VPD), soil temperature (Ts) and air temperature (Ta) decreased with increasing elevation, while growing season precipitation, soil moisture (SM), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), AGB and GPP increased with increasing elevation. The growing season Ta, Ts and VPD in 2015 was greater than that in 2014, while the growing season precipitation, SM, NDVI, SAVI, AGB and GPP in 2015 was lower than that in 2014, respectively. Compared to the mean air temperature and precipitation during the growing season in 1963–2015, it was a warmer and wetter year in 2014 and a warmer and drier year in 2015. Experimental warming increased growing season Ts, Ta,VPD, but decreased growing season SM in 2014–2015 at all the three elevations. Experimental warming only reduced growing season NDVI, SAVI, AGB and GPP at the low elevation in 2015. Growing season NDVI, SAVI, AGB and GPP increased with increasing SM and precipitation, but decreased with increasing VPD, indicating vegetation index and biomass production increased with environmental humidity. The VPD explained more variation of growing season NDVI, SAVI, AGB and GPP compared to Ts, Ta and SM at all the three elevations. Therefore, environmental humidity regulated the effect of experimental warming on vegetation index and biomass production in alpine meadows on the Tibetan Plateau. PMID:27798690

  10. 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

  11. 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.

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

    PubMed

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

    2014-11-01

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

  13. Calculating accurate aboveground dry weight biomass of herbaceous vegetation in the Great Plains: A comparison of three calculations to determine the least resource intensive and most accurate method

    Treesearch

    Ben Butler

    2007-01-01

    Obtaining accurate biomass measurements is often a resource-intensive task. Data collection crews often spend large amounts of time in the field clipping, drying, and weighing grasses to calculate the biomass of a given vegetation type. Such a problem is currently occurring in the Great Plains region of the Bureau of Indian Affairs. A study looked at six reservations...

  14. 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.

  15. 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

  16. 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

  17. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    DOE PAGES

    Magnabosco Marra, Daniel; Higuchi, Niro; Trumbore, Susan E.; ...

    2016-03-11

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

  20. Developing above-ground woody biomass equations for open-grown, multiple-stemmed tree species: shelterbelt-grown Russian-olive

    Treesearch

    Xinhau Zhour; James R. Brandle; Michele M. Schoeneberger; Tala Awada

    2007-01-01

    Multiple-stemmed tree species are often used in agricultural settings, playing a significant role in natural resource conservation and carbon sequestration. Biomass estimation, whether for modeling growth under different climate scenarios, accounting for carbon sequestered, or inclusion in natural resource inventories, requires equations that can accurately describe...

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

    Treesearch

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

    2012-01-01

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

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

    USDA-ARS?s Scientific Manuscript database

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

  3. Five-year vegetation control effects on aboveground biomass and nitrogen content and allocation in Douglas-fir plantations on three contrasting sites

    Treesearch

    Warren D. Devine; Timothy B. Harrington; Thomas A. Terry; Robert B. Harrison; Robert A. Slesak; David H. Peter; Constance A. Harrington; Carol J. Shilling; Stephen H. Schoenholtz

    2011-01-01

    Despite widespread use of intensive vegetation control (VC) in forest management, the effects of VC on allocation of biomass and nutrients between young trees and competing vegetation are not well understood. On three Pacific Northwest sites differing in productivity, soil parent material, and understory vegetation community, we evaluated year-5 effects of presence/...

  4. Unearthing the hidden world of roots: Root biomass and architecture differ among species within the same guild

    PubMed Central

    2017-01-01

    The potential benefits of planting trees have generated significant interest with respect to sequestering carbon and restoring other forest based ecosystem services. Reliable estimates of carbon stocks are pivotal for understanding the global carbon balance and for promoting initiatives to mitigate CO2 emissions through forest management. There are numerous studies employing allometric regression models that convert inventory into aboveground biomass (AGB) and carbon (C). Yet the majority of allometric regression models do not consider the root system nor do these equations provide detail on the architecture and shape of different species. The root system is a vital piece toward understanding the hidden form and function roots play in carbon accumulation, nutrient and plant water uptake, and groundwater infiltration. Work that estimates C in forests as well as models that are used to better understand the hydrologic function of trees need better characterization of tree roots. We harvested 40 trees of six different species, including their roots down to 2 mm in diameter and created species-specific and multi-species models to calculate aboveground (AGB), coarse root belowground biomass (BGB), and total biomass (TB). We also explore the relationship between crown structure and root structure. We found that BGB contributes ~27.6% of a tree’s TB, lateral roots extend over 1.25 times the distance of crown extent, root allocation patterns varied among species, and that AGB is a strong predictor of TB. These findings highlight the potential importance of including the root system in C estimates and lend important insights into the function roots play in water cycling. PMID:29023553

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  6. 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

  7. Current Mysteries of AGB Stars

    NASA Astrophysics Data System (ADS)

    Tout, Christopher A.

    We pay tribute to the memory of Manuel Forestini by recalling his contributions to astronomy and in particular to our understanding of AGB stars. We critically examine the current status of this understanding amongst the community and deduce that major uncertainties arise in the physics of convection, any form of extra mixing beyond convection and the mass loss from the stellar surface. Coupled with these are numerical difficulties associated with the short and similar timescales for structural changes, nuclear burning and convective mixing. We hope that workshops such as this will promote familiarity amongst our diverse international community young and old and so promote effective dialogue that will ultimately lead to solutions to our problems along with the creation of new ones for the future!

  8. 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

  9. Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

    DOE PAGES

    Magnabosco Marra, Daniel; Higuchi, Niro; Trumbore, Susan E.; ...

    2016-04-27

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

  10. Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

    SciTech Connect

    Magnabosco Marra, Daniel; Higuchi, Niro; Trumbore, Susan E.

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

  11. The Rb problem in massive AGB stars.

    NASA Astrophysics Data System (ADS)

    Pérez-Mesa, V.; García-Hernández, D. A.; Zamora, O.; Plez, B.; Manchado, A.; Karakas, A. I.; Lugaro, M.

    2017-03-01

    The asymptotic giant branch (AGB) is formed by low- and intermediate-mass stars (0.8 M_{⊙} < M < 8 M_{⊙}) in their last nuclear-burning phase, when they develop thermal pulses (TP) and suffer extreme mass loss. AGB stars are the main contributor to the enrichment of the interstellar medium (ISM) and thus to the chemical evolution of galaxies. In particular, the more massive AGB stars (M > 4 M_{⊙}) are expected to produce light (e.g., Li, N) and heavy neutron-rich s-process elements (such as Rb, Zr, Ba, Y, etc.), which are not formed in lower mass AGB stars and Supernova explosions. Classical chemical analyses using hydrostatic atmospheres revealed strong Rb overabundances and high [Rb/Zr] ratios in massive AGB stars of our Galaxy and the Magellanic Clouds (MC), confirming for the first time that the ^{22}Ne neutron source dominates the production of s-process elements in these stars. The extremely high Rb abundances and [Rb/Zr] ratios observed in the most massive stars (specially in the low-metallicity MC stars) uncovered a Rb problem; such extreme Rb and [Rb/Zr] values are not predicted by the s-process AGB models, suggesting fundamental problems in our present understanding of their atmospheres. We present more realistic dynamical model atmospheres that consider a gaseous circumstellar envelope with a radial wind and we re-derive the Rb (and Zr) abundances in massive Galactic AGB stars. The new Rb abundances and [Rb/Zr] ratios derived with these dynamical models significantly resolve the problem of the mismatch between the observations and the theoretical predictions of the more massive AGB stars.

  12. INFRARED TWO-COLOR DIAGRAMS FOR AGB STARS, POST-AGB STARS, AND PLANETARY NEBULAE

    SciTech Connect

    Suh, Kyung-Won, E-mail: kwsuh@chungbuk.ac.kr

    2015-08-01

    We present various infrared two-color diagrams (2CDs) for asymptotic giant branch (AGB) stars, post-AGB stars, and Planetary Nebulae (PNe) and investigate possible evolutionary tracks. We use catalogs from the available literature for the sample of 4903 AGB stars (3373 O-rich; 1168 C-rich; 362 S-type), 660 post-AGB stars (326 post-AGB; 334 pre-PN), and 1510 PNe in our Galaxy. For each object in the catalog, we cross-identify the IRAS, AKARI, Midcourse Space Experiment, and 2MASS counterparts. The IR 2CDs can provide useful information about the structure and evolution of the dust envelopes as well as the central stars. To find possible evolutionarymore » tracks from AGB stars to PNe on the 2CDs, we investigate spectral evolution of post-AGB stars by making simple but reasonable assumptions on the evolution of the central star and dust shell. We perform radiative transfer model calculations for the detached dust shells around evolving central stars in the post-AGB phase. We find that the theoretical dust shell model tracks using dust opacity functions of amorphous silicate and amorphous carbon roughly coincide with the densely populated observed points of AGB stars, post-AGB stars, and PNe on various IR 2CDs. Even though some discrepancies are inevitable, the end points of the theoretical post-AGB model tracks generally converge in the region of the observed points of PNe on most 2CDs.« less

  13. 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

  14. 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...

  15. Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

    NASA Astrophysics Data System (ADS)

    Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

    2017-12-01

    Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively

  16. Aggravated phosphorus limitation on biomass production under increasing nitrogen loading: a meta-analysis.

    PubMed

    Li, Yong; Niu, Shuli; Yu, Guirui

    2016-02-01

    Nitrogen (N) and phosphorus (P), either individually or in combination, have been demonstrated to limit biomass production in terrestrial ecosystems. Field studies have been extensively synthesized to assess global patterns of N impacts on terrestrial ecosystem processes. However, to our knowledge, no synthesis has been done so far to reveal global patterns of P impacts on terrestrial ecosystems, especially under different nitrogen (N) levels. Here, we conducted a meta-analysis of impacts of P addition, either alone or with N addition, on aboveground (AGB) and belowground biomass production (BGB), plant and soil P concentrations, and N : P ratio in terrestrial ecosystems. Overall, our meta-analysis quantitatively confirmed existing notions: (i) colimitation of N and P on biomass production and (ii) more P limitation in tropical forest than other ecosystems. More importantly, our analysis revealed new findings: (i) P limitation on biomass production was aggravated by N enrichment and (ii) plant P concentration was a better indicator of P limitation than soil P availability. Specifically, P addition increased AGB and BGB by 34% and 13%, respectively. The effect size of P addition on biomass production was larger in tropical forest than grassland, wetland, and tundra and varied with P fertilizer forms, P addition rates, or experimental durations. The P-induced increase in biomass production and plant P concentration was larger under elevated than ambient N. Our findings suggest that the global limitation of P on biomass production will become severer under increasing N fertilizer and deposition in the future. © 2015 John Wiley & Sons Ltd.

  17. Optimal climate for large trees at high elevations drives patterns of biomass in remote forests of Papua New Guinea.

    PubMed

    Venter, Michelle; Dwyer, John; Dieleman, Wouter; Ramachandra, Anurag; Gillieson, David; Laurance, Susan; Cernusak, Lucas A; Beehler, Bruce; Jensen, Rigel; Bird, Michael I

    2017-11-01

    Our ability to model global carbon fluxes depends on understanding how terrestrial carbon stocks respond to varying environmental conditions. Tropical forests contain the bulk of the biosphere's carbon. However, there is a lack of consensus as to how gradients in environmental conditions affect tropical forest carbon. Papua New Guinea (PNG) lies within one of the largest areas of contiguous tropical forest and is characterized by environmental gradients driven by altitude; yet, the region has been grossly understudied. Here, we present the first field assessment of aboveground biomass (AGB) across three main forest types of PNG using 193 plots stratified across 3,100-m elevation gradient. Unexpectedly, AGB had no direct relationship to rainfall, temperature, soil, or topography. Instead, natural disturbances explained most variation in AGB. While large trees (diameter at breast height > 50 cm) drove altitudinal patterns of AGB, resulting in a major peak in AGB (2,200-3,100 m) and some of the most carbon-rich forests at these altitudes anywhere. Large trees were correlated to a set of climatic variables following a hump-shaped curve. The set of "optimal" climatic conditions found in montane cloud forests is similar to that of maritime temperate areas that harbor the largest trees in the world: high ratio of precipitation to evapotranspiration (2.8), moderate mean annual temperature (13.7°C), and low intra-annual temperature range (7.5°C). At extreme altitudes (2,800-3,100 m), where tree diversity elsewhere is usually low and large trees are generally rare or absent, specimens from 18 families had girths >70 cm diameter and maximum heights 20-41 m. These findings indicate that simple AGB-climate-edaphic models may not be suitable for estimating carbon storage in forests where optimal climate niches exist. Our study, conducted in a very remote area, suggests that tropical montane forests may contain greater AGB than previously thought and the importance of

  18. Biomass

    Treesearch

    Bernard R. Parresol

    2001-01-01

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

  19. 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.

  20. 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

  1. The Executive Committee. AGB Effective Committee Series

    ERIC Educational Resources Information Center

    Legon, Richard D.

    2012-01-01

    This publication is part of an Association of Governing Boards of Universities and Colleges (AGB) series devoted to strengthening the role of key standing committees of governing boards. While there is no optimum committee system for institutions of higher education, certain principles, practices, and procedures prevail. The best practices…

  2. The Investment Committee. AGB Effective Committee Series

    ERIC Educational Resources Information Center

    Yoder, Jay A.

    2011-01-01

    This publication is part of an AGB series devoted to strengthening the role of key standing committees of governing boards. While there is no optimum committee system for institutions of higher education, certain principles, practices, and procedures prevail. The best practices included in this text support the objectives of board committees:…

  3. The Facilities Committee. AGB Effective Committee Series

    ERIC Educational Resources Information Center

    Kaiser, Harvey H.

    2012-01-01

    This publication is part of an Association of Governing Boards of Universities and Colleges (AGB) series devoted to strengthening the role of key standing committees of governing boards. While there is no optimum committee system for institutions of higher education, certain principles, practices, and procedures prevail. The best practices…

  4. The Audit Committee. AGB Effective Committee Series

    ERIC Educational Resources Information Center

    Staisloff, Richard L.

    2011-01-01

    This publication is part of an Association of Governing Boards of Universities and Colleges (AGB) series devoted to strengthening the role of key standing committees of governing boards. While there is no optimum committee system for institutions of higher education, certain principles, practices, and procedures prevail. The best practices…

  5. 2011 AGB Survey of Higher Education Governance

    ERIC Educational Resources Information Center

    Association of Governing Boards of Universities and Colleges, 2011

    2011-01-01

    This report, the second of AGB's studies of higher education governance, documents the extent to which college and university boards are following good-governance practices. In addition, it takes a focused look at board engagement to determine the degree to which governing boards are actively, intellectually, and strategically involved with their…

  6. The Compensation Committee. AGB Effective Committee Series

    ERIC Educational Resources Information Center

    Hyatt, Thomas K.

    2013-01-01

    This publication is part of an Association of Governing Boards of Universities and Colleges (AGB) series devoted to strengthening the role of key standing committees of governing boards. While there is no optimum committee system for institutions of higher education, certain principles, practices, and procedures prevail. The best practices…

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

    NASA Astrophysics Data System (ADS)

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

    2018-05-01

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

  8. 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.

  9. Spectropolarimetry of Post-AGB Stars

    NASA Astrophysics Data System (ADS)

    Trammell, S. R.; Goodrich, R. W.; Dinerstein, H. L.

    1992-12-01

    We have used the technique of optical spectropolarimetry to investigate post-AGB stars, objects that represent the first stages of the transition from the AGB to a planetary nebula. Several of the observed objects display unpolarized emission lines superimposed on a highly polarized continuum. The continuum polarization provides evidence for the presence of an aspherical dust envelope early in the transition process. The observed objects were chosen from several samples: high latitude supergiants with IR excesses that are thought to be post-AGB stars (e.g. Bond et. al. 1984, PASP, 96, 176), their lower latitude counterparts (e.g. Hrivnak et. al. 1989, ApJ, 346, 265), post-AGB stars shown by Johnson & Jones (1991, AJ, 101, 1735) to have high broad band polarizations, and three highly polarized extreme carbon stars investigated by Cohen & Schmidt (1982, ApJ, 259, 693). GL 1403, an extreme carbon star, shows an abrupt position angle rotation at 6000 Angstroms, implying that at blue wavelengths we see a scattered stellar continuum, while the star itself is hidden from direct view. Longward of the position angle rotation, we begin to see the star directly. Menzies & Whitelock (1988, MNRAS, 233, 697) proposed that IRAS 20056+1834, an unreddened GO supergiant with very strong Na I emission lines and a large infrared excess, is a mass-losing star obscured from direct view, in which the photospheric light is seen in reflection. Our data support this interpretation; the Na I emission is unpolarized, indicating that it is produced in the shell, while the continuum is scattered and polarized (5-7%) by the aspherical shell of material. IRAS 20000+3239 also shows unpolarized Na I D emission and is probably similar to IRAS 20056+1834. IRC +10420 exhibits unpolarized Hα emission and GL 2699, an extreme carbon star, displays both polarized and unpolarized Hα as well as unpolarized low excitation forbidden [S II] and [O I] emission lines.

  10. Luminosity Variations in Post-AGB Stars

    NASA Astrophysics Data System (ADS)

    Mesler, Robert; Henson, G.

    2007-12-01

    Although much is known about AGB stars and planetary nebulae, relatively little is known about the phase of a star's life in which it transitions between those two states. We have measured the variations in luminosity of a sample of known Post-AGB stars (as well as several candidates) relative to nearby, non-variable stars in order to compare them with theoretical models. The typical behavior of the observed variations is described and an attempt is made to discern whether any periodicity might be present. Luminosity variations were found to be on the order of a few hundredths to a few tenths of a magnitude for the stars that were surveyed, with occasional fluctuations of up to a magnitude. This agrees with current models of Post-AGB stars. Each star fell into one of three categories, which were termed groups 1, 2, and 3. Group 1 stars showed long term, non-periodic luminosity variations on the scale of weeks or longer and were most likely to display some sort of short term, coherent luminosity oscillation (each of which lasted for only a few cycles). Group 2 stars showed erratic, short-term magnitude variations occurring on scales of several days. Group 3 stars showed little or no variation in magnitude. Of the 27 Post-AGB stars that were sampled, five fell into group 1, fifteen fell into group 2, and seven fell into group 3. The luminosity variations tended to be color-independent, and occurred on timescales ranging nearly continuously from a few days to more than a year. No clear periodic behavior was found in any star in our sample. This project was funded by a partnership between the National Science Foundation (NSF AST-0552798), Research Experiences for Undergraduates (REU), and the Department of Defense (DoD) ASSURE (Awards to Stimulate and Support Undergraduate Research Experiences) programs.

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

    SciTech Connect

    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.

  12. AGB subpopulations in the nearby globular cluster NGC 6397

    NASA Astrophysics Data System (ADS)

    MacLean, B. T.; Campbell, S. W.; De Silva, G. M.; Lattanzio, J.; D'Orazi, V.; Cottrell, P. L.; Momany, Y.; Casagrande, L.

    2018-03-01

    It has been well established that Galactic Globular clusters (GCs) harbour more than one stellar population, distinguishable by the anticorrelations of light-element abundances (C-N, Na-O, and Mg-Al). These studies have been extended recently to the asymptotic giant branch (AGB). Here, we investigate the AGB of NGC 6397 for the first time. We have performed an abundance analysis of high-resolution spectra of 47 red giant branch (RGB) and eight AGB stars, deriving Fe, Na, O, Mg, and Al abundances. We find that NGC 6397 shows no evidence of a deficit in Na-rich AGB stars, as reported for some other GCs - the subpopulation ratios of the AGB and RGB in NGC 6397 are identical, within uncertainties. This agrees with expectations from stellar theory. This GC acts as a control for our earlier work on the AGB of M4 (with contrasting results), since the same tools and methods were used.

  13. 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

  14. 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.

  15. 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...

  16. The 2014 AGB Survey of Higher Education Governance

    ERIC Educational Resources Information Center

    Hodge-Clark, Kristen

    2014-01-01

    "The 2014 AGB Survey of Higher Education Governance" is the fourth in AGB's studies of college and university governance. This report, based on survey responses from 592 public and independent boards, addresses a range of important governance topics that are receiving attention from boards and the news media, including presidential…

  17. Dust in AGB Stars: Transparent or Opaque?

    NASA Astrophysics Data System (ADS)

    Bladh, S.; Höfner, S.; Aringer, B.

    2011-09-01

    The optical properties of the dust particles that drive the winds of cool giant stars affect the stellar spectra in two ways: (1) indirectly, through their influence on the dynamical structure of the atmosphere/envelope and the resulting molecular features, and (2) directly, by changes of the spectral energy distribution due to absorption and scattering on dust grains. The qualitative differences in the energy distributions of C-type and M-type AGB stars in the visual and near-infrared regions suggest that the dust particles in oxygen rich atmospheres are relatively transparent to radiation. By using detailed dynamical models of gas and radiation combined with a simple description for the dust opacity (which can be adjusted to mimic different wavelength dependences and condensation temperatures) and also by adjusting the fraction of the opacity that is treated as true absorption, we investigate which dust properties produce synthetic photometry consistent with observations. The goal of this study is to narrow down the possible dust species that may be driving the winds in M-type AGB stars.

  18. Effects of Grazing on Above- vs. Below-Ground Biomass Allocation of Alpine Grasslands on the Northern Tibetan Plateau

    PubMed Central

    Zeng, Chaoxu; Wu, Jianshuang; Zhang, Xianzhou

    2015-01-01

    Biomass allocation is an essential concept for understanding above- vs. below-ground functions and for predicting the dynamics of community structure and ecosystem service under ongoing climate change. There is rare available knowledge of grazing effects on biomass allocation in multiple zonal alpine grassland types along climatic gradients across the Northern Tibetan Plateau. We collected the peak above- and below-ground biomass (AGB and BGB) values at 106 pairs of well-matched grazed vs. fenced sites during summers of 2010–2013, of which 33 pairs were subject to meadow, 52 to steppe and 21 to desert-steppe. The aboveground net primary productivity (ANPP) was represented by the peak AGB while the belowground net primary productivity (BNPP) was estimated from ANPP, the ratio of living vs. dead BGB, and the root turnover rate. Two-ways analyses of variance (ANOVA) and paired samples comparisons with t-test were applied to examine the effects of pasture managements (PMS, i.e., grazed vs. fenced) and zonal grassland types on both ANPP and BNPP. Allometric and isometric allocation hypotheses were also tested between logarithmically transformed ANPP and BNPP using standardized major axis (SMA) analyses across grazed, fenced and overall sites. In our study, a high community-dependency was observed to support the allometric biomass allocation hypothesis, in association with decreased ANPP and a decreasing-to-increasing BNPP proportions with increasing aridity across the Northern Tibetan Plateau. Grazing vs. fencing seemed to have a trivial effect on ANPP compared to the overwhelming influence of different zonal grassland types. Vegetation links above- and below-ground ecological functions through integrated meta-population adaptive strategies to the increasing severity of habitat conditions. Therefore, more detailed studies on functional diversity are essentially to achieve conservation and sustainability goals under ongoing climatic warming and intensifying human

  19. 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...

  20. 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,...

  1. Frequency Variation of the Polarimetric Scattering Mechanisms of Forests and its Consequences on Biomass Estimation using InSAR

    NASA Astrophysics Data System (ADS)

    Thirion-Lefevre, L.; Guinvarc'h, R.

    2016-12-01

    InSAR provides forest height estimation that can be used to evaluate the aboveground biomass (AGB). This estimation depends on frequency, polarization and forest structure. If the forest is dense, high frequency gives a good estimation of the AGB whatever the polarization. For other forests, the response is a mix of scattering mechanisms with different phase centers. For instance at P-band, more information can be obtained on the structure thanks to a deeper penetration. However, double bounce mechanism can be strong with its phase center closer to the ground. As a consequence, AGB is underestimated. Quantifying double bounce mechanism can therefore help to assess this estimation. This mechanism can actually be significantly lowered using the Double Brewster Effect (DBE). The latter occurs for a dielectric dihedral and results in a reduced VV component by more than 10 dB for a large angular bandwidth, typically from 20° to 70° (HH is not affected). It consists in two successive Brewster effects, one for the ground, one for the trunk. This DBE is then dependent on the frequency and on the properties of the scatterers (moisture, ground composition, etc). It gives a new light on the interpretation of InSAR height estimation, based on a phenomenology study. We will first quantify this effect on real data at P- and L-bands. We will then present the relation between DBE and the interferometric height using a coherent scattering electromagnetic model previously validated on forests at P- and L-bands. Actually, the interferometric coherence of a forest can be modeled for each polarization by a simple summation of the coherence of the main scattering mechanisms (single and double bounce scattering), weighted by their respective magnitude. Thus, at HH, the resulting height will be determined by the relative weight of the scattering mechanisms. At VV, if DBE is strong, then the interferometric height will depend on the single scattering only.

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

    SciTech Connect

    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

  3. 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

  4. 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

  5. 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...

  6. A new tool for post-AGB SED classification

    NASA Astrophysics Data System (ADS)

    Bendjoya, P.; Suarez, O.; Galluccio, L.; Michel, O.

    We present the results of an unsupervised classification method applied on a set of 344 spectral energy distributions (SED) of post-AGB stars extracted from the Torun catalogue of Galactic post-AGB stars. This method aims to find a new unbiased method for post-AGB star classification based on the information contained in the IR region of the SED (fluxes, IR excess, colours). We used the data from IRAS and MSX satellites, and from the 2MASS survey. We applied a classification method based on the construction of the dataset of a minimal spanning tree (MST) with the Prim's algorithm. In order to build this tree, different metrics have been tested on both flux and color indices. Our method is able to classify the set of 344 post-AGB stars in 9 distinct groups according to their SEDs.

  7. 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

  8. Fluorine Abundances in AGB Carbon Stars: New Results?

    NASA Astrophysics Data System (ADS)

    Abia, C.; de Laverny, P.; Recio-Blanco, A.; Domínguez, I.; Cristallo, S.; Straniero, O.

    2009-09-01

    A recent reanalysis of the fluorine abundance in three Galactic Asymptotic Giant Branch (AGB) carbon stars (TX Psc, AQ Sgr and R Scl) by Abia et al. (2009) results in estimates of fluorine abundances systematically lower by ~0.8 dex on average, with respect to the sole previous estimates by Jorissen, Smith & Lambert (1992). The new F abundances are in better agreement with the predictions of full-network stellar models of low-mass (<3 Msolar) AGB stars.

  9. Searching for X-ray emission from AGB stars

    NASA Astrophysics Data System (ADS)

    Ramstedt, S.; Montez, R.; Kastner, J.; Vlemmings, W. H. T.

    2012-07-01

    Context. Magnetic fields have been measured around asymptotic giant branch (AGB) stars of all chemical types using maser polarization observations. If present, a large-scale magnetic field would lead to X-ray emission, which should be observable using current X-ray observatories. Aims: The aim is to search the archival data for AGB stars that are intrinsic X-ray emitters. Methods: We have searched the ROSAT, CXO, and XMM-Newton archives for serendipitous X-ray observations of a sample of ~500 AGB stars. We specifically searched for the AGB stars detected with GALEX. The data is calibrated, analyzed and the X-ray luminosities and temperatures are estimated as functions of the circumstellar absorption. Results: We identify 13 AGB stars as having either serendipitous or targeted observations in the X-ray data archives, however for a majority of the sources the detailed analysis show that the detections are questionable. Two new sources are detected by ROSAT: T Dra and R UMa. The spectral analysis suggests that the emission associated with these sources could be due to coronal activity or interaction across a binary system. Conclusions: Further observations of the detected sources are necessary to clearly determine the origin of the X-ray emission. Moreover, additional objects should be subject to targeted X-ray observations in order to achieve better constraints for the magnetic fields around AGB stars. Appendices are available in electronic form at http://www.aanda.org

  10. 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.

  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. 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...

  13. 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.

  14. The Fate of Super-AGB Stars at Low Metallicity

    NASA Astrophysics Data System (ADS)

    Decressin, T.; Siess, L.; Charbonnel, C.; Leclair, G.

    2005-11-01

    Super-AGBs are stars massive enough to ignite carbon off center and to climb the asymptotic giant branch (where they undergo thermal pulses) after core carbon exhaustion. The destiny of these stars, ONe white dwarfs or neutron stars, depends essentially on the ability of the mass loss to peel the stellar envelope before the core reaches the critical mass for electron captures to occur. Here, we focus on a super-AGB stars of 8.5 Msolar at Z=0.0001 and investigate the effects of various mass loss prescriptions. We study the interplay between mass loss and diffusive overshooting below the convective envelope. The former determines the duration of the AGB phase and the final state of the star; the latter affects the increase of the core mass and the nucleosynthesis as well.

  15. 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

  16. The FRUITY database on AGB stars: past, present and future

    NASA Astrophysics Data System (ADS)

    Cristallo, S.; Piersanti, L.; Straniero, O.

    2016-01-01

    We present and show the features of the FRUITY database, an interactive web- based interface devoted to the nucleosynthesis in AGB stars. We describe the current available set of AGB models (largely expanded with respect to the original one) with masses in the range 1.3≤M/M⊙≤3.0 and metallicities -2.15 ≤[Fe/H]≤+0.15. We illustrate the details of our s-process surface distributions and we compare our results to observations. Moreover, we introduce a new set of models where the effects of rotation are taken into account. Finally, we shortly describe next planned upgrades.

  17. Certified and uncertified logging concessions compared in Gabon: changes in stand structure, tree species, and biomass.

    PubMed

    Medjibe, V P; Putz, Francis E; Romero, Claudia

    2013-03-01

    Forest management certification is assumed to promote sustainable forest management, but there is little field-based evidence to support this claim. To help fill this gap, we compared a Forest Stewardship Council (FSC)-certified with an adjacent uncertified, conventionally logged concession (CL) in Gabon on the basis of logging damage, above-ground biomass (AGB), and tree species diversity and composition. Before logging, we marked, mapped, and measured all trees >10 cm dbh in 20 and twelve 1-ha permanent plots in the FSC and CL areas, respectively. Soil and tree damage due to felling, skidding, and road-related activities was then assessed 2-3 months after the 508 ha FSC study area and the 200 ha CL study area were selectively logged at respective intensities of 5.7 m(3)/ha (0.39 trees/ha) and 11.4 m(3)/ha (0.76 trees/ha). For each tree felled, averages of 9.1 and 20.9 other trees were damaged in the FSC and CL plots, respectively; when expressed as the impacts per timber volume extracted, the values did not differ between the two treatments. Skid trails covered 2.9 % more of the CL surface, but skid trail length per unit timber volume extracted was not greater. Logging roads were wider in the CL than FSC site and disturbed 4.7 % more of the surface. Overall, logging caused declines in AGB of 7.1 and 13.4 % at the FSC and CL sites, respectively. Changes in tree species composition were small but greater for the CL site. Based on these findings and in light of the pseudoreplicated study design with less-than perfect counterfactual, we cautiously conclude that certification yields environmental benefits even after accounting for differences in logging intensities.

  18. Assessing Performance of P-Band Backscattering Coefficients and TSAR in Hemi-Boreal Forest AGB Estimation

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    To assess performance of P-band backscattering coefficients and TSAR for hemi-boreal forest AGB estimation, airborne P-band repeat-path Pol-InSAR data collected by ESAR in Ramingstorp test site during March and May 2007 are applied. The correlation coefficient (R) between P-band backscattering coefficients and in-situ biomass reaches 0.87 for HH polarization. Meanwhile, the R between P-band backscattering power at specific height and in-situ biomass are higher in VV polarization than that in HH and HV polarization. And R between P-band backscattering power and in-situ biomass reaches 0.70 at 5m and 10m height in VV polarization.

  19. Assessing Performance of P-Band Backscattering Coefficients and TSAR in Hemi-Boreal Forest AGB Estimation

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    To assess performance of P-band backscattering coefficients and TSAR for hemi-boreal forest AGB estimation, airborne P-band repeat-path Pol-InSAR data collected by ESAR in Ramingstorp test site during March and May 2007 are applied.The correlation coefficient (R) between P-band backscattering coefficients and in-situ biomass reaches 0.87 for HH polarization. Meanwhile, the R between P-band backscattering power at specific height and in-situ biomass are higher in VV polarization than that in HH and HV polarization. And R between P-band backscattering power and in-situ biomass reaches 0.70 at 5m and 10m height in VV polarization.

  20. 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...

  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. Gas and dust from solar metallicity AGB stars

    NASA Astrophysics Data System (ADS)

    Ventura, P.; Karakas, A.; Dell'Agli, F.; García-Hernández, D. A.; Guzman-Ramirez, L.

    2018-04-01

    We study the asymptotic giant branch (AGB) evolution of stars with masses between 1 M⊙and8.5 M⊙. We focus on stars with a solar chemical composition, which allows us to interpret evolved stars in the Galaxy. We present a detailed comparison with models of the same chemistry, calculated with a different evolution code and based on a different set of physical assumptions. We find that stars of mass ≥3.5 M⊙ experience hot bottom burning at the base of the envelope. They have AGB lifetimes shorter than ˜3 × 105 yr and eject into their surroundings gas contaminated by proton-capture nucleosynthesis, at an extent sensitive to the treatment of convection. Low-mass stars with 1.5 M⊙ ≤ M ≤ 3 M⊙ become carbon stars. During the final phases, the C/O ratio grows to ˜3. We find a remarkable agreement between the two codes for the low-mass models and conclude that predictions for the physical and chemical properties of these stars, and the AGB lifetime, are not that sensitive to the modelling of the AGB phase. The dust produced is also dependent on the mass: low-mass stars produce mainly solid carbon and silicon carbide dust, whereas higher mass stars produce silicates and alumina dust. Possible future observations potentially able to add more robustness to the present results are also discussed.

  3. From Nuclei to Dust Grains: How the AGB Machinery Works

    NASA Astrophysics Data System (ADS)

    Gobrecht, D.; Cristallo, S.; Piersanti, L.

    2015-12-01

    With their circumstellar envelopes AGB stars are marvelous laboratories to test our knowledge of microphysics (opacities, equation of state), macrophysics (convection, rotation, stellar pulsations, magnetic fields) and nucleosynthesis (nuclear burnings, slow neutron capture processes, molecules and dust formation). Due to the completely different environments those processes occur, the interplay between stellar interiors (dominated by mixing events like convection and dredge-up episodes) and stellar winds (characterized by dust formation and wind acceleration) is often ignored. We intend to develop a new approach involving a transition region, taking into consideration hydrodynamic processes which may drive AGB mass-loss. Our aim is to describe the process triggering the mass-loss in AGB stars with different masses, metallicities and chemical enrichments, possibly deriving a velocity field of the outflowing matter. Moreover, we intend to construct an homogeneous theoretical database containing detailed abundances of atomic and molecular species produced by these objects. As a long term goal, we will derive dust production rates for silicates, alumina and silicon carbides, in order to explain laboratory measurements of isotopic ratios in AGB dust grains.

  4. The Governance Committee: Independent Institutions. AGB Effective Committee Series

    ERIC Educational Resources Information Center

    Wilson, E. B.; Lanier, James L.

    2013-01-01

    This publication is part of an AGB series devoted to strengthening the role of key standing committees of governing boards. While there is no optimal committee system for institutions of higher education, certain principles, practices, and procedures prevail. The best practices outlined in this publication support the objectives of board…

  5. Cool Bottom Processing on the AGB and Presolar Grain Compositions

    NASA Technical Reports Server (NTRS)

    Nollett, Kenneth M.; Busso, M.; Wasserburg, G. J.

    2002-01-01

    We describe results from a model of cool bottom processing (CBP) in AGB (asymptotic giant branch) stars. We predict O, Al, C and N isotopic compositions of circumstellar grains. Measured compositions of mainstream SiC grains and many oxide grains are consistent with CBP. Additional information is contained in the original extended abstract.

  6. 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.

  7. Rubidium and Zirconium Production in Massive AGB Stars

    SciTech Connect

    Raai, M. A. van; Lugaro, M.; Karakas, A. I.

    2008-04-06

    A recent survey of a large sample of massive Galactic asymptotic giant branch (AGB) stars shows that significant overabundances of rubidium (up to 100 times solar), but merely solar zirconium, are present in these stars. These observations can set constraints on our theoretical notion of the slow neutron capture process (the s process) in AGB stars, as well as on the rates of the neutron capture reactions involved in the production of Rb and Zr. We use the Monash nucleosynthesis code with a recently extended network to try to reproduce these observations. We present results for AGB stars of massesmore » 5, 6, and 6.5 M{center_dot} and solar metallicity. We also show results for different available choices of the neutron capture rates, as well as for the possible inclusion of a partial mixing zone (PMZ), leading to the activation of the {sup 13}C neutron source. We find increasing Rb overabundances with increasing stellar mass, as observed, but we are far from matching the highest observed Rb enhancements. Inclusion of a PMZ increases the Rb abundance, but also produces an overabundance of Zr, contrary to what is observed. Only if the third dredge up efficiency remains as high as before the onset of the superwind phase during the final few pulses of a massive AGB star, can we match the highest [Rb/Fe] ratios observed by Garcia-Hernandez et al. [l]. A better understanding of the third dredge up efficiency with decreasing envelope mass for massive AGB stars is essential for further investigation of this issue.« less

  8. On Driving AGB Mass-Loss from Core-Contraction

    NASA Astrophysics Data System (ADS)

    Lewis, B. M.

    1997-12-01

    A bulk movement of mass constitutes a momentum flow. An instructive instance occurs in the radial pulsation of stars and white dwarfs, where a symmetric contraction phase implies the existence of an inwardly- directed radial momentum flow, that is followed during the subsequent expansion by an outwardly-directed flow. The key notion here is that an inward flow is effectively transmitted through the center to become in turn an outward flow: in adiabatic processes the momentum flux is not cancelled simply because it arrives at the center. However, during the radial pulsation of AGB stars momentum is cancelled in atmospheric shock-waves and consumed in work against gravity while mass is lifted far enough away from the star for dust to form, whereon radiation pressure drives it away. These momentum-dissipative conditions at the outer boundary therefore require a stellar source of radially directed momentum if pulsation is to continue in an AGB star. A sufficient source is found in the contraction of the whole of the electron-degenerate core of an AGB star under the addition of He ashes from shell-hydrogen burning. This produces an inwardly- directed radial momentum flow that must reach the center. Lewis quantifies the resulting momentum flux (http://xxx.lanl.gov/ps/astro-ph /9707233), and finds that it easily suffices to support the mass-loss of every AGB star. But it is necessary to assume that most of the inwardly directed flux is transmitted through the center to become in turn an outwardly directed flux. The AGB core maintains its virial equilibrium by exporting its excess momentum flux to the stellar envelope. This mechanism explains the dependence of the mass-loss rate from AGB stars on core mass; its generalization to objects with angular momentum and/or strong magnetic fields suggests a novel explanation for the axial symmetry exhibited by most planetary nebulae and proto planetary nebulae. Gravitational contraction can also account for the momentum flux in the

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

    NASA Astrophysics Data System (ADS)

    Langner, Andreas; Achard, Frédéric; Grassi, Giacomo

    2014-05-01

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

  10. GRAMS: A Grid of RSG and AGB Models

    NASA Astrophysics Data System (ADS)

    Srinivasan, S.; Sargent, B. A.; Meixner, M.

    2011-09-01

    We present a grid of oxygen- and carbon-rich circumstellar dust radiative transfer models for asymptotic giant branch (AGB) and red supergiant (RSG) stars. The grid samples a large region of the relevant parameter space, and it allows for a quick calculation of bolometric fluxes and dust mass-loss rates from multi-wavelength photometry. This method of fitting observed spectral energy distributions (SEDs) is preferred over detailed radiative transfer calculations, especially for large data sets such as the SAGE (Surveying the Agents of a Galaxy's Evolution) survey of the Magellanic Clouds. The mass-loss rates calculated for SAGE data will allow us to quantify the dust returned to the interstellar medium (ISM) by the entire AGB population. The total injection rate provides an important constraint for models of galactic chemical evolution. Here, we discuss our carbon star models and compare the results to SAGE observations in the Large Magellanic Cloud (LMC).

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. 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...

  16. Search for X-ray Emission from AGB Stars in the Coronal Graveyard

    NASA Astrophysics Data System (ADS)

    Montez, Rodolfo

    2013-10-01

    Maser observations demonstrate the existence of magnetic fields in the circumstellar envelopes of AGB stars. However, thus far, only 2-3 AGB stars have exhibited evidence for coronal X-ray emission. We have demonstrated that only the sensitivity of modern X-ray telescopes can detect magnetically-induced coronal emission and have identified a sample of AGB stars which are ideal candidates to search for such emission. Specifically, we have selected a sample of AGB stars with SiO maser emission, UV emission in at least one of the GALEX bandpasses, and low mass loss rates. The four selected AGB stars provide a pilot sample that optimally probes for coronal activity beyond the giant phase and that provides valuable tests for the launching and shaping of AGB mass loss.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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...

  3. 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...

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

    EPA Science Inventory

    Because the world's forests play a major role in regulating nutrient and carbon cycles, there is much interest in estimating their biomass. Estimates of aboveground biomass based on well-established methods are relatively abundant; estimates of root biomass based on standard meth...

  5. Incorporating Canopy Cover for Airborne-Derived Assessments of Forest Biomass in the Tropical Forests of Cambodia.

    PubMed

    Singh, Minerva; Evans, Damian; Coomes, David A; Friess, Daniel A; Suy Tan, Boun; Samean Nin, Chan

    2016-01-01

    This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests.

  6. Incorporating Canopy Cover for Airborne-Derived Assessments of Forest Biomass in the Tropical Forests of Cambodia

    PubMed Central

    Singh, Minerva; Evans, Damian; Coomes, David A.; Friess, Daniel A.; Suy Tan, Boun; Samean Nin, Chan

    2016-01-01

    This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests. PMID:27176218

  7. HIRAS images of fossil dust shells around AGB stars

    NASA Technical Reports Server (NTRS)

    Waters, L. B. F. M.; Kester, Do J. M.; Bontekoe, Tj. Romke; Loup, C.

    1994-01-01

    We present high resolution HIRAS 60 and 100 micron images of AGB stars surrounded by fossil dust shells. Resolving the extended emission of the circumstellar dust allows a determination of the mass loss history of the star. We show that the geometry of the 60 micron emission surrounding HR 3126 agrees well with that of the optical reflection nebula. The emission around the carbon star U Hya is resolved into a central point source and a ring of dust, and the mass loss rate in the detached shell is 70 times higher than the current mass loss rate.

  8. Quasiperiodicity and chaos in post-AGB stars

    NASA Astrophysics Data System (ADS)

    Icke, V.

    2003-03-01

    This is a mini-presentation of three subjects, which are all related to the atmospheric motion in post-AGB stars. First, a summary of my 1990 equation of a driven stellar oscillator that exhibits chaotic solutions. Second, an advertisement for the subtle interplay of hydrodynamics, gas/dust drift, gas chemistry, dust formation, and radiation pressure, as presented in the thesis by Simis. Third, a new model equation for nonspherical stellar oscillations that resembles the FPU-equation which shows permanent non-equilibrium, with possibly intermittent solutions.

  9. Stellar Evolution with Rotation: Mixing Processes in AGB Stars

    NASA Astrophysics Data System (ADS)

    Driebe, T.; Blöcker, T.

    We included diffusive angular momentum transport and rotationally induced mixing processes in our stellar evolution code and studied the influence of rotation on the evolution of intermediate mass stars (M*=2dots6 Msolar) towards and along the asymptotic giant branch (AGB). The calculations start in the fully convective pre-main sequence phase and the initial angular momentu m was adjusted such that on the zero-age main sequence vrot=200 km/ s is achieved. The diffusion coefficients for the five rotational instabilities considered (dynamical shear, secular shear, Eddington-Sweet (ES) circulation, Solberg-Høiland-instability and Goldreich-Schubert-Fricke (GSF) instability) were adopted from Heger et al. (2000, ApJ 528, 368). Mixing efficiency and sensitivity of these processes against molecular weight gradients have been determined by calibration of the main sequence width. In this study we focus on the abundance evolution of carbon. On the one hand, the surface abundance ratios of 12C/13C a nd 12C/16O at the base of the AGB were found to be ≈ 7dots 10 and ≈ 0.1, resp., being a factor of two lower than in non-rotating models. This results from the slow but continuously operating rotationally induced mixing due to the ES-circulation and the GSF-instability during the long main sequence phase. On the other hand, 13C serves as neutron source for interior s-process nucleosynthesis in AGB stars vi a 13C(α,n)16O. Herwig et al. (1997, A&A 324, L81) found that a 13C pocket is forme d in the intershell region of 3 Msolar AGB star if diffusive overshoot is considered. Our calculations show, that mixing processes due to rotation open an alternative channel for the formation of a 13C pocket as found by Langer et al. (1999, A&A 346, L37). Again, ES-circulation and GSF-instability are the predominant rotational mixing processes.

  10. Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

    NASA Technical Reports Server (NTRS)

    Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

    2013-01-01

    Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI

  11. 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...

  12. The AGB 2017 Trustee Index. Trustees and Higher Education's Value Proposition

    ERIC Educational Resources Information Center

    Association of Governing Boards of Universities and Colleges, 2017

    2017-01-01

    "The AGB 2017 Trustee Index" is the first in a series of three annual surveys, conducted by Gallup under the direction of AGB, to assess trustee perspectives on the state of higher education. This year's report reveals a number of interesting findings: the centrality of the liberal arts, the lack of trustee involvement in influencing…

  13. AGB stars as tracers to IC 1613 evolution.

    NASA Astrophysics Data System (ADS)

    Hashemi, S. A.; Javadi, A.; van Loon, J. Th.

    We are going to apply AGB stars to find star formation history for IC 1613 galaxy; this a new and simple method that works well for nearby galaxies. IC 1613 is a Local Group dwarf irregular galaxy that is located at distance of 750 kpc, a gas rich and isolated dwarf galaxy that has a low foreground extinction. We use the long period variable stars (LPVs) that represent the very final stage of evolution of stars with low and intermediate mass at the AGB phase and are very luminous and cool so that they emit maximum brightness in near-infrared bands. Thus near-infrared photometry with using stellar evolutionary models help us to convert brightness to birth mass and age and from this drive star formation history of the galaxy. We will use the luminosity distribution of the LPVs to reconstruct the star formation history-a method we have successfully applied in other Local Group galaxies. Our analysis shows that the IC 1613 has had a nearly constant star formation rate, without any dominant star formation episode.

  14. 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

  15. 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

  16. 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...

  17. 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...

  18. AGB stars in Leo P and their use as metallicity probes

    NASA Astrophysics Data System (ADS)

    Lee, Chien-Hsiu

    2016-09-01

    Leo P is the most metal-poor yet star-forming galaxy in the local volume, and has the potential to serve as a local counterpart to interpret the properties of distant galaxies in the early universe. We present a comprehensive search of asymptotic giant branch (AGB) stars in Leo P using deep infrared imaging. AGB stars are the major dust contributors; the metal poor nature of Leo P can help to shed light on the dust formation process in very low-metallicity environments, similar to the early Universe. We select and classify oxygen-rich and carbon-rich candidate AGB stars using J - K versus K colour-magnitude diagram. To filter out contaminations from background galaxies, we exploit the high-resolution Hubble Space Telescope imaging and identify 9 oxygen-rich AGBs and 13 carbon-rich AGB stars in Leo P. We then use the ratio of carbon-rich and oxygen-rich AGB stars (C/M ratio) as an indicator of on-site metallicity and derive the global metallicity [Fe/H] = -1.8 dex for Leo P, in good agreement with previous studies using isochrone fitting. Follow-up observations of these Leo P AGB stars in the mid-infrared [e.g. Spitzer, James Webb Space Telescope (JWST)] will be invaluable to measure the dust formation rates using Spectral energy distribution (SED) fitting.

  19. Fluorine Abundances of AGB Stars in Stellar Clusters

    NASA Astrophysics Data System (ADS)

    Hren, A.; Lebzelter, T.; Aringer, B.; Hinkle, K. H.; Nowotny, W.

    2015-08-01

    We have measured the abundance of fluorine, [F/Fe], in a number of AGB stars in stellar clusters have correlated the results with their C/O ratios. This allows us to investigate the change in the fluorine abundance along the evolution on the giant branch. The target list includes primarily O-rich stars in three LMC globular clusters - NGC 1806, NGC 1846 and NGC 1978 - as well as Rup 106 and 47 Tuc in our Galaxy. The observational data were obtained with the PHOENIX spectrograph, and the COMA code was used for modelling the synthetic spectra. Within individual clusters, we find consistent [F/Fe] values at similar C/O for most of our target stars.

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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.

  5. Arabidopsis G-protein β subunit AGB1 interacts with NPH3 and is involved in phototropism.

    PubMed

    Kansup, Jeeraporn; Tsugama, Daisuke; Liu, Shenkui; Takano, Tetsuo

    2014-02-28

    Heterotrimeric G proteins (Gα, Gβ and Gγ) have pleiotropic roles in plants, but molecular mechanisms underlying them remain to be elucidated. Here we show that Arabidopsis Gβ (AGB1) interacts with NPH3, a regulator of phototropism. Yeast two-hybrid assays, in vitro pull-down assays and bimolecular fluorescence complementation assays showed that AGB1 and NPH3 physically interact. NPH3-null mutation (nph3) is known to completely abolish hypocotyl phototropism. Loss-of-function mutants of AGB1 (agb1-1 and agb1-2) showed decreased hypocotyl phototropism, and agb1/nph3 double mutants showed no hypocotyl phototropism. These results suggest that AGB1 is involved in the NPH3-mediated regulation of phototropism. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. 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

  7. AGB Sodium Abundances in the Globular Cluster 47 Tucanae (NGC 104)

    NASA Astrophysics Data System (ADS)

    Johnson, Christian I.; McDonald, Iain; Pilachowski, Catherine A.; Mateo, Mario; Bailey, John I., III; Cordero, Maria J.; Zijlstra, Albert A.; Crane, Jeffrey D.; Olszewski, Edward; Shectman, Stephen A.; Thompson, Ian

    2015-02-01

    A recent analysis comparing the [Na/Fe] distributions of red giant branch (RGB) and asymptotic giant branch (AGB) stars in the Galactic globular cluster NGC 6752 found that the ratio of Na-poor to Na-rich stars changes from 30:70 on the RGB to 100:0 on the AGB. The surprising paucity of Na-rich stars on the AGB in NGC 6752 warrants additional investigations to determine if the failure of a significant fraction of stars to ascend the AGB is an attribute common to all globular clusters. Therefore, we present radial velocities, [Fe/H], and [Na/Fe] abundances for 35 AGB stars in the Galactic globular cluster 47 Tucanae (47 Tuc; NGC 104), and compare the AGB [Na/Fe] distribution with a similar RGB sample published previously. The abundances and velocities were derived from high-resolution spectra obtained with the Michigan/Magellan Fiber System and MSpec spectrograph on the Magellan-Clay 6.5 m telescope. We find the average heliocentric radial velocity and [Fe/H] values to be < R{{V}helio.}> = -18.56 km s-1 (σ = 10.21 km s-1) and < [Fe/H]> = -0.68 (σ = 0.08), respectively, in agreement with previous literature estimates. The average [Na/Fe] abundance is 0.12 dex lower in the 47 Tuc AGB sample compared to the RGB sample, and the ratio of Na-poor to Na-rich stars is 63:37 on the AGB and 45:55 on the RGB. However, in contrast to NGC 6752, the two 47 Tuc populations have nearly identical [Na/Fe] dispersion and interquartile range values. The data presented here suggest that only a small fraction (≲20%) of Na-rich stars in 47 Tuc may fail to ascend the AGB, which is a similar result to that observed in M13. Regardless of the cause for the lower average [Na/Fe] abundance in AGB stars, we find that Na-poor stars and at least some Na-rich stars in 47 Tuc evolve through the early AGB phase. The contrasting behavior of Na-rich stars in 47 Tuc and NGC 6752 suggests that the RGB [Na/Fe] abundance alone is insufficient for predicting if a star will ascend the AGB.

  8. AGB sodium abundances in the globular cluster 47 Tucanae (NGC 104)

    SciTech Connect

    Johnson, Christian I.; McDonald, Iain; Zijlstra, Albert A., E-mail: cjohnson@cfa.harvard.edu, E-mail: iain.mcdonald-2@manchester.ac.uk, E-mail: albert.zijlstra@manchester.ac.uk

    A recent analysis comparing the [Na/Fe] distributions of red giant branch (RGB) and asymptotic giant branch (AGB) stars in the Galactic globular cluster NGC 6752 found that the ratio of Na-poor to Na-rich stars changes from 30:70 on the RGB to 100:0 on the AGB. The surprising paucity of Na-rich stars on the AGB in NGC 6752 warrants additional investigations to determine if the failure of a significant fraction of stars to ascend the AGB is an attribute common to all globular clusters. Therefore, we present radial velocities, [Fe/H], and [Na/Fe] abundances for 35 AGB stars in the Galactic globularmore » cluster 47 Tucanae (47 Tuc; NGC 104), and compare the AGB [Na/Fe] distribution with a similar RGB sample published previously. The abundances and velocities were derived from high-resolution spectra obtained with the Michigan/Magellan Fiber System and MSpec spectrograph on the Magellan–Clay 6.5 m telescope. We find the average heliocentric radial velocity and [Fe/H] values to be 〈RV{sub helio.}〉 = −18.56 km s{sup −1} (σ = 10.21 km s{sup −1}) and 〈[Fe/H]〉 = −0.68 (σ = 0.08), respectively, in agreement with previous literature estimates. The average [Na/Fe] abundance is 0.12 dex lower in the 47 Tuc AGB sample compared to the RGB sample, and the ratio of Na-poor to Na-rich stars is 63:37 on the AGB and 45:55 on the RGB. However, in contrast to NGC 6752, the two 47 Tuc populations have nearly identical [Na/Fe] dispersion and interquartile range values. The data presented here suggest that only a small fraction (≲20%) of Na-rich stars in 47 Tuc may fail to ascend the AGB, which is a similar result to that observed in M13. Regardless of the cause for the lower average [Na/Fe] abundance in AGB stars, we find that Na-poor stars and at least some Na-rich stars in 47 Tuc evolve through the early AGB phase. The contrasting behavior of Na-rich stars in 47 Tuc and NGC 6752 suggests that the RGB [Na/Fe] abundance alone is insufficient for predicting if a

  9. [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.

  10. 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

  11. Soil Respiration in Tibetan Alpine Grasslands: Belowground Biomass and Soil Moisture, but Not Soil Temperature, Best Explain the Large-Scale Patterns

    PubMed Central

    Geng, Yan; Wang, Yonghui; Yang, Kuo; Wang, Shaopeng; Zeng, Hui; Baumann, Frank; Kuehn, Peter; Scholten, Thomas; He, Jin-Sheng

    2012-01-01

    The Tibetan Plateau is an essential area to study the potential feedback effects of soils to climate change due to the rapid rise in its air temperature in the past several decades and the large amounts of soil organic carbon (SOC) stocks, particularly in the permafrost. Yet it is one of the most under-investigated regions in soil respiration (Rs) studies. Here, Rs rates were measured at 42 sites in alpine grasslands (including alpine steppes and meadows) along a transect across the Tibetan Plateau during the peak growing season of 2006 and 2007 in order to test whether: (1) belowground biomass (BGB) is most closely related to spatial variation in Rs due to high root biomass density, and (2) soil temperature significantly influences spatial pattern of Rs owing to metabolic limitation from the low temperature in cold, high-altitude ecosystems. The average daily mean Rs of the alpine grasslands at peak growing season was 3.92 µmol CO2 m−2 s−1, ranging from 0.39 to 12.88 µmol CO2 m−2 s−1, with average daily mean Rs of 2.01 and 5.49 µmol CO2 m−2 s−1 for steppes and meadows, respectively. By regression tree analysis, BGB, aboveground biomass (AGB), SOC, soil moisture (SM), and vegetation type were selected out of 15 variables examined, as the factors influencing large-scale variation in Rs. With a structural equation modelling approach, we found only BGB and SM had direct effects on Rs, while other factors indirectly affecting Rs through BGB or SM. Most (80%) of the variation in Rs could be attributed to the difference in BGB among sites. BGB and SM together accounted for the majority (82%) of spatial patterns of Rs. Our results only support the first hypothesis, suggesting that models incorporating BGB and SM can improve Rs estimation at regional scale. PMID:22509373

  12. 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...

  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. 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...

  15. 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 (...

  16. 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....

  17. 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...

  18. 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

  19. Biomass of open-grown Virginia pine

    SciTech Connect

    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.

  20. 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

  1. a Study of the AGB in Local Group Bulge Populations

    NASA Astrophysics Data System (ADS)

    Rich, R.

    1994-01-01

    We propose to survey the bolometric luminosities, colors, and space distribution of the most luminous asymptotic giant branch (AGB) stars in the bulges of M31, M32, and M33. We seek to discover whether the bulges of these galaxies are relatively young, of order 10 Gyr rather than 15 Gyr. We will use WFPC2 and the R, I, and F1042M (1 micron) filters. Knowing that F1042M falls on the first continuum point of M giants, we have shown that we can use 1.04 micron fluxes to reliably calculate bolometric magnitudes for these very red stars. Color information from R and I will permit (1) comparison with Galactic bulge M giants, (2) an estimate of the spread of abundance and (3) increase the accuracy of the bolometric magnitudes. Frames with the damaged HST show signs of resolution to within 3" of the M31 nucleus; Red images with the aberrated HST show a red star cluster associated with the nucleus. Ground-based studies of M32 find an intermediate-age population from spectroscopy and infrared photometry. The repaired HST should resolve stars close to the nuclei of these galaxies. We will measure bolometric luminosity functions to determine if the populations are intermediate age, and attempt to measure the abundance range for stars near the nuclei of these galaxies. If metals have been lost due to winds, theory predicts that we should see a substantial spread of abundances even near the nucleus.

  2. Molecular processes from the AGB to the PN stage

    NASA Astrophysics Data System (ADS)

    García-Hernández, D. Anibal

    2012-08-01

    Many complex organic molecules and inorganic solid-state compounds have been observed in the circumstellar shell of stars (both C-rich and O-rich) in the transition phase between Asymptotic Giant Branch (AGB) stars and Planetary Nebulae (PNe). This short (~102-104 years) phase of stellar evolution represents a wonderful laboratory for astrochemistry and provides severe constraints on any model of gas-phase and solid-state chemistry. One of the major challenges of present day astrophysics and astrochemistry is to understand the formation pathways of these complex organic molecules and inorganic solid-state compounds (e.g., polycyclic aromatic hydrocarbons, fullerenes, and graphene in the case of a C-rich chemistry and oxides and crystalline silicates in O-rich environments) in space. In this review, I present an observational review of the molecular processes in the late stages of stellar evolution with a special emphasis on the first detections of fullerenes and graphene in PNe.

  3. Observational constraints for C-rich AGB stars

    NASA Astrophysics Data System (ADS)

    Rau, G.; Hron, J.; Paladini, C.; Aringer, B.; Marigo, P.; Eriksson, K.

    We modeled the atmospheres of six carbon-rich Asymptotic Giant Branch stars (R Lep, R Vol, Y Pav, AQ Sgr, U Hya, and X TrA) using VLTI/MIDI interferometric observations, together with spectro-photometric data, we compared them with self-consistent, dynamic model atmospheres. The results show that the models can reproduce the Spectral Energy Distribution (SED) data well at wavelengths longer than 1 mu m, and the interferometric observations between 8 mu m and 10 mu m. We found differences at wavelengths shorter than 1 mu m in the SED, and longer than 10 mu m in the visibilities. The discrepancies observed can be explained in terms of a combination of data- and model-related reasons. We derived some stellar parameters, and our findings agree well with literature values within the uncertainties. Also, when comparing the location of the stars in the H-R diagram, with evolutionary tracks, the results show that the main derived properties (L, Teff, C/O ratios and stellar masses) from the model fitting are in good agreement with TP-AGB evolutionary calculations.

  4. 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...

  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 ersist longer after harvest than aboveground biomass and fine oots. The main objective was to assess the carbon accumulation in coarse...

  6. 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...

  7. 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

  8. 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

  9. High rotational CO lines in post-AGB stars and PNe

    NASA Technical Reports Server (NTRS)

    Justtanont, K.; Tielens, Alexander G. G. M.; Skinner, C. J.; Haas, Michael R.

    1995-01-01

    A significant fraction of a star's initial mass is lost while it is on the Asymptotic Giant Branch (AGB). Mass loss rates range from 10(exp -7) solar mass/yr for early AGB stars to a few 10(exp -4) solar mass/yr for stars at the tip of the AGB. Dust grains condense from the outflow as the gas expands and form a dust shell around the central star. A superwind (approximately 10(exp -4) to 10(exp -3) solar mass/yr) is thought to terminate the AGB phase. In the post-AGB phase, the star evolves to a higher effective temperature, the mass loss decreases (approximately 10(exp -8) solar mass/yr), but the wind velocity increases (approximately 1000 km/s). During this evolution, dust and gas are exposed to an increasingly harsher radiation field and when T(sub eff) reaches about 30,000 K, the nebula is ionized and becomes a planetary nebula (PN). Photons from the central star can create a photodissociation region (PDR) in the expanding superwind. Gas can be heated through the photoelectric effect working on small grains and polycyclic aromatic hydrocarbons (PAH's). This gas can cool via the atomic fine structure lines of O I (63 microns and 145 microns) and C II (158 microns), as well as the rotational lines of CO. In the post-AGB phase, the fast wind from the central star will interact with the material ejected during the AGB phase. The shock caused by this interaction will dissociate and heat the gas. This warm gas will cool through atomic fine structure lines of O I and the rotational lines of (newly formed) CO.

  10. The nebula around the post-AGB star 89 Herculis

    NASA Astrophysics Data System (ADS)

    Bujarrabal, V.; van Winckel, H.; Neri, R.; Alcolea, J.; Castro-Carrizo, A.; Deroo, P.

    2007-06-01

    Aims:We aim to study the structure of the nebula around the post-AGB, binary star 89 Her. The presence of a rotating disk around this star had been proposed but not been yet confirmed by observations. Methods: We present high-resolution PdBI maps of CO J=2-1 and 1-0. Properties of the nebula are directly derived from the data and model fitting. We also present N-band interferometric data on the extent of the hot dust emission, obtained with the VLTI. Results: Two nebular components are found: (a) an extended hour-glass-like structure, with expansion velocities of 7 km s-1 and a total mass 3× 10-3 M{⊙}, and (b) an unresolved very compact component, smaller than 0.4 arcsec and with a low total velocity dispersion of 5 km s-1. We cannot determine the velocity field in the compact component, but we argue that it can hardly be in expansion, since this would require too recent and too sudden an ejection of mass. On the other hand, assuming that this component is a Keplerian disk, we derive disk properties that are compatible with expectations for such a structure; in particular, the size of the rotating gas disk should be very similar to the extent of the hot dust component from our VLTI data. Assuming that the equator of the extended nebula coincides with the binary orbital plane, we provide new results on the companion star mass and orbit. Based on observations carried out with the IRAM Plateau de Bure Interferometer, as well as on observations of the Belgian Guaranteed time on VISA (ESO). IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain).

  11. 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.

  12. 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

  13. Abundance Patterns in S-type AGB Stars: Setting Constraints on Nucleosynthesis and Stellar Evolution Models

    NASA Astrophysics Data System (ADS)

    Neyskens, P.; van Eck, S.; Plez, B.; Goriely, S.; Siess, L.; Jorissen, A.

    2011-09-01

    During evolution on the AGB, stars of type S are the first to experience s-process nucleosynthesis and the third dredge-up, and therefore to exhibit s-process signatures in their atmospheres. Their high mass-loss rates (10-7 to 10-6 M⊙/year) make them major contributors to the AGB nucleosynthesis yields at solar metallicity. Precise abundance determinations in S stars are of the utmost importance for constraining e.g. the third dredge-up luminosity and efficiency (which has been only crudely parameterized in current nucleosynthetic models so far). Here, dedicated S-star model atmospheres are used to determine precise abundances of key s-process elements, and to set constraints on nucleosynthesis and stellar evolution models. Special interest is paid to technetium, an element with no stable isotopes. Its detection is considered the best signature that the star effectively populates the thermally-pulsing AGB phase of evolution. The derived Tc/Zr abundances are compared, as a function of the derived [Zr/Fe] overabundances, with AGB stellar model predictions. The [Zr/Fe] overabundances are in good agreement with model predictions, while the Tc/Zr abundances are slightly overpredicted. This discrepancy can help to set better constraints on nucleosynthesis and stellar evolution models of AGB stars.

  14. FUV Emission from AGB Stars: Modeling Accretion Activity Associated with a Binary Companion

    NASA Technical Reports Server (NTRS)

    Stevens, Alyx Catherine; Sahai, Raghvendra

    2012-01-01

    It is widely believed that the late stages of evolution for Asymptotic Giant Branch (AGB) stars are influenced by the presence of binary companions. Unfortunately, there is a lack of direct observational evidence of binarity. However, more recently, strong indirect evidence comes from the discovery of UV emission in a subsample of these objects (fuvAGB stars). AGB stars are comparatively cool objects (< or =3000 K), thus their fluxes falls off drastically for wavelengths 3000 Angstroms and shorter. Therefore, ultraviolet observations offer an important, new technique for detecting the binary companions and/or associated accretion activity. We develop new models of UV emission from fuvAGB stars constrained by GALEX photometry and spectroscopy of these objects. We compare the GALEX UV grism spectra of the AGB M7 star EY Hya to predictions using the spectral synthesis code Cloudy, specifically investigating the ultraviolet wavelength range (1344-2831 Angstroms). We investigate models composed of contributions from a photoionized "hot spot" due to accretion activity around the companion, and "chromospheric" emission from collisionally ionized plasma, to fit the UV observations.

  15. Influence of the outer boundary condition on models of AGB stars

    NASA Astrophysics Data System (ADS)

    Wagstaff, G.; Weiss, A.

    2018-07-01

    Current implementations of the stellar atmosphere typically derive boundary conditions for the interior model from either grey plane-parallel atmospheres or scaled solar atmospheres, neither of which can be considered to have appropriate underlying assumptions for the Thermally Pulsing Asymptotic Giant Branch (TP-AGB). This paper discusses the treatment and influence of the outer boundary condition within stellar evolution codes, and the resulting effects on the AGB evolution. The complex interaction of processes, such as the third dredge up and mass-loss, governing the TP-AGB can be affected by varying the treatment of this boundary condition. Presented here are the results from altering the geometry, opacities, and the implementation of a grid of MARCS/COMARCS model atmospheres in order to improve this treatment. Although there are changes in the TP-AGB evolution, observable quantities, such as the final core mass, are not significantly altered as a result of the change of atmospheric treatment. During the course of the investigation, a previously unseen phenomenon in the AGB models was observed and further investigated. This is believed to be physical, although arising from specific conditions which make its presence unlikely. If it were present in stars, this phenomenon would increase the carbon-star lifetime above 10 Myr and increase the final core mass by ˜0.1 M⊙ in the narrow initial-mass range where it was observed (˜2-2.3 M⊙).

  16. Influence of the Outer Boundary Condition on models of AGB stars

    NASA Astrophysics Data System (ADS)

    Wagstaff, G.; Weiss, A.

    2018-04-01

    Current implementations of the stellar atmosphere typically derive boundary conditions for the interior model from either grey plane-parallel atmospheres or scaled solar atmospheres, neither of which can be considered to have appropriate underlying assumptions for the Thermally Pulsing Asymptotic Giant Branch (TP-AGB). This paper discusses the treatment and influence of the outer boundary condition within stellar evolution codes, and the resulting effects on the AGB evolution. The complex interaction of processes, such as the third dredge up and mass loss, governing the TP-AGB can be affected by varying the treatment of this boundary condition. Presented here are the results from altering the geometry, opacities and the implementation of a grid of MARCS/COMARCS model atmospheres in order to improve this treatment. Although there are changes in the TP-AGB evolution, observable quantities, such as the final core mass, are not significantly altered as a result of the change of atmospheric treatment. During the course of the investigation, a previously unseen phenomena in the AGB models was observed and further investigated. This is believed to be physical, although arising from specific conditions which make its presence unlikely. If it were present in stars, this phenomenon would increase the carbon-star lifetime above 10Myr and increase the final core mass by ˜0.1M⊙ in the narrow initial-mass range where it was observed (˜2 - 2.3M⊙).

  17. VizieR Online Data Catalog: AGB stars with GALEX observations (Montez+, 2017)

    NASA Astrophysics Data System (ADS)

    Montez, R.; Ramstedt, S.; Kastner, J. H.; Vlemmings, W.; Sanchez, E.

    2018-01-01

    Our sample of AGB stars is derived from numerous AGB samples found in the literature and was originally compiled by Ramstedt+ (2012A&A...543A.147R) to search for X-ray detections associated with AGB stars. The GALEX mission performed a two-band survey of the UV sky. Using a dichromatic beam splitter, GALEX simultaneously observed far-UV (FUV; λeff~1528Å; 1344-1786Å) and near-UV (NUV; λeff~2310Å; 1771-2831Å) in surveys with different depths. The spatial resolution is 4.3" in FUV and 5.3" in NUV. As described in further detail in Morrissey+ (2007ApJS..173..682M), spectroscopic observations place a grism into the converging beam of the telescope to simultaneously disperse all sources onto the detector plane. According to Morrissey+ (2007), the usable ranges of the grism spectra are 1300-1820Å and 1820-3000Å in the FUV and NUV, with average resolutions of 8Å and 20Å, respectively. To supplement our study of the GALEX observations of AGB stars, we collected photometric data from across the electromagnetic spectrum for all the AGB stars considered using SIMBAD and VizieR tools. We aslo collected AAVSO light curves that span the GALEX mission lifetime (2003 May 28 to 2013 June 28) from the AAVSO International Database. (3 data files).

  18. Evaluation of vegetation indices for rangeland biomass estimation in the Kimberley area of Western Australia

    NASA Astrophysics Data System (ADS)

    Mundava, C.; Helmholz, P.; Schut, A. G. T.; Corner, R.; McAtee, B.; Lamb, D. W.

    2014-09-01

    The objective of this paper is to test the relationships between Above Ground Biomass (AGB) and remotely sensed vegetation indices for AGB assessments in the Kimberley area in Western Australia. For 19 different sites, vegetation indices were derived from eight Landsat ETM+ scenes over a period of two years (2011-2013). The sites were divided into three groups (Open plains, Bunch grasses and Spinifex) based on similarities in dominant vegetation types. Dry and green biomass fractions were measured at these sites. Single and multiple regression relationships between vegetation indices and green and total AGB were calibrated and validated using a "leave site out" cross validation. Four tests were compared: (1) relationships between AGB and vegetation indices combining all sites; (2) separate relationships per site group; (3) multiple regressions including selected vegetation indices per site group; and (4) as in 3 but including rainfall and elevation data. Results indicate that relationships based on single vegetation indices are moderately accurate for green biomass in wide open plains covered with annual grasses. The cross-validation results for green AGB improved for a combination of indices for the Open plains and Bunch grasses sites, but not for Spinifex sites. When rainfall and elevation data are included, cross validation improved slightly with a Q2 of 0.49-0.72 for Open plains and Bunch grasses sites respectively. Cross validation results for total AGB were moderately accurate (Q2 of 0.41) for Open plains but weak or absent for other site groups despite good calibration results, indicating strong influence of site-specific factors.

  19. 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.

  20. First evidence of multiple populations along the AGB from Strömgren photometry

    NASA Astrophysics Data System (ADS)

    Gruyters, Pieter; Casagrande, Luca; Milone, Antonino P.; Hodgkin, Simon T.; Serenelli, Aldo; Feltzing, Sofia

    2017-07-01

    Spectroscopic studies have demonstrated that nearly all Galactic globular clusters (GCs) harbour multiple stellar populations with different chemical compositions. Moreover, colour-magnitude diagrams based exclusively on Strömgrem photometry have allowed us to identify and characterise multiple populations along the RGB of a large number of clusters. In this paper we show for the first time that Strömgren photometry is also very efficient at identifying multiple populations along the AGB, and demonstrate that the AGB of M 3, M 92, NGC 362, NGC 1851, and NGC 6752 are not consistent with a single stellar population. We also provide a catalogue of RGB and AGB stars photometrically identified in these clusters for further spectroscopic follow-up studies. We combined photometry and elemental abundances from the literature for RGB and AGB stars in NGC 6752 where the presence of multiple populations along the AGB has been widely debated. We find that, while the MS, SGB, and RGB host three stellar populations with different helium and light element abundances, only two populations of AGB stars are present in the cluster. These results are consistent with standard evolutionary theory. Based on observations made with the Isaac Newton Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias.Full Tables B.1 and B.2 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/603/A37

  1. A NEW GENERATION OF PARSEC-COLIBRI STELLAR ISOCHRONES INCLUDING THE TP-AGB PHASE

    SciTech Connect

    Marigo, Paola; Aringer, Bernhard; Chen, Yang

    2017-01-20

    We introduce a new generation of PARSEC–COLIBRI stellar isochrones that includes a detailed treatment of the thermally pulsing asymptotic giant branch (TP-AGB) phase, covering a wide range of initial metallicities (0.0001 < Z {sub i} < 0.06). Compared to previous releases, the main novelties and improvements are use of new TP-AGB tracks and related atmosphere models and spectra for M and C-type stars; inclusion of the surface H+He+CNO abundances in the isochrone tables, accounting for the effects of diffusion, dredge-up episodes and hot-bottom burning; inclusion of complete thermal pulse cycles, with a complete description of the in-cycle changes in themore » stellar parameters; new pulsation models to describe the long-period variability in the fundamental and first-overtone modes; and new dust models that follow the growth of the grains during the AGB evolution, in combination with radiative transfer calculations for the reprocessing of the photospheric emission. Overall, these improvements are expected to lead to a more consistent and detailed description of properties of TP-AGB stars expected in resolved stellar populations, especially in regard to their mean photometric properties from optical to mid-infrared wavelengths. We illustrate the expected numbers of TP-AGB stars of different types in stellar populations covering a wide range of ages and initial metallicities, providing further details on the “C-star island” that appears at intermediate values of age and metallicity, and about the AGB-boosting effect that occurs at ages close to 1.6-Gyr for populations of all metallicities. The isochrones are available through a new dedicated web server.« less

  2. On the missing second generation AGB stars in NGC 6752

    NASA Astrophysics Data System (ADS)

    Cassisi, Santi; Salaris, Maurizio; Pietrinferni, Adriano; Vink, Jorick S.; Monelli, Matteo

    2014-11-01

    In recent years the view of Galactic globular clusters as simple stellar populations has changed dramatically, it is now thought that basically all globular clusters host multiple stellar populations, each with its own chemical abundance pattern and colour-magnitude diagram sequence. Recent spectroscopic observations of asymptotic giant branch stars in the globular cluster NGC 6752 have disclosed a low [Na/Fe] abundance for the whole sample, suggesting that they are all first generation stars, and that all second generation stars fail to reach the AGB in this cluster. A scenario proposed to explain these observations invokes strong mass loss in second generation horizontal branch stars - all located at the hot side of the blue and extended horizontal branch of this cluster - possibly induced by the metal enhancement associated to radiative levitation. This enhanced mass loss would prevent second generation stars from reaching the asymptotic giant branch phase, thus explaining at the same time the low value of the ratio between horizontal branch and asymptotic giant branch stars (the R2 parameter) observed in NGC 6752. We have critically discussed this mass-loss scenario, finding that the required mass-loss rates are of the order of 10-9 M⊙ yr-1, significantly higher than current theoretical and empirical constraints. By making use of synthetic horizontal branch simulations, we demonstrate that our modelling correctly predicts the R2 parameter for NGC 6752, without the need to invoke very efficient mass loss during the core He-burning stage. As a test of our stellar models we show that we can reproduce the observed value of R2 for both M 3, a cluster of approximately the same metallicity and with a redder horizontal branch morphology, and M 13, a cluster with a horizontal branch very similar to NGC 6752. However, our simulations for the NGC 6752 horizontal branch predict however the presence of a significant fraction of second generation stars (about 50%) along

  3. VizieR Online Data Catalog: Torun catalog of post-AGB and related objects (Szczerba+, 2007)

    NASA Astrophysics Data System (ADS)

    Szczerba, R.; Siodmiak, N.; Stasinska, G.; Borkowski, J.

    2007-09-01

    With the ongoing AKARI infrared sky survey, of much greater sensitivity than IRAS, a wealth of post-AGB objects may be discovered. It is thus time to organize our present knowledge of known post-AGB stars in the galaxy with a view to using it to search for new post-AGB objects among AKARI sources. We searched the literature available on the NASA Astrophysics Data System up to 1 October 2006, and defined criteria for classifying sources into three categories: very likely, possible and disqualified post-AGB objects. The category of very likely post-AGB objects is made up of several classes. We have created an evolutionary, on-line catalogue of Galactic post-AGB objects, to be referred to as the Torun catalogue of Galactic post-AGB and related objects. The present version of the catalogue contains 326 very likely, 107 possible and 64 disqualified objects. For the very likely post-AGB objects, the catalogue gives the available optical and infrared photometry, infrared spectroscopy and spectral types, and links to finding charts and bibliography. (3 data files).

  4. Probing the collimation of pristine post-AGB jets with STIS

    NASA Astrophysics Data System (ADS)

    Sanchez Contreras, Carmen

    2009-07-01

    The shaping of planetary and protoplanetary nebulae {PNe and PPNe} is probably the most exciting yet least understood problem in the late evolution of 1-8 solar mass stars. An increasing number of astronomers believe that fast jet-like winds ejected in the PPN phase are responsible for carving out the diverse shapes in the dense envelopes of the Asymptotic Giant Branch {AGB} stars. To date, the properties of these post-AGB jets have not been characterized and, indeed, their launching/collimation mechanism is still subject to controversial debate. This is due to the lack of the direct observations probing the spatio-kinematic structure of post-AGB winds in the stellar vicinity { 10e16cm}, which is only possible with HST+STIS. Recently, STIS observations have allowed us for the first time the DIRECT study of the structure and kinematics of the elusive post-AGB winds in one PPN, He3-1475 {Sanchez Contreras & Sahai 2001}. Those winds have been discovered through H-alpha blue-shifted absorption features in the inner 0.3"-0.7" of the nebula. These STIS observations have revealed an ultra-fast collimated outflow relatively unaffected by the interaction with the AGB wind that is totally hidden in ground-based spectroscopic observations and HST images. The discovery of the pristine ultra-fast { 2300km/s} jet in He3-1475 is the first observational confirmation of the presence of collimated outflows as close as 10e16cm from the central star. Most importantly, the spatio-kinematic structure of the ultra-fast jet clearly rules out hydrodynamical collimation alone and favors magnetic wind collimation. Therefore, STIS observations provide a unique method of probing the structure, kinematics, and collimation mechanism of the elusive post-AGB winds. We now propose similar observations for a sample of bipolar PPNe with ongoing post-AGB ejections in order to investigate the frequency of jets like those in He3-1475 in other PPNe and elucidate their nature and collimation mechanism

  5. A mechanism to account for well known peculiarities of low mass AGB star nucleosynthesis

    NASA Astrophysics Data System (ADS)

    Palmerini, Sara; Trippella, Oscar; Vescovi, Diego; Busso, Maurizio

    2018-01-01

    We present here the application of a model for a mass circulation mechanism induced by the stellar magnetic field to study peculiar aspects of AGB star nucleosynthesis. The mixing scheme is based on a previously suggested magnetic-buoyancy process [1, 2] and here shown to account adequately for the formation of the 13C neutron source for s-processes. In particular our analysis results are focused on addressing the constrains to AGB nucleosynthesis coming from the isotopic composition of presolar grains recovered in meteorites. It turns out that n-captures driven by the magnetically-induced mixing can account for the isotopic abundance ratios of s-elements recorded.

  6. 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

  7. Preliminary study on aerobic granular biomass formation with aerobic continuous flow reactor

    NASA Astrophysics Data System (ADS)

    Yulianto, Andik; Soewondo, Prayatni; Handajani, Marissa; Ariesyady, Herto Dwi

    2017-03-01

    A paradigm shift in waste processing is done to obtain additional benefits from treated wastewater. By using the appropriate processing, wastewater can be turned into a resource. The use of aerobic granular biomass (AGB) can be used for such purposes, particularly for the processing of nutrients in wastewater. During this time, the use of AGB for processing nutrients more reactors based on a Sequencing Batch Reactor (SBR). Studies on the use of SBR Reactor for AGB demonstrate satisfactory performance in both formation and use. SBR reactor with AGB also has been applied on a full scale. However, the use use of SBR reactor still posses some problems, such as the need for additional buffer tank and the change of operation mode from conventional activated sludge to SBR. This gives room for further reactor research with the use of a different type, one of which is a continuous reactor. The purpose of this study is to compare AGB formation using continuous reactor and SBR with same operation parameter. Operation parameter are Organic Loading Rate (OLR) set to 2,5 Kg COD/m3.day with acetate as substrate, aeration rate 3 L/min, and microorganism from Hospital WWTP as microbial source. SBR use two column reactor with volumes 2 m3, and continuous reactor uses continuous airlift reactor, with two compartments and working volume of 5 L. Results from preliminary research shows that although the optimum results are not yet obtained, AGB can be formed on the continuous reactor. When compared with AGB generated by SBR, then the characteristics of granular diameter showed similarities, while the sedimentation rate and Sludge Volume Index (SVI) characteristics showed lower yields.

  8. 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.

  9. Modelling a Set of Carbon-Rich AGB Stars at High-Angular Resolution

    NASA Astrophysics Data System (ADS)

    Rau, Gioia; Hron, Josef; Paladini, Claudia; Aringer, Bernard; Eriksson, Kjell; Marigo, Paola; Nowotny, Walter; Grellmann, Rebekka

    2016-07-01

    We compared spectro-photometric and interferometric observations of six carbon-rich AGB stars with a grid of self-consistentmodel atmospheres. The targets are: R Lep, R Vol, Y Pav, AQ Sgr, U Hya and X TrA. Please refer to the publication Rau et al. 2016(subm.) for further details on those findings.

  10. Taking the Pulse of Campus Climate: Key Findings of the AGB Survey on Diversity and Inclusion

    ERIC Educational Resources Information Center

    Association of Governing Boards of Universities and Colleges, 2017

    2017-01-01

    Campus climate issues continue to pervade many institutions, with related news stories commanding headlines across the country. Through oversight and leadership, college and university governing boards play an important role in helping to create inclusive campuses. AGB conducted a survey of nearly 1,000 board members to take the pulse of campus…

  11. The LF of TP-AGB stars in the LMC/SMC

    NASA Technical Reports Server (NTRS)

    Bruzual, Gustavo; Charlot, Stephane; GonzalezLopezlira, Rosa; Srinivasan, Sundar; Boyer, Martha L.

    2013-01-01

    We show that Monte Carlo simulations of the TP-AGB stellar population in the LMC and SMC galaxies using the CB. models produce LF and color distributions that are in closer agreement with observations than those obtained with the BC03 and CB07 models. This is a progress report of work that will be published elsewhere.

  12. AGB Statement on Board Responsibility for the Oversight of Educational Quality

    ERIC Educational Resources Information Center

    Association of Governing Boards of Universities and Colleges, 2011

    2011-01-01

    This "Statement on Board Responsibility for the Oversight of Educational Quality," approved by the Board of Directors of the Association of Governing Boards (AGB) in March 2011, urges institutional administrators and governing boards to engage fully in this area of board responsibility. The seven principles in this statement offer suggestions to…

  13. Sage Studies Of The Mass Return From AGB And RSG Stars In The Large Magellanic Cloud

    NASA Astrophysics Data System (ADS)

    Sargent, Benjamin A.; Srinivasan, S.; Meixner, M.

    2011-01-01

    The Surveying the Agents of a Galaxy's Evolution (SAGE; PI: M. Meixner) Spitzer Space Telescope Legacy project aims to further our understanding of the life cycle of matter in galaxies by studying this life cycle in our neighboring galaxy, the Large Magellanic Cloud (LMC). Combining SAGE mid-infrared photometry with that at shorter wavelengths from other catalogs, the spectral energy distribution (SED) for each of >25000 Asymptotic Giant Branch (AGB) and Red Supergiant (RSG) stars in the LMC has been assembled. To model mass loss from these stars, my colleagues and I have constructed the grid of RSG and AGB models (GRAMS) using the radiative transfer code 2Dust. I will discuss how GRAMS was constructed, and how we use it to determine the mass-loss rate for each evolved star studied, which gives the total mass-loss return to the LMC from AGB and RSG stars. In my talk, I show how this total mass-loss return is divided into oxygen-rich (O-rich) and carbon-rich (C-rich) dust using SED-fitting to identify O-rich versus C-rich AGB stars. Applications of this work to determining the mass return from evolved stars in other galaxies, including the Milky Way, will also be discussed.

  14. Biomass Burning

    Atmospheric Science Data Center

    2015-07-27

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

  15. Inter-relationships between the heterotrimeric Gβ subunit AGB1, the RLK FERONIA and RALF1 in salinity response.

    PubMed

    Yu, Yunqing; Assmann, Sarah M

    2018-06-15

    Plant heterotrimeric G proteins modulate numerous developmental stress responses. Recently, receptor-like kinases (RLKs) have been implicated as functioning with G proteins, and may serve as plant G-protein-coupled-receptors (GPCRs). The RLK FERONIA (FER), in the Catharantus roseus RLK1-like subfamily, is activated by a family of polypeptides called Rapid Alkalinization Factors (RALFs). We previously showed that the Arabidopsis G protein β subunit, AGB1, physically interacts with FER, and that RALF1 regulation of stomatal movement through FER requires AGB1. Here, we investigated genetic interactions of AGB1 and FER in plant salinity response by comparing salt responses in the single and double mutants of agb1 and fer. We show that AGB1 and FER act additively or synergistically depending on the conditions of the NaCl treatments. We further show that the synergism likely occurs through salt-induced ROS production. In addition, we show that RALF1 enhances salt toxicity through increasing Na + accumulation and decreasing K + accumulation rather than by inducing ROS production, and that the RALF1 effect on salt response occurs in an AGB1-independent manner. Our results indicate that RLK epistatic relationships are not fixed, as AGB1 and FER display different genetic relationships to RALF1 in stomatal vs. salinity responses. This article is protected by copyright. All rights reserved.

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

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

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

  17. Elicitors aboveground: an alternative for control of a belowground pest

    USDA-ARS?s Scientific Manuscript database

    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 ...

  18. Evaluation and Validation of Aboveground Techniques for Coating Condition Assessment

    DOT National Transportation Integrated Search

    2006-02-28

    The overall objective was to determine the accuracy, resolution, and limitations of equipment typically used for modern aboveground ECDA work with respect to locating holidays and disbondments with commonly used coatings with varying spatial relation...

  19. 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.

  20. Proven Alternatives for Aboveground Treatment of Arsenic in Groundwater

    EPA Pesticide Factsheets

    This issue paper, developed for EPA's Engineering Forum, identifies and summarizes experiences with proven aboveground treatment alternatives for arsenic in groundwater, and provides information on their relative effectiveness and cost.

  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. Abundances of presolar graphite and SiC from supernovae and AGB stars in the Murchison meteorite

    SciTech Connect

    Amari, Sachiko; Zinner, Ernst; Gallino, Roberto

    2014-05-02

    Pesolar graphite grains exhibit a range of densities (1.65 – 2.20 g/cm{sup 3}). We investigated abundances of presolar graphite grains formed in supernovae and in asymptotic giant branch (AGB) stars in the four density fractions KE3, KFA1, KFB1 and KFC1 extracted from the Murchison meteorite to probe dust productions in these stellar sources. Seventy-six and 50% of the grains in the low-density fractions KE3 and KFA1, respectively, are supernova grains, while only 7.2% and 0.9% of the grains in the high-density fractions KFB1 and KFC1 have a supernova origin. Grains of AGB star origin are concentrated in the high-density fractionsmore » KFB1 and KFC1. From the C isotopic distributions of these fractions and the presence of s-process Kr with {sup 86}Kr/{sup 82}Kr = 4.43±0.46 in KFC1, we estimate that 76% and 80% of the grains in KFB1 and KFC1, respectively, formed in AGB stars. From the abundance of graphite grains in the Murchison meteorite, 0.88 ppm, the abundances of graphite from supernovae and AGB stars are 0.24 ppm and 0.44 ppm, respectively: the abundances of graphite in supernovae and AGB stars are comparable. In contrast, it has been known that 1% of SiC grains formed in supernovae and 95% formed in AGB stars in meteorites. Since the abundance of SiC grains is 5.85 ppm in the Murchison meteorite, the abundances of SiC from supernovae and AGB stars are 0.063 ppm and 5.6 ppm, respectively: the dominant source of SiC grains is AGB stars. Since SiC grains are harder and likely to survive better in space than graphite grains, the abundance of supernova graphite grains, which is higher than that of supernova SiC grains, indicates that supernovae proficiently produce graphite grains. Graphite grains from AGB stars are, in contrast, less abundant that SiC grains from AGB stars (0.44 ppm vs. 5.6 ppm). It is difficult to derive firm conclusions for graphite and SiC formation in AGB stars due to the difference in susceptibility to grain destruction

  3. 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

  4. 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...

  5. 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...

  6. 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.

  7. AI canis minoris, a pulsating low-mass supergiant at an early transition phase from the AGB to the post-AGB stage of evolution

    NASA Astrophysics Data System (ADS)

    Arkhipova, V. P.; Ikonnikova, N. P.; Esipov, V. F.; Komissarova, G. V.

    2017-06-01

    The U BV photometry and low-resolution spectroscopy for the semiregular variable AI CMi, a candidate for post-AGB objects, performed in 1996-2016 and 2000-2013, respectively, are presented. The star showed multiperiodic brightness variations with an amplitude up to 1\\underset{\\cdot}{m} 5 in the V band, a significant (up to 0\\underset{\\cdot}{m} 4) bluing of the B - V and U - B colors as the star faded, and a change of its spectrum from G5 I to K3-5 I, depending on its brightness. A possible long-term fading of AI CMi below 8\\underset{\\cdot}{m} 5 in the period from May 2013 to early 2015 is observed in the light curve. The colors in this episode did not change the pattern of their unusual behavior with brightness. The main feature of the spectrum for AI CMi is the appearance and strengthening of TiO absorption bands as its brightness declines, which are atypical in the spectra of ordinary G5-K3 supergiants. The bluing of the B - V and U - B colors is interpreted as the blanketing of stellar radiation predominantly in V (and to a lesser extent in B) by the TiO absorption bands whose intensity increases dramatically with decreasing brightness. Another cause of the bluing can be the scattering of stellar radiation by small dust particles in the gas-dust shell of AI CMi. The star's continuum-normalized spectra over the period from 2000 to 2013 in the wavelength range 4200 to 7700 or 9200 Å are presented. These were taken at different phases of the pulsation cycle and clearly demonstrate the behavior of the TiO absorption bands depending on the V magnitude and B - V color. The equivalent widths of individual TiO bands weremeasured, and their correlation with the photometric parameters of the star is shown. AI CMi belongs to the O-rich branch of AGB/post-AGB supergiants and has a luminosity of 4000 L ⊙ at a distance of 1500 ± 700 pc. The mass of AI CMi is most likely small and close to the lower mass limit for post-AGB stars. The connection of the star

  8. Short-lived Isotopes from a Close-by AGB Star Triggering the Protosolar Nebula

    NASA Astrophysics Data System (ADS)

    Gallino, R.; Busso, M.; Wasserburg, G. J.; Straniero, O.

    The presence of short-lived isotopes in the early solar system, in particular 26Al, 41Ca, 60Fe, and 107Pd, point to a close-by and fresh nucleosynthesis source, possibly triggering the collapse of the protosolar nebula. We present the results of nucleosynthesis calculations based on an AGB polluting hypothesis. A general concordance of the predicted yields of the above radioactivities relative to 26Al can be obtained in the case of an intermediate mass AGB star with hot bottom burning in the envelope (thus producing 26Al), and mixing through a series of third dredge-up episodes a fraction of the C-rich and s-processed material from the He intershell with the extended envelope. Polution of the protosolar nebula with freshly synthesized material may derive from the efficient winds of the AGB star. In AGB stars, the s-process nucleosynthesis occurs both during the maximum phase of every thermal runaway, driven by the partial activation of the 22Ne(alpha,n)25Mg reaction, and in the interpulse phase, where the 13C nuclei are fully consumed in radiative conditions by the activation of the 13C(alpha,n)16O reaction. We have used different prescriptions for the amount of the 13C nuclei present in the intershell. A minimum amount of 13C is naturally expected in the ashes of H-shell burning. Possible formation of an extra "13C-pocket" derives from the injection of a small amount of protons from the envelope into the 12C-rich intershell during any third dredge-up episode, when the H-shell is inactivated. Prediction for other short-lived, 36Cl, 135Cs, and 205Pb, are given. General consequences for the pollution of the protosolar nebula with newly synthesized stable isotopes from the AGB winds are outlined. The origin of other detected short-lived nuclei, in particular 53Mn, 129I, and 182Hf, which cannot come from an AGB source, is analysed. The alternative trigger hypothesis by a close-by Supernova is discussed.

  9. 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.

  10. Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature

    PubMed Central

    Cayuela, Luis; González-Caro, Sebastián; Aldana, Ana M.; Stevenson, Pablo R.; Phillips, Oliver; Cogollo, Álvaro; Peñuela, Maria C.; von Hildebrand, Patricio; Jiménez, Eliana; Melo, Omar; Londoño-Vega, Ana Catalina; Mendoza, Irina; Velásquez, Oswaldo; Fernández, Fernando; Serna, Marcela; Velázquez-Rua, Cesar; Benítez, Doris; Rey-Benayas, José M.

    2017-01-01

    Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage. PMID:28301482

  11. Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature.

    PubMed

    Álvarez-Dávila, Esteban; Cayuela, Luis; González-Caro, Sebastián; Aldana, Ana M; Stevenson, Pablo R; Phillips, Oliver; Cogollo, Álvaro; Peñuela, Maria C; von Hildebrand, Patricio; Jiménez, Eliana; Melo, Omar; Londoño-Vega, Ana Catalina; Mendoza, Irina; Velásquez, Oswaldo; Fernández, Fernando; Serna, Marcela; Velázquez-Rua, Cesar; Benítez, Doris; Rey-Benayas, José M

    2017-01-01

    Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage.

  12. On the formation of molecules and solid-state compounds from the AGB to the PN phases

    NASA Astrophysics Data System (ADS)

    García-Hernández, D. A.; Manchado, A.

    2016-07-01

    During the asymptoyic giant branch (AGB) phase, different elements are dredge- up to the stellar surface depending on progenitor mass and metallicity. When the mass loss increases at the end of the AGB, a circumstellar dust shell is formed, where different (C-rich or O-rich) molecules and solid-state compounds are formed. These are further processed in the transition phase between AGB stars and planetary nebulae (PNe) to create more complex organic molecules and inorganic solid-state compounds (e.g., polycyclic aromatic hydrocarbons, fullerenes, and graphene precursors in C-rich environments and oxides and crystalline silicates in O-rich ones). We present an observational review of the different molecules and solid-state materials that are formed from the AGB to the PN phases. We focus on the formation routes of complex fullerene (and fullerene-based) molecules as well as on the level of dust processing depending on metallicity.

  13. 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

  14. Nucleation Studies under the Conditions of Carbon-rich AGB Star Envelopes: TiC

    NASA Astrophysics Data System (ADS)

    Patzer, A. B. C.; Wendt, M.; Chang, C.; Sülzle, D.

    2011-09-01

    Many studies of dust nucleation in winds of carbon-rich AGB stars consider primarily carbon as the dust forming material. But dust grains formed in such circumstellar envelopes are rather a mixture of several chemical elements such as titanium or silicon in addition to carbon, as verified by many investigations of pre-solar grains enclosed in meteorites, for example. In this contribution we focus on the study of the nucleation of titanium carbide particles from the gas phase. The necessary properties of molecular titanium carbide clusters have been estimated by the density functional approach, and the first implications for the homogeneous nucleation of TiC are studied for conditions representative of circumstellar dust shells around carbon-rich AGB stars.

  15. The Contribution of TP-AGB Stars to the Mid-infrared Colors of Nearby Galaxies

    NASA Astrophysics Data System (ADS)

    Chisari, Nora E.; Kelson, Daniel D.

    2012-07-01

    We study the mid-infrared color space of 30 galaxies from the Spitzer Infrared Nearby Galaxies Survey (SINGS) survey for which Sloan Digital Sky Survey data are also available. We construct two-color maps for each galaxy and compare them to results obtained from combining Maraston evolutionary synthesis models, galactic thermally pulsating asymptotic giant branch (TP-AGB) colors, and smooth star formation histories. For most of the SINGS sample, the spatially extended mid-IR emission seen by Spitzer in normal galaxies is consistent with our simple model in which circumstellar dust from TP-AGB stars dominates at 8 and 24 μm. There is a handful of exceptions that we identify as galaxies that have high star formation rates presumably with star formation histories that cannot be assumed to be smooth, or anemic galaxies, which were depleted of their H I at some point during their evolution and have very low ongoing star formation rates.

  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. Lithium and zirconium abundances in massive Galactic O-rich AGB stars

    NASA Astrophysics Data System (ADS)

    García-Hernández, D. A.; García-Lario, P.; Plez, B.; Manchado, A.; D'Antona, F.; Lub, J.; Habing, H.

    2007-02-01

    Lithium and zirconium abundances (the latter taken as representative of s-process enrichment) are determined for a large sample of massive Galactic O-rich AGB stars, for which high-resolution optical spectroscopy has been obtained (R˜ 40 000{-}50 000). This was done by computing synthetic spectra based on classical hydrostatic model atmospheres for cool stars and using extensive line lists. The results are discussed in the framework of "hot bottom burning" (HBB) and nucleosynthesis models. The complete sample is studied for various observational properties such as the position of the stars in the IRAS two-colour diagram ([ 12] - [25] vs. [ 25] - [60] ), Galactic distribution, expansion velocity (derived from the OH maser emission), and period of variability (when available). We conclude that a considerable fraction of these sources are actually massive AGB stars (M>3{-}4 M⊙) experiencing HBB, as deduced from the strong Li overabundances we found. A comparison of our results with similar studies carried out in the past for the Magellanic Clouds (MCs) reveals that, in contrast to MC AGB stars, our Galactic sample does not show any indication of s-process element enrichment. The differences observed are explained as a consequence of metallicity effects. Finally, we discuss the results obtained in the framework of stellar evolution by comparing our results with the data available in the literature for Galactic post-AGB stars and PNe. Based on observations at the 4.2 m William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de Los Muchachos of the Instituto de Astrofisica de Canarias. Also based on observations with the ESO 3.6 m telescope at La Silla Observatory (Chile). Tables [see full text]-[see full text] are only available in electronic form at http://www.aanda.org

  20. Super-AGB Stars and their Role as Electron Capture Supernova Progenitors

    NASA Astrophysics Data System (ADS)

    Doherty, Carolyn L.; Gil-Pons, Pilar; Siess, Lionel; Lattanzio, John C.

    2017-11-01

    We review the lives, deaths and nucleosynthetic signatures of intermediate-mass stars in the range ≈6-12 M⊙, which form super-AGB stars near the end of their lives. The critical mass boundaries both between different types of massive white dwarfs (CO, CO-Ne, ONe), and between white dwarfs and supernovae, are examined along with the relative fraction of super-AGB stars that end life either as an ONe white dwarf or as a neutron star (or an ONeFe white dwarf), after undergoing an electron capture supernova event. The contribution of the other potential single-star channel to electron-capture supernovae, that of the failed massive stars, is also discussed. The factors that influence these different final fates and mass limits, such as composition, rotation, the efficiency of convection, the nuclear reaction rates, mass-loss rates, and third dredge-up efficiency, are described. We stress the importance of the binary evolution channels for producing electron-capture supernovae. Recent nucleosynthesis calculations and elemental yield results are discussed and a new set of s-process heavy element yields is presented. The contribution of super-AGB star nucleosynthesis is assessed within a Galactic perspective, and the (super-)AGB scenario is considered in the context of the multiple stellar populations seen in globular clusters. A brief summary of recent works on dust production is included. Last, we conclude with a discussion of the observational constraints and potential future advances for study into these stars on the low mass/high mass star boundary.

  1. CONSTRAINTS OF THE PHYSICS OF LOW-MASS AGB STARS FROM CH AND CEMP STARS

    SciTech Connect

    Cristallo, S.; Piersanti, L.; Gobrecht, D.

    2016-12-20

    We analyze a set of published elemental abundances from a sample of CH stars which are based on high resolution spectral analysis of ELODIE and SUBARU/HDS spectra. All the elemental abundances were derived from local thermodynamic equilibrium analysis using model atmospheres, and thus they represent the largest homogeneous abundance data available for CH stars to date. For this reason, we can use the set to constrain the physics and the nucleosynthesis occurring in low mass asymptotic giant branch (AGB) s.tars. CH stars have been polluted in the past from an already extinct AGB companion and thus show s-process enriched surfaces.more » We discuss the effects induced on the surface AGB s-process distributions by different prescriptions for convection and rotation. Our reference theoretical FRUITY set fits only part of the observations. Moreover, the s-process observational spread for a fixed metallicity cannot be reproduced. At [Fe/H] > −1, a good fit is found when rotation and a different treatment of the inner border of the convective envelope are simultaneously taken into account. In order to increase the statistics at low metallicities, we include in our analysis a selected number of CEMP stars and, therefore, we compute additional AGB models down to [Fe/H] = −2.85. Our theoretical models are unable to attain the large [hs/ls] ratios characterizing the surfaces of those objects. We speculate on the reasons for such a discrepancy, discussing the possibility that the observed distribution is a result of a proton mixing episode leading to a very high neutron density (the so-called i-process).« less

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Dust formation and wind acceleration around the aluminum oxide-rich AGB star W Hydrae

    NASA Astrophysics Data System (ADS)

    Takigawa, Aki; Kamizuka, Takafumi; Tachibana, Shogo; Yamamura, Issei

    2017-11-01

    Dust grains, formed around asymptotic giant branch (AGB) stars, are accelerated by stellar radiation to drive stellar winds, which supply freshly synthesized nuclides to the Galaxy. Silicate is the dominant dust species in space, but 40% of oxygen-rich AGB stars are thought to have comparable amounts of aluminum oxide dust. Dust formation and the wind-driving mechanism around these oxygen-rich stars, however, are poorly understood. We report on the spatial distributions of AlO and 29SiO molecules around an aluminum oxide-rich M-type AGB star, W Hydrae, based on observations obtained with the Atacama Large Millimeter/submillimeter Array. AlO molecules were only observed within three stellar radii (Rstar), whereas 29SiO was distributed in the accelerated wind beyond 5 Rstar without significant depletion. This strongly suggests that condensed aluminum oxide dust plays a key role in accelerating the stellar wind and in preventing the efficient formation of silicate dust around W Hydrae.

  7. ALMA reveals sunburn: CO dissociation around AGB stars in the globular cluster 47 Tucanae

    NASA Astrophysics Data System (ADS)

    McDonald, I.; Zijlstra, A. A.; Lagadec, E.; Sloan, G. C.; Boyer, M. L.; Matsuura, M.; Smith, R. J.; Smith, C. L.; Yates, J. A.; van Loon, J. Th.; Jones, O. C.; Ramstedt, S.; Avison, A.; Justtanont, K.; Olofsson, H.; Blommaert, J. A. D. L.; Goldman, S. R.; Groenewegen, M. A. T.

    2015-11-01

    Atacama Large Millimetre Array observations show a non-detection of carbon monoxide around the four most luminous asymptotic giant branch (AGB) stars in the globular cluster 47 Tucanae. Stellar evolution models and star counts show that the mass-loss rates from these stars should be ˜1.2-3.5 × 10-7 M⊙ yr-1. We would naïvely expect such stars to be detectable at this distance (4.5 kpc). By modelling the ultraviolet radiation field from post-AGB stars and white dwarfs in 47 Tuc, we conclude that CO should be dissociated abnormally close to the stars. We estimate that the CO envelopes will be truncated at a few hundred stellar radii from their host stars and that the line intensities are about two orders of magnitude below our current detection limits. The truncation of CO envelopes should be important for AGB stars in dense clusters. Observing the CO (3-2) and higher transitions and targeting stars far from the centres of clusters should result in the detections needed to measure the outflow velocities from these stars.

  8. Dust formation and wind acceleration around the aluminum oxide–rich AGB star W Hydrae

    PubMed Central

    Takigawa, Aki; Kamizuka, Takafumi; Tachibana, Shogo; Yamamura, Issei

    2017-01-01

    Dust grains, formed around asymptotic giant branch (AGB) stars, are accelerated by stellar radiation to drive stellar winds, which supply freshly synthesized nuclides to the Galaxy. Silicate is the dominant dust species in space, but ~40% of oxygen-rich AGB stars are thought to have comparable amounts of aluminum oxide dust. Dust formation and the wind-driving mechanism around these oxygen-rich stars, however, are poorly understood. We report on the spatial distributions of AlO and 29SiO molecules around an aluminum oxide–rich M-type AGB star, W Hydrae, based on observations obtained with the Atacama Large Millimeter/submillimeter Array. AlO molecules were only observed within three stellar radii (Rstar), whereas 29SiO was distributed in the accelerated wind beyond 5 Rstar without significant depletion. This strongly suggests that condensed aluminum oxide dust plays a key role in accelerating the stellar wind and in preventing the efficient formation of silicate dust around W Hydrae. PMID:29109978

  9. 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.

  10. 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.

  11. 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.

  12. Monitoring Observatinos of H2O and SiO Masers Toward Post-AGB Stars

    NASA Astrophysics Data System (ADS)

    Kim, Jaeheon; Cho, Se-Hyung; Yoon, Dong-Hwan

    2016-12-01

    We present the results of simultaneous monitoring observations of H_2O 6_{1,6}-5_{2,3} (22 GHz) and SiO J=1-0, 2-1, 3-2 maser lines (43, 86, 129 GHz) toward five post-AGB (candidate) stars, using the 21-m single-dish telescopes of the Korean VLBI Network. Depending on the target objects, 7 - 11 epochs of data were obtained. We detected both H_2O and SiO maser lines from four sources: OH16.1-0.3, OH38.10-0.13, OH65.5+1.3, and IRAS 19312+1950. We could not detect H_2O maser emission toward OH13.1+5.1 between the late OH/IR and post-AGB stage. The detected H_2O masers show typical double-peaked line profiles. The SiO masers from four sources, except IRAS 19312+1950, show the peaks around the stellar velocity as a single peak, whereas the SiO masers from IRAS 19312+1950 occur above the red peak of the H_2O maser. We analyzed the properties of detected maser lines, and investigated their evolutionary state through comparison with the full widths at zero power. The distribution of observed target sources was also investigated in the IRAS two-color diagram in relation with the evolutionary stage of post-AGB stars. From our analyses, the evolutionary sequence of observed sources is suggested as OH65.5+1.3 → OH13.1+5.1 → OH16.1-0.3 → OH38.10-0.13, except for IRAS 19312+1950. In addition, OH13.1+5.1 from which the H_2O maser has not been detected is suggested to be on the gateway toward the post-AGB stage. With respect to the enigmatic object, IRAS 19312+1950, we could not clearly figure out its nature. To properly explain the unusual phenomena of SiO and H_2O masers, it is essential to establish the relative locations and spatial distributions of two masers using VLBI technique. We also include the 1.2 - 160 μm spectral energy distribution using photometric data from the following surveys: 2MASS, WISE, MSX, IRAS, and AKARI (IRC and FIS). In addition, from the IRAS LRS spectra, we found that the depth of silicate absorption features shows significant variations

  13. 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

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

    SciTech Connect

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

    1993-03-01

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

  15. The abundance of HCN in circumstellar envelopes of AGB stars of different chemical type

    NASA Astrophysics Data System (ADS)

    Schöier, F. L.; Ramstedt, S.; Olofsson, H.; Lindqvist, M.; Bieging, J. H.; Marvel, K. B.

    2013-02-01

    Aims: A multi-transition survey of HCN (sub-) millimeter line emission from a large sample of asymptotic giant branch (AGB) stars of different chemical type is presented. The data are analysed and circumstellar HCN abundances are estimated. The sample stars span a large range of properties such as mass-loss rate and photospheric C/O-ratio. The analysis of the new data allows for more accurate estimates of the circumstellar HCN abundances and puts new constraints on chemical models. Methods: In order to constrain the circumstellar HCN abundance distribution a detailed non-local thermodynamic equilibrium (LTE) excitation analysis, based on the Monte Carlo method, is performed. Effects of line overlaps and radiative excitation from dust grains are included. Results: The median values for the derived abundances of HCN (with respect to H2) are 3 × 10-5, 7 × 10-7 and 10-7 for carbon stars (25 stars), S-type AGB stars (19 stars) and M-type AGB stars (25 stars), respectively. The estimated sizes of the HCN envelopes are similar to those obtained in the case of SiO for the same sample of sources and agree well with previous results from interferometric observations, when these are available. Conclusions: We find that there is a clear dependence of the derived circumstellar HCN abundance on the C/O-ratio of the star, in that carbon stars have about two orders of magnitude higher abundances than M-type AGB stars, on average. The derived HCN abundances of the S-type AGB stars have a larger spread and typically fall in between those of the two other types, however, slightly closer to the values for the M-type AGB stars. For the M-type stars, the estimated abundances are much higher than what would be expected if HCN is formed in thermal equilibrium. However, the results are also in contrast to predictions from recent non-LTE chemical models, where very little difference is expected in the HCN abundances between the various types of AGB stars. This publication is based on data

  16. Biomass pretreatment

    DOEpatents

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

    2013-05-21

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

  17. Interactions between aboveground herbivores and the mycorrhizal mutualists of plants.

    PubMed

    Gehring, C A; Whitham, T G

    1994-07-01

    Plant growth, reproduction and survival can be affected both by mycorrhizal fungi and aboveground herbivores, but few studies have examined the interactive effects of these factors on plants. Most of the available data suggest that severe herbivory reduces root colonization by vesicular-arbuscular and ectomycorrhizal fungi. However, the reverse interaction has also been documented - mycorrhizal fungi deter herbivores and interact with fungal endophytes to influence herbivory. Although consistent patterns and mechanistic explanations are yet to emerge, it is likely that aboveground herbivore-mycorrhiza interactions have important implications for plant populations and communities. Copyright © 1994. Published by Elsevier Ltd.

  18. 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.

  19. 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

  20. 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...

  1. 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...

  2. 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...

  3. 49 CFR 195.307 - Pressure testing aboveground breakout tanks.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 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 Standard 620 and first placed in service after October 2, 2000, hydrostatic and pneumatic testing must be...

  4. WEAPONS STORAGE AREA. FROM RIGHT TO LEFT, ABOVEGROUND STORAGE MAGAZINE ...

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

    WEAPONS STORAGE AREA. FROM RIGHT TO LEFT, ABOVEGROUND STORAGE MAGAZINE (BUILDING 3568), SPARES INERT STORAGE BUILDING (BUILDING 3570), MISSILE ASSEMBLY SHOP (BUILDING 3578) AND SEGREGATED MAGAZINE STORAGE BUILDING (BUILDING 3572). VIEW TO NORTHWEST - Plattsburgh Air Force Base, U.S. Route 9, Plattsburgh, Clinton County, NY

  5. Aboveground growth interactions of paired conifer seedlings in close proximity

    Treesearch

    Warren D. Devine; Timothy B. Harrington

    2011-01-01

    Where belowground resources are relatively abundant, naturally established trees sometimes occur in very close proximity to one another. We conducted a two-year study to assess the aboveground interactions between Douglas-fir (Pseudotsuga menziesii), grand fir (Abies grandis) and noble fir (Abies procera)...

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

    USDA-ARS?s Scientific Manuscript database

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

  7. 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.

  8. Binarity and Accretion in AGB Stars: HST/STIS Observations of UV Flickering in Y Gem

    NASA Astrophysics Data System (ADS)

    Sahai, R.; Sánchez Contreras, C.; Mangan, A. S.; Sanz-Forcada, J.; Muthumariappan, C.; Claussen, M. J.

    2018-06-01

    Binarity is believed to dramatically affect the history and geometry of mass loss in AGB and post-AGB stars, but observational evidence of binarity is sorely lacking. As part of a project to search for hot binary companions to cool AGB stars using the GALEX archive, we discovered a late-M star, Y Gem, to be a source of strong and variable UV and X-ray emission. Here we report UV spectroscopic observations of Y Gem obtained with the Hubble Space Telescope that show strong flickering in the UV continuum on timescales of ≲20 s, characteristic of an active accretion disk. Several UV lines with P-Cygni-type profiles from sp