Advancing individual tree biomass prediction: assessment and alternatives to the component ratio method

Treesearch

Aaron Weiskittel; Jereme Frank; David Walker; Phil Radtke; David Macfarlane; James Westfall

2015-01-01

Prediction of forest biomass and carbon is becoming important issues in the United States. However, estimating forest biomass and carbon is difficult and relies on empirically-derived regression equations. Based on recent findings from a national gap analysis and comprehensive assessment of the USDA Forest Service Forest Inventory and Analysis (USFS-FIA) component...

Biomass and health based forest cover delineation using spectral un-mixing

Treesearch

Mohan Tiruveedhula; Joseph Fan; Ravi R. Sadasivuni; Surya S. Durbha; David L. Evans

2009-01-01

Remote sensing is a well-suited source of information on various forest characteristics such as forest cover type, leaf area, biomass, and health. The use of appropriate layers helps to quantify the variables of interest. For example, normalized difference vegetation index (NDVI) and greenness help explain variability in biomass as well as health of forests....

Biogeographical patterns of biomass allocation in leaves, stems, and roots in China's forests.

PubMed

Zhang, Hao; Wang, Kelin; Xu, Xianli; Song, Tongqing; Xu, Yanfang; Zeng, Fuping

2015-11-03

To test whether there are general patterns in biomass partitioning in relation to environmental variation when stand biomass is considered, we investigated biomass allocation in leaves, stems, and roots in China's forests using both the national forest inventory data (2004-2008) and our field measurements (2011-2012). Distribution patterns of leaf, stem, and root biomass showed significantly different trends according to latitude, longitude, and altitude, and were positively and significantly correlated with stand age and mean annual precipitation. Trade-offs among leaves, stems, and roots varied with forest type and origin and were mainly explained by stand biomass. Based on the constraints of stand biomass, biomass allocation was also influenced by forest type, origin, stand age, stand density, mean annual temperature, precipitation, and maximum temperature in the growing season. Therefore, after stand biomass was accounted for, the residual variation in biomass allocation could be partially explained by stand characteristics and environmental factors, which may aid in quantifying carbon cycling in forest ecosystems and assessing the impacts of climate change on forest carbon dynamics in China.

Biogeographical patterns of biomass allocation in leaves, stems, and roots in China’s forests

PubMed Central

Zhang, Hao; Wang, Kelin; Xu, Xianli; Song, Tongqing; Xu, Yanfang; Zeng, Fuping

2015-01-01

To test whether there are general patterns in biomass partitioning in relation to environmental variation when stand biomass is considered, we investigated biomass allocation in leaves, stems, and roots in China’s forests using both the national forest inventory data (2004–2008) and our field measurements (2011–2012). Distribution patterns of leaf, stem, and root biomass showed significantly different trends according to latitude, longitude, and altitude, and were positively and significantly correlated with stand age and mean annual precipitation. Trade-offs among leaves, stems, and roots varied with forest type and origin and were mainly explained by stand biomass. Based on the constraints of stand biomass, biomass allocation was also influenced by forest type, origin, stand age, stand density, mean annual temperature, precipitation, and maximum temperature in the growing season. Therefore, after stand biomass was accounted for, the residual variation in biomass allocation could be partially explained by stand characteristics and environmental factors, which may aid in quantifying carbon cycling in forest ecosystems and assessing the impacts of climate change on forest carbon dynamics in China. PMID:26525117

High-biomass forests of the Pacific Northwest: who manages them and how much is protected?

PubMed

Krankina, Olga N; DellaSala, Dominick A; Leonard, Jessica; Yatskov, Mikhail

2014-07-01

To examine ownership and protection status of forests with high-biomass stores (>200 Mg/ha) in the Pacific Northwest (PNW) region of the United States, we used the latest versions of publicly available datasets. Overlay, aggregation, and GIS-based computation of forest area in broad biomass classes in the PNW showed that the National Forests contained the largest area of high-biomass forests (48.4 % of regional total), but the area of high-biomass forest on private lands was important as well (22.8 %). Between 2000 and 2008, the loss of high-biomass forests to fire on the National Forests was 7.6 % (236,000 ha), while the loss of high-biomass forest to logging on private lands (364,000 ha) exceeded the losses to fire across all ownerships. Many remaining high-biomass forest stands are vulnerable to future harvest as only 20 % are strictly protected from logging, while 26 % are not protected at all. The level of protection for high-biomass forests varies by state, for example, 31 % of all high-biomass federal forests in Washington are in high-protection status compared to only 9 % in Oregon. Across the conterminous US, high-biomass forest covers <3 % of all forest land and the PNW region holds 56.8 % of this area or 5.87 million ha. Forests with high-biomass stores are important to document and monitor as they are scarce, often threatened by harvest and development, and their disturbance including timber harvest results in net C losses to the atmosphere that can take a new generation of trees many decades or centuries to offset.

Carbon savings with transatlantic trade in pellets: accounting for market-driven effects

NASA Astrophysics Data System (ADS)

Wang, Weiwei; Dwivedi, Puneet; Abt, Robert; Khanna, Madhu

2015-11-01

Exports of pellets from the United States (US) are growing significantly to meet the demand for renewable energy in the European Union. This transatlantic trade in pellets has raised questions about the greenhouse gas (GHG) intensity of these pellets and their effects on conventional forest product markets in the US. This paper examines the GHG intensity of pellets exported from the US using either forest biomass only or forest and agricultural biomass combined. We develop an integrated dynamic, price-endogenous, partial equilibrium model of the forestry, agricultural, and transportation sectors in the US to investigate not only the direct life-cycle GHG intensity of pellets but also the accompanying indirect market and land use effects induced by changes in prices of forest and agricultural products over the 2007-2032 period. Across different scenarios of high and low pellet demand that can be met with either forest biomass only or with forest and agricultural biomass, we find that the GHG intensity of pellet based electricity is 74% to 85% lower than that of coal-based electricity. We also find that the GHG intensity of pellets produced using agricultural and forest biomass is 28% to 34% lower than that of pellets produced using forest biomass only. GHG effects due to induced direct and indirect changes in forest carbon stock caused by changes in harvest rotations, changes in land use and in conventional wood production account for 11% to 26% of the overall GHG intensity of pellets produced from forest biomass only; these effects are negative with the use of forest and agricultural biomass.

[Spatial pattern of forest biomass and its influencing factors in the Great Xing'an Mountains, Heilongjiang Province, China].

PubMed

Wang, Xiao-Li; Chang, Yu; Chen, Hong-Wei; Hu, Yuan-Man; Jiao, Lin-Lin; Feng, Yu-Ting; Wu, Wen; Wu, Hai-Feng

2014-04-01

Based on field inventory data and vegetation index EVI (enhanced vegetation index), the spatial pattern of the forest biomass in the Great Xing'an Mountains, Heilongjiang Province was quantitatively analyzed. Using the spatial analysis and statistics tools in ArcGIS software, the impacts of climatic zone, elevation, slope, aspect and vegetation type on the spatial pattern of forest biomass were explored. The results showed that the forest biomass in the Great Xing'an Mountains was 350 Tg and spatially aggregated with great increasing potentials. Forest biomass density in the cold temperate humid zone (64.02 t x hm(-2)) was higher than that in the temperate humid zone (60.26 t x hm(-2)). The biomass density of each vegetation type was in the order of mixed coniferous forest (65.13 t x hm(-2)) > spruce-fir forest (63.92 t x hm(-2)) > Pinus pumila-Larix gmelinii forest (63.79 t x hm(-2)) > Pinus sylvestris var. mongolica forest (61.97 t x hm(-2)) > Larix gmelinii forest (61.40 t x hm(-2)) > deciduous broadleaf forest (58.96 t x hm(-2)). With the increasing elevation and slope, the forest biomass density first decreased and then increased. The forest biomass density in the shady slopes was greater than that in the sunny slopes. The spatial pattern of forest biomass in the Great Xing' an Mountains exhibited a heterogeneous pattern due to the variation of climatic zone, vegetation type and topographical factor. This spatial heterogeneity needs to be accounted when evaluating forest biomass at regional scales.

Uncertainty in countrywide forest biomass estimates.

Treesearch

C.E. Peterson; D. Turner

1994-01-01

Country-wide estimates of forest biomass are the major driver for estimating and understanding carbon pools and flux, a critical component of global change research. Important determinants in making these estimates include the areal extent of forested lands and their associated biomass. Estimates for these parameters may be derived from surface-based data, photo...

Secondary Forest Age and Tropical Forest Biomass Estimation Using TM

NASA Technical Reports Server (NTRS)

Nelson, R. F.; Kimes, D. S.; Salas, W. A.; Routhier, M.

1999-01-01

The age of secondary forests in the Amazon will become more critical with respect to the estimation of biomass and carbon budgets as tropical forest conversion continues. Multitemporal Thematic Mapper data were used to develop land cover histories for a 33,000 Square kM area near Ariquemes, Rondonia over a 7 year period from 1989-1995. The age of the secondary forest, a surrogate for the amount of biomass (or carbon) stored above-ground, was found to be unimportant in terms of biomass budget error rates in a forested TM scene which had undergone a 20% conversion to nonforest/agricultural cover types. In such a situation, the 80% of the scene still covered by primary forest accounted for over 98% of the scene biomass. The difference between secondary forest biomass estimates developed with and without age information were inconsequential relative to the estimate of biomass for the entire scene. However, in futuristic scenarios where all of the primary forest has been converted to agriculture and secondary forest (55% and 42% respectively), the ability to age secondary forest becomes critical. Depending on biomass accumulation rate assumptions, scene biomass budget errors on the order of -10% to +30% are likely if the age of the secondary forests are not taken into account. Single-date TM imagery cannot be used to accurately age secondary forests into single-year classes. A neural network utilizing TM band 2 and three TM spectral-texture measures (bands 3 and 5) predicted secondary forest age over a range of 0-7 years with an RMSE of 1.59 years and an R(Squared) (sub actual vs predicted) = 0.37. A proposal is made, based on a literature review, to use satellite imagery to identify general secondary forest age groups which, within group, exhibit relatively constant biomass accumulation rates.

Predictions of Tropical Forest Biomass and Biomass Growth Based on Stand Height or Canopy Area Are Improved by Landsat-Scale Phenology across Puerto Rico and the U.S. Virgin Islands

Treesearch

David Gwenzi; Eileen Helmer; Xiaolin Zhu; Michael Lefsky; Humfredo Marcano-Vega

2017-01-01

Remotely-sensed estimates of forest biomass are usually based on various measurements of canopy height, area, volume or texture, as derived from LiDAR, radar or fine spatial resolution imagery. These measurements are then calibrated to estimates of stand biomass that are primarily based on tree stem diameters. Although humid tropical...

Measuring carbon in forests: current status and future challenges.

PubMed

Brown, Sandra

2002-01-01

To accurately and precisely measure the carbon in forests is gaining global attention as countries seek to comply with agreements under the UN Framework Convention on Climate Change. Established methods for measuring carbon in forests exist, and are best based on permanent sample plots laid out in a statistically sound design. Measurements on trees in these plots can be readily converted to aboveground biomass using either biomass expansion factors or allometric regression equations. A compilation of existing root biomass data for upland forests of the world generated a significant regression equation that can be used to predict root biomass based on aboveground biomass only. Methods for measuring coarse dead wood have been tested in many forest types, but the methods could be improved if a non-destructive tool for measuring the density of dead wood was developed. Future measurements of carbon storage in forests may rely more on remote sensing data, and new remote data collection technologies are in development.

The Role of Remote Sensing in Assessing Forest Biomass in Appalachian South Carolina

NASA Technical Reports Server (NTRS)

Shain, W.; Nix, L.

1982-01-01

Information is presented on the use of color infrared aerial photographs and ground sampling methods to quantify standing forest biomass in Appalachian South Carolina. Local tree biomass equations are given and subsequent evaluation of stand density and size classes using remote sensing methods is presented. Methods of terrain analysis, environmental hazard rating, and subsequent determination of accessibility of forest biomass are discussed. Computer-based statistical analyses are used to expand individual cover-type specific ground sample data to area-wide cover type inventory figures based on aerial photographic interpretation and area measurement. Forest biomass data are presented for the study area in terms of discriminant size classes, merchantability limits, accessibility (as related to terrain and yield/harvest constraints), and potential environmental impact of harvest.

Statistical properties of mean stand biomass estimators in a LIDAR-based double sampling forest survey design.

Treesearch

H.E. Anderson; J. Breidenbach

2007-01-01

Airborne laser scanning (LIDAR) can be a valuable tool in double-sampling forest survey designs. LIDAR-derived forest structure metrics are often highly correlated with important forest inventory variables, such as mean stand biomass, and LIDAR-based synthetic regression estimators have the potential to be highly efficient compared to single-stage estimators, which...

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

Treesearch

M. D. Brinckman; J. F. Munsell

2009-01-01

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

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

PubMed

Xu, Bing; Guo, ZhaoDi; Piao, ShiLong; Fang, JingYun

2010-07-01

China's forests are characterized by young forest age, low carbon density and a large area of planted forests, and thus have high potential to act as carbon sinks in the future. Using China's national forest inventory data during 1994-1998 and 1999-2003, and direct field measurements, we investigated the relationships between forest biomass density and forest age for 36 major forest types. Statistical approaches and the predicted future forest area from the national forestry development plan were applied to estimate the potential of forest biomass carbon storage in China during 2000-2050. Under an assumption of continuous natural forest growth, China's existing forest biomass carbon (C) stock would increase from 5.86 Pg C (1 Pg=10(15) g) in 1999-2003 to 10.23 Pg C in 2050, resulting in a total increase of 4.37 Pg C. Newly planted forests through afforestation and reforestation will sequestrate an additional 2.86 Pg C in biomass. Overall, China's forests will potentially act as a carbon sink for 7.23 Pg C during the period 2000-2050, with an average carbon sink of 0.14 Pg C yr(-1). This suggests that China's forests will be a significant carbon sink in the next 50 years.

Estimates of Forest Biomass Carbon Storage in Liaoning Province of Northeast China: A Review and Assessment

PubMed Central

Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J.; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

2014-01-01

Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha−1 in 1980 to 31.0 Mg ha−1 in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations. PMID:24586881

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

PubMed

Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

2014-01-01

Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha(-1) in 1980 to 31.0 Mg ha(-1) in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations.

Developing Biomass Equations for Western Hemlock and Red Alder Trees in Western Oregon Forests

Treesearch

Krishna Poudel; Hailemariam Temesgen

2016-01-01

Biomass estimates are required for reporting carbon, assessing feedstock availability, and assessing forest fire threat. We developed diameter- and height-based biomass equations for Western hemlock (Tsuga heterophylla (Raf.) Sarg.) and red alder (Alnus rubra Bong.) trees in Western Oregon. A system of component biomass...

FINAL TECHNICAL REPORT FOR FORESTRY BIOFUEL STATEWIDE COLLABORATION CENTER (MICHIGAN)

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

LaCourt, Donna M.; Miller, Raymond O.; Shonnard, David R.

A team composed of scientists from Michigan State University (MSU) and Michigan Technological University (MTU) assembled to better understand, document, and improve systems for using forest-based biomass feedstocks in the production of energy products within Michigan. Work was funded by a grant (DE-EE-0000280) from the U.S. Department of Energy (DOE) and was administered by the Michigan Economic Development Corporation (MEDC). The goal of the project was to improve the forest feedstock supply infrastructure to sustainably provide woody biomass for biofuel production in Michigan over the long-term. Work was divided into four broad areas with associated objectives: • TASK A: Developmore » a Forest-Based Biomass Assessment for Michigan – Define forest-based feedstock inventory, availability, and the potential of forest-based feedstock to support state and federal renewable energy goals while maintaining current uses. • TASK B: Improve Harvesting, Processing and Transportation Systems – Identify and develop cost, energy, and carbon efficient harvesting, processing and transportation systems. • TASK C: Improve Forest Feedstock Productivity and Sustainability – Identify and develop sustainable feedstock production systems through the establishment and monitoring of a statewide network of field trials in forests and energy plantations. • TASK D: Engage Stakeholders – Increase understanding of forest biomass production systems for biofuels by a broad range of stakeholders. The goal and objectives of this research and development project were fulfilled with key model deliverables including: 1) The Forest Biomass Inventory System (Sub-task A1) of feedstock inventory and availability and, 2) The Supply Chain Model (Sub-task B2). Both models are vital to Michigan’s forest biomass industry and support forecasting delivered cost, as well as carbon and energy balance. All of these elements are important to facilitate investor, operational and policy decisions. All other sub-tasks supported the development of these two tools either directly or by building out supporting information in the forest biomass supply chain. Outreach efforts have, and are continuing to get these user friendly models and information to decision makers to support biomass feedstock supply chain decisions across the areas of biomass inventory and availability, procurement, harvest, forwarding, transportation and processing. Outreach will continue on the project website at http://www.michiganforestbiofuels.org/ and http://www.michiganwoodbiofuels.org/« less

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Demographic drivers of tree biomass change during secondary succession in northeastern Costa Rica.

PubMed

Rozendaal, Danae M A; Chazdon, Robin L

2015-03-01

Second-growth tropical forests are an important global carbon sink. As current knowledge on biomass accumulation during secondary succession is heavily based on chronosequence studies, direct estimates of annual rates of biomass accumulation in monitored stands are largely unavailable. We evaluated the contributions of tree diameter increment, recruitment, and mortality to annual tree biomass change during succession for three groups of tree species: second-growth (SG) specialists, generalists, and old-growth (OG) specialists. We monitored six second-growth tropical forests that varied in stand age and two old-growth forests in northeastern Costa Rica. We monitored these over a period of 8 to 16 years. To assess rates of biomass change during secondary succession, we compared standing biomass and biomass dynamics between second-growth forest stages and old-growth forest, and evaluated the effect of stand age on standing biomass and biomass dynamics in second-growth forests. Standing tree biomass increased with stand age during succession, whereas the rate of biomass change decreased. Biomass change was largely driven by tree diameter increment and mortality, with a minor contribution from recruitment. The relative importance of these demographic drivers shifted over succession. Biomass gain due to tree diameter increment decreased with stand age, whereas biomass loss due to mortality increased. In the age range of our second-growth forests, 10-41 years, SG specialists dominated tree biomass in second-growth forests. SG specialists, and to a lesser extent generalists, also dominated stand-level biomass increase due to tree diameter increment, whereas SG specialists largely accounted for decreases in biomass due to mortality. Our results indicate that tree growth is largely driving biomass dynamics early in succession, whereas both growth and mortality are important later in succession. Biomass dynamics are largely accounted for by a few SG specialists and one generalist species, Pentaclethra macroloba. To assess the generality of our results, similar long-term studies should be compared across tropical forest landscapes.

Integrating LIDAR and forest inventories to fill the trees outside forests data gap.

PubMed

Johnson, Kristofer D; Birdsey, Richard; Cole, Jason; Swatantran, Anu; O'Neil-Dunne, Jarlath; Dubayah, Ralph; Lister, Andrew

2015-10-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all "nonforest" Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6%, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47% increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

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 learning algorithms are better means to do so than parametric regression models.

The Roles of Forest Biomass Carbon Sinks in Offsetting Anthropogenic Emissions in China

NASA Astrophysics Data System (ADS)

Ju, W.; Zhang, C.

2016-12-01

Forests play a critical role in mitigating climate change because of their high carbon storage and productivity. China has experienced a pronounced increase in forest area resulting from afforestation and reforestation activities since the 1970s. Meanwhile, anthropogenic carbon emission also increased very quickly owing to fast economic development. This study was devoted to assess the roles of forest biomass carbon sinks in offsetting anthropogenic emissions in China for the period from 2000 to 2012. Forest biomass carbon sinks of China's forests were calculated at provincial levels based on eight national forest inventory datasets from 1973 to 2013. The anthropogenic carbon emissions of individual provinces were estimated for different sectors over the period from 2000 to 2012, including industrial, transportation, and other energy consumption and industrial processes. The national forest biomass carbon sinks increased from 25.0 to 166.5 Tg C yr-1 between 1973 and 2008, and then decreased to 130.9 Tg C yr-1 for the period of 2009-2013 because the increases in forest area and biomass carbon density became slower. About 7% and 93% of this sink reduction occurred in planted and natural forests. The carbon sinks for young, middle-aged and premature forests decreased by 27.3, 27.0, and 7.6 Tg C yr-1, respectively. 42% of this decrease was offset by mature and overmature forests. During 2009-2013, forest biomass carbon sinks decreased in all regions but the north and northwest regions. The drivers for changes of forest biomass sinks differ spatially. The average national total anthropogenic carbon emissions were 1107.2 Tg C yr-1 , 1876.7 Tg C yr-1 and 2670 Tg C yr-1 over the periods from 2000 to 2003, 2004 to 2008, 2009 to 2012, respectively. The forest biomass carbon sinks approximately offset 14.6%, 8.9%, and 4.9% of these emissions. The declined roles of forest biomass carbon sinks in offsetting anthropogenic carbon emissions were mainly caused by large increase of anthropogenic carbon emissions and small disturbance-induced decrease of forest biomass carbon sinks. Keywords: anthropogenic carbon emissions, biomass carbon sink, forest disturbances

A New Synthetic Global Biomass Carbon Map for the year 2010

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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)...

Evaluating the remote sensing and inventory-based estimation of biomass in the western Carpathians

Treesearch

Magdalena Main-Knorn; Gretchen G. Moisen; Sean P. Healey; William S. Keeton; Elizabeth A. Freeman; Patrick Hostert

2011-01-01

Understanding the potential of forest ecosystems as global carbon sinks requires a thorough knowledge of forest carbon dynamics, including both sequestration and fluxes among multiple pools. The accurate quantification of biomass is important to better understand forest productivity and carbon cycling dynamics. Stand-based inventories (SBIs) are widely used for...

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.

Evaluation of alternative approaches for landscape-scale biomass estimation in a mixed-species northern forest

Treesearch

Coeli M. Hoover; Mark J. Ducey; R. Andy Colter; Mariko Yamasaki

2018-01-01

There is growing interest in estimating and mapping biomass and carbon content of forests across large landscapes. LiDAR-based inventory methods are increasingly common and have been successfully implemented in multiple forest types. Asner et al. (2011) developed a simple universal forest carbon estimation method for tropical forests that reduces the amount of required...

Massive mortality of aspen following severe drought along the southern edge of the Canadian boreal forest

PubMed Central

Michaelian, Michael; Hogg, Edward H; Hall, Ronald J; Arsenault, Eric

2011-01-01

Drought-induced, regional-scale dieback of forests has emerged as a global concern that is expected to escalate under model projections of climate change. Since 2000, drought of unusual severity, extent, and duration has affected large areas of western North America, leading to regional-scale dieback of forests in the southwestern US. We report on drought impacts on forests in a region farther north, encompassing the transition between boreal forest and prairie in western Canada. A central question is the significance of drought as an agent of large-scale tree mortality and its potential future impact on carbon cycling in this cold region. We used a combination of plot-based, meteorological, and remote sensing measures to map and quantify aboveground, dead biomass of trembling aspen (Populus tremuloides Michx.) across an 11.5 Mha survey area where drought was exceptionally severe during 2001–2002. Within this area, a satellite-based land cover map showed that aspen-dominated broadleaf forests occupied 2.3 Mha. Aerial surveys revealed extensive patches of severe mortality (>55%) resembling the impacts of fire. Dead aboveground biomass was estimated at 45 Mt, representing 20% of the total aboveground biomass, based on a spatial interpolation of plot-based measurements. Spatial variation in percentage dead biomass showed a moderately strong correlation with drought severity. In the prairie-like, southern half of the study area where the drought was most severe, 35% of aspen biomass was dead, compared with an estimated 7% dead biomass in the absence of drought. Drought led to an estimated 29 Mt increase in dead biomass across the survey area, corresponding to 14 Mt of potential future carbon emissions following decomposition. Many recent, comparable episodes of drought-induced forest dieback have been reported from around the world, which points to an emerging need for multiscale monitoring approaches to quantify drought effects on woody biomass and carbon cycling across large areas.

Simulating carbon stocks and fluxes of an African tropical montane forest with an individual-based forest model.

PubMed

Fischer, Rico; Ensslin, Andreas; Rutten, Gemma; Fischer, Markus; Schellenberger Costa, David; Kleyer, Michael; Hemp, Andreas; Paulick, Sebastian; Huth, Andreas

2015-01-01

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha(-1) yr(-1). Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.

Forest-based biomass supply in Massachusetts: How much is there and how much is available

Treesearch

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

2012-01-01

Forest owners in Massachusetts (U.S.) live in a densely populated state and near forestland that is under pressure of development and characterized by small parcel size. Forest-based biomass harvesting in Massachusetts is a renewable energy topic generating a great deal of discussion among all constituents. To provide perspective on these discussions, our analysis asks...

The importance of age-related decline in forest NPP for modeling regional carbon balances.

PubMed

Zaehle, Sönke; Sitch, Stephen; Prentice, I Colin; Liski, Jari; Cramer, Wolfgang; Erhard, Markus; Hickler, Thomas; Smith, Benjamin

2006-08-01

We show the implications of the commonly observed age-related decline in aboveground productivity of forests, and hence forest age structure, on the carbon dynamics of European forests in response to historical changes in environmental conditions. Size-dependent carbon allocation in trees to counteract increasing hydraulic resistance with tree height has been hypothesized to be responsible for this decline. Incorporated into a global terrestrial biosphere model (the Lund-Potsdam-Jena model, LPJ), this hypothesis improves the simulated increase in biomass with stand age. Application of the advanced model, including a generic representation of forest management in even-aged stands, for 77 European provinces shows that model-based estimates of biomass development with age compare favorably with inventory-based estimates for different tree species. Model estimates of biomass densities on province and country levels, and trends in growth increment along an annual mean temperature gradient are in broad agreement with inventory data. However, the level of agreement between modeled and inventory-based estimates varies markedly between countries and provinces. The model is able to reproduce the present-day age structure of forests and the ratio of biomass removals to increment on a European scale based on observed changes in climate, atmospheric CO2 concentration, forest area, and wood demand between 1948 and 2000. Vegetation in European forests is modeled to sequester carbon at a rate of 100 Tg C/yr, which corresponds well to forest inventory-based estimates.

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

USGS Publications Warehouse

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

2015-01-01

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

Recent changes in the estimation of standing dead tree biomass and carbon stocks in the U.S. forest inventory

Treesearch

Grant M. Domke; Christopher W. Woodall; James E. Smith

2012-01-01

Until recently, standing dead tree biomass and carbon (C) has been estimated as a function of live tree growing stock volume in the U.S. Forest Service, Forest Inventory and Analysis (FIA) Program. Traditional estimates of standing dead tree biomass/C attributes were based on merchantability standards that did not reflect density reductions or structural loss due to...

Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods

Treesearch

Zhaodi Guo; Jingyun Fang; Yude Pan; Richard Birdsey

2010-01-01

Several studies have reported different estimates for forest biomass carbon (C) stocks in China. The discrepancy among these estimates may be largely attributed to the methods used. In this study, we used three methods [mean biomass density method (MBM), mean ratio method (MRM), and continuous biomass expansion factor (BEF) method (abbreviated as CBM)] applied to...

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

ERIC Educational Resources Information Center

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

2008-01-01

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

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;

Reducing uncertainty for estimating forest carbon stocks and dynamics using integrated remote sensing, forest inventory and process-based modeling

NASA Astrophysics Data System (ADS)

Poulter, B.; Ciais, P.; Joetzjer, E.; Maignan, F.; Luyssaert, S.; Barichivich, J.

2015-12-01

Accurately estimating forest biomass and forest carbon dynamics requires new integrated remote sensing, forest inventory, and carbon cycle modeling approaches. Presently, there is an increasing and urgent need to reduce forest biomass uncertainty in order to meet the requirements of carbon mitigation treaties, such as Reducing Emissions from Deforestation and forest Degradation (REDD+). Here we describe a new parameterization and assimilation methodology used to estimate tropical forest biomass using the ORCHIDEE-CAN dynamic global vegetation model. ORCHIDEE-CAN simulates carbon uptake and allocation to individual trees using a mechanistic representation of photosynthesis, respiration and other first-order processes. The model is first parameterized using forest inventory data to constrain background mortality rates, i.e., self-thinning, and productivity. Satellite remote sensing data for forest structure, i.e., canopy height, is used to constrain simulated forest stand conditions using a look-up table approach to match canopy height distributions. The resulting forest biomass estimates are provided for spatial grids that match REDD+ project boundaries and aim to provide carbon estimates for the criteria described in the IPCC Good Practice Guidelines Tier 3 category. With the increasing availability of forest structure variables derived from high-resolution LIDAR, RADAR, and optical imagery, new methodologies and applications with process-based carbon cycle models are becoming more readily available to inform land management.

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.

Comparing tree foliage biomass models fitted to a multispecies, felled-tree biomass dataset for the United States

Treesearch

Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Philip J. Radtke

2016-01-01

tEstimation of live tree biomass is an important task for both forest carbon accounting and studies of nutri-ent dynamics in forest ecosystems. In this study, we took advantage of an extensive felled-tree database(with 2885 foliage biomass observations) to compare different models and grouping schemes based onphylogenetic and geographic variation for predicting foliage...

Sustainability Impact Assessment of two forest-based bioenergy production systems related to mitigation and adaption to Climate Change

NASA Astrophysics Data System (ADS)

Gartzia-Bengoetxea, Nahia; Arias-González, Ander; Tuomasjukka, Diana

2016-04-01

New forest management strategies are necessary to resist and adapt to Climate Change (CC) and to maintain ecosystem functions such as forest productivity, water storage and biomass production. The increased use of forest-based biomass for energy generation as well as the application of combustion or pyrolysis co-products such as ash or biochar back into forest soils is being suggested as a CC mitigation and adaptation strategy while trying to fulfil the targets of both: (i) Europe 2020 growth strategy in relation to CC and energy sustainability and (ii) EU Action Plan for the Circular Economy. The energy stored in harvested biomass can be released through combustion and used for energy generation to enable national energy security (reduced oil dependence) and the substitution of fossil fuel by renewable biomass can decrease the emission of greenhouse gases.In the end, the wood-ash produced in the process can return to the forest soil to replace the nutrients exported by harvesting. Another way to use biomass in this green circular framework is to pyrolyse it. Pyrolysis of the biomass produce a carbon-rich product (biochar) that can increase carbon sequestration in the soils and liquid and gas co-products of biomass pyrolysis can be used for energy generation or other fuel use thereby offsetting fossil fuel consumption and so avoiding greenhouse gas emissions. Both biomass based energy systems differ in the amount of energy produced, in the co-product (biochar or wood ash) returned to the field, and in societal impacts they have. The Tool for Sustainability Impact Assessment (ToSIA) was used for modelling both energy production systems. ToSIA integrates several different methods, and allows a quantification and objective comparison of economic, environmental and social impacts in a sustainability impact assessment for different decision alternatives/scenarios. We will interpret the results in order to support the bioenergy planning in temperate forests under the light of its implications for different policy aims and concerns.

Spatial and temporal quantification of forest residue volumes and delivered costs

Treesearch

Lucas A. Wells; Woodam Chung; Nathaniel M. Anderson; John S. Hogland

2016-01-01

Growing demand for bioenergy, biofuels, and bioproducts has increased interests in the utilization of biomass residues from forest treatments as feedstock. In areas with limited history of industrial biomass utilization, uncertainties in the quantity, distribution, and cost of biomass production and logistics can hinder the development of new bio-based...

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.

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

PubMed Central

Fischer, Rico; Ensslin, Andreas; Rutten, Gemma; Fischer, Markus; Schellenberger Costa, David; Kleyer, Michael; Hemp, Andreas; Paulick, Sebastian; Huth, Andreas

2015-01-01

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances. PMID:25915854

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.

[Estimation of Shenyang urban forest green biomass].

PubMed

Liu, Chang-fu; He, Xing-yuan; Chen, Wei; Zhao, Gui-ling; Xu, Wen-duo

2007-06-01

Based on ARC/GIS and by using the method of "planar biomass estimation", the green biomass (GB) of Shenyang urban forests was measured. The results demonstrated that the GB per unit area was the highest (3.86 m2.m(-2)) in landscape and relaxation forest, and the lowest (2.27 m2.m(-2)) in ecological and public welfare forest. The GB per unit area in urban forest distribution area was 2.99 m2.m(-2), and that of the whole Shenyang urban area was 0.25 m2.m(-2). The total GB of Shenyang urban forests was about 1.13 x 10(8) m2, among which, subordinated forest, ecological and public welfare forest, landscape and relaxation forest, road forest, and production and management forest accounted for 36.64% , 23.99% , 19.38% , 16.20% and 3.79%, with their GB being 4. 15 x 10(7), 2.72 x 10(7), 2.20 x 10(7), 1.84 x 10(7) and 0.43 x 10(7) m2, respectively. The precision of the method "planar biomass estimation" was 91.81% (alpha = 0.05) by credit test.

Evaluation of Sentinel-1A Data For Above Ground Biomass Estimation in Different Forests in India

NASA Technical Reports Server (NTRS)

Vadrevu, Krishna Prasad

2017-01-01

Use of remote sensing data for mapping and monitoring of forest biomass across large spatial scales can aid in addressing uncertainties in carbon cycle. Earlier, several researchers reported on the use of Synthetic Aperture Radar (SAR) data for characterizing forest structural parameters and the above ground biomass estimation. However, these studies cannot be generalized and the algorithms cannot be applied to all types of forests without additional information on the forest physiognomy, stand structure and biomass characteristics. The radar backscatter signal also saturates as forest parameters such as biomass and the tree height increase. It is also not clear how different polarizations (VV versus VH) impact the backscatter retrievals in different forested regions. Thus, it is important to evaluate the potential of SAR data in different landscapes for characterizing forest structural parameters. In this study, the SAR data from Sentinel-1A has been used to characterize forest structural parameters including the above ground biomass from tropical forests of India. Ground based data on tree density, basal area and above ground biomass data from thirty-eight different forested sites has been collected to relate to SAR data. After the pre-processing of Sentinel 1-A data for radiometric calibration, geo-correction, terrain correction and speckle filtering, the variability in the backscatter signal in relation tree density, basal area and above biomass density has been investigated. Results from the curve fitting approach suggested exponential model between the Sentinel-1A backscatter versus tree density and above ground biomass whereas the relationship was almost linear with the basal area in the VV polarization mode. Of the different parameters, tree density could explain most of the variations in backscatter. Both VV and VH backscatter signals could explain only thirty and thirty three percent of variation in above biomass in different forest sites of India. Results also suggested saturation of the Sentinel-1A backscatter signal around hundred tonnes per hectare for VV polarization and one hundred and forty five tonnes per hectare for VH polarization. The presentation will highlight the above results in addition to potentials and limitations of Sentinel-1A data for retrieving forest structural parameters. Also, background information on different forest types of India, biomass variations and forest type mapping efforts in the region will be presented.

Using Lidar and Radar measurements to constrain predictions of forest ecosystem structure and function.

PubMed

Antonarakis, Alexander S; Saatchi, Sassan S; Chazdon, Robin L; Moorcroft, Paul R

2011-06-01

Insights into vegetation and aboveground biomass dynamics within terrestrial ecosystems have come almost exclusively from ground-based forest inventories that are limited in their spatial extent. Lidar and synthetic-aperture Radar are promising remote-sensing-based techniques for obtaining comprehensive measurements of forest structure at regional to global scales. In this study we investigate how Lidar-derived forest heights and Radar-derived aboveground biomass can be used to constrain the dynamics of the ED2 terrestrial biosphere model. Four-year simulations initialized with Lidar and Radar structure variables were compared against simulations initialized from forest-inventory data and output from a long-term potential-vegtation simulation. Both height and biomass initializations from Lidar and Radar measurements significantly improved the representation of forest structure within the model, eliminating the bias of too many large trees that arose in the potential-vegtation-initialized simulation. The Lidar and Radar initializations decreased the proportion of larger trees estimated by the potential vegetation by approximately 20-30%, matching the forest inventory. This resulted in improved predictions of ecosystem-scale carbon fluxes and structural dynamics compared to predictions from the potential-vegtation simulation. The Radar initialization produced biomass values that were 75% closer to the forest inventory, with Lidar initializations producing canopy height values closest to the forest inventory. Net primary production values for the Radar and Lidar initializations were around 6-8% closer to the forest inventory. Correcting the Lidar and Radar initializations for forest composition resulted in improved biomass and basal-area dynamics as well as leaf-area index. Correcting the Lidar and Radar initializations for forest composition and fine-scale structure by combining the remote-sensing measurements with ground-based inventory data further improved predictions, suggesting that further improvements of structural and carbon-flux metrics will also depend on obtaining reliable estimates of forest composition and accurate representation of the fine-scale vertical and horizontal structure of plant canopies.

Geographical Distribution of Woody Biomass Carbon in Tropical Africa: An Updated Database for 2000 (NDP-055.2007, NDP-055b))

DOE Data Explorer

Gibbs, Holly K. [Center for Sustainability and the Global Environment (SAGE), University of Wisconsin, Madison, WI (USA); Brown, Sandra [Winrock International, Arlington, VA (USA); Olsen, L. M. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory, Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory, Oak Ridge, TN (USA)

2007-09-01

Maps of biomass density are critical inputs for estimating carbon emissions from deforestation and degradation of tropical forests. Brown and Gatson (1996) pioneered methods to use GIS analysis to map forest biomass based on forest inventory data (ndp055). This database is an update of ndp055 (which represent conditions in circa 1980) and accounts for land cover changes occurring up to the year 2000.

Preliminary results of the global forest biomass survey

Treesearch

S. Healey; E. Lindquist

2014-01-01

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

Re-evaluation of forest biomass carbon stocks and lessons from the world's most carbon-dense forests.

PubMed

Keith, Heather; Mackey, Brendan G; Lindenmayer, David B

2009-07-14

From analysis of published global site biomass data (n = 136) from primary forests, we discovered (i) the world's highest known total biomass carbon density (living plus dead) of 1,867 tonnes carbon per ha (average value from 13 sites) occurs in Australian temperate moist Eucalyptus regnans forests, and (ii) average values of the global site biomass data were higher for sampled temperate moist forests (n = 44) than for sampled tropical (n = 36) and boreal (n = 52) forests (n is number of sites per forest biome). Spatially averaged Intergovernmental Panel on Climate Change biome default values are lower than our average site values for temperate moist forests, because the temperate biome contains a diversity of forest ecosystem types that support a range of mature carbon stocks or have a long land-use history with reduced carbon stocks. We describe a framework for identifying forests important for carbon storage based on the factors that account for high biomass carbon densities, including (i) relatively cool temperatures and moderately high precipitation producing rates of fast growth but slow decomposition, and (ii) older forests that are often multiaged and multilayered and have experienced minimal human disturbance. Our results are relevant to negotiations under the United Nations Framework Convention on Climate Change regarding forest conservation, management, and restoration. Conserving forests with large stocks of biomass from deforestation and degradation avoids significant carbon emissions to the atmosphere, irrespective of the source country, and should be among allowable mitigation activities. Similarly, management that allows restoration of a forest's carbon sequestration potential also should be recognized.

Re-evaluation of forest biomass carbon stocks and lessons from the world's most carbon-dense forests

PubMed Central

Keith, Heather; Mackey, Brendan G.; Lindenmayer, David B.

2009-01-01

From analysis of published global site biomass data (n = 136) from primary forests, we discovered (i) the world's highest known total biomass carbon density (living plus dead) of 1,867 tonnes carbon per ha (average value from 13 sites) occurs in Australian temperate moist Eucalyptus regnans forests, and (ii) average values of the global site biomass data were higher for sampled temperate moist forests (n = 44) than for sampled tropical (n = 36) and boreal (n = 52) forests (n is number of sites per forest biome). Spatially averaged Intergovernmental Panel on Climate Change biome default values are lower than our average site values for temperate moist forests, because the temperate biome contains a diversity of forest ecosystem types that support a range of mature carbon stocks or have a long land-use history with reduced carbon stocks. We describe a framework for identifying forests important for carbon storage based on the factors that account for high biomass carbon densities, including (i) relatively cool temperatures and moderately high precipitation producing rates of fast growth but slow decomposition, and (ii) older forests that are often multiaged and multilayered and have experienced minimal human disturbance. Our results are relevant to negotiations under the United Nations Framework Convention on Climate Change regarding forest conservation, management, and restoration. Conserving forests with large stocks of biomass from deforestation and degradation avoids significant carbon emissions to the atmosphere, irrespective of the source country, and should be among allowable mitigation activities. Similarly, management that allows restoration of a forest's carbon sequestration potential also should be recognized. PMID:19553199

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

PubMed

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

Quantifying the state and the change of the World's forests is crucial because of their ecological, social and economic value. Concerning their ecological importance, forests provide important feedbacks on the global carbon, energy and water cycles. In addition to their influence on albedo and evapotranspiration, they have the potential to sequester atmospheric carbon dioxide and thus to mitigate global warming. The current state and inter-annual variability of forest carbon stocks remain relatively unexplored, but remote sensing can serve to overcome this shortcoming. While for the tropics wall-to-wall estimates of above-ground biomass have been recently published, up to now there was a lack of similar products covering boreal and temperate forests. Recently, estimates of forest growing stock volume (GSV) were derived from ENVISAT ASAR C-band data for latitudes above 30° N. Utilizing a wood density and a biomass compartment database, a forest carbon density map covering North-America, Europe and Asia with 0.01° resolution could be derived out of this dataset. Allometric functions between stem, branches, root and foliage biomass were fitted and applied for different leaf types (broadleaf, needleleaf deciduous, needleleaf evergreen forest). Additionally, this method enabled uncertainty estimation of the resulting carbon density map. Intercomparisons with inventory-based biomass products in Russia, Europe and the USA proved the high accuracy of this approach at a regional scale (r2 = 0.70 - 0.90). Based on the final biomass map, the forest carbon stocks and densities (excluding understorey vegetation) for three biomes were estimated across three continents. While 40.7 ± 15.7 Gt of carbon were found to be stored in boreal forests, temperate broadleaf/mixed forests and temperate conifer forests contain 24.5 ± 9.4 Gt(C) and 14.5 ± 4.8 Gt(C), respectively. In terms of carbon density, most of the carbon per area is stored in temperate conifer (62.1 ± 20.7 Mg(C)/ha(Forest)) and broadleaf/mixed forests (58.0 ± 22.1 Mg(C)/ha(Forest)), whereas boreal forests have a carbon density of only 40.0 ± 15.4 Mg(C)/ha(Forest). While European forest carbon stocks are relatively small, the carbon density is higher compared to the other continents. The derived biomass map substantially improves the knowledge on the current carbon stocks of the northern-hemispheric boreal and temperate forests, serving as a new benchmark for spatially explicit and consistent biomass mapping with moderate spatial resolution. This product can be of great value for global carbon cycle models as well as national carbon monitoring systems. Further investigations concentrate on improving biomass parameterizations and representations in such kind of models. The presented map will help to improve the simulation of biomass spatial patterns and variability and enables identifying the dominant influential factors like climatic conditions and disturbances.

An empirical, integrated forest biomass monitoring system

NASA Astrophysics Data System (ADS)

Kennedy, Robert E.; Ohmann, Janet; Gregory, Matt; Roberts, Heather; Yang, Zhiqiang; Bell, David M.; Kane, Van; Hughes, M. Joseph; Cohen, Warren B.; Powell, Scott; Neeti, Neeti; Larrue, Tara; Hooper, Sam; Kane, Jonathan; Miller, David L.; Perkins, James; Braaten, Justin; Seidl, Rupert

2018-02-01

The fate of live forest biomass is largely controlled by growth and disturbance processes, both natural and anthropogenic. Thus, biomass monitoring strategies must characterize both the biomass of the forests at a given point in time and the dynamic processes that change it. Here, we describe and test an empirical monitoring system designed to meet those needs. Our system uses a mix of field data, statistical modeling, remotely-sensed time-series imagery, and small-footprint lidar data to build and evaluate maps of forest biomass. It ascribes biomass change to specific change agents, and attempts to capture the impact of uncertainty in methodology. We find that: • A common image framework for biomass estimation and for change detection allows for consistent comparison of both state and change processes controlling biomass dynamics. • Regional estimates of total biomass agree well with those from plot data alone. • The system tracks biomass densities up to 450-500 Mg ha-1 with little bias, but begins underestimating true biomass as densities increase further. • Scale considerations are important. Estimates at the 30 m grain size are noisy, but agreement at broad scales is good. Further investigation to determine the appropriate scales is underway. • Uncertainty from methodological choices is evident, but much smaller than uncertainty based on choice of allometric equation used to estimate biomass from tree data. • In this forest-dominated study area, growth and loss processes largely balance in most years, with loss processes dominated by human removal through harvest. In years with substantial fire activity, however, overall biomass loss greatly outpaces growth. Taken together, our methods represent a unique combination of elements foundational to an operational landscape-scale forest biomass monitoring program.

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

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

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

2012-04-01

Sound policy recommendations relating to the role of forest management in mitigating atmospheric carbon dioxide (CO{sub 2}) depend upon establishing accurate methodologies for quantifying forest carbon pools for large tracts of land that can be dynamically updated over time. Light Detection and Ranging (LiDAR) remote sensing is a promising technology for achieving accurate estimates of aboveground biomass and thereby carbon pools; however, not much is known about the accuracy of estimating biomass change and carbon flux from repeat LiDAR acquisitions containing different data sampling characteristics. In this study, discrete return airborne LiDAR data was collected in 2003 and 2009 acrossmore » {approx}20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho, USA. Forest inventory plots, established via a random stratified sampling design, were established and sampled in 2003 and 2009. The Random Forest machine learning algorithm was used to establish statistical relationships between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level. Over this 6-year period, we found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). In these non-harvested areas, we found a significant difference in biomass increase among forest successional stages, with a higher biomass increase in mature and old forest compared to stand initiation and young forest. Approximately 20% of the landscape had been disturbed by harvest activities during the six-year time period, representing a biomass loss of >70 Mg/ha in these areas. During the study period, these harvest activities outweighed growth at the landscape scale, resulting in an overall loss in aboveground carbon at this site. The 30-fold increase in sampling density between the 2003 and 2009 did not affect the biomass estimates. Overall, LiDAR data coupled with field reference data offer a powerful method for calculating pools and changes in aboveground carbon in forested systems. The results of our study suggest that multitemporal LiDAR-based approaches are likely to be useful for high quality estimates of aboveground carbon change in conifer forest systems.« less

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

Treesearch

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

2015-01-01

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

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.

Retrieval of forest biomass for tropical deciduous mixed forest using ALOS PALSAR mosaic imagery and field plot data

NASA Astrophysics Data System (ADS)

Ningthoujam, Ramesh K.; Joshi, P. K.; Roy, P. S.

2018-07-01

Tropical forest is an important ecosystem rich in biodiversity and structural complexity with high woody biomass content. Longer wavelength radar data at L-band sensor provides improved forest biomass (AGB) information due to its higher penetration level and sensitivity to canopy structure. The study presents a regression based woody biomass estimation for tropical deciduous mixed forest dominated by Shorea robusta using ALOS PALSAR mosaic (HH, HV) and field data at the lower Himalayan belt of Northern India. For the purpose of understanding the scattering mechanisms at L-band from this forest type, Michigan Microwave Canopy Scattering model (MIMICS-I) was parameterized with field data to simulate backscatter across polarization and incidence range. Regression analysis between field measured forest biomass and L-band backscatter data from PALSAR mosaic show retrieval of woody biomass up to 100 Mg ha-1 with error between 92 and 94 Mg ha-1 and coefficient of determination (r2) between 0.53 and 0.55 for HH and HH + HV polarized channel at 0.25 ha resolution. This positive relationship could be due to strong volume scattering from ground/trunk interaction at HH-polarized while in combination with direct canopy scattering for HV-polarization at ALOS specific incidence angles as predicted by MIMICS-I model. This study has found that L-band SAR data from currently ALOS-1/-2 and upcoming joint NASA-ISRO SAR (NISAR) are suitable for mapping forest biomass ≤100 Mg ha-1 at 25 m resolution in far incidence range in dense deciduous mixed forest of Northern India.

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 non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery.

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...

Jointly optimizing selection of fuel treatments and siting of forest biomass-based energy production facilities for landscape-scale fire hazard reduction.

Treesearch

Peter J. Daugherty; Jeremy S. Fried

2007-01-01

Landscape-scale fuel treatments for forest fire hazard reduction potentially produce large quantities of material suitable for biomass energy production. The analytic framework FIA BioSum addresses this situation by developing detailed data on forest conditions and production under alternative fuel treatment prescriptions, and computes haul costs to alternative sites...

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

NASA Technical Reports Server (NTRS)

Nelson, Ross F.

2010-01-01

Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.

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.

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

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

Mobini, Mahdi; Sowlati, T.; Sokhansanj, Shahabaddine

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

Forest-Observation-System.net - towards a global in-situ data repository for biomass datasets validation

NASA Astrophysics Data System (ADS)

Shchepashchenko, D.; Chave, J.; Phillips, O. L.; Davies, S. J.; Lewis, S. L.; Perger, C.; Dresel, C.; Fritz, S.; Scipal, K.

2017-12-01

Forest monitoring is high on the scientific and political agenda. Global measurements of forest height, biomass and how they change with time are urgently needed as essential climate and ecosystem variables. The Forest Observation System - FOS (http://forest-observation-system.net/) is an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. FOS aims to link the Remote Sensing (RS) community with ecologists who measure forest biomass and estimating biodiversity in the field for a common benefit. The benefit of FOS for the RS community is the partnering of the most established teams and networks that manage permanent forest plots globally; to overcome data sharing issues and introduce a standard biomass data flow from tree level measurement to the plot level aggregation served in the most suitable form for the RS community. Ecologists benefit from the FOS with improved access to global biomass information, data standards, gap identification and potential improved funding opportunities to address the known gaps and deficiencies in the data. FOS closely collaborate with the Center for Tropical Forest Science -CTFS-ForestGEO, the ForestPlots.net (incl. RAINFOR, AfriTRON and T-FORCES), AusCover, Tropical managed Forests Observatory and the IIASA network. FOS is an open initiative with other networks and teams most welcome to join. The online database provides open access for both metadata (e.g. who conducted the measurements, where and which parameters) and actual data for a subset of plots where the authors have granted access. A minimum set of database values include: principal investigator and institution, plot coordinates, number of trees, forest type and tree species composition, wood density, canopy height and above ground biomass of trees. Plot size is 0.25 ha or large. The database will be essential for validating and calibrating satellite observations and various models.

The allometry of coarse root biomass: log-transformed linear regression or nonlinear regression?

PubMed

Lai, Jiangshan; Yang, Bo; Lin, Dunmei; Kerkhoff, Andrew J; Ma, Keping

2013-01-01

Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.

Assessing Public Preferences for Forest Biomass Based Energy in the Southern United States

Treesearch

Andres Susaeta; Janaki Alavalapati; Pankaj Lal; Jagannadha R Matta; Evan Mercer

2010-01-01

This article investigated public preferences for forest biomass based liquid biofuels, particularly ethanol blends of 10% (E10) and 85% (E85). We conducted a choice experiment study in three southern states in the United States: Arkansas, Florida, and Virginia. Reducing atmospheric CO2, decreasing risk of wildfires and pest outbreaks, and enhancing biodiversity were...

Changes in forest biomass and linkage to climate and forest disturbances over Northeastern China.

PubMed

Zhang, Yuzhen; Liang, Shunlin

2014-08-01

The forests of northeastern China store nearly half of the country's total biomass carbon stocks. In this study, we investigated the changes in forest biomass by using satellite observations and found that a significant increase in forest biomass took place between 2001 and 2010. To determine the possible reasons for this change, several statistical methods were used to analyze the correlations between forest biomass dynamics and forest disturbances (i.e. fires, insect damage, logging, and afforestation and reforestation), climatic factors, and forest development. Results showed that forest development was the most important contributor to the increasing trend of forest biomass from 2001 to 2010, and climate controls were the secondary important factor. Among the four types of forest disturbance considered in this study, forest recovery from fires, and afforestation and reforestation during the past few decades played an important role in short-term biomass dynamics. This study provided observational evidence and valuable information for the relationships between forest biomass and climate as well as forest disturbances. © 2014 John Wiley & Sons Ltd.

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

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

PubMed

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

2014-12-01

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

Assessing Earthquake-Induced Tree Mortality in Temperate Forest Ecosystems: A Case Study from Wenchuan, China

DOE PAGES

Zeng, Hongcheng; Lu, Tao; Jenkins, Hillary; ...

2016-03-17

Earthquakes can produce significant tree mortality, and consequently affect regional carbon dynamics. Unfortunately, detailed studies quantifying the influence of earthquake on forest mortality are currently rare. The committed forest biomass carbon loss associated with the 2008 Wenchuan earthquake in China is assessed by a synthetic approach in this study that integrated field investigation, remote sensing analysis, empirical models and Monte Carlo simulation. The newly developed approach significantly improved the forest disturbance evaluation by quantitatively defining the earthquake impact boundary and detailed field survey to validate the mortality models. Based on our approach, a total biomass carbon of 10.9 Tg·C wasmore » lost in Wenchuan earthquake, which offset 0.23% of the living biomass carbon stock in Chinese forests. Tree mortality was highly clustered at epicenter, and declined rapidly with distance away from the fault zone. It is suggested that earthquakes represent a signif icant driver to forest carbon dynamics, and the earthquake-induced biomass carbon loss should be included in estimating forest carbon budgets.« less

Assessing Earthquake-Induced Tree Mortality in Temperate Forest Ecosystems: A Case Study from Wenchuan, China

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

Zeng, Hongcheng; Lu, Tao; Jenkins, Hillary

Earthquakes can produce significant tree mortality, and consequently affect regional carbon dynamics. Unfortunately, detailed studies quantifying the influence of earthquake on forest mortality are currently rare. The committed forest biomass carbon loss associated with the 2008 Wenchuan earthquake in China is assessed by a synthetic approach in this study that integrated field investigation, remote sensing analysis, empirical models and Monte Carlo simulation. The newly developed approach significantly improved the forest disturbance evaluation by quantitatively defining the earthquake impact boundary and detailed field survey to validate the mortality models. Based on our approach, a total biomass carbon of 10.9 Tg·C wasmore » lost in Wenchuan earthquake, which offset 0.23% of the living biomass carbon stock in Chinese forests. Tree mortality was highly clustered at epicenter, and declined rapidly with distance away from the fault zone. It is suggested that earthquakes represent a signif icant driver to forest carbon dynamics, and the earthquake-induced biomass carbon loss should be included in estimating forest carbon budgets.« less

Application of Remote Sensing for Forest Management in Nepal

NASA Astrophysics Data System (ADS)

Bajracharya, B.; Matin, M. A.

2016-12-01

Large area of the Hindu Kush Himalayan (HKH) region is covered by forest that is playing a vital role to address the challenges of climate change and livelihood options for a growing population. Effective management of forest cover needs establishment of regular monitoring system for forest. Supporting REDD assessment needs reliable baseline assessment of forest biomass and its monitoring at multiple scale. Adaptation of forest to climate change needs understanding vulnerability of forests and dependence of local communities on these forest. We present here different forest monitoring products developed under the SERVIR-Himalaya programme to address these issues. Landsat 30 meter images were used for decadal land cover change assessment and annual forest change hotspot monitoring. Methodology developed for biomass estimation at national and sub-national level biomass estimation. Decision support system was developed for analysis of forest vulnerability and dependence and selection of adaptation options based on resource availability. These products are forming the basis for development of an integrated system that will be very useful for comprehensive forest monitoring and long term strategy development for sustainable forest management.

Global-scale patterns of nutrient density and partitioning in forests in relation to climate.

PubMed

Zhang, Kerong; Song, Conghe; Zhang, Yulong; Dang, Haishan; Cheng, Xiaoli; Zhang, Quanfa

2018-01-01

Knowledge of nutrient storage and partitioning in forests is imperative for ecosystem models and ecological theory. Whether the nutrients (N, P, K, Ca, and Mg) stored in forest biomass and their partitioning patterns vary systematically across climatic gradients remains unknown. Here, we explored the global-scale patterns of nutrient density and partitioning using a newly compiled dataset including 372 forest stands. We found that temperature and precipitation were key factors driving the nutrients stored in living biomass of forests at global scale. The N, K, and Mg stored in living biomass tended to be greater in increasingly warm climates. The mean biomass N density was 577.0, 530.4, 513.2, and 336.7 kg/ha for tropical, subtropical, temperate, and boreal forests, respectively. Around 76% of the variation in biomass N density could be accounted by the empirical model combining biomass density, phylogeny (i.e., angiosperm, gymnosperm), and the interaction of mean annual temperature and precipitation. Climate, stand age, and biomass density significantly affected nutrients partitioning at forest community level. The fractional distribution of nutrients to roots decreased significantly with temperature, suggesting that forests in cold climates allocate greater nutrients to roots. Gymnosperm forests tended to allocate more nutrients to leaves as compared with angiosperm forests, whereas the angiosperm forests distributed more nutrients in stems. The nutrient-based Root:Shoot ratios (R:S), averaged 0.30 for R:S N , 0.36 for R:S P , 0.32 for R:S K , 0.27 for R:S Ca , and 0.35 for R:S Mg , respectively. The scaling exponents of the relationships describing root nutrients as a function of shoot nutrients were more than 1.0, suggesting that as nutrient allocated to shoot increases, nutrient allocated to roots increases faster than linearly with nutrient in shoot. Soil type significantly affected the total N, P, K, Ca, and Mg stored in living biomass of forests, and the Acrisols group displayed the lowest P, K, Ca, and Mg. © 2017 John Wiley & Sons Ltd.

Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

2017-12-01

Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

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.

Hydrothermal treatment followed by enzymatic hydrolysis and hydrothermal carbonization as means to valorise agro- and forest-based biomass residues.

PubMed

Wikberg, Hanne; Grönqvist, Stina; Niemi, Piritta; Mikkelson, Atte; Siika-Aho, Matti; Kanerva, Heimo; Käsper, Andres; Tamminen, Tarja

2017-07-01

The suitability of several abundant but underutilized agro and forest based biomass residues for hydrothermal treatment followed by enzymatic hydrolysis as well as for hydrothermal carbonization was studied. The selected approaches represent simple biotechnical and thermochemical treatment routes suitable for wet biomass. Based on the results, the hydrothermal pre-treatment followed by enzymatic hydrolysis seemed to be most suitable for processing of carbohydrate rich corn leaves, corn stover, wheat straw and willow. High content of thermally stable components (i.e. lignin) and low content of ash in the biomass were advantageous for hydrothermal carbonization of grape pomace, coffee cake, Scots pine bark and willow. Copyright © 2017 Elsevier Ltd. All rights reserved.

Live tree carbon stock equivalence of fire and fuels extension to the Forest Vegetation Simulator and Forest Inventory and Analysis approaches

Treesearch

James E. Smith; Coeli M. Hoover

2017-01-01

The carbon reports in the Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) provide two alternate approaches to carbon estimates for live trees (Rebain 2010). These are (1) the FFE biomass algorithms, which are volumebased biomass equations, and (2) the Jenkins allometric equations (Jenkins and others 2003), which are diameter based. Here, we...

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...

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-...

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.

ROE Carbon Storage - Forest Biomass

EPA Pesticide Factsheets

This polygon dataset depicts the density of forest biomass in counties across the United States, in terms of metric tons of carbon per square mile of land area. These data were provided in spreadsheet form by the U.S. Department of Agriculture (USDA) Forest Service. To produce the Web mapping application, EPA joined the spreadsheet with a shapefile of U.S. county (and county equivalent) boundaries downloaded from the U.S. Census Bureau. EPA calculated biomass density based on the area of each county polygon. These data sets were converted into a single polygon feature class inside a file geodatabase.

Validating Community-Led Forest Biomass Assessments.

PubMed

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

2015-01-01

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

Validating Community-Led Forest Biomass Assessments

PubMed Central

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

2015-01-01

The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha-1, which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees. PMID:26126186

Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts.

PubMed

Longo, Marcos; Knox, Ryan G; Levine, Naomi M; Alves, Luciana F; Bonal, Damien; Camargo, Plinio B; Fitzjarrald, David R; Hayek, Matthew N; Restrepo-Coupe, Natalia; Saleska, Scott R; da Silva, Rodrigo; Stark, Scott C; Tapajós, Raphael P; Wiedemann, Kenia T; Zhang, Ke; Wofsy, Steven C; Moorcroft, Paul R

2018-05-22

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km 2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

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 AGB retrieval showed R2 value of 0.5, RMSE of 62.73 (t ha-1) and a percent accuracy of 51%. TSI based PolInSAR inversion modeling showed the most accurate result for forest height estimation. The correlation between the field measured forest height and the estimated tree height using TSI technique is 62% with an average accuracy of 91.56% and RMSE of 2.28 m. The study suggested that PolInSAR coherence based modeling approach has significant potential for retrieval of forest biophysical parameters.

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

PubMed

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

2013-07-01

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

Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

NASA Technical Reports Server (NTRS)

Fatoyinbo, Temilola E.

2010-01-01

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

Rapid assessment of U.S. forest and soil organic carbon storage and forest biomass carbon-sequestration capacity

USGS Publications Warehouse

Sundquist, Eric T.; Ackerman, Katherine V.; Bliss, Norman B.; Kellndorfer, Josef M.; Reeves, Matt C.; Rollins, Matthew G.

2009-01-01

This report provides results of a rapid assessment of biological carbon stocks and forest biomass carbon sequestration capacity in the conterminous United States. Maps available from the U.S. Department of Agriculture are used to calculate estimates of current organic carbon storage in soils (73 petagrams of carbon, or PgC) and forest biomass (17 PgC). Of these totals, 3.5 PgC of soil organic carbon and 0.8 PgC of forest biomass carbon occur on lands managed by the U.S. Department of the Interior (DOI). Maps of potential vegetation are used to estimate hypothetical forest biomass carbon sequestration capacities that are 3–7 PgC higher than current forest biomass carbon storage in the conterminous United States. Most of the estimated hypothetical additional forest biomass carbon sequestration capacity is accrued in areas currently occupied by agriculture and development. Hypothetical forest biomass carbon sequestration capacities calculated for existing forests and woodlands are within ±1 PgC of estimated current forest biomass carbon storage. Hypothetical forest biomass sequestration capacities on lands managed by the DOI in the conterminous United States are 0–0.4 PgC higher than existing forest biomass carbon storage. Implications for forest and other land management practices are not considered in this report. Uncertainties in the values reported here are large and difficult to quantify, particularly for hypothetical carbon sequestration capacities. Nevertheless, this rapid assessment helps to frame policy and management discussion by providing estimates that can be compared to amounts necessary to reduce predicted future atmospheric carbon dioxide levels.

Proxies for soil organic carbon derived from remote sensing

NASA Astrophysics Data System (ADS)

Rasel, S. M. M.; Groen, T. A.; Hussin, Y. A.; Diti, I. J.

2017-07-01

The possibility of carbon storage in soils is of interest because compared to vegetation it contains more carbon. Estimation of soil carbon through remote sensing based techniques can be a cost effective approach, but is limited by available methods. This study aims to develop a model based on remotely sensed variables (elevation, forest type and above ground biomass) to estimate soil carbon stocks. Field observations on soil organic carbon, species composition, and above ground biomass were recorded in the subtropical forest of Chitwan, Nepal. These variables were also estimated using LiDAR data and a WorldView 2 image. Above ground biomass was estimated from the LiDAR image using a novel approach where the image was segmented to identify individual trees, and for these trees estimates of DBH and Height were made. Based on AIC (Akaike Information Criterion) a regression model with above ground biomass derived from LiDAR data, and forest type derived from WorldView 2 imagery was selected to estimate soil organic carbon (SOC) stocks. The selected model had a coefficient of determination (R2) of 0.69. This shows the scope of estimating SOC with remote sensing derived variables in sub-tropical forests.

Carbon Uptake and Storage in Old-Growth and Second-Growth Forests in Central Vermont

NASA Astrophysics Data System (ADS)

Lloyd, A. H.; Weisser, O.

2013-12-01

Managing forests towards the goal of maximizing carbon uptake and storage provides an important tool for climate change mitigation. There is significant spatial and temporal variation among forests, even within an ecosystem type, in annual uptake and storage of carbon. Understanding the causes for that variation is important in refining management practices and restoration goals that promote carbon storage. We explore the variation in carbon storage and uptake among forests differing in age in central Vermont, comparing young, intermediate-aged, and old-growth forests. We generally expected that younger forests would have a higher annual uptake of carbon than older forests. Significant uncertainty exists, however, about the temporal trajectory from a young, rapidly growing forest to an old-growth forest that may be in a steady-state, with no net uptake of carbon. Within each forest, we compare differences among functional groups of species (e.g., hardwoods versus softwoods) in contribution to overall forest carbon uptake and storage. Our study sites include an old-growth hemlock/mixed hardwood forest that has not been directly affected by human activities, and which contains trees upwards of 350 years old; a 130-year-old mixed hardwood forest that has recolonized former pasture land; and a 90-year-old mixed hardwood forest on formerly agricultural floodplain land. Carbon storage in live and dead biomass pools was estimated from allometric equations, based on repeated measurements of tree diameters in permanently marked study plots. Historical patterns of carbon storage in living biomass were estimated by reconstructing tree diameter from measured increment cores, and then estimating the living biomass in each year. As expected, the old-growth forest stored almost twice the C in live biomass as the two second-growth forests, which stored equivalent amounts of carbon, despite the difference in age. Dead biomass was a larger pool of C in the old-growth forest than in the two second-growth forests, but still contained only a quarter of the C of the live biomass pool. Both repeated measurements of tree diameters and tree-ring reconstructions of historical patterns of C accumulation suggested that all three forests were continuing to accumulate C in biomass, but the rate differed substantially among sites, with the lowest rates of accumulation occurring in the old-growth forest. Within the old-growth forest, the fastest rates of biomass accumulation occurred in younger hardwoods, which appear to have colonized old canopy gaps in the mid-1800s. Together, these results are consistent with prior research suggesting that C continues to accumulate in temperate forests for hundreds of years. Both species differences and forest age, however, have a significant effect on C uptake and storage.

Tree allometry and improved estimation of carbon stocks and balance in tropical forests.

PubMed

Chave, J; Andalo, C; Brown, S; Cairns, M A; Chambers, J Q; Eamus, D; Fölster, H; Fromard, F; Higuchi, N; Kira, T; Lescure, J-P; Nelson, B W; Ogawa, H; Puig, H; Riéra, B; Yamakura, T

2005-08-01

Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees >or= 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5-6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle.

[Biomass allometric equations of nine common tree species in an evergreen broadleaved forest of subtropical China].

PubMed

Zuo, Shu-di; Ren, Yin; Weng, Xian; Ding, Hong-feng; Luo, Yun-jian

2015-02-01

Biomass allometric equation (BAE) considered as a simple and reliable method in the estimation of forest biomass and carbon was used widely. In China, numerous studies focused on the BAEs for coniferous forest and pure broadleaved forest, and generalized BAEs were frequently used to estimate the biomass and carbon of mixed broadleaved forest, although they could induce large uncertainty in the estimates. In this study, we developed the species-specific and generalized BAEs using biomass measurement for 9 common broadleaved trees (Castanopsis fargesii, C. lamontii, C. tibetana, Lithocarpus glaber, Sloanea sinensis, Daphniphyllum oldhami, Alniphyllum fortunei, Manglietia yuyuanensis, and Engelhardtia fenzlii) of subtropical evergreen broadleaved forest, and compared differences in species-specific and generalized BAEs. The results showed that D (diameter at breast height) was a better independent variable in estimating the biomass of branch, leaf, root, aboveground section and total tree than a combined variable (D2 H) of D and H (tree height) , but D2H was better than D in estimating stem biomass. R2 (coefficient of determination) values of BAEs for 6 species decreased when adding H as the second independent variable into D- only BAEs, where R2 value for S. sinensis decreased by 5.6%. Compared with generalized D- and D2H-based BAEs, standard errors of estimate (SEE) of BAEs for 8 tree species decreased, and similar decreasing trend was observed for different components, where SEEs of the branch decreased by 13.0% and 20.3%. Therefore, the biomass carbon storage and its dynamic estimates were influenced largely by tree species and model types. In order to improve the accuracy of the estimates of biomass and carbon, we should consider the differences in tree species and model types.

The woody biomass resource of Alabama

Treesearch

James F. Jr. Rosson; Charles E. Thomas

1986-01-01

Presents findings and analysis of woody biomass based on the fifth forest survey of Alabama (1982). The green weights by component-total, merchantable, residual, sapling, and rough and rotten-are presented by various categories such as ownership, forest type, physiographic class, size class, basal area, species, and age. After-harvest residual is also presented and...

Nocturnal insect availability in bottomland hardwood forests managed for wildlife in the Mississippi Alluvial Valley

USGS Publications Warehouse

Loraine Ketzler,; Christopher Comer,; Twedt, Daniel J.

2017-01-01

Silviculture used to alter forest structure and thereby enhance wildlife habitat has been advocated for bottomland hardwood forest management on public conservation lands in the Mississippi Alluvial Valley. Although some songbirds respond positively to these management actions to attain desired forest conditions for wildlife, the response of other species, is largely unknown. Nocturnal insects are a primary prey base for bats, thereby influencing trophic interactions within hardwood forests. To better understand how silviculture influences insect availability for bats, we conducted vegetation surveys and sampled insect biomass within silviculturally treated bottomland hardwood forest stands. We used passive blacklight traps to capture nocturnal flying insects in 64 treated and 64 untreated reference stands, located on 15 public conservation areas in Arkansas, Louisiana, and Mississippi. Dead wood and silvicultural treatments were positively associated with greater biomass of macro-Lepidoptera, macro-Coleoptera, and all insect taxa combined. Biomass of micro-Lepidoptera was negatively associated with silvicultural treatment but comprised only a small proportion of total biomass. Understanding the response of nocturnal insects to wildlife-forestry silviculture provides insight for prescribed silvicultural management affecting bat species.

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

NASA Astrophysics Data System (ADS)

Saleh, Dalia El Sayed Abbas Mohamed

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

Multi-Scale Mapping of Vegetation Biomass

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

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

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

NASA Technical Reports Server (NTRS)

Laurance, William F.

2004-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

The Arctic-Boreal zone is known be warming at an accelerated rate relative to other biomes. The taiga or boreal forest covers over 16 x106 km2 of Arctic North America, Scandinavia, and Eurasia. A large part of the northern Boreal forests are in Russia's Siberia, as area with recent accelerated climate warming. During the last two decades we have been working on characterization of boreal forests in north-central Siberia using field and satellite measurements. We have published results of circumpolar biomass using field plots, airborne (PALS, ACTM) and spaceborne (GLAS) lidar data with ASTER DEM, LANDSAT and MODIS land cover classification, MODIS burned area and WWF's ecoregion map. Researchers from ESA and Russia have also been working on biomass (or growing stock) mapping in Siberia. For example, they developed a pan-boreal growing stock volume map at 1-kilometer scale using hyper-temporal ENVISAT ASAR ScanSAR backscatter data. Using the annual PALSAR mosaics from 2007 to 2010 growing stock volume maps were retrieved based on a supervised random forest regression approach. This method is being used in the ESA/Russia ZAPAS project for Central Siberia Biomass mapping. Spatially specific biomass maps of this region at higher resolution are desired for carbon cycle and climate change studies. In this study, our work focused on improving resolution ( 50 m) of a biomass map based on PALSAR L-band data and Landsat Vegetation Canopy Fraction products. GLAS data were carefully processed and screened using land cover classification, local slope, and acquisition dates. The biomass at remaining footprints was estimated using a model developed from field measurements at GLAS footprints. The GLAS biomass samples were then aggregated into 1 Mg/ha bins of biomass and mean VCF and PALSAR backscatter and textures were calculated for each of these biomass bins. The resulted biomass/signature data was used to train a random forest model for biomass mapping of entire region from 50oN to 75oN, and 80oE to 145oE. The spatial patterns of the new biomass map is much better than the previous maps due to spatially specific mapping in high resolution. The uncertainties of field/GLAS and GLAS/imagery models were investigated using bootstrap procedure, and the final biomass map was compared with previous maps.

External benefits of biomass-e in Spain: an economic valuation.

PubMed

Soliño, Mario

2010-03-01

This article analyses the willingness to pay for a program that promotes the production of electricity from forest biomass, instead of that based on fossil fuels. The program decreases greenhouse gas emissions, reduces the pressure on non-renewable resources, lowers the risk of summer forest fires, creates employment in rural areas. Results from a choice experiment show that consumers are willing to pay a higher price for electricity in order to obtain the external benefits of the substitution. Respondents attach a higher value to programs that decrease the pressure of non-renewable resources and the risk of forest fires. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

DOE PAGES

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard; ...

2018-01-02

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

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

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Comparison of interferometric and stereo-radargrammetric 3D metrics in mapping of forest resources

NASA Astrophysics Data System (ADS)

Karila, K.; Karjalainen, M.; Yu, X.; Vastaranta, M.; Holopainen, M.; Hyyppa, J.

2015-04-01

Accurate forest resources maps are needed in diverse applications ranging from the local forest management to the global climate change research. In particular, it is important to have tools to map changes in forest resources, which helps us to understand the significance of the forest biomass changes in the global carbon cycle. In the task of mapping changes in forest resources for wide areas, Earth Observing satellites could play the key role. In 2013, an EU/FP7-Space funded project "Advanced_SAR" was started with the main objective to develop novel forest resources mapping methods based on the fusion of satellite based 3D measurements and in-situ field measurements of forests. During the summer 2014, an extensive field surveying campaign was carried out in the Evo test site, Southern Finland. Forest inventory attributes of mean tree height, basal area, mean stem diameter, stem volume, and biomass, were determined for 91 test plots having the size of 32 by 32 meters (1024 m2). Simultaneously, a comprehensive set of satellite and airborne data was collected. Satellite data also included a set of TanDEM-X (TDX) and TerraSAR-X (TSX) X-band synthetic aperture radar (SAR) images, suitable for interferometric and stereo-radargrammetric processing to extract 3D elevation data representing the forest canopy. In the present study, we compared the accuracy of TDX InSAR and TSX stereo-radargrammetric derived 3D metrics in forest inventory attribute prediction. First, 3D data were extracted from TDX and TSX images. Then, 3D data were processed as elevations above the ground surface (forest canopy height values) using an accurate Digital Terrain Model (DTM) based on airborne laser scanning survey. Finally, 3D metrics were calculated from the canopy height values for each test plot and the 3D metrics were compared with the field reference data. The Random Forest method was used in the forest inventory attributes prediction. Based on the results InSAR showed slightly better performance in forest attribute (i.e. mean tree height, basal area, mean stem diameter, stem volume, and biomass) prediction than stereo-radargrammetry. The results were 20.1% and 28.6% in relative root mean square error (RMSE) for biomass prediction, for TDX and TSX respectively.

Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks.

PubMed

Mukul, Sharif A; Herbohn, John; Firn, Jennifer

2016-03-08

In the tropics, shifting cultivation has long been attributed to large scale forest degradation, and remains a major source of uncertainty in forest carbon accounting. In the Philippines, shifting cultivation, locally known as kaingin, is a major land-use in upland areas. We measured the distribution and recovery of aboveground biomass carbon along a fallow gradient in post-kaingin secondary forests in an upland area in the Philippines. We found significantly higher carbon in the aboveground total biomass and living woody biomass in old-growth forest, while coarse dead wood biomass carbon was higher in the new fallow sites. For young through to the oldest fallow secondary forests, there was a progressive recovery of biomass carbon evident. Multivariate analysis indicates patch size as an influential factor in explaining the variation in biomass carbon recovery in secondary forests after shifting cultivation. Our study indicates secondary forests after shifting cultivation are substantial carbon sinks and that this capacity to store carbon increases with abandonment age. Large trees contribute most to aboveground biomass. A better understanding of the relative contribution of different biomass sources in aboveground total forest biomass, however, is necessary to fully capture the value of such landscapes from forest management, restoration and conservation perspectives.

Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks

PubMed Central

Mukul, Sharif A.; Herbohn, John; Firn, Jennifer

2016-01-01

In the tropics, shifting cultivation has long been attributed to large scale forest degradation, and remains a major source of uncertainty in forest carbon accounting. In the Philippines, shifting cultivation, locally known as kaingin, is a major land-use in upland areas. We measured the distribution and recovery of aboveground biomass carbon along a fallow gradient in post-kaingin secondary forests in an upland area in the Philippines. We found significantly higher carbon in the aboveground total biomass and living woody biomass in old-growth forest, while coarse dead wood biomass carbon was higher in the new fallow sites. For young through to the oldest fallow secondary forests, there was a progressive recovery of biomass carbon evident. Multivariate analysis indicates patch size as an influential factor in explaining the variation in biomass carbon recovery in secondary forests after shifting cultivation. Our study indicates secondary forests after shifting cultivation are substantial carbon sinks and that this capacity to store carbon increases with abandonment age. Large trees contribute most to aboveground biomass. A better understanding of the relative contribution of different biomass sources in aboveground total forest biomass, however, is necessary to fully capture the value of such landscapes from forest management, restoration and conservation perspectives. PMID:26951761

Tropical secondary forests regenerating after shifting cultivation in the Philippines uplands are important carbon sinks

NASA Astrophysics Data System (ADS)

Mukul, Sharif A.; Herbohn, John; Firn, Jennifer

2016-03-01

In the tropics, shifting cultivation has long been attributed to large scale forest degradation, and remains a major source of uncertainty in forest carbon accounting. In the Philippines, shifting cultivation, locally known as kaingin, is a major land-use in upland areas. We measured the distribution and recovery of aboveground biomass carbon along a fallow gradient in post-kaingin secondary forests in an upland area in the Philippines. We found significantly higher carbon in the aboveground total biomass and living woody biomass in old-growth forest, while coarse dead wood biomass carbon was higher in the new fallow sites. For young through to the oldest fallow secondary forests, there was a progressive recovery of biomass carbon evident. Multivariate analysis indicates patch size as an influential factor in explaining the variation in biomass carbon recovery in secondary forests after shifting cultivation. Our study indicates secondary forests after shifting cultivation are substantial carbon sinks and that this capacity to store carbon increases with abandonment age. Large trees contribute most to aboveground biomass. A better understanding of the relative contribution of different biomass sources in aboveground total forest biomass, however, is necessary to fully capture the value of such landscapes from forest management, restoration and conservation perspectives.

Degradation in carbon stocks near tropical forest edges.

PubMed

Chaplin-Kramer, Rebecca; Ramler, Ivan; Sharp, Richard; Haddad, Nick M; Gerber, James S; West, Paul C; Mandle, Lisa; Engstrom, Peder; Baccini, Alessandro; Sim, Sarah; Mueller, Carina; King, Henry

2015-12-18

Carbon stock estimates based on land cover type are critical for informing climate change assessment and landscape management, but field and theoretical evidence indicates that forest fragmentation reduces the amount of carbon stored at forest edges. Here, using remotely sensed pantropical biomass and land cover data sets, we estimate that biomass within the first 500 m of the forest edge is on average 25% lower than in forest interiors and that reductions of 10% extend to 1.5 km from the forest edge. These findings suggest that IPCC Tier 1 methods overestimate carbon stocks in tropical forests by nearly 10%. Proper accounting for degradation at forest edges will inform better landscape and forest management and policies, as well as the assessment of carbon stocks at landscape and national levels.

Degradation in carbon stocks near tropical forest edges

PubMed Central

Chaplin-Kramer, Rebecca; Ramler, Ivan; Sharp, Richard; Haddad, Nick M.; Gerber, James S.; West, Paul C.; Mandle, Lisa; Engstrom, Peder; Baccini, Alessandro; Sim, Sarah; Mueller, Carina; King, Henry

2015-01-01

Carbon stock estimates based on land cover type are critical for informing climate change assessment and landscape management, but field and theoretical evidence indicates that forest fragmentation reduces the amount of carbon stored at forest edges. Here, using remotely sensed pantropical biomass and land cover data sets, we estimate that biomass within the first 500 m of the forest edge is on average 25% lower than in forest interiors and that reductions of 10% extend to 1.5 km from the forest edge. These findings suggest that IPCC Tier 1 methods overestimate carbon stocks in tropical forests by nearly 10%. Proper accounting for degradation at forest edges will inform better landscape and forest management and policies, as well as the assessment of carbon stocks at landscape and national levels. PMID:26679749

[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.

Modeling nonstructural carbohydrate reserve dynamics in forest trees

NASA Astrophysics Data System (ADS)

Richardson, Andrew; Keenan, Trevor; Carbone, Mariah; Pederson, Neil

2013-04-01

Understanding the factors influencing the availability of nonstructural carbohydrate (NSC) reserves is essential for predicting the resilience of forests to climate change and environmental stress. However, carbon allocation processes remain poorly understood and many models either ignore NSC reserves, or use simple and untested representations of NSC allocation and pool dynamics. Using model-data fusion techniques, we combined a parsimonious model of forest ecosystem carbon cycling with novel field sampling and laboratory analyses of NSCs. Simulations were conducted for an evergreen conifer forest and a deciduous broadleaf forest in New England. We used radiocarbon methods based on the 14C "bomb spike" to estimate the age of NSC reserves, and used this to constrain the mean residence time of modeled NSCs. We used additional data, including tower-measured fluxes of CO2, soil and biomass carbon stocks, woody biomass increment, and leaf area index and litterfall, to further constrain the model's parameters and initial conditions. Incorporation of fast- and slow-cycling NSC pools improved the ability of the model to reproduce the measured interannual variability in woody biomass increment. We show how model performance varies according to model structure and total pool size, and we use novel diagnostic criteria, based on autocorrelation statistics of annual biomass growth, to evaluate the model's ability to correctly represent lags and memory effects.

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.

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

Spaceborne Applications of P Band Imaging Radars for Measuring Forest Biomass

NASA Technical Reports Server (NTRS)

Rignot, Eric J.; Zimmermann, Reiner; vanZyl, Jakob J.

1995-01-01

In three sites of boreal and temperate forests, P band HH, HV, and VV polarization data combined estimate total aboveground dry woody biomass within 12 to 27% of the values derived from allometric equations, depending on forest complexity. Biomass estimates derived from HV-polarization data only are 2 to 14% less accurate. When the radar operates at circular polarization, the errors exceed 100% over flooded forests, wet or damaged trees and sparse open tall forests because double-bounce reflections of the radar signals yield radar signatures similar to that of tall and massive forests. Circular polarizations, which minimize the effect of Faraday rotation in spaceborne applications, are therefore of limited use for measuring forest biomass. In the tropical rain forest of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 50 kg/sq m in old, undisturbed floodplain stands, the P band horizontal and vertical polarization data combined separate biomass classes in good agreement with forest inventory estimates. The worldwide need for large scale, updated, biomass estimates, achieved with a uniformly applied method, justifies a more in-depth exploration of multi-polarization long wavelength imaging radar applications for tropical forests inventories.

Assessing biomass and forest area classifications from modis satellite data while incrementing the number of FIA data panels

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2005-01-01

Our objective was to determine at what level biomass and forest area obtained from 2, 3, 4, or 5 panels of forest inventory data compares well with forested area and biomass estimates from the national inventory data. A subset of 2605 inventory plots (100% forested, 100% non-forested) was used to classify the land cover and model the biomass in South Carolina. Mixed...

Estimating tropical forest structure using LIDAR AND X-BAND INSAR

NASA Astrophysics Data System (ADS)

Palace, M. W.; Treuhaft, R. N.; Keller, M. M.; Sullivan, F.; Roberto dos Santos, J.; Goncalves, F. G.; Shimbo, J.; Neumann, M.; Madsen, S. N.; Hensley, S.

2013-12-01

Tropical forests are considered the most structurally complex of all forests and are experiencing rapid change due to anthropogenic and climatic factors. The high carbon stocks and fluxes make understanding tropical forests highly important to both regional and global studies involving ecosystems and climate. Large and remote areas in the tropics are prime targets for the use of remotely sensed data. Radar and lidar have previously been used to estimate forest structure, with an emphasis on biomass. These two remote sensing methods have the potential to yield much more information about forest structure, specifically through the use of X-band radar and waveform lidar data. We examined forest structure using both field-based and remotely sensed data in the Tapajos National Forest, Para, Brazil. We measured multiple structural parameters for about 70 plots in the field within a 25 x 15 km area that have TanDEM-X single-pass horizontally and vertically polarized radar interferometric data. High resolution airborne lidar were collected over a 22 sq km portion of the same area, within which 33 plots were co-located. Preliminary analyses suggest that X-band interferometric coherence decreases by about a factor of 2 (from 0.95 to 0.45) with increasing field-measured vertical extent (average heights of 7-25 m) and biomass (10-430 Mg/ha) for a vertical wavelength of 39 m, further suggesting, as has been observed at C-band, that interferometric synthetic aperture radar (InSAR) is substantially more sensitive to forest structure/biomass than SAR. Unlike InSAR coherence versus biomass, SAR power at X-band versus biomass shows no trend. Moreover, airborne lidar coherence at the same vertical wavenumbers as InSAR is also shown to decrease as a function of biomass, as well. Although the lidar coherence decrease is about 15% more than the InSAR, implying that lidar penetrates more than InSAR, these preliminary results suggest that X-band InSAR may be useful for structure and biomass estimation over large spatial scales not attainable with airborne lidar. In this study, we employed a set of less commonly used lidar metrics that we consider analogous to field-based measurements, such as the number of canopy maxima, measures of canopy vegetation distribution diversity and evenness (entropy), and estimates of gap fraction. We incorporated these metrics, as well as lidar coherence metrics pulled from discrete Fourier transforms of pseudowaveforms, and hypothetical stand characteristics of best-fit synthetic vegetation profiles into multiple regression analysis of forest biometric properties. Among simple and complex measures of forest structure, ranging from tree density, diameter at breast height, and various canopy geometry parameters, we found strong relationships with lidar canopy vegetation profile parameters. We suggest that the sole use of lidar height is limited in understanding biomass in a forest with little variation across the landscape and that there are many parameters that may be gleaned by lidar data that inform on forest biometric properties.

Going beyond the green: senesced vegetation material predicts basal area and biomass in remote sensing of tree cover conditions in an African tropical dry forest (miombo woodland) landscape

NASA Astrophysics Data System (ADS)

Mayes, Marc; Mustard, John; Melillo, Jerry; Neill, Christopher; Nyadzi, Gerson

2017-08-01

In sub-Saharan Africa (SSA), tropical dry forests and savannas cover over 2.5 million km2 and support livelihoods for millions in fast-growing nations. Intensifying land use pressures have driven rapid changes in tree cover structure (basal area, biomass) that remain poorly characterized at regional scales. Here, we posed the hypothesis that tree cover structure related strongly to senesced and non-photosynthetic (NPV) vegetation features in a SSA tropical dry forest landscape, offering improved means for satellite remote sensing of tree cover structure compared to vegetation greenness-based methods. Across regrowth miombo woodland sites in Tanzania, we analyzed relationships among field data on tree structure, land cover, and satellite indices of green and NPV features based on spectral mixture analyses and normalized difference vegetation index calculated from Landsat 8 data. From satellite-field data relationships, we mapped regional basal area and biomass using NPV and greenness-based metrics, and compared map performances at landscape scales. Total canopy cover related significantly to stem basal area (r 2 = 0.815, p < 0.01) and biomass (r 2 = 0.635, p < 0.01), and NPV dominated ground cover (> 60%) at all sites. From these two conditions emerged a key inverse relationship: skyward exposure of NPV ground cover was high at sites with low tree basal area and biomass, and decreased with increasing stem basal area and biomass. This pattern scaled to Landsat NPV metrics, which showed strong inverse correlations to basal area (Pearson r = -0.85, p < 0.01) and biomass (r = -0.86, p < 0.01). Biomass estimates from Landsat NPV-based maps matched field data, and significantly differentiated landscape gradients in woody biomass that greenness metrics failed to track. The results suggest senesced vegetation metrics at Landsat scales are a promising means for improved monitoring of tree structure across disturbance and ecological gradients in African and other tropical dry forests.

Regional paleofire regimes affected by non-uniform climate, vegetation and human drivers

NASA Astrophysics Data System (ADS)

Blarquez, Olivier; Ali, Adam A.; Girardin, Martin P.; Grondin, Pierre; Fréchette, Bianca; Bergeron, Yves; Hély, Christelle

2015-09-01

Climate, vegetation and humans act on biomass burning at different spatial and temporal scales. In this study, we used a dense network of sedimentary charcoal records from eastern Canada to reconstruct regional biomass burning history over the last 7000 years at the scale of four potential vegetation types: open coniferous forest/tundra, boreal coniferous forest, boreal mixedwood forest and temperate forest. The biomass burning trajectories were compared with regional climate trends reconstructed from general circulation models, tree biomass reconstructed from pollen series, and human population densities. We found that non-uniform climate, vegetation and human drivers acted on regional biomass burning history. In the open coniferous forest/tundra and dense coniferous forest, the regional biomass burning was primarily shaped by gradual establishment of less climate-conducive burning conditions over 5000 years. In the mixed boreal forest an increasing relative proportion of flammable conifers in landscapes since 2000 BP contributed to maintaining biomass burning constant despite climatic conditions less favourable to fires. In the temperate forest, biomass burning was uncoupled with climatic conditions and the main driver was seemingly vegetation until European colonization, i.e. 300 BP. Tree biomass and thus fuel accumulation modulated fire activity, an indication that biomass burning is fuel-dependent and notably upon long-term co-dominance shifts between conifers and broadleaf trees.

Forest biomass and tree planting for fossil fuel offsets in the Colorado Front Range

Treesearch

Mike A. Battaglia; Kellen Nelson; Dan Kashian; Michael G. Ryan

2010-01-01

This study estimates the amount of carbon available for removal in fuel reduction and reforestation treatments in montane forests of the Colorado Front Range based on site productivity, pre-treatment basal area, and planting density. Thinning dense stands will yield the greatest offsets for biomass fuel. However, this will also yield the greatest carbon losses, if the...

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

Treesearch

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

2013-01-01

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

Consistency of forest presence and biomass predictions modeled across overlapping spatial and temporal extents

Treesearch

Mark D. Nelson; Sean Healey; W. Keith Moser; J.G. Masek; Warren Cohen

2011-01-01

We assessed the consistency across space and time of spatially explicit models of forest presence and biomass in southern Missouri, USA, for adjacent, partially overlapping satellite image Path/Rows, and for coincident satellite images from the same Path/Row acquired in different years. Such consistency in satellite image-based classification and estimation is critical...

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 quantification of the vegetation structure, will have an important impact in many aspects of ecosystem function, such as carbon cycling and biodiversity. For example, areas of forest loss or degradation and areas of growth or recovery, can be determined by the vegetation structure and its temporal change.

Estimating the carbon dynamics of South Korean forests from 1954 to 2012

NASA Astrophysics Data System (ADS)

Lee, J.; Yoon, T. K.; Han, S.; Kim, S.; Yi, M. J.; Park, G. S.; Kim, C.; Kim, R.; Son, Y.

2014-03-01

Forests play an important role in the global carbon (C) cycle, and the South Korean forests also contribute to this global C cycle. While the South Korean forest ecosystem was almost completely destroyed by exploitation and the Korean War, it has successfully recovered because of national-scale reforestation programs since 1973. There have been several studies on the estimation of C stocks and balances in the South Korean forests over the past decades. However, a retrospective long-term study including biomass and dead organic matter (DOM) C and validating DOM C is still insufficient. Accordingly, we estimated the C stocks and balances of both biomass and DOM C during 1954-2012 using a~process-based model, the Korean Forest Soil Carbon model, and the 5th Korean National Forest Inventory (NFI) report. Validation processes were also conducted based on the 5th NFI and statistical data. Simulation results showed that the biomass C stocks increased from 36.4 to 440.4 Tg C and sequestered C at a rate of 7.0 Tg C yr-1 during 1954-2012. The DOM C stocks increased from 386.0 to 463.1 Tg C and sequestered C at a rate of 1.3 Tg C yr-1 during the same period. The estimates of biomass and DOM C stocks agreed well with observed C stock data. The annual net biome production (NBP) during 1954-2012 was 141.3 g C m-2 yr-1, which increased from -8.8 to 436.6 g C m-2 yr-1 in 1955 and 2012, respectively. Compared to forests in other countries and global forests, the annual C sink rate of South Korean forests was much lower, but the NBP was much higher. Our results could provide the forest C dynamics in South Korean forests before and after the onset of reforestation programs.

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

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

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

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

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 forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.

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 the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.« less

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.

The effect of using complete and partial forested FIA plot data on biomass and forested area classifications from MODIS satellite data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2006-01-01

Authors’ objective was to determine at what level biomass and forest area obtained from partial and complete forested plot inventory data compares with forested area and biomass estimates from the national inventory data. A subset of 3819 inventory plots (100% forested, 100% non-forested, mixed-forest/non-forest) was used to classify the land cover and model the...

Assessment of potential biomass energy production in China towards 2030 and 2050

NASA Astrophysics Data System (ADS)

Zhao, Guangling

2018-01-01

The objective of this paper is to provide a more detailed picture of potential biomass energy production in the Chinese energy system towards 2030 and 2050. Biomass for bioenergy feedstocks comes from five sources, which are agricultural crop residues, forest residues and industrial wood waste, energy crops and woody crops, animal manure, and municipal solid waste. The potential biomass production is predicted based on the resource availability. In the process of identifying biomass resources production, assumptions are made regarding arable land, marginal land, crops yields, forest growth rate, and meat consumption and waste production. Four scenarios were designed to describe the potential biomass energy production to elaborate the role of biomass energy in the Chinese energy system in 2030. The assessment shows that under certain restrictions on land availability, the maximum potential biomass energy productions are estimated to be 18,833 and 24,901 PJ in 2030 and 2050.

Michigan's forests 2004

Treesearch

Scott A. Pugh; Mark H. Hansen; Lawrence D. Pedersen; Douglas C. Heym; Brett J. Butler; Susan J. Crocker; Dacia Meneguzzo; Charles H. Perry; David E. Haugen; Christopher Woodall; Ed Jepsen

2009-01-01

The first annual inventory of Michigan's forests, completed in 2004, covers more than 19.3 million acres of forest land. The data in this report are based on visits to 10,355 forested plots from 2000 to 2004. In addition to detailed information on forest attributes, this report includes data on forest health, biomass, land-use change, and timber-product outputs....

Metasequoia glyptostroboides and its Utility in Paleoecological Reconstruction of Eocene High Latitude Forests

NASA Astrophysics Data System (ADS)

Williams, C. J.; LePage, B. A.; Vann, D. R.; Johnson, A. H.

2001-05-01

Abundant fossil plant remains are preserved in the Eocene-aged deposits of the Buchanan Lake formation on Axel Heiberg Island, Nunavut, Canada. Intact leaf litter, logs, and stumps preserved in situ as mummified remains present an opportunity to determine forest composition, structure, and productivity of a Taxodiaceae-dominated forest that once grew north of the Arctic Circle (paleolatitude 75-80° N). We excavated 37 tree stems for dimensional analysis from mudstone and channel-sand deposits. Stem length ranged from 1.0 m to 14.8 m (average = 3.2 m). Stem diameter ranged from less than 10 cm to greater than 75 cm (average = 32.2 cm). All stem wood was tentatively identified to genus as Metasequoia sp. The diameters and parabolic shape of the preserved tree trunks indicate that the Metasequoia were about 39 m tall across a wide range of diameters. The allometric relationships we derived for modern Metasequoia (n=70) allowed independent predictions of Metasequoia height given the stand density and stump diameters of the fossil forest. The two height estimates of 40 and 40.5 m match the results obtained from measurements of the Eocene trees. We used stump diameter data (n =107, diameter > 20 cm) and an uniform canopy height of 39 m to calculate parabolic stem volume and stem biomass for a 0.22 ha area of fossil forest. Stem volume equaled 2065 m3 ha-1 and stem biomass equaled 560 Mg ha-1 . In the Eocene forest, as determined from length of stems that were free of protruding branches and from 7 exhumed tree tops, the uppermost 9 m of the trees carried live branches with foliage. In living conifers, branch weights and the amount of foliage carried by branches are well correlated with branch diameters measured where the branch joins the main stem. To determine the biomass in branches and foliage in the Eocene forest, we used relationships derived from large modern Metasequoia. Based on the regression of branch weight v. branch diameter (r2 = 0.97) and foliar biomass v. branch diameter (r2 = 0.91) for living Metasequoia and branch diameters of the Eocene trees, branch biomass of the Eocene trees was estimated to be 28 Mg ha-1 dry weight and foliar biomass (and annual foliar production for this deciduous conifer) of fossil Metasequoia was estimated to be 3.5 Mg ha-1 dry weight. Total standing biomass of the fossil forest was estimated to be 591 Mg ha-1 dry weight. On a stand-average basis, the annual ring width of the trees we sampled equaled 1.3 mm. Based on this ring width our preliminary estimate for the aboveground net primary productivity (NPP) of these forests is 5.9 Mg ha-1yr^{-1}$ (foliage production plus wood production). Thus, these were high biomass forests with moderate productivity typical of modern cool temperate forests similar in stature and total biomass to the modern old-growth forests of the Pacific Northwest (USA).

A biomass representative land cover classification for the Democratic Republic of Congo derived from the Forets D'Afrique Central Evaluee par Teledetection (FACET) data set

NASA Astrophysics Data System (ADS)

Molinario, G.; Hansen, M.; Potapov, P.; Altstatt, A. L.; Justice, C. O.

2012-12-01

The FACET forest cover and forest cover loss 2000-2005-2010 data set has been produced by South Dakota State University, the University of Maryland and the Kinshasa-based Observatoire Satellital des Forets D'Afrique Central (OSFAC) with funding from the USAID Central African Regional Program for the Environment (CARPE). The product is now available or being finalized for the DRC, the ROC and Gabon with plans to complete all Congo Basin countries. While FACET provides unprecedented synoptic detail in the extent of Congo Basin forest and the forest cover loss, additional information is required to stratify land cover into types indicative of biomass content. Analysis of the FACET patterns of deforestation, more detailed remote sensing analysis of biophysical attributes within the FACET land cover classes and GIS-derived classes of degradation obtained through variable distance buffers based on relevant literature and ground truth data are combined with the existing FACET classes to produce a ranking of land cover from low biomass to high biomass for the Democratic Republic of Congo. The resulting classification can be used in all Reduced Emissions from Degradation and Deforestation (REDD) pre-inventory phases when baseline forest cover needs to be known and the location and amount of forest biomass inventory plots needs to be designed. FACET cover loss classes were kept in the classification and can provide the Monitoring, Reporting and Verification tools needed for REDD projects. The project will be demonstrated for the Maringa Lopori Wamba Landscape of the DRC where this work was funded by the African Wildlife Foundation to support the design of a REDD pilot project.

Timber harvest as the predominant disturbance regime in northeastern U.S. forests: Effects of harvest intensification

USGS Publications Warehouse

Brown, Michelle L.; Canham, Charles D.; Murphy, Lora; Donovan, Therese M.

2018-01-01

Harvesting is the leading cause of adult tree mortality in forests of the northeastern United States. While current rates of timber harvest are generally sustainable, there is considerable pressure to increase the contribution of forest biomass to meet renewable energy goals. We estimated current harvest regimes for different forest types and regions across the U.S. states of New York, Vermont, New Hampshire, and Maine using data from the U.S. Forest Inventory and Analysis Program. We implemented the harvest regimes in SORTIE‐ND, an individual‐based model of forest dynamics, and simulated the effects of current harvest regimes and five additional harvest scenarios that varied by harvest frequency and intensity over 150 yr. The best statistical model for the harvest regime described the annual probability of harvest as a function of forest type/region, total plot basal area, and distance to the nearest improved road. Forests were predicted to increase in adult aboveground biomass in all harvest scenarios in all forest type and region combinations. The magnitude of the increase, however, varied dramatically—increasing from 3% to 120% above current landscape averages as harvest frequency and intensity decreased. The variation can be largely explained by the disproportionately high harvest rates estimated for Maine as compared with the rest of the region. Despite steady biomass accumulation across the landscape, stands that exhibited old‐growth characteristics (defined as ≥300 metric tons of biomass/hectare) were rare (8% or less of stands). Intensified harvest regimes had little effect on species composition due to widespread partial harvesting in all scenarios, resulting in dominance by late‐successional species over time. Our analyses indicate that forest biomass can represent a sustainable, if small, component of renewable energy portfolios in the region, although there are tradeoffs between carbon sequestration in forest biomass and sustainable feedstock supply. Integrating harvest regimes into a disturbance theory framework is critical to understanding the dynamics of forested landscapes, especially given the predominance of logging as a disturbance agent and the increasing pressure to meet renewable energy needs.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

An Integrated, Observation-based System to Monitor Aboveground Forest Carbon Dynamics in Washington, Oregon, and California

NASA Astrophysics Data System (ADS)

Kennedy, R. E.; Hughes, J.; Neeti, N.; Yang, Z.; Gregory, M.; Roberts, H.; Kane, V. R.; Powell, S. L.; Ohmann, J.

2016-12-01

Because carbon pools and fluxes on wooded landscapes are constrained by their type, age and health, understanding the causes and consequences of carbon change requires frequent observation of forest condition and of disturbance, mortality, and growth processes. As part of USDA and NASA funded efforts, we built empirical monitoring system that integrates time-series Landsat imagery, Forest Inventory and Analysis (FIA) plot data, small-footprint lidar data, and aerial photos to characterize key carbon dynamics in forested ecosystems of Washington, Oregon and California. Here we report yearly biomass estimates for every forested 30 by 30m pixel in the states of Washington, Oregon, and California from 1990 to 2010, including spatially explicit estimates of uncertainty in our yearly predictions. Total biomass at the ecoregion scale agrees well with estimates from FIA plot data alone, currently the only method for reliable monitoring in the forests of the region. Comparisons with estimates of biomass modeled from four small-footprint lidar acquisitions in overlapping portions of our study area show general patterns of agreement between the two types of estimation, but also reveal some disparities in spatial pattern potentially attributable to age and vegetation condition. Using machine-learning techniques based on both Landsat image time series and high resolution aerial photos, we then modeled the agent causing change in biomass for every change event in the region, and report the relative distribution of carbon loss attributable to natural disturbances (primarily fire and insect-related mortality) versus anthropogenic causes (forest management and development).

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 significantly higher biomass than angiosperm species. In Brazil, this endangered species is part of a high diversity forest (Araucaria Forest) and has the potential for biomass storage. The results of the present study show the spatial and local variability in aboveground biomass in subtropical forests and highlight the importance of these ecosystems in global carbon stock, stimulating the improvement of future biomass estimates.

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

NASA Technical Reports Server (NTRS)

Nelson, Ross

2008-01-01

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

Effects of LiDAR point density and landscape context on estimates of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.

2015-03-01

Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest assessment without compromising the accuracy of biomass estimates, and these estimates can be further improved using development density.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

The Importance of Seedlings Quality in Timber and Bio-energy Production on marginal lands

NASA Astrophysics Data System (ADS)

Fragkiskakis, Nikitas; Kiourtsis, Fotios; Keramitzis, Dimitrios; Papatheodorou, Ioannis; Georgiadou, Margarita; Repmann, Frank; Gerwin, Werner

2017-04-01

One of the main issues that the forest sector is facing is to achieve a balance between the demand for biomass &wood production and the need to preserve the sustainability and biodiversity of forest ecosystems. The purposes of the new approaches are to ensure more efficient management of ecosystems and implement intensive forestry that will increase biomass production & timber yields. To achieve this, we need to determine the macroeconomic potential of the various options available, including the use of biotechnology and genetics. The success of the forests plantations capacity may be solved through forest certification, based on: a) Stabilization of the forests and soils structure. b) Hierarchy of biomass production in the forest's management process. c) Οrganization and implementation of effective plantation on marginal lands. d) Maintenance or increase of forest productivity by introducing new items as and when they are required. It is important to evaluate of the influence of factors such as the quality of soils of plantation areas, the utilization of the genetic resources and the management of forest operations with the environmental economic criteria such as net present value of benefits (NPV) and the corresponding flow annuities (EACF).The existing evaluations studies showed that the quality of the plantation areas has the most influence and through validated quality seed production can generate an increase in the NPV up to 73%. The importance of seedlings quality in timber and bio-energy production on marginal lands based on the literature it is estimated according to the heredity of the characteristics of the wood structure (except shrinkage). This clearly indicate that seedlings with the appropriate morphological characteristics can significantly improve the growth performance and help to support the development of biomass plantations oriented in tailor-made timber and bio-energy production.

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.

Education Highlights: Forest Biomass

ScienceCinema

Barone, Rachel; Canter, Christina

2018-06-25

Argonne intern Rachel Barone from Ithaca College worked with Argonne mentor Christina Canter in studying forest biomass. This research will help scientists develop large scale use of biofuels from forest biomass.

Education Highlights: Forest Biomass

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

Barone, Rachel; Canter, Christina

2016-01-27

Argonne intern Rachel Barone from Ithaca College worked with Argonne mentor Christina Canter in studying forest biomass. This research will help scientists develop large scale use of biofuels from forest biomass.

Regional paleofire regimes affected by non-uniform climate, vegetation and human drivers

PubMed Central

Blarquez, Olivier; Ali, Adam A.; Girardin, Martin P.; Grondin, Pierre; Fréchette, Bianca; Bergeron, Yves; Hély, Christelle

2015-01-01

Climate, vegetation and humans act on biomass burning at different spatial and temporal scales. In this study, we used a dense network of sedimentary charcoal records from eastern Canada to reconstruct regional biomass burning history over the last 7000 years at the scale of four potential vegetation types: open coniferous forest/tundra, boreal coniferous forest, boreal mixedwood forest and temperate forest. The biomass burning trajectories were compared with regional climate trends reconstructed from general circulation models, tree biomass reconstructed from pollen series, and human population densities. We found that non-uniform climate, vegetation and human drivers acted on regional biomass burning history. In the open coniferous forest/tundra and dense coniferous forest, the regional biomass burning was primarily shaped by gradual establishment of less climate-conducive burning conditions over 5000 years. In the mixed boreal forest an increasing relative proportion of flammable conifers in landscapes since 2000 BP contributed to maintaining biomass burning constant despite climatic conditions less favourable to fires. In the temperate forest, biomass burning was uncoupled with climatic conditions and the main driver was seemingly vegetation until European colonization, i.e. 300 BP. Tree biomass and thus fuel accumulation modulated fire activity, an indication that biomass burning is fuel-dependent and notably upon long-term co-dominance shifts between conifers and broadleaf trees. PMID:26330162

A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)

Treesearch

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

2012-01-01

Lidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform "shots," which have been shown to be strongly correlated with aboveground forest...

Assessing bioenergy harvest risks: Geospatially explicit tools for maintaining soil productivity in western US forests

Treesearch

Mark Kimsey; Deborah Page-Dumroese; Mark Coleman

2011-01-01

Biomass harvesting for energy production and forest health can impact the soil resource by altering inherent chemical, physical and biological properties. These impacts raise concern about damaging sensitive forest soils, even with the prospect of maintaining vigorous forest growth through biomass harvesting operations. Current forest biomass harvesting research...

Residue distribution and biomass recovery following biomass harvest of plantation pine

Treesearch

Johnny Grace III; John Klepac; S. Taylor; Dana Mitchell

2016-01-01

Forest biomass is anticipated to play a significant role in addressing an alternative energy supply. However, the efficiencies of current state-of-the-art recovery systems operating in forest biomass harvests are still relatively unknown. Forest biomass harvest stands typically have higher stand densities and smaller diameter trees than conventional stands which may...

Life-cycle energy and GHG emissions of forest biomass harvest and transport for biofuel production in Michigan

DOE PAGES

Zhang, Fengli; Johnson, Dana M.; Wang, Jinjiang

2015-04-01

High dependence on imported oil has increased U.S. strategic vulnerability and prompted more research in the area of renewable energy production. Ethanol production from renewable woody biomass, which could be a substitute for gasoline, has seen increased interest. This study analysed energy use and greenhouse gas emission impacts on the forest biomass supply chain activities within the State of Michigan. A life-cycle assessment of harvesting and transportation stages was completed utilizing peer-reviewed literature. Results for forest-delivered ethanol were compared with those for petroleum gasoline using data specific to the U.S. The analysis from a woody biomass feedstock supply perspective uncoveredmore » that ethanol production is more environmentally friendly (about 62% less greenhouse gas emissions) compared with petroleum based fossil fuel production. Sensitivity analysis was conducted with key inputs associated with harvesting and transportation operations. The results showed that research focused on improving biomass recovery efficiency and truck fuel economy further reduced GHG emissions and energy consumption.« less

Life-cycle energy and GHG emissions of forest biomass harvest and transport for biofuel production in Michigan

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

Zhang, Fengli; Johnson, Dana M.; Wang, Jinjiang

High dependence on imported oil has increased U.S. strategic vulnerability and prompted more research in the area of renewable energy production. Ethanol production from renewable woody biomass, which could be a substitute for gasoline, has seen increased interest. This study analysed energy use and greenhouse gas emission impacts on the forest biomass supply chain activities within the State of Michigan. A life-cycle assessment of harvesting and transportation stages was completed utilizing peer-reviewed literature. Results for forest-delivered ethanol were compared with those for petroleum gasoline using data specific to the U.S. The analysis from a woody biomass feedstock supply perspective uncoveredmore » that ethanol production is more environmentally friendly (about 62% less greenhouse gas emissions) compared with petroleum based fossil fuel production. Sensitivity analysis was conducted with key inputs associated with harvesting and transportation operations. The results showed that research focused on improving biomass recovery efficiency and truck fuel economy further reduced GHG emissions and energy consumption.« less

Evidence for environmentally enhanced forest growth

PubMed Central

Fang, Jingyun; Kato, Tomomichi; Guo, Zhaodi; Yang, Yuanhe; Hu, Huifeng; Shen, Haihua; Zhao, Xia; Kishimoto-Mo, Ayaka W.; Tang, Yanhong; Houghton, Richard A.

2014-01-01

Forests in the middle and high latitudes of the northern hemisphere function as a significant sink for atmospheric carbon dioxide (CO2). This carbon (C) sink has been attributed to two processes: age-related growth after land use change and growth enhancement due to environmental changes, such as elevated CO2, nitrogen deposition, and climate change. However, attribution between these two processes is largely controversial. Here, using a unique time series of an age-class dataset from six national forest inventories in Japan and a new approach developed in this study (i.e., examining changes in biomass density at each age class over the inventory periods), we quantify the growth enhancement due to environmental changes and its contribution to biomass C sink in Japan’s forests. We show that the growth enhancement for four major plantations was 4.0∼7.7 Mg C⋅ha−1 from 1980 to 2005, being 8.4–21.6% of biomass C sequestration per hectare and 4.1–35.5% of the country's total net biomass increase of each forest type. The growth enhancement differs among forest types, age classes, and regions. Our results provide, to our knowledge, the first ground-based evidence that global environmental changes can increase C sequestration in forests on a broad geographic scale and imply that both the traits and age of trees regulate the responses of forest growth to environmental changes. These findings should be incorporated into the prediction of forest C cycling under a changing climate. PMID:24979781

Tropical forest biomass and successional age class relationships to a vegetation index derived from Landsat TM data

NASA Technical Reports Server (NTRS)

Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, Armond T.

1989-01-01

Forest stand structure and biomass data were collected using conventional forest inventory techniques in tropical, subtropical, and warm temperate forest biomes. The feasibility of detecting tropical forest successional age class and total biomass differences using Landsat-Thematic mapper (TM) data, was evaluated. The Normalized Difference Vegetation Index (NDVI) calculated from Landsat-TM data were not significantly correlated with forest regeneration age classes in the mountain terrain of the Luquillo Experimental Forest, Puerto Rico. The low sun angle and shadows cast on steep north and west facing slopes reduced spectral reflectance values recorded by TM orbital altitude. The NDVI, calculated from low altitude aircraft scanner data, was significatly correlated with forest age classes. However, analysis of variance suggested that NDVI differences were not detectable for successional forests older than approximately 15-20 years. Also, biomass differences in young successional tropical forest were not detectable using the NDVI. The vegetation index does not appear to be a good predictor of stand structure variables (e.g., height, diameter of main stem) or total biomass in uneven age, mixed broadleaf forest. Good correlation between the vegetation index and low biomass in even age pine plantations were achieved for a warm temperate study site. The implications of the study for the use of NDVI for forest structure and biomass estimation are discussed.

Understory biomass from southern pine forests as a fuel source

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

Ku, T.T.; Baker, J.B.

1993-12-31

The energy crisis in the US in the late 1970s led to accelerated research on renewable energy resources. The use of woody biomass, harvested from pine forests in the southern US, as a renewable energy source would not only provide an efficient energy alternative to forest industries, but its use would also reduce understory competition and accelerate growth of overstory crop trees. This study was initiated in the early 1980s to investigate the feasibility and applicability of the use of understory vegetation as a possible energy fuel resource. All woody understory vegetation [<14 cm (<5.5 in) in dbh], on 0.2more » ha (0.5 ac) plots that represented a range of stand/site conditions of pine stands located in twelve southern Arkansas counties and two northern Louisiana parishes were characterized, quantified, and harvested. Based on the biomass yield from 720 subplots nested within 40 main plots, the top five dominant species in the understory, based on number and size were: Red maple, red oaks, pines, sweetgum, and winged elm. Some other species occurring, but in smaller proportions, were flowering dogwood, beautyberry, white oaks, black gum, wax myrtle, hickories, persimmon, and ashes. Most of these species are deciduous hardwoods that provide high BTU output upon burning. The average yield of chipped understory biomass was 23.5 T/ha with no difference occurring between summer and winter harvests. A predictive model of understory biomass production was developed using a step-wise multivariate regression analysis. In relation to forest type, high density pine stands produced 53% more understory biomass than high density pine-hardwood stands. The average moisture content of biomass was significantly lower when harvested in winter than when harvested in summer.« less

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.

Use of GIS for estimating potential and actual forest biomass for continental South and Southeast Asia.

Treesearch

L. R. Iverson; S. Brown; A. Prasad; H. Mitasova; A. J. R. Gillespie; A. E. Lugo

1994-01-01

A geographic information system (GIS) was used to estimate total biomass and biomass density of the tropical forest in south and southeast Asia because available data from forest inventories were insufficient to extrapolate biomass-density estimates across the region.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

Treesearch

Elizabeth A. Freeman; Gretchen G. Moisen

2007-01-01

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

Arizona’s forest resources, 2001-2014

Treesearch

John D. Shaw; Jim Menlove; Chris Witt; Todd A. Morgan; Michael C. Amacher; Sara A. Goeking; Charles E. Werstak

2018-01-01

This report presents a summary of the most recent inventory of Arizona’s forests based on field data collected between 2001 and 2014. The report includes descriptive highlights and tables of forest and timberland area, numbers of trees, biomass, volume, growth, mortality, and removals. Most sections and tables are organized by forest type or forest-type group, species...

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

PubMed

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

2016-10-05

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

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

PubMed Central

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

2016-01-01

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

Modeling and Assessing Insect Disturbance on Boreal Forests in the Krasnoyarsk region of Russia by Employing the FAREAST Gap Model and Local Forest Inventory and Disturbance Data.

NASA Astrophysics Data System (ADS)

Erler, A. E.; Shuman, J. K.; Soukhavolosky, V.; Kovalev, A.; Stevens, T.; Shugart, H. H.

2008-12-01

FAREAST: an individual-based forest dynamics model was initially developed to simulate the forested region around Changbai Mountain in northern China. In recent years the model has been expanded across Siberia. The model output for biomass (tCha-1) has been verified against forest inventory data for a number of sites across Russia. With this success, an additional module for the model was written by Anton Kovalev to predict the impact of insect disturbance on the Boreal forests. This model predicts the probability of an insect outbreak occurring, and then, by assessing each individual tree in a modeled stand, predicts whether a tree will be killed as a result of insect predation. From this, a disturbance index is calculated that includes lost biomass as a result of insect disturbance and subsequent species composition. This disturbance "fingerprint" is being compared to forest inventory and insect disturbance data from the Usolsky forests in the Krasnoyarsk region of central Siberia. Silkworm disturbance is expressed in this geo- database as a percentage of trees damaged or killed in a stand. The forest inventory data allows us to calculate a biomass estimate that will be compared to the biomass outputs generated by the model post insect disturbance. The validation of simulated biomass with independent inventory data confirms that FAREAST is a robust model of Russian forest dynamics. Effective validation of the insect disturbance model will allow us to generate a more complete picture of the changing ecology of the Siberian Boreal landscape. The economic cost of lumber lost as a result of Silkworm damage has been enormous, if verified, FAREAST will afford us the opportunity to estimate the extent of that loss and predict the changing ecological dynamics of the Boreal forest system under the worlds evolving climate.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

[Simulation of three-dimensional green biomass of urban forests in Shenyang City and the factors affecting the biomass].

PubMed

Liu, Chang-Fu; He, Xing-Yuan; Chen, Wei; Zhao, Gui-Ling; Xue, Wen-Duo

2008-06-01

Based on the fractal theory of forest growth, stepwise regression was employed to pursue a convenient and efficient method of measuring the three-dimensional green biomass (TGB) of urban forests in small area. A total of thirteen simulation equations of TGB of urban forests in Shenyang City were derived, with the factors affecting the TGB analyzed. The results showed that the coefficients of determination (R2) of the 13 simulation equations ranged from 0.612 to 0.842. No evident pattern was shown in residual analysis, and the precisions were all higher than 87% (alpha = 0.05) and 83% (alpha = 0.01). The most convenient simulation equation was ln Y = 7.468 + 0.926 lnx1, where Y was the simulated TGB and x1 was basal area at breast height per hectare (SDB). The correlations between the standard regression coefficients of the simulation equations and 16 tree characteristics suggested that SDB was the main factor affecting the TGB of urban forests in Shenyang.

A comparison of producer gas, biochar, and activated carbon from two distributed scale thermochemical conversion systems used to process forest biomass

Treesearch

Nathaniel Anderson; J. Greg Jones; Deborah Page-Dumroese; Daniel McCollum; Stephen Baker; Daniel Loeffler; Woodam Chung

2013-01-01

Thermochemical biomass conversion systems have the potential to produce heat, power, fuels and other products from forest biomass at distributed scales that meet the needs of some forest industry facilities. However, many of these systems have not been deployed in this sector and the products they produce from forest biomass have not been adequately described or...

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...

Estimating the carbon dynamics of South Korean forests from 1954 to 2012

NASA Astrophysics Data System (ADS)

Lee, J.; Yoon, T. K.; Han, S.; Kim, S.; Yi, M. J.; Park, G. S.; Kim, C.; Son, Y. M.; Kim, R.; Son, Y.

2014-09-01

Forests play an important role in the global carbon (C) cycle, and the South Korean forests also contribute to this global C cycle. While the South Korean forest ecosystem was almost completely destroyed by exploitation and the Korean War, it has successfully recovered because of national-scale reforestation programs since 1973. There have been several studies on the estimation of C stocks and balances over the past decades in the South Korean forests. However, a retrospective long-term study that includes biomass and dead organic matter C and validates dead organic matter C is still lacking. Accordingly, we estimated the C stocks and their changes of both biomass and dead organic matter C during the 1954-2012 period using a process-based model, the Korean Forest Soil Carbon model, and the 5th South Korean national forest inventory (NFI) report. Validation processes were also conducted based on the 5th NFI and statistical data. Simulation results showed that the biomass C stocks increased from 36.4 to 440.4 Tg C at a rate of 7.0 Tg C yr-1 during the period 1954-2012. The dead organic matter C stocks increased from 386.0 to 463.1 Tg C at a rate of 1.3 Tg C yr-1 during the same period. The estimates of biomass and dead organic matter C stocks agreed well with observed C stock data. The annual net biome production (NBP) during the period 1954-2012 was 141.3 g C m-2 yr-1, which increased from -8.8 g C m-2 yr-1 in 1955 to 436.6 g C m-2 yr-1 in 2012. Because of the small forested area, the South Korean forests had a comparatively lower contribution to the annual C sequestration by global forests. In contrast, because of the extensive reforestation programs, the NBP of South Korean forests was much higher than those of other countries. Our results could provide the forest C dynamics in South Korean forests before and after the onset of reforestation programs.

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

Treesearch

Roger M. Rowell

2007-01-01

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

Integrating LIDAR and forest inventories to fill the trees outside forests data gap

Treesearch

Kristofer D. Johnson; Richard Birdsey; Jason Cole; Anu Swatantran; Jarlath O' Neil-Dunne; Ralph Dubayah; Andrew Lister

2015-01-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data....

Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.

2014-12-01

Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest biomass assessment without compromising the accuracy of estimation, which may further be improved using development density.

Increasing biomass carbon stocks in trees outside forests in China over the last three decades

NASA Astrophysics Data System (ADS)

Guo, Z. D.; Hu, H. F.; Pan, Y. D.; Birdsey, R. A.; Fang, J. Y.

2014-08-01

Trees outside forests (TOF) play important roles in national economies, ecosystem services, and international efforts for mitigating climate warming. Detailed assessment of the dynamics of carbon (C) stocks in China's TOF is necessary for fully evaluating the role of the country's trees in the national C cycle. This study is the first to explore the changes in biomass C stocks of China's TOF over the last three decades, using the national forest inventory data in six periods from 1977 to 2008. According to the definition of the forest inventory, China's TOF could be categorized into three groups: woodlands, shrubberies, and trees on non-forest land (including four-side greening trees, defined in the article, and scattered trees). We estimated biomass C stocks of woodlands and trees on non-forest land by using the provincial biomass-volume conversion equations derived from the data of low-canopy forests, and estimated the biomass C stocks of shrubberies using the provincial mean biomass density. Total TOF biomass C stock increased by 62.7% from 823 Tg C (1 Tg = 1012 g) in the initial period of 1977-1981 to 1339 Tg C in the last period of 2004-2008. As a result, China's TOF have accumulated biomass C of 516 Tg during the study period, with 12, 270, and 234 Tg in woodlands, shrubberies, and trees on non-forest land, respectively. The annual biomass C sink of China's TOF averaged 19.1 Tg C yr-1, offsetting 2.1% of the contemporary fossil-fuel CO2 emissions in the country. These estimates are equal to 16.5-20.7% of the contemporary total forest biomass C stock and 27.2% of the total forest biomass C sink in the country, suggesting that TOF are substantial components in China's tree C budget.

Forest biomass, canopy structure, and species composition relationships with multipolarization L-band synthetic aperture radar data

NASA Technical Reports Server (NTRS)

Sader, Steven A.

1987-01-01

The effect of forest biomass, canopy structure, and species composition on L-band synthetic aperature radar data at 44 southern Mississippi bottomland hardwood and pine-hardwood forest sites was investigated. Cross-polarization mean digital values for pine forests were significantly correlated with green weight biomass and stand structure. Multiple linear regression with five forest structure variables provided a better integrated measure of canopy roughness and produced highly significant correlation coefficients for hardwood forests using HV/VV ratio only. Differences in biomass levels and canopy structure, including branching patterns and vertical canopy stratification, were important sources of volume scatter affecting multipolarization radar data. Standardized correction techniques and calibration of aircraft data, in addition to development of canopy models, are recommended for future investigations of forest biomass and structure using synthetic aperture radar.

Drivers of metacommunity structure diverge for common and rare Amazonian tree species.

PubMed

Bispo, Polyanna da Conceição; Balzter, Heiko; Malhi, Yadvinder; Slik, J W Ferry; Dos Santos, João Roberto; Rennó, Camilo Daleles; Espírito-Santo, Fernando D; Aragão, Luiz E O C; Ximenes, Arimatéa C; Bispo, Pitágoras da Conceição

2017-01-01

We analysed the flora of 46 forest inventory plots (25 m x 100 m) in old growth forests from the Amazonian region to identify the role of environmental (topographic) and spatial variables (obtained using PCNM, Principal Coordinates of Neighbourhood Matrix analysis) for common and rare species. For the analyses, we used multiple partial regression to partition the specific effects of the topographic and spatial variables on the univariate data (standardised richness, total abundance and total biomass) and partial RDA (Redundancy Analysis) to partition these effects on composition (multivariate data) based on incidence, abundance and biomass. The different attributes (richness, abundance, biomass and composition based on incidence, abundance and biomass) used to study this metacommunity responded differently to environmental and spatial processes. Considering standardised richness, total abundance (univariate) and composition based on biomass, the results for common species differed from those obtained for all species. On the other hand, for total biomass (univariate) and for compositions based on incidence and abundance, there was a correspondence between the data obtained for the total community and for common species. Our data also show that in general, environmental and/or spatial components are important to explain the variability in tree communities for total and common species. However, with the exception of the total abundance, the environmental and spatial variables measured were insufficient to explain the attributes of the communities of rare species. These results indicate that predicting the attributes of rare tree species communities based on environmental and spatial variables is a substantial challenge. As the spatial component was relevant for several community attributes, our results demonstrate the importance of using a metacommunities approach when attempting to understand the main ecological processes underlying the diversity of tropical forest communities.

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

Treesearch

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

2009-01-01

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

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

PubMed

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

2017-03-01

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

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

Treesearch

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

2015-01-01

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

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results from various remote sensing scenarios will also be presented.

Can portable pyrolysis units make biomass utilization affordable while using bio-char to enhance soil productivity and sequester carbon?

Treesearch

Mark Coleman; Deborah Page-Dumroese; Jim Archuleta; Phil Badger; Woodum Chung; Tyron Venn; Dan Loeffler; Greg Jones; Kristin McElligott

2010-01-01

We describe a portable pyrolysis system for bioenergy production from forest biomass that minimizes long-distance transport costs and provides for nutrient return and long-term soil carbon storage. The cost for transporting biomass to conversion facilities is a major impediment to utilizing forest biomass. If forest biomass could be converted into bio-oil in the field...

Evaluating the impacts of slope aspect on forest dynamic succession in Northwest China based on FAREAST model

NASA Astrophysics Data System (ADS)

Hu, Shanshan; Ma, Jianyong; Shugart, Herman H.; Yan, Xiaodong

2018-03-01

Mountain forests provide the main water resources and lumber for Northwest China. The understanding of the differences in forests growing among individual slope aspects in mountainous regions is of great significance to the wise management and planning of these natural systems. The aim of this study was to investigate the impacts of slope aspect on forest dynamic succession in Northwest China by using the dynamic forest succession model (FAREAST). First, the simulated forest composition and vertical forest zonation produced by the model were compared against recorded data in three sub-regions of the Altai Mountains. The FAREAST model accurately reproduced the vertical zonation, forest composition, growth curves of the dominant species (Larix sibirica), and forest biomass in the Altai Mountains. Transitions along the forest zones of the Altai Mountains averaged about a 400 m difference between the northern and southern sites. Biomass for forests on north-facing slopes were 11.0, 15.3 and 55.9 t C ha-1 higher than for south-facing slopes in the Northeast, Central and Southeast sub-regions, respectively. Second, our analyses showed that the FAREAST model can be used to predict dynamic forest succession in Northwest China under the influence of slope and aspect. In the Altai Mountains, the north-facing slopes supported the best forest growth, followed by the west- and east-facing slopes. South-facing slopes consistently exhibited the lowest growth, biomass storage and forest diversity.

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

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.

Assessment of forest biomass for use as energy. GIS-based analysis of geographical availability and locations of wood-fired power plants in Portugal

Treesearch

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

2010-01-01

Following the European Union strategy concerning renewable energy (RE), Portugal established in their national policy programmes that the production of electrical energy from RE should reach 45% of the total supply by 2010. Since Portugal has large forest biomass resources, a significant part of this energy will be obtained from this source. In addition to the two...

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

PubMed

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

2014-12-02

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

Multiple metrics of diversity have different effects on temperate forest functioning over succession.

PubMed

Yuan, Zuoqiang; Wang, Shaopeng; Gazol, Antonio; Mellard, Jarad; Lin, Fei; Ye, Ji; Hao, Zhanqing; Wang, Xugao; Loreau, Michel

2016-12-01

Biodiversity can be measured by taxonomic, phylogenetic, and functional diversity. How ecosystem functioning depends on these measures of diversity can vary from site to site and depends on successional stage. Here, we measured taxonomic, phylogenetic, and functional diversity, and examined their relationship with biomass in two successional stages of the broad-leaved Korean pine forest in northeastern China. Functional diversity was calculated from six plant traits, and aboveground biomass (AGB) and coarse woody productivity (CWP) were estimated using data from three forest censuses (10 years) in two large fully mapped forest plots (25 and 5 ha). 11 of the 12 regressions between biomass variables (AGB and CWP) and indices of diversity showed significant positive relationships, especially those with phylogenetic diversity. The mean tree diversity-biomass regressions increased from 0.11 in secondary forest to 0.31 in old-growth forest, implying a stronger biodiversity effect in more mature forest. Multi-model selection results showed that models including species richness, phylogenetic diversity, and single functional traits explained more variation in forest biomass than other candidate models. The models with a single functional trait, i.e., leaf area in secondary forest and wood density in mature forest, provided better explanations for forest biomass than models that combined all six functional traits. This finding may reflect different strategies in growth and resource acquisition in secondary and old-growth forests.

Ammonia emissions from biomass burning

Treesearch

Dean A. Hegg; Lawrence F. Radke; Peter V. Hobbs; Philip J. Riggan

1988-01-01

Measurements in the plumes from seven forest fires show that the concentrations of NH3 were considerably in excess of ambient values. Calculation of NH3 emissions from the fires, based on the ratio of NH3/CO in the plumes and emissions of CO from biomass burning, suggest that biomass burning may be a...

Vision of the U.S. biofuel future: a case for hydrogen-enriched biomass gasification

Treesearch

Mark A. Dietenberger; Mark Anderson

2007-01-01

Researchers at the Forest Product Laboratory (FPL) and the University of Wisconsin-Madison (UW) envision a future for biofuels based on biomass gasification with hydrogen enrichment. Synergisms between hydrogen production and biomass gasification technologies will be necessary to avoid being marginalized in the biofuel marketplace. Five feasible engineering solutions...

Seeing the forest beyond the trees

Treesearch

Sassan Saatchi; Joseph Mascaro; Liang Xu; Michael Keller; Yan Yang; Paul Duffy; Fernando Espirito-Santo; Alessandro Baccini; Jeffery Chambers; David Schimel

2014-01-01

In a recent paper (Mitchard et al. 2014, Global Ecology and Biogeography, 23,935-946) a new map of forest biomass based on a geostatistical model of field data for the Amazon (and surrounding forests) was presented and contrasted with two earlier maps based on remote sensing data Saatchi et al. (2011; RS1) and Baccini et al. (2012; RS2). Mitchard et al....

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

NASA Technical Reports Server (NTRS)

Saatchi, Sasan; Rignot, Eric; Vanzyl, Jakob

1995-01-01

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

Long-term effects of clear cutting and intensive biomass harvesting on the nitrogen leaching to groundwater in the boreal forest environment

NASA Astrophysics Data System (ADS)

Kubin, Eero

2013-04-01

Clear-cutting and site preparation cause the greatest changes in site conditions and to the environment. The oldest research carried out within the boreal coniferous forest zone on the leaching of nutrients into watercourses was conducted in Sweden in the early 1970s. Also in Finland, the effect of clear-cutting and site preparation on the quality of surface runoff has been monitored since 1974 and into the groundwater, after waste wood harvesting, since 1986. Recently intensive biomass harvest has been rapidly increasing and nowadays about seven percent of the total consumption of energy in Finland comes from forest energy. The consumption derived from wood-based fuels is as much as 23 per cent of the total energy. Thus study and understanding forest ecosystems function is nowadays facing new challenges, especially when harvested forest energy, especially stumps, course disturbances and more water penetrating into the soil and groundwater in addition to other ecosystem changes. According the long term-monitoring results nitrate nitrogen seems to be the foremost nutrient leached into the groundwater as a consequence of forestry operations. The effects of clear-cutting on nitrate nitrogen leaching and concentrations in surface water have been shown to last only a few years, but the long-term property of increasing groundwater concentrations, have persisted 25 years which has not reported earlier from other sites. Clear-cutting increases the input of precipitation, but in northern areas this cannot be the main reason for the higher values. The greater part of the increased concentrations is due to the decomposition of cutting waste and humus. This is interesting in relation to intensive biomass harvesting. The availability and the quality of water are strongly influenced by forests. The relationship between forests and water is therefore a critical issue that must be accorded high priority also when developing forest biomass harvesting for energy. To develop best forest management practices to protect water quality is becoming more and more important. Forests are stabilizing soils and protecting watersheds. In the conference the long-term effects of different regeneration cuttings and biomass harvesting to the ground water will be discussed with special attention to the needs of understanding the great value of catchment base monitoring.

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 (...

Estimation of merchantable bole volume and biomass above sawlog top in the National Forest inventory of the United States

Treesearch

Grant M. Domke; Christopher M. Oswalt; Christopher W. Woodall; Jeffery A. Turner

2013-01-01

Emerging markets for small-diameter roundwood along with a renewed interest in forest biomass for energy have created a need for estimates of merchantable biomass above the minimum sawlog top diameter for timber species in the national forest inventory of the United States. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service recently adopted the...

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...

Colorado's forest resources, 2004-2013

Treesearch

Michael T. Thompson; John D. Shaw; Chris Witt; Charles E. Werstak; Michael C. Amacher; Sara A. Goeking; R. Justin DeRose; Todd A. Morgan; Colin B. Sorenson; Steven W. Hayes; Jim Menlove

2017-01-01

This report presents a summary of the most recent inventory of Colorado’s forests based on field data collected between 2004 and 2013. The report includes descriptive highlights and tables of area, numbers of trees, biomass, carbon, volume, growth, mortality, and removals. Most sections and tables are organized by forest type or forest-type group, species group,...

Utah's forest resources, 2003-2012

Treesearch

Charles E. Werstak; John D. Shaw; Sara A. Goeking; Christopher Witt; James Menlove; Mike T. Thompson; R. Justin DeRose; Michael C. Amacher; Sarah Jovan; Todd A. Morgan; Colin B. Sorenson; Steven W. Hayes; Chelsea P. McIver

2016-01-01

This report presents a summary of the most recent inventory of Utah’s forests based on field data collected from 2003 through 2012. The report includes descriptive highlights and tables of area, numbers of trees, biomass, volume, growth, mortality, and removals. Most sections and tables are organized by forest type or forest-type group, species group, diameter class,...

Measuring moisture dynamics to predict fire severity in longleaf pine forests.

Treesearch

Sue A. Ferguson; Julia E. Ruthford; Steven J. McKay; David Wright; Clint Wright; Roger Ottmar

2002-01-01

To understand the combustion limit of biomass fuels in a longleaf pine (Pinus palustris) forest, an experiment was conducted to monitor the moisture content of potentially flammable forest floor materials (litter and duff) at Eglin Air Force Base in the Florida Panhandle. While longleaf pine forests are fire dependent ecosystems, a long history of...

New Mexico's forest resources, 2008-2012

Treesearch

Sara A. Goeking; John D. Shaw; Chris Witt; Michael T. Thompson; Charles E. Werstak; Michael C. Amacher; Mary Stuever; Todd A. Morgan; Colin B. Sorenson; Steven W. Hayes; Chelsea P. McIver

2014-01-01

This report presents a summary of the most recent inventory of New Mexico’s forests based on field data collected between 2008 and 2012. The report includes descriptive highlights and tables of area, numbers of trees, biomass, volume, growth, mortality, and removals. Most sections and tables are organized by forest type or forest type group, species group, diameter...

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China.

PubMed

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia.

Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China.

PubMed

He, Huaijiang; Zhang, Chunyu; Zhao, Xiuhai; Fousseni, Folega; Wang, Jinsong; Dai, Haijun; Yang, Song; Zuo, Qiang

2018-01-01

Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9-12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China

PubMed Central

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia. PMID:27002822

Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China

PubMed Central

He, Huaijiang; Zhao, Xiuhai; Fousseni, Folega; Wang, Jinsong; Dai, Haijun; Yang, Song; Zuo, Qiang

2018-01-01

Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9–12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China. PMID:29351291

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

Carbon stock change due to forest management and disturbance must be accounted for in UNFCCC national inventory reports and for signatories to the Kyoto Protocol. Impacts of disturbance on greenhouse gas (GHG) inventories are important for many countries with large forest estates prone to wildfires. Our objective was to measure changes in carbon stocks due to short-term combustion and to simulate longer-term carbon stock dynamics resulting from redistribution among biomass components following wildfire. We studied the impacts of a wildfire in 2009 that burnt temperate forest of tall, wet eucalypts in south-eastern Australia. Biomass combusted ranged from 40 to 58 tC ha−1, which represented 6–7% and 9–14% in low- and high-severity fire, respectively, of the pre-fire total biomass carbon stock. Pre-fire total stock ranged from 400 to 1040 tC ha−1 depending on forest age and disturbance history. An estimated 3.9 TgC was emitted from the 2009 fire within the forest region, representing 8.5% of total biomass carbon stock across the landscape. Carbon losses from combustion were large over hours to days during the wildfire, but from an ecosystem dynamics perspective, the proportion of total carbon stock combusted was relatively small. Furthermore, more than half the stock losses from combustion were derived from biomass components with short lifetimes. Most biomass remained on-site, although redistributed from living to dead components. Decomposition of these components and new regeneration constituted the greatest changes in carbon stocks over ensuing decades. A critical issue for carbon accounting policy arises because the timeframes of ecological processes of carbon stock change are longer than the periods for reporting GHG inventories for national emissions reductions targets. Carbon accounts should be comprehensive of all stock changes, but reporting against targets should be based on human-induced changes in carbon stocks to incentivise mitigation activities. PMID:25208298

Woody biomass-based bioenergy development at the Atikokan Power Generating Station: Local perceptions and public opinions

NASA Astrophysics Data System (ADS)

Baten, Cassia Sanzida

To tackle climate change, reduce air pollution and promote development of renewable energy, the Ontario government is investing in the conversion of the coal-based Atikokan Power Generating Station (APGS) in Atikokan, Ontario, to woody biomass feedstock. This research offers one of the first looks at the perspectives of different individuals and groups on converting woody biomass to energy. Using a combination of study instruments which include literature review, surveys, interviews with key informants, semi-structured interviews, and focus group discussions, this dissertation uses qualitative research to provide a picture of the public's opinions and attitudes towards the APGS biomass energy development. Given Ontario's huge and sustainably managed forest resource, woody biomass is expected to be a major component of renewable energy production in Ontario. The move towards renewable energy that replaces fossil fuels with woody biomass will have considerable socio-economic implications for local and First Nation communities living in and around the bioenergy power generating station. Findings indicate that there is wide support for biomass utilization at the APGS by local people, especially since the project would create sustainable employment. The connection of woody biomass-based energy generation and rural community development provides opportunities and challenges for Atikokan's economic development. Respondents identified economic, environmental and social barriers to biomass utilization, and emphasized trust and transparency as key elements in the successful implementation of the APGS project. As demand for woody biomass-based energy increases, special attention will be needed to ensure and maintain the social, economic and environmental sustainability of biomass use at the APGS. In this research, respondents' views about biomass utilization for energy mainly focused on forest-related issues rather than energy. In Atikokan much of the project's social acceptability is directly linked to woody biomass providing job creation and community stability. Given this, it will be important to design policies and projects from a community development perspective to ensure long term community support. Information provided by this research creates a base for discussions as forest biomass energy becomes a vital issue in Northwestern Ontario, Canada, and other regions of the world. This research provides a look at a community's views using a method that provides breadth of information but that is specific in scope. Further research will be required to determine the reach of these opinions within the stakeholder groups, the general public, and across different regions.

Effects of harvesting forest biomass on water and climate regulation services: A synthesis of long-term ecosystem experiments in eastern North America

USGS Publications Warehouse

Caputo, Jesse; Beier, Colin D; Groffman, Peter M; Burns, Douglas A.; Beall, Frederick D; Hazlett, Paul W.; Yorks, Thad E

2016-01-01

Demand for woody biomass fuels is increasing amidst concerns about global energy security and climate change, but there may be negative implications of increased harvesting for forest ecosystem functions and their benefits to society (ecosystem services). Using new methods for assessing ecosystem services based on long-term experimental research, post-harvest changes in ten potential benefits were assessed for ten first-order northern hardwood forest watersheds at three long-term experimental research sites in northeastern North America. As expected, we observed near-term tradeoffs between biomass provision and greenhouse gas regulation, as well as tradeoffs between intensive harvest and the capacity of the forest to remediate nutrient pollution. In both cases, service provision began to recover along with the regeneration of forest vegetation; in the case of pollution remediation, the service recovered to pre-harvest levels within 10 years. By contrast to these two services, biomass harvesting had relatively nominal and transient impacts on other ecosystem services. Our results are sensitive to empirical definitions of societal demand, including methods for scaling societal demand to ecosystem units, which are often poorly resolved. Reducing uncertainty around these parameters can improve confidence in our results and increase their relevance for decision-making. Our synthesis of long-term experimental studies provides insights on the social-ecological resilience of managed forest ecosystems to multiple drivers of change.

Woody biomass utilization trends, barriers, and strategies: Perspectives of U.S. Forest Service managers

Treesearch

Shiloh Sundstrom; Max Nielsen-Pincus; Cassandra Moseley; Sarah McCaffrey

2012-01-01

The use of woody biomass is being promoted across the United States as a means of increasing energy independence, mitigating climate change, and reducing the cost of hazardous fuels reduction treatments and forest restoration projects. The opportunities and challenges for woody biomass use on the national forest system are unique. In addition to making woody biomass...

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...

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...

Shifts in tree functional composition amplify the response of forest biomass to climate

NASA Astrophysics Data System (ADS)

Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W.

2018-04-01

Forests have a key role in global ecosystems, hosting much of the world’s terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.

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

PubMed

Zhang, Tao; Niinemets, Ülo; Sheffield, Justin; Lichstein, Jeremy W

2018-04-05

Forests have a key role in global ecosystems, hosting much of the world's terrestrial biodiversity and acting as a net sink for atmospheric carbon. These and other ecosystem services that are provided by forests may be sensitive to climate change as well as climate variability on shorter time scales (for example, annual to decadal). Previous studies have documented responses of forest ecosystems to climate change and climate variability, including drought-induced increases in tree mortality rates. However, relationships between forest biomass, tree species composition and climate variability have not been quantified across a large region using systematically sampled data. Here we use systematic forest inventories from the 1980s and 2000s across the eastern USA to show that forest biomass responds to decadal-scale changes in water deficit, and that this biomass response is amplified by concurrent changes in community-mean drought tolerance, a functionally important aspect of tree species composition. The amplification of the direct effects of water stress on biomass occurs because water stress tends to induce a shift in tree species composition towards species that are more tolerant to drought but are slower growing. These results demonstrate concurrent changes in forest species composition and biomass carbon storage across a large, systematically sampled region, and highlight the potential for climate-induced changes in forest ecosystems across the world, resulting from both direct effects of climate on forest biomass and indirect effects mediated by shifts in species composition.

Quantifying legacies of clearcut on carbon fluxes and biomass carbon stock in northern temperate forests

Treesearch

W. Wang; J. Xiao; S. V. Ollinger; J. Chen; A. Noormets

2014-01-01

Stand-replacing disturbances including harvests have substantial impacts on forest carbon (C) fluxes and stocks. The quantification and simulation of these effects is essential for better understanding forest C dynamics and informing forest management 5 in the context of global change. We evaluated the process-based forest ecosystem model, PnET-CN, for how well and by...

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

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.

[Effects of forest canopy gap on Abies faxoniana seedling's biomass and its allocation in sub-alpine coniferous forest of West Sichuan].

PubMed

Xian, Jun-Ren; Hu, Ting-Xing; Zhang, Yuan-Bin; Wang, Kai-Yun

2007-04-01

By the method of strip transect sampling, the density, height, basal diameter, and components biomass of Abies faxoniana seedlings (H < or = 100 cm) lived in the forest gap (FG) and under the forest canopy (FC) of subalpine natural coniferous forest in West Sichuan were investigated, and the relationships among different components biomass were analyzed. The results indicated that the density and average height (H) of A. faxoniana seedlings were significantly different in FG and under FC, with the values being 12 903 and 2 017 per hectare, and 26.6 cm and 24.3 cm, respectively, while no significant differences were found in average basal diameter (D) and biomass. The biomass allocation in seedling's components was markedly affected by forest gap. In FG, the biomass ratio of branch to trunk (BRBT) reached the maximum (1.54) at 12th year, and then, declined and fluctuated at 0. 69. Under FC, the BRBT was increased with seedlings growth, and exceeded 1.0 at about 15th year. The total biomass and the biomass of leaf, stem, shoot and root grown in FG and under FC were significantly linearly correlated with D2H. There were significant positive correlations among the biomass of different seedling's components.

Effects of site preparation for pine forest/switchgrass Intercropping on water quality

Treesearch

A. Muwamba; D. M. Amatya; H. Ssegane; G.M. Chescheir; T. Appelboom; E.W. Tollner; J. E. Nettles; M. A. Youssef; F. Birgand; R. W. Skaggs; S. Tian

2015-01-01

A study was initiated to investigate the sustainability effects of intercropping switchgrass (Panicum virgatum L.) in a loblolly pine (Pinus taeda L.) plantation. This forest-based biofuel system could possibly provide biomass from the perennial energy grass while maintaining the economics and environmental benefits of a forest...

An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India.

PubMed

Deb, Dibyendu; Singh, J P; Deb, Shovik; Datta, Debajit; Ghosh, Arunava; Chaurasia, R S

2017-10-20

Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology in last few decades, AGB estimation now can be done using space-borne and airborne remotely sensed data. It is a well-established, time saving and cost effective technique with high precision and is frequently applied by the scientific community. It involves development of allometric equations based on correlations of ground-based forest biomass measurements with vegetation indices derived from remotely sensed data. However, selection of the best-fit and explanatory models of biomass estimation often becomes a difficult proposition with respect to the image data resolution (spatial and spectral) as well as the sensor platform position in space. Using Resourcesat-2 satellite data and Normalized Difference Vegetation Index (NDVI), this pilot scale study compared traditional linear and nonlinear models with an artificial intelligence-based non-parametric technique, i.e. artificial neural network (ANN) for formulation of the best-fit model to determine AGB of forest of the Bundelkhand region of India. The results confirmed the superiority of ANN over other models in terms of several statistical significance and reliability assessment measures. Accordingly, this study proposed the use of ANN instead of traditional models for determination of AGB and other bio-physical parameters of any dry deciduous forest of tropical sub-humid or semi-arid area. In addition, large numbers of sampling sites with different quadrant sizes for trees, shrubs, and herbs as well as application of LiDAR data as predictor variable were recommended for very high precision modelling in ANN for a large scale study.

Forest structure and downed woody debris in boreal, temperate, and tropical forest fragments.

PubMed

Gould, William A; González, Grizelle; Hudak, Andrew T; Hollingsworth, Teresa Nettleton; Hollingsworth, Jamie

2008-12-01

Forest fragmentation affects the heterogeneity of accumulated fuels by increasing the diversity of forest types and by increasing forest edges. This heterogeneity has implications in how we manage fuels, fire, and forests. Understanding the relative importance of fragmentation on woody biomass within a single climatic regime, and along climatic gradients, will improve our ability to manage forest fuels and predict fire behavior. In this study we assessed forest fuel characteristics in stands of differing moisture, i.e., dry and moist forests, structure, i.e., open canopy (typically younger) vs. closed canopy (typically older) stands, and size, i.e., small (10-14 ha), medium (33 to 60 ha), and large (100-240 ha) along a climatic gradient of boreal, temperate, and tropical forests. We measured duff, litter, fine and coarse woody debris, standing dead, and live biomass in a series of plots along a transect from outside the forest edge to the fragment interior. The goal was to determine how forest structure and fuel characteristics varied along this transect and whether this variation differed with temperature, moisture, structure, and fragment size. We found nonlinear relationships of coarse woody debris, fine woody debris, standing dead and live tree biomass with mean annual median temperature. Biomass for these variables was greatest in temperate sites. Forest floor fuels (duff and litter) had a linear relationship with temperature and biomass was greatest in boreal sites. In a five-way multivariate analysis of variance we found that temperature, moisture, and age/structure had significant effects on forest floor fuels, downed woody debris, and live tree biomass. Fragment size had an effect on forest floor fuels and live tree biomass. Distance from forest edge had significant effects for only a few subgroups sampled. With some exceptions edges were not distinguishable from interiors in terms of fuels.

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

Treesearch

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

2012-01-01

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

Emissions tradeoffs associated with cofiring forest biomass with coal: A case study in Colorado, USA

Treesearch

Dan Loeffler; Nathaniel Anderson

2014-01-01

Cofiring forest biomass residues with coal to generate electricity is often cited for its potential to offset fossil fuels and reduce greenhouse gas emissions, but the extent to which cofiring achieves these objectives is highly dependent on case specific variables. This paper uses facility and forest specific data to examine emissions from cofiring forest biomass with...

Multiscale assessment of water limitations on forest carbon cycling in the western United States

NASA Astrophysics Data System (ADS)

Berner, L. T.; Law, B. E.

2016-12-01

Water is a key environmental constraint on carbon uptake, storage, and release by forests in the western United States. Climate in this region is becoming warmer and drier, thus highlighting the need to better understand how forest carbon cycling responds to variation in water availability. Here, we describe how forest carbon cycling varied spatially along local to regional gradients in climatic water availability. We examined local variation in net primary productivity (NPP) and aboveground biomass (AGB) using 12 intensive field plots in Oregon's Cascade Mountains. Regional analysis of forest NPP and AGB was based on federal forest inventories (>8,000 plots) in Washington, Oregon, and California, multiple biomass maps and MODIS NPP (2003-2012). We also quantified annual forest AGB mortality due to bark beetles and fires across the region from 2003-2012 by combining several disturbance and biomass data sets. Over each spatial extent, forest NPP and AGB increased curvilinearly with average growing-year climate moisture index, computed as the cumulative difference between precipitation and potential evapotranspiration from October-September and averaged over preceding decades. Thus, climatic water availability strongly constrains forest carbon uptake and storage, particularly in the driest areas, but also in the wettest. Forest AGB mortality rates from bark beetles and fires peaked in moderately dry forests and then declining rapidly in the wettest areas. Annual forest AGB mortality from bark beetles was about twice as high as from fires. Bark beetle impacts were most pronounced in the Rock Mountains, while fire impacts were most pronounced in western portion of the region. Our multiscale analysis based on field inventory and remote sensing data sets demonstrates that climatic water availability is a key environmental constraint on forest carbon cycling in the western US. Consequently, continued warming and drying can be expected to have substantial impacts on forest carbon cycling in this region over the coming century.

Assessing the Impact of Disturbance on Carbon Stocks in Western Forests using Remote Sensing and Forest Inventory Data

NASA Astrophysics Data System (ADS)

Cooper, L. A.; Ballantyne, A. P.; Landguth, E.; Holden, Z. A.

2014-12-01

Forest disturbances have important impacts on regional and global carbon-climate feedbacks. Tree mortality resulting from disturbance can cause large areas to transition from carbon (C) sinks to C sources. Although severe acute disturbance, such as fire, has been quantified extensively in the literature, the impacts of disturbance that cause more spatially heterogeneous, gradual, mortality, such as beetle kill, are more difficult to quantify and have not been studied as extensively. Combining a 13 year time series of 250 meter, 16-day, MODIS Enhanced Vegetation Index (EVI) data with field data on insect mortality collected by the U.S. Forest Service Forest Inventory and Analysis (FIA) program, we have produced large-scale maps of dead woody biomass resulting from insect epidemics. Using a change detection algorithm, we were able to determine the timing and severity of changes in EVI due to insect epidemics across the western United States. A model was created to predict biomass based on EVI and a variety of environmental variables. Using the difference between post- and pre-outbreak EVI values, we were able to estimate the loss of biomass during insect outbreaks. These biomass data were then converted to carbon as a percentage of dry biomass using the Jenkins equations. This spatially explicit map of C currently stored in beetle kill wood will allow us to assess the vulnerability of this C to re-entering the atmosphere as CO2 via combustion or decomposition.

The financial feasibility of delivering forest treatment residues to bioenergy facilities over a range of diesel fuel and delivered biomass prices

Treesearch

Greg Jones; Dan Loeffler; Edward Butler; Susan Hummel; Woodam Chung

2013-01-01

Forest treatments have the potential to produce significant quantities of forest residue biomass, which includes the tops and limbs from merchantable trees and smaller trees removed to meet management objectives. We spatially analyzed the sensitivity of financially feasible biomass volumes for delivery to a bioenergy facility across 16 combinations of delivered biomass...

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...

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.

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.

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

PubMed Central

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

2007-01-01

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

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

PubMed

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

2007-11-22

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

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

PubMed

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

2017-10-18

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

Opportunities for using wood and biofibers for energy, chemical feedstocks, and structural applications

Treesearch

J. E. Winandy; R. S. Williams; A. W. Rudie; R. J. Ross

2008-01-01

This chapter describes 'integrated biomass technologies', a systematic approach for maximizing value, performance, resource sustainability, and profitability in the agriculture and forest products industries. The fundamental principles of integrated biomass technologies provide a global roadmap to a bio-based economy based on the systematic use of many less-...

Minnesota's forest resources in 2005

Treesearch

Patrick D. Miles; Gary J. Brand

2007-01-01

Reports forest statistics for Minnesota based on five annual inventories from 2001 through 2005. Minnesota's total forest area is estimated at 16.3 million acres or 32 percent of the total land area of the State. The estmated total live-tree volume on forest land is 17.7 billion cubic feet or 1,085 cubic feet per acre. The estimated aboveground live-tree biomass...

Long-term soil productivity: genesis of the concept and principles behind the program

Treesearch

Robert F. Powers

2006-01-01

The capacity of a forest site to capture carbon and convert it into biomass defines fundamental site productivity. In the United States, the National Forest Management Act (NFMA) of 1976 mandates that this capacity must be protected on federally managed lands. Responding to NFMA, the USDA Forest Service began a soil-based monitoring program for its managed forests....

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

Treesearch

Veronika Leitold; Michael Keller; Douglas C Morton; Bruce D Cook; Yosio E Shimabukuro

2015-01-01

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas...

National scale biomass estimators for United States tree species

Treesearch

Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

2003-01-01

Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...

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

Treesearch

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

2009-01-01

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

Tree biomass in the North Central Region.

Treesearch

Gerhard K. Raile; Pamela J. Jakes

1982-01-01

Methods for calculating tree biomass are outlined, and the biomass on commercial forest land is estimated for 11 north-central states. Tree biomass in the North Central Region totals 3.6 billion tons, or 50 tons per commercial forest acre. For all species, total tree biomass is concentrated in growing-stock boles.

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

PubMed

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

2013-01-01

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

Using LiDAR Data to Measure the 3D Green Biomass of Beijing Urban Forest in China

PubMed Central

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

2013-01-01

The purpose of the paper is to find a new approach to measure 3D green biomass of urban forest and to testify its precision. In this study, the 3D green biomass could be acquired on basis of a remote sensing inversion model in which each standing wood was first scanned by Terrestrial Laser Scanner to catch its point cloud data, then the point cloud picture was opened in a digital mapping data acquisition system to get the elevation in an independent coordinate, and at last the individual volume captured was associated with the remote sensing image in SPOT5(System Probatoired'Observation dela Tarre)by means of such tools as SPSS (Statistical Product and Service Solutions), GIS (Geographic Information System), RS (Remote Sensing) and spatial analysis software (FARO SCENE and Geomagic studio11). The results showed that the 3D green biomass of Beijing urban forest was 399.1295 million m3, of which coniferous was 28.7871 million m3 and broad-leaf was 370.3424 million m3. The accuracy of 3D green biomass was over 85%, comparison with the values from 235 field sample data in a typical sampling way. This suggested that the precision done by the 3D forest green biomass based on the image in SPOT5 could meet requirements. This represents an improvement over the conventional method because it not only provides a basis to evalue indices of Beijing urban greenings, but also introduces a new technique to assess 3D green biomass in other cities. PMID:24146792

Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms

PubMed Central

Dube, Timothy; Mutanga, Onisimo; Adam, Elhadi; Ismail, Riyad

2014-01-01

The quantification of aboveground biomass using remote sensing is critical for better understanding the role of forests in carbon sequestration and for informed sustainable management. Although remote sensing techniques have been proven useful in assessing forest biomass in general, more is required to investigate their capabilities in predicting intra-and-inter species biomass which are mainly characterised by non-linear relationships. In this study, we tested two machine learning algorithms, Stochastic Gradient Boosting (SGB) and Random Forest (RF) regression trees to predict intra-and-inter species biomass using high resolution RapidEye reflectance bands as well as the derived vegetation indices in a commercial plantation. The results showed that the SGB algorithm yielded the best performance for intra-and-inter species biomass prediction; using all the predictor variables as well as based on the most important selected variables. For example using the most important variables the algorithm produced an R2 of 0.80 and RMSE of 16.93 t·ha−1 for E. grandis; R2 of 0.79, RMSE of 17.27 t·ha−1 for P. taeda and R2 of 0.61, RMSE of 43.39 t·ha−1 for the combined species data sets. Comparatively, RF yielded plausible results only for E. dunii (R2 of 0.79; RMSE of 7.18 t·ha−1). We demonstrated that although the two statistical methods were able to predict biomass accurately, RF produced weaker results as compared to SGB when applied to combined species dataset. The result underscores the relevance of stochastic models in predicting biomass drawn from different species and genera using the new generation high resolution RapidEye sensor with strategically positioned bands. PMID:25140631

Nitrogen fertilization decreases forest soil fungal and bacterial biomass in three long-term experiments

Treesearch

Matthew D. Wallenstein; Steven McNulty; Ivan J. Fernandez; Johnny Boggs; William H. Schlesinger

2006-01-01

We examined the effects of N fertilization on forest soil fungal and bacterial biomass at three long-term experiments in New England (Harvard Forest, MA; Mt. Ascutney, VT; Bear Brook, ME). At Harvard Forest, chronic N fertilization has decreased organic soil microbial biomass C (MBC) by an average of 54% and substrate induced respiration (SIR) was decreased by an...

Biomass removal and its effect on productivity of an artificially regenerated forest stand in the Missouri ozarks

Treesearch

Flex Jr. Ponder

2007-01-01

Intensive harvesting, which removes a greater proportion of the forest biomass than conventional harvesting and the associated nutrients, may cause a decline in forest productivity. Planted seedling response to three biomass removal levels (1. removal of boles only=OM1, 2. all surface organic matter removed, forest floor not removed=OM2, and 3. removal of all surface...

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 by providing novel, annual measurements of carbon losses and gains, from forest loss, degradation, and growth, with reduced uncertainty that stems from an unconventional shift in emphasis away from classifications of land area change toward direct estimation of carbon density dynamics.

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

PubMed

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

2014-06-01

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

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

PubMed

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

2016-09-01

The impacts of climate change on forest net biomass change are poorly understood but critical for predicting forest's contribution to the global carbon cycle. Recent studies show climate change-associated net biomass declines in mature forest plots. The representativeness of these plots for regional forests, however, remains uncertain because we lack an assessment of whether climate change impacts differ with forest age. Using data from plots of varying ages from 17 to 210 years, monitored from 1958 to 2011 in western Canada, we found that climate change has little effect on net biomass change in forests ≤ 40 years of age due to increased growth offsetting increased mortality, but has led to large decreases in older forests due to increased mortality accompanying little growth gain. Our analysis highlights the need to incorporate forest age profiles in examining past and projecting future forest responses to climate change. © 2016 John Wiley & Sons Ltd/CNRS.

The stage-classified matrix models project a significant increase in biomass carbon stocks in China’s forests between 2005 and 2050

PubMed Central

Hu, Huifeng; Wang, Shaopeng; Guo, Zhaodi; Xu, Bing; Fang, Jingyun

2015-01-01

China’s forests are characterized by young age, low carbon (C) density and a large plantation area, implying a high potential for increasing C sinks in the future. Using data of provincial forest area and biomass C density from China’s forest inventories between 1994 and 2008 and the planned forest coverage of the country by 2050, we developed a stage-classified matrix model to predict biomass C stocks of China’s forests from 2005 to 2050. The results showed that total forest biomass C stock would increase from 6.43 Pg C (1 Pg = 1015 g) in 2005 to 9.97 Pg C (95% confidence interval: 8.98 ~ 11.07 Pg C) in 2050, with an overall net C gain of 78.8 Tg C yr−1 (56.7 ~ 103.3 Tg C yr−1; 1 Tg = 1012 g). Our findings suggest that China’s forests will be a large and persistent biomass C sink through 2050. PMID:26110831

The stage-classified matrix models project a significant increase in biomass carbon stocks in China's forests between 2005 and 2050.

PubMed

Hu, Huifeng; Wang, Shaopeng; Guo, Zhaodi; Xu, Bing; Fang, Jingyun

2015-06-25

China's forests are characterized by young age, low carbon (C) density and a large plantation area, implying a high potential for increasing C sinks in the future. Using data of provincial forest area and biomass C density from China's forest inventories between 1994 and 2008 and the planned forest coverage of the country by 2050, we developed a stage-classified matrix model to predict biomass C stocks of China's forests from 2005 to 2050. The results showed that total forest biomass C stock would increase from 6.43 Pg C (1 Pg = 10(15) g) in 2005 to 9.97 Pg C (95% confidence interval: 8.98 ~ 11.07 Pg C) in 2050, with an overall net C gain of 78.8 Tg C yr(-1) (56.7 ~ 103.3 Tg C yr(-1); 1 Tg = 10(12) g). Our findings suggest that China's forests will be a large and persistent biomass C sink through 2050.

Influence of Tree Species Composition and Community Structure on Carbon Density in a Subtropical Forest

PubMed Central

Hu, Yanqiu; Su, Zhiyao; Li, Wenbin; Li, Jingpeng; Ke, Xiandong

2015-01-01

We assessed the impact of species composition and stand structure on the spatial variation of forest carbon density using data collected from a 4-ha plot in a subtropical forest in southern China. We found that 1) forest biomass carbon density significantly differed among communities, reflecting a significant effect of community structure and species composition on carbon accumulation; 2) soil organic carbon density increased whereas stand biomass carbon density decreased across communities, indicating that different mechanisms might account for the accumulation of stand biomass carbon and soil organic carbon in the subtropical forest; and 3) a small number of tree individuals of the medium- and large-diameter class contributed predominantly to biomass carbon accumulation in the community, whereas a large number of seedlings and saplings were responsible for a small proportion of the total forest carbon stock. These findings demonstrate that both biomass carbon and soil carbon density in the subtropical forest are sensitive to species composition and community structure, and that heterogeneity in species composition and stand structure should be taken into account to ensure accurate forest carbon accounting. PMID:26317523

Influence of Tree Species Composition and Community Structure on Carbon Density in a Subtropical Forest.

PubMed

Hu, Yanqiu; Su, Zhiyao; Li, Wenbin; Li, Jingpeng; Ke, Xiandong

2015-01-01

We assessed the impact of species composition and stand structure on the spatial variation of forest carbon density using data collected from a 4-ha plot in a subtropical forest in southern China. We found that 1) forest biomass carbon density significantly differed among communities, reflecting a significant effect of community structure and species composition on carbon accumulation; 2) soil organic carbon density increased whereas stand biomass carbon density decreased across communities, indicating that different mechanisms might account for the accumulation of stand biomass carbon and soil organic carbon in the subtropical forest; and 3) a small number of tree individuals of the medium- and large-diameter class contributed predominantly to biomass carbon accumulation in the community, whereas a large number of seedlings and saplings were responsible for a small proportion of the total forest carbon stock. These findings demonstrate that both biomass carbon and soil carbon density in the subtropical forest are sensitive to species composition and community structure, and that heterogeneity in species composition and stand structure should be taken into account to ensure accurate forest carbon accounting.

Kansas' forest resources, 2005

Treesearch

W. Keith Moser; Gary J. Brand; Melissa Powers

2007-01-01

The USDA Forest Service, Northern Research Station, Forest Inventory and Analysis (NRS-FIA) program is changing to a Web-based, dynamically linked reporting system. As part of the process, this year NRS-FIA is producing this abbreviated summary of 2005 data. This resource bulletin reports on area, volume, and biomass using data from 2001 through 2005. Estimates from...

Carbon fluxes in tropical forest ecosystems: the value of Eddy-covariance data for individual-based dynamic forest gap models

NASA Astrophysics Data System (ADS)

Roedig, Edna; Cuntz, Matthias; Huth, Andreas

2015-04-01

The effects of climatic inter-annual fluctuations and human activities on the global carbon cycle are uncertain and currently a major issue in global vegetation models. Individual-based forest gap models, on the other hand, model vegetation structure and dynamics on a small spatial (<100 ha) and large temporal scale (>1000 years). They are well-established tools to reproduce successions of highly-diverse forest ecosystems and investigate disturbances as logging or fire events. However, the parameterizations of the relationships between short-term climate variability and forest model processes are often uncertain in these models (e.g. daily variable temperature and gross primary production (GPP)) and cannot be constrained from forest inventories. We addressed this uncertainty and linked high-resolution Eddy-covariance (EC) data with an individual-based forest gap model. The forest model FORMIND was applied to three diverse tropical forest sites in the Amazonian rainforest. Species diversity was categorized into three plant functional types. The parametrizations for the steady-state of biomass and forest structure were calibrated and validated with different forest inventories. The parameterizations of relationships between short-term climate variability and forest model processes were evaluated with EC-data on a daily time step. The validations of the steady-state showed that the forest model could reproduce biomass and forest structures from forest inventories. The daily estimations of carbon fluxes showed that the forest model reproduces GPP as observed by the EC-method. Daily fluctuations of GPP were clearly reflected as a response to daily climate variability. Ecosystem respiration remains a challenge on a daily time step due to a simplified soil respiration approach. In the long-term, however, the dynamic forest model is expected to estimate carbon budgets for highly-diverse tropical forests where EC-measurements are rare.

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 used Dynamic Global Vegetation Model to understand the possible vegetation dynamics in the event of climate change. The vegetation represents a biogeographic regime. Simulations were carried out for 70 years time period. The model produced leaf area index and biomass for each plant functional type and biome for each grid in that region.

[Characteristics of carbon storage of Inner Mongolia forests: a review].

PubMed

Yang, Hao; Hu, Zhong-Min; Zhang, Lei-Ming; Li, Sheng-Gong

2014-11-01

Forests in Inner Mongolia account for an important part of the forests in China in terms of their large area and high living standing volume. This study reported carbon storage, carbon density, carbon sequestration rate and carbon sequestration potential of forest ecosystems in Inner Mongolia using the biomass carbon data from the related literature. Through analyzing the data of forest inventory and the generalized allometric equations between volume and biomass, previous studies had reported that biomass carbon storage of the forests in Inner Mongolia was about 920 Tg C, which was 12 percent of the national forest carbon storage, the annual average growth rate was about 1.4%, and the average of carbon density was about 43 t · hm(-2). Carbon storage and carbon density showed an increasing trend over time. Coniferous and broad-leaved mixed forest, Pinus sylvestris var. mongolica forest and Betula platyphylla forest had higher carbon sequestration capacities. Carbon storage was reduced due to human activities such as thinning and clear cutting. There were few studies on carbon storage of the forests in Inner Mongolia with focus on the soil, showing that the soil car- bon density increased with the stand age. Study on the carbon sequestration potential of forest ecosystems was still less. Further study was required to examine dynamics of carbon storage in forest ecosystems in Inner Mongolia, i. e., to assess carbon storage in the forest soils together with biomass carbon storage, to compute biomass carbon content of species organs as 45% in the allometric equations, to build more species-specific and site-specific allometric equations including root biomass for different dominant species, and to take into account the effects of climate change on carbon sequestration rate and carbon sequestration potential.

Accuracy assessment of biomass and forested area classification from modis, landstat-tm satellite imagery and forest inventory plot data

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2007-01-01

The objective of this study was to determine how well forestfnon-forest and biomass classifications obtained from Landsat-TM and MODIS satellite data modeled with FIA plots, compare to each other and with forested area and biomass estimates from the national inventory data, as well as whether there is an increase in overall accuracy when pixel size (spatial resolution...

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

PubMed

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

2014-09-23

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

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

PubMed Central

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

2014-01-01

Whether the fraction of total forest biomass distributed in roots, stems, or leaves varies systematically across geographic gradients remains unknown despite its importance for understanding forest ecology and modeling global carbon cycles. It has been hypothesized that plants should maintain proportionally more biomass in the organ that acquires the most limiting resource. Accordingly, we hypothesize greater biomass distribution in roots and less in stems and foliage in increasingly arid climates and in colder environments at high latitudes. Such a strategy would increase uptake of soil water in dry conditions and of soil nutrients in cold soils, where they are at low supply and are less mobile. We use a large global biomass dataset (>6,200 forests from 61 countries, across a 40 °C gradient in mean annual temperature) to address these questions. Climate metrics involving temperature were better predictors of biomass partitioning than those involving moisture availability, because, surprisingly, fractional distribution of biomass to roots or foliage was unrelated to aridity. In contrast, in increasingly cold climates, the proportion of total forest biomass in roots was greater and in foliage was smaller for both angiosperm and gymnosperm forests. These findings support hypotheses about adaptive strategies of forest trees to temperature and provide biogeographically explicit relationships to improve ecosystem and earth system models. They also will allow, for the first time to our knowledge, representations of root carbon pools that consider biogeographic differences, which are useful for quantifying whole-ecosystem carbon stocks and cycles and for assessing the impact of climate change on forest carbon dynamics. PMID:25225412

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

USGS Publications Warehouse

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

2014-01-01

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

Biomass utilization modeling on the Bitterroot National Forest

Treesearch

Robin P. Silverstein; Dan Loeffler; J. Greg Jones; Dave E. Calkin; Hans R. Zuuring; Martin Twer

2006-01-01

Utilization of small-sized wood (biomass) from forests as a potential source of renewable energy is an increasingly important aspect of fuels management on public lands as an alternative to traditional disposal methods (open burning). The potential for biomass utilization to enhance the economics of treating hazardous forest fuels was examined on the Bitterroot...

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...

Forest fuel reduction and biomass supply: perspectives from southern private landowners

Treesearch

Jianbang Gan; Adam Jarrett; Cassandra Johnson Gaither

2013-01-01

Removing excess biomass from fire-hazardous forests can serve dual purposes: enhancing the health and sustainability of forest ecosystems and supplying feedstock for energy production. The physical availability of this biomass is fairly well-known, yet availability does not necessarily translate into actual supply. We assess the perception and behavior of private...

Drivers of biomass co-firing in U.S. coal-fired power plants

Treesearch

Michael E. Goerndt; Francisco X. Aguilar; Kenneth Skog

2013-01-01

Substantial knowledge has been generated in the U.S. about the resource base for forest and other residue-derived biomass for bioenergy including co-firing in power plants. However, a lack of understanding regarding power plant-level operations and manager perceptions of drivers of biomass co-firing remains. This study gathered information from U.S. power plant...

Calibration of volume and component biomass equations for Douglas-fir and lodgepole pine in Western Oregon forests

Treesearch

Krishna P. Poudel; Temesgen Hailemariam

2016-01-01

Using data from destructively sampled Douglas-fir and lodgepole pine trees, we evaluated the performance of regional volume and component biomass equations in terms of bias and RMSE. The volume and component biomass equations were calibrated using three different adjustment methods that used: (a) a correction factor based on ordinary least square regression through...

Unexpectedly large impact of forest management and grazing on global vegetation biomass

PubMed Central

Erb, K.-H.; Bais, A.L.S.; Carvalhais, N.; Fetzel, T.; Gingrich, S.; Haberl, H.; Lauk, C.; Niedertscheider, M.; Pongratz, J.; Thurner, M.; Luyssaert, S.

2017-01-01

Carbon stocks in vegetation play a key role in the climate system1–4, but their magnitude and patterns, their uncertainties, and the impact of land use on them remain poorly quantified. Based on a consistent integration of state-of-the art datasets, we show that vegetation currently stores ~450 PgC. In the hypothetical absence of land use, potential vegetation would store ~916 PgC, under current climate. This difference singles out the massive effect land use has on biomass stocks. Deforestation and other land-cover changes are responsible for 53-58% of the difference between current and potential biomass stocks. Land management effects, i.e. land-use induced biomass stock changes within the same land cover, contribute 42-47% but are underappreciated in the current literature. Avoiding deforestation hence is necessary but not sufficient for climate-change mitigation. Our results imply that trade-offs exist between conserving carbon stocks on managed land and raising the contribution of biomass to raw material and energy supply for climate change mitigation. Efforts to raise biomass stocks are currently only verifiable in temperate forests, where potentials are limited. In contrast, large uncertainties hamper verification in the tropical forest where the largest potentials are located, pointing to challenges for the upcoming stocktaking exercises under the Paris agreement. PMID:29258288

The relative contributions of forest growth and areal expansion to forest biomass carbon

Treesearch

P. Li; J. Zhu; H. Hu; Z. Guo; Y. Pan; R. Birdsey; J. Fang

2016-01-01

Forests play a leading role in regional and global terrestrial carbon (C) cycles. Changes in C sequestration within forests can be attributed to areal expansion (increase in forest area) and forest growth (increase in biomass density). Detailed assessment of the relative contributions of areal expansion and forest growth to C sinks is crucial to reveal the mechanisms...

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

NASA Technical Reports Server (NTRS)

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

1995-01-01

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

Forest treatment residues for thermal energy compared with disposal by onsite burning: Emissions and energy return

Treesearch

Greg Jones; Dan Loeffler; David Calkin; Woodam Chung

2010-01-01

Mill residues from forest industries are the source for most of the current wood-based energy in the US, approximately 2.1% of the nation's energy use in 2007. Forest residues from silvicultural treatments, which include limbs, tops, and small non-commercial trees removed for various forest management objectives, represent an additional source of woody biomass for...

Measuring and modeling carbon stock change estimates for US forests and uncertainties from apparent inter-annual variability

Treesearch

James E. Smith; Linda S. Heath

2015-01-01

Our approach is based on a collection of models that convert or augment the USDA Forest Inventory and Analysis program survey data to estimate all forest carbon component stocks, including live and standing dead tree aboveground and belowground biomass, forest floor (litter), down deadwood, and soil organic carbon, for each inventory plot. The data, which include...

[Carbon storage of forest vegetation and allocation for main forest types in the east of Da-xing'an Mountains based on additive biomass model].

PubMed

Peng, Wei; Dong, Li Hu; Li, Feng Ri

2016-12-01

Based on the biomass investigation data of main forest types in the east of Daxing'an Mountains, the additive biomass models of 3 main tree species were developed and the changes of carbon storage and allocation of forest community of tree layer, shrub layer, herb layer and litter layer from different forest types were discussed. The results showed that the carbon storage of tree layer, shrub layer, herb layer and litter layer for Rhododendron dauricum-Larix gmelinii forest was 71.00, 0.34, 0.05 and 11.97 t·hm -2 , respectively. Similarly, the carbon storage of the four layers of Ledum palustre-L. gmelinii forest was 47.82, 0.88, 0, 5.04 t·hm -2 , 56.56, 0.44, 0.04, 8.72 t·hm -2 for R. dauricum-mixed forest of L. gmelinii-Betula platyphylla, 46.21, 0.66, 0.07, 6.16 t·hm -2 for L. palustre-mixed forest of L. gmelinii-B. platyphylla, 40.90, 1.37, 0.04, 3.67 t·hm -2 for R. dauricum-B. platyphylla forest, 36.28, 1.12, 0.18, 4.35 t·hm -2 for L. palustre-B. platyphylla forest. The carbon storage of forest community for the understory vegetation of R. dauricum was higher than that of the forest with L. palustre. In the condition of similar circumstances for the understory, the order of carbon storage for forest community was L. gmelinii forest > the mixed forest of L. gmelinii-B. platyphylla > B. platyphylla forest. The carbon storage of different forest types was different with the order of R. dauricum-L. gmelinii forest (83.36 t·hm -2 )> R. dauricum-mixed forest of L. gmelinii-B. platyphylla (65.76 t·hm -2 ) > L. palustre-L. gmelinii forest (53.74 t·hm -2 )> L. palustre-mixed forest of L. gmelinii-B. platyphylla (53.10 t·hm -2 )> R. dauricum-B. platyphylla forest (45.98 t·hm -2 ) > L. palustre-B. platyphylla forest (41.93 t·hm -2 ). The order of carbon storage for the vertical distribution in forest communities with diffe-rent forest types was the tree layer (85.2%-89.0%) > litter layer (8.0%-14.4%) > shrub layer (0.4%-2.7%) > herb layer (0-0.4%).

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.

Biomass production efficiency controlled by management in temperate and boreal ecosystems

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Forest succession in the Upper Rio Negro of Colombia and Venezuela

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

Saldarriaga, J.G.; West, D.C.; Tharp, M.L.

1986-11-01

Woody vegetation from 23 forest stands along the Upper Rio Negro of Venezuela and Colombia was sampled in 1982 to examine the hypothesis that the Amazon forest has been largely undisturbed since the Pleistocene, to quantify vegetation development during different stages of succession following agricultural development, and to determine the time required for a successional stand to become a mature forest. The ubiquitousness of charcoal in the tierra firme forest indicated the presence of fire associated with extreme dry periods and human disturbances. Changes in species composition, vegetation structure, and woody biomass were studied on 19 abandoned farms and fourmore » mature forest stands. Living and dead biomass for the tress and their components was determined by regression equations developed from measurements of harvested trees. The rate of recovery of floristic composition, structure, and biomass following disturbance is relatively slow. Aboveground dead biomass remained high 14 years after the forest was disturbed by the agricultural practices. The lowest dead biomass is reached 20 years after abandonment, and the largest values are found in mature forests. Data analysis of 80-year-old stands showed that the species composition approached that of a mature forest. Approximately 140 to 200 years was required for an abandoned farm to attain the basal area and biomass values comparable to those of a mature forest. The results of this study indicate that recovery is five to seven times longer in the Upper Rio Negro than it is in other tropical areas in South America.« less

Estimating leaf area and leaf biomass of open-grown deciduous urban trees

Treesearch

David J. Nowak

1996-01-01

Logarithmic regression equations were developed to predict leaf area and leaf biomass for open-grown deciduous urban trees based on stem diameter and crown parameters. Equations based on crown parameters produced more reliable estimates. The equations can be used to help quantify forest structure and functions, particularly in urbanizing and urban/suburban areas.

Short and long-term carbon balance of bioenergy electricity production fueled by forest treatments.

PubMed

Kelsey, Katharine C; Barnes, Kallie L; Ryan, Michael G; Neff, Jason C

2014-01-01

Forests store large amounts of carbon in forest biomass, and this carbon can be released to the atmosphere following forest disturbance or management. In the western US, forest fuel reduction treatments designed to reduce the risk of high severity wildfire can change forest carbon balance by removing carbon in the form of biomass, and by altering future potential wildfire behavior in the treated stand. Forest treatment carbon balance is further affected by the fate of this biomass removed from the forest, and the occurrence and intensity of a future wildfire in this stand. In this study we investigate the carbon balance of a forest treatment with varying fates of harvested biomass, including use for bioenergy electricity production, and under varying scenarios of future disturbance and regeneration. Bioenergy is a carbon intensive energy source; in our study we find that carbon emissions from bioenergy electricity production are nearly twice that of coal for the same amount of electricity. However, some emissions from bioenergy electricity production are offset by avoided fossil fuel electricity emissions. The carbon benefit achieved by using harvested biomass for bioenergy electricity production may be increased through avoided pyrogenic emissions if the forest treatment can effectively reduce severity. Forest treatments with the use of harvested biomass for electricity generation can reduce carbon emissions to the atmosphere by offsetting fossil fuel electricity generation emissions, and potentially by avoided pyrogenic emissions due to reduced intensity and severity of a future wildfire in the treated stand. However, changes in future wildfire and regeneration regimes may affect forest carbon balance and these climate-induced changes may influence forest carbon balance as much, or more, than bioenergy production.

Assimilation of repeated woody biomass observations constrains decadal ecosystem carbon cycle uncertainty in aggrading forests

NASA Astrophysics Data System (ADS)

Smallman, T. L.; Exbrayat, J.-F.; Mencuccini, M.; Bloom, A. A.; Williams, M.

2017-03-01

Forest carbon sink strengths are governed by plant growth, mineralization of dead organic matter, and disturbance. Across landscapes, remote sensing can provide information about aboveground states of forests and this information can be linked to models to estimate carbon cycling in forests close to steady state. For aggrading forests this approach is more challenging and has not been demonstrated. Here we apply a Bayesian approach, linking a simple model to a range of data, to evaluate their information content, for two aggrading forests. We compare high information content analyses using local observations with retrievals using progressively sparser remotely sensed information (repeated, single, and no woody biomass observations). The net biome productivity of both forests is constrained to be a net sink with <2 Mg C ha-1 yr-1 variation across the range of inputs. However, the sequestration of particular carbon pool(s) varies with assimilated biomass information. Assimilation of repeated biomass observations reduces uncertainty and/or bias in all ecosystem C pools not just wood, compared to analyses using single or no stock information. As verification, our repeated biomass analysis explains 78-86% of variation in litter dynamics at one forest, while at the second forest total dead organic matter estimates are within observational uncertainty. The uncertainty of retrieved ecosystem traits in the repeated biomass analysis is reduced by up to 50% compared to analyses with less biomass information. This study quantifies the importance of repeated woody observations in constraining the dynamics of both wood and dead organic matter, highlighting the benefit of proposed remote sensing missions.

Inference for lidar-assisted estimation of forest growing stock volume

Treesearch

Ronald E. McRoberts; Erik Næsset; Terje Gobakken

2013-01-01

Estimates of growing stock volume are reported by the national forest inventories (NFI) of most countries and may serve as the basis for aboveground biomass and carbon estimates as required by an increasing number of international agreements. The probability-based (design-based) statistical estimators traditionally used by NFIs to calculate estimates are generally...

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

PubMed

Daigneault, Adam; Sohngen, Brent; Sedjo, Roger

2012-06-05

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

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.

Colossal carbon! Disturbance and biomass dynamics in Alaska's national forests

Treesearch

John Kirkland; Tara Barrett

2016-01-01

The Chugach and Tongass National Forests are changing, possibly in response to global warming. Forested areas within Alaska's temperate rain forests are creeping into areas that were previously too cold or too wet. These forests are also becoming denser. As biomass increases, the amount of carbon stored in the forest also increases. Tara Barrett, a...

Effects of Forest Disturbances on Forest Structural Parameters Retrieval from Lidar Waveform Data

NASA Technical Reports Server (NTRS)

Ranson, K, Lon; Sun, G.

2011-01-01

The effect of forest disturbance on the lidar waveform and the forest biomass estimation was demonstrated by model simulation. The results show that the correlation between stand biomass and the lidar waveform indices changes when the stand spatial structure changes due to disturbances rather than the natural succession. This has to be considered in developing algorithms for regional or global mapping of biomass from lidar waveform data.

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...

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Estimating Amazonian rainforest stability and the likelihood for large-scale forest dieback

NASA Astrophysics Data System (ADS)

Rammig, Anja; Thonicke, Kirsten; Jupp, Tim; Ostberg, Sebastian; Heinke, Jens; Lucht, Wolfgang; Cramer, Wolfgang; Cox, Peter

2010-05-01

Annually, tropical forests process approximately 18 Pg of carbon through respiration and photosynthesis - more than twice the rate of anthropogenic fossil fuel emissions. Current climate change may be transforming this carbon sink into a carbon source by changing forest structure and dynamics. Increasing temperatures and potentially decreasing precipitation and thus prolonged drought stress may lead to increasing physiological stress and reduced productivity for trees. Resulting decreases in evapotranspiration and therefore convective precipitation could further accelerate drought conditions and destabilize the tropical ecosystem as a whole and lead to an 'Amazon forest dieback'. The projected direction and intensity of climate change vary widely within the region and between different scenarios from climate models (GCMs). In the scope of a World Bank-funded study, we assessed the 24 General Circulation Models (GCMs) evaluated in the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4) with respect to their capability to reproduce present-day climate in the Amazon basin using a Bayesian approach. With this approach, greater weight is assigned to the models that simulate well the annual cycle of rainfall. We then use the resulting weightings to create probability density functions (PDFs) for future forest biomass changes as simulated by the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJmL) to estimate the risk of potential Amazon rainforest dieback. Our results show contrasting changes in forest biomass throughout five regions of northern South America: If photosynthetic capacity and water use efficiency is enhanced by CO2, biomass increases across all five regions. However, if CO2-fertilisation is assumed to be absent or less important, then substantial dieback occurs in some scenarios and thus, the risk of forest dieback is considerably higher. Particularly affected are regions in the central Amazon basin. The range of potential biomass change arising from the weighting of rainfall patterns is smaller than the uncertainty arising from CO2-fertilisation effects, which highlights the importance of reducing the uncertainties in the direct effects of CO2 on tropical ecosystems. Strong biomass changes also imply changes in forest structure and thus, forest stability. Our results display shifts in forest composition from closed rainforest to more open forest or even shrubland. Our probability-based risk analysis could be used to advise regional forest protection.

Projecting the past and future impacts of hurricanes on the carbon balance of eastern U.S. forests (1851-2100)

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; Chambers, J. Q.; Zeng, H.

2009-12-01

In U.S. Atlantic coastal areas, hurricanes are a principal agent of catastrophic wind damage, with dramatic impacts on the structure and functioning of forests. Estimates of the carbon emissions resulting from single storms range as high as ~100 Tg C, an amount equivalent to the annual U.S. carbon sink in forest trees. Recent studies have estimated the historic regional carbon emissions from hurricane activity using an empirically based approach. Here, we use a mechanistic ecosystem model, the Ecosystem Demography (ED) model, driven by maps of mortality and damage based on historic hurricane tracks and future scenarios to predict the past and future impacts of hurricanes on the carbon balance of eastern U.S. forests. Model estimates compare well to previous empirically based estimates, with mean annual biomass loss of 26 Tg C yr-1 (range 0 to ~225 Tg C yr-1) resulting from hurricanes during the period 1851-2000. Using the mechanistic model, we are able to include the effects of both disturbance and recovery on the net carbon flux. We find a regional carbon sink throughout much of the 20th century resulting from forest recovery following a peak in hurricane activity during the late 19th century exceeding biomass loss. Recent increased hurricane activity has resulted in the region becoming a net carbon source. For the future, several recent studies have linked increased sea surface temperatures expected with climate change to increased hurricane activity. Based on these relationships, we investigate a range of scenarios of future hurricane activity and find the potential for substantial increases in emissions from hurricane mortality and reductions in regional carbon stocks. In our scenario with the largest increase in hurricane activity, we find a 35% increase in area disturbed by 2100, but due to the reduction of standing biomass, only a 20% increase in biomass loss per year. Developing this kind of predictive modeling capability that tracks disturbance events and recovery is key to our understanding and ability to predict the carbon balance of forests of the eastern U.S.

GIS-Based Suitability Model for Assessment of Forest Biomass Energy Potential in a Region of Portugal

NASA Astrophysics Data System (ADS)

Quinta-Nova, Luis; Fernandez, Paulo; Pedro, Nuno

2017-12-01

This work focuses on developed a decision support system based on multicriteria spatial analysis to assess the potential for generation of biomass residues from forestry sources in a region of Portugal (Beira Baixa). A set of environmental, economic and social criteria was defined, evaluated and weighted in the context of Saaty’s analytic hierarchies. The best alternatives were obtained after applying Analytic Hierarchy Process (AHP). The model was applied to the central region of Portugal where forest and agriculture are the most representative land uses. Finally, sensitivity analysis of the set of factors and their associated weights was performed to test the robustness of the model. The proposed evaluation model provides a valuable reference for decision makers in establishing a standardized means of selecting the optimal location for new biomass plants.

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...

Abiotic and biotic determinants of coarse woody productivity in temperate mixed forests.

PubMed

Yuan, Zuoqiang; Ali, Arshad; Wang, Shaopeng; Gazol, Antonio; Freckleton, Robert; Wang, Xugao; Lin, Fei; Ye, Ji; Zhou, Li; Hao, Zhanqing; Loreau, Michel

2018-07-15

Forests play an important role in regulating the global carbon cycle. Yet, how abiotic (i.e. soil nutrients) and biotic (i.e. tree diversity, stand structure and initial biomass) factors simultaneously contribute to aboveground biomass (coarse woody) productivity, and how the relative importance of these factors changes over succession remain poorly studied. Coarse woody productivity (CWP) was estimated as the annual aboveground biomass gain of stems using 10-year census data in old growth and secondary forests (25-ha and 4.8-ha, respectively) in northeast China. Boosted regression tree (BRT) model was used to evaluate the relative contribution of multiple metrics of tree diversity (taxonomic, functional and phylogenetic diversity and trait composition as well as stand structure attributes), stand initial biomass and soil nutrients on productivity in the studied forests. Our results showed that community-weighted mean of leaf phosphorus content, initial stand biomass and soil nutrients were the three most important individual predictors for CWP in secondary forest. Instead, initial stand biomass, rather than diversity and functional trait composition (vegetation quality) was the most parsimonious predictor of CWP in old growth forest. By comparing the results from secondary and old growth forest, the summed relative contribution of trait composition and soil nutrients on productivity decreased as those of diversity indices and initial biomass increased, suggesting the stronger effect of diversity and vegetation quantity over time. Vegetation quantity, rather than diversity and soil nutrients, is the main driver of forest productivity in temperate mixed forest. Our results imply that diversity effect for productivity in natural forests may not be so important as often suggested, at least not during the later stage of forest succession. This finding suggests that as a change of the importance of different divers of productivity, the environmentally driven filtering decreases and competitively driven niche differentiation increases with forest succession. Copyright © 2018 Elsevier B.V. All rights reserved.

The contribution of trees outside forests to national tree biomass and carbon stocks--a comparative study across three continents.

PubMed

Schnell, Sebastian; Altrell, Dan; Ståhl, Göran; Kleinn, Christoph

2015-01-01

In contrast to forest trees, trees outside forests (TOF) often are not included in the national monitoring of tree resources. Consequently, data about this particular resource is rare, and available information is typically fragmented across the different institutions and stakeholders that deal with one or more of the various TOF types. Thus, even if information is available, it is difficult to aggregate data into overall national statistics. However, the National Forest Monitoring and Assessment (NFMA) programme of FAO offers a unique possibility to study TOF resources because TOF are integrated by default into the NFMA inventory design. We have analysed NFMA data from 11 countries across three continents. For six countries, we found that more than 10% of the national above-ground tree biomass was actually accumulated outside forests. The highest value (73%) was observed for Bangladesh (total forest cover 8.1%, average biomass per hectare in forest 33.4 t ha(-1)) and the lowest (3%) was observed for Zambia (total forest cover 63.9%, average biomass per hectare in forest 32 t ha(-1)). Average TOF biomass stocks were estimated to be smaller than 10 t ha(-1). However, given the large extent of non-forest areas, these stocks sum up to considerable quantities in many countries. There are good reasons to overcome sectoral boundaries and to extend national forest monitoring programmes on a more systematic basis that includes TOF. Such an approach, for example, would generate a more complete picture of the national tree biomass. In the context of climate change mitigation and adaptation, international climate mitigation programmes (e.g. Clean Development Mechanism and Reduced Emission from Deforestation and Degradation) focus on forest trees without considering the impact of TOF, a consideration this study finds crucial if accurate measurements of national tree biomass and carbon pools are required.

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 to the entire scene (226/69) from the optical data and to obtain an overview of the biomass distribution throughout the area.

Identification of wood energy resources in central Michigan

NASA Technical Reports Server (NTRS)

Hudson, W. D.; Kittleson, K.

1978-01-01

Existing biomass studies were compiled for determining their applicability in measuring forest biomass in an entirely new way. Over sixty tree-weight tables were prepared from existing tables or formulas. An estimate of forest biomass was made on a defined area by using Landsat Satellite data analysis, existing forest cover type maps and actual weighting of the entire biomass. Control plots were cruised for normal volume data and weight data, harvested and weighed to determine actual tonnage yields.

Carbon Legacy of Forest Degradation Foregone: can Europe's Forests Contribute to Deep Decarbonization?

NASA Astrophysics Data System (ADS)

Kauppi, P.; Nabuurs, G. J.

2016-12-01

Contemporary European forests, comprising 161 Mha, play a large role in mitigation of the EU carbon emissions. These intensively managed forests, roughly compensate 10% of EU emissions in forest carbon, in synchrony with the harvest for lumber, fibre and bioenergy, . But this has not always been the case; European forests are recovering since roughly 1850 from thousands of years of human induced degradation. The impact of more recent management is profound and has stimulated a worldwide unique and unprecedented recovery of this forest biome, partly in terms of area, but mainly in forest density that is, biomass per hectare increases. Based on what we know of the recent historic development, can these forests further contribute to deep decarbonization and how? We outline historic development of European forests since roughly 0 AD. We sketch evidence on degradation and deforestation, and on the impact of forest management on restoring the forest growth thus feeding on biomass recovery. We estimate the historical trajectory of the recovery from forest degradation. We discuss the future pathways of European forest resources, and the prospects for the European-model recovery to occur in degraded forests of the other continents. Based on this evidence from the past, we outline what Climate Smart Forestry could mean in the European circumstances aiming to further strengthen this role of European forests. Big scientific challenges remain to understand and project the future development of these forests under climate change and natural disturbances closely entangled with forest management and new demands of industry in the bio-economy.

Relating P-band AIRSAR backscatter to forest stand parameters

NASA Technical Reports Server (NTRS)

Wang, Yong; Melack, John M.; Davis, Frank W.; Kasischke, Eric S.; Christensen, Norman L., Jr.

1993-01-01

As part of research on forest ecosystems, the Jet Propulsion Laboratory (JPL) and collaborating research teams have conducted multi-season airborne synthetic aperture radar (AIRSAR) experiments in three forest ecosystems including temperate pine forest (Duke, Forest, North Carolina), boreal forest (Bonanza Creek Experimental Forest, Alaska), and northern mixed hardwood-conifer forest (Michigan Biological Station, Michigan). The major research goals were to improve understanding of the relationships between radar backscatter and phenological variables (e.g. stand density, tree size, etc.), to improve radar backscatter models of tree canopy properties, and to develop a radar-based scheme for monitoring forest phenological changes. In September 1989, AIRSAR backscatter data were acquired over the Duke Forest. As the aboveground biomass of the loblolly pine forest stands at Duke Forest increased, the SAR backscatter at C-, L-, and P-bands increased and saturated at different biomass levels for the C-band, L-band, and P-band data. We only use the P-band backscatter data and ground measurements here to study the relationships between the backscatter and stand density, the backscatter and mean trunk dbh (diameter at breast height) of trees in the stands, and the backscatter and stand basal area.

[Carbon storage of forest stands in Shandong Province estimated by forestry inventory data].

PubMed

Li, Shi-Mei; Yang, Chuan-Qiang; Wang, Hong-Nian; Ge, Li-Qiang

2014-08-01

Based on the 7th forestry inventory data of Shandong Province, this paper estimated the carbon storage and carbon density of forest stands, and analyzed their distribution characteristics according to dominant tree species, age groups and forest category using the volume-derived biomass method and average-biomass method. In 2007, the total carbon storage of the forest stands was 25. 27 Tg, of which the coniferous forests, mixed conifer broad-leaved forests, and broad-leaved forests accounted for 8.6%, 2.0% and 89.4%, respectively. The carbon storage of forest age groups followed the sequence of young forests > middle-aged forests > mature forests > near-mature forests > over-mature forests. The carbon storage of young forests and middle-aged forests accounted for 69.3% of the total carbon storage. Timber forest, non-timber product forest and protection forests accounted for 37.1%, 36.3% and 24.8% of the total carbon storage, respectively. The average carbon density of forest stands in Shandong Province was 10.59 t x hm(-2), which was lower than the national average level. This phenomenon was attributed to the imperfect structure of forest types and age groups, i. e., the notably higher percentage of timber forests and non-timber product forest and the excessively higher percentage of young forests and middle-aged forest than mature forests.

Biomass and carbon pools of disturbed riparian forests

Treesearch

Laura A.B. Giese; W.M. Aust; Randall K. Kolka; Carl C. Trettin

2003-01-01

Quantification of carbon pools as affected by forest ageldevelopment can facilitate riparian restoration and increase awareness of the potential for forests to sequester global carbon. Riparian forest biomass and carbon pools were quantified for four riparian forests representing different sera1 stages in the South Carolina Upper Coastal Plain. Three of the riparian...

Biomass and carbon pools of disturbed riparian forests

Treesearch

Laura A. B. Giese; W. M. Aust; Randall K. Kolka; Carl C. Trettin

2003-01-01

Quantification of carbon pools as affected by forest age/development can facilitate riparian restoration and increase awareness of the potential for forests to sequester global carbon. Riparian forest biomass and carbon pools were quantified for four riparian forests representing different seral stages in the South Carolina Upper Coastal Plain. Three of the riparian...

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

USGS Publications Warehouse

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

2014-01-01

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

Soil Nitrogen-Cycling Responses to Conversion of Lowland Forests to Oil Palm and Rubber Plantations in Sumatra, Indonesia

PubMed Central

Tjoa, Aiyen; Veldkamp, Edzo

2015-01-01

Rapid deforestation in Sumatra, Indonesia is presently occurring due to the expansion of palm oil and rubber production, fueled by an increasing global demand. Our study aimed to assess changes in soil-N cycling rates with conversion of forest to oil palm (Elaeis guineensis) and rubber (Hevea brasiliensis) plantations. In Jambi Province, Sumatra, Indonesia, we selected two soil landscapes – loam and clay Acrisol soils – each with four land-use types: lowland forest and forest with regenerating rubber (hereafter, “jungle rubber”) as reference land uses, and rubber and oil palm as converted land uses. Gross soil-N cycling rates were measured using the 15N pool dilution technique with in-situ incubation of soil cores. In the loam Acrisol soil, where fertility was low, microbial biomass, gross N mineralization and NH4 + immobilization were also low and no significant changes were detected with land-use conversion. The clay Acrisol soil which had higher initial fertility based on the reference land uses (i.e. higher pH, organic C, total N, effective cation exchange capacity (ECEC) and base saturation) (P≤0.05–0.09) had larger microbial biomass and NH4 + transformation rates (P≤0.05) compared to the loam Acrisol soil. Conversion of forest and jungle rubber to rubber and oil palm in the clay Acrisol soil decreased soil fertility which, in turn, reduced microbial biomass and consequently decreased NH4 + transformation rates (P≤0.05–0.09). This was further attested by the correlation of gross N mineralization and microbial biomass N with ECEC, organic C, total N (R=0.51–0. 76; P≤0.05) and C:N ratio (R=-0.71 – -0.75, P≤0.05). Our findings suggest that the larger the initial soil fertility and N availability, the larger the reductions upon land-use conversion. Because soil N availability was dependent on microbial biomass, management practices in converted oil palm and rubber plantations should focus on enriching microbial biomass. PMID:26222690

Estimating total forest biomass in Maine, 1995

Treesearch

Eric H. Wharton; Douglas M. Griffith; Douglas M. Griffith

1998-01-01

Presents methods for synthesizing information from existing biomass literature for estimating biomass over extensive forest areas with specific applications to Maine. Tables of appropriate regression equations and the tree and shrub species to which these equations can be applied are presented as well as biomass estimates at the county and state level.

Potential for Coal Power Plants to Co-Fire with Woody Biomass in the U. S. North, 2010-2030: A Technical Document Supporting the Northern Forest Futures Project

Treesearch

Michael E. Goerndt; Francisco X. Aguilar; Kenneth E. Skog

2015-01-01

Future use of woody biomass to produce electric power in the U.S. North can have an important influence on timber production, carbon storage in forests, and net carbon emissions from producing electric power. The Northern Forest Futures Project (NFFP) has provided regional- and state-level projections of standing forest biomass, land-use change, and timber harvest,...

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

EXPLAINING FOREST COMPOSITION AND BIOMASS ACROSS MULTIPLE BIOGEOGRAPHIC REGIONS

EPA Science Inventory

Current scientific concerns regarding the impacts of global change include the responses of forest composition and biomass to rapid changes in climate, and forest gap models, have often been used to address this issue. These models reflect the concept that forest composition and...

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

PubMed

Dar, Javid Ahmad; Sundarapandian, Somaiah

2015-02-01

An accurate characterization of tree, understory, deadwood, floor litter, and soil organic carbon (SOC) pools in temperate forest ecosystems is important to estimate their contribution to global carbon (C) stocks. However, this information on temperate forests of the Himalayas is lacking and fragmented. In this study, we measured C stocks of tree (aboveground and belowground biomass), understory (shrubs and herbaceous), deadwood (standing and fallen trees and stumps), floor litter, and soil from 111 plots of 50 m × 50 m each, in seven forest types: Populus deltoides (PD), Juglans regia (JR), Cedrus deodara (CD), Pinus wallichiana (PW), mixed coniferous (MC), Abies pindrow (AP), and Betula utilis (BU) in temperate forests of Kashmir Himalaya, India. The main objective of the present study is to quantify the ecosystem C pool in these seven forest types. The results showed that the tree biomass ranged from 100.8 Mg ha(-1) in BU forest to 294.8 Mg ha(-1) for the AP forest. The understory biomass ranged from 0.16 Mg ha(-1) in PD forest to 2.36 Mg ha(-1) in PW forest. Deadwood biomass ranged from 1.5 Mg ha(-1) in PD forest to 14.9 Mg ha(-1) for the AP forest, whereas forest floor litter ranged from 2.5 Mg ha(-1) in BU and JR forests to 3.1 Mg ha(-1) in MC forest. The total ecosystem carbon stocks varied from 112.5 to 205.7 Mg C ha(-1) across all the forest types. The C stocks of tree, understory, deadwood, litter, and soil ranged from 45.4 to 135.6, 0.08 to 1.18, 0.7 to 6.8, 1.1 to 1.4, and 39.1-91.4 Mg ha(-1), respectively, which accounted for 61.3, 0.2, 1.4, 0.8, and 36.3 % of the total carbon stock. BU forest accounted 65 % from soil C and 35 % from biomass, whereas PD forest contributed only 26 % from soil C and 74 % from biomass. Of the total C stock in the 0-30-cm soil, about 55 % was stored in the upper 0-10 cm. Soil C stocks in BU forest were significantly higher than those in other forests. The variability of C pools of different ecosystem components is influenced by vegetation type, stand structure, management history, and altitude. Our results reveal that a higher percentage (63 %) of C is stored in biomass and less in soil in these temperate forests except at the higher elevation broad-leaved BU forest. Results from this study will enhance our ability to evaluate the role of these forests in regional and global C cycles and have great implications for planning strategies for conservation. The study provides important data for developing and validating C cycling models for temperate forests.

The creation and role of the USDA biomass research centers

USDA-ARS?s Scientific Manuscript database

The Five USDA Biomass Research Centers were created to facilitate coordinated research to enhance the establishment of a sustainable feedstock production for bio-based renewable energy in the United States. Scientists and staff of the Agriculture Research Service (ARS) and Forest Service (FS) withi...

Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change.

PubMed

Levine, Naomi M; Zhang, Ke; Longo, Marcos; Baccini, Alessandro; Phillips, Oliver L; Lewis, Simon L; Alvarez-Dávila, Esteban; Segalin de Andrade, Ana Cristina; Brienen, Roel J W; Erwin, Terry L; Feldpausch, Ted R; Monteagudo Mendoza, Abel Lorenzo; Nuñez Vargas, Percy; Prieto, Adriana; Silva-Espejo, Javier Eduardo; Malhi, Yadvinder; Moorcroft, Paul R

2016-01-19

Amazon forests, which store ∼ 50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.

Forest inventory with LiDAR and stereo DSM on Washington department of natural resources lands

Treesearch

Jacob L. Strunk; Peter J. Gould

2015-01-01

DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived...

Monitoring individual tree-based change with airborne lidar.

PubMed

Duncanson, Laura; Dubayah, Ralph

2018-05-01

Understanding the carbon flux of forests is critical for constraining the global carbon cycle and managing forests to mitigate climate change. Monitoring forest growth and mortality rates is critical to this effort, but has been limited in the past, with estimates relying primarily on field surveys. Advances in remote sensing enable the potential to monitor tree growth and mortality across landscapes. This work presents an approach to measure tree growth and loss using multidate lidar campaigns in a high-biomass forest in California, USA. Individual tree crowns were delineated in 2008 and again in 2013 using a 3D crown segmentation algorithm, with derived heights and crown radii extracted and used to estimate individual tree aboveground biomass. Tree growth, loss, and aboveground biomass were analyzed with respect to tree height and crown radius. Both tree growth and loss rates decrease with increasing tree height, following the expectation that trees slow in growth rate as they age. Additionally, our aboveground biomass analysis suggests that, while the system is a net source of aboveground carbon, these carbon dynamics are governed by size class with the largest sources coming from the loss of a relatively small number of large individuals. This study demonstrates that monitoring individual tree-based growth and loss can be conducted with multidate airborne lidar, but these methods remain relatively immature. Disparities between lidar acquisitions were particularly difficult to overcome and decreased the sample of trees analyzed for growth rate in this study to 21% of the full number of delineated crowns. However, this study illuminates the potential of airborne remote sensing for ecologically meaningful forest monitoring at an individual tree level. As methods continue to improve, airborne multidate lidar will enable a richer understanding of the drivers of tree growth, loss, and aboveground carbon flux.

Single tree biomass modelling using airborne laser scanning

NASA Astrophysics Data System (ADS)

Kankare, Ville; Räty, Minna; Yu, Xiaowei; Holopainen, Markus; Vastaranta, Mikko; Kantola, Tuula; Hyyppä, Juha; Hyyppä, Hannu; Alho, Petteri; Viitala, Risto

2013-11-01

Accurate forest biomass mapping methods would provide the means for e.g. detecting bioenergy potential, biofuel and forest-bound carbon. The demand for practical biomass mapping methods at all forest levels is growing worldwide, and viable options are being developed. Airborne laser scanning (ALS) is a promising forest biomass mapping technique, due to its capability of measuring the three-dimensional forest vegetation structure. The objective of the study was to develop new methods for tree-level biomass estimation using metrics derived from ALS point clouds and to compare the results with field references collected using destructive sampling and with existing biomass models. The study area was located in Evo, southern Finland. ALS data was collected in 2009 with pulse density equalling approximately 10 pulses/m2. Linear models were developed for the following tree biomass components: total, stem wood, living branch and total canopy biomass. ALS-derived geometric and statistical point metrics were used as explanatory variables when creating the models. The total and stem biomass root mean square error per cents equalled 26.3% and 28.4% for Scots pine (Pinus sylvestris L.), and 36.8% and 27.6% for Norway spruce (Picea abies (L.) H. Karst.), respectively. The results showed that higher estimation accuracy for all biomass components can be achieved with models created in this study compared to existing allometric biomass models when ALS-derived height and diameter were used as input parameters. Best results were achieved when adding field-measured diameter and height as inputs in the existing biomass models. The only exceptions to this were the canopy and living branch biomass estimations for spruce. The achieved results are encouraging for the use of ALS-derived metrics in biomass mapping and for further development of the models.

[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 sylvestris var. mongolica, Picea koraiensis and Populus davidiana showed increasing trend at different degrees during the entire simulation period. There was a time lag for the direct effect of climate warming on biomass for coniferous and broadleaved species. The response time of coniferous species to climate warming was 25-30 years, which was longer than that for broadleaf species. The forest landscape in the Great Xing'an Mountains was sensitive to the interactive effect of climate warming (high CO 2 emissions) and high intensity fire disturbance. Future climate warming and high intensity forest fire disturbance would significantly change the composition and structure of forest ecosystem.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Carbon and Aerosol Emissions from Biomass Fires in Mexico

NASA Astrophysics Data System (ADS)

Hao, W. M.; Flores Garnica, G.; Baker, S. P.; Urbanski, S. P.

2009-12-01

Biomass burning is an important source of many atmospheric greenhouse gases and photochemically reactive trace gases. There are limited data available on the spatial and temporal extent of biomass fires and associated trace gas and aerosol emissions in Mexico. Biomass burning is a unique source of these gases and aerosols, in comparison to industrial and biogenic sources, because the locations of fires vary considerably both daily and seasonally and depend on human activities and meteorological conditions. In Mexico, the fire season starts in January and about two-thirds of the fires occur in April and May. The amount of trace gases and aerosols emitted by fires spatially and temporally is a major uncertainty in quantifying the impact of fire emissions on regional atmospheric chemical composition. To quantify emissions, it is necessary to know the type of vegetation, the burned area, the amount of biomass burned, and the emission factor of each compound for each ecosystem. In this study biomass burning experiments were conducted in Mexico to measure trace gas emissions from 24 experimental fires and wildfires in semiarid, temperate, and tropical ecosystems from 2005 to 2007. A range of representative vegetation types were selected for ground-based experimental burns to characterize fire emissions from representative Mexico fuels. A third of the country was surveyed each year, beginning in the north. The fire experiments in the first year were conducted in Chihuahua, Nuevo Leon, and Tamaulipas states in pine forest, oak forest, grass, and chaparral. The second-year fire experiments were conducted on pine forest, oak forest, shrub, agricultural, grass, and herbaceous fuels in Jalisco, Puebla, and Oaxaca states in central Mexico. The third-year experiments were conducted in pine-oak forests of Chiapas, coastal grass, and low subtropical forest on the Yucatan peninsula. FASS (Fire Atmosphere Sampling System) towers were deployed for the experimental fires. Each FASS system contains 4 electro-polished stainless steel canisters to sample trace gas emissions, with a corresponding set of Teflon filters in the sampling ports to collect PM2.5 particulates. In addition, biomass burning was sampled by aircraft with canisters and real-time instruments as part of the MILAGRO field campaign. We present the emission factors of CO2, CO, CH4, C2-C4 compounds, and PM2.5 for prescribed fires of the major vegetation types in Mexico, as well as for regional wildfires in southern and central Mexico. We will also present a high-resolution vegetation map in Mexico based on the Landsat satellites and the fuel consumption models for various components and sizes of fuels.

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...

Long-term effects on distribution of forest biomass following different harvesting levels in the northern Rocky Mountains

Treesearch

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

2015-01-01

With increasing public demand for more intensive biomass utilization from forests, the concerns over adverse impacts on productivity by nutrient depletion are increasing. We remeasured the 1974 site of the Forest Residues Utilization Research and Development in northwestern Montana to investigate long-term impacts of intensive biomass utilization on aspects of site...

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

Treesearch

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

2012-01-01

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

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

Treesearch

Christopher S. Galik; Robert C. Abt

2012-01-01

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

Lidar-based biomass assessment for the Yukon River Basin

NASA Astrophysics Data System (ADS)

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

2010-12-01

Climate change is expected to have a significant impact on high-latitude forests in terms of their ability to sequester carbon as expressed as pools of standing total biomass and soil organic matter. Above ground biomass is an important driver in ecosystem process models used to assess, predict, and understand climate change impacts. Therefore, it is of compelling interest to acquire accurate assessments of current biomass levels for these high-latitude forests, a particular challenge because of their vastness and remoteness. At this time, remote sensing is the only feasible method through which to acquire such assessments. In this study, the use of lidar data for estimating shrub and tree biomass for the Yukon Flats region of Alaska’s Yukon River Basin (YRB) is demonstrated. The lidar data were acquired in the late summer and fall of 2009 as were an initial set of field sampling data collected for training and validation purposes. The 2009 field campaigns were located near Canvasback Lake and Boot Lake in the YRB. Various tallies of biomass were calculated from the field data using allometric equations (Bond-Lamberty et al. 2002, Yarie et al. 2007, Mack et al. 2008). Additional field data were also collected during two 2010 field campaigns at different locations in the Yukon Flats. Linear regressions have been developed based on field-based shrub and tree biomass and various lidar metrics of canopy height calculated for the plots (900 m^2). A multiple linear regression performed at the plot level resulted in a strong relationship (R^2=0.88) between observed and predicted biomass at the plot level. The coefficients for this regression were used to generate a shrub and tree biomass map for the entire Yukon Flats study area covered by lidar. This biomass map will be evaluated using additional field data collected in 2010 as well as other remote sensing data sources. Furthermore, additional lidar metrics (e.g. height of median energy) are being derived from the raw lidar data set and are expected to result in improved biomass products for the YRB as they have been shown to be highly predictive of biomass in other biomes. The results of this project represent the first step in a larger effort to collect lidar and field data for various study sites across the YRB for biomass estimations to train large-scale mapping efforts using Landsat imagery and radar data. Bond-Lamberty, B., C. Wang, and S.T. Gower. 2002. Aboveground and belowground biomass and sapwood area allometric equations for six boreal tree species of northern Manitoba. Canadian Journal of Forest Research 32: 1441-1450. Mack, M., K. Treseder, K. Manies, J. Harden, E. Schuur, J. Vogel, J. Randerson, and F.S. Chapin III. 2008. Recovery of Aboveground Plant Biomass and Productivity After Fire in Mesic and Dry Black Spruce Forests of Interior Alaska, Ecosystems v.11:209-225. Yarie, J., E. Kane, and M. Mack. 2007. Aboveground Biomass Equations for the Trees of Interior Alaska. AFES Bulletin 115.

The Global Impact of Biomass Burning: An Interview with EPA's Robert Huggett

NASA Technical Reports Server (NTRS)

Sevine, Joel S.

1995-01-01

The extent of biomass burning has increased significantly over the past 100 years because of human activities, and such burning is much more frequent and widespread than was previously believed. Biomass burning is now recognized as a significant global source of emissions, contributing as much as 40% of gross carbon dioxide and 38% of tropospheric ozone. Most of the world's burned biomass matter is from the savannas, and because two-thirds of the Earth's savannas are located in Africa, that continent is now recognized as the "burn center" of the planet. In the past few years the international scientific community has conducted field experiments using ground-based and airborne measurements in Africa, South America. and Siberia to better assess the global production of gases and particulates by biomass burning. Researchers are gathering this month in Williamsburg, VA, to discuss the results of these and other investigations at the Second Chapman Conference on Biomass Burning and Global Change, sponsored by the American Geophysical Union. The first international biomass burning conference, held in 1990, was attended by atmospheric chemists, climatologists, ecologists, forest and soil scientists, fire researchers, remote- sensins specialists, and environmental planners and managers from more than 25 countries.When we hear about biomass burning, we usually think of the burning of the worlds tropical forests for permanent land clearing. However, biomass burning serves a variety of land use changes, including the clearing of forests and savannas for agricultural and grazing use; shifting agriculture practices; the control of grass, weeds, and litter on agricultural and grazing lands; the elimination of stubble and waste on agricultural lands after the harvest; and the domestic use of biomass matter.

Systems Based Approaches for Thermochemical Conversion of Biomass to Bioenergy and Bioproducts

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

Taylor, Steven

2016-07-11

Auburn’s Center for Bioenergy and Bioproducts conducts research on production of synthesis gas for use in power generation and the production of liquid fuels. The overall goal of our gasification research is to identify optimal processes for producing clean syngas to use in production of fuels and chemicals from underutilized agricultural and forest biomass feedstocks. This project focused on construction and commissioning of a bubbling-bed fluidized-bed gasifier and subsequent shakedown of the gasification and gas cleanup system. The result of this project is a fully commissioned gasification laboratory that is conducting testing on agricultural and forest biomass. Initial tests onmore » forest biomass have served as the foundation for follow-up studies on gasification under a more extensive range of temperatures, pressures, and oxidant conditions. The laboratory gasification system consists of a biomass storage tank capable of holding up to 6 tons of biomass; a biomass feeding system, with loss-in-weight metering system, capable of feeding biomass at pressures up to 650 psig; a bubbling-bed fluidized-bed gasification reactor capable of operating at pressures up to 650 psig and temperatures of 1500oF with biomass flowrates of 80 lb/hr and syngas production rates of 37 scfm; a warm-gas filtration system; fixed bed reactors for gas conditioning; and a final quench cooling system and activated carbon filtration system for gas conditioning prior to routing to Fischer-Tropsch reactors, or storage, or venting. This completed laboratory enables research to help develop economically feasible technologies for production of biomass-derived synthesis gases that will be used for clean, renewable power generation and for production of liquid transportation fuels. Moreover, this research program provides the infrastructure to educate the next generation of engineers and scientists needed to implement these technologies.« less

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.

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

USGS Publications Warehouse

Hall, S. A.; Burke, I.C.; Box, D. O.; Kaufmann, M. R.; Stoker, Jason M.

2005-01-01

The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important, such as fire prone forests.

Carbon and nitrogen distribution in oak-hickory forests distributed along a productivity gradient

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

Reber, R.T.; Kaczmarek, D.J.; Pope, P.E.

1993-12-31

Biomass, carbon and nitrogen pools were determined for oak-hickory forests of varying productivity. Little information of this type is available for the central hardwood region. Six oak-hickory dominated forests were chosen to represent a range in potential site productivity as influenced by soil type, amount of recyclable nutrients and available water. Biomass, carbon and nitrogen storage were determined for the following components: above ground standing biomass, fine root biomass, forest floor organic layers and litterfall. As site sequestered at each site was dependent more on the amount of living biomass at each site Litterfall, to some extent, increased with increasingmore » site productivity. As potential site productivity decreased, total fine root biomass increased. The data suggest that as site quality decreased fine root production and turnover may become as important in nutrient cycling as annual litterfall.« less

Fuel supply structure of wood-fired power plants in the Northeast: Loggers' perspectives

Treesearch

Neil K. Huyler; Neil K. Huyler

1989-01-01

A study of loggers' perceptions of the impact of large biomass demand centers on the forest resource base in the Northeast indicated that most loggers strongly believe that the post-harvest stand has improved. However, the impact of whole-tree chipping on the forest resource base was not made clear from the loggers' survey.

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...

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...

Dominant effect of increasing forest biomass on evapotranspiration: interpretations of movement in Budyko space

NASA Astrophysics Data System (ADS)

Jaramillo, Fernando; Cory, Neil; Arheimer, Berit; Laudon, Hjalmar; van der Velde, Ype; Hasper, Thomas B.; Teutschbein, Claudia; Uddling, Johan

2018-01-01

During the last 6 decades, forest biomass has increased in Sweden mainly due to forest management, with a possible increasing effect on evapotranspiration. However, increasing global CO2 concentrations may also trigger physiological water-saving responses in broadleaf tree species, and to a lesser degree in some needleleaf conifer species, inducing an opposite effect. Additionally, changes in other forest attributes may also affect evapotranspiration. In this study, we aimed to detect the dominating effect(s) of forest change on evapotranspiration by studying changes in the ratio of actual evapotranspiration to precipitation, known as the evaporative ratio, during the period 1961-2012. We first used the Budyko framework of water and energy availability at the basin scale to study the hydroclimatic movements in Budyko space of 65 temperate and boreal basins during this period. We found that movements in Budyko space could not be explained by climatic changes in precipitation and potential evapotranspiration in 60 % of these basins, suggesting the existence of other dominant drivers of hydroclimatic change. In both the temperate and boreal basin groups studied, a negative climatic effect on the evaporative ratio was counteracted by a positive residual effect. The positive residual effect occurred along with increasing standing forest biomass in the temperate and boreal basin groups, increasing forest cover in the temperate basin group and no apparent changes in forest species composition in any group. From the three forest attributes, standing forest biomass was the one that could explain most of the variance of the residual effect in both basin groups. These results further suggest that the water-saving response to increasing CO2 in these forests is either negligible or overridden by the opposite effect of the increasing forest biomass. Thus, we conclude that increasing standing forest biomass is the dominant driver of long-term and large-scale evapotranspiration changes in Swedish forests.

Short and long-term carbon balance of bioenergy electricity production fueled by forest treatments

Treesearch

Katherine C. Kelsey; Kallie L. Barnes; Michael G. Ryan; Jason C. Neff

2014-01-01

Forests store large amounts of carbon in forest biomass, and this carbon can be released to the atmosphere following forest disturbance or management. In the western US, forest fuel reduction treatments designed to reduce the risk of high severity wildfire can change forest carbon balance by removing carbon in the form of biomass, and by altering future potential...

Decomposer food web in a deciduous forest shows high share of generalist microorganisms and importance of microbial biomass recycling.

PubMed

López-Mondéjar, Ruben; Brabcová, Vendula; Štursová, Martina; Davidová, Anna; Jansa, Jan; Cajthaml, Tomaš; Baldrian, Petr

2018-06-01

Forest soils represent important terrestrial carbon (C) pools where C is primarily fixed in the plant-derived biomass but it flows further through the biomass of fungi and bacteria before it is lost from the ecosystem as CO 2 or immobilized in recalcitrant organic matter. Microorganisms are the main drivers of C flow in forests and play critical roles in the C balance through the decomposition of dead biomass of different origins. Here, we track the path of C that enters forest soil by following respiration, microbial biomass production, and C accumulation by individual microbial taxa in soil microcosms upon the addition of 13 C-labeled biomass of plant, fungal, and bacterial origin. We demonstrate that both fungi and bacteria are involved in the assimilation and mineralization of C from the major complex sources existing in soil. Decomposer fungi are, however, better suited to utilize plant biomass compounds, whereas the ability to utilize fungal and bacterial biomass is more frequent among bacteria. Due to the ability of microorganisms to recycle microbial biomass, we suggest that the decomposer food web in forest soil displays a network structure with loops between and within individual pools. These results question the present paradigms describing food webs as hierarchical structures with unidirectional flow of C and assumptions about the dominance of fungi in the decomposition of complex organic matter.

Estimating total forest biomass in New York, 1993

Treesearch

Eric Wharton; Carol Alerich; David A. Drake; David A. Drake

1997-01-01

Presents methods for synthesizing information from existing biomass literature for estimating biomass over extensive forest areas with specific applications to New York. Tables of appropriate regression equations and the tree and shrub species to which these equations can be applied are presented well as biomass estimates at the county, geographic unit, and state level...

Physical pretreatment – woody biomass size reduction – for forest biorefinery

Treesearch

J.Y. Zhu

2011-01-01

Physical pretreatment of woody biomass or wood size reduction is a prerequisite step for further chemical or biochemical processing in forest biorefinery. However, wood size reduction is very energy intensive which differentiates woody biomass from herbaceous biomass for biorefinery. This chapter discusses several critical issues related to wood size reduction: (1)...

Strategies for assessing inter- and intra-specific variation in tree biomass in the interior west

Treesearch

David L.R. Affleck; John M. Goodburn; John D. Shaw

2012-01-01

Wildfire hazard mitigation and bioenergy harvesting have emerged as forest management priorities throughout the Interior West (IW) of the USA. Regional forest inventory and forecasting applications are therefore increasingly focused on tree biomass, including biomass in traditionally non-merchantable components. Yet accurate biomass equations for the latter components...

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...

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.

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

Allometric scaling theory applied to FIA biomass estimation

Treesearch

David C. Chojnacky

2002-01-01

Tree biomass estimates in the Forest Inventory and Analysis (FIA) database are derived from numerous methodologies whose abundance and complexity raise questions about consistent results throughout the U.S. A new model based on allometric scaling theory ("WBE") offers simplified methodology and a theoretically sound basis for improving the reliability and...

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

EPA Science Inventory

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

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

NASA Technical Reports Server (NTRS)

Leitold, Veronika; Keller, Michael; Morton, Douglas C.; Cook, Bruce D.; Shimabukuro, Yosio E.

2015-01-01

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

PubMed

Leitold, Veronika; Keller, Michael; Morton, Douglas C; Cook, Bruce D; Shimabukuro, Yosio E

2015-12-01

Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (~20 returns m -2 ) data was highly accurate (mean signed error of 0.19 ± 0.97 m), while those derived from reduced-density datasets (8 m -2 , 4 m -2 , 2 m -2 and 1 m -2 ) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4 m -2 , the bias in height estimates translated into errors of 80-125 Mg ha -1 in predicted aboveground biomass. Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

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.

Estimating release of carbon from 1990 and 1991 forest fires in Alaska

NASA Technical Reports Server (NTRS)

Kaisischke, Eric S.; French, Nancy H. F.; Bourgeau-Chavez, Laura L.; Christensen, N. L., Jr.

1995-01-01

An improved method to estimate the amounts of carbon released during fires in the boreal forest zone of Alaska in 1990 and 1991 is described. This method divides the state into 64 distinct physiographic regions and estimates areal extent of five different land covers: two forest types, peat land, tundra, and nonvegetated. The areal extent of each cover type was estimated from a review of topographic maps of each region and observations on the distribution of foreat types within the state. Using previous observations and theoretical models for the two forest types found in interior Alaska, models of biomass accumulation as a function of stand age were developed. Stand age distributions for each region were determined using a statistical distribution based on fire frequency, which was from available long-term historical records. Estimates of the degree of biomass combusted were based on recent field observations as well as research reported in the literature. The location and areal extent of fires in this region for 1990 and 1991 were based on both field observations and analysis of satellite (advanced very high resolution radiometer (AVHRR)) data sets. Estimates of average carbon release for the two study years ranged between 2.54 and 3.00 kg/sq m, which are 2.2 to 2.6 times greater than estimates used in other studies of carbon release through biomass burning in boreal forests. Total average annual carbon release for the two years ranged between 0.012 and 0.018 Pg C/yr, with the lower value resulting from the AVHRR estimates of fire location and area.

Developing and managing sustainable forest ecosystems for spotted owls in the Sierra Nevada

Treesearch

J. Verner; K.S. McKelvey

1994-01-01

Studies of the California spotted owl have revealed significant selection for habitats with large, old trees; relatively high basal areas of snags; and relatively high biomass in large, downed logs. Based on planning documents for national forests in the Sierra Nevada, we projected declining amounts of older-forest attributes. Region 5 has adopted measures to retain...

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....

Carbon emissions from deforestation and forest fragmentation in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Numata, Izaya; Cochrane, Mark A.; Souza, Carlos M., Jr.; Sales, Marcio H.

2011-10-01

Forest-fragmentation-related edge effects are one of the major causes of forest degradation in Amazonia and their spatio-temporal dynamics are highly influenced by annual deforestation patterns. Rapid biomass collapse due to edge effects in forest fragments has been reported in the Brazilian Amazon; however the collective impacts of this process on Amazonian carbon fluxes are poorly understood. We estimated biomass loss and carbon emissions from deforestation and forest fragmentation related to edge effects on the basis of the INPE (Brazilian National Space Research Institute) PRODES deforestation data and forest biomass volume data. The areas and ages of edge forests were calculated annually and the corresponding biomass loss and carbon emissions from these forest edges were estimated using published rates of biomass decay and decomposition corresponding to the areas and ages of edge forests. Our analysis estimated carbon fluxes from deforestation (4195 Tg C) and edge forest (126-221 Tg C) for 2001-10 in the Brazilian Amazon. The impacts of varying rates of deforestation on regional forest fragmentation and carbon fluxes were also investigated, with the focus on two periods: 2001-5 (high deforestation rates) and 2006-10 (low deforestation rates). Edge-released carbon accounted for 2.6-4.5% of deforestation-related carbon emissions. However, the relative importance of carbon emissions from forest fragmentation increased from 1.7-3.0% to 3.3-5.6% of the respective deforestation emissions between the two contrasting deforestation rates. Edge-related carbon fluxes are of increasing importance for basin-wide carbon accounting, especially as regards ongoing reducing emissions from deforestation and forest degradation (REDD) efforts in Brazilian Amazonia.

Management of forest fires to maximize carbon sequestration in temperate and boreal forests

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

Guggenheim, D.E.

1996-12-31

This study examines opportunities for applying prescribed burning strategies to forest stands to enhance net carbon sequestration and compared prescribed burning strategies with more conventional forestry-based climate change mitigation alternatives, including fire suppression and afforestation. Biomass burning is a major contributor to greenhouse gas accumulation in the atmosphere. Biomass burning has increased by 50% since 1850. Since 1977, the annual extent of burning in the northern temperate and boreal forests has increased dramatically, from six- to nine-fold. Long-term suppression of fires in North America, Russia, and other parts of the world has led to accumulated fuel load and an increasemore » in the destructive power of wildfires. Prescribed burning has been used successfully to reduce the destructiveness of wildfires. However, across vast areas of Russia and other regions, prescribed burning is not a component of forest management practices. Given these factors and the sheer size of the temperate-boreal carbon sink, increasing attention is being focused on the role of these forests in mitigating climate change, and the role of fire management strategies, such as prescribed burning, which could work alongside more conventional forestry-based greenhouse gas offset strategies, such as afforestation.« less

Timber Volume and Biomass Estimates in Central Siberia from Satellite Data

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Kimes, Daniel S.; Kharuk, Vyetcheslav I.

2007-01-01

Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. The biggest deficiency of the existing ground based forest inventories is the uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse, lacking, and often decades old. Remote sensing methods can help overcome these problems. In this joint US and Russian study, we used the moderate resolution imaging spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) and produced a map of timber volume for a 10degx12deg area in Central Siberia. Using these methods, the mean timber volume for the forested area in the total study area was 203 m3/ ha. The new remote sensing methods used in this study provide a truly independent estimate of forest structure, which is not dependent on traditional ground forest inventory methods.

Liquid biofuels - can they meet our expectations?

NASA Astrophysics Data System (ADS)

Glatzel, G.

2012-04-01

Liquid biofuels are one of the options for reducing the emission of greenhouse gases and the dependence on fossil fuels. This is reflected in the DIRECTIVE 2003/30/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on the promotion of the use of biofuels or other renewable fuels for transport. The promotion of E10, an automotive fuel containing 10 percent bioethanol, is based on this directive. At present almost all bioethanol is produced from agricultural crops such as maize, corn or sugar beet and sugar cane in suitable climates. In view of shortages and rising prices of food, in particular in developing countries, the use of food and feed crops for biofuel production is increasingly criticized. Alternative sources of biomass are perennial grasses and wood, whose cellulose fraction can be converted to alcohol by the so called "second generation" processes, which seem to be close to commercial deployment. The use of the total plant biomass increases the biofuel yield per hectare as compared to conventional crops. Of special interest for biofuel production is woody biomass from forests as this avoids competition with food production on arable land. Historically woody biomass was for millennia the predominant source of thermal energy. Before fossil fuels came into use, up to 80 percent of a forest was used for fuel wood, charcoal and raw materials such as potash for trade and industry. Now forests are managed to yield up to 80 percent of high grade timber for the wood industry. Replacing sophisticatedly managed forests by fast growing biofuel plantations could make economic sense for land owners when a protected market is guaranteed by politics, because biofuel plantations would be highly mechanized and cheap to operate, even if costs for certified planting material and fertilizer are added. For forest owners the decision to clear existing long rotation forests for biofuel plantations would still be weighty because of the extended time of decades required to rebuild a timber forest if alternative fuel sources would outcompete biofuels in the future. Because second generation bioethanol plants are technically complex and will require substantial amounts of biomass - at least at current perception - the impact of large scale conversion of arable and forests to biofuel plantations on biodiversity, ground water, rural communities, tourism as well as traffic and transport, just to mention a few, must be considered. Another factor is storability of biomass. Whole plant and woody biomass is much more difficult to store than grains and a steady flux from the plantation to the mill might be difficult to sustain under adverse weather conditions.

Assessing Canada's Forest Carbon Sinks from 1901 TO 2008 BY Combining Inventory with Climate Data (Invited)

NASA Astrophysics Data System (ADS)

Chen, J. M.; Wu, C.; Gonsamo, A.; Kurz, W.; Hember, R.; Price, D. T.; Boisvenue, C.; Zhang, F.; Chang, K.

2013-12-01

The forest carbon cycle is not only controlled by climate, tree species and site conditions, but also by disturbance affecting the biomass and age of forest stands. The Carbon Budget Model of the Canadian forest sector (CBM-CFS3) calculates the complete forest carbon cycle by combining forest inventory data on forest species, biomass and stand age with empirical yield information and statistics on forest disturbances, management and land-use change. It is used for national reporting and climate policy purposes. The Integrated Terrestrial Ecosystem Carbon model (InTEC) is driven by remotely-sensed vegetation parameters (forest type, leaf area index, clumping index) and fire scar, soil and climate data and simulates forest growth and the carbon cycle as a function of stand age using a process-based approach. Gridded forest biomass, stand age and disturbance data based on forest inventory are also used as inputs to InTEC. Efforts are being made to enhance the CBM-CFS3's capacity to assess the impacts of global change on the forest carbon budget by utilizing InTEC process modeling methodology. For this purpose, InTEC is first implemented on 3432 permanent sampling plots in coastal and interior BC, and it is found that climate warming explained 70% and 75% of forest growth enhancement over the period from 1956 to 2001 in coastal and interior BC, respectively, and the remainder is attributed to CO2 and nitrogen fertilization effects. The growth enhancement, in terms of the increase in the stemwood accumulation rate after adjusting for the stand age effect, is about 24% for both areas over the same period. To assess the impact of climate change on the forest carbon cycle across Canada, polygon-based CBM and gridded InTEC results are aggregated to 60 reconciliation units (RU), and their interannual variabilities over the period from 1990 to 2008 are compared in each RU. CBM results show interannual variability in response to forest disturbance, while InTEC results show larger interannual variability because it is affected by both disturbance and climate. The impact of climate at the RU level is generally positive (increased sink) due to warming, but sometimes negative due to water stress. Averaged over Canada, climate warming induced a longer growing season by about one week from 1901 to 2008, enhancing the annual forest carbon sink by about 42×30 TgC y-1 over the period from 1990 to 2008, while CO2 and nitrogen fertilization effects each also contributed about the same amount to Canada's forest carbon sink.

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 (...

Potential Impact of Bioenergy Demand on the Sustainability of the Southern Forest Resource

Treesearch

Karen L. Abt; Robert C. Abt

2012-01-01

The use of woody biomass for the production of domestic bioenergy to meet policy-driven demands could lead to significant changes in the forest resource. These impacts may be limited if woody biomass from forests is defined as only the residues from logging. Yet, if only residue is used, the contribution of woody biomass to a renewable energy portfolio will also be...

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...

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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 TanDEM-X AGB rate from MODIS-derived conversion factors will be compared to that derived from field-based conversion factors. We will also attempt to improve phase-height rate to AGB rate transformation by deriving improved models of mass density dependences on height, based on the aggregation of single-stem allometrics.

Edge effects on growth and biomass partitioning of an Amazonian understory herb (Heliconia acuminata; Heliconiaceae).

PubMed

Bruna, Emilio M; de Andrade, Ana Segalin

2011-10-01

After deforestation, environmental changes in the remaining forest fragments are often most intense near the forest edge, but few studies have evaluated plant growth or plasticity of plant growth in response to edge effects. In a 2-year common garden experiment, we compared biomass allocation and growth of Heliconia acuminata with identical genotypes grown in 50 × 35 m common gardens on a 25-year-old edge and in a forest interior site. Genetically identical plants transplanted to the forest edge and understory exhibited different patterns of growth and biomass allocation. However, individuals with identical genotypes in the same garden often had very different responses. Plants on forest edges also had higher growth rates and increased biomass at the end of the experiment, almost certainly due to the increased light on the forest edge. With over 70000 km of forest edge created annually in the Brazilian Amazon, phenotypic plasticity may play an important role in mediating plant responses to these novel environmental conditions.

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 SRTM data is well suited for vegetation 3-D mapping on a continental scale.

Understory cover and biomass indices predictions for forest ecosystems of the Northwestern United States

Treesearch

Vasile A. Suchar; Nicholas L. Crookston

2010-01-01

The understory community is a critical component of many processes of forest ecosystems. Cover and biomass indices of shrubs and herbs of forested ecosystems of Northwestern United States are presented. Various forest data were recorded for 10,895 plots during a Current Vegetation Survey, over the National Forest lands of entire Pacific Northwest. No significant...

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.

Successional dynamics drive tropical forest nutrient limitation

NASA Astrophysics Data System (ADS)

Chou, C.; Hedin, L. O. O.

2017-12-01

It is increasingly recognized that nutrients such as N and P may significantly constrain the land carbon sink. However, we currently lack a complete understanding of these nutrient cycles in forest ecosystems and how to incorporate them into Earth System Models. We have developed a framework of dynamic forest nutrient limitation, focusing on the role of secondary forest succession and canopy gap disturbances as bottlenecks of high plant nutrient demand and limitation. We used succession biomass data to parameterize a simple ecosystem model and examined the dynamics of nutrient limitation throughout tropical secondary forest succession. Due to the patterns of biomass recovery in secondary tropical forests, we found high nutrient demand from rapid biomass accumulation in the earliest years of succession. Depending on previous land use scenarios, soil nutrient availability may also be low in this time period. Coupled together, this is evidence that there may be high biomass nutrient limitation early in succession, which is partially met by abundant symbiotic nitrogen fixation from certain tree species. We predict a switch from nitrogen limitation in early succession to one of three conditions: (i) phosphorus only, (ii) phosphorus plus nitrogen, or (iii) phosphorus, nitrogen, plus light co-limitation. We will discuss the mechanisms that govern the exact trajectory of limitation as forests build biomass. In addition, we used our model to explore scenarios of tropical secondary forest impermanence and the impacts of these dynamics on ecosystem nutrient limitation. We found that secondary forest impermanence exacerbates nutrient limitation and the need for nitrogen fixation early in succession. Together, these results indicate that biomass recovery dynamics early in succession as well as their connection to nutrient demand and limitation are fundamental for understanding and modeling nutrient limitation of the tropical forest carbon sink.

Climate consequences of large-scale land-use changes as climate engineering tools

NASA Astrophysics Data System (ADS)

Mayer, Dorothea; Kracher, Daniela; Reick, Christian; Pongratz, Julia

2015-04-01

Terrestrial carbon sinks are much-discussed as climate engineering methods both in politics and science. The debate focuses mostly on their potential for carbon sequestration and fossil-fuel substitution, whereas other effects such as changes in heat and water fluxes are often ignored. We assess potentials and side-effects of two different land-use types suggested as climate engineering tools, forest and herbaceous biomass plantations. We integrate herbaceous biomass plantations as new plant functional types into the land component (JSBACH) of the Max-Planck-Institute Earth System Model (MPI-ESM). Herbaceous biomass plantations alter surface albedo, carbon and water cycles compared to forests. We adapted the JSBACH carbon cycle (assimilation and respiration) to reflect a highly productive biomass grass and the phenology to account for harvests just before the beginning of the growing season. The harvested material is transferred to a separate pool that can be adapted to reflect different biomass utilization pathways. Where possible, the model was validated using yield measurements and water-use efficiency calculations available from literature data. We compare the potentials and side-effects of afforestation and herbaceous biomass plantations in a plausible global scenario: under the representative concentration pathway (RCP) 4.5, large areas of agricultural lands are projected to be abandoned as food production intensifies on the most productive soils. We intend to model the climatic consequences of using these abandoned croplands for afforestation or biomass plantations, under an RCP 8.5 forcing (high CO2 emissions). We emphasize differences between biogeochemical and biogeophysical effects of land-use on climate and how these factors interact on the local and global scale. Apart from direct climatic effects (energy, water, and carbon fluxes), we attempt to consistently account for fossil-fuel substitution effects of biomass plantations in a coupled model. This study comprises the fist part of a larger project analyzing four different land-use types: unmanaged forest, managed forest, woody biomass plantations and herbaceous biomass plantations. Our study is part of the interdisciplinary program 'Climate Engineering: Risks, Challenges and Opportunities?' which allows for a consistent comparison of land-based climate engineering to other methods such as solar radiation management or ocean alkalinization.

The Oldest, Slowest Rainforests in the World? Massive Biomass and Slow Carbon Dynamics of Fitzroya cupressoides Temperate Forests in Southern Chile.

PubMed

Urrutia-Jalabert, Rocio; Malhi, Yadvinder; Lara, Antonio

2015-01-01

Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP), carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC) in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA) in the Andean Cordillera. Aboveground live biomass was 113-114 Mg C ha(-1) and 448-517 Mg C ha(-1) in AC and AA, respectively. Aboveground productivity was 3.35-3.36 Mg C ha(-1) year(-1) in AC and 2.22-2.54 Mg C ha(-1) year(-1) in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21-4.24 and 3.78-4.10 Mg C ha(-1) year(-1) in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539-640 years for the whole forest in the Andes and 1368-1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia.

The Oldest, Slowest Rainforests in the World? Massive Biomass and Slow Carbon Dynamics of Fitzroya cupressoides Temperate Forests in Southern Chile

PubMed Central

Urrutia-Jalabert, Rocio; Malhi, Yadvinder; Lara, Antonio

2015-01-01

Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP), carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC) in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA) in the Andean Cordillera. Aboveground live biomass was 113–114 Mg C ha-1 and 448–517 Mg C ha-1 in AC and AA, respectively. Aboveground productivity was 3.35–3.36 Mg C ha-1 year-1 in AC and 2.22–2.54 Mg C ha-1 year-1 in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21–4.24 and 3.78–4.10 Mg C ha-1 year-1 in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539–640 years for the whole forest in the Andes and 1368–1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia. PMID:26353111

Variation in forest biomass change highlights regional differences in forest succession in the Pacific Northwest, USA.

NASA Astrophysics Data System (ADS)

Bell, D. M.; Gray, A. N.

2014-12-01

Forest successional theory describes the changes in forest biomass and community composition from forest establishment to climax communities, but the drivers of succession are still widely debated. For example, successional models have related biomass and community change to stand age, species rarity within the community, small-scale disturbance, or the ability of species to survive under low resource conditions. The degree to which these drivers might vary regionally limits our ability to model and predict ecosystem change. Our objective was to assess whether forest successional theory explains observed changes in species biomass and community composition across forests of the U. S. Pacific Northwest. Using remeasurements of 9,700 Current Vegetation Survey (CVS) National Forest inventory plots primarily in Oregon and Washington, we quantified the effects of forest stand age, community composition, disturbance, and moisture (i.e., topography and climate) on changes in species-specific proportional live biomass (ΔB) and species dominance (ΔD). We focused on differences in forest successional patterns in two vegetation zones: the Tsuga heterophylla (TSHE) zone, found at low elevations on the wet, west side of the Cascade Mountains; and the Abies concolor (ABCO) zone, found at mid-elevations on the dry, east side of the Cascade Mountains. Preliminary results indicate that the regional differences in tree species biomass change and dominance appear to be related to responses to climate and disturbance. Strong positive effects of cover change on ΔB were observed in the drier ABCO zone, but not the wetter TSHE zone. ΔB and ΔD were more often sensitive to precipitation and topographic position in the ABCO zone. In both regions, we found that ΔB was strongly negatively related to species biomass and stand age while ΔD was strongly negatively related to relative density, highlighting the importance of both age and community in shaping succession. Given that the importance of different forest successional processes in shaping ecosystem change varied regionally, this work provides valuable insights into potential risks of changing climate and disturbance regimes to species persistence and ecosystem stability across forests of the U.S. Pacific Northwest.

Producer gas production of Indonesian biomass in fixed-bed downdraft gasifier as an alternative fuels for internal combustion engines

NASA Astrophysics Data System (ADS)

Simanjuntak, J. P.; Lisyanto; Daryanto, E.; Tambunan, B. H.

2018-03-01

downdraft biomass gasification reactors, coupled with reciprocating internal combustion engines (ICE) are a viable technology for small scale heat and power generation. The direct use of producer gas as fuel subtitution in an ICE could be of great interest since Indonesia has significant land area in different forest types that could be used to produce bioenergy and convert forest materials to bioenergy for use in energy production and the versatility of this engine. This paper will look into the aspect of biomass energie as a contributor to energy mix in Indonesia. This work also contains information gathered from numerous previews study on the downdraft gasifier based on experimental or simulation study on the ability of producer gas as fuels for internal combustion engines aplication. All data will be used to complement the preliminary work on biomass gasification using downdraft to produce producer gas and its application to engines.

[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 rising trend in general. During the period of 2014-2094, the total aboveground biomass under RCP2.6, RCP4.5 and RCP8.5 scenarios increased by 68.2%, 79.3% and 72.6%, respectively. The total aboveground biomass under various climatic scenarios sort as: RCP4.5>RCP8.5>RCP2.6. We thought that an appropriate temperature might be beneficial to the biomass accumulation in this study area. However, overextended temperature might hinder the sustainable development of forest production and ecological function.

Production of bio-oil from underutilized forest biomass using an auger reactor

Treesearch

H. Ravindran; S. Thangalzhy-Gopakumar; S. Adhikari; O. Fasina; M. Tu; B. Via; E. Carter; S. Taylor

2015-01-01

Conversion of underutilized forest biomass to bio-oil could be a niche market for energy production. In this work, bio-oil was produced from underutilized forest biomass at selected temperatures between 425–500°C using an auger reactor. Physical properties of bio-oil, such as pH, density, heating value, ash, and water, were analyzed and compared with an ASTM standard...

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.

PCDD/F EMISSIONS FROM FOREST FIRES

EPA Science Inventory

Polychlorinated dibenzo-p-dioxin and polychlorinated dibenzofuran (PCDD/F) emissions from combustion of forest biomass were sampled to obtain an estimated emission factor for forest fires. An equal composition of live shoot and litter biomass from Oregon and North Carolina was bu...

PCDD/F EMISSIONS FROM FOREST FIRE SIMULATIONS

EPA Science Inventory

Polychlorinated dibenzo-p-dioxin and polychlorinated dibenzofuran (PCDD/F) emissions from combustion of forest biomass were sampled to obtain an estimated emission factor for forest fires. An equal composition of live shoot and litter biomass from Oregon and North Carolina was b...

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

PubMed Central

Holden, Sandra R.; Treseder, Kathleen K.

2013-01-01

Climate warming is likely to increase the frequency and severity of forest disturbances, with uncertain consequences for soil microbial communities and their contribution to ecosystem C dynamics. To address this uncertainty, we conducted a meta-analysis of 139 published soil microbial responses to forest disturbances. These disturbances included abiotic (fire, harvesting, storm) and biotic (insect, pathogen) disturbances. We hypothesized that soil microbial biomass would decline following forest disturbances, but that abiotic disturbances would elicit greater reductions in microbial biomass than biotic disturbances. In support of this hypothesis, across all published studies, disturbances reduced soil microbial biomass by an average of 29.4%. However, microbial responses differed between abiotic and biotic disturbances. Microbial responses were significantly negative following fires, harvest, and storms (48.7, 19.1, and 41.7% reductions in microbial biomass, respectively). In contrast, changes in soil microbial biomass following insect infestation and pathogen-induced tree mortality were non-significant, although biotic disturbances were poorly represented in the literature. When measured separately, fungal and bacterial responses to disturbances mirrored the response of the microbial community as a whole. Changes in microbial abundance following disturbance were significantly positively correlated with changes in microbial respiration. We propose that the differential effect of abiotic and biotic disturbances on microbial biomass may be attributable to differences in soil disruption and organic C removal from forests among disturbance types. Altogether, these results suggest that abiotic forest disturbances may significantly decrease soil microbial abundance, with corresponding consequences for microbial respiration. Further studies are needed on the effect of biotic disturbances on forest soil microbial communities and soil C dynamics. PMID:23801985

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.

Spatial and topographic trends in forest expansion and biomass change, from regional to local scales.

PubMed

Buma, Brian; Barrett, Tara M

2015-09-01

Natural forest growth and expansion are important carbon sequestration processes globally. Climate change is likely to increase forest growth in some regions via CO2 fertilization, increased temperatures, and altered precipitation; however, altered disturbance regimes and climate stress (e.g. drought) will act to reduce carbon stocks in forests as well. Observations of asynchrony in forest change is useful in determining current trends in forest carbon stocks, both in terms of forest density (e.g. Mg ha(-1) ) and spatially (extent and location). Monitoring change in natural (unmanaged) areas is particularly useful, as while afforestation and recovery from historic land use are currently large carbon sinks, the long-term viability of those sinks depends on climate change and disturbance dynamics at their particular location. We utilize a large, unmanaged biome (>135 000 km(2) ) which spans a broad latitudinal gradient to explore how variation in location affects forest density and spatial patterning: the forests of the North American temperate rainforests in Alaska, which store >2.8 Pg C in biomass and soil, equivalent to >8% of the C in contiguous US forests. We demonstrate that the regional biome is shifting; gains exceed losses and are located in different spatio-topographic contexts. Forest gains are concentrated on northerly aspects, lower elevations, and higher latitudes, especially in sheltered areas, whereas loss is skewed toward southerly aspects and lower latitudes. Repeat plot-scale biomass data (n = 759) indicate that within-forest biomass gains outpace losses (live trees >12.7 cm diameter, 986 Gg yr(-1) ) on gentler slopes and in higher latitudes. This work demonstrates that while temperate rainforest dynamics occur at fine spatial scales (<1000 m(2) ), the net result of thousands of individual events is regionally patterned change. Correlations between the disturbance/establishment imbalance and biomass accumulation suggest the potential for relatively rapid biome shifts and biomass changes. © 2015 John Wiley & Sons Ltd.

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.

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

PubMed

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

2015-02-01

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

Drought effects on fine-root and ectomycorrhizal-root biomass in managed Pinus oaxacana Mirov stands in Oaxaca, Mexico.

PubMed

Valdés, María; Asbjornsen, Heidi; Gómez-Cárdenas, Martín; Juárez, Margarita; Vogt, Kristiina A

2006-03-01

The effects of a severe drought on fine-root and ectomycorrhizal biomass were investigated in a forest ecosystem dominated by Pinus oaxacana located in Oaxaca, Mexico. Root cores were collected during both the wet and dry seasons of 1998 and 1999 from three sites subjected to different forest management treatments in 1990 and assessed for total fine-root biomass and ectomycorrhizal-root biomass. Additionally, a bioassay experiment with P. oaxacana seedlings was conducted to assess the ectomycorrhizal inoculum potential of the soil for each of the three stands. Results indicated that biomasses of both fine roots and ectomycorrhizal roots were reduced by almost 60% in the drought year compared to the nondrought year. There were no significant differences in ectomycorrhizal and fine-root biomass between the wet and dry seasons. Further, the proportion of total root biomass consisting of ectomycorrhizal roots did not vary between years or seasons. These results suggest that both total fine-root biomass and ectomycorrhizal-root biomass are strongly affected by severe drought in these high-elevation tropical pine forests, and that these responses outweigh seasonal effects. Forest management practices in these tropical pine forests should consider the effects of drought on the capacity of P. oaxacana to maintain sufficient levels of ectomycorrhizae especially when there is a potential for synergistic interactions between multiple disturbances that may lead to more severe stress in the host plant and subsequent reductions in ectomycorrhizal colonization.

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+).

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

Treesearch

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

2008-01-01

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

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...

Decadal change of forest biomass carbon stocks and tree demography in the Delaware River Basin

Treesearch

Bing Xu; Yude Pan; Alain F. Plante; Arthur Johnson; Jason Cole; Richard Birdsey

2016-01-01

Quantifying forest biomass carbon (C) stock change is important for understanding forest dynamics and their feedbacks with climate change. Forests in the northeastern U.S. have been a net carbon sink in recent decades, but C accumulation in some northern hardwood forests has been halted due to the impact of emerging stresses such as invasive pests, land use change and...

Changing Amazon biomass and the role of atmospheric CO2 concentration, climate, and land use

NASA Astrophysics Data System (ADS)

Almeida Castanho, Andrea D.; Galbraith, David; Zhang, Ke; Coe, Michael T.; Costa, Marcos H.; Moorcroft, Paul

2016-01-01

The Amazon tropical evergreen forest is an important component of the global carbon budget. Its forest floristic composition, structure, and function are sensitive to changes in climate, atmospheric composition, and land use. In this study biomass and productivity simulated by three dynamic global vegetation models (Integrated Biosphere Simulator, Ecosystem Demography Biosphere Model, and Joint UK Land Environment Simulator) for the period 1970-2008 are compared with observations from forest plots (Rede Amazónica de Inventarios Forestales). The spatial variability in biomass and productivity simulated by the DGVMs is low in comparison to the field observations in part because of poor representation of the heterogeneity of vegetation traits within the models. We find that over the last four decades the CO2 fertilization effect dominates a long-term increase in simulated biomass in undisturbed Amazonian forests, while land use change in the south and southeastern Amazonia dominates a reduction in Amazon aboveground biomass, of similar magnitude to the CO2 biomass gain. Climate extremes exert a strong effect on the observed biomass on short time scales, but the models are incapable of reproducing the observed impacts of extreme drought on forest biomass. We find that future improvements in the accuracy of DGVM predictions will require improved representation of four key elements: (1) spatially variable plant traits, (2) soil and nutrients mediated processes, (3) extreme event mortality, and (4) sensitivity to climatic variability. Finally, continued long-term observations and ecosystem-scale experiments (e.g. Free-Air CO2 Enrichment experiments) are essential for a better understanding of the changing dynamics of tropical forests.

The Creation and Role of the USDA Biomass Research Centers

Treesearch

William F. Anderson; Jeffery Steiner; Randy Raper; Ken Vogel; Terry Coffelt; Brenton Sharratt; Bob Rummer; Robert L. Deal; Alan Rudie

2011-01-01

The Five USDA Biomass Research Centers were created to facilitate coordinated research to enhance the establishment of a sustainable feedstock production for bio-based renewable energy in the United States. Scientists and staff of the Agricultural Research Service (ARS) and Forest Service (FS) within USDA collaborate with other federal agencies, universities and...

Mercury emissions from biomass burning in China.

PubMed

Huang, Xin; Li, Mengmeng; Friedli, Hans R; Song, Yu; Chang, Di; Zhu, Lei

2011-11-01

Biomass burning covers open fires (forest and grassland fires, crop residue burning in fields, etc.) and biofuel combustion (crop residues and wood, etc., used as fuel). As a large agricultural country, China may produce large quantities of mercury emissions from biomass burning. A new mercury emission inventory in China is needed because previous studies reflected outdated biomass burning with coarse resolution. Moreover, these studies often adopted the emission factors (mass of emitted species per mass of biomass burned) measured in North America. In this study, the mercury emissions from biomass burning in China (excluding small islands in the South China Sea) were estimated, using recently measured mercury concentrations in various biomes in China as emission factors. Emissions from crop residues and fuelwood were estimated based on annual reports distributed by provincial government. Emissions from forest and grassland fires were calculated by combining moderate resolution imaging spectroradiometer (MODIS) burned area product with combustion efficiency (ratio of fuel consumption to total available fuels) considering fuel moisture. The average annual emission from biomass burning was 27 (range from 15.1 to 39.9) Mg/year. This inventory has high spatial resolution (1 km) and covers a long period (2000-2007), making it useful for air quality modeling.

Estimating plant biomass for undergrowth species of northeastern Minnesota forest communities.

Treesearch

Lewis F. Ohmann; David F. Grigal; Lynn L. Rogers

1981-01-01

Biomass prediction equations were developed for some common ground cover plants from forest communities of northeastern Minnesota. The allometric function was used to predict biomass (dry weight) with ocular estimates of percent ground cover of the plant as the independent variable.

Estimating tree biomass regressions and their error, proceedings of the workshop on tree biomass regression functions and their contribution to the error

Treesearch

Eric H. Wharton; Tiberius Cunia

1987-01-01

Proceedings of a workshop co-sponsored by the USDA Forest Service, the State University of New York, and the Society of American Foresters. Presented were papers on the methodology of sample tree selection, tree biomass measurement, construction of biomass tables and estimation of their error, and combining the error of biomass tables with that of the sample plots or...

A dataset of forest biomass structure for Eurasia.

PubMed

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

2017-05-16

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

A dataset of forest biomass structure for Eurasia

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Estimating volumes and costs of forest biomass in western Montana using forest inventory and geospatial data

Treesearch

Dan Loeffler; David E. Calkin; Robin P. Silverstein

2006-01-01

Utilizing timber harvest residues (biomass) for renewable energy production provides an alternative disposal method to onsite burning that may improve the economic viability of hazardous fuels treatments. Due to the relatively low value of biomass, accurate estimates of biomass volumes and costs of collection and delivery are essential if investment in renewable energy...

Regional biomass stores and dynamics in forests of coastal Alaska

Treesearch

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

2015-01-01

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

Regulatory and information support for evaluation of biological productivity of Ukrainian forests and climate change

NASA Astrophysics Data System (ADS)

Lakyda, Petro; Vasylyshyn, Roman; Lakyda, Ivan

2013-04-01

Stabilization and preservation of the planet's climate system today is regarded as one of the most important global political-economic, environmental and social problems of mankind. Rising concentration of carbon dioxide in the planet's atmosphere due to anthropogenic impact is the main reason leading to global climate change. Due to the above mentioned, social demands on forests are changing their biosphere role and function of natural sink of greenhouse gases becomes top priority. It is known that one of the most essential components of biological productivity of forests is their live biomass. Absorption, long-term sequestration of carbon and generation of oxygen are secured by its components. System research of its parametric structure and development of regulatory and reference information for assessment of aboveground live biomass components of trees and stands of the main forest-forming tree species in Ukraine began over twenty-five years ago at the department of forest mensuration and forest inventory of National University of Life and Environmental Sciences of Ukraine, involving staff from other research institutions. Today, regulatory and reference materials for evaluation of parametric structure of live biomass are developed for trees of the following major forest-forming tree species of Ukraine: Scots pine of natural and artificial origin, Crimean pine, Norway spruce, silver fir, pedunculate oak, European beech, hornbeam, ash, common birch, aspen and black alder (P.I. Lakyda et al., 2011). An ongoing process on development of similar regulatory and reference materials for forest stands of the abovementioned forest-forming tree species of Ukraine is secured by scientists of departments of forest management, and forest mensuration and forest inventory. The total experimental research base is 609 temporary sample plots, where 4880 model trees were processed, including 3195 model trees with estimates of live biomass components. Laboratory studies conducted on 1743 research sections of tree stems, 809 samples of crown branches, 2560 model tree greenery branches, 346 batches of needles and 534 batches of leaves. These materials have high scientific and practical value, forming a basis for quantitative evaluation of biological productivity of forests in Ukraine, which are of great importance for mitigation of climate change. They also can be used as a data source for development of systems of models of various purposes, which find their application in Ukrainian and world forest science and practice.

Widespread decline of Congo rainforest greenness in the past decade.

PubMed

Zhou, Liming; Tian, Yuhong; Myneni, Ranga B; Ciais, Philippe; Saatchi, Sassan; Liu, Yi Y; Piao, Shilong; Chen, Haishan; Vermote, Eric F; Song, Conghe; Hwang, Taehee

2014-05-01

Tropical forests are global epicentres of biodiversity and important modulators of climate change, and are mainly constrained by rainfall patterns. The severe short-term droughts that occurred recently in Amazonia have drawn attention to the vulnerability of tropical forests to climatic disturbances. The central African rainforests, the second-largest on Earth, have experienced a long-term drying trend whose impacts on vegetation dynamics remain mostly unknown because in situ observations are very limited. The Congolese forest, with its drier conditions and higher percentage of semi-evergreen trees, may be more tolerant to short-term rainfall reduction than are wetter tropical forests, but for a long-term drought there may be critical thresholds of water availability below which higher-biomass, closed-canopy forests transition to more open, lower-biomass forests. Here we present observational evidence for a widespread decline in forest greenness over the past decade based on analyses of satellite data (optical, thermal, microwave and gravity) from several independent sensors over the Congo basin. This decline in vegetation greenness, particularly in the northern Congolese forest, is generally consistent with decreases in rainfall, terrestrial water storage, water content in aboveground woody and leaf biomass, and the canopy backscatter anomaly caused by changes in structure and moisture in upper forest layers. It is also consistent with increases in photosynthetically active radiation and land surface temperature. These multiple lines of evidence indicate that this large-scale vegetation browning, or loss of photosynthetic capacity, may be partially attributable to the long-term drying trend. Our results suggest that a continued gradual decline of photosynthetic capacity and moisture content driven by the persistent drying trend could alter the composition and structure of the Congolese forest to favour the spread of drought-tolerant species.

Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change

PubMed Central

Longo, Marcos; Baccini, Alessandro; Phillips, Oliver L.; Lewis, Simon L.; Alvarez-Dávila, Esteban; Segalin de Andrade, Ana Cristina; Brienen, Roel J. W.; Erwin, Terry L.; Feldpausch, Ted R.; Monteagudo Mendoza, Abel Lorenzo; Nuñez Vargas, Percy; Prieto, Adriana; Silva-Espejo, Javier Eduardo; Malhi, Yadvinder; Moorcroft, Paul R.

2016-01-01

Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem’s resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest’s response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions. PMID:26711984

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.

Germination and initial growth of tree seedlings on deforested and natural forest soil at Dulhazara, Bangladesh.

PubMed

Hossain, M Mohitul

2012-12-01

The destruction of natural forest is increasing due to urbanization, industrialization, settlement and for the agricultural expansion over last few decades, and studies for their recovery need to be undertaken. With this aim, this comparative study was designed to see the effects of deforested soil on germination and growth performance of five different tree species. In the experiment, five species namely Gmelina arborea, Swietenia mahagoni, Dipterocarpus turbinatus, Acacia auriculiformis and Syzygium grande were germinated for six weeks on seedbeds and raised in pots (25cm diameter, 30cm height), that were filled with two soil and type of land use: deforested and adjacent natural forest of Dulhazara Safari Park. Growth performance of seedling was observed up to 15 months based on height, collar diameter and biomass production at the end. Our results showed that the germination rate was almost similar in both type of land uses. Height growth of D. turbinatus, G. arborea and S. mahagoni seedlings was almost similar and A. auriculi formis and S. grande lower in deforested soil compared to natural forest soil, while collar diameter ofA. auriculi formis, G. arborea, S. grande and S. mahagoni lower and D. turbinatus similar in deforested soil compared to natural forest soil. After uprooting at 19 months, S. mahagoni seedlings were showed significantly (p< or =0.05) higher oven dry biomass, D. turbinatus and A. auriculiformis higher, while G. arborea showed significantly (p< or =0.05) lower and S. grande almost similar oven dry biomass in deforested soil compared to natural forest soil. Oven dry biomass of D. turbinatus seedlings at 19 month age in deforested soil was 21.96g (n=5) and in natural forest soil 18.86g (n=5). However, differences in germination rate and growth performance for different tree species indicated that soil are not too much deteriorated through deforestation at Dulhazara and without any failure such deforested lands would be possible to bring under forest through plantation.

Improving Large-scale Biomass Burning Carbon Consumption and Emissions Estimates in the Former Soviet Union based on Fire Weather

NASA Astrophysics Data System (ADS)

Westberg, D. J.; Soja, A. J.; Tchebakova, N.; Parfenova, E. I.; Kukavskaya, E.; de Groot, B.; McRae, D.; Conard, S. G.; Stackhouse, P. W., Jr.

2012-12-01

Estimating the amount of biomass burned during fire events is challenging, particularly in remote and diverse regions, like those of the Former Soviet Union (FSU). Historically, we have typically assumed 25 tons of carbon per hectare (tC/ha) is emitted, however depending on the ecosystem and severity, biomass burning emissions can range from 2 to 75 tC/ha. Ecosystems in the FSU span from the tundra through the taiga to the forest-steppe, steppe and desserts and include the extensive West Siberian lowlands, permafrost-lain forests and agricultural lands. Excluding this landscape disparity results in inaccurate emissions estimates and incorrect assumptions in the transport of these emissions. In this work, we present emissions based on a hybrid ecosystem map and explicit estimates of fuel that consider the depth of burning based on the Canadian Forest Fire Weather Index System. Specifically, the ecosystem map is a fusion of satellite-based data, a detailed ecosystem map and Alexeyev and Birdsey carbon storage data, which is used to build carbon databases that include the forest overstory and understory, litter, peatlands and soil organic material for the FSU. We provide a range of potential carbon consumption estimates for low- to high-severity fires across the FSU that can be used with fire weather indices to more accurately estimate fire emissions. These data can be incorporated at ecoregion and administrative territory scales and are optimized for use in large-scale Chemical Transport Models. Additionally, paired with future climate scenarios and ecoregion cover, these carbon consumption data can be used to estimate potential emissions.

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...

Phosphate addition enhanced soil inorganic nutrients to a large extent in three tropical forests.

PubMed

Zhu, Feifei; Lu, Xiankai; Liu, Lei; Mo, Jiangming

2015-01-21

Elevated nitrogen (N) deposition may constrain soil phosphorus (P) and base cation availability in tropical forests, for which limited evidence have yet been available. In this study, we reported responses of soil inorganic nutrients to full factorial N and P treatments in three tropical forests different in initial soil N status (N-saturated old-growth forest and two less-N-rich younger forests). Responses of microbial biomass, annual litterfall production and nutrient input were also monitored. Results showed that N treatments decreased soil inorganic nutrients (except N) in all three forests, but the underlying mechanisms varied depending on forests: through inhibition on litter decomposition in the old-growth forest and through Al(3+) replacement of Ca(2+) in the two younger forests. In contrast, besides great elevation in soil available P, P treatments induced 60%, 50%, 26% increases in sum of exchangeable (K(+)+Ca(2+)+Mg(2+)) in the old-growth and the two younger forests, respectively. These positive effects of P were closely related to P-stimulated microbial biomass and litter nutrient input, implying possible stimulation of nutrient return. Our results suggest that N deposition may result in decreases in soil inorganic nutrients (except N) and that P addition can enhance soil inorganic nutrients to support ecosystem processes in these tropical forests.

Phosphate addition enhanced soil inorganic nutrients to a large extent in three tropical forests

PubMed Central

Zhu, Feifei; Lu, Xiankai; Liu, Lei; Mo, Jiangming

2015-01-01

Elevated nitrogen (N) deposition may constrain soil phosphorus (P) and base cation availability in tropical forests, for which limited evidence have yet been available. In this study, we reported responses of soil inorganic nutrients to full factorial N and P treatments in three tropical forests different in initial soil N status (N-saturated old-growth forest and two less-N-rich younger forests). Responses of microbial biomass, annual litterfall production and nutrient input were also monitored. Results showed that N treatments decreased soil inorganic nutrients (except N) in all three forests, but the underlying mechanisms varied depending on forests: through inhibition on litter decomposition in the old-growth forest and through Al3+ replacement of Ca2+ in the two younger forests. In contrast, besides great elevation in soil available P, P treatments induced 60%, 50%, 26% increases in sum of exchangeable (K++Ca2++Mg2+) in the old-growth and the two younger forests, respectively. These positive effects of P were closely related to P-stimulated microbial biomass and litter nutrient input, implying possible stimulation of nutrient return. Our results suggest that N deposition may result in decreases in soil inorganic nutrients (except N) and that P addition can enhance soil inorganic nutrients to support ecosystem processes in these tropical forests. PMID:25605567

Using airborne lidar as a sampling tool for estimating forest biomass resources in the upper Tanana Valley of interior Alaska

Treesearch

Hans-Erik Andersen; Jacob Strunk; Hailemariam Temesgen

2011-01-01

Airborne laser scanning, collected in a sampling mode, has the potential to be a valuable tool for estimating the biomass resources available to support bioenergy production in rural communities of interior Alaska. In this study, we present a methodology for estimating forest biomass over a 201,226-ha area (of which 163,913 ha are forested) in the upper Tanana valley...

Total peroxy nitrates and ozone production : analysis of forest fire plumes during BORTAS campaign

NASA Astrophysics Data System (ADS)

Busilacchio, Marcella; Di Carlo, Piero; Aruffo, Eleonora; Biancofiore, Fabio; Giammaria, Franco; Bauguitte, Stephane; Lee, James; Moller, Sarah; Lewis, Ally; Parrington, Mark; Palmer, Paul; Dari Salisburgo, Cesare

2014-05-01

The goal of this work is to investigate the connection between PNS and ozone within plumes emitted from boreal forest fires and the possible perturbation to oxidant chemistry in the troposphere. During the Aircraft campaign in Canada called BORTAS (summer 2011 ) were carried out several profiles from ground up to 10 km with the BAe-146 aircraft to observe the atmospheric composition inside and outside fire plumes. The BORTAS flights have been selected based on the preliminary studies of 'Plume identification', selecting those effected by Boreal forest fire emissions (CO > 200 ppbv). The FLAMBE fire counts were used concertedly with back trajectory calculations generated by the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to locate the sources of Boreal biomass burning.Profiles measured on board the BAe-146 aircraft are used to calculate the productions of PNs and O3 within the biomass burning plume. By selecting the flights that intercept the biomass burning plume, we evaluate the ratio between the ozone production and the PNs production within the plume. Analyzing this ratio it is possible to determine whether O3 production or PNs production is the dominant process in the biomass burning boreal plume detected during BORTAS campaign.

Estimation of Forest Fuel Load from Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Saatchi, Sassan; Despain, Don G.; Halligan, Kerry; Crabtree, Robert

2007-01-01

Understanding fire behavior characteristics and planning for fire management require maps showing the distribution of wildfire fuel loads at medium to fine spatial resolution across large landscapes. Radar sensors from airborne or spaceborne platforms have the potential of providing quantitative information about the forest structure and biomass components that can be readily translated to meaningful fuel load estimates for fire management. In this paper, we used multifrequency polarimetric synthetic aperture radar imagery acquired over a large area of the Yellowstone National Park (YNP) by the AIRSAR sensor, to estimate the distribution of forest biomass and canopy fuel loads. Semi-empirical algorithms were developed to estimate crown and stem biomass and three major fuel load parameters, canopy fuel weight, canopy bulk density, and foliage moisture content. These estimates when compared directly to measurements made at plot and stand levels, provided more than 70% accuracy, and when partitioned into fuel load classes, provided more than 85% accuracy. Specifically, the radar generated fuel parameters were in good agreement with the field-based fuel measurements, resulting in coefficients of determination of R(sup 2) = 85 for the canopy fuel weight, R(sup 2)=.84 for canopy bulk density and R(sup 2) = 0.78 for the foliage biomass.

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 resemble the FIA aboveground biomass in terms of data distribution, overall agreement, and spatial similarity across scales. Uncertainties are quantified (ranged from 0.2 to 0.4) by taking into account the spatial mismatch (FIA plot vs. PRISM grid), heterogeneity (species composition), and an example bias scenario (= 0.2) in the root system extents.

Estimating forest biomass and volume using airborne laser data

NASA Technical Reports Server (NTRS)

Nelson, Ross; Krabill, William; Tonelli, John

1988-01-01

An airborne pulsed laser system was used to obtain canopy height data over a southern pine forest in Georgia in order to predict ground-measured forest biomass and timber volume. Although biomass and volume estimates obtained from the laser data were variable when compared with the corresponding ground measurements site by site, the present models are found to predict mean total tree volume within 2.6 percent of the ground value, and mean biomass within 2.0 percent. The results indicate that species stratification did not consistently improve regression relationships for four southern pine species.

Changes in necromass and nutrients on the forest floor of a palm floodplain forest in the Luquillo mountains of Puerto Rico.

Treesearch

ARIEL E. LUGO; JORGE L. FRANGI

2003-01-01

We studied changes that occurred between 1980 and 2000 in forest floor biomass (necromass+ biomass of herbaceous plants), nutrient stocks, and plant composition of a Prestoea montana floodplain forest. The forest was located in the Luquillo Mountains of Puerto Rico. Several storms and hurricanes passed near the study site during that period, the most severe being...

Relating multifrequency radar backscattering to forest biomass: Modeling and AIRSAR measurement

NASA Technical Reports Server (NTRS)

Sun, Guo-Qing; Ranson, K. Jon

1992-01-01

During the last several years, significant efforts in microwave remote sensing were devoted to relating forest parameters to radar backscattering coefficients. These and other studies showed that in most cases, the longer wavelength (i.e. P band) and cross-polarization (HV) backscattering had higher sensitivity and better correlation to forest biomass. This research examines this relationship in a northern forest area through both backscatter modeling and synthetic aperture radar (SAR) data analysis. The field measurements were used to estimate stand biomass from forest weight tables. The backscatter model described by Sun et al. was modified to simulate the backscattering coefficients with respect to stand biomass. The average number of trees per square meter or radar resolution cell, and the average tree height or diameter breast height (dbh) in the forest stand are the driving parameters of the model. The rest of the soil surface, orientation, and size distributions of leaves and branches, remain unchanged in the simulations.

The limited contribution of large trees to annual biomass production in an old-growth tropical forest.

PubMed

Ligot, Gauthier; Gourlet-Fleury, Sylvie; Ouédraogo, Dakis-Yaoba; Morin, Xavier; Bauwens, Sébastien; Baya, Fidele; Brostaux, Yves; Doucet, Jean-Louis; Fayolle, Adeline

2018-04-16

Although the importance of large trees regarding biodiversity and carbon stock in old-growth forests is undeniable, their annual contribution to biomass production and carbon uptake remains poorly studied at the stand level. To clarify the role of large trees in biomass production, we used data of tree growth, mortality, and recruitment monitored during 20 yr in 10 4-ha plots in a species-rich tropical forest (Central African Republic). Using a random block design, three different silvicultural treatments, control, logged, and logged + thinned, were applied in the 10 plots. Annual biomass gains and losses were analyzed in relation to the relative biomass abundance of large trees and by tree size classes using a spatial bootstrap procedure. Although large trees had high individual growth rates and constituted a substantial amount of biomass, stand-level biomass production decreased with the abundance of large trees in all treatments and plots. The contribution of large trees to annual stand-level biomass production appeared limited in comparison to that of small trees. This pattern did not only originate from differences in abundance of small vs. large trees or differences in initial biomass stocks among tree size classes, but also from a reduced relative growth rate of large trees and a relatively constant mortality rate among tree size classes. In a context in which large trees are increasingly gaining attention as being a valuable and a key structural characteristic of natural forests, the present study brought key insights to better gauge the relatively limited role of large trees in annual stand-level biomass production. In terms of carbon uptake, these results suggest, as already demonstrated, a low net carbon uptake of old-growth forests in comparison to that of logged forests. Tropical forests that reach a successional stage with relatively high density of large trees progressively cease to be carbon sinks as large trees contribute sparsely or even negatively to the carbon uptake at the stand level. © 2018 by the Ecological Society of America.

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

PubMed

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

2013-10-26

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

Improving SWAT for simulating water and carbon fluxes of forest ecosystems

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

Yang, Qichun; Zhang, Xuesong

2016-11-01

As a widely used watershed model for assessing impacts of anthropogenic and natural disturbances on water quantity and quality, the Soil and Water Assessment Tool (SWAT) has not been extensively tested in simulating water and carbon fluxes of forest ecosystems. Here, we examine SWAT simulations of evapotranspiration (ET), net primary productivity (NPP), net ecosystem exchange (NEE), and plant biomass at ten AmeriFlux forest sites across the U.S. We identify unrealistic radiation use efficiency (Bio_E), large leaf to biomass fraction (Bio_LEAF), and missing phosphorus supply from parent material weathering as the primary causes for the inadequate performance of the default SWATmore » model in simulating forest dynamics. By further revising the relevant parameters and processes, SWAT’s performance is substantially improved. Based on the comparison between the improved SWAT simulations and flux tower observations, we discuss future research directions for further enhancing model parameterization and representation of water and carbon cycling for forests.« less

Explaining biomass growth of tropical canopy trees: the importance of sapwood.

PubMed

van der Sande, Masha T; Zuidema, Pieter A; Sterck, Frank

2015-04-01

Tropical forests are important in worldwide carbon (C) storage and sequestration. C sequestration of these forests may especially be determined by the growth of canopy trees. However, the factors driving variation in growth among such large individuals remain largely unclear. We evaluate how crown traits [total leaf area, specific leaf area and leaf nitrogen (N) concentration] and stem traits [sapwood area (SA) and sapwood N concentration] measured for individual trees affect absolute biomass growth for 43 tropical canopy trees belonging to four species, in a moist forest in Bolivia. Biomass growth varied strongly among trees, between 17.3 and 367.3 kg year(-1), with an average of 105.4 kg year(-1). We found that variation in biomass growth was chiefly explained by a positive effect of SA, and not by tree size or other traits examined. SA itself was positively associated with sapwood growth, sapwood lifespan and basal area. We speculate that SA positively affects the growth of individual trees mainly by increasing water storage, thus securing water supply to the crown. These positive roles of sapwood on growth apparently offset the increased respiration costs incurred by more sapwood. This is one of the first individual-based studies to show that variation in sapwood traits-and not crown traits-explains variation in growth among tropical canopy trees. Accurate predictions of C dynamics in tropical forests require similar studies on biomass growth of individual trees as well as studies evaluating the dual effect of sapwood (water provision vs. respiratory costs) on tropical tree growth.

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

NASA Astrophysics Data System (ADS)

Takayama, T.; Iwasaki, A.

2016-06-01

Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE) of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.

Characterizing Tropical Forest Structure using Field-based Measurements and a Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Palace, M. W.; Sullivan, F.; Ducey, M. J.; Herrick, C.

2015-12-01

Forest structure comprises numerous quantifiable components of forest biometric characteristics, one of which is tree architecture. This structural component is important in the understanding of the past and future trajectories of these biomes. Tropical forests are often considered the most structurally complex and yet least understood of forested ecosystems. New technologies have provided novel avenues for quantifying properties of forested ecosystems, one of which is LIght Detection And Ranging (lidar). This sensor can be deployed on satellite, aircraft, unmanned aerial vehicles, and terrestrial platforms. In this study we examined the efficacy of a terrestrial lidar scanner (TLS) system in a tropical forest to estimate forest structure. Our study was conducted in January 2012 at La Selva, Costa Rica at twenty locations in predominantly undisturbed forest. At these locations we collected field measured biometric attributes using a variable plot design. We also collected TLS data from the center of each plot. Using this data we developed relative vegetation profiles (RVPs) and calculated a series of parameters including entropy, FFT, number of layers and plant area index to develop statistical relationships with field data. We developed statistical models using multiple linear regressions, all of which converged on statistically significant relationships with the strongest relationship being for mean crown depth (r2 = 0.87, p < 0.01, RMSE = 1.1 m). Tree density was found to have the least strong statistical relationship (r2 = 0.45, p < 0.01, RMSE = 160.7 n ha-1). We found significant relationship between basal area and lidar metrics (r2 = 0.76, p < 0.001, RMSE = 3.68 number ha-1). Models developed for biomass 1 had a higher r-squared value and lower RMSE than that of biomass2 (biomass1: r2 = 0.7, p < 0.01, RMSE = 28.94 Mg ha-1; biomass2: r2 = 0.67, p < 0.01, RMSE = 40.62 Mg ha-1). Parameters selected in our models varied, thus indicating the potential relevance of multiple features in canopy profiles and geometry that are related to field-measured structure. Our work indicates that TLS data can provide useful information on tropical forest structure.

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. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system

Treesearch

Kristofer D. Johnson; Richard Birdsey; Andrew O Finley; Anu Swantaran; Ralph Dubayah; Craig Wayson; Rachel Riemann

2014-01-01

Forest Inventory and Analysis (FIA) data may be a valuable component of a LIDAR-based carbon monitoring system, but integration of the two observation systems is not without challenges. To explore integration methods, two wall-to-wall LIDAR-derived biomass maps were compared to FIA data at both the plot and county levels in Anne Arundel and Howard Counties in Maryland...

Estimation of the Above Ground Biomass of Tropical Forests using Polarimetric and Tomographic SAR Data Acquired at P Band and 3-D Imaging Techniques

NASA Astrophysics Data System (ADS)

Ferro-Famil, L.; El Hajj Chehade, B.; Ho Tong Minh, D.; Tebaldini, S.; LE Toan, T.

2016-12-01

Developing and improving methods to monitor forest biomass in space and time is a timely challenge, especially for tropical forests, for which SAR imaging at larger wavelength presents an interesting potential. Nevertheless, directly estimating tropical forest biomass from classical 2-D SAR images may reveal a very complex and ill-conditioned problem, since a SAR echo is composed of numerous contributions, whose features and importance depend on many geophysical parameters, such has ground humidity, roughness, topography… that are not related to biomass. Recent studies showed that SAR modes of diversity, i.e. polarimetric intensity ratios or interferometric phase centers, do not fully resolve this under-determined problem, whereas Pol-InSAR tree height estimates may be related to biomass through allometric relationships, with, in general over tropical forests, significant levels of uncertainty and lack of robustness. In this context, 3-D imaging using SAR tomography represents an appealing solution at larger wavelengths, for which wave penetration properties ensures a high quality mapping of a tropical forest reflectivity in the vertical direction. This paper presents a series of studies led, in the frame of the preparation of the next ESA mission BIOMASS, on the estimation of biomass over a tropical forest in French Guiana, using Polarimetric SAR Tomographic (Pol-TomSAR) data acquired at P band by ONERA. It is then shown that Pol-TomoSAR significantly improves the retrieval of forest above ground biomass (AGB) in a high biomass forest (200 up to 500 t/ha), with an error of only 10% at 1.5-ha resolution using a reflectivity estimates sampled at a predetermined elevation. The robustness of this technique is tested by applying the same approach over another site, and results show a similar relationship between AGB and tomographic reflectivity over both sites. The excellent ability of Pol-TomSAR to retrieve both canopy top heights and ground topography with an error of the order of 2m compared to LiDAR estimates, is then used to generalize this tomographic technique by selecting in an adaptive way the height at which reflectivity is estimated. Results indicate that this generalized techniques reduces the estimation error to values inferior to 10% and improve the representativity of the obtained AGB maps.

A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area

Treesearch

Donald Gagliasso; Susan Hummel; Hailemariam Temesgen

2014-01-01

Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...

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...

Idaho forest growth response to post-thinning energy biomass removal and complementary soil amendments

Treesearch

Lauren A. Sherman; Deborah S. Page-Dumroese; Mark D. Coleman

2018-01-01

Utilization of woody biomass for biofuel can help meet the need for renewable energy production. However, there is a concern biomass removal will deplete soil nutrients, having short- and long-term effects on tree growth. This study aimed to develop short-term indicators to assess the impacts of the first three years after small-diameter woody biomass removal on forest...

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...

Forest biomass sustainability and availability

Treesearch

K.E. Skog; John Stanturf

2011-01-01

This chapter provides a synthesis of information on potential supply of forest biomass given needs for sustainable development of forestry. Sustainability includes maintenance of water supply, biodiversity, and carbon storage as well as timber products, community development, and recreation. Biomass removals can reduce fire hazard and insect and disease attack, restore...

77 FR 10718 - Request for Proposals: 2012 Hazardous Fuels Woody Biomass Utilization Grant Program

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-23

... DEPARTMENT OF AGRICULTURE Forest Service Request for Proposals: 2012 Hazardous Fuels Woody Biomass Utilization Grant Program AGENCY: Forest Service, USDA. ACTION: Notice; Correction. SUMMARY: The Department of... Biomass Coordinator as listed in the addresses above or contact Susan LeVan-Green, Program Manager of the...

Bioenergy production and forest landscape change in the southeastern United States

USGS Publications Warehouse

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

2016-01-01

Production of woody biomass for bioenergy, whether wood pellets or liquid biofuels, has the potential to cause substantial landscape change and concomitant effects on forest ecosystems, but the landscape effects of alternative production scenarios have not been fully assessed. We simulated landscape change from 2010 to 2050 under five scenarios of woody biomass production for wood pellets and liquid biofuels in North Carolina, in the southeastern United States, a region that is a substantial producer of wood biomass for bioenergy and contains high biodiversity. Modeled scenarios varied biomass feedstocks, incorporating harvest of ‘conventional’ forests, which include naturally regenerating as well as planted forests that exist on the landscape even without bioenergy production, as well as purpose-grown woody crops grown on marginal lands. Results reveal trade-offs among scenarios in terms of overall forest area and the characteristics of the remaining forest in 2050. Meeting demand for biomass from conventional forests resulted in more total forest land compared with a baseline, business-as-usual scenario. However, the remaining forest was composed of more intensively managed forest and less of the bottomland hardwood and longleaf pine habitats that support biodiversity. Converting marginal forest to purpose-grown crops reduced forest area, but the remaining forest contained more of the critical habitats for biodiversity. Conversion of marginal agricultural lands to purpose-grown crops resulted in smaller differences from the baseline scenario in terms of forest area and the characteristics of remaining forest habitats. Each scenario affected the dominant type of land-use change in some regions, especially in the coastal plain that harbors high levels of biodiversity. Our results demonstrate the complex landscape effects of alternative bioenergy scenarios, highlight that the regions most likely to be affected by bioenergy production are also critical for biodiversity, and point to the challenges associated with evaluating bioenergy sustainability.

Integration of carbon conservation into sustainable forest management using high resolution satellite imagery: A case study in Sabah, Malaysian Borneo

NASA Astrophysics Data System (ADS)

Langner, Andreas; Samejima, Hiromitsu; Ong, Robert C.; Titin, Jupiri; Kitayama, Kanehiro

2012-08-01

Conservation of tropical forests is of outstanding importance for mitigation of climate change effects and preserving biodiversity. In Borneo most of the forests are classified as permanent forest estates and are selectively logged using conventional logging techniques causing high damage to the forest ecosystems. Incorporation of sustainable forest management into climate change mitigation measures such as Reducing Emissions from Deforestation and Forest Degradation (REDD+) can help to avert further forest degradation by synergizing sustainable timber production with the conservation of biodiversity. In order to evaluate the efficiency of such initiatives, monitoring methods for forest degradation and above-ground biomass in tropical forests are urgently needed. In this study we developed an index using Landsat satellite data to describe the crown cover condition of lowland mixed dipterocarp forests. We showed that this index combined with field data can be used to estimate above-ground biomass using a regression model in two permanent forest estates in Sabah, Malaysian Borneo. Tangkulap represented a conventionally logged forest estate while Deramakot has been managed in accordance with sustainable forestry principles. The results revealed that conventional logging techniques used in Tangkulap during 1991 and 2000 decreased the above-ground biomass by an annual amount of average -6.0 t C/ha (-5.2 to -7.0 t C/ha, 95% confidential interval) whereas the biomass in Deramakot increased by 6.1 t C/ha per year (5.3-7.2 t C/ha, 95% confidential interval) between 2000 and 2007 while under sustainable forest management. This indicates that sustainable forest management with reduced-impact logging helps to protect above-ground biomass. In absolute terms, a conservative amount of 10.5 t C/ha per year, as documented using the methodology developed in this study, can be attributed to the different management systems, which will be of interest when implementing REDD+ that rewards the enhancement of carbon stocks.

Earth science research

NASA Technical Reports Server (NTRS)

Botkin, Daniel B.

1987-01-01

The analysis of ground-truth data from the boreal forest plots in the Superior National Forest, Minnesota, was completed. Development of statistical methods was completed for dimension analysis (equations to estimate the biomass of trees from measurements of diameter and height). The dimension-analysis equations were applied to the data obtained from ground-truth plots, to estimate the biomass. Classification and analyses of remote sensing images of the Superior National Forest were done as a test of the technique to determine forest biomass and ecological state by remote sensing. Data was archived on diskette and tape and transferred to UCSB to be used in subsequent research.

Using airborne light detection and ranging as a sampling tool for estimating forest biomass resources in the upper Tanana Valley of interior Alaska

Treesearch

Hans-Erik Andersen; Jacob Strunk; Hailemariam Temesgen

2011-01-01

Airborne laser scanning, collected in a sampling mode, has the potential to be a valuable tool for estimating the biomass resources available to support bioenergy production in rural communities of interior Alaska. In this study, we present a methodology for estimating forest biomass over a 201,226-ha area (of which 163,913 ha are forested) in the upper Tanana valley...

VARIABILITY IN NET PRIMARY PRODUCTION AND CARBON STORAGE IN BIOMASS ACROSS OREGON FORESTS - AN ASSESSMENT INTEGRATING DATA FROM FOREST INVENTORIES, INTENSIVE SITES, AND REMOTE SENSING. (R828309)

EPA Science Inventory

We used a combination of data from USDA Forest Service inventories, intensive
chronosequences, extensive sites, and satellite remote sensing, to estimate biomass
and net primary production (NPP) for the forested region of western Oregon. The
study area was divided int...

Aquatic invertebrate abundance and biomass in Arkansas, Mississippi, and Missouri bottomland hardwood forests during winter

Treesearch

Justyn R. Foth; Jacob N. Straub; Richard M. Kaminski; J. Brian Davis; Theodor D. Leininger

2014-01-01

The Mississippi Alluvial Valley once had extensive bottomland hardwood forests, but less than 25% of the original area remains. Impounded bottomland hardwood forests, or greentree reservoirs, and naturally flooded forests are important sources of invertebrate or other prey for waterfowl, but no previous studies of invertebrate abundance and biomass have been at the...

Forest biomass as an energy source

Treesearch

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

1979-01-01

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

Deriving biomass models for small-diameter loblolly pine on the Crossett Experimental Forest

Treesearch

K.M. McElligott; D.C. Bragg

2013-01-01

Foresters and landowners have a growing interest in carbon sequestration and cellulosic biofuels in southern pine forests, and hence need to be able to accurately predict them. To this end, we derived a set of aboveground biomass models using data from 62 small-diameter loblolly pines (Pinus taeda) sampled on the Crossett Experimental Forest in...

Integration of Remote Sensing Products with Ground-Based Measurements to Understand the Dynamics of Nepal's Forests and Plantation Sites

NASA Astrophysics Data System (ADS)

Gilani, H.; Jain, A. K.

2016-12-01

This study assembles information from three sources - remote sensing, terrestrial photography and ground-based inventory data, to understand the dynamics of Nepal's tropical and sub-tropical forests and plantation sites for the period 1990-2015. Our study focuses on following three specific district areas, which have conserved forests through social and agroforestry management practices: 1. Dolakha district: This site has been selected to study the impact of community-based forest management on land cover change using repeat photography and satellite imagery, in combination with interviews with community members. The study time period is during the period 1990-2010. We determined that satellite data with ground photographs can provide transparency for long term monitoring. The initial results also suggests that community-based forest management program in the mid-hills of Nepal was successful. 2. Chitwan district: Here we use high resolution remote sensing data and optimized community field inventories to evaluate potential application and operational feasibility of community level REDD+ measuring, reporting and verification (MRV) systems. The study uses temporal dynamics of land cover transitions, tree canopy size classes and biomass over a Kayar khola watershed REDD+ study area with community forest to evaluate satellite Image segmentation for land cover, linear regression model for above ground biomass (AGB), and estimation and monitoring field data for tree crowns and AGB. We study three specific years 2002, 2009, 2012. Using integration of WorldView-2 and airborne LiDAR data for tree species level. 3. Nuwakot district: This district was selected to study the impact of establishment of tree plantation on total barren/fallow. Over the last 40 year, this area has went through a drastic changes, from barren land to forest area with tree species consisting of Dalbergia sissoo, Leucaena leucocephala, Michelia champaca, etc. In 1994, this district area was registered and established to grow and process high quality trees shaded of Arabica coffee beans. Here we use temporal satellite images and repeat terrestrial and aerial photographs, along with plot level biomass to show impact of this positive transformation of the landscape on above and below ground carbon masses. The study time period is 1990-2015.

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.

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

PubMed

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

2015-05-01

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

Growing stock and woody biomass assessment in Asola-Bhatti Wildlife Sanctuary, Delhi, India.

PubMed

Kushwaha, S P S; Nandy, S; Gupta, Mohini

2014-09-01

Biomass is an important entity to understand the capacity of an ecosystem to sequester and accumulate carbon over time. The present study, done in collaboration with the Delhi Forest Department, focused on the estimation of growing stock and the woody biomass in the so-called lungs of Delhi--the Asola-Bhatti Wildlife Sanctuary in northern Aravalli hills. The satellite-derived vegetation strata were field-inventoried using stratified random sampling procedure. Growing stock was calculated for the individual sample plots using field data and species-specific volume equations. Biomass was estimated from the growing stock and the specific gravity of the wood. Among the four vegetation types, viz. Prosopis juliflora, Anogeissus pendula, forest plantation and the scrub, the P. juliflora was found to be the dominant vegetation in the area, covering 23.43 km(2) of the total area. The study revealed that P. juliflora forest with moderate density had the highest (10.7 m(3)/ha) while A. pendula forest with moderate density had the lowest (3.6 m(3)/ha) mean volume. The mean woody biomass was also found to be maximum in P. juliflora forest with moderate density (10.3 t/ha) and lowest in A. pendula forest with moderate density (3.48 t/ha). The total growing stock was estimated to be 20,772.95 m(3) while total biomass worked out to be 19,366.83 t. A strong correlation was noticed between the normalized difference vegetation index (NDVI) and the growing stock (R(2) = 0.84)/biomass (R(2) = 0.88). The study demonstrated that growing stock and the biomass of the woody vegetation in Asola-Bhatti Wildlife Sanctuary could be estimated with high accuracy using optical remote sensing data.

[Effects of altitudes on soil microbial biomass and enzyme activity in alpine-gorge regions.

PubMed

Cao, Rui; Wu, Fu Zhong; Yang, Wan Qin; Xu, Zhen Feng; Tani, Bo; Wang, Bin; Li, Jun; Chang, Chen Hui

2016-04-22

In order to understand the variations of soil microbial biomass and soil enzyme activities with the change of altitude, a field incubation was conducted in dry valley, ecotone between dry valley and mountain forest, subalpine coniferous forest, alpine forest and alpine meadow from 1563 m to 3994 m of altitude in the alpine-gorge region of western Sichuan. The microbial biomass carbon and nitrogen, and the activities of invertase, urease and acid phosphorus were measured in both soil organic layer and mineral soil layer. Both the soil microbial biomass and soil enzyme activities showed the similar tendency in soil organic layer. They increased from 2158 m to 3028 m, then decreased to the lowest value at 3593 m, and thereafter increased until 3994 m in the alpine-gorge region. In contrast, the soil microbial biomass and soil enzyme activities in mineral soil layer showed the trends as, the subalpine forest at 3028 m > alpine meadow at 3994 m > montane forest ecotone at 2158 m > alpine forest at 3593 m > dry valley at 1563 m. Regardless of altitudes, soil microbial biomass and soil enzyme activities were significantly higher in soil organic layer than in mineral soil layer. The soil microbial biomass was significantly positively correlated with the activities of the measured soil enzymes. Moreover, both the soil microbial biomass and soil enzyme activities were significantly positively correlated with soil water content, organic carbon, and total nitrogen. The activity of soil invertase was significantly positively correlated with soil phosphorus content, and the soil acid phosphatase was so with soil phosphorus content and soil temperature. In brief, changes in vegetation and other environmental factors resulting from altitude change might have strong effects on soil biochemical properties in the alpine-gorge region.

Small Sample Sizes Yield Biased Allometric Equations in Temperate Forests

PubMed Central

Duncanson, L.; Rourke, O.; Dubayah, R.

2015-01-01

Accurate quantification of forest carbon stocks is required for constraining the global carbon cycle and its impacts on climate. The accuracies of forest biomass maps are inherently dependent on the accuracy of the field biomass estimates used to calibrate models, which are generated with allometric equations. Here, we provide a quantitative assessment of the sensitivity of allometric parameters to sample size in temperate forests, focusing on the allometric relationship between tree height and crown radius. We use LiDAR remote sensing to isolate between 10,000 to more than 1,000,000 tree height and crown radius measurements per site in six U.S. forests. We find that fitted allometric parameters are highly sensitive to sample size, producing systematic overestimates of height. We extend our analysis to biomass through the application of empirical relationships from the literature, and show that given the small sample sizes used in common allometric equations for biomass, the average site-level biomass bias is ~+70% with a standard deviation of 71%, ranging from −4% to +193%. These findings underscore the importance of increasing the sample sizes used for allometric equation generation. PMID:26598233

A Model-Data Intercomparison of Carbon Fluxes, Pools, and LAI in the Community Land Model (CLM) and Alternative Carbon Allocation Schemes

NASA Astrophysics Data System (ADS)

Montane, F.; Fox, A. M.; Arellano, A. F.; Alexander, M. R.; Moore, D. J.

2016-12-01

Carbon (C) allocation to different plant tissues (leaves, stem and roots) remains a central challenge for understanding the global C cycle, as it determines C residence time. We used a diverse set of observations (AmeriFlux eddy covariance towers, biomass estimates from tree-ring data, and Leaf Area Index measurements) to compare C fluxes, pools, and Leaf Area Index (LAI) data with the Community Land Model (CLM). We ran CLM for seven temperate forests in North America (including evergreen and deciduous sites) between 1980 and 2013 using different C allocation schemes: i) standard C allocation scheme in CLM, which allocates C to the stem and leaves as a dynamic function of annual net primary productivity (NPP); ii) two fixed C allocation schemes, one representative of evergreen and the other one of deciduous forests, based on Luyssaert et al. 2007; iii) an alternative C allocation scheme, which allocated C to stem and leaves, and to stem and coarse roots, as a dynamic function of annual NPP, based on Litton et al. 2007. At our sites CLM usually overestimated gross primary production and ecosystem respiration, and underestimated net ecosystem exchange. Initial aboveground biomass in 1980 was largely overestimated for deciduous forests, whereas aboveground biomass accumulation between 1980 and 2011 was highly underestimated for both evergreen and deciduous sites due to the lower turnover rate in the sites than the one used in the model. CLM overestimated LAI in both evergreen and deciduous sites because the Leaf C-LAI relationship in the model did not match the observed Leaf C-LAI relationship in our sites. Although the different C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, one of the alternative C allocation schemes used (iii) gave more realistic stem C/leaf C ratios, and highly reduced the overestimation of initial aboveground biomass, and accumulated aboveground NPP for deciduous forests by CLM. Our results would suggest using different C allocation schemes for evergreen and deciduous forests. It is crucial to improve CLM in the near future to minimize data-model mismatches, and to address some of the current model structural errors and parameter uncertainties.

Environmental correlates underlying elevational richness, abundance, and biomass patterns of multi-feeding guilds in litter invertebrates across the treeline.

PubMed

Xu, Guorui; Zhang, Shuang; Zhang, Yuxin; Ma, Keming

2018-08-15

Elevational richness patterns and underlying environmental correlates have contributed greatly to a range of general theories of biodiversity. However, the mechanisms underlying elevational abundance and biomass patterns across several trophic levels in belowground food webs remain largely unknown. In this study, we aimed to disentangle the relationships between the elevational patterns of different trophic levels of litter invertebrates and their underlying environmental correlates for two contrasting ecosystems separated by the treeline. We sampled 119 plots from 1020 to 1770 asl in forest and 21 plots from 1790 to 2280 asl in meadow on Dongling Mountain, northwest of Beijing, China. Four functional guilds were divided based on feeding regime: omnivores, herbivores, predators, and detritivores. We used eigenvector-based spatial filters to account for spatial autocorrelation and multi-model selection to determine the best environmental correlates for the community attributes of the different feeding guilds. The results showed that the richness, abundance and biomass of omnivores declined with increasing elevation in the meadow, whereas there was a hump-shaped richness pattern for detritivores. The richness and abundance of different feeding guilds were positively correlated in the forest, while not in the meadow. In the forest, the variances of richness in omnivores, predators, and detritivores were mostly correlated with litter thickness, with omnivores being best explained by mean annual temperature in the meadow. In conclusion, hump-shaped elevational richness, abundance and biomass patterns driven by the forest gradient below the treeline existed in all feeding guilds of litter invertebrates. Climate replaced productivity as the primary factor that drove the richness patterns of omnivores above the treeline, whereas heterogeneity replaced climate for herbivores. Our results highlight that the correlated elevational richness, abundance, and biomass patterns of feeding guilds are ecosystem-dependent and that the underlying environmental correlates shifted at the treeline for most feeding guilds. Copyright © 2018 Elsevier B.V. All rights reserved.

Overview of the Fire Lab at Missoula Experiments (FLAME)

Treesearch

S. M. Kreidenweis; J. L. Collett; H. Moosmuller; W. P. Arnott; WeiMin Hao; W. C. Malm

2010-01-01

The Fire Lab at Missoula Experiments (FLAME) used a series of open biomass burns, conducted in 2006 and 2007 at the Forest Service Fire Science Laboratory in Missoula, MT, to characterize the physical, chemical and optical properties of biomass combustion emissions. Fuels were selected primarily based on their projected importance for emissions from prescribed and wild...

Specific gravity and other properties of wood and bark for 156 tree species found in North America

Treesearch

Patrick D. Miles

2009-01-01

This paper reports information for the estimation of biomass for 156 tree species found in North America for use in national forest inventory applications. We present specific gravities based on average green volume as well as 12 percent moisture content volume for calculation of oven-dry biomass....

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...

Estimating forest biomass and identifying low-intensity logging areas using airborne scanning lidar in Antimary State Forest, Acre State, Western Brazilian Amazon

Treesearch

Marcus V.N. d' Oliveira; Stephen E. Reutebuch; Robert J. McGaughey; Hans-Erik. Andersen

2012-01-01

The objectives of this study were to estimate above ground forest biomass and identify areas disturbed by selective logging in a 1000 ha Brazilian tropical forest in the Antimary State Forest using airborne lidar data. The study area consisted of three management units, two of which were unlogged, while the third unit was selectively logged at a low intensity. A...

Forest Resources

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

None

2016-06-01

Forest biomass is an abundant biomass feedstock that complements the conventional forest use of wood for paper and wood materials. It may be utilized for bioenergy production, such as heat and electricity, as well as for biofuels and a variety of bioproducts, such as industrial chemicals, textiles, and other renewable materials. The resources within the 2016 Billion-Ton Report include primary forest resources, which are taken directly from timberland-only forests, removed from the land, and taken to the roadside.

Estimating tropical-forest density profiles from multibaseline interferometric SAR

NASA Technical Reports Server (NTRS)

Treuhaft, Robert; Chapman, Bruce; dos Santos, Joao Roberto; Dutra, Luciano; Goncalves, Fabio; da Costa Freitas, Corina; Mura, Jose Claudio; de Alencastro Graca, Paulo Mauricio

2006-01-01

Vertical profiles of forest density are potentially robust indicators of forest biomass, fire susceptibility and ecosystem function. Tropical forests, which are among the most dense and complicated targets for remote sensing, contain about 45% of the world's biomass. Remote sensing of tropical forest structure is therefore an important component to global biomass and carbon monitoring. This paper shows preliminary results of a multibasline interfereomtric SAR (InSAR) experiment over primary, secondary, and selectively logged forests at La Selva Biological Station in Costa Rica. The profile shown results from inverse Fourier transforming 8 of the 18 baselines acquired. A profile is shown compared to lidar and field measurements. Results are highly preliminary and for qualitative assessment only. Parameter estimation will eventually replace Fourier inversion as the means to producing profiles.

The GEDI Strategy for Improved Mapping of Forest Biomass and Structure

NASA Astrophysics Data System (ADS)

Dubayah, R.

2017-12-01

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

Roots and the stability of forested slopes

Treesearch

R. R. Ziemer

1981-01-01

Abstract - Root decay after timber cutting can lead to slope failure. In situ measurements of soil with tree roots showed that soil strength increased linearly as root biomass increased. Forests clear-felled 3 years earlier contained about one-third of the root biomass of old-growth forests. Nearly all of the roots

Allocation strategies of savanna and forest tree seedlings in response to fire and shading: outcomes of a field experiment

NASA Astrophysics Data System (ADS)

Gignoux, Jacques; Konaté, Souleymane; Lahoreau, Gaëlle; Le Roux, Xavier; Simioni, Guillaume

2016-12-01

The forest-savanna ecotone may be very sharp in fire-prone areas. Fire and competition for light play key roles in its maintenance, as forest and savanna tree seedlings are quickly excluded from the other ecosystem. We hypothesized a tradeoff between seedling traits linked to fire resistance and to competition for light to explain these exclusions. We compared growth- and survival-related traits of two savanna and two forest species in response to shading and fire in a field experiment. To interpret the results, we decomposed our broad hypothesis into elementary tradeoffs linked to three constraints, biomass allocation, plant architecture, and shade tolerance, that characterize both savanna and adjacent forest ecosystems. All seedlings reached similar biomasses, but forest seedlings grew taller. Savanna seedlings better survived fire after topkill and required ten times less biomass than forest seedlings to survive. Finally, only savanna seedlings responded to shading. Although results were consistent with the classification of our species as mostly adapted to shade tolerance, competition for light in the open, and fire tolerance, they raised new questions: how could savanna seedlings survive better with a 10-times lower biomass than forest seedlings? Is their shade intolerance sufficient to exclude them from forest understory?

Energy from wood biomass: The experience of the Brazilian forest sector

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

Couto, L.; Graca, L.R.; Betters, D.R.

Wood biomass is one of the most significant renewable sources of energy in Brazil. Fuelwood and charcoal play a very important role not only for household energy consumption but also for the cement, iron and steel industries. Wood is used as an energy source by the pulp and paper, composite board and other industries of the country, mainly for steam and electricity generation. Ethanol, lignin-based coke and methanol from wood were produced at experimental units in Brazil but were not implemented on a commercial scale. Currently, a new experimental plant using a technology developed in the US is being builtmore » in the state of Bahia to generate electricity from Eucalyptus. This technology is a Biomass Integrated Gasification/Gas Turbine process which is expected to make the use of wood biomass economically feasible for electricity generation. Forest plantations are the main source of wood biomass for energy consumption by the Brazilian industrial sector. Fiscal incentives in the 1960s helped the country to begin a massive reforestation program mainly using Eucalyptus and Pinus species. A native species, bracatinga (Mimosa scabrella) has also been used extensively for wood energy plantations in southern Brazil. Technical, economic, social and environmental impacts of these plantation forests are discussed along with a forecast of the future wood energy utilization in Brazil.« less

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

PubMed

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

2014-01-01

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

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

PubMed Central

Wang, Xiaoke; Ren, Yin

2014-01-01

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

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

Treesearch

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

2009-01-01

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

Ozone exposure and nitrogen deposition lowers root biomass of ponderosa pine in the San Bernardino Mountains, California

Treesearch

Nancy Grulke; C.P. Andersen; M.E. Fenn; P.R. Miller

1998-01-01

Decreased root biomass in forest trees in response to anthropogenic pollutants is believed to be one of the first steps in forest health degradation. Although decreased root biomass has been observed in controlled experiments, ozone eff€ects on mature tree roots in natural stands has not previously been documented. Here we report standing root biomass of ponderosa pine...

Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-fooprint lidar data

Treesearch

Yunsuk Kim; Zhiqiang Yang; Warren B. Cohen; Dirk Pflugmacher; Chris L. Lauver; John L. Vankat

2009-01-01

Accurate estimation of live and dead biomass in forested ecosystems is important for studies of carbon dynamics, biodiversity, wildfire behavior, and for forest management. Lidar remote sensing has been used successfully to estimate live biomass, but studies focusing on dead biomass are rare. We used lidar data, in conjunction with field measurements from 58 plots to...

Lidar-based multinomial classification algorithms for tropical forest degradation status: Implications for biomass estimation

NASA Astrophysics Data System (ADS)

Duffy, P.; Keller, M.; Longo, M.; Morton, D. C.; dos-Santos, M. N.; Pinagé, E. R.

2017-12-01

There is an urgent need to quantify the effects of land use and land cover change on carbon stocks in tropical forests to support REDD+ policies and improve characterization of global carbon budgets. This need is underscored by the fact that the variability in forest biomass estimates from global forest carbon maps is artificially low relative to estimates generated from forest inventory and high-resolution airborne lidar data. Both deforestation and degradation processes (e.g. logging, fire, and fragmentation) affect carbon fluxes at varying spatial and temporal scales. While the spatial extent and impact of deforestation has been relatively well characterized, the quantification of degradation processes is still poorly constrained. In the Brazilian Amazon, the largest source of uncertainty in CO2 emissions estimates is data on changes in tropical forest carbon stocks through time, followed closely by incomplete information on the carbon losses from forest degradation. In this work, we present a method for classifying the degradation status of tropical forests using higher order moments (skewness and kurtosis) of lidar return distributions aggregated at grids with resolution ranging from 50 m to 250 m. Across multiple spatial resolutions, we quantify the strength of the functional relationship between the lidar returns and the classification based on historical time series of Landsat imagery. Our results show that the higher order moments of the lidar return distributions provide sufficient information to build multinomial models that accurately classify the landscape into intact, logged, and burned forests. Model fit improved with coarser spatial resolution with Kappa statistics of 0.70 at 50 m, and 0.77 at 250 m. In addition, multi-class AUC was estimated as 0.87 at 50 m, and 0.95 at 250 m. This classification provides important information regarding the applicability of the use of lidar data for regional monitoring of recent logging, as well as the trajectory of the carbon budget. Differentiating between the biomass changes associated with deforestation and degradation processes is critical for accurate accounting of disturbance impacts on carbon cycling within the Brazilian Amazon and global tropical forests.

Changes in Amazonian forest biomass, dynamics, and composition, 1980-2002

NASA Astrophysics Data System (ADS)

Phillips, Oliver L.; Higuchi, Niro; Vieira, Simone; Baker, Timothy R.; Chao, Kuo-Jung; Lewis, Simon L.

Long-term, on-the-ground monitoring of forest plots distributed across Amazonia provides a powerful means to quantify stocks and fluxes of biomass and biodiversity. Here we examine the evidence for concerted changes in the structure, dynamics, and functional composition of old-growth Amazonian forests over recent decades. Mature forests have, as a whole, gained biomass and undergone accelerated growth and dynamics, but questions remain as to the long-term persistence of these changes. Because forest growth on average exceeds mortality, intact Amazonian forests have been functioning as a carbon sink. We estimate a net biomass increase in trees ≥10 cm diameter of 0.62 ± 0.23 t C ha-1 a-1 through the late twentieth century. If representative of the wider forest landscape, this translates into a sink in South American old-growth forest of at least 0.49 ± 0.18 Pg C a-1. If other biomass and necromass components also increased proportionally, the estimated South American old-growth forest sink is 0.79 ± 0.29 Pg C a-1, before allowing for possible gains in soil carbon. If tropical forests elsewhere are behaving similarly, the old-growth biomass forest sink would be 1.60 ± 0.58 Pg C a-1. This bottom-up estimate of the carbon balance of tropical forests is preliminary, pending syntheses of detailed biometric studies across the other tropical continents. There is also some evidence for recent changes in the functional composition (biodiversity) of Amazonian forest, but the evidence is less comprehensive than that for changes in structure and dynamics. The most likely driver(s) of changes are recent increases in the supply of resources such as atmospheric carbon dioxide, which would increase net primary productivity, increasing tree growth and recruitment, and, in turn, mortality. In the future the growth response of remaining undisturbed Amazonian forests is likely to saturate, and there is a risk of these ecosystems transitioning from sink to source driven by higher respiration (temperature), higher mortality (drought), or compositional change (functional shifts toward lighterwooded plants). Even a modest switch from carbon sink to source for Amazonian forests would impact global climate, biodiversity, and human welfare, while the documented acceleration of tree growth and mortality may already be affecting the interactions of thousands of plant and millions of animal species.

Effects of nutrient additions on ecosystem carbon cycle in a Puerto Rican tropical wet forest

Treesearch

YIQING LI; MING XU; XIAOMING ZOU

2006-01-01

Wet tropical forests play a critical role in global ecosystem carbon (C) cycle, but C allocation and the response of different C pools to nutrient addition in these forests remain poorly understood. We measured soil organic carbon (SOC), litterfall, root biomass, microbial biomass and soil physical and chemical properties in a wet tropical forest from May 1996 to July...

Predicting live and dead tree basal area of bark beetle affected forests from discrete-return lidar

Treesearch

Benjamin C. Bright; Andrew T. Hudak; Robert McGaughey; Hans-Erik Andersen; Jose Negron

2013-01-01

Bark beetle outbreaks have killed large numbers of trees across North America in recent years. Lidar remote sensing can be used to effectively estimate forest biomass, but prediction of both live and dead standing biomass in beetle-affected forests using lidar alone has not been demonstrated. We developed Random Forest (RF) models predicting total, live, dead, and...

Trends in standing biomass in Interior West forests: Reassessing baseline data from periodic inventories

Treesearch

Sara A. Goeking

2012-01-01

Trends in U.S. forest biomass and carbon are assessed using Forest Inventory and Analysis (FIA) data relative to baseline assessments from the 1990s. The integrity of baseline data varies by state and depends largely on the comparability of periodic versus annual forest inventory data. In most states in the Interior West FIA region, the periodic inventory's sample...

First Assessment of Carbon Stock in the Belowground Biomass of Brazilian Mangroves.

PubMed

Santos, Daniel M C; Estrada, Gustavo C D; Fernandez, Viviane; Estevam, Marciel R M; Souza, Brunna T DE; Soares, Mário L G

2017-01-01

Studies on belowground roots biomass have increasingly reported the importance of the contribution of this compartment in carbon stock maintenance in mangrove forests. To date, there are no estimates of this contribution in Brazilian mangrove forests, although the country has the second largest area of mangroves worldwide. For this study, trenches dug in fringing forests in Guaratiba State Biological Reserve (Rio de Janeiro, Brazil) were used to evaluate the contribution of the different classes of roots and the vertical stratification of carbon stock. The total carbon stock average in belowground roots biomass in these forests was 104.41 ± 20.73 tC.ha-1. From that, an average of 84.13 ± 21.34 tC.ha-1 corresponded to the carbon stock only in fine roots, which have diameters smaller than 5 mm and are responsible for over 80% of the total belowground biomass. Most of the belowground carbon stock is concentrated in the first 40 cm below the surface (about 70%). The root:shoot ratio in this study is 1.14. These estimates demonstrate that the belowground roots biomass significantly contributes, more than 50%, to the carbon stock in mangrove forests. And the mangrove root biomass can be greater than that of other Brazilian ecosystems.

Nutrient limitation in three lowland tropical forests in southern China receiving high nitrogen deposition: insights from fine root responses to nutrient additions.

PubMed

Zhu, Feifei; Yoh, Muneoki; Gilliam, Frank S; Lu, Xiankai; Mo, Jiangming

2013-01-01

Elevated nitrogen (N) deposition to tropical forests may accelerate ecosystem phosphorus (P) limitation. This study examined responses of fine root biomass, nutrient concentrations, and acid phosphatase activity (APA) of bulk soil to five years of N and P additions in one old-growth and two younger lowland tropical forests in southern China. The old-growth forest had higher N capital than the two younger forests from long-term N accumulation. From February 2007 to July 2012, four experimental treatments were established at the following levels: Control, N-addition (150 kg N ha(-1) yr(-1)), P-addition (150 kg P ha(-1) yr(-1)) and N+P-addition (150 kg N ha(-1) yr(-1) plus 150 kg P ha(-1) yr(-1)). We hypothesized that fine root growth in the N-rich old-growth forest would be limited by P availability, and in the two younger forests would primarily respond to N additions due to large plant N demand. Results showed that five years of N addition significantly decreased live fine root biomass only in the old-growth forest (by 31%), but significantly elevated dead fine root biomass in all the three forests (by 64% to 101%), causing decreased live fine root proportion in the old-growth and the pine forests. P addition significantly increased live fine root biomass in all three forests (by 20% to 76%). The combined N and P treatment significantly increased live fine root biomass in the two younger forests but not in the old-growth forest. These results suggest that fine root growth in all three study forests appeared to be P-limited. This was further confirmed by current status of fine root N:P ratios, APA in bulk soil, and their responses to N and P treatments. Moreover, N addition significantly increased APA only in the old-growth forest, consistent with the conclusion that the old-growth forest was more P-limited than the younger forests.

Large-Scale Variation in Forest Carbon Turnover Rate and its Relation to Climate - Remote Sensing vs. Global Vegetation Models

NASA Astrophysics Data System (ADS)

Carvalhais, N.; Thurner, M.; Beer, C.; Forkel, M.; Rademacher, T. T.; Santoro, M.; Tum, M.; Schmullius, C.

2015-12-01

While vegetation productivity is known to be strongly correlated to climate, there is a need for an improved understanding of the underlying processes of vegetation carbon turnover and their importance at a global scale. This shortcoming has been due to the lack of spatially extensive information on vegetation carbon stocks, which we recently have been able to overcome by a biomass dataset covering northern boreal and temperate forests originating from radar remote sensing. Based on state-of-the-art products on biomass and NPP, we are for the first time able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests. The implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current global vegetation models. In contrast to our observation-based findings, investigated models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well to observation-based NPP, simulated vegetation carbon stocks are severely biased compared to our biomass dataset. Current limitations lead to considerable uncertainties in the estimated vegetation carbon turnover, contributing substantially to the forest feedback to climate change. Our results are the basis for improving mortality concepts in global vegetation models and estimating their impact on the land carbon balance.

Temporal variations in soil moisture content and its influence on biomass estimates, observed by UAVSAR, ALOS PALSAR, and in-situ field data

NASA Astrophysics Data System (ADS)

Calderhead, A. I.; Simard, M.; Lavalle, M.

2010-12-01

Temporal changes of repeat-pass SAR backscatter over bare ground or forests results mostly from changes in the target's dielectric properties or moisture content; especially when the timescale is on the order of a few days or weeks. It is important to properly correct for moisture content when using SAR based estimates of tree height or biomass. The objective of this work is to quantify the error in biomass estimates associated with variations in moisture content in temperate and boreal forested areas. In addition, the accuracy of three polarimetric soil moisture surface inversion models (Dubois et al., 1995, Oh et al., 1992; Oh, 2004) are tested on UAVSAR and PALSAR data of bare soils in temperate and boreal forested areas. In addition to PALSAR data from 2007 to 2009, a JPL/UAVSAR campaign over parts of New England and Quebec was completed in August, 2009; L-band SAR images were acquired on August 5th, August 7th, and August 14th. In-situ soil moisture probes at three locations gathered hourly soil moisture content data. LVIS LIDAR is used for quantifying and classifying biomass ranges. Slope corrected backscatter values resampled to 1 hectare at HH, HV, and VV polarizations, and ratios thereof, are compared with soil moisture, precipitation, biomass, and incidence angle. It is seen that the backscatter for high biomass areas varies significantly due to moisture variations. An increase in 1% soil moisture content at the Laurentides field site leads to a change in HV backscatter of 1dB. Regions with high biomass do not vary uniformly with varying moisture content: this can be explained by saturation of the L-band at higher biomass levels. The three inversion algorithms produce varying results with the ‘Dubois et al’ inversion producing the best correlation at the Bartlett Forest site while the ‘Oh 2004’ inversion produces better results at the Laurentides site. Although the accuracy is often poor, the temporal variation of the moisture content for all three inversion algorithms is generally captured.

Projection of U.S. forest sector carbon sequestration under U.S. and global timber market and wood energy consumption scenarios, 2010-2060

Treesearch

Prakash Nepal; Peter J. Ince; Kenneth E. Skog; Sun J. Chang

2012-01-01

This study provides a modeling framework to examine change over time in U.S. forest sector carbon inventory (in U.S. timberland tree biomass and harvested wood products) for alternative projections of U.S. and global timber markets, including wood energy consumption, based on established IPCC/RPA scenarios. Results indicated that the U.S. forest sector’s projected...

Biomass statistics for Maryland--1986

Treesearch

Thomas S. Frieswyk; Dawn M. DiGiovanni; Dawn M. DiGiovanni

1990-01-01

A statistical report on the fourth forest survey of Maryland (1986). Findings are displayed in 97 tables containing estimates of forest area, tree biomass, and timber volume. Data are presented by state and county level.

Creation of a Digital Surface Model and Extraction of Coarse Woody Debris from Terrestrial Laser Scans in an Open Eucalypt Woodland

NASA Astrophysics Data System (ADS)

Muir, J.; Phinn, S. R.; Armston, J.; Scarth, P.; Eyre, T.

2014-12-01

Coarse woody debris (CWD) provides important habitat for many species and plays a vital role in nutrient cycling within an ecosystem. In addition, CWD makes an important contribution to forest biomass and fuel loads. Airborne or space based remote sensing instruments typically do not detect CWD beneath the forest canopy. Terrestrial laser scanning (TLS) provides a ground based method for three-dimensional (3-D) reconstruction of surface features and CWD. This research produced a 3-D reconstruction of the ground surface and automatically classified coarse woody debris from registered TLS scans. The outputs will be used to inform the development of a site-based index for the assessment of forest condition, and quantitative assessments of biomass and fuel loads. A survey grade terrestrial laser scanner (Riegl VZ400) was used to scan 13 positions, in an open eucalypt woodland site at Karawatha Forest Park, near Brisbane, Australia. Scans were registered, and a digital surface model (DSM) produced using an intensity threshold and an iterative morphological filter. The DSMs produced from single scans were compared to the registered multi-scan point cloud using standard error metrics including: Root Mean Squared Error (RMSE), Mean Squared Error (MSE), range, absolute error and signed error. In addition the DSM was compared to a Digital Elevation Model (DEM) produced from Airborne Laser Scanning (ALS). Coarse woody debris was subsequently classified from the DSM using laser pulse properties, including: width and amplitude, as well as point spatial relationships (e.g. nearest neighbour slope vectors). Validation of the coarse woody debris classification was completed using true-colour photographs co-registered to the TLS point cloud. The volume and length of the coarse woody debris was calculated from the classified point cloud. A representative network of TLS sites will allow for up-scaling to large area assessment using airborne or space based sensors to monitor forest condition, biomass and fuel loads.

Slash and Learn: Revealing Stakeholder Knowledge, Support, and Preferred Communication Methods Relative to Wood-Based Biofuels Projects

ERIC Educational Resources Information Center

Moroney, Jillian; Laninga, Tamara; Brooks, Randall

2016-01-01

The Northwest Advanced Renewables Alliance (NARA) is examining the feasibility of a woody biomass-to-biofuels supply chain in Idaho, Montana, Oregon, and Washington. A part of the ongoing feasibility study involved conducting a survey of informed stakeholders on the use of woody biomass from forest residuals in producing sustainable bioenergy.…

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 descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies.

Examining the social acceptability of forest biomass harvesting and utilization from collaborative forest landscape restoration: A case study from western Colorado, USA

Treesearch

Jessica M. Western; Antony S. Cheng; Nathaniel M. Anderson; Pamela Motley

2017-01-01

Collaborative efforts have expanded in recent years to reduce fuel loads and restore the resilience of forest landscapes to future fires. The social acceptability of harvesting and using forest biomass associated with these programs are a hot topic, with questions about the extent to which collaboration can generate unified acceptance. We present results from a Q-...

Modeling the impacts of climate variability and hurricane on carbon sequestration in a coastal forested wetland in South Carolina

Treesearch

Zhaohua Dai; Carl C. Trettin; Changsheng Li; Ge Sun; Devendra M. Amatya; Harbin Li

2013-01-01

The impacts of hurricane disturbance and climate variability on carbon dynamics in a coastal forested wetland in South Carolina of USA were simulated using the Forest-DNDC model with a spatially explicit approach. The model was validated using the measured biomass before and after Hurricane Hugo and the biomass inventories in 2006 and 2007, showed that the Forest-DNDC...

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...

Recovery and diversity of the forest shrub community 38 years after biomass harvesting in the northern Rocky Mountains

Treesearch

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

2016-01-01

We investigated the long-term impact of biomass utilization on shrub recovery, species composition, and biodiversity 38 years after harvesting at Coram Experimental Forest in northwestern Montana. Three levels of biomass removal intensity (high, medium, and low) treatments combined with prescribed burning treatment were nested within three regeneration harvest...

Detrital carbon pools in temperate forests: magnitude and potential for landscape-scale assessment

Treesearch

John B. Bradford; Peter Weishampel; Marie-Louise Smith; Randall Kolka; Richard A. Birdsey; Scott V. Ollinger; Michael G. Ryan

2009-01-01

Reliably estimating carbon storage and cycling in detrital biomass is an obstacle to carbon accounting. We examined carbon pools and fluxes in three small temperate forest landscapes to assess the magnitude of carbon stored in detrital biomass and determine whether detrital carbon storage is related to stand structural properties (leaf area, aboveground biomass,...

Correlation analysis between forest carbon stock and spectral vegetation indices in Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam

NASA Astrophysics Data System (ADS)

Dung Nguyen, The; Kappas, Martin

2017-04-01

In the last several years, the interest in forest biomass and carbon stock estimation has increased due to its importance for forest management, modelling carbon cycle, and other ecosystem services. However, no estimates of biomass and carbon stocks of deferent forest cover types exist throughout in the Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam. This study investigates the relationship between above ground carbon stock and different vegetation indices and to identify the most likely vegetation index that best correlate with forest carbon stock. The terrestrial inventory data come from 380 sample plots that were randomly sampled. Individual tree parameters such as DBH and tree height were collected to calculate the above ground volume, biomass and carbon for different forest types. The SPOT6 2013 satellite data was used in the study to obtain five vegetation indices NDVI, RDVI, MSR, RVI, and EVI. The relationships between the forest carbon stock and vegetation indices were investigated using a multiple linear regression analysis. R-square, RMSE values and cross-validation were used to measure the strength and validate the performance of the models. The methodology presented here demonstrates the possibility of estimating forest volume, biomass and carbon stock. It can also be further improved by addressing more spectral bands data and/or elevation.

Satellite chlorophyll fluorescence measurements reveal large-scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests.

PubMed

Walther, Sophia; Voigt, Maximilian; Thum, Tea; Gonsamo, Alemu; Zhang, Yongguang; Köhler, Philipp; Jung, Martin; Varlagin, Andrej; Guanter, Luis

2016-09-01

Mid-to-high latitude forests play an important role in the terrestrial carbon cycle, but the representation of photosynthesis in boreal forests by current modelling and observational methods is still challenging. In particular, the applicability of existing satellite-based proxies of greenness to indicate photosynthetic activity is hindered by small annual changes in green biomass of the often evergreen tree population and by the confounding effects of background materials such as snow. As an alternative, satellite measurements of sun-induced chlorophyll fluorescence (SIF) can be used as a direct proxy of photosynthetic activity. In this study, the start and end of the photosynthetically active season of the main boreal forests are analysed using spaceborne SIF measurements retrieved from the GOME-2 instrument and compared to that of green biomass, proxied by vegetation indices including the Enhanced Vegetation Index (EVI) derived from MODIS data. We find that photosynthesis and greenness show a similar seasonality in deciduous forests. In high-latitude evergreen needleleaf forests, however, the length of the photosynthetically active period indicated by SIF is up to 6 weeks longer than the green biomass changing period proxied by EVI, with SIF showing a start-of-season of approximately 1 month earlier than EVI. On average, the photosynthetic spring recovery as signalled by SIF occurs as soon as air temperatures exceed the freezing point (2-3 °C) and when the snow on the ground has not yet completely melted. These findings are supported by model data of gross primary production and a number of other studies which evaluated in situ observations of CO2 fluxes, meteorology and the physiological state of the needles. Our results demonstrate the sensitivity of space-based SIF measurements to light-use efficiency of boreal forests and their potential for an unbiased detection of photosynthetic activity even under the challenging conditions interposed by evergreen boreal ecosystems. © 2015 John Wiley & Sons Ltd.

Assessing fire emissions from tropical savanna and forests of central Brazil

Treesearch

Philip J. Riggan; James A. Brass; Robert N. Lockwood

1993-01-01

Wildfires in tropical forest and savanna are a strong source of trace gas and particulate emissions to the atmosphere, but estimates of the continental-scale impacts are limited by large uncertainties in the rates of fire occurrence and biomass combustion. Satellite-based remote sensing offers promise for characterizing fire physical properties and impacts on the...

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

Treesearch

Katherine Sinacore; Jefferson Scott Hall; Catherine Potvin; Alejandro A. Royo; Mark J. Ducey; Mark S. Ashton; Shijo Joseph

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...

An exergy based assessment of the production and conversion of switchgrass, equine waste and forest residue to bio-oil using fast pyrolysis

USDA-ARS?s Scientific Manuscript database

The resource efficiency of biofuel production via biomass pyrolysis is evaluated using exergy as an assessment metric. Three feedstocks, important to various sectors of US agriculture, switchgrass, forest residue and equine waste are considered for conversion to bio-oil (pyrolysis oil) via fast pyro...

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

Treesearch

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

2017-01-01

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...

Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests.

PubMed

Ma, Zhihai; Peng, Changhui; Zhu, Qiuan; Chen, Huai; Yu, Guirui; Li, Weizhong; Zhou, Xiaolu; Wang, Weifeng; Zhang, Wenhua

2012-02-14

The boreal forests, identified as a critical "tipping element" of the Earth's climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canada's boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canada's boreal forests may become net carbon sources if the climate change-induced droughts continue to intensify.

Forest biomass flow for fuel wood, fodder and timber security among tribal communities of Jharkhand.

PubMed

Islam, M A; Quli, S M S; Rai, R; Ali, Angrej; Gangoo, S A

2015-01-01

The study investigated extraction and consumption pattern of fuel wood, fodder and timber and forest biomass flow for fuel wood, fodder and timber security among tribal communities in Bundu block of Ranchi district in Jharkhand (India). The study is based on personal interviews of the selected respondents through structured interview schedule, personal observations and participatory rural appraisal tools i.e. key informant interviews and focus group discussions carried out in the sample villages, using multi-stage random sampling technique. The study revealed that the total extraction of fuel wood from different sources in villages was 2978.40 tons annum(-1), at the rate of 0.68 tons per capita annum(-1), which was mostly consumed in cooking followed by cottage industries, heating, community functions and others. The average fodder requirement per household was around 47.77 kg day(-1) with a total requirement of 14227.34 tons annum(-1). The average timber requirement per household was computed to be 0.346 m3 annum(-1) accounting for a total timber demand of 282.49 m3 annum(-1), which is mostly utilized in housing, followed by agricultural implements, rural furniture, carts and carriages, fencing, cattle shed/ store house and others. Forest biomass is the major source of fuel wood, fodder and timber for the primitive societies of the area contributing 1533.28 tons annum(-1) (51.48%) of the total fuel wood requirement, 6971.55 tons annum(-1) (49.00%) of the total fodder requirement and 136.36 m3 annum(-1) (48.27%) of the total timber requirement. The forest biomass is exposed to enormous pressure for securing the needs by the aboriginal people, posing great threat to biodiversity and environment of the region. Therefore, forest biomass conservation through intervention of alternative avenues is imperative to keep pace with the current development and future challenges in the area.

Modeling mangrove biomass using remote sensing based age and growth estimates

NASA Astrophysics Data System (ADS)

Lagomasino, D.; Fatoyinbo, T. E.; Feliciano, E. A.; Lee, S. K.; Trettin, C.; Mangora, M.; Rahman, M.

2016-12-01

Mangroves are highly regarded coastal forests because of their ecosystem services and high carbon storage potential. In addition, these forests can develop rapidly in locations where congenial environmental conditions and sediment supply are available. Monitoring the growth and age of developing mangrove forests is crucial for sustainable management and estimating carbon stocks. Combining imagery from radar and optical satellites (e.g., TanDEM-X and Landsat), we can estimate young mangrove growth and age at regional and continental scales. We used TanDEM-X radar interferometry for modeling canopy height in 2013 and Landsat to measure land cover change from 1990 to 2013. Annual NDVI composites were determined for each calendar year between 1990 and 2013. New land areas gained from the transition of water to vegetation were determined by the differences in annual NDVI composites and the reference year 2013. The year of the greatest NDVI difference that met the threshold criteria was used as the initial tree height (0 m). Annual canopy height growth rates were estimated by the duration between land generation times and 2013 canopy height models derived from TanDEM-X and very-high resolution optical data. In this presentation, we compare growth rates and biomass accumulation in mangrove forests at four river deltas; the Zambezi (Mozambique), Rufiji (Tanzania), Ganges (Bangladesh), and Mekong (Vietnam). The spatial patterns of growth rates coincided with characteristic successional paradigms and stream morphology, where the maximum growth rates typically occurred along prograding creek banks. Initial comparisons between height-only and growth-age biomass indicate that the latter tend to overestimate biomass for younger forest stands of similar height. Both the vertical (e.g., canopy height) and horizontal (e.g., expansion) growth rates measured from remote sensing can garner important information regarding mangrove succession and primary productivity. Continued research will combine mangrove growth-age and biomass modeling in other mangrove ecosystems order to resolve the development patterns between different geomorphologies.

Characterization of biomass burning aerosols from forest fire in Indonesia

NASA Astrophysics Data System (ADS)

Fujii, Y.; Iriana, W.; Okumura, M.; Lestari, P.; Tohno, S.; Akira, M.; Okuda, T.

2012-12-01

Biomass burning (forest fire, wild fire) is a major source of pollutants, generating an estimate of 104 Tg per year of aerosol particles worldwide. These particles have adverse human health effects and can affect the radiation budget and climate directly and indirectly. Eighty percent of biomass burning aerosols are generated in the tropics and about thirty percent of them originate in the tropical regions of Asia (Andreae, 1991). Several recent studies have reported on the organic compositions of biomass burning aerosols in the tropical regions of South America and Africa, however, there is little data about forest fire aerosols in the tropical regions of Asia. It is important to characterize biomass burning aerosols in the tropical regions of Asia because the aerosol properties vary between fires depending on type and moisture of wood, combustion phase, wind conditions, and several other variables (Reid et al., 2005). We have characterized PM2.5 fractions of biomass burning aerosols emitted from forest fire in Indonesia. During the dry season in 2012, PM2.5 aerosols from several forest fires occurring in Riau, Sumatra, Indonesia were collected on quartz and teflon filters with two mini-volume samplers. Background aerosols in forest were sampled during transition period of rainy season to dry season (baseline period). Samples were analyzed with several analytical instruments. The carbonaceous content (organic and elemental carbon, OC and EC) of the aerosols was analyzed by a thermal optical reflectance technique using IMPROVE protocol. The metal, inorganic ion and organic components of the aerosols were analyzed by X-ray Fluorescence (XRF), ion chromatography and gas chromatography-mass spectrometry, respectively. There was a great difference of chemical composition between forest fire and non-forest fire samples. Smoke aerosols for forest fires events were composed of ~ 45 % OC and ~ 2.5 % EC. On the other hand, background aerosols for baseline periods were composed of ~ 18 % OC and ~ 10 % EC. OC/EC ratio was consistently lower (~ 2) for baseline periods than that for forest fire events (~ 20). OC and EC concentrations for forest fire events were more than 150 times and 10 times higher than those for baseline periods.

Quantification of forest carbon degradation in Nicaragua using RapidEye remote sensing data: El Cuá and Wiwili case studies

NASA Astrophysics Data System (ADS)

Argoty, F. N.; Cifuentes, M.; Imbach, P. A.; Vilchez, S.; Casanoves, F.; Ibrahim, M.; Vierling, L. A.

2012-12-01

Forest degradation and deforestation affect ecosystem function and climate regulation services such as carbon storage. Historically, Central America has been a deforestation and forest degradation hotspot. Wiwili and El Cuá municipalities in northern Nicaragua are no exception, where subsistence agriculture and cattle ranch expansion have driven deforestation and other wood extraction activities, leading to various levels of forest degradation. Reduction of Emissions from forest Degradation and Deforestation (REDD) projects are proposed as a tool to slow the degradation and loss of carbon stocks by restoring carbon to its natural levels in order to mitigate carbon dioxide emissions that cause global warming. REDD projects require baseline estimations of current carbon stocks and forest degradation status. We estimated carbon stocks across a forest degradation gradient based on common biophysical variables and commercially available (RapidEye) remote sensing data. We measured 80 temporary forest plots (50x20m) for aboveground biomass to sample a gradient of forest degradation at two municipalities (El Cuá and Wiwili) in northern Nicaragua. We measured biomass in trees (≥10 cm DBH), saplings (5-9.9 cm DBH), other growth forms (ferns, palms and woody vines), and large detritus (snags and downed wood). Biomass was estimated by a range of allometric models and a constant conversion factor (0.47) was applied to calculate aboveground carbon stocks. Remote sensing data from a RapidEye scene for 02/2010 provided data for 5 spectral bands and 19 vegetation indexes at 6 m spatial resolution. Precipitation, temperature, altitude, slope, canopy cover, and aspect were also used as input variables for carbon modeling. We tested linear mixed models, generalized additive mixed models and regression tree approaches to explain carbon stocks based on vegetation indexes and biophysical variables. Additionally, we grouped plots into low (17-168 Mg C ha-1), medium (168-302 Mg C ha-1) and high (302-418 Mg C ha-1) carbon stocks (with conglomerate analysis) to test for a categorical classification approach based on discriminant analysis. Results show a gradient of total aboveground carbon between 17.78 - 379.2 Mg C ha-1. Models predicting carbon stock had an R2 that ranged between 0.32-0.52 (p<0.0001) across the three methods evaluated. Linear mixed models using the MCARI-MTVI2 vegetation index, based on the red-edge band (690-730 nm), showed the best performance. Categorical classification showed improved performance, with a 17% mean classification error, using 20 predictors (MCARI-MTVI2 was the most important). Our results show the importance of the red-edge band and the potential of multi-spectral high-resolution imagery to quantify tropical forest degradation. Although model performance for prediction of continuous biomass values is somewhat constrained, there is potential for coarser applications in the context of developing REDD baselines and monitoring using categorical mapping of forest degradation (with a trade-off in inference power) by means of relatively low-cost remote sensing and ancillary data.

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

PubMed

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

2016-02-01

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