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Biologically Enhanced Carbon Sequestration: Research Needs and Opportunities

Description: Fossil fuel combustion, deforestation, and biomass burning are the dominant contributors to increasing atmospheric carbon dioxide (CO{sub 2}) concentrations and global warming. Many approaches to mitigating CO{sub 2} emissions are being pursued, and among the most promising are terrestrial and geologic carbon sequestration. Recent advances in ecology and microbial biology offer promising new possibilities for enhancing terrestrial and geologic carbon sequestration. A workshop was held October 29, 2007, at Lawrence Berkeley National Laboratory (LBNL) on Biologically Enhanced Carbon Sequestration (BECS). The workshop participants (approximately 30 scientists from California, Illinois, Oregon, Montana, and New Mexico) developed a prioritized list of research needed to make progress in the development of biological enhancements to improve terrestrial and geologic carbon sequestration. The workshop participants also identified a number of areas of supporting science that are critical to making progress in the fundamental research areas. The purpose of this position paper is to summarize and elaborate upon the findings of the workshop. The paper considers terrestrial and geologic carbon sequestration separately. First, we present a summary in outline form of the research roadmaps for terrestrial and geologic BECS. This outline is elaborated upon in the narrative sections that follow. The narrative sections start with the focused research priorities in each area followed by critical supporting science for biological enhancements as prioritized during the workshop. Finally, Table 1 summarizes the potential significance or 'materiality' of advances in these areas for reducing net greenhouse gas emissions.
Date: March 21, 2008
Creator: Oldenburg, Curtis; Oldenburg, Curtis M. & Torn, Margaret S.
Partner: UNT Libraries Government Documents Department

A highly portable, rapidly deployable system for eddy covariance measurements of CO2 fluxes

Description: To facilitate the study of flux heterogeneity within a region, the authors have designed, built, and field-tested a highly portable, rapidly deployable, eddy covariance CO{sub 2} flux measurement system. The system is built from off-the-shelf parts and was assembled at a minimal cost. The unique combination of features of this system allow for a very rapid deployment with a minimal number of field personnel. The system is capable of making high precision, unattended measurements of turbulent CO{sub 2} fluxes, latent heat (LE) fluxes, sensible heat fluxes (H), and momentum transfer fluxes. In addition, many of the meteorological and ecosystem variables necessary for quality control of the fluxes and for running ecosystem models are measured. A side-by-side field comparison of the system at a pair of established AmeriFlux sites has verified that, for single measurements, the system is capable of CO{sub 2} flux accuracy of about {+-} 1.2 {micro}mole/m{sup 2}/sec, LE flux accuracy of about {+-} 15 Watts/m{sup 2}, H flux accuracy of about {+-} 7 Watts/m{sup 2}, and momentum transfer flux accuracy of about {+-} 11 gm-m/sec/sec. System deployment time is between 2 and 4 hours by a single person. The system was measured to draw between 30 and 35 Watts of power and may be run from available line power, storage batteries, or solar panels.
Date: September 19, 2001
Creator: Billesbach, David P.; Fischer, Marc L.; Torn, Margaret S. & Berry, Joe A.
Partner: UNT Libraries Government Documents Department

Spatiotemporal variations in growing season exchanges of CO2, H2O,and sensible heat in agricultural fields of the Southern GreatPlains

Description: Climate, vegetation cover, and management create fine-scaleheterogeneity in unirrigated agricultural regions, with important but notwell-quantified consequences for spatial and temporal variations insurface CO2, water, and heat fluxes. We measured eddy covariance fluxesin seven agricultural fields--comprising winter wheat, pasture, andsorghum--in the U.S. Southern Great Plains (SGP) during the 2001-2003growing seasons. Land-cover was the dominant source of variation insurface fluxes, with 50-100 percent differences between fields planted inwinter-spring versus fields planted in summer. Interannual variation wasdriven mainly by precipitation, which varied more than two-fold betweenyears. Peak aboveground biomass and growing-season net ecosystem exchange(NEE) of CO2 increased in rough proportion to precipitation. Based on apartitioning of gross fluxes with a regression model, ecosystemrespiration increased linearly with gross primary production, but with anoffset that increased near the time of seed production. Because theregression model was designed for well-watered periods, it successfullyretrieved NEE and ecosystem parameters during the peak growing season,and identified periods of moisture limitation during the summer. Insummary, the effects of crop type, land management, and water limitationon carbon, water, and energy fluxes were large. Capturing the controllingfactors in landscape scale models will be necessary to estimate theecological feedbacks to climate and other environmental impactsassociated with changing human needs for agricultural production of food,fiber, and energy.
Date: June 13, 2007
Creator: Fischer, Marc L.; Billesbach, David P.; Berry, Joseph A.; Riley,William J. & Torn, Margaret S.
Partner: UNT Libraries Government Documents Department

Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data

Description: Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.
Date: October 1, 2008
Creator: Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.; Bolstad, Paul V.; Burns, Sean P.; Chen, Jiquan et al.
Partner: UNT Libraries Government Documents Department

Estimation of Net Ecosystem Carbon Exchange for the Conterminous UnitedStates by Combining MODIS and AmeriFlux Data

Description: Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board NASA's Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a regression tree approach. The predictive model was trained and validated using NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE reasonably well at the site level. We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day period in 2005 using spatially-explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets for large areas.
Date: March 6, 2009
Creator: Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.; Law, Beverly E.; Richardson, Andrew D.; Chen, Jiquan et al.
Partner: UNT Libraries Government Documents Department

A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

Description: The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual ...
Date: January 28, 2009
Creator: Xia, Jingfeng; Zhuang, Qianlai; Law, Beverly E.; Chen, Jiquan; Baldocchi, Dennis D.; Cook, David R. et al.
Partner: UNT Libraries Government Documents Department