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United States Department of Agriculture

Agricultural Research Service

Research Project: CHLOROPLAST GENETIC ENGINEERING Title: Cropland Carbon Fluxes in the United States: Increasing Geospatial Resolution of Inventory-based Carbon Accounting

Authors
item West, Tristram -
item Brandt, Craig -
item Baskaran, Latha -
item Hellwinckel, Chad -
item Mueller, Richard -
item Bernacchi, Carl
item Bandaru, Varaprasad -
item Yang, Bai -
item Wilson, Bradley -
item Marland, Gregg -
item Nelson, Richard -
item DE La Torre Ugarte, Daniel -
item Post, Wilfred -

Submitted to: Ecological Applications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 1, 2010
Publication Date: June 1, 2010
Repository URL: http://hdl.handle.net/10113/42508
Citation: West, T.O., Brandt, C.C., Baskaran, L.M., Hellwinckel, C.M., Mueller, R., Bernacchi, C.J., Bandaru, V., Yang, B., Wilson, B.S., Marland, G., Nelson, R.G., De La Torre Ugarte, D.G., Post, W.M. 2010. Cropland Carbon Fluxes in the United States: Increasing Geospatial Resolution of Inventory-based Carbon Accounting. Ecological Applications. 20(4):1074-1086.

Interpretive Summary: Various methods are used to measure the exchange of carbon between the atmosphere and the terrestrial land surface. These methods vary according to how frequently measurements can be made and the spatial scale represented by the measurements. Measurements made at small spatial scales (such as over one field) usually consist of high frequency measurements whereas the measurements made over larger spatial scales (such as a county) generally represent a snapshot of current conditions but with high spatial resolution. A major goal associated with quantifying carbon inventories in ecosystems around the planet is to resolve differences in the small- and large-scale measurements. This study compares two satellite-based methods for quantifying ecosystem productivity over a large spatial scale with measurements made at the small scale for two locations in the Midwestern U.S. The two large spatial scale measurements include the “Moderate Resolution Imaging Spectroradiometer (MODIS)” and the “Cropland Data Layer (CDL)” satellite based measurement techniques. The analysis from these satellite-based measurements was compared with field-scale measurements using a technique referred to as Eddy Covariance, which uses wind and air samples to calculated carbon fluxes. The results show that the CDL method for estimating carbon exchange was closely correlated with the ground-based measurements, suggesting that this measure is the more reliable of the two. CDL also has higher resolution allowing for better estimates of cropland carbon dynamics, leading to more accurate measures of current interactions between croplands and the atmosphere.

Technical Abstract: Net annual soil carbon change, fossil fuel emissions from cropland production, and cropland net primary productivity were estimated and spatially distributed using land cover defined by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by the Cropland Data Layer (CDL). Spatially resolved estimates of net ecosystem exchange (NEE) and net ecosystem carbon balance (NECB) were developed. NEE represents net on-site vertical fluxes of carbon. NECB represents all on-site and off-site carbon fluxes associated with crop production. Estimates of cropland NEE using moderate resolution (~1km2) land cover data were generated for the conterminous US and compared with higher resolution (30m) estimates of NEE and with direct measurements of CO2 flux from croplands in Illinois and Nebraska. Estimates of NEE using the CDL (30m resolution) had a higher correlation with eddy covariance flux tower estimates compared with estimates of NEE using MODIS. Estimates of NECB are primarily driven by net soil carbon change, fossil-fuel emissions associated with crop production, and CO2 emissions from the application of agricultural lime. NEE and NECB for US croplands were -274 and 7 Tg C yr**-1 for 2004, respectively. Use of moderate to high resolution satellite-based land cover data enables improved estimates of cropland carbon dynamics.

Last Modified: 12/17/2014
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