A continuous measure of gross primary production for the conterminous United States derived from MODIS and AmeriFlux data

REMOTE SENSING OF ENVIRONMENT

卷:114

Article

Xiao, Jingfeng¹  Zhuang, Qianlai²  Law, Beverly E.³  Chen, Jiquan⁴  Baldocchi, Dennis D.⁵  Cook, David R.⁶  Oren, Ram⁷  Richardson, Andrew D.⁸  Wharton, Sonia⁹  Ma, Siyan⁵  Martin, Timothy A.¹⁰  Verma, Shashi B.¹¹  Suyker, Andrew E.¹¹  Scott, Russell L.¹²  Monson, Russell K.¹³  Litvak, Marcy¹⁴  Hollinger, David Y.¹⁵  Sun, Ge¹⁶  Davis, Kenneth J.¹⁷  Bolstad, Paul V.¹⁸  Burns, Sean P.¹³  Curtis, Peter S.¹⁹  Drake, Bert G.²⁰  Falk, Matthias⁹  Fischer, Marc L.²¹  Foster, David R.²²  Gu, Lianhong²³  Katul, Gabriel G.⁷  Matamala, Roser²⁴  McNulty, Steve¹⁶  Meyers, Tilden P.²⁵  Noormets, Asko^27,28  Oechel, Walter C.²⁹  Paw U, Kyaw Tha⁹  Schmid, Hans Peter^30,31  Starr, Gregory³²  Torn, Margaret S.³³  Wofsy, Steven C.²⁶ 

[1] Purdue Univ, Purdue Climate Change Res Ctr, Dept Earth & Atmospher Sci, W Lafayette, IN 47907 USA

[2] Purdue Univ, Purdue Climate Change Res Ctr, Dept Earth & Atmospher Sci, Dept Agron, W Lafayette, IN 47907 USA

[3] Oregon State Univ, Coll Forestry, Corvallis, OR 97331 USA

[4] Univ Toledo, Dept Environm Sci, Toledo, OH 43606 USA

[5] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Ecosyst Sci Div, Berkeley, CA 94720 USA

[6] Argonne Natl Lab, Div Environm Sci, Argonne, IL 60439 USA

[7] Duke Univ, Nicholas Sch Environm, Durham, NC 27708 USA

[8] Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USA

[9] Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA

[10] Univ Florida, Sch Forest Resources & Conservat, Gainesville, FL 32611 USA

[11] Univ Nebraska, Sch Nat Resources, Lincoln, NE 68583 USA

[12] USDA ARS, SW Watershed Res Ctr, Tucson, AZ 85719 USA

[13] Univ Colorado, Dept Ecol & Evolutionary Biol, Boulder, CO 80309 USA

[14] Univ New Mexico, Dept Biol, Albuquerque, NM 87131 USA

[15] US Forest Serv, USDA, NE Res Stn, Durham, NH 03824 USA

[16] US Forest Serv, USDA, So Res Stn, Raleigh, NC 27606 USA

[17] Univ New Hampshire, Complex Syst Res Ctr, Durham, NH 03824 USA

[18] Univ Minnesota, Dept Forest Resources, St Paul, MN 55108 USA

[19] Ohio State Univ, Dept Evolut Ecol & Organismal Biol, Columbus, OH 43210 USA

[20] Smithsonian Environm Res Ctr, Edgewater, MD 21037 USA

[21] Univ Calif Berkeley, Lawrence Berkeley Lab, Environm Energy Technol Div, Dept Atmospher Sci, Berkeley, CA 94720 USA

[22] Harvard Univ, Dept Organism & Evolutionary Biol, Petersham, MA 01366 USA

[23] Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA

[24] Argonne Natl Lab, Biosci Div, Argonne, IL 60439 USA

[25] NOAA, ARL, Atmospher Turbulence & Diffus Div, Oak Ridge, TN 37831 USA

[26] Harvard Univ, Dept Earth & Planetary Sci, Div Engn & Appl Sci, Cambridge, MA 02138 USA

[27] N Carolina State Univ, Dept Forestry & Environm Resources, Raleigh, NC 27695 USA

[28] N Carolina State Univ, So Global Change Program, Raleigh, NC 27695 USA

[29] San Diego State Univ, Dept Biol, San Diego, CA 92182 USA

[30] Indiana Univ, Dept Geog, Bloomington, IN 47405 USA

[31] FZK IMK IFU, Res Ctr Karlsruhe, Inst Meteorol & Climate Res, D-82467 Garmisch Partenkirchen, Germany

[32] Univ Alabama, Dept Biol Sci, Tuscaloosa, AL 35487 USA

[33] Univ Calif Berkeley, Lawrence Berkeley Lab, Div Earth Sci, Berkeley, CA 94720 USA

关键词: Gross primary productivity;    MODIS;    AmeriFlux;    Eddy covariance;    Regression tree;    US;    Carbon fluxes;    Interannual variability;    Satellite data;    Biomes;   

DOI  :  10.1016/j.rse.2009.10.013

来源: Elsevier

【 摘 要 】

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 I km x I 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(-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 variability of U.S. GPP were dominated by these extreme climate events and disturbances. (C) 2009 Elsevier Inc. All rights reserved.

【 授权许可】

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