Toward the Use of the MODIS ET Product to Estimate Terrestrial GPP for Nonforest Ecosystems

Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data (MOD17), based on the light-use-efficiency algorithm, have been widely used to assess large-scale carbon budgets. However, systemic errors of this product have been reported, particularly for nonforest ecosystems. Here, we test a simple and operational way to estimate GPP in nonforest ecosystems by inverting the MODIS evapotranspiration (ET) product (MOD16) using ecosystem water use efficiency (WUE = GPP/ET) . Field measurements from 17 nonforest AmeriFlux sites of GPP were used for validation. Results show that the inverted GPP from MOD16 (MOD16 GPP) agrees better with the observed GPP than MOD17 does. The overall root-mean-square error (RMSE) and mean bias of MOD16 GPP are 19.63 g C/m2/8-day and -4.06 g C/m2 /8-day, respectively, which are lower than the corresponding values of MOD17 GPP ( RMSE = 23.82 g C/ m2/8-day and mean bias = -9.07 g C/m2/8-day). This finding suggests the potential to achieve a better assessment of GPP for nonforest ecosystems with a fine resolution.

[1]  Di Long,et al.  Remote estimation of terrestrial evapotranspiration without using meteorological data , 2013 .

[2]  David P. Billesbach,et al.  Carbon, water, and heat flux responses to experimental burning and drought in a tallgrass prairie , 2012 .

[3]  Andrew E. Suyker,et al.  Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems , 2005 .

[4]  Timothy Martin,et al.  Surface energy and carbon dioxide fluxes above different vegetation types within ABLE , 2006 .

[5]  Seung Oh Lee,et al.  Validation of MODIS 16 global terrestrial evapotranspiration products in various climates and land cover types in Asia , 2012 .

[6]  J. Rice.  Mathematical Statistics and Data Analysis , 1988 .

[7]  David P. Billesbach,et al.  Spatiotemporal Variations in Growing Season Exchanges of CO2, H2O, and Sensible Heat in Agricultural Fields of the Southern Great Plains , 2007 .

[8]  D. Baldocchi,et al.  Inter-annual variability in carbon dioxide exchange of an oak/grass savanna and open grassland in California , 2007 .

[9]  W. Cohen,et al.  Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation , 2003 .

[10]  Naoya Wada,et al.  Global negative vegetation feedback to climate warming responses of leaf litter decomposition rates in cold biomes. , 2007, Ecology letters.

[11]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[12]  J. Townshend,et al.  Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .

[13]  Jing M. Chen,et al.  Evaluating spatial and temporal patterns of MODIS GPP over the conterminous U.S. against flux measurements and a process model , 2012 .

[14]  M. S. Moran,et al.  Ecosystem resilience despite large-scale altered hydroclimatic conditions , 2013, Nature.

[15]  Jason P. Kaye,et al.  Long‐term impact of a stand‐replacing fire on ecosystem CO2 exchange of a ponderosa pine forest , 2008 .

[16]  Songhao Shang,et al.  A novel algorithm to assess gross primary production for terrestrial ecosystems from MODIS imagery , 2013 .

[17]  Marcy E. Litvak,et al.  An eddy covariance mesonet to measure the effect of forest age on land–atmosphere exchange , 2006 .

[18]  Markus Reichstein,et al.  Temporal and among‐site variability of inherent water use efficiency at the ecosystem level , 2009 .

[19]  Xiaoliang Lu,et al.  Evaluating evapotranspiration and water-use efficiency of terrestrial ecosystems in the conterminous United States using MODIS and AmeriFlux data , 2010 .

[20]  D. Sims,et al.  Potential of MODIS EVI and surface temperature for directly estimating per‐pixel ecosystem C fluxes , 2005 .

[21]  John M. Baker,et al.  Direct measurement of biosphere‐atmosphere isotopic CO2 exchange using the eddy covariance technique , 2008 .

[22]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .