Comparing cropland net primary production estimates frominventory, a satellite-based model, and a process-based model in theMidwest of the United States

Authors

Zengpeng Li, Earth System Science Interdisciplinary Center (ESSIC/UMD)Follow
Shuguang Liu, U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center
Zhengxi Tan, ASRC Federal InuTeq, Contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center
Normann B. Bliss, ASRC Federal InuTeq, Contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) CenterFollow
Claudia J. Young, Earth Resources Technology, Inc. (ERT)
Tristram O. West, Joint Global Change Research Institute; Earth System Science Interdisciplinary Center (ESSIC/UMD)
Stephen M. Ogle, Natural Resource Ecology Laboratory; Department of Ecosystem Science and Sustainability

Date of this Version

2014

Citation

Ecological Modelling 277, 2014

Comments

U.S. Government work

Abstract

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for crop-lands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2yr−1and total NPP in the range of318–490 Tg C yr−1for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2yr−1while the MODISNPP product estimated the mean NPP was less than 500 g C m−2yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.