Interannual variation in global‐scale net primary production: Testing model estimates

Abstract

Testing estimates of year‐to‐year variation in global net primary production (NPP) poses some challenges. Large‐scale, multiyear records of production are not readily available for natural systems but are for agricultural systems. We use records of agricultural yields at selected sites to test NPP estimates produced by CASA, a global‐scale production model driven by both meteorological data and the satellite‐derived normalized difference vegetation index (NDVI). We also test estimates produced by the Miami model, which has underlain several analyses of biosphere response to interannual changes in climate. In addition, we test estimates against tree ring data for one boreal site for which data from both coniferous and deciduous species were available. The agricultural tests demonstrate that CASA can reasonably estimate interannual variation in production. The Miami model estimates variation more poorly. However, differences in NDVI‐processing algorithms substantially affect CASA's estimates of interannual variation. Of the four versions tested, the FASIR NDVI most closely reproduced yield data and showed the least correlation with changes in equatorial crossing time of the National Oceanic and Atmospheric Administration satellites. One issue raised is the source of the positive trends evident in CASA's NDVI‐based estimates of global NPP. The existence of these trends is consistent with potential stimulation of terrestrial production by factors such as CO 2 enrichment, N fertilization, or temperature warming, but the magnitude of the global trends seen is significantly greater than suggested by constraints imposed by atmospheric fluxes.

Keywords

Affiliated Institutions

• University of California, Berkeley US
• Carnegie Institution for Science US
• University of Alaska Fairbanks US
• Goddard Space Flight Center US
• Harvard University Press US

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