Assessing variability of optimum air temperature for photosynthesis across site-years, sites and biomes and their effects on photosynthesis estimation

Abstract

Gross primary productivity (GPP) of vegetation is affected by air temperature. Biogeochemical models use the optimum air temperature (Topt) parameter, which comes from biome-specific look-up tables (Topt−b−LT). Many studies have shown that plants have the capacity to adapt to changes in environmental conditions over time, which suggests that the static Topt−b−LT parameters in the biogeochemical models may poorly represent actual Topt and induce uncertainty in GPP estimates. Here, we estimated biome-specific, site-year-specific, and site-specific optimum air temperature using GPP data from eddy covariance (EC) flux tower sites (GPPEC) (Topt−b−EC, Topt−sy−EC, Topt−s−EC), the Enhanced Vegetation Index (EVI) from MODIS images (Topt−b−EVI, Topt−sy−EVI, Topt−s−EVI), and mean daytime air temperature (TDT). We evaluated the consistency among the four Topt parameters (Topt−b, Topt−sy, Topt−s and Topt−b−LT), and assessed how they affect satellite-based GPP estimates. We find that Topt parameters from MODIS EVI agree well with those from GPPEC, which indicates that EVI can be used as a variable to estimate Topt at individual pixels over large spatial domains. Topt−b, Topt−sy, and Topt−s differed significantly from Topt−b−LT. GPP estimates using Topt−b and Topt−sy were more consistent with GPPEC than when using Topt−b−LT for all the land cover types. Our use of Topt−sy substantially improved 8-day and annual GPP estimates across biomess (from 1% to 34%), especially for cropland, grassland, and open shrubland. Our simple calculation shows that global GPP estimates differ by up to 10 Pg C/yr when using our suggested Topt−sy−EVI instead of using the static Topt−b−LT. Our new approach on estimating Topt has the potential to improve estimates of GPP from satellite-based models, which could lead to better understanding of carbon-climate interactions.