Global datasets of leaf photosynthetic capacity for ecological and earth system research

The maximum rate of Rubisco carboxylation (V_cmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to V_cmax, based on plants' optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive V_cmax from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global V_cmax products agree well (r²=0.79,RMSE=15.46μmol m^-2 s^-1, P<0.001) and compare well with 3672 ground-based measurements (r²=0.69,RMSE=13.8μmol m^-2 s^-1 and P<0.001 for SIF; r²=0.55,RMSE=18.28μmol m^-2 s^-1 and P<0.001 for LCC). The LCC-derived V_cmax product is also used to constrain the retrieval of Vcmax from TROPical Ozone Mission (TROPOMI) SIF data to produce an optimized V_cmax product using both SIF and LCC information. The global distributions of these products are compatible with V_cmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH, and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial V_cmax products are primed to play a major role in global ecosystem research. The three remote sensing V_cmax products based on SIF, LCC, and SIF+LCC are available at 10.5281/zenodo.6466968 (Chen et al., 2022), and the code for implementing the ecological optimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R and 10.5281/zenodo.5899564 (last access: 31 August 2022) (Smith et al., 2022).