Global datasets of leaf photosynthetic capacity for ecological and earth system research - Chen,JM; Wang,R; Liu,Y; He,L; Croft,H; Luo,X; Wang,H; Smith,NG; Keenan,TF; Prentice,IC; Zhang,Y; Ju,W; et al. (Earth System Science Data, 2022)
The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a keyparameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecologicalresearch. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants’ optimaldistribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2)observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilationtechnique. These two independent global Vcmax products agree well (r2=0.79, RMSE=15.46 μmol m-2s-1 25 , P<0.001) andcompare well with 3672 ground-based measurements (r2=0.68, RMSE=13.55 μmol m-2s-1and P<0.001 for SIF; r2=0.55,RMSE=17.55 μmol m-2s-1 and P<0.001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval ofVcmax from TROPOMI SIF data to produce an optimized Vcmax product using both SIF and LCC information. The globaldistributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH andleaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play amajor role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC and SIF+LCC areavailable at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2020) and the code for implementing the ecologicaloptimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R (Smith, 2020).