Comment on essd-2022-136

Abstract

The maximum rate of Rubisco carboxylation (Vcmax) 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 Vcmax, based on plants’ optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis. These two independent global Vcmax products agree well (r2 = 0.79, RMSE = 15.46 μmol m-2 s-1, P < 0.001) and compare well with 3672 ground-based measurements (r2 = 0.68, RMSE = 13.55 μmol m-2 s-1 and P < 0.001 for SIF; r2 = 0.55, RMSE = 17.55 μmol m-2 s-1 and P < 0.001 for LCC). Through a data assimilation technique, these two types of Vcmax products from remote sensing are combined to provide an optimized Vcmax product. The global distributions 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 and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products are available at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2020) and the code for implementing the ecological optimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R (Smith, 2020).