Dataset for Global distribution and drivers of leaf maximum carboxylation rate

The maximum carboxylation rate of Rubisco (Vcmax) is a crucial parameter in terrestrial biosphere models (TBMs) for simulating photosynthetic carbon assimilation. Most TBMs, however, prescribe Vcmax as a constant within each plant functional type, neglecting spatial variability and limiting the accuracy of terrestrial carbon cycle estimates. Although several attempts have been made to map Vcmax globally, its large-scale patterns and controlling factors remain poorly understood. Here, we compiled 6386 in situ measurements of Vcmax together with leaf nitrogen (LNC), phosphorus (LPC), and mass per area (LMA), and used machine learning to generate a global Vcmax map and identify its drivers. The predicted Vcmax shows strong agreement with three existing products (R2 ≥ 0.74) and have the best performance when validated against independent field data. We further find that leaf nutrients, climate, and soil jointly regulate global Vcmax variation, with LNC, LPC, and soil pH emerging as primary predictors. These results advance understanding of the factors controlling Vcmax, and suggest that projections of photosynthetic capacity and terrestrial carbon fluxes could be markedly improved by incorporating the interactive effects of leaf nutrient traits, climate, and soil properties into Vcmax parameterization in TBMs.