Global photosynthetic capacity is optimized to the environment.

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V-cmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co-optimization of carboxylation and water costs for photosynthesis, suggests that optimal V-cmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field-measured V-cmax dataset for C-3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first-order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.