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Abstract

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation
rate (Vcmax), 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 Vcmax 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 Vcmax dataset for C3 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.