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 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.

Technological advances during the past several decades have greatly enhanced our ability to measure leaf photosynthesis virtually anywhere and under any condition. Associated with the resulting proliferation of gas-exchange data is a lingering uncertainty regarding the importance of such measurements when it comes to explaining intrinsic causes of plant growth variation. Accordingly, in this paper we rely on a compilation of data to address the following questions: from both statistical and mechanistic standpoints, how closely does plant growth correlate with measures of leaf photosynthesis? Moreover, in this context, does the importance of leaf photosynthesis as an explanatory variable differ among growth light environments? Across a wide array of species and environments, relative growth rate (RGR) was positively correlated with daily integrals of photosynthesis expressed per unit leaf area (Aarea), leaf mass (Amass), and plant mass (Aplant). The amount of RGR variation explained by these relationships increased from 36% for the former to 93% for the latter. Notably, there was close agreement between observed RGR and that estimated from Aplant after adjustment for theoretical costs of tissue construction. Overall, based on an analysis of growth response coefficients (GRCs), gross assimilation rate (GAR), a photosynthesis-based estimate of biomass gain per unit leaf area, explained about as much growth variation as did leaf mass ratio (LMR) and specific leaf area (SLA). Further analysis of GRCs indicated that the importance of GAR in explaining growth variation increased with increasing light intensity. Clearly, when considered in combination with other key determinants, appropriate measures of leaf gas exchange effectively capture the fundamental role of leaf photosynthesis in plant growth variation.