No abstract

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.

Predicting the large-scale consequences of drought in contrasting environments requires that we understand how drought effects differ among species originating from those environments. A previous meta-analysis of published experiments suggested that the effects of drought on both stomatal and non-stomatal limitations to photosynthesis may vary consistently among species from different hydroclimates. Here, we explicitly tested this hypothesis with two short-term water stress experiments on congeneric mesic and xeric species. One experiment was run in Australia using Eucalyptus species and the second was run in Spain using Quercus species as well as two more mesic species. In each experiment, plants were grown under moist conditions in a glasshouse, then deprived of water, and gas exchange was monitored. The stomatal response was analysed with a recently developed stomatal model, whose single parameter g1 represents the slope of the relationship between stomatal conductance and photosynthesis. The non-stomatal response was partitioned into effects on mesophyll conductance (gm), the maximum Rubisco activity (Vcmax) and the maximum electron transport rate (Jmax). We found consistency among the drought responses of g1, gm, Vcmax and Jmax, suggesting that drought imposes limitations on Rubisco activity and RuBP regeneration capacity concurrently with declines in stomatal and mesophyll conductance. Within each experiment, the more xeric species showed relatively high g1 under moist conditions, low drought sensitivity of g1, gm, Vcmax and Jmax, and more negative values of the critical pre-dawn water potential at which Vcmax declines most steeply, compared with the more mesic species. These results indicate adaptive interspecific differences in drought responses that allow xeric tree species to continue transpiration and photosynthesis for longer during periods without rain.

Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account