Stomatal conductance (g_s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g_s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g_s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g_s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model¹ and the leaf and wood economics spectrum^2,3. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of g_s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.

Stomatal conductance (g_s) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between g_s model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We constrained the key model parameter "g₁", which represents plant water use strategy, by PFT, based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g₁ parameter can be estimated using two long-term average (1960–1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal model, in conjunction with PFT parameterisations, resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance against upscaled data products was not degraded, but did not noticeably reduce existing model–data biases. We identified assumptions relating to the coupling of the vegetation to the atmosphere and the parameterisation of the minimum stomatal conductance as areas requiring further investigation in both CABLE and potentially other LSMs. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.

The response of photosynthesis to temperature is a central facet of plant response to climate. Such responses have been found to be highly variable among species and among studies. Understanding this variability is key when trying to predict the effects of rising global temperatures on plant productivity. There are three major factors affecting the response of leaf net photosynthesis to temperature (A_n–T): (i) photosynthetic biochemistry, (ii) respiration and (iii) vapour pressure deficit (D) and stomatal sensitivity to vapour pressure deficit during measurements. The overall goal of our study was to quantify the relative contribution of each of these factors in determining the response of A_n to temperature. We first conducted a sensitivity analysis with a coupled photosynthesis–stomatal (A_n–g_s) model, using ranges for parameters of each factor taken from the literature, and quantified how these parameters affected the A_n–T response. Second, we applied the A_n–g_s model to two example sets of field data, which had different optimum temperatures (T_opt) of A_n, to analyse which factors were most important in causing the difference. We found that each of the three factors could have an equally large effect on T_opt of A_n. In our comparison between two field datasets, the major cause for the difference in T_opt was not the biochemical component, but rather the differences in respiratory components and in D conditions during measurements. We concluded that shifts in A_n–T responses are not always driven by acclimation of photosynthetic biochemistry, but can result from other factors. The D conditions during measurements and stomatal responses to D also need to be quantified if we are to better understand and predict shifts in A_n–T with climate.

Models of stomatal conductance (g_s) are based on coupling between g_s and CO₂ assimilation (A_net), and it is often assumed that the slope of this relationship (‘g₁’) is constant across species. However, if different plant species have adapted to different access costs of water, then there will be differences in g₁ among species. We hypothesized that g₁ should vary among species adapted to different climates, and tested the theory and its linkage to plant hydraulics using four Eucalyptus species from different climatic origins in a common garden.Optimal stomatal theory predicts that species from sub‐humid zones have a lower marginal water cost of C gain, hence lower g₁ than humid‐zone species. In agreement with the theory that g₁ is related to tissue carbon costs for water supply, we found a relationship between wood density and g₁ across Eucalyptus species of contrasting climatic origins. There were significant reductions in the parameter g₁ during drought in humid but not sub‐humid species, with the latter group maintaining g₁ in drought. There are strong differences in stomatal behaviour among related tree species in agreement with optimal stomatal theory, and these differences are consistent with the economics involved in water uptake and transport for carbon gain.