Models of vegetation function are widely used to predict the effects of climate change on carbon, water and nutrient cycles of terrestrial ecosystems, and their feedbacks to climate. Stomatal conductance, the process that governs plant water use and carbon uptake, is fundamental to such models. In this paper, we reconcile two long-standing theories of stomatal conductance. The empirical approach, which is most commonly used in vegetation models, is phenomenological, based on experimental observations of stomatal behaviour in response to environmental conditions. The optimal approach is based on the theoretical argument that stomata should act to minimize the amount of water used per unit carbon gained. We reconcile these two approaches by showing that the theory of optimal stomatal conductance can be used to derive a model of stomatal conductance that is closely analogous to the empirical models. Consequently, we obtain a unified stomatal model which has a similar form to existing empirical models, but which now provides a theoretical interpretation for model parameter values. The key model parameter, g 1 , is predicted to increase with growth temperature and with the marginal water cost of carbon gain. The new model is fitted to a range of datasets ranging from tropical to boreal trees. The parameter g 1 is shown to vary with growth temperature, as predicted, and also with plant functional type. The model is shown to correctly capture responses of stomatal conductance to changing atmospheric CO 2 , and thus can be used to test for stomatal acclimation to elevated CO 2 . The reconciliation of the optimal and empirical approaches to modelling stomatal conductance is important for global change biology because it provides a simple theoretical framework for analyzing, and simulating, the coupling between carbon and water cycles under environmental change.

SummaryLeaf dark respiration (R dark ) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of R dark and associated leaf traits. Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in R dark .Area-based R dark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8-28°C). By contrast, R dark at a standard T (25°C, R dark 25 ) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher R dark 25 at a given photosynthetic capacity (V cmax 25 ) or leaf nitrogen concentration ([N]) than species at warmer sites. R dark 25 values at any given V cmax 25 or [N] were higher in herbs than in woody plants.The results highlight variation in R dark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of R dark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs).

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Predicted responses of transpiration to elevated atmospheric CO2 concentration (eCO2 ) are highly variable amongst process-based models. To better understand and constrain this variability amongst models, we conducted an intercomparison of 11 ecosystem models applied to data from two forest free-air CO2 enrichment (FACE) experiments at Duke University and Oak Ridge National Laboratory. We analysed model structures to identify the key underlying assumptions causing differences in model predictions of transpiration and canopy water use efficiency. We then compared the models against data to identify model assumptions that are incorrect or are large sources of uncertainty. We found that model-to-model and model-to-observations differences resulted from four key sets of assumptions, namely (i) the nature of the stomatal response to elevated CO2 (coupling between photosynthesis and stomata was supported by the data); (ii) the roles of the leaf and atmospheric boundary layer (models which assumed multiple conductance terms in series predicted more decoupled fluxes than observed at the broadleaf site); (iii) the treatment of canopy interception (large intermodel variability, 2-15%); and (iv) the impact of soil moisture stress (process uncertainty in how models limit carbon and water fluxes during moisture stress). Overall, model predictions of the CO2 effect on WUE were reasonable (intermodel μ = approximately 28% ± 10%) compared to the observations (μ = approximately 30% ± 13%) at the well-coupled coniferous site (Duke), but poor (intermodel μ = approximately 24% ± 6%; observations μ = approximately 38% ± 7%) at the broadleaf site (Oak Ridge). The study yields a framework for analysing and interpreting model predictions of transpiration responses to eCO2 , and highlights key improvements to these types of models.

Summary The temperature response of photosynthesis is one of the key factors determining predicted responses to warming in global vegetation models (GVMs). The response may vary geographically, owing to genetic adaptation to climate, and temporally, as a result of acclimation to changes in ambient temperature. Our goal was to develop a robust quantitative global model representing acclimation and adaptation of photosynthetic temperature responses. We quantified and modelled key mechanisms responsible for photosynthetic temperature acclimation and adaptation using a global dataset of photosynthetic CO2 response curves, including data from 141 C3 species from tropical rainforest to Arctic tundra. We separated temperature acclimation and adaptation processes by considering seasonal and common‐garden datasets, respectively. The observed global variation in the temperature optimum of photosynthesis was primarily explained by biochemical limitations to photosynthesis, rather than stomatal conductance or respiration. We found acclimation to growth temperature to be a stronger driver of this variation than adaptation to temperature at climate of origin. We developed a summary model to represent photosynthetic temperature responses and showed that it predicted the observed global variation in optimal temperatures with high accuracy. This novel algorithm should enable improved prediction of the function of global ecosystems in a warming climate.

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.

Heatwaves are likely to increase in frequency and intensity with climate change, which may impair tree function and forest C uptake. However, we have little information regarding the impact of extreme heatwaves on the physiological performance of large trees in the field. Here, we grew Eucalyptus parramattensis trees for 1 year with experimental warming (+3°C) in a field setting, until they were greater than 6 m tall. We withheld irrigation for 1 month to dry the surface soils and then implemented an extreme heatwave treatment of 4 consecutive days with air temperatures exceeding 43°C, while monitoring whole-canopy exchange of CO and H O, leaf temperatures, leaf thermal tolerance, and leaf and branch hydraulic status. The heatwave reduced midday canopy photosynthesis to near zero but transpiration persisted, maintaining canopy cooling. A standard photosynthetic model was unable to capture the observed decoupling between photosynthesis and transpiration at high temperatures, suggesting that climate models may underestimate a moderating feedback of vegetation on heatwave intensity. The heatwave also triggered a rapid increase in leaf thermal tolerance, such that leaf temperatures observed during the heatwave were maintained within the thermal limits of leaf function. All responses were equivalent for trees with a prior history of ambient and warmed (+3°C) temperatures, indicating that climate warming conferred no added tolerance of heatwaves expected in the future. This coordinated physiological response utilizing latent cooling and adjustment of thermal thresholds has implications for tree tolerance of future climate extremes as well as model predictions of future heatwave intensity at landscape and global scales.

Contents 986I.987II.987III.988IV.991V.992VI.995VII.997VIII.998References998 Summary It has been 75 yr since leaf respiratory metabolism in the light (day respiration) was identified as a low‐flux metabolic pathway that accompanies photosynthesis. In principle, it provides carbon backbones for nitrogen assimilation and evolves CO2 and thus impacts on plant carbon and nitrogen balances. However, for a long time, uncertainties have remained as to whether techniques used to measure day respiratory efflux were valid and whether day respiration responded to environmental gaseous conditions. In the past few years, significant advances have been made using carbon isotopes, ‘omics’ analyses and surveys of respiration rates in mesocosms or ecosystems. There is substantial evidence that day respiration should be viewed as a highly dynamic metabolic pathway that interacts with photosynthesis and photorespiration and responds to atmospheric CO2 mole fraction. The view of leaf day respiration as a constant and/or negligible parameter of net carbon exchange is now outdated and it should now be regarded as a central actor of plant carbon‐use efficiency.