Abstract. Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a Richards’ equation-based model of plant hydraulics in which all parameters of its constitutive equations are biologically-interpretable and measureable plant hydraulic traits (e.g. turgor loss point πtlp, bulk elastic modulus ε, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf:sapwood area ratio Al:As). We embedded this plant hydraulics model within a forest simulator (TFS) that modeled individual tree light environments and their upper boundary condition (transpiration) as well as provided a means for parameterizing individual variation in hydraulic traits. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits wood density (WD), leaf mass per area (LMA) and photosynthetic capacity (Amax) and evaluated the coupled model’s (TFS-Hydro) predictions against diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait-trait relationships derived from this synthesis, the TFS-Hydro model parameterization is capable of representing patterns of coordination and trade-offs in hydraulic traits. TFS-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration under control conditions, but the absence of a vertically stratified soil hydrology model precluded improvements to the simulation of drought response. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.
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Abstract. Accurately representing the response of ecosystems to environmental change in land surface models (LSM) is crucial to making accurate predictions of future climate. Many LSMs do not correctly capture plant respiration and growth fluxes, particularly in response to extreme climatic events. This is in part due to the unrealistic assumption that total plant carbon expenditure (PCE) is always equal to gross carbon accumulation by photosynthesis. We present and evaluate a simple model of labile carbon storage and utilisation (SUGAR), designed to be integrated into an LSM, that allows simulated plant respiration and growth to vary independently of photosynthesis. SUGAR buffers simulated PCE against seasonal variation in photosynthesis, producing more constant (less variable) predictions of plant growth and respiration relative to an LSM that does not represent labile carbon storage. This allows the model to more accurately capture observed carbon fluxes at a large-scale drought experiment in a tropical moist forest in the Amazon, relative to the Joint UK Land Environment Simulator LSM (JULES). SUGAR is designed to improve the representation of carbon storage in LSMs and provides a simple framework that allows new processes to be integrated as the empirical understanding of carbon storage in plants improves. The study highlights the need for future research into carbon storage and allocation in plants, particularly in response to extreme climate events such as drought.
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A large portion of the terrestrial vegetation carbon stock is stored in the above-ground biomass (AGB) of tropical forests, but the exact amount remains uncertain, partly owing to the lack of measurements. To date, accessible peer-reviewed data are available for just 10 large tropical trees in the Amazon that have been harvested and directly measured entirely via weighing. Here, we harvested four large tropical rainforest trees (stem diameter: 0.6-1.2 m, height: 30-46 m, AGB: 3960-18 584 kg) in intact old-growth forest in East Amazonia, and measured above-ground green mass, moisture content and woody tissue density. We first present rare ecological insights provided by these data, including unsystematic intra-tree variations in density, with both height and radius. We also found the majority of AGB was usually found in the crown, but varied from 42 to 62%. We then compare non-destructive approaches for estimating the AGB of these trees, using both classical allometry and new lidar-based methods. Terrestrial lidar point clouds were collected pre-harvest, on which we fitted cylinders to model woody structure, enabling retrieval of volume-derived AGB. Estimates from this approach were more accurate than allometric counterparts (mean tree-scale relative error: 3% versus 15%), and error decreased when up-scaling to the cumulative AGB of the four trees (1% versus 15%). Furthermore, while allometric error increased fourfold with tree size over the diameter range, lidar error remained constant. This suggests error in these lidar-derived estimates is random and additive. Were these results transferable across forest scenes, terrestrial lidar methods would reduce uncertainty in stand-scale AGB estimates, and therefore advance our understanding of the role of tropical forests in the global carbon cycle.

Plant traits are increasingly being used to improve prediction of plant function, including plant demography. However, the capability of plant traits to predict demographic rates remains uncertain, particularly in the context of trees experiencing a changing climate. Here we present data combining 17 plant traits associated with plant structure, metabolism and hydraulic status, with measurements of long-term mean, maximum and relative growth rates for 176 trees from the world's longest running tropical forest drought experiment. We demonstrate that plant traits can predict mean annual tree growth rates with moderate explanatory power. However, only combinations of traits associated more directly with plant functional processes, rather than more commonly employed traits like wood density or leaf mass per area, yield the power to predict growth. Critically, we observe a shift from growth being controlled by traits related to carbon cycling (assimilation and respiration) in well-watered trees, to traits relating to plant hydraulic stress in drought-stressed trees. We also demonstrate that even with a very comprehensive set of plant traits and growth data on large numbers of tropical trees, considerable uncertainty remains in directly interpreting the mechanisms through which traits influence performance in tropical forests.

Comparisons among methods are essential to validate plant traits measured across studies. However, a rigorous analysis is a complex task that needs to take into account not only the principle of the method and its correct use, but also inherent intraspecific trait variability, something we feel is not fully considered by Sergent et al. (2020). They compared the Bench dehydration, MicroCT, and Pneumatic methods using three long-vesseled species and found divergence among these methods. As a key finding, Sergent and colleagues reported unreliable estimates of Ψ. for Olea europaea when using the Pneumatic method in a such long-vesseled species. Here, we tested this finding by measuring independently vulnerability curves for O. europaea. Our results reinforce the viability of the Pneumatic method to estimate embolism vulnerability in long-vesseled species, as already found by others. Briefly, we also discuss important procedures when using the Pneumatic method and encourage further experiments, as the only way to know better the limitations of available methods and improve our understanding about plant water relations. 50

The response of small understory trees to long-term drought is vital in determining the future composition, carbon stocks and dynamics of tropical forests. Long-term drought is, however, also likely to expose understory trees to increased light availability driven by drought-induced mortality. Relatively little is known about the potential for understory trees to adjust their physiology to both decreasing water and increasing light availability. We analysed data on maximum photosynthetic capacity (Jmax , Vcmax ), leaf respiration (Rleaf ), leaf mass per area (LMA), leaf thickness and leaf nitrogen and phosphorus concentrations from 66 small trees across 12 common genera at the world's longest running tropical rainfall exclusion experiment and compared responses to those from 61 surviving canopy trees. Small trees increased Jmax , Vcmax , Rleaf and LMA (71, 29, 32, 15% respectively) in response to the drought treatment, but leaf thickness and leaf nutrient concentrations did not change. Small trees were significantly more responsive than large canopy trees to the drought treatment, suggesting greater phenotypic plasticity and resilience to prolonged drought, although differences among taxa were observed. Our results highlight that small tropical trees have greater capacity to respond to ecosystem level changes and have the potential to regenerate resilient forests following future droughts.

Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf- and ecosystem-level observations. SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem-level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root-mean-square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.

Xylem vulnerability to embolism represents an important trait to determine species distribution patterns and drought resistance. However, estimating embolism resistance frequently requires time-consuming and ambiguous hydraulic lab measurements. Based on a recently developed pneumatic method, we present and test the "Pneumatron", a device that generates high time-resolution and fully automated vulnerability curves. Embolism resistance is estimated by applying a partial vacuum to extract air from an excised xylem sample, while monitoring the pressure change over time. Although the amount of gas extracted is strongly correlated with the percentage loss of xylem conductivity, validation of the Pneumatron was performed by comparison with the optical method for Eucalyptus camaldulensis leaves. The Pneumatron improved the precision of the pneumatic method considerably, facilitating the detection of small differences in the (percentage of air discharged [PAD] < 0.47%). Hence, the Pneumatron can directly measure the 50% PAD without any fitting of vulnerability curves. PAD and embolism frequency based on the optical method were strongly correlated (r2 = 0.93) for E. camaldulensis. By providing an open source platform, the Pneumatron represents an easy, low-cost, and powerful tool for field measurements, which can significantly improve our understanding of plant-water relations and the mechanisms behind embolism.

Abstract. Accurately representing the response of ecosystems to environmental change in land surface models (LSMs) is crucial to making accurate predictions of future climate. Many LSMs do not correctly capture plant respiration and growth fluxes, particularly in response to extreme climatic events. This is in part due to the unrealistic assumption that total plant carbon expenditure (PCE) is always equal to gross carbon accumulation by photosynthesis. We present and evaluate a simple model of labile carbon storage and utilisation (SUGAR) designed to be integrated into an LSM, which allows simulated plant respiration and growth to vary independent of photosynthesis. SUGAR buffers simulated PCE against seasonal variation in photosynthesis, producing more constant (less variable) predictions of plant growth and respiration relative to an LSM that does not represent labile carbon storage. This allows the model to more accurately capture observed carbon fluxes at a large-scale drought experiment in a tropical moist forest in the Amazon, relative to the Joint UK Land Environment Simulator LSM (JULES). SUGAR is designed to improve the representation of carbon storage in LSMs and provides a simple framework that allows new processes to be integrated as the empirical understanding of carbon storage in plants improves. The study highlights the need for future research into carbon storage and allocation in plants, particularly in response to extreme climate events such as drought.
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The absorption of atmospheric water directly into leaves enables plants to alleviate the water stress caused by low soil moisture, hydraulic resistance in the xylem and the effect of gravity on the water column, while enabling plants to scavenge small inputs of water from leaf-wetting events. By increasing the availability of water, and supplying it from the top of the canopy (in a direction facilitated by gravity), foliar uptake (FU) may be a significant process in determining how forests interact with climate, and could alter our interpretation of current metrics for hydraulic stress and sensitivity. FU has not been reported for lowland tropical rainforests; we test whether FU occurs in six common Amazonian tree genera in lowland Amazônia, and make a first estimation of its contribution to canopy-atmosphere water exchange. We demonstrate that FU occurs in all six genera and that dew-derived water may therefore be used to "pay" for some morning transpiration in the dry season. Using meteorological and canopy wetness data, coupled with empirically derived estimates of leaf conductance to FU (kfu ), we estimate that the contribution by FU to annual transpiration at this site has a median value of 8.2% (103 mm/year) and an interquartile range of 3.4%-15.3%, with the biggest sources of uncertainty being kfu and the proportion of time the canopy is wet. Our results indicate that FU is likely to be a common strategy and may have significant implications for the Amazon carbon budget. The process of foliar water uptake may also have a profound impact on the drought tolerance of individual Amazonian trees and tree species, and on the cycling of water and carbon, regionally and globally.

Biomass and area ratios between leaves, stems and roots regulate many physiological and ecological processes. The Huber value Hv (sapwood area/leaf area ratio) is central to plant water balance and drought responses. However, its coordination with key plant functional traits is poorly understood, and prevents developing trait-based prediction models. Based on theoretical arguments, we hypothesise that global patterns in Hv of terminal woody branches can be predicted from variables related to plant trait spectra, that is plant hydraulics and size and leaf economics. Using a global compilation of 1135 species-averaged Hv , we show that Hv varies over three orders of magnitude. Higher Hv are seen in short small-leaved low-specific leaf area (SLA) shrubs with low Ks in arid relative to tall large-leaved high-SLA trees with high Ks in moist environments. All traits depend on climate but climatic correlations are stronger for explanatory traits than Hv. Negative isometry is found between Hv and Ks , suggesting a compensation to maintain hydraulic supply to leaves across species. This work identifies the major global drivers of branch sapwood/leaf area ratios. Our approach based on widely available traits facilitates the development of accurate models of above-ground biomass allocation and helps predict vegetation responses to drought.

The Amazon rainforest presents high temperatures and annual precipitation, although there are large interannual variations in these meteorological elements. Air temperature (Tar) and relative air humidity (RH) in and above a forest are the result of complex energy exchanges through the processes of reflection, transmission, and absorption of solar energy. This study was carried out in the Caxiuanã National Forest, Pará, Brasil, and the objective was to evaluate the seasonal variability of air temperature and humidity from a vertical profile analysis within the forest with measures heights of 2, 16, 28 and 42 m, with readings taken every 30 minutes from 2012 to 2016. The results indicated a great seasonality in these meteorological elements, since the highest temperatures occurred at the canopy level (28 m), and the lowest ones were observed near the surface (2 m) due to the attenuation of solar radiation inside the forest. The highest RH values were observed near the surface (2 m), and the lowest values occurred above the canopy, due to the higher wind speeds at this level. These results indicate a large spatial-temporal variability of these meteorological elements, which influence the behavior of living organisms that inhabit that forest environment.

Meteorological extreme events such as El Niño events are expected to affect tropical forest net primary production (NPP) and woody growth, but there has been no large-scale empirical validation of this expectation. We collected a large high-temporal resolution dataset (for 1-13 years depending upon location) of more than 172 000 stem growth measurements using dendrometer bands from across 14 regions spanning Amazonia, Africa and Borneo in order to test how much month-to-month variation in stand-level woody growth of adult tree stems (NPPstem) can be explained by seasonal variation and interannual meteorological anomalies. A key finding is that woody growth responds differently to meteorological variation between tropical forests with a dry season (where monthly rainfall is less than 100 mm), and aseasonal wet forests lacking a consistent dry season. In seasonal tropical forests, a high degree of variation in woody growth can be predicted from seasonal variation in temperature, vapour pressure deficit, in addition to anomalies of soil water deficit and shortwave radiation. The variation of aseasonal wet forest woody growth is best predicted by the anomalies of vapour pressure deficit, water deficit and shortwave radiation. In total, we predict the total live woody production of the global tropical forest biome to be 2.16 Pg C yr-1, with an interannual range 1.96-2.26 Pg C yr-1 between 1996-2016, and with the sharpest declines during the strong El Niño events of 1997/8 and 2015/6. There is high geographical variation in hotspots of El Niño-associated impacts, with weak impacts in Africa, and strongly negative impacts in parts of Southeast Asia and extensive regions across central and eastern Amazonia. Overall, there is high correlation (r = -0.75) between the annual anomaly of tropical forest woody growth and the annual mean of the El Niño 3.4 index, driven mainly by strong correlations with anomalies of soil water deficit, vapour pressure deficit and shortwave radiation.This article is part of the discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

The current generation of dynamic global vegetation models (DGVMs) lacks a mechanistic representation of vegetation responses to soil drought, impairing their ability to accurately predict Earth system responses to future climate scenarios and climatic anomalies, such as El Niño events. We propose a simple numerical approach to model plant responses to drought coupling stomatal optimality theory and plant hydraulics that can be used in dynamic global vegetation models (DGVMs). The model is validated against stand-scale forest transpiration (E) observations from a long-term soil drought experiment and used to predict the response of three Amazonian forest sites to climatic anomalies during the twentieth century. We show that our stomatal optimization model produces realistic stomatal responses to environmental conditions and can accurately simulate how tropical forest E responds to seasonal, and even long-term soil drought. Our model predicts a stronger cumulative effect of climatic anomalies in Amazon forest sites exposed to soil drought during El Niño years than can be captured by alternative empirical drought representation schemes. The contrasting responses between our model and empirical drought factors highlight the utility of hydraulically-based stomatal optimization models to represent vegetation responses to drought and climatic anomalies in DGVMs.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Are short-term responses by tropical rainforest to drought (e.g. during El Niño) sufficient to predict changes over the long-term, or from repeated drought? Using the world's only long-term (16-year) drought experiment in tropical forest we examine predictability from short-term measurements (1-2 years). Transpiration was maximized in droughted forest: it consumed all available throughfall throughout the 16 years of study. Leaf photosynthetic capacity [Formula: see text] was maintained, but only when averaged across tree size groups. Annual transpiration in droughted forest was less than in control, with initial reductions (at high biomass) imposed by foliar stomatal control. Tree mortality increased after year three, leading to an overall biomass loss of 40%; over the long-term, the main constraint on transpiration was thus imposed by the associated reduction in sapwood area. Altered tree mortality risk may prove predictable from soil and plant hydraulics, but additional monitoring is needed to test whether future biomass will stabilize or collapse. Allocation of assimilate differed over time: stem growth and reproductive output declined in the short-term, but following mortality-related changes in resource availability, both showed long-term resilience, with partial or full recovery. Understanding and simulation of these phenomena and related trade-offs in allocation will advance more effectively through greater use of optimization and probabilistic modelling approaches.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

In the tropics, research, conservation and public attention focus on rain forests, but this neglects that half of the global tropics have a seasonally dry climate. These regions are home to dry forests and savannas (Figures 1 and 2), and are the focus of this Primer. The attention given to rain forests is understandable. Their high species diversity, sheer stature and luxuriance thrill biologists today as much as they did the first explorers in the Age of Discovery. Although dry forest and savanna may make less of a first impression, they support a fascinating diversity of plant strategies to cope with stress and disturbance including fire, drought and herbivory. Savannas played a fundamental role in human evolution, and across Africa and India they support iconic megafauna. Pennington et al. introduce seasonally dry biomes in the tropics – savannahs and dry forests.

Faster growth in tropical trees is usually associated with higher mortality rates, but the mechanisms underlying this relationship are poorly understood. In this study, we investigate how tree growth patterns are linked with environmental conditions and hydraulic traits, by monitoring the cambial growth of 9 tropical cloud forest tree species coupled with numerical simulations using an optimization model. We find that fast-growing trees have lower xylem safety margins than slow-growing trees and this pattern is not necessarily linked to differences in stomatal behaviour or environmental conditions when growth occurs. Instead, fast-growing trees have xylem vessels that are more vulnerable to cavitation and lower density wood. We propose the growth - xylem vulnerability trade-off represents a wood hydraulic economics spectrum similar to the classic leaf economic spectrum, and show through numerical simulations that this trade-off can emerge from the coordination between growth rates, wood density, and xylem vulnerability to cavitation. Our results suggest that vulnerability to hydraulic failure might be related with the growth-mortality trade-off in tropical trees, determining important life history differences. These findings are important in furthering our understanding of xylem hydraulic functioning and its implications on plant carbon economy.

The seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and 35 litter productivity measurements), their associated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonality in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rainfall is &lt; 2000ĝ€-mmĝ€-yrĝ'1 (water-limited forests) and to radiation otherwise (light-limited forests). On the other hand, independent of climate limitations, wood productivity and litterfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosynthetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest productivity in a drier climate in water-limited forest, and in current light-limited forest with future rainfall &lt; 2000ĝ€-mmĝ€-yrĝ'1. Author(s) 2016.

Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g. turgor loss point π , bulk elastic modulus ϵ, hydraulic capacitance C , xylem hydraulic conductivity k , water potential at 50% loss of conductivity for both xylem (P ) and stomata (P ), and the leafg: sapwood area ratio a : a ). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (A ), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait-trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted. tlp ft s,max 50,x 50,gs l s max

Summary: Leaf dark respiration (R. ) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of R. 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. Area-based R. 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. at a standard T (25°C, R. ) 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. at a given photosynthetic capacity (V. ) or leaf nitrogen concentration ([N]) than species at warmer sites. R. values at any given V. or [N] were higher in herbs than in woody plants. The results highlight variation in R. 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. in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs). dark dark dark dark dark dark dark cmax dark cmax dark dark 25 25 25 25 25

Leaf dark respiration (Rdark ) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of Rdark 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 Rdark. Area-based Rdark 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, Rdark at a standard T (25°C, Rdark (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 Rdark (25) at a given photosynthetic capacity (Vcmax (25) ) or leaf nitrogen concentration ([N]) than species at warmer sites. Rdark (25) values at any given Vcmax (25) or [N] were higher in herbs than in woody plants. The results highlight variation in Rdark 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 Rdark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs).

Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model - CLM3.5-DGVM; Ecosystem Demography model version 2 - ED2; the Joint UK Land Environment Simulator version 2.1 - JULES; Simple Biosphere model version 3 - SiB3; and the soil-plant-atmosphere model - SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model-data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in an with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.

© 2015 Macmillan Publishers Limited. All rights reserved.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 model and the leaf and wood economics spectrum. 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.