17Drought threatens tropical rainforests over seasonal to decadal timescales [1][2][3][4] , but the drivers 18 of tree mortality following drought remain poorly understood 5,6 . It has been suggested that 19 reduced availability of non-structural carbohydrates (NSC) critically increases mortality risk 20 through insufficient carbon supply to metabolism ('carbon starvation') 7,8 . However little is 21 known about how NSC stores are affected by drought, especially over the long term, and 22 whether they are more important than hydraulic processes in determining drought-induced 23 mortality. Using data from the world's longest-running experimental drought study in tropical 24 rainforest (in the Brazilian Amazon), we test whether carbon starvation or deterioration of the 25 water-conducting pathways from soil to leaf trigger tree mortality. Biomass loss from 26 mortality in the experimentally-droughted forest increased substantially after >10 years of 27 reduced soil moisture availability. The mortality signal was dominated by the death of large 28 trees, which were at a much greater risk of hydraulic deterioration than smaller trees. 29However, we find no evidence that the droughted trees suffered carbon starvation, as their 30 NSC concentrations were similar to those of un-droughted trees, and growth rates did not 31 decline in either living or dying individuals. Our results indicate that hydraulics, rather than 32 carbon starvation, triggers tree death from drought in tropical rainforest. 34Drought-response observations from both field-scale experiments and natural droughts have 35 demonstrated increased mortality over the short-term (1-3 years), with notably higher 36 vulnerability for some taxa, and for larger trees 6,9,10 . After several years of drought, 37 recovering growth rates in smaller trees, dbh (diameter at breast height) <40 cm, and reduced 38 mortality have been recorded at different locations 6,11,12 . However, the long-term (>10 yr) 39 sensitivity of tropical forests to predicted prolonged and repeated water deficit [1][2][3] we synthesise these data to test whether long-term soil moisture deficit alters NSC storage 64 and use in tropical rainforest trees, and if this, or hydraulic processes, are most strongly 65 associated with increased mortality rates. 66By 2014, following 13 years of the TFE treatment, cumulative biomass loss through mortality 67 was 41.0±2.7% relative to pre-treatment values (Fig. 1a), and the rate of loss had increased 68 substantially since the previous reported value of 17.2±0.8%, after 7 years of TFE 6 . 69Accelerating biomass loss and failure to recover substantially, or to reach a new 70 equilibrium 13 , has led to a committed flux to the atmosphere from decomposing necromass of 71 101.9±19.1 Mg C ha -1 (Fig. 1a). This biomass loss has been driven by elevated mortality in 72 the largest trees (Fig. 1b), as previously observed over shorter timescales 6 , and has created a 73 canopy that has had a persistently lower average leaf area index during 2010-2014 74 (12.0±1...

No abstract

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).

SummaryConsiderable uncertainty surrounds the fate of Amazon rainforests in response to climate change.Here, carbon (C) flux predictions of five terrestrial biosphere models (Community Land Model version 3.5 (CLM3.5), Ecosystem Demography model version 2.1 (ED2), Integrated BIosphere Simulator version 2.6.4 (IBIS), Joint UK Land Environment Simulator version 2.1 (JULES) and Simple Biosphere model version 3 (SiB3)) and a hydrodynamic terrestrial ecosystem model (the Soil-Plant-Atmosphere (SPA) model) were evaluated against measurements from two large-scale Amazon drought experiments.Model predictions agreed with the observed C fluxes in the control plots of both experiments, but poorly replicated the responses to the drought treatments. Most notably, with the exception of ED2, the models predicted negligible reductions in aboveground biomass in response to the drought treatments, which was in contrast to an observed c. 20% reduction at both sites. For ED2, the timing of the decline in aboveground biomass was accurate, but the magnitude was too high for one site and too low for the other.Three key findings indicate critical areas for future research and model development. First, the models predicted declines in autotrophic respiration under prolonged drought in contrast to measured increases at one of the sites. Secondly, models lacking a phenological response to drought introduced bias in the sensitivity of canopy productivity and respiration to drought. Thirdly, the phenomenological water-stress functions used by the terrestrial biosphere models to represent the effects of soil moisture on stomatal conductance yielded unrealistic diurnal and seasonal responses to drought.

Abstract. 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 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 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 (Amax), 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.

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.

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 ecosystemlevel 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.

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’.