A stomatal control model based on optimization of carbon gain versus hydraulic risk predicts aspen sapling responses to drought

Incorporating photosynthetic acclimation improves stomatal optimisation models

Stomatal opening in plant leaves is regulated through a balance of carbon and water exchange under different environmental conditions. Accurate estimation of stomatal regulation is crucial for understanding how plants respond to changing environmental conditions, particularly under climate change. A new generation of optimality-based modelling schemes determines instantaneous stomatal responses from a balance of trade-offs between carbon gains and hydraulic costs, but most such schemes do not account for biochemical acclimation in response to drought. Here, we compare the performance of six instantaneous stomatal optimisation models with and without accounting for photosynthetic acclimation. Using experimental data from 37 plant species, we found that accounting for photosynthetic acclimation improves the prediction of carbon assimilation in a majority of the tested models. Photosynthetic acclimation contributed significantly to the reduction of photosynthesis under drought conditions in all tested models. Drought effects on photosynthesis could not accurately be explained by the hydraulic impairment functions embedded in the stomatal models alone, indicating that photosynthetic acclimation must be considered to improve estimates of carbon assimilation during drought.

A new empirical framework to quantify the hydraulic effects of soil and atmospheric drivers on plant water status

Metrics to quantify regulation of plant water status at the daily as opposed to the seasonal scale do not presently exist. This gap is significant since plants are hypothesised to regulate their water potential not only with respect to slowly changing soil drought but also with respect to faster changes in air vapour pressure deficit (VPD), a variable whose importance for plant physiology is expected to grow because of higher temperatures in the coming decades. We present a metric, the stringency of water potential regulation, that can be employed at the daily scale and quantifies the effects exerted on plants by the separate and combined effect of soil and atmospheric drought. We test our theory using datasets from two experiments where air temperature and VPD were experimentally manipulated. In contrast to existing metrics based on soil drought that can only be applied at the seasonal scale, our metric successfully detects the impact of atmospheric warming on the regulation of plant water status. We show that the thermodynamic effect of VPD on plant water status can be isolated and compared against that exerted by soil drought and the covariation between VPD and soil drought. Furthermore, in three of three cases, VPD accounted for more than 5 MPa of potential effect on leaf water potential. We explore the significance of our findings in the context of potential future applications of this metric from plant to ecosystem scale.

Intrinsic and extrinsic factors influencing Populus water use: A literature review

Poplars (Populus L. spp.) are versatile, productive trees that are used in environmental systems worldwide to provide a variety of benefits. Though poplars are recognized for their elevated water use, summaries of existing data on poplar water use, its influencing factors, and the methodologies used to measure it, are lacking. We sought to 1) summarize the sap flow methodologies used to quantify poplar water use, 2) review sap flow-derived water use data reported in the literature for Populus hybrids and non-hybrids, and 3) assess the effects of different intrinsic factors (plant variables) and extrinsic factors (environmental variables) on poplar water use. We identified 133 articles containing information on the methodologies used to measure poplar sap flow. Of these, the thermal dissipation method was used in a majority (55%) of the studies. Poplar water use data were reported in 51 of the articles, with studies taking place in 13 countries, and representing the time period of 1992-2018. Hybrids were studied in 18 articles and included 17 genotypes, while non-hybrids were studied in 33 articles, and included eight species. Hybrid poplar water use ranged from 0.7 to 11.3 mm day-1, with an overall mean of 2.7 ± 0.3 mm day-1. Non-hybrid water use ranged from 0.2 to 19.5 mm day-1 with an average of 2.8 ± 0.4 mm day-1. Hybrid poplar water use differed significantly among hybrid types, tree age classes, and water availability classes, and non-hybrid water use was significantly different among species, experimental context, and water availability classes. While we focused on poplar water use measured by sap flow methodologies, this review builds the foundation for a comprehensive summary of available poplar water use information that has been reported in the literature. Our results on the factors influencing poplar water use can be used to aid in the decision-making process when designing poplar-based environmental systems such as remediation, bioenergy, and agroforestry systems.

Key hydraulic traits control the dynamics of plant dehydration in four contrasting tree species during drought

Trees are at risk of mortality during extreme drought, yet our understanding of the traits that govern the timing of drought-induced hydraulic failure remains limited. To address this, we tested SurEau, a trait-based soil-plant-atmosphere model designed to predict the dynamics of plant dehydration as represented by the changes in water potential against those observed in potted trees of four contrasting species (Pinus halepensis Mill., Populus nigra L., Quercus ilex L. and Cedrus atlantica (Endl.) Manetti ex Carriére) exposed to drought. SurEau was parameterized with a range of plant hydraulic and allometric traits, soil and climatic variables. We found a close correspondence between the predicted and observed plant water potential (in MPa) dynamics during the early phase drought, leading to stomatal closure, as well as during the latter phase of drought, leading to hydraulic failure in all four species. A global model's sensitivity analysis revealed that, for a common plant size (leaf area) and soil volume, dehydration time from full hydration to stomatal closure (Tclose) was most strongly controlled by the leaf osmotic potential (Pi0) and its influence on stomatal closure, in all four species, while the maximum stomatal conductance (gsmax) also contributed to Tclose in Q. ilex and C. atlantica. Dehydration times from stomatal closure to hydraulic failure (Tcav) was most strongly controlled by Pi0, the branch residual conductance (gres) and Q10a sensitivity of gres in the three evergreen species, while xylem embolism resistance (P50) was most influential in the deciduous species P. nigra. Our findings point to SurEau as a highly useful model for predicting changes in plant water status during drought and suggest that adjustments made in key hydraulic traits are potentially beneficial to delaying the onset of drought-induced hydraulic failure in trees.

Declining tree growth resilience mediates subsequent forest mortality in the US Mountain West

Climate change-triggered forest die-off is an increasing threat to global forests and carbon sequestration but remains extremely challenging to predict. Tree growth resilience metrics have been proposed as measurable proxies of tree susceptibility to mortality. However, it remains unclear whether tree growth resilience can improve predictions of stand-level mortality. Here, we use an extensive tree-ring dataset collected at ~3000 permanent forest inventory plots, spanning 13 dominant species across the US Mountain West, where forests have experienced strong drought and extensive die-off has been observed in the past two decades, to test the hypothesis that tree growth resilience to drought can explain and improve predictions of observed stand-level mortality. We found substantial increases in growth variability and temporal autocorrelation as well declining drought resistance and resilience for a number of species over the second half of the 20th century. Declining resilience and low tree growth were strongly associated with cross- and within-species patterns of mortality. Resilience metrics had similar explicative power compared to climate and stand structure, but the covariance structure among predictors implied that the effect of tree resilience on mortality could partially be explained by stand and climate variables. We conclude that tree growth resilience offers highly valuable insights on tree physiology by integrating the effect of stressors on forest mortality but may have only moderate potential to improve large-scale projections of forest die-off under climate change.

Observed forest trait velocities have not kept pace with hydraulic stress from climate change

The extent to which future climate change will increase forest stress and the amount to which species and forest ecosystems can acclimate or adapt to increased stress is a major unknown. We used high-resolution maps of hydraulic traits representing the diversity in tree drought tolerance across the United States, a hydraulically enabled tree model, and forest inventory observations of demographic shifts to quantify the ability for within-species acclimation and between-species range shifts to mediate climate stress. We found that forests are likely to experience increases in both acute and chronic hydraulic stress with climate change. Based on current species distributions, regional hydraulic trait diversity was sufficient to buffer against increased stress in 88% of forested areas. However, observed trait velocities in 81% of forested areas are not keeping up with the rate required to ameliorate projected future stress without leaf area acclimation.

GrapevineXL reliably predicts multi-annual dynamics of vine water status, berry growth, and sugar accumulation in vineyards

Climate and water availability greatly affect each season's grape yield and quality. Using models to accurately predict environment impacts on fruit productivity and quality is a huge challenge. We calibrated and validated the functional-structural model, GrapevineXL, with a data set including grapevine seasonal midday stem water potential (Ψ_xylem), berry dry weight (DW), fresh weight (FW), and sugar concentration per volume ([Sugar]) for a wine grape cultivar (Vitis vinifera cv. Cabernet Franc) in field conditions over 13 years in Bordeaux, France. Our results showed that the model could make a fair prediction of seasonal Ψ_xylem and good-to-excellent predictions of berry DW, FW, [Sugar] and leaf gas exchange responses to predawn and midday leaf water potentials under diverse environmental conditions with 14 key parameters. By running virtual experiments to mimic climate change, an advanced veraison (i.e. the onset of ripening) of 14 and 28 days led to significant decreases of berry FW by 2.70% and 3.22%, clear increases of berry [Sugar] by 2.90% and 4.29%, and shortened ripening duration in 8 out of 13 simulated years, respectively. Moreover, the impact of the advanced veraison varied with seasonal patterns of climate and soil water availability. Overall, the results showed that the GrapevineXL model can predict plant water use and berry growth in field conditions and could serve as a valuable tool for designing sustainable vineyard management strategies to cope with climate change.

Do stomata optimize turgor-driven growth? A new framework for integrating stomata response with whole-plant hydraulics and carbon balance

Every existing optimal stomatal model uses photosynthetic carbon assimilation as a proxy for plant evolutionary fitness. However, assimilation and growth are often decoupled, making assimilation less ideal for representing fitness when optimizing stomatal conductance to water vapor and carbon dioxide. Instead, growth should be considered a closer proxy for fitness. We hypothesize stomata have evolved to maximize turgor-driven growth, instead of assimilation, over entire plants' lifetimes, improving their abilities to compete and reproduce. We develop a stomata model that dynamically maximizes whole-stem growth following principles from turgor-driven growth models. Stomata open to assimilate carbohydrates that supply growth and osmotically generate turgor, while stomata close to prevent losses of turgor and growth due to negative water potentials. In steady state, the growth optimization model captures realistic stomatal, growth, and carbohydrate responses to environmental cues, reconciles conflicting interpretations within existing stomatal optimization theories, and explains patterns of carbohydrate storage and xylem conductance observed during and after drought. Our growth optimization hypothesis introduces a new paradigm for stomatal optimization models, elevates the role of whole-plant carbon use and carbon storage in stomatal functioning, and has the potential to simultaneously predict gross productivity, net productivity, and plant mortality through a single, consistent modeling framework.

From comfort zone to mortality: Sequence of physiological stress thresholds in Robinia pseudoacacia seedlings during progressive drought

INTRODUCTION

Parameterizing the process of trees from the comfort zone to mortality during progressive drought is important for, but is not well represented in, vegetation models, given the lack of appropriate indices to gauge the response of trees to droughts. The objective of this study was to determine reliable and readily available tree drought stressindices and the thresholds at which droughts activate important physiological responses.

METHODS

We analyzed the changes in the transpiration (T), stomatal conductance, xylem conductance, and leaf health status due to a decrease in soil water availability (SWA), predawn xylem water potential (ψ_pd), and midday xylem water potential (ψ_md) in Robinia pseudoacacia seedlings during progressive drought.

RESULTS

The results showed that ψ_md was a better indicator of drought stress than SWA and ψ_pd, because ψ_md was more closely related to the physiological response (defoliation and xylem embolization) during severe drought and could be measured more conveniently. We derived the following five stress levels from the observed responses to decreasing ψ_md: comfort zone (ψ_md > -0.9 MPa), wherein transpiration and stomatal conductance are not limited by SWA; moderate drought stress (-0.9 to -1.75 MPa), wherein transpiration and stomatal conductance are limited by drought; high drought stress (-1.75 to -2.59 MPa), wherein transpiration decreases significantly (T< 10%) and stomata closes completely; severe drought stress (-2.59 to -4.02 MPa), wherein transpiration ceases (T< 0.1%) and leaf shedding orwilting is > 50%; and extreme drought stress (< -4.02 MPa), leading to tree mortality due to xylem hydraulic failure.

DISCUSSION

To our knowledge, our scheme is the first to outline the quantitative thresholds for the downregulation of physiological processes in R. pseudoacacia during drought, therefore, can be used to synthesize valuable information for process-based vegetation models.

Linking remotely sensed ecosystem resilience with forest mortality across the continental United States

Episodes of forest mortality have been observed worldwide associated with climate change, impacting species composition and ecosystem services such as water resources and carbon sequestration. Yet our ability to predict forest mortality remains limited, especially across large scales. Time series of satellite imagery has been used to document ecosystem resilience globally, but it is not clear how well remotely sensed resilience can inform the prediction of forest mortality across continental, multi-biome scales. Here, we leverage forest inventories across the continental United States to systematically assess the potential of ecosystem resilience derived using different data sets and methods to predict forest mortality. We found high resilience was associated with low mortality in eastern forests but was associated with high mortality in western regions. The unexpected resilience-mortality relation in western United States may be due to several factors including plant trait acclimation, insect population dynamics, or resource competition. Overall, our results not only supported the opportunity to use remotely sensed ecosystem resilience to predict forest mortality but also highlighted that ecological factors may have crucial influences because they can reverse the sign of the resilience-mortality relationships.

Functional xylem characteristics associated with drought-induced embolism in angiosperms

Hydraulic failure resulting from drought-induced embolism in the xylem of plants is a key determinant of reduced productivity and mortality. Methods to assess this vulnerability are difficult to achieve at scale, leading to alternative metrics and correlations with more easily measured traits. These efforts have led to the longstanding and pervasive assumed mechanistic link between vessel diameter and vulnerability in angiosperms. However, there are at least two problems with this assumption that requires critical re-evaluation: (1) our current understanding of drought-induced embolism does not provide a mechanistic explanation why increased vessel width should lead to greater vulnerability, and (2) the most recent advancements in nanoscale embolism processes suggest that vessel diameter is not a direct driver. Here, we review data from physiological and comparative wood anatomy studies, highlighting the potential anatomical and physicochemical drivers of embolism formation and spread. We then put forward key knowledge gaps, emphasising what is known, unknown and speculation. A meaningful evaluation of the diameter-vulnerability link will require a better mechanistic understanding of the biophysical processes at the nanoscale level that determine embolism formation and spread, which will in turn lead to more accurate predictions of how water transport in plants is affected by drought.

Towards a unified theory of plant photosynthesis and hydraulics

The global carbon and water cycles are governed by the coupling of CO₂ and water vapour exchanges through the leaves of terrestrial plants, controlled by plant adaptations to balance carbon gains and hydraulic risks. We introduce a trait-based optimality theory that unifies the treatment of stomatal responses and biochemical acclimation of plants to environments changing on multiple timescales. Tested with experimental data from 18 species, our model successfully predicts the simultaneous decline in carbon assimilation rate, stomatal conductance and photosynthetic capacity during progressive soil drought. It also correctly predicts the dependencies of gas exchange on atmospheric vapour pressure deficit, temperature and CO₂. Model predictions are also consistent with widely observed empirical patterns, such as the distribution of hydraulic strategies. Our unified theory opens new avenues for reliably modelling the interactive effects of drying soil and rising atmospheric CO₂ on global photosynthesis and transpiration.

Stem notching decreases stem hydraulic conductance but does not influence drought impacts and post-drought recovery in Scots pine and Norway spruce

The tight connection between the deterioration of xylem function and plant mortality under drought is well recognized. However, a lack of mechanistic understanding of how substantial conductivity loss influences plant performance under drought and during post-drought recovery hinders our ability to model tree responses to drought stress. We artificially induced a loss of 50% of xylem conducting area in Scots pine and Norway spruce saplings by stem notching and investigated plant performance under drought and during post-drought recovery. Plant mortality, xylem hydraulic conductivity, leaf water status and stomatal conductance were measured. We observed no preferential mortality of top plant parts (above the notches) compared to basal plant parts (below the notches), and no consistent trend in hydraulic conductivity loss was observed between top and basal parts of dying plants. Stem hydraulic conductivity, water status of the needles and stomatal conductance changed similarly between the top and basal parts during drought and post-drought recovery, which indicated the substantial hydraulic overcapacity of the stems. The recovery of stomatal conductance demonstrated prominent hysteresis due to non-hydraulic stomatal limitations. The results obtained are highly important for modelling the influence of plant hydraulic impairment on plant performance under drought and during post-drought recovery.

Physiological trait networks enhance understanding of crop growth and water use in contrasting environments

Plant function arises from a complex network of structural and physiological traits. Explicit representation of these traits, as well as their connections with other biophysical processes, is required to advance our understanding of plant-soil-climate interactions. We used the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Net primary productivity (NPP) and grain yield were simulated across five contrasting climate scenarios. Simulations achieving high NPP and grain yield in high precipitation environments featured trait networks conferring high water use strategies: deep roots, high stomatal conductance at low water potential ("risky" stomatal regulation), high xylem hydraulic conductivity and high maximal leaf area index. In contrast, high NPP and grain yield was achieved in dry environments with low late-season precipitation via water conserving trait networks: deep roots, high embolism resistance and low stomatal conductance at low leaf water potential ("conservative" stomatal regulation). We suggest that our approach, which allows for the simultaneous evaluation of physiological traits, soil characteristics and their interactions (i.e., networks), has potential to improve our understanding of crop performance in different environments. In contrast, evaluating single traits in isolation of other coordinated traits does not appear to be an effective strategy for predicting plant performance.

Predicting resilience through the lens of competing adjustments to vegetation function

There is a pressing need to better understand ecosystem resilience to droughts and heatwaves. Eco-evolutionary optimization approaches have been proposed as means to build this understanding in land surface models and improve their predictive capability, but competing approaches are yet to be tested together. Here, we coupled approaches that optimize canopy gas exchange and leaf nitrogen investment, respectively, extending both approaches to account for hydraulic impairment. We assessed model predictions using observations from a native Eucalyptus woodland that experienced repeated droughts and heatwaves between 2013 and 2020, whilst exposed to an elevated [CO₂ ] treatment. Our combined approaches improved predictions of transpiration and enhanced the simulated magnitude of the CO₂ fertilization effect on gross primary productivity. The competing approaches also worked consistently along axes of change in soil moisture, leaf area, and [CO₂ ]. Despite predictions of a significant percentage loss of hydraulic conductivity due to embolism (PLC) in 2013, 2014, 2016, and 2017 (99th percentile PLC > 45%), simulated hydraulic legacy effects were small and short-lived (2 months). Our analysis suggests that leaf shedding and/or suppressed foliage growth formed a strategy to mitigate drought risk. Accounting for foliage responses to water availability has the potential to improve model predictions of ecosystem resilience.

The influence of increasing atmospheric CO2 , temperature, and vapor pressure deficit on seawater-induced tree mortality

Increasing seawater exposure is killing coastal trees globally, with expectations of accelerating mortality with rising sea levels. However, the impact of concomitant changes in atmospheric CO₂ concentration, temperature, and vapor pressure deficit (VPD) on seawater-induced tree mortality is uncertain. We examined the mechanisms of seawater-induced mortality under varying climate scenarios using a photosynthetic gain and hydraulic cost optimization model validated against observations in a mature stand of Sitka spruce (Picea sitchensis) trees in the Pacific Northwest, USA, that were dying from recent seawater exposure. The simulations matched well with observations of photosynthesis, transpiration, nonstructural carbohydrates concentrations, leaf water potential, the percentage loss of xylem conductivity, and stand-level mortality rates. The simulations suggest that seawater-induced mortality could decrease by c. 16.7% with increasing atmospheric CO₂ levels due to reduced risk of carbon starvation. Conversely, rising VPD could increase mortality by c. 5.6% because of increasing risk of hydraulic failure. Across all scenarios, seawater-induced mortality was driven by hydraulic failure in the first 2 yr after seawater exposure began, with carbon starvation becoming more important in subsequent years. Changing CO₂ and climate appear unlikely to have a significant impact on coastal tree mortality under rising sea levels.

Plasticity in stomatal behaviour across a gradient of water supply is consistent among field-grown maize inbred lines with varying stomatal patterning

Stomata regulate leaf CO₂ assimilation (A) and water loss. The Ball-Berry and Medlyn models predict stomatal conductance (g_s ) with a slope parameter (m or g₁ ) that reflects the sensitivity of g_s to A, atmospheric CO₂  and humidity, and is inversely related to water use efficiency (WUE). This study addressed knowledge gaps about what the values of m and g₁ are in C₄ crops under field conditions, as well as how they vary among genotypes and with drought stress. Four inbred maize genotypes were unexpectedly consistent in how m and g₁ decreased as water supply decreased. This was despite genotypic variation in stomatal patterning, A and g_s . m and g₁ were strongly correlated with soil water content, moderately correlated with predawn leaf water potential (Ψ_pd ), but not correlated with midday leaf water potential (Ψ_md ). This implied that m and g₁ respond to long-term water supply more than short-term drought stress. The conserved nature of m and g₁ across anatomically diverse genotypes and water supplies suggests there is flexibility in structure-function relationships underpinning WUE. This evidence can guide the simulation of maize g_s across a range of water supply in the primary maize growing region and inform efforts to improve WUE.

Towards species-level forecasts of drought-induced tree mortality risk

Predicting species-level responses to drought at the landscape scale is critical to reducing uncertainty in future terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and parameterised the model for 15 canopy dominant eucalypt tree species across South-Eastern Australia (mean annual precipitation range: 344-1424 mm yr^-1 ). We conducted three experiments: applying CABLE to the 2017-2019 drought; a 20% drier drought; and a 20% drier drought with a doubling of atmospheric carbon dioxide (CO₂ ). The severity of the drought was highlighted as for at least 25% of their distribution ranges, 60% of species experienced leaf water potentials beyond the water potential at which 50% of hydraulic conductivity is lost due to embolism. We identified areas of severe hydraulic stress within-species' ranges, but we also pinpointed resilience in species found in predominantly semiarid areas. The importance of the role of CO₂ in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of individual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or net-zero emission strategies.

Stomatal responses of Eucalyptus spp. under drought can be predicted with a gain-risk optimization model

The frequency and severity of drought events are expected to increase due to climate change, with optimal environmental conditions for forestry likely to shift. Modeling plant responses to a changing climate is therefore vital. We tested the process-based gain-risk model to predict stomatal responses to drought of two Eucalyptus hybrids. The process-based gain-risk model has the advantage that all the parameters used within the model are based on measurable plant traits. The gain-risk model proposes that plants optimize photosynthetic gain while minimizing a hydraulic cost. Previous versions of the model used hydraulic risk as a cost function; however, they did not account for delayed or reduced hydraulic recovery rates from embolism post-drought. Hydraulic recovery has been seen in many species, however it is still unclear how this inclusion of a partial or delayed hydraulic recovery would affect the predictive power of the gain-risk model. Many hydraulic parameters required by the model are also difficult to measure and are not freely available. We therefore tested a simplified gain-risk model that includes a delayed or reduced hydraulic recovery component post-drought. The simplified gain-risk model performed well at predicting stomatal responses in both Eucalyptus grandis × camaldulensis (GC) and Eucalyptus urophylla × grandis (UG). In this study two distinct strategies were seen between GC and UG, with GC being more resistant to embolism formation, however it could not recover hydraulic conductance compared with UG. The inclusion of a delayed or reduced hydraulic recovery component slightly improved model predictions for GC, however not for UG, which can be related to UG being able to recover lost hydraulic conductance and therefore can maintain stomatal conductance regardless of hydraulic risk. Even though the gain-risk model shows promise in predicting plant responses, more information is needed regarding hydraulic recovery after drought.

Analysis of Plant Water Transport Mechanism and Water Requirement for Growth Based on the Effect of Thermal Environment

This paper put forward a model for calculating the water requirements of plants, including a transpiration model, stem water delivery model, and root water uptake model. The results showed that the model had good accuracy. The relative error between simulated values and measured values was 2.09%–14.13%. The limiting effects of stem water delivery capacity and root water uptake capacity on plant–water relations were analyzed. When the transpiration rate is large, even if there is enough root water uptake capacity, the limited stem water delivery capacity may affect the plant–water relationship. In order to understand the relationship between a plant and the thermal environment, the effect of the thermal environment on a plant’s water requirements was analyzed, and the effect of air temperature was obvious. Under the simulated condition, when the air temperature increased from 0 °C to 40 °C, the water requirement of an apple tree increased from 0.0134 L/h to 33.8 L/h.

Integrating plant physiology and community ecology across scales through trait-based models to predict drought mortality

Forests are a critical carbon sink and widespread tree mortality resulting from climate-induced drought stress has the potential to alter forests from a carbon sink to a source, causing a positive feedback on climate change. Process-based vegetation models aim to represent the current understanding of the underlying mechanisms governing plant physiological and ecological responses to climate. Yet model accuracy varies across scales, and regional-scale model predictive skill is frequently poor when compared with observations of drought-driven mortality. I propose a framework that leverages differences in model predictive skill across spatial scales, mismatches between model predictions and observations, and differences in the mechanisms included and absent across models to advance the understanding of the physiological and ecological processes driving observed patterns drought-driven mortality.

Turgor-limited predictions of tree growth, height and metabolic scaling over tree lifespans

Increasing evidence suggests that tree growth is sink-limited by environmental and internal controls rather than by carbon availability. However, the mechanisms underlying sink-limitations are not fully understood and thus not represented in large-scale vegetation models. We develop a simple, analytically solved, mechanistic, turgor-driven growth model (TDGM) and a phloem transport model (PTM) to explore the mechanics of phloem transport and evaluate three hypotheses. First, phloem transport must be explicitly considered to accurately predict turgor distributions and thus growth. Second, turgor-limitations can explain growth-scaling with size (metabolic scaling). Third, turgor can explain realistic growth rates and increments. We show that mechanistic, sink-limited growth schemes based on plant turgor limitations are feasible for large-scale model implementations with minimal computational demands. Our PTM predicted nearly uniform sugar concentrations along the phloem transport path regardless of phloem conductance, stem water potential gradients and the strength of sink-demands contrary to our first hypothesis, suggesting that phloem transport is not limited generally by phloem transport capacity per se but rather by carbon demand for growth and respiration. These results enabled TDGM implementation without explicit coupling to the PTM, further simplifying computation. We test the TDGM by comparing predictions of whole-tree growth rate to well-established observations (site indices) and allometric theory. Our simple TDGM predicts realistic tree heights, growth rates and metabolic scaling over decadal to centurial timescales, suggesting that tree growth is generally sink and turgor limited. Like observed trees, our TDGM captures tree-size- and resource-based deviations from the classical ¾ power-law metabolic scaling for which turgor is responsible.

The Native Arbuscular Mycorrhizal Fungi and Vermicompost-Based Organic Amendments Enhance Soil Fertility, Growth Performance, and the Drought Stress Tolerance of Quinoa

The present study aimed to determine the effects of biostimulants on the physicochemical parameters of the agricultural soil of quinoa under two water regimes and to understand the mode of action of the biostimulants on quinoa for drought adaptation. We investigated the impact of two doses of vermicompost (5 and 10 t/ha) and arbuscular mycorrhizal fungi applied individually, or in joint application, on attenuating the negative impacts of water shortage and improving the agro-physiological and biochemical traits of quinoa, as well as soil fertility, under two water regimes (well-watered and drought stress) in open field conditions. Exposure to drought decreased biomass, leaf water potential, and stomatal conductance, and increased malondialdehyde and hydrogen peroxide content. Mycorrhiza and/or vermicompost promoted plant growth by activating photosynthesis machinery and nutrient assimilation, leading to increased total soluble sugars, proteins, and antioxidant enzyme activities in the leaf and root. After the experiment, the soil's total organic matter, phosphorus, nitrogen, calcium, and soil glomalin content improved by the single or combined application of mycorrhiza and vermicompost. This knowledge suggests that the combination of mycorrhiza and vermicompost regulates the physiological and biochemical processes employed by quinoa in coping with drought and improves the understanding of soil-plant interaction.

Stability of tropical forest tree carbon-water relations in a rainfall exclusion treatment through shifts in effective water uptake depth

Increasing severity and frequency of drought is predicted for large portions of the terrestrial biosphere, with major impacts already documented in wet tropical forests. Using a 4-year rainfall exclusion experiment in the Daintree Rainforest in northeast Australia, we examined canopy tree responses to reduced precipitation and soil water availability by quantifying seasonal changes in plant hydraulic and carbon traits for 11 tree species between control and drought treatments. Even with reduced soil volumetric water content in the upper 1 m of soil in the drought treatment, we found no significant difference between treatments for predawn and midday leaf water potential, photosynthesis, stomatal conductance, foliar stable carbon isotope composition, leaf mass per area, turgor loss point, xylem vessel anatomy, or leaf and stem nonstructural carbohydrates. While empirical measurements of aboveground traits revealed homeostatic maintenance of plant water status and traits in response to reduced soil moisture, modeled belowground dynamics revealed that trees in the drought treatment shifted the depth from which water was acquired to deeper soil layers. These findings reveal that belowground acclimation of tree water uptake depth may buffer tropical rainforests from more severe droughts that may arise in future with climate change.

To what extent can rising [CO2 ] ameliorate plant drought stress?

Plant responses to elevated atmospheric carbon dioxide (eCO₂ ) have been hypothesized as a key mechanism that may ameliorate the impact of future drought. Yet, despite decades of experiments, the question of whether eCO₂ reduces plant water use, yielding 'water savings' that can be used to maintain plant function during periods of water stress, remains unresolved. In this Viewpoint, we identify the experimental challenges and limitations to our understanding of plant responses to drought under eCO₂ . In particular, we argue that future studies need to move beyond exploring whether eCO₂ played 'a role' or 'no role' in responses to drought, but instead more carefully consider the timescales and conditions that would induce an influence. We also argue that considering emergent differences in soil water content may be an insufficient means of assessing the impact of eCO₂ . We identify eCO₂ impact during severe drought (e.g. to the point of mortality), interactions with future changes in vapour pressure deficit and uncertainty about changes in leaf area as key gaps in our current understanding. New insights into CO₂  × drought interactions are essential to better constrain model theory that governs future climate model projections of land-atmosphere interactions during periods of water stress.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

Coupled whole-tree optimality and xylem hydraulics explain dynamic biomass partitioning

Trees partition biomass in response to resource limitation and physiological activity. It is presumed that these strategies evolved to optimize some measure of fitness. If the optimization criterion can be specified, then allometry can be modeled from first principles without prescribed parameterization. We present the Tree Hydraulics and Optimal Resource Partitioning (THORP) model, which optimizes allometry by estimating allocation fractions to organs as proportional to their ratio of marginal gain to marginal cost, where gain is net canopy photosynthesis rate, and costs are senescence rates. Root total biomass and profile shape are predicted simultaneously by a unified optimization. Optimal partitioning is solved by a numerically efficient analytical solution. THORP's predictions agree with reported tree biomass partitioning in response to size, water limitations, elevated CO₂ and pruning. Roots were sensitive to soil moisture profiles and grew down to the groundwater table when present. Groundwater buffered against water stress regardless of meteorology, stabilizing allometry and root profiles as deep as c. 30 m. Much of plant allometry can be explained by hydraulic considerations. However, nutrient limitations cannot be fully ignored. Rooting mass and profiles were synchronized with hydrological conditions and groundwater even at considerable depths, illustrating that the below ground shapes whole-tree allometry.

Understanding and predicting forest mortality in the western United States using long-term forest inventory data and modeled hydraulic damage

Global warming is expected to exacerbate the duration and intensity of droughts in the western United States, which may lead to increased tree mortality. A prevailing proximal mechanism of drought-induced tree mortality is hydraulic damage, but predicting tree mortality from hydraulic theory and climate data still remains a major scientific challenge. We used forest inventory data and a plant hydraulic model (HM) to address three questions: can we capture regional patterns of drought-induced tree mortality with HM-predicted damage thresholds; do HM metrics improve predictions of mortality across broad spatial areas; and what are the dominant controls of forest mortality when considering stand characteristics, climate metrics, and simulated hydraulic stress? We found that the amount of variance explained by models predicting mortality was limited (R² median = 0.10, R² range: 0.00-0.52). HM outputs, including hydraulic damage and carbon assimilation diagnostics, moderately improve mortality prediction across the western US compared with models using stand and climate predictors alone. Among factors considered, metrics of stand density and tree size tended to be some of the most critical factors explaining mortality, probably highlighting the important roles of structural overshoot, stand development, and biotic agent host selection and outbreaks in mortality patterns.

Optimization theory explains nighttime stomatal responses

Nocturnal transpiration is widely observed across species and biomes, and may significantly impact global water, carbon, and energy budgets. However, it remains elusive why plants lose water at night and how to model it at large scales. We hypothesized that plants optimize nighttime leaf diffusive conductance (g_wn ) to balance potential daytime photosynthetic benefits and nocturnal transpiration benefits. We quantified nighttime benefits from respiratory reductions due to evaporative leaf cooling. We described nighttime costs in terms of a reduced carbon gain during the day because of water use at night. We measured nighttime stomatal responses and tested our model with water birch (Betula occidentalis) saplings grown in a glasshouse. The g_wn of water birch decreased with drier soil, higher atmospheric CO₂ , wetter air, lower leaf temperature, and lower leaf respiration rate. Our model predicted all these responses correctly, except for the response of g_wn to air humidity. Our results also suggested that the slow decrease in g_wn after sunset could be associated with decreasing leaf respiration. The optimality-based nocturnal transpiration model smoothly integrates with daytime stomatal optimization approaches, and thus has the potential to quantitatively predict nocturnal transpiration across space and time.

Plant traits controlling growth change in response to a drier climate

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.

Root vascular traits differ systematically between African savanna tree and grass species, with implications for water use

PREMISE

Belowground functional traits play a significant role in determining plant water-use strategies and plant performance, but we lack data on root traits across communities, particularly in the tropical savanna biome, where vegetation dynamics are hypothesized to be strongly driven by tree-grass functional differences in water use.

METHODS

We grew seedlings of 21 tree and 18 grass species (N = 5 individuals per species) from the southern African savanna biome under greenhouse conditions and collected fine-root segments from plants for histological analysis. We identified and measured xylem vessels in 539 individual root cross sections. We then quantified six root vascular anatomy traits and tested them for phylogenetic signals and tree-grass differences in trait values associated with vessel size, number, and hydraulic conductivity.

RESULTS

Grass roots had larger root xylem vessels than trees, a higher proportion of their root cross-sectional area comprised vessels, and they had higher estimated axial conductivities than trees, while trees had a higher number of vessels per root cross-sectional area than grasses did. We found evidence of associations between trait values and phylogenetic relatedness in most of these traits across tree species, but not grasses.

CONCLUSIONS

Our findings support the hypothesis that grass roots have higher water transport capacity than tree roots in terms of maximum axial conductivity, consistent with the observation that grasses are more "aggressive" water users than trees under conditions of high soil moisture availability. Our study identifies root functional traits that may drive differential responses of trees and grasses to soil moisture availability.

Identifying areas at risk of drought-induced tree mortality across South-Eastern Australia

South-East Australia has recently been subjected to two of the worst droughts in the historical record (Millennium Drought, 2000-2009 and Big Dry, 2017-2019). Unfortunately, a lack of forest monitoring has made it difficult to determine whether widespread tree mortality has resulted from these droughts. Anecdotal observations suggest the Big Dry may have led to more significant tree mortality than the Millennium drought. Critically, to be able to robustly project future expected climate change effects on Australian vegetation, we need to assess the vulnerability of Australian trees to drought. Here we implemented a model of plant hydraulics into the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterized the drought response behaviour of five broad vegetation types, based on a common garden dry-down experiment with species originating across a rainfall gradient (188-1,125 mm/year) across South-East Australia. The new hydraulics model significantly improved (~35%-45% reduction in root mean square error) CABLE's previous predictions of latent heat fluxes during periods of water stress at two eddy covariance sites in Australia. Landscape-scale predictions of the greatest percentage loss of hydraulic conductivity (PLC) of about 40%-60%, were broadly consistent with satellite estimates of regions of the greatest change in both droughts. In neither drought did CABLE predict that trees would have reached critical PLC in widespread areas (i.e. it projected a low mortality risk), although the model highlighted critical levels near the desert regions of South-East Australia where few trees live. Overall, our experimentally constrained model results imply significant resilience to drought conferred by hydraulic function, but also highlight critical data and scientific gaps. Our approach presents a promising avenue to integrate experimental data and make regional-scale predictions of potential drought-induced hydraulic failure.

A theoretical and empirical assessment of stomatal optimization modeling

Optimal stomatal control models have shown great potential in predicting stomatal behavior and improving carbon cycle modeling. Basic stomatal optimality theory posits that stomatal regulation maximizes the carbon gain relative to a penalty of stomatal opening. All models take a similar approach to calculate instantaneous carbon gain from stomatal opening (the gain function). Where the models diverge is in how they calculate the corresponding penalty (the penalty function). In this review, we compare and evaluate 10 different optimization models in how they quantify the penalty and how well they predict stomatal responses to the environment. We evaluate models in two ways. First, we compare their penalty functions against seven criteria that ensure a unique and qualitatively realistic solution. Second, we quantitatively test model against multiple leaf gas-exchange datasets. The optimization models with better predictive skills have penalty functions that meet our seven criteria and use fitting parameters that are both few in number and physiology based. The most skilled models are those with a penalty function based on stress-induced hydraulic failure. We conclude by proposing a new model that has a hydraulics-based penalty function that meets all seven criteria and demonstrates a highly predictive skill against our test datasets.

Plant profit maximization improves predictions of European forest responses to drought

Knowledge of how water stress impacts the carbon and water cycles is a key uncertainty in terrestrial biosphere models. We tested a new profit maximization model, where photosynthetic uptake of CO₂ is optimally traded against plant hydraulic function, as an alternative to the empirical functions commonly used in models to regulate gas exchange during periods of water stress. We conducted a multi-site evaluation of this model at the ecosystem scale, before and during major droughts in Europe. Additionally, we asked whether the maximum hydraulic conductance in the soil-plant continuum k_max (a key model parameter which is not commonly measured) could be predicted from long-term site climate. Compared with a control model with an empirical soil moisture function, the profit maximization model improved the simulation of evapotranspiration during the growing season, reducing the normalized mean square error by c. 63%, across mesic and xeric sites. We also showed that k_max could be estimated from long-term climate, with improvements in the simulation of evapotranspiration at eight out of the 10 forest sites during drought. Although the generalization of this approach is contingent upon determining k_max , it presents a mechanistic trait-based alternative to regulate canopy gas exchange in global models.

Plant responses to rising vapor pressure deficit

Recent decades have been characterized by increasing temperatures worldwide, resulting in an exponential climb in vapor pressure deficit (VPD). VPD has been identified as an increasingly important driver of plant functioning in terrestrial biomes and has been established as a major contributor in recent drought-induced plant mortality independent of other drivers associated with climate change. Despite this, few studies have isolated the physiological response of plant functioning to high VPD, thus limiting our understanding and ability to predict future impacts on terrestrial ecosystems. An abundance of evidence suggests that stomatal conductance declines under high VPD and transpiration increases in most species up until a given VPD threshold, leading to a cascade of subsequent impacts including reduced photosynthesis and growth, and higher risks of carbon starvation and hydraulic failure. Incorporation of photosynthetic and hydraulic traits in 'next-generation' land-surface models has the greatest potential for improved prediction of VPD responses at the plant- and global-scale, and will yield more mechanistic simulations of plant responses to a changing climate. By providing a fully integrated framework and evaluation of the impacts of high VPD on plant function, improvements in forecasting and long-term projections of climate impacts can be made.

Stomatal optimization based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate

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.

Forecasting semi-arid biome shifts in the Anthropocene

Shrub encroachment, forest decline and wildfires have caused large-scale changes in semi-arid vegetation over the past 50 years. Climate is a primary determinant of plant growth in semi-arid ecosystems, yet it remains difficult to forecast large-scale vegetation shifts (i.e. biome shifts) in response to climate change. We highlight recent advances from four conceptual perspectives that are improving forecasts of semi-arid biome shifts. Moving from small to large scales, first, tree-level models that simulate the carbon costs of drought-induced plant hydraulic failure are improving predictions of delayed-mortality responses to drought. Second, tracer-informed water flow models are improving predictions of species coexistence as a function of climate. Third, new applications of ecohydrological models are beginning to simulate small-scale water movement processes at large scales. Fourth, remotely-sensed measurements of plant traits such as relative canopy moisture are providing early-warning signals that predict forest mortality more than a year in advance. We suggest that a community of researchers using modeling approaches (e.g. machine learning) that can integrate these perspectives will rapidly improve forecasts of semi-arid biome shifts. Better forecasts can be expected to help prevent catastrophic changes in vegetation states by identifying improved monitoring approaches and by prioritizing high-risk areas for management.

Linking water relations and hydraulics with photosynthesis

For land plants, water is the principal governor of growth. Photosynthetic performance is highly dependent on the stable and suitable water status of leaves, which is balanced by the water transport capacity, the water loss rate as well as the water capacitance of the plant. This review discusses the links between leaf water status and photosynthesis, specifically focussing on the coordination of CO₂ and water transport within leaves, and the potential role of leaf capacitance and elasticity on CO₂ and water transport.

The response of stomatal conductance to seasonal drought in tropical forests

Stomata regulate CO₂ uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (g_s ) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.e. a measure of intrinsic plant water-use-efficiency), is still limited, particularly in the tropics. Here we collected diurnal measurements of leaf gas exchange and leaf water potential (Ψ_leaf ), and a suite of plant traits from the upper canopy of 15 tropical trees in two contrasting Panamanian forests throughout the dry season of the 2016 El Niño. The plant traits included wood density, leaf-mass-per-area (LMA), leaf carboxylation capacity (V_c,max ), leaf water content, the degree of isohydry, and predawn Ψ_leaf . We first investigated how the choice of four commonly used leaf-level g_s models with and without the inclusion of Ψ_leaf as an additional predictor variable influence the ability to predict g_s , and then explored the abiotic (i.e. month, site-month interaction) and biotic (i.e. tree-species-specific characteristics) drivers of slope parameter variation. Our results show that the inclusion of Ψ_leaf did not improve model performance and that the models that represent the response of g_s to vapor pressure deficit performed better than corresponding models that respond to relative humidity. Within each g_s model, we found large variation in the slope parameter, and this variation was attributable to the biotic driver, rather than abiotic drivers. We further investigated potential relationships between the slope parameter and the six available plant traits mentioned above, and found that only one trait, LMA, had a significant correlation with the slope parameter (R²  = 0.66, n = 15), highlighting a potential path towards improved model parameterization. This study advances understanding of g_s dynamics over seasonal drought, and identifies a practical, trait-based approach to improve modeling of carbon and water exchange in tropical forests.

Optimal stomatal drought response shaped by competition for water and hydraulic risk can explain plant trait covariation

The classical theory of stomatal optimization stipulates that stomata should act to maximize photosynthesis while minimizing transpiration. This theory, despite its remarkable success in reproducing empirical patterns, does not account for the fact that the available water to plants is dynamically regulated by plants themselves, and that plants compete for water in most locations. Here, we develop an alternative theory in which plants maximize the expected carbon gain under stochastic rainfall in a competitive environment. We further incorporate xylem hydraulic limitation as an additional constraint to transpiration and evaluate its impacts on stomatal optimization by incorporating the direct carbon cost of xylem recovery and the opportunity cost of reduced future photosynthesis as a result of irrecoverable xylem damage. We predict stomatal behaviour to be more conservative with a higher cost induced by xylem damage. By varying the unit carbon cost and extent of xylem recovery, characterizing the direct and opportunity cost of xylem damage, respectively, our model can reproduce several key patterns of stomatal-hydraulic trait covariations. By addressing the key elements of water limitation in plant gas exchange simultaneously, including plants' self-regulation of water availability, competition for water and hydraulic risk, our study provides a comprehensive theoretical basis for understanding stomatal behaviour.

Competition and Drought Alter Optimal Stomatal Strategy in Tree Seedlings

A better understanding of plant stomatal strategies holds strong promise for improving predictions of vegetation responses to drought because stomata are the primary mechanism through which plants mitigate water stress. It has been assumed that plants regulate stomata to maintain a constant marginal water use efficiency and forego carbon gain when water is scarce. However, recent hypotheses pose that plants maximize carbon assimilation while also accounting for the risk of hydraulic damage via cavitation and hydraulic failure. This "gain-risk" framework incorporates competition in stomatal regulation because it takes into account that neighboring plants can "steal" unused water. This study utilizes stomatal models representing both the water use efficiency and carbon-maximization frameworks, and empirical data from three species in a potted growth chamber experiment, to investigate the effects of drought and competition on seedling stomatal strategy. We found that drought and competition responses in the empirical data were best explained by the carbon-maximization hypothesis and that both drought and competition affected stomatal strategy. Interestingly, stomatal responses differed substantially by species, with seedlings employing a riskier strategy when planted with a high water use competitor, and seedlings employing a more conservative strategy when planted with a low water use competitor. Lower water users in general had less stomatal sensitivity to decreasing Ψ _L compared to moderate to high water users. Repeated water stress also resulted in legacy effects on plant stomatal behavior, increasing stomatal sensitivity (i.e., conservative behavior) even when the seedling was returned to well-watered conditions. These results indicate that stomatal strategies are dynamic and change with climate and competition stressors. Therefore, incorporating mechanisms that allow for stomatal behavioral changes in response to water limitation may be an important step to improving carbon cycle projections in coupled climate-Earth system models.

A Dynamic Model for Strategies and Dynamics of Plant Water-Potential Regulation Under Drought Conditions

Vegetation responds to drought through a complex interplay of plant hydraulic mechanisms, posing challenges for model development and parameterization. We present a mathematical model that describes the dynamics of leaf water-potential over time while considering different strategies by which plant species regulate their water-potentials. The model has two parameters: the parameter λ describing the adjustment of the leaf water potential to changes in soil water potential, and the parameter Δψ_ww describing the typical 'well-watered' leaf water potentials at non-stressed (near-zero) levels of soil water potential. Our model was tested and calibrated on 110 time-series datasets containing the leaf- and soil water potentials of 66 species under drought and non-drought conditions. Our model successfully reproduces the measured leaf water potentials over time based on three different regulation strategies under drought. We found that three parameter sets derived from the measurement data reproduced the dynamics of 53% of an drought dataset, and 52% of a control dataset [root mean square error (RMSE) < 0.5 MPa)]. We conclude that, instead of quantifying water-potential-regulation of different plant species by complex modeling approaches, a small set of parameters may be sufficient to describe the water potential regulation behavior for large-scale modeling. Thus, our approach paves the way for a parsimonious representation of the full spectrum of plant hydraulic responses to drought in dynamic vegetation models.

Remote sensing and modeling fusion for investigating the ecosystem water-carbon coupling processes

The water and carbon cycles are tightly linked and play a key role in the material and energy flows between terrestrial ecosystems and the atmosphere, but the interactions of water and carbon cycles are not quite clear. The global climate change and intensive human activities could also complicate the water and carbon coupling processes. Better understanding the coupled water-carbon cycles and their spatiotemporal evolution can inform management and decision-making efforts regarding carbon uptake, food production, water resources, and climate change. The integration of remote sensing and numeric modeling is an attractive approach to address the challenge. Remote sensing can provide extensive data for a number of variables at regional scale and support models, whereas process-based modeling can facilitate investigating the processes that remote sensing cannot well handle (e.g., below-ground and lateral material movement) and backcast/forecast the impacts of environmental change. Over the past twenty years, an increasing number of studies using a variety of remote sensing products together with numeric models have examined the water-carbon interactions. This article reviewed the methodologies for integrating remote sensing data into these models and the modeling of water-carbon coupling processes. We first summarized the major remote sensing datasets and models used for studying the coupled water-carbon cycles. We then provided an overview of the methods for integrating remote sensing data into water-carbon models, and discussed their strengths and challenges. We also prospected the development of potential new remote sensing datasets, modeling methods, and their potential applications in the field of eco-hydrology.

Leveraging plant hydraulics to yield predictive and dynamic plant leaf allocation in vegetation models with climate change

Plant functional traits provide a link in process-based vegetation models between plant-level physiology and ecosystem-level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large-scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re-evaluation of trait-based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type-specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.

The impact of rising CO2 and acclimation on the response of US forests to global warming

The response of forests to climate change depends in part on whether the photosynthetic benefit from increased atmospheric CO₂ (∆C_a = future minus historic CO₂) compensates for increased physiological stresses from higher temperature (∆T). We predicted the outcome of these competing responses by using optimization theory and a mechanistic model of tree water transport and photosynthesis. We simulated current and future productivity, stress, and mortality in mature monospecific stands with soil, species, and climate sampled from 20 continental US locations. We modeled stands with and without acclimation to ∆C_a and ∆T, where acclimated forests adjusted leaf area, photosynthetic capacity, and stand density to maximize productivity while avoiding stress. Without acclimation, the ∆C_a-driven boost in net primary productivity (NPP) was compromised by ∆T-driven stress and mortality associated with vascular failure. With acclimation, the ∆C_a-driven boost in NPP and stand biomass (C storage) was accentuated for cooler futures but negated for warmer futures by a ∆T-driven reduction in NPP and biomass. Thus, hotter futures reduced forest biomass through either mortality or acclimation. Forest outcomes depended on whether projected climatic ∆C_a/∆T ratios were above or below physiological thresholds that neutralized the negative impacts of warming. Critically, if forests do not acclimate, the ∆C_a/∆T must be above ca 89 ppm⋅°C^-1 to avoid chronic stress, a threshold met by 55% of climate projections. If forests do acclimate, the ∆C_a/∆T must rise above ca 67 ppm⋅°C^-1 for NPP and biomass to increase, a lower threshold met by 71% of projections.