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Drought-induced productivity reductions and tree mortality have been increasing in recent decades in forests around the globe. Developing adaptation strategies hinges on an adequate understanding of the mechanisms governing the drought vulnerability of forest stands. Prescribed reduction in stand density has been used as a management tool to reduce water stress and wildfire risk, but the processes that modulate fine-scale variations in plant water supply and water demand are largely missing in ecosystem models. We used an ecohydrological model that couples plant hydraulics with groundwater hydrology to examine how within-stand variations in tree spatial arrangements and topography might mitigate forest vulnerability to drought at individual-tree and stand scales. Our results demonstrated thinning generally ameliorated plant hydraulic stress and improved carbon and water fluxes of the remaining trees, although the effectiveness varied by climate and topography. Variable thinning that adjusted thinning intensity based on topography-mediated water availability achieved higher stand productivity and lower mortality risk, compared to evenly-spaced thinning at comparable intensities. The results from numerical experiments provided mechanistic evidence that topography mediates the effectiveness of thinning and highlighted the need for an explicit consideration of within-stand heterogeneity in trees and abiotic environments when designing forest thinning to mitigate drought impacts.

 

Abstract Forest mortality has been widely observed across the globe during recent episodes of drought and extreme heat events. But the future of forest mortality remains poorly understood. While the direct effects of future climate and elevated CO 2 on forest mortality risk have been studied, the role of lateral subsurface water flow has rarely been considered. Here we demonstrated the fingerprint of lateral flow on the forest mortality risk of a riparian ecosystem using a coupled plant hydraulics-hydrology model prescribed with multiple Earth System Model projections of future hydroclimate. We showed that the anticipated water-saving and drought ameliorating effects of elevated CO 2 on mortality risk were largely compromised when lateral hydrological processes were considered. Further, we found lateral flow reduce ecosystem sensitivity to climate variations, by removing soil water excess during wet periods and providing additional water from groundwater storage during dry periods. These findings challenge the prevailing expectation of elevated CO 2 to reduce mortality risk and highlight the need to assess the effects of lateral flow exchange more explicitly moving forward with forest mortality projections. 

The response of forests to climate change depends in part on whether the photosynthetic benefit from increased atmospheric CO 2 (∆C a = future minus historic CO 2 ) 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. 

This article is a Commentary onElleret al.,226: 1622–1637, andSabotet al.,226: 1638–1655.

 

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi‐empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi‐arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big‐leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

 

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.

 

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 CO₂and 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 the genetic and physiological basis of abiotic stress tolerance under field conditions is key to varietal crop improvement in the face of climate variability. Here, we investigate dynamic physiological responses to water stressin silicoand their relationships to genotypic variation in hydraulic traits of cotton (Gossypium hirsutum), an economically important species for renewable textile fiber production.

In conjunction with an ecophysiological process‐based model, heterogeneous data (plant hydraulic traits, spatially‐distributed soil texture, soil water content and canopy temperature) were used to examine hydraulic characteristics of cotton, evaluate their consequences on whole plant performance under drought, and explore potential genotype × environment effects.

Cotton was found to have R‐shaped hydraulic vulnerability curves (VCs), which were consistent under drought stress initiated at flowering. Stem VCs, expressed as percent loss of conductivity, differed across genotypes, whereas root VCs did not. Simulation results demonstrated how plant physiological stress can depend on the interaction between soil properties and irrigation management, which in turn affect genotypic rankings of transpiration in a time‐dependent manner.

Our study shows how a process‐based modeling framework can be used to link genotypic variation in hydraulic traits to differential acclimating behaviors under drought.