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Observations show vulnerability segmentation between stems and leaves is highly variable within and between environments. While a number of species exhibit conventional vulnerability segmentation (stem leaf ), others exhibit no vulnerability segmentation and others reverse vulnerability segmentation (stem leaf ). We developed a hydraulic model to test hypotheses about vulnerability segmentation and how it interacts with other traits to impact plant conductance. We do this using a series of experiments across a broad parameter space and with a case study of two species with contrasting vulnerability segmentation patterns:Quercus douglasiiandPopulus trichocarpa. We found that while conventional vulnerability segmentation helps to preserve conductance in stem tissues, reverse vulnerability segmentation can better maintain conductance across the combined stem‐leaf hydraulic pathway, particularly when plants have more vulnerable s and have hydraulic segmentation with greater resistance in the leaves. These findings show that the impacts of vulnerability segmentation are dependent upon other plant traits, notably hydraulic segmentation, a finding that could assist in the interpretation of variable observations of vulnerability segmentation. Further study is needed to examine how vulnerability segmentation impacts transpiration rates and recovery from water stress.

 

Stomata have recently been theorized to have evolved strategies that maximize turgor-driven growth over plants’ lifetimes, finding support through steady-state solutions in which gas exchange, carbohydrate storage and growth have all reached equilibrium. However, plants do not operate near steady state as plant responses and environmental forcings vary diurnally and seasonally. It remains unclear how gas exchange, carbohydrate storage and growth should be dynamically coordinated for stomata to maximize growth. We simulated the gas exchange, carbohydrate storage and growth that dynamically maximize growth diurnally and annually. Additionally, we test whether the growth-optimization hypothesis explains nocturnal stomatal opening, particularly through diel changes in temperature, carbohydrate storage and demand. Year-long dynamic simulations captured realistic diurnal and seasonal patterns in gas exchange as well as realistic seasonal patterns in carbohydrate storage and growth, improving upon unrealistic carbohydrate responses in steady-state simulations. Diurnal patterns of carbohydrate storage and growth in day-long simulations were hindered by faulty modelling assumptions of cyclic carbohydrate storage over an individual day and synchronization of the expansive and hardening phases of growth, respectively. The growth-optimization hypothesis cannot currently explain nocturnal stomatal opening unless employing corrective ‘fitness factors’ or reframing the theory in a probabilistic manner, in which stomata adopt an inaccurate statistical ‘memory’ of night-time temperature. The growth-optimization hypothesis suggests that diurnal and seasonal patterns of stomatal conductance are driven by a dynamic carbon-use strategy that seeks to maintain homeostasis of carbohydrate reserves.

 

Classifying the diverse ways that plants respond to hydrologic stress into generalizable ‘water‐use strategies’ has long been an eco‐physiological research goal. While many schemes for describing water‐use strategies have proven to be quite useful, they are also associated with uncertainties regarding their theoretical basis and their connection to plant carbon and water relations. In this review, we discuss the factors that shape plant water stress responses and assess the approaches used to classify a plant's water‐use strategy, paying particular attention to the popular but controversial concept of a continuum from isohydry to anisohydry.

A generalizable and predictive framework for assessing plant water‐use strategies has been historically elusive, yet recent advances in plant physiology and hydraulics provide the field with a way past these obstacles. Specifically, we promote the idea that many metrics that quantify water‐use strategies are highly dynamic and emergent from the interaction between plant traits and environmental conditions, and that this complexity has historically hindered the development of a generalizable water‐use strategy framework.

This idea is explored using a plant hydraulics model to identify: (a) distinct temporal phases in plant hydraulic regulation during drought that underpin dynamic water‐use responses, and (b) how variation in both traits and environmental forcings can significantly alter common metrics used to characterize plant water‐use strategies. This modelling exercise can bridge the divide between various conceptualizations of water‐use strategies and provide targeted hypotheses to advance the understanding and quantification of plant water status regulation across spatial and temporal scales.

Finally, we describe research frontiers that are necessary to improve the predictive capacity of the plant water‐use strategy concept, including further investigation into the below‐ground determinants of plant water relations, targeted data collection efforts and the potential to scale these concepts from individuals to whole regions.

A freePlain Language Summarycan be found within the Supporting Information of this article.

 

Eddy covariance data are invaluable for determining ecosystem water use strategies under soil water stress. However, existing stress inference methods require numerous subjective data processing and model specification assumptions whose effect on the inferred soil water stress signal is rarely quantified. These uncertainties may confound the stress inference and the generalization of ecosystem water use strategies across multiple sites and studies. In this research, we quantify the sensitivity of soil water stress signals inferred from eddy covariance data to the prevailing data and modeling assumptions (i.e., their robustness) to compile a comprehensive list of sites with robust soil water stress signals and assess the performance of current stress inference methods. To accomplish this, we identify the most prevalent assumptions from the literature and perform a digital factorial experiment to extract probability distributions of plausible soil water stress signals and model performance at 151 FLUXNET2015 and AmeriFlux-FLUXNET sites. We develop a new framework that summarizes these probability distributions to classify and rank the robustness of each site’s soil water stress signal, which we display with a user-friendly heat map. We estimate that only 5%–36% of sites exhibit a robust soil water stress signal due to deficient model performance and poorly constrained ecosystem water use parameters. We also find that the lack of robustness is site-specific, which undermines grouping stress signals by broad ecosystem categories or comparing results across studies with differing assumptions. Lastly, existing stress inference methods appear better suited for eddy covariance sites with grass/annual vegetation. Our findings call for more careful and consistent inference of ecosystem water stress from eddy covariance data. 

Abstract. Elevated atmospheric CO2 concentration is expectedto increase leaf CO2 assimilation rates, thus promoting plant growthand increasing leaf area. It also decreases stomatal conductance, allowingwater savings, which have been hypothesized to drive large-scale greening,in particular in arid and semiarid climates. However, the increase in leafarea could reduce the benefits of elevated CO2 concentration through soilwater depletion. The net effect of elevated CO2 on leaf- andcanopy-level gas exchange remains uncertain. To address this question, wecompare the outcomes of a heuristic model based on the Partitioning ofEquilibrium Transpiration and Assimilation (PETA) hypothesis and three modelvariants based on stomatal optimization theory. Predicted relative changes in leaf-and canopy-level gas exchange rates are used as a metric of plant responsesto changes in atmospheric CO2 concentration. Both model approaches predictreductions in leaf-level transpiration rate due to decreased stomatalconductance under elevated CO2, but negligible (PETA) or no(optimization) changes in canopy-level transpiration due to the compensatoryeffect of increased leaf area. Leaf- and canopy-level CO2 assimilationis predicted to increase, with an amplification of the CO2fertilization effect at the canopy level due to the enhanced leaf area. Theexpected increase in vapour pressure deficit (VPD) under warmer conditions isgenerally predicted to decrease the sensitivity of gas exchange toatmospheric CO2 concentration in both models. The consistentpredictions by different models that canopy-level transpiration varieslittle under elevated CO2 due to combined stomatal conductancereduction and leaf area increase highlight the coordination ofphysiological and morphological characteristics in vegetation to maximizeresource use (here water) under altered climatic conditions. 

Abstract. Plant transpiration downregulation in the presence of soil water stress is a critical mechanism for predicting global water, carbon, and energy cycles. Currently, many terrestrial biosphere models (TBMs) represent this mechanism with an empirical correction function (β) of soil moisture – a convenient approach that can produce large prediction uncertainties. To reduce this uncertainty, TBMs have increasingly incorporated physically based plant hydraulic models (PHMs). However, PHMs introduce additional parameter uncertainty and computational demands. Therefore, understanding why and when PHM and β predictions diverge would usefully inform model selection within TBMs. Here, we use a minimalist PHM to demonstrate that coupling the effects of soil water stress and atmospheric moisture demand leads to a spectrum of transpiration responses controlled by soil–plant hydraulic transport (conductance). Within this transport-limitation spectrum, β emerges as an end-member scenario of PHMs with infinite conductance, completely decoupling the effects of soil water stress and atmospheric moisture demand on transpiration. As a result, PHM and β transpiration predictions diverge most for soil–plant systems with low hydraulic conductance (transport-limited) that experience high variation in atmospheric moisture demand and have moderate soil moisture supply for plants. We test these minimalist model results by using a land surface model at an AmeriFlux site. At this transport-limited site, a PHM downregulation scheme outperforms the β scheme due to its sensitivity to variations in atmospheric moisture demand. Based on this observation, we develop a new “dynamic β” that varies with atmospheric moisture demand – an approach that overcomes existing biases within β schemes and has potential to simplify existing PHM parameterization and implementation.