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Trees are long-lived organisms that integrate climate conditions across years or decades to produce secondary growth. This integration process is sometimes referred to as 'climatic memory.' While widely perceived, the physiological processes underlying this temporal integration, such as the storage and remobilization of non-structural carbohydrates (NSC), are rarely explicitly studied. This is perhaps most apparent when considering drought legacies (perturbed post-drought growth responses to climate), and the physiological mechanisms underlying these lagged responses to climatic extremes. Yet, drought legacies are likely to become more common if warming climate brings more frequent drought. To quantify the linkages between drought legacies, climate memory and NSC, we measured tree growth (via tree ring widths) and NSC concentrations in three dominant species across the southwestern USA. We analyzed these data with a hierarchical mixed effects model to evaluate the time-scales of influence of past climate (memory) on tree growth. We then evaluated the role of climate memory and the degree to which variation in NSC concentrations were related to forward-predicted growth during the hot 2011–2012 drought and subsequent 4-year recovery period. Populus tremuloides exhibited longer climatic memory compared to either Pinus edulis or Juniperus osteosperma , but following the 2011–2012 drought, P. tremuloides trees with relatively longer memory of temperature conditions showed larger (more negative) drought legacies. Conversely, Pinus edulis trees with longer temperature memory had smaller (less negative) drought legacies. For both species, higher NSC concentrations followed more negative (larger) drought legacies, though the relevant NSC fraction differed between P. tremuloides and P. edulis. Our results suggest that differences in tree NSC are also imprinted upon tree growth responses to climate across long time scales, which also underlie tree resilience to increasingly frequent drought events under climate change. [ABSTRACT FROM AUTHOR]

In trees, large uncertainties remain in how nonstructural carbohydrates (NSCs) respond to variation in water availability in natural, intact ecosystems. Variation in NSC pools reflects temporal fluctuations in supply and demand, as well as physiological coordination across tree organs in ways that differ across species and NSC fractions (e.g. soluble sugars vs starch). Using landscape-scale crown (leaves and twigs) NSC concentration measurements in three foundation tree species (Populus tremuloides , Pinus edulis , Juniperus osteosperma), we evaluated in situ, seasonal variation in NSC responses to moisture stress on three timescales: short-term (via predawn water potential), seasonal (via leaf δ13C) and annual (via current year's ring width index). Crown NSC responses to moisture stress appeared to depend on hydraulic strategy, where J. osteosperma appears to regulate osmotic potentials (via higher sugar concentrations), P. edulis NSC responses suggest respiratory depletion and P. tremuloides responses were consistent with direct sink limitations. We also show that overly simplistic models can mask seasonal and tissue variation in NSC responses, as well as strong interactions among moisture stress at different timescales. In general, our results suggest large seasonal variation in crown NSC concentrations reflecting the multiple cofunctions of NSCs in plant tissues, including storage, growth and osmotic regulation of hydraulically vulnerable leaves. We emphasize that crown NSC pool size cannot be viewed as a simple physiological metric of stress; in situ NSC dynamics are complex, varying temporally, across species, among NSC fractions and among tissue types. [ABSTRACT FROM AUTHOR]

Modeling stomatal control is critical for predicting forest responses to the changing environment and hence the global water and carbon cycles. A trait-based stomatal control model that optimizes carbon gain while avoiding hydraulic risk has been shown to perform well in response to drought. However, the model's performance against changes in atmospheric CO2, which is rising rapidly due to human emissions, has yet to be evaluated. The present study tested the gain–risk model's ability to predict the stomatal response to CO2 concentration with potted water birch (Betula occidentalis Hook.) saplings in a growth chamber. The model's performance in predicting stomatal response to changes in atmospheric relative humidity and soil moisture was also assessed. The gain–risk model predicted the photosynthetic assimilation, transpiration rate and leaf xylem pressure under different CO2 concentrations, having a mean absolute percentage error (MAPE) of 25%. The model also predicted the responses to relative humidity and soil drought with a MAPE of 21.9% and 41.9%, respectively. Overall, the gain–risk model had an MAPE of 26.8% compared with the 37.5% MAPE obtained by a standard empirical model of stomatal conductance. Importantly, unlike empirical models, the optimization model relies on measurable physiological traits as inputs and performs well in predicting responses to novel environmental conditions without empirical corrections. Incorporating the optimization model in larger scale models has the potential for improving the simulation of water and carbon cycles. [ABSTRACT FROM AUTHOR]

Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g-1 for soluble sugars, 6-533 (mean = 94) mg g-1 for starch and 53-649 (mean = 153) mg g-1 for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R² = 0.05-0.12 for soluble sugars, 0.10-0.33 for starch and 0.01-0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g-1 for total NSC, compared with the range of laboratory estimates of 596 mg g-1. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41-0.91), but less so for total NSC (r = 0.45-0.84) and soluble sugars (r = 0.11-0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods. [ABSTRACT FROM AUTHOR]

Modeling stomatal control is critical for predicting forest responses to the changing environment and hence the global water and carbon cycles. A trait-based stomatal control model that optimizes carbon gain while avoiding hydraulic risk has been shown to perform well in response to drought. However, the model's performance against changes in atmospheric CO2, which is rising rapidly due to human emissions, has yet to be evaluated. The present study tested the gain-risk model's ability to predict the stomatal response to CO2 concentration with potted water birch (Betula occidentalis Hook.) saplings in a growth chamber. The model's performance in predicting stomatal response to changes in atmospheric relative humidity and soil moisture was also assessed. The gain-risk model predicted the photosynthetic assimilation, transpiration rate and leaf xylem pressure under different CO2 concentrations, having a mean absolute percentage error (MAPE) of 25%. The model also predicted the responses to relative humidity and soil drought with a MAPE of 21.9% and 41.9%, respectively. Overall, the gain-risk model had an MAPE of 26.8% compared with the 37.5% MAPE obtained by a standard empirical model of stomatal conductance. Importantly, unlike empirical models, the optimization model relies on measurable physiological traits as inputs and performs well in predicting responses to novel environmental conditions without empirical corrections. Incorporating the optimization model in larger scale models has the potential for improving the simulation of water and carbon cycles., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Global patterns of drought-induced forest die-off indicate that many forests may be sensitive to climate-driven mortality, but the lack of understanding of how trees and saplings die during drought hinders the projections of die-off, demographic bottlenecks and ecosystem trajectories. In this study, we performed a severe controlled drought experiment on saplings of Pinus edulis Engelm. and Juniperus osteosperma (Torr.) Little, two species that both experienced die-off in a recent 'climate change-type' drought. We examined the roles of carbohydrate and hydraulic changes in multiple tissues as the saplings died. We found that saplings of both species exhibited large degrees of loss of hydraulic conductivity prior to death. Neither species exhibited significant changes in carbohydrate concentrations in any tissue during the relatively short and severe imposed drought. Native hydraulic conductivity successfully predicted the degree of canopy mortality in both species, highlighting the importance of drought characteristics and tree attributes in influencing physiological pathways to mortality. The relationships elucidated here, as well as the differences between our results and previous findings in adult trees, can help inform mortality mechanisms in climate-vegetation models, especially for young trees, and to understand species response to severe drought across ontogeny.