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ABSTRACT Climate extremes—e.g., drought, atmospheric rivers, heat waves—are increasing in severity and frequency across the western United States of America (USA). Tree‐ring widths reflect the concurrent and legacy effects of such climate extremes, yet our ability to predict extreme tree growth is often poor. Could tree‐ring data themselves identify the most important climate variables driving extreme low‐ and high‐growth states? How does the importance of these climate drivers differ across species and time? To address these questions, we explored the spatial synchrony of extreme low‐ and high‐growth years, the symmetry of climate effects on the probability of low‐ and high‐growth years, and how climate drivers of extreme growth vary across tree species. We compiled ring widths for seven species (four gymnosperms and three angiosperms) from 604 sites in the western USA and classified each annual ring as representing extreme low, extreme high, or nominal growth. We used classification random forest (RF) models to evaluate the importance of 30 seasonal climate variables for predicting extreme growth, including precipitation, temperature, and vapor pressure deficit (VPD) during and up to four years prior to ring formation. For four species (three gymnosperms, one angiosperm) for which climate was predictive of growth, the RF models correctly classified 89%–98% and 80%–95% of low‐ and high‐growth years, respectively. For these species, asymmetric climate responses dominated. Current‐year winter hydroclimate (precipitation and VPD) was most important for predicting low growth, but prediction of high growth required multiple years of favorable moisture conditions, and the occurrence of low‐growth years was more synchronous across space than high‐growth years. Summer climate and temperature (regardless of season) were only weakly predictive of growth extremes. Our results motivate ecologically relevant definitions of drought such that current winter moisture stress exerts a dominant role in governing growth reductions in multiple tree species broadly distributed across the western USA. 

Abstract Radiocarbon (∆14C) measurements of nonstructural carbon enable inference on the age and turnover time of stored photosynthate (e.g., sugars, starch), of which the largest pool in trees resides in the main bole. Because of potential issues with extraction-based methods, we introduce an incubation method to capture the ∆14C of nonstructural carbon via respired CO2. In this study, we compared the ∆14C obtained from these incubations with ∆14C from a well-established extraction method, using increment cores from a mature trembling aspen (Populus tremuloides Michx). To understand any potential ∆14C disagreement, the yields from both methods were also benchmarked against the phenol-sulfuric acid concentration assay. We found incubations captured less than 100% of measured sugar and starch carbon, with recovery ranging from ~ 3% in heartwood to 85% in shallow sapwood. However, extractions universally over-yielded (mean 273 ± 101% expected sugar carbon; as high as 480%), where sugars represented less than half of extracted soluble carbon, indicating very poor specificity. Although the separation of soluble and insoluble nonstructural carbon is ostensibly a strength of extraction-based methods, there was also evidence of poor separation of these two fractions in extractions. The ∆14C of respired CO2 and ∆14C from extractions were similar in the sapwood, whereas extractions resulted in comparatively higher ∆14C (older carbon) in heartwood and bark. Because yield and ∆14C discrepancies were largest in old tissues, incubations may better capture the ∆14C of nonstructural carbon that is actually metabolically available. That is, we suggest extractions include metabolically irrelevant carbon from dead tissues or cells, as well as carbon that is neither sugar nor starch. In contrast, nonstructural carbon captured by extractions must be respired to be measured. We thus suggest incubations of live tissues are a potentially viable, inexpensive and versatile method to study the ∆14C of metabolically relevant (available) nonstructural carbon. 

Summary Carbon reserves are distributed throughout plant cells allowing past photosynthesis to fuel current metabolism. In trees, comparing the radiocarbon (Δ¹⁴C) of reserves to the atmospheric bomb spike can trace reserve ages.We synthesized Δ¹⁴C observations of stem reserves in nine tree species, fitting a new process model of reserve building. We asked how the distribution, mixing, and turnover of reserves vary across trees and species. We also explored how stress (drought and aridity) and disturbance (fire and bark beetles) perturb reserves.Given sufficient sapwood, young (< 1 yr) and old (20–60+ yr) reserves were simultaneously present in single trees, including ‘prebomb’ reserves in two conifers. The process model suggested that most reserves are deeply mixed (30.2 ± 21.7 rings) and then respired (2.7 ± 3.5‐yr turnover time). Disturbance strongly increased Δ¹⁴C mean ages of reserves (+15–35 yr), while drought and aridity effects on mixing and turnover were species‐dependent. Fire recovery inSequoia sempervirensalso appears to involve previously unobserved outward mixing of old reserves.Deep mixing and rapid turnover indicate most photosynthate is rapidly metabolized. Yet ecological variation in reserve ages is enormous, perhaps driven by stress and disturbance. Across species, maximum reserve ages appear primarily constrained by sapwood longevity, and thus old reserves are probably widespread. 

Abstract 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. 

Forest dynamics arise from the interplay of environmental drivers and disturbances with the demographic processes of recruitment, growth, and mortality, subsequently driving biomass and species composition. However, forest disturbances and subsequent recovery are shifting with global changes in climate and land use, altering these dynamics. Changes in environmental drivers, land use, and disturbance regimes are forcing forests toward younger, shorter stands. Rising carbon dioxide, acclimation, adaptation, and migration can influence these impacts. Recent developments in Earth system models support increasingly realistic simulations of vegetation dynamics. In parallel, emerging remote sensing datasets promise qualitatively new and more abundant data on the underlying processes and consequences for vegetation structure. When combined, these advances hold promise for improving the scientific understanding of changes in vegetation demographics and disturbances.