Moisture stress limits radial mixing of non-structural carbohydrates in sapwood of trembling aspen.

Dynamics in non-structural carbohydrate (NSC) pools may underlie observed drought legacies in tree growth. We assessed how aridity influences the dynamics of different-aged NSC pools in tree sapwood at two sites with differing climate conditions ('wet' vs. 'dry') that also experienced widespread regional drought five years earlier. We used an incubation method to measure radiocarbon (Δ14C) in CO2 respired from Populus tremuloides (aspen) tree rings to evaluate NSC storage and mixing patterns, coupled with measurements of NSC (soluble sugars, starch) concentrations and respired δ13C-CO2. At a wet site, CO2 respired from rings formed during 1962-1967 was only ~ 11 years old, suggesting deep sapwood mixing of NSCs as starch. At a dry site, total NSC was about one-third of wet site totals, maximum ages in deep rings were lower, and ages more rapidly increased in shallow rings then plateaued. These results suggest historically shallower mixing and/or relatively higher consumption of NSCs under dry conditions. Both sites, however, had similar aged NSC (<1 yr) in the most recent six rings, indicative of deep radial mixing following relatively wet conditions during the sampling year. We suggest significant differences in NSC mixing among sites are driven by moisture stress, where aridity reduces NSC reserves and restricts the depth of radial mixing. However, dynamic climate conditions in the southwestern US resulted in more complex radial patterns of sapwood NSC age than previously described. We suggest a novel conceptual framework to understand how moisture variability might influence the dynamics of NSC mixing in the sapwood.

An incubation method to determine the age of available nonstructural carbon in woody plant tissues.

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). 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. While 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, while 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.

Provenance, genotype, and flooding influence growth and resource acquisition characteristics in a clonal, riparian shrub.

PREMISE: Riparian plants can exhibit intraspecific phenotypic variability across the landscape related to temperature and flooding gradients. Phenotypes that vary across a climate gradient are often partly genetically determined and may differ in their response to inundation. Changes to inundation patterns across a climate gradient could thus result in site-specific inundation responses. Phenotypic variability is more often studied in riparian trees, yet riparian shrubs are key elements of riparian systems and may differ from trees in phenotypic variability and environmental responses. METHODS: We tested whether individuals of a clonal, riparian shrub, Pluchea sericea, collected from provenances spanning a temperature gradient differed in their phenotypes and responses to inundation and to what degree any differences were related to genotype. Plants were subjected to different inundation depths and a subset genotyped. Variables related to growth and resource acquisition were measured and analyzed using hierarchical, multivariate Bayesian linear regressions. RESULTS: Individuals from different provenances differed in their phenotypes, but not in their response to inundation. Phenotypes were not related to provenance temperature but were partially governed by genotype. Growth was more strongly influenced by inundation, while resource acquisition was more strongly controlled by genotype. CONCLUSIONS: Growth and resource acquisition responses in a clonal, riparian shrub are affected by changes to inundation and plant demographics in unique ways. Shrubs appear to differ from trees in their responses to environmental change. Understanding environmental effects on shrubs separately from those of trees will be a key part of evaluating impacts of environmental change on riparian ecosystems.

Contemporary tree growth shows altered climate memory.

Trees are long-lived organisms, exhibiting temporally complex growth arising from strong climatic "memory." But conditions are becoming increasingly arid in the western USA. Using a century-long tree-ring network, we find altered climate memory across the entire range of a widespread western US conifer: growth is supported by precipitation falling further into the past (+15 months), while increasingly impacted by more recent temperature conditions (-8 months). Tree-ring datasets can be biased, so we confirm altered climate memory in a second, ecologically-sampled tree-ring network. Predicted drought responses show trees may have also become more sensitive to repeat drought. Finally, plots near sites with relatively longer precipitation memory and shorter temperature memory had significantly lower recent mortality rates (R2  = 0.61). We argue that increased drought frequency has altered climate memory, demonstrate how non-stationarity may arise from failure to account for memory, and suggest memory length may be predictive of future tree mortality.

Tree growth sensitivity to climate varies across a seasonal precipitation gradient.

Spatial patterns of precipitation in the southwestern United States result in a complex gradient from winter-to-summer moisture dominance that influences tree growth. In response, tree growth exhibits seasonal-to-annual variability that is evident in the growth of whole tree rings, and in sub-annual sections such as earlywood and latewood. We evaluated the influence of precipitation and temperature on the growth of Pinus ponderosa trees in 11 sites in the southwestern US. Precipitation during the year of growth and the prior year accounted for about half of the climate influence on annual growth, with the other half reflecting conditions 2-4 years prior to growth, indicating that individual trees do indeed exhibit multi-year "memory" of climate. Trees in wetter sites exhibited weaker influence of past precipitation inputs, but longer memory of climatic variability. Conversely, trees in dry sites exhibited shorter memory of long-term climatic variability, but greater sensitivity to past precipitation effects. These results are consistent with the existence of complex interactions between endogenous (phenotype) effects and exogenous (climate) effects in controlling climate memory in trees. After accounting for climate, residual variability in latewood growth was negatively correlated with earlywood growth, indicating a potential tradeoff between latewood versus earlywood growth. This study provides new insights that will assist the accurate prediction of woody biomass growth and forest carbon sequestration across a southwestern US precipitation gradient.

Disentangling the Legacies of Climate and Management on Tree Growth.

Legacies of past climate conditions and historical management govern forest productivity and tree growth. Understanding how these processes interact and the timescales over which they influence tree growth is critical to assess forest vulnerability to climate change. Yet, few studies address this issue, likely because integrated long-term records of both growth and forest management are uncommon. We applied the stochastic antecedent modelling (SAM) framework to annual tree-ring widths from mixed forests to recover the ecological memory of tree growth. We quantified the effects of antecedent temperature and precipitation up to 4 years preceding the year of ring formation and integrated management effects with records of harvesting intensity from historical forest management archives. The SAM approach uncovered important time periods most influential to growth, typically the warmer and drier months or seasons, but variation among species and sites emerged. Silver fir responded primarily to past climate conditions (25-50 months prior to the year of ring formation), while European beech and Scots pine responded mostly to climate conditions during the year of ring formation and the previous year, although these responses varied among sites. Past management and climate interacted in such a way that harvesting promoted growth in young silver fir under wet and warm conditions and in old European beech under drier and cooler conditions. Our study shows that the ecological memory associated with climate legacies and historical forest management is species-specific and context-dependent, suggesting that both aspects are needed to properly evaluate forest functioning under climate change. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10021-021-00650-8.

Temperature memory and non-structural carbohydrates mediate legacies of a hot drought in trees across the southwestern USA.

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.

A hierarchical, multivariate meta-analysis approach to synthesising global change experiments.

Meta-analyses enable synthesis of results from globally distributed experiments to draw general conclusions about the impacts of global change factors on ecosystem function. Traditional meta-analyses, however, are challenged by the complexity and diversity of experimental results. We illustrate how several key issues can be addressed by a multivariate, hierarchical Bayesian meta-analysis (MHBM) approach applied to information extracted from published studies. We applied an MHBM to log-response ratios for aboveground biomass (AB, n = 300), belowground biomass (BB, n = 205) and soil CO2 exchange (SCE, n = 544), representing 100 studies. The MHBM accounted for study duration, climate effects and covariation among the AB, BB and SCE responses to elevated CO2 (eCO2 ) and/or warming. The MHBM revealed significant among-study covariation in the AB and BB responses to experimental treatments. The MHBM imputed missing duration (4.2%) and climate (6%) data, and revealed that climate context governs how eCO2 and warming impact ecosystem function. Predictions identified biomes that may be particularly sensitive to eCO2 or warming, but that are under-represented in global change experiments. The MHBM approach offers a flexible and powerful tool for synthesising disparate experimental results reported across multiple studies, sites and response variables.

Temporal controls on crown nonstructural carbohydrates in southwestern US tree species.

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.

Lower soil moisture and deep soil temperatures in thermokarst features increase old soil carbon loss after 10 years of experimental permafrost warming.

Almost half of the global terrestrial soil carbon (C) is stored in the northern circumpolar permafrost region, where air temperatures are increasing two times faster than the global average. As climate warms, permafrost thaws and soil organic matter becomes vulnerable to greater microbial decomposition. Long-term soil warming of ice-rich permafrost can result in thermokarst formation that creates variability in environmental conditions. Consequently, plant and microbial proportional contributions to ecosystem respiration may change in response to long-term soil warming. Natural abundance δ13 C and Δ14 C of aboveground and belowground plant material, and of young and old soil respiration were used to inform a mixing model to partition the contribution of each source to ecosystem respiration fluxes. We employed a hierarchical Bayesian approach that incorporated gross primary productivity and environmental drivers to constrain source contributions. We found that long-term experimental permafrost warming introduced a soil hydrology component that interacted with temperature to affect old soil C respiration. Old soil C loss was suppressed in plots with warmer deep soil temperatures because they tended to be wetter. When soil volumetric water content significantly decreased in 2018 relative to 2016 and 2017, the dominant respiration sources shifted from plant aboveground and young soil respiration to old soil respiration. The proportion of ecosystem respiration from old soil C accounted for up to 39% of ecosystem respiration and represented a 30-fold increase compared to the wet-year average. Our findings show that thermokarst formation may act to moderate microbial decomposition of old soil C when soil is highly saturated. However, when soil moisture decreases, a higher proportion of old soil C is vulnerable to decomposition and can become a large flux to the atmosphere. As permafrost systems continue to change with climate, we must understand the thresholds that may propel these systems from a C sink to a source.

Ecological Dynamics: Integrating Empirical, Statistical, and Analytical Methods.

Understanding ecological processes and predicting long-term dynamics are ongoing challenges in ecology. To address these challenges, we suggest an approach combining mathematical analyses and Bayesian hierarchical statistical modeling with diverse data sources. Novel mathematical analysis of ecological dynamics permits a process-based understanding of conditions under which systems approach equilibrium, experience large oscillations, or persist in transient states. This understanding is improved by combining ecological models with empirical observations from a variety of sources. Bayesian hierarchical models explicitly couple process-based models and data, yielding probabilistic quantification of model parameters, system characteristics, and associated uncertainties. We outline relevant tools from dynamical analysis and hierarchical modeling and argue for their integration, demonstrating the value of this synthetic approach through a simple predator-prey example.

Ensuring identifiability in hierarchical mixed effects Bayesian models.

Ecologists are increasingly familiar with Bayesian statistical modeling and its associated Markov chain Monte Carlo (MCMC) methodology to infer about or to discover interesting effects in data. The complexity of ecological data often suggests implementation of (statistical) models with a commensurately rich structure of effects, including crossed or nested (i.e., hierarchical or multi-level) structures of fixed and/or random effects. Yet, our experience suggests that most ecologists are not familiar with subtle but important problems that often arise with such models and with their implementation in popular software. Of foremost consideration for us is the notion of effect identifiability, which generally concerns how well data, models, or implementation approaches inform about, i.e., identify, quantities of interest. In this paper, we focus on implementation pitfalls that potentially misinform subsequent inference, despite otherwise informative data and models. We illustrate the aforementioned issues using random effects regressions on synthetic data. We show how to diagnose identifiability issues and how to remediate these issues with model reparameterization and computational and/or coding practices in popular software, with a focus on JAGS, OpenBUGS, and Stan. We also show how these solutions can be extended to more complex models involving multiple groups of nested, crossed, additive, or multiplicative effects, for models involving random and/or fixed effects. Finally, we provide example code (JAGS/OpenBUGS and Stan) that practitioners can modify and use for their own applications.

Pervasive shifts in forest dynamics in a changing world.

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.

Non-structural carbohydrate dynamics associated with antecedent stem water potential and air temperature in a dominant desert shrub.

Non-structural carbohydrates (NSCs) are necessary for plant growth and affected by plant water status, but the temporal dynamics of water stress impacts on NSC are not well understood. We evaluated how seasonal NSC concentrations varied with plant water status (predawn xylem water potential, Ψ) and air temperature (T) in the evergreen desert shrub Larrea tridentata. Aboveground sugar and starch concentrations were measured weekly or monthly for ~1.5 years on 6-12 shrubs simultaneously instrumented with automated stem psychrometers; leaf photosynthesis (Anet ) was measured monthly for 1 year. Leaf sugar increased during the dry, premonsoon period, associated with lower Ψ (greater water stress) and high T. Leaf sugar accumulation coincided with declines in leaf starch and stem sugar, suggesting the prioritization of leaf sugar during low photosynthetic uptake. Leaf starch was strongly correlated with Anet and peaked during the spring and monsoon seasons, while stem starch remained relatively constant except for depletion during the monsoon. Recent photosynthate appeared sufficient to support spring growth, while monsoon growth required the remobilization of stem starch reserves. The coordinated responses of different NSC fractions to water status, photosynthesis, and growth demands suggest that NSCs serve multiple functions under extreme environmental conditions, including severe drought.

Temporal shifts in iso/anisohydry revealed from daily observations of plant water potential in a dominant desert shrub.

Plant species are characterized along a spectrum of isohydry to anisohydry depending on their regulation of water potential (Ψ), but the plasticity of hydraulic strategies is largely unknown. The role of environmental drivers was evaluated in the hydraulic behavior of Larrea tridentata, a drought-tolerant desert shrub that withstands a wide range of environmental conditions. With a 1.5 yr time-series of 2324 in situ measurements of daily predawn and midday Ψ, the temporal variability of hydraulic behavior was explored in relation to soil water supply, atmospheric demand and temperature. Hydraulic behavior in Larrea was highly dynamic, ranging from partial isohydry to extreme anisohydry. Larrea exhibited extreme anisohydry under wet soil conditions corresponding to periods of high productivity, whereas partial isohydry was exhibited after prolonged dry or cold conditions, when productivity was low. Environmental conditions can strongly influence plant hydraulic behavior at relatively fast timescales, which enhances our understanding of plant drought responses. Although species may exhibit a dominant hydraulic behavior, variable environmental conditions can prompt plasticity in Ψ regulation, particularly for species in seasonally dry climates.

Tree growth sensitivity to climate is temporally variable.

Despite a long history of discussion of 'non-stationarity' in dendrochronology, researchers and modellers in diverse fields commonly rely on the implicit assumption that tree growth responds to climate drivers in the same way at any given time. Synthesising recent work on drought legacies and other climate-related phenomena, we show tree growth responses to climate are temporally variable, and that abrupt variability is commonly observed in response to diverse events. Thus, we put forth a 'growth-climate sensitivity' framework for understanding temporal variability (including non-stationarity) in the sensitivity of tree growth to climate. We argue that temporal variability is ubiquitous, illustrating limits to the ways in which tree growth is often conceptualised. We present two conceptual hypotheses (homoeostatic sensitivity and dynamic sensitivity) for how tree growth sensitivity to climate varies, and evaluate the evidence for each. In doing so, we hope to motivate increased investigation of the temporal variability in tree growth through innovative disturbance or drought experiments, particularly via the inclusion of recovery treatments. Focusing on growth-climate sensitivity and its temporal variability can improve prediction of the future states and functioning of trees under climate change, and has the potential to be incorporable into predictive dynamic vegetation models.

Ecological memory of daily carbon exchange across the globe and its importance in drylands.

How do antecedent (past) conditions influence land-carbon dynamics after those conditions no longer persist? In particular, quantifying such memory effects associated with the influence of past environmental (exogenous) and biological (endogenous) conditions is crucial for understanding and predicting the carbon cycle. Here we show, using data from 42 eddy covariance sites across six major biomes, that ecological memory-decomposed into environmental and biological memory components-of daily net carbon exchange (NEE) is critical for understanding the land-carbon metabolism, especially in drylands for which memory explains ~ 32% of the variation in NEE. The strong environmental memory in drylands was primarily driven by short- and long-term moisture status. Moreover, the strength of environmental memory scales with increasing water stress. This universal scaling relationship, emerging within and among major biomes, suggests a potential adaptive response to water limitation. Our findings underscore the necessity of considering ecological memory in experiments, observations and modelling.

Legacies of more frequent drought in ponderosa pine across the western United States.

Despite widespread interest in drought legacies-multiyear impacts of drought on tree growth-the key implication of reported drought legacies remains unaddressed: as impaired growth and slow recovery associated with drought legacies are pervasive across forest ecosystems, what is the impact of more frequent drought conditions? We investigated the assumption that either multiple drought years occurring during a short period (multiyear droughts), or droughts occurring during the recovery period from previous drought (compounded droughts), are detrimental to subsequent growth. There is evidence that drought responses may vary among populations of widespread species, leading us to examine regional differences in responses of the conifer Pinus ponderosa to historic drought frequency in the western United States. More frequent drought conditions incurred additional growth declines and shifts in growth-climate sensitivities in the years following drought relative to single-drought events, with 'triple-droughts' being worse than 'double-droughts'. Notably, prediction skill was not strongly reduced when ignoring compounded droughts, a consequence of the temporally comprehensive formulation of our stochastic antecedent model that accounts for the climatic memory of tree growth. We argue that incorporating drought-induced temporal variability in tree growth sensitivities can aid inference gained from statistical models, where more simplistic models could overestimate the severity of drought legacies. We also found regional differences in response to repeated drought, and suggest plastic post-drought sensitivities and climatic memory may represent beneficial physiological adjustments in interior regions. Within-species variability may thus mediate forest responses to increasing drought frequency under future climate change, but experimental approaches using more species are necessary to improve our understanding of the mechanisms that underlie drought legacy effects on tree growth.

Legacies of La Niña: North American monsoon can rescue trees from winter drought.

While we often assume tree growth-climate relationships are time-invariant, impacts of climate phenomena such as the El Niño Southern Oscillation (ENSO) and the North American Monsoon (NAM) may challenge this assumption. To test this assumption, we grouped ring widths (1900-present) in three southwestern US conifers into La Niña periods (LNP) and other years (OY). The 4 years following each La Niña year are included in LNP, and despite 1-2 year growth declines, compensatory adjustments in tree growth responses result in essentially equal mean growth in LNP and OY, as average growth exceeds OY means 2-4 years after La Niña events. We found this arises because growth responses in the two periods are not interchangeable: Due to differences in growth-climate sensitivities and climatic memory, parameters representing LNP growth fail to predict OY growth and vice versa (decreases in R2 up to 0.63; lowest R2  = 0.06). Temporal relationships between growth and antecedent climate (memory) show warmer springs and longer growing seasons negatively impact growth following dry La Niña winters, but that NAM moisture can rescue trees after these events. Increased importance of monsoonal precipitation during LNP is key, as the largest La Niña-related precipitation deficits and monsoonal precipitation contributions both occur in the southern part of the region. Decreases in first order autocorrelation during LNP were largest in the heart of the monsoon region, reflecting both the greatest initial growth declines and the largest recovery. Understanding the unique climatic controls on growth in Southwest conifers requires consideration of both the influences and interactions of drought, ENSO, and NAM, each of which is likely to change with continued warming. While plasticity of growth sensitivity and memory has allowed relatively quick recovery in the tree-ring record, recent widespread mortality events suggest conditions may soon exceed the capacity for adjustment in current populations.

Antecedent soil water content and vapor pressure deficit interactively control water potential in Larrea tridentata.

Plant water potential Ψ is regulated by stomatal responses to atmospheric moisture demand D and soil water availability W, but the timescales of influence and interactions between these drivers of plant Ψ are poorly understood. Here, we quantify the effects of antecedent D and W on plant Ψ in the desert shrub Larrea tridentata. Repeated measurements of plant baseline water potential ΨB and diurnal water potential ΨD were analyzed in a Bayesian framework to evaluate the influence of antecedent D and W at daily and subdaily timescales. Both ΨB and ΨD exhibited negative, 2- to 4-d lagged responses to daily-scale D; conversely, plant ΨD responded almost instantaneously to subdaily D, though the direction of this response depended on antecedent moisture conditions. Plant ΨB and ΨD responded positively and immediately (no lag) to shallow W, which contrasts the negative, lagged (6-7 d) response to deep W. The changing sensitivity of ΨD to subdaily D highlights shifting modes of plant Ψ regulation: D effects on ΨD range from negative to neutral to positive depending on past conditions and time of day. Explicit consideration of antecedent conditions across multiple timescales can reveal important complexities in plant responses.