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Recent observational studies report weak or flat temperature − growth relationships for many tree species in temperate forests. In contrast, distribution limits of trees are strongly shaped by temperature, and studies show marked short‐term temperature effects on leaf‐level ecophysiology. To better determine the effects of warming on trees, we planted one‐year‐old seedlings of one lower montane (ponderosa pine), two upper montane (quaking aspen and lodgepole pine), and one subalpine tree species (subalpine fir) in in situ experimental gardens on an elevation gradient in the Rocky Mountains (USA) which span a 6°C range in temperature but have approximately uniform precipitation. Seedlings were lightly watered the first three growing seasons to facilitate establishment, and growth and survivorship were followed for four years. We expected a trade‐off between growth and survivorship, as seedlings in high temperatures grow faster (e.g., with a longer growing season), but have higher mortality from heat stress. Compared to the coldest site, aspen (+256% wider, +337% taller), ponderosa pine (+234% wider, 270% taller), and lodgepole pine (+235% wider, 283% taller) all had strikingly higher cumulative diameter and height growth in the warmest site by the end of the study. Linear models of cumulative and annual growth in the montane species showed strong, positive relationships with growing‐season temperature, but no significant relationships with growing‐season precipitation. In contrast, growth of subalpine fir did not vary significantly with temperature, but increased slightly with higher growing‐season precipitation. Accelerated growth did not come at the expense of survivorship in the montane species: cumulative four‐year survivorship of the montane species remained robust (71.4–94.4%) in high temperatures, but caused complete mortality of subalpine fir. As long as precipitation remains adequate, these results indicate that warming is likely to strongly increase growth in seedlings of montane species with only modest decreases in survivorship despite higher evapotranspiration, especially in cooler and wetter portions of their current distributions where hydric stress is low. In contrast, warming may negatively affect seedling growth and survival in hotter and drier areas of the Rockies, and warming of +3–6°C may endanger the persistence of subalpine fir over much of its current distribution.

During the 1930s Dust Bowl drought in the central United States, species with the C₃ photosynthetic pathway expanded throughout C₄-dominated grasslands. This widespread increase in C₃ grasses during a decade of low rainfall and high temperatures is inconsistent with well-known traits of C₃ vs. C₄ pathways. Indeed, water use efficiency is generally lower, and photosynthesis is more sensitive to high temperatures in C₃ than C₄ species, consistent with the predominant distribution of C₃ grasslands in cooler environments and at higher latitudes globally. We experimentally imposed extreme drought for 4 y in mixed C₃/C₄ grasslands in Kansas and Wyoming and, similar to Dust Bowl observations, also documented three- to fivefold increases in C₃/C₄ biomass ratios. To explain these paradoxical responses, we first analyzed long-term climate records to show that under nominal conditions in the central United States, C₄ grasses dominate where precipitation and air temperature are strongly related (warmest months are wettest months). In contrast, C₃ grasses flourish where precipitation inputs are less strongly coupled to warm temperatures. We then show that during extreme drought years, precipitation–temperature relationships weaken, and the proportion of precipitation falling during cooler months increases. This shift in precipitation seasonality provides a mechanism for C₃ grasses to respond positively to multiyear drought, resolving the Dust Bowl paradox. Grasslands are globally important biomes and increasingly vulnerable to direct effects of climate extremes. Our findings highlight how extreme drought can indirectly alter precipitation seasonality and shift ecosystem phenology, affecting function in ways not predictable from key traits of C₃ and C₄ species.

Drought, defined as a marked deficiency of precipitation relative to normal, occurs as periods of below-average precipitation or complete failure of precipitation inputs, and can be limited to a single season or prolonged over multiple years. Grasslands are typically quite sensitive to drought, but there can be substantial variability in the magnitude of loss of ecosystem function. We hypothesized that differences in how drought occurs may contribute to this variability. In four native Great Plains grasslands (three C₄-and one C₃-dominated) spanning a ~ 500-mm precipitation gradient, we imposed drought for four consecutive years by (1) reducing each rainfall event by 66% during the growing season (chronic drought) or (2) completely excluding rainfall during a shorter portion of the growing season (intense drought). The drought treatments were similar in magnitude but differed in the following characteristics: event number, event size and length of dry periods. We observed consistent drought-induced reductions (28–37%) in aboveground net primary production (ANPP) only in the C₄-dominated grasslands. In general, intense drought reduced ANPP more than chronic drought, with little evidence that drought duration altered this pattern. Conversely, belowground net primary production (BNPP) was reduced by drought in all grasslands (32–64%), with BNPP reductions greater in intense vs. chronic drought treatments in the most mesic grassland. We conclude that grassland productivity responses to drought did not strongly differ between these two types of drought, but when differences existed, intense drought consistently reduced function more than chronic drought.

Plant traits can be used to predict ecosystem responses to environmental change using a response–effect trait framework. To do this, appropriate traits must be identified that explain a species' influence on ecosystem function (“effect traits”) and the response of those species to environmental change (“response traits”). Response traits are often identified and measured along gradients in plant resources, such as water availability; however, precipitation explains very little variation in most plant traits globally. Given the strong relationship between plant traits and ecosystem functions, such as net primary productivity (NPP), and between NPP and precipitation, the lack of correlation between precipitation and plant traits is surprising. We address this issue through a systematic review of >500 published studies that describe plant trait responses to altered water availability. The overarching goal of this review was to identify potential causes for the weak relationship between commonly measured plant traits and water availability so that we may identify more appropriate “response traits.” We attribute weak trait–precipitation relationships to an improper selection of traits (e.g., nonhydraulic traits) and a lack of trait‐based approaches that adjust for trait variation within communities (only 4% of studies measure community‐weighted traits). We then highlight the mechanistic value of hydraulic traits as more appropriate “response traits” with regard to precipitation, which should be included in future community‐scale trait surveys. Trait‐based ecology has the potential to improve predictions of ecosystem responses to predicted changes in precipitation; however, this predictive power depends heavily on the identification of reliable response and effect traits. To this end, trait surveys could be improved by a selection of traits that reflect physiological functions directly related to water availability with traits weighted by species relative abundance. A plain language summary is available for this article. Plain Language Summary

Global climate models predict increases in the frequency and severity of drought worldwide, directly affecting most ecosystem types. Consequently, drought legacy effects (drought-induced alterations in ecosystem function postdrought) are expected to become more common in ecosystems varying from deserts to grasslands to forests. Drought legacies in grasslands are usually negative and reduce ecosystem function, particularly after extended drought. Moreover, ecosystems that respond strongly to drought (high sensitivity) might be expected to exhibit the largest legacy effects the next year, but this relationship has not been established. We quantified legacy effects of a severe regional drought in 2012 on postdrought (2013) aboveground net primary productivity (ANPP) in six central US grasslands. We predicted that (1) the magnitude of drought legacy effects measured in 2013 would be positively related to the sensitivity of ANPP to the 2012 drought, and (2) drought legacy effects would be negative (reducing 2013 ANPP relative to that expected given normal precipitation amounts). The magnitude of legacy effects measured in 2013 was strongly related (r² = 0.88) to the sensitivity of ANPP to the 2012 drought across these six grasslands. However, contrary to expectations, positive legacy effects (greater than expected ANPP) were more commonly observed than negative legacy effects. Thus, while the sensitivity of ANPP to drought may be a useful predictor of the magnitude of legacy effects, short-term (1-year) severe droughts may cause legacy effects that are more variable than those observed after multiyear droughts.

Climate change is increasing the frequency and severity of droughts globally, and grasslands are particularly vulnerable to such hydrological extremes. Drought effects at the ecosystem scale have been assessed both experimentally and through the study of naturally occurring drought, with emerging evidence that the magnitude of drought effects may vary depending on the approach used. We took advantage of a decadal study of four grasslands to directly contrast responses of aboveground net primary productivity (ANPP) to simulated vs. natural drought. The grasslands spanned a ~ threefold mean annual precipitation gradient (335–857 mm) and were all subjected to a natural 1-year drought (~ 40% reduction in precipitation from the long-term mean) and a 4 year experimental drought (~ 50% precipitation reduction). We expected that the 4 year drought would reduce ANPP more, and that post-drought recovery would be delayed, compared to the 1-year drought. We found instead that the short-term natural drought reduced ANPP more strongly than the simulated drought in all grasslands (~ 10 to ~ 50%) likely due to the co-occurrence of higher temperatures and vapor pressure deficits with reduced precipitation. Post-drought recovery was site specific and each site differed in their recovery from the natural and experimental droughts. These results align with past analyses that experiments that only manipulate soil moisture likely underestimate the magnitude of natural drought events. However, experiments can provide valuable insight into the relative sensitivity of ecosystems to reduced precipitation and soil moisture, a key aspect of drought.

Experiments are widely used in ecology, particularly for assessing global change impacts on ecosystem function. However, results from experiments often are inconsistent with observations made under natural conditions, suggesting the need for rigorous comparisons of experimental and observational studies. We conducted such a “reality check” for a grassland ecosystem by compiling results from nine independently conducted climate change experiments. Each experiment manipulated growing season precipitation (GSP) and measured responses in aboveground net primary production (ANPP). We compared results from experiments with long-term (33-yr) annual precipitation and ANPP records to ask if collectively (n = 44 experiment-years) experiments yielded estimates of ANPP, rain-use efficiency (RUE, grams per square meter ANPP per mm precipitation), and the relationship between GSP and ANPP comparable to observations. We found that mean ANPP and RUE from experiments did not deviate from observations. Experiments and observational data also yielded similar functional relationships between ANPP and GSP, but only within the range of historically observed GSP. Fewer experiments imposed extreme levels of GSP (outside the observed 33-yr record), but when these were included, they altered the GSP–ANPP relationship. This result underscores the need for more experiments imposing extreme precipitation levels to resolve how forecast changes in climate regimes will affect ecosystem function in the future.

Aim The rate and magnitude of climate‐induced tree range shifts may be influenced by range‐wide variation in recruitment, which acts as a bottleneck in tree range dynamics. Here, we compare range predictions made using standard species distribution models (SDMs) and an integrated metamodelling approach that assimilates data on adult occurrence, seedling recruitment dynamics, and seedling survival under both current and future climate, and evaluate the degree to which information provided by seedling data can improve predictions of range dynamics. Location The interior west region of the United States. Time period 1990–2015. Major taxa studied Five widespread conifer tree species. Methods We used a previously published metamodelling framework to combine information from SDMs of adult tree occurrence and sub‐models describing seedling recruitment dynamics and seedling survival into a single set of predictions for the probability of occurrence for each species. The integrated framework links sub‐models to a SDM to generate cohesive predictions that consider information and uncertainty contained in all datasets. We then compared predictions from the integrated model to SDM predictions. Results Integration of seedling information served primarily to improve characterization of model uncertainty, particularly in regions where recruitment may be limited by temperatures that exceed seedling tolerance. Integration constrained response curves very slightly across most climate gradients, particularly across temperature gradients. These differences were primarily attributable to the isolated effects of temperature on seedling survival and not to recruitment dynamics. Main conclusions Our results indicate that range‐wide variation in recruitment both now and in the future is most uncertain along the edges of occupied regions, which increases uncertainty in projections of future species occurrence along range margins. Overall, the broad‐scale climatic dependence of the regeneration niche appears weaker than that of the adult climatic niche, and this enhances uncertainty in predicting range‐wide responses of these species to climate change.

Terrestrial ecosystems often vary dramatically in their responses to drought, but the reasons for this are unclear. With climate change forecasts for more frequent and extensive drought in the future, a more complete understanding of the mechanisms that determine differential ecosystem sensitivity to drought is needed. In 2012, the Central US experienced the fourth largest drought in a century, with a regional-scale 40 % reduction in growing season precipitation affecting ecosystems ranging from desert grassland to mesic tallgrass prairie. This provided an opportunity to assess ecosystem sensitivity to a drought of common magnitude in six native grasslands. We tested the prediction that drought sensitivity is inversely related to mean annual precipitation (MAP) by quantifying reductions in aboveground net primary production (ANPP). Long-term ANPP data available for each site (mean length = 16 years) were used as a baseline for calculating reductions in ANPP, and drought sensitivity was estimated as the reduction in ANPP per millimeter reduction in precipitation. Arid grasslands were the most sensitive to drought, but drought responses and sensitivity varied by more than twofold among the six grasslands, despite all sites experiencing 40 % reductions in growing season precipitation. Although drought sensitivity generally decreased with increasing MAP as predicted, there was evidence that the identity and traits of the dominant species, as well as plant functional diversity, influenced sensitivity. A more comprehensive understanding of the mechanisms leading to differences in drought sensitivity will require multi-site manipulative experiments designed to assess both biotic and abiotic determinants of ecosystem sensitivity.

Tree die-off, driven by extreme drought and exacerbated by a warming climate, is occurring rapidly across every wooded continent—threatening carbon sinks and other ecosystem services provided by forests and woodlands. Forecasting the spatial patterns of tree die-off in response to drought is a priority for the management and conservation of forested ecosystems under projected future hotter and drier climates. Several thresholds derived from drought-metrics have been proposed to predict mortality of Pinus edulis, a model tree species in many studies of drought-induced tree die-off. To improve future capacity to forecast tree mortality, we used a severe drought as a natural experiment. We compared the ability of existing mortality thresholds derived from four drought metrics (the Forest Drought Severity Index (FDSI), the Standardized Precipitation Evapotranspiration Index, and raw values of precipitation (PPT) and vapor pressure deficit, calculated using 4 km PRISM data) to predict areas of P. edulis die-off following an extreme drought in 2018 across the southwestern US. Using aerial detection surveys of tree mortality in combination with gridded climate data, we calculated the agreement between these four proposed thresholds and the presence and absence of regional-scale tree die-off using sensitivity, specificity, and the area under the curve (AUC). Overall, existing mortality thresholds tended to over predict the spatial extent of tree die-off across the landscape, yet some retain moderate skill in discriminating between areas that experienced and did not experience tree die-off. The simple PPT threshold had the highest AUC score (71%) as well as fair sensitivity and specificity, but the FDSI had the greatest sensitivity to die-off (85.9%). We highlight that empirically derived climate thresholds may be useful forecasting tools to identify vulnerable areas to drought induced die-off, allowing for targeted responses to future droughts and improved management of at-risk areas.