Grassland sensitivity to drought is related to functional composition across East Asia and North America.

Plant traits can be helpful for understanding grassland ecosystem responses to climate extremes, such as severe drought. However, intercontinental comparisons of how drought affects plant functional traits and ecosystem functioning are rare. The Extreme Drought in Grasslands experiment (EDGE) was established across the major grassland types in East Asia and North America (six sites on each continent) to measure variability in grassland ecosystem sensitivity to extreme, prolonged drought. At all sites, we quantified community-weighted mean functional composition and functional diversity of two leaf economic traits, specific leaf area and leaf nitrogen content, in response to drought. We found that experimental drought significantly increased community-weighted means of specific leaf area and leaf nitrogen content at all North American sites and at the wetter East Asian sites, but drought decreased community-weighted means of these traits at moderate to dry East Asian sites. Drought significantly decreased functional richness but increased functional evenness and dispersion at most East Asian and North American sites. Ecosystem drought sensitivity (percentage reduction in aboveground net primary productivity) positively correlated with community-weighted means of specific leaf area and leaf nitrogen content and negatively correlated with functional diversity (i.e., richness) on an intercontinental scale, but results differed within regions. These findings highlight both broad generalities but also unique responses to drought of community-weighted trait means as well as their functional diversity across grassland ecosystems.

Aridity drives clinal patterns in leaf traits and responsiveness to precipitation in a broadly distributed Australian tree species.

Aridity shapes species distributions and plant growth and function worldwide. Yet, plant traits often show complex relationships with aridity, challenging our understanding of aridity as a driver of evolutionary adaptation. We grew nine genotypes of Eucalyptus camaldulensis subsp. camaldulensis sourced from an aridity gradient together in the field for ~650 days under low and high precipitation treatments. Eucalyptus camaldulesis is considered a phreatophyte (deep-rooted species that utilizes groundwater), so we hypothesized that genotypes from more arid environments would show lower aboveground productivity, higher leaf gas-exchange rates, and greater tolerance/avoidance of dry surface soils (indicated by lower responsiveness) than genotypes from less arid environments. Aridity predicted genotype responses to precipitation, with more arid genotypes showing lower responsiveness to reduced precipitation and dry surface conditions than less arid genotypes. Under low precipitation, genotype net photosynthesis and stomatal conductance increased with home-climate aridity. Across treatments, genotype intrinsic water-use efficiency and osmotic potential declined with increasing aridity while photosynthetic capacity (Rubisco carboxylation and RuBP regeneration) increased with aridity. The observed clinal patterns indicate that E. camaldulensis genotypes from extremely arid environments possess a unique strategy defined by lower responsiveness to dry surface soils, low water-use efficiency, and high photosynthetic capacity. This strategy could be underpinned by deep rooting and could be adaptive under arid conditions where heat avoidance is critical and water demand is high.

Traits that distinguish dominant species across aridity gradients differ from those that respond to soil moisture.

Many plant traits respond to changes in water availability and might be useful for understanding ecosystem properties such as net primary production (NPP). This is especially evident in grasslands where NPP is water-limited and primarily determined by the traits of dominant species. We measured root and shoot morphology, leaf hydraulic traits, and NPP of four dominant North American prairie grasses in response to four levels of soil moisture in a greenhouse experiment. We expected that traits of species from drier regions would be more responsive to reduced water availability and that this would make these species more resistant to low soil moisture than species from wetter regions. All four species grew taller, produced more biomass, and increased total root length in wetter treatments. Each species reduced its leaf turgor loss point (TLP) in drier conditions, but only two species (one xeric, one mesic) maintained leaf water potential above TLP. We identified a suite of traits that clearly distinguished species from one another, but, surprisingly, these traits were relatively unresponsive to reduced soil moisture. Specifically, more xeric species produced thinner roots with higher specific root length and had a lower root mass fraction. This suggest that root traits are critical for distinguishing species from one another but might not respond strongly to changing water availability, though this warrants further investigation in the field. Overall, we found that NPP of these dominant grass species responded similarly to varying levels of soil moisture despite differences in species morphology, physiology, and habitat of origin.

Responses of a semiarid grassland to recurrent drought are linked to community functional composition.

Recurrent droughts are an inevitable consequence of climate change, yet how grasslands respond to such events is unclear. We conducted a 6-year rainfall manipulation experiment in a semiarid grassland that consisted of an initial 2-year drought (2015-2016), followed by a recovery period (2017-2018) and, finally, a second 2-year drought (2019-2020). In each year, we estimated aboveground net primary productivity (ANPP), species richness, community-weighted mean (CWM) plant traits, and several indices of functional diversity. The initial drought led to reduced ANPP, which was primarily driven by limited growth of forbs in the first year and grasses in the second year. Total ANPP completely recovered as the rapid recovery of grass productivity compensated for the slow recovery of forb productivity. The subsequent drought led to a greater reduction in total ANPP than the initial drought due to the greater decline of both grass and forb productivity. The structural equation models revealed that soil moisture influenced ANPP responses directly during the initial drought, and indirectly during the subsequent drought by lowering functional diversity, which resulted in reduced total ANPP. Additionally, ANPP was positively influenced by CWM plant height and leaf nitrogen during the recovery period and recurrent drought, respectively. Overall, the greater impact of the second drought on ecosystem function than the initial drought, as well as the underlying differential mechanism, underscores the need for an understanding of how increased drought frequency may alter semiarid grassland functioning.

Legacy effects of a multi-year extreme drought on belowground bud banks in rhizomatous vs bunchgrass-dominated grasslands.

Belowground bud banks play a crucial role in plant population regeneration, community dynamics, and functional responses of ecosystems to environmental change and disturbance. In mesic grasslands, belowground bud banks are largely resistant to short-term drought. However, the sensitivity of belowground bud banks to long-term extreme drought in semi-arid grasslands is less understood. We investigated the legacy effects of a four-year experimental drought (i.e., 66% reduction in growing season precipitation) on belowground bud density, aboveground shoot density, and the meristem limitation index (MLI; the ratio of bud to shoot density) in two semi-arid grasslands that differ in dominant grass species growth forms (i.e., rhizomatous vs. bunchgrasses). Measurements were made during the first recovery year following drought; thus, we report the legacy effects of drought on belowground bud banks. At the community level, drought reduced belowground bud density and aboveground shoot density with no change in MLI. However, drought had no significant influences on belowground buds, aboveground shoots and MLI of the dominant plant growth form in each community. The legacy effects of drought were largely dependent on plant community type and growth form. Specifically, bunchgrasses and bunchgrass-dominated communities were characterized by greater meristem limitation than rhizomatous grasses, likely due to their cluster/phalanx clonal growth. Overall, our study suggests bud banks may indeed be sensitive to long-term drought, although this depends on plant growth forms and community characteristics.

Differential responses of grassland community nonstructural carbohydrate to experimental drought along a natural aridity gradient.

Plant nonstructural carbohydrates (NSC) can reflect community and ecosystem responses to environmental changes such as water availability. Climate change is predicted to increase aridity and the frequency of extreme drought events in grasslands, but it is unclear how community-scale NSC will respond to drought or how such responses may vary along aridity gradients. We experimentally imposed a 4-year drought in six grasslands along a natural aridity gradient and measured the community-weighted mean of leaf soluble sugar (SSCWM) and total leaf NSC (NSCCWM) concentrations. We observed a bell-shape relationship across this gradient, where SSCWM and total NSCCWM concentrations were lowest at intermediate aridity, with this pattern driven primarily by species turnover. Drought manipulation increased both SSCWM and total NSCCWM concentrations at one moderately arid grassland but decreased total NSCCWM concentrations at one moist site. These differential responses to experimental drought depended on the relative role of species turnover and intraspecific variation in driving shifts in SSCWM and total NSCCWM concentrations. Specifically, the synergistic effects of species turnover and intraspecific variation drove the responses of leaf NSC concentrations to drought, while their opposing effects diminished the effect of drought on plant SSCWM and total NSCCWM concentrations. Plant resource strategies were more acquisitive, via higher chlorophyllCWM concentration, to offset reduced NSCCWM concentrations and net aboveground primary productivity (ANPP) with increasing aridity at more mesic sites, but more conservative (i.e., decreased plant heightCWM and ANPP) to reduce NSC consumption at drier sites. The relationship between water availability and NSCCWM concentrations may contribute to community drought resistance and improve plant viability and adaptation strategies to a changing climate.

Plant traits and soil fertility mediate productivity losses under extreme drought in C3 grasslands.

Extreme drought decreases aboveground net primary production (ANPP) in most grasslands, but the magnitude of ANPP reductions varies especially in C3 -dominated grasslands. Because the mechanisms underlying such differential ecosystem responses to drought are not well resolved, we experimentally imposed an extreme 4-yr drought (2015-2018) in two C3 grasslands that differed in aridity. These sites had similar annual precipitation and dominant grass species (Leymus chinensis) but different annual temperatures and thus water availability. Drought treatments differentially affected these two semiarid grasslands, with ANPP of the drier site reduced more than at the wetter site. Structural equation modeling revealed that community-weighted means for some traits modified relationships between soil moisture and ANPP, often due to intraspecific variation. Specifically, drought reduced community mean plant height at both sites, resulting in a reduction in ANPP beyond that attributable to reduced soil moisture alone. Higher community mean leaf carbon content enhanced the negative effects of drought on ANPP at the drier site, and ANPP-soil-moisture relationships were influenced by soil C:N ratio at the wetter site. Importantly, neither species richness nor functional dispersion were significantly correlated with ANPP at either site. Overall, as expected, soil moisture was a dominant, direct driver of ANPP response to drought, but differential sensitivity to drought in these two grasslands was also related to soil fertility and plant traits.

Is a drought a drought in grasslands? Productivity responses to different types of drought.

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.

Resolving the Dust Bowl paradox of grassland responses to extreme drought.

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.

Extending the osmometer method for assessing drought tolerance in herbaceous species.

Community-scale surveys of plant drought tolerance are essential for understanding semi-arid ecosystems and community responses to climate change. Thus, there is a need for an accurate and rapid methodology for assessing drought tolerance strategies across plant functional types. The osmometer method for predicting leaf osmotic potential at full turgor (πo), a key metric of leaf-level drought tolerance, has resulted in a 50-fold increase in the measurement speed of this trait; however, the applicability of this method has only been tested in woody species and crops. Here, we assess the osmometer method for use in herbaceous grassland species and test whether πo is an appropriate plant trait for understanding drought strategies of herbaceous species as well as species distributions along climate gradients. Our model for predicting leaf turgor loss point (πTLP) from πo (πTLP = 0.80πo-0.845) is nearly identical to the model previously presented for woody species. Additionally, πo was highly correlated with πTLP for graminoid species (πtlp = 0.944πo-0.611; r2 = 0.96), a plant functional group previously flagged for having the potential to cause erroneous measurements when using an osmometer. We report that πo, measured with an osmometer, is well correlated with other traits linked to drought tolerance (namely, leaf dry matter content and leaf vulnerability to hydraulic failure) as well as climate extremes linked to water availability. The validation of the osmometer method in an herb-dominated ecosystem paves the way for rapid community-scale surveys of drought tolerance across plant functional groups, which could improve trait-based predictions of ecosystem responses to climate change.

Drought timing, not previous drought exposure, determines sensitivity of two shortgrass species to water stress.

Climate change will alter global precipitation patterns, making it increasingly important that we understand how ecosystems will be impacted by more frequent and severe droughts. Yet most drought studies examine a single, within-season drought, and we know relatively little about the impacts of multiple droughts that occur within a single growing season. This distinction is important because many plant species are able to acclimate physiologically, such that the effects of multiple droughts on ecosystem function deviate significantly from the effects of cumulative, independent droughts. Unfortunately, we know relatively little about the ability of dominant species to acclimate to drought in drought-sensitive ecosystems like semi-arid grasslands. Here, we tested for physiological acclimation to multiple drought events in two dominant shortgrass steppe species: Bouteloua gracilis (C4) and Elymus elymoides (C3). Neither species exhibited physiological acclimation to drought; leaf water potential, stomatal conductance, and photosynthesis rates were all similarly affected by a single, late period drought and a second, late period drought. Biomass was lowest in plants exposed to two droughts, but this is likely due to the cumulative effects of both an early and late period drought. Our results suggest that late period droughts do exert weaker effects on biomass production of two dominant shortgrass species, but that the weaker effects are due to ontogenetic changes in plant physiology as opposed to physiological acclimation against multiple droughts. As a consequence, current ecosystem models that incorporate grass phenology and seasonal physiology should provide accurate predictions of primary production under future climates.

A reality check for climate change experiments: Do they reflect the real world?

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.

Host Plants of the Wheat Stem Sawfly (Hymenoptera: Cephidae).

Wheat stem sawfly (Cephus cinctus Norton) is a pest of economic importance across much of the wheat (Triticum aestivum L.)-growing areas of the western Great Plains of North America as well as an ecologically important insect owing to its wide range of grass hosts. Little research has been published regarding the noncultivated native and invasive grasses attacked by this insect. Knowledge of the complete host range of C. cinctus can inform future research about potential new sources of genetic resistance, improve understanding of the biology and spread of natural enemies, and better define this insect's role in grassland and agricultural systems. The aim of this review is to compile a checklist of reported host plants of C. cinctus and present data from an extensive survey of noncultivated hosts used by C. cinctus.

Pushing precipitation to the extremes in distributed experiments: recommendations for simulating wet and dry years.

Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multiyear droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity, suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e.g., cost, comparability, standardization). Here, we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of 'Drought-Net', a relatively low-cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i.e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites - a common approach to standardization in CDEs. This is because precipitation variability varies >fivefold globally resulting in a wide range of ecosystem-specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based on each site's past climatic characteristics. This approach, though not often used by ecologists, allows ecological responses to be directly compared across disparate ecosystems and climates, facilitating process-level understanding of ecosystem sensitivity to precipitation extremes.