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1. Growing recognition of the importance of climate extremes as drivers of contemporary and future ecological dynamics has led to increasing interest in studying these locally and globally important phenomena. 2. Many ecological studies examining the impacts of what are deemed climate extremes, such as heat waves and severe drought, do not provide a definition of extremity, either from a statistical context based on the long-term climatic record or from the perspective of the response of the system - are the effects extreme (unusual or profound) in comparison to normal variability? 3. A synthetic definition of an extreme climatic event (ECE) is proposed that includes ‘extremeness' in both the driver and the response: an ECE is as an episode or occurrence in which a statistically rare or unusual climatic period alters ecosystem structure and/or function well outside the bounds of what is considered typical or normal variability. This definition is accompanied by a mechanistic framework based on the concept that extreme response thresholds associated with significant community change and altered ecosystem function must be crossed in order for an ECE to occur. 4. Synthesis. A definition and mechanistic framework for ECEs is used to identify priorities for future research that will enable ecologists to more fully assess the ecological consequences of climate extremes for ecosystem structure and function today and in a future world where their frequency and intensity are expected to increase.

Precipitation (PPT) is a primary climatic determinant of plant growth and aboveground net primary production (ANPP) over much of the globe. Thus, PPT–ANPP relationships are important both ecologically and to land–atmosphere models that couple terrestrial vegetation to the global carbon cycle. Empirical PPT–ANPP relationships derived from long-term site-based data are almost always portrayed as linear, but recent evidence has accumulated that is inconsistent with an underlying linear relationship. We review, and then reconcile, these inconsistencies with a nonlinear model that incorporates observed asymmetries in PPT–ANPP relationships. Although data are currently lacking for parameterization, this new model highlights research needs that, when met, will improve our understanding of carbon cycle dynamics, as well as forecasts of ecosystem responses to climate change.

Climate change forecasts of more frequent climate extremes suggest that such events will become increasingly important drivers of future ecosystem dynamics and function. Because the rarity and unpredictability of naturally occurring climate extremes limits assessment of their ecological impacts, we experimentally imposed extreme drought and a mid-summer heat wave over two years in a central U.S. grassland. While the ecosystem was resistant to heat waves, it was not resistant to extreme drought, which reduced aboveground net primary productivity (ANPP) below the lowest level measured in this grassland in almost 30 years. This extreme reduction in ecosystem function was a consequence of reduced productivity of both C 4 grasses and C 3 forbs. However, the dominant forb was negatively impacted by the drought more than the dominant grass, and this led to a reordering of species abundances within the plant community. Although this change in community composition persisted post-drought, ANPP recovered completely the year after drought due to rapid demographic responses by the dominant grass, compensating for loss of the dominant forb. Overall, these results show that an extreme reduction in ecosystem function attributable to climate extremes (e.g., low resistance) does not preclude rapid ecosystem recovery. Given that dominance by a few species is characteristic of most ecosystems, knowledge of the traits of these species and their responses to climate extremes will be key for predicting future ecosystem dynamics and function.

1. Plant traits can provide unique insights into plant performance at the community scale. Functional composition, defined by both functional diversity and community-weighted trait means (CWMs), can affect the stability of above-ground net primary production (ANPP) in response to climate extremes. Further complexity arises, however, when functional composition itself responds to environmental change. The duration of climate extremes, such as drought, is expected to increase with rising global temperatures; thus, understanding the impacts of long-term drought on functional composition and the corresponding effect that has on ecosystem function could improve predictions of ecosystem sensitivity to climate change. 2. We experimentally reduced growing season precipitation by 66% across six temperate grasslands for 4 years and measured changes in three indices of functional diversity (functional dispersion, richness and evenness), community-weighted trait means and phylogenetic diversity (PD). Specific leaf area (SLA), leaf nitrogen content (LNC) and (at most sites) leaf turgor loss point (πTLP) were measured for species cumulatively representing ~90% plant cover at each site. 3. Long-term drought led to increased community functional dispersion in three sites, with negligible effects on the remaining sites. Species re-ordering following the mortality/senescence of dominant species was the main driver of increased functional dispersion. The response of functional diversity was not consistently matched by changes in phylogenetic diversity. Community-level drought strategies (assessed as CWMs) largely shifted from drought tolerance to drought avoidance and/or escape strategies, as evidenced by higher community-weighted , πTLP, SLA and LNC. Lastly, ecosystem drought sensitivity (i.e. relative reduction in ANPP in drought plots) was positively correlated with community-weighted SLA and negatively correlated with functional diversity. 4. Synthesis. Increased functional diversity following long-term drought may stabilize ecosystem functioning in response to future drought. However, shifts in community-scale drought strategies may increase ecosystem drought sensitivity, depending on the nature and timing of drought. Thus, our results highlight the importance of considering both functional diversity and abundance-weighted traits means of plant communities as their collective effect may either stabilize or enhance ecosystem sensitivity to drought.

Why some species are consistently more abundant than others, and predicting how species will respond to global change, are fundamental questions in ecology. Long-term observations indicate that plant species with high stoichiometric homeostasis for nitrogen ( H N ), i.e., the ability to decouple foliar N levels from variation in soil N availability, were more common and stable through time than low- H N species in a central U.S. grassland. However, with nine years of nitrogen addition, species with high H N decreased in abundance, while those with low H N increased in abundance. In contrast, in climate change experiments simulating a range of forecast hydrologic changes, e.g., extreme drought (two years), increased rainfall variability (14 years), and chronic increases in rainfall (21 years), plant species with the highest H N were least responsive to changes in soil water availability. These results suggest that H N may be predictive of plant species success and stability, and how plant species and ecosystems will respond to global-change-driven alterations in resource availability.

In contrast to pulses in resource availability following disturbance events, many of the most pressing global changes, such as elevated atmospheric carbon dioxide concentrations and nitrogen deposition, lead to chronic and often cumulative alterations in available resources. Therefore, predicting ecological responses to these chronic resource alterations will require the modification of existing disturbance-based frameworks. Here, we present a conceptual framework for assessing the nature and pace of ecological change under chronic resource alterations. The \"hierarchical-response framework\" (HRF) links well-documented, ecological mechanisms of change to provide a theoretical basis for testing hypotheses to explain the dynamics and differential sensitivity of ecosystems to chronic resource alterations. The HRF is based on a temporal hierarchy of mechanisms and responses beginning with individual (physiological/metabolic) responses, followed by species reordering within communities, and finally species loss and immigration. Each mechanism is hypothesized to differ in the magnitude and rate of its effects on ecosystem structure and function, with this variation depending on ecosystem attributes, such as longevity of dominant species, rates of biogeochemical cycling, levels of biodiversity, and trophic complexity. Overall, the HRF predicts nonlinear changes in ecosystem dynamics, with the expectation that interactions with natural disturbances and other global-change drivers will further alter the nature and pace of change. The HRF is explicitly comparative to better understand differential sensitivities of ecosystems, and it can be used to guide the design of coordinated, cross-site experiments to enable more robust forecasts of contemporary and future ecosystem dynamics.

Drought is intensifying globally with climate change, creating an urgency to understand ecosystem response to drought both during and after these events end to limit loss of ecosystem functioning. The literature is replete with studies of how ecosystems respond during drought, yet there are far fewer studies focused on ecosystem dynamics after drought ends. Furthermore, while the terms used to describe drought can be variable and inconsistent, so can those that describe ecosystem responses following drought. With this review, we sought to evaluate and create clear definitions of the terms that ecologists use to describe post-drought responses. We found that legacy effects, resilience and recovery were used most commonly with respect to post-drought ecosystem responses, but the definitions used to describe these terms were variable. Based on our review of the literature, we propose a framework for generalizing ecosystem responses after drought ends, which we refer to as ‘the post-drought period’. We suggest that future papers need to clearly describe characteristics of the imposed drought, and we encourage authors to use the term post-drought period as a general term that encompasses responses after drought ends and use other terms as more specific descriptors of responses during the post-drought period.

Random species loss has been shown experimentally to reduce ecosystem function, sometimes more than other anthropogenic environmental changes. Yet, controversy surrounds the importance of this finding for natural systems where species loss is non‐random. We compiled data from 16 multi‐year experiments located at a single native tallgrass prairie site. These experiments included responses to 11 anthropogenic environmental changes, as well as non‐random biodiversity loss either the removal of uncommon/rare plant species or the most common (dominant) species. As predicted by the mass ratio hypothesis, loss of a dominant species had large impacts on productivity that were comparable to other anthropogenic drivers. In contrast, the loss of uncommon/rare species had small effects on productivity despite having the largest effects on species richness. The anthropogenic drivers that had the largest effects on productivity nitrogen, irrigation, and fire experienced not only loss of species but also significant changes in the abundance and identity of dominant species. Synthesis. These results suggest that mass ratio effects, rather than species loss per se, are an important determinant of ecosystem function with environmental change. The mass ratio effects, rather than richness loss, determine ecosystem function with environmental change.

Insect herbivores play a pivotal role in regulating plant production and community composition, and their role in terrestrial ecosystems is partly determined by their feeding behavior and performance among plants of differing nutritional quality. Historically, nitrogen (N) has been considered the primary limiting nutrient of herbivorous insects, but N is only one of many potential nutrients important to insect performance. Of these nutrients, phosphorus (P) is perhaps the most important because somatic growth depends upon P-rich ribosomal RNA. Yet relatively few studies have assessed the strength of P-limitation for terrestrial insects and even fewer have simultaneously manipulated both N and P to assess the relative strengths of N- and P-limitation. Here, we tested for potential N and P limitation, as well as N:P co-limitation, on Chorthippis curtipennis (Orthoptera, Acrididae), an abundant member of arthropod communities of central US prairies. Our results demonstrate weak evidence for both N and P limitation of C. curtipennis growth rates in laboratory feeding assays. Importantly, P-limitation was just as strong as N-limitation, but we found no evidence for NP co-limitation in our study. Furthermore, nutrient limitation was not apparent in field studies, suggesting that insect growth rates may be predominately controlled by other factors, including temperature and predation. Our results suggest that P should be jointly considered, along with N, as a primary determinant of herbivore feeding behavior under both current and future climate conditions.

Univariate and multivariate methods are commonly used to explore the spatial and temporal dynamics of ecological communities, but each has limitations, including oversimplification or ion of communities. Rank abundance curves (RACs) potentially integrate these existing methodologies by detailing species‐level community changes. Here, we had three goals: first, to simplify analysis of community dynamics by developing a coordinated set of R functions, and second, to demystify the relationships among univariate, multivariate, and RACs measures, and examine how each is influenced by the community parameters as well as data collection methods. We developed new functions for studying temporal changes and spatial differences in RACs in an update to the R package library(“codyn”), alongside other new functions to calculate univariate and multivariate measures of community dynamics. We also developed a new approach to studying changes in the shape of RAC curves. The R package update presented here increases the accessibility of univariate and multivariate measures of community change over time and difference over space. Next, we use simulated and real data to assess the RAC and multivariate measures that are output from our new functions, studying (1) if they are influenced by species richness and evenness, temporal turnover, and spatial variability and (2) how the measures are related to each other. Lastly, we explore the use of the measures with an example from a long‐term nutrient addition experiment. We find that the RAC and multivariate measures are not sensitive to species richness and evenness and that all the measures detail unique aspects of temporal change or spatial differences. We also find that species reordering is the strongest correlate of a multivariate measure of compositional change and explains most community change observed in long‐term nutrient addition experiment. Overall, we show that species reordering is potentially an understudied determinant of community changes over time or differences between treatments. The functions developed here should enhance the use of RACs to further explore the dynamics of ecological communities.