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• Understanding how plant communities respond to temporal patterns of precipitation in water-limited ecosystems is necessary to predict interannual variation and trends in ecosystem properties, including forage production, biogeochemical cycling, and biodiversity. • In North American shortgrass prairie, we measured plant abundance, functional traits related to growth rate and drought tolerance, and aboveground net primary productivity to identify: species-level responsiveness to precipitation (precipitation sensitivity S spp) across functional groups; S spp relationships to continuous plant traits; and whether continuous trait–S spp relationships scaled to the community level. • Across 32 plant species, we found strong bivariate relationships of both leaf dry matter content (LDMC) and leaf osmotic potential Ψosm with S spp. Yet, LDMC and specific leaf area were retained in the lowest Akaike information criterion multiple regression model, explaining 59% of S spp. Most relationships between continuous traits and S spp scaled to the community level but were often contingent on the presence/absence of particular species and/or land management at a site. • Thus, plant communities in shortgrass prairie may shift towards slower growing, more stress-resistant species in drought years and/or chronically drier climate. These findings highlight the importance of both leaf economic and drought tolerance traits in determining species and community responses to altered precipitation.

Forecast increases in the frequency, intensity, and duration of droughts with climate change may have extreme and extensive ecological consequences. There are currently hundreds of published, ongoing, and new drought experiments worldwide aimed to assess ecological sensitivity to drought and identify the mechanisms governing resistance and resilience. To date, the results from these experiments have varied widely, and thus, patterns of drought sensitivities and the underlying mechanisms have been difficult to discern. Here we examined 89 published drought experiments, along with their associated historical precipitation records to (1) identify where and how drought experiments have been imposed, (2) determine the extremity of drought treatments in the context of historical climate, and (3) assess the influence of ambient precipitation variability on the magnitude of drought experiments. In general, drought experiments were most common in water‐limited ecosystems, such as grasslands, and were often short‐term, as 80% were 1–4 yr in duration. When placed in a historical context, the majority of drought experiments imposed extreme drought, with 61% below the 5th, and 43% below the 1st percentile of the 50‐yr annual precipitation distribution. We also determined that interannual precipitation variability had a large and potentially underappreciated effect on the magnitude of drought treatments due to the co‐varying nature of control and drought precipitation inputs. Thus, detecting significant ecological effects in drought experiments is strongly influenced by the interaction between experimental drought magnitude, precipitation variability, and key ecological thresholds. The patterns that emerged from this study have important implications for the design and interpretation of drought experiments and also highlight critical gaps in our understanding of the ecological effects of drought.

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.

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.

A major goal in ecology is to make generalizable predictions of organism responses to environmental variation based on their traits. However, straightforward relationships between traits and fitness are rare and likely to vary with environmental context. Characterizing how traits mediate demographic responses to the environment may enhance the predictions of organism responses to global change. We synthesized 15 years of demographic data and species-level traits in a shortgrass steppe to determine whether the effects of leaf and root traits on growth and survival depended on seasonal water availability. We predicted that (1) species with drought-tolerant traits, such as lower leaf turgor loss point (TLP) and higher leaf and root dry matter content (LDMC and RDMC), would be more likely to survive and grow in drier years due to higher wilting resistance, (2) these traits would not predict fitness in wetter years, and (3) traits that more directly measure physiological mechanisms of water use such as TLP would best predict demographic responses. We found that graminoids with more negative TLP and higher LDMC and RDMC had higher survival rates in drier years. Forbs demonstrated similar yet more variable responses. Graminoids grew larger in wetter years, regardless of traits. However, in both wet and dry years, graminoids with more negative TLP and higher LDMC and RDMC grew larger than less negative TLP and low LDMC and RDMC species. Traits significantly mediated the impact of drought on survival, but not growth, suggesting that survival could be a stronger driver of species’ drought response in this system. TLP predicted survival in drier years, but easier to measure LDMC and RDMC were equal or better predictors. These results advance our understanding of the mechanisms by which drought drives population dynamics, and show that abiotic context determines how traits drive fitness.

Herbivory and fire shape plant community structure in grass-dominated ecosystems, but these disturbance regimes are being altered around the world. To assess the consequences of such alterations, we excluded large herbivores for seven years from mesic savanna grasslands sites burned at different frequencies in North America (Konza Prairie Biological Station, Kansas, USA) and South Africa (Kruger National Park). We hypothesized that the removal of a single grass-feeding herbivore from Konza would decrease plant community richness and shift community composition due to increased dominance by grasses. Similarly, we expected grass dominance to increase at Kruger when removing large herbivores, but because large herbivores are more diverse, targeting both grasses and forbs, at this study site, the changes due to herbivore removal would be muted. After seven years of large-herbivore exclusion, richness strongly decreased and community composition changed at Konza, whereas little change was evident at Kruger. We found that this divergence in response was largely due to differences in the traits and numbers of dominant grasses between the study sites rather than the predicted differences in herbivore assemblages. Thus, the diversity of large herbivores lost may be less important in determining plant community dynamics than the functional traits of the grasses that dominate mesic, disturbance-maintained savanna grasslands.

In areas with diverse herbivore communities such as African savannas, the frequency of disturbance by fire may alter the top–down role of different herbivore species on plant community dynamics. In a seven year experiment in the Kruger National Park, South Africa, we examined the habitat use of nine common herbivore species across annually burned, triennially burned and unburned areas. We also used two types of exclosures (plus open access controls) to examine the impacts of different herbivores on plant community dynamics across fire disturbance regimes. Full exclosures excluded all herbivores > 0.5 kg (e.g. elephant, zebra, impala) while partial exclosures allowed access only to animals with shoulder heights ≤ 0.85 m (e.g. impala, steenbok). Annual burns attracted a diverse suite of herbivores, and exclusion of larger herbivores (e.g. elephant, zebra, wildebeest) increased plant abundance. When smaller species, mainly impala, were also excluded there were declines in plant diversity, likely mediated by a decline in open space available for colonization of uncommon plant species. Unburned areas attracted the least diverse suite of herbivores, dominated by impala. Here, herbivore exclusion, especially of impala, led to strong declines in plant richness and diversity. With no fire disturbance, herbivore exclusion led to competitive exclusion via increases in plant dominance and light limitation. In contrast, on triennial burns, herbivore exclusion had no effect on plant richness or diversity, potentially due to relatively little open space for colonization across exclosure treatments but also little competitive exclusion due to the intermediate fire disturbance. Further, the diverse suite of grazers and browsers on triennial burns may have had a compensating effect of on the diversity of grasses and forbs. Ultimately, our work shows that differential disturbance regimes can result in differential consumer pressure across a landscape and result in heterogeneous patterns in top–down control of community dynamics.

Ecological communities are being impacted by global change worldwide. Experiments are a powerful tool to understand how global change will impact communities by comparing control and treatment replicates. Communities consist of multiple species, and their associated abundances make multivariate methods an effective approach to study community compositional differences between control and treated replicates. Dissimilarity metrics are a commonly employed multivariate measure of compositional differences; however, while highly informative, dissimilarity metrics do not elucidate the specific ways in which communities differ. Integrating two multivariate methods, dissimilarity metrics and rank abundance curves (RACs), have the potential to detect complex differences based on dissimilarity metrics and detail the how these differences came about through differences in richness, evenness, species ranks, or species identity. Here we use a database of 106 global change experiments located in herbaceous ecosystems and explore how patterns of ordinations based on dissimilarity metrics relate to RAC‐based differences. We find that combining dissimilarity metrics alongside RAC‐based measures clarifies how global change treatments are altering communities. We find that when there is no difference in community composition (no distance between centroids of control and treated replicates), there are rarely differences in species ranks or species identities and more often differences in richness or evenness alone. In contrast, when there are differences between centroids of control and treated replicates, this is most often associated with differences in ranks either alone or co‐occurring with differences in richness, evenness, or species identities. We suggest that integrating these two multivariate measures of community composition results in a deeper understanding of how global change impacts communities.

Climatic extremes, such as severe drought, are expected to increase in frequency and magnitude with climate change. Thus, identifying mechanisms of resilience is critical to predicting the vulnerability of ecosystems. An exceptional drought (

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