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Abstract Multiyear periods (≥4 years) of extreme rainfall are increasing in frequency as climate continues to change, yet there is little understanding of how rainfall amount and heterogeneity in biophysical properties affect state changes in a sequence of wet and dry periods. Our objective was to examine the importance of rainfall periods, their legacies, and vegetation and soil properties to either the persistence of woody plants or a shift toward perennial grass dominance and a state reversal. We examined a 28‐year record of rainfall consisting of a sequence of multiyear periods (average, dry, wet, dry, average) for four ecosystem types in the Jornada Basin. We analyzed relationships between above ground net primary production (ANPP) and rainfall for three plant functional groups that characterize alternative states (perennial grasses, other herbaceous plants, dominant shrubs). A multimodel comparison was used to determine the relative importance of rainfall, soil, and vegetation properties. For perennial grasses, the greatest mean ANPP in mesquite‐ and tarbush‐dominated shrublands occurred in the wet period and in the dry period following the wet period in grasslands. Legacy effects in grasslands were asymmetric, where the lowest production was found in a dry period following an average period, and the greatest production occurred in a dry period following a wet period. For other herbaceous plants, in contrast, the greatest ANPP occurred in the wet period. Mesquite was the only dominant shrub species with a significant positive response in the wet period. Rainfall amount was a poor predictor of ANPP for each functional group when data from all periods were combined. Initial herbaceous biomass at the plant scale, patch‐scale biomass, and soil texture at the landscape scale improved the predictive relationships of ANPP compared with rainfall alone. Under future climate, perennial grass production is expected to benefit the most from wet periods compared with other functional groups with continued high grass production in subsequent dry periods that can shift (desertified) shrublands toward grasslands. The continued dominance by shrubs will depend on the effects that rainfall has on perennial grasses and the sequence of high‐ and low‐rainfall periods rather than the direct effects of rainfall on shrub production. 

Vesicular stomatitis (VS) is the most common vesicular livestock disease in North America. Transmitted by direct contact and by several biting insect species, this disease results in quarantines and animal movement restrictions in horses, cattle and swine. As changes in climate drive shifts in geographic distributions of vectors and the viruses they transmit, there is considerable need to improve understanding of relationships among environmental drivers and patterns of disease occurrence. Multidisciplinary approaches integrating pathology, ecology, climatology, and biogeophysics are increasingly relied upon to disentangle complex relationships governing disease. We used a big data model integration approach combined with machine learning to estimate the potential geographic range of VS across the continental United States (CONUS) under long-term mean climate conditions over the past 30 years. The current extent of VS is confined to the western portion of the US and is related to summer and winter precipitation, winter maximum temperature, elevation, fall vegetation biomass, horse density, and proximity to water. Comparison with a climate-only model illustrates the importance of current processes-based parameters and identifies regions where uncertainty is likely to be greatest if mechanistic processes change. We then forecast shifts in the range of VS using climate change projections selected from CMIP5 climate models that most realistically simulate seasonal temperature and precipitation. Climate change scenarios that altered climatic conditions resulted in greater changes to potential range of VS, generally had non-uniform impacts in core areas of the current potential range of VS and expanded the range north and east. We expect that the heterogeneous impacts of climate change across the CONUS will be exacerbated with additional changes in land use and land cover affecting biodiversity and hydrological cycles that are connected to the ecology of insect vectors involved in VS transmission. 

In drylands, most studies of extreme precipitation events examine effects of individual years or short-term events, yet multiyear periods (>3 y) are expected to have larger impacts on ecosystem dynamics. Our goal was to take advantage of a sequence of multiple long-term (4-y) periods (dry, wet, average) that occurred naturally within a 26-y time frame to examine responses of plant species richness to extreme rainfall in grasslands and shrublands of the Chihuahuan Desert. Our hypothesis was that richness would be related to rainfall amount, and similar in periods with similar amounts of rainfall. Breakpoint analyses of water-year precipitation showed five sequential periods (1993–2018): AVG1 (mean = 22 cm/y), DRY1 (mean = 18 cm/y), WET (mean = 30 cm/y), DRY2 (mean = 18 cm/y), and AVG2 (mean = 24 cm/y). Detailed analyses revealed changes in daily and seasonal metrics of precipitation over the course of the study: the amount of nongrowing season precipitation decreased since 1993, and summer growing season precipitation increased through time with a corresponding increase in frequency of extreme rainfall events. This increase in summer rainfall could explain the general loss in C3 species after the wet period at most locations through time. Total species richness in the wet period was among the highest in the five periods, with the deepest average storm depth in the summer and the fewest long duration (>45 day) dry intervals across all seasons. For other species-ecosystem combinations, two richness patterns were observed. Compared to AVG2, AVG1 had lower water-year precipitation yet more C3 species in upland grasslands, creosotebush, and mesquite shrublands, and more C4 perennial grasses in tarbush shrublands. AVG1 also had larger amounts of rainfall and more large storms in fall and spring with higher mean depths of storm and lower mean dry-day interval compared with AVG2. While DRY1 and DRY2 had the same amount of precipitation, DRY2 had more C4 species than DRY1 in creosote bush shrublands, and DRY1 had more C3 species than DRY2 in upland grasslands. Most differences in rainfall between these periods occurred in the summer. Legacy effects were observed for C3 species in upland grasslands where no significant change in richness occurred from DRY1 to WET compared with a 41% loss of species from the WET to DRY2 period. The opposite asymmetry pattern was found for C4 subdominant species in creosote bush and mesquite shrublands, where an increase in richness occurred from DRY1 to WET followed by no change in richness from WET to DRY2. Our results show that understanding plant biodiversity of Chihuahuan Desert landscapes as precipitation continues to change will require daily and seasonal metrics of rainfall within a wet-dry period paradigm, as well as a consideration of species traits (photosynthetic pathways, lifespan, morphologies). Understanding these relationships can provide insights into predicting species-level dynamics in drylands under a changing climate. 

abstract Long-term observations and experiments in diverse drylands reveal how ecosystems and services are responding to climate change. To develop generalities about climate change impacts at dryland sites, we compared broadscale patterns in climate and synthesized primary production responses among the eight terrestrial, nonforested sites of the United States Long-Term Ecological Research (US LTER) Network located in temperate (Southwest and Midwest) and polar (Arctic and Antarctic) regions. All sites experienced warming in recent decades, whereas drought varied regionally with multidecadal phases. Multiple years of wet or dry conditions had larger effects than single years on primary production. Droughts, floods, and wildfires altered resource availability and restructured plant communities, with greater impacts on primary production than warming alone. During severe regional droughts, air pollution from wildfire and dust events peaked. Studies at US LTER drylands over more than 40 years demonstrate reciprocal links and feedbacks among dryland ecosystems, climate-driven disturbance events, and climate change. 

Abstract Detecting and understanding disturbance is a challenge in ecology that has grown more critical with global environmental change and the emergence of research on social–ecological systems. We identify three areas of research need: developing a flexible framework that incorporates feedback loops between social and ecological systems, anticipating whether a disturbance will change vulnerability to other environmental drivers, and incorporating changes in system sensitivity to disturbance in the face of global changes in environmental drivers. In the present article, we review how discoveries from the US Long Term Ecological Research (LTER) Network have influenced theoretical paradigms in disturbance ecology, and we refine a framework for describing social–ecological disturbance that addresses these three challenges. By operationalizing this framework for seven LTER sites spanning distinct biomes, we show how disturbance can maintain or alter ecosystem state, drive spatial patterns at landscape scales, influence social–ecological interactions, and cause divergent outcomes depending on other environmental changes.