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The stress‐dominance hypothesis (SDH) is a model of community assembly predicting that the relative importance of environmental filtering increases and competition decreases along a gradient of increasing environmental stress. Tests of the SDH at limited spatial scales have thus far demonstrated equivocal support and no prior study has assessed the generality of the SDH at continental scales. We examined over 53 000 tree communities spanning the eastern United States to determine whether functional trait variation and phylogenetic diversity support the SDH for gradients of water and soil nutrient availability. This analysis incorporated two complementary datasets, those of the U.S. Forest Service Forest Inventory and Analysis National program and the Carolina Vegetation Survey, and was based on three ecologically important traits: leaf nitrogen, seed mass, and wood density. We found that mean trait values were weakly correlated with water and soil nutrient availability, but that trait diversity did not vary consistently along either gradient. This did not conform to trait variation expected under the SDH and instead suggested that environmental filters structure tree communities throughout both gradients, without evidence for an increased role of competition in less stressful environments. Phylogenetic diversity of communities was principally driven by the ratio of angiosperms to gymnosperms and therefore did not exhibit the pattern of variation along stress gradients expected under the SDH. We conclude that the SDH is not a general paradigm for all eastern North American tree communities, although it may operate in certain contexts.

Simulation models are valuable tools for estimating ecosystem response to environmental conditions and are particularly relevant for investigating climate change impacts. However, because of high computational requirements, models are often applied over a coarse grid of points or for representative locations. Spatial interpolation of model output can be necessary to guide decision‐making, yet interpolation is not straightforward because the interpolated values must maintain the covariance structure among variables. We present methods for two key steps for utilizing limited simulations to generate detailed maps of multivariate and time series output. First, we present a method to select an optimal set of simulation sites that maximize the area represented for a given number of sites. Then, we introduce a multivariate matching approach to interpolate simulation results to detailed maps for the represented area. This approach links simulation output to environmentally analogous matched sites according to user‐defined criteria. We demonstrate the methods with case studies using output from (1) an individual‐based plant simulation model to illustrate site selection, and (2) an ecosystem water balance simulation model to illustrate interpolation. For the site selection case study, we identified 200 simulation sites that represented 96% of a large study area (1.12 × 106 km2) at a ~1‐km resolution. For the interpolation case study, we generated ~1‐km resolution maps across 4.38 × 106 km2 of drylands in North America from a 10 × 10 km grid of simulated sites. Estimates of interpolation errors using cross validation were low (<10% of the range of each variable). Our point selection and interpolation methods, which are available as an easy‐to‐use R package, provide a means of cost‐effectively generating detailed maps of expensive, complex simulation output (e.g., multivariate and time series) at scales relevant for local conservation planning. Our methods are flexible and allow the user to identify relevant matching criteria to balance interpolation uncertainty with areal coverage to enhance inference and decision‐making at management‐relevant scales across large areas.

Ecohydrological responses to climate change will exhibit spatial variability and understanding the spatial pattern of ecological impacts is critical from a land management perspective. To quantify climate change impacts on spatial patterns of ecohydrology across shrub steppe ecosystems in North America, we asked the following question: How will climate change impacts on ecohydrology differ in magnitude and variability across climatic gradients, among three big sagebrush ecosystems ( SB ‐Shrubland, SB ‐Steppe, SB ‐Montane), and among Sage‐grouse Management Zones? We explored these potential changes for mid‐century for RCP 8.5 using a process‐based water balance model ( SOILWAT ) for 898 big sagebrush sites using site‐ and scenario‐specific inputs. We summarize changes in available soil water ( ASW ) and dry days, as these ecohydrological variables may be helpful in guiding land management decisions about where to geographically concentrate climate change mitigation and adaptation resources. Our results suggest that during spring, soils will be wetter in the future across the western United States, while soils will be drier in the summer. The magnitude of those predictions differed depending on geographic position and the ecosystem in question: Larger increases in mean daily spring ASW were expected for high‐elevation SB ‐Montane sites and the eastern and central portions of our study area. The largest decreases in mean daily summer ASW were projected for warm, dry, mid‐elevation SB ‐Montane sites in the central and west‐central portions of our study area (decreases of up to 50%). Consistent with declining summer ASW , the number of dry days was projected to increase rangewide, but particularly for SB ‐Montane and SB ‐Steppe sites in the eastern and northern regions. Collectively, these results suggest that most sites will be drier in the future during the summer, but changes were especially large for mid‐ to high‐elevation sites in the northern half of our study area. Drier summer conditions in high‐elevation, SB ‐Montane sites may result in increased habitat suitability for big sagebrush, while those same changes will likely reduce habitat suitability for drier ecosystems. Our work has important implications for where land managers should prioritize resources for the conservation of North American shrub steppe plant communities and the species that depend on them.

Livestock grazing is a globally important land use and has the potential to significantly influence plant community structure and ecosystem function, yet several critical knowledge gaps remain on the direction and magnitude of grazing impacts. Furthermore, much of our understanding of the long-term effects on plant community composition and structure are based on grazer exclusion experiments, which explicitly avoid characterizing effects along grazing intensity gradients. We sampled big sagebrush plant communities using 68 plots located along grazing intensity gradients to determine how grazing intensity influences multiple aspects of plant community structure over time. This was accomplished by sampling plant communities at different distances from 17 artificial watering sources, using distance from water and cow dung density as proxies for grazing intensity at individual plots. Total vegetation cover and total grass cover were negatively related to grazing intensity, and cover of annual forbs, exotic cover, and exotic richness were positively related to grazing intensity. In contrast, species richness and composition, bunchgrass biomass, shrub density and size, percentage cover of bare ground, litter, and biological soil crusts did not vary along our grazing intensity gradients, in spite of our expectations to the contrary. Our results suggest that the effects of livestock grazing over multiple decades (mean = 46 years) in our sites are relatively small, especially for native perennial species, and that the big sagebrush plant communities we sampled are somewhat resistant to livestock grazing. Collectively, our findings are consistent with existing evidence that indicates the stability of the big sagebrush plant functional type composition under current grazing management regimes.

The probability of extreme weather events is increasing, with the potential for widespread impacts to plants, plant communities, and ecosystems. Reports of drought-related tree mortality are becoming more frequent, and there is increasing evidence that drought accompanied by high temperatures is especially detrimental. Simultaneously, extreme large precipitation events have become more frequent over the past century. Water-limited ecosystems may be more vulnerable to these extreme events than other ecosystems, especially when pushed outside of their historical range of variability. However, drought-related mortality of shrubs—an important component of dryland vegetation—remains understudied relative to tree mortality. In 2014, a landscape-scale die-off of the widespread shrub, big sagebrush (Artemisia tridentata Nutt.), was reported in southwest Wyoming, following extreme hot and dry conditions in 2012 and extremely high precipitation in September of 2013. Here we examine how severe drought, extreme precipitation, soil texture and salinity, and shrub-stand characteristics contributed to this die-off event. At 98 plots within and around the die-off, we quantified big sagebrush mortality, characterized soil texture and salinity, and simulated soil-water conditions from 1916 to 2016 using an ecosystem water-balance model. We found that the extreme weather conditions alone did not explain patterns of big sagebrush mortality and did not result in extreme (historically unprecedented) soil-water conditions during the drought. Instead, plots with chronically dry soil conditions experienced greatest mortality following the global change–type (hot) drought in 2012. Furthermore, mortality was greater in locations with high potential run-on and low potential run-off where saturated soil conditions were simulated in September 2013, suggesting that extreme precipitation also played an important role in the die-off in these locations. In locations where drought alone contributed to mortality, stem density negatively impacted big sagebrush. In locations that may have been affected by both drought and saturation, however, mortality was greatest where stem density was lowest, suggesting that these locations may have already been less favorable to big sagebrush. Paradoxically, vulnerability to both extreme events (drought and saturation) was associated with finer-textured soils, and our results highlight the importance of soils in determining local variation of the vulnerability of dryland plants to extreme events.

Precipitation events have been predicted and observed to become fewer, but larger, as the atmosphere warms. Water-limited ecosystems are especially sensitive to changes in water cycling, yet evidence suggests that productivity may either increase or decrease in response to precipitation intensification. Interactions among climate, soil properties, and vegetation type may explain different responses, but this is difficult to experimentally test over large spatial scales. Simulation modeling may reveal the mechanisms through which climate, soils, and vegetation interact to affect plant growth. We use an individual-based plant ecohydrological model to simulate the effects of 25%, 50%, and 100% increases in precipitation event sizes on water cycling and shrub, grass, and forb biomass in 200 shrub-steppe sites spanning 651,000 km2 of the Intermountain West, USA. Simulations did not change annual precipitation amounts and were performed for 0, 3, and 5 °C warming. Larger precipitation events decreased evaporation and ‘pushed’ water into shrub root zones in arid and semi-arid sites, but ‘pushed’ water below shrub root zones in mesic sites resulting in increased shrub biomass in arid and semi-arid, but not mesic, sites. Positive effects of precipitation intensification on shrub growth partially counteracted negative effects of warming. Grasses and forbs showed no consistent response to precipitation intensification. Results indicate that increased precipitation intensity creates a competitive advantage for shrubs in arid and semi-arid sites. This advantage results in greater shrub relative abundance and suggests that precipitation intensification contributes to woody plant encroachment observed globally in arid and semi-arid ecosystems.

In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: (1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems, and (2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980—2010, 2030—2060, and 2070—2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT, to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, whereas changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030—2060, 12% by 2070—2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030—2060, 10% by 2070—2100) and groundwater recharge (26% and 30% increase by 2030—2060 and 2070—2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer, drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.

Background Pollinators are declining due to habitat loss, pesticides, and climate change. Fire may be an effective management tool for enhancing pollinator habitat in fire-maintained ecosystems. Many studies have demonstrated that fire can promote understory plant biodiversity and cover, but considerably less is known about the effects of fire on floral abundance and pollinators, particularly in mixed-oak forests of the eastern USA. Our goal was to assess the long-term effects of repeated prescribed fire on floral abundance and the abundance of bumble bees, a globally important group of pollinators, in mixed-oak forests. We hypothesized that repeated prescribed fire would increase floral abundance, particularly the abundance of bumble bee host plants. Results We sampled 22 vegetation plots in the Wayne National Forest, Ohio, USA, that were part of a fire experiment initiated in 1995 with three treatments: frequent fire, periodic fire, and no fire. To determine if fire treatment, plant cover, and environmental variables were related to floral abundance, we fitted generalized linear models with a negative binomial distribution, and then used model selection using AICc. Total floral abundance and floral abundance of bumble bee host plants were significantly higher in plots with repeated fire relative to unburned plots. Plant cover and soil texture were also significant predictors of floral abundance: plots with higher herbaceous plant cover and fine-textured soils generally had higher floral abundance. We detected a relatively small number of bumble bees, had low power to detect differences in bumble bee abundance, and this may be why bumble bee abundance was similar between the repeated fire and no fire plots. Conclusions These results suggest that prescribed fire enhanced floral abundance for bumble bees and potentially other pollinator groups in our mixed-oak forest plots and may be an effective tool for enhancing pollinator habitat. Additional studies are needed to characterize the effects of different fire regimes on bumble bees and pollinators more broadly in mixed-oak forests of the eastern USA.

Background Without periodic fire, fire-adapted plant communities across the Central Hardwood Forest Region (CHF) in the USA have undergone significant changes in forest structure and species composition, most notably a decrease in oak regeneration and herbaceous diversity and an increase in shade-tolerant, fire-sensitive tree species. In this study, we conducted a comparative analysis of two mixed pine-oak ( Pinus-Quercus) forests with different land management histories in the Cumberland Mountains of southern West Virginia where fire ecology and fire effects are understudied. We reconstructed the fire history of both sites from fire-scarred shortleaf pine ( Pinus echinata Mill.) and pitch pine ( Pinus rigida Mill.) trees to describe variation in the fire regimes over time. We also made plant community measurements that spatially coincided with fire-scarred pines to assess present-day plant community structure in relation to recent fire history. Results Before 1970, fires at Hite Fork and Wall Fork occurred frequently and almost exclusively in the dormant season, every 7–8 years on average. The fire regimes diverged in the Post-Industrial era (1970–2020), during which there was a single fire at Wall Fork, while six major fires, scarring more than 40% of sampled trees, occurred between 1985 and 2017 at Hite Fork. Four of these dormant-season fires correspond to late fall incendiary fires in the observational record. These differences in recent fire history had large effects on plant community structure. Recent mixed-severity fires at Hite Fork likely caused mortality of pole-sized trees and opened the canopy, creating conditions favorable for pine recruitment and resulted in significantly higher species richness in the herbaceous layer compared to Wall Fork, which exhibited the effects of mesophication. Conclusions Our results suggest that frequent mixed-severity fire in pine-oak forests of the Cumberland Mountains can meet management objectives by reducing mesophytic tree abundance, increasing herbaceous diversity and pine recruitment, and generally promoting forest heterogeneity.

Background Wildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush ( Artemisia tridentata Nutt.) plant communities and declines in sagebrush obligate wildlife species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better understanding of long-term wildfire drivers across the big sagebrush region. Here, we integrated wildfire observations with climate and vegetation data to derive a statistical model for the entire big sagebrush region that represents how annual wildfire probability is influenced by climate and fine fuel characteristics. Results Wildfire frequency varied significantly across the sagebrush region, and our statistical model represented much of that variation. Biomass of annual and perennial grasses and forbs, which we used as proxies for fine fuels, influenced wildfire probability. Wildfire probability was highest in areas with high annual forb and grass biomass, which is consistent with the well-documented phenomenon of increased wildfire following annual grass invasion. The effects of annuals on wildfire probability were strongest in places with dry summers. Wildfire probability varied with the biomass of perennial grasses and forbs and was highest at intermediate biomass levels. Climate, which varies substantially across the sagebrush region, was also predictive of wildfire probability, and predictions were highest in areas with a low proportion of precipitation received in summer, intermediate precipitation, and high temperature. Conclusions We developed a carefully validated model that contains relatively simple and biologically plausible relationships, with the goal of adequate performance under novel conditions so that useful projections of average annual wildfire probability can be made given general changes in conditions. Previous studies on the impacts of vegetation and climate on wildfire probability in sagebrush ecosystems have generally used more complex machine learning approaches and have usually been applicable to only portions of the sagebrush region. Therefore, our model complements existing work and forms an additional tool for understanding future wildfire and ecological dynamics across the sagebrush region.