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Abstract Exotic annual grass invasions in water‐limited systems cause degradation of native plant and animal communities and increased fire risk. The life history of invasive annual grasses allows for high sensitivity to interannual variability in weather. Current distribution and abundance models derived from remote sensing, however, provide only a coarse understanding of how species respond to weather, making it difficult to anticipate how climate change will affect vulnerability to invasion. Here, we derived germination covariates (rate sums) from mechanistic germination and soil microclimate models to quantify the favorability of soil microclimate for cheatgrass (Bromus tectorumL.) establishment and growth across 30 years at 2662 sites across the sagebrush steppe system in the western United States. Our approach, using four bioclimatic covariates alone, predicted cheatgrass distribution with accuracy comparable to previous models fit using many years of remotely‐sensed imagery. Accuracy metrics from our out‐of‐sample testing dataset indicate that our model predicted distribution well (72% overall accuracy) but explained patterns of abundance poorly (R² = 0.22). Climatic suitability for cheatgrass presence depended on both spatial (mean) and temporal (annual anomaly) variation of fall and spring rate sums. Sites that on average have warm and wet fall soils and warm and wet spring soils (high rate sums during these periods) were predicted to have a high abundance of cheatgrass. Interannual variation in fall soil conditions had a greater impact on cheatgrass presence and abundance than spring conditions. Our model predicts that climate change has already affected cheatgrass distribution with suitable microclimatic conditions expanding 10%–17% from 1989 to 2019 across all aspects at low‐ to mid‐elevation sites, while high‐ elevation sites (>2100 m) remain unfavorable for cheatgrass due to cold spring and fall soils. 

Abstract: One strand of modern coexistence theory (MCT) partitions invader growth rates (IGR) to quantify how different mechanisms contribute to species coexistence, highlighting fluctuation‐dependent mechanisms. A general conclusion from the classical analytic MCT theory is that coexistence mechanisms relying on temporal variation (such as the temporal storage effect) are generally less effective at promoting coexistence than mechanisms relying on spatial or spatiotemporal variation (primarily growth‐density covariance). However, the analytic theory assumes continuous population density, and IGRs are calculated for infinitesimally rare invaders that have infinite time to find their preferred habitat and regrow, without ever experiencing intraspecific competition. Here we ask if the disparity between spatial and temporal mechanisms persists when individuals are, instead, discrete and occupy finite amounts of space. We present a simulation‐based approach to quantifying IGRs in this situation, building on our previous approach for spatially non‐varying habitats. As expected, we found that spatial mechanisms are weakened; unexpectedly, the contribution to IGR from growth‐density covariance could even become negative, opposing coexistence. We also found shifts in which demographic parameters had the largest effect on the strength of spatial coexistence mechanisms. Our substantive conclusions are statements about one model, across parameter ranges that we subjectively considered realistic. Using the methods developed here, effects of individual discreteness should be explored theoretically across a broader range of conditions, and in models parameterized from empirical data on real communities. 

Abstract Spatial environmental heterogeneity maintains species diversity in ecological communities, but it is difficult to model and its effects on individuals are often ignored in empirical studies of species coexistence. This is problematic because many studies estimate plant competition at the neighbourhood level, and modelling individual demographic responses without neighbourhood‐level environmental data could lead to biased results. We aimed to understand how and when ignoring spatial heterogeneity produces biased estimates of the strength of intraspecific and interspecific competition and, therefore, incorrect predictions about species coexistence.First, we used a spatially explicit individual‐based model (IBM), with neighbourhood competition depending on neighbour size and distance, to simulate two plant populations that coexist via differing responses to spatial heterogeneity. Next, we mimicked the action of ecologists collecting data in observational studies or short‐term experimental studies and sampled from the simulated populations. Then, we fitted demographic models for each species including parameters for the intensity of intra‐ and interspecific competitionwithoutinformation about spatial heterogeneity. Finally, we simulated invasions of species at low density using the IBM and estimated parameters to compute invasion growth rates (IGR).Demographic modelling with data from simulated observational studies resulted in underestimates of intraspecific competition and overestimates of interspecific competition. When we simulated invasions with the IBM and those estimated competition coefficients, the IGRs were negative or around zero and incorrectly predicted competitive exclusion. In simulated experimental studies, the estimates of competition were more accurate, but the model still incorrectly predicted competitive exclusion.Synthesis: Our study demonstrates how biases can arise in neighbourhood competition studies and highlights the importance of explicitly incorporating spatial heterogeneity into empirical coexistence studies. Failure to account for environmental heterogeneity at the level of individual plants may lead to mistaken conclusions about coexistence outcomes. 

Variability of the terrestrial global carbon sink is largely determined by the response of dryland productivity to annual precipitation. Despite extensive disturbance in drylands, how disturbance alters productivity-precipitation relationships remains poorly understood. Using remote-sensing to pair more than 5600 km of natural gas pipeline corridors with neighboring undisturbed areas in North American drylands, we found that disturbance reduced average annual production 6 to 29% and caused up to a fivefold increase in the sensitivity of net primary productivity (NPP) to interannual variation in precipitation. Disturbance impacts were larger and longer-lasting at locations with higher precipitation (>450 mm mean annual precipitation). Disturbance effects on NPP dynamics were mostly explained by shifts from woody to herbaceous vegetation. Severe disturbance will amplify effects of increasing precipitation variability on NPP in drylands. 

Abstract Forbs (“wildflowers”) are important contributors to grassland biodiversity but are vulnerable to environmental changes. In a factorial experiment at 94 sites on 6 continents, we test the global generality of several broad predictions: (1) Forb cover and richness decline under nutrient enrichment, particularly nitrogen enrichment. (2) Forb cover and richness increase under herbivory by large mammals. (3) Forb richness and cover are less affected by nutrient enrichment and herbivory in more arid climates, because water limitation reduces the impacts of competition with grasses. (4) Forb families will respond differently to nutrient enrichment and mammalian herbivory due to differences in nutrient requirements. We find strong evidence for the first, partial support for the second, no support for the third, and support for the fourth prediction. Our results underscore that anthropogenic nitrogen addition is a major threat to grassland forbs, but grazing under high herbivore intensity can offset these nutrient effects. 

Abstract Interactions between plants and soil microbes can influence plant population dynamics and diversity in plant communities. Traditional theoretical paradigms view the microbial community as a black box with net effects described by phenomenological models.This approach struggles to quantify the importance of plant–microbe interactions relative to other competition and coexistence mechanisms and to explain context dependence in microbe effects.We argue that a mechanistic framework focused on microbial functional groups will lead to conceptual and empirical advances, as demonstrated by extending resource ratio theory to plant–microbe interactions. We review the diverse pathways by which different microbial functional groups can influence plant resource competition. Finally, we suggest approaches to link theory with observations to measure the key parameters of our framework.Synthesis: Our review highlights recent experimental advancements for uncovering microbial mechanisms that alter plant host resource competition and coexistence. We synthesize these mechanisms into a conceptual model that provides a framework for future experiments to investigate the importance of plant–microbe interactions in structuring plant populations and communities. 

Community assembly is often treated as deterministic, converging on one or at most a few possible stable endpoints. However, in nature, we typically observe continuous change in community composition, which is often ascribed to environmental change. But continuous changes in community composition can also arise in deterministic, time‐invariant community models, especially food web models. Our goal was to determine why some models produce continuous assembly and others do not. We investigated a simple two‐trophic‐level community model to show that continuous assembly is driven by the relative niche width of the trophic levels. If predators have a larger niche width than prey, community assembly converges to a stable equilibrium. Conversely, if predators have a smaller niche width than prey, then community composition never stabilizes. Evidence that food webs need not reach a stable equilibrium has important implications, as many ecological theories of community ecology based on equilibria may be difficult to apply to such food webs.