Exotic annual grass invasion is a widespread threat to the integrity of sagebrush ecosystems in Western North America. Although many predictors of annual grass prevalence and native perennial vegetation have been identified, there remains substantial uncertainty about how regional-scale and local-scale predictors interact to determine vegetation heterogeneity, and how associations between vegetation and cattle grazing vary with environmental context. Here, we conducted a regionally extensive, one-season field survey across burned and unburned, grazed, public lands in Oregon and Idaho, with plots stratified by aspect and distance to water within pastures to capture variation in environmental context and grazing intensity.
View Article and Find Full Text PDFAdvances in restoration ecology are needed to guide ecological restoration in a variable and changing world. Coexistence theory provides a framework for how variability in environmental conditions and species interactions affects species success. Here, we conceptually link coexistence theory and restoration ecology.
View Article and Find Full Text PDFRestoration ecology commonly seeks to re-establish species of interest in degraded habitats. Despite a rich understanding of how succession influences re-establishment, there are several outstanding questions that remain unaddressed: are short-term abundances sufficient to determine long-term re-establishment success, and what factors contribute to unpredictable restorations outcomes? In other words, when restoration fails, is it because the restored habitat is substandard, because of strong competition with invasive species, or alternatively due to changing environmental conditions that would equally impact established populations? Here, we re-purpose tools developed from modern coexistence theory to address these questions, and apply them to an effort to restore the endangered Contra Costa goldfields (Lasthenia conjugens) in constructed ("restored") California vernal pools. Using 16 years of data, we construct a population model of L.
View Article and Find Full Text PDFModelling species interactions in diverse communities traditionally requires a prohibitively large number of species-interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity-inducing priors on non-linear species abundance models to determine which species interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out-of-sample predictive accuracy and parameter recovery across different input sample sizes.
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