Publications by authors named "Lauren G Shoemaker"

AbstractPopulation spatial synchrony-the tendency for temporal population fluctuations to be correlated across locations-is common and important to metapopulation stability and persistence. One common cause of spatial synchrony, termed the Moran effect, occurs when populations respond to environmental fluctuations, such as weather, that are correlated over space. Although the degree of spatial synchrony in environmental fluctuations can differ between seasons and different population processes occur in different seasons, the impact on population spatial synchrony is uncertain because prior work has largely assumed that the spatial synchrony of environmental fluctuations and their effect on populations are consistent over annual sampling intervals.

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While community synchrony is a key framework for predicting ecological constancy, the interplay between community synchrony and ecological invasions remains unclear. Yet the degree of synchrony in a resident community may influence its resistance and resilience to the introduction of an invasive species. Here we used a generalizable mathematical framework, constructed with a modified Lotka-Volterra competition model, to first simulate resident communities across a range of competitive strengths and species' responses to environmental fluctuations, which yielded communities that ranged from strongly synchronous to compensatory.

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Advances 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.

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Temporal patterns of plant-insect interactions are readily observed within fossil datasets but spatial variability is harder to disentangle without comparable modern methods due to limitations in preservation. This is problematic as spatial variability influences community structure and interactions. To address this we replicated paleobotanical methods within three modern forests, creating an analogous dataset that rigorously tested inter- and intra-forest plant-insect variability.

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Disturbance and environmental change may cause communities to converge on a steady state, diverge towards multiple alternative states or remain in long-term transience. Yet, empirical investigations of successional trajectories are rare, especially in systems experiencing multiple concurrent anthropogenic drivers of change. We examined succession in old field grassland communities subjected to disturbance and nitrogen fertilization using data from a long-term (22-year) experiment.

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Pathogen coexistence depends on ecological processes operating at both within and between-host scales, making it difficult to quantify which processes may promote or prevent coexistence. Here, we propose that adapting modern coexistence theory-traditionally applied in plant communities-to pathogen systems provides an exciting approach for examining mechanisms of coexistence operating across different spatial scales. We first overview modern coexistence theory and its mechanistic decomposition; we subsequently adapt the framework to quantify how spatial variation in pathogen density, host resources and immunity, and their interaction may promote pathogen coexistence.

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It is well known that species interactions between exotic and native species are important for determining the success of biological invasions and how influential exotic species become in invaded communities. The strength and type of interactions between species can substantially vary, however, from negative and detrimental to minimal or even positive. Increasing evidence from the literature shows that exotic species have positive interactions with native species more often than originally thought.

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Natural systems contain more complexity than is accounted for in models of modern coexistence theory. Coexistence modelling often disregards variation arising from stochasticity in biological processes, heterogeneity among individuals and plasticity in trait values. However, these unaccounted-for sources of uncertainty are likely to be ecologically important and have the potential to impact estimates of coexistence.

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Restoration 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.

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Synchronous dynamics (fluctuations that occur in unison) are universal phenomena with widespread implications for ecological stability. Synchronous dynamics can amplify the destabilizing effect of environmental variability on ecosystem functions such as productivity, whereas the inverse, compensatory dynamics, can stabilize function. Here we combine simulation and empirical analyses to elucidate mechanisms that underlie patterns of synchronous versus compensatory dynamics.

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Modelling 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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Dispersal and dormancy are two common strategies allowing for species persistence and the maintenance of biodiversity in variable environments. However, theory and empirical tests of spatial diversity patterns tend to examine either mechanism in isolation. Here, we developed a stochastic, spatially explicit metacommunity model incorporating seed banks with varying germination and survival rates.

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Synchrony is broadly important to population and community dynamics due to its ubiquity and implications for extinction dynamics, system stability, and species diversity. Investigations of synchrony in community ecology have tended to focus on covariance in the abundances of multiple species in a single location. Yet, the importance of regional environmental variation and spatial processes in community dynamics suggests that community properties, such as species richness, could fluctuate synchronously across patches in a metacommunity, in an analog of population spatial synchrony.

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While we know climate change will impact individuals, populations, and communities, we lack a cross-scale synthesis for understanding global variation in climate change impacts and predicting their ecological effects. Studies of latitudinal variation in individuals' thermal responses have developed primarily in isolation from studies of natural populations' warming responses. Further, it is unclear whether latitudinal variation in temperature-dependent population responses will manifest into latitudinal patterns in community stability.

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Ecological stability refers to a family of concepts used to describe how systems of interacting species vary through time and respond to disturbances. Because observed ecological stability depends on sampling scales and environmental context, it is notoriously difficult to compare measurements across sites and systems. Here, we apply stochastic dynamical systems theory to derive general statistical scaling relationships across time, space, and ecological level of organisation for three fundamental stability aspects: resilience, resistance, and invariance.

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Coexistence and food web theory are two cornerstones of the long-standing effort to understand how species coexist. Although competition and predation are known to act simultaneously in communities, theory and empirical study of these processes continue to be developed largely independently. Here, we integrate modern coexistence theory and food web theory to simultaneously quantify the relative importance of predation and environmental fluctuations for species coexistence.

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Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics.

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Communities of free-living organisms are shaped by processes operating within and among patches of habitat, whereas pathogen communities are shaped by analogous processes operating within and among hosts. Resource competition (R*) theory can describe dynamics within patches or hosts, and metacommunity dynamics describe competition-colonization trade-offs, extinction debts, and superinfection. However, models at this broader scale often assume instantaneous competitive exclusion in co-inhabited patches or co-infected hosts.

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Environmental variability can structure species coexistence by enhancing niche partitioning. Modern coexistence theory highlights two fluctuation-dependent temporal coexistence mechanisms -the storage effect and relative nonlinearity - but empirical tests are rare. Here, we experimentally test if environmental fluctuations enhance coexistence in a California annual grassland.

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The spread of vector-borne pathogens depends on a complex set of interactions among pathogen, vector, and host. In single-host systems, pathogens can induce changes in vector preferences for infected vs. healthy hosts.

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Four metacommunity paradigms-usually called neutral, species sorting, mass effects, and patch dynamics, respectively-are widely used for empirical and theoretical studies of spatial community dynamics. The paradigm framework highlights key ecological mechanisms operating in metacommunities, such as dispersal limitation, competition-colonization tradeoffs, or species equivalencies. However, differences in coexistence mechanisms between the paradigms and in situations with combined influences of multiple paradigms are not well understood.

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Multilevel societies, containing hierarchically nested social levels, are remarkable social structures whose origins are unclear. The social relationships of sperm whales are organized in a multilevel society with an upper level composed of clans of individuals communicating using similar patterns of clicks (codas). Using agent-based models informed by an 18-year empirical study, we show that clans are unlikely products of stochastic processes (genetic or cultural drift) but likely originate from cultural transmission via biased social learning of codas.

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Background: Fetal intrauterine growth restriction (IUGR) results in increased placental resistance to blood flow, fetal hypertension, and increased pulsatility stresses shown to lead to vascular remodeling. We tested our hypothesis that IUGR causes decreased compliance in the carotid and umbilical arteries due to altered extracellular matrix (ECM) composition and structure.

Methods: A sheep model of placental insufficiency-induced IUGR (PI-IUGR) was created by exposure of the pregnant ewe to elevated ambient temperatures.

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