Karen Abbott

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  Effects of endogenous vs exogenous sources of spatial heterogeneity on population stability and persistence
  Karen Abbott
  Invasive species can be heavily influenced by spatial heterogeneity in the landscape through which they are spreading. This heterogeneity may be endogenous (that is, patchiness in the distribution of the invader itself, or heterogeneity in other species due directly to interactions with the invader) or it may be exogenous (such as patchy resources or heterogenous climatic conditions). I will discuss two studies, each dealing with one of these types of heterogeneity. First, I will present a model for spatial spread of an invasive seaweed that suggests different native grazers can have very different effects on invasion success by generating unique patterns of exogenous heterogeneity. This difference is due to the spatial distribution of disturbed patches, which when cleared of native seaweeds become available for establishment by the invader, that are characteristic of different grazers. Second, I will discuss the effects of population asynchrony (endogenous heterogeneity) on population stability and persistence. For this second topic, I will draw on models that are commonly applied to insect populations.
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  Giving "noise" the respect it deserves: ways to understand and visualize effects of stochasticity in ecological dynamics
  Karen Abbott
  Population dynamics result from a combination of deterministic mechanisms (e.g. competition, predation) that drive density-dependent dynamics and stochastic forces that disrupt the neat patterns that would otherwise result. Stochastic noise is often effectively viewed as a nuisance, seen as creating uncertainty and unpredictability without contributing in interesting ways to the list of mechanisms driving dynamics. However, it is becoming increasingly clear that in some situations, stochasticity itself plays an important qualitative role in shaping overall dynamical patterns, such that the dynamics cannot be fully understood by studying the deterministic mechanisms alone. Classical approaches to studying theoretical models are not well-equipped to make insights about these situations. Alternative analytical approaches exist but are not yet widely used in ecology. In this talk, I will present some useful ways to interpret and visualize effects of stochasticity in noisy ecological models, as well as some proof-of-concept examples to show the value of these approaches.