Understanding how restoration reduces competition for habitat by combining theory, observation, and experiment.

Habitat selection theory enables inferences about species habitat choice across a range of observed population densities. However, it is relatively uncommon to use habitat selection theory in studies of habitat restoration efficacy to understand the effect of restoration on habitat competition. We combined observational density data and resource selection functions to analyze habitat correlations with both habitat selection theory and a mark-recapture experiment to show how habitat restoration can mitigate competition between species with similar habitat preferences.

Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.

Individual growth data are useful in assessing relative habitat quality, but this approach is less common when evaluating the efficacy of habitat restoration. Furthermore, available models describing growth are infrequently combined with computational approaches capable of handling large data sets. We apply a mechanistic model to evaluate whether selection of restored habitat can affect individual growth.

An Empirical Test of the Role of Small-Scale Transmission in Large-Scale Disease Dynamics.

A key assumption of epidemiological models is that population-scale disease spread is driven by close contact between hosts and pathogens. At larger scales, however, mechanisms such as spatial structure in host and pathogen populations and environmental heterogeneity could alter disease spread. The assumption that small-scale transmission mechanisms are sufficient to explain large-scale infection rates, however, is rarely tested.