Predicting invasions: alternative models of human-mediated dispersal and interactions between dispersal network structure and Allee effects.
Abstract
Human-mediated dispersal has been shown to be the most important vector for the spread of invasive species, yet there has been little evaluation of alternative models of dispersal in terms of differences in their predictions of invasion patterns. Moreover, no analyses have been attempted to elucidate the potential interaction between alternative models of human-mediated dispersal and population dynamical characteristics, such as Allee effects, which are central to the probability of an invasion. Two prominent models in the literature which have previously been employed to predict human movement patterns are explored: (i) gravity models, which use the attractiveness of and distance to a location to predict travel patterns, and (ii) random utility models, which assume that individuals decide where to travel by maximizing the benefits that they receive according to some partially observable function of individual and site characteristics. While distinction is often drawn between them in the literature, we demonstrate that these two approaches can be reduced to alternative functional forms describing the trip-taking decisions of individuals. Each model was empirically parameterized using a survey of recreational boaters in Ontario, Canada. Within each model, both boater- and site-specific characteristics were important and the functional form provided by the gravity model was significantly better at capturing the behaviour of recreational boaters. Synthesis and applications. The dispersal and establishment of species into novel habitats are central components of the invasion process and of quantitative risk assessments. However, predictions are dependent on the estimated spatial structure of the dispersal network and its potential interactions with species characteristics. This study demonstrates that Allee effects can interact with dispersal network structure to significantly alter predicted spread rates and that the consequences of these interactions manifest differently at the system and site levels. This modelling framework can be used to inform management interventions aimed at modifying human-mediated dispersal to reduce the spread of invasive species.