Accounting for uncertainty in colonisation times: a novel approach to modelling the spatio-temporal dynamics of alien invasions using distribution data

Abstract
A novel, yet generic, Bayesian approach to parameter inference in a stochastic, spatio-temporal model of dispersal and establishment is developed and applied to the invasion of a region by an alien plant species. The method requires species distribution data from multiple time points, and accounts for temporal uncertainty in colonisation times inherent in such data. Covariates which capture landscape heterogeneity are easily incorporated into the model, which is applicable to any plant species whose range is expanding over time. The implementation of the model and inference algorithm are illustrated through application to British floristic atlas data for Heracleum mantegazzianum (giant hogweed), an invasive alien plant that has rapidly increased its range since 1970. We infer key characteristics of this species, predict its future spread, and use the resulting fitted model to inform a simulation-based assessment of the methodology. Simulated distribution data are used to validate the inference algorithm. Our results suggest that the accuracy of inference is not sensitive to the number of distribution time points, requiring only that there are at least two points in time when distributions are mapped. We demonstrate the utility of the modelling by making future and historic predictions of the distribution of giant hogweed in Britain and discuss the potential for modelling distribution data for other species and at different spatial scales.
Year
2012
Category
Refereed journal
Output Tags
WP6.2 - Prevention and control of important diseases of animals
WP3.4 - Resilience of Scotland's biodiversity to change