Integrating species distribution models and interacting particle systems to predict the spread of an invasive alien plant

Aim We demonstrate how to integrate two widely used tools for modelling the spread of invasive plants, and compare the performance of the combined model with that of its individual components using the recent range dynamics of the invasive annual weed Ambrosia artemisiifolia L. Location Austria. Methods Species distribution models, which deliver habitat-based information on potential distributions, and interacting particle systems, which simulate spatio-temporal range dynamics as dependent on neighbourhood configurations, were combined into a common framework. We then used the combined model to simulate the invasion of A. artemisiifolia in Austria between 1990 and 2005. For comparison, simulations were also performed with models that accounted only for habitat suitability or neighbourhood configurations. The fit of the three models to the data was assessed by likelihood ratio tests, and simulated invasion patterns were evaluated against observed ones in terms of predictive discrimination ability (area under the receiver operating characteristic curve, AUC) and spatial autocorrelation (Moran's I). Results The combined model fitted the data significantly better than the single-component alternatives. Simulations relying solely on parameterized spread kernels performed worst in terms of both AUC and spatial pattern formation. Simulations based only on habitat information correctly predicted infestation of susceptible areas but reproduced the autocorrelated patterns of A. artemisiifolia expansion less adequately than did the integrated model. Main conclusions Our integrated modelling approach offers a flexible tool for forecasts of spatio-temporal invasion patterns from landscape to regional scales. As a further advantage, scenarios of environmental change can be incorporated consistently by appropriately updating habitat suitability layers. Given the susceptibility of many alien plants, including A. artemisiifolia, to both land use and climate changes, taking such scenarios into account will increasingly become relevant for the design of proactive management strategies.