Habitat connectivity is a crucial determinant of population dynamics in fragmented landscapes. We present a study exploring how targeted disruption of connectivity may provide a useful tool for controlling invasive species. We hypothesized that by targeting the most connected habitats in a landscape, based on network topology, control of invasive species can be optimized. To test this hypothesis, we implemented a simulation model of the spread of an invasive species on a network and used it to evaluate whether targeting the better-connected components of the landscape enhances control effectiveness. This was compared to strategies where a similar level of control was applied to either randomly chosen locations, locations that were close to other locations, or locations based on demographic parameters, such as carrying capacity or the intrinsic rate of increase.
Results/Conclusions
Our findings show that control strategies based on network topology consistently outperform strategies based on random habitat selection or on separation distance alone. The advantages of the connectivity-based strategy were strongest in the early phases of the invasion process, when a small number of habitats are occupied at low population density. However, if long distance dispersal events are common, the advantages of the connectivity approach are markedly weakened. Further exploration of the model indicated that our results were robust to habitat-level demographic stochasticity. In fact, connectivity-based targeting outperformed a strategy based on demographic processes, with the additional benefit that it requires less information to be implemented.
Overall, our model outcomes demonstrate that deliberately targeting the best-connected components of a landscape is an efficient control strategy if long-distance dispersal is infrequent, and it is likely to be cheaper than other alternatives such as targeting population sources.