A metapopulation approach to predict species range shifts under different climate change and landscape connectivity scenarios

- We propose a method to combine metapopulation and ecological niche models.
- Local extinction and colonization events are simulated using the incidence function model.
- Species range distributions are forecast for different landscape connectivity scenarios.
- Future climatic suitability is estimated with ecological niche models.
- Combining dispersal kernels and climatic suitability improves range shift predictions.

Forecasting future species distributions under climate change scenarios using Ecological Niche Models (ENM) is common practice. Typically, these projections do not account for landscape connectivity and species dispersal abilities. When they do account for these factors, they are based on either rather simplistic or overly complex and data-hungry approaches. Here we apply a new approach for predicting species range shifts under different climate change and landscape connectivity scenarios that balances data requirements and output quality. The approach builds on the metapopulation concept to produce a dispersal model based on repeated simulations of stochastic extinction-colonization dynamics across multiple landscapes of variable connectivity. The model is then combined with an ENM to produce more realistic predictions of species range shifts under environmental change. Using the near-threatened Cabrera vole (Microtus cabrerae) as a model species and considering two contrasting climate change scenarios (B2 and A1b) and three scenarios of increasing landscape connectivity, we confirmed that model predictions based solely on ENM overestimated future range sizes (2050 and 2080) in relation to predictions incorporating both future climates and landscape connectivity constraints. This supports the idea that landscape change critically affects species range shifts in addition to climate change, and that models disregarding landscape connectivity tend to produce overly optimistic predictions, particularly for species with low dispersal abilities. We suggest that our empirically-based simulation modelling approach provides a useful framework to improve range shift predictions for a broad range of species, which is essential for the conservation planning of metapopulations under climate and landscape change.