Species may be driven extinct by climate change, unless their populations are able to shift fast enough to track regions of suitable climate. It is therefore crucial to understand and quantify the rate of a species' advance into newly suitable regions. Shifting will be easier as the proportion of suitable habitat in the landscape increases. However, it is not known how the spatial arrangement of habitat will affect the speed of advance that can be achieved, especially when habitat is scarce, as is the case for many specialist species. There is considerable debate about the relative benefits of linking features in the form of corridors or stepping stones, versus preserving or enlarging sites that will support large, robust populations. We have developed new methods for calculating the speed of advance of a population front that are appropriate for highly fragmented, stochastic systems.
Results/Conclusions
We reveal that spatial aggregation of habitat tends to reduce the speed of advance. This is despite the fact that aggregation increases the steady-state population size and the proportion of habitat that is occupied (without climate change). Some core principles of conservation have been based on such steady-state properties. Because rate of advance is a property that behaves very differently, these principles are no longer sufficient to manage conservation under climate change. We need to explicitly consider and disentangle characteristics of a landscape that affect of ease of colonization from outside, versus characteristics that affect the probability of persistence once established. Steady-state occupancy and persistence can be predicted from simple statistics of spatial aggregation of habitat, but speed of advance can not. For example, the fastest advance results when the habitat has a "channeled" pattern, which is neither maximally aggregated nor maximally disaggregated. Channeled patterns can be interpreted as providing as system of corridors, but these are routes allowing population establishment and growth, not just dispersal. We can efficiently predict the rate of advance in any landscape in a given direction by employing techniques from electrical circuit theory. We demonstrate, using a case study, how our methods can be used to aid land use planning to conserve multiple species.