Assisted migration is a controversial management technique involving the intentional movement of a species beyond its historical range to promote that species’ persistence under rapid climate change. On the population level, a well-planned relocation should decrease the extinction risk of a dispersal-limited species, but moving that species to the wrong place at the wrong time might instead increase its extinction risk. On the community level, there is substantial concern that a relocated species could become invasive. However, the relocated species might also contribute to community stability by preventing the competitive release of dominant, high-dispersal species. To quantify the relative risks of both engaging and not engaging in relocation, we created a stochastic, temperature-dependent, spatial metacommunity model. Each species in the community moves along a temperature gradient as they cycle through reproduction, dispersal, and competition, each of which can be temperature-dependent processes. With this model, we created a set of randomized metacommunities that are stable with low environmental stochasticity. We then simulated these metacommunities over projected climate change scenarios, comparing the results from cases where declining populations are either relocated or left untouched.
Results/Conclusions
When unmanaged, few species in the community go extinct in response to climate change without competition, and few species go extinct in response to competition without climate change. However, extinction rates are highest when both competition and climate change occur together, implying that the interaction between these factors can decrease the biodiversity of a previously stable metacommunity. When declining populations are relocated to areas that match their optimum temperature, not only are they more likely to persist, the total metacommunity diversity is also higher. These results stress the potential community-scale benefits of relocating a population to an analogous self-dispersing community. However, many of these results assume we have perfect knowledge of each parameter and variable. Under a more realistic scenario where we do not know the details of community interactions and each species’ niche space, we will have little precision in estimating the fate of individual populations, but we can hope to make some predictions on the community level. We encourage more research on community interactions that might impact the invasiveness or stability associated with assisted migration, including the potential for predator and pathogen release.