The adaptive capacity of a species underlies its ability to persist in novel or actively changing environments. At a particular location, population-level responses to new conditions are determined by ecological and evolutionary processes that are difficult to disentangle. The eco-evolutionary dynamics in spatially distinct subpopulations may also be linked within a regional-scale metapopulation by individuals that disperse among sites. These subpopulations can occupy patches with biophysical characteristics that vary significantly, potentially favoring a wide array of optimal traits or trait values across the system. The dispersal network therefore dictates both demographic and genetic connectivity among subpopulations. Despite evidence that this connectivity constrains a metapopulation’s adaptive potential, the consequences of dispersal network topology in a changing environment have yet to be evaluated within a general eco-evolutionary framework. Here, we construct an eco-evolutionary metapopulation model in which we track the relative abundance of subpopulations across a network as well as a corresponding average trait value, the optimal growth temperature. Subpopulations are located across an environmental gradient where the similarity of temperature regimes decreases with distance between patches. We simulate the response of the metapopulation to climate change by performing temperature increase experiments on systems with regular and random dispersal networks.
Results/Conclusions
Under directed environmental change, dispersal network structure interacts with population growth and local selection to constrain the adaptive dynamics of a metapopulation. To encompass a range of biological systems, we test different levels of additive genetic variance as well as the ‘openness’ of the network, here defined as the relative amount of recruitment that occurs from outside vs. within the patch. Patches in regular networks reached higher levels of abundance across more combinations of system openness and additive genetic variance when compared to random networks. In general, closed systems lead to higher persistence than open systems, although in regular networks, we find evidence for an openness trade-off: at the same amount of additive genetic variance, a more open network can allow some patches to persist while relatively closed networks face system-wide extinction. However, maximum abundance is only possible in the latter. Finally, we find the strongest effects of dispersal network topology in the warmest patches, due to their greater reliance on evolutionary processes to adapt.