Abstract

Climate change can affect the habitat resources available to species by changing habitat quantity, suitability and spatial configuration, which largely determine population persistence in the landscape. In this context, dispersal is a central process for species to track their niche. Assessments of the amount of reachable habitat (ARH) using static snap‐shots do not account, however, for the temporal overlap of habitat patches that may enhance stepping‐stone effects. Here, we quantified the impacts of climate change on the ARH using a spatio–temporal connectivity model. We first explored the importance of spatio–temporal connectivity relative to purely spatial connectivity in a changing climate by generating virtual species distributions and analyzed the relative effects of changes in habitat quantity, suitability and configuration. Then, we studied the importance of spatio–temporal connectivity in three vertebrate species with divergent responses to climate change in North America (grey wolf, Canadian lynx and white‐tailed deer). We found that the spatio–temporal connectivity could enhance the stepping‐stone effect for species predicted to experience range contractions, and the relative importance of the spatio–temporal connectivity increased with the reduction in habitat quantity and suitability. Conversely, for species that are likely to expand their ranges, spatio–temporal connectivity had no additional contribution to improve the ARH. We also found that changes in habitat amount (quantity and suitability) were more influential than changes in habitat configuration in determining the relative importance of spatio–temporal connectivity. We conclude that spatio–temporal connectivity may provide less biased and more realistic estimates of habitat connectivity than purely spatial connectivity.

Highlights

  • Patch i and j may either be directly connected if they are close enough, or may be indirectly connected through consecutive spatial paths if they are distant, it accounts for the stepping-stone effect

  • Where a( and a) are the patch attributes of node i and j, respectively; p(∗) is the maximum product probability of all possibly paths between i and j; A0 is the area of the study site

  • EC is defined as the habitat resources of a single patch that can provide the same value of probability of connectivity as the actual habitat pattern in a landscape (Saura, et al 2011). It is independent of the study area A0, it can avoid obtaining very little PC values when habitat area is small compared to the study area (Mailec 2008)

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Summary

Introduction

We used the PC family of metrics in our study. PC is the probability that two individuals randomly placed within a landscape fall into habitat patches that are reachable for each other across the habitat network (Saura and Pascual-Hortal 2007).

Results
Conclusion

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