Maintaining the ability of organisms to move between suitable patches of habitat despite ongoing habitat loss is essential to conserving biodiversity. Quantifying connectivity has therefore become a central focus of conservation planning. A large number of metrics have been developed to estimate potential connectivity based on habitat configuration, matrix structure and information on organismal movement, and it is often assumed that metrics explain actual connectivity. Yet, validation of metrics is rare, particularly across entire landscapes undergoing habitat loss—a crucial problem that connectivity conservation aims to mitigate. We leveraged a landscape‐scale habitat loss and fragmentation experiment to assess the performance of commonly used patch‐ and landscape‐scale connectivity metrics against observed movement data, test whether incorporating information about the matrix improves connectivity metrics and examine the performance of metrics across a gradient of habitat loss. We tested whether 38 connectivity metrics predict movement at the patch (i.e. patch immigration rates) and landscape (i.e., total movements) scale for a pest insect, the cactus bug Metrics varied widely in their ability to explain actual connectivity. At the patch scale, dPC
Connectivity has long played a central role in ecological and evolutionary theory and is increasingly emphasized for conserving biodiversity. Nonetheless, connectivity assessments often focus on individual species even though understanding and preserving connectivity for entire communities is urgently needed. Here we derive and test a framework that harnesses the well-known allometric scaling of animal movement to predict community-level connectivity across protected area networks. We used a field translocation experiment involving 39 species of southern African birds to quantify movement capacity, scaled this relationship to realized dispersal distances determined from ring-and-recovery banding data, and used allometric scaling equations to quantify community-level connectivity based on multilayer network theory. The translocation experiment explained observed dispersal distances from ring-recovery data and emphasized allometric scaling of dispersal based on morphology. Our community-level networks predicted that larger-bodied species had a relatively high potential for connectivity, while small-bodied species had lower connectivity. These community networks explained substantial variation in observed bird diversity across protected areas. Our results highlight that harnessing allometric scaling can be an effective way of determining large-scale community connectivity. We argue that this trait-based framework founded on allometric scaling provides a means to predict connectivity for entire communities, which can foster empirical tests of community theory and contribute to biodiversity conservation strategies aimed at mitigating the effects of environmental change.
more » « less- NSF-PAR ID:
- 10187067
- Publisher / Repository:
- Proceedings of the National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 117
- Issue:
- 36
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- p. 22274-22280
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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