Estimating extinction risk with metapopulation models of large-scale fragmentation.
Journal Article (Journal Article)
Habitat loss is the principal threat to species. How much habitat remains-and how quickly it is shrinking-are implicitly included in the way the International Union for Conservation of Nature determines a species' risk of extinction. Many endangered species have habitats that are also fragmented to different extents. Thus, ideally, fragmentation should be quantified in a standard way in risk assessments. Although mapping fragmentation from satellite imagery is easy, efficient techniques for relating maps of remaining habitat to extinction risk are few. Purely spatial metrics from landscape ecology are hard to interpret and do not address extinction directly. Spatially explicit metapopulation models link fragmentation to extinction risk, but standard models work only at small scales. Counterintuitively, these models predict that a species in a large, contiguous habitat will fare worse than one in 2 tiny patches. This occurs because although the species in the large, contiguous habitat has a low probability of extinction, recolonization cannot occur if there are no other patches to provide colonists for a rescue effect. For 4 ecologically comparable bird species of the North Central American highland forests, we devised metapopulation models with area-weighted self-colonization terms; this reflected repopulation of a patch from a remnant of individuals that survived an adverse event. Use of this term gives extra weight to a patch in its own rescue effect. Species assigned least risk status were comparable in long-term extinction risk with those ranked as threatened. This finding suggests that fragmentation has had a substantial negative effect on them that is not accounted for in their Red List category.
- Schnell, JK; Harris, GM; Pimm, SL; Russell, GJ
- June 2013
Volume / Issue
- 27 / 3
Start / End Page
- 520 - 530
Electronic International Standard Serial Number (EISSN)
International Standard Serial Number (ISSN)
Digital Object Identifier (DOI)