Literature DB >> 20345399

Ecological-niche modeling and prioritization of conservation-area networks for Mexican herpetofauna.

J Nicolás Urbina-Cardona1, Oscar Flores-Villela.   

Abstract

One of the most important tools in conservation biology is information on the geographic distribution of species and the variables determining those patterns. We used maximum-entropy niche modeling to run distribution models for 222 amphibian and 371 reptile species (49% endemics and 27% threatened) for which we had 34,619 single geographic records. The planning region is in southeastern Mexico, is 20% of the country's area, includes 80% of the country's herpetofauna, and lacks an adequate protected-area system. We used probabilistic data to build distribution models of herpetofauna for use in prioritizing conservation areas for three target groups (all species and threatened and endemic species). The accuracy of species-distribution models was better for endemic and threatened species than it was for all species. Forty-seven percent of the region has been deforested and additional conservation areas with 13.7% to 88.6% more native vegetation (76% to 96% of the areas are outside the current protected-area system) are needed. There was overlap in 26 of the main selected areas in the conservation-area network prioritized to preserve the target groups, and for all three target groups the proportion of vegetation types needed for their conservation was constant: 30% pine and oak forests, 22% tropical evergreen forest, 17% low deciduous forest, and 8% montane cloud forests. The fact that different groups of species require the same proportion of habitat types suggests that the pine and oak forests support the highest proportion of endemic and threatened species and should therefore be given priority over other types of vegetation for inclusion in the protected areas of southeastern Mexico.

Mesh:

Year:  2010        PMID: 20345399     DOI: 10.1111/j.1523-1739.2009.01432.x

Source DB:  PubMed          Journal:  Conserv Biol        ISSN: 0888-8892            Impact factor:   6.560


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