Abstract

AbstractIn order to make robust and feasible conservation plans, assessments of species' vulnerability or risk of extinction are ideally needed. However, there are wide differences in the criteria used to assess species vulnerability. Recently, a growing approach seeks to understand the patterns of biodiversity loss using life history traits because these traits show differential responses to environmental disturbances. In order to generate a functional vulnerability assessment for Mexican endemic amphibians, we integrated information from species distribution modeling, functional traits, and spatially explicit threats weighted differentially for each functional group. We obtained 124 distribution models evaluated by species, nine functional groups that represent the differential risk of species against anthropic threats, and 124 layers of spatial vulnerability. We found a generalized presence of threats to amphibians throughout the Mexican territory, highlighting the center of the country as the most affected area, while the southeast and north had a lower level of anthropic activity. We found differential vulnerability values in the distributions of Mexican endemic amphibians. In general, the anthropogenic impact on the distribution of Mexican endemic amphibians is high, and the percentage of habitat loss ranges from 51 to 97%, with an average of 83% lost to anthropogenic pressures. The functional group with the greatest loss of distributional area was found in the salamander genus Ambystoma, while functional groups 2 (frogs with arboreal habits, small size, and reproduction and development in bodies of water) and 4 (small or medium size frogs occupying terrestrial or riparian habitats with oviposition and development occurring in bodies of water or phytotelms) maintain the largest remaining suitable area after considering the threats. We present a replicable methodology that can be implemented anywhere, providing a new tool to generate specific layers that represent threats to functional groups. This allows for updated assessments of species distribution models that can be used in conservation planning, offering more robust data to make conservation planning decisions.

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