Predicting and setting conservation priorities for Bolivian mammals based on biological correlates of the risk of decline |
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| Authors: | Diego A. Peñaranda Javier A. Simonetti |
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| Affiliation: | 1. Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile, Casilla, Santiago, Chile;2. Programa para la Conservación de los Murciélagos de Bolivia, Cochabamba, Bolivia |
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| Abstract: | The recognition that growing proportions of species worldwide are endangered has led to the development of comparative analyses to elucidate why some species are more prone to extinction than others. Understanding factors and patterns of species vulnerability might provide an opportunity to develop proactive conservation strategies. Such comparative analyses are of special concern at national scales because this is the scale at which most conservation initiatives take place. We applied powerful ensemble learning models to test for biological correlates of the risk of decline among the Bolivian mammals to understand species vulnerability at a national scale and to predict the population trend for poorly known species. Risk of decline was nonrandomly distributed: higher proportions of large‐sized taxa were under decline, whereas small‐sized taxa were less vulnerable. Body mass, mode of life (i.e., aquatic, terrestrial, volant), geographic range size, litter size, home range, niche specialization, and reproductive potential were strongly associated with species vulnerability. Moreover, we found interacting and nonlinear effects of key traits on the risk of decline of mammals at a national scale. Our model predicted 35 data‐deficient species in decline on the basis of their biological vulnerability, which should receive more attention in order to prevent their decline. Our results highlight the relevance of comparative analysis at relatively narrow geographical scales, reveal previously unknown factors related to species vulnerability, and offer species‐by‐species outcomes that can be used to identify targets for conservation, especially for insufficiently known species. Predección y Definición de Prioridades de Conservación para Mamíferos de Bolivia con Base en Correlaciones Biológicas del Riesgo de Declinación |
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| Keywords: | extinction population trend predictive modeling random forest species vulnerability bosque aleatorio extinció n modelado predictivo tendencia poblacional vulnerabilidad de especies |
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