4.4 Review

Biases, gaps, and opportunities in mammalian extinction risk research

期刊

MAMMAL REVIEW
卷 46, 期 1, 页码 17-29

出版社

WILEY
DOI: 10.1111/mam.12049

关键词

bibliometric; hotspots; macroecology; modelling; threat status

资金

  1. Consejo Nacional de Ciencia y Tecnologia (CONACYT) [308685]
  2. University of Queensland UQ International

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1. A subdiscipline of conservation science involves the study of differences between threatened and non-threatened species. The relevance of multispecies analyses of extinction risk to conservation practice has been questioned, but there has been no synthesis of the allocation of research effort to different regions and groups of mammals to assess whether or not sufficient knowledge is available to support conservation science where it is most needed. 2. I reviewed 68 comparative studies of mammalian extinction risk to test whether existing research reflects our concern for threatened species. Additionally, I examined the variables used and various methodological issues that can lead to uninformative results. 3. Known spatial and taxonomic biases in conservation science persisted in extinction risk research, leaving large proportions of globally threatened taxa unstudied. Primates and carnivores had more dedicated studies, whereas small mammals such as rodents and the Eulipotyphla (true shrews, talpids, solenodons, gymnures, and hedgehogs) lack research effort despite their high diversity, threat, and extinction record. Except for the Australian mammal fauna (a clear priority given the number of threatened, extinct, and endemic taxa), most areas of conservation importance remain underrepresented in these types of studies. 4. Detailed country-level analyses can provide applicable results for understudied regions. I propose Southeast Asia and the Caribbean for further research, given their high levels of extinction, threat and endemism, and their unique biogeographic histories. Finally, I offer suggestions for general methodological improvements to avoid problems with missing data and statistical circularity in order to maximise conservation relevance.

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