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Environmental and socioeconomic correlates of extinction risk in endemic species

Publikace na Přírodovědecká fakulta |
2022

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

Aim: Our current understanding of the causes of global extinction risk is mostly informed by the expert knowledge-based "threats classification scheme" of the IUCN Red List of Threatened Species. Studies based on this dataset came to different conclusions about the relative importance of threats to species, depending on which taxonomic groups and levels of extinction risk were considered, and which version of the database was used. A key reason may lie in data limitations as causes of threat are well known for charismatic and well-studied species, but not for the majority of species assessed. Here, we aim to fill current knowledge gaps about the importance of drivers of global extinction risks by focusing on endemic species.

Location: Global.

Methods: We examined country-level variation in the proportion of globally threatened and extinct endemic species (Index of Threat, IoT) with a range of spatially explicit information about anthropogenic pressures, mitigation measures and data limitations.

Results: IoT coincided with several anthropogenic pressures, with substantial differences among kingdoms, life-forms, levels of extinction risk and geographic locations. IoT of plants, particularly tropical woody plants of moderate extinction risk, was higher in countries with higher GDP and more invasive species. Furthermore, IoT of animals, particularly tropical mammals and invertebrates of moderate extinction risk, was higher in countries with higher GDP and smaller roadless areas.

Main conclusions: The extinction crisis for endemic species is associated with a complex network of potential drivers that need to be considered in concert in conservation policy and practice. Although our results require careful interpretation and remain sensitive to data limitations, we encourage similar studies at smaller scales to identify potential drivers of extinction risk at a higher resolution, particularly in regions where species assessments have been conducted consistently or on organisms with a uniform response time to pressures.