Toward quantification of the impact of 21st‐century deforestation on the extinction risk of terrestrial vertebrates

Łukasz Tracewski, Stuart H.M. Butchart, Moreno Di Marco, Gentile F. Ficetola, Carlo Rondinini, Andy Symes, Hannah Wheatley, Alison E. Beresford, and Graeme M. Buchanan

Conservation actions need to be prioritised, often taking into account species’ extinction risk. The International Union for Conservation of Nature (IUCN) Red List provides an accepted objective framework for the assessment of extinction risk, but field data to apply the IUCN Red List criteria are often limited. Information collected through remote sensing can inform these assessments, and forests are perhaps the best-studied habitat type for use in this approach. Using an open-access 30 m resolution map of tree cover and its change between 2000 and 2012, the extent of forest cover and loss within the distributions of 11,186 forest-dependent amphibians, birds and mammals worldwide was assessed. Sixteen species have experienced sufficiently high rates of forest loss to be considered at elevated extinction risk under Red List criterion A, owing to inferred rapid population declines. This number would increase to 23 if data deficient species (i.e., those with insufficient information previously to apply the Red List criteria) were included. Some 484 species (855 if data deficient species are included) may be considered at elevated extinction risk under Red List criterion B2, owing to restricted areas of occupancy resulting from little forest cover remaining within their ranges. This would increase the proportion of species of conservation concern by 32.8% for amphibians, 15.1% for birds and 24.7% for mammals. Central America, the Northern Andes, Madagascar, the Eastern Arc forests in Africa and the islands of South-East Asia are hotspots for these species. The analyses illustrate the utility of satellite imagery for global extinction risk assessment and measurement of progress towards international environmental agreement targets. We highlight areas for which subsequent analyses could be performed on satellite image data in order to improve our knowledge of extinction risk of species.

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