Journal article

Cost-effective assessment of extinction risk with limited information

Lucie M Bland, C David L Orme, Jon Bielby, Ben Collen, Emily Nicholson, Michael A McCarthy



Cost‐effective reduction of uncertainty in global biodiversity indicators is a central goal of conservation. Comprising a sixth of the 74 000+ species currently on the IUCN Red List, Data Deficient species contribute to considerable uncertainty in estimates of extinction risk. Estimating levels of risk in Data Deficient species will require large resources given the costs of surveys and Red List assessments. Predicting extinction risk from species traits and geographical information could provide a cheaper approach for determining the proportion of Data Deficient species at risk of extinction. We use double sampling theory to compare the cost‐effectiveness of predictive models and IUCN Red L..

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Funding Acknowledgements

This research was supported by a Travel Fellowship to L.B. from the Australian Research Council (ARC) Centre of Excellence for Environmental Decisions, an ARC Future Fellowship to M.A.M. and a Centenary Research Fellowship to E.N. We thank the collaborative effort among the National Autonomous University of Mexico, Stony Brook University, Nature Serve and the Institute of Zoology for the collection of reptile data, particularly Andres Garcia, Monika Bohm and Ana Davidson. We thank the curation staff of the Natural History Museum London, Musee d'Histoire Naturelle Paris, Museum Victoria and the Australian Museum for assistance in collecting crayfish data.