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Title
Determining ranges of poorly known mammals as a tool for global conservation assessment
Author(s)
Stewart, Claire L.;Watson, James E.M.;Bland, Lucie M.;Tulloch, Ayesha I.T.
Published
2021
Publisher
Biological Conservation
Published Version DOI
https://doi.org/10.1016/j.biocon.2021.109188
Abstract
Incomplete taxonomic knowledge impedes biodiversity conservation. One in six species are classified as Data Deficient (DD) on the IUCN Red List. Despite often warranting urgent conservation attention, data-poor species are excluded from resource prioritizations and funding schemes. To enable strategic allocation of limited funds when knowledge gaps prevent effective conservation decisions, we provide a framework that estimates the costs of surveying species to accurately determine geographic range and extent of occurrence — such information is critical for informing criteria B1/B2 and D2 of IUCN extinction risk assessments. We determine the costs of surveying the entire distributional ranges of 493 IUCN DD mammal species and estimate that US$9.1–22.2 million is needed to improve knowledge on all species' extent of occurrence. Species costs varied substantially - for US$1,000,000, 116 (24%) of the least expensive DD mammals could be surveyed compared with only 18 (4%) of the most expensive mammals. Importantly, we found that sharing survey costs for co-occurring DD species reduced per-species costs in a location by more than 60%, indicating cost-efficiencies for allocating surveys to locations that might gain knowledge on a high number of species for low cost. We show how our framework and analytical methods to derive survey costs, can be adapted for other objectives, including tracking changes in species' populations over time to inform IUCN criterion A. Our study assists global and national efforts to conserve biodiversity, by identifying where and how to conduct surveys for data-poor species to identify significant populations that can be monitored over time.
Keywords
Optimal monitoring;Data deficient species;IUCN Red List;Mammals;Cost-effectiveness analysis
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PUB26595