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Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments
Estimates of species geographic ranges constitute critical input for biodiversity assessments, including those for the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. Area of occupancy (AOO) is one metric that IUCN uses to quantify a species’ range, but data...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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John Wiley and Sons Inc.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099578/ https://www.ncbi.nlm.nih.gov/pubmed/36285611 http://dx.doi.org/10.1111/cobi.14019 |
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author | Anderson, Robert P. |
author_facet | Anderson, Robert P. |
author_sort | Anderson, Robert P. |
collection | PubMed |
description | Estimates of species geographic ranges constitute critical input for biodiversity assessments, including those for the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. Area of occupancy (AOO) is one metric that IUCN uses to quantify a species’ range, but data limitations typically lead to either under‐ or overestimates (and unnecessarily wide bounds of uncertainty). Fortunately, existing methods in which range maps and land‐cover data are used to estimate the area currently holding habitat for a species can be extended to yield an unbiased range of plausible estimates for AOO. Doing so requires estimating the proportion of sites (currently containing habitat) that a species occupies within its range (i.e., prevalence). Multiplying a quantification of habitat area by prevalence yields an estimate of what the species inhabits (i.e., AOO). For species with intense sampling at many sites, presence–absence data sets or occupancy modeling allow calculation of prevalence. For other species, primary biodiversity data (records of a species’ presence at a point in space and time) from citizen‐science initiatives and research collections of natural history museums and herbaria could be used. In such cases, estimates of sample prevalence should be corrected by dividing by the species’ detectability. To estimate detectability from these data sources, extensions of inventory‐completeness analyses merit development. With investments to increase the quality and availability of online biodiversity data, consideration of prevalence should lead to tighter and more realistic bounds of AOO for many taxonomic groups and geographic regions. By leading to more realistic and representative characterizations of biodiversity, integrating maps of current habitat with estimates of prevalence should empower conservation practitioners and decision makers and thus guide actions and policy worldwide. |
format | Online Article Text |
id | pubmed-10099578 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100995782023-04-14 Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments Anderson, Robert P. Conserv Biol Essays Estimates of species geographic ranges constitute critical input for biodiversity assessments, including those for the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. Area of occupancy (AOO) is one metric that IUCN uses to quantify a species’ range, but data limitations typically lead to either under‐ or overestimates (and unnecessarily wide bounds of uncertainty). Fortunately, existing methods in which range maps and land‐cover data are used to estimate the area currently holding habitat for a species can be extended to yield an unbiased range of plausible estimates for AOO. Doing so requires estimating the proportion of sites (currently containing habitat) that a species occupies within its range (i.e., prevalence). Multiplying a quantification of habitat area by prevalence yields an estimate of what the species inhabits (i.e., AOO). For species with intense sampling at many sites, presence–absence data sets or occupancy modeling allow calculation of prevalence. For other species, primary biodiversity data (records of a species’ presence at a point in space and time) from citizen‐science initiatives and research collections of natural history museums and herbaria could be used. In such cases, estimates of sample prevalence should be corrected by dividing by the species’ detectability. To estimate detectability from these data sources, extensions of inventory‐completeness analyses merit development. With investments to increase the quality and availability of online biodiversity data, consideration of prevalence should lead to tighter and more realistic bounds of AOO for many taxonomic groups and geographic regions. By leading to more realistic and representative characterizations of biodiversity, integrating maps of current habitat with estimates of prevalence should empower conservation practitioners and decision makers and thus guide actions and policy worldwide. John Wiley and Sons Inc. 2022-11-16 2023-02 /pmc/articles/PMC10099578/ /pubmed/36285611 http://dx.doi.org/10.1111/cobi.14019 Text en © 2022 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Essays Anderson, Robert P. Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments |
title | Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments |
title_full | Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments |
title_fullStr | Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments |
title_full_unstemmed | Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments |
title_short | Integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments |
title_sort | integrating habitat‐masked range maps with quantifications of prevalence to estimate area of occupancy in iucn assessments |
topic | Essays |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099578/ https://www.ncbi.nlm.nih.gov/pubmed/36285611 http://dx.doi.org/10.1111/cobi.14019 |
work_keys_str_mv | AT andersonrobertp integratinghabitatmaskedrangemapswithquantificationsofprevalencetoestimateareaofoccupancyiniucnassessments |