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Matching expert range maps with species distribution model predictions
Species’ range maps based on expert opinion are a critical resource for conservation planning. Expert maps are usually accompanied by species descriptions that specify sources of internal range heterogeneity, such as habitat associations, but these are rarely considered when using expert maps for an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7540670/ https://www.ncbi.nlm.nih.gov/pubmed/32115748 http://dx.doi.org/10.1111/cobi.13492 |
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author | Mainali, Kumar Hefley, Trevor Ries, Leslie Fagan, William F. |
author_facet | Mainali, Kumar Hefley, Trevor Ries, Leslie Fagan, William F. |
author_sort | Mainali, Kumar |
collection | PubMed |
description | Species’ range maps based on expert opinion are a critical resource for conservation planning. Expert maps are usually accompanied by species descriptions that specify sources of internal range heterogeneity, such as habitat associations, but these are rarely considered when using expert maps for analyses. We developed a quantitative metric (expert score) to evaluate the agreement between an expert map and a habitat probability surface obtained from a species distribution model. This method rewards both the avoidance of unsuitable sites and the inclusion of suitable sites in the expert map. We obtained expert maps of 330 butterfly species from each of 2 widely used North American sources (Glassberg [1999, 2001] and Scott [1986]) and computed species‐wise expert scores for each. Overall, the Glassberg maps secured higher expert scores than Scott (0.61 and 0.41, respectively) due to the specific rules (e.g., Glassberg only included regions where the species was known to reproduce whereas Scott included all areas a species expanded to each year) they used to include or exclude areas from ranges. The predictive performance of expert maps was almost always hampered by the inclusion of unsuitable sites, rather than by exclusion of suitable sites (deviance outside of expert maps was extremely low). Map topology was the primary predictor of expert performance rather than any factor related to species characteristics such as mobility. Given the heterogeneity and discontinuity of suitable landscapes, expert maps drawn with more detail are more likely to agree with species distribution models and thus minimize both commission and omission errors. |
format | Online Article Text |
id | pubmed-7540670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75406702020-10-15 Matching expert range maps with species distribution model predictions Mainali, Kumar Hefley, Trevor Ries, Leslie Fagan, William F. Conserv Biol Conservation Methods Species’ range maps based on expert opinion are a critical resource for conservation planning. Expert maps are usually accompanied by species descriptions that specify sources of internal range heterogeneity, such as habitat associations, but these are rarely considered when using expert maps for analyses. We developed a quantitative metric (expert score) to evaluate the agreement between an expert map and a habitat probability surface obtained from a species distribution model. This method rewards both the avoidance of unsuitable sites and the inclusion of suitable sites in the expert map. We obtained expert maps of 330 butterfly species from each of 2 widely used North American sources (Glassberg [1999, 2001] and Scott [1986]) and computed species‐wise expert scores for each. Overall, the Glassberg maps secured higher expert scores than Scott (0.61 and 0.41, respectively) due to the specific rules (e.g., Glassberg only included regions where the species was known to reproduce whereas Scott included all areas a species expanded to each year) they used to include or exclude areas from ranges. The predictive performance of expert maps was almost always hampered by the inclusion of unsuitable sites, rather than by exclusion of suitable sites (deviance outside of expert maps was extremely low). Map topology was the primary predictor of expert performance rather than any factor related to species characteristics such as mobility. Given the heterogeneity and discontinuity of suitable landscapes, expert maps drawn with more detail are more likely to agree with species distribution models and thus minimize both commission and omission errors. John Wiley and Sons Inc. 2020-08-23 2020-10 /pmc/articles/PMC7540670/ /pubmed/32115748 http://dx.doi.org/10.1111/cobi.13492 Text en © 2020 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Conservation Methods Mainali, Kumar Hefley, Trevor Ries, Leslie Fagan, William F. Matching expert range maps with species distribution model predictions |
title | Matching expert range maps with species distribution model predictions |
title_full | Matching expert range maps with species distribution model predictions |
title_fullStr | Matching expert range maps with species distribution model predictions |
title_full_unstemmed | Matching expert range maps with species distribution model predictions |
title_short | Matching expert range maps with species distribution model predictions |
title_sort | matching expert range maps with species distribution model predictions |
topic | Conservation Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7540670/ https://www.ncbi.nlm.nih.gov/pubmed/32115748 http://dx.doi.org/10.1111/cobi.13492 |
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