Matching expert range maps with species distribution model predictions
© 2020 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.
| Veröffentlicht in: | Conservation biology : the journal of the Society for Conservation Biology. - 1999. - 34(2020), 5 vom: 02. Okt., Seite 1292-1304 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | Conservation biology : the journal of the Society for Conservation Biology |
| Schlagworte: | Journal Article Research Support, U.S. Gov't, Non-P.H.S. Glassberg Glassberg 地图 Scott Scott 地图 acuerdo entre expertos borde detallado concavidad concavity mehr... |
| Zusammenfassung: | © 2020 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology. 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 |
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| Beschreibung: | Date Completed 26.02.2021 Date Revised 29.03.2024 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1523-1739 |
| DOI: | 10.1111/cobi.13492 |