Two alternative geographic distributions according to different methodologies.
The orange polygons represent the current distribution proposal according to the IUCN [ 37 ], in red the predicted areas as environmentally suitable for the species according to our niche model, the occurrence records are represented by gray points and green points are the records obtained during recent field expeditions. (A) Some areas predicted by the model but not included in the IUCN system were corroborated in the field with presence records of the species. (B) Some areas included in the IUCN system that were corroborated with presence data were not predicted by the model as suitable. The... Mehr ...
| Verfasser: | |
|---|---|
| Dokumenttyp: | Image |
| Erscheinungsdatum: | 2021 |
| Schlagwörter: | Molecular Biology / Evolutionary Biology / Ecology / Environmental Sciences not elsewhere classified / Biological Sciences not elsewhere classified / Maximum Entropy algorithm / ENM / Sabaleta Brycon henni / variable / Ecological niche modeling / IUCN / species occurrences / organism |
| Sprache: | unknown |
| Permalink: | https://search.fid-benelux.de/Record/base-28829161 |
| Datenquelle: | BASE; Originalkatalog |
| Powered By: | BASE |
| Link(s) : | https://doi.org/10.1371/journal.pone.0247876.g004 |
The orange polygons represent the current distribution proposal according to the IUCN [ 37 ], in red the predicted areas as environmentally suitable for the species according to our niche model, the occurrence records are represented by gray points and green points are the records obtained during recent field expeditions. (A) Some areas predicted by the model but not included in the IUCN system were corroborated in the field with presence records of the species. (B) Some areas included in the IUCN system that were corroborated with presence data were not predicted by the model as suitable. The data used for this figure under CC BY license is granted permission from the International Union for the Conservation of Nature (IUCN), original copyright 2019.