Details

Autor(en) / Beteiligte

• McShea, William J.
• Hwang, Mei-Hsiu
• Liu, Fang
• Li, Sheng
• Lamb, Clayton
• McLellan, Bruce
• Morin, Dana J.
• Pigeon, Karine
• Proctor, Michael F.
• Hernandez-Yanez, Haydee
• Frerichs, Taylor
• Garshelis, David L.

Titel

Is the delineation of range maps useful for monitoring Asian bears?

Ist Teil von

• Global ecology and conservation, 2022-06, Vol.35, p.e02068, Article e02068

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2022

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Changes in the distribution of a species can be used to as a metric of conservation status and to identify the loss or gain of isolated populations. This mapping process is a primary tool of the IUCN SSC Red List assessment. Most distribution maps are based on expert opinion or species distribution models based on a combination of species detection records and known habitat and landscape affiliations for that species. However, modeling the distribution for some species is difficult due to low levels of sampling, low detectability, and loose or uncertain associations with landscape attributes. These issues may be particularly prevalent for Asian bears that have generalist habitat requirements and are heavily poached across their range. Presently the range of all bear species in Asia is delineated primarily using expert opinion. Members of the IUCN SSC Bear Specialist Group attempted to create a rule set to combine current detections with known habitat and home range preferences to improve distribution maps for the purpose of conservation metrics and monitoring. The results of applying this rule set for giant pandas (Ailuropoda melanoleuca) closely matched the current IUCN mapped range, but the results for Asiatic black bears (Ursus thibetanus) did not corroborate the IUCN map based solely on expert opinion. We present a list of recommended actions for improving distribution mapping for bears in Asia and possibly any species whose current distribution is heavily influenced by poorly measured metrics such as poaching.