Details

Autor(en) / Beteiligte

• Bai, Wenke
• Huang, Qiongyu
• Zhang, Jindong
• Stabach, Jared
• Huang, Jinyan
• Yang, Hongbo
• Songer, Melissa
• Connor, Thomas
• Liu, Jianguo
• Zhou, Shiqiang
• Zhang, Hemin
• Zhou, Caiquan
• Hull, Vanessa

Titel

Microhabitat selection by giant pandas

Ist Teil von

• Biological conservation, 2020-07, Vol.247, p.108615, Article 108615

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2020

Link zum Volltext

Quelle

ScienceDirect Journals (5 years ago - present)

Beschreibungen/Notizen

• Understanding habitat selection is important for effective habitat management and recovery of species. However, many habitat selection studies are based on presence and absence data and do not differentiate the intensity of use and its association with fine-scale habitat characteristics. Such information is critical for improving our understanding of habitat suitability to inform conservation planning and practices, particularly for vulnerable species such as the giant panda (Ailuropoda melanoleuca) in China. We integrated Global Positioning Systems (GPS) tracking data of 5 giant pandas in Wolong Nature Reserve, China with detailed vegetation surveys to understand habitat selection by giant pandas. We compared microhabitat characteristics between the core and secondary home range areas of giant pandas and determined their relative importance using a resource selection function (RSF). We found that giant panda core areas had higher elevations, shorter distance to animal paths, shorter trees, and higher density of bamboo than the secondary area. Our findings shed new light on the importance of microhabitat characteristics that are generally overlooked in coarse-scale models in influencing giant panda habitat selection within the home range, such as bamboo density and accessibility to habitat that play important roles in the determination of core areas. We suggest prioritizing dense bamboo forests and areas with animal paths to improve giant pandas' habitat management, restoration, and corridor construction. The methods we used here regarding combining GPS-tracking derived intensity of use data and detailed habitat surveys could also be applied to better understand habitat selection strategies of a variety of other wildlife species.