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A MaxEnt modelling approach to understand the climate change effects on the distributional range of White-bellied Sholakili Sholicola albiventris (Blanford, 1868) in the Western Ghats,India
Institution:1. Department of Wildlife and Habitat Management, Forest College and Research Institute, Mulugu, Hyderabad, Telangana 502279, India;2. Department of Wildlife Science, College of Forestry, Kerala Agricultural University, Thrissur, Kerala 680656, India;1. Center for Biological Control, Department of Zoology and Entomology, Rhodes University, Makhanda, 6140, South Africa;2. Afromontane Research Unit and Department Zoology and Entomology, University of the Free State, Phuthaditjhaba, 9866, South Africa;1. Higher Agronomic Institute of Chott-Mariem, University of Sousse, BP 47, 4042 Sousse, Tunisia;2. Aix_Marseille University and University of Sfax, Tunisia;1. Faculty of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China;2. National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Changsha 410004, China;3. Huitong National Field Station for Scientific Observation and Research of Chinese Fir Plantation Ecosystem in Hunan Province, Huitong 438107, China
Abstract:Each species is uniquely influenced by anthropogenic climate change. Change in temperature and precipitation due to climate change may lead to species adaptation or extinction, or in some cases, a range shift. To know the influence of climate change on a restricted and endemic bird species of the Western Ghats (WG), White-bellied Sholakili (WBS) Sholicola albiventris (Blanford, 1868), we conducted a study by using species distribution modelling. We considered 73 spatial bias-corrected occurrence points of WBS along with environmental variables like the mean temperature of coldest quarter (Bio 11), precipitation of driest month (Bio 14) and mean precipitation of warmest quarter (Bio 18). We used the MaxEnt application with ENM evaluate tool in R statistical package for developing a climate model for WBS. Bio 11 was observed to be the most crucial climate variable shaping the habitat of WBS. The current study predicts that only 2823km2 in WG is suitable for WBS. One-third of this area falls under the protected area network, of which 52% is becoming unsuitable to this narrow endemic due to climate warming. The model also predicts 26% to 45% habitat loss under different climate change scenarios by the 2050s.
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