Prediction of potential habitat suitability of snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) and niche overlap in the parts of western Himalayan region

IF 1.7 Q2 GEOGRAPHY
Mohd Islam, Mehebub Sahana, Gopala Areendran, Chubamenla Jamir, Krishna Raj, Haroon Sajjad
{"title":"Prediction of potential habitat suitability of snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) and niche overlap in the parts of western Himalayan region","authors":"Mohd Islam,&nbsp;Mehebub Sahana,&nbsp;Gopala Areendran,&nbsp;Chubamenla Jamir,&nbsp;Krishna Raj,&nbsp;Haroon Sajjad","doi":"10.1002/geo2.121","DOIUrl":null,"url":null,"abstract":"<p>The snow leopard (<i>Panthera uncia</i>) and blue sheep (<i>Pseudois nayaur</i>) are the inhabitants of remote areas at higher altitudes with extreme geographic and climatic conditions. The habitats of these least-studied species are crucial for sustaining the Himalayan ecosystem. We employed the Maximum Entropy (MaxEnt) species distribution model to predict the potential habitat suitability of snow leopards and blue sheep and extracted common overlapped niches. For this, we utilised presence location, bio-climatic and environmental variables, and correlation analysis was applied to reduce the negative impact of multicollinearity. A total of 134 presence locations of snow leopards and 64 for blue sheep were selected from the Global Biodiversity Information Facility (GBIF). The annual mean temperature (Bio1) was found to be the most useful and highly influential factor to predict the potential habitat suitability of snow leopards. Annual mean temperature, annual precipitation and isothermality were the major influencing factors for blue sheep habitat suitability. Highly influential bio-climatic, topographic and environmental variables were integrated to construct the model for predicting habitat suitability. The area under the curve (AUC) values for snow leopard (0.87) and blue sheep (0.82) showed that the models are under good representation. Of the total area investigated, 47% was suitable for the blue sheep and 38% for the snow leopards. Spatial habitat assessment revealed that nearly 11% area from the predicted suitable habitat class of both species was spatially matched (overlapped), 48.6% area was unsuitable under niche overlap and 40.5% area was spatially mismatched niche. The presence of snow leopards and blue sheep in some highly suitable areas was not observed, yet such areas have the potential to sustain these elusive species. The other geographical regions interested in exploring habitat suitability may find the methodological framework adopted in this study useful for formulating an effective conservation policy and management strategy.</p>","PeriodicalId":44089,"journal":{"name":"Geo-Geography and Environment","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/geo2.121","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geo-Geography and Environment","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/geo2.121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 1

Abstract

The snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) are the inhabitants of remote areas at higher altitudes with extreme geographic and climatic conditions. The habitats of these least-studied species are crucial for sustaining the Himalayan ecosystem. We employed the Maximum Entropy (MaxEnt) species distribution model to predict the potential habitat suitability of snow leopards and blue sheep and extracted common overlapped niches. For this, we utilised presence location, bio-climatic and environmental variables, and correlation analysis was applied to reduce the negative impact of multicollinearity. A total of 134 presence locations of snow leopards and 64 for blue sheep were selected from the Global Biodiversity Information Facility (GBIF). The annual mean temperature (Bio1) was found to be the most useful and highly influential factor to predict the potential habitat suitability of snow leopards. Annual mean temperature, annual precipitation and isothermality were the major influencing factors for blue sheep habitat suitability. Highly influential bio-climatic, topographic and environmental variables were integrated to construct the model for predicting habitat suitability. The area under the curve (AUC) values for snow leopard (0.87) and blue sheep (0.82) showed that the models are under good representation. Of the total area investigated, 47% was suitable for the blue sheep and 38% for the snow leopards. Spatial habitat assessment revealed that nearly 11% area from the predicted suitable habitat class of both species was spatially matched (overlapped), 48.6% area was unsuitable under niche overlap and 40.5% area was spatially mismatched niche. The presence of snow leopards and blue sheep in some highly suitable areas was not observed, yet such areas have the potential to sustain these elusive species. The other geographical regions interested in exploring habitat suitability may find the methodological framework adopted in this study useful for formulating an effective conservation policy and management strategy.

Abstract Image

喜马拉雅西部部分地区雪豹(Panthera uncia)和蓝羊(Pseudois nayaur)潜在栖息地适宜性和生态位重叠的预测
雪豹(Panthera uncia)和蓝羊(Pseudois nayaur)生活在海拔较高的偏远地区,那里有极端的地理和气候条件。这些研究最少的物种的栖息地对维持喜马拉雅生态系统至关重要。利用最大熵(MaxEnt)物种分布模型对雪豹和蓝羊的潜在生境适宜性进行了预测,并提取了常见的重叠生态位。为此,我们利用存在位置、生物气候和环境变量,并应用相关分析来减少多重共线性的负面影响。从全球生物多样性信息设施(GBIF)中选择了134个雪豹和64个蓝羊的存在地点。年平均气温(Bio1)是预测雪豹潜在生境适宜性最有用且影响最大的因子。年平均气温、年降水量和等温是影响蓝羊生境适宜性的主要因素。综合影响较大的生物气候、地形和环境变量,构建了生境适宜性预测模型。雪豹(0.87)和蓝羊(0.82)的曲线下面积(AUC)值表明模型具有较好的代表性。在调查总面积中,适合蓝羊和雪豹生存的面积分别为47%和38%。空间生境评价结果表明,两种物种适宜生境类别中空间匹配(重叠)面积接近11%,生态位重叠不适宜面积为48.6%,生态位不匹配面积为40.5%。在一些高度适宜的地区没有观察到雪豹和蓝羊的存在,但这些地区有可能维持这些难以捉摸的物种。其他有兴趣探索生境适宜性的地理区域,可能会发现本研究采用的方法框架对制定有效的保育政策和管理策略有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.20
自引率
0.00%
发文量
12
审稿时长
25 weeks
期刊介绍: Geo is a fully open access international journal publishing original articles from across the spectrum of geographical and environmental research. Geo welcomes submissions which make a significant contribution to one or more of the journal’s aims. These are to: • encompass the breadth of geographical, environmental and related research, based on original scholarship in the sciences, social sciences and humanities; • bring new understanding to and enhance communication between geographical research agendas, including human-environment interactions, global North-South relations and academic-policy exchange; • advance spatial research and address the importance of geographical enquiry to the understanding of, and action about, contemporary issues; • foster methodological development, including collaborative forms of knowledge production, interdisciplinary approaches and the innovative use of quantitative and/or qualitative data sets; • publish research articles, review papers, data and digital humanities papers, and commentaries which are of international significance.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信