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白颊猕猴在西藏雅鲁藏布大峡谷国家级自然保护区的栖息地适宜性评价

徐进博1#, 崔雅倩2#, 王渊4, 王伟波2,3, 刘锋4, 王广龙4, 扈晶晶4, 普布顿珠4, 边巴多吉4, 旦增4, 胡开4, 王小川4, 宋刚2, 吕永磊2,3,4*, 温知新2*   

  1. 1. 西藏农牧学院资源与环境学院, 西藏林芝 860000; 2. 中国科学院动物研究所动物进化与系统学院重点实验室, 北京 100101; 3. 中国科学院大学, 北京 100049; 4. 西藏自治区林业调查规划研究院, 拉萨 850000
  • 收稿日期:2024-11-08 修回日期:2025-02-17 接受日期:2025-05-11
  • 通讯作者: 吕永磊, 温知新

Habitat suitability evaluation of Macaca leucogenys in the Yarlung Zangbo Grand Canyon National Nature Reserve, Xizang

Jinbo Xu1#, Yaqian Cui2#, Yuan Wang4, Weibo Wang2,3, Feng Liu4, Guanglong Wang4, Jingjing Hu4, Dunzhu Pubu4, Duojl Bianba4, Zeng Dan4, Kai Hu4, Xiaochuan Wang4, Gang Song2, Yonglei Lü2,3,4*, Zhixin Wen2*   

  1. 1 College of Resources and Environment, Xizang Agricultural & Animal Husbandry University, Linzhi, Xizang 860000, China 

    2 Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China 

    3 University of Chinese Academy of Sciences, Beijing 100049, China 

    4 Forestry Inventory and Planning Institute of Xizang Autonomous Region, Lhasa 850000, China

  • Received:2024-11-08 Revised:2025-02-17 Accepted:2025-05-11
  • Contact: Yonglei Lü, Zhixin Wen

摘要: 白颊猕猴(Macaca leucogenys)是灵长目猴科猕猴属的国家二级重点保护野生动物, 是我国学者于2015年在墨脱地区发现并命名的新哺乳动物物种。白颊猕猴的分布范围有限, 种群数量稀少, 对于白颊猕猴栖息地适宜性评价方面尚缺乏相关的研究。为了解白颊猕猴的分布格局, 本研究通过红外相机布设与野外调查数据, 结合冠层高度、人类影响指数(human influence index)、归一化植被指数、海拔、坡向、坡度和19个生物气候因子, 使用MaxEnt模型系统分析了白颊猕猴在西藏雅鲁藏布大峡谷国家级自然保护区的栖息地分布现状及影响因素, 并根据未来不同气候变化情景下该区域的生境状况, 预测其栖息地的变化趋势。结果显示: (1)筛选后的影响因素拟合的MaxEnt模型AUC值为0.924, 表明模型预测结果较为准确; (2)影响白颊猕猴当前分布的关键环境变量为最湿月降水量(bio13)、人类影响指数(HII)、气温年较差(bio7)、降水季节性(bio15); (3)当前气候条件下, 白颊猕猴的高适生区大部分集中在西藏雅鲁藏布大峡谷国家级自然保护区的实验区内, 部分高适生区分布于达木核心区。在未来2050s年SSP1-2.6气候情景与SSP3-7.0气候情景下, 白颊猕猴的适生区相较于当前气候条件下均有所增加。本研究可为了解白颊猕猴当前及未来的分布情况以及对该珍稀物种实施有效的保护策略提供理论和基础数据支持。

关键词: 白颊猕猴, 西藏雅鲁藏布大峡谷国家级自然保护区, MaxEnt模型, 适宜性评价, 气候变化

Abstract

Aims: The white-cheeked macaque (Macaca leucogenys), a primate species of the genus Macaca, is classified as a Class II National Protected Animal in China. It is a newly discovered mammal species, first identified and named by Chinese scholars in the Motuo area in 2015. Due to its limited distribution range and small population size, research on the habitat suitability of Macaca leucogenys remains scarce. 

Methods: To understand the distribution patterns of Macaca leucogenys, this study integrated infrared camera surveys and field investigation data, with multiple environmental variables, including canopy height, human influence index (HII), normalized difference vegetation index (NDVI), elevation, aspect, slope, and 19 bioclimatic factors. We applied the MaxEnt model to systematically analyze the species’ current habitat distribution and key influencing factors within the Yarlung Zangbo Grand Canyon National Nature Reserve, Xizang. Additionally, we predicted habitat changes trends based on the habitat conditions of the region under different future climate scenarios. 

Results: (1) The MaxEnt models, fitted with the selected factors, achieved an AUC value of 0.924, indicating a high level of prediction accuracy; (2) the key environmental variables affecting the current distribution of Macaca leucogenys were precipitation of wettest month (bio13), human influence index (HII), annual temperature range (bio7) and seasonal precipitation (bio15); (3) under current climate conditions, the most suitable habitats for Macaca leucogenys are primarily concentrated in the experimental area of the Yarlung Zangbo Grand Canyon National Nature Reserve, with some high-suitability areas extending into Damu core area; (4) under future climate scenarios (SSP1-2.6 and SSP3-7.0) for the 2050s, the suitable habitat area for Macaca leucogenys is projected to increase compared to the current climate conditions. 

Conclusion: This study provides theoretical and foundational data for understanding the current and future distribution of Macaca leucogenys, which is important for designing effective conservation strategies for this endangered species.

Key words: Macaca leucogenys, Tibet's Yarlung Zangbo Grand Canyon National Nature Reserve, MaxEnt model, habitat suitability evaluation, climate change