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应用生态学报 ›› 2026, Vol. 37 ›› Issue (3): 865-875.doi: 10.13287/j.1001-9332.202602.029

• 研究论文 • 上一篇    下一篇

西藏芒康滇金丝猴国家级自然保护区生态环境质量时空变化及影响因素

任雨航1,2, 张同3, 廖梓延1, 潘俊杰1,2, 刘黄诚4, 李金洁5, 潘开文1, 张林1, 伍小刚1*   

  1. 1中国科学院成都生物研究所山地生态恢复与生物多样性保护四川省重点实验室, 成都 610213;
    2中国科学院大学, 北京 100049;
    3国家林业和草原局中南调查规划院, 长沙 410014;
    4中国电建集团中南勘测设计研究院有限公司, 长沙 410014;
    5华能澜沧江水电股份有限公司, 昆明 650214
  • 收稿日期:2025-07-30 接受日期:2025-12-30 出版日期:2026-03-18 发布日期:2026-09-18
  • 通讯作者: *E-mail: wuxg@cib.ac.cn
  • 作者简介:任雨航, 男, 2000年生, 硕士研究生。主要从事植被生态遥感研究。E-mail: renyh@cib.ac.cn
  • 基金资助:
    国家自然科学基金项目(32201424)、2020年中央财政林业草原生态保护恢复资金项目(GZFCG2022-7627)和中国华能集团有限公司科技项目(HNKJ22-H109)

Spatiotemporal variation and driving factor of ecological enviornment quality in the Markam Yunnan Snub-nosed Monkey National Nature Reserve, Tibet, China

REN Yuhang1,2, ZHANG Tong3, LIAO Ziyan1, PAN Junjie1,2, LIU Huangcheng4, LI Jinjie5, PAN Kaiwen1, ZHANG Lin1, WU Xiaogang1*   

  1. 1Mountain Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610213, China;
    2University of Chinese Academy of Sciences, Beijing 100049, China;
    3Central South Survey and Planning Institute of National Forestry and Grassland Administration, Changsha 410014, China;
    4China Power Construction Corporation Zhongnan Survey and Design Institute Co., Ltd, Changsha 410014, China;
    5Huaneng Lancang River Hydropower Co., Ltd, Kunming 650214, China
  • Received:2025-07-30 Accepted:2025-12-30 Online:2026-03-18 Published:2026-09-18

摘要: 滇金丝猴是我国特有珍稀濒危物种,其栖息地生态环境质量直接影响种群存续。本研究以西藏芒康滇金丝猴国家级自然保护区为研究对象,基于2000—2024年Landsat影像数据计算得到遥感生态指数(RSEI),通过Theil-Sen Median等趋势分析方法及XGBoost结合SHAP模型分析了该保护区生态环境质量的时空变化特征及影响因素。结果表明:2000—2024年间,研究区RSEI值总体呈现波动上升趋势,并于2024年达到最高值;空间上呈现出“中心稳定、边缘退化”的分布格局。研究区RSEI值改善的区域主要分布于中东部及西部部分高海拔地区,退化区域集中在保护区西侧边缘地带,预测未来约42%的区域可能面临生态退化风险。土地利用是影响RSEI的主要因素,高程、年均气温和积雪覆盖率与其对RSEI值的交互影响作用显著,各驱动因子对RSEI呈明显的非线性影响。本研究可为珍稀濒危保护物种栖息地生态环境质量评估提供科学依据。

关键词: 遥感生态指数, 空间异质性, 机器学习, 自然保护区

Abstract: Rhinopithecus bieti is a rare and endangered species unique to China, and habitat ecological environment quality would affect its population persistence. Taking the Markam Yunnan Snub-nosed Monkey National Nature Reserve in Tibet as the study area, we calculated a remote sensing ecological index (RSEI) based on Landsat imagery from 2000 to 2024. We further analyzed the spatiotemporal variations and driving factors of ecological environmental quality using trend analysis methods, including the Theil-Sen median estimator, in combination with XGBoost and SHAP models. From 2000 to 2024, the RSEI of the study area exhibited an overall fluctuating upward trend and peaked in 2024. Spatially, it showed a distribution pattern characterized by stable core areas and degraded marginal areas. Areas with significant RSEI improvement were mainly distributed in the central-eastern part of the reserve and some high-altitude regions in the west area, while markedly degraded areas were concentrated along the western marginal zone. About 42% of the reserve area was predicted to face potential ecological degradation risks in the future. Land use was the dominant factor influencing RSEI variation, and its interaction effects with elevation, mean annual temperature, and snow cover ratio on RSEI were significant. The impacts of all driving factors on RSEI exhibited pronounced nonlinear characteristics. This study would provide a scientific basis for assessing the ecological environmental quality of habitats of rare and endangered species and offer important references for ecological monitoring and sustainable development of protected areas located in high-altitude regions.

Key words: remote sensing ecological index, spatial heterogeneity, machine learning, national nature reserve