生物多样性 ›› 2018, Vol. 26 ›› Issue (9): 951-961.DOI: 10.17520/biods.2018012

• 研究报告 • 上一篇    下一篇

印度野牛在中国的分布及其栖息地适宜性分析

丁晨晨1,2#, 胡一鸣1,2#, 李春旺1,2, 蒋志刚1,2,*()   

  1. 1 (中国科学院动物研究所动物生态与保护生物学重点实验室, 北京 100101)
    2 (中国科学院大学, 北京 100049);
  • 收稿日期:2018-01-11 接受日期:2018-05-26 出版日期:2018-09-20 发布日期:2019-01-05
  • 通讯作者: 蒋志刚
  • 作者简介:# 共同第一作者
  • 基金资助:
    国家重点研发计划项目(2016YFC0503304, 2016YFC0503303)、国家自然科学基金(31372175)和全国第二次陆生野生动物资源调查专项调查资助

Distribution and habitat suitability assessment of the gaur Bos gaurus in China

Chenchen Ding1,2#, Yiming Hu1,2#, Chunwang Li1,2, Zhigang Jiang1,2,*()   

  1. 1 Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences,Beijing 100101
    2 University of Chinese Academy of Sciences, Beijing 100049
  • Received:2018-01-11 Accepted:2018-05-26 Online:2018-09-20 Published:2019-01-05
  • Contact: Jiang Zhigang
  • About author:# Co-first authors

摘要:

印度野牛(Bos gaurus)在中国分布在云南省南部和西藏藏南地区。2016年2-3月和2016年11-12月, 我们在西双版纳州、普洱市及高黎贡山区域开展印度野牛调查, 并对藏南地区进行文献调研, 共获得47处印度野牛有效出现位点数据。目前云南地区印度野牛种群数量约180-210头, 面临着严重的生存危机; 在高黎贡山未发现印度野牛。利用印度野牛分布位点数据, 选取地形、土地覆被类型、人类足迹指数、距水源和道路距离以及气候共5类14种因子作为自变量建立MaxEnt生态位模型, 通过模拟云南和西藏印度野牛的适宜分布区, 分析各环境因子对该物种分布的影响。结果表明: 模型预测精度较高, 平均AUC (area under the curve)值为0.994。印度野牛潜在适宜栖息地可划分为高适宜、次适宜、低适宜和不适宜4个等级。高适宜栖息地主要分布在云南省西双版纳和藏南地区, 其中西双版纳部分镶嵌有次适宜和低适宜栖息地斑块, 面积为4,987 km²; 藏南部分高适宜栖息地面积为13,995 km²。次适宜栖息地主要分布于云南省南部、高黎贡山区域以及藏南高适宜栖息地区的边缘, 总面积为32,778 km²。低适宜和不适宜栖息地区连接成片, 位于云南省中部、北部地区和藏南地区北部。Jackknife检验结果显示, 季节温度变化和等温线对印度野牛潜在分布区的影响较大, 而地形因子和降水变化的影响较弱。遥感地物分类结果表明: 橡胶林等人工经济林的种植占据了西双版纳野牛的适宜栖息地, 降低了景观连接度。建议管理部门加大对天然林的保护力度, 控制橡胶林等人工林在野牛适宜栖息地的扩张, 提高景观连接度, 以促进该物种种群的恢复。

关键词: 云南, 藏南, 印度野牛, 生态位模型, 橡胶林, 栖息地适宜性

Abstract:

Gaur (Bos gaurus) are found in the Yunnan Province and Zangnan in southern Tibet in China. We conducted two field surveys in Xishuangbanna, Pu’er and Mt. Gaoligongshan in Yunnan Province, from February to March and November to December in 2016. We collected 47 valid occurrence locations of gaur by combining survey data and records from literature. Our analysis suggests that there are 180-210 gaurs in the Yunnan Province which face a serious survival crisis. No gaur signs were found in Mt. Gaoligongshan. Next, we used MaxEnt models to predict the potentially suitable habitats for gaur. We grouped 14 habitat predictor variables into five classes—terrain, land cover type, human footprint index, the distance to water and road, as well as climatic factors, and determined the contribution of each habitat factor to habitat suitability for gaur. The accuracy of our prediction models was accessed by the area under the curve (AUC) values for a receiver operating characteristic (ROC) curve. The validation showed that the results had high average AUC value of 0.994. The simulated potential habitat was divided into four classes—the most suitable habitat, moderately suitable habitat, low suitability habitat, and unsuitable habitat. The most suitable habitats for gaur are mainly located in southern Yunnan and Zangnan and spanned 4,987 km² and 13,995 km² respectively. Habitats with moderate suitability (total area = 32,778 km²) were located in the marginal areas of the most suitable habitats and in the Mt. Gongligongshan area. The most suitable habitats were mixed with habitat patches of moderate and low suitability for gaur in the southern parts of Xishuangbanna. In contrast, the central and northern parts of the study area were classified entirely as low suitable habitats and unsuitable habitats. The results of a Jackknife test indicated that temperature seasonality and isothermality had the strongest influence on habitat suitability for gaur, whereas terrain factor and precipitation had little effect. Temperature difference, land cover type and human footprint index were the main variables that explained patterns of gaur distribution. The results of land cover classification (using remote sensing) showed that rubber plantations have fragmented the suitable habitat and reduced landscape connectivity for gaur. We recommend that the relevant management authorities should protect natural forests, control the development of rubber plantations and other agricultural development in habitats suitable for gaur, and improve landscape connectivity to restore gaur populations in the landscape.

Key words: Yunnan, Zangnan, Bos gaurus, ecological niche model, rubber plantations, habitat suitability assessment