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确定巴基斯坦雪豹保护的重点景观。

Identifying priority landscapes for conservation of snow leopards in Pakistan.

机构信息

Department of Zoology, Quaid-i-Azam University, Islamabad, Pakistan.

Snow Leopard Trust, Pakistan Program, Islamabad, Pakistan.

出版信息

PLoS One. 2020 Nov 5;15(11):e0228832. doi: 10.1371/journal.pone.0228832. eCollection 2020.

Abstract

Pakistan's total estimated snow leopard habitat is about 80,000 km2 of which about half is considered prime habitat. However, this preliminary demarcation was not always in close agreement with the actual distribution-the discrepancy may be huge at the local and regional level. Recent technological developments like camera trapping and molecular genetics allow for collecting reliable presence records that could be used to construct realistic species distribution based on empirical data and advanced mathematical approaches like MaxEnt. The current study followed this approach to construct an accurate distribution of the species in Pakistan. Moreover, movement corridors, among different landscapes, were also identified through circuit theory. The probability of habitat suitability, generated from 98 presence points and 11 environmental variables, scored the snow leopard's assumed range in Pakistan, from 0 to 0.97. A large portion of the known range represented low-quality habitat, including areas in lower Chitral, Swat, Astore, and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber, Broghil, and Central Karakoram represented high-quality habitats. Variables with higher contributions in the MaxEnt model were precipitation during the driest month (34%), annual mean temperature (19.5%), mean diurnal range of temperature (9.8%), annual precipitation (9.4%), and river density (9.2). The model was validated through receiver operating characteristic (ROC) plots and defined thresholds. The average test AUC in Maxent for the replicate runs was 0.933 while the value of AUC by ROC curve calculated at 0.15 threshold was 1.00. These validation tests suggested a good model fit and strong predictive power. The connectivity analysis revealed that the population in the Hindukush landscape appears to be more connected with the population in Afghanistan as compared to other populations in Pakistan. Similarly, the Pamir-Karakoram population is better connected with China and Tajikistan, while the Himalayan population was connected with the population in India. Based on our findings we propose three model landscapes to be considered under the Global Snow Leopard Ecosystem Protection Program (GSLEP) agenda as regional priority areas, to safeguard the future of the snow leopard in Pakistan and the region. These landscapes fall within mountain ranges of the Himalaya, Hindu Kush and Karakoram-Pamir, respectively. We also identified gaps in the existing protected areas network and suggest new protected areas in Chitral and Gilgit-Baltistan to protect critical habitats of snow leopard in Pakistan.

摘要

巴基斯坦估计的雪豹总栖息地约为 8 万平方公里,其中约一半被认为是主要栖息地。然而,这种初步划定并不总是与实际分布完全一致——在局部和区域水平上可能存在巨大差异。最近的技术发展,如相机陷阱和分子遗传学,允许收集可靠的存在记录,这些记录可用于根据经验数据和高级数学方法(如最大熵)构建现实的物种分布。本研究采用这种方法来构建巴基斯坦境内该物种的精确分布。此外,还通过电路理论确定了不同景观之间的迁徙走廊。从 98 个存在点和 11 个环境变量中生成的栖息地适宜性概率,对巴基斯坦雪豹的假定范围进行了评分,范围从 0 到 0.97。已知范围的很大一部分代表低质量栖息地,包括较低的奇特拉尔、斯瓦特、阿斯特和克什米尔地区。相反,罕萨、米斯加尔、恰普桑、库伦伯尔、布罗吉尔和喀喇昆仑中部则代表高质量栖息地。最大熵模型中贡献较高的变量是最干旱月的降水量(34%)、年平均温度(19.5%)、日温度范围的平均值(9.8%)、年降水量(9.4%)和河流密度(9.2%)。该模型通过接收者操作特征(ROC)图和定义的阈值进行了验证。在最大熵的重复运行中,平均测试 AUC 为 0.933,而在 0.15 阈值下计算的 ROC 曲线的 AUC 值为 1.00。这些验证测试表明模型拟合良好,预测能力较强。连通性分析表明,与巴基斯坦其他地区的种群相比,兴都库什景观中的种群与阿富汗的种群联系更为紧密。同样,帕米尔-喀喇昆仑种群与中国和塔吉克斯坦的联系更为紧密,而喜马拉雅种群与印度的种群联系更为紧密。根据我们的研究结果,我们提出了三个模型景观,作为全球雪豹生态系统保护计划(GSLEP)议程下的区域优先领域,以保护巴基斯坦和该地区雪豹的未来。这些景观分别位于喜马拉雅山脉、兴都库什山脉和喀喇昆仑山脉-帕米尔山脉。我们还发现了现有保护区网络中的空白,并建议在奇特拉尔和吉尔吉特-巴尔蒂斯坦设立新的保护区,以保护巴基斯坦雪豹的关键栖息地。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea5d/7644022/b00635525150/pone.0228832.g001.jpg

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