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基于MaxEnt模型的珠穆朗玛峰国家级自然保护区雪豹生境适宜性评价

机译:基于MaxEnt模型的珠穆朗玛峰国家级自然保护区雪豹生境适宜性评价

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摘要

Habitat evaluation constitutes an important and fundamental step in the management of wildlife populations and conservation policy planning. Geographic information system (GIS) and species presence data provide the means by which such evaluation can be done. Maximum Entropy (MaxEnt) is widely used in habitat suitability modeling due to its power of accuracy and additional descriptive properties. To survey snow leopard populations in Qomolangma (Mt. Everest, QNNR) National Nature Reserve, Tibet, China, we pooled 127 pugmarks, 415 scrape marks, and 127 non-invasive identifications of the animal along line transects and recorded 87 occurrences through camera traps from 2014–2017. We adopted the MaxEnt model to generate a map highlighting the extent of suitable snow leopard habitat in QNNR. Results showed that the accuracy of the MaxEnt model was excellent (mean AUC=0.921). Precipitation in the driest quarter, ruggedness, elevation, maximum temperature of the warmest month, and annual mean temperature were the main environmental factors influencing habitat suitability for snow leopards, with contribution rates of 20.0%, 14.4%, 13.3%, 8.7%, and 8.2% respectively. The suitable habitat area extended for 7001.93 km2, representing 22.72% of the whole reserve. The regions bordering Nepal were the main suitable snow leopard habitats and consisted of three separate habitat patches. Our findings revealed that precipitation, temperature conditions, ruggedness, and elevations of around 4000 m influenced snow leopard preferences at the landscape level in QNNR. We advocate further research and cooperation with Nepal to evaluate habitat connectivity and to explore possible proxies of population isolation among these patches. Furthermore, evaluation of subdivisions within the protection zones of QNNR is necessary to improve conservation strategies and enhance protection.
机译:栖息地评估构成了野生动物人口和保护政策规划的重要而基本的一步。地理信息系统(GIS)和物种存在数据提供了可以完成此类评估的方法。由于其精度和附加描述性能,最大熵(MaxEnt)广泛用于栖息地适用性建模。在QoMolangma(Mt. everest,QNNR)国家自然保护区调查雪豹群体,中国西藏,我们汇集了127名普彭,415块刮痕和127个动物的非侵入式识别,通过相机陷阱录制了87次出现87次出现从2014-2017起。我们采用了最大模型来生成地图突出QNNR中合适的雪豹栖息地的范围。结果表明,最大模型的准确性优异(平均AUC = 0.921)。在最干燥的季度降水,坚固性,高度,最热月的最高温度和年平均温度是影响雪豹栖息地适合性的主要环境因素,贡献率为20.0%,14.4%,13.3%,8.7%,和分别为8.2%。合适的栖息地面积延长了7001.93平方公里,占整个储备的22.72%。邻近尼泊尔的地区是主要合适的雪豹栖息地,包括三个单独的栖息地补丁。我们的研究结果表明,沉淀,温度条件,坚固性和高度约为4000米,影响QNNR的景观水平的雪豹偏好。我们倡导与尼泊尔的进一步研究与合作,评估栖息地连接,并探讨这些补丁中的人口隔离代表。此外,需要评估QNNR保护区内的细分,以改善保护策略和增强保护。

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