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Challenges and opportunities in population monitoring of cheetahs

机译:猎豹人口监测的挑战与机遇

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Population monitoring is key to wildlife conservation and management but is challenging at the spatial and temporal extents necessary for understanding changes. Noninvasive survey methods and spatial capture-recapture (SCR) models have revolutionized wildlife monitoring by providing the means to acquire data at large scales and the framework to generate spatially explicit predictions, respectively. Despite opportunities for improved monitoring, challenges can remain in the study design and model fitting phases of an SCR approach. Here, we used a search-encounter design with multi-session SCR models to collect spatially indexed photographs and estimate changes in density of cheetahs between 2005 and 2013-2016 in the Masai Mara National Reserve (MMNR) in Kenya. Our SCR models of cheetah encounters suggested little change in cheetah density from 2005 to 2013-2016, with some evidence that density fluctuated annually in the MMNR. The sampling period length (5 vs. 10 months) and timing (early, late, full year) over which spatial encounters were modeled did not alter inferences about density when sample sizes were adequate (>20 spatially distinct encounters). Our average density estimate of similar to 1.2 cheetahs/100 km(2)is consistent with the impression that the MMNR provides important cheetah habitat in Africa. During most years, spatial distribution of vegetation greenness (proxy for ungulate habitat quality) accounted for important variation in encounter rates. The search-encounter design here could be applied to other regions for cheetah monitoring. While snapshot estimates of population size across time are useful for wildlife monitoring, open population models may better identify the mechanisms behind temporal changes.
机译:人口监测是野生动物保护和管理的关键,但在理解变革所需的空间和时间范围内挑战。非侵入性调查方法和空间捕获 - 重新捕获(SCR)模型通过提供在大规模和框架下获取数据的手段,分别为生成空间显式预测的方法而彻底改变了野生动物监测。尽管有机会改进的监测,但挑战可以留在SCR方法的研究设计和模型拟合阶段。在这里,我们使用了一个搜索遇到的设计与多次会话SCR模型,以收集肯尼亚马赛马拉国家储备(MMNR)2005年至2013 - 2016年期间的空间索引照片和近2013-2016之间的密度变化。我们的Cheetah遇到的SCR模型表明2005年至2013 - 2016年猎豹密度的变化很小,有一些证据表明,在MMNR中每年每年都会波动。采样周期长度(5 vs.10个月)和时序(早期,晚期,全年),在空间遭遇的情况下,当样本尺寸足够(> 20个空间不同的遭遇时)没有改变关于密度的推断。我们的平均密度估计与1.2猎豹/ 100公里(2)相一致,MMNR在非洲提供重要的猎豹栖息地。在大多数年内,植被绿色的空间分布(代理栖息地质量)占遇到的重要变化。这里的搜索遇到设计可以应用于猎豹监控的其他地区。虽然跨时间的人口大小的快照估计对于野生动物监测有用,但开放人口模型可能更好地识别时间变化背后的机制。

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