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Estimating large carnivore populations at global scale based on spatial predictions of density and distribution - Application to the jaguar (Panthera onca)

机译:基于密度分布的空间预测估算全球规模的大型加管人群 - 应用于Jaguar(Panthera Onca)

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Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species' entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world's jaguar population at 173,000 (95% CI: 138,000-208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km(2)) and low human densities (< 1 person/km(2)) coinciding with high primary productivity in the core area of jaguar range. Our results show the importance of protected areas for jaguar persistence. We conclude that combining modelling of density and distribution can reveal ecological patterns and processes at global scales, can provide robust estimates for use in species assessments, and can guide broad-scale conservation actions.
机译:保护努力需要广泛的种群估算下降的物种的估计。但是,对于许多秘密物种,包括大型食肉动物,这种估计往往是困难的。基于通过相机捕获,存在/不存在数据和来自卫星图像的全球可用的预测变量获得的发布密度估计,我们建模密度和发生大食道,捷豹,横跨物种的整个范围。然后,我们将这些模型组合在分层框架中以估计总人口。我们的模型表明,潜在的Jaguar密度最适合通过初级生产率的测量来预测,最高型热带栖息地的密度最高,以及距离赤道距离的清晰下降梯度。相比之下,捷豹分布是由人体影响和环境因素的综合影响决定:捷豹发生的概率随着森林覆盖,平均温度和年降水量而增加,随着人的脚印指数和人密度的增加而下降。受保护区域的发生概率也明显高于它们之外的受保护区域。我们估计世界捷豹人口为173,000人(95%:138,000-208,000)个体,主要集中在亚马逊盆地;在其他地方,人口往往是小而碎片化。仍然占用的大型总面积的大量捷豹(近900万公里(2))和低人类密度(<1人/ km(2)),在捷豹范围的核心区域中的高初级生产率。我们的结果表明了捷豹持久性保护区的重要性。我们得出结论,密度和分配的结合建模可以揭示全局尺度的生态模式和过程,可以为物种评估提供强大的估计,并可以指导广泛的保护作用。

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