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Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics

机译:量化Bufo Boreas连接在黄石国家公园与景观遗传学

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A major objective of ecology is to understand how ecological processes limit population connectivity and species' distributions. By spatially quantifying ecological components driving functional connectivity, we can understand why some locally suitable habitats are unoccupied, resulting, in observed discontinuities in distribution. However, estimating connectivity may be difficult due to population stochasticity and violations of assumptions of parametric statistics. To address these issues, we present a novel application of Random Forests to landscape genetic data. We address the effects of three key ecological components oil Bufo boreas connectivity in Yellowstone National Park: ecological process, scale. and hierarchical organization. Habitat permeability, topographic morphology, and temperature-moisture regime are all significant ecological processes associated with B. boreas Connectivity. Connectivity was influenced by growing-season precipitation, 1988 Yellowstone fires, cover, temperature, impervious surfaces (roads and development), and topographic complexity (56% variation explained). We found that habitat permeability generally operates oil fine scales, while topographic morphology and temperature-moisture regime operate across Multiple scales, thus demonstrating the importance of cross-scale analysis for ecological interpretation. In a hierarchical analysis, we were able to explain more variation within genetic clusters as identified using Structure (a Bayesian algorithm) (74%; dispersal cover, growing-season precipitation, impervious surfaces) as opposed to between genetic clusters (45%; ridgelines, hot, dry slopes, length of hot season. and annual precipitation). Finally. the analytical methods we developed ire powerful and an be applied to any species or system with appropriate landscape genetic data.
机译:生态的主要目标是了解生态过程如何限制人口连接和物种的分布。通过空间量化的生态部件推动功能连接,我们可以理解为什么某些当地合适的栖息地都没有占用,导致了观察到的分布中的不连续性。然而,由于种群随机性和违反参数统计的假设,估计连接可能是困难的。为了解决这些问题,我们提出了一种新建的随机林应用于景观遗传数据。我们解决了黄石国家公园三个关键生态成分石油Bufo Boreas连通性的影响:生态过程,规模。和分层组织。栖息地渗透性,地形形态和温度 - 水分制度都是与B.BORAS连通性相关的重要生态过程。连通性受到生长季节降水的影响,1988年黄石火,覆盖,温度,不透水表面(道路和发展)以及地形复杂性(56%解释)。我们发现栖息地渗透性通常操作油精细鳞片,而地形形态和温度 - 湿度制度在多种尺度上运行,从而展示了跨规范分析对生态解释的重要性。在一个层次分析中,我们能够在使用结构(贝叶斯算法)(74%;分散盖,生长季沉淀,不透水的表面)而不是遗传群(45%; ridgelines之间的遗传群中的遗传簇内的更多变化,热,干燥的斜坡,炎热的季节。和年降水)。最后。我们开发IRE强大的分析方法,并且应用于具有适当景观遗传数据的任何物种或系统。

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