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利用系统发育网络对保护种群进行优先级排序。

Prioritizing populations for conservation using phylogenetic networks.

作者信息

Volkmann Logan, Martyn Iain, Moulton Vincent, Spillner Andreas, Mooers Arne O

机构信息

Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, Canada.

Interdisciplinary Research in the Mathematical and Computational Sciences (IRMACS) Centre, Simon Fraser University, Burnaby, British Columbia, Canada.

出版信息

PLoS One. 2014 Feb 28;9(2):e88945. doi: 10.1371/journal.pone.0088945. eCollection 2014.

Abstract

In the face of inevitable future losses to biodiversity, ranking species by conservation priority seems more than prudent. Setting conservation priorities within species (i.e., at the population level) may be critical as species ranges become fragmented and connectivity declines. However, existing approaches to prioritization (e.g., scoring organisms by their expected genetic contribution) are based on phylogenetic trees, which may be poor representations of differentiation below the species level. In this paper we extend evolutionary isolation indices used in conservation planning from phylogenetic trees to phylogenetic networks. Such networks better represent population differentiation, and our extension allows populations to be ranked in order of their expected contribution to the set. We illustrate the approach using data from two imperiled species: the spotted owl Strix occidentalis in North America and the mountain pygmy-possum Burramys parvus in Australia. Using previously published mitochondrial and microsatellite data, we construct phylogenetic networks and score each population by its relative genetic distinctiveness. In both cases, our phylogenetic networks capture the geographic structure of each species: geographically peripheral populations harbor less-redundant genetic information, increasing their conservation rankings. We note that our approach can be used with all conservation-relevant distances (e.g., those based on whole-genome, ecological, or adaptive variation) and suggest it be added to the assortment of tools available to wildlife managers for allocating effort among threatened populations.

摘要

面对未来生物多样性不可避免的损失,按保护优先级对物种进行排名似乎不仅仅是审慎之举。随着物种分布范围变得碎片化且连通性下降,在物种内部(即种群层面)设定保护优先级可能至关重要。然而,现有的优先级设定方法(例如,根据生物体预期的遗传贡献对其进行评分)是基于系统发育树的,而系统发育树可能无法很好地代表物种以下水平的分化情况。在本文中,我们将保护规划中使用的进化隔离指数从系统发育树扩展到了系统发育网络。此类网络能更好地代表种群分化情况,我们的扩展方法还能让种群按照它们对集合的预期贡献程度进行排序。我们使用来自两个濒危物种的数据对该方法进行了说明:北美洲的斑点猫头鹰(Strix occidentalis)和澳大利亚的山地侏儒负鼠(Burramys parvus)。利用先前发表的线粒体和微卫星数据,我们构建了系统发育网络,并根据每个种群的相对遗传独特性对其进行评分。在这两个案例中,我们的系统发育网络都捕捉到了每个物种的地理结构:地理边缘种群所拥有的冗余遗传信息较少,这提高了它们的保护排名。我们注意到,我们的方法可用于所有与保护相关的距离(例如,基于全基因组、生态或适应性变异的距离),并建议将其添加到野生动物管理者可用于在受威胁种群之间分配工作的工具组合中。

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