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Circuit theory predicts gene flow in plant and animal populations.电路理论预测植物和动物种群中的基因流动。
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Spectrum of genetic diversity and networks of clonal organisms.克隆生物的遗传多样性谱与网络
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Isolation by Distance.距离隔离
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网络分析可识别集合种群系统中的弱连接和强连接。

Network analysis identifies weak and strong links in a metapopulation system.

作者信息

Rozenfeld Alejandro F, Arnaud-Haond Sophie, Hernández-García Emilio, Eguíluz Víctor M, Serrão Ester A, Duarte Carlos M

机构信息

Instituto Mediterraneo de Estudios Avanzados (Consejo Superior de Investigaciones Científicas-Universidad de las Islas Baleares), C/Miquel Marqués 21, 07190 Esporles, Mallorca, Spain.

出版信息

Proc Natl Acad Sci U S A. 2008 Dec 2;105(48):18824-9. doi: 10.1073/pnas.0805571105. Epub 2008 Nov 20.

DOI:10.1073/pnas.0805571105
PMID:19022909
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2585483/
Abstract

The identification of key populations shaping the structure and connectivity of metapopulation systems is a major challenge in population ecology. The use of molecular markers in the theoretical framework of population genetics has allowed great advances in this field, but the prime question of quantifying the role of each population in the system remains unresolved. Furthermore, the use and interpretation of classical methods are still bounded by the need for a priori information and underlying assumptions that are seldom respected in natural systems. Network theory was applied to map the genetic structure in a metapopulation system by using microsatellite data from populations of a threatened seagrass, Posidonia oceanica, across its whole geographical range. The network approach, free from a priori assumptions and from the usual underlying hypotheses required for the interpretation of classical analyses, allows both the straightforward characterization of hierarchical population structure and the detection of populations acting as hubs critical for relaying gene flow or sustaining the metapopulation system. This development opens perspectives in ecology and evolution in general, particularly in areas such as conservation biology and epidemiology, where targeting specific populations is crucial.

摘要

识别塑造集合种群系统结构和连通性的关键种群是种群生态学中的一项重大挑战。在种群遗传学理论框架中使用分子标记已使该领域取得了巨大进展,但量化每个种群在系统中的作用这一主要问题仍未得到解决。此外,经典方法的使用和解释仍然受到先验信息和潜在假设的限制,而这些在自然系统中很少能得到满足。通过使用来自受威胁海草波喜荡草(Posidonia oceanica)在其整个地理范围内的种群的微卫星数据,网络理论被应用于绘制集合种群系统中的遗传结构。网络方法不受先验假设以及经典分析解释所需的常见潜在假设的限制,既允许直接表征分层种群结构,又能检测出对基因流动传递或维持集合种群系统至关重要的枢纽种群。这一进展总体上为生态学和进化领域开辟了前景,特别是在保护生物学和流行病学等领域,其中针对特定种群至关重要。