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基于距离隔离模型的空间自相关分析检验。

A Test of Spatial Autocorrelation Analysis Using an Isolation-by-Distance Model.

机构信息

Department of Ecology, State University of New York at Stony Brook, Stony Brook, New York 11794.

出版信息

Genetics. 1983 Sep;105(1):219-37. doi: 10.1093/genetics/105.1.219.

Abstract

Using the isolation-by-distance model as an example, we have examined several assumptions of spatial autocorrelation analysis applied to gene frequency surfaces. Gene frequency surfaces generated by a simulation of Wright's isolation-by-distance model were shown to exhibit spatial autocorrelation, except in the panmictic case. Identical stochastic generating processes result in surfaces with characteristics that are functions of the process parameters, such as parental vagility and neighborhood size. Differences in these parameters are detectable as differences in spatial autocorrelations after only a few generations of the simulations. Separate realizations of processes with identical parameters yield similar spatial correlograms. We have examined the inferences about population structure that could have been made from these observations if they had been real, rather than simulated, populations. From such inferences, we could have drawn conclusions about the presence of selection, migration and drift in given natural systems.

摘要

以隔离距离模型为例,我们已经检验了应用于基因频率曲面的空间自相关分析的若干假设。由 Wright 的隔离距离模型的模拟产生的基因频率曲面表现出空间自相关,除了在完全混合的情况下。相同的随机生成过程会导致曲面具有特征,这些特征是过程参数的函数,例如亲本的迁移能力和邻域大小。在模拟仅进行了几代之后,这些参数的差异就可以作为空间自相关的差异来检测到。具有相同参数的过程的不同实现会产生相似的空间相关图。我们已经检查了如果这些观察结果是真实的而不是模拟的种群,那么可以从这些观察结果中得出关于种群结构的推论。通过这些推论,我们可以得出关于给定自然系统中选择、迁移和漂变存在的结论。

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