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GENE DISPERSAL AND SPATIAL GENETIC STRUCTURE
Author(s) -
Epperson Bryan K.,
Li TianQuan
Publication year - 1997
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/j.1558-5646.1997.tb03651.x
Subject(s) - biological dispersal , spatial analysis , biology , statistics , autocorrelation , population , sampling (signal processing) , genetic structure , evolutionary biology , genetic variation , ecology , mathematics , genetics , computer science , gene , demography , filter (signal processing) , sociology , computer vision
Spatial autocorrelation statistics have been studied in theoretical population genetic models and widely used in experimental studies of spatial structure in many plant and animal populations. However, the statistical properties of spatial autocorrelation statistics have remained uncharacterized. Little is known about how values of spatial autocorrelation statistics in population samples depend on the level of dispersal and scheme of sampling. In this paper, we characterize the statistical properties of join‐count spatial autocorrelation statistics for population genetic surveys under various conditions of dispersal and sampling. The results indicate generally high statistical power. These results can provide a method to estimate gene dispersal based on standing spatial patterns of genetic variation observed within populations.