作者: ALLAN E. STRAND , JAMES M. NIEHAUS
DOI: 10.1111/J.1471-8286.2007.01832.X
关键词: Metapopulation 、 Type I and type II errors 、 Context (language use) 、 Population 、 Ecology 、 Biology 、 Biological dispersal 、 Estimator 、 Software 、 Mathematical optimization 、 Variety (cybernetics)
摘要: Individual-based, spatially explicit models provide a mechanism to understand distributions of individuals on the landscape; however, few have been coupled with population genetics. The primary benefits such combination is assess performance population-genetic estimators in realistic situations. kernelpop represents flexible framework implement almost any arbitrary and demographic model context using variety dispersal kernels. Estimates type I error associated genome scans metapopulations are provided as an illustration this software's utility.