生物扩散
变异
分歧(语言学)
人口
生物
有效人口规模
进化生物学
生态学
遗传学
遗传变异
人口学
系统地理学
系统发育学
语言学
哲学
社会学
基因
作者
Raúl Araya‐Donoso,Sarah M. Baty,Pedro Alonso‐Alonso,María José Sanín,Benjamin T. Wilder,Adrián Munguía‐Vega,Greer Dolby
摘要
Abstract Aim Previous population genetic and phylogeographical studies have shown how generation time and dispersal affect population divergence in the presence of a vicariant barrier. More recently, speciation genomic studies have revealed that selection and recombination can be equally impactful. Here, we test how the interaction of these factors shapes the divergence expected in response to an ephemeral barrier and compare these results to empirical literature using the Baja California peninsula as a test case. Location Global. Taxon Diploid eukaryotes. Methods We forward simulated population genomic data with CDMetaPOP and SLiM by varying dispersal rate, mutation rate, generation time, selection pressure and recombination in the presence and then removal of a physical barrier. We tested which factors affect the divergence signal (measured as F ST ). We compared simulation results to empirical literature that included 147 records of generation times and 78 divergence estimates from population genomic studies. Results Population differentiation not only occurred due to the presence of a barrier under lower dispersal abilities but also emerged as a result of low dispersal among structured populations without a barrier. Divergent selection strengthened differentiation, which is supported by empirical data. Barrier removal quickly eroded the divergence signal (~500 generations) for high‐dispersing species, but low dispersal species retained divergence after gene flow resumed. In the empirical data, generation times varied by four orders of magnitude and dispersal by three orders of magnitude. Main Conclusions Divergence can arise without vicariant barriers, it may not produce a tight co‐divergence peak in absolute time, and co‐divergence may not imply a common cause of divergence. Deeper integration of geologic, climatic and genomic data (i.e. geogenomics) may help clarify origins of divergence in physically complex settings.
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