生物
自然选择
局部适应
适应(眼睛)
选择(遗传算法)
进化生物学
背景(考古学)
特质
生态学
人口
微进化
人口学
古生物学
人工智能
神经科学
程序设计语言
社会学
计算机科学
作者
Robert I. Colautti,Jennifer A. Lau
摘要
Abstract Biological invasions are ‘natural’ experiments that can improve our understanding of contemporary evolution. We evaluate evidence for population differentiation, natural selection and adaptive evolution of invading plants and animals at two nested spatial scales: (i) among introduced populations (ii) between native and introduced genotypes. Evolution during invasion is frequently inferred, but rarely confirmed as adaptive. In common garden studies, quantitative trait differentiation is only marginally lower (~3.5%) among introduced relative to native populations, despite genetic bottlenecks and shorter timescales (i.e. millennia vs. decades). However, differentiation between genotypes from the native vs. introduced range is less clear and confounded by nonrandom geographic sampling; simulations suggest this causes a high false‐positive discovery rate (>50%) in geographically structured populations. Selection differentials (¦s¦) are stronger in introduced than in native species, although selection gradients (¦ β ¦) are not, consistent with introduced species experiencing weaker genetic constraints. This could facilitate rapid adaptation, but evidence is limited. For example, rapid phenotypic evolution often manifests as geographical clines, but simulations demonstrate that nonadaptive trait clines can evolve frequently during colonization (~two‐thirds of simulations). Additionally, Q ST ‐ F ST studies may often misrepresent the strength and form of natural selection acting during invasion. Instead, classic approaches in evolutionary ecology (e.g. selection analysis, reciprocal transplant, artificial selection) are necessary to determine the frequency of adaptive evolution during invasion and its influence on establishment, spread and impact of invasive species. These studies are rare but crucial for managing biological invasions in the context of global change.
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