Data from: On the evolutionary interplay between dispersal and local adaptation in heterogeneous environments
收藏DataONE2015-04-15 更新2024-06-27 收录
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Dispersal, whether in the form of a dandelion seed drifting on the breeze, or a salmon migrating upstream to breed in a non-natal stream, transports genes between locations. At these locations, local adaptation modifies the gene frequencies so their carriers are better suited to particular conditions, be those of newly disturbed soil or a quiet river pool. Both dispersal and local adaptation are major drivers of population structure; however, in general, their respective roles are not independent and the two may often be at odds with one another evolutionarily, each one exhibiting negative feedback on the evolution of the other. Here we investigate their joint evolution within a simple discrete-time, metapopulation model. Depending on environmental conditions, their evolutionary interplay leads to either a monomorphic population of highly dispersing generalists or a rarely dispersing, locally adapted, polymorphic population, each adapted to a particular habitat type. A critical value of environmental heterogeneity divides these two selection regimes and the nature of the transition between them is determined by the level of kin competition. When kin competition is low, at the transition we observe discontinuities, bistability and hysteresis in the evolved strategies; however, when high, kin competition moderates the evolutionary feedback and the transition is smooth.
扩散(dispersal)——无论是随风飘散的蒲公英种子,还是溯流而上至非出生溪流繁殖的鲑鱼——均会在不同地理区域间传递基因。在这些区域中,局域适应(local adaptation)会改变基因频率,使携带相关基因的个体更适配特定环境条件,无论是新近扰动的土壤,还是静谧的河流水塘。
扩散与局域适应均为种群结构形成的核心驱动因素;但总体而言,二者的作用并非独立,在进化层面往往相互掣肘,彼此均会对对方的进化产生负反馈。
本研究依托一个简单的离散时间集合种群(metapopulation)模型,探究二者的协同进化过程。根据环境条件的差异,二者的进化交互作用会催生两类演化结果:一类是高度扩散的单态(monomorphic)泛化种群,另一类则是极少扩散、经局域适应的多态(polymorphic)种群,每一类均适配特定的生境类型。
环境异质性的临界值将这两种选择模式区分开来,二者间的转变本质由亲缘竞争(kin competition)的程度决定。当亲缘竞争程度较低时,转变阶段的演化策略会出现不连续性、双稳性与滞后现象;而当亲缘竞争程度较高时,亲缘竞争会缓和进化反馈,使得转变过程趋于平滑。
创建时间:
2015-04-15



