School of Life Sciences, University of Warwick, Coventry, United Kingdom.
PLoS One. 2012;7(8):e43254. doi: 10.1371/journal.pone.0043254. Epub 2012 Aug 27.
Computational models of evolutionary processes are increasingly required to incorporate multiple and diverse sources of data. A popular feature to include in population genetics models is spatial extension, which reflects more accurately natural populations than does a mean field approach. However, such models necessarily violate the mean field assumptions of classical population genetics, as do natural populations in the real world. Recently, it has been questioned whether classical approaches are truly applicable to the real world. Individual based models (IBM) are a powerful and versatile approach to achieve integration in models. In this study an IBM was used to examine how populations of plants deviate from classical expectations under spatial extension. Populations of plants that used three different mating strategies were placed in a range of arena sizes giving crowded to sparse occupation densities. Using a measure of population density, the pollen communication distance (P(cd)), the deviation exhibited by outbreeding populations differed from classical mean field expectations by less than 5% when P(cd) was less than 1, and over this threshold value the deviation significantly increased. Populations with an intermediate mating strategy did not have such a threshold and deviated directly with increasing isolation between individuals. Populations with a selfing strategy were influenced more by the mating strategy than by increased isolation. In all cases pollen dispersal was more influential than seed dispersal. The IBM model showed that mean field calculations can be reasonably applied to natural outbreeding plant populations that occur at a density in which individuals are less than the average pollen dispersal distance from their neighbors.
进化过程的计算模型越来越需要纳入多种和多样化的数据来源。在种群遗传学模型中加入空间扩展是一种很受欢迎的特征,它比平均场方法更能准确地反映自然种群。然而,这种模型必然违反了经典种群遗传学的平均场假设,就像现实世界中的自然种群一样。最近,人们质疑经典方法是否真的适用于现实世界。基于个体的模型(IBM)是实现模型整合的强大而通用的方法。在这项研究中,使用 IBM 来研究在空间扩展下植物种群如何偏离经典预期。使用三种不同交配策略的植物种群被放置在一系列的竞技场大小中,从拥挤到稀疏的占有密度。使用种群密度的度量——花粉传播距离(P(cd)),当 P(cd)小于 1 时,异交种群的偏离值比经典平均场预期值小 5%,超过这个阈值,偏离值显著增加。具有中间交配策略的种群没有这样的阈值,并且随着个体之间的隔离增加而直接偏离。具有自交策略的种群受到交配策略的影响大于隔离的影响。在所有情况下,花粉传播比种子传播更有影响力。IBM 模型表明,平均场计算可以合理地应用于自然异交植物种群,这些种群的密度在个体小于其邻居平均花粉扩散距离的范围内。