Department of Biology, Bucknell University, 337 Biology Building, Lewisburg, PA 17837, USA.
Integr Comp Biol. 2024 Nov 21;64(5):1484-1493. doi: 10.1093/icb/icae041.
Phenotypic integration is often perceived as being able to produce convergent evolution in the absence of selection, but specific mechanisms for this process are lacking and a connection has never been empirically demonstrated. A new model of the effect of integration on convergence provides such a mechanism, along with other predictions about the influence of integration on evolutionary patterns. I use simulations and data from three empirical systems-turtle shells, characiform fish, and squirrel mandibles-to investigate the degree to which evolutionary integration is associated with high levels of convergent evolution. Levels of integration were varied in Brownian motion simulations and the resulting amounts of stochastic convergent evolution were quantified. Each empirical system was divided into modules, and the strength of integration, average amount of convergence, phenotypic disparity, and rate of evolution in each module were measured. Results from the simulations and from all three empirical systems converge on a common result: higher levels of phenotypic integration are indeed associated with higher levels of convergence. This is despite a lack of consistent association between the strength of phenotypic integration and evolutionary rate or disparity. The results here are only correlational. Further studies that more closely examine the influence of within-population drivers of evolutionary integration-for example, genetic or developmental integration-on convergence are required before it is possible to definitively establish when phenotypic integration can cause evolutionary convergence. Until then, however, the results of this study strongly suggest that phenotypic integration will often promote convergent evolution.
表型整合通常被认为能够在没有选择的情况下产生趋同进化，但该过程的具体机制尚不清楚，也从未有过实证证明。一个新的整合对趋同影响的模型提供了这样一种机制，以及关于整合对进化模式影响的其他预测。我使用了来自三个经验系统（龟壳、鲇形目鱼和松鼠下颚）的模拟和数据，来研究进化整合与高水平趋同进化之间的关联程度。在布朗运动模拟中改变了整合水平，并量化了随机趋同进化的数量。将每个经验系统划分为模块，并测量每个模块中的整合强度、平均趋同程度、表型差异和进化速度。模拟和三个经验系统的结果都得出了一个共同的结果：更高水平的表型整合确实与更高水平的趋同进化相关。尽管表型整合的强度与进化速度或差异之间没有一致的关联。这里的结果只是相关的。在能够明确确定表型整合何时会导致进化趋同之前，还需要进一步研究影响进化整合的种群内驱动因素（例如遗传或发育整合）对趋同的影响。然而，目前的研究结果强烈表明，表型整合通常会促进趋同进化。
