Evolutionary dynamics in complex phenotype spaces

40年前，人们认识到生态动态可能非常复杂，甚至是混乱的，这一认识彻底改变了生态学。相反，在进化生物学中，流行的观点仍然是进化是一个平衡过程，趋同于最佳适应表型。当频率无关的选择作用于简单表型时，这种观点对于简单的情况是正确的。在大多数生物体中，许多表型特性以复杂的方式结合在一起，决定了生态相互作用，因此产生了频率依赖性选择。因此，考虑到进化是由于频率依赖的选择同时作用于许多不同的表型是很自然的。例如，当表型是多维的时候，多样性更有可能进化。然而，一般来说，由于复杂表型空间中频率依赖的选择，我们对进化动力学理论知之甚少。特别是，不知道振荡和混沌演化动力学发生的频率有多高。我的研究旨在解决这些基本问题。我使用竞争、捕食和共生进化的数学模型来对多维表型空间中发生的不同类型的进化动力学进行分类，并评估振荡和混沌动力学在这些模型中发生的频率。此外，我将使用化石（冷冻）记录的微生物种群在不同复杂性的营养环境中进化的全基因组测序，以测试表型复杂性对进化动力学的影响。这将从经验上显示，在更复杂的环境中，多样化是否变得更有可能，进化动力学是否表现出更大的波动，变得更不可预测。最后，我将使用数学模型来研究表型复杂性对另一个基本进化问题的影响：合作的进化。总的来说，这项研究有可能改变我们对一般进化过程的看法。如果复杂的动力学在高维表型空间中是常见的，那么我们将进化视为一个平衡过程的观点必须从根本上修正。

40 years ago, the realization that ecological dynamics can be very complicated, and indeed chaotic, has revolutionized ecology. In contrast, in evolutionary biology the prevalent perspective still is of evolution as an equilibrium process, converging towards optimally adapted phenotypes. This perspective is correct for simple scenarios, when frequency-independent selection acts on simple phenotypes. In most organisms, many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency-dependent selection. Therefore, it is natural to consider evolution due to frequency-dependent selection acting simultaneously on many different phenotypes. For example, diversity is more likely to evolve when phenotypes are multi-dimensional. In general, however, very little is known about the theory of evolutionary dynamics due to frequency-dependent selection in complex phenotype spaces. In particular, it is not known how often oscillatory and chaotic evolutionary dynamics are expected to occur. My research aims to address these fundamental questions. I use mathematical models for evolution due to competition, predation and mutualism to classify the different types of evolutionary dynamics occurring in multi-dimensional phenotype spaces, and to assess how often oscillatory and chaotic dynamics occur in such models. Also, I will use whole-genome sequencing of the fossil (frozen) record of microbial populations evolving in nutritional environments of varying complexity to test the effect of phenotypic complexity on evolutionary dynamics. This will show empirically whether in more complex environments, diversification becomes more likely, and evolutionary dynamics exhibit larger fluctuations and become less predictable. Finally, I will use mathematical models to investigate the effect of phenotypic complexity on another fundamental evolutionary problem: the evolution of cooperation. Taken together, the proposed research has the potential to alter our view of general evolutionary processes. If complex dynamics is common in high-dimensional phenotype spaces, then our view of evolution as an equilibrium process must be fundamentally revised.