Evolutionary dynamics in complex phenotype spaces

40年前，人们认识到生态动态可以是非常复杂的，甚至是混乱的，这给生态学带来了革命性的变化。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，朝着最佳适应的表型收敛。这种观点对于简单的情况是正确的，当频率无关选择作用于简单的表型时。在大多数生物体中，许多表型特性以复杂的方式联合收割机决定生态相互作用，从而决定频率依赖选择。因此，很自然地认为进化是由于频率依赖性选择同时作用于许多不同的表型。例如，当表型是多维的时，多样性更有可能进化。然而，在一般情况下，很少有人知道的进化动力学理论，由于频率依赖的选择在复杂的表型空间。特别是，目前还不知道多久振荡和混沌的进化动力学预计会发生。我的研究旨在解决这些基本问题。我使用数学模型的进化，由于竞争，捕食和互利共生的多维表型空间中发生的不同类型的进化动力学进行分类，并评估如何经常振荡和混沌动力学发生在这样的模型。此外，我将使用全基因组测序的化石（冷冻）记录的微生物种群在不同复杂性的营养环境中进化，以测试表型复杂性对进化动力学的影响。这将从经验上表明，在更复杂的环境中，多样化是否会变得更有可能，进化动力学是否会表现出更大的波动，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。总之，这项研究有可能改变我们对一般进化过程的看法。如果复杂动力学在高维表型空间中很常见，那么我们将进化视为一个平衡过程的观点必须从根本上加以修正。

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.