DMS-EPSRC Eco-Evolutionary Dynamics of Fluctuating Populations

了解物种多样性的起源和合作的演变是一个重大的科学谜题，与许多社会关切产生共鸣，如抗菌素耐药性的上升或生物多样性的丧失，甚至与流行病学有关。人口动力学传统上忽略波动，考虑静态和同质环境。然而，随机发生的出生/死亡事件(人口噪声)和环境条件的变化(环境变异性)引起的波动，以及物种的空间分散，对于理解种群的规模和组成如何随着时间共同演变，即其生态进化动态，发挥着至关重要的作用。在这里，我们关注的是无处不在的情况，其中波动的种群的生态进化动态是由人口噪声和环境变异性的耦合塑造的。人们对环境变异性和人口噪声之间的相互依赖知之甚少，但在微生物群落中却非常重要，因为微生物群落往往会受到突然和极端的环境变化的影响。特别是，对受外部因素影响的不同大小和组成的种群进行建模，对于了解微生物抗生素耐药性的演变至关重要。事实上，药效学主要集中在对大量混合良好的细菌种群的确定性描述上，但没有考虑到在小型社区产生的关键随机效应。当抗生素将一个庞大的种群减少到一个非常小的种群，但无法根除它时，存活的细胞可能会复制并恢复感染，这些幸存者很可能会产生抗生素耐药性。由于人口规模较小，结果的细节会有很大的波动。这个重要的例子清楚地表明，需要理论上的进步来阐明波动环境中的灭绝和抵抗情景。这一雄心勃勃的提议是从以前的一系列较小的合作项目中扩展出来的，例如，参见参考文献[1，2，12]、访问和研讨会(由利兹数学学院和EPSRC Network Plus共同资助)。这是开展前沿研究计划的及时机会，该计划包含冒险元素，其中心目标是开发一套理论工具，使我们能够描述与生物相关的进化模型，并在实验室控制的实验中做出可测试的预测。对于这一联合努力，关键是建立在团队独特的互补专业知识基础上，我们将采用结合各种数学工具的多学科方法，并将考虑日益复杂的模型。我们的理论模型的许多特征，如切换环境、时变的人口规模、公共产品生产等，都可以在实验室实验中重现。这打开了一系列令人兴奋的可能性的大门，以解决与直接生物学相关的理论问题，并对我们的理论模型的各种预测进行实验测试。我们将与我们的实验生物学家项目合作伙伴一起探索这些机会(参见何塞·希门尼斯博士的支持信)。

Understanding the origin of species diversity and the evolution of cooperation is a major scientific riddle that resonates with numerous societal concerns, like the rise of antimicrobial resistance or the loss of biodiversity, and is even relevant to epidemiology. Population dynamics traditionally ignores fluctuations and considers static and homogeneous environments. However, fluctuations arising from randomly occurring birth / death events (demographic noise) and the change of environmental conditions (environmental variability), together with the spatial dispersal of species, play a crucial role in understanding how the size and composition of a population jointly evolve in time, i.e. its eco-evolutionary dynamics. Here, we focus on the ubiquitous situation where the eco-evolutionary dynamics of fluctuating populations is shaped by the coupling of demographic noise and environmental variability. The interdependence of environmental variability and demographic noise is poorly understood but of great importance in microbial communities, which are often subject to sudden and extreme environmental changes. In particular, modelling population of varying size and composition subject to changing external factors is crucial to understand the evolution of microbial antibiotic resistance. In fact, pharmacodynamics largely focuses on the deterministic description of large well-mixed bacterial populations, but fails to account crucial stochastic effects arising in small communities. When antibiotics reduce a large population to a very small one but fail to eradicate it, surviving cells may replicate and restore infections, and these survivors are likely to develop antibiotic resistance. Owing to the small population size, the details of the outcome are subject to large fluctuations.This important example clearly illustrates the need for theoretical advances to shed light on extinction and resistance scenarios in fluctuating environments.This ambitious proposal has branched out from a series of previous smaller collaborative projects, see e.g. References [1,2,12], visits and a workshop (co-funded by the Leeds School of Mathematics and the EPSRC Network Plus). It is a timely opportunity to carry out a cutting-edge research programme, containing elements of adventure and whose central goal is to develop a suite of theoretical tools that will allow us to describe biologically relevant evolutionary models, and to make testable predictions in laboratory-controlled experiments. For this joint effort, crucially building on the team's unique complementary expertise, we will adopt a multidisciplinary approach combining various mathematical tools and will consider models of an increasing level of complexity. Many of the features of our theoretical models, such as switching environments, time-varying population sizes, public good production, etc. can be reproduced in laboratory experiments. This opens the door to a host of exciting possibilities to address theoretical questions of direct biological relevance, and to experimentally test various predictions of our theoretical models. We will explore these opportunities with our experimental biologist project partner (see Dr Jose Jimenez's letter of support).