论文标题
从生态进化动力学得出的进化图理论
Evolutionary graph theory derived from eco-evolutionary dynamics
论文作者
论文摘要
在网络结构群体中开发了一种基于生物动机的基于个人动机的基于个人进化的框架，可以适应生态进化动态。该框架用于构建网络出生和死亡模型。仅考虑进化动力学的进化图理论模型被推导为一种特殊情况，突出了与实际生物过程不同的其他假设。这是通过引入负面的生态反馈回路来实现的，该反馈循环通过迫使出生和死亡耦合来抑制生态动力学。我们还研究了适应性是一种在进化图理论中使用的生殖成功的度量，它与个人的出生和死亡率有关。在简单的网络中，这些出于生态动机的动力学用于提供对自适应突变的传播的新见解，无论是在有或没有克隆干扰的情况下。例如，众所周知，星际网络是进化图理论中选择的放大器，可以抑制当个体可以自然死亡时自适应突变的传播。
A biologically motivated individual-based framework for evolution in network-structured populations is developed that can accommodate eco-evolutionary dynamics. This framework is used to construct a network birth and death model. The evolutionary graph theory model, which considers evolutionary dynamics only, is derived as a special case, highlighting additional assumptions that diverge from real biological processes. This is achieved by introducing a negative ecological feedback loop that suppresses ecological dynamics by forcing births and deaths to be coupled. We also investigate how fitness, a measure of reproductive success used in evolutionary graph theory, is related to the life-history of individuals in terms of their birth and death rates. In simple networks, these ecologically motivated dynamics are used to provide new insight into the spread of adaptive mutations, both with and without clonal interference. For example, the star network, which is known to be an amplifier of selection in evolutionary graph theory, can inhibit the spread of adaptive mutations when individuals can die naturally.
