标题： 两种状态系统中的信息与适应度：在波动环境中的自我复制个体 显示英文标题

标题： Information and fitness in two-state systems: self-replicating individuals in a fluctuating environment

摘要： 具有相同基因的个体种群可以表现出异质性特征（表型）。 这种异质性的普遍性可以解释为一种赌注规避策略，它在波动的环境中提高了种群的增殖率（适应度）。 表型分布受到竞争、环境状态持续时间以及表型转换速率等因素的影响。 我们在一个系统中展示了这些影响，其中环境和表型都可以采用两种状态。 该系统包括对称赌注规避和休眠-增殖表型等情景。 我们研究了环境状态和表型状态之间共享的互信息（以比特为单位），并探讨了这种信息与种群适应度之间的关系。 我们认为，当适应度相对于表型和环境独立的情况进行测量时，信息和适应度可以被视为等效的度量。 我们研究了个体可以用来提高这种信息的策略，例如调整增殖速率和表型转换速率相对于环境波动速率的比率。 通过这些策略，在固定边缘分布的情况下，信息的增加意味着种群适应度的增加。 我们还确定了最大可实现适应度和信息的极限，并讨论了这种信息在新的归一化适应度中的价值。 我们的框架为生物体如何适应波动的环境条件提供了新的见解。 显示英文摘要

摘要： A population of individuals with the same genes can present heterogeneous traits (phenotypes). The prevalence of this heterogeneity can be explained as a bet-hedging strategy that improves the population proliferation rate (fitness) in fluctuating environments. The phenotype distribution is influenced by factors such as competition between phenotypes, the duration of environmental states, and the rate of phenotype-switching. We illustrate these effects in a system where both the environment and the phenotype can adopt two states. This system includes scenarios such as symmetric bet-hedging and dormant-proliferating phenotypes. We examine how environmental and phenotypic states share mutual information, measured in bits, and explore the relationship between this information and population fitness. We propose that when fitness is measured relative to the case where phenotype and environment are independent, information and fitness can be treated as equivalent measures. We investigate strategies that individuals can use to improve this information, such as adjusting the rates of proliferation and phenotype-switching relative to the environmental fluctuation rate. Through these strategies, with fixed marginal distributions, an increase in information implies an increase in population fitness. We also identify limits to the maximum achievable fitness and information and discuss the value of the information in terms of this new normalized fitness. Our framework offers new insights into how organisms adapt to fluctuating environmental conditions.