波动环境中表型多样性与种群增长的MBPRE方法
Phenotypic diversity and population growth in fluctuating environment: a MBPRE approach
摘要：
生物体通过调节其动力学来适应波动的环境，并通过调整其表型以适应环境变化。我们在随机环境中使用多类型分支过程来模拟种群增长，其中具有性状$t\in\cT$的某些生物在环境$e\in\cE$中的后代分布由$\bbN$上的某些（固定）分布$Υ_{t,e}$给出。然后，使用性状空间$\cT$上的分布（策略）$π_{t,e}$对表型进行归属。我们寻找最优策略$π_{t,e}$，$t\in\cT$，$e\in\cE$使净增长率或Lyapounov指数最大化，并刻画了最优策略的集合.这被认为是生物学中的各种模型的兴趣：遗传与非遗传的策略和涉及或不涉及传感机制的策略。我们的主要结果是在非遗传策略的设置：由于减少到简单的分支过程在随机环境中，我们得到一个精确的表达式的净增长率和最优策略的特征。我们也关注典型的系谱，也就是说，我们考虑的问题，找到一个随机选择的有机体的典型谱系。
英文摘要：
Organisms adapt to fluctuating environments by regulating their dynamics, and by adjusting their phenotypes to environmental changes. We model population growth using multitype branching processes in random environments, where the offspring distribution of some organism having trait $t\in\cT$ in environment $e\in\cE$ is given by some (fixed) distribution $Υ_{t,e}$ on $\bbN$. Then, the phenotypes are attributed using a distribution (strategy) $π_{t,e}$ on the trait space $\cT$. We look for the optimal strategy $π_{t,e}$, $t\in\cT$, $e\in\cE$ maximizing the net growth rate or Lyapounov exponent, and characterize the set of optimal strategies. This is considered for various models of interest in biology: hereditary versus non-hereditary strategies and strategies involving or not involving a sensing mechanism. Our main results are obtained in the setting of non-hereditary strategies: thanks to a reduction to simple branching processes in random environment, we derive an exact expression for the net growth rate and a characterisation of optimal strategies. We also focus on typical genealogies, that is, we consider the problem of finding the typical lineage of a randomly chosen organism.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
