多状态切换环境中波动种群的动力学
Dynamics of fluctuating populations in multi-state switching environments
AI总结：
本文研究多状态切换环境中两菌株的种群竞争，通过计算与分析手段表征种群动力学，明确环境波动的频率与幅度对种群动态的影响。
AI中文摘要：
微生物种群通常在随时间变化的波动环境中进化，这类环境常被描述为二元切换模型，有时可视为粗粒化的丰食-饥荒周期，其中资源可获得性在丰富与匮乏状态间突然切换。然而实验研究表明，丰食-饥荒环境实际呈现更复杂的时间动态。本文研究两个菌株在含有限数量中间状态的波动环境中竞争相同资源的情况，其中每个中间状态有其自身的环境容纳量；环境在这些状态间的切换及对应的环境容纳量代表营养可获得性的逐渐变化。这类多状态随机切换模型可被解释为丰食-饥荒周期的粗粒化描述，使我们能研究资源逐渐恢复与耗竭下的菌株竞争。通过计算与分析手段，我们表征了这类多状态波动环境中的种群动力学，尤其研究了切换率与环境容纳量分布如何影响种群规模统计、固定概率及平均固定时间。将这些结果与二元环境中的对应结果对比，我们阐明了环境波动的频率与幅度如何影响粗粒化丰食-饥荒周期中的种群动力学。
英文摘要：
Microbial populations generally evolve in fluctuating environments under time-varying conditions. These are often described by binary switching models, sometimes seen as coarse-grained feast-famine cycles, in which resource availability switches abruptly between abundant and scarce conditions. However, experimental studies suggest that feast-famine environments actually exhibit more complex temporal dynamics. Here, we study how two strains, one growing slightly slower than the other, compete for the same resources in fluctuating environments comprising a finite number of intermediate states, each having its own carrying capacity. Environmental switching between these states and their carrying capacities represents gradual changes in nutrient availability. This class of multi-state stochastic switching models can be interpreted as a coarse-grained description of feast--famine cycles and allows us to investigate strain competition under the gradual recovery and depletion of resources. By computational and analytical means, we characterise the population dynamics in these multi-state fluctuating environments. In particular, we study how the switching rates and distribution of carrying capacities affect the population-size statistics, fixation probability, and mean fixation time. By comparing these results with their counterparts in binary environments, we clarify how the frequency and amplitude of environmental fluctuations influence population dynamics in coarse-grained feast-famine cycles.
