Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging

Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging
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短视的进化限制了长期赌注对冲的功效

DOI:
10.1086/701786
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发表时间:
2019
期刊:
The American Naturalist
影响因子:
--
通讯作者:
Ratcliff, William C.
Ratcliff, William C.
中科院分区:
--
文献类型:
--
作者:
Libby, Eric;Ratcliff, William C.

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为了在不可预测的环境变化中生存下来,许多生物采用了一种下注对冲策略,这种策略最初代价高昂,但却能提供长期的适应性利益。这些延迟适应度收益的时间范围决定了下注对冲生物是否能够存活足够长的时间来实现它们。在本文中,我们研究了一个微生物下注对冲模型,其中有两条灭绝路径:不可预测的环境变化和人口统计学随机性。在时间相关的环境中,这些灭绝驱动因素选择不同的开关策略。快速的表型转换确保了在面对不可预测的环境变化时的生存,而转换较慢的生物则会灭绝。然而,当两种转换策略都出现在同一种群中时,人口统计学的随机性——由有限的种群规模强制执行——会导致转换速度更快的生物体灭绝。因此,我们发现了一种进化自杀的新形式,即在波动的环境中选择有利于下注对冲策略,最终增加灭绝的风险。具有多个亚群和分散的种群结构可以减少因不可预测的环境变化而灭绝的风险,并改变平衡,从而促进转换较慢的生物的进化。
To survive unpredictable environmental change, many organisms adopt bet-hedging strategies that are initially costly but provide a long-term fitness benefit. The temporal extent of these deferred fitness benefits determines whether bet-hedging organisms can survive long enough to realize them. In this article, we examine a model of microbial bet hedging in which there are two paths to extinction: unpredictable environmental change and demographic stochasticity. In temporally correlated environments, these drivers of extinction select for different switching strategies. Rapid phenotype switching ensures survival in the face of unpredictable environmental change, while slower-switching organisms become extinct. However, when both switching strategies are present in the same population, then demographic stochasticity—enforced by a limited population size—leads to extinction of the faster-switching organism. As a result, we find a novel form of evolutionary suicide whereby selection in a fluctuating environment can favor bet-hedging strategies that ultimately increase the risk of extinction. Population structures with multiple subpopulations and dispersal can reduce the risk of extinction from unpredictable environmental change and shift the balance so as to facilitate the evolution of slower-switching organisms.
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