Predicting evolutionary rescue via evolving plasticity in stochastic environments
Predicting evolutionary rescue via evolving plasticity in stochastic environments
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DOI：
10.1098/rspb.2016.1690
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发表时间：
2016-09-28
影响因子：
4.7
通讯作者：
Baskett, Marissa L.
中科院分区：
文献类型：
--
作者：
Ashander, Jaime;Chevin, Luis-Miguel;Baskett, Marissa L.
表型可塑性及其进化可能有助于在新的和紧张的环境中进行进化拯救，特别是如果环境新奇性揭示了使可塑性增加的进化成为可能的神秘遗传变异。然而，在自然系统中普遍存在的环境随机性可能会改变这些预测，因为高可塑性可能会放大表型-环境失配。虽然以前的研究已经强调了随机环境中可塑性的这种潜在有害影响，但他们没有研究它如何影响进化拯救背景下的灭绝风险和不断发展的可塑性。我们调查这个问题，在这里通过整合随机人口与数量遗传理论的平均值和环境的可预测性（时间自相关）的同时变化的模型。我们开发了一个近似的预测下的环境波动的新模式的长期持久性，并将其与数值模拟的短期和长期的灭绝风险。我们发现，减少可预测性增加灭绝的风险，降低持久性，因为它增加了随机负载在救援过程中。当进化作用于新环境中揭示的神秘遗传变异时，这种对随机人口统计学、表型可塑性和进化如何相互作用的理解可以为入侵、防御或害虫耐药性的出现提供信息。
Phenotypic plasticity and its evolution may help evolutionary rescue in a novel and stressful environment, especially if environmental novelty reveals cryptic genetic variation that enables the evolution of increased plasticity. However, the environmental stochasticity ubiquitous in natural systems may alter these predictions, because high plasticity may amplify phenotype-environment mismatches. Although previous studies have highlighted this potential detrimental effect of plasticity in stochastic environments, they have not investigated how it affects extinction risk in the context of evolutionary rescue and with evolving plasticity. We investigate this question here by integrating stochastic demography with quantitative genetic theory in a model with simultaneous change in the mean and predictability (temporal autocorrelation) of the environment. We develop an approximate prediction of long-term persistence under the new pattern of environmental fluctuations, and compare it with numerical simulations for short-and long-term extinction risk. We find that reduced predictability increases extinction risk and reduces persistence because it increases stochastic load during rescue. This understanding of how stochastic demography, phenotypic plasticity, and evolution interact when evolution acts on cryptic genetic variation revealed in a novel environment can inform expectations for invasions, extinctions, or the emergence of chemical resistance in pests.