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Transitions in optimal adaptive strategies for populations in fluctuating environments

机译:波动环境中群体的最佳自适应策略转换

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摘要

Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.
机译:生物学群受到环境条件波动的影响。不同的自适应策略可以允许它们应对这些波动:专业化一个特定的环境条件,采用条件之间妥协的一般表型,或人口明显多样化(赌注套期化)。其中哪种策略在长期上提供了最大的选择性优势取决于可访问表型的范围和环境波动的统计数据。在这里,我们在群体增长的简单数学模型中分析了这个问题。首先,我们审查并扩展了一种图形方法,以确定当环境波动不相关时的最佳策略的性质。环境波动中的时间相关性开辟了依赖记忆的新策略,但在数学上挑战研究:我们提出了分析结果来解决这一挑战。我们通过分析在受试者的存在下分析最佳自适应策略来说明我们的一般方法,这些策略限制了可访问的表型范围的范围。我们的结果延长了几项研究,并具有各种生物现象的应用,从细菌中的抗生素抗性免受脊椎动物的免疫应答。

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