在序列搜索策略中，交配选择和固定阈值的进化稳定性。
Mate choice and the evolutionary stability of a fixed threshold in a sequential search strategy.
机构信息
Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA 23529, United States.
Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH 43403, United States.
出版信息
Comput Struct Biotechnol J. 2014 Jun 10;10(16):8-11. doi: 10.1016/j.csbj.2014.05.002. eCollection 2014 Jun.
The sequential search strategy is a prominent model of searcher behavior, derived as a rule by which females might sample and choose a mate from a distribution of prospective partners. The strategy involves a threshold criterion against which prospective mates are evaluated. The optimal threshold depends on the attributes of prospective mates, which are likely to vary across generations or within the lifetime of searchers due to stochastic environmental events. The extent of this variability and the cost to acquire information on the distribution of the quality of prospective mates determine whether a learned or environmentally canalized threshold is likely to be favored. In this paper, we determine conditions on cross-generational perturbations of the distribution of male phenotypes that allow for the evolutionary stability of an environmentally canalized threshold. In particular, we derive conditions under which there is a genetically determined threshold that is optimal over an evolutionary time scale in comparison to any other unlearned threshold. These considerations also reveal a simple algorithm by which the threshold could be learned.
序贯搜索策略是一种突出的搜索者行为模型，它是从女性可能从潜在伴侣的分布中抽样和选择伴侣的规则中推导出来的。该策略涉及一个潜在伴侣评估的阈值标准。最优阈值取决于潜在伴侣的属性，由于随机环境事件，这些属性可能在不同世代或搜索者的生命周期内发生变化。这种可变性的程度以及获取潜在伴侣质量分布信息的成本决定了学习的或环境引导的阈值是否可能受到青睐。在本文中，我们确定了跨世代雄性表型分布的扰动条件，这些条件允许环境引导的阈值在进化上的稳定性。具体来说，我们推导出了在遗传上确定的阈值在进化时间尺度上相对于任何其他未学习的阈值都是最优的条件。这些考虑还揭示了一个简单的算法，通过该算法可以学习阈值。
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