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Generalists versus specialists in fluctuating environments: a bet‐hedging perspective
Oikos ( IF 3.1 ) Pub Date : 2020-04-09 , DOI: 10.1111/oik.07109
Thomas Ray Haaland 1, 2 , Jonathan Wright 1 , Irja Ida Ratikainen 1
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Bet‐hedging evolves in fluctuating environments because long‐term genotype success is determined by geometric (rather than arithmetic) mean fitness across generations. Diversifying bet‐hedging produces different specialist offspring, whereas conservative bet‐hedging produces similar generalist offspring. However, many fields, such as behavioral ecology and thermal physiology, typically consider specialist versus generalist strategies only in terms of maximizing arithmetic mean fitness benefits to individuals. Here we model how environmental variability affects optimal amounts of phenotypic variation within and among individuals to maximise genotype fitness, and we disentangle the effects of individual‐level optimization and genotype‐level bet‐hedging by comparing long‐term arithmetic versus geometric mean fitness. For traits with additive fitness effects within lifetimes (e.g. foraging‐related traits), genotypes of similar generalists or diversified specialists perform equally well. However, if fitness effects are multiplicative within lifetimes (e.g. sequential survival probabilities), generalist individuals are always favored. In this case, geometric mean fitness optimization requires even more within‐individual phenotypic variation than does arithmetic mean fitness, causing individuals to be more generalist than required to simply maximize their own expected fitness. In contrast to previous results in the bet‐hedging literature, this generalist conservative bet‐hedging effect is always favored over diversifying bet‐hedging. These results link the evolution of behavioral and ecological specialization with earlier models of bet‐hedging, and we apply our framework to a range of natural phenomena from habitat choice to host specificity in parasites.

中文翻译:

波动环境中的通才与专家:对冲观点

赌注套期保值在波动的环境中发展,因为长期的基因型成功取决于几代人的几何(而不是算术)平均适应度。多样化的对冲产生不同的专业后代,而保守的对冲产生类似的通才子代。但是,许多领域(例如行为生态学和热生理学)通常仅在最大化算术平均适应性对个人的好处方面考虑专家策略与通才策略。在这里,我们模拟环境变异性如何影响个体内部和个体之间的最佳表型变异量,以最大程度地提高基因型适应性,并通过比较长期算术与几何平均适应性来解散个体水平优化和基因型水平对冲的影响。对于一生中具有加性适应性效应的性状(例如与觅食相关的性状),相似的通才或多样化专家的基因型表现同样良好。但是,如果适应性效应在一生中成倍增加(例如,顺序生存概率),那么通才个体将始终受到青睐。在这种情况下,与算术平均适应度相比,几何平均适应度优化需要更大的个体内表型变异,这导致个人比单纯地最大化自己的预期适应度所需的通用性更高。与博彩对冲文献中的先前结果相反,这种通才保守的博彩对冲效应始终优于多样化的博彩对冲。这些结果将行为和生态专业化的发展与早期的对冲模型联系在一起,
更新日期:2020-04-09
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