猎物种群进化稳定的象征性防御水平

IF 1.2 4区 生物学 Q4 ECOLOGY Theoretical Population Biology Pub Date : 2023-10-01 DOI:10.1016/j.tpb.2023.03.001
Alan Scaramangas , Mark Broom , Graeme D. Ruxton , Anna Rouviere
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引用次数: 0

摘要

自19世纪末首次观察到启示主义以来,我们对启示主义(防御捕食者的明显信号)的理解取得了显著进步。事实上,它从分析的角度(通过考虑不同背景死亡率和群体规模的制度)和实践的角度(评估其在预测有限模拟种群中猎物特征进化方面的有效性和局限性)扩展了这一过程的既定博弈论模型的范围。手头手稿的性质更具数学性,其目的有两个:首先,确定在不同背景死亡率和菌落大小的情况下,进化稳定的防御水平和信号强度之间的关系。其次,将这些预测与受随机局部突变影响的有限猎物种群的模拟进行比较。我们比较了绝对驻留适应度、变异适应度和随机性在猎物特征进化中的作用,并讨论了种群规模在上述方面的重要性。
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Evolutionarily stable levels of aposematic defence in prey populations

Our understanding of aposematism (the conspicuous signalling of a defence for the deterrence of predators) has advanced notably since its first observation in the late nineteenth century. Indeed, it extends the scope of a well-established game-theoretical model of this very same process both from the analytical standpoint (by considering regimes of varying background mortality and colony size) and from the practical standpoint (by assessing its efficacy and limitations in predicting the evolution of prey traits in finite simulated populations). The nature of the manuscript at hand is more mathematical and its aim is two-fold: first, to determine the relationship between evolutionarily stable levels of defence and signal strength under various regimes of background mortality and colony size. Second, to compare these predictions with simulations of finite prey populations that are subject to random local mutation. We compare the roles of absolute resident fitness, mutant fitness and stochasticity in the evolution of prey traits and discuss the importance of population size in the above.

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来源期刊
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
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