扩大人口中的赌注对冲策略
Bet-hedging strategies in expanding populations
摘要：
在生态学中，物种可以通过使个体表型多样化来减轻其在不确定环境中的灭绝风险。这一观察是量化的赌注对冲理论，它提供了一个理由，即使在克隆种群中观察到的表型多样性的程度。混合种群中的对冲理论已经发展得相当成熟。然而，许多物种在其进化历史中经历了范围扩张，表型多样性在这种情况下的重要性仍然需要理解。在本文中，我们开发了一个理论的赌注对冲人口殖民新的，未知的环境中波动的空间或时间。在这种情况下，我们发现，赌注对冲是一个更有利的战略比在混合人口。对于缓慢的变化率，时间和空间波动导致不同的结果。在空间波动的环境中，下注对冲比时间波动的环境更受欢迎。在频繁的环境变化的限制下，无论环境波动的性质如何，都不存在下注对冲的机会。对于同一模型，在混合良好的情况下，押注对冲从来都不是一个有利的策略，这支持了范围扩张强烈促进多元化的观点。这些结论是强大的有限的人口规模引起的随机性。我们的研究结果揭示了表型异质性在范围扩张中的重要性，为了解生物多样性如何出现和维持的新方法铺平了道路。
英文摘要：
In ecology, species can mitigate their extinction risks in uncertain environments by diversifying individual phenotypes. This observation is quantified by the theory of bet-hedging, which provides a reason for the degree of phenotypic diversity observed even in clonal populations. The theory of bet-hedging in well-mixed populations is rather well developed. However, many species underwent range expansions during their evolutionary history, and the importance of phenotypic diversity in such scenarios still needs to be understood. In this paper, we develop a theory of bet-hedging for populations colonizing new, unknown environments that fluctuate either in space or time. In this case, we find that bet-hedging is a more favorable strategy than in well-mixed populations. For slow rates of variation, temporal and spatial fluctuations lead to different outcomes. In spatially fluctuating environments, bet-hedging is favored compared to temporally fluctuating environments. In the limit of frequent environmental variation, no opportunity for bet-hedging exists, regardless of the nature of the environmental fluctuations. For the same model, bet-hedging is never an advantageous strategy in the well-mixed case, supporting the view that range expansions strongly promote diversification. These conclusions are robust against stochasticity induced by finite population sizes. Our findings shed light on the importance of phenotypic heterogeneity in range expansions, paving the way to novel approaches to understand how biodiversity emerges and is maintained.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
