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基于智能体与集体模型的赌注对冲灭绝研究

Extinction in agent-based and collective models of bet-hedging

Manuel Dávila-Romero, Francisco J. Cao-García, Luis Dinis

AI总结:

本文通过基于智能体和集体模型研究赌注对冲策略如何降低灭绝概率,发现种群数量增加四倍比从最大生长策略转为最小灭绝策略对降低灭绝风险更有效,揭示了有限种群效应对该策略成功的重要性。

摘要:

赌注对冲是一种表型多样化策略,它将快速生长但脆弱的表型与生长缓慢但具有抗性的表型相结合。在有利与不利条件之间切换的环境中,赌注对冲能够在长期内优化生长并减少波动,因此有望降低灭绝风险。本文直接探讨了在基于智能体的模型中赌注对冲如何降低灭绝概率。由于接近灭绝时个体数量很少,基于智能体的模型适合用于研究灭绝现象。我们还表明,对于数量达到100个或更多个体的种群,基于智能体的模型会收敛到集体模型的行为。然而,即使对于低数量种群,集体模型也能提供相关的定性见解。集体模型给出了灭绝概率的表达式,强调了种群数量的重要性,表明总种群数量增加四倍比将策略从最大生长改为最小灭绝具有更大的效果。这项工作进一步揭示了有限种群效应对赌注对冲策略成功的影响。

英文摘要:

Bet-hedging is a phenotype diversification strategy that combines a fast-growing vulnerable phenotype with a slow-growing resistant phenotype. In environments switching between favorable and unfavorable conditions, bet-hedging optimizes growth and reduces fluctuations over a long time, which is expected to reduce extinction risk. Here, we address directly how bet-hedging can reduce extinction probability in an agent-based model. An agent-based model is appropriate for studying extinction due to the low number of individuals close to extinction. We also show that the agent-based model converges to the collective model behavior for populations of $100$ individuals or more. However, the collective model provides relevant qualitative insight even for low populations. The collective model provides expressions for extinction that stress the relevance of the population number, showing that a factor four increase in the total population has a greater effect than a change of strategy from maximum growth to minimal extinction. This work provides further insight into the impact of finite population effects on the bet-hedging strategy's success.

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。

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