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

Fuente: arXiv
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Autores principales: Dávila-Romero, Manuel, Cao-García, Francisco J., Dinis, Luis
Formato: Preprint
Publicado: 2024
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author Dávila-Romero, Manuel
Cao-García, Francisco J.
Dinis, Luis
author_facet Dávila-Romero, Manuel
Cao-García, Francisco J.
Dinis, Luis
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2406_11482
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Extinction in agent-based and collective models of bet-hedging
Dávila-Romero, Manuel
Cao-García, Francisco J.
Dinis, Luis
Populations and Evolution
Statistical Mechanics
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.
title Extinction in agent-based and collective models of bet-hedging
topic Populations and Evolution
Statistical Mechanics
url https://arxiv.org/abs/2406.11482