Oladepo Oluwagbemisola, Peace Angela
Department of Mathematics and Statistics, Texas Tech University, 2500 Broadway, Lubbock, 79409, TX, USA.
Bull Math Biol. 2025 Jun 25;87(8):102. doi: 10.1007/s11538-025-01482-6.
This study investigates the nutrient-driven adaptability of foraging efforts in producer-grazer dynamics. We develop two stoichiometric producer-grazer models: a base model incorporating a fixed energetic cost of feeding and an adaptive model where feeding costs vary over time in response to environmental conditions. By comparing these models, we examine the effects of adaptive foraging strategies on population dynamics. Our adaptive model suggests a potential mechanism for evolutionary rescue, where the population dynamically adjusts to environmental changes, such as fluctuations in food quality, by modifying its feeding strategies. However, when population densities oscillate in predator-prey limit cycles, fast adaptation can lead to very wide amplitude cycles, where populations are in danger of stochastic extinction. Overall, this increases our understanding of the conditions under which nutrient-driven adaptive foraging strategies can yield benefits to grazers.
本研究调查了生产者-食草动物动态中觅食努力的营养驱动适应性。我们开发了两个化学计量生产者-食草动物模型：一个基础模型，纳入了固定的觅食能量成本；另一个是适应性模型，其中觅食成本会随时间根据环境条件而变化。通过比较这些模型，我们研究了适应性觅食策略对种群动态的影响。我们的适应性模型提出了一种进化拯救的潜在机制，即种群通过改变其觅食策略来动态适应环境变化，如食物质量的波动。然而，当种群密度在捕食者-猎物极限环中振荡时，快速适应可能导致非常宽的振幅周期，此时种群面临随机灭绝的危险。总体而言，这增加了我们对营养驱动的适应性觅食策略在何种条件下能使食草动物受益的理解。
