The energy allocation toward life-history functions: Link between the individual and population levels
Year: 2025
Type: article
Abstract: The population dynamics of organisms are strongly influenced by life-history strategies that result from the optimal allocation of energy to vital functions such as growth, reproduction, and survival. These strategies, characterized by phenotypic traits, emerge as evolutionary adaptations to specific ecological conditions and define functional trade-offs relevant facing biotic and abiotic pressures. The aim of this study is to examine the link between life history and population dynamics from a bioenergetic perspective, articulating individual and population-level processes through mathematical models that capture adaptive decisions in simulated environments described in terms of constant, decreasing, and periodic resource availability over time. Using a discrete-time mathematical model with two state variables, internal energy and survival probability, energy allocation toward reproduction and foraging is incorporated in order to determine the optimal strategy that maximizes the net reproductive rate. To solve this control problem, Pontryagin’s maximum principle is applied, using the forward–backward method to obtain optimal trajectories of allocation, energy, and survival. These trajectories are analyzed with respect to relevant physiological parameters under different scenarios of resource availability, thereby allowing the exploration of how environmental conditions influence the bioenergetic decisions of organisms.
Source: Selecciones Matemáticas
Authors: Facultad de Ingeniería, Departamento de Matemática, Universidad Autónoma de Chile, Talca, Chile., Víctor Saldaña-Núñez, Alex Altamirano-Fernández, Facultad de Ciencias Básicas, Departamento de Matemática, Física y Estadística, Universidad Católica del Maule, Talca, Chile., Ranghely Hernández-Castañeda, Doctorado en Modelamiento Matemático Aplicado, Universida Católica del Maule, Talca, Chile., Rodrigo Gutiérrez, Facultad de Ciencias Básicas, Departamento de Matemática, Física y Estadística, Universidad Católica del Maule, Talca, Chile.
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4412771780