Biomass prediction of sea lamprey population based on dynamic feature matrix composite differential equation system

Abstract

This article presents a mathematical model to predict sea lamprey biomass, addressing the species' impact on the Great Lakes fishery. The model, comprising a Dynamic Age Pyramid and a Multi-species Lotka-Volterra system, captures the complex life stages and behaviors of sea lampreys. It simulates their diet, habits, and growth parameters across different ages, considering their adaptive sex ratio variation. Key findings include the model's ability to dynamically update sea lamprey population characteristics annually in response to environmental changes. Simulations show that populations with dynamic sex ratios reach equilibrium faster, with an increasing female proportion over time in resource-rich environments. However, these populations exhibit less resilience to rapid environmental shifts compared to those with stable sex ratios. The study concludes that the model offers a valuable tool for understanding complex organism-environment interactions and enhances traditional ecological models by providing a dynamic, biologically meaningful population feature matrix. This innovation aids in managing invasive species like sea lampreys without harming native ecosystems.