Mathematical modeling reveals growth dynamics in agricultural ecosystems, suggesting strategies for sustainability.
With the global population growth and the rising demand for agricultural products, the impact of agricultural expansion on the ecosystem has attracted much attention, and how to balance the ecological benefits and economic benefits has become a concern. Therefore, we establish a mathematical model to study the dynamic evolution process of the agricultural ecosystem, aiming to analyze the influence of natural factors and human decision-making and provide a theoretical basis for farmers to adopt agricultural production strategies that combine both ecological and economic benefits. Based on the Logistic Growth model modified Lotka-Volterra model (LMLV), this study constructed a food web model of the agricultural ecosystem, simulating the influence of inter-species competition, agricultural cycle, persistence cycle, and chemical factors on the dynamic change of the ecosystem. In addition, we established the agroecological ecosystem stability index ( ) to quantify ecosystem stability. Then we conducted numerical simulation of the model through the Runge-Kutta methods in MATLAB, and the results show that the improved LMLV model we constructed can effectively describe the dynamic evolution process of the agricultural ecosystem, which provides a scientific basis for optimizing the agricultural production strategies. This model not only contributes to understanding the complex interactions of ecosystems but also provides theoretical support for achieving sustainable agriculture.
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Deng et al. (2025) studied this question.
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