Dynamic-Multiple Model for Agricultural Ecosystem Evolution and Effects of Biological Interventions

Abstract

As forest resources are continuously converted into agricultural land, the ecosystem balance faces significant challenges, disrupting local biodiversity. To understand the evolutionary process of agricultural ecosystems, a Dynamic-Multiple (DM) agricultural ecosystem model is proposed. The Lotka-Volterra model is referenced, integrating natural processes and human decision-making, to develop the DM model and examine the population biomass variations of four species in the eastern Hubei Yangtze Plain. Biomass variation trends of different species under the influence of five factors are identified. The DM agricultural ecosystem is modified by introducing two new species, snakes and mice. Re-analysis of biomass variations shows that the introduction of snakes and mice significantly impacts bat biomass, with no notable effect on other species. The model is further modified by incorporating Plant Growth-Promoting Bacteria (PGPB) and pollination effects. PGPB is found to primarily influence crop biomass, while the pollination effect mainly affects crop growth rate. When herbicides are removed during sowing in the third year, a significant decline in crop biomass is observed, and the number of consumers tends to stabilize. The model is validated through the above three cases.