An Economic-Ecological Modeling Framework for Agroecosystems: Integrating Dynamic Food Webs and Multi-Criteria Assessment

This paper proposes an intelligent algorithmic system for analyzing farmland ecosystems, focusing on computerized modeling and evaluation mechanisms that integrate multi-species interactions, agricultural intervention strategies, and system stability. First, an ecological computation pipeline centered on continuous-time dynamics is constructed. Producers, consumers, decomposers, and environmental factors are uniformly abstracted as computable state variables. Pulsed functions and decay mechanisms enable algorithmic representation of agricultural cycles and external inputs. Second, within this framework, multi-predator coordination and species recovery modules are introduced to conduct scenario simulations and comparative analyses of different regulatory strategies. Combined with a multi-indicator weighted algorithm, this enables automatic assessment of ecological status. Finally, ecological constraints are embedded into the profit optimization process, forming a decision support algorithm that balances system stability and output efficiency. This intelligent algorithmic system features a modular structure, excellent scalability, and scenario generalization capabilities. It can characterize complex ecological evolution processes with low computational complexity, providing an algorithmic paradigm with practical application value for intelligent agricultural management and ecological decision-making.