Agroecosystem Modeling and Sustainable Optimization: An Empirical Study Based on XGBoost and EEBS Model

Meiqing Xu, Zilong Yao, Yuxin Lu and Chunru Xiong ()
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Meiqing Xu: School of Computer Science and Engineering, Guangdong Ocean University, Zhanjiang 529500, China
Zilong Yao: School of Computer Science and Engineering, Guangdong Ocean University, Zhanjiang 529500, China
Yuxin Lu: School of Computer Science and Engineering, Guangdong Ocean University, Zhanjiang 529500, China
Chunru Xiong: School of Computer Science and Engineering, Guangdong Ocean University, Zhanjiang 529500, China

Sustainability, 2025, vol. 17, issue 15, 1-20

Abstract: As agricultural land continues to expand, the conversion of forests to farmland has intensified, significantly altering the structure and function of agroecosystems. However, the dynamic ecological responses and their interactions with economic outcomes remain insufficiently modeled. This study proposes an integrated framework that combines a dynamic food web model with the Eco-Economic Benefit and Sustainability (EEBS) model, utilizing empirical data from Brazil and Ghana. A system of ordinary differential equations solved using the fourth-order Runge–Kutta method was employed to simulate species interactions and energy flows under various land management strategies. Reintroducing key species (e.g., the seven-spot ladybird and ragweed) improved ecosystem stability to over 90%, with soil fertility recovery reaching 95%. In herbicide-free scenarios, introducing natural predators such as bats and birds mitigated disturbances and promoted ecological balance. Using XGBoost (Extreme Gradient Boosting) to analyze 200-day community dynamics, pest control, resource allocation, and chemical disturbance were identified as dominant drivers. EEBS-based multi-scenario optimization revealed that organic farming achieves the highest alignment between ecological restoration and economic benefits. The model demonstrated strong predictive power ( R 2 = 0.9619, RMSE = 0.0330), offering a quantitative basis for green agricultural transitions and sustainable agroecosystem management.

Keywords: agroecosystem modeling; XGBoost algorithm; EEBS framework; forest-to-farmland conversion; green agricultural management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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