Modeling and Stability Analysis of Agricultural Ecosystems: A Comparative Study of Traditional and Organic Farming Practices

With the increasing concerns over ecological degradation caused by traditional agricultural practices, this study explores the dynamic relationship between human agricultural activities and the environment. We propose a comprehensive modeling framework to evaluate the evolution and stability of agricultural ecosystems under varying conditions. Using the Lotka-Volterra model, we simulate species interactions and ecosystem transitions from dense forests to agricultural systems. A stability evaluation model, enhanced by the Analytic Hierarchy Process (AHP), quantifies ecosystem robustness through a stability index (St). Our results reveal that the use of pesticides and herbicides slightly reduces ecosystem stability, while the reintroduction of native species such as eagles and rabbits improves stability. Furthermore, reducing herbicide use and introducing biological control agents-specifically bats and woodpeckers-significantly enhances ecosystem resilience. We also explore the feasibility of adopting organic farming through a multi-objective programming model that balances economic returns and ecological sustainability. The analysis demonstrates that organic farming outperforms traditional methods in crop health, biodiversity, and pest control. Finally, a sensitivity analysis is conducted to assess model robustness. This study provides a data-driven, multi-dimensional approach to support the sustainable transition from conventional to organic agriculture.

Authors

Publication Details

Journal
Scientific journal of intelligent systems research.
Published
2025-06-30
DOI
https://doi.org/10.54691/15sb7656
Primary Topic
Sustainable Agricultural Systems Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling and Stability Analysis of Agricultural Ecosystems: A Comparative Study of Traditional and Organic Farming Practices

Hong-Hao Niu, Jinming Zhang
Scientific journal of intelligent systems research.
Sustainable Agricultural Systems Analysis
article

Modeling and Stability Analysis of Agricultural Ecosystems: A Comparative Study of Traditional and Organic Farming Practices

Hong-Hao Niu, Jinming Zhang
article en

Abstract

With the increasing concerns over ecological degradation caused by traditional agricultural practices, this study explores the dynamic relationship between human agricultural activities and the environment. We propose a comprehensive modeling framework to evaluate the evolution and stability of agricultural ecosystems under varying conditions. Using the Lotka-Volterra model, we simulate species interactions and ecosystem transitions from dense forests to agricultural systems. A stability evaluation model, enhanced by the Analytic Hierarchy Process (AHP), quantifies ecosystem robustness through a stability index (St). Our results reveal that the use of pesticides and herbicides slightly reduces ecosystem stability, while the reintroduction of native species such as eagles and rabbits improves stability. Furthermore, reducing herbicide use and introducing biological control agents-specifically bats and woodpeckers-significantly enhances ecosystem resilience. We also explore the feasibility of adopting organic farming through a multi-objective programming model that balances economic returns and ecological sustainability. The analysis demonstrates that organic farming outperforms traditional methods in crop health, biodiversity, and pest control. Finally, a sensitivity analysis is conducted to assess model robustness. This study provides a data-driven, multi-dimensional approach to support the sustainable transition from conventional to organic agriculture.

Scientific journal of intelligent systems research.Vol. 7(6)
Openalex Percentile: Top 86%
Sustainable Agricultural Systems Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.