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Updated: Oct 7, 2025
11:53
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
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Understanding the Effects of China's Agro-Environmental Policies on Rural Households' Labor and Land Allocation with
Ying Wang1, Qi Zhang2, Srikanta Sannigrahi3
1School of Public Administration, China University of Geosciences, Wuhan, Hubei 430074, China.
Journal of Artificial Societies and Social Simulation : JASSS
|January 7, 2022
Summary
Agro-environmental policies in rural China impact household land and labor decisions differently. Forest restoration increases migration and land shrinkage, while conservation boosts non-farm jobs, and subsidies aid good land but not marginal land abandonment.
Area of Science:
- Environmental Social Science
- Agricultural Economics
- Spatially Explicit Modeling
Background:
- Household decision-making regarding land and labor is complex under agro-environmental policies.
- Human-environment interactions significantly influence these decisions in rural settings.
Purpose of the Study:
- To simulate household land and labor allocation decisions using a spatially explicit agent-based model.
- To investigate the impacts of forest restoration, forest conservation, and agricultural subsidy programs in rural China.
Main Methods:
- Development of a spatially explicit agent-based model (ABM).
- Integration of spatial and socioeconomic data for household simulations.
- Analysis of policy impacts on labor out-migration, cropland changes, and livelihood diversification.
Main Results:
- Forest restoration accelerates labor out-migration and cropland shrinkage.
- Forest conservation promotes livelihood diversification through non-farm employment.
- Agricultural subsidies retain labor on good quality land but are less effective for marginal land abandonment.
Conclusions:
- Agro-environmental policies exhibit nonlinear social-ecological impacts over time, influenced by household decision-making rules (bounded rationality vs. empirical knowledge).
- Agent-based modeling effectively captures adaptive decision-making and interactions in dynamic environments.
- Policy outcomes can deviate from expectations due to complex human-land interplays.
Keywords:
Agro-environmental policiesLabor allocationLand useSocial-ecological systemsSpatially explicit agent-based modelMore Related Videos
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