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Development of an agent-based model for estimation of agricultural land preservation in rural Japan

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  • Yamashita, Ryohei
  • Hoshino, Satoshi

Abstract

In rural Japan, the lack of successors for aging farmers has become a serious problem, given that these areas experience a population outflow as well. In response, national authorities have promoted reconsideration and strengthening of regional agricultural management systems. In order to achieve consensus for such a transition, it is important to streamline this agricultural management. In this study, we constructed an analytical simulation model based on multi-agent simulations to support such changes. With this model, we investigated the effectiveness of deliberate organization of agricultural management. First, we collected data on farmer behavioral patterns and intentions. In addition, we gathered data at individual farm level with a field survey, and predicted an initial trend (Trend_Simulation). In order to compare simulations with the Trend_Simulation, we assumed that the future labor force in the model settlement was centralized and performed the work as an agricultural organization (Systematic_Simulation). The results from Trend_Simulation predicted that farmland degradation would occur from 2010 onwards, after which the amount of abandoned cultivated and fallow land would increase rapidly. In contrast, for the Systematic_Simulation, as a result of increased management efficiency through labor force accumulation and joint use of agricultural machines, abandonment of cultivated land would not occur for at least 20 more years. Finally, expansion of management scale per individual farm through land leasing between farms was predicted to decrease gradually in the Trend_Simulation, but to increase in the Systematic_Simulation.

Suggested Citation

  • Yamashita, Ryohei & Hoshino, Satoshi, 2018. "Development of an agent-based model for estimation of agricultural land preservation in rural Japan," Agricultural Systems, Elsevier, vol. 164(C), pages 264-276.
    • Handle: RePEc:eee:agisys:v:164:y:2018:i:c:p:264-276
    DOI: 10.1016/j.agsy.2018.05.004
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