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An agent-based model for assessing grazing strategies and institutional arrangements in Zeku, China

机译：基于代理的评估Zeku，中国Zeku的放牧战略和制度安排模型

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摘要

The assessment of grassland grazing strategies and institutional arrangements is essential for ensuring the sustainable development of grassland grazing systems. By employing per-pixel grazing information derived from remote sensing data, this paper presents an agent-based model of grassland grazing (ABMGG) for Zeku, China that was designed as a framework for assessing the effects of different combinations of grazing strategies and institutional arrangements on grassland status. By calibrating the parameter values of the ABMGG to the system status values under a policy that has already been implemented, the ABMGG can help us to understand grassland degradation in response to management interventions for each patch of land. In the Zeku implementation, it was found that although different grazing policy scenarios could not significantly improve or decrease the overall grassland leaf area index, a rotational group grazing scenario with a land market tenure system did produce a smaller number of severely degraded grass patches than other policy scenarios (except regional continuous grazing). This provides a new perspective on the consequences of grassland management practices where past research has concentrated more on overall grassland productivity. The ABMGG can extend the ability of policy assessment tools to a high resolution level with pixel-specific real-time remote sensing data, making the assessment results more accurate and representative.
机译：对草地放牧策略和机构安排的评估对于确保草原放牧系统可持续发展至关重要。通过采用从遥感数据导出的每个像素放牧信息，本文介绍了中国泽库的基于代理的草地草原（ABMGG）模型，旨在评估不同组合和机构安排的不同组合影响的框架论草原地位。通过在已经实施的政策下校准ABMGG的参数值来校准系统状态值，ABMGG可以帮助我们了解草地退化，以应对每种土地的管理干预措施。在Zeku实施中，发现虽然不同的放牧政策情景无法显着改善或减少整体草原叶面积指数，但与土地市场任期系统的旋转集团放牧场景确实产生了比其他更少的严重降级的草斑块产生了较少数量的严重降级的草斑块政策情景（区域持续放牧除外）。这为过去研究集中在整体草地生产力更多的草地管理实践的后果提供了新的视角。 ABMGG可以将策略评估工具的能力扩展到具有像素特定的实时遥感数据的高分辨率级别，使评估结果更准确和代表。

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