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ForestSim Model of Impacts of Smallholder Dynamics: Forested Landscapes of the Upper Peninsula of Michigan

机译:小农动力影响的ForestSim模型:密歇根州上半岛的森林景观

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Many forested landscapes in the United States contain a large number of small private landowners (smallholders). The individual decisions of these smallholders can collectively have a large impact on the structure, composition, and connectivity of forests. While models have been developed to try to understand this large-scale collective impact, few models have incorporated extensive information from individual decision-making. Here we introduce an agent-based model, infused with sociological data from smallholders, overlaid on a GIS layer to represent individual smallholders, and used to simulate the impact of thousands of harvesting decisions. Our preliminary results suggest that certain smallholder characteristics (such as relative smallholder age and education level as well as whether a smallholder is resident or absentee) and information flow among owners can radically impact forests at the landscape scale. While still in its preliminary stages, this modeling approach is likely to demonstrate in detail the consequences of decision-making due to changing smallholder demographics or new policies and programs. This approach can help estimate the effectiveness of programs based on landscape-scale programmatic goals and the impact of new policy initiatives.
机译:在美国,许多森林景观都包含大量的小型私人土地所有者(小农)。这些小农户的个人决定可能对森林的结构,组成和连通性产生巨大影响。虽然已经开发出模型来尝试理解这种大规模的集体影响,但是很少有模型结合了来自个体决策的大量信息。在这里,我们介绍了一个基于代理的模型,该模型注入了小农户的社会学数据,并覆盖在GIS层上以代表各个小农户,并用于模拟成千上万个收获决策的影响。我们的初步结果表明,某些小农户特征(例如相对的小农户年龄和教育水平,以及小农户是否居住或缺席)以及所有者之间的信息流都可以从景观尺度上对森林产生根本性的影响。尽管仍处于初步阶段,但是这种建模方法可能会详细展示由于小农户人口统计数据变化或新政策和计划而导致的决策后果。这种方法可以帮助根据景观规模的计划目标和新政策措施的影响来评估计划的有效性。

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