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A Rapid Forest Assessment Method for Multiparty Monitoring Across Landscapes

机译:一种用于森林多方监测的快速森林评估方法

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Collaborative natural resource management has emerged as a means to increase the transparency of decisionmaking in public lands management and to promote shared learning among stakeholders. We developed a rapid forest assessment (RFA) approach for monitoring the key characteristics of forests that capitalizes on the growing interest for citizen science monitoring and can be implemented at large extents. The methods were designed for use with minimal training, to maximize field efficiency, and to simplify interpretation of the data. We chose our variables based on the common interests and questions of collaborative groups. We collected data on trees, fuels, woody debris, understory, horizontal cover, weeds, and soil disturbance. We tested the methods with several student groups and quantified the variability of measures within groups. We discuss the benefits of and challenges to engaging citizen scientists in monitoring. The simplicity and efficiency of the RFA make it a useful tool for multiparty monitoring.
机译:协作性自然资源管理已成为增加公共土地管理决策透明度和促进利益相关者之间共同学习的一种手段。我们开发了一种用于监视森林关键特征的快速森林评估(RFA)方法,该方法利用了对公民科学监视日益增长的兴趣,并可以在很大程度上实施。这些方法设计用于最少的培训,以最大化现场效率,并简化数据的解释。我们根据协作小组的共同兴趣和问题选择变量。我们收集了有关树木,燃料,木屑,林下,水平覆盖物,杂草和土壤干扰的数据。我们与几个学生小组一起测试了这些方法,并量化了小组内部度量的变异性。我们讨论了让公民科学家参与监测的好处和挑战。 RFA的简单性和效率使其成为多方监视的有用工具。

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