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A Rapid Forest Assessment Method for Multiparty Monitoring Across Landscapes

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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.

Management and Policy Implications: Contemporary forest management in the western United States is endeavoring to match the scale of management with the scale of important ecosystem processes, especially fire. This has resulted in forest management actions that are planned and implemented at increasingly broader spatial extents. Such actions often necessitate both collaboration and adaptive management to address uncertainty and mistrust. Traditional intensive monitoring methods are not designed for use by citizens and are limited in their geographic scope by the costs of data collection. The forest vegetation monitoring method we describe here, the rapid forest assessment, is simple to learn and can be implemented at a low cost. It is designed for use by collaborative groups, citizen scientists, and youth conservation corps, and the data can be used to answer many pertinent management questions. The data can also be used in existing software programs to model forest processes (e.g., fire behavior, forest growth, and wildlife habitat suitability). Involving stakeholders in monitoring can build trust and ultimately improve management efficiency to work at larger scales. Collaborative groups can use these methods to monitor management outcomes at a landscape scale and provide input to forest managers.
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Keywords: adaptive management; citizen science; collaboration; forest management; landscape; monitoring

Document Type: Research Article

Publication date: March 1, 2016

This article was made available online on September 24, 2015 as a Fast Track article with title: "A Rapid Forest Assessment Method for Multiparty Monitoring Across Landscapes".

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