A rapid forest assessment method for multiparty monitoring across landscapes

Abstract

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.