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A Review of Tools for Incorporating Community Knowledge, Preferences, and Values into Decision Making in Natural Resources Management

Timothy Lynam, University of Zimbabwe
Wil de Jong, Center for Integrated Area Studies, Kyoto University
Douglas Sheil, CIFOR
Trikurnianti Kusumanto, CIFOR
Kirsten Evans, CIFOR


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We survey and evaluate selected participatory tools that have been proven effective in natural resources management and research during our extensive experience with forest communities. We first establish a framework for our analysis by identifying a set of criteria for evaluating each tool. Next we provide a brief description of each tool, followed by an evaluation and comparison of the strengths and weaknesses of all the tools examined and how well they can be adapted to diverse contexts. We also provide suggestions for avoiding common pitfalls. Our findings suggest that most tools are flexible enough to be adapted to a range of applications, and that results are more robust when tools are used in concert. Practitioners should not be disturbed when results are contradictory or unexpected; initial surprises can lead to unexpected discoveries. Given the complexity of natural resources and their management, picking the right tool does not guarantee that the data desired will be produced, but selecting the wrong tool does make success less likely. The tools assessed are Bayesian belief networks and system dynamic modeling tools, discourse-based valuation, the 4Rs framework, participatory mapping, scoring or the Pebble Distribution Method, future scenarios, spidergrams, Venn diagrams, and Who Counts Matrices.

Key words

participatory tools; review; natural resources management; co-management: co-learning

Copyright © 2007 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution 4.0 International License. You may share and adapt the work provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.

Ecology and Society. ISSN: 1708-3087