A review of tools for incorporating community knowledge, preferences, and values into decision making in natural resources management

Timothy Lynam*, Wil de Jong, Douglas Sheil, Thikurnianti Kusumanto, Kirsten Evans

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

368 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number5
JournalEcology and Society
Volume12
Issue number1
DOIs
Publication statusPublished - Jun 2007
Externally publishedYes

Keywords

  • Co-learning
  • Co-management
  • Natural resources management
  • Participatory tools
  • Review

Fingerprint

Dive into the research topics of 'A review of tools for incorporating community knowledge, preferences, and values into decision making in natural resources management'. Together they form a unique fingerprint.

Cite this