Ecology and Society Ecology and Society
E&S Home > Vol. 23, Iss. 2 > Art. 14 > Abstract Open Access Publishing 
Local knowledge in ecological modeling

Annie Claude Bélisle, Université du Québec en Abitibi-Témiscamingue
Hugo Asselin, Université du Québec en Abitibi-Témiscamingue
Patrice LeBlanc, Université du Québec en Abitibi-Témiscamingue
Sylvie Gauthier, Natural Resources Canada, Canadian Forest Service


Full Text: HTML   
Download Citation


Local people and scientists both hold ecological knowledge, respectively stemming from prolonged day-to-day contact with the environment and from systematic inquiry based on the scientific method. As the complementarity between scientific ecological knowledge (SEK) and local ecological knowledge (LEK) is increasingly acknowledged, LEK is starting to be involved in all branches of ecology, including ecological modeling. However, the integration of both knowledge types into ecological models raises methodological challenges, among which (1) consistency between the degree of LEK involvement and modeling objectives, (2) combination of concepts and methods from natural and social sciences, (3) reliability of the data collection process, and (4) model accuracy. We analyzed how 23 published studies dealt with those issues. We observed LEK reaches its full potential when involved at all steps of the research process. The validity of a modeling exercise is enhanced by an interdisciplinary approach and is jeopardized when LEK elicitation lacks rigor. Bayesian networks and fuzzy rule-based models are well suited to include LEK.

Key words

ecological modeling; elicitation; interdisciplinarity; local ecological knowledge; participatory research

Copyright © 2018 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