Local knowledge in ecological modeling

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 (LE...

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Bibliographic Details
Published in:Ecology and society 2018-06, Vol.23 (2), p.14, Article art14
Main Authors: Bélisle, Annie Claude, Asselin, Hugo, LeBlanc, Patrice, Gauthier, Sylvie
Format: Article
Language:English
Subjects:
Accuracy
Bayesian analysis
Complementarity
Data analysis
Data collection
ecological modeling
Ecological studies
Ecology
elicitation
interdisciplinarity
Interdisciplinary aspects
Knowledge
local ecological knowledge
Local knowledge
Mathematical models
Model accuracy
Modelling
Networks
participatory research
Reliability
Reliability analysis
Scientific knowledge
Scientific method
Scientists
Social sciences
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Summary: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.
ISSN:1708-3087
1708-3087
DOI:10.5751/ES-09949-230214