BelisleAsselinLeblancEtAl2018

Référence

Belisle, A.C., Asselin, H., LeBlanc, P. and Gauthier, S. (2018) Local knowledge in ecological modeling. Ecology and Society, 23(2). (URL )

Résumé

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.

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@ARTICLE { BelisleAsselinLeblancEtAl2018,
    TITLE = { Local knowledge in ecological modeling. },
    AUTHOR = { Belisle, A.C. and Asselin, H. and LeBlanc, P. and Gauthier, S. },
    JOURNAL = { Ecology and Society },
    YEAR = { 2018 },
    NUMBER = { 2 },
    VOLUME = { 23 },
    ABSTRACT = { 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. },
    DOI = { 10.5751/ES-09949-230214 },
    KEYWORDS = { ecological modeling },
    OWNER = { DanielLesieur },
    PUBLISHER = { The Resilience Alliance },
    TIMESTAMP = { 2018.04.27 },
    URL = { https://www.ecologyandsociety.org/vol23/iss2/art14/ },
}

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