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Using Consensus Analysis to Assess Mental Models about Water Use and Management in the Crocodile River Catchment, South Africa

Samantha S Stone-Jovicich, CSIRO Ecosystem Sciences, Townsville
Timothy Lynam, CSIRO Ecosystem Sciences, Townsville
Anne Leitch, CSIRO Ecosystem Sciences, Brisbane; ARC CoE Coral Reef Studies, James Cook University
Natalie A Jones, University of Queensland, School of Rural and Natural Systems Management


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The content, structure, and distribution of mental models can be elicited and measured using a variety of methods. In this article we explore a method for eliciting mental models within the context of water use and management in South Africa. This method is consensus analysis, a technique developed in cognitive anthropology. We used it to analyze qualitative data from semistructured interviews, pilesorts, and questionnaires to test quantitatively the degree of sharing and diversity of mental models within and across social groups. The consensus analysis method focused on comparing the mental models of two key stakeholder groups in the Crocodile River catchment in South Africa, i.e., conservationists and irrigators, to better understand the level of consensus between these groups. We specifically investigated the level of agreement regarding: (1) major water users of the Crocodile River, (2) causes of the current problems with flows in the river, (3) consequences of the river not flowing, and 4) priorities for future use. We discuss the results and examine the strengths and challenges of consensus analysis for eliciting and measuring mental models. We also evaluated the usefulness of this method in assisting natural resource managers to identify strategies for improving integrated management of water resources.

Key words

consensus analysis; mental models; South Africa; water management

Copyright © 2011 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