Developing shared qualitative models for complex systems
Understanding complex systems is essential to ensure their conservation and effective management. Models commonly support understanding of complex ecological systems and, by extension, their conservation. Modeling, however, is largely a social process constrained by individuals’ mental models (i.e.,...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
WILEY
2021
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| Subjects: | |
| Online Access: | http://purl.org/au-research/grants/arc/DE180100391 http://hdl.handle.net/20.500.11937/90252 |
| _version_ | 1848765356512903168 |
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| author | Moon, K. Browne, Nicola |
| author_facet | Moon, K. Browne, Nicola |
| author_sort | Moon, K. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Understanding complex systems is essential to ensure their conservation and effective management. Models commonly support understanding of complex ecological systems and, by extension, their conservation. Modeling, however, is largely a social process constrained by individuals’ mental models (i.e., a small-scale internal model of how a part of the world works based on knowledge, experience, values, beliefs, and assumptions) and system complexity. To account for both system complexity and the diversity of knowledge of complex systems, we devised a novel way to develop a shared qualitative complex system model. We disaggregated a system (carbonate coral reefs) into smaller subsystem modules that each represented a functioning unit, about which an individual is likely to have more comprehensive knowledge. This modular approach allowed us to elicit an individual mental model of a defined subsystem for which the individuals had a higher level of confidence in their knowledge of the relationships between variables. The challenge then was to bring these subsystem models together to form a complete, shared model of the entire system, which we attempted through 4 phases: develop the system framework and subsystem modules; develop the individual mental model elicitation methods; elicit the mental models; and identify and isolate differences for exploration and identify similarities to cocreate a shared qualitative model. The shared qualitative model provides opportunities to develop a quantitative model to understand and predict complex system change. |
| first_indexed | 2025-11-14T11:33:57Z |
| format | Journal Article |
| id | curtin-20.500.11937-90252 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:33:57Z |
| publishDate | 2021 |
| publisher | WILEY |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-902522023-06-08T09:07:00Z Developing shared qualitative models for complex systems Moon, K. Browne, Nicola Science & Technology Life Sciences & Biomedicine Biodiversity Conservation Ecology Environmental Sciences Biodiversity & Conservation Environmental Sciences & Ecology cognitive maps ecological modeling influence diagrams knowledge perceptions qualitative modeling social science research methods workshop facilitation conocimiento diagramas de influencia facilitació n de talleres mapas cognitivos mé todos de investigació n de ciencias sociales modelado cualitativo modelado ecoló gico percepciones MENTAL MODELS INFLUENCE DIAGRAMS REEF CARBONATE STAKEHOLDERS METHODOLOGY KNOWLEDGE FRAMEWORK Understanding complex systems is essential to ensure their conservation and effective management. Models commonly support understanding of complex ecological systems and, by extension, their conservation. Modeling, however, is largely a social process constrained by individuals’ mental models (i.e., a small-scale internal model of how a part of the world works based on knowledge, experience, values, beliefs, and assumptions) and system complexity. To account for both system complexity and the diversity of knowledge of complex systems, we devised a novel way to develop a shared qualitative complex system model. We disaggregated a system (carbonate coral reefs) into smaller subsystem modules that each represented a functioning unit, about which an individual is likely to have more comprehensive knowledge. This modular approach allowed us to elicit an individual mental model of a defined subsystem for which the individuals had a higher level of confidence in their knowledge of the relationships between variables. The challenge then was to bring these subsystem models together to form a complete, shared model of the entire system, which we attempted through 4 phases: develop the system framework and subsystem modules; develop the individual mental model elicitation methods; elicit the mental models; and identify and isolate differences for exploration and identify similarities to cocreate a shared qualitative model. The shared qualitative model provides opportunities to develop a quantitative model to understand and predict complex system change. 2021 Journal Article http://hdl.handle.net/20.500.11937/90252 10.1111/cobi.13632 English http://purl.org/au-research/grants/arc/DE180100391 http://creativecommons.org/licenses/by/4.0/ WILEY fulltext |
| spellingShingle | Science & Technology Life Sciences & Biomedicine Biodiversity Conservation Ecology Environmental Sciences Biodiversity & Conservation Environmental Sciences & Ecology cognitive maps ecological modeling influence diagrams knowledge perceptions qualitative modeling social science research methods workshop facilitation conocimiento diagramas de influencia facilitació n de talleres mapas cognitivos mé todos de investigació n de ciencias sociales modelado cualitativo modelado ecoló gico percepciones MENTAL MODELS INFLUENCE DIAGRAMS REEF CARBONATE STAKEHOLDERS METHODOLOGY KNOWLEDGE FRAMEWORK Moon, K. Browne, Nicola Developing shared qualitative models for complex systems |
| title | Developing shared qualitative models for complex systems |
| title_full | Developing shared qualitative models for complex systems |
| title_fullStr | Developing shared qualitative models for complex systems |
| title_full_unstemmed | Developing shared qualitative models for complex systems |
| title_short | Developing shared qualitative models for complex systems |
| title_sort | developing shared qualitative models for complex systems |
| topic | Science & Technology Life Sciences & Biomedicine Biodiversity Conservation Ecology Environmental Sciences Biodiversity & Conservation Environmental Sciences & Ecology cognitive maps ecological modeling influence diagrams knowledge perceptions qualitative modeling social science research methods workshop facilitation conocimiento diagramas de influencia facilitació n de talleres mapas cognitivos mé todos de investigació n de ciencias sociales modelado cualitativo modelado ecoló gico percepciones MENTAL MODELS INFLUENCE DIAGRAMS REEF CARBONATE STAKEHOLDERS METHODOLOGY KNOWLEDGE FRAMEWORK |
| url | http://purl.org/au-research/grants/arc/DE180100391 http://hdl.handle.net/20.500.11937/90252 |