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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.,...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317195/ https://www.ncbi.nlm.nih.gov/pubmed/32888365 http://dx.doi.org/10.1111/cobi.13632 |
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author | Moon, Katie Browne, Nicola K |
author_facet | Moon, Katie Browne, Nicola K |
author_sort | Moon, Katie |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-8317195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83171952021-08-03 Developing shared qualitative models for complex systems Moon, Katie Browne, Nicola K Conserv Biol Conservation Methods 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. John Wiley and Sons Inc. 2020-12-21 2021-06 /pmc/articles/PMC8317195/ /pubmed/32888365 http://dx.doi.org/10.1111/cobi.13632 Text en © 2020 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Conservation Methods Moon, Katie Browne, Nicola K 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 | Conservation Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317195/ https://www.ncbi.nlm.nih.gov/pubmed/32888365 http://dx.doi.org/10.1111/cobi.13632 |
work_keys_str_mv | AT moonkatie developingsharedqualitativemodelsforcomplexsystems AT brownenicolak developingsharedqualitativemodelsforcomplexsystems |