A qualitative model of limiting factors for a salmon life cycle in the context of river rehabilitation

• Published in: Ecological Informatics
• Main Authors: Noble, R. A. A., Cowx, I. G., Bredeweg, B., Linnebank, F., Salles, P.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Elsevier 2009
• Subjects: Salmon; Life cycle; Qualitative reasoning; River rehabilitation; Simulation; Conceptual modelling; Specialist Research - Other; Atlantic salmon
• Online Access: https://hull-repository.worktribe.com/output/387095; https://doi.org/10.1016/j.ecoinf.2009.09.006

Qualitative Reasoning modelling has been promoted as a tool for formalising, integrating and exploring conceptual knowledge in ecological systems, such as river rehabilitation, which draw different information from multiple domains. A qualitative model was developed in Garp3 to capture and formalise knowledge about river rehabilitation and the management of an Atlantic salmon population, for use in an educational setting. The model integrated information about the ecology of the salmon life cycle, the environmental factors that may limit the survival of key life stages and their links with human activities such as agriculture, habitat rehabilitation and fishing. Whilst the compositional approach to qualitative modelling allowed simple representation of component concepts, the successful integration of these components in simulations of complex scenarios required a number of abstract representations, assumptions and technical modelling solutions to handle aspects of ambiguity and complexity, and to obtain the desired system behaviour. The final scenarios and simulations produced were able to represent river rehabilitation concepts in the context of a complete life cycle, but at this scale processing the simulations was very time consuming. Therefore, to handle this complexity an additional series of smaller demonstrator scenarios was developed that succinctly explored individual concepts within the system. This study indicates that qualitative modelling may be a valuable tool for exploring large systems, provided suitable means can be used to handle complexity and ambiguity. © 2009 Elsevier B.V. All rights reserved.