title: Integrating local and scientific knowledge: an example in fisheries science.
abstract: Attempting to predict the spatial dynamics fish stocks, as required for management, is an ominous task given our incomplete understanding of biological and ecological mechanisms underpinning behavioral responses of fish. Large gaps still exist in our basic scientific knowledge. Nonetheless, the knowledge of fishers and fishery managers is not incorporated into our scientific analyses, even though such information is rich in observation since knowledge of fish behavior and distribution is a prerequisite for their profession. Combining such observations with more conventional scientific studies and theoretical interpretations provides a means by which we may bridge some gaps in our knowledge. Presented here is an example of how both local and scientific knowledge can be integrated in a heuristic model. The model, CLUPEX, is developed in the framework of a fuzzy logic expert system and uses linguistic statements written in natural language to capture and combine knowledge sources in the form of IF... THEN rules. The rules are inferred from interviews with experts and fishery professionals including fishers, fishery managers, scientists, and First Nations people. The knowledge base, comprised of the set of rules, is flexible in the sense that it can easily be modified to add additional information or change current information. Using input pertaining to biotic and abiotic environmental conditions, CLUPEX uses the rules to provide quantitative and qualitative predictions on the structure, dynamics and mesoscale distribution of shoals of migratory adult herring during different life stages of their annual life cycle.
authors: Fisheries Centre, University of British Columbia, Vancouver, Canada. s.mackinson@wcefas.co.uk
authors: S
authors: S
authors: Mackinson
mesh_terms: D000818:Animals; D005398:Fisheries; D005399:Fishes; D005544:Forecasting; D017143:Fuzzy Logic; D006801:Humans; D007198:Indians, North American; D019359:Knowledge; D011157:Population Dynamics