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ICES Journal of Marine Science: Journal du Conseil 1994 51(4):439-445; doi:10.1006/jmsc.1994.1045
© 1994 by ICES/CIEM International Council for the Exploration of the Sea/Conseil International pour l'Exploration de la Mer
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GMDH algorithm as a tool for bivalve growth analysis and prediction

Michel R. Claereboudt

Department de Biologie and GIROQ (Groupe Interuniversitaire de Recherches Océanographiques du Québec), Laval University Québec G1K 7P4, Canada

The question of whether growth in bivalves is predictable in terms of environmental condition is addressed directly by trying to infer juvenile scallop growth from environment data within and between two locations in the Baie des Chaleurs, Québec. Using models based on either self-organizing models – the group method of data handling (GMDH) algorithm - or multilinear regressions, scallop growth was found to be predictable. GMDH models lead consistently to better predictions than multilinear regressions and could thus be a useful alternative tool in managing scallop fisheries aquaculture. Temperature and food availability were the most prominent variables included in the GMDHD models, emphisizing their importance as physical determinants of scallop growth.

Keywords: GMDH, multilinear regression, growth, environmental effects

Received 5 May 1993; accepted 14 April 1994.


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