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ICES Journal of Marine Science: Journal du Conseil Advance Access published online on August 22, 2009
ICES Journal of Marine Science: Journal du Conseil, doi:10.1093/icesjms/fsp220
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© Canadian Government, Department of Fisheries and Oceans and the Australian Government, Australian Institute of Marine Science 2009

Hierarchical analysis of a remote, Arctic, artisanal longline fishery

Susan T. Dennard1, M. Aaron MacNeil2, Margaret A. Treble3, Steven Campana4 and Aaron T. Fisk1

1 Great Lakes Institute for Environmental Research, University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada N9B 3P4
2 Australian Institute of Marine Science, PMB 3 Townsville MC, Townsville 4810, Queensland, Australia
3 Freshwater Institute, Canada Department of Fisheries and Oceans, Arctic Aquatic Research Division, 501 University Crescent, Winnipeg, Canada MB R3T 2N6
4 Bedford Institute of Oceanography, Canada Department of Fisheries and Oceans, Eastern Scotian Shelf, 1 Challenger Drive, Dartmouth, NS, Canada B2Y 4A2

Correspondence to M. A. MacNeil: tel: +61 7 4753 4191; fax: +61 7 4772 5852; e-mail: a.macneil{at}aims.gov.au and macneil{at}glau.ca.

Dennard, S. T., MacNeil, M. A., Treble, M. A., Campana, S., and Fisk, A. T. 2010. Hierarchical analysis of a remote, Arctic, artisanal longline fishery. – ICES Journal of Marine Science, 67: 000–000.

This is the first paper to explore trends in catch per unit effort (cpue) through time of a Greenland halibut Reinhardtius hippoglossoides stock targeted by an artisanal, winter fishery in Cumberland Sound on southern Baffin Island, Canada. We modelled cpue data from 1987 to 2003, looking at two questions: what factors have driven cpue trends, and is cpue an accurate index of a stock's abundance? In the context of limited data availability, we used generalized linear models (GLMs) and hierarchical models to assess important predictors of cpue. Hierarchical models with multiple fixed environmental effects contained fishing location or individual fisher as random effects. A month effect showed greatest catch rates during February and March; the monthly North Atlantic Oscillation index was positively associated with catch rates; and a change from decreasing to increasing cpue after 1996 was linked to reduced fishery participation following a large storm. The best Akaike's information criterion-ranked GLM identified a negative relationship of cpue with shark bycatch. Although data limitations precluded conventional stock assessment, our models implicated the environment and fisher behaviour as drivers of cpue trends. Additionally, using multiple hierarchical models to predict cpue provided a more informative analysis for understanding trends in cpue than a GLM alone.

Keywords: catch per unit effort, Cumberland Sound, Greenland halibut, mixed effects models, North Atlantic Oscillation

Received 1 December 2008; accepted 1 July 2009.


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