Advancing the application of the ideal free distribution to spatial models of fishing effort: the isodar approach

• Published in: Canadian journal of fisheries and aquatic sciences Vol. 69; no. 10; pp. 1610 - 1620
• Main Authors: GILLIS, D. M, DER LEE, A. Van
• Format: Journal Article
• Language: English
• Published: Ottawa, ON NRC Research Press 01.10.2012; National Research Council of Canada; Canadian Science Publishing NRC Research Press
• Subjects: Analysis; Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Correlation analysis; Ecology; Evolutionary ecology; Exploitation and management of natural biological resources (hunting, fishing and exploited populations survey, etc.); Fisheries; Fishery management; Fishing; Fundamental and applied biological sciences. Psychology; Marine; Melanogrammus aeglefinus; Parameter estimation; Population biology; Canada; ANW, Atlantic, Scotian Shelf, Browns Bank; Aquatic environment; Spatial model; Ideal free distribution; Catch effort
• DOI: 10.1139/f2012-091
• ISSN: 0706-652X

The ideal free distribution (IFD) of behavioral ecology has been used in the study of the distribution of fishing effort since the 1990s. Concurrently, evolutionary perspectives on forager distributions have led to the development of theoretical curves of equal fitness, named isodars, to test IFD hypotheses. We develop isodars, based upon catch rates and unknown costs, to quantify regularity in the distribution of fishing effort among alternative areas. Our analyses indicate that these isodars provide significantly better predictions than a simple IFD without costs. Autocorrelation in the catch and effort data necessitates the use of generalized linear least squares when estimating model parameters. Differences in costs that are proportional to effort are more clearly identified in the model than nonlinear effects, which may arise from extreme interference competition. The isodar approach provides a new tool for examining the spatial dynamics of catch and effort data. It improves the accuracy of predictions and provides new parameters related to costs and vessel interactions that can be applied to rapidly identify situations where effort dynamics have changed.