Analysis of spatial variability of Georges Bank haddock (Melanogrammus aeglefinus) from trawl survey data using a linear regression model with spatial interaction
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A regression model with spatially autocorrelated errors is used to test if there is systematic spatial variation across the study area in haddock catch per tow data from the NEFC annual fall survey from 1963 - 1987. A maximum likelihood estimation procedure is used, and the likelihoodratio method is used for testing the significance of the model. The results suggest that for many of the years analyzed information on the depth and location of sampling stations can be used to explain part of the spatial variability of the trawl catches. If model-based inferences are made from the survey data, the depth related trend and the autocorrelation for the errors of the model should be taken into account. The potential use of a spatial prediction method for geographic mapping of density is discussed.