Inclusion of prey data improves prediction of bluefin tuna ( Thunnus thynnus ) distribution

Abstract We examined the distribution of Atlantic bluefin tuna ( Thunnus thynnus ) in the Gulf of Maine, Northwest Atlantic Ocean, from 17 to 23 August 1995, in relation to physical and biological parameters. Specifically, we fit a binomial GLM to the bluefin tuna presence–absence data and predictor variables that include: sea surface temperature (SST), ocean depth, distance to an SST front, time‐lagged density of SST fronts, and an interpolated surface of Atlantic herring ( Clupea harengus ) density. In addition, we use simple and partial Mantel tests to examine whether bluefin tuna presence–absence data are significantly associated with these predictors, once spatial autocorrelation is accounted for. Results suggest that the distribution of bluefin tuna significantly correlated with herring density ( z  =   3.525, P  =   0.000424), and that inclusion of biological variables results in a more parsimonious model. Mantel tests results indicate that bluefin tuna abundance is significantly correlated with herring density after the effect of spatial structure is removed (Mantel r  =   0.043, P  <   0.019).