Pelagic longline gear depth and shoaling

Temperature-depth recorders (TDRs) were attached to pelagic longline gear in the Hawaii-based commercial fishery to obtain actual fishing depths and to test the accuracy of catenary algorithms for predicting fishing depths. Swordfish gear was set shallow by typically deploying four hooks between successive floats. The observed depth of the settled deepest hook had a median value of 60 m for 333 swordfish sets. Tuna longline gear deployed more hooks between floats (mean = 26.8), and the observed median depth of the deepest hook was 248 m (n = 266 sets). Maximum gear depth was predicted from estimates of the longline sag ratio and catenary algorithms; however, depth was not predicted for all TDR-monitored sets because estimating sag ratios proved problematic. Swordfish sets had less slack in the main line and correspondingly smaller catenary angles (median = 54.2 degrees) than tuna sets (median = 63.7 degrees). Median values of the predicted catenary depth were 123 m for swordfish sets (n = 203) and 307 m for tuna sets (n = 198). Shallow swordfish sets reached only similar to 50% of their predicted depth, while deeper tuna sets reached about 70%. These values indicated that capture depths using traditional catenary equations may be biased without the benefit of TDRs affixed to longlines. Generalized linear models (GLMs) and generalized additive models (GAMs) were developed to explain the percentage of longline shoaling as a function of predicted catenary depth and environmental effects of wind stress, surface current velocity, and current shear. The GAM explained 67.2% of the deviance in shoaling for tuna sets and 41.3% for swordfish sets. Predicted catenary depth was always the initial variable included in the stepwise process, and the inclusion of environmental information in the GAM approach explained an additional 10-17% of the deviance compared to the GLMs. The explanatory ability of the environmental data may have been limited by the scale of the observations (P in space; weekly or monthly in time) or the geometric (transverse versus in-line) forcing between the environment and longline set. Longline gear models with environmental forcing affecting shoaling may be improved in future studies by incorporating contemporaneous environmental information, although this may restrict analyses to fine-scale experimental longlines. Published by Elsevier B.V.