A Principal Component Analysis of Vertical Temperature Profiles for Tracking Movements of Swordfish Xiphias gladius

Light-based algorithms using pop-up satellite archival tag (PSAT) technology has successfully derived geolocation estimates along the course of the deployment track. However, the diel behavior of swordfish, and other commercially viable highly migratory species (HMS), precludes this methodology because of the lack of ambient light data. Advances in geolocation methods have allowed coordinate estimates of swordfish to be within 0.3° longitude and 0.7° latitude under optimal conditions. A principal component analysis (PCA) of temperature profiles is used to estimate the movement between the initial location of release and the location of tag release and transmission. PSAT data from swordfish (n = 3) and blue marlin (n = 3) tagged within the Caribbean and Northwest Atlantic, were used to generate daily coordinate estimations. The blue marlin data included light information sufficient to derive geolocation estimates using the TrackIt model, while the PCA model was used to derive comparison estimates. Comparisons of the two models show an average root mean square error of 32.9 km, demonstrating that the PCA model can be used to extract the movement of tagged fish. This study shows the feasibility of using temperature and depth data instead of light levels to allow effective track derivation for swordfish and as an additional datastream for refining the tracks of other electronically tagged fish.