Relative Bycatch:Target Catch Probability Product (daily), EcoCast Project, Lon0360

The Relative Bycatch:Target Catch Probability Product is produced using a data-driven, multi-species predictive habitat modelling framework. First, boosted regression tree models were fit to determine the habitat preferences of the target species, broadbill swordfish (Xiphias gladius), and three bycatch-sensitive species that interact with the California drift gillnet fishery (leatherback sea turtle (Dermochelys coricea), blue shark (Prionace glauca), California sea lion (Zalophus californianus)). Then, individual species weightings were set to reflect the level of bycatch and management concern for each species. Prediction layers for each species were then combined into a single surface by multiplying the layer by the species weighting, summing the layers, and then re-calculating the range of values in the final predictive surface from -1 (low catch & high bycatch probabilities) to 1 (high catch & low bycatch probabilities).