A predictive krill distribution model for Euphausia pacifica and Thysanoessa spinifera using scaled acoustic backscatter in the Northern California Current

Abstract

Euphausiids (krill) are globally significant zooplankton prey for many commercially important or endangered predator species. In the productive upwelling system of the Northern California Current (NCC), two krill species, Euphausia pacifica and Thysanoessa spinifera, dominate the preyscape and constitute an important food resource for many seabirds, cetaceans, and fish. In this study, we use five years of hydroacoustic and net tow data collected in the NCC to develop integrative models predicting acoustic backscatter scaled for E. pacifica or T. spinifera separately. Boosted Regression Trees and Generalized Additive Models are applied in an original ensemble hurdle framework to predict krill presence and abundance from a diverse set of topographic and oceanographic predictors. Krill metrics had significant relationships with seabed depth, distance to submarine canyons, and variables indicative of dynamic ocean conditions (e.g., total deviance explained in acoustic data: 25 % in the presence-absence model & 49 % in the abundance model). Predictions of krill abundance at 5 km resolution averaged by month indicate differential habitat preferences between the two species: T. spinifera was constrained to the continental shelf, around and inshore of the 200 m isobath, whereas E. pacifica was found in greater abundances just offshore of the 200 m isobath and into offshore water in lower abundances. E. pacifica was generally more abundant than T. spinifera (10:1.3 ratio). Both species increased in abundance in the spring and summer, followed by a rapid decline in the fall, and lowest abundances in the winter. These models can produce fine-scale spatial and year-round weekly predictions of E. pacifica and T. spinifera abundance in the NCC, which will provide essential knowledge and new spatial layers about critical ecosystem components to support research and management.