Predicting krill swarm characteristics important for marine predators foraging off East Antarctica

• Published in: Ecography
• Main Authors: Bestley, Sophie, Raymond, B, Gales, N., Harcourt, R., Hindell, Mark A, Jonsen, I., Nicol, S., Péron, C., Sumner, M., Weimerskirch, Henri, Wotherspoon, Simon, Cox, M.
• Other Authors: Australian Antarctic Division (AAD), Australian Government, Department of the Environment and Energy, Dept of Biological Sciences Australia, Macquarie University Sydney, Institute for Marine and Antarctic Studies Hobart (IMAS), University of Tasmania Hobart, Australia (UTAS), Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC), Institut National de la Recherche Agronomique (INRA)-La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2018
• Subjects: [SDE]Environmental Sciences; Antarctic; Southern Ocean; The Antarctic; East Antarctica; Austral; Antarc*; Antarctic Krill; Antarctica; Euphausia superba
• Online Access: https://hal.science/hal-01571975; https://doi.org/10.1111/ecog.03080

International audience Open ocean predator-prey interactions are often difficult to interpret because of a lack of information on prey fields at scales relevant to predator behaviour. Hence, there is strong interest in identifying the biological and physical factors influencing the distribution and abundance of prey species, which may be of broad predictive use for conservation planning and evaluating effects of environmental change. This study focuses on a key Southern Ocean prey species, Antarctic krill Euphausia superba, using acoustic observations of individual swarms (aggregations) from a large-scale survey off East Antarctica. We developed two sets of statistical models describing swarm characteristics, one set using underway survey data for the explanatory variables, and the other using their satellite remotely sensed analogues. While survey data are in situ and contemporaneous with the swarm data, remotely sensed data are all that is available for prediction and inference about prey distribution in other areas or at other times. The fitted models showed that the primary biophysical influences on krill swarm characteristics included daylight (solar elevation/radiation) and proximity to the Antarctic continental slope, but there were also complex relationships with current velocities and gradients. Overall model performance was similar regardless of whether underway or remotely sensed predictors were used. We applied the latter models to generate regional-scale spatial predictions using a 10-yr remotely-sensed time series. This retrospective modelling identified areas off east Antarctica where relatively dense krill swarms were consistently predicted during austral mid-summers, which may underpin key foraging areas for marine predators. Spatiotemporal predictions along Antarctic predator satellite tracks, from independent studies, illustrate the potential for uptake into further quantitative modelling of predator movements and foraging. The approach is widely applicable to other krill-dependent ...