Prediction of krill swarm characteristics that drive a marine predator ‘hotspot' region off East Antarctica

Understanding open-ocean predator-prey interactions is often hampered by a lack of information on prey fields at scales relevant to the behaviour of the predators. 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, using acoustic observations of individual swarms from a large-scale survey off East Antarctica (BROKE-West, 2006). Two sets of statistical models are developed and evaluated that predict indices related to swarm densities: firstly using underway survey data for the explanatory variables, and secondly their satellite remotely-sensed analogues. While survey data are in situ and contemporaneous, remotely-sensed data is all that will be available for prediction and inference about prey distribution in most cases. Spatio-temporal confounding within these data requires some care, particularly with model selection, validation and estimation of uncertainties. Emergent patterns in fitted models show a strong lunar influence with higher night-time relative swarm densities amplified during the full moon. Complex environmental relationships indicate higher relative swarm densities in association with lower chlorophyll/fluorescence; in ‘aged’ areas (longer time since ice melt) where rates of ice melt were higher; and in areas where bathymetric gradients were high but current gradients not extreme. Model performance was similar based on underway and remotely sensed predictors. Two applications are demonstrated (i) spatial prey-field prediction and (ii) spatio-temporal prediction along Antarctic predator satellite tracks drawn from independent studies. Outcomes include the prediction of prey field characteristics of practical use for predator studies, as well as identification of influential bio-physical variables of use in further modelling studies. Our methods are widely applicable to other high-latitude, krill-dependent, offshore ecosystems, and our findings should be relevant to similar efforts examining biophysical linkages elsewhere in the Southern Ocean.