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

Authors :
Robert Harcourt
Sophie Bestley
Clara Péron
Stephen Nicol
Michael D. Sumner
Simon Wotherspoon
Nick Gales
Ian D. Jonsen
Henri Weimerskirch
Mark A. Hindell
Ben Raymond
Martin J. Cox
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 [Horbat] (IMAS)
University of Tasmania (UTAS)
Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC)
Institut National de la Recherche Agronomique (INRA)-Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS)
Macquarie University [Sydney]
University of Tasmania [Hobart, Australia] (UTAS)
Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Université de La Rochelle (ULR)
Source :
Ecography, Ecography, Wiley, 2018, 41, pp.996-1012. ⟨10.1111/ecog.03080⟩
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

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 ecosystems, and our findings are relevant to similar efforts examining biophysical linkages elsewhere in the Southern Ocean and beyond.

Details

Language :
English
ISSN :
09067590 and 16000587
Database :
OpenAIRE
Journal :
Ecography, Ecography, Wiley, 2018, 41, pp.996-1012. ⟨10.1111/ecog.03080⟩
Accession number :
edsair.doi.dedup.....930a7eafa46863de0f888dd623c52429
Full Text :
https://doi.org/10.1111/ecog.03080⟩