Literature DB >> 24737765

What a jerk: prey engulfment revealed by high-rate, super-cranial accelerometry on a harbour seal (Phoca vitulina).

Kristina S Ydesen1, Danuta M Wisniewska2, Janni D Hansen3, Kristian Beedholm4, Mark Johnson5, Peter T Madsen4.   

Abstract

A key component in understanding the ecological role of marine mammal predators is to identify how and where they capture prey in time and space. Satellite and archival tags on pinnipeds generally only provide diving and position information, and foraging is often inferred to take place in particular shaped dives or when the animal remains in an area for an extended interval. However, fast movements of the head and jaws may provide reliable feeding cues that can be detected by small low-power accelerometers mounted on the head. To test this notion, a harbour seal (Phoca vitulina) was trained to wear an OpenTag (sampling at 200 or 333 Hz with ± 2 or ± 16 g clipping) on its head while catching fish prey in front of four underwater digital high-speed video cameras. We show that both raptorial and suction feeding generate jerk (i.e. differential of acceleration) signatures with maximum peak values exceeding 1000 m s(-3). We conclude that reliable prey capture cues can be derived from fast-sampling, head-mounted accelerometer tags, thus holding a promising potential for long-term studies of foraging ecology and field energetics of aquatic predators in their natural environments.
© 2014. Published by The Company of Biologists Ltd.

Entities:  

Keywords:  Accelerometry; Feeding; Foraging; Harbour seal; Jerk; Pinniped; Tag

Mesh:

Year:  2014        PMID: 24737765     DOI: 10.1242/jeb.100016

Source DB:  PubMed          Journal:  J Exp Biol        ISSN: 0022-0949            Impact factor:   3.312


  21 in total

Review 1.  Challenges and solutions for studying collective animal behaviour in the wild.

Authors:  Lacey F Hughey; Andrew M Hein; Ariana Strandburg-Peshkin; Frants H Jensen
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-05-19       Impact factor: 6.237

2.  High rates of vessel noise disrupt foraging in wild harbour porpoises (Phocoena phocoena).

Authors:  Danuta Maria Wisniewska; Mark Johnson; Jonas Teilmann; Ursula Siebert; Anders Galatius; Rune Dietz; Peter Teglberg Madsen
Journal:  Proc Biol Sci       Date:  2018-02-14       Impact factor: 5.349

3.  Prey encounters and spatial memory influence use of foraging patches in a marine central place forager.

Authors:  Virginia Iorio-Merlo; Isla M Graham; Rebecca C Hewitt; Geert Aarts; Enrico Pirotta; Gordon D Hastie; Paul M Thompson
Journal:  Proc Biol Sci       Date:  2022-03-02       Impact factor: 5.349

4.  Identification of Prey Captures in Australian Fur Seals (Arctocephalus pusillus doriferus) Using Head-Mounted Accelerometers: Field Validation with Animal-Borne Video Cameras.

Authors:  Beth L Volpov; Andrew J Hoskins; Brian C Battaile; Morgane Viviant; Kathryn E Wheatley; Greg Marshall; Kyler Abernathy; John P Y Arnould
Journal:  PLoS One       Date:  2015-06-24       Impact factor: 3.240

5.  Australian fur seals (Arctocephalus pusillus doriferus) use raptorial biting and suction feeding when targeting prey in different foraging scenarios.

Authors:  David P Hocking; Marcia Salverson; Erich M G Fitzgerald; Alistair R Evans
Journal:  PLoS One       Date:  2014-11-12       Impact factor: 3.240

6.  Dive characteristics can predict foraging success in Australian fur seals (Arctocephalus pusillus doriferus) as validated by animal-borne video.

Authors:  Beth L Volpov; David A S Rosen; Andrew J Hoskins; Holly J Lourie; Nicole Dorville; Alastair M M Baylis; Kathryn E Wheatley; Greg Marshall; Kyler Abernathy; Jayson Semmens; Mark A Hindell; John P Y Arnould
Journal:  Biol Open       Date:  2016-02-12       Impact factor: 2.422

7.  High sea surface temperatures driven by a strengthening current reduce foraging success by penguins.

Authors:  Gemma Carroll; Jason D Everett; Robert Harcourt; David Slip; Ian Jonsen
Journal:  Sci Rep       Date:  2016-02-29       Impact factor: 4.379

8.  Seeing It All: Evaluating Supervised Machine Learning Methods for the Classification of Diverse Otariid Behaviours.

Authors:  Monique A Ladds; Adam P Thompson; David J Slip; David P Hocking; Robert G Harcourt
Journal:  PLoS One       Date:  2016-12-21       Impact factor: 3.240

9.  Putting the behavior into animal movement modeling: Improved activity budgets from use of ancillary tag information.

Authors:  Sophie Bestley; Ian Jonsen; Robert G Harcourt; Mark A Hindell; Nicholas J Gales
Journal:  Ecol Evol       Date:  2016-10-20       Impact factor: 2.912

10.  Heart rate and startle responses in diving, captive harbour porpoises (Phocoena phocoena) exposed to transient noise and sonar.

Authors:  Siri L Elmegaard; Birgitte I McDonald; Jonas Teilmann; Peter T Madsen
Journal:  Biol Open       Date:  2021-06-16       Impact factor: 2.422

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