Literature DB >> 20836459

Predicting feeding success in a migratory predator: integrating telemetry, environment, and modeling techniques.

Sophie Bestley1, Toby A Patterson, Mark A Hindell, John S Gunn.   

Abstract

Foraging theory predicts that mobile predators should target high profitability areas with plentiful resources and minimize time spent moving between these areas. This has led to a focus in recent literature on the identification of "hotspots" important for migratory marine predators, i.e., regions where predators spend disproportionate amounts of time ostensibly due to high prey abundance; and determination of the environmental features characteristic of such areas. We investigated factors predicting foraging success in southern bluefin tuna (SBT; Thunnus maccoyii), by integrating telemetry-based feeding and movement data (n = 19 fish, length to caudal fork [LCF] = 99 +/- 3 cm) with environmental data over the scale of their annual oceanic migrations during 1998-2000. We used widely available statistical modeling techniques, generalized linear models, and generalized linear mixed models, formulated to represent feeding as a Markov process. The results showed increased feeding and predictability of feeding occurs in the coastal waters of southern Australia, providing some evidence that this area represents a fixed foraging "hotspot" for juvenile tuna during the austral summer. However, in oceanic waters southern bluefin tuna did not fit the common model of migration, but rather showed a pattern of relatively high foraging success throughout their migratory range, especially during periods of continuous travel. Interestingly, foraging "coldspots" (prolonged low-feeding periods) as well as "hotspots" were apparent across individual tracks, predicted most strongly by warm ocean temperatures. These results provide a new perspective on the ecology of large-scale feeding migrations within the context of the heterogeneous ocean environment, where the continuous and opportunistic feeding of generalist predators may be more common, particularly in predatory large pelagic fishes, than is currently documented.

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Year:  2010        PMID: 20836459     DOI: 10.1890/08-2019.1

Source DB:  PubMed          Journal:  Ecology        ISSN: 0012-9658            Impact factor:   5.499


  15 in total

1.  Predicting the Influence of Streamflow on Migration and Spawning of a Threatened Diadromous Fish, the Australian Grayling Prototroctes Maraena.

Authors:  W M Koster; D A Crook; D R Dawson; S Gaskill; J R Morrongiello
Journal:  Environ Manage       Date:  2017-04-03       Impact factor: 3.266

2.  Integrative modelling of animal movement: incorporating in situ habitat and behavioural information for a migratory marine predator.

Authors:  Sophie Bestley; Ian D Jonsen; Mark A Hindell; Christophe Guinet; Jean-Benoît Charrassin
Journal:  Proc Biol Sci       Date:  2012-11-07       Impact factor: 5.349

3.  Spawning Dynamics and Size Related Trends in Reproductive Parameters of Southern Bluefin Tuna, Thunnus maccoyii.

Authors:  Jessica H Farley; Tim L O Davis; Mark V Bravington; Retno Andamari; Campbell R Davies
Journal:  PLoS One       Date:  2015-05-18       Impact factor: 3.240

4.  Hidden Markov models: the best models for forager movements?

Authors:  Rocio Joo; Sophie Bertrand; Jorge Tam; Ronan Fablet
Journal:  PLoS One       Date:  2013-08-23       Impact factor: 3.240

5.  Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.

Authors:  Morgane Viviant; Pascal Monestiez; Christophe Guinet
Journal:  PLoS One       Date:  2014-03-06       Impact factor: 3.240

Review 6.  Path segmentation for beginners: an overview of current methods for detecting changes in animal movement patterns.

Authors:  Hendrik Edelhoff; Johannes Signer; Niko Balkenhol
Journal:  Mov Ecol       Date:  2016-09-01       Impact factor: 3.600

7.  Using hierarchical bayes to understand movement, health, and survival in the endangered north atlantic right whale.

Authors:  Robert S Schick; Scott D Kraus; Rosalind M Rolland; Amy R Knowlton; Philip K Hamilton; Heather M Pettis; Robert D Kenney; James S Clark
Journal:  PLoS One       Date:  2013-06-06       Impact factor: 3.240

8.  Estimating resource acquisition and at-sea body condition of a marine predator.

Authors:  Robert S Schick; Leslie F New; Len Thomas; Daniel P Costa; Mark A Hindell; Clive R McMahon; Patrick W Robinson; Samantha E Simmons; Michele Thums; John Harwood; James S Clark
Journal:  J Anim Ecol       Date:  2013-07-19       Impact factor: 5.091

9.  Expectation-Maximization Binary Clustering for Behavioural Annotation.

Authors:  Joan Garriga; John R B Palmer; Aitana Oltra; Frederic Bartumeus
Journal:  PLoS One       Date:  2016-03-22       Impact factor: 3.240

10.  DNA barcoding identifies a cosmopolitan diet in the ocean sunfish.

Authors:  Lara L Sousa; Raquel Xavier; Vânia Costa; Nicolas E Humphries; Clive Trueman; Rui Rosa; David W Sims; Nuno Queiroz
Journal:  Sci Rep       Date:  2016-07-04       Impact factor: 4.379

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