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On the movement behaviours of tropical tuna in modern commercial fisheries

On the movement behaviours of tropical tuna in modern commercial fisheries
On the movement behaviours of tropical tuna in modern commercial fisheries
Exploitation of tropical tunas in the western and central Pacific Ocean constitutes an industry generating over US$5 billion annually. As concern for the sustainability of fishing operations grows, there is an increasing need to explore the potential effects that small-scale movement behaviours, typically ignored in stock assessment, may have on larger scale population dynamics. In this thesis, I examine a variety of individual movement behaviours exhibited by skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacares) and bigeye (Thunnus obesus) tuna in the context of their vulnerability to fishers.

A number of simulation models of potential foraging by tuna in their environment were developed. Simulations used alternate habitat-utilisation and prey-field assumptions to test hypotheses regarding emergent behaviour in tuna, in particular examining vulnerability to habitat-specific fishing gears and fish aggregation devices (FADs). In conjunction, vertical movement data from bio-logging experiments on tuna were examined, initially using machine learning classification, but problems of autocorrelated data, lack of objectivity and low statistical power suggested that new analytical methods were needed. In light of this, a new approach to probabilistically classify multivariate biologging time-series, using existing methods of hidden Markov modelling, was developed.

The method was applied to vertical movement from 75 yellowfin and bigeye tuna, identifying two clear behavioural states and strong patterns of diurnal state-switching in both species. Evidence for deepening of deep state behaviour in bigeye was found, and high levels of behavioural variability between individuals seen, particularly in the hours following dawn.

The methods developed in this study are an improvement over previous approaches, being more objective and quantitative, and their suggested incorporation into standardisation of catch-per-unit-effort and catchability parameters is discussed. Specifically, they suggest that FADs may not act as ‘ecological traps’ as has previously been hypothesised, and that fluctuations in the prey field are the likely mechanism behind the high variability seen in vertical movement behaviours of tropical tuna.
Scutt Phillps, Joe
be2d2132-3a12-46c8-b609-05defc3f27e8
Scutt Phillps, Joe
be2d2132-3a12-46c8-b609-05defc3f27e8
Trueman, Clive
d00d3bd6-a47b-4d47-89ae-841c3d506205

Scutt Phillps, Joe (2014) On the movement behaviours of tropical tuna in modern commercial fisheries. University of Southampton, Ocean & Earth Science, Doctoral Thesis, 246pp.

Record type: Thesis (Doctoral)

Abstract

Exploitation of tropical tunas in the western and central Pacific Ocean constitutes an industry generating over US$5 billion annually. As concern for the sustainability of fishing operations grows, there is an increasing need to explore the potential effects that small-scale movement behaviours, typically ignored in stock assessment, may have on larger scale population dynamics. In this thesis, I examine a variety of individual movement behaviours exhibited by skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacares) and bigeye (Thunnus obesus) tuna in the context of their vulnerability to fishers.

A number of simulation models of potential foraging by tuna in their environment were developed. Simulations used alternate habitat-utilisation and prey-field assumptions to test hypotheses regarding emergent behaviour in tuna, in particular examining vulnerability to habitat-specific fishing gears and fish aggregation devices (FADs). In conjunction, vertical movement data from bio-logging experiments on tuna were examined, initially using machine learning classification, but problems of autocorrelated data, lack of objectivity and low statistical power suggested that new analytical methods were needed. In light of this, a new approach to probabilistically classify multivariate biologging time-series, using existing methods of hidden Markov modelling, was developed.

The method was applied to vertical movement from 75 yellowfin and bigeye tuna, identifying two clear behavioural states and strong patterns of diurnal state-switching in both species. Evidence for deepening of deep state behaviour in bigeye was found, and high levels of behavioural variability between individuals seen, particularly in the hours following dawn.

The methods developed in this study are an improvement over previous approaches, being more objective and quantitative, and their suggested incorporation into standardisation of catch-per-unit-effort and catchability parameters is discussed. Specifically, they suggest that FADs may not act as ‘ecological traps’ as has previously been hypothesised, and that fluctuations in the prey field are the likely mechanism behind the high variability seen in vertical movement behaviours of tropical tuna.

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More information

Published date: October 2014
Organisations: University of Southampton, Ocean and Earth Science

Identifiers

Local EPrints ID: 384578
URI: http://eprints.soton.ac.uk/id/eprint/384578
PURE UUID: 8044e342-218c-41cf-b7e1-975c4c868a99

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Date deposited: 08 Dec 2015 14:37
Last modified: 17 Jul 2017 20:03

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Contributors

Author: Joe Scutt Phillps
Thesis advisor: Clive Trueman

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