Understanding fleet behaviour to reduce uncertainty in tuna fisheries management
The behaviour of a fishing fleet is a critical, but all too often overlooked, uncertainty in the implementation of fisheries management. Unexpected responses by fishers to management controls, such as effort restrictions or spatial closures, can result in unintended and potentially undesirable outco...
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ndltd-bl.uk-oai-ethos.bl.uk-6566242016-08-04T03:44:09ZUnderstanding fleet behaviour to reduce uncertainty in tuna fisheries managementDavies, TimothyMilner-Gulland, E. J.; Mees, Chris2014The behaviour of a fishing fleet is a critical, but all too often overlooked, uncertainty in the implementation of fisheries management. Unexpected responses by fishers to management controls, such as effort restrictions or spatial closures, can result in unintended and potentially undesirable outcomes. Whilst this uncertainty can be reduced by anticipating the behavioural response of a fishing fleet, it is first necessary to understand the characteristics and drivers of fleet behaviour. The aim of this thesis was to address gaps in knowledge of the behaviour of offshore tuna fleets, using the Indian Ocean tropical tuna purse seine fishery as a case study example. I used statistical modelling to examine the factors that influence the spatial behaviour of the purse seine fleet at broad spatiotemporal scales. This analysis revealed consistency in the use of seasonal fishing grounds by the fleet, as well as a forcing influence of biophysical ocean conditions on the allocation of effort. These findings, which suggested strong inertia in fleet spatial behaviour, have important implications for predicting the response of the fleet to certain natural events or management measures (e.g. spatial closures). To better understand the impact of spatial closures on purse seine fleet dynamics, I used the statistical model of fleet behaviour to isolate the policy effect of two recent closures on fleet behaviour. By comparing the observed behaviour of the fleet against a model-generated counterfactual scenario I revealed, in the case of one of the closures, a policy effect that was inconsistent between years, and that the absence of fishing effort in the closed area was explained primarily by biophysical ocean conditions. These findings demonstrate the importance of using a counterfactual approach to evaluate spatial closures in open ocean systems where fleet behaviour is influenced by highly variable biophysical conditions. Fish aggregating devices (FADs) have become a dominant fishing practice in tuna purse seine fisheries worldwide, and I examined the influence of the use of FADs on purse seine fleet dynamics in the Indian Ocean. I reviewed historical catch trends and spatiotemporal patterns of fleet behaviour and linked this to the use of FADs. I also reviewed the existing management of FAD-fishing and speculated at the influence of possible future management measures on the behaviour of the fleet. Finally, I used a scenario planning approach to think about how the main drivers of purse seine fleet behaviour might change in the future, and how this might affect fleet dynamics. This analysis served to highlight aspects of purse seine fleet behaviour that should be a priority consideration of tuna fishery managers and policy makers. This thesis showed fleet behaviour to be a dynamic aspect of tuna fisheries management, and stressed the importance of anticipating the response of fleets to management measures in order to avoid unintentional outcomes. The understanding of purse seine fleet behaviour developed throughout this thesis provides a good basis for building the anticipation of fleet behaviour into existing management tools and processes.570Imperial College Londonhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.656624http://hdl.handle.net/10044/1/24762Electronic Thesis or Dissertation |
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570 Davies, Timothy Understanding fleet behaviour to reduce uncertainty in tuna fisheries management |
description |
The behaviour of a fishing fleet is a critical, but all too often overlooked, uncertainty in the implementation of fisheries management. Unexpected responses by fishers to management controls, such as effort restrictions or spatial closures, can result in unintended and potentially undesirable outcomes. Whilst this uncertainty can be reduced by anticipating the behavioural response of a fishing fleet, it is first necessary to understand the characteristics and drivers of fleet behaviour. The aim of this thesis was to address gaps in knowledge of the behaviour of offshore tuna fleets, using the Indian Ocean tropical tuna purse seine fishery as a case study example. I used statistical modelling to examine the factors that influence the spatial behaviour of the purse seine fleet at broad spatiotemporal scales. This analysis revealed consistency in the use of seasonal fishing grounds by the fleet, as well as a forcing influence of biophysical ocean conditions on the allocation of effort. These findings, which suggested strong inertia in fleet spatial behaviour, have important implications for predicting the response of the fleet to certain natural events or management measures (e.g. spatial closures). To better understand the impact of spatial closures on purse seine fleet dynamics, I used the statistical model of fleet behaviour to isolate the policy effect of two recent closures on fleet behaviour. By comparing the observed behaviour of the fleet against a model-generated counterfactual scenario I revealed, in the case of one of the closures, a policy effect that was inconsistent between years, and that the absence of fishing effort in the closed area was explained primarily by biophysical ocean conditions. These findings demonstrate the importance of using a counterfactual approach to evaluate spatial closures in open ocean systems where fleet behaviour is influenced by highly variable biophysical conditions. Fish aggregating devices (FADs) have become a dominant fishing practice in tuna purse seine fisheries worldwide, and I examined the influence of the use of FADs on purse seine fleet dynamics in the Indian Ocean. I reviewed historical catch trends and spatiotemporal patterns of fleet behaviour and linked this to the use of FADs. I also reviewed the existing management of FAD-fishing and speculated at the influence of possible future management measures on the behaviour of the fleet. Finally, I used a scenario planning approach to think about how the main drivers of purse seine fleet behaviour might change in the future, and how this might affect fleet dynamics. This analysis served to highlight aspects of purse seine fleet behaviour that should be a priority consideration of tuna fishery managers and policy makers. This thesis showed fleet behaviour to be a dynamic aspect of tuna fisheries management, and stressed the importance of anticipating the response of fleets to management measures in order to avoid unintentional outcomes. The understanding of purse seine fleet behaviour developed throughout this thesis provides a good basis for building the anticipation of fleet behaviour into existing management tools and processes. |
author2 |
Milner-Gulland, E. J.; Mees, Chris |
author_facet |
Milner-Gulland, E. J.; Mees, Chris Davies, Timothy |
author |
Davies, Timothy |
author_sort |
Davies, Timothy |
title |
Understanding fleet behaviour to reduce uncertainty in tuna fisheries management |
title_short |
Understanding fleet behaviour to reduce uncertainty in tuna fisheries management |
title_full |
Understanding fleet behaviour to reduce uncertainty in tuna fisheries management |
title_fullStr |
Understanding fleet behaviour to reduce uncertainty in tuna fisheries management |
title_full_unstemmed |
Understanding fleet behaviour to reduce uncertainty in tuna fisheries management |
title_sort |
understanding fleet behaviour to reduce uncertainty in tuna fisheries management |
publisher |
Imperial College London |
publishDate |
2014 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.656624 |
work_keys_str_mv |
AT daviestimothy understandingfleetbehaviourtoreduceuncertaintyintunafisheriesmanagement |
_version_ |
1718371003750416384 |