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Thirty years of fleet dynamics modelling using discrete-choice models: what have we learned?
Citation
Girardin, R and Hamon, KG and Pinnegar, J and Poos, JJ and Thebaud, O and Tidd, A and Vermard, Y and Marchal, P, Thirty years of fleet dynamics modelling using discrete-choice models: what have we learned?, Fish and Fisheries, 18, (4) pp. 638-655. ISSN 1467-2960 (2017) [Refereed Article]
Copyright Statement
Copyright 2016 John Wiley & Sons Ltd.
Abstract
Anticipating fisher behaviour is necessary for successful fisheries management. Of
the different concepts that have been developed to understand individual fisher
behaviour, random utility models (RUMs) have attracted considerable attention in
the past three decades, and more particularly so since the 2000s. This study aimed
at summarizing and analysing the information gathered from RUMs used during
the last three decades around the globe. A methodology has been developed to
standardize information across different studies and compare RUM results. The
studies selected focused on fishing effort allocation. Six types of fisher behaviour
drivers were considered: the presence of other vessels in the same fishing area, tradition,
expected revenue, species targeting, costs, and risk-taking. Analyses were
performed using three separate linear modelling approaches to assess the extent to
which these different drivers impacted fisher behaviour in three fleet types: fleets
fishing for demersal species using active gears, fleets fishing for demersal species
using passive gears and fleets fishing for pelagic species. Fishers are attracted by
higher expected revenue, tradition, species targeting and presence of others, but
avoid choices involving large costs. Results also suggest that fishers fishing for
demersal species using active gears are generally more influenced by past seasonal
(long-term) patterns than by the most recent (short-term) information. Finally, the
comparison of expected revenue with other fisher behaviour drivers highlights that
demersal fishing vessels are risk-averse and that tradition and species targeting
influence fisher decisions more than expected revenue.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | fisher behaviour, meta-analysis, random utility model |
| Research Division: | Agricultural, Veterinary and Food Sciences |
| Research Group: | Fisheries sciences |
| Research Field: | Fisheries management |
| Objective Division: | Environmental Management |
| Objective Group: | Terrestrial systems and management |
| Objective Field: | Assessment and management of terrestrial ecosystems |
| UTAS Author: | Tidd, A (Dr Alexander Tidd) |
| ID Code: | 116217 |
| Year Published: | 2017 |
| Web of Science® Times Cited: | 43 |
| Deposited By: | Ecology and Biodiversity |
| Deposited On: | 2017-05-03 |
| Last Modified: | 2018-08-15 |
| Downloads: | 0 |
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