Subjective judgement in data subsetting: implications for CPUE standardisation and stock assessment of non-target chondrichthyans
J. M. Braccini A C D , M.-P. Etienne A B and S. J. D. Martell AA Fisheries Centre, The University of British Columbia, Vancouver, BC V6T1Z4, Canada.
B AgroParisTech, UMR MIA 518, 75231 Paris, France.
C Agri-Science Queensland, Queensland Department of Employment, Economic Development and Innovation, Ecoscience Precinct, GPO Box 46, Brisbane, Qld 4001, Australia.
D Corresponding author. Email: m.braccini@fisheries.ubc.ca
Marine and Freshwater Research 62(6) 734-743 https://doi.org/10.1071/MF10172
Submitted: 26 June 2010 Accepted: 10 November 2010 Published: 24 June 2011
Journal Compilation © CSIRO Publishing 2011 Open Access CC BY-NC-ND
Abstract
Standardisation of catch-per-effort (CPUE) data is an essential component for nearly all stock assessments. The first step in CPUE standardisation is to separate the comparable from the non-comparable catch and effort records and this is normally done based on subjective rules. In the present study, we used catch-and-effort data from the elephant fish (Callorhinchus milii) to illustrate the differences in CPUE when using expert judgement to define different ad hoc selection criteria used to subset these data. The data subsets were then used in the standardisation of CPUE and the stock assessment of elephant fish. The catch-and-effort subsets produced different patterns of precision and trends, each of which led to different estimates (and related uncertainty) of model parameters and management reference points. For most CPUE series, there was a very high probability that the elephant fish stock is overexploited and that overfishing is occurring. The estimates of total allowable catch (TAC) and the uncertainty around these estimates also varied considerably depending on the CPUE series used. Our study shows how sensitive TAC estimation is when there is high uncertainty in the definition of the fishing effort targeted at the species analysed.
Additional keywords: Bayesian, chimaeras, rays, sharks, subjectivity, uncertainty.
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