A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments

Length frequency data (LFD) are an important input to integrated stock assessments, and statistical tests for variables that significantly influence the length distribution of fish can assist in the definition of effort strata, typically denoted as fisheries or sub-fisheries, in order to account for...

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Published in:Fisheries Research
Main Authors: Candy, S, Ziegler, P, Welsford, D
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier Science Bv 2014
Subjects:
Online Access:https://doi.org/10.1016/j.fishres.2014.05.002
http://ecite.utas.edu.au/119527
id ftunivtasecite:oai:ecite.utas.edu.au:119527
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spelling ftunivtasecite:oai:ecite.utas.edu.au:119527 2023-05-15T16:33:56+02:00 A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments Candy, S Ziegler, P Welsford, D 2014 https://doi.org/10.1016/j.fishres.2014.05.002 http://ecite.utas.edu.au/119527 en eng Elsevier Science Bv http://dx.doi.org/10.1016/j.fishres.2014.05.002 Candy, S and Ziegler, P and Welsford, D, A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments, Fisheries Research, 159 pp. 34-44. ISSN 0165-7836 (2014) [Refereed Article] http://ecite.utas.edu.au/119527 Agricultural and Veterinary Sciences Fisheries Sciences Aquatic Ecosystem Studies and Stock Assessment Refereed Article PeerReviewed 2014 ftunivtasecite https://doi.org/10.1016/j.fishres.2014.05.002 2019-12-13T22:18:42Z Length frequency data (LFD) are an important input to integrated stock assessments, and statistical tests for variables that significantly influence the length distribution of fish can assist in the definition of effort strata, typically denoted as fisheries or sub-fisheries, in order to account for important systematic differences due to availability and/or gear-specific selectivity of size classes. Here, a nonparametric model of the probability density function of lengths is described which, instead of fitting to LFD directly, is fitted to the set of length quantiles for a pre-determined set of corresponding probabilities p (in this instance 0.05, 0.1-0.9 in 0.1 increments, and 0.95). These length quantile data (LQD) can be constructed with individual hauls as sampling units or after pooling hauls to sampling units defined by combinations of covariates such as gear type, spatial block, depth strata, or the sex of sampled fish. The length quantiles are modelled as a Gaussian response variable using a Generalised Additive Mixed Model (GAMM) with smoothing splines fitted for each combination of the covariates (i.e. gear type, depth strata and sex). Graphical presentation of the fitted splines along with standard error of difference bounds were used to investigate where differences were significant in order to assist in the optimal definition of sub-fisheries. The model has the advantage of greater generality and sensitivity in detecting differences compared to modelling a single quantile such as the median. In addition, fitting splines allows flexible and parsimonious modelling of length distributions of any shape. The model is demonstrated using LQD from commercial fishing for Patagonian toothfish at Heard Island. Article in Journal/Newspaper Heard Island Patagonian Toothfish eCite UTAS (University of Tasmania) Heard Island Fisheries Research 159 34 44
institution Open Polar
collection eCite UTAS (University of Tasmania)
op_collection_id ftunivtasecite
language English
topic Agricultural and Veterinary Sciences
Fisheries Sciences
Aquatic Ecosystem Studies and Stock Assessment
spellingShingle Agricultural and Veterinary Sciences
Fisheries Sciences
Aquatic Ecosystem Studies and Stock Assessment
Candy, S
Ziegler, P
Welsford, D
A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments
topic_facet Agricultural and Veterinary Sciences
Fisheries Sciences
Aquatic Ecosystem Studies and Stock Assessment
description Length frequency data (LFD) are an important input to integrated stock assessments, and statistical tests for variables that significantly influence the length distribution of fish can assist in the definition of effort strata, typically denoted as fisheries or sub-fisheries, in order to account for important systematic differences due to availability and/or gear-specific selectivity of size classes. Here, a nonparametric model of the probability density function of lengths is described which, instead of fitting to LFD directly, is fitted to the set of length quantiles for a pre-determined set of corresponding probabilities p (in this instance 0.05, 0.1-0.9 in 0.1 increments, and 0.95). These length quantile data (LQD) can be constructed with individual hauls as sampling units or after pooling hauls to sampling units defined by combinations of covariates such as gear type, spatial block, depth strata, or the sex of sampled fish. The length quantiles are modelled as a Gaussian response variable using a Generalised Additive Mixed Model (GAMM) with smoothing splines fitted for each combination of the covariates (i.e. gear type, depth strata and sex). Graphical presentation of the fitted splines along with standard error of difference bounds were used to investigate where differences were significant in order to assist in the optimal definition of sub-fisheries. The model has the advantage of greater generality and sensitivity in detecting differences compared to modelling a single quantile such as the median. In addition, fitting splines allows flexible and parsimonious modelling of length distributions of any shape. The model is demonstrated using LQD from commercial fishing for Patagonian toothfish at Heard Island.
format Article in Journal/Newspaper
author Candy, S
Ziegler, P
Welsford, D
author_facet Candy, S
Ziegler, P
Welsford, D
author_sort Candy, S
title A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments
title_short A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments
title_full A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments
title_fullStr A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments
title_full_unstemmed A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments
title_sort nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments
publisher Elsevier Science Bv
publishDate 2014
url https://doi.org/10.1016/j.fishres.2014.05.002
http://ecite.utas.edu.au/119527
geographic Heard Island
geographic_facet Heard Island
genre Heard Island
Patagonian Toothfish
genre_facet Heard Island
Patagonian Toothfish
op_relation http://dx.doi.org/10.1016/j.fishres.2014.05.002
Candy, S and Ziegler, P and Welsford, D, A nonparametric model of empirical length distributions to inform stratification of fishing effort for integrated assessments, Fisheries Research, 159 pp. 34-44. ISSN 0165-7836 (2014) [Refereed Article]
http://ecite.utas.edu.au/119527
op_doi https://doi.org/10.1016/j.fishres.2014.05.002
container_title Fisheries Research
container_volume 159
container_start_page 34
op_container_end_page 44
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