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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Online Access: | https://doi.org/10.1016/j.fishres.2014.05.002 http://ecite.utas.edu.au/119527 |
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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 |
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Open Polar |
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eCite UTAS (University of Tasmania) |
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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 |
_version_ |
1766023678842109952 |