Spatial age-length key modelling using continuation ratio logits

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Spatial age-length key modelling using continuation ratio logits. / Berg, Casper W.; Kristensen, Kasper.

In: Fisheries Research, Vol. 129-130, 2012, p. 119-126.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Author

Berg, Casper W.; Kristensen, Kasper / Spatial age-length key modelling using continuation ratio logits.

In: Fisheries Research, Vol. 129-130, 2012, p. 119-126.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

Bibtex

@article{9c29206c02324fdf9ab783185a678f38,
title = "Spatial age-length key modelling using continuation ratio logits",
keywords = "Age length key comparison, Continuation ratio logits, Generalized Additive Models",
publisher = "Elsevier BV",
author = "Berg, {Casper W.} and Kasper Kristensen",
year = "2012",
doi = "10.1016/j.fishres.2012.06.016",
volume = "129-130",
pages = "119--126",
journal = "Fisheries Research",
issn = "0165-7836",

}

RIS

TY - JOUR

T1 - Spatial age-length key modelling using continuation ratio logits

A1 - Berg,Casper W.

A1 - Kristensen,Kasper

AU - Berg,Casper W.

AU - Kristensen,Kasper

PB - Elsevier BV

PY - 2012

Y1 - 2012

N2 - Many fish stock assessments are based on numbers at age from research sampling programmes and samples from commercial catches. However, only a small fraction of the catch is typically analyzed for age as this is a costly and time-consuming process. Larger samples of the length distribution and a so-called age-length key (ALK) is then used to obtain the age distribution. Regional differences in ALKs are not uncommon, but stratification is often problematic due to a small number of samples. Here, we combine generalized additive modelling with continuation ratio logits to model the probability of age given length and spatial coordinates to overcome these issues. The method is applied to data gathered on North Sea haddock (Melanogrammus aeglefinus), cod (Gadus morhua), whiting (Merlangius merlangus) and herring (Clupea harengus) and its implications for a simple age-based survey index of abundance are examined. The spatial varying ALK outperforms simpler approaches with respect to AIC and BIC, and the survey indices created using the spatial varying ALK displays better internal and external consistency indicating improved precision.

AB - Many fish stock assessments are based on numbers at age from research sampling programmes and samples from commercial catches. However, only a small fraction of the catch is typically analyzed for age as this is a costly and time-consuming process. Larger samples of the length distribution and a so-called age-length key (ALK) is then used to obtain the age distribution. Regional differences in ALKs are not uncommon, but stratification is often problematic due to a small number of samples. Here, we combine generalized additive modelling with continuation ratio logits to model the probability of age given length and spatial coordinates to overcome these issues. The method is applied to data gathered on North Sea haddock (Melanogrammus aeglefinus), cod (Gadus morhua), whiting (Merlangius merlangus) and herring (Clupea harengus) and its implications for a simple age-based survey index of abundance are examined. The spatial varying ALK outperforms simpler approaches with respect to AIC and BIC, and the survey indices created using the spatial varying ALK displays better internal and external consistency indicating improved precision.

KW - Age length key comparison

KW - Continuation ratio logits

KW - Generalized Additive Models

U2 - 10.1016/j.fishres.2012.06.016

DO - 10.1016/j.fishres.2012.06.016

JO - Fisheries Research

JF - Fisheries Research

SN - 0165-7836

VL - 129-130

SP - 119

EP - 126

ER -