A simulation approach to assessing bias in a fisheries self-sampling programme

The hierarchical structure and non-probabilistic sampling in fisher self-sampling programmes makes it difficult to evaluate biases in total catch estimates. While so, it is possible to evaluate bias in the reported component of catches, which can then be used to infer likely bias in total catches. W...

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Published in:ICES Journal of Marine Science
Main Authors: Clegg, Tom, Fuglebakk, Edvin, Ono, Kotaro, Vølstad, Jon Helge, Nedreaas, Kjell Harald
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/11250/2838166
https://doi.org/10.1093/icesjms/fsab242
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spelling ftimr:oai:imr.brage.unit.no:11250/2838166 2023-05-15T15:38:59+02:00 A simulation approach to assessing bias in a fisheries self-sampling programme Clegg, Tom Fuglebakk, Edvin Ono, Kotaro Vølstad, Jon Helge Nedreaas, Kjell Harald 2021 application/pdf https://hdl.handle.net/11250/2838166 https://doi.org/10.1093/icesjms/fsab242 eng eng ICES Journal of Marine Science. 2021, . urn:issn:1054-3139 https://hdl.handle.net/11250/2838166 https://doi.org/10.1093/icesjms/fsab242 cristin:1975984 12 ICES Journal of Marine Science Peer reviewed Journal article 2021 ftimr https://doi.org/10.1093/icesjms/fsab242 2022-01-26T23:38:54Z The hierarchical structure and non-probabilistic sampling in fisher self-sampling programmes makes it difficult to evaluate biases in total catch estimates. While so, it is possible to evaluate bias in the reported component of catches, which can then be used to infer likely bias in total catches. We assessed bias in the reported component of catches for 18 species in the Barents Sea trawl and longline fisheries by simulating 2000 realizations of the Norwegian Reference Fleet sampling programme using the mandatory catch reporting system, then for each realization we estimated fleet-wide catches using simple design-based estimators and quantified bias. We then inserted variations (e.g. simple random and systematic sampling) at different levels of the sampling design (sampling frame, vessel, and operation) to identify important factors and trends affecting bias in reported catches. We found that whilst current sampling procedures for fishing operations were not biased, non-probabilistic vessel sampling resulted in bias for some species. However, we concluded this was typically within the bounds of expected variation from probabilistic sampling. Our results highlight the risk of applying these simple estimators to all species. We recommend that future estimates of total catches consider alternative estimators and more conservative estimates of uncertainty where necessary. publishedVersion Article in Journal/Newspaper Barents Sea Institute for Marine Research: Brage IMR Barents Sea ICES Journal of Marine Science 79 1 76 87
institution Open Polar
collection Institute for Marine Research: Brage IMR
op_collection_id ftimr
language English
description The hierarchical structure and non-probabilistic sampling in fisher self-sampling programmes makes it difficult to evaluate biases in total catch estimates. While so, it is possible to evaluate bias in the reported component of catches, which can then be used to infer likely bias in total catches. We assessed bias in the reported component of catches for 18 species in the Barents Sea trawl and longline fisheries by simulating 2000 realizations of the Norwegian Reference Fleet sampling programme using the mandatory catch reporting system, then for each realization we estimated fleet-wide catches using simple design-based estimators and quantified bias. We then inserted variations (e.g. simple random and systematic sampling) at different levels of the sampling design (sampling frame, vessel, and operation) to identify important factors and trends affecting bias in reported catches. We found that whilst current sampling procedures for fishing operations were not biased, non-probabilistic vessel sampling resulted in bias for some species. However, we concluded this was typically within the bounds of expected variation from probabilistic sampling. Our results highlight the risk of applying these simple estimators to all species. We recommend that future estimates of total catches consider alternative estimators and more conservative estimates of uncertainty where necessary. publishedVersion
format Article in Journal/Newspaper
author Clegg, Tom
Fuglebakk, Edvin
Ono, Kotaro
Vølstad, Jon Helge
Nedreaas, Kjell Harald
spellingShingle Clegg, Tom
Fuglebakk, Edvin
Ono, Kotaro
Vølstad, Jon Helge
Nedreaas, Kjell Harald
A simulation approach to assessing bias in a fisheries self-sampling programme
author_facet Clegg, Tom
Fuglebakk, Edvin
Ono, Kotaro
Vølstad, Jon Helge
Nedreaas, Kjell Harald
author_sort Clegg, Tom
title A simulation approach to assessing bias in a fisheries self-sampling programme
title_short A simulation approach to assessing bias in a fisheries self-sampling programme
title_full A simulation approach to assessing bias in a fisheries self-sampling programme
title_fullStr A simulation approach to assessing bias in a fisheries self-sampling programme
title_full_unstemmed A simulation approach to assessing bias in a fisheries self-sampling programme
title_sort simulation approach to assessing bias in a fisheries self-sampling programme
publishDate 2021
url https://hdl.handle.net/11250/2838166
https://doi.org/10.1093/icesjms/fsab242
geographic Barents Sea
geographic_facet Barents Sea
genre Barents Sea
genre_facet Barents Sea
op_source 12
ICES Journal of Marine Science
op_relation ICES Journal of Marine Science. 2021, .
urn:issn:1054-3139
https://hdl.handle.net/11250/2838166
https://doi.org/10.1093/icesjms/fsab242
cristin:1975984
op_doi https://doi.org/10.1093/icesjms/fsab242
container_title ICES Journal of Marine Science
container_volume 79
container_issue 1
container_start_page 76
op_container_end_page 87
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