Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty

Despite their name, hierarchical stock–recruit meta-analyses are often parameterized in terms of steepness, which depends not only on the assumed stock–recruitment relationship but also on the recruit–spawner relationship. This parameterization requires assumptions about the reproductive potential o...

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Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Authors: Pulkkinen, Henni, Mäntyniemi, Samu
Other Authors: Chen, Yong
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2013
Subjects:
Online Access:http://dx.doi.org/10.1139/cjfas-2012-0268
http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2012-0268
http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2012-0268
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spelling crcansciencepubl:10.1139/cjfas-2012-0268 2023-12-17T10:27:27+01:00 Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty Pulkkinen, Henni Mäntyniemi, Samu Chen, Yong 2013 http://dx.doi.org/10.1139/cjfas-2012-0268 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2012-0268 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2012-0268 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Fisheries and Aquatic Sciences volume 70, issue 4, page 527-533 ISSN 0706-652X 1205-7533 Aquatic Science Ecology, Evolution, Behavior and Systematics journal-article 2013 crcansciencepubl https://doi.org/10.1139/cjfas-2012-0268 2023-11-19T13:39:15Z Despite their name, hierarchical stock–recruit meta-analyses are often parameterized in terms of steepness, which depends not only on the assumed stock–recruitment relationship but also on the recruit–spawner relationship. This parameterization requires assumptions about the reproductive potential of the recruit that are not desirable if the focus of the study is limited to the spawning–recruitment phase instead of the full life cycle. Thus, usage of steepness should be avoided in studies that aim to produce informative priors for the stock–recruit relationship for use in studies of other salmon stocks. An alternative key parameter for stock–recruit models is the maximum survival of eggs, which is the slope at the origin of the stock–recruitment curve when spawning stock size is defined in terms of the number of eggs. Furthermore, the current widely used practices in stock–recruit modeling could be improved by taking into account the stock-specific model uncertainty. We use the method of Bayesian model averaging to build a hierarchical stock–recruit model that allows stock-specific model structures with Beverton–Holt, Ricker, and hockey stick models as alternatives, all of which can be parameterized with the maximum survival of eggs. We illustrate our approach by analyzing nine previously published datasets for Atlantic salmon (Salmo salar). Article in Journal/Newspaper Atlantic salmon Salmo salar Canadian Science Publishing (via Crossref) Canadian Journal of Fisheries and Aquatic Sciences 70 4 527 533
institution Open Polar
collection Canadian Science Publishing (via Crossref)
op_collection_id crcansciencepubl
language English
topic Aquatic Science
Ecology, Evolution, Behavior and Systematics
spellingShingle Aquatic Science
Ecology, Evolution, Behavior and Systematics
Pulkkinen, Henni
Mäntyniemi, Samu
Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty
topic_facet Aquatic Science
Ecology, Evolution, Behavior and Systematics
description Despite their name, hierarchical stock–recruit meta-analyses are often parameterized in terms of steepness, which depends not only on the assumed stock–recruitment relationship but also on the recruit–spawner relationship. This parameterization requires assumptions about the reproductive potential of the recruit that are not desirable if the focus of the study is limited to the spawning–recruitment phase instead of the full life cycle. Thus, usage of steepness should be avoided in studies that aim to produce informative priors for the stock–recruit relationship for use in studies of other salmon stocks. An alternative key parameter for stock–recruit models is the maximum survival of eggs, which is the slope at the origin of the stock–recruitment curve when spawning stock size is defined in terms of the number of eggs. Furthermore, the current widely used practices in stock–recruit modeling could be improved by taking into account the stock-specific model uncertainty. We use the method of Bayesian model averaging to build a hierarchical stock–recruit model that allows stock-specific model structures with Beverton–Holt, Ricker, and hockey stick models as alternatives, all of which can be parameterized with the maximum survival of eggs. We illustrate our approach by analyzing nine previously published datasets for Atlantic salmon (Salmo salar).
author2 Chen, Yong
format Article in Journal/Newspaper
author Pulkkinen, Henni
Mäntyniemi, Samu
author_facet Pulkkinen, Henni
Mäntyniemi, Samu
author_sort Pulkkinen, Henni
title Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty
title_short Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty
title_full Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty
title_fullStr Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty
title_full_unstemmed Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty
title_sort maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty
publisher Canadian Science Publishing
publishDate 2013
url http://dx.doi.org/10.1139/cjfas-2012-0268
http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2012-0268
http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2012-0268
genre Atlantic salmon
Salmo salar
genre_facet Atlantic salmon
Salmo salar
op_source Canadian Journal of Fisheries and Aquatic Sciences
volume 70, issue 4, page 527-533
ISSN 0706-652X 1205-7533
op_rights http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
op_doi https://doi.org/10.1139/cjfas-2012-0268
container_title Canadian Journal of Fisheries and Aquatic Sciences
container_volume 70
container_issue 4
container_start_page 527
op_container_end_page 533
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