Bayesian mark–recapture estimation with an application to a salmonid smolt population

We developed a Bayesian probability model for mark–recapture data. Three alternative versions of the model were applied to two sets of data on the abundance of migrating Atlantic salmon (Salmo salar) smolt populations, and the results were then compared with those of two widely used maximum likeliho...

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Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Authors: Mäntyniemi, Samu, Romakkaniemi, Atso
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2002
Subjects:
Online Access:http://dx.doi.org/10.1139/f02-146
http://www.nrcresearchpress.com/doi/pdf/10.1139/f02-146
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spelling crcansciencepubl:10.1139/f02-146 2023-12-17T10:27:25+01:00 Bayesian mark–recapture estimation with an application to a salmonid smolt population Mäntyniemi, Samu Romakkaniemi, Atso 2002 http://dx.doi.org/10.1139/f02-146 http://www.nrcresearchpress.com/doi/pdf/10.1139/f02-146 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Fisheries and Aquatic Sciences volume 59, issue 11, page 1748-1758 ISSN 0706-652X 1205-7533 Aquatic Science Ecology, Evolution, Behavior and Systematics journal-article 2002 crcansciencepubl https://doi.org/10.1139/f02-146 2023-11-19T13:39:05Z We developed a Bayesian probability model for mark–recapture data. Three alternative versions of the model were applied to two sets of data on the abundance of migrating Atlantic salmon (Salmo salar) smolt populations, and the results were then compared with those of two widely used maximum likelihood models (Petersen method and a model using stratified data). Our model follows the basic principles of stochastic models presented for stratified data. In contrast to the earlier models, our model can deal with sparse data. Moreover, even weak dependencies between the studied parameters and the possible factors affecting them can be used to improve the plausibility of the estimates. The assumptions behind our approach are more realistic than those of earlier models, taking into account such factors as overdispersion, which is expected to be present in the mark–recapture data of salmon smolts because of their schooling behavior. Our examples also show that assumptions about the model structure can have a substantial impact on the resulting inferences on the size of the smolt run, especially in terms of the precision of the estimate. Article in Journal/Newspaper Atlantic salmon Salmo salar Canadian Science Publishing (via Crossref) Petersen ENVELOPE(-101.250,-101.250,-71.917,-71.917) Canadian Journal of Fisheries and Aquatic Sciences 59 11 1748 1758
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
Mäntyniemi, Samu
Romakkaniemi, Atso
Bayesian mark–recapture estimation with an application to a salmonid smolt population
topic_facet Aquatic Science
Ecology, Evolution, Behavior and Systematics
description We developed a Bayesian probability model for mark–recapture data. Three alternative versions of the model were applied to two sets of data on the abundance of migrating Atlantic salmon (Salmo salar) smolt populations, and the results were then compared with those of two widely used maximum likelihood models (Petersen method and a model using stratified data). Our model follows the basic principles of stochastic models presented for stratified data. In contrast to the earlier models, our model can deal with sparse data. Moreover, even weak dependencies between the studied parameters and the possible factors affecting them can be used to improve the plausibility of the estimates. The assumptions behind our approach are more realistic than those of earlier models, taking into account such factors as overdispersion, which is expected to be present in the mark–recapture data of salmon smolts because of their schooling behavior. Our examples also show that assumptions about the model structure can have a substantial impact on the resulting inferences on the size of the smolt run, especially in terms of the precision of the estimate.
format Article in Journal/Newspaper
author Mäntyniemi, Samu
Romakkaniemi, Atso
author_facet Mäntyniemi, Samu
Romakkaniemi, Atso
author_sort Mäntyniemi, Samu
title Bayesian mark–recapture estimation with an application to a salmonid smolt population
title_short Bayesian mark–recapture estimation with an application to a salmonid smolt population
title_full Bayesian mark–recapture estimation with an application to a salmonid smolt population
title_fullStr Bayesian mark–recapture estimation with an application to a salmonid smolt population
title_full_unstemmed Bayesian mark–recapture estimation with an application to a salmonid smolt population
title_sort bayesian mark–recapture estimation with an application to a salmonid smolt population
publisher Canadian Science Publishing
publishDate 2002
url http://dx.doi.org/10.1139/f02-146
http://www.nrcresearchpress.com/doi/pdf/10.1139/f02-146
long_lat ENVELOPE(-101.250,-101.250,-71.917,-71.917)
geographic Petersen
geographic_facet Petersen
genre Atlantic salmon
Salmo salar
genre_facet Atlantic salmon
Salmo salar
op_source Canadian Journal of Fisheries and Aquatic Sciences
volume 59, issue 11, page 1748-1758
ISSN 0706-652X 1205-7533
op_rights http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
op_doi https://doi.org/10.1139/f02-146
container_title Canadian Journal of Fisheries and Aquatic Sciences
container_volume 59
container_issue 11
container_start_page 1748
op_container_end_page 1758
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