Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge
Annual run size and timing of Atlantic salmon smolt migration was estimated using Bayesian model framework and data from six years of a video monitoring survey. The model has a modular structure. It separates sub-processes of departing, traveling and observing, of which the first two together define...
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ftunivtoronto:oai:localhost:1807/98724 2023-05-15T15:31:34+02:00 Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge Pulkkinen, Henni Orell, Panu Erkinaro, Jaakko Mäntyniemi, Samu 2019-07-28 http://hdl.handle.net/1807/98724 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0352 unknown NRC Research Press (a division of Canadian Science Publishing) 0706-652X http://hdl.handle.net/1807/98724 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0352 Article 2019 ftunivtoronto 2020-06-17T12:29:02Z Annual run size and timing of Atlantic salmon smolt migration was estimated using Bayesian model framework and data from six years of a video monitoring survey. The model has a modular structure. It separates sub-processes of departing, traveling and observing, of which the first two together define the arrival distribution. The sub-processes utilize biological background and expert knowledge about the migratory behavior of smolts and about the probability to observe them from the video footage under varying environmental conditions. Daily mean temperature and discharge were used as environmental covariates. The model framework does not require assuming a simple distributional shape for the arrival dynamics and thus also allows for multimodal arrival distributions. Results indicate that 20 % - 43% of smolts passed the Utsjoki monitoring site unobserved during the years of study. Predictive studies were made to estimate daily run size in cases with missing counts either at the beginning or in the middle of the run, indicating good predictive performance. The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author. Article in Journal/Newspaper Atlantic salmon Utsjoki University of Toronto: Research Repository T-Space |
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University of Toronto: Research Repository T-Space |
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ftunivtoronto |
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description |
Annual run size and timing of Atlantic salmon smolt migration was estimated using Bayesian model framework and data from six years of a video monitoring survey. The model has a modular structure. It separates sub-processes of departing, traveling and observing, of which the first two together define the arrival distribution. The sub-processes utilize biological background and expert knowledge about the migratory behavior of smolts and about the probability to observe them from the video footage under varying environmental conditions. Daily mean temperature and discharge were used as environmental covariates. The model framework does not require assuming a simple distributional shape for the arrival dynamics and thus also allows for multimodal arrival distributions. Results indicate that 20 % - 43% of smolts passed the Utsjoki monitoring site unobserved during the years of study. Predictive studies were made to estimate daily run size in cases with missing counts either at the beginning or in the middle of the run, indicating good predictive performance. The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author. |
format |
Article in Journal/Newspaper |
author |
Pulkkinen, Henni Orell, Panu Erkinaro, Jaakko Mäntyniemi, Samu |
spellingShingle |
Pulkkinen, Henni Orell, Panu Erkinaro, Jaakko Mäntyniemi, Samu Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge |
author_facet |
Pulkkinen, Henni Orell, Panu Erkinaro, Jaakko Mäntyniemi, Samu |
author_sort |
Pulkkinen, Henni |
title |
Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge |
title_short |
Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge |
title_full |
Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge |
title_fullStr |
Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge |
title_full_unstemmed |
Bayesian arrival model for Atlantic salmon smolt counts powered by environmental covariates and expert knowledge |
title_sort |
bayesian arrival model for atlantic salmon smolt counts powered by environmental covariates and expert knowledge |
publisher |
NRC Research Press (a division of Canadian Science Publishing) |
publishDate |
2019 |
url |
http://hdl.handle.net/1807/98724 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0352 |
genre |
Atlantic salmon Utsjoki |
genre_facet |
Atlantic salmon Utsjoki |
op_relation |
0706-652X http://hdl.handle.net/1807/98724 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0352 |
_version_ |
1766362086825263104 |