Validation of a hidden Markov model for the geolocation of Atlantic cod

Models developed to geolocate individual fish from data recorded by electronic tags often require significant modification to be applied to new regions, species, or tag types due to variability in oceanographic conditions, fish behavior, and data resolution. We developed a model for geolocating Atla...

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Main Authors: Liu, Chang, Cowles, Geoffrey W., Zemeckis, Douglas R., Cadrin, Steven X., Dean, Micah J.
Format: Article in Journal/Newspaper
Language:unknown
Published: NRC Research Press (a division of Canadian Science Publishing) 2016
Subjects:
Online Access:http://hdl.handle.net/1807/78476
http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0376
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spelling ftunivtoronto:oai:localhost:1807/78476 2023-05-15T15:27:18+02:00 Validation of a hidden Markov model for the geolocation of Atlantic cod Liu, Chang Cowles, Geoffrey W. Zemeckis, Douglas R. Cadrin, Steven X. Dean, Micah J. 2016-12-22 http://hdl.handle.net/1807/78476 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0376 unknown NRC Research Press (a division of Canadian Science Publishing) 0706-652X http://hdl.handle.net/1807/78476 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0376 Article 2016 ftunivtoronto 2020-06-17T12:06:05Z Models developed to geolocate individual fish from data recorded by electronic tags often require significant modification to be applied to new regions, species, or tag types due to variability in oceanographic conditions, fish behavior, and data resolution. We developed a model for geolocating Atlantic cod off New England that builds upon an existing hidden Markov model (HMM) framework and addresses region- and species-specific challenges. The HMM framework contains a likelihood model which compares tag-recorded environmental data (depth, temperature, tidal characteristics) with those derived from an oceanographic model and a behavior model which constrains the horizontal movement of the fish. Validation experiments were performed on stationary tags, double-electronic-tagged fish (archival and acoustic tags), and simulated tracks. Known data, including fish locations and activity metrics, showed good agreement with those estimated by the modified approach, and improvements in performance of the modified method over the original. The modified geolocation approach will be applicable to additional species and regions to obtain valuable movement information that is not typically available for demersal fishes. 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 cod University of Toronto: Research Repository T-Space
institution Open Polar
collection University of Toronto: Research Repository T-Space
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language unknown
description Models developed to geolocate individual fish from data recorded by electronic tags often require significant modification to be applied to new regions, species, or tag types due to variability in oceanographic conditions, fish behavior, and data resolution. We developed a model for geolocating Atlantic cod off New England that builds upon an existing hidden Markov model (HMM) framework and addresses region- and species-specific challenges. The HMM framework contains a likelihood model which compares tag-recorded environmental data (depth, temperature, tidal characteristics) with those derived from an oceanographic model and a behavior model which constrains the horizontal movement of the fish. Validation experiments were performed on stationary tags, double-electronic-tagged fish (archival and acoustic tags), and simulated tracks. Known data, including fish locations and activity metrics, showed good agreement with those estimated by the modified approach, and improvements in performance of the modified method over the original. The modified geolocation approach will be applicable to additional species and regions to obtain valuable movement information that is not typically available for demersal fishes. 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 Liu, Chang
Cowles, Geoffrey W.
Zemeckis, Douglas R.
Cadrin, Steven X.
Dean, Micah J.
spellingShingle Liu, Chang
Cowles, Geoffrey W.
Zemeckis, Douglas R.
Cadrin, Steven X.
Dean, Micah J.
Validation of a hidden Markov model for the geolocation of Atlantic cod
author_facet Liu, Chang
Cowles, Geoffrey W.
Zemeckis, Douglas R.
Cadrin, Steven X.
Dean, Micah J.
author_sort Liu, Chang
title Validation of a hidden Markov model for the geolocation of Atlantic cod
title_short Validation of a hidden Markov model for the geolocation of Atlantic cod
title_full Validation of a hidden Markov model for the geolocation of Atlantic cod
title_fullStr Validation of a hidden Markov model for the geolocation of Atlantic cod
title_full_unstemmed Validation of a hidden Markov model for the geolocation of Atlantic cod
title_sort validation of a hidden markov model for the geolocation of atlantic cod
publisher NRC Research Press (a division of Canadian Science Publishing)
publishDate 2016
url http://hdl.handle.net/1807/78476
http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0376
genre atlantic cod
genre_facet atlantic cod
op_relation 0706-652X
http://hdl.handle.net/1807/78476
http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0376
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