Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty
The use of archival tags on fish gives information of individual behaviour with an unprecedented high resolution in time. A central problem in the analysis of data from retrieved tags is the geolocation, namely the infererence of movements of the fish by comparing the data from the tags with environ...
Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
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Online Access: | http://dx.doi.org/10.1139/f07-037 http://www.nrcresearchpress.com/doi/pdf/10.1139/f07-037 |
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crcansciencepubl:10.1139/f07-037 2024-04-28T08:12:56+00:00 Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty Andersen, K H Nielsen, A Thygesen, U H Hinrichsen, H -H Neuenfeldt, S 2007 http://dx.doi.org/10.1139/f07-037 http://www.nrcresearchpress.com/doi/pdf/10.1139/f07-037 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Fisheries and Aquatic Sciences volume 64, issue 4, page 618-627 ISSN 0706-652X 1205-7533 Aquatic Science Ecology, Evolution, Behavior and Systematics journal-article 2007 crcansciencepubl https://doi.org/10.1139/f07-037 2024-04-02T06:55:55Z The use of archival tags on fish gives information of individual behaviour with an unprecedented high resolution in time. A central problem in the analysis of data from retrieved tags is the geolocation, namely the infererence of movements of the fish by comparing the data from the tags with environmental observations like temperature, tide, day length, etc. The result is usually represented as a track; however, the spatial and temporal variability in the precision is often substantial. In this article, the particle filter is applied to geolocate Atlantic cod (Gadus morhua) in the Baltic Sea, leading to a representation of the results as probability distributions for each time step, thus giving an explicit representation of uncertainty. Furthermore, the method is used to estimate the magnitude of the error in the measurements by the tags and the swimming velocity of the fish. The average swimming velocity during a day was estimated to be around 0.20 m·s –1 for fish of ~60 cm length. The method is general and the presentation is formulated to facilitate implementation for different systems where other quantities are observed. Article in Journal/Newspaper atlantic cod Gadus morhua Canadian Science Publishing Canadian Journal of Fisheries and Aquatic Sciences 64 4 618 627 |
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Open Polar |
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Canadian Science Publishing |
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crcansciencepubl |
language |
English |
topic |
Aquatic Science Ecology, Evolution, Behavior and Systematics |
spellingShingle |
Aquatic Science Ecology, Evolution, Behavior and Systematics Andersen, K H Nielsen, A Thygesen, U H Hinrichsen, H -H Neuenfeldt, S Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty |
topic_facet |
Aquatic Science Ecology, Evolution, Behavior and Systematics |
description |
The use of archival tags on fish gives information of individual behaviour with an unprecedented high resolution in time. A central problem in the analysis of data from retrieved tags is the geolocation, namely the infererence of movements of the fish by comparing the data from the tags with environmental observations like temperature, tide, day length, etc. The result is usually represented as a track; however, the spatial and temporal variability in the precision is often substantial. In this article, the particle filter is applied to geolocate Atlantic cod (Gadus morhua) in the Baltic Sea, leading to a representation of the results as probability distributions for each time step, thus giving an explicit representation of uncertainty. Furthermore, the method is used to estimate the magnitude of the error in the measurements by the tags and the swimming velocity of the fish. The average swimming velocity during a day was estimated to be around 0.20 m·s –1 for fish of ~60 cm length. The method is general and the presentation is formulated to facilitate implementation for different systems where other quantities are observed. |
format |
Article in Journal/Newspaper |
author |
Andersen, K H Nielsen, A Thygesen, U H Hinrichsen, H -H Neuenfeldt, S |
author_facet |
Andersen, K H Nielsen, A Thygesen, U H Hinrichsen, H -H Neuenfeldt, S |
author_sort |
Andersen, K H |
title |
Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty |
title_short |
Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty |
title_full |
Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty |
title_fullStr |
Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty |
title_full_unstemmed |
Using the particle filter to geolocate Atlantic cod ( Gadus morhua ) in the Baltic Sea, with special emphasis on determining uncertainty |
title_sort |
using the particle filter to geolocate atlantic cod ( gadus morhua ) in the baltic sea, with special emphasis on determining uncertainty |
publisher |
Canadian Science Publishing |
publishDate |
2007 |
url |
http://dx.doi.org/10.1139/f07-037 http://www.nrcresearchpress.com/doi/pdf/10.1139/f07-037 |
genre |
atlantic cod Gadus morhua |
genre_facet |
atlantic cod Gadus morhua |
op_source |
Canadian Journal of Fisheries and Aquatic Sciences volume 64, issue 4, page 618-627 ISSN 0706-652X 1205-7533 |
op_rights |
http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining |
op_doi |
https://doi.org/10.1139/f07-037 |
container_title |
Canadian Journal of Fisheries and Aquatic Sciences |
container_volume |
64 |
container_issue |
4 |
container_start_page |
618 |
op_container_end_page |
627 |
_version_ |
1797579642657308672 |