Institute of

SF Sea Fisheries

Project

The demography of fishes

Lead Institute SF Institute of Sea Fisheries

Otolith mit Markierungen für die Alterlesung

Further development of age determination methods for commercial fish species

Age composition data for fish stocks are essential input parameters for stock assessment. It is therefore necessary to permanently develop age determination methodology further.

Background and Objective

Age composition data for fish stocks are essential input parameters for stock assessment. The methodology of age determination is being permanently developed further in order to work efficiently and to reach consistent results. In this respect, state-of-the-art processing methods (e.g. fully automated otolith sectioning machines) and investigation methods (e.g. digital image analysis) are being employed.

In a PhD project, we test artificial intelligence (AI) methods for age determination.

Target Group

Fisheries science

Approach

The age of fish is being determined by counting growth zones in their ear stones (otoliths). Using state-of-the-art processing techniques and image analysis, annual rings (increments) become visible and are used for age determination.

Please see here for details on the utilization of AI methods for age reading.

Preliminary Results

Various publications, e.g. Stransky, C., Gudmundsdottir, S., Sigurdsson, T., Lemvig, S., Nedreaas, K., Saborido-Rey, F. (2005): Age determination and growth of Atlantic redfish (Sebastes marinus and S. mentella): bias and precision of age readers and otolith preparation methods. ICES J. Mar. Sci. 62: 655-670.

Unser Otolithen-Team!

Age composition data for fish stocks are essential input parameters for stock assessment. It is therefore necessary to permanently develop age determination methodology further.

Thünen-Contact

Dr. Christoph Stransky

Telephone

+49 471 94460 141

christoph.stransky@thuenen.de

SF Institute of Sea Fisheries

Involved Thünen-Partners

Duration

1.2008 - 12.2027

More Information

Project status: ongoing

Publications

0
Cayetano A, Stransky C, Birk A, Brey T (2024) Fish age reading using deep learning methods for object-detection and segmentation. ICES J Mar Sci: Online First, Feb 2024, DOI:10.1093/icesjms/fsae020
https://literatur.thuenen.de/digbib_extern/dn067737.pdf
1
Follesa MC, Hilvarsson A, Songer S, Aanestad Godiksen J, Beier U, Bekaert K, Berg F, Canha A, Carbonara P, Ni Chonchuir G, Coad Davies J, Denechaud C, Dubroca L, Farias I, Finnbogadottir G, Gault M, Gillespie-Mules R, Heimbrand Y, Krumme U, Ulleweit J, et al (2023) Working Group on Biological Parameters (WGBIOP; outputs from 2022 meeting). Copenhagen: ICES, 365 p, ICES Sci Rep 5(76), DOI:10.17895/ices.pub.23617833
https://literatur.thuenen.de/digbib_extern/dn066665.pdf
2
Carbonara P, Coad Davies J, Damme CJG van, Aanestad Godiksen J, Allegaert W, Beier U, Bekaert K, Canha A, Farias I, Follesa MC, Gault M, Gillespie-Mules R, Haase S, Hilvarsson A, Hüssy K, Korta M, Krüger-Johnsen M, Krumme U, Stransky C, Ulleweit J, et al (2020) Working Group on Biological Parameters (WGBIOP). Copenhagen: ICES, 150 p, ICES Sci Rep 2(117), DOI:10.17895/ices.pub.7651
3
Van der Sleen P, Stransky C, Morrongiello JR, Haslob H, Perharda M, Black BA (2018) Otolith increments in European plaice (Pleuronectes platessa) reveal temperature and density-dependent effects on growth. ICES J Mar Sci 75(5):1655-1663, DOI:10.1093/icesjms/fsy011
4
Stransky C, Gudmundsdóttir S, Sigurdsson T, Lemvig S, Nedreaas K, Saborido-Rey F (2005) Age determination and growth of Atlantic redfish (Sebastes marinus and S. mentella): bias and precision of age readers and otolith preparation methods. ICES J Mar Sci 62(4):655-670, doi:10.1016/j.icesjms.2005.01.018
5
Stransky C, Kanisch G, Krüger A, Purkl S (2005) Radiometric age validation of golden redfish (Sebastes marinus) and deep-sea redfish (S. mentella) in the Northeast Atlantic. Fish Res 74(1-3):186-197, DOI:10.1016/j.fishres.2005.03.003

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