Abstract

Long time series of reliable individual growth estimates are crucial for understanding the status of a fish stock and deciding upon appropriate management. Tagging data provide valuable information about fish growth, and are especially useful when age-based growth estimates and stock assessments are compromised by age-determination uncertainties. However, in the literature there is a lack of studies assessing possible changes in growth over time using tagging data. Here, data from tagging experiments performed in the Baltic Sea between 1971 and 2019 were added to those previously analysed for 1955-1970 to build the most extensive tagging dataset available for Eastern Baltic cod (Gadus morhua, Gadidae), a threatened stock with severe age-determination problems. Two length-based methods, the GROTAG model (based on the von Bertalanffy growth function) and a Generalized Additive Model, were used to assess for the first time the potential long-term changes in cod growth using age-independent data. Both methods showed strong changes in growth with an increase until the end of the 1980s (8.6-10.6 cm/year for a 40 cm cod depending on the model) followed by a sharp decline. This study also revealed that the current growth of cod is the lowest observed in the past 7 decades (4.3-5.1 cm/year for a 40 cm cod depending on the model), indicating very low productivity. This study provides the first example of the use of tagging data to estimate multidecadal changes in growth rates in wild fish. This methodology can also be applied to other species, especially in those cases where severe age-determination problems exist.

Keywords

Baltic cod; generalized additive model; growth modelling; mark‐recapture; time series; von Bertalanffy growth function

Published in

Fish and Fisheries
2021, volume: 22, number: 2, pages: 413-427

Authors' information