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The code of the long-term biomass cycles in the Barents Sea

Barents Sea capelin (Mallotus villosus), Norwegian spring-spawning herring (Cluea harengus), and Northeast Arctic cod (Gadus morhua) have been associated with large fluctuations of biomass growth. The cause of these large fluctuations has been poorly understood and led to problems in biomass managem...

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Bibliographic Details
Published in:ICES journal of marine science 2003, Vol.60 (6), p.1251-1264
Main Author: Yndestad, Harald
Format: Article
Language:English
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Summary:Barents Sea capelin (Mallotus villosus), Norwegian spring-spawning herring (Cluea harengus), and Northeast Arctic cod (Gadus morhua) have been associated with large fluctuations of biomass growth. The cause of these large fluctuations has been poorly understood and led to problems in biomass management. The identification of a deterministic cause would provide the possibility of forecasting future biomass fluctuations. In this investigation, the Kola Section sea temperature and the biomasses of capelin, herring, and cod have been analyzed by a wavelet transform to identify the source of the long-term cycles. The wavelet analysis shows that the Kola Section temperature has dominant cycles at the lunar-nodal tide cycles of 3×18.6=55.8, 18.5 and 18.6/3 = 6.2 years. The recruitment of Barents Sea capelin, Norwegian spring-spawning herring, and Northeast Arctic cod has adopted an optimal recruitment cycle close to the stationary 6.2 years Kola temperature cycle. Long-term biomass growth is correlated to the phase relation between the biomass eigen-frequency cycle and the Kola temperature cycles. The biomasses of capelin, herring and cod have long-term growth when the 6.2 and 18.6 years Kola temperature cycles are positive at the same time. There is a long-term biomass reduction when the temperature cycles are not positive at the same time, and a biomass collapse when the temperature cycles are negative at the same time. The deterministic property of the 18.6 years lunar-nodal tide provides a new way of long-term biomass forecasting over periods of 50–80 years or more.
ISSN:1054-3139
1095-9289
DOI:10.1016/S1054-3139(03)00152-8