MEPS 216:213-222 (2001)  -  doi:10.3354/meps216213

Breaking down the climate effects on cod recruitment by principal component analysis and canonical correlation

Paolo Sirabella1, Alessandro Giuliani2, Alfredo Colosimo1,*, Joachim W. Dippner3

1University of Rome ŒLa Sapienza¹, Department of Biochemical Sciences - P.le A. Moro 5, 00185 Roma, Italy
2Istituto Superiore di Sanitá - TCE Laboratory, V.le Regina Elena, 199, 00161 Roma, Italy
3Institut für Ostseeforschung Warnemünde, Seestr. 15, 18119 Rostock, Germany
*Corresponding author. E-mail:

ABSTRACT: The pattern of temporal correlations between cod recruitment and sea temperature, in conjuction with the climate variability of atmospheric pressure anomalies (NAO index) was investigated by means of a combined use of principal component analysis (PCA) and canonical correlation analysis (CCA), using time series collected in the area surrounding the Kola peninsula (Barents Sea) and in the North Sea. The proposed data analysis strategy, namely to carry out a PCA of the temperature, cod recruitment and NAO time series followed by a CCA between the component spaces of all the possible data sets couples (recruitment vs temperature, recruitment vs NAO and NAO vs temperature), allowed us to sketch a general model of correlation between climate and cod recruitment dynamics. Two independent effects of temperature variability on cod recruitment emerged for the Kola region, pointing to the existence of at least 2 different mechanisms of comparable importance by which temperature may affect cod recruitment. In the North Sea the situation is somewhat simpler, and the data are compatible with only 1 major interaction mechanism. Moreover, the general effect of temperature on cod recruitment was opposite in the 2 regions: direct correlation for the Barents Sea, inverse correlation for the North Sea. This is probably due to the existence of an optimal temperature regime for cod recruitment lying in between the Œcold¹ Barents Sea and the Œwarm¹ North Sea.


KEY WORDS: Cod recruitment · Climate variability · Descriptive ecology · Multivariate analysis


Full text in pdf format