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An interesting phaenomenon is observed in zooplankton, namely, the accumulation of lithium by some crustacean species, mainly belonging to the Calanus taxon. The relation of atomic composition and changes in molecular structure of tissues is a key to reveal the mechanism of such a behavior. Thus we combined LIBS and Raman studies of zooplankton organisms. A 20 mJ 266 nm Nd:YAG laser was used in LIBS, and Raman spectra were recorded with a 780 nm red laser. Signals were collected separately from dark, light, and medium-coloured spots on the surface of pelletized samples (29 samples of zooplankton, 14 of them from the Calanus taxon). The obtained data were subjected to different matrix decomposition techniques, viz., common principal component analysis (PCA), non-negative matrix factorization (NMF), and common components and specific weights analysis (ComDim) in its PCA-based realization [1]. Bulk composition, obtained by ICP-AES and ICP-MS after digestion, was also available. For PCA and NMF, the influence of data fusion on the results of decomposition was studied. When applied either to LIBS or Raman data separately, the both techniques allowed classification of samples in terms of Li enrichment. Lithium in Calanus appears to be associated with carotenoid compounds and amino acids. However, there are more components in LIBS than in Raman spectra, which causes an extra component to appear in the Raman domain when the spectra are simply concatenated. This fact promotes the use of ComDim for data fusion which realizes weighting of data of different origin to provide meaningful contribution of all sources. Besides the interrelation of Li with carotenoids and amino acids, ComDim analysis revealed its link to potassium. Interestingly, this holds true only for dark and medium-coloured spots, but not for light spots. There is always a part of Li signal not separated from other elements. This might indicate the existence of different mechanisms of Li uptake by crustaceans. ICP-AES and ICP-MS elemental analyses of zooplankton samples were funded by the Russian Science Foundation (research project No. 18-77-00064). The authors are grateful to Á. Bélteki, A. Kéri, P. Janovszky, D. Palásti, Dr. K. Fintor (University of Szeged) and Dr. R. Rajkó (Universtity of Pécs, Hungary) for their valuable assistance. References [1] The MATLAB code for performing ComDim was kindly provided by Prof. D.N. Rutledge (AgroParisTech, France).