Extracting environmental histories from sclerochronological structures — Recursive partitioning as a mean to explore multi-elemental composition of fish otolith
Résumé
During the last decades, ecologists have paid a great deal of attention to the proper techniques to track fish movement in the wild. In this context, otoliths have proved useful and were increasingly used in a wide range of species worldwide. Otolith material incorporates elements from the surrounding water in a layered manner that preserves the timing of deposition. Elemental composition along otolith centre-edge transects thus represent a permanent record of the growing habitats experienced by the fish throughout its entire lifetime. While the analysis of these elements is of primary importance in fishery management and population ecology, the traditional approaches mostly fail to capture the multivariate nature of structural change in time series data. In this paper, I propose a simple approach aiming at coping with the multi-elemental compositional otolith transect in a multi-scale quantitative manner. More specifically, the proposed recursive partitioning method tries to bias the chronological clustering process by accommodating some form of user-specified constraints based on both intra- and inter-groups characteristics. This allows researchers to focus on biologically relevant information (i.e. the one researcher look for and can interpret). The finding of this study may be considered from the more general perspective of the utility of chronological clustering study of multivariate time series. Chronological clustering based on recursive partition is easily interpretable and directly applicable to detection of hidden discontinuities in any multivariate time series. In a multi-proxy context, it also provides a powerful exploratory tool for assessing the relative importance of cross-correlated variables in structuring the environmental histories, as well as the congruency between variables. Ultimately, this approach demonstrates the actual interest in using advanced processing techniques to fully exploit the rich potential of individual biological archives, such as fish otoliths, to characterize individual life history. This appears as a promising new tool for ecologists wishing to extract environmental histories from dendro- and sclerochronological structures and would be a great help for practitioners working with chemical fingerprints. New functions for recursive partitioning using the R software environment are provided in a package and in the online Supplementary material together with a complete tutorial using full worked examples