Abstract
Chemical reactions in aqueous geochemical systems are driven by nonequilibrium conditions, and their dynamics can be deduced through the distributional analysis (identification of probability laws) of complex compositional indices. In this perspective, compositional data analysis offers the possibility to investigate the behavior of the composition as a whole instead of isolated chemical species, with the awareness that multispecies systems are characterized by the simultaneous interactions among all their parts. We addressed this problem using D − 1 isometric log-ratio coordinates describing the D compositional dataset of the river chemistry of the Alpine region (D number of variables), thus working in the \({{\mathbb{R}}^{D - 1}}\) statistical sample space. The D − 1 coordinates were chosen using the decreasing variance criterion so that each one could provide information about different space–time properties for the investigated geochemical system. Coordinates dominated by heterogeneity appear to be able to capture regime shifts only on a long-time period and monitor processes on a very wide scale. On the other hand, coordinates characterized by lower variability present multimodality, thus capturing the presence of alternative states in the analyzed spatial domain also for the current time. Further developments are needed to determine the ranges of conditions for which variability and other statistics can be useful indicators of regime shifts on different time–space scales in geochemical systems.
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Acknowledgements
We acknowledge financial support from the University of Florence (Fondi Ateneo 2017 and Strategic plan for 3-year Ph.D. interdisciplinary grants, 2017), the Geobasi Project sustained by Tuscany Region, and the International Association for Mathematical Geosciences (IAMG) for the 2016 Natural Resource Research Student Awards (CG).
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This article is part of a Topical Collection in Environmental Earth Sciences on “Learning from spatial data: unveiling the geo-environment through quantitative approaches”, guest edited by Sebastiano Trevisani, Marco Cavalli, Jean Golay, and Paulo Pereira.
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Gozzi, C., Graziano, R.S., Frondini, F. et al. Innovative monitoring tools for the complex spatial dynamics of river chemistry: case study for the Alpine region. Environ Earth Sci 77, 579 (2018). https://doi.org/10.1007/s12665-018-7756-0
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DOI: https://doi.org/10.1007/s12665-018-7756-0