Inorganic geochemistry of lake sediments: A review of analytical techniques and guidelines for data interpretation

Bertrand, Sebastien; Tjallingii, Rik; Kylander, Malin E.; Wilhelm, Bruno; Roberts, Stephen J. ORCID:; Arnaud, Fabien; Brown, Erik; Bindler, Richard. 2024 Inorganic geochemistry of lake sediments: A review of analytical techniques and guidelines for data interpretation. Earth-Science Reviews, 249, 104639. 31, pp.

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Inorganic geochemistry is a powerful tool in paleolimnology. It has become one of the most commonly used techniques to analyze lake sediments, particularly due to the development and increasing availability of XRF core scanners during the last two decades. It allows for the reconstruction of the continuous processes that occur in lakes and their watersheds, and it is ideally suited to identify event deposits. How earth surface processes and limnological conditions are recorded in the inorganic geochemical composition of lake sediments is, however, relatively complex. Here, we review the main techniques used for the inorganic geochemical analysis of lake sediments and we offer guidance on sample preparation and instrument selection. We then summarize the best practices to process and interpret bulk inorganic geochemical data. In particular, we emphasize that log-ratio transformation is critical for the rigorous statistical analysis of geochemical datasets, whether they are obtained by XRF core scanning or more traditional techniques. In addition, we show that accurately interpreting inorganic geochemical data requires a sound understanding of the main components of the sediment (organic matter, biogenic silica, carbonates, lithogenic particles) and mineral assemblages. Finally, we provide a series of examples illustrating the potential and limits of inorganic geochemistry in paleolimnology. Although the examples presented in this paper focus on lake and fjord sediments, the principles presented here also apply to other sedimentary environments.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 0012-8252
Additional Keywords: XRF core scanner, normalization, calibration, compositional data, statistical exploration, grain size, provenance
Date made live: 19 Jan 2024 11:55 +0 (UTC)

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