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Reproducibility of Clathromorphum compactum coralline algal Mg/Ca ratios and comparison to high-resolution sea surface temperature data

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Complete Citation

  • Hetzinger, S., Halfar, J., Kronz, A., Simon, K., Adey, Walter H., and Steneck, R. S. 2018. "Reproducibility of Clathromorphum compactum coralline algal Mg/Ca ratios and comparison to high-resolution sea surface temperature data." Geochimica et Cosmochimica Acta, 220 96–109. https://doi.org/10.1016/j.gca.2017.09.044.

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Abstract

  • The potential of crustose coralline algae as high-resolution archives of past ocean variability in mid-to high-latitudes has only recently been recognized. Few comparisons of coralline algal proxies, such as temperature-dependent algal magnesium to calcium (Mg/Ca) ratios, with in situ-measured surface ocean data exist, even rarer are well replicated records from individual sites. We present Mg/Ca records from nine coralline algal specimens (Clathromorphum compactum) from a single site in the Gulf of Maine, North Atlantic. Sections from algal mounds were analyzed using Laser Ablation-Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) yielding individual Mg/Ca records of up to 30 years in length. We first test intra-and inter-sample signal replication and show that algal Mg/Ca ratios are reproducible along several transects within individual sample specimens and between different samples from the same study site. In addition, LA-ICP-MS-derived Mg/Ca ratios are compared to electron microprobe (EMP) analyzed data on the longest-lived specimens and were found to be statistically commensurable. Second, we evaluate whether relationships between algal-based SST reconstructions and in situ temperature data can be improved by averaging Mg/Ca records from multiple algal specimens (intersample averages). We found that intersample averages yield stronger relationships to sea surface temperature (SST) data than Mg/Ca records derived from individual samples alone. Thus, Mg/Ca-based paleotemperature reconstructions from coralline algae can benefit from using multiple samples per site, and can expand temperature proxy precision from seasonal to monthly. (C) 2017 Elsevier Ltd. All rights reserved.

Publication Date

  • 2018

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