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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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Year:
2018
Type of Publication:
Article
Keywords:
Coralline algae, Sea surface temperature, Calibration, Paleotemperature
Authors:
Hetzinger, S.; Halfar, J.; Kronz, Andreas; Simon, Klaus; Adey, W. H.; Steneck, R. S.
Journal:
Geochimica et Cosmochimica Acta
Volume:
220
Pages:
96 - 109
ISSN:
0016-7037
BibTex:
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 intersample 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.

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