{Reference Type}: Journal Article
{Title}: Synthetic and practical reconstructions of SST and seawater pH using the novel multiproxy SMITE method.
{Author}: Hughes HP;Thompson D;Foster GL;Lees J;Surge D;Standish CD;
{Journal}: PLoS One
{Volume}: 19
{Issue}: 6
{Year}: 2024
{Factor}: 3.752
{DOI}: 10.1371/journal.pone.0305607
{Abstract}: Geochemical proxies of sea surface temperature (SST) and seawater pH (pHsw) in scleractinian coral skeletons are valuable tools for reconstructing tropical climate variability. However, most coral skeletal SST and pHsw proxies are univariate methods that are limited in their capacity to circumvent non-climate-related variability. Here we present a novel multivariate method for reconstructing SST and pHsw from the geochemistry of coral skeletons. Our Scleractinian Multivariate Isotope and Trace Element (SMITE) method optimizes reconstruction skill by leveraging the covariance across an array of coral elemental and isotopic data with SST and pHsw. First, using a synthetic proxy experiment, we find that SMITE SST reconstruction statistics (correlation, accuracy, and precision) are insensitive to noise and variable calibration period lengths relative to Sr/Ca. While SMITE pHsw reconstruction statistics remain relative to δ11B throughout the same synthetic experiment, the magnitude of the long-term trend in pHsw is progressively lost under conditions of moderate-to-high analytical uncertainty. Next, we apply the SMITE method to an array of seven coral-based geochemical variables (B/Ca, δ11B, Li/Ca, Mg/Ca, Sr/Ca, U/Ca & Li/Mg) measured from two Bermudan Porites astreoides corals. Despite a <3.5 year calibration period, SMITE SST and pHsw estimates exhibit significantly better accuracy, precision, and correlation with their respective climate targets than the best single- and dual-proxy estimators. Furthermore, SMITE model parameters are highly reproducible between the two coral cores, indicating great potential for fossil applications (when preservation is high). The results shown here indicate that the SMITE method can outperform the most common coral-based SST and pHsw reconstructions methods to date, particularly in datasets with a large variety of geochemical variables. We therefore provide a list of recommendations and procedures for users to begin implementing the SMITE method as well as an open-source software package to facilitate dissemination of the SMITE method.