Global Core Top Calibration of <i>δ</i><sup>18</sup>O in Planktic Foraminifera to Sea Surface Temperature

Malevich, S. B.; Vetter, L.; Tierney, Jessica E.

doi:10.1029/2019pa003576

Cited by 43 publications

(54 citation statements)

References 137 publications

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“…In addition to patterns that may reflect the impact of the latent variable discussed above, there are negative residuals for G. bulloides in the west African and Benguela upwelling zones; along frontal regions in the Southern Ocean; and near the confluence of the Brazil and Malvinas currents (Figure e) indicating that Mg/Ca values are lower than the model predicts. Similar patterns were observed in the residuals of our Bayesian δ 18 O models (Malevich et al, ) and might suggest that G. bulloides is calcifying during either a cooler season than our seasonal SST inferences predict or in a deeper habitat. These patterns could also conceivably reflect geochemical differences between G. bulloides genotypes (Sadekov et al, ) or high productivity driving locally enhanced dissolution (Hertzberg & Schmidt, ).…”

Section: Baymag: Bayesian Calibration Models For Mg/casupporting

confidence: 87%

“…Alternatively, this residual trend could suggest that our relatively simple inference of seasonal SST (based on sediment trap abundances) does not apply well to G. ruber. However, we did not see this residual trend in our model for 18 O of G. ruber, which uses the same seasonal estimation method (Malevich et al, 2019). Accounting for subtle differences in depth habitat would make the trend worse, as studies suggest that G. ruber should have a deeper habitat in the tropics (and therefore lower Mg/Ca) and shallower one in the subtropics (and therefore higher Mg/Ca) (Hertzberg & Schmidt, 2013;Hönisch et al, 2013).…”

Section: Model Resultsmentioning

confidence: 66%

“…Following our previous work with δ 18 O of foraminifera (Malevich et al, ), we developed two styles of forward models to represent core top Mg/Ca: one that pools all species together (mainly for deep‐time applications with extinct species) and another that treats each species group separately, with information shared through parameters and hyperparameters. The pooled model design is

\begin{matrix} right \ln ({boldMg/Ca}_{boldc}) & left = \{\begin{array}{ll} α_{i} + T_{c} \cdot β_{T c} + S_{c} \cdot β_{S} + ϵ_{c} & if i n c o m p t a, s a c c u l i f e r \\ α_{i} + T_{c} \cdot β_{T c} + S_{c} \cdot β_{S} + {pH}_{c} \cdot β_{P} + ϵ_{c} & if r u b e r, b u l l o i d e s, u n i v e r s a \end{array} & right \\ right ϵ_{c} & left \sim N (0, σ_{c i}^{2}), \end{matrix}

\begin{matrix} right \ln (Mg/Ca) & left = α + T \cdot β_{T} + S \cdot β_{S} + pH \cdot β_{P} + {normalΩ}^{- 2} \cdot β_{O} + (1 - clean \cdot β_{C}) + ϵ, & right \\ right ϵ & left \sim N (0, σ^{2}) \end{matrix}

with different values of α and σ for each i cultured species.…”

Section: Baymag: Bayesian Calibration Models For Mg/camentioning

confidence: 99%

“…Following our previous work with 18 O of foraminifera (Malevich et al, 2019), we developed two styles of forward models to represent core top Mg/Ca: one that pools all species together (mainly for deep-time applications with extinct species) and another that treats each species group separately, with information Paleoceanography 10.1029/2019PA003744 shared through parameters and hyperparameters. The pooled model design is…”

Section: Model Designmentioning

confidence: 99%

“…First, we assess the impact of adding known secondary environmental predictors (bottom water saturation state, salinity, pH, and laboratory cleaning technique) to a Mg/Ca calibration model. We then compute both pooled (all species groups considered together) and hierarchical (species groups considered separately) calibration models using Bayesian methodology similar to that previously developed for core top models of planktic foraminiferal δ 18 O (Malevich et al, ). We assess the validity of the new regressions by applying them to sediment trap data and downcore measurements of foraminiferal Mg/Ca.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian Calibration of the Mg/Ca Paleothermometer in Planktic Foraminifera

Tierney

Malevich

Gray

et al. 2019

Paleoceanog and Paleoclimatol

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146

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The Mg/Ca ratio of planktic foraminifera is a widely used proxy for sea-surface temperature but is also sensitive to other environmental factors. Previous work has relied on correcting Mg/Ca for nonthermal influences. Here, we develop a set of Bayesian models for Mg/Ca in four major planktic groups-Globigerinoides ruber (including both pink and white chromotypes), Trilobatus sacculifer, Globigerina bulloides, and Neogloboquadrina pachyderma (including N. incompta)-that account for the multivariate influences on this proxy in an integrated framework. We use a hierarchical model design that leverages information from both laboratory culture studies and globally distributed core top data, allowing us to include environmental sensitivities that are poorly constrained by core top observations alone. For applications over longer geological timescales, we develop a version of the model that incorporates changes in the Mg/Ca ratio of seawater. We test our models-collectively referred to as BAYMAG-on sediment trap data and on representative paleoclimate time series and demonstrate good agreement with observations and independent sea-surface temperature proxies. BAYMAG provides probabilistic estimates of past temperatures that can accommodate uncertainties in other environmental influences, enhancing our ability to interpret signals encoded in Mg/Ca. Plain Language SummaryThe amount of magnesium (Mg) incorporated into the calcite shells of tiny protists called foraminifera is determined by the temperature of the water in which they grew. This allows paleoclimatologists to measure the magnesium-to-calcium (Mg/Ca) ratio of fossil foraminiferal shells and determine how past sea-surface temperatures have changed. However, other factors can influence Mg/Ca, like the salinity and pH of seawater. Here, we develop Bayesian models of foraminiferal Mg/Ca that account for all of the influences on Mg/Ca and show how we can use these to improve our interpretations of Mg/Ca data. Culture experiments provide precise constraints on environmental sensitivities but are limited in that laboratory conditions are not perfect analogs for the natural environment. Sediment traps have an advantage in that seasonality of foraminiferal occurrence and corresponding ocean temperatures are well constrained, but they do not account for the effects of dissolution or bioturbation. Sedimentary core tops integrate effects associated with both occurrence and preservation and are thus better analogs for the conditions typical of the geological record, but uncertainties in seasonal preferences and the depth of calcification can in some cases lead to misleading inference of secondary environmental sensitivities (Hertzberg & Schmidt, 2013;Hönisch et al., 2013).Here, we use both core top and laboratory culture data to develop a suite of Bayesian hierarchical models for Mg/Ca. We collate over 1,000 sedimentary Mg/Ca measurements to formulate new calibrations for four major planktic groups: Globigerinoides ruber (including both pink and white chromotypes), Trilobat...

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Section: Baymag: Bayesian Calibration Models For Mg/casupporting

confidence: 87%