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Supplementary data accompanying Hess et al. (2025) 'The I/Ca paleo-oxygenation proxy in planktonic foraminifera: A multispecies core-top calibration' published in Geochimica et Cosmochimica Acta

<p>This data accompanies Hess et al. (2025) 'The I/Ca paleo-oxygenation proxy in planktonic foraminifera: A multispecies core-top calibrations' published in Geochimica et Cosmochimica Acta.</p> <p>Data columns and explanation:</p> <table> <tbody> <tr> <td>reference</td> <td>reference for the I/Ca and Mg/Ca data</td> </tr> <tr> <td>site</td> <td>site name</td> </tr> <tr> <td>sample_depth_cm</td> <td>sample depth (cm below sediment surface)</td> </tr> <tr> <td>basin</td> <td>ocean basin</td> </tr> <tr> <td>site_depth_km</td> <td>site water depth (km)</td> </tr> <tr> <td>species</td> <td>foraminifera species</td> </tr> <tr> <td>calcification_depth</td> <td>foraminifera calcification depth</td> </tr> <tr> <td>size_fraction</td> <td>foraminifera size fraction</td> </tr> <tr> <td>cleaning_oxidative_reductive</td> <td>cleaning applied to sample before trace element analysis (O = oxidative, O+R = oxidative and reductive)</td> </tr> <tr> <td>local_O2_variability</td> <td>indication of whether the site experiences local O2 variability, rows with "yes" are excluded from Figure 4</td> </tr> <tr> <td>MgCa</td> <td>Mg/Ca (mmol/mol)</td> </tr> <tr> <td>MgCa_corr</td> <td>Mg/Ca corrected for effect of reductive cleaning, as necessary (mmol/mol)</td> </tr> <tr> <td>T_anand</td> <td>calcification temperature calculated from Mg/Ca using Anand et al. (2003) multispecies equation</td> </tr> <tr> <td>T_Hollstein_multispec</td> <td>calcification temperature calculated from Mg/Ca using Hollstein et al. (2017) multispecies equation</td> </tr> <tr> <td>T_Hollstein_spec</td> <td>calcification temperature calculated from Mg/Ca using species-specific Hollstein et al. (2017) equations</td> </tr> <tr> <td>T_Cleroux</td> <td>calcification temperature calculated from Mg/Ca using species-specific Cléroux et al. (2008) equations</td> </tr> <tr> <td>depth_anand</td> <td>calcification depth from water column temperature data (Moffett et al., 2020) and T_anand</td> </tr> <tr> <td>depth_Hollstein_multispec</td> <td>calcification depth from water column temperature data (Moffett et al., 2020) and T_Hollstein_multispec</td> </tr> <tr> <td>depth_Hollstein_spec</td> <td>calcification depth from water column temperature data (Moffett et al., 2020) and T_Hollstein_spec</td> </tr> <tr> <td>depth_Cleroux</td> <td>calcification depth from water column temperature data (Moffett et al., 2020) and T_Cleroux</td> </tr> <tr> <td>ICa</td> <td>I/Ca (µmol/mol)</td> </tr> <tr> <td>ICa_corr</td> <td>I/Ca corrected for effect of reductive cleaning, as necessary (µmol/mol)</td> </tr> <tr> <td>O2av_0-500m</td> <td>average oxygen concentration in the top 500 m of the water column at this site, calculated from Moffett et al. (2020) CTD data</td> </tr> <tr> <td>O2min_0-500m</td> <td>minimum oxygen concentration in the top 500 m of the water column at this site, calculated from Moffett et al. (2020) CTD data</td> </tr> <tr> <td>O2min_alldepths</td> <td>minimum oxygen concentration at any depth in the water column at this site, calculated from Moffett et al. (2020) CTD data</td> </tr> <tr> <td>O2av_0-100m</td> <td>average oxygen concentration in the top 100 m of the water column at this site, calculated from Moffett et al. (2020) CTD data</td> </tr> <tr> <td>O2min_0-100m</td> <td>minimum oxygen concentration in the top 100 m of the water column at this site, calculated from Moffett et al. (2020) CTD data</td> </tr> </tbody> </table>

FIGURE 2 in The Volhynian (late Middle Miocene) marine fishes and mammals as proxies for the onset of the Eastern Paratethys re-colonisation by vertebrate fauna

FIGURE 2. Correlation of the Central and Eastern Paratethyan regional stages with standard chronostratigraphy and magnetostratigraphy modified after Harzhauser et al. (2004), Studencka, (1999), Ionesi (1991), and Vernyhorova (2015).

FIGURE 1 in The Volhynian (late Middle Miocene) marine fishes and mammals as proxies for the onset of the Eastern Paratethys re-colonisation by vertebrate fauna

FIGURE 1. Geographic location map of the Volhynian fossil-bearing sites: 1 – Brykiv; 2 – Vilkhovets; 3 – Kolubaivtsi; 4 – Khotin; 5 – Hrushivtsi; 6 – Khonkivtsi; 7 – Karpov Yar (Naslavcea); 8 – Darabani; 9 – Ghireni; 10 – Cordăreni; 11 – Hănești; 12 – Mitoc; 13 – Drăgușeni; 14 – Stâncești; 15 – Leucucești; 16 – Basarabi; 17 – Stăuceni; 18 – Erbiceni; 19 – Românești; 20 – Aroneanu; 21 – Voinești; 22 – Amvrosiivka; 23 – Saur-Mohyla.

FIGURE 5 in The Volhynian (late Middle Miocene) marine fishes and mammals as proxies for the onset of the Eastern Paratethys re-colonisation by vertebrate fauna

FIGURE 5. Marine mammals from the Volhynian beds of the Moldavian Platform: A – Phocinae indet. 2, scapula and caudal vertebra, Stăuceni; B – Kentriodon fuchsii, a lumbar vertebra, dorsal and posterior view, Basarabi; C – Kentriodontidae indet. 1 (cf. Imerodelphis thabagarii), lumbar vertebra, dorsal and anterior view, Saur-Mohyla; D – Kentriodontidae indet. 2, caudal vertebra, anterior and lateral view, Stăuceni; E – Kentriodontidae indet. 2, thoracic vertebra, anterior view, Stâncești; F – Kentriodontidae indet. 3, caudal vertebra, anterior and lateral view, Stăuceni; G – Pachyacanthus sp., thoracic vertebra, anterior and lateral view, Vilkhovets; H – Cetotheriidae indet., caudal vertebra, dorsal and lateral view, Stăuceni; I-J –? Mysticeti indet. ("Archaeocetus fockii"), rib fragment, lateral view and cross-section (I), caudal vertebra (J), dorsal and lateral view, Drăgușeni. Scale bars equal 2 cm in A–I and 5 cm in J.

FIGURE 4 in The Volhynian (late Middle Miocene) marine fishes and mammals as proxies for the onset of the Eastern Paratethys re-colonisation by vertebrate fauna

FIGURE 4. The partial skeleton of a true seal (Phocinae indet. 1) from the Volhynian beds of Kolubaivtsi (Ukraine). Scale bar equals 10 cm.

FIGURE 6 in The Volhynian (late Middle Miocene) marine fishes and mammals as proxies for the onset of the Eastern Paratethys re-colonisation by vertebrate fauna

FIGURE 6. The periotic bone of Kentriodon fuchsii from the Volhynian of Stăuceni (Romania) in ventral (A), lateral (B), and posterior view (C). Abbreviations: abf, anterior bullar facet; ap, anterior process; fc, ventral foramen of the facial canal; fo, fenestra ovalis; fr, fenestra rounda; pbf, posterior bullar facet; pc, pars cochlearis; pb, periotic body; pp, posterior process; vt, ventrolateral tuberosity. Scale bars equal 2 cm.

FIGURE 3 in The Volhynian (late Middle Miocene) marine fishes and mammals as proxies for the onset of the Eastern Paratethys re-colonisation by vertebrate fauna

FIGURE 3. Fish remains from the Volhynian beds of Romania and Ukraine: A-B – Sarmatella doljeana (Kramberger, 1884), anterior part of the body (A), and caudal part (B), Leucuşeşti; C – Clupeinae gen. et sp. indet., isolated scale, Voineşti; D-E – Scombroidei indet., caudal part (D), Erbiceni, and middle part of the body (E), Aroneanu; F – Sparus brusinai (Kramberger, 1882), skeleton, Hrushivtsi; G-H – Sparus cf. brusinai (Kramberger, 1882), right dentary in lateral (G) and dorsal view (H), Pârâul lui Gheorghe; I – Bothus parvulus (Kramberger, 1883), body imprint, Româneşti. Scale bars equal 2 mm in C, 5 mm in A-B, D-E, G-I, and 2 cm in F.

FIGURE 7 in The Volhynian (late Middle Miocene) marine fishes and mammals as proxies for the onset of the Eastern Paratethys re-colonisation by vertebrate fauna

FIGURE 7. Suggested scheme of marine vertebrate fauna dispersal in the Eastern Paratethys during the Volhynian age (modified after Schneider et al., 2013).

opencc-zeroJun 2024View details →

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The rare earth element distribution in marine carbonates as a potential proxy for seawater pH on early earth

<p>Understanding the marine environment of early Earth is crucial for understanding the evolution of climate and early life. However, the master variable of Archean and Proterozoic seawater, the pH, is poorly constrained, and published ideas about the pH range encompass ~7 pH units from mildly acidic to hyperalkaline. To better infer ancient seawater pH, we examine the possibility of a seawater pH proxy using rare earth elements (REEs) in marine carbonates. The principle is based on increasing concentrations of heavy rare earth elements in solution relative to the light REEs with decreasing pH due to REE complexation and scavenging. We calibrated such an REE pH proxy using pH variability in modern seawater and tested the proxy with ~100 REE measurements from 13 separate carbonate formations. We compared our pH estimates derived from the REE proxy to published pH estimates of Cenozoic and Neoproterozoic seawater that use the established pH proxy of boron isotopes (δ<sup>11</sup>B). REE-pH estimates agree with the Cenozoic and the Ediacaran δ<sup>11</sup>B-pH proxy based on the type of carbonate and boron isotopic composition at corresponding times. The uncertainty in our REE-pH proxy can probably be explained by model assumptions, noise from freshwater influence, siliciclastic input, and diagenesis. This proof-of-concept study demonstrates that the REE-pH method provides pH estimates comparable to boron isotope pH estimates within uncertainties, which potentially could constrain changes in Precambrian seawater pH to better understand the coevolution of life and early Earth's environment.</p>

FIGURE 8 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 8. Difference maps showing the percentage of events accurately detected by simulations without bioturbation subtracted from the percentage of events accurately detected by simulations with bioturbation. 100% sampling completeness and transition durations 0.001 times the event duration for A; 100% sampling completeness and transition durations five times the event duration for B; 25% sampling completeness and transition durations 0.001 times the event duration for C; 25% sampling completeness and transition durations five times the event duration for D. The solid black line marks the contour line for zero difference between the bioturbated and non-bioturbated simulations.

FIGURE 6 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 6. Effect of varying completeness with the duration of transition intervals. Simulation results with 25% completeness and transition lengths 0.001 times the event duration for A; and 25% completeness with transition lengths of five times the event duration for B. Background DCA-1 value is -0.5 and no bioturbation occurs. Excursion magnitude (y-axis) indicates the difference between the simulated background DCA-1 value and the simulated event DCA- 1 value. Resolution potential (x-axis) is the event duration divided by the time represented by the sample interval. Color shading indicates the median excursion magnitude of all samples that intersect an event. Contour lines show the parameter space where 50% (dashed line), 75% (dotted line) and 95% (solid line) of events are accurately detected.

FIGURE 12 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 12. Effect of sample thickness on accurate detection of events with excursion magnitudes of 2.8 DCA-1 units. Y-axis shows the percentage of accurately detected events at different sedimentation rates (x-axis) for three different event durations: 50 years, 100 years and 1000 years. Simulations are for the 2016 data set to approximate how a researcher might use a pilot data set to design a sampling procedure and are based on sampling with 25% completeness. A is simulations without the effect of bioturbation; B is simulations with the effect of bioturbation.

FIGURE 2 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 2. Simulation workflow in the paleontological assemblage mixer (paleoAM). A. Relative abundances of a given species (Epistominella pacifica) from the 355 samples of the 2021 data set, along the empirically derived DCA Axis 1 gradient. B. The per-bin mean of absolute abundance of E. pacifica across all samples within each bin. Absolute abundances are calculated from the relative abundances in A by rescaling the relative abundances to 10000 total specimens. C. Scaled kernel density estimates for E. pacifica, which depict the predicted abundance distribution of E. pacifica along DCA Axis 1 after fitting a kernel density estimate to the absolute abundances in B. D. Scaled kernel density estimates, like in C, for all taxa in the dataset showing their differing predicted abundance distributions along DCA Axis 1 with the kernel density of E. pacifica shown in C marked with an asterisk. E. Visual representation of parameters varied within the simulation along a vertical sediment core. From left to right: standard scenario, increased excursion magnitude, increased background value, increased resolution potential, sampling completeness, bioturbation and increased transition duration. Stacked rectangles represent potential sample intervals. In the first and last column, black dots indicate which intervals are sampled, gray dots indicate unsampled intervals. In the standard scenario, all potential sample intervals are sampled. Curved arrows denote sediment mixing among potential sample intervals.

FIGURE 1 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 1. Sample scores from detrended correspondence analysis (DCA) performed on benthic foraminiferal assemblages in the>63 µm size fraction from Integrated Ocean Drilling Program Expedition 341 Site U1419 in the Gulf of Alaska used in the simulation case study. A. DCA Axis 1 values for 355 assemblages from Sharon et al. (2021); B. DCA Axis 1 values for 47 assemblages representing a "pilot" data set of samples available and processed in 2016.

FIGURE 4 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 4. Percentage of events that are accurately detected and median excursion magnitudes for simulations performed with background DCA-1 values of -0.5, 0.5 and 1. For A and B, simulations used a background DCA-1 value of -0.5; for C and D, a background DCA-1 value of 0.5; for E and F, a background DCA-1 value of 1. Excursion magnitude (y-axis) indicates the difference between the simulated background DCA-1 value and the simulated event DCA- 1 value. Resolution potential (x-axis) is the event duration divided by the time represented by the sample interval. A, C and E. Color shading indicates the percentage of events that are accurately detected by at least one sample (i.e., the sample produces a DCA-1 value outside the 95% envelope of samples simulated at the background value, and within one DCA-1 unit of the simulated excursion magnitude). B, D and F. Color shading indicates the median excursion magnitude of all samples that intersect an event. Contour lines show the parameter space where 50% (dashed line), 75% (dotted line) and 95% (solid line) of events are accurately detected.

FIGURE 5 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 5. Effect of varying transition duration. Each panel represents a set of simulations generated at transition interval lengths of 0.001 times the event duration for A, 0.5 times the event duration for B, 1.0 times the event duration for C, and 5.0 times the event duration for D. Background DCA-1 value is -0.5 and completeness is 100%. Excursion magnitude (y-axis) indicates the difference between the simulated background DCA-1 value and the simulated event DCA-1 value. Resolution potential (x-axis) is the event duration divided by the time represented by the sample interval.Color shading indicates the median excursion magnitude of all samples that intersect an event. Contour lines show the parameter space where 50% (dashed line), 75% (dotted line) and 95% (solid line) of events are accurately detected.

FIGURE 9. DCA-1 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 9. DCA-1 values observed when assemblages simulated at different event values are mixed with different proportions of the background assemblage. For A, the maximum DCA-1 value observed is shown; for B, the median DCA-1 value observed; and for C, the minimum DCA-1 value observed. In all cases, background assemblages are simulated at a DCA-1 value of -0.5 and are mixed with an event assemblage with a DCA-1 value as given on the x-axis.

FIGURE 3 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 3. Multivariate comparison of empirical and simulated foraminiferal assemblages. A. Detrended correspondence analysis showing empirical (red filled) and simulated (black open) assemblages in the same ordination space. B. DCA1 scores for empirical samples paired with the DCA1 score of the corresponding simulated sample. Dotted line is the 1:1 line and is largely obscured by the points. C. All pairwise dissimilarities among empirical samples plotted against the average pairwise dissimilarity of 300 corresponding samples simulated at the same DCA1 values. Color scale depicts the density of dissimilarities with higher concentrations of dissimilarities in brighter colors. Black line is the 1:1 line.

FIGURE 7 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 7. The interaction of bioturbation, completeness and transition duration. All simulations figured include bioturbation and use a background DCA-1 value of -0.5. Simulation results for 100% sampling completeness and transition durations 0.001 times the event duration for A; 100% sampling completeness and transition durations five times the event duration for B; 25% sampling completeness and transition durations 0.001 times the event duration for C; 25% sampling completeness and transition durations five times the event duration for D. Excursion magnitude (yaxis) indicates the difference between the simulated background DCA-1 value and the simulated event DCA-1 value. Resolution potential (x-axis) is the event duration divided by the time represented by the sample interval. Color shading indicates the median excursion magnitude of all samples that intersect an event. Contour lines show the parameter space where 50% (dashed line), 75% (dotted line) and 95% (solid line) of events are accurately detected.

FIGURE 14 in Simulating our ability to accurately detect abrupt changes in assemblage-based paleoenvironmental proxies

FIGURE 14. Estimated ability of the record to detect 100 year-long events with 3 cm samples, given a known sedimentation rate at three excursion magnitudes (0.4, 1.2 and 2.8), based on 'worst-case scenario' simulations with 25% sampling, bioturbation, rapid transitions between events and the background condition (-0.5 DCA-1 value). A and B are simulated with an excursion magnitude of 0.4; C and D are simulated with an excursion magnitude of 1.2; and E and F are simulated with an excursion magnitude of 2.8. A, C and E show the percentage of events that are detectable above a background value of -0.5. An event is detected if a sample has an observed DCA-1 value exceeding the 95% quantile of the DCA-1 value of assemblages simulated at the background value. B, D and F show the median DCA-1 values recovered from samples intersecting simulated events. Values that fall above the blue dashed line are detected; that is, they exceed the 95% quantile of the DCA-1 value of assemblages simulated at the background value. Values that fall above the red dotted line are accurately detected; that is, they exceed the 2.75% quantile on DCA-1 values recovered from simulations at the event value.