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Paleoceanography
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Supporting Information for
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Export Production Fluctuations in the Eastern Equatorial Pacific during the
Pliocene-Pleistocene: Reconstruction Using Barite Accumulation Rates
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Zhongwu Ma1,2, Christina Ravelo2, Zhonghui Liu3, Liping Zhou1, Adina Paytan2*
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1Laboratory
for Earth Surface Processes, Department of Geography, Peking University, Beijing 100871, China
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2University
3Department
of California Santa Cruz, Santa Cruz CA, 95064, USA
of Earth Sciences, The University of Hong Kong, James Lee Science Building, Pokfulam Road, Hong
Kong,
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Contents of this file
Text S1 to S3
Figures S1 to S5
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Introduction
Marine barite crystals form in the water column in microenvironments associated with
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decaying organic matter and their accumulation in marine sediments has been used
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extensively as an export production proxy. A detailed description of the strengths and
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limitations of barite as an export productivity proxy are given by Paytan and Griffith [2007]
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and a summary of these points is included in the supplemental text below. Since one of the
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potential limitations associated with the use of barite accumulation rates (BAR, which is the
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product of weight % barite and the sediment mass accumulation rates) is the impact of major
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constituent in the sediment (CaCO3 in this case) on the weight % of minor constituents (barite
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in this case) on BAR, several means for calculating BAR are shown. This includes BAR
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derived using an orbitally tunes age model, 230Th and 3He based accumulation rates (Figure
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S1) as well as a comparison between wt% barite and wt% CaCO3 and wt% CaCO3 and BAR
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and carbonate accumulation rates (Figure S2A). Finally we also included a plot of BAR
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calculated on a carbonate free bases by removing the carbonate weight from the total
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sediment used in the calculation (Figure S2B). .
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The record of BAR derived export production over the past 4.3 Ma at ODP site 849 is
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divided into three intervals which are illustrated in Figure S3 using 800kry, 400kyr and
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200kyr smoothed curves; this highlights the long term trends in the record. We also show a
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detailed statistical relationship between reconstructed export production and the climate
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system by comparing BAR and benthic oxygen isotope using spectral analysis methods
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(Figure S4). Finally BAR and total organic carbon accumulation rates from the same samples
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for a selected interval at site 849 are plotted together to demonstrate that they both correspond
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to productivity in Figure S5.
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Text S1. Barite accumulation rates as an export productivity proxy
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The ocean is under-saturated with respect to barite; however, authigenic barite
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crystals form in the water column in microenvironments with decaying organic debris
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[Arrhenius, 1959; Church, 1970; Goldberg and G.O.S, 1958]. Organisms normally
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contain barium in their cells [Paytan and Griffith, 2007] and during the decay of
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marine organic matter, barium is released saturating the microenvironment with
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respect to barite and precipitating barite crystal [Ganeshram et al., 2003]. Bacteria
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may also be involved by providing nucleation sites [Gonzalez-Muñoz et al., 2012].
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The nutrient-like depth distribution of dissolved Ba and the distribution of particulate
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barite in the water column [Dehairs et al., 1980; Jacquet et al., 2005; Jeandel et al.,
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1996], as well as controlled mesocosm experiments [Ganeshram et al., 2003] and
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analyses of Ba isotopes in seawater and particulate matter [Horner et al., 2015] all
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support this mechanism of barite formation.
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Because barite has low solubility, most of the barite that forms in the water
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column is thought to reach the ocean sediment [Paytan and Kastner 1996a] with as
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much as 30% of the barite “rain” to the sediment persevered in oxic sediments
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[Dymond et al., 1992; Paytan et al., 1996b] a considerable advantage over proxies
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such as organic carbon or opal which are not preserved as well. Once barite is buried,
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regeneration of various Ba carrying phases within the upper few centimeters of the
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sediment results in barite saturation in pore fluids thus the remaining barite is
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preserved in sediments that do not undergo sulfate reduction [Paytan and Kastner
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1996a; Paytan et al., 2007].
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The strong correlation between marine barite and the export of organic carbon to
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depth [Dymond et al., 1992; Eagle et al., 2003; Paytan et al., 1996b] lends itself to the
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use of Ba and barite accumulation rates (BAR) for the reconstruction of export
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production [Bains et al., 2000; Bonn et al., 1998; Eagle et al., 2003; Nürnberg, 1997;
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Paytan et al., 2007; Schmitz, 1987]. BAR represents the Ba that is associated with Corg
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flux below the euphotic zone, and BAR can directly be used to estimate export
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production or new production [Paytan et al., 1996a; Paytan et al., 1997]. Excess Ba
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(total Ba in the sediment normalized to Al or Ti to correct for the terrigenous
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component of Ba input [Dymond et al., 1992] has also been using for export
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production reconstruction. The correction or calculation of excess Ba is done to
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account only for the so called biogenic Ba component which is equivalent to barite.
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The correction however does not work at all sites and a direct measurement of barite
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is as done and reported here is preferable [Averyt and Paytan, 2004; Eagle et al.,
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2003; Gonneea and Paytan, 2006].
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When significant sulfate reduction occurs, barite is dissolved and can no longer be
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used as a productivity proxy. However, barite that forms under diagenetic conditions
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or in hydrothermal environments can be identified based on crystal morphology (see
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image below of marine barite separated from the sediments) as well as using S and/or
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Sr isotopes in the barite [Paytan and Griffith, 2007 and references therein] and
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samples used in this study are all of water column origin and have not been impacted
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by diagenesis based on these criteria [Markovik et al., 2015].
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Another process that may affect BAR calculations is sediment focusing, the
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redistribution of recently deposited material (i.e., syndepositional redistribution) from
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zones of sediment winnowing to zones to sediment focusing [Francois et al., 2004].
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This could affect BAR by changing mass accumulation rates (MAR) without
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impairing the stratigraphy. In our study we used LSR to compute MAR and calculate
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BAR, hence we did not account for sediment focusing. However, we compare these
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values to MAR based on thorium in the first 500 kyr and helium between 1.3 to 1.6
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Ma (where such data are available) (e.g. there is little recognized refocusing of
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sediment at this site according to G. Winckler’s personal communication, 2015). Our
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BARs show generally higher values (by a factor of 2) when compared to the thorium
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based BAR and slightly lower when compared to helium based BAR (Figure S1), this
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would affect the amplitude but not the trends we see in the record. Our discussion
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focuses on observed trends and does not emphasize the absolute values. Notably each
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of the methods used for calculating sedimentation rates has its own associated
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assumptions and limitations and additional research should be done, which is beyond
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the scope of this work, to determine the reasons of the systematic offsets between
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these three methods for calculating sedimentation rates at this site and in general.
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An additional potential limitation of using BAR is the impact of major
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constituents in the sediment (e.g. CaCO3) on the wt% of minor constituents (e.g.
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barite). In other words because barite is a minor component in marine sediments, wt%
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barite is affected by changes in abundance of other sedimentary components and
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particularly CaCO3 which is the major sedimentary phase at site 849. To account for
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that we use the BAR and not wt% barite to reconstruct export productivity. Using
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mass accumulation rates should reduce the impact CaCO3 changes because these
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changes are incorporated in the sediment mass accumulation rates used. To
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demonstrate however that carbonate content does not exert the only control on barite
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distribution we plot the relation between barite abundance (ppm) and CaCO3
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abundance (wt%) (Figure S2 a) as well as the relationships between BAR and wt%
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CaCO3 and BAR and CAR. As seen in Figure S2a while a slight negative correlation
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is indeed observed it is quite weak and illustrates that changes in carbonate abundance
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do not solely control the barite distribution. The correlation is weaker when BAR is
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used as expected. Actually when we used the carbonate free BAR (BAR calculated
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from the non-carbonate materials by deducted the carbonate from bulk sediments),
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trends are similar to the BAR record (Figure S2 b). Few Ba/Al data we have (not
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shown) which is immune to the carbonate dilution effect also support this conclusion.
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The 4.3 Ma BAR based export production record in the Eastern Equatorial Pacific
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(EEP, Site 849) fluctuates considerably on orbital and on long (million years) time
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scales. The long term trends in the record can be divided into three distinct intervals
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as seen when the data is plotted using 800 kyr, 400 kyr and 200 kyr smoothing. These
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3 intervals are seen also in a Gaussian fit of the 800 kyr smoothed BAR data (Figure
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S3).
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Text S2. Relations between BAR and the benthic oxygen isotope record
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To identify whether periodicities presented in our data are statistically significant,
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we used the Singular Spectrum Analyses - MultiTaper Method (SSA-MTM) Tool kit
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to map both benthic δ18O and the BAR spectral densities with the multi-taper method
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assuming a red noise model [Ghil et al., 2002]. Data were interpolated to be evenly
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distributed with a resolution of 10 kyr under AnalySeries software before spectral
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analyze [Paillard et al., 1996]. This is as close as possible to the average original
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temporal resolution, although there are intervals with resolution that is higher and
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intervals with resolution that is lower. Because of the possibility of aliasing orbital
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scale variability in some intervals, we used MTM evolutive spectrum analysis, carried
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out using AnalySeries software, with a large 600 kyr time window of ~100%
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oversampling; constant 100% pre-whitening was adopted here to diminish low
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frequency signals. To test the coherence between reconstructed productivity and the
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benthic oxygen isotope record, the 41 kyr and 100 kyr bands were selected for the
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cross-spectral analysis, with a 400 kyr time window, 30% lags and 200 kyr increment.
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This was conducted by the Arand software package [Howell et al., 2006]. Strong
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coherence at the 80% and 95% level (Figure S4) is found during some intervals, but
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low sampling resolution may explain the low spectral power and low coherency in
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some of the other intervals.
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The BAR spectral map shows some similarity to the benthic δ18O spectral map,
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with differences that might be explained by the poor resolution of our BAR in some
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intervals (Figure S4 a, b). With regards to the moving, and overlapping, 400-kyr
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windows used for our analyses, there is coherency (80% level) between BAR and
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δ18O in the obliquity (41-kyr band) in 10 out of the 15 windows analyzed between 4.3
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Ma to ~1 Ma, and in none of the windows analyzed between 1.0 – 0 Ma. For the 100-
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kyr band, in the interval between 1.0 – 0 Ma, there is coherency between BAR and
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δ18O in 3 out of the 4 windows analyzed (Figure S4 c). Notably, in the intervals where
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BAR and δ18O varied coherently (80% level), BAR (productivity) 41-kyr variability
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was in phase, or nearly in phase, with δ18O variability between 4.3 Ma to 1.1 Ma,
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while 100-kyr variability lagged δ18O variability between 1.1 Ma and present (Figure
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S4 c, d).
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Text S3. Comparison of BAR with other productivity records in the EEP
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The BAR record is compared to other productivity proxies in this region (opal,
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alkenone, organic C, etc.), as discussed in the text. In addition select samples between
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1.8 and 2.65 Ma were analyzed for TOC on the EA-IRMS in the UCSC Stable Isotope
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Lab, following the method described by [Krupinski et al., 2013]. The records show
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that at this interval BAR and Corg records are similar and a general correspondence
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between TOC and BAR is seen (Figure S5).
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Figure S1. BAR derived from oxygen isotopes chronology (black line, used in this study),
thorium (green line) and helium (red line and red shadow) based BAR [Winckler et al., 2005;
Winckler et al., 2008]. Note Thorium based BAR is plotted with a different Y-axis (green
labeled), while Helium and oxygen isotopes based chronology BAR have the same Y-axis
(black labeled). BAR in the red line during the early Pleistocene was derived from a constant
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HeET of 0.8 pcc STP cm-2 kyr-1 and the boundary conditions are 0.5 and 1.1 pcc STP cm-2 kyr1
respectively.
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Figure S2 a. Carbonate abundance (wt%) and carbonate accumulation rates (CAR)
plot against barite abundance (ppm) and barite accumulation rates (BAR). BAR have
less influence by carbonate dissolution effect comparing with the barite abundance.
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Figure S2 b. (A) BAR compare with (B) carbonate free BAR, (C) the carbonate abundance
are also shown in the figure. Bold line in the BAR and carbonate free BAR panels are 100 kyr
smoothed line. The general trends of BAR and carbonate free BAR are similar.
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Figure S3. A 200-kyr, 400-kyr and 800-kyr averaging smoothed BAR record at site 849 are
plotted to display the 3 intervals we identify in the record. Between 4.3 and 3 Ma BAR is
high, from 3 to 1 Ma a decreasing BAR trend is seen and from 1 Ma to present BAR is
increasing. A Gaussian fit for the 800 kyr smoothed data shows these clear transitions.
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Figure S4. MTM spectral analysis and the MTM evolution for (a) benthic δ18O and (b) the
BAR at site 849; (c) the coherency between benthicδ18O and the BAR; and (d) phase relation
between the records which is only shown for the windows in which the benthic 18O and the
BAR are coherent at the 80% level.
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Figure S5. Comparison between BAR and organic carbon accumulation rates at ODP site 849
between 1.8 and 2.6 Ma
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