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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0" article-type="research-article"><?xmltex \bartext{Research article}?>
  <front>
    <journal-meta><journal-id journal-id-type="publisher">BG</journal-id><journal-title-group>
    <journal-title>Biogeosciences</journal-title>
    <abbrev-journal-title abbrev-type="publisher">BG</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Biogeosciences</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1726-4189</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/bg-20-1725-2023</article-id><title-group><article-title>Fossil coccolith morphological attributes as a new proxy for deep ocean
carbonate chemistry</article-title><alt-title>Fossil coccolith morphology controlled by deep ocean carbon chemistry</alt-title>
      </title-group><?xmltex \runningtitle{Fossil coccolith morphology controlled by deep ocean carbon chemistry}?><?xmltex \runningauthor{A. Gerotto et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1 aff3">
          <name><surname>Gerotto</surname><given-names>Amanda</given-names></name>
          <email>gerottoamanda@alumni.usp.br</email>
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff2">
          <name><surname>Zhang</surname><given-names>Hongrui</given-names></name>
          <email>zhh@ethz.ch</email>
        <ext-link>https://orcid.org/0000-0003-1782-5976</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Nagai</surname><given-names>Renata Hanae</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-1358-5074</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Stoll</surname><given-names>Heather M.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2953-7835</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Figueira</surname><given-names>Rubens César Lopes</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-8945-4540</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Liu</surname><given-names>Chuanlian</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Hernández-Almeida</surname><given-names>Iván</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-9329-8357</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Oceanographic Institute, University of São Paulo, São Paulo,
Brazil</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Geological Institute, ETH Zurich, Zurich, Switzerland</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Center for Marine Studies, Federal University of Paraná, Pontal do
Paraná, Brazil</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>State Key Laboratory of Marine Geology, Tongji
University, Shanghai, China</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Amanda Gerotto (gerottoamanda@alumni.usp.br) and Hongrui
Zhang (zhh@ethz.ch)</corresp></author-notes><pub-date><day>9</day><month>May</month><year>2023</year></pub-date>
      
      <volume>20</volume>
      <issue>9</issue>
      <fpage>1725</fpage><lpage>1739</lpage>
      <history>
        <date date-type="received"><day>23</day><month>November</month><year>2022</year></date>
           <date date-type="rev-request"><day>7</day><month>December</month><year>2022</year></date>
           <date date-type="rev-recd"><day>4</day><month>April</month><year>2023</year></date>
           <date date-type="accepted"><day>7</day><month>April</month><year>2023</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2023 Amanda Gerotto et al.</copyright-statement>
        <copyright-year>2023</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023.html">This article is available from https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023.html</self-uri><self-uri xlink:href="https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023.pdf">The full text article is available as a PDF file from https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d1e159">Understanding the variations in past ocean carbonate chemistry is critical
to elucidating the role of the oceans in balancing the global carbon cycle.
The fossil shells from marine calcifiers present in the sedimentary record
are widely applied as past ocean carbon cycle proxies. However, the
interpretation of these records can be challenging due to the complex
physiological and ecological response to the carbonate system during an
organisms' life cycle and the potential for preservation at the
seafloor. Here we present a new dissolution proxy based on the morphological
attributes of coccolithophores from the Noëlaerhabdaceae family
(<italic>Emiliania huxleyi</italic> <inline-formula><mml:math id="M1" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 2 <inline-formula><mml:math id="M2" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, and small <italic>Gephyrocapsa</italic> spp.). To evaluate the influences of
coccolithophore calcification and coccolith preservation on fossil
morphology, we measured morphological attributes, mass, length, thickness,
and shape factor (ks) of coccoliths in a laboratory dissolution experiment
and surface sediment samples from the South China Sea. The coccolith
morphological data in surface sediments were also analyzed with environment
settings, namely surface temperature, nutrients, pH, chlorophyll <inline-formula><mml:math id="M3" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>
concentration, and carbonate saturation of bottom water by a redundancy
analysis. Statistical analysis indicates that carbonate saturation of the
deep ocean explains the highest proportion of variation in the morphological
data instead of the environmental variables of the surface ocean. Moreover,
the dissolution trajectory in the ks vs. length of coccoliths is comparable
between natural samples and laboratory dissolution experiments, emphasizing
the importance of carbonate saturation on fossil coccolith morphology.
However, the mean ks alone cannot fully explain the main variations observed
in our work. We propose that the normalized ks variation (<inline-formula><mml:math id="M4" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>), which is the ratio between the standard deviation of ks (<inline-formula><mml:math id="M5" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>) and the mean
ks,
could reflect different degrees of dissolution and size-selective
dissolution, influenced by the assemblage composition. Applied together
with the <inline-formula><mml:math id="M6" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> ratio, the ks factor of fossil coccoliths in deep
ocean sediments could be a potential proxy for a quantitative reconstruction
of past carbonate dissolution dynamics.</p>
  </abstract>
    
<funding-group>
<award-group id="gs1">
<funding-source>Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung</funding-source>
<award-id>200021_182070</award-id>
</award-group>
<award-group id="gs2">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>42188102</award-id>
<award-id>41930536</award-id>
</award-group>
<award-group id="gs3">
<funding-source>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior</funding-source>
<award-id>001</award-id>
</award-group>
</funding-group>
</article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e235">The ocean's large reservoir capacity of carbon dioxide (CO<inline-formula><mml:math id="M7" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) plays an
essential role in the carbon cycle and, consequently, in controlling
atmospheric CO<inline-formula><mml:math id="M8" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (Ridgwell and Zeebe, 2005; Wang et al., 2016). The
ocean CO<inline-formula><mml:math id="M9" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> is influenced by temperature, salinity, and biological
activity, including primary production, respiration, calcification, and
carbonate dissolution (Ridgwell and Zeebe, 2005; Sarmiento and Gruber, 2006;
Libes, 2009; Wang et al., 2016). When CO<inline-formula><mml:math id="M10" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> dissolves in water, the
ocean becomes more acidic, decreasing pH, carbonate ion concentration, and
carbonate saturation (<inline-formula><mml:math id="M11" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>). The carbonate compensation depth
(CCD) is the depth at which the rate of calcite dissolution is balanced by
the rate of calcite supply. The CCD is usually several hundred meters deeper
than the chemical lysocline, the saturation horizon of calcite, due to the
kinetics of dissolution (Ridgwell and Zeebe, 2005). Whereas the photic zone
is supersaturated with<?pagebreak page1726?> respect to calcite in most areas of the ocean, large
areas of the deep ocean are currently undersaturated because of the
increased solubility of calcite with pressure (Sulpis et al., 2018). As the
ocean continues absorbing larger amounts of CO<inline-formula><mml:math id="M12" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> from anthropogenic fuel
emissions, a shallowing of the CCD is expected for the next 100 years due to
the sharp decrease of carbonate saturation from surface to deep ocean
(Hönisch et al., 2012; USGCRP, 2017; Sulpis et al., 2018; IPCC, 2019).
Variations in the CCD on timescales from millions to several thousands of
years are an important process in determining the ocean's carbonate
chemistry and regulating atmospheric CO<inline-formula><mml:math id="M13" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (Emerson and Archer, 1990;
Pälike et al., 2006). Understanding the role of physical and
biogeochemical parameters in marine carbonates is therefore critical to
interpret the geological record correctly and to reconstruct variations in
the ocean carbon cycle in the past.</p>
      <p id="d1e304">The effects of carbonate chemistry changes and variations in the position of
the CCD in the geological past have been investigated using a wide array of
geochemical and microfossil proxies such as <inline-formula><mml:math id="M14" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C in benthic and
planktonic foraminifera (Zachos et al., 2005; Hönisch et al., 2012),
fragmentation indices of calcareous microfossils (Le and Shackleton, 1992;
Broerse et al., 2000; Flores et al., 2003), and CaCO<inline-formula><mml:math id="M15" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> content (Archer
et al., 2000; Pälike et al., 2012) in marine sediments. However, these
proxies do not provide quantitative estimates of past changes in carbonate
chemistry because additional ecological mechanisms determine the
calcification and preservation responses (Hönisch et al., 2012; Rae et
al., 2021). <inline-formula><mml:math id="M16" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">11</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>B provides a quantitative proxy for past
seawater pH (Hönisch et al., 2012), albeit additional carbonate
chemistry parameters impose some limits on the interpretation of the proxy
(Yu and Elderfield, 2007; Rae et al., 2021). Benthic <inline-formula><mml:math id="M17" display="inline"><mml:mrow class="chem"><mml:mi mathvariant="normal">B</mml:mi><mml:mo>/</mml:mo><mml:mi mathvariant="normal">Ca</mml:mi></mml:mrow></mml:math></inline-formula> provides a
quantitative proxy for deep sea CO<inline-formula><mml:math id="M18" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> concentration (Yu et al.,
2016). Yet both of these methods require monospecific foraminifera samples
for measurements, which are time-consuming to pick, and analyses are limited
to sediment samples that contain sufficient concentration of this
microfossil group.</p>
      <p id="d1e365">Coccolithophores, a group of single-celled calcifying algae, are
characterized by the production of calcite plates called coccoliths.
Coccoliths are the main constituent of marine biogenic sediments,
contributing up to 80 % of deep-sea carbonate fluxes (Young and Ziveri,
2000; Hay, 2004). Changes in coccoliths morphology, distribution, and
abundances are believed to record the evolution history of coccolithophores
and reflect the environmental conditions in the surface ocean (i.e., during
coccolith biomineralization) (Riebesell et al., 2000; Iglesias-Rodriguez et
al., 2008; Beaufort et al., 2011; Charalampopoulou et al., 2016;
Rigual-Hernández et al., 2020a). Because of that, coccoliths are widely
used in paleoclimate and paleoceanographic reconstructions (e.g., Bollman
and Herrle, 2007; Rickaby et al., 2007; Henderiks and Pagani, 2007; Bolton
et al., 2016). Several methods exist to estimate coccolithophore
calcification in the fossil record. Assumed proportional length and
thickness allowed for the first estimates of coccolith mass using microscope
techniques (Young and Ziveri, 2000). More recent methods based on the
optical properties of calcite under polarized light microscopy (circular and
linear) allowed a more precise estimate of the thickness of individual
coccoliths (Beaufort, 2005; Bollman, 2014; Fuertes et al., 2014;
Johnsen and Bollmann, 2020; Beaufort et al., 2021). The optical techniques
have been successfully employed in downcore records to estimate
coccolithophore calcification across time and evolutionary steps (e.g.,
Bolton et al., 2016; Beaufort et al., 2022; Guitián et al., 2022).
However, until now there has been no study that evaluates the response of
calcification patterns of fossil coccolithophores to both environmental
parameters controlling biomineralization in the photic zone and calcite
saturation state at the depth of burial.</p>
      <p id="d1e368">The South China Sea (SCS) is the largest marginal basin of the Western
Pacific, characterized by very dynamic spatial environmental conditions and
a steep bathymetric profile (Wang et al., 2015). Sediment records from this
basin have been used to study the response of coccolithophores to different
environmental variables. Previous studies found positive correlations
between coccolithophore biometry from plankton samples and nutrients and
light at the photic zone (Jin et al., 2016). Building on these results, but
applied to the sedimentary record, Su et al. (2020) explored the dependency
of coccolithophore weight and past surface ocean carbon chemistry parameters
and nutrient conditions. However, it has also been demonstrated that there
is intense coccolithophore dissolution above the lysocline in the SCS
(Fernando et al., 2007a). More recently, a study using plankton tow material
found that the degree of calcification in the coccolithophore species
<italic>Emiliania huxleyi</italic> was insensitive to carbonate chemistry in surface waters (Jin et al.,
2022a). This diversity of results calls for new studies that systematically
explore the drivers of coccolithophore morphology and calcification in the
fossil record.</p>
      <p id="d1e375">Here, we analyzed morphological attributes of fossil coccolithophores in
surface sediment samples in the SCS, located across spatial environmental
gradients in the surface ocean but also across a bathymetric transect
related to the calcite saturation at the seafloor which leads to lower
calcite saturation at the seafloor in deeper sites. In addition, we
evaluated the morphological variations of coccoliths under different
dissolution intensities in a laboratory experiment. Using an automated
algorithm to estimate coccolithophore calcification from images taken with a
microscope under cross-polarization, we show that scale-invariant measures
of coccolith thickness (shape factor – ks) from coccolithophores located
along a depth gradient in the SCS are highly correlated to the calcite
saturation state at the seafloor. We propose a new calibration to
reconstruct past calcite saturation based on ks which would enable the
quantitative reconstruction of changes in the calcite saturation in the deep
ocean and position of the CCD in the past.</p>
</sec>
<?pagebreak page1727?><sec id="Ch1.S2">
  <label>2</label><title>Oceanographic settings</title>
      <p id="d1e386">The SCS is a marginal basin located in the Western Pacific, connected to the
open ocean by shallow passages to the north and south (Fig. 1a). The Luzon
Strait in the north is the deepest (<inline-formula><mml:math id="M19" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 2000 m) and the
principal channel for water exchange between the SCS and the Pacific through
the Kuroshio Current (Qu et al., 2006; Liu et al., 2011; Wan and Jian,
2014). The modern surface circulation and hydrographic characteristics of
the SCS are directly associated with the seasonal changes promoted by the
East Asian Monsoon (EAM; Wang and Li, 2009). These seasonal hydrodynamic
patterns control the regional sea surface temperature (SST) distribution,
salinity, and nutrients (Fig. 1b–e, Wang and Li, 2009). The SST latitudinal
gradient is up to 2 <inline-formula><mml:math id="M20" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C with an annual average of 28–29 <inline-formula><mml:math id="M21" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C in the southern SCS and 26–27 <inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C in the north (Tian et al.,
2010). Salinity varies seasonally between 32.8–34.2 psu, with smaller
salinity variation in the north than in the south (Wang and Li, 2009).
Northern SCS primary productivity reflects the seasonality of the EAM with
more productive and well-mixed waters during the winter season (Zhang et
al., 2016), with higher chlorophyll <inline-formula><mml:math id="M23" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> concentration (0.65 mg Chl <inline-formula><mml:math id="M24" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> m<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and 600 mg C m<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> d<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) (Chen, 2005; Chen et al., 2006; Jin
et al., 2016).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><?xmltex \def\figurename{Figure}?><label>Figure 1</label><caption><p id="d1e476">Map of the South China Sea and location of core-top samples used
in the present study. Dots and squares represent stations located from
6 to 15<inline-formula><mml:math id="M28" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, and from 15 to 22<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N <bold>(a)</bold>. Vertical profiles along N–S (5 to 22<inline-formula><mml:math id="M30" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) transect
(dotted red line on <bold>(a</bold>) of <bold>(b)</bold> temperature, <bold>(c)</bold> salinity, <bold>(d)</bold> nitrate, <bold>(e)</bold> phosphate, <bold>(f)</bold> total alkalinity (TALK), and <bold>(g)</bold> total inorganic
carbon concentration (TCO<inline-formula><mml:math id="M31" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>), <bold>(h)</bold> pH and <bold>(i)</bold> <inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> calculated
at CO2SYS (Pierrot et al., 2006). See Sect. 3.3 for data sources.
The map and the vertical profiles were plotted with Ocean Data View (ODV)
software (Schlitzer, 2019). Colored dots in <bold>(b)</bold> indicate the
geographical position along the transect shown in <bold>(a)</bold> of the surface
sediment samples used in this study.</p></caption>
        <?xmltex \igopts{width=441.017717pt}?><graphic xlink:href="https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023-f01.png"/>

      </fig>

      <p id="d1e570">The modern SCS lysocline is approximately 1200 m, and the CCD lies between
3500 and 3800 m (Thunell et al., 1992; Wang et al., 1995; Luo et al., 2018).
In the northern SCS, surface waters (e.g., the upper 300 m) are
characterized by relatively low dissolved inorganic carbon (DIC) and total alkalinity (TALK) (Fig. 1f–g) and higher pH and
<inline-formula><mml:math id="M33" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, compared to deeper waters (Fig. 1h–i) (Chou et al., 2007;
Jin et al., 2016). Below 1000 m, the SCS across a N–S transect is
characterized by relatively homogeneous DIC, <inline-formula><mml:math id="M34" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C, and
[CO<inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>] (Chen et al., 2006; Qu et al., 2006; Chou et al., 2007;
Wan et al., 2020).</p>
      <p id="d1e611">The SCS deep waters originate from the North Pacific Deep Water (NPDW) that
penetrates the marginal basin through the Luzon Strait (Qu et al., 2006; Liu
et al., 2011; Wan and Jian, 2014; Wan et al., 2018). The route traced from
the Luzon Strait to the northwest suggests a predominantly cyclonic deep
circulation (Qu et al., 2006; Wang and Li, 2009). The deep-water residence
time of the SCS is estimated to be approximately 30–50 years, like that of
intermediate waters, 52 years (Chen et al., 2001). Due to this short
residence time, the SCS presents a homogeneous vertical profile; below 2000 m, there are no evident chemical stratification or changes compared to the
Pacific deep-water chemistry (<inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2000</mml:mn></mml:mrow></mml:math></inline-formula> m) characteristics (Chen et
al., 2001, 2006; Qu et al., 2009). The rapid residence time potentially
implies that, when replaced, deep waters occupy intermediate water levels
(between 300 and 1300 m), contributing to the circulation of intermediate
and shallow waters and ocean–atmosphere exchanges (Qu et al., 2009; Tian et
al., 2010).</p><?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Material and methods</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Material and sample treatments</title>
      <p id="d1e640">The core-top samples (<inline-formula><mml:math id="M37" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">28</mml:mn></mml:mrow></mml:math></inline-formula>) employed in this study were retrieved from
different depths in the basin of SCS (Fig. 1) during the R/V <italic>Sonne</italic> cruises
(SO-95) (Table 1). Toothpick samples from each location were used to prepare
smear slides, without any chemical or physical treatment, following standard
micropaleontological procedures (Marsaglia et al., 2015). Unfortunately, the
surface sediments were already depleted resulting in not having enough
material to perform dissolution experiments using the same samples. For the
dissolution experiment, we employed 240 mg of dry sediment obtained from a
Late Pleistocene sample from the Western Equatorial Pacific (Ocean Drilling
Program – ODP – 807A-2H-2W; 57–59 cm). The distribution of coccolithophore
species belonging to the Noëlaerhabdaceae family in the sample ODP 807 is 41 % of <italic>Gephyrocapsa oceanica</italic>, 34 % of <italic>Gephyrocapsa caribbeanica</italic>, and 23 % of small <italic>Gephyrocapsa</italic>. These taxa are thicker,
particularly <italic>G. caribbeanica</italic>, than the thinner Noëlaerhabdaceae species commonly found
in the SCS (e.g., <italic>E. huxleyi</italic>; Roth and Berger, 1975; Roth and Coulbourn, 1982). The
sediment sample was suspended in 120 mL Milli-Q water, and then the
suspension was separated into six centrifuge tubes, each with a volume of 20 mL and containing the equivalent of 40 mg of sediment. Sodium
hexametaphosphate (NaPO<inline-formula><mml:math id="M38" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M39" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">6</mml:mn></mml:msub></mml:math></inline-formula> (Calgon<sup>®</sup>) has
traditionally been used in pretreatment of samples with calcareous
microfossils, particularly foraminifera (Olson and Smart, 2004; Smart,
2008). However, it has been observed that application of this chemical agent
dissolves these microfossils due to complexation of Ca with phosphates, an
effect which varies with the exposure time (Feldmeijer et al., 2013).
Therefore, we added 100 mg of Calgon<sup>®</sup> into 100 mL Milli-Q
water, resulting in a concentration of 1.6 mM, to conduct our dissolution
experiment. Different volumes of Calgon<sup>®</sup> solution (0, 0.4,
0.8, 2, 4, 6 mL) were added to each of the six subsamples. The
Calgon<sup>®</sup> is very corrosive to the fine carbonate particles, and
the reaction between Calgon<sup>®</sup> and carbonate could be simplified
in two steps. First, the (NaPO<inline-formula><mml:math id="M40" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M41" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">6</mml:mn></mml:msub></mml:math></inline-formula> hydrolysis releases the sodium
trimetaphosphate (Na<inline-formula><mml:math id="M42" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>P<inline-formula><mml:math id="M43" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>O<inline-formula><mml:math id="M44" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">9</mml:mn></mml:msub></mml:math></inline-formula>). Then, the calcium in the solution
is exchanged with sodium and precipitate as Ca(PO<inline-formula><mml:math id="M45" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M46" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>,
CaNa(PO<inline-formula><mml:math id="M47" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M48" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, and CaNa<inline-formula><mml:math id="M49" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula>(PO<inline-formula><mml:math id="M50" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M51" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">6</mml:mn></mml:msub></mml:math></inline-formula>, strongly reducing
the free calcium concentration in the solution. The decrease in calcium
concentration promotes carbonate dissolution. In theory, adding 1 mol (NaPO<inline-formula><mml:math id="M52" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M53" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">6</mml:mn></mml:msub></mml:math></inline-formula> would result in the dissolution of 3 mol CaCO<inline-formula><mml:math id="M54" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> at
maximum. So, there could be <inline-formula><mml:math id="M55" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 80 % carbonate left even
after adding 6 mL Calgon<sup>®</sup> solution. The particles in all tubes
were kept suspended gently by a rotating disaggregation wheel as described
previously (Stoll and Ziveri, 2002) for 2 d to achieve a full reaction
between carbonate and (NaPO<inline-formula><mml:math id="M56" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>)<inline-formula><mml:math id="M57" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">6</mml:mn></mml:msub></mml:math></inline-formula>. Slides were prepared for coccolith
morphological analyses using the drop technique as<?pagebreak page1728?> described by Bordiga et
al. (2015) to trace the variations of coccolith amount during dissolution.</p>
</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Coccolith morphological parameters</title>
      <p id="d1e882">The morphological parameters of coccoliths in the dissolution experiment and
surface sediment were analyzed using a polarized microscope (Zeiss Axio
Scope HAL100), configured with circularly polarized light and a Zeiss
Plan-APOCHROMAT <inline-formula><mml:math id="M58" display="inline"><mml:mrow><mml:mn mathvariant="normal">100</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math></inline-formula>/1.4 oil objective, and a coupled camera (Zeiss Axiocam
506 Color). For every sample, at least 40 fields of view were photographed.
After species identification and selection of coccolithophores images
belonging to the Noëlaerhabdaceae family (<italic>Emiliania huxleyi</italic> <inline-formula><mml:math id="M59" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M60" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, and
small <italic>Gephyrocapsa</italic> spp.), each sample had between 100 and 400 (average of 250 per
sample) coccolithophore images. The relationship between the color of
coccolith images and thickness was calibrated using a reference calcite
wedge, the thickness of which had been carefully quantified
(González-Lemos et al., 2018). After calibration, all images were
analyzed in the Matlab-based software, C-Calcita (Fuertes et<?pagebreak page1729?> al., 2014), to
obtain the coccolith morphological parameters, including length, volume, and
mass. The length-shape factor of each coccolith, ks, was calculated using
the formula by Young and Ziveri (2000) based on the coccolith mass and
length obtained from C-Calcita:
            <disp-formula id="Ch1.Ex1"><mml:math id="M61" display="block"><mml:mrow><mml:mi mathvariant="normal">ks</mml:mi><mml:mo>=</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mi mathvariant="normal">mass</mml:mi><mml:mrow><mml:mn mathvariant="normal">2.7</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mi mathvariant="normal">length</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>.</mml:mo></mml:mrow></mml:math></disp-formula>
          Beyond the traditional morphological parameters, we calculated the
normalized ks variation, which is the ratio between the standard deviation of ks
(<inline-formula><mml:math id="M62" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>) over the mean ks (<inline-formula><mml:math id="M63" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>). The goal of this novel
parameter is to provide a new dimension to trace the dissolution process in
coccoliths, especially when the coccolith assemblage is diverse. For
example, if the coccoliths dissolve at different speeds in the assemblage
due to differential sensitivity to acidification, a small increase of
<inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> would be expected at the beginning of the dissolution because
of the <inline-formula><mml:math id="M65" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> increase and ks decrease. Then, after all fragile
coccoliths dissolve, leaving only thicker coccoliths in the assemblage, the
<inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> should show a decreasing trend which could be mainly caused by
a decrease in <inline-formula><mml:math id="M67" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e1013">Station, coordinate data, and water depth of core-top samples used
in this study.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Station</oasis:entry>
         <oasis:entry colname="col2">Longitude (E)</oasis:entry>
         <oasis:entry colname="col3">Latitude (N)</oasis:entry>
         <oasis:entry colname="col4">Water depth (m)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">17930</oasis:entry>
         <oasis:entry colname="col2">115.782</oasis:entry>
         <oasis:entry colname="col3">20.333</oasis:entry>
         <oasis:entry colname="col4">629</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17965</oasis:entry>
         <oasis:entry colname="col2">112.552</oasis:entry>
         <oasis:entry colname="col3">6.157</oasis:entry>
         <oasis:entry colname="col4">889</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17943</oasis:entry>
         <oasis:entry colname="col2">117.553</oasis:entry>
         <oasis:entry colname="col3">18.95</oasis:entry>
         <oasis:entry colname="col4">917</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17931</oasis:entry>
         <oasis:entry colname="col2">115.963</oasis:entry>
         <oasis:entry colname="col3">20.1</oasis:entry>
         <oasis:entry colname="col4">1005</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17944</oasis:entry>
         <oasis:entry colname="col2">113.637</oasis:entry>
         <oasis:entry colname="col3">18.658</oasis:entry>
         <oasis:entry colname="col4">1219</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17963</oasis:entry>
         <oasis:entry colname="col2">112.667</oasis:entry>
         <oasis:entry colname="col3">6.167</oasis:entry>
         <oasis:entry colname="col4">1233</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17932</oasis:entry>
         <oasis:entry colname="col2">116.037</oasis:entry>
         <oasis:entry colname="col3">19.952</oasis:entry>
         <oasis:entry colname="col4">1365</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17964</oasis:entry>
         <oasis:entry colname="col2">112.213</oasis:entry>
         <oasis:entry colname="col3">6.158</oasis:entry>
         <oasis:entry colname="col4">1556</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17960</oasis:entry>
         <oasis:entry colname="col2">115.558</oasis:entry>
         <oasis:entry colname="col3">10.12</oasis:entry>
         <oasis:entry colname="col4">1707</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17940</oasis:entry>
         <oasis:entry colname="col2">117.383</oasis:entry>
         <oasis:entry colname="col3">20.117</oasis:entry>
         <oasis:entry colname="col4">1728</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17961</oasis:entry>
         <oasis:entry colname="col2">112.332</oasis:entry>
         <oasis:entry colname="col3">8.507</oasis:entry>
         <oasis:entry colname="col4">1795</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17959</oasis:entry>
         <oasis:entry colname="col2">115.287</oasis:entry>
         <oasis:entry colname="col3">11.138</oasis:entry>
         <oasis:entry colname="col4">1957</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17962</oasis:entry>
         <oasis:entry colname="col2">112.082</oasis:entry>
         <oasis:entry colname="col3">7.182</oasis:entry>
         <oasis:entry colname="col4">1970</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17949</oasis:entry>
         <oasis:entry colname="col2">115.167</oasis:entry>
         <oasis:entry colname="col3">17.348</oasis:entry>
         <oasis:entry colname="col4">2195</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17957</oasis:entry>
         <oasis:entry colname="col2">115.31</oasis:entry>
         <oasis:entry colname="col3">10.9</oasis:entry>
         <oasis:entry colname="col4">2197</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17941</oasis:entry>
         <oasis:entry colname="col2">118.483</oasis:entry>
         <oasis:entry colname="col3">21.517</oasis:entry>
         <oasis:entry colname="col4">2201</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17951</oasis:entry>
         <oasis:entry colname="col2">113.41</oasis:entry>
         <oasis:entry colname="col3">16.288</oasis:entry>
         <oasis:entry colname="col4">2340</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17945</oasis:entry>
         <oasis:entry colname="col2">113.777</oasis:entry>
         <oasis:entry colname="col3">18.127</oasis:entry>
         <oasis:entry colname="col4">2404</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17955</oasis:entry>
         <oasis:entry colname="col2">112.177</oasis:entry>
         <oasis:entry colname="col3">14.122</oasis:entry>
         <oasis:entry colname="col4">2404</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17939</oasis:entry>
         <oasis:entry colname="col2">117.455</oasis:entry>
         <oasis:entry colname="col3">19.97</oasis:entry>
         <oasis:entry colname="col4">2473</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17958</oasis:entry>
         <oasis:entry colname="col2">115.082</oasis:entry>
         <oasis:entry colname="col3">11.622</oasis:entry>
         <oasis:entry colname="col4">2581</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17934</oasis:entry>
         <oasis:entry colname="col2">116.462</oasis:entry>
         <oasis:entry colname="col3">19.032</oasis:entry>
         <oasis:entry colname="col4">2665</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17938</oasis:entry>
         <oasis:entry colname="col2">117.538</oasis:entry>
         <oasis:entry colname="col3">19.787</oasis:entry>
         <oasis:entry colname="col4">2835</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17925</oasis:entry>
         <oasis:entry colname="col2">119.047</oasis:entry>
         <oasis:entry colname="col3">19.853</oasis:entry>
         <oasis:entry colname="col4">2980</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17956</oasis:entry>
         <oasis:entry colname="col2">112.588</oasis:entry>
         <oasis:entry colname="col3">13.848</oasis:entry>
         <oasis:entry colname="col4">3387</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17937</oasis:entry>
         <oasis:entry colname="col2">117.665</oasis:entry>
         <oasis:entry colname="col3">19.5</oasis:entry>
         <oasis:entry colname="col4">3428</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17946</oasis:entry>
         <oasis:entry colname="col2">114.25</oasis:entry>
         <oasis:entry colname="col3">18.125</oasis:entry>
         <oasis:entry colname="col4">3465</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">17936</oasis:entry>
         <oasis:entry colname="col2">117.12</oasis:entry>
         <oasis:entry colname="col3">18.767</oasis:entry>
         <oasis:entry colname="col4">3809</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table><?xmltex \gdef\@currentlabel{1}?></table-wrap>

<?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Environmental data for surface sediment</title>
      <p id="d1e1485">Annual means of different physical, chemical, and biological variables in
both 50 m depth and bottom water for the location of the surface samples
(Table 1) were extracted from different databases, interpolated to the
geographical location of the surface sediment samples. Here the 50 m depth
was selected because it is the depth at which the highest concentration of
Noëlaerhabdaceae coccolithophorid is observed in the SCS (Jin et al.,
2016). Seawater temperature, salinity, nitrate, and phosphate concentrations
(used as a proxy of phytoplankton) at 50 m were obtained from the World Ocean Atlas 2001 (Fig. 1b, c, d, e; Conkright et al., 2002). Sea surface chlorophyll <inline-formula><mml:math id="M68" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> concentration data were based on MODIS
data (2003–2016) extracted from Oregon State University Ocean Productivity
(<uri>http://www.science.oregonstate.edu/ocean.productivity/</uri>, last access: 16 July 2021). Annual averaged
concentrations of total alkalinity (TALK) and dissolved inorganic carbon
(TCO<inline-formula><mml:math id="M69" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) were extracted from Goyet et al. (2000) (Fig. 1f, g). Then the
carbonate ion concentration, pH (Fig. 1h), and <inline-formula><mml:math id="M70" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>CO<inline-formula><mml:math id="M71" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> for the depth of 50 m
and <inline-formula><mml:math id="M72" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> for the seafloor depth were calculated by CO2SYS macro
for Excel<sup>®</sup> (Pierrot et al., 2006) (Fig. 1i) using salinity,
temperature, pressure, total phosphate, total silicate, TALK, and TCO<inline-formula><mml:math id="M73" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
at the corresponding depth (50 m or depth of the surface sediment sample).
The light intensity at 50 m water depth was calculated using a model of
penetration of photosynthetic active radiation (PAR) from surface to depth
(Buiteveld, 1995; Murtugudde et al., 2002), monthly climatologies of PAR
from the MODIS ocean database (<uri>http://oceancolor.gsfc.nasa.gov/cgi/l3</uri>, last access: 16 July 2021), and
the diffuse attenuation coefficient for downwelling irradiance at 490 nm
(Kd490) and Eq. (1) in Lin et al. (2016).</p>
</sec>
<sec id="Ch1.S3.SS4">
  <label>3.4</label><title>Statistical analysis</title>
      <p id="d1e1558">Pearson correlation and redundancy analysis (RDA) were employed to explore
the relationship between morphological features of the coccoliths in surface
sediment samples and the environmental data. All statistical analyses were
performed using the PAST 4.06 software (Hammer et al., 2001).</p>
</sec>
</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Results</title>
<sec id="Ch1.S4.SS1">
  <label>4.1</label><title>Variations of coccoliths morphology in the dissolution experiment</title>
      <?pagebreak page1730?><p id="d1e1577">In the dissolution experiment, mean ks decreased with increasing volume of
Calgon<sup>®</sup> solution (Fig. 2a). The mean ks varied between 0.12 (0 mL Calgon<sup>®</sup>) and 0.04 (6 mL Calgon<sup>®</sup>) (Fig. 2a).
The <inline-formula><mml:math id="M74" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> represents variation in preservation among coccoliths
within each sample. Higher differences in <inline-formula><mml:math id="M75" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> were observed in samples
containing 2, 4, 0.8, 0.4, 0, and 6 mL, respectively (Fig. 2b). Increasing the amount of Calgon<sup>®</sup> solution up to 2 mL
showed a decrease in mean ks and an increase in <inline-formula><mml:math id="M76" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>. Samples with 4
and 6 mL Calgon<sup>®</sup> solution showed a reduction in mean ks and
<inline-formula><mml:math id="M77" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> among coccoliths (Fig. 2b). The lowest mean ks (0.04) and the
maximum mean length (3.95 <inline-formula><mml:math id="M78" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) were recorded under the higher
Calgon<sup>®</sup> solution (6 mL) amount (Fig. 2c). Increased amounts of
Calgon<sup>®</sup> solution also resulted in a gradual increase in
coccolith length leading to a negative correlation between length and ks
(<inline-formula><mml:math id="M79" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.68</mml:mn></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>), but this was not significant due to the small
number of observations (Fig. 2c).</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><?xmltex \def\figurename{Figure}?><label>Figure 2</label><caption><p id="d1e1674">Coccolith morphological variations in the dissolution experiment.
<bold>(a)</bold> Box plots of the median (horizontal line inside the boxes), minimal and
maximal values of coccoliths mean ks (vertical bars) under the different
volumes of Calgon<sup>®</sup> solution. <bold>(b)</bold> Scatter plot of mean ks and
<inline-formula><mml:math id="M81" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>, and <bold>(c)</bold> linear correlation and correlation coefficient (<inline-formula><mml:math id="M82" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>) between mean ks and mean length.</p></caption>
          <?xmltex \igopts{width=412.564961pt}?><graphic xlink:href="https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023-f02.png"/>

        </fig>

</sec>
<sec id="Ch1.S4.SS2">
  <label>4.2</label><title>Variations in coccolith morphology in natural conditions</title>
      <p id="d1e1730">Overall, the mean ks, thickness, and volume in the core-top sampling
stations (Fig. 3) presented higher values in shallower depths. The mean ks
varied between 0.03 and 0.07, and the mean thickness was between 0.25 and
0.44 <inline-formula><mml:math id="M83" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, with maximum values recorded at station 17931 located in
northern SCS at 1005 m water depth. The mean length of coccolith varied
between 3.23 and 3.78 <inline-formula><mml:math id="M84" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, with the highest values recorded at 2195 m
water depth (site 17949) in northern SCS but without a significant trend
along depths. The mean volume of coccoliths ranged between 1.70 and 2.97 <inline-formula><mml:math id="M85" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula>, and the mean mass was between 4.61 and 8.03 pg, with maximum
values for both recorded in the shallowest station (e.g., 17930), at 629 m
water depth in northern SCS.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><?xmltex \def\figurename{Figure}?><label>Figure 3</label><caption><p id="d1e1768">Coccolith mean ks, thickness (<inline-formula><mml:math id="M87" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), length (<inline-formula><mml:math id="M88" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), volume
(<inline-formula><mml:math id="M89" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m<inline-formula><mml:math id="M90" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula>), and mass (pg) in surface samples from SCS. The sampling
stations are distributed along the <inline-formula><mml:math id="M91" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> axis according to their depth, sorted
from the shallowest to the deepest.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023-f03.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><?xmltex \def\figurename{Figure}?><label>Figure 4</label><caption><p id="d1e1819">Morphological parameters of coccolith in surface sediments. <bold>(a)</bold> Scatter plot between mean ks and <inline-formula><mml:math id="M92" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>, and <bold>(b)</bold> linear correlation and
correlation coefficient (<inline-formula><mml:math id="M93" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>) between mean ks and mean length.
Shaded arrows in <bold>(a)</bold> represent ideal trajectories of the normalized ks
variation (mean ks vs. <inline-formula><mml:math id="M94" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>) as shown in Fig. 2b, to interpret the
trends in the surface sediment samples. Note that the mean ks of Figs. 2
and 4 are different due to the higher abundance of the species <italic>G. caribbeanica</italic>, with higher
thickness, in the sample for the dissolution experiment.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023-f04.png"/>

        </fig>

      <p id="d1e1882">In general, the degree of dissolution varied according to the depth of the
sediment samples. The calcite saturation, <inline-formula><mml:math id="M95" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, decreases with
colder temperature, higher pressure, and higher CO<inline-formula><mml:math id="M96" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration in
deep ocean. The normalized ks variation presents different trajectories
associated with light, strong, or no dissolution (Fig. 4a). The shallowest
stations in the south (<inline-formula><mml:math id="M97" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M98" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) and north SCS (<inline-formula><mml:math id="M99" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M100" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) show a linear and increasing trend between ks and <inline-formula><mml:math id="M101" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>. For the samples below 2000 m, there is no clear pattern of variation
related to the mean ks standard deviation. However, samples below 3000 m are
mainly located on the left upper part of the plot, in a similar position as
the samples treated with 4 and 6 mL of Calgon<sup>®</sup> in the
normalized ks variation comparison of the dissolution experiment (Fig. 3b).
The mean ks vs. mean length shows a negative correlation (<inline-formula><mml:math id="M102" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.62</mml:mn></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M103" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>), with the deepest samples showing larger size coccoliths and
lower mean ks (Fig. 4b).</p>
      <p id="d1e1985">We analyzed the correlations between the biological and environmental
datasets (Table 2). Although some of the surface variables were
autocorrelated (e. g., TALK–salinity, pH–<inline-formula><mml:math id="M104" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>CO<inline-formula><mml:math id="M105" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, and nitrate–phosphate),
they were included in our analyses because some studies have identified a
strong influence of these parameters on coccolith morphology during the
life-cycle (e.g., Chen et al., 2007; Jin et al., 2016). Significant
correlations can be found (<inline-formula><mml:math id="M106" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>) between several morphological
parameters of coccolith and bottom water carbonate chemistry (<inline-formula><mml:math id="M107" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>), with a correlation coefficient <inline-formula><mml:math id="M108" display="inline"><mml:mi>r</mml:mi></mml:math></inline-formula> <inline-formula><mml:math id="M109" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.67 between mean ks and
<inline-formula><mml:math id="M110" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M111" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.66</mml:mn></mml:mrow></mml:math></inline-formula> between mean volume and <inline-formula><mml:math id="M112" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, and <inline-formula><mml:math id="M113" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.66</mml:mn></mml:mrow></mml:math></inline-formula> between mass and <inline-formula><mml:math id="M114" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>. The mean thickness of the
coccolith shows a significant correlation with <inline-formula><mml:math id="M115" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> at the
sample depth (<inline-formula><mml:math id="M116" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.41</mml:mn></mml:mrow></mml:math></inline-formula>), and with the concentrations of nutrients nitrate
and phosphate at 50 m (<inline-formula><mml:math id="M117" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.44</mml:mn></mml:mrow></mml:math></inline-formula> and 0.4, respectively). Surprisingly, the
mean length showed no significant correlation to any environmental variables
except with PAR (<inline-formula><mml:math id="M118" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.35</mml:mn></mml:mrow></mml:math></inline-formula>).</p>
      <p id="d1e2147">The results of RDA can provide another critical perspective on the control
of environmental variables on coccolith morphology. The RDA1 and RDA2
explain together 58.3 % of the total variations in coccolith
morphological data. The surface sediment samples, color-coded by different
depth intervals, are distributed along the axis of RDA1, which is the most
important and explains 54.6 % of the total variance (Fig. 5a). Among the
environmental variables, <inline-formula><mml:math id="M119" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> shows the highest correlation to
RDA1 (<inline-formula><mml:math id="M120" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.67</mml:mn></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M121" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>). The results of both the correlation
analyses and the RDA show that <inline-formula><mml:math id="M122" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> in bottom water is the most
important environmental variable driving the morphological dataset, which
shows a high correlation with mean ks (<inline-formula><mml:math id="M123" display="inline"><mml:mrow><mml:mi>r</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.69</mml:mn></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M124" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>) and
could explain up to 47 % (<inline-formula><mml:math id="M125" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.47</mml:mn></mml:mrow></mml:math></inline-formula>) of the variance observed in
mean ks (Fig. 5b). The RDA2 explained 3.69 % of the variance and is
mainly correlated to the salinity, temperature, pH, phosphate, TALK, and
<inline-formula><mml:math id="M126" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>CO<inline-formula><mml:math id="M127" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (Fig. 5a). The null response of coccolith length to any
environmental parameter is also observed in the RDA plot by its position
near the center of the ordination space, significantly contrasting with
other morphological parameters (Fig. 5a).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2" specific-use="star"><?xmltex \currentcnt{2}?><label>Table 2</label><caption><p id="d1e2257">Correlation matrix (<inline-formula><mml:math id="M128" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value and Pearson correlation) between
biological and environmental variables. Bold values indicate significant
correlations (with <inline-formula><mml:math id="M129" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>).</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="11">
     <oasis:colspec colnum="1" colname="col1" align="justify" colwidth="2cm"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right" colsep="1"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:colspec colnum="10" colname="col10" align="right"/>
     <oasis:colspec colnum="11" colname="col11" align="right"/>
     <oasis:thead>
       <oasis:row>

         <?xmltex \mrwidth{2cm}?><oasis:entry colname="col1" morerows="1">Environmental/ <?xmltex \hack{\newline}?> biological</oasis:entry>

         <oasis:entry rowsep="1" namest="col2" nameend="col6" align="center" colsep="1"><inline-formula><mml:math id="M131" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value </oasis:entry>

         <oasis:entry rowsep="1" namest="col7" nameend="col11" align="center"><inline-formula><mml:math id="M132" display="inline"><mml:mi>r</mml:mi></mml:math></inline-formula></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col2">Mean</oasis:entry>

         <oasis:entry colname="col3">Mean</oasis:entry>

         <oasis:entry colname="col4">Mean</oasis:entry>

         <oasis:entry colname="col5">Mean</oasis:entry>

         <oasis:entry colname="col6">Mean</oasis:entry>

         <oasis:entry colname="col7">Mean</oasis:entry>

         <oasis:entry colname="col8">Mean</oasis:entry>

         <oasis:entry colname="col9">Mean</oasis:entry>

         <oasis:entry colname="col10">Mean</oasis:entry>

         <oasis:entry colname="col11">Mean</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col2">ks</oasis:entry>

         <oasis:entry colname="col3">thickness</oasis:entry>

         <oasis:entry colname="col4">length</oasis:entry>

         <oasis:entry colname="col5">volume</oasis:entry>

         <oasis:entry colname="col6">mass</oasis:entry>

         <oasis:entry colname="col7">ks</oasis:entry>

         <oasis:entry colname="col8">thickness</oasis:entry>

         <oasis:entry colname="col9">length</oasis:entry>

         <oasis:entry colname="col10">volume</oasis:entry>

         <oasis:entry colname="col11">mass</oasis:entry>

       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>

         <oasis:entry colname="col1">Salinity</oasis:entry>

         <oasis:entry colname="col2">0.79</oasis:entry>

         <oasis:entry colname="col3">0.07</oasis:entry>

         <oasis:entry colname="col4">0.87</oasis:entry>

         <oasis:entry colname="col5">0.86</oasis:entry>

         <oasis:entry colname="col6">0.86</oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M133" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.05</oasis:entry>

         <oasis:entry colname="col8">0.34</oasis:entry>

         <oasis:entry colname="col9">0.03</oasis:entry>

         <oasis:entry colname="col10"><inline-formula><mml:math id="M134" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.03</oasis:entry>

         <oasis:entry colname="col11"><inline-formula><mml:math id="M135" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.03</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">Temperature</oasis:entry>

         <oasis:entry colname="col2">0.94</oasis:entry>

         <oasis:entry colname="col3">0,04</oasis:entry>

         <oasis:entry colname="col4">1.0</oasis:entry>

         <oasis:entry colname="col5">0.90</oasis:entry>

         <oasis:entry colname="col6">0.90</oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M136" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.01</oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M137" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.39</oasis:entry>

         <oasis:entry colname="col9">0.00</oasis:entry>

         <oasis:entry colname="col10"><inline-formula><mml:math id="M138" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.02</oasis:entry>

         <oasis:entry colname="col11"><inline-formula><mml:math id="M139" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.02</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">Phosphate</oasis:entry>

         <oasis:entry colname="col2">0.88</oasis:entry>

         <oasis:entry colname="col3">0.03</oasis:entry>

         <oasis:entry colname="col4">0.63</oasis:entry>

         <oasis:entry colname="col5">0.96</oasis:entry>

         <oasis:entry colname="col6">0.96</oasis:entry>

         <oasis:entry colname="col7">0.03</oasis:entry>

         <oasis:entry colname="col8"><bold>0.41</bold></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M140" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.09</oasis:entry>

         <oasis:entry colname="col10"><inline-formula><mml:math id="M141" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.01</oasis:entry>

         <oasis:entry colname="col11"><inline-formula><mml:math id="M142" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.01</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">Nitrate</oasis:entry>

         <oasis:entry colname="col2">0.36</oasis:entry>

         <oasis:entry colname="col3">0.02</oasis:entry>

         <oasis:entry colname="col4">0.30</oasis:entry>

         <oasis:entry colname="col5">0.71</oasis:entry>

         <oasis:entry colname="col6">0.71</oasis:entry>

         <oasis:entry colname="col7">0.17</oasis:entry>

         <oasis:entry colname="col8"><bold>0.44</bold></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M143" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.20</oasis:entry>

         <oasis:entry colname="col10">0.07</oasis:entry>

         <oasis:entry colname="col11">0.07</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">TALK</oasis:entry>

         <oasis:entry colname="col2">0.53</oasis:entry>

         <oasis:entry colname="col3">0.13</oasis:entry>

         <oasis:entry colname="col4">0.70</oasis:entry>

         <oasis:entry colname="col5">0.60</oasis:entry>

         <oasis:entry colname="col6">0.60</oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M144" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.12</oasis:entry>

         <oasis:entry colname="col8">0.28</oasis:entry>

         <oasis:entry colname="col9">0.07</oasis:entry>

         <oasis:entry colname="col10"><inline-formula><mml:math id="M145" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.10</oasis:entry>

         <oasis:entry colname="col11"><inline-formula><mml:math id="M146" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.10</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">Chlorophyll <inline-formula><mml:math id="M147" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col2">0.26</oasis:entry>

         <oasis:entry colname="col3">0.18</oasis:entry>

         <oasis:entry colname="col4">0.88</oasis:entry>

         <oasis:entry colname="col5">0.18</oasis:entry>

         <oasis:entry colname="col6">0.18</oasis:entry>

         <oasis:entry colname="col7">0.22</oasis:entry>

         <oasis:entry colname="col8">0.25</oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M148" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.02</oasis:entry>

         <oasis:entry colname="col10">0.26</oasis:entry>

         <oasis:entry colname="col11">0.26</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">PAR</oasis:entry>

         <oasis:entry colname="col2">0.28</oasis:entry>

         <oasis:entry colname="col3">0.05</oasis:entry>

         <oasis:entry colname="col4">0.06</oasis:entry>

         <oasis:entry colname="col5">0.50</oasis:entry>

         <oasis:entry colname="col6">0.50</oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M149" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.21</oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M150" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.38</oasis:entry>

         <oasis:entry colname="col9">0.35</oasis:entry>

         <oasis:entry colname="col10"><inline-formula><mml:math id="M151" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.13</oasis:entry>

         <oasis:entry colname="col11"><inline-formula><mml:math id="M152" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.13</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">pH</oasis:entry>

         <oasis:entry colname="col2">0.18</oasis:entry>

         <oasis:entry colname="col3">0.31</oasis:entry>

         <oasis:entry colname="col4">0.38</oasis:entry>

         <oasis:entry colname="col5">0.24</oasis:entry>

         <oasis:entry colname="col6">0.24</oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M153" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.26</oasis:entry>

         <oasis:entry colname="col8">0.19</oasis:entry>

         <oasis:entry colname="col9">0.17</oasis:entry>

         <oasis:entry colname="col10"><inline-formula><mml:math id="M154" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.22</oasis:entry>

         <oasis:entry colname="col11"><inline-formula><mml:math id="M155" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.22</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"><inline-formula><mml:math id="M156" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>CO<inline-formula><mml:math id="M157" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col2">0.16</oasis:entry>

         <oasis:entry colname="col3">0.33</oasis:entry>

         <oasis:entry colname="col4">0.38</oasis:entry>

         <oasis:entry colname="col5">0.21</oasis:entry>

         <oasis:entry colname="col6">0.21</oasis:entry>

         <oasis:entry colname="col7">0.27</oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M158" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.19</oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M159" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.17</oasis:entry>

         <oasis:entry colname="col10">0.24</oasis:entry>

         <oasis:entry colname="col11">0.24</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"><inline-formula><mml:math id="M160" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col2"><bold>0.00</bold></oasis:entry>

         <oasis:entry colname="col3"><bold>0.03</bold></oasis:entry>

         <oasis:entry colname="col4">0.05</oasis:entry>

         <oasis:entry colname="col5"><bold>0.00</bold></oasis:entry>

         <oasis:entry colname="col6"><bold>0.00</bold></oasis:entry>

         <oasis:entry colname="col7"><bold>0.67</bold></oasis:entry>

         <oasis:entry colname="col8"><bold>0.41</bold></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M161" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.36</oasis:entry>

         <oasis:entry colname="col10"><bold>0.66</bold></oasis:entry>

         <oasis:entry colname="col11"><bold>0.66</bold></oasis:entry>

       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table><table-wrap-foot><p id="d1e2279">TALK – total alkalinity, PAR – photosynthetic active radiation, and
<inline-formula><mml:math id="M130" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> – carbonate saturation.</p></table-wrap-foot><?xmltex \gdef\@currentlabel{2}?></table-wrap>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><?xmltex \currentcnt{5}?><?xmltex \def\figurename{Figure}?><label>Figure 5</label><caption><p id="d1e2985">Redundancy analysis (RDA) ordinations for environmental variables,
and morphological measurements <bold>(a)</bold> and <bold>(b)</bold> linear correlation and
correlation coefficient (<inline-formula><mml:math id="M162" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>) between <inline-formula><mml:math id="M163" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> at
bottom depths and mean ks from surface samples.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://bg.copernicus.org/articles/20/1725/2023/bg-20-1725-2023-f05.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S5">
  <label>5</label><title>Discussion</title>
<sec id="Ch1.S5.SS1">
  <label>5.1</label><title>Comparison between laboratory dissolution experiment and natural samples</title>
      <p id="d1e3040">In this study, we evaluate fossil coccolith responses to dissolution under
laboratory experiments and field settings. In the dissolution experiment, ks
values are higher than the modern coccoliths in the SCS due to the higher
abundance of the relatively thicker <italic>G. caribbeanica</italic> in the downcore sediment sample. Though
the absolute values of ks cannot be directly compared between the
dissolution experiment (Fig. 2b) and surface sediments (Fig. 4a), the
trajectory of morphological variations during the dissolution experiment
does provide important diagnostic information to explain phenomena observed
in the surface sediment samples.</p>
      <?pagebreak page1732?><p id="d1e3046">First, the phenomenon that coccolith length increased with the decrease of
ks could be observed in both the dissolution experiment (Fig. 2c) and
natural surface sediments (Fig. 4b). The laboratory experiment showed that
under controlled conditions (known changes in water chemistry and uniform
species composition), the coccolith morphology variations (mean length and
mean ks) reflected different degrees of dissolution. We also observed a
length-related dissolution pattern, where smaller coccoliths gradually
dissolve with the increase in Calgon<sup>®</sup> concentration, leading
to a higher average length but a lower mean ks. The mean ks and mean length
relationships in the surface samples (Fig. 4b) show a similar trend to the
laboratory observations (Fig. 2c). Thus, the observed trend and the largest
size and lowest ks in the surface sediment samples are explained by the
dissolution of the smallest species due to the lower <inline-formula><mml:math id="M164" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> at the
deepest samples and increasing the abundance of the larger coccoliths.</p>
      <p id="d1e3063">Second, changes in the <inline-formula><mml:math id="M165" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> ratio in the dissolution experiment
reflect a slight and gradual increase in dissolution and then a decrease
with the highest concentrations of Calgon<sup>®</sup> (Fig. 2c). In the
laboratory experiment, the subsample with no Calgon<sup>®</sup> solution
presented well-preserved coccoliths with high mean ks and a small standard
deviation. As the amount of Calgon<sup>®</sup> solution added to each
subsample increases, small coccoliths start dissolving preferentially,
decreasing the mean ks and increasing the standard deviation (Fig. 2b). With
higher amounts of Calgon<sup>®</sup> solution (4 and 6 mL), the small
coccoliths are completely dissolved, resulting in an assemblage dominated by
larger coccoliths (Fig. 2c). Under these highest dissolution stages, the
larger coccoliths are also partially dissolved, then both mean ks and <inline-formula><mml:math id="M166" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> decrease (Fig. 2b). In this way, the <inline-formula><mml:math id="M167" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> reflects how differential
dissolution size selection affects the composition of the<?pagebreak page1733?> assemblages.
Hence, samples that are more (less) susceptible to dissolution result in
more homogeneous (heterogeneous) assemblages regarding carbonate
preservation.</p>
      <p id="d1e3107">However, the trajectory of the normalized ks variation in surface sediments
seems more complex than in the dissolution experiment (Fig. 4a). First,
there is a group of samples with a positive correlation between <inline-formula><mml:math id="M168" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>
and ks from shallow areas of the north and south SCS. The depth of samples
from northern and southern SCS regions is similar, so we argue that this
feature is not caused by dissolution but due to the assemblage composition
differences in both parts of the SCS. The coccolithophores have multistage
blooms in the north SCS, with a peak of <italic>G. oceanica</italic> in late winter, when
coccolithophore fluxes are highest due to strong water column mixing and
renewed nutrient inventory, and another of <italic>E. huxleyi</italic> in early spring (Chen et al.,
2007; Jin et al., 2019). In contrast, <italic>E. huxleyi</italic> is the dominant species in the more
oligotrophic south SCS (Fernando et al., 2007b) due to its higher
competitiveness in situations of lower nutrient concentration (particularly
nitrate) compared to <italic>G. oceanica</italic> (Eppley et al., 1969; Rhodes et al., 1995). So, even
without any influence from dissolution, the assemblages in the north SCS
should feature a higher species diversity and, thereby, a higher <inline-formula><mml:math id="M169" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> compared with the coccolith in the south SCS. Hence, the variety of the
coccolith assemblages in the surface sediment samples results in different
trajectories in the normalized ks variation plotting. But the general trend
of the normalized ks variation in surface sediment is still following the
trends observed in the dissolution experiment: (1) ks decreases with
dissolution, (2) <inline-formula><mml:math id="M170" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> increases slightly when dissolution starts, and
(3) then it decreases with greater dissolution.</p>
</sec>
<sec id="Ch1.S5.SS2">
  <label>5.2</label><title>Sedimentary record of coccolith morphology: calcification vs. dissolution
factors</title>
      <p id="d1e3173">Previous studies have evaluated changes in the calcification of
Noëlaerhabdaceae coccoliths in glacial–interglacial cycles through
analyses of the coccolith mass and attributed morphological variations
mainly to water column nutrient availability and carbonate chemistry
parameters, related to the coccolithophores physiological response (e.g.,
Beaufort et al., 2011). Su et al. (2020) found that the environmental
dynamics of the surface photic zone controlled Noëlaerhabdaceae
coccoliths' calcification in northern SCS (MD05-2904). Similarly, higher
calcite production recorded by increased coccolith mass has been attributed
to the increased [CO<inline-formula><mml:math id="M171" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>] in the surface water column in the South
Indian Ocean and North Atlantic Ocean in modern sediments (Beaufort et al.,
2011). Dissolution effects were thought to be less likely drivers of changes
in the morphology of coccolith (Beaufort et al., 2011; Su et al., 2020),
which is a reasonable assumption for the coccoliths depositing in shallow
sediments above the lysocline. These interpretations are partially sustained
by the findings of Beaufort et al. (2007), who found no significant
coccolith dissolution during the settling in sediment traps deployed between
250 and 2500 m. The former study proposed that most of the dissolution
occurs in the euphotic zone and possibly in the guts of grazers, therefore,
discarding the impact of bottom water chemistry and/or post-burial processes
on coccolithophore weight.</p>
      <?pagebreak page1734?><p id="d1e3191"><?xmltex \hack{\newpage}?>In our set of samples in the SCS, the RDA results show that mean thickness
and length significantly correlate to nitrate and phosphate at 50 m (Table 2). This observation agrees with Jin et al. (2016), who found that biometric
attributes of <italic>E. huxleyi</italic> correlated with nutrient concentrations in the plankton
samples in the East China Sea (ECS). Nutrient variables are important for
coccolithophore calcification (Raven and Crawfurd, 2012) and morphological
parameters, at least in species of the Noëlaerhabdaceae family
(Båtvik et al., 1997; Paasche, 1998). However, based on the
extended evidence of our study, including carbonate chemistry at the depth
of the sediment samples in the SCS, we observe evidence that several of the
morphological parameters measured are not just influenced by primary
biomineralization. Still, abiogenic post- or syn-depositional processes
override this signal in the sediment samples in this region. The highest
correlations between coccolith morphology, namely mean ks, volume, and
thickness, with the bottom water calcite saturation, <inline-formula><mml:math id="M172" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>,
indicates that the calcium carbonate preservation conditions could strongly
override some of the morphological parameters in fossil coccoliths (Table 2,
Fig. 5a). We suggest that the mean ks of coccolith could be a potential
proxy for the carbonate dissolution in the bottom water, especially in sites
near or below the lyscocline.</p>
      <p id="d1e3209">Carbonate dissolution may also happen within the shallow sediment (Sulpis et
al., 2021; Subhas et al., 2022). Based on our current dataset and using only
the morphological variations, we cannot distinguish where the dissolution
happens at the time of deposition in the sediment water interface, or
post-burial in the first centimeters of the seafloor sediment. For the deep ocean
deposits with lower sedimentary rates, such as the deepest parts of the SCS
(Huang and Wang, 2006), the exposure time of particles to bottom water
should be longer than that along the continental slope. Thus, we suggest
that the major dissolution in the deep SCS happens on the sediment–water
boundary instead of within pore water. Interestingly, the ks of coccolith in
the surface sediment of the ECS is much lower, as low as 0.01 (Jin et al.,
2019), than those in our study, which is higher than 0.04. However, the ks
of coccoliths during the laboratory dissolution experiment performed by Jin
et al. (2019; Fig. 9a in that study) shows the same range as our
measurements. The ECS samples are from the continental shelf with high
sedimentary rates and organic carbon content (Jin et al., 2019). In these
settings, the coccoliths continuously dissolve after being buried within the
first centimeters of the seafloor sediments in response to organic matter
remineralization and CO<inline-formula><mml:math id="M173" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> release, resulting in a <inline-formula><mml:math id="M174" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 30 %–50 % decrease in coccolith mass (Jin et al., 2019). Therefore, the
sedimentary environment has to be individually evaluated to understand which
process is controlling the dissolution of coccolithophores at the seafloor.
More detailed work, such as in situ pore water chemistry measurements, would
be necessary to fully reveal the fate of coccolith dissolution in different
burial scenarios (Holcová and Scheiner, 2023).</p>
      <p id="d1e3228">Among all the morphological parameters, we find the mean ks of coccolith is
a more robust dissolution proxy compared to the other measured morphological
parameters. Firstly, we observe a higher correlation coefficient between
mean ks of coccolith and <inline-formula><mml:math id="M175" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> compared with other morphological
parameters. Secondly, although volume, mass, and thickness are also highly
correlated with <inline-formula><mml:math id="M176" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">Ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, these morphological parameters vary more
with the feature of different coccolithophores, including variations in
coccolith circularity and cell sizes (Young and Ziveri, 2000; Bolton et al.,
2016). Thirdly, the thickness is a morphological pattern sensitive to the
upper ocean's preservation and surface ocean nutrients conditions during
biomineralization (Table 2). Another important feature of ks is its high
sensitivity to dissolution. As shown in Fig. 4, the ks of coccoliths have
already begun to decrease even though the water depths are only at
<inline-formula><mml:math id="M177" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 2000 m, which is below the modern lysocline but above the
CDD in the SCS (Wang et al., 1995; Luo et al., 2018). Finally, the
dissolution effects on morphological attributes of mean ks agree well with
the laboratory dissolution experiment, in which each subsample's mean ks
reflected different preservation stages (Fig. 4).</p>
      <p id="d1e3261">Despite a noticeable degree of uncertainty due to the mixing of life cycle
and post-mortem signals in the sedimentary record, similar findings of
calcite dissolution modifying coccolith's morphology in waters at or below
saturation suggest that the conclusions drawn from the present study are not
unique to the SCS. In the sub-Antarctic and Antarctic zone, dissolution
signals affecting coccolithophores were manifested as a decrease in mass and
distal shield length of <italic>E. huxleyi</italic> coccoliths preserved in surface sediments
(Rigual-Hernández et al., 2020b; Vollmar et al., 2022). Based on this
collective evidence, a key reasonable question could be can the
morphological variation of coccoliths be employed to trace their evolution
safely or instead be a good proxy for carbonate preservation?</p>
</sec>
<sec id="Ch1.S5.SS3">
  <label>5.3</label><title>Implications for interpreting the downcore history of coccolithophore morphology</title>
      <p id="d1e3275">On longer timescales, the morphological variations of coccoliths have been
employed to trace coccolithophores evolutionary trends. Bolton et al. (2016)
first measured the ks of Noëlaerhabdaceae in the last 15 million years.
They found that the decrease of coccolith ks paralleled the reduction of
atmospheric <inline-formula><mml:math id="M178" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>CO<inline-formula><mml:math id="M179" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> since the late Miocene and interpreted this as a
decrease in biomineralization. More recent works by Beaufort et al. (2022)
and Jin et al. (2022b) focused on the coccolithophore evolution over the
last 2 million years by measuring coccolith mass, highlighting the role of
seasonality and local environments in the evolution and production of
Noëlaerhabdaceae. Similarly, Guitián et al. (2020) studied size
trends across different regions between Oligocene to the Early Miocene,
concluding that cell size distribution was controlled by multiple competing
factors, with a strong selective pressure from CO<inline-formula><mml:math id="M180" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> decline as a
potential mechanism.<?pagebreak page1735?> This study examined dissolution by looking at, among
others, the fragmentation and etching of coccoliths and found that
temporal trends in lith size distributions were not significantly affected.
This agrees with our observations since the mean length in SCS surface
sediments does not correlate with any saturation state-related parameter.
However, Guitián et al. (2022), using a new calibration in the C-Calcita
software that enables estimations of coccolith thickness up to 3.1 <inline-formula><mml:math id="M181" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m,
found that elliptical ks (kse) was inversely correlated with the relative
abundance of dissolution-resistant nannoliths. This was interpreted as a
dissolution control on the elliptical shape factors in coccolithophores
between Oligocene and Miocene, as it was found in our surface sediment
samples. Therefore, we propose that for studies focusing on coccolithophore
evolutionary histories, it would be safer to select a shallow sediment core
with low organic carbon content, high clay content, and always lying above
the carbonate lysocline (Guitián et al., 2020).</p>
      <p id="d1e3311">One useful way to identify dissolution in these studies covering geological
timescales could be plotting the <inline-formula><mml:math id="M182" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> against ks. If an increase of
<inline-formula><mml:math id="M183" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> is detected in the sediment coccolith without any significant
variations in coccolith assemblage or with an increase in
dissolution-resistant species (Guitián et al., 2022), it should be
interpreted as dissolution. Another way to determine separate
evolutionary/ecological influences on ks variations could be to measure the
ks of coccolith across a close spatial gradient which includes different
depositional depths. Significant variations in the morphological attributes
of the fossil coccolithophores would likely be caused by different
saturation through time at different sites. Related to this last suggestion,
coupling downcore morphological assessment in coccolithophores with other
calcareous proxies measurements, such as size-normalized weight of planktic
foraminiferal tests (Lohman, 1995; Broecker and Clark, 2001; Barker and Elderfield,
2002), which include recent advances in morphological analyses in large
microfossils (Iwasaki et al., 2015, 2019), may provide an even more precise
and safe quantitative estimates of past deep-carbonate chemistry parameters.</p>
</sec>
</sec>
<sec id="Ch1.S6" sec-type="conclusions">
  <label>6</label><title>Summary</title>
      <p id="d1e3351">This study demonstrates, based on morphological attributes of <italic>E. huxleyi</italic> and
<italic>Gephyrocapsa</italic> spp. (<inline-formula><mml:math id="M184" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M185" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), that dissolution effects primarily affect
the morphology of coccoliths preserved in the deep ocean. In the SCS surface
sediments, bottom water <inline-formula><mml:math id="M186" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Ω</mml:mi><mml:mi mathvariant="normal">ca</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> saturation plays a major role in
the variation of the coccoliths' ks shape factor, which has the potential,
based on the current calibration, to quantitatively reconstruct past
carbonate dissolution changes. Our laboratory-controlled dissolution results
show that the mean ks decreased in response to increased amounts of
corrosive solution. We propose the normalized ks variation to evaluate the
degree of dissolution (light, strong, or no dissolution) occurring in the
sedimentary record. A length-related dissolution pattern was also observed
in the laboratory and surface sediments, with small coccoliths more prone to
dissolution, increasing larger coccolith specimens and affecting the
assemblage composition. As in the laboratory experiment, the coccolith's ks
from surface sediments decreased with dissolution, and the <inline-formula><mml:math id="M187" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>
trajectory reflected different dissolution stages. However, the <inline-formula><mml:math id="M188" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula>
in surface sediment showed a more complex response due to the natural
variability of the surface sediment samples in terms of geographical
differences in multiple environmental factors. These findings demonstrate
that, despite the complementary of the carbonate system and ecological
aspects, the coccoliths ks factor allied to <inline-formula><mml:math id="M189" display="inline"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>/</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi mathvariant="normal">ks</mml:mi></mml:mrow></mml:math></inline-formula> ratio has potential
as a dissolution proxy to track changes in the seafloor carbonate saturation
state. Although a stable proxy, the mean ks should be applied with caution,
particularly when applied to longer timescales, in which evolutionary
trends might exert control on morphological attributes of fossil
coccolithophores.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d1e3436">Research data are available in the Zenodo (<uri>https://doi.org/10.5281/zenodo.7271441</uri>, Gerotto et al., 2022) and PANGAEA (<uri>https://doi.org/10.1594/PANGAEA.954015</uri> and <uri>https://doi.org/10.1594/PANGAEA.954016</uri>, Gerotto et al.,
2023a, b) data repositories.</p>
  </notes><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3451">AG, HZ, RHN, and IHA conceived and designed the study. AG and HZ conducted
the lab work and sample analyses. AG, HZ, and IHA performed the statistical
analysis. AG, HZ, and IHA wrote the paper with substantial contributions
from all co-authors.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3457">The contact author has declared that none of the authors has any competing interests.</p>
  </notes><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d1e3463">Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3469">Thanks  to the
International Ocean Discovery program for providing the sample used for the
dissolution experiment.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3474">This study was financed in part by the Coordenação de
Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) –
Finance Code 001 to Amanda Gerotto and the ETH Core and Swiss National Science
Foundation (award 200021_182070) funding to Heather M. Stoll.
Additional funding was provided by the National Natural Science Foundation
of China (grant nos. 42188102 and 41930536) to Chuanlian Liu.</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3480">This paper was edited by Chiara Borrelli and reviewed by Francisco Díaz-Rosas, Manuela Bordiga, and one anonymous referee.</p>
  </notes><ref-list>
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