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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Ecol. Evol.</journal-id>
<journal-title>Frontiers in Ecology and Evolution</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Ecol. Evol.</abbrev-journal-title>
<issn pub-type="epub">2296-701X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fevo.2023.1238334</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Ecology and Evolution</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Surface fertilisation and organic matter delivery enhanced carbonate dissolution in the western South Atlantic</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Su&#xe1;rez-Ibarra</surname>
<given-names>Jaime Y.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1430290"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Freire</surname>
<given-names>Tiago M.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Frozza</surname>
<given-names>Cristiane F.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1641263"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pinho</surname>
<given-names>Tain&#xe3; M. L.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2343781"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Petr&#xf3;</surname>
<given-names>Sandro M.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Dias</surname>
<given-names>Bruna B.</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1731368"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chalk</surname>
<given-names>Thomas B.</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2342773"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chaabane</surname>
<given-names>Sonia</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1719850"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Srivastava</surname>
<given-names>Medhavi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Costa</surname>
<given-names>Karen B.</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Toledo</surname>
<given-names>Felipe A. L.</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1714011"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>de Garidel-Thoron</surname>
<given-names>Thibault</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/136523"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Coimbra</surname>
<given-names>Jo&#xe3;o C.</given-names>
</name>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pivel</surname>
<given-names>Mar&#xed;a A. G.</given-names>
</name>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1693029"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>&#xda;stav Geologie a Paleontologie, P&#x159;&#xed;rodov&#x11b;deck&#xe1; fakulta, Univerzita Karlova</institution>, <addr-line>Praha</addr-line>, <country>Czechia</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Programa de P&#xf3;s-Gradua&#xe7;&#xe3;o em Geoci&#xea;ncias, Instituto de Geoci&#xea;ncias, Universidade Federal do Rio Grande do Sul</institution>, <addr-line>Porto Alegre</addr-line>, <country>Brazil</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research</institution>, <addr-line>Bremerhaven</addr-line>, <country>Germany</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>itt OCEANEON &#x2013; Instituto Tecnol&#xf3;gico de Paleoceanografia e Mudan&#xe7;as Clim&#xe1;ticas, Universidade do Vale do Rio dos Sinos</institution>, <addr-line>S&#xe3;o Leopoldo, RS</addr-line>, <country>Brazil</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>School of Arts, Science and Humanities, University of S&#xe3;o Paulo, Cidade Universit&#xe1;ria</institution>, <addr-line>S&#xe3;o Paulo</addr-line>, <country>Brazil</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Murray Edwards College, University of Cambridge</institution>, <addr-line>Cambridge</addr-line>, <country>United Kingdom</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Aix-Marseille Universit&#xe9;, CNRS, IRD, INRAE, CEREGE, Europ&#xf4;le M&#xe9;diterran&#xe9;en de l&#x2019;Arbois</institution>, <addr-line>Aix-en-Provence Cedex</addr-line>, <country>France</country>
</aff>
<aff id="aff8">
<sup>8</sup>
<institution>Department of Climate Geochemistry, Max Planck Institute for Chemistry</institution>, <addr-line>Mainz</addr-line>, <country>Germany</country>
</aff>
<aff id="aff9">
<sup>9</sup>
<institution>Fondation pour la recherche sur la biodiversit&#xe9; (FRB-CESAB)</institution>, <addr-line>Montpellier</addr-line>, <country>France</country>
</aff>
<aff id="aff10">
<sup>10</sup>
<institution>Laborat&#xf3;rio de Paleoceanografia do Atl&#xe2;ntico Sul, Instituto Oceanogr&#xe1;fico, Universidade de S&#xe3;o Paulo, Pra&#xe7;a do Oceanogr&#xe1;fico</institution>, <addr-line>S&#xe3;o Paulo</addr-line>, <country>Brazil</country>
</aff>
<aff id="aff11">
<sup>11</sup>
<institution>Centro de Estudos de Geologia Costeira e Oc&#xea;anica (CECO), Instituto de Geoci&#xea;ncias, Universidade Federal do Rio Grande do Sul</institution>, <addr-line>Porto Alegre</addr-line>, <country>Brazil</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Alessio Fabbrini, University College London, United Kingdom</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Thomas Mark Cronin, United States Geological Survey (USGS), United States; Selvaraj Kandasamy, Central University of Kerala, India; Janne Repschlaeger, Max Planck Institute for Chemistry, Germany</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Jaime Y. Su&#xe1;rez-Ibarra, <email xlink:href="mailto:jysuarezibarra@gmail.com">jysuarezibarra@gmail.com</email>;; <email xlink:href="mailto:suarezij@natur.cuni.cz">suarezij@natur.cuni.cz</email>
</p>
</fn>
<fn fn-type="present-address" id="fn003">
<p>&#x2020;Present address: Tiago M. Freire, Institut f&#xfc;r Geologie &amp; Mineralogie, Universit&#xe4;t zu K&#xf6;ln, K&#xf6;ln, Germany</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>03</day>
<month>11</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>11</volume>
<elocation-id>1238334</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>06</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>12</day>
<month>10</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Su&#xe1;rez-Ibarra, Freire, Frozza, Pinho, Petr&#xf3;, Dias, Chalk, Chaabane, Srivastava, Costa, Toledo, de Garidel-Thoron, Coimbra and Pivel</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Su&#xe1;rez-Ibarra, Freire, Frozza, Pinho, Petr&#xf3;, Dias, Chalk, Chaabane, Srivastava, Costa, Toledo, de Garidel-Thoron, Coimbra and Pivel</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>The last glacial inception was characterised by rapid changes in temperature, atmospheric pCO<sub>2</sub>, and changes in the water mass geometry of the major ocean basins. Although several climatic feedback mechanisms have been proposed to explain the glacial/interglacial cycles witnessed in the Quaternary, the exact mechanistic responses of these processes are still under constrained. In this study we use proxies including planktonic foraminifera compositional assemblages and oxygen stable isotopes to reconstruct past changes in sea surface productivity, stratification, and carbonate dissolution. We use core SIS-249 (2,091 mbsl, western South Atlantic 30&#xb0;S 47&#xb0;W), spanning 30&#x2013;110 thousand years ago (ka), and currently bathed by modern Northern Component Water. We test existing hypotheses suggesting that the orbital obliquity cycle modulates the biological pump in the study area. Spectral analysis run on our synthesised productivity proxies recognises a ~43 kyr-cycle, related to the obliquity cycle. We propose that the enhanced productivity is produced by two mechanisms: i) the glacial upwelling of subsurface nutrient-rich waters and, ii) the continental (wind-driven dust and riverine outflows) fertilisation of the photic zone, with the latter process being obliquity-paced. We also suggest that not only the increased organic matter export but also a change in its bioavailability (from refractory to labile) led to calcium carbonate dissolution, as the degradation of the more soluble organic matter decreased the pH of the glacial bottom water, partially dissolving the calcium carbonate. Although our correlation analyses show a strong benthic-pelagic coupling through the relation between the enhanced biological pump and carbonate dissolution (<italic>&#x3c1;</italic>&lt;0.05, <italic>r</italic>=0.80), we cannot reject the potential of corrosive Southern Component Water bathing the site during the glacial. Finally, we highlight that these processes are not mutually exclusive and that both can be modulated by the obliquity cycle.</p>
</abstract>
<kwd-group>
<kwd>planktonic foraminifera</kwd>
<kwd>primary productivity</kwd>
<kwd>stratification</kwd>
<kwd>southern Brazilian continental margin</kwd>
<kwd>late Quaternary</kwd>
</kwd-group>
<counts>
<fig-count count="4"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="130"/>
<page-count count="14"/>
<word-count count="6841"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Paleoecology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Glacial-interglacial cycles are characterised by cold stages, witnessing decreased temperatures and carbon dioxide (CO<sub>2</sub>) concentrations, the growth of ice sheets and the rearrangement of water mass geometry (<xref ref-type="bibr" rid="B70">Lisiecki and Raymo, 2005</xref>; <xref ref-type="bibr" rid="B1">Ahn and Brook, 2008</xref>; <xref ref-type="bibr" rid="B30">Doughty et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B111">Shackleton et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B78">Menking et&#xa0;al., 2022</xref>). During these cycles, multiple mechanisms contribute to CO<sub>2</sub> drawdown, resulting in a reduction of atmospheric CO<sub>2</sub> levels. These mechanisms include changes in ocean carbonate chemistry (<xref ref-type="bibr" rid="B102">Rickaby et&#xa0;al., 2010</xref>), boosted biological pump (<xref ref-type="bibr" rid="B75">Martin, 1990</xref>; <xref ref-type="bibr" rid="B112">Sigman and Boyle, 2000</xref>), enhanced calcium carbonate preservation (<xref ref-type="bibr" rid="B4">Archer and Maier-Reimer, 1994</xref>; <xref ref-type="bibr" rid="B16">Brovkin et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B29">Doss and Marchitto, 2013</xref>) and expanded Antarctic sea ice (<xref ref-type="bibr" rid="B117">Stephens and Keeling, 2000</xref>; <xref ref-type="bibr" rid="B113">Sigman et&#xa0;al., 2010</xref>), among others.</p>
<p>The growth of southern ice sheets during glacial stages resulted in a reorganised Atlantic Ocean, marked by the expansion of corrosive carbon-rich deep-water masses to shallower depths (e.g., <xref ref-type="bibr" rid="B31">Duplessy et&#xa0;al., 1988</xref>; <xref ref-type="bibr" rid="B23">Curry and Oppo, 2005</xref>; <xref ref-type="bibr" rid="B46">Govin et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B55">Howe et&#xa0;al., 2016a</xref>; <xref ref-type="bibr" rid="B54">Howe et&#xa0;al., 2018</xref>) and, the redistribution of nutrients, boosting the biological pump and enhancing the oceans&#x2019; capacity to sequestrate atmospheric CO<sub>2</sub> during glacial periods (<xref ref-type="bibr" rid="B14">Broecker, 1982</xref>; <xref ref-type="bibr" rid="B112">Sigman and Boyle, 2000</xref>; <xref ref-type="bibr" rid="B114">Skinner, 2009</xref>; <xref ref-type="bibr" rid="B102">Rickaby et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B130">Ziegler et&#xa0;al., 2013</xref>). Yet, the precise way in which these two mechanisms act and interact is still under debate.</p>
<p>For the western South Atlantic, several studies have documented the impact of glacial-interglacial stages on the carbon cycle (<xref ref-type="bibr" rid="B48">Gu et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B90">Pereira et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B98">Portilho-Ramos et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B37">Frozza et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B119">Su&#xe1;rez-Ibarra et&#xa0;al., 2022</xref>) and past bottom water mass geometry (<xref ref-type="bibr" rid="B55">Howe et&#xa0;al., 2016a</xref>; <xref ref-type="bibr" rid="B56">Howe et&#xa0;al., 2016b</xref>; <xref ref-type="bibr" rid="B54">Howe et&#xa0;al., 2018</xref>). One important characteristic of these climatic variations is the effect on calcium carbonate preservation, as it plays an important role in the global carbon cycle. The reorganised &#x201c;glacial&#x201d; Atlantic Ocean affects the calcium carbonate preservation both hemispheres negatively (i.e., <xref ref-type="bibr" rid="B17">Chalk et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B93">Petr&#xf3; et&#xa0;al., 2021</xref>). In addition, another well-known mechanism affected by the glacial-interglacial cycles intemperate zones is the expansion of the southwesterly winds (<xref ref-type="bibr" rid="B123">Toggweiler et&#xa0;al., 2006</xref>), displacing the north limit of the wind belt (from 40&#xb0;S to 30&#xb0;S latitude, <xref ref-type="bibr" rid="B39">Gili et&#xa0;al., 2017</xref>). The change in the wind belt position, associated with an increasing wind strength paced by the obliquity cycle, has been pointed to enhance the terrestrial nutrient supply (<xref ref-type="bibr" rid="B73">Lopes et&#xa0;al., 2021</xref>). This enhancement is thought to increase the productivity of the marine ecosystems.</p>
<p>Another critical factor that can influence calcium carbonate preservation is the biological pump, transporting organic carbon from the surface to the deep ocean. In the western South Atlantic, <xref ref-type="bibr" rid="B119">Su&#xe1;rez-Ibarra et&#xa0;al. (2022)</xref> documented that high primary productivity during the last glacial exported a higher amount of organic matter to the seafloor, where it is remineralised. This process releases CO<sub>2(aq)</sub>, which increases acidity, affecting the preservation of calcium carbonate, and raising questions about the potential of an enhanced glacial biological pump to efficiently sequester carbon in the sediments.</p>
<p>Yet, the extent of the mechanisms driving calcium carbonate preservation and carbon cycling in the western South Atlantic remains to be fully elucidated. It is required an integrated approach encompassing both benthic and pelagic systems to provide insights into the underlying dynamics during the last interglacial-glacial interval. Thus, we use planktonic and benthic foraminifera counts, geochemical analysis (oxygen stable isotopes, &#x3b4;<sup>18</sup>O), sedimentological quantifications (size fraction) and various statistical tools such as correlation, spectral and clustering analyses from the western South Atlantic. By comparing our data with other records from the southern and southeastern Brazilian continental margin, our objectives are: i) to infer the mechanisms that modulate the oceanic fertilisation, ii) to quantify the potential effect of sea surface productivity on carbonate dissolution, and iii) to test the influence of the orbital obliquity cycle on surface and bottom conditions.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Oceanographic setting</title>
<p>The modern upper ocean circulation of the subtropical South Atlantic is governed by the subtropical gyre (<xref ref-type="bibr" rid="B91">Peterson and Stramma, 1991</xref>). The western boundary of the subtropical gyre is impacted mainly by the Brazil Current, which transports warm, salty, oligotrophic waters at the surface (tropical surface water, temperature &gt; 20&#xb0;C; salinity &gt; 36 psu; <xref ref-type="bibr" rid="B91">Peterson and Stramma, 1991</xref>; <xref ref-type="bibr" rid="B118">Stramma and England, 1999</xref>). Below this tropical surface water (~100 m) flow the cooler and more nutrient-rich South Atlantic Central Water (<xref ref-type="bibr" rid="B118">Stramma and England, 1999</xref>), and the Antarctic Intermediate Water with lower salinity and temperature and higher oxygen values (<xref ref-type="bibr" rid="B118">Stramma and England, 1999</xref>). To the South of our study site (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>), at about 38&#xb0;S, the Brazil Current encounters the cool, fresher, and nutrient-rich waters of the Malvinas Current (temperature &lt; 15&#xb0;C; salinity &lt; 34.2 psu), forming the Brazil-Malvinas Confluence (<xref ref-type="bibr" rid="B44">Gordon and Greengrove, 1986</xref>; <xref ref-type="bibr" rid="B43">Gordon, 1989</xref>; <xref ref-type="bibr" rid="B95">Piola et&#xa0;al., 2000</xref>). Currently, the seafloor core location is bathed by the southward movement of North Atlantic Deep Water, (hereafter termed generally as Northern Component water, NCW) a water mass that promotes calcium carbonate preservation due to its oversaturation in carbonate ion (CO<sub>3</sub>
<sup>2&#x2212;</sup>). Conversely, Southern Component water (SCW, comprising the Antarctic Intermediate Water, Circumpolar Deep Water and Antarctic Bottom Water), which is undersaturated in CO<sub>3</sub>
<sup>2&#x2212;</sup>, flows northward above and below the NCW at this location, and its increased corrosiveness leads to calcium carbonate dissolution (<xref ref-type="bibr" rid="B15">Broecker and Peng, 1982</xref>; <xref ref-type="bibr" rid="B36">Frenz et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B35">Frenz and Henrich, 2007</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>
<bold>(A)</bold> Annual mean sea surface temperature and <bold>(B)</bold> annual mean sea surface salinity from the World Ocean Atlas 2013 (WOA13, <xref ref-type="bibr" rid="B71">Locarnini et&#xa0;al., 2013</xref>) relative to core SIS-249 location (in orange). Other cores analysed in this study are indicated in grey (GeoB2107-3, <xref ref-type="bibr" rid="B48">Gu et&#xa0;al., 2017</xref>; GL1090, <xref ref-type="bibr" rid="B104">Santos et&#xa0;al., 2017a</xref>; SAT048A, <xref ref-type="bibr" rid="B119">Su&#xe1;rez-Ibarra et&#xa0;al., 2022</xref>). <bold>(C)</bold> Vertical dissolved phosphate section profile through the western South Atlantic according to the World Ocean Circulation Experiment (WOCE, Section A17; <xref ref-type="bibr" rid="B108">Schlitzer, 2000</xref>) and recovery depth of cores. SBCM, Southern Brazilian Continental Margin; SEBCM, Southeastern Brazilian Continental Margin; RdlP, R&#xed;o de la Plata; MC, Malvinas Current; BC, Brazil Current; BMC , Brazil-Malvinas Confluence; TSW, Tropical Surface Water; SACW, South Atlantic Central Water; SCW, Southern Component Water; NCW, Northern Component Water. Plotted using Ocean Data View (<xref ref-type="bibr" rid="B109">Schlitzer, 2020</xref>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fevo-11-1238334-g001.tif"/>
</fig>
<p>Close to the coring site (35&#xb0; S), the R&#xed;o de la Plata (RdlP), the second largest continental water outflow in South America, reaches the South Atlantic (<xref ref-type="bibr" rid="B76">Matano et&#xa0;al., 2014</xref>). The RdlP drains cool and low salinity waters into the coastal region and increases the nutrient availability, enhancing biological productivity along the continental shelves of Uruguay and southern Brazil during austral winter. Northward displacement of the RdlP outflow occurs in response to the variability of the alongshore wind stress (e.g., <xref ref-type="bibr" rid="B13">Braga et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B80">M&#xf6;ller et&#xa0;al., 2008</xref>). The RdlP outflows can reach 28&#xb0; S along the modern inner and mid-shelves (<xref ref-type="bibr" rid="B95">Piola et&#xa0;al., 2000</xref>; <xref ref-type="bibr" rid="B96">Piola et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B80">M&#xf6;ller et&#xa0;al., 2008</xref>). In contrast, during austral summer, NE winds restrict the RdlP outflows to the south (~32&#xb0; S), inhibiting fertilisation by reducing nutrient supply from continental outflows.</p>
</sec>
<sec id="s3" sec-type="materials|methods">
<label>3</label>
<title>Materials and methods</title>
<sec id="s3_1">
<label>3.1</label>
<title>Marine sediment core</title>
<p>The sediment samples used in this study come from the piston core SIS-249, which measures 1.94 metres in length. This core was retrieved from the lower continental slope of the southern Brazilian continental margin at 2,091 metres below sea level (30&#xb0;05&#x2032; S; 47&#xb0;05&#x2032; W, <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Core SIS-249 was obtained during an oceanographic campaign in the austral spring-summer of 2007 by <italic>Fugro Brasil Ltda</italic> for the Brazilian National Agency of Petroleum, Natural Gas and Biofuels. Due to the presence of shallower allochthonous sands in the uppermost 48&#xa0;cm of the core, this study focuses on the carbonate-rich pelagic mud and sandy mud, which lie between 48 and 194&#xa0;cm. Within this interval, we collected 45 samples with a sampling spacing of 2 to 4&#xa0;cm to analyse the planktonic foraminifera fossil assemblages and stable isotopes.</p>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Planktonic foraminifera compositional assemblage</title>
<p>To assess planktonic foraminifera assemblages, each sample (~9 cc) was sequentially weighed, washed over a 63 &#xb5;m sieve, dried at 55&#xb0;C, and weighed again. To avoid juvenile specimens, which would induce taxonomic biases, planktonic foraminifera were only picked from the &gt;150 &#xb5;m size fraction (<xref ref-type="bibr" rid="B19">CLIMAP Project Members, 1976</xref>; <xref ref-type="bibr" rid="B89">Peeters et&#xa0;al., 1999</xref>). The processed samples were then divided with a micro splitter to recover at least 300 non-fragmented planktonic foraminifera tests per sample, as to support significant statistical variations of around 10% for assemblage analyses (<xref ref-type="bibr" rid="B87">Patterson and Fishbein, 1989</xref>). The taxonomic classification on the species level followed <xref ref-type="bibr" rid="B107">Schiebel and Hemleben (2017)</xref>.</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Age model improvement</title>
<p>The chronology of core SIS-249 was first published by <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al. (2018)</xref> based on one single Accelerator Mass Spectrometry (AMS) radiocarbon age combined with benthic oxygen stable isotope (&#x3b4;<sup>18</sup>O) stratigraphy. The AMS radiocarbon date from <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al. (2018)</xref> was measured on tests of <italic>Globigerinoides ruber</italic> at 58&#xa0;cm core-depth and the age model developed in the software AnalySeries 1.1 (<xref ref-type="bibr" rid="B85">Paillard et&#xa0;al., 1996</xref>).</p>
<p>In the present study, we improved the age model by using six &#x3b4;<sup>18</sup>O tie-points (two points from the new &#x3b4;<sup>18</sup>O<italic>
<sub>G.rub</sub>
</italic> record and four from &#x3b4;<sup>18</sup>O<italic>
<sub>Uvig</sub>
</italic>), which are now correlated with the records from core GL-1090 (<xref ref-type="bibr" rid="B104">Santos et&#xa0;al., 2017a</xref>), a nearby core with high-resolution and well-calibrated age model (based on 14 AMS <sup>14</sup>C and 13 stable oxygen isotope correlation points to two reference curves: <xref ref-type="bibr" rid="B70">Lisiecki and Raymo, 2005</xref> and <xref ref-type="bibr" rid="B45">Govin et&#xa0;al., 2014</xref>). The new refined age model was created in the R-package &#x201c;Bacon&#x201d; v. 2.5.3, which implements Bayesian statistics (<xref ref-type="bibr" rid="B9">Blaauw and Christeny, 2011</xref>). We considered a propagated error of 2.5 kyr, conservatively estimated based on the mean accumulation rates of cores SIS-249 and GL-1090 (ca. 1.87 and 0.29 cm/kyr, respectively) and the &lt;2 kyr age error from the GL-1090 reference curve (<xref ref-type="bibr" rid="B104">Santos et&#xa0;al., 2017a</xref>). The raw AMS radiocarbon age date from <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al. (2018)</xref> was calibrated within the R-package &#x201c;bacon&#x201d;, using the Marine20 curve (<xref ref-type="bibr" rid="B51">Heaton et&#xa0;al., 2020</xref>) and applying a regional reservoir effect (&#x394;R) of &#x2212;85 &#xb1; 40 years (<xref ref-type="supplementary-material" rid="SM1">
<bold>Tables S1</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>S2</bold>
</xref>). This estimate follows the Marine Reservoir Correction Database (<ext-link ext-link-type="uri" xlink:href="http://calib.org/marine/">http://calib.org/marine/</ext-link>), considering the ages of <xref ref-type="bibr" rid="B81">Nadal De Masi (1999)</xref>, <xref ref-type="bibr" rid="B3">Angulo et&#xa0;al. (2005)</xref>, and <xref ref-type="bibr" rid="B2">Alves et&#xa0;al. (2015)</xref>.</p>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Productivity proxies</title>
<p>We reconstruct past sea surface productivity using the ratio between the species <italic>Globigerina bulloides</italic> and <italic>Globigerinoides ruber</italic> (<italic>G.bull/G.rub</italic>), the relative abundance (%) of <italic>Globigerinita glutinata</italic>, and the benthic foraminifera accumulation rate (BFAR).</p>
<p>The <italic>G.bull/G.rub</italic> ratio is used to reconstruct upwelling events (<xref ref-type="bibr" rid="B21">Conan et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B124">Toledo et&#xa0;al., 2008</xref>) based on the contrasting ecological preferences of both species. The opportunistic species <italic>G. bulloides</italic> is associated with eutrophic waters in upwelling zones (<xref ref-type="bibr" rid="B106">Sautter and Thunell, 1991</xref>; <xref ref-type="bibr" rid="B88">Peeters et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B129">Zaric et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B79">Mohtadi et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B65">Lessa et&#xa0;al., 2014</xref>), while <italic>G. ruber</italic>, a symbiont-bearing shallow water-dwelling species, is abundant in tropical/subtropical planktonic foraminiferal provinces (<xref ref-type="bibr" rid="B6">B&#xe9; and Hutson, 1977</xref>; <xref ref-type="bibr" rid="B59">Ku&#x10d;era, 2007</xref>; <xref ref-type="bibr" rid="B107">Schiebel and Hemleben, 2017</xref>). Moreover, the <italic>G. glutinata</italic> abundance is typically higher in phytoplankton-rich waters and is used as a proxy for paleoproductivity (<xref ref-type="bibr" rid="B20">Conan and Brummer, 2000</xref>; <xref ref-type="bibr" rid="B116">Souto et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B90">Pereira et&#xa0;al., 2018</xref>).</p>
<p>We also applied the BFAR index, calculated here as the total number of benthic foraminifera multiplied by the sediment accumulation rate as it has been shown to be a reliable proxy for the organic carbon flux to the seafloor in the Brazilian margin (<xref ref-type="bibr" rid="B28">Dias et&#xa0;al., 2021</xref>). The BFAR index represents the increments of primary productivity export to the seafloor, in which the increases on benthic biomass are associated to the increasing food availability to the benthic community (<xref ref-type="bibr" rid="B52">Herguera and Berger, 1991</xref>; <xref ref-type="bibr" rid="B49">Guichard et&#xa0;al., 1997</xref>; <xref ref-type="bibr" rid="B58">Jorissen et&#xa0;al., 2007</xref>). Thus, these planktonic and benthic foraminiferal proxies together can indicate changes in the fertilisation mechanisms affecting the photic zone (i.e., biological pump, terrestrial nutrient input) and posterior organic matter export.</p>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Upper water column stratification proxies</title>
<p>To assess changes in sea surface stratification, we studied both the stable isotopic composition of selected planktonic foraminifera species and assemblage counts. As planktonic foraminifera calcitic tests record a mean value corresponding to that of the local water mass properties (i.e., temperature, salinity) at the different depths where they live, their &#x3b4;<sup>18</sup>O signal allows the reconstruction of the seawater conditions at different depth layers (<xref ref-type="bibr" rid="B33">Emiliani, 1954</xref>; <xref ref-type="bibr" rid="B100">Ravelo and Hillaire-Marcel, 2007</xref>). The species <italic>G. ruber</italic> dwells at surface-shallow depths, while the species <italic>Globorotalia inflata</italic> is a subsurface-thermocline dweller (<xref ref-type="bibr" rid="B18">Chiessi et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B47">Groeneveld and Chiessi, 2011</xref>; <xref ref-type="bibr" rid="B107">Schiebel and Hemleben, 2017</xref>; <xref ref-type="bibr" rid="B64">Lessa et&#xa0;al., 2020</xref>). Therefore, the gradient between the &#x3b4;<sup>18</sup>O values of these two species (&#x394;&#x3b4;<sup>18</sup>O<italic>
<sub>G.</sub>
</italic>
<italic>
<sub>inf-G.rub</sub>
</italic>) indicates a decreased (increased) upper water column stratification according to the lower (higher) &#x394;&#x3b4;<sup>18</sup>O<italic>
<sub>G.</sub>
</italic>
<italic>
<sub>inf-G.rub</sub>
</italic> values (<xref ref-type="bibr" rid="B105">Santos et&#xa0;al., 2017b</xref> and references therein).</p>
<p>Around 10 specimens of <italic>G. ruber</italic> and <italic>G. inflata</italic> were collected per sample for the &#x3b4;<sup>18</sup>O analyses from the size fraction &gt;250 &#xb5;m to limit ontogenetic effects &#x200b;&#x200b;(<xref ref-type="bibr" rid="B32">Elderfield et&#xa0;al., 2002</xref>). The tests were cleaned with distilled water using an ultrasonic bath to remove any contamination by external particles. The isotopic measurements were performed on a ThermoFisher Scientific MAT253 gas Isotope Ratio Mass Spectrometer coupled to a Kiel IV automated carbonate device at the Research Center for Geochronology and Isotopic Geochemistry (CPGeo) from the University of S&#xe3;o Paulo. Isotopic data used the Vienna Pee-Dee-Belemnite (VPDB) reference standard. Here we report the standard deviation of the laboratory reference material used for normalisation (SHP2L; <xref ref-type="bibr" rid="B22">Crivellari et&#xa0;al., 2021</xref>), being 0.07&#x2030; (n=20 standards) over the measurement period. The standard deviation of the VPDB &#x3b4;<sup>18</sup>O values of the measured samples did not exceed 0.1&#x2030;. As no replicated measurements were carried out, we confirmed the consistency of our &#x3b4;<sup>18</sup>O values and value offset between <italic>G. ruber</italic> and <italic>G. inflata</italic> with the expected values for our study site. We verify this by comparing our records with published Holocene (<xref ref-type="bibr" rid="B18">Chiessi et&#xa0;al., 2007</xref>) and last glacial and interglacial stage (<xref ref-type="bibr" rid="B105">Santos et&#xa0;al., 2017b</xref>) datasets.</p>
<p>In addition, we use the abundances of the <italic>Globorotalia truncatulinoides</italic> right coiling form, as it has been documented to represent a well-mixed upper water column (reduced stratification), since this morphotype migrates to relatively shallower depths to complete its reproductive cycle (e.g., <xref ref-type="bibr" rid="B72">Lohmann and Schweitzer, 1990</xref>
<italic>;</italic> <xref ref-type="bibr" rid="B101">Renaud and Schmidt, 2003</xref>; <xref ref-type="bibr" rid="B34">Feldmeijer et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B8">Billups et&#xa0;al., 2016</xref>).</p>
</sec>
<sec id="s3_6">
<label>3.6</label>
<title>Dissolution proxies</title>
<p>We quantify the effect of dissolution on foraminiferal assemblages by using: i) the ratio between the benthic and planktonic foraminifera (B/P ratio, <xref ref-type="bibr" rid="B5">Arrhenius, 1952</xref>; <xref ref-type="bibr" rid="B86">Parker and Berger, 1971</xref>; <xref ref-type="bibr" rid="B59">Ku&#x10d;era, 2007</xref>), ii) the number of whole planktonic foraminifera tests per gram of dry sediment (PF/g, <xref ref-type="bibr" rid="B63">Le and Shackleton, 1992</xref>; <xref ref-type="bibr" rid="B120">Su&#xe1;rez-Ibarra et&#xa0;al., 2021</xref>), iii) the abundance (%) of the coarse fraction i.e. larger than 63 &#xb5;m (<xref ref-type="bibr" rid="B7">Berger et&#xa0;al., 1982</xref>; <xref ref-type="bibr" rid="B40">Gonzales et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B120">Su&#xe1;rez-Ibarra et&#xa0;al., 2021</xref>) and, iv) the CaCO<sub>3</sub> content (%) (<xref ref-type="bibr" rid="B7">Berger et&#xa0;al., 1982</xref>; <xref ref-type="bibr" rid="B40">Gonzales et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B120">Su&#xe1;rez-Ibarra et&#xa0;al., 2021</xref>). The CaCO<sub>3</sub> (%) was previously calculated by <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al. (2018)</xref>. The fraction &gt;63 &#xb5;m was estimated using a laser diffraction particle size analyzer Horiba Partica-LA-950X, which determined the grain size of the bulk sediment samples at the <italic>Centro de Estudo de Geologia Costeira e Oce&#xe2;nica</italic> (CECO) of the <italic>Universidade Federal do Rio Grande do Sul</italic> (UFRGS).</p>
</sec>
<sec id="s3_7">
<label>3.7</label>
<title>Multivariate statistical analyses</title>
<p>To divide the time series record into distinct cluster intervals (periods characterised by similar conditions) we carry out a clustering analysis. Posteriorly, to distinguish the dependencies of the grouping process we utilize an ordinate analysis. Both clustering and ordinate analyses are applied on the planktonic foraminifera species with relative abundances &gt;1% (See <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary material</bold>
</xref>).</p>
<p>Additionally, since all proxies are inevitably affected by different environmental processes other than the targeted parameters, we decrease the bias by also synthesising the variation through time of i) sea surface productivity, ii) upper water column stratification, and iii) carbonate dissolution. To do so, we run principal component analyses (PCA) on the above proxies, based on the correlation matrix. The data were centralised and standardised by dividing the difference between the dataset mean and the sample value by the dataset standard deviation. The synthesised productivity, stratification and dissolution proxies were extracted from the first axes of the PCAs as PC1<sub>P</sub> (productivity), PC1<sub>S</sub> (stratification) and PC1<sub>D</sub> (dissolution). Correlations between (and within) the first axes of the PCAs and other proxies were calculated using reduced major axis regressions. All PCA and correlation analyses were conducted using the software PAST (version 4.08; <xref ref-type="bibr" rid="B50">Hammer et&#xa0;al., 2001</xref>).</p>
</sec>
<sec id="s3_8">
<label>3.8</label>
<title>Spectral analysis</title>
<p>To test whether variations through time correspond to cyclic events, paced by orbital forcings, first we run a Multi-Taper-Method (MTM) test using the software &#x201c;Acycle&#x201d; (<xref ref-type="bibr" rid="B69">Li et&#xa0;al., 2019</xref>). The PC1<sub>P</sub> curve was detrended using a locally weighted scatterplot smoothing (LOWESS) and then analysed with the MTM. We set the smoother with a Time-bandwidth product of &#x201c;2&#x201d;, and calculated the red noise following the Classical autoregressive (AR) model AR(1) (<xref ref-type="bibr" rid="B57">Husson, 2014</xref>). Second, we conducted a REDFIT spectral analysis utilising the software PAST (version 4.08; <xref ref-type="bibr" rid="B50">Hammer et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B110">Schulz and Mudelsee, 2002</xref>). The spectral analysis used the &#x201c;Welch&#x201d; window, a configuration of &#x201c;4&#x201d; for the oversampling and &#x201c;2&#x201d; as number of segments.</p>
</sec>
</sec>
<sec id="s4" sec-type="results">
<label>4</label>
<title>Results</title>
<p>The <italic>G.bull</italic>/<italic>G.rub</italic> ratio (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>) varies from 0.18 to 0.52 (mean 0.37 &#xb1; 0.09), increasing through MIS 5 up to the boundary with MIS 4 (90.1 to 75 ka) and again during MIS 3 (38.7 to 29.5 ka). Relative abundances of <italic>G. glutinata</italic> (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>) range between 4.9 and 24.8% (average 15 &#xb1; 4.05%) and show an increasing trend towards the MIS 5/4 boundary (from 91.9 to 72.7 ka). The BFAR (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2C</bold>
</xref>) varies between 11 (at 90 ka) and 230 ind.cm<sup>-2</sup>.kyr<sup>-1</sup> (at 59 ka), with three intervals: first, a low decreasing trend from 105 to 87 ka (mean 27 ind.cm<sup>-2</sup>.kyr<sup>-1</sup>), followed by an abrupt jump and another decreasing trend from 84 to 39 ka (mean 92 ind.cm<sup>-2</sup>.kyr<sup>-1</sup>), and a final increasing trend until 30 ka (mean 67 ind.cm<sup>-2</sup>.kyr<sup>-1</sup>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Time series records used to estimate productivity (in lilac: <bold>(A)</bold> <italic>G</italic>. <italic>bulloides</italic>/<italic>G. ruber</italic>, <bold>(B)</bold> <italic>G</italic>. <italic>glutinata</italic> abundance and <bold>(C)</bold> BFAR), stratification (in teal: <bold>(D)</bold> abundance of <italic>G</italic>. <italic>truncatulinoides</italic> right coiling and I &#x394;&#x3b4;<sup>18</sup>O<italic>
<sub>G.</sub>
</italic>
<italic>
<sub>inf-G.rub</sub>
</italic>), and dissolution (in steel blue: <bold>(F)</bold> B/P ratio, <bold>(G)</bold> PF/g, <bold>(H)</bold> CaCO<sub>3</sub> content (<xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al., 2018</xref>) and <bold>(I)</bold> &gt;63 &#xb5;m fraction). The black vertical dotted lines divide the record into biotic clusters where: Cluster I (red) is dominated by species characteristic of warm and oligotrophic water; cluster II (purple) by species related to eutrophic water, characterised by high productivity and low stratification; and cluster III (blue) by species from cooler waters. Y axes in <bold>(E&#x2013;I)</bold> are reversed.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fevo-11-1238334-g002.tif"/>
</fig>
<p>The abundance of <italic>G. truncatulinoides</italic> right coiling (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2D</bold>
</xref>) is low throughout the core (0 to 6.5%, mean 1.73). However, the 73&#x2013;51 ka interval (approximately MIS 4) is marked by increased abundances and two abrupt peaks. The &#x3b4;<sup>18</sup>O<italic>
<sub>G.rub</sub>
</italic> values range between -0.96 and 0.29&#x2030; (mean -0.25 &#xb1; 0.33&#x2030;), with lower values during MIS 5, increasing towards MIS 4 and decreasing at the MIS 3 onset (<xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S1</bold>
</xref>). The &#x3b4;<sup>18</sup>O<italic>
<sub>G.</sub>
</italic>
<italic>
<sub>inf</sub>
</italic> values vary between 0.56 and 1.56&#x2030; (mean 1.16 &#xb1; 0.18&#x2030;) and display a progressively increasing trend from MIS 5 to MIS 3 (<xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S1</bold>
</xref>). The &#x3b4;<sup>18</sup>O<italic>
<sub>G.</sub>
</italic>
<italic>
<sub>inf</sub>
</italic> record from core SIS-249 shows a good fit with the values from core GL-1090, except at 80 ka. The &#x394;&#x3b4;<sup>18</sup>O between <italic>G. inflata</italic> and <italic>G. ruber</italic> (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2E</bold>
</xref>) presents values from 0.90 to 1.90&#x2030; (mean 1.38 &#xb1; 0.24&#x2030;). &#x394;&#x3b4;<sup>18</sup>O<italic>
<sub>G.</sub>
</italic>
<italic>
<sub>inf-G.rub</sub>
</italic> values are higher during MIS 5 (around 1.6&#x2030;), intermediate during MIS 3 (above 1.30&#x2030;), and generally lower during MIS 4 (mean 1.16 &#xb1; 0.18&#x2030;).</p>
<p>The B/P ratio (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2F</bold>
</xref>) ranges between 0.02 and 0.19, with low values during MIS 5d-c, an increase through MIS 5b, a reduction during MIS 5a (with a steep peak at 65 ka), followed by an increase at the end of MIS 4 and a further decrease with relatively stable values during MIS 3. The PF/g (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2G</bold>
</xref>) varies between 400 and 5540 (mean 1922 &#xb1; 1141 ind./g) and presents a decreasing trend from 91.9 to 70.3 ka, remaining low throughout MIS 4 and 3. The fraction coarser than 63 &#xb5;m (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2I</bold>
</xref>) presents relatively high values (around 22%) during the 107&#x2013;84 ka time interval, except at 105 ka when values drop to 8.5%. At 78 ka, values reach 3% and remain under 8% until the top of the record (30.4 ka). All the productivity, stratification, and dissolution proxies are shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>.</p>
<p>Concerning the multivariate analyses, the first principal components of the PCA&#x2019;s analyses run on the productivity, stratification, and dissolution proxies (PC1<sub>P</sub>, PC1<sub>S and</sub> PC1<sub>D</sub>) synthesise 61.9, 78.6 and 66.4% of the variance, respectively. The results for the reduced major axis regressions within the PC1<sub>P</sub>, PC1<sub>S</sub>, PC1<sub>D</sub>, &#x3b4;<sup>13</sup>C<italic>
<sub>Uvig</sub>
</italic>, accumulation rate (Acc. rates) and accumulation rates of total organic carbon (ARTOC) are shown in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. All regression analyses show a significant (<italic>p &lt;</italic>0.05) correlation except between &#x3b4;<sup>13</sup>C<italic>
<sub>Uvig</sub>
</italic> and PC1<sub>D</sub>.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Reduced major axis regression results.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">RMA Regression</th>
<th valign="middle" align="center">PC1<sub>P</sub>-<break/>PC1<sub>S</sub>
</th>
<th valign="middle" align="center">PC1<sub>P</sub>- &#x3b4;<sup>13</sup>C<italic>
<sub>Uvig</sub>
</italic>
</th>
<th valign="middle" align="center">PC1<sub>P</sub>-<break/>PC1<sub>D</sub>
</th>
<th valign="middle" align="center">&#x3b4;<sup>13</sup>C<italic>
<sub>Uvig</sub>
</italic>-PC1<sub>D</sub>
</th>
<th valign="middle" align="center">PC1<sub>P</sub>-<break/>Acc. rates</th>
<th valign="middle" align="center">PC1<sub>S</sub>-<break/>Acc. rates</th>
<th valign="middle" align="center">PC1<sub>S</sub>-<break/>ARTOC</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">
<italic>r</italic>:</td>
<td valign="middle" align="center">
<bold>0.51</bold>
</td>
<td valign="middle" align="center">
<bold>-0.32</bold>
</td>
<td valign="middle" align="center">
<bold>0.80</bold>
</td>
<td valign="middle" align="center">-0.28</td>
<td valign="middle" align="center">
<bold>0.58</bold>
</td>
<td valign="middle" align="center">
<bold>0.77</bold>
</td>
<td valign="middle" align="center">
<bold>0.66</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">
<italic>r</italic>
<sup>2</sup>:</td>
<td valign="middle" align="center">0.26</td>
<td valign="middle" align="center">0.01</td>
<td valign="middle" align="center">0.64</td>
<td valign="middle" align="center">0.08</td>
<td valign="middle" align="center">0.34</td>
<td valign="middle" align="center">0.59</td>
<td valign="middle" align="center">0.44</td>
</tr>
<tr>
<td valign="middle" align="center">t:</td>
<td valign="middle" align="center">3.90</td>
<td valign="middle" align="center">-2.13</td>
<td valign="middle" align="center">4.99</td>
<td valign="middle" align="center">-1.07</td>
<td valign="middle" align="center">4.62</td>
<td valign="middle" align="center">7.79</td>
<td valign="middle" align="center">3.20</td>
</tr>
<tr>
<td valign="middle" align="center">
<italic>p</italic>:</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">
<bold>0.04</bold>
</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">0.30</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">
<bold>0.01</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">Permutation <italic>p</italic>:</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">
<bold>0.04</bold>
</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">0.31</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">
<bold>&lt;0.05</bold>
</td>
<td valign="middle" align="center">
<bold>0.01</bold>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>In bold are significant (<italic>p &lt;</italic>0.05) values. PC1 stands for first component axes of productivity (PC1<sub>P</sub>) stratification (PC1<sub>S</sub>), and dissolution (PC1<sub>D</sub>) proxies. Accumulation rates (Acc. rates) were calculated according to the age model presented in this study. the accumulation rates of total organic carbon (TOC*AR) used data from <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al. (2018)</xref>.</p>
</table-wrap-foot>
</table-wrap>
<p>Finally, the MTM spectral analyses yield significant results for the PC1<sub>P</sub> (<xref ref-type="supplementary-material" rid="SM1">
<bold>supplementary material</bold>
</xref>). The Classic AR(1) indicates the strongest power at the frequency 0.023 (&gt;99%), associated with a 43 kyr-cycle (period = 1/frequency). The REDFIT points the strongest power also at the frequency 0.023 (&gt;99%), associated with the same 43 kyr-cycle.</p>
</sec>
<sec id="s5" sec-type="discussion">
<label>5</label>
<title>Discussion</title>
<sec id="s5_1">
<label>5.1</label>
<title>Upper water column conditions</title>
<p>The relatively high <italic>G.bull</italic>/<italic>G</italic>.<italic>rub</italic> ratios, <italic>G. glutinata</italic> (%) and BFAR values (<xref ref-type="fig" rid="f2">
<bold>Figures&#xa0;2A&#x2013;C</bold>
</xref>) imply a period of enhanced sea surface productivity during MIS 4 and, to a lesser extent, MIS 3. The high glacial productivity recorded by core SIS-249 agrees with previous studies for the southern Brazilian continental margin (SBCM), that also document enhanced productivity during the last glacial stage (e.g., <xref ref-type="bibr" rid="B48">Gu et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B90">Pereira et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B98">Portilho-Ramos et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B37">Frozza et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B119">Su&#xe1;rez-Ibarra et&#xa0;al., 2022</xref>). The increase of around 40% in <italic>G.bull</italic>/<italic>G</italic>.<italic>rub</italic> mean ratios from ~0.27 (110&#x2013;83 ka) to ~0.39 (83&#x2013;30 ka) suggests an increase in the upwelling of subsurface more nutrient-rich South Atlantic Central Water (<xref ref-type="bibr" rid="B127">Venancio et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B66">Lessa et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B67">Lessa et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B98">Portilho-Ramos et&#xa0;al., 2019</xref>).</p>
<p>As the upwelling of subsurface waters necessarily implies a break in the upper water column stratification, we should also expect a similar behaviour in the stratification proxies. This can be primarily confirmed by the high relative abundances of <italic>G. truncatulinoides</italic> right coiling form, which also point to a less stratified, well-mixed upper water column during MIS 4 (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2D</bold>
</xref>, <xref ref-type="bibr" rid="B72">Lohmann and Schweitzer, 1990</xref>
<italic>;</italic> <xref ref-type="bibr" rid="B101">Renaud and Schmidt, 2003</xref>; <xref ref-type="bibr" rid="B34">Feldmeijer et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B8">Billups et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B94">Pinho et&#xa0;al., 2021</xref>). Furthermore, <italic>G. truncatulinoides</italic> types II and V (right coiling forms) have also been associated with a shallow thermocline and eutrophic conditions (<xref ref-type="bibr" rid="B27">de Vargas et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B126">Ujii&#xe9; and Lipps, 2009</xref>; <xref ref-type="bibr" rid="B125">Ujii&#xe9; et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B99">Quill&#xe9;v&#xe9;r&#xe9; et&#xa0;al., 2013</xref>). Finally, the less stratified upper water column during MIS 4 (and to a lesser extent MIS 3) is also supported by the lower &#x394;&#x3b4;<sup>18</sup>O<italic>
<sub>G.</sub>
</italic>
<italic>
<sub>inf-G.rub</sub>
</italic>values (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2E</bold>
</xref>), which implies a reduced stratification between the mixed layer and the thermocline (<xref ref-type="bibr" rid="B105">Santos et&#xa0;al., 2017b</xref>).</p>
<p>Considering that the utilised foraminiferal proxies also depend on other environmental parameters (for instance, changes in the relative abundances of one species can be due to variations in the abundances of other species), the use of the principal component analysis helps to synthesise the variation of the proxies through time. The PC1<sub>P</sub> (the synthesised first principal component of the <italic>G.bull/G.rub</italic> ratios, <italic>G. glutinata</italic> (%), and BFAR proxies) from our core SIS-249 (in the SBCM) suggests a transition, from MIS 5 to MIS 4, to more eutrophic conditions in the upper water column (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). This shift in nutrient availability is also evident in the clustering and PCoA analyses (<xref ref-type="supplementary-material" rid="SM1">
<bold>Figures S3</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>S4</bold>
</xref>), where the dominant/significant species shift from warm and oligotrophic conditions during MIS 5 (<italic>G. ruber albus</italic>, <italic>O. universa</italic> and <italic>G. menardii</italic>) to species associated with high productivity during MIS 4 (<italic>G. glutinata, G. bulloides</italic> and <italic>G. truncatulinoides</italic> dextral coiling). However, studies for the southeastern Brazilian continental margin (SEBCM) document a shift to less eutrophic conditions during the same time interval (e.g., <xref ref-type="bibr" rid="B97">Portilho-Ramos et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B66">Lessa et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B67">Lessa et&#xa0;al., 2019</xref>), associated with the eccentricity cycle. Our study suggests two different mechanisms fertilising the SBCM and SEBCM regions i) enhanced Fe-fertilisation through dust delivery and riverine input due to the strengthening of southwesterly winds during glacial stadials and ii) boosted upwelling delivering subsurface nutrient rich waters to the surface during interstadials, respectively.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Time series graph showing the close relation between <bold>(A)</bold> obliquity values (<xref ref-type="bibr" rid="B62">Laskar et&#xa0;al., 2004</xref>), Infaunal/Epifaunal benthic foraminifera ratio by <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al. (2018)</xref>, and <bold>(B)</bold> the proxies for productivity (PC1<sub>P</sub>), stratification (PC1<sub>S</sub>) and dissolution (PC1<sub>D</sub>) from core SIS-249. On <bold>(C)</bold>, synthesised record of productivity (PC1<sub>P</sub>) and dissolution (PC1<sub>D</sub>) from core SAT-048A (<xref ref-type="bibr" rid="B119">Su&#xe1;rez-Ibarra et&#xa0;al., 2022</xref>) and <bold>(D)</bold> SWW strength, as inferred by terrestrial pollen and the dinoflagellate species <italic>O. centrocarpum</italic> recorded by <xref ref-type="bibr" rid="B48">Gu et&#xa0;al. (2017</xref>, core GeoB2107-3, southern Brazilian continental margin), and the Total Organic Carbon (values from <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al., 2018</xref>, also in core SIS-249) times the Accumulation Rates are shown. On <bold>(E)</bold>, the dust flux in Antarctica (Dome C ice core, <xref ref-type="bibr" rid="B60">Lambert et&#xa0;al., 2008</xref>) and core SIS-249 &#x3b4;<sup>13</sup>C<italic>
<sub>Uvig</sub>
</italic> values (<xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al., 2018</xref>). Finally, on <bold>(F)</bold> the <sup>231</sup>Pa/<sup>230</sup>Th proxy by <xref ref-type="bibr" rid="B77">McManus et&#xa0;al. (2004</xref>, light blue line, sediment core CE326-GGC5, 33&#xb0;42&#x2019;N, 57&#xb0;35&#x2019;W, 4550 mbsl) and <xref ref-type="bibr" rid="B10">B&#xf6;hm et&#xa0;al. (2015</xref>, dark blue line, sediment core ODP Site 1063, Leg 172, 33&#xb0;41&#x2019;N, 57&#xb0;37&#x2019;W, 4,584 mbsl). Y axes in <bold>(A)</bold>, <italic>O. centrocarpum</italic> (%) and <italic>Uvigerina</italic> spp. &#x3b4;<sup>13</sup>C are reversed.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fevo-11-1238334-g003.tif"/>
</fig>
<p>Notably, our PC1<sub>P</sub> (along with the PC1<sub>S</sub> and PC1<sub>D</sub>) varies alongside the obliquity cycle, as shown by the spectral analyses (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). The Classic AR(1) (<xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S5</bold>
</xref>) and REDFIT (<xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S6</bold>
</xref>) give a &gt;99% confidence for our PC1<sub>P</sub> to be orbitally paced by the obliquity cycle (43 kyr). Our results support the hypothesis that the obliquity cycle modulates a dust delivered Fe-fertilising mechanism at the studied site (<xref ref-type="bibr" rid="B73">Lopes et&#xa0;al., 2021</xref>). Briefly, under low-obliquity values, annual average insolation decreases at the poles (<xref ref-type="bibr" rid="B84">Paillard, 2021</xref>), which would favour the expansion of Antarctica&#x2019;s ice sheets (<xref ref-type="bibr" rid="B30">Doughty et&#xa0;al., 2021</xref>), intensifying the southwesterly winds (SWW, <xref ref-type="bibr" rid="B123">Toggweiler et&#xa0;al., 2006</xref>) and the wind-driven dust delivery. Then, during low-obliquity intervals, the north limit of the SWW belt migrates north (from 40&#xb0;S to 30&#xb0;S latitude, <xref ref-type="bibr" rid="B61">Lamy et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B39">Gili et&#xa0;al., 2017</xref>) close to our coring site. This would allow the northward/offshore transport of more nutrient-rich, fresher, and cooler waters of the RdlP closer to our study area, also fertilising the photic zone (e.g., <xref ref-type="bibr" rid="B48">Gu et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B90">Pereira et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B98">Portilho-Ramos et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B12">Bottezini et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B11">Bottezini et&#xa0;al., 2022</xref>).</p>
<p>In fact, a northern/offshore influence of RdlP outflows during periods of low obliquity values would be supported by the population collapses of the dinoflagellate species <italic>Operculodinium centrocarpum</italic>, associated with the Brazil Current, documented by <xref ref-type="bibr" rid="B48">Gu et&#xa0;al. (2017)</xref> (core GeoB2107-3) for the SBCM during MIS 4 and the MIS 3/2 boundary (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3D</bold>
</xref>). Also, the decreased influence of the core of the Brazil Current (which transports warm oligotrophic water) in the study area would lead to a decrease in upper water column stratification, evidenced by our PC1<sub>S</sub> (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). In addition, a northern/offshore intrusion of the nutrient-rich RdlP outflows (or freshwater bodies formed along the continental shelf) can also be inferred from the presence of freshwater diatoms during MIS 3&#x2013;2 from core SIS-188 (<xref ref-type="bibr" rid="B12">Bottezini et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B11">Bottezini et&#xa0;al., 2022</xref>).</p>
<p>Moreover, strengthened SWW would also transport wind-driven particles from southern South America to the study area, increasing the Fe-fertilisation from terrestrial sources (<xref ref-type="bibr" rid="B73">Lopes et&#xa0;al., 2021</xref>). During MIS 5/4 and 3/2 boundaries, the elevated pollen concentrations (e.g., <xref ref-type="bibr" rid="B48">Gu et&#xa0;al., 2017</xref>, SBCM, core GeoB2107-3) can be interpreted as enhanced aeolian transport (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>), and thus, terrestrial dust fertilisation. Additionally, the presence of the Andean pollen <italic>Nothofagus</italic>, recorded by <xref ref-type="bibr" rid="B48">Gu et&#xa0;al. (2017)</xref> during the late MIS 3 and MIS 2, corroborates the idea of enhanced windiness, strengthened SWW and aeolian Fe-fertilisation from South American sources. On top of it, <xref ref-type="bibr" rid="B73">Lopes et&#xa0;al. (2021)</xref> compiled chemical studies analysing the provenance of glacial terrigenous dust in the southwest Atlantic, pointing southern South America (central-western Argentina and Patagonia) as the main source (e.g., <xref ref-type="bibr" rid="B25">Delmonte et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B128">Weber et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B39">Gili et&#xa0;al., 2017</xref>).</p>
<p>In summary, our record suggests two mechanisms to have fertilised the study area: i) upwelling, enhanced by the interplay of lower glacial sea level and the local bathymetry allowing the shoaling of nutrient-rich South Atlantic Central Water (also richer in silicic acid, <xref ref-type="bibr" rid="B98">Portilho-Ramos et&#xa0;al., 2019</xref>) to the sub-surface (e.g., <xref ref-type="bibr" rid="B74">Mahiques et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B68">Lessa et&#xa0;al., 2016</xref>) and; ii) obliquity-paced fertilisation from southern South America (wind-driven dust and the RdlP outflows) through enhanced aeolian transport, associated with expanded SWW. Both processes lead to a decrease in the upper water column stratification, first, by the ascension of cooler and less salty subsurface South Atlantic Central Water and, second, by the offshore displacement of the core of the Brazil Current. Ultimately, the correlation value between PC1<sub>P</sub> and PC1<sub>S</sub> (<italic>&#x3c1;</italic>&lt;0.05, <italic>r</italic>=0.51) corroborates the synergy between the boosted biological pump and less stratified conditions.</p>
</sec>
<sec id="s5_2">
<label>5.2</label>
<title>Organic matter export and seafloor dynamics</title>
<p>Enhanced primary productivity (i.e., <italic>G.bull</italic>/<italic>G</italic>.<italic>rub</italic> and <italic>G. glutinata</italic> %) and decreased upper water column stratification (PC1<sub>S</sub>) are mirrored by high accumulation rates of total organic carbon during MIS 4 (TOC*AR, <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>, TOC data from <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al., 2018</xref>, and accumulation rates from this study). In addition, the BFAR proxy, commonly employed to reconstruct past surface productivity by examining organic matter export to the seafloor (<xref ref-type="bibr" rid="B52">Herguera and Berger, 1991</xref>), demonstrates significant co-variation (<italic>&#x3c1;</italic>&lt;0.05) with both <italic>G.bull</italic>/<italic>G.rub</italic> (<italic>r</italic>=0.5) and <italic>G. glutinata</italic> relative abundances (<italic>r</italic>=0.55). Although the BFAR proxy has been widely used to quantitatively estimate past productivity changes, this relationship is not always straightforward (e.g., <xref ref-type="bibr" rid="B82">Naidu and Malmgren, 1995</xref>; <xref ref-type="bibr" rid="B26">Den Dulk et&#xa0;al., 2000</xref>; <xref ref-type="bibr" rid="B58">Jorissen et&#xa0;al., 2007</xref>). This limitation arises from the lack of calibration across various productivity settings, among other factors (for an in-depth discussion, please refer to <xref ref-type="bibr" rid="B58">Jorissen et&#xa0;al., 2007</xref>). However, <xref ref-type="bibr" rid="B28">Dias et&#xa0;al. (2021)</xref> demonstrated that the BFAR can indicate variations in the Cabo Frio Upwelling System, located in the SEBCM, where higher BFAR values correspond to increased export of fresh marine organic carbon.</p>
<p>The above-mentioned coupling suggests efficient glacial carbon sequestration via biological pump in the study area. A schematic representation of coupled benthic-pelagic changes observed in mid-latitude southwest Atlantic during the 107&#x2013;30 ka time interval is presented in <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Schematic representation of main changes in sea surface and seafloor conditions recorded by core SIS-249 for the 107&#x2013;30 ka interval, according to the foraminiferal assemblages and their respective three clusters. Interval I (107&#x2013;74 ka) is dominated by species related to warm and oligotrophic water; species from interval II (73&#x2013;61 ka) are related to eutrophic water, with high productivity and low stratification; and interval III (60&#x2013;30 ka) is related to cooler water species. Interval II suggests higher levels of CO<sub>2</sub> at the seafloor mainly due to larger exports of OM. Benthic epifaunal and infaunal proportions, as well as TOC*AR.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fevo-11-1238334-g004.tif"/>
</fig>
<p>The here evidenced increase in the export of organic matter (OM) to the seafloor from MIS 5 to MIS 4 (and to a lesser extent in MIS 3) aligns with the findings of <xref ref-type="bibr" rid="B103">Rodrigues et&#xa0;al. (2018)</xref>. They observe a decrease in the infaunal/epifaunal benthic foraminifera ratio in core SIS-249, indicating a shift in the bioavailability of OM from refractory to labile forms (<xref ref-type="bibr" rid="B41">Gooday, 1993</xref>; <xref ref-type="bibr" rid="B115">Smart et&#xa0;al., 1994</xref>; <xref ref-type="bibr" rid="B42">Gooday, 2003</xref>; <xref ref-type="bibr" rid="B38">Garcia-Chapori et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B24">de Almeida et&#xa0;al., 2022</xref>). This change has significant implications for calcium carbonate preservation. As highlighted in our study, during phytoplankton blooms in glacial periods, higher amounts of OM (more labile, more soluble, and more easily remineralised) are exported to the seafloor, resulting in increased CO<sub>2</sub> release, lower pH, and the dissolution of CaCO<sub>3</sub> (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). In addition, despite the relatively brief sinking time of planktonic foraminifera tests (<xref ref-type="bibr" rid="B121">Takahashi and B&#xe9;, 1984</xref>; <xref ref-type="bibr" rid="B107">Schiebel and Hemleben, 2017</xref>), they could experience minor dissolution during transit through the CO<sub>3</sub>
<sup>2&#x2212;</sup> under-saturated intermediate SCWs (<xref ref-type="bibr" rid="B36">Frenz et&#xa0;al., 2003</xref>). These findings shed light on the important role of sea surface productivity and water mass properties in influencing the dynamics of carbonate preservation during different climatic periods.</p>
<p>Despite the sparser sampling in PC1<sub>D</sub> compared to PC1<sub>P</sub> and PC1<sub>S</sub>, our study found a strong correlation between PC1<sub>P</sub> and PC1<sub>D</sub> in core SIS-249 (<italic>&#x3c1;</italic>&lt;0.05, <italic>r</italic>=0.80, <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). This correlation supports the idea that enhanced dissolution is triggered by glacial high productivity, as it is also documented during the last deglaciation (<xref ref-type="bibr" rid="B119">Su&#xe1;rez-Ibarra et&#xa0;al., 2022</xref>, <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>), even in deeper cores under the presence of modern non-corrosive Northern Component water. While inferring changes in paleoproductivity based on compositional assemblages from partially dissolved samples can be imprecise, our study addresses this issue by complementing the data with geochemical and sedimentological analyses. These additional analyses, like the &#x3b4;<sup>18</sup>O signal from the species <italic>G. inflata</italic> and <italic>G. ruber</italic> (both dissolution resistant according to experimental studies from <xref ref-type="bibr" rid="B92">Petr&#xf3; et&#xa0;al., 2018</xref>), as well as the BFAR and the TOC*AR, are less biased by dissolution.</p>
<p>Due to the OM enrichment in <sup>12</sup>C from photosynthesis (<xref ref-type="bibr" rid="B83">O'Leary, 1988</xref>; <xref ref-type="bibr" rid="B100">Ravelo and Hillaire-Marcel, 2007</xref>), remineralisation at the seafloor is expected to drive negative excursions in the endobenthic foraminiferal &#x3b4;<sup>13</sup>C values, as seen in MIS 5c and 4 (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3E</bold>
</xref>). Nevertheless, although &#x3b4;<sup>13</sup>C<italic>
<sub>Uvig</sub>
</italic> is significantly anti correlated with our PC1<sub>P</sub> (<italic>&#x3c1;</italic>&lt;0.05), the correlation value is weak (<italic>r</italic>=-0.31) and is likely impacted by additional changes in the dissolved inorganic carbon &#x3b4;<sup>13</sup>C of pore waters and/or the local bottom water mass geometry (<xref ref-type="bibr" rid="B100">Ravelo and Hillaire-Marcel, 2007</xref>; <xref ref-type="bibr" rid="B53">Hesse et&#xa0;al., 2014</xref>). <xref ref-type="bibr" rid="B73">Lopes et&#xa0;al. (2021)</xref> suggested an increased influence of more corrosive SCW at the core site during MIS 4 and 3, based on an apparent phasing between the &#x3b4;<sup>13</sup>C<italic>
<sub>Uvig</sub>
</italic> record from core SIS-249 and the dust flux record from Dome C ice core (<xref ref-type="bibr" rid="B60">Lambert et&#xa0;al., 2008</xref>), as the dust-fertilisation in the Southern Ocean would be recorded in the &#x3b4;<sup>13</sup>C of the bottom water masses (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3E</bold>
</xref>). Although we do not exclude the possible influence of a higher proportion of SCW on carbonate preservation, our data show a relationship between the changes in the organic carbon cycle (periods of enhanced sea surface productivity associated with higher exportation of labile OM) and the deep-sea carbonate system. This highlights the need for further investigations applying a conservative or quasi-conservative water mass circulation tracer to elucidate the water masses mixing proportions at our site during the last glacial inception.</p>
<p>Furthermore, a third process that could have impacted the calcium carbonate preservation is the intensity of the Atlantic Meridional Overturning Circulation (AMOC). In a scenario with a sluggish AMOC, the reduced water flow at the seafloor leads to an accumulation of respired CO<sub>2</sub>, resulting in decreased water pH and subsequent corrosion of CaCO<sub>3</sub> (<xref ref-type="bibr" rid="B77">McManus et&#xa0;al., 2004</xref>; <xref ref-type="bibr" rid="B122">Thornalley et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B56">Howe et&#xa0;al., 2016b</xref>). Despite the lower temporal resolution of our PC1<sub>D</sub> record, it is evident that the positive excursions of <sup>231</sup>Pa/<sup>230</sup>Th (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3F</bold>
</xref>), indicative of a sluggish AMOC (<xref ref-type="bibr" rid="B77">McManus et&#xa0;al., 2004</xref>; <xref ref-type="bibr" rid="B10">B&#xf6;hm et&#xa0;al., 2015</xref>), do not align with the longer-term events of intense dissolution recorded by core SIS-249, which also seem to follow the 43 kyr-cycle. Furthermore, our findings are consistent with the conclusions of <xref ref-type="bibr" rid="B119">Su&#xe1;rez-Ibarra et&#xa0;al. (2022)</xref>, who, using a dataset with higher temporal resolution, found that surface productivity was the primary factor driving calcium carbonate dissolution close to our study site.</p>
<p>Additionally, we would like to highlight that these processes, i) the biological pump and ii) water mass configuration, are not mutually exclusive and both may respond to the obliquity cycle. Under low obliquity values and decreased insolation at high latitudes, the (sub)polar fronts migrate equatorward: (i) displacing the north limit of the SSW belt closer to the study site, enhancing the wind-driven dust and continental river fertilisation, and boosting the biological pump; (ii) expanding the southern ice coverage, leading to an increased brine production and enhanced SCW formation (<xref ref-type="bibr" rid="B46">Govin et&#xa0;al., 2009</xref>). This would result in the volumetric increase in the deep Atlantic of more corrosive SCWs which also act in part as a CO<sub>2</sub> storage reservoir.</p>
<p>Finally, although the enhanced remineralization causes part of the OM and biogenic carbonate to be recirculated back in the system instead of being exported to the sediments, we suggest an efficient biological pump in the mixed-layer, which removes inorganic carbon and points out the importance of the SBCM as a glacial carbon capture and sink of atmospheric CO<sub>2</sub> and thus part of the puzzle of glacial-interglacial CO<sub>2</sub> changes.</p>
</sec>
</sec>
<sec id="s6" sec-type="conclusions">
<label>6</label>
<title>Conclusions</title>
<p>Based on our multiproxy analysis carried out in the sediments of core SIS-249, retrieved from the lower continental slope of the southwest Atlantic, southern Brazilian continental margin, we can conclude:</p>
<list list-type="simple">
<list-item>
<p>(i) In the study area, there was an increase in sea surface productivity from the last interglacial (MIS 5) to the subsequent glacial (MIS 4 and, partly, MIS 3). When compared to cores from the southeastern Brazilian continental margin, two possible fertilising mechanisms were identified: during glacial stadials the south was Fe-fertilised by enhanced dust delivery and riverine input due to the strengthening of southwesterly winds. During interstadials the southeastern region experienced expanded upwelling delivering subsurface nutrient rich waters to the surface.</p>
</list-item>
<list-item>
<p>(ii) Glacial increased continental aeolian-riverine fertilisation and reduced upper water column stratification led to an efficient removal of inorganic carbon via the biological pump, as evidenced by the high accumulation rates of total organic carbon, suggesting that the study area is capable to efficiently capture and sink atmospheric CO<sub>2</sub>.</p>
</list-item>
<list-item>
<p>(iii) The degradation of the exported glacial organic matter can lead to decreased pH in bottom water, aiding dissolution and may play a major role in carbon sequestration irrespective of/addition to, deep water mass conditions.</p>
</list-item>
</list>
</sec>
<sec id="s7" sec-type="data-availability">
<title>Data availability statement</title>
<p>The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>Conceptualization &#x2013; JS-I, TF, JC, MP; Data curation &#x2013; JS-I, TF, CF; Formal Analysis &#x2013; All; Funding acquisition &#x2013; JS-I, JC, MP; Investigation &#x2013; TF, MP; Methodology &#x2013; JS-I, TF, CF, MP; Project administration &#x2013; JC, MP; Resources &#x2013; JS-I, JC, MP; Software &#x2013; JS-I, CF, SC, MP; Supervision &#x2013; TC, SC, TG-T, JC, MP; Validation &#x2013; All; Visualization &#x2013; JS-I, CF, SC, MP; Writing &#x2013; original draft &#x2013; JS-I, TF, CF; Writing &#x2013; review &amp; editing &#x2013; All. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>The author/s declare financial support was received for the research, authorship, and/or publication of this article. This work was funded by the Brazilian Coordination of Higher Education Staff Improvement&#x2013;CAPES (grant number 88887.091729/2014-01), the Brazilian National Council for Scientific and Technological Development &#x2013;CNPq (grant number 407922/2016-4) and the Charles University Grant Agency (GAUK, grant number 355422). JS-I thanks the STARS program (P&#x159;&#xed;rodov&#x11b;deck&#xe1; Fakulta, Univerzita Karlova), the ERASMUS+ program, the 4EU+ Alliance and the Johanna M. Resig Fellowship from the Cushman Foundation for Foraminiferal Research. TF thanks the CAPES and the DAAD for his MSc and PhD scholarships, respectively. CF thanks the CAPES for her PhD scholarship. TP acknowledges the AWI INSPIRES II program. BD appreciates financial support from FAPESP (grants 2022/01056-9, 2020/11452-3, and 2018/15123-4). MS thanks the STARS program (P&#x159;&#xed;rodov&#x11b;deck&#xe1; Fakulta, Univerzita Karlova). JC and MP acknowledge support from CNPq, grants 309394/2021-0 and 315684/2021-6, respectively.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The authors thank Rodrigo Portilho-Ramos, Thiago Santos, Jo&#xe3;o Ballalai, Manuel F.G. Weinkauf and three reviewers for discussions through the development of this manuscript.</p>
</ack>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fevo.2023.1238334/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fevo.2023.1238334/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet_1.pdf" id="SM1" mimetype="application/pdf"/>
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