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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2025.1626578</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Marine Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Temporal dynamics of the carbonate system in a tropical rhodolith bed from a protected Caribbean bay</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Rinc&#xf3;n-D&#xed;az</surname>
<given-names>Natalia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
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<contrib contrib-type="author">
<name>
<surname>G&#xf3;mez</surname>
<given-names>Carlos E.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<contrib contrib-type="author">
<name>
<surname>Pi&#xf1;eros-P&#xe9;rez</surname>
<given-names>Valentina</given-names>
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<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<contrib contrib-type="author">
<name>
<surname>Alvarado-Jim&#xe9;nez</surname>
<given-names>F&#xe9;lix</given-names>
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<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<contrib contrib-type="author">
<name>
<surname>N&#xfa;&#xf1;ez</surname>
<given-names>Samuel</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
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<contrib contrib-type="author">
<name>
<surname>Garc&#xed;a-Urue&#xf1;a</surname>
<given-names>Roc&#xed;o</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<aff id="aff1">
<sup>1</sup>
<institution>Grupo de Investigaci&#xf3;n en Ecolog&#xed;a y Diversidad de Algas Marinas y Arrecifes Coralinos, Universidad del Magdalena</institution>, <addr-line>Santa Marta</addr-line>, <country>Colombia</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Laboratorio de Biolog&#xed;a Molecular Marina (BIOMMAR), Universidad de los Andes</institution>, <addr-line>Bogot&#xe1;</addr-line>, <country>Colombia</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Universidad del Magdalena</institution>, <addr-line>Santa Marta</addr-line>, <country>Colombia</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Jose Martin Hernandez-Ayon, Autonomous University of Baja California, Mexico</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Peng Zhang, Guangdong Ocean University, China</p>
<p>Cecilia Chapa-Balcorta, Universidad del Mar, Mexico</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Natalia Rinc&#xf3;n-D&#xed;az, <email xlink:href="mailto:mnrincon@unimagdalena.edu.co">mnrincon@unimagdalena.edu.co</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>28</day>
<month>08</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1626578</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>29</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Rinc&#xf3;n-D&#xed;az, G&#xf3;mez, Pi&#xf1;eros-P&#xe9;rez, Alvarado-Jim&#xe9;nez, N&#xfa;&#xf1;ez and Garc&#xed;a-Urue&#xf1;a.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Rinc&#xf3;n-D&#xed;az, G&#xf3;mez, Pi&#xf1;eros-P&#xe9;rez, Alvarado-Jim&#xe9;nez, N&#xfa;&#xf1;ez and Garc&#xed;a-Urue&#xf1;a</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>Coastal zones are key players in the global carbon cycle, yet the temporal dynamics of their carbonate system, particularly in tropical rhodolith habitats, remain understudied. This study assessed seasonal and spatial variability in carbonate chemistry in Gairaca Bay, a protected tropical bay within Tayrona National Natural Park, Colombian Caribbean. Sampling was conducted in 2023&#x2013;2024 across three habitats: a rhodolith bed (1, 7, 15 m depth), the bay entrance (outer bay, 10 m depth), and a shallow sandy-bottom area (inner bay, 1 and 6 m depths). Temperature, salinity, and total scale pH (pH<sub>T</sub>) were measured <italic>in situ</italic>; total alkalinity (TA) was determined via open-cell titration, and dissolved inorganic carbon (DIC), pCO<sub>2</sub>, bicarbonate (HCO<sub>3</sub>
<sup>-</sup>), carbonate (CO<sub>3</sub>
<sup>2-</sup>), and aragonite saturation state (&#x2126;<sub>arag</sub>) were calculated. Seasonal and spatial patterns were analyzed using PERMANOVA. Significant seasonal differences were found in temperature (F = 248.42, p &lt; 0.05), salinity (F = 49.02, p &lt; 0.05), TA (F = 7.65, p &lt; 0.001), and DIC (F = 2.54, p &lt; 0.001), with no significant variation among sites or depths. Upwelling periods were cooler and saltier (25.9 &#xb1; 1.14 &#xb0;C; 34.48 &#xb1; 0.46), with elevated TA and DIC, and slightly lower pH<sub>T</sub> and &#x2126;<sub>arag</sub>. Non-upwelling periods were warmer (30.0 &#xb1; 0.76 &#xb0;C), less saline (33.36 &#xb1; 0.28), and had higher pH<sub>T</sub> and &#x2126;<sub>arag</sub>. Seasonal delta analysis indicated greater variability during non-upwelling, linked to enhanced freshwater discharge. The outer bay showed the highest variability in pH<sub>T</sub> and &#x2126;<sub>arag</sub>, while the inner bay was most stable for TA and DIC. The rhodolith bed bottom exhibited high TA variability but stability in pH<sub>T</sub> and &#x2126;<sub>arag</sub>, especially during non-upwelling. Seasonal processes, including upwelling and freshwater inputs, drive carbonate system variability in Gairaca Bay. The stability of pH<sub>T</sub> and &#x2126;<sub>arag</sub> in the rhodolith bed bottom suggests a potential role as a biogeochemical refuge in acidification-prone tropical environments.</p>
</abstract>
<kwd-group>
<kwd>carbonate chemistry</kwd>
<kwd>upwelling</kwd>
<kwd>rhodolith beds</kwd>
<kwd>tropical coastal ecosystems</kwd>
<kwd>runoff</kwd>
</kwd-group>
<contract-sponsor id="cn001">Ministerio de Ciencia, Tecnolog&#xed;a e Innovaci&#xf3;n<named-content content-type="fundref-id">10.13039/100022965</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">Instituto Colombiano de Cr&#xe9;dito Educativo y Estudios T&#xe9;cnicos en el Exterior<named-content content-type="fundref-id">10.13039/501100014908</named-content>
</contract-sponsor>
<counts>
<fig-count count="9"/>
<table-count count="5"/>
<equation-count count="4"/>
<ref-count count="74"/>
<page-count count="21"/>
<word-count count="12054"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Marine Biogeochemistry</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>The coastal marine carbonate system is increasingly recognized as critical components of the global carbon cycle, particularly in light of ongoing climate change and ocean acidification (<xref ref-type="bibr" rid="B38">Martin and Hall-Spencer, 2017</xref>; <xref ref-type="bibr" rid="B48">Padin et&#xa0;al., 2020</xref>). Although coastal ecosystems occupy a relatively small fraction of the ocean&#x2019;s surface, they contribute disproportionately to marine primary production, fisheries, and biodiversity, supporting essential ecosystem services (<xref ref-type="bibr" rid="B20">Doney et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B66">Silbiger and Sorte, 2018</xref>). In 2013, demersal and pelagic fisheries yielded approximately 2 &#xd7; 10<sup>10</sup> kg and 8 &#xd7; 10<sup>9</sup> kg of catch, respectively, together accounting for 28% of global fish production (<xref ref-type="bibr" rid="B36">Lu et&#xa0;al., 2018</xref>). These habitats also excel at carbon sequestration, salt marshes, mangroves, and seagrasses store more carbon per unit area than most terrestrial forests (<xref ref-type="bibr" rid="B36">Lu et&#xa0;al., 2018</xref>). Consequently, developing a comprehensive understanding of natural carbonate chemistry dynamics in coastal systems is essential for predicting their resilience to future environmental change (<xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>).</p>
<p>Within tropical coastal zones, the interplay between physical, chemical, and biological processes generates high spatial and temporal variability in carbonate system parameters (<xref ref-type="bibr" rid="B60">Roberts et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B26">Garc&#xed;a-Ib&#xe1;&#xf1;ez et&#xa0;al., 2024</xref>). Seasonal drivers, such as coastal upwelling and freshwater inflows, exert a influence on carbonate chemistry by modulating temperature, salinity, dissolved inorganic carbon (DIC), and total alkalinity (TA) (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). Despite their importance, tropical upwelling systems remain understudied compared to their temperate counterparts, limiting our understanding of their natural variability and resilience.</p>
<p>Upwelling processes, which transport cold deeper nutrient-rich waters to the surface, can alter coastal carbonate chemistry. These changes include reductions in pH and aragonite saturation state (&#x2126;<sub>arag</sub>) associated with increased partial pressure of CO<sub>2</sub> (pCO<sub>2</sub>), TA and DIC concentrations (<xref ref-type="bibr" rid="B57">Reum et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B71">Xiu et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B29">G&#xf3;mez et&#xa0;al., 2023</xref>). However, the magnitude and consequences of these fluctuations can vary depending on regional oceanography, local biogeochemical processes, and climatic phenomena such as the El Ni&#xf1;o&#x2013;Southern Oscillation (ENSO) (<xref ref-type="bibr" rid="B54">Reithmaier et&#xa0;al., 2023</xref>).</p>
<p>In the Colombian Caribbean region, the North Atlantic Subtropical Underwater (SUW) enters the basin from the tropical Atlantic and becomes shallower along the continental slope, reaching depths of approximately 50 m near Santa Marta and Tayrona National Natural Park (TNNP) (<xref ref-type="bibr" rid="B14">Correa-Ramirez et&#xa0;al., 2020</xref>). Before reaching these coastal upwelling zones, the SUW mixes with fresher waters influenced by the Caribbean Coastal Countercurrent within the Panama-Colombia Gyre. This mixing reduces salinity and alter the carbonate chemistry and nutrient content of upwelled waters (<xref ref-type="bibr" rid="B5">Bayraktarov et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B14">Correa-Ramirez et&#xa0;al., 2020</xref>), ultimately impacting coastal ecosystems.</p>
<p>Gairaca Bay (TNNP), offers a unique setting to study the seasonal and interannual variability of carbonate system dynamics in a tropical upwelling-influenced environment. Seasonal upwelling events within the TNNP, deliver cooler, more saline, carbon-enriched waters to the bay, lowering pH and increasing DIC and TA, while during non-upwelling periods dominated by freshwater input, dilution effects elevate pH and reduce DIC and TA, creating contrasting biogeochemical conditions (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). In TNNP, ENSO drives interannual variability, whereas seasonal changes are primarily influenced by coastal upwelling and freshwater discharge from the Magdalena River (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>).</p>
<p>Among the key habitats within Gairaca Bay are rhodolith beds, composed of free-living coralline algae, which were originally referred to as <italic>Lithothamnion</italic> meadows by <xref ref-type="bibr" rid="B27">Garz&#xf3;n-Ferreira and Cano (1991)</xref>. These structures play vital ecological and biogeochemical roles, serving as biodiversity hotspots, stabilizing sediments, and significantly contributing to carbonate production in marine sediments (<xref ref-type="bibr" rid="B22">Foster, 2001</xref>; <xref ref-type="bibr" rid="B67">van der Heijden and Kamenos, 2015</xref>; <xref ref-type="bibr" rid="B38">Martin and Hall-Spencer, 2017</xref>). Unlike coral reefs, which are generally considered carbon sources, rhodolith beds can act as either carbon sinks or sources depending on species composition and environmental conditions (<xref ref-type="bibr" rid="B65">Schubert et&#xa0;al., 2024</xref>). Their resilience to extreme environmental conditions (<xref ref-type="bibr" rid="B38">Martin and Hall-Spencer, 2017</xref>) and capacity for photosynthesis and calcification make them potential buffers against local acidification (<xref ref-type="bibr" rid="B59">Riosmena-Rodr&#xed;guez et&#xa0;al., 2017</xref>). Moreover, while mangroves are recognized as blue carbon sinks (<xref ref-type="bibr" rid="B73">Yong et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B72">Yeemin et&#xa0;al., 2024</xref>), rhodolith beds offer a complementary biogeochemical function. However, their ecological functionality may be threatened under future environmental scenarios due to projected changes in temperature, nutrient availability, and carbonate chemistry (<xref ref-type="bibr" rid="B40">McCoy and Ragazzola, 2014</xref>; <xref ref-type="bibr" rid="B39">Mccoy and Kamenos, 2015</xref>).</p>
<p>In this study, we analyzed carbonate system variability across three contrasting environments within Gairaca Bay: a rhodolith bed, the bay entrance (Outer bay), and a shallow sandy-bottom area (Inner bay). Our goals were to (i) characterize spatial and temporal patterns in carbonate system parameters (TA, DIC, pH<sub>T</sub>, pCO<sub>2</sub>, &#x2126;<sub>arag</sub>) across these habitats; (ii) evaluate the influence of seasonal climatic phases (upwelling vs. non-upwelling) on the carbonate chemistry; and (iii) explore the potential role of rhodolith beds as a proxy for understanding local modulation of carbonate system dynamics under natural upwelling conditions.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Study area</title>
<p>This study was conducted from March 2023 to July 2024 in Gairaca Bay, a protected bay located within TNNP, on the Caribbean coast of Colombia (11&#xb0;15&#x2019;33&#x2019;&#x2019; N, 73&#xb0;24&#x2019;06&#x2019;&#x2019; W) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). The bay is situated between the eastern sector of Taganga and the Piedras River basin, and features diverse geomorphology including rhodolith beds, coral reefs, rocky shores, sandy beaches, shallow sandy-bottom areas, and a transitional zone at the bay&#x2019;s entrance influenced by open ocean processes (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Map of Gairaca Bay within Tayrona National Natural Park, showing the sampling stations used for carbonate chemistry characterization. Depth contours (isobaths) are shown to illustrate the bathymetry of the bay.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g001.tif">
<alt-text content-type="machine-generated">Map of Gairaca Bay in Tayrona National Natural Park, Colombia, showing isobaths and three station points: Bay entrance, Coastal sandy area, and Rhodolith bed. An inset highlights the park's location in Colombia.</alt-text>
</graphic>
</fig>
<p>The region experiences pronounced seasonal variability, modulated by the interplay of coastal upwelling, precipitation, and freshwater inflow (<xref ref-type="bibr" rid="B7">Bayraktarov et&#xa0;al., 2014</xref>) (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). The local climate follows a bimodal seasonal pattern, with alternating wet and dry periods throughout the year. The rainy season typically extends from August to November, while the dry season occurs between December and April. During the dry season, intensified northeasterly trade winds promote upwelling of SUW with sea surface temperatures between 19&#x2013;25 &#xb0;C and salinities exceeding 36.5 (<xref ref-type="bibr" rid="B49">Paramo et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B14">Correa-Ramirez et&#xa0;al., 2020</xref>). In contrast, rainy season conditions are characterized by warmer surface waters (average 28.7 &#xb0;C, reaching up to 30.3 &#xb0;C) and reduced salinity (~34.7) due to increased freshwater input from the Magdalena river and local tributaries draining from the Sierra Nevada de Santa Marta (<xref ref-type="bibr" rid="B2">Ar&#xe9;valo-Mart&#xed;nez and Franco-Herrera, 2008</xref>; <xref ref-type="bibr" rid="B6">Bayraktarov et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B1">Alvarado-Jim&#xe9;nez et&#xa0;al., 2024</xref>) that alters salinity, total alkalinity (TA), and dissolved inorganic carbon (DIC) within the bay (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). These seasonal changes in water mass properties are driven by the alternating dominance of coastal upwelling and fluvial inputs.</p>
<p>To further characterize the upwelled water mass, we used ARGO profiling float data to identify the presence of SUW in the offshore region of the Colombian Caribbean. The gridded distribution of potential temperature (&#x3b8;) was derived from validated ARGO profiles (WOD code: 12; originator&#x2019;s flag set to use = 12), collected in April 2024 approximately 200 km off the coast during oceanographic cruises. The figure was generated using the &#x201c;Two Scatter Windows&#x201d; tool in Ocean Data View (ODV) with gridded field interpolation enabled. SUW was identified by its characteristic high-salinity core (~37.16 &#xb1; 0.18) located at ~120 m depth (<xref ref-type="bibr" rid="B14">Correa-Ramirez et&#xa0;al., 2020</xref>). This thermohaline signature is consistent with SUW properties previously described for the western tropical Atlantic, supporting the notion that this water mass is the primary source of upwelled water in the region during the dry season (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_1</bold>
</xref>).</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Sampling station selection and environmental variable collection</title>
<p>Three stations were strategically selected to represent different habitats and hydrodynamic conditions: A rhodolith bed located at the center of the bay (sampled at 1, 7, and 15 m depths), the outer bay at the entrance (10 m depth), and the inner bay, a shallow sandy-bottom zone near the beach (sampled at 1 and 6 m depths). The selection of the three sampling sites within Gairaca Bay, was guided by the objective of capturing environmental contrasts within a relatively small spatial scale, such as physical and oceanographic features related to depth, exposure to oceanic exchange, and proximity to terrestrial inputs (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>).</p>
<p>At each station and depth, <italic>in situ</italic> measurements of temperature, salinity, and pH were taken immediately after sample collection. The pH on the total scale (pH<sub>T</sub>) was measured using a SI Analytics HandyLab 100 meter equipped with a WTW Sentix 41 pH electrode. The instrument had a resolution setting of 0.001 pH units (3 decimal places) and an accuracy of &#x2264; 0.005 pH &#xb1;1 digit. pH measurements were recorded in millivolts and later converted to pH<sub>T</sub> using the values of Tris buffer (Batch T41) and the <italic>in situ</italic> temperature, following standard operating procedures (<xref ref-type="bibr" rid="B19">Dickson et&#xa0;al., 2007</xref>). The electrode was calibrated monthly using NBS buffers (pH 4.01, 7.00, and 10.00), and during each calibration, the slope was checked and consistently exceeded 97%, indicating a near-Nernstian response (<xref ref-type="bibr" rid="B19">Dickson et&#xa0;al., 2007</xref>). Dissolved oxygen was measured <italic>in situ</italic> using a WTW Oxi 3310 meter, with a manufacturer-reported accuracy of &#x2264; 0.1 K &#xb1;1 digit. Salinity and conductivity were measured using an SI Analytics HandyLab 200 meter, with an accuracy of &#x2264; 0.5% of the measured value &#xb1;1 digit. These measurements were taken immediately after water sample collection at each station and depth to ensure reliable representation of ambient conditions. Additionally, 500 mL seawater samples were collected monthly either by SCUBA diving or using a 7-liter Niskin bottle. Samples for TA analysis were preserved with saturated mercuric chloride to prevent chemical alterations. All samples were transported to the Water Quality Laboratory at the University of Magdalena and stored at temperatures below 17 &#xb0;C until further analysis.</p>
<p>Precipitation data for the study period were obtained from the Institute of Hydrology, Meteorology, and Environmental Studies (IDEAM), using records from the Sim&#xf3;n Bol&#xed;var Airport station near Gairaca Bay. Wind speed and wind direction data were retrieved from the Copernicus product Global Ocean Hourly Sea Surface Wind and Stress, with a spatial resolution of 0.125&#xb0; (DOI: 10.48670/moi-00305). Continuous temperature monitoring was performed <italic>in situ</italic> at the rhodolith bed (15 m depth) using an Onset HOBO UA-002&#x2013;64 data logger, programmed to record every 2 hours.</p>
<p>All nutrient analyses were performed following the methodology described by <xref ref-type="bibr" rid="B25">Garay et&#xa0;al. (2003)</xref>. Dissolved inorganic nutrient concentrations were determined using standard colorimetric techniques. Ammonium (NH<sub>4</sub>
<sup>+</sup>) was quantified using the indophenol blue method, which involves its reaction with phenol and sodium nitroprusside in an alkaline medium in the presence of hypochlorite. Nitrite (NO<sub>2</sub>
<sup>-</sup>) was measured via diazotization, using sulfanilamide and N-(1-naphthyl) ethylenediamine as reagents. Nitrate (NO<sub>3</sub>
<sup>-</sup>) was first reduced to nitrite using a cadmium column activated with copper sulfate and then analyzed using the same procedure as for nitrite. Inorganic phosphate (PO<sub>4</sub>
<sup>3-</sup>) was quantified using the molybdenum blue method, employing a reagent mixture of ammonium heptamolybdate, ascorbic acid, sulfuric acid, and potassium antimonyl tartrate. Absorbance measurements were performed using a UV-Vis spectrophotometer, with wavelengths ranging from 543 to 885 nm depending on the nutrient analyzed.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Sample analysis and carbonate system calculations</title>
<p>TA was determined via open-cell potentiometric titration with 0.1 mol L<sup>-1</sup> hydrochloric acid buffered in 0.6 mol L<sup>-1</sup> NaCl (Certified Reference Material - CRM, Dickson Laboratory, Batch 205), following the Remarco protocol (<xref ref-type="bibr" rid="B9">Bernal et&#xa0;al., 2021</xref>). The titration&#x2019;s analytical accuracy was monitored using the CRM with an uncertainty of &#xb1;10 &#xb5;mol kg<sup>-1</sup>.</p>
<p>Using the measured TA and pH<sub>T</sub> values, additional carbonate system parameters, dissolved inorganic carbon (DIC), partial pressure of carbon dioxide (pCO<sub>2</sub>), bicarbonate (HCO<sub>3</sub>
<sup>-</sup>) and carbonate ions (CO<sub>3</sub>
<sup>2-</sup>), and saturation state for calcite (&#x2126;<sub>cal</sub>) and aragonite (&#x2126;<sub>arag</sub>), were calculated using the Excel-CO2SYS software version 2.5 (<xref ref-type="bibr" rid="B52">Pierrot et&#xa0;al., 2006</xref>). Dissociation constants K1, K2 were taken from (<xref ref-type="bibr" rid="B43">Mehrbach et&#xa0;al., 1973</xref>) refit by (<xref ref-type="bibr" rid="B18">Dickson and Millero, 1987</xref>), KHSO<sub>4</sub> by (<xref ref-type="bibr" rid="B17">Dickson, 1990</xref>) and boron concentration following (<xref ref-type="bibr" rid="B34">Lee et&#xa0;al., 2010</xref>).</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Data analysis: temporal and spatial variability of environmental and carbonate system variables</title>
<p>Trends in sea surface temperature, wind velocity, and precipitation were analyzed through time series plots to identify fluctuations associated with different climatic phases (upwelling, non-upwelling, transition pre-upwelling, and transition post-upwelling). Climatic classifications were based on temporal patterns of these environmental drivers.</p>
<p>Descriptive statistics compiling the mean &#xb1; standard deviation values of carbonate system variables such as TA, DIC, pH<sub>T</sub>, &#x2126;<sub>arag</sub>, and CO<sub>3</sub>
<sup>2-</sup> were done per site, climatic season, and year (2023&#x2013;2024). To illustrate the relative temporal deviations in the carbonate system (increases or decreases of the carbonate variables over the study time), minimum and maximum seasonal deltas (&#x394; - deviations from the mean) were calculated for TA, DIC, Salinity, and &#x2126;<sub>arag</sub> across the rhodolith bed bottom, outer bay, and inner bay sites for each climatic season in 2023 and 2024.</p>
<p>Deltas (&#x394;<sub>i</sub>) were computed as:</p>
<disp-formula>
<mml:math display="block" id="M1">
<mml:mrow>
<mml:mtext>&#x394;</mml:mtext>
<mml:mi>i</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi>X</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mover accent="true">
<mml:mi>X</mml:mi>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Where <inline-formula>
<mml:math display="inline" id="im1">
<mml:mrow>
<mml:mi>X</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula> is the observed value and <inline-formula>
<mml:math display="inline" id="im2">
<mml:mrow>
<mml:mover accent="true">
<mml:mi>X</mml:mi>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
</mml:mrow>
</mml:math>
</inline-formula> is the overall mean of each variable, calculated using all available observations across sites, seasons, and years. The mean was chosen as the reference value to center the data around a consistent baseline, facilitating the comparison of variability across sites and time frames. This method allowed for the identification of relative increases or decreases in carbonate system parameters with respect to their average behavior.</p>
<p>Sectional plots of each parameter were then generated in Ocean Data View (ODV) using the Gridded Field option with DIVA gridding, with sampling date (month&#x2013;year) on the X-axis, depth (m) on the Y-axis, and parameter concentration on the Z-axis. To enhance interpretability, the X-axis scale was set to 50 and the Y-axis scale increased to 350 &#x2030;, a vertical extrapolation of &#xb1; 0.5 m was applied, and contour lines were added to highlight gradients throughout the water column.</p>
<p>PERMANOVA was performed to detect differences in the carbonate system parameters (TA, DIC, pCO<sub>2</sub>, &#x2126;<sub>cal</sub>, &#x2126;<sub>arag</sub>, pH<sub>T</sub>, salinity) among sites, depths, and seasons. A Euclidean distance matrix was computed using standardized data with the vegdist function (vegan package, R version 4.3.2). PERMANOVA was performed using the adonis2 function, with 9,999 permutations and type II sums of squares. The homogeneity of multivariate dispersion was tested using the betadisper function and confirmed by ANOVA (p &gt; 0.05).</p>
<p>To assess the predictive capacity of temperature on carbonate system variables, we fitted both simple and multiple linear regression models to estimate dissolved inorganic carbon (DIC, &#xb5;mol kg<sup>-1</sup>) and partial pressure of CO<sub>2</sub> (pCO<sub>2</sub>, &#xb5;atm). The analysis used discrete <italic>in situ</italic> data collected from three representative sites within Gairaca Bay: rhodolith bed bottom, inner bay and outer bay. The following models were applied:</p>
<p>Simple regression model for DIC:</p>
<disp-formula>
<mml:math display="block" id="M2">
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>I</mml:mi>
<mml:mi>C</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi>a</mml:mi>
<mml:mo>.</mml:mo>
<mml:mi>T</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>m</mml:mi>
<mml:mi>p</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>b</mml:mi>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Simple regression model for pCO<sub>2</sub>:</p>
<disp-formula>
<mml:math display="block" id="M3">
<mml:mrow>
<mml:mi>P</mml:mi>
<mml:mi>C</mml:mi>
<mml:msub>
<mml:mi>O</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mi>a</mml:mi>
<mml:mo>.</mml:mo>
<mml:mi>T</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>m</mml:mi>
<mml:mi>p</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>b</mml:mi>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Multiple regression model for pCO<sub>2</sub>:</p>
<disp-formula>
<mml:math display="block" id="M4">
<mml:mrow>
<mml:mi>p</mml:mi>
<mml:mi>C</mml:mi>
<mml:msub>
<mml:mi>O</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mi>a</mml:mi>
<mml:mo>.</mml:mo>
<mml:mi>T</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>m</mml:mi>
<mml:mi>p</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>b</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>S</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>n</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>t</mml:mi>
<mml:mi>y</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>c</mml:mi>
<mml:mo>.</mml:mo>
<mml:mi>T</mml:mi>
<mml:mi>A</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>d</mml:mi>
<mml:mo>.</mml:mo>
<mml:mi>D</mml:mi>
<mml:mi>I</mml:mi>
<mml:mi>C</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>e</mml:mi>
<mml:mo>.</mml:mo>
<mml:mo stretchy="false">(</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>I</mml:mi>
<mml:mi>C</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mi>T</mml:mi>
<mml:mi>A</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Model fitting was conducted in R using the lm () function. Model performance was assessed using the coefficient of determination (R&#xb2;) and root mean square error (RMSE).</p>
<p>An additional PERMANOVA was performed between seasons at the rhodolith bed bottom site. SIMPER analyses were carried out to identify the contribution of individual variables to the observed dissimilarities between seasons, with 9,999 permutations. Spearman&#x2019;s rank correlation was used to assess relationships between environment and carbonate system variables (T&#xb0;C, pCO<sub>2</sub>, CO<sub>3</sub>
<sup>2-</sup>, salinity, pH<sub>T</sub>, DIC, &#x2126;<sub>arag</sub>) and nutrient concentrations (ammonium - NH<sub>4</sub>
<sup>+</sup>, nitrate - NO<sub>3</sub>
<sup>-</sup>, nitrite - NO<sub>2</sub>
<sup>-</sup>, and phosphate - PO<sub>4</sub>
<sup>3-</sup>) at the rhodolith bed bottom. All statistical analyses were performed in RStudio (version 2024.12.1 Build 563; Posit Software, PBC, 2025), using the packages vegan (<xref ref-type="bibr" rid="B47">Oksanen et&#xa0;al., 2025</xref>), ggplot2 (<xref ref-type="bibr" rid="B68">Wickham, 2016</xref>), car (<xref ref-type="bibr" rid="B24">Fox et&#xa0;al., 2024</xref>) (<xref ref-type="bibr" rid="B23">Fox and Weisberg, 2019</xref>), dplyr (<xref ref-type="bibr" rid="B69">Wickham et&#xa0;al., 2023a</xref>), and tidyr (<xref ref-type="bibr" rid="B70">Wickham et&#xa0;al., 2023b</xref>).</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Descriptive analysis of environmental variables</title>
<p>Seasonal and spatial variability in discrete <italic>in situ</italic> measurements of temperature, salinity, and dissolved oxygen was evident across the main sampling sites and depths in Gairaca Bay between March 2023 and July 2024. At the rhodolith bed bottom (15 m depth), temperatures ranged from 26.2 &#xb0;C during upwelling (March 2024) to 30.5 &#xb0;C in the post-upwelling transition (June 2024), with salinity between 33.5 and 35.9 and oxygen concentrations inversely correlated with temperature (3.50&#x2013;7.28 mg&#xb7;L<sup>-1</sup>). At the inner bay (6 m depth), temperatures varied from 27.0 to 30.8 &#xb0;C, salinity ranged from 33.0 to 35.9, and oxygen concentrations declined from a peak of 7.93 mg&#xb7;L<sup>-1</sup> (March 2023) to 4.03 mg&#xb7;L<sup>-1</sup> (October 2023). The outer bay (10 m depth) showed intermediate conditions, with temperatures between 26.4 and 30.5 &#xb0;C, salinity from 32.7 to 35.8, and dissolved oxygen following the seasonal temperature pattern (3.51&#x2013;7.67 mg&#xb7;L<sup>-1</sup>) (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Additional <italic>in situ</italic> data from 1 m and 7 m depths at the rhodolith bed, and from 1 m depth at the inner bay, are presented in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref> (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Monthly summary of carbonate system parameters (e.g., pH<sub>T</sub>, TA, DIC, &#x3a9;<sub>arag,</sub> CO<sub>3</sub>
<sup>2-</sup>) and <italic>in situ</italic> environmental variables (temperature, salinity, dissolved oxygen) across sites and depths (Rhodolith bed: 15 m, Inner bay: 6 m, Outer bay: 10 m) in Gairaca Bay, categorized by climatic season.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Site/year-month</th>
<th valign="middle" align="center">Season</th>
<th valign="middle" align="center">TA <break/>(&#xb5;mol kg <sup>-1</sup>)</th>
<th valign="middle" align="center">ph<sub>T</sub>
</th>
<th valign="middle" align="center">DIC <break/>(&#xb5;mol kg <sup>-1</sup>)</th>
<th valign="middle" align="center">&#x2126;<sub>arag</sub>
</th>
<th valign="middle" align="center">CO<sub>3</sub> <break/>(&#xb5;mol kg <sup>-1</sup>)</th>
<th valign="middle" align="center">Salinity</th>
<th valign="middle" align="center">Temperature &#xb0;C</th>
<th valign="middle" align="center">O<sub>2</sub> mg&#xb7;L<sup>-1</sup>
</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="10" align="left">Rhodolith bed bottom (15 m depth)</th>
</tr>
<tr>
<td valign="middle" align="left">2023-3</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2469.30</td>
<td valign="middle" align="right">7.99</td>
<td valign="middle" align="right">2166.24</td>
<td valign="middle" align="right">3.55</td>
<td valign="middle" align="right">220.51</td>
<td valign="middle" align="right">34.50</td>
<td valign="middle" align="right">27.20</td>
<td valign="middle" align="right">7.04</td>
</tr>
<tr>
<td valign="middle" align="left">2023-4</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2411.50</td>
<td valign="middle" align="right">7.99</td>
<td valign="middle" align="right">2115.74</td>
<td valign="middle" align="right">3.46</td>
<td valign="middle" align="right">214.33</td>
<td valign="middle" align="right">34.00</td>
<td valign="middle" align="right">27.40</td>
<td valign="middle" align="right">4.37</td>
</tr>
<tr>
<td valign="middle" align="left">2023-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2376.80</td>
<td valign="middle" align="right">7.97</td>
<td valign="middle" align="right">2089.15</td>
<td valign="middle" align="right">3.38</td>
<td valign="middle" align="right">208.17</td>
<td valign="middle" align="right">34.00</td>
<td valign="middle" align="right">28.30</td>
<td valign="middle" align="right">5.64</td>
</tr>
<tr>
<td valign="middle" align="left">2023-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2357.80</td>
<td valign="middle" align="right">7.94</td>
<td valign="middle" align="right">2080.12</td>
<td valign="middle" align="right">3.24</td>
<td valign="middle" align="right">200.22</td>
<td valign="middle" align="right">35.00</td>
<td valign="middle" align="right">28.70</td>
<td valign="middle" align="right">7.28</td>
</tr>
<tr>
<td valign="middle" align="left">2023-7</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2451.70</td>
<td valign="middle" align="right">8.00</td>
<td valign="middle" align="right">2138.33</td>
<td valign="middle" align="right">3.64</td>
<td valign="middle" align="right">226.14</td>
<td valign="middle" align="right">35.00</td>
<td valign="middle" align="right">27.70</td>
<td valign="middle" align="right">7.19</td>
</tr>
<tr>
<td valign="middle" align="left">2023-8</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2295.90</td>
<td valign="middle" align="right">7.96</td>
<td valign="middle" align="right">2007.64</td>
<td valign="middle" align="right">3.41</td>
<td valign="middle" align="right">206.83</td>
<td valign="middle" align="right">33.50</td>
<td valign="middle" align="right">30.50</td>
<td valign="middle" align="right">6.26</td>
</tr>
<tr>
<td valign="middle" align="left">2023-9</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="right">2365.50</td>
<td valign="middle" align="right">8.02</td>
<td valign="middle" align="right">2036.28</td>
<td valign="middle" align="right">3.88</td>
<td valign="middle" align="right">235.66</td>
<td valign="middle" align="right">33.50</td>
<td valign="middle" align="right">29.90</td>
<td valign="middle" align="right">5.02</td>
</tr>
<tr>
<td valign="middle" align="left">2023-10</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="right">2287.30</td>
<td valign="middle" align="right">8.01</td>
<td valign="middle" align="right">1977.78</td>
<td valign="middle" align="right">3.60</td>
<td valign="middle" align="right">219.57</td>
<td valign="middle" align="right">33.60</td>
<td valign="middle" align="right">29.30</td>
<td valign="middle" align="right">4.17</td>
</tr>
<tr>
<td valign="middle" align="left">2023-11</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="right">2375.80</td>
<td valign="middle" align="right">7.92</td>
<td valign="middle" align="right">2108.56</td>
<td valign="middle" align="right">3.14</td>
<td valign="middle" align="right">194.21</td>
<td valign="middle" align="right">35.00</td>
<td valign="middle" align="right">28.50</td>
<td valign="middle" align="right">4.63</td>
</tr>
<tr>
<td valign="middle" align="left">2023-12</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="right">2446.40</td>
<td valign="middle" align="right">7.91</td>
<td valign="middle" align="right">2196.89</td>
<td valign="middle" align="right">3.00</td>
<td valign="middle" align="right">185.70</td>
<td valign="middle" align="right">34.20</td>
<td valign="middle" align="right">27.30</td>
<td valign="middle" align="right">4.04</td>
</tr>
<tr>
<td valign="middle" align="left">2024-1</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2435.00</td>
<td valign="middle" align="right">7.92</td>
<td valign="middle" align="right">2175.97</td>
<td valign="middle" align="right">3.06</td>
<td valign="middle" align="right">190.66</td>
<td valign="middle" align="right">34.80</td>
<td valign="middle" align="right">26.90</td>
<td valign="middle" align="right">4.23</td>
</tr>
<tr>
<td valign="middle" align="left">2024-2</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2372.00</td>
<td valign="middle" align="right">7.93</td>
<td valign="middle" align="right">2113.12</td>
<td valign="middle" align="right">3.06</td>
<td valign="middle" align="right">189.19</td>
<td valign="middle" align="right">34.20</td>
<td valign="middle" align="right">27.50</td>
<td valign="middle" align="right">4.99</td>
</tr>
<tr>
<td valign="middle" align="left">2024-3</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2380.10</td>
<td valign="middle" align="right">7.94</td>
<td valign="middle" align="right">2125.23</td>
<td valign="middle" align="right">2.97</td>
<td valign="middle" align="right">185.98</td>
<td valign="middle" align="right">34.70</td>
<td valign="middle" align="right">26.20</td>
<td valign="middle" align="right">4.23</td>
</tr>
<tr>
<td valign="middle" align="left">2024-4</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2358.10</td>
<td valign="middle" align="right">7.98</td>
<td valign="middle" align="right">2063.97</td>
<td valign="middle" align="right">3.37</td>
<td valign="middle" align="right">210.08</td>
<td valign="middle" align="right">35.10</td>
<td valign="middle" align="right">27.40</td>
<td valign="middle" align="right">4.67</td>
</tr>
<tr>
<td valign="middle" align="left">2024-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2388.10</td>
<td valign="middle" align="right">8.00</td>
<td valign="middle" align="right">2075.15</td>
<td valign="middle" align="right">3.57</td>
<td valign="middle" align="right">222.85</td>
<td valign="middle" align="right">35.60</td>
<td valign="middle" align="right">28.00</td>
<td valign="middle" align="right">5.10</td>
</tr>
<tr>
<td valign="middle" align="left">2024-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2355.90</td>
<td valign="middle" align="right">7.99</td>
<td valign="middle" align="right">2034.46</td>
<td valign="middle" align="right">3.70</td>
<td valign="middle" align="right">228.02</td>
<td valign="middle" align="right">35.30</td>
<td valign="middle" align="right">30.00</td>
<td valign="middle" align="right">3.50</td>
</tr>
<tr>
<td valign="middle" align="left">2024-7</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2412.10</td>
<td valign="middle" align="right">7.89</td>
<td valign="middle" align="right">2150.61</td>
<td valign="middle" align="right">3.07</td>
<td valign="middle" align="right">191.16</td>
<td valign="middle" align="right">35.90</td>
<td valign="middle" align="right">28.80</td>
<td valign="middle" align="right">5.49</td>
</tr>
<tr>
<th valign="middle" colspan="10" align="left">Inner bay (6 m depth)</th>
</tr>
<tr>
<td valign="middle" align="left">2023-3</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2420.20</td>
<td valign="middle" align="right">8.13</td>
<td valign="middle" align="right">2031.37</td>
<td valign="middle" align="right">4.42</td>
<td valign="middle" align="right">274.54</td>
<td valign="middle" align="right">34.50</td>
<td valign="middle" align="right">27.30</td>
<td valign="middle" align="right">7.93</td>
</tr>
<tr>
<td valign="middle" align="left">2023-4</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2416.10</td>
<td valign="middle" align="right">7.98</td>
<td valign="middle" align="right">2124.03</td>
<td valign="middle" align="right">3.43</td>
<td valign="middle" align="right">212.15</td>
<td valign="middle" align="right">34.00</td>
<td valign="middle" align="right">27.50</td>
<td valign="middle" align="right">3.62</td>
</tr>
<tr>
<td valign="middle" align="left">2023-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2436.40</td>
<td valign="middle" align="right">8.00</td>
<td valign="middle" align="right">2116.75</td>
<td valign="middle" align="right">3.73</td>
<td valign="middle" align="right">230.33</td>
<td valign="middle" align="right">34.70</td>
<td valign="middle" align="right">28.70</td>
<td valign="middle" align="right">5.20</td>
</tr>
<tr>
<td valign="middle" align="left">2023-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2391.10</td>
<td valign="middle" align="right">7.98</td>
<td valign="middle" align="right">2095.02</td>
<td valign="middle" align="right">3.43</td>
<td valign="middle" align="right">213.03</td>
<td valign="middle" align="right">34.80</td>
<td valign="middle" align="right">27.80</td>
<td valign="middle" align="right">7.20</td>
</tr>
<tr>
<td valign="middle" align="left">2023-7</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2457.60</td>
<td valign="middle" align="right">7.96</td>
<td valign="middle" align="right">2161.41</td>
<td valign="middle" align="right">3.49</td>
<td valign="middle" align="right">215.69</td>
<td valign="middle" align="right">34.90</td>
<td valign="middle" align="right">28.50</td>
<td valign="middle" align="right">6.50</td>
</tr>
<tr>
<td valign="middle" align="left">2023-8</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2294.30</td>
<td valign="middle" align="right">7.95</td>
<td valign="middle" align="right">2006.03</td>
<td valign="middle" align="right">3.42</td>
<td valign="middle" align="right">206.87</td>
<td valign="middle" align="right">33.50</td>
<td valign="middle" align="right">30.80</td>
<td valign="middle" align="right">6.94</td>
</tr>
<tr>
<td valign="middle" align="left">2023-9</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="right">2317.00</td>
<td valign="middle" align="right">8.03</td>
<td valign="middle" align="right">1986.73</td>
<td valign="middle" align="right">3.86</td>
<td valign="middle" align="right">234.33</td>
<td valign="middle" align="right">33.60</td>
<td valign="middle" align="right">30.20</td>
<td valign="middle" align="right">6.32</td>
</tr>
<tr>
<td valign="middle" align="left">2023-10</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="right">2281.50</td>
<td valign="middle" align="right">7.99</td>
<td valign="middle" align="right">1970.95</td>
<td valign="middle" align="right">3.68</td>
<td valign="middle" align="right">221.30</td>
<td valign="middle" align="right">33.00</td>
<td valign="middle" align="right">31.20</td>
<td valign="middle" align="right">4.03</td>
</tr>
<tr>
<td valign="middle" align="left">2023-11</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="right">2432.10</td>
<td valign="middle" align="right">7.98</td>
<td valign="middle" align="right">2133.12</td>
<td valign="middle" align="right">3.49</td>
<td valign="middle" align="right">216.44</td>
<td valign="middle" align="right">34.70</td>
<td valign="middle" align="right">27.60</td>
<td valign="middle" align="right">5.01</td>
</tr>
<tr>
<td valign="middle" align="left">2023-12</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="right">2342.50</td>
<td valign="middle" align="right">7.86</td>
<td valign="middle" align="right">2123.33</td>
<td valign="middle" align="right">2.62</td>
<td valign="middle" align="right">162.96</td>
<td valign="middle" align="right">34.50</td>
<td valign="middle" align="right">27.00</td>
<td valign="middle" align="right">4.43</td>
</tr>
<tr>
<td valign="middle" align="left">2024-1</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2365.20</td>
<td valign="middle" align="right">7.76</td>
<td valign="middle" align="right">2188.48</td>
<td valign="middle" align="right">2.25</td>
<td valign="middle" align="right">138.59</td>
<td valign="middle" align="right">34.20</td>
<td valign="middle" align="right">28.10</td>
<td valign="middle" align="right">4.50</td>
</tr>
<tr>
<td valign="middle" align="left">2024-2</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2316.40</td>
<td valign="middle" align="right">7.91</td>
<td valign="middle" align="right">2071.33</td>
<td valign="middle" align="right">2.88</td>
<td valign="middle" align="right">178.40</td>
<td valign="middle" align="right">34.50</td>
<td valign="middle" align="right">27.70</td>
<td valign="middle" align="right">4.66</td>
</tr>
<tr>
<td valign="middle" align="left">2024-3</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2422.20</td>
<td valign="middle" align="right">7.85</td>
<td valign="middle" align="right">2192.47</td>
<td valign="middle" align="right">2.77</td>
<td valign="middle" align="right">172.00</td>
<td valign="middle" align="right">35.20</td>
<td valign="middle" align="right">28.10</td>
<td valign="middle" align="right">4.86</td>
</tr>
<tr>
<td valign="middle" align="left">2024-4</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2371.10</td>
<td valign="middle" align="right">8.00</td>
<td valign="middle" align="right">2054.55</td>
<td valign="middle" align="right">3.61</td>
<td valign="middle" align="right">224.67</td>
<td valign="middle" align="right">35.50</td>
<td valign="middle" align="right">28.20</td>
<td valign="middle" align="right">4.91</td>
</tr>
<tr>
<td valign="middle" align="left">2024-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2288.20</td>
<td valign="middle" align="right">7.92</td>
<td valign="middle" align="right">2020.34</td>
<td valign="middle" align="right">3.17</td>
<td valign="middle" align="right">193.08</td>
<td valign="middle" align="right">34.00</td>
<td valign="middle" align="right">30.40</td>
<td valign="middle" align="right">4.32</td>
</tr>
<tr>
<td valign="middle" align="left">2024-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2371.30</td>
<td valign="middle" align="right">7.89</td>
<td valign="middle" align="right">2113.71</td>
<td valign="middle" align="right">3.01</td>
<td valign="middle" align="right">187.25</td>
<td valign="middle" align="right">35.90</td>
<td valign="middle" align="right">28.70</td>
<td valign="middle" align="right">5.48</td>
</tr>
<tr>
<th valign="middle" colspan="10" align="left">Outer bay (10 m depth)</th>
</tr>
<tr>
<td valign="middle" align="left">2023-3</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2440.00</td>
<td valign="middle" align="right">7.97</td>
<td valign="middle" align="right">2152.81</td>
<td valign="middle" align="right">3.37</td>
<td valign="middle" align="right">209.43</td>
<td valign="middle" align="right">34.30</td>
<td valign="middle" align="right">27.20</td>
<td valign="middle" align="right">7.04</td>
</tr>
<tr>
<td valign="middle" align="left">2023-4</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2399.20</td>
<td valign="middle" align="right">8</td>
<td valign="middle" align="right">2105.32</td>
<td valign="middle" align="right">3.43</td>
<td valign="middle" align="right">212.63</td>
<td valign="middle" align="right">33.90</td>
<td valign="middle" align="right">27.00</td>
<td valign="middle" align="right">3.46</td>
</tr>
<tr>
<td valign="middle" align="left">2023-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2443.90</td>
<td valign="middle" align="right">8</td>
<td valign="middle" align="right">2127.37</td>
<td valign="middle" align="right">3.69</td>
<td valign="middle" align="right">228.46</td>
<td valign="middle" align="right">34.70</td>
<td valign="middle" align="right">28.30</td>
<td valign="middle" align="right">5.52</td>
</tr>
<tr>
<td valign="middle" align="left">2023-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2431.80</td>
<td valign="middle" align="right">7.97</td>
<td valign="middle" align="right">2138.51</td>
<td valign="middle" align="right">3.41</td>
<td valign="middle" align="right">212.45</td>
<td valign="middle" align="right">35.00</td>
<td valign="middle" align="right">27.60</td>
<td valign="middle" align="right">6.88</td>
</tr>
<tr>
<td valign="middle" align="left">2023-7</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2335.90</td>
<td valign="middle" align="right">8.03</td>
<td valign="middle" align="right">2019.29</td>
<td valign="middle" align="right">3.6</td>
<td valign="middle" align="right">223.81</td>
<td valign="middle" align="right">34.90</td>
<td valign="middle" align="right">27.50</td>
<td valign="middle" align="right">7.67</td>
</tr>
<tr>
<td valign="middle" align="left">2023-8</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2457.60</td>
<td valign="middle" align="right">7.95</td>
<td valign="middle" align="right">2163.25</td>
<td valign="middle" align="right">3.55</td>
<td valign="middle" align="right">216.34</td>
<td valign="middle" align="right">33.60</td>
<td valign="middle" align="right">29.70</td>
<td valign="middle" align="right">5.61</td>
</tr>
<tr>
<td valign="middle" align="left">2023-9</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="right">2333.40</td>
<td valign="middle" align="right">7.95</td>
<td valign="middle" align="right">2046.94</td>
<td valign="middle" align="right">3.41</td>
<td valign="middle" align="right">206.97</td>
<td valign="middle" align="right">33.50</td>
<td valign="middle" align="right">30.10</td>
<td valign="middle" align="right">5.35</td>
</tr>
<tr>
<td valign="middle" align="left">2023-10</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="right">2320.50</td>
<td valign="middle" align="right">8.01</td>
<td valign="middle" align="right">2005.63</td>
<td valign="middle" align="right">3.75</td>
<td valign="middle" align="right">225.82</td>
<td valign="middle" align="right">32.70</td>
<td valign="middle" align="right">30.50</td>
<td valign="middle" align="right">3.87</td>
</tr>
<tr>
<td valign="middle" align="left">2023-11</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="right">2335.00</td>
<td valign="middle" align="right">7.97</td>
<td valign="middle" align="right">2053.41</td>
<td valign="middle" align="right">3.23</td>
<td valign="middle" align="right">201.46</td>
<td valign="middle" align="right">34.90</td>
<td valign="middle" align="right">27.30</td>
<td valign="middle" align="right">4.78</td>
</tr>
<tr>
<td valign="middle" align="left">2023-12</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="right">2478.00</td>
<td valign="middle" align="right">7.9</td>
<td valign="middle" align="right">2234.49</td>
<td valign="middle" align="right">2.92</td>
<td valign="middle" align="right">182.24</td>
<td valign="middle" align="right">34.60</td>
<td valign="middle" align="right">26.40</td>
<td valign="middle" align="right">4.58</td>
</tr>
<tr>
<td valign="middle" align="left">2024-1</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2420.90</td>
<td valign="middle" align="right">7.91</td>
<td valign="middle" align="right">2159.99</td>
<td valign="middle" align="right">3.09</td>
<td valign="middle" align="right">191.64</td>
<td valign="middle" align="right">35.00</td>
<td valign="middle" align="right">28.10</td>
<td valign="middle" align="right">5.00</td>
</tr>
<tr>
<td valign="middle" align="left">2024-2</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2330.80</td>
<td valign="middle" align="right">7.96</td>
<td valign="middle" align="right">2058.48</td>
<td valign="middle" align="right">3.18</td>
<td valign="middle" align="right">196.49</td>
<td valign="middle" align="right">34.10</td>
<td valign="middle" align="right">27.90</td>
<td valign="middle" align="right">5.26</td>
</tr>
<tr>
<td valign="middle" align="left">2024-3</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2435.80</td>
<td valign="middle" align="right">8.01</td>
<td valign="middle" align="right">2127.88</td>
<td valign="middle" align="right">3.56</td>
<td valign="middle" align="right">221.97</td>
<td valign="middle" align="right">34.70</td>
<td valign="middle" align="right">26.60</td>
<td valign="middle" align="right">4.73</td>
</tr>
<tr>
<td valign="middle" align="left">2024-4</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="right">2421.00</td>
<td valign="middle" align="right">7.99</td>
<td valign="middle" align="right">2122.72</td>
<td valign="middle" align="right">3.45</td>
<td valign="middle" align="right">215.07</td>
<td valign="middle" align="right">35.00</td>
<td valign="middle" align="right">27.10</td>
<td valign="middle" align="right">4.71</td>
</tr>
<tr>
<td valign="middle" align="left">2024-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2363.20</td>
<td valign="middle" align="right">7.94</td>
<td valign="middle" align="right">2085.04</td>
<td valign="middle" align="right">3.21</td>
<td valign="middle" align="right">200.1</td>
<td valign="middle" align="right">35.40</td>
<td valign="middle" align="right">28.10</td>
<td valign="middle" align="right">5.02</td>
</tr>
<tr>
<td valign="middle" align="left">2024-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2332.00</td>
<td valign="middle" align="right">7.94</td>
<td valign="middle" align="right">2045.35</td>
<td valign="middle" align="right">3.35</td>
<td valign="middle" align="right">205.41</td>
<td valign="middle" align="right">35.00</td>
<td valign="middle" align="right">30.10</td>
<td valign="middle" align="right">3.51</td>
</tr>
<tr>
<td valign="middle" align="left">2024-7</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="right">2388.20</td>
<td valign="middle" align="right">7.88</td>
<td valign="middle" align="right">2135.68</td>
<td valign="middle" align="right">2.97</td>
<td valign="middle" align="right">184.81</td>
<td valign="middle" align="right">35.80</td>
<td valign="middle" align="right">28.80</td>
<td valign="middle" align="right">4.93</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Mean wind speeds and water temperatures (the latter continuously measured with a HOBO sensor at the rhodolith bed bottom) exhibited a clear seasonal pattern influenced by climatic and oceanographic processes. Unless otherwise noted, all mean values are presented with their corresponding standard deviations (mean &#xb1; SD). In 2023, water temperature and wind speed exhibited marked seasonal variability associated with the upwelling season. The lowest mean water temperature was observed in March (24.73 &#xb1; 0.66 &#xb0;C), corresponding to the peak of the upwelling season, while the highest was recorded in June (28.67 &#xb1; 0.98 &#xb0;C), followed by a slight decrease in July (28.14 &#xb1; 0.60 &#xb0;C), reflecting the transition out of the upwelling phase. Wind speeds during this period peaked in July, reaching a monthly average of 7.80 &#xb1; 1.62 m&#xb7;s<sup>-1</sup>, with a maximum of 10.28 m&#xb7;s<sup>-1</sup>. The lowest wind speeds occurred in May and June, with daily minima of 2.04  m&#xb7;s<sup>-1</sup> and 1.69  m&#xb7;s<sup>-1</sup>, respectively, indicating a relaxation phase before re-intensification (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Average monthly wind speed and water temperature at the study site. Temperature was recorded <italic>in situ</italic> at the rhodolith bed (15 m depth) using HOBO data loggers.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g002.tif">
<alt-text content-type="machine-generated">Graph showing temperature (&#xb0;C) in red and wind speed (m.s-1) in blue from March 2023 to June 2024. Colored bands represent upwelling (blue), transition post-upwelling (red), non-upwelling (orange), and transition pre-upwelling (green) periods, highlighting seasonal changes.</alt-text>
</graphic>
</fig>
<p>In 2024, the seasonal pattern remained consistent, but wind speeds were generally stronger and temperatures slightly higher during the post-upwelling transition. The highest mean wind speed was observed in January (10.06 &#xb1; 1.16 m&#xb7;s<sup>-1</sup>), and high wind activity persisted through February to April (means between 8.30 and 8.53 m&#xb7;s<sup>-1</sup>), with peak gusts exceeding 13 m&#xb7;s<sup>-1</sup> in February (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). As wind strength declined in May (5.83 &#xb1; 1.97 m&#xb7;s<sup>-1</sup>), water temperatures rose to a maximum monthly mean of 27.95 &#xb1; 0.44 &#xb0;C, marking the post-upwelling transition. The coldest daily temperature in 2024 was 23.27 &#xb0;C, recorded in January, slightly earlier than in 2023.</p>
<p>Wind direction also followed a seasonal pattern, with prevailing northeasterly and easterly winds during upwelling months (January to March and December), reinforcing the wind-driven upwelling dynamics. In contrast, during transitional and non-upwelling periods, wind direction became more variable, with increased frequencies from the southeast, south, and southwest, indicating a weakening of the trade wind system and reduced upwelling potential (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_2</bold>
</xref>).</p>
<p>Precipitation in 2023 showed a pronounced seasonal pattern influenced by the upwelling season and associated climatic transitions. During the upwelling season (March to April) only 0.1 mm of rain was recorded on a single day in March, and a moderate onset of rainfall in April, for a total of 81.9 mm over 3 rainy days, with a peak of 54.1 mm. During the post-upwelling transition (May to July), rainfall initially decreased to 12.8 mm in May, but increased considerable in June, reaching 175.6 mm, with an extreme event of 102.4 mm on a single day. Rainfall decreased again in July to 51.1 mm, although distributed over 13 rainy days. In 2024, the first quarter of the year was extremely dry, with only 0.4 mm of rain in February. A slight increase occurred in April (5.9 mm) and May (6.8 mm), with isolated light rain events. June, marked the onset of the rainy season, with 126.9 mm, including 7 days with rainfall exceeding 5 mm, and a maximum daily value of 43.0 mm. In July, rainfall was 72.2 mm, although concentrated in fewer events, with one day of heavy rainfall peaking at 63.1 mm (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Seasonal precipitation trends in the area near Gairaca Bay during 2023 and 2024.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g003.tif">
<alt-text content-type="machine-generated">Line graph showing daily precipitation from March 2023 to July 2024, categorized by seasons: upwelling (blue), transition post-upwelling (pink), non-upwelling (orange), and transition pre-upwelling (green). Precipitation peaks significantly in June and November.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Carbonate system dynamics</title>
<p>A summary of carbonate system variables and <italic>in situ</italic> environmental parameters across the three main sites, rhodolith bed bottom (15 m), inner bay (6 m), and outer bay (10 m), is shown in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. A full dataset including additional depths and sites (e.g., rhodolith bed surface (1 m depth) and midwater (7 m depth), inner bay surface (1 m depth)) is provided in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref> (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>).</p>
<p>The seasonal averages and standard deviations reported below were calculated from the raw data presented in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>. For clarity and synthesis, values were grouped by site and climatic period (upwelling, non-upwelling, and transitional seasons), to better describe temporal variability across the study period.</p>
<p>Temporal variations were observed in the main physicochemical parameters and carbonate system variables in Gairaca Bay from April 2023 to July 2024. Total alkalinity (TA) exhibited higher values during the upwelling season in both years, reaching 2427.95 &#xb1; 29.4 &#x3bc;mol kg<sup>-1</sup> in 2023 at the rhodolith bed bottom (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). In 2024, the highest TA was recorded at the outer bay, with 2377.46 &#xb1; 35.2 &#x3bc;mol kg<sup>-1</sup> (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_7A</bold>
</xref>). In contrast, the lowest TA values occurred during the non-upwelling season at the inner bay (1 m depth) in 2023 (2316.3 &#xb1; 37.0 &#x3bc;mol kg<sup>-1</sup>), reflecting the influence of less alkaline surface waters over sandy bottoms (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_5A</bold>
</xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Monthly and interannual variation of carbonate system parameters at the rhodolith bed bottom. Panels show: <bold>(A)</bold> total alkalinity (TA, &#xb5;mol kg<sup>-1</sup>), <bold>(B)</bold> dissolved inorganic carbon (DIC, &#xb5;mol kg<sup>-1</sup>), <bold>(C)</bold> salinity, <bold>(D)</bold> pH<sub>T</sub> (total scale), <bold>(E)</bold> aragonite saturation state (&#x2126;<sub>arag</sub>), and <bold>(F)</bold> carbonate ion concentration (CO<sub>3</sub>
<sup>2-</sup>, &#xb5;mol kg<sup>-1</sup>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g004.tif">
<alt-text content-type="machine-generated">Six contour plots display various oceanographic parameters over time and in rhodolith bed bottom. Panels A-F show total alkalinity, dissolved inorganic carbon, salinity, pH, aragonite saturation, and carbonate ion concentration, respectively. All plots use color gradients to illustrate variations, with depth on the y-axis and time from 2023 to 2024 on the x-axis. Color bars indicate value ranges.</alt-text>
</graphic>
</fig>
<p>The total pH (pH<sub>T</sub>) showed a seasonal pattern consistent with TA fluctuations. The highest values were recorded during the non-upwelling season in 2023 at the rhodolith bed midwater (7 m depth), averaging 7.99 &#xb1; 0.03 (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_4</bold>
</xref>). A decrease in pH<sub>T</sub> was observed during the upwelling season, particularly in 2024, when the lowest value (7.94 &#xb1; 0.05) was recorded at the inner bay at 6 m depth (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_6</bold>
</xref>). However, overall variations in this variable across sites and seasons were relatively small, indicating a general stability of the carbonate system&#x2019;s pH throughout the study period.</p>
<p>Dissolved inorganic carbon (DIC) showed the highest concentrations during the pre-upwelling transition in 2023 at the outer bay (2134.05 &#xb1; 46.5 &#x3bc;mol kg<sup>-1</sup>), and during upwelling at the rhodolith bed bottom in both years (2122.60 &#xb1; 40.7 &#x3bc;mol kg<sup>-1</sup> in 2023 and 2109.86 &#xb1; 40.9 &#x3bc;mol kg<sup>-1</sup> in 2024) (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>).</p>
<p>Salinity exhibited both spatial and interannual variability. In 2023, the lowest salinity values were recorded at the inner bay (1 m depth) during the non-upwelling season (33.36 &#xb1; 0.29) (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_5C</bold>
</xref>). In contrast, in 2024, salinity increased significantly at the rhodolith bed midwater, reaching 35.17 &#xb1; 0.97 during the post-upwelling transition season (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_4C</bold>
</xref>).</p>
<p>The aragonite saturation state (&#x2126;<sub>arag</sub>) exhibited a seasonal pattern similar to pH<sub>T</sub>. In 2023, the highest &#x2126;<sub>arag</sub> values were recorded at the rhodolith bed surface during the non-upwelling season (3.65 &#xb1; 0.17) (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_3E</bold>
</xref>). However, a general decline in &#x2126;<sub>arag</sub> was observed across all sites in 2024, with the most pronounced decrease at the inner bay (6 m depth) during the upwelling season (average 3.13 &#xb1; 0.31), representing the lowest value recorded during the study (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_6E</bold>
</xref>).</p>
<p>The carbonate ion concentration (CO<sub>3</sub>
<sup>2-</sup>) showed pronounced seasonal and between year variability. In 2023, the highest average CO<sub>3</sub>
<sup>2-</sup> concentration was recorded at the inner Bay (6 m depth) during upwelling (274.54 &#xb1; 22.1 &#xb5;mol kg<sup>-1</sup>) (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure SM_6F</bold>
</xref>). Conversely, in 2024 at the same site and season, the lowest values were observed, averaging 138.59 &#xb1; 19.5 &#xb5;mol kg<sup>-1</sup>. Overall, CO<sub>3</sub>
<sup>2-</sup> concentrations tended to be higher during non-upwelling and transitional periods, and lower during upwelling events, particularly in 2024 across most sites (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>).</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Seasonal and spatial variability of carbonate system</title>
<p>Seasonal deltas, calculated as deviations from the mean, revealed interannual and spatial variability in carbonate system variables across the three sites: rhodolith bed bottom (15 m depth) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref>), inner bay (6 m depth) (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>), and outer bay (10&#xa0;m&#xa0;depth) (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>). In 2023, the strongest deviations were observed at rhodolith bed bottom, &#x394;TA reaching a maximum delta&#xa0;of +92.5 &#xb5;mol kg<sup>-1</sup> during upwelling and a minimum of &#x2013;89.5 &#xb5;mol kg<sup>-1</sup> during non-upwelling (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>). Similar but&#xa0;less pronounced patterns were detected in 2024, with &#x394;TA ranging from +58.2 to &#x2013;20.9 &#xb5;mol kg<sup>-1</sup>. At inner bay, &#x394;TA in 2023&#xa0;ranged approximately from &#x2013;27.7 to +88.7 &#xb5;mol kg<sup>-1</sup>, while in&#xa0;2024&#xa0;the spread was narrower (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6A</bold>
</xref>). Outer bay showed more moderate fluctuations across both years, with most &#x394;TA values remaining within approximately &#xb1;45 &#xb5;mol kg<sup>-1</sup> (range: &#x2212;71 to 85 &#xb5;mol kg<sup>-1</sup>) (<xref ref-type="fig" rid="f7">
<bold>Figure 7A</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Seasonal deltas for carbonate system variables measured in Gairaca Bay between 2023 and 2024 at rhodolith bed bottom (15 m). Panels show: <bold>(A)</bold> total alkalinity (TA), <bold>(B)</bold> dissolved inorganic carbon (DIC), <bold>(C)</bold> salinity, <bold>(D)</bold> total pH (pH<sub>T</sub>), and <bold>(E)</bold> saturation state aragonite (&#x2126;<sub>arag</sub>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g005.tif">
<alt-text content-type="machine-generated">Five bar charts labeled A to E, titled &#x201c;Rhodolith bed bottom,&#x201d; showing monthly changes from March 2023 to July 2024. Chart A depicts &#x394;TA (total alkalinity), B shows &#x394;DIC (dissolved inorganic carbon), C illustrates &#x394;Salinity, D represents &#x394;pH&#x1d40;, and E displays &#x394;&#x3a9;&#x1d43;&#x2b3;&#x1d43; (aragonite saturation state). Colors indicate different phases: upwelling (blue), transition post-upwelling (pink), non-upwelling (orange), and transition pre-upwelling (green).</alt-text>
</graphic>
</fig>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Seasonal deltas for carbonate system variables measured in Gairaca Bay between 2023 and 2024 at inner bay (6 m). Panels show: <bold>(A)</bold> total alkalinity (TA), <bold>(B)</bold> dissolved inorganic carbon (DIC), <bold>(C)</bold> salinity, <bold>(D)</bold> total pH (pH<sub>T</sub>), and <bold>(E)</bold> saturation state aragonite (&#x2126;<sub>arag</sub>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g006.tif">
<alt-text content-type="machine-generated">Bar charts display variations in the inner bay from March 2023 to July 2024. Panel A shows changes in total alkalinity, B in dissolved inorganic carbon, C in salinity, D in pH, and E in aragonite saturation. Colored bars indicate different periods: upwelling in blue, post-upwelling in pink, non-upwelling in orange, and pre-upwelling in green.</alt-text>
</graphic>
</fig>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Seasonal deltas for carbonate system variables measured in Gairaca Bay between 2023 and 2024 at outer bay (10 m). Panels show: <bold>(A)</bold> total alkalinity (TA), <bold>(B)</bold> dissolved inorganic carbon (DIC), <bold>(C)</bold> salinity, <bold>(D)</bold> total pH (pH<sub>T</sub>), and <bold>(E)</bold> saturation state aragonite (&#x2126;<sub>arag</sub>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g007.tif">
<alt-text content-type="machine-generated">Five bar charts illustrate various oceanographic changes in the Outer Bay from 2023 to 2024. Chart A shows changes in total alkalinity, B in dissolved inorganic carbon, C in salinity, D in pH, and E in aragonite saturation. The colored bars represent different phases: blue for upwelling, pink for transition post-upwelling, orange for non-upwelling, and green for transition pre-upwelling. Each chart depicts monthly data variations over the two-year period.</alt-text>
</graphic>
</fig>
<p>&#x394;DIC at rhodolith bed bottom showed the widest range in 2023, peaking at +88.3 &#xb5;mol kg<sup>-1</sup> during the transition pre-upwelling and dropping to &#x2013;130.8 &#xb5;mol kg<sup>-1</sup> during non-upwelling. In 2024, &#x394;DIC remained high, with values between +67.4 and &#x2013;74.1 &#xb5;mol kg<sup>-1</sup> (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). At inner bay, &#x394;DIC in 2023 followed a similar pattern but did not reach the same extremes, with the most negative value (&#x2212;115.89 &#xb5;mol kg<sup>-1</sup>) recorded in October during the non-upwelling season. In 2024, the variation decreased overall, although a maximum positive &#x394;DIC of 105.62 &#xb5;mol kg<sup>-1</sup> was observed during the upwelling season (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6B</bold>
</xref>).</p>
<p>The general behavior of salinity across the three sites shows a decreasing trend during the non-upwelling season, especially at outer bay and rhodolith bed bottom. In 2023, rhodolith bed bottom showed the strongest salinity deviations, reaching &#x2013;1.08 during the wet season and +0.42 during the transition post and pre-upwelling (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5C</bold>
</xref>). These patterns persisted in 2024 with similar magnitude. At inner bay, the salinity deltas show a contrasting pattern between 2023 and 2024. In 2023, there was a slight decreasing trend in salinity (mean of -0.25), with a higher proportion of negative values. In 2024, however, a clear increasing trend was observed (mean of 0.41) (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6C</bold>
</xref>).</p>
<p>At the rhodolith bed bottom, &#x394;pH<sub>T</sub> values were generally negative during upwelling and positive during non-upwelling. In 2023, they ranged from &#x2212;0.06 to +0.06, with peaks during the non-upwelling season. In 2024, the largest deviations occurred during the transition post-upwelling (&#x2212;0.07 to +0.03), while changes during upwelling remained moderate (&#x2212;0.04 to +0.02) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5D</bold>
</xref>). At inner Bay, &#x394;pH<sub>T</sub> values in 2023 were mostly positive across all seasons, reaching up to +0.18 during upwelling and +0.08 during non-upwelling. However, negative values were observed during the transition pre-upwelling (as low as &#x2212;0.09). In contrast, in 2024, &#x394;pH<sub>T</sub> values at inner bay were predominantly negative, particularly during the upwelling season, reaching as low as &#x2212;0.19. During the transition post-upwelling, fluctuations were more moderate, ranging from &#x2212;0.06 to +0.05 (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6D</bold>
</xref>). At outer bay, &#x394;pH<sub>T</sub> values in 2023 were mostly positive, with peaks during the transition post-upwelling (+0.06) and non-upwelling (+0.05) periods. In 2024, however, values exhibited greater variability, with a pronounced minimum of &#x2212;0.09 during the transition post-upwelling and a maximum of +0.05 during upwelling. Overall, both positive and negative &#x394;pH<sub>T</sub> values remained within &#xb1;0.1 units across years (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7D</bold>
</xref>).</p>
<p>&#x2126;<sub>arag</sub> deltas were generally lowest during upwelling and highest during non-upwelling across all sites. At the rhodolith bed bottom, 2023 showed the largest amplitude, with deltas ranging from &#x2212;0.36 to +0.52, while 2024 displayed a slightly narrower and more negative range (&#x2212;0.38 to +0.35) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5E</bold>
</xref>). Inner bay exhibited a different pattern, with much greater variability. In 2023, deltas ranged widely from &#x2212;0.71 to +1.09, and in 2024 the extremes were even more pronounced (&#x2212;1.08 to +0.28), indicating fluctuations in carbonate saturation (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6E</bold>
</xref>). At outer bay, &#x2126;<sub>arag</sub> remained relatively stable in both years, with deltas mostly contained between &#x2212;0.44 and +0.38 in 2023 and between &#x2212;0.39 and +0.19 in 2024 (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7E</bold>
</xref>).</p>
<p>Although no statistically significant differences were found between sites (PERMANOVA: R&#xb2; = 0.04, F = 0.76, p = 0.66), the outer bay exhibited the greatest changes in DIC (&#x394; &#x2248; 229 &#xb5;mol kg<sup>-1</sup>) and salinity (&#x394; = 3.1), whereas the inner bay showed the highest variability in pH<sub>T</sub> (&#x394; &#x2248; 0.37) and aragonite saturation state (&#x394;&#x2126;<sub>arag</sub> &#x2248; 2.18). Meanwhile, the rhodolith bed bottom recorded the largest variation in total alkalinity (&#x394;TA &#x2248; 182 &#xb5;mol kg<sup>-1</sup>). Overall, DIC was the most variable parameter across all sites.</p>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Seasonal variability in carbonate system parameters and contribution of key variables</title>
<p>PERMANOVA indicated no significant differences in carbonate system composition among sites or depths (p &gt; 0.05). However, seasonal differences were detected between the non-upwelling and upwelling periods. The transition pre-upwelling season closely resembled the upwelling period. Significant seasonal variation was also observed for temperature (F = 248.42, p &lt; 0.05), salinity (F = 49.02, p &lt; 0.05), TA (F = 7.65, p &lt; 0.00), and DIC (F = 2.54, p &lt; 0.00). The SIMPER analysis identified the carbonate system variables contributing most significantly to seasonal dissimilarities. In the upwelling versus non-upwelling contrast, DIC (38.9%) and TA (28.6%) were the major contributors to observed differences, both statistically significant (p &#x2264; 0.05). Other variables such as salinity, aragonite saturation state (&#x2126;<sub>arag</sub>), and calcite saturation state (&#x2126;<sub>cal</sub>) contributed less than 0.4% (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>SIMPER analysis summary showing carbonate system variables contributing most significantly to differences between climatic seasons.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Contrast</th>
<th valign="middle" align="center">Variable</th>
<th valign="middle" align="center">Contribution (%)</th>
<th valign="middle" align="center">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="5" align="center">Upwelling vs non-upwelling</td>
<td valign="middle" align="center">DIC</td>
<td valign="middle" align="center">38.9</td>
<td valign="middle" align="left">***</td>
</tr>
<tr>
<td valign="middle" align="center">TA</td>
<td valign="middle" align="center">28.6</td>
<td valign="middle" align="left">**</td>
</tr>
<tr>
<td valign="middle" align="center">Salinity</td>
<td valign="middle" align="center">0.4</td>
<td valign="middle" align="left">**</td>
</tr>
<tr>
<td valign="middle" align="center">&#x2126;<sub>cal</sub>
</td>
<td valign="middle" align="center">0.2</td>
<td valign="middle" align="left">**</td>
</tr>
<tr>
<td valign="middle" align="center">&#x2126;<sub>arag</sub>
</td>
<td valign="middle" align="center">0.2</td>
<td valign="middle" align="left">**</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="center">Transition post-upwelling vs non-upwelling</td>
<td valign="middle" align="center">DIC</td>
<td valign="middle" align="center">36.9</td>
<td valign="middle" align="left">*</td>
</tr>
<tr>
<td valign="middle" align="center">Salinity</td>
<td valign="middle" align="center">0.7</td>
<td valign="middle" align="left">***</td>
</tr>
<tr>
<td valign="middle" rowspan="7" align="center">Non-upwelling vs transition pre-upwelling</td>
<td valign="middle" align="center">DIC</td>
<td valign="middle" align="center">39</td>
<td valign="middle" align="left">***</td>
</tr>
<tr>
<td valign="middle" align="center">pCO<sub>2</sub>
</td>
<td valign="middle" align="center">34.6</td>
<td valign="middle" align="left">*</td>
</tr>
<tr>
<td valign="middle" align="center">TA</td>
<td valign="middle" align="center">25.6</td>
<td valign="middle" align="left">**</td>
</tr>
<tr>
<td valign="middle" align="center">Salinity</td>
<td valign="middle" align="center">0.4</td>
<td valign="middle" align="left">***</td>
</tr>
<tr>
<td valign="middle" align="center">&#x2126;<sub>cal</sub>
</td>
<td valign="middle" align="center">0.2</td>
<td valign="middle" align="left">***</td>
</tr>
<tr>
<td valign="middle" align="center">&#x2126;<sub>arag</sub>
</td>
<td valign="middle" align="center">0.2</td>
<td valign="middle" align="left">***</td>
</tr>
<tr>
<td valign="middle" align="center">pH<sub>T</sub>
</td>
<td valign="middle" align="center">0.07</td>
<td valign="middle" align="left">*</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Significance: ***p &#x2264; 0.001, **p &#x2264; 0.01, *p &#x2264; 0.05.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In the transition post-upwelling vs. non-upwelling comparison, DIC accounted for 36.9% of the dissimilarity (p = 0.03), while salinity contributed only 0.7% (p &#x2264; 0.00), despite its low explanatory power. In the non-upwelling versus transition pre-upwelling contrast, DIC again emerged as the dominant factor (39.0%, p &#x2264; 0.00), followed by pCO<sub>2</sub> (34.6%, p = 0.01) and TA (25.6%, p = 0.00). Although salinity, &#x2126;<sub>cal</sub>, &#x2126;<sub>arag</sub>, and pH<sub>T</sub> contributed to the differences, their individual contributions were relatively small (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). These results highlight the importance of DIC and TA in the seasonal differentiation of the carbonate system. However, the interaction between different variables can further modulate the variability of the carbonate system.</p>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Factors driving carbonate system variability</title>
<p>The variability of the carbonate system cannot be explained solely by individual factors. Temperature explained 39% of DIC variability, showing a statistically significant relationship (R&#xb2; = 0.39, p &lt; 0.001) (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8A</bold>
</xref>). In contrast, no significant relationship was found between temperature and pCO<sub>2</sub> (R&#xb2; = 0.02, p = 0.32), indicating that temperature alone was not a good predictor of pCO<sub>2</sub> variability in the study area (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Observed versus predicted values for <bold>(A)</bold> DIC and <bold>(B)</bold> pCO<sub>2</sub> in seawater samples from Gairaca Bay. <bold>(A)</bold> shows the simple linear regression between observed and predicted DIC using temperature as the sole predictor (R&#xb2; = 0.04; RMSE &#x2248; 48 &#xb5;mol kg<sup>-1</sup>). <bold>(B)</bold> presents the results of a multiple linear regression predicting pCO<sub>2</sub> based on temperature, salinity, total alkalinity (TA), DIC, and the DIC: TA ratio (R&#xb2; = 0.96; RMSE = 17 &#xb5;mol kg<sup>-1</sup>). Dashed lines indicate the 1:1 relationship.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g008.tif">
<alt-text content-type="machine-generated">Two scatter plots compare observed versus predicted values. Chart A shows DIC (dissolved inorganic carbon) with R&#xb2; = 0.4 and RMSE &#x2248; 48 micromoles per kilogram. Data points are scattered with moderate correlation. Chart B shows pCO&#x2082; (partial pressure of carbon dioxide) with R&#xb2; = 0.96 and RMSE &#x2248; 17 microatmospheres, exhibiting a strong correlation with data points closely aligned to the dashed line. Both charts depict observed values on the x-axis and predicted values on the y-axis.</alt-text>
</graphic>
</fig>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Simple linear regression models of temperature on carbonate system variables.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Variable</th>
<th valign="middle" align="center">Formula</th>
<th valign="middle" align="center">R&#xb2;</th>
<th valign="middle" align="center">RMSE (&#xb5;mol kg<sup>-1</sup> or &#xb5;atm)</th>
<th valign="middle" align="center">Temp significance</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">DIC</td>
<td valign="middle" align="left">
<inline-formula>
<mml:math display="inline" id="im3">
<mml:mrow>
<mml:mi>D</mml:mi>
<mml:mi>I</mml:mi>
<mml:mi>C</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi>a</mml:mi>
<mml:mo>.</mml:mo>
<mml:mi>T</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>m</mml:mi>
<mml:mi>p</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>b</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td valign="middle" align="left">0.39</td>
<td valign="middle" align="left">49.0 &#xb5;mol kg<sup>-1</sup>
</td>
<td valign="middle" align="left">*** p &lt; 0.001</td>
</tr>
<tr>
<td valign="middle" align="left">pCO<sub>2</sub>
</td>
<td valign="middle" align="left">
<inline-formula>
<mml:math display="inline" id="im4">
<mml:mrow>
<mml:mi>P</mml:mi>
<mml:mi>C</mml:mi>
<mml:msub>
<mml:mi>O</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mi>a</mml:mi>
<mml:mo>.</mml:mo>
<mml:mi>T</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>m</mml:mi>
<mml:mi>p</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>b</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>
</td>
<td valign="middle" align="left">0.02</td>
<td valign="middle" align="left">90.1 &#xb5;atm</td>
<td valign="middle" align="left">p = 0.32</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>***p &#x2264; 0.001.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>When considering additional hydrochemical variables, the multiple regression model achieved a markedly improved fit for pCO<sub>2</sub> (adjusted R&#xb2; = 0.96, RMSE = 18.1 &#xb5;atm) (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>; <xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8B</bold>
</xref>). In this model, temperature, salinity, and the DIC/TA ratio emerged as significant predictors, whereas total alkalinity (TA) and DIC alone did not significantly contribute to the explained variance.</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Multiple linear regression model predicting pCO<sub>2</sub> from carbonate system variables.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Predictor</th>
<th valign="middle" align="center">Estimate</th>
<th valign="middle" align="center">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Intercept</td>
<td valign="middle" align="left">-18618.5</td>
<td valign="middle" align="left">0.04 *</td>
</tr>
<tr>
<td valign="middle" align="left">Temp</td>
<td valign="middle" align="left">20.86</td>
<td valign="middle" align="left">&lt;0.00 ***</td>
</tr>
<tr>
<td valign="middle" align="left">Salinity</td>
<td valign="middle" align="left">10.25</td>
<td valign="middle" align="left">0.02 *</td>
</tr>
<tr>
<td valign="middle" align="left">TA</td>
<td valign="middle" align="left">5.28</td>
<td valign="middle" align="left">0.15</td>
</tr>
<tr>
<td valign="middle" align="left">DIC</td>
<td valign="middle" align="left">-5.86</td>
<td valign="middle" align="left">0.16</td>
</tr>
<tr>
<td valign="middle" align="left">DIC/TA</td>
<td valign="middle" align="left">20339.4</td>
<td valign="middle" align="left">0.04 *</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>-Adjusted R&#xb2;: 0.96; RMSE: 18.1 &#xb5;atm.</p>
</fn>
<fn>
<p>***p &#x2264; 0.001, *p &#x2264; 0.05.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_6">
<label>3.6</label>
<title>Carbonate system dynamics at the rhodolith bed bottom</title>
<p>At the rhodolith bed bottom site, the carbonate system parameters and salinity exhibited relatively stable average values, with notable seasonal variability (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). TA had a mean value of 2384.66 &#xb1; 49.87 &#xb5;mol kg<sup>-1</sup>, ranging from 2287.30 to 2469.30 &#xb5;mol kg<sup>-1</sup> (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>), DIC averaged 2097.37 &#xb1; 60.64 &#xb5;mol kg<sup>-1</sup>, with a range between 1977.78 and 2196.89 &#xb5;mol kg<sup>-1</sup> (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>) and salinity averaged 34.58 &#xb1; 0.73, fluctuating between 33.5 and 35.9 (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4C</bold>
</xref>). The pH<sub>T</sub> showed limited variability across seasons, with an overall mean of 7.96 &#xb1; 0.04. The maximum value (8.02) was recorded during the non-upwelling season in September 2023, while the minimum (7.89) occurred in July 2024 during the post-upwelling transition (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4D</bold>
</xref>). The &#x2126;<sub>arag</sub> averaged 3.36 &#xb1; 0.28 (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4E</bold>
</xref>). The CO<sub>3</sub>
<sup>2-</sup> had a mean value of 211.38 &#xb1; 13.28 &#xb5;mol kg<sup>-1</sup>, the highest concentration (235.66 &#xb5;mol kg<sup>-1</sup>) was observed in September 2023 during the non-upwelling period, coinciding with elevated &#x2126;<sub>arag</sub> and lower DIC values, while the lowest value (185.70 &#xb5;mol kg<sup>-1</sup>) was observed in December 2023 during the pre-upwelling transition, when pCO<sub>2</sub> peaked and &#x2126;<sub>arag</sub> declined (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4F</bold>
</xref>).</p>
<p>PERMANOVA revealed statistically significant differences among seasons (F = 3.0596; p = 0.01). SIMPER analysis further identified the variables contributing most to these seasonal dissimilarities at the rhodolith bed bottom site. The transition post-upwelling vs. transition pre-upwelling comparison exhibited the strongest dissimilarities, with DIC (41.4%, p = 0.04) and TA (92.7%, p = 0.03) showing statistically significant differences. In the upwelling vs. transition post-upwelling comparison, the major contributors were &#x2126;<sub>arag</sub> (34.7%) and &#x2126;<sub>calc</sub> (30.1%), followed by DIC (18.8%) and TA (6.7%) with no significant differences (p &gt; 0.1). In the upwelling vs. non-upwelling contrast, DIC (19.6%), &#x2126;<sub>arag</sub> (19.1%), and &#x2126;<sub>calc</sub> (18.3%) contributed most, followed by TA (16.8%), salinity (12.3%), and pCO<sub>2</sub> (12.1%) with no statistically significant differences detected (p &gt; 0.75).</p>
<p>Similarly, in the upwelling vs. transition pre-upwelling comparison, &#x2126;<sub>calc</sub> (31.7%), &#x2126;<sub>arag</sub> (29.4%), and pCO<sub>2</sub> (27.2%) were the dominant contributors without significant differences. The transition post-upwelling vs. non-upwelling comparison revealed salinity as the main contributor (21.6%), with no significant differences (p &gt; 0.30), likewise, no significant differences were found between non-upwelling and transition pre-upwelling periods, despite salinity accounting for 100% of the observed dissimilarity (p = 0.80).</p>
</sec>
<sec id="s3_7">
<label>3.7</label>
<title>Nutrient dynamics and their relationship with carbonate chemistry at the rhodolith bed bottom site</title>
<p>The analysis of nutrient concentrations revealed clear seasonal and between year variation. Maximum nitrate concentrations were recorded in June 2023, reaching 0.08 mg&#xb7;L<sup>-1</sup>. Regarding nitrite, the highest values were observed in July 2023 and April 2024, while the lowest concentration was recorded in December 2023 (0.03 mg&#xb7;L<sup>-1</sup>). For ammonium, the highest concentration was detected in August 2023 (0.01 mg&#xb7;L<sup>-1</sup>); however, from June to December 2023 and throughout 2024, ammonium levels were consistently below the detection limit. Phosphate concentrations also varied notably between years. In 2023, the highest concentration occurred in September (0.31 mg&#xb7;L<sup>-1</sup>), whereas the lowest was measured in December (0.22 mg&#xb7;L<sup>-1</sup>). In contrast, 2024 exhibited a significant increase, with a peak concentration of 0.39 mg&#xb7;L<sup>-1</sup> recorded in May; in all other sampled months, phosphate concentrations were below the detection limit (<xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>). Among the nutrient variables, a positive correlation was found between nitrite (NO<sub>2</sub>
<sup>-</sup>) and both CO<sub>3</sub>
<sup>2-</sup> (r = 0.59, p = 0.02) and &#x2126;<sub>arag</sub> (r = 0.54, p = 0.04). Additionally, nitrate (NO<sub>3</sub>
<sup>-</sup>) was positively correlated with phosphate (PO<sub>4</sub>
<sup>3-</sup>) (r = 0.53, p = 0.04).</p>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Monthly concentrations of dissolved inorganic nutrients at the rhodolith bed bottom in Gairaca Bay during 2023 and 2024.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Year-month</th>
<th valign="middle" align="center">Season</th>
<th valign="middle" align="center">Ammonium <break/>(NH<sub>4</sub>
<sup>+</sup>, mg&#xb7;L<sup>-1</sup>)</th>
<th valign="middle" align="center">Nitrate <break/>(NO<sub>3</sub>
<sup>-</sup>, mg&#xb7;L<sup>-1</sup>)</th>
<th valign="middle" align="center">Nitrite <break/>(NO<sub>2</sub>
<sup>-</sup>, mg&#xb7;L<sup>-1</sup>)</th>
<th valign="middle" align="center">Phosphate <break/>(PO<sub>4</sub>
<sup>3-</sup>, mg&#xb7;L<sup>-1</sup>)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">2023-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="left">0.001</td>
<td valign="middle" align="left">0.043</td>
<td valign="middle" align="left">0.038</td>
<td valign="middle" align="left">0.310</td>
</tr>
<tr>
<td valign="middle" align="left">2023-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="left">&lt;0.0001</td>
<td valign="middle" align="left">0.077</td>
<td valign="middle" align="left">0.042</td>
<td valign="middle" align="left">0.296</td>
</tr>
<tr>
<td valign="middle" align="left">2023-7</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="left">0.000</td>
<td valign="middle" align="left">0.056</td>
<td valign="middle" align="left">0.056</td>
<td valign="middle" align="left">0.287</td>
</tr>
<tr>
<td valign="middle" align="left">2023-8</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="left">0.010</td>
<td valign="middle" align="left">0.043</td>
<td valign="middle" align="left">0.036</td>
<td valign="middle" align="left">0.287</td>
</tr>
<tr>
<td valign="middle" align="left">2023-9</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="left">&lt;0.0001</td>
<td valign="middle" align="left">0.068</td>
<td valign="middle" align="left">0.047</td>
<td valign="middle" align="left">0.315</td>
</tr>
<tr>
<td valign="middle" align="left">2023-10</td>
<td valign="middle" align="left">Non-upwelling</td>
<td valign="middle" align="left">&lt;0.0001</td>
<td valign="middle" align="left">0.040</td>
<td valign="middle" align="left">0.037</td>
<td valign="middle" align="left">0.301</td>
</tr>
<tr>
<td valign="middle" align="left">2023-11</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="left">&lt;0.0001</td>
<td valign="middle" align="left">0.050</td>
<td valign="middle" align="left">0.036</td>
<td valign="middle" align="left">0.313</td>
</tr>
<tr>
<td valign="middle" align="left">2023-12</td>
<td valign="middle" align="left">Transition pre-upwelling</td>
<td valign="middle" align="left">&lt;0.0001</td>
<td valign="middle" align="left">0.042</td>
<td valign="middle" align="left">0.031</td>
<td valign="middle" align="left">0.219</td>
</tr>
<tr>
<td valign="middle" align="left">2024-1</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="left">&lt;0.0002</td>
<td valign="middle" align="left">0.023</td>
<td valign="middle" align="left">0.035</td>
<td valign="middle" align="left">&lt;0.004</td>
</tr>
<tr>
<td valign="middle" align="left">2024-2</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="left">&lt;0.0002</td>
<td valign="middle" align="left">0.012</td>
<td valign="middle" align="left">0.037</td>
<td valign="middle" align="left">&lt;0.004</td>
</tr>
<tr>
<td valign="middle" align="left">2024-3</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="left">&lt;0.0002</td>
<td valign="middle" align="left">0.048</td>
<td valign="middle" align="left">0.035</td>
<td valign="middle" align="left">&lt;0.004</td>
</tr>
<tr>
<td valign="middle" align="left">2024-4</td>
<td valign="middle" align="left">Upwelling</td>
<td valign="middle" align="left">&lt;0.0002</td>
<td valign="middle" align="left">0.001</td>
<td valign="middle" align="left">0.049</td>
<td valign="middle" align="left">&lt;0.004</td>
</tr>
<tr>
<td valign="middle" align="left">2024-5</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="left">&lt;0.0002</td>
<td valign="middle" align="left">0.015</td>
<td valign="middle" align="left">0.035</td>
<td valign="middle" align="left">0.390</td>
</tr>
<tr>
<td valign="middle" align="left">2024-6</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="left">&lt;0.0002</td>
<td valign="middle" align="left">0.015</td>
<td valign="middle" align="left">0.038</td>
<td valign="middle" align="left">&lt;0.004</td>
</tr>
<tr>
<td valign="middle" align="left">2024-7</td>
<td valign="middle" align="left">Transition post-upwelling</td>
<td valign="middle" align="left">&lt;0.0002</td>
<td valign="middle" align="left">0.008</td>
<td valign="middle" align="left">0.046</td>
<td valign="middle" align="left">&lt;0.004</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Values are expressed in mg&#xb7;L<sup>-1</sup> for ammonium (NH<sub>4</sub>
<sup>+</sup>), nitrate (NO<sub>3</sub>
<sup>-</sup>), nitrite (NO<sub>2</sub>
<sup>-</sup>), and phosphate (PO<sub>4</sub>
<sup>3-</sup>). Values below the detection limit are indicated with &#x201c;&lt;&#x201c;.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Correlations between carbonate chemistry variables and nutrient concentrations at the rhodolith bed bottom site revealed strong internal coherence within the carbonate system, but weak associations with nutrient dynamics (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9</bold>
</xref>). Total alkalinity (TA) showed a strong positive correlation with dissolved inorganic carbon (DIC) (&#x3c1; = 0.91, p &lt; 0.00), while DIC was also positively correlated with pCO<sub>2</sub> (&#x3c1; = 0.67, p = 0.00) and negatively with pH<sub>T</sub> (&#x3c1; = &#x2013;0.51, p = 0.04) and CO<sub>3</sub>
<sup>2-</sup> (&#x3c1; = &#x2013;0.51, p = 0.04). Aragonite saturation state proxies (pH<sub>T</sub> and CO<sub>3</sub>
<sup>2-</sup>) were highly correlated with each other (&#x3c1; = 0.89, p &lt; 0.00), and both were strongly and negatively correlated with pCO<sub>2</sub> (&#x3c1; = &#x2013;0.96 and &#x2013;0.89, respectively, p &lt; 0.00). Among the nutrients, only nitrite (NO<sub>2</sub>
<sup>-</sup>) showed a significant positive correlation with CO<sub>3</sub>
<sup>2-</sup> (&#x3c1; = 0.59, p = 0.02). All other correlations between nutrients (NH<sub>4</sub>
<sup>+</sup>, NO<sub>3</sub>
<sup>-</sup>, PO<sub>4</sub>
<sup>3-</sup>) and carbonate system variables were not statistically significant (p &gt; 0.05). Temperature also exhibited significant relationships with carbonate parameters. It was negatively correlated with TA (&#x3c1; = &#x2013;0.68, p = 0.00) and DIC (&#x3c1; = &#x2013;0.74, p = 0.00), and positively correlated with &#x2126;<sub>arag</sub> (&#x3c1; = 0.54, p = 0.02) (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9</bold>
</xref>).</p>
<fig id="f9" position="float">
<label>Figure&#xa0;9</label>
<caption>
<p>Spearman correlation matrix between carbonate system variables and nutrients at the rhodolith bed bottom site (n = 15). The color scale represents the strength and direction of the correlation coefficients (r), with blue indicating positive correlations and red indicating negative correlations. Blank cells indicate non-significant correlations (p &gt; 0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1626578-g009.tif">
<alt-text content-type="machine-generated">Correlation matrix showing relationships among various environmental parameters, including total alkalinity (TA), partial pressure of carbon dioxide (pCO2), pH, carbonate ions (CO3^2-), salinity, and nutrients like ammonium (NH4+), nitrate (NO3^-), nitrite (NO2^-), and phosphate (PO4^3-). Positive correlations are in red, negative in blue, with values indicating strength and significance (p-values). A color gradient bar on the right represents correlation coefficients from -1 to 1.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<sec id="s4_1">
<label>4.1</label>
<title>Seasonal and spatial patterns of the carbonate system</title>
<p>This study highlights the significant influence of seasonal variability on carbonate chemistry in tropical coastal ecosystems, particularly those affected by upwelling. Our results show a clear connection between the non-upwelling season, characterized by the rainy period and increased runoff from the Magdalena River (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>), and significant fluctuations in the carbonate system parameters in Gairaca Bay. These patterns are comparable to those reported for Moorea reef flats (<xref ref-type="bibr" rid="B32">Kleypas et&#xa0;al., 2011</xref>) and suggest that continental runoff plays a central role in modulating water chemistry in Gairaca, setting it apart from other tropical coastal systems where oceanic upwelling exerts a more dominant influence (<xref ref-type="bibr" rid="B62">S&#xe1;nchez-Noguera et&#xa0;al., 2018</xref>). Notably, freshwater inputs contribute substantially to the spatial variability of carbonate chemistry, reinforcing the importance of accounting for runoff in coastal biogeochemical assessments.</p>
<p>During upwelling peaks, DIC and TA increase, while pH<sub>T</sub> drops below 7.95 and &#x2126;<sub>arag</sub> decreases to ~3.0, similar to conditions observed in the Gulf of Papagayo (<xref ref-type="bibr" rid="B62">S&#xe1;nchez-Noguera et&#xa0;al., 2018</xref>). In contrast, the non-upwelling season reflects a diminished influence of cold, CO<sub>2</sub>-rich subsurface waters (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>), with pH<sub>T</sub> rising from 7.93&#x2013;7.99 (upwelling) to 8.01&#x2013;8.03 at sites such as the rhodolith bed surface and inner bay (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>). This increase in pH<sub>T</sub> is accompanied by a decrease in DIC, which drops from 2115.77 &#xb5;mol kg<sup>-1</sup> in April 2023 (upwelling, inner bay) to around 1973.10 &#xb5;mol kg<sup>-1</sup> in October (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Similarly, TA shows a slight decline, such as at rhodolith bed surface, where it decreases from 2487.40 &#xb5;mol kg<sup>-1</sup> in March to 2268.00 &#xb5;mol kg<sup>-1</sup> in October (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>). These changes are coupled with a decline in DIC, from 2115.77 &#xb5;mol kg<sup>-1</sup> in April (inner bay) to ~1973.10 &#xb5;mol kg<sup>-1</sup> in October, and a moderate decrease in TA, for example from 2487.40 to 2268.00 &#xb5;mol kg<sup>-1</sup> at the rhodolith bed surface. Conversely, &#x2126;<sub>arag</sub> and CO<sub>3</sub> concentrations increase during this period, reaching up to 3.88 and 235.66 &#xb5;mol kg<sup>-1</sup> at the rhodolith bed bottom, respectively.</p>
<p>Salinity also decreases (e.g., from 34.4 in March to 33.2 in October), while temperature rises to 30.5 &#xb0;C, compared to 27.0&#x2013;27.5 &#xb0;C during upwelling. Dissolved oxygen concentrations tend to decline, as observed at the rhodolith bed bottom (from 7.04 to 4.17 mg&#xb7;L<sup>-1</sup>). These warmer, fresher waters exhibit higher pH<sub>T</sub> and &#x3a9;<sub>arag</sub>, which thermodynamically lowers the energy barrier for CaCO<sub>3</sub> precipitation (<xref ref-type="bibr" rid="B45">Mucci, 1983</xref>; <xref ref-type="bibr" rid="B16">Cyronak et&#xa0;al., 2016</xref>). Carbonate speciation under elevated pH shifts the equilibrium toward CO<sub>3</sub>
<sup>2-</sup>, enhancing local carbonate ion availability (<xref ref-type="bibr" rid="B18">Dickson and Millero, 1987</xref>).</p>
<p>The freshwater influx into Gairaca Bay during the rainy season results in a distinct carbonate chemistry response, differentiating it from systems like Papagayo, dominated by oceanic upwelling with minimal freshwater influence (<xref ref-type="bibr" rid="B62">S&#xe1;nchez-Noguera et&#xa0;al., 2018</xref>), and Bocas del Toro, which experiences moderate terrestrial runoff (<xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>). Gairaca is subjected to pronounced seasonal and interannual variability in runoff, particularly from the Magdalena River during the rainy, non-upwelling season. This input amplifies fluctuations in pH<sub>T</sub>, TA, DIC, and &#x2126;<sub>arag</sub>, especially during periods of intense rainfall and river discharge, when upwelling is absent (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). Additionally, the Magdalena River transports organic matter and nutrients (<xref ref-type="bibr" rid="B56">Restrepo et&#xa0;al., 2006</xref>), whose remineralization can further alter DIC and pH<sub>T</sub> dynamics. Maximum runoff typically occurs from September to November, coinciding with weakened trade winds, enhanced coastal countercurrents, and the suppression of upwelling, thereby strongly influencing the carbonate system (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). Although spatial variability in water chemistry exists within Bocas del Toro due to terrestrial runoff and benthic metabolism (<xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>), Gairaca shows notably higher temporal variability driven by the strong seasonal freshwater inputs during the non-upwelling season. Nonetheless, the three sites evaluated within Gairaca Bay exhibit similar responses to these runoff and rainy conditions.</p>
<p>Spatial differences among the rhodolith bed bottom, inner bay, and outer bay sites were minimal, likely due to a generally well-mixed water column (see Section 4.3). However, the pronounced seasonal shifts highlight the interplay between oceanic and terrestrial influences, which may enable site-specific buffering mechanisms, such as localized photosynthesis or sediment-driven alkalinity release (<xref ref-type="bibr" rid="B63">Savoie et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). These seasonal shifts in carbonate chemistry not only reflect oceanographic-terrestrial interactions but may also have significant implications for the physiological performance of calcifying organisms (<xref ref-type="bibr" rid="B35">Li et&#xa0;al., 2022</xref>).</p>
<p>Finally, it is important to consider the analytical uncertainty associated with TA and DIC measurements in this study, which is estimated at &#xb1;10 &#xb5;mol kg<sup>-1</sup>. This level of precision corresponds to the &#x201c;weather goal&#x201d; defined by the Global Ocean Acidification Observing Network (GOA-ON), which is considered adequate for characterizing short-term variability and spatial gradients in coastal systems (<xref ref-type="bibr" rid="B33">Kortazar et&#xa0;al., 2020</xref>). Although not suitable for detecting long-term anthropogenic trends, this uncertainty is acceptable in highly dynamic environments like Gairaca Bay, where variability in TA and DIC often exceeded 100 &#xb5;mol kg<sup>-1</sup>, ensuring that the observed patterns remain robust and interpretable.</p>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Influence of seasonal variability and climatic conditions</title>
<p>During the study period, rainy days were recorded even during months that are typically dry, resulting in unusual hydrological conditions for that time of year (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). These unexpected rainfall events likely intensified freshwater inputs, leading to dilution effects, changes in salinity and alkalinity, and potential decoupling among carbonate system parameters. Elevated runoff may also have altered water column structure and enhanced biogeochemical fluxes, contributing to the variability observed in carbonate chemistry (<xref ref-type="bibr" rid="B14">Correa-Ramirez et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B46">Norzagaray et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B11">Cai et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B54">Reithmaier et&#xa0;al., 2023</xref>).</p>
<p>During the non-upwelling months, which coincide with the rainy season, Gairaca Bay exhibited reduced salinity, lower TA and DIC concentrations, and elevated pCO<sub>2</sub> levels. These shifts likely resulted from increased remineralization and microbial respiration, stimulated by the influx of terrestrial organic matter during intense rainfall. In coastal ecosystems, remineralization refers to the breakdown of organic matter into inorganic constituents. This process, particularly when driven by microbial activity, generates CO<sub>2</sub> and modifies porewater chemistry (<xref ref-type="bibr" rid="B8">Bayraktarov and Wild, 2014</xref>; <xref ref-type="bibr" rid="B53">Quintana et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B13">Cohn et&#xa0;al., 2024</xref>). However, the observed decrease in TA during the rainy season suggests that the dilution effect of freshwater inputs, which are typically low in TA, may outweigh any potential increase in TA from remineralization processes (<xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>).</p>
<p>Terrestrial&#x2013;marine interactions, especially those involving organic matter inputs from river discharge, mangroves, and seagrass meadows, are known to modulate carbonate chemistry in Caribbean coastal systems by altering TA and DIC concentrations (<xref ref-type="bibr" rid="B44">Mel&#xe9;ndez et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>). These biogeochemical dynamics are ecologically relevant for calcifying organisms such as corals and coralline algae, which are particularly sensitive to fluctuations in pH and carbonate saturation state (<xref ref-type="bibr" rid="B38">Martin and Hall-Spencer, 2017</xref>; <xref ref-type="bibr" rid="B66">Silbiger and Sorte, 2018</xref>). Increased freshwater runoff can suppress calcification and alter benthic community composition (<xref ref-type="bibr" rid="B21">Fabricius, 2005</xref>). However, rhodolith beds may partially buffer these effects by maintaining relatively stable micro-environmental conditions through photosynthesis, calcification, and microbial mediation (<xref ref-type="bibr" rid="B30">Isah et&#xa0;al., 2022</xref>).</p>
</sec>
<sec id="s4_3">
<label>4.3</label>
<title>Carbonate chemistry responses and delta patterns</title>
<p>Delta patterns revealed that climatic seasonality is a major driver of carbonate system variability across Gairaca Bay. Although statistically significant differences between sites were not detected, the magnitude of variation in parameters such as TA, DIC, &#x2126;<sub>arag</sub>, and pH<sub>T</sub>, differed notably across seasons (<xref ref-type="fig" rid="f5">
<bold>Figures&#xa0;5</bold>
</xref>-<xref ref-type="fig" rid="f7">
<bold>7</bold>
</xref>).</p>
<p>During the non-upwelling season, the variability between sampling locations was markedly higher for all measured parameters. TA showed the greatest inter-site difference, with a 90.7% relative difference, followed by pH<sub>T</sub> (83.2%), DIC (80.5%), and &#x2126;<sub>arag</sub> (68.7%). These pronounced variations suggest that localized processes, such as freshwater input, biological activity, and water column stratification, exert greater influence under low-mixing conditions when upwelling is absent. The rhodolith bed bottom recorded the highest TA variability, while the outer bay exhibited the greatest fluctuations in DIC and pH<sub>T</sub>. Conversely, the inner bay consistently showed lower variability across most parameters during this period. These findings highlight the complex interplay of regional and local factors in shaping carbonate system dynamics in tropical coastal environments (<xref ref-type="bibr" rid="B62">S&#xe1;nchez-Noguera et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B46">Norzagaray et&#xa0;al., 2020</xref>).</p>
<p>Consistent with these observations, temperature emerged as a key driver of DIC variability, due to its effects on solubility and biologically mediated processes such as calcification and respiration. Warmer temperatures generally reduce DIC solubility (<xref ref-type="bibr" rid="B4">Bakker et&#xa0;al., 1999</xref>), while biological processes are also temperature-dependent: enhanced respiration increases DIC concentrations, and decreased calcification reduces DIC uptake (<xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>). In contrast, pCO<sub>2</sub> was influenced by multiple interacting variables. The strong performance of the multiple linear model (R&#xb2; = 0.96; RMSE &#x2248; 18 &#xb5;atm) indicates that including salinity and the DIC/TA ratio significantly improves prediction accuracy, capturing the combined influence of freshwater input, mixing, and net community metabolism. Such complexity is typical in estuarine and coastal systems, where biogeochemical and physical drivers interact dynamically (<xref ref-type="bibr" rid="B11">Cai et&#xa0;al., 2021</xref>).</p>
<p>These findings emphasize that, while DIC dynamics are influenced by temperature, pCO<sub>2</sub> is shaped by a broader suite of environmental factors, including carbonate equilibrium and the balance between DIC and TA, which determines buffering capacity and resistance to pH changes (<xref ref-type="bibr" rid="B31">Khan et&#xa0;al., 2020</xref>). Understanding these interactions is crucial for predicting the impacts of environmental variability on coastal carbonate chemistry (<xref ref-type="bibr" rid="B12">Carstensen and Duarte, 2019</xref>).</p>
<p>Observed reductions in salinity, TA, and DIC during the non-upwelling season support the central role of freshwater inputs in modulating carbonate conditions (<xref ref-type="bibr" rid="B51">P&#xe9;rez et&#xa0;al., 2015</xref>). Biological processes, particularly photosynthesis, may further contribute to DIC drawdown (<xref ref-type="bibr" rid="B30">Isah et&#xa0;al., 2022</xref>), while decoupling between production and respiration can amplify pH variability in stratified coastal waters (<xref ref-type="bibr" rid="B12">Carstensen and Duarte, 2019</xref>).</p>
<p>In contrast, during the upwelling season, spatial differences across sampling sites diminished considerably. Relative differences in pH<sub>T</sub> (48.9%), TA (42.9%), DIC (20.0%), and &#x2126;<sub>arag</sub> (18.9%) were all lower, suggesting a homogenizing effect of upwelling, driven by the intrusion of cold, CO<sub>2</sub>-rich subsurface and enhanced vertical mixing across the water column, which together affect the entire bay. This influence was most pronounced at the outer bay, where pH<sub>T</sub> and &#x2126;<sub>arag</sub> variability peaked, while the rhodolith bed bottom and inner bay showed more moderate changes. The predominance of northeasterly and easterly winds during this season plays a key role in sustaining upwelling-favorable conditions, enhancing the upward advection of DIC-enriched subsurface water masses. This mechanism likely contributes to the observed increase in DIC concentrations during upwelling, compared to the more variable and stratified conditions of the non-upwelling season. The stronger divergence observed during the non-upwelling period may be further intensified by unusually high rainfall and riverine discharge (<xref ref-type="bibr" rid="B55">Restrepo and Kjerfve, 2000</xref>; <xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>), which enhance the effects of local processes under stratified conditions and limited vertical mixing (<xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>). On average, &#x2126;<sub>arag</sub> remained above the aragonite saturation threshold (&gt;1) at all sites (see <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table SM_1</bold>
</xref>), indicating generally favorable conditions for marine calcification (<xref ref-type="bibr" rid="B41">McGrath et&#xa0;al., 2019</xref>). Slightly higher values were observed at the outer bay, followed by the rhodolith bed bottom and inner bay.</p>
<p>Rhodolith bed bottom site exhibited the most stable &#x2126;<sub>arag</sub> values across seasons, while outer and inner bay sites showed greater variability. This stability supports the buffering potential of rhodolith habitats, consistent with previous findings that suggest rhodolith beds may act as microhabitat refugia under ocean acidification scenarios (<xref ref-type="bibr" rid="B15">Costa et&#xa0;al., 2023</xref>). Their capacity to maintain stable chemical conditions through biological and sedimentary processes may offer protection to vulnerable calcifiers. In contrast, shallow inner bay areas, dominated by sandy bottoms, are more susceptible to fluctuations in carbonate availability. These results highlight the interplay between regional climatic drivers and local environmental features in shaping the chemical mosaic of tropical marine systems (<xref ref-type="bibr" rid="B29">G&#xf3;mez et&#xa0;al., 2023</xref>).</p>
<p>Although direct measurements of metabolic or calcification rates were not conducted, the consistently elevated and stable &#x2126;<sub>arag</sub> values at the rhodolith bed suggest the presence of biologically mediated buffering. While average values across sites and depths were relatively similar, SIMPER analysis revealed that variables such as TA and DIC contributed significantly to seasonal dissimilarities at the rhodolith bed bottom, particularly between transition phases. These patterns support the notion that, despite limited spatial contrast in mean values, rhodolith beds may play a role in modulating carbonate chemistry under fluctuating conditions, especially during periods of environmental stress such as upwelling pulses or freshwater inputs (<xref ref-type="bibr" rid="B50">Pedersen et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>).</p>
</sec>
<sec id="s4_4">
<label>4.4</label>
<title>Nutrients and biogeochemical interactions</title>
<p>Nutrient dynamics at the rhodolith bed bottom revealed clear seasonal trends driven by upwelling, freshwater inputs, and biological processes. Nitrate concentrations peaked during June and July 2023 (0.07 and 0.06 mg&#xb7;L<sup>-1</sup> respectively), coinciding with the post-upwelling transition. These peaks likely reflect enhanced remineralization following the intrusion of subsurface waters (<xref ref-type="bibr" rid="B64">Schubert et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). In contrast, ammonium remained largely undetectable throughout 2024, while phosphate concentrations increased notably in May 2024 (0.39 mg&#xb7;L<sup>-1</sup>), coinciding with the onset of the rainy season and heightened river discharge.</p>
<p>Interestingly, &#x2126;<sub>arag</sub> showed a positive correlation with NO<sub>2</sub>
<sup>-</sup> y PO<sub>4</sub>
<sup>3-</sup>. While this relationship is not necessarily causal, it may reflect the combined influence of terrestrial runoff and <italic>in situ</italic> biogeochemical processes in this tropical coastal environment. Seasonal runoff in Gairaca Bay, particularly during the rainy season, introduces nutrients and organic matter that can stimulate biological activity and indirectly affect carbonate chemistry (<xref ref-type="bibr" rid="B3">Aronson et&#xa0;al., 2014</xref>). In coastal waters, nutrient enrichment and remineralization can influence pH and DIC, sometimes resulting in complex or even counterintuitive correlations with &#x2126;<sub>arag</sub> (<xref ref-type="bibr" rid="B11">Cai et&#xa0;al., 2021</xref>). Therefore, the observed positive correlation may be the result of overlapping hydrological and biological processes rather than a direct mechanistic link.</p>
<p>The carbonate system at the rhodolith bed is shaped by a complex interplay between pH<sub>T</sub>, DIC, &#x3a9;<sub>arag</sub>, and nutrient concentrations. A significant inverse relationship was found between DIC and both pH<sub>T</sub> and &#x3a9;<sub>arag</sub>, consistent with acid-base dynamics in marine systems: as DIC increases, pH<sub>T</sub> and &#x3a9;<sub>arag</sub> decrease. This pattern aligns with observations in other tropical regions, such as the northern South China Sea, where similar relationships were reported by <xref ref-type="bibr" rid="B60">Roberts et&#xa0;al. (2021)</xref>, highlighting the widespread influence of DIC on carbonate chemistry across diverse marine environments.</p>
<p>The positive correlation observed between temperature and aragonite saturation state (&#x2126;<sub>arag</sub>) can be attributed to the seasonal dynamics of the studied tropical coastal system. During the rainy season, surface water temperatures rise while upwelling intensity decreases, reducing the input of cold, CO<sub>2</sub>-rich subsurface waters and thereby limiting acidification from vertical mixing. Consequently, pH<sub>T</sub> and carbonate ion (CO<sub>3</sub>
<sup>2-</sup>) concentrations increase, resulting in elevated &#x2126;<sub>arag</sub> values. This pattern, characteristic of shallow tropical environments with seasonal forcing, contrasts with systems dominated by persistent upwelling, where the influx of subsurface waters typically lowers &#x2126;<sub>arag</sub> despite cooler temperatures (<xref ref-type="bibr" rid="B45">Mucci, 1983</xref>; <xref ref-type="bibr" rid="B74">Zeebe and Wolf-Gladrow, 2001</xref>; <xref ref-type="bibr" rid="B37">Manzello, 2010</xref>). However, the hysteresis effect described by (<xref ref-type="bibr" rid="B42">McMahon et&#xa0;al., 2013</xref>) underscores the importance of considering diel variability and metabolic feedbacks when interpreting correlations between &#x2126;<sub>arag</sub> and environmental drivers such as temperature.</p>
<p>Nevertheless, most correlations between pH<sub>T</sub> or DIC and nutrient concentrations were not statistically significant, indicating that nutrient variability does not directly control carbonate system dynamics in this setting. Although nutrients are essential for biological productivity, their short-term influence on pH<sub>T</sub> and DIC appears less pronounced than other drivers such as temperature, salinity, or air&#x2013;sea CO<sub>2</sub> exchange (<xref ref-type="bibr" rid="B28">Gattuso et&#xa0;al., 1998</xref>; <xref ref-type="bibr" rid="B74">Zeebe and Wolf-Gladrow, 2001</xref>). In tropical coastal systems, these physical and chemical factors often dominate carbonate chemistry, especially under stratified or runoff-influenced conditions (<xref ref-type="bibr" rid="B61">Salisbury et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B11">Cai et&#xa0;al., 2021</xref>).</p>
<p>This nutrient enrichment pattern supports the role of freshwater inputs in modulating carbonate dynamics in Gairaca Bay (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>). Riverine waters are typically low in TA and DIC but high in nutrients and temperature, promoting seawater dilution and enhanced biological CO<sub>2</sub> uptake through primary production (<xref ref-type="bibr" rid="B10">Borges and Gypens, 2010</xref>). Such correlations likely reflect the contribution of remineralization and biologically driven CO<sub>2</sub> uptake in shaping local carbonate dynamics (<xref ref-type="bibr" rid="B10">Borges and Gypens, 2010</xref>). These interactions likely explain some of the shifts in carbonate chemistry observed during transition periods, when freshwater delivery and biological activity are both elevated.</p>
<p>Although freshwater inputs from rainfall and runoff are well-documented drivers of biogeochemical variability in this region (<xref ref-type="bibr" rid="B58">Ricaurte-Villota et&#xa0;al., 2025</xref>) our data suggest that internal metabolic activity within rhodolith beds may help maintain conditions favorable to calcification, even under elevated pCO<sub>2</sub> and DIC levels. Future studies should investigate diel metabolic variability and long-term biogeochemical trends to better understand the mechanisms sustaining rhodolith bed resilience under changing oceanographic conditions.</p>
</sec>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>This study highlights the role of seasonal dynamics in modulating the carbonate system of Gairaca Bay, a tropical coastal ecosystem influenced by oceanic upwelling and freshwater runoff. Marked seasonal variations were observed in total alkalinity (TA), dissolved inorganic carbon (DIC), pH<sub>T</sub>, and aragonite saturation state (&#x3a9;<sub>arag</sub>), reflecting the combined effects of oceanographic forcing and terrestrial inputs.</p>
<p>Non-upwelling periods, coinciding with increased rainfall and riverine discharge, intensified spatial variability in TA and DIC, emphasizing the significance of localized processes such as water column stratification, organic matter inputs, and benthic remineralization. Conversely, upwelling periods produced more homogeneous carbonate conditions across all sites due to the influence of cold, CO<sub>2</sub>-rich subsurface waters.</p>
<p>Notably, rhodolith beds exhibited the most stable &#x3a9;<sub>arag</sub> values, especially relative to the greater seasonal variability observed at the outer and inner bay sites, reinforcing their potential role as localized buffers under fluctuating environmental conditions. This buffering capacity likely results from biological activities including photosynthesis, calcification, microbial processes, and sediment-mediated alkalinity release. Collectively, these processes may offer significant ecological protection to vulnerable calcifying organisms inhabiting or adjacent to rhodolith beds, particularly during episodic acidification events linked to upwelling pulses.</p>
<p>In contrast, (inner bay) shallow sandy-bottom areas demonstrated greater fluctuations in carbonate chemistry, making them more susceptible to variations in carbonate availability. This variability underscores the intricate interplay between regional climatic drivers and local environmental conditions, highlighting the necessity of considering both regional oceanographic processes and site-specific factors in managing and understanding tropical coastal carbonate chemistry.</p>
<p>Seasonal nutrient dynamics, influenced by rainfall-driven hydrological changes, showed elevated nitrate and phosphate concentrations during periods of increased precipitation. These nutrient influxes likely stimulated primary productivity and microbial respiration, further influencing local carbonate chemistry and demonstrating the interconnectedness of nutrient and carbonate system variability.</p>
<p>Additionally, our analysis indicated that temperature significantly influenced DIC variability due to its direct impact on carbon solubility and biologically mediated processes such as respiration and calcification. While temperature was a primary driver of DIC dynamics, pCO<sub>2</sub> variability was regulated by multiple interacting factors, including salinity and the DIC/TA ratio, highlighting the complex regulation of carbonate chemistry in coastal ecosystems.</p>
<p>Overall, this study emphasizes the functional importance of rhodolith beds in buffering carbonate chemistry fluctuations under variable climatic conditions. Although direct measurements of metabolic and calcification rates were beyond the scope of this study, consistently elevated and stable &#x3a9;<sub>arag</sub> values in rhodolith habitats strongly suggest biologically mediated buffering. Future research should prioritize <italic>in situ</italic> assessments of photosynthesis, respiration, and calcification rates in diverse rhodolith species, and investigate the role of associated microbial communities in modulating carbonate chemistry. Such research is essential for advancing our understanding of the resilience mechanisms within rhodolith beds and their broader ecological implications under ongoing climatic variability and ocean acidification scenarios.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>NR: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. CG: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. VP: Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing &#x2013; review &amp; editing. FA: Data curation, Investigation, Methodology, Software, Writing &#x2013; review &amp; editing. SN: Conceptualization, Data curation, Formal analysis, Project administration, Supervision, Validation, Writing &#x2013; review &amp; editing. RG: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing &#x2013; review &amp; editing.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research and/or publication of this article. This research was supported by the Colombian Institute for Educational Credit and Technical Studies Abroad (ICETEX) and the Ministry of Science, Technology, and Innovation of Colombia (MINCIENCIAS) under project code CD 82611 CT ICETEX 2021-1032. The lead author&#x2019;s doctoral studies were also funded through the Bicentennial Doctoral Scholarship Program. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>We are grateful to Cleimar Cay&#xf3;n and Jair L&#xf3;pez, for their assistance during fieldwork, as well as to Andr&#xe9;s Alvarado and Juan Garc&#xed;a for their help with logistics. We extend our thanks to the staff of the Water Quality Laboratory (Carlos Espa&#xf1;a, Laudys Guti&#xe9;rrez, and Isaac Romero) for their support in total alkalinity analyses; and to C&#xe9;sar Bernal and Marco Correa (INVEMAR) for their technical guidance in sample processing and ODV plotting. We also acknowledge the support of Iv&#xe1;n Villamil and the Mollusk Research Group for assisting in assembling the alkalinity measurement system and lending equipment. Special thanks to Colombia&#x2019;s National Natural Parks System (permit AUR 003-2021) and the Vice-Rectorate for Research at Universidad del Magdalena (especially Heidy P&#xe9;rez) for their support in permit management.</p>
</ack>
<sec id="s9" 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="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
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<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&#xa0;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/fmars.2025.1626578/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmars.2025.1626578/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
</sec>
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