# Winter Dynamics of Phytoplankton and Micronutrients in the Southern Ocean

Johannes J Viljoen, Ryan Cloete, Raïssa Philibert, Alexander Hayward, Ole Valk, Jean C Loock, Natasha R van Horsten, Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou, et al.

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## ► To cite this version:

Johannes J Viljoen, Ryan Cloete, Raïssa Philibert, Alexander Hayward, Ole Valk, et al. Winter Dynamics of Phytoplankton and Micronutrients in the Southern Ocean. Journal of Geophysical Research. Oceans, 2025, 130 (10), pp.e2025JC022431. 10.1029/2025jc022431. hal-05328749

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Distributed under a Creative Commons Attribution 4.0 International License
# JGR Oceans

## RESEARCH ARTICLE

10.1029/2025JC022431

**Key Points:**

* Total chlorophyll-*a* was lower in winter than in summer, but declined southward across the Polar Front, opposite to summer patterns

* A combination of macro- and micronutrients unique to each zone shaped phytoplankton abundance and community structure

* Phytoplankton group specific metal uptake influenced winter metal dynamics, such as cyanobacteria-cobalt and diatom-zinc associations

**Supporting Information:**

Supporting Information may be found in the online version of this article.

**Correspondence to:**

J. J. Viljoen and S. Fietz, 
j.j.viljoen@exeter.ac.uk; 
sfietz@sun.ac.za

**Citation:**

Viljoen, J. J., Cloete, R., Philibert, R., Hayward, A., Valk, O., Loock, J. C., et al. (2025). Winter dynamics of phytoplankton and micronutrients in the Southern Ocean. *Journal of Geophysical Research: Oceans*, 130, e2025JC022431. https://doi.org/10.1029/2025JC022431

Received 29 JAN 2025
Accepted 26 SEP 2025

**Author Contributions:**

**Conceptualization:** Johannes J. Viljoen, Susanne Fietz

**Data curation:** Johannes J. Viljoen, Ryan Cloete, Ole Valk, Jean C. Loock, Natasha R. van Horsten, Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou, Alakendra N. Roychoudhury, Susanne Fietz

**Formal analysis:** Johannes J. Viljoen, Ryan Cloete, Raïssa Philibert, Alexander Hayward, Ole Valk, Jean C. Loock, Natasha R. van Horsten, Hélène Planquette, Eva Bucciarelli

**Funding acquisition:** Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou,

# Winter Dynamics of Phytoplankton and Micronutrients in the Southern Ocean

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Johannes J. Viljoen¹,² ID, Ryan Cloete¹,³ ID, Raïssa Philibert⁴ ID, Alexander Hayward⁵ ID, Ole Valk¹ ID, Jean C. Loock¹ ID, Natasha R. van Horsten¹,³,⁶,⁷ ID, Hélène Planquette³ ID, Eva Bucciarelli³, Géraldine Sarthou³ ID, Alakendra N. Roychoudhury¹ ID, and Susanne Fietz¹ ID

¹Department of Earth Sciences, University of Stellenbosch, Stellenbosch, South Africa, ²Now at Department of Earth and Environmental Sciences, University of Exeter, Penryn, UK, ³CNRS, University Brest, IRD, Ifremer, LEMAR, Plouzané, France, ⁴Ecofish Research Ltd, Vancouver, BC, Canada, ⁵National Centre for Climate Research (NCKF), Danish Meteorological Institute, Copenhagen, Denmark, ⁶Southern Ocean Carbon-Climate Observatory, Council for Scientific and Industrial Research (CSIR), Cape Town, South Africa, ⁷Now at Department of Physics and Earth Sciences, Constructor University, Bremen, Germany

**Abstract** Combined observations of phytoplankton abundance, community structure, and trace metals in winter are scarce but crucial for understanding Southern Ocean biogeochemistry. This study provides the first early winter insights of phytoplankton-micronutrient dynamics in the Indian sector of the Southern Ocean. Depth-resolved measurements of chlorophyll-*a*, phytoplankton composition, and micronutrients iron (Fe), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd) reveal low phytoplankton abundance (0.27–0.08 µg L⁻¹ chlorophyll-*a*) and variable phytoplankton–micronutrient dynamics between the zones. In the Subtropical Zone, cyanobacteria, and haptophytes dominated, driven by higher temperatures, limiting macronutrients, Fe and Zn, and shaped Co and Mn through biological uptake. In the Subantarctic and Polar Frontal Zones, cyanobacteria contributions declined but continued to play a key role in shaping Co dynamics. Diatoms were limited by Mn, Zn, and silicic acid, enabling the dominance of prasinophytes. Other groups such as coccolithophores may have benefitted from the ability to substitute Zn for Cd and contributed to the formation of particulate Cd. Coccolithophores along *Phaeocystis* also contributed to particulate Cd in the Antarctic Zone, where Fe and Mn limited the abundance of the dominating diatoms. Diatoms, in turn, strongly contributed to particulate Zn. This perspective on phytoplankton-micronutrient relationships shows that despite their low productivity in the harsh low light wintertime Southern Ocean, phytoplankton continue to influence trace metal distribution and that there are strong phytoplankton group-specific associations with various essential metals, rather than Fe alone, that vary latitudinally.

**Plain Language Summary** Phytoplankton are microscopic photosynthetic organisms in the ocean. They form the base of the marine food web and play a vital role in planetary processes such as carbon cycling. Their growth and community composition depend on various factors, such as nutrient availability, including trace metals such as iron and zinc, which are essential for cellular processes. However, measurements combining phytoplankton and micronutrients are scarce, particularly during harsh Southern Ocean winters. This study provides the first insights into how phytoplankton interact with micronutrients in winter. We find that even in cold, low light conditions, when growth slows down, phytoplankton still strongly influence biologically important micronutrients. Although iron remains the main limiting nutrient of phytoplankton growth in much of the Southern Ocean, our results highlight that other micronutrients also matter. Different phytoplankton groups are associated strongly with some micronutrients and only weakly with others. Their winter uptake influences the nutrient availability and thus the phytoplankton community in the following spring. This helps us understand how changes in the ocean conditions, such as warming of the surface ocean, might shift the phytoplankton community composition in the future and affect the food web, carbon cycling, and climate systems they support.

## 1. Introduction

Phytoplankton community structure has a crucial influence on nutrient uptake, on microbial and zooplankton community structure, cell agglomeration, sinking, and degradation, and on carbon transfer and storage in the sediment (Deppeler and Davidson, 2017; Nissen et al., 2021; Terrats et al., 2023). In turn, the abundance and structure of phytoplankton communities is affected by various factors such as temperature, light, grazing, and the

© 2025. The Author(s). This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
**Alakendra N. Roychoudhury,**
Susanne Fietz

**Investigation:** Johannes J. Viljoen, Ryan Cloete, Raïssa Philibert, Jean C. Loock, Natasha R. van Horsten, Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou, Alakendra N. Roychoudhury, Susanne Fietz

**Methodology:** Johannes J. Viljoen, Ryan Cloete, Raïssa Philibert, Ole Valk, Jean C. Loock, Natasha R. van Horsten, Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou, Alakendra N. Roychoudhury, Susanne Fietz

**Resources:** Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou, Alakendra N. Roychoudhury, Susanne Fietz

**Software:** Johannes J. Viljoen, Raïssa Philibert

**Supervision:** Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou, Alakendra N. Roychoudhury, Susanne Fietz

**Validation:** Ryan Cloete, Ole Valk, Jean C. Loock, Natasha R. van Horsten

**Visualization:** Johannes J. Viljoen, Raïssa Philibert

**Writing – original draft:** Johannes J. Viljoen

**Writing – review & editing:** Johannes J. Viljoen, Ryan Cloete, Raïssa Philibert, Alexander Hayward, Ole Valk, Jean C. Loock, Natasha R. van Horsten, Hélène Planquette, Eva Bucciarelli, Géraldine Sarthou, Alakendra N. Roychoudhury, Susanne Fietz

availability of nutrients (Anderson et al., 2021; Hayward et al., 2025; Litchman et al., 2015; W. O. Smith and Lancelot, 2004).

The impact of trace metals, essential micronutrients for phytoplankton, is group or even species specific (Sunda, 2012), similar to silicic acid, which primarily affects silicifying groups (i.e., diatoms). Such a specific influence arises from differences in cellular requirements, because trace metals such as iron (Fe), cobalt (Co), zinc (Zn), manganese (Mn), copper (Cu), nickel (Ni), and cadmium (Cd) perform unique photosynthetic and metabolic functions (Bruland et al., 1991; Ho et al., 2003; Twining and Baines, 2013). Iron plays a central role in the photosynthetic electron transport and nitrogen acquisition in all phytoplankton (Morel et al., 2003). However, the Fe requirement differs between groups, as illustrated, for example, in the distinct Fe requirements between North Atlantic diatoms and flagellates (76 and 5 mmol per mol phosphorus, mmol mol⁻¹ P; Twining et al., 2015). In addition, cyanobacteria, that is, photosynthetic prokaryotes such as *Synechococcus*, often have even higher Fe requirements than eukaryotes such as diatoms (2–38 mmol mol⁻¹ P compared to <0.4 mmol mol⁻¹ P; Brand, 1991; Sunda and Huntsman, 2015). Recent measurements indicate that the cyanobacteria *Prochlorococcus* can exhibit much lower Fe:C quotas attributed to its small cell size and flexible photosystem composition (Cunningham and John, 2017; Zhang et al., 2024). Zn has a similarly important role in a wide range of cellular functions (Frausto da Silva and Williams, 2001; Vallee and Auld, 1990). Zn is critical for enzymes such as the carbonic anhydrase that facilitates the hydration and dehydration of carbon dioxide (CO₂) (Morel et al., 1994; Sunda, 1989). The Zn requirement for these ubiquitous processes though greatly differs between Southern Ocean groups, for example, between diatoms and flagellates (16 and 2–4 mmol mol⁻¹ P; Twining and Baines, 2013), and some photosynthetic prokaryotes (cyanobacteria) seem to lack an absolute Zn requirement (Sunda and Huntsman, 2015). Similarly, Cu is essential for photosynthetic electron transport (Bruland, 1980; Peers and Price, 2006) and Mn for the oxidation of water during photosynthesis (Peers and Price, 2004; Sunda, 1989). Both Cu and Mn requirements also vary by groups and regions. For example, estimated Cu quotas of diatoms in the Southern Ocean (1.4 mmol mol⁻¹ P; Cullen et al., 2003) are much lower than in the North Atlantic (9.5 mmol mol⁻¹ P; Twining et al., 2015).

Cd is also essential for many phytoplankton groups (Lee and Morel, 1995; Xu et al., 2007), most notably in a diatom specific carbonic anhydrase (Lane et al., 2005; Lane and Morel, 2000). The Cd cellular requirement can vary by over two orders of magnitude between groups and species (Ho et al., 2003; Twining and Baines, 2013). Other trace metals such as Co and Ni serve very specialized functions. Co is essential for the catalytic activity of cobalamin (vitamin B12), a cofactor in several enzymes. Ni is associated with the hydrolysis of urea—an important source of reduced nitrogen—widespread in phytoplankton—and with superoxide dismutase, which reduces oxidative stress particularly in cyanobacteria (Twining and Baines, 2013).

Adding further complexity, some phytoplankton can substitute one metal for another in some of the key pathways outlined above (Saito and Goepfert, 2008; Sunda and Huntsman, 1995). For example, the coccolithophore *Emiliania huxleyi* substitutes Cd and Co for Zn (Xu et al., 2007). Such capacity alleviates Zn limitation and provides a competitive advantage. In contrast, cyanobacteria have an absolute Co requirement that cannot be met by Zn, making Co particularly critical in cyanobacteria (Saito et al., 2002). Ultimately, trace metal availability, alongside group or species-specific cellular requirements, metabolic flexibility, and competition between groups for scarce nutrient resources shapes community structure (Browning et al., 2019; Klausmeier et al., 2004; Moore et al., 2013).

Phytoplankton in the Southern Ocean play a vital role in sustaining Antarctic food webs (Deppeler and Davidson, 2017), contributing to carbon export (Buesseler et al., 2020; Siegel et al., 2014), and regulating other global biogeochemical cycles (Moore et al., 2013; Nissen et al., 2021; Tagliabue et al., 2017). Throughout the year, pronounced changes in temperature, light, grazing, and nutrient availability drive a seasonal phytoplankton succession. Although much attention has been given to understanding these Southern Ocean dynamics during the productive spring and summer months (Flynn et al., 2023; Mendes et al., 2015; Viljoen et al., 2019), fewer studies have explored phytoplankton communities in the darker austral winter (Hayward et al., 2024; S. Smith et al., 2022; Weir et al., 2020). Studies investigating trace metal composition in parallel with phytoplankton community structure during this period are also scarce. Yet, winter conditions in most high-latitude marine systems, which experience extreme seasonal variability, favor very different phytoplankton communities than summer. For example, low light conditions often favor a shift toward smaller celled communities (Sunda and Huntsman, 1997), which alters remineralization, downward flux of biogenic particles, and carbon export (Henson
<figure><img src="image_4.png" /><figcaption>**Figure 1.** Station positions during the 2017 Winter Cruise along the GEOTRACES G1pr07 transect (30°E longitude). The red dot symbols indicate CTD stations (Table 1). The dashed horizontal lines indicate the frontal positions: Subtropical Front; Subantarctic Front; Polar Front; as well as the Southern Antarctic Circumpolar Current Front (sAACf) and the Southern Boundary of the ACC. Zones crossed: Subtropical Zone, Subantarctic Zone, Polar Frontal Zone and Antarctic Zone.
Currents: Agulhas Current, Agulhas Return Current. \*No trace metal samples were collected at St. 53.5°S.</figcaption></figure>

et al., 2019; Richardson and Jackson, 2007). These shifts then cascade through the food web and affect predator foraging (Moline et al., 2004, 2008). Gaining insight into winter phytoplankton communities and their interactions with trace metals is essential for a more comprehensive understanding of Southern Ocean ecosystem dynamics and its sensitivity to environmental change.

In this context, this study provides a fundamental first overview of the interactions between phytoplankton and micronutrients in the western Indian sector of the Southern Ocean, across all major frontal zones during early winter. By examining depth-resolved phytoplankton abundance and community composition alongside a unique suite of both dissolved and particulate trace metal concentrations, we explore group-specific phytoplankton relationships with micronutrient distributions and distinct patterns of micronutrient uptake, offering new insights into these dynamics during the early winter season in the Southern Ocean.

## 2. Methods

### 2.1. Cruise Track and Hydrography

Samples for this study were collected during the Winter Cruise of 2017 from 28 June to 13 July 2017 on the Research Vessel SA *Agulhas II* in the South-West Indian sector of the Southern Ocean. Eight stations were sampled northbound along the 30°E WOCE section IO6S (GEOTRACES section G1pr07) from the Marginal Ice Zone (MIZ) towards South Africa (Figure 1; Table 1). Data on temperature, salinity and positions of frontal systems have been published previously for this transect in Weir et al. (2020), Cloete, Loock, van Horsten, Fietz, et al. (2021), Cloete, Loock, van Horsten, Menzel Barraqueta et al. (2021), van Horsten (2022), and S. Smith et al. (2022). The MIZ during this winter transect was located at 61.7°S (de Jong et al., 2018). Hereafter, stations are denoted by their latitude, for example, St 58.5°S (Figure 1). For example, St. 58.5°S refers to the southernmost station sampled first and northernmost station St 41.0°S corresponds to WOCE station IO08 (Table 1).
<table><caption>Table 1<br>Station Information Along the 30°E Longitude (WOCE Section IO6S; GEOTRACES Section G1pr07)</caption><thead><tr><th>Station label</th><th>WOCE Station</th><th>Zone</th><th>Euphotic zone (m)</th><th>MLD (m)</th><th>Temp. (°C)</th><th>Tchl-α (µg/L)</th><th>POC (µM)</th><th>NPP (nM N d<sup>-1</sup>)</th><th>NO<sub>3</sub><sup>-</sup> (µM)</th><th>PO<sub>4</sub><sup>3-</sup> (µM)</th><th>Si(OH)<sub>4</sub> (µM)</th><th>pP (nmol/kg)</th></tr></thead><tbody><tr><td>St. 41.0°S<br>STF = 42.4°S</td><td>IO08</td><td>STZ</td><td>18</td><td>113 (122)</td><td>18.02 ± 0.01</td><td>0.27 ± 0.01</td><td>4.7 ± 0.4</td><td>497 ± 42*</td><td>2.6 ± 0.3</td><td>0.22 ± 0.00</td><td>2.91 ± 0.02</td><td>18 ± 3</td></tr><tr><td>St. 43.0°S</td><td>IO07</td><td>SAZ</td><td>56</td><td>197 (190)</td><td>10.55 ± 0.01</td><td>0.24 ± 0.03</td><td>4.79 ± 0.09</td><td>330</td><td>10 ± 1</td><td>0.68 ± 0.03</td><td>2.3 ± 0.1</td><td>21 ± 3</td></tr><tr><td>St. 45.5°S</td><td>IO06</td><td>SAZ</td><td>23</td><td>212 (220)</td><td>9.57 ± 0.05</td><td>0.23 ± 0.03</td><td>5.0 ± 0.7</td><td>ND</td><td>12.0 ± 0.1</td><td>0.98 ± 0.04</td><td>2.6 ± 0.2</td><td>16 ± 2</td></tr><tr><td>SAF = 46.2°S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>St. 48.0°S</td><td>IO05</td><td>PFZ</td><td>32</td><td>146 (134)</td><td>5.10 ± 0.01</td><td>0.19 ± 0.01</td><td>5 ± 1</td><td>300</td><td>22.5 ± 0.2</td><td>1.75 ± 0.02</td><td>5.28 ± 0.04</td><td>21 ± 1</td></tr><tr><td>PF = 49.3°S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>St. 50.6°S</td><td>IO04</td><td>AAZ</td><td>26</td><td>136 (124)</td><td>1.78 ± 0.01</td><td>0.12 ± 0.01</td><td>3.6 ± 0.6</td><td>ND</td><td>26.3 ± 0.2</td><td>1.89 ± 0.01</td><td>26.6 ± 0.7</td><td>19 ± 2</td></tr><tr><td>St. 53.5°S</td><td>IO03</td><td>AAZ</td><td>68</td><td>82</td><td>0.90 ± 0.00</td><td>0.11 ± 0.00</td><td>4.8 ± 0.5</td><td>80</td><td>24.7 ± 0.2</td><td>1.78 ± 0.08</td><td>39.8 ± 0.7</td><td>ND</td></tr><tr><td>St. 56.0°S</td><td>IO02</td><td>AAZ</td><td>ND</td><td>154 (132)</td><td>0.50 ± 0.00</td><td>0.09 ± 0.01</td><td>2.95 ± 0.06</td><td>ND</td><td>28.3 ± 0.1</td><td>1.98 ± 0.01</td><td>43.1 ± 0.2</td><td>14 ± 2</td></tr><tr><td>sAAcf = 56.5°S</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>St. 58.5°S</td><td>IO01</td><td>AAZ</td><td>56</td><td>159 (161)</td><td>-0.06 ± 0.00</td><td>0.08 ± 0.00</td><td>3.1 ± 0.2</td><td>40</td><td>28.1 ± 0.2</td><td>1.79 ± 0.04</td><td>46 ± 1</td><td>14 ± 4</td></tr></tbody></table>

Note. The station label indicates station latitudes, STF, SAF, and PF indicate major frontal systems in between stations (see Figure 1). Mixed layer depths (MLD) are reported for Niskin casts, with MLDs for GoFlo casts shown in parentheses (Weir et al., 2020). Median (±MAD) mixed layer temperature and concentrations are shown at all stations. MAD—Median Absolute Deviation. Net primary productivity (NPP) data for selected stations are from S. Smith et al. (2022) at the surface (5–10 m). The asterisk * indicates that NPP for St. 41.0°S represents the average (±SD) across the STZ during this cruise as NPP was not determined for this station specifically (S. Smith et al., 2022). pP = particulate phosphorus. ND = not determined. SBdy = 58.5°S.
Samples were collected from Niskin and GoFlo hydrocast stations. CTD casts allowed sampling at high resolution down to 500 m at all stations. Deep GoFlo trace metal-clean casts were also conducted at all stations, except for St 53.5°S, where intense storm conditions prevented deployment. Vertical profiles of temperature and salinity were recorded using the conductivity-temperature-depth (CTD) sensors during Niskin casts. Mixed layer depths (MLD) and euphotic zone depths were previously determined using Niskin CTD data, and MLD were also calculated for GoFlo casts (Weir et al., 2020) (Table 1). Mixed layer means or medians for all parameters, except for trace metals and particulate phosphorus (pP), were calculated using the MLD from Niskin CTD casts. For trace metals and pP concentrations, mixed layer medians were calculated using the MLD calculated from GoFlo casts. Euphotic zone depths were previously calculated as the depth at which 1% of surface PAR was measured (Kirk, 1994). See Weir et al. (2020) for PAR depth profiles that illustrate the euphotic depth across this transect. Similarly, frontal positions and zone denotations were previously determined (Weir et al., 2020), following the criteria outlined in Park et al. (1993) and Orsi et al. (1995). Based on the absence of vertical gradients in trace metals and ammonia (S. Smith et al., 2022), we assume minimal remineralization below the euphotic depth within the mixed layer.

## 2.2. Macronutrients, Dissolved and Particulate Trace Metals, and Particulate Phosphorus

The sampling protocols, analytical techniques and resulting concentrations for macronutrients have been described in detail for this cruise by Weir et al. (2020). All reported nitrate values refer to $NO_3^-$ concentrations, determined by subtracting nitrite ($NO_2^-$) from the measured $NO_3^-$ + $NO_2^-$ . A summary can be found in the Supporting Methods (Text S1.1 in Supporting Information S1). A suite of bioactive trace metals was determined at all stations except St. 53.5°S: iron (Fe), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd) following established dissolved and particulate methods (Lagerström et al., 2013; Planquette and Sherrell, 2012; Samanta et al., 2021; Text 1.2 in Supporting Information S1). For this study, dissolved Co and Cu were reanalysed following a UV-oxidation step (Text 1.2 in Supporting Information S1). Details pertaining to the sample bottle cleaning, particulate filter preparation, sampling, instrument calibrations, and analytical techniques for this cruise have previously been described (Cloete, Loock, van Horsten, Fietz, et al., 2021; Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021; Van Horsten et al., 2022). Dissolved and particulate fractions are denoted with a “d” and “p” respectively.

In this study we define the excess particulate trace metal concentrations as $pMetal_{excess} = pMetal_{total} - pMetal_{litho}$. Lithogenic fractions of particulate trace metal concentrations ($pMetal_{litho}$) were calculated using particulate aluminum (pAl) concentrations (Van Horsten et al., 2022) and universal crustal ratios (Rudnick and Gao, 2013). These ratios closely match bulk elemental ratios of Patagonian lithogenic sources (Demasy et al., 2024; Gaiero et al., 2003; Text 1.3 in Supporting Information S1), which are the expected primary dust inputs in this region. For most particulate trace metal concentrations, the lithogenic fraction was negligible in the mixed layer across the transect except for pFe (53%-90%) and pMn (20%-56%; Table S1 in Supporting Information S1). Lithogenic fractions were subsequently subtracted from total particulate concentrations for all metals. The remaining excess particulate trace metal concentrations (e.g., $pZn_{excess}$) are considered biogenic in this study, although authigenic contribution cannot be excluded (Sofen et al., 2023; Tagliabue et al., 2023). At stations where diatoms dominate, this approach may represent the upper estimate of lithogenic trace metal concentrations as some biogenic aluminum can be incorporated in some diatom silica walls (Tian et al., 2022).

Trace metal requirements of phytoplankton were estimated using the phytoplankton trace-metal-to-phosphorus ratios (TM:P) described in Cullen et al. (2003) and Twining and Baines (2013). Metal* (nM) was used to estimate phytoplankton metal requirements normalised to phosphate following Moore (2016) as Metal* (nM) = $dTM - R_{TM:P} \times PO_4^{3-}$. dTM is the measured dissolved trace metal concentration, $R_{TM:P}$ the estimated cellular trace metal to phosphorus (TM:P) ratio (i.e., assumed requirement) in phytoplankton, and $PO_4^{3-}$ the measured dissolved phosphate concentration. Metal* represents the difference between measured dissolved trace metal concentrations and estimated phytoplankton requirements associated with the available phosphate. The Metal* were determined for all dissolved trace metal measurements within the mixed layer, and for the requirements of various phytoplankton groups and regions based on available literature-derived cell quota estimates (TM:P). We also report the mixed layer median Metal* for each station. In this study, Metal* serves as an indicator of the relative micronutrient availability and phytoplankton region-specific requirements. Negative
Metal* values indicate potential deficiencies of micronutrient availability relative to the phytoplankton's estimated biological demand, signaling possible micronutrient limitation (Moore, 2016).

Our Metal* framework and interpretation rely on literature-derived cellular quotas and bulk phytoplankton TM:P ratios mostly from summer and spring studies. The lack of wintertime cellular TM:P measurements highlight a key knowledge gap that limits our understanding of the seasonal evolution of cellular stoichiometry. The seasonal mismatch could have biased our Metal* interpretations. For example, in the deep, low-light mixed layers of the winter Southern Ocean, phytoplankton growth is expected to be light limited despite acclimation strategies (Singh et al., 2025; Strzepek et al., 2019). Under these conditions, slow winter growth and division rates induce growth-rate dilution effects (Croot et al., 2011; Cullen et al., 2003) contributing to higher pTM:P at higher latitudes, as observed for Cd, Zn and Ni across this transect (Cloete, Loock, van Horsten, Fietz, et al., 2021; Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021; Cloete et al., 2025). As such, the summer/spring derived TM:P ratios used in the Metal* calculations should be considered a lower estimate of cellular stoichiometry.

Trace metal concentration data used for statistical analysis related to phytoplankton distribution for the upper 150 m, as well as all trace metal measurements in the upper 250 m, is available in a Zenodo repository (Viljoen et al., 2025). Full trace metal depth profiles can be found in related publications (Cloete, Loock, van Horsten, Fietz, et al., 2021; Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021; Cloete et al., 2025; Van Horsten, 2022; Van Horsten et al., 2022).

## 2.3. Phytoplankton Pigments and Community Structure

Seawater for pigment analyses was collected in opaque amber Nalgene bottles from Niskin CTD casts at six depths for most stations: 10, 25, 50, 75, 100, and 150 m. Pigment samples were not taken in duplicate due to water budget constraints. Seawater was filtered, under dim light, through 25 mm Whatmann® GF/F glass fibre filters (0.7 µm nominal pore size), whereafter filters were immediately stored at -80°C for post-cruise analysis. Phytoplankton pigments were extracted from the freeze-dried filters in methanol at -20°C and analyzed by High-Performance Liquid Chromatography (HPLC) at Laboratoire d'Océanographie de Villefranche/Mer (LOV-CNRS) as described by Ras et al. (2008). Detailed pigment concentration data is freely available in a Zenodo repository (Viljoen and Fietz, 2025).

Chlorophyll and diagnostic accessory pigments were employed in identifying the phytoplankton community structure by estimating group-specific chl-*a* contributions utilizing CHEMTAX (Mackey et al., 1996; Wright, 2008). The total chlorophyll-*a* (Tchl-*a*), defined as the sum of chlorophyll-*a* (chl-*a*) and divinyl chlorophyll-*a* (DVchl-*a*), was used as an indicator of total photosynthetic community biomass. The concentrations of DVchl-*a* specifically served as a biomass indicator for *Prochlorococcus*. The initial pigment ratios of the main phytoplankton groups included were based on the mean of a range of literature values and limits (Higgins et al., 2011; Wright, 2008). Initial pigment ratios were adjusted for winter phytoplankton ratios using surface microphytoplankton cell counts (Weir et al., 2020) and multiple CHEMTAX test runs before starting the final CHEMTAX analysis. The pigment data were grouped into four bins to account for regional variations in pigment ratios, assuming that the ratios were minimally influenced by vertical light gradients, due to the deep mixed layers (Vishnu et al., 2025). Chl-*a* derived for a specific group through CHEMTAX analysis, is referred to as [group]-chl*a*. For example, the chl-*a* concentration (µg L⁻¹) derived from diatoms is referred to as “diatom-chla.” Although microscopy comparison cannot fully validate the absolute chl-*a* contribution of each group, it does confirm the occurrence of key groups (e.g., coccolithophores as haptophytes-6). Detailed CHEMTAX methods, including phytoplankton groups, pigment choices, and optimized pigment ratios are provided in Supporting Information S1 (Text S1.4 and Table S2). A comparison of CHEMTAX results with *phytoclass* (Hayward et al., 2023) appears in Figure S1 in Supporting Information S1. CHEMTAX and *phytoclass* results showed strong agreement for most groups, except for pelagophytes, where CHEMTAX estimates were higher.

## 2.4. Statistical Analysis

In this study, to assess phytoplankton and micronutrient dynamics, we focused on the upper 150 m, which includes the mixed layer at most stations. In addition, to assess if trace metals showed nutrient-type profiles, dissolved trace metal depth profiles were compared to macronutrient depth profiles over the upper 1,000 m. Figures were created using Ocean Data View (Schlitzer, 2023) and the Python *matplotlib* package. Four sets of statistical methods were used in Python 3.11 and R (R Core Team, 2020) to complement the interpretation of
phytoplankton and trace metal data. Code availability is described at the end of this paper within the Data Availability Statement.

### 2.4.1. Pearson Correlation Between Dissolved Trace Metals and Macronutrients

To assess the depth profile characteristics of dissolved trace metals, Pearson correlation coefficients were calculated using the *pearsonr* Python function from the *scipy.stats* package. Nutrient-type behavior of dissolved trace metals was inferred if depth profiles of their concentrations were significantly (*p* < 0.05) and positively correlated versus the concentrations of phosphate over the upper 1,000 m water column. To supplement the investigation of phytoplankton group-specific trace metal relationships, correlation coefficients were also calculated between nitrate and silicic acid.

### 2.4.2. Kendall-Tau Correlation Between Phytoplankton and Micronutrients

Kendall-Tau correlation coefficients were calculated to assess the strength of the relationship of phytoplankton abundance (*Tchl-a*) and community composition with other variables using the *kendalltau* Python function from the *scipy.stats* package. Only data parallel-sampled at the same depths across the transect over the upper 150 m were included in the analysis. Variables that were included are: chemotaxonomic group *chl-a* concentrations, macronutrients, dissolved trace metals (i.e., micronutrients), particulate trace metals and pP. These latitudinal correlation calculations included all samples taken at each depth within the upper 150 m at all stations. The upper 150 m were chosen for correlation purposes as *Tchl-a* and phytoplankton pigments were sampled between 10 and 150 m. The MLD varied across the transect and, therefore, this approach included samples below the mixed layer at four stations where the MLDs were shallower than 150 m (Table 1). This does not affect the calculations of mixed layer means and medians (Table 1), which were calculated using only data from within the mixed layer. We acknowledge that Kendall-Tau linear correlations cannot fully capture multivariate interactions. Nevertheless, they complement the Pearson nutrient-type analysis and canonical correspondence analysis, enabling mechanistic interpretations of our observations.

### 2.4.3. Canonical Correspondence Analysis

Canonical correspondence analyses (CCA) were also used to assess the factors influencing the phytoplankton community structure. All measurements taken within the upper 150 m were included, that is, within the mixed layer at most stations. This approach assumes a uniform (low) light regime across the mixed layer, owing to deep mixing (Table 1; Figure S2 in Supporting Information S1). The CCAs were conducted in R using the *cca* function from the *Vegan* package (Oksanen et al., 2020). The biotic variables were the CHEMTAX-derived phytoplankton group concentrations (µg L⁻¹ of *chl-a*). The CCA was performed on three sets of environmental parameters, including macronutrients, dissolved trace metals and excess particulate trace metals. Each CCA was evaluated both including and excluding St. 41.0°S (six runs total). The Subtropical Zone (STZ) station St. 41.0°S was excluded from three CCAs due to its markedly distinct environmental conditions compared to Southern Ocean waters south of the Subtropical Front (STF). Permutation tests were run based on 999 permutations to evaluate the significance of the CCA axes and the significance (*p* < 0.05) of the environmental variables (Legendre et al., 2011). Variance inflation factors were calculated using the R *vif.cca* function as an indicator of the likelihood of collinearity of the variables (Tables S7–S9 in Supporting Information S1).

## 3. Results

### 3.1. Hydrography

This 30°E transect crosses the Antarctic Circumpolar Current (ACC) that flows eastward around Antarctica, and the Agulhas Return Current (ARC) that flows eastward north of the ACC (Barrett et al., 2018; Lutjeharms and Ansorge, 2001). The core of the ARC intersected our transect at ca. 40°S, thus at the time of sampling, the northernmost station at 41.0°S was located within the southern extent of the ARC (Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021). The STF (42.4°S), Subantarctic Front (SAF; 46.2°S) and Polar Front (PF; 49.3°S) as well as the Southern ACC Front (sAACf; 56.5°S) and the Southern Boundary (SBdy; 58.5°S) (Figure 1) were crossed during this transect (Weir et al., 2020). Accordingly, four Southern Ocean zones were distinguished: STZ, Subantarctic Zone (SAZ), Polar Frontal Zone (PFZ) and the Antarctic Zone (AAZ)
(Figure 1). Mixed layer potential temperature decreased from ca. 18°C at the northernmost station in the STZ to -0.06°C at the southernmost station in the AAZ (Table 1; Figure S3 in Supporting Information S1).

The MLDs for our transect (Table 1; Figure S2 in Supporting Information S1) are within the range of mean winter MLDs reported for this western Indian Southern Ocean region from Argo float data (Sallée et al., 2010). The MLD was relatively shallow at the northernmost station (113 m; Table 1). South of the STF, the MLDs were generally deeper, ranging from 212 m in the SAZ to 136 m in the PFZ. In the AAZ the MLDs ranged widely from an exceptionally shallow 82–154 m close to the sACCf and 159 m at the SBdy. The euphotic depths generally shoaled northwards from the AAZ (>56 m) to the STZ (18 m) except for St. 53.5°S, where the deepest euphotic zone was recorded (68 m), and at St 43.0°S (56 m) close to the STF (Table 1).

## 3.2. Macronutrients, Particulate Phosphorus, and Trace Metals

Macronutrient concentrations (Weir et al., 2020), pP concentrations (Cloete, Loock, van Horsten, Fietz, et al., 2021; Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021), and full depth profiles for selected trace metals (Cloete, Loock, van Horsten, Fietz, et al., 2021; Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021; Cloete et al., 2025; Van Horsten, 2022) have previously been described for this winter cruise. Here we present summary findings to provide context for our statistical analysis of the community composition. All macronutrients increased from north to south (Table 1; Figure S4 in Supporting Information S1) consistent with trends observed in summer (Mendes et al., 2015). Median mixed layer nitrate and phosphate concentrations increased by an order of magnitude from the STZ (2.6 ± 0.3 and 0.22 ± 0.00 µM respectively) to the southern AAZ (28.3 ± 0.1 and 1.98 ± 0.01 µM respectively), with the most pronounced increase occurring across the SAF (Table 1). Silicic acid concentrations were low north of the PF (<6 µM) and steeply increased across the PF to the AAZ (46 ± 1 µM). Median mixed layer pP was higher north of the PF than south (Table 1; Figure S5 in Supporting Information S1).

Mixed layer dFe decreased from the STZ and SAZ (0.11–0.13 nmol kg⁻¹) to the southern AAZ (0.04 ± 0.02 nmol kg⁻¹) with the steepest decrease observed across the SAF (Figure 2a). Vertical dFe versus phosphate distributions indicated nutrient- or hybrid type depth profiles at all stations (Figure 3). Mixed layer pFeexcess decreased from the STZ (0.14 ± 0.02 nmol kg⁻¹) and northern SAZ (0.16 ± 0.03 nmol kg⁻¹) to the PFZ (0.02 ± 0.02 nmol kg⁻¹) and steeply increased from the PFZ to the southern AAZ (0.15 ± 0.07 nmol kg⁻¹). North of the PF, dFe depth profiles correlated the strongest with nitrate and phosphate, while south of the PF, dFe depth profiles correlated the strongest with silicic acid (Figure 3). dMn and pMnexcess decreased from the STZ, where median values were 0.99 ± 0.03 nmol kg⁻¹ and 74.2 ± 10.1 pmol kg⁻¹, respectively, across the STF. South of the STF, concentrations remained relatively low, with median values ranging from 0.24 to 0.44 nmol kg⁻¹ for dMn and 9.2–18.6 pmol kg⁻¹ for pMnexcess (Figures 2a and 2e). However, dMn depth profiles, were only positively correlated to phosphate and nitrate at the two southernmost stations (Figure 3). Mixed layer dCo concentrations increased from the STZ (15.2 ± 0.6 pmol kg⁻¹) to the AAZ (34.5 ± 0.4 pmol kg⁻¹) with the steepest increase occurring around the SAF (Figure 2b). Contrary to dCo, mixed layer pCoexcess decreased southward from the STZ (3.6 ± 1.2 pmol kg⁻¹) to the AAZ (0.70 ± 0.08 pmol kg⁻¹; Figure 2f). The dCo depth profiles were positively correlated to phosphate and nitrate, at the two stations north and south of the STF and the northernmost AAZ station south of the PF (Figure 3).

Mixed layer dNi and dCu were often the most abundant micronutrients as they increased southward from the STZ (Figure 2d; Table S4 in Supporting Information S1). The depth profiles of dCu exhibited significant positive correlations with silicic acid across all stations, except in the PFZ, where dCu showed a stronger correlation with phosphate, and at the northernmost station of the AAZ, where no significant correlations with macronutrients were observed (Figure 3). The depth profiles of dNi also showed nutrient-type characteristics at most stations but only correlated to silicic acid at the southernmost station (Figure 3). Similar to dCu, mixed layer pCuexcess concentrations were lower north of the SAF (18.9–24.6 pmol kg⁻¹) than at stations farther south; the highest concentrations were observed in the southern AAZ (47.0 ± 0.7 pmol kg⁻¹; Figure 2h; Table S4 in Supporting Information S1). In contrast to the high dNi, median mixed layer pNiexcess was low across the transect (18.2–30.3 pmol kg⁻¹; Table S4 in Supporting Information S1) but showed weak increases south of the PF. Similarly to dNi and dCu, mixed layer dZn and dCd also increased steeply southwards from the STZ to the AAZ (Figure 2c). Mixed layer pZnexcess followed dZn's southward trend steeply increasing across the PFZ to maximum concentrations in the southern AAZ (0.12 ± 0.02 nmol kg⁻¹; Figure 2g). Mixed layer pCdexcess concentrations also increased across the PFZ, however,
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Mixed layer median concentrations across the 30°E transect of dissolved (left) and excess particulate (right) trace metals (Table S4 in Supporting Information S1). (a) dFe and dMn, (b) dCo, (c) dZn and dCd, (d) dNi and dCu, (e) pFe<sub>excess</sub> and pMn<sub>excess</sub>, (f) pCo<sub>excess</sub>, (g) pZn<sub>excess</sub> and pCd<sub>excess</sub>, (h) pNi<sub>excess</sub> and pCu<sub>excess</sub>. Error bars indicate the Median Absolute Deviation in the mixed layer (±MAD). Particulate trace metal concentrations shown here are the excess concentrations after removing the estimated lithogenic fractions (Section 2.2; Text 1.3 in Supporting Information S1). See Table 1 for mixed layer depths of each station and Figure 1 for the cruise map.</figcaption></figure>

concentrations were higher in the northern AAZ (19.2 ± 1.5 pmol kg⁻¹) compared to the southern AAZ (11.6 ± 2.2 pmol kg⁻¹; Figure 2g; Table S4 in Supporting Information S1). The depth profiles of dZn showed the strongest correlations with silicic acid and profiles of dCd with nitrate at most stations, however they both also showed significant positive correlations with phosphate at all stations (Figure 3).

### 3.3. Phytoplankton Abundance and Community Composition

Total chlorophyll-*a* (Tchl-*a*) median concentrations in the mixed layer ranged from 0.27 ± 0.01 µg L⁻¹ in the STZ to 0.08 ± 0.00 µg L⁻¹ in the AAZ (Table 1, Figure 4). Weir et al. (2020) previously published fluorometer-based chl-*a* for the same cruise and the HPLC-based Tchl-*a* from this study showed the same trends but were up to two-fold lower compared to the fluorometer-based chl-*a* (Table S3; see Supporting Results in Supporting Information S1). Winter mixed layer POC also decreased southward from 4.7 ± 0.4 µM in the STZ to peak concentrations of 5.4 ± 1.0 µM in the PFZ and decreased to a minimum of 2.95 ± 0.06 µM in the southern AAZ (Table 1). Furthermore, during winter, net primary productivity was higher in the STZ compared to the other zones within this Indian sector of the Southern Ocean (Table 1; Mendes et al., 2015).

The community composition in the upper 150 m changed from north to south. Diatoms typically dominated the low Tchl-*a* communities south of the PF, along with major contributions from the haptophyte *Phaeocystis* (Figure 4; Table S5 in Supporting Information S1). In contrast, *Phaeocystis* and other smaller flagellate groups, such as prasinophytes, typically dominated the higher Tchl-*a* communities north of the PF, and cyanobacteria in the STZ north of the STF. Overall, these chemotaxonomic phytoplankton composition estimates compared well
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Assessment of nutrient-type behavior considering depth profiles over the upper 1,000 m of the water column. Nutrient-type behavior and strongest correlations indicated in bold. Values represent Pearson correlation coefficients. Nutrient-type behavior is assumed herein if depth profiles for metals and a macronutrient (Nitrate—NO₃⁻, Phosphate—PO₄³⁻, or Silicate—Si(OH)₄) were significantly and positively correlated. Detailed analysis of full depth profiles can be found in Van Horsten (2022) for dFe, Cloete, Loock, van Horsten, Fietz, et al. (2021), Cloete, Loock, van Horsten, Menzel Barraqueta et al. (2021), Cloete et al. (2025) for dCd, dZn, and dNi. All correlation coefficients provided are for the strongest metal versus macronutrient relationship. *** indicate that correlation is significant at *p* < 0.001 level, ** indicate that correlation is significant at *p* < 0.01 level, * indicate that correlation is significant at *p* < 0.05 level; *n* = 12–16 for all. Note, a negative correlation or lack of significant correlation indicates lack of nutrient-type behavior. See Figure 1 for cruise map.</figcaption></figure>

with surface microscope nanoplankton cell counts (Table S6 in Supporting Information S1) that included diatoms, flagellates, and coccolithophores (Weir et al., 2020).

In the STZ, cyanobacteria (*Synechococcus* and *Prochlorococcus*) and *Phaeocystis* dominated the mixed layer communities with median mixed layer contributions of 27% and 29% respectively, whereas nanoplankton such as coccolithophores, cryptophytes and diatoms contributed 10%–14% to the Tchl-*a* (Figure 4). Below the relatively shallow MLD in the STZ, following a 10-fold decrease in Tchl-*a*, the contribution of small-celled phytoplankton groups such as cyanobacteria decreased (from 30% to 11%; Figure 5a). Cyanobacteria were also found in the SAZ (up to 14% ± 1%) and PFZ (3.2% ± 1.0%), entirely comprised of *Synechococcus*, but were absent south of the PF (Figure 4).

Chlorophytes, small-celled flagellates, were only observed in mixed layer communities in the SAZ (up to 7.5% ± 2.7%) and PFZ (13% ± 2%; Figure 4). Below the mixed layer, chlorophytes occurred in the STZ (14%; Figure 5a) and in the PFZ (27%; Figure 5d). Cryptophyte occurrence did not show any latitudinal trend (Figure 4), as highest contributions (13.8% ± 0.3%) were observed in the STZ as well as in the northern AAZ (7.2% ± 0.3%). Prasinophytes dominated communities in the SAZ and PFZ (25.8%–32.5% Figure 4) and the mixed layer at St. 53.5°S (31.1% ± 0.4%; Figure 4; Table S5 in Supporting Information S1). S. Smith et al. (2022) also noted the dominance of picoeukaryotes in the SAZ using flow cytometry (cf. Figure 6b in S. Smith et al., 2022), confirming the dominance of small-celled phytoplankton in the winter SAZ. Dinoflagellate contributions were generally low across the transect, with elevated contributions in the SAZ and peak contributions (6.4% ± 0.7%) at St. 53.5°S in the AAZ (Table S5 in Supporting Information S1).
<figure><img src="image_7.png" /><figcaption>**Figure 4.** Median mixed layer community composition (percentage contribution to Tchl-*a*) and Tchl-*a* concentrations (µg L⁻¹) in purple at each station across the transect (Table S5 in Supporting Information S1). See Figure S6 in Supporting Information S1 for section plots of Tchl-*a* and phytoplankton group-chla distribution. See Figure 1 for cruise map, frontal positions, and zones.</figcaption></figure>

Coccolithophore contributions followed no clear latitudinal trend (Figure 4). Highest contributions were observed in the STZ mixed layer (12.6% ± 0.6%; Figure 4) and just below the MLD (18%; Figure 5a). In contrast, in summer, coccolithophores contributed most in the SAZ (Gibberd et al., 2013; Mendes et al., 2015) and south of 60°S associated with ice-melt induced blooms (Viljoen et al., 2019). Confirming previous winter microscopic observations (Weir et al., 2020), coccolithophores also occurred in the waters of the SAZ through to the AAZ, even at the southernmost station St. 58.5°S at water temperatures below 1°C, albeit mostly with low (<5%) contributions to Tchl-*a* (Figures 4 and 5).

The haptophyte *Phaeocystis*, most likely *Phaeocystis antarctica* (Deppeler and Davidson, 2017; Mendes et al., 2015), abound (18%–29%) in the low Tchl-*a* (<0.13 µg L⁻¹ Tchl-*a*) AAZ communities south of the PF and in the STZ (Figure 4). However, similar to summer (Mendes et al., 2015; Viljoen et al., 2019), the estimated abundance of *Phaeocystis*, that is, *Phaeocystis*-derived chla, was higher north of the PF, especially in the STZ where they also dominated (up to 41% at the surface; Figure 5a) the communities along with cyanobacteria (Figure 4). Diatoms typically dominated south of the PF (Figure 4) with contributions of up to 61% in the southern AAZ (Figure 5g). In contrast to those diatom-dominated stations in the AAZ, at St. 53.5°S, *Phaeocystis* (22% ± 1%) and prasinophytes (31.1% ± 0.4%) dominated the mixed layer community surpassing diatoms (18% ± 1%). This confirms earlier microscopy-based findings (Weir et al., 2020) that indicated lowest microphytoplankton cell counts, lowest estimated diatom carbon contribution to POC (5%), and species diversity that aligned more with stations north of the PF than the other AAZ stations. However, below the relatively shallow MLD of 82 m, diatoms dominated (48%; Figure 5f).

3.4. Phytoplankton Community and Micronutrient Relationships

Latitudinal and vertical phytoplankton community shifts in the upper 150 m often coincided with changes in the trace metal distribution, resulting in several statistically significant correlations between specific groups and metals (Figure 6). Among these, cyanobacteria-chla had a significant positive correlation with pCo<sub>excess</sub>, the strongest of all groups, alongside a significant negative correlation with dCo. Additional positive correlations were observed between Cyanobacteria-chla and dFe, dMn, pMn<sub>excess</sub>, and pP. Chlorophyte-chla was only weakly
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Depth distribution of phytoplankton group-specific chla concentrations (µg L⁻¹) for each station across the 30°E transect. Blue dashed lines and text indicate the mixed layer depths (Table 1). See Figure S7 in Supporting Information S1 for average vertical contribution per zone and Figure S2 in Supporting Information S1 for density and fluorescence profiles. See Table S5 in Supporting Information S1 for median percent contribution of each phytoplankton group per station. Detailed community concentrations can be found in the online data repository (Data Availability Statement).</figcaption></figure>

negatively correlated to dCu, whereas cryptophyte-chla was positively correlated to dFe, pCo<sub>excess</sub>, and pP, and negatively to all other dissolved trace metals except dMn (Figure 6). Prasinophyte-chla was only significantly (positively) correlated to dFe, pCo<sub>excess</sub>, and pP (Figure 6), whereas Dinoflagellate-chla was positively correlated to pCo<sub>excess</sub> and negatively to dCo. Coccolithophore-chla was negatively correlated to most trace metals but positively to pCo<sub>excess</sub> and pP. *Phaeocystis-chla* correlated positively to pCo<sub>excess</sub>, pP, and dFe (Figure 6). Diatom-chla was positively correlated to several dissolved trace metals (dZn, dCd, dNi, dCu), yet pZn<sub>excess</sub> was the only particulate metal that significantly correlated with diatoms. pZn<sub>excess</sub> concentrations were indeed high in the AAZ, where diatom-chla concentration and contribution to Tchl-*a* (Figures 4 and 5), as well as cell contribution (Table S6 in Supporting Information S1) were also high.

Four CCA analyses were run in total, two each for dissolved metals and excess particulate metals, with and without the STZ (Figures 7a–7d). Initial analyses including all stations (Figures 7a and 7b) revealed a clear zonal separation, highlighting the distinctiveness of the STZ station (green circles in Figures 7a and 7b), where *Prochlorococcus* co-dominated. This station was mainly associated with dMn, pMn<sub>excess</sub>, dFe, pFe<sub>excess</sub>, and pCo<sub>excess</sub>. In these CCA with all stations, *Synechococcus*, had a strong association with pCo<sub>excess</sub> and dCo was negatively correlated to both cyanobacteria, although stronger with *Synechococcus* than *Prochlorococcus* (Figures 7a and 7b). Kendall-Tau analyses supported the strong association of both groups with Co, showing
<figure><img src="image_9.png" /><figcaption>**Figure 6.** Kendall-Tau correlation between concentrations of Tchl-a and phytoplankton group chla concentrations with concentrations of dissolved and particulate nutrients across the transect in the upper 150 m (includes a sample below the mixed layer for St.41°S, St.48°S, St.50.6°S, St.53.5°S): macronutrients, phosphorus (pP), dissolved and excess particulate trace metals. Note that for each Kendall-Tau correlation between two parameters, samples at eight stations and six sample depths were typically included, except at station 53.5°S. Trace metal data were not available at St. 53.5°S and thus only seven stations were included for trace metals. This results in a difference in the number of samples considered in correlations against macronutrients (n = 46) compared to the number of samples (n < 34) considered in correlations against trace metals. Bold values indicate significant correlations. *** indicate significance at *p* < 0.001 level, ** significance at *p* < 0.01, * significance at *p* < 0.05. “Cyano.” refers to the derived chla of both *Prochlorococcus* and *Synechococcus*.</figcaption></figure>

pCo<sub>excess</sub> and dCo correlated strongest with total cyanobacteria (Figure 6). DFe was also correlated with *Synechococcus*, and negatively with diatoms (Figure 7a). In the dissolved trace metal CCA (Figure 7a), all metals were significant except dNi and dCd (Table S7 in Supporting Information S1). However, dFe and dMn were the only metals with no likelihood of collinearity, while others, especially those positively associated with the AAZ, showed some likelihood of collinearity.

Considering the distinctiveness of the STZ (Figures 7a and 7b), CCAs including only stations south of the STF were added (Figures 7c and 7d). For dissolved trace metals south of the STF (Figure 7c), the first two CCA axes explained a combined 80% of the phytoplankton distribution and all dissolved trace metals were significantly associated with phytoplankton distribution except for dCd and dNi (Table S7 in Supporting Information S1). Stations north of the PF plotted separately from those south of the PF along the first axis and along the second axis the PFZ station were separated from the SAZ stations (Figure 7c). The micronutrients dFe and dMn were associated with SAZ stations and showed a positive correlation with *Synechococcus* similar to the Kendall-Tau correlations (Figure 6). In contrast, dCo showed a negative correlation to *Synechococcus*, dinoflagellates and pelagophytes in this CCA analysis and in the Kendall-Tau correlations. dZn and dCu showed collinearity (Table S7 in Supporting Information S1); both exhibited highest concentrations in the AAZ and were positively correlated with diatoms, consistent with the Kendall-Tau correlations. dZn showed the strongest association with diatoms and the southernmost AAZ stations (Figure 7c).

In the CCA for excess particulate trace metals south of the STF (Figure 7d), pMn<sub>excess</sub>, pCo<sub>excess</sub> and pZn<sub>excess</sub> were significant (Table S8 in Supporting Information S1). Similarly to the overall CCA, pCo<sub>excess</sub> was strongly associated with *Synechococcus* and stations in the SAZ. pMn<sub>excess</sub> exhibited a distribution pattern similar to
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Canonical Correspondence Analysis (CCA) ordination plots showing the relationship between phytoplankton group specific chl-*a* and dissolved trace metals (a, c), and excess particulate trace metals (b, d) as environmental parameters (Section 2.4.3). The first row shows the overall CCA analysis including all stations for (a) dissolved trace metals and (b) excess particulate trace metals, and the second row CCA analysis for only stations south of the Subtropical Front excluding the Subtropical Zone station for (c) dissolved trace metals and (d) excess particulate trace metals. Symbols represent the seven different stations along the transect where parallel trace metal and group composition were assessed. See Tables S7 and S8 in Supporting Information S1 for the significance of environmental variables and variance inflation factors. Note that denotation "pTM<sub>excess</sub>" is simplified in panels (b), (d) as "pTM".</figcaption></figure>
<caption>**Table 2**</caption>

Cellular Quotas (P-Normalized) and Bulk Metal:P Ratios (mmol mol⁻¹) of Various Phytoplankton Groups and Regions as Estimates of Phytoplankton Trace Metal Requirements

<table><thead><tr><th>Reference</th><th>Site/Phytoplankton</th><th>Fe:P</th><th>Mn:P</th><th>Co:P</th><th>Ni:P</th><th>Cu:P</th><th>Zn:P</th><th>Cd:P</th></tr></thead><tbody><tr><td>Twining and Baines (2013)</td><td>Southern Ocean—sPF<br>Diatoms</td><td><strong>1.42</strong></td><td><strong>0.54</strong></td><td>NA</td><td><strong>1.23</strong></td><td>NA</td><td><strong>15.7</strong></td><td>NA</td></tr><tr><td>Cullen et al. (2003)</td><td>Southern Ocean<br>Bulk—large Diatoms</td><td>NA</td><td>1.68</td><td><strong>0.15</strong></td><td>NA</td><td><strong>1.44</strong></td><td>11.09</td><td><strong>1.29</strong></td></tr><tr><td>Twining and Baines (2013)</td><td>Southern Ocean—sPF<br>Flagellates</td><td><strong>1.31</strong></td><td><strong>0.21</strong></td><td>NA</td><td><strong>0.47</strong></td><td>NA</td><td><strong>3.9</strong></td><td>NA</td></tr><tr><td>Twining and Baines (2013)</td><td>Southern Ocean—nPF<br>Flagellates</td><td><strong>0.87</strong></td><td><strong>0.22</strong></td><td>NA</td><td><strong>0.15</strong></td><td>NA</td><td><strong>2</strong></td><td>NA</td></tr><tr><td>Twining and Baines (2013)</td><td>Temperate Pacific Diatoms</td><td>2.68</td><td>0.4</td><td>0.05</td><td>0.28</td><td>NA</td><td>5.5</td><td>NA</td></tr><tr><td>Twining and Baines (2013)</td><td>Temperate Pacific Flagellates</td><td><strong>3</strong></td><td><strong>0.38</strong></td><td><strong>0.17</strong></td><td><strong>0.2</strong></td><td>NA</td><td><strong>1.2</strong></td><td>NA</td></tr><tr><td>Twining and Baines (2013)</td><td>Temperate Pacific<br>Pico</td><td><strong>4.6</strong></td><td><strong>0.31</strong></td><td><strong>0.12</strong></td><td><strong>0.22</strong></td><td>NA</td><td><strong>0.93</strong></td><td>NA</td></tr><tr><td>Twining et al. (2019)</td><td>Tropical Indian Ocean Bulk Cells</td><td><strong>0.9</strong></td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>Twining et al. (2011)</td><td>Equatorial Pacific<br>Bulk</td><td>4.7</td><td>0.53</td><td>0.07</td><td>1.1</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>Kuss and Kremling (1999)</td><td>North Atlantic<br>Bulk Flagellates</td><td>4.6</td><td>1.6</td><td>0.19</td><td>1.4</td><td>0.37</td><td>1.9</td><td>0.51</td></tr><tr><td>Tovar-Sanchez et al. (2006), Nuester et al. (2012)</td><td>North Atlantic Trichodesium</td><td>5–31</td><td>1–5</td><td>0.01–0.15</td><td>1–8</td><td>0.4–2.1</td><td>0.2–13</td><td>0.02–0.13</td></tr><tr><td>Twining et al. (2015)</td><td>North Atlantic<br>Diatoms</td><td>76</td><td>2.3</td><td>3.1</td><td>0.45</td><td>9.5</td><td>12</td><td>NA</td></tr><tr><td>Twining et al. (2015)</td><td>North Atlantic<br>Flagellates</td><td>5.0</td><td>0.44</td><td>0.14</td><td>0.32</td><td>5.3</td><td>1.8</td><td>NA</td></tr><tr><td>Twining et al. (2015)</td><td>North Atlantic<br>Pico</td><td>5.0</td><td>0.34</td><td>0.15</td><td>0.48</td><td>4.6</td><td>1.2</td><td>NA</td></tr><tr><td>Ho et al. (2003)</td><td>Emiliania huxleyi (Coccolithophore)</td><td>3.5</td><td>7.1</td><td>0.29</td><td>NA</td><td>0.07</td><td>0.38</td><td>0.36</td></tr></tbody></table>

Note. This table is a combination of adapted versions of tables and figures contained in Twining and Baines (2013) with some additions from other regions for comparison. sPF—south of the Polar Front; nPF—north of the Polar Front. Bold values indicate ratios used for Metal* calculations. NA indicates ratios are not available.

pCo$_{excess}$ but showed a stronger association with pelagophytes and prasinophytes, with greater variation along the first CCA axis. This suggests that differences in pMn$_{excess}$ between SAZ and PFZ stations were less pronounced than those observed for pCo$_{excess}$ at the same stations. Similarly, pZn$_{excess}$ varied significantly along the first axis, with higher concentrations observed at AAZ stations and showed a strong association with diatoms, consistent with their strong correlation in the overall Kendall-Tau analysis (Figure 6). Although pCd$_{excess}$ was not significant in the CCA, it showed a modest association with coccolithophores (Figure 7d).

## 4. Discussion

The community structure changed with latitude across the transect. Prasinophytes, *Phaeocystis* and other smaller flagellates dominated north of the PF, while diatoms and *Phaeocystis* dominated south of the PF. The PF therefore represented an important biogeochemical boundary, supporting microscopic observations made by Weir et al. (2020). In addition to changes in physical environment conditions and macronutrient concentrations, trace nutrient composition changed across frontal boundaries, indicating that changes in the phytoplankton group composition are potentially linked to trace metal composition (Viljoen et al., 2019).
**4.1. Characterization of the Winter Conditions Compared to Summer**

The conditions encountered during this study were typical of early winter: lower temperatures, deeper MLDs and higher mixed layer nutrient concentrations than in summer. For example, our peak winter temperatures south of the PF (<2°C) were up to 2°C lower and the mixed layers were generally much deeper (82–212 m) than during summer (9–112 m) in the west Indian Southern Ocean (Mendes et al., 2015). Consequently, the mixed layer was always deeper than the euphotic zone, especially north of the PF (Table 1). This contrasts typical summer conditions, when enhanced stratification leads to mixed layers that are shallower than the euphotic zones, which results in exposure to higher integrated light levels compared to winter (Llort et al., 2019). Hence, most phytoplankton communities across the winter transect experienced light stress, a key driver contributing to lower productivity in winter than summer (Weir et al., 2020).

Deep winter MLDs suggest nutrient resupply from enriched waters below the summer mixed layer (Cloete, Loock, van Horsten, Fietz, et al., 2021; Van Horsten et al., 2022; Weir et al., 2020), which is consistent with previous reports describing nutrient increases due to winter entrainment (Ramalepe et al., 2024; Rigby et al., 2020; Tagliabue et al., 2014) and corresponds to elevated mixed layer metal concentrations observed in this study. Macronutrient concentrations (nitrate, phosphate and silicic acid) were indeed similar or higher than in summer, with particularly higher silicic acid south of the PF (Weir et al., 2020). Winter mixed layer dCd also exceeded summer concentrations, especially at higher latitudes (PFZ and AAZ), possibly owing to physical entrainment and reduced biological uptake (Cloete, Loock, van Horsten, Fietz, et al., 2021). Similarly, winter dCu and dNi concentrations were comparable to Atlantic summer surface values north of the PF (Cloete et al., 2019) but exceeded them south of the PF (Cloete et al., 2019, 2025). In contrast, median winter dFe concentrations across the entire transect were similar to, but not higher than, those observed in summer (Grand et al., 2015; Van Horsten, 2022), indicating early winter conditions before dFe replenishment (Tagliabue et al., 2014). These examples illustrate the variability in seasonal changes, and distinct re-supply of various trace nutrients, particularly at high latitudes.

Some of the observed elevated concentrations in the upper ocean may also be driven by weaker biological uptake. Under the assumption of weak winter productivity, we would expect weak utilization of metal nutrients by phytoplankton and thus higher dissolved and lower excess particulate trace metal concentrations. These winter Tchl-*a* concentrations indeed contrasted summer observations. Winter Tchl-*a* concentrations decreased southward, contrasting the summer southward increase previously observed in the Atlantic and Indian sectors (Gibberd et al., 2013; Mendes et al., 2015), but aligning with reports of a southward decrease in winter in the Atlantic (Philibert et al., 2015). Peak winter mixed layer Tchl-*a* concentrations (0.28 µg L⁻¹) of this HPLC based study were up to 2-fold lower than Tchl-*a* in summer (0.65 µg L⁻¹ Indian AAZ, Mendes et al., 2015). Previous fluorometer-based studies (Weir et al., 2020) did not provide such a clear winter signature compared to summer. However, previous ¹⁵N-based net primary production estimates (Table 1) did indicate weak winter productivity and net heterotrophic grazing for this transect, especially south of the PF (S. Smith et al., 2022). Heterotrophic grazing and bacterial remineralization can also shape trace metal dynamics (Boyd et al., 2017). Phaeophorbide-*a* and phaeophytin-*a* (*phaeopigments*) were detected across the transect, albeit at relatively low concentrations (up to 0.02 µg L⁻¹ in the STZ) compared to summer in the same region and water masses (e.g., 0.11 µg L⁻¹ in the AAZ, Mendes et al., 2015). Our winter phaeopigment: Tchl-*a* ratios (up to 0.07; Table S3 and Figure S9 in Supporting Information S1) were much lower than summer ratios reported for this region (0.21; Mendes et al., 2015) with a similar southward increasing trend, indicating lower grazing and/or cell degradation compared to summer (Wright et al., 2010). Therefore, this HPLC based study confirms that phytoplankton abundance as well as cell senescence and grazing, are generally lower in winter compared to summer. Nonetheless, Southern Ocean phytoplankton were still active in winter and shifts in the phytoplankton community structure appeared to have affected the uptake of trace metals, from the STZ to south of the PF where phytoplankton abundance and productivity were lowest. The dynamics between trace metals shaping the community structure and the community structure shaping the metal distributions are complex. In the following we elucidate some of these complex dynamics.

**4.2. Phytoplankton—Trace Metal Dynamics From the STZ to the AAZ**

**4.2.1. STZ**

The STZ station (St. 41.0°S) was characterized by warm, low nitrate waters, with a phytoplankton community dominated by picophytoplankton such as cyanobacteria (27%) and nanophytoplankton such as *Phaeocystis*
(30%), alongside cryptophytes (14%) and coccolithophores (12%), consistent with summer observations (Mendes et al., 2015). This community is most likely influenced by the warm and macronutrient-poor ARC (Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021; Phoma et al., 2018), in addition to the typical low nitrate conditions of subtropical waters favoring small cells (Mendes et al., 2015; Schlüter et al., 2011; van Leeuwe et al., 2015). Cyanobacteria likely dominated due to their ability to use regenerated ammonium and urea (Gruber and Sarmiento, 1997; Hörstmann et al., 2021; S. Smith et al., 2022), while diatoms were limited by nitrate and low silicic acid (Aranguren-Gassis et al., 2019; Weir et al., 2020). These conditions also favored *Phaeocystis* and cryptophytes that can adapt and thrive in warmer, higher irradiance environments (Mendes et al., 2018; Trimborn et al., 2019).

Trace metal availability also played a significant role in shaping STZ phytoplankton communities. The overall CCA (Figure 7a) indicated that dFe and dMn were positively associated with STZ stations. Both showed minimal collinearity with other trace metals and were likely the dominant micronutrients driving phytoplankton distribution in the STZ. Elevated dFe concentrations at St 41.0°S sustained the peak *Tchl-*a community dominated by *Phaeocystis* and cyanobacteria, while the negative Fe* indicated Fe deficiency (Table 3) for other groups (Brand, 1991; Hogle et al., 2022; Twining and Baines, 2013). Zn* also indicate Zn deficiency for all phytoplankton groups except picophytoplankton in the STZ (Table 3), likely enhanced by strong organic complexation north of the PF (Baars & Croot, 2011). These conditions favor cyanobacteria over diatoms. Prokaryotes (e.g., cyanobacteria) have few Zn-dependent proteins (Saito et al., 2002; Sunda and Huntsman, 1995), whereas diatoms depend on Zn for Fe uptake and silicic acid transport (Koch and Trimborn, 2019; Varela et al., 2011). Many groups can substitute Cd or Co for Zn and the prevalence of *Phaeocystis* and coccolithophores in these low dZn and unfavorable Zn* conditions (Zn* < 0 for diatoms and flagellates) can be explained by their capacity to interreplace Zn with Cd and Co (Lane and Morel, 2000; Price and Morel, 1990; Saito and Goepfert, 2008). Mixed layer Co* values near zero indicate that dCo met the requirements to support Zn-substitution. In contrast, negative Cd* indicate Cd deficiency for diatoms preventing such Zn replacement (Table 3). The depth profile of dCd, correlates strongest to nitrate rather than silicic acid (Figure 3) suggesting that the dCd supported non-silicifiers (e.g., coccolithophores) more than diatoms in the STZ.

Concentrations of dCu and dNi appeared sufficient for most groups (positive Cu* and Ni*; Table 3). The strong nutrient-type correlation of dCu with silicic acid suggests diatom utilization, without providing diatoms a sufficient advantage to dominate in the STZ (Maldonado et al., 2006). Replete dNi, in contrast, may have provided cyanobacteria with a strategic advantage in the nitrate-limited STZ by supporting Ni-dependent urea uptake and superoxide dismutase activity (Dupont et al., 2008; Veaudor et al., 2019). Mn was also sufficient for STZ phytoplankton, indicated by positive Mn* and significant positive dMn association (Figure 7a). dMn availability might have been additionally favorable, due to its predominant occurrence as free Mn²⁺ and low organic complexation (Von Langen et al., 1997). The strong association of *Prochlorococcus* with pMn<sub>excess</sub> (Figure 7b) and dMn with cyanobacteria (Figure 6) suggests cyanobacterial uptake of Mn in the STZ. Cryptophytes too had strong associations with pMn<sub>excess</sub>, reflecting their increased Mn uptake under Zn-limiting conditions (Koch and Trimborn, 2019). However, strong Mn uptake is not apparent from the dMn vertical profiles (Figure 3). We suggest that a strong influx of dMn, from in situ photochemical reduction of Mn oxides or from the external influx of ARC waters (Boye et al., 2012; Viljoen et al., 2019), outpaces biological uptake of Mn in the STZ.

Among the trace metals with nutrient-type depth profiles, only Co was characterized by high pCo<sub>excess</sub> indicating strong biological uptake of Co. This dCo uptake was likely predominantly caused by cyanobacteria considering that the cyanobacteria-chla was strongly positively correlated with pCo<sub>excess</sub> along the transect and strongly negatively correlated with dCo (Figure 6). Cyanobacteria have been suggested as a key driver of Co biogeochemistry by controlling Co speciation through ligand production (Bown et al., 2012). *Synechococcus* was more strongly associated with pCo<sub>excess</sub> and dCo uptake than *Prochlorococcus* (Figure 7b). This preference may reflect species specific abilities to access Co which is strongly complexed by organic ligands (Saito and Moffett, 2001). Alternatively, inhibited Co uptake has been observed in *Prochlorococcus* at elevated free dMn (>10 nmol kg⁻¹) and free dZn (>1 pmol kg⁻¹) concentrations (Hawco and Saito, 2018). Although the observed dMn is too low to induce such Co uptake inhibition, the observed dZn (0.19 nmol kg⁻¹; Table S4 in Supporting Information S1) could inhibit Co uptake (Bruland, 1989). Even assuming 98%–99% complexation (Bruland, 1989), the remaining free dZn would be 2–4 pmol kg⁻¹, and sufficient to induce inhibition of Co uptake in *Prochlorococcus*. Although preferential utilization of dZn relative to dCo was previously reported in the summertime southeastern Atlantic
<caption>**Table 3**</caption>

Median Mixed Layer Metal* (nM) and Median Absolute Deviation (±MAD) for Each Station and Region-Relevant Phytoplankton Groups

<table><thead><tr><th>Station and zone</th><th>Region/Phyto</th><th>Fe*</th><th>Mn*</th><th>Co*</th><th>Ni*</th><th>Cu*</th><th>Zn*</th><th>Cd*</th></tr></thead><tbody><tr><td>St. 41.0°S</td><td>SO Bulk Diatoms</td><td></td><td></td><td>-0.02 ± 0.00</td><td></td><td><strong>0.40 ± 0.01</strong></td><td></td><td>-0.27 ± 0.01</td></tr><tr><td rowspan="5">STZ</td><td>SO Diatoms</td><td>-0.16 ± 0.05</td><td><strong>0.91 ± 0.03</strong></td><td></td><td><strong>1.81 ± 0.05</strong></td><td></td><td>-3.19 ± 0.05</td><td></td></tr><tr><td>SO Flagellates—nPF</td><td>-0.04 ± 0.04</td><td><strong>0.97 ± 0.03</strong></td><td></td><td><strong>2.03 ± 0.03</strong></td><td></td><td>-0.22 ± 0.02</td><td></td></tr><tr><td>SO Flagellates—sPF</td><td>-0.13 ± 0.04</td><td><strong>0.98 ± 0.03</strong></td><td></td><td><strong>1.96 ± 0.03</strong></td><td></td><td>-0.62 ± 0.03</td><td></td></tr><tr><td>Temp Flagellates</td><td>-0.50 ± 0.06</td><td><strong>0.94 ± 0.03</strong></td><td>-0.02 ± 0.00</td><td><strong>2.02 ± 0.03</strong></td><td></td><td>-0.06 ± 0.01</td><td></td></tr><tr><td>Temp Pico</td><td>-0.84 ± 0.06</td><td><strong>0.96 ± 0.03</strong></td><td>-0.01 ± 0.00</td><td><strong>2.01 ± 0.03</strong></td><td></td><td>-0.00 ± 0.01</td><td></td></tr><tr><td>St. 43.0°S</td><td>SO Bulk Diatoms</td><td></td><td></td><td>-0.09 ± 0.01</td><td></td><td>-0.39 ± 0.10</td><td></td><td>-0.86 ± 0.09</td></tr><tr><td rowspan="5">SAZ</td><td>SO Diatoms</td><td>-0.88 ± 0.09</td><td><strong>0.06 ± 0.03</strong></td><td></td><td><strong>2.77 ± 0.06</strong></td><td></td><td>-10.66 ± 1.06</td><td></td></tr><tr><td>SO Flagellates—nPF</td><td>-0.46 ± 0.02</td><td><strong>0.29 ± 0.00</strong></td><td></td><td><strong>3.57 ± 0.05</strong></td><td></td><td>-0.61 ± 0.05</td><td></td></tr><tr><td>SO Flagellates—sPF</td><td>-0.81 ± 0.09</td><td><strong>0.30 ± 0.00</strong></td><td></td><td><strong>3.31 ± 0.06</strong></td><td></td><td>-2.06 ± 0.30</td><td></td></tr><tr><td>Temp Flagellates</td><td>-1.99 ± 0.20</td><td><strong>0.18 ± 0.01</strong></td><td>-0.10 ± 0.01</td><td><strong>3.53 ± 0.05</strong></td><td></td><td>-0.05 ± 0.12</td><td></td></tr><tr><td>Temp Pico</td><td>-3.10 ± 0.31</td><td><strong>0.22 ± 0.01</strong></td><td>-0.07 ± 0.01</td><td><strong>3.51 ± 0.05</strong></td><td></td><td><strong>0.12 ± 0.10</strong></td><td></td></tr><tr><td>St. 45.5°S</td><td>SO Bulk Diatoms</td><td></td><td></td><td>-0.13 ± 0.01</td><td></td><td>-0.80 ± 0.09</td><td></td><td>-1.16 ± 0.02</td></tr><tr><td rowspan="5">SAZ</td><td>SO Diatoms</td><td>-1.22 ± 0.09</td><td>-0.15 ± 0.02</td><td></td><td><strong>2.40 ± 0.11</strong></td><td></td><td>-14.98 ± 0.11</td><td></td></tr><tr><td>SO Flagellates—nPF</td><td>-0.70 ± 0.06</td><td><strong>0.15 ± 0.01</strong></td><td></td><td><strong>3.46 ± 0.08</strong></td><td></td><td>-1.89 ± 0.01</td><td></td></tr><tr><td>SO Flagellates—sPF</td><td>-1.12 ± 0.09</td><td><strong>0.16 ± 0.01</strong></td><td></td><td><strong>3.15 ± 0.09</strong></td><td></td><td>-3.69 ± 0.00</td><td></td></tr><tr><td>Temp Flagellates</td><td>-2.72 ± 0.12</td><td>-0.00 ± 0.02</td><td>-0.15 ± 0.01</td><td><strong>3.41 ± 0.08</strong></td><td></td><td>-1.14 ± 0.01</td><td></td></tr><tr><td>Temp Pico</td><td>-4.23 ± 0.11</td><td><strong>0.07 ± 0.02</strong></td><td>-0.10 ± 0.01</td><td><strong>3.39 ± 0.08</strong></td><td></td><td>-0.88 ± 0.01</td><td></td></tr><tr><td>St. 48.0°S</td><td>SO Bulk Diatoms</td><td></td><td></td><td>-0.23 ± 0.00</td><td></td><td>-1.54 ± 0.02</td><td></td><td>-1.94 ± 0.03</td></tr><tr><td rowspan="5">PFZ</td><td>SO Diatoms</td><td>-2.40 ± 0.03</td><td>-0.70 ± 0.02</td><td></td><td><strong>3.36 ± 0.12</strong></td><td></td><td>-26.67 ± 0.35</td><td></td></tr><tr><td>SO Flagellates—nPF</td><td>-1.43 ± 0.02</td><td>-0.14 ± 0.01</td><td></td><td><strong>5.25 ± 0.10</strong></td><td></td><td>-2.50 ± 0.15</td><td></td></tr><tr><td>SO Flagellates—sPF</td><td>-2.21 ± 0.02</td><td>-0.12 ± 0.01</td><td></td><td><strong>4.69 ± 0.11</strong></td><td></td><td>-5.86 ± 0.12</td><td></td></tr><tr><td>Temp Flagellates</td><td>-5.18 ± 0.05</td><td>-0.42 ± 0.01</td><td>-0.27 ± 0.00</td><td><strong>5.16 ± 0.11</strong></td><td></td><td>-1.09 ± 0.17</td><td></td></tr><tr><td>St. 50.6°S</td><td>SO Bulk Diatoms</td><td></td><td></td><td>-0.25 ± 0.00</td><td></td><td>-1.11 ± 0.01</td><td></td><td>-1.93 ± 0.02</td></tr><tr><td rowspan="5">AAZ</td><td>SO Diatoms</td><td>-2.65 ± 0.02</td><td>-0.70 ± 0.01</td><td></td><td><strong>4.17 ± 0.09</strong></td><td></td><td>-26.97 ± 0.58</td><td></td></tr><tr><td>SO Flagellates—nPF</td><td>-1.61 ± 0.02</td><td>-0.10 ± 0.01</td><td></td><td><strong>6.19 ± 0.10</strong></td><td></td><td>-1.24 ± 0.31</td><td></td></tr><tr><td>SO Flagellates—sPF</td><td>-2.44 ± 0.02</td><td>-0.08 ± 0.01</td><td></td><td><strong>5.59 ± 0.10</strong></td><td></td><td>-4.80 ± 0.35</td><td></td></tr><tr><td>St. 56.0°S</td><td>SO Bulk Diatoms</td><td></td><td></td><td>-0.26 ± 0.00</td><td></td><td>-0.81 ± 0.04</td><td></td><td>-1.79 ± 0.02</td></tr><tr><td>AAZ</td><td>SO Diatoms</td><td>-2.74 ± 0.06</td><td>-0.72 ± 0.01</td><td></td><td><strong>4.92 ± 0.07</strong></td><td></td><td>-27.72 ± 0.99</td><td></td></tr><tr><td rowspan="5">AAZ</td><td>SO Flagellates—nPF</td><td>-1.66 ± 0.04</td><td>-0.09 ± 0.00</td><td></td><td><strong>7.06 ± 0.06</strong></td><td></td><td>-0.49 ± 0.49</td><td></td></tr><tr><td>SO Flagellates—sPF</td><td>-2.52 ± 0.05</td><td>-0.07 ± 0.00</td><td></td><td><strong>6.42 ± 0.06</strong></td><td></td><td>-4.27 ± 0.56</td><td></td></tr><tr><td>St. 58.5°S</td><td>SO Bulk Diatoms</td><td></td><td></td><td>-0.23 ± 0.00</td><td></td><td>-0.65 ± 0.06</td><td></td><td>-1.59 ± 0.02</td></tr><tr><td>AAZ</td><td>SO Diatoms</td><td>-2.51 ± 0.03</td><td>-0.65 ± 0.01</td><td></td><td><strong>4.69 ± 0.18</strong></td><td></td><td>-24.82 ± 0.39</td><td></td></tr><tr><td>SO Flagellates—nPF</td><td>-1.52 ± 0.02</td><td>-0.09 ± 0.00</td><td></td><td><strong>6.62 ± 0.19</strong></td><td></td><td>-0.34 ± 0.18</td><td></td></tr><tr><td>SO Flagellates—sPF</td><td>-2.31 ± 0.03</td><td>-0.07 ± 0.00</td><td></td><td><strong>6.05 ± 0.19</strong></td><td></td><td>-3.78 ± 0.09</td><td></td></tr></tbody></table>

Note. Metal* were calculated using group- and region-specific cellular metal:P quotas (Table 2; Cullen et al., 2003; Twining and Baines, 2013). SO—Southern Ocean; sPF—south of the Polar Front; nPF—north of the Polar Front. Positive Metal* values are highlighted in bold.

(Chen et al., 2024; Wyatt et al., 2021), our findings suggest that biological uptake, particularly by cyanobacteria, plays a significant role in shaping winter dCo dynamics in this Indian Ocean sector.

In summary, the phytoplankton community structure in the STZ was shaped by the interplay of both macro- and micronutrients. Small-celled groups, such as cyanobacteria, *Phaeocystis*, and cryptophytes dominated the STZ,
due to limiting nitrate, phosphate and silicic acid, and low dFe and dZn concentrations. In turn, these groups shaped micronutrient distributions. Cyanobacteria were strongly linked to Co uptake, while both cyanobacteria and cryptophytes likely accounted for most pMn<sub>excess</sub>. Although biological Mn uptake was high, a clear dMn drawdown signal remained masked, likely due to photochemical Mn-oxide reduction and ARC input. *Phaeocystis* and coccolithophores likely contributed to dCd and dCo drawdown by substituting Zn with these metals in response to dZn scarcity. Overall, our observations demonstrate that macronutrient limitation and trace metal stress shaped the phytoplankton community, which in turn modulated metal distributions, particularly Cd, Co, Cu, and Mn distributions.

### 4.2.2. North of the Polar Front

In the SAZ and PFZ, mixed layer Tchl-*a* concentrations were also relatively high (0.19–0.24 µg L⁻¹) but hosted distinct phytoplankton communities compared to the STZ (Figure 4). Prasinophytes dominated along with *Phaeocystis*, cyanobacteria and diatoms, largely consistent with cell counts indicating a dominance of flagellates north of the PF (Weir et al., 2020). Cyanobacteria have previously been observed in the Southern Ocean (Viljoen et al., 2019; Vincent, 2000). This community structure was influenced by macronutrient concentrations; in particular, silicic acid shows a strong relationship with diatoms (Figure S10a in Supporting Information S1).

As in the STZ, several trace metals played a role in shaping the community in the SAZ and PFZ (Figure 7c). Strong Fe deficiency, evidenced by negative Fe* for all groups, reflect the ubiquitous requirement for Fe by all phytoplankton groups. The lack of group-specific pFe<sub>excess</sub> associations in both the Kendall-Tau correlations and the CCA's likely reflects this ubiquitous Fe requirement by all phytoplankton. Contribution of authigenic fractions of labile pFe (Sofen et al., 2023; Tagliabue et al., 2023) could further obscure biological associations. In contrast, the positive associations of dFe with *Synechococcus* and prasinophytes in the SAZ (Figure 7c) underscore picophytoplankton's notably high Fe demand (Twining and Baines, 2013). The Fe-deficiency also affected other micronutrients. For example, Fe limitation induces stronger Mn uptake in diatoms, aggravating Mn limitation (Peers and Price, 2004). Although Mn* was lower in the SAZ than in the STZ, dMn was sufficient (Mn* > 0 nM) for most phytoplankton groups, except diatoms (Table 3), supporting Mn uptake and biological contribution to pMn<sub>excess</sub>. However, in the PFZ, mixed layer Mn* suggested Mn-deficiency for all groups, especially diatoms, leading to reduced Mn utilisation and weak association of phytoplankton with pMn<sub>excess</sub>. *Phaeocystis* may also have been strongly impacted by the combination of Fe and Mn deficiency, restructuring their photosynthetic apparatus (Wu et al., 2019). The potential (co-)limitation of diatoms and *Phaeocystis* by insufficient Fe and Mn could have favoured the dominance of other groups such as prasinophytes in the PFZ.

In the SAZ, negative Co* values imply Co deficiency across all phytoplankton groups (Table 3). However, nutrient-type dCo depth profiles and elevated pCo<sub>excess</sub> suggest biological uptake of Co in the SAZ. The CCA revealed a strong association between pCo<sub>excess</sub> and *Synechococcus*, which underscores a dominant role for cyanobacteria in Co uptake (Figure 7d). In cyanobacteria, Co is an obligate requirement, which cannot be substituted by any other metal (Saito and Moffett, 2002; Saito et al., 2002; Sunda and Huntsman, 1995). These observations suggest that *Synechococcus* is a major driver of Co utilisation and contributes to pCo<sub>excess</sub> in the winter SAZ. Zinc availability may have aggravated the Co uptake, as in the low dZn and negative Zn* waters, eukaryotes may substitute Zn with Co (Price and Morel, 1990; Saito and Goepfert, 2008; Xu et al., 2007), increasing Co utilization. In the PFZ, surface dCo increased and vertical distribution shifted away from nutrient-type behavior. This reflected lower cyanobacteria abundance (Figure 4), and reduced Co utilization, combined with enhanced winter mixing that replenished upper ocean dCo stocks. In both the SAZ and PFZ, low dCu and negative Cu* (Table 3), exacerbated by strong organic complexation (Heller and Croot, 2015), may have co-limited diatoms alongside Fe (Annett et al., 2008), due to the Cu requirement in diatoms for photosynthetic electron transport and Fe transport by multicopper oxidase (Maldonado et al., 2006; Peers and Price, 2006). Yet, dCu conditions may have been sufficient for Southern Ocean flagellates with lower Cu requirements (Twining and Baines, 2013; Twining et al., 2015), favoring prasinophytes and *Phaeocystis*.

Prasinophytes, which dominate the SAZ and PFZ communities, show the strongest negative correlation with dZn south of the STF (Figure 7c), reflecting the essential cellular roles of Zn (Twining and Baines, 2013) and Zn utilization by prasinophytes when diatom growth is Si-limited. In the SAZ, Zn* indicated Zn deficiency for most groups, especially diatoms (Zn* < −10 nM; Table 3). However, dZn appeared sufficient for the observed (Figure 4) temperate picophytoplankton in the northern SAZ (Zn* = 0.1 nM). Low dZn in the southern SAZ likely
favored chlorophytes that can substitute Zn with Cd under Zn stress (Lee and Morel, 1995). In the PFZ, high pCd_excess coincided with increased coccolithophore contributions (Figure 4), and pCd_excess showed some association with coccolithophores (Figure 7d), suggesting that elevated dCd (Figure 2) sustained coccolithophores and chlorophytes.

In summary, winter phytoplankton growth in the SAZ and PFZ was primarily constrained by low dFe availability and contributed to increased utilization of dMn in the SAZ. Fe and Mn co-limitation in diatoms and *Phaeocystis* reduced their competitive advantage, creating conditions that favored other groups such as prasinophytes. Low dZn levels and severe Zn deficiency further hindered diatom growth. Flagellate groups, including prasinophytes, likely gained a competitive advantage through their lower Cu requirements. Dissolved cobalt appears to have been biologically utilised in the wintertime SAZ but did not show nutrient profiles in the PFZ, likely driven by a combination of lower uptake by fewer *Synechococcus* and enhanced recharge. Again, as for the STZ, the relationship is bidirectional, where metals shape the community and the shift in communities drives metal distribution; and where consequently, one metal indirectly affects another. The types of relationships observed in the SAZ and PFZ differed from those observed in the STZ though and differ from those south of the PF.

### 4.2.3. South of the Polar Front

In the AAZ, Tchl-*a* concentrations were the lowest (0.08–0.11 µg L⁻¹) and phytoplankton were comprised of distinctly different communities compared to the winter transect north of the PF (Figure 4). Phytoplankton communities were generally dominated by diatoms, except at St. 53°S, where prasinophytes and *Phaeocystis* prevailed. At St. 53°S, storm activity may have caused deeper mixing compared to other stations prior to occupation, intensifying light limitation (Weir et al., 2020). Under these very low irradiance conditions, small motile flagellates (e.g., prasinophytes and *Phaeocystis*) that can photosynthesize and resist sinking outcompete other groups, including chain-forming diatoms (Dell’aquila et al., 2017; Rousseau et al., 2007; Schoemann et al., 2005). Coccolithophores were also observed in the AAZ, including at the southernmost station with surface water temperatures below 1°C. This occurrence aligns with earlier microscopic determinations in the southernmost cold winter waters (Weir et al., 2020) and supports reports of coccolithophore poleward expansion previously documented in summer (Balch et al., 2019; Oziel et al., 2020; Winter et al., 2014).

Diatom dominance in the AAZ reflects the higher silicic acid concentrations (Figure S10b in Supporting Information S1). Positive Si\* values (Weir et al., 2020) along with a Si:N ratio higher than 1 mol mol⁻¹ (Brzezinski, 1985) indicate that silicic acid enabled diatom growth and was sufficient for the formation of their silica cell walls. These conditions are characteristic of the AAZ (Nissen and Vogt, 2021). Additionally, slightly shallower MLDs and deeper euphotic zones were observed compared to the SAZ, which reduced the severity of light limitation (S. Smith et al., 2022; Weir et al., 2020). In addition to the silicic acid and light relief, the low dFe concentration may have favored the diatoms in the AAZ over other groups. dFe showed the strongest negative association with AAZ stations and diatoms (Figure 7c) and Fe\* was negative for diatoms and flagellates in the AAZ (Fe\* < −2 nM; Table 3), indicating Fe deficiency. However, diatoms may have been better adapted to these low dFe conditions in the Si-rich waters with lower Fe requirements compared to those in Si-limited regions north of the PF (Strzepek et al., 2011; Twining and Baines, 2013). Nutrient-type dFe depth profiles correlated the strongest with silicic acid, suggesting diatoms dominated Fe utilization in the AAZ, consistent with the hypothesis of increased silicic acid utilization for their silica cell walls as dFe declines (Hutchins and Bruland, 1998). Negative Mn\* suggested Mn deficiency, which might have led to Fe-Mn co-limitation of phytoplankton growth, a pattern previously observed in Southern Ocean incubation experiments (Balaguer et al., 2022; Browning et al., 2021). Contrary to dFe, dMn depth profiles correlated the strongest to nitrate and phosphate in the southern AAZ rather than silicic acid, supporting Browning et al. (2021) that Mn limitation weakens the preferential silica: nitrate utilization found in Fe-limited conditions. These findings imply that Fe shaped the residual silicic acid dynamics of the glacial Southern Ocean, with further modulation from co- or serial limitation by other trace metals.

All other micronutrients (dCo, dCu, dNi, dZn, and dCd) increased south of the PF (Figure 2), likely driven by upwelling of deep waters enriched in micronutrients (Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021; Vance et al., 2017). Despite the increase, most Metal\* values remained negative, similar to Fe\* and Mn\*. Only Ni was replete relative to phosphate (Ni\* > 4 nM). dZn showed the strongest positive association with AAZ stations and in particular with diatoms (Figure 7c). Nutrient-type dZn depth profiles correlated the strongest with silicic
acid, reflecting strong Zn uptake and remineralization by diatoms (de Souza et al., 2018; Vance et al., 2017). Elevated diatom abundance enhanced the overall Zn demand, evidenced by the strong diatom-pZn<sub>excess</sub> relationship (Figure 7) and consistent with diatom preference for Zn carbonic anhydrase rather than the Cd variant (Lane et al., 2005). Low pCO<sub>2</sub> (&lt;200 µatm) can also increase Zn demand in Zn-replete Southern Ocean waters (Kell et al., 2024, 2025), but winter pCO<sub>2</sub> south of the PF during our study were likely too high for this effect (pCO<sub>2</sub> &gt; 375 µatm; Mackay et al., 2022).

dCu nutrient-type depth profiles also correlated the strongest with silicic acid in the diatom dominated AAZ, consistent with the Cu requirement of diatoms for photosynthetic electron transport and Fe transport by multi-copper oxidase (Maldonado et al., 2006; Peers and Price, 2006). In contrast to Zn and Cu, dCd depth profiles correlated stronger with nitrate than with silicic acid, suggesting greater Cd uptake by non-silicifying groups, such as *Phaeocystis*. However, because trace metal depth-profiles were classified based on data up to 1,000 m (Figure 3), subsurface mixing of water masses with preformed macronutrient and trace metal concentrations likely also played a major role in these observations. In addition, pCd<sub>excess</sub> was associated with coccolithophores in the northern AAZ (Figure 7d). The likely relationship of Cd with *Phaeocystis* and coccolithophores can be explained by the ability of both groups to interreplace Cd and Zn in conditions where diatoms dominate and preferentially utilize Zn (Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021; Price and Morel, 1990).

In summary, Fe and Mn were likely the key limiting micronutrients, which together with the silicic acid-rich waters favored diatom dominance in the AAZ. In turn, diatoms, with high silicic acid and Zn requirements, shaped major nutrients and trace metal dynamics, particularly Zn, through strong utilization and remineralization. This confirms previous findings of strong diatom-Zn coupling in winter (Cloete, Loock, van Horsten, Menzel Barraqueta et al., 2021). Meanwhile, *Phaeocystis* and coccolithophores likely played a more prominent role in Cd uptake.

## 5. Conclusions

This study presents the first depth-resolved phytoplankton community structure in conjunction with a suite of dissolved and particulate trace metals in the Southern Ocean during winter. No single nutrient could explain the changes in phytoplankton community structure across the transect. Instead, we showed a combination of macro- and micronutrients unique to each zone shaped phytoplankton community structure. In turn, despite low winter productivity, phytoplankton group-specific metal uptake shaped winter micronutrient dynamics including particulate trace metal distributions. In the STZ, cyanobacteria dominated despite Fe deficiency in otherwise trace metal replete conditions for picophytoplankton, and along with *Phaeocystis* partly shaped Co and Mn dynamics in the STZ through biological uptake. In Subantarctic waters south of STF, Mn and Zn contributed to changes in community structure where Mn may have constrained diatoms and *Phaeocystis*, favouring prasinophytes while in the PFZ, increased Zn deficiency relative to phosphate favoured groups such as *Phaeocystis* and chlorophytes that can substitute Zn for Cd or Co. Diatoms dominated the AAZ, despite overall Fe-Mn co-limiting conditions, contributing to Cu and Zn biological uptake, while *Phaeocystis* and coccolithophores influenced Cd winter dynamics. These winter observations of strong, latitude dependent, group-specific associations with various essential trace metals, reflect the complex interplay between metal requirements, stoichiometry and phytoplankton composition. Shifts in these complex relationships, for example, under enhanced stratification, could lead to globally significant cascading effects on Southern Ocean biogeochemistry.

## Conflict of Interest

The authors declare there are no conflicts of interest for this manuscript.

## Data Availability Statement

The compilation of data used for the upper 150 m (i.e., matched phytoplankton data) and compilation of trace metal data used for the upper 250 m can be found in a Zenodo repository at https://doi.org/10.5281/zenodo.6615070 (Viljoen et al., 2025). Original HPLC phytoplankton pigment concentration data used in this study and other pigments can be found in a separate Zenodo repository at https://doi.org/10.5281/zenodo.14610498 (Viljoen and Fietz, 2025). Full depth profiles of UV-radiated dCo and dCu can be found at https://doi.org/10.5281/zenodo.14032493 (Roychoudhury and Valk, 2024).
Acknowledgments

The work leading to these results received funding from the National Research Foundation (NRF), South Africa, under the South African National Antarctic Programme (SANAP), Grants 93072, 110731, and 230529111300, awarded to S. Fietz. J.J. Viljoen acknowledges funding from NRF through a Masters Innovation Scholarship and financial assistance through a PhD NRF grant-linked bursary through SANAP, Grant 110731. We extend our gratitude to Shantelle Smith, Raquel Flynn, Raymond Roman, Kurt Spence, and Sarah Fawcett (University of Cape Town) for providing the macronutrient data from the Winter 2017 voyage. We thank Captain Knowledge Bengu and the crew of the *SA Agulhas II* for their support. We furthermore thank chief scientist Marcello Vichi, UCT-Oceanography, and all the cruise participants of the Winter 2017 scientific voyage. We also acknowledge and thank David Walker (CPUT) for use of fluorometer chlorophyll-a data. We thank Ray Barlow, Tommy Bornman and Peter Morton for providing insightful comments on an earlier version of this manuscript. We would like to express our gratitude to the two anonymous reviewers whose comments greatly improved this paper.

**Code availability:** Python code used to process data, produce figures and for statistical analysis is available at https://doi.org/10.5281/zenodo.16025350 (Viljoen, 2025). R code for detailed CCA results and plots is also available at https://doi.org/10.5281/zenodo.16060767 (Philibert, 2025).

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