# Major and trace nutrient concentrations in sub-Antarctic forage fish around the Kerguelen Islands: All are not equal for nutrient recycling by top predators

Lola Gilbert, Tiphaine Jeanniard-Du-Dot, Yves Cherel, Jérôme Spitz

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Lola Gilbert, Tiphaine Jeanniard-Du-Dot, Yves Cherel, Jérôme Spitz. Major and trace nutrient con- centrations in sub-Antarctic forage fish around the Kerguelen Islands: All are not equal for nutrient re- cycling by top predators. Journal of Experimental Marine Biology and Ecology, 2025, 586, pp.152097. 10.1016/j.jembe.2025.152097 . hal-05010509

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# Major and trace nutrient concentrations in sub-Antarctic forage fish around the Kerguelen Islands: All are not equal for nutrient recycling by top predators

Lola Gilbert<sup>a,b,*</sup>, Tiphaine Jeanniard-du-Dot<sup>a</sup>, Yves Cherel<sup>a</sup>, Jérôme Spitz<sup>a,b</sup>

## ARTICLE INFO

### Keywords:

Biological nutrient transfers

Prey quality

Contaminants

Trace metals

Animal-mediated nutrient cycling

Southern Ocean

## ABSTRACT

While the nutrient content of forage species is crucial to study how marine top predators release nutrients in their waste (faeces and urine) and possibly facilitate nutrient recycling at lower trophic levels of the food webs, it is poorly documented in many ecosystems. Here, we analyse the concentrations of five major nutrients, eight essential trace nutrients, and four non-essential nutrients in 34 mesopelagic and demersal forage fish species from the Kerguelen Plateau area (Southern Indian Ocean). This biogeochemically singular region benefits from natural iron (Fe) fertilisation and is an oasis for marine life in the high nutrient low chlorophyll Southern Ocean. Its nutrient dynamics have been subject to intense research for decades, but the contribution of the biota remain unexplored. Local forage fish were found to be significantly heterogeneous in their absolute nutrient concentrations, and in their relative nutrient content. Using hierarchical clustering, we showed that some species were enriched in nutrients found in limited concentrations in Southern Ocean surface waters, such as Fe and manganese (Mn), whereas others were enriched in nutrients likely limiting primary productivity in terrestrial ecosystems, such as phosphorus (P) or calcium (Ca). These fish species could be major contributors to these nutrients' biological cycling in different ecosystems when consumed by predators. This functional typology further demonstrates that prey are not interchangeable. The consumption of one or another prey species modulates not only the ability of the predator to meet its requirements and exposure to contaminants, but also predator-mediated nutrient recycling. This work provides valuable baseline knowledge that can be used in studies of nutrition, nutrient dynamics, and contaminant transfer. It also paves the way for the inclusion of predator-prey relationships in local biogeochemical studies to help unravel the complex processes at work in this unique ecosystem.

## 1. Introduction

Nutrients such as nitrogen (N), phosphorus (P), or iron (Fe) are essential to support primary production in all ecosystems (Lavelle et al., 2005). While they may be sequestered in inert minerals (e.g., rocks, sediments) or in live biomass (e.g., bacteria, plants, animals), their bioavailable form can be limiting to primary producer growth (Foster and Bhatti, 2006; Moore et al., 2013). Nutrient fluxes between the different ecosystem compartments are therefore major determinants of ecosystem structure, functioning, and productivity (Marzetz et al., 2017). Physical processes such as erosion, wind, currents, or the upwelling of nutrient-rich cold water from the deep ocean to the surface

are essential in making bioavailable nutrients sequestered in inert matter, and in making accessible nutrients that were bioavailable but inaccessible to primary producers (e.g., in deep waters; Bakun, 1997). At a finer scale, animals also participate to ecosystem nutrient recycling through food consumption, subsequent nutrient storage in their biomass, and release of undigested nutrient-rich matter and metabolic wastes in their faeces and urine (McInturf et al., 2019). Nutrients from animal waste may then partially return to organic production through primary producer uptake (either directly or after remineralisation by the microbial community), if accessible (McInturf et al., 2019; Schmitz et al., 2010). In oceans, the contribution of air-breathing predators such as cetaceans, pinnipeds, and seabirds to this biological nutrient

<footnote><sup>a</sup> Centre d'Etudes Biologiques de Chizé (CEBC), UMR7372 CNRS - La Rochelle Université, 79360 Villiers-en-Bois, France</footnote>

<footnote><sup>b</sup> Observatoire Pelagis, UAR3462 CNRS - La Rochelle Université, 5 allées de l'océan, 17000 La Rochelle, France</footnote>

<footnote>* Corresponding author at: Centre d'Etudes Biologiques de Chizé (CEBC), UMR7372 CNRS - La Rochelle Université, 79360 Villiers-en-Bois, France.
E-mail address: lola.gilbert@lilo.org (L. Gilbert).</footnote>
<caption>**Table 1**</caption>

Characteristics of forage fish samples collected in waters around Kerguelen Islands in 2005 and 2010 and analysed for nutrient composition, including the number of samples per species (n), the range of samples' standard length, % moisture, preferential habitat, marine predator species for which the forage species was previously identified in the diet and the associated references (Ref.). SD is standard deviation; preferential habitat was from FishBase or our own expertise; marine predators species included the Antarctic prion *Pachyptila desolata* (AP), thin-billed prion *Pachyptila belcheri* (TBP), blue petrel *Halobaena caerulea* (BP), soft-plumaged petrel *Pterodroma mollis* (SPP), white-chinned petrel *Procellaria aequinoctialis* (WCP), white-headed petrel *Pterodroma lessonii* (WHP), Kerguelen shag *Leucocarbo verrucosus* (KS), black-browed albatross *Thalassarche melanophris* (BBA), wandering albatross *Diomedea exulans* (WA), gentoo penguin *Pygoscelis papua* (GP), king penguin *Aptenodytes patagonicus* (KP), rockhopper penguin *Eudyptes chrysocome* (RP), Antarctic fur seal *Arctocephalus gazella* (AFS), elephant seal *Mirounga leonina* (ES), with the location in the literature search restricted to around Kerguelen and down to Heard Island, but no further.

<table><thead><tr><th>Family/Species</th><th>n</th><th>Standard length (cm)<br>(min-max)</th><th>Moisture % (mean<br>± SD)</th><th>Preferential habitat</th><th>Confirmed predator</th><th>Ref.</th></tr></thead><tbody><tr><td>Achiropsettidae<br><i>Mancopsetta maculata</i></td><td>2</td><td>21.1-28.2</td><td>73 ± 1</td><td>Demersal</td><td>BBA</td><td>5</td></tr><tr><td>Bathydraconidae<br><i>Bathydraco antarcticus</i></td><td>5</td><td>16.5-18.5</td><td>73 ± 2</td><td>Bathydemersal</td><td></td><td></td></tr><tr><td>Bathylagidae<br><i>Bathylagus tenuis</i></td><td>11</td><td>8.5-17.1</td><td>75 ± 5</td><td>Mesopelagic</td><td>BP</td><td>9</td></tr><tr><td>Carapidae<br><i>Echionodon cryomargarites</i></td><td>10</td><td>28.5-39.1</td><td>79 ± 1</td><td>Bathydemersal</td><td></td><td></td></tr><tr><td>Channichthyidae<br><i>Champssocephalus gunnari</i></td><td>10</td><td>19.7-28.8</td><td>79 ± 3</td><td>Benthopelagic</td><td>WHP, BBA, WA, GP, RP, AFS, ES</td><td>1, 3, 5-7, 11-12, 18, 20</td></tr><tr><td>Channichthys rhinoceratus</td><td>10</td><td>14.9-24.1</td><td>76 ± 1</td><td>Demersal</td><td>BBA, KS, GP</td><td>5, 12, 17</td></tr><tr><td>Gempylidae<br><i>Paradiplospinus gracilis</i></td><td>10</td><td>29.4-35.5</td><td>70 ± 3</td><td>Benthopelagic</td><td>AP, BP, SPP, WCP, WHP, BBA, AFS</td><td>3, 5, 7, 9-10, 13-15, 19-20</td></tr><tr><td>Macrouridae<br><i>Macrourus carinatus</i></td><td>10</td><td>17.3-29.9</td><td>74 ± 3</td><td>Bathydemersal</td><td>SPP, WCP, WHP, BBA, WA</td><td>5, 15, 18-20</td></tr><tr><td>Melamphaidae<br><i>Poromitra crassiceps</i></td><td>1</td><td>12.2</td><td>71</td><td>Mesopelagic</td><td>BP</td><td>9</td></tr><tr><td>Microstomatidae<br><i>Nansenia antarctica</i></td><td>5</td><td>20.1-22.2</td><td>70 ± 3</td><td>Mesopelagic</td><td>TBP, BP, WHP, AFS</td><td>7, 9-10, 14, 19</td></tr><tr><td>Muraenolepididae<br><i>Muraenolepis marmorata</i></td><td>10</td><td>18.7-30.3</td><td>76 ± 3</td><td>Benthopelagic</td><td>BP, WHP, KS, BBA, WA, GP, KP, AFS</td><td>5, 7-9, 12-13, 17-19</td></tr><tr><td>Myctophidae<br><i>Electrona antarctica</i></td><td>10</td><td>6.8-7.8</td><td>67 ± 2</td><td>Mesopelagic</td><td>AP, TBP, SPP, BP, KP, AFS, ES</td><td>1-3, 7-11, 13-14, 16, 19</td></tr><tr><td>Electrona carlsbergi</td><td>10</td><td>8.5-10.5</td><td>69 ± 3</td><td>Mesopelagic</td><td>TBP, BP, SPP, WHP, KP, AFS, ES</td><td>1-2, 4, 7-11, 13-14, 19-20</td></tr><tr><td>Electrona subaspera</td><td>10</td><td>6.8-12.9</td><td>72 ± 2</td><td>Mesopelagic</td><td>BP, SPP, WHP, AFS, ES</td><td>1, 3, 7, 9, 11, 16, 19-20</td></tr><tr><td>Gymnoscopelus bolini</td><td>10</td><td>13.5-22.4</td><td>66 ± 1</td><td>Mesopelagic</td><td>WHP, AFS, ES</td><td>1, 3, 7, 11, 14, 20</td></tr><tr><td>Gymnoscopelus braueri</td><td>12</td><td>9.9-12.2</td><td>64 ± 1</td><td>Mesopelagic</td><td>AFS, ES</td><td>1, 3, 7, 11</td></tr><tr><td>Gymnoscopelus fraseri</td><td>12</td><td>7.2-8.8</td><td>71 ± 2</td><td>Mesopelagic/ epibenthic</td><td>WHP, AFS</td><td>3, 7, 11, 16, 20</td></tr><tr><td>Gymnoscopelus nicholsi</td><td>10</td><td>12.0-13.5</td><td>68 ± 2</td><td>Mesopelagic/ epibenthic</td><td>BP, SPP, AFS, ES</td><td>1-4, 7, 9, 11, 14, 16, 19</td></tr><tr><td>Gymnoscopelus piabilis</td><td>10</td><td>12.5-15.3</td><td>68 ± 2</td><td>Mesopelagic/ epibenthic</td><td>WHP, AFS</td><td>3, 7, 11, 14, 16, 20</td></tr><tr><td>Krefftichthys anderssoni</td><td>4</td><td>5.5-5.5</td><td>69 ± 1</td><td>Mesopelagic</td><td>AP, TBP, BP, WHP, BBA, GP, KP, AFS, ES</td><td>1, 3-5, 7-8, 9-12, 14, 16, 20</td></tr><tr><td>Protomyctophum andriashevi</td><td>4</td><td>4.5-5.7</td><td>75 ± 1</td><td>Mesopelagic</td><td>BP, SPP, WHP, KP, AFS</td><td>7-9, 11, 19-20</td></tr><tr><td>Protomyctophum bolini</td><td>10</td><td>4.8-5.9</td><td>72 ± 4</td><td>Mesopelagic</td><td>AP, BP, SPP, WHP, BBA, KP, AFS, ES</td><td>1, 3, 5, 7-11, 16, 19-20</td></tr><tr><td>Protomyctophum choriodon</td><td>8</td><td>6.0-6.7</td><td>73 ± 1</td><td>Mesopelagic</td><td>BP, SPP, WHP, AFS</td><td>3-4, 7, 9, 11, 13-14, 16, 19-20</td></tr><tr><td>Protomyctophum tenisoni</td><td>10</td><td>4.9-5.4</td><td>71 ± 2</td><td>Mesopelagic</td><td>KP, AFS, ES</td><td>1, 3-4, 7-8, 11, 14, 16</td></tr><tr><td>Notosudidae<br><i>Luciosudis normani</i></td><td>1</td><td>23.9</td><td>74</td><td>Mesopelagic</td><td></td><td></td></tr><tr><td>Nototheniidae<br><i>Dissostichus eleginoides</i></td><td>2</td><td>26.1-26.4</td><td>75 ± 3</td><td>Demersal</td><td>BBA, WA, GP, ES</td><td>2, 5, 12, 18</td></tr><tr><td>Gobionotothen acuta</td><td>8</td><td>16.0-21.4</td><td>75 ± 2</td><td>Demersal</td><td>SPP, KS, BBA, GP, AFS</td><td>3, 5, 7, 12, 14, 17, 19</td></tr><tr><td>Lepidonotothen squamifrons</td><td>10</td><td>9.7-20.1</td><td>73 ± 2</td><td>Benthopelagic</td><td>BBA, GP, AFS, ES</td><td>1, 3, 5, 12</td></tr><tr><td>Lindbergichthys mizops</td><td>7</td><td>5.6-15.0</td><td>73 ± 4</td><td>Benthopelagic</td><td>BP, SPP, KS, BBA, ES</td><td>1, 5, 13, 17, 19</td></tr><tr><td>Paralepididae<br><i>Arctozenus risso</i></td><td>3</td><td>22.5-24.2</td><td>74 ± 1</td><td>Mesopelagic</td><td>TBP, BP</td><td>9-10</td></tr><tr><td>Notolepis coasi</td><td>10</td><td>6.9-9.0</td><td>73 ± 5</td><td>Mesopelagic</td><td>TBP, WCP</td><td>10, 15</td></tr><tr><td>Stomiidae<br><i>Idiacanthus atlanticus</i></td><td>1</td><td>40.8</td><td>67</td><td>Mesopelagic</td><td></td><td></td></tr><tr><td>Stomias spp.</td><td>10</td><td>15.3-23.6</td><td>74 ± 5</td><td>Mesopelagic</td><td></td><td></td></tr><tr><td>Zoarcidae<br><i>Melanostigma gelatinosum</i></td><td>10</td><td>18.8-26.2</td><td>83 ± 2</td><td>Mesopelagic</td><td>AFS</td><td>7</td></tr></tbody></table>

<footnote n="1">¹Green et al., 1989; ²Slip, 1995; ³Cherel et al., 1997; ⁴Raclot et al., 1998; ⁵Cherel et al., 2000; ⁶Tremblay and Cherel, 2000; ⁷Guinet et al., 2001; ⁸Bost et al., 2002; ⁹Cherel et al., 2002b; ¹⁰Cherel et al., 2002a; ¹¹Lea et al., 2002; ¹²Lescroël et al., 2004; ¹³Connan et al., 2008; ¹⁴Lea et al., 2008; ¹⁵Delord et al., 2010; ¹⁶Jeanniard-du-Dot, 2015; ¹⁷Cambrasse et al., 2017; ¹⁸Cherel et al., 2017; ¹⁹Cherel et al., 2022; ²⁰Cherel and Bocher, 2022.</footnote>
recycling is singular compared to other marine species, because they release their waste near the water surface – where sunlight penetrates and nutrients can limit primary productivity, while breathing and resting (Roman and McCarthy, 2010; Shatova et al., 2016).

The possible ecological relevance of this top predator-mediated nutrient recycling in ecosystem nutrient dynamics makes it a growing area of research, which largely depends on relevant data on prey nutrient content, diet composition, predator physiology and behaviour, and population dynamics. Yet being crucial, the multi-nutrient composition of forage prey communities is poorly documented worldwide (Chouvelon et al., 2022; Cipro et al., 2018), especially when considering multiple nutrients. Most available data focus on specific species, nutrients, and body tissues (e.g., liver, muscle) (e.g., Bustamante et al., 2003; Mille et al., 2018). Most estimates of top predators' contributions to nutrient recycling from bioenergetic approaches are therefore derived from prey nutrient composition data that are either averaged at high taxonomical levels (e.g., order) or from another area/season (e.g., Gilbert et al., 2023a, 2023b; Roman and McCarthy, 2010). However, the composition of forage prey can vary greatly between taxa, species, and individuals within species due to their different ecology and physiology, and also between regions, habitats, and seasons (Chouvelon et al., 2022; Goutte et al., 2015; Lischka et al., 2021; Mille et al., 2018). For example, crustaceans and cephalopods are enriched in copper (Cu) as it is a component of their respiratory pigment haemocyanin (White and Rainbow, 1985). Fish, which is a major forage prey community for top predators, live at all depths, from epipelagic to bathypelagic and demersal waters, and present a varied range of trophic ecologies, from herbivorous to zooplanktivorous and piscivorous species (Cury et al., 2000; Duhamel et al., 2017; Saunders et al., 2019). They are exposed to different biochemical environments (abiotic environment and food), with possible physiological adaptations, which translates into different nutritional characteristics (Chouvelon et al., 2022; Goutte et al., 2015). If predator switch prey in their diet, it can be directly linked to changes in the nutrient content in their waste products (Wing et al., 2021), with possible consequences on the ecosystem response to their nutrient input. The lack of prey composition data for a wide range of prey, ecosystems, and nutrients therefore possibly introduces significant bias in quantitative assessments of the role of predators in ecosystem nutrient dynamics.

In the high nutrient-low chlorophyll and primarily Fe-limited SO, the volcanic Kerguelen Plateau (Indian sector of the SO) obstructs the flows of the Antarctic Circumpolar Current (including the Polar Front), and benefits from natural Fe fertilisation through upwelling and atmospheric dust (Blain et al., 2001; Duhamel et al., 2017; van Der Merwe et al., 2015). The sub-Antarctic Kerguelen Archipelago is therefore a highly productive region where nutrient and productivity dynamics have been subject to an intense research effort for decades (e.g., Blain et al., 2008; Hunt et al., 2021; van Der Merwe et al., 2015). While this oasis host numerous marine predators, including cetaceans, pinnipeds, and both diving and flying seabirds (Hindell et al., 2011), their role in local nutrient cycling processes has not been examined yet. They rely on a diverse community of forage prey, including small crustaceans and zooplankton, cephalopods, and fish, in varying proportions depending on species, individuals, areas and seasons, and with varying foraging strategies. Notably, the importance of fish as forage prey in this Indian subantarctic sector is greater than that of other taxa, especially small crustaceans such as the Antarctic krill *Euphausia superba*, which is the main forage species in the rest of the SO (Tierney et al., 2002). To the best of our knowledge, the nutrient content of these potential prey has been quantified only for the essential nutrients (i.e., with known biological function and deleterious effect when missing) Cu and zinc (Zn), and the non-essential nutrients (i.e., with no known biological function) and potentially toxic cadmium (Cd) and mercury (Hg) (Cipro et al., 2018).

The present study focuses on the nutrient content of a range of forage fish species that make up a large proportion of the prey available to

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Map of the study area of the northern Kerguelen Plateau, in the Indian sector of the Southern Ocean. Bathymetry is indicated with a blue gradient coloured scale. The red square indicates the location where the first fish sampling campaign occurred (mesopelagic fauna, January 2005; Cherel et al., 2010). The second campaign (demersal fauna, September 2010; Duhamel et al., 2017) sampled 200 stations randomly spread over the shelf and deep-sea slope down to 1000 m depth, their approximate location are indicated by red dots. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

marine top predators in this remote and biogeochemically singular ecosystem. Naturally, fish also contribute to nutrient recycling through waste release. Their contribution can be significant in some ecosystems (e.g., coral reefs) and their body nutrient content is a key parameter to study this (Schiettekatte et al., 2020). However, our focus here was on fish as potential prey, because of the particularity of air-breathing predators releasing their waste in the euphotic zone and the possible consequences on productivity in pelagic ecosystems. We analysed 34 fish species for their whole-body concentrations in 17 nutrients, with 13 essentials and four non-essentials. Our goals were twofold. First, we aimed to assess the variability in the nutrient content of potential fish prey in the Kerguelen area, including as many nutrients as possible. Indeed, the stoichiometry (i.e., the ratio in the amount of multiple nutrients in a nutrient blend) of nutrient fluxes is essential to track at all ecosystem levels. Multiple essential nutrients interact and co-vary due to their biochemical affinity or to physiological processes (Sterner and Elser, 2008), as different organisms may have different nutrient requirements and associated metabolisms, and thus different response to a given nutrient input. Non-essential nutrients recycled along essential nutrients could also interfere in the ecosystem response to an input in essential nutrients (Permana and Akbarsyah, 2021; Szteren et al., 2023). Secondly, we aimed to identify functional 'multi-nutrient content' groups of fish around the Kerguelen Islands which may have singular roles in the biological cycling of specific nutrients when they are consumed by top predators.

## 2. Material & Methods

### 2.1. Fish sampling

We collected 264 individuals of 34 forage fish species (29 of which previously identified as part of local marine predators' diet; Table 1 and references therein) during two research cruises on and around the Kerguelen Plateau. The first sampling campaign took place on the eastern
slope waters of the Kerguelen Islands (49°05′–49°20′S, 71°15′–72°15′E) on the 25 m-long FPV La Curieuse in January 2005 (Fig. 1), and aimed to sample the mesopelagic fauna. Fishing operations were carried out at night, with an International Young Gadoid Pelagic Trawl (IYGPT) with 12 m × 7 m opening and 10 mm cod-end mesh deployed for 30-min at constant speed, at depth varying from 50 to 425 m (Cherel et al., 2010; Duhamel et al., 2000). Most samples caught during this campaign (n = 167) were myctophids (n = 119). The second sampling campaign (named 'Poker 2') took place from August to September 2010 on the 77 m-long trawler FV Austral. It focused on the demersal fauna and yielded the remaining 97 fish samples. Two hundred stations from shelf and deep-sea habitats (Fig. 1) were sampled during 30-min day trawling operations using a bottom trawl (35 m headline/39 m footrope, reference: G2035013 from Le Drezen: www.ledrezen.com) with a 40 mm cod-end mesh (Duhamel et al., 2017). For both campaigns, fish were sorted on board after initial identification and then kept frozen at –20 °C until processing. Identification was again confirmed before sample processing relying on fish external features using a published guide (Hulley, 1981) and our own reference collection.

## 2.2. Sample processing

Each fish was thawed, rinsed with ultrapure water, measured, weighed, and ground in the laboratory in a clean and contamination-free setting before being stored at –20 °C. All material was carefully rinsed with ultrapure water and ethanol between samples to avoid contamination. Samples were then freeze-dried for a minimum of 72 h and ground to a fine powder until analysis.

## 2.3. Multi-nutrient composition analysis

Total concentrations of six major constitutive chemical elements in biological tissues (calcium Ca, potassium K, magnesium Mg, sodium Na, phosphorus P, and strontium Sr) were determined by inductively coupled plasma atomic emission spectrometry (ICP-OES, Vista-Pro Varian). Note than even though Sr is found in high concentrations in a large range of animals, it is not considered essential (i.e., with deleterious effects when deficient) (Chowdhury and Blust, 2011). Aliquots of samples (≈250 mg dry mass of homogenised powder) were digested using a 6:2 (v/v) mixture with nitric acid (HNO₃ 69 %, Trace Metal Grade®, FisherScientific) and hydrochloric acid (HCl, 34 %, Trace Metal Grade®, FisherScientific). Acidic digestion of the samples was performed over-night at room temperature and then in a microwave oven (START-D, Milestone). Finally, the digestats were diluted to 50 mL with ultrapure water before analyses with ICP-OES. Total concentrations of 10 essential trace nutrients (arsenic As, cobalt Co, copper Cu, iron Fe, manganese Mn, molybdenum Mo, nickel Ni, selenium Se, zinc Zn, vanadium V) and four non-essential trace metals (silver Ag, cadmium Cd, chromium Cr and lead Pb) were determined by inductively coupled plasma mass spectrometry (ICP-MS, ICAP-Qc ThermoFisher). Aliquots of samples (≈200 mg dry mass of homogenised powder) were placed in Teflon bombs and mineralized with a mixture of ultrapure HNO₃ acid (PlasmaPure Plus grade, SCP Science®) and ultrapure water using a micro-wave (ETHOS-UP, Milestone). The digests were then diluted to 50 mL with ultrapure water before analyses with ICP-MS. The quality assurance of all metal analyses relied on blank and internal standard controls, and on the accuracy and reproducibility of data relative to the certified reference materials (CRMs) used in each analytical run. The CRMs used were TORT-3 (lobster hepatopancreas, National Research Council of Canada/NRCC) and DOLT-5 (dogfish liver, NRCC). Blank values were systematically below the detection limits, CRM values concurred with certified concentrations, and recovery rates ranged between 75 % and 116 % depending on the nutrients and the CRMs. The complete dataset is available in InDoRes (Inventaire des Données de la Recherche en Environnement et Sociétés) (https://doi.org/10.48579/PRO/2AXFDD).

For Ag, Cr, Mo, Pb, and V some samples had concentrations below the limit of quantification (loq). The loq is estimated for each sample based on the mass of the aliquot analysed. For Cr, Mo and V, more than 20 % of the samples had concentrations under the loq, so these nutrients were excluded from subsequent analysis. For Ag and Pb (with respectively 16 and 5 % of concentrations under loq), concentrations under loq were replaced by half of the sample loq, so the final analysis was conducted for 17 nutrients including 13 essentials and four non-essentials.

## 2.4. Nutritional variability and multi-nutrient typology of forage fish

We first estimated the variability in nutrient concentrations of fish species with a nutrient-by-nutrient approach, using basic descriptive statistics and boxplots. We considered the species absolute nutrient concentrations (in mg·kg⁻¹ dry weight) and the relative ratio of each nutrient within the nutrient mix it contained (i.e., stoichiometry). To approach the latter (as we did not quantify all nutrients), for each nutrient we divided the species mean absolute concentration by the sum of its concentrations in Ca, P, Mg, K, Na, Fe, Zn, Cu, Mn, Se, Ni, As, Co, Ag, Cd, Sr, and Pb, so that for a given fish species the sum of the relative fractions in the 17 nutrients is 1. We also assessed the covariation between different nutrient concentrations based on correlation coefficients.

Second, we used hierarchical clustering (HC) on forage fish species to (i) identify relative similarity between species and groups of species in terms of concentrations in multiple nutrients, and (ii) identify nutrients that are the most discriminating between these groups. In this part, we chose to focus on the 13 essential nutrients only (Ca, P, Mg, K, Na, Fe, Zn, Cu, Mn, Se, Ni, As, Co) to identify functional groups of prey based on their content in multiple essential nutrients, setting aside the non-essential nutrients for the identification of clusters. Still, we included concentrations in non-essential nutrients of clusters identified along that of essential nutrients, to illustrate how the ecosystem recycling of both types of nutrients can be correlated. Clustering with high dimension can cause problems in differentiating similar and dissimilar objects, and this “curse of dimensionality” can occur with as few as ten dimensions (Assent, 2012). Consequently, we performed a principal component analysis (PCA) to reduce the number of dimensions of the dataset (originally, 13 nutrients). We then used coordinates of samples on the first principal components of the PCA as an input for the HC analysis, selecting the first five principal components that together explained at least 90 % of the dataset variance.

Classical statistical methods (such as PCA and HC) can be deemed unsuitable to analyse composition data, because they rely on Euclidean geometry (Filzmoser et al., 2018). Thus, we used algorithms designed for composition datasets using Robcomposition R package (Templ et al., 2011). Correlation coefficients between composition parts were based on symmetric pivot coordinates, and data were transformed to be expressed in isometric log-ratio coordinates before performing a robust PCA (Filzmoser et al., 2018; Templ and Templ, 2021). These transformations allow to express the original compositional data in the usual Euclidean geometry (and thus with associated geometrical properties for them to meet assumptions of classic statistical analysis methods) (Filzmoser et al., 2018). By using PCA to reduce the number of dimensions of the datasets, the input for the hierarchical clustering was no longer compositional in nature, so we used a classical algorithm with Ward's minimum variance method (Ward, 1963). We estimated the optimal number of clusters using dendrograms and standard validating measures (e.g., average and median distance between clusters, minimum cluster size). Clusters were then compared based on their nutrient concentrations using basic descriptive statistics and boxplots. To better identify nutrients that were discriminating between the potentially functional fish groups (clusters), we also assessed cluster differences nutrient-by-nutrient using Mann-Whitney-Wilcoxon (MWW) tests. Some forage fish species or families were over represented in the dataset (e.g., myctophids with *n* = 119 individuals; Table 1), so we used nutrient
<caption>**Table 2**</caption>

Nutrient concentrations (in mg·kg⁻¹ dry weight) for 34 forage fish species from waters around the Kerguelen Islands (mean ± standard deviation). Biochemical analyses were conducted on whole organisms, n indicating the number of individuals analysed per species. Nutrients are ordered according to their approximate concentration levels in samples, with essential nutrients (i.e., with deleterious effects if their concentrations in organisms are too low) on the left part of the table and non-essential nutrients on the right part of the table. Stars (*) indicate sample concentrations under the limit of quantification (LOQ; 5% of samples across species for Pb and 15% for Ag); when only a star is indicated, all sample concentrations from the indicated species were under the LOQ; when there is both a number and a star, samples with concentrations under the LOQ were not included to estimate the mean and the standard deviation. Raw composition results per sample are available in InDoRes (Inventaire des Données de la Recherche en Environnement et Sociétés) (https://doi.org/10.48579/PRO/2AXFDD).

<table><thead><tr><th>Family/Species</th><th>n</th><th>Ca</th><th>P</th><th>Na</th><th>K</th><th>Mg</th><th>Fe</th><th>Zn</th><th>Cu</th><th>Mn</th><th>As</th><th>Se</th><th>Ni</th><th>Co</th><th>Sr</th><th>Cd</th><th>Pb</th><th>Ag</th></tr></thead><tbody><tr><td>Achiropsettidae<br>Mancopsetta maculata</td><td>2</td><td>35,956 ± 408</td><td>24,590 ± 196</td><td>14,209 ± 845</td><td>10,623 ± 621</td><td>2194 ± 162</td><td>42.8 ± 8.3</td><td>44.3 ± 2.1</td><td>5.67 ± 0.04</td><td>3.82 ± 1.31</td><td>2.66 ± 0.31</td><td>2.61 ± 0.39</td><td>1.27 ± 0.00</td><td>0.11 ± 0.00</td><td>212.1 ± 23.9</td><td>0.14 ± 0.07</td><td>0.05 ± 0.01</td><td>0.02*</td></tr><tr><td>Bathydraconidae<br>Bathydraco antarcticus</td><td>5</td><td>33,387 ± 13,714</td><td>22,954 ± 7270</td><td>9917 ± 1192</td><td>11,734 ± 590</td><td>1874 ± 235</td><td>64.0 ± 28.2</td><td>65.6 ± 9.9</td><td>6.32 ± 1.53</td><td>4.07 ± 1.21</td><td>9.74 ± 4.24</td><td>2.66 ± 0.57</td><td>1.15 ± 0.26</td><td>0.12 ± 0.03</td><td>167.1 ± 115.7</td><td>0.88 ± 0.61</td><td>0.06 ± 0.03</td><td>0.04 ± 0.03*</td></tr><tr><td>Bathylagidae<br>Bathylagus tenuis</td><td>11</td><td>9723 ± 5943</td><td>10,088 ± 3579</td><td>11,767 ± 3409</td><td>8987 ± 1429</td><td>1894 ± 815</td><td>35.7 ± 24.7</td><td>48.1 ± 24.3</td><td>5.82 ± 2.99</td><td>1.70 ± 1.01</td><td>3.91 ± 1.24</td><td>2.01 ± 1.50</td><td>0.65 ± 1.86</td><td>0.05 ± 0.74</td><td>59.7 ± 35.5</td><td>0.83 ± 0.69</td><td>0.13 ± 0.19</td><td>0.08 ± 0.06</td></tr><tr><td>Carapidae<br>Eciodon<br>cryomargarites</td><td>10</td><td>18,953 ± 3522</td><td>17,085 ± 1891</td><td>21,855 ± 1651</td><td>11,176 ± 883</td><td>2018 ± 288</td><td>39.6 ± 51.3</td><td>53.8 ± 6.4</td><td>9.58 ± 1.05</td><td>2.66 ± 0.57</td><td>1.50 ± 0.14</td><td>1.50 ± 0.31</td><td>0.65 ± 0.10</td><td>0.06 ± 0.01</td><td>104.1 ± 17.9</td><td>0.37 ± 0.44</td><td>0.03 ± 0.00</td><td>0.02 ± 0.01*</td></tr><tr><td>Channichthyidae<br>Champscephalus<br>gunnari</td><td>10</td><td>19,859 ± 8854</td><td>19,382 ± 4587</td><td>11,214 ± 1584</td><td>17,128 ± 1304</td><td>1811 ± 197</td><td>11.4 ± 4.5</td><td>75.2 ± 13.0</td><td>3.90 ± 0.66</td><td>0.81 ± 0.27</td><td>9.48 ± 2.39</td><td>3.83 ± 0.73</td><td>0.81 ± 0.29</td><td>0.08 ± 0.03</td><td>74.5 ± 31.2</td><td>1.81 ± 1.05</td><td>0.04 ± 0.03*</td><td>0.03 ± 0.02*</td></tr><tr><td>Channichthys<br>rhinoferus</td><td>10</td><td>24,320 ± 3780</td><td>18,848 ± 1347</td><td>12,493 ± 1581</td><td>13,702 ± 1003</td><td>1937 ± 267</td><td>23.5 ± 13.9</td><td>72.7 ± 10.0</td><td>4.01 ± 1.01</td><td>1.42 ± 0.45</td><td>12.34 ± 0.57</td><td>3.48 ± 0.59</td><td>0.96 ± 0.12</td><td>0.08 ± 0.01</td><td>69.1 ± 17.9</td><td>0.25 ± 0.34</td><td>0.01 ± 0.00*</td><td>0.02 ± 0.02*</td></tr><tr><td>Gempylidae<br>Paradiplospinus gracilis</td><td>10</td><td>15,165 ± 3467</td><td>13,391 ± 2387</td><td>7333 ± 1867</td><td>9686 ± 961</td><td>1548 ± 351</td><td>65.6 ± 94.7</td><td>34.8 ± 7.4</td><td>3.76 ± 0.79</td><td>1.77 ± 1.40</td><td>1.85 ± 0.20</td><td>2.56 ± 0.41</td><td>0.83 ± 0.16</td><td>0.07 ± 0.02</td><td>48.4 ± 13.1</td><td>0.21 ± 0.17</td><td>0.08 ± 0.05</td><td>0.02 ± 0.01</td></tr><tr><td>Macrouridae<br>Macrourus carinatus</td><td>10</td><td>21,559 ± 4411</td><td>17,808 ± 2345</td><td>10,848 ± 2110</td><td>11,099 ± 1331</td><td>1853 ± 338</td><td>63.7 ± 21.0</td><td>68.4 ± 6.5</td><td>5.28 ± 1.23</td><td>2.51 ± 0.60</td><td>7.96 ± 4.79</td><td>2.77 ± 0.75</td><td>0.92 ± 0.42</td><td>0.11 ± 0.09</td><td>101.5 ± 17.6</td><td>0.40 ± 0.31</td><td>0.05 ± 0.02</td><td>0.09 ± 0.10</td></tr><tr><td>Melamphaidae<br>Poromitra crassiceps</td><td>1</td><td>12,626</td><td>9890</td><td>9726</td><td>5958</td><td>1354</td><td>27.9</td><td>30.6</td><td>3.63</td><td>1.98</td><td>3.00</td><td>3.19</td><td>0.62</td><td>0.05</td><td>72.6</td><td>1.30</td><td>0.04</td><td>0.02</td></tr><tr><td>Microstomatidae<br>Nansenia antarctica</td><td>5</td><td>7475 ± 3947</td><td>8423 ± 1724</td><td>7719 ± 1315</td><td>7424 ± 2144</td><td>1356 ± 191</td><td>27.1 ± 7.7</td><td>35.1 ± 17.3</td><td>3.23 ± 0.74</td><td>1.82 ± 0.52</td><td>2.90 ± 1.00</td><td>1.62 ± 0.23</td><td>0.62 ± 0.20</td><td>0.05 ± 0.01</td><td>38.0 ± 19.5</td><td>1.28 ± 1.05</td><td>0.07 ± 0.02</td><td>0.08 ± 0.05</td></tr><tr><td>Muraenolepididae<br>Muraenolepis<br>marmorata</td><td>10</td><td>20,431 ± 9526</td><td>18,241 ± 5453</td><td>9158 ± 1515</td><td>15,143 ± 1226</td><td>2001 ± 451</td><td>60.4 ± 23.1</td><td>53.6 ± 8.0</td><td>6.46 ± 2.10</td><td>1.38 ± 0.43</td><td>4.86 ± 2.19</td><td>2.66 ± 0.55</td><td>1.19 ± 0.41</td><td>0.11 ± 0.05</td><td>114.3 ± 44.1</td><td>1.25 ± 2.41</td><td>0.12 ± 0.03*</td><td>0.27 ± 0.12</td></tr><tr><td>Myctophidae<br>Electrona antarctica</td><td>10</td><td>13,285 ± 1048</td><td>10,886 ± 501</td><td>8090 ± 1494</td><td>5802 ± 426</td><td>1624 ± 197</td><td>27.1 ± 5.5</td><td>29.6 ± 3.6</td><td>3.34 ± 0.58</td><td>1.40 ± 0.22</td><td>1.49 ± 0.19</td><td>2.01 ± 0.52</td><td>1.33 ± 0.18</td><td>0.08 ± 0.01</td><td>47.7 ± 6.4</td><td>0.42 ± 0.23</td><td>0.17 ± 0.09</td><td>0.02 ± 0.01*</td></tr><tr><td>Electrona carlsbergi</td><td>10</td><td>18,477 ± 3428</td><td>13,932 ± 2145</td><td>7537 ± 1617</td><td>7616 ± 699</td><td>1793 ± 326</td><td>40.2 ± 18.7</td><td>39.7 ± 8.0</td><td>3.70 ± 0.69</td><td>2.21 ± 0.45</td><td>2.53 ± 0.26</td><td>4.03 ± 0.63</td><td>1.32 ± 0.30</td><td>0.11 ± 0.02</td><td>58.0 ± 11.7</td><td>0.53 ± 0.21</td><td>0.09 ± 0.02</td><td>0.02 ± 0.01</td></tr><tr><td>Electrona subaspera</td><td>10</td><td>19,616 ± 3510</td><td>15,730 ± 2394</td><td>7014 ± 1441</td><td>9915 ± 1307</td><td>1729 ± 344</td><td>27.9 ± 8.0</td><td>40.3 ± 7.0</td><td>4.80 ± 0.90</td><td>2.22 ± 0.43</td><td>3.01 ± 0.61</td><td>2.78 ± 0.57</td><td>1.16 ± 0.10</td><td>0.09 ± 0.01</td><td>54.4 ± 10.0</td><td>0.90 ± 0.35</td><td>0.08 ± 0.05</td><td>0.02 ± 0.01</td></tr><tr><td>Gymnoscopelus bolini</td><td>10</td><td>16,329 ± 6162</td><td>12,716 ± 3084</td><td>4161 ± 569</td><td>8369 ± 430</td><td>1203 ± 126</td><td>24.0 ± 14.2</td><td>21.2 ± 3.6</td><td>2.54 ± 0.34</td><td>1.71 ± 0.54</td><td>3.57 ± 0.48</td><td>2.39 ± 0.36</td><td>0.96 ± 0.27</td><td>0.08 ± 0.03</td><td>58.7 ± 23.2</td><td>0.50 ± 0.19</td><td>0.05 ± 0.02</td><td>0.01 ± 0.00*</td></tr><tr><td>Gymnoscopelus braueri</td><td>12</td><td>12,924 ± 1699</td><td>10,116 ± 945</td><td>5094 ± 561</td><td>6647 ± 229</td><td>1220 ± 118</td><td>18.0 ± 7.9</td><td>31.2 ± 4.9</td><td>2.71 ± 0.27</td><td>1.34 ± 0.28</td><td>2.00 ± 0.20</td><td>1.95 ± 0.17</td><td>0.96 ± 0.13</td><td>0.07 ± 0.01</td><td>63.2 ± 13.8</td><td>0.81 ± 0.44</td><td>0.07 ± 0.02</td><td>0.01 ± 0.00*</td></tr><tr><td>Gymnoscopelus fraseri</td><td>12</td><td>19,601 ± 3200</td><td>14,590 ± 1663</td><td>8142 ± 1204</td><td>8025 ± 558</td><td>1995 ± 268</td><td>30.8 ± 8.2</td><td>50.9 ± 35.6</td><td>5.31 ± 1.61</td><td>2.65 ± 0.60</td><td>2.73 ± 0.43</td><td>3.65 ± 0.61</td><td>1.42 ± 0.15</td><td>0.10 ± 0.01</td><td>75.9 ± 16.7</td><td>0.65 ± 0.27</td><td>0.10 ± 0.07</td><td>0.10 ± 0.05</td></tr><tr><td>Gymnoscopelus nicholsi</td><td>10</td><td>13,620 ± 4264</td><td>11,243 ± 2657</td><td>6242 ± 1039</td><td>8065 ± 728</td><td>1486 ± 281</td><td>24.9 ± 11.1</td><td>24.2 ± 3.4</td><td>4.43 ± 0.47</td><td>1.37 ± 0.37</td><td>3.18 ± 0.41</td><td>2.94 ± 0.59</td><td>1.11 ± 0.25</td><td>0.08 ± 0.01</td><td>48.4 ± 12.8</td><td>0.45 ± 0.10</td><td>0.06 ± 0.01</td><td>0.03 ± 0.01</td></tr><tr><td>Gymnoscopelus piabilis</td><td>10</td><td>16,044 ± 1748</td><td>12,972 ± 767</td><td>5455 ± 962</td><td>8405 ± 630</td><td>1486 ± 203</td><td>24.3 ± 5.5</td><td>27.5 ± 4.8</td><td>3.74 ± 0.54</td><td>1.55 ± 0.21</td><td>2.40 ± 0.26</td><td>2.85 ± 0.65</td><td>1.09 ± 0.10</td><td>0.07 ± 0.01</td><td>57.1 ± 8.1</td><td>0.58 ± 0.17</td><td>0.06 ± 0.02</td><td>0.03 ± 0.01</td></tr><tr><td>Kreftichthys anderssoni</td><td>4</td><td>11,623 ± 1619</td><td>11,787 ± 1590</td><td>9649 ± 1409</td><td>6833 ± 526</td><td>1847 ± 163</td><td>63.7 ± 6.3</td><td>45.6 ± 10.8</td><td>5.73 ± 1.13</td><td>2.69 ± 0.60</td><td>4.66 ± 0.26</td><td>3.10 ± 0.28</td><td>0.87 ± 0.13</td><td>0.07 ± 0.01</td><td>45.2 ± 6.9</td><td>1.04 ± 0.62</td><td>0.16 ± 0.04</td><td>0.09 ± 0.06</td></tr><tr><td>Protomyctophum<br>andriashevi</td><td>4</td><td>30,374 ± 7698</td><td>21,764 ± 4379</td><td>15,311 ± 2059</td><td>8886 ± 1571</td><td>3214 ± 609</td><td>84.2 ± 50.3</td><td>51.7 ± 17.6</td><td>6.06 ± 0.85</td><td>3.24 ± 0.99</td><td>2.11 ± 0.23</td><td>3.39 ± 0.14</td><td>1.99 ± 0.25</td><td>0.11 ± 0.01</td><td>94.2 ± 28.1</td><td>0.16 ± 0.03</td><td>0.15 ± 0.07</td><td>0.06 ± 0.01</td></tr><tr><td>Protomyctophum bolini</td><td>10</td><td>26,261 ± 4970</td><td>17,957 ± 2396</td><td>13,353 ± 2951</td><td>6284 ± 1533</td><td>2879 ± 572</td><td>99.0 ± 59.7</td><td>57.5 ± 10.6</td><td>6.29 ± 1.16</td><td>3.61 ± 0.95</td><td>2.30 ± 0.56</td><td>2.79 ± 0.73</td><td>1.68 ± 0.22</td><td>0.12 ± 0.01</td><td>90.6 ± 20.6</td><td>0.24 ± 0.06</td><td>1.17 ± 1.27</td><td>0.10 ± 0.04</td></tr></tbody></table>

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<table><caption>Table 2 (continued)</caption><thead><tr><th>Family/Species</th><th>n</th><th>Ca</th><th>P</th><th>Na</th><th>K</th><th>Mg</th><th>Fe</th><th>Zn</th><th>Cu</th><th>Mn</th><th>As</th><th>Se</th><th>Ni</th><th>Co</th><th>Sr</th><th>Cd</th><th>Pb</th><th>Ag</th></tr></thead><tbody><tr><td>Protonyctophum chortodon</td><td>8</td><td>22,256 ± 2533</td><td>17,573 ± 1561</td><td>12,194 ± 1198</td><td>8524 ± 1091</td><td>2484 ± 274</td><td>70.2 ± 37.8</td><td>53.4 ± 6.2</td><td>6.35 ± 1.24</td><td>3.03 ± 0.42</td><td>2.17 ± 0.45</td><td>2.62 ± 0.43</td><td>1.32 ± 0.27</td><td>0.10 ± 0.01</td><td>67.8 ± 10.7</td><td>0.62 ± 0.28</td><td>0.35 ± 0.47</td><td>0.05 ± 0.02</td></tr><tr><td>Protonyctophum tenisoni</td><td>10</td><td>26,471 ± 3736</td><td>19,493 ± 1744</td><td>12,141 ± 1367</td><td>7991 ± 1321</td><td>2707 ± 213</td><td>73.9 ± 18.6</td><td>71.1 ± 26.3</td><td>8.22 ± 2.46</td><td>3.55 ± 0.76</td><td>2.09 ± 0.37</td><td>3.34 ± 0.70</td><td>1.85 ± 0.36</td><td>0.13 ± 0.02</td><td>87.9 ± 13.5</td><td>0.40 ± 0.18</td><td>0.29 ± 0.14</td><td>0.06 ± 0.03</td></tr><tr><td>Notosudidae</td><td>1</td><td></td><td>12,117</td><td>13,495</td><td>8143</td><td>12,402</td><td>1686</td><td>72.9</td><td>6.49</td><td>2.59</td><td>3.20</td><td>2.93</td><td>0.61</td><td>0.06</td><td>54.9</td><td>0.43</td><td>0.03</td><td>0.06</td></tr><tr><td>Luciosudis normani</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><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Nototheniidae</td><td>2</td><td>22,532 ± 1260</td><td>20,935 ± 756</td><td>8302 ± 805</td><td>16,603 ± 3201</td><td>1645 ± 95</td><td>32.6 ± 4.7</td><td>53.0 ± 0.3</td><td>3.99 ± 0.25</td><td>2.42 ± 0.15</td><td>7.55 ± 0.21</td><td>3.57 ± 0.37</td><td>1.09 ± 0.02</td><td>0.09 ± 0.01</td><td>74.3 ± 17.8</td><td>0.51 ± 0.18</td><td>0.01 ± 0.00</td><td>*</td></tr><tr><td>Dissostichus eleginoides</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><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Gobionotothen acuta</td><td>8</td><td>31,488 ± 14,137</td><td>23,221 ± 6655</td><td>9063 ± 1624</td><td>12,993 ± 1754</td><td>1613 ± 353</td><td>43.0 ± 12.5</td><td>72.2 ± 9.9</td><td>3.47 ± 0.62</td><td>11.12 ± 3.47</td><td>17.51 ± 5.81</td><td>3.92 ± 2.18</td><td>1.24 ± 0.03</td><td>0.11 ± 0.03</td><td>131.4 ± 56.4</td><td>1.04 ± 1.19</td><td>0.03 ± 0.04</td><td>0.02 ± 0.01*</td></tr><tr><td>Lepidonoton squamifrons</td><td>10</td><td>24,467 ± 6100</td><td>18,474 ± 2817</td><td>7898 ± 504</td><td>12,716 ± 501</td><td>1618 ± 150</td><td>32.6 ± 9.2</td><td>48.6 ± 7.2</td><td>3.29 ± 0.90</td><td>10.65 ± 0.33</td><td>2.31 ± 2.19</td><td>1.18 ± 0.26</td><td>0.09 ± 0.02</td><td>89.8 ± 26.7</td><td>0.65 ± 0.27</td><td>0.02 ± 0.01</td><td>0.02 ± 0.01</td><td>0.02 ± 0.01*</td></tr><tr><td>Lindbergichthys mizops</td><td>7</td><td>35,207 ± 6034</td><td>24,524 ± 3806</td><td>10,090 ± 1717</td><td>13,460 ± 950</td><td>2263 ± 388</td><td>44.9 ± 23.1</td><td>75.3 ± 26.1</td><td>7.29 ± 1.21</td><td>4.25 ± 0.94</td><td>6.60 ± 1.77</td><td>3.33 ± 1.40</td><td>1.51 ± 0.03</td><td>0.13 ± 0.03</td><td>133.8 ± 27.9</td><td>0.90 ± 0.66</td><td>0.06 ± 0.02</td><td>0.02 ± 0.01*</td></tr><tr><td>Paralepididae</td><td>3</td><td>18,909 ± 519</td><td>17,977 ± 122</td><td>18,584 ± 151</td><td>13,053 ± 281</td><td>3262 ± 151</td><td>204.7 ± 10.50</td><td>67.3 ± 0.32</td><td>10.50 ± 0.42</td><td>3.63 ± 0.02</td><td>1.27 ± 0.02</td><td>3.71 ± 0.82</td><td>0.82 ± 0.05</td><td>0.08 ± 0.00</td><td>69.8 ± 1.3</td><td>0.20 ± 0.08</td><td>0.06 ± 0.02</td><td>0.00 ± 0.00</td></tr><tr><td>Arctoconus risso</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><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Noolepis coati</td><td>10</td><td>21,455 ± 2344</td><td>18,625 ± 1509</td><td>21,796 ± 1734</td><td>9881 ± 686</td><td>4185 ± 201.0</td><td>12.92 ± 107.7</td><td>12.92 ± 23.9</td><td>5.88 ± 4.43</td><td>0.80 ± 1.31</td><td>2.01 ± 0.13</td><td>3.95 ± 1.39</td><td>0.22 ± 0.08</td><td>95.6 ± 10.5</td><td>0.23 ± 0.08</td><td>1.35 ± 0.93</td><td>0.05 ± 0.07*</td><td>0.05 ± 0.02</td></tr><tr><td>Stomilidae</td><td>1</td><td>7771</td><td>8642</td><td>20,069</td><td>7073</td><td>2726</td><td>39.2</td><td>42.9</td><td>5.78</td><td>2.08</td><td>1.48</td><td>2.23</td><td>0.37</td><td>0.04</td><td>47.8</td><td>0.80</td><td>0.03</td><td>0.02</td><td>0.02</td></tr><tr><td>Idiacanthus atlanticus</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><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Stomias spp.</td><td>10</td><td>17,538 ± 7301</td><td>14,184 ± 4643</td><td>17,782 ± 4365</td><td>8671 ± 1965</td><td>3003 ± 783</td><td>171.6 ± 188.1</td><td>60.0 ± 16.9</td><td>3.88 ± 0.62</td><td>3.12 ± 1.58</td><td>1.74 ± 0.34</td><td>1.49 ± 0.14</td><td>1.03 ± 0.28</td><td>0.08 ± 0.02</td><td>74.8 ± 28.8</td><td>0.45 ± 0.22</td><td>0.02 ± 0.01*</td><td>0.02 ± 0.02</td></tr><tr><td>Zoarcidae</td><td>10</td><td>17,731 ± 6413</td><td>14,505 ± 3684</td><td>22,335 ± 3478</td><td>7881 ± 1108</td><td>2384 ± 494</td><td>22.1 ± 2.2</td><td>90.7 ± 24.3</td><td>11.26 ± 2.19</td><td>1.01 ± 0.27</td><td>4.17 ± 0.68</td><td>2.25 ± 0.16</td><td>0.75 ± 0.19</td><td>0.07 ± 0.02</td><td>94.1 ± 35.2</td><td>1.71 ± 0.55</td><td>0.04 ± 0.24</td><td>0.05 ± 0.05</td></tr></tbody></table>

concentrations averaged by species for the statistical analysis (PCA and HC) to supply similar statistical weight for each species. We detected five outliers in fish samples with extreme high values for one nutrient. These values were replaced with values of the 97.5 % percentile (calculated with all forage species samples) to keep the samples while limiting their influence in statistical analysis.

All analyses were computed in R (R core Team, 2023) and the associated R project can be found in GitHub (https://github.com/Lola-san/Kerguelen_fish_composition).

### 3. Results

The nutrient content of Kerguelen forage fish included in this study was significantly variable within the community, both for absolute nutrient concentrations and relative nutrient fractions. The pattern and magnitude of variability differed between nutrients (major or trace, essentials or non-essentials), with significant co-variations for some pairs of nutrients. Using hierarchical clustering, we found four forage fish groups (clusters) based on their concentrations in essential nutrients.

#### 3.1. Forage fish absolute nutrient concentrations

Concentrations of major essential nutrients in forage fish species varied from 1203 ± 126 mg·kg⁻¹ dry weight (dw; with mean ± standard deviation) (G. bolini, n = 10) to 4185 ± 400 mg·kg⁻¹ dw (N. coati, n = 10) for Mg, and from 7475 ± 3947 mg·kg⁻¹ dw (N. antarctica, n = 5) to 35,956 ± 408 mg·kg⁻¹ dw (M. mancopedsetta, n = 2) for Ca (Table 2). Lowest concentrations in essential trace nutrients were found for Co with 0.04 mg·kg⁻¹ dw (I. atlanticus, n = 1) to 0.22 ± 0.08 mg·kg⁻¹ dw (N. coati, n = 10), while highest concentrations varied from 11.4 ± 4.5 mg·kg⁻¹ dw (C. gunnari, n = 10) to 204.7 ± 69.6 mg·kg⁻¹ dw (A. risso, n = 3) for Fe. Iron concentrations were the most variable across essential nutrients and species (coefficient of variation CV = 0.86). Concentrations in Sr, the most concentrated non-essential nutrient and the least variable (CV = 0.45), varied from 38.0 ± 19.5 mg·kg⁻¹ dw (N. antarctica, n = 5) to 212.1 ± 23.9 mg·kg⁻¹ dw (M. maculata, n = 2). Then, Cd concentrations varied from 0.14 ± 0.07 mg·kg⁻¹ dw (M. maculata, n = 2) to 1.81 ± 1.05 mg·kg⁻¹ dw (C. gunnari, n = 10); Pb concentrations from 0.01 ± 0.00 mg·kg⁻¹ dw (C. rhinoceratus, n = 10 and D. eleginoides, n = 2) to 1.35 ± 0.93 mg·kg⁻¹ dw (N. coati, n = 10) and finally Ag concentrations from 0.01 ± 0.00 mg·kg⁻¹ dw (G. bolini, n = 10 and G. braueri, n = 12) to 0.27 ± 0.12 mg·kg⁻¹ dw (M. marmorata, n = 10). Concentrations of Ag and Pb were the most variable across species (CV of 1.2 and 1.9 respectively).

The distribution of observed concentrations within each nutrient concentration range differed between nutrients (Fig. 2), with approximately platykurtic (i.e., short and fat bell with few or no extreme values) distributions for P, Se; slightly right-skewed unimodal distributions for Ca, Na, K, Zn, Cd; and right-skewed uni- to bi-modal distributions for other nutrients, with the most leptokurtic (i.e., high and skinny bell with long tails) distributions for Pb, Ag, As, Ni, Mn, and Fe (in order of intensity).

Fish species were not consistent in their concentration rank for the different nutrients, i.e., a species rich in iron and therefore with concentrations in the right tail of the distribution across species was not necessarily enriched in other nutrients (Fig. 3). For example, A. risso was the richest in Fe, but the second poorest in As, the 10th richest species in Zn and had an average P concentration. In contrast, C. gunnari showed the lowest Fe concentration, but was part of the eight most-concentrated species in P, Zn and As. N. coati was part of the richest for all nutrients but As and Se (Fig. 3; Table 2), while species such as G. braueri were consistently amongst the poorest for all nutrients.
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Density plots of nutrient concentrations (in mg·kg⁻¹ dry weight) in whole fish samples from 34 species collected around the Kerguelen Islands (Southern Ocean) for the 13 essential nutrients calcium Ca, phosphorus P, potassium K, sodium Na, magnesium Mg, iron Fe, zinc Zn, copper Cu, manganese Mn, arsenic As, nickel Ni, selenium Se, cobalt Co (dark grey strip background) and the four non-essential nutrients strontium Sr, cadmium Cd, lead Pb and silver Ag (light grey strip background). Density plots were colour-filled with one colour per nutrient to facilitate reading.</figcaption></figure>

## 3.2. Forage fish relative nutrient composition and nutrient co-variation

Major nutrients Ca, P, Na, K, and Mg made up the bulk of the nutrient mix contained in forage fish, and their nutrient fractions appeared quite close in the range of species included here (Fig. 4). However, the nutrient fraction of less concentrated nutrients, and especially in Fe, As, Cd, and Ag was more variable between species, so that species alike in their nutrient cocktail in Ca, P, Na, K, and Mg could show different profiles in their less concentrated nutrients. For example, *E. cryomargarites* and *C. gunnari* are similar in their nutrient fractions in Ca, P, Na, K, Mg, Sr, Zn, but *C. gunnari* is six and five time richer in As and Cd respectively; or *A. risso* and *N. coati* are similar for their nutrient fractions in most nutrients, but *N. coati* is three times richer in Ni and twenty-three times richer in Pb.

In addition, nutrient concentrations (and thus fractions) did not vary independently (Fig. 5). On the 136 pairs of nutrients tested, concentrations were quite strongly positively correlated for 18 % (correlation coefficient > 0.4), and quite strongly negatively correlated (correlation coefficient < -0.4) for 9 %. Strong positive correlations (i.e., > 0.4; Appendix A) were found between concentrations in the major nutrients Ca and P, Na and Mg, and both Ca and P concentrations and As, Ni, Se, Co, and Sr concentrations. There were also some strong co-variations between major and trace nutrients such as K and As and Mg and Cu, and between essential trace nutrients such as Fe and Mn, As and Ni, Se and Co. Forage fish concentrations in the non-essential trace nutrient Cd were negatively correlated to concentrations in Fe and positively correlated to concentrations in As. Concentrations in Pb were negatively correlated to concentrations in P, K, Mn, As, and Ni but positively correlated to Fe and Se concentrations. Finally, Ag concentrations were negatively correlated to concentrations in Ca, P, and Mn.

## 3.3. Forage fish nutritional typology

Hierarchical clustering (HC) resulted in four clusters of forage fish species with shared essential nutrient composition characteristics

(Fig. 6). Cluster 1 contained eleven species (including eight myctophids species) and had the lowest average concentrations in Na and Zn (p-values of Mann-Whitney-Wilcoxon tests in Appendix A). Cluster 2 contained eight species associated to the ocean bottom (i.e., demersal, bathydemersal, or benthopelagic; Table 1), characterised by the highest concentrations in P, K, and As, and high concentrations in Ca, Zn, and Se. Cluster 3 contained six mesopelagic species. They were characterised by the lowest concentrations in Ca, Ni, and Co, and low concentrations in P and K. Cluster 4 contained nine species with eight mesopelagic and one bathydemersal. They had the highest concentrations in Na, Mg and Fe, the lowest concentrations in As and relatively high concentrations of Ca, Cu, Mn, and Ni.

In terms of their concentrations in non-essential trace nutrients, cluster 2 species had the lowest concentrations in Pb (although they were not significantly different from that of cluster 3; Appendix A) but high concentrations in Sr and Cd, cluster 3 species had the highest concentrations in Ag and relatively high concentrations in Cd (with Cd concentrations not significantly different from that of cluster 2), and cluster 4 species had the lowest concentrations in Cd (but not significantly different from that of cluster 1) and relatively high concentrations in Pb (Fig. 6c).

## 4. Discussion

This study provides the first assessment of the nutrient composition of the mesopelagic and demersal fish community around the Kerguelen Islands, in the Indian sector of the Southern Ocean (SO), for such a diversity of nutrients, including five essential major nutrients, eight essential trace nutrients and four non-essential nutrients. We showed that fish were significantly heterogeneous in their nutrient content, with four clusters found based on their composition in essential nutrients. By including multiple nutrients and showing variability in both absolute and relative composition, we provide novel baseline information on the quality of fish as prey in this ecologically important subantarctic region, including interactions between different essential nutrients, and
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Species concentrations (in mg·kg⁻¹ dry weight) in phosphorous P, iron Fe, zinc Zn and arsenic As in whole forage fish from 34 species collected around the Kerguelen Islands (Southern Ocean). For each species, the central point is the median, and the line extend to the 2.5th and 97.5th percentiles respectively, with each being coloured by species. The colour gradient was set to match the species concentration order for Fe, and kept for other nutrients. In the species list legend, *n* indicates the number of sample per species. Black arrows and associated species names point out to species mentioned in the main text. Red solid and dashed lines are median and mean values of all samples, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

between essential and non-essential nutrients, which are poorly documented (Cipro et al., 2018). This information further demonstrates that prey are not interchangeable, as the consumption of one or another prey species modulates the ability of the predator to meet its requirements and its exposure to contaminants (Bocher et al., 2003; Chouvelon et al., 2022). With a focus on nutrient dynamics, it may also modulate predator-mediated nutrient recycling, as the balance between the nutrient input from forage prey and the predator's nutrient requirements likely determines the balance in the nutrient output after consumption.

The typology obtained here differs from prey taxonomical and nutritional classifications, the latter being mostly based on energy contents and macromolecule ratios (e.g., lipids, proteins; Spitz et al., 2010). Fulfilling an organism's nutrient needs, whether from live prey or from inert matter (i.e., including primary producers' nutrient intake and food intake by herbivorous or carnivorous micro- to megafauna) is a matter of balance (Raubenheimer et al., 2022). This balance varies at the scale of macromolecules as well as the finer scale of nutrients, so our study provides a complementary functional view of the diversity of prey in marine ecosystems. For example, while myctophids are identified as energy-rich prey (Spitz et al., 2010), most of the species analysed here are separated into two clusters (1 and 4) based on their concentrations in Na, Mg, Fe, and Mn (Fig. 6). However, species of the same genus are

found in the same cluster (Electrona, Gymnoscopelus and Protomyctophum spp.), which suggest that there may be taxonomic patterns of composition beyond macronutrient and energy content. It is also noteworthy that *Protomyctophum* species belong to the cluster enriched in trace nutrients (4) despite having a lower average trophic level than *Gymnoscopelus* and *Electrona* species (Cherel et al., 2010), which may indicate that nutrient concentrations in fish are not necessarily proportionate to their trophic positions. Only one previous study shares species (12) and nutrients (Cu, Cd and Zn) in the same area (Cipro et al., 2018), but the analytical methods used to estimate nutrient concentrations differ (flame and graphite furnace atomic absorption spectrophotometer vs inductively coupled plasma emission and mass spectrometry). For the same species, we generally obtained concentrations twice greater for Cu, slightly greater for Cd, and similar for Zn. However, it is difficult to attribute these differences to either a temporal change in fish nutrient concentrations (their samples were collected in 1997, 1998 and 1999 austral summers) or to the analytical method.

Our classification relates to aspects of ecology or physiology of the sampled fish, to some extent. For example, bottom-associated species in cluster 2 showed higher P and Ca than other clusters, likely due to heavier bones, meaning they contain more calcium phosphate than pelagic species. The two ice fish species *C. gunnari* and *C. rhinoceratus* (also in cluster 2), which have no haemoglobin (Galbraith et al., 2019),
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Variability in the relative nutrient content of whole forage fish from 34 species collected around the Kerguelen Islands (Southern Ocean). Relative proportion of Ca, P, Mg, Na, K (top panel), Sr, Fe, Zn (2nd from the top panel), Cu, Mn, As, Ni, Se (3rd panel), Cd, Co, Pb and Ag (bottom panel) within the total nutrient mix in an average fish, with the absolute concentrations for this calculation being averaged by species. Vertical bars represent individual species, identically ordered on all panels according to their families (i.e., same order as in Tables 1 and 2). The fraction missing to reach 1 on the top panel is shown on the following panels with magnified scales, with nutrients separated in different panels according to their relative fraction range.</figcaption></figure>

showed accordingly the lowest and the 4th lowest Fe concentrations (Fig. 2; Table 2). In addition, species from cluster 2 had high As concentrations, similar to what was found in benthopelagic bony fish species in the Northeast Atlantic, which suggests a higher exposition to this nutrient in the benthic habitat (Chouvelon et al., 2022). Cluster 4 included two species (*Stomias* spp. and *A. risso*) occurring both in the SO and in the Northeast Atlantic, and belonging to a group enriched in Fe and Na. However, their cluster in the SO was not as Fe-enriched (102 ± 58 mg·kg⁻¹ dw) as in the analogous Northeast Atlantic one (270 mg·kg⁻¹ dw) (Chouvelon et al., 2022). In addition, Fe enrichment in Northeast Atlantic fish, where Fe is not the primary limiting nutrient (Moore et al., 2013), was associated with the lowest average Cu concentrations (2.0 mg·kg⁻¹ dw respectively; Chouvelon et al., 2022), whereas fish in our cluster 4 were characterised by the highest Cu concentrations (7.7 ± 2.8 mg·kg⁻¹ dw). Diatoms have higher Cu requirements in Fe-limited oceanic environments than in coastal and comparatively nutrient-enriched waters (Peers and Price, 2006). In the context of the SO, where Fe paucity limits the growth of primary producers, the lower Fe concentrations and differences in Fe and Cu co-variations in fish from ecosystems with different nutrient regimes suggest that physiological adaptations to nutrient limitations may also extend to higher trophic levels (Boersma et al., 2008), with the lack of haemoglobin being an extreme example of such adaptation (Galbraith et al., 2019).

Our results also point to the variability in the content of forage fish in non-essential and potentially toxic nutrients, as the four clusters of species differed in their absolute and relative concentrations in Sr, Cd, Ag, and Pb. Fish with the lowest concentrations for most nutrients

(cluster 3) showed the greatest concentrations in Cd and Ag. The Fe-enriched fish (cluster 4) were the richest in Pb but had the lowest concentrations in Cd, which concurred with Fe concentrations being positively correlated to Pb concentrations and negatively correlated to Cd concentrations. Bottom-associated species (cluster 2) enriched in Ca, P, K, and As were also the richest in Sr and second richest in Cd, also concurring with the positive co-variations between Sr and the former essential nutrients, and between Cd and As concentrations. Cadmium and As were previously identified as interacting in organisms (Yáñez et al., 1991), similar to Fe and Pb (Kwong et al., 2004). It is likely that Cd and Pb in fish are absorbed through the gills or guts by mimicking essential nutrients and using the same absorption pathways (Bridges and Zalups, 2005; Kwong, 2024). Similar to essential nutrients, species differences are likely driven by the fish physiology, their habitat use and exposure (Bustamante et al., 2003), and their trophic ecology (Goutte et al., 2015; Lischka et al., 2021). For example, Sr in fish (and in most vertebrates) accumulates in bone tissue and behaves similarly to Ca (Chowdhury and Blust, 2011), so its higher concentrations in benthopelagic species is consistent with their likely heavier bones. Whether Sr is an essential nutrient is still debated, but it is unlikely to be harmful (Chowdhury and Blust, 2011). However, Cd, Pb, and Ag can have detrimental effects on primary producers (Permana and Akbarsyah, 2021), primary (Bielmyer et al., 2006) secondary (Hogstrand and Wood, 1998; Shahjahan et al., 2022) consumers, and predators (Ali et al., 2019; Desforges et al., 2016). The typology we obtained therefore shows how nutrition can be a trade-off, no forage prey can be good in all respects in terms of nutrient intake and have the lowest levels of contamination.

Most of the species analysed here (85 %) have been previously
<figure><img src="image_7.png" /><figcaption>**Fig. 5.** Correlation coefficients between different nutrients' concentrations suggest covariation between nutrients in whole forage fish (264 samples from 34 species, with concentrations averaged by species) collected around the Kerguelen Islands (Southern Ocean). Only the strongest correlation coefficients are displayed, i.e., < -0.4 (negative covariation) in blue and > 0.4 (positive covariation) in red, with intermediate values displayed in grey. Correlation coefficients are provided in Appendix A. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

identified as prey for up to 14 marine predator species found in the Kerguelen area (including flying and diving seabirds, and pinnipeds; Table 1 and references therein). Nutrients in living fish are fixed in biomass (excluding the waste they release) and are not available to lower trophic levels. Through predation however, a fraction can return to lower trophic levels through the waste products of predators (faeces and urine). Once released, nutrients can leach into the environment and may be up-taken by primary producers, either directly, after complexation with free bacterial ligands (Ratnarajah et al., 2017) or remineralisation by the microbial community (Ratnarajah and Bowie, 2016). Alternatively, they can also be ingested directly by lower trophic levels (e.g., zooplankton, Roman and McCarthy, 2010; or coprophagous microfauna), or sink to deeper waters in ocean ecosystems (Ratnarajah et al., 2018; Ratnarajah et al., 2016a). Depending on locations and ecosystems, different forage fish could therefore act as long-term reservoirs of limiting nutrients (Le Mézo et al., 2022), similarly to Antarctic krill *Euphausia superba* in the SO (Nicol et al., 2010; Ratnarajah et al., 2016b). Our clustering showed that some species were enriched in specific nutrients, such as *C. gunnari* in Ca and P (cluster 2) or *P. tenisoni* in Mg, Fe, and Mn (cluster 4). As predators consume these different prey species, their egesta may become even more enriched in these nutrients, thereby increasing the fertilisation of the environment where they defecate.

In the SO, Fe and Mn can both limit the growth of primary producers (Hassler et al., 2012; Hawco et al., 2022). The consumption of species from cluster 4, enriched in Mg, Fe, and Mn, may facilitate their return to euphotic waters and their recycling in light-based food webs, making them "super-contributors" to the biological recycling of these nutrients. Myctophids are major forage prey in pelagic food webs and are part of the diet of at least 12 local predators (Table 1). Their proportion in average diet descriptions can reach 60 % of ingested biomass (e.g., king penguins; Bost et al., 2002). However, our results suggest that the nutrient load of the potential fertiliser produced by predators may vary depending on whether they preferentially consume *Protomyctophum*

species (cluster 4), *Gymnoscopelus* and *Electrona* species (cluster 1) or *K. anderssoni* (cluster 3).

In addition, the coastal terrestrial ecosystem benefits from allopatric marine-derived nutrients, as pinnipeds and seabirds come ashore during the breeding season and defecate on land. This nutrient enrichment from open ocean marine predators may also occur in coastal waters as some nutrients may leach out in front of colonies (Finne et al., 2022; Treasure et al., 2015). On land, productivity is mainly limited by major nutrients such as nitrogen (N) or P (Bokhorst et al., 2007; Smith, 2008). Inputs of these nutrients by marine predators influence several sub-Antarctic coastal ecosystems (Bokhorst et al., 2019b; Bokhorst et al., 2019a; Souza-Kasprzyk et al., 2022), and could be important on the shores of the Kerguelen Islands. Interestingly, a proportion of fish – including seven species out of eight previously found in the diet of local predators (Table 1), was enriched in major nutrients Ca, P, and K (cluster 2). If their consumption translates into higher concentrations for these nutrients in the faeces of predators, they may be super-contributors to the biological transfer of Ca, P, and K to terrestrial ecosystems.

As sample collection happened 15 to 20 years ago, environmental conditions may have evolved since then – especially given the speed and intensity of climate changes in this region (Chapman et al., 2020; Lebouvier et al., 2011), and thus nutrient content of fish as well. Assessing this potential change would provide information on how global changes affect biochemical levels of nutrients in ecosystems and how they might alter the indirect role of the fauna in nutrient dynamics. However, the variability in the multi-nutrient content of the prey community presented here is likely to still be observed today if its functional composition has not changed significantly. Another consequence of the time lag between sample collection and biochemical analysis is that the estimated moisture percentage per sample may be negatively biased, as samples were frozen for years before analysis. In this study, we only considered dry weight concentrations, so this does not affect our results and conclusions. However, it should be taken into account when converting dry weight concentrations to wet weight concentrations, for example to estimate the nutrient composition of the average diet of a predator. Finally, we have no information on the biochemical speciation of nutrients in prey, despite the fact that it will likely impact their absorption by predators during digestion (Bustamante et al., 2003) and their speciation in predators' waste (Ratnarajah et al., 2017). This, in turn, should also determine their fate in the environments and uptake by primary producers (Ali et al., 2019; Ratnarajah et al., 2018).

Despite these limitations, our results highlight the different potentialities of fish species in nutrient recycling when they are consumed by predators. The dataset and analyses presented in this study provide a valuable baseline knowledge that can be used in nutrition, nutrient dynamics, and contaminant transfer studies. Assessing the variability in the multi-nutrient composition of other important forage taxa, namely crustaceans and cephalopods, would complete our understanding of the functionality of the forage community in the area. It would also help to quantitatively estimate the nutrient output of predators by considering the balance of prey with different nutrient contents using diet descriptions and bioenergetic modelling. Given the unique ecological context of the Kerguelen region, where most biogeochemical research to date has focused on abiotic processes or primary trophic levels, this would greatly enhance our understanding of the complex biochemical processes that occur within an ecosystem.

## Author contribution

LG, JS and TJDD designed the study. YC lead the sampling campaign on *La Curieuse* and provided fish samples. LG performed the lab preparation of samples with contributions of YC and JS for fish species identification. LG performed data analysis with contributions of JS and TJDD on statistical analyses. LG wrote the first draft of this manuscript, which was improved by JS, TJDD and YC.
<figure><img src="image_8.png" /><figcaption>Fig. 6. Hierarchical clustering analysis from Ward's minimum variance method distinguished four clusters in the 34 forage fish species sampled around the Kerguelen Islands (Southern Ocean), based on their concentrations in the 13 essential nutrients calcium Ca, phosphorus P, sodium Na, potassium K, magnesium Mg, iron Fe, zinc Zn, copper Cu, manganese Mn, selenium Se, arsenic As, nickel Ni and cobalt Co. Species in the four clusters are shown on a dendrogram (a) and their nutrient concentrations (in mg·kg⁻¹ dry weight) are shown with boxplots for the essential nutrients used for the clustering analysis (b) and for the non-essential nutrients strontium Sr, cadmium Cd, lead Pb and silver Ag which were not included in the clustering analysis (c). Significance letters indicate the output of pairwise comparison tests (Mann-Whitney-Wilcoxon), with no letter in common indicating concentrations were found to be significantly different and a common letter indicating concentrations were not found to be significantly different (Appendix A). Boxplots display the median with solid black line in each box, lower and upper hinges correspond to the 25th and 75th percentiles, respectively; upper and lower whiskers extend respectively from the hinges to the largest and lowest values no further than 1.5 times the inter-quartile range, and data beyond the end of whiskers are plotted as individual points. Boxplots were combined to violin plots to highlight the distribution around the median. Median and mean for all samples are indicated with the red solid and dashed lines, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

## Author statement

I, the corresponding author Lola Gilbert, declare that this manuscript or a very similar manuscript has not been published, nor is under consideration by any other journal.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

We thank the technical and scientific crews from the two vessels *La Curieuse* and *Austral* in enabling sample collection. We also thank the "Plateforme Analyses Elémentaire" of the LIENSs (LIttoral ENvironmentment et Sociétés; UMR 7266 CNRS - La Rochelle Université) for their technical support in the nutrient analysis, and especially Carine Churlaud and Maud Brault-Favrou for their help and kindness. The present work was

supported by La Rochelle University through a PhD grant, with sample collection supported financially and logistically by the Institut Polaire Français Paul Emile Victor (IPEV, programme no. 109, C. Barbraud), and the Terres Australes et Antarctiques Françaises (TAAF).

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jembe.2025.152097.

## Data availability

The fish nutrient composition data supporting the conclusions of this article are publicly available through the data.InDoRES (Inventaire des Données de la Recherche en Environnement et Sociétés) platform: https://doi.org/10.48579/PRO/2AXFDD.
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