Marina Renedo
email: marina.renedo@ird.fr

Paco Bustamante

Yves Cherel

Zoyne Pedrero

Emmanuel Tessier

David Amouroux
email: david.amouroux@univ-pau.fr

A "seabird-eye" on mercury stable isotopes and cycling in the Southern Ocean

Keywords: methylmercury, biogeochemistry, latitude gradients, penguins, skuas

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Graphical abstract 1. Introduction

Although the Southern Ocean is usually perceived as a pristine area untouched by anthropogenic pressures, contaminants can nonetheless reach this region by ocean circulation and atmospheric transport [START_REF] Fitzgerald | Marine biogeochemical cycling of mercury[END_REF]. Mercury (Hg) is considered a globally distributed contaminant of major concern for humans and wildlife, especially in its methylmercury (MeHg) form [START_REF] Eagles-Smith | Modulators of mercury risk to wildlife and humans in the context of rapid global change[END_REF]. Indeed, MeHg is a potent organometallic neurotoxin that accumulates in living organisms and that biomagnifies within food webs [START_REF] Mason | Uptake, toxicity and trophic transfer of Hg in a coastal diatom[END_REF][START_REF] Watras | Bioaccumulation of mercury in pelagic freshwater food webs[END_REF]. The Hg biogeochemical cycle is highly complex and comprises several chemical processes and biological transformations, such as methylation/demethylation and redox reactions, that control MeHg production and its bioavailability to marine organisms. Hg methylation is thought to be mainly driven by anaerobic micro-organisms within the water column down to at least the oxygen minimum zone (Lehnherr et al., 2011[START_REF] Heimbürger | Shallow methylmercury production in the marginal sea ice zone of the central Arctic Ocean[END_REF]. Due to biomagnification processes, top predators are

Winter mixing

Bioassimilation exposed to high levels of MeHg, thereby presenting severe health risks for their populations (Tartu et al., 2013, Goutte et al., 2014ab).

In the Southern Ocean, particularly in the Indian Ocean sector, various studies have reported significant levels of Hg bioaccumulation in top predators such as seabirds [START_REF] Goutte | Demographic consequences of heavy metals and persistent organic pollutants in a vulnerable long-lived bird, the wandering albatross[END_REF][START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF](Carravieri et al., , 2020;;[START_REF] Cherel | Accumulate or eliminate? Seasonal mercury dynamics in albatrosses, the most contaminated family of birds[END_REF], with a common MeHg concentration trend exhibiting 4 to 8-fold higher concentrations in Subtropical relative to Antarctic populations for all of the seabird species studied to date [START_REF] Goutte | Demographic consequences of heavy metals and persistent organic pollutants in a vulnerable long-lived bird, the wandering albatross[END_REF][START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF]. There is however a paucity of information in regard to Hg concentrations, the spatial distribution, and speciation in the water column from this remote area of the world's oceans (Cossa et al., 2011;[START_REF] Lamborg | A global ocean inventory of anthropogenic mercury based on water column measurements[END_REF][START_REF] Canario | Mercury and methylmercury in the Atlantic sector of the Southern Ocean[END_REF]. Complex oceanic dynamics along the Southern Ocean regions induce changes in the properties and subduction/upwelling rates of water masses [START_REF] Sallée | Zonally asymmetric response of the Southern Ocean mixed-layer depth to the Southern[END_REF], thereby influencing the vertical advection of MeHg in the water column (Cossa et al., 2011), and consequently its availability for its assimilation within the marine food web. Substantial inter-seasonal variations also result in build-up of Hg-enriched surface waters during winter months and its subsequent downward transfer during spring and early summer (Cossa et al., 2011) before the shallow mixed layer is re-established [START_REF] Sallée | Zonally asymmetric response of the Southern Ocean mixed-layer depth to the Southern[END_REF].

The study of Cossa et al., (2011) is the only one to date investigating latitudinal variations of methylated Hg (MeHg and dimethylmercury (Me2Hg)) and the distribution in the water column of the Southern Ocean. This study revealed slightly higher concentrations in Antarctic seawaters (0.15 to 0.21 pmol L -1 ) compared to Subantarctic and Subtropical seawaters (0.08 to 0.10 pmol L -1 ). Although these data only reflected a single seasonal setting, this north to south gradient of increasing MeHg concentrations in water is opposite to the trend observed in the tissues of seabirds [START_REF] Becker | Feather mercury concentrations in Southern Ocean seabirds: Variation by species, site and time[END_REF][START_REF] Goutte | Demographic consequences of heavy metals and persistent organic pollutants in a vulnerable long-lived bird, the wandering albatross[END_REF][START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF]Carravieri et al., , 2020;;[START_REF] Cherel | Accumulate or eliminate? Seasonal mercury dynamics in albatrosses, the most contaminated family of birds[END_REF].

However, the seasonal mismatch (March-April) between the sampling campaign of Cossa et al., (2011) and studies during seabird breeding stages (November-February) [START_REF] Goutte | Demographic consequences of heavy metals and persistent organic pollutants in a vulnerable long-lived bird, the wandering albatross[END_REF][START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF](Carravieri et al., , 2020) ) must be carefully considered because intra-annual fluctuations in vertical oceanic dynamics, atmospheric deposition, chlorophyll-a concentrations, and light irradiance availability could affect MeHg production, transformations and transport in the water column.

The spatial range of methylated Hg concentrations (MeHg and Me2Hg) reported in the Southern Ocean water column might drive variations in biota MeHg concentrations. However, seasonal and geographical differences in Hg atmospheric deposition and Hg release during the melting of sea ice can greatly influence Hg concentrations in the water column. Therefore, Hg assimilation efficiency for primary producers might also be altered, thereby making this association much more complex. For instance, higher productivity in Antarctic and Polar Front zones [START_REF] Sullivan | Distributions of phytoplankton blooms in the Southern Ocean[END_REF][START_REF] Sokolov | Chlorophyll blooms in the Antarctic Zone south of Australia and New Zealand in reference to the Antarctic Circumpolar Current fronts and sea ice forcing[END_REF], could dilute biologically the MeHg reducing its uptake at the base of the food web [START_REF] Pickhardt | Algal blooms reduce the uptake of toxic methylmercury in freshwater food webs[END_REF]. Additionally, differences in food web complexities between ecosystems (Cherel et al., 2007[START_REF] Bost | Where do penguins go during the inter-breeding period? Using geolocation to track the winter dispersion of the bioindicators of mercury contamination in the southern Indian Ocean: geographical and temporal trends[END_REF], could induce a differential MeHg biomagnification, leading to different levels of exposure in top predators [START_REF] Lavoie | Biomagnification of Mercury in Aquatic Food Webs: A Worldwide Meta-Analysis[END_REF].

The measurement of subtle deviations in naturally occurring Hg stable isotope ratios provides a new and powerful perspective for the exploration of the cycle of this element, and it has been shown to be useful to depict Hg sources or to quantify its reactivity within different environmental compartments [START_REF] Blum | Mercury isotopes in Earth and environmental sciences[END_REF]. Hg has seven isotopes that experience massdependent and mass-independent isotopic fractionation (MDF and MIF, respectively). Most biogeochemical processes such as volatilization, reduction, absorption, demethylation, and methylation induce MDF (usually reported as δ 202 Hg) (Kritee et al., 2007[START_REF] Kritee | Mass dependent stable isotope fractionation of mercury during mer mediated microbial degradation of monomethylmercury[END_REF][START_REF] Rodriguez Gonzalez | Species-specific stable isotope fractionation of mercury during Hg (II) methylation by an anaerobic bacteria (Desulfobulbus propionicus) under dark conditions[END_REF][START_REF] Zheng | Isotope fractionation of mercury during its photochemical reduction by low-molecular-weight organic compounds[END_REF]. Aqueous photochemical processes (MeHg photodemethylation and inorganic Hg photoreduction) have been shown to lead to significant levels of MIF of odd Hg isotopes (∆ 199 Hg and ∆ 201 Hg) (Bergquist and Blum, 2007;[START_REF] Zheng | Mercury isotope fractionation during photoreduction in natural water is controlled by its Hg/DOC ratio[END_REF][START_REF] Perrot | Higher mass-independent isotope fractionation of methylmercury in the pelagic food web of Lake Baikal (Russia)[END_REF]. Intracellular odd-MIF was recently discovered during photomicrobial MeHg demethylation and Hg(II) reduction in a marine microalga in the presence or absence of UV-B light [START_REF] Kritee | Photomicrobial Visible Light-Induced Magnetic Mass Independent Fractionation of Mercury in a Marine Microalga[END_REF]. MIF of even-mass Hg isotopes, reported as ∆ 200 Hg and ∆ 204 Hg (i.e., anomalous fractionation of the 200/198 Hg and 204/198 Hg ratio from the theoretical MDF line), was first detected in rainfall samples and is thought to be associated to mechanisms occurring in the atmosphere, such as photo-oxidation in the upper tropopause and/or neutron capture in space (Gratz et al., 2010;Chen et al., 2012;[START_REF] Wang | Mass-dependent and mass-independent fractionation of mercury isotopes in precipitation from Guiyang, SW China[END_REF]. This signature is increasingly being investigated as a potential tracer of Hg sources of atmospheric origin. Consequently, the combination of Hg MDF and MIF signatures provide interesting and complementary information for potential sources and transformation pathways of Hg. In the Southern Ocean, Hg isotopic investigations in sediments and biota are limited to the Antarctic sector (Zheng et al., 2015;[START_REF] Liu | Different circulation history of mercury in aquatic biota from King George Island of the Antarctic[END_REF], and as a result, the information about the biogeochemical cycle of Hg in larger zones across Antarctic remote oceanic regions remains insufficient (Bowman et al., 2020).

Seabirds are meso-to top-predators that forage in various compartments of the pelagic ecosystems. Several studies have demonstrated the usefulness of seabirds to assess Hg contamination as far as the biological characteristics are mastered (e.g. moulting patterns, migration or foraging strategies [START_REF] Furness | Seabirds as monitors of the marine environment[END_REF][START_REF] Blévin | Wide range of mercury contamination in chicks of southern ocean seabirds[END_REF]Carravieri et al., , 2016;;Bustamante et al., 2016). Chicks of flying birds and both chick and adult penguins (a group of diving birds) are the most pertinent seabird models for tracing local Hg contamination pathways using Hg isotopic approaches because they reflect the Hg contamination around the colony [START_REF] Blévin | Wide range of mercury contamination in chicks of southern ocean seabirds[END_REF]Renedo et al., 2018a). Previous studies extensively explored the physiological, ecological and environmental aspects concerning the specific application of skua chicks and adult penguins for effective biomonitoring of Hg contamination at a large scale of the Southern Ocean (Carravieri et al., 2016[START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF]. Therefore, the use of skua chicks and adult penguins for Hg isotopic investigations provides significant advantages in regard to the survey of Hg sources and its associated biogeochemical processes in the ocean (Point et al., 2011;[START_REF] Day | Mercury stable isotopes in seabird eggs reflect a gradient from terrestrial geogenic to oceanic mercury reservoirs[END_REF]Zheng et al., 2015;Renedo et al., 2018b). Moreover, non-lethal sampling of feathers (reflecting the inter-moult period) and blood (reflecting short-term exposure) provides complementary and specific spatio-temporal information of Hg exposure in adults (Renedo et al., 2018a). Since blood Hg reflects recent Hg acquisition over the last weeks preceding sampling [START_REF] Bearhop | Dynamics of mercury in blood and feathers of greet skuas[END_REF], the Hg isotopic composition of blood of chicks and penguins is considered as indicative of local exposure with a relevant resolution (Renedo et al., 2018a).

In this work, we investigated the Hg isotopic composition (mainly as MeHg; Renedo et al., 2018a) of blood cells of two seabird models (skua chicks and adult penguins) in Antarctic, Subantartic and Subtropical zones (Fig. 1). We hypothesized that the specific regional MeHg dynamics and transfer to the marine pelagic trophic chain at different latitudes of the Southern Indian Ocean could lead to significant variations of Hg isotopic signatures of seabird blood (both MIF and MDF), then providing new insights to better constrain Hg and MeHg cycling in the Southern Ocean and seabird exposure to Hg. chrysocome filholi and northern rockhopper E. chrysocome moseleyi) were randomly chosen at the end of the chick-rearing period (Fig. 1). Blood was sampled from an alar vein, centrifuged to separate the plasma from the blood cells (hereafter blood) which were kept frozen at -20 °C.

Material and Methods

Sample collection

Before the analysis, blood samples were lyophilized with Hg concentrations being reported as dry weight (dw). The dates and localities of the sampling protocol, as well as the ecological characteristics of each seabird species at the various localities are specified in the SI section.

Carbon (δ 13 C) and nitrogen (δ 15 N) stable isotope ratios were determined in blood cells as detailed in previous work (Renedo et al., 2018b).

Reference materials, sample preparation, and analytical description

Reference samples. To validate the analytical results for Hg speciation, four certified reference materials were analyzed: human hair NIES-13 and IAEA-086; tuna fish ERM-CE-464 and dogfish liver DOLT-4 (Table S1). Hg isotopic results for blood were also validated with these four reference materials by intercomparison with previously reported values (Li et al., 2014;Yamakawa et al., 2016) and with reference values of Lake Michigan fish tissue NIST SRM 1947. Two internal reference samples were also prepared with the pooled samples collected from different king penguin individuals from Crozet Islands: RBC-KP (red blood cells) and F-KP (feathers) and were analyzed at each analytical session. Analytical uncertainty for delta values was calculated using SD typical errors for reference materials, as recommended by reference publications for standard reporting of Hg isotopic ratio uncertainties (Table S2).

Measurement of the Hg compound concentrations (GC-ICPMS).

For speciation analyses, Hg was extracted from blood (0.10-0.15 g) by alkaline microwave digestion with 5 mL of tetramethylammonium hydroxide (25% TMAH in H2O, Sigma Aldrich) [START_REF] Rodrigues | Mercury speciation in whole blood by gas chromatography coupled to ICP-MS with a fast microwave-assisted sample preparation procedure[END_REF][START_REF] Queipo Abad | Development of a Common Procedure for the Determination of Methylmercury, Ethylmercury, and Inorganic Mercury in Human Whole Blood, Hair, and Urine by Triple Spike Species-Specific Isotope Dilution Mass Spectrometry[END_REF]. The extraction method, analysis, and quantification of Hg species have been detailed previously (Renedo et al., 2018a). Total Hg concentrations were quantified by using an advanced Hg analyzer (AMA-254, Altec). Total Hg concentrations obtained by Hg speciation analyses (i.e., the sum of inorganic and organic Hg) were compared to total Hg concentrations obtained by AMA-254 for method validation. Recoveries of Hg and MeHg concentrations with respect to certified values for each reference material varied between 96 and 101% (see Table S1 for details).

Measurement of the total Hg isotopic composition by CVG-MC-ICPMS. For isotopic analyses, blood (0.05-0.10 g) was predigested overnight at room temperature and then digested the following day with 3 or 5 mL of HNO3 acid (65%, INSTRA quality). Samples were subsequently extracted in a Hotblock at 75 ºC for 8 h (6 h in HNO3 and >2 h after the addition of 1/3 of the total volume of H2O2 (30%, ULTREX quality)). Hg isotopic analyses were carried out as reported previously (Renedo et al., 2018a). Hg isotopic values were reported as delta notation, calculated relative to the bracketing standard NIST SRM-3133 reference material to allow inter-laboratory comparisons, as described in the SI section. NIST SRM-997 thallium standard solution was used for the instrumental mass-bias correction using the exponential law.

Secondary standard NIST RM-8160 (previously UM-Almadén standard) was used for validation of the analytical session (Table S2). Total Hg concentrations in the extract solution were compared to the concentrations found by AMA-254 analyses to assess method recovery.

The obtained average recovery was 100 ± 2% (n=110).

Statistical tests

Statistical analyses were performed using R 3.3.2 software (R Core Team, 2016). Prior to the analyses, the data were checked for normality of the distribution and homogeneity of variances using Shapiro-Wilk and Breusch-Pagan tests, respectively. Non-parametric tests (Kruskal-Wallis with the Conover-Iman test) were performed accordingly. We examined the correlations between MeHg concentrations, Hg MDF (δ 202 Hg) and MIF (∆ 199 Hg and ∆ 200 Hg) with latitude using linear regressions and Spearman correlation rank tests. Statistically significant results

were set at α= 0.05.

Results and discussion

Total Hg concentrations (THg) and Hg speciation trends

MeHg was the dominant Hg form in the blood of all the individuals (92 ± 7%, mean ± SD;

Table 1). This means that Hg isotopic composition of blood corresponded essentially to the MeHg isotopic values. Both the skua and penguin blood samples exhibited significantly different MeHg concentrations according to the sites (Kruskal-Wallis, H=31.09 and 43.05, respectively, both p < 0.0001). The skua blood MeHg concentrations increased from 0.51 to 3.78 µg•g -1 dw (n=40) from the Antarctic to Subtropical populations, respectively.

Concentrations of MeHg in penguin blood were also lower for Antarctic than for Subtropical species (0.43 to 1.95 µg•g -1 dw, respectively, n=51), increasing in the order Adélie < eastern rockhopper < macaroni < king < northern rockhopper penguins (Table 1). MeHg concentrations in seabird blood showed a significant correlation with latitude for both skuas (Adjusted r 2 =0.62, p<0.0001) and penguins (Adjusted r 2 =0.33, p<0.0001) (Fig. S1). Previous studies addressed the influence of the intrinsic and extrinsic ecological factors of these two seabird models (age, sex, moulting patterns, diet or feeding habitats) on the latitudinal variations of MeHg concentrations (Carravieri et al., 2016[START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF], as well as the Hg isotopic composition (Renedo et al., 2018a) of blood or feathers at the same study sites. The main factor explaining inter-species differences in Hg levels in a same ecosystem were feeding habits, rather than physiological or taxonomic differences [START_REF] Goutte | Demographic consequences of heavy metals and persistent organic pollutants in a vulnerable long-lived bird, the wandering albatross[END_REF](Carravieri et al., , 2016)). However, the influence of the dietary habits did not influence the latitudinal variations of MeHg blood levels, suggesting that the higher seabird MeHg concentrations in Subtropics than in Antarctica depend mainly on the geographical differences of Hg sources and dynamics (Renedo et al., 2018b) or incorporation into food webs (Carravieri et al., 2016).

Latitudinal trends of Hg stable isotopic composition

A wide range of mean blood δ 202 Hg values was observed between Antarctic and Subtropical populations for both skuas and penguins (0.23-1.56 ‰ and 0.53-2.16 ‰, respectively) (Table 1). The mean variation of ẟ 202 Hg values of blood between Antarctic and Subtropical sites was 1.33 ± 0.15 ‰ (-0.02 to 1.71 ‰) for skuas and 1.60 ± 0.25 ‰ (0.24-2.37 ‰) for penguins. We observed a significant relationship between latitude and δ 202 Hg values of blood for skuas and penguins (Adjusted r 2 =0.90 and 0.85, respectively, both p < 0.0001) (Fig. 2A). ∆ 199 Hg values varied slightly between the various sites in skuas (1.51-1.76 ‰) and penguins (1.54-1.89 ‰).

The mean variation of ∆ 199 Hg values was 0.25 ± 0.09 ‰ (1.31-1.85 ‰) for skuas and 0.36 ± 0.16 ‰ (1.38-2.04 ‰) for penguins. The ∆ 199 Hg values of blood were also significantly correlated with latitude in skuas (Adj. r 2 =0.55, p < 0.0001) and penguins (Adj. r 2 =0.18, p<0.0001) (Fig. 2B). Low differences were observed for the even-MIF signatures (denoted here as ∆ 200 Hg) between Antarctic (-0.02 ± 0.04 ‰) and Subtropical populations (0.04 ± 0.05 ‰).

The even-MIF values of Subantarctic seabirds (0.00 ± 0.04 ‰) were not significantly different from Antarctic seabirds, when skuas and penguins were considered together (H=13.22, p=0.001). Although the even-MIF latitudinal variations were low for the two groups of seabirds, they exhibited a significant linear trend with latitude in both skuas (Adj. r 2 =0.15, p=0.008) and penguins (Adj. r 2 =0.15, p=0.001) (Fig. 2C).

The strong relationship of Hg isotopic signatures with latitude (Fig. 2) could be explained by a combined influence of different Hg sources (with different Hg isotopic baselines) and processes associated with geographically changing conditions that would induce Hg isotopic fractionation across the study sites. In the following sections, we conceptually propose, estimate and discuss the contribution of these potential explanatory factors, from regional atmospheric sources (even Hg-MIF), through sea surface photochemistry (Hg odd-MIF) to biotic dark processes in the water column (additional Hg MDF).

Regional atmospheric sources potentially affect Hg isotopic baseline in seabirds from distant latitudes of the Southern Ocean

Hg even-MIF (Δ 200 Hg) is thought to be associated with mechanisms occurring in the upper atmosphere, and it is not affected by any biogeochemical processes, including photochemical processes in the euphotic zone, as observed so far (Gratz et al., 2010;Chen et al., 2012;Sherman et al., 2012). The Δ 200 Hg values detected in the blood of skuas and penguins exhibited minor variations between the distant latitudes and high variability at the population level (Fig. 2C).

We observed higher Δ 200 Hg values in Subtropical seabirds (skuas + penguins) from Amsterdam Island (0.04 ± 0.05‰), whereas slightly lower Δ 200 Hg values were obtained in Subantarctic (0.00 ± 0.04‰) and Antarctic seabirds (-0.02 ± 0.04‰). Our Δ 200 Hg values of seabirds are in the same range to the observed in Arctic marine predators of Alaska that also presented a decreasing trend of Δ 200 Hg values with latitude (from 0.10 to -0.01‰; 53.93 to 71.30°N, [START_REF] Masbou | Hg-Stable Isotope Variations in Marine Top Predators of the Western Arctic Ocean[END_REF]. Interestingly, precipitation samples worldwide generally exhibited an inverse latitudinal gradient, with higher Δ 200 Hg values at high latitudes relative to low latitude regions (Chen et al., 2012;Gratz et al., 2010;Sherman et al., 2012b), which is potentially associated with the shallower troposphere at higher latitudes [START_REF] Wang | Mass-dependent and mass-independent fractionation of mercury isotopes in precipitation from Guiyang, SW China[END_REF]. The inversed Δ 200 Hg trends between atmospheric samples and biological tissues with latitude highlights the complexity of Hg atmospheric deposition pathways and the necessity of further research exploring Hg isotopes in atmospheric samples in Southern Polar Regions to elucidate the mixed contribution of Hg atmospheric inputs. Although the slight variations of seabird Δ 200 Hg values do not provide conclusive evidence, our close-to-zero data is closer to the values observed atmospheric total gaseous Hg (-0.11 to -0.01‰, Demers et al., 2013;Sherman et al., 2010). This seems to indicate that the predominant Hg atmospheric source are originating from tropospheric gaseous elemental Hg, which would be oxidized to Hg 2+ and deposited as dry or wet deposition, and eventually re-emitted after reduction in surface environment. Recent models in the Arctic Ocean estimated limited uptake of Hg 0 as a result of ice cover and saturation of surface waters in dissolved Hg 0 [START_REF] Soerensen | Global Biogeochemical Cycles in the Arctic Ocean[END_REF], therefore analogous processes in sea-ice covered regions of Antarctica can be assumed. Though, the sequestration of atmospheric Hg 0 (and oxidized Hg 2+ ) in the sea ice compartment in Antarctic zones is thought to be responsible for an additional input of Hg to the ocean (Cossa et al., 2011;Gionfriddo et al., 2016). Moreover, additional processes could transport oxidized Hg 2+ from the Antarctic continent to Antarctic coasts by katabatic winds (Angot et al., 2016) (Renedo et al., 2018b).

Low variability of MeHg photodemethylation extent between distant latitudes of the

Southern Ocean

As a significantly positive Hg odd-MIF is thought to be mainly due to the photochemical processes prior to MeHg incorporation into food webs (Bergquist and Blum, 2007), we initially considered that the variability of ∆ 199 Hg values of seabirds between the three geographically distant areas (Antarctic, Subantarctic, and Subtropical) (Fig. 2B) could be primarily due to distinct conditions influencing photochemical reactivity in surface waters. Aquatic photochemical MeHg demethylation is known to induce an increase in odd-MIF (Δ 199 Hg and Δ 201 Hg) and in MDF values (δ 202 Hg) in the residual MeHg pool (Bergquist and Blum, 2007).

This process results in a Δ 199 Hg/Δ 201 Hg ratio of 1.36 ± 0.04, as reported experimentally (Bergquist and Blum, 2007). Meanwhile, experimental photochemical reduction of Hg(II) yielded a Δ 199 Hg/Δ 201 Hg ratio of 1.00 ± 0.01 (Bergquist and Blum, 2007). The ∆ 199 Hg/∆ 201 Hg slopes obtained for penguin blood (1.17 ± 0.06, intercept: -0.07 ± 0.08, SE) and skua blood (1.14 ± 0.07, intercept: 0.05 ± 0.11, SE) (Fig. S2) differed slightly from those obtained from previous photodemethylation laboratory experiments, but they are in good agreement with those previously obtained with marine fish (Senn et al., 2010;Blum et al., 2013) and seabird eggs (Point et al., 2011;[START_REF] Day | Mercury stable isotopes in seabird eggs reflect a gradient from terrestrial geogenic to oceanic mercury reservoirs[END_REF]. The overall ∆ 199 Hg/∆ 201 Hg slope for both skuas and penguins was 1.16 ± 0.05 (SE) with negligible intercept (0.01 ± 0.07). Our slopes were also similar to the ∆ 199 Hg/∆ 201 Hg ratios obtained in fish from King George Island (1.19 ± 0.17, n=8;[START_REF] Liu | Different circulation history of mercury in aquatic biota from King George Island of the Antarctic[END_REF] and faeces from Antarctic seals (1.16, n=2;Zheng et al., 2015), but slightly lower than ratios reported on Adélie penguin guano (~1.30, n=2; Zheng et al., 2015). The lower ∆ 199 Hg/∆ 201 Hg slopes typically observed in marine biota compared to laboratory photochemical experiments can be the consequence of differences in organic matter or the influence of dissolved cations and halogens present in seawater. Recently, other studies have focused on the influence of the type of solar radiation and different ligands in MeHg photodemethylation processes in aquatic systems (Chandan et al., 2015;[START_REF] Rose | Effects of ultraviolet radiation on mercury isotope fractionation during photo-reduction for inorganic and organic mercury species[END_REF]. [START_REF] Rose | Effects of ultraviolet radiation on mercury isotope fractionation during photo-reduction for inorganic and organic mercury species[END_REF] investigated the effect of solar radiation (different intensities and frequencies) on Hg MIF during MeHg aquatic photodemethylation and obtained a ratio similar to Bergquist and Blum (2007). Chandan et al., (2015) documented variable Δ 199 Hg/Δ 201 Hg ratios for MeHg photodemethylation under different types and concentrations of dissolved organic carbon (DOC) ligands with different content of reduced sulphur (S-red). Under low MeHg/S-red-DOC ratios Δ 199 Hg/Δ 201 Hg slopes were consistent and less variable (1.38±0.02); whereas high MeHg/S-red-DOC ratios presented lower slopes varying from 1.17±0.04 to 1.30±0.02 (Chandan et al., 2015).

Assuming that MeHg photodegradation is the dominant photochemical process before MeHg incorporation into food webs, we estimated the fraction of photodemethylated MeHg of each area based on three experimental models (Bergquist and Blum, 2007;Chandan et al., 2015).

Although the use of experimental models based on more realistic environmental conditions (low MeHg: Sred-DOC ratios) can be more representative of the processes occurring under natural conditions in the environment, we are conscious of the degree of extrapolation of these models to real environments. Therefore, the isotopic fractionation systems of these models were adjusted to our specific conditions of MeHg:Sred-DOC ratios and MeHg:DOC ratios by fitting equations for the three sites (Antarctic, Subantarctic and Subtropical zones) to maximize the accuracy and veracity of our estimations (Tables S5, S6 andS7). The difference in the extent of photodemethylated MeHg from Antarctic and Subantarctic to Subtropical zones was on the order of 2%, independently of the experimental model used. Taking the closer estimates for MeHg, DOC, and dissolved organic sulfur (DOS) concentrations in the study areas (Bergquist and Blum, 2007;Chandan et al., 2015), the extent of photodemethylated MeHg varied from ~ 9% in Antarctic to ~ 11% in Subtropical zones (Table S8). Despite the wide distance between the studied sites, the variation of the extent of MeHg photodemethylation was surprisingly low.

For instance, previous isotopic investigations in open ocean areas reported an extent of MeHg photodemethylation of ∼40-80% (Senn et al., 2010;Blum et al., 2013), although the high degree of stratification and low productivity of these oligotrophic opened areas compared to our studied sector of the Southern Ocean can lead to this significant difference. However, our estimated MeHg photodemethylation extents are similar to those calculated in eggs of seabirds of the Arctic Ocean (~8-16%, Point et al., 2011) and in ornithogenic sediment cores of the Antarctic coastal ecosystem (~13-18%; Zheng et al., 2015), using similar calculation models (Chandan et al., 2015). A similar variation of the degree of MeHg photodemethylation was also calculated across the Crozet penguin community between benthic (13%) and epipelagic (16%)

foragers (Renedo et al., 2018b) also estimated using similar calculation models (Bergquist and Blum, 2007;Chandan et al., 2015). Also, Blum et al., (2013) found that the fish Δ 199 Hg values of the MeHg in mesopelagic fish of the Pacific Ocean were about 1.5 -2.0 ‰., i.e. within the same range as Δ 199 Hg values for seabirds in our study.

Based on the previous observations of Hg isotopes of penguins from Crozet Islands (Renedo et al., 2018b) and on the variations observed of Hg odd-MIF as a function of the foraging depth of marine fish (Blum et al., 2013), the low degree and the minor variations of MeHg photodegradation in distant sites of the Southern Ocean strongly suggest that the major proportion of the MeHg that accumulated in the seabirds was minimally photodemethylated, thus primarily originating from dark environments. Moreover, maximum MeHg concentrations in the open ocean water column are commonly observed at areas with minimum oxygen levels [START_REF] Monperrus | Mercury methylation, demethylation and reduction rates in coastal and marine surface waters of the Mediterranean Sea[END_REF][START_REF] Kirk | Methylated Mercury Species in Marine Waters of the Canadian High and Sub Arctic[END_REF]Sunderland et al., 2009;[START_REF] Cossa | The origin of methylmercury in open Mediterranean waters[END_REF], including in the Southern Ocean (Cossa et al., 2011). These observations demonstrated active MeHg production and accumulation in organisms from such environments (e.g., [START_REF] Chouvelon | Enhanced bioaccumulation of mercury in deep-sea fauna from the Bay of Biscay (north-east Atlantic) in relation to trophic positions identified by analysis of carbon and nitrogen stable isotopes[END_REF]. Substantial deep net Hg methylation can be supported by a larger export of organic matter [START_REF] Sokolov | Chlorophyll blooms in the Antarctic Zone south of Australia and New Zealand in reference to the Antarctic Circumpolar Current fronts and sea ice forcing[END_REF][START_REF] Sullivan | Distributions of phytoplankton blooms in the Southern Ocean[END_REF], subsequent larger inorganic Hg substrate supply (Cossa et al., 2011) from the euphotic zone (< 60 m depth; [START_REF] Tripathy | Deep-Sea Research II Deep chlorophyll maximum and primary productivity in Indian Ocean sector of the Southern Ocean : Case study in the Subtropical and Polar Front during austral summer 2011[END_REF] to mesopelagic waters, and MeHg preservation from photodegradation [START_REF] Monperrus | Mercury methylation, demethylation and reduction rates in coastal and marine surface waters of the Mediterranean Sea[END_REF][START_REF] Heimbürger | Shallow methylmercury production in the marginal sea ice zone of the central Arctic Ocean[END_REF]. Therefore, the existence of substantial net methylation occurring at depth suggests that the MeHg accumulated in seabirds from the Southern Ocean was predominantly of mesopelagic origin. Further, the lower Δ 199 Hg/Δ 201 Hg slopes of seabirds compared to previous studies (i.e. Blum et al., 2013) also suggest potential export of surface Hg 2+ to mesopelagic environments where it is methylated. Due to the high intensity of winter cooling and the seasonal mixed layer depths oscillations, the vertical transport of MeHg and Hg 2+ between shallow and deep-water masses could be a preponderant factor explaining the low extent of photochemical processes over these oceanic regions.

Major variations of the Hg isotopic composition between distant latitudes indicate distinct regional biogenic transformation and bioaccumulation extent.

Trophic transfer and accumulation. The strong correlation between the Δ 199 Hg and the δ 202 Hg values of both skuas and penguins (Adj. r 2 =0.76 and 0.61, respectively, both p< 0.0001; Fig. S3) could be indicative of different sources of Hg with distinct isotopic signatures (MDF and MIF) and/or different processes before Hg incorporation or during uptake and bioaccumulation in the food web that produce both Hg MDF and MIF across the different sites. By calculation of the corresponding latitudinal differences of δ 202 Hg obtained experimentally for photochemical demethylation (Chandan et al., 2015), we estimated that approximately 0.3 ‰ of the total δ 202 Hg variation may be induced by photochemical MeHg breakdown (Tables S9 andS10). This means that the remaining 1.0-1.3 ‰ of δ 202 Hg differences between latitudes may be the consequence of various Hg sources and/or biogeochemical processes inducing a reservoir of isotopically heavier Hg in the Subtropical region (Fig. 3).

The Antarctic ecosystem is characterized by a less complex food web in which top predators feed mainly on a limited number of key available species, such as the Antarctic krill Euphausia superba (Cherel, 2008;Brasso et al., 2014). By contrast, Subantarctic and Subtropical ecosystems have a larger diversity of prey species including four species of Euphausiids (Cherel et al., 2007;[START_REF] Bost | Where do penguins go during the inter-breeding period? Using geolocation to track the winter dispersion of the bioindicators of mercury contamination in the southern Indian Ocean: geographical and temporal trends[END_REF], constituting more complex food webs. Therefore, the difference in food web complexity between the studied sites could explain the increasing MeHg levels from Antarctic to Subtropical ecosystems [START_REF] Lavoie | Biomagnification of Mercury in Aquatic Food Webs: A Worldwide Meta-Analysis[END_REF]. However, such difference in the marine trophic transfer of MeHg was not yet found to induce any significant variations of ẟ 202 Hg. Trophic processes do not appear to explain the total MDF variation, because both seabird models with contrasting trophic ecologies exhibited the same MDF variations between the different latitudes and similar associated slopes. Indeed, although higher blood Hg concentrations were obtained in skua chicks relative to adult penguins at each locality, skuas exhibited lower δ 202 Hg values despite their higher trophic level [START_REF] Goutte | Demographic consequences of heavy metals and persistent organic pollutants in a vulnerable long-lived bird, the wandering albatross[END_REF] chicks, and which also matched with the penguins' MDF-latitude slope (Fig. S4). This observation suggested that the difference in δ 202 Hg values between the two models may be due to a specific metabolic response related to age and/or species, while the latitudinal variation remains mostly independent of such internal biotic pathways. This conclusion agrees with those of previous studies in marine fish [START_REF] Kwon | Absence of fractionation of mercury isotopes during trophic transfer of methylmercury to freshwater fish in captivity[END_REF]Blum et al., 2013) in which trophic effects were found to be independent of Hg isotopic trends and did not significantly affect Hg MDF.

Variations in δ 202 Hg values between seabird species of the same ecosystem can be dependent on the Hg sources associated with different integration times between tissues (Renedo et al., 2018a) or specific foraging ecologies (Renedo et al., 2018b). However, the consistent variations of seabird MDF signatures between the different latitudes suggests that a process driven by kinetic isotope fractionation operating at large/regional scales could be the main driver of Hg isotopic geographical variations. In light of this, we have proposed and tested several potential major biogeochemical processes that could drive the observed variations of Hg MDF in seabirds from the four sites (Fig. 4).

Biotic reduction and volatilization. First, we postulated that the higher surface temperature of Subtropical seawaters compared to Antarctic waters could result in a greater degree of biotic reduction and volatilization of inorganic Hg 0 from the aquatic compartment to the atmosphere, thereby leading to a residual pool of isotopically heavier Hg(II) in the aqueous phase. To test this hypothesis, previous experimental results were used to estimate the variation in the extent of Hg volatilization and Hg biotic reduction from Antarctic to Subtropical waters. By considering the specific conditions of water temperature recorded on the approximate latitudinal sites (Cossa et al., 2011;[START_REF] Canario | Mercury and methylmercury in the Atlantic sector of the Southern Ocean[END_REF]) and calculation of Henry's law constant reported by experimental studies in seawater (Andersson et al., 2008), we estimated that volatilization can only contribute to 0.03 ‰ of the MDF variation (Table S11). Thus, a different degree of volatilization itself is not enough to explain the total Hg MDF variations across the investigated latitudinal gradient. Based on experimental models for Hg dark bacterial reduction (Kritee et al., 2007(Kritee et al., , 2008)), estimations showed that the extent of biological reduction in Subtropical waters should be on the order of 1.5 to 3 times higher than in Antarctic waters during the summer period to explain the observed MDF variations between regions (Table S12).

However, such a high degree of variation in the dark biological reduction rate in the studied oceanic regions should be taken with caution since it cannot be demonstrated by any robust dataset in these regions of the Southern Ocean. Since most of the MeHg that bioaccumulates in seabird tissues seems to originate from the mesopelagic zone (see above), Hg(II) dark biological reduction cannot be discarded, while the environmental conditions are also supposed to be favorable to the formation of MeHg [START_REF] Sullivan | Distributions of phytoplankton blooms in the Southern Ocean[END_REF]Cossa et al., 2011). Moreover, we cannot rule out that ẟ 202 Hg of MeHg would follow a similar trend after various methylation and demethylation steps.

Biotic net Hg methylation and uptake. As a second hypothesis, we postulated that higher MeHg concentrations in Subtropical seabirds could possibly be the result of greater net biotic methylation taking place in the mesopelagic zone. We refer here as "net" methylation extent to the combination of simultaneous methylation and demethylation processes. An increase in the methylation/demethylation ratio from Antarctic to Subtropical zones could also be in agreement with the isotopically heavier residual pool of MeHg + (i.e., assuming a steady state) in Subtropical zones. Based on experimental measurements of Hg isotopic fractionation during net MeHg methylation under abiotic (Jiménez-Moreno et al., 2013) and biotic (Perrot et al., 2015) conditions, the net degree of methylation should be on the order of 1.5 to 2.5 times higher in Subtropical waters compared to Antarctic waters (Table S13). Although estimates are based Due to the complex processes of MeHg production and bioaccumulation, the correlation between abiotic MeHg concentrations in seawater and MeHg levels in biota is rarely found in marine ecosystems. The existence of clearly distinct bioregions in the Southern Ocean in terms of vertical profiles of phytoplanktonic biomass and the seasonality of bloom timing is closely related to seasonal fluctuations in vertical oceanic dynamics and light irradiance availability [START_REF] Ardyna | Delineating environmental control of phytoplankton biomass and phenology in the Southern Ocean 5016-5024[END_REF]. These factors would clearly affect MeHg production and transport in the water column. Recent Hg isotopic investigations in the North Pacific Subtropical Gyre highlighted that the bioaccumulation of MeHg is strongly linked to the vertical mobilization of Hg with marine sinking particles and by vertical migration of zooplankton [START_REF] Motta | Mercury Cycling in the North Pacific Subtropical Gyre as Revealed by Mercury Stable Isotope Ratios[END_REF].

In the Southern Ocean, an increasing delay in phytoplankton blooms occurs from Subtropical (October) to Subantarctic latitudes (November/December) to Antarctic latitudes (January/February) [START_REF] Ardyna | Delineating environmental control of phytoplankton biomass and phenology in the Southern Ocean 5016-5024[END_REF]. Since the bloom periods at each site occurred before or during our sample collection periods during the Austral summer of 2011-2012 (Table S14),

the MeHg integration time in seabird blood corresponded to the stage of maximal primary productivity at each sampling site. The seasonal release of nutrients and algal blooms during austral summer [START_REF] Sullivan | Distributions of phytoplankton blooms in the Southern Ocean[END_REF][START_REF] Sokolov | On the relationship between fronts of the Antarctic Circumpolar Current and surface chlorophyll concentrations in the Southern Ocean[END_REF], enhanced by sea-ice melting in Antarctic coastal zones [START_REF] Sokolov | On the relationship between fronts of the Antarctic Circumpolar Current and surface chlorophyll concentrations in the Southern Ocean[END_REF][START_REF] Riaux-Gobin | Environmental conditions, particle flux and sympagic microalgal succession in spring before the sea-ice break-up in Adélie Land, East Antarctica[END_REF], induce a higher productivity in Antarctic and Polar Front zones. This biomass dilution of Hg could then contribute to lower Hg levels accumulated in Antarctic final predators.

Latitudinal and regional differences in the seasonal dynamics and the oceanic vertical exchange of water masses have been observed in the upwelling branch of the Southern Ocean [START_REF] Marshall | Closure of the meridional overturning circulation through Southern Ocean upwelling[END_REF] . The seasonal variability of the mixed layer depth is substantial in all the sectors of the Southern Ocean [START_REF] Sallée | Zonally asymmetric response of the Southern Ocean mixed-layer depth to the Southern[END_REF]. During summertime, the mixed layer depth in the vicinity of the Antarctic Circumpolar Current (ACC) reaches about 100 m [START_REF] Sallée | Zonally asymmetric response of the Southern Ocean mixed-layer depth to the Southern[END_REF]. The water column is destabilized during winter cooling and the mixed layer deepens, finding its maxima at the north of the Antarctic Circumpolar Current, where the amplitude of the seasonal cycle can exceed 400 m, particularly in the Indian sector [START_REF] Sallée | Zonally asymmetric response of the Southern Ocean mixed-layer depth to the Southern[END_REF]. We therefore suggest, as illustrated in Fig. 4, that these regional dynamics could be potential key factors influencing the efficiency of the vertical transport of MeHg between deeper mesopelagic waters and surface waters within the euphotic zone (Cossa et al., 2011;[START_REF] Sallée | Zonally asymmetric response of the Southern Ocean mixed-layer depth to the Southern[END_REF].

Deeper

Conclusion

The deductions listed above lead to the conclusion that the variability of Hg isotopic signatures among Antarctic to Subtropical seabirds are strongly influenced by both the specific oceanic

MIF signatures are expressed using capital delta notation, as suggested elsewhere (Bergquist and Blum, 2007), according to the following equations: (Bergquist and Blum, 2007).

S43

Table S3. Total and MeHg concentrations (µg g -1 ), Hg isotopic composition (‰) and carbon (δ 13 C, ‰) and nitrogen (δ 15 N, ‰) isotopes for all the skua individuals from the four studied populations from the Southern Ocean. The variations in the surface ocean MeHg photodemethylation can be estimated from the odd-MIF values recorded in seabird blood based on a Rayleigh model:

(1) ln 1000+ ∆ 1000+ ∆ 𝑖 = ε(∆ 199 𝐻𝑔) 1000 × ln(𝑓)
where Δ 199 Hgi corresponds to the initial odd-MIF of the marine MeHg before undergoing photodemethylation, which was assumed to be close to zero based on the negligible total Hg Δ 199 Hg values previously measured in seawater (Štrok et al., 2015). MeHg is also assumed to have a similar odd-MIF than the total Hg before photodemethylation because it is likely converted from inorganic Hg (Hg(II)) in the photic zone of the water column.

The ε(Δ 199 Hg) is the enrichment factor, reported as ε = 1000*(α∆199Hg -1) as a function of the kinetic fractionation factor (α∆199H) determined in laboratory experiments. f is the remaining fraction of non-photodemethylated MeHg.

S21

The experimental estimations of the enrichment factors of MeHg aquatic photodemethylation were first calculated as a function of the MeHg/dissolved organic carbon (DOC) ratio by Bergquist and Blum, (2007). The relation between the odd-MIF values and the fraction of the remaining MeHg was used in fish from the Lake Michigan to estimate the MeHg photodegradation extent. This reference fractionation model was later applied for the estimation of the MeHg loss due to photodemethylation in marine environments [START_REF] Gehrke | Sources of mercury to San Francisco Bay surface sediment as revealed by mercury stable isotopes[END_REF]Point et al., 2011;Senn et al., 2010). Point et al. (2011) extrapolated the fractionation model to the presence of DOC in Arctic marine natural waters (lower DOC content) (Point et al., 2011). In a recent study, Chandan et al. (2015) investigated the Hg isotopic fractionation factors considering changing DOC binding sites and concluded that the odd-MIF extent is strongly dependent on the amount of reduced sulfur content in organic matter (Sred-DOC). The enrichment factors were evaluated under different types and concentrations of organic matter standards: Suwanee River fulvic acid (SRFA), Pony Lake fulvic acid (PL FAR) and Nordic Lake natural organic matter (NL NOM). These two reference organic matter models present contrasted proportions of reduced sulfur organic matter (35% for SRFA, 59% for PL FAR and 50% for NL NOM).

Furthermore, these models represent more realistic environmental conditions (low MeHg:

Sred-DOC ratios) than previous experimental studies and can be more representative of the processes occurring under natural conditions in the environment.

In order to estimate the extent of photochemical demethylation of MeHg over the studied sites of the Southern Ocean, we calculated the corresponding enrichment factors by S21 application of experimental models in our own environmental conditions of MeHg:DOC and MeHg: S red-DOC. The assessment was based on the three mentioned experimental studies: in mid-range MeHg: S-red-DOM ratio (SRFA) and low MeHg: S-red-DOM ratio (NL NOM) conditions (Chandan et al., 2015) and in function of MeHg:DOC ratios under high DOC conditions (Bergquist and Blum, 2007). The MeHg and DOC concentrations at each site were extracted from published data ( S56 Table S5, Table S6 and Table S7). As previously explained, the concentrations of DOC in surface waters were not considered because photochemical reactions are known to photodegrade the organic matter. Moreover, MeHg is mainly produced at the bottom or below the photic zone, where plankton material is undergoing bacterial degradation and mineralization [START_REF] Mason | Mercury biogeochemical cycling in the ocean and policy implications[END_REF]. We therefore extrapolated the isotopic fractionation systems of these three experimental models to our conditions of MeHg: S-red-DOC ratios and MeHg:DOC ratios by fitting equations for the three sites (Antarctic, subantarctic and subtropical zones). We obtained that the difference on the extent of photodemethylated S). No substantial changes in the latitudinal variations were observed in the calculated results when changing the mentioned parameters for all the empirical models used here. Previously calculated degrees of photodemethylation in Antarctic coastal ecosystems by the same experimental approximation were similar to our findings (Zheng et al., 2015). Also, Blum et al., (2013) found that the Δ 199 Hg values of the MeHg at mesopelagic depth in the Pacific Ocean were about 1.5 -2.0‰. These values are within the same range as our Δ 199 Hg values, strongly suggesting that, since deep mixing in subtropical zones in the Southern Ocean occurs at > S57 400m depth, the MeHg accumulated in seabirds of the Southern oceanic Regions has a mesopelagic origin.

S58

Table S5. Calculation of the MeHg:Sred-DOC ratios for the estimation of MeHg photodemethylation based on experimental fractionation factors (Chandan et al., 2015) for midrange MeHg:Sred-DOC, SRFA organic matter conditions, 35% S-red).

Reference data for this study (1) Other publishe d data (2) Reference data (3) Reference data (4) Zone Depth MeHg (pmol L - Cossa et al. 2011 (2) AZ: Nerentorp Mastromonaco et al. 2017; SAZ: Canario et al. 2017; STZ: Bratkic et al. 2016 (3) Tremblay et al. 2015; Canario et al. 2017; Ogawa et al., 1999 (4) [START_REF] Ksionzek | Dissolved organic sulfur in the ocean: Biogeochemistry of a petagram inventory[END_REF]

S59

Table S6. Calculation of the MeHg:Sred-DOC ratios for the estimation of MeHg photodemethylation based on experimental fractionation factors (Chandan et al., 2015) for low-range MeHg:Sred-DOC, NL NOM organic matter conditions, 50% S-red).

Reference data for this study (1) Other published data (2) Reference data (3) Reference data (4) Zone Depth Cossa et al. 2011 (2) AZ: Nerentorp Mastromonaco et al. 2017; SAZ: Canario et al. 2017; STZ: Bratkic et al. 2016 (3) Tremblay et al. 2015; Canario et al. 2017; Ogawa et al., 1999 (4) [START_REF] Ksionzek | Dissolved organic sulfur in the ocean: Biogeochemistry of a petagram inventory[END_REF]

S60

Table S7. Calculation of the MeHg: DOC ratios for the estimation of the MeHg photodemethylation based on experimental fractionation factors (Bergquist and Blum, 2007) for high MeHg:DOC conditions.

Reference data for this study (1) Other published data (2) Reference data

(3) Cossa et al. 2011 (2) AZ: Nerentorp Mastromonaco et al. 2017; SAZ: Canario et al. 2017; STZ: Bratkic et al. 2016 (3) [START_REF] Tremblay | Origin and fate of particulate and dissolved organic matter in a naturally iron-fertilized region of the Southern Ocean[END_REF][START_REF] Canario | Mercury and methylmercury in the Atlantic sector of the Southern Ocean[END_REF][START_REF] Ogawa | Vertical distributions of dissolved organic carbon and nitrogen in the Southern Ocean[END_REF]

S61

Table S8. Estimation of the MeHg photodemethylation extent based on experimental fractionation factors (Bergquist and Blum, 2007)

S62

Estimation of the MDF enrichment factor associated to MeHg photodemethylation

In order to estimate the enrichment of MDF values associated to the calculated photodemethylation extent at each site, we performed a recalculation of the fractionation factor of δ 202 Hg values (α (δ 202 Hg)) for our environmental conditions. We based this calculation on the enrichment factors attributed to mid-range MeHg;S red-DOC ( S63 and the volatilization rates [START_REF] Zheng | Mercury isotope fractionation during volatilization of Hg(0) from solution into the gas phase[END_REF]. According to this volatilization experiment, we calculated the α( 198 Hg/ 202 Hg) from the slope when plotting log(1000-δf/1000-δi) vs log(fR) following this equation:

(4)

where δ is the isotopic composition of the remaining reactant at time t, δi is the initial isotopic composition of the reactant, fR is the fraction of the remaining reactant at time t, and α is the kinetic fractionation factor.

Based on experimental calculations, we determined the Rayleigh-type fractionation slope for our model, assuming that initial δ 202 Hg (δi) is 0 and taking α( 198 Hg/ 202 Hg) of 1.00047 [START_REF] Zheng | Mercury isotope fractionation during volatilization of Hg(0) from solution into the gas phase[END_REF] (Table S). The obtained slope represents a α( 198 Hg/ 202 Hg) factor of 1.0005, meaning a total mass-dependent fractionation of 0.03 ‰ due to volatilization (i.e. kinetic fractionation between seawater and air).

log 1000 -δ 1000 -δi = 1 α -1 × log (f R ) 1 S68

S69

Estimation of the "biogenic" MDF enrichment associated to the extent of microbial transformation processes (reduction and net methylation) at the different sites

In order to explain the Hg MDF enrichment observed in the studied latitudinal gradient, we suggested the existence of potential differences in the extent of biological processes (only inducing MDF) between sites. For the estimation of these potential differences, we related the difference of MDF fractionation extent between Antarctic and subtropical zones, here ∆(δ 202 Hg), to the ratio of the remaining reactant Hg fraction (fR) between both sites by applying the following equation:

(5)

The remaining fraction (fR) calculated at the respective sites corresponds to:

f R = 1 - (Hg f ) (Hg i ) ∆(δ 202
=( 1 α -1)×log(f R ) STZ -( 1 α -1)×log(f R ) AZ ∆(δ 202 Hg)×α 1000 × (1 -α) = log( (f R ) STZ (f R ) AZ

S70

Considering similar conditions of Hg bioavailability between both sites (Hgi,AZ ~ Hgi,STZ), we directly related the remaining reactant Hg fraction to the concentration of the produced Hg fraction (Hgf) between sites: et al., 2007, 2008). In these previous studies, Hg isotopic fractionation was first measured during Hg reduction by Hgresistant bacteria expressing the mercuric reductase (merA) enzyme. This process induces Hg MDF leaving the remaining inorganic fraction enriched in heavy isotopes and defining a Rayleigh system with an associated kinetic fractionation factor α( 198 Hg/ 202 Hg) ranging between 1.0013 and 1.0020 (meaning a δ 202 Hg enrichment of Hg(0) between -1.3‰ and -2.0‰) (Kritee et al., 2007). Similar results were obtained during biological reduction by two Hg-resistant strains (-1.6‰) and the MDF fractionation obtained by Hg-sensitive strain without the enzyme merA (-0.4‰) (Kritee et al., 2008). Considering these kinetic fractionation factors α( 198 Hg/ 202 Hg), we estimated that, to explain a total latitudinal MDF enrichment between 1.0 and 1.5‰, the extent of biological reduction in subtropical waters S71 should be around 1.65 to 3.18 times higher in subtropical waters than in Antarctic waters for Hg-resistant bacteria and until 40 times higher in the case of un-resistant bacteria ( S72 Table S). Considering that the natural bacteria are not adapted to high Hg concentrations, the reduction by Hg-sensitive bacteria without merA enzyme may be more representative of marine ecosystems. However, these potential isotopic fractionation pathways directly affect the Hg(II) isotopic baseline mainly in the euphotic zone, while MeHg isotopic baseline will be more directly affected by methylation and demethylation pathways in both the euphotic and the mesopelagic zones. Consequently, such estimations obtained for Hg(II) reduction/volatilization mechanisms do not preclude for any solid conclusion regarding the latitudinal MDF variations of MeHg. Most importantly, the impact on MDF of Hg of biogenic processes leading to the net methylation/demethylation of Hg must be explored and evaluated.

(6) log( (f R ) STZ (f R ) AZ ~ ( Hg
Estimation of the MDF enrichment associated to the extent of MeHg microbial net methylation at different latitudes. We wanted to estimate the difference of net "apparent" Hg methylation associated to the observed MDF enrichment between latitudes. We refer to the term "apparent" methylation because methylation and demethylation occur simultaneously so that the product of the reaction (MeHg) would be converted back to the reactant (Hg(II)). During microbial demethylation, the lighter Hg isotopes of the MeHg molecules are preferentially transformed and have been found to influence the Hg isotopic composition when significant amounts of MeHg are accumulated [START_REF] Pedrero | Transformation, localization, and biomolecular binding of Hg species at subcellular level in methylating and nonmethylating sulfate-reducing bacteria[END_REF].

We based our calculations on two experimental model by sulphate reducing bacteria (SRB) under sulphate respiration conditions (Perrot et al., 2015) and abiotic methylation/demethylation by methylcobalamin (MeCo) (Jiménez-Moreno et al., 2013).

S73

The associated kinetic fractionation factor α( 198 Hg/ 202 Hg) were, respectively, 1.0025 and 1.0016. During these experiments, a steady-state between the Hg(II) and MeHg isotopic composition was observed after 24 h of experiment. It was demonstrated that the occurrence of significant simultaneous demethylation would lead to uncertainty in the modelled fractionation factor since lighter Hg isotopes of MeHg would be preferentially demethylated. These experiments were conducted in closed system allowing reversible reaction to occur (methylation/demethylation). Under these conditions two opposite Rayleigh distillation system are in competition, and probably represent a better approximation of such antagonistic and simultaneous mechanisms involved in specific methylating niches of the marine water column (oxygen minimum, pycnocline or maximum planktonic biomass) (Sunderland et al., 2009;Cossa et al., 2011). This assumption implies that MeHg is biogenically produced in confined media or at very specific location in the pelagic zone to avoid any effect from turbulent diffusion or vertical advection.

The difference of MDF fractionation between the Antarctic and the subtropical zones was related to the ratio of produced MeHg (Hgf) fraction between sites with equation (6). For the explanation of a total MDF enrichment between 1.0 and 1.5‰ between sites, we obtained that the net methylation extent in subtropical waters might be around 1.5 to 2.5 times higher than in Antarctic waters (Table S). The obtained variability for MeHg net formation between Antarctic and subtropical marine waters seems quite reasonable. The two different and productive pelagic systems have a substantial temperature difference (0 S74 ºC to 18 ºC in the photic zone from Antarctic to subtropical waters) that can dramatically control bacterial activities towards a higher net production of MeHg in subtropical waters.

This also provides an additional explanation for the higher bioaccumulation of MeHg in seabirds moving northward.

S75

S79 Section 3. Additional information on ecological characteristics of seabird species

The diet of skua chicks is usually composed of other birds and marine mammals scavenge or seabird eggs, and also of fish when feeding at sea. Depending on the location, skuas present different feeding ecologies. South polar skuas from Adélie Land feed their chick with eggs and carcasses of Adélie penguins Pygoscelis adeliae [START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF].

In the Kerguelen Islands, skua diet is particularly composed of blue petrels Halobaena caerulea and thin-billed prions, Pachyptila belcheri [START_REF] Mougeot | Predation on burrowing petrels by the brown skua (Catharacta skua lo È nnbergi) at Mayes Island, Kerguelen[END_REF]. Crozet skuas rely mainly on eggs and carcasses of crested penguins (Eudyptes chrysolophus and E.

chrysocome filholi), but also on black rats Rattus rattus that were introduced by humans.

In Amsterdam Island, skua diet is not completely recognized but, according to field observations, chicks are fed with other seabird eggs and carcasses and with Antarctic fur seals Arctocephalus tropicalis scavenge, but also with the introduced subantarctic rats Rattus norvegicus [START_REF] Carravieri | From Antarctica to the subtropics : Contrasted geographical concentrations of selenium , mercury , and persistent organic pollutants in skua chicks ( Catharacta spp .)[END_REF].

We studied penguin adult individuals from five species: king penguin Aptenodytes patagonicus, Adélie Pygoscelis adeliae, macaroni Eudyptes chrysolophus, eastern rockhopper E. chrysocome filholi and northern rockhopper E. chrysocome moseleyi penguins. King penguins mainly feed on pelagic fish, especially myctophids such as Krefftichthys anderssoni [START_REF] Bost | Feeding of diving predators and diel vertical migration of prey: King penguins' diet versus trawl sampling at Kerguelen Islands[END_REF][START_REF] Cherel | Isotopic niches and trophic levels of myctophid fishes and their predators in the Southern Ocean[END_REF]. Adélie penguins also consume fish but their diet is mostly composed of krill (especially, Euphausia superba and E. crystallorophias) (Rodary et al., 2000b). Macaroni penguins primarily feed on crustaceans, such as hyperiids (e.g. Themisto gaudichaudii, and Primno macropa) and euphausiids (e.g. E. vallentini, Thysanoessa spp.), and on fish such as the myctophid Krefftichthys anderssoni [START_REF] Cherel | Isotopic niches and trophic levels of myctophid fishes and their predators in the Southern Ocean[END_REF]Cherel and Hobson, 2007;[START_REF] Thiebot | Adjustment of pre-moult foraging strategies in Macaroni Penguins Eudyptes chrysolophus according to locality, sex and breeding status[END_REF]. Eastern rockhopper penguins from Crozet Islands are known to rely upon the S80 Antarctic krill E. vallentini, while northern rockhopper penguins from Amsterdam Island mainly feed on the euphasiid Thysanoessa gregaria and squid [START_REF] Tremblay | Geographic variation in the foraging behaviour, diet and chick growth of rockhopper penguins[END_REF]. Chicks of emperor penguins (Aptenodytes forsteri) are winter breeders and were studied in order to evaluate the seasonal variations (summer vs winter) in the Antarctic continent. In winter, emperor penguins mainly feed over the Antarctic continental shelf and they present excellent diving capacities. They forage mainly on fish (and squids) of benthic areas between 200 and 400 m depth [START_REF] Wienecke | Extreme dives by free-ranging emperor penguins[END_REF]. Due to their seasonal mismatch relative to the other studied seabirds, they were not considered for the exploration of Hg isotopes at different latitudes.

in winter as a result of lower solar radiation and a potentially higher influence of sea ice cover, as already observed in previous studies in the Arctic [START_REF] Masbou | Hg stable isotope time trend in ringed seals registers decreasing sea ice cover in the Alaskan Arctic[END_REF]Point et al., 2011). The sea ice coverage during sample collection in spring (November 2011) and summer (February 2012) was 10.8 x 10 6 km 2 and 2.2 x 10 6 km 2 , respectively (National Snow and Ice Data Center (NSIDC)).

Because Hg odd-MIF varies as a function of the extent of light penetration at different depths of the water column, another potential contributor factor that could enhance the Δ 199 Hg variations between Antarctic seabird populations is the different foraging habitat.

Indeed, emperor penguins dive deep (until 400 m depth, as observed from satellite and dive tracking (Rodary et al., 2000a;[START_REF] Wienecke | Extreme dives by free-ranging emperor penguins[END_REF] and they forage in more neritic waters (as concluded from ẟ 13 C signatures, Cherel, 2008). Previously observed Δ 199 Hg differences between penguins with contrasted foraging depths and coastal vs open ocean feeders within a same community (Crozet Islands) accounted for less than 0.4‰ between epipelagic and benthic foragers (Renedo et al., 2018b). Based on this approach, the greater difference in Δ 199 Hg values between Antarctic summer and winter breeders could be partly attributed to the difference in foraging depths between species. However, other factors that could explain the observed Hg odd-MIF trend are probably seasonal climatic differences such as the solar radiation and the sea ice coverage.

  on closed system experiments, it is assumed to be equivalent to the processes occurring in diffusion-limited microenvironments within an open system such as the open ocean. The theoretical magnitude of MDF enrichment during net methylation could thus largely explain the observed MDF latitudinal variation across the studied areas. Indeed, potentially increasing net methylation rates from Antarctic to Subtropical zones are very much in line with both the Hg isotopic latitudinal trends and the higher MeHg levels found in Subtropical seabirds compared to those from Antarctica. Latitudinal variations of MeHg concentrations and Hg isotopic signatures of seabird blood are likely the result of spatial differences in the MeHg production and degradation rates, especially in the darker mesopelagic zone, as suggested by the degree of Hg odd-MIF.

  mixed layer depths in the north of the Antarctic Circumpolar Current compared to Antarctic waters indicate weaker stratification and deeper vertical mixing at northern Subtropical waters. A shallower winter vertical mixing at Antarctic and Subantarctic waters near the Polar Front could inhibit the downward transport of Hg to deeper pelagic zones, where net methylation should take place. This would also restrain the upward transfer of nutrients and newly formed MeHg at depth and reduce its uptake by phytoplankton and accumulation along the food web. By contrast, a deeper winter mixed layer depth and higher vertical advection to the surface in Subtropical waters should provide efficient downward transport of Hg and subsequent upward transfer of nutrients and MeHg to the productive euphotic zone. As a result, a complex interplay between MeHg formation at depth and winter mixed layer dynamics may contribute to more efficient vertical MeHg upload in Subtropical waters compared to Subantarctic and Antarctic waters. The higher MeHg exposure observed in Subtropical seabirds may, therefore, be the consequence of both greater microbial formation of MeHg and its vertical transport towards the plankton biomass in Subtropical productive zones.

  dynamics and biological productivity turnover from the three contrasted bioregions of the Southern Ocean. Slight variability of Hg odd-MIF isotopic signatures (Δ 199 Hg) between Antarctic and Subtropical seabirds strongly suggests that the MeHg accumulated in trophic webs from the Southern Ocean has a dominant mesopelagic origin. Significant variability of MDF Hg isotopic signatures (δ 202 Hg) and its correlation to MeHg concentrations in seabirds from the three studied latitudes demonstrates how regional Southern Ocean dynamics and productivity control marine MeHg biogeochemistry and the exposure of seabirds to Hg contamination. Indeed, the investigation of δ 202 Hg latitudinal variability help elucidate the observed increasing MeHg exposure of seabirds from Antarctic to Subtropical waters by an increasing effect of specific biogenic Hg pathways from Antarctic to Subtropical waters, such as Hg biological transformations and accumulation. This study is the first large scale report of Hg isotopic composition in marine organisms from the Southern Ocean and highlights the potential of seabirds to cover for the first time these wide geographic ranges to document Hg isotopic variations at the ocean scale. However, complementary Hg isotopic studies in these isolated regions are essential to deeply understand the processes driving Hg isotope variations in these ecosystems. macaroni penguin. Biol. Lett.

Figure S1 .Figure S2 .

 S1S2 Figure S1. Mean MeHg concentrations (dry weight, µg g -1 ) versus foraging latitude for blood samples of skua chicks and penguin adults from the Southern Ocean. Regression equations for skua MeHg concentration blood-latitude (y= -0.10x+7.22, Adj. R 2 =0.62, p<0.0001) and for penguin MeHg blood-latitude (y= -0.05x+3.71, Adj. R 2 =0.33, p<0.0001).

Figure S3 .Figure S4 .

 S3S4 Figure S3. Hg MDF and odd-MIF signatures for blood of skua chicks (left side) and of penguins (right side) from the Southern Ocean. A) ẟ 202 Hg versus ẟ 200 Hg, B) ẟ 202 Hg versus ẟ 199 Hg. Blue (Adélie Land), green (Crozet and Kerguelen) and red (Amsterdam). The dotted lines represent the theoretically predicted MDF based on ẟ 202 Hg.

  photodemthylated in Antarctic waters whereas ~ 6% in subtropical waters. The

S83

  Figure S5. Odd-MIF differences between Antarctic winter and summer breeders. Hg isotopic composition (δ 202 Hg, Δ 199 Hg) of Antarctic seabirds, which are representative of both the summer period (AP: Adélie penguins, AS: Antarctic skua) and the winter period (EP: emperor penguins) of Adélie Land.

  . Since the two different seabird species have contrasted foraging ecology, different MDF values would be expected due to distinct foraging habitats, trophic levels, and consequently different level of exposure to MeHg, Different extent of metabolic processes due to both age status and speciesspecific characteristics can also lead to significant MDF variations among seabirds. The lower MDF values in seabird chicks could be therefore potentially explained if metabolic processes are less efficient due to their age. This would induce lower in vivo Hg isotopic fractionation, thereby leading to lower blood δ 202 Hg values compared to adult penguins. To check this hypothesis, we investigated skua adult blood from the Kerguelen population, for which significantly higher δ 202 Hg values (a mean ~0.54 ‰ difference) were observed compared to

  5, 473-476. https://doi.org/10.1098/rsbl.2009.0265 Bowman, K.L., Lamborg, C.H., Agather, A.M., 2020. A global perspective on mercury cycling ://doi.org/10.1016/j.scitotenv.2019.136166 Brasso, R.L., Chiaradia, A., Polito, M.J., Raya Rey, A., Emslie, S.D., 2014. A comprehensive assessment of mercury exposure in penguin populations throughout the Southern Hemisphere: Using trophic calculations to identify sources of population-level variation. Mar. Pollut. Bull. 97, 408-418. https://doi.org/10.1016/j.marpolbul.2015.05.059 Bustamante, P., Carravieri, A., Goutte, A., Barbraud, C., Delord, K., Chastel, O., Weimerskirch, H., Cherel, Y., 2016. High feather mercury concentrations in the wandering albatross are related to sex, breeding status and trophic ecology with no demographic consequences. Environ. Res. 144, 1-10. https://doi.org/10.1016/j.envres.2015.10.024Cai, H., Chen, J., 2015. Mass-independent fractionation of even mercury isotopes. Sci. Bull.

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httpshttps://doi.org/10.1007/s11434-015-0968-8 Canario, J., Santos-Echeandía, J., Koch, B.P., Laglera, L., 2017. Mercury and methylmercury in the Atlantic sector of the Southern Ocean. Deep. Res. Part II 138, 52-62. https://doi.org/10.1016/j.dsr2.2016.07.012 Carravieri, A., Bustamante, P., Churlaud, C., Cherel, Y., 2013. Penguins as bioindicators of mercury contamination in the Southern Ocean: birds from the Kerguelen Islands as a case https://doi.org/10.1016/j.scitotenv.2013.02.060

Carravieri, A., Bustamante, P., Labadie, P., Budzinski, H., Chastel, O., Cherel, Y., 2020. Trace elements and persistent organic pollutants in chicks of 13 seabird species from Antarctica to the subtropics. Environ. Int. 134, 105225. https://doi.org/10.1016/j.envint.2019.105225

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Table of content

 of Section 1. Supplemental figures and tables .................................................................... 35 Section 2. Calculation procedures of the Hg isotopic fractionation extent due to biogeochemical processes ............................................................................................... 53 Section 3. Additional information on ecological characteristics of seabird species ...... 79 Section 4. Supplemental discussion on temporal variability in odd-MIF values: winter and summer periods in Antarctic zone. .......................................................................... 81

Section 1. Supplemental figures and tables Experimental

Hg isotopic composition analyses

Hg isotopic compositions of samples are reported using delta notation according to the following equations: δ xxx Hg =

[( xxx/198

Hgsample / xxx/198 Hg NIST 3133 ) -1)] • 1000 (‰)

Table S1 .

 S1 Mean values of Hg concentrations and Hg speciation obtained for reference materials with validated THg and MeHg concentration values: ERM-CE-464 (tuna fish), Dolt-4 (dogfish liver); and internal reference materials: RBC-KP (penguin red blood cells). Values are Mean±SD.

	Tissue	Reference material			Concentrations (ng•g -1 )	Recoveries (%)
				n	MeHg	iHg	THg	MeHg (%)	THg(%)
	Human hair (CRM)	NIES-13	Certified values	3800±400		4420±200
			This study	3 3647±46		4238±52 96±1	96±1
	Tuna fish (CRM) ERM-CE-464 Certified values	5117±158		5240±100
			This study	3 4809±61 265±11 5074±67 94±1	97±1
	Dogfish liver (CRM)	Dolt-4	Certified values	1330±120		2580±220
			This study	3 1202±13 1154±42 2516±81 95 ±3	98 ±3
	Penguin red blood cells (IRM)	RBC-KP	Values 254	AMA-			1980±76
			This study	3 1956±38	62±13	1988±39	101±2
							S41

Table S2 .

 S2 Mean values of Hg isotopic composition obtained for reference materials with validated reference isotopic values: NIST RM 8610

		Yamakawa et al., 2016		0.87±0.12	0.58±0.09	0.64±0.09	0.31±0.04	0.41±0.02	0.00±0.04	0.20±0.03	0.02±0.04	0.26±0.02
	(former UM-Almadén), NIST SRM 1947 (Lake Michigan fish tissue) and NIES-13 (human hair); previously published intercomparison values:
	IAEA-086 (human hair), ERM-CE-464 (tuna fish); and internal reference materials: F-KP (penguin feathers) and RBC-KP (penguin red blood ERM-CE-464 This study 0.91±0.13 0.64±0.04 2.37±0.03 0.40±0.01 2.49±0.01 -0.04±0.19 1.89±0.05 0.08±0.01 2.33±0.01
	cells). Values are Mean±SD. Li et al., 2014		0.94±0.06	0.70±0.04	2.49	0.43±0.05	2.55±0.08	-	1.96±0.06	0.07±0.04	2.38±0.07
	Sample	Reference	n	δ 204 Hg±2SD	δ 202 Hg±2SD δ 201 Hg±2SD δ 200 Hg±2SD δ 199 Hg±2SD ∆ 204 Hg±2SD ∆ 201 Hg±2SD ∆ 200 Hg±2SD ∆ 199 Hg±2SD
	F-KP	This study	17	‰ 2.40±0.25	‰ 1.58±0.22	‰ 2.67±0.21	‰ 0.80±0.16	‰ 2.11±0.18	‰ 0.04±0.24	‰ 1.48±0.13	‰ 0.01±0.09	‰ 1.71±0.15
	RBC-KP	This study This study	77	-0.84±0.22 1.98±0.18	-0.55±0.16 1.30±0.13	-0.45±0.13 2.26±0.14	-0.27±0.51 0.64±0.13	-0.17±0.12 1.78±0.17	-0.01±0.16 0.04±0.10	-0.04±0.09 1.28±0.09	0.00±0.11 -0.01±0.09	-0.03±0.11 1.46±0.14
	NIST RM 8610
	(UM Almadén)	Reference values		-0.82±0.07	-0.56±0.03	-0.46±0.02	-0.27±0.01	-0.17±0.01	-	-0.04±0.01	0.00±0.01	-0.03±0.02
	NIST SRM 1947	This study	4	1.68±0.25	1.19±0.10	5.02±0.15	0.69±0.09	5.54±0.14	-0.09±0.12	4.13±0.12	0.09±0.05	5.25±0.13
		Reference values		1.66±0.07	1.20±0.07	5.09±0.18	0.69±0.09	5.62±0.25	-0.13±0.02	4.17±0.28	0.09±0.02	5.31±0.29
	NIES-13	This study	8	2.99±0.22	2.08±0.15	3.07±0.16	1.09±0.10	2.34±0.10	-0.12±0.28	1.51±0.06	0.04±0.04	1.81±0.09
		Yamakawa et al., 2016	11	2.76±0.16	1.89±0.10	2.77±0.10	0.98±0.08	2.13±0.07	-0.04±0.11	1.36±0.07	0.04±0.04	1.65±0.06
	IAEA-086	This study	6	0.94±0.25	0.73±0.13	0.77±0.09	0.37±0.11	0.44±0.16	-0.14±0.26	0.22±0.08	0.00±0.09	0.26±0.15

Table S4 .

 S4 Total and MeHg concentrations (µg g -1 ), Hg isotopic composition (‰) and carbon (δ 13 C, ‰) and nitrogen (δ 15 N, ‰) isotopes for all the penguin individuals from the five studied populations from the Southern Ocean.

	Brown Brown Brown Emperor King penguin Macaroni Eastern Northern Section 2. Kergue Kergue Crozet	SSKER SSKER SSCR 46°26′S Oct 2011 KPA01 Jan-Feb MPA1	1.71		1.85	2.51	1.65	2.60	0.81	2.02		0.05		1.36	-0.02	1.60	-21.76 10.10
	skua skua adult skua penguin penguin rockhopper rockhopper	len len Crozet 46°26′S 49°21′S 49°21′S Adélie Crozet 46°26′S Jan 2012 Dec Dec 2012 OP10 P03 A06 ERPA 10.75 2.03 0.89 7 0.99 NRPA	2.14 11.32 0.93	1.46 2.41 1.92 1.03	0.96 1.59 1.27 2.45	2.16 2.53 2.29 1.59	0.49 0.78 0.69 2.53	1.92 1.86 1.97 0.81	1.94	0.03 0.04 0.02	0.08	1.44 1.34 1.34	1.34	0.01 -0.02 0.05 0.01	1.68 1.46 1.65 1.54	-22.76 -21.70 -20.26 -19.57 8.26 10.13 11.25 9.64
	chick King penguin penguin penguin	Land Crozet Crozet Amsterdam 37°50′S Nov 2011 66°40'S Nov 2011 EPP 01 46°26′S Oct 2011 KPA02 46°26′S Feb 18 18	0.55 2.04 0.87 2.51		1.43 2.19 0.89 2.77	0.78 2.12 3.10 3.63	0.55 1.51 2.12 2.32	1.43 2.47 3.05 3.28	0.25 0.70 0.93 1.33	1.34 1.92 2.09 2.57		-0.04 -0.13 -0.07 0.16		1.01 1.34 1.45 1.53	-0.02 -0.05 -0.13 0.17	1.20 1.54 1.55 1.98	-25.56 12.51 -21.57 10.10 -20.93 8.64 -19.17 10.17
	Species Brown skua Brown Brown skua adult Brown Brown skua Brown Species Macaroni Emperor King penguin penguin Eastern Northern penguin rockhopper rockhopper chick King penguin Macaroni penguin penguin	Locati on Kergue len Kergue Kergue len Kergue Crozet 46°26′S Latitude Sampling 49°21′S Dec 49°21′S Dec Jan-Feb 2012 Amster Location Latitude Sampling Code SSKER P04 SSKER SSKER A07 SSKER SSCR OP11 SSAM date Code MeHg (µg g -1 ) 1.78 8.70 1.02 MeHg (µg g -1 ) THg 2.03 9.24 1.09 (µg g -1 ) MPA1 THg δ 204 Hg (‰) 1.36 2.43 2.26 (µg g -1 ) δ 204 Hg δ 202 Hg (‰) 0.88 1.63 1.49 (‰) δ 202 Hg δ 201 H g (‰) 2.06 2.52 2.66 (‰) Crozet 46°26′S Oct 2011 KPA03 1.63 1.73 2.24 1.48 Crozet 46°26′S Jan 2012 8 1.16 1.25 2.41 1.61 Adélie ERPA NRPA Land 66°40'S Nov 2011 EPP 02 0.57 1.37 0.76 0.57 Crozet 46°26′S Oct 2011 KPA04 1.73 1.87 2.29 1.52 MPA1 Crozet 46°26′S Feb 19 0.78 0.81 2.78 1.81 Amsterdam 37°50′S Nov 2011 19 1.84 2.01 3.45 2.37	δ 200 Hg (‰) 0.41 0.83 0.75 δ 201 Hg (‰) 2.49 2.55 1.37 2.52 2.79 3.38	δ 199 Hg (‰) 1.82 1.95 2.13 δ 200 Hg (‰) δ 199 Hg ∆ 204 Hg (‰) 0.05 0.00 0.03 (‰) ∆ 204 Hg ∆ 201 Hg (‰) 1.40 1.30 1.54 (‰) ∆ 201 Hg ∆ 200 Hg (‰) -0.03 0.02 0.00 (‰) ∆ 200 Hg ∆ 199 Hg (‰) 1.60 1.54 1.75 (‰) ∆ 199 Hg (‰) 0.71 2.01 0.02 1.38 -0.03 1.64 0.72 1.88 0.01 1.34 -0.09 1.48 0.15 1.15 -0.09 0.94 -0.13 1.01 0.79 2.02 0.02 1.37 0.03 1.64 0.89 2.12 0.08 1.42 -0.02 1.67 1.14 2.44 -0.09 1.60 -0.05 1.84	δ 13 C (‰) -22.84 -21.27 -20.27 δ 13 C (‰) -22.12 9.95 δ 15 N (‰) 10.29 11.25 9.65 -19.45 8.00 δ 15 N (‰) -25.85 12.75 -22.31 9.82 -20.99 8.23 -18.89 10.46
	South polar skua skua Brown skua adult Brown skua Brown Adélie penguin penguin Emperor King penguin Eastern Northern penguin Macaroni rockhopper rockhopper	Adélie Land len Kergue len Kergue dam Amster Crozet 66°40'S 49°21′S 49°21′S 37°50′S 46°26′S Jan 2012 Dec-Jan 2012 ASP 01 Dec P05 SSKER Dec A08 SSKER Dec S12P01 SSAM 9 Adélie Land 66°40'S Feb 2012 APA11 0.56 2.50 11.57 3.30 1.13 0.42 Crozet 46°26′S Oct 2011 KPA05 1.96 Adélie MPA2 ERPA NRPA	0.59 2.69 12.32 3.34	0.55 1.60 2.65 2.21 1.18 0.45 2.12	0.31 1.12 1.65 1.50 2.23 1.03 1.85	1.53 2.20 2.48 2.60 1.49 0.69 1.28	0.13 0.53 0.80 0.80 2.40 1.87 2.37	1.59 1.80 1.89 2.18 0.71 0.33 0.61	0.09 -0.07 0.18 -0.03 1.84 1.77 1.87	0.01 0.00 -0.06	1.30 1.36 1.24 1.47	1.28 1.35 1.40	-0.02 -0.04 -0.03 0.05 -0.04 -0.02 -0.03	1.51 1.51 1.48 1.80 1.47 1.60 1.55	-23.39 -22.84 -21.55 -17.82 -21.89 9.10 11.48 10.13 11.32 14.55 -21.32 10.07 -24.01 8.88
	South polar skua skua adult skua Adélie chick King penguin penguin penguin penguin	Adélie len len dam Adélie 49°21′S 49°21′S 37°50′S Land 66°40'S Nov 2011 EPP 03 Dec-Jan Dec P06 Dec A10 Dec S12P02 Crozet 46°26′S Oct 2011 KPA06 2.22 8.64 4.27 Crozet 46°26′S Jan 2012 0 Crozet 46°26′S Feb 20 Amsterdam 37°50′S Nov 2011 20	0.38 1.80 1.29 0.73 2.41	2.37 9.25 4.33	1.60 2.25 2.32 1.20 1.90 1.34 0.77 2.59	1.01 1.51 1.56 0.50 2.17 2.80 2.45 3.19	2.07 2.44 2.67 0.38 1.59 1.88 1.61 2.17	0.55 0.84 0.83 1.20 2.60 2.83 2.90 3.02	1.80 1.92 2.18 0.10 0.76 0.95 0.93 1.11	0.09 -0.01 -0.01 1.06 1.97 2.05 2.32 2.23	-0.07 -0.20 -0.01 0.05 -0.05	1.31 1.30 1.49	0.91 1.41 1.41 1.69 1.39	0.04 0.08 0.05 -0.10 -0.03 0.00 0.12 0.02	1.55 1.54 1.78 0.96 1.57 1.57 1.91 1.69	-22.60 -21.82 -17.71 -25.80 12.75 10.34 11.17 14.34 -21.88 10.21 -20.59 8.48 -21.03 7.79 -19.13 9.70
	skua Brown Brown Brown penguin Emperor King penguin Eastern Northern	Land Kergue Amster Land Crozet 66°40'S 66°40'S Feb 2012 APA12 2012 ASP 02 0.55 SSKER Jan-Feb SSCR SSAM 46°26′S Oct 2011 KPA07	0.38 2.44	0.61	0.08 0.42 2.60	-0.02 0.52 2.14	1.32 0.33 1.53	0.00 1.78 2.50	1.55 0.13 0.78	1.66 1.98	0.11	0.03 -0.16	1.33	1.53 1.35	0.01 -0.04 0.01	1.55 1.58 1.59	-23.58 -24.35 8.99 11.32 -21.50 10.05
	South polar skua skua Brown skua Brown skua Brown Adélie penguin penguin rockhopper rockhopper chick King penguin penguin penguin	Adélie Land len Kergue Crozet 46°26′S 66°40'S 49°21′S dam 37°50′S Amster Adélie Adélie Land 66°40'S Feb 2012 APA13 Dec-Jan 2012 ASP 03 0.56 Dec P07 1.64 SSKER 2012 OP01 2.10 Jan-Feb SSCR Dec S12P03 3.96 SSAM ERPA NRPA Land 66°40'S Nov 2011 EPP 04 Crozet 46°26′S Oct 2011 KPA08 Crozet 46°26′S Feb 2012 11 Amsterdam 37°50′S Nov 11	0.48 0.59 1.57 0.80 2.11	0.59 1.77 2.43 4.51	0.19 1.55 2.14 2.26 0.50 1.37 1.70 0.84 2.90	0.22 1.07 1.40 1.44 1.14 0.74 2.12 2.57 3.28	1.41 2.13 2.45 2.55 0.74 0.59 1.45 1.67 2.19	0.07 0.57 0.71 0.82 1.92 1.37 2.50 2.72 3.15	1.55 1.85 1.96 2.11 0.38 0.18 0.71 0.89 1.10	-0.13 -0.05 0.05 0.10 1.80 1.20 1.97 2.13 2.32	0.03 -0.14 -0.04 0.07 0.01	1.25 1.33 1.40 1.46	1.36 0.93 1.41 1.46 1.50	-0.04 0.03 0.01 0.09 0.01 -0.12 -0.02 0.05 0.00	1.50 1.58 1.60 1.75 1.61 1.05 1.60 1.71 1.77	-23.38 -22.55 -20.62 -17.53 -24.28 9.22 11.56 10.36 11.39 14.42 -25.79 12.84 -21.96 9.76 -20.16 8.53 -18.86 10.11
	South polar skua skua Brown skua Brown skua Brown Adélie penguin Emperor King penguin Eastern Northern penguin rockhopper rockhopper chick King penguin penguin penguin	Adélie Land len Kergue Crozet 46°26′S 66°40'S 49°21′S dam 37°50′S Amster Crozet 46°26′S Oct 2011 KPA09 Dec-Jan 2012 ASP 04 0.39 Dec P08 2.30 SSKER 2012 OP02 2.91 Jan-Feb SSCR Dec S12P04 3.28 SSAM Adélie Land 66°40'S Feb 2012 APA14 Adélie ERPA NRPA Land 66°40'S Nov 2011 EPP 05 Crozet 46°26′S Oct 2011 KPA10 Crozet 46°26′S Feb 2012 12 Amsterdam 37°50′S Nov 12	1.91 0.38 0.48 2.26 0.74 1.38	0.44 2.47 2.96 3.44	0.23 1.45 2.02 2.33 2.02 0.40 1.36 2.42 0.78 2.20	0.13 0.98 1.32 1.60 2.12 0.45 0.72 2.10 2.92 2.91	1.49 2.05 2.34 2.68 1.40 0.31 0.48 1.37 2.00 1.99	0.03 0.46 0.68 0.91 2.38 1.41 1.36 2.45 3.13 3.19	1.61 1.81 1.84 2.25 0.71 0.13 0.20 0.69 1.00 1.00	0.03 -0.02 0.04 -0.05 1.96 1.46 1.28 1.97 2.45 2.54	0.03 -0.01 0.00 0.05 -0.06 -0.05	1.38 1.32 1.35 1.48	1.33 1.17 1.00 1.41 1.63 1.70	-0.04 -0.03 0.02 0.11 0.00 -0.03 -0.04 0.00 0.00 0.00	1.58 1.56 1.51 1.85 1.61 1.38 1.16 1.62 1.95 2.04	-23.54 -23.19 -20.57 -17.56 -21.44 10.05 11.55 9.99 11.44 14.32 -24.17 9.45 -25.64 12.58 -21.24 10.32 -20.33 8.78 -19.29 8.89
	South polar skua skua Brown skua Brown skua Brown Adélie penguin Emperor King penguin Eastern Northern penguin rockhopper rockhopper	Adélie Land len Kergue Crozet 46°26′S 66°40'S 49°21′S dam 37°50′S Amster Adélie Land 66°40'S Feb 2012 APA15 Dec-Jan 2012 ASP 05 0.38 Dec P09 2.62 SSKER 2012 OP03 1.07 Jan-Feb SSCR Dec S12P05 4.47 SSAM Crozet 46°26′S Oct 2011 KPA11 Adélie ERPA NRPA	0.48 1.65	0.43 2.83 1.14 4.94	0.50 1.74 1.86 2.18 0.64 1.77	0.34 1.14 1.33 1.52 1.02 2.33	1.51 2.25 2.42 2.54 0.73 1.64	0.19 0.53 0.73 0.71 1.77 2.61	1.59 1.90 2.00 2.07 0.39 0.77	0.00 0.04 -0.12 -0.08 1.65 2.07	-0.07 -0.12	1.25 1.40 1.42 1.40	1.22 1.38	0.02 -0.04 0.06 -0.05 0.03 -0.06	1.50 1.61 1.66 1.69 1.47 1.65	-23.02 -22.49 -19.59 -17.63 -22.22 10.35 10.03 10.58 10.58 14.11 -24.02 10.12
	South polar skua skua Brown skua Brown skua Brown Adélie penguin chick Macaroni penguin penguin penguin Emperor Eastern Northern	Adélie Land len Kergue Crozet 46°26′S 66°40'S 49°21′S dam 37°50′S Amster Adélie Land 66°40'S Feb 2012 APA16 Dec-Jan 2012 ASP 08 0.40 Dec P10 2.32 SSKER 2012 OP04 4.38 Jan-Feb SSCR Dec S12P06 5.54 SSAM Land 66°40'S Nov 2011 EPP 06 Crozet MPA1 Crozet 46°26′S Feb 2012 13 Amsterdam 37°50′S Nov 13 46°26′S Jan 2012 1	0.46 0.57 1.04 1.68 0.87	0.50 2.51 4.52 5.82	0.29 1.53 2.20 2.40 0.49 1.43 1.12 1.83 0.95	0.16 1.06 1.49 1.71 1.09 1.01 3.04 2.87 2.48	1.23 2.24 2.46 2.72 0.79 0.57 2.00 1.91 1.65	0.03 0.59 0.76 0.85 1.85 1.43 3.06 3.02 2.65	1.35 1.92 2.01 2.14 0.35 0.31 1.05 1.02 0.82	0.05 -0.06 -0.03 -0.15 1.78 1.36 2.27 2.49 2.04	-0.10 0.15 0.06 0.02 0.02	1.12 1.44 1.34 1.44	1.25 1.00 1.56 1.59 1.41	-0.05 0.06 0.02 -0.01 -0.05 0.02 0.05 0.06 0.00	1.31 1.65 1.64 1.71 1.58 1.21 1.77 2.00 1.63	-23.73 -22.98 -20.56 -18.30 -26.02 12.74 11.76 10.18 11.27 14.81 -20.78 8.84 -18.75 10.85 -19.60 8.16 -24.23 9.67
	South polar skua skua adult Brown skua Brown skua Brown Adélie penguin penguin Macaroni rockhopper rockhopper chick penguin penguin penguin	Adélie Land len Kergue Crozet 46°26′S 66°40'S 49°21′S dam 37°50′S Amster Adélie Adélie Land 66°40'S Feb 2012 APA17 Dec-Jan 2012 ASP 09 0.40 Dec A01 10.73 SSKER 2012 OP05 2.50 Jan-Feb SSCR Dec S12P07 2.93 SSAM MPA1 ERPA NRPA 0.18 Land 66°40'S Nov 2011 EPP 07 0.48 Crozet 46°26′S Jan 2012 2 1.05 Crozet 46°26′S Feb 2012 14 1.07 Amsterdam 37°50′S Nov 14 2.42	0.45 11.87 2.68 3.00	0.36 2.48 1.93 2.39 0.18 1.30 1.09 1.13 3.50	0.21 1.64 1.22 1.66 0.71 0.70 2.59 3.00 3.19	1.48 2.48 2.28 2.74 0.56 0.48 1.73 2.01 2.14	0.13 0.82 0.59 0.85 2.00 1.30 2.69 3.08 3.06	1.63 1.90 1.91 2.18 0.14 0.16 0.90 1.05 1.14	0.05 0.04 0.11 -0.09 1.87 1.29 2.00 2.34 2.33	-0.12 -0.02 0.01 -0.01 -0.01	1.33 1.25 1.36 1.49	1.58 0.94 1.39 1.57 1.45	0.02 0.00 -0.02 0.01 -0.14 -0.09 0.03 0.04 0.06	1.58 1.49 1.61 1.77 1.73 1.17 1.57 1.83 1.79	-23.66 -21.75 -20.28 -16.89 -24.17 8.48 11.61 11.24 11.05 14.42 -25.25 12.55 -19.94 9.04 -20.93 8.75 -19.14 10.23
	South polar skua South polar skua Brown skua Brown skua skua adult Brown skua adult Brown skua adult Brown skua adult skua Brown skua Brown skua Brown skua skua Brown skua Brown skua Adélie penguin Emperor Macaroni Eastern Northern penguin penguin rockhopper rockhopper Adélie penguin chick Macaroni penguin penguin Emperor penguin Eastern Northern Adélie penguin penguin chick Macaroni penguin rockhopper rockhopper penguin penguin Emperor penguin chick Macaroni penguin Eastern Northern rockhopper rockhopper penguin penguin	Adélie Land Adélie Land Kergue len Kergue len len Kergue len Kergue len Kergue len Crozet 46°26′S 66°40'S 66°40'S 49°21′S 49°21′S 49°21′S 49°21′S 49°21′S 49°21′S Crozet 46°26′S Crozet 46°26′S Crozet 46°26′S dam 37°50′S Amster dam 37°50′S Amster dam 37°50′S Adélie Land 66°40'S Feb 2012 APA18 Dec-Jan 2012 ASP 10 0.49 Dec-Jan 2012 ASP 11 0.59 Dec 2011 SSKER P01 2.37 Dec 2011 SSKER P02 1.83 Dec A02 7.51 Dec SSKER A03 9.69 Dec SSKER A04 10.60 Dec SSKER A05 14.36 2012 OP06 0.67 Jan-Feb 2012 SSCR OP07 1.09 Jan-Feb 2012 SSCR OP08 0.88 Jan-Feb 2012 SSCR OP09 1.17 Dec S12P08 3.47 Dec SSAM S12P09 3.31 Dec SSAM S12P10 3.24 MPA1 0.56 Adélie Crozet 46°26′S Jan 2012 3 1.06 ERPA NRPA Land 66°40'S Nov 2011 EPP 08 0.72 Crozet 46°26′S Feb 2012 15 0.89 Amsterdam 37°50′S Nov 15 1.46 MPA1 Adélie Land 66°40'S Feb 2012 APA19 0.52 Crozet 46°26′S Jan 2012 4 0.80 Adélie Land 66°40'S Feb 2012 APA20 0.45 Adélie Land 66°40'S Nov 2011 EPP 09 0.51 Crozet 46°26′S Jan 2012 ERPA NRPA MPA1 5 0.91 Crozet 46°26′S Feb 2012 16 1.34 Amsterdam 37°50′S Nov 16 2.19 Adélie Land 66°40'S Nov 2011 EPP 10 0.48 Crozet 46°26′S Jan 2012 MPA1 6 0.89 ERPA NRPA Crozet 46°26′S Feb 2012 17 1.00 Amsterdam 37°50′S Nov 17 1.48	0.55 0.65 2.48 1.94 8.52 10.55 11.22 15.16 0.74 1.18 0.93 1.25 3.81 3.43 3.38	0.45 0.53 1.54 1.64 2.32 2.17 2.32 2.52 2.19 2.54 1.64 2.02 2.21 2.48 2.30 0.58 1.10 1.58 0.93 1.62 0.55 0.82 0.45 1.39 0.95 1.39 2.32 1.33 0.92 1.03 2.20	0.30 0.41 1.08 1.05 1.53 1.42 1.55 1.66 1.56 1.73 1.07 1.42 1.49 1.59 1.53 0.77 2.51 1.20 2.74 3.01 1.10 2.49 0.37 0.78 2.31 3.22 3.44 0.69 2.61 3.04 3.15	1.48 1.60 2.20 2.19 2.45 2.38 2.50 2.54 2.65 2.83 2.34 2.62 2.56 2.75 2.63 0.47 1.63 0.72 1.89 2.11 0.71 1.67 0.24 0.51 1.60 2.12 2.28 0.48 1.74 2.05 2.08	0.12 0.22 0.54 0.50 0.74 0.68 0.77 0.83 0.77 0.92 0.55 0.77 0.75 0.82 0.80 1.66 2.53 1.58 2.99 3.22 1.86 2.64 1.41 1.39 2.52 3.05 3.27 1.33 2.63 3.09 3.12	1.59 1.65 1.93 1.92 1.86 1.83 1.91 1.93 2.21 2.23 2.01 2.23 2.09 2.20 2.11 0.26 0.80 0.50 0.96 1.08 0.30 0.86 0.09 0.20 0.81 1.08 1.23 0.16 0.90 1.03 1.16	0.01 -0.09 -0.08 0.06 0.03 0.06 0.00 0.04 -0.13 -0.04 0.04 -0.10 -0.02 0.11 0.01 1.65 1.89 1.51 2.35 2.49 1.67 2.05 1.45 1.29 1.94 2.18 2.46 1.15 1.97 2.26 2.51	0.07 0.08 0.12 -0.08 -0.14 0.04 0.00 0.01 0.03 -0.08 0.06 0.03 -0.03 0.00 -0.02 0.05	1.26 1.28 1.38 1.39 1.29 1.32 1.33 1.29 1.48 1.52 1.54 1.55 1.44 1.56 1.48	1.30 1.31 1.04 1.57 1.64 1.33 1.38 1.23 1.01 1.32 1.46 1.55 0.97 1.32 1.54 1.56	-0.03 0.01 -0.01 -0.03 -0.03 -0.03 -0.01 -0.01 -0.01 0.05 0.02 0.06 0.00 0.02 0.03 0.02 -0.02 0.13 0.01 0.02 -0.06 0.02 -0.04 -0.06 0.01 0.01 0.08 -0.08 0.03 0.00 0.12	1.52 1.55 1.65 1.65 1.47 1.48 1.52 1.51 1.82 1.79 1.74 1.87 1.71 1.80 1.72 1.53 1.48 1.33 1.87 1.95 1.49 1.63 1.39 1.16 1.54 1.65 1.89 1.03 1.53 1.74 1.99	-23.74 -23.34 -22.51 -22.68 -20.97 -21.31 -21.64 -21.49 -19.91 -19.64 -20.91 -20.15 -17.98 -17.54 -17.69 -19.92 8.58 11.52 11.35 10.30 10.20 11.25 11.25 11.20 11.25 10.65 10.20 9.76 10.57 14.12 14.28 14.30 -24.16 10.04 -25.87 12.60 -21.02 8.08 -18.93 10.36 -19.79 8.79 -24.04 9.63 -25.67 13.03 -20.89 9.29 -19.17 9.95 -19.44 8.62 -24.23 9.71 -25.85 12.83 -19.65 8.52 -21.12 8.64 -18.89 10.33
																		S45 S47 S49 S51
										S21

Calculation procedures of the Hg isotopic fractionation extent due to biogeochemical processes Estimation of the fraction of photodemethylated MeHg in surface waters at distant sites of the Southern Ocean

  for the different MeHg:DOC or MeHg-Sred/DOC calculated ratios.

				Mid-range
						Low MeHg:DOC
				MeHg:Sred-DOC	Low MeHg:Sred-
						ratio
				ratio	DOC ratio
				Chandan et al.,	Chandan et al.,	Bergquist and
				2015	2015	Blum, 2007
				MeHg	MeHg	MeHg
	Zone	Site	Seabird species	photodemethylation	photodemethylation	photodemethylation
				(% )	(% )	(% )
	Antarctic Zone	Adélie Land	Antarctic skuas	9.5±0.5	4.9±0.5	14.5±2.3
		Adélie Land	Emperor penguins	7.2±0.7	3.7±0.4	12.9±1.2
		Adélie Land	Adélie penguins	9.7±0.6	5.0±0.3	15.7±1.1
	Subantarctic Zone Kerguelen	Brown skuas	9.5±0.3	4.9±0.2	17.9±0.6
		Crozet	Brown skuas	9.7±0.5	5.1±0.3	18.8±1.1
		Crozet (Polar Front) King penguins	9.4±0.2	4.9±0.1	14.7±0.3
		Crozet	Gentoo penguins	8.4±0.4	4.3±0.2	13.1±0.6
		Crozet	Macaroni penguins	9.1±0.3	4.7±0.2	14.3±0.5
		Crozet	Rockhopper penguins	9.3±0.8	4.9±0.4	16.2±1.1
	Subtropical Zone Amsterdam	Brown skuas	10.6±0.3	5.5±0.1	17.2±0.4
		Amsterdam	Northern rockhopper penguin	11.3±0.7	5.9±0.4	18.4±1.1

Table S )

 S and low MeHg;S red-DOC (TableS), which seem to be the closest model to our conditions in the Southern Ocean. We could estimate a α (δ 202 Hg)/α (∆ 199 Hg) near 1 in both cases (and both seabird models), meaning that during photodemethylation of MeHg, the same degree of fractionation is experienced by δ 202 Hg and ∆ 199 Hg. Consequently,

	considering that the overall latitudinal MIF variations are attributed to MeHg
	photodemethylation and are in the order of 0.3‰ (~ 0.25‰ and ~ 0.32‰, respectively for
	skuas and penguins), we could explain ~ 0.3‰ of the total latitudinal MDF variations due
	to MeHg photodemethylation.
	S64

Table S9 .

 S9 Calculation of the fractionation factors of MDF (α (δ 202 Hg)) corresponding to MeHg photodemethylation for each study area based on experimental studies under mid-range MeHg:Sred-DOC conditions (SRFA organic matter conditions, 35% S-red)(Chandan et al., 2015).

		Conditions: mid-range MeHg;S red-DOC (35% S-red)
	Population/
	Sites	ε ∆ 199 Hg (‰) α (∆ 199 Hg) ε δ 202 Hg (‰)	α (δ 202 Hg)	Ratio α (δ 202 Hg)/α (∆ 199 Hg)
	Skuas
	AZ	-5.23895	0.99476	-4.73312	0.99527
	SAZ	-5.24037	0.99476	-4.73440	0.99527
	STZ	-5.20641	0.99479	-4.70372	0.99530	1.00051
	Penguins
	AZ	-5.30277	0.99470	-4.79078	0.99521
	SAZ	-5.26504	0.99473	-4.75669	0.99524
	STZ	-5.163113	0.99484	-4.66461	0.99534	1.00050
						S65

Table S10 .

 S10 Calculation of the fractionation factors of MDF (α (δ 202 Hg)) corresponding to MeHg photodemethylation for each study area based on experimental studies under mid-range MeHg:Sred-DOC conditions (SRFA organic matter conditions, 35% S-red)(Chandan et al., 2015).

	Calculation of the kinetic fractionation factor α( 198 Hg/ 202 Hg) as a function of the Hg
	remaining fraction (fR) at each latitude. The Hg remaining fraction (fR) was calculated from
	the water/air partitioning constant KH in order to estimate the Hg fractionation magnitude
	Conditions: low MeHg;S red-DOC (50% S-red) during volatilization at each location. The experimental volatilization of aqueous Hg 0 into
	Population/ gaseous Hg 0 indicated a MDF with a low kinetic fractionation factor α( 198 Hg/ 202 Hg). The
	obtained during experimental volatilization process was similar for accumulative
	Sites	ε ∆ 199 Hg (‰) α (∆ 199 Hg) ε δ 202 Hg (‰)	α (δ 202 Hg)	Ratio α (δ 202 Hg)/α (∆ 199 Hg)
	fractionation (1.00044) and instantaneous fractionation (1.00047), indicating that Hg
	Skuas isotopic fractionation during volatilization is independent of the initial solution volumes
	AZ	-1.501006	0.998499	-1.520006	0.998480
	SAZ	-1.500575	0.998499	-1.519569	0.998480
	STZ	-1.495628	0.998504	-1.514560	0.998485	0.99998
	Penguins
	AZ	-1.438243	0.998562	-1.456449	0.998544
	SAZ	-1.504152	0.998496	-1.523191	0.998477
	STZ	-1.489287	0.998511	-1.508138	0.998492	0.99998
						S67

Table S11 .

 S11 Calculation of the volatilised fraction of Hg and the MDF enrichment factor (δ 202 Hg) corresponding to Hg volatilisation following the Henry's law constant value and the Hg isotopic fractionation models during experimental volatilisation processes.

			Henry's	Conc
	Site	Water	constant	Hg 0	(air)	Calculated	fR (Hg 0	log (fR)	ε δ 202 Hg
		temperature (K)				Eq. Hg 0	(aq)	aq)		(‰)
			(KH)	(ng m -3 )
						(ng m -3 )
				(1)
	AZ	273	0.21	0.93	4.50		0.829	-0.188	0.088
	SAZ	281	0.25	0.90	3.58		0.799	-0.224	0.105
	STZ	291	0.31	1.03	3.32		0.763	-0.270	0.127

(1)

AZ:

[START_REF] Pfaffhuber | Atmospheric mercury observations from Antarctica: Seasonal variation and source and sink region calculations[END_REF] SAZ: ; STZ :Angot et et al. 2014

Table S12 .

 S12 Calculation of the fraction of reduced Hg between the studied sites considering theoretical kinetic fractionation factors.

	1.5	-3.75	0.02	42.6
	1.00	-0.63	0.53	1.87
	Hg(II) reduction (aq)-Hg-resistant bacteria merA Hg(II) bacterial reduction (aq)-Hg-resistant
	α δ 202 Hg (‰)	1.0013
	α δ 202 Hg (‰)	1.0016
	Kritee et al., 2007
	Kritee et al., 2008
		log
				conc [MeHg]
	∆(δ 202 Hg) ∆(δ 202 Hg)	(fR STZ/ fR AZ) fR STZ/ fR AZ log (fR STZ/ fR AZ) fR STZ/ fR AZ	conc [MeHg] STZ/[MeHg] AZ STZ/[MeHg] AZ
	2	-0.8020	0.4484	2.23
	1.50	-0.94	0.39	2.56
	1.50	-1.16	0.31	3.18
	1.00	-0.63	0.53	1.87
	1.00	-0.77	0.46	2.16
	Hg(II) reduction (aq)-Hg-resistant
	bacteria merA
	α δ 202 Hg (‰)	1.002
	Kritee et al., 2007
		log (fR STZ/ fR		conc [MeHg]
	∆(δ 202 Hg)	AZ)	fR STZ/ fR AZ	STZ/[MeHg] AZ
	1.50	-0.75	0.47	2.12
	1.00	-0.50	0.61	1.65
	Hg(II) bacterial reduction (aq)-Hg-sensitive bacteria (no mer system)
	α δ 202 Hg (‰)	1.0004
	Kritee et al., 2008
		log (fR STZ/ fR		conc [MeHg]
	∆(δ 202 Hg)	AZ)	fR STZ/ fR AZ	STZ/[MeHg] AZ
				S76 S77

Table S13 .

 S13 Calculation of the fraction of methylated Hg between the studied sites considering theoretical kinetic fractionation factors.

	Hg(II) net bacterial methylation (aq)-sulphate respiration
	α δ 202 Hg (‰)	1.0025	Perrot et al., 2015
		log (fR STZ/ fR
	∆(δ 202 Hg)	AZ)	fR STZ/ fR AZ	[MeHg] STZ/[MeHg] AZ
	1.50	-0.60	0.55	1.82
	1.00	-0.40	0.67	1.49
	Hg(II) net abiotic methylation (aq) by MeCo
	α δ 202 Hg (‰)	1.0016	Jiménez Moreno et al., 2013
		log (fR STZ/ fR
	∆(δ 202 Hg)	AZ)	fR STZ/ fR AZ	[MeHg] STZ/[MeHg] AZ
	1.50	-0.94	0.39	2.56
	1.00	-0.63	0.53	1.87
				S78

Table S14 .

 S14 Details of sample collection periods and phytoplankton bloom periods in each study area during austral summer 2011-2012.

	Species	Location Latitude	Sampling	Bloom period
	South polar skua	Adélie Land 66°40'S December 2011 /January 2012 January/February
	Adélie penguin	Adélie Land 66°40'S February 2012	January/February
	Brown skua	Kerguelen	49°21′S December 2011	November/December
	Brown skua	Crozet	46°26′S January/February 2012	November/December
	King penguin	Crozet	46°26′S October 2012	November/December
	Macaroni penguin	Crozet	46°26′S January 2012	November/December
	Eastern rockhopper penguin Crozet	46°26′S February 2012	November/December
	Brown skua	Amsterdam 37°50′S December 2011	October
	Northern rockhopper penguin Amsterdam 37°50′S November 2011	October

Acknowledgements

The authors wish to thank the fieldworkers who helped collecting blood samples. This study received financial and logistical support from the Institut Polaire Français Paul Emile Victor (IPEV, program no. 109, H. Weimerskirch), the French Southern and Antarctic Lands, and by the Agence Nationale de la Recherche (ANR, program POLARTOP, O. Chastel). Special thanks are due to A. Carravieri who managed the sample database. We also wish to thank Prof. S. Blain (UPMC) for fruitful discussions and help with the oceanographic interpretation of our data. The present work was supported financially by the Région Poitou-Charentes (now the Région Nouvelle Aquitaine) through a Ph.D. scholarship to MR, and by the French national program EC2CO Biohefect/Ecodyn//Dril/MicrobiEen (TIMOTAAF project, P.I. D. Amouroux). The IUF (Institut Universitaire de France) is also acknowledged for its support to PB as a senior member.

Supporting Information

A "seabird-eye" on mercury stable isotopes and cycling in the Southern Ocean Marina Renedo a,b,* , Paco Bustamante a,c , Yves Cherel d , Zoyne Pedrero b , Emmanuel Tessier b , David Amouroux b,* a Littoral Environnement et Sociétés (LIENSs), UMR 7266 CNRS-La Rochelle Université, 2 rue Olympe de Gouges, 17000 La Rochelle, France *Corresponding authors: marina.renedo@ird.fr, david.amouroux@univ-pau.fr S66 Fractionation (MDF) involved during Hg 0 partitioning and equilibrium between water and air Calculation of the Henry's law constant (KH). The calculation of Henry's law constant permits to estimate the gaseous elemental Hg partition at equilibrium between water and air as a function of the water surface temperature. This constant represents the fraction of gaseous Hg 0 as a function of the Hg 0 remaining in the aqueous phase.

(2)

An equation for artificial sea water (concentration conditions of 1.5 M of NaCl) proposed by (Andersson et al., 2008).

(3)

The data of water temperature were taken from previous studies in austral autumn (Cossa et al., 2011) and summer [START_REF] Canario | Mercury and methylmercury in the Atlantic sector of the Southern Ocean[END_REF]