Karine Leblanc
email: karine.leblanc@univ-amu.fr

Bernard Queguiner

Frederic Diaz

Veronique Cornet

Mónica Michel-Rodriguez

Xavier Durrieu De Madron

Chris Bowler

Shruti Malviya

Melilotus Thyssen

Gérald Grégori

Bernard Quéguiner

Frédéric Diaz

Véronique Cornet

Mathieu Rembauville

Olivier Grosso

Julie Poulain

Colomban De Vargas

Mireille Pujo-Pay

Pascal Conan

Nanoplanktonic diatoms are globally overlooked but play a role in spring blooms and carbon export

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

Introduction

The widely accepted characteristics of spring blooms in marine systems are that highly turbulent front regions and eutrophic areas generally result in the proliferation of diatoms along an ecological succession sequence, which then favours coccolithophores and finally dinoflagellates as stratification and oligotrophy increase 1 . Another textbook view of the functioning of these high primary productivity events is that they contribute disproportionately to the export of carbon to the ocean interior. This concept is explicit in Legendre and Lefèvre's bifurcation model 2 which states that large microalgal blooms often result in increased sinking of phytoplanktonic cells or faecal pellet production, while smaller organisms are preferentially shifted towards the microbial loop, thereby reducing the fraction available for export 2 . Phytoplankton communities are typically characterized using bulk measurements, satellite data and model outputs that do not yet allow a fine scale understanding of specific floristic successions. Since the nature of the organisms composing the bloom events has dramatic effects on both higher trophic levels and biogeochemical export fluxes, it is crucial to refine our understanding of their succession determinism.

For eutrophic regions, a three-stage typical spring bloom diatom succession was proposed by Margalef 1 and modified by Guillard and Kilham 3 . It involves a first sequence after upwelling or strong mixing that is dominated by fast-growing small species (>10 µm) belonging to the Thalassiosira, Chaetoceros or Skeletonema genera, followed next by the appearance of a larger number of medium-sized Chaetoceros species, often forming long chains. Last, as nutrients are consumed, species more adapted to oligotrophic environments then thrive, such as large Rhizosolenia and Hemiaulus species, often associated with nitrogen-fixing cyanobacteria. The rate of succession can then be modulated by loss rates of diatoms from the euphotic zone, through diffusion, sinking and grazing 3 . At the global scale, centric diatoms such as Rhizosolenia, Chaetoceros and Thalassiosira represent a little under 50% of total diatom biomass 4 , tending to confirm this general diatom succession. However, deviations from Margalef's typical diatom bloom scenario 1 , with very small (<5 µm) diatom species developing into quasi-monospecific blooms have been reported on occasion, mostly in mid-and high-latitude well-mixed environments [5][6][7][8][9][10] . These phenomena are depicted as anomalous, and as a consequence, the large-scale distribution and significance of these minute diatom species are still not widely recognized.

Here, we present data relative to the 2013 spring bloom in the Northwestern Mediterranean Sea, evidencing the massive development of the small diatom genus Minidiscus, which overlaps both the pico-and nano-size fractions with diameters ranging from <2 to 5 µm. We show that this tiny diatom accumulated in extremely high numbers (10 6 cells L -1 ) over a deep convection area following a particularly intense winter mixing event which extended down to the sea bottom (2,400 m) 11 . Thanks to a trait-based modelling approach, we attempt to determine which key biological factors favour the proliferation of such nano-sized diatom blooms and propose that top-down control mechanisms (selective grazing, viral or bacterial lysis) may exert a specific control on the development of larger cells, opening an ecological niche for small diatoms to succeed. We then extend our results to a global scale, using metabarcoding data from the Tara Oceans survey 12 , showing that Minidiscus ranked in the top 20 most abundant diatom genera, although it has rarely been described in phytoplankton process studies. We propose, as hinted by several other authors but still not integrated into the classical view, that nanoplanktonic diatom blooms may be more frequent than currently appreciated in open ocean and coastal areas perturbed by turbulence following vernal mixing or frontal stirring but that their tiny dimensions and dynamics have prevented both adequate sampling and observation until now. Last, we look for evidence of the potential impact of these diatoms in carbon export, using our Mediterranean case study, data from Tara Oceans, and from literature reviews, and question whether we should revise the classical view that lower-end nanoplankton-sized cells are entirely recycled through the microbial loop and do not contribute in any significant way to carbon export to the deep ocean, as was already suggested for picophytoplankton 13 . We thus highlight these tiny, elusive diatom species as being of potential global significance in productive environments and for carbon export.

Results

Spring bloom of nano-sized diatoms in the Mediterranean Sea

The Gulf of Lions in the northwestern Mediterranean Sea is the hotspot for the recurrent deep-water formation during winter, due to significant autumnal and winter heat losses caused by strong Northern winds, and the presence of a cyclonic gyre enclosing dense water in the middle of the basin 14 . An intense convection event occurred during the Deep Water Experiment (DeWeX) in 2013, leading to mixing of the water column from the surface to the seafloor at 2,400 m depth 15 . This massive overturn induced fertilization of the surface waters with upwelled nutrients and triggered a large phytoplankton spring bloom (Fig. 1a,b). Such an annual event is well known and recurrently observed, both from space 16,17 and from field campaigns 18 . However, the nature of the phytoplankton bloom in this area is poorly characterized, even though it has been estimated to contribute approximately 15% of the primary production in the Mediterranean Sea 16 .

In such a turbulent eutrophic environment, small-to medium-sized chain-forming diatom genera are usually expected to proliferate first upon alleviation of light limitation, followed by larger species as nutrients are consumed. However, phytoplankton determination during the DeWeX spring bloom revealed a different diatom community, with a massive accumulation dominated by at least two species of the smallest known centric diatom genus Minidiscus (M. trioculatus and M. comicus). They belong to the very small end of the nanophytoplankton size fraction (~2-5 µm diameter in our observations) even though they are reported to extend to the pico-size fraction with known minimum diameters for M. trioculatus and M. comicus of 1.5 and 1.9 µm respectively 19 . These species reached very high abundances (4-6 million cells L -1 at several stations in April -Leg 2) and were the dominant diatoms over a large region (17 out of 32 stations) of the study area (Figs. 2a,b and Supplementary Figs. 1 and2). Their abundance peaked mainly in the centre of the convection region at around 42°N, 5°E and in an anticyclonic eddy south of the study region around 40.5°N, 6°E, where abundances ranged from 5,000 to 425,000 cells L -1 . Meanwhile, microphytoplanktonic diatoms (>20 µm) were only observed closer to the Gulf of Lions plateau in winter and in the northeastern region between the coast of France and Corsica in spring, but never exceeded 17,000 cells L -1 , a low value for a spring bloom. Minidiscus was not observed at any site during February (leg 1), which suggests an earliest bloom initiation in March. Increased biogenic silica (BSi) in the areas where Minidiscus was absent was associated with typical larger diatoms such as Pseudo-nitzschia spp., Leptocylindrus spp., Cylindrotheca spp. and other large Thalassiosira spp. during winter and mainly to Guinardia delicatula and Chaetoceros spp. during spring (Supplementary Figs. 1 and2). At a few stations during April (leg 2), the small pennate Nitzschia bicapitata (~10 µm) was also observed in elevated concentrations in association with Minidiscus, but the abundances of the latter were always at least 1 or 2 orders of magnitude higher. BSi concentrations associated with the densest Minidiscus bloom area were elevated for the Mediterranean Sea (1 µmol L -1 ) and particulate Si:C ratios (0.07-0.10) were close to Brzezinski's values for small diatoms 20 . An estimation of the growth rates required to produce such an accumulation yields a minimum approximate net rate of 0.3 d -1 (for an average of 805,000 cells L -1 ) between early March and mid-April starting from a seed population of 10-100 cells L -1 . This is higher than the rate of 0.13 d -1 measured in situ during a more moderate Minidiscus spring bloom observed in the Norwegian basin in 2012 10 , which could be explained by the lower temperature (~6-7°C) compared to our study area (~13°C) 21 .

However, if the Minidiscus bloom grew over a shorter period of time, for instance over a week, growth rates would have been much higher and closer to 2 d -1 . The unexpected very small size structure of this phytoplankton community was confirmed by an automated flow cytometer installed on an inflow of surface water pumped continuously at 3 m depth. It evidenced that the massive spring bloom in April was almost entirely dominated by nanophytoplankton (Supplementary Fig. 3). Observations by optical microscopy revealed that the Minidiscus bloom co-existed with even larger numbers of undetermined nanoflagellates and cryptophytes, all smaller than 20 µm, while abundances of larger cells were about three orders of magnitude lower at most sites (Supplementary Fig. 3).

A further unusual feature was the overall dominance of diatoms by Minidiscus during this bloom. At all sites where Minidiscus was observed, it represented on average 92% of total diatom abundance (Table 1). Notwithstanding, conclusions drawn on abundance are difficult to transpose to biogeochemical relevance, in particular at both ends of the size spectrum where abundance and biomass are no longer closely related. To assess whether this numerically abundant bloom was an important contributor to total phytoplankton biomass, we converted abundance data to carbon (C) content, using an average biovolume of 18 µm 3 and subsequent Si and C content estimate of ~0.8 pmol C cell -1 and 0.08 pmol Si cell -1 , consistently with the data given in Brzezinski (1985) 20 for another similar sized species (24 µm 3 ), but about 3-fold higher than the quotas predicted using standard allometric approaches 22,23 . Minidiscus biomass was then compared to measured Particulate Organic Carbon (POC) and BSi concentrations in the same samples. While Minidiscus was not the dominant contributor to C biomass given its small size, the high abundances of other nanoplankton groups and the variable content of dead material in POC, it still reaches between 18 and 26% of total POC at stations 74 and 99 (Table 1), located close to the centre of the convection area (42°N, 5°E). At station 74, Minidiscus constituted the bulk of in situ BSi stocks (99.4%) on one occasion on April 19 th , whereas its relative contribution decreased to 36% by the end of April at the same location (Table 1). This locally significant contribution is surprising given that the genus Minidiscus has never been documented to form such intense blooms in the Mediterranean Sea. Minidiscus is in fact absent from many taxonomic books for this basin, and appeared for the first time in an inventory of the Catalan Sea only in 1992 24 . M. comicus was only recently observed in the same region of the northwestern Mediterranean during spring 25 , and in nearby regions of the Gulf of Naples 26 , while M. trioculatus was considered to be rare. Minidiscus was observed for the first time in April 2012 at a coastal bi-monthly time-series site located on the Gulf of Lions coastal shelf in the Bay of Marseille (SOMLIT), at very low baseline abundances.

Higher abundances were reported in May and July 2013 following our study (Pers. Comm. B.

Beker). The only other report of such massive nano-sized diatom bloom in the Mediterranean Sea was that of the small centric diatom Thalassiosira partheneia (<8 µm) in the Almeria-Oran front 6 , where it accumulated in a thin layer at depth up to ~10 million cells L -1 with a similar calculated net growth rate of 0.2 d -1 .

The nutrient concentrations at stations sampled during winter revealed that the amount of nutrients upwelled to the euphotic layer was dependent on the area covered by the convection event, while nutrient stoichiometry was dependent on the vertical extent of the convection depth 11 . From a hierarchical ascendant classification analysis of stations sampled during winter (DeWeX cruise leg1), we found that highly convective regions were characterized in the surface layer (0-50 m) by high H4SiO4 and NO3 -concentrations (7.7 µM and 8.4 µM, respectively), while weakly convective regions showed much lower nutrient content (2.1 µM Si and 2.7 µM N, respectively) 11 . In parallel, the Si:N nutrient ratio prior to the spring bloom in the surface layer was 15% higher in the case of high convection compared to low convection or no mixing at all (Fig. 3). High convection events mixing deep water masses with the surface layer thus seem necessary to supply enough Si to the surface relative to N and P to sustain a high bloom situation dominated by diatoms 27 . The dominance of Minidiscus during DeWeX could thus partly be attributed to their higher efficiency with respect to larger diatoms for taking up high silicic acid concentrations, which were preferentially upwelled compared to nitrate 28 . In the absence of physiological rate measurements during the cruise, we rely on the following 0D modelling simulation (not coupled to physical forcings) to test which bottom-up or top-down processes could best explain the preferential development of nano-sized diatoms over larger species.

Biogeochemical models are often based on two main numerical representations of biota, the Plankton Functional Type (PFT) models that are now widely used 29 and the trait-based models grounded on the Reynolds' C-S-R classification 30 built on Margalef's mandala 1 . On one hand, PFT-based models only depict diatoms as a single large phytoplankton box connected to the Si cycle and are therefore inherently unable to reproduce different life strategies and traits within diatom community. On the other hand, the C-S-R models can be applied in the present context as an adapted tool to represent a spectrum of different strategies of development among diatoms. Each of these strategists is characterized by a specific ecological niche, defined by a combination of nutrient and light variables, which are the major factors impacting diatom survival strategies 31 . We used a simple C-S-R trait-based model representing four different types of strategists to attempt to understand the reasons underlying the occurrence of the massive bloom of Minidiscus evidenced during DeWeX in 2013.

Among the four considered strategists, two diatom types were differentiated. Owing to its morphological and physiological traits, Minidiscus was considered in the present model as a colonist genus (i.e., a C-strategist). This group is characterized by a high growth rate, a small size and a round shape (Figs. 4 and5). The other diatom type, characterized by higher growth rates, larger sizes and elongated shapes, such as Chaetoceros, groups light-stress tolerant ruderal species (i.e., R-strategists). Using conditions based on the measured light and nutrient levels prevailing prior to the 2013 spring bloom 27 , the results of our trait-based model show a large and rapid dominance of R-strategist diatoms (Supplementary Fig. 4 and5), which is not in line with the observations of the Minidiscus bloom. Given the nature of our model, this result suggests that some processes occurring in the field other than bottom-up factors may prevent the bloom of R-strategists, such as for instance a sharp increase in their mortality rate, which in turn may favour the emergence of C-strategists (i.e., Minidiscus) by escaping predation. When higher mortality rates are applied to the R-strategists, the model correctly simulates a rapid dominance of C-strategists. Although the numerical model is unable to determine which exact process is driving the prevalence of C-strategists over R-strategists in the field, it nonetheless offers a plausible hypothesis that a selective top-down control on larger diatoms is necessary given each strategist's defined niche and environmental parameters matching the DeWeX dataset. In situ, viral lysis, attacks by various pathogens [START_REF] Scholz | Zoosporic parasites infecting marine diatoms-A black box that needs to be opened[END_REF] , differential sensitivity to mixing, preferential grazing as well as larger differences in the traits between Minidiscus and others diatom genera are some of the known processes that may exert control on abundance of large diatoms. A transient lower vulnerability or accessibility of Minidiscus to grazers may also be an indirect mechanism involving its success during DeWeX.

It is known that Minidiscus can produce some protruding organic threads depending on turbulence conditions [START_REF] Verity | The Relative Food Value of Diatoms, Dinoflagellates, Flagellates, and Cyanobacteria for Tintinnid Ciliates[END_REF] and that these threads would increase its vulnerability to copepod grazing [START_REF] Gifford | Spines on diatoms: do copepods care ?[END_REF] . Unfortunately, these delicate threads are only preserved up to 3 months in glutaraldehyde and dissolve in less than 15 days in Lugol [START_REF] Gifford | Spines on diatoms: do copepods care ?[END_REF] , which made us unable to confirm their presence. The upscaling of mortality rates for large diatoms in the model is further supported by the observations made on the zooplankton community during DeWeX [START_REF] Donoso | Zooplankton community response to the winter-spring transition in the NW Mediterranean Sea[END_REF] . The deep convection zone where Minidiscus prevailed was characterized by high abundances of large herbivorous genera (such as Centropages, Calanus) while smaller grazers (e.g., Microsetella, Oncae) were much less abundant. Trophic pathways of phytoplankton community through the zooplankton food-web determined using stable isotopes during DeWeX, also revealed that the nanoplankton size-class made the largest contribution to zooplankton biomass during winter while the high convective area was characterized by the largest contribution of microplankton to zooplankton biomass during spring [START_REF] Hunt | Trophic pathways of phytoplankton size classes through the zooplankton food web over the spring transition period in the north-west Mediterranean Sea[END_REF] . Hence, an ecological framework for nanoplanktonic diatom blooms can be postulated from this simple trait-based model and supported by observation. Small diatoms would be likely dominant during the early bloom phase in both low and high convective areas but in the latter case only a strong top-down control on R-strategists (by viral/bacterial pathogenesis, parasites or grazing) would allow nano-sized species such as Minidiscus to reach the observed high bloom intensities.

The case for large-scale oversight of nano-diatoms

The genus Minidiscus, composed of only a few reported species, was initially described in 1973 in the Norwegian Sea [START_REF] Hasle | Some marine plankton genera of the diatom family Thalassiosiraceae[END_REF] . It is considered a cosmopolitan genus [START_REF] Hasle | The biogeography of some marine planktonic diatoms[END_REF] , having been observed in all oceanic basins, including northern and southern polar environments (Fig. 6).

However, this genus goes frequently unnoticed because it is easily overlooked in conventional microscopy, and is often misidentified and/or systematically under-sampled by net hauls due to inappropriate mesh sizes. When discrete water sampling is adequate, pico-and nano-sized diatoms may be enumerated using light microscopy but can only be determined to the genus and species levels using scanning electron microscopy (SEM) (Fig. 5), a difficulty that has already been emphasized for Minidiscus 9,[START_REF] Hasle | The biogeography of some marine planktonic diatoms[END_REF][START_REF] Kang | Planktonic centric diatom Minidiscus chilensis dominated sediment trap material in eastern Bransfield Strait, Antarctica[END_REF][START_REF] Kaczmarska | Morphological and molecular characteristics of selected species of Minidiscus (Bacillariophyta, Thalassiosiraceae)[END_REF] . Only a few other studies have documented significant bloom events of nano-sized diatoms. Blooms of Minidiscus spp. have for instance been reported during a 14-year survey in Monterey Bay, a coastal region characterized by strong upwelling events, an ecological situation similar to that of the DeWeX study 9 , as well as in other eutrophic areas of the Subarctic Pacific 5 , Norwegian Basin 10 , and Antarctic Peninsula [START_REF] Kang | Planktonic centric diatom Minidiscus chilensis dominated sediment trap material in eastern Bransfield Strait, Antarctica[END_REF][START_REF] Annett | Seasonal progression of diatom assemblages in surface waters of Ryder Bay, Antarctica[END_REF] . In the Mediterranean Sea, a massive bloom (~10 million cells L -1 ) of the nano-sized diatom Thalassiosira partheneia (<8 µm) was reported near the Gibraltar Strait 6 .

Large spring blooms of the tiny pennate diatom Nanoneis hasleae (2 × 5 µm) have also been reported on a few occasions in the North Atlantic and may be similarly overlooked on a global scale [START_REF] Savidge | The BOFS 1990 spring bloom experiment: Temporal evolution and spatial variability of the hydrographic field[END_REF][START_REF] Savidge | Phytoplankton production and biomass estimates in the northeast Atlantic Ocean, May-June 1990[END_REF] . Nano-planktonic biomineralizing algae, including diatoms, Parmales (siliceous plate-bearing phytoplankton <5 µm) and coccolithophores were also found to have been largely underestimated in the Southern Ocean [START_REF] Hinz | Comparative seasonal biogeography of mineralising nannoplankton in the Scotia Sea: Emiliania huxleyi, Fragilariopsis spp. and Tetraparma pelagica[END_REF] .

It therefore seems possible that Minidiscus together with other nano-planktonic sized diatoms, may be responsible for occasional massive blooms, which may go undetected due to either collection or identification biases. This is further exemplified in the global diatom database compiled during the MAREDAT project 4 , which presented close to 10,000 unique georeferenced locations and 607 reported diatom species since the 1930s, in which nano-sized genera such as Minidiscus, Minutocellus, Cyclotella, Lennoxia or Nanofrustulum are completely absent. This absence suggests that, if adequately sampled at all, they were either confused with similar looking species such as small Thalassiosira species, counted as undetermined species, or simply not even recognized as diatoms.

Tara Oceans metabarcoding data

The advent of high-throughput sequencing now allows unprecedented access to pico-and nano-plankton, as they can be detected even at low levels in filtered samples, thus circumventing both sampling and observational biases. Analysis of the metabarcoding-based descriptions of eukaryotic plankton by Tara Oceans [START_REF] De Vargas | Eukaryotic plankton diversity in the sunlit ocean[END_REF][START_REF] Malviya | Insights into global diatom distribution and diversity in the world's ocean[END_REF] indeed reveals the predominance of nano-sized diatoms such as Minidiscus (Fig. 7) and Minutocellus (Supplementary Fig. 6).

Their ubiquitous biogeographical distribution confirms and significantly extends previous observations, in particular regarding open ocean systems, as previous biogeography described in the literature evidenced Minidiscus mostly in coastal environments (Fig. 6). Significantly, Minidiscus is in the top 20 most abundant diatom genera (Supplementary Fig. 7) even though it has never been described as a major bloom-forming species [START_REF] Malviya | Insights into global diatom distribution and diversity in the world's ocean[END_REF][START_REF] Richter | Global plankton biogeography is shaped via ocean circulation dynamics[END_REF] . Supporting our previous observations made during DeWeX, the distributions from the Tara Oceans data show that the relative abundance of Minidiscus was the highest in the Mediterranean Sea, followed by the Southern Ocean and the North Atlantic Ocean (Supplementary Fig. 8a). Furthermore, the data reveals that Minidiscus is not only abundant at the surface but also in samples taken from deep chlorophyll maxima (DCM) contributing to what is known as the shade flora which benefits from the best ratio between sufficient light and upward limiting nutrient fluxes (Supplementary Fig. 8b). Size-class fractionations further confirmed that Minidiscus and Minutocellus were mostly represented in the smaller size-fractions, but also occurred in larger size classes probably due to cell aggregation (Supplementary Fig. 8c). A recent study has also transferred two Thalassosira species to the Minidiscus genus after fine structure examination and molecular sequence comparisons [START_REF] Park | Transfer of the small diatoms Thalassiosira proschkinae and T. spinulata to the genus Minidiscus and their taxonomic re-description[END_REF] , illustrating the difficulty of correct identification in this size-class. These recent changes have been included in the present Tara Oceans data analysis, but do not significantly change the global scale picture. However, while sequence information is available from M. trioculatus cultures, this is not yet the case for M. comicus implying that Tara Oceans data underestimates Minidiscus abundances. Also recently, Minutocellus has been shown to be a symbiotic species of the foraminifera Pararotalia calcariformata in the Mediterranean Sea [START_REF] Schmidt | Recent Invasion of the Symbiont-Bearing Foraminifera Pararotalia into the Eastern Mediterranean Facilitated by the Ongoing Warming Trend[END_REF] , which is another factor explaining why they may be overlooked in phytoplankton samples and why they are more important in the large size-fraction of the Tara Oceans samples than Minidiscus (Supplementary Fig. 7c). These results, together with previous observations, build a strong case for a large-scale oversight of these genera, together with many other nano-sized diatom species in the marine realm.

Contribution of nano-planktonic diatoms to carbon export

In order to examine the impact of small-sized diatoms to carbon export to depth, we collected samples from a deep sediment trap (2,400 m) moored at 42°N, 4.5°E from the end of March to the end of May 2013 during the DeWeX study, below the main area where Minidiscus reached ~6 million cells L -1 . Scanning Electron Microscopy (SEM) observations of samples from the three sediment trap samples collected during that period revealed the presence at high abundances of both M. trioculatus and M. comicus frustules (Table 2, Figs. 5e-h). Due to the low representativity of SEM counts (small area imaged and heterogeneous nature of the collected material), accurate Minidiscus flux calculations were not attempted.

However, given the time-lag between surface observations and sediment trap collection of Minidiscus, about one month assuming a bloom initiation in early March, a rough estimate indicates that a minimum sinking rate of 80 meters d -1 is likely, which is in the range of literature values for phytoplankton aggregates [START_REF] Alldredge | Direct observations of the mass flocculation of diatom blooms[END_REF][START_REF] Agustí | Ubiquitous healthy diatoms in the deep sea confirm deep carbon injection by the biological pump[END_REF] . It was also inferred from the vertical distribution and temporal evolution of particle concentrations in the water column during the DeWeX cruises [START_REF] Durrieu De Madron | Deep sediment resuspension and thick nepheloid layer generation by open-ocean convection[END_REF] that particulate matter was primarily composed of aggregates with settling rates of ~1 mm s -1 (i.e., 86 m d -1 ), which supports the previous hypothesis of a rapid sinking of Minidiscus as phytoplanktonic aggregates. Unidentifiable clumped aggregates were observed in SEM but could not be discriminated with certainty between faecal pellets or phyto-aggregates due to the long-term storage of these samples between sampling and observation (4 years). It was already noted using culture collections of M. trioculatus that single cells growing exponentially became aggregated in compact clusters during stationary phase [START_REF] Kaczmarska | Morphological and molecular characteristics of selected species of Minidiscus (Bacillariophyta, Thalassiosiraceae)[END_REF] . It is further known that these species are able to grow thin chitin threads protruding from the strutted processes of the valves, a feature considered unique to Thalassiosiroids 69 and modulated by turbulence [START_REF] Verity | The Relative Food Value of Diatoms, Dinoflagellates, Flagellates, and Cyanobacteria for Tintinnid Ciliates[END_REF] . Finally, M. comicus is known to form small colonies of 2-3 cells connected with extruded threads [START_REF] Kaczmarska | Morphological and molecular characteristics of selected species of Minidiscus (Bacillariophyta, Thalassiosiraceae)[END_REF] . Clearly, these features could if present, increase aggregation and sinking rates significantly [START_REF] Verity | The Relative Food Value of Diatoms, Dinoflagellates, Flagellates, and Cyanobacteria for Tintinnid Ciliates[END_REF][START_REF] Gifford | Spines on diatoms: do copepods care ?[END_REF] .

At least three other studies carried out at both northern and southern high latitudes have revealed high abundances and even a dominance of Minidiscus in sediment traps. The first study was carried out in relatively shallow sediment traps (100 to 200 m) during a temporal survey from 1985 to 1987 in a Vancouver Island inlet where abundant contributions of both M. chilensis and M. trioculatus were noted in spring and winter [START_REF] Hay | Distribution of diatom surface sediment assemblages within Effingham Inlet, a temperate fjord on the west coast of Vancouver Island (Canada)[END_REF] . Other studies carried out near the Antarctic Peninsula reported high abundances of M. chilensis in surface waters [START_REF] Kang | Planktonic centric diatom Minidiscus chilensis dominated sediment trap material in eastern Bransfield Strait, Antarctica[END_REF][START_REF] Annett | Seasonal progression of diatom assemblages in surface waters of Ryder Bay, Antarctica[END_REF] , and the annual survey conducted in 1998 in the Bransfield Strait revealed massive M. chilensis fluxes in 1,000 m deep trap samples, representing up to 87% of total diatom flux and associated to elevated BSi flux (~150 mg Si m -2 d -1 ) [START_REF] Kang | Planktonic centric diatom Minidiscus chilensis dominated sediment trap material in eastern Bransfield Strait, Antarctica[END_REF] .

In support of the hypothesis of a rapid sinking of nano-diatoms, Tara Oceans data show that both Minidiscus and Minutocellus cells are consistently present in multiple mesopelagic samples collected at around 700 m depth (Supplementary Fig. 8c) while, on average, diatoms represent up to 46% of photosynthetic read abundance at 700 m. Furthermore, with respect to samples collected in the photic zone, these small diatoms are present at higher proportions with respect to other diatom genera, e.g., Minidiscus is the eighth most abundant diatom genus in mesopelagic samples and the 21 st most abundant in photic zone samples (Supplementary Fig. 7). The conclusion from these multiple observations is therefore that small nano-sized diatoms are able to contribute to deep-sea carbon injection, even though this compartment is not usually considered to fuel export.

Discussion

Minidiscus was described for the first time in 1973 [START_REF] Hasle | Some marine plankton genera of the diatom family Thalassiosiraceae[END_REF] and has traditionally been considered a rare genus, but the results reported here show on the contrary that it ranks among the most abundant diatom genera in the global ocean. The most likely explanation for this apparent discrepancy is that traditional collection and identification methods were unable to detect and taxonomically resolve such small-sized species. Flow cytometric analyses do not resolve diatom taxonomy and only detect these small diatoms as undetermined nanoplanktonic eukaryotes, while the diagnostic pigments approach [START_REF] Vidussi | Phytoplankton pigment distribution in relation to upper thermocline circulation in the eastern Mediterranean Sea during winter[END_REF] usually attributes all fucoxanthin to the microphytoplankton size-class, which is obviously erroneous for the DeWeX case study. Much like the application of flow cytometry was required to detect the significance of Prochlorococcus in the global ocean [START_REF] Chisholm | A novel free-living prochlorophyte abundant in the oceanic euphotic zone[END_REF] , the advent of improved genomic sequencing performed on a global scale and systematic coupling of faster SEM techniques to regular optical microscopy should help to further resolve this diatom size class in coming years. But clearly, quantitative physiological rates will be needed to improve model parameterizations.

Diatom cell sizes, as well as their Si/C cellular quotas, are key variables controlling their sinking fluxes [START_REF] Quéguiner | Iron fertilization and the structure of planktonic communities in high nutrient regions of the Southern Ocean[END_REF][START_REF] Assmy | Thick-shelled, grazer-protected diatoms decouple ocean carbon and silicon cycles in the iron-limited Antarctic Circumpolar Current[END_REF] . In the North Atlantic in 1989-1990, a nearly two-fold reduction in carbon flux to deep sediment traps occurred during two successive years following the spring diatom bloom 7 . In 1990, the spring bloom was dominated by the tiny pennate Nanoneis hasleae forming a bloom as large as 50,000 km 2 visible from space [START_REF] Savidge | Phytoplankton production and biomass estimates in the northeast Atlantic Ocean, May-June 1990[END_REF] , while it was dominated by a large size chain-forming Chaetoceros assemblage in the previous year 7 . This was one of the first studies to document a direct effect of the community structure within the same PFT on the modulation of carbon export fluxes to depth. This scenario was consistent with the classical opposition between small solitary diatoms carrying no protective spines correlated to slower sinking rates and faster C remineralization (through either bacterial lysis or grazing) in the water column compared to larger chain-forming and/or spiny cells, prone to aggregation and fast sinking. The data collected during the DeWeX spring bloom from deep sediment traps adds, however, a further aspect to this scenario, demonstrating that they are able to sink out of the surface layer in aggregated form at high sinking rates contrary to the common assertion that they are more likely to be entirely remineralized within the microbial loop in the water column. There is, therefore, a need to better constrain sedimentation rates and aggregation processes from different sizes of diatoms. This focus probably needs to be extended to other nanoeukaryotic groups, such as Parmales, another elusive siliceous scale-bearing phytoplankton of 2-6 µm diameter, whose importance has likely been underestimated [START_REF] Hinz | Comparative seasonal biogeography of mineralising nannoplankton in the Scotia Sea: Emiliania huxleyi, Fragilariopsis spp. and Tetraparma pelagica[END_REF] . Nano-diatoms and Parmales are ballasted by their mineral casings, which should lead to a different fate in the water column with respect to other non-siliceous organisms of the same size-class. The possibility for picoplankton to escape the microbial loop and fuel export was already demonstrated by sediment trap data 13 but to date it has not been considered extensively. We further propose that the diatom group represented in models as a single PFT should be redefined to better include various life strategies of survival and growth, such as in trait-based models, and that the nanophytoplankton group also needs to be connected to the siliceous pathway.

Another outcome of the modelling study is that traits of diatoms concerning their relationships to predators need to be further explored. Size-selective predation, which can include zoosporic parasitism [START_REF] Scholz | Zoosporic parasites infecting marine diatoms-A black box that needs to be opened[END_REF] , rather than competition for resources may be a major selective pressure for diatoms, driving their ecological properties 3 . At least two other studies reporting spring bloom abundances of Minidiscus sp. in the Subarctic Pacific 5 and in the Norwegian basin 10 displayed similar context and pointed towards the same explanation. Both studies argued that despite generous supplies of nutrients, usually favorable to the growth of large cells, the net accumulation of small-sized diatoms could be a result of selective grazing pressure on larger cells and possibly linked to a lack of seed populations from coastal environments during the initial stages of the bloom. None of these studies, including ours, were able to precisely determine the interspecific predator-prey relationships between zooplankton groups and distinct diatom species. Indeed, determining trophic links in the natural environment remains a major challenge and constitutes a bottleneck in our understanding of marine planktonic ecosystems. Understanding of accessibility, vulnerability, prey-induced biases in the predator perception and trophic relations with organisms other than copepods is still in its infancy and needs to be scaled up. The same is true about symbiotic interactions such as the one recently discovered between Minutocellus and a foraminifera. The advent of improved genomic sequencing and systematic coupling of faster SEM techniques to regular optical microscopy should help to further resolve this diatom size class in coming years.

Altogether, these observations challenge the common assumption that small (defined as >10 µm) to large-sized chain-forming diatoms are the usual initial bloomers in frontal areas and turbulent environments following winter fertilization 2 . We propose that Minidiscus and other overlooked minute diatom taxa (<5 µm) may be occasional major contributors to spring blooms in turbulent nutrient-rich environments of various coastal and offshore oceanic regions and that, upon aggregation, they may also contribute significantly to carbon export. 1.

METHODS

Satellite products

Satellite

DeWeX cell counts and taxonomical determination

Water samples (125 mL) were collected during the DeWeX cruises at the surface using Niskin bottles mounted on a CTD frame and immediately fixed with 0.4 mL acidified Lugol (100g KI, 50 g I, 100 mL glacial acetic acid) and stored at 4°C. Diatoms were identified and enumerated by light microscopy at X4400 and X8800 magnification depending on size on a Nikon TE-2000 microscope in 50 or 100 mL Utermöhl sedimentation chambers depending on diatom abundance. Large and numerically rare taxa were counted in the entire settling chamber, while smaller dominant taxa such as Minidiscus were determined by light microscopy at X 8800 by counting two cuve diameters (i.e. 1/33 of the cuve area), which amounts to a volume of 3 mL counted in the case of 100 mL sedimented samples and 1.5 mL in the case of 50 mL sedimented samples. Minidiscus trioculatus and comicus were taxonomically determined using an FEI Teneo Scanning Electron Microscope (SEM) in one of the very high abundance samples (station 99, leg 2, 24 April 2013). All similar looking small centrics subsequently observed by light microscopy were assumed to be Minidiscus.

Data for microscopic diatom counts is available at http://www.obs-vlfr.fr/proof/ftpfree/dewex/db/data/DIATOMS/.

Semi-continuous automated flow cytometry

Phytoplankton cells were counted semi-continuously (one sample every hour during day time and every 2 hours during night time) using an automated Cytosense flow cytometer (Cytobuoy, NL) connected to a continuous sea water flow-through pumped at 3 m depth. In order to ensure an accurate position and limit the distance traveled while analyzing the sample, the Cytosense pumped its sample from an isolated chamber of 300 mL filled in less than 30 s.

The chamber was opened to the flow-through in between each analysis. The Cytosense instrument is specially adapted to detecting wide in-situ phytoplankton wide size ranges and abundances. Each sample was driven towards the flow cell by a calibrated peristaltic pump running between <1 μL s -1 and 20 μL s -1 from which the volume analysed was calculated.

Every particle (cell) in suspension in the sample was then separated through a laminar flow thanks to a 0.2 µm filtered sheath fluid made of sea water and crossed a laser beam (Coherent, 488 nm, 20 mW). The instrument recorded various pulse shapes emitted while the cells were crossing the laser beam, resulting in: forward angle light scatter and sideward angle light scatter as well as red, orange and yellow fluorescence bands in the size range 1-800 µm in width and a few mm in length for chain forming cells. Laser scattering at small angles was collected by two distinct photodiodes to check for the sample core alignment. Two trigger levels on the red fluorescence were applied for distinction between highly concentrated and picophytoplankton and cyanobacteria groups (trigger level FLR 8 mV, sampling at a flow rate of 10 mL 3 s -1 analyzing approx. 1mL), and lower concentrated nano-and microphytoplankton (trigger level FLR 10 mV, at a flow rate of 10 mL 3 s -1 analyzing approx.

Biogeochemical determinations

Biogenic silica samples (2L) were collected in the same Niskin bottles as cell counts and filtered onto 0.8 µm, 47 mm polycarbonate filters, dried at 60°C for 24h and stored at room temperature. As samples were coastal and susceptible to receive large terrigeneous riverine inputs, they were analyzed in the laboratory following the three-step digestion method allowing for determination of biogenic silica corrected for the interference from lithogenic silica [START_REF] Ragueneau | A new method for the measurement of biogenic silica in suspended matter of coastal waters: using Si:Al ratios to correct for the mineral interference[END_REF] . Data for biogenic silica concentrations are available at http://www.obs-vlfr.fr/proof/ftpfree/dewex/db/data/Si/. Particulate Organic Carbon (POC) from water samples was analyzed on GF/F filters on a CHN elemental analyzer. Nutrient samples were stored in 20 mL polyethylene vials and immediately frozen at -20°C until analysis. In the laboratory, samples were analyzed by colorimetry on a Seal-Bran-Luebbe AutoAnalyzer AA3 HR [START_REF] Aminot | Dosage automatique des nutriments dans les eaux marines : méthodes en flux continu[END_REF] .

Trait-based model of phytoplankton strategists

A trait-based model of a phytoplankton community is used in the present study to explore hypotheses related to the occurrence of the massive Minidiscus bloom observed during the DeWeX 2013 campaign. Four types of phytoplankton strategists are represented according to their distinctive traits with regards to the available amounts of light and nutrients. The difference in these physiological traits between phytoplankton types is based on the Reynolds' C-S-R classification 30 , and combination of these traits within a phytoplankton genus enables to determine its ecological niche. The main assumption of the Reynolds' model is that a bloom of a given strategist occurs when the environmental conditions (light, nutrients) match its ecological niche. In the present study, the following four strategists are defined.

SS-strategists are recurrent nutrient stress tolerant genera in high light environments such as the cyanobacteria Synechococcus that are constitutive members of the picophytoplankton in the Mediterranean Sea [START_REF] Mella-Flores | Is the distribution of Prochlorococcus and Synechococcus ecotypes in the Mediterranean Sea affected by global warming?[END_REF] . R-strategists optimally grow in low light environments but they require high nutrients in order to form bloom events. This group incorporates many genera of large diatoms with elongated body shapes such as Chaetoceros, Leptocylindrus, Guinardia, all of which are genera observed during the spring leg of the DeWeX cruise (see Results section). In our study, R-strategists represent large diatoms with fast sinking rates generally observed during spring blooms at mid-latitudes. The last group is that of C-strategists (colonist genera). The physiological and morphological traits common to all genera of this group are small sizes in the nanoplanktonic spectra, flat cylindrical body shapes, and some fast-growing abilities when nutrients and light are abundant. The choice was made to divide C-strategists into two categories according to close traits: on the one hand, C1-strategists gather autotrophic flagellates and small-sized cryptophyceae that showed a marked presence during the spring leg of DeWeX cruise [START_REF] Dugenne | Dynamique du phytoplancton en mer Méditerranée: Approches par mesures à haute fréquence, modélisation et statistiques bayésiennes[END_REF] , on the other hand, C2-strategist represents Minidiscus diatoms.

The two latter strategists, C1 and C2, are considered to be in the same range of size and to have similar traits [START_REF] Litchman | Trait-Based Community Ecology of Phytoplankton[END_REF] . In our model, some differences in traits are however assumed and they go beyond just a difference in a reliance or not on Si uptake for the C2-and C1-strategists. In particular, the C2-strategist is also considered more tolerant to light stress and less tolerant to nutrient stress than C1-strategists. These different abilities are based on knowledge of the spring succession of the phytoplankton community acquired by remote sensing [START_REF] Uitz | Estimates of phytoplankton class-specific and total primary production in the Mediterranean Sea from satellite ocean color observations[END_REF] and in situ observations [START_REF] Marty | Seasonal and interannual variations in phytoplankton production at DYFAMED time-series station, northwestern Mediterranean Sea[END_REF] in the northwestern Mediterranean Sea. These studies indicate that the first community to peak is generally diatoms from January to March followed several weeks later by a peak of nano-eukaryotes at the beginning of the stratification period when surface nutrients decrease. This is the usual pattern of the second stage of the bloom dominated by nano-eukaryotes (i.e. autotrophic flagellates, small cryptophyceae) that has typically been observed in various oceanic areas at mid-latitudes [START_REF] Bidigare | Evidence for phytoplankton succession and chromatic adaptation in the Sargasso Sea during spring 1985[END_REF][START_REF] Bustillos-Guzman | Specific phytoplankton signatures and their relationship to hydrographic conditions in the coastal northwestern Mediterranean Sea[END_REF] . As suggested in the study of Marty et al. ( 2002) [START_REF] Marty | Seasonal and interannual variations in phytoplankton production at DYFAMED time-series station, northwestern Mediterranean Sea[END_REF] , nano-eukaryotes would flourish during the time period for which successive events of stratification and destratification of the water column accompanied with weak injections of nutrients from deep layers occur. These differences in traits involve some emergent properties specific to each strategist such as, for example, their ability to grow differently depending on light and nutrient availability (see net photosynthetic growth rates in Supplementary Table 5). The choices of parameters in the trait-based model are crucial because they determine in fine the differences in functional traits between strategists. These choices have been made on the basis of different sources for usual allometric rules between functional traits and size or biovolume [START_REF] Terseleer | Trait-based representation of diatom functional diversity in a plankton functional type model of the eutrophied southern North Sea[END_REF][START_REF] Lichtman | The role of functional traits and trade-offs in structuring phytoplankton communities: scaling from cellular to ecosystem level[END_REF] as well as different types of experimental data (field, laboratory assays). All the sources of parameters are indicated in the Suppl. Tables 1234).

For example, in the model, the half-saturation constant for nitrogen uptake increases with cell size while the photosynthetic efficiency (given in our model by the product of maximum quantum yield by Chl-specific absorption coefficient) decreases along cell size. In the same way, the choices of values for internal quotas are based on the observations of decreasing stoichiometric molar quotas along increasing cell volumes 23,[START_REF] Montagnes | Effect of temperature on diatom volume, growth rate, and carbon and nitrogen content: Reconsidering some paradigms[END_REF] and from the use of the combined dataset of carbon cell contents vs. cell volume [START_REF] Lichtman | The role of functional traits and trade-offs in structuring phytoplankton communities: scaling from cellular to ecosystem level[END_REF][START_REF] Mullin | Relationship between carbon content, cell volume, and area Inphytoplankton[END_REF] .

However, when a new strategist (nano-diatoms in the present study) is incorporated in a trait-based model, it can often be difficult to allocate an accurate value to each of its physiological parameters owing to insufficient experimental information. In this case, the choices of the latter parameters are rather made on a qualitative idea that the trait of the strategist should be affected by environmental conditions. The difference in mortality rates between C1-and C2-strategists illustrates this point: the C1-strategist is assumed to represent a heterogeneous mix of nano-eukaryotes while the C2-strategist is a numerical representation of closely related species of one genus (i.e. Minidiscus). It is hypothesized that the mortality processes would have lower impacts on a heterogeneous community of plankton species because if one species collapses under a viral attack, for example, another one will arise, which enables the maintenance of numerous nano-eukaryotes. This mechanism is less likely to occur when a more homogeneous group such as Minidiscus is considered.

The type of trait-based model used here has been implemented in the biogeochemical modular numerical platform Eco3M [START_REF] Baklouti | Investigation of mechanistic formulations depicting phytoplankton dynamics and description of a new model[END_REF][START_REF] Baklouti | Investigation and sensitivity analysis of a mechanistic phytoplankton model implemented in a new modular numerical tool (Eco3M) dedicated to biogeochemical modelling[END_REF] . The main characteristics of the model are mentioned hereafter. Each group of strategists is represented through several states variables of C, N, P, Si and Chl contents and intracellular ratios can thus be computed at each time point allowing a non-redfieldian behavior of the model. They have the ability to take up dissolved inorganic and organic matter (i.e. mixotrophy) and to exude organic matter in order to adjust their stoichiometric internal requirements. A heterotrophic bacteria compartment is also considered for their ability to recycle organic matter into inorganic nutrients. Compartments of inorganic nutrients such as nitrate, phosphate and silicic acid as well as of organic matter are represented. Grazers and viruses of phytoplankton are not explicitly accounted for in the model but their processes of control are implicitly represented through mortality rates. All the mathematical formulations of processes are provided in details in Campbell et al. (2013) [START_REF] Campbell | Nutrients and plankton spatial distributions induced by a coastal eddy in the Gulf of Lions[END_REF] .

Two numerical experiments were conducted to test the impact of these processes on the temporal dynamics of the different strategists. In particular, the mortality rate of R-strategists has been thus modulated upward (HCC: High Control Conditions) or downward (LCC: Low Control Conditions, standard simulation). In the HCC condition, the mortality rate corresponds to a disappearance of biomass by 25% d -1 while this rate is 10% d -1 in the LCC condition according to the study of Broglio et al. ( 2004) [START_REF] Broglio | Trophic impact and prey selection by crustacean zooplankton on the microbial communities of an oligotrophic area (NW Mediterranean Sea)[END_REF] . Given the short simulation time (40 days) variations in water temperature are neglected and no temperature-dependent processes are then considered in the model formulations. This assumption is corroborated by field observations that show temperature variation lower than 1°C over the time of the simulated period [START_REF] Waldman | Modeling the intense 2012-2013 dense water formation event in the Northwestern Mediterranean Sea: Evaluation with an ensemble simulation approach[END_REF] .

Model parameters characterizing each group of strategists and initial conditions in nutrients, living biomasses and organic matter are given in Supplementary Table All simulations for the present study were performed under a constant irradiance of 300 W m -2 and a 12h/12h day/night cycle corresponding to the beginning of spring at mid-latitudes.

Time step of the model is 300 seconds. The time of simulation is 40 days (roughly corresponding to the period of bloom during DeWeX) from the end 27 . From this last event, it is assumed that a light vs. nutrient optimal tradeoff exists for the phytoplankton bloom without any further variation of the physical environment (e.g. nutrient supplies, light variations). In this theoretical context, a trait-based model without considering any physical forcing (0D) can be used over the simulation period. Although useful to understand community dynamics, it does limit the model's ability to correctly estimate in situ biomass levels because no loss terms due to physics are included, while considerable turbulent mixing and advection are known to occur in the area. Model parameters and initial conditions of state variables are presented in Supplementary Tables 1 to 5.

Sediment trap data

A short mooring line (~50 m long) was deployed at 42°01'N -4°48'E (depth of 2400 m). It was equipped with a Technicap PPS-3 sediment trap (collecting area of 0.125 m 2 , aspect ratio of 2.5, and 12 collecting cups) at 30 m above the seabed. The trap samples were collected with sampling interval between 15 and 23 days. Prior to deployment, the sampling bottles were filled with 0.45 µm filtered seawater containing sodium borate-buffered formalin to yield a final concentration of 5% formalin to prevent in situ microbial decomposition. Upon recovery, samples were stored in the dark at 4°C 95 . 1 mL aliquots were filtered onto the center of 0.4 µm polycarbonate filter using a filtering funnel of 6 mm aperture, and carefully rinsed with DIW water, then dehydrated in increasing series of ethanol 30%, 50%, 70%, 80%, 90%, 100% during 10 mn for each step. Samples were completely dried overnight, mounted on aluminum stubs with double sticky carbon tabs and sputter-coated with gold for 10 min.

Samples from each of the three available trap samples were analyzed with a FEI Teneo SEM.

Tara Oceans V9-18S rDNA metabarcodes

We used the global metabarcoding data set (EBI accession number PRJEB16766) generated from the biological samples collected from 146 sampling locations during the Tara Oceans expedition 12,96,97 . We extracted ribotypes that were assigned to Minidiscus and Minutocellus from the three depths -surface (SRF), deep chlorophyll maximum (DCM) and mesopelagic (MESO)-within the different size class filters (ranging from 0.8 -2,000 µm, with the smallest fraction being 0.8 to 5 µm). The taxonomic assignations were done using PR2 reference database 98 A spring bloom of Minidiscus (2-5 µm) was reported during leg 2, at 17 out the 32 stations sampled, principally over the deep winter convection area and in an anticyclonic eddy South of the study area. Small yellow circles correspond to abundances comprised between 5,000 and 100,000 cells L -1 , medium red circles to between 100,000 and 1,000,000 cells L -1 and large purple circles to between 1 and 6 million cells L -1 . The northeastern area where BSi also accumulates during leg 2 is due to larger microplanktonic sized diatoms such as Guinardia delicatula. showing the impossibility of identifying it with the latter technique, while it remains possible to count it and compare with parallel SEM identification. The yellow Lugol stain background was removed using the camera's autowhite function. Scale bar is 10 µm. Silicon mmolSi m -3 0.665E -4

  5 mL). Different sets of 2D projections of the data were plotted in Cytoclus® software to manually gate the various phytoplankton groups. A combination of standard beads (PolyScience® Yellow Green Polystyrene 2 μm, 3 μm, 6 μm, 10 μm, 20 μm diameter) was regularly analysed to monitor the stability of the flow cytometer. The volume analysed was weight calibrated.

1

 1

  . The standard run is launched from initial conditions in nutrients corresponding to those observed during DeWeX 94 just at the end of the high convective episode (HCNC: High Convective Nutrient Condition) with [H4SiO4]=7.72 µM, [NO3]=8.40 µM and [PO4]=0.39 µM. Another run is launched with a reduced supply of nutrients characterizing reduced convective events (LCNC: Low Convective Nutrient Condition). These concentrations were chosen in the PERSEUS database for a low convective year (1990) and were set at [H4SiO4]=2.10 µM, [NO3]=2.66 µM and [PO4]=0.09 µM.

Figure 1 :

 1 Figure 1: Surface chlorophyll and geostrophic circulation during DeWeX in the North Western Mediterranean Sea. Images are averages of 8 days composites for both satellite-derived chlorophyll a and geostrophic velocities (in m s -1 ) over time periods corresponding to the DeWeX cruises a. leg 1 (03-21 February 2013) and b. leg 2 (05-24 April 2013) with a resolution of 4 km. Black dots correspond to CTD (Conductivity Temperature Depth) casts. The black contour line shows the impoverished area with Chlorophyll a (Chla) during leg 1 (<0.2 mg Chla m -3 ) and indicates the location of the winter deep convection area, which extended until the seafloor (2,400m) in 2013. Station numbers are labelled where discrete phytoplankton samples were collected for diatom cell counts.

Figure 2 :

 2 Figure 2: Biogenic silica distribution during DeWeX and Minidiscus distribution and abundance. Surface distribution of biogenic silica in blue (Ocean Data View interpolation)

Figure 3 :

 3 Figure 3: Vertical Si-N nutrient ratio profiles in different regions of the DeWeX cruise. H4SiO:NO3 -(mol:mol) ratio profiles in three station clusters (NC: No Convection, LC: Low Convection, HC: High Convection) based on hierarchical clustering of the depth extent of the winter mixing 11 .

Figure 4 :

 4 Figure 4: Minidiscus spp. in light microscopy. The dominating nano-sized Minidiscus centric diatoms (2-5 µm diameter) seen in light microscopy at station 74 (5.8 million cells L -1 )

Figure 5 :

 5 Figure 5: Minidiscus comicus and Minidiscus trioculatus in surface water and sediment trap samples during spring 2013. a,b. M. comicus, c,d. M. trioculatus observed in Scanning Electron Microscopy (SEM) at station 99, located at 42°N, 5°E on 24 th April 2013 at the surface. e,f. M. comicus, g,h. M. trioculatus observed in SEM in three deep sediment traps samples (2,400 m) at 42°N, 4.5°E covering 30 th March to 22 nd May 2013. All scale bars are 1 µm.

Figure 6 :

 6 Figure 6: Biogeographical distribution of Minidiscus across ocean basins. Information regarding the biogeographical distribution of Minidiscus spp. was derived from a literature review (from references 19, 37-55).

Figure 7 :

 7 Figure 7: Biogeographical distributions of Minidiscus from metabarcoding data. Biogeographical distributions at the surface (SRF) and Deep Chlorophyll Maximum (DCM) depths of genus abundance and diversity of Minidiscus as relative abundance of total diatom reads (a-c) and as relative abundance of total phytoplankton reads (b-d) in the 0.8 to 5 µm size fractions collected during the Tara Oceans expedition (2009-2013) 96 . The variation in

  which has six reference sequences from Minidiscus trioculatus, 2 from Minidiscus sp., and one from an environmental sequence. This article is contribution #XX of Tara Oceans. M.T. and G.G. thank Dominique Lefèvre and Caroline Bachet for setting up the continuous seawater supply for automated multiparametric monitoring during the ship navigation and for help in the autonomous flow cytometer deployment. The project leading to this publication has received funding from European FEDER Fund under project 1166-39417.

	conducted using open source R version 3.3.1 (data and R-script available at primary production: a case study in the North Atlantic. J. Geophys. Res. 110, C07S12 fellowship during the 2016-2017 academic year.
	https://figshare.com/s/6f3190905564f6c6e20c). (2005).
	95. Heussner, S., Ratti, C. & Carbonne, J. The PPS3 time-series sediment traps and trap
	sample processing techniques used during the ECOMARGE experiment. Cont. Shelf Res.
	10, 943-958 (1990).
	96. Pesant, S. et al. Open science resources for the discovery and analysis of Tara Oceans
	data. Sci. data 2, 150023 (2015).
	97. De Vargas, C. Audic, S. & Tara Oceans Consortium, Coordinators; Tara Oceans
	Expedition, Participants (2017): Total V9 rDNA information organized at the OTU level
	(Database W5). PANGAEA, https://doi.org/10.1594/PANGAEA.873275.
	98. Guillou, L. et al. The Protist Ribosomal Reference database (PR2): A catalog of
	unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic
	Acids Res. 41, 597-604 (2013).
	END NOTES
	From the photic zone, for Minidiscus, a total of 908 different V9 rDNA ribotypes (represented
	by 66,043 reads) were retrieved from the 81 communities representing the smallest size
	fraction (0.8 to 5 µm), while for Minutocellus we retrieved 776 V9 rDNA ribotypes
	(represented by 35,108 reads) from the 118 communities representing the smallest size
	fraction (0.8 to 5 µm). From the mesopelagic zone, a total of 49,239 reads for Minidiscus and
	27,181 reads for Minutocellus were retrieved from 79 size-fractionated samples. Relative
	abundance was calculated with respect to total diatom reads and to total phytosynthetic reads,
	which comprised reads assigned to major phytoplanktonic groups 44 , namely Bacillariophyta,
	Chlorophyceae,	Cryptophyta,	Dictyochophyceae,	Dinophyceae,	Haptophyta,
	Mamiellophyceae, Pelagophyceae and Raphidophyceae. Exponentiated Shannon-Weiner H'
	diversity index was used as an estimate of diversity at each station. All the analyses were

Table 1 : Minidiscus spp. cell counts and relative contribution to abundance and biomass. Contribution

 1

	to total diatom

Table 2 :

 2 Observations of Minidiscus valves in the LIONCEAU sediment trap samples during DeWeX. The LIONCEAU sediment trap was located at 42°N 4.5°E at 2,400 m depth at the center of the DeWeX deep vernal convection area and close to where the Minidiscus bloom was most elevated in surface samples. Minidiscus valves were searched in the sediment trap samples in SEM and were found to be abundant in all three.

	Trap sample (42°N, 5°E, 2400 m)	Date of sampling	Minidiscus valves
	LIONCEAU 9	31/03/13-15/04/13	abundant
	LIONCEAU 10	15/04/13-30/04/13	abundant
	LIONCEAU 11	30/04/13-23/05/13	abundant

Table 2 :

 2 Numerical parameters of the trait-based model.

	Phytoplankton	Unit	R-strategist C1-strategist C2-strategist SS-strategist	Ref
	Max. quantum yield	mmolC J -1	2.55E -4	1.80E -4	2.00E -4	1.64E -4	1,2,3
	Chl-specific absorption coeff.	m 2 mg -1	0.015	0.030	0.025	0.050	1,2
	Photosystems renewal time	d	2.30E -8	5.44E -8	2.30E -8	8.10E -8	4
	Photosystems cross-section	m 2 J -1	10.9	15.8	13.7	21.0	5,6
	PSII damage rate	-	2.6E -8	2.6E -8	2.6E -8	2.6E -8	7
	Rate of repair of damaged PSII	d -1	2.0E -9	2.0E -9	2.0E -9	2.0E -9	7
	Min. internal N/C quota	molN molC -1	0.050	0.100	0.070	0.115	8,9,10,11
	Max. internal N/C quota	molN molC -1	0.170	0.215	0.180	0.229	9,10,11,12,13
	Min. internal P/C quota	molP molC -1	0.0031	0.0062	0.0044	0.0071	10,11,14,15
	Max. internal P/C quota	molP molC -1	0.0100	0.0130	0.0110	0.0143	10,11,14,15
	Min. internal Si/C quota	molSi molC -1	0.040	-	0.056	-	1,15
	Max. internal Si/C quota	molSi molC -1	0.136	-	0.144	-	1,15
	Max. internal Chl/N quota	molChl molN -1	3.00	2.55	2.70	2.20	16,17,18
	Respiration cost for growth	-	0.20	0.30	0.20	0.32	17,19
	Half sat. constant for NO3	mmolN m -3	3.50	1.50	1.75	0.73	8,15,20,21
	Half sat. constant for NH4	mmolN m -3	0.18	0.12	0.15	0.07	8,20,21
	Half sat. constant for PO4	mmolP m -3	0.200	0.055	0.070	0.008	8,15,20,22
	Half sat. constant for silicic acid	mmolSi m -3	2.75	-	1.20	-	8,15
	Constant in the quota function for silicic acid uptake	molSi molC -1	0.10	-	0.10	-	23
	Shape constant in the quota function for silicic acid uptake	-	10.	-	10.	-	23
	Half sat. constant for DON	mmolN m -3	2.25	1.50	2.05	0.85	8,21
	Half sat. constant for DOP	mmolP m -3	0.65	0.155	0.55	0.085	8,22
	Resp. cost for NO3 uptake	molC molN -1	0.397	0.397	0.397	0.397	19
	Resp. cost for NH4 uptake	molC molN -1	0.198	0.198	0.198	0.198	20
	Resp. cost for PO4 uptake	molC molP -1	0.350	0.350	0.350	0.350	21
	Resp. cost for silicic acid uptake	molC molSi -1	0.140	-	0.140	-	22
	Mortality rate	d -1	0.10 , 0.25(HCC)	0.02	0.10	0.05	24,25,26

27 Supplementary 24 Supplementary

Table 3 : Numerical parameters of the trait-based model. SupplementaryTable 4 : Initial conditions for the state variables of the trait-based model under high and low convective nutrient conditions (HCNC and LCNC, respectively).

 34

	Phytoplankton	Unit	R-strategist	C1-strategist C2-strategist SS-strategist
	Carbon biomass	mmolC m -3	0.156	0.200	0.175	0.100
	Nitrogen biomass	mmolN m -3	0.024	0.030	0.026	0.015
	Phosphorus biomass	mmolP m -3	0.0015	0.0019	0.0017	0.0009
	Biogenic silica content	mmolSi m -3	0.019	-	0.020	-
	Chlorophyll biomass	mg m -3	0.038	0.048	0.042	0.024
	Heterotrophic bacteria
	Carbon biomass	mmolC m -3	30
	Nitrogen biomass	mmolN m -3	7
	Phosphorus biomass	mmolP m -3	0.66
	Inorganic Nutrients		HCNC	LCNC
	Nitrate	mmolN m -3	8.40	2.66
	Ammonium	mmolN m -3	0.001	0.004
	Phosphate	mmolP m -3	0.39	0.09
	Silicic acid	mmolSi m -3	7.72	2.10

Acknowledgements

We thank the captain and crew of the R/V Le Suroît for their assistance during the DeWeX cruises. We acknowledge sponsorship from the MISTRALS-MERMEX, MOOSE, and Tara Oceans projects. Original data used in this work are available through the MERMEX-DEWEX (http://mistrals.sedoo.fr/MERMeX/) and MOOSE (Mediterranean Ocean Observing System on Environment; http://mistrals.sedoo.fr/MOOSE/), and Tara Oceans (https://www.ebi.ac.uk/metagenomics/) databases, cruises DeWeX-MERMEX 2013 LEG1 (http://doi.org/10.17600/13020010) and LEG2 (http://doi.org/10.17600/13020030) and sediment trap in the convection zone (http://doi.org/10.17882/45980). For SEM imagery, we thank the CINAM for the use of their SEM platform as well as the PICsL Imaging Facility, member of the national infrastructure France-BioImaging supported by the French National Research Agency (ANR-10-INBS-04). We thank Adriana Zingone for help in identifying Minidiscus species. C.B. acknowledges funding from the ERC Advanced Award Diatomite, EU FP7 grant MicroB3 (No.287589), the Louis D Foundation, and the French Government Investissements d'Avenir programmes MEMO LIFE (ANR-10-LABX-54), PSL* Research University (ANR-1253 11-IDEX-0001-02), and OCEANOMICS (ANR-11-BTBR-0008). CB also thanks the Radcliffe Institute of Advanced Study at Harvard University for a scholar

Data availability statement

The authors declare that all data supporting the findings of this study are available within the paper and its supplementary information files.

F.D. wrote the modelling section, Supplementary Figs. 45. And Supplementary Tables 12345.

All authors discussed and commented on the manuscript.

Competing interests

The Authors declare no competing interests. 2). Four types of phytoplankton strategists are represented according to their distinctive traits with regards to available amounts of light and nutrients. The difference in these physiological traits between phytoplankton types is thus based on the Reynolds' C-S-R classification 14 . The combination of these traits within a phytoplankton genus enables to determine its ecological niche. The main assumption of the Reynolds' model is that bloom of a given strategist occurs when the environmental conditions (light, nutrients) match its ecological niche. In the present study, the following four strategists are defined: (i) SS-strategists are recurrent nutrient stress tolerant genera in high light environments such as the cyanobacteria Synechococcus that are constitutive of a major part of picophytoplanktonic group in the Mediterranean Sea. (ii) R-strategists optimally grow in low light environments but they require high nutrients in order to form bloom events. This group gathers many genera of large diatoms with elongated body shapes such as some Chaetoceros. In our study, R-strategists represent large diatoms with fast sinking rates generally observed during spring blooms under mid-latitudes. The last group is that of C-strategists Supplementary Figure 6

Supplementary Information

SUPPLEMENTARY FIGURES

SUPPLEMENTARY TABLES

Supplementary Table 1: Numerical parameters of the trait-based model.

Supplementary Table 5:

Net photosynthetic rates of modeled strategists during the simulations. Values of net photosynthetic growth rates (d -1 ) of each strategist at three different times (at noon on the 10th, 15 th and 30 th days) of the simulation in Low Control condition (LCC) and High Control condition (HCC), under high and low convective nutrient conditions (HCNC and LCNC respectively). The net growth rates of all strategists are realistic and within the orders of magnitude of the observed datasets 1,15,31


Vincent Fauvelle

Angel Belles

Hélène Budzinski

Nicolas Mazzella

Martin Plus

Simulated conservative tracer as a proxy for S-metolachlor concentration predictions compared to POCIS measurements in Arcachon Bay

Keywords: Passive sampling, POCIS, Mars-2D, contaminant, monitoring, coastal area, pesticides, Smetolachlor

The work presented here aims at comparing monitoring of S-metolachlor, the major pesticide in use in the Arcachon Bay (South West of France, transitional coastal area), by chemical analysis (monthly passive sampling) and contaminant dissipation modeling from sources (Mars-2D model). The global strategy consisted in i) identifying the major sources of Smetolachlor to the Bay, ii) monitoring these sources for 12 months, and iii) comparing modeled data in the Bay based on measured inputs, to chemical measurements made inside the Bay along with the 12-month source monitoring. Results first showed that the major S-metolachlor surface inputs to the Arcachon Bay are mainly from one single source. Modeled and measured data were in good agreement at 5 sites in the Bay, both in terms of concentration range and seasonal trends. Modeling thus offers a cost-effective solution for monitoring contaminants in transitional waters, overcoming in addition the technical limitations for measuring pg L -1 or lower levels in coastal waters. However, we highlighted that secondary sources may affect accuracy at local level.

Introduction

The need for monitoring tools in natural water increases with regulation [START_REF] Allan | A "toolbox" for biological and chemical monitoring requirements for the European Union's Water Framework Directive[END_REF][START_REF] Poulier | Can POCIS be used in Water Framework Directive (2000/60/EC) monitoring networks? A study focusing on pesticides in a French agricultural watershed[END_REF]. However, monitoring networks are often expensive when they aim at covering the entire area of interest. Among the targeted organic contaminants, pesticides are largely represented in priority pollutant lists because of their toxicity and ubiquitous presence (e.g., half of the Water Framework Directive, 2000/60/EC). Remarkably, herbicides exhibit the highest sales volumes (e.g., glyphosate, S-metolachlor), and are thus quantified in surface waters at higher levels than other pesticides [START_REF] Comoretto | Pesticides in the Rhône river delta (France): basic data for a field-based exposure assessment[END_REF]. These substances may reach coastal water from freshwater inputs and affect organisms that were not initially targeted.

For example, measurable biological effect of S-metolachlor on marine organisms vary between levels higher than mg L -1 for microalgae growth, photosynthetic efficiency or lipid content [START_REF] Ebenezer | Quantification of Toxic Effects of the Herbicide Metolachlor on Marine Microalgae Ditylum brightwellii (Bacillariophyceae), Prorocentrum minimum (Dinophyceae), and Tetraselmis suecica (Chlorophyceae)[END_REF][START_REF] Coquillé | The influence of natural dissolved organic matter on herbicide toxicity to marine microalgae is species-dependent[END_REF], to environmentally realistic sub µg L -1 levels causing spermio and embryotoxicity on Crassostrea gigas [START_REF] Mai | Environmental concentrations of irgarol, diuron and S-metolachlor induce deleterious effects on gametes and embryos of the Pacific oyster, Crassostrea gigas[END_REF]. Passive sampling is increasingly developed for a wide range of contaminants, because it provides more accurate data, e.g., time-weighted average concentrations, freely dissolved contamination fraction, high preconcentration rates decreasing limits of detection (LD). It offers attractive advantages when considering how challenging surface water (and coastal water more importantly) monitoring is, due to high concentration variability over time and analytical difficulties inherent to trace level measurements in complex matrices. The Polar Organic Chemical Integrative Sampler (POCIS) was introduced by [START_REF] Alvarez | Development of a passive, in situ, integrative sampler for hydrophilic organic contaminants in aquatic environments[END_REF] for the sampling of medium polar and polar organic contaminants (e.g., pesticides, pharmaceuticals), and is therefore a sampler of choice for the study of emerging pesticides, although recent developments tend to improve the quantitative ability of such adsorption based passive samplers [START_REF] Chen | Evidence and recommendations to support the use of a novel passive water sampler to quantify antibiotics in wastewaters[END_REF][START_REF] Belles | Calibration and response of an agarose gel based passive sampler to record short pulses of aquatic organic pollutants[END_REF][START_REF] Fauvelle | Glyphosate and AMPA passive sampling in freshwater using a microporous polyethylene diffusion sampler[END_REF].

The work presented here aims at monitoring S-metolachlor with POCIS in the Arcachon Bay and its main tributaries, in order to get a comprehensive overview of sources and transfer from freshwater to seawater. Contamination modeling using Mars-2D (2-dimensions Hydrodynamical Model for Applications at Regional Scale) adapted to Arcachon Bay [START_REF] Plus | Hydrodynamic characterization of the Arcachon Bay, using model-derived descriptors[END_REF] is also assessed as a monitoring tool. The monitoring strategy we propose is based on three consecutive steps, i) preliminary mapping for sources identification during 4 months (03/22/2010 to 07/17/2010), ii) actual monitoring of the sources and the Bay by POCIS for the consecutive 12 months (07/17/2010 to 07/21/2011), iii) comparing MARS-2D modeled data from sources inside the Bay to the chemical measurements. channels is 20 m. The area supports several activities in the Bay itself or its watershed (e.g., oyster farming, agriculture, aquatic recreational activities) that present conflicts of practice, to some extent related to the water contamination induced by any of these activities [START_REF] Gamain | Can pesticides, copper and seasonal water temperature explain the seagrass Zostera noltei decline in the Arcachon bay? Mar. Pollut. Bull[END_REF]. Five sampling stations inside the Bay together with the six main tributaries were selected for monthly sampling (Fig. 1). All analytical procedures are described by [START_REF] Belles | Development of an adapted version of polar organic chemical integrative samplers (POCIS-Nylon)[END_REF] for POCIS exposed inside the Bay, and by [START_REF] Fauvelle | Use of mixed-mode ion exchange sorbent for the passive sampling of organic acids by polar organic chemical integrative sampler (POCIS)[END_REF] for POCIS exposed in the Bay tributaries. As S-metolachlor is exclusively used for agricultural purposes, we assumed that sources were located only at freshwater input sites. Therefore, the six main tributaries were selected in term of flowrate (Fig. 1, > 90 % total river inputs, [START_REF] Auby | Etude de la proliferation des algues vertes dans le Bassin d'Arcachon[END_REF] and monitored by POCIS immersed for four consecutive periods of 4 weeks from 03/22/2010 to 07/17/2010 for mapping the main sources of S-metolachlor to the Bay [START_REF] Roubeix | Assessing the impact of chloroacetanilide herbicides and their metabolites on periphyton in the Leyre River (SW France) via short term growth inhibition tests on autochthonous diatoms[END_REF]. Afterwards, 5 sampling stations inside the Bay (Fig. 1) together with the main sources previously identified were monitored the same way from 07/17/2010 to 07/21/2011 to perform the modeling exercise.

Methods

Sampling and chemical analysis

MARS-2D model

MARS is a hydrodynamical model that solves fluid mechanics equations commonly known as Navier-Stokes [START_REF] Lazure | An external-internal mode coupling for a 3D hydrodynamical model for applications at Regional Scale (MARS)[END_REF]. This model has been previously applied to the Arcachon Bay [START_REF] Plus | Hydrodynamic characterization of the Arcachon Bay, using model-derived descriptors[END_REF], assuming the horizontal current does not vary significantly with depth and that the vertical current acceleration is negligible when compared to gravitational acceleration. Indeed, in this bay the water column is well-mixed all along the year, due to the strong tidal currents, the somewhat shallow depths and the low freshwater inputs when compared to the oscillating volume [START_REF] Plus | Hydrodynamic characterization of the Arcachon Bay, using model-derived descriptors[END_REF]. The model geographical extension is 44°21 -44°54 N and 0°57 -1°27 W, horizontal resolution is 235 x 235m (squared cells), and time step varies between 60 and 200 seconds. The model also accommodates with wet/dry zones and has been validated against tide gauges, acoustic Doppler current profiler and salinity measurements. The model used, at its open boundaries, a tide obtained from the Legos model (FES2004, [START_REF] Lyard | Modelling the global ocean tides: modern insights from FES2004[END_REF]; decimetric precision close to the coasts) and a meteorological forcing obtained from the ARPEGE model (meteo France, [START_REF] Déqué | and of the Council of 23 October 2000 establishing a framework for Community action in[END_REF]. In addition, the model incorporates pooled bathymetric data provided by L' Yavanc (L' Yavanc, 1995), the Gironde maritime navigation service and the Marine Hydrographic and Oceanographic Service (SHOM). For our purpose, it was hypothesized that i) vertical contaminant concentration heterogeneity is negligible, and ii) S-metolachlor is conservative (no degradation, no export to other compartments such as sediment or biota) under the environmental conditions of our study due to its high solubility and polarity (solubility 0.5 g L - 1 , log Kow = 3.1). The model goodness-of-fit (observed vs. predicted values) on the variable 'Salinity' gives a good idea on the capacity of the model to reproduce passive tracer concentrations in the bay: the calculated root mean squared deviation of simulated salinity is 2.25, which corresponds to a 7.4% error on average [START_REF] Plus | Hydrodynamic characterization of the Arcachon Bay, using model-derived descriptors[END_REF].

Results and discussion

Identification and monitoring of sources

Table 1. S-metolachlor concentration (ng L -1 ) in the main tributaries of Arcachon Bay measured by POCIS over the preliminary contamination mapping period (03/22/2010 to 07/17/2010).

Method relative standard deviation is 23 % and limit of detection (LD) is considered 1.5 ng L - 1 for POCIS exposed for 1 month in freshwater [START_REF] Lissalde | Liquid chromatography coupled with tandem mass spectrometry method for thirty-three pesticides in natural water and comparison of performance between classical solid phase extraction and passive sampling approaches[END_REF]. Tributaries flow data are from [START_REF] Auby | Etude de la proliferation des algues vertes dans le Bassin d'Arcachon[END_REF]Auby et al., over the 1989Auby et al., -1993 Leyre river was found to be the main provider of S-metolachlor to the Bay over the preliminary concentration mapping step (03/22/2010 to 07/17/2010, Table 1). It had by far the highest flow and was the most contaminated sites (Table 1). Thus, it was considered thereafter as the only source of S-metolachlor to the Bay, i.e., only the Leyre river inputs were considered in MARS-2D model. S-metolachlor concentration in the Leyre river was then measured in the range of 10-80 ng L -1 during the actual modeling exercise (07/17/2010 to 07/21/2011, Fig. 2). The maximum concentration in this tributary occurred together with the maximum stream flow, resulting in an estimated massive flux of S-metolachlor towards the Bay during winter time (up to an average of 200 g day -1 over the 11/30/2010-01/02/2011 period). This major flux was grown by the unconventional rainfall behavior in 2010 (twice higher rainfall in November compared to the seasonal norms). Linking this 200 g day -1 S-metolachlor flux to the total volume (~ 0.8 10 12 L) and the residence time of freshwater in the Bay (10 days for 120 m 3 s -1

and 24 days for 10 m 3 s -1 freshwater flow, De Wit et al., 2005, extrapolated to 22 days in our case, with a maximum flow of 28 m 3 s -1 in November 2010, Fig. 2), we can roughly estimate a maximum averaged S-metolachlor concentration inside the Bay of 5 ng L -1 . It is interesting to note that the maximum stream concentration measured in winter does not match the Smetolachlor application period, generally occurring in April-May for maize cultivation in this area. This finding suggests an unconventional fate of S-metolachlor from field application to its transfer to the receptive river. Indeed, because of the permeability of the sandy soils of the watershed surrounding the Arcachon Bay, the watercourses are more comparable to groundwater drains than to receptacles of the runoff water [START_REF] Rimmelin | Study of annual and seasonal dissolved inorganic nitrogen inputs into the Arcachon Lagoon, Atlantic Coast (France)[END_REF]. Therefore, the lag time observed in river contamination could be attributed to a temporary contaminant storage in superficial groundwater prior to discharge in rivers when groundwater table level is high enough to be drained by the neighboring river. The modeled data inside the Bay at different points were in good agreement with measured concentrations (Fig. 3) both in terms of concentration range and seasonal trend. The maximum concentrations modeled at the 5 sites are also in the range of that estimated roughly in the previous section (i.e., 5 ng L -1 ). The dilution gradient between the source (Leyre, Fig. 1) and the open water (Arguin, Fig. 1) is also well represented by the modeled data at the various sampling stations. Data measured at Arguin site suffer from high dispersion, in relation with low levels quantified, close to LD. Although modeled and measured trends are roughly similar, we obtained an almost systematic underestimation of data modeled compared to the one measured. As highlighted in section 3.1, groundwater is probably a crucial compartment for contaminants fate. [START_REF] Deborde | Role of tidal pumping on nutrient cycling in a temperate lagoon (Arcachon Bay, France)[END_REF] showed that groundwater inputs to the Bay are between 2.7 and 5.3 % of the rivers freshwater inputs, which could be negligible at the global scale, but might be of importance at the local scale. Unfortunately, we don't have any chemical monitoring of groundwaters around the Bay to discuss this hypothesis in more details. Moreover, the substantial underestimation observed at Balise 9 might highlight a secondary source on the northern side of the Bay. Canal des Etangs has a significant flow (26 % that of Leyre, Table 1) and might affect S-metolachlor concentration at Balise 9, but the concentrations found at that site were < LD most of the time, with occasional detection at levels always below 7 ng L -1 . Other issues could arise when trying to implement such an approach for more hydrophobic contaminants, which might have higher affinity for suspended matter, and would therefore not be detectable in the dissolved fraction of the water column. In light of a previous study [START_REF] Mai | Environmental concentrations of irgarol, diuron and S-metolachlor induce deleterious effects on gametes and embryos of the Pacific oyster, Crassostrea gigas[END_REF], implications of these results for the local economy of Arcachon Bay could be of importance, since most of the oyster farms are located close to the Leyre river mouth where S-metolachlor concentrations are the highest, eventually implying spermio and embryotoxicity.

Thus, the model outputs have to be considered with caution despite their ability to predict concentrations ranges and seasonal trends, in good agreement with measurements at different points of the Bay. In fact, we speculate the need for more complexity in the behavior modeling of the simulated tracer as well as for more accuracy in the estimation of sources. This type of monitoring strategy would however be of interest given the drastic reduction of analytical costs both in terms of number of samples required, and analytical challenges for quantifying low pg L -1 levels. In addition, it offers the opportunity to get a comprehensive and high spatial resolution overview of contaminants dispersion.

Figure 1 .

 1 Figure 1. Localization of tributaries (right list) and sampling stations inside the Arcachon Bay (left list). Map from French National Institute of Geographic and Forestry Information.Arcachon Bay is a 180 km 2 mesotidal lagoon on the South Atlantic coast of France (44°40'N,

Figure 2 .Figure 3 .

 23 Figure 2. Concentration of S-metolachlor and flow of Leyre river over the modeling exercise period (07/17/2010 to 07/21/2011). Method relative standard deviation is 23 % and LD is considered 1.5 ng L -1 for POCIS exposed for 1 month in freshwater[START_REF] Lissalde | Liquid chromatography coupled with tandem mass spectrometry method for thirty-three pesticides in natural water and comparison of performance between classical solid phase extraction and passive sampling approaches[END_REF].

  period

	Sampler exposure period	Unit Leyre	Canal des Etangs	Canal des Landes	Cirès	Lanton Ponteils
	03/22/2010	04/19/2010	ng L -1	44	7	19	43	63	< LD
	04/19/2010	05/17/2010	ng L -1	51	< LD	16	97	148	< LD
	05/17/2010	06/17/2010	ng L -1 139	< LD	< LD	< LD	< LD	< LD
	06/17/2010	07/17/2010	ng L -1	27	< LD	< LD	30	105	< LD
	Stream flow / Leyre flow	-	1.0	0.26	0.03	0.04	0.02	0.02

Acknowledgements

The authors are grateful to the Region Aquitaine (OSQUAR project), and FEDER (OSQUAR project) and ANR Ripost for financial support.