B Serranito
email: serranitobruno@gmail.com

J.-L Jamet

N Rossi

D Jamet

Decadal shifts of coastal microphytoplankton communities in a semi-enclosed bay of NW Mediterranean Sea subjected to multiple stresses

Long-term evolution of microphytoplankton communities remains poorly studied in anthropized coastal zones submitted to multiple stressors. Here, we investigate decadal (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017) microphytoplankton community changes, focusing on abundance and biovolume of major taxa related to both local abiotic conditions (rainfall rate, temperature and salinity) and regional convection events (wintering deep mixing) in the highly urbanized and semi-enclosed Toulon Bay (NW Mediterranean Sea). Results showed that persistent variations in local rainfall regime were followed by major changes in microphytoplankton community composition. Wet period (P 2 ) (increase of wintering precipitations observed between late 2008 and early 2015) was associated to an increase of large heterotrophic dinoflagellates and disappearance of dominant diatom taxa, while dry periods (2005-2008 (P 1 ) and 2015-2017 (P 3 )) promoted diatoms, microflagellates and small mixotrophic/heterotrophic dinoflagellates including potentially toxic species. Concomitance between intense deep mixing events, reported in open Ligurian Basin (particularly during winters 2005 and 2006) and higher values in the total microphytoplankton abundance and in spring diatom abundance regardless of rainfall conditions, presents this meso-scale process as the main fertilization mechanism in Toulon Bay. Although no change was detected in the chlorophyll a concentration during the 2006-2017 period, its trend was negatively correlated to the total microphytoplankton abundance. This negative relation as well as a change of size in dinoflagellates suggested a shift in the primary producer nature, from large autotrophic cells (diatoms and microflagellates) to smaller ones, driven by a runoff intensification. Finally, different communities composition were observed during both dry periods (i.e. diatoms-dominated and autotrophic microflagellate-dominated communities during P 1 and P 3 , respectively), suggesting another environmental driver of change for phytoplankton communities of this coastal ecosystem.

Introduction

Microphytoplankton defining photoautotrophic plankton range between 20 and 200 μm [START_REF] Sieburth | Pelagic ecosystem structure: heterotrophic compartiments of the plankton and their relationship to plankton size fractions[END_REF] is a master piece of marine systems as it represents one of the main component of primary production [START_REF] Uitz | Estimates of phytoplankton class-specific and total primary production in the Mediterranean Sea from satellite ocean color observations: PRIMARY PRODUCTION IN THE MEDITER-RANEAN[END_REF]. Shaping the most efficient carbon transfer along the trophic web [START_REF] Cushing | A difference in structure between ecosystems in strongly stratified waters and in those that are only weakly stratified[END_REF], microphytoplankton also plays a major role in biochemical cycles such as atmospheric carbon sequestration and export [START_REF] Basu | Phytoplankton as key mediators of the biological carbon pump: their responses to a changing climate[END_REF] or in most of HAB (Harmful Algal bloom) events [START_REF] Vila | Phytoplankton functional groups and harmful algal species in anthropogenically impacted waters of the NW Mediterranean Sea[END_REF]. Thus, many studies have predicted that changes in microphytoplankton communities and abundance could have large impacts on trophic web structure (Chivers et al., 2017;D'Alelio et al., 2015;Stibor et al., 2004), bio chemical cycles [START_REF] Guidi | Plankton networks driving carbon export in the oligotrophic ocean[END_REF][START_REF] Litchman | The role of functional traits and trade-offs in structuring phytoplankton communities: scaling from cellular to ecosystem level[END_REF][START_REF] Wang | Impacts of shifts in phytoplankton community on clouds and climate via the sulfur cycle[END_REF] as well as water quality [START_REF] Cloern | Phytoplankton community ecology: principles applied in San Francisco Bay[END_REF].

This latest concern affects particularly coastal zone which provides among the most of ecological services to human being [START_REF] Costanza | Changes in the global value of ecosystem services[END_REF][START_REF] De Groot | Global estimates of the value of ecosystems and their services in monetary units[END_REF]. Coastal systems located at the sea-land interface, are subjected to multiple perturbations [START_REF] Tett | Defining and detecting undesirable disturbance in the context of marine eutrophication[END_REF], related to climate variability and anthropogenic pressure such as nutrient enrichment from river runoff [START_REF] Cloern | Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems[END_REF]. In this context, numerous works have highlighted the relevance of microphytoplankton communities as an indicator for the assessment of "good environmental status" (GES) of EU marine waters required by the Water Framework Directive (WFD: 2000/60/EC) [START_REF] Devlin | Establishing boundary classes for the classification of UK marine waters using phytoplankton communities[END_REF][START_REF] Jaanus | Potential phytoplankton indicator species for monitoring Baltic coastal waters in the summer period[END_REF][START_REF] Tett | Framework for understanding marine ecosystem health[END_REF][START_REF] Tett | Use of a Phytoplankton Community Index to assess the health of coastal waters[END_REF].

For a long time, these issues have increased interest in microphytoplankton monitoring in relation to variations of environmental condi tions in order to determine mechanisms driving and structuring communities at annual and interannual scales. Although microphytoplankton was mainly composed by diatoms (Ochrophyta;Cavalier-Smith, 1995) and dinoflagellates (Myzozoa;Cavalier-Smith and Chao, 2004), the high taxonomical and morphological diversity [START_REF] Naselli-Flores | Shape and size in phytoplankton ecology: do they matter?[END_REF] already mentioned by the Margalef "plankton paradox" [START_REF] Margalef | Succession in marine populations[END_REF], remains a hindrance to the assessment of these concerns. In application of the guild concept [START_REF] Root | The niche exploitation pattern of the blue-gray gnatcatcher[END_REF], trait-based approaches using measurable properties from organisms [START_REF] Mcgill | Rebuilding community ecology from functional traits[END_REF] are nowadays currently used to summarize the functional diversity of phytoplankton communities. Cell size has been considered as a "master trait" [START_REF] Weithoff | Measures and approaches in trait-based phytoplankton community ecologyfrom freshwater to marine ecosystems[END_REF], as it conditioned many physiological and ecological functions such as metabolic rate [START_REF] López-Urrutia | Scaling the metabolic balance of the oceans[END_REF], nutrient intakes [START_REF] Grover | Influence of cell shape and size on algal competitive ability[END_REF][START_REF] Marañón | Cell size as a key determinant of phytoplankton metabolism and community structure[END_REF] or trophic interactions [START_REF] Barton | The biogeography of marine plankton traits[END_REF][START_REF] Hansen | The size ratio between planktonic predators and their prey[END_REF]. Early on, size-based approaches succeed to describe important succession and distribution patterns related to environment such as the classical diatoms to dinoflagellates phenological succession in temperate coastal systems [START_REF] Margalef | Life-forms of phytoplankton as survival alternatives in an unstable environment[END_REF] or the description of community niches along environmental gradients (Smayda andReynolds, 2003, 2001). Species-specific biovolumes are particularly useful to describe mixed communities exhibiting a wide range of complex shapes [START_REF] Ignatiades | Redefinition of cell size classification of phytoplanktona potential tool for improving the quality and assurance of data interpretation[END_REF], reflecting species adaptations and strategies under diverse environmental and nutrient conditions for diatoms [START_REF] Kemp | The case of the diatoms and the muddled mandalas: time to recognize diatom adaptations to stratified waters[END_REF][START_REF] Smayda | Strategies of marine dinoflagellate survival and some rules of assembly[END_REF] or dinoflagellates [START_REF] Reynolds | Ecology of Phytoplankton[END_REF]. For instance, it was also shown that cell sizes and shapes determines the prey nature for mixotrophic and heterotrophic dinoflagellates [START_REF] Jeong | Growth, feeding and ecological roles of the mixotrophic and heterotrophic dinoflagellates in marine planktonic food webs[END_REF]. Such features play a crucial role on marine ecosystems impacting trophic web efficiency [START_REF] Ward | Marine mixotrophy increases trophic transfer efficiency, mean organism size, and vertical carbon flux[END_REF] but still remain poorly considered in phytoplankton dynamic studies [START_REF] Flynn | Misuse of the phytoplankton-zooplankton dichotomy: the need to assign organisms as mixotrophs within plankton functional types[END_REF][START_REF] Mitra | Modelling mixotrophy in harmful algal blooms: more or less the sum of the parts?[END_REF].

For decades, chlorophyll a concentration (and derived parameters) was widely used in long-term phytoplankton studies as a proxy of phytoplankton biomass (Cullen et al., 2002), because it allows to study homogenously primary production at large spatio-temporal scales [START_REF] O'reilly | Ocean color chlorophyll algorithms for SeaWiFS[END_REF]. Although these methods have shown significant advances in the recognition of functional types [START_REF] Nair | Remote sensing of phytoplankton functional types[END_REF] or size classes [START_REF] Brewin | An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing[END_REF], it only roughly describes the size structure from phytoplankton communities [START_REF] Boyce | From mice to elephants: overturning the 'one size fits all' paradigm in marine plankton food chains[END_REF]. Thus, long-term time series from stations remain critical and powerful tools for describing and studying high-resolution community variability related to environmental forcings [START_REF] Adolf | Environmental forcing of phytoplankton floral composition, biomass, and primary productivity in Chesapeake Bay, USA[END_REF][START_REF] Ducklow | Contributions of long-term research and time-series observations to marine ecology and biogeochemistry[END_REF][START_REF] Harding | Long-term trends of nutrients and phytoplankton in chesapeake bay[END_REF][START_REF] Olli | Diatom stratigraphy and long-term dissolved silica concentrations in the Baltic Sea[END_REF]. However, the high cost associated with the establishment and the maintenance of stationary long-term time series may explain the limited number of coastal system monitoring at global scale [START_REF] Smetacek | OCEANS: on phytoplankton trends[END_REF]. Mediterranean sea which was designated as a hotspot to survey the impact of environmental variations on marine ecosystems, is unfortunately particularly subject to low monitoring effort [START_REF] Mazzocchi | Temporal variability of Centropages typicus in the Mediterranean Sea over seasonal-to-decadal scales[END_REF].

As a result, only few investigations have attempt to characterize interannual variations of coastal microphytoplankton communities [START_REF] Garrido | Contrasting patterns of phytoplankton assemblages in two coastal ecosystems in relation to environmental factors (corsica, NW Mediterranean sea)[END_REF] unlike to other plankton compartments such as zooplankton [START_REF] Siokou-Frangou | Plankton in the open Mediterranean sea: a review[END_REF]. Finally, due to an additional effort required, cell size is rarely considered in these long-term microphytoplankton community studies which mainly focus on abundance and taxonomic diversity which make difficult the comparison between ecosystems [START_REF] Vadrucci | Biovolume determination of phytoplankton guilds in transitional water ecosystems of Mediterranean Ecoregion[END_REF]. This lack of knowledge has, for instance led to promote chlorophyll a concentration as the only parameter to assess water coastal quality in Mediterranean GIG (Geographical Intercalibration Group) country members [START_REF] Höglander | Overview of coastal phytoplankton indicators and their potential use in Swedish waters[END_REF] while some other basins such as North Sea [START_REF] Devlin | Establishing boundary classes for the classification of UK marine waters using phytoplankton communities[END_REF] or Baltic Sea [START_REF] Höglander | Overview of coastal phytoplankton indicators and their potential use in Swedish waters[END_REF][START_REF] Tett | Use of a Phytoplankton Community Index to assess the health of coastal waters[END_REF] focused on shift in functional groups as Biological Quality Element (BQE).

From remote sensing of chlorophyll a concentrations, the Ligurian Basin (NW Mediterranean sea) has been identified as a "intermittent" and a "blooming" ecoregion (d'Ortenzio and Ribera d'Alcalà, 2009). This category defines Mediteranean areas displaying intense spring blooms fueled by wintering deep mixing events [START_REF] Coppola | Seasonal and inter-annual variations of dissolved oxygen in the northwestern Mediterranean Sea (DYFAMED site)[END_REF][START_REF] Marty | Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995-2007 and biogeochemical consequences[END_REF]. During the 2000s, three main events related to the deepening of the MLD (Mix Layer Depth) have been reported at the DYFAMED point (Ligurian Sea): winters 2005 and 2013 (D 'Ortenzio et al., 2014;[START_REF] Coppola | Seasonal and inter-annual variations of dissolved oxygen in the northwestern Mediterranean Sea (DYFAMED site)[END_REF] and a particularly intense one occurring in winter 2006 [START_REF] Coppola | Seasonal and inter-annual variations of dissolved oxygen in the northwestern Mediterranean Sea (DYFAMED site)[END_REF][START_REF] Heimbürger | Temporal variability of vertical export flux at the DYFAMED time-series station (Northwestern Mediterranean Sea)[END_REF][START_REF] Marty | Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995-2007 and biogeochemical consequences[END_REF][START_REF] Pasqueron De Fommervault | Temporal variability of nutrient concentrations in the northwestern Mediterranean sea (DYFAMED time-series station)[END_REF]. Such events were responsible of an increase of winter-spring chlorophyll a concentration attributed to microphytoplankton [START_REF] Heimbürger | Temporal variability of vertical export flux at the DYFAMED time-series station (Northwestern Mediterranean Sea)[END_REF][START_REF] Marty | Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995-2007 and biogeochemical consequences[END_REF]. Therefore, as other urbanized coastal regions, NW Mediterranean Sea is also under the influence of terrestrial inputs and pollution from coastal rivers and small streams [START_REF] Nicolau | Transfer of nutrients and labile metals from the continent to the sea by a small Mediterranean river[END_REF] which might deeply impact phytoplankton communities and participate to the current unpredictability of its dynamic.

Here, we investigate decadal microphytoplankton community variations in the highly urbanized semi-enclosed Toulon Bay located in Ligurian Basin impacted by both offshore (wintering deep mixing vents) and terrestrial (anthropogenic) influences to extract main shifts at interannual scale. Main objectives were i) to investigate main microphytoplankton community shifts at a decadal scale within the 2005-2017 period, ii) to describe changes in communities at the taxonomical level using cell biovolumes, iii) to correlate this changes to meteorological modulations or water descriptors, iv) to compare microphytoplankton variations with main phytoplankton biomass proxy (chlorophyll a concentration) and v) to propose mechanisms of changes focusing on trophic preferences.

Materials and methods

Study site

Toulon Bay is a Mediterranean semi-enclosed coastal zone near the Toulon agglomeration (∼428 000 inhabitants) which extends over 367 km 2 at the south-east of France (43°05′ N -05°55' E). The bay is divided by an artificial breakwater facing north/south into two connected basins. The West part called "Little Bay" is characterized by smaller and narrower dimensions and is particularly submitted to human influences such as harbour activities (commercial, military and shipyard) or urban runoff mainly driven by the Las river [START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF][START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. The larger and deeper eastern part named "Large Bay" (42 km 2 and ∼17 m deep) is directly open to the Mediterranean Sea (Fig. 1), benefiting from the influence of the Northern Current [START_REF] Taupier-Letage | Les îles d'Hyères dans le système de circulation marine et atmosphérique de la Méditerranée[END_REF] which generates a general weak cyclonic circulation into the bay whose intensity is correlated to wind regime [START_REF] Dufresne | Wind-forced circulation model and water exchanges through the channel in the Bay of Toulon[END_REF][START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. Therefore, as other coastal region of Ligurian Basin, Large Bay also host coastal current instabilities like "eddies" which are involved in setting up of punctual coastal spring blooms [START_REF] Casella | Ecosystem dynamics in the Liguro-Provençal Basin: the role of eddies in the biological production[END_REF]. Large Bay is also impacted by diverse terrestrial input sources whose main is the flooded Eygoutier River. As a typical Mediterranean river, the Eygoutier flow shows seasonal fluctuations (from 10 m 3 h -1 to 40.10 3 m 3 h -1 during dry winter and summer and wet spring and fall, respectively) in connection to the local precipitation rate [START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF][START_REF] Nicolau | Transfer of nutrients and labile metals from the continent to the sea by a small Mediterranean river[END_REF]. Both the hydrographic regime and the large Eygoutier watershed (∼70 km 2 ) covering urban, rural and industrial zones, have led to high organic matter discharges (2300 t.an -1 ), nitrate enrichment and metallic contamination (Cu, Pb and Zn) during high runoff periods [START_REF] Nicolau | Transfer of nutrients and labile metals from the continent to the sea by a small Mediterranean river[END_REF]. To a less extent, presence of outfall pipe from AmphorA waste- water plant could represent another source of organic matter (∼90 t. an

-1
).

Plankton sampling

Monthly monitoring of microphytoplankton was realized on "Large Bay sampling point" (LaB) (43°05′45'' N; 05°56′30'' E), located at 1 km from the Eygoutier outfall, from January 2005 to November 2017 and between 8:00 to 11:00 a.m. For microphytoplankton, 10-20 L were collected at 3 m depth using a Niskin sampling bottle. Samples were concentrated into a final volume of 50 ml using inverse filtration [START_REF] Dodson | Concentrating plankton in a gentle fashion[END_REF], and fixed with a 0.3% lugol solution. Because it was dissolved by fixation method, coccolithophorids were not considered in this study. Finally, counts and identification were performed after a 24 h column sedimentation as recommended by [START_REF] Lund | The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting[END_REF] and [START_REF] Utermöhl | Zur Vervollkommnung der quantitativen Phytoplankton-Methodik[END_REF] by using a phase-contrast microscopy (Leica DMI 4000; magnitude ×400). As described by the Utermöhl method at least 20 fields and 200 cells were counted by sample and abundances were computed as followed:

With N ij the abundance of the species i in a sample j (cell.l -1 ), n ij the number of cells of the species i, f j the number of fields counted in sample j, F j total number of fields, V j volume of sample j.

To focus on main community changes, selection of representative taxa was performed. A threshold of 10% was applied to both occurrence throughout the time series and relative abundance in at least one sample. Finally, 57 taxa were selected of which 25 diatoms, 22 dinoflagellates and 10 taxa belonging to micro-and upper size classes from nanoflagellates (microflagellates, hereafter) (Table 1).

Environmental data

Temperature, salinity and chlorophyll a concentration monthly time-series from REPHY sampling point ("Rephy 112-P-010": 43°0 4′44''N; 5°57′17''E) located in the Large Bay (Fig. 1) were extracted from Quadrige 2 database, grouping French metropolitan coastal stations belonging to the "Observation and Monitoring Network for Phyto plankton and Hydrology in Coastal Water" (REPHY). The aim of this network implemented by the "French Research Institute for Exploitation of the Sea" (IFREMER) results in the monitoring of phytoplankton, phytotoxic species and hydrology of french coastal areas and valuation of calibrated dataset [START_REF] Belin | REPHY dataset -French Observation and Monitoring program for Phytoplankton and Hydrology in coastal waters. 1987-2016 Metropolitan data[END_REF]. In accordance to the REPHY protocol, surface temperature and salinity were assessed using in situ sensor, chlorophyll a concentration was evaluated at 1 m depth using monochromatic spectrophotometry or fluorimetry method [START_REF] Aminot | Hydrologie des écosystèmes marins: paramètres et analyses[END_REF]. Therefore, environmental dataset was completed with monthly rainfall rate (average in mm) from Météo France meteorological Toulon station (43°06′11''N; 5°55′ 52''E).

Nitrite/nitrate and phosphate (NO Using 10 L sampled at 3 m depth, concentrations were obtained following the method proposed by [START_REF] Murphy | A modified single solution method for the determination of phosphate in natural waters[END_REF] and [START_REF] Tréguer | Manuel d'analyse des sels nutritifs dans l'eau de mer (utilisation de l'AutoAnalyser II Technicon (r))[END_REF] modified by [START_REF] Strickland | A practical handbook of seawater analysis -determination of reactive phosphorus[END_REF] for N-NO , respectively. Supplementary N-NO

x -and P-PO 4 3-concentration data from "112-P-010-22B" sampling station and measured at 3 m depth using flow spectrophotometry between March 2009 and March 2010 were added to previous measures. (For more information, see [START_REF] Aminot | Méthodes en flux continu[END_REF]).

Data analysis 2.4.1. Data partitioning

The identification of main and persistent changes into microphytoplanktonic community and environmental conditions across the 2005-2017 period were evaluated using chronological clustering [START_REF] Legendre | Succession of species within a community: chronological clustering, with applications to marine and freshwater zooplankton[END_REF]. This partitioning method constrained the gathering of dates with adjacent ones allowing to identify homogeneous period. The chronological clustering was applied on log-Chord and Euclidean matrix distance, for microphytoplankton and environmental datasets respectively. Log-Chord distance [START_REF] Legendre | Box-Cox-chord transformations for community composition data prior to beta diversity analysis[END_REF] was the computation of Chord distance: On log-transformed data count:

U N C O R R E C T E D P R O O F B.
Where y ij was the abundance of species i in sampling j.

As determined by the authors, log-chord distance was particularly useful to normalize highly asymmetrical count data while retaining chord distance properties (e.g. low weight for rare species and low counts) [START_REF] Legendre | Ecologically meaningful transformations for ordination of species data[END_REF].

Influence of partitioning as well as months, years and interannual variability (Months x Years) on microphytoplankton assemblage was evaluated using non-parametric PERmatutional Multivariate ANalysis Of Variance (PERMANOVA) analysis performed on distance matrix [START_REF] Anderson | A new method for non-parametric multivariate analysis of variance[END_REF].

Considering the scarcity of nutrient data, only water temperature, salinity and rainfall rate were used to describe environmental conditions in clustering analysis using the euclidean distance.

Univariate shift detection method

Mean shift detection in univariate variables were performed using "Binary Segmentation" algorithm (from r package "changepoint") which was a sequential method minimizing the sum of costs and allowing to detect optimal segmentation (for more informations see [START_REF] Killick | changepoint : an R Package for Changepoint Analysis[END_REF]). To avoid seasonal detection and to focus on long-term changes, a maximum of 3 main change points with a minimum segment length of 24 months were considered. Significance of extracted periods was evaluated using post-hoc non-parametric Krukall-Wallis pairwise comparison with Bonferroni correction (PMCMR r Package). Furthermore, loess regression (α = 0.3) was computed on 12-month moving average to summarize the interannual trend of each variable.

Assemblage characterization and community changes

The communities relating to different periods previously extracted were identified using the "Group-equalized Indicator Value index" (Ind-Val g ) [START_REF] De Cáceres | Improving indicator species analysis by combining groups of sites[END_REF][START_REF] De Cáceres | Associations between species and groups of sites indices and statistical inference[END_REF] which was the improved version of IndVal index [START_REF] Dufrene | Species assemblages and indicator species: the need for a flexible asymmetrical approach[END_REF] adapted for unbalanced size groups.

summarized i species affinity for j period by computing its "Specificity" and "Fidelity" (B ij ) component:

"Specificity" may be traduced as the relative abundance of species during a specific period and was computing as follow:

With the number of samples belonging to period j and J the total number of period j.

While "Fidelity" quantifies the frequency with which a species was found in the target period compared to the whole time series:

With O ij number of occurrence of species i within the target period j.

Then significance of each IndVal g was evaluated computing 10′000 random permutations of samples by bootstrapping. For each species, In-dVal g with single period association was first computed in order to identify indicator species. Then, the same association measure but involving combination of periods was performed to identity communities associated with more than one period.

For each season, the relative influence of phytoplankton groups (diatoms, dinoflagellates and microflagellates) on time-serie partitioning were also evaluated using ANOSIM (see appendix A).

As mixotrophy is a widespread strategy among dinoflagellates [START_REF] Stoecker | Mixotrophy among Dinoflagellates1[END_REF], trophic status (i.e. autotrophic, mixotrophic or heterotrophic) were identified for dinoflagellate and also for microflagellate taxa from the literature reports to focus the interpretation of community changes on trophic preferences (Table 1).

Size variations

To investigate variations in size structure, species-specific cell biovolumes (μm 3 ) were computed from geometric shapes described in [START_REF] Hillebrand | Biovolume calculation for pelagic and benthic microalgae[END_REF], [START_REF] Sun | Geometric models for calculating cell biovolume and surface area for phytoplankton[END_REF] and [START_REF] Vadrucci | Biovolume determination of phytoplankton guilds in transitional water ecosystems of Mediterranean Ecoregion[END_REF][START_REF] Vadrucci | Cell biovolume and surface area in phytoplankton of Mediterranean transitional water ecosystems: methodological aspects[END_REF] using cell linear dimensions collected by inverted microscopy between 2005 and 2013. Missing dimensions were extrapolated using allometric ratios computed from [START_REF] Olenina | Biovolumes and size-classes of phytoplankton in the Baltic Sea[END_REF] database (see appendix B, for details).

To evaluate size variations in communities, mean cell biovolumes were computed for the three main microphytoplankton classes (i.e. di Serranito et al. Estuarine, Coastal and Shelf Science xxx (xxxx) xxx-xxx atoms, dinoflagellates and microflagellates) as followed:

U N C O R R E C T E D P R O O F B.
With Ntot the total abundance of the specific class, N and Bv abundance and biovolume of i taxa, respectively. Comparisons between periods were performed using a non-parametric pairwise Wilcoxon rank test with Bonferonni correction. In the case of significant changes in mean biovolumes between periods, different "lifeforms" were investigated in diatoms and dinoflagellates to detect changes in life-strategies in these two classes. Here, lifeforms were defined as biovolume classes characterizing change in community abundance between two consecutives periods. A linear regression model was used to identify mean biovolumes for which we observed a shift in abundance between periods (see appendix C, for details). Due to biases caused by the sampling methodology used, microflagellate community was considered as a unique lifeform. To compare interannual dynamics from lifeforms, Spearman correlation was then performed on yearly average values of standardized abundance anomalies (deviation from monthly mean abundance divided by standard deviation) for each season.

Results

Time partitioning

The concomitance of 2 major interannual changes was identified between "environmental" and "microphytoplankton community" datasets using chronological clustering, leading to the distinction of 3 periods (P 1 , P 2 and P 3 ) (Fig. 2 2). However, the partitioning explained less the total variance rather than annual or interannual variability (R 2 = 6, 13 and 17% respectively for "Period", "Months" and "Years" factors, respectively).

Environmental variability and nutrients

Analysis of univariate environmental data showed that period partitioning was primarily driven by changes in the rainfall rate (Fig. 3a). P 1 was characterized by a relative low precipitation rate (∼27 ± 48 mm), associated with a high and stable salinity in the Large Bay (∼38.1 ± 0.5). Conversely, P 2 showed an increase of rainfall (∼68.8 ± 59.9 mm), particularly during winter 2008/2009 which led to a brutal and persistent decrease of salinity in the Large Bay (∼35.6 ± 1.2) detected from the end of 2008 until early 2011. Despite the maintenance of a high rainfall rate over the period 2009-2015, the increase in salinity trend was observed in 2011 and has conserved a relative steady state until the end of 2017 (∼37.4 ± 1.19) (Fig. 3b). Finally, from early 2015 rainfall rate showed a significant and sudden reduction until the end of 2017 (∼28.9 ± 28.6 mm). Seasonal variations in rainfall rate described a classical Mediterranean precipitation pattern with lowest values during summer and higher during late-fall/early-winter season (mean of 4.5 and 88.1 mm, respectively). The latest season was particularly impacted by the intensification of rainfall rate during P 2 (mean of 114 ± 15 mm between October to January) (Fig. 3d). Similarly, highest differences in salinity between periods were found during the cold season (from November to February, mean of 38.1, 35.8 and 37.5 for P 1 , P 2 and P 3 , respectively) (Fig. 3e). For each dataset, colored branches identified 3 homogeneous periods (P 1 , P 2 , and P 3 in blue, red and brown) extracted from the 2 main change points (Cut-off levels at h = [3658; 3429] and h = [67.2; 64.4] for the "environmental" and the "micro-phytoplankton" time series, respectively). Asymmetry between year boxes was relative to missing values in biological time-series. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Table 2

Summary of PERMANOVA analysis testing the influence of the partitioning (Periods), months (Months), years (Years), and their interaction (Months x Years) on log-chord distance of micro-phytoplankton abundance dataset. Df: degree of Freedom. SS: Sum of Squares. F.Model: F statistic from the permutation procedure. , respectively) and P-PO June and July with no clear phenological signal (Fig. 4 d). Conversely, N-NO x -concentrations showed a noticeable annual pattern with minima found during late spring/summer (mean of 0.26 μmol l -1 between May and August) and higher concentrations found in September (mean of 4.8 ± 9.2 μmol l -1 ) and winter (mean of 3.3 ± 1.8 μmol l -1 between January and March) (Fig. 4c). These two latter peaks were present in , respectively). Furthermore, P 2 seasonal mean variation exhibited lower concentration values for both nutrients. Finally, water temperature didn't show significant change (p > 0.05) in the mean (∼17.5 °C) despite a strong seasonal variability with maximum values occurring in August (21.7 ± 1.7 °C) and minimum in February (13.2 ± 0.4 °C) in the 3 periods (Fig. 3c andf).

Df

General phytoplankton composition

Total microphytoplankton abundance

Total microphytoplankton abundance showed a high range of values from 168 to 7.6.10 5 cells.l -1 , during December 2010 and August 2006, respectively with an average of 1.3.10 4 cells.l -1 (Fig. 5a). The "Binary segmentation" method identified two significant change points ). The latter did not show any significant difference with the 2005-2007 subperiod (pval>0.05). Clear seasonal pattern was observed over the 2005-2017 period characterized by 2 seasonal blooms occurring in March (4.10 4 cells.l -1 ) and September (8.10 4 cells.l -1 ) and with lowest values found in December (2.10 3 cells.l -1) and August (3.10 3 cells.l -1) (Fig. 5c). Global lower average values were observed during P 2 , except in October showing higher values than average (mean of 7.8.10 3 cells.l -1 ). March abundance peak was identified during each period with high confident interval describing an inter-annual variability of bloom events. Nonetheless the highest bloom values were found during P ) and in November (mean of 0.49 ± 0.46 μg l -1

) (Fig. 5d). Globally, all periods showed spring blooms with higher values found in March during P 3 and P 1 (mean of 0.77 ± 0.08 and 0.68 ± 0.33 μg l -1

, respectively) and in April during P 2 (mean of 0.47 ± 0.22 μg l -1 ). Otherwise, the November peak was only identified during P 2 and P 3 (0.64 ± 0.56 and 0.51 ± 0.11 μg l -1 ). No significant difference was observed between periods (pval>0.05).

Despite the absence of significant change in mean values, loess regression on moving average trend showed a gradual increase of the phytoplankton biomass in early 2008 (from 0.28 ± 0.26 to 0.41 ± 0.33 μg l -1

) (Fig. 5b). The most important change in trend observed was a decrease of the chlorophyll a concentration from spring 2012 to fall 2014 (from 0.41 ± 0.22 to 0.25 ± 0.14 μg l -1

). Finally, both loess regressions (α = 0.3) on total abundance and on chlorophyll a concentration showed significant negative spearman correlation (rho = -0.61, pval <0.01).

Microphytoplankton composition

Diatoms were dominant in total microphytoplankton abundance, during the whole 2005-2017 period (53.3% on average) as well as in the three extracted periods (61.1%, 57.3% and 39.8%, for P 1 , P 2 and P 3 , respectively) mostly due to the main representative taxa: P. delicatissima, Chaetoceros spp., Cyclotella spp., Thalassionema spp. and L.danicus (Table 1). Dinoflagellate group was the second most represented, especially during P 2 (∼31%), driving by abundant species (e.g. C. furca, P. micans, P.arcuatum, Alexandrium spp.). However, the most abundant dinoflagellate taxa Gymnodinium spp. showed the highest mean contribution during P 3 (10.2%). Globally microflagellates were less abundant over the 2005-2017 period (14.2%) but were identified as the second contributor in total abundance during P 3 (34%) driven by abundant autotrophic species H. fusiformis and Chlorella sp. (12.2 and 6.8%, respectively).

Changes in microphytoplankton assemblage

Among the 57 selected taxa, 21, 13 and 23 were respectively associated to P 1 , P 2 and P 3 from the single IndVal g index (Table 3). P 1 community was mostly composed of diatoms (13 out of 26 diatom taxa selected) and mixo/heterotrophic microflagellates (8 out of 15) (Table 1). Among the most abundant taxa, it was possible to mention Chaetoceros spp. ( 0

Biovolumes and lifeform variations

Globally, the dinoflagellate community described higher mean cell biovolumes with values ranging from 1.10 4 to 2.10 4 μm 3 (for Q25 and Q75, respectively) during the whole 2005-2017 period (Fig. 6). Diatom mean cell biovolumes were, in turn, ranged between 6.2.10 3 and 1.3.10 4 μm 3 (for Q25 and Q75, respectively) and finally, microflagellate community was constituted by lower cell sizes varying between 684 and 2.6.10 3 μm 3 (for Q25 and Q75, respectively). Contrary to diatom community, dinoflagellates and microflagellates exhibited significant change of mean cell biovolumes between periods (pval<0.05). Thus, dinoflagellates described an increase of mean cell biovolumes between P 1 and P 2 (from 1.3.10 4 to 2.2 .10 4 μm 3 , respectively) and then a decrease in P 3 (mean of 7.9.10 3 μm 3 ), suggesting an important shift within the community. Microflagellates only showed a significant decrease of mean cell biovolume between P 1 and P 2 (from 2.2.10 3 to 1.7.10 3 μm 3 , respectively), and then conserved low cell sizes during P 3 (mean of 1.1.10 3 μm

3

). As none significant change in mean biovolumes was found for diatoms, the whole diatom community was subsequently considered as a unique lifeform. Conversely, these results led to the consideration of two different lifeforms for dinoflagellates characterizing species with biovolumes lower (small dinoflagellates) and higher (large dinoflagellates) than 1.5.10 3 μm 3 (see appendix C, for methodological details).

Mean seasonal anomalies of lifeform abundances described different interannual variations over the 2005-2017 period (Fig. 7). First, spring and summer diatom abundances increased mostly during years hosting intense wintering deep mixing in Ligurian Sea (+0.27, +1.59 and in a less extent -0.12 for 2005, 2006 and 2013, respectively) and also in 2017 (+0.63) for which there is no current report in the literature. Spring and summer anomalies of large dinoflagellates were positive during P 2 wet period (mean of +0.57 and + 0.72, respectively) except during spring 2013 (-0.35). In addition, large dinoflagellate variations were negatively correlated to diatoms during spring (rho = -0.91) (see the summary in appendix E). Then, accordingly to seasonal anomalies, microflagellate and small dinoflagellate abundances showed significant correlation in all seasons except in spring, despite a maximum abundance found in spring 2017 for both of them (+2.84 and + 2.87, respectively). With an exception for summer showing negative anomalies during rainy periods, no clear impact of wet period (P 2 ) was observed on abundances for both microflagellates and small dinoflagellates. Large and small dinoflagellate also showed a significant negative correlation during spring and summer (rho = -0.62 and -0.74). Finally, microflagellate and diatom variations showed significant positive correlation during winter (rho = 0.58).

Discussion

Located in a deep convection area and nearby a large agglomeration, the semi-enclosed Toulon Bay was relevant to investigate the evolution of Mediterranean marine coastal systems confronted to both climatic and anthropogenic perturbations. The monitoring of plankton in Toulon Bay was already used to study annual variability of zooplankton [START_REF] Jamet | The zooplankton community in bays of Toulon area (northwest Mediterranean Sea, France)[END_REF][START_REF] Richard | An unusual distribution of Oithona nana Griesbrecht (1892) (Crustacea: cyclopoida) in a bay: the case of Toulon bay (France, Mediterranean sea)[END_REF], microphytoplankton [START_REF] Boge | Seasonal changes in phosphatase activities in Toulon Bay (France)[END_REF][START_REF] Jamet | Plankton succession and assemblage structure in two neighbouring littoral ecosystems in the north-west Mediterranean Sea[END_REF][START_REF] Rossi | Structure and succession of plankton communities in two mediterranean neighbouring coastal ecosystems (Toulon bays, France)[END_REF] and pico-nanophytoplankton [START_REF] Delpy | Picoand nanophytoplankton dynamics in two coupled but contrasting coastal bays in the NW Mediterranean sea (France)[END_REF] as well as to identify local water indicators of anthropogenic pressure [START_REF] Serranito | Proposition of indicators of anthropogenic pressure in the Bay of Toulon (Mediterranean Sea) based on zooplankton time-series[END_REF]. By using long-term time series, the present study focuses on decadal variability (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017) of the microphytoplankton community structure, to evaluate the impact of local and large-scale perturbations on coastal systems.

Microphytoplankton assemblage features

Previously cited in 1999-2000 [START_REF] Jamet | Plankton succession and assemblage structure in two neighbouring littoral ecosystems in the north-west Mediterranean Sea[END_REF]) and 2006-2007[START_REF] Rossi | Structure and succession of plankton communities in two mediterranean neighbouring coastal ecosystems (Toulon bays, France)[END_REF] annual cycles in Toulon Bay, representative taxa selected were also characteristic of the coastal NW Mediterranean basin. Abundant diatoms such as Chaetoceros spp., Thalasionema spp. or Pseudonitzschia spp. were, in agreement with typical blooming genera, dominant in deep convections areas [START_REF] Siokou-Frangou | Plankton in the open Mediterranean sea: a review[END_REF]. Although it remained less frequently reported, selective dinoflagellate taxa such as C. furca, P. micans, Gymnodinium spp., or Protoperidinium spp. were commonly associated with summer oligotrophic period [START_REF] Gómez | Annual microplankton cycles in villefranche bay, Ligurian Sea, NW mediterranean[END_REF] and particularly in shallow anthropized areas [START_REF] Garrido | Contrasting patterns of phytoplankton assemblages in two coastal ecosystems in relation to environmental factors (corsica, NW Mediterranean sea)[END_REF][START_REF] Vila | Phytoplankton functional groups and harmful algal species in anthropogenically impacted waters of the NW Mediterranean Sea[END_REF]. It should be noticed that among dinoflagellate representative taxa, five were reported as potentially toxic (i.e. D. acuminata, P. micans, Alexandrium spp., Gonyaulax spp., and Gymnodinium spp.) [START_REF] Faust | Identifying harmful marine dinoflagellates[END_REF][START_REF] Ignatiades | A review on toxic and harmful algae in Greek coastal waters (E. Mediterranean sea)[END_REF][START_REF] Mohamed | Potentially harmful microalgae and algal blooms in the Red Sea: current knowledge and research needs[END_REF].

Drivers of changes

Asynchronous qualitative and quantitative changes in microphytoplankton communities were detected during the 2005-2017 period. A significant increase of wintering rainfall rate from late 2008 associated with a catastrophic change in salinity was followed during the next spring by the most important change among representative communities according to chronological clustering (Figs. 2 and3). It should be noticed that the accuracy of change points is a well-known issue in regime shift studies, as it depends on the length and regularity of time-series used. Hence, the absence of data during most of 2015 led to the detection of the second change point from the end of 2015, rather than during the expecting previous spring. Investigations on total microphytoplankton abundance revealed higher values during dry periods, i.e. from 2005 to late spring 2006 which coincide with major wintering deep mixing events reported in Ligurian Basin [START_REF] Heimbürger | Temporal variability of vertical export flux at the DYFAMED time-series station (Northwestern Mediterranean Sea)[END_REF][START_REF] Marty | Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995-2007 and biogeochemical consequences[END_REF] and during spring 2016 to the end of 2017 (Fig. 5).

Thenceforth, investigations on community changes pointed out two different aspects: (1) diatom and microflagellate taxa were mainly associated to dry periods (Table 3). Diatom community was furthermore promoted during springs following convection event in Ligurian open sea (Fig. 7). Only diatom taxa Actinoptychus spp. showed an association Serranito et al. Estuarine, Coastal and Shelf Science xxx (xxxx) xxx-xxx with wet period, highlighting the wide diversity of life-strategies in diatoms as recently described by [START_REF] Kemp | The case of the diatoms and the muddled mandalas: time to recognize diatom adaptations to stratified waters[END_REF]. ( 2) For dinoflagellate taxa, analysis identified two lifeforms involved in the main community changes: while small dinoflagellates (<1,5.10 4 μm 3 ) were also associated with dry periods, following microflagellate variations, the less abundant large dinoflagellate taxa (>1,5.10 4 μm 3 ) were favored by wet period (P 2 ). These findings argued that changes in precipitation regime was the main driver of community changes during the 2005-2017 period, acting through different but superimposed processes at different scales: (1) a local wintering precipitation effect by runoff influence and (2) a regional precipitation deficit effect which mainly promoted vertical mixing.

U N C O R R E C T E D P R O O F B.

Impact of local precipitation 4.3.1. Impacts on microphytoplancton community

In Toulon Bay, concomitant increase of rainfall regime and qualitative changes in microphytoplankton communities assumed impact of terrestrial runoff on community assemblage. This community change was first characterized by a shift in mixotrophic/heterotrophic dinoflagellate community, particularly during spring and summer (see appendix A), promoting the large size taxa (>1,5.10 4 μm 3 ) at the expense of smaller ones. Such a shift in size structure of heterotrophic communities also suggested a change in the nature of available preys. As pointed out by significant positive correlations, small dinoflagellates were highly associated to small size microflagellates assuming a predator-prey relationship (appendix E). This hypothesis is in agreement with reports about trophic preference of mixotrophic and heterotrophic dinoflagellates reported in scientific literature. For instance, it was shown that abundant species belonging to the small dinoflagellate lifeform such as Gymnodinium spp. or P. micans, fed mainly on small size cryptophytes such as Teleaulax sp. [START_REF] Jeong | Growth, feeding and ecological roles of the mixotrophic and heterotrophic dinoflagellates in marine planktonic food webs[END_REF]. Unlike other mixotrophic and heterotrophic dinoflagellates, armored Protoperidinium spp. which were found highly associated with (P 2 ) wet period, executed external digestion with an important range of size for its preys [START_REF] Assmy | Algal blooms[END_REF][START_REF] Buskey | Behavioral components of feeding selectivity of the heterotrophic dinoflagellate Protoperidinium pellucidum[END_REF][START_REF] Jacobson | Widespread phagocytosis of ciliates and other protists by marine mixotrophic and heterotrophic thecate dinoflagellates[END_REF]. This extended diet included preferentially larger ones such as diatoms, dinoflagellates as well as ciliates [START_REF] Jeong | Growth, feeding and ecological roles of the mixotrophic and heterotrophic dinoflagellates in marine planktonic food webs[END_REF][START_REF] Lee | Feeding by common heterotrophic dinoflagellates and a ciliate on the red-tide ciliate Mesodinium rubrum[END_REF]. Such feeding mechanisms allow them to modulate the classical predator-prey allometric ratio of 10:1 [START_REF] Azam | The ecological role of water-column microbes in the sea[END_REF]. Protoperidinium genus was furthermore considered as an important opportunistic grazer of red-tide species, involved in their reduction [START_REF] Jeong | Growth and grazing rates of the heterotrophic dinoflagellates Protoperidinium spp. on red tide dinoflagellates[END_REF]. Thus, high predation impact from large heterotrophic dinoflagellates on other smaller protists such as little dinoflagellates and diatoms, as previously emphasized by [START_REF] Jeong | Growth, feeding and ecological roles of the mixotrophic and heterotrophic dinoflagellates in marine planktonic food webs[END_REF], was consistent with the significant negative correlation found between these lifeforms during spring and winter (Fig. 7). Although it was not considered in this study, the increase of ciliate community during (P 2 ) wet period was suspected as low abundances of diatoms and small dinoflagellates observed seemed insufficient to support large dinoflagellate population growth. Furthermore, the widespread reported predation on ciliates from abundant large dinoflagellate C.furca [START_REF] Ignatiades | Mixotrophic and heterotrophic dinoflagellates in eutrophic coastal waters of the Aegean Sea (eastern Mediterranean Sea)[END_REF][START_REF] Jeong | Growth, feeding and ecological roles of the mixotrophic and heterotrophic dinoflagellates in marine planktonic food webs[END_REF][START_REF] Smalley | Feeding in the mixotrophic dinoflagellate Ceratium furca is influenced by intracellular nutrient concentrations[END_REF][START_REF] Smalley | Ecology of the red-tide dinoflagellate ceratium furca: distribution, mixotrophy, and grazing impact on ciliate populations of chesapeake bay[END_REF] (which was highly associated to (P 2 ) wet period), also supported the increase of the ciliate population during (P 2 ) wet period. Finally, for the poorly studied P. arcuatum, also belonging to large dinoflagellates, mixotrophy and opportunistic nature was supported by the absence of correlation between abundance and nutrient concentration [START_REF] Skejić | Morphology and ecology of the poorly known dinoflagellate prorocentrum arcuatum (dinophyceae) from the medulin bay (eastern Adriatic sea)[END_REF].

Impacts on diatom community

Although diatom community was less impacted by the increase of wintering rainfall rate during P 2 than dinoflagellates (see appendix A), main diatom taxa were associated to dry periods (P 1 and P 3 ). Strict autotrophic siliceous diatoms are more sensitive to nutrient depletion or change in nutrient supply ratios than dinoflagellates, particularly for silicon (Si) [START_REF] Anderson | Harmful algal blooms and eutrophication:nutrient sources, composition and comsequences[END_REF]. It was assumed that diatoms were favored in Si:N:P = 16:16:1 conditions [START_REF] Redfield | The influence of organims on the composition of sea-water[END_REF] and that a variation from this ratio may result in a community shift toward non siliceous and smaller community [START_REF] Cloern | Our evolving conceptual model of the coastal eutrophication problem[END_REF][START_REF] Reynolds | Ecology of Phytoplankton[END_REF]. For instance, a decrease in SI:N ratio in Bay of Brest between 1977 and 1995 due to an increase of anthropogenic nitrogen inputs from runoff, led to a limitation of the spring bloom intensity and an increase of haptophyta Phaeocystis sp. bloom [START_REF] Chauvaud | Long-term variation of the Bay of Brest ecosystem:benthic-pelagic coupling revisited[END_REF]. Though nutrients (mainly nitrates) and organic matter as well as metallic contaminant were carried into Toulon Bay by Eygoutier River induced by heavy rain events [START_REF] Nicolau | Transfer of nutrients and labile metals from the continent to the sea by a small Mediterranean river[END_REF], the relation between our increase of rainfall and nutrient supply remained unclear due to the lack of data. However, the reduction and the disappearance of the most abundant spring bloom diatom taxa as well as the silico flagellate Dictyocha sp. during P 2 suggested a nutrient depletion condition or a change in nutrient supply ratios. Also, as mixotrophic dinoflagellates were known to outcompete diatoms in organic nutrient conditions [START_REF] Spilling | Shifting diatom-dinoflagellate dominance during spring bloom in the Baltic Sea and its potential effects on biogeochemical cycling[END_REF], the change observed within the community may also suggest the impact of organic matter input from the Eygoutier River. It is interesting to note that such hypothesis contrast with the few available studies investigating the impact of freshwater runoff on phytoplankton communities in coastal northwestern subbasin due to specific trophic state conditions. For instance, from shallow Blanes Bay station (Catalan coast) rainfall events were followed by an increase of diatom, dinoflagellate or cryptophyte abundances as well as spring bloom intensity [START_REF] Nunes | Seasonal and interannual variability of phytoplankton community structure in a Mediterranean coastal site[END_REF]. Similarly, in oligotrophic northern coastal Adriatic sea, the reduction of freshwater flow was identified as a driver of both change in phytoplanktonic composition, and reduction of total abundance during the 1986-2077 period [START_REF] Aubry | Plankton communities in the northern Adriatic Sea: patterns and changes over the last 30 years[END_REF][START_REF] Cabrini | Phytoplankton temporal changes in a coastal northern Adriatic site during the last 25 years[END_REF]. Recently in the same region, a re-increase of the Pô river outflow observed during the 2007-2016 was followed by a reduction of coccolithophorid and by an increase in phytoflagellate biomass [START_REF] Totti | Phytoplankton communities in the northwestern Adriatic Sea: interdecadal variability over a 30-years period (1988-2016) and relationships with meteoclimatic drivers[END_REF].

Impacts on chlorophyll a

In Toulon Bay, the absence of significant change in chlorophyll a concentration at the decadal scale contrast with the total microphytoplankton dynamic which followed mainly diatom variations. A significant negative correlation was furthermore found between their respective trends. As such, and although nanophytoplankton coccolithophorids were not investigated, chlorophyll a concentration would reflected mainly the nanophytoplankton dynamic rather than upper phytoplankton size class. As pointed out by [START_REF] Uitz | Estimates of phytoplankton class-specific and total primary production in the Mediterranean Sea from satellite ocean color observations: PRIMARY PRODUCTION IN THE MEDITER-RANEAN[END_REF], except during blooming periods, small size classes of phytoplankton (particularly nanoplankon) contributed more to chlorophyll a concentration than microphytoplankton in NW Mediterranean Sea. Nanophytoplankton was also known to 'overcompete' other phytoplankton classes in oligotrophic conditions [START_REF] Siokou-Frangou | Plankton in the open Mediterranean sea: a review[END_REF], particularly due to a higher population growth rate and their ability to reduce the nutrient diffusion [START_REF] Marañón | Cell size as a key determinant of phytoplankton metabolism and community structure[END_REF]. Thus, the contrasted dynamics between microphytoplancton and chlorophyll a also argue in favor of a shift in trophic conditions toward oligotrophy as a result of the increased rainfall rate. This shift would lead, in turn to changes from diatom and microflagellate dominance to smaller phytoplankton dominance-based system, which favored opportunistic large dinoflagellates.

Footprints from wintering deep mixings

Impact of wintering deep mixings was also observed in total microphytoplankton abundance as well as in diatom anomalies. During the early 2000s, deficit in freshwater budget caused by a low annual pre Serranito et al. Estuarine, Coastal and Shelf Science xxx (xxxx) 7) and reported deep-mixings, supported the hypothesis of the influence of regional mixing events on local microphytoplankton. Likewise, high salinity and dry conditions observed in 2005-2007 period (P 1 ) were in agreement with the increase of salinity and the deficit in precipitation pointed out from the early 2000's in Ligurian Basin [START_REF] Marty | Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995-2007 and biogeochemical consequences[END_REF]. It would confirm the role of salinity as a powerful indicator of large scale process in NW Mediterranean Sea [START_REF] Somot | Transient climate change scenario simulation of the Mediterranean Sea for the twenty-first century using a high-resolution ocean circulation model[END_REF]. However, no coherent change or trend was identified in water temperature in Toulon Bay during the 2005-2017 period (Fig. 3c). Changes in water temperature has been also suspected as the main hydrologic feature related to climate change and large scale processes in NW Mediterranean Sea [START_REF] Goffart | Drivers of the winter-spring phytoplankton bloom in a pristine NW Mediterranean site, the Bay of Calvi (Corsica): a long-term study (1979-2011[END_REF][START_REF] Goffart | Changes in the development of the winter-spring phytoplankton bloom in the Bay of Calvi (NW Mediterranean) over the last two decades: a response to changing climate?[END_REF][START_REF] Trigo | Decline in Mediterranean rainfall caused by weakening of Mediterranean cyclones[END_REF][START_REF] Vargas-Yáñez | Climate change in the western Mediterranean sea 1900-2008[END_REF], 2008). We assumed that the absence of significant variability of water temperature in Toulon Bay during wintering deep mixing events (i.e. decrease of Sea Surface Temperature) [START_REF] Marty | Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995-2007 and biogeochemical consequences[END_REF] was probably due to both low water circulation into the bay and the impact of the local northern cold wind (Mistral). Second salty and dry period observed from early 2015 was also followed in winter and spring 2017 by an abrupt increase in total microphytoplankton abundance as well as positive anomalies in diatom and particularly in autotrophic microflagellates. Similarly to the beginning of 2000's, as low precipitation rate was observed in other meteorological stations around the Ligurian basin (i.e. Marseille, Nice and Calvi, see appendix F for details), a new freshwater deficit at a regional scale was suspected, leading to a potential new intense mixing event in 2017. Due to the absence of current reports, further investigations on late 2010s would be necessary to confirm occurrence of such a new deep mixing in Ligurian Sea as suggested by our biological responses and abiotic conditions.

U N C O R R E C T E D P R O O F B.
From the above discussion points, we produced a simplified model (Fig. 8) about the impact of rainfall on long term microphytoplankton dynamic in Toulon Bay, through two main mechanisms: 1) regional deep mixing events triggered by rainfall deficit, is the main fertilization driver of Toulon Bay, by shaping interannual variations of microflagellate and particularly diatom spring bloom intensity. 2) the impact of wintering runoff intensification which promote smaller primary producer and lead to substantial changes in upper trophic levels such as in heterotrophic protists.

Community variability during dry periods

Although both dry and salty periods i.e. 2005-2008 (P 1 ) and 2015-2017 (P 3 ) shared assemblages dominated by diatoms and smaller microflagellate taxa, numerous taxa were associated with only one of them. Thus, P 1 appeared mainly associated with diatoms and some heterotrophic flagellates whereas P 3 was characterized by smaller autotrophic microflagellate (mainly cryptophyte species H.fusiformis) as shown by IndVal g (Table 3). Such pattern characterizing a second alternation in primary producer nature may be driven by another notable variability in nutrient supply during dry period. For instance, as the nutrient content of deep layers showed a decadal variability [START_REF] Pasqueron De Fommervault | Temporal variability of nutrient concentrations in the northwestern Mediterranean sea (DYFAMED time-series station)[END_REF], variations in the composition of the nutrients provided by wintering mixing events could be considered. Likewise, presence of instabilities from Northern Current in Toulon Bay [START_REF] Guihou | A case study of the mesoscale dynamics in the North-Western Mediterranean Sea: a combined data-model approach[END_REF] could represent another local factor of nutrient enrichment, fueling punctual blooms [START_REF] Casella | Ecosystem dynamics in the Liguro-Provençal Basin: the role of eddies in the biological production[END_REF] Fig. 8. Simplified scenario of microphytoplanktonic ecosystem functioning in Toulon Bay related to wintering rainfall variability. Arrows indicated highlighted (full black) and suspected (dashed grey) trophic relations between investigated (full circles) and not-investigated (dashed circles) planktonic communities. Arrow thickness indicated the strength of relation supported by evidences. Rainy winters seemed favor small autotrophic cells (nanoflagellates) leading to important increase of large heterotrophic dinoflagellates sustained by ciliates. Dry winters promoted slightly abundant diatom and especially micro-flagellate communities which were highly correlated with small mixotrophic dinoflagellates. Both diatoms and small dinoflagellates may also be predated by larger dinoflagellates (mainly Protoperidinium spp.). Finally, rainfall deficit over several years was assumed as a driver of winter deep mixing at regional scale which triggered intense diatom spring blooms in Toulon Bay.

as pointed out in the French Riviera [START_REF] Sammari | Aspects of the seasonal and mesoscale variabilities of the Nothern current in the western Mediterranean Sea inferred from the PRO-LIG-2 and PROS-6 experiments[END_REF][START_REF] Taupier-Letage | General hydrodynamical features in the Ligurian Sea inferred from the DYOME experiment[END_REF].

Conclusion

Using long-term monitoring time-series (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017), the present study provides new insights on decadal microphytoplancton variations in a semi-enclosed and anthropized area, highlighting cell size as an important descriptor of structure composition changes. Our data showed that precipitations were a keystone of microphytoplankton dynamics as it was involved in assemblage variations and bloom intensity: 1) Local wintering runoff was suspected to modify water nutrient supply ratio to the benefit of smaller and non-siliceous autotrophic communities such as nanophytoplankton and promoting opportunistic heterotrophic protists. 2) Regional rainfall deficit was identified as an important conditioning factor for wintering deep mixings in Ligurian Basin, and a key regulator of intense diatom and microflagellate spring blooms in the northern coast. Further investigations might be necessary to highlight suspected impacts of riverine on nutrient concentrations as well as consequences in upper trophic levels such as copepods. Furthermore, our results support the idea that microphytoplankton composition with an emphasis on size structure can be used as BQE regarding of WFD and MSFD (Marine Strategy Framework Directory, 2008/56/ EC) policies as it succeeds to detect substantial changes in plankton ecosystem functioning while chlorophyll a concentration failed. As a result, we highlighted the importance to consider the size of dinoflagellate as a hallmark of deep changes in trophic state of coastal ecosystems. Finally, in agreement with [START_REF] Nunes | Seasonal and interannual variability of phytoplankton community structure in a Mediterranean coastal site[END_REF], this work confirms the need of a higher consideration of rainfall variations for future predictions related to climate change in the frame of coastal management as it represents a major stressor for ecosystems confronted to high human pressures.

Declaration of interests

None.

Appendix C.

Mean difference in dinoflagellate species abundances between P2 and P1 (left panel) and between P3 and P2 (right panel) with respect to their mean cell biovolume. X axis was expressed in log transformed data to linearize the relation. Full red lines with confident interval (shaded areas) were for significant linear regressions on log transformed biovolums, used to evaluate the threshold defining lifeforms. Red dotted vertical line indicated when the linear model displayed a change in sign in the difference, leading to an average biovolume threshold at 1,5.10

Fig. 1 .

 1 Fig. 1. Map of Toulon Bay with location of the Large Bay phytoplankton sampling site (LaB) and the REPHY sampling site (Rephy 112-P-010). The meteorological Toulon station was also identified (black points), as well as The Eygoutier River and AmphorA wastewater outfall flowing to the Large Bay. Main cyclonic circulation of the Large bay was also specified (adapted from Dufresne et al. (2014)) (dotted arrowed line).

  were monthly measured at "LaB" between January 2005 and March 2007 and between March and December 2015.

  ). First change was observed during late-fall 2008 and spring 2009 and a second during winter 2015 and at the end of 2015, in environmental and microphytoplankton datasets respectively (see appendix D). Despite the uncertainty about the timing of the second change point in microphytoplankton composition due to a lack of data during 2015, PERMANOVA analysis indicated the significance of the partitioning (pval<0.01) (Table

Fig. 2 .

 2 Fig. 2. Comparison of the chronological clusterings performed on the 2006-2017 "environmental" dataset (water temperature, salinity and rainfall rate) using euclidean distance (left cluster) and on the 2005-2017 "micro-phytoplankton community" dataset using log-Chord distance (right cluster). For each dataset, colored branches identified 3 homogeneous periods (P 1 , P 2 , and P 3 in blue, red and brown) extracted from the 2 main change points (Cut-off levels at h = [3658; 3429] and h =[67.2; 64.4] for the "environmental" and the "micro-phytoplankton" time series, respectively). Asymmetry between year boxes was relative to missing values in biological time-series. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

  Fig. 3. 2005-2017 time series of rainfall rate (a), salinity (b), and water temperature (c). Moving average (solid black line) and loess filter regression (α = 0.3) (blue line) were performed on raw data (black dots) to summarize the trend. Significant mean changes were indicated by red segments. Shaded area indicated (P 2 ) wet period delimited by change points (vertical dotted lines) from environmental clustering. Respective mean annual variations (d, e and f) over the 2005-2017 (dark thick line) and the monthly averaged value with non-parametric 0.95 confident interval during each extracted period (blue, red and brown for P 1 , P 2 and P 3 , respectively). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

  identifying2005-2006, 2007-2014 and 2015-2017 subperiods. The first change occurred during early spring 2007 while the second appeared in early winter 2015 and coincided with the second change in partitioning analysis (Fig.2). The 2005-2006 subperiod was characterized by a higher average abundance (6.10 4 cells.l -1 ) and contrasted with lowest average abundance observed during 2007-2014 period (3.10 3 cells.l -1 ). Finally, second change point was characterized by an increase of total abundance during the 2015-2017 subperiod (mean of 2

Fig

  Fig. 4. 2005-2017 N-NO x -and P-PO 4 3-time series (a and b, respectively) and annual variations (c and d, respectively) over the 2005-2017 period and mean monthly values from P 1 , P 2 and P 3 (blue, red and brown, respectively) with non-parametric 0.95 confident interval. Shaded area indicated (P 2 ) wet period delimited by change points (vertical dotted lines) from environmental clustering. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

  Finally, P 3 was mainly associated with autotrophic microflagellates species (e.g. Rhodomonas sp. (0.93), Hillea fusiformis (0.93), Chlorella sp. (0.92) but also with diatom taxa (e.g. Cyclotella spp. (0.88), Nitzschia spp. (0.84), Navicula sp. (0.78), Guinardia spp. (0.75)) and some dinoflagellates (e.g. Gymnodinium spp. (0.89), Gyrodinium sp. (0.83), P.micans. (0.74), Oxytoxum spp. (0.68)).

Fig. 6 .

 6 Fig. 6. Mean cell biovolume variations of diatom (left panel), dinoflagellate (middle panel) and micro-flagellate (right panel) communities during the 3 extracted periods (P 1 , P 2 and P 3 ). Black dots were for data, red point indicated averaged values during each period and red line summarized changes in mean. Boxplot indicated values ranged between the 25 and 75th percentile and median values. Results for Wilcoxon pairwise comparison using Bonferroni correction were specified: NS: no significant. * <0.05, ** <0.01, *** <0.001. Values were represented in 10 log scale. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

  et al.Estuarine, Coastal and Shelf Science xxx (xxxx) xxx-xxx

Table 1

 1 Summary of representative micro-phytoplankton taxa features with average abundance (Ab), respective standard deviation and mean contribution in total phytoplankton abundance(Cont)

	respectively for P 1 , P 2 , P 3 , and overall the 2005-2017 period (Tot); name abbreviation (Abb); geometric cellular shape associated (Shape); mean cellular biovolum (Biov); corresponding lifeform (Lifeform): diatoms (Diat), micro-flagellates (Fla), small dinoflagellates (s.Dino) and large dinoflagellates (L.Dino); trophic status reported in literature for dinoflagellate with references: H: Heterotrophic M:Mixotrophic. A:Autotrophic. (): trophic status was suggested. ?: absence of trophic preference data.
	Class	Species	Abb	Ab	Cont (%)			Shape	Biov	Life form	Trophic status
				(ind.l -1 )	Tot	P 1	P 2	P 3		(μm 3 )
	Diatoms Micoflagellates Dinoflagellates	Pseudonitzschia delicatissima Chaetoceros spp. Cyclotella spp. Thalassionema spp. Leptocylindrus danicus Guinardia spp. Cylindrotheca closterium Pseudonitzschia seriata Actinoptychus spp. Coscinodiscus spp. Dactyliosolen fragilissimus Nitzschia spp. Skeletonema costatum Licmophora gracilis Navicula spp. Rhizosolenia spp. Bacteriastrum delicatulum Asterionellopsis glacialis Pleurosigma spp. Thalasiosira spp. Gyrosigma spp. Lioloma spp. Pseudonitzschia sp. Fragilariopsis cylindrus Hemiaulus hauckii Mean Hillea fusiformis Chlorella sp. Dictyocha spp. Chromulina sp. Leucocryptos sp. Rhodomonas sp. Hemiselmis sp. Chlamydomonas sp. Heterosigma sp. Tetraselmis spp. Mean Gymnodinium spp. Ceratium furca Prorocentrum micans Prorocentrum arcuatum Scrippsiella spp. Achradina spp. Alexandrium spp. Ceratium fusus Oxytoxum spp. Gyrodinium sp. Goniodoma sp. Gonyaulax spp. Protoperidinium divergens Protoperidinium pellucidum	P.del Chae Cyc Tnema L.dan Gui C.clo P.ser Act Cos D.fra Nit S.cos L.gra Nav Rhi B.del A.gla Pleu Tsira Gyros Lio Pseu F.cyl H.hau H.fus Chlo Dict Chro Leu Rho Hemi Chla Het Tet Gym.spp C.fur P.mic P.arc Scri Achr Alex C.fus Oxy Gyrod Gon Gony P.div P.pel	2′791 ± 11′437 6′057 ± 47′102 388 ± 1′528 409 ± 1′773 1′270 ± 7′902 192 ± 575 167 ± 548 437 ± 3′030 23 ± 58 21 ± 37 168 ± 938 48 ± 172 628 ± 6′583 17 ± 67 19 ± 37 33 ± 156 141 ± 894 192 ± 1883 9 ± 22 29 ± 96 3 ± 9 1 ± 6 9 ± 95 2 ± 16 5 ± 22 13′059 461 ± 1′314 314 ± 915 75 ± 224 18 ± 61 18 ± 59 46 ± 207 23 ± 97 6 ± 22 10 ± 52 55 ± 363 1′026 760 ± 1′751 39 ± 71 48 ± 130 32 ± 76 61 ± 166 43 ± 121 22 ± 54 11 ± 19 27 ± 164 48 ± 229 7 ± 18 7 ± 14 8 ± 19 5 ± 15	11.8 10.4 6.8 4.6 3.8 3.7 2.1 1.4 1.2 1.2 1.1 0.8 0.8 0.6 0.6 0.6 0.5 0.4 0.4 0.3 0.2 0.2 0.2 0.1 0.1 53.3 6.1 3.3 2.3 0.6 0.4 0.4 0.3 0.2 0.2 0.2 14.2 13 2 1.8 1.7 1.5 1.1 0.7 0.5 0.5 0.4 0.3 0.3 0.3 0.3	15.5 20.8 5.8 6.7 14.8 3.7 5.3 10.3 2.4 0.7 11.1 0.8 3.2 2.2 1.5 1.0 3.8 2.1 0.8 1.2 0.7 0.4 0.1 1.2 0.8 61.1 4.8 2.2 5.9 2.9 2.4 0.3 0.1 1.6 0.9 0.3 12.8 16.6 1.9 1.4 1.2 2.8 2.9 1.7 0.6 0.7 0.2 0.5 0.6 0.1 0.4	24.3 15.8 10.1 7.7 0.7 11.1 1.6 1.4 3.3 4.5 0.2 1.9 2.0 1.7 1.2 2.8 0.0 0.0 1.6 0.0 0.4 2.6 2.8 0.0 0.0 57.3 6.9 8.6 3.4 0.7 0.3 0.6 0.1 0.0 0.5 0.0 11.7 8.6 6.1 5.5 5.7 2.8 1.7 2.7 1.5 0.9 0.8 1.3 0.6 1.3 1.4	17.8 8.4 8.2 3.3 12.5 6.4 5.3 2.9 0.0 0.5 0.0 1.8 0.0 0.5 0.7 1.0 0.0 0.6 0.3 0.6 0.0 0.1 0.0 0.0 0.0 39.8 12.2 6.8 3.4 0.0 0.0 1.7 2.4 0.2 0.3 1.6 34.0 10.2 0.5 1.8 0.3 0.3 0.9 0.5 0.1 1.6 1.6 0.1 0.1 0.2 0.1	prism on parallelogram base 2 cônes cylinder cylinder cylinder cylinder cylinder prism on parallelogram base cône + half sphere elliptic prism cylinder prism on parallelogram base cylindre gomphonemoid elliptic prism cylinder cylinder cylinder prism on parallelogram base parallelepiped prism on parallelogram base cylinder prism on parallelogram base prism on elliptic base cylinder cône + half sphere sphere sphere sphere cône + half sphere cône + half sphere prolate spheroid sphere cône + half sphere prolate spheroid ellipsoïd prolate spheroid + 2 cones + cylinder prolate spheroid prolate spheroid prolate spheroid prolate spheroid prolate spheroid 2 cônes prolate spheroid ellipsoïd sphere cône + half sphere 2 cônes 2 cônes	536 2′612 2′521 1′695 2′679 33′384 426 1′419 9′531 140′122 21′657 15′161 1′927 2′653 14′833 247′143 2′867 496 20′863 10′941 19′274 30′598 5′150 2′276 19′721 316 503 6′587 856 198 1′059 983 1′544 1′425 1′488 6′338 59′072 9′634 23′125 7′701 3′116 7′968 10′679 6′065 13′480 63′809 37′431 46′645 23′324	Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Diat Fla Fla Fla Fla Fla Fla Fla Fla Fla Fla s.Dino L.Dino s.Dino L.Dino s.Dino s.Dino s.Dino s.Dino s.Dino s.Dino L.Dino L.Dino L.Dino L.Dino	A A A A A A A A A A A A A A A A A A A A A A A A A A A A (M) (15) H (13) A M (15) M (19) A (M) (5) M (2,11,18) M (7,8,11,18) M (11,17,18) ? M (11,21) (H) (16) M (3,11) M (11. 18) H (7) M (11,18) ? M (3,6) H (10,11) H (11)

Table 1 (

 1 Continued)

	Class	Species	Abb	Ab	Cont (%)				Shape	Biov	Life form	Trophic status
				(ind.l -1 )	Tot	P 1	P 2	P 3		(μm 3 )
		Protoperidinium pentagonum large Protoperidinium spp. Amphidinium spp. Amylax spp. Ceratium penatogonum Corythodinium sp. Dinophysis acuminata small Protoperidinium spp Mean	P.pen Prot.L Amp Amy C.pen Cor D.acu Prot.s	5 ± 18 6 ± 19 12 ± 76 4 ± 12 3 ± 8 6 ± 21 5 ± 13 9 ± 38 1′168	0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 26.0	0.4 0.0 1.3 0.3 0.3 0.9 0.2 0.9 26.1	1.3 1.6 0.1 0.9 1.3 0.6 0.8 0.0 31.0	0.0 0.1 0.5 2.0 0.1 0.0 0.4 0.2 26.2	2 cônes prolate spheroid ellipsoïd cône + half sphere prolate spheroid + 2 cones + cylinder 2 cônes ellipsoïd 2 cônes	156′799 17′548 1′838 5′054 101′915 4′026 22′266 7′043	L.Dino L.Dino s.Dino s.Dino L.Dino s.Dino L.Dino s.Dino	H (11) H (11) (M) (11,21) (M) (9,14) ? ? M (1,9,12) H (11)
	Notes: (1) Berland et al. (1995); (2) Bockstahler and Coats (1993); (3) Brahim et al. (2015); (4) Buric et al. (2009); (5) Cid et al. (1992); (6) Hansen et al. (1996); (7) Ignatiades (2012); (8) Ignatiades and Gotsis-Skretas (2010); (9) Jacobson and Anderson (1996); (10) Jeong (1994); (11) Jeong et al. (2010); (12) Kim et al. (2008); (13) Novarino et al. (1997); (14) Park et al. (2013); (15) Saad et al. (2016); (16) Sakka et al. (2000); (17) Shim et al. (2011); (18) Stoecker (1999); (19) Weithoff and Wacker (2007); (20) Yamaguchi and Horiguchi (2005) (21) Yoo et al. (2010);

Serranito et al. Estuarine, Coastal and Shelf Science xxx (xxxx) xxx-xxx

  xxx-xxx cipitation rate was identified as the main driver of intense convection events in the central Ligurian Sea, observed in 2005 and particularly in 2006[START_REF] Marty | Hydrological changes in the Ligurian Sea (NW Mediterranean, DYFAMED site) during 1995-2007 and biogeochemical consequences[END_REF]. More recently,[START_REF] Coppola | Seasonal and inter-annual variations of dissolved oxygen in the northwestern Mediterranean Sea (DYFAMED site)[END_REF], reported at the DYFAMED point (central Ligurian Sea), a deepening of MLD during the winter 2013 suggesting a new but less intense, deep-mixing event. Concomitance between positive anomalies observed in diatom abundances during spring2005[START_REF] Reynolds | Ecology of Phytoplankton[END_REF] and 2013 (Fig. (Fig.

3-annual mean variations showed values ranged between 0.15 μmol l -1 in January and 0.03 μmol l -1 in

Acknowledgements

We would like to thank Dr Daniel Petit for his helpful comments, Dr Charlotte Dubois and Dr Luce Perié for the proofreading of the manuscript and their valuable advices. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Fundings

This study was financed by an in-house funding from the EBMA (Marine Ecology and Biology) research team (PROTEE laboratory EA 3819, University of Toulon, France).

Author contributions

B.S. conceived this study, designed figures, performed analysis and wrote the paper. D.J., J-L.J, N.R., and B.S. participated to the biological data collection. D.J. with N.R. realized the biological sampling expertise. B.S. also gathered abiotic data and other biological traits with D.J. and N.R. D.J. and J-L.J. conceived the global framework of the project and were responsible to the setting up of plankton monitoring in Toulon Bay. All authors agreed on the final version of the manuscript.

Appendix A.

Summary of the non-parametric pairwise ANOSIM analysis between extracted periods (P 1 , P 2 et P 3 , respectively) for total microphytoplankton community (Total) and for diatoms, dinoflagellates and microflagellates, using respective log-chord distance matrix, and for each season independently (JFM, AMJ, JAS, and OND, were for winter, spring, summer and fall, respectively). Analysis returned "R" values, ranged between -1 and 1, indicating the degree of differences between periods. High positive values suggested more similarities within the same period than between periods. Significance of differences between periods (blue bold cases) was performed by bootstrapping using 10′000 random permutations with Bonferroni corrections.

Appendix B.

Details and summary for biovolume computation of selected taxa.