Faycal Kessouri

Caroline Ulses

Claude Estournel

Patrick Marsaleix

Tatiana Severin

Mireille Pujo-Pay

Jocelyne Caparros

Patrick Raimbault

Orens Pasqueron De Fommervault

Fabrizio D'ortenzio

Vincent Taillandier

Pierre Testor

Pascal Conan

Nitrogen and phosphorus budgets in the Northwestern Mediterranean deep convection region

Keywords: Mediterranean Sea, physical-biogeochemical modeling, nutrient seasonal dynamics, nitrate and phosphate budget, N:P stoichiometry

Key points up to three (<140 characters) -Modeling of annual nitrogen and phosphorus cycles in the northwestern Mediterranean deep convection region for the period 2012-2013.

-The deep convection area was a sink of inorganic matter and a source of organic matter for the surrounding area over the period 2012-2013.

Introduction

The Mediterranean Sea, often considered as an oligotrophic region [Antoine et al., 1995], exhibits nutrient-depleted surface waters most of the year and low nutrient concentrations in deep waters [START_REF] Krom | Phosphorus limitation of primary productivity in the eastern Mediterranean Sea[END_REF]. With respect to the global ocean Redfield nitrate (NO 3 ) to phosphate (PO 4 ) ratio of 16:1 [Redfield, 1964], the Mediterranean Sea is characterized by particularly high values [Ribera d'Alcalà et al., 2003]. Moreover, these oligotrophic conditions and high NO 3 :PO 4 (hereafter N:P) ratios show a pronounced east-west gradient [START_REF] Pujo-Pay | Integrated survey of elemental stoichiometry (C, N, P) from the western to eastern Mediterranean Sea[END_REF], with the eastern basin presenting ultra-oligotrophic conditions. The N:P ratios in deep layers were estimated at 20-22 in the western sub-basin [Béthoux et al.1998] and at 27-30 in the eastern sub-basin [Ribera d'Alcala et al., 2003] of the Mediterranean.

The distribution of nutrients in the semi-enclosed Mediterranean Sea results from internal physical and biogeochemical dynamics, from atmospheric and terrestrial inputs, and from exchanges with the Atlantic Ocean and the Black Sea. Physical dynamics are partly controlled by the formation of intermediate and deep waters as the winter climate of the Mediterranean Sea is characterized by cold, dry local winds blowing from the north [Hauser et al., 2003], which induce an increase of the surface layer density by strong evaporation and cooling, and then trigger the deep convection mixing. This process is responsible for the formation of intermediate and deep water masses in the northwestern basin (hereafter NW Med) [Medoc Group, 1970], the south Adriatic [START_REF] Pollak | The sources of deep water of the Eastern Mediterranean Sea[END_REF], the Aegean [START_REF] Nittis | Dense water formation in the Aegean Sea: Numerical simulations during the Eastern Mediterranean Transient[END_REF] and the Rhodes Gyre [START_REF] Ovchinnikov | The formation of Intermediate Water in the Mediterranean[END_REF]. The high nitrate and phosphate surface concentrations (values close to deep concentrations) observed during convective episodes in these regions [Yilmaz and Tugrul, 1998;Gacic et al., 2002;[START_REF] Santinelli | New insights into C, N and P stoichiometry in the Mediterranean Sea: The Adriatic Sea case[END_REF][START_REF] Severin | Impact of open-ocean convection on nutrients, phytoplankton biomass and activity[END_REF] demonstrate that the deep convection process is also responsible for large nutrient enrichments of the upper layers. In addition, a study based on satellite-derived chlorophyll a data [D'Ortenzio and Ribera d'Alcalà, 2009] has shown that the deep convection regions are characterized by intense to moderate spring blooms, while phytoplankton development in the rest of the open Mediterranean Sea is of low magnitude. This feature of phytoplankton dynamics in convection regions may be explained by the large amounts of nutrient supplied during the intense vertical mixing events [Lavigne et al., 2015].

Among the deep convection regions of the Mediterranean Sea, the NW Med (Fig. 1A) has been identified as the region where the vertical mixing and the associated phytoplankton spring bloom are the most intense and recurrent [START_REF] Houpert | Seasonal cycle of the mixed layer, the seasonal thermocline and the upperocean heat storage rate in the Mediterranean Sea derived from observations[END_REF]D'Ortenzio and Ribera d'Alcalà, 2009;[START_REF] Lavigne | Impact of mixed layer depth seasonal variations on the phytoplankton phenology in the Mediterranean Sea[END_REF]Mayot et al., 2016]. The NW Med convection has been shown to largely influence the regional biogeochemical cycles and marine ecosystems, mostly by importing nutrient-enriched deep waters to the surface [START_REF] Severin | Impact of open-ocean convection on nutrients, phytoplankton biomass and activity[END_REF][START_REF] Estournel | High resolution modeling of dense water formation in the north-western Mediterranean during winter 2012-2013: Processes and budget[END_REF]. This enrichment changes the biogeochemical characteristics of the surface layers [START_REF] Durrieu De Madron | Marine ecosystems' responses to climatic and anthropogenic forcings in the Mediterranean[END_REF][START_REF] Herrmann | Impact of atmospheric and oceanic interannual variability on the Northwestern Mediterranean Sea pelagic planktonic ecosystem and associated carbon cycle[END_REF][START_REF] Auger | Interannual control of plankton communities by deep winter mixing and prey/predator interactions in the NW Mediterranean: Results from a 30-year 3D modeling study[END_REF], induces a large phytoplankton spring bloom [D'Ortenzio et al., 2009;[START_REF] Lavigne | Impact of mixed layer depth seasonal variations on the phytoplankton phenology in the Mediterranean Sea[END_REF][START_REF] Estrada | Seasonal and mesoscale variability of primary production in the deep winter-mixing region of the NW Mediterranean[END_REF], favors high particulate carbon export [Gogou et al., 2014;[START_REF] Estournel | High resolution modeling of dense water formation in the north-western Mediterranean during winter 2012-2013: Processes and budget[END_REF] and shifts the zooplankton community toward larger sized organisms [START_REF] Auger | Interannual control of plankton communities by deep winter mixing and prey/predator interactions in the NW Mediterranean: Results from a 30-year 3D modeling study[END_REF]. Moreover, deep convection in the NW Med has also been shown to promote a change of the surface nutrient ratios [START_REF] Severin | Impact of open-ocean convection on nutrients, phytoplankton biomass and activity[END_REF]Pasqueron de Fommervault et al., 2015a]. However, the impact of nutrient replenishments on the seasonal cycles of nitrogen and phosphorus has been poorly explored. The few quantifications of the upward flux of nitrate and phosphate that have been performed [START_REF] Severin | Impact of open-ocean convection on nutrients, phytoplankton biomass and activity[END_REF][START_REF] Estournel | High resolution modeling of dense water formation in the north-western Mediterranean during winter 2012-2013: Processes and budget[END_REF] remain limited in space and/or time. A thorough quantification of the processes linked to the seasonal variations of nitrogen and phosphorus cycles during one complete year has not yet been proposed in this region.

The objectives of the DeWEX project (Deep Water formation EXperiment) are (i) to better understand the impact of dense water formation on the marine biogeochemical cycles and (ii) to provide a consistent dataset of hydrological and biogeochemical parameters to improve the numerical modeling of the convection hydrology and coupled biogeochemical processes. To fulfill these objectives, oceanographic research vessels covered the deep convection area during each season from summer 2012 to summer 2013. Once calibrated and validated, numerical modeling is expected to achieve goals at different time scales. In the short term, the model is expected to interpolate between the DeWEX cruises to calculate the nutrient and organic matter budgets over an annual cycle. In the long term, and after complementary validations with multiyear datasets, modeling will be used as an integrative tool to investigate the question of how climate change and anthropogenic activities could impact the cycle of biogenic elements and marine ecosystems.

The present study aims to quantify the dynamics of nutrients at the seasonal scale and to estimate an annual budget of nitrogen and phosphorus, in the NW Med dense water formation area. After a brief description of the observation network, the modeling strategy is described (section 2), and then evaluated through comparisons with observations (section 3). The seasonal variabilities of the atmospheric forcing and hydrography are presented (section 4.1.1), together with the annual cycles of nutrient stocks in the upper layer (4.1.2). In section 4.1.3, we discuss the impact of physical and biogeochemical processes on the N:P ratio in the upper layer. Finally, an annual nitrogen and phosphorus budget of the region is proposed (section 4.2).

Method

2.1.Observations

During the period from September 2012 to September 2013, a large number of hydrological and biogeochemical observations (>178 profiles) were made in the NW Med in the framework of the MERMEX (Marine Ecosystems Response in the Mediterranean Experiment) and HyMeX (Hydrological cycle in the Mediterranean Experiment) programs. The objective was to better understand the interactions between horizontal and vertical physical processes during a convection event [Estournel et al., 2016a] and their impact on nutrient budgets and marine ecosystems.

In this study, we used the observations collected during three cruises that covered the NW Med in winter, spring and summer of 2013. During DeWEX Leg 1, conducted from 1 to 21 February Confidential manuscript submitted to Journal of Geophysical Research Oceans 6 2013 on board the R/V Le Suroît, 75 hydrological and 45 biogeochemical profiles were obtained (Fig. 1B) [Testor, 2013;[START_REF] Severin | Open-oceanconvection process: A driver of thewinter nutrient supply and the springphytoplankton distribution in theNorthwestern Mediterranean Sea[END_REF], with the objective of globally mapping the convection area, the distribution of the newly formed deep waters and the distribution of inorganic and organic matter. DeWEX Leg 2 sampled the spring bloom from 5 to 24 April 2013 [Conan, 2013;Mayot et al., 2017]. It followed the same sampling network as the winter cruise, with 99 hydrological profiles and 59 biogeochemical profiles (Fig. 1C) [START_REF] Severin | Open-oceanconvection process: A driver of thewinter nutrient supply and the springphytoplankton distribution in theNorthwestern Mediterranean Sea[END_REF].

The third cruise was carried out during the oligotrophic period, between 24 July and 7 August 2013, in the framework of the integrated observation network MOOSE (Mediterranean Ocean Observing System for the Environment) [Testor et al., 2013]. 100 biogeochemical profiles were measured (Fig. 1D).

Then, data provided by the Bio-Argo float LovBio17b between April and September 2013 [Pasqueron de Fommervault et al., 2015b] were used to assess the modeled vertical evolution of the nitrate concentration. LovBio17b provided 73 vertical profiles at a daily frequency during the first 55 days of spring, and then at 5-day frequency for the next summer weeks. Calibration was performed at the deployment using in situ observations from 0 to 1000 m depth (about 10 m resolution in the 0-250 m layer, and 30 m below).

2.2.Modeling

Hydrodynamics

The SYMPHONIE model used in this study is a 3D primitive equation, with free surface and generalized sigma vertical coordinate, described by [START_REF] Marsaleix | Energy conservation issues in sigma-coordinate free-surface ocean models[END_REF][START_REF] Marsaleix | Open boundary conditions for internal gravity wave modelling using[END_REF]Marsaleix et al. [ , 2011Marsaleix et al. [ and 2012]]. It was previously used for the Mediterranean Sea to simulate convection in the deep sea [START_REF] Herrmann | Modeling the deep convection in the Northwestern Mediterranean sea using an eddy-permitting and an eddyresolving model: Case study of winter 1986-87[END_REF]Estournel et al., 2016b], coastal dense water formation [START_REF] Estournel | Dense water formation and cascading in the Gulf of Thermaikos (North Aegean) from observations and modelling[END_REF][START_REF] Marsaleix | Energy conservation issues in sigma-coordinate free-surface ocean models[END_REF] and circulation on the continental shelf of the Gulf of Lions [START_REF] Petrenko | Barotropic eastward currents in the western Gulf of Lion, north-western Mediterranean Sea, during stratified conditions[END_REF]. The numerical domain (Fig. 1A) covers most of the western Mediterranean basin, using a curvilinear grid with variable horizontal resolution [Bentsen et al., 1999]. The resolution is 1.4 km to the south and about 0.8 km to the north. The southward decrease of the resolution is intended to cover the W Med basin at a more reasonable cost while considering the northward decrease of the Rossby radius, in particular the need for increased resolution in the winter dense water formation area [Estournel et al., 2016b].

Forty vertical levels were used with closer spacing near the surface (15 levels in the first 100 meters in the center of the convection zone characterized by depths of ~2500 m). The model was initialized and forced at its lateral boundaries with daily analyses provided by the Mercator-Ocean operational system based on the NEMO ocean model [START_REF] Maraldi | NEMO on the shelf: assessment of the Iberia-Biscay-Ireland configuration[END_REF]. The configuration of this model was the PSY2V2R4 prototype based on the NEMO Ocean modeling platform and the SAM data assimilation system [START_REF] Lellouche | Evaluation of global monitoring and forecasting systems at Mercator Océan[END_REF] at a resolution of 1/12° over the Atlantic and the Mediterranean from 20° S to 80° N. As in Estournel et al. [2016b], the initial field and open boundary conditions were corrected for stratification biases deduced from comparisons between analysis and observations taken during the MOOSE cruise of August 2012.

The atmospheric forcing (turbulent fluxes) was calculated using the bulk formulae of [START_REF] Large | Diurnal to decadal global forcing for ocean and seaice models: the data sets and flux climatologies[END_REF]. Meteorological parameters, including radiative fluxes, were given by the ECMWF operational forecasts at 1/8° horizontal resolution and 3-hour temporal resolution based on daily analysis at 00.00 UTC. Since the underestimation of strong winds is a source of uncertainty in atmospheric forcing [Herrmann et al., 2010], Estournel et al. [2016b] performed sensitivity tests to the wind speed. According to those tests, the wind velocity was increased by 13% in order to increase the accuracy of the model results in reproducing the convection event [Estournel et al., 2016b] in our hydrodynamic simulation. River runoffs were considered using measured daily values for French rivers (data provided by Banque Hydro, www.hydro.eaufrance.fr) and the Ebro (data provided by SAIH Ebro, www.saihebro.com) and mean annual values for the others.

Biogeochemistry

The Eco3M-S model [START_REF] Estournel | High resolution modeling of dense water formation in the north-western Mediterranean during winter 2012-2013: Processes and budget[END_REF] is a multi-nutrient and multi-plankton functional type model that simulates the dynamics of the biogeochemical decoupled cycles of several biogenic elements (carbon, nitrogen, phosphorus, silicon and oxygen) and of non-Redfieldian plankton groups. The model comprises seven compartments. A first compartment of phytoplankton classified by size is described by the mechanistic formulations of the model Eco3M [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], where pico-phytoplankton [0.7-2 μm] and nanophytoplankton [2-20 μm] are composed of dinoflagellates, and micro-phytoplankton [20-200 μm] is composed of diatoms. A second compartment of zooplankton is composed of nano-zooplankton [5-20 μm] (small flagellates), micro-zooplankton [20-200 μm] (ciliates and large flagellates) and mesozooplankton [>200 μm] (copepods and amphipods). A third compartment, bacteria, is also considered. The behavior of heterotrophic organisms is derived from the model by Anderson and Pondaven [2003]. The other compartments are dissolved organic matter, particulate organic matter (small and large, differentiated by the settling speed and origin), inorganic nutrients (nitrate, ammonium, phosphate and silicate) and dissolved oxygen. A total of 34 state variables are calculated. The model structure (Fig. 2) used in this study is based on the same pelagic plankton ecosystem model as the one fully described and used by [START_REF] Auger | Functioning of the planktonic ecosystem on the Gulf of Lions shelf (NW Mediterranean) during spring and its impact on the carbon deposition: A field data and 3-D modelling combined approach[END_REF] and Ulses et al. [2016]. Here we recall the equations of the rates of change of the nitrate and phosphate, since we will discuss the time evolution of their stock and of their ratios in section 4.1:

𝜕[𝑁𝑂 3 ] 𝜕𝑡 = 𝑁𝑖𝑡𝑟𝑖𝑓𝑖𝑐𝑎𝑡𝑖𝑜𝑛 -𝑃ℎ𝑦𝑡𝑜𝑝𝑙𝑎𝑛𝑘𝑡𝑜𝑛𝑈𝑝𝑡𝑎𝑘𝑒 (1) 𝜕[𝑃𝑂 4 ] 𝜕𝑡 = 𝑍𝑜𝑜𝑝𝑙𝑎𝑛𝑘𝑡𝑜𝑛𝐸𝑥𝑐𝑟𝑒𝑡𝑖𝑜𝑛 + 𝐵𝑎𝑐𝑡𝑒𝑟𝑖𝑎𝐸𝑥𝑐𝑟𝑒𝑡𝑖𝑜𝑛 -𝑃ℎ𝑦𝑡𝑜𝑝𝑙𝑎𝑛𝑘𝑡𝑜𝑛𝑈𝑝𝑡𝑎𝑘𝑒 (2)
where Nitrification is the nitrification rate, PhytoplanktonUptake is the nutrient uptake by phytoplankton, and ZooplanktonExcretion and BacteriaExcretion are the nutrient excretions by zooplankton and bacteria, respectively. The formulas of these fluxes are given in Auger et al.

[2011] (their Table A4). The uptake of nutrients by phytoplankton (PhytoplanktonUptake) depends on the gross primary production rate and on the nutrient concentrations (A19 to A22 in Table A.4 of [START_REF] Auger | Functioning of the planktonic ecosystem on the Gulf of Lions shelf (NW Mediterranean) during spring and its impact on the carbon deposition: A field data and 3-D modelling combined approach[END_REF]. Excretions (ZooplanktonExcretion and BacteriaExcretion) are the processes enabling heterotrophs to keep their internal composition constant by releasing the excess elements in the form of dissolved inorganic matter (A38 to A42 in Table A.4 of [START_REF] Auger | Functioning of the planktonic ecosystem on the Gulf of Lions shelf (NW Mediterranean) during spring and its impact on the carbon deposition: A field data and 3-D modelling combined approach[END_REF]. Nitrification is the production of nitrate by bacteria, represented here in an implicit way by a first order function of the ammonium concentration (A55 in Table A.4 of [START_REF] Auger | Functioning of the planktonic ecosystem on the Gulf of Lions shelf (NW Mediterranean) during spring and its impact on the carbon deposition: A field data and 3-D modelling combined approach[END_REF]. Nitrification is regulated by light intensity and temperature. For the present study of the NW Med, where winter convection favors strong vertical transport of nutrients in the photic zone, we neglected the process of nitrogen fixation. This process has been shown to have only a small effect on stoichiometry in the W Med [Ribera d'Alcala et al., 2003]. Most of the values of biogeochemical model parameters were based on the previous modeling study by Ulses et al.

[2016], but some parameters were re-calibrated using several datasets (MODIS, BOUM,

MOOSE-GE and DeWEX cruises).

In this study, we used the "Source Splitting" coupling method [Butenschön al., 2012]. It consists in an offline forcing of the biogeochemical model by the daily averaged outputs of the physical model. A time step of a few minutes was used for the advection and diffusion of biogeochemical variables, while Eco3M-S computed the biogeochemical fluxes with a time step of about one hour. It was then assumed that biogeochemical properties do not significantly impact the hydrodynamics.

The biogeochemical model was downscaled from the Mediterranean basin scale to the regional scale as described hereafter. First, the biogeochemical basin scale model was forced by the daily fields from the NEMO model (PSY2V2R4 analyses), also used for the boundary conditions of the hydrodynamic model as indicated in section 2.2.1. This basin configuration was initialized in June 2010 with climatological nutrient fields from the Medar/MedAtlas database [START_REF] Manca | Physical and biochemical averaged vertical profiles in the Mediterranean regions: an important tool to trace the climatology of water masses and to validate incoming data from operational oceanography[END_REF] corresponding to oligotrophic conditions. Daily values of all state variables were extracted from the basin run for the initial and lateral boundary conditions of the regional model. This nesting protocol ensures coherence of the physical and biogeochemical fields at the open boundaries. The regional model was initialized in August 2012.

At the mouth of the Rhone river, nitrate, ammonium, phosphate, silicate and dissolved organic carbon concentrations were prescribed using in situ daily data [P. Raimbault, personal communication, 2015]. Concentrations of dissolved organic phosphorus and nitrogen and also of particulate organic matter were estimated from these data and the relations deduced from the literature [START_REF] Moutin | The input of nutrients by the Rhône river into the Mediterranean Sea: recent observations and comparison with earlier data[END_REF][START_REF] Sempéré | Carbon Inputs of the Rhöne River to the Mediterranean Sea: Biogeochemical Implications[END_REF] as described in [START_REF] Auger | Functioning of the planktonic ecosystem on the Gulf of Lions shelf (NW Mediterranean) during spring and its impact on the carbon deposition: A field data and 3-D modelling combined approach[END_REF]. At the other river mouths, climatological values were prescribed according to [START_REF] Ludwig | Water and nutrient fluxes from major Mediterranean and Black Sea rivers: Past and future trends and their implications for the basin-scale budgets[END_REF]. The deposition of organic and inorganic matter from the atmosphere was neglected in this study. The benthic fluxes of inorganic nutrients were considered by coupling the pelagic model with a simplified version of the meta-model described by [START_REF] Soetaert | Numerical Reference Ribera d'Alcalà et al[END_REF]. The parameters of this model were set according to the modeling study on the Gulf of Lions shelf performed by [START_REF] Pastor | Modeling biogeochemical processes in sediments from the Rhone River prodelta area (NW Mediterranean Sea)[END_REF].

Figure 2.

Eco3m-S biogeochemical model scheme.

Area of study

The analysis of the nitrogen and phosphorus seasonal cycles, and annual budgets, was performed for the deep convection area of the NW Med, defined here using a mixed layer criterion. This region (indicated in blue on Fig. 1A), named Deep Convection Area (DCA) hereafter, represents the area where the mixed layer depth (MLD), defined in section 2.4, exceeded 1000 m for at least one day during the study period. According to the model, it covered more than 61 700 km 2 in 2013.

For the analysis and budget estimates, we divided the water column into two layers: an upper layer corresponding to the layer where primary production takes place, and a deep layer corresponding to the reservoir of inorganic nutrients. We chose to delimit these two layers with a nutricline criterion. The depth of the nutricline varies over time. As a variable depth would not allow a simple analysis of stock variations and annual budget of processes, we took a constant value corresponding to the maximum depth of the nutricline in the model domain, equal to 130 m, as our criterion. As the gradient of nutrient concentration is strong at the nutricline depth, the model estimate of nutrient stock in the upper layer is highly sensitivity to the depth criterion. For instance, an overestimation of the nutricline depth in the model would lead to an underestimation of the modeled nutrient stock. In this study, we focus then on the variation of the nutrient inventory rather than on the value of this inventory. Moreover, we consider the temporal variation of nutricline depth when analyzing that of upper layer nutrient stock.

Besides, previous studies [Martin and Pondaven, 2006;Kortzinger et al., 2008] demonstrated that material exported below the productive layer could be resuspended within this zone during mixing periods. Then the maximum yearly mixed layer depth was recommended as a threshold to calculate the export flux or new primary production [Martin and Pondaven, 2006;Palevsky et al., 2016]. The computation of the modeled export of organic and inorganic matter as the sum of sedimentation (for particulate matter) and net flux induced by turbulent mixing and vertical advection in the present study avoids counting the export of organic and inorganic matter that is then reinjected into the upper layer during mixing periods. However, we are aware that if new primary production is considered as the algal growth fueled by nitrate coming in the upper layer for the first time of the studied year, then it could be overestimated due to the recycling of exported organic material in the deep layer whose products would be upwelled back in the upper layer during the mixing period. The estimate of nitrification in the upper layer will be used to estimate this overestimation.

Derived variables

Variables used for the analysis of the annual cycles and budgets were derived from the coupled model. The modeled MLD is defined as the depth where the potential density exceeds its value at 10 m below the surface by 0.01 kg m -3 . We calculated the depths of the 1 mmolN m -3 and 0.05 mmolP m -3 iso-concentrations of nitrate and phosphate, as a proxy of the depths of the nitracline and phosphacline, respectively, according to [START_REF] Lavigne | Impact of mixed layer depth seasonal variations on the phytoplankton phenology in the Mediterranean Sea[END_REF] and Lazzari et al. [2012] studies. Both depths are significantly correlated in time in this region (R=0.84, p<0.01) and the maximum difference between the depths of the nutriclines is 10 m. For this reason, the nutricline refers to both the nitracline and the phosphacline hereafter. The stock of nutrients in the surface layer [0-130 m] was calculated in the simulation. Moreover, we computed a second estimate of the nutrient stock in the Deep Convection Area using the observations from the three cruises described in section 2.1. The nutrient concentrations measured during the cruises were interpolated over the model grid and then integrated in the 0-130 m layer as in the model. The interpolation method considers the notion of distance in space but also the deviation from selected physical fields (temperature, salinity). In practice, the nitrate and phosphate fields are interpolated from the cruise data (74 vertical nutrient profiles for MOOSE, 104 nutrient profiles for DEWEX cruises). It is therefore possible to estimate the deviation of temperature and salinity between all points of the numerical grid and the points corresponding to the position of the nutrient profiles to be interpolated. Since the bathymetry of a region such as the Mediterranean has a great influence on the organization of the circulation, the bathymetry deviation was also considered in a similar way. Finally, the concentration of the nutrients 𝐶 at grid point (x, y, z) was obtained in the following way:

𝐶(𝑥, 𝑦, 𝑧) = ∑ 𝑊 𝑞 𝐶(𝑞,𝑧) 𝑞 ∑ 𝑊 𝑞 𝑞 ( 3
)
where q is the nutrient profile number, C(q,z) the concentration of nutrients at the point corresponding to the position of the nutrient profile q and depth z, and W q the weight depending on the tracers and bathymetry deviations according to:

𝑤 𝑞 = 𝑒 -( 𝑆 𝑥,𝑦,𝑧 -𝑆 𝑞,𝑧 𝛿𝑆 0 ) 2 × 𝑒 -( 𝑇 𝑥,𝑦,𝑧 -𝑇 𝑞,𝑧 𝛿𝑇 0 ) 2 × 𝑒 -( 𝐻 𝑥,𝑦 -𝐻 𝑞 𝛿𝐻 0 ) 2 × 𝑒 -( 𝐷 𝑞 𝐷 0 ) 2 (4)
where S is the salinity, and δS 0 is an empirically determined scale of salinity variation (the terms related to temperature (T) and bathymetry (H) are obtained in a similar manner), Dq is the horizontal distance between the considered grid point and the nutrient profile q, D0 is an empirically determined scale of distance.

Finally, we deduced a value of the N:P ratio from the ratio of nitrate to phosphate stocks in the upper layer, 𝐼𝑁𝑂 3 𝑎𝑛𝑑 𝐼𝑃𝑂 4 (in mmol m -2 ), respectively. The contribution of biogeochemical or physical processes to the change of N:P ratio, was computed with Eq. 5: ) 𝑏𝑖𝑜 are the upper layer integrated biogeochemical processes (see Eq. 1 and Eq. 2).

𝜕(𝑁: 𝑃) 𝜕𝑡 = 𝐼𝑃𝑂 4 𝜕𝐼𝑁𝑂 3 𝜕𝑡 -𝐼𝑁𝑂 3 𝜕𝐼𝑃𝑂 4 𝜕𝑡 (𝐼𝑃𝑂 4 ) 2

Statistical analysis of the model results

A point-to-point approach was used to quantify the performance of the model in its ability to represent the dynamics of inorganic nutrients and chlorophyll over the study period. The model results were compared with the observations at the same dates and positions. Following the recommendations of Allen et al. [2007] we calculated four metrics: the standard deviation ratio

(𝑟 𝜎 = 𝜎 𝑚 𝜎 𝑜
where 𝜎 𝑚 and 𝜎 𝑜 are the standard deviation of model outputs and observations, respectively); the Pearson correlation coefficient (𝑅

= 1 𝑘 ∑ (𝑚 𝑛 -𝑚 ̅ )-(𝑜 𝑛 -𝑜 ̅) 𝑁 𝑛=1 𝜎 𝑚 × 𝜎 𝑂
), where K is the number of observations, 𝑚 𝑛 is the model output that corresponds to the observation n, 𝑜 𝑛 , 𝑚 ̅ and 𝑜̅ are the mean of model outputs and observations respectively); the Nash-Sutcliffe

efficiency (𝑁𝑆 = 1 - 1 𝑁 ∑ (𝑜 𝑛 -𝑚 𝑛 ) 2 𝑁 𝑛=1 ∑ (𝑜 𝑛 -𝑜 ̅) 2 𝑁 𝑛=1
) and the percentage bias (𝑃𝐵 = [2007] the performance of the model can be considered as excellent if the percentage bias is < 10%.

Comparison of model results with observations

An evaluation of the hydrodynamic simulation is described in Estournel et al. [2016b] where modeled temperature and salinity were compared with different available sets of observations..

The present study focuses on evaluating the model's ability to reproduce the spatial and temporal variability of inorganic nutrients.

Comparison with winter, spring and summer cruise observations

To evaluate the model's performance to reproduce the horizontal and vertical biogeochemical patterns in relation with the hydrology, the simulation was compared to the observations from cruises that took place during three key periods for the ecosystem (winter, spring and summer). For winter and spring periods, first, we compared the surface concentrations of nutrients. Then the model/observations comparison was made over the water column along a transect across the deep convection area, from the Balearic Islands to the Gulf of Lions shelf (measurement locations are indicated by the red dots on Fig. 1B for winter and 1C for spring).

For both comparisons, the modeled concentrations of nutrients were averaged over the period of sampling: 21 and 20 days for the surface observations, and 2 and 3 days for the transect observations, for the winter and spring cruises, respectively.

Winter

In winter, during the winter cruise, modeled and observed surface concentrations of nitrate and phosphate (Fig. 3A and3B) show some heterogeneity. The model indicates that the patch of high surface nutrient concentrations (> 7.5 mmol m -3 for nitrate and > 0.3 mmol m -3 for phosphate)

was located between 40.5°N and 43°N and between 3°E and 8°E. These characteristics and values match the observations, which show surface concentrations >7.64 mmol m -3 for nitrate and >0.35 mmol m -3 for phosphate [START_REF] Severin | Open-oceanconvection process: A driver of thewinter nutrient supply and the springphytoplankton distribution in theNorthwestern Mediterranean Sea[END_REF]. The highest values corresponded to the center of the Deep Convection region where intense convection brought nutrients to the surface layer [START_REF] Severin | Open-oceanconvection process: A driver of thewinter nutrient supply and the springphytoplankton distribution in theNorthwestern Mediterranean Sea[END_REF]. Outside the convective mixed patch, the surface nutrient concentrations were very low (<1 mmol m -3 for nitrate and <0.05 mmol m -3 for phosphate) as detected in the observations south of latitude 41°N. Between these two regions, a strong gradient was observed and modeled on a narrow band. Around the convective patch, in the Balearic Sea and in the Gulf of Lions, the observations show values close to 2.95 mmol m -3 for nitrate and 0.11 mmol m -3 for phosphate, while the model overestimates these values by 1 mmol m -3 for nitrate and by 0.4 mmol m -3 for phosphate. The strong gradient between the deep convection patch and the surrounding areas was a location of complex frontal dynamics. The greatest biases could originate from vertical motions at very fine scale on these fronts. Nevertheless, it is interesting to note the fine scale structures in the model, which could be explained by the enrichment of deep nutrients induced by the small-scale dynamics.

Figures 3C-E give complementary information on the vertical distribution of chlorophyll and nutrient concentrations in the model compared with the observations. Between latitudes 41.5°N and 42.5°N, the modeled and observed water column was homogeneous in biogeochemical variables. Both model and observations show that the surface chlorophyll a concentration was minimum in the deep convection area (lower than 0.10 mg m-3 in the model, lower than 0.16 mg m-3 in the observations). This feature was previously highlighted using satellite data and 3D

coupled modeling [START_REF] Auger | Interannual control of plankton communities by deep winter mixing and prey/predator interactions in the NW Mediterranean: Results from a 30-year 3D modeling study[END_REF][START_REF] Estournel | HyMeX-SOP2, the field campaign dedicated to dense water formation in the north-western Mediterranean[END_REF]Herrmann et al. 2017]) and was explained by a low phytoplankton growth and/or the vertical dilution of phytoplankton cells throughout the whole mixed layer that can reach the ocean bottom (~2500 m). The maximum vertical gradient of nutrients corresponded to the 29.05 kg m -3 isopycnal (superimposed on vertical sections; Fig. 3C-E) at the northern and southern limits of the Deep Convection Area.

The isopycnal depth varies between 200 m to the south and 400 m to the north. Beyond this threshold, modeled nitrate concentration increased from 6 to 8 mmol m -3 and phosphate concentration from 0.2 to 0.35 mmol m -3 .

Vertical homogeneity, at least over several hundred meters in the center of the Deep Convection Area, in temperature, salinity [Estournel et al., 2016b] and nutrient concentrations, was also observed during winter 2011 as reported by [START_REF] Severin | Impact of open-ocean convection on nutrients, phytoplankton biomass and activity[END_REF][START_REF] Mignot | Understanding the seasonal dynamics of phytoplankton biomass and the deep chlorophyll maximum in oligotrophic environments: A Bio-Argo float investigation[END_REF].

Other authors [Yilmaz and Tugrul, 1998;Gacic et al., 2002;Dilek et al., 2005;[START_REF] Santinelli | New insights into C, N and P stoichiometry in the Mediterranean Sea: The Adriatic Sea case[END_REF] have reported some homogeneous biogeochemical profiles and high surface inorganic matter enrichment by convective mixing in the eastern Mediterranean basin as mentioned before.

When and the percentage biases of -1.5% and -5.5%, respectively, an underestimation of nutrient concentrations, visible around the convective region on Figure 3. Regarding the modeled chlorophyll concentrations (mean value and standard deviation: 0.12 ± 0.16 mg m -3 ) compared to that observed on the cruise period (mean value and standard deviation: 0.18 ± 0.19 mg m -3 ), the Pearson coefficient correlation of 0.81 and the Nash-Sutcliffe efficiency of 0.56 show that the model reproduces very well the spatial phytoplankton distribution. However, the percentage bias shows that the model underestimates the observations by 32% in average.

Spring

In spring, nutrient and chlorophyll patterns (Fig. 4) changed drastically compared to February 2013. [START_REF] Severin | Open-oceanconvection process: A driver of thewinter nutrient supply and the springphytoplankton distribution in theNorthwestern Mediterranean Sea[END_REF] attributed these changes to a strong phytoplankton development, that was considered as a bloom by Mayot et al. [2017]. In this study, the onset of the bloom was considered as the day when the net accumulation rate of the carbon biomass integrated through the water column [START_REF] Behrenfeld | 91: 977-989. its relationship with chlorophyll-a in the upper layer of the NE Mediterranean Sea[END_REF] exceeded 50% of its maximum yearly value. Surface nutrient concentrations were low (Fig. 4A and4B) but remained higher in the Deep Convection Area than outside. In the observations, as in the model, surface values of 2 to 3 mmol m -3 of nitrate and 0.08 to 0.12 mmol m -3 of phosphate were observed in the center of the basin, while oligotrophic conditions were becoming established outside the Deep Convection Area, with surface nutrient concentrations down to 0 mmol m -3 in some areas away from the convection zone. In general, the model appears to underestimate the surface nutrient concentrations.

Variability between April and September 2013

The objective of this section is to evaluate the ability of the model to reproduce the variability of the biogeochemistry during a transitional phase. The Bio-Argo float Lovbio17B deployed in the NW Med in April 2013 during the bloom presents a time-series of the nitrate concentration that describes the transition in the surface layer from the bloom to the oligotrophic phase.

Results and Discussion

The comparison exercise reveals that the coupled model is able to reproduce the general seasonal dynamics of inorganic nutrients and phytoplankton growth deduced from the cruise observations.

The spatial extension of the convection area, where deep inorganic nutrients were upwelled and phytoplankton were diluted over the whole water column, appears to be in good agreement with cruise observations. The model reproduces the strong inorganic nutrient decrease between winter and spring cruises. Finally, the modeled depletion of nutrients of the upper layer in summer agrees with MOOSE and Lovbio17B observations. However, the model appears to generally underestimates the observed surface nutrient concentrations in spring and to anticipate the deepening of the nutricline observed by the Bio-Argo float.

Aware of the weaknesses and the strengths of the present coupled simulation, in the following sections, we use the model outputs to disentangle the impact of the physical and biogeochemical processes on the seasonal variations of the nutrient stock and stoichiometry in the upper layer of the Deep Convection Area, from September 2012 to September 2013. Finally, the model is also used to estimate a budget of nitrogen and phosphorus in the upper and deeper layers over the one-year study period. October 2012, positive heat fluxes were regularly interrupted by short, strong heat loss events corresponding to wind gusts from the north. In late October, an extreme heat loss event (-1300 W m -2 ) severely weakened the stratification of the upper layer and the spatially-averaged MLD deepened by 20 m (Fig. 8). In late November/early December, a strong wind episode lasted three weeks. Then a succession of heat loss events followed from mid-January to the end of February.

4.1.Annual cycle of nutrients

Atmospheric forcing and ocean vertical mixing

From December, each event produced a pronounced increase of the MLD. At the beginning of February, the ML reached the seafloor in the deep convection center (not shown), when the spatially averaged MLD reached 1500 m (maximum deepening not shown in Fig. 8). A final short, strong wind episode occurred between the second and the third weeks of March. This the period when the MLD was higher than 1000 m (deep convective mixing), gray is for spring and white is for summer.

Figure 10 presents the annual cycle of the biogeochemical sink and source terms of nitrate and phosphate as well as the trends induced by vertical hydrodynamics, for the period 2012-2013.

From early September to the end of October 2012, a shallowing of the nutricline from 80 to 60 m was modeled (standard deviation of 20 m). This upward displacement of the nutricline (Fig. 8) could be induced by the isopycnal doming during the preconditioning phase of the deep convection process in the NW Med [START_REF] Marshall | Open-ocean convection: Observations, theory, and models[END_REF] and/or by the variation of light intensity [START_REF] Mignot | Understanding the seasonal dynamics of phytoplankton biomass and the deep chlorophyll maximum in oligotrophic environments: A Bio-Argo float investigation[END_REF]. This led to a low but continuous increase of the nutrient stock in the upper layer (Fig. 9). At the same time, the uptake of nutrients decreased continuously (Fig. 10B). From October to November 2012, uptake of nitrate (respectively phosphate) became lower than nitrification (respectively excretion of phosphate). Therefore, the net effects of both physical and biogeochemical processes led to an increase of the nutrient stock in the upper layer (Fig. 9).

The sudden northern wind event occurring at the end of November -beginning of December (Fig. 7), thickening the ML to 50-60 m depth on average, close to the depth of the nutricline (Fig. 8), led to an abrupt import of nutrients into the surface layer (Fig. 10A), which were rapidly assimilated by phytoplankton (Fig. 10B). This was followed by a progressive increase of phosphate excretion (Fig. 10C), reflecting the triggering of the development of heterotrophs.

Regarding the surface nutrients stock, after the wind gust of early December, the balance of source (vertical import and nitrification/phosphate excretion) and sink (mainly uptake) terms explains the nearly constant stocks (Fig. 9).

The deep convection mixing, beginning in mid-January when the MLD exceeded 100 m (Fig. 8), led to a large upwelling of inorganic nutrients to the surface layer (Fig. 10A). The deep convection event also caused a sudden reduction of nitrate and phosphate uptake which, nevertheless, remained non-negligible (Fig 10B). The phytoplankton biomass was vertically mixed, and preys and predators were then decoupled as shown by [START_REF] Auger | Interannual control of plankton communities by deep winter mixing and prey/predator interactions in the NW Mediterranean: Results from a 30-year 3D modeling study[END_REF]. This resulted in an increase of the zooplankton mortality as shown by the intense drop of excretion rates during this period (Fig 10C). The decrease of ammonium and phosphate excretion rates was higher than the decrease of nitrate and phosphate uptake rates. It is noteworthy that the uptake of nitrate (mean value: 6.4 mmolN m -2 d -1 ) was higher than the uptake of ammonium (mean value:

1.9 mmolN m -2 d -1 ) during deep convection (Fig. 10B and10D). Also, nitrification rate in the upper layer (mean value: 1.2 mmolN m -2 d -1 ) was low during this intense mixing period (Fig. 10C). Thus, during deep convection, nitrate and phosphate stock in the surface layer increased in the model (Fig. 9) because of the nutrient convective supply and the reduced nutrient uptake.

They reached their maximum in early March (Fig. 9), when the main deep convection mixing stopped (Fig. 8).

An intense phytoplankton development began during the second week of March, favored by the weakening of vertical mixing (not shown). This bloom was characterized by a sudden, strong consumption of nutrients (Fig. 10B) that provoked a first sharp decrease of their surface stocks (Fig. 9).

From the end of March to mid-April, nitrate and phosphate uptake remained strong (Fig. 10B) (phytoplankton biomass reached its maximum in mid-April, not shown). In parallel, excretion increased rapidly (Fig. 10C and10D). In mid-April, the reduction of vertical mixing (Fig. 10A) led to a clear decrease of the vertical enrichment of the upper layer in nutrients. At this period, a strong decrease of nutrient uptake occurred. At the end of April, a new wind gust induced a brief deepening of the mixed layer (Fig. 8) that enriched the surface layer in nutrients. A last strong, short pulse of nutrient uptake (Fig. 10B) was then observed. Afterwards, the nitrate and phosphate stock continuously decreased (Fig. 9), and the nutricline and DCM depth increased (Fig. 8). It is important to note that, after this last strong wind event, ammonium uptake dominated the total nitrogen uptake (Fig. 10B and10D). Regarding the nutrient stock, it can be concluded that, during the spring period, the strong rate of uptake (higher than the excretion and nitrification rate) explains the strong decreasing trend (Fig. 9).

From June to August, the surface layer was depleted in nutrients (Fig. 8 and9). The model indicates an increase of the phosphate and ammonium excretion as well as of the nitrification rate (Fig. 10C and10D). The vertical physical flux was very weak (Fig. 10A) and the net biogeochemical flux resulted in a low, continuous decrease of the nitrate and phosphate surface layer stock until the beginning of August, when it reached the value of November 2012 (Fig. 8).

In August, as the DCM and nutricline depths, the nutrient stock stabilized.

The trend of the contribution of nitrate and ammonium uptake in the total nitrogen uptake, shown in late spring, remained throughout the summer as the trophic regime was dominated by regenerated production, ammonium being continuously produced (Fig. 10D), while nitrate was weakly imported from intermediate layers (Fig. 10A). During summer, nitrification increased slightly but continuously (from 3 to 4 mmol m -2 d -1 , Fig. 10C). It constituted from ~60 to 100% of nitrate uptake. The simulated nitrification rate presents the same order of magnitude as the measurements of Bianchi et al. [1999] who reported a rate of 1.4 mmol m -2 d -1 within the DCM in the NW deep sea. In the model results, we found a value of 1.8 mmol m -2 d -1 (25% higher than in the observations of Bianchi et al. [1999]) by integrating nitrification only within the DCM in the Deep Convection Area.

N:P ratio in the upper layer

In marine ecology, the nitrate to phosphate ratio was determined to be universally 16:1 because of the phytoplankton requirements which control the marine biogeochemistry [START_REF] Redfield | The influence of organisms on the composition of sea-water. Contribution No 1113[END_REF]. Even if this averaged ratio has been reappraised several times [START_REF] Banse | Seasonality of coastal zone color scanner phytoplankton pigment in the offshore oceans[END_REF]Geider and La Roche, 2002], its dynamics can still be used to understand the nitrogen and the phosphorus reactivity [START_REF] Arrigo | Review Marine microorganisms and global nutrient cycles[END_REF]. Indeed, the N:P stoichiometry reflects relations between several processes: nutrients uptake by phytoplankton and small heterotrophs, rate of mineralization of organic matter, inorganic matter excretion by heterotrophs and finally the effects of physical processes (mixing and advection).

In the Mediterranean Sea, the ratio N:P is higher than the canonical value of 16:1. Alcalà et al., 2003]. The N:P ratio can be much higher above the thermocline [START_REF] Raimbault | Very high values of nitrate:phosphate ratio (>30) in the subsurface layers of the western Mediterranean Sea. Rapp[END_REF] because of the preference of phytoplankton for phosphate compared to nitrate. These ratios confirm that the Mediterranean waters are limited by phosphate, especially in the eastern basin.

In this section, we use our simulation to characterize the time evolution of the stoichiometry in the upper layer of the Deep Convection Area, playing a key role in the water mass biogeochemical characteristics in the Mediterranean Sea, and to quantify the impact of the physical and biogeochemical processes responsible for their seasonal variations, over the period September 2012 to September 2013. The N:P ratio generally presents a negative gradient in the water column as observed in previous observational studies [START_REF] Pujo-Pay | Integrated survey of elemental stoichiometry (C, N, P) from the western to eastern Mediterranean Sea[END_REF][START_REF] Huertas | Atlantic forcing of the Mediterranean oligotrophy[END_REF][START_REF] Severin | Impact of open-ocean convection on nutrients, phytoplankton biomass and activity[END_REF]Pasqueron de Fommervault et al., 2015a]. The deep value (averaged between 130 m and the seafloor in the Deep Convection Area, not shown) is 22.4 on average (standard deviation: 0.5) in the model results (it is 21.7 on average, standard deviation: 0.6 according to the interpolation of Dewex cruise observations). The maximum N:P vertical gradient is located below the nutricline (not shown). The N:P ratio presents higher variability in the surface layer than in deep layers [Pasqueron de Fommervault et al., 2015].

Figure 11A shows the time series of the spatially averaged N:P ratio in the upper layer of the Deep Convection Area. N:P ratio deduced from the three cruise observations are also indicated by horizontal bars. Since the underestimation of phosphate stock is more pronounced than that of nitrate stock in the model during the winter cruise (Figure 9), the model overestimates the N:P ratio during this period. Besides, the overestimation of phosphate stock during MOOSE cruise period lead to an underestimation of N:P ratio during the summer period.

A first general remark about the effect of physical and biogeochemical processes on N:P is that uptake increases seawater N:P ratio while release of nitrate and phosphate decreases N:P (Fig. 11B). The N:P ratio of uptake is lower than the ratio in seawater, which presents an excess of nitrate compared to phosphate. The effect of uptake is then to increase the water N:P ratio. For the same reason, the release of nutrients by the ecosystem produces a decrease of water N:P. A second remark is that convective mixing events characterized by depths > 200 m produce a decrease of surface N:P ratio because of the general negative gradient of N:P. At the beginning of September 2012, the spatial mean N:P ratio was 24.1 (standard deviation: 0.5) according to the model (Fig. 11A). From September to December 2012, the influence of each physical process on the N:P ratio was lower than the effect of the biogeochemical processes (Fig. 11C and11D). Yet, both physical and biogeochemical processes had a negative impact on N:P (-0.7 for the net effect of the biogeochemical processes and -0.5 for the net effect of physical processes), explaining its slow and regular decrease.

From December 2012 to mid-January 2013, when nitrate and phosphate uptake rates were higher than the nitrification and phosphate excretion, respectively, the biogeochemical processes tended to strongly increase the N:P ratio (Fig. 11B and11D). In parallel, the horizontal dynamics tended to slightly decrease the N:P ratio. The resulting evolution was a rapid increase of the N:P ratio from 22.8 to 24.2 in the first 15 days of the autumnal bloom (1 December to 15 December), and a second slow increase from 24.2 to 25 during the following month (15 December to 15 January).

During the main convective period (16 January to 7 March 2013), the contributions of individual biogeochemical processes to N:P variations were low (Fig 11B). Besides, the strong deepening of the mixed layer in mid-January induced a rapid decrease of surface N:P, due to vertical imports of lower N:P deep waters (Fig. 11C). During the rest of the convective period, the N:P ratio reached a relatively stationary phase: the positive trend of the nutrient uptake that dominated the biology was balanced by the negative trend of the vertical mixing. During this period, the model N:P ratio was around 23, which is close to the mean value of 22.5 (standard deviation: 0.6) deduced from the observations of the February cruise. This difference between the two ratios could be explained by an underestimation of the N:P ratio of the deep waters at the model initialization.

Then, the sudden and strong consumption of nutrients at the onset of the winter/spring bloom induced a pronounced increase of the N:P ratio to 26 (Fig. 11A and11B). This increase was interrupted during the secondary convective mixing of the third week of March, inducing a small decrease of the N:P ratio of 0.3 (Fig. 11C).

The period with the highest N:P ratio corresponds to the transition between winter and spring (late March -early April) when the phytoplankton growth and nutrient uptake were strong (Fig. 10B and11A). In early April, phosphate excretion increased proportionally more rapidly than the production of nitrate by nitrification (Fig. 10C). This induced a decrease of the N:P ratio (Fig. 11B and 11D), intensified by the effect of vertical physical processes.

From mid-April, the contribution of physical processes to the variations of N:P was very low, N:P being mostly affected by the balance between excretion and uptake processes. The time lag between excretion of phosphate, nitrification and uptakes of nitrate and phosphate, as well as the difference in the rate of these processes, produced a biogeochemical contribution that was alternately positive and negative, with a decreasing trend until the end of spring.

From early June to early August, the effect of vertical motions balanced the effect of horizontal motions, and, likewise, the effect of uptake processes balanced the effect of production processes. Overall, the variations of N:P were negligible. For the period of the MOOSE summer cruise, the modeled N:P (24.2) is close to the ratio deduced from observations (25.1).

Our results shows that the N:P ratio was submitted to strong changes in the upper layer at the beginning of phytoplankton blooms. Those rapid modeled increases of N:P ratio, reflecting a phosphorus limitation for phytoplankton growth, are in agreement with the increase measured by Séverin et al. [2014] in March 2011 after restratification. This is also coherent with the results of [START_REF] Lazzari | Spatial variability of phosphate and nitrate in the Mediterranean Sea: A modeling approach[END_REF], based on 3D modelling on the whole Mediterranean sea, indicating a limitation of primary production by phosphate in our study area. Two other rapid changes (decrease) were also modeled during the studied period. The first modeled decrease of N:P ratio in the upper layer occurring at the beginning ot the deep convection event is coherent with the negative vertical gradient observed in the study region. The second modeled decrease occurred when uptake of nitrate by phytoplankton started to decrease after the peak of the spring bloom.

This should be addressed and confirmed with further observations.

Annual budgets of nitrogen and phosphorus

The annual nitrogen and phosphorus budgets of the deep convection area were calculated with the model in the upper layer (0-130 m) and in the deep layer (130 m -seafloor) (Fig. 12). The total stocks of nitrogen and phosphorus in this area exhibit a variation of -0.37% for nitrogen and -1.37% for phosphorus between September 2012 and September 2013.

The annual net vertical import of nitrate and phosphate is estimated at 1029 mmolN m -2 y -1 and 59 mmolP m -2 y -1 respectively. The nutrient vertical supply occurring over the convection period (17 January -17 March) corresponds to 68% of the annual vertical supply. According to the comparison exercise (section 3), it may have been underestimated. The simulated vertical nutrients import is of the same order of magnitude as previous estimates for the NW Med [Pujo-Pay and Conan, 2003;[START_REF] Severin | Impact of open-ocean convection on nutrients, phytoplankton biomass and activity[END_REF] (Table 1). It is also of the same order of magnitude as the estimation of 1400 mmolN m -2 y -1 in the convective Atlantic subpolar region [Williams et al., 2000]. The annual lateral exports of nitrate and phosphate from the surface layer of the convection zone, to the surrounding areas, are low and are estimated at 5 mmolN m -2 y -1 and 2 mmolP m -2 y -1 respectively.

Regarding the biogeochemical processes budget in the surface layer, the consumption of nitrate and ammonium makes up 39% and 61%, respectively, of the total nitrogen uptake. The annual production of nitrate by nitrification is 103% of the annual nitrate supply from deep waters and 50% of the nitrate uptake. Therefore, the new production as defined by [START_REF] Dugdale | Uptake of new and regenerated forms of nitrogen in primary productivity[END_REF] (primary production fueled by non-regenerated nutrients) could be overestimated by 100% if nitrification rates are taken into account in the calculation. Our results are coherent with those of [START_REF] Raimbault | Carbon and nitrogen uptake and export in the equatorial Pacific at 150°W: evidence of an efficient regenerated production cycle[END_REF], who showed a 20% to 100% overestimation of new primary production in the Pacific Ocean when nitrification was not taken into account in the calculation.

They agree also with those of [START_REF] Dore | Nitrification in the euphotic zone as a source for nitrite, nitrate, and nitrous oxide at Station ALOHA[END_REF], who established that 47 to 142% of the nitrate assimilated by primary producers was produced by nitrification at the ALOHA oligotrophic station, and those of Martin and Pondaven [2006] who found that uptake of regenerated nitrate through nitrification constituted 22 to 57% of the total nitrate uptake. Our results are also close to the results of [START_REF] Gentilhomme | Quantification des flux d'absorption et de regénération de l'azote minéral (nitrate, nitrite, ammonium) et organique (urée) dans la couche euphotique des océans oligotrophes[END_REF] who found that nitrification represented 23% of total nitrogen uptake (18% in this study) in the Algerian basin. From a quantitative point of view, using the Redfield ratio to facilitate comparison with previous studies, we have obtained a new production ranging between 77 and 162 gC m -2 y -1 , depending on whether nitrification is considered in the calculation. As mentioned in section 2.3 the choice of a constant depth corresponding to the base of the productive layer could lead to an overestimation of the new production. Indeed, as demonstrated by previous studies [Martin and Pondaven, 2006;Kortzinger et al., 2008;Palevsky et al., 2016], nitrate originating from the recycling of organic matter exported downward during deep mixing periods could have been reinjected in the upper layer. We estimate nitrification in the deep layer during deep convection period at 158 mmol m -2 (28% of the annual deep nitrification). If the whole nitrate produced by nitrification in the deep layer during convection period is reinjected in the upper layer and used by phytoplankton for its growth, then our estimate of new production is overestimated by 13 gC m -2 y -1 (using a Redfield ratio). The lower values of our estimate of new production (65-77 gC m -2 y - 1 ) are in the range of a previous estimate for the offshore NW Med (Table 1), a region that exhibits the highest values in the open Mediterranean Sea [Béthoux, 1989].

The net amount of organic matter produced in the surface layer is mostly exported towards the deep layer. The amount of produced organic matter advected horizontally toward the adjacent surface regions represents a small percentage of the net amount produced: 11% of the total organic nitrogen and 9% of the total organic phosphorus. The vertical export to the deep layer of dissolved and particulate organic nitrogen and phosphorus is estimated at 724 mmolN m -2 y -1 and 52 mmolP m -2 y -1 respectively. These estimates are in the same order of magnitude as the estimates in Pujo- [START_REF] Pujo-Pay | Seasonal variability and export of dissolved organic nitrogen in the northwestern Mediterranean Sea[END_REF] (Table 1). During the convection period (17 January to 17 March), the export represents 55% of the annual amount of organic nitrogen and 58% of the annual amount of organic phosphorus. Two thirds of the total exported organic matter is remineralized by heterotrophs and one third is advected to the surrounding deep regions. With respect to the deep-water biogeochemical nitrogen cycle, the ammonium produced by remineralization is mostly transformed into nitrate by nitrification. The difference in the nitrification:uptake of ammonium ratio (<1 in the upper layer and >1 in the deep layer) in upper and deep layer is explained by both higher ammonium uptake rates in the upper layer and lower nitrification rates due to an inhibition effect by light in the upper layer. An annual import of nitrate (260 mmolN m -2 y -1 ) and phosphate (6 mmolP m -2 y -1 ) is obtained by horizontal advection in the deep layer. It is worth noting that this net horizontal supply results from two strong opposite fluxes: an import of 936 mmolN m -2 y -1 for nitrate and of 39 mmolP m -2 y -1 for phosphate in the intermediate waters (between 130 m and 800 m) and an export of 676 mmolN m -2 y -1 for nitrate and of 33 mmolP m -2 y -1 for phosphate in the deep waters (below 800 m).

The model results suggest that, at the annual scale, the Deep Convection Area appears as an autotrophic system (uptake rates dominate excretion rates) where deep inorganic nutrients injected in the surface layer are almost entirely consumed by phytoplankton. Our estimates for the period 2012-2013 suggest that, at the scale of the Mediterranean Sea, the total vertical supply by physical processes in the NW deep convection region could constitute a major source of nutrients in the surface layer compared to the terrestrial and atmospheric inputs [Ribera d'Alcala et al., 2003;[START_REF] Krom | Nutrient budget for the Eastern Mediterranean: Implications for phosphorus limitation[END_REF] (Table 2).

Atmospheric deposition and nitrogen fixation were not taken into account in the simulation.

Results of previous studies suggested that they would have little influence on the annual N and P budget in the NW Med deep convection region, where there is a large vertical supply of nutrients. Aphotic nitrogen fixation was shown to contribute 0.5% of the total nitrogen inputs in the whole Mediterranean basin [Benavides et al., 2016]. Regarding the atmospheric deposition, Lazzari et al. [2012], using coupled modeling, showed that atmospheric and terrestrial inputs led to a 5% increase in the net primary production. The experiments performed by [START_REF] Ridame | Saharan input of phosphate to the oligotrophic water of the open western Mediterranean Sea[END_REF] showed that, in the western Mediterranean, the inputs of Saharan dissolved inorganic phosphorus had a negligible impact on the new production integrated over the productive layer, at the scale of the oligotrophic period, when the contribution of atmospheric deposition to the total nutrient input to the euphotic layer is largest.

The budget of the present study was obtained using a given coupled model and for a one-year period. Multi-year simulations would allow the variability of these terms in response to the interannual variability of atmospheric and ocean conditions to be evaluated. Moreover, uncertainties on the various terms of this budget could be estimated from additional experiments based on other coupled models.

Process

Conclusion and perspectives

A coupled physical-biogeochemical model was compared to a high-resolution dataset of three seasons of the same year ( 2013) and Bio-Argo float data, which document a strong convective winter, a phytoplankton bloom and an oligotrophic period in the NW Med. Despite some limits highlighted through the comparisons with observations, the model was shown to be able to reproduce the general observed seasonal dynamics of the physical and biogeochemical events correctly.

Our study shows that injections of nutrients during the wind intensification period triggered the autumn bloom. Then, convection in winter upwelled large amounts of nutrients into the upper layer. Decoupling of phytoplankton and zooplankton due to dilution as suggested by the collapse of heterotrophs when the mixed layer deepened strongly (mid-January), reduced the grazing pressure. When the conditions for phytoplankton development were all present (reduction of vertical mixing, low grazing pressure), a bloom was triggered with a massive consumption of nutrients during more than one month, resulting in a depletion of nutrients at the surface by the end of April. Nutrient consumption continued to deplete nutrients at increasing depths, inducing a deepening of the nutricline and DCM. This finally led to the summer oligotrophy of the water column.

The N:P ratio changed mainly through physical or biogeochemical processes during transition periods. Firstly, during the intense convection mixing, the large enrichment of surface waters in deep nutrients suddenly reduced the surface N:P ratio. Secondly, during the beginning of the Confidential manuscript submitted to Journal of Geophysical Research Oceans 50 bloom, the predominance of high nutrient uptake over low excretion induced a strong increase of the N:P. Thirdly, during the peak of the bloom when the nutrient stock decreased strongly, uptake decreased, and excretion was maximum. Nitrification created a decoupling in the recycling of nutrients, decreasing the ratio N:P. At the annual scale, the surface N:P ratio did not appear to be impacted by the intense vertical mixing and spring bloom induced by the deep convection.

At the annual scale and for the studied year, the dense water formation area was a sink of nitrate and phosphate in intermediate layers, and a source of organic nitrogen and phosphorus throughout the water column, for the surrounding regions (Fig. 13). The upward nutrient fluxes into the surficial NW Med deep convection area is estimated to be in the same order of magnitude as the atmospheric and terrestrial inputs of each of the western and eastern sub-basins of the Mediterranean Sea.

Further multi-year simulations from the coupled model will be used to better understand and quantify the impact of atmospheric and ocean interannual variability of the pelagic ecosystem and associated carbon, nitrogen and phosphorus cycles in this region. Previous studies suggested that deep convection could be strongly weakened [Somot et al., 2006;Adloff et al., 2015] or strengthened [Adloff et al., 2015] by the end of XXI century. We will then use the coupled model to explore and quantify how climate change and anthropogenic forcing may alter the NW Med deep convection biogeochemical cycles, in particular the nutrient vertical supply in the euphotic layer and the new production, in the near future. -Mayot, N., D'Ortenzio, F., Ribera d'Alcalà, M., Lavigne, H., and H. Claustre (2016), The Mediterranean trophic regimes from ocean color satellites: a reappraisal. Biogeoscience, 13, 1901-1917, doi:10.5194/bg-13-1901-2016-Mayot, N., D'Ortenzio, F., Taillandier, V., Prieur, L., Pasqueron de Fommervault, O., Claustre, H., Bosse, A., Testor, P and Conan, P. (2017) Physical and biogeochemical controls of the phytoplankton blooms in North Western Mediterranean Sea: a multiplatform approach over a complete annual cycle (2012-2013 DEWEX experiment), J. Geophys. Res.

-MEDOC Group (1970), Observation of formation of deep water in the Mediterranean Sea,

Figure 1 .

 1 Figure 1. A/ Bathymetry (m) of the coupled physical-biogeochemical model domain. The red dots represent the modeled river locations. The blue area DCA (Deep Convection Area) corresponds to the simulation analysis area. The yellow star corresponds to the LION station where the heat flux plotted on Fig. 6 was modeled. Maps B, C and D represent the biogeochemical measurement stations of the DeWEX Leg 1 (February 2013), DeWEX Leg 2 (April 2013) and MOOSE-GE 2013 (July 2013) cruises respectively. Stations in red on Fig. B and C are located on the transect presented in Fig. 3 and Fig. 4.

  m -2 d -1 ) are the rates of change of upper layer nitrate and phosphate stocks, respectively: where 𝑉𝑒𝑟𝑡𝑁𝑂 3 and 𝑉𝑒𝑟𝑡𝑃𝑂 4 are the net upward fluxes of nitrate and phosphate, respectively, at 130 m depth, due to vertical advection and turbulent mixing, 𝐻𝑜𝑟𝐴𝑑𝑣𝑁𝑂 3 and 𝐻𝑜𝑟𝐴𝑑𝑣𝑃𝑂 4 are the net horizontally advected inputs of nitrate and phosphate, respectively, in the upper layer from surrounding regions,

  complementary metrics enabled different aspects of the model results to be assessed. The standard deviation ratio assessed the variability in the model results compared to that in observations, a value of 𝑟 𝜎 > 1 indicating that the variability was stronger in the model outputs than in observations. The correlation coefficient assessed the similarity between model and observations and significative correlations (p<0.01) were obtained for all R calculations presented in section 3. The Nash-Sutcliffe efficiency assessed the difference between model and observations compared to the variability in the observations. According to Allen et al. [2007] a value > 0.65 indicates excellent performance, [0.65,0.5] is very good, [0.5,0.2] is good, and <0.2 indicates poor performance. Finally, the percentage bias indicated a general overestimation in the model results when it was positive and conversely. According to Allen et al.

Figure 3 .

 3 Figure 3. Comparison of modeled and observed surface (A) nitrate and (B) phosphate concentrations (mmol m -3 ) during the winter cruise. Vertical section of (C) chlorophyll (mg m -3 ), (D) nitrate (mmol m -3 ) and (E) phosphate (mmol m -3 ) concentrations across the Deep Convection Area, indicated by red dots on Fig. 1B. The model is represented by background colors and observations are indicated in colored circles (DeWEX Leg1, February 2013). White lines in the

Figures

  Figures4D and 4Egive an estimation of the nutricline depth, located at 60 m in average (standard deviation: 20 m) in the model, and following the density gradient. A surface chlorophyll development was observed and modeled (Figure4C) in conjunction with the nutrient depletion (Fig.4D and 4E), with a concentration exceeding 1.5 mg m -3 in the first 30 m, then 0.4 ± 0.2 mg.m -3 from 30 to 60 m and zero below 60 m. A homogeneous physical, biogeochemical profile was observed at the station 42°N 5°E in April 8. Although the model reproduces this

Figure 4 .

 4 Figure 4. Same as Figure 3 but for spring cruise (DeWEX Leg 2) in April 2013. Model outputs are averaged over the period 5-24 April for panel. A and B, and over the period 8-10 April for panels C, D, and E. The numbers of the measurement stations along the vertical section are indicated on the x-axis of panels C and D. Latitudes are indicated on the x-axis of panel E.

Figure 5 :

 5 Figure 5: Comparison of modeled (red) and observed (black) nitrate and phosphate concentration (mmol m -3 ) profiles during MOOSE cruise in July 2013.

Figure 6

 6 Figure6shows an evolution of nitrate concentration measured by the float and simulated by the model at the same points. The deepening of the nitracline occurs earlier in the model than in the observations. The nitrate concentration measured by the float in April is 1 mmol m -3 higher than in the model but measured and modeled concentrations are identical in May, with a nutricline

Figure 6 .

 6 Figure 6. Hovemöller diagram of the nitrate concentration (mmol m -3 ) along the float track from April to September 2013. Data are extracted from the float Lovbio17B (upper panel) and from the model (lower panel). White line represents the depth of the nitracline (position of the 1 mmol m -3 concentration) and the green dashed line represents the MLD.

Figure 7

 7 Figure 7 presents the time series of the modeled heat flux at the LION station (42°N, 5°E), located in the center of the Deep Convection Area, and Fig. 8 presents the time series of the modeled MLD averaged over the Deep Convection Area, from September 2012 to September 2013. Seasonal variability of the atmospheric forcing is clearly visible. In September and

  event caused a breakdown of the weak restratification established during the calm second week of March. Winter 2013 was thus characterized by a first and main convection event, from mid-January to early March, and a secondary convection event occurring during the third week of March. During the last week of March, the heat flux became durably positive in general. The frequency of the short, intense wind events decreased from three per month in April to one per month in summer. After March, the heat gain was a component of the progressive surface layer restratification, the development of instabilities around the mixed patch being the other component[Estournel et al, 2016b]. In spring, large variations (40 m) of the MLD (Fig.8) can be noted because of the wind effect on a weak stratified surface layer, as during the third week of April.

Figure 7 .

 7 Figure 7. Time series of modeled total heat flux (W m -2 ) at LION (indicated on Fig. 1A) from September 2012 to September 2013. Blue bars represent the period when the MLD was higher than 1000 m (convective mixing), while the green bar represents the restratification period coinciding with the phytoplankton development maximum.

Figure 8 .

 8 Figure 8. Time series of the depth (m) of the modeled mixed layer (in black), nitracline (in red), phosphacline (in blue) and deep chlorophyll maximum (in green) averaged over the deep convection region from September 2012 to September 2013. The background color stands for the season: yellow for autumn, blue for winter, with the dark blue representing the period when the MLD was higher than 1000 m (convective mixing), gray for spring and white for summer.

Figure 9 .

 9 Figure 9. Time evolution of modeled nitrate (upper panel) and phosphate (lower panel) stocks (in mmol m -2 ) in the upper layer [0-130 m] of the Deep Convection Area from September 2012 to September 2013. Stock estimates derived from observations are shown as horizontal bars overlaying the model outputs. The four seasons identified in section 4.1.2 are indicated with background colors: yellow represents autumn, blue is for winter -with the dark blue representing

Figure 10 .

 10 Figure 10. Time series of physical and biogeochemical fluxes that impact the stock of the inorganic nitrogen and phosphorus in the surface layer (0-130 m) from September 2012 to September 2013. These fluxes are inferred from the model and averaged over the open Deep Convection Area. (A) Net import due to vertical advection and turbulent mixing of nitrate (red) and of phosphate (blue) into the surface layer, (B) uptake of nitrate (red) and phosphate (blue), (C) nitrification (red) and inorganic phosphorus excretion rates (blue), (D) ammonia excretion (red) and uptake (blue). Units: mmol m -2 d -1 .

Figure 11 .

 11 Figure 11. (A) Time series of the modeled N:P ratio (molN molP -1 ) averaged in the upper layer [0-130 m] of the Deep Convection Area from September 2012 to September 2013. Estimates from observations are shown as horizontal bars overlaying the model output. (B) Biogeochemical and (C) physical processes (molN molP -1 d -1 ) influencing the N:P dynamics and (D) their net time integrated resultant.

Figure 12 .

 12 Figure 12. Modeled annual fluxes of nitrogen (top panel) and phosphorus (bottom panel) in the deep convection region (in mmol m -2 y -1 ) over the period from September 2012 to September 2013.

Figure 13 .

 13 Figure 13. Conceptual model of the main processes driving the organic and inorganic matter dynamics in the NW Mediterranean Sea over the period from September 2012 to September 2013.

Figure 1 .

 1 Figure 1. A/ Bathymetry (m) of the coupled physical-biogeochemical model domain. The red dots represent the modeled river locations. The blue area DCA (Deep Convection Area) corresponds to the simulation analysis area. The yellow star corresponds to the LION station where the heat flux plotted on Fig. 6 was modeled. Maps B, C and D represent the biogeochemical measurement stations of the DeWEX Leg 1 (February 2013), DeWEX Leg 2 (April 2013) and MOOSE-GE 2013 (July 2013) cruises respectively. Stations in red on Fig. B and C are located on the transect presented in Fig. 3 and Fig. 4

Figure 2 .

 2 Figure 2. Eco3m-S biogeochemical model scheme.

Figure 3 .Figure 4 .

 34 Figure 3. Comparison of modeled and observed surface (A) nitrate and (B) phosphate concentrations (mmol m -3 ) during the winter cruise. Vertical section of (C) chlorophyll (mg m -3 ), (D) nitrate (mmol m -3 ) and (E) phosphate (mmol m -3 ) concentrations across the Deep Convection Area, indicated by red dots on Fig. 1B. The model is represented by background colors and observations are indicated in colored circles (DeWEX Leg1, February 2013). White lines in the vertical sections (C to E) represent the 29.05 kg m -3 isopycnal potential density anomaly. The maps (A and B) correspond to an average modeled concentration over the period of the cruise (1 to 21 February) while the vertical cross section represents a model average over the transect observation period (12 to 13 February). The numbers of the measurement stations along the vertical section are indicated on the x-axis of panels. C and D. Latitudes are indicated on the xaxis of panel. E

Figure 5 :

 5 Figure 5: Comparison of modeled (red) and observed (black) nitrate and phosphate concentration (mmol m -3 ) profiles during MOOSE cruise in July 2013.

Figure 6 .

 6 Figure 6. Hovemöller diagram of the nitrate concentration (mmol m -3 ) along the float track from April to September 2013. Data are extracted from the float Lovbio17B (upper panel) and from the model (lower panel). White line represents the depth of the nitracline (position of the 1 mmol m -3 concentration) and the green dashed line represents the MLD.

Figure 7 .

 7 Figure 7. Time series of modeled total heat flux (W m -2 ) at LION (indicated on Fig. 1A) from September 2012 to September 2013. Blue bars represent the period when the MLD was higher than 1000 m (convective mixing), while the green bar represents the restratification period coinciding with the phytoplankton development maximum.

Figure 8 .

 8 Figure 8. Time series of the depth (m) of the modeled mixed layer (in black), nitracline (in red), phosphacline (in blue) and deep chlorophyll maximum (in green) averaged over the deep convection region from September 2012 to September 2013. The background color stands for the season: yellow for autumn, blue for winter, with the dark blue representing the period when the MLD was higher than 1000 m (convective mixing), gray for spring and white for summer.

Figure 9 .

 9 Figure 9. Time evolution of modeled nitrate (upper panel) and phosphate (lower panel) stocks (in mmol m -2 ) in the upper layer [0-130 m] of the Deep Convection Area from September 2012 to September 2013. Stock estimates derived from observations are shown as horizontal bars overlaying the model outputs. The four seasons identified in section 4.1.2 are indicated with background colors: yellow represents autumn, blue is for winter -with the dark blue representingthe period when the MLD was higher than 1000 m (deep convective mixing), gray is for spring and white is for summer.

Figure 10 .

 10 Figure 10. Time series of physical and biogeochemical fluxes that impact the stock of the inorganic nitrogen and phosphorus in the surface layer (0-130 m) from September 2012 to September 2013. These fluxes are inferred from the model and averaged over the open Deep Convection Area. (A) Net import due to vertical advection and turbulent mixing of nitrate (red)and of phosphate (blue) into the surface layer, (B) uptake of nitrate (red) and phosphate (blue), (C) nitrification (red) and inorganic phosphorus excretion rates (blue), (D) ammonia excretion (red) and uptake (blue). Units: mmol m -2 d -1 .

Figure 11 .

 11 Figure 11. (A) Time series of the modeled N:P ratio (molN molP -1 ) averaged in the upper layer [0-130 m] of the Deep Convection Area from September 2012 to September 2013. Estimates from observations are shown as horizontal bars overlaying the model output. (B) Biogeochemical and (C) physical processes (molN molP -1 d -1 ) influencing the N:P dynamics and (D) their net time integrated resultant.

Figure 12 .

 12 Figure 12. Modeled annual fluxes of nitrogen (top panel) and phosphorus (bottom panel) in the deep convection region (in mmol m -2 y -1 ) over the period from September 2012 to September

  Figure 1.

  Figure 2.

  Figure 3.

  Figure 4.

  Figure 5.

  Figure 6.

  Figure 7.

  Figure 8.

  Figure 9.

  Figure 13.

Table 1 .

 1 Compilation of nutrient flux estimates in the northwestern Mediterranean deep sea.

		Severin et al. [2014] Feb./March 2011	46/63
		This study	Sept. 2012-Sept.	65-77
			2013
	Export of	mmol m -2
	organic	y -1
	matter
		Pujo-Pay and	1993	274-814
		Conan [2003]
		This study	Sept. 2012-Sept.	724
			2013
	876

Table 2 .

 2 Estimates of the net inputs of nitrogen and phosphorus in the surface layer in the Mediterranean Sea (in 10 6 mol y -1 ).

Figures and tables captions

		Reference temperature	°C	14	14	14
		Natural mortality rate	d -1	0.09	0.03	0.05
		Maximum quantum yield	mmolC J -1	2.6 10 -4 2.87 10 -4	3.85 10 -4
				Zoo 1	Zoo 2	Zoo 3
		Reference temperature	°C	18	18	18
		Natural mortality rate	d -1	0.01	0.008 d -1	-
		Non-living matter remineralization rate
		Detritus remineralisation rate, C	d -1	0.17
		Detritus remineralisation rate, N	d -1	0.2
	Additional Supporting Information Detritus remineralisation rate, P	d -1	0.18
		Detritus remineralisation rate, Si	d -1	0.4
	Symbol	Description	Unit		Value
		Detritus remineralisation rate, Chl	d -1	Phy 1 0.02	Phy 2	Phy 3

Mar. Syst., 16,[3][4][253][254][255][256][257][258][259][260][261][262][263][264][265][266][267][268]

Acknowledgments

This study has been funded by the PERSEUS project (European Union FP7 Grant Agreement 287600). It is a contribution to the MerMex (Marine Ecosystem Response in the Mediterranean Experiment. http://dx.doi.org/10.17600/13020010, http://dx.doi.org/10.17600/13020030, http://dx.doi.org/10.17600/13450110), particularly DeWEX and MOOSE projects project of the MISTRALS international program. Numerical simulations were performed using the computing cluster of Laboratoire d'Aérologie and HPC resources from CALMIP (grants P1325 and P1331). The biogeochemical floats have been funded by the French NAOS project (« Investissement d'Avenir », ANR J11R107-F).

Sea, Global Biogeochem. Cycles, 30,[952][953][954][955][956][957][958][959][960][961] doi:10.1002/ 2015GB005326.

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