Dimethylsulfoniopropionate and dimethylsulfoxide in Posidonia oceanica

Dimethylsulfoniopropionate and dimethylsulfoxide in Posidonia oceanica | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dimethylsulfoniopropionate and dimethylsulfoxide in Posidonia oceanica Jonathan Richir, Willy Champenois, Jimmy de Fouw, Alberto V. Borges This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-309046/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract The present work aims at determining the natural variability of dimethylsulfoniopropionate (DMSP) and dimethylsulfoxide (DMSO) contents in the seagrass Posidonia oceanica , which is the largest producer of these molecules reported to data among coastal autotrophs. Samples were collected during a period of 3.5 years in the pristine Revellata Bay (Calvi, northwestern Corsica, France). The DMSP content ranged from 25 to 265 µmol.g fw −1 ; DMSO from 1.0 to 13.9 µmol.g fw −1 . The dynamics of the two molecules were closely linked, the DMSO content being equivalent to 3.5 % of the DMSP content, all leaf samples considered (n = 423 samples and 414 DMSP(O) data pairs). The annual growth cycle of the seagrass diluted the initial stocks of the two molecules. Temperature indirectly affected molecule content dynamics through their direct effect on the seagrass productivity and biomass. Inter-annual variations in DMSP(O) content in relation to shallow water temperature might further indicate that DMSP(O) could have been involved in the physiological response of P. oceanica to heat-stress. Finally, middle-aged leaf tissues with an organosulfur molecule content similar to the average value calculated for the seagrass leaf bundle appeared to be the best choice of sample material to study DMSP and DMSO in that species. More research is needed to elucidate the biosynthetic pathways of these molecules in seagrasses, the evolutionary reasons for such a high production in P. oceanica and the physiological functions they play. Marine and Freshwater Biology Posidonia oceanica seagrass organosulfured compounds dimethylsulfoniopropionate (DMSP) dimethylsulfoxide (DMSO) ecology physiology primary production Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Haas ( 1935 ) showed that the red macroalgae Polysiphonia fastigiata and P. nigrescens when exposed to air emitted dimethyl sulphide (DMS). It was unlikely that DMS was stored as such in the macroalgae, given the small size of the molecule and its high diffusivity. This suggested the occurrence of a precursor sulphonium compound, identified as DMSP by Challenger and Simpson (1948). The first report on the second biogenic precursor of DMS in marine algae, dimethylsulfoxide (DMSO) is more recent. Given the large, often dominant pool of DMSO in aquatic environments, it was hard to envisage its maintenance solely via a DMS precursor (Lee and de.Mora 1999 ). de Mora et al. ( 1996 ) speculated a direct biosynthetic pathway on the basis of evidence gathered in Antarctic melt-water ponds that contained relatively high levels of dissolved DMSO but low concentrations of DMS and very little dissolved DMSP. In the coastal waters of North Island, New Zealand, Lee and de Mora ( 1996 ) speculated that algal photosynthetic processes may have played a role in the rapid daytime production of dissolved DMSO that could not have only resulted from photo- and bacterial oxidation of DMS. Simó et al. ( 1998 ) confirmed the biogenic production of DMSO by marine microalgae in laboratory cultures of Amphidinium carterae and Emiliania huxleyi . Since these initial results reporting DMSP and DMSO associated with macroalgae and phytoplankton (Challenger and Simpson, 1948; Simó et al., 1998 ), a number of studies have addressed first their occurrence and production, then their biosynthesis in marine primary producers (Lee and de.Mora 1999 ; Lee et al. 1999 ; Stefels 2000 ; Hatton et al. 2004 ; Stefels et al. 2007 ). DMS, DMSP and DMSO are tightly interrelated compounds that constitute an integral part of the marine sulfur cycle and play an important role in the global sulfur budget (Stefels et al. 2007 ; Asher et al. 2017 ). The proposed cooling effect on climate through increased albedo of DMS derived cloud condensation nuclei (Lovelock and Maggs 1972 ; Charlson et al. 1987 ) has stimulated considerable research into this gas and its precursors during the last three decades. The recent discovery of a new metabolite, dimethylsulfoxonium propionate (DMSOP) synthesized by several DMSP-producing microalgae and marine bacteria, has extended the paradigm of the marine sulfur cycle (Thume et al. 2018 ). DMSP and DMSO are ubiquitous in the upper ocean (Lee et al. 1999 ; Simó and Vila-Costa 2006 ). Their biogenic production is however taxon-dependent and large producers are confined to a few classes of micro- and macroalgae (Stefels 2000 ; Simó and Vila-Costa 2006 ; Hatton and Wilson 2007 ). Unlike algae, for which an important scientific literature is available, observations of DMSP (and DMSO) in higher plants are rare (Stefels 2000 ). Vegetated sediments of salt marshes are major sources of DMS emission to the atmosphere (Steudler and Peterson 1984 ). It was obvious to investigate their biogenic precursors in the dominant grasses of these systems, i.e. plants of the genus Spartina . DMSP was first reported in Spartina anglica (Larher et al. 1977 ), later in S. alterniflora (Dacey et al. 1987 ) and in S. foliosa (Otte and Morris 1994 ). The first report of DMSO in salt marsh grasses is more recent. Its discovery in S. alterniflora by Husband and Kiene ( 2007 ) relied on the idea that if DMSO was present in some DMSP producing phytoplankton, this compound might also be found in DMSP producing higher plants. These authors reported DMSO content in ratio to DMSP of 1.6-4.0 %, values much lower than for phytoplankton (8–50 %; Simó and Vila-Costa 2006 ). Reports of DMSP and DMSO in seagrasses are even more rare than in cordgrasses. White ( 1982 ) when developing a method for the analysis of dimethyl sulfonium compounds in marine macrophytes, measured DMSP in Zostera sp. (most probably Z. marina , the dominant native Zostera species on the Pacific coast of North America [Green and Short 2003 ] and referred as such by Dacey et al. [ 1987 ]), although its production was likely affected by algal epiphytes (Bianchi 2007 ). In the mid-90s, Dacey et al. ( 1994 ) measured DMSP in the epiphytized leaves of three seagrasses: Halodule wrightii , Syringodium filiforme and Thalassia testudinum ; they attributed DMSP mostly to leaf epiphytes, since DMSP content in T. testudinum non-epiphytized leaves was 3–8 times lower. Very low DMSP contents were also reported in non-epiphytized leaves of Z. noltei (Jonkers et al. 2000 ), in roots of that species (Jonkers et al. 2000 ) and in rhizomes of T. testudinum (Dacey et al. 1994 ). In the oligotrophic coastal ecosystem of Niel Bay (NW Mediterranean, France), algal biomass and particulate DMSP were low; because phytoplankton alone could not fully explain the high dissolved DMSP levels measured there, Jean et al. ( 2006 , 2009 ) assumed benthic macrophytes including P. oceanica contributed to the dissolved DMSP pool. This assumption was recently, confirmed by Borges and Champenois ( 2015 ), who resurrected the interest in the production of DMSP by seagrasses by investigating its content in Posidonia oceanica ; they also showed the occurrence of DMSO in this plant (Borges and Champenois 2017 ). DMS was further reported to be the main volatile organic compound (59.3%) in P. oceanica (Jerković et al. 2018 ), de facto explained by the high values of DMSP and DMSO measured in its leaves (Borges and Champenois 2017 ; Richir et al. 2020 ). P. oceanica is a top producer of DMSP and DMSO among marine and intertidal autotrophs, with foliar contents reaching up to 265 µmol.g fw −1 for DMSP and 13 µmol.g fw −1 for DMSO (Richir et al., 2020 ). The production dynamics of the two molecules in P. oceanica are closely linked and depend more on the plant’s annual growth cycle than on environmental variables (light and temperature; Richir et al. 2020 ). DMSP and DMSO, more concentrated in young tissues, could play antioxidant and grazer deterrent functions (Richir et al. 2020 ). Their ratio, considering DMSO is the product of the oxidation of DMSP, could be a generic indicator of oxidative stress in the plant (Richir et al. 2020 ), as initially postulated and verified for S. alterniflora (Husband and Kiene 2007 ; Husband et al. 2012 ; McFarlin and Alber 2013 ). The present work aims at determining the natural variability of the DMSP and DMSO contents in P. oceanica leaves (i) at seasonal and interannual time scales, (ii) with depth, (iii) in relation to leaf tissues ageing and (iv), in the context of ocean warming, with water temperature. This complete and detailed, depth-gradient (10–30 m) study of almost 3.5 years (April 2015 - August 2018) on the ecophysiology of DMSP(O) in P. oceanica leaves was carried out in a non-disturbed meadow in Corsica, France, in the framework of the STARECAPMED program (Richir et al. 2015 ). In addition to P. oceanica , some preliminary, indicative data on DMSP(O) contents in Z. marina and Cymodocea nodosa leaves are also given. 2. Material And Methods 2.1. Study design To study the natural variability of DMSP and DMSO contents in P. oceanica leaves over time, we compiled and analysed a large data set of novel unpublished data (n = 293 samples and 285 DMSP(O) data pairs) and previously published data (n = 130 samples and 129 DMSP(O) data pairs) by Richir et al. ( 2020 ). The previous data set covered, on a weekly to fortnightly basis, the period from mid-April to mid-July 2016 (Richir et al., 2020 ) to which we added additional unpublished data collected in May, August and November 2016, February, August and November 2017, and February, May and August 2018 (see Sect. 2.4 for details). For these additional May 2016 to August 2018 data, sampling was systematically carried out along a 10–30 m depth gradient (unlike the study of Richir et al. [ 2020 ] that mainly focused on the depth of 10 m). The compiled data set (n = 423 samples and 414 DMSP(O) data pairs) allowed to explore the seasonal and interannual variations of the seagrass leaf DMSP(O) content in relation to those of temperature, that were marked during time period given strong heatwave in 2018 (Liu et al. 2020 ); it further allowed to test the hypothesis of the involvement of DMSP(O) in the physiological response of P. oceanica to heat stress. Also, Richir et al. ( 2020 ) only reported variations of the DMSP(O) content in the first 20 basal cm of P. oceanica third rank leaf. Here, we explored the variability of DMSP(O) contents in leaves of different rank, i.e. age classes, from their base towards their tip (10 cm long leaf section; Suppl. Mat. Figure 1 ). P. oceanica shoot structure is characterized by the distichous and alternating arrangement of its ribbon-like leaves, with the youngest ones at the center of the shoot, and the oldest ones on the outside (Buia et al. 2004 ; Augier 2007 ); foliar tissues are therefore older towards the outside of the leaf bundle and the tip of the leaf. In addition, the analysis of the leaf class and leaf section variability provided important information for the design of the best leaf tissue sampling protocol for assessing organosulfur dynamics in P. oceanica . 2.2. Study site The study was conducted in a dense and healthy P. oceanica meadow in the northwestern part of the Revellata Bay in the Gulf of Calvi (Corsica, France; Norie 1831 ), close to the STARESO research station (42.580°N, 8.725°E). The Gulf of Calvi has an area of about 22 km 2 , opens to the Ligurian Sea on the northeast with a border of about 6 km and connects to the deep sea by a canyon. The Gulf of Calvi is a ‘reference site’ in a good state of environmental conservation (Gobert et al. 2009 ; Lopez y Royo et al. 2010, 2011). The sea floor is dominated by a dense and healthy P. oceanica meadow down to about 38 m depth (Bay 1984 ; Champenois and Borges 2012 ; Richir et al. 2015 ). The study site of the present work is identical to that of Borges and Champenois (Borges and Champenois 2015 , 2017 ) and Richir et al. ( 2020 ). 2.3. Water temperature recording Water temperature was recorded continuously with probes and loggers deployed in the P. oceanica meadow facing the STARESO. Temperature data were accessed from the RACE database (Binard 2017 ). Temperature was recorded at 9.5 (considered 10) m depth with the incorporated temperature sensor of an Aanderaa oxygen optode (3835) mounted on Alec Instrument data-loggers (60 min interval; Xylem Inc.; Champenois and Borges 2012 ), and at 20 and 29 (considered 30) m depth with Hobo loggers (10 min interval; HOBO Pendant® Temperature/Light Data Logger, Onset Computer Corporation; Richir et al. 2020 ). The temperature sensors of the Aanderaa oxygen optode and the Hobo loggers were factory-calibrated. 2.4. Seagrass sample collection P. oceanica sampling was performed weekly to seasonally by scuba diving between April 2015 and August 2018. Three successive sampling designs were performed over that period: in years 2015–2016 (first), 2016–2017 (second) and 2017–2018 (third), as described below. P. oceanica sampling was performed in triplicate, on orthotropic shoots (i.e. vertical growth, as opposite to plagiotropic - horizontal - growth; Boudouresque et al. 2012 ) randomly selected on surfaces of a few m 2 . Sampling was performed by cutting the leaves just above the meristem area with a scissor to ensure their post-regrowth (Suppl. Mat. Figure 1 A; De los Santos et al. 2016; Gobert et al. 2020 ). Between April 2015 and July 2016, the first seagrass sampling design was performed at 10 m depth, at a weekly to fortnightly frequency; in July 2015, seagrasses were sampled along a depth gradient at 3, 10, 15, 20, 25, 29 (considered 30) and 36 m depth. Only the third leaf from the inside of the leaf bundle (i.e. rank 3; juvenile leaves - <5 cm long [Giraud 1979 ] - were excluded) was sampled. The first 20 basal cm of sampled leaves were dissected for analysis (see Richir et al. 2020 ). In May, August and November 2016 and in February 2017, the second seagrass sampling design was performed along the depth gradient at 10, 15, 20, 25 and 30 m depth. Only the third external leaf from the outside of the leaf bundle (usually rank 4) was sampled. The first 10 basal cm of sampled leaves were dissected for analysis. P. oceanica shoots have in average six leaves (Gobert et al. 2003 ; Richir et al. 2020 ); whether taken from outside (second sampling design) or inside (first sampling design) the bundle, the third leaf is therefore similar (rank 3 or 4; Suppl. Mat. Figure 1 A). In August and November 2017 and in February, May and August 2018, the third seagrass sampling design was performed along the depth gradient at 10, 15, 20, 25 and 30 m depth. Entire P. oceanica leaf bundles were sampled. Leaf bundles were clipped in situ with plastic tongs prior cutting to keep the insertion order of the leaves. The leaves were sorted and pooled into three classes: the two most external leaves on each side (called ‘external’), the following two leaves on each side (called ‘intermediary’), all of the following leaves (called ‘internal’). Pooled leaf classes were then cut into four sections of 10 cm (0–10, 10–20, 20–30 and 30–40 cm) for analysis (Suppl. Mat. Figures 1 B). The leaf grows from the base (acropetal growth; Boudouresque et al. 2012 ), so the younger section of the leaf corresponded to the first section (0–10 cm) according to our convention. Because most leaf tips of the August 2017 samples were necrotic (most of leaves, old and senescent, are ready to decay at the end of summer), only the 40 first cm of P. oceanica living leaf tissues were considered. Quickly after the end of the dive, seagrass leaf samples were dissected in STARESO facility, then prepared and stored according to the protocol of Borges and Champenois ( 2017 ). Briefly, leaf samples were cleaned of epiphytes (when present) with a razor blade (Dauby and Poulicek 1995 ) during dissection, and lower little-pigmented sections of sampled leaves systematically discarded. Dissected leaf tissues were stored in 20 ml borosilicate vials sealed with polytetrafluoroethylene coated silicone septa stopper or in plastic bags and frozen at -20°C until DMSP and DMSO analysis. Samples were brought back frozen to the University of Liège (Belgium) to avoid DMSP loss during transport. In addition to P. oceanica sampling and for comparison purpose between temperate seagrass species, Cymodocea nodosa (subtidal species) and Zostera marina (predominantly subtidal species) shoots were collected in August of years 2018 and 2019; in Alfax Bay, Spain, for C. nodosa , and in three sites in Brittany (Kernisi, Dinard, Port Laso), France, and in Kristineberg, Sweden for Z. marina (Table 1). Sampling depth was 30–150 cm, except for Dinard Z. marina sampling (emerged at low tide). Seagrass shoots were rinsed with water to get rid of the sediment, then brought back frozen to Radboud University (The Netherlands). In the laboratory, unfrozen seagrass shoots were dissected, and leaf bundles cleaned of epiphytes reconditioned frozen and sent to the University of Liège (Belgium) for DMSP and DMSO analysis. Complete seagrass leaf bundles were pooled into one to three sample replicates per site, of about 500 mg each (preliminary test analyses showed low organosulfur compound contents). Samples were processed for DMSP and DMSO content in a similar fashion as for P. oceanica leaves (see section below). 2.5. DMSP and DMSO analysis P. oceanica dissected leaves sampled for DMSP and DMSO analysis were unfrozen, gently dried of water droplets on absorptive paper and cut in 3 mm 2 square fragments. In average 31 mg of fresh leaf tissues (7–50 mg, according to tissue availability and expected organosulfur compound contents) were transferred to pre-weighted 20 ml glass vials for analysis (three analytical replicates by leaf sample except for years 2016–2017 second sampling design and for C. nodosa and Z. marina , no analytical replicate; Borges and Champenois 2017 ). DMSP and DMSO contents were measured after conversion into DMS using the headspace technique with a gas chromatograph (GC) with a flame photometric detector (FPD) (Agilent 7890A, Thermo Fisher Scientific Inc.). The temperature of the FPD was kept at 250°C with H 2 and synthetic air flows (respectively 50 and 60 ml.min − 1 ; Air Liquide Belgium). The column was a capillary column (CP-Sil 5CB, 30 m long, 0.32 mm internal diameter, 0.5 mm film thickness, CS - Chromatographie Service GmbH), the carrier gas ultrapure He (2 ml.min − 1 ; alphagas-2 grade, Air Liquide Belgium). The temperature of the oven and injection port was kept at 60°C. The headspace was sampled with syringes of 10–500 µL and injected through a split-splitless injection port to the head of the column. The methodology for seagrass leaf sample preparation and DMSP(O) analysis is fully detailed in Champenois and Borges ( 2019 ). In brief, the method consists of first digesting P. oceanica leaf fragments in 2.5 ml of NaOH (12 M; solution prepared from granular NaOH, VWR International, LLC) in the 20 ml closed vials. In the presence of NaOH, DMSP cleaves quantitatively into DMS and acrylate (Stefels 2009 ). The DMS in the vial headspace is measured by GC-FPD. The NaOH digestate is then bubbled with ambient air to evacuate the DMS and acidified with 2.5 ml of pure HCl (12 M; HCl 37 % Normapur, VWR International, LLC). The DMSO present in the digestate is reduced to DMS by adding 1 ml of TiCl 3 (TiCl 3 30 % m/v, Merck KGaA; Stefels 2009 ). The DMS in the vial headspace is again measured by GC-FPD. Median (min-max) headspace volumes sampled for direct injection were 10 µl (8-500 µl) for DMSP, and 100 µl (25–500 µl) for DMSO, respectively, all samples considered. The GC-FPD peaks of DMS were converted into DMSP and DMSO concentrations from a series of standards of known concentrations treated in the same way and at the same time as the samples. Digestate DMSP and DMSO concentrations were converted to leaf contents (µmol per g of leaf fresh weight, µmol.g fw −1 ). The ratio of DMSP on DMSO was computed from the measured DMSP and DMSO contents. The DMSP(O) set of individual data (averages of analytical replicates) - and temperature data - are hosted in the Mendeley Data repository ( http://dx.doi.org/10.17632/y65hzhbfsk.1 ). 2.6. Data processing and statistical analysis The spatiotemporal and compartmentalisation analysis of DMSP and DMSO consisted of linear mixed effects models (LMMs). LMMs extend traditional linear models to include a combination of fixed and random effects as predictor variables (Harrison et al. 2018 ). Fixed effects represent variables with intercepts, means or slopes to be estimated; random effects infer the variance associated with group membership (Silk et al. 2020 ). The model we used included depth, period and leaf class as fixed effects, and leaf section as random effect. LMM p -values were computed by using Satterhwaite approximation for denominator degrees of freedom (Satterthwaite 1946 ). Analysis of variance (one- and two-way ANOVAs) on mean DMSP, DMSO and DMSP:DMSO ratio data for the basal section of P. oceanica rank 3–4 leaves were used to study the effect of year (2015-2016-2017-2018) and season (autumn, winter, spring, summer), followed by Tukey’s post-hoc comparison test (Zar 2010 ). Linear modelling (LMMs and ANOVAs) was performed on log-transformed data. DMSP and DMSO contents of the maximum twelve leaf class-section combinations of the compartmentalisation study were averaged to calculate P. oceanica leaf bundle values. They were also averaged to calculate six new 0–20 and 20–40 cm leaf class-section combinations. The leaf-class sections of 10 or 20 cm long were proportionally compared to the seagrass DMSP and DMSO content averages to determine which one best represents the whole 0–40 cm leaf bundle. The linear relationship between DMSP and DMSO contents in P. oceanica leaf tissues of the three sampling designs (n = 414 data pairs, including the 129 data pairs from Richir et al. 2020 Fig. 5A) was analysed using bootstrapped median regression. Quantile (including median) regression presents several advantages for ecological data: it is robust to outliers; avoids parametric distribution assumptions; estimates rates of change in all parts of the response variable distribution and is invariant to monotonic transformations (Koenker and Bassett 1978 ; Cade and Noon 2003 ). The R 1 goodness of fit of the model was measured according to Koenker and Machado ( 1999 ). The 0.95 prediction interval was created using quantiles 0.025 and 0.975. The relationships among response variables DMSP, DMSO or DMSP:DMSO ratio and the potential explanatory variable temperature were analysed using median regression with restricted cubic spline function and best linear fit lines. Cubic spline is essentially a piecewise cubic polynomial. Cubic polynomials have good ability to fit sharply curving shapes. Cubic spline is made to be smooth at the join points, called knots. A restricted cubic spline has the additional property that the curve is linear before the first knot and after the last knot. The number of knots used in the spline is determined by the user, but in practice five or fewer knots are sufficient (Harrell 2015 ; Gauthier et al. 2019 ). In the present study, we used one knot as free parameter. Differences in temperature summer maxima were measured for years 2015 to 2018, with daily average values sometimes close to 28°C. Relationships were therefore analysed for July and August data. P. oceanica tissue considered for the analysis was the basal section analysed for each sampling design (0–20 cm for years 2015–2016, 0–10 cm for years 2016–2017 and years 2017–2018). In addition, July and August daily mean temperatures used in the models were values greater than or equal to their respective 75th percentiles. Data analysis and statistics were performed in RStudio version 1.1.383 (RStudio Team 2019), using R’s base function (R.Core Team 2020) and functions of packages ‘dplyr’ (Wickham et al. 2019 ), ‘tidyr’ (Wickham and Henry 2019 ), ‘lmerTest’ (Kuznetsova et al. 2017 ), ‘car’ (Fox and Weisberg 2019 ), ‘agricolae’ (de Mendiburu 2020 ), ‘ggplot2’ (Wickham 2016 ), ‘quantreg’ (Koenker 2019 ) and ‘rms’ (Harrell 2019 ). Linear model assumptions (including residual distribution, variance homoscedasticity and overdispersion) and model fits were checked with diagnostic plots and tests. Statistical results are given according to Wasserstein (2019). 3. Results According to the LMM analysis, DMSP and DMSO in P. oceanica varied over time (DMSP: F (4,202.20) = 58.32, p < 2.2 x 10 − 16 ; DMSO: F (4,201.53) = 51.29, p < 2.2 x 10 − 16 ) and among leaf classes, i.e. leaf age (DMSP: F (2,201.49) = 69.03, p < 2.2 x 10 − 16 ; DMSO: F (2,200.69) = 69.47, p < 2.2 x 10 − 16 ). Depth also had an effect on organosulfur compound contents (DMSP: F (4,201.26) = 4.85, p = 0.0010; DMSO: F (4,200.86) = 3.02, p = 0.0190), as did the interaction between period and depth (DMSP: F (16,200.89) = 2.48, p = 0.0019; DMSO: F (16,200.52) = 4.20, p = 5.3 x 10 − 7 ). The DMSP leaf content (Fig. 1 , Suppl. Mat. Figure 2 A) ranged from 25 µmol.g fw −1 (external leaf, Sect. 10–20 cm, August 2017, 10 m depth) to 167 µmol.g fw −1 (external leaf, Sect. 20–30 cm, February 2018, 15 m depth), for an average value of 78 ± 26 µmol.g fw −1 (mean ± standard deviation [SD], n = 230). The DMSO leaf content (Fig. 1 , Suppl. Mat. Figure 2 B) ranged from 0.9 µmol.g fw −1 (external leaf, Sect. 0–10 cm, August 2018, 15 m depth) to 7.1 µmol.g fw −1 (internal leaf, Sect. 0–10 cm, August 2017, 30 m depth), for an average value of 3.3 ± 1.4 µmol.g fw −1 (mean ± SD, n = 230). Overall, the DMSP leaf content was higher in February compared to other period and increased from external to internal leaves; it was lower at intermediate 15–20 m depths. This pattern for DMSP was similar for DMSO. The DMSP:DMSO ratio value (Fig. 1 , Suppl. Mat. Figure 2 C) ranged from 13 µmol:µmol to 52 µmol:µmol, for an average value of 25 ± 7 µmol:µmol (mean ± SD, n = 230). Out of the 230 DMSP:DMSO ratio values, 59 were lower than 20 µmol:µmol, including 22 lower than 18 µmol:µmol. Averaged by factor (period, depth, leaf class), all ratio values except August 2018 were between 20 and 27 µmol:µmol. The number of P. oceanica leaf samples analysed for DMSP and DMSO according to period (5), depth (5), leaf class (3) and leaf Sect. (4) was 230 (out of a theoretical maximum of 300; see coloured filled boxes in Suppl. Mat. Figure 2 heatmaps). Not all leaf classes and/or sections were present at each period and depth, with the exception of the basal part of intermediary and external leaves (Suppl. Mat. Figure 2 ). Internal younger leaves were shorter than intermediary and external leaves. Internal leaves were absent at 20 m depth in November 2017 and 10 and 15 m depth in August 2018. Leaves were shorter at 30 m depth and were shorter in November after the renewal of the leaf bundle (Bay 1984 ). The ratio of the leaf class-section DMSP and DMSO contents to the seagrass leaf bundle average contents (Suppl. Mat. Table 1) ranged, for the basal sections (0–10, 10–20, 0–20 cm) of external leaves, between 0.77 and 0.80. It ranged between 0.98 and 1.15 for the basal sections of intermediary leaves, with the best leaf section to bundle match for the 10–20 cm section (1.06 for DMSP, 0.98 for DMSO), then the 0–20 cm section (1.09 for DMSP, 1.04 for DMSO). DMSP and DMSO contents in the basal section (0–20 cm for years 2015–2016, 0–10 cm for years 2016–2017 and years 2017–2018) of P. oceanica rank 3–4 leaves showed seasonal and interannual variability at all depths from 10 to 30 m (Fig. 2 , Suppl. Mat. Figures 3 A,B). The variability of DMSP and DMSO contents with depth was less, in agreement with the observations made for P. oceanica 2017–2018 compartmentalisation study. DMSP and DMSO contents were higher in winter, lower in summer-autumn. Of the 87 sample average values, the maximum for DMSP was measured in February 2017 at 30 m depth (233 µmol.g fw −1 ; mean, n = 2) and the minimum in May 2018 at 15 m depth (50 µmol.g fw −1 ; n = 1). For DMSO, the maximum was measured in February 2017 at 20 m depth (12.3 ± 1.3 µmol.g fw −1 ; mean ± SD, n = 3) and the minimum in July 2016 at 10 m depth (1.5 µmol.g fw −1 ; mean, n = 2). The minimum (14.6 µmol:µmol; mean, n = 2) and maximum (55.9 µmol:µmol; mean, n = 2) of the DMSP:DMSO ratio were observed in May and July of year 2016, at depths 30 and 10 m, respectively. The DMSP:DMSO ratio value varied little compared to the DMSP and DMSO contents, and was to some extend lower in 2017 and 2018 at all depths except 30 m (Fig. 2 , Suppl. Mat. Figure 3 C). The average DMSP:DMSO ratio value of the 87 samplings performed between 10 and 30 m deep from spring 2015 to summer 2018 was 28.2 ± 7.2 µmol:µmol (mean ± SD, n = 87). The season effect on the organosulfur compounds in P. oceanica rank 3–4 leaf basal sections was evident when data were averaged by meteorological seasons and years, excluding the depth (DMSP: F (3,80) = 14.76, p = 9.8 x 10 − 8 ; DMSO: F (3,80) = 13.66, p = 2.8 x 10 − 7 ; Fig. 3 ). DMSP decreased from autumn-winter to summer. DMSO decreased from winter to summer, autumn showing transitional values. The inter-annual variability of organosulfur compound contents (DMSP: F (3,80) = 18.43, p = 3.5 x 10 − 9 , DMSO: F (3,80) = 6.77, p = 0.0004) resulted, for DMSP, from differences in autumn and spring between the years 2015-16 and 2017-18; between 2015 and 2018 for DMSO. The DMSP:DMSO ratio value remained relatively constant over time, with a slight increase from winter to summer-autumn ( F (3,80) = 5.06, p = 0.003) and inter-annual variability measured mainly between the years 2016 and 2017-18 ( F (3,80) = 8.60, p = 5.1 x 10 − 5 ). These annual differences in the DMSP:DMSO ratio, when considered on a seasonal basis, resulted in systematically higher values for the year 2016 ( p < 0.05 for summer and autumn), followed by the years 2015 and 2017-18. DMSP and DMSO contents measured in Z. marina and C. nodosa whole leaf bundles (Table 1) were 1 to 3 orders of magnitude lower than in P. oceanica leaf samples (all leaf classes and sections of the three sampling designs combined). They varied by a factor of 7 between minimum and maximum contents for DMSP, from 0.02 µmol.g fw −1 (Port Laso, France) to 0.13 µmol.g fw −1 (Kernisi, France); by a factor of 15 for DMSO, from 0.04 µmol.g fw −1 (Krisitneberg, Sweden) to 0.58 µmol.g fw −1 (Kernisi, France). The levels of organosulfur compounds in C. nodosa were within the range of variation of the levels in Z. marina . The inter-sites variability did not follow a geographical pattern. Overall, the general scatterplot of DMSP and DMSO contents for all P. oceanica leaf samples collected between years 2015 and 2018 showed a clear linear relationship between the two compounds (R 1 = 0.40, F (1,412) = 322.9, p < 2.2 x 10 − 16 ; Suppl. Mat. Figure 4 ); and similarly for Z. marina and C. nodosa (Suppl. Mat. Figure 5). The relationship in P. oceanica was modelled from measurements performed on different sections of the different leaf classes-ranks, sampled along a depth gradient at different seasons over several years, in a non-disturbed meadow. Therefore, we argue this is representative of a P. oceanica meadow in its biological/physiological complexity. The slope of the median regression was 0.035, i.e. the amount of DMSO in P. oceanica leaf tissues was equivalent to 3.5 % that of DMSP. Seawater temperatures in July and August, especially at the shallowest depth of 10 m, were up to 4°C higher in 2018 compared to 2016 (Fig. 2 ), most probably in response to the European 2018 heatwave (Liu et al. 2020 ). Predictions for DMSP and DMSO contents in P. oceanica intermediary leaf basal section from median regression with restricted cubic spline function was minimal for a temperature of 24.5°C (DMSP: b 1 = -29.21, t (9) = -4.14, p = 0.0025 and b 2 = 20.48, t (9) = 5.79, p = 0.0003; DMSO: b 1 = -0.94, t (9) = -2.54, p = 0.032 and b 2 = 0.87, t (9) = 2.48, p = 0.035; Fig. 4 ). This temperature corresponded to the average value at 10 m depth for 2016, the coldest summer water temperature recorded at that depth over the survey. The averages of July and August temperatures at 20 m depth were relatively similar between years, close to the value of 24.5°C. At temperatures lower (for 30 m depth) or higher (for years 2015, 2017 and 2018 at 10 m depth) corresponded higher DMSP and DMSO contents in P. oceanica rank 3–4 leaf basal section. P. oceanica relative growth rate (d − 1 ) response to experimental warming, fitted with the temperature cardinal model with inflexion (Savva et al. 2018 ), mirrored DMSP and DMSO model trends. The curvature of the median regression model prediction, convex for the DMSP:DMSO ratio (DMSP: b 1 = 3.17, t (9) = 1.11, p = 0.294 and b 2 = -3.01, t (9) = -0.85, p = 0.420; Fig. 4 ), showed maximum value for the depth 10 m in 2016. The increase of DMSP and DMSO contents with increasing temperature was particularly evident when considering 10 m depth data only (DMSP: b = 17.11, t (2) = 5.41, p = 0.033; DMSO: b = 1.17, t (2) = 25.29, p = 0.0016; Fig. 4 ). An increase in average temperature in July and August of 3°C corresponded to a doubling of the DMSP and DMSO contents remaining in summer (i.e. at the end of the autumn/winter to summer seasonal decrease of molecule contents in leaves). The trend for the DMSP:DMSO ratio ( b = -7.21, t (2) = -3.05, p = 0.093; Fig. 4 ) was opposite to that of the individual organosulfur compounds. The opposite slopes and curvatures of the models meant that the decrease in DMSO from recorded temperature extrema to 24.5°C was greater than that of DMSP. 4. Discussion This study confirms that P. oceanica is a top producer of DMSP and DMSO among marine photoautotrophs, with leaf contents ranging from 25 to 265 µmol.g fw −1 for DMSP and from 1.0 to 13.9 µmol.g fw −1 for DMSO. This observation was in line with recent research on that species (Borges and Champenois 2015 , 2017 ; Champenois and Borges 2019 ; Richir et al. 2020 ). High DMSP contents, of the same order of magnitude as in P. oceanica , were reported in Chlorophyta, mainly of the genus Ulva with up to 128 µmol.g fw −1 in U. lactuca (Van Alstyne and Puglisi 2007; Van Alstyne et al. 2007); and for DMSO, up to 16.7 µmol.g fw −1 in natural marine phytoplankton communities from warm waters (Simó and Vila-Costa 2006 ; Richir et al. 2020 ). The scientific literature on DMSP in seagrasses is scarce; so far, inexistent for DMSO. DMSP measured in the epiphyte-leaf complex of H. wrightii , S. filiforme (Dacey et al. 1994 ) and Z. marina (White 1982 ) was very low compared to P. oceanica (≤ 3.3 µmol.g fw −1 , after transformation from dry to fresh weight content for Z. marina , considering a moisture content of 75 %); and the production of DMSP by non-epiphytized leaves was two to three orders of magnitude lower in T. testudinum (0.18, 0.21 µmol.g fw −1 ; Dacey et al. 1994 ) and Z. noltei (0.14 µmol.g fw −1 ; Jonkers et al. 2000 ) than in P. oceanica . This difference in DMSP content with P. oceanica was similar for C. nodosa (0.07 µmol.g fw −1 ) and Z. marina (0.02–0.12 µmol.g fw −1 ) leaf bundles in the present study; and DMSO content differed by one order of magnitude in average for C. nodosa (0.25 µmol.g fw −1 ) and Z. marina (0.04–0.39 µmol.g fw −1 ). High DMSP(O) production may therefore not be a general characteristic shared among seagrasses, as previously reported for Chlorophyta (Van Alstyne 2008). The amount of DMSO relative to that of DMSP in P. oceanica leaf tissues was 3.5 %. This value was similar to that of 3.8 % previously reported by Richir et al. ( 2020 ) on their reduced dataset (less than one third of the present dataset) and to that of 1.6-4.0 % reported by Husband and Kiene ( 2007 ) for S. alterniflora . DMSP and DMSO contents were also correlated in C. nodosa and Z. marina confirming the finding of Richir et al. ( 2020 ) that DMSP and DMSO are correlated in marine autotrophs (phytoplankton, macroalgae, magnoliophytes). Higher DMSP and DMSO contents in young leaf tissues decreased continuously with the growing cycle, which was the aging of the leaf bundle. This seasonal feature, reported by Richir et al. ( 2020 ) for P. oceanica third (rank 3) leaves was confirmed in the present study, regardless of the year, depth or leaf tissue. Contents of photosynthetic pigments that are essential compounds in photoautotrophs also decrease with leaf tissue aging in seagrasses, e.g. T. testudinum (Enríquez et al. 2002 ). Several processes can explain this decrease in organosulfur compound contents: young leaf tissues benefit from an initial stock of molecules that decreases (dilution and metabolism) with aging; leaves produce these compounds continuously but at a rate too low to compensate for their dilution and metabolism; minimum contents in late summer early autumn prior annual renewal of the leaf bundle result from translocalisation and recycling of essential elements including S through rhizomes from old, senescent, decaying adult leaves. S. alterniflora is the largest DMSP producer among Spartina species (Otte et al. 2004 ; Rousseau et al. 2017 ) and the second among coastal higher plants after P. oceanica . In P. oceanica , the plant size, age and biomass are directly related. The production of DMSP and DMSO decreases with aging, therefore with the increase of biomass. The experimental stimulation with nitrogen supply of S. alterniflora biomass production led to the dilution of DMSP content (Otte and Morris 1994 ). Of the hypotheses listed above for P. oceanica , DMSP and DMSO dilution with biomass increase was more likely to occur. Finally, results of the present study showed that intermediary leaves (rank 3–4; i.e. inserted between the recently grown internal leaves [rank 1–2] and the oldest external ones, possibly senescent and ready to fall [rank 5–6, for an average number of 6 leaves per P. oceanica bundle]), with an organosulfur molecule content similar to the average value calculated for the seagrass leaf bundle, appeared to be the best choice of sample material to study DMSP and DMSO in that species. Observations from this study and previous work (Romero et al. 2007 ; Luy et al. 2012 ; Richir et al. 2020 ) therefore justify the election of intermediary, rank 3–4 leaves as representative tissue to study the plant biology. In addition, sampling only intermediary leaves above their meristem is non-destructive and allows for plant survival (Gobert et al. 2020 ). Temperature could play a (indirect) role in the observed seasonal trends of DMSP and DMSO contents in P. oceanica leaf tissues. There is little/no data to our best knowledge on the relationship between DMSP and DMSO production in marine coastal higher plants and temperature, except in Richir et al. ( 2020 ). These authors reported weak to modest relationships of P. oceanica leaf organosulfur compound contents with temperature. In algae, the negative relationship between DMSP content and temperature (Karsten et al. 1992 ; Lyons et al. 2010 ) suggested a cryoprotectant function (reviews on DMSP functions in: Otte et al. 2004 ; Stefels et al. 2007 ; Van.Alstyne 2008 ). Such a function is unlikely in P. oceanica because that species, endemic of the Mediterranean, grows in temperate environmental conditions (Boudouresque and Meinesz 1982 ) and must not cope with cold water temperatures but with global warming (Duarte et al. 2018 ; Darmaraki et al. 2019 ). Average DMSP and DMSO contents according to the year and depth in July-August were the lowest for a narrow range of temperature, between 23.5–25.5°C. Temperatures lower (for 30 m depth) or higher (for years 2015, 2017 and 2018 at 10 m depth) corresponded with higher summer average DMSP and DMSO contents. Hendriks et al. ( 2017 ) experimentally tested the effect of light availability and warm temperature (29–30°C) on P. oceanica growth and photosynthetic activity. Temperature had a negative effect on growth. Low light availability also negatively affected photosynthetic performance. DMSP and DMSO contents in P. oceanica seemed, like in S. alterniflora (Otte and Morris 1994 ), to be related to the growth and biomass production of the plant (dilution and resource allocation). Considering that organosulfur compound contents would decrease as a result of improved plant growth under optimal environmental conditions, the relationships modelled in the present study reflected the negative impact of higher temperature on the plant biomass production at low depth (10 m) and the combined negative effect of low light availability but positive effect of increased temperature on biomass production in deeper water (30 m). In addition, the relative growth rate response of P. oceanica to experimental warming modelled in Saava et al. (2018) mirrored the relationships between DMSP and DMSO summer contents with temperature. Based on these observations, the next work should focus on the direct effect of primary production in contrasted environmental conditions on the contents of DMSP and DMSO. The trend for the DMSP:DMSO ratio in relation to summer temperature, depending on the year and depth, was opposite to that of the organosulfur compounds, with maximum at 24.5°C and a decrease towards recorded temperature extrema. DMSP, DMSO, DMS, acrylate and methane-sulfinic acid constitute a cascade reaction system against oxidative stress in the algal cell (Sunda et al. 2002 ; Deschaseaux et al. 2014 ). In yellowing (senescence) and herbicide treated S. alterniflora (Husband and Kiene 2007 ; Husband et al. 2012 ), and in cordgrasses collected from areas affected by sudden dieback, grazing and wrack deposition (McFarlin and Alber 2013 ), DMSP was converted to its oxidation product DMSO resulting in a lower DMSP:DMSO ratio (published as DMSO:DMSP ratio by the authors) compared to healthy unstressed plants. Conversely, at environmental optima (e.g. light and temperature), P. oceanica biomass production would be maximum, its physiological status globally very good, and the higher DMSP:DMSO ratio value an indicator of this overall good health status (corresponding to maximum growth rate; Savva et al. 2018 ). The average DMSP:DMSO ratio value of 28.2 ± 7.2 µmol:µmol in P. oceanica basal section of rank 3–4 leaves (min = 14.6 µmol:µmol, max = 55.9 µmol:µmol) was close to that of 29.2 ± 9.0 µmol:µmol reported by Richir et al. ( 2020 ). Just as the DMSP and DMSO contents of healthy Z. marina and C. nodosa leaf bundles were low compared to P. oceanica , so were their ratios. In different marine algal taxa grown under axenic conditions and used for DMSO reduction studies, Spiese et al. ( 2009 ) reported DMSP p :DMSO p ( p for particulate) ratios (published as DMSO p :DMSP p ratio by the authors) varying by four order of magnitude, from 3.3 for Thalassiosira oceanica to 1,870 for Isochrysis galbana . In response to salinity stress, the DMSP p :DMSO p ratio increased in laboratory batch cultures of the two phytoplankton species Phaeocystis globosa and Heterocapsa triquetra (Speeckaert et al. 2019 ); and in Fe-limited T. oceanica phytoplanktonic cells, the higher DMSP p :DMSO p ratio relative to Fe-sufficient cells was explained by the net loss of DMSO via its enzymatic reduction to more lipophilic DMS (Bucciarelli et al. 2013 ). The evolution of DMSP and DMSO levels, and thus their ratio in marine primary producers exposed to environmental stresses, and the relevance of its use as a stress indicator therefore requires a thorough knowledge of the production-transformation kinetics of these compounds, specific to the species and the stressor. Inter-annual variations of DMSP, at 10 m depth (and shallower) where the temperature can reach and exceed the physiological maximum of P. oceanica might indicate that the organosulfur compound contents were directly involved in the response of the plant to heat-stress. Stress, including heat-stress leads to the enhanced accumulation of toxic compounds in cells, among them reactive oxygen species (ROS; Suzuki and Mittler 2006 ; Kotak et al. 2007 ) efficiently scavenged by DMSP and DMSO (Sunda et al. 2002 ). McLenon and DiTulino (2012) experimentally observed an increase of DMSP concentration in Symbiodinium cells isolated from the cnidarian Acacia pulchella when maintained at 33°C, suggesting an antioxidant function of DMSP under temperature-induced oxidative stress. Experimental temperature increase had, in contrast, no or little effect on antioxidant capacity and DMSP concentrations in Symbiodinium cells and their host sea anemone Entacmaea quadricolor (Deschaseaux et al. 2018 ). An end of century temperature scenario (23°C) had no significant effects on the concentrations of DMSP and DMS in Amphidinium carterae cultured dinoflagellates (Li et al. 2020 ). However, two ecotypes of the terrestrial plant Arundo donax from warm sub-humid (Central Italy) and hot semi-arid (Morocco) habitats - existing environmental scenarios - showed differences in DMSP leaf content, with DMSP (and isoprene) increase under the moderate stress conditions of the second habitat (Haworth et al. 2017 ). These observations, different but not contradictory (no DMSP decrease), seem to indicate a potential direct link between heat stress, ROS and the dynamics of DMSP(O) and DMS in plants and algae. DMSP content in seagrasses could be explored in relation to phylogenetic history. In cordgrasses of the genus Spartina , the physiological ability to biosynthesize DMSP was explained phylogenetically (Rousseau et al. 2017 ). P. oceanica and T. testudinum belong to two different lineages, respectively the Posidoniaceae/Zosteraceae and the Marine Hydrocharitaceae viz. Enhalus/Thalassia (according to the revised classification of Dilipan et al. 2018 ); but their belonging to different lineages is probably not the explanation for the measured differences in leaf DMSP production. Indeed, low DMSP content was measured in Z. marina (0.04–0.39 µmol.g fw −1 ) and Z. noltei (0.14 µmol.g fw −1 ; Jonkers et al. 2000 ), two species that belong like P. oceanica , to the Posidoniaceae/Zosteraceae lineage. Another useful method of categorizing seagrasses is on the basis of their growth forms, from small plants with thin leaves (e.g. Halodule ) to large plants with thick leaves (e.g. Posidonia ). This seagrass functional form model proposed by Walker et al. ( 1999 ) is ultimately related to seagrass rhizome turnover: rapid rhizome turnover in the smaller seagrass genera and slower turnover of persistent rhizomes in the larger seagrasses. Consistent with rhizome turnover rate is leaf turnover rate, more rapid in smaller seagrasses than in larger species (Duarte 1991 ; Duarte and Chiscano 1999 ; Walker et al. 1999 ). The two Zostera species share with T. testudinum (and to a lesser extend with C. nodosa ) a rapid turnover rate of their tissues when compared to P. oceanica (Duarte 1991 ; Duarte and Chiscano 1999 ). Slower turnover rates allow higher buildup of secondary compounds including predator deterrents, thus reducing palatability to grazers (Walker et al. 1999 ). High secondary metabolite DMSP production by the slow-turnover species P. oceanica has been proposed as a protective mechanism against grazing (Richir et al., 2020 ; Borges and Champenois, 2015 ). Grazing plays a central role in seagrass ecology (Heck and Valentine 2006 ; Valentine and Duffy 2006 ). Depending on time and location, between ∼3 % and 100 % of seagrass net primary production enters food webs via the grazing pathway (Heck and Valentine 2006 ). As an example, 50 % to 100 % of the aboveground biomass of T. testudinum can be consumed by the purple urchin Lytechinus variegates (Valentine and Heck 1991 ) and 40 % to 70 % of P. oceanica leaf production can be grazed by the herbivorous fish Sarpa salpa (Tomas et al. 2005 ; Prado et al. 2007 ). Peirano et al. ( 2001 ) reported - for the three main grazers of P. oceanica - a maximum grazing on leaves in September and June for S. salpa , in March for the urchin Paracentrotus lividus , whereas it was irregular for the isopods Idotea spp.; and Tomas et al. ( 2005 ) observed abundant S. salpa grazing marks (> 55 % of collected shoots) all year round, and higher P. lividus bites in winter/spring. Grazing pressure, which may be seasonal depending on the herbivorous behaviour of the species, occurs throughout the annual growth cycle of the seagrass. Vergés et al. ( 2007 ) experimentally showed that organic extracts of P. oceanica (secondary metabolites, including phenolics) deterred grazers from feeding. However, it is worth to say that seagrass deterrence response to grazers is not unique, with grazer identity and density, and seagrass species and leaf tissue all playing important roles in deterrent production (Steele and Valentine 2015 ). Herbivory on seagrasses is an important process whose potential effect on the production of the secondary metabolites DMSP and DMSO remains to be investigated; especially considering the grazer deterrent function of DMSP and its cleavage products (DMS, acrylic acid) discussed in other marine photoautotrophs (Van.Alstyne and Houser 2003 ; Otte et al. 2004 ; Fredrickson and Strom 2009 ). A common trait to seagrasses is the need of osmoregulation in seawater. Seagrasses have developed several strategies for osmoregulation (Papenbrock 2012 ) including the synthesis of compatible osmolytes. DMSP is a compatible osmolyte used for osmoregulation by macro-algae and micro-algae (Stefels et al. 2007 ), that can be advantageous in oligotrophic environments (e.g. Mediterranean coastal waters) compared to N containing compatible osmolytes such as betaine (Colmer et al. 1996 ; Kocsis and Hanson 2000 ). In P. oceanica , the increase of salinity leads to the synthesis of sugars and amino acids (Marín-Guirao et al. 2011a , b ; Sandoval-Gil et al. 2012 ), but the synthesis of DMSP was not tested, which does not exclude that it could act as an osmolyte. Increased synthesis of amino acids is compatible with the one of DMSP, since in plants methionine is usually a precursor of DMSP (Kocsis and Hanson 2000 ; Bullock et al. 2017 ). The fact that seagrasses have developed different strategies for osmoregulation is compatible with a strong variability of DMSP content among different seagrasses. 5. Conclusion Recent work on P. oceanica and the present study demonstrated this seagrass species was the largest producer of DMSP and DMSO reported to date among coastal autotrophs, and most probably the major contributor to the dissolved DMS(P,O) pool in coastal waters of the oligotrophic Mediterranean. DMSP and DMSO production and content dynamics in P. oceanica were related to the plant biology/physiology, in particular to its growth cycle and productivity which varies over time (season, year) and with depth. Temperature would indirectly affect DMSP and DMSO content dynamics through direct effect on the plant biomass production, leading to the more or less rapid dilution of an initial stock of molecules concentrated in newly grown leaf tissues. Whatever the sampling conditions or the leaf tissue analysed, a notable characteristic was the constant ratio of the two molecule contents. Such a constant ratio was an indicator of a strong biochemical link between DMSP and DMSO. Now that we have a basic, in depth understanding of the natural variability of DMSP and DMSO in P. oceanica leaves, future work should focus on their biosynthetic pathways and metabolism in relationship to its growth cycle and productivity. DMSP (and DMSO) physiological functions are not fully elucidated, and it may vary among coastal higher plants. Although hypothetical, grazer deterrence seems to be a likely function in P. oceanica , whilst the antioxidant function - including against heat stress - will require experimental testing. Current studies on sampling location and species comparison and the analysis of experimentally stressed plants will allow responding to some of the questions raised in this work. Declarations Funding (information that explains whether and by whom the research was supported) Funding was provided by F.R.S-FNRS for salary and material, and by the STARESO via the STARECAPMED programme for fieldwork. Conflicts of interest/Competing interests (include appropriate disclosures) No conflict of interest. Ethics approval (include appropriate approvals or waivers) Authors had all the necessary authorizations for seagrass sampling, and used a little invasive, non-destructive technique that ensures the post-regrowth of sampled tissues. Consent to participate (include appropriate statements) All authors consent to participate. Consent for publication (include appropriate statements) All authors and all institutions that provided funding and to which the authors belong consent to the publication of this study. Availability of data and material (data transparency) Raw DMSP(O) data are published alongside the paper (Mendeley Data). Code availability (software application or custom code) Out of scope. Authors' contributions (optional: please review the submission guidelines from the journal whether statements are mandatory) Jonathan Richir: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing. Willy Champenois: Conceptualization, Investigation, Validation, Writing – review & editing. Jimmy de Fouw: Formal Analysis, Investigation, Writing – review & editing. Alberto V. Borges: Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – review & editing. Acknowledgements This work was funded by the Fonds National de la Recherche Scientifique (FNRS) (Fellowship-Grant 1237018F and contract 2.4.637.10). Authors thank Pr R. Koenker from the Department of Economics, University College London, UK for his help in quantile regression. At the time of this study, J. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-309046","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":44133308,"identity":"e31b7af3-6f79-463e-b529-f270b0f97436","order_by":0,"name":"Jonathan Richir","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-5890-5724","institution":"University of Liège","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Richir","suffix":""},{"id":44133309,"identity":"0f93a5ef-7b1d-4091-a678-e217df2fa781","order_by":1,"name":"Willy Champenois","email":"","orcid":"","institution":"Universtity of Liege","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Willy","middleName":"","lastName":"Champenois","suffix":""},{"id":44133310,"identity":"7dad7bc5-6386-47ec-8eaa-3544c15ec7b1","order_by":2,"name":"Jimmy de Fouw","email":"","orcid":"","institution":"Radboud University Nijmegen: Radboud Universiteit","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jimmy","middleName":"","lastName":"de Fouw","suffix":""},{"id":44133311,"identity":"5d920db9-2f5a-4f12-a356-1be41f96d01f","order_by":3,"name":"Alberto V. Borges","email":"","orcid":"","institution":"University of Liege","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"V.","lastName":"Borges","suffix":""}],"badges":[],"createdAt":"2021-03-08 08:12:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-309046/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-309046/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":12257277,"identity":"6b584201-e828-47d1-93c2-0e74ebde1b53","added_by":"auto","created_at":"2021-08-09 17:53:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":14820,"visible":true,"origin":"","legend":"DMSP content (μmol.gfw-1), DMSO content (μmol.gfw-1) and C) DMSP:DMSO ratio value (μmol:µmol) in Posidonia oceanica leaf samples (n = 230) grouped by factor variables leaf class, period and depth (m). Data are averages (mean ± SD) of P. oceanica 10 cm long leaf sections (n = 1-4 sections, depending on the length of the leaves). The three leaf classes are: internal (rank 1-2 on average), intermediary (rank 3-4 on average) and external (rank 4-5 on average).","description":"","filename":"OnlineFig.1canopy.png","url":"https://assets-eu.researchsquare.com/files/rs-309046/v1/67bf37ff288e5a04bce8723c.png"},{"id":12257005,"identity":"64e1a853-13c9-4838-a370-25a10c748290","added_by":"auto","created_at":"2021-08-09 17:50:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":16262,"visible":true,"origin":"","legend":"Seasonal and interannual variability of A) DMSP content (μmol.gfw-1), B) DMSO content (μmol.gfw-1) and C) DMSP:DMSO ratio value (μmol:µmol) in the basal section (0-20 cm for years 2015-2016, 0-10 cm for years 2016-2017 and years 2017-2018) of Posidonia oceanica rank 3-4 leaves, sampled at 10 m depth. P. oceanica data (dots) are mean ± SD (n = 1-3). The light grey line is the daily mean temperature (one record every 10 or 60 min). Bright coloured rectangles highlight the data for July and August. ","description":"","filename":"OnlineFig.210mts.png","url":"https://assets-eu.researchsquare.com/files/rs-309046/v1/bdcd893d401a94ff98015c45.png"},{"id":12257008,"identity":"53d18f54-b716-40e4-bdd5-455d9f95a64d","added_by":"auto","created_at":"2021-08-09 17:50:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":16108,"visible":true,"origin":"","legend":"Boxplots (median [bold line]; Q1 and Q3 [boxes], ranges [whiskers] and outliers [dots]) of seasonal and interannual variability of DMSP content (μmol.gfw-1), DMSO content (μmol.gfw-1) and DMSP:DMSO ratio value (μmol:µmol) in the basal section (0-20 cm for years 2015-2016, 0-10 cm for years 2016-2017 and years 2017-2018) of Posidonia oceanica rank 3-4 leaves. P. oceanica data are mean ± SD (n = 5-16 dates and depths on a data set of 87 samplings), all 10 to 30 m depths considered. Season are meteorological seasons. The winter value for 2016 corresponds to the average of data for December 2015, January 2016 and February 2016 (same for winter values for 2017 and 2018). Upper case letters in brackets represent differences (p \u003c 0.05, two-way ANOVA and Tukey’s post-hoc test) between seasons (in the graphic windows) or years (in the legends). Lower case letters represent differences (p \u003c 0.05, one-way ANOVA and Tukey’s post-hoc test) between years, for each season.","description":"","filename":"OnlineFig.3Meteo.Season1223568911.png","url":"https://assets-eu.researchsquare.com/files/rs-309046/v1/87c851cdef7c9477d22d1ed7.png"},{"id":12257276,"identity":"f010db48-ee9d-4e49-a9cd-99be6e1cb62f","added_by":"auto","created_at":"2021-08-09 17:53:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":17846,"visible":true,"origin":"","legend":"Relationships between DMSP content (μmol.gfw-1), DMSO content (μmol.gfw-1) or DMSP:DMSO ratio value (μmol:µmol) in the basal section (0-20 cm for years 2015-2016, 0-10 cm for years 2016-2017 and years 2017-2018) of Posidonia oceanica rank 3-4 leaves with temperature, for depths 10, 20 and 30 m (three left graphics) or depth 10 m only (three right graphics). Numbers 5 to 8 represent years 2015 to 2018, respectively. P. oceanica and temperature data are mean ± SD (n = 1-8 for P. oceanica; n = 16 daily average values for temperature) for July and August. Temperature data are values greater than or equal to their respective 75th percentile for that period. Blue lines are predictions from median regression with restricted cubic spline function (three left graphics) or best linear-fits (three right graphics). The red line is P. oceanica relative growth rate (d-1) response to experimental warming, fitted with the temperature cardinal model with inflexion (Savva et al., 2018).","description":"","filename":"OnlineFig.4.DMSvsTemp75th.perc.RGS.png","url":"https://assets-eu.researchsquare.com/files/rs-309046/v1/77cd735f25c8d4f420834576.png"},{"id":15674521,"identity":"7ee347f5-ab2e-44c8-90f5-b0e89a530538","added_by":"auto","created_at":"2021-11-18 14:23:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":465409,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-309046/v1/50ee1691-8e0a-4037-b1e2-250d343daaf7.pdf"},{"id":12257006,"identity":"afd4725a-5625-4bb7-bf71-a765c283b8df","added_by":"auto","created_at":"2021-08-09 17:50:23","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":334988,"visible":true,"origin":"","legend":"","description":"","filename":"Table.1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-309046/v1/b6f4592b56dcbef6c67d3037.pdf"},{"id":12257009,"identity":"e281bbce-0fc8-4da3-8a11-0a7c0966dc56","added_by":"auto","created_at":"2021-08-09 17:50:24","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":7687477,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Material.docx","url":"https://assets-eu.researchsquare.com/files/rs-309046/v1/72733e598689f782bfc58d06.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eDimethylsulfoniopropionate and dimethylsulfoxide in \u003cem\u003ePosidonia oceanica\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHaas (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1935\u003c/span\u003e) showed that the red macroalgae \u003cem\u003ePolysiphonia fastigiata\u003c/em\u003e and \u003cem\u003eP. nigrescens\u003c/em\u003e when exposed to air emitted dimethyl sulphide (DMS). It was unlikely that DMS was stored as such in the macroalgae, given the small size of the molecule and its high diffusivity. This suggested the occurrence of a precursor sulphonium compound, identified as DMSP by Challenger and Simpson (1948). The first report on the second biogenic precursor of DMS in marine algae, dimethylsulfoxide (DMSO) is more recent. Given the large, often dominant pool of DMSO in aquatic environments, it was hard to envisage its maintenance solely via a DMS precursor (Lee and de.Mora \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). de Mora et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) speculated a direct biosynthetic pathway on the basis of evidence gathered in Antarctic melt-water ponds that contained relatively high levels of dissolved DMSO but low concentrations of DMS and very little dissolved DMSP. In the coastal waters of North Island, New Zealand, Lee and de Mora (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) speculated that algal photosynthetic processes may have played a role in the rapid daytime production of dissolved DMSO that could not have only resulted from photo- and bacterial oxidation of DMS. Sim\u0026oacute; et al. (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) confirmed the biogenic production of DMSO by marine microalgae in laboratory cultures of \u003cem\u003eAmphidinium carterae\u003c/em\u003e and \u003cem\u003eEmiliania huxleyi\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eSince these initial results reporting DMSP and DMSO associated with macroalgae and phytoplankton (Challenger and Simpson, 1948; Sim\u0026oacute; et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), a number of studies have addressed first their occurrence and production, then their biosynthesis in marine primary producers (Lee and de.Mora \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Lee et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Stefels \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Hatton et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Stefels et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). DMS, DMSP and DMSO are tightly interrelated compounds that constitute an integral part of the marine sulfur cycle and play an important role in the global sulfur budget (Stefels et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Asher et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The proposed cooling effect on climate through increased albedo of DMS derived cloud condensation nuclei (Lovelock and Maggs \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; Charlson et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) has stimulated considerable research into this gas and its precursors during the last three decades. The recent discovery of a new metabolite, dimethylsulfoxonium propionate (DMSOP) synthesized by several DMSP-producing microalgae and marine bacteria, has extended the paradigm of the marine sulfur cycle (Thume et al. \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDMSP and DMSO are ubiquitous in the upper ocean (Lee et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Sim\u0026oacute; and Vila-Costa \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Their biogenic production is however taxon-dependent and large producers are confined to a few classes of micro- and macroalgae (Stefels \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Sim\u0026oacute; and Vila-Costa \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Hatton and Wilson \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Unlike algae, for which an important scientific literature is available, observations of DMSP (and DMSO) in higher plants are rare (Stefels \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Vegetated sediments of salt marshes are major sources of DMS emission to the atmosphere (Steudler and Peterson \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). It was obvious to investigate their biogenic precursors in the dominant grasses of these systems, i.e. plants of the genus \u003cem\u003eSpartina\u003c/em\u003e. DMSP was first reported in \u003cem\u003eSpartina anglica\u003c/em\u003e (Larher et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1977\u003c/span\u003e), later in \u003cem\u003eS. alterniflora\u003c/em\u003e (Dacey et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1987\u003c/span\u003e) and in \u003cem\u003eS. foliosa\u003c/em\u003e (Otte and Morris \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). The first report of DMSO in salt marsh grasses is more recent. Its discovery in \u003cem\u003eS. alterniflora\u003c/em\u003e by Husband and Kiene (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) relied on the idea that if DMSO was present in some DMSP producing phytoplankton, this compound might also be found in DMSP producing higher plants. These authors reported DMSO content in ratio to DMSP of 1.6-4.0 %, values much lower than for phytoplankton (8\u0026ndash;50 %; Sim\u0026oacute; and Vila-Costa \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eReports of DMSP and DMSO in seagrasses are even more rare than in cordgrasses. White (\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e1982\u003c/span\u003e) when developing a method for the analysis of dimethyl sulfonium compounds in marine macrophytes, measured DMSP in \u003cem\u003eZostera\u003c/em\u003e sp. (most probably \u003cem\u003eZ. marina\u003c/em\u003e, the dominant native \u003cem\u003eZostera\u003c/em\u003e species on the Pacific coast of North America [Green and Short \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2003\u003c/span\u003e] and referred as such by Dacey et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1987\u003c/span\u003e]), although its production was likely affected by algal epiphytes (Bianchi \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In the mid-90s, Dacey et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) measured DMSP in the epiphytized leaves of three seagrasses: \u003cem\u003eHalodule wrightii\u003c/em\u003e, \u003cem\u003eSyringodium filiforme\u003c/em\u003e and \u003cem\u003eThalassia testudinum\u003c/em\u003e; they attributed DMSP mostly to leaf epiphytes, since DMSP content in \u003cem\u003eT. testudinum\u003c/em\u003e non-epiphytized leaves was 3\u0026ndash;8 times lower. Very low DMSP contents were also reported in non-epiphytized leaves of \u003cem\u003eZ. noltei\u003c/em\u003e (Jonkers et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), in roots of that species (Jonkers et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and in rhizomes of \u003cem\u003eT. testudinum\u003c/em\u003e (Dacey et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the oligotrophic coastal ecosystem of Niel Bay (NW Mediterranean, France), algal biomass and particulate DMSP were low; because phytoplankton alone could not fully explain the high dissolved DMSP levels measured there, Jean et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) assumed benthic macrophytes including \u003cem\u003eP. oceanica\u003c/em\u003e contributed to the dissolved DMSP pool. This assumption was recently, confirmed by Borges and Champenois (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), who resurrected the interest in the production of DMSP by seagrasses by investigating its content in \u003cem\u003ePosidonia oceanica\u003c/em\u003e; they also showed the occurrence of DMSO in this plant (Borges and Champenois \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). DMS was further reported to be the main volatile organic compound (59.3%) in \u003cem\u003eP. oceanica\u003c/em\u003e (Jerković et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), \u003cem\u003ede facto\u003c/em\u003e explained by the high values of DMSP and DMSO measured in its leaves (Borges and Champenois \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). \u003cem\u003eP. oceanica\u003c/em\u003e is a top producer of DMSP and DMSO among marine and intertidal autotrophs, with foliar contents reaching up to 265 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e for DMSP and 13 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e for DMSO (Richir et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The production dynamics of the two molecules in \u003cem\u003eP. oceanica\u003c/em\u003e are closely linked and depend more on the plant\u0026rsquo;s annual growth cycle than on environmental variables (light and temperature; Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). DMSP and DMSO, more concentrated in young tissues, could play antioxidant and grazer deterrent functions (Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Their ratio, considering DMSO is the product of the oxidation of DMSP, could be a generic indicator of oxidative stress in the plant (Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), as initially postulated and verified for \u003cem\u003eS. alterniflora\u003c/em\u003e (Husband and Kiene \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Husband et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; McFarlin and Alber \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe present work aims at determining the natural variability of the DMSP and DMSO contents in \u003cem\u003eP. oceanica\u003c/em\u003e leaves (i) at seasonal and interannual time scales, (ii) with depth, (iii) in relation to leaf tissues ageing and (iv), in the context of ocean warming, with water temperature. This complete and detailed, depth-gradient (10\u0026ndash;30 m) study of almost 3.5 years (April 2015 - August 2018) on the ecophysiology of DMSP(O) in \u003cem\u003eP. oceanica\u003c/em\u003e leaves was carried out in a non-disturbed meadow in Corsica, France, in the framework of the STARECAPMED program (Richir et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In addition to \u003cem\u003eP. oceanica\u003c/em\u003e, some preliminary, indicative data on DMSP(O) contents in \u003cem\u003eZ. marina\u003c/em\u003e and \u003cem\u003eCymodocea nodosa\u003c/em\u003e leaves are also given.\u003c/p\u003e"},{"header":"2. Material And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design\u003c/h2\u003e \u003cp\u003eTo study the natural variability of DMSP and DMSO contents in \u003cem\u003eP. oceanica\u003c/em\u003e leaves over time, we compiled and analysed a large data set of novel unpublished data (n\u0026thinsp;=\u0026thinsp;293 samples and 285 DMSP(O) data pairs) and previously published data (n\u0026thinsp;=\u0026thinsp;130 samples and 129 DMSP(O) data pairs) by Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The previous data set covered, on a weekly to fortnightly basis, the period from mid-April to mid-July 2016 (Richir et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to which we added additional unpublished data collected in May, August and November 2016, February, August and November 2017, and February, May and August 2018 (see Sect.\u0026nbsp;\u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003e2.4\u003c/span\u003e for details). For these additional May 2016 to August 2018 data, sampling was systematically carried out along a 10\u0026ndash;30 m depth gradient (unlike the study of Richir et al. [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e] that mainly focused on the depth of 10 m). The compiled data set (n\u0026thinsp;=\u0026thinsp;423 samples and 414 DMSP(O) data pairs) allowed to explore the seasonal and interannual variations of the seagrass leaf DMSP(O) content in relation to those of temperature, that were marked during time period given strong heatwave in 2018 (Liu et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); it further allowed to test the hypothesis of the involvement of DMSP(O) in the physiological response of \u003cem\u003eP. oceanica\u003c/em\u003e to heat stress. Also, Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) only reported variations of the DMSP(O) content in the first 20 basal cm of \u003cem\u003eP. oceanica\u003c/em\u003e third rank leaf. Here, we explored the variability of DMSP(O) contents in leaves of different rank, i.e. age classes, from their base towards their tip (10 cm long leaf section; Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). \u003cem\u003eP. oceanica\u003c/em\u003e shoot structure is characterized by the distichous and alternating arrangement of its ribbon-like leaves, with the youngest ones at the center of the shoot, and the oldest ones on the outside (Buia et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Augier \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2007\u003c/span\u003e); foliar tissues are therefore older towards the outside of the leaf bundle and the tip of the leaf. In addition, the analysis of the leaf class and leaf section variability provided important information for the design of the best leaf tissue sampling protocol for assessing organosulfur dynamics in \u003cem\u003eP. oceanica\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study site\u003c/h2\u003e \u003cp\u003eThe study was conducted in a dense and healthy \u003cem\u003eP. oceanica\u003c/em\u003e meadow in the northwestern part of the Revellata Bay in the Gulf of Calvi (Corsica, France; Norie \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e1831\u003c/span\u003e), close to the STARESO research station (42.580\u0026deg;N, 8.725\u0026deg;E). The Gulf of Calvi has an area of about 22 km\u003csup\u003e2\u003c/sup\u003e, opens to the Ligurian Sea on the northeast with a border of about 6 km and connects to the deep sea by a canyon. The Gulf of Calvi is a \u0026lsquo;reference site\u0026rsquo; in a good state of environmental conservation (Gobert et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Lopez y Royo et al. 2010, 2011). The sea floor is dominated by a dense and healthy \u003cem\u003eP. oceanica\u003c/em\u003e meadow down to about 38 m depth (Bay \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Champenois and Borges \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Richir et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The study site of the present work is identical to that of Borges and Champenois (Borges and Champenois \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Water temperature recording\u003c/h2\u003e \u003cp\u003eWater temperature was recorded continuously with probes and loggers deployed in the \u003cem\u003eP. oceanica\u003c/em\u003e meadow facing the STARESO. Temperature data were accessed from the RACE database (Binard \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Temperature was recorded at 9.5 (considered 10) m depth with the incorporated temperature sensor of an Aanderaa oxygen optode (3835) mounted on Alec Instrument data-loggers (60 min interval; Xylem Inc.; Champenois and Borges \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and at 20 and 29 (considered 30) m depth with Hobo loggers (10 min interval; HOBO Pendant\u0026reg; Temperature/Light Data Logger, Onset Computer Corporation; Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The temperature sensors of the Aanderaa oxygen optode and the Hobo loggers were factory-calibrated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Seagrass sample collection\u003c/h2\u003e \u003cp\u003e \u003cem\u003eP. oceanica\u003c/em\u003e sampling was performed weekly to seasonally by scuba diving between April 2015 and August 2018. Three successive sampling designs were performed over that period: in years 2015\u0026ndash;2016 (first), 2016\u0026ndash;2017 (second) and 2017\u0026ndash;2018 (third), as described below. \u003cem\u003eP. oceanica\u003c/em\u003e sampling was performed in triplicate, on orthotropic shoots (i.e. vertical growth, as opposite to plagiotropic - horizontal - growth; Boudouresque et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) randomly selected on surfaces of a few m\u003csup\u003e2\u003c/sup\u003e. Sampling was performed by cutting the leaves just above the meristem area with a scissor to ensure their post-regrowth (Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; De los Santos et al. 2016; Gobert et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBetween April 2015 and July 2016, the first seagrass sampling design was performed at 10 m depth, at a weekly to fortnightly frequency; in July 2015, seagrasses were sampled along a depth gradient at 3, 10, 15, 20, 25, 29 (considered 30) and 36 m depth. Only the third leaf from the inside of the leaf bundle (i.e. rank 3; juvenile leaves - \u0026lt;5 cm long [Giraud \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1979\u003c/span\u003e] - were excluded) was sampled. The first 20 basal cm of sampled leaves were dissected for analysis (see Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn May, August and November 2016 and in February 2017, the second seagrass sampling design was performed along the depth gradient at 10, 15, 20, 25 and 30 m depth. Only the third external leaf from the outside of the leaf bundle (usually rank 4) was sampled. The first 10 basal cm of sampled leaves were dissected for analysis. \u003cem\u003eP. oceanica\u003c/em\u003e shoots have in average six leaves (Gobert et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); whether taken from outside (second sampling design) or inside (first sampling design) the bundle, the third leaf is therefore similar (rank 3 or 4; Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eIn August and November 2017 and in February, May and August 2018, the third seagrass sampling design was performed along the depth gradient at 10, 15, 20, 25 and 30 m depth. Entire \u003cem\u003eP. oceanica\u003c/em\u003e leaf bundles were sampled. Leaf bundles were clipped \u003cem\u003ein situ\u003c/em\u003e with plastic tongs prior cutting to keep the insertion order of the leaves. The leaves were sorted and pooled into three classes: the two most external leaves on each side (called \u0026lsquo;external\u0026rsquo;), the following two leaves on each side (called \u0026lsquo;intermediary\u0026rsquo;), all of the following leaves (called \u0026lsquo;internal\u0026rsquo;). Pooled leaf classes were then cut into four sections of 10 cm (0\u0026ndash;10, 10\u0026ndash;20, 20\u0026ndash;30 and 30\u0026ndash;40 cm) for analysis (Suppl. Mat. Figures\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The leaf grows from the base (acropetal growth; Boudouresque et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), so the younger section of the leaf corresponded to the first section (0\u0026ndash;10 cm) according to our convention. Because most leaf tips of the August 2017 samples were necrotic (most of leaves, old and senescent, are ready to decay at the end of summer), only the 40 first cm of \u003cem\u003eP. oceanica\u003c/em\u003e living leaf tissues were considered.\u003c/p\u003e \u003cp\u003eQuickly after the end of the dive, seagrass leaf samples were dissected in STARESO facility, then prepared and stored according to the protocol of Borges and Champenois (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Briefly, leaf samples were cleaned of epiphytes (when present) with a razor blade (Dauby and Poulicek \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) during dissection, and lower little-pigmented sections of sampled leaves systematically discarded. Dissected leaf tissues were stored in 20 ml borosilicate vials sealed with polytetrafluoroethylene coated silicone septa stopper or in plastic bags and frozen at -20\u0026deg;C until DMSP and DMSO analysis. Samples were brought back frozen to the University of Li\u0026egrave;ge (Belgium) to avoid DMSP loss during transport.\u003c/p\u003e \u003cp\u003eIn addition to \u003cem\u003eP. oceanica\u003c/em\u003e sampling and for comparison purpose between temperate seagrass species, \u003cem\u003eCymodocea nodosa\u003c/em\u003e (subtidal species) and \u003cem\u003eZostera marina\u003c/em\u003e (predominantly subtidal species) shoots were collected in August of years 2018 and 2019; in Alfax Bay, Spain, for \u003cem\u003eC. nodosa\u003c/em\u003e, and in three sites in Brittany (Kernisi, Dinard, Port Laso), France, and in Kristineberg, Sweden for \u003cem\u003eZ. marina\u003c/em\u003e (Table\u0026nbsp;1). Sampling depth was 30\u0026ndash;150 cm, except for Dinard \u003cem\u003eZ. marina\u003c/em\u003e sampling (emerged at low tide). Seagrass shoots were rinsed with water to get rid of the sediment, then brought back frozen to Radboud University (The Netherlands). In the laboratory, unfrozen seagrass shoots were dissected, and leaf bundles cleaned of epiphytes reconditioned frozen and sent to the University of Li\u0026egrave;ge (Belgium) for DMSP and DMSO analysis. Complete seagrass leaf bundles were pooled into one to three sample replicates per site, of about 500 mg each (preliminary test analyses showed low organosulfur compound contents). Samples were processed for DMSP and DMSO content in a similar fashion as for \u003cem\u003eP. oceanica\u003c/em\u003e leaves (see section below).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. DMSP and DMSO analysis\u003c/h2\u003e \u003cp\u003e \u003cem\u003eP. oceanica\u003c/em\u003e dissected leaves sampled for DMSP and DMSO analysis were unfrozen, gently dried of water droplets on absorptive paper and cut in 3 mm\u003csup\u003e2\u003c/sup\u003e square fragments. In average 31 mg of fresh leaf tissues (7\u0026ndash;50 mg, according to tissue availability and expected organosulfur compound contents) were transferred to pre-weighted 20 ml glass vials for analysis (three analytical replicates by leaf sample except for years 2016\u0026ndash;2017 second sampling design and for \u003cem\u003eC. nodosa\u003c/em\u003e and \u003cem\u003eZ. marina\u003c/em\u003e, no analytical replicate; Borges and Champenois \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). DMSP and DMSO contents were measured after conversion into DMS using the headspace technique with a gas chromatograph (GC) with a flame photometric detector (FPD) (Agilent 7890A, Thermo Fisher Scientific Inc.). The temperature of the FPD was kept at 250\u0026deg;C with H\u003csub\u003e2\u003c/sub\u003e and synthetic air flows (respectively 50 and 60 ml.min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; Air Liquide Belgium). The column was a capillary column (CP-Sil 5CB, 30 m long, 0.32 mm internal diameter, 0.5 mm film thickness, CS - Chromatographie Service GmbH), the carrier gas ultrapure He (2 ml.min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; alphagas-2 grade, Air Liquide Belgium). The temperature of the oven and injection port was kept at 60\u0026deg;C. The headspace was sampled with syringes of 10\u0026ndash;500 \u0026micro;L and injected through a split-splitless injection port to the head of the column. The methodology for seagrass leaf sample preparation and DMSP(O) analysis is fully detailed in Champenois and Borges (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In brief, the method consists of first digesting \u003cem\u003eP. oceanica\u003c/em\u003e leaf fragments in 2.5 ml of NaOH (12 M; solution prepared from granular NaOH, VWR International, LLC) in the 20 ml closed vials. In the presence of NaOH, DMSP cleaves quantitatively into DMS and acrylate (Stefels \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The DMS in the vial headspace is measured by GC-FPD. The NaOH digestate is then bubbled with ambient air to evacuate the DMS and acidified with 2.5 ml of pure HCl (12 M; HCl 37 % Normapur, VWR International, LLC). The DMSO present in the digestate is reduced to DMS by adding 1 ml of TiCl\u003csub\u003e3\u003c/sub\u003e (TiCl\u003csub\u003e3\u003c/sub\u003e 30 % m/v, Merck KGaA; Stefels \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The DMS in the vial headspace is again measured by GC-FPD. Median (min-max) headspace volumes sampled for direct injection were 10 \u0026micro;l (8-500 \u0026micro;l) for DMSP, and 100 \u0026micro;l (25\u0026ndash;500 \u0026micro;l) for DMSO, respectively, all samples considered. The GC-FPD peaks of DMS were converted into DMSP and DMSO concentrations from a series of standards of known concentrations treated in the same way and at the same time as the samples. Digestate DMSP and DMSO concentrations were converted to leaf contents (\u0026micro;mol per g of leaf fresh weight, \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e). The ratio of DMSP on DMSO was computed from the measured DMSP and DMSO contents. The DMSP(O) set of individual data (averages of analytical replicates) - and temperature data - are hosted in the Mendeley Data repository (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.17632/y65hzhbfsk.1\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Data processing and statistical analysis\u003c/h2\u003e \u003cp\u003eThe spatiotemporal and compartmentalisation analysis of DMSP and DMSO consisted of linear mixed effects models (LMMs). LMMs extend traditional linear models to include a combination of fixed and random effects as predictor variables (Harrison et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Fixed effects represent variables with intercepts, means or slopes to be estimated; random effects infer the variance associated with group membership (Silk et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The model we used included depth, period and leaf class as fixed effects, and leaf section as random effect. LMM \u003cem\u003ep\u003c/em\u003e-values were computed by using Satterhwaite approximation for denominator degrees of freedom (Satterthwaite \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e1946\u003c/span\u003e). Analysis of variance (one- and two-way ANOVAs) on mean DMSP, DMSO and DMSP:DMSO ratio data for the basal section of \u003cem\u003eP. oceanica\u003c/em\u003e rank 3\u0026ndash;4 leaves were used to study the effect of year (2015-2016-2017-2018) and season (autumn, winter, spring, summer), followed by Tukey\u0026rsquo;s post-hoc comparison test (Zar \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Linear modelling (LMMs and ANOVAs) was performed on log-transformed data.\u003c/p\u003e \u003cp\u003eDMSP and DMSO contents of the maximum twelve leaf class-section combinations of the compartmentalisation study were averaged to calculate \u003cem\u003eP. oceanica\u003c/em\u003e leaf bundle values. They were also averaged to calculate six new 0\u0026ndash;20 and 20\u0026ndash;40 cm leaf class-section combinations. The leaf-class sections of 10 or 20 cm long were proportionally compared to the seagrass DMSP and DMSO content averages to determine which one best represents the whole 0\u0026ndash;40 cm leaf bundle.\u003c/p\u003e \u003cp\u003eThe linear relationship between DMSP and DMSO contents in \u003cem\u003eP. oceanica\u003c/em\u003e leaf tissues of the three sampling designs (n\u0026thinsp;=\u0026thinsp;414 data pairs, including the 129 data pairs from Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e Fig.\u0026nbsp;5A) was analysed using bootstrapped median regression. Quantile (including median) regression presents several advantages for ecological data: it is robust to outliers; avoids parametric distribution assumptions; estimates rates of change in all parts of the response variable distribution and is invariant to monotonic transformations (Koenker and Bassett \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Cade and Noon \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The R\u003csub\u003e1\u003c/sub\u003e goodness of fit of the model was measured according to Koenker and Machado (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The 0.95 prediction interval was created using quantiles 0.025 and 0.975.\u003c/p\u003e \u003cp\u003eThe relationships among response variables DMSP, DMSO or DMSP:DMSO ratio and the potential explanatory variable temperature were analysed using median regression with restricted cubic spline function and best linear fit lines. Cubic spline is essentially a piecewise cubic polynomial. Cubic polynomials have good ability to fit sharply curving shapes. Cubic spline is made to be smooth at the join points, called knots. A restricted cubic spline has the additional property that the curve is linear before the first knot and after the last knot. The number of knots used in the spline is determined by the user, but in practice five or fewer knots are sufficient (Harrell \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Gauthier et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In the present study, we used one knot as free parameter. Differences in temperature summer maxima were measured for years 2015 to 2018, with daily average values sometimes close to 28\u0026deg;C. Relationships were therefore analysed for July and August data. \u003cem\u003eP. oceanica\u003c/em\u003e tissue considered for the analysis was the basal section analysed for each sampling design (0\u0026ndash;20 cm for years 2015\u0026ndash;2016, 0\u0026ndash;10 cm for years 2016\u0026ndash;2017 and years 2017\u0026ndash;2018). In addition, July and August daily mean temperatures used in the models were values greater than or equal to their respective 75th percentiles.\u003c/p\u003e \u003cp\u003eData analysis and statistics were performed in RStudio version 1.1.383 (RStudio Team 2019), using R\u0026rsquo;s base function (R.Core Team 2020) and functions of packages \u0026lsquo;dplyr\u0026rsquo; (Wickham et al. \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u0026lsquo;tidyr\u0026rsquo; (Wickham and Henry \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u0026lsquo;lmerTest\u0026rsquo; (Kuznetsova et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), \u0026lsquo;car\u0026rsquo; (Fox and Weisberg \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u0026lsquo;agricolae\u0026rsquo; (de Mendiburu \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), \u0026lsquo;ggplot2\u0026rsquo; (Wickham \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), \u0026lsquo;quantreg\u0026rsquo; (Koenker \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and \u0026lsquo;rms\u0026rsquo; (Harrell \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Linear model assumptions (including residual distribution, variance homoscedasticity and overdispersion) and model fits were checked with diagnostic plots and tests. Statistical results are given according to Wasserstein (2019).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eAccording to the LMM analysis, DMSP and DMSO in \u003cem\u003eP. oceanica\u003c/em\u003e varied over time (DMSP: \u003cem\u003eF\u003c/em\u003e(4,202.20)\u0026thinsp;=\u0026thinsp;58.32, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;2.2 x 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e; DMSO: \u003cem\u003eF\u003c/em\u003e(4,201.53)\u0026thinsp;=\u0026thinsp;51.29, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;2.2 x 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e) and among leaf classes, i.e. leaf age (DMSP: \u003cem\u003eF\u003c/em\u003e(2,201.49)\u0026thinsp;=\u0026thinsp;69.03, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;2.2 x 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e; DMSO: \u003cem\u003eF\u003c/em\u003e(2,200.69)\u0026thinsp;=\u0026thinsp;69.47, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;2.2 x 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e). Depth also had an effect on organosulfur compound contents (DMSP: \u003cem\u003eF\u003c/em\u003e(4,201.26)\u0026thinsp;=\u0026thinsp;4.85, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0010; DMSO: \u003cem\u003eF\u003c/em\u003e(4,200.86)\u0026thinsp;=\u0026thinsp;3.02, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0190), as did the interaction between period and depth (DMSP: \u003cem\u003eF\u003c/em\u003e(16,200.89)\u0026thinsp;=\u0026thinsp;2.48, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0019; DMSO: \u003cem\u003eF\u003c/em\u003e(16,200.52)\u0026thinsp;=\u0026thinsp;4.20, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.3 x 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e). The DMSP leaf content (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) ranged from 25 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (external leaf, Sect.\u0026nbsp;10\u0026ndash;20 cm, August 2017, 10 m depth) to 167 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (external leaf, Sect.\u0026nbsp;20\u0026ndash;30 cm, February 2018, 15 m depth), for an average value of 78\u0026thinsp;\u0026plusmn;\u0026thinsp;26 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation [SD], n\u0026thinsp;=\u0026thinsp;230). The DMSO leaf content (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) ranged from 0.9 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (external leaf, Sect.\u0026nbsp;0\u0026ndash;10 cm, August 2018, 15 m depth) to 7.1 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (internal leaf, Sect.\u0026nbsp;0\u0026ndash;10 cm, August 2017, 30 m depth), for an average value of 3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;230). Overall, the DMSP leaf content was higher in February compared to other period and increased from external to internal leaves; it was lower at intermediate 15\u0026ndash;20 m depths. This pattern for DMSP was similar for DMSO. The DMSP:DMSO ratio value (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC) ranged from 13 \u0026micro;mol:\u0026micro;mol to 52 \u0026micro;mol:\u0026micro;mol, for an average value of 25\u0026thinsp;\u0026plusmn;\u0026thinsp;7 \u0026micro;mol:\u0026micro;mol (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;230). Out of the 230 DMSP:DMSO ratio values, 59 were lower than 20 \u0026micro;mol:\u0026micro;mol, including 22 lower than 18 \u0026micro;mol:\u0026micro;mol. Averaged by factor (period, depth, leaf class), all ratio values except August 2018 were between 20 and 27 \u0026micro;mol:\u0026micro;mol.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe number of \u003cem\u003eP. oceanica\u003c/em\u003e leaf samples analysed for DMSP and DMSO according to period (5), depth (5), leaf class (3) and leaf Sect.\u0026nbsp;(4) was 230 (out of a theoretical maximum of 300; see coloured filled boxes in Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e heatmaps). Not all leaf classes and/or sections were present at each period and depth, with the exception of the basal part of intermediary and external leaves (Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Internal younger leaves were shorter than intermediary and external leaves. Internal leaves were absent at 20 m depth in November 2017 and 10 and 15 m depth in August 2018. Leaves were shorter at 30 m depth and were shorter in November after the renewal of the leaf bundle (Bay \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). The ratio of the leaf class-section DMSP and DMSO contents to the seagrass leaf bundle average contents (Suppl. Mat. Table\u0026nbsp;1) ranged, for the basal sections (0\u0026ndash;10, 10\u0026ndash;20, 0\u0026ndash;20 cm) of external leaves, between 0.77 and 0.80. It ranged between 0.98 and 1.15 for the basal sections of intermediary leaves, with the best leaf section to bundle match for the 10\u0026ndash;20 cm section (1.06 for DMSP, 0.98 for DMSO), then the 0\u0026ndash;20 cm section (1.09 for DMSP, 1.04 for DMSO).\u003c/p\u003e \u003cp\u003eDMSP and DMSO contents in the basal section (0\u0026ndash;20 cm for years 2015\u0026ndash;2016, 0\u0026ndash;10 cm for years 2016\u0026ndash;2017 and years 2017\u0026ndash;2018) of \u003cem\u003eP. oceanica\u003c/em\u003e rank 3\u0026ndash;4 leaves showed seasonal and interannual variability at all depths from 10 to 30 m (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Suppl. Mat. Figures\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA,B). The variability of DMSP and DMSO contents with depth was less, in agreement with the observations made for \u003cem\u003eP. oceanica\u003c/em\u003e 2017\u0026ndash;2018 compartmentalisation study. DMSP and DMSO contents were higher in winter, lower in summer-autumn. Of the 87 sample average values, the maximum for DMSP was measured in February 2017 at 30 m depth (233 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e; mean, n\u0026thinsp;=\u0026thinsp;2) and the minimum in May 2018 at 15 m depth (50 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e; n\u0026thinsp;=\u0026thinsp;1). For DMSO, the maximum was measured in February 2017 at 20 m depth (12.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e; mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;3) and the minimum in July 2016 at 10 m depth (1.5 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e; mean, n\u0026thinsp;=\u0026thinsp;2). The minimum (14.6 \u0026micro;mol:\u0026micro;mol; mean, n\u0026thinsp;=\u0026thinsp;2) and maximum (55.9 \u0026micro;mol:\u0026micro;mol; mean, n\u0026thinsp;=\u0026thinsp;2) of the DMSP:DMSO ratio were observed in May and July of year 2016, at depths 30 and 10 m, respectively. The DMSP:DMSO ratio value varied little compared to the DMSP and DMSO contents, and was to some extend lower in 2017 and 2018 at all depths except 30 m (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The average DMSP:DMSO ratio value of the 87 samplings performed between 10 and 30 m deep from spring 2015 to summer 2018 was 28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 \u0026micro;mol:\u0026micro;mol (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;87). The season effect on the organosulfur compounds in \u003cem\u003eP. oceanica\u003c/em\u003e rank 3\u0026ndash;4 leaf basal sections was evident when data were averaged by meteorological seasons and years, excluding the depth (DMSP: \u003cem\u003eF\u003c/em\u003e(3,80)\u0026thinsp;=\u0026thinsp;14.76, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.8 x 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e; DMSO: \u003cem\u003eF\u003c/em\u003e(3,80)\u0026thinsp;=\u0026thinsp;13.66, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.8 x 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). DMSP decreased from autumn-winter to summer. DMSO decreased from winter to summer, autumn showing transitional values. The inter-annual variability of organosulfur compound contents (DMSP: \u003cem\u003eF\u003c/em\u003e(3,80)\u0026thinsp;=\u0026thinsp;18.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.5 x 10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e, DMSO: \u003cem\u003eF\u003c/em\u003e(3,80)\u0026thinsp;=\u0026thinsp;6.77, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004) resulted, for DMSP, from differences in autumn and spring between the years 2015-16 and 2017-18; between 2015 and 2018 for DMSO. The DMSP:DMSO ratio value remained relatively constant over time, with a slight increase from winter to summer-autumn (\u003cem\u003eF\u003c/em\u003e(3,80)\u0026thinsp;=\u0026thinsp;5.06, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and inter-annual variability measured mainly between the years 2016 and 2017-18 (\u003cem\u003eF\u003c/em\u003e(3,80)\u0026thinsp;=\u0026thinsp;8.60, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.1 x 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e). These annual differences in the DMSP:DMSO ratio, when considered on a seasonal basis, resulted in systematically higher values for the year 2016 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for summer and autumn), followed by the years 2015 and 2017-18.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDMSP and DMSO contents measured in \u003cem\u003eZ. marina\u003c/em\u003e and \u003cem\u003eC. nodosa\u003c/em\u003e whole leaf bundles (Table\u0026nbsp;1) were 1 to 3 orders of magnitude lower than in \u003cem\u003eP. oceanica\u003c/em\u003e leaf samples (all leaf classes and sections of the three sampling designs combined). They varied by a factor of 7 between minimum and maximum contents for DMSP, from 0.02 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (Port Laso, France) to 0.13 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (Kernisi, France); by a factor of 15 for DMSO, from 0.04 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (Krisitneberg, Sweden) to 0.58 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e (Kernisi, France). The levels of organosulfur compounds in \u003cem\u003eC. nodosa\u003c/em\u003e were within the range of variation of the levels in \u003cem\u003eZ. marina\u003c/em\u003e. The inter-sites variability did not follow a geographical pattern.\u003c/p\u003e \u003cp\u003eOverall, the general scatterplot of DMSP and DMSO contents for all \u003cem\u003eP. oceanica\u003c/em\u003e leaf samples collected between years 2015 and 2018 showed a clear linear relationship between the two compounds (R\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.40, \u003cem\u003eF\u003c/em\u003e(1,412)\u0026thinsp;=\u0026thinsp;322.9, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;2.2 x 10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e; Suppl. Mat. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e); and similarly for \u003cem\u003eZ. marina\u003c/em\u003e and \u003cem\u003eC. nodosa\u003c/em\u003e (Suppl. Mat. Figure\u0026nbsp;5). The relationship in \u003cem\u003eP. oceanica\u003c/em\u003e was modelled from measurements performed on different sections of the different leaf classes-ranks, sampled along a depth gradient at different seasons over several years, in a non-disturbed meadow. Therefore, we argue this is representative of a \u003cem\u003eP. oceanica\u003c/em\u003e meadow in its biological/physiological complexity. The slope of the median regression was 0.035, i.e. the amount of DMSO in \u003cem\u003eP. oceanica\u003c/em\u003e leaf tissues was equivalent to 3.5 % that of DMSP.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSeawater temperatures in July and August, especially at the shallowest depth of 10 m, were up to 4\u0026deg;C higher in 2018 compared to 2016 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), most probably in response to the European 2018 heatwave (Liu et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Predictions for DMSP and DMSO contents in \u003cem\u003eP. oceanica\u003c/em\u003e intermediary leaf basal section from median regression with restricted cubic spline function was minimal for a temperature of 24.5\u0026deg;C (DMSP: \u003cem\u003eb\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e = -29.21, \u003cem\u003et\u003c/em\u003e(9) = -4.14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0025 and \u003cem\u003eb\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;20.48, \u003cem\u003et\u003c/em\u003e(9)\u0026thinsp;=\u0026thinsp;5.79, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0003; DMSO: \u003cem\u003eb\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e = -0.94, \u003cem\u003et\u003c/em\u003e(9) = -2.54, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032 and \u003cem\u003eb\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.87, \u003cem\u003et\u003c/em\u003e(9)\u0026thinsp;=\u0026thinsp;2.48, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This temperature corresponded to the average value at 10 m depth for 2016, the coldest summer water temperature recorded at that depth over the survey. The averages of July and August temperatures at 20 m depth were relatively similar between years, close to the value of 24.5\u0026deg;C. At temperatures lower (for 30 m depth) or higher (for years 2015, 2017 and 2018 at 10 m depth) corresponded higher DMSP and DMSO contents in \u003cem\u003eP. oceanica\u003c/em\u003e rank 3\u0026ndash;4 leaf basal section. \u003cem\u003eP. oceanica\u003c/em\u003e relative growth rate (d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) response to experimental warming, fitted with the temperature cardinal model with inflexion (Savva et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), mirrored DMSP and DMSO model trends. The curvature of the median regression model prediction, convex for the DMSP:DMSO ratio (DMSP: \u003cem\u003eb\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3.17, \u003cem\u003et\u003c/em\u003e(9)\u0026thinsp;=\u0026thinsp;1.11, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.294 and \u003cem\u003eb\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e = -3.01, \u003cem\u003et\u003c/em\u003e(9) = -0.85, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.420; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), showed maximum value for the depth 10 m in 2016. The increase of DMSP and DMSO contents with increasing temperature was particularly evident when considering 10 m depth data only (DMSP: \u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17.11, \u003cem\u003et\u003c/em\u003e(2)\u0026thinsp;=\u0026thinsp;5.41, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033; DMSO: \u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.17, \u003cem\u003et\u003c/em\u003e(2)\u0026thinsp;=\u0026thinsp;25.29, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0016; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). An increase in average temperature in July and August of 3\u0026deg;C corresponded to a doubling of the DMSP and DMSO contents remaining in summer (i.e. at the end of the autumn/winter to summer seasonal decrease of molecule contents in leaves). The trend for the DMSP:DMSO ratio (\u003cem\u003eb\u003c/em\u003e = -7.21, \u003cem\u003et\u003c/em\u003e(2) = -3.05, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.093; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) was opposite to that of the individual organosulfur compounds. The opposite slopes and curvatures of the models meant that the decrease in DMSO from recorded temperature extrema to 24.5\u0026deg;C was greater than that of DMSP.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study confirms that \u003cem\u003eP. oceanica\u003c/em\u003e is a top producer of DMSP and DMSO among marine photoautotrophs, with leaf contents ranging from 25 to 265 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e for DMSP and from 1.0 to 13.9 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e for DMSO. This observation was in line with recent research on that species (Borges and Champenois \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Champenois and Borges \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). High DMSP contents, of the same order of magnitude as in \u003cem\u003eP. oceanica\u003c/em\u003e, were reported in Chlorophyta, mainly of the genus \u003cem\u003eUlva\u003c/em\u003e with up to 128 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e in \u003cem\u003eU. lactuca\u003c/em\u003e (Van Alstyne and Puglisi 2007; Van Alstyne et al. 2007); and for DMSO, up to 16.7 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e in natural marine phytoplankton communities from warm waters (Sim\u0026oacute; and Vila-Costa \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The scientific literature on DMSP in seagrasses is scarce; so far, inexistent for DMSO. DMSP measured in the epiphyte-leaf complex of \u003cem\u003eH. wrightii\u003c/em\u003e, \u003cem\u003eS. filiforme\u003c/em\u003e (Dacey et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) and \u003cem\u003eZ. marina\u003c/em\u003e (White \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e1982\u003c/span\u003e) was very low compared to \u003cem\u003eP. oceanica\u003c/em\u003e (\u0026le;\u0026thinsp;3.3 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e, after transformation from dry to fresh weight content for \u003cem\u003eZ. marina\u003c/em\u003e, considering a moisture content of 75 %); and the production of DMSP by non-epiphytized leaves was two to three orders of magnitude lower in \u003cem\u003eT. testudinum\u003c/em\u003e (0.18, 0.21 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e ; Dacey et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) and \u003cem\u003eZ. noltei\u003c/em\u003e (0.14 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e ; Jonkers et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) than in \u003cem\u003eP. oceanica\u003c/em\u003e. This difference in DMSP content with \u003cem\u003eP. oceanica\u003c/em\u003e was similar for \u003cem\u003eC. nodosa\u003c/em\u003e (0.07 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e) and \u003cem\u003eZ. marina\u003c/em\u003e (0.02\u0026ndash;0.12 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e) leaf bundles in the present study; and DMSO content differed by one order of magnitude in average for \u003cem\u003eC. nodosa\u003c/em\u003e (0.25 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e) and \u003cem\u003eZ. marina\u003c/em\u003e (0.04\u0026ndash;0.39 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e). High DMSP(O) production may therefore not be a general characteristic shared among seagrasses, as previously reported for Chlorophyta (Van Alstyne 2008). The amount of DMSO relative to that of DMSP in \u003cem\u003eP. oceanica\u003c/em\u003e leaf tissues was 3.5 %. This value was similar to that of 3.8 % previously reported by Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) on their reduced dataset (less than one third of the present dataset) and to that of 1.6-4.0 % reported by Husband and Kiene (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) for \u003cem\u003eS. alterniflora\u003c/em\u003e. DMSP and DMSO contents were also correlated in \u003cem\u003eC. nodosa\u003c/em\u003e and \u003cem\u003eZ. marina\u003c/em\u003e confirming the finding of Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) that DMSP and DMSO are correlated in marine autotrophs (phytoplankton, macroalgae, magnoliophytes).\u003c/p\u003e \u003cp\u003eHigher DMSP and DMSO contents in young leaf tissues decreased continuously with the growing cycle, which was the aging of the leaf bundle. This seasonal feature, reported by Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) for \u003cem\u003eP. oceanica\u003c/em\u003e third (rank 3) leaves was confirmed in the present study, regardless of the year, depth or leaf tissue. Contents of photosynthetic pigments that are essential compounds in photoautotrophs also decrease with leaf tissue aging in seagrasses, e.g. \u003cem\u003eT. testudinum\u003c/em\u003e (Enr\u0026iacute;quez et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Several processes can explain this decrease in organosulfur compound contents: young leaf tissues benefit from an initial stock of molecules that decreases (dilution and metabolism) with aging; leaves produce these compounds continuously but at a rate too low to compensate for their dilution and metabolism; minimum contents in late summer early autumn prior annual renewal of the leaf bundle result from translocalisation and recycling of essential elements including S through rhizomes from old, senescent, decaying adult leaves. \u003cem\u003eS. alterniflora\u003c/em\u003e is the largest DMSP producer among \u003cem\u003eSpartina\u003c/em\u003e species (Otte et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Rousseau et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and the second among coastal higher plants after \u003cem\u003eP. oceanica\u003c/em\u003e. In \u003cem\u003eP. oceanica\u003c/em\u003e, the plant size, age and biomass are directly related. The production of DMSP and DMSO decreases with aging, therefore with the increase of biomass. The experimental stimulation with nitrogen supply of \u003cem\u003eS. alterniflora\u003c/em\u003e biomass production led to the dilution of DMSP content (Otte and Morris \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Of the hypotheses listed above for \u003cem\u003eP. oceanica\u003c/em\u003e, DMSP and DMSO dilution with biomass increase was more likely to occur. Finally, results of the present study showed that intermediary leaves (rank 3\u0026ndash;4; i.e. inserted between the recently grown internal leaves [rank 1\u0026ndash;2] and the oldest external ones, possibly senescent and ready to fall [rank 5\u0026ndash;6, for an average number of 6 leaves per \u003cem\u003eP. oceanica\u003c/em\u003e bundle]), with an organosulfur molecule content similar to the average value calculated for the seagrass leaf bundle, appeared to be the best choice of sample material to study DMSP and DMSO in that species. Observations from this study and previous work (Romero et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Luy et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Richir et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) therefore justify the election of intermediary, rank 3\u0026ndash;4 leaves as representative tissue to study the plant biology. In addition, sampling only intermediary leaves above their meristem is non-destructive and allows for plant survival (Gobert et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTemperature could play a (indirect) role in the observed seasonal trends of DMSP and DMSO contents in \u003cem\u003eP. oceanica\u003c/em\u003e leaf tissues. There is little/no data to our best knowledge on the relationship between DMSP and DMSO production in marine coastal higher plants and temperature, except in Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These authors reported weak to modest relationships of \u003cem\u003eP. oceanica\u003c/em\u003e leaf organosulfur compound contents with temperature. In algae, the negative relationship between DMSP content and temperature (Karsten et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Lyons et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) suggested a cryoprotectant function (reviews on DMSP functions in: Otte et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Stefels et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Van.Alstyne \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Such a function is unlikely in \u003cem\u003eP. oceanica\u003c/em\u003e because that species, endemic of the Mediterranean, grows in temperate environmental conditions (Boudouresque and Meinesz \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1982\u003c/span\u003e) and must not cope with cold water temperatures but with global warming (Duarte et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Darmaraki et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Average DMSP and DMSO contents according to the year and depth in July-August were the lowest for a narrow range of temperature, between 23.5\u0026ndash;25.5\u0026deg;C. Temperatures lower (for 30 m depth) or higher (for years 2015, 2017 and 2018 at 10 m depth) corresponded with higher summer average DMSP and DMSO contents. Hendriks et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) experimentally tested the effect of light availability and warm temperature (29\u0026ndash;30\u0026deg;C) on \u003cem\u003eP. oceanica\u003c/em\u003e growth and photosynthetic activity. Temperature had a negative effect on growth. Low light availability also negatively affected photosynthetic performance. DMSP and DMSO contents in \u003cem\u003eP. oceanica\u003c/em\u003e seemed, like in \u003cem\u003eS. alterniflora\u003c/em\u003e (Otte and Morris \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), to be related to the growth and biomass production of the plant (dilution and resource allocation). Considering that organosulfur compound contents would decrease as a result of improved plant growth under optimal environmental conditions, the relationships modelled in the present study reflected the negative impact of higher temperature on the plant biomass production at low depth (10 m) and the combined negative effect of low light availability but positive effect of increased temperature on biomass production in deeper water (30 m). In addition, the relative growth rate response of \u003cem\u003eP. oceanica\u003c/em\u003e to experimental warming modelled in Saava et al. (2018) mirrored the relationships between DMSP and DMSO summer contents with temperature. Based on these observations, the next work should focus on the direct effect of primary production in contrasted environmental conditions on the contents of DMSP and DMSO.\u003c/p\u003e \u003cp\u003eThe trend for the DMSP:DMSO ratio in relation to summer temperature, depending on the year and depth, was opposite to that of the organosulfur compounds, with maximum at 24.5\u0026deg;C and a decrease towards recorded temperature extrema. DMSP, DMSO, DMS, acrylate and methane-sulfinic acid constitute a cascade reaction system against oxidative stress in the algal cell (Sunda et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Deschaseaux et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In yellowing (senescence) and herbicide treated \u003cem\u003eS. alterniflora\u003c/em\u003e (Husband and Kiene \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Husband et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and in cordgrasses collected from areas affected by sudden dieback, grazing and wrack deposition (McFarlin and Alber \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), DMSP was converted to its oxidation product DMSO resulting in a lower DMSP:DMSO ratio (published as DMSO:DMSP ratio by the authors) compared to healthy unstressed plants. Conversely, at environmental optima (e.g. light and temperature), \u003cem\u003eP. oceanica\u003c/em\u003e biomass production would be maximum, its physiological status globally very good, and the higher DMSP:DMSO ratio value an indicator of this overall good health status (corresponding to maximum growth rate; Savva et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The average DMSP:DMSO ratio value of 28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 \u0026micro;mol:\u0026micro;mol in \u003cem\u003eP. oceanica\u003c/em\u003e basal section of rank 3\u0026ndash;4 leaves (min\u0026thinsp;=\u0026thinsp;14.6 \u0026micro;mol:\u0026micro;mol, max\u0026thinsp;=\u0026thinsp;55.9 \u0026micro;mol:\u0026micro;mol) was close to that of 29.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0 \u0026micro;mol:\u0026micro;mol reported by Richir et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Just as the DMSP and DMSO contents of healthy \u003cem\u003eZ. marina\u003c/em\u003e and \u003cem\u003eC. nodosa\u003c/em\u003e leaf bundles were low compared to \u003cem\u003eP. oceanica\u003c/em\u003e, so were their ratios. In different marine algal taxa grown under axenic conditions and used for DMSO reduction studies, Spiese et al. (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) reported DMSP\u003csub\u003ep\u003c/sub\u003e:DMSO\u003csub\u003ep\u003c/sub\u003e (\u003csub\u003ep\u003c/sub\u003e for particulate) ratios (published as DMSO\u003csub\u003ep\u003c/sub\u003e:DMSP\u003csub\u003ep\u003c/sub\u003e ratio by the authors) varying by four order of magnitude, from 3.3 for \u003cem\u003eThalassiosira oceanica\u003c/em\u003e to 1,870 for \u003cem\u003eIsochrysis galbana\u003c/em\u003e. In response to salinity stress, the DMSP\u003csub\u003ep\u003c/sub\u003e:DMSO\u003csub\u003ep\u003c/sub\u003e ratio increased in laboratory batch cultures of the two phytoplankton species \u003cem\u003ePhaeocystis globosa\u003c/em\u003e and \u003cem\u003eHeterocapsa triquetra\u003c/em\u003e (Speeckaert et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); and in Fe-limited \u003cem\u003eT. oceanica\u003c/em\u003e phytoplanktonic cells, the higher DMSP\u003csub\u003ep\u003c/sub\u003e:DMSO\u003csub\u003ep\u003c/sub\u003e ratio relative to Fe-sufficient cells was explained by the net loss of DMSO via its enzymatic reduction to more lipophilic DMS (Bucciarelli et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The evolution of DMSP and DMSO levels, and thus their ratio in marine primary producers exposed to environmental stresses, and the relevance of its use as a stress indicator therefore requires a thorough knowledge of the production-transformation kinetics of these compounds, specific to the species and the stressor.\u003c/p\u003e \u003cp\u003eInter-annual variations of DMSP, at 10 m depth (and shallower) where the temperature can reach and exceed the physiological maximum of \u003cem\u003eP. oceanica\u003c/em\u003e might indicate that the organosulfur compound contents were directly involved in the response of the plant to heat-stress. Stress, including heat-stress leads to the enhanced accumulation of toxic compounds in cells, among them reactive oxygen species (ROS; Suzuki and Mittler \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Kotak et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) efficiently scavenged by DMSP and DMSO (Sunda et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). McLenon and DiTulino (2012) experimentally observed an increase of DMSP concentration in \u003cem\u003eSymbiodinium\u003c/em\u003e cells isolated from the cnidarian \u003cem\u003eAcacia pulchella\u003c/em\u003e when maintained at 33\u0026deg;C, suggesting an antioxidant function of DMSP under temperature-induced oxidative stress. Experimental temperature increase had, in contrast, no or little effect on antioxidant capacity and DMSP concentrations in \u003cem\u003eSymbiodinium\u003c/em\u003e cells and their host sea anemone \u003cem\u003eEntacmaea quadricolor\u003c/em\u003e (Deschaseaux et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). An end of century temperature scenario (23\u0026deg;C) had no significant effects on the concentrations of DMSP and DMS in \u003cem\u003eAmphidinium carterae\u003c/em\u003e cultured dinoflagellates (Li et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, two ecotypes of the terrestrial plant \u003cem\u003eArundo donax\u003c/em\u003e from warm sub-humid (Central Italy) and hot semi-arid (Morocco) habitats - existing environmental scenarios - showed differences in DMSP leaf content, with DMSP (and isoprene) increase under the moderate stress conditions of the second habitat (Haworth et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These observations, different but not contradictory (no DMSP decrease), seem to indicate a potential direct link between heat stress, ROS and the dynamics of DMSP(O) and DMS in plants and algae.\u003c/p\u003e \u003cp\u003eDMSP content in seagrasses could be explored in relation to phylogenetic history. In cordgrasses of the genus \u003cem\u003eSpartina\u003c/em\u003e, the physiological ability to biosynthesize DMSP was explained phylogenetically (Rousseau et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cem\u003eP. oceanica\u003c/em\u003e and \u003cem\u003eT. testudinum\u003c/em\u003e belong to two different lineages, respectively the Posidoniaceae/Zosteraceae and the Marine Hydrocharitaceae viz. Enhalus/Thalassia (according to the revised classification of Dilipan et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); but their belonging to different lineages is probably not the explanation for the measured differences in leaf DMSP production. Indeed, low DMSP content was measured in \u003cem\u003eZ. marina\u003c/em\u003e (0.04\u0026ndash;0.39 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e) and \u003cem\u003eZ. noltei\u003c/em\u003e (0.14 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e; Jonkers et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), two species that belong like \u003cem\u003eP. oceanica\u003c/em\u003e, to the Posidoniaceae/Zosteraceae lineage. Another useful method of categorizing seagrasses is on the basis of their growth forms, from small plants with thin leaves (e.g. \u003cem\u003eHalodule\u003c/em\u003e) to large plants with thick leaves (e.g. \u003cem\u003ePosidonia\u003c/em\u003e). This seagrass functional form model proposed by Walker et al. (\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) is ultimately related to seagrass rhizome turnover: rapid rhizome turnover in the smaller seagrass genera and slower turnover of persistent rhizomes in the larger seagrasses. Consistent with rhizome turnover rate is leaf turnover rate, more rapid in smaller seagrasses than in larger species (Duarte \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Duarte and Chiscano \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Walker et al. \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). The two \u003cem\u003eZostera\u003c/em\u003e species share with \u003cem\u003eT. testudinum\u003c/em\u003e (and to a lesser extend with \u003cem\u003eC. nodosa\u003c/em\u003e) a rapid turnover rate of their tissues when compared to \u003cem\u003eP. oceanica\u003c/em\u003e (Duarte \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Duarte and Chiscano \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Slower turnover rates allow higher buildup of secondary compounds including predator deterrents, thus reducing palatability to grazers (Walker et al. \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). High secondary metabolite DMSP production by the slow-turnover species \u003cem\u003eP. oceanica\u003c/em\u003e has been proposed as a protective mechanism against grazing (Richir et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Borges and Champenois, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGrazing plays a central role in seagrass ecology (Heck and Valentine \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Valentine and Duffy \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Depending on time and location, between \u0026sim;3 % and 100 % of seagrass net primary production enters food webs via the grazing pathway (Heck and Valentine \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). As an example, 50 % to 100 % of the aboveground biomass of \u003cem\u003eT. testudinum\u003c/em\u003e can be consumed by the purple urchin \u003cem\u003eLytechinus variegates\u003c/em\u003e (Valentine and Heck \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) and 40 % to 70 % of \u003cem\u003eP. oceanica\u003c/em\u003e leaf production can be grazed by the herbivorous fish \u003cem\u003eSarpa salpa\u003c/em\u003e (Tomas et al. \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Prado et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Peirano et al. (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) reported - for the three main grazers of \u003cem\u003eP. oceanica\u003c/em\u003e - a maximum grazing on leaves in September and June for \u003cem\u003eS. salpa\u003c/em\u003e, in March for the urchin \u003cem\u003eParacentrotus lividus\u003c/em\u003e, whereas it was irregular for the isopods \u003cem\u003eIdotea\u003c/em\u003e spp.; and Tomas et al. (\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) observed abundant \u003cem\u003eS. salpa\u003c/em\u003e grazing marks (\u0026gt;\u0026thinsp;55 % of collected shoots) all year round, and higher \u003cem\u003eP. lividus\u003c/em\u003e bites in winter/spring. Grazing pressure, which may be seasonal depending on the herbivorous behaviour of the species, occurs throughout the annual growth cycle of the seagrass. Verg\u0026eacute;s et al. (\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) experimentally showed that organic extracts of \u003cem\u003eP. oceanica\u003c/em\u003e (secondary metabolites, including phenolics) deterred grazers from feeding. However, it is worth to say that seagrass deterrence response to grazers is not unique, with grazer identity and density, and seagrass species and leaf tissue all playing important roles in deterrent production (Steele and Valentine \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Herbivory on seagrasses is an important process whose potential effect on the production of the secondary metabolites DMSP and DMSO remains to be investigated; especially considering the grazer deterrent function of DMSP and its cleavage products (DMS, acrylic acid) discussed in other marine photoautotrophs (Van.Alstyne and Houser \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Otte et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Fredrickson and Strom \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA common trait to seagrasses is the need of osmoregulation in seawater. Seagrasses have developed several strategies for osmoregulation (Papenbrock \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) including the synthesis of compatible osmolytes. DMSP is a compatible osmolyte used for osmoregulation by macro-algae and micro-algae (Stefels et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), that can be advantageous in oligotrophic environments (e.g. Mediterranean coastal waters) compared to N containing compatible osmolytes such as betaine (Colmer et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Kocsis and Hanson \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In \u003cem\u003eP. oceanica\u003c/em\u003e, the increase of salinity leads to the synthesis of sugars and amino acids (Mar\u0026iacute;n-Guirao et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2011a\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003eb\u003c/span\u003e; Sandoval-Gil et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), but the synthesis of DMSP was not tested, which does not exclude that it could act as an osmolyte. Increased synthesis of amino acids is compatible with the one of DMSP, since in plants methionine is usually a precursor of DMSP (Kocsis and Hanson \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Bullock et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The fact that seagrasses have developed different strategies for osmoregulation is compatible with a strong variability of DMSP content among different seagrasses.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eRecent work on \u003cem\u003eP. oceanica\u003c/em\u003e and the present study demonstrated this seagrass species was the largest producer of DMSP and DMSO reported to date among coastal autotrophs, and most probably the major contributor to the dissolved DMS(P,O) pool in coastal waters of the oligotrophic Mediterranean. DMSP and DMSO production and content dynamics in \u003cem\u003eP. oceanica\u003c/em\u003e were related to the plant biology/physiology, in particular to its growth cycle and productivity which varies over time (season, year) and with depth. Temperature would indirectly affect DMSP and DMSO content dynamics through direct effect on the plant biomass production, leading to the more or less rapid dilution of an initial stock of molecules concentrated in newly grown leaf tissues. Whatever the sampling conditions or the leaf tissue analysed, a notable characteristic was the constant ratio of the two molecule contents. Such a constant ratio was an indicator of a strong biochemical link between DMSP and DMSO. Now that we have a basic, in depth understanding of the natural variability of DMSP and DMSO in \u003cem\u003eP. oceanica\u003c/em\u003e leaves, future work should focus on their biosynthetic pathways and metabolism in relationship to its growth cycle and productivity. DMSP (and DMSO) physiological functions are not fully elucidated, and it may vary among coastal higher plants. Although hypothetical, grazer deterrence seems to be a likely function in \u003cem\u003eP. oceanica\u003c/em\u003e, whilst the antioxidant function - including against heat stress - will require experimental testing. Current studies on sampling location and species comparison and the analysis of experimentally stressed plants will allow responding to some of the questions raised in this work.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e (information that explains whether and by whom the research was supported)\u003c/p\u003e\n\u003cp\u003eFunding was provided by F.R.S-FNRS for salary and material, and by the STARESO via the STARECAPMED programme for fieldwork.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests\u003c/strong\u003e (include appropriate disclosures)\u003c/p\u003e\n\u003cp\u003eNo conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e (include appropriate approvals or waivers)\u003c/p\u003e\n\u003cp\u003eAuthors had all the necessary authorizations for seagrass sampling, and used a little invasive, non-destructive technique that ensures the post-regrowth of sampled tissues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e (include appropriate statements)\u003c/p\u003e\n\u003cp\u003eAll authors consent to participate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e (include appropriate statements)\u003c/p\u003e\n\u003cp\u003eAll authors and all institutions that provided funding and to which the authors belong consent to the publication of this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e (data transparency)\u003c/p\u003e\n\u003cp\u003eRaw DMSP(O) data are published alongside the paper (Mendeley Data).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e (software application or custom code)\u003c/p\u003e\n\u003cp\u003eOut of scope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e (optional: please review the submission guidelines from the journal whether statements are mandatory)\u003c/p\u003e\n\u003cp\u003eJonathan Richir: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation,\u0026nbsp;Validation,\u0026nbsp;Visualization,\u0026nbsp;Writing \u0026ndash; original draft,\u0026nbsp;Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eWilly Champenois: Conceptualization, Investigation,\u0026nbsp;Validation,\u0026nbsp;Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eJimmy de Fouw: Formal Analysis, Investigation,\u0026nbsp;Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAlberto V. Borges: Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the \u003cem\u003eFonds National de la Recherche Scientifique\u003c/em\u003e (FNRS) (Fellowship-Grant 1237018F and contract 2.4.637.10). Authors thank Pr R. Koenker from the Department of Economics, University College London, UK for his help in quantile regression. At the time of this study, J. Richir was a postdoctoral researcher at the FNRS. A. V. Borges is a research director at the FNRS. 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Pearson\u003c/span\u003e\u003c/p\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"marine-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mabi","sideBox":"Learn more about [Marine Biology](https://www.springer.com/journal/227)","snPcode":"227","submissionUrl":"https://submission.nature.com/new-submission/227/3","title":"Marine Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Posidonia oceanica, seagrass, organosulfured compounds, dimethylsulfoniopropionate (DMSP), dimethylsulfoxide (DMSO), ecology, physiology, primary production ","lastPublishedDoi":"10.21203/rs.3.rs-309046/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-309046/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe present work aims at determining the natural variability of dimethylsulfoniopropionate (DMSP) and dimethylsulfoxide (DMSO) contents in the seagrass \u003cem\u003ePosidonia oceanica\u003c/em\u003e, which is the largest producer of these molecules reported to data among coastal autotrophs. Samples were collected during a period of 3.5 years in the pristine Revellata Bay (Calvi, northwestern Corsica, France). The DMSP content ranged from 25 to 265 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e; DMSO from 1.0 to 13.9 \u0026micro;mol.g\u003csub\u003efw\u003c/sub\u003e\u003csup\u003e\u0026minus;1\u003c/sup\u003e. The dynamics of the two molecules were closely linked, the DMSO content being equivalent to 3.5 % of the DMSP content, all leaf samples considered (n\u0026thinsp;=\u0026thinsp;423 samples and 414 DMSP(O) data pairs). The annual growth cycle of the seagrass diluted the initial stocks of the two molecules. Temperature indirectly affected molecule content dynamics through their direct effect on the seagrass productivity and biomass. Inter-annual variations in DMSP(O) content in relation to shallow water temperature might further indicate that DMSP(O) could have been involved in the physiological response of \u003cem\u003eP. oceanica\u003c/em\u003e to heat-stress. Finally, middle-aged leaf tissues with an organosulfur molecule content similar to the average value calculated for the seagrass leaf bundle appeared to be the best choice of sample material to study DMSP and DMSO in that species. More research is needed to elucidate the biosynthetic pathways of these molecules in seagrasses, the evolutionary reasons for such a high production in \u003cem\u003eP. oceanica\u003c/em\u003e and the physiological functions they play.\u003c/p\u003e","manuscriptTitle":"Dimethylsulfoniopropionate and dimethylsulfoxide in Posidonia oceanica","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-09 17:50:22","doi":"10.21203/rs.3.rs-309046/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2021-08-05T06:49:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-07-25T07:27:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Marine Biology","date":"2021-07-22T09:51:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"marine-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mabi","sideBox":"Learn more about [Marine Biology](https://www.springer.com/journal/227)","snPcode":"227","submissionUrl":"https://submission.nature.com/new-submission/227/3","title":"Marine Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"05aa89c7-464b-454a-a522-6e629bde1fba","owner":[],"postedDate":"August 9th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":6328912,"name":"Marine and Freshwater Biology"}],"tags":[],"updatedAt":"2021-08-26T06:42:14+00:00","versionOfRecord":[],"versionCreatedAt":"2021-08-09 17:50:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-309046","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-309046","identity":"rs-309046","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}