Stable carbon isotopic composition of dissolved inorganic carbon (DIC) as a driving factor of aquatic plants organic matter build-up related to salinity

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Stable carbon isotopic composition of dissolved inorganic carbon (DIC) as a driving factor of aquatic plants organic matter build-up related to salinity

T

Eugeniusz Pronina,b, , Marco Panettieric,d, Kaire Torne, Cornelia Rumpelf ⁎

a

Department of Plant Ecology and Environmental Conservation, Institute of Botany, Faculty of Biology, University of Warsaw Biological and Chemical Research Centre, ul. Żwirki i Wigury 101, 02-089 Warszawa, Poland b Department of Hydrobiology, Faculty of Biology, Adam Mickiewicz University, Umultowska 89, 61-614 Poznań, Poland c INRA, AgroParisTech, UMR1402 ECOSYS, F-78850 Thiverval-Grignon, France d Biogéosciences, UMR 6282 CNRS, Université Bourgogne Franche-Comté, 6 Boulevard Gabriel, 21000 Dijon, France e Estonian Marine Institute, University of Tartu, Mäealuse 14, 12618 Tallinn, Estonia f CNRS, IEES (UMR 7618, UPMC-CNRS-INRA-IRD-UPEC), Bâtiment EGER, Aile B, 78820 Thiverval-Grignon, France

ARTICLE INFO

ABSTRACT

Keywords: Carbon isotopes geochemistry Brackish estuary Organic matter Baltic Sea Stuckenia pectinata Lignin phenols Lakes

Stable isotopes probing is among the most used methods applied in the studies of paleoenvironment. Isotope signatures of sediments are influenced by different environmental conditions such as climate, salinity, and plant coverage at the time those sediments were deposited, representing an inestimable value for paleoenvironmental reconstruction and interpretation. In this study the carbon stable isotopic composition of organic matter (δ13CORG) and lignin monophenols (δ13CVSC) extracted from this organic matter of submerged vascular plant Stuckenia pectinata (L.) Böerner 1912 syn. Potamogeton pectinatus L 1753 was investigated. Samples were collected from five different environments along a gradient of salinity from brackish Baltic Sea and freshwater lake in Estonia. The salinity influenced δ13CDIC of ambient water, in the freshwater 13C depletion was observed compare to brackish sites. S. pectinata have an intraspecific variation of the carbon stable isotope signature of organic matter depending on the environmental conditions, samples were 13C enriched in the more brackish sites. Strong positive correlation between δ13CORG and C/N ratio for both leaves and stems were found. Lignin monophenols were 13C depleted if compared with bulk organic matter, reflecting a common biochemical pattern of C fixation during lignin synthesis as for terrestrial plants. To conclude, organic matter isotopic signature and lignin composition of aquatic plants responded to environmental salinity. The innovative combination of these analyses provides a more refined interpretation of δ13CORG recorded in sediment deposited in the zones colonized by those plants.

1. Introduction Aquatic plants are an important element of very diverse aquatic ecosystems from rivers through small water bodies and lakes, to estuary and lagoon system as well as shallow parts of seas and oceans. They play many important roles in those ecosystems, e.g. they can provide shelter for associated species, which also contribute with regulation processes of organic matter and nutrient cycling. Under appropriate conditions, aquatic plants can create extensive communities covering big areas on the bottom of water bodies in which they occur. In this situation, living plants prevent resuspension of the bottom sediments, and dead plant material is in turn incorporated into the same sediments (Królikowska, 1997; Kufel and Kufel, 2002; Blindow et al., 2014 and

reference therein). The organic matter buried in the bottom sediments can provide useful information about environmental conditions at the time they were formed (Mayers and Ishiwatari, 1993; Mayers, 1994; Leng and Marshal, 2004; O'Beirne et al., 2017; Yang et al., 2017). One of the most used methods in sediment research over the last fifty years is the analysis of stable carbon isotopes in bulk organic matter and preserved remains of organisms (Herzschuh et al., 2010a,b; Woszczyk et al., 2014; Rodrigo et al., 2016; Pronin et al., 2016; Chappuis et al., 2017; Wang et al., 2017). The relative abundance of carbon stable isotopes in plant tissues is affected by different environmental conditions, operating through their impact on biological fractionation processes (Cloern et al., 2002; Leng and Marshal, 2004; Mendonça et al., 2013; Woszczyk et al., 2014; Pronin et al., 2016;

⁎ Corresponding author at: Department of Plant Ecology and Environmental Conservation, Institute of Botany, Faculty of Biology, University of Warsaw Biological and Chemical Research Centre, ul. Żwirki i Wigury 101, 02-089 Warszawa, Poland. E-mail address: [email protected] (E. Pronin).

https://doi.org/10.1016/j.ecolind.2018.12.036 Received 15 August 2018; Received in revised form 22 November 2018; Accepted 17 December 2018 1470-160X/ © 2018 Elsevier Ltd. All rights reserved.

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Chappuis et al., 2017). The stable carbon isotope composition of organic matter in vascular plants (δ13CORG) is mostly determined by their photosynthetic pathway (C3 or C4 as well as CAM plants) (Cloern et al., 2002, Mendonça et al., 2013, Chappuis et al., 2017). The source of CO2 used for the process of photosynthesis also influences the resulting δ13C of the plants at a tissue and molecular level (O’Leary, 1988; Farquhar et al., 1989). Aquatic submerged plants can use for the photosynthesis process CO2 as well as HCO3−, which is typically enriched in 13C by 8–12‰ compared to dissolved CO2 in water (Mook et al., 1974). Thus, the δ13CORG value of aquatic vascular plants is depending on the proportions of CO2 versus HCO3− used for photosynthesis that are present in the water, where plants are developing (Mendonça et al., 2013 and references therein, Pronin et al., 2016 and references therein). In the aquatic environment, there are several different factors influencing the δ13CDIC, the main biological one is the photosynthesis being simply an outcome of the plant abundance. Compact meadows with high amounts of biomass have a more significant impact on the water pools of carbon than plants growing sparsely (i.e. van Donk and van de Bund 2002; Kufel and Kufel, 2002; Pełechaty et al., 2013; Pukacz et al., 2014; Pukacz et al., 2016). Among the abiotic factors regulating δ13CDIC dynamics, precipitation and water supply in the aquatic ecosystem (groundwater, inflow, and outflows of rivers, tides, etc.) are the most relevant. Furthermore, δ13CDIC dynamics depend on the time of water exchange, which is influenced by the size of the water bodies. It is worth to mention that also the character of water (fresh, brackish or salt water) might present different δ13CDIC dynamics (Cloern et al., 2002) and different proportions between CO2 and HCO3− (i.e. Raymon and Bauer, 2000 and reference therein). Usually, the total DIC increases at higher salinity, since the latter is related to concentrations of ions in water. Taking into account these results, Fry (2002) constructed a mixing model across a salinity gradient, where δ13CDIC values increased from freshwater to salt waters. Additionally, there is no detailed study of lignin monophenols of submerged vascular plants creating lacustrine sediments. The isotopic signature of lignin phenols extracted from C3 and C4 terrestrial plants differs following the same pattern of bulk organic matter, but isotopic fractioning during lignin synthesis is responsible for depleted δ13C values of lignin as compared to bulk organic material. Indeed, monophenols extracted from C3 terrestrial plants have isotopic signature of about −30‰ or slightly higher, whereas monophenols from C4 plants have signatures ranging −17‰ or slightly lower (Goñi and Eglinton, 1996). Lignin content of aquatic plants is considerably lower than those of terrestrial vascular plants (Mayers and Ishiwatari, 1993), representing a further analytical challenge. Combining isotopic analysis on plant material, and carbon to nitrogen ratio (C/N) of the plant and sediments has been suggested by Mayers (1994) as a way to identify with higher precision the origin of sediments. This information is very useful especially in palaeoecological studies to recognize the group of plants, which contributed to the creation of lacustrine sediments. Adding further detail with compoundspecific analyses, such as the isotopic signature of the lignin monophenols, will improve the interpretation of the collected data. One of the most abundant aquatic plants worldwide is Stuckenia pectinata (L.) Böerner, which occurs in every continent with the exception of Antarctica (Kautsky, 1987, 1990; Nies and Reusch 2005; Abbasi et al., 2016). Additionally, S. pectinata was the most frequently occurring macrophyte specie in the vegetation zone in sandbanks habitat and the second most frequently occurring specie in mudflats habitats in the Estonian marine area between the years 1995 and 2015 (Torn et al., 2017). The dynamics of organic sedimentation from one of the most common aquatic vascular plants in the world may be used as a proxy for environmental monitoring of the aquatic environment. The δ13CORG of the sediments may be strongly influenced by δ13C of lignin because lignin is selectively preserved during early diagenesis (Hatcher and Clifford, 1997). Moreover, the synthesis and spatial assemblage of lignin units characteristic for different plant species may be

influenced by environmental conditions. Therefore, an important knowledge gap concerns the influence of environmental conditions, e.g. water salinity on the stable carbon isotope signature of bulk soil organic matter (δ13CORG) and lignin components (δ13CVSC). In this study, we sampled S. pectinata plant material from lake and shallow bays with contrasting salinity, in order to investigate (i) whether δ13CORG, δ13CVSC and C/N ratios of submerged vascular plant S. pectinata, reflect reproducible differences, (ii) if there are differences in δ13CORG, δ13CVSC, and C/N ratios between stems and leafs of this aquatic plant, (iii) if there are any correlations between δ13C of investigated organic matter components and salinity as well as δ13C of dissolved inorganic carbon in collected water (iv) if there are correlations between decompositions ratios based on values of C/N ratios, extracted lignin monophenols, and the δ13CORG and δ13CVSC values of steam and leaves. We hypothesized that there would be intraspecific relationships between the δ13C values of the above components and elemental composition and lignin contents resulting from the differences of salinity conditions. 2. Materials and methods 2.1. Study sites The study was carried out sampling a total of five areas: four bays of the Baltic Sea as well as in one lake located in north Estonia (Fig. 1). For isotopic analyses, a few individuals of studied species S. pectinata were sampled in the five studied areas and at three sites per study area considered as field replicates (Stuckenia stands). Altogether, the study was carried out at 15 sampling points. The investigated lake and brackish sites differed in terms of salinity, pH, water flow, catchment area and sampling depth on which the individuals of S. pectinata were collected (Table 1). 2.2. Description of Stuckenia pectinata stands Environmental samples were collected from stands dominated by S. pectinata or from stands dominated by different macrophytes, where S. pectinata was a co-occurring specie. In three studied areas (Paope Bay, Sõru Bay, Tallinn Bay) S. pectinata created dense patches, which overgrew the bottom sediments. In Maardu Lake S. pectinata co-occurred with two charophytes species: Chara rudis A. Braun in Leonh. 1864 and Chara globularis J. L. Thuiller 1799, and in Rame Bay the investigated species co-occurred also with Chara species: Chara tomentosa Linnaeus 1753 and Chara aspera Willdenow 1809. In 9 out of the 15 S. pectinata stands sampled, cover reached between 60 and 100%, whereas at 6 stands it was about 10–20% but in each case overall macrophytes cover of studied area, counting co-occurring species, was ranging from 60 to 100%. 2.3. Field sampling In July 2014, at each study site, five individuals of S. pectinata from an area of 4 m2 were collected for each identified sampling point. At the same time, water from the surrounding environment was sampled for isotopic analyses. Prior to Stuckenia sampling, the basic physical and chemical properties of the water (water temperature, and salinity) just above each studied Stuckenia patch were measured. Water samples for carbon stable isotopes analysis of DIC were collected in 10-ml glass septa test tubes and preserved with two drops of HgCl2. All Stuckenia samples were collected by diving or snorkeling in the case of the shallow stands. 2.4. Sample preparation and lignin analyses The Stuckenia samples were air-dried for 3 weeks. Gravimetric water content was checked every 3 days until the stable weight of the samples was reached. Samples were kept on paper sheets until further 231

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Fig. 1. Locations of the sampling areas in which Stuckenia pectinata stands were investigated.

treatment. The individuals of Stuckenia were then separated into leaves and stems and homogenized using agate mortar and pestle. The prepared material was transferred to Eppendorf tubes for storage until further analyses. Lignin extraction, separately for leaves and stems samples was carried out using CuO oxidation method (Hedges and Ertel, 1982). After that, the concentration of lignin monophenols was assessed following purification using solid-phase extraction (C18 columns) as suggested by Kögel and Bochter, (1985), using gas chromatography (HP GC 6890) equipped with a flame ionisation detector (GC-FID) and a SGE BPX-5 column (65.0 m × 320 μm ID, 0.25 μm film thickness, SGE, Australia). The concentration of each monophenol was calculated against standard mixtures of vanillin, acetovanillone and vanillic acid for the vanillyl (V)–type lignin units, syringaldehyde, acetosyringone, syringic acid for the syringyl (S) units, and p-coumaric acid and ferulic acid for cinnamyl (C)–type units. A sum of VSC monophenols represented the total lignin content. The acid to aldehyde mass ratios (Ac/Al)V and (Ac/Al)S, together with the mass ratios S/V and C/V were used as indicators of lignin degradation (Hedges and Ertel, 1982). The lignin extractions were performed separately for stems and leaves where possible. However, lignin extractions were not performed for Maardu Lake samples (stems and leaves), Tallinn Bay 1 (only for leaves) as well as Rame Bay 3 (only for leaves) due to the small quantity of sample collected.

Finnigan MAT 253 isotope ratio mass spectrometer (IRMS). To ensure the precision of the results, three international carbonate standards were measured in each series of samples: NBS 18, NBS 19, LSVEC. The standard errors of δ13CDIC analysis were lower than 0.2‰. Further details of the method are available in Apolinarska et al. (2016) and Pronin et al. (2016). The Stuckenia organic matter (δ13CORG), lignin monophenols 13 (δ CVSC), and water δ18O samples were analysed in Biogeochemistry Laboratory of the Institute of Ecology and Environmental Sciences Paris in France. About 1 mg of S. pectinata leaves and stems of was weighed in tin capsules for IRMS analysis. Carbon isotopes analysis of organic matter was determined using an elemental analyser (CHN NA 1500, Carlo Erba) coupled with an isotopic ratio mass spectrometer (VG Sira 10, Girardin and Mariotti, 1991). The IRMS system provides both elemental (C and N) and isotopic analysis on the same sample and the corresponding C/N ratios. Carbon isotope compositions (δ13C) were calculated as deviations of the C isotope ratio (13C/12C), from the international standard (Vienna Pee Dee Belemnite, V-PDB). The precision on the IRMS instrument was ∼0.5‰. The δ13C isotopic signature of the lignin-derived CuO oxidation products was determined using compound specific isotope analysis (Goñi and Eglinton, 1996). Samples were measured after derivatisation by BSTFA (N,O-Bis(trimethylsilyl)trifluoroacetamide) using an HP5890 gas chromatograph coupled via a combustion interface to an Isochrom III isotope ratio mass spectrometer (Micromass-GVI Optima). A volume of 0.3 ml was injected in splitless mode. The same column and injection parameters were used for the quantification of lignin with GC/FIDas described in details by Dümig et al. (2013). The precision of the analytical method is in the range of 0.2–0.8‰. We additionally performed a stable isotopic composition of oxygen in water collected from above Stuckenia stands. Water δ18O analyses were performed, as described by Epstein and Mayeda (1953), with a

2.5. The stable C isotope composition analyses of dissolved inorganic carbon (δ13CDIC) and organic matter (δ13CORG) as well as lignin monophenols (δ13CVSC) The stable C isotopes compositions of dissolved inorganic carbon (δ13CDIC) were measured at the Isotope Dating and Environment Research Laboratory in Warsaw, Poland. The δ13CDIC analyses were conducted using a GasBench-II headspace autosampler connected to a 232

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dense patches dense patches spread with dense patches of Chara species dense patches dense patches urban and forest urban forest and agricultural agricultural forest

preparatory system for equilibration (Isoprep 18, Fison) coupled to a triple collector mass spectrometer (Optima, Fison). Standard errors for δ18O analyses were checked and were lower than 0.15‰. 2.6. Statistical analyses The normal distribution of the data was checked with a ShapiroWilk’s test. Therefore, statistically significant differences were assessed by non-parametric Kruskal-Wallis’ test ran with the Dunn's multiple pairwise comparisons at a significance level p = 0.05. Analysis were performed using XLSTAT (Addinsoft, Paris, France). Spearman's rank correlation coefficient between analysed parameters were calculated and presented in a table of correlation. A first level of significance was set at p < 0.05, additionally, a Bonferroni correction was applied to correct the inflation of alpha on data distributions, setting an additional significance level p < 0.006 for Table 2 and p < 0.003 for Supplementary Material 3. Principal components analysis (PCA) was performed to visualize the distribution of environmental conditions in relation to study sites and to confirm correlations between variables found using non-parametric Spearman's rank correlation with the software CANOCO 4.5. Prior to the PCA data were standardized to avoid scale effects. 3. Results 3.1. Results of stable isotopic analyses (C and O) of water DIC, bulk organic matter and CuO extracted lignin monophenols

8.6 8.4 8.4 8.3 8.3

Description of Stuckenia pectinata community

1.2 0.4 3.0 1.2 1.0

24 22 17 20 20

0.5 4.8 5.9 6.2 6.8

The δ13CDIC values of the waters above S. pectinata stands ranged from the freshwater 13C-depleted ones collected from Maardu Lake, to the brackish 13C-depleted samples collected in Rame Bay, finishing to the slightly 13C-enriched samples collected in Tallinn Bay and near to Estonian Islands Saaremaa and Hiiumaa (Supplementary Material 1). The results of δ18O showed very similar values in all investigated stands. The highest values of δ18O was recorded in water from Rame Bay and the lowest values was recorded in water from Tallinn Bay (Supplementary Material 1). Compared to DIC, the stable isotope composition of organic matter of both stems and leaves was significantly depleted in 13C (Fig. 2, p < 0.05). The most depleted δ13C values for stems and leaves organic matter were found in Maardu Lake. On the other hand, the less 13C depleted values of stems and leafs of organic matter were found in Tallinn and Sõru Bay (Supplementary Material 1; Fig. 3). The values of δ13CVSC for stems and leaves were statistically significant depleted if compared with the δ13CDIC and δ13CORG values (Fig. 2; Kruskal-Wallis test p < 0.05). Nevertheless, we did not find statistically significant differences between stems and leaves for δ13CORG and δ13CVSC values (Fig. 2; Kruskal-Wallis test p > 0.05). The correlations between the δ13CDIC and δ13CORG values of the S. pectinata leaves and stems were presented in Table 2. A co-variation between the δ13CDIC and δ13CORG values was reflected by their high correlation coefficients (Table 2). We also found a correlation between the δ13CORG and salinity as well as between δ13CORG values of stems and leaves (Table 2). In Table 2 we also presented the values of correlation coefficients between δ13C of DIC and leaves and stems of organic matter in relation to C/N ratio and percentage coverage of S. pectinata, which were in many cases high and statistically significant. The δ13C values of extracted lignin phenols were presented as the sum of V, S and C phenols group for each replicate (Supplementary Material 1). Due to low amount of sample collected, we could not acquire data of δ13C monophenols for Maardu lake, the sampling point with the lowest salinity. The most 13C-depleted values were recorded for a sample from Tallinn Bay in both cases for leaves and stems (Supplementary Material 1). We also found few positive and significant correlations between the δ13CVSC values of leaves and stems with environmental variables (Table 2).

24.996485 24.819609 23.576719 22.425660 22.487222 59.450999 N, 59.498975 N, 58.561174 N, 58.973549 N, 58.702448 N, Maardu Lake Tallinn Bay Rame Bay Paope Bay Sõru Bay

E E E E E

Depth [m] Geographical coordinates Stand

Table 1 Selected habitat characteristics of investigated study sites.

Water temperature [°C]

Salinity [‰]

pH

Land use type nearby catchment

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Table 2 Spearman’s rank correlation coefficient table for the analysed parameters: carbon stable isotope composition of DIC (δ13CDIC) leaves organic matter (δ13CLEAVES), steams organic matters (δ13CSTEAMS), δ13C of VSC leaves and stems lignin (δ13CVSC leaves lignin and δ13CVSC stems lignin), C:N ratio of leaves and steams, salinity and S. pectinate percentage coverage. n = 15 in all cases except δ13CVSC leaves (n = 10) and δ13CVSC stems (n = 12). * indicates the statistical significance at a p < 0.05; ** indicates the statistical significance at a p < 0.006, according to Bonferroni’s correction. δ13CLEAVES 13

δ CDIC δ13CLEAVES δ13CSTEAMS δ13CVSC leaves lignins δ13CVSC steams lignins Salinity Coverage of S. pectinata C:N leaves ratio

*

0.62

δ13CSTEAMS *

0.59 0.98**

δ13CVSC leaves lignins −0.20 0.21 0.35

δ13CVSC steams lignins −0.43 0.28 0.34 0.87**

Salinity 0.34 0.88* 0.88* 0.52 0.67*

Coverage of S. pectinata *

0.52 0.88** 0.88** 0.37 0.37 0.70*

C:N leaves ratio

C:N steams ratio

0.51 0.89** 0.87** 0.66* 0.69* 0.88** 0.79**

0.60* 0.93** 0.91** 0.32 0.28 0.75** 0.92** 0.86**

Fig. 2. Boxplot represents δ13C signature of dissolved inorganic carbon (δ13CDIC), plant material (δ13CORG) of leaves and stems, and VSC lignin (δ13CVSC) of leaves and stems; n = 15 for δ13CORG and δ13CDIC, n = 12 for δ13CVSC of stems, n = 10 for δ13CVSC of leaves. Significant differences at a p < 0.05 (Kruskal-Wallis’ test with the Dunn’s multiple pairwise comparisons) are highlighted by different letters.

Principal components analysis (PCA) was performed in order to highlight the influence of analysed parameters on the samples of S. pectinata from studied areas. First and second principal components (PC1 and PC2), represented as the two axes of the plot, explained 84.4% of variance (Fig. 4). Among physicochemical properties of waters, salinity and pH well correlated, in opposite directions, with the first principal component (PC1). Moreover, percentage of coverage, C/N ratios, and carbon stable isotope compositions were also related with PC1 (Fig. 4). The PC2 was better described by depth of sampling and by δ13CVSC of leaves and stems. PCA confirmed the above mentioned strong positive correlations for salinity and δ13CDIC, δ13CORG of leaves, δ13CORG of stems and leaves. Additionally, PCA analysis confirm that δ13CDIC and δ13CORG of stems and leaves have close relationship and are related to PC1, which explain 63.5% of the total variance (Fig. 4). Regarding samples distribution within the plot, PC1 well separated Maardu Lake and Rame Bay samples, placed separately around positive values of PC1, from Paope and Sõru Bay ones, which were in turn grouped at negative values of PC1. Tallinn Bay samples were distributed close to the zero of PC1. Samples from all sampling sites except Maardu Lake were scattered along PC2. Tallinn Bay samples shifted

considerably toward positive values of PC2 if compared with the other treatments, strongly and negatively correlated with depth of sampling and δ13CVSC of leaves and stems (Fig. 4). 3.2. Relationships between salinity and other parameters The four Bay and one investigated lake differed in terms of salinity, pH, water flow, catchment area and depth on which the individuals of S. pectinata were collected (Table 1). The lowest salinity was recorded in Lake Maardu and the highest was recorded in Sõru Bay. The differences of recorded pH were very small and not exceeded 0.5 including the 0.1 error of the measurements device (Table 1). Our results concerning physicochemical parameters are similar to those recorded by Estonian Marine Institute during long-term monitoring research in this area. The highest values of C/N ratios were recorded for leaves and stems in Sõru Bay, whereas the lowest values for leaves and stems were recorded in Maardu Lake. Nevertheless, for stems in Rame Bay we also noticed comparable low values (Supplementary Material 1). 234

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Fig. 3. Boxplot represents δ13C signature plant material (δ13CORG) of stems and leaves along salinity gradient. The recorded differences were tested using KruskalWallis’ test with the Dunn's multiple pairwise comparisons with Bonferroni’s corrections and were not statistically significant.

Fig. 4. Principal components analysis (PCA) of environmental conditions distribution in relation to study sites.

3.3. The content of extracted lignin phenols and the ratio of particular phenols indicating the decomposition processes

The highest values of V and S phenols were recorded in Paope Bay and Rame Bay (sampling areas with the intermediate salinity), the lowest ones in Tallinn Bay (sampling area with the lowest salinity excluding Maardu Lake) and Sõru Bay (sampling area with the highest salinity, Supplementary Material 2). For C phenols we found the highest values for leaves in Paope Bay and for stems in Sõru Bay, whereas the lowest ones were recorded in Tallinn Bay (Supplementary Material 2). The highest content of VSCLEAVES was recorded in Paope Bay, whereas

The values of extracted lignin phenols were present as the sum of V, S and C phenols group (Supplementary Material 2). As we mentioned earlier, data about lignin extraction are missing for Lake Maardu, the sampling points with the lowest salinity, due to low amount of sample collected. 235

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Fig. 5. Boxplots describing composition ratios of lignin monophenols: cinnamyl to vanillyl units (C/V), syringyl to vanillyl (S/V), and the acid to aldehyde ratios (Ac/ Al) for vanillyl and syringyl units, n = 11 for calculated ratios of stems, n = 12 for calculated ratios of leaves. Significant differences between sampling points at a p < 0.05 (Kruskal-Wallis’ test with the Dunn’s multiple pairwise comparisons) are highlighted by different letters.

the highest content of VSCSTEMS was recorded in Rame Bay. The lowest total VSC content for both leaves and stems were recorded in Tallinn Bay (Supplementary Material 2). We also calculate the C/V phenols group ratio. The highest values were recorded in Tallinn Bay for both leaves and stems, whereas the lowest ones for leaves and stems were recorded in Rame Bay (Supplementary Material 2; Fig. 5). Lastly, the highest values of S/V ratio were determined in Tallinn Bay for both leaves and stems and the lowest values for leaves and stems were recorded in Sõru Bay (Supplementary Material 2, Fig. 5). We also compared the calculated ratios separately for stems and leaves to check if there are statistically significant differences between sampling areas. We found statistically significant differences for C/V ratio of studied areas only for leaves between Tallinn and Rame Bay (Fig. 5). For S/V ratio we found statistically significant differences between Tallinn and Sõru Bay both for leaves and steams. In the case of acid to aldehyde

mass ratios (Ac/Al) of V phenols of leaves we recorded the highest values in Tallinn Bay, for stems the highest values occurred in Sõru Bay. In both cases the (Ac/Al) of V phenols group calculated ratio have the lowest values in Rame Bay (Supplementary Material 2; Fig. 5). For (Ac/ Al) of S phenols group the highest values for leaves were recorded in Rame Bay but for stems the highest values were recorded in Peope Bay. The lowest values of this ratio for leaves were recorded in Rame Bay and for stems in Sõru Bay (Supplementary Material 2; Fig. 5). For (Ac/ Al)V ratio the statistically significant differences between were found between Tallinn Bay and Rame as well as Paope Bay only for leaves. For (Ac/Al)S ratio we found statistically significant differences between Rame and Paope Bay only for leaves (Fig. 5).

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4. Discussion

environmental conditions, the proportion between water DIC components differs. Moreover, the fluctuation of physicochemical parameters in shallow lakes is faster if compared to the Baltic Sea, even if events of water eutrophication in the Baltic Sea caused by the human activity were reported (Blindow et al., 2016). Additionally, very slight differences between δ18O values from the sampling sites located in the Baltic Sea may confirm that the fluctuation of physicochemical parameters in those localizations were rather small. Torniainen et al. (2017) estimated that in the summer period the values of δ13CDIC in this region of Baltic Sea vary from −1‰ to 0‰. Mentioned results were close to our results with exception of Rame Bay were we observed 13C-depletion of DIC in water (δ13CDIC about −4.30‰). This differences might be caused by the stronger isolation of this bay form the open sea as well as by the incoming freshwater from the Uustalu river (a small artificial ditch) flowing into the Rame Bay. Comparing our results to those recorded by Herzschuh et al. (2010a) we found out comparable values of correlation coefficient between δ13CDIC and δ13CORG (r = 0.62, versus r = 0.59 for Herzschuh et al., 2010a). This result confirms that the values of δ13CORG might be strongly influenced by the values of δ13CDIC, as reported in PCA analysis.

4.1. δ13CDIC as a main influencing factors of δ13CORG of Stuckenia pectinata in different aquatic ecosystems Considering all aquatic ecosystems, the inorganic carbon contained therein is mostly present under two forms which can be used in to the photosynthesis process: CO2 and HCO3− (Smith and Walker, 1980; Keeley, 1990; Pedersen et al., 2013). In the marine environment, CO2 is usually 13C-depleted compared to other components of DIC (H2CO3, HCO3−, CO32−) by typically 8 to 12‰ (Mook et al., 1974) and this depletion is temperature-dependent. The δ13C values of CO2 are 12‰ lower than those of HCO3− at 0 °C and 8.4‰ lower at 30 °C (Mook et al., 1974). Fry (1996) assumed that under isotopic equilibrium, the cells using CO2 should have δ13C values 8 to 12‰ lower than cells using HCO3−. Thus, the δ13C values of ambient DIC depend not only on the character of an aquatic ecosystems but also on the variable in time and space, temperature, and the pH-dependent proportions of CO2, HCO3− and CO3−2 (Smith and Walker, 1980; Zhang et al., 1995). The pH values of waters in each study sites were almost equal, exceeding 8 at each site, permitting the assumption that HCO3− ions were largely the most abundant form of inorganic carbon in all waters sampled above S. pectinata stands. The mean differences between δ13CDIC and δ13CORG for all studied sites (-8.4‰) evidence that the cell plants did not reflect the isotopic equilibrium with HCO3− but were similar to the above-mentioned differences between CO2 and HCO3−. However, when we consider our sampling areas separately there are some differences, which may indicate that in the case of Maardu Lake S. pectinata may use both sources of DIC of surrounding water, more HCO3− in the case of Rame Bay and more CO2 in the case of Tallinn Bay sampling area. Those differences might also be caused by recorded differences of the surface of study sites covered by S. pectinata. In a previous study of the macroscopic algae (C. tomentosa and C. globularis) we found that the structure and depth of submerged macrophytes communities might change measured values of δ13CORG (Pronin et al., 2016; Apolinarska et al., 2016). Moreover, we also found out that in the case of values of δ13CORG leaves and stems were 13C depleted compare to values of δ13CDIC in each study sites. Observed differences of S. pectinata δ13CORG in the different sampling sites were significantly correlated to δ13CDIC of surrounding water, which confirms that the δ13CDIC was one of the main influencing factor of recorded δ13CORG. In comparison to δ13CDIC signature, δ13CORG was depleted for all sampled points. The magnitude of this depletion, identified as Δ13C, ranged between 5.08‰ in Maardu Lake to 11.74‰ in Tallinn Bay. The most 13C-depleted DIC water was in Maardu Lake but the Δ13C between DIC and leaves of S. pectinata were the lowest; this indicates that in this freshwater ecosystems the isotopic fractionation process carried out by S. pectinata discriminate against the heavier 13C isotope. The samples of Maardu Lake were collected at lower depth compared to the ones in Tallinn Bay and this probably influenced the δ13CDIC values as well as the photosynthetic process (Farquhar et al., 1989), which were probably less intense compared to Tallinn Bay. That might be caused because of the differences in the catchment of those two samplings areas. The sampling area in the case of Tallinn Bay was open without any trees, rushes and that was different compared to Maardu Lake where the shoreline was covered by a wide belt of Phragmites australis (Cav.) Trin. ex Steud. Those differences might have influence to the photosynthesis intensity due to different shadow effect. According to Cloern et al. (2002), the values of δ13CORG of submerged vascular plants recorded in the trophy gradient varied from −16‰ to − 31‰. In our study, we registered higher values of S. pectinata δ13CORG ranging from −7.8‰ to −17.1‰. Our results are similar to the largest recorded database of δ13CORG for submerged macrophytes: a study by Herzschuh et al. (2010a) regarding lakes located in the Tibetan plateau and Central Yakutia (values from −23.3‰ to +0.4‰ with the median values close to 12.1‰). Those results refer to divers lake ecosystems with pH ranges from 8 to 11, and under these

4.2. Isotopic signature (δ13CORG) of Stuckenia pectinata as an indicator of C sources in the salinity gradient of aquatic ecosystems A general trend found for this study indicated that the carbon stable isotope values of organic matter were 13C-enriched in stands with higher salinity, supported by high and statistically significant correlation between salinity and the δ13CORG values. The δ13CORG values of S. pectinata obtained for this study are similar to those reported in literature for 13C-enriched vascular macrophytes. Mendonça et al. (2013) reported an average value of −13.5‰, and in our case recorded values were even more 13C-enriched for leaves of S. pectinata (average value −11.2‰). Thus, the recorded δ13C values for organic matter were similar to those of 13C-enriched C4 plants, with δ13C values ranging from −16‰ to −10‰ (e.g. O’Leary et al., 1992; Hayes, 1993; Fry, 1996 and reference therein; Mendonça et al., 2013). In terrestrial plants, C3 plants have a lower isotopic signature of organic matter compared to C4 plants, which are 13C-enriched (O’Leary et al., 1992; Hayes, 1993; Fry, 1996 and references therein; Mendonça et al., 2013) due to a different photosynthetic pathways used for CO2 fixation. On the other hand, for aquatic plants, the carbon source (CO2 versus HCO3−) seems to be a key factor for isotopic fractionation. In a previous study the reported differences between δ13C values of organic matter for two investigated Chara species (8.28‰ in average) were similar to the difference between δ13C values of CO2 and HCO3− (Pronin et al., 2016), which ranged from 8‰ to 12‰ depending on the temperature, and reaches 9‰ in 25 °C (Mook et al., 1974). Our results indicate that salinity in addition to temperature and pH influences δ13C of aquatic plant tissues, and it should be taken into account when δ13C values are used in palaeoecological studies as an indication of the source of organic matter in sediment deposits. It is worth to mention that we also found strong positive correlation between δ13CORG and C/N ratio for both leaves and stems, which might be also very informative when we will investigate sediments with not fully decomposed S. pectinata remains. The C/N ratios of stems were two time higher than those recorded for leaves, particularly in the two areas of Paope and Sõru Bay, a common pattern reported in literature (i.e. Hicks, 1928; He et al., 2015). However, in the case of Rame Bay the recorded C/N differences between stems and leaves were much lower, this might be due to the poorer spatial and growth development of the individuals collected in the deepest sampling sites, as well as a more frequent presence of cooccurred charophytes communities (see Section 2.2). Furthermore, C/N ratios of leaves and stems reported for this study were higher than results reported for algae, which are usually < 10 (i.e. Mayers, 1994; Geider and La Roche, 2002). As shown by Mayers (1994), the C/N ratio of the costal sediments from vascular plant origin is about 15 (based on 237

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vascular plants with C/N ratio ranged from 30 to 40), whereas algae sediments have lower C/N values (< 10). So in the case of our C/N results we can assume that in most of the cases the sediments produced after S. pectinata decomposition will have C/N ratio higher than 15, but it may vary with the development status of plants, and the co-occurrence of charophytes communities, which may provide more detailed information regarding the origin of these sediments. To confirm this assumption, additionally studies on the decomposition of S. pectinata organic matter are needed.

and the flowers were not present, personal field observation). We suggest that salinity and depth of the sampling points may be co-occurring factors that have influenced the different processes of lignin synthesis in S. pectinata tissues, which was also reflected in relationships with δ13CVSC values presented on the PCA graph. However, we cannot assess which factor is the main driver of these results, and further research is needed.

4.3. δ13C of lignin monophenols as a support information to δ13CORG of Stuckenia pectinata

Bulk organic matter of S. pectinata was found to be 13C-depleted compared to δ13C values of water DIC in all the studied sites. The shift of about −8.4‰ in stable isotope composition between the mean δ13C values of water DIC and δ13C of bulk organic matter, might indicates that δ13C values of water DIC influence the proportion of CO2 versus HCO3− used for photosynthesis process of S. pectinata and can be recorded by δ13C organic matter of this species. Our data suggest that δ13C values of water DIC, influenced by the salinity of waters in the sampling area, might be the driving factor for the δ13C values of bulk organic matter. Furthermore, we also found a strong positive correlation between δ13CORG and C/N ratios for both leaves and stems. This information might be very useful to refine future researches on sediments composed by partially decomposed S. pectinata remains. Lignin monophenols were 13C depleted as compared to bulk organic matter, reflecting a common biochemical pattern of C fixation during lignin synthesis for aquatic and terrestrial plants. The slight differences of δ13C values of lignin monophenols might be related to salinity and depth of the sampling points. Those two factors may be co-occurring factors that have influenced the different biosynthetic processes of lignin in S. pectinata tissues, but at this stage we cannot ascertain which factor was the most important. To clarify our assumptions, further studies focusing on sediment created by the decomposition processes of S. pectinata organic matter are needed.

5. Conclusions

In addition to δ13CORG we extracted the lignin V, S, and C monophenols of S. pectinata and we measured their δ13C signature: a method commonly used as a proxy of organic matter synthesis and degradation for vascular plants. The δ13CVSC results showed that monophenols were statistically significant 13C-depleted compared to bulk organic matter. Our results of δ13CVSC are similar to those obtained by Goñi and Eglinton (1996) for vascular C3 plants, and also for submerged plants (Carex rostrata Stokes, 1787) and organic matter investigated by Chabbi et al. (2007). However, Chabbi et al. (2007) found several strong and statistical significant correlations between δ13C and VSC group of phenols as well as other lignin parameters like, S/V and C/V (Ac/Al)V phenols group ratios. In contrast our data showed only few negative statistically significant correlations, the most interesting between (Ac/ Al)S leaves and δ13CORG and δ13CVSC of leaves (Supplementary Material 3). On the other hand, we did not find any correlation between acid to aldehyde ratios and δ13C of bulk organic matter. Ratios of lignin compound classes, as well as the acid to aldehyde ratios are commonly used proxies for lignin characterization and to assess its degradation status. Lignin degradation requires intermediate states in which monophenols are oxidized and transformed into their acidic forms. An increase of Ac/ Al ratio is related to a more advanced process of degradation of lignin in soil organic matter and sediments (Panettieri et al., 2017; Rasse et al., 2006; Smith et al., 2010; Thevenot et al., 2010) but here we investigated only dried samples of undecomposed parts of S. pectinate and those ratios may not follow the expected trends. Additionally, our results indicated low (Ac/Al)V and (Ac/Al)S, comparable to those recorded by Smith et al. (2010) for leaf litter which was related to lignin “freshness” (not fully decomposed material). Furthermore this hypothesis is supported by results from Chabbi et al. (2007) showing that organic matter from submerged plots had lower (Ac/Al)V then those from partly submerged and forest plots because of bigger contribution of undecomposed parts of plants. The 13C-depletetion mentioned above between δ13CVSC in comparison to δ13CORG is related to different patterns of C fixation during the synthesis of polyphenols, such as lignin (Hobbie and Werner, 2004). Moreover, the higher proportion of V units in leaves than in stems is in contrast with results found for vascular plants, in which V units are more abundant in roots and shoots, rather than in leaves (Panettieri et al., 2017; Rasse et al., 2006; Thevenot et al., 2010). Tallinn Bay, the sampling points with the lowest salinity excluding Maardu Lake, evidenced a different composition in lignin polymers, favouring the incorporation of higher proportion of S and C units in comparison with the other sampling points. On the other hand, samples from Tallinn Bay showed a less evident trend towards higher Ac/Al values for V and S units in leaves, but not for stems. The highest and statistically significant differences of the (Ac/Al)V values for leaves were observed between Tallinn Bay and Rame Bay. The S. pectinata individuals in Tallinn Bay were collected from very shallow water, which might increase the development of plant (in the case of Tallinn Bay, 30–40 cm long, flowers were present, personal field observation). In Rame Bay the individuals of S. pectinata were collected from much deeper sites and these plants differ in the case of development status (the individuals were very small, not exceeded 10 cm long

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