Organic matter (OM) in reservoir sediment consists of a range of biomolecules, but their individual contribution to the biogeochemical cycling of carbon and nitrogen nutrients is not documented. This work proposes to investigate whether the nature of the OM determines its accessibility in lacustrine sediment matrix.
Materials and methods
We adapted an OM chemical sequential method developed for soils (particle size ≤ 20 μm) for use on sediments collected from four reservoirs (particle size ≤ 2 mm), coupled with a carbon and nitrogen elementary analysis and colorimetric quantification.
This method allowed for the extraction of more than 70% of carbon and 61% of nitrogen. This OM includes exchangeable, extractable, free particulate, and residual OM, whose carbon content represented < 2%, 64 to 86%, 4 to 16%, and 9 to 24%, respectively. The sum of chemically extracted biochemical molecules that recover the extracted elementary carbon and nitrogen represents the chemically extracted OM. Phenols are the main carbon contributor (55 to 60%), followed by carbohydrates and proteins (14 to 18% and 21 to 29%, respectively). Nitrogen is mainly composed of proteins, amino acids, and ammonium (46 to 56%, 20 to 34%, and 8 to 28%, respectively). Among the four reservoir sediment samples, this same trend applies to the exchangeable and extractable phases: phenols, carbohydrates, and proteins are similarly distributed along the extracted phases, whereas nitrogen, forming as ammonium, amino acids, and nitrogen oxides, exhibits specific distributions.
In reservoir sediments, the nature of the carbon does not impact its physicochemical accessibility; nitrogen material presents more varied profiles depending on its accessibility.
For lacustrine sediments, the main environmental and reuse considerations, such as methanization and microelement release, depend on the evolution in organic matter (OM) (Chen and Hur 2015; Mattei et al. 2017; Lima et al. 2007). The increase in the number of reservoirs (Zarfl et al. 2014), and therefore in the submerged areas and sediment volumes, highlights the importance of resource management (either in situ or ex situ) and moreover shows the benefit of knowing the factors that control their OM evolution, which in organo-mineral matrices is attributed to OM bioavailability based on potential degradability and accessibility.
Synthetic works on soil have demonstrated that OM degradability depends on the strength of association with the organo-mineral matrix, inducing specific accessibility, and therefore on its organization within these matrices (Lehmann and Kleber 2015; Paul 2016). The organization of the OM in organo-mineral matrices has subsequently been redefined. Many authors explain the matrix organization, from micro- to macroscale, using a multilayered structure function of the OM composition and its interactions (Kleber et al. 2007; Kögel-Knabner and Amelung 2014). These models determine the OM organization in organo-mineral matrices by its nature and the strength of its interactions (Kleber et al. 2007). Among these interactions, the following are proposed: (i) weak interactions like hydrogen, electrostatic and electric dipole moment, plus π interactions or Van der Walls interactions; (ii) hydrophobic interactions implying non-charged mineral surfaces and/or nonpolar OM groups; (iii) strong interactions such as ionic interactions, including complexation phenomena (Wershaw 1993; Kögel-Knabner and Amelung 2014; Paul 2016). The type of these interactions determines the OM arrangement in organo-mineral matrices. Direct interactions between the OM and the various mineral surfaces are associated with ionic or hydrophobic mechanism interactions, which depend on the mineral composition. Short-distanced mineral organizations are mainly due to hydrophobic interactions, as caused by (i) hydrophobic, high molecular weight compounds in soils and sediments (Wershaw 1993; Kerré et al. 2016); and (ii) lipids of biological origin (Zocatelli et al. 2012), which present a high residence time, thus suggesting their role in OM stabilization. A longer mineral organization form determines the potentially accessible OM arrangement and implies ionic bonds (including divalent cation bonding) along with weak interactions (Wershaw 1993; Kleber et al. 2007).
The models mainly focus on carboned organic matter (COM) and not on nitrogenous organic matter (NOM). The distribution and dynamics of the various nitrogen forms in soil and sediment have been poorly documented and understood, despite the increasing level of interest. Nitrogen is usually considered easy to measure overall and interpreted using the elemental C/N ratio as a main factor of OM catabolism (Roudaut et al. 2011; Fanin et al. 2013). However, in organo-mineral matrices, nitrogen compounds display a specific reactivity that depends on their nature. Amino acid and proteins, which present functional groups with several properties, imply strong selective interactions with the mineral surface and are capable of generating a covalent reaction such as glycation (Maillard reaction between NH4+ group from an amino acid, protein with tannin, phenol or sugar), whereas mineral nitrogen (NH4+, NOx-) is known to be easily released (Quiquampoix and Burns 2007; Kögel-Knabner and Amelung 2014). This rationale supports the role of nitrogen bioaccessibility on its dynamic, which is in agreement with the Bingham and Cotrufo (2016) study showing that total nitrogen is insufficiently specific to be a pertinent indicator. In addition, in lacustrine sediment, nitrogenous molecules exhibit numerous transformation processes controlling mineralization and fixation, in constituting a complex and relatively unknown cycling (Schulten and Schnitzer 1998; Purvaja et al. 2008; Canfield et al. 2010). Lacustrine sediment does indeed present a specific and unexplained nitrogen behavior as a weak relative response of OM biodegradation to nitrogen addition; moreover, this behavior is suspected to necessitate specific storage processes (Elser et al. 2007).
Many studies have focused on quantifying OM in marine (Leong and Tanner 1999) and lacustrine sediments (Meyers and Ishiwatari 1995) or on qualifying OM in marine (Meyers and Teranes 2001) and lacustrine sediment (Belzile et al. 1997). These works have typically relied on several extractions to separate OM based on (i) physical means (sieving, densitometry) (Dorodnikov et al. 2011) and (ii) chemical means using various solvents to allow distinguishing several pools (< 3) (Belzile et al. 1997; Mikutta et al. 2006). These works usually present a basic characterization of the OM, contained in the organo-mineral matrices, generally based on C and N elementary analyses (Belzile et al. 1997; McLauchlan and Hobbie 2004). More, studies considering the OM biochemical nature apply few step fractionations of the OM only. Moreover, the spectrofluorimetric OM analysis after a few extractions does not allow determining the chemical nature of the OM within the entire sediment (Coble et al. 2014; Carstea et al. 2016). Lastly, pyrolysis methods applied directly on the whole/solid matrix can involve chemical recombination (Schulten and Schnitzer 1998).
No study however has focused on the organo-mineral interaction involving OM, such as Lopez-Sangil and Rovira (2013), which depended on eight solvent extractions. In their study, the authors developed an integrated approach to extracting and fractionating OM from soil based on an increasingly powerful chemical extractant representative of OM interaction strength. By coupling this method with carbon and nitrogen elemental analyses, they were able to determine carbon and nitrogen distribution and the C/N OM ratio based on their arrangement in the soil matrix. Nevertheless, no investigation was performed on the OM chemical structure. In addition, comparison across different studies is difficult, and the assumed selective action of solvents involved in these extractions (considered to act on pH, polarity, specific mineral modification, or specific interactions, but for the most part mixed) does not allow experimentally concluding on the type of biochemical family extracted.
The aim of the study is to observe whether the nature of the OM determines its accessibility in reservoir sediment matrix. For this, several OM fractions will be isolated according to their physicochemical accessibility with respect to the sedimentary matrix. We will apply a sequential extraction method for OM. Then the fractions will be characterized by colorimetric assays to assess the carbon and nitrogen in their qualitative and quantitative aspects.
The specificity of this work is to study a lacustrine sedimentary matrix which is less documented in the literature than on soil or on marine sediment. Moreover, the biochemical characterization by colorimetric assays is direct, without modification of the OM, compare to methods such as pyrolysis GC-MS. Thus, Schulten and Schnitzer (1998) detect organic cyclized nitrogen with pyrolysis but do not find it by the NMR method. To finish, it can be noted that the study of OM stability in organo-mineral matrices mainly concerns its carbon nature and not its nitrogen nature, since the dating methods mainly concern carbon (Amelung et al. 2008).
Materials and methods
The sediments studied during this work were sampled on four dam reservoirs in France: Charpal (CPL), Champsanglard (CSG), Saint-Pardoux (SP), and Villefort (VF). These sediments, located in the mid-mountain zone at the head of the watershed, are generally rich in OM. The general characteristics of the reservoir and the watershed of each site are shown in Supplementary data 1.
The samples were extracted during November 2017 on superficial underwater sediment, from 0 to 10 cm deep, using a shovel (CPL, CSG, VF) or an Ekman grab over a 9-m2 area (CSG). The samples were stored at 4 °C underwater until sieving (2 mm) and then analyzed. The general characteristics of these sediments, listed in Table 1, were measured according to the following methods. Loss on ignition (LOI) was conducted by placing the sediment sample, previously dried (105 °C for 24 h), in an oven at 550 °C for 2 hours. The particle size distribution was determined using a Malvern Panalytical Mastersizer 3000 laser diffraction granulometer on dry sediment rehydrated with ultrapure water (UPW). Elementary analyses of the carbon and nitrogen were performed using a ThermoFisher 2000 elementary analyzer (CHN) on solid samples, and elemental composition for elements heavier than sodium was analyzed by means of X-ray fluorescence with SPECTRO XEPOS. Carbonates were measured according to the AFNOR Standard NF ISO 10693 (X31-105). Since the carbonate count lies below the detection limit (Table 1), the carbon from carbonates does not accumulate with the carbon from OM, which allows us to consider LOI as the OM content and total carbon as organic carbon (Nakhli et al. 2019).
During this study, an OM extraction protocol, inspired by the Lopez-Sangil and Rovira (2013), has been optimized. The extraction process is applied on wet sediment, previously sieved under N2 atmosphere with a 2-mm stainless steel Gilson sieve, using a sieve shaker (Retsch AS TAP basic digit control). The OM extraction is duplicated, using a quantity of wet sediment equivalent to 10 g of dry sediment, placed in a flacon and centrifuged at 10,000 g for 15 minutes. The sequential OM extraction protocol uses different solvents while extracting OM with an increasing strength relative to the sedimentary matrix.
This protocol can be divided into two parts: (i) chemical extraction (Fig. 1, 6 steps from A to F) and (ii) physical extraction (Fig. 1, G). For each chemical extraction step, the solvent is placed into contact with the sediment and stirred using a vertical agitator at 160 rpm (first overnight and then followed with several washes). After each solvent contact, the mix is centrifuged, which yields the extracted OM dissolved in the supernatant and the residual OM in the pellet (denoted “X”). Steps E and F comprise a treatment stage followed by the same extraction routine as the other steps. The physical extraction applied to the last residue F’ relies on a densitometric step with a 1.6 density threshold.
Step A Potassium sulfate (K2SO4) 100 mL, 0.5 M—extraction overnight + two washings
Extraction of phase A, water-soluble OM based on ionic exchange and considered bioaccessible
Step B Sodium tetraborate (Na2B4O7) 120 mL, 0.1 M (pH = 9.7)—extraction overnight + three washings
Extraction of phase B, weakly linked OM and potentially mobilized by sediment microorganisms, considered to be recently adsorbed OM (in interaction with adsorption, electrostatics, H linkage, Van der Walls interactions, cationic bond strength)
Step C Sodium pyrophosphate (Na4P2O7) 120 mL, 0.1 M (pH = 10.2)—extraction overnight + three washings
Extraction of phase C, OM associated with metal cations under the chelating action of a sodium pyrophosphate reagent, which will complex with these compounds and free OM
Step D Sodium hydroxide (NaOH) 120 mL, 0.1 M (pH ~ 12)—extraction overnight + three washings
Extraction of phase D, representing a massive OM extraction
Step E Sulfuric acid (H2SO4) 20 mL, 4 °C, concentration dependent on the carbonate concentration—treatment overnight + two cleanings with 65 mL of UPW
Sodium hydroxide 120 mL, 0.1 M (pH ~ 12)—extraction overnight + three washings
Extraction of phase E, OM occluded mainly by carbonates
Step F Dithionite sodium (Na2S2O4) 20 mL, 0.1 M (pH = 8.0)—treatment overnight + two cleanings with 65 mL of UPW
Sodium hydroxide 120 mL, 0.1 M (pH ~ 12): extraction overnight + three washings
Extraction of phase F, OM linked to oxyhydroxides
Step G Sodium polytungstate (Na6O39W12) dense liquor 25 mL, density = 1.6—dispersion (sonication + stirring)
Separation of phases G and H, with phase G being the residual free particulate organic matter and phase H the residual OM
Optimization of an extraction method
Standard extractions on soils and sediments allowed us to distinguish a small number of pools. Lopez-Sangil and Rovira (2013) proposed a sequential chemical extraction method that separates OM among 8 pools. However, even though this protocol proposes a powerful OM discrimination depending on the interaction between OM and the organo-mineral matrix, it nonetheless has been developed for a soil fraction < 20 μm. Yet the OM fraction between 63 and 2000 μm is also known to contain a large proportion of OM in soils and sediments (Belzile et al. 1997; Mikutta et al. 2006; Lopez-Sangil and Rovira 2013) and moreover many studies conducted on the sediment use a 2-mm threshold. In addition, lacustrine sediments contain a significant fraction of OM from 5 to 10%, which is greater than the soil material used in the Lopez-Sangil and Rovira (2013) study, whose fraction of organic carbon ranged from 1.8 to 3.4%.
Accordingly, an adaptation of Lopez-Sangil and Rovira’s (2013) method (to be considered here as the reference protocol) is tested by virtue of (i) use of the sediment instead of soil and (ii) granulometry < 2000 μm instead of < 20 μm. The method improvement is developed on the CSG sediment sample, displaying high OM content (8% carbon) and the largest fine particle fraction (92% < 63 μm). That suggests an important part of OM associated by organo-mineral interactions in this sample and so the highest OM rates during the chemical extraction steps.
Chemical extraction optimization
The first part of this study consists of comparing the impact of conditions on the carbon chemical extraction yield. The reference protocol applied a washing time of 1 hour, with a number of washings equal to two and three for the first step and the other steps, respectively; also applied was a washing volume of 50 and 65 mL for the first step and other steps, respectively. We chose to increase the extraction rate by increasing the washing numbers, volume of solvent used, or extraction time, hence increasing the equilibrium state limited either kinetically or chemically. The extraction yields obtained (Fig. 2a) are compared to the reference method for a number of washes increased to eight (column a), a washing time increased to 3 hours (column b), and a higher washing volume due to doubling the liquid/solid ratio (column c). As expected, the modification of each parameter allowed extracting more carbon, i.e., 73 ± 1%, than the reference (52%). These results show that carbon extraction with the reference protocol seems to be limited by solvent saturation effects. It has also been noted that despite the absence of carbonates, OM was extracted during the Step E (around 20% of total carbon extracted), which means that this step is not so specific for carbonates as indicated in many studies (Olk et al. 1995).
Nevertheless, distribution of the extracted carbon per each step between phases is indeed impacted by volume, time, and number of washes. It should in particular be noticed that the longer washing time generates an overestimation of pools B and C (24 vs. 17%) and that the higher washing volume leads to overestimating pools E and F (23 vs. 14% and 17 vs. 9%, respectively). The increase in number of washings more heavily impacts the OM distribution. The extracted phases are interdependent, and the quantity of OM extracted during the first phases affects the quantity of OM extracted during the subsequent phases. To compare OM extracted across the various samples, we therefore need to establish a single protocol in order to avoid changes in extraction conditions, which in turn would modify the carbon quality and quantity extracted during the various steps (Gleyzes et al. 2002).
To better understand the impact of increasing the number of washings, the COM for each phase and each time of the 8 repeated times is as follows (Fig. 2b). The successive washes do not allow for depleting extractable OM at each step and moreover that the evolution in OM quantity extracted during each washing trends linearly. This finding highlights the nonselective processes implied during chemical extraction with a high number of washes; therefore, such a method does not serve to deduce the specific chemical interaction taking place between OM and the organo-mineral matrix.
Based on these results, we have chosen to apply a protocol with a 3-hour washing time, a volume of 100 or 120 mL, and an added washing step (3 washes during step A and 4 washes for the other steps), all of which will serve to increase the extraction yield.
Physical extraction optimization
Based on visual observation, despite the optimization of OM extraction efficiency, the presence of residual free particulate organic matter (rfPOM) has been recorded. To separate the rfPOM, a densitometric extraction step, with a 1.6 density threshold, is added to the last chemical extraction residue (F). This densitometric step, usually applied at the beginning of fractionation methods, has been performed in this case at the end of the chemical extraction to avoid perturbing the whole sediment equilibrium state, which could perturb the phase A extraction. Moreover, this fraction can also contain organo-mineral interactive OM contributing to the chemically extractable budget. The addition of a physical extraction step allows extracting 6 ± 0.5% more total carbon, thus increasing the extractable carbon from 70 ± 4 to 76 ± 4%. This step, which improves the method’s extraction yield, highlights the presence of nonchemically extractable rfPOM.
OM characterization of the fractions
Particulate OM observation
Particulate matter, with density dropping to 1.6 (step G, Fig. 1), is observed with a standard optical microscope (× 400).
Elementary analyses of the carbon and nitrogen can be carried out according to two methods: (i) use of a ThermoFisher 2000 elementary analyzer (CHN) on solid samples and (ii) use of a COT-NT Shimadzu analyzer on the liquid samples.
Biochemical OM quantification
Proteins and phenolic groups were measured by implementing Frolund’s method, in order to correct the colorimetric detection interference between the peptide bond from the protein and phenol group humic acid in a complex matrix-like biological sludge (Frølund et al. 1996). Total sugar was determined according to Dubois’ method, by hydrolyzing carbohydrate polymer in a carbohydrate monomer (with acid) followed by detecting the carbohydrate monomer with a phenol reagent (Dubois et al. 1956). Amino acids were processed using the ninhydrin method (assayed ion ammonium) after NH2 amino acid group condensation (Michel and Hannequart 1968). Analyses were conducted in triplicate. Supplementary data 2 provides the overall parameters of these colorimetric methods.
Nitrogen chemical form quantification
N-NH4+ were determined according to Hach method 8038 and French standard NF T90-015 (August 1975), using Nessler’s method, which entails the reaction, under alkaline conditions, between NH4+ and Nessler reagent to form dimercurammonium. N-NOx were measured, according to Canadian Standard MA.300-NO320, by reducing nitrates into nitrites and then measuring NOx content with total nitrite using a diazotization reagent. The analyses were duplicated; the overall parameters of these colorimetric methods are shown in Supplementary data 2.
The various compounds are expressed in mgeqC for phenols, carbohydrates, proteins, and amino acids and in mgeqN for proteins, amino acids, ammonium, and nitrogen oxide. The quantities of phenols, carbohydrates, proteins, amino acids, ammonium, and nitrogen oxide measured have been converted into an elemental carbon and/or nitrogen contribution based on their content in terms of the standards used for the quantification step. For gallic acid, glucose, bovine albumin serum, and alanine, the values in mgeqC/mg are 0.42, 0.33, 0.53, and 0.40, respectively. For gallic acid, glucose, bovine albumin serum, alanine, ammonium, and nitrate, the values in mgeqN/mg are 0.16, 0.16, 0.78, and 0.23, respectively.
3D spectrofluorimetric analysis is commonly employed to differentiate and track the evolution of dissolved OM in natural complex matrices (Coble et al. 2014; Carstea et al. 2016). This technique distinguishes OM depending on the characteristic fluorescence of the fluorophores involved. In the case of natural OM, the fluorophores involved are mainly conjugated systems and especially aromatic cycles (Coble et al. 2014).
Fluorescence emission-excitation matrices (EEMs) were acquired on dissolved OM fractions using a Shimadzu RF 5301pc luminescence spectrometer monitored by Panorama, with a 5-nm excitation wavelength increment from 220 to 400 nm and a 1-nm excitation wavelength increment from 250 to 550 nm. To obtain EEMs, a quinine sulfate solution (1 μg/L) was introduced to monitor the stability of energy emitted by the lamp, and no change was observed throughout the study. According to Chen et al. (2003), who observed only minor differences between natural dissolved OM at pH = 3.0 and pH = 8.0, OM fluorescence was measured at a unique pH = 7.0, using a 0.1-M sodium phosphate buffer (pH = 7.0) to diluted samples, until fluorescence emission intensity did not exceed 1000 AU.
Spectrofluorimetric interpretation was performed by examining the OM fluorescence intensity with a wavelength emission > 380 nm and calculated per unit of carbon. Various treatments were carried out in order to overlap results and confirm their efficiency. The EEMs were treated using 2-way component PARAFAC deconvolution, run on Matlab© using the PROGMEEF application with Rayleigh and Raman scattering limited by means of a mathematical treatment (Zepp et al. 2004) to determine the integrated intensity of components with a 380-nm emission wavelength threshold.
Results and discussion
Carbon and nitrogen elementary distribution
Carbon and nitrogen distribution
The carbon and nitrogen distribution between phases are described in Fig. 3; it highlights the quantitative composition as a function of OM interactions within the four lacustrine sediments. A major portion of both the carbon of organic matter (COM) and nitrogen of organic matter (NOM) (from 76 ± 4 to 91 ± 2% and from 65 ± 7 to 86 ± 5%, respectively) is chemically extractable from all four lacustrine sediments. It can be observed that extractable NOM is less than COM, most likely due to stronger interactions, revealing nitrogen-stabilizing processes and thus nitrogen storage. In comparison, a study on two granitic soils (Lopez-Sangil and Rovira 2013) showed a poorer extraction rate, with 67 to 71% of total carbon and 57 to 63% of total N.
Residual OM, after chemical extractions, are composed of rfPOM (phase G) and residual OM (phase H). As regards the total carbon distribution, rfPOM and residual OM represent respectively from 4 ± 0.2 to 16 ± 0.2% and from 9 ± 2 to 24 ± 3% of the total carbon, and relative to the total nitrogen distribution, these ranges extend from 3 ± 0.1 to 6 ± 0.1% and from 14 ± 3% to 35 ± 5% of the total nitrogen. These results suggest that residual OM, with high carbon and nitrogen contributions and variability (standard deviation for carbon distribution: 39%), offers a significant pathway for sediment to accumulate carbon and especially nitrogen, whose variability depends on sediment origin and/or variability in the mineral part. The rfPOM contribution to COM, i.e., about 5, 6, 4, and 18%, respectively, for CPL, CSG, SP and VF, shows a major variation, with 74% relative standard deviation. This finding can also be explained by the specificities of the site where the sediment originated.
The chemically extractable carbon and nitrogen (phases A to F), considered potentially bioavailable OM, represent a major share of total carbon and nitrogen content (from 70 ± 5 to 87 ± 2% and from 61 ± 7 to 81 ± 5%, respectively). In considering that the relative standard deviation of carbon and nitrogen distribution is around 10 and 15%, respectively, a similar distribution trend for carbon and nitrogen can be assumed between samples for the chemically extracted phases (A to F). The exchangeable OM (phase A) contributes to a minor share of carbon (from 0.9 ± 0.1 to 1.9 ± 0.1%), but its contribution in the nitrogen balance is not negligible (between 5.0 ± 0.1 and 9.6 ± 0.1%). In the study by Wang et al. (2018), applying a sequential extraction method on soil to study the nitrogenous matter of the sediment reveals the same finding, namely, the distribution of the “exchangeable,” “extractable,” and “residual” nitrogen pools (9 ± 2, 62 ± 5, and 29 ± 5%, respectively), with phase B constituting the most highly contributing phase in carbon and nitrogen (from 30 ± 1 to 43 ± 1% and from 32 ± 0.1 to 36 ± 0.3%, respectively). Phases B, C, and D, assessed as linked OM, represent a major share of the extractable OM in the sediments, contributing from 78 ± 4 to 82 ± 5% of the carbon and from 75 ± 9 to 81 ± 4% of the nitrogen.
Compared to granitic soil (Lopez-Sangil and Rovira 2013), the COM and NOM distributions present several differences, thus suggesting differences in their carbon and nitrogen dynamic. COM extracted on phases C and D is lower for soil than sediment (5 vs. 13%; 10 vs. 15%, respectively), while the NOM distribution differs between phases B, C, and D for both soils and sediments (37 vs. 24%; 8 vs. 13%; and 12 vs. 17%, respectively). In conclusion, a major share of the carbon and nitrogen is chemically extractable in all four lacustrine sediments; however, a smaller share of total nitrogen is extractable in reservoir sediment. Elementary carbon and nitrogen arrangements in the chemically extractable OM are equivalent for the fourth samples upon applying the chemical method. The solid extraction phases for particulate OM (G) and non-extractable OM (H) could be impacted by sediment origin.
Studies typically express %CLOL and %NLOL as the masses of C and N, respectively, divided per mass of extracted LOL. In our study, %CLOL and %NLOL are similar for all sediments, ranging from 46 ± 5 to 60 ± 6% and from 2.1 ± 0.4 to 4.7 ± 0.9%, respectively. These values correspond to those found in lacustrine sediment by Belzile et al. (1997). In comparison, marine sediment and soil OM display equivalent CLOL content (between 50 and 55%), yet their NLOL content differs by being higher for marine sediment (around 10%) and lower for soil (around 2%) (Rice and MacCarthy 1991; Hedges and Oades 1997). These results, according to the extractable OM C/N, support several origins with various terrestrial contributions: soil > lacustrine sediment > marine sediment.
C/N ratios of the extracted OM (presented in Supplementary data 3) show comparable values for equivalent phases of the various sediments. Phase A has a low C/N (< 5), as nitrogen content in the phase (3 to 10%), associated with labile nitrogen, suggests that nitrogen is certainly not limiting microbial activity in the sediment. The chemical composition could offer information on the behavior of nitrogen in the sediment (Qafoku and Sumner 2001). Phases B to F indicate a C/N mainly from 10 to 18, hence supporting the fact that the elementary carbon and nitrogen distribution does not depend on OM interaction type and moreover is not sufficiently index-specific. Phase G, associated with a low degraded OM, presents a high C/N and sizable variations (20, 17, 25, and 29, respectively, for CPL, CSG, SP, and VF). These results could underscore the specificity of OM in relation to different allochthonous/autochthonous OM origins. Phase H has a C/N ranging from 4 to 22; this ratio is expected to be higher according to many works on soil (Hedges and Keil 1995) that have reported an extracted OM C/N increasing with a decrease in matrix granulometry. The authors attributed a higher C/N ratio to stronger OM interactions.
C/N ratios of the various OM pools allow differentiating exchangeable OM (phase A) and residual OM from others. Furthermore, the extractable OM pools exhibit comparable (phases B to F) C/N ratios. Nevertheless, the C/N ratio alone is insufficient to determine the interaction, as are the dynamics of nitrogen and carbon in the organo-mineral matrix, as mentioned in the studies by Cabrera et al. (2005) and Bingham and Cotrufo (2016).
Indeed, different materials with the same C/N can yield a different mineralization (Rowell et al. 2001), and the correlation of nitrogen mineralization is possible with different factors but not with C/N ratio (Schjønning et al. 1999; Qafoku and Sumner 2001). In addition, this ratio does not integrate the nitrogen type and its potential biodegradability. As suggested for various soils by limiting C/N from 15 to 40, the level of biodegradation assumes the importance of nitrogen type on its accessibility and distribution (Van Kessel et al. 2000; Qian and Schoenau 2002).
OM sediment composition
Characterization of particulate OM (rfPOM)
Phase G (rfPOM) displays a significant quantitative variation depending on sample origin. This fraction is solid, and we cannot therefore use colorimetric assays for chemical characterization. We have chosen to analyze rfPOM by means of optic microcopy (×400) for the qualitative determination of the nature of the various compounds included in the four samples. The low rfPOM quantities analyzed did not enable a reliable quantitative analysis, thus preventing us from proceeding with a particle count.
The identification of rfPOM constituents has been assessed by Marchand (2003). The rfPOM, from a few μm to 2 mm, is composed for all samples by variable constituents (Fig. 4). We can distinguish the following:
Spores and pollens—possessing very different sizes and shapes
Preserved lignocellulosic fragments—variable morphology and contours of the visible structure, cell walls clear and thin, translucent cell interiors
Degraded lignocellulosic debris—generally elongated shape and major changes in structure, with thickened cell walls and orange cells
Opaque lignocellulosic debris—totally opaque, generally small, angular, and elongated without a visible structure
Jelled debris—generally small in size and polygonal in shape, structure, and color (reddish orange) highly uniform
Reddish amorphous OM—varied shape and size, nonhomogeneous shade (orange to brown)
Grayish amorphous OM—gray to opaque, flakes of various sizes with diffuse edges
Polyframboidal pyrite—opaque circular shape, composed of framboid accumulation
These observations highlight the presence and preponderance of lignocellulosic fragments, at various stages of decomposition (Fig. 4, pictures d, e, f, k, and l). These vegetal compounds, especially lignocelluloses, with a high C/N ratio (from 17 to 29) originate from terrestrial inputs (allochthons) and largely constitute the rfPOM. In addition, the presence and nature of all the spore blades might be consistent with the watershed land use mapping. The presence of grayish amorphous OM, generally resulting from the bacterial decomposition of algae matter and of aquatic species organ fragments, reveals the presence of native contributions in the sedimentary rfPOM. Also, the observation of pyrite in the superficial sediment, formed under anaerobic conditions, indicates the environmental condition of the reservoir sediment OM evolution.
The introduction of this physical fractionation step of low transformed OM, suspected to evolve quickly, offers the possibility of characterizing residual OM. The nature, quantity, and ratio of allochthon/autochthon rfPOM are seasonally dependent, and rfPOM identification allows supporting its origin (mostly allochthonous).
Characterization of chemically extracted OM
The biochemical characterization of OM, using colorimetric assays, is performed on dissolved OM from the four samples. The contribution of each compound studied, as a quantity of equivalent carbon and nitrogen extracted during each step, is provided in the supplementary data section (Supplementary data 4 and Supplementary data 6).
The chemical composition of extracted OM is calculated as a percentage of the quantity of carbon extracted, based on the colorimetric assays to the elemental analyses. The dissolved COM composition in phenols, proteins, carbohydrates, and amino acids represents, respectively, from 55 ± 2 to 60 ± 5, from 21 ± 5 to 29 ± 7, from 14 ± 1 to 18 ± 1, and less than 1 ± 0.1% of the extracted carbon. Moreover, the total quantity of extracted carbon, as measured by colorimetric assays, recovers roughly 106% of the total chemically extracted carbon measured with the COT meter (ranging from 91 ± 5 to 116 ± 13%). Consequently, these four compounds do seem to be representative of the COM composition of the sediment. To a similar extent, the elemental nitrogen contribution of the various kinds of nitrogen (proteins, amino acids, NH4+, and NOx) has been calculated based on the elementary nitrogen composition of standards used for the quantification step (i.e., bovine albumin serum, alanine, NH4+, and NO3, respectively, for proteins, amino acids, ammonium, and nitrogen oxides). As for the elemental nitrogen extracted, based on the colorimetric assays and COT-NT meter, the nitrogen recovers around 90% (from 83 ± 15 to 101 ± 15%) of the extracted nitrogen. The nitrogen forms investigated are therefore representative of the nitrogen constituting the sediment. The sediment NOM composition in proteins, amino acid, NH4+, and NOx represents respectively of the nitrogen extracted: from 46 ± 7 to 56 ± 25; from 20 ± 1 to 34 ± 2; from 8 ± 11 to 28 ± 3; and from 0.3 ± 0.2 to 2.4 ± 0.1%. However, these good material balances do not exclude the presence of other contributions, such as lipids or heterocyclic nitrogen in small quantities.
The OM compositions (carbon and nitrogen forms) in various organo-mineral matrices, as well as in marine, estuarine, (salted) lake sediment, and soil, are described in Table 2. The composition comparison is complex due to the use of different extraction (whole, alkaline, acid) and characterization methods. A study of the biochemical forms of carbon and nitrogen is mainly grasped by their hydrolysable characteristic under acidic conditions. Hence, the carbohydrate from marine, lake, and salted lake sediments equals around 20%—from 1 to 55%—of the carbon, including the content of our samples (10 ± 2%). Proteinaceous compounds contribute around 10%—from 0 to 19%—of the carbon of the same matrix as our study. Lipids represent little content (less than 10% of marine sediment carbon). It should be pointed out that a large share of carbon in the sample has not been characterized (Table 2). For nitrogen, NH4+, easily extractable and analyzed by a similar method, shows equivalent compositions among the various matrices (from 9 to 30%), which is consistent with our results. By comparing the contribution of proteinaceous compounds, they constitute for our study a much larger share of the nitrogen balance than the carbon balance, thus suggesting their major role in the nitrogen dynamic. Moreover, their contribution to the total carbon balance is seen to be lower for terrestrial environments, compared to aquatic environments; this difference can be explained by plankton contribution to the protein pool.
OM nature distribution and interaction
Description of OM nature distribution in the extraction phase from lacustrine sediments
The characterization of OM extracted in each phase allows describing the qualitative nature of the OM depending on its accessibility. The average composition, as well as the fluorescence, of the extracted OM at λemission > 380 nm for the four sediment samples is shown in Fig. 5. This figure highlights the OM composition for each phase, with each depiction representing a degree of interaction with the organo-mineral matrix.
The composition of COM is investigated in each phase by assessing its main components, expressed as a fraction of total carbon (phenol, protein, and carbohydrate), and then differentiating the phase composition using the ANOVA test (**p < 0.05). Carbohydrate yields a constant COM contribution from 6 ± 4 to 23 ± 2%. The protein contribution distinguishes phase A, with a weak contribution (from 0 ± 3 to 17 ± 13%), from the other phases, with a mean from 16 ± 3 to 26 ± 7% for phase B and gradually increasing to between 23 ± 11 and 46 ± 5% for phase F. Phenol is the major COM constituent and decreases with the strength of the interactions. Phase A has the highest phenol proportion (62 ± 4 to 94 ± 9%). Phases B and C also display high phenol content (54 ± 43 to 67 ± 5%), while the phenol content of the other phases ranges from 33 ± 5 to 63 ± 5%. These same results have been described by Gale et al. (1992) using a similar process to extract the labile phase (A) and observing a high phenol content in the OM composing this fraction. As regards OM fluorescence results, based on the PARAFAC deconvolution component, phases B and D present, for all samples, a higher fluorescence for the fluorophore located in the area λemission > 380 nm. According to the literature, this fluorescence area is correlated with polycyclic compounds; thus, the phenol extracted on phases B and D may be more polymerized than those from other phases (Chen et al. 2003; Carstea et al. 2016).
The nitrogen composition in the various phases has been studied by evaluating the mean contributions in protein, amino acid, NOx, and NH4+ to the nitrogen balance in each phase. The NOM composition differs among samples, highlighting the availability of specific species; nevertheless, the overall trend can be discussed. Phase A is composed of NH4+ (from 36 ± 0 to 75 ± 1%) and amino acids (17 ± 6 to 62 ± 2%), as per Rillig et al. (2007). These results were expected, when considering their exchangeability components; consequently, microbial activities are impacting the mineralization of protein compounds. Phase B presents the highest protein contribution (from 65 ± 8 to 88 ± 38%). The main phase C nitrogen contributors are protein (44 ± 3 to 80 ± 4%) and NH4+ (20 ± 5 to 57 ± 3%), while phase D is composed of protein (36 ± 3 to 49 ± 6%) and amino acids (51 ± 5 to 61 ± 0%). Phases E and F are characterized by major protein contributions (34 ± 5 to 82 ± 9%). Proteins are therefore better preserved from mineralization due to low microbial activity for all phases following phase A. However, the evaluation of nitrogen dynamic is complicated by a lack of knowledge on the origin of nitrogen forms present in the phase, due to their interaction potential or as a result of microbial activity. The phases containing the least mineral nitrogen in % and a major share of proteins are B, D, E, and F; the interactions involved in these phases could therefore provide a preferential protection for proteins.
NOx, only present in the last phase, is formed by NH4+ nitrification, thus suggesting the occurrence of aerobic conditions.
The biochemical composition of COM is similar across the samples, and its evolution between the phases is mainly characterized by the polymerized nature of the phenolic OM, which features a preferential “protection” with phases B and D. Sugars do not show any preferential protection, unlike proteins.
Specific interactions involving OM
The distribution of the various compounds among the phases is presented in Fig. 6, which highlights the preferential interaction (via the extraction phase) of a biochemical compound.
The mechanisms involved in the OM extraction process in organo-mineral matrices are studied below; they are generally deduced by comparing the extraction conditions, the possible reactions under these conditions, and the results of the extractions. In addition, several mechanisms can occur simultaneously and be influenced by parameters, including pH, OM ionization, dissolution of crystalline phases carrying OM, surface charge of colloidal structures, and ionic complexation.
Among the main OM components, the phenol and carbohydrate distribution among phases (Fig. 6) has an equivalent trend (r2 = 0.98, 0.97, 0.97, and 0.94, respectively, for CPL, CSG, SP, and VF). The protein correlation with phenol is less significant (r2 = 0.72, 0.64, 0.93, and 0.87 for CPL, CSG, SP, and VF, respectively), which translates the distribution variations for proteins. These molecules are subjected to a similar behavior as in the extraction process, where they are stabilized by each other and destabilizing one allows releasing the others. For example, a protein is suspected to be involved in the soil OM stabilization process (Rillig et al. 2007; Kögel-Knabner and Amelung 2014), and cyclized OM is able to encapsulate protein (Zang et al. 2000). These compounds are weakly extracted during phase A; therefore, the ionic saturation determines a negligible fraction of this OM organization and is mainly distributed in phases B, C, and D. Moreover, sugar and phenol are mostly extracted during phase B. The sequential alkalinity actually increases (pH = 7, 9.7, 10.2, and 12 for phases A, B, C, and other), which allows breaking the electrostatic bonds and enhancing the ionization of functional groups (e.g., phenolic). These modifications imply repulsive electrostatic forces between phenol and protein (pka phenol = 8 to 10, pka protein = 8 to 12.5) over the course of phase B extraction. However, for carbohydrates characterized by aldehyde (pka around 12) and alcohol (pka around 16 for secondary alcohol) functional groups, pH variation between 7 and 12 does not induce OM ionization and thus is not involved in carbohydrate extraction; also, natural sugars are known to complex with divalent metal cations (Alekseev et al. 1998). The solvents used during extraction display specific interactions. Sodium tetraborate, used during phase B, is under a boric acid form in water, and the equilibrium state between boric acid and tetrahydroxyborate with pka = 9.14 induces the principal part of the basic form during extraction. This form is notably known for complexing sugars, which can be destabilized via the bridging of polyol groups (Dijkgraaf et al. 1987; Springsteen and Wang 2002). Sodium pyrophosphate leads to high extraction content, which in turn could be attributed to the dissolution of calcic humates (Pansu and Gautheyrou 2007), based on substitution by Na+ of the Ca2+ involved in divalent bonding and calcium pyrophosphate insolubility in water precipitation.
Amino acids are specifically extracted on phase D (64 ± 14%), although these compounds raising the pkaNH4+/NH3 from 9 to 10 were therefore expected to be extracted during the previous extraction phases. We can thus hypothesize that amino acid extraction is not due to ionization phenomena, or else they would be protected by other compounds destabilized during this extraction step. The amino acid and protein arrangement processes in these matrices are associated with adsorption phenomena on crystal mineral surfaces (Nicora et al. 2013). However, in comparing the mineralogy of sediments by DRX before and after extraction results (shown in Supplementary data 8), we observe a higher crystallinity in the residual phase, thus suggesting (i) a possible amorphous phase dissolution rich in Si, Al, and metals during phase D extraction and (ii) release of amino acids adsorbed to crystalline phases attributable to the desorption processes. The first hypothesis is in agreement with studies highlighting amino acid concentrations correlated with these elements in soil and sediment (Sowden et al. 1977; Schnitzer and Kodama 1992; Wagener et al. 2015). Similarly, amino acids are involved in complexation processes with transition metals. On the other hand, the -OH ion nucleophile, present in Phase D, may easily substitute for amino acid and generates their release. All these results emphasize the behavior and therefore the varied dynamics of amino acid and protein in the sedimentary matrices. Nicora et al. (2013) showed their competition for site occupation in a controlled environment (clay + water); however, according to our results, this competition does not suggest an impact on their distribution under sedimentary conditions. In addition, the difference between their adsorption and desorption coefficients on clay surfaces, as observed by Wang and Lee (1993), suggests that electrostatic bonding is not the only mechanism involved in amino acid sorption. Specific affinities between functional groups and adsorptive surfaces may also be involved (Wang and Lee 1993; Liu and Lee 2007; Cui and van Duijneveldt 2010).
These reactions, which stabilize amino acids adsorbed in the sedimentary matrix, could generate amino acid desorption at higher pH than adsorption, according to Cui and van Duijneveldt (2010), who observed polymer desorption based on amine interactions at pH > 10.3. This finding could explain the absence of amino acid extraction in phases B and C (pH = 9.7 and 10.2, respectively), along with the massive amino acid extraction in Phase D (pH = 12). Proteins may be involved in such direct ionic adsorption on the mineral fraction since, as observed previously, their rate is greater during the phase D extraction than that of either carbohydrate or phenol. Proteins do indeed have amino functions on the side chains of some amino acids (lysine and arginine with pkas values of 10.5 and 12.5, respectively).
Ammonium is a small, monovalent cation known for its exchangeable nature and used as an anion for sequential extractions (Bremner and Shaw 1954) and for the determination of cationic exchange capacity. During phase A, ionic saturation allows extracting a significant proportion of NH4+, according to Rillig et al. (2007), which can be associated with exchangeable NH4+ (34 ± 14%), i.e., higher than the soil count at around 25% (Schulten and Schnitzer 1998). Moreover, ammonium with a pka = 9.2 was expected to be mainly extracted during both phase A (exchangeable) and phase B (pH 9.7) for the “fixed” NH4+. Yet it can be observed that phase B extracts little NH4+, which implies specific stabilization mechanisms, according to the main extraction during phase C (41 ± 15%). Phase C extraction, using sodium pyrophosphate, seems to specifically extract ammonium, which might be due to complexation or precipitation with the combined action of substitution by Na+ and water insolubility of ammonium pyrophosphate, complexed with divalent cations under these conditions (temperature = 25 °C; pH = 10.2) as struvite (Stratful et al. 2001). Moreover, under ammonium assay with Nessler reagent (pH > 13), struvite is decomposed, releasingNH4+ and enabling its measurement (Ortueta et al. 2015; Kim et al. 2016). This behavior confirms and completes the observation by Bremner and Lees (1949), with a high extraction yield of nitrogen by pyrophosphate. NH4+ is able to generate numerous reactions involving, for example, aromatic compounds like phenols, quinones (Flaig et al. 1975; Schnitzer 1991), or amino acids, such as glutamate forming glutamine (Schulten and Schnitzer 1998). These reactions could explain the lower extraction rate by sodium tetraborate, as well as the pH difference (10.2 and 9.7, respectively).
Lastly, the NOx distribution in the various phases highlights the distribution of a major portion of this pool of material, for all samples, in phase F (Fig. 6). This extraction is correlated with a reduction reaction, which would suggest that NOx associated with metal oxides (Fe, Mn) must be stable (Leinweber and Schulten 2000; Wagener et al. 2015). NOx is easily leached (more mobile than NH4+) and assumed to be reduced into N2 or NH4+ under anaerobic conditions. This finding suggests that microorganisms cannot reduce NOx trapped by metal oxide, which seems to constitute a strong means for stabilizing nitrogen in sediments (Schulten and Schnitzer 1998).
In addition to these mechanisms, numerous works have highlighted the important role played by the OM fraction on the remainder of the OM. This OM generates a matrix favorable to adsorption, encapsulation, and occlusion processes based on various interactions (Knicker and Hatcher 1997; Zang et al. 2000; Keiluweit and Kleber 2009).
The distribution of the various biochemical compounds by extraction phase is in agreement with the extraction mechanisms mentioned in the study by Lopez-Sangil and Rovira (2013). However, our results take into consideration a contribution of complexation mechanisms with tetrahydroxyborate in the extraction processes (in addition to those already mentioned), as well as the possible precipitation of Ca2+ and NH4+ with pyrophosphate. “Massive extraction” in phase D is likely to be caused by the nucleophilic nature of -OH ions and/or the dissolution of amorphous phases.
A sequential method for extracting four reservoir OM sediments has been proposed herein, along with enhanced chemical extraction steps and the introduction of a density separation step. The ratio of extracted carbon and nitrogen ranges from 70 ± 5 to 87 ± 2 and from 61 ± 7 to 81 ± 5%, respectively. The characterization of the OM chemically extracted, i.e., phenol, carbohydrate, protein, amino acid, NH4+, and NOx, recovered most of the chemically extracted carbon and nitrogen contents. These compounds are a significant part of the chemically extractable matter and represent in eq carbon from 55 ± 2 to 60 ± 5%, 14 ± 1 to 18 ± 1%, 21 ± 5 to 29 ± 7% and < 1 ± 0.1% for phenol, carbohydrate, protein, and amino acid, respectively. Results expressed in eq nitrogen are 46 ± 7 to 56 ± 25, 20 ± 1 to 34 ± 2, 8 ± 11 to 28 ± 3, and 0.3 ± 0.2 to 2.4 ± 0.1% for proteins, amino acid, NH4+, and NOx, respectively. In addition, this sequential method explained the OM arrangement and accessibility in lacustrine sedimentary matrices, especially for nitrogen compounds. Organic nitrogen compounds are in particular closely correlated with the sedimentary matrix, which explains the low accessibility of proteins and amino acids, mostly extracted using Na2B4O7, Na4P2O7, and NaOH. Protein stabilization processes can be attributed to several mechanisms, by virtue of their high reactivity. Moreover, the trend distribution is similar to carbohydrate and phenol supporting a major stabilization through OM interactions and encapsulation processes. Proteins could also be involved in ionic absorption on the mineral matrix should basic amino acid be present in their structure. Amino acids are primarily linked by direct interactions with the mineral matrix (amorphous and crystallized), thus implying adsorption and/or complexation processes. As regards mineral nitrogen, the ammonium is easily exchangeable, while non-accessible forms and nitrogen oxide can be stabilized by metals.
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We thank to Roland Redon, Stéphane Mounier, and Houssam Hajjoul from PROTEE laboratory of Toulon University for PARAFAC calculations. The authors would like to thank the Limoges University Foundation and EDF Hydro Center for their financially support.
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Bascle, S., Bourven, I. & Baudu, M. Nature and accessibility of organic matter in lacustrine sediment. J Soils Sediments 21, 1504–1522 (2021). https://doi.org/10.1007/s11368-021-02888-0
- Lacustrine sediment;
- Organic matter;
- Sequential extraction;
- Nitrogen and carbon nature;
- Organo-mineral interactions