# Dissolved organic matter dynamics and chemistry under fungal activity: A microcosm incubation with litter differentially 13C-labelled

Thanh Thuy Nguyen Tu, Marion Texier, Rania Krimou, Philippe Biron, Sylvie Collin, Emmanuel Aubry, Mercedes Mendez-Millan, Christelle Anquetil, Caroline Kunz, Frédéric Delarue, et al.

► To cite this version:

Thanh Thuy Nguyen Tu, Marion Texier, Rania Krimou, Philippe Biron, Sylvie Collin, et al. Dissolved organic matter dynamics and chemistry under fungal activity: A microcosm incubation with litter differentially 13C-labelled. Geoderma, 2026, 466, pp.117670. 10.1016/j.geoderma.2025.117670. hal-05497928

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# Dissolved organic matter dynamics and chemistry under fungal activity: A microcosm incubation with litter differentially ¹³C-labelled

Thanh Thuy Nguyen Tu<sup>a,*</sup>, Marion Texier<sup>a</sup>, Rania Krimou<sup>a</sup>, Philippe Biron<sup>b,†</sup>, Sylvie Collin<sup>a,‡</sup>, Emmanuel Aubry<sup>a</sup>, Mercedes Mendez-Millan<sup>c</sup>, Christelle Anquetil<sup>a</sup>, Caroline Kunz<sup>d</sup>, Frédéric Delarue<sup>a,‡</sup>, Marie A. Alexis<sup>a</sup>, Joëlle Dupont<sup>e</sup>

## ARTICLE INFO

Handling Editor: Dr Daniel Said-Pullicino

### Keywords:

- Dissolved organic matter

- Fungi

- ¹³C-labelling

- Chemical composition

- Decomposition processes

- Enzyme activity

## ABSTRACT

This work aimed at better documenting the effects of fungal activity on dissolved organic matter (OM) in soils. Dynamics of water-extractable OM (as surrogate for dissolved OM) quantity and chemical quality was monitored during a ca. 6 month microcosm incubation of plant residues in the presence of fungi. Differential ¹³C-labelling of metabolites vs structural compounds of the incubated residues further allowed clarifying the balance between fungal mineralisation and production of soluble compounds (through biosynthesis and/or decomposition). The fungus *Trichoderma harzianum* was mainly active during the first weeks of incubation, substantially mineralizing WEOM, preferentially consuming carbohydrates. The fungus induced chemical modification of WEOM, notably selective preservation of lipids and oxidation of lignin moieties. While *T. harzianum* probably degraded some insoluble structural molecules and produced biomass, these contributions to bulk WEOM appeared minor (when compared with leaching and mineralization), either because non-significant or entering non-extractable carbon pool. Additionally, characterization of control fungus-free microcosms, highlighted the potential role of abiotic processes on WEOM production, including leaching and depolymerisation by extracellular enzymes, notably of carbohydrate rich (insoluble) macromolecules.

## 1. Introduction

Soils correspond to the largest pool of terrestrial carbon as they comprise more carbon than atmosphere and global vegetation, combined (e.g. Eswaran et al., 1993; Lal, 2008). Although the primary source for organic carbon in soils is plant material, microorganisms are the actual builders of soil organic matter due to their constant metabolic activities (e.g. Kögel-Knabner, 2002; Liang et al., 2017). Microbial activity favours not only organic carbon recycling but also its inclusion in stable soil (micro)structures, under chemical forms of both high and weak preservation potential (Cotrufo et al., 2013; Lehmann and Kleber, 2015). Among soil microorganisms, fungi are the most efficient in degrading the lignocellulose complex of plant litters (Cooke and Rayner, 1984; Cragg et al. 2015) and fungal necromass contributes more to soil organic carbon than bacterial necromass (Nakas and Klein, 1979, Six

et al., 2006, Li et al., 2022). Due to its high reactivity, dissolved organic matter (DOM) plays a crucial role in soils: it both constitutes a main carbon source for microorganisms and is an important contributor to sequestered carbon (e.g. Kalbitz et al., 2000; Lehmann and Kleber, 2015). The multiplicity and complexity of processes interplaying on DOM dynamics in soils has been integrated in the conceptual model built by Kalbitz et al. right from the beginning of this century: adsorption/-desorption from mineral (or organic) phases, leaching from plant and microbial biomass, mineralisation, assimilation and degradation by microorganisms, etc (Kalbitz et al., 2000). However, our knowledge on DOM and its dynamics still requires investigation, especially concerning the role of microorganisms and particularly fungi. Recent papers notably called for further studies on the balance between (1) carbon removal through mineralisation of DOM and (2) fungal contribution to DOM through biosynthesis or biodegradation of insoluble components into

<footnote><sup>a</sup> Sorbonne Université, CNRS, EPHE, UMR 7619 METIS, F-75005 Paris, France</footnote>

<footnote><sup>b</sup> Sorbonne Université, CNRS, IRD, INRAe, UPEC, Université Paris Cité, UMR 7618 iEES Paris F-75005 Paris, France</footnote>

<footnote><sup>c</sup> Sorbonne Université, CNRS, IRD, MNHN, UMR 7159 LOCEAN, F-75005 Paris, France</footnote>

<footnote><sup>d</sup> MNHN, CNRS, UMR 7245 MCAM, F-75005 Paris, France</footnote>

<footnote><sup>e</sup> Sorbonne Université, CNRS, MNHN, EPHE, Université des Antilles, UMR 7205 ISYEB, F-75005 Paris, France</footnote>

<footnote>* Corresponding author.
E-mail address: Thanh-thuy.Nguyen_tu@sorbonne-universite.fr (T.T. Nguyen Tu).</footnote>
smaller ones (Liang et al., 2017; Gentile et al., 2024). Grassland eco-
systems are ubiquitous in temperate and tropical areas; they constitute
an essential pool for soil carbon sequestration, but are less studied than
agricultural and forest soils (Jones and Donnelly, 2004; Bai and Cotrufo,
2022). The present work thus aimed at better documenting the effects of
fungal activity on DOM dynamics in grassland soils.

A combination of microbiological and geochemical approaches were thus set up to document, among others, DOM chemistry at both bulk and molecular scales. Monitoring variations in DOM chemistry and sources through soil transformation may be complicated by the diversity of its components, whose chemical structure is often unspecific or non-diagnostic of microbial processes (Kelleher and Simpson, 2006; Kögel-Knabner, 2017). Differential ¹³C-labelling of plant residues and their incubation allow tracing specifically carbon pools of different origin, notably metabolic and structural components (Girardin et al., 2009; Haddix et al., 2016). As a result, this study is based on a microcosm incubation of plant residues, differentially ¹³C-labelled, in the presence of fungi. The experiment was achieved on leaf residues from a single plant species, *Lolium multiflorum* (Italian ray-grass), incubated by a single fungus, *Trichoderma harzianum*, so as to limit degrading trends due to variations in DOM source or microbial community, which may be difficult to identify. Ryegrass is among the most prevalent grass in natural and cultivated grasslands (Humphreys et al. 2010). *Trichoderma* corresponds to a cosmopolitan fungus in decaying woods, herbaceous litters and soils in general, thanks to its diverse metabolic capability including cellulose-, hemicellulose- and lignin-degrading enzymes (Gams and Bissett, 1998; Ahmed et al., 2009; Sharma et al., 2019; Bagewadi et al., 2017; Sánchez-Corzo et al., 2021). Water-extractable organic matter (WEOM), a common surrogate for DOM, was characterized by a multi-technique approach. Fungal enzymatic activity as well as elemental, isotopic and chemical composition of WEOM were monitored along a nearly 6-month incubation in order to evaluate the role of fungal activity on WEOM quantity and chemical quality. The strategy aimed at describing the transformation kinetics, as well as determining whether (1) specific WEOM compounds are preferentially mineralized and/or produced by the fungus and (2) *T. harzianum* substantially decompose insoluble macromolecular components into smaller extractable molecules.

## 2. Material and methods

The main experimental and analytical steps of the present study are
synthesized as flowchart (Fig. 1).

### 2.1. Litter labelling

Plant residues were specifically ¹³C-labelled to trace labile metabo-
lites, taking advantage of the high turnover of metabolic carbohydrates
that are continuously synthesized under a day-night regime (Girardin
et al. 2009; Fahey et al. 2011). Growing mature plants under ¹³C-
enriched atmosphere for a few days before sampling enables strong
labelling of metabolites to the contrary of storage compounds and
structural polymers that are little sensitive to such short-term labelling.
Italian ryegrass (*Lolium multiflorum* Lam.) was selected for its high leaf
productivity and because it is widespread in temperate grasslands
(Beckie and Jasieniuk, 2021). *L. multiflorum* seeds were sown in pots
containing vermiculite, and plants grown for six weeks under natural
atmosphere (δ ¹³C<sub>CO2</sub> ~ -8.8 ‰) in a controlled chamber with constant
climatic conditions (SERVATHIN Rubic V, iEES Paris, Thiverval-
Grignon, France; 70 % relative humidity, 400 ppmv CO₂, 23 °C day
temperature, 12 h daylight period at 250 µmol/m²/s of photosyntheti-
cally active radiation). Plants were fed twice a week with a Hoagland
nutritive solution (pH 6). Three days before harvesting, ¹³C-enriched
CO₂ (+807.8 ‰) was continuously injected in the chamber from a bottle
(10 % in abundance ¹³C, Eurisotop) in mixing ratio of 1/10. CO₂ isotope
composition (+808 ‰ in average) was monitored daily from purified

<figure><img src="image_2.png" /><figcaption>Fig. 1. Experimental protocol.</figcaption></figure>

cryoscopic samples and measured with an isotope ratio mass spec-
trometer (Micromass/Elementar Dual Inlet).

At the end of the labelling period, ryegrass leaves were collected,
dried to constant weight at 45 °C (ca. 3 days) and cut into pieces ca. 0.5
cm long which were thoroughly mixed for homogenisation. Bulk leaves
composition was 36.5 ‰C, 4.5 ‰N with δ¹³C + 115.1 ‰. The isotope
composition of WEOM was + 246.4 ‰ while that of the extraction
residue was + 65.4 ‰. Plant material was further sterilized by gamma
irradiation (45–70 kGy, Ionisos, ISO14001, France) as this method was
shown optimal for soil incubation studies (Maire et al., 2013).

### 2.2. Microcosm experiment

The experiment was performed in 250 ml glass bottles filled with ca. 7 g of vermiculite (millimetric pellets) and further autoclaved. 10 mL of Mandels medium (Mandels and Reese 1957) and 10 mL of antibiotic solution (teicoplanine, 200 µg/L final concentration) were added to each microcosm in order to favour the growth of the target fungus while inhibiting development of other microorganisms. About 2 g of γ-irradiated labelled plant material were added to the microcosms except the one used as control (i.e. containing no plant material). Half of the
microcosms were inoculated with 4 mL of water solution containing 14.10⁶ spores of *Trichoderma harzianum* Rifai strain LCP3428 (MNHN, Paris, France), while 4 mL of autoclaved ultrapure water was added to the other half of the microcosms.

All in all, four treatments were applied to the microcosms: (1) no plant-no fungus, (2) no plant-fungus, (3) plant-no fungus and (4) plant-fungus. Bottle lids were left loose so as to allow gas exchange with atmosphere and microcosms of each treatment were incubated in separate chambers in the presence of CO₂ trap (1 M NaOH) to avoid cross contamination (CO₂ characterization was beyond the scope of this work). Incubation conditions were designed toward that of natural soils while promoting *T. harzianum* growth: 20 °C, 70 % relative humidity and 8 h daylight period (80 µmol/m²/s of photosynthetically active radiation).

Microcosms were regularly watered (3 mL of autoclaved ultrapure water per month per microcosm) and examined with the naked eye for potential contamination by exogenous fungus. Microcosms exhibiting traces of development, even tenuous, of potential contamination by microorganisms other than *T. harzianum* were removed from the experimental design (3 out of 84 microcosms). Twice during the incubation (40 and 150 days), a few milligrams of randomly selected microcosms were taken for subculturing on potato dextrose agar and malt extract agar solid medium and further microscope examined so as to confirm the presence of *Trichoderma* fungus in the inoculated microcosms and the absence of any micro-organisms in the control microcosms. At the end of the incubation, DNA from 5 randomly selected subsamples were further sequenced for ITS1 and ITS2 molecular markers that confirmed identification with *T. harzianum*.

4 sets of triplicate microcosms were destructively sampled (i.e. sacrificed) at each of the seven time step investigated (1, 14, 28, 56, 91, 133 and 168 days), representing a total of 81 microcosms.

## 2.3. WEOM extraction

WEOM extraction protocol was adapted from Chantigny et al. (2007), after preliminary tests. The complete content of each microcosm was extracted with ultrapure water (1:50 w:w) for 2 h in a rotary shaker at 5 °C. Extracts were pre-filtered through nylon muslin (20 µm) and further centrifuged for 90 min at 5 °C and 5000 g. The supernatant was then filtered through nylon syringe filters (0.45 µm). Blanks and reference mixtures (vermiculite:unlabelled plants,7:2 w:w) were extracted along with each extraction batch for quality purposes. Aliquots of the obtained extracts were directly submitted to elemental analysis. Other aliquots were frozen at -20 °C in glycerol 20 % final concentration until determination of β -glucosidase activity. The remaining part of the extract was frozen at -20 °C, freeze-dried and crushed in a mortar prior to further analyses.

## 2.4. Chemical and isotope analyses

Raw data are available as *supplementary materials* (Table S1).

Dissolved organic carbon (DOC) and dissolved nitrogen (DN) were determined as non-purgeable organic carbon (NPOC) and total nitrogen (TN) using a TOC-L analyser (Shimadzu, Kyoto, Japan). C (TOC standard 25 mg.L⁻¹, Sigma-Aldrich, Saint Louis, Missouri, United States) and N (1 mg.L⁻¹N in H₂O, Merck Group, Darmstadt, Germany) standards were used as quantification references. Limits of detection and quantification were calculated based on the analysis of 10 extraction blanks: 0.14 mg. L⁻¹ and 0.24 mg.L⁻¹, respectively, for NPOC, and 0.03 mg. L⁻¹ and 0.07 mg.L⁻¹, respectively, for TN. DOC and DN contents were further normalized per gram of dry plant material (DPM) introduced in a given microcosm at the beginning of the experiment (mg.gDPM). WEOM C/N was calculated as weight ratio.

Approximately 0.2–0.3 mg of freeze-dried extracts were combusted using an elemental analyser (Thermo Fisher Scientific Flash, 2000) coupled to an isotope ratio mass spectrometer (Thermo Fisher Scientific

Delta V advantage) to determine δ¹³C. Oak wood, tyrosine and urea were used as standards for isotopic calibration (standard deviation of ca. 0.1 ‰).

## 2.5. Enzyme assays

β-glucosidase enzymatic activity was measured according to Medina et al. (2020) with minor modifications. The reaction mixture (0.5 mL) contained p-nitrophenyl-β-D-glucopyranoside (p-NPG, Sigma-Aldrich) as a substrate at a concentration of 2.4 mM in sodium citrate buffer 60 mM pH 4.8. Enzymatic activity was carried out in 1 mL spectrophotometer cuvettes. It was triggered by the addition of 100 µL of WEOM containing 20 % glycerol before the samples were immediately incubated at 30 °C, in triplicates. The reaction was stopped by the addition of 1 mL 2 M Ca₂CO₃ pH 11 and the amount of released p-nitrophenol (p-NP) was measured at 410 nm. Kinetics were carried out to calculate each activity after checking for linearity over a time period of 100 min. Calibration curves were established using p-NP (Sigma-Aldrich) solutions in reaction buffer (0, 25, 50, 100, 150, 200, 300 nmol). An absorbance of 1 corresponded to a variation of 83.8 nmoles. Activities were calculated using the following equation (Tab. S1):

$$V = [\frac{(\Delta A/\text{min}) \times 60 \times 83.8 \times 100]}{8} \text{ in nmol/h.mL}$$

## 2.6. Infrared spectroscopy

Fourier transform infrared spectroscopy (FTIR) was performed with attenuated total reflectance (ATR) mode using a Bruker Tensor 27 spectrometer. The powdered lyophilised samples were placed directly on a germanium crystal. FTIR spectra were acquired by 64 scans at a 4 cm⁻¹ resolution over the range 4000–600 cm⁻¹ (Table S4). All spectra were corrected for water vapour, CO₂, baseline and for differences in depth of beam penetration at different wavelengths (ATR correction; Opus software). As the amount of each component, except plant residues and fungus, introduced in the bottles at the beginning of the experiment was identical in all microcosms, we hypothesized that the absorbance of their contribution to FTIR spectra is similar in all microcosms. Therefore, to eliminate contribution from vermiculite, antibiotic and Mandel medium, the mean spectrum of the WEOM obtained from the three control microcosms (no plant-no fungus) at initial time was calculated and subtracted from other spectra (Margenot et al. 2016).

## 2.7. Pyrolysis-GC-MS

Py-GC-MS analyses were carried out with a pyrolyzer (Pyroprobe 6250, CDS) coupled to a gas chromatograph (7890B, Agilent) and to a mass spectrometer (5977B, Agilent). Samples were pyrolyzed at 650 °C for 15 s under helium at 1 mL/mn. Tetramethylammonium hydroxide (TMAH 25 % methanol) was added as a derivatization agent in excess quantity. This thermochemolysis resulted in thermal cleavage concurrent with the chemical cleavage of ester and ether bonds of the OM, and simultaneously to the methylation of polar functional groups improving detection of these compounds. The released pyrolysis products were online separated using a non-polar GC column Rxi5Sil MS (30 m*0.25 mm*0.5 µm, Restek) through an oven ramp (initial temperature of 50 °C maintained during 10 min, raised at 2 °C/min until 320 °C, the final temperature, maintained during 13 min). The molecules were then ionized and fragmented in a mass spectrometer, working with an electron impact source (70 eV; 230 °C). Fragments were analysed with a simple quadrupole operating at 2 scans/s from 35 to 700 m/z. Each compound was identified based on literature and using the NIST library V2.3 (Table S5).

## 2.8. Statistics

Results are shown as means, error bars representing standard
deviations of the replicated microcosms for each treatment. When triplicate data were available, Student's t-tests were performed with XLStat-Pro (v2010 AddinSoft) to test for significant effect (p-value < 0.05) of fungus inoculation on biogeochemical features of WEOM on each time step (Table S2). Dynamics in element and isotope content of water extracts were further investigated fitting linear or exponential models in R statistical environment (R Development Core Team, 2015). Carbon and nitrogen content were modelled using linear models with day and fungus inoculation as independent variables. Stable carbon isotope composition fitted single exponential decay models $\delta^{13}C_t = \alpha.e^{kt} + \beta$, in which k is the constant rate (d⁻¹), and α and β isotope coefficients (‰) so that $\delta^{13}C_0 = \alpha + \beta$ (Table S3). In the following sections, only differences which significance was statistically tested are described as significant.

## 2.9. Isotope mass balance calculation

Taking benefit of the differential ¹³C-labelling, basic theoretical calculation of the isotope composition of bulk WEOM was achieved to test for potential (1) release, into WEOM, of OM from other fractions that are not water extractable and (2) uptake of some WEOM components into other carbon fractions (i.e. insoluble OM, CO₂, etc.).

The relative abundance and isotope composition of the various components of each carbon fraction cannot be determined from the present data, but as a first approach they were tentatively approximated to the basic mixture of two carbon pools: one dominated by relatively ¹³C-depleted molecules (i.e. storage carbohydrates or structural polymers, 13D) and another one dominated by relatively ¹³C-enriched molecules (i.e. metabolic carbohydrates, 13R) which relative amount is given by $\tau$, so that the carbon content of a given carbon fraction CF can be written:

$$C_{CF} = C_{13D} + C_{13R} \text{ with } C_{13D} = \tau * C_{CF} \text{ and } C_{13R} = (1 - \tau) * C_{CF}.$$

Considering one process P1 changing the carbon content of WEOM, the carbon released or uptaken ($C_{P1}$) can similarly be distributed into 13D and 13R so that $C_{P1} = C_{13D-P1} + C_{13R-P1}$

$$\text{with } C_{13D-P1} = \tau_{P1} * C_{P1} \text{ and } C_{13R-P1} = (1 - \tau_{P1}) * C_{P1},$$

$C_{P1}$ being positive or negative according to the process type.

After P1, the carbon content of WEOM at a given time step ($t$) can be written:

$$C_{WEOM}(t) = C_{13D-WEOM}(t) + C_{13R-WEOM}(t)$$

with $C_{13D-WEOM}(t) = C_{13D-WEOM}(t-1) + \tau_{P1} * C_{P1}$ and

$C_{13R-WEOM}(t) = C_{13R-WEOM}(t-1) + (1-\tau_{P1}) * C_{P1}$; $t-1$ corresponding to the time step preceding $t$.

The carbon released or uptaken from WEOM by additional processes may be similarly calculated. For example, with a second process P2 changing the carbon content of WEOM, the amount of the ¹³C-depleted and ¹³C-enriched pools can be determined with:

$$C_{13D-WEOM}(t) = C_{13D-WEOM}(t-1) + \tau_{P1} * C_{P1} + \tau_{P2} * C_{P2} \text{ and}$$

$$C_{13R-WEOM}(t) = C_{13R-WEOM}(t-1) + (1-\tau_{P1}) * C_{P1} + (1-\tau_{P2}) * C_{P2}$$

Supplementary processes may be further taken into account in the same way.

The isotope composition of a given carbon fraction corresponding to the weighted mean of the isotope composition of each of its pools, it can be expressed as $\delta_{CF} = [C_{13D} * \delta_{13D} + C_{13R} * \delta_{13R}]/C_{CF}$.

Considering as a first approach, that the isotope effects associated with degradation process(es) are small with respect to the labelled isotope compositions of the present study, the isotope composition of WEOM at a given time step can finally be expressed as:

$$\delta_{WEOM}(t) = [C_{13D-WEOM}(t) * \delta_{13D} + C_{13R-WEOM}(t) * \delta_{13R}]/C_{WEOM}(t), \text{ with } \delta_{13D} \text{ and } \delta_{13R} \text{ being the isotope composition of the } ¹³C-depleted and } ¹³C \text{ enriched pools, respectively. } C_{13D-WEOM} \text{ and } C_{13R-WEOM} \text{ may be calculated with the above equations, according to the number of processes considered to change WEOM through degradation.}$$

# 3. Results

## 3.1. Elemental contents

WEOM from microcosms incubated without plant material exhibited negligible carbon and nitrogen content (ca. 3.31 mg.L⁻¹ and 3.93 mg.L⁻¹, respectively) when compared with those containing plant organic matter (ca. 372.32 mg.L⁻¹ and 102.31 mg.L⁻¹, respectively). Their carbon and nitrogen contents remained stable throughout the incubation period and were similar in microcosms incubated with (3.34 mg.L⁻¹ and 3.32 mg.L⁻¹, respectively) and without (3.28 mg.L⁻¹ and 4.53 mg.L⁻¹, respectively) fungus (Table S1). As a result, *T. harzianum* did not develop in microcosms without plant material, and the C and N contribution from the spore inoculum, Mandels medium and antibiotics to WEOM was negligible. To enable comparison with literature and between microcosms with organic matter, DOC and DN contents were further normalized per gram of dry plant material introduced in a given microcosm at the beginning of the experiment.

WEOM of all microcosms containing plant organic matter exhibited a carbon content of ca. 62 $mg_{DOC} \cdot g_{DPM}^{-1}$ at the beginning of the experiment, while reaching ca. 48 and ca. 121 $mg_{DOC} \cdot g_{DPM}^{-1}$ at the end, in microcosms with and without fungus, respectively (Fig. 2). Carbon content from fungus-containing microcosms were significantly different from the fungus-free ones after 14, 28, 56 and 91 days of incubation (p < 0.05). WEOM from microcosms inoculated with fungus exhibited a sharp decrease in C during the first two weeks of incubation (−13 $mg_{DOC} \cdot g_{DPM}^{-1}$) then remained stable, although this trend did not appear statistically significant. On the contrary, WEOM from microcosms without fungus showed a significant increase in carbon content through time (p < 0.05) for about 70 days before stabilizing around 110 $mg_{DOC} \cdot g_{DPM}^{-1}$.

WEOM of all microcosms containing plant organic matter exhibited a nitrogen content of ca. 20 $mg_{DN} \cdot g_{DPM}^{-1}$ at the beginning of the experiment, reaching ca. 14 and ca. 19 $mg_{DN} \cdot g_{DPM}^{-1}$ at the end, in microcosms with and without fungus, respectively (Fig. 2). Nitrogen content from fungus-containing microcosms was significantly different from the fungus-free ones after 14, 28, 56 and 91 days of incubation (p < 0.05). Although more variable than carbon content, WEOM nitrogen content also tended toward higher values for microcosms without fungus when compared to those with fungus. While changes in nitrogen content of microcosms without fungus did not appear statistically significant, microcosms inoculated with fungus exhibited a significant decrease through time (p < 0.05). WEOM of microcosms containing plant organic matter exhibited a C/N ratio of ca. 3.0 at the beginning of the experiment, while it reached ca. 3.2 and ca. 5.7 after 24 week decay for microcosms with and without fungus, respectively (Fig. 2). C/N ratio differed significantly between both microcosm type (p < 0.05).

## 3.2. Isotope composition

In agreement with the negligible C contributions of the spore inoculum, Mandels medium and antibiotics to WEOM, at the beginning of the experiment, the microcosms containing only plant material had similar $\delta^{13}C$ than the plant material itself: ca. 246 ‰. WEOM isotope composition followed exponential decays with constant rates significantly higher for microcosms with fungus than without fungus (Fig. 3, Table S3).

Theoretical isotope composition of bulk WEOM was calculated from mass balance as tentative estimation of the main processes potentially accounting for such decrease in isotope composition: (1) abiotic release of ¹³C-depleted molecules from insoluble fraction, (2) fungal ingestion of ¹³C-rich WEOM components and (3) release of ¹³C-depleted compounds due to fungal degradation.

The carbon involved in these processes is approximated to the
<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Carbon and nitrogen content and C/N ratio of WEOM (mean ± SD) from microcosms incubated with (solid symbols) and without fungus (open symbols).* indicates statistically significant difference (p < 0.05).</figcaption></figure>

mixture of a ¹³C-depleted pool and a ¹³C-enriched pool, in differing proportion according to the process considered (see experimental section 2.9). The amount of carbon provided by abiotic leaching was determined from the carbon content of microcosms without fungus (C<sub>NOFUN</sub>) at two successive time steps (t and t-1): C<sub>AB</sub>(t) = C<sub>NOFUN</sub>(t) - C<sub>NOFUN</sub>(t-1). The amount of carbon removed by biomineralization was further calculated from the carbon content of microcosms with fungus (C<sub>FUNGI</sub>) at two successive time steps and the carbon released by abiotic leaching, adjusted by a coefficient derived from the enzymatic activity of microcosms with fungus γ(t): C<sub>BM</sub>(t) = [C<sub>FUNGI</sub>(t-1) + C<sub>AB</sub>(t) - C<sub>FUNGI</sub>(t)]* γ (t). The carbon involved in each of these processes can further be divided into the ¹³C-depleted pool and the ¹³C-enriched pool, and the bulk isotope composition of WEOM calculated as the weighted mean of the combined ¹³C-depleted pools and ¹³C-enriched pools (see

<figure><img src="image_4.png" /><figcaption>**Fig. 3.** WEOM isotope composition measured (m, triangles, mean ± SD) and calculated (c, crosses, mean) for microcosms incubated with (FUNGI) and without (NOFUN) fungus. Blue and red bands indicate the isotope composition of initial WEOM and extraction residue (ER), respectively; *: statistically significant difference (p < 0.05).</figcaption></figure>

experimental section 2.9). Although several values can be applied within the frame of the initially measured bulk isotope values (+246 ‰ and + 65 ‰ for WEOM and extraction residue, respectively), calculation with abiotically leached carbon comprising 75 % of molecules relatively ¹³C-depleted (~+50 ‰) and biomineralized carbon comprising 85 % of molecules relatively ¹³C-enriched (~+300 ‰) is shown as a plausibility check on Fig. 3 (crosses). Tentative calculation adding a supplementary term to take into account the potential addition of biodegradation products of insoluble components (i.e. ¹³C-depleted extraction residue) did not improve the results (data not shown).

### 3.3. β-glucosidase activity

Whether or not inoculated with *Trichoderma*, microcosms incubated without plant material exhibited, all along the experiment, enzymatic activity negligible (2.14 nmol/h.mL) when compared with those containing plant organic matter (between 22.95 and 195.93 nmol/h.mL according to time step and treatment; Table S1). Accordingly, the following is focused on microcosms incubated with plant litter.

A similar background level of activity was observed in both types of microcosms at time 0 day (Fig. 4). After 2 weeks, a 4-fold increase in the enzymatic activity was observed in the presence of *Trichoderma harzianum* but not when it was absent (significant difference, p < 0.05). After 29 days the activity had reduced and was similar to that observed at time

<figure><img src="image_5.png" /><figcaption>**Fig. 4.** β-Glucosidase activity of WEOM (mean ± SD) from microcosms incubated with (solid symbols) and without fungus (open symbols).</figcaption></figure>
0 day in both conditions. In the following days, up the final sampling time, β-glucosidase activity remained at a background level in the fungus-containing microcosms, and went down to undetectable in the absence of the fungus.

### 3.4. Chemical analyses

WEOM chemistry was investigated by spectroscopy and spectrometry to further document the molecular changes associated with the elemental and isotopic changes described above. Although not suitable for (absolute) quantification, FTIR and Py-GC-MS can provide qualitative information on the chemical changes undergone by WEOM through incubation. Considering the negligible carbon content of the microcosms without plant material and the carbon dynamics evidenced, the following chemical study focuses on the microcosms incubated with plant material at initial time, after 28 days of incubation and final time (168 days).

The WEOM of all the microcosms containing plant material exhibited FTIR-ATR spectra typical for natural organic matter, with similar absorption bands indistinctive of the presence of fungus: a very broad band centred around 3200 cm⁻¹ and three intense bands in the 1800–1000 cm⁻¹ zone (Fig. 5). The 3200 cm⁻¹ band is mainly attributed to the O-H bonds of residual water (He et al. 2009, Szymanski, 2017) likely trapped on the mineral and/or organic phase of the extract. The small band at ca. 2930 cm⁻¹ is generally attributed to C-H bonds (Stevenson, 1982) but its smooth shape and inclusion with the shoulder of the previous band make it unsuitable to monitor the effects of incubation on WEOM

<figure><img src="image_6.png" /><figcaption>**Fig. 5.** FTIR-ATR characterization of samples: spectra typical of WEOM from microcosm incubated with plant material and fungi (168 days, top) and ratio of absorbance at 1350 cm⁻¹ to 1032 cm⁻¹ bands (mean ± SD, bottom) from microcosms incubated with (solid symbols) and without fungus (open symbols).</figcaption></figure>

quality. The band maximizing at ca. 1612 cm⁻¹ is generally attributed to aromatic C=C vibrations, symmetric stretching of COO⁻ groups, and H-bonded C=O of conjugated ketones (Stevenson, 1982; He et al., 2009, Szymanski, 2017). However, the lack of strong absorbance bands typical for the latter suggests the 1612 cm⁻¹ band to be primarily attributed to aromatic C=C, probably mostly corresponding to lignin. The highest absorption band is centred around 1360 cm⁻¹ and may be attributed to aliphatic C-H deformation and/or stretching of COO⁻ (Szymanski, 2017; Sharma et al., 2021). Finally, the band maximizing at ca. 1032 cm⁻¹ was primarily attributed to C-O stretch of polysaccharides, according to previous soil studies on water extractable organic matter (Stevenson, 1982; Kalbitz et al., 1999; Szymanski, 2017).

WEOM of the studied microcosms appeared as a complex mixture of diversified components under py-GC-MS analyses (Fig. 6). The identified components correspond to molecules commonly reported in plant and soil, particulate and dissolved organic matter (Huang et al., 1998; Spencer et al., 2009; Wang et al., 2021a). These molecules can be classified into four main categories: phenolics, carbohydrate-derived compounds, nitrogen-containing molecules as well as aliphatics (Fig. 6). Most of the identified phenolic compounds comprise methoxy groups and various alkyl substitutions which are typical for lignin (Saiz-Jimenez and de Leeuw, 1986; Huang et al., 1998). No phenol exclusively originating from tannins could be detected. Basic phenols and benzene derivatives may also result from the pyrolysis of polysaccharides or proteins including fungal chitin (Chefetz et al., 2000; Saiz-Jimenez et al., 2021). Carbohydrate-derived compounds include various cyclic and acyclic (anhydro)-hexoses and –pentoses, including levoglucosan, the main pyrolysis product of cellulose (Pouwels et al., 1989; Shen and Gu, 2009). Most of the identified N-containing molecules correspond to typical pyrolysis products of amino acids (i.e. methylated derivatives, decarboxylation and/or cyclization products, Fig. 6) pointing to proteinaceous origin for these compounds (Stankiewicz et al., 1996; Tempier et al., 2013). Although several of these compounds may originate from fungal chitin or melanin (e.g. pyridine- or pyrrolidine-containing molecules) in addition to plant proteins, none could be unambiguously attributed to fungi (Stankiewicz et al., 1996; Saiz-Jimenez et al., 2021). Identified aliphatic molecules mainly correspond to alkanes, acids and alcohols, saturated or not, some including further functionalized homologues (Fig. 6). While long chain aliphatics (>C₂₀) are typically of plant origin, the shorter one may equally be of plant or microbe origin (Eglinton and Hamilton, 1967; Wiensenberg et al., 2004).

## 4. Discussion

### 4.1. Abiotic release of WEOM

Increasing C-content and to a lesser extent N-content (Fig. 2), of WEOM from microcosms without fungus reveals substantial release and subsequent accumulation of soluble compounds, especially during the first weeks of incubation. All microcosms were sterilized at the beginning of the experiment, included teicoplanine antibiotic, and subculturing of fungus-free microcosms confirmed they remained sterile throughout the incubation period (see experimental section). Senescent leaves contain large amount of water-soluble molecules that are prone to physical leaching during (very) early decomposition (Benner et al., 1990; Maie et al. 2006; Nishimura et al. 2012). As a result, the observed WEOM release may be due to abiological processes. Although litter decomposition and DOC release were long thought as mainly controlled by microorganisms (e.g. Salamanca et al., 2003; Christ and David, 1996), abiological degradation of organic matter is now acknowledged as a significant process in soils (Kemmitt et al. 2008, Toosi et al. 2012; Zhou et al. 2020). It comprises mechanisms as diverse as solubilisation, chemical oxidation, chemical hydrolysis or else photodegradation (Austin and Vivanco, 2006; Toosi et al., 2014; Day et al., 2018; Wang et al., 2021b). The experimental conditions of the present incubation
<figure><img src="image_7.png" /><figcaption>**Fig. 6.** 650 °C pyrochromatograms typical of WEOM from microcosms containing plant material at the beginning of the experiment (top, without fungi), and after 168 day-incubation without (middle) and with (bottom) fungus. Brown molecules and discs: lignin derivatives, green molecules and diamonds: carbohydrates, pink molecules and triangles: N-containing compounds, blue pentagons and molecules: aliphatics, black symbols correspond to ubiquitous compounds. Most compounds occur in the three pyrochromatograms so that molecular structures were shown alternatively in one of the three, so as to limit graphic overload.</figcaption></figure>

(regular watering, light–dark cycles, ...) are compatible with such mechanisms. The metabolism associated with the residual enzymes naturally present in soils is also often included in abiotic degradation processes (Maire et al., 2013; Kéraval et al. 2016; Lohse et al., 2022). These enzymes may correspond to those excreted by soil microorganisms or those naturally included in plant residues (either extracellular or intracellular); such enzymes are generally preserved in soils thanks to associations with minerals or plant or microbial necromass. In the present study, such enzymes most likely originate from plant residues as no activity could be detected for the microcosms incubated without plant residues. Non-zero value of β –glucosidase activity in fungus-free microcosms, notably at the beginning of the experiment, shows this enzyme remained active in spite of gamma ray sterilisation of plant residue, and further suggests abiotic enzymatic activities for our *in vitro* experiment. Subsequent accumulation of released compounds is to relate with the *de facto* absence of microbial mineralization.

Although the cation exchange capacity of vermiculite is rather high, its potential to adsorb dissolved organic matter is negligible excepted when modified by cation exchange or intercalation (Abate et al. 2006). As a result, the marked increase in WEOM carbon content without fungus also suggests that potential adsorption of WEOM on the vermiculite pellet remains probably constant during incubation and minor with respect to litter decomposition processes. Increasing WEOM C/N ratio (Fig. 2) further suggests that these abiotically released molecules are N-depleted and qualitative chemical ratios (Figs. 5 & 7) point to substantial contribution of carbohydrate to the released and accumulated products. Carbohydrates are indeed recognized as main components of soluble litter material that are notably released during (very) early degradation (Benner et al. 1990; Kalbitz et al., 2003; Hishi et al. 2004). WEOM isotope composition (Fig. 3) decreases toward that of extraction residue of undegraded plant material, further suggesting abiotic release-degradation of linked (or polymerised) material. Although these early degradation patterns are in agreement with literature (Osono and Takeda, 2001; Kalbitz et al. 2003; Zhu et al., 2022a,b),

the present study highlights the potential role of abiotic processes in OM degradation.

## 4.2. Early fungal activity

As incubation proceeds, carbon, C/N and to a lesser extent nitrogen content of WEOM from microcosms inoculated with *T. harzianum* showed trends different from those without the fungus, pointing to fungal activity, especially during the first month of the experiment (Figs. 2 and 4). Higher β –glucosidase activity in the fungus-inoculated microcosms when compared with the others further confirms *T. harzianum* activity. β –glucosidase (β –D-glucoside glucohydrolase, EC 3.2.1.21) belongs to the glucosidase class that catalyze the hydrolysis of 1–4 β –glucosidic linkages of aryl-, amino- or alkyl- β –glucosides, β –linked oligosaccharides and other oligosaccharides, finally releasing D-glucose. In fungi they are part of the cellulosome and are involved in the last step of cellulose degradation by degrading cellobiose to D-glucose. In several *Trichoderma* species, β –glucosidase has been found in association with cell wall and/or purified from the extracellular medium (Tiwari et al 2013). *T. harzianum* is actually among the first fungi to colonize decomposing leaves in the succession of soil decomposers (Osono & Takeda, 2001). In agreement with literature on soil and compost WEOM, elemental contents decrease, as a result of microbial mineralization (Christ and David, 1996; Hishi et al., 2004; Said-Pullicino et al., 2007; Bahadori et al., 2021). Decrease in WEOM carbon content toward 3/4 of the initial value after one month (Fig. 2) indicates *T. harzianum* not only consumes the carbon released by abiotic degradation, but also a significant part of the WEOM initially present in plant material.

The WEOM from the present study appeared, upon chemical and molecular analyses, as a complex mixture of carbohydrates, lignin, protein and lipid derived compounds (Figs. 5 and 6), in agreement with previous studies on soil OM (Huang et al., 1998; Wang et al., 2021a). At first sight, the relatively high diversity and relative abundance of
<figure><img src="image_8.png" /><figcaption>**Fig. 7.** Abundance ratios of the main compound families identified by Py-GC-MS analyses of WEOM (mean ± SD) from microcosms incubated with (solid symbols) and without fungus (open symbols). The relative abundance of each compound family was derived from pyrochromatogram peak areas (i.e. sum of all the identified compounds of the family); * indicates statistically significant difference (p < 0.05).</figcaption></figure>

carbohydrate derived- and N-containing compounds suggested only slightly degraded OM as these compounds are generally considered as relatively sensitive to degradation (Opsahl and Benner, 1995; Mikutta et al., 2006). While FTIR-ATR spectra show no obvious trend through incubation, a slight decrease in the ratio of absorbance at 1032 cm⁻¹ to that at 1360 cm⁻¹ for microcosms with fungus when compared the fungus-free one can be noted. As a result, *T. harzianum* may have induced an apparent preferential degradation of polysaccharides when compared with other components (Fig. 5), first consuming easily degradable plant material such as carbohydrates for its metabolism.

No unambiguous fungal biomarker could be detected in substantial amounts in the pyrolysates of the WEOM extracted from microcosms inoculated with *T. harzianum*. Aside from ω-OH fatty acids, ergosterol and, to a lower extent, 3-acetamidopyrones, that are recognized as markers of fungal biomass but were not detected here, most pyrolysis products associated with fungi or fungal decay of plant organic matter can also correspond to plant or unspecific soil organic matter components. Indeed, the cracking of (macro)molecules during pyrolysis and the potential rearrangement of the obtained moieties, often lead to

unspecific compounds (Sobeih et al. 2008). As a result, small fungal production may have remained undetected here. While pyrochromatograms show no obvious trend through incubation (Fig. 6), abundance ratios of main compound families tend to exhibit different kinetics according to the presence of the fungus (Fig. 7, Tab. S1). N-compounds, carbohydrates- and lignin-derived molecules exhibit no particular trend with respect to each other through incubation, but seem preferentially degraded when compared with aliphatics in the presence of *T. harzianum* (Fig. 7). This is in agreement with the often assumed high preservation potential of lipids (Opsahl and Benner, 1995; Zonneveld et al., 2010) and the possible production of water soluble aliphatics during fungal degradation (of lignin; Khatami et al., 2019).

The absence of a noticeable relative degradation trend in pyrochromatograms between carbohydrates, lignin moieties and nitrogen-containing compounds is to relate to the fact that soluble organic matter is not only a substrate for fungal growth and activity, but may also include products of microbial metabolism. The contribution of microbial carbohydrates, peptides and even free fatty acids to WEOM was indeed evidenced in several soil and compost studies (Kalbitz et al., 2003; Haynes, 2005; Said-Pullicino et al., 2007). Although tenuous, the slight carbon increase from 2 months of incubation (Fig. 2) may further support the hypothesis of fungal production of WEOM compounds. Considering the relative chemical stability of aromatic compounds, accumulation of lignin-derived products may be expected in WEOM as incubation proceeds (Kalbitz et al., 2003; Said-Pullicino et al., 2007). This was not the case here, suggesting actual degradation of this macromolecule (and/or its soluble derived products). Fungal degradation of lignin is further confirmed by qualitative changes among lignin derived compounds: guaiacyl- and *p*-coumaryl moieties appear preferentially degraded with respect to syringyl-moieties that additionally exhibit a marked increase in acid/aldehyde ratio (Fig. 8). Indeed, an increase in the acid/aldehyde ratio of syringyl phenols is typical for lignin oxidation (Goni et al., 1993; Robertson et al., 2008; Nakakuni et al., 2023). Syringyl moieties are generally preferentially degraded during early degradation of soil OM or isolated lignin (Ziegler et al., 1986; Huang et al., 1998; Pichler and Kogel-Knabner, 2000); their relative enrichment in WEOM may suggest (1) lignin degradation mechanisms are different for *T. harzianum* from that of previously documented microorganisms, and/or (2) contribution from insoluble OM (that is biodegraded into smaller molecules extractable with water).

Inoculated microcosms seem to attain an apparent steady-state after a few weeks (Figs. 2-4), probably due to *T. harzianum* starvation as soon as easily metabolisable carbohydrates and nitrogen are no longer available, in agreement with previous *in vitro* studies on the decomposition of DOM or humic substances by fungi (e.g. Lerch et al., 2011; Collado et al., 2018; Gentile et al., 2024).

### 4.3. Fungal decay of insoluble compounds?

While (bio)chemical patterns undoubtedly point to fungal consumption of WEOM, indicators of degradation of insoluble OM into WEOM components are rather tenuous: slight carbon increase from 2 months of incubation, relative increase in aliphatics when compared with other compound families, relative changes in the chemistry of lignin moieties. Isotope patterns of incubated microcosms were thus further investigated to test whether *T. harzianum* actually degraded insoluble OM, taking advantage of the differential ¹³C-labelling of plant residues.

Both abiotic release of WEOM and fungal activity lead to a decrease in WEOM isotope composition, this ¹³C-depletion being significantly higher in the presence of *T. harzianum* (Fig. 3). Although fungal activity had clearly a significant impact on WEOM ¹³C-content, several isotope processes should be taken into account for both microcosm types. Chemical bonds involving heavy isotopes being harder to break and build, kinetic isotope effect associated with OM degradation and biosynthesis generally favours the production of ¹³C-depleted molecules
<figure><img src="image_9.png" /><figcaption>**Fig. 8.** Lignin degradation ratios of WEOM (mean ± SD) from microcosms incubated with (solid symbols) and without fungus (open symbols). The relative abundance of each compound family was derived from pyrochromatogram peak areas (i.e. sum of all the identified compounds of the family); * indicates statistically significant difference (p < 0.05).</figcaption></figure>

*(Urey, 1947; Fry, 2006).* Yet, these kinetic isotope effects are small (i.e. no more than a few per mil; Blair et al., 1985; Ghashgaie et al., 2003; Tcherkez, 2010; Lerch et al., 2011) when compared with the measured changes. Accordingly, they likely only played a minor role on the isotope signature of the studied WEOM. The observed isotope patterns more likely reflect relative changes in the different carbon pools contributing to WEOM. The three days isotope labelling applied to the plants led to contrasted isotope composition of WEOM and extraction residue (246 ‰ and 65 ‰, respectively), each being likely composed of molecules of different isotope composition as a consequence of their various multi-step biosynthetic pathways (Girardin et al., 2009; Haddix et al., 2016).

WEOM may thus have undergone isotope variation due to prefer-
ential uptake and/or addition of carbon from pools of isotope compo-
sition differing from initial WEOM. The processes the most likely
involved are (1) abiotic leaching of ¹³C-depleted molecules released
from insoluble fraction, (2) fungal consumption of ¹³C-rich WEOM
components and (3) release of ¹³C-depleted molecules upon fungal
degradation. Theoretical isotope composition of bulk WEOM was
calculated from mass balance as tentative estimation of these processes
(see result section 3.2). Calculated isotope compositions only consid-
ering the two first processes are in rather good agreement with the
measured values (Fig. 3). Tentative calculation adding a supplementary
term to take into account the potential addition of biodegradation

products of insoluble components did not improve the results (data not
shown) so that this process may have played a minor role on bulk
WEOM.

As a result, abiotic release of ¹³C-depleted carbon from insoluble OM
combined to preferential biomineralization of ¹³C-rich carbohydrate of
WEOM probably constitute the main processes controlling the observed
degradation patterns. Although (1) isotope fractionation undoubtedly
occurred, and (2) some chemical pattern suggested biodegradation
products of insoluble OM and fungal biomass may have contributed to
WEOM, these processes probably only played a minor role in the present
experiment.

**5. Conclusion**

This ca. 6 months monitoring of litter-vermiculite microcosms first allowed highlighting the potential role of abiotic processes on WEOM production, including leaching and depolymerisation by extracellular enzymes, notably of carbohydrate rich (insoluble) macromolecules. The fungus *T. harzianum* was mainly active during the first weeks of incubation, mineralizing not only abiotically released but also initial WEOM, preferentially consuming carbohydrates. The chemical modification of WEOM induced by this fungus also implied selective preservation of lipids and oxidation of lignin moieties. While *T. harzianum* probably degraded some insoluble structural molecules and produced biomass, these contributions to bulk WEOM appeared minor (when compared with leaching and mineralization), either because non-significant or entering non-extractable carbon pool. As a result, the studied fungus probably mainly played a catabolic rather than anabolic role on this soil OM pool (Liang et al., 2017). The modifications of WEOM induced by this single fungus are substantial but limited in time. Further experiments taking into account the complexity of soils, especially the succession of the diverse microbial populations naturally occurring in soils are now necessary to try to extrapolate the present results to natural soils.

CRediT authorship contribution statement

**Thanh Thuy Nguyen Tu:** Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization. **Marion Texier:** Writing – review & editing, Investigation. **Rania Krimou:** Investigation. **Philippe Biron:** Writing – review & editing, Investigation. **Sylvie Collin:** Writing – original draft, Supervision, Methodology, Investigation. **Emmanuel Aubry:** Investigation. **Mercedes Mendez-Millan:** Writing – review & editing, Supervision, Methodology, Investigation. **Christelle Anquetil:** Writing – review & editing, Methodology, Investigation. **Caroline Kunz:** Investigation. **Frédéric Delarue:** Writing – review & editing, Methodology. **Marie A. Alexis:** Writing – review & editing, Methodology, Investigation. **Joëlle Dupont:** Resources, Methodology, Conceptualization.

**Declaration of competing interest**

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.

**Acknowledgements**

We are indebted to Thierry Bariac for access to the controlled
chamber and to Patricia Richard for technical and analytical support
during the labelling experiment. Thanks are also due to Sandrine Lacoste
and Gail Monvoisin for taking care of *Trichoderma* cultures. We are
grateful to Sylvain Théry and Bénédicte Sabatier for assistance on pre-
liminary experiments during COVID lockdown. We also thank Aliénor
Allain and Katell Quénéa for valuable help in interpreting IR and SM
data, respectively. We are grateful to Laurent Rémusat, Delphine Derien, Thomas Lerch and Julie Leloup for smart advices on experimental design. Helpful discussions with Sylvie Derené, Nicolas Valette, Maryse Rouelle, Pierpaolo Zuddas and Arnaud Huguet deserve warm acknowledgements as well. Isotopic analyses were performed at the ALYSES platform (IRD/SU, Bondy) and statistical modelling were run by LEKIRO. This work was funded by a grant from CNRS-INSU (EC2CO AO2019) which was greatly appreciated

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.geoderma.2025.117670.

### Data availability

Data will be made available on request.

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