# The impact of polyvinyl chloride microplastics on carbon and nitrogen cycling in peatforming environments: relevance of the filler additive calcium carbonate (CaCO3)

Juanita Mora Gomez, Adrien Jacotot, Nicolas Freslon, Hela Ben Zeineb, Michael Charron, Catherine Joulian, Claude Le Milbeau

► To cite this version:

Juanita Mora Gomez, Adrien Jacotot, Nicolas Freslon, Hela Ben Zeineb, Michael Charron, et al.. The impact of polyvinyl chloride microplastics on carbon and nitrogen cycling in peatforming environments: relevance of the filler additive calcium carbonate (CaCO3). Science of the Total Environment, 2025, 977, pp.179341. 10.1016/j.scitotenv.2025.179341. insu-05033070

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The impact of polyvinyl chloride microplastics on carbon and nitrogen cycling in peat-forming environments: relevance of the filler additive calcium carbonate (CaCO₃).

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Juanita Mora-Gomez¹,*, Adrien Jacotot¹, Nicolas Freslon¹, Hela Ben Zeineb¹, Michael Charron², Catherine Joulian², Claude Le Milbeau¹

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¹ Institut des Sciences de la Terre d'Orléans (ISTO), UMR 7327, Univ. Orléans, CNRS, BRGM, OSUC, F-45071 Orléans, France.

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² BRGM, F-45060 Orléans, France

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*Corresponding author: Juanita Mora-Gomez e-mail=juanita.mora.gomez78@gmail.com

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## Graphic abstract

<figure><img src="image_2.png" /></figure>

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## Highlights

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* We investigated the impacts of PVC-MP and its additive CaCO₃ on OM degradation in peat-forming wetlands-PFW

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* PVC-MP accelerated C but disrupted N cycle mainly through microbial alterations
* $CaCO_3$ influence on PVC- MP impact was clear in the C cycle but only partial in the N cycle

* Results suggest implications of PVC-MP pollution on the role of PFW as global C sinks

## Abstract

Peat-forming wetlands (PFW) are crucial in the global C-cycle, yet they are increasingly threatened by various anthropogenic pressures, including microplastic (MP) pollution. We investigate the impacts of polyvinyl chloride (PVC) and its additive, calcium carbonate ($CaCO_3$) on organic matter (OM) degradation in PFW. We conducted two experiments: first, by mixing peat soil with increasing concentrations of crushed sanitary PVC-MP (0.3%, 3%, and 30%) and second, by assessing the role of $CaCO_3$ in modulating these impacts. Our findings revealed significant alterations in peat chemical properties largely mediated by $CaCO_3$ (i.e. increased pH, and $Ca^{2+}$, $Mg^{2+}$, $K^+$ concentrations). PVC-MP increased carbon dioxide ($CO_2$) and methane ($CH_4$) production, as well as dissolved organic carbon release. $CaCO_3$ may have enhanced $CO_2$ release through its dissolution and contributed to $CH_4$ production as a C source for a more diverse and active metagenomic community (higher *mcrA* gene abundance). Shifts in microbial community composition (e.g. reduction of *Acidobacteria* and increase in active fermenters, such as *Clostridia*) and metabolism (higher lignin-like compounds degradation and P-uptake activity but lower C-degrading enzyme activity) also contributed in the C-cycle alterations. PVC-MP enhanced denitrification (*narG* gene abundance) but reduced relative proportion of the ammonia-oxidizing archaea *Nitrososphaeria*, leading to inhibition of nitrification. The effects of PVC-MP were concentration-dependent, with $CaCO_3$ strongly influencing the C cycle but only partially affecting the N cycle, suggesting potential effect of other additives, such as plasticisers. Overall, our results highlight a significant disruption of microbial processes due to MP
pollution, leading to increased greenhouse gas emissions and significant implications on the role of PFW as global C-sinks.

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46 **Keywords**: PVC, microplastics, nutrient cycling, wetlands, organic matter degradation

## 1. Introduction

About 250 millions tonnes of plastics annually enter to the environment (Geyer et al., 2017) and they break down into microplastics (MP, <5mm) due to biotic and abiotic factors (Alimi et al., 2018). MP are transported by both air (Allen et al., 2019) or water (Wagner and Lambert, 2018), potentially reaching even the most remote areas. Despite the estimated higher concentration of MP in terrestrial ecosystems compared to oceans (Horton et al., 2017), their potential impacts have only recently gained attention. Current research efforts are primarily focused on agricultural systems, where substantial amounts of MP are expected due to various input pathways such as sewage sludge, compost, and plastic mulching. However, our understanding of MP in other ecosystems, including wetlands, drylands, and forests, remains limited. The dynamics of MP in these ecosystems may vary significantly due to differences in their conditions (de Souza Machado et al., 2018; Rillig and Lehmann, 2020).

Peat forming environments primarily consist of wetlands, i.e. transitional areas that are either permanently or temporarily flooded and include freshwater, brackish, and saline environments from polar regions to tropical areas (Hu et al., 2017). Additionally, wetlands are also constructed for removing pollutants from wastewater (Overbeek et al., 2020). Wetlands play a key role in the carbon (C) cycle as they act as C sinks (Köchy et al., 2015) while also may serving as significant methane (CH₄) producers (Bridgham et al., 2013; Kayranli et al., 2010). Nutrient cycling in wetlands is highly modulated by microorganisms involving processes, such as degradation of organic matter (OM), nitrification, denitrification,
and methanogenesis (Yarwood, 2018). However, microbial metabolism in these environments may be constrained due to various environmental conditions, such as low oxygen availability, low pH, or high concentrations of phenolic compounds (Freeman et al., 2001; Limpens et al., 2008). Wetlands face significant threats from activities such as drainage and agriculture (Hu et al., 2017), as well as from plastic pollution (Qian et al., 2020). Under disturbances, wetlands potentially export substantial amounts of dissolved carbon (DOC) to aquatic environments and release large quantities of C in the form of carbon dioxide (CO₂) or CH₄ (Kayranli et al., 2010). In many regions, wetlands experience considerable plastic pollution, particularly in areas where they are used for agriculture or where they receive plastic and microplastics from freshwater catchments or the ocean (Meera et al., 2022; Qian et al., 2020).

MP are found in soils and wetlands in a wide range of concentrations (0.001% - 7% DW/DW) depending on the proximity to human activities (Büks and Kaupenjohann, 2020; Qian et al., 2020; Wei et al., 2022). However, these quantities might be substantially underestimated, and comparisons remain challenging due to the lack of accurate detection methods and standardised quantification protocols. For instance, MP estimation are often reported either by area or weight, and in many cases, it is unclear whether the values are based on dry or wet weight. Without detailed information on water content or soil density, meaningful comparisons are limited (Büks and Kaupenjohann, 2020). Peat-forming wetlands, in particular, are expected to contain comparatively higher MP concentrations per gram of dry soil due to their high organic matter and water content, as well as their role as plastic sinks (Cyvin et al., 2021; Martin et al., 2020). For instance, Cyvin et al., 2021 reported plastic concentrations between 3 to 72% of soil DW in coastal peaty soils.

Polyvinyl chloride (PVC) pollution is a significant environmental concern due to its extensive use and diverse chemical additives. PVC is one of the most abundant MP found in terrestrial
systems, ranking after polyethylene (PE), polypropylene (PP), polystyrene (PS) or nylon (Qian et al., 2020). It has been detected in hotspots at concentrations up to 6.7% (w/w) (Fuller and Gautam, 2016). PVC is utilised in various applications, including pipes, hoses, toys, medical devices, mulch film, and automotive parts. It accounts for 10% of the total European demand of plastic polymers, with global PVC production projected to increase by about 3.2% annually (Peng et al., 2020). Furthermore, about 73% of the annual global production of plasticisers (e.g. phthalate esters, benzophenones) is derived from PVC products (Groh et al., 2019; Hahladakis et al., 2018). PVC products often contain a diverse array of additional chemical compounds, such as biocides, fillers, and stabilisers, further contributing to their chemical complexity (Groh et al., 2019; Hahladakis et al., 2018). Consequently, PVC residues, when present as MP, are chemically complex and are considered among the most environmentally damaging polymers, warranting further research.

MP can influence biodiversity and ecosystem functions, including nutrient cycling. Effects on C and N cycling has been reported, particularly in terms of the forms and relative concentrations of C and N compounds, emissions of related GHG, and impacts on plant growth and photosynthesis (Wang et al., 2024). Effect of MP on nutrient cycling may occur via changes in soil biochemical properties, shifts in microbial composition, changes in the expression patterns of functional genes, variations in relevant enzyme activities, or microbial-mediated plastic degradation (Wang et al., 2024; Zhang et al., 2021). Yet, MP effects on ecosystem functions and microbial communities have been shown to vary depending on factors such as polymer type, size, and dose, as well as specific properties of the ecosystem (Li et al., 2023). For example, PVC-MP may reduce total N and P, with not changes in bacterial community composition at 1% of in wetlands soils (Yu et al., 2021), while at similar dose, PVC-MP may reduce FDAse activity and change microbial community in a loamy agricultural soil (Fei et al., 2020). In a recent meta-analysis on the microbial response to MP,
Li et al. (2023) suggest that PE and PVC inhibit microbial community the most in soils, as it has been previously proposed for coastal sediments (Seeley et al., 2020). It has been found that plasticisers and their metabolites can interfere with biological processes but they can be also biodegraded by microorganisms (Wright et al., 2020), however the mechanisms involved regarding to the role of all chemical additives present in the PVC, are still elusive (Zhu et al., 2022). Furthermore, studies evaluating MP effects on wetlands are still scared and deserve more attention.

With the aim to improving our understanding of the mechanisms underlying the consequences of MP pollution on ecosystems functioning and potential feedbacks to climate change, we conducted a study to investigate the effects of PVC-MP on microbial OM degradation and nutrient (C, N) cycling in peat forming environments. We specifically chose to examine MP derived from sanitary PVC used in pipes as PVC is one of the most widely consumed plastic types and construction represents one of the most prevalent applications of PVC polymers. PVC products typically contain various additives, including calcium carbonate (CaCO₃) (Hahladakis et al., 2018), which was found in high percentages in the PVC used in our experiment (sanitary PVC tube; Ben Zeineb et al., 2021). Consequently, our study encompasses two complementary experiments designed to elucidate by on side the effects of PVC-MP on both the physicochemical characteristics of peat soil and microbial properties, and on the other side explore the role of CaCO₃ on these effects as relevant additive of this type of PVC product. Specifically we aimed to answer three key questions: i) what is the impact of PVC-MP on OM degradation and nutrient cycling in peat forming wetlands?, ii) what is the relevance of CaCO₃ in mediating this impact?, and iii) what are the potential implication in term of climate change?

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141 **2. Materials and Methods**

142 **2.1. Microplastics preparation**

143 A piece of sanitary polyvinyl chloride (PVC) was grated and sieved to obtain MP between
144 250-1000 µm in size for the experiment (PVC-MP). A chemical analysis on the PVC showed
145 presence of organic additives (14%), and more particularly n-alkanes, diisoctyl phthalate,
146 diinonyl phthalate, and inorganic additives (CaCO3 20-30%; Ben Zeineb et al., 2021). Due to
147 the high content of CaCO3 found in this type of MP, we decided to conduct a complementary
148 experiment testing the independent effects of pure grey PVC (PVC) and with the addition of
149 CaCO3 (PVC + 20% CaCO3 = PVC<sub>CaCO3</sub>). Before microcosms preparation, in both
150 experiments PVC-MP, PVC, and PVC<sub>CaCO3</sub> were exposed to ultraviolet clean bench for 20
151 min to minimize microbial contamination.

152 **2.2. Experimental setting**

153 We conducted two complementary experiments with similar set up (Fig. 1). Peat soil from 5
154 to 15 cm in depth was collected from a peatland located in Neuvy-sur-Barangeon, France
155 (Gogo et al., 2011) in May 2021 (first experiment-E1) and May 2022 (second experiment-E2)
156 and kept in sterilised aluminium trays at 4°C until the experiments were conducted. On the
157 day of the experimental setup, the peat soil was mixed, air dried for 3 hours, and roots larger
158 than 5 mm were removed. Microcosms were prepared by mixing air-dried peat soil with
159 different proportions of PVC-MP, PVC, or PVC<sub>CaCO3</sub>. E1 consisted of four replicates of air-
160 dried peat mixed with PVC-MP at 0.5% and 5% of wet peat soil (WW), equivalent to 3% and
161 30% of dry peat soil (DW), respectively. This adjustment was necessary due to the high
162 proportion of water typically present in peat soils, with an initial water content in E1 recorded
163 as 85%. In E2, we tested a broad range of three replicated concentrations of PVC-MP, PVC,
164 and PVC<sub>CaCO3</sub>: 0.04%, 0.4% and 4% of peat soil WW or 0.3%, 3%, 30% of peat soil DW, as
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the initial water content of peat for E2 was 88%. Both experiments included control microcosms (only peat), and saturated water conditions were assured by adding the same weight of sterilised ultra-pure water than the initial weight of peat. Microcosms were incubated at 20°C in the dark and covered with aluminium foil to reduce evaporation. Peat chemical and biological properties were evaluated at the initial state (freshly collected peat soil) and at four sampling dates for the E1 (after 5, 15, 40, 91 days) and two sampling dates for E2 (0 day-after mixing with MP and after 26 days, Fig. 1)

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## 2.3. Pore water chemistry

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50g of wet peat soil was centrifuged in 50 ml centrifuge tubes at 5000 rpm for 45 minutes. Supernatant (water) was filtered, collected in different 15ml vials, and processed depending on the analysis: i) 0.45µm-filter water no acidified, for measuring dissolved inorganic carbon (DIC); ii) acidified with H₃PO₄ for measuring dissolved organic carbon (DOC)/total nitrogen (TN) in a Shimadzu TOC-L analyser; 0.20 µm-filter water for measuring; iii) anions; and iv) cations (after acidification with HNO₃) by ion chromatography. Additionally, SUVA index was calculated after the measure of the absorbance of the 0.45µm-filtered water at 254 nm.

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## 2.4. Biological properties

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Microbial properties were assessed by measuring extracellular enzyme activities (EEA), GHG soil respiration (CO₂, CH₄), abundance of specific genes (16S rRNA, fungal 18S rRNA, *mcrA*, *pmoA*, bacterial lacasse) and community assembly of Archaea, Fungi, and Bacteria. Molecular analyses were conducted exclusively in the E1.

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Six EAA related to different biochemical cycles were evaluated. C cycle = β-1,4-glucosidase (B-GLU), β-1,4-xylosidase (B-XYL), phenol oxidase (POX); sulphur cycle = arylsulfatase (ARS), nitrogen cycle = β-1,4-N-acetyl-glucosaminidase (NAG), phosphorus cycle = acid phosphatase (PHOS). Enzyme activity was measured at experimental conditions using

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adjusted methodology based on previous protocols (Dunn et al., 2013; German et al., 2011).

Summing up, 1 g of wet peat was used for each enzyme essay, hydrolases by measuring
fluorescence (355exc/460em) after 1 h incubation with MUF-labelled substrates (at 0.5 or 1
mM depending on the enzyme), while; phenol oxidase activity was measured by absorbance
at 460 nm after a 10-min incubation with L-DOPA (5 mM). Microbial respiration of CO₂ and
CH₄ was evaluated through a closed incubation method modified from Li et al., (2021), i.e.
peat matrix was subjected to both aerobic (air) and anaerobic (nitrogen gas) incubation and
gas concentrations were measured with a Los Gatos Research Ultraportable Greenhouse Gas
Analyser at 0, 30, and 180 min to calculate production rates. Based on E1 result patterns for
enzymes and GHG, a simplified protocol was used in E2. Thus, the biological component of
E2 was assessed only measuring B-GLU, PHOS, and GHG production under aerobic
conditions.

Abundance of functional and taxonomic genes were analysed in three of the four biological replicates of E1, at the initial peat sample, and at the day 5 and 91. While microbial community composition of Bacteria, Archaea, and Fungi only in the initial sample and after 91 days of the experiment. At each sampling date, 5g of homogenised peat was collected, and stored at -80°C within 1h, until use. PowerSoil™ Total RNA Isolation Kit and DNA Elution Accessory Kit (Qiagen) were used for gDNA/RNA co-extraction following manufacturer's protocols. Extracted RNA was DNA-cleaned by TURBO DNA-free™ kit (invitrogen, USA) and reverse-transcribed using the iScript™ Select cDNA synthesis Kit (BIO-RAD). Resulting cDNA and gDNA were used in the quantitative PCR (qPCR) analyses of functional genes (narG, mcrA, pmoA, Lacasse bacteria) while only gDNA was used to measure taxonomic genes abundances (16S rRNA, 18S rRNA). gDNA and cDNA/RNA concentrations were measured with Quantus™ fluorometer/QuantiFluor® ONE dsDNA System (Promega) and BioPhotometer (Eppendorf) respectively. The choice of primer sets was based on studies
conducted in peat environments (Supplementary Table 1A), and preliminary PCR reactions were carried out to verify the amplification of the desired PCR products and optimize the reaction conditions. All qPCRs were run in duplicate with the gDNA or the cDNA obtained from each soil sample, final volume of reaction mixture containing 2ng of DNA template, forward and reverse primers at 0.4 µM, and 1X of GoTaq® qPCR Master Mix (Promega) for taxonomic genes or 1X of SsoAdvanced™ Universal SYBR® Green Supermix (BIORAD) for functional genes. Thermal cycling conditions were standardised (Supplementary Table 1A) and gene amplification was followed by a DNA melting curve analysis. The efficiencies of the qPCR were 90-95% and R2 > 0.994 (Supplementary Table 1A).

Templates for qPCR standard curves were plasmids obtained by cloning the target gene from the initial peat sample or from a known strain (Supplementary Table 1A). Gene copy number was calculated using spectrophotometry (260 nm), the molecular weight of the gDNA, and the number of copies of the target genes in the genome. 10x serial dilution of plasmids, with a range of $10^7$ to $10^2$, were used for calculating the number of gene copies, and values were normalized by the DNA concentration extracted per gram of dry peat matrix of each sample.

Microbial community composition was analysed by metabarcoding. The gDNA were submitted to the ADNID laboratory of the Qualtech group for sequencing. Briefly, the initial PCR was carried out with primers targeting the V3-V4 16S rRNA gene region (341F/806R) and the fungal ITS region (ITS86-F/ITS4-R). A second PCR step was performed to index the individual samples. Specific PCR products were quantified with a fluorescent nucleic acid stain and pooled in equimolar quantities. The library quality control (qualitative and quantitative) was conducted with a Fragment Analyzer system (Agilent) and by qPCR. Each library pool was then loaded onto an Illumina MiSeq Standard v2 flow cell, and sequencing was performed in a 2x250 bp paired-end format, utilizing a MiSeq v2 500 cycles reagent cartridge. Base calling was carried out using Illumina Real Time Analysis (RTA) software
(v1.18.54). The sequencing output generated by RTA was demultiplexed, and the data was
subsequently converted into FastQ format using Illumina Bcl2fastq software (v2.20).

Sequence data was then processed using *dada2-version 1.26.0* (Callahan et al., 2016) package
for R program (version 4.0.3) and following a standard pipeline of paired end Illumina MiSeq
data analysis for prokaryote (https://benjjneb.github.io/dada2/tutorial.html) and fungi
(https://benjjneb.github.io/dada2/ITS.html) to produce the final taxa and sequences
tables. In short, primers were eliminated from sequences and quality of reads was checked.

Reads were denoised (i.e. to combine all identical sequencing reads into unique sequences),
paired reads merged, and chimeras removed. The amplicon sequence variant (ASV) table was
constructed using the *assignTaxonomy* function (based on the RDP naive Bayesian classifier
method) and comparing with the databases: Silva_nr_v138_train (Quast et al., 2013) for
prokaryotes and UNITE dataset (sh_general_release_dynamic_s_10.05.2021) for fungi
(Nilsson et al., 2018). DNA amplicon sequences have been submitted to the SRA databases
under accession number SUB14849124.

## 2.5. Data Analyses:

Statistical analyses were performed in R version 4.2.3 (R-Core-Team, 2023). Correlation
among biochemical variables of E1 were analysed with the "cor" function of "corrplot"
package. Differences among treatments in E1 were assessed using the "nlme" package and its
"lme" function to fit a repeated measures model that accounts for the non-independence of
replicates across experimental sampling. For E2, we utilised the "stats" package and the "lm"
function as this was a punctual assessment at a single time point (0 or 26 days). Tukey's
multiple comparison test (multcomp, *glht*) was used for post hoc analyses of the differences
among the levels of the fixed effects (treatments) in the final model. Assumptions of
normality and homogeneity were assessed by using diagnostic plots, and variables were log-
transformed when needed.

Microbial community at day 91 of E1 was analysed based on the ASV databases of Bacteria,
Archaea, and Fungi obtained from metabarcoding analyses. Analyses were conducted using
"phyloseq" (Mcmurdie and Holmes, 2013) and "vegan" R packages (Oksanen et al., 2013).
The complete ASV database was employed to calculate the alpha diversity indexes and
differences among treatments were tested with lineal models, function "lm". To assess
community structure, taxa with an average relative abundance of reads exceeding 0.01% were
selected. This filtering step was implemented to mitigate the influence of rare species on the
subsequent ordination analysis. Non-metric Multidimensional Scaling (NMDS) analysis,
based on Bray-Curtis dissimilarity, was performed using the "metaMDS" function. Statistical
differences in community similarity were evaluated using permutational multivariate analysis
of variance (PERMANOVA), "adonis2" function, and the average contribution of each ASV
to the difference among groups was determined using the "simper" function. The influence of
soil environmental variables on microbial communities was assessed using distance-based
redundancy analysis (dbRDA), performed with the "trans_env$cal_ordination()" function
from the "microeco" package (Liu et al., 2021). Due to strong correlations (>80%, see
Appendix Fig. A.2) among some environmental variables, a subset was used for the dbRDA
analysis. Additionally, Pearson correlations between microbial class and environmental
variables were conducted with the "trans_env$cal_cor()" function from the same package.

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283 **3. Results**

284 **3.1. PVC-MP effects on peat chemical properties**
The unaltered peat, i.e. control treatment at day 0, was an acidic matrix (pH = 4.33 ± 0.01) with a relatively low amount of some extractable ions (Na⁺ = 0.14 ± 0.03 mmol L⁻¹; K⁺ = 0.04 ± 0.009 mmol L⁻¹; Mg²⁺ = 0.02 ± 0.002 mmol L⁻¹; Ca²⁺ = 0.04 ± 0.01 mmol L⁻¹; Cl⁻ = 0.09 ± 0.01 mmol L⁻¹; SO₄²⁻ = 0.08 ± 0.02 mmol L⁻¹; total N = 0.13 ± 0.03 mmol L⁻¹), an important release of highly aromatic C (SUVA₂₅₄ = 4.9 ± 0.3 L mg⁻¹ m⁻¹) as DOC (1.80 ± 0.08 mmol C L⁻¹) but low DIC (0.02 ± 0.005 mmol C L⁻¹). Soil manipulation altered the initial properties of peat matrix in both experiments. Throughout the conducted experiments, and relative to initial peat conditions, control microcosms generally exhibited an increase in pH, and extractable DOC, Cl⁻, K⁺, and Na⁺, while SO₄²⁻ concentrations decreased. In contrast, DIC, SUVA₂₅₄, NH₄⁺, and NO₃⁻ displayed variability (Fig. 2, Table 1, Appendix A Fig. A.1). At time 0 in E2, just after PVC-MP, PVC and PVCₐ₅CO₃ addition some changes were already observed, and they were more pronounced in the PVC-MP treatment compared to PVCₐ₅CO₃ and pure PVC, where either no impact or only minimal effects were found (Appendix A Table A.2). Hence, immediately after addition of PVC-MP we observed a significant increase of K⁺, Na⁺, NH₄⁺, Mg²⁺, Ca²⁺, Cl⁻, DOC, TN, and NO₃⁻, at all evaluated concentrations (0.3%, 3%, 30%). Consequently, pH also raised and interestingly SUVA₂₅₄ increased at 0.3% and 3% but not at 30% suggesting aromaticity of C released from the peat-PVC-MP mixture was higher at lower concentrations of PVC-MP.

Significant differences were obtained between the control and PVC-MP treatments in most of the chemical peat properties except for NO₃⁻ concentration, for both E1 and E2 (Tables 1 and 2). In E1, the pH, total N, DIC, K⁺, Na⁺, NH₄⁺, Mg²⁺, Ca²⁺ values increased after 5 days of PVC-MP addition, and these values were either maintained or further augmented during the 91 days of experimentation, except for DIC and Ca²⁺ (Fig. 2, Appendix A Fig. A.1). PVC-MP addition progressively increased DOC and Cl⁻ and decreased SO₄²⁻ (Fig. 2, Supplementary Fig. 1A) throughout E1. The impact of PVC-MP at a concentration of 30%
was larger compared to 3%, and significant alterations were consistently observed at both concentrations in at least one sampling date (*p*<0.05), except for the SUVA₂₅₄ index, which increased at 3% but decreased at 30%. Effects of PVC-MP on peat chemical properties observed in E2 were like those found in E1, particularly for PVC-MP and for the mixture of CaCO₃+PVCpure (PVC₄CaCO₃) at concentration of 3% and 30% (Table 1). Interestingly, the increase in TN and NH₄⁺ detected was more pronounced with PVC-MP (impact at all concentrations) than PVC₄CaCO₃ (impact only at higher concentrations). Pure PVC (PVC) increased the pH, Na⁺ and Cl⁻ at 3% and/or 30% (Table 1). Finally, some physicochemical properties (DOC, NH₄⁺, Mg²⁺, Ca²⁺, TN, K⁺, Na⁺) were affected at all PVC-MP concentrations evaluated in E2 (0.3%, 3%, 30%) while others (DIC, pH, SUVA, Cl⁻, Na⁺) were only affected at the higher concentrations (3%-30%, Table 1). Some of the variables also showed an increase in change with increasing MP dose (pH, NH₄⁺, Ca²⁺, TN, Cl⁻).

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**3.2. PVC-MP effects on microbial organic matter degradation in peaty matrix**

Microbial extracellular activity measured in E1 was affected by PVC-MP addition (Table 2) but patterns were diverse. Activity of all measured hydrolases were strongly reduced at the higher concentration (30%) of PVC-MP, but at 3% only the activity of β-D-glucosidase, β-D-xylosidase, and arylsulfatase decreased, whilst phosphatase and β-1,4-N-acetyl-glucosaminidase activity was larger than control in some sampling dates (Fig. 2, Appendix A Fig. A.1). Additionally, despite phenol oxidase activity was highly variable throughout E1 (Appendix A Fig. A.1), a significant tendency of lower values in the control treatment was detected (Table 2). CO₂ and CH₄ soil production was stimulated by PVC-MP at aerobic and anaerobic conditions (Table 2), but while CO₂ increased just after the MP-PVC addition, CH₄ progressively increased over time (Fig. 2, Appendix A Fig. A.1 and Table A.2). In both cases,
334 the effect was stronger at 30% MP concentration. After 26 days of incubation in E2, the
335 PVC-MP and $PVC_{CaCO_3}$ treatments exhibited effects similar to those observed in E1,
336 increased CO₂ production and reduced β-D-glucosidase and phosphatase activity at the
337 highest concentration, but an increase of phosphatase activity at 0.3 and 3%. Pure PVC
338 reduced CO₂ production at 0.3% and decreased phosphatase activity at 30% (Table 1).

339 The microbial metabolic potential and its expression were measured only in E1 by qPCR of
340 selected genes with gDNA and cDNA respectively. After 5 days of PVC-MP addition, the
341 denitrification potential (*narG* gene abundance) was reduced at a concentration of 30%, while
342 the abundance of bacterial laccase genes increased at 3% (Table 3). Following 90 days of
343 experimentation, copy numbers of most genes and their expression (*NarG*, *mcrA*, *pmoA*)
344 increased in the PVC-MP treatments, with significant changes mainly observed at the 30%
345 concentration (Table 3). Potential abundance of bacterial laccase gene was the only with
346 lower values at higher concentration of PVC-MP after 90 days of experimentation (Table 3).

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348 **3.3. PVC-MP effects on microbial community assemblages**

349 Microbial community abundance and assemblages were assessed only in E1. Based on qPCR
350 results (Table 3), total Bacteria (16S rRNA gene) abundance did not change in day 5, but was
351 higher after 90 days of PVC-MP treatment at both concentrations 3 and 30%. In contrast, the
352 addition of PVC-MP reduced Archaea (*mcrA* gene) and Fungi (18S rRNA gene) abundances
353 principally at 30% PVC-MP concentration since day 5.

354 A total of 153,310 raw sequences of 16S rRNA gene for Prokaryotes, with an average of
355 12,755 sequences per sample, were obtained. 6.6% (10,129) of prokaryote sequences
356 belonged to Archaea and were analysed separately. For fungal ITS, a total of 199,028 row
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sequences and an average of 16,585 per sample were obtained. A total of 2,767 ASV were identified for Bacteria, 96 ASV for Archaea, and 559 ASV for Fungi.

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No differences among treatments in richness nor in biodiversity indexes for any of the microbial groups were found (LM analyses *p* > 0.08, Appendix A Table A.3). Nevertheless, after 90 days of PVC-MP addition, archaeal assembly differed among all treatments (Fig. 3a, adonis test, *p* = 0.003). Dominant archaeal classes (Fig. 3b) in the initial peat matrix were *Nitrososphaeria* (50%), *Bathyarchaeia* (20%), and *Nanoarchaeia* (17%), and methanogens were predominantly ASV from the genus *Methanobacterium* (*c_Methanobacteria*) accounting for approximately 14% of the archaeal community in control treatment (Appendix B Table B.1). PVC-MP addition reduced several dominant archaeal ASV from the class *Nitrososphaeria* (e.g. *Candidatus Nitrosotalea*), and favoured ASV from methanogen archaeal groups from the classes *Methanocellia*, *Methanomicrobia*, *Methanosarcinia*, and *Methanobacteria*, collectively reaching up to 13% at 3% of PVC-MP concentration (simper *p* < 0.05, Appendix B Table B.1). Remarkably, at 30% PVC-MP, the class *Methanocellia* (e.g. *Methanocella*) and *Methanomicrobia* (e.g. *Methanoregula*) constituted about 40% of the total archaea community. Distance-based redundancy analysis (dbRDA) indicated that archaeal community composition across treatments in E1 was significantly influenced by pH, DOC, SUVA₂₅₄, Na⁺, NH₄⁺, Mg²⁺, and SO₄²⁻ (*p* < 0.05, Appendix A Fig. 3A). Additionally, Pearson correlations with environmental variables revealed that the class *Thermoplasmata* and *Methanocellia* were positively correlated with pH and CH₄ production, while *Methanomicrobia* correlated to NH₄⁺. In contrast, *Nitrososphaeria* showed a positive correlation with arylsulfatase activity but negative correlation with CH₄ and pH (*p* < 0.01, Appendix A Fig. A.2).

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Bacterial community assembly at day 91 of E1 significantly shifted only at the higher concentration (30%) of PVC-MP (Fig. 3c, adonis test, *p* = 0.004). Bacterial community (Fig.

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3d) in the original peat matrix (initial) had a strong dominance of the class *Acidobacteria* (~45%), followed by *Alphaproteobacteria* (~11%), and *Verrucomicrobiae* (~9%). Control (0%) and 3% of PVC-MP showed similar bacterial composition. Dominance of bacterial classes at 30% of PVC-MP shifted to *Clostridia* (~22%), *Alphaproteobacteria* (~17%), and *Gammaproteobacteria* (~10%). Thus, among other changes at 30% PVC-MP, initial abundant ASV such as *Acidobacteria* (e.g. taxa from the order *Acidobacteriales*) and *Thermodesulfovibrionia* were reduced, and no previously detected groups of *Gammaproteobacteria* (e.g. *Methyloversatilis*, *Aquabacterium*), *Acidobacteria* (e.g. *Bryobacter*), and *Firmicutes* (e.g. *Mobilitalea*, and genus *Ruminiclostridium*) emerged (simper *p* < 0.05, Appendix B Table B.2). Methanotrophs found in our experiment were *Methylocapsa*, *Methylocystis*, *Methylovirgula*, *Methylomonas* but not significant changes of these groups were observed among treatments (simper *p* > 0.05, Appendix B Table B.2). dbRDA showed that pH and SUVA₂₅₄ significantly influenced bacterial composition (*p* < 0.05, Appendix A Fig. 3A). Significant positive correlations (Pearson, *p* <0.01) with pH and CH₄ were observed for several abundant class including *Negativicutes*, *Clostridia*, and *Bacteroidia*. *Gammaproteobacteria* showed a positive correlation with Mg⁺², while negative correlations were found for *Acidobacteria* with pH and CH₄ and *Alphaproteobacteria* with the SUVA₂₅₄ index (Appendix A Fig. A.4).

Fungal assembly changed by PVC-MP addition mainly at the 30% (Fig. 2e, adonis test *p* = 0.001). Dominant fungal class in the initial peat matrix were *Agaricomycetes* (30%) *Leotiomycetes* (40%) and several undetermined ASV (20%). PVC-MP addition reduced the abundance of several taxa of *Agaricomycetes* (e.g. *Hypochnicium*), considerably augmented undetermined ASV and taxa of the class *Sordariomycetes* (e.g. *Scedosporium dehoogii*) and *Orbiliomycetes* (e.g. *Arthrobotrys*) (simper *p*<0.05, Appendix B Table 3B). dbRDA revealed that pH, DOC, SUVA₂₅₄, Na⁺, NH₄⁺, and SO₄²⁻ significantly influenced fungal
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community composition ($p < 0.05$, Appendix A Fig. 3A). Additionally, a positive correlation

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(*Pearson*, *p* < 0.01) was found between the class *Spizellomycetes* and NH₄⁺, and between

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*Orbiliomytcetes* and Mg⁺² (Appendix A Fig. A.4).

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411

## 4. Discussion

412

Ecological stress caused by MP contamination on ecosystem functioning and biota is a

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growing global concern. However, many aspects remain poorly understood, particularly the

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influence of the various additives found in plastics. In this study, we evaluated the impact of

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PVC-MP on peaty soil using PVC grey sourced from sanitised pipes, known to contain

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various additives such as plasticisers (Hahladakis et al., 2018). The PVC utilised in our study

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had a notably high concentration of CaCO₃ (20-32%, Ben Zeineb et al., 2021) prompting us

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to investigate the potential relevance of this additive on the observed effects. CaCO₃ serves as

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a common filler additive in different types of plastics, not limited to PVC (Hahladakis et al.,

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2018), and it is also used as soil amendment in agricultural peat soils (Ronkainen et al.,

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2025), implying that the impacts observed in our study may extend to other types of plastics

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utilising this additive and some agricultural practices.

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Our study encompassed a wide range of PVC-MP concentrations (0.3%, 3%, and 30%). The

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selection of 0.3% and 3% concentrations are in agreement with reported levels of MP found

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in soils and wetlands (Büks and Kaupenjohann, 2020), while exploring higher concentrations,

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such as 30%, that may occur in hotspots or are projected due to the role of wetlands as plastic

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sinks (Martin et al., 2020). For instance, projections suggest concentrations of up to 70% w/w

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of plastics in coastal peatlands in Norway (Cyvin et al., 2021).

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PVC-MP strongly affected the chemical balance of peat matrix, with this effect becoming

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more pronounced as the concentration of PVC-MP increased. Our findings suggest potential
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disruptions to nutrient cycling, particularly regarding C and N, with CaCO₃ playing a crucial
role of in PVC-MP effects.

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433

434

**4.1. PVC-MP effects on C cycle**

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MP can influence soil C cycle changing content and forms of C compounds, as well as GHG
emissions, by different mechanisms. However, the magnitude and nature of these impacts
depend largely on the characteristics of both the soil and the microplastics. (Chen et al., 2023;
Wang et al., 2024). In our study, PVC-MP led to a significant increase in the release of CO₂,
CH₄, and/or DOC indicating an accelerated C cycle even at the lower evaluated
concentration. Based on our results, the mechanisms involved might have included both i) a
chemical liberation of inorganic and organic C from PVC-MP, and ii) the activation of
microbial OM degradation. An important amount of inorganic C might have originated from
the initial reaction between the CaCO₃ present in the PVC-MP with the acidic peaty matrix,
as evidenced by the substantial and parallel rise in pH, Ca²⁺, DIC, and CO₂ just after PVC-
MP and PVCₕCaCO₃ (CaCO₃+ pure PVC) addition (Appendix A Table A.2), followed by
subsequent decreases over time (Fig. 2). Release of CO₂ from CaCO₃ has been also reported
in amended peat soils accounting for up to 50% of the CO₂ emissions in short-term
incubation experiments (Biasi et al., 2008; Ronkainen et al., 2025). Additionally, a release of
C through the leaching of PVC polymer is also expected, as demonstrated previously
(Romera-Castillo et al., 2018), yet this aspect was not explicitly tested in our experiment.

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Conversely, the progressive increase in DOC and CH₄ (Fig. 2) over time suggests a potential
biological C source coming from the gradual activation of OM degradation. Increased levels
of DOC, CO₂ or CH₄ under MP exposure have been associated with enhanced soil enzyme
activities and/or shifts in microbial community composition (Barili et al., 2023; Chen et al.,

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2023). However, results may vary depending on the type of MP, soil characteristics, dosage, and duration of exposure (Wang et al., 2024). In peat-forming wetlands, microbial OM degradation is limited by harsh physicochemical conditions, including low pH, low oxygen availability, and elevated concentrations of phenolic compounds (Freeman et al., 2001; Limpens et al., 2008). In our experimental set up, oxygen was kept constantly low (<2 mg/L) in all treatments throughout both experiments hence OM degradation occurred primarily under anaerobic conditions. On the contrary, pH was clearly impacted by the PVC-MP addition, increasing significantly from ~4 in the initial peat matrix, to ~5.5 at 0.3%, ~6 at 3%, and ~7 at 30% of MP concentration. Changes in pH were correlated to the enhanced in other ions such as Ca⁺², Na⁺, Mg⁺², K⁺ in E1 (Appendix A Fig. A2) and they were significant in the three treatments of E2 - PVC, PVC-MP and PVCₚₐₚ₃ - at 3% and 30% concentrations. However, pH values were similarly more elevated in the PVC-MP and PVCₚₐₚ₃ treatments, suggesting that CaCO₃ played an important role in driving these changes (Table 1). This aligns with the expected effect of CaCO₃, as it is commonly used as a pH regulator in acidic soils (Biasi et al., 2008). Decomposition of OM can be accelerated even with small increase in pH, as demonstrated in Welsh acidic streams (Merrix et al., 2006). Additionally, pH is a strong modulator of bacterial assembly in soils (Rousk et al., 2010) and the enhanced degradation of OM may be linked to shifts in microbial community composition resulting from the pH increase. In our experiment, pH significantly influenced microbial community composition (Appendix A Fig. A3). For example, the relative abundance of *Acidobacteria* was negatively correlated with pH and consequently several of its ASVs decreased at higher PVC-MP concentrations (Appendix A Fig. A2, Appendix B Table B2) coinciding with a shift toward neutral pH. *Acidobacteria* is commonly a dominant taxon in acidic wetlands, and it is known for its association with slow C-degrading metabolism (Lin et al., 2012; Pankratov et al., 2011). Furthermore, the class *Clostridia*, *Nagativicutes*, and *Bacteroidia* were positively
480 correlated with pH and increased their abundances in the PVC-MP treatments (Fig. 3, 481 Appendix A Fig. A2). *Clostridia*, recognized as active fermenters (Pankratov et al., 2011), 482 may have significantly contributed to the enhanced OM degradation observed in PVC-MP 483 treatments. Additionally, the class *Bacteroidia* is related to the degradation of complex C 484 substrates and have been identified in marine plastic biofilms (Näkki et al., 2021; 485 Oberbeckmann and Labrenz, 2020), suggesting a potential role of the bacterial community in 486 the PVC-MP degradation.

487 Despite changes in pH and in microbial community composition supported the activation of 488 microbial activity and OM degradation, microbial metabolism in response to PVC-MP 489 showed contrasting evidence in our study. Hydrolases related to the degradation of cellulose 490 (B-GLU) and hemicellulose (B-XYL), as well as sulphate uptake (ARS), were strongly 491 inhibited in the 3% and 30% PVC-MP treatments (Fig. 2, Appendix A Fig A1). However, 492 lignin degradation (POX activity and qPCR results of bacterial Lacasse) and phosphorus 493 uptake (PHOS activity, except at the highest concentration of PVC-MP) seemed to be 494 activated, and bacterial biomass increased (Fig. 2, Table 1 and 3). Similar responses to MP 495 pollution have been reported for C- acquisition, P-acquisition and oxidative enzymes in a 496 recent meta-analysis (Li et al., 2023). Our results thus suggest that PVC-MP enhanced 497 microbial degradation of lignin-like compounds but reduced more labile compounds 498 degradation. Reduction of enzyme activity in soils has been linked to lower richness and 499 diversity of microbial communities in acid soils exposed to 5% of PVC-MP (Fei et al., 2020), 500 but alpha diversity indexes of Bacteria, Archaea or Fungi were not altered in our experiment, 501 despite the high MP concentration tested, suggesting other mechanisms involved. EEA 502 activity may also be suppressed under high concentrations of substrates, possibly due to 503 competitive interactions or enzyme down-regulation (Allison et al., 2014). In our experiment, 504 the increase in DOC, CO₂, TN and NH₄⁺ following the mixing of peat with PVC-MP
505 (Appendix A Table A2) suggests a substantial input of labile C and N, which fuels microbes
506 (Romera-Castillo et al., 2018). This readily available substrate may reduce the need for
507 certain C-degrading enzymes. However, it may also stimulate the activity of other enzymes,
508 such as phosphatase or lignin-degrading enzymes, to maintain stoichiometric ratios or by
509 priming effect, i.e. whereby increases in labile substrate inputs stimulate the decomposition
510 of more recalcitrant OM (Bengtsson et al., 2018). Other mechanisms potentially involved in
511 the reduction of the EAA, principally at higher PVC-MP concentrations, include pH
512 alterations that may interfere with microbial enzymatic performance (Puissant et al., 2019).
513 Changes in pH in our experiment were strongly modulated by CaCO₃, and a negative effect
514 on B-GLU under PVC₄CaCO₃ treatments was also observed (Table 2). Additionally, the toxicity
515 of other additives, such as phthalate plasticizers present in PVC (Zhu et al., 2022) may also
516 influence microbial metabolism. More experimentation is needed to clarify the relevance of
517 the possible mechanisms proposed. Finally, fungal community also play an important role in
518 OM degradation in peat soils (Thormann, 2006) and the reduced biomass and observed
519 changes associated to PVC-MP treatments (Fig 3, Table 3) might have also contributed to the
520 reduced fungal decomposer activity, as it has been observed in other soils polluted by
521 microplastics (Temporiti et al., 2022). Moreover, one of the taxa most favoured by PVC-MP
treatments was *Arthrobötrys* from the class *Orbiliomycetes*, which is known to coexist with
522 nematodes and act as a generalist predator (Yang et al., 2020). This suggests potential
523 bottom-up changes in the microbial food web associated with PVC-MP, which might have
524 also influenced C dynamics (Shi et al., 2023).
525

526 PVC-MP at concentrations of 3% and 30% also led to an increase in the CH₄ production.
527 This was expected, as microbial metabolism primarily occurred under low-oxygen conditions
528 in our microcosms. However, since the system was not completely closed, some gas
529 exchange with the atmosphere occurred. Consequently, we observed the stimulation of both
methanogenesis (*mcrA* gene) and methane mineralisation (*pmoA* gene). Previous research has similarly noted an increase in CH₄ production with PVC-MP, particularly at lower concentrations (0.25%), suggesting a potential inhibition of microbial activity at higher concentrations (up to 7%) (Chen et al., 2023; Wei et al., 2019). In our study, we observed the positive PVC-MP effect even in an elevated concentration of PVC-MP and observed that the presence of CaCO₃ within the PVC influenced CH₄ production (E2, Table 2). It has been demonstrated that CaCO₃ can serve as C source for hydrogenotrophic methanogenesis (Fiore et al., n.d.; Wang et al., 2018) which may help explain the increased methane production observed in our study. However, other plastic additives might have also played a role in the CH₄ response, as the impact was more pronounced with the PVC-MP than the PVC₄CO₃ treatment (Table 2). The activation of methanogenesis may have been also favoured by the diversification and increased abundances of methanogenic taxa following PVC-MP addition.
Methanogenic community went from the dominance of a single genus in the control treatment, *Methanobacterium*, to the dominance of the total archaeal community by four methanogenic genus in the PVC-MP treatments (*Methanobacterium*, *Methanoregula*, *Methanocella*, *Methanomassiliicoccus*). Additionally, we found a strong correlation between methane production and *Methanocellia* class (Appendix A, Fig. A.4). Most of these methanogens found in the peat matrix utilise the reduction of CO₂ with H₂ during the production of CH₄, a process typically favoured in systems where the degradation of organic matter is incomplete (Conrad, 2020) as in peat forming wetlands. It has been observed that hydrogenotrophic methanogenesis can be coupled with bacterial groups including *Acidobacteria* (the most abundant bacterial phylum in the initial and control treatment) or *Firmicutes* (dominant bacteria phylum at 30% of PVC-MP) in anaerobic OM degradation. These bacteria may produce substrates for hydrogenotrophic methanogenesis, such as H₂ and CO₂ (Wilmoth et al., 2021). In our study, a significant correlation was found between some
taxa of *Firmicutes* (*Negativicutes*, *Clostridia*) and methane production (Appendix A Fig A.4),
supporting the hypothesis of a couple C-degrading metabolism. Finally, other variables
potentially inhibiting CH₄ production are humic substances and low pH, directly or indirectly
through their effects on fermentation (Conrad, 2020; Ye et al., 2012). We observed a decrease
in the SUVA₂₅₄ index (indicative of lower concentrations of aromatic compounds) and
neutral pH at the higher concentration of PVC-MP (Fig. 2), which may have also contributed
to facilitate CH₄ production in PVC-MP amended peat soils.

Produced methane may be oxidized by methanotrophic and methylotrophic bacteria and
archaea (Serrano-Silva et al., 2014). We didn't found changes in the abundance of
methanotrophs but methanotrophic activity (*pmoA* gene qPCR results) increased at 3 and
30% of PVC-MP addition (Table 3). We also observed an important augmentation of
*Methyloversatilis* (Gammaproteobacteria), a recognised methylotroph (microorganisms
oxidizing methyl group compounds into CH₄ and CO₂), and a synergistic interaction may
occur between the methanotrophs and non-methane-utilizing methylotrophs (Rani et al.,
2021). All these results suggest that potentially part of the produced methane was oxidated in
our microcosms treated with PVC-MP.

571

572 **4.2. PVC-MP effects on N cycle**

N cycle was strongly altered by PVC-MP addition, as evidenced by the increase in NH₄⁺ and
TN in the peat matrix from the lowest concentration tested (0.3%). We did not evaluate all
the microbial routes of N compounds metabolism, yet we had evidence of an activation of the
first step of denitrification (increased *narG* gene abundance at 3% and 30% of PVC-MP,
Table 3) and no changes in nitrification (similar NO₃⁻ concentration despite strong increase in
NH₄⁺ and TN). Strong impact of MP on N cycle has been broadly reported, and some
mechanisms have been described, suggesting effects of MP on soil inorganic N are modulated by MP properties, experimental conditions, and soil properties (Huang et al., 2023; Wang et al., 2024; Xiang et al., 2023). For PVC-MP, results are not conclusive as for example some studies have reported an increase in $NH_4^+$ (Chen et al., 2023; Zhu et al., 2022) whilst others a decrease (Tong et al., 2023). In most cases, changes in N cycling bacteria or/and archaea are reported (Xiang et al., 2023). In our study, some shifts in microbial assembly were consistent with a reduction in nitrification. Members of the known ammonia-oxidizing archaea (AOA) adapted to low pH environments *Candidatus Nitrosotalea* (class *Nitrososphaeria*, included in the ancient phylum *Thaumarchaeota*) (Herbold et al., 2017) were the dominant archaeal taxa in the initial peat soil and control treatment. The increase in pH in PVC-MP treatments was negatively correlated with the abundance of the class *Nitrososphaeria* (Appendix A Fig. A.4), and members of the group 1.1c and *Nitrosotaleales* were dramatically reduced at neutral pH, consistent with previous observations in *Thaumarchaeota* (Tripathi et al., 2013). In addition to AOA, it has been found that bacteria contributed significantly to $NO_3^-$ formation in peatland forests where the pH was higher than 4.6. (Truu et al., 2020). However, in our experiment no ammonia-oxidizing bacteria were found even in PVC-MP treatments, where pH exceeded 5. Reduced ammonia-oxidizing microbial community might have limited nitrification and contribute to the accumulation of $NH_4^+$ in the peat matrix amended with PVC-MP. Similar results has been reported in a study on plasticized PVC-MP in acidic agricultural soils at lower MP concentrations (0.05%, 0.1%, 0.5%) (Shen et al., 2023), highlighting the relevance of soil pH and MP characteristics in shaping MP effects on N cycle (Wang et al., 2024).

Impact on N cycle was more marked and significant from the lower tested concentration (0.3%) in the treatment of PVC-MP than in the treatment with $PVC_{CaCO_3}$ (Table 2). This result suggests other additives in the PVC might have played a role, which aligns with the
results found by Zhu et al. (2022). These authors found that phthalate plasticizer released from MP was the main driver of the PVC-MP effects on N cycle, such as an increase in NH₄, urea decomposers, and nitrate reducers, but a decrease in NO₃ and nitrifiers (Zhu et al., 2022)

607

## 5. Conclusion and implications

Peat-forming wetlands, encompassing various ecosystems like peatlands, saltmarshes, ponds, and constructed wetlands, play a crucial role in the global C cycle and climate change mitigation efforts. While these ecosystems act as C sinks, they also have the potential to release significant amounts of CO₂ and methane (CH₄) when disturbed or polluted. MP pollution in wetlands originates from multiple sources including atmospheric deposition, waterborne transport, and direct disposal (Qian et al., 2020). Additionally, the widespread agricultural use of wetlands (Biasi et al., 2008; Page and Baird, 2016) increases the risk of MP pollution, posing significant threats to these ecosystems and exacerbating climate change feedback loops. Our study investigated the impact of PVC derived MP (PVC-MP) on nutrient cycling in peat-forming wetlands, with a particular focus on the role of calcium carbonate (CaCO₃), a common plastic additive. We found that PVC-MP significantly affected C and N cycling in peaty wetlands soils across all tested concentrations (0.3%, 3%, and 30%). PVC-MP altered water-extractable nutrient concentrations and GHG soil production, with CaCO₃ playing a mediating role. There effects were also driven by shifts in microbial structure and metabolism. PVC-MP increased CO₂ and CH₄ production through multiple mechanisms. CaCO₃ contributed to CO₂ release through its dissolution in the acidic peat matrix and acted as C source for a more diverse community of hydrogenotrophic methanogens (e.g., *Methanoregula*, *Methanocella*), thereby enhancing methanogenesis (*mcrA* gene). Additionally, PVC-MP altered the C-cycle by enhancing microbial degradation of lignin-like
compounds while reducing the activity of labile C-degrading enzymes, potentially leading to increased DOC release. Changes in OM degradation were associated with microbial community shifts driven by increased pH, Na⁺, and NH₄⁺ levels. Notably, Acidobacteria, a commonly abundant bacterial class in peaty wetlands, was largely replaced by Clostridia under PVC-MP treatments. PVC-MP also had a strong impact on the N cycle, although CaCO₃ appeared to play a more indirect role. Across all tested concentrations, NH₄⁺ levels increased, while NO₃⁻ remained stable, suggesting an inhibition of nitrification. This was likely due to a reduction in ammonia-oxidizing microbial communities (AOA, Candidatus Nitrosotalea), possibly driven by pH increases, which may have contributed to NH₄⁺ accumulation in PVC-MP-amended peat. To the best of our knowledge, this study is the first to explore the effect of CaCO₃ as a plastic additive on biogeochemical cycles in peat-forming wetlands. Our finding support a positive feedback loop between MP pollution and climate change (Chen et al., 2023; Chia et al., 2023). The significant role of CaCO₃ in altering C and N cycling provides novel insights into the mechanisms underlying MP-induced disruptions. Our findings shed light on a previously overlooked aspect of plastic pollution and may serve as a scientific and practical reference for the prevention and control of MP pollution, as well as risk assessment of global climate change feedback induced by MP.

## Acknowledgments

This paper was conducted as part of the project CARPLAST funding by Labex VOLTAIRE (ANR-10-LABX-100-01) and of the workpackage CORI of EURAD project that has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 847593. The authors would like to thank to Jocelyn Groussier for help in the laboratory work and to the GEOMIN platform (ISTO, UMR7327 ; GEOF, I.R. RéGEF) for the analyses and the technical assistance. We also thank Fabienne Battaglia for her support and advice during the development of this research.
653 **Authorship contribution**

654 JMG conceptualization, experimental design, laboratory work, formal analysis, writing –
655 original draft, review and editing, funding acquisition. AJ: conceptualization, experimental
656 design, laboratory work, data curation, writing – review and editing. NF: laboratory work.
657 HBZ: laboratory work. MC: laboratory work. CJ: experimental design, writing – review and
658 editing. CLM: conceptualization, experimental design, laboratory work, writing – review and
659 editing.

660 Declaration of generative AI and AI-assisted technologies in the writing process

661 During the preparation of this work the authors used ChatGPT in order to improve language
662 and readability. After using this tool/service, the authors reviewed and edited the content as
663 needed and take full responsibility for the content of the publication.

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931
**Figure 1.** Scheme of the experiments conducted to test the impact of PVC-MP on microbial OM degradation in peat-forming wetlands. E1= experiment 1 aimed to understand general PVC-MP effect on nutrient cycling; E2 = experiment 2 aimed to investigate influence of the additive CaCO₃. PVC = PVC pure, PVC-MP= MP of PVC from pipe, PVC<sub>CaCO3</sub>= PVC pure + CaCO3.

A) Experiment 1 (E1)

<figure><img src="image_3.png" /></figure>

B) Experiment 2 (E2)

<figure><img src="image_4.png" /></figure>

937

938

939

**Figure 2.** Biochemical properties of peat matrix over 91 days of the E1. Initial peat (time 0), control treatment (0% PVC), and PVC-MP treatments at 3% and 30% DW.

940

941
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Microbial community composition after 91 days of incubation in E1. NMDS of Archaea (A), Bacteria (B), and Fungi (C), initial community (time 0, gray light circles), control treatment (0% PVC, light gray squares), PVC-MP treatment at 3% (middle gray diamonds) and 30% (dark gray triangles). Class of Archaea (D), Bacteria (E), and Fungi (F) after 91 days of incubation in E1, initial community, control, 3% and 30% PVC-MP treatments.</figcaption></figure>
A) Archaea

<figure><img src="image_6.png" /></figure>

B)

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

C) Bacteria

<figure><img src="image_9.png" /></figure>

D)

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

E) Fungi

<figure><img src="image_12.png" /></figure>

F)

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>
<table><caption>**Table 1.** Mean (SEM) of the biochemical variables measured in E2 at day 26 (E2 is explained in figure 1).</caption><thead><tr><th rowspan="2"></th><th>Initial</th><th>Control</th><th colspan="3">PVC</th><th colspan="3">PVC-MP</th><th colspan="3">PVC<sub>CaCO3</sub></th></tr><tr><th>0%</th><th>0%</th><th>0.3%</th><th>3%</th><th>30%</th><th>0.3%</th><th>3%</th><th>30%</th><th>0.3%</th><th>3%</th><th>30%</th></tr></thead><tbody><tr><td>pH</td><td>4.34<br>(0.02)</td><td>5.57<br>(0.12)</td><td>5.77<br>(0.01)</td><td><strong>5.88</strong><br>(0.08)</td><td><strong>5.86</strong><br>(0.03)</td><td>5.76<br>(0.04)</td><td><strong>6.19</strong><br>(0.07)</td><td><strong>7.82</strong><br>(0.09)</td><td>5.75<br>(0.05)</td><td><strong>6.06</strong><br>(0.08)</td><td><strong>7.63</strong><br>(0.10)</td></tr><tr><td>DOC (mmol L<sup>-1</sup>)</td><td>1.37<br>(0.05)</td><td>2.72<br>(0.15)</td><td>2.56<br>(0.17)</td><td>2.60<br>(0.10)</td><td>2.48<br>(0.14)</td><td><strong>3.28</strong><br>(0.03)</td><td><strong>3.15</strong><br>(0.17)</td><td><strong>6.38</strong><br>(0.14)</td><td><strong>3.29</strong><br>(0.19)</td><td><strong>2.93</strong><br>(0.14)</td><td><strong>6.84</strong><br>(0.17)</td></tr><tr><td>TN (mmol L<sup>-1</sup>)</td><td>0.16<br>(0.04)</td><td>0.10<br>(0.003)</td><td>0.09<br>(0.01)</td><td>0.10<br>(0.004)</td><td>0.11<br>(0.004)</td><td><strong>0.14</strong><br>(0.004)</td><td><strong>0.16</strong><br>(0.01)</td><td><strong>0.65</strong><br>(0.002)</td><td>0.11<br>(0.01)</td><td>0.13<br>(0.01)</td><td><strong>0.64</strong><br>(0.02)</td></tr><tr><td>DIC (mmol L<sup>-1</sup>)</td><td>0.003<br>(0.001)</td><td>0.07<br>(0.01)</td><td>0.08<br>(0.004)</td><td>0.07<br>(0.004)</td><td>0.07<br>(0.001)</td><td>0.08<br>(0.002)</td><td>0.07<br>(0.02)</td><td><strong>3.40</strong><br>(0.41)</td><td>0.08<br>(0.001)</td><td><strong>0.13</strong><br>(0.003)</td><td><strong>4.19</strong><br>(0.04)</td></tr><tr><td>SUVA<sub>254</sub> (L mg<sup>-1</sup> m<sup>-1</sup>)</td><td>4.99<br>(0.77)</td><td>10.42<br>(0.52)</td><td>11.08<br>(0.74)</td><td>11.01<br>(0.42)</td><td>11.56<br>(0.61)</td><td>9.52<br>(0.10)</td><td>9.77<br>(0.55)</td><td><strong>2.03</strong><br>(0.04)</td><td>8.92<br>(0.71)</td><td>9.77<br>(0.55)</td><td><strong>1.83</strong><br>(0.01)</td></tr><tr><td>Na<sup>+</sup> (mmol L<sup>-1</sup>)</td><td>0.16<br>(0.01)</td><td>0.39<br>(0.04)</td><td>0.40<br>(0.03)</td><td>0.46<br>(0.01)</td><td><strong>0.52</strong><br>(0.04)</td><td>0.45<br>(0.02)</td><td>0.42<br>(0.02)</td><td><strong>0.76</strong><br>(0.04)</td><td><strong>0.59</strong><br>(0.03)</td><td>0.45<br>(0.003)</td><td><strong>0.56</strong><br>(0.01)</td></tr></tbody></table>
<table><tr><td>NH<sub>4</sub><sup>+</sup> (mmol L<sup>-1</sup>)</td><td>0.03<br>(0.02)</td><td>0.05<br>(0.003)</td><td>0.05<br>(0.003)</td><td>0.05<br>(0.01)</td><td>0.06<br>(0.001)</td><td><b>0.09</b><br>(0.01)</td><td><b>0.09</b><br>(0.01)</td><td><b>0.47</b><br>(0.01)</td><td>0.05<br>(0.003)</td><td><b>0.10</b><br>(0.01)</td><td><b>0.46</b><br>(0.01)</td></tr><tr><td>K<sup>+</sup> (mmol L<sup>-1</sup>)</td><td>0.05<br>(0.01)</td><td>0.05<br>(0.001)</td><td>0.05<br>(0.001)</td><td>0.05<br>(0.001)</td><td>0.06<br>(0.002)</td><td><b>0.07</b><br>(0.003)</td><td>0.06<br>(0.004)</td><td><b>0.18</b><br>(0.004)</td><td>0.06<br>(0.002)</td><td><b>0.06</b><br>(0.004)</td><td><b>0.18</b><br>(0.01)</td></tr><tr><td>Mg<sup>2+</sup> (mmol L<sup>-1</sup>)</td><td>0.03<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td><b>0.02</b><br>(0.001)</td><td><b>0.02</b><br>(0.001)</td><td><b>0.19</b><br>(0.001)</td><td><b>0.02</b><br>(0.001)</td><td><b>0.02</b><br>(0.001)</td><td><b>0.12</b><br>(0.001)</td></tr><tr><td>Ca<sup>2+</sup> (mmol L<sup>-1</sup>)</td><td>0.05<br>(0.001)</td><td>0.03<br>(0.001)</td><td>0.03<br>(0.001)</td><td>0.03<br>(0.001)</td><td>0.03<br>(0.001)</td><td><b>0.04</b><br>(0.002)</td><td><b>0.09</b><br>(0.001)</td><td><b>2.35</b><br>(0.02)</td><td><b>0.05</b><br>(0.002)</td><td><b>0.12</b><br>(0.02)</td><td><b>2.53</b><br>(0.003)</td></tr><tr><td>Cl<sup>-</sup> (mmol L<sup>-1</sup>)</td><td>0.06<br>(0.004)</td><td>0.20<br>(0.01)</td><td>0.19<br>(0.02)</td><td><b>0.24</b><br>(0.01)</td><td>0.23<br>(0.01)</td><td>0.22<br>(0.004)</td><td><b>0.24</b><br>(0.01)</td><td><b>0.29</b><br>(0.02)</td><td><b>0.28</b><br>(0.02)</td><td>0.23<br>(0.01)</td><td><b>0.30</b><br>(0.01)</td></tr><tr><td>SO<sub>4</sub><sup>2-</sup> (mmol L<sup>-1</sup>)</td><td>0.11<br>(0.01)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.005<br>(0.001)</td><td>0.01<br>(0.002)</td><td>0.01<br>(0.001)</td><td>0.005<br>(0.001)</td><td><b>0.01</b><br>(0.001)</td></tr><tr><td>NO<sub>3</sub><sup>-</sup> (mmol L<sup>-1</sup>)</td><td>0.04<br>(0.01)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td><td>0.01<br>(0.001)</td></tr><tr><td>CH<sub>4</sub> (µg C gDW<sup>-1</sup> d<sup>-1</sup>)</td><td>-0.003<br>(0.002)</td><td>-0.01<br>(0.01)</td><td>-0.01<br>(0.002)</td><td>0.003<br>(0.001)</td><td>-0.01<br>(0.002)</td><td>-0.01<br>(0.001)</td><td><b>0.01</b><br>(0.002)</td><td><b>2.65</b><br>(0.09)</td><td>-0.01<br>(0.01)</td><td>0.003<br>(0.001)</td><td><b>3.69</b><br>(0.32)</td></tr></table>
<table><tr><td>CO<sub>2</sub> (µg C gDW<sup>-1</sup> d<sup>-1</sup>)</td><td>33.77<br>(2.8)</td><td>29.23<br>(4.95)</td><td><b>18.88</b><br>(0.43)</td><td>22.99<br>(1.71)</td><td>22.12<br>(2.29)</td><td>26.34<br>(2.18)</td><td>29.98<br>(0.85)</td><td><b>64.80</b><br>(1.95)</td><td>24.99<br>(2.78)</td><td>26.38<br>(1.49)</td><td><b>69.47</b><br>(2.65)</td></tr><tr><td>B-GLU<br>(µmol MUF gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>2.10<br>(0.31)</td><td>1.77<br>(0.09)</td><td>1.52<br>(0.07)</td><td>2.02<br>(0.27)</td><td>1.52<br>(0.03)</td><td>1.87<br>(0.16)</td><td>1.74<br>(0.17)</td><td><b>0.28</b><br>(0.002)</td><td>2.10<br>(0.11)</td><td><b>1.27</b><br>(0.17)</td><td><b>0.22</b><br>(0.002)</td></tr><tr><td>PHOS<br>(µmol MUF gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>21.87<br>(1.31)</td><td>22.08<br>(0.76)</td><td>20.73<br>(0.61)</td><td>22.08<br>(0.60)</td><td><b>15.48</b><br>(1.04)</td><td>25.67<br>(1.97)</td><td><b>33.67</b><br>(5.36)</td><td><b>12.88</b><br>(0.39)</td><td><b>27.38</b><br>(0.69)</td><td><b>31.18</b><br>(2.11)</td><td><b>16.63</b><br>(0.44)</td></tr></table>

PVC = PVC pure, PVCp = PVC-MP from pipe, PVC<sub>CaCO3</sub> = PVC pure + CaCO3, DOC=Dissolved Organic Carbon, B-GLU = β-1,4-glucosidase, PHOS = Phosphatase, DW= dry weight of peat matrix. In bold the significant differences (p < 0.05) between treatment and control at 26 days.
<table><caption>**Table 2.** *F* and (*p*) values of mixed linear models analyses of biochemical variables measured in the peat matrix over 91 days of incubation in E1 (explained in figure 1).</caption><thead><tr><th></th><th>Time</th><th>ConcMP</th><th>Time:ConcMP</th></tr></thead><tbody><tr><td>pH</td><td>21.8 (&lt;0.001)</td><td>773 (&lt;0.001)</td><td>4.0 (0.004)</td></tr><tr><td>DOC (mmol L<sup>-1</sup>)</td><td>250.3 (&lt;0.001)</td><td>146.6 (&lt;0.001)</td><td>38.5 (&lt;0.001)</td></tr><tr><td>TN (mmol L<sup>-1</sup>)</td><td>5.4 (0.004)</td><td>907.1 (&lt;0.001)</td><td>5.3 (&lt;0.001)</td></tr><tr><td>DIC (mmol L<sup>-1</sup>)</td><td>34.8 (&lt;0.001)</td><td>255.1 (&lt;0.001)</td><td>7.3 (&lt;0.001)</td></tr><tr><td>SUVA254 (L mg<sup>-1</sup> m<sup>-1</sup>)</td><td>31.3 (&lt;0.001)</td><td>224.1 (&lt;0.001)</td><td>5.6 (&lt;0.001)</td></tr><tr><td>Na<sup>+</sup> (mmol L<sup>-1</sup>)</td><td>32.2 (&lt;0.001)</td><td>34.5 (&lt;0.001)</td><td>3.6 (0.007)</td></tr><tr><td>NH<sub>4</sub><sup>+</sup> (mmol L<sup>-1</sup>)</td><td>2.7 (0.06)</td><td>48.8 (&lt;0.001)</td><td>0.8 (0.5)</td></tr><tr><td>K<sup>+</sup> (mmol L<sup>-1</sup>)</td><td>9.9 (&lt;0.001)</td><td>95.0 (&lt;0.001)</td><td>1.6 (0.2)</td></tr><tr><td>Mg<sub>2</sub><sup>+</sup> (mmol L<sup>-1</sup>)</td><td>6.2 (0.002)</td><td>210.5 (&lt;0.001)</td><td>3.7 (0.006)</td></tr><tr><td>Ca<sub>2</sub><sup>+</sup> (mmol L<sup>-1</sup>)</td><td>17.9 (&lt;0.001)</td><td>1983.6 (&lt;0.001)</td><td>6.9 (&lt;0.001)</td></tr><tr><td>Cl<sup>-</sup> (mmol L<sup>-1</sup>)</td><td>20.7 (&lt;0.001)</td><td>2.3 (0.1)</td><td>4.4 (0.002)</td></tr><tr><td>SO<sub>4</sub><sup>2-</sup> (mmol L<sup>-1</sup>)</td><td>197.8 (&lt;0.001)</td><td>1.51 (0.2)</td><td>15.6 (&lt;0.001)</td></tr><tr><td>NO<sub>3</sub><sup>-</sup> (mmol L<sup>-1</sup>)</td><td>14.1 (&lt;0.001)</td><td>2.3 (0.1)</td><td>1.1 (0.4)</td></tr><tr><td>B-GLU (µmol MUF gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>22.4 (&lt;0.001)</td><td>663.1 (&lt;0.001)</td><td>21.6 (&lt;0.001)</td></tr><tr><td>ARS (µmol MUF gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>6.0 (0.002)</td><td>123.1 (&lt;0.001)</td><td>1.4 (0.3)</td></tr><tr><td>B-XYL (µmol MUF gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>14.4 (&lt;0.001)</td><td>114.9 (&lt;0.001)</td><td>16.9 (&lt;0.001)</td></tr><tr><td>NAG (µmol MUF gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>5.3 (0.004)</td><td>111.7 (&lt;0.001)</td><td>3.3 (0.01)</td></tr><tr><td>PHOS (µmol MUF gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>4.8 (0.007)</td><td>238.9 (&lt;0.001)</td><td>14.8 (&lt;0.001)</td></tr><tr><td>POX (µmol DICQ gDW<sup>-1</sup> h<sup>-1</sup>)</td><td>1.9 (0.1)</td><td>3.2 (0.05)</td><td>1.3 (0.3)</td></tr><tr><td>CO<sub>2</sub>-aer (µg C gDW<sup>-1</sup> d<sup>-1</sup>)</td><td>21.5 (&lt;0.001)</td><td>56.9 (&lt;0.001)</td><td>5.3 (&lt;0.001)</td></tr><tr><td>CO<sub>2</sub>-oxic (µg C gDW<sup>-1</sup> d<sup>-1</sup>)</td><td>67.2 (&lt;0.001)</td><td>192.4 (&lt;0.001)</td><td>38.7 (&lt;0.001)</td></tr><tr><td>CH<sub>4</sub>-aer (µg C gDW<sup>-1</sup> d<sup>-1</sup>)</td><td>40.0 (&lt;0.001)</td><td>90.7 (&lt;0.001)</td><td>17.2 (&lt;0.001)</td></tr><tr><td>CH<sub>4</sub>-oxic (µg C gDW<sup>-1</sup> d<sup>-1</sup>)</td><td>65.8 (&lt;0.001)</td><td>96.0 (&lt;0.001)</td><td>20.6 (&lt;0.001)</td></tr></tbody></table>
B-GLU=β-1,4-glucosidase, B-XYL=β-1,4-xylosidase, ARS = arylsulfatase, NAG =β-1,4-N-acetyl-glucosaminidase, PHOS=acid phosphatase, and POX= phenol oxidase. Significant differences (p < 0.05) in bold.

.
<table><caption>**Table 3.** Mean (SEM) of the target gens abundances based on qPCR of gDNA (potential activity) and cDNA (measured activity) for days 5 and 91 of the E1 (E1- explained in figure 1). Gene abundance is given in copies DW⁻¹ of peat matrix. Significant differences in letters.</caption><thead><tr><th rowspan="2"></th><th colspan="3">Day 5</th><th colspan="3">Day 91</th></tr><tr><th>0%</th><th>3%</th><th>30%</th><th>0%</th><th>3%</th><th>30%</th></tr><tr><th colspan="7">gDNA</th></tr></thead><tbody><tr><td>Bacteria (16S)</td><td>7.9E+10<sup>a</sup><br>(7.8E+09)</td><td>9.0E+10<sup>a</sup><br>(3.8E+09)</td><td>8.4E+10<sup>a</sup><br>(4.0E+09)</td><td>7.2E+10<sup>B</sup><br>(1.2E+10)</td><td>9.5E+10<sup>A</sup><br>(1.6E+09)</td><td>9.0E+10<sup>AB</sup><br>(1.2E+10)</td></tr><tr><td>Archaea (16S)</td><td>1.4E+09<sup>ab</sup><br>(1.0E+08)</td><td>1.8E+09<sup>a</sup><br>(2.1E+08)</td><td>8.6E+08<sup>b</sup><br>(1.3E+08)</td><td>1.6E+09<sup>A</sup><br>(3.3E+08)</td><td>1.7E+09<sup>A</sup><br>(9.2E+07)</td><td>7.3E+08<sup>B</sup><br>(8.8E+07)</td></tr><tr><td>Fungi (18S)</td><td>4.7E+10<sup>a</sup><br>(4.9E+09)</td><td>5.2E+10<sup>a</sup><br>(6.7E+09)</td><td>3.4E+10<sup>b</sup><br>(3.4E+09)</td><td>1.2E+11<sup>A</sup><br>(9.2E+09)</td><td>5.6E+10<sup>C</sup><br>(6.4E+09)</td><td>9.2E+10<sup>B</sup><br>(8.1E+09)</td></tr><tr><td>Denitrification<br>(NarG)</td><td>1.8E+09<sup>ab</sup><br>(1.9E+08)</td><td>2.1E+09<sup>a</sup><br>(4.3E+07)</td><td>1.3E+09<sup>b</sup><br>(5.4E+07)</td><td>1.5E+09<sup>B</sup><br>(2.7E+08)</td><td>2.1E+09<sup>AB</sup><br>(7.2E+07)</td><td>2.7E+09<sup>A</sup><br>(5.7E+08)</td></tr><tr><td>Methanogenesis<br>(mcrA)</td><td>1.9E+07<sup>a</sup><br>(1.7E+06)</td><td>2.8E+07<sup>a</sup><br>(2.5E+06)</td><td>1.8E+07<sup>a</sup><br>(5.9E+05)</td><td>3.7E+07<sup>AB</sup><br>(7.7E+06)</td><td>3.6E+07<sup>B</sup><br>(3.0E+06)</td><td>6.0E+07<sup>A</sup><br>(1.3E+07)</td></tr><tr><td>Methanothrophy<br>(pmoA)</td><td>1.3E+08<sup>a</sup><br>(1.2E+07)</td><td>1.7E+08<sup>a</sup><br>(8.4E+06)</td><td>9.5E+07<sup>a</sup><br>(1.4E+06)</td><td>9.3E+07<sup>B</sup><br>(1.3E+07)</td><td>1.6E+08<sup>AB</sup><br>(4.1E+06)</td><td>2.6E+08<sup>A</sup><br>(9.3E+07)</td></tr><tr><td>Lacasse bacteria</td><td>1.2E+09<sup>b</sup><br>(1.2E+08)</td><td>2.0E+09<sup>a</sup><br>(1.7E+08)</td><td>9.1E+08<sup>b</sup><br>(9.2E+07)</td><td>1.4E+09<sup>A</sup><br>(2.7E+08)</td><td>1.9E+09<sup>A</sup><br>(6.0E+07)</td><td>7.8E+08<sup>B</sup><br>(2.0E+08)</td></tr></tbody></table>
cDNA

<table><tr><td>Denitrification<br>(NarG)</td><td>3.2E+05<sup>a</sup><br>(1.7E+05)</td><td>8.9E+05<sup>a</sup><br>(5.5E+05)</td><td>7.8E+06<sup>a</sup><br>(4.7E+06)</td><td>3.1E+04<sup>B</sup><br>(4.5E+02)</td><td>7.5E+05<sup>AB</sup><br>(2.1E+05)</td><td>1.8E+06<sup>A</sup><br>(6.0E+05)</td></tr><tr><td>Methanogenesis<br>(mcrA)</td><td>3.6E+04<sup>a</sup><br>(1.1E+04)</td><td>4.2E+05<sup>a</sup><br>(2.5E+05)</td><td>2.4E+04<sup>a</sup><br>(2.7E+03)</td><td>6.1E+04<sup>B</sup><br>(3.0E+04)</td><td>1.6E+05<sup>B</sup><br>(8.1E+04)</td><td>1.7E+06<sup>A</sup><br>(7.3E+05)</td></tr><tr><td>Methanothrophy<br>(pmoA)</td><td>9.9E+04<sup>a</sup><br>(4.1E+04)</td><td>6.1E+04<sup>a</sup><br>(2.4E+04)</td><td>2.4E+04<sup>a</sup><br>(2.7E+03)</td><td>3.1E+04<sup>B</sup><br>(4.5E+02)</td><td>4.7E+04<sup>B</sup><br>(2.3E+04)</td><td>1.6E+06<sup>A</sup><br>(5.2E+05)</td></tr><tr><td>Lacasse bacteria</td><td>7.4E+04<sup>a</sup><br>(2.9E+04)</td><td>5.5E+04<sup>a</sup><br>(1.8E+04)</td><td>2.4E+04<sup>a</sup><br>(2.7E+03)</td><td>3.1E+04<sup>B</sup><br>(4.5E+02)</td><td>7.8E+04<sup>B</sup><br>(3.2E+04)</td><td>1.6E+06<sup>A</sup><br>(7.7E+05)</td></tr></table>