Peatlands store a substantial fraction of the global soil carbon pool. Widespread drainage and land-use change have accelerated peat decomposition, while current restoration efforts aim to slow or reverse peat carbon oxidation and associated greenhouse gas emissions through rewetting. Understanding when and to what extent rewetting restores carbon sequestration and long-term peat accumulation remains a key scientific and management challenge.

Over recent decades, substantial progress has been made in identifying the biogeochemical controls on peat carbon turnover in rewetted systems. Water table dynamics, hydrological connectivity, redox conditions, substrate availability, nutrient status, and vegetation composition jointly regulate microbial processes driving organic matter decomposition and carbon fluxes. Yet, key questions remain: what really drives carbon turnover in peatlands? Is it “the overriding role of the water table”, the “iron gate” of mineral interactions, or the “iron wheel”? Could there even be a single enzyme controlling global carbon storage (Wen et al., 2019)? These questions highlight how peat carbon cycling defies simple explanations and directly challenges long-standing paradigms. Classical concepts emphasizing intrinsic substrate recalcitrance, single inhibitory controls (e.g., phenolics or water table position), or strictly separated aerobic–anaerobic microbial pathways fail to capture the complexity of carbon stabilization and turnover observed in rewetted peatlands (Zak et al., 2019). Instead, emerging evidence points to a network of interacting, context-dependent processes, including microbial community turnover, mineral–organic interactions, and dynamic redox condition changes, underpinning peat carbon persistence.

Yet, these mechanisms are typically studied at micro- to plot scales, while restoration success and climate feedbacks are evaluated at ecosystem to landscape scales, posing persistent challenges for upscaling. In this contribution, we synthesize current insights into carbon cycling in rewetted riparian peatlands by explicitly linking microbial and biogeochemical controls on carbon decomposition with restoration approaches aimed at managing carbon fluxes. Emphasis is placed on spatial and temporal heterogeneity in peat properties, hydrology, and microbial functioning, and on how this variability propagates uncertainty in carbon balance assessments and model predictions.

By integrating process-based understanding with measurements and modeling perspectives, both recent advances and remaining knowledge gaps in predicting peat carbon cycling under restoration will be highlighted. Re-assessing prevailing paradigms and strengthening cross-scale linkages are essential for designing effective rewetting strategies.

References

Wen, Y., Zang, H., Ma, Q., Evans, C. D., Chadwick, D. R., & Jones, D. L. (2019). Is the ‘enzyme latch’or ‘iron gate’the key to protecting soil organic carbon in peatlands?. Geoderma, 349, 107-113.

Zak, D., Roth, C., Unger, V., Goldhammer, T., Fenner, N., Freeman, C., & Jurasinski, G. (2019). Unraveling the importance of polyphenols for microbial carbon mineralization in rewetted riparian peatlands. Frontiers in Environmental Science, 7, 147.

How to cite: Zak, D., Jurasinski, G., Christiansen, J., Liebner, S., Petersen, R., Audet, J., Vroom, R., and Hermansen, N.: The complexity of carbon cycling in peatlands: a biogeochemical perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17613, https://doi.org/10.5194/egusphere-egu26-17613, 2026.

Northern peatlands are major carbon sinks, but their response to warming is difficult to predict because carbon uptake depends on complex interactions between climate, vegetation and drainage. We tested whether the composition of dissolved organic matter (DOM) in peat pore water reflects the biogeochemical functioning of the system and, therefore, can predict the carbon sink response to increased temperature. Using 16 peatland mesocosms subjected to contrasting climatic and hydrological conditions, we measured noon-time CO₂ exchange and analyzed DOM optical properties. Interaction forest models were used to predict carbon balance from peatland characteristics combined with DOM composition data. The CO₂ sink strengthened with warming in mesocosms with low DOM aromaticity, marked by high protein-like and microbially derived fluorescence, but remained weak when DOM was more aromatic. These results show that DOM composition is a sensitive indicator of peatland carbon balance under warming and can improve predictions of future carbon sink behavior.

How to cite: Berggren, M., Salimi, S., Tafazoli, M., and Scholz, M.: Dissolved organic matter composition predicts the carbon sink in a northern peatland warming experiment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20511, https://doi.org/10.5194/egusphere-egu26-20511, 2026.

Permafrost peatlands represent a large organic carbon stock and are currently a net carbon sink. However, some permafrost regions will develop anoxic conditions due to soil subsidence and waterlogging in the future. Under these conditions, it is estimated that methane (CH₄) emissions will increase due to the higher availability of newly mobilized dissolved organic matter (DOM) for microorganisms. However, little attention has been given to redox-active functional groups within DOM, which could also play a role in lowering CH₄ emissions. On the one hand, oxidized redox-active DOM could suppress methanogenesis thermodynamically, while on the other hand it could act as an electron acceptor for anaerobic CH₄ oxidation (AOM). Both processes would decrease net CH₄ release. However, the change in redox-active moieties in DOM across thaw in permafrost peatlands and their role in AOM have not been determined yet. In this project, we therefore aim (i) to quantify the changes in abundance and oxidation state of redox-active DOM along a thaw gradient and (ii) to determine the effect of oxidized redox-active DOM on AOM. To achieve this, we collected porewater samples over four depths (10-40 cm) across multiple thaw stages during July and September 2025 in a thawing permafrost peatland in Sweden (Stordalen Mire, Abisko). We analyzed the electron accepting and donating capacity of the anoxic porewater via mediated electrochemical reduction and oxidation, respectively. We found that the electron accepting capacity attributable to DOM significantly decreases from recently thawed to fully thawed sites (from 1.68±0.65 to 0.77±0.58 mmol e^- g^-1 C^-1, p<0.01). Further, mean electron donating capacity attributable to DOM was positively correlated to the average CH₄ flux per site (R=0.53, p<0.05), suggesting that more reduced redox-active DOM co-occurs with a higher CH₄ release. Additionally, microcosm experiments with water-extracted DOM from the peat and ¹³C-labeled CH₄ were performed in order to quantify the rates of methane oxidation in the presence and absence of redox-active DOM. We used a combination of electrochemical, isotope-tracing and molecular biology techniques to track the reduction of amended DOM, production of ¹³C-CO₂ and the change in abundance of methane-oxidizing microorganisms. Overall, this work will help to assess the importance of redox-active DOM for CH₄ cycling in thawing permafrost peatlands.

How to cite: Voggenreiter, E., Hahn, Z., Valenzuela, E. I., Hudson, J., Kappler, A., and van Grinsven, S.: Role of redox-active dissolved organic matter for methane cycling in thawing permafrost peatlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5304, https://doi.org/10.5194/egusphere-egu26-5304, 2026.

Peatlands are globally important sources and sinks of methane (CH₄), yet the extent to which land-use change alters the balance between methanogenesis and methane oxidation across peatland types remains poorly constrained. Here, we quantify potential methane production and aerobic methane oxidation across 27 peatland sites within the EU Biodiversa+ project network, spanning Estonia, Finland, Germany, and Czechia and encompassing pristine, drained, and rewetted bogs and fens.

We combined laboratory incubation assays with molecular approaches to assess methane cycling potential in both the aerobic peat layer and below the water table. Potential CH₄ production and oxidation rates were measured under controlled conditions, alongside quantitative PCR targeting methanogenic (mcrA), methanotrophic (pmoA), and total bacterial (16S rRNA) genes. Shotgun metagenomics and 16S rRNA gene sequencing were used to explore the genomic potential for methane oxidation and to identify microbial taxa involved.

Preliminary results indicate that pristine peatlands exhibit the highest potential rates of both methane production and oxidation. Drained sites show strongly reduced methanogenic potential, while rewetted sites display partial recovery, with rates generally remaining lower than in pristine systems. Higher methane oxidation rates in long-term rewetted sites (>15 years) suggest that functional recovery may increase with time since rewetting. When separated by peatland type, bogs show higher methane cycling potentials than fens across all land-use categories.

Pristine peatlands consistently showed highest methanogen gene abundances compared to rewetted and drained, particularly in the anaerobic peat layer. Methanotrophic gene abundances were highest in pristine peatlands in the aerobic layer; however, anaerobic layers of rewetted and drained peatlands harbored higher methanotrophic communities than in their aerobic layers. This suggests that methanotrophic communities in managed peatlands may establish deeper in the peat profile, potentially in response to oxygenic microsites or dynamic redox conditions. In rewetted and drained sites, pmoA gene abundance explained ~20% of the variation in methane oxidation rates, and mcrA explained ~10% in rewetted sites.

Overall, these findings suggest that drainage substantially suppresses methanogenic potential, while rewetting promotes partial functional recovery, particularly in bog systems and on timescales of at least decades. Integrating process-based and molecular data provides new insight into how land-use change shapes peatland methane cycling.

How to cite: Zivkovic, T., Deinert, S., Peltoniemi, K., Hultman, J., Korrensalo, A., Hájek, T., Urbanová, Z., Truu, J., Truu, M., Kull, A., and Liebner, S.: Land-use effects on microbial methane dynamics across European peatlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18049, https://doi.org/10.5194/egusphere-egu26-18049, 2026.

Peatlands, known to be important carbon sinks, have been transformed into sources of carbon due to human activities, contributing around 1 GtCO₂ equivalents annually to global emissions. Denmark's Green Deal aims to restore 100,000 hectares of peatlands by 2030 to mitigate these emissions, with studies indicating that rewetting drained peatlands could significantly reduce greenhouse gas emissions. Microbial communities play a central role in peatland carbon cycling, driving the production of CO₂ and CH₄ through decomposition. Moreover, microbial communities are sensitive to changes in moisture conditions, particularly during dry and rewetting cycles. Previous studies show that CO₂ rose during drought but returned to control levels during rewetting, while CH₄ fluxes fell and remained suppressed throughout the rewetting period. Moreover, it has been found that microbial communities differed to a lesser extent between drained and rewetted peatland, than in drained and undrained peatlands, highlighting the importance of restoration.

Our aim in this study was to evaluate peatland restoration effectiveness in carbon sequestration and to improve the understanding of microbial controls on carbon dynamics in these ecosystems. To achieve this, we monitored CO₂ and CH₄ fluxes in restored and unrestored peatlands during spring and summer 2025, alongside assessments of microbial activity and community composition.

Preliminary results indicate that raising the water table in degraded peatlands reduces both CO₂ and CH₄ emissions, suggesting improved carbon storage following restoration. Despite decades of drainage, both sites retained high organic carbon stocks. Bacterial community composition differed more strongly between restored and unrestored sites than between seasons, and topsoil communities showed greater divergence from mid- and subsoil layers. Microbial activity analyses revealed that anoxic conditions limited bacterial growth, whereas fresh litter inputs and elevated temperatures stimulated it.

These findings deepen our understanding of how restoration influences peatland carbon processes and microbial ecology. By identifying conditions that promote carbon storage, this research supports the development of management strategies that enhance peatlands’ capacity to function as effective carbon sinks, contributing to climate change mitigation.

How to cite: Cruz Paredes, C., Olvasstovu Midjord, K., Aguilar Vilar, C., and Herzog, S.:  Impact of peatland restoration on CO2 and CH4 emissions and microbial communities , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9827, https://doi.org/10.5194/egusphere-egu26-9827, 2026.

Peat soils store a disproportionate share of terrestrial carbon, yet agricultural drainage accelerates peat oxidation, converting long-term carbon sinks into substantial sources of greenhouse gases (GHGs). We conducted a two-year mesocosm experiment to quantify how water table level (WTL) and organic amendment type interactively regulate peat oxidation and emissions of CO₂, CH₄, and N₂O under agricultural management. Three hydrological regimes were applied over 730 days: permanently saturated conditions (WTL 0 cm) during the first year, moderate drainage (WTL 20 cm) during the second year, and a continuously deeply drained business-as-usual control (WTL 40 cm). Each regime was combined with five amendments such as Miscanthus biochar, Miscanthus chips, paper waste, biosolids, and cereal straw and an unamended control.

Moderate drainage (WTL 20 cm) emerged as a critical threshold that constrained peat oxidation while strongly suppressing methanogenesis. Although CO₂ emissions increased relative to saturated conditions, CH₄ fluxes declined by more than 90% compared with WTL 0 cm, where CH₄ dominated total GHG output. This shift resulted in a 27-35% reduction in net CO₂ -equivalent emissions, demonstrating a clear climate benefit of maintaining a moderately lowered water table. Labile, low C:N amendments (biosolids and straw) intensified CO₂ and N₂O emissions under WTL 20 cm, reflecting rapid microbial activation following oxygen exposure and enhanced peat decomposition. In contrast, Miscanthus biochar consistently reduced GHG emissions across hydrological conditions, lowering cumulative CO₂-equivalent emissions by up to 52% relative to the deeply drained control after 730 days. chemical recalcitrance of biochar, high microporosity, and redox-buffering capacity promoted CH₄ oxidation, limited N₂O production, and stabilized native peat carbon against oxidative loss.

Our findings demonstrate that peat oxidation and associated GHG emissions can be substantially mitigated through the combined application of moderate water table regulation and stable, recalcitrant organic amendments. Integrating WTL management at -20 cm with biochar addition represents a robust, climate smart strategy for reducing emissions from agricultural peatlands while preserving long-term soil carbon stocks.

How to cite: Peduruhewa, J. H., Rhymes, J. M., Evans, C., Chadwick, D., and Jones, D.: Water table regulation and biochar amendments govern peat oxidation and greenhouse gas emissions in agricultural peatlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5981, https://doi.org/10.5194/egusphere-egu26-5981, 2026.

Globally, peatlands store one third of global soil carbon. Peatlands accumulate carbon under waterlogged anoxic conditions, but drainage increases oxygen availability causing peatland degradation. Therefore, drainage is responsible for ~2% of anthropogenic greenhouse gas (GHG) emissions. GHG emission estimates from drained peatlands are often based on hydrological proxies. In this research, we propose to improve these estimates by adding the redox potential that controls peat degradation more directly compared to hydrological proxies. We quantified in-situ soil production rates of CO2 and CH4 by combining in-situ redox potential measurements with corresponding laboratory basal respiration rates scaled to in-situ soil temperature. Using this approach, we estimated soil CO2 and CH4 production rates for 12 field sites over multiple years and validated these estimates by comparing them to aboveground Net Ecosystem Carbon Balance (NECB) measurements. We show that (1) laboratory incubation measurements can serve as a strong basis to estimate field-scale CO2 and CH4 emissions, (2) compared to water table depth, the redox potential is a more reliable parameter for estimating soil CO2 production, and (3) anaerobic respiration processes contribute substantially to peat decomposition and soil CO2 production.  Our results provide valuable new insights for assessing GHG emissions from drained peatlands and enhances our understanding of aerobic and anaerobic peat decomposition processes. 

How to cite: van der Velde, Y., Boonman, J., Tolunay, D., Keuskamp, J., Heffernan, L., Buzacott, A., Harpenslager, S. F., van Dijk, G., and Hefting, M.: Anaerobic decomposition contributions to greenhouse gas emissions of agriculturally used peatlands. , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14965, https://doi.org/10.5194/egusphere-egu26-14965, 2026.

Agricultural use of peat soils results in large amounts of GHG emissions. Drainage of peat soils leads to mineralisation and thus CO₂ emissions. Wet conditions and copious amounts of carbon in fertilised peat soils generally also lead to high N₂O emissions. Water infiltration systems (WIS) could regulate the groundwater table (GWT), allowing agricultural use of these soils while at the same time reducing peat oxidation, CO₂-emissions and land subsidence. These changes to the groundwater will also affect N cycling processes yet it remains unclear how N₂O emissions will be affected. We hypothesised that 1) active drainage reduces N₂O emissions due to increased GWT stability, 2) a high GWT reduced N₂O emissions due to limited mineralisation and 3) active drainage prevents large peaks in N₂O emissions otherwise expected from fertilisers with a high mineral N content.  

In this study, we conducted two one-year field studies. In the first study (2024), we tested how N₂O emissions from peat soils were affected by grazing (urine and dung patches) and groundwater management (GWT and WIS). Treatments consisted of urine, dung patches and compaction or combinations thereof. These were laid out in a full factorial block design on 4 field parcels. In the second study (2025) we tested how different fertilisers affect N₂O emissions from peat soils under two GWTs. Treatments consisted of an unfertilised control, standard synthetic fertilisers (CAN and Urea), Urea + urease- or nitrification inhibitor, cattle slurry and manure derived bio-based fertilisers (liquid and solid fraction of cattle slurry and ammonium sulphate). In both studies N₂O emissions were measured using a closed chamber technique and gas monitor. In addition, grass yield and nitrogen uptake were recorded.

In 2024, N₂O emissions were highest from all treatments containing urine patches. N₂O emissions were highest from the field with a GWT. This could be explained by higher nitrogen mineralisation of peat, resulting in a high carbon availability for denitrification and thus increased N₂O fluxes. Surprisingly we did not see an effect of WIS on N₂O emissions. In 2025 GWT did not affect N₂O emissions, yet crop N uptake was higher from the field with a low GWT. Emissions from ammonium sulphate (1% of applied N) were highest compared to the other fertilisers. Surprisingly all other treatments resulted in similarly low N₂O emissions (<0.5%) with no effect of nitrification or urease inhibitor. Perhaps conditions such as temperature and precipitation inhibited emissions in 2025.

How to cite: Porre, R., Ros, M., Blondeau, E., and Velthof, G.: N2O emissions from fertilised peat soils under different water infiltration systems and groundwater levels, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20061, https://doi.org/10.5194/egusphere-egu26-20061, 2026.

Advanced process-oriented models can reliably predict emissions of carbon containing greenhouse gases (CO₂ and CH₄) from both peatlands and arable soils. However, changes in land use, such as the conversion of peatlands into arable land or grassland following drainage, or the rewetting of drained peatlands, make it challenging for a single model to simulate soil processes and greenhouse gas emissions accurately across such different conditions.

We evaluated the LandscapeDNDC (LDNDC) model (Kraus et al., 2015) by comparing its simulations with field measurements of soil properties and CO₂ and CH₄ exchange rates (Eickenscheidt et al., 2015; Hommeltenberg et al., 2015). The default distribution of soil organic carbon (SOC) into pools with different decomposability, which is typically initialized in models based on the C:N ratio of soil organic matter (SOM), was ineffective for soils with a high organic matter content (>10% organic C). To address this, we distributed SOC into particulate and mineral-associated fractions (POM and MAOM) based on the concept of Lavallee et al (2020). Furthermore, we divided the MAOM into fast- and slow-decomposable pools, according to the C:N ratio of total organic matter (OM). The initial fraction of POM in total OM was derived from the total C content using the function proposed by Rühlmann (2020). Incorporating these changes into LDNDC’s soil biochemistry module improved agreement with observations and resolved the problem of underestimating ecosystem respiration in drained peatlands used for grassland or crop production. The improved initialization of SOC pools in the LDNDC model should enable more precise simulation of soil C stocks and GHG emissions at regional level, where soils with a wide range of SOC content need to be considered simultaneously.

References

Eickenscheidt, T., Heinichen, J., Drösler, M., 2015. The greenhouse gas balance of a drained fen peatland is mainly controlled by land-use rather than soil organic carbon content. Biogeosciences 12, 5161–5184. https://doi.org/10.5194/bg-12-5161-2015

Hommeltenberg, J., Mauder, M., Drösler, M., Heidbach, K., Werle, P., Schmid, H.P., 2014. Ecosystem scale methane fluxes in a natural temperate bog-pine forest in southern Germany. Agricultural and Forest Meteorology 198–199, 273–284. https://doi.org/10.1016/j.agrformet.2014.08.017

Kraus, D., Weller, S., Klatt, S., Haas, E., Wassmann, R., Kiese, R., Butterbach-Bahl, K., 2015. A new LandscapeDNDC biogeochemical module to predict CH₄ and N₂O emissions from lowland rice and upland cropping systems. Plant Soil 386, 125–149. https://doi.org/10.1007/s11104-014-2255-x

Lavallee, J.M., Soong, J.L., Cotrufo, M.F., 2020. Conceptualizing soil organic matter into particulate and mineral-associated forms to address global change in the 21st century. Global Change Biology 26, 261–273. https://doi.org/10.1111/gcb.14859

Ruehlmann, J., 2020. Soil particle density as affected by soil texture and soil organic matter: 1. Partitioning of SOM in conceptional fractions and derivation of a variable SOC to SOM conversion factor. Geoderma 375, 114542. https://doi.org/10.1016/j.geoderma.2020.114542

How to cite: Blagodatsky, S., Kraus, D., Braumann, F., Klatt, J., Drösler, M., Kiese, R., and Sheer, C.: Simulation of CO2 and CH4 emissions from peatlands and organic soils: an improvement of SOC pool initialization in LDNDC model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11059, https://doi.org/10.5194/egusphere-egu26-11059, 2026.

Peat soil degradation in the Netherlands contributes an estimated 4.6–7 Mt CO₂ annually, accounting for approximately 3% of national greenhouse gas emissions. In response, the Dutch Climate Agreement (2019) established a target to reduce net CO₂ emissions from fen meadows by 1 Mt CO₂ per year by 2030. To achieve this objective, the Dutch National Research Programme on Greenhouse Gases in Peatlands (NOBV) implemented an intensive monitoring network that integrates chamber-based measurements with both on-site and airborne eddy covariance (EC) observations. A primary challenge in this context is attributing and upscaling CO₂ emissions across diverse peat types, soil conditions, groundwater regimes, and grassland management practices.

Direct measurement of peat oxidation at the ecosystem scale is not feasible; instead, it must be inferred from EC fluxes that encompass autotrophic respiration, heterotrophic decomposition, and management-induced vegetation turnover resulting from mowing and regrowth. Attribution remains challenging because conventional emission–response functions emphasise groundwater levels while neglecting soil physical properties and vegetation dynamics, which is a significant limitation in highly degraded, nutrient-rich peatlands.

Our modelling strategy consists of two components. First, we employ machine learning to analyse the data without imposing prior assumptions. Shapley-based attribution quantifies the contributions of groundwater depth, meteorological forcing, vegetation state, and mowing timing to fluxes, along with their interactions. These models identify nonlinear thresholds and regime-dependent behaviours that are challenging to specify a priori. We compare response structures across sites to assess sensitivities, rather than prescribing specific management scenarios.

Second, we develop a physics-based deep learning framework that integrates biophysically meaningful equations with adaptable learning components. Groundwater dynamics regulate oxygen availability and determine the proportion of organic matter exposed to air. Soil moisture profiles are used to characterise oxic and anoxic zones. Bulk density and porosity, which define degraded peat, constrain oxygen diffusion and moisture retention. By explicitly representing vegetation growth and mowing disturbances, we distinguish autotrophic respiration from peat oxidation.

Integrating soil physics and groundwater dynamics within a deep learning framework enhances both temporal robustness and cross-site transferability while maintaining model flexibility. This approach enables inference of peat oxidation from EC observations in a mechanistically consistent manner, thereby providing a robust foundation for evaluating mitigation strategies in intensively managed peatlands.

How to cite: Bataille, L., Kruijt, B., van der Poel, L., Franssen, W., Jans, W., van Huissteden, C., Zhao, H., Berghuis, H., Biermann, J., Andueza Kovacevic, I., Engel, F., Zerrudo, J., Ingle, R., Lippman, T. J., Cabezas-Dueñas, I., Nouta, R., Boon, V., Buzacott, A., van der Velde, Y., and Hutjes, R.: Deciphering eddy-covariance CO₂ flux patterns in Dutch peatlands, from machine-learning to physics-based deep-learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2034, https://doi.org/10.5194/egusphere-egu26-2034, 2026.