Abstract. Field-based measurements are foundational to the study of short- and long-term peatland carbon dynamics. For decades, the scientific community has amassed hundreds of valuable empirical datasets in the form of peat core records from around the world. Those records typically include peat depth, basal age, peat organic matter content, peat dry bulk density, peat organic density, and/or carbon and nitrogen content. Once combined with chronological constraints and models, peat core time series can be used to estimate changes in peat-carbon accumulation rates through time. Consolidating these peat records can help improve global peat-carbon stock estimates and quantifications of past, present, and future greenhouse gas exchanges between peatlands and the atmosphere. Large-scale synthesis can also shed light on the sensitivity of peat-carbon accumulation processes to climate change and provide context for current and future global environmental change. We can also use spatial and temporal peat data to inform, validate, and benchmark existing models that include peatland representations. This paper presents the first formal version of PAGES’ C-PEAT Global Peatland Carbon Database (GD), which is available for download in the PANGAEA and International Soil Carbon Network (ISCN) data repositories. The C-PEAT GD contains 267 independently catalogued peat cores and a large number of observations from those cores, including: peat depths, organic matter content values, dry bulk density values, organic density values, as well as carbon and nitrogen content values. Raw and calibrated chronological data are included for each individual dataset when available. The metadata fields are easily searchable and interoperable, as per PANGAEA’s standards. The main objective of this article is to describe the structure and content of the database, itself aimed at increasing the use, assimilation, and interoperability of peat-core data across disciplines. The C-PEAT GD can be accessed at the PANGAEA data repository (https://doi.org/10.1594/PANGAEA.986891; Loisel et al., 2025).

Abstract Peatlands are among Earth’s largest terrestrial carbon stores and are crucial for climate regulation, biodiversity conservation, and water security. Yet peatlands worldwide are deteriorating under pressures from climate change and human disturbance. Strategic, globally coordinated research is urgently needed to protect, restore and manage peatlands so they can continue to deliver essential ecosystem services. To meet this challenge, here we present a global research prioritisation for peatland science, based on a two-stage online survey and expert voting exercise involving 467 participants from 54 countries. We identify 50 priority research questions spanning carbon dynamics, climate impacts, restoration and management, technological innovation, and community and policy engagement. These questions provide a community-informed agenda to guide peatland research over the next decade. Addressing them will help close critical knowledge gaps, strengthen evidence-based decision making, and support the role of peatlands in achieving global climate and biodiversity goals.

Wetlands, as the largest natural source of methane (CH₄) emissions, have received increasing attention in climate modelling. Recognising that methanogenesis is governed by anaerobic microbial processes, some models explicitly represent methanogen activity to simulate CH₄ emissions from permanently inundated wetlands. In such models, CH₄ emissions from seasonally flooded wetlands are usually estimated using an empirical oxidation factor to represent methanotrophic consumption. However, this approach neglects an additional important effect of atmospheric oxygen ingress during hydrological drawdown: the stimulation of organic matter decomposition upon rewetting, analogous to the Birch effect in seasonally dry ecosystems.Despite the high annual methane emissions from permanently inundated sites, some of the highest intensity CH₄ emission spikes throughout the year are exhibited by seasonally inundated systems, such as freshwater marshes, floodplain wetlands and fens. Consequently, improved mechanistic representation of biogeochemical processes in seasonally inundated wetlands is needed to robustly assess global wetland greenhouse gas contribution.This study presents a process-based wetland biogeochemical model that explicitly represents oxygen-stimulated substrate dynamics and microbial functional differentiation. Dissolved organic carbon (DOC) is partitioned into a “dry DOC” pool that accumulates during dry periods, and a “wet DOC” pool that is replenished upon rewetting. Microbial processes include distinct aerobic and anaerobic pools, whose activities are regulated by soil water content (SWC). Aerobic microbial activity follows a Gaussian response to SWC, reflecting optimal activity under intermediate moisture conditions. Water table depth (WTD), a relatively commonly measured wetland metric, is used to infer vertical SWC profiles in the soil column through a fitted van Genuchten soil water retention curve.The microbial-DOC framework is coupled with the Joint UK Land Environment Simulator (JULES), a community land-surface model simulating the exchanges of energy, water and carbon between the land surface and the atmosphere, which can also be used as the land surface scheme of the UK Earth System Model (UKESM). JULES drives the microbial-DOC module by providing partitioned pools of litter, soil organic carbon, and root exudates, each characterised by distinct turnover kinetics. Temperature sensitivity is represented using Arrhenius kinetics, while substrate and microbial limitations are described using Michaelis–Menten formulations. Model parameters are constrained using methane and carbon dioxide flux measurements, alongside methanogen abundance data, from flooded hardwood and palm forests in Panama.Resolving oxygen-mediated substrate priming and microbial responses, the framework moves beyond oxidation-only representations and improves estimates of wetland carbon source–sink dynamics under climate change.

Peatlands are important environmental archives and mineral dust trapped in peat cores from multiple sites can be used to track past changes in hemispheric and global wind circulation patterns. X-ray Fluorescence Core Scanning (XRF-CS) can rapidly geochemically characterise minerals deposited in peat at sub-millimetre-resolution, but calibration is needed to obtain quantitative data. Here, we present a unique calibration of > 14,000 contiguous mm-scale XRF-CS measurements depth-matched to 268 interval-based cm-scale Inductively Coupled Plasma Mass Spectrometry (ICP-MS) quantitative measurements from five peat records located on the west coasts of four sub-Antarctic islands impacted by the Southern Hemisphere Westerly Winds. Of eight calibration models tested, a four-element (Ca, Ti, Sr, Zr) multivariate partial least squares (PLS) model optimised for the widely used dust flux elements Ti and Zr accounts for covariance and provides the most reliable predicted XRF-CS concentrations for Ti (R2CV = 0.76, RMSEPboot = 2203 ± 705 mg kg− 1, R2pred. = 0.87, RMSEpred. = 2136 mg kg− 1, P < 0.0001). Predictions for Zr are indicative due to low Zr concentrations, but calibrated Ti and Zr XRF-CS concentrations align well with ICP-MS Ti and Zr concentrations for all five peatland sites. Our multivariate calibration protocol expands the scope of quantitative high-resolution palaeoenvironmental and geochemical research potentially to decadal–centennial timescales for peat records from, and beyond, the sub-Antarctic islands.

Human degradation has caused many peatlands worldwide to shift from long-term carbon sinks to net sources. In upland blanket peatlands, erosion disrupts plant-derived carbon input and exposes deep peat, accelerating oxidation of old carbon. The efficacy of restoration in preventing carbon loss and recovering ecosystem function depends on microbial responses to both water table manipulation and renewed litter input. Yet it is unclear how these factors alter the microbial communities that ultimately control carbon storage and emissions. Here we show that microbial community composition in the eroded Waun Fignen Felen peatland, South Wales, was governed primarily by organic matter bioavailability rather than water-table position. Long-term erosion leaves a legacy of highly decomposed organic matter, unaltered by re-wetting. Where plant litter accumulation is renewed on formerly eroded peat surfaces, the influx of bioavailable organic input supports a distinct prokaryote community with a greater bacterial population size, and evidence of elevated respiration. Microbial community composition is primarily governed by the renewal of plant litter at the peat surface and utilization of recent bioavailable organic matter in the recovering layer, rather than water-table position, based on field study at Waun Fignen Felen peatland, South Wales, UK

This paper describes the climate-related forcings (CRFs), i.e. change in climate comprising the atmosphere and the ocean, coastal water levels, and atmospheric composition ( CO (2) and methane concentrations), provided as input data within the "b" part of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). While ISIMIP3a comprises historical impact models simulations forced by observational Direct Human Forcings (DHF), such as changes in population and asset distributions, land use, fishing efforts, agricultural and water management driven by socio-economic development or climate protection strategies, and observational CRF, the ISIMIP3b CRFs are based on climate model simulations generated within the sixth phase of the Coupled Model Intercomparison Project (CMIP6). In a first set of experiments covering the pre-industrial (1601-1849) and historical period (1850-2014) (ISIMIP3b, group I) the CMIP6-based CRFs for the historical period are combined with historical observation-based DHF also considered in ISIMIP3a. These group I simulations allow for the quantification of impacts of historical climate change by comparison to simulations where the observational DHF are combined with simulated pre-industrial CRFs. In addition, the impacts of observed changes in CRFs can be compared to the impacts of simulated changes in CRFs by comparing the ISIMIP3a simulations to the ISIMIP3b, group I simulations. The second group of experiments (ISIMIP3b, group II) comprises future projections assuming constant observational direct human forcings at 2015 levels to estimate the impact of climate change given today's DHF for the low emission scenario SSP1-2.6, the high and the very high emission scenarios SSP3-7.0, SSP5-8.5, and reference simulations based on pre-industrial CRF, respectively. The very high emissions scenarios and the assumption of fixed present day DHF particularly allow for testing the scalability of impacts in terms of global temperature change. The provided CRFs comprise atmospheric CO (2) and CH 4 concentrations, atmospheric and oceanic climate data, coastal water levels, tropical cyclone (TC) tracks and their associated wind speed and precipitation fields. In addition to the CRFs data, this paper describes the experiments belonging to group I and II and the rationale behind them. Another set of future projections accounting for changing DHFs (ISIMIP3b, group III) is in preparation and will be described in another paper.

Monitored seabird populations have declined by up to 70% worldwide since the 1950s. Yet, data on long-term seabird population dynamics prior to the anthropogenic era are largely unknown. This limits our ability to understand future population trajectories, particularly in the Southern Ocean, where seabirds are facing multiple environmental threats. Here, we use mercury (Hg) derived from seabird guano in peatland catchments as a tracer of colony population sizes on sub-Antarctic Bird Island (South Georgia). Peat Hg flux and isotope signature results show that the first sustained seabird colonies after deglaciation were established on the island between 6800 and 6100 years ago, predating evidence for colonization on other sub-Antarctic islands by more than 1,000 y. The four subsequent periods with large local seabird populations occurred during phases of less intense Southern Hemisphere westerly winds. Our study unveils significant and repeated millennial-scale shifts in seabird abundance in response to natural climate changes, implying that the present-day increase in westerly wind intensity may lead to further declines in seabird populations in the Southern Ocean.

Africa hosts an enormous variety of peatland types spanning a wide range of climates. Despite their importance for biodiversity, carbon storage, water provisioning and livelihoods, African peatlands remain understudied. Here, we provide an overview of monitoring and research of African peatlands. We focus on a series of topics that reflect ongoing research efforts on peatlands worldwide, including peatland extent and depth mapping, which are still under-developed for the continent. We also highlight the scarce coverage of African peatlands in paleo-studies, including information on the timing of peatland inception, peatland carbon accumulation rates and fire paleo-records. We describe the importance of African peatlands in the Global Methane Budget, and we map greenhouse gas flux sites (chamber and eddy covariance) to understand where the data gaps in ground observations remain. We finally highlight the low level of protection given to these important ecosystems. In summary, our overview highlights large existing knowledge gaps in African peatland science, suggesting remaining questions and opportunities for research and urging funders to support the African scientific community to take up these remaining challenges that will help design best management practices for these vital ecosystems. A French translation of this abstract is available in the supplementary material. This article is part of the discussion meeting issue 'African tropical peatlands: function, value and vulnerability'.

Abstract Peatlands are some of the most carbon-dense ecosystems on Earth, and Africa houses the world's largest tropical peatland complex covering 16.7 million hectares of the central Congo Basin. Yet, the peatlands of Africa are neglected ecosystems. In this special issue, we begin to rectify this scientific ignorance. We present 16 reports, two reviews and 14 papers presenting original research findings, building on the first-ever conference on African peatlands held on 17 and 18 February 2025 in London. These cover what we know of the presence of peatlands in Africa, identifying three broad classes (coastal peatlands, lowland interior peatlands, and higher-altitude peatlands); newly confirmed peatlands in Angola; new findings on the long-term development of the central Congo peatlands; the first study of insect biodiversity in the central Congo peatlands; work on the threats to African peatlands from both land use and climate change; and social science studies on how local communities are utilizing and managing African peatlands. We conclude with a call for African and international scientists to work in equal partnerships to better understand these valuable yet vulnerable ecosystems. A French translation of this abstract is available in the supplementary material. This article is part of the discussion meeting issue ‘African tropical peatlands: function, value and vulnerability’.

Peatlands are major carbon stores that are sensitive to climate change and increasingly affected by human activity. Accurate assessment of carbon stocks and modelling of peatland responses to future climate scenarios requires robust information on peat depth. We developed PeatDepth-ML, a machine learning framework that predicts global peat depths using a comprehensive database of peat depth measurements for training and validation. Building on an existing framework for mapping peatland extent, we incorporated new environmental datasets relevant to peat formation, revised cross-validation procedures, and introduced a custom scoring metric to improve predictions of deep peat deposits. To evaluate model sensitivity to sampling bias inherent in the training data, we applied a bootstrapping approach. Model performance, assessed using a blocked leave-one-out approach, yielded a root mean square error of 70.1 ± 0.9 cm and a mean bias error of 2.1 ± 0.7 cm, performing as well as or better than previously published models. The global map produced by PeatDepth-ML predicts a median peat depth of 134 cm (IQR: 87–187) over areas with more than 30 cm of peat. Like other regression-based models, PeatDepth-ML tended to predict toward mean training depths. An area of applicability analysis suggests the model has good applicability globally with the exception of some coastal and several mountainous regions like the Andes and the highlands of Borneo and New Guinea. Predictor selection was highly sensitive to training data subsets that arose from the bootstrapping approach, occasionally resulting in regional variations in accuracy. The bootstrapping approach and our area of applicability analysis thus clearly demonstrates the prime importance of quality training data in data-driven approaches like PeatDepth-ML. Using our predicted peat depth map, together with peatland extent and literature-derived estimates of bulk density and organic carbon content, we estimate global peat carbon stocks at 327–373 Pg C, consistent with previous global estimates.

Global peatlands store vast amounts of terrestrial carbon (C), yet the regional heterogeneity and subsurface C dynamics of Chinese peatlands remain poorly quantified. These data gaps limit potential model extrapolations and vulnerability assessments of peatlands from one region to another in a global perspective. Our systematic investigation of peat profiles across four major climate regimes in China revealed generally lower C content (38.4 ± 7.2%, n = 957) than the global average. A widespread mismatch between surface vegetation and subsurface peat type was documented, with a paradox where high C accumulation rates coincided low C stocks in Sphagnum peats and vice versa in non-Sphagnum peats. Crucially, we identified a fundamental vertical stratification in drivers: geoclimatic factors exerted a stronger influence on shallow, 0–20 cm, C stocks, whereas microbial processing of labile C significantly governed only deeper >20 cm reservoirs. Thus, the vulnerability of deeper peat hinges primarily on the decomposition resistance of subsurface peat C, rather on surface conditions. Our findings highlight the need for a depth-resolved framework for managing and modeling these peatlands to accurately project their climatic responses.

Peatlands host the largest store of terrestrial carbon on Earth and it is widely accepted that reversal of their widespread degradation is required to meet emissions targets. Thus, significant action is underway globally to encourage their rewetting and restoration. However, restoration success can be complicated by geological factors in the local environment. Peatlands in regions with iron sulphide-rich rocks and sediments experience drastic drops in pH following drainage and release high concentrations of iron and toxic metals. Accumulation of iron and sulphur in the peat during this time will fundamentally alter biogeochemical cycling, yet we have little understanding of the extent to which these effects can be reversed following the raising of water tables. Furthermore, the long-term impacts on resident microbial communities responsible for dictating the nature and scale of green-house gas emissions from such sites is unknown.We have compared two neighbouring fens in southern England underlain by glauconite- and pyrite-rich sandstone which are within the same hydrological regime but have experienced differing degrees of historical drainage and degradation. Both fens were designated for conservation and rewetted in the 1970s. Porewater nutrient and greenhouse gas profiles, peat geochemistry, mineralogy and microbial community analyses collectively suggest lasting differences in redox state and element cycling between the two areas. Wolferton Fen, which experienced less historical land disturbance, had returned to a near-natural state in 2022. However, Dersingham Fen, which was historically deeply drained and experienced significant peat loss, had a low pH, thick crusts of iron (oxyhydr)oxides remaining on the surface, and very high porewater iron and sulphate concentrations. High abundances of these alternative terminal electron acceptors inhibit methanogens in Dersingham Fen, which continues to be a source of CO2 despite anoxia.These results suggest that iron and sulphur-rich peatlands can tolerate some degree of degradation, but extensive drainage and peat loss will likely lead to permanent contamination which remains following rewetting. However, there may be a lot to gain from restoration of such sites as rewetting can protect remaining peat and reduce CO2 emissions whilst methane production would remain low.

Human degradation of peatlands worldwide has turned them into net carbon sources. In upland blanket peatlands, erosion disrupts new plant-derived carbon input and exposes deep peat, putting old carbon at risk of oxidation. The efficacy of restoration in preventing carbon loss and recovering ecosystem function depends on microbial responses to both water table manipulation and renewed litter input. Yet it is unclear how these factors alter the microbial communities that ultimately control carbon storage and emissions. We show that microbial community composition in the eroded peatland of Waun Fignen Felen, South Wales, was primarily governed by the bioavailability of organic matter rather than water-table position. Long-term erosion leaves behind a legacy of highly degraded organic matter, unaltered by re-wetting. Where plant litter accumulation is renewed on formerly eroded peat surfaces, the influx of bioavailable organic input supports a distinct microbial community with greater biomass, and evidence of elevated respiration.

Methane (CH4) emissions from tropical wetlands remain the largest uncertainty in the global CH4 cycle, and due to the high global warming potential of CH4 (84 times that of CO2 over a 20-year timescale), changes inemissions can disproportionately influence the climate over the coming decades. Methane has a short atmospheric life span, therefore reducing CH4 emissions could be key to meeting the Paris agreement temperature targets. To achieve this, it is essential to improve our understanding of regional CH4 emissions, especially from tropical areas, the largest natural sources but where field observations remain scarce. Although plant CH4 emissions can be regionally important in the tropics, in some cases contributing up to 81 % of total ecosystem level fluxes, they are neglected in global methane budgets. Peatlands, a type of wetland where waterlogged conditions result in accumulation of organic matter and anoxic conditions in the soil, most likely play an important but uncertain role in CH4 release (40 to 80% of tropical CH4 emissions). The large uncertainties in plant mediated CH4 emissions in tropical peatlands occur due to insufficient long-term field experiments to capture seasonal and interannual variability in CH4 fluxes and lack of information about plant species-specific emissions patterns and their drivers. To fill this gap, we are measuring plant trunk/stem CH4 fluxes across seasons in four tropical peatlands in Africa and South America with contrasting vegetation types: 1) a papyrus swamp (herbaceous, Mpologoma, Uganda) 2) a hardwood swamp forest (Bomboma, Democratic Republic of Congo) 3) a Montrichardia swamp (herbaceous, Leticia, Colombia) and 4) a hardwood swamp forest (Inirida, Colombia). We hypothesize that the magnitude and temporal dynamics of CH4 is intimately linked to environmental variables (e.g., water table level, temperature, etc) and plant growth cycles. By identifying the magnitude and main drivers behind CH4 emissions through plants it will be possible to reduce uncertainties in modelling future emissions and hence future climate projections.

Peatlands are some of the world’s most carbon-dense ecosystems and release substantial quantities of greenhouse gases when degraded. However, conserving peatlands in many tropical areas is challenging due to limited knowledge of their distribution. To address this, we surveyed soils and plant communities in Colombia’s eastern lowlands, where few peatlands have previously been described. We documented peat soils >40 cm thick at 51 of more than 100 surveyed wetlands. We use our data to update a regional peatland classification, which includes a new and possibly widespread peatland type, ‘the white-sand peatland,’ as well as two distinctive open-canopy sub-types. Analysis of peat bulk density and organic matter content from 39 intact peat cores indicates that the average per-area carbon densities of these sites (490–1230 Mg C ha ^−1 , depending on type) is 4–10 times the typical carbon stock of a (non-peatland) Amazonian forest. We used remote sensing to upscale our observations, generating the first data-driven peatland map for the region. The total estimated carbon stock of these peatlands of 1.91 petagrams (Pg C) (2-sigma confidence interval, 0.60–4.22) approaches that of South America’s largest known peatland complex in the northern Peruvian Amazon, indicating that substantial peat carbon stores on the continent have yet to be documented. These observations indicate that tropical peatlands may be far more diverse in form and structure and broadly distributed than is widely understood, which could have important implications for tropical peatland conservation strategies.

Amazonian peatlands are carbon-rich ecosystems that act as long-term carbon sinks but have faced increasing fire risks in recent decades. As a legacy of past fires, the contribution of pyrogenic carbon (PyC) to carbon cycling in these peatlands remains poorly understood. Here, we assess PyC accumulation variability using six cores spanning peatlands in northwestern Amazonia using hydrogen pyrolysis. We also estimate the PyC stock for the entire Amazonian peatlands by combining our field dataset with published sources. The PyC to total organic carbon ratio averaged 1.2% across our sites and increased with peat age. We estimate a total peatland PyC stock of 0.73 ± 0.61 Pg for the Amazon Basin, representing 1.6% of their TOC stock. Due to the slower turnover of PyC in peatland ecosystems, our findings indicate the importance of PyC generated by past fires and highlight the potential long-term carbon sequestration role of PyC in the future carbon cycle.

Peatlands are globally important carbon stores that face increasing threats from human activities and climate change impacts. Comprehensive peatland data are essential for understanding ecosystem responses to these stressors and mapping their past and current characteristics. Current peatland datasets remain limited due to poor representation in global soil mapping initiatives and the absence of a recognized, coordinated central repository for peat depth data. Existing compilations often contain errors, duplicates, and outdated observations, requiring researchers to repeatedly gather and harmonize data on a study-by-study basis. To address these challenges, we present Peat-DBase version 1.0 – a harmonized, quality-controlled global compilation of basal peat depth measurements. Version 1.0 of Peat-DBase comprises 204 902 peat depth measurements from 29 sources spanning 54.933° S to 82.217° N, with a significant proportion of measurements in Atlantic Canada and Scotland due to the inclusion of two particularly large datasets focused on those regions. We supplement the peat study measurements with 94 615 non-peat soil measurements to ensure comprehensive coverage consistent with the relatively low spatial coverage of peatlands globally. Despite the uneven distribution of peat depth measurements, Peat-DBase contains reasonable coverage of the major global peatland complexes in temperate and boreal North America and Europe, portions of Russia, the Amazon and Congo basins, and the Malay Archipelago, though gaps remain in the lower Amazon Basin, Eastern Indonesia, and Eastern Russia. From the current data, peat depths have a median value of 130 cm (IQR: 60–240), although this is influenced by a predominance of measurements in the North Atlantic regions. Peat-DBase's deepest measurement is 2223 cm. While sampling biases and measurement uncertainties exist, Peat-DBase provides an essential foundation for global peatland research. Peat-DBase is under active development and future versions will incorporate additional datasets, information on current peatland status, and improved positional uncertainty quantification. Peat-DBase eliminates the need for overlapping data compilation efforts while identifying critical observational gaps for future research. Peat-DBase is available at https://doi.org/10.5281/zenodo.15530644 (Skye et al., 2025).

Peatlands have been widely recognised as important carbon stores, ecological habitats and natural hydrological buffers. However, comparatively less attention has been given to the role of peatlands as long-term stores of pollutants, particularly toxic metals and metalloids (TMMs). Furthermore, the potential for their release is poorly understood. An improved understanding of TMM distribution and release in peatlands is critical, because climate warming risks increasing their mobilisation, through enhanced decomposition and changes to hydrological processes, with potentially significant implications for natural ecosystems and human health. The PIPES project (Pollutants In Peatlands: from sink to Source) aims to identify global “hot spots” of peatland pollutants and establish likely release mechanisms of currently inert TMMs. We use a unique combination of observational and controlled-experimental approaches to address two research questions: (1) What is the content and distribution of pollutants in global peatlands? and (2) Under what conditions, and through which pathways, are these pollutants most likely to be released? In this presentation, we share early findings from both components of the PIPES project. Firstly, we present our ongoing analysis of the distribution of TMMs in global peatlands, with a primarily focus on spatial patterns identified across our comprehensive network of sites in the UK and Ireland. We quantify the total content of TMMs using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) in peat cores compiled by a network of > 90 international collaborators. Secondly, we present preliminary results from controlled environmental simulations of TMM release in peat monoliths from subarctic Sweden. We explore both pore-water and atmospheric release under scenarios of drought, climate warming and a shallow burn. Our findings provide crucial new insights into the potential fate of pollutants in global peatlands and their implications for human health and natural ecosystems.