Hydrological conditions are important factors controlling the carbon dynamics of peatlands. Disentangling the response of methane (CH4) cycling in northern peatlands to hydroclimate is crucial for understanding the role peatlands played in global carbon budgets and the future contributions of CH4 from northern peatlands to these budgets. This study analyzed plant macrofossils and the compound-specific delta C-13 of lipids (n-alkanes, hopanoids, and triterpenoids) in peat profiles retrieved from Sweden to investigate the biogeochemistry of CH4 cycling in a northern peatland over the last 2000 years. Our results revealed the occurrence of a fen-bog transition at similar to 1200 CE, marked by a shift from Cyperaceae-dominated vegetation to Sphagnum-dominated assemblages. During some 800 years as a fen, the delta C-13 values of plant-derived n-alkanes and bacterial C-30 hopene remained stable, while during the bog stage, there were negative excursions (2-3 parts per thousand) of the delta C-13 of Sphagnum-derived n-C-23 alkane during two drought intervals (1400-1600 CE and 1800-2000 CE). The delta C-13 values of n-C-2(9) alkane, taraxer-14-ene and C-30 hopene showed 1-2 parts per thousand decreases during the drying interval of 1800-2000 CE. These isotopic patterns are indications of enhanced methane oxidation activity under drought conditions in the more ombrotrophic bog settings where methane-derived carbon contributes to carbon assimilated by Sphagnum and vascular plants. Collectively, our results highlight how carbon cycling in bogs is more affected by drought stress compared to fens, and the value of tracking the uptake and flow of methane-derived carbon in peatland ecosystems.

Measurements of surface-atmosphere carbon dioxide (CO2) and methane (CH4) fluxes have been relatively sparse across the Arctic tundra and boreal biomes, causing significant uncertainties in carbon budget estimates from the region. While the availability of Arctic-boreal carbon flux data has increased substantially over the past decade, the data have remained spread across different repositories, scientific articles, and unpublished sources, making it difficult to leverage. Here we present a new dataset of monthly Arctic-boreal carbon fluxes (ABCFlux v2) across terrestrial (wetlands and uplands) and freshwater (lakes and rivers) ecosystems compiled from previous syntheses including the Arctic-boreal CO2 flux database (ABCFlux v1), the Boreal-Arctic Wetland and Lake Methane Dataset (BAWLD-CH4), and the Global River Methane Database (GRiMeDB). In addition, we consider data from general-purpose (e.g., Zenodo) and flux network repositories, literature, and site principal investigators. The dataset includes surface-atmosphere CO2 fluxes of gross primary production (GPP), ecosystem respiration (Reco), and net ecosystem exchange (NEE), alongside CH4 fluxes. For aquatic ecosystems, we split CH4 fluxes into diffusive and ebullitive flux pathways, and included potential emissions from transient storage in the water column (“storage fluxes”), alongside CO2 and CH4 concentrations dissolved in the surface water. Fluxes are measured through a variety of methods including chamber and eddy covariance techniques alongside bubble traps, ice-surveys, and concentration-based turbulence-driven modelling in aquatic ecosystems. The monthly flux data are reported together with supporting methodological and environmental metadata. The resulting ABCFlux v2 has 23 847 flux site-months, 8182 concentration site-months, and 199 seasonal observations from 1024 sites, and includes 56 139 reported fluxes (i.e. sum of GPP, Reco, NEE, and CH4 fluxes) from the years 1984 to 2024. The majority of monthly observations occurred after 1999. Wetlands had the highest number of site-month observations (8758), followed by boreal forest (6981), lotic ecosystems (6275), lentic ecosystems (3799) and upland tundra (3308). Measurements of CO2 dominated the dataset across most ecosystem types (25 222) except for lentic ecosystems, where CH4 flux site-months (3098) were more frequent than CO2 flux site-months (2915). Overall, ABCFlux v2 includes 160 % more site-months for terrestrial CO2 flux data compared to ABCFlux v1. Integrating and updating BAWLD-CH4 flux data from growing season averages to monthly fluxes resulted in 5671 site-months of chamber CH4 data compared to 762 site-years. This collaborative initiative, involving contributions from over 260 researchers, provides a comprehensive overview of the current state of the Arctic-boreal carbon flux network and its data, and serves as an important step in reducing uncertainties in Arctic-boreal carbon budgets and in enhancing our understanding of climate feedbacks. The data can be accessed at ORNL DAAC at https://doi.org/10.3334/ORNLDAAC/2448 (Virkkala et al., 2026).

Over the past century, extensive areas of northern peatlands have been drained for forestry. Today, concerns about their role as significant sources of greenhouse gases (GHG) have sparked growing interest in peatland rewetting as a climate mitigating strategy. However, empirical evidence for rewetting effects on ecosystem carbon (C) and GHG balances is still limited, particularly for minerogenic boreal peatland forests. Rewetting of peatland forests also involves decisions about tree harvest, which can have important but understudied consequences for the C cycle. In this study, we quantified tree growth and estimated carbon dioxide (CO2) and methane (CH4) fluxes in both peatland areas and ditches over 2 years before (2019-2020) and after (2021-2022) rewetting a low-productive, minerogenic peatland forest in boreal Sweden. We also assessed effects of tree removal during rewetting by comparing harvest and non-harvest areas. Our results suggest that the peatland forest was, on average, C-neutral at the ecosystem-scale during the drained years. After rewetting, the harvested area became a C source (79 g C m-2 year-1), while the treed area acted as a small C sink (-24 g C m-2 year-1), with the difference due to diverging responses in net CO2 exchange. Furthermore, CH4 emissions doubled after rewetting, resulting in a two- to threefold increase in total GHG emissions (expressed in CO2 equivalents) over both 20- and 100-year timeframes. While ditches functioned as significant CO2 sinks and moderate CH4 sources during the drained years, they became CO2-neutral and CH4 emission hotspots after being infilled. Altogether, our findings suggest that rewetting low-productive boreal peatland forests may have a negative short-term climate impact. However, rewetting without tree harvest considerably meliorates ecosystem C and GHG balances. Overall, our study highlights the importance of tree harvesting decisions and the need for a deeper understanding of rewetting as a climate mitigation strategy.

Forest attribute maps are essential for supporting local decision-making regarding forest resource use. Such maps are produced by combining remote sensing and field data through various modeling approaches. When mapping across large areas, spatial gaps in field data used for model training are common. Our study evaluates the performance of three methods—k-Nearest Neighbor (k-NN), Random Forests (RF), and Multi-Layer Perceptron (MLP)—for forest resource mapping across Norway, Sweden, and Finland in an experimental setup with respect to availability of field data around the target area. Models were trained with sample plot sizes (N) ranging from 100 to 3000. RF consistently produced the most accurate predictions in terms of relative bias and RMSE. While spatial gaps in the training data (radius: 7–141 km) affected %RMSE of broad-leaved above ground biomass (AGB), they had minimal impact on %RMSE of both local and country-level predictions of total AGB and volume. For RF with N=3000, %RMSE of total AGB ranged between 53%–55% in Finland and Sweden, and 70%–72% in Norway across gap sizes. However, %bias increased for local predictions across the whole study region with larger gaps: RF with N=500 showed bias of −12%–12% (7 km gap) and −17%–28% (78 km gap). Similarly, country-level %bias of total AGB for Norway increased from −1.7% to −3.7% with larger gaps. In conclusion, spatial gaps in training data can significantly affect bias in predictions. Therefore, forest attribute maps should always be accompanied by metadata describing the training data used.

Boreal peatlands provide an important carbon store, which is highly susceptible to future changes in the global climate. Predictions of climate feedbacks on the peatland carbon balance require an in-depth understanding of how vegetation dynamics and environmental conditions jointly govern the production and decomposition of organic matter. However, detailed knowledge on the separate roles of plant functional groups (PFGs) in regulating peatland production and respiration fluxes in response to various abiotic factors at sub-seasonal scales is currently lacking. In this study, we used high-temporal resolution CO2 flux data from an automated chamber system established across experimental vegetation removal plots to separate the production and respiration fluxes of vascular plants and Sphagnum mosses over three growing seasons (2021-2023) in a boreal peatland. We found that gross primary production (GPP) of Sphagnum mosses exceeded that of vascular plants during green-up (average ratio: 1.18) and senescence (1.11), whereas vascular plants were the main contributor during the peak season (0.88). Vascular plants dominated autotrophic respiration (RA; 78%-93%) in all phenophases and contributed 38%-40% to growing season ecosystem respiration. For both PFGs, plant phenology was the primary driver for variations in GPP during green-up, whereas photosynthetic photon flux density was most important in regulating GPP during the peak season and senescence. Vascular plants reached greater maximum GPP throughout all phenophases, whereas Sphagnum mosses had a higher initial light use efficiency during green-up and senescence. Moss RA exhibited greater daytime temperature sensitivity than vascular plants during the peak season and senescence, but not during nighttime. These findings highlight that climate change effects on vegetation phenology and composition may strongly alter the peatland carbon cycle. Thus, understanding the separate roles of vascular plants and Sphagnum mosses in regulating production and respiration fluxes in different environmental conditions is crucial to improve predictions of northern peatland carbon cycle-climate feedbacks.

Boreal forests play a key role in the global carbon and water cycles, with water use efficiency (WUE) linking their carbon gain and water loss. However, the variation in WUE among contrasting boreal forests and its response to environmental conditions remains poorly understood. We utilised six years (2015–2020) of eddy-covariance data to compare the ecosystem (EWUE), canopy (WUEc), and underlying (UWUE) WUE of two adjacent mature boreal forests: a monoculture pine stand and a mixed spruce-pine stand growing under the same climatic conditions in Northern Sweden.Our results suggest that the mixed forest exhibited lower EWUE, WUEc, and UWUE than the pine monoculture, driven by disproportionately higher evapotranspiration. This difference diminished as atmospheric dryness increased. Daily WUE variability was primarily controlled by solar radiation and vapour pressure deficit, with no functional difference between the two forest stands. Mixed forest EWUE was more sensitive to soil moisture variability, with no difference in canopy WUE, highlighting the role of soil evaporation and higher water availability in the mixed stand.The mixed forest exhibited stronger WUE responses to drought, with both increases and decreases depending on drought intensity, reflecting a more reactive adjustment of carbon gain relative to water loss. In contrast, the pine monoculture maintained comparatively stable WUE across wide drought conditions, indicating a more conservative strategy that sustains ecosystem functioning under atmospheric water limitation.Our findings demonstrate that forest composition and structure strongly influence WUE, with important implications for predicting boreal forest resilience under different management and climate change scenarios.

Northern mires are significant natural sources of atmospheric methane (CH4), yet estimating CH4 emissions remains challenging due to their complex spatio-temporal dynamics. While eddy covariance (EC) measurements provide valuable insights into ecosystem-scale CH4 fluxes (FCH4) over mire areas typically < 0.05 km(2), the predictability of FCH4 at the mesoscale (similar to 0.5 - 20 km(2)) of a mire complex based on single-site EC measurements has not been explored. In this study, we utilized a network of four EC towers and developed a machine learning approach that integrates these EC data with comprehensive spatial information on drivers to predict FCH4 across a boreal mire complex in Northern Sweden. For this purpose, environmental driver variables were mapped and area-weighted within dynamic EC flux footprints and related to FCH4 in a spatially-explicit random forest model ('footprint-based model'). For comparison, we also considered a standard random forest model used for gapfilling of FCH4 data that is based on environmental measurements from fixed sensor locations ('biomet model'). For both models, variable importance analysis revealed NDVI as the strongest predictor of temporal FCH4 patterns, followed by air pressure, soil temperature and water table. Adjusting for site-specific carbon-to-nitrogen (C:N) ratios substantially improved model performance. Both models significantly improved estimates of the mire complex average FCH4 compared to simple extrapolation of single-site measurements, reducing the uncertainty from similar to 22 % in 2022 and 32 % in 2023 to <10 % and <25 % for the footprint-based model, and to <11 % and <30 % for the biomet model, respectively. Overall, our findings suggest that the comprehensive spatially-resolved driver information resulted in only marginally improved model performance at our study site. In comparison, the biomet model offers practical advantages through simpler implementation and wider applicability. However, we encourage testing the footprint-based model approach at other more heterogenous sites where it might become superior due to its ability to account for complex site conditions.

Wetland and upland ecosystems play significant but opposing roles in the global methane (CH4) budget, acting as natural sources and sinks, respectively. Two of the most common approaches for measuring CH4 fluxes (FCH4) are chambers, which measure fluxes at fine spatial scales (ca. 1 m2), and eddy covariance (EC) towers, which integrate fluxes across larger footprints (ca. 100-10 000 m2). Although chamber and EC observations have been combined in various syntheses and databases to estimate CH4 budgets, a unified cross-site evaluation of FCH4 estimates at plot and ecosystem scales is lacking. As a first step toward a systematic spatiotemporal scaling of EC tower and chamber footprints, we quantified differences in site-level aggregate FCH4 between EC and chamber measurements (Delta FCH4) across ten wetland and upland sites at half-hourly, hourly, daily, weekly, monthly, and annual timescales. We found that ecosystem-scale median FCH4 was consistently higher than plot-scale FCH4 at all temporal scales, with the smallest difference at the daily timescale (multi-site median Delta FCH4: 1.36 nmol m-2 s-1; median ecosystem-scale FCH4 = 1.56 nmol m-2 s-1, median plot-scale FCH4 = 0.06 nmol m-2 s-1) and the largest at annual scales (2.58 nmol m-2 s-1; median ecosystem-scale FCH4 = 25.91 nmol m-2 s-1, median plot-scale FCH4 = 6.55 nmol m-2 s-1). In general, the agreement between ecosystem- and plot-scale FCH4 decreased with finer temporal resolution (from Spearman rho = 0.95 at the annual scale to rho = 0.65 at the half-hourly scale), while Delta FCH4 variation was greatest at daily-to-annual scales. Key environmental predictors of Delta FCH4 across the ten sites included plot-scale spatial heterogeneity, dominant vegetation type, vapor pressure deficit, atmospheric pressure, and friction velocity at the daily and monthly scales. Wind direction was a significant predictor only at the monthly scale, suggesting EC footprint effects at these sites. These findings suggest that accounting for variability in EC footprint extent, chamber measurement placement, and measurement artifacts is key to reconciling multi-scale FCH4 observations across diverse ecosystems and refining CH4 budgets.

High-latitude mires store a considerable part of the global soil carbon. Current understanding suggests that wetter conditions promote carbon accumulation. This paradigm is based primarily on temperate ombrogenic bogs and overlooks the influence of minerogenic water from the catchment area, despite most northern mires being minerogenic fens. Here we show that minerogenic water is the main negative influence on past century carbon accumulation in boreal fens. This effect is most pronounced in mires formed during the last millennia. Rather than enhancing productivity, minerogenic water stimulates organic matter decay, apart from in elevated hummocks where both decay and productivity were stimulated. These findings reshape our understanding of carbon cycling at high-latitudes, highlighting how shifts in precipitation-evapotranspiration may impact carbon sequestration in fens, which are widespread in the circum-arctic. Contrary to expectations for temperate regions, we argue that increased catchment water input in sub-arctic peatlands is unlikely to enhance mire carbon accumulation.

High latitude mires are key ecosystems in the context of climate change since they store large amounts of carbon while constituting an important natural source of methane (CH4). However, while a growing number of studies have investigated methane fluxes (FCH4) at the plot- (~1 m2) and ecosystem-scale (~0.1-0.5 km2) across the boreal biome, variations of FCH4 magnitudes and drivers at the mesoscale (i.e., 0.5-20 km2) of a mire complex are poorly understood. This study leveraged a network of four eddy-covariance flux towers to explore the spatio-temporal variations in ecosystem-scale FCH4 across a boreal mire complex in northern Sweden over 3 years (2020-2022). We found a consistent hierarchy of drivers for the temporal variability in FCH4 across the mire complex, with gross primary production and soil temperature jointly emerging as primary controls, whereas water table depth had no independent effect. In contrast, peat physical and chemical properties, particularly bulk density and C:N ratio, were identified as significant baseline constraints for the spatial variations in FCH4 across the mire complex. Our observations further revealed that the 3-year mean annual FCH4 across the mire complex ranged from 7 g C m-2 y-1 to 11 g C m-2 y-1, with a coefficient of variation of 16% that is similar to the variation observed among geographically distant mire systems and peatland types across the boreal biome. Thus, our findings highlight an additional source of uncertainty when scaling information from single-site studies to the mire complex scale and beyond. Furthermore, they suggest an urgent need for peatland ecosystem models to resolve the mesoscale variations in FCH4 at the mire complex level to reduce uncertainties in the predictions of peatland carbon cycle-climate feedbacks.

Northern peatlands are key carbon reservoirs and natural sources of methane (CH 4 ). However, the environmental controls of CH 4 ‐related processes remain unclear, making modeling the emissions a challenge. In this study, we first evaluated the process‐based CoupModel with unique long‐term (2001–2023) in situ measurements from a pristine sedge‐dominated peatland in northern Sweden. Results show that the calibrated model can reproduce the hourly CH 4 fluxes ( r 2 = 0.63) and CO 2 flux, and the abiotic variations well. The CH 4 flux showed significant sensitivity (66% relative importance) to parameters related to CH 4 transport, followed by production and oxidation. We further showed that CH 4 fluxes respond to temperature and water table depth (WTD) with a seasonal hysteresis, suggesting a 35% higher temperature sensitivity during below‐average WTD compared to above‐average WTD, and a two times higher sensitivity of CH 4 to lowering WTD than to elevating WTD. The hourly growing‐season CH 4 fluxes response to temperature also displayed a hysteresis in the diurnal cycle, with nighttime CH 4 fluxes being 14%–23% higher than the daytime fluxes. We presented a CH 4 budget for the site and estimated the annual mean methane emissions from 2014 to 2023 to be 12.2 ± 1.2 gC/m 2 /yr, identifying the emissions predominantly contributed by diffusion. We conclude that CoupModel can effectively simulate the CH 4 emission and its controls for the northern pristine peatland. Our study reveals the importance of hysteresis in the response of methane fluxes to environmental changes and highlights the need for considering the temporal and hydrologic variability in CH 4 ‐temperature dependencies in peatland management.

The dataset includes Pan-European maps of timber volume (Vol), above-ground biomass (AGB), and deciduous-coniferous proportion (DCP) with a pixel size of 10×10 m for the reference year 2020. In addition, a measure of prediction uncertainty is provided for each pixel. The maps have been created using a combination of a Sentinel-2 mosaic, Copernicus layers, and National Forest Inventory (NFI) data.The mapping was done with the k-Nearest Neighbour (kNN, k=7) approach with harmonized data of species-specific Vol and AGB from 14 NFIs consisting of approximately 151 000 field plots across Europe. The maps cover 40 European countries, forming a continuous coverage of the western part of the European continent.A sample of 1/3 of NFI plots was left out for validation, whereas 2/3 of the plots were used for mapping. Maps were created independently for 13 multi-country processing areas. Root-mean-squared-errors (RMSEs) for AGB ranged from 53 % in the Nordic processing area to 73 % in the South-Eastern area. The maps are on average nearly unbiased on European level (1.0 % of the mean AGB), but show significant overestimation for small biomass values (53 % bias for forests with AGB less than 150 t/ha) and underestimation for high biomass values (-55 % bias for forests with AGB higher than 500 t/ha).The created maps are the first of their kind as they are utilizing a large number of harmonized NFI plot observations and consistent remote sensing data for high-resolution forest attribute mapping. While the published maps can be useful for visualization and other purposes, they are primarily meant as auxiliary information in model-assisted estimation where model-related biases can be mitigated, and field-based estimates improved. Therefore, additional calibration procedures were not applied, and especially high Vol and AGB values tend to be underestimated. We therefore discourage from summarizing map values (pixel counting) over areas in interest, as this may inadvertently result in biased estimates.

Wetlands are the largest natural source of methane (CH4) emissions globally. Northern wetlands (>45° N), accounting for 42 % of global wetland area, are increasingly vulnerable to carbon loss, especially as CH4 emissions may accelerate under intensified high-latitude warming. However, the magnitude and spatial patterns of high-latitude CH4 emissions remain relatively uncertain. Here, we present estimates of daily CH4 fluxes obtained using a new machine learning-based wetland CH4 upscaling framework (WetCH4) that combines the most complete database of eddy-covariance (EC) observations available to date with satellite remote-sensing-informed observations of environmental conditions at 10 km resolution. The most important predictor variables included near-surface soil temperatures (top 40 cm), vegetation spectral reflectance, and soil moisture. Our results, modeled from 138 site years across 26 sites, had relatively strong predictive skill, with a mean R2 of 0.51 and 0.70 and a mean absolute error (MAE) of 30 and 27 nmol m−2 s−1 for daily and monthly fluxes, respectively. Based on the model results, we estimated an annual average of 22.8±2.4 Tg CH4 yr−1 for the northern wetland region (2016–2022), and total budgets ranged from 15.7 to 51.6 Tg CH4 yr−1, depending on wetland map extents. Although 88 % of the estimated CH4 budget occurred during the May–October period, a considerable amount (2.6±0.3 Tg CH4) occurred during winter. Regionally, the Western Siberian wetlands accounted for a majority (51 %) of the interannual variation in domain CH4 emissions. Overall, our results provide valuable new high-spatiotemporal-resolution information on the wetland emissions in the high-latitude carbon cycle. However, many key uncertainties remain, including those driven by wetland extent maps and soil moisture products and the incomplete spatial and temporal representativeness in the existing CH4 flux database; e.g., only 23 % of the sites operate outside of summer months, and flux towers do not exist or are greatly limited in many wetland regions. These uncertainties will need to be addressed by the science community to remove the bottlenecks currently limiting progress in CH4 detection and monitoring. The dataset can be found at https://doi.org/10.5281/zenodo.10802153 (Ying et al., 2024).

The Arctic–Boreal Zone is rapidly warming, impacting its large soil carbon stocks. Here we use a new compilation of terrestrial ecosystem CO2 fluxes, geospatial datasets and random forest models to show that although the Arctic–Boreal Zone was overall an increasing terrestrial CO2 sink from 2001 to 2020 (mean ± standard deviation in net ecosystem exchange, −548 ± 140 Tg C yr−1; trend, −14 Tg C yr−1; P < 0.001), more than 30

Atmospheric mercury (Hg) uptake by vegetation and subsequent deposition via litterfall constitutes a major pathway in the global Hg cycle. However, the temporal dynamics of litterfall Hg deposition and its environmental controls remain poorly understood. Here, we present a detailed assessment of Hg concentrations and deposition fluxes for individual litter components in a Swedish boreal forest from 1987 to 2000. Atmospheric Hg concentrations declined 41 % during this period. Correspondingly, Hg concentrations in Scots pine and Norway spruce needles decreased significantly (∼22 % and ∼26 %, respectively). However, the total litterfall Hg deposition flux remained stable at 11.7 ± 1.8 μg m-2 yr-1, showing no clear temporal trend. Foliar litter (needles) contributed 44 % of total Hg deposition, while non-foliar litter (twigs, residual material, and cones) accounted for the remaining 56 % (32 %, 22 %, and 2 %, respectively). The importance of this non-foliar component in modulating litterfall Hg deposition is often overlooked. Litterfall Hg deposition was 1.7 times higher in the non-growing season than in the growing season, primarily due to greater litterfall biomass. The weak response of litterfall Hg deposition to declining atmospheric Hg concentrations highlights the importance of biological factors (e.g., litterfall compositions and productivity) in regulating Hg inputs to boreal forest. Our findings also underscore the need for long-term assessments of Hg deposition dynamics via different litterfall components for assessing the effectiveness of the Minamata Convention on Mercury.

Northern wetlands are considered to be one of the most significant natural sources of methane (CH4) emissions. The default wetland CH4 emission scheme in JULES, a current state-of-art land surface model, only takes into account the CH4 emissions from inundated wetland areas in a simple manner based on soil temperature and substrate availability. In this work, a process-based peatland CH4 emission model HIMMELI was integrated with JULES, and the HIMMELI parameters were optimized with measured CH4 flux at six northern wetland sites for each site separately or multi-sites simultaneously. The simulated CH4 emission was significantly improved when using the optimized parameter values, with the bias of 54.88 mg m-2 d-1 averaged across all the studied sites in the simulation using the default parameter (DPR) values being reduced to -0.70 mg m-2 d-1 in the simulations using parameters values derived from the single site optimization (SSO) for each site. In the simulations using parameters values from the averages of single site optimization (SSO_AVG) and the multi-site optimization (MSO), the biases averaged across all the studied sites were -7.39 mg m-2 d-1 and -8.36 mg m-2 d-1, respectively. The MSO simulations demonstrated more stable root mean square error (RMSE) between the simulated and observed methane emissions than the SSO_AVG simulations over the studied sites, when the RMSEs of SSO simulations were used as reference points. To further reduce the uncertainties in the simulated CH4 emissions by the JULES-HIMMELI model, model processes related to the environment conditions (e.g. water table, soil carbon and vegetation) of wetland and northern wetland CH4 emission processes (e.g. snow and ice covering effect) are suggested to be improved in JULES and HIMMELI, respectively. This study presents a comprehensive analysis of the impact of different parameters on the CH4 emission in the JULES-HIMMELI model and obtains optimal parameter values for modelling CH4 emissions at the studied northern wetlands. These findings pave the way for accurate regional estimates of northern wetland CH4 emission.

ABSTRACT Sphagnum moss is the dominant plant genus in northern peatlands responsible for long‐term carbon accumulation. Sphagnum hosts diverse microbial communities (microbiomes), and its phytobiome (plant host + constituent microbiome + environment) plays a key role in nutrient acquisition along with carbon cycling. Climate change can modify the Sphagnum ‐associated microbiome, resulting in enhanced host growth and thermal acclimation as previously shown in warming experiments. However, the extent of microbiome benefits to the host and the influence of host–microbe specificity on Sphagnum thermal acclimation remain unclear. Here, we extracted Sphagnum microbiomes from five donor species of four peatland warming experiments across a latitudinal gradient and applied those microbiomes to three germ‐free Sphagnum species grown across a range of temperatures in the laboratory. Using this experimental system, we test if Sphagnum 's growth response to warming depends on the donor and/or recipient host species, and we determine how the microbiome's growth conditions in the field affect Sphagnum host growth across a range of temperatures in the laboratory. After 4 weeks, we found that the highest growth rate of recipient Sphagnum was observed in treatments of matched host–microbiome pairs, with rates approximately 50% and 250% higher in comparison to maximum growth rates of non‐matched host–microbiome pairs and germ‐free Sphagnum , respectively. We also found that the maximum growth rate of host–microbiome pairs was reached when treatment temperatures were close to the microbiome's native temperatures. Our study shows that Sphagnum 's growth acclimation to temperature is partially controlled by its constituent microbiome. Strong Sphagnum host–microbiome species specificity indicates the existence of underlying, unknown physiological mechanisms that may drive Sphagnum 's ability to acclimatize to elevated temperatures. Together with rapid acclimation of the microbiome to warming, these specific microbiome–plant associations have the potential to enhance peatland resilience in the face of climate change.

Abstract. Wetland and upland ecosystems play significant but opposing roles in the global methane (CH4) budget, acting as natural sources and sinks, respectively. Two of the most common approaches for measuring CH4 fluxes (FCH4) are chambers, which capture temporally intermittent, fine-scale spatial heterogeneity (ca. 1 m2), and eddy covariance (EC) towers, which cover a larger area (ca. 100–10000 m2) at a longer term. Although chamber and EC observations have been combined in various syntheses and databases to estimate CH4 budgets, a unified cross-site evaluation of FCH4 estimates at plot and ecosystem scales is lacking. As a first step toward a systematic spatiotemporal scaling of EC tower and chamber footprints, we quantified the differences between site-level aggregate FCH4 (EC vs chamber; ΔFCH4) from ten wetland and upland sites at half-hourly, hourly, daily, weekly, monthly, and annual timescales. We found that ecosystem-scale median FCH4 was consistently higher than plot-scale FCH4 at all temporal scales, with the smallest difference at daily timescale (multi-site median ΔFCH4: 1.36 nmol m-2 s-1; ~ 104 % higher ecosystem-scale than plot-scale FCH4) and largest at annual scales (2.58 nmol m-2 s-1; ~ 87 % higher ecosystem-scale than plot-scale FCH4). In general, the agreement between ecosystem- and plot-scale FCH4 decreased with finer temporal resolution (from Spearman ⍴ = 0.95 at annual scale to ⍴ = 0.65 at half-hourly scale), while ΔFCH4 variation was greatest at daily-to-annual scales. Key environmental predictors of ΔFCH4 included plot-scale spatial heterogeneity, dominant vegetation type, vapor pressure deficit, atmospheric pressure, and friction velocity at the daily and monthly scales. Wind direction was a significant predictor only at the monthly scale, suggesting EC footprint effects. These findings suggest accounting for variation in EC footprint extent, chamber measurement placement and artifacts is key to reconciling multi-scale FCH4 observations in diverse ecosystems and refining CH4 budgets.

Northern peatlands are recognised as important long-term carbon sinks. However, measurements from a number of peatland sites reveal a large amount of interannual variability in their net carbon dioxide (CO2) balance. Differences in both weather conditions and plant phenology (i.e. the seasonal development of the vegetation canopy) between years are thought to be key here. Timing of the growing season (i.e. start, end, length) regulates the period over which vegetation can actively photosynthesise. Hence, a longer growing season is often related to increased seasonal CO2 uptake for example. At the same time, meteorological conditions (e.g. air temperature, water-table depth) affect not only plant physiology, but also its phenological cycle. Our current understanding of the complex interplay between these two main drivers of peatland carbon dynamics has been limited by a lack of long-term phenology studies. This work explores a unique, decade-long record of phenocam and eddy-covariance data from Degerö Stormyr, a northern Swedish peatland. We used structural equation modelling (SEM) to identify the pathways regulating CO2 uptake, and found that phenology plays an important ‘mediator’ role over the growing season. Our analysis of the interannual and seasonal variability in the drivers of CO2 uptake further suggest that increases in vegetation greenness are linked to increased CO2 uptake over the growing season. These findings provide valuable insight on the controls of peatland carbon dynamics, and its feedbacks with future climate change.