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Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17±11days, and lagged air and soil temperature by median values of 8±16 and 5±15days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

In the global methane budget, the largest natural source is attributed to wetlands, which encompass all ecosystems composed of waterlogged or inundated ground, capable of methane production. Among them, northern peatlands that store large amounts of soil organic carbon have been functioning, since the end of the last glaciation period, as long-term sources of methane (CH4) and are one of the most significant methane sources among wetlands. To reduce uncertainty of quantifying methane flux in the global methane budget, it is of significance to understand the underlying processes for methane production and fluxes in northern peatlands. A methane model that features methane production and transport by plants, ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model that includes an explicit representation of northern peatlands. ORCHIDEE-PCH4 was calibrated and evaluated on 14 peatland sites distributed on both the Eurasian and American continents in the northern boreal and temperate regions. Data assimilation approaches were employed to optimized parameters at each site and at all sites simultaneously. Results show that methanogenesis is sensitive to temperature and substrate availability over the top 75 cm of soil depth. Methane emissions estimated using single site optimization (SSO) of model parameters are underestimated by 9 g CH4 m−2 yr−1 on average (i.e., 50 % higher than the site average of yearly methane emissions). While using the multi-site optimization (MSO), methane emissions are overestimated by 5 g CH4 m−2 yr−1 on average across all investigated sites (i.e., 37 % lower than the site average of yearly methane emissions).

Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH$_{4}$ fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH$_{4}$ data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the boreal zone. The parameter posterior distributions were generated by the adaptive population importance sampler (APIS); then the optimal values were estimated by a simple stochastic optimisation algorithm. The model was constrained with in situ observations of evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity in spring. This modification enabled the model to correctly reproduce the springtime increase in GPP for all conifer sites used in this study. Overall, the calibration and model modifications improved the coefficient of determination and the model bias for GPP with all stomatal conductance formulations. However, only the coefficient of determination was clearly improved for ET. The optimisation resulted in best performance by the Bethy, Ball–Berry, and the Friend and Kiang stomatal conductance models. We also optimised the model during a drought event at a Finnish Scots pine forest site. This optimisation improved the model behaviour but resulted in significant changes to the parameter values except for the unified stomatal optimisation model (USO). Interestingly, the USO demonstrated the best performance during this event.

Accounting for temporal changes in carbon dioxide (CO2) emissions from freshwaters remains a challenge for global and regional carbon budgets. Here, we synthesize 171 site-months of e...

A significant proportion of the global carbon emissions to the atmosphere originate from agriculture. Therefore, continuous long-term monitoring of CO2 fluxes is essential to understand the carbon dynamics and balances of different agricultural sites. Here we present results from a new eddy covariance flux measurement site located in southern Finland. We measured CO2 and H2O fluxes at this agricultural grassland site for 2 years, from May 2018 to May 2020. In particular the first summer experienced prolonged dry periods, which affected the CO2 fluxes, and substantially larger fluxes were observed in the second summer. During the dry summer, leaf area index (LAI) was notably lower than in the second summer. Water use efficiency increased with LAI in a similar manner in both years, but photosynthetic capacity per leaf area was lower during the dry summer. The annual carbon balance was calculated based on the CO2 fluxes and management measures, which included input of carbon as organic fertilizers and output as yield. The carbon balance of the field was −57 ± 10 and −86 ± 12 g C m−2 yr−1 in the first and second study years, respectively.

Northern mires have sequestered substantial amounts of atmospheric carbon since the last glacial period forming one of the largest carbon pools in the biosphere (Hugelius et al., 2020). Current global warming is causing the subarctic and arctic regions warm rapidly, two to three times as fast as the rest of the world (Masson-Delmotte et al., 2018), which will affect the carbon balance of these mires.In Kaamanen, northern Finland, we studied carbon dioxide (CO2) and methane (CH4) exchange between patterned mesotrophic fen and the atmosphere, both on ecosystem and plant community level. The ecosystem level measurements were conducted by utilizing eddy covariance method, while the fluxes on plant community scale were measured with flux chambers. The studied fen can be described as a mosaic of strings and flarks (or hummocks and hollows, respectively). The microtopography of the string-flark continuum form four main plant community types with varying water table conditions and vegetation composition. The measurements took place in 2017–2018. The two years in question were contrasting in their meteorological and environmental conditions. The 2017 growing season had average temperature, but high precipitation sum, while 2018 growing season was warm and dry. In July 2018 a north-western Europe-wide heatwave caused a month-long drought period at the site. Compared to 2017, the annual carbon balance of the Kaamanen fen was affected by earlier onset of photosynthesis in spring and the drought event during summer 2018.We found that the annual carbon balance of the fen did not differ markedly between the studied years, even though the meteorological and environmental conditions did. The earlier onset of growing season in 2018 strengthened the CO2 sink of the ecosystem, but this gain was counterbalanced by the later drought period. Additionally, we found strong spatial variation in CO2 and CH4 dynamics between the main plant communities. Most of the variation in ecosystem level carbon exchange could be explained by the variation in water table level, soil temperature and vegetation characteristics, which were also the environmental factors that varied between the plant community types. ReferencesHugelius, G., Loisel, J., Chadburn, S., Jackson, R. B., Jones, M., MacDonald, G., Marushchak, M., Olefeldt, D., Packalen, M., Siewert, M. B., Treat, C., Turetsky, M., Voigt, C. and Yu, Z.: Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw, Proceedings of the National Academy of Sciences - PNAS, 117, 20438–20446, doi:10.1073/pnas.1916387117, 2020.Masson-Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., Shukla, P. R., Pirani, A., Moufouma-Okia, W., Péan, C., Pidcock, R., Connors, S., Matthews, J. B. R., Chen, Y., Zhou, X., Gomis, M. I., Lonnoy, E., Maycock, T., Tignor, M. and Waterfield T. (Eds.): Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty, World Meteorological Organization, Geneva, Switzerland, 2018.

Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf-level chlorophyll fluorescence measurements (Chl F) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite-observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. At regional scale the model was able to simulate observed SIF averaged over 5 years with r2 of 0.86. The GOME-2-based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation). The observed SIF captured the seasonality of the photosynthesis at site scale and showed feasibility for use in improving of model seasonality at site and regional scale.

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.

Terrestrial evapotranspiration (ET) is thermodynamically expected to increase with increasing atmospheric temperature; however, the actual constraints on the intensification of ET remain uncertain due to a lack of direct observations. Based on the FLUXNET2015 Dataset, we found that relative humidity (RH) is a more important driver of ET than temperature. While actual ET decrease at reduced RH, potential ET increases, consistently with the complementary relationship (CR) framework stating that the fraction of energy not used for actual ET is dissipated as increased sensible heat flux that in turn increases potential ET. In this study, we proposed an improved CR formulation requiring no parameter calibration and assessed its reliability in estimating ET both at site-level with the FLUXNET2015 Dataset and at basin-level. Using the ERA-Interim meteorological dataset for 1979–2017 to calculate ET, we found that the global terrestrial ET showed an increasing trend until 1998, while the trend started to decline afterwards. Such decline was largely associated with a reduced RH, inducing water stress conditions that triggered stomatal closure to conserve water. For the first time, this study quantified the global-scale implications of changes in RH on terrestrial ET, indicating that the temperature-driven acceleration of the terrestrial water cycle will be likely constrained by terrestrial vegetation feedbacks.

Northern peatlands are projected to be crucial in future atmospheric methane (CH4) budgets and have a positive feedback on global warming. Fens receive nutrients from catchments via inflowing water and are more sensitive than bogs to variations in their ecohydrology. Yet, due to a lack of data detailing the impacts of moving water on microhabitats and CH4 fluxes in fens, large uncertainties remain with respect to predicting CH4 emissions from these sites under climate changes. We measured CH4 fluxes with manual chambers over three growing seasons (2017–2019) at a northern boreal fen. To address the spatial variation at the site where a stream flows through the long and narrow valley fen, we established sample plots at varying distances from the stream. To link the variations in CH4 emissions to environmental controls, we quantified water levels, peat temperature, dissolved oxygen concentration, vegetation composition, and leaf area index in combination with flux measurements during the growing season in 2019. We found that due to the flowing water, there was a higher water level, cooler peat temperatures, and more oxygen in the peat close to the stream, which also had the highest total leaf area and gross primary production (GPP) values but the lowest CH4 emissions. CH4 emissions were highest at an intermediate distance from the stream where the oxygen concentration in the surface peat was low but GPP was still high. Further from the stream, the conditions were drier and produced low CH4 emissions. Our results emphasize the key role of ecohydrology in CH4 dynamics in fens and, for the first time, show how a stream controls CH4 emissions in a flow-through fen. As valley fens are common peatland ecosystems from the Arctic to the temperate zones, future projections of global CH4 budgets need to take flowing water features into account.

Wetlands are one of the most important terrestrial ecosystems for land-atmosphere CH4 exchange. A new process-based, biophysical model to quantify CH4 emissions from natural wetlands was developed and integrated into a terrestrial ecosystem model (Integrated Biosphere Simulator). The new model represents a multisubstance system (CH4, O-2, CO2, and H-2) and describes CH4 production, oxidation, and three transport processes (diffusion, plant-mediated transport, and ebullition). The new model uses several critical microbial mechanisms to represent the interaction of anaerobic fermenters and homoacetogens, hydrogenotrophic, and acetoclastic methanogens, and methanotrophs in CH4 production and oxidation. We applied the model to 24 different wetlands globally to compare the simulated CH4 emissions to observations and conducted a sensitivity analysis. The results indicated that (1) for most sites, the model was able to capture the magnitude and variation of observed CH4 emissions under varying environmental conditions; (2) the parameters that regulate dissolved organic carbon and acetate production, and acetoclastic methanogenesis had the significant impact on simulated CH4 emissions; (3) the representation of the process components of CH4 cycling showed that CH4 oxidation was about half or more of CH4 production, and plant-mediated transport was the dominant pathway at most sites; and (4) the seasonality of simulated CH4 emissions can be controlled by soil temperature, water table position, or combinations thereof.

Long-term continuous measurement of reduction-oxidation (redox) potential is an emerging tool for analysing ecosystem status. Redox processes are intrinsically linked to methane (CH4) production and consumption in soils. Under highly reducing conditions, acetate and carbon dioxide (CO2) are reduced into CH4, while at less reducing conditions, CH4 is readily oxidised into CO2. These oxidation processes do not necessarily require oxygen; other electron acceptors such as nitrate (NO3-) and iron can also be used by microbes. The prevalence of different electron acceptors and donors is reflected in the redox potential of the soil solution which can be measured. Thus measurements of soil redox potential could in principle be used for predicting CH4 flux.We measured soil redox potential at 4 depths between 5 and 40 cm continuously over one growing season on nine measurement plots on three different microsites (flark, lawn and string), in a north boreal flark fen, while concurrently measuring CO2 and CH4 flux of the same plots using the manual chamber method. Flux measurements were conducted five to seven times per week from late June to late September, 2019. Along with the redox potential, water table level (WTL), air and soil temperature (Tair, Tsoil) and several vegetation characteristics were also measured.Tsoil was found to be the major control of the momentary CH4 flux, but after standardizing the flux to 10 C using the Lloyd-Taylor equation, including the soil redox potential was found to significantly (p < 0.001) improve the prediction of the flux over a model incorporating only WTL and momentary Tsoil.This is an initial step towards inclusion of redox potential as a continuous variable describing the processes active in the soil into CH4 production/consumption models.

Agriculture is globally a significant source of carbon emissions to the atmosphere. Main causes for these high emissions are conventional intensive management practices which include such as frequent ploughing, monocropping and high use of agrochemicals. These practices contribute to the loss of biodiversity and soil organic matter, as well as to the CO2 emissions from land use. Recently, it has been recognised that agriculture functioning on the basis of regenerative practices is one of the most potential tools to mitigate climate change.It is well known that topsoil layer and especially humus-rich soils can store more carbon than atmosphere and vegetation together. Therefore, increasing the amount of soil organic matter in the agroecosystems, by applying enhanced management practices such as reduced tillage, high biodiversity and cover cropping, agricultural soils would not only help to mitigate climate change but also to restore soil quality and fertility. To understand the carbon dynamics on different agricultural sites, factors affecting and comprising the carbon balance, and to verify soil carbon and ecosystem models, continuous long-term monitoring of the GHG fluxes is essential at such managed ecosystems. Here we present results from a new eddy covariance (EC) flux study site located in southern Finland.Continuous CO2 flux measurements using the EC method have been conducted at Qvidja farm on mineral (clay) soil forage grassland in Parainen, southern Finland (60.29550°N, 22.39281°E) since the spring 2018. Based on the flux and biomass data, the annual carbon balance was estimated to be negative, i.e. the site acted as an overall sink of carbon even in the dry and hot year 2018. However, the seasonal CO2 fluxes were greatly dependent on weather conditions and management procedures. Results from 2019 show that the growing season accompanied with more mature and dense grass, a bit higher precipitation and lower temperatures, as well as higher cutting height was more favorable for carbon uptake in Qvidja as compared to year 2018.

Mitigation of climate change requires – besides reductions in greenhouse gas emissions – actions to increase carbon sinks and storages in terrestrial ecosystems. Agricultural lands have a high potential for increased carbon sequestration through climate-smart land management and agricultural practices. However, in order to make climate-smart farming an accredited solution for climate policy, carbon markets and product footprints, reliable verification of carbon sequestration is needed. Direct measurement of the changes in soil carbon stock is slow, laborious and expensive and has significant uncertainties due to large background stocks and high spatial variability. An alternative is to infer the soil carbon stock change from measurements of the gaseous carbon fluxes between ecosystems and the atmosphere using the micrometeorological eddy covariance (EC) method.Eddy covariance measures net ecosystem exchange (NEE), which is a small difference between two large components: carbon uptake by photosynthesis and losses due to plant and soil respiration. Therefore, small changes in either of them results in a large change in NEE. This sensitivity is also reflected in uncertainty estimates, which are critical for defining confidence intervals for annual carbon budget estimates and for making statistically valid comparisons of different management practices. In addition, there are inevitable gaps in the data due to instrument failure, power shortages and non-ideal flow conditions. Therefore, in order to calculate daily and annual sums, the collected data must be temporally upscaled or gap-filled, which constitutes a major additional source of uncertainty. This study compares two different gap-filling methods for CO₂ fluxes: (1) an artificial neural network and (2) non-linear regression, which uses temperature and radiation as drivers. Uncertainties associated with both methods are estimated and discussed. The analysis is based on EC flux measurements conducted at two agricultural grassland sites in Finland.

Drainage and other management activities in peatlands make especially the fertile sites a source of greenhouse gases into the atmosphere. In addition to typically losing carbon dioxide (CO2) from the old peat, they act as sources of nitrous oxide (N2O) into the atmosphere. In contrary to CO2, N2O fluxes do not necessarily show a distinct seasonal cycle with high emissions in summer and low in winter. Instead, the most intense peaks in N2O fluxes have been earlier attributed to freezing-thawing cycles of peat soil. Emissions of N2O have been reported to vary greatly both in time and space. Due to instrument limitations, the fluxes have been typically measured using manual chamber technique which provides only a snapshot of the potentially highly dynamic fluxes.In this presentation we show multi-year results of N2O fluxes captured by automatic chambers and compare those to temporally sparse manual chamber measurements. Our study site was a nutrient-rich drained peatland ‘Lettosuo’ located in Tammela in southern Finland. The peatland, originally an herb-rich tall sedge pine fen was drained for forestry in 1969. After that, the tree stand was a mixture of Scots pine, Norway spruce and Downy birch. N2O fluxes were measured hourly with six automatic chambers. We will address the temporal and spatial variability in the fluxes and the plausible reasons behind them, including the drought of summer 2018, and give a summary of the exploitability of different methods. Suggestions for an improved chamber configuration and for the optimal sampling frequency for manual chambers will be given based on the results.

"The effects of atmospheric nitrogen deposition (N-dep) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of N-dep across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry + wet) reactive nitrogen (N-r) deposition. We propose a methodology for untangling the effects of N-dep from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO2 exchange fluxes from a Europe-wide network of 22 forest flux towers. Total N-r deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP/dN(dep)) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP/dN(dep) value. This model-enhanced analysis of the C and N-dep flux observations at the scale of the European network suggests a mean overall dNEP/dN(dep) response of forest lifetime C sequestration to N-dep of the order of 40-50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus N-dep were non-linear, with no further growth responses at high N-dep levels (N-dep > 2.5-3 gNm(-2) yr(-1)) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high N-dep levels implies that the forecast increased N-r emissions and increased N-dep levels in large areas of Asia may not positively impact the continent's forest CO2 sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC/dN response." The authors gratefully acknowledge financialsupport by the European Commission through the two FP6 in-tegrated projects CarboEurope-IP (project no. GOCE-CT-2003-505572) and NitroEurope Integrated Project (project no. 017841),the FP7 ECLAIRE project (grant agreement no. 282910), and theABBA COST Action ES0804. We are also thankful for fundingfrom the French GIP-ECOFOR consortium under the F-ORE-T for-est observation and experimentation network, as well as from theMDM-2017-0714 Spanish grant. We are grateful to Janne Korho-nen, Mari Pihlatie and Dave Simpson for their comments on the pa-per. Finalization of the paper was supported by the UK Natural En-vironment Research Council award number NE/R016429/1 as partof the UK-SCAPE programme delivering national capability. Wealso wish to thank two anonymous referees for their constructivecriticism of the paper.

The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO−3 leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO−3 were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep. The authors gratefully acknowledge financial support by the European Commission through the two FP6 integrated projects CarboEurope Integrated Project (project no. GOCE-CT-2003-505572) and NitroEurope Integrated Project (project no. 017841), the FP7 ECLAIRE project (grant agreement no. 282910), and the ABBA COST Action ES0804. We are also thankful for funding from the French GIP-ECOFOR consortium under the F-ORE-T forest observation and experimentation network, as well as from the MDM-2017-0714 Spanish grant. Computer time for EMEP model runs was supported by the Research Council of Norway through the NOTUR project EMEP (NN2890K). Finalization of the paper was supported by the UK Natural Environment Research Council award number NE/R016429/1 as part of the UKSCAPE programme delivering national capability.

Methane emissions from natural wetlands tend to increase with temperature and therefore may lead to a positive feedback under future climate change. However, their temperature response includes confounding factors and appears to differ on different time scales. Observed methane emissions depend strongly on temperature on a seasonal basis, but if the annual mean emissions are compared between sites, there is only a small temperature effect. We hypothesize that microbial dynamics are a major driver of the seasonal cycle and that they can explain this apparent discrepancy. We introduce a relatively simple model of methanogenic growth and dormancy into a wetland methane scheme that is used in an Earth system model. We show that this addition is sufficient to reproduce the observed seasonal dynamics of methane emissions in fully saturated wetland sites, at the same time as reproducing the annual mean emissions. We find that a more complex scheme used in recent Earth system models does not add predictive power. The sites used span a range of climatic conditions, with the majority in high latitudes. The difference in apparent temperature sensitivity seasonally versus spatially cannot be recreated by the non‐microbial schemes tested. We therefore conclude that microbial dynamics are a strong candidate to be driving the seasonal cycle of wetland methane emissions. We quantify longer‐term temperature sensitivity using this scheme and show that it gives approximately a 12% increase in emissions per degree of warming globally. This is in addition to any hydrological changes, which could also impact future methane emissions. publishedVersion

Wetlands are one of the most significant natural sources of methane (CH4) to the atmosphere. They emit CH4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH4, in addition to carbon dioxide (CO2). Production of CH4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH4 emissions are thus needed for upscaling observations to estimate present CH4 emissions and for producing scenarios of future atmospheric CH4 concentrations. Aiming at a CH4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH4, CO2, and oxygen (O2) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH4-related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of the total CH4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O2 concentrations that affect the CH4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH4 emissions in this model version., published version, peerReviewed

We measured methane (CH4) exchange rates with automatic chambers at the forest floor of a nutrient-rich drained peatland in 2011–2013. The fen, located in southern Finland, was drained for forestry in 1969 and the tree stand is now a mixture of Scots pine, Norway spruce, and pubescent birch. Our measurement system consisted of six transparent chambers and stainless steel frames, positioned on a number of different field and moss layer compositions. Gas concentrations were measured with an online cavity ring-down spectroscopy gas analyzer. Fluxes were calculated with both linear and exponential regression. The use of linear regression resulted in systematically smaller CH4 fluxes by 10–45 % as compared to exponential regression. However, the use of exponential regression with small fluxes ( 4 m−2 h−1) typically resulted in anomalously large absolute fluxes and high hour-to-hour deviations. Therefore, we recommend that fluxes are initially calculated with linear regression to determine the threshold for low fluxes and that higher fluxes are then recalculated using exponential regression. The exponential flux was clearly affected by the length of the fitting period when this period was 4 flux: the forest floor acted as a CH4 sink particularly from early summer until the end of the year, while in late winter the flux was very small and fluctuated around zero. However, the magnitude of fluxes was relatively small throughout the year, ranging mainly from −130 to +100 µg CH4 m−2 h−1. CH4 emission peaks were observed occasionally, mostly in summer during heavy rainfall events. Diurnal variation, showing a lower CH4 uptake rate during the daytime, was observed in all of the chambers, mainly in the summer and late spring, particularly in dry conditions. It was attributed more to changes in wind speed than air or soil temperature, which suggest that physical rather than biological phenomena are responsible for the observed variation. The annual net CH4 exchange varied from −104 ± 30 to −505 ± 39 mg CH4 m−2 yr−1 among the six chambers, with an average of −219 mg CH4 m−2 yr−1 over the 2-year measurement period.

Subarctic and boreal emissions of CH4 are important contributors to the atmospheric greenhouse gas (GHG) balance and subsequently the global radiative forcing. Whilst N2O emissions may be lower, the much greater radiative forcing they produce justifies their inclusion in GHG studies. In addition to the quantification of flux magnitude, it is essential that we understand the drivers of emissions to be able to accurately predict climate-driven changes and potential feedback mechanisms. Hence this study aims to increase our understanding of what drives fluxes of CH4 and N2O in a subarctic forest/wetland landscape during peak summer conditions and into the shoulder season, exploring both spatial and temporal variability, and uses satellite-derived spectral data to extrapolate from chamber-scale fluxes to a 2 km × 2 km landscape area.From static chamber measurements made during summer and autumn campaigns in 2012 in the Sodankylä region of northern Finland, we concluded that wetlands represent a significant source of CH4 (3.35 ± 0.44 mg C m−2 h−1 during the summer campaign and 0.62 ± 0.09 mg C m−2 h−1 during the autumn campaign), whilst the surrounding forests represent a small sink (−0.06 ±

The most common forest management method in Fennoscandia is rotation forestry, including clear-cutting and forest regeneration. In clear-cutting, stem wood is removed and the logging residues are either removed or left on site. Clear-cutting changes the microclimate and vegetation structure at the site, both of which affect the site's carbon balance. Peat soils with poor aeration and high carbon densities are especially prone to such changes, and significant changes in greenhouse gas exchange can be expected. We measured carbon dioxide (CO2) and energy fluxes with the eddy covariance method for 2 years (April 2016–March 2018) after clear-cutting a drained peatland forest. We observed a significant rise (23 cm) in the water table level and a large CO2 source (first year: 3086±148 g CO2 m−2 yr−1; second year: 2072±124 g CO2 m−2 yr−1). These large CO2 emissions resulted from the very low gross primary production (GPP) following the removal of photosynthesizing trees and the decline of ground vegetation, unable to compensate for the decomposition of logging residues and peat. During the second summer (June–August) after the clear-cutting, GPP had already increased by 96 % and total ecosystem respiration decreased by 14 % from the previous summer. The mean daytime ratio of sensible to latent heat flux decreased after harvesting from 2.6 in May 2016 to 1.0 in August 2016, and in 2017 it varied mostly within 0.6–1.0. In April–September, the mean daytime sensible heat flux was 33 % lower and latent heat flux 40 % higher in 2017, probably due to the recovery of ground vegetation that increased evapotranspiration and albedo of the site. In addition to CO2 and energy fluxes, we measured methane (CH4) and nitrous oxide (N2O) fluxes with manual chambers. After the clear-cutting, the site turned from a small CH4 sink into a small source and from N2O neutral to a significant N2O source. Compared to the large CO2 emissions, the 100-year global warming potential (GWP100) of the CH4 emissions was negligible. Also, the GWP100 due to increased N2O emissions was less than 10 % of that of the CO2 emission change.

We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the Boreal zone. The parameter posterior distributions were generated by adaptive population importance sampler and the optimal values by a simple stochastic optimisation algorithm. The observations used to constrain the model are evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. We were able to improve the coefficient of determination and the model bias with all stomatal conductance formulations. There was no clear candidate for the best stomatal conductance model, although certain versions produced better estimates depending on the examined variable (ET, GPP) and the used metric. We were also able to significantly enhance the model behaviour during a drought event in a Finnish Scots pine forest site. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity. This modification enabled the model to correctly time and replicate the springtime increase in GPP (and ET) for conifers throughout the measurements sites used in this study.

Forests play a crucial role in the global carbon (C) cycle by storing and sequestering a substantial amount of C in the terrestrial biosphere. Due to temporal dynamics in climate and vegetation activity, there are significant regional variations in carbon dioxide (CO₂) fluxes between the biosphere and atmosphere in forests that are affecting the global C cycle. Current forest CO₂ flux dynamics are controlled by instantaneous climate, soil, and vegetation conditions, which carry legacy effects from disturbances and extreme climate events. Our level of understanding from the legacies of these processes on net CO₂ fluxes is still limited due to their complexities and their long-term effects. Here, we combined remote sensing, climate, and eddy-covariance flux data to study net ecosystem CO₂ exchange (NEE) at 185 forest sites globally. Instead of commonly used non-dynamic statistical methods, we employed a type of recurrent neural network (RNN), called Long Short-Term Memory network (LSTM) that captures information from the vegetation and climate’s temporal dynamics. The resulting data-driven model integrates interannual and seasonal variations of climate and vegetation by using Landsat and climate data at each site. The presented LSTM algorithm was able to effectively describe the overall seasonal variability (Nash-Sutcliffe efficiency, NSE = 0.66) and across-site (NSE = 0.42) variations in NEE, while it had less success in predicting specific seasonal and interannual anomalies (NSE = 0.07). This analysis demonstrated that an LSTM approach with embedded climate and vegetation memory effects outperformed a non-dynamic statistical model (i.e. Random Forest) for estimating NEE. Additionally, it is shown that the vegetation mean seasonal cycle embeds most of the information content to realistically explain the spatial and seasonal variations in NEE. These findings show the relevance of capturing memory effects from both climate and vegetation in quantifying spatio-temporal variations in forest NEE., 28 Feb 2019: The PLOS ONE Staff (2019) Correction: Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests. PLOS ONE 14(2): e0213467. https://doi.org/10.1371/journal.pone.0213467.

Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).

Permafrost peatlands are biogeochemical hot spots in the Arctic as they store vast amounts of carbon. Permafrost thaw could release part of these long-term immobile carbon stocks as the greenhouse gases (GHGs) carbon dioxide (CO 2 ) and methane (CH 4 ) to the atmosphere, but how much, at which time-span and as which gaseous carbon species is still highly uncertain. Here we assess the effect of permafrost thaw on GHG dynamics under different moisture and vegetation scenarios in a permafrost peatland. A novel experimental approach using intact plant–soil systems (mesocosms) allowed us to simulate permafrost thaw under near-natural conditions. We monitored GHG flux dynamics via high-resolution flow-through gas measurements, combined with detailed monitoring of soil GHG concentration dynamics, yielding insights into GHG production and consumption potential of individual soil layers. Thawing the upper 10–15 cm of permafrost under dry conditions increased CO 2 emissions to the atmosphere (without vegetation: 0.74 ± 0.49 vs. 0.84 ± 0.60 g CO 2 –C m −2 day −1 ; with vegetation: 1.20 ± 0.50 vs. 1.32 ± 0.60 g CO 2 –C m −2 day −1 , mean ± SD, pre- and post-thaw, respectively). Radiocarbon dating ( 14 C) of respired CO 2 , supported by an independent curve-fitting approach, showed a clear contribution (9%–27%) of old carbon to this enhanced post-thaw CO 2 flux. Elevated concentrations of CO 2 , CH 4 , and dissolved organic carbon at depth indicated not just pulse emissions during the thawing process, but sustained decomposition and GHG production from thawed permafrost. Oxidation of CH 4 in the peat column, however, prevented CH 4 release to the atmosphere. Importantly, we show here that, under dry conditions, peatlands strengthen the permafrost–carbon feedback by adding to the atmospheric CO 2 burden post-thaw. However, as long as the water table remains low, our results reveal a strong CH 4 sink capacity in these types of Arctic ecosystems pre- and post-thaw, with the potential to compensate part of the permafrost CO 2 losses over longer timescales.

Boreal/arctic wetlands are dominated by diverse plant species, which vary in their contribution to CH4 production, oxidation and transport processes. Earlier studies have often lumped the processes all together, which may induce large uncertainties into the results. We present a novel model, which includes three vegetation classes and can be used to simulate CH4 emissions from boreal and arctic treeless wetlands. The model is based on an earlier biogeophysical model, CH4MODwetland. We grouped the vegetation as graminoids, shrubs and Sphagnum and recalibrated the vegetation parameters according to their different CH4 production, oxidation and transport capacities. Then, we used eddy-covariance-based CH4 flux observations from a boreal (Siikaneva) and a subarctic fen (Lompolojankka) in Finland to validate the model. The results showed that the recalibrated model could generally simulate the seasonal patterns of the Finnish wetlands with different plant communities. The comparison between the simulated and measured daily CH4 fluxes resulted in a correlation coefficient (R2) of 0.82 with a slope of 1.0 and an intercept of -0.1mgm-2h-1 for the Siikaneva site (n=2249, p

Simple models are less input demanding and their calibration involves a lower number of parameters, however their general applicability to vast areas must be tested. We analysed if a simple ecosystem model (PRELES) can be applied to estimate carbon and water fluxes of Boreal forests at regional scale. Multi-site (M-S) and site-specific (S-S) calibrations were compared using evapotranspiration (ET) and gross primary production (GPP) measurements from 10 sites. The performances of M-S were similar to S-Ss except for a site with agricultural history. Although PRELES predicted GPP better than ET, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. We further found that, in the calibration, the use of a long and carefully collected flux dataset from one site that covers a wide range of climate variability leads to better model performance in other sites as well.

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

Chamber measurements of trace gas fluxes between the land surface and the atmosphere have been conducted for almost a century. Different chamber techniques, including static and dynamic, have been used with varying degrees of success in estimating greenhouse gases (CO2, CH4, N2O) fluxes. However, all of these have certain disadvantages which have either prevented them from providing an adequate estimate of greenhouse gas exchange or restricted them to be used under limited conditions. Generally, chamber methods are relatively low in cost and simple to operate. In combination with the appropriate sample allocations, chamber methods are adaptable for a wide variety of studies from local to global spatial scales, and they are particularly well suited for in situ and laboratory-based studies. Consequently, chamber measurements will play an important role in the portfolio of the Pan-European long-term research infrastructure Integrated Carbon Observation System. The respective working group of the Integrated Carbon Observation System Ecosystem Monitoring Station Assembly has decided to ascertain standards and quality checks for automated and manual chamber systems instead of defining one or several standard systems provided by commercial manufacturers in order to define minimum requirements for chamber measurements. The defined requirements and recommendations related to chamber measurements are described here.

Subarctic and boreal emissions of CH4 are important contributors to the atmospheric greenhouse gas (GHG) balance and subsequently the global radiative forcing. Whilst N2O emissions may be lower, the much greater radiative forcing they produce justifies their inclusion in GHG studies. In addition to the quantification of flux magnitude, it is essential that we understand the drivers of emissions to be able to accurately predict climate-driven changes and potential feedback mechanisms. Hence this study aims to increase our understanding of what drives fluxes of CH4 and N2O in a subarctic forest/wetland landscape during peak summer conditions and into the shoulder season, exploring both spatial and temporal variability, and uses satellite-derived spectral data to extrapolate from chamber-scale fluxes to a 2 km × 2 km landscape area.From static chamber measurements made during summer and autumn campaigns in 2012 in the Sodankylä region of northern Finland, we concluded that wetlands represent a significant source of CH4 (3.35 ± 0.44 mg C m−2 h−1 during the summer campaign and 0.62 ± 0.09 mg C m−2 h−1 during the autumn campaign), whilst the surrounding forests represent a small sink (−0.06 ± −2 h−1 during the summer campaign and −0.03 ± −2 h−1 during the autumn campaign). N2O fluxes were near-zero across both ecosystems.We found a weak negative relationship between CH4 emissions and water table depth in the wetland, with emissions decreasing as the water table approached and flooded the soil surface and a positive relationship between CH4 emissions and the presence of Sphagnum mosses. Temperature was also an important driver of CH4 with emissions increasing to a peak at approximately 12 °C. Little could be determined about the drivers of N2O emissions given the small magnitude of the fluxes.A multiple regression modelling approach was used to describe CH4 emissions based on spectral data from PLEIADES PA1 satellite imagery across a 2 km × 2 km landscape. When applied across the whole image domain we calculated a CH4 source of 2.05 ± 0.61 mg C m−2 h−1. This was significantly higher than landscape estimates based on either a simple mean or weighted by forest/wetland proportion (0.99 ± 0.16, 0.93 ± 0.12 mg C m−2 h−1, respectively). Hence we conclude that ignoring the detailed spatial variability in CH4 emissions within a landscape leads to a potentially significant underestimation of landscape-scale fluxes. Given the small magnitude of measured N2O fluxes a similar level of detailed upscaling was not needed; we conclude that N2O fluxes do not currently comprise an important component of the landscape-scale GHG budget at this site.

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in land use intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out whether CO2 fluxes, measured at different sites, can be explained by common processes and parameters or to what extend a site specific configuration is needed. The model was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analyzed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. Seasonal variability in the major fluxes was well captured, when a site independent configuration was utilized for most of the parameters. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, rate coefficients for heterotrophic respiration were consistently the lowest on formerly drained sites and the highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Specific parameter values for the timing of plant shooting and senescence, the photosynthesis response to temperature, litter fall and plant respiration rates, leaf morphology and allocation fractions of new assimilates, were not needed, even though the gradient in site latitude ranged from 48° N (southern Germany) to 68° N (northern Finland) differed largely in their vegetation. This was also true for common parameters defining the moisture and temperature response for decomposition, leading to the conclusion that a site specific interpretation of these processes is not necessary. In contrast, the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon pool need to be estimated from available information on specific soil conditions, vegetation and management of the ecosystems, to be able to describe CO2 fluxes under different conditions.

Commercially available fast-response analysers for methane (CH4) and nitrous oxide (N2O) have recently become more sensitive, more robust and easier to operate. This has made their application for long-term flux measurements with the eddy-covariance method more feasible. Unlike for carbon dioxide (CO2) and water vapour (H2O), there have so far been no guidelines on how to optimise and standardise the measurements. This paper reviews the state-of-the-art of the various steps of the measurements and discusses aspects such as instrument selection, setup and maintenance, data processing as well as the additional measurements needed to aid interpretation and gap-filling. It presents the methodological protocol for eddy covariance measurements of CH4 and N2O fluxes as agreed for the ecosystem station network of the pan-European Research Infrastructure Integrated Carbon Observation System and provides a first international standard that is suggested to be adopted more widely. Fluxes can be episodic and the processes controlling the fluxes are complex, preventing simple mechanistic gap-filling strategies. Fluxes are often near or below the detection limit, requiring additional care during data processing. The protocol sets out the best practice for these conditions to avoid biasing the results and long-term budgets. It summarises the current approach to gap-filling.

Sedges ( Cyperaceae ) are dominant plants in many northern wetlands and contribute to the carbon cycling in several ways. In order to more accurately estimate the carbon balance of a wetland it is essential to be able to simulate the temporal changes of the leaf area of the sedges. Our aim was to test the ability of a simple carbon dioxide (CO 2 ) exchange model to predict the seasonal development of sedge leaf area index (LAI). The model simulates the development of sedge LAI that depends on carbon gain/loss in net photosynthesis, utilization of stored carbon in spring, and LAI decline due to senescence in late summer. The net photosynthesis model is driven by LAI, air temperature, water table depth and photosynthetically active radiation. We parameterized and validated the model with two years of observational LAI data from two boreal pristine peatland sites and included data points from both pristine and manipulated (drainage and warming) treatment plots. Model parameter values other than the timing of the start of senescence, LAI decline rate in senescence and size of carbon storage were independent of observational data. The model successfully simulated the seasonal course of LAI development and is thus an easy and adjustable tool for producing estimates of sedge LAI for other peatland sites. It can be adjusted to different sites although it cannot predict the exact LAI level of a site that is controlled by site characteristics. Its ability to simulate the interannual variation in this two-year dataset was inadequate so there is a need to test the model against longer time series of measured LAIs in order to validate models’ capability to predict the interannual variability of LAI.

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in land use intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out whether CO2 fluxes, measured at different sites, can be explained by common processes and parameters or to what extend a site specific configuration is needed. The model was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analyzed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. Seasonal variability in the major fluxes was well captured, when a site independent configuration was utilized for most of the parameters. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, rate coefficients for heterotrophic respiration were consistently the lowest on formerly drained sites and the highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Specific parameter values for the timing of plant shooting and senescence, the photosynthesis response to temperature, litter fall and plant respiration rates, leaf morphology and allocation fractions of new assimilates, were not needed, even though the gradient in site latitude ranged from 48° N (southern Germany) to 68° N (northern Finland) differed largely in their vegetation. This was also true for common parameters defining the moisture and temperature response for decomposition, leading to the conclusion that a site specific interpretation of these processes is not necessary. In contrast, the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon pool need to be estimated from available information on specific soil conditions, vegetation and management of the ecosystems, to be able to describe CO2 fluxes under different conditions.

Isotopic data provide powerful constraints on regional and global methane emissions and their source profiles. However, inverse modeling of spatially resolved methane flux is currently constrained by a lack of information on the variability of source isotopic signatures. In this study, isotopic signatures of emissions in the Fennoscandian Arctic have been determined in chambers over wetland, in the air 0.3 to 3 m above the wetland surface and by aircraft sampling from 100 m above wetlands up to the stratosphere. Overall, the methane flux to atmosphere has a coherent δ13C isotopic signature of −71 ± 1‰, measured in situ on the ground in wetlands. This is in close agreement with δ13C isotopic signatures of local and regional methane increments measured by aircraft campaigns flying through air masses containing elevated methane mole fractions. In contrast, results from wetlands in Canadian boreal forest farther south gave isotopic signatures of −67 ± 1‰. Wetland emissions dominate the local methane source measured over the European Arctic in summer. Chamber measurements demonstrate a highly variable methane flux and isotopic signature, but the results from air sampling within wetland areas show that emissions mix rapidly immediately above the wetland surface and methane emissions reaching the wider atmosphere do indeed have strongly coherent C isotope signatures. The study suggests that for boreal wetlands (>60°N) global and regional modeling can use an isotopic signature of −71‰ to apportion sources more accurately, but there is much need for further measurements over other wetlands regions to verify this.

This special issue comprising 14 articles emerged from the PAGES supported meeting: Holocene Circum Arctic Peatland Carbon Dynamics Community Wide Data Synthesis and Modeling Initiatives which took place from the 12 16 October 2013 in Bethlehem Pennsylvania. It is a precursor product of PAGES' C PEAT Working Group. ABSTRACT: Three dimensional reconstructions of peatland development patterns carbon (C) dynamics and the related radiative forcing (RF) were analyzed to improve understanding of peatland–climate feedback mechanisms. We investigated vertical and horizontal peat growth patterns of a subarctic fen (Lompolojänkkä) located in Finnish Lapland. We calculated C accumulation rates and based on these and modern gas exchange measurements developed different scenarios of Holocene carbon dioxide (CO2) and methane (CH4) fluxes and reconstructed the RF driven by these fluxes. Holocene C accumulation rates at Lompolojänkkä ranged between 2 and 30 g C/m2/yr. Plant macrofossil analysis suggests that a fen environment prevailed throughout the Holocene. However net C accumulation rates showed an extended period of low C accumulation during the mid Holocene. At the same time the lateral expansion rate of the peat area also decreased. The C flux scenarios resulted in a positive RF effect (warming) on the atmosphere following peat initiation. The RF turned negative (cooling) several hundreds to 2000 years after peat initiation. Subsequently the cooling effect increased steadily and was only temporarily interrupted when CH4 emissions were forced to increase in the model. Although climate had an important effect on peatland C dynamics its influence on RF was buffered by the long term history of C uptake.

We estimated the CH4 budget in Finland for 2004–2014 using the CTE-CH4 data assimilation system with an extended atmospheric CH4 observation network of seven sites from Finland to surrounding regio...

Earth observing systems are now routinely used to infer leaf area index (LAI) given its significance in spatial aggregation of land surface fluxes. Whether LAI is an appropriate scaling parameter for daytime growing season energy budget, surface conductance (Gs), water- and light-use efficiency and surface–atmosphere coupling of European boreal coniferous forests was explored using eddy-covariance (EC) energy and CO2 fluxes. The observed scaling relations were then explained using a biophysical multilayer soil–vegetation–atmosphere transfer model as well as by a bulk Gs representation. The LAI variations significantly alter radiation regime, within-canopy microclimate, sink/source distributions of CO2, H2O and heat, and forest floor fluxes. The contribution of forest floor to ecosystem-scale energy exchange is shown to decrease asymptotically with increased LAI, as expected. Compared with other energy budget components, dry-canopy evapotranspiration (ET) was reasonably ‘conservative’ over the studied LAI range 0.5–7.0 m2 m−2. Both ET and Gs experienced a minimum in the LAI range 1–2 m2 m−2 caused by opposing nonproportional response of stomatally controlled transpiration and ‘free’ forest floor evaporation to changes in canopy density. The young forests had strongest coupling with the atmosphere while stomatal control of energy partitioning was strongest in relatively sparse (LAI ~2 m2 m−2) pine stands growing on mineral soils. The data analysis and model results suggest that LAI may be an effective scaling parameter for net radiation and its partitioning but only in sparse stands (LAI

Globally, terrestrial ecosystems have absorbed about 30% of anthropogenic greenhouse gas emissions over the period 2000–2007 and inter-hemispheric gradients indicate that a significant fraction of terrestrial carbon sequestration must be north of the Equator. We present a compilation of the CO2, CO, CH4 and N2O balances of Europe following a dual constraint approach in which (1) a land-based balance derived mainly from ecosystem carbon inventories and (2) a land-based balance derived from flux measurements are compared to (3) the atmospheric data-based balance derived from inversions constrained by measurements of atmospheric GHG (greenhouse gas) concentrations. Good agreement between the GHG balances based on fluxes (1294 ± 545 Tg C in CO2-eq yr−1), inventories (1299 ± 200 Tg C in CO2-eq yr−1) and inversions (1210 ± 405 Tg C in CO2-eq yr−1) increases our confidence that the processes underlying the European GHG budget are well understood and reasonably sampled. However, the uncertainty remains large and largely lacks formal estimates. Given that European net land to atmosphere exchanges are determined by a few dominant fluxes, the uncertainty of these key components needs to be formally estimated before efforts could be made to reduce the overall uncertainty. The net land-to-atmosphere flux is a net source for CO2, CO, CH4 and N2O, because the anthropogenic emissions by far exceed the biogenic sink strength. The dual-constraint approach confirmed that the European biogenic sink removes as much as 205 ± 72 Tg C yr−1 from fossil fuel burning from the atmosphere. However, This C is being sequestered in both terrestrial and inland aquatic ecosystems. If the C-cost for ecosystem management is taken into account, the net uptake of ecosystems is estimated to decrease by 45% but still indicates substantial C-sequestration. However, when the balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is offset by emissions of non-CO2 GHGs. As such, the European ecosystems are unlikely to contribute to mitigating the effects of climate change.

Nitrous oxide (N 2 O) fluxes were measured fortnightly to monthly with manual chambers in 2004-2008 and hourly with automatic chambers during the snow-free seasons of 2007 and 2008 in a sedge fen in northern Finland. The fluxes were generally low, varying from -45 to 37 μg N 2 O―N m ―2 hour ―1 (negative fluxes indicating uptake of N 2 O from the atmosphere into the soil) and showing large spatial and temporal variation. Slightly higher emissions were observed in winter than in summer. On an annual scale, the fen acted as a N 2 O source. The annual balances showed a clear decreasing trend from 1.1 kg N ha ―1 year ―1 (= 12.2 μg N m ―2 hour ―1 ) in 2004 to zero balances in 2007 and 2008. Two potential reasons for the decreasing mean flux were (i) a decreasing atmospheric N deposition during the snow-free season, and (ii) a rising water-table level (WTL), which restricts the availability of oxygen in the peat and therefore favours the formation of molecular nitrogen (N 2 ) instead of N 2 O by the denitrifying microbes. The measurements conducted with the automatic chambers during the snow-free season showed a positive exponential relationship between the N 2 O flux and the temperature in 2008, but not in 2007. Similarly, a unimodal relationship with the WTL was found in 2008, with maximum fluxes observed when the WTL was about 4 cm above the fen surface. No diurnal variation in N 2 O fluxes measured by automatic chambers was found. The fluxes measured by the manual or automatic chambers were similar in magnitude, but different in their temporal pattern. The daily N 2 O concentration at a depth of 0.15 m in the peat was always lower than the ambient atmospheric concentration, indicating that at this depth the atmospheric N 2 O was consumed. Together with the observed negative flux rates this suggests that microbial N 2 production is a significant part of the N cycle in this fen.

Northern peatlands cover approximately 4% of the global land surface area. Those peatlands will be particularly vulnerable to environmental and climate change and therefore it is important to investigate their total greenhouse gas (GHG) budgets, to determine the feedback on the climate. Nitrogen (N) is known to influence the GHG budget in particular by affecting the methane (CH(4)) balance. At two peatland sites in Scotland and Finland GHG fluxes of carbon dioxide (CO(2)), methane and nitrous oxide (N(2)O) and nitrogen fluxes were measured as part of the European project 'NitroEurope'. The Scottish site, Auchencorth Moss, was a GHG sink of -321, -490 and -321 g CO(2) eq m(-2) year(-1) in 2006, 2007 and 2008, respectively, with CO(2) as the dominating GHG. In contrast, the dominating GHG at the Finnish site, Lompolojankka, was CH(4), resulting in the site being a net GHG source of +485 and +431 g CO(2) eq m(-2) year(-1) in 2006 and 2007, respectively. Therefore. Auchencorth Moss had a negative global warming potential (GWP) whilst Lompolojankka had a positive GWP over the investigated time period. Initial results yielded a positive N budget for Lompolojankka of 7.1 kg N ha(-1) year(-1), meaning the site was gaining nitrogen, and a negative N budget for Auchencorth Moss of -2.4 kg N ha year(-1), meaning the site was losing nitrogen.