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International audience; Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (

Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

Methane (CH4) is a strong greenhouse gas that accelerates climate change, yet its emissions from wetlands in general and Arctic permafrost-affected wetlands in particular remain very uncertain in the global CH4 budget. Arctic CH4 sources and the expected effect of permafrost thaw on these sources have gained much attention by the public, media, policy makers, and researchers during the past decade, but neither inversion nor process-based models provide clear trends in emissions and there has not been any observational evidence for increasing CH4 emissions from Arctic permafrost ecosystems.Here, we provide this observational evidence. Based on the longest record of direct Arctic CH4 flux observations acquired since 2002 at a Siberian tundra site using the eddy covariance method, we found an increase in the early summer (June and July) CH4 emissions by 1.9 ± 0.7 % yr-1 since 2004 along with a strong increase in June air temperatures of 0.3 ± 0.1 °C yr-1. Although the tundra’s maximum source strength in August has not yet changed and the overall mean annual emissions of 171.5 ± 12.3 mmol m−2 yr−1 remain in the lower half of the published range, the increase in early summer methane emissions shows that atmospheric warming has begun to affect the methane flux dynamics of permafrost-affected ecosystems in the Arctic. This is especially noteworthy, given the very thick and cold continuous permafrost in the study area compared to most other observational sites.While the observed changes clearly happen in the early warm season, we also estimate 39 % of the annual emission to originate from the re-freezing and frozen period, highlighting the importance of the cold season for annual permafrost CH4 emission estimates and the substantial challenges in achieving continuous data coverage in the Arctic winter.

Spatio-temporal patterns of methane (CH4) and carbon dioxide (CO2) release from natural sources needs to be better understood across the Arctic region. Climate change in the Arctic is occurring at a pace that may be 2 to 4 times the global average, and existing measurements derive from a limited number of field sites, and most originate during the growing season although important studies show that release continues during winter. The Mackenzie River Delta in the western Canadian Arctic holds thin and destabilizing permafrost, high organic content soils, a high proportion of wetlands, and vast natural gas occurrences at depth, all of which create high methane potential. In the present study, we conducted atmospheric CH4 and CO2 measurements using a mobile laboratory equipped with a greenhouse gas analyzer during the summer and winter. We also visited known aquatic and terrestrial CH4 flux hotspots, including pingos, lakes, river channels and wetlands, where we measured concentration transects and stable carbon isotope (13C-CH4) values to characterize CH4source and spatial pattern. Source stable carbon isotope (δ13C-CH4) signatures at hotspots ranged from -42 to -88 ‰ δ13C-CH4. Active surface microbial production was responsible for at least 4 of the 8 hotspots investigated, indicating that microbial production may be responsible for a greater number of CH4 hotspots than is indicated by previous studies in the region. Mobile surveys showed that shrubland, grassland and deep water were the most important ecosystems for CH4 and CO2 production during the wintertime and that low lying areas of the Delta had the highest atmospheric mixing ratios of CH4.

Rewetting drained peatlands is recognized as a leading and effective natural climate solution to curbing greenhouse gas (GHG) emissions. However, CO2 source-to-sink transition is not necessarily detected in years immediately following rewetting and temporal dynamics in carbon budgets can be seen in rewetted systems. Here, we investigate long-term (2008 & 2013 - present) ecosystem flux measurements using the eddy covariance technique, revealing the temporal patterns of annual carbon dioxide (CO2) and methane (CH4) fluxes, in a rewetted peatland site in northeastern Germany. We show that site-level annual emissions presented in this study are only approaching the IPCC default Tier 1 emission factors (EFs) and those suggested for the German national inventory report after 13-16 years of rewetting when the optimum range of water level (close to the soil surface) is reached during the vegetation period. Overall, our results indicate that in addition to annual variation in soil temperature, vegetation development (post-rewetting successional vegetation dynamics) along with water table depth have the greatest effect on the carbon sink function. We further observe a transitional change into a new phase in the ecosystem carbon status throughout the study period that includes a source-to-sink transition of annual CO2 fluxes in 2020. The decreasing trend for CO2 fluxes is estimated at -0.37 t CO2-C ha-1 yr-1 and -44 kg CH4 ha-1 yr-1 for CH4 emissions for the period until 2021. While we found a strong reduction in CH4 emissions in 2019 (following a severe drought), the negative trend in CH4 emissions in the years before the drought event is still statistically significant (-17 kg CH4 ha-1 yr-1). Accordingly, a considerable reduction of the 100-year annual global warming potential (GWP) and sustained-flux global warming potential (SGWP) was observed during the course of the study and potentially approaching a new steady-state phase within the last few years. In Germany, the published long-term datasets from rewetted peatlands only cover a period of ≤10 years after rewetting, thus, the duration of potential phases and development of future emissions are still unclear. This outlines the need for more long-term datasets to cover the source-to-sink transition in rewetted peatlands that also capture the impacts of likely future climate extremes. Here, we aim to establish a baseline to contribute a better understanding of the transitioning, complexity, and climate sensitivity of rewetted systems by analyzing the dynamics within the site and the inter-annual variability via their respective drivers. The introduction, monitoring, and targeted management of an ensemble of site characteristics (coverage/type of dominant vegetation, average water level along with microclimate and microtopographic conditions) is necessary in understanding the transient nature of such systems and further refine the existing static default EFs.

Being the most accurate, direct, and defensible method available to date for studying the ecosystem scale gas exchange, the eddy covariance (EC) method was used to examine the net carbon exchange over an alpine steppe ecosystem near the Nam Co Station for Multi-sphere Observation and Research (NAMORS) on the Tibetan Plateau. EC measurements are site-specific and the values represent the total sum of the relative contribution of fluxes from all the components within the footprint over the measurement time. The scattered and uneven distribution of EC towers and their small footprint demand upscaling of the flux observations to a regional scale for improving understanding of the net exchange of CO2 between the terrestrial biosphere and the atmosphere. Regional scale carbon estimates are highly variable and not fully explored as compared to carbon balance studies at extreme ends of the spatial scale spectrum (large continental scale and small vegetation stand scale). Translating the spatially sparse measurements into consistent, gridded flux estimates at the regional scale is a prerequisite for quantifying the current terrestrial carbon cycle. But the uncertainties caused by the representativeness error in the model grids while quantifying the regional estimates of carbon exchange are not fully investigated due to limited data availability as well as knowledge of flux variability at the grid scale. Rather than extrapolating the point scale and/or site-specific scale measurements by fitting any statistical model to predict ecosystem or earth system processes, a systematic upscaling approach is vital for refining mathematical models and accounting for the grid-scale uncertainties for better policy decisions. As an initial step to this, the net ecosystem exchange (NEE) of carbon estimated at two different measurement heights of 3 m and 19 m, in the early growing period of 2019 were used to quantify and analyze the interdependencies in the flux measurements at two heights and the influence of heterogeneity within the footprint in the measured fluxes.Keywords: Eddy covariance, Carbon flux, Net ecosystem exchange, Tibetan Plateau

The cropland carbon (C) balance at regional scale still contains high uncertainties not the least due to the problem of up-scaling C fluxes of temporarily and spatially highly divers ecosystems. The C-exchange between the terrestrial ecosystem and the atmosphere constitute the largest and most uncertain flux of the cropland C balance, as opposed to C import from organic (manure) and C export through harvest which are lower and less uncertain.Combining satellite data with local eddy covariance CO2-flux data is commonly used to up-scale the C-exchange signal from point to regional scale across global ecosystems. Low spatial resolution products like MODIS limit their applicability and accuracy to larger homogeneous areas involving a high degree of uncertainty rather than detecting and tracing highly dynamic (farm-)field scale CO2-fluxes from space. We are using eddy-covariance CO2-flux data of an arable field in conjunction with Sentinel-2 derived vegetation indices (VI) to assess the ability of the satellite data to monitor daily net-ecosystem exchange (NEE), gross-primary productivity (GPP) and ecosystem respiration (Reco) based on a matched footprint. Simple linear regression models are built to test the ability of a range of VIs (NDVI, GNDVI, EVI, EVI2, SAVI, MNDWI, NDWI, SR, S2REP) to monitor and predict CO2-exchange for croplands. We analyze the correlation between measured CO2-fluxes and VIs over the course of the growing seasons to assess the suitability and accuracy of the VIs along the phenological year. We present a single site analysis to zoom into short-comings of this approach and how the satellite signal relates to vegetation CO2-exchange. VIs generally show a high variability in their predictive power. Still, results suggest a similarly high accuracy as mechanistic modelling approaches for suitable VIs, e.g. the cumulative C-exchange (NEE) of winter wheat of one growing season based on NDVI and GNDVI is over- and under-estimated by only 33 (15%) and 41 (18%) g C m-2 respectively.

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).

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003–2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco), net ecosystem CO2 exchange (NEE; Reco − GPP), and terrestrial methane (CH4) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of −850 Tg CO2-C year−1. Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4) were estimated at 35 Tg CH4-C year−1. Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Peatlands are among the largest stocks of soil carbon, which can be stored for thousands of years under well-wetted conditions. The main goals of the study were to assess annual and seasonal CO2 balances of a temperate peatland and the main biophysical factors affecting these CO2 fluxes. The studied peatland was usually a CO2 sink with a mean annual net ecosystem production (NEP) of 110±83 gCO2-C·m^−2·yr^−1 and extreme balances in 2006 (-17 gCO2-C·m^−2·yr^−1) and 2011 (194 gCO2-C·m^−2·yr^−1). Annual fluxes were not significantly correlated with biophysical variables, unlike seasonal data. Furthermore, the average air temperature in spring and summer was related to NEP at r^2=0.65 and r^2=0.61, respectively (warmer spring increased NEP while hot summer decreased NEP in these seasons). A decrease in daytime measured NEP during the summer period (June-August) was observed when TA exceeded 25 °C or VPD was above 15 hPa, respectively, due to the growing Reco and possibly plant photorespiration. These findings suggest a negative impact of ongoing global warming on temperate peatland CO2 balances.

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.

The Arctic–boreal zone (ABZ) is experiencing amplified warming, actively changing biogeochemical cycling of vegetation and soils. The land-to-atmosphere fluxes of CO2 in the ABZ have the potential to increase in magnitude and feedback to the climate causing additional large-scale warming. The ability to model and predict this vulnerability is critical to preparation for a warming world, but Earth system models have biases that may hinder understanding of the rapidly changing ABZ carbon fluxes. Here we investigate circumpolar carbon cycling represented by the Community Land Model 5 (CLM5.0) with a focus on seasonal gross primary productivity (GPP) in plant functional types (PFTs). We benchmark model results using data from satellite remote sensing products and eddy covariance towers. We find consistent biases in CLM5.0 relative to observational constraints: (1) the onset of deciduous plant productivity to be late; (2) the offset of productivity to lag and remain abnormally high for all PFTs in fall; (3) a high bias of grass, shrub, and needleleaf evergreen tree productivity; and (4) an underestimation of productivity of deciduous trees. Based on these biases, we focus on model development of alternate phenology, photosynthesis schemes, and carbon allocation parameters at eddy covariance tower sites. Although our improvements are focused on productivity, our final model recommendation results in other component CO2 fluxes, e.g., net ecosystem exchange (NEE) and terrestrial ecosystem respiration (TER), that are more consistent with observations. Results suggest that algorithms developed for lower latitudes and more temperate environments can be inaccurate when extrapolated to the ABZ, and that many land surface models may not accurately represent carbon cycling and its recent rapid changes in high-latitude ecosystems, especially when analyzed by individual PFTs.

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.

The Tibetan alpine steppe ecosystem covers an area of roughly 800 000 km 2 and contains up to 3.3 % soil organic carbon in the uppermost 30 cm, summing up to 1.93 Pg C for the Tibet Autonomous Region only (472 037 km 2 ). With temperatures rising 2 to 3 times faster than the global average, these carbon stocks are at risk of loss due to enhanced soil respiration. The remote location and the harsh environmental conditions on the Tibetan Plateau (TP) make it challenging to derive accurate data on the ecosystem–atmosphere exchange of carbon dioxide (CO 2 ) and water vapor ( H2O ). Here, we provide the first multiyear data set of CO 2 and H2O fluxes from the central Tibetan alpine steppe ecosystem, measured in situ using the eddy covariance technique. The calculated fluxes were rigorously quality checked and carefully corrected for a drift in concentration measurements. The gas analyzer self-heating effect during cold conditions was evaluated using the standard correction procedure and newly revised formulations ( Burba et al. , 2008 ; Frank and Massman , 2020 ) . A wind field analysis was conducted to identify influences of adjacent buildings on the turbulence regime and to exclude the disturbed fluxes from subsequent computations. The presented CO 2 fluxes were additionally gap filled using a standardized approach. The very low net carbon uptake across the 15-year data set highlights the special vulnerability of the Tibetan alpine steppe ecosystem to become a source of CO 2 due to global warming. The data are freely available at https://doi.org/10.5281/zenodo.3733202 ( Nieberding et al. , 2020 a ) and https://doi.org/10.11888/Meteoro.tpdc.270333 ( Nieberding et al. , 2020 b ) and may help us to better understand the role of the Tibetan alpine steppe in the global carbon–climate feedback.

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 (https://doi.org/10.3334/ORNLDAAC/1934, Virkkala et al., 2021a).

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...

The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for sustainable development in the Artic-boreal region. Air quality in China and long-range transport of the atmospheric pollutants was also indicated as one of the most crucial topics of the research agenda. This paper summarizes results obtained during the last five years in the Northern Eurasian region. It also introduces recent observations on the air quality in the urban environments in China. The main regions of interest are the Russian Arctic, Northern Eurasian boreal forests (Siberia) and peatlands and on the mega cities in China. We frame our analysis against research themes introduced in 2015. We summarize recent progress in the understanding of the land – atmosphere – ocean systems feedbacks. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate-Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, such as enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate the climate change and the socio-economic development to tackle air quality issues.

The regional variability in tundra and boreal carbon dioxide (CO

Optical images of the Earth at very high spatial resolutions (VHR, typically < 5 m) are seeing rapid growth in volumes over the past 5 years, due in part to the fast-expanding constellations of CubeSats. Special preprocessing of these VHR images is required to ensure their geometric and radiometric consistency for quantitative analyses for a wide range of Earth and environmental sciences and applications. Here we describe a hierarchical normalization framework (HiNF) to achieve and evaluate geometric and radiometric normalization of these VHR images towards producing analysis ready data (ARD) of optical CubeSat images. We demonstrated HiNF at a spatially heterogeneous and temporally dynamic wetland site in northeastern Germany by generating a stack of temporally consistent ~ biweekly 5-m images over 8 years (2013–2020) at visible and near infrared bands (VNIR). The HiNF combined images from rigorously calibrated multispectral sensors onboard large satellites (Landsat-7/8 and Sentinel-2) and less well calibrated sensors onboard RapidEye (SmallSats) and PlanetScope (CubeSats). A two-stage radiometric normalization procedure produced two levels of image normalization and resulted in more normalized images that passed the quality control in time series compared to common one-stage procedures. The outcome of this novel procedure allows for downstream applications to balance between the quality and the quantity of available normalized CubeSat images in a time series. The HiNF provides a new approach to quantitative evaluations of radiometric normalizations using daily MODIS imagery as bridging benchmark data. The quantitative evaluations showed the HiNF resulted in greater normalization efficacy in the visible bands than in the NIR over the predominantly wetland area. The two normalization levels yielded statistically similar efficacy for the NIR band and the widely-used normalized difference vegetation index according to the Chow test (at significance level of 0.05) but less so for the visible bands. The HiNF facilitates generating ARD of optical CubeSat images and assuring their qualities through its demonstrated efficacy and its quantitative evaluation approach. Such ARD-quality time series of VHR images from CubeSats allow for improved analyses and quantitative applications of this new stream of multispectral images at spatial scales that are better related to ground measurements and environmental management in terrestrial ecosystems.

The Arctic-boreal zone (ABZ) is experiencing amplified warming, actively changing biogeochemical cycling of vegetation and soils. The land-to-atmosphere fluxes of CO2 in the ABZ have the potential to increase in magnitude and feedback to the climate causing additional large scale warming. The ability to model and predict this vulnerability is critical to preparation for a warming world, but Earth system models have biases that may hinder understanding the rapidly changing ABZ carbon fluxes. Here we investigate circumpolar carbon cycling represented by the Community Land Model 5 (CLM5.0) with a focus on seasonal gross primary productivity (GPP) in plant functional types (PFTs). We benchmark model results using data from satellite remote sensing products and eddy covariance towers. We find consistent biases in CLM5.0 relative to observational constraints: (1) the onset of deciduous plant productivity to be late, (2) the offset of productivity to lag and remain abnormally high for all PFTs in fall, (3) a high bias of grass, shrub, and needleleaf evergreen tree productivity, and (4) an underestimation of productivity of deciduous trees. Based on these biases, we focus model development of alternate phenology, photosynthesis schemes, and carbon allocation parameters at eddy covariance tower sites. Although our improvements are focused on productivity, our final Model Recommendation results in other component CO2 fluxes, e.g. Net Ecosystem Exchange (NEE) and Terrestrial Ecosystem Respiration (TER), that are more consistent with observations. Results suggest that algorithms developed for lower latitudes and more temperate environments can be inaccurate when extrapolated to the ABZ, and that many land surface models may not accurately represent carbon cycling and its recent rapid changes in high latitude ecosystems, especially when analyzed by individual PFTs.

The Tibetan alpine steppe ecosystem covers an area of roughly 800,000 km2, containing up to 3.3 % soil organic carbon in the uppermost 30 cm, summing up to 1.93 PgvC for the Tibet Autonomous Region only (472,037 km2). With temperatures rising two to three times faster than the global average, these carbon stocks are at risk of loss due to enhanced soil respiration. The remote location and the harsh environmental conditions on the Tibetan Plateau (TP) make it challenging to derive accurate data on ecosystem-atmosphere exchange of carbon dioxide (CO2) and water vapor (H2O). Here, we provide the first multi-year data set of CO2 and H2O fluxes from the central Tibetan alpine steppe ecosystem, measured in situ using the eddy covariance technique. The calculated fluxes were rigorously quality checked and carefully corrected for a drift in concentration measurements and gas analyzer self heating during cold conditions. A wind field analysis was conducted to identify influences of adjacent buildings on the turbulence regime and to exclude the disturbed fluxes from subsequent computations. The presented CO2 fluxes were additionally gap filled using a standardized approach. The very low net carbon uptake across the 15-year data set highlights the special vulnerability of the Tibetan alpine steppe ecosystem to become a source of CO2 due to global warming. The data is freely available (https://www.doi.org/10.5281/zenodo.3733203, Nieberding et al., 2020b) and may help to better understand the role of the Tibetan alpine steppe in the global carbon-climate feedback.

Changing environmental conditions in the Arctic have profound impacts on permafrost coasts, which erode at great pace. Although numbers exist on annual carbon and sediment fluxes from coastal erosion, little is known on how terrestrial organic matter (OM) is transformed by thermokarst and –erosional processes on transit from land to sea. Here, we investigated a retrogressive thaw slump (RTS) on Qikiqtaruk - Herschel Island in the western Canadian Arctic. The RTS was classified into an undisturbed, disturbed and nearshore zone and systematically sampled along transects. Collected sediments were analyzed for organic carbon (OC), nitrogen (N), stable carbon isotopes (δ13C-OC) and ammonium. C/N-ratios, δ13C-signatures and ammonium concentrations were used as general indicator for OM degradation. Permafrost sediments from the RTS headwall and mud lobe sediments from the thaw stream outlet were incubated to further assess OM degradation and potential greenhouse gas formation during slumping and upon release into the nearshore zone. Our results show that OM concentrations significantly decrease upon slumping in the disturbed zone with OC and N decreasing by >70% and >50%, respectively. Whereas δ13C-signatures remain fairly stable, C/N-ratios decrease significantly and ammonium concentrations increase slightly in fresh slumping material. Nearshore sediments have low OM contents and a terrestrial signature comparable to disturbed sites on land. The incubations show that carbon dioxide (CO2) forms quickly from thawing permafrost deposits and mud debris with ~2-3 mg CO2 per gram dry weight being cumulatively produced within two months. We suggest that the initial strong decrease in OM concentration after slumping is caused by a combination of OC degradation, dilution with melted massive ice and immediate offshore transport via the thaw stream. After stabilization in the slump floor, recolonizing vegetation takes up N from the disturbed sediment. Upon release into the nearshore zone, larger portions of OM are directly deposited in marine sediments, where they further degrade or being buried. The incubations indicate that CO2 is rapidly produced upon slumping and potentially continues to form within the nearshore zone that receives eroded material. We conclude that coastal RTS systems profoundly change the characteristic of modern and ancient permafrost terrestrial OM during transit from land to sea - a process which is likely linked to the production of greenhouse gases. Our study provides valuable information on the potential fate of terrestrial OM along eroding permafrost coasts under the trajectory of a warming Arctic.

When using open path infrared gas analyzers (IRGA), lens contamination, calibration inaccuracies and ageing internal chemicals may lead to a slow drift in gas concentration measurements. During flux calculations, these errors are usually not accounted for under the assumption, that a slow drift in mean gas concentrations (i.e. over several weeks to months) does not affect the estimation of turbulent fluctuations and, hence, of covariances. This is however not the case. In fact, Serrano-Ortiz et al. (2008) estimated that an underestimation of the CO2 concentration will propagate into an overestimation of the carbon uptake via the WPL correction. In addition, for instruments – such as the widely used LI-7500 – where a nonlinear calibration curve relates raw absorptance measurements to gas concentration, Fratini et al. (2014) have shown that errors in mean concentrations leak into errors in fluxes on account of amplified or dampened estimated fluctuations. Both these effects can be eliminated, possibly completely, when the drift in gas concentration is corrected before raw data processing. Therefore, the offset between measured and reference (i.e. "real") gas concentrations has to be quantified and converted into the corresponding zero absorption biases. We performed the drift correction on a 15 years dataset from the Tibetan Plateau, where an extreme drift in concentration measurements occurred. Due to the remote location, user calibrations were performed irregularly, and no independent gas concentration measurements are available. Hence, we used the CO2 concentration measurements from the Mauna Loa atmospheric observatory (NOAA ESRL Global Monitoring Division, 2018, updated annually) as reference gas concentration to derive an offset for every half hour measurement. The offset in H­­2O mixing ratios could be determined from auxiliary low frequency measurements of relative humidity, temperature and air pressure. We then converted mixing ratios to raw absorptances using the instrument-specific calibration curve to apply an absorptance offset to every 10 Hz measurement, thus eliminating the long-term drift in both mean values and fluctuations of gas concentrations. The corrected raw data time series were then used for calculation of fluxes and subsequent corrections, including de-spiking, axis rotation, detrending and correction for spectral attenuations and air density fluctuations. In comparison to the uncorrected fluxes, the corrected fluxes yielded a considerably lower carbon uptake during daytime and summer, which is in compliance with instrument theory of operation and the results from numerical simulations and field data analysis as conducted by Fratini et al. (2014). Fratini, G., McDermitt, D.K. & Papale, D. (2014) Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction. Biogeosciences, 11, 1037–1051.NOAA ESRL Global Monitoring Division (2018, updated annually) Atmospheric Carbon Dioxide Dry Air Mole Fractions from quasi-continuous measurements at Mauna Loa, Hawaii, Barrow, Alaska, American Samoa and South Pole. Compiled by K.W. Thoning, D.R. Kitzis, and A. Crotwell., 2019th edn. NOAA ESRL GMD CCGG Group, Boulder, Colorado, USA.Serrano-Ortiz, P., Kowalski, A.S., Domingo, F., Ruiz, B. & Alados-Arboledas, L. (2008) Consequences of Uncertainties in CO2 Density for Estimating Net Ecosystem CO2 Exchange by Open-path Eddy Covariance. Boundary-Layer Meteorology, 126, 209–218.

Increased methane (CH4) release from a warming Arctic is expected to be a major feedback on the global climate. However, due to the complex effects of climate change on arctic geoecosystems, projections of future CH4 emissions are highly uncertain. CH4 emissions from complex tundra landscapes will be controlled not only by direct climatic effects on production, oxidation and transport of CH4 but, importantly, also by geomorphology and hydrology changes caused by gradual or abrupt permafrost degradation. Therefore, improving our understanding of both the temporal dynamics and the spatial heterogeneity of CH4 fluxes on multiple scales is still necessary.Here, we present pedon- and landscape-scale CH4 flux measurements at two widespread tundra landscapes (active floodplains and late-holocene river terraces) of the Lena River Delta in the Siberian Arctic (72.4° N, 126.5° E). The dominating scales of spatial variability of soil, vegetation and CH4 fluxes differ between the two landscapes of different geological development stage. The active floodplains are characterized by sandy beaches and ridges, and backswamp depressions, forming a mesorelief with height differences of several meters on horizontal scales of 10-1000 m. On the other hand, the river terraces are characterized by the formation of ice-wedge polygons, which lead to a regular microrelief with height differences of several decimeters on horizontal scales of 1 to 10 meters. CH4 fluxes were investigated on the landscape scale with the eddy covariance method (15 campaigns during 2002-2018 at the river terrace, 2 campaigns 2014-2015 at the floodplain) and on the pedon scale with chamber methods (campaigns at different sites in 2002, 2006, 2013, 2014, 2015).Average growing season (June-September) CH4 flux for the floodplain was 166 ± 4 mmol m-2 (n=2) and for the river terrace 100 ± 25 mmol m-2 (n=15). There was pronounced spatial variability of CH4 fluxes within both tundra landscapes types. On the river terrace, growing season CH4 flux was only 20-40 mmol m-2 at elevated polygon rims and polygon high centers, respectively, and up to 300 mmol m-2 at polygon low centers. On the floodplain, CH4 flux was as low as 5 mmol m-2 at sandy ridges and above 400 mmol m-2 in backswamp depressions. Mean growing season CH4 fluxes at the river terrace were positively linearly correlated (r2 = 0.9, n=15) to growing-degree-days (base temperature of 5 °C). Our findings suggest that a warmer climate stimulates the production of CH4, which is directly reflected in increased CH4 emissions. On the other hand, warming effects on CH4 oxidation appear limited because transport processes that bypass the soil oxidation zone, i.e. plant-mediated transport and ebullition, dominate CH4 emission from wet tundra landscapes. However, since CH4 emissions strongly vary with (micro-)topographical situation within tundra landscapes, the changes of geomorphology and hydrology due to permafrost degradation will probably be the dominating driver of future CH4 emissions from arctic tundra landscapes.

Forest soils are often a sink for atmospheric methane (CH4) and are thus worth special attention in the context of mitigation of greenhouse gases (GHGs) and offset of agricultural GHG emissions at farm to national levels. The litter layer influences the exchange of GHGs between soil and atmosphere; however, most studies focus on the contribution of only soil to the CH4 cycle. In order to improve the inventory of this gas, it is worth investigating how litter influences the exchange of GHGs. Its effect on CH4 uptake may vary in deciduous and coniferous sites due to the different properties of litter. Field experiments were carried out to assess the CH4 uptake capability in 5 different soil types (with and without litter) under different forest types (deciduous, coniferous, and mixed) in Poland. During summer 2019, the highest CH4 uptake (about 2 mg C m-2 day-1) in a variant without litter on the ground was detected in Dystric Cambisol (with the highest C/N ratio) under a 100-year-old coniferous forest and in Albic Luvisol under a 58-year-old mixed forest. The presence of the litter level reduced the CH4 flux in the range of 6-27% in these locations. Methane consumption was the lowest in silty soils (~ 0.4 – 1 mg C m-2 day-1) in the mixed forest and decreased by 13-29% when covered with the litter layer. The negative effect of the litter layer on CH4 absorption was the lowest (~ 3-4%) in sandy Eutric Gleysol under a 75-year-old deciduous forest with 90% of oak and 10% of European hornbeam. The dry conditions in the summer 2019 (with total rainfall 163 mm during the tested months in the studied region) resulted in low moisture in both the litter and soil. However, even low-humidity litter (below 10%) reduced CH4 consumption rates in the measured sites.Research was partially conducted under the project financed by Polish National Centre for Research and Development within of ERA-NET CO-FUND ERA-GAS Programme (ERA-GAS/I/GHG-MANAGE/01/2018).

Northern lakes are considered a major source of atmospheric methane (CH4), a potent GHG1,2. However, large uncertainties in their emissions (7–26 Tg CH4 yr–1; ref. 2) arise from challenges in upscaling field data, including fluxes by ebullition (bubbling), the dominant emission pathway2. Remote sensing of ebullition would allow detailed mapping of regional emissions but has hitherto not been developed. Here, we show that lake ebullition can be imaged using synthetic aperture radar remote sensing during ice-cover periods by exploiting the effect of ebullition on the texture of the ice–water interface. Applying this method to five Alaska regions and combining spatial remote sensing information with year-round bubble-trap flux measurements, we create ebullition-flux maps for 5,143 Alaskan lakes. Regional lake CH4 emissions, based on satellite remote sensing analyses, were lower compared to previous estimates based on upscaling from individual lakes2,3 and were consistent with independent airborne CH4 observations. Thermokarst lakes formed by thaw of organic-rich permafrost had the highest fluxes, although lake density and lake size distributions also controlled regional emissions. This new remote sensing approach offers an opportunity to improve knowledge about Arctic CH4 fluxes and helps to explain long-standing discrepancies between estimates of CH4 emissions from atmospheric measurements and data upscaled from individual lakes. Arctic lake methane emissions, which occur primarily by ebullition, are difficult to quantify from extrapolating in situ data due to spatial and temporal variability. Remote sensing can detect ebullition, through changes in frozen lake surface properties, reducing uncertainty in emission fluxes.

Low-level flights over tundra wetlands in Alaska and Canada have been conducted during the Airborne Measurements of Methane Emissions (AirMeth) campaigns to measure turbulent methane fluxes in the atmosphere. In this paper we describe the instrumentation and new calibration procedures for the essential pressure parameters required for turbulence sensing by aircraft that exploit suitable regular measurement flight legs without the need for dedicated calibration patterns. We estimate the accuracy of the mean wind and the turbulence measurements. We show that airborne measurements of turbulent fluxes of methane and carbon dioxide using cavity ring-down spectroscopy trace gas analysers together with established turbulence equipment achieve a relative accuracy similar to that of measurements of sensible heat flux if applied during low-level flights over natural area sources. The inertial subrange of the trace gas fluctuations cannot be resolved due to insufficient high-frequency precision of the analyser, but, since this scatter is uncorrelated with the vertical wind velocity, the covariance and thus the flux are reproduced correctly. In the covariance spectra the -7/3 drop-off in the inertial subrange can be reproduced if sufficient data are available for averaging. For convective conditions and flight legs of several tens of kilometres we estimate the flux detection limit to be about 4 mg m−2 d−1 for w′CH4′‾, 1.4 g m−2 d−1 for w′CO2′‾ and 4.2 W m−2 for the sensible heat flux.

We conducted eddy covariance measurements from April to August 2014 on a Siberian thermokarst lake. The study site is located in the Lena River Delta and characterized as a floating ice lake. Heat fluxes differed in magnitudes, directions and temporal patterns depending on the lake surface conditions (“frozen” ice cover, ice cover melt, and open water). Significant heat release during frozen ice cover conditions highlighted the importance of lakes for the landscape heat budget and water balance. The energy balance was nearly closed during the open water period and highlighted the impact of melting energy on its closure during the ice cover period. Sensible and latent heat dynamics were driven by temperature and water vapor gradients scaled by wind speed, respectively. We calculated bulk aerodynamics transfer coefficients and evaluated the performance of the derived in situ and three independent heat flux parameterization schemes. We found that bulk transfer models perform moderately to poorly for the different lake surface conditions. During the open water period small-scale temporal variability could not be represented by the models, particularly in case of latent heat flux. The model results were less sensitive to the specific model type than to the accuracy of the surface water temperature measurement, which is dependent on a well-thought-out measurement design. Our study stresses considerations that are crucial for similar campaigns in the future, in order to face the measurement challenges encountered on arctic lakes especially during the ice cover period.

Both the frequency and intensity of drought events are expected to increase, with unresolved alterations to peatland methane cycling and the involved microbial communities. While existing studies have assessed drought effects via experimental approaches under controlled conditions, to our knowledge, no studies have examined the in-situ effects of natural drought in restored temperate fens. In this study, we used quantitative polymerase chain reaction (qPCR) and high throughput 16S rRNA gene amplicon sequencing of DNA and complementary DNA (cDNA) to determine the abundances and community structure of total and putatively active microbial communities following the 2018 European summer drought. Together with geochemical and methane flux data, we compared these results to a non-drought reference dataset. During drought, water level and methane flux rates decreased to a new recent minimum in both fens. This corresponded with pronounced shifts in porewater geochemistry. Microbial community composition in the drought year differed markedly, and was characterized by a greater relative and total abundance of aerobic methanotrophs, and, in one of the two sites, by a decrease in total methanogen abundance. In contrast to the non-drought reference years, type I methanotrophs were clearly more dominant than type II methanotrophs in both fens. cDNA sequencing confirmed the activity of type I methanotrophs during drought, with Methylomonaceae having the highest average relative abundance of bacterial cDNA transcripts. We show that changes in microbial community dynamics, porewater geochemistry, and ecosystem methane fluxes can be substantial following natural drought in restored fens, and provide the first in-situ evidence from a natural drought which suggests type I methanotroph populations are more active than type II methanotrophs in response to drought effects. Type I methanotrophs may represent a key microbial control over methane emissions in restored temperate fens subject to natural drought.

A proof of concept study was performed to demonstrate the capabilities of quadrocopter air sampling for analysing the methane isotopic composition in the laboratory. Boundary layer mixing processes and the methane isotopic composition were studied with a quadrocopter system at Polder Zarnekow in Mecklenburg–West Pomerania in the North East of Germany, which has become a strong source of biogenically produced methane after rewetting the drained and degraded peatland. Methane fluxes are measured continuously at the site. They show high emissions from May to September, and a strong diurnal variability with maximum methane fluxes up to 2 μmol m−2 s−1 for summer 2018. For two case studies on 23 May 2018 and 5 September 2018, vertical profiles of temperature and humidity were recorded up to an altitude of 650 m and 1000 m, respectively, during the morning transition. Air samples were taken at different altitudes and analysed in the laboratory for methane isotopic composition. The values showed a different isotopic signature in the vertical distribution during stable conditions in the morning (−51.5 ‰ below the temperature inversion at an altitude of 150 m on 23 May 2018 and at an altitude of 50 m on 5 September 2018, −50.1 ‰ above). After the onset of turbulent mixing, the isotopic signature was the same throughout the vertical column with a mean value of −49.9 &pm; 0.45 ‰. During the September study, water samples were analysed as well for methane concentration and isotopic composition in order to provide a link between surface and atmosphere. The water samples reveal high variability on scales of few 10 m for this particular case. The airborne sampling system and consecutive analysis chain were shown to provide reliable and reproducible results for two samples obtained simultaneously. The method presents a powerful tool for constraining the origin of methane by analysing its isotopic signature, and for measuring the vertical distribution of methane isotopic signature, which is based on mixing processes of methane within the atmospheric boundary layer.

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO 2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004–2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO 2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.

In natural coastal wetlands, high supplies of marine sulfate suppress methanogenesis. Coastal wetlands are, however, often subject to disturbance by diking and drainage for agricultural use and can turn to potent methane sources when rewetted for remediation. This suggests that preceding land use measures can suspend the sulfate-related methane suppressing mechanisms. Here, we unravel the hydrological relocation and biogeochemical S and C transformation processes that induced high methane emissions in a disturbed and rewetted peatland despite former brackish impact. The underlying processes were investigated along a transect of increasing distance to the coastline using a combination of concentration patterns, stable isotope partitioning, and analysis of the microbial community structure. We found that diking and freshwater rewetting caused a distinct freshening and an efficient depletion of the brackish sulfate reservoir by dissimilatory sulfate reduction (DSR). Despite some legacy effects of brackish impact expressed as high amounts of sedimentary S and elevated electrical conductivities, contemporary metabolic processes operated mainly under sulfate-limited conditions. This opened up favorable conditions for the establishment of a prospering methanogenic community in the top 30–40 cm of peat, the structure and physiology of which resemble those of terrestrial organic-rich environments. Locally, high amounts of sulfate persisted in deeper peat layers through the inhibition of DSR, probably by competitive electron acceptors of terrestrial origin, for example Fe(III). However, as sulfate occurred only in peat layers below 30–40 cm, it did not interfere with high methane emissions on an ecosystem scale. Our results indicate that the climate effect of disturbed and remediated coastal wetlands cannot simply be derived by analogy with their natural counterparts. From a greenhouse gas perspective, the re-exposure of diked wetlands to natural coastal dynamics would literally open up the floodgates for a replenishment of the marine sulfate pool and therefore constitute an efficient measure to reduce methane emissions.

Ground-based observations of land--atmosphere fluxes are necessary to progressively improve global climate models. Observed data can be used for model evaluation and to develop or tune process models. In arctic permafrost regions, climate–carbon feedbacks are amplified. Therefore, increased efforts to better represent these regions in global climate models have been made in recent years. We present a multiannual time series of land–atmosphere carbon dioxide fluxes measured in situ with the eddy covariance technique in the Siberian Arctic (72°22′ N, 126°30′ E). The site is part of the international network of carbon dioxide flux observation stations (FLUXNET, Site ID: Ru-Sam). The dataset includes consistently processed fluxes based on concentration measurements of closed-path and open-path gas analyzers. With parallel records from both sensor types, we were able to apply a site-specific correction to open-path fluxes. This correction is necessary due to a deterioration of data, caused by heat generated by the electronics of open-path gas analyzers. Parameterizing this correction for subperiods of distinct sensor setups yielded good agreement between open and closed-path fluxes. We compiled a long-term (2002 to 2017) carbon dioxide flux time series that we additionally gap-filled with a standardized approach. The data set was uploaded to the Pangaea data base and can be accessed through https://doi.pangaea.de/10.1594/PANGAEA.892751.

The rewetting of drained peatlands alters peat geochemistry and often leads to sustained elevated methane emission. Although this methane is produced entirely by microbial activity, the distribution and abundance of methane-cycling microbes in rewetted peatlands, especially in fens, is rarely described. In this study, we compare the community composition and abundance of methane-cycling microbes in relation to peat porewater geochemistry in two rewetted fens in northeastern Germany, a coastal brackish fen and a freshwater riparian fen, with known high methane fluxes. We utilized 16S rDNA high-throughput sequencing and quantitative polymerase chain reaction on 16S rDNA, mcrA, and pmoA genes to determine microbial community composition and the abundance of total bacteria, methanogens, and methanotrophs. Electrical conductivity was more than three times higher in the coastal fen than in the riparian fen, averaging 5.3 and 1.5 mS cm−1, respectively. Porewater concentrations of terminal electron acceptors varied within and among the fens. This was also reflected in similarly high intra- and inter-site variations of microbial community composition. Despite these differences in environmental conditions and electron acceptor availability, we found a low abundance of methanotrophs and a high abundance of methanogens, represented in particular by Methanosaetaceae, in both fens. This suggests that rapid re/establishment of methanogens and slow re/establishment of methanotrophs contributes to prolonged increased methane emissions following rewetting.

Low level flights over tundra wetlands in Alaska and Canada have been conducted during the AirMeth campaigns to measure turbulent methane fluxes into the atmosphere. In this paper we describe the instrumentation and new calibration procedures for the essential pressure parameters required for turbulence sensing by an aircraft that exploit suitable regular measurement flight legs without the need for dedicated calibration patterns. We estimate the accuracy of the mean wind and the turbulence measurements. We show that airborne measurements of turbulent fluxes of methane and carbon dioxide using cavity ring down spectroscopy trace gas analysers together with established turbulence equipment achieves a relative accuracy similar to that of measurements of sensible heat flux if applied during low level flights over natural area sources. The inertial subrange of the trace gas fluctuations cannot be resolved due to insufficient high frequency precision of the analyser but since this scatter is uncorrelated with the vertical wind velocity, the covariance and thus the flux is reproduced correctly. In the covariance spectra the −7/3 drop-off in the inertial subrange can be reproduced if sufficient data are available for averaging. For convective conditions and flight legs of several tens of kilometers we estimate the flux detection limit to about 4 mg/m2/d for w'CH4', 1.4 g/m2/d for w'CO2', and 4.2 W/m2/s for the sensible heat flux.

High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR ≦ GPP

Evapotranspiration (ET) estimates based on remote sensing are constrained by the spatial and temporal resolution of spaceborne observations. Therefore, the choice to be made is whether mode...

Waterbodies in the arctic permafrost zone are considered a major source of the greenhouse gas methane (CH4) in addition to CH4 emissions from arctic wetlands. However, the spatio-temporal variability of CH4 fluxes from waterbodies compli- cates spatial extrapolation of CH4 measurements from single waterbodies. There- fore, their contribution to the CH4 budget of the arctic permafrost zone is not yet well understood. Using the example of two study areas of 1,000 km2 each in the Mackenzie Delta, Canada, we approach this issue (i) by analyzing correlations on the landscape scale between numerous waterbodies and CH4 fluxes and (ii) by analyzing the influence of the spatial resolution of CH4 flux data on the detected relation- ships. A CH4 flux map with a resolution of 100 m was derived from two aircraft eddy-covariance campaigns in the summers of 2012 and 2013. We combined the CH4 flux map with high spatial resolution (2.5 m) waterbody maps from the Per- mafrost Region Pond and Lake Database and classified the waterbody depth based on Sentinel-1 SAR backscatter data. Subsequently, we reduced the resolution of the CH4 flux map to analyze if different spatial resolutions of CH4 flux data affected the detectability of relationships between waterbody coverage, number, depth, or size and the CH4 flux. We did not find consistent correlations between waterbody characteristics and the CH4 flux in the two study areas across the different resolu- tions. Our results indicate that waterbodies in permafrost landscapes, even if they seem to be emission hot spots on an individual basis or contain zones of above average emissions, do currently not necessarily translate into significant CH4 emis- sion hot spots on a regional scale, but their role might change in a warmer climate. KEYWORDS airborne eddy-covariance, Arctic, CH4, lakes, ponds, remote sensing, Sentinel-1, TerraSAR-X

Peatlands store substantial amount of carbon, are vulnerable to climate change. To predict the fate of carbon stored in peatlands, the complex interactions between water, peat and vegetations need more attention. This study describes a modified version of the ORCHIDEE land surface model for simulating the hydrology, surface energy and CO2 fluxes of peatlands on daily to annual time scales. The model, referred to as ORCHIDEE-PEAT, includes a separate soil tile in each 0.5° grid-cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation with a grid-cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model is evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site to match the peak of growing season gross primary productivity (GPP), derived from direct EC measurements. Regarding short-term variations from day to day, the model performance was good for the variations in GPP (r2 = 0.76, Nash-Sutcliff modeling efficiency, MEF = 0.76), with lesser accuracy for latent heat fluxes (LE, r2 = 0.42, MEF = 0.14) and Net ecosystem CO2 exchange (NEE, r2 = 0.38, MEF = 0.26). Seasonal variations in GPP, NEE and energy fluxes on monthly scales showed moderate to high r2 values ranging from 0.57 to 0.86. For spatial across-sites gradients of annual mean GPP, NEE and LE, r2 of 0.93, 0.27, and 0.71, respectively, were achieved. The water table variations are not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, when using the observed water table in the carbon module to define the fraction of oxic and anoxic decomposition instead of the modeled water table, ORCHIDEE-PEAT shows a small improvement in reproducing NEE. Moreover, we found a significant relationship between optimized Vcmax and the latitude (temperature), which can better reflect the spatial gradients of annual NEE than using an average Vcmax value. In a future version of ORCHIDEE-PEAT, the influences of water table on photosynthesis and depth-dependent influences of soil temperature on respiration may be included.

This study presents the systematic development of an open-source, flexible and modular eddy-covariance (EC) data processing framework. This is achieved through adopting a Development and Systems Operation (DevOps) philosophy, building on the eddy4R family of EC code packages in the R Language for Statistical Computing as foundation. These packages are community-developed via the GitHub distributed version control system and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. This framework is applicable beyond EC, and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time. The efficiency and consistency of this framework is demonstrated in the form of three application examples. These include tower EC data from first instruments installed at a National Ecological Observatory (NEON) field site, aircraft flux measurements in combination with remote sensing data, as well as a software intercomparison. In conjunction with this study, the first two eddy4R packages and simple NEON EC data products are released publicly. While this proof-of-concept represents a significant advance, substantial work remains to arrive at the automated framework needed for the streaming generation of science-grade EC fluxes.

Estimation of high-resolution terrestrial evapotranspiration (ET) from Landsat data is important in many climatic, hydrologic, and agricultural applications, as it can help bridging the gap between existing coarse-resolution ET products and point-based field measurements. However, there is large uncertainty among existing ET products from Landsat that limit their application. This study presents a simple Taylor skill fusion (STS) method that merges five Landsat-based ET products and directly measured ET from eddy covariance (EC) to improve the global estimation of terrestrial ET. The STS method uses a weighted average of the individual ET products and weights are determined by their Taylor skill scores (S). The validation with site-scale measurements at 206 EC flux towers showed large differences and uncertainties among the five ET products. The merged ET product exhibited the best performance with a decrease in the averaged root-mean-square error (RMSE) by 2-5 W/m(2) when compared to the individual products. To evaluate the reliability of the STS method at the regional scale, the weights of the STS method for these five ET products were determined using EC ground-measurements. An example of regional ET mapping demonstrates that the STS-merged ET can effectively integrate the individual Landsat ET products. Our proposed method provides an improved high-resolution ET product for identifying agricultural crop water consumption and providing a diagnostic assessment for global land surface models. (C) 2017 Elsevier B.V. All rights reserved.