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Tundra and boreal ecosystems encompass the northern circumpolar permafrost region and are experiencing rapid environmental change with important implications for the global carbon (C) budget. We analysed multi-decadal time series containing 302 annual estimates of carbon dioxide (CO2) flux across 70 permafrost and non-permafrost ecosystems, and 672 estimates of summer CO2 flux across 181 ecosystems. We find an increase in the annual CO2 sink across non-permafrost ecosystems but not permafrost ecosystems, despite similar increases in summer uptake. Thus, recent non-growing-season CO2 losses have substantially impacted the CO2 balance of permafrost ecosystems. Furthermore, analysis of interannual variability reveals warmer summers amplify the C cycle (increase productivity and respiration) at putatively nitrogen-limited sites and at sites less reliant on summer precipitation for water use. Our findings suggest that water and nutrient availability will be important predictors of the C-cycle response of these ecosystems to future warming.

AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux's diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team's quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.

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, 10.3334/ORNLDAAC/1934). Copyright:

Arctic tundra has the potential to generate significant climate feedbacks, but spatial complexity makes it difficult to quantify the impacts of climate on ecosystem-atmosphere fluxes, particularly in polygonal tundra comprising wetter and drier polygon types on the scale of tens of meters. We measured CO2, CH4, and energy fluxes using eddy covariance for 7 yr (April to November, 2013–2019) in polygonal tundra near Utqiagvik, Alaska. This period saw the earliest snowmelt, latest snow accumulation, and hottest summer on record. To estimate fluxes by polygon type, we combined a polygon classification with a flux-footprint model. Methane fluxes were highest in the summer months but were also large during freeze-up and increased with the warming trend in August–November temperatures. While CO2 respiration had a consistent, exponential relationship with temperature, net ecosystem exchange was more variable among years. CO2 and CH4 exchange (June–September) ranged between −0.83 (Standard error [SE] = 0.03) and −1.32 (SE = 0.04) μmol m−2 s−1 and 13.92 (SE = 0.26)—23.42 (SE = 0.45) nmol m−2 s−1, respectively, and varied interannually (p ≤ 0.05). The maximum-influence method effectively attributed fluxes to polygon types. Areas dominated by low-centered polygons had higher CO2 fluxes except in 2016–2017. Methane fluxes were highest in low-centered polygons 2013–2015 and in flat-centered polygons in subsequent years, possibly due to increasing temperature and precipitation. Sensible and latent heat fluxes also varied significantly among polygon types. Accurate characterization of Arctic fluxes and their climate dependencies requires spatial disaggregation and long term observations.

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

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 20g g€¯S to 20g g€¯N) the spring onset of elevated CH4 emissions starts 3g€¯d earlier, and the CH4 emission season lasts 4g€¯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 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.

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

We describe a new coordination activity and initial results for a global synthesis of eddy covariance CH4 flux measurements.

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; CO 2 , CH 4 , N 2 O, H 2 O) 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.

Solar radiation is a key driver of energy and carbon fluxes in natural ecosystems. Radiation measurements are essential for interpreting ecosystem scale greenhouse gases and energy fluxes as well as many other observations performed at ecosystem stations of the Integrated Carbon Observation System (ICOS). We describe and explain the relevance of the radiation variables that are monitored continuously at ICOS ecosystem stations and define recommendations to perform these measurements with consistent and comparable accuracy. The measurement methodology and instruments are described including detailed technical specifications. Guidelines for instrumental set up as well as for operation, maintenance and data collection are defined considering both ICOS scientific objectives and practical operational constraints. For measurements of short-wave (solar) and long wave (infrared) radiation components, requirements for the ICOS network are based on available well-defined state-of-The art standards (World Meteorological Organization, International Organization for Standardization). For photosynthetically active radiation measurements, some basic instrumental requirements are based on the performance of commercially available sensors. Since site specific conditions and practical constraints at individual ICOS ecosystem stations may hamper the applicability of standard requirements, we recommend that ICOS develops mid-Term coordinated actions to assess the effective level of uncertainties in radiation measurements at the network scale.

We determine the annual timing of spring recovery from space-borne microwave radiometer observations across northern hemisphere boreal evergreen forests for 1979-2014. We find a trend of advanced spring recovery of carbon uptake for this period, with a total average shift of 8.1 d (2.3 d/decade). We use this trend to estimate the corresponding changes in gross primary production (GPP) by applying in situ carbon flux observations. Micrometeorological CO2 measurements at four sites in northern Europe and North America indicate that such an advance in spring recovery would have increased the January-June GPP sum by 29 g⋅C⋅m-2 [8.4 g⋅C⋅m-2 (3.7%)/decade]. We find this sensitivity of the measured springtime GPP to the spring recovery to be in accordance with the corresponding sensitivity derived from simulations with a land ecosystem model coupled to a global circulation model. The model-predicted increase in springtime cumulative GPP was 0.035 Pg/decade [15.5 g⋅C⋅m-2 (6.8%)/decade] for Eurasian forests and 0.017 Pg/decade for forests in North America [9.8 g⋅C⋅m-2 (4.4%)/decade]. This change in the springtime sum of GPP related to the timing of spring snowmelt is quantified here for boreal evergreen forests.

Arctic terrestrial ecosystems are major global sources of methane (CH4); hence, it is important to understand the seasonal and climatic controls on CH4 emissions from these systems. Here, we report year-round CH4 emissions from Alaskan Arctic tundra eddy flux sites and regional fluxes derived from aircraft data. We find that emissions during the cold season (September to May) account for ≥ 50% of the annual CH4 flux, with the highest emissions from noninundated upland tundra. A major fraction of cold season emissions occur during the zero curtain period, when subsurface soil temperatures are poised near 0 °C. The zero curtain may persist longer than the growing season, and CH4 emissions are enhanced when the duration is extended by a deep thawed layer as can occur with thick snow cover. Regional scale fluxes of CH4 derived from aircraft data demonstrate the large spatial extent of late season CH4 emissions. Scaled to the circumpolar Arctic, cold season fluxes from tundra total 12 ± 5 (95% confidence interval) Tg CH4 y(-1), ∼ 25% of global emissions from extratropical wetlands, or ∼ 6% of total global wetland methane emissions. The dominance of late-season emissions, sensitivity to soil environmental conditions, and importance of dry tundra are not currently simulated in most global climate models. Because Arctic warming disproportionally impacts the cold season, our results suggest that higher cold-season CH4 emissions will result from observed and predicted increases in snow thickness, active layer depth, and soil temperature, representing important positive feedbacks on climate warming.

Arctic tundra has the potential to generate significant climate feedbacks, but spatial complexity makes it difficult to quantify the impacts of climate on ecosystem‐atmosphere fluxes, particularly in polygonal tundra comprising wetter and drier polygon types on the scale of tens of meters. We measured CO2, CH4, and energy fluxes using eddy covariance for 7 yr (April to November, 2013–2019) in polygonal tundra near Utqiagvik, Alaska. This period saw the earliest snowmelt, latest snow accumulation, and hottest summer on record. To estimate fluxes by polygon type, we combined a polygon classification with a flux‐footprint model. Methane fluxes were highest in the summer months but were also large during freeze‐up and increased with the warming trend in August–November temperatures. While CO2 respiration had a consistent, exponential relationship with temperature, net ecosystem exchange was more variable among years. CO2 and CH4 exchange (June–September) ranged between −0.83 (Standard error [SE] = 0.03) and −1.32 (SE = 0.04) μmol m−2 s−1 and 13.92 (SE = 0.26)—23.42 (SE = 0.45) nmol m−2 s−1, respectively, and varied interannually (p ≤ 0.05). The maximum‐influence method effectively attributed fluxes to polygon types. Areas dominated by low‐centered polygons had higher CO2 fluxes except in 2016–2017. Methane fluxes were highest in low‐centered polygons 2013–2015 and in flat‐centered polygons in subsequent years, possibly due to increasing temperature and precipitation. Sensible and latent heat fluxes also varied significantly among polygon types. Accurate characterization of Arctic fluxes and their climate dependencies requires spatial disaggregation and long term observations. Plain Language Summary: We measured carbon dioxide and methane fluxes for 7 yr (April to November, 2013–2019) in polygonal tundra near Utqiagvik (Barrow), Alaska using eddy covariance (EC). The EC method provides the measurements of vertical flux of transported air parcels by correlation of the fluctuations in carbon dioxide or methane concentration with fluctuations in the vertical wind speed. The ice wedge polygonal tundra area is covered by ponds, drained lake basins, and wetter and drier polygon types on the scale of tens of meters across. This period saw the earliest snowmelt, latest snow accumulation date, and hottest summer on record. To estimate fluxes by polygon type, we combined a polygon classification with a flux‐footprint model. The model represents the field of view of the EC system and allows the user to extract the location of the peak contribution. The site was a net carbon sink between June and September in each of the seven years. Areas dominated by low‐centered polygons had higher carbon dioxide fluxes except in 2016–2017, while methane fluxes were highest in low‐centered polygons 2013–2015 and in flat‐centered polygons in subsequent years. This is possibly due to increasing temperature and precipitation. Not only were methane fluxes highest in the summer months but also large during freeze‐up and increased with the warming trend in August–November temperatures. Key Points: The site was a carbon sink between June and September in each of the 7 yr (2013–2019)Combining a polygon classification with footprint model allowed separation of fluxes by polygon typeWe recorded high methane fluxes during summer but also during freeze‐up periods [ABSTRACT FROM AUTHOR]