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over the past decade, the data have remained spread across different repositories, scientific articles, and unpublished sources, making it difficult to leverage.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

The Arctic-boreal region’s carbon balance is shifting, with major implications for global climate. Models predict high carbon emissions by 2100, consisting of greenhouse gases, carbon dioxide (CO 2 ) and methane (CH 4 ), thus a representative carbon flux monitoring network is crucial to constrain fluxes. Eddy flux towers are increasingly used to inform models, and the area towers represent define model limitations. The Arctic-boreal flux tower network has grown from one to over 100 over past decades, however, towers are not designed to have broad regional representation. We analyzed flux tower network improvements made between 2022 and 2024, when targeted sites were added in part by the Permafrost Pathways project. We assessed the representativeness of active sites for four measurement categories: growing season CO 2 , growing season CH 4 , year-round CO 2 , and year-round CH 4 . Sixteen new or upgraded sites improved representation over 23–55% of the Arctic-boreal region across categories. Seventy-five percent of the region was well represented given improvements in growing season CO 2 measurements; however, only 45% of the domain was well represented for year-round CH 4 . We show targeted improvements can obtain better representativeness with limited sites, but continued upgrades are necessary to close gaps, particularly in Russia where gaps remain large.

Abstract Peatlands store about one‐third of total global soil carbon. Vegetation composition strongly regulates peatland carbon dynamics. Global warming and climate‐driven ecohydrological changes are expected to alter peatland vegetation composition, necessitating accurate simulation of vegetation dynamics to predict future fate of peatland carbon. We incorporated six plant functional types (PFTs) into the ORCHIDEE‐PEAT model to represent bryophytes (mosses), C3 graminoids (sedges and grasses), boreal broadleaf deciduous shrubs, boreal needleleaf evergreen trees, tropical evergreen and raingreen (water‐driven deciduous) trees growing in peatlands. The introduction and elimination of each PFT in response to bioclimatic conditions, as well as sapling establishment, growth, mortality, and competition among PFTs, are explicitly modeled. Simulated vegetation distributions align well with site‐level observations from West Siberian wetlands, where extensive vegetation composition measurements are available for model evaluation. The model slightly overestimated gross primary productivity (GPP) across 60 sites. Evaluation using global satellite‐derived land cover, leaf area index and GPP data was encouraging, though challenges lie in the lack of observational data specific to peatlands. From 1901 to 2020, simulated tropical peatland vegetation composition remains relatively stable. In northern peatlands, as a result of warming and declining water table, bryophyte and C3 graminoid cover decrease by 0.2 (13%) and 0.1 (13%) million km2, respectively, while shrub and tree cover increase by 0.3 (75%) and 0.03 (2%) million km2, respectively. The impacts of these vegetation shift on peatland carbon balance can be explored in future studies using the model, which integrates peatland vegetation dynamics with peatland‐specific hydrology and carbon cycling.

Methane measurements, particularly of natural sources, need to be expanded considerably.

Small uncrewed aerial systems (sUASs) can be used to quantify emissions of greenhouse and other gases, providing flexibility in quantifying these emissions from a multitude of sources, including oil and gas infrastructure, volcano plumes, wildfire emissions, and natural sources. However, sUAS-based emission estimates are sensitive to the accuracy of wind speed and direction measurements. In this study, we examined how filtering and correcting sUAS-based wind measurements affects data accuracy by comparing data from a miniature ultrasonic anemometer mounted on a sUAS in a joust configuration to highly accurate wind data taken from a nearby eddy covariance flux tower (aka the Tower). These corrections had a small effect on wind speed error, but reduced wind direction errors from 50° to >120° to 20–30°. A concurrent experiment examining the amount of error due to the sUAS and the Tower not being co-located showed that the impact of this separation was 0.16–0.21 ms−1, a small influence on wind speed errors. Lower wind speed errors were correlated with lower turbulence intensity and higher relative wind speeds. There were also some loose trends in diminished wind direction errors at higher relative wind speeds. Therefore, to improve the quality of sUAS-based wind measurements, our study suggested that flight planning consider optimizing conditions that can lower turbulence intensity and maximize relative wind speeds as well as include post-flight corrections.

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

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

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15-70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

We review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science. We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire. Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.

Global warming increases ecosystem respiration (ER), creating a positive carbon-climate feedback. Thermal acclimation, the direct responses of biological communities to reduce the effects of temperature changes on respiration rates, is a critical mechanism that compensates for warming-induced ER increases and dampens this positive feedback. However, the extent and effects of this mechanism across diverse ecosystems remain unclear. By analyzing CO2 flux data from 93 eddy covariance sites worldwide, we observed thermal acclimation at 84 % of the sites. If sustained, thermal acclimation could reduce projected warming-induced nighttime ER increases by at least 25 % across most climate zones by 2041-2060. Strong thermal acclimation is particularly evident in ecosystems at high elevation, with low-carbon-content soils, and within tundra, semi-arid, and warm-summer Mediterranean climates, supporting the hypothesis that extreme environments favor the evolution of greater acclimation potential. Moreover, ecosystems with dense vegetation and high productivity such as humid tropical and subtropical forests generally exhibit strong thermal acclimation, suggesting that regions with substantial CO2 uptake may continue to serve as strong carbon sinks. Conversely, some ecosystems in cold continental climates show signs of enhancing thermal responses, the opposite of thermal acclimation, which could exacerbate carbon losses as climate warms. Our study underscores the widespread yet climate-specific patterns of thermal acclimation in global terrestrial ER, emphasizing the need to incorporate these patterns into Earth System Models for more accurate carbon-climate feedback projections.

The warming Arctic could accelerate climate change as permafrost soil carbon is released as greenhouse gas emissions from boreal forest, tundra, and wetland ecosystems. Record climate conditions are increasingly common, with the 2023–2024 winter (September–April) documented as having the warmest land surface air temperatures on record for the Arctic region. However, corresponding impacts on ecosystem greenhouse gas fluxes typically take several years to diagnose, creating a knowledge gap between contemporary climate events and these fluxes. Here we synthesized near real-time data from 19 eddy covariance flux tower sites across the Arctic through the summer of 2024. This analysis revealed record net carbon dioxide and methane emissions occurring in winter, coinciding with warm 2023–2024 winter conditions. The increasing recognition of the importance of winter in shaping ecosystem carbon balance is still challenged by the difficulty of collecting data, with far more carbon flux measurements available in summer as compared to year-round. Improving the observation network’s extent and ability to deliver near real-time updates could provide immediate knowledge about the speed and strength of the permafrost carbon feedback to climate change. This increased awareness could help nations adapt their emissions policies aimed to avoid the worst impacts of climate change.

Widespread changes to near-surface permafrost in northern ecosystems are occurring through gradual top-down thaw and more abrupt localized thermokarst development. Both thaw types are associated with a loss of ecosystem services, including soil hydrothermal and mechanical stability and long-term carbon storage. Here, we analyzed relationships between the vascular understory, basal moss layer, active layer thickness (ALT), and greenhouse gas fluxes along a thaw gradient from permafrost peat plateau to thaw bog in Interior Alaska. We used ALT to define four distinct stages of thaw: Stable, Early, Intermediate, and Advanced, and we identified key plant taxa that serve as reliable indicators of each stage. Advanced thaw, with a thicker active layer and more developed thermokarst features, was associated with increased abundance of graminoids and Sphagnum mosses but decreased plant species richness and ericoid abundance, as well as a substantial increase in methane emissions. Early thaw, characterized by active layer thickening without thermokarst development, coincided with decreased ericoid cover and plant species richness and an increase in CH4 emissions. Our findings suggest that early stages of thaw, prior to the formation of thermokarst features, are associated with distinct vegetation and soil moisture changes that lead to abrupt increases in methane emissions, which then are perpetuated through ground surface subsidence and collapse scar bog formation. Current modeling of permafrost peatlands will underestimate carbon emissions from thawing permafrost unless these linkages between plant community, nonlinear active layer dynamics, and carbon fluxes of emerging thaw features are integrated into modeling frameworks.

The Arctic-Boreal Zone (ABZ) is rapidly warming, impacting its large soil carbon stocks. We use a new compilation of terrestrial ecosystem CO2 fluxes, geospatial datasets and random forest models to show that although the ABZ was an increasing terrestrial CO2 sink from 2001 to 2020 (mean ± standard deviation in net ecosystem exchange: -548 ± 140 Tg C yr-1; trend: -14 Tg C yr-1, p<0.001), more than 30% of the region was a net CO2 source. Tundra regions may have already started to function on average as CO2 sources, demonstrating a critical shift in carbon dynamics. After factoring in fire emissions, the increasing ABZ sink was no longer statistically significant (budget: -319 ± 140 Tg C yr-1; trend: -9 Tg C yr-1), with the permafrost region becoming CO2 neutral (budget: -24 ± 123 Tg C yr-1; trend: -3 Tg C yr-1), underscoring the importance of fire in this region.### Competing Interest StatementThe authors have declared no competing interest.

Intraspecific trait variation can influence plant performance in different environments and may thereby determine the ability of individual plants to respond to climate change. However, our understanding of its patterns and environmental drivers across different spatial scales is incomplete, especially in understudied regions like the Arctic. To fill this knowledge gap, we examined above-ground and below-ground traits from three shrub taxa expanding across the tundra biome and evaluated their relationships with multiple microenvironmental and macroclimatic factors. The traits reflected plant size and structure (plant height, leaf area and root to shoot ratio), leaf economics (specific leaf area, nitrogen content), and root economics and collaboration with mycorrhizal fungi (specific root length, root tissue density, nitrogen content, and ectomycorrhizal colonisation intensity). We also measured leaf and root delta 15N and leaf delta 13C to characterise nitrogen source and acquisition pathways and plant water stress. Traits were measured in replicated plots (N = 135) varying in soil microclimate, thaw depth and organic layer thickness established across five sites spanning a macroclimate gradient in northern Alaska. This hierarchical design allowed us to disentangle the independent and combined effects of fine-scale and broad-scale factors on intraspecific trait variation. We found substantial intraspecific variation at fine spatial scales for most traits and less variation along the macroclimate gradient and between shrub taxa. Consistent with these patterns, microenvironmental factors, mainly soil moisture and thaw depth, interacted with macroclimate, mainly climatic water deficit, to structure size-structural and leaf trait variation. In contrast, most root traits responded additively to thaw depth and macroclimate. Synthesis. Our results demonstrate that above-ground and below-ground tundra shrub traits respond differently to microenvironmental and macroclimatic variation. These differing responses contribute to substantial trait variation at fine spatial scales and may decouple above-ground and below-ground trait responses to climate change. Studying three deciduous shrub taxa expanding across the tundra biome, the authors found substantial intraspecific trait variation at fine spatial scales and less variation along a macroclimate gradient and among taxa. Non-additive interactions between soil microenvironmental variables and climatic water deficit suggest that above-ground traits will exhibit responses to climate change that depend strongly on subsurface environmental conditions.image

Decadal scale lake drying in interior Alaska results in lake margin colonization by willow shrub and graminoid vegetation, but the effects of these changes on plant production, biodiversity, soil properties, and soil microbial communities are not well known. We studied changes in soil organic carbon (SOC) and nitrogen (N) storage, plant and microbial community composition, and soil microbial activities in drying and non-drying lakes in the Yukon Flats National Wildlife Refuge. Historic changes in lake area were determined using Landsat imagery. Results showed that SOC storage in drying lake margins declined by 0.13 kg C m-2 yr-1 over 30 years of exposure of lake sediments, with no significant change in soil N. Lake drying resulted in an increase in graminoid and shrub aboveground net primary production (ANPP, +3% yr-1) with little change in plant functional composition. Increases in ANPP were similar in magnitude (but opposite in sign) to losses in SOC over a 30-year drying trend. Potential decomposition rates and soil enzyme activities were lower in drying lake margins compared to stable lake margins, possibly due to high salinities in drying lake margin soils. Microbial communities shifted in response to changing plant communities, although they still retained a legacy of the previous plant community. Understanding how changing lake hydrology impacts the ecology and biogeochemistry of lake margin terrestrial ecosystems is an underexamined phenomenon with large impacts to landscape processes. Lake dominated ecosystems in Alaska have experienced periods of widespread lake drying in the past. We understand little of what occurs on these new nearshore habitats following lake drying, especially changes in soil properties and soil microbial communities. Using a combination of remote sensing and field sampling on hundreds of lakes in the Yukon Flats National Wildlife Refuge, we learned that lake margin soils lose significant quantities of soil C in the decades following lake drying, and at the same time soils become increasingly saline and soil microbial activites are reduced. Overall, lake drying has large impacts on the surrounding ecosystems and it is important to understand these changes for management. Lake drying in the Yukon Flats National Wildlife Refuge triggers a succession of plant and microbial communities and losses of lake margin soil organic carbon (SOC) Lake drying also results in increases in the salinity of lake margin soils, slowing rates of microbial activities Although lake drying resulted in losses of SOC, increases in Aboveground Net Primary Production (ANPP) compensated for these losses

Accurate representation of cryohydrological processes is fundamental for biosphere models, particularly at high-latitudes, given their influence on carbon and permafrost dynamics in carbon-rich peatlands and wetlands.This study analyzes site-level simulations in moist and wet drainage conditions in continuous or discontinuous permafrost regions, using a terrestrial ecosystem model DVM-DOS-TEM.Functional benchmarking was conducted against eddy covariance flux alongside soil temperature, moisture, and thaw depth observations.Thermal and hydrological analysis reveals parameter sensitivity and uncertainty concerning carbon cycling and permafrost dynamics.Flux representation is markedly consistent at sites characterized by continuous permafrost with less seasonal variation, owing to longer soil freezing duration.Sites in discontinuous permafrost, exhibiting active permafrost degradation and talik formation, pose considerable challenges in accurately depicting thaw depth.Underprediction of soil moisture across all sites has more pronounced effects on boreal wetlands characterized by thick organic layers up to 1 m.These results illustrate the limitations of terrestrial ecosystem models to represent environmental and ecological dynamics in wetlands.Attempts to adjust model hydrology have yielded marginal improvements in thaw depth prediction, but revealed large effects of abrupt phase changes for poorly drained sites on discontinuous permafrost.Our analysis suggests the importance of gradual phase change representation, particularly in icerich wetlands with thick organic layers, which will be crucial when evaluating the permafrost carbon-climate feedback in model projections.1

Permafrost degradation in peatlands is altering vegetation and soil properties and impacting net carbon storage. We studied four adjacent sites in Alaska with varied permafrost regimes, including a black spruce forest on a peat plateau with permafrost, two collapse scar bogs of different ages formed following thermokarst, and a rich fen without permafrost. Measurements included year-round eddy covariance estimates of net carbon dioxide (CO2 ), mid-April to October methane (CH4 ) emissions, and environmental variables. From 2011 to 2022, annual rainfall was above the historical average, snow water equivalent increased, and snow-season duration shortened due to later snow return. Seasonally thawed active layer depths also increased. During this period, all ecosystems acted as slight annual sources of CO2 (13-59 g C m-2  year-1 ) and stronger sources of CH4 (11-14 g CH4  m-2 from ~April to October). The interannual variability of net ecosystem exchange was high, approximately ±100 g C m-2  year-1 , or twice what has been previously reported across other boreal sites. Net CO2 release was positively related to increased summer rainfall and winter snow water equivalent and later snow return. Controls over CH4 emissions were related to increased soil moisture and inundation status. The dominant emitter of carbon was the rich fen, which, in addition to being a source of CO2 , was also the largest CH4 emitter. These results suggest that the future carbon-source strength of boreal lowlands in Interior Alaska may be determined by the area occupied by minerotrophic fens, which are expected to become more abundant as permafrost thaw increases hydrologic connectivity. Since our measurements occur within close proximity of each other (≤1 km2 ), this study also has implications for the spatial scale and data used in benchmarking carbon cycle models and emphasizes the necessity of long-term measurements to identify carbon cycle process changes in a warming climate.

Mapping in-situ eddy covariance measurements of terrestrial land-atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented up-scaling framework, FLUXCOM-X. The X-BASE products comprise of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP) as well as evapotranspiration (ET) and, for the first time, a novel fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at -5.75 ± 0.33 Pg C ⋅ yr-1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site-years resulting in a wider coverage of bio-climatic conditions. However, X-BASE global net ecosystem exchange shows a very low inter-annual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C ⋅ yr-1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7x10³ ± 0.9x10³ km3 globally for the years 2001–2020, but exceeds precipitation in many dry areas likely indicating overestimation in these regions. On average 57 % of evapotranspiration are estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous up-scaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy-covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.