Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km²resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km²pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

The regional variability in tundra and boreal carbon dioxide (CO₂) fluxes can be high, complicating efforts to quantify sink‐source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO₂ fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO₂ fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high‐latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO₂ fluxes and test the accuracy and uncertainty of different statistical models. CO₂ fluxes were upscaled at relatively high spatial resolution (1 km²) across the high‐latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE‐focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO₂ sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m⁻² yr⁻¹, respectively) compared to tundra (average annual NEE +10 and −2 g C m⁻² yr⁻¹). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO₂ budget, estimated using the annual NEE ensemble prediction, suggests the high‐latitude region was on average an annual CO₂ sink during 1990–2015, although uncertainty remains high.

Organic soils are a main source of direct emissions of nitrous oxide (N₂O), an important greenhouse gas (GHG). Observed N₂O emissions from organic soils are highly variable in space and time, which causes high uncertainties in national emission inventories. Those uncertainties could be reduced when relating the upscaling process to a priori-identified key drivers by using available N₂O observations from plot scale in empirical approaches. We used the empirical fuzzy modelling approach MODE to identify main drivers for N₂O and utilize them to predict the spatial emission pattern of European organic soils. We conducted a meta-study with a total amount of 659 annual N₂O measurements, which was used to derive separate models for different land use types. We applied our models to available, spatially explicit input driver maps to upscale N₂O emissions at European level and compared the inventory with recently published IPCC emission factors. The final statistical models explained up to 60% of the N₂O variance. Our study results showed that cropland and grasslands emitted the highest N₂O fluxes 0.98 ± 1.08 and 0.58 ± 1.03 g N₂O-N m⁻² a⁻¹, respectively. High fluxes from cropland sites were mainly controlled by low soil pH value and deep-drained groundwater tables. Grassland hotspot emissions were strongly related to high amount of N-fertilizer inputs and warmer winter temperatures. In contrast, N₂O fluxes from natural peatlands were predominantly low (0.07 ± 0.27 g N₂O-N m⁻² a⁻¹) and we found no relationship with the tested drivers. The total inventory for direct N₂O emissions from organic soils in Europe amount up to 149.5 Gg N₂O-N a⁻¹, which also included fluxes from forest and peat extraction sites and exceeds the inventory calculated by IPCC emission factors of 87.4 Gg N₂O-N a⁻¹. N₂O emissions from organic soils represent up to 13% of total European N₂O emissions reported in the European Union (EU) greenhouse gas inventory of 2011 from only 7% of the EU area. Thereby the model demonstrated that the major part (85%) of the inventory is induced by anthropogenic management, which shows the significant reduction potential by rewetting and extensification of agriculturally used peat soils.

Peatland restoration may provide a potential after-use option to mitigate the negative climate impact of abandoned peat extraction areas; currently, however, knowledge about restoration effects on the annual balances of carbon (C) and greenhouse gas (GHG) exchanges is still limited. The aim of this study was to investigate the impact of contrasting mean water table levels (WTLs) on the annual C and GHG balances of restoration treatments with high (Res_H) and low (Res_L) WTL relative to an unrestored bare peat (BP) site. Measurements of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) fluxes were conducted over a full year using the closed chamber method and complemented by measurements of abiotic controls and vegetation cover. Three years following restoration, the difference in the mean WTL resulted in higher bryophyte and lower vascular plant cover in Res_H relative to Res_L. Consequently, greater gross primary production and autotrophic respiration associated with greater vascular plant cover were observed in Res_L compared to Res_H. However, the means of the measured net ecosystem CO₂ exchanges (NEE) were not significantly different between Res_H and Res_L. Similarly, no significant differences were observed in the respective means of CH₄ and N₂O exchanges. In comparison to the two restored sites, greater net CO₂, similar CH₄ and greater N₂O emissions occurred in BP. On the annual scale, Res_H, Res_L and BP were C sources of 111, 103 and 268 g C m⁻² yr⁻¹ and had positive GHG balances of 4.1, 3.8 and 10.2 t CO₂ eq ha⁻¹ yr⁻¹, respectively. Thus, the different WTLs had a limited impact on the C and GHG balances in the two restored treatments 3 years following restoration. However, the C and GHG balances in Res_H and Res_L were considerably lower than in BP due to the large reduction in CO₂ emissions. This study therefore suggests that restoration may serve as an effective method to mitigate the negative climate impacts of abandoned peat extraction areas.

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).