Northern peatlands have accumulated large stocks of organic carbon (C) and nitrogen (N), but their spatial distribution and vulnerability to climate warming remain uncertain. Here, we used machine-learning techniques with extensive peat core data (n > 7,000) to create observation-based maps of northern peatland C and N stocks, and to assess their response to warming and permafrost thaw. We estimate that northern peatlands cover 3.7 ± 0.5 million km² and store 415 ± 150 Pg C and 10 ± 7 Pg N. Nearly half of the peatland area and peat C stocks are permafrost affected. Using modeled global warming stabilization scenarios (from 1.5 to 6 °C warming), we project that the current sink of atmospheric C (0.10 ± 0.02 Pg C⋅y⁻¹) in northern peatlands will shift to a C source as 0.8 to 1.9 million km² of permafrost-affected peatlands thaw. The projected thaw would cause peatland greenhouse gas emissions equal to ∼1% of anthropogenic radiative forcing in this century. The main forcing is from methane emissions (0.7 to 3 Pg cumulative CH₄-C) with smaller carbon dioxide forcing (1 to 2 Pg CO₂-C) and minor nitrous oxide losses. We project that initial CO₂-C losses reverse after ∼200 y, as warming strengthens peatland C-sinks. We project substantial, but highly uncertain, additional losses of peat into fluvial systems of 10 to 30 Pg C and 0.4 to 0.9 Pg N. The combined gaseous and fluvial peatland C loss estimated here adds 30 to 50% onto previous estimates of permafrost-thaw C losses, with southern permafrost regions being the most vulnerable. Significance Over many millennia, northern peatlands have accumulated large amounts of carbon and nitrogen, thus cooling the global climate. Over shorter timescales, peatland disturbances can trigger losses of peat and release of greenhouses gases. Despite their importance to the global climate, peatlands remain poorly mapped, and the vulnerability of permafrost peatlands to warming is uncertain. This study compiles over 7,000 field observations to present a data-driven map of northern peatlands and their carbon and nitrogen stocks. We use these maps to model the impact of permafrost thaw on peatlands and find that warming will likely shift the greenhouse gas balance of northern peatlands. At present, peatlands cool the climate, but anthropogenic warming can shift them into a net source of warming.

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that 1014−175+194 Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

Soil organic carbon (SOC) stored in northern peatlands and permafrost-affected soils are key components in the global carbon cycle. This article quantifies SOC stocks in a sub-Arctic mountainous peatland environment in the discontinuous permafrost zone in Abisko, northern Sweden. Four machine-learning techniques are evaluated for SOC quantification: multiple linear regression, artificial neural networks, support vector machine and random forest. The random forest model performed best and was used to predict SOC for several depth increments at a spatial resolution of 1 m (1×1 m). A high-resolution (1 m) land cover classification generated for this study is the most relevant predictive variable. The landscape mean SOC storage (0–150 cm) is estimated to be 8.3 ± 8.0 kg C m⁻² and the SOC stored in the top meter (0–100 cm) to be 7.7 ± 6.2 kg C m⁻². The predictive modeling highlights the relative importance of wetland areas and in particular peat plateaus for the landscape's SOC storage. The total SOC was also predicted at reduced spatial resolutions of 2, 10, 30, 100, 250 and 1000 m and shows a significant drop in land cover class detail and a tendency to underestimate the SOC at resolutions > 30 m. This is associated with the occurrence of many small-scale wetlands forming local hot-spots of SOC storage that are omitted at coarse resolutions. Sharp transitions in SOC storage associated with land cover and permafrost distribution are the most challenging methodological aspect. However, in this study, at local, regional and circum-Arctic scales, the main factor limiting robust SOC mapping efforts is the scarcity of soil pedon data from across the entire environmental space. For the Abisko region, past SOC and permafrost dynamics indicate that most of the SOC is barely 2000 years old and very dynamic. Future research needs to investigate the geomorphic response of permafrost degradation and the fate of SOC across all landscape compartments in post-permafrost landscapes.

Permafrost‐affected ecosystems are important components in the global carbon (C) cycle that, despite being vulnerable to disturbances under climate change, remain poorly understood. This study investigates ecosystem carbon storage in two contrasting continuous permafrost areas of NE and East Siberia. Detailed partitioning of soil organic carbon (SOC) and phytomass carbon (PC) is analyzed for one tundra (Kytalyk) and one taiga (Spasskaya Pad/Neleger) study area. In total, 57 individual field sites (24 and 33 in the respective areas) have been sampled for PC and SOC, including the upper permafrost. Landscape partitioning of ecosystem C storage was derived from thematic upscaling of field observations using a land cover classification from very high resolution (2 × 2 m) satellite imagery. Nonmetric multidimensional scaling was used to explore patterns in C distribution. In both environments the ecosystem C is mostly stored in the soil (≥86%). At the landscape scale C stocks are primarily controlled by the presence of thermokarst depressions (alases). In the tundra landscape, site‐scale variability of C is controlled by periglacial geomorphological features, while in the taiga, local differences in catenary position, soil texture, and forest successions are more important. Very high resolution remote sensing is highly beneficial to the quantification of C storage. Detailed knowledge of ecosystem C storage and ground ice distribution is needed to predict permafrost landscape vulnerability to projected climatic changes. We argue that vegetation dynamics are unlikely to offset mineralization of thawed permafrost C and that landscape‐scale reworking of SOC represents the largest potential changes to C cycling.

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 10⁴ m², have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 10⁶ km² across the Arctic, about 17 % of the Arctic lowland ( < 300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 10⁶ m² down to 1. 0 × 10² m² contributed up to 21 % to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 10¹ km⁻². Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349.

Spatial analysis in earth sciences is often based on the concept of spatial autocorrelation, expressed by W. Tobler as the first law of geography: “everything is related to everything else, but near things are more related than distant things." Here, we show that subsurface soil properties in permafrost tundra terrain exhibit tremendous spatial variability. We describe the subsurface variability of soil organic carbon (SOC) and ground ice content from the centimeter to the landscape scale in three typical tundra terrain types common across the Arctic region. At the soil pedon scale, that is, from centimeters to 1–2 m, variability is caused by cryoturbation and affected by tussocks, hummocks and nonsorted circles. At the terrain scale, from meters to tens of meters, variability is caused by different generations of ice‐wedges. Variability at the landscape scale, that is, ranging hundreds of meters, is associated with geomorphic disturbances and catenary shifts. The co‐occurrence and overlap of different processes and landforms creates a spatial structure unique to permafrost environments. The coefficient of variation of SOC at the pedon scale (21%–73%) exceeds that found at terrain (17%–66%) and even landscape scale (24%–67%). Such high values for spatial variation are otherwise found at regional to continental scale. Clearly, permafrost soils do not conform to Tobler's law, but are among the most variable soils on Earth. This needs to be accounted for in mapping and predictions of the permafrost carbon feedbacks through various ecosystem processes. We conclude that scale deserves special attention in permafrost regions.