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.

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.

Tundra soils account for 50% of global stocks of soil organic carbon (SOC), and it is expected that the amplified climate warming in high latitude could cause loss of this SOC through decomposition. Decomposed SOC could become hydrologically accessible, which increase downstream dissolved organic carbon (DOC) export and subsequent carbon release to the atmosphere, constituting a positive feedback to climate warming. However, DOC export is often neglected in ecosystem models. In this paper, we incorporate processes related to DOC production, mineralization, diffusion, sorption-desorption, and leaching into a customized arctic version of the dynamic ecosystem model LPJ-GUESS in order to mechanistically model catchment DOC export, and to link this flux to other ecosystem processes. The extended LPJ-GUESS is compared to observed DOC export at Stordalen catchment in northern Sweden. Vegetation communities include flood-tolerant graminoids (Eriophorum) and Sphagnum moss, birch forest and dwarf shrub communities. The processes, sorption-desorption and microbial decomposition (DOC production and mineralization) are found to contribute most to the variance in DOC export based on a detailed variance-based Sobol sensitivity analysis (SA) at grid cell-level. Catchment-level SA shows that the highest mean DOC exports come from the Eriophorum peatland (fen). A comparison with observations shows that the model captures the seasonality of DOC fluxes. Two catchment simulations, one without water lateral routing and one without peatland processes, were compared with the catchment simulations with all processes. The comparison showed that the current implementation of catchment lateral flow and peatland processes in LPJ-GUESS are essential to capture catchment-level DOC dynamics and indicate the model is at an appropriate level of complexity to represent the main mechanism of DOC dynamics in soils. The extended model provides a new tool to investigate potential interactions among climate change, vegetation dynamics, soil hydrology and DOC dynamics at both stand-alone to catchment scales.

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 x 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.

Decomposition of soil organic matter (SOM) in permafrost terrain and the production of greenhouse gases is a key factor for understanding climate change-carbon feedbacks. Previous studies have shown that SOM decomposition is mostly controlled by soil temperature, soil moisture, and carbon-nitrogen ratio (C:N). However, focus has generally been on site-specific processes and little is known about variations in the controls on SOM decomposition across Arctic sites. For assessing SOM decomposition, we retrieved 241 samples from 101 soil profiles across three contrasting Arctic regions and incubated them in the laboratory under aerobic conditions. We assessed soil carbon losses (C-loss) five times during a 1year incubation. The incubated material consisted of near-surface active layer (AL(NS)), subsurface active layer (AL(SS)), peat, and permafrost samples. Samples were analyzed for carbon, nitrogen, water content, C-13, N-15, and dry bulk density (DBD). While no significant differences were observed between total AL(SS) and permafrost C-loss over 1year incubation (2.32.4% and 2.51.5% C-loss, respectively), AL(NS) samples showed higher C-loss (7.94.2%). DBD was the best explanatory parameter for active layer C-loss across sites. Additionally, results of permafrost samples show that C:N ratio can be used to characterize initial C-loss between sites. This data set on the influence of abiotic parameter on microbial SOM decomposition can improve model simulations of Arctic soil CO2 production by providing representative mean values of CO2 production rates and identifying standard parameters or proxies for upscaling potential CO2 production from site to regional scales.

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 x 10(4) m(2), 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 5m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6m 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 x 10(6) km(2) across the Arctic, about 17% of the Arctic lowland (<300ma. s.l.) land surface area. PeRL waterbodies with sizes of 1.0 x 10(6) m(2) down to 1.0 x 10(2) m(2) contributed up to 21% to the total water fraction. Waterbody density ranged from 1.0 x 10 to 9.4 x 10(1) 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.

A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25% less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 x 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with similar to 120m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

Large amounts of carbon are stored in soils of the northern circumpolar permafrost region. High-resolution mapping of this soil organic carbon (SOC) is important to better understand and predict local to global scale carbon dynamics. In this thesis, studies from five different areas across the permafrost region indicate a pattern of generally higher SOC storage in Arctic tundra soils compared to forested sub-Arctic or Boreal taiga soils. However, much of the SOC stored in the top meter of tundra soils is permanently frozen, while the annually thawing active layer is deeper in taiga soils and more SOC may be available for turnover to ecosystem processes. The results show that significantly more carbon is stored in soils compared to vegetation, even in fully forested taiga ecosystems. This indicates that over longer timescales, the SOC potentially released from thawing permafrost cannot be offset by a greening of the Arctic. For all study areas, the SOC distribution is strongly influenced by the geomorphology, i.e. periglacial landforms and processes, at different spatial scales. These span from the cryoturbation of soil horizons, to the formation of palsas, peat plateaus and different generations of ice-wedges, to thermokarst creating kilometer scale macro environments. In study areas that have not been affected by Pleistocene glaciation, SOC distribution is highly influenced by the occurrence of ice-rich and relief-forming Yedoma deposits. This thesis investigates the use of thematic maps from highly resolved satellite imagery (<6.5 m resolution). These maps reveal important information on the local distribution and variability of SOC, but their creation requires advanced classification methods including an object-based approach, modern classifiers and data-fusion. The results of statistical analyses show a clear link of land cover and geomorphology with SOC storage. Peat-formation and cryoturbation are identified as two major mechanisms to accumulate SOC. As an alternative to thematic maps, this thesis demonstrates the advantages of digital soil mapping of SOC in permafrost areas using machine-learning methods, such as support vector machines, artificial neural networks and random forests. Overall, high-resolution satellite imagery and robust spatial prediction methods allow detailed maps of SOC. This thesis significantly increases the amount of soil pedons available for the individual study areas. Yet, this information is still the limiting factor to better understand the SOC distribution in permafrost environments at local and circumpolar scale. Soil pedon information for SOC quantification should at least distinguish the surface organic layer, the mineral subsoil in the active layer compared to the permafrost and further into organic rich cryoturbated and buried soil horizons.

To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58 ± 10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2 ± 2.0 kg C m− 2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.

This study relates soil organic matter (SOM) characteristics to initial soil incubation carbon release from upper permafrost samples in Yedoma region soils of northeastern Siberia, Russia. Carbon (C) and nitrogen (N) content, carbon to nitrogen ratios (C:N), delta C-13 and delta N-15 values show clear trends that correspond with SOM age and degree of decomposition. Incubation results indicate that older and more decomposed soil material shows higher C respiration rates per unit incubated C than younger and less decomposed samples with higher C content. This is important as undecomposed material is often assumed to be more reactive upon thawing. Large stocks of SOM and their potential decomposability, in combination with complex landscape dynamics that include one or more events of Holocene thaw in most of the landscape, are of consequence for potential greenhouse gas release from permafrost soils in the Yedoma region.