Litter decomposition represents a major path for atmospheric carbon influx into Arctic soils, thereby controlling below-ground carbon accumulation. Yet, little is known about how tundra litter decomposition varies with microenvironmental conditions, hindering accurate projections of tundra soil carbon dynamics with future climate change. Over 14 months, we measured landscape-scale decomposition of two contrasting standard litter types (Green tea and Rooibos tea) in 90 plots covering gradients of micro-climate and -topography, vegetation cover and traits, and soil characteristics in Western Greenland. We used the tea bag index (TBI) protocol to estimate relative variation in litter mass loss, decomposition rate (k) and stabilisation factor (S) across space, and structural equation modelling (SEM) to identify relationships among environmental factors and decomposition. Contrasting our expectations, microenvironmental factors explained little of the observed variation in both litter mass loss, as well as k and S, suggesting that the variables included in our study were not the major controls of decomposer activity in the soil across the studied tundra landscape. We use these unexpected findings of our study combined with findings from the current literature to discuss future avenues for improving our understanding of the drivers of tundra decomposition and, ultimately, carbon cycling across the warming Arctic.

Climate change has had a significant impact on the seasonal transition dates of Arctic tundra ecosystems, causing diverse variations between distinct land surface classes. However, the combined effect of multiple controls as well as their individual effects on these dates remains unclear at various scales and across diverse land surface classes. Here we quantified spatiotemporal variations of three seasonal transition dates (start of spring, maximum normalized difference vegetation index (NDVImax) day, end of fall) for five dominating land surface classes in the ice-free Greenland. Using a distributed snow model, structural equation modeling, and a random forest model, based on ground observations and remote sensing data, we assessed the indirect and direct effects of climate, snow, and terrain on seasonal transition dates. We then presented new projections of likely changes in seasonal transition dates under six future climate scenarios. The coupled climate, snow cover, and terrain conditions explained up to 61% of seasonal transition dates across different land surface classes. Snow ending day played a crucial role in the start of spring and timing of NDVImax. A warmer June and a decline in wind could advance the NDVImax day. Increased precipitation and temperature during July-August are the most important for delaying the end of fall. We projected that a 1-4.5 degrees C increase in temperature and a 5%-20% increase in precipitation would lengthen the spring-to-fall period for all five land surface classes by 2050, thus the current order of spring-to-fall lengths for the five land surface classes could undergo notable changes. Tall shrubs and fens would have a longer spring-to-fall period under the warmest and wettest scenario, suggesting a competitive advantage for these vegetation communities. This study's results illustrate controls on seasonal transition dates and portend potential changes in vegetation composition in the Arctic under climate change. Employing the distributed snow modeling, structural equation modeling, and random forest model, we assessed the effect of climatic, snow, and terrain conditions on the seasonal transition dates of Arctic tundra ecosystems and projected their changes by 2050 in ice-free Greenland, between diverse land surface classes. We found that the start of spring and the end of fall respond differently to various environmental conditions. Future temperature and precipitation changes could significantly affect the spring-to-fall period for different land surface classes, with potential implications for Arctic vegetation composition, providing valuable insights into the controls on seasonal transition dates under climate change.image

Permafrost in the NE European Russian Arctic is suffering from some of the highest degradation rates in the world. The rising mean annual air temperature causes warming permafrost, the increase in the active layer thickness (ALT), and the reduction of the permafrost extent. These phenomena represent a serious risk for infrastructures and human activities. ALT characterization is important to estimate the degree of permafrost degradation. We used a multidisciplinary approach to investigate the ALT distribution in the Khanovey railway station area (close to Vorkuta, Arctic Russia), where thaw subsidence leads to railroad vertical deformations up to 2.5 cm/year. Geocryological surveys, including vegetation analysis and underground temperature measurements, together with the faster and less invasive electrical resistivity tomography (ERT) geophysical method, were used to investigate the frozen/unfrozen ground settings between the railroad and the Vorkuta River. Borehole stratigraphy and landscape microzonation indicated a massive prevalence of clay and silty clay sediments at shallow depths in this area. The complex refractive index method (CRIM) was used to integrate and quantitatively validate the results. The data analysis showed landscape heterogeneity and maximum ALT and permafrost thickness values of about 7 and 50 m, respectively. The active layer was characterized by resistivity values ranging from about 30 to 100 omega m, whereas the underlying permafrost resistivity exceeded 200 omega m, up to a maximum of about 10 k omega m. In the active layer, there was a coexistence of frozen and unfrozen unconsolidated sediments, where the ice content estimated using the CRIM ranged from about 0.3 - 0.4 to 0.9. Moreover, the transition zone between the active layer base and the permafrost table, whose resistivity values ranged from 100 to 200 omega m for this kind of sediments, showed ice contents ranging from 0.9 to 1.0. Taliks were present in some depressions of the study area, characterized by minimum resistivity values lower than 10 omega m. This thermokarst activity was more active close to the railroad because of the absence of insulating vegetation. This study contributes to better understanding of the spatial variability of cryological conditions, and the result is helpful in addressing engineering solutions for the stability of the railway.

Rapid climate warming has widely been considered as the main driver of recent increases in Arctic tundra productivity. Field observations and remote sensing both show that tundra greening has been widespread, but heterogeneity in regional and landscape-scale trends suggest that additional controls are mediating the response of tundra vegetation to warming. In this study, we examined the relationship between changes in vegetation productivity in the western Canadian Arctic and biophysical variables by analyzing trends in the Enhanced Vegetation Index (EVI) obtained from nonparametric regression of annual Landsat surface reflectance composites. We used Random Forests classification and regression tree modelling to predict the trajectory and magnitude of greening from 1984 to 2016 and identify biophysical controls. More than two-thirds of our study area showed statistically significant increases in vegetation productivity, but observed changes were heterogeneous, occurring most rapidly within areas of the Southern Arctic that were: (1) dominated by dwarf and upright shrub cover types, (2) moderately sloping, and (3) located at lower elevation. These findings suggest that the response of tundra vegetation to warming is mediated by regional- and landscape-scale variation in microclimate, topography and soil moisture, and physiological differences among plant functional groups. Our work highlights the potential of the joint analysis of annual remotely sensed vegetation indices and broad-scale biophysical data to understand spatial variation in tundra vegetation change.

Warming temperatures in continuous permafrost zones of the Arctic will alter both hydrological and geochemical soil conditions, which are strongly linked with heterotrophic microbial carbon (C) cycling. Heterogeneous permafrost landscapes are often dominated by polygonal features formed by expanding ice wedges: water accumulates in low centered polygons (LCPs), and water drains outward to surrounding troughs in high centered polygons (HCPs). These geospatial differences in hydrology cause gradients in biogeochemistry, soil C storage potential, and thermal properties. Presently, data quantifying carbon dioxide (CO2) and methane (CH4) release from HCP soils are needed to support modeling and evaluation of warming-induced CO2 and CH4 fluxes from tundra soils. This study quantifies the distribution of microbial CO2 and CH4 release in HCPs over a range of temperatures and draws comparisons to previous LCP studies. Arctic tundra soils were initially characterized for geochemical and hydraulic properties. Laboratory incubations at -2, +4, and +8 degrees C were used to quantify temporal trends in CO2 and CH4 production from homogenized active layer organic and mineral soils in HCP centers and troughs, and methanogen abundance was estimated from mcrA gene measurements. Results showed that soil water availability, organic C, and redox conditions influence temporal dynamics and magnitude of gas production from HCP active layer soils during warming. At early incubation times (2-9 days), higher CO2 emissions were observed from HCP trough soils than from HCP center soils, but increased CO2 production occurred in center soils at later times (>20 days). HCP center soils did not support methanogenesis, but CH4-producing trough soils did indicate methanogen presence. Consistent with previous LCP studies, HCP organic soils showed increased CO2 and CH4 production with elevated water content, but HCP trough mineral soils produced more CH4 than LCP mineral soils. HCP mineral soils also released substantial CO2 but did not show a strong trend in CO2 and CH4 release with water content. Knowledge of temporal and spatial variability in microbial C mineralization rates of Arctic soils in response to warming are key to constraining uncertainties in predictive climate models.

Warming in the Arctic accelerates top-soil decomposition and deep-soil permafrost thaw. This may lead to an increase in plant-available nutrients throughout the active layer soil and near the permafrost thaw front. For nitrogen (N) limited high arctic plants, increased N availability may enhance growth and alter community composition, importantly affecting the ecosystem carbon balance. However, the extent to which plants can take advantage of this newly available N may be constrained by the following three factors: vertical distribution of N within the soil profile, timing of N-release, and competition with other plants and microorganisms. Therefore, we investigated species- and depth-specific plant N uptake in a high arctic tundra, northeastern Greenland. Using stable isotopic labelling (N-15-NH4+), we simulated autumn N-release at three depths within the active layer: top (10 cm), mid (45 cm) and deep-soil near the permafrost thaw front (90 cm). We measured plant species-specific N uptake immediately after N-release (autumn) and after 1 year, and assessed depth-specific microbial N uptake and resource partitioning between above- and below-ground plant parts, microorganisms and soil. We found that high arctic plants actively foraged for N past the peak growing season, notably the graminoidKobresia myosuroides. While most plant species (Carex rupestris,Dryas octopetala,K. myosuroides) preferred top-soil N, the shrubSalix arcticaalso effectively acquired N from deeper soil layers. All plants were able to obtain N from the permafrost thaw front, both in autumn and during the following growing season, demonstrating the importance of permafrost-released N as a new N source for arctic plants. Finally, microbial N uptake markedly declined with depth, hence, plant access to deep-soil N pools is a competitive strength. In conclusion, plant species-specific competitive advantages with respect to both time- and depth-specific N-release may dictate short- and long-term plant community changes in the Arctic and consequently, larger-scale climate feedbacks.

Cold seasons in Arctic ecosystems are increasingly important to the annual carbon balance of these vulnerable ecosystems. Arctic winters are largely harsh and inaccessible leading historic data gaps during that time. Until recently, cold seasons have been assumed to have negligible impacts on the annual carbon balance but as data coverage increases and the Arctic warms, the cold season has been shown to account for over half of annual methane (CH4) emissions and can offset summer photosynthetic carbon dioxide (CO2) uptake. Freeze-thaw cycle dynamics play a critical role in controlling cold season CO(2)and CH(4)loss, but the relationship has not been extensively studied. Here, we analyze freeze-thaw processes through in situ CO(2)and CH(4)fluxes in conjunction with soil cores for physical structure and porewater samples for redox biogeochemistry. We find a movement of water toward freezing fronts in soil cores, leaving air spaces in soils, which allows for rapid infiltration of oxygen-rich snow melt in spring as shown by oxidized iron in porewater. The snow melt period coincides with rising ecosystem respiration and can offset up to 41% of the summer CO(2)uptake. Our study highlights this important seasonal process and shows spring greenhouse gas emissions are largely due to production from respiration instead of only bursts of stored gases. Further warming is projected to result in increases of snowpack and deeper thaws, which could increase this ecosystem respiration dominate snow melt period causing larger greenhouse gas losses during spring.

Soil microbial communities in the Arctic play a critical role in regulating the global carbon (C) cycle. Vast amounts of C are stored in northern high latitude soils, and rising temperatures in the Arctic threaten to thaw permafrost, making relatively inaccessible C sources more available for mineralization by soil microbes. Few studies have characterized how microbial community structure responds to thawing permafrost in the context of varying soil chemistries associated with contrasting tundra landscapes. We subjected active layer and permafrost soils from upland and lowland tundra sites on the North Slope of Alaska to a soil-warming incubation experiment and compared soil bacterial community profiles (obtained by 16S rRNA amplicon sequencing) before and after incubation. The influence of soil composition (characterized by mid-infrared [MIR] spectroscopy) on bacterial community structure and class abundance was analyzed using redundancy and correlation analyses. We found increased abundances of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes [Sphingobacteriia] post incubation, particularly in permafrost soils. The categorical descriptors site and soil layer had the most explanatory power in our predictive models of bacterial community structure, highlighting the close relationship between soil bacteria and the soil environment. Specific soil chemical attributes characterizing the soil environments that were found to be the best predictors included MIR spectral bands associated with inorganic C, silicates, amide II (C=N stretch), and carboxylics (C-O stretch), and MIR peak ratios representing C substrate quality. Overall, these results further characterize soil bacterial community shifts that may occur as frozen environments with limited access to C sources, as is found in undisturbed permafrost, transition to warmer and more C-available environments, as is predicted in thawing permafrost due to climate change.

Vegetation change has consequences for terrestrial ecosystem structure and functioning and may involve climate feedbacks. Hence, when monitoring ecosystem states and changes thereof, the vegetation is often a primary monitoring target. Here, we summarize current understanding of vegetation change in the High Arctic-the World's most rapidly warming region-in the context of ecosystem monitoring. To foster development of deployable monitoring strategies, we categorize different kinds of drivers (disturbances or stresses) of vegetation change either as pulse (i.e. drivers that occur as sudden and short events, though their effects may be long lasting) or press (i.e. drivers where change in conditions remains in place for a prolonged period, or slowly increases in pressure). To account for the great heterogeneity in vegetation responses to climate change and other drivers, we stress the need for increased use of ecosystem-specific conceptual models to guide monitoring and ecological studies in the Arctic. We discuss a conceptual model with three hypothesized alternative vegetation states characterized by mosses, herbaceous plants, and bare ground patches, respectively. We use moss-graminoid tundra of Svalbard as a case study to discuss the documented and potential impacts of different drivers on the possible transitions between those states. Our current understanding points to likely additive effects of herbivores and a warming climate, driving this ecosystem from a moss-dominated state with cool soils, shallow active layer and slow nutrient cycling to an ecosystem with warmer soil, deeper permafrost thaw, and faster nutrient cycling. Herbaceous-dominated vegetation and (patchy) bare ground would present two states in response to those drivers. Conceptual models are an operational tool to focus monitoring efforts towards management needs and identify the most pressing scientific questions. We promote greater use of conceptual models in conjunction with a state-and-transition framework in monitoring to ensure fit for purpose approaches. Defined expectations of the focal systems' responses to different drivers also facilitate linking local and regional monitoring efforts to international initiatives, such as the Circumpolar Biodiversity Monitoring Program.

Aims For informed predictions on the sensitivity of Arctic tundra landscape to permafrost thaw, we aimed to investigate the distribution pattern of near-surface ground ice and its influencing factors in Northeast Siberia. Methods Near-surface permafrost cores (60 cm) were sampled along small-scale topographic gradients in two drained lakebeds. We investigated which factors (vegetation, hydrological and soil) correlated strongest with ice content and explored its spatial heterogeneity at different scales (1 to 100 m). Results The ice content was highest in the depressions of the wet lakebed and lowest at the slopes of the dry lakebed. In the wet lakebed the ice content increased with depth, while in the dry lakebed the vertical distribution depended on topographical position. Spatial variability in ice content was similar at different scales, stressing strong influence of local drivers. 0-60 cm ice content correlated strongest with soil moisture of the overlying unfrozen soil, while 0-20 cm ice content correlated strongest with vegetation characteristics. Conclusions Our study implies that vegetation effect on microclimate is strong enough to affect near-surface ice distribution, and that ice-rich tundra may be highly sensitive to thaw once climate warming offsets the protective impact of vegetation.