Polygonal tundra geomorphological change in response to warming alters future CO2 and CH4 flux on the Barrow Peninsula

Organic matter sources and flows in tundra wetland food webs

Arctic lowland tundra is often dominated by wetlands. As numbers and types of these wetlands change with climate warming, their invertebrate biomass and assemblages may also be affected. Increased influx of nutrients and dissolved organic matter (DOM) from thawing peat may alter the relative availability of organic matter (OM) sources, differentially affecting taxa with disparate dependence on those sources. In five shallow wetland types (<40 to 110 cm deep) and in littoral zones of deeper lakes (>150 cm), we used stable isotopes (δ13C, δ15N) to compare contributions of four OM sources (periphytic microalgae, cyanobacteria, macrophytes, peat) to the diets of nine macroinvertebrate taxa. Living macrophytes were not distinguishable isotopically from peat that likely contributed most DOM. Within invertebrate taxa, relative OM contributions were similar among all wetland types except deeper lakes. Physidae snails consumed substantial amounts of OM from cyanobacteria. However, for all other taxa examined, microalgae were the dominant or a major OM source (39-82%, mean 59%) in all wetland types except deeper lakes (20‒62%, mean 31%). Macrophytes and macrophyte-derived peat, likely consumed mostly indirectly as DOM-supported bacteria, ranged from 18‒61% (mean 41%) of ultimate OM sources in all wetland types except deeper lakes (38-80%, mean 69%). Invertebrate consumption of microalgal C may often have involved bacterial intermediates, or a mix of algae with bacteria consuming peat-derived OM. High production of periphyton with very low δ13C values were favored by continuous daylight illuminating shallow depths, high N and P levels, and high CO2 concentrations from bacterial respiration of peat-derived DOM. Although relative OM sources were similar across wetland types except deeper lakes, total invertebrate biomass was much higher in shallow wetlands with emergent vegetation. Impacts of warming on the availability of invertebrate prey to waterbirds will likely depend not on shifts in OM sources, but more on changes in overall number or area of shallow emergent wetlands.

Lowering water table reduces carbon sink strength and carbon stocks in northern peatlands

Peatlands at high latitudes have accumulated >400 Pg carbon (C) because saturated soil and cold temperatures suppress C decomposition. This substantial amount of C in Arctic and Boreal peatlands is potentially subject to increased decomposition if the water table (WT) decreases due to climate change, including permafrost thaw-related drying. Here, we optimize a version of the Organizing Carbon and Hydrology In Dynamic Ecosystems model (ORCHIDEE-PCH4) using site-specific observations to investigate changes in CO₂ and CH₄ fluxes as well as C stock responses to an experimentally manipulated decrease of WT at six northern peatlands. The unmanipulated control peatlands, with the WT <20 cm on average (seasonal max up to 45 cm) below the surface, currently act as C sinks in most years (58 ± 34 g C m^-2  year^-1 ; including 6 ± 7 g C-CH₄ m^-2  year^-1 emission). We found, however, that lowering the WT by 10 cm reduced the CO₂ sink by 13 ± 15 g C m^-2  year^-1 and decreased CH₄ emission by 4 ± 4 g CH₄ m^-2  year^-1 , thus accumulating less C over 100 years (0.2 ± 0.2 kg C m^-2 ). Yet, the reduced emission of CH₄ , which has a larger greenhouse warming potential, resulted in a net decrease in greenhouse gas balance by 310 ± 360 g CO_2-eq  m^-2  year^-1 . Peatlands with the initial WT close to the soil surface were more vulnerable to C loss: Non-permafrost peatlands lost >2 kg C m^-2 over 100 years when WT is lowered by 50 cm, while permafrost peatlands temporally switched from C sinks to sources. These results highlight that reductions in C storage capacity in response to drying of northern peatlands are offset in part by reduced CH₄ emissions, thus slightly reducing the positive carbon climate feedbacks of peatlands under a warmer and drier future climate scenario.

Increased Arctic NO3− Availability as a Hydrogeomorphic Consequence of Permafrost Degradation and Landscape Drying

Climate-driven permafrost thaw alters the strongly coupled carbon and nitrogen cycles within the Arctic tundra, influencing the availability of limiting nutrients including nitrate (NO3−). Researchers have identified two primary mechanisms that increase nitrogen and NO3− availability within permafrost soils: (1) the ‘frozen feast’, where previously frozen organic material becomes available as it thaws, and (2) ‘shrubification’, where expansion of nitrogen-fixing shrubs promotes increased soil nitrogen. Through the synthesis of original and previously published observational data, and the application of multiple geospatial approaches, this study investigates and highlights a third mechanism that increases NO3− availability: the hydrogeomorphic evolution of polygonal permafrost landscapes. Permafrost thaw drives changes in microtopography, increasing the drainage of topographic highs, thus increasing oxic conditions that promote NO3− production and accumulation. We extrapolate relationships between NO3− and soil moisture in elevated topographic features within our study area and the broader Alaskan Coastal Plain and investigate potential changes in NO3− availability in response to possible hydrogeomorphic evolution scenarios of permafrost landscapes. These approximations indicate that such changes could increase Arctic tundra NO3− availability by ~250–1000%. Thus, hydrogeomorphic changes that accompany continued permafrost degradation in polygonal permafrost landscapes will substantially increase soil pore water NO3− availability and boost future fertilization and productivity in the Arctic.

High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

An Object-Based Approach for Mapping Tundra Ice-Wedge Polygon Troughs from Very High Spatial Resolution Optical Satellite Imagery

Very high spatial resolution commercial satellite imagery can inform observation, mapping, and documentation of micro-topographic transitions across large tundra regions. The bridging of fine-scale field studies with pan-Arctic system assessments has until now been constrained by a lack of overlap in spatial resolution and geographical coverage. This likely introduced biases in climate impacts on, and feedback from the Arctic region to the global climate system. The central objective of this exploratory study is to develop an object-based image analysis workflow to automatically extract ice-wedge polygon troughs from very high spatial resolution commercial satellite imagery. We employed a systematic experiment to understand the degree of interoperability of knowledge-based workflows across distinct tundra vegetation units—sedge tundra and tussock tundra—focusing on the same semantic class. In our multi-scale trough modelling workflow, we coupled mathematical morphological filtering with a segmentation process to enhance the quality of image object candidates and classification accuracies. Employment of the master ruleset on sedge tundra reported classification accuracies of correctness of 0.99, completeness of 0.87, and F1 score of 0.92. When the master ruleset was applied to tussock tundra without any adaptations, classification accuracies remained promising while reporting correctness of 0.87, completeness of 0.77, and an F1 score of 0.81. Overall, results suggest that the object-based image analysis-based trough modelling workflow exhibits substantial interoperability across the terrain while producing promising classification accuracies. From an Arctic earth science perspective, the mapped troughs combined with the ArcticDEM can allow hydrological assessments of lateral connectivity of the rapidly changing Arctic tundra landscape, and repeated mapping can allow us to track fine-scale changes across large regions and that has potentially major implications on larger riverine systems.

Divergent shrub-cover responses driven by climate, wildfire, and permafrost interactions in Arctic tundra ecosystems

The expansion of shrubs across the Arctic tundra may fundamentally modify land-atmosphere interactions. However, it remains unclear how shrub expansion pattern is linked with key environmental drivers, such as climate change and fire disturbance. Here we used 40+ years of high-resolution (~1.0 m) aerial and satellite imagery to estimate shrub-cover change in 114 study sites across four burned and unburned upland (ice-poor) and lowland (ice-rich) tundra ecosystems in northern Alaska. Validated with data from four additional upland and lowland tundra fires, our results reveal that summer precipitation was the most important climatic driver (r = 0.67, p < 0.001), responsible for 30.8% of shrub expansion in the upland tundra between 1971 and 2016. Shrub expansion in the uplands was largely enhanced by wildfire (p < 0.001) and it exhibited positive correlation with fire severity (r = 0.83, p < 0.001). Three decades after fire disturbance, the upland shrub cover increased by 1077.2 ± 83.6 m²  ha^-1 , ~7 times the amount identified in adjacent unburned upland tundra (155.1 ± 55.4 m²  ha^-1 ). In contrast, shrub cover markedly decreased in lowland tundra after fire disturbance, which triggered thermokarst-associated water impounding and resulted in 52.4% loss of shrub cover over three decades. No correlation was found between lowland shrub cover with fire severity (r = 0.01). Mean summer air temperature (MSAT) was the principal factor driving lowland shrub-cover dynamics between 1951 and 2007. Warmer MSAT facilitated shrub expansion in unburned lowlands (r = 0.78, p < 0.001), but accelerated shrub-cover losses in burned lowlands (r = -0.82, p < 0.001). These results highlight divergent pathways of shrub-cover responses to fire disturbance and climate change, depending on near-surface permafrost and drainage conditions. Our study offers new insights into the land-atmosphere interactions as climate warming and burning intensify in high latitudes.

Temporal, Spatial, and Temperature Controls on Organic Carbon Mineralization and Methanogenesis in Arctic High-Centered Polygon Soils

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°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.

Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamics

In northern Alaska nearly 65% of the terrestrial surface is composed of polygonal ground, where geomorphic tundra landforms disproportionately influence carbon and nutrient cycling over fine spatial scales. Process-based biogeochemical models used for local to Pan-Arctic projections of ecological responses to climate change typically operate at coarse-scales (1km2-0.5°) at which fine-scale (<1km2) tundra heterogeneity is often aggregated to the dominant land cover unit. Here, we evaluate the importance of tundra heterogeneity for representing soil carbon dynamics at fine to coarse spatial scales. We leveraged the legacy of data collected near Utqiaġvik, Alaska between 1973 and 2016 for model initiation, parameterization, and validation. Simulation uncertainty increased with a reduced representation of tundra heterogeneity and coarsening of spatial scale. Hierarchical cluster analysis of an ensemble of 21st-century simulations reveals that a minimum of two tundra landforms (dry and wet) and a maximum of 4km2 spatial scale is necessary for minimizing uncertainties (<10%) in regional to Pan-Arctic modeling applications.

Iron and iron-bound phosphate accumulate in surface soils of ice-wedge polygons in arctic tundra

Phosphorus (P) is a limiting or co-limiting nutrient to plants and microorganisms in diverse ecosystems that include the arctic tundra. Certain soil minerals can adsorb or co-precipitate with phosphate, and this mineral-bound P provides a potentially large P reservoir in soils. Iron (Fe) oxyhydroxides have a high capacity to adsorb phosphate; however, the ability of Fe oxyhydroxides to adsorb phosphate and limit P bioavailability in organic tundra soils is not known. Here, we examined the depth distribution of soil Fe and P species in the active layer (<30 cm) of low-centered and high-centered ice-wedge polygons at the Barrow Environmental Observatory on the Alaska North Slope. Soil reservoirs of Fe and P in bulk horizons and in narrower depth increments were characterized using sequential chemical extractions and synchrotron-based X-ray absorption spectroscopy (XAS). Organic horizons across all polygon features (e.g., trough, ridge, and center) were enriched in extractable Fe and P relative to mineral horizons. Soil Fe was dominated by organic-bound Fe and short-range ordered Fe oxyhydroxides, while soil P was primarily associated with oxides and organic matter in organic horizons but apatite and/or calcareous minerals in mineral horizons. Iron oxyhydroxides and Fe-bound inorganic P (Pi) were most enriched at the soil surface and decreased gradually with depth, and Fe-bound Pi was >4× greater than water-soluble Pi. These results demonstrate that Fe-bound Pi is a large and ecologically important reservoir of phosphate. We contend that Fe oxyhydroxides and other minerals may regulate Pi solubility under fluctuating redox conditions in organic surface soils on the arctic tundra.

Fast response of cold ice-rich permafrost in northeast Siberia to a warming climate

The ice- and organic-rich permafrost of the northeast Siberian Arctic lowlands (NESAL) has been projected to remain stable beyond 2100, even under pessimistic climate warming scenarios. However, the numerical models used for these projections lack processes which induce widespread landscape change termed thermokarst, precluding realistic simulation of permafrost thaw in such ice-rich terrain. Here, we consider thermokarst-inducing processes in a numerical model and show that substantial permafrost degradation, involving widespread landscape collapse, is projected for the NESAL under strong warming (RCP8.5), while thawing is moderated by stabilizing feedbacks under moderate warming (RCP4.5). We estimate that by 2100 thaw-affected carbon could be up to three-fold (twelve-fold) under RCP4.5 (RCP8.5), of what is projected if thermokarst-inducing processes are ignored. Our study provides progress towards robust assessments of the global permafrost carbon–climate feedback by Earth system models, and underlines the importance of mitigating climate change to limit its impacts on permafrost ecosystems.

Siberian Arctic permafrost contains vast stores of carbon, the fate of which is dependent on the climate. Here the authors use models of future scenarios to show that under the direst climate changes up to 2/3 of the stored organic carbon could thaw.

High-resolution mapping of spatial heterogeneity in ice wedge polygon geomorphology near Prudhoe Bay, Alaska

It is well known that microtopography associated with ice wedge polygons drives pronounced, meter-scale spatial gradients in hydrologic and ecological processes on the tundra. However, high-resolution maps of polygonal geomorphology are rarely available, due to the complexity and subtlety of ice wedge polygon relief at landscape scales. Here we present a sub-meter resolution map of >106 discrete ice wedge polygons across a ~1200 km2 landscape, delineated within a lidar-derived digital elevation model. The delineation procedure relies on a convolutional neural network paired with a set of common image processing operations and permits explicit measurement of relative elevation at the center of each ice wedge polygon. The resulting map visualizes meter- to kilometer-scale spatial gradients in polygonal geomorphology across an extensive landscape with unprecedented detail. This high-resolution inventory of polygonal geomorphology provides rich spatial context for extrapolating observations of environmental processes across the landscape. The map also represents an extensive baseline dataset for quantifying contemporary land surface deformation (i.e., thermokarst) at the survey area, through future topographic surveys.

Species interactions and distinct microbial communities in high Arctic permafrost affected cryosols are associated with the CH4 and CO2 gas fluxes

Microbial metabolism of the thawing organic carbon stores in permafrost results in a positive feedback loop of greenhouse gas emissions. CO₂ and CH₄ fluxes and the associated microbial communities in Arctic cryosols are important in predicting future warming potential of the Arctic. We demonstrate that topography had an impact on CH₄ and CO₂ flux at a high Arctic ice-wedge polygon terrain site, with higher CO₂ emissions and lower CH₄ uptake at troughs compared to polygon interior soils. The pmoA sequencing suggested that USCα cluster of uncultured methanotrophs is likely responsible for observed methane sink. Community profiling revealed distinct assemblages across the terrain at different depths. Deeper soils contained higher abundances of Verrucomicrobia and Gemmatimonadetes, whereas the polygon interior had higher Acidobacteria and lower Betaproteobacteria and Deltaproteobacteria abundances. Genome sequencing of isolates from the terrain revealed presence of carbon cycling genes including ones involved in serine and ribulose monophosphate pathways. A novel hybrid network analysis identified key members that had positive and negative impacts on other species. Operational Taxonomic Units (OTUs) with numerous positive interactions corresponded to Proteobacteria, Candidatus Rokubacteria and Actinobacteria phyla, while Verrucomicrobia and Acidobacteria members had negative impacts on other species. Results indicate that topography and microbial interactions impact community composition.

Evaluating temporal controls on greenhouse gas (GHG) fluxes in an Arctic tundra environment: An entropy-based approach

There is significant spatial and temporal variability associated with greenhouse gas (GHG) fluxes in high-latitude Arctic tundra environments. The objectives of this study are to investigate temporal variability in CO₂ and CH₄ fluxes at Barrow, AK and to determine the factors causing this variability using a novel entropy-based classification scheme. In particular, we analyzed which geomorphic, soil, vegetation and climatic properties most explained the variability in GHG fluxes (opaque chamber measurements) during the growing season over three successive years. Results indicate that multi-year variability in CO₂ fluxes was primarily associated with soil temperature variability as well as vegetation dynamics during the early and late growing season. Temporal variability in CH₄ fluxes was primarily associated with changes in vegetation during the growing season and its interactions with primary controls like seasonal thaw. Polygonal ground features, which are common to Arctic regions, also demonstrated significant multi-year variability in GHG fluxes. Our results can be used to prioritize field sampling strategies, with an emphasis on measurements collected at locations and times that explain the most variability in GHG fluxes. For example, we found that sampling primary environmental controls at the centers of high centered polygons in the month of September (when freeze-back period begins) can provide significant constraints on GHG flux variability - a requirement for accurately predicting future changes to GHG fluxes. Overall, entropy results document the impact of changing environmental conditions (e.g., warming, growing season length) on GHG fluxes, thus providing clues concerning the manner in which ecosystem properties may be shifted regionally in a future climate.

Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery

The microtopography associated with ice-wedge polygons governs many aspects of Arctic ecosystem, permafrost, and hydrologic dynamics from local to regional scales owing to the linkages between microtopography and the flow and storage of water, vegetation succession, and permafrost dynamics. Wide-spread ice-wedge degradation is transforming low-centered polygons into high-centered polygons at an alarming rate. Accurate data on spatial distribution of ice-wedge polygons at a pan-Arctic scale are not yet available, despite the availability of sub-meter-scale remote sensing imagery. This is because the necessary spatial detail quickly produces data volumes that hamper both manual and semi-automated mapping approaches across large geographical extents. Accordingly, transforming big imagery into ‘science-ready’ insightful analytics demands novel image-to-assessment pipelines that are fueled by advanced machine learning techniques and high-performance computational resources. In this exploratory study, we tasked a deep-learning driven object instance segmentation method (i.e., the Mask R-CNN) with delineating and classifying ice-wedge polygons in very high spatial resolution aerial orthoimagery. We conducted a systematic experiment to gauge the performances and interoperability of the Mask R-CNN across spatial resolutions (0.15 m to 1 m) and image scene contents (a total of 134 km2) near Nuiqsut, Northern Alaska. The trained Mask R-CNN reported mean average precisions of 0.70 and 0.60 at thresholds of 0.50 and 0.75, respectively. Manual validations showed that approximately 95% of individual ice-wedge polygons were correctly delineated and classified, with an overall classification accuracy of 79%. Our findings show that the Mask R-CNN is a robust method to automatically identify ice-wedge polygons from fine-resolution optical imagery. Overall, this automated imagery-enabled intense mapping approach can provide a foundational framework that may propel future pan-Arctic studies of permafrost thaw, tundra landscape evolution, and the role of high latitudes in the global climate system.

Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska

Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10–100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (~60,000 km²) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30 m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999–2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.

Reduced arctic tundra productivity linked with landform and climate change interactions

Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (~60,000 km²) using the Landsat archive (1999-2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.

Threshold loss of discontinuous permafrost and landscape evolution

This study demonstrates linkages between the 1997/1998 El Niño/Southern Oscillation index and a threshold shift to increased permafrost loss within a southern Taiga Plains watershed, Northwest Territories, Canada. Three-dimensional contraction of permafrost plateaus and changes in vegetation structural characteristics are determined from multitemporal airborne Light Detection And Ranging (LiDAR) surveys in 2008, 2011 and 2015. Morphological changes in permafrost cover are compared with optical image analogues from 1970, 1977, 2000 and 2008 and time-series hydro-climate data. Results demonstrate that significant changes in air temperature, precipitation, runoff and a shortening of the snow-covered season by 35 days (1998-2014) and 50 days (1998 only) occurred after 1997. The albedo reduction associated with 35 and 50 days less snow cover leads to increases in shortwave energy receipt during the active thaw period of ~12% (3% annually) and ~16% (5% annually), respectively. From 2000 to 2015, sporadic permafrost loss accelerated from 0.19% (of total basin area) per year between 1970 and 2000 to 0.58% per year from 2000 to 2015, with a projected total loss of permafrost by ~2044. From ~1997 to 2011, we observe a corresponding shift to increased runoff ratio. However, observed increases in the proportion of snow precipitation and the volumetric contribution of permafrost loss to runoff post-1997 (0.6-6.4% per year) cannot fully explain this shift. This suggests increases in drainage efficiency and possible losses from long-term groundwater storage as a result of subtle terrain morphological and soil zone hydraulic conductivity changes. These hydrological changes appear coincident with high vegetation mortality at plateau margins combined with succession-related canopy growth in some bog and fen areas, which are presumed to be drying. Similar changes in runoff response were observed at adjacent Birch, Trout and Jean Marie River watersheds indicating that observations are representative of northern Boreal sporadic permafrost/wetland watersheds in the Taiga Plains.

Rising plant-mediated methane emissions from arctic wetlands

Plant-mediated CH₄ flux is an important pathway for land-atmosphere CH₄ emissions, but the magnitude, timing, and environmental controls, spanning scales of space and time, remain poorly understood in arctic tundra wetlands, particularly under the long-term effects of climate change. CH₄ fluxes were measured in situ during peak growing season for the dominant aquatic emergent plants in the Alaskan arctic coastal plain, Carex aquatilis and Arctophila fulva, to assess the magnitude and species-specific controls on CH₄ flux. Plant biomass was a strong predictor of A. fulva CH₄ flux while water depth and thaw depth were copredictors for C. aquatilis CH₄ flux. We used plant and environmental data from 1971 to 1972 from the historic International Biological Program (IBP) research site near Barrow, Alaska, which we resampled in 2010-2013, to quantify changes in plant biomass and thaw depth, and used these to estimate species-specific decadal-scale changes in CH₄ fluxes. A ~60% increase in CH₄ flux was estimated from the observed plant biomass and thaw depth increases in tundra ponds over the past 40 years. Despite covering only ~5% of the landscape, we estimate that aquatic C. aquatilis and A. fulva account for two-thirds of the total regional CH₄ flux of the Barrow Peninsula. The regionally observed increases in plant biomass and active layer thickening over the past 40 years not only have major implications for energy and water balance, but also have significantly altered land-atmosphere CH₄ emissions for this region, potentially acting as a positive feedback to climate warming.

Isotopic insights into methane production, oxidation, and emissions in Arctic polygon tundra

Arctic wetlands are currently net sources of atmospheric CH4 . Due to their complex biogeochemical controls and high spatial and temporal variability, current net CH4 emissions and gross CH4 processes have been difficult to quantify, and their predicted responses to climate change remain uncertain. We investigated CH4 production, oxidation, and surface emissions in Arctic polygon tundra, across a wet-to-dry permafrost degradation gradient from low-centered (intact) to flat- and high-centered (degraded) polygons. From 3 microtopographic positions (polygon centers, rims, and troughs) along the permafrost degradation gradient, we measured surface CH4 and CO2 fluxes, concentrations and stable isotope compositions of CH4 and DIC at three depths in the soil, and soil moisture and temperature. More degraded sites had lower CH4 emissions, a different primary methanogenic pathway, and greater CH4 oxidation than did intact permafrost sites, to a greater degree than soil moisture or temperature could explain. Surface CH4 flux decreased from 64 nmol m(-2)  s(-1) in intact polygons to 7 nmol m(-2)  s(-1) in degraded polygons, and stable isotope signatures of CH4 and DIC showed that acetate cleavage dominated CH4 production in low-centered polygons, while CO2 reduction was the primary pathway in degraded polygons. We see evidence that differences in water flow and vegetation between intact and degraded polygons contributed to these observations. In contrast to many previous studies, these findings document a mechanism whereby permafrost degradation can lead to local decreases in tundra CH4 emissions.

Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type.