Permafrost degradation in peatlands is altering vegetation and soil properties and impacting net carbon storage. We studied four adjacent sites in Alaska with varied permafrost regimes, including a black spruce forest on a peat plateau with permafrost, two collapse scar bogs of different ages formed following thermokarst, and a rich fen without permafrost. Measurements included year-round eddy covariance estimates of net carbon dioxide (CO2), mid-April to October methane (CH4) emissions, and environmental variables. From 2011 to 2022, annual rainfall was above the historical average, snow water equivalent increased, and snow-season duration shortened due to later snow return. Seasonally thawed active layer depths also increased. During this period, all ecosystems acted as slight annual sources of CO2 (13-59 g C m(-2) year(-1)) and stronger sources of CH4 (11-14 g CH4 m(-2) from similar to April to October). The interannual variability of net ecosystem exchange was high, approximately +/- 100 g C m(-2) year(-1), or twice what has been previously reported across other boreal sites. Net CO2 release was positively related to increased summer rainfall and winter snow water equivalent and later snow return. Controls over CH4 emissions were related to increased soil moisture and inundation status. The dominant emitter of carbon was the rich fen, which, in addition to being a source of CO2, was also the largest CH4 emitter. These results suggest that the future carbon-source strength of boreal lowlands in Interior Alaska may be determined by the area occupied by minerotrophic fens, which are expected to become more abundant as permafrost thaw increases hydrologic connectivity. Since our measurements occur within close proximity of each other (<= 1 km(2)), this study also has implications for the spatial scale and data used in benchmarking carbon cycle models and emphasizes the necessity of long-term measurements to identify carbon cycle process changes in a warming climate.

Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land-atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integrates in-situ measurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics-active layer thickness (ALT), carbon dioxide flux (CO2), and methane flux (CH4)-with high precision and minimal loss (i.e. ALTRMSE: 1.327 cm [1969-2022]; CO2 RMSE: 0.697 mu molCO2m-2s-1 [2003-2021]; CH4 RMSE: 0.715 nmolCH4m-2s-1 [2011-2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Permafrost degradation is altering biogeochemical processes throughout the Arctic. Thaw-induced changes in organic matter transformations and mineral weathering reactions are impacting fluxes of inorganic carbon (IC) and alkalinity (ALK) in Arctic rivers. However, the net impact of these changing fluxes on the concentration of carbon dioxide in the atmosphere (pCO(2)) is relatively unconstrained. Resolving this uncertainty is important as thaw-driven changes in the fluxes of IC and ALK could produce feedbacks in the global carbon cycle. Enhanced production of sulfuric acid through sulfide oxidation is particularly poorly quantified despite its potential to remove ALK from the ocean-atmosphere system and increase pCO(2), producing a positive feedback leading to more warming and permafrost degradation. In this work, we quantified weathering in the Koyukuk River, a major tributary of the Yukon River draining discontinuous permafrost in central Alaska, based on water and sediment samples collected near the village of Huslia in summer 2018. Using measurements of major ion abundances and sulfate (SO42-) sulfur (S-34/S-32) and oxygen (O-18/O-16) isotope ratios, we employed the MEANDIR inversion model to quantify the relative importance of a suite of weathering processes and their net impact on pCO(2). Calculations found that approximately 80% of SO42- in mainstem samples derived from sulfide oxidation with the remainder from evaporite dissolution. Moreover, S-34/S-32 ratios, C-13/C-12 ratios of dissolved IC, and sulfur X-ray absorption spectra of mainstem, secondary channel, and floodplain pore fluid and sediment samples revealed modest degrees of microbial sulfate reduction within the floodplain. Weathering fluxes of ALK and IC result in lower values of pCO(2) over timescales shorter than carbonate compensation (similar to 10(4) yr) and, for mainstem samples, higher values of pCO(2) over timescales longer than carbonate compensation but shorter than the residence time of marine SO42- (similar to 10(7) yr). Furthermore, the absolute concentrations of SO42- and Mg2+ in the Koyukuk River, as well as the ratios of SO42- and Mg2+ to other dissolved weathering products, have increased over the past 50 years. Through analogy to similar trends in the Yukon River, we interpret these changes as reflecting enhanced sulfide oxidation due to ongoing exposure of previously frozen sediment and changes in the contributions of shallow and deep flow paths to the active channel. Overall, these findings confirm that sulfide oxidation is a substantial outcome of permafrost degradation and that the sulfur cycle responds to permafrost thaw with a timescale-dependent feedback on warming.

The thawing of permafrost in the Arctic has led to an increase in coastal land loss, flooding, and ground subsidence, seriously threatening civil infrastructure and coastal communities. However, a lack of tools for synthetic hazard assessment of the Arctic coast has hindered effective response measures. We developed a holistic framework, the Arctic Coastal Hazard Index (ACHI), to assess the vulnerability of Arctic coasts to permafrost thawing, coastal erosion, and coastal flooding. We quantified the coastal permafrost thaw potential (PTP) through regional assessment of thaw subsidence using ground settlement index. The calculations of the ground settlement index involve utilizing projections of permafrost conditions, including future regional mean annual ground temperature, active layer thickness, and talik thickness. The predicted thaw subsidence was validated through a comparison with observed long-term subsidence data. The ACHI incorporates the PTP into seven physical and ecological variables for coastal hazard assessment: shoreline type, habitat, relief, wind exposure, wave exposure, surge potential, and sea-level rise. The coastal hazard assessment was conducted for each 1 km2 coastline of North Slope Borough, Alaska in the 2060s under the Representative Concentration Pathway 4.5 and 8.5 forcing scenarios. The areas that are prone to coastal hazards were identified by mapping the distribution pattern of the ACHI. The calculated coastal hazards potential was subjected to validation by comparing it with the observed and historical long-term coastal erosion mean rates. This framework for Arctic coastal assessment may assist policy and decision-making for adaptation, mitigation strategies, and civil infrastructure planning.

In the context of global warming, permafrost degrades gradually. To cope with the instability of the cryosphere, it is very important to strengthen the monitoring of the seasonal freeze-thaw cycle. At present, active and passive microwave remote sensing data are widely used in freeze/thaw (F/T) onset detection. There is some potential to improve accuracy through the combination of active and passive microwave data. Compared with the traditional method for combination, the machine learning algorithm has a stronger nonlinear expression ability. Therefore, it is advisable to use machine learning to combine multi-source data for freeze/thaw onset detection. In this study, the temporal change detection method is applied to SMAP data and ASCAT data respectively for preliminary detection. Then the Random Forest algorithm (RF) is used to combine the preliminary results of active and passive microwave data with site observation to estimate the freeze/thaw onsets more accurately. The method is validated with data obtained in Alaska from 2015 to 2019. The accuracy evaluation shows that the proposed method can effectively improve the accuracy of freeze/thaw onset detection. The predicted distribution of the freeze/thaw cycle indicates that the variation of the freeze-thaw cycle is closely related to latitude. In general, the proposed method based on machine learning is promising in the research of freeze-thaw state monitoring.

Manifestations of climate change in the Arctic are numerous and include hydrological cycle intensification and permafrost thaw, both expected as a result of atmospheric and surface warming. Across the terrestrial Arctic dissolved organic carbon (DOC) entrained in arctic rivers may be providing a carbon subsidy to coastal food webs. Yet, data from field sampling is too often of limited duration to confidently ascertain impacts of climate change on freshwater and DOC flows to coastal waters. This study applies numerical modeling to investigate trends in freshwater and DOC exports from land to Elson Lagoon in Northwest Alaska over the period 1981-2020. While the modeling approach has limitations, the results point to significant increases in freshwater and DOC exports to the lagoon over the past four decades. The model simulation reveals significant increases in surface, subsurface (suprapermafrost), and total freshwater exports. Significant increases are also noted in surface and subsurface DOC production and export, influenced by warming soils and associated active-layer thickening. The largest changes in subsurface components are noted in September, which has experienced a similar to 50% increase in DOC export emanating from suprapermafrost flow. Direct coastal suprapermafrost freshwater and DOC exports in late summer more than doubled between the first and last five years of the simulation period, with a large anomaly in September 2019 representing a more than fourfold increase over September direct coastal export during the early 1980s. These trends highlight the need for dedicated measurement programs that will enable improved understanding of climate change impacts on coastal zone processes in this data sparse region of Northwest Alaska.

Permafrost soils store approximately twice the amount of carbon currently present in Earth's atmosphere and are acutely impacted by climate change due to the polar amplification of increasing global temperature. Many organic-rich permafrost sediments are located on large river floodplains, where river channel migration periodically erodes and redeposits the upper tens of meters of sediment. Channel migration exerts a first-order control on the geographic distribution of permafrost and floodplain stratigraphy and thus may affect microbial habitats. To examine how river channel migration in discontinuous permafrost environments affects microbial community composition, we used amplicon sequencing of the 16S rRNA gene on sediment samples from floodplain cores and exposed riverbanks along the Koyukuk River, a large tributary of the Yukon River in west-central Alaska. Microbial communities are sensitive to permafrost thaw: communities found in deep samples thawed by the river closely resembled near-surface active-layer communities in nonmetric multidimensional scaling analyses but did not resemble floodplain permafrost communities at the same depth. Microbial communities also displayed lower diversity and evenness in permafrost than in both the active layer and permafrost-free point bars recently deposited by river channel migration. Taxonomic assignments based on 16S and quantitative PCR for the methyl coenzyme M reductase functional gene demonstrated that methanogens and methanotrophs are abundant in older permafrost-bearing deposits but not in younger, nonpermafrost point bar deposits. The results suggested that river migration, which regulates the distribution of permafrost, also modulates the distribution of microbes potentially capable of producing and consuming methane on the Koyukuk River floodplain. IMPORTANCE Arctic lowlands contain large quantities of soil organic carbon that is currently sequestered in permafrost. With rising temperatures, permafrost thaw may allow this carbon to be consumed by microbial communities and released to the atmosphere as carbon dioxide or methane. We used gene sequencing to determine the microbial communities present in the floodplain of a river running through discontinuous permafrost. We found that the river's lateral movement across its floodplain influences the occurrence of certain microbial communities-in particular, methane-cycling microbes were present on the older, permafrost-bearing eroding riverbank but absent on the newly deposited river bars. Riverbank sediment had microbial communities more similar to those of the floodplain active-layer samples than permafrost samples from the same depth. Therefore, spatial patterns of river migration influence the distribution of microbial taxa relevant to the warming Arctic climate.

The Circumpolar Active Layer Monitoring (CALM) network is an ongoing international effort to collect and disseminate standardized measurements of active-layer dynamics to monitor the response of near-surface permafrost parameters to climate change. This work presents a distillation of 25 years (1995-2019) of observations from three north-south transects of CALM sites in tundra environments of Alaska. Transects examined in this work bisect tundra regions of discontinuous permafrost on the Seward Peninsula, and the continuous permafrost zone on the western and eastern sections of the Arctic Foothills and Arctic Coastal Plain. These transects represent regional climatic gradients, several physiographic provinces, and regionally characteristic landcover associations. Total active-layer thickening at observed sites ranged from 7 to 26 cm; more significant thaw occurred in the foothills despite less pronounced warming air temperature trends. This summary highlights several regional active layer responses to climate warming, complicated by distinct thermal landscape sensitivities, landscape variability, and documented thaw subsidence. Data summarized in this report are publicly available and represent an important validation resource for earth-system models that include regions in the continuous and discontinuous permafrost zones of northern and western Alaska.

As the Arctic warms, tundra wildfires are expected to become more frequent and severe. Assessing how the most flammable regions of the tundra respond to burning can inform us about how the rest of the Arctic may be affected by climate change. Here we describe ecosystem responses to tundra fires in the Noatak River watershed of northwestern Alaska using shrub dendrochronology, active-layer depth monitoring, and remotely sensed vegetation productivity. Results show that relatively productive tundra is more likely to experience fires and to burn more severely, suggesting that fuel loads currently limit tundra fire distribution in the Noatak Valley. Within three years of burning, most alder shrubs sampled had either germinated or resprouted, and vegetation productivity inside 60 burn perimeters had recovered to prefire values. Tundra fires resulted in two phases of increased primary productivity as manifested by increased landscape greening. Phase one occurred in most burned areas 3-10 years after fires, and phase two occurred 16-44 years after fire at sites where tundra fires triggered near-surface permafrost thaw resulting in shrub proliferation. A fire-shrub-greening positive feedback is currently operating in the Noatak Valley and this feedback could expand northward as air temperatures, fire frequencies, and permafrost degradation increase. This feedback will not occur at all locations. In the Noatak Valley, the fire-shrub-greening process is relatively limited in tussock tundra communities, where low-severity fires and shallow active layers exclude shrub proliferation. Climate warming and enhanced fire occurrence will likely shift fire-poor landscapes into either the tussock tundra or erect-shrub-tundra ecological attractor states that now dominate the fire-rich Noatak Valley.

To characterize the spatiotemporal variations of glacier surface speed on the Kenai Peninsula, Alaska (similar to 3,900 km(2)), we derived 92 surface speed fields between October 2014 and December 2019 using intensity offset tracking on Sentinel-1 data. On average, speeds are 50% greater in spring (March-May) than the annual mean (69 m a(-1)) while winter speeds are close to the annual mean. While marine-terminating glaciers have their maximum speed near the terminus, both land- and lake-terminating glaciers flow fastest around the median glacier elevation. On average, the lake-terminating and tidewater glaciers flow 1.7 and 2.3 times faster than the land-terminating glaciers, respectively. Monthly variations over the 5-year period are strikingly synchronous regardless of terminus type suggesting that regional-scale meteorological drivers govern the temporal variability. Mean annual speeds fluctuate roughly +/- 10% of the period mean without an apparent trend. At lake-terminating Bear Glacier, a short-term tripling in ice speed in fall 2019 over the area below an ice-dammed lake coincides with an observed glacier lake outburst flood (GLOF). An earlier GLOF caused a persistent breach of the beach barrier between the proglacial lake and ocean which likely led to overall speed-up of the lower glacier part throughout 2019. A significant speedup was also observed at the lower part of the lake-terminating Ellsworth Glacier and attributed to rapid glacier retreat and lake expansion, probably further amplified by the terminus area becoming buoyant and a large tabular iceberg breaking off. Our results highlight the impact of GLOFs and proglacial characteristics in spatial and temporal glacier speed variations.