Search for: All records

ABSTRACT The Yukon‐Kuskokwim Delta (YKD), covering ~75,000 km²of Alaska's discontinuous permafrost zone, has a historic (1902–2023) mean annual air temperature of ~−1°C and was previously thought to lack ice wedge networks. However, our recent investigations near Bethel, Alaska, revealed numerous near‐surface ice wedges. Using 20 cm resolution aerial orthoimagery from 2018, we identified ~50 linear km of ice wedge troughs in a 60 km²study area. Fieldwork in 2023 and 2024 confirmed ice wedges up to ~1.5 m wide and ~2.5 m in vertical extent, situated on average 0.9 m below the tundra surface (n = 29). Ground‐penetrating radar (GPR) detected additional ice wedges beyond those visible in the remote sensing imagery, suggesting an underestimation of their true abundance. Coring of polygonal centers revealed late‐Quaternary deposits, including thick early Holocene peat, late‐Pleistocene ice‐rich silts (reworked Yedoma), charcoal layers from tundra fires, and the Aniakchak CFE II tephra (~3600 cal yrs BP). Stable water isotopes from Bethel's wedge ice (mean δ¹⁸O = −15.7 ‰, δ²H = −113.1 ‰) indicate a relatively enriched signature compared to other Holocene ice wedges in Alaska, likely due to warmer temperatures and maritime influences. Expanding our mapping across the YKD using high‐resolution satellite imagery from 2012 to 2024, we estimate that the Holocene ice wedge zone encompasses ~30% of the YKD tundra region. Our findings demonstrate that ice wedge networks are more widespread across the YKD than previously recognized, emphasizing both the resilience and vulnerability of the region's warm, ice‐rich permafrost. These insights are crucial for understanding permafrost responses to climate change and assessing agricultural potential and development in the region. 

Abstract Many studies of Earth surface processes and landscape evolution rely on having accurate and extensive data sets of surficial geologic units and landforms. Automated extraction of geomorphic features using deep learning provides an objective way to consistently map landforms over large spatial extents. However, there is no consensus on the optimal input feature space for such analyses. We explore the impact of input feature space for extracting geomorphic features from land surface parameters (LSPs) derived from digital terrain models (DTMs) using convolutional neural network (CNN)‐based semantic segmentation deep learning. We compare four input feature space configurations: (a) a three‐layer composite consisting of a topographic position index (TPI) calculated using a 50 m radius circular window, square root of topographic slope, and TPI calculated using an annulus with a 2 m inner radius and 10 m outer radius, (b) a single illuminating position hillshade, (c) a multidirectional hillshade, and (d) a slopeshade. We test each feature space input using three deep learning algorithms and four use cases: two with natural features and two with anthropogenic features. The three‐layer composite generally provided lower overall losses for the training samples, a higher F1‐score for the withheld validation data, and better performance for generalizing to withheld testing data from a new geographic extent. Results suggest that CNN‐based deep learning for mapping geomorphic features or landforms from LSPs is sensitive to input feature space. Given the large number of LSPs that can be derived from DTM data and the variety of geomorphic mapping tasks that can be undertaken using CNN‐based methods, we argue that additional research focused on feature space considerations is needed and suggest future research directions. We also suggest that the three‐layer composite implemented here can offer better performance in comparison to using hillshades or other common terrain visualization surfaces and is, thus, worth considering for different mapping and feature extraction tasks. 

Abstract Seawater intrusion (SWI) affects coastal landscapes worldwide. Here we describe the hydrologic pathways through which SWI occurs ‐ over land via storm surge or tidal flooding, under land via groundwater transport, and through watersheds via natural and artificial surface water channels—and how human modifications to those pathways alter patterns of SWI. We present an approach to advance understanding of spatiotemporal patterns of salinization that integrates these hydrologic pathways, their interactions, and how humans modify them. We use examples across the East Coast of the United States that exemplify mechanisms of salinization that have been reported around the planet to illustrate how hydrologic connectivity and human modifications alter patterns of SWI. Finally, we suggest a path for advancing SWI science that includes (a) deploying standardized and well‐distributed sensor networks at local to global scales that intentionally track SWI fronts, (b) employing remote sensing and geospatial imaging techniques targeted at integrating above and belowground patterns of SWI, and (c) continuing to develop data analysis and model‐data fusion techniques to measure the extent, understand the effects, and predict the future of coastal salinization. 

Abstract 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⁻²from ~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 CO₂release was positively related to increased summer rainfall and winter snow water equivalent and later snow return. Controls over CH₄emissions 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 CH₄emitter. 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 km²), 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. 

Abstract The tectonometamorphic evolution of the southern Appalachians, which results from multiple Paleozoic orogenies (Taconic, Neoacadian, and Alleghanian), has lacked a consensus interpretation regarding its thermal‐metamorphic history. The Blue Ridge terranes have remained the focus of the debate, with the interpreted timing of regional Barrovian metamorphism and associated deformation ranging from early (Taconic) to late Paleozoic (Alleghanian). New monazite U‐Pb geochronology and thermobarometric data are integrated with previously reported geo‐ and thermochronology to delimit the Paleozoic thermal‐metamorphic evolution of these terranes. Monazite compositional, textural, and U‐Pb age systematics are remarkably consistent for all samples, yielding a single dominant age mode for each sample. The western, central, and eastern Blue Ridge terranes yield weighted mean monazite U‐Pb ages of 450–441, 459–457, and 458–453 Ma, respectively. Thermodynamic modeling using mineral assemblages yields peak conditions of 600°C–650°C and 5.8–8.9 kbar for staurolite and kyanite grade western Blue Ridge units, including the stratigraphically youngest unit in the Murphy syncline, which also yields a weighted mean monazite U‐Pb age of 441 Ma. The Taconic metamorphic core of the central Blue Ridge yields peak conditions of 775°C and ∼11.5 kbar. Combined, these ages indicate that the relatively intact Barrovian metamorphic progression mapped across the Blue Ridge of Tennessee, North Carolina, and northern Georgia is solely of Ordovician (Taconic) age. Synthesis of this new data with existing geo‐ and thermochronology support a model of Barrovian metamorphism resulting from construction of a Taconic accretionary wedge and subduction complex, followed by post‐Taconic unroofing during Neoacadian and Alleghanian thrusting. 

Abstract Climate warming in high‐latitude regions is thawing carbon‐rich permafrost soils, which can release carbon to the atmosphere and enhance climate warming. Using a coupled model of long‐term peatland dynamics (Holocene Peat Model, HPM‐Arctic), we quantify the potential loss of carbon with future climate warming for six sites with differing climates and permafrost histories in Northwestern Canada. We compared the net carbon balance at 2100 CE resulting from new productivity and the decomposition of active layer and newly thawed permafrost peats under RCP8.5 as a high‐end constraint. Modeled net carbon losses ranged from −3.0 kg C m⁻²(net loss) to +0.1 kg C m⁻²(net gain) between 2015 and 2100. Losses of newly thawed permafrost peat comprised 0.2%–25% (median: 1.6%) of “old” C loss, which were related to the residence time of peat in the active layer before being incorporated into the permafrost, peat temperature, and presence of permafrost. The largest C loss was from the permafrost‐free site, not from permafrost sites. C losses were greatest from depths of 0.2–1.0 m. New C added to the profile through net primary productivity between 2015 and 2100 offset ∼40% to >100% of old C losses across the sites. Differences between modeled active layer deepening and flooding following permafrost thaw resulted in very small differences in net C loss by 2100, illustrating the important role of present‐day conditions and permafrost aggradation history in controlling net C loss. 

Abstract Hurricanes cause substantial loss of life and resources in coastal areas. Unfortunately, historical hurricane records are too short and incomplete to capture hurricane‐climate interactions on multi‐decadal and longer timescales. Coarse‐grained, hurricane‐induced deposits preserved in blue holes in the Caribbean can provide records of past hurricane activity extending back thousands of years. Here we present a high resolution record of intense hurricane events over the past 1500 years from a blue hole on South Andros Island on the Great Bahama Bank. This record is corroborated by shorter reconstructions from cores collected at two nearby blue holes. The record contains coarse‐grained event deposits attributable to known historical hurricane strikes within age uncertainties. Over the past 1500 years, South Andros shows evidence of four active periods of hurricane activity. None of these active intervals occurred in the past 163 years. We suggest that Intertropical Convergence Zone position modulates hurricane activity on the island based on a correlation with Cariaco Basin titanium concentrations. An anomalous gap in activity on South Andros Island in the early 13th century corresponds to a period of increased volcanism. The patterns of hurricane activity reconstructed from South Andros Island closely match those from the northeastern Gulf of Mexico but are anti‐phased with records from New England. We suggest that either changes in local environmental conditions (e.g., SSTs) or a northeastward shift in storm tracks can account for the increased activity in the western North Atlantic when the Gulf of Mexico and southeastern Caribbean are less active.