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This dataset describes measurements of river migration rates (averaged over the period 2016-2022) in three locations within the Yukon River Watershed: Huslia, Alaska (AK) (65.700 N, 156.387 W), Beaver, AK (66.362 N, 147.398 W), and Alakanuk, AK (62.685 N, 164.644 W). Huslia is located on the Koyukuk River and Beaver and Alakanuk are located on the Yukon River. The river migration rates are quantified from sub-pixel correlation of optical satellite imagery (Sentinel-2 imagery, 10 meter (m) spatial resolution), following the methodology of Geyman et al. (2024). The methodology allows for the detection of riverbank erosion at scales approximately 5-10 times smaller than the pixel size, so the detection threshold is 1-2 m over the approximately 7-year interval, corresponding to a migration rate of 0.1 to 0.3 m/year. The motion of the eroding and accreting sides of the river are quantified separately. The river migration rate datasets are made available as georeferenced shapefiles. 

This document describes geomorphic relative age mapping and radiocarbon (14C) measurements used to construct floodplain age models for three locations within the Yukon River Watershed: Huslia, Alaska (65.700 N, 156.387 W), Alakanuk, Alaska (62.685 N, 164.644 W), and Beaver, Alaska (66.362 N, 147.398 W). We describe the field sampling protocols, geomorphic mapping of cross-cutting relationships (aided by digital elevation models (DEMs) and high-resolution satellite imagery), 14C and optically stimulated luminescence (OSL) lab analyses, Markov Chain Monte Carlo (MCMC) interpolation through the geomorphic–radiogenic age constraints, and the resulting floodplain terrain age models. 

The carbon stored in permafrost deposits represents the single largest soil carbon reservoir on Earth. Concerns about the instability and dynamics of this carbon reservoir during permafrost thaw associated with polar amplification of climate warming contribute a large part of the uncertainty in forecasting future climate. We have been studying the carbon dynamics of permafrost deposits contained in the floodplains of large Arctic rivers. Across Arctic floodplains, accelerating bank erosion can liberate permafrost organic carbon (OC) as carbon dioxide (CO2) or methane (CH4), and/or redeposit it in fluvial units. These different fates have very different implications for climate feedback. Determining OC stocks and their dynamics in Arctic floodplain cutbanks and point bars, as well as the OC load in fluvial transport, is essential to better understand the recycling and export of permafrost carbon. As part of a National Science Foundation (NSF) funded project to better understand the effects of erosion in the Yukon River Basin, floodplain sediments were collected between June and September 2022 at two locations underlain by discontinuous permafrost within the Yukon River Basin in Alaska: Beaver (65.700° North (N), 156.387° West (W)) and Huslia (66.362° N, 147.398° W). This dataset mainly reports OC contents for collected subsurface sediments in floodplains measured by elemental analyzer. The coupled mercury content can be found in Isabel et al., 2024 (https://doi.org/10.18739/A2RF5KH5J). 

Due to atmospheric circulation and preservation of organic matter, large amounts of mercury (Hg) are stored in permafrost regions. Due to rapid warming and thawing permafrost in the Arctic, this Hg may be released, potentially degrading water quality and impacting human health. River bank erosion in particular has the ability to quickly mobilize large amounts of Hg-rich floodplain sediments. As part of a National Science Foundation (NSF) funded project to better understand the effects of erosion in the Yukon River Basin, floodplain sediments were collected between June and September 2022 at two locations underlain by discontinuous permafrost within the Yukon River Basin: Beaver, Alaska (AK) (65.700 N, 156.387 W) and Huslia, AK (66.362N, 147.398 W). This dataset contains mercury contents for collected floodplain sediments measured by direct thermal decomposition. Sample metadata also includes information recorded in the field (location, visual grain size description, and sample collection depth) and collected post sample processing (water content and dry density). 

This dataset includes field measurements of above-ground biomass made between May and October, 2023 in three locations within the Yukon River Watershed: Huslia, Alaska(AK) (65.700 N, 156.387W), Beaver, AK (66.362 N, 147.398W), and Alakanuk, AK (62.685N, 164.644W). We measured a total of 11,335 trees, distributed in 190 field plots (approximately 10 meter (m) x 10 m). We apply allometric scaling relations to convert measurements of tree diameter to kilograms of dry biomass. We then link these filed measurements of above-ground biomass density to the mean forest canopy height (MCH), derived from airborne Light Detection and Ranging (LiDAR) data. We derive empirical regressions linking MCH to above-ground biomass in each of the field sites, and then apply these empirical relationships to the LiDAR datasets to obtain maps of above-ground biomass density. This dataset includes both the field observations (coordinates, tree type, and tree diameter of the 11,335 inventoried trees) and the processed above-ground biomass maps (georeferenced TIFF files, with a spatial resolution of 10 m). 

ABSTRACT Quantitative analysis of quartz microtextures by means of scanning electron microscopy (SEM) can reveal the transport histories of modern and ancient sediments. However, because workers identify and count microtextures differently, it is difficult to directly compare quantitative microtextural data analyzed by different workers. As a result, the defining microtextures of certain transport modes and their probabilities of occurrence are not well constrained. We used principal-component analysis (PCA) to directly compare modern and ancient aeolian, fluvial, and glacial samples from the literature with nine new samples from active aeolian and glacial environments. Our results demonstrate that PCA can group microtextural samples by transport mode and differentiate between aeolian transport and fluvial and glacial transport across studies. The PCA ordination indicates that aeolian samples are distinct from fluvial and glacial samples, which are in turn difficult to disambiguate from each other. Ancient and modern sediments are also shown to have quantitatively similar microtextural relationships. Therefore, PCA may be a useful tool to constrain the ambiguous transport histories of some ancient sediment grains. As a case study, we analyzed two samples with ambiguous transport histories from the Cryogenian Bråvika Member (Svalbard). Integrating PCA with field observations, we find evidence that the Bråvika Member facies investigated here includes aeolian deposition and may be analogous to syn-glacial Marinoan aeolian units including the Bakoye Formation in Mali and the Whyalla Sandstone in South Australia.