Search for: All records

This dataset describes measurements of inter-annual to sub-seasonal riverbank erosion rates on the Koyukuk River, Alaska, over the period 2016-2022. The data are used in the paper: “Geyman, E., Douglas, M., Avouac, J.-P. and Lamb, M. Permafrost slows Arctic riverbank erosion, in review (2024).” The dataset contains two sets of measurements: (1) riverbank displacement estimated from Sentinel-2 optical satellite imagery (10 meter (m) resolution) over the period 30-Aug-2016 to 13-Jul-2022, and (2) riverbank displacement estimated from Planet optical satellite imagery (3 m resolution) over the period 31-Aug-2016 to 01-Oct-2022. The first dataset is based on comparison of Sentinel-2 satellite acquisitions from the start and end of the study interval. The second dataset analyzes 65 PlanetScope image mosaics (for an average of 9 observations per year). The Matlab code used to analyze the Sentinel-2 and PlanetScope imagery, as well as to process the sub-seasonal displacement estimates, is included in the file “Code.zip”. 

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). 

Carbonate mud represents one of the most important geochemical archives for reconstructing ancient climatic, environmental, and evolutionary change from the rock record. Mud also represents a major sink in the global carbon cycle. Yet, there remains no consensus about how and where carbonate mud is formed. Here, we present stable isotope and trace-element data from carbonate constituents in the Bahamas, including ooids, corals, foraminifera, and algae. We use geochemical fingerprinting to demonstrate that carbonate mud cannot be sourced from the abrasion and mixture of any combination of these macroscopic grains. Instead, an inverse Bayesian mixing model requires the presence of an additional aragonite source. We posit that this source represents a direct seawater precipitate. We use geological and geochemical data to show that “whitings” are unlikely to be the dominant source of this precipitate and, instead, present a model for mud precipitation on the bank margins that can explain the geographical distribution, clumped-isotope thermometry, and stable isotope signature of carbonate mud. Next, we address the enigma of why mud and ooids are so abundant in the Bahamas, yet so rare in the rest of the world: Mediterranean outflow feeds the Bahamas with the most alkaline waters in the modern ocean (>99.7th-percentile). Such high alkalinity appears to be a prerequisite for the nonskeletal carbonate factory because, when Mediterranean outflow was reduced in the Miocene, Bahamian carbonate export ceased for 3-million-years. Finally, we show how shutting off and turning on the shallow carbonate factory can send ripples through the global climate system.