Radiocarbon dates of peatland initiation across the northern high latitudes

A compilation of basal dates of peatland initiation across the northern high latitudes, associated metadata including location, age, raw and calibrated radiocarbon ages, and associated references. Includes previously published datasets from sources below as well as 365 new data points

High-latitude Lake Basal Ages and Origins - link to datafile

This dataset is a compilation of 1,207 lake basal ages used to identify spatial and temporal patterns of lake formation across the high northern latitudes. Data was gathered from scientific literature descriptions of lake cores, peat cores underlain by lake sediments, and exposures within the domain of glaciation and permafrost extent during the Last Glacial Maximum. We distinguished eight classes of lake origin. Where not indicated by the author, we sought to determine lake origin from lithology, geological history and site descriptions within the text. Though most records (95%) were radiocarbon dated, we included robust dates obtained by a variety of methods including varve counting, photoluminescence, Pb/Cs, Th/U, wiggle matching and tephrochronology. We reported oldest sample ages in the majority of cases, electing not to utilize basal ages derived from age-depth models extrapolated beyond dated levels due to both their high level of uncertainty and differences between methodologies used to construct each model. We excluded dates from shallow lake cores that clearly did not reach basal lake sediments, or that were collected for the sole purpose of methods development or recent human impact studies. Records that did not include dates from lower-most cored sediments, that suffered from uncorrected reservoir effects (noted by original author) or that contained copious age reversals were also excluded. Some records provided distinct stratigraphic evidence of lake formation that allowed for exact determination of lake basal age, while other lithologies were more ambiguous. To address this uncertainty, we categorized each lake age as "minimum" or "basal" based on interpretation of contextual, geographical and lithological information

Isotopic composition of ground ice, ebullition gases and thermokarst lake water, North America

Thermokarst lakes are thought to have been an important source of methane (CH4) during the last deglaciation when atmospheric CH4 concentrations increased rapidly. Here we demonstrate that meltwater from permafrost ice serves as an H source to CH4 production in thermokarst lakes, allowing for region-specific reconstructions of dD-CH4 emissions from Siberian and North American lakes. dD CH4 reflects regionally varying dD values of precipitation incorporated into ground ice at the time of its formation. Late Pleistocene-aged permafrost ground ice was the dominant H source to CH4 production in primary thermokarst lakes, whereas Holocene-aged permafrost ground ice contributed H to CH4 production in later generation lakes. We found that Alaskan thermokarst lake dD-CH4 was higher (-334 ± 17 per mil) than Siberian lake dD-CH4 (-381 ± 18 per mil). Weighted mean dD CH4 values for Beringian lakes ranged from -385 per mil to -382 per mil over the deglacial period. Bottom-up estimates suggest that Beringian thermokarst lakes contributed 15 ± 4 Tg CH4 /yr to the atmosphere during the Younger Dryas and 25 ± 5 Tg CH4 /yr during the Preboreal period. These estimates are supported by independent, top-down isotope mass balance calculations based on ice core dD-CH4 and d13C-CH4 records. Both approaches suggest that thermokarst lakes and boreal wetlands together were important sources of deglacial CH4

Data set for modeling methane fluxes of Beringian coastal wetlands

For upscaling CH4 flux estimates in Beringia during the past 20,000 years, we collected 231 present-day CH4 fluxes from coastal wetlands in the Northern Hemisphere. We combined our own flux data (27 plot measurements) from the Kenai Peninsula, Alaska with previously published data. Data were compiled from different sources (e.g. Treat et al. 2018; 2021; Poffenbarger et al. 2011; Liikanen et al. 2009; Holmquist et al. 2018; Kuhn et al. 2021). CH4 fluxes from the literature were calculated in g CH4 m-2 yr-1 for the growing season, which we set to 153 days (May to September). Each CH4 data entry was harmonized by classifying it into one of the six wetland types Saltwater, tidal regularly flooded, Temporarily irregularly flooded, Permanently to semi-permanently flooded, Seasonally flooded, Non-tidal saturated, Water-body. This resulted in a stratified pool of CH4 fluxes and allowed a bootstrapping approach to estimate uncertainty in the CH4 fluxes for Beringian coastal wetlands based on the variability of CH4 fluxes associated to the different wetland types. For each of 258 sites, the dataset includes a site description, calculated CH4 flux from this research, wetland type, wetland class, method of CH4 measurement, major vegetation type, site location, the originally published CH4 value ("orig val") in the referenced paper, original units of measurement, citation and persistent identifier for the original data source, and comments. For some of the data points no coordinates information was given in the original publication, therefore the latitude and longitude fields were left blank

Methane flux measurements from coastal wetlands on the Kenai Peninsula

The methane (CH4) flux was measured during a field campaign in August 2021 on the Kenai Peninsula, Alaska. We chose locations in coastal wetlands along transects to cover a gradient from freshwater flooded into tidal, saltwater flooded wetlands. In total, we measured at 27 different locations including saltwater tidal regularly flooded bare grounds, temporarily irregularly flooded, as well as seasonally flooded, vegetated coastal wetlands. Flux measurements were made with a micro-portable LosGatos greenhouse gas analyzer (LosGatos Research) and a light-weight custom-made bucket chamber consisting of non-transparent PVC (diameter = 26 cm, volume ~ 19,000 cm3). We chose this small, lightweight equipment in order to be highly mobile in muddy, shrubby terrain and measure at field sites which were not easy to access. At each site we measured three replicates for 7 to 10 minutes, described the vegetation cover (if present), and measured the chamber and air temperature. The bucket chamber was equipped with a venting tube and a small fan to have well-mixed conditions in the chamber. The CH4 flux (in mg CH4 m-2 h-1) for each replicate measurement was calculated based on the volume and temperature of the bucket chamber, and the ideal gas law. We manually removed the first 30 sec of each measurement, because of potential disturbance while placing the bucket chamber on the site (we did not use pre-installed collars). Fluxes were calculated by applying a linear regression to the CH4 concentration and were given in mg CH4 m-2 h-1. The r squared was used to determine the quality of the linear regression. Fluxes that had a linear regression with a r squared below 0.9 were discarded. However, we did not want to exclude all the near-zero measurements as these indicate important data as well (no CH4 fluxes). Therefore, all measurements, which were below the precision of the greenhouse gas analyzer of 0.5 ppb (~0.44 mg CH4 m-2 h-1, depending on chamber volume) were included in the analysis as zero fluxes. In a final step, we averaged all the replicates from a measurement site in order to have one CH4 flux value per measurement site and calculated the CH4 flux for the growing season of 153 days in g CH4 m-2 yr-1, which served as input data for the bootstrapping of the Beringia coastal wetland CH4 estimation

Modeled timing of flooding for the Beringian shelf for the past 20,000 years

The paleo bathymetry grids (PaleoMIST 1.0 (Gowan et al. 2021) were used to calculate the timing of flooding in the Beringia study region. The resulting GeoTiff (Year of flooding.tif) has a spatial resolution of 5,000 m and each pixel contains the modeled time of flooding (in yrs BP), e.g., when this location was flooded by rising sea levels. PaleoMIST 1.0 is a glacial isostatic adjustment-based paleo topographic reconstruction model that includes relative sea level and paleo bathymetry as an output. The model was created to estimate the sea level contribution of the global ice sheets and is validated using observations of relative sea level change. To estimate the timing of flooding, nine of the PaleoMIST 1.0 raster data sets (20,000 yrs BP to 0 yrs BP, with 2,500 years time steps) were used. In order to estimate the timing of flooding for each pixel, we first calculated the linear increase (or decrease) for each pixel between two sequential PaleoMIST 1.0 grids to establish grids for every 1,000 years. In addition, we calculated the timing of flooding for each pixel, again by assuming a linear transition between two sequential grids. The timing of flooding was then determined as the point in time when a pixel elevation value relative to sea level switched from positive (>0; above sea level) to negative (<0; below sea level). These two procedures allowed us to estimate the area, which became flooded in each 1,000-year time interval from 20,000 yrs BP to present (0 yrs BP). The associated files can be imported, read and viewed with a geographic information system software or through a programming language