# Yukon-Kuskokwim Delta, Alaska, Last millennium lake sediment macrocharcoal, biomarker, and geochemical data #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # Template Version 4.0 # Encoding: UTF-8 # NOTE: Please cite original publication, NOAA Landing Page URL, dataset and publication DOIs (where available), and date accessed when using downloaded data. # If there is no publication information, please cite investigator, study title, NOAA Landing Page URL, and date accessed. # # Description/Documentation lines begin with '#' followed by a space # Data lines have no '#' # # NOAA_Landing_Page: https://www.ncei.noaa.gov/access/paleo-search/study/36776 # Landing_Page_Description: NOAA Landing Page of this file's parent study, which includes all study metadata. # # Study_Level_JSON_Metadata: https://www.ncei.noaa.gov/pub/data/metadata/published/paleo/json/noaa-36776.json # Study_Level_JSON_Description: JSON metadata of this data file's parent study, which includes all study metadata. # # Data_Type: Paleolimnology # # Dataset_DOI: 10.25921/swff-7y78 # # Science_Keywords: Air temperature reconstruction, Arctic, Other reconstruction #--------------------------------------- # Resource_Links # # Data_Download_Resource: https://www.ncei.noaa.gov/pub/data/paleo/paleolimnology/alaska/sae-lim2022/sae-lim2019-ykdelta-brgdgt.txt # Data_Download_Description: NOAA Template File; Biomarker Data # #--------------------------------------- # Contribution_Date # Date: 2022-09-10 #--------------------------------------- # File_Last_Modified_Date # Date: 2022-09-10 #--------------------------------------- # Title # Study_Name: Yukon-Kuskokwim Delta, Alaska, Last millennium lake sediment macrocharcoal, biomarker, and geochemical data #--------------------------------------- # Investigators # Investigators: Sae-Lim, Jarunetr; Russell, James; Vachula, Richard; Holmes, Robert; Mann, Paul; Schade, John; Natali, Susan #--------------------------------------- # Description_Notes_and_Keywords # Description: # Provided Keywords: Arctic, Alaska, Paleofire, late Holocene, GDGTs, charcoal #--------------------------------------- # Publication # Authors: Sae-Lim, J., Russell, J.M., Vachula, R.S., Holmes, R.M., Mann, P.J., Schade, J.D., and Natali, S.M. # Published_Date_or_Year: 2019 # Published_Title: Temperature-controlled tundra fire severity and frequency during the last millennium in the Yukon-Kuskokwim Delta, Alaska # Journal_Name: The Holocene # Volume: 29 # Edition: # Issue: 7 # Pages: 1223-1233 # Report_Number: # DOI: 10.1177/0959683619838036 # Online_Resource: https://journals.sagepub.com/doi/10.1177/0959683619838036 # Full_Citation: # Abstract: Wildfire is an important disturbance to Arctic tundra ecosystems. In the coming decades, tundra fire frequency, intensity, and extent are projected to increase because of anthropogenic climate change. To more accurately predict the effects of climate change on tundra fire regimes, it is critical to have detailed knowledge of the natural frequency and extent of past wildfires and how they responded to past climate variability. We present analyses of fire frequency and temperature from a lake sediment core from the Yukon-Kuskokwim (YK) Delta. Our ca. 1000 macroscopic charcoal record shows more frequent but possibly less severe tundra fires during the first half of the last millennium, whereas less frequent, possibly more severe fires characterize the latter half. Our temperature reconstruction, based on distributional changes of branched glycerol dialkyl glycerol tetraethers (brGDGTs), shows slightly warmer conditions from ca. AD 1000 to 1500, and cooler conditions thereafter (ca. AD 1500 to 2000), suggesting that fire frequency increases when climate is relatively warmer in this region. When wildfires occur more frequently, fire severity may decrease because of limited biomass (fuel source) accumulating between fires. The data suggest that tundra ecosystems are highly sensitive to climate change, and that a warmer climate, which is predicted to develop in the near future, will result in more frequent tundra wildfires. #--------------------------------------- # Funding_Agency # Funding_Agency_Name: National Science Foundation # Grant: NSF-1624927 #--------------------------------------- # Funding_Agency # Funding_Agency_Name: Institute at Brown for Environment and Society # Grant: Voss Undergraduate Research Fellowship in Environmental Science and Communication #--------------------------------------- # Site_Information # Site_Name: Lake Lin (unofficial name) # Location: Alaska # Northernmost_Latitude: 61.28721 # Southernmost_Latitude: 61.28721 # Easternmost_Longitude: -163.26052 # Westernmost_Longitude: -163.26052 # Elevation_m: 2.43 #--------------------------------------- # Data_Collection # Collection_Name: YKDelta-brGDGT # First_Year: 948 # Last_Year: -65 # Time_Unit: calendar year before present # Core_Length_m: 0.515 # Parameter_Keywords: carbon isotopes, geochemistry # Notes: #--------------------------------------- # Chronology_Information # Chronology: # Radiocarbon ages from Lake Lin. Present is AD 1950. # Sample# NOSAMS sample code # Depth.Top Corrected depth top of sample interval (cm) # Depth.Bot Corrected depth bottom of sample interval (cm) # Material Material measured # 14C.age 14C AMS age (year BP) # 14C.age.1SD 14C AMS age 1-sigma (year BP) # 14C.calib Calibrated age (cal year AD) # 14C.calib.1SD Calibrated age 1-sigma (cal year AD) # rejected Rejected sample # # Sample# Depth.Top Depth.Bot Material 14C.age 14C.age.1SD 14C.calib 14C.calib.1SD rejected # 148150 12.4448 12.752 Twigs 335 15 1579 22 NaN # 148149 24.53 25.15 Leaves 2490 20 -618 78 Yes # 148148 38.5925 38.921 Twigs >modern N/A >1950 NaN Yes # 148147 47.7855 48.45 Small parts of plants 915 20 1101 63 NaN # #--------------------------------------- # Variables # PaST_Thesaurus_Download_Resource: https://www.ncei.noaa.gov/access/paleo-search/skos/past-thesaurus.rdf # PaST_Thesaurus_Download_Description: Paleoenvironmental Standard Terms (PaST) Thesaurus terms, definitions, and relationships in SKOS format. # # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-var components: what, material, error, units, seasonality, data type, detail, method, C or N for Character or Numeric data) # ## Depth_cm Depth,,,centimeter,,paleolimnology; climate reconstructions,,,N,corrected depth (see Sae-Lim et al. 2019) ## Age age,,,calendar year before present,,paleolimnology; climate reconstructions,,,N,calibrated age; modeled age of sediment ## f1050_III branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-III ## f1050_III_prime branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-III_prime ## f1048_IIIb branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIIb ## f1048_IIIb_prime branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIIb_prime ## f1046_IIIc branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIIc ## f1046_IIIc_prime branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIIc_prime ## f1036_II branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIa ## f1036_II_prime branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIa_prime ## f1034_IIb branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIb ## f1034_IIb_prime branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIb_prime ## f1032_IIc branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIc ## f1032_IIc_prime branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-IIc_prime ## f1022_I branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-I ## f1020_Ib branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-Ib ## f1018_Ic branched glycerol dialkyl glycerol tetraether,,,fraction,,paleolimnology,,,N,fraction of GDGT-Ic ## MAAT_MBT5Me air temperature,glycerol dialkyl glycerol tetraether index,,degree Celsius,annual,paleolimnology; climate reconstructions,,,N,based on MBT_prime5Me; Calculated using brGDGT fractional abundances in De Jonge et al. (2014) calibration ## MAAT_INDEX_1 air temperature,glycerol dialkyl glycerol tetraether index,,degree Celsius,annual,paleolimnology; climate reconstructions,,,N,based on Index1; Calculated using brGDGT fractional abundances in De Jonge et al. (2014) calibration ## MATmr air temperature,glycerol dialkyl glycerol tetraether index,,degree Celsius,annual,paleolimnology; climate reconstructions,,,N,based on Multiple linear regression; Calculated using brGDGT fractional abundances in De Jonge et al. (2014) calibration ## pH_CBT5Me pH,soil; glycerol dialkyl glycerol tetraether index,,dimensionless,,paleolimnology; climate reconstructions,,,N,based on CBT_prime5Me; Calculated using brGDGT fractional abundances in De Jonge et al. (2014) calibration ## pH_CBT pH,soil; glycerol dialkyl glycerol tetraether index,,dimensionless,,paleolimnology; climate reconstructions,,,N,based on CBT_prime; Calculated using brGDGT fractional abundances in De Jonge et al. (2014) calibration #------------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: -999 Depth_cm Age f1050_III f1050_III_prime f1048_IIIb f1048_IIIb_prime f1046_IIIc f1046_IIIc_prime f1036_II f1036_II_prime f1034_IIb f1034_IIb_prime f1032_IIc f1032_IIc_prime f1022_I f1020_Ib f1018_Ic MAAT_MBT5Me MAAT_INDEX_1 MATmr pH_CBT5Me pH_CBT 0.86 -65 0.248 0.014 0.001 0.000 0.000 0.000 0.466 0.007 0.008 0.008 0.003 0 0.232 0.011 0.002 -0.612 -1.461 -1.89 5.128 4.797 1.42 -48 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 2.07 -37 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 2.73 -24 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 3.59 -10 0.234 0.012 0.001 0.001 0.000 0.000 0.452 0.033 0.008 0.008 0.003 0 0.237 0.011 0.002 -0.247 -0.53 -1.404 5.121 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