# Lake Lyadhej-To Air and Lake Surface Temperature Reconstructions during the last 11 ka #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program # National Centers for Environmental Information (NCEI) #----------------------------------------------------------------------- # Template Version 3.0 # Encoding: UTF-8 # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/30652 # Online_Resource_Description: NOAA Landing Page # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/27330 # Online_Resource_Description: NOAA Landing Page for Temperature-12k Database # # Online_Resource: https://www.ncei.noaa.gov/pub/data/paleo/reconstructions/climate12k/temperature/version1.0.0/Temp12k_directory_NOAA_files/LakeLyadhej-To.Andreev.2005.txt # Online_Resource_Description: NOAA location of the template # # Online_Resource: https://www.ncei.noaa.gov/pub/data/paleo/reconstructions/climate12k/temperature/version1.0.0/Temp12k_directory_LiPD_files/LakeLyadhej-To.Andreev.2005.lpd # Online_Resource_Description: Linked Paleo Data (LiPD) formatted file containing metadata and data related to this file, for version 1.0.0 of this dataset. # # Original_Source_URL: # Description/Documentation lines begin with # # Data lines have no # # # Data_Type: Climate Reconstructions # Parameter_Keywords: air temperature # Dataset_DOI: # #------------------ # Contribution_Date # Date: 2020-04-15 #------------------ # File_Last_Modified_Date # Date: 2020-05-16 #------------------ # Title # Study_Name: Lake Lyadhej-To Air and Lake Surface Temperature Reconstructions during the last 11 ka #------------------ # Investigators # Investigators: Andreev, Andrei A.; Tarasov, Pavel E.; Ilyashuk, Boris P.; Ilyashuk, Elena A.; Cremer, Holger; Hermichen, Wolf-Dieter; Wischer, Frank; Hubberten, Hans-Wolfgang #------------------ # Description_Notes_and_Keywords # Description: This dataset was contributed as part of the Temperature-12k project (https://doi.org/10.25921/4RY2-G808). Data were contributed to the project from the original data generators, who are listed in the Investigator field of this template file. Additional notes regarding the use of these data in the Temperature-12k project can be found in the LiPD file listed as an Online_Resource of this template file. #------------------ # Publication # Authors: Andreev, Andrei A.; Tarasov, Pavel E.; Ilyashuk, Boris P.; Ilyashuk, Elena A.; Cremer, Holger; Hermichen, Wolf-Dieter; Wischer, Frank; Hubberten, Hans-Wolfgang # Published_Date_or_Year: 2005 # Published_Title: Holocene environmental history recorded in Lake Lyadhej-To sediments, polar Urals, Russia # Journal_Name: Palaeogeography, Palaeoclimatology, Palaeoecology # Volume: 223 # Edition: # Issue: 3-4 # Pages: 181-203 # Report: # DOI: 10.1016/j.palaeo.2005.04.004 # Online_Resource: # Full_Citation: # Abstract: An 1180-cm long core recovered from Lake Lyadhej-To (68°15′ N, 65°45′ E, 150 m a.s.l.) at the NW rim of the Polar Urals Mountains reflects the Holocene environmental history from ca. 11,000 cal. yr BP. Pollen assemblages from the diamicton (ca. 11,000–10,700 cal. yr BP) are dominated by Pre-Quaternary spores and redeposited Pinaceae pollen, pointing to a high terrestrial input. Turbid and nutrient-poor conditions existed in the lake ca. 10,700–10,550 cal. yr BP. The chironomid-inferred reconstructions suggest that mean July temperature increased rapidly from 10.0 to 11.8 °C during this period. Sparse, treeless vegetation dominated on the disturbed and denuded soils in the catchment area. A distinct dominance of planktonic diatoms ca. 10,500–8800 cal. yr BP points to the lowest lake-ice coverage, the longest growing season and the highest bioproductivity during the lake history. Birch forest with some shrub alder grew around the lake reflecting the warmest climate conditions during the Holocene. Mean July temperature was likely 11–13 °C and annual precipitation—400–500 mm. The period ca. 8800–5500 cal. yr BP is characterized by a gradual deterioration of environmental conditions in the lake and lake catchment. The pollen- and chironomid-inferred temperatures reflect a warm period (ca. 6500–6000 cal. BP) with a mean July temperature at least 1–2 °C higher than today. Birch forests disappeared from the lake vicinity after 6000 cal. yr BP. The vegetation in the Lyadhej-To region became similar to the modern one. Shrub (Betula nana, Salix) and herb tundra have dominated the lake catchment since ca. 5500 cal. yr BP. All proxies suggest rather harsh environmental conditions. Diatom assemblages reflect relatively short growing seasons and a longer persistence of lake-ice ca. 5500–2500 cal. yr BP. Pollen-based climate reconstructions suggest significant cooling between ca. 5500 and 3500 cal. yr BP with a mean July temperature 8–10 °C and annual precipitation—300–400 mm. The bioproductivity in the lake remained low after 2500 cal. yr BP, but biogeochemical proxies reflect a higher terrestrial influx. Changes in the diatom content may indicate warmer water temperatures and a reduced ice cover on the lake. However, chironomid-based reconstructions reflect a period with minimal temperatures during the lake history. #------------------ # Publication # Authors: Kaufman, D., N. McKay, C. Routson, M. Erb, B. Davis, O. Heiri, S. Jaccard, J. Tierney, C. Dätwyler, Y. Axford, T. Brussel, O. Cartapanis, B. Chase, A. Dawson, A. de Vernal, S. Engels, L. Jonkers, J. Marsicek, P. Moffa-Sánchez, C. Morrill, A. Orsi, K. Rehfeld, K. Saunders, P. S. Sommer, E. Thomas, M. Tonello, M. Tóth, R. Vachula, A. Andreev, S. Bertrand, B. Biskaborn, M. Bringué, S. Brooks, M. Caniupán, M. Chevalier, L. Cwynar, J. Emile-Geay, J. Fegyveresi, A. Feurdean, W. Finsinger, M-C. Fortin, L. Foster, M. Fox, K. Gajewski, M. Grosjean, S. Hausmann, M. Heinrichs, N. Holmes, B. Ilyashuk, E. Ilyashuk, S. Juggins, D. Khider, K. Koinig, P. Langdon, I. Larocque-Tobler, J. Li, A. Lotter, T. Luoto, A. Mackay, E. Magyari, S. Malevich, B. Mark, J. Massaferro, V. Montade, L. Nazarova, E. Novenko, P. Paril, E. Pearson, M. Peros, R. Pienitz, M. Plóciennik, D. Porinchu, A. Potito, A. Rees, S. Reinemann, S. Roberts, N. Rolland, S. Salonen, A. Self, H. Seppä, S. Shala, J-M. St-Jacques, B. Stenni, L. Syrykh, P. Tarrats, K. Taylor, V. van den Bos, G. Velle, E. Wahl, I. Walker, J. Wilmshurst, E. Zhang, S. Zhilich # Published_Date_or_Year: 2020-04-14 # Published_Title: A global database of Holocene paleotemperature records # Journal_Name: Scientific Data # Volume: 7 # Edition: 115 # Issue: # Pages: # Report_Number: # DOI: 10.1038/s41597-020-0445-3 # Online_Resource: https://www.nature.com/articles/s41597-020-0445-3 # Full_Citation: # Abstract: A comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cut-off values slackened in data-sparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. The multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format. #------------------ # Funding_Agency # Funding_Agency_Name: # Grant: #------------------ # Site_Information # Site_Name: Lyadhej-To # Location: Europe>Eastern Europe>Russia # Country: Russia # Northernmost_Latitude: 68.26 # Southernmost_Latitude: 68.26 # Easternmost_Longitude: 65.8 # Westernmost_Longitude: 65.8 # Elevation: 150 #------------------ # Data_Collection # Collection_Name: LakeLyadhej-To.Andreev.2005 # Earliest_Year: 10888.064 # Most_Recent_Year: 68.889 # Time_Unit: cal yr BP # Core_Length: # Notes: #------------------ # Species # Species_Name: # Species_Code: # Common_Name: #------------------ # Chronology_Information # Chronology: # OriginalDateID depth_top depth_bottom age_type age uncertainty_old uncertainty_young IncludeYN material age_type-1 # nan 0.0 0.0 Core top -48.0 nan nan Y nan core top # KIA-10040 8.0 10.0 C14 Uncalibrated 690.0 720.0 660.0 Y Non-identified macrofossils C14 # KIA-8915 98.0 100.0 C14 Uncalibrated 2460.0 2500.0 2420.0 Y Non-identified macrofossils C14 # KIA-10041 200.0 202.0 C14 Uncalibrated 5135.0 5195.0 5075.0 Y Non-identified macrofossils C14 # KIA-8916 298.0 300.0 C14 Uncalibrated 6730.0 6800.0 6660.0 Y Non-identified macrofossils C14 # KIA-8920 398.0 400.0 C14 Uncalibrated 8550.0 8650.0 8450.0 Y Non-identified macrofossils C14 # KIA-8917 500.0 502.0 C14 Uncalibrated 9230.0 9320.0 9140.0 Y Non-identified macrofossils C14 # KIA-12131 596.0 598.0 C14 Uncalibrated 10780.0 10920.0 10640.0 N Non-identified macrofossils C14 # KIA-8759 652.0 654.0 C14 Uncalibrated 11230.0 11380.0 11080.0 N Non-identified macrofossils C14 # KIA-8760 670.0 672.0 C14 Uncalibrated 14210.0 14300.0 14120.0 N Non-identified macrofossils C14 # KIA-8761 717.0 719.0 C14 Uncalibrated 9600.0 9660.0 9540.0 N Shrub twig C14 # KIA-12132 734.0 736.0 C14 Uncalibrated 10940.0 11030.0 10850.0 N Non-identified macrofossils C14 # KIA-12133 793.0 795.0 C14 Uncalibrated 11850.0 11930.0 11770.0 N Non-identified macrofossils C14 # KIA-12134 993.0 995.0 C14 Uncalibrated 9880.0 9930.0 9830.0 N Non-identified macrofossils C14 # KIA-12135 1034.0 1036.0 C14 Uncalibrated 9490.0 9550.0 9430.0 Y Moss remains C14 #------------------ # Variables # # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ## depth depth,,,centimeter,,insect;paleolimnology;climate reconstructions,,,N, ## age age,,,calendar year before present,,insect;paleolimnology;climate reconstructions,,,N, ## temperature lake surface temperature,midge assemblage,,degree Celsius,Jul,insect;paleolimnology;climate reconstructions,,,N,100-lake training set from Sweden (Larocque et al. 2001); WAPLS ## uncertaintyHigh lake surface temperature,midge assemblage,unspecified error upper bound,degree Celsius,Jul,insect;paleolimnology;climate reconstructions,,,N, ## uncertaintyLow lake surface temperature,midge assemblage,unspecified error lower bound,degree Celsius,Jul,insect;paleolimnology;climate reconstructions,,,N, ## ReliabIeYN1 notes,,,,,insect;paleolimnology;climate reconstructions,,,C,Data are reliable (Yes or No) ## Commentregardingreliability1 notes,,,,,insect;paleolimnology;climate reconstructions,,,C,comment regarding reliability # #------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: nan # depth age temperature uncertaintyHigh uncertaintyLow ReliabIeYN1 Commentregardingreliability1 1.0 68.889 8.15 9.526 6.774 Y nan 5.0 344.444 9.168 10.548 7.788 Y nan 11.0 620.0 8.405 9.802 7.008 Y very poor' fit 19.0 834.444 9.206 10.574 7.838 Y nan 27.0 963.111 8.388 9.797 6.979 Y very poor' fit 33.0 1134.667 7.997 9.371 6.624 Y very poor' fit 43.0 1349.111 8.724 10.134 7.315 Y very poor' fit 51.0 1520.667 8.477 9.895 7.06 Y very poor' fit 57.0 1649.333 8.463 9.867 7.06 Y very poor' fit 67.0 1863.778 8.751 10.126 7.376 Y nan 73.0 1992.444 8.699 10.08 7.318 Y nan 87.0 2292.667 8.542 9.974 7.11 Y very poor' fit 95.0 2464.222 8.895 10.257 7.533 Y nan 111.0 2940.588 9.164 10.509 7.818 Y nan 121.0 3266.078 8.608 9.958 7.258 Y very poor' fit 127.0 3461.373 8.678 10.042 7.314 Y nan 135.0 3721.765 9.973 11.28 8.667 Y nan 147.0 4112.353 9.093 10.446 7.74 Y nan 151.0 4242.549 8.024 9.427 6.621 Y very poor' fit 163.0 4633.137 8.476 9.872 7.08 Y nan 171.0 4893.529 8.877 10.188 7.565 Y nan 177.0 5088.824 9.765 11.102 8.427 Y nan 187.0 5414.314 9.201 10.555 7.847 Y nan 195.0 5674.706 8.466 9.813 7.119 Y very poor' fit 207.0 5974.694 9.579 10.896 8.263 Y nan 219.0 6184.082 10.154 11.503 8.804 Y nan 227.0 6323.673 10.449 11.773 9.125 Y nan 239.0 6498.163 9.569 10.933 8.205 Y nan 247.0 6672.653 8.867 10.228 7.507 Y nan 255.0 6812.245 9.49 10.836 8.144 Y nan 263.0 6951.837 9.521 10.86 8.182 Y nan 279.0 7231.021 9.516 10.846 8.186 Y nan 287.0 7370.612 9.684 11.015 8.354 Y nan 295.0 7510.204 10.368 11.647 9.089 Y nan 305.0 7696.4 9.8 11.092 8.508 Y nan 315.0 7890.4 10.601 11.883 9.32 Y nan 327.0 8123.2 9.507 10.811 8.203 Y nan 343.0 8433.6 10.041 11.315 8.767 Y nan 351.0 8588.8 10.794 12.093 9.495 Y nan 363.0 8821.6 10.654 11.947 9.361 Y nan 371.0 8976.8 11.276 12.585 9.966 Y nan 379.0 9132.0 10.565 11.855 9.275 Y nan 391.0 9364.8 10.904 12.186 9.623 Y nan 407.0 9592.941 11.163 12.464 9.863 Y nan 415.0 9665.883 11.419 12.712 10.126 Y nan 431.0 9811.765 11.427 12.731 10.124 Y nan 447.0 9957.647 11.63 12.928 10.331 Y nan 455.0 10030.588 11.272 12.54 10.005 Y nan 463.0 10103.529 11.151 12.437 9.864 Y nan 475.0 10212.941 11.893 13.191 10.596 Y nan 489.0 10340.588 9.691 11.009 8.372 Y nan 513.0 10477.097 11.602 12.861 10.342 Y nan 545.0 10549.354 11.669 12.954 10.383 Y nan 569.0 10603.549 11.638 12.926 10.349 Y nan 599.0 10671.29 12.461 13.757 11.165 Y nan 623.0 10725.483 11.909 13.178 10.64 Y nan 645.0 10775.161 10.387 11.691 9.083 Y nan 663.0 10815.807 9.212 10.575 7.849 Y nan 681.0 10856.451 11.265 12.895 9.634 Y very poor' fit 695.0 10888.064 10.02 11.448 8.592 Y very poor' fit