# Northeastern USA Little Ice Age Temperature and Precipitation Reconstructions #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program # National Centers for Environmental Information (NCEI) #----------------------------------------------------------------------- # Template Version 2.0 # 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/6221 # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/pollen/recons/liadata.txt # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/pollen/recons/dark1988.txt # # Original_Source_URL: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstructions # # Parameter_Keywords: air temperature, precipitation #-------------------- # Contribution_Date # Date: 1993-01-04 #-------------------- # Title # Study_Name: Northeastern USA Little Ice Age Temperature and Precipitation Reconstructions #-------------------- # Investigators # Investigators: Gajewski, K. #-------------------- # Description_and_Notes # Description: Mean summer (JJA) temperatures and total annual precipitation for the past 2000 years # reconstructed from pollen from lakes with laminated sediments. The laminations ensure a more precise # time control than normally obtained from radiocarbon. #-------------------- # Publication # Authors: K. Gajewski # Published_Date_or_Year: 1988-05-01 # Published_Title: Late holocene climate changes in eastern North America estimated from pollen data # Journal_Name: Quaternary Research # Volume: 29 # Edition: # Issue: 3 # Pages: 255-262 # Report_Number: # DOI: 10.1016/0033-5894(88)90034-8 # Online_Resource: http://www.sciencedirect.com/science/article/pii/0033589488900348 # Full_Citation: # Abstract: Well-dated pollen profiles from six sites from Maine to Minnesota record vegetation changes indicative of summer temperature and annual precipitation variations over the past 2000 yr. Laminations in the sediment provide accurate time control. Multiple regression techniques were used to calculate calibration functions from a spatial network of modern pollen and climate data. When applied to the six pollen diagrams, these calibration functions yielded estimates that show a long-term trend toward lower summer temperature. Superimposed on this long-term trend are short-term fluctuations that are frequently in phase at the sites. Departures from the long-term cooling trend are positive around 1500 yr ago (indicating relative warmth) and negative between 200 and 500 yr ago (indicating relative cold). Annual precipitation showed a slight increase at several sites during the past 1000 yr relative to the previous 1000 yr. #------------------ # Publication # Authors: K. Gajewski # Published_Date_or_Year: 1987-01-01 # Published_Title: Climatic impacts on the vegetation of eastern North America during the past 2000 years # Journal_Name: Plant Ecology (formerly Vegetatio) # Volume: 68 # Edition: # Issue: 3 # Pages: 179-190 # Report_Number: # DOI: 10.1007/BF00114719 # Online_Resource: http://link.springer.com/article/10.1007/BF00114719 # Full_Citation: # Abstract: Pollen diagrams from seven lakes with annually laminated sediments sampled at 40-year intervals are analyzed to isolate the climatic effects from other effects on the long-term dynamics of vegetation during the past 1000-2000 years along a transect from Maine to Minnesota. Principal components analysis is used to reduce the dimensionality of the pollen data. The pollen records from all lakes show long-term trends, medium frequency oscillations, and higher frequency fluctuations. The long-term trend is associated with the neoglacial expansion of the boreal forest. The mechanism causing this replacement is a change in frequency of air masses in the area. The medium-frequency oscillations are also associated with climate changes, the most recent of which is the 'Little Ice Age'. The climate-related mechanism causing the medium-frequency changes may be changes in disturbance frequency. The higher frequency fluctuations may also be related to disturbance. This analysis of pollen diagrams into time scales of variation has enabled the separation of climate from other factors affecting vegetation dynamics. By comparing the principal components across a transect of sites it proved possible to interpret the climatic effects on vegetation at most sites and not only at range boundaries and 'sensitive' sites. #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: ATM-8219079, ATM-7926039, ATM-7423041 #------------------ # Site_Information # Site_Name: Dark Lake # Location: North America>United States Of America>Minnesota # Country: United States Of America # Northernmost_Latitude: 45.16 # Southernmost_Latitude: 45.16 # Easternmost_Longitude: -91.28 # Westernmost_Longitude: -91.28 # Elevation: 334 m #------------------ # Data_Collection # Collection_Name: Dark1988LIA # Earliest_Year: 930 # Most_Recent_Year: 10 # Time_Unit: Cal. Year BP # Core_Length: m # Notes: #------------------ # Chronology_Information # Chronology: # #---------------- # Variables # # Data variables follow are preceded by "##" in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ## age_calBP age, , , calendar years before 1975AD, , , , ,N ## temp-JJA surface temperature, , , Deg C, June-July-August, climate reconstructions, , ,N ## precip precipitation, , , mm, annual, climate reconstructions, , ,N # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # age_calBP temp-JJA precip 10 20.4 812 20 20.4 834 30 20.7 792 40 20.6 793 50 20.5 869 60 20.2 797 70 19.3 785 80 19.7 823 90 19.5 739 100 19.6 769 110 20.4 782 120 19.8 798 130 19.8 853 140 19.9 854 150 19.0 830 160 19.3 825 170 19.3 819 180 19.5 946 190 19.2 809 200 19.6 821 210 19.7 857 246 19.5 792 286 19.5 806 324 19.3 876 364 19.5 859 402 19.9 822 450 20.0 889 491 20.5 913 530 19.8 819 570 19.7 830 610 20.0 840 650 19.8 855 690 20.0 842 730 20.0 883 770 20.0 862 810 20.0 788 850 20.0 821 890 19.7 839 930 19.9 832