# Northeastern United States 11,000 Year Precipitation Reconstructions #----------------------------------------------------------------------- # 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/23072 # Description: NOAA Landing Page # # Online_Resource: https://www1.ncdc.noaa.gov/pub/data/paleo/pages2k/nam2k-hydro-v1-1.0.0/noaa-templates/data-version-1.0.0/BloodPond.Marsicek.2013.txt # Online_Resource_Description: This file. NOAA WDS Paleo formatted metadata and data for version v1-1.0.0 of this dataset. # # Online_Resource: https://www1.ncdc.noaa.gov/pub/data/paleo/pages2k/nam2k-hydro-v1-1.0.0/data-version-1.0.0/BloodPond.Marsicek.2013.lpd # Online_Resource_Description: Linked Paleo Data (LiPD) formatted file containing the same metadata and data as this file, for version v1-1.0.0 of this dataset. # # Original_Source_URL: https://www.ncdc.noaa.gov/paleo/study/6207 # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstruction # Parameter_Keywords: precipitation # Dataset_DOI: # #------------------ # Contribution_Date # Date: 2018-01-08 #------------------ # File_Last_Modified_Date # Modified_Date: 2018-01-08 #------------------ # Title # Study_Name: Northeastern United States 11,000 Year Precipitation Reconstructions #------------------ # Investigators # Investigators: Marsicek, Jeremiah P.; Shuman, Bryan; Brewer, Simon; Foster, David R.; Oswald, W. Wyatt #------------------ # Description_Notes_and_Keywords # Description: Precipitation reconstructions for 5 locations in the northeastern United States over the Holocene. #------------------ # Publication # Authors: Jeremiah P. Marsicek, Bryan Shuman, Simon Brewer, David R. Foster, W. Wyatt Oswald # Published_Date_or_Year: 2013-11-15 # Published_Title: Moisture and temperature changes associated with the mid-Holocene Tsuga decline in the northeastern United States # Journal_Name: Quaternary Science Reviews # Volume: 80 # Edition: # Issue: # Pages: 129-142 # Report: # DOI: 10.1016/j.quascirev.2013.09.001 # Online_Resource: https://www.sciencedirect.com/science/article/pii/S0277379113003375 # Full_Citation: # Abstract: A decline of hemlock (Tsuga) populations at ca 5.5 ka (thousands of calibrated radiocarbon years before 1950 AD) stands out as the most abrupt vegetation change of the Holocene in North America, but remains poorly understood after decades of study. Recent analyses of fossil pollen have revealed a concurrent, abrupt oak (Quercus) decline and increases in the abundance of beech (Fagus) and pine (Pinus) on Cape Cod in eastern Massachusetts, but the replacement of drought-tolerant oaks by moisture-sensitive beeches appears inconsistent with low lake levels in the region at the same time. The oak and beech changes are also limited to coastal areas, and the coastal-inland differences require an explanation. Here, we develop a new lake-level reconstruction from Deep Pond, Cape Cod by using a transect of sediment cores and ground-penetrating radar (GPR) profiles to constrain the past elevations of the sandy, littoral zone of the pond. The reconstruction shows that a series of multi-century episodes of low water coincide with the abrupt hemlock and oak declines, and interrupt subsequent phases of hemlock recovery. The lake-level variations equal precipitation deficits of ~100 mm superimposed on a Holocene long moisture increase of >400 mm. However, because moisture deficits do not easily explain the oak and beech changes, we also evaluate how the climate preferences of the regional vegetation changed over time by matching the fossil pollen assemblages from Deep Pond with their modern equivalents. Reconstructions of the precipitation requirements of the vegetation correlate well even in detail with the lake-level record (r = 0.88 at Deep Pond), and indicate close tracking of effective moisture (precipitation minus evapotranspiration) by the vegetation despite the abrupt species declines, which could have decoupled climate and vegetation trends. Reconstructions of the temperature preferences of the vegetation indicate that coastal sites may have cooled by 0.5-2.5C after ca 5.5 ka, while inland sites warmed by 0.5-1C. The change in coastal temperature preferences agrees with sea surface cooling in the western Atlantic Ocean of >1C. Consequently, the persistence of low hemlock abundance after 5.5 ka in the northeast U.S. may have resulted from oceanic changes that produced multi-century droughts and thus delayed the post-decline recovery of hemlock populations. #------------------ # Publication # Authors: Oswald, W.W., Faison, E.K., Foster, D.R., Doughty, E.D., Hall, B.R., Hansen, B.C.S. # Published_Date_or_Year: 2007 # Published_Title: # Journal_Name: # Volume: # Edition: # Issue: # Pages: # Report: # DOI: 10.1111/j.1365-2699.2006.016 # Online_Resource: # Full_Citation: # Abstract: #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: DEB-0816731, DEB-0815036 #------------------ # Site_Information # Site_Name: Blood Pond # Location: North America>United States Of America>Massachusetts # Country: United States Of America # Northernmost_Latitude: 42.08 # Southernmost_Latitude: 42.08 # Easternmost_Longitude: -71.962 # Westernmost_Longitude: -71.962 # Elevation: 214 #------------------ # Data_Collection # Collection_Name: BloodPond.Marsicek.2013 # Earliest_Year: 11000.0 # Most_Recent_Year: 0.0 # Time_Unit: BP # Core_Length: # Notes: #------------------ # Chronology: #------------------ # Variables # # Data variables follow that are preceded by "##" in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components # ## age_CE age, , , year CE, , , , ,N, ## precip Precipitation, ,,mm/yr, annual, climate reconstruction, ,,N, ## age_calBP age, , , calendar years before present, , , , ,N, # #------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header) # Missing_Values: nan age_CE precip age_calBP 1950.0 1164.746 0 1900.0 1120.682 50 1850.0 1075.049 100 1800.0 1065.537 150 1750.0 1087.649 200 1700.0 1218.57 250 1650.0 1221.116 300 1600.0 1223.661 350 1550.0 1226.207 400 1500.0 1221.383 450 1450.0 1209.757 500 1400.0 1198.131 550 1350.0 1186.505 600 1300.0 1155.774 650 1250.0 1119.011 700 1200.0 1082.248 750 1150.0 1074.801 800 1100.0 1084.434 850 1050.0 1072.692 900 1000.0 1043.862 950 950.0 1036.084 1000 900.0 1051.153 1050 850.0 1047.069 1100 800.0 1014.66 1150 750.0 1007.403 1200 700.0 1051.853 1250 650.0 1086.119 1300 600.0 1090.007 1350 550.0 1093.896 1400 500.0 1077.172 1450 450.0 1054.953 1500 400.0 1046.057 1550 350.0 1059.648 1600 300.0 1073.24 1650 250.0 1086.888 1700 200.0 1100.539 1750 150.0 1108.413 1800 100.0 1111.308 1850 50.0 1117.791 1900 0.0 1150.647 1950 -50.0 1171.344 2000 -100.0 1190.854 2050 -150.0 1210.363 2100 -200.0 1229.872 2150 -250.0 1232.722 2200 -300.0 1232.39 2250 -350.0 1232.059 2300 -400.0 1231.727 2350 -450.0 1234.104 2400 -500.0 1238.878 2450 -550.0 1243.652 2500 -600.0 1248.426 2550 -650.0 1252.525 2600 -700.0 1254.249 2650 -750.0 1255.972 2700 -800.0 1257.696 2750 -850.0 1259.42 2800 -900.0 1215.08 2850 -950.0 1166.313 2900 -1000.0 1117.546 2950 -1050.0 1068.779 3000 -1100.0 1057.548 3050 -1150.0 1071.007 3100 -1200.0 1095.032 3150 -1250.0 1132.04 3200 -1300.0 1169.048 3250 -1350.0 1206.056 3300 -1400.0 1194.374 3350 -1450.0 1176.535 3400 -1500.0 1162.89 3450 -1550.0 1085.708 3500 -1600.0 1087.362 3550 -1650.0 1089.327 3600 -1700.0 1076.061 3650 -1750.0 1071.256 3700 -1800.0 1085.623 3750 -1850.0 1099.989 3800 -1900.0 1097.643 3850 -1950.0 1094.77 3900 -2000.0 1071.207 3950 -2050.0 1035.627 4000 -2100.0 1007.194 4050 -2150.0 995.775 4100 -2200.0 984.357 4150 -2250.0 973.911 4200 -2300.0 964.205 4250 -2350.0 954.498 4300 -2400.0 973.375 4350 -2450.0 1003.745 4400 -2500.0 1034.116 4450 -2550.0 1021.944 4500 -2600.0 1002.731 4550 -2650.0 983.606 4600 -2700.0 995.864 4650 -2750.0 1008.122 4700 -2800.0 1021.171 4750 -2850.0 1038.783 4800 -2900.0 1056.395 4850 -2950.0 1068.711 4900 -3000.0 1068.211 4950 -3050.0 1067.71 5000 -3100.0 1086.996 5050 -3150.0 1131.753 5100 -3200.0 1156.677 5150 -3250.0 1132.123 5200 -3300.0 1141.355 5250 -3350.0 1150.588 5300 -3400.0 1155.966 5350 -3450.0 1148.303 5400 -3500.0 1140.639 5450 -3550.0 1132.586 5500 -3600.0 1115.331 5550 -3650.0 1098.076 5600 -3700.0 1080.821 5650 -3750.0 1094.113 5700 -3800.0 1112.668 5750 -3850.0 1131.222 5800 -3900.0 1090.719 5850 -3950.0 1027.315 5900 -4000.0 1051.606 5950 -4050.0 1062.358 6000 -4100.0 1058.324 6050 -4150.0 1045.334 6100 -4200.0 1040.168 6150 -4250.0 1056.974 6200 -4300.0 1073.781 6250 -4350.0 1090.484 6300 -4400.0 1106.282 6350 -4450.0 1122.08 6400 -4500.0 1137.878 6450 -4550.0 1133.422 6500 -4600.0 1120.029 6550 -4650.0 1106.637 6600 -4700.0 1093.381 6650 -4750.0 1082.037 6700 -4800.0 1070.693 6750 -4850.0 1059.348 6800 -4900.0 1060.633 6850 -4950.0 1077.965 6900 -5000.0 1075.586 6950 -5050.0 1061.485 7000 -5100.0 1080.203 7050 -5150.0 1106.43 7100 -5200.0 1112.103 7150 -5250.0 1115.602 7200 -5300.0 1109.654 7250 -5350.0 1103.706 7300 -5400.0 1097.759 7350 -5450.0 1091.811 7400 -5500.0 1085.863 7450 -5550.0 1079.915 7500 -5600.0 1073.967 7550 -5650.0 1102.253 7600 -5700.0 1129.04 7650 -5750.0 1126.991 7700 -5800.0 1122.979 7750 -5850.0 1114.531 7800 -5900.0 1106.082 7850 -5950.0 1088.832 7900 -6000.0 1060.786 7950 -6050.0 1044.047 8000 -6100.0 1033.1 8050 -6150.0 1018.455 8100 -6200.0 1003.273 8150 -6250.0 988.092 8200 -6300.0 999.546 8250 -6350.0 1073.855 8300 -6400.0 1082.915 8350 -6450.0 1029.22 8400 -6500.0 1048.778 8450 -6550.0 1096.56 8500 -6600.0 1114.864 8550 -6650.0 1123.671 8600 -6700.0 1089.153 8650 -6750.0 1054.634 8700 -6800.0 1020.116 8750 -6850.0 1000.523 8800 -6900.0 992.173 8850 -6950.0 983.824 8900 -7000.0 975.474 8950 -7050.0 983.217 9000 -7100.0 991.047 9050 -7150.0 998.878 9100 -7200.0 1001.037 9150 -7250.0 995.326 9200 -7300.0 989.616 9250 -7350.0 943.812 9300 -7400.0 867.388 9350 -7450.0 818.324 9400 -7500.0 830.47 9450 -7550.0 842.238 9500 -7600.0 846.92 9550 -7650.0 843.553 9600 -7700.0 798.079 9650 -7750.0 949.281 9700 -7800.0 999.704 9750 -7850.0 870.897 9800 -7900.0 783.034 9850 -7950.0 802.266 9900 -8000.0 820.77 9950 -8050.0 800.588 10000 -8100.0 780.407 10050 -8150.0 775.107 10100 -8200.0 796.421 10150 -8250.0 813.7 10200 -8300.0 817.458 10250 -8350.0 883.612 10300 -8400.0 817.443 10350 -8450.0 804.714 10400 -8500.0 810.412 10450 -8550.0 816.85 10500 -8600.0 818.321 10550 -8650.0 816.379 10600 -8700.0 808.138 10650 -8750.0 813.532 10700 -8800.0 811.37 10750 -8850.0 805.987 10800 -8900.0 804.315 10850 -8950.0 802.663 10900 -9000.0 801.469 10950 -9050.0 784.226 11000