# Waccamaw/Savannah River Wetlands Late Holocene Multiproxy Sediment Data #----------------------------------------------------------------------- # 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/26690 # Description: NOAA Landing Page # Online_Resource: https://www1.ncdc.noaa.gov/pub/data/paleo/paleolimnology/northamerica/usa/georgia/savannah2017pollen12-12-11-1.txt # Description: NOAA location of the template # # Original_Source_URL: # Description: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Paleolimnology # # Dataset DOI: # # Parameter_Keywords: geochemistry, physical properties, population abundance #-------------------- # Contribution_Date # Date: 2019-05-01 #-------------------- # File_Last_Modified_Date # Date: 2019-05-01 #-------------------- # Title # Study_Name: Waccamaw/Savannah River Wetlands Late Holocene Multiproxy Sediment Data #-------------------- # Investigators # Investigators: Jones, M.C.; Bernhardt, C.E.; Krauss, K.W.; Noe, G.B. #-------------------- # Description_Notes_and_Keywords # Description: Multiproxy (pollen, plant macrofossils, sediment accretion, and carbon accumulation) data from river wetlands sediment cores. # Cores are from 2 transects ranging from tidal freshwater forested wetlands (TFFW) to oligohaline marsh, along the Waccamaw and Savannah # Rivers (South Carolina and Georgia, USA) for the late Holocene (~6,000 - 1,500 years BP). #-------------------- # Publication # Authors: Miriam C. Jones, Christopher E. Bernhardt, Ken W. Krauss, Gregory B. Noe # Published_Date_or_Year: 2017-12-01 # Published_Title: The Impact of Late Holocene Land Use Change, Climate Variability, and Sea Level Rise on Carbon Storage in Tidal Freshwater Wetlands on the Southeastern United States Coastal Plain # Journal_Name: Journal of Geophysical Research Biogesciences # Volume: 122 # Edition: # Issue: 12 # Pages: 3126-3141 # Report_Number: # DOI: 10.1002/2017JG004015 # Online_Resource: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017JG004015 # Full_Citation: # Abstract: This study examines Holocene impacts of changes in climate, land use, and sea level rise (SLR) on sediment accretion, carbon accumulation rates (CAR), and vegetation along a transect of tidal freshwater forested wetlands (TFFW) to oligohaline marsh along the Waccamaw River, South Carolina (four sites) and along the Savannah River, Georgia (four sites). We use pollen, plant macrofossils, accretion, and CAR from cores, spanning the last 1,500-6,000 years to test the hypothesis that TFFW have remained stable throughout the late Holocene and that marshes transitioned from TFFW during elevated SLR during the Medieval Climate Anomaly, with further transformation resulting from colonial land use change. Results show low and stable accretion and CAR through much of the Holocene, despite moderate changes associated with Holocene paleoclimate. In all records, the largest observed change occurred within the last ~400 years, driven by colonial land clearance, shifting terrigenous sediment into riparian wetlands, resulting in order-of-magnitude increases in accretion and C accumulation. The oligohaline marshes transitioned from TFFW ~300-500 years ago, coincident with colonial land clearance. Postcolonial decreases in CAR and accretion occur because of watershed reforestation over the last century. All sites show evidence of recent (decades to century) swamp forest decline due to increasing salinity and tidal inundation from SLR. This study suggests that allochthonous sediment input during colonialization helped maintain TFFW but that current SLR rates are too high for TFFW to persist, although higher accretion rates in oligohaline marshes increase the resilience of tidal wetlands as they transition from TFFW to marsh. #------------------ # Funding_Agency # Funding_Agency_Name: United States Geological Survey # Grant: Climate and Land Use Change R&D #------------------ # Site_Information # Site_Name: Savannah12-12-11-1 # Location: North America>United States Of America>Georgia # Country: United States Of America # Northernmost_Latitude: 32.238 # Southernmost_Latitude: 32.238 # Easternmost_Longitude: -81.155 # Westernmost_Longitude: -81.155 # Elevation: #------------------ # Data_Collection # Collection_Name: Savannah12-12-11-1pollen # Earliest_Year: 4000 # Most_Recent_Year: -61 # Time_Unit: Cal. Year BP # Core_Length: 3.2 # Notes: Upper Freshwater TFFW (tidal freshwater forested wetlands) #------------------ # Chronology_Information # Chronology: # Lab_ID depth_cm age_14C 14C error Material dated # Beta-381823 68-69 590 30 Bulk organic, picked free of roots # Beta-357069 102-103 1350 30 Bulk organic, picked free of roots # Beta-420004 197-198 3010 30 Bulk organic, picked free of roots # Beta-357070 243-244 3940 30 Bulk organic, picked free of roots # Beta-357071 313-314 4010 30 Bulk organic, picked free of roots # #---------------- # Variables # # Data variables follow are preceded by "##" in columns one and two. # Data line variables format: one per line, shortname-tab-variable components (what, material, error, units, seasonality, data type,detail, method, C or N for Character or Numeric data, free text) # ## depth_cm depth, , , cm, , , , ,C, Depths are midpoints ## Pinus Pinus, sediment, , count, ,Pollen,,,N, ## Quercus Quercus, sediment, , count, ,Pollen,,,N, ## Carya Carya, sediment, , count, ,Pollen,,,N, ## Liquidambar Liquidambar, sediment, , count, ,Pollen,,,N, ## Tsuga Tsuga, sediment, , count, ,Pollen,,,N, ## Picea Picea, sediment, , count, ,Pollen,,,N, ## Betula Betula, sediment, , count, ,Pollen,,,N, ## Salix Salix, sediment, , count, ,Pollen,,,N, ## Nyssa Nyssa, sediment, , count, ,Pollen,,,N, ## Ulmus Ulmus, sediment, , count, ,Pollen,,,N, ## Juglans Juglans, sediment, , count, ,Pollen,,,N, ## Ostrya/Carpinus Ostrya/Carpinus, sediment, , count, ,Pollen,,,N, ## Fagus Fagus, sediment, , count, ,Pollen,,,N, ## Myrica Myrica, sediment, , count, ,Pollen,,,N, ## Alnus Alnus, sediment, , count, ,Pollen,,,N, ## Acer Acer, sediment, , count, ,Pollen,,,N, ## Fraxinus Fraxinus, sediment, , count, ,Pollen,,,N, ## Ilex Ilex, sediment, , count, ,Pollen,,,N, ## Liriodendron Liriodendron, sediment, , count, ,Pollen,,,N, ## Magnolia Magnolia, sediment, , count, ,Pollen,,,N, ## Tilia Tilia, sediment, , count, ,Pollen,,,N, ## Cephalanthus Cephalanthus, sediment, , count, ,Pollen,,,N, ## Cyperaceae Cyperaceae, sediment, , count, ,Pollen,,,N, ## Poaceae Poaceae, sediment, , count, ,Pollen,,,N, ## Zea mays Zea mays, sediment, , count, ,Pollen,,,N, ## Typha Typha, sediment, , count, ,Pollen,,,N, ## Ericaceae Ericaceae, sediment, , count, ,Pollen,,,N, ## Sagittaria Sagittaria, sediment, , count, ,Pollen,,,N, ## Hymenocallis Hymenocallis, sediment, , count, ,Pollen,,,N, ## Amaranthaceae Amaranthaceae, sediment, , count, ,Pollen,,,N, ## Ambrosia Ambrosia, sediment, , count, ,Pollen,,,N, ## Asteraceae indet. Asteraceae indet., sediment, , count, ,Pollen,,,N, ## Artemesia Artemesia, sediment, , count, ,Pollen,,,N, ## Onagraceae Onagraceae, sediment, , count, ,Pollen,,,N, ## Polygalaceae Polygalaceae, sediment, , count, ,Pollen,,,N, ## Malvaceae Malvaceae, sediment, , count, ,Pollen,,,N, ## Apiaceae Apiaceae, sediment, , count, ,Pollen,,,N, ## Solanaceae Solanaceae, sediment, , count, ,Pollen,,,N, ## Ponteridaceae Ponteridaceae, sediment, , count, ,Pollen,,,N, ## Boraginaceae Boraginaceae, sediment, , count, ,Pollen,,,N, ## Rhus Rhus, sediment, , count, ,Pollen,,,N, ## Cichorieae Cichorieae, sediment, , count, ,Pollen,,,N, ## Fabaceae Fabaceae, sediment, , count, ,Pollen,,,N, ## Vitis Vitis, sediment, , count, ,Pollen,,,N, ## Tricolpate Tricolpate, sediment, , count, ,Pollen,,,N, ## Tricolporate Tricolporate, sediment, , count, ,Pollen,,,N, ## Triporate Triporate, sediment, , count, ,Pollen,,,N, ## Trilete Trilete, sediment, , count, ,Pollen,,,N, ## Monolete Monolete, sediment, , count, ,Pollen,,,N, ## Blechnum Blechnum, sediment, , count, ,Pollen,,,N, ## Acrostichum Acrostichum, sediment, , count, ,Pollen,,,N, ## Osmunda Osmunda, sediment, , count, ,Pollen,,,N, ## Fossil Lyco Fossil Lyco, sediment, , count, ,Pollen,,,N, ## Unknown/Crumpled Unknown/Crumpled, sediment, , count, ,Pollen,,,N, ## Total Total, sediment, , count, ,Pollen,,,N, ## Weight (g) Weight, sediment, , g, ,Pollen,,,N, ## Lycopodium (exotic) Lycopodium (exotic), sediment, , count, ,Pollen,,,N, # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # depth_cm Pinus Quercus Carya Liquidambar Tsuga Picea Betula Salix Nyssa Ulmus Juglans Ostrya/Carpinus Fagus Myrica Alnus Acer Fraxinus Ilex Liriodendron Magnolia Tilia Cephalanthus Cyperaceae Poaceae Zea mays Typha Ericaceae Sagittaria Hymenocallis Amaranthaceae Ambrosia Asteraceae indet. Artemesia Onagraceae Polygonaceae Malvaceae Apiaceae Solanaceae Ponteridaceae Boraginaceae Rhus Cichorieae Fabaceae Vitis Tricolpate Tricolporate Triporate Trilete Monolete Blechnum Acrostichum Osmunda Fossil Lyco Crumpled/Unknown Total Sample weight (g) Lycopodium (exotic) 5.5 602 69 39 10 0 0 0 0 105 3 0 0 0 5 1 2 1 0 1 0 0 0 1 9 0 1 0 0 0 4 7 3 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 2 0 3 876 0.7 157 10.5 427 16 33 6 0 0 0 0 48 1 1 0 0 1 0 0 1 0 0 0 0 0 1 4 0 1 0 0 0 0 2 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 2 2 0 0 1 0 2 553 0.19 101 20.5 155 54 15 16 0 1 1 0 50 2 0 2 0 4 0 1 2 0 0 0 0 0 0 2 0 1 0 0 0 0 17 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 2 332 1.8 24 30.5 244 11 22 17 0 0 1 0 59 3 0 0 0 5 0 1 0 0 0 0 0 1 0 2 0 1 0 0 0 1 8 5 0 0 1 0 0 0 0 0 0 0 10 0 0 1 0 1 0 0 0 0 0 4 398 5 16 40.5 396 10 7 14 0 0 0 0 68 6 0 1 0 3 0 0 0 1 0 0 0 0 0 6 0 1 0 0 0 0 5 1 0 0 1 0 0 0 0 0 1 0 1 0 1 0 1 0 7 0 0 0 1 1 533 5.02 49 50.5 231 11 16 12 0 0 2 0 61 6 0 3 0 1 2 1 0 1 0 0 0 0 0 4 0 0 1 0 0 0 2 3 0 0 0 0 0 1 0 0 0 0 0 0 1 3 0 0 7 0 0 0 0 3 372 4.03 20 60.5 180 4 14 11 0 1 1 0 179 7 0 0 0 1 0 1 0 0 0 0 0 0 0 4 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 7 0 0 0 0 2 416 4.2 14 70.5 137 2 9 10 0 0 0 0 221 3 0 0 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 9 0 0 1 0 0 398 5.02 4 80.5 144 3 8 3 0 0 0 0 147 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 2 0 0 0 0 1 313 5 7 90.5 375 3 19 19 0 0 1 0 31 0 1 0 1 1 0 1 0 0 0 0 1 0 0 2 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 12 0 0 3 0 1 474 5 25 100.5 211 13 26 15 0 0 1 0 44 2 0 4 0 0 0 1 0 1 0 0 0 0 0 2 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 12 0 0 6 0 4 349 4.03 34 110.5 222 12 20 16 0 0 0 0 52 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 3 0 0 0 0 1 336 5.02 9 120.5 202 13 8 16 0 2 0 0 56 1 1 2 0 0 0 0 1 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 4 23 0 0 8 0 1 343 5.01 33 130.5 98 17 9 20 0 0 2 0 76 2 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 0 0 1 0 0 1 0 0 0 50 0 3 14 0 5 306 5 155 140.5 205 16 20 13 0 0 0 0 44 1 0 2 1 4 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 2 0 0 0 0 0 1 0 0 24 0 0 0 0 0 0 1 8 0 0 3 0 2 349 5.02 24 150.5 219 10 17 8 0 0 0 0 86 5 0 3 0 2 0 0 0 1 0 0 0 0 2 2 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 2 10 0 0 1 0 1 374 4 8 160.5 158 35 8 13 0 0 0 0 122 1 0 0 0 5 0 0 2 0 0 0 0 0 1 2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 4 0 0 0 0 0 359 5.02 5 170.5 179 10 15 14 0 0 1 1 104 10 0 1 0 7 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 1 353 5 4 180.5 153 3 12 10 0 0 0 0 149 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 335 5 2 190.5 178 2 15 12 0 0 0 0 118 10 1 1 0 2 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 0 0 0 0 0 347 5 2 200.5 200 11 10 15 1 0 0 0 106 30 0 1 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 380 4.01 12 210.5 124 10 10 26 0 0 1 0 195 9 0 0 0 2 0 0 1 2 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 385 5 6 220.5 119 17 16 20 0 0 1 0 133 4 0 4 0 2 2 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 4 0 0 1 0 0 330 5 2 230.5 184 18 7 23 0 0 1 1 124 8 0 3 0 1 2 0 2 1 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 382 1.48 8 240.5 222 18 12 16 0 0 0 0 104 4 0 4 0 1 0 0 1 1 0 0 0 0 0 6 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 1 0 0 0 3 399 2.41 69 250.5 232 28 24 9 0 0 0 0 85 6 0 1 0 2 0 1 0 5 0 0 0 0 0 11 0 0 1 0 1 0 0 7 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 3 0 0 1 0 2 423 3.17 8 260.5 210 23 9 26 0 0 0 0 35 2 0 1 0 2 0 0 0 1 0 0 1 0 0 3 0 0 0 0 0 0 1 3 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 5 0 0 0 0 1 327 3.21 6 270.5 200 21 26 13 0 0 1 0 48 2 0 2 0 1 0 2 0 0 0 0 0 0 0 6 0 0 1 0 0 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 2 0 5 339 5.01 2 280.5 201 40 23 6 4 0 3 0 28 2 0 4 0 2 0 0 0 0 1 0 1 1 0 9 0 0 2 0 0 3 0 4 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 7 0 0 1 0 3 347 3.54 17 290.5 182 44 33 20 2 0 2 0 18 7 0 1 0 2 0 0 0 0 2 1 0 0 0 5 0 0 1 0 0 3 1 2 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 6 0 0 2 0 1 340 5.02 9 300.5 192 42 63 7 1 0 0 0 12 3 2 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 1 10 0 0 1 0 0 345 4.01 21 310.5 196 63 18 13 2 0 2 0 14 13 0 3 0 2 2 2 2 0 0 0 0 0 0 9 0 0 4 0 0 0 2 1 0 0 2 0 0 0 0 0 0 3 0 0 1 0 1 2 7 0 0 1 0 4 369 5.01 181 320.5 192 40 19 15 0 0 1 0 35 5 0 2 0 0 0 0 3 0 0 0 0 0 0 3 1 0 3 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 4 3 0 0 1 0 1 333 4 53