# 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/southcarolina/waccamaw2017pollen11-11-2-3.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: Waccamaw11-11-2-3 # Location: North America>United States Of America>Georgia # Country: United States Of America # Northernmost_Latitude: 33.34001 # Southernmost_Latitude: 33.34001 # Easternmost_Longitude: -79.34166 # Westernmost_Longitude: -79.34166 # Elevation: #------------------ # Data_Collection # Collection_Name: Waccamaw11-11-2-3pollen # Earliest_Year: 4270 # Most_Recent_Year: -61 # Time_Unit: Cal. Year BP # Core_Length: 0.84 # Notes: Heavily salt impacted, Turkey Creek. Percent compression: not calculated/hole collapsed; Original depth not recorded #------------------ # Chronology_Information # Chronology: # Lab_ID depth_cm age_14C 14C error Material dated # Beta-352951 10-11 >Modern Bulk organic, picked free of roots # Beta-238781 21-22 970 30 Bulk organic, picked free of roots # Beta-352953 34-36 1110 30 Bulk organic, picked free of roots # Beta-328782 41-42 2200 30 Bulk organic, picked free of roots # Beta-328783 83-84 3850 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, ## Celtis Celtis, sediment, , count, ,Pollen,,,N, ## Myrica Myrica, sediment, , count, ,Pollen,,,N, ## Salix Salix, sediment, , count, ,Pollen,,,N, ## Nuphar Nuphar, sediment, , count, ,Pollen,,,N, ## Nyssa Nyssa, sediment, , count, ,Pollen,,,N, ## Magnolia Magnolia, sediment, , count, ,Pollen,,,N, ## Ilex Ilex, sediment, , count, ,Pollen,,,N, ## Amaranthaceae Amaranthaceae, sediment, , count, ,Pollen,,,N, ## Poaceae Poaceae, sediment, , count, ,Pollen,,,N, ## Ambrosia Ambrosia, sediment, , count, ,Pollen,,,N, ## Asteraceae indet Asteraceae indet, sediment, , count, ,Pollen,,,N, ## TCT TCT, sediment, , count, ,Pollen,,,N, ## Ericaceae Ericaceae, sediment, , count, ,Pollen,,,N, ## Cyperaceae Cyperaceae, sediment, , count, ,Pollen,,,N, ## Nymphaea Nymphaea, sediment, , count, ,Pollen,,,N, ## Typha Typha, sediment, , count, ,Pollen,,,N, ## Fabaceae Fabaceae, sediment, , count, ,Pollen,,,N, ## Apiaceae Apiaceae, sediment, , count, ,Pollen,,,N, ## Onagraceae Onagraceae, sediment, , count, ,Pollen,,,N, ## Sagittaria Sagittaria, sediment, , count, ,Pollen,,,N, ## Polygonaceae Polygonaceae, sediment, , count, ,Pollen,,,N, ## Triporate Triporate, sediment, , count, ,Pollen,,,N, ## Tricolporate Tricolporate, sediment, , count, ,Pollen,,,N, ## Tricolpate Tricolpate, sediment, , count, ,Pollen,,,N, ## Trilete Trilete, sediment, , count, ,Pollen,,,N, ## Monolete Monolete, sediment, , count, ,Pollen,,,N, ## Pteris Pteris, sediment, , count, ,Pollen,,,N, ## Osmunda Osmunda, sediment, , count, ,Pollen,,,N, ## Crumpled Crumpled, sediment, , count, ,Pollen,,,N, ## Betula Betula, sediment, , count, ,Pollen,,,N, ## Ulmus Ulmus, sediment, , count, ,Pollen,,,N, ## Fraxinus Fraxinus, sediment, , count, ,Pollen,,,N, ## Acer Acer, sediment, , count, ,Pollen,,,N, ## Alnus Alnus, sediment, , count, ,Pollen,,,N, ## Plantago Plantago, sediment, , count, ,Pollen,,,N, ## Ostrya/Carpinus Ostrya/Carpinus, sediment, , count, ,Pollen,,,N, ## Rosaceae Rosaceae, sediment, , count, ,Pollen,,,N, ## Coylus Coylus, sediment, , count, ,Pollen,,,N, ## Vitis Vitis, sediment, , count, ,Pollen,,,N, ## Liriodendron Liriodendron, sediment, , count, ,Pollen,,,N, ## Parthenocissus Parthenocissus, sediment, , count, ,Pollen,,,N, ## Lycopodium(natural) Lycopodium(natural), sediment, , count, ,Pollen,,,N, ## Fagus Fagus, sediment, , count, ,Pollen,,,N, ## Juglans Juglans, sediment, , count, ,Pollen,,,N, ## Picea Picea, sediment, , count, ,Pollen,,,N, ## Unknown Unknown, sediment, , count, ,Pollen,,,N, ## Artemesia Artemesia, sediment, , count, ,Pollen,,,N, ## Solanaceae Solanaceae, sediment, , count, ,Pollen,,,N, ## P0X P0X, sediment, , count, ,Pollen,,,N, ## Thalicrcum Thalicrcum, sediment, , count, ,Pollen,,,N, ## Fenestrate Fenestrate, sediment, , count, ,Pollen,,,N, ## Anacard Anacard, sediment, , count, ,Pollen,,,N, ## Plantus Plantus, 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 Celtis Myrica Salix Nuphar Nyssa Magnolia Ilex Amaranthaceae Poaceae Ambrosia Asteraceae indet TCT Ericaceae Cyperaceae Nymphaea Typha Fabaceae Apiaceae Onagraceae Sagittaria Polygonaceae Triporate Tricolporate Tricolpate Trilete Monolete Pteris Osmunda Crumpled Betula Ulmus Fraxinus Acer Alnus Plantago Ostrya/Carpinus Rosaceae Coylus Vitis Liriodendron Parthenocissus Lycopodium(natural) Fagus Juglans Picea Unknown Artemesia Solanaceae P0X Thalicrcum Fenestrate Anacard Plantus Total Weight (g) Lycopodium (exotics) 0-2 127 23 8 7 0 54 1 0 30 1 2 2 4 9 3 0 0 0 0 11 0 1 0 5 0 0 1 1 1 0 0 9 2 0 1 0 0 2 0 0 1 2 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 311 0.75 19 2-4 202 7 8 1 0 14 0 0 48 0 6 2 7 2 1 0 2 2 0 1 0 0 0 2 0 1 2 1 0 1 0 9 5 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 326 1.05 19 4-6 199 9 4 2 0 8 0 0 43 0 2 3 2 5 4 2 0 3 0 1 1 0 0 0 0 0 0 1 4 1 0 11 3 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 311 0.82 12 6-8 210 3 3 0 0 8 0 0 44 0 1 1 3 1 1 0 0 1 0 0 0 0 0 1 0 1 0 0 0 5 0 24 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 309 1.09 12 8-10 164 4 7 0 0 11 0 0 65 0 0 1 4 0 5 1 0 2 0 2 1 0 0 0 0 0 0 0 2 2 0 21 0 0 2 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 296 1.04 23 10-12 161 9 2 2 0 16 0 0 38 0 3 0 5 11 3 0 1 3 0 3 0 0 1 0 0 1 0 1 2 3 0 10 6 0 1 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 287 0.96 17 12-14 195 14 5 6 0 17 0 0 47 1 4 1 5 0 8 0 1 2 0 2 3 0 0 0 0 1 0 0 1 2 0 13 2 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 332 1.03 41 14-16 239 4 5 1 0 16 1 0 40 0 0 0 2 1 3 0 0 0 0 0 5 0 0 0 0 1 0 1 0 5 0 12 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 339 0.96 11 16-18 181 8 10 3 0 14 0 0 48 0 1 1 4 0 3 0 0 3 0 0 1 0 0 0 0 1 0 0 2 3 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 293 1.11 27 18-20 176 13 7 1 0 21 0 0 61 0 3 1 8 0 5 2 0 0 0 0 3 0 0 0 0 0 2 0 0 3 0 6 2 0 1 0 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 318 1.01 19 20-22 245 9 3 4 0 13 0 0 46 0 0 0 5 0 1 2 0 1 0 0 0 0 0 0 0 2 2 1 0 6 0 23 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 367 0.7 15 22-24 191 5 5 4 0 19 0 0 71 0 0 1 1 0 2 1 0 3 0 0 1 0 0 0 1 2 0 0 1 7 0 8 2 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 327 1.12 35 24-26 194 9 4 1 0 20 0 0 49 0 0 0 4 1 3 0 0 1 0 1 2 0 0 1 0 1 1 2 4 7 0 15 4 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 326 0.64 16 26-28 195 10 2 0 0 15 0 0 71 0 1 0 4 0 2 3 0 3 0 1 1 0 0 0 0 2 1 3 0 0 1 7 6 0 2 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 333 1.01 28 28-30 196 9 4 4 0 9 0 0 48 0 1 0 4 0 2 0 1 2 0 1 0 0 0 0 0 2 0 0 1 5 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 295 1.01 27 30-32 230 5 3 0 0 15 0 0 47 0 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 1 0 1 1 9 0 10 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 327 0.78 14 32-34 177 11 8 0 0 17 0 0 67 0 2 0 3 1 4 0 0 0 0 0 0 0 0 0 0 1 0 0 2 8 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 307 1.14 18 34-36 165 14 4 3 0 47 0 0 41 0 1 0 1 0 2 0 1 2 0 1 0 0 0 0 0 0 0 3 3 2 0 13 8 0 5 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 318 0.98 11 36-38 222 5 2 1 0 29 0 0 25 0 1 0 0 1 4 0 1 0 0 0 0 0 0 0 0 2 0 1 0 4 0 13 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 313 1.06 18 38-40 219 3 4 5 0 17 0 0 40 3 0 0 0 0 2 0 0 1 0 0 1 0 0 0 0 0 1 1 2 5 0 14 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 322 4.06 12 40-42 164 12 3 3 0 38 2 0 13 0 3 1 7 1 8 0 0 1 0 1 1 0 0 0 1 3 5 2 2 3 0 18 2 0 0 1 1 2 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 1 1 1 1 305 4.91 1 42-44 239 3 10 2 0 1 0 0 14 0 0 0 2 0 1 0 0 3 0 1 0 0 0 0 0 0 0 1 3 6 0 23 3 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 314 4.99 9 44-46 246 13 5 1 0 4 0 0 9 0 1 0 2 0 7 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 21 6 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 320 4.94 7 46-48 250 2 10 0 0 0 0 0 7 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 2 5 20 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 299 5.07 12 48-50 226 5 4 5 0 3 0 0 15 1 0 0 4 0 1 0 0 3 0 0 0 0 0 0 0 2 0 0 1 1 0 10 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 282 5.11 21 50-52 207 11 7 6 0 20 0 0 13 0 0 1 7 0 0 0 0 4 0 0 2 0 0 0 0 4 0 2 3 2 0 14 4 0 1 0 3 3 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 317 4.94 6 52-54 260 1 7 4 0 1 0 0 12 0 0 0 3 0 4 0 0 1 0 1 0 0 0 0 0 0 0 1 0 3 0 16 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 316 5.07 8 54-56 174 30 2 7 0 18 0 0 22 0 1 0 10 0 9 6 0 7 0 0 1 0 0 0 0 2 1 4 1 10 1 8 7 0 2 2 1 4 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 332 4.89 6 56-58 225 4 5 4 0 3 0 0 21 0 0 0 5 0 1 0 0 1 0 0 0 0 0 0 0 0 2 0 1 11 0 11 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 296 5.01 41 58-60 219 4 8 6 0 0 0 0 21 0 0 0 2 0 2 0 0 3 0 0 1 0 0 0 0 0 1 0 1 7 0 3 1 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 282 5.01 61 60-62 183 11 11 10 0 4 0 0 39 2 0 1 4 1 2 0 0 5 0 0 0 0 0 0 0 1 0 1 2 13 0 7 3 0 2 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 306 4.87 20 62-64 236 8 6 4 0 3 0 0 17 0 1 0 5 0 2 0 0 0 0 0 0 0 0 0 0 1 1 0 0 7 0 16 2 0 0 0 1 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 314 5.02 45 64-66 169 28 8 14 0 11 4 0 36 0 0 1 15 0 6 4 0 7 0 0 1 1 0 0 0 2 3 1 2 2 0 5 4 0 2 0 6 3 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 338 4.94 5 66-68 207 17 13 10 0 2 0 0 23 0 0 1 7 0 2 2 0 1 0 0 0 0 0 0 0 0 0 1 2 5 1 5 4 0 3 0 1 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 310 5.02 30 68-70 245 8 16 3 0 4 0 0 22 0 0 0 1 0 0 9 0 0 0 0 0 0 0 0 0 1 1 0 0 4 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 318 5.11 38 70-72 215 8 22 10 0 1 0 0 10 0 1 0 11 0 1 1 0 10 0 0 0 0 0 0 0 1 2 1 0 5 0 0 4 0 2 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 309 4.91 15 72-74 252 6 8 6 0 1 0 0 18 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 4 3 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 309 5.14 21 74-76 226 7 11 5 0 4 0 1 20 0 0 0 6 0 2 0 0 2 0 0 0 0 0 0 1 2 2 1 0 7 0 0 2 0 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 303 4.98 24 76-78 232 26 10 6 0 3 0 0 14 0 1 1 1 0 1 5 0 4 0 0 0 0 0 0 0 0 0 1 0 2 0 3 6 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 320 5.02 22 78-80 217 19 12 12 0 3 0 0 14 0 1 0 0 0 0 1 0 3 0 0 0 0 0 0 0 0 0 2 0 2 0 3 3 0 2 0 3 1 0 4 0 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 305 5.15 30 80-82 227 30 5 5 0 1 0 0 11 0 1 0 2 0 1 1 0 1 0 0 0 0 0 0 0 3 2 0 0 4 0 0 5 0 6 1 3 0 0 8 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 318 4.9 21 82-83 215 19 10 8 0 7 0 0 9 0 0 1 4 0 2 3 0 1 0 0 0 0 0 0 0 0 0 3 0 4 0 1 3 0 4 0 4 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 299 5 55