# 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/waccamaw2017pollen11-11-2-1.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: Waccamaw11-11-2-1 # Location: North America>United States Of America>Georgia # Country: United States Of America # Northernmost_Latitude: 33.55564 # Southernmost_Latitude: 33.55564 # Easternmost_Longitude: -79.08943 # Westernmost_Longitude: -79.08943 # Elevation: #------------------ # Data_Collection # Collection_Name: Waccamaw11-11-2-1pollen # Earliest_Year: 2200 # Most_Recent_Year: -61 # Time_Unit: Cal. Year BP # Core_Length: 0.78 # Notes: Oligohaline Marsh. Percent compression: 45.07; Original depth 142 #------------------ # Chronology_Information # Chronology: # Lab_ID depth_cm age_14C 14C error Material dated # Beta-348404 22-23 30 30 Bulk organic, picked free of roots # Beta-352945 31-32 220 30 Bulk organic, picked free of roots # Beta-348405 37-38 1260 30 Bulk organic, picked free of roots # Beta-348406 60-61 1850 30 Bulk organic, picked free of roots # Beta-348407 72-73 2180 30 Bulk organic, picked free of roots # Beta-344281 77-78 2030 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, ## Myriophyllum Myriophyllum, 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, ## Mint Mint, 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, ## Juglans Juglans, sediment, , count, ,Pollen,,,N, ## Ostrya/Carpinus Ostrya/Carpinus, sediment, , count, ,Pollen,,,N, ## Rosaceae Rosaceae, sediment, , count, ,Pollen,,,N, ## Coylus Coylus, sediment, , count, ,Pollen,,,N, ## Ipomea Ipomea, sediment, , count, ,Pollen,,,N, ## Liriodendron Liriodendron, sediment, , count, ,Pollen,,,N, ## Parthenocissus Parthenocissus, sediment, , count, ,Pollen,,,N, ## Onagraceae Onagraceae, sediment, , count, ,Pollen,,,N, ## Fagus Fagus, sediment, , count, ,Pollen,,,N, ## Juglans Juglans, sediment, , count, ,Pollen,,,N, ## Pontedaria Pontedaria, sediment, , count, ,Pollen,,,N, ## Castanea-like Castanea-like, sediment, , count, ,Pollen,,,N, ## Tsuga Tsuga, sediment, , count, ,Pollen,,,N, ## Plantus Plantus, sediment, , count, ,Pollen,,,N, ## Lonicera Lonicera, sediment, , count, ,Pollen,,,N, ## Vitus Vitus, sediment, , count, ,Pollen,,,N, ## Artemesia Artemesia, sediment, , count, ,Pollen,,,N, ## Picea Picea, 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 Myriophyllum Sagittaria Polygonaceae Triporate Tricolporate Tricolpate Trilete Monolete Mint Osmunda Crumpled Betula Ulmus Fraxinus Acer Alnus Juglans Ostrya/Carpinus Rosaceae Coylus Ipomea Liriodendron Parthenocissus Onagraceae Fagus Juglans Pontedaria Castanea-like Tsuga Plantus Lonicera Vitus Artemesia Picea Total Weight (g) Lycopodium (Exotics) 0-1 163 35 8 13 0 16 1 0 29 0 2 1 16 5 6 0 0 0 0 14 0 0 0 2 0 1 1 0 0 2 0 1 0 0 4 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 0 0 0 0 324 4.67 8 3-4 169 37 4 8 0 13 0 0 13 0 1 0 14 2 4 0 0 0 0 25 1 0 0 3 1 0 0 2 0 2 0 0 1 1 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 305 1.97 15 5-6 198 25 6 12 0 13 0 0 7 0 2 3 18 3 3 0 1 1 0 0 0 0 0 2 0 0 0 0 0 1 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 299 1.37 12 8-9 236 12 6 5 0 13 0 0 27 0 1 4 2 2 3 0 0 0 0 6 1 0 0 2 0 0 1 0 1 1 0 2 0 0 2 0 0 3 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 332 1.48 22 10-11 195 14 2 4 0 8 0 0 29 0 0 7 18 3 7 0 0 1 0 6 0 0 0 7 0 0 1 0 0 4 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 311 2.17 9 13-14 233 15 4 2 0 18 0 0 33 0 0 4 4 0 6 0 0 0 0 0 2 0 0 0 0 0 1 0 0 1 0 0 2 0 2 0 0 4 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 333 2.23 14 15-16 220 6 14 2 0 10 0 0 39 0 1 1 5 0 6 0 1 1 0 0 1 0 0 0 0 1 0 0 1 3 0 1 3 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 318 5.14 12 18-19 214 10 23 3 0 9 0 0 53 0 0 1 6 1 1 0 0 0 0 1 2 2 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 337 4.96 18 20-21 142 11 14 5 0 13 0 1 80 0 0 0 12 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 2 0 0 2 0 3 0 0 1 0 0 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 293 5.15 17 23-24 197 8 15 6 0 9 0 0 49 1 0 0 16 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 8 0 2 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 318 5.18 12 25-26 183 13 15 10 0 10 0 0 60 0 0 0 5 0 2 0 0 1 0 0 0 0 0 0 1 1 0 1 0 5 0 2 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 311 5.06 6 28-29 223 15 23 7 0 3 0 0 36 0 0 0 4 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 6 0 6 2 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 329 5.04 12 30-31 236 13 12 6 0 10 0 0 27 0 1 3 6 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 3 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 321 5.18 7 33-34 249 14 16 7 0 8 0 0 16 0 0 2 2 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 323 5.19 11 35-36 250 6 21 4 0 3 0 0 22 0 0 1 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 317 5.1 12 38-39 251 26 11 8 0 8 0 0 27 0 0 1 2 0 2 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 0 0 344 5 14 40-41 221 22 14 6 0 13 0 0 32 0 0 2 10 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 3 0 2 0 0 3 0 1 0 0 0 0 0 0 8 0 0 1 1 0 0 0 0 0 0 0 0 341 4.98 6 43-44 224 18 16 3 0 7 0 0 23 0 0 1 8 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 310 5.11 23 45-46 188 9 13 7 0 6 0 0 36 0 0 4 5 0 6 0 2 0 0 0 1 0 0 1 0 0 0 0 0 4 0 1 0 0 2 1 0 0 0 1 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 290 5.34 10 48-49 210 19 14 4 0 6 0 0 23 0 0 1 4 0 2 0 0 0 0 0 0 0 0 0 0 1 0 0 0 4 1 1 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 295 5.04 17 50-51 139 24 12 6 0 8 0 0 49 0 1 7 12 0 10 0 0 2 0 0 1 0 0 0 0 0 0 0 0 6 0 13 4 1 2 0 0 0 0 0 0 0 0 4 0 0 1 0 0 0 0 0 0 0 0 0 302 5.52 32 53-54 169 15 24 6 0 14 0 0 46 0 1 1 18 1 3 0 1 0 0 0 0 0 0 0 0 1 1 0 0 7 0 2 1 1 3 0 0 1 0 1 0 0 0 5 0 0 1 1 0 0 0 0 0 0 0 0 324 4.44 71 55-56 185 10 20 3 0 3 0 0 33 0 1 2 4 0 3 1 0 0 0 0 1 0 0 0 0 0 0 1 0 6 0 3 1 0 1 3 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 287 5.56 25 58-59 203 5 12 0 0 9 0 0 23 0 0 2 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 1 0 4 2 0 1 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 277 4.99 17 60-61 260 6 12 6 0 6 0 0 20 1 1 1 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 3 0 1 0 0 2 0 0 1 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 331 5.34 13 63-64 270 21 9 5 0 5 0 0 16 2 0 2 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 1 1 2 5 0 2 0 0 0 0 0 7 1 0 1 0 0 0 0 0 0 0 1 0 363 5.01 6 65-66 260 13 14 5 0 11 0 0 27 0 0 3 4 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 1 0 2 4 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 354 5.52 7 68-69 221 12 12 8 0 11 0 0 24 1 0 3 9 1 1 0 1 0 0 0 1 0 0 0 0 1 0 0 1 1 0 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 312 4.98 10 70-71 213 18 7 4 0 9 0 0 32 0 0 3 7 1 3 2 0 0 1 0 1 0 0 0 0 0 0 0 0 2 0 1 2 0 2 3 1 0 0 0 0 1 0 1 0 0 1 2 0 0 0 0 0 0 0 0 317 5.4 26 73-74 238 20 13 3 0 13 0 0 39 1 0 2 3 0 4 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 1 0 4 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 350 4.9 13 75-76 216 9 9 9 0 5 0 0 46 0 0 1 7 0 5 4 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 4 0 0 2 3 0 2 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 332 5.17 14 76-77 220 23 8 3 0 10 0 0 29 0 0 2 6 0 1 0 0 2 0 0 0 1 0 0 0 1 1 0 0 3 0 2 2 0 4 7 0 1 0 0 0 0 0 1 3 0 1 0 0 0 0 0 0 0 0 0 331 3.6 13