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Accession: MSH-GCEM-2508 Research Theme: Marsh Ecology (Monitoring)
Contributors: Peter Hawman, Deepak Mishra, Wade Sheldon
Title: Eddy covariance (EC) vertical carbon fluxes from a Georgia tidal salt marsh from 2014 to 2024
Abstract: We present our methodology and data for science ready vertical carbon fluxes from a Spartina alterniflora tidal salt marsh as part of the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) site on Sapelo Island, Georgia, USA. Vertical carbon fluxes were measured through the eddy covariance (EC) method from 2014 to 2024. The EC flux tower was located on the western side of Sapelo Island bounded by the Duplin River and Barn Creek. The proportional influence of marsh habitats on the flux measurements were 4% tall, 38% short, and 58% medium height form Spartina alterniflora. We present the net ecosystem exchange (NEE), ecosystem respiration (ER), and gross primary production (GPP) at 30-minute fluxes (μmol CO2 m-2 s-1), daily averages (μmol CO2 m-2 s-1) and totals (g C m-2 day-1), and annual (g C m-2 year-1) quantities. We provide estimated uncertainty for each flux at each integrated timescale as 95% confidence intervals. Providing open access to 10-year carbon flux datasets can facilitate collaboration for advancing regional and global blue carbon synthesis and scale-up studies.
DOI: 10.6073/pasta/e9371ead3fbe0cdf67083fe7c97c2893
Key Words: carbon assimilation, carbon cycling, carbon dioxide, carbon fluxes, Duplin River, ecology, ecosystems, GCE, Georgia, LTER, marshes, photosynthesis, Plant Monitoring, Sapelo Island, vegetation
LTER Core Area: Primary Production
Research Themes: Marsh Ecology, Plant Ecology
Study Period: 01-Jan-2014 to 31-Dec-2024
Study Sites:
GCE_Flux -- GCE Flux Tower Marsh, Sapelo Island, Georgia
» Download Geographic Coverage: Google Earth
Research Protocols:

Protocol for calculating sampling error in CO2 flux measurements (Journal of Geophysical Research)

Impact of post-field data processing on eddy covariance flux estimates and energy balance closure (Meteorologische Zeitschrift)

Averaging Detrending and Filtering of Eddy Covariance Time Series (Handbook of Micrometeorology)

A system to measure surface fluxes of momentum, sensible heat, water vapour and carbon dioxide (Journal of Hydrology)

Quality Control and Flux Sampling Problems for Tower and Aircraft Data (Journal of Atmospheric and Oceanic Technology)

Correction of flux measurements for density effects due to heat and water vapour transfer (Quarterly Journal of the Royal Meteorological Society)

Sonic Anemometer Tilt Correction Algorithms (Boundary-Layer Meteorology)

Downloads: Information

Data Table: MSH-GCEM-2508_30min (30-minute NEE, ER, and GPP data, 192864 records)

Access: Public (released 15-Aug-2025)

Metadata: Text (ESA FLED), XML (Ecological Metadata Language)

Data Formats: Spreadsheet (CSV) [39918.68kb],  Text File [41330.51kb],  MATLAB (GCE Toolbox) [21974.14kb],  MATLAB (Variables) [21975.72kb],  Text Report [42572.19kb]

Column List:(display)


Data Table: MSH-GCEM-2508_daily (daily averages and totals of NEE, ER, and GPP, 4018 records)

Access: Public (released 15-Aug-2025)

Metadata: Text (ESA FLED), XML (Ecological Metadata Language)

Data Formats: Spreadsheet (CSV) [570.86kb],  Text File [562.38kb],  MATLAB (GCE Toolbox) [405.22kb],  MATLAB (Variables) [406.00kb],  Text Report [609.88kb]

Column List:(display)


Data Table: MSH-GCEM-2508_yearly (annual quantities or NEE, ER, and GPP, 11 records)

Access: Public (released 15-Aug-2025)

Metadata: Text (ESA FLED), XML (Ecological Metadata Language)

Data Formats: Spreadsheet (CSV) [1.50kb],  Text File [1.05kb],  MATLAB (GCE Toolbox) [28.99kb],  MATLAB (Variables) [30.19kb],  Text Report [28.21kb]

Column List:(display)

Statistics: Generate script code to retrieve data tables for analysis in: MATLAB, R, SAS, SPSS
Citation: Hawman, Peter. 2025. Eddy covariance (EC) vertical carbon fluxes from a Georgia tidal salt marsh from 2014 to 2024. Georgia Coastal Ecosystems LTER Project, University of Georgia, Long Term Ecological Research Network. http://dx.doi.org/10.6073/pasta/e9371ead3fbe0cdf67083fe7c97c2893

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This material is based upon work supported by the National Science Foundation under grants OCE-9982133, OCE-0620959, OCE-1237140, OCE-1832178 and OCE-2425396. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.