Coastal Carbon Data Clearinghouse
The CCRCN strives for transparency with methods of data archival and management. Here we overview data types and structure associated with the Network, and procedures for data storage and quality control.
An exhaustive description of the naming convention for attributes and variables recommended by the CCRCN.
Use this web interface to visualize, query, and download data from the Coastal Carbon Clearinghouse.
Want to know how to use the Atlas? Check out this video tutorial:
The Network recognizes three classes of data: (i) data that we curate, (ii) data that we ingest, and (iii) synthesis products we create. Data that we curate will be hosted on Smithsonian Institution (SI) servers, but the original data submitter and funding sources will be credited as the dataset’s creators. Data that we ingest will include both data we curate and data from any outside sources that meet basic availability, archiving, and metadata standards.
See below for a list of CCRCN data products.
|Kemp et al. (2020)||Kemp, Andrew C.; Sommerfield, Christopher K.; Vane, Christopher H.; P. Horton, Benjamin; Chenery, Simon; Anisfeld, Shimon; et al. (2020): Dataset: Use of lead isotopes for developing chronologies in recent salt-marsh sediments. figshare. Dataset. https://doi.org/10.25573/serc.11569419.v1||16 January 2020|
|McTigue et al. (2020)||McTigue, Nathan; Davis, Jenny; Rodriguez, Antonio; McKee, Brent; Atencio, Anna; Currin, Carolyn (2020): Dataset: Carbon accumulation rates in a salt marsh over the past two millennia. figshare. Dataset. https://doi.org/10.25573/serc.11421063.v1||10 January 2020|
|Breithaupt et al. (2019)||Breithaupt, Joshua L.; Smoak, Joseph M.; Sanders, Christian J.; Smith III, Thomas J. (2019): Dataset: Temporal variability of carbon and nutrient burial, sediment accretion, and mass accumulation over the past century in a carbonate platform mangrove forest of the Florida Everglades. figshare. Dataset. https://doi.org/10.25573/serc.11310926.v1||20 December 2019|
|Coastal Wetland Elevation and Carbon Flux Inventory with Uncertainty, USA, 2006-2011 (Associated Paper here)||Holmquist, J.R., L. Windham-Myers, B. Bernal, K.B. Byrd, S. Crooks, M.E. Gonneea, N. Herold, S.H. Knox, K. Kroeger, J. Mccombs, P.J. Megonigal, L. Meng, J.T. Morris, A.E. Sutton-grier, T. Troxler, and D. Weller. 2019. Coastal Wetland Elevation and Carbon Flux Inventory with Uncertainty, USA, 2006-2011. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1650||17 December 2019|
|Thom 2019||Thom, Ronald M. (2019): Dataset: Accretion rates of low intertidal salt marshes in the Pacific Northwest. figshare. Dataset. https://doi.org/10.25573/data.10046189.v2||13 November 2019|
|Belshe et al., 2019||Belshe, E. Fay; Sanjuan, Jose; Leiva-Dueñas, Carmen; Piñeiro-Juncal, Nerea; Serrano, Oscar; S. Lavery, Paul; et al. (2019): Dataset: Modeling organic carbon accumulation rates and residence times in coastal vegetated ecosystems. figshare. Dataset. https://doi.org/10.25573/data.9856769.v1||01 November 2019|
|Abbott et al, 2019||Abbott, Katherine M; Quirk, Tracy; Delaune, Ronald D. (2019): Dataset: Factors influencing blue carbon accumulation across a 32‐year chronosequence of created coastal marshes. figshare. Dataset. https://doi.org/10.25573/data.10005215.v1||01 November 2019|
|Poppe and Rybczyk, 2019||Poppe, Katrina L; Rybczyk, John M (2019): Dataset: Sediment carbon stocks and sequestration rates in the Pacific Northwest region of Washington, USA. figshare. Dataset. https://doi.org/10.25573/data.10005248.v1||24 October 2019|
|The Coastal Carbon Network - Below Ground Survey||This is a web interface we designed with the goal of surveying best educated guesses on how key below ground plant traits and decay rates vary for tidal wetlands. The app uses a formal expert elicitation protocol and feedback will be pooled to inform the modeling effort of our soils working group.||21 October 2019|
|Boyd et al. 2019||Boyd, Brandon; Sommerfield, Christopher K.; Quirk, Tracy; Unger, Viktoria (2019): Dataset: Accretion and sediment accumulation in impounded and unimpounded marshes in the Delaware Estuary and Barnegat Bay. figshare. Dataset. https://doi.org/10.25573/data.9747065.v1||03 September 2019|
|Callaway et al. 2019||Callaway, John C.; Borgnis, Evyan L.; Turner, R. Eugene; Milan, Charles S. (2019): Dataset: Carbon sequestration and sediment accretion in San Francisco Bay tidal wetlands. figshare. Dataset. https://doi.org/10.25573/data.9693251.v1||03 September 2019|
|Doughty et al. 2019||Doughty, Cheryl; Langley, J. Adam; Walker, Wayne; Feller, Ilka C.; Schaub, Ronald; Chapman, Samantha (2019): Mangroves marching northward: the impacts of rising seas and temperatures on ecosystems at Kennedy Space Center. figshare. Dataset. https://doi.org/10.25573/data.9695918.v1||26 August 2019|
|The Coastal Carbon Atlas||Use this web interface to visualize, query, and download data from the Coastal Carbon Clearinghouse.||22 February 2019|
|Tidal Wetland Soil Carbon Stocks for CONUS||This dataset provides modeled estimates of soil carbon stocks for tidal wetland areas of the Conterminous United States (CONUS) for the period 2006-2010.||20 February 2019|
|Accuracy and Precision of Tidal Wetland Soil Carbon Mapping (associated paper here)||Per-depth soil organic matter and carbon metrics, plant species identity, state of human impact, field and lab methodology, and metadata of 1534 soil cores||21 June 2018|
|Coastal National Greenhouse Gas Inventory: Report, Datasets, and Workflow||Literature review, data, analysis, and report||9 December 2017|
Malhotra, A., Todd-Brown, K., Nave, L. E., Batjes, N. H., Holmquist, J. R., Hoyt, A. M., ... & Vindušková, O. (2019). The landscape of soil carbon data: emerging questions, synergies and databases. Progress in Physical Geography: Earth and Environment, 43(5), 707-719.
Rogers, K., Kelleway, J. J., Saintilan, N., Megonigal, J. P., Adams, J. B., Holmquist, J. R., ... & Woodroffe, C. D. (2019). Wetland carbon storage controlled by millennial-scale variation in relative sea-level rise.
Holmquist, J. R., Windham-Myers, L., Bernal, B., Byrd, K. B., Crooks, S., Gonneea, M. E., ... & Megonigal, J. P. (2018). Uncertainty in United States coastal wetland greenhouse gas inventorying. Environmental Research Letters, 13(11), 115005.
Holmquist, J. R., Windham-Myers, L., Bliss, N., Crooks, S., Morris, J. T., Megonigal, J. P., ... & Ferner, M. C. (2018). Accuracy and precision of tidal wetland soil carbon mapping in the conterminous United States. Scientific reports, 8(1), 9478.
Testimonials to Data Contribution
“The Coastal Carbon Research Coordination Network dataset has been invaluable in our recent research identifying global drivers of variability in coastal wetland carbon cycling. The Network’s dataset greatly complemented our own previous data collation efforts, filling important gaps in our record. The availability of a comprehensive and well-curated dataset allowed us to focus on the analysis and interpretation of data, deriving important new insights in global patterns of carbon storage.”
- Jeffrey Kelleway, Department of Environmental Sciences, Macquarie University
"The CCRCN database is a key cornerstone in accelerating the pace of discovery for coastal carbon cycling. I recently downloaded version 1, and have begun analylzing it and intercomparing its features with other national and global sets on soil core characteristics. As it focuses only on soilcores from tidal wetland, it is the single largest and spatially explicit empirical dataset, globally, for populating carbon stock assessments or testing models across space and time. For coastal lands, it is an invaulable asset for scientists and managers alike. The developers of the dataset and platform should be commended, as should the many community contributors who are fueling advances in science and practice by sharing their data."
"[The CCRCN administrators] are doing an amazing job at this organization and promoting inclusivity. I am floored by your intuition and abilities. You are the natural heirs to this community-building."
- Lisamarie Windham-Myers, U.S. Geological Survey