Automated Author ProfileWatson, Elizabeth
Watson, Elizabeth
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kgC m-3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision. This data release includes the soil carbon data currently considered public by the data submittors. Additional detail can be found in the publication. Holmquist JR et al. (2018). Accuracy and Precision of Tidal Wetlands Soil Carbon Mapping in the Conterminous United States. Scientific Reports. DOI:10.1038/s41598-018-26948-7
Authors
- Holmquist, James ;
- Windham-Myers, Lisamarie ;
- Bliss, Norman ;
- Crooks, Stephen ;
- Morris, James T. ;
- Megonigal, Patrick ;
- Troxler, Tiffany ;
- Weller, Donald ;
- Callaway, John ;
- Drexler, Judith ;
- Ferner, Matthew C. ;
- Gonneea, Meagan E. ;
- Kroeger, Kevin D. ;
- Schile-Beers, Lisa M ;
- Woo, Isa ;
- Buffington, Kevin ;
- Boyd, Brandon M. ;
- Breithaupt, Joshua ;
- Brown, Lauren N. ;
- Dix, Nicole ;
- A. Hice, Lyndie ;
- P. Horton, Benjamin ;
- MacDonald, Glen M ;
- P. Moyer, Ryan ;
- Reay, William ;
- Shaw, Timothy ;
- Smith, Erik ;
- M. Smoak, Joseph ;
- Sommerfield, Christopher ;
- Thorne, Karen ;
- J. Velinsky, David ;
- Watson, Elizabeth ;
- Wilson Grimes, Kristen ;
- Woodrey, Mark
Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kgC m-3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision. This data release includes the soil carbon data currently considered public by the data submittors. Additional detail can be found in the publication. Holmquist JR et al. (2018). Accuracy and Precision of Tidal Wetlands Soil Carbon Mapping in the Conterminous United States. Scientific Reports. DOI:10.1038/s41598-018-26948-7
Authors
- Holmquist, James ;
- Windham-Myers, Lisamarie ;
- Bliss, Norman ;
- Crooks, Stephen ;
- Morris, James T. ;
- Megonigal, Patrick ;
- Troxler, Tiffany ;
- Weller, Donald ;
- Callaway, John ;
- Drexler, Judith ;
- Ferner, Matthew C. ;
- Gonneea, Meagan E. ;
- Kroeger, Kevin D. ;
- Schile-Beers, Lisa M ;
- Woo, Isa ;
- Buffington, Kevin ;
- Boyd, Brandon M. ;
- Breithaupt, Joshua ;
- Brown, Lauren N. ;
- Dix, Nicole ;
- A. Hice, Lyndie ;
- P. Horton, Benjamin ;
- MacDonald, Glen M ;
- P. Moyer, Ryan ;
- Reay, William ;
- Shaw, Timothy ;
- Smith, Erik ;
- M. Smoak, Joseph ;
- Sommerfield, Christopher ;
- Thorne, Karen ;
- J. Velinsky, David ;
- Watson, Elizabeth ;
- Wilson Grimes, Kristen ;
- Woodrey, Mark