Automated Author Profile[email protected] [email protected]
[email protected] [email protected]
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: 0.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
We distribute the output data from our global simulation of wetlands affected by agricultural runoff. The computational domain involves about 25,000 grid cells globally distributed describing the wetlands, and neglects lakes, rivers, rice paddies, saline estuaries, salt marshes, and reservoirs (Poulter et al., 2017). We include 14 maps and videos for the principal greenhouse gasses GHG (CH4, CO2, and N2O), wetland extension area, soil temperature, soil moisture, long-term average soil pH, carbon input, long-term average annual carbon, long-term average soil carbon, nitrogen, and sulfur sequestration rate. This data release includes also the following plant-dependent variables: CH4 plant emission efficiency for aerenchyma transport, C:N and C:S ratio of litter in grassland, forest, and shrubland, N2 fixation rate in grassland, forest, shrubland, and wetland, and the average root density for forest, grassland, shrublands, and wetland.
We distribute the output data from our global simulation of wetlands affected by agricultural runoff. The computational domain involves about 25,000 grid cells globally distributed describing the wetlands, and neglects lakes, rivers, rice paddies, saline estuaries, salt marshes, and reservoirs (Poulter et al., 2017). We include 14 maps and videos for the principal greenhouse gasses GHG (CH4, CO2, and N2O), wetland extension area, soil temperature, soil moisture, long-term average soil pH, carbon input, long-term average annual carbon, long-term average soil carbon, nitrogen, and sulfur sequestration rate. This data release includes also the following plant-dependent variables: CH4 plant emission efficiency for aerenchyma transport, C:N and C:S ratio of litter in grassland, forest, and shrubland, N2 fixation rate in grassland, forest, shrubland, and wetland, and the average root density for forest, grassland, shrublands, and wetland.