Automated Organization ProfileNational Ice Core Laboratory
National Ice Core Laboratory
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization'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: 4.7 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This data release includes metadata and tabular data that documents the distribution of yellow crazy ants (Anoplolepis gracilipes) across Wake Atoll. The three islands that comprise the atoll were systematically searched by hand. The dataset describes the outcome of searching 3,675 cells, each 50 x 50 m in size, during 6-21 October 2023. .
Authors
- Robert W Peck ;
- Sheldon Plentovich ;
- Elyse Sachs
Multi-species recovery planning can be a challenging natural resource management task. In collaboration with state and federal agencies, and botanical and technical experts, we developed and tested a multi-step optimization process to assist in identifying the minimum climate resilient habitat for the recovery of multiple threatened, endangered, and at-risk plant species across east Maui. Data include the underlying land-use configuration file, predictive climate models, list of plant species and number of populations to recover/protect, habitat and forest bird distribution information, presence of fencing, land management status, and naming protocol file. We identified a suite of potential conservation footprints that are constrained by ecological and resource management selection criteria based input and co-production with botanical experts and resource managers. These solutions include recovery habitat for all species of interest. The optimization process also identified priority recovery planning units, equal to the number of populations required for recovery, to inform find-scale recovery efforts. Data include: 1) underlying land-use configuration and input metrics used for optimization, input_metrics.gpkg; 2) species list, species_list.csv; 3) and output metrics from an example solution, pu_solution_example.gpkg.
Authors
- Christina Leopold ;
- Lucas Fortini ;
- Fred Amidon ;
- Scott Fretz ;
- James D Jacobi ;
- Loyal Mehrhoff ;
- Robert Sutter
This data release includes data and metadata containing documentation of 1) ambrosia beetle (Coleoptera: Curculionidae) species caught in cross-vane panel traps (CVPT) in ʻōhiʻa (Metrosideros polymorpha) dominated forests with geographical locations and elevations and 2) ambrosia beetle species reared directly from cut ʻōhiʻa tree sections (bolts) infected with Rapid ʻŌhiʻa Death (ROD)-causing pathogens at various elevations from Kauaʻi, HI USA. Data were used in a study describing bark and ambrosia beetles associated with ROD and ʻōhiʻa lehua forests on Kauaʻi.
Authors
- Ellen J Dunkle ;
- Kylle Roy ;
- Roshan Manandhar ;
- Michelle Clark ;
- Kalli Harshman ;
- Robert W Peck