Automated Author ProfileMartone, Rebecca
Ministry of Forests, Lands, Natural Resource Operations and Rural Development, Province of British Columbia
Martone, Rebecca
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: 3.9 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This repository contains spatial layers from the analysis in Friesen et al (2021). See "Related Publication". Our objective was to assess how ecological connectivity between MPAs may shift with projected seasonal ocean temperature changes in the Northern Shelf Bioregion in British Columbia, Canada. We used benthic temperature outputs from a regional ocean model of the British Columbia continental margin. These model outputs cover a hindcast simulation (1981-2010) and a future climate projection based on the RCP8.5 scenario (2041-2070). To generate the input layers for the analysis, we first calculated mean seasonal temperatures for each pixel in the two time periods. We also subtracted the hindcast temperature value from the projected future temperature value to determine temperature change, then averaged temperature change across the pixels intersecting each MPA. Second, we modelled suitable habitats for each time period and season based on the adult environmental preferences of two case study species: Metacarcinus magister (Dungeness Crab) and Sebastolobus alascanus (Shortspine Thornyhead). Third, we generated resistance surfaces for each time period and season using the adult environmental preferences of the two case study species. Fourth, we identified MPAs that contained suitable habitats and defined those as network nodes for the connectivity analyses. Once the analysis input layers were generated, we applied least-cost and circuit theory-based tools to identify potential linkages between MPAs via adult movement and compare MPA interconnectedness between the two time periods. Specifically, we used Linkage Mapper to generate least-cost corridors and Pinchpoint Mapper to conduct a seascape-level analysis simulating random exploratory movements within the network. This repository contains the layers from each step of this analysis.
Authors
- Friesen, Sarah K. ;
- Rubidge, Emily ;
- Martone, Rebecca ;
- Hunter, Karen L. ;
- Peña, M. Angelica ;
- Ban, Natalie C.
This is a metadata record for a dataset archived in the Dryad Digital Repository at DOI:10.5061/dryad.ts0jb2s. To download and cite this data, please navigate to https://datadryad.org/stash/dataset/doi:10.5061/dryad.ts0jb2s. This record was created to increase the discoverability of the data. This dataset was used to evaluate ecological connectivity via adult movement using network centrality metrics, multiplex network structures, and network density in the Northern Shelf Bioregion, British Columbia, Canada. Input data for these analyses were obtained from the BC Marine Conservation Analysis (data sources: SciTech Environmental Consulting, Parks Canada, Province of British Columbia, Pacific Estuary Conservation Program).
Authors
- Friesen, Sarah ;
- Martone, Rebecca ;
- Rubidge, Emily ;
- Baggio, Jacopo A. ;
- Ban, Natalie