Automated Author ProfilePetro, Bergita
University of Toronto
Petro, Bergita
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: 2.0 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The timing of transition out of one life history phase determines where in the seasonal succession of environments the next phase is spent. Shifts in the general environment (e.g., seasonal climate) affect the expected fitness for particular transition dates. Variation in transition date also leads to temporal variation in the social environment. For instance, early transition may confer a competitive advantage over later individuals. If so, the social environment will impose frequency- and density-dependent selection components. In effect, the general environment imposes hard selection while the social environment imposes soft selection on phenology. We examined hard and soft selection on seedling emergence time in an experiment on Brassica rapa. In monoculture (uniform social environment), early emergence results in up to a 1.5-fold increase in seed production. In bi-cultures (heterogeneous social environment), early-emerging plants capitalized on their head start, suppressing their late neighbors and increasing their fitness advantage to as much as 38-fold, depending on density. We devised a novel adaptation of contextual analysis to partition total selection (i.e., Cov(ω, z)) into the hard and soft components. Hard and soft components had similar strengths at low density, whereas soft selection was five times stronger than hard at high density.
Authors
- Weis, Arthur E. ;
- Turner, Kyle M. ;
- Petro, Bergita ;
- Austen, Emily J. ;
- Wadgymar, Susana M.