Automated Author ProfileAmarasekare, Priyanga
Amarasekare, Priyanga
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: 7.6 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
No description available
Authors
- Uszko, Wojciech ;
- Diehl, Sebastian ;
- Englund, Göran ;
- Amarasekare, Priyanga
We develop a theoretical framework to elucidate the mechanistic basis of thermal niche partitioning in ectotherms. Using a food web module of two consumers competing for a biotic resource, we investigate how temperature effects on species' attack and mortality rates scale up to population-level outcomes of coexistence and exclusion. We find that species' differences in competitive effects arise from asymmetries generated by the non-linear temperature response of mortality: cold-adapted species experience stronger intra-specific competition than warm-adapted species; they also exert weaker competition on, and experience stronger competition from, warm-adapted species. These asymmetries become greater as seasonal fluctuations increase, generating latitudinal variation in coexistence and priority effects. Characterizing species' thermal niches in terms of mechanistic descriptions of trait responses allows for testable predictions about population-level competitive outcomes based solely on three fundamental, and easily measurable, quantities: attack rate optima, response breadths and temperature sensitivity of mortality. We test our predictions with data from an insect host-parasitoid community. By quantifying the three basic quantities we predict that priority effects cannot occur, which is borne out by population-level experiments showing that the outcome of competition does not depend on initial conditions. More broadly, our framework can predict the conditions under which exotic invasive species can exclude, or coexist with, native biota, and the effects of climate warming on competitive communities across latitudinal gradients.
Authors
- Smith, Daniel J. ;
- Amarasekare, Priyanga
No description available
Authors
- Amarasekare, Priyanga