Automated Author ProfileRobuchon, Marine
Centre National de la Recherche Scientifique
Robuchon, Marine
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: 0.7 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Aim: Dispersal limitation, environmental selection and drift are known to influence both taxonomic similarity between communities and genetic similarity between populations. However, disentangling the relative roles of these processes on spatial patterns of differentiation - whether regarding taxonomic differentiation between communities or genetic differentiation between populations - is challenging. Investigating whether spatial patterns of taxonomic differentiation and genetic differentiation are correlated (β-SGDCs) is a promising approach to address this issue. Here, we investigated β-SGDCs over broad spatial scales and 22 freshwater fish species to elucidate the processes shaping taxonomic and genetic differentiations between drainage basins. Location: Global scope, data mainly from Europe and North America. Taxon: Actinopterygii and Petromyzontiformes (freshwater fishes). Methods: We used Mantel tests to investigate the raw correlation between taxonomic and genetic differentiations. We carried out multiple regressions to characterise the effects of geographic distance (proxy of dispersal limitation), environmental distance (proxy of environmental selection) and pairwise harmonic mean area between basins (proxy of drift) on taxonomic differentiation and genetic differentiation taken separately. We then analysed the correlation between the residuals of these two regressions with Mantel tests. Finally, we investigated whether the variation in β-SGDC between species was related to species traits. Results: We detected an overall positive β-SGDC, both for the raw and the residual correlations. This implies that, unmeasured effects, other than geographic distance, environmental distance and harmonic mean area, influence the β-SGDC observed. Values of β-SGDCs greatly varied between species, but this was not explained by any species traits. Main conclusions: Independently of the effects of geographic distance, environmental distance and harmonic mean area, the β-SGDC we observed suggests that historical processes strongly shaped the patterns of taxonomic and genetic differentiations between basins. Consequently, taxonomic differentiation may be an appropriate proxy to explain the influence of historical processes on genetic differentiation.
Authors
- Robuchon, Marine ;
- Leroy, Boris ;
- Jézéquel, Céline ;
- Hugueny, Bernard