Automated Author ProfileWangensteen, Owen S.
University of Salford
Wangensteen, Owen S.
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
Here we pilot a novel, rapid and non-invasive environmental DNA (eDNA) metabarcoding approach specifically targeted to infer shark presence, diversity and eDNA read abundance in tropical habitats. We identified at least 21 shark species, from both Caribbean and Pacific Coral Sea water samples, whose geographical patterns of diversity and read abundance coincide with geographical differences in levels of anthropogenic pressure and conservation effort. We demonstrate that eDNA metabarcoding can be effectively employed to study shark diversity.
Authors
- Bakker, Judith ;
- Wangensteen, Owen S. ;
- Demian D. Chapman ;
- Boussarie, Germain ;
- Dayne Buddo ;
- Guttridge, Tristan L. ;
- Hertler, Heidi ;
- Mouillot, David ;
- Vigliola, Laurent ;
- Mariani, Stefano
Here we pilot a novel, rapid and non-invasive environmental DNA (eDNA) metabarcoding approach specifically targeted to infer shark presence, diversity and eDNA read abundance in tropical habitats. We identified at least 21 shark species, from both Caribbean and Pacific Coral Sea water samples, whose geographical patterns of diversity and read abundance coincide with geographical differences in levels of anthropogenic pressure and conservation effort. We demonstrate that eDNA metabarcoding can be effectively employed to study shark diversity.
Authors
- Bakker, Judith ;
- Wangensteen, Owen S. ;
- Demian D. Chapman ;
- Boussarie, Germain ;
- Dayne Buddo ;
- Guttridge, Tristan L. ;
- Hertler, Heidi ;
- Mouillot, David ;
- Vigliola, Laurent ;
- Mariani, Stefano
Given their positioning and biological productivity, estuaries have long represented key providers of ecosystem services, and consequently remain under remarkable pressure from numerous forms of anthropogenic impact. The monitoring of fish communities in space and time are one of the most widespread and established approaches to assess the ecological status of estuaries and other coastal habitats, but traditional fish surveys are invasive, costly, labour intensive and highly selective. Recently, the application of metabarcoding techniques, on either sediment or aqueous environmental DNA, has rapidly gained popularity. Here, we evaluate the application of a novel, high through-put DNA-based monitoring tool to assess fish diversity, based on the analysis of the gut contents of a generalist predator/scavenger, the European brown shrimp, Crangon crangon. Sediment and shrimp samples were collected from eight European estuaries and DNA metabarcoding (using both 12S and COI markers) was carried out to infer fish assemblage composition. We detected 32 teleost species (16 and 20, for 12S and COI respectively). Twice as many species were recovered using metabarcoding than by traditional net surveys. By comparing and interweaving trophic, environmental DNA and traditional survey-based techniques, we show that the DNA-assisted gut content analysis of a ubiquitous, easily accessible, generalist species may serve as a powerful, rapid and cost-effective tool for large scale, routine estuarine biodiversity monitoring.
Authors
- Siegenthaler, Andjin ;
- Wangensteen, Owen S. ;
- Soto, Ana Z. ;
- Benvenuto, Chiara ;
- Corrigan, Laura ;
- Mariani, Stefano
A thorough understanding of ecological networks relies on comprehensive information on trophic relationships among species. Since unpicking the diet of many organisms is unattainable using traditional morphology‐based approaches, the application of high‐throughput sequencing methods represents a rapid and powerful way forward. Here, we assessed the application of DNA‐metabarcoding with nearly universal primers for the mitochondrial marker cytochrome c oxidase I (COI) in defining the trophic ecology of adult brown shrimp, Crangon crangon, in six European estuaries. The exact trophic role of this abundant and widespread coastal benthic species is somewhat controversial, while information on geographical variation remains scant. Results revealed a highly opportunistic behaviour. Shrimp stomach contents contained hundreds of taxa (>1000 molecular operational taxonomic units), of which 291 were identified as distinct species, belonging to 35 phyla. Only twenty ascertained species had a mean relative abundance of more than 0.5%. Predominant species included other abundant coastal and estuarine taxa, including the shore crab Carcinus maenas and the amphipod Corophium volutator. Jacobs’ selectivity index estimates based on DNA extracted from both shrimp stomachs and sediment samples were used to assess the shrimp's trophic niche indicating a generalist diet, dominated by crustaceans, polychaetes and fish. Spatial variation in diet composition, at regional and local scales, confirmed the highly flexible nature of this trophic opportunist. Furthermore, the detection of a prevalent, possibly endoparasitic fungus (Purpureocillium lilacinum) in the shrimp's stomach demonstrates the wide range of questions that can be addressed using metabarcoding, towards a more robust reconstruction of ecological networks.
Authors
- Siegenthaler, Andjin ;
- Wangensteen, Owen S. ;
- Benvenuto, Chiara ;
- Campos, Joana ;
- Mariani, Stefano