Automated Author ProfilePoynter, Sarah
Poynter, Sarah
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: 0.4 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This paper uses an extensive dataset from more than 200 samples to provide a comprehensive source-to-sink analysis of the Amur River and its delta in the Russian Far East. The majority of sand-sized sediment in the Amur River and its former delta comes from upstream of the Lesser Khingan Ridge, shown by uniformity of sediment composition in the lower 1700 km of the river. Stable mineral ratios, U–Pb age spectra and garnet geochemistry show little stratigraphic provenance-specific variation in the Neogene delta. This renders Miocene–Pliocene drainage capture models unlikely. The onset of uplift in the delta is marked by a decrease in the apatite–tourmaline index (ATi) in Upper Pliocene offshore well samples, caused by dissolution of apatite as sediments were uplifted and eroded onshore Sakhalin. These wells also show variable ATi and garnet–zircon index (GZi) values in Lower Miocene samples, which could potentially be used for stratigraphic correlation. A positive correlation between GZi values and distance from the river mouth is attributed to hydrodynamic sorting across the delta system. This has negative implications for the use of this stable mineral index and others of a similar hydraulic equivalence as regional correlation tools on a basin scale (>100 km).
Authors
- Nicholson, Uisdean ;
- Poynter, Sarah ;
- Clift, Peter D. ;
- Macdonald, David I. M.
This paper uses an extensive dataset from more than 200 samples to provide a comprehensive source-to-sink analysis of the Amur River and its delta in the Russian Far East. The majority of sand-sized sediment in the Amur River and its former delta comes from upstream of the Lesser Khingan Ridge, shown by uniformity of sediment composition in the lower 1700 km of the river. Stable mineral ratios, U–Pb age spectra and garnet geochemistry show little stratigraphic provenance-specific variation in the Neogene delta. This renders Miocene–Pliocene drainage capture models unlikely. The onset of uplift in the delta is marked by a decrease in the apatite–tourmaline index (ATi) in Upper Pliocene offshore well samples, caused by dissolution of apatite as sediments were uplifted and eroded onshore Sakhalin. These wells also show variable ATi and garnet–zircon index (GZi) values in Lower Miocene samples, which could potentially be used for stratigraphic correlation. A positive correlation between GZi values and distance from the river mouth is attributed to hydrodynamic sorting across the delta system. This has negative implications for the use of this stable mineral index and others of a similar hydraulic equivalence as regional correlation tools on a basin scale (>100 km).
Authors
- Nicholson, Uisdean ;
- Poynter, Sarah ;
- Clift, Peter D. ;
- Macdonald, David I. M.