Automated Author ProfileClarke, Charlotte
University of Southampton0000-0002-1296-2229
Clarke, Charlotte
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: 6.6 (sum of 5 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Script to develop the LOI predictive model based on lacustrine samples scanned by means of near infra-red reflectance spectroscopy
Authors
- Ancin-Murguzur, Francisco Javier ;
- Brown, Antony G. ;
- Clarke, Charlotte ;
- Sjøgren, Per ;
- Svendsen, John Inge ;
- Alsos, Inger Greve
README file
Authors
- Ancin-Murguzur, Francisco Javier ;
- Brown, Antony G. ;
- Clarke, Charlotte ;
- Sjøgren, Per ;
- Svendsen, John Inge ;
- Alsos, Inger Greve
This dataset contains the reference data and script to develop a predictive NIRS model to measure LOI in lacustrine sediments, as described in the article: How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
Authors
- Ancin-Murguzur, Francisco Javier ;
- Brown, Antony G. ;
- Clarke, Charlotte ;
- Sjøgren, Per ;
- Svendsen, John Inge ;
- Alsos, Inger Greve
Reference dataset containing the spectral values, LOI values and lake ID
Authors
- Ancin-Murguzur, Francisco Javier ;
- Brown, Antony G. ;
- Clarke, Charlotte ;
- Sjøgren, Per ;
- Svendsen, John Inge ;
- Alsos, Inger Greve
Plants adapted to extreme conditions can be at high risk from climate change; arctic-alpine plants, in particular, could “run out of space” as they are out-competed by expansion of woody vegetation. Mountain regions could potentially provide safe sites for arctic-alpine plants in a warmer climate, but empirical evidence is fragmentary. Here we present a 24,000-year record of species persistence based on sedimentary ancient DNA (sedaDNA) from Lake Bolshoye Shchuchye (Polar Urals). We provide robust evidence of long-term persistence of arctic-alpine plants through large-magnitude climate changes but document a decline in their diversity during a past expansion of woody vegetation. Nevertheless, most of the plants that were present during the last glacial interval, including all of the arctic-alpines, are still found in the region today. This underlines the conservation significance of mountain landscapes via their provision of a range of habitats that confer resilience to climate change, particularly for arctic-alpine taxa.
Authors
- Clarke, Charlotte ;
- Edwards, Mary ;
- Gielly, Ludovic ;
- Ehrich, Dorothee ;
- Hughes, Paul ;
- Morozova, Liudmila ;
- Haflidason, Haflidi ;
- Mangerud, Jan ;
- Svendsen, John Inge ;
- Alsos, Inger