Automated Author ProfileRengstorf, Anna M
Rengstorf, Anna M
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: 3.8 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
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Datasets
This is the original abstract of the paper: Cold-water corals (CWCs) form large mounds on the seafloor that are hotspots of biodiversity in the deep sea, but it remains enigmatic how CWCs can thrive in this food-limited environment. Here, we infer from model simulations that the interaction between tidal currents and CWC-formed mounds induces downwelling events of surface water that brings organic matter to 600-m deep CWCs. This positive feedback between CWC growth on carbonate mounds and enhanced food supply is essential for their sustenance in the deep sea and represents an example of ecosystem engineering of unparalleled magnitude. This 'topographically-enhanced carbon pump' leaks organic matter that settles at greater depths. The ubiquitous presence of biogenic and geological topographies along ocean margins suggests that carbon sequestration through this pump is of global importance. These results indicate that enhanced stratification and lower surface productivity, both expected consequences of climate change, may negatively impact the energy balance of CWCs. In this data repository, we store the model output as 4 csv files: lon: longitude of each model box lat: latitude of each model box iscoral: a 0/1 matrix indicating whether corals are predicted to be present (1) or absent (0) as returned from the habitat suitability model of Rengstorf et al. (see paper for details) MeanCordepo: a matrix with mean OC deposition rates (mmol C m-2 d-1, averaged over the 3 months of model run, see paper) of the model run with corals present (i.e. the data underlying Fig. 5A).
Authors
- Soetaert, Karline ;
- Mohn, Christian ;
- Rengstorf, Anna M ;
- Grehan, Anthony J ;
- van Oevelen, Dick
The present data set was used as a training set for a Habitat Suitability Model. It contains occurrence (presence-only) of living Lophelia pertusa reefs in the Irish continental margin, which were assembled from databases, cruise reports and publications. A total of 4423 records were inspected and quality assessed to ensure that they (1) represented confirmed living L. pertusa reefs (so excluding 2900 records of dead and isolated coral colony records); (2) were derived from sampling equipment that allows for accurate (<200 m) geo-referencing (so excluding 620 records derived mainly from trawling and dredging activities); and (3) were not duplicated. A total of 245 occurrences were retained for the analysis. Coral observations are highly clustered in regions targeted by research expeditions, which might lead to falsely inflated model evaluation measures (Veloz, 2009). Therefore, we coarsened the distribution data by deleting all but one record within grid cells of 0.02° resolution (Davies & Guinotte 2011). The remaining 53 points were subject to a spatial cross-validation process: a random presence point was chosen, grouped with its 12 closest neighbour presence points based on Euclidean distance and withheld from model training. This process was repeated for all records, resulting in 53 replicates of spatially non-overlapping sets of test (n=13) and training (n=40) data. The final 53 occurrence records were used for model training.
Authors
- Rengstorf, Anna M ;
- Yesson, Chris ;
- Brown, Colin ;
- Grehan, Anthony J
This dataset contains raster grids in GeoTIFF format describing the habitat suitability for living Lophelia pertusa reefs in the Irish continental margin (extended continental shelf claim). The habitat suitability map is given in continuous and binary (based on the 10th percentile threshold) format. The geographic extent is 25°53.801'W - 6°42.401'W and 46°45.033'N - 57°27.033'N. The spatial resolution is 0.01°x0.01°. The map projection is WGS 1984.
Authors
- Rengstorf, Anna M ;
- Yesson, Chris ;
- Brown, Colin ;
- Grehan, Anthony J