Automated Author ProfileXie, Zi-xuan
Nanjing Agricultural University
Xie, Zi-xuan
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: 2.2 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent platform for addressing topics in long-term evolution and paleobiology, such as mass extinction and recovery, with experimental evolutionary approaches. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths, along with unperturbed control experiments. We examined how stability in the digital communities was affected from the perspectives of division of labor, relative shift in rank abundance, and genealogical connectedness of the community's component ecotypes. Mass extinction that was due to a Strong Press treatment was most effective in producing reshaped communities that differed from the pre-treatment ones in all of the measured perspectives; weaker versions of the treatments did not generally produce significant departures from a Control treatment; and results for the Strong Pulse treatment generally fell between those extremes. The Strong Pulse treatment differed from others in that it produced a slight but detectable shift towards more generalized communities. Compared to Press treatments, Pulse treatments also showed a greater contribution from re-evolved ecological doppelgangers rather than new ecotypes. However, relatively few Control communities showed stability in any of these metrics over the whole course of the experiment, and most did not represent stable states (by some measure of stability) that were disrupted by the extinction treatments. Our results have interesting, broad qualitative parallels with findings from the paleontological record, and show the potential of digital evolution studies to illuminate many aspects of mass extinction and recovery by addressing them in a truly experimental manner.
Authors
- Luo, Tian-tong ;
- Heier, Lise ;
- Khan, Zaki Ahmad ;
- Hasan, Faraz ;
- Reitan, Trond ;
- Yasseen III., Abdool S. ;
- Xie, Zi-xuan ;
- Zhu, Jian-long ;
- Yedid, Gabriel