Automated Author Profile

Vorselen, Daan

Vrije Universiteit Amsterdam

Current S-Index

2.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

2.6

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

76.9%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Generic indicators for loss of resilience before a tipping point leading to population collapse (Version: 1)

Theory predicts that the approach of catastrophic thresholds in natural systems (e.g., ecosystems, the climate) may result in an increasingly slow recovery from small perturbations, a phenomenon called critical slowing down. We used replicate laboratory populations of the budding yeast Saccharomyces cerevisiae for direct observation of critical slowing down before population collapse. We mapped the bifurcation diagram experimentally and found that the populations became more vulnerable to disturbance closer to the tipping point. Fluctuations of population density increased in size and duration near the tipping point, in agreement with the theory. Our results suggest that indicators of critical slowing down can provide advance warning of catastrophic thresholds and loss of resilience in a variety of dynamical systems.

Authors

  • Dai, Lei ;
  • Vorselen, Daan ;
  • Korolev, Kirill S. ;
  • Gore, Jeff
2 Citations0 Mentions77% FAIR2.6 Dataset Index
10.5061/dryad.p2481134June 2012