- NSF goals:
- combine control methods and warning signals
- do non-parametric or machine learning increase or decrease chance of transition
- Further areas (from comment piece)
- baselines (statistical; emperical)
- context-specific (additional data sources, reflecting context in model)
Warning signals in managed systems
Estimating Stability in managed systems
Recovery rate in optimally fished vs unfished system (based on the OU model): stability.md
- How would a use of a signal feed back into a control algorithm? Need probabilities of possible models for driving a belief SDP?
Learning about a tipping point: models are the correct allee-threshold (Myers) model, and the best-fit Beverton Holt model. Inability to learn fast enough leads to crashes model_uncertainty.md
- Active learning about parameters can be worse than not learning?