Critical Transitions Midterm Report Keith Heyde Diks et

Critical Transitions Midterm Report Keith Heyde

Diks et al. 2012

What Are Critical Transitions?

Early Warning Signs 1) Critical Slowing 2) Asymmetry of Fluctuation 3) Flickering (with stochastic magnitude)

Predicting Critical Transitions: Case Study Lake Eutrophication Wang et al. 2012

Critical Slowing Slow Perturbation Recovery Increased autocorrelation Increased Variance - The focus of my analysis thus far has been identifying critical slowing in certain metrics

Previous Successful (Published) Examples Stock Market (mixed results) Climate – Flickering and critical slowing at Younger Dryas Cold Period Ecosystems- Vegetation and Desertification Agri/Aquaculture- Fishing stocks Neurological- Epilepsy/ Depression Leemput et al. 2013

Methods Pursued Find Sample Data Understand potential chaotic drop If smooth add noise (matlab) If ‘stochastic’ leave as is Examine autocorrelation and skewness

Examples Pursued Splitting States Nationalization/Privatization of Industry - Mining in Chile - Oil Reserves in Latin America country) (country by Venture capital Investment patterns by industry In all cases data was taken from The Economist (in turn taken from primary sources)

Moving forward: Predicting Antibiotic Resistance 1) Normal (mutation) Death Response 2) Altruistic Death Response Yurtsev et al.

Moving Forward Cont. . • Parameters: public good production (B 2) • Multiple equilibria (including zero) • Sample data processing within MATLAB (autocorrelation and variance analysis) Tanouchi et al. 2012

Have a Great Day! And thanks to Prof. Ross for all the help!