EDM Readings and Resources recommended by George Sugihara

I. Summary Readings:

  • Causation: http://www.sciencemag.org/content/338/6106/496.full?keytype=ref&siteid=sci&ijkey=GzlL9h2cAY51A

  • Model-free: http://www.wired.com/2015/10/is-it-foolish-to-model-natures-complexity-with-equations/

  • PNAS Commentary: http://www.pnas.org/content/112/13/3856.short

  • Frequent Asked Questions About EDM: https://academic.oup.com/icesjms/article/77/4/1463/5643857

II.Essential Resource:

The rEDM package on CRAN is a key resource that contains a tutorial that many have found useful. It consists of code and vignettes with data that will help implementing EDM analysis.

  • rEDM package: https://cran.r-project.org/web/packages/rEDM/vignettes/rEDM-tutorial.pdf
  • rEDM Get Started!: https://ha0ye.github.io/rEDM/articles/rEDM.html

III. Additional Readings

Describe the two main EDM forecasting methods and a short note addressing time lags in CCM.

  • Simplex (1990): http://www.nature.com/nature/journal/v344/n6268/abs/344734a0.html

  • S-maps original paper (1994): http://rsta.royalsocietypublishing.org/content/348/1688/477

  • S-maps. Deyle et al (2016) - contrary to classic model assumptions shows for the first time that ecological interactions are episodic: http://rspb.royalsocietypublishing.org/content/283/1822/20152258

  • CCM with time lags. Ye et al (2015): https://www.nature.com/articles/srep14750

IV. Mathematical-Theoretical Background Readings

  • Embedology: Sauer, Yorke, Casdagli (1991). An excellent summary of state space reconstruction results: https://link.springer.com/article/10.1007%2FBF01053745

  • Deyle and Sugihara (2011): http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0018295

  • Ye and Sugihara Science 2016: Multiview Embedding (information leverage): http://science.sciencemag.org/content/353/6302/922/tab-figures-data

V. Supplementary Readings with Case Examples

  • Dixon et al Science (1999): http://science.sciencemag.org/content/283/5407/1528.full, http://deepeco.ucsd.edu/~george/publications/01_noise_nonlinearity.pdf

  • McGowan et al Ecology (2017) SIO Red tides: http://onlinelibrary.wiley.com/doi/10.1002/ecy.1804/full Hsieh et al Nature (2006): https://www.nature.com/articles/nature03553

  • Ye et al PNAS (2015): http://www.pnas.org/content/112/13/E1569

  • Glasser et al (2014): http://onlinelibrary.wiley.com/doi/10.1111/faf.12037/full

  • Deyle et. al. (2013): Climate effects on pacific sardines. Explains scenario exploration with EDM: http://www.pnas.org/content/110/16/6430.full

  • Deyle et. al. (2016):Global Environmental Drivers of Flu. An interesting use of scenario exploration to discover a temperature threshold (75F) below which absolute humidity inhibits flu transmission and above which it promotes flu transmission: http://www.pnas.org/content/113/46/13081.full

  • Ushio et. al. (2019):Fluctuating interaction network and time-varying stability of a natural fish community. A use of EDM to reveal a network of interaction between organism into acquatic ecosystem: https://www.nature.com/articles/nature25504

  • Runge et. al. (2019):Inferring causation from time series in Earth system sciences. A perspective for a intesive use of the framework of EDM to reveal and produce more direct inference of causality to better understand and better overview the Earth System: https://www.nature.com/articles/s41467-019-10105-3

VI. Ancillary:

YouTube Playlist of 3 one-minute Animations (from the supplement of the Causality paper in Science 2012): http://www.youtube.com/watch?v=fevurdpiRYg&list=PL-SSmlAMhY3bnogGTe2tf7hpWpl508pZZ