Detecting predictability in complex ecosystems

A couple people pointed me to a recent article, “Detecting Causality in Complex Ecosystems,” by fisheries researchers George Sugihara, Robert May, Hao Ye, Chih-hao Hsieh, Ethan Deyle, Michael Fogarty, and Stephan Munch.

I don’t know anything about ecology research but I could imagine this method being useful in that field. I can’t see the approach doing much in political science, where I think their stated goal of “identifying causal networks” is typically irrelevant.

That said, if you replace the word “causality” by “predictability” everywhere in the paper, it starts to make a lot more sense. As they write, they are working within “a framework that uses predictability as opposed to correlation to identify causation between time-series variables.” Setting causation aside, predictability is an important topic in itself. The search for patterns of predictability in complex structures may motivate causal hypotheses that can be studied more directly, using more traditional statistical designs such as experiments and observational studies.