Presented by George Sugihara, Scripps Institute for Oceanography

Abstract: While everyone knows Berkeley’s 1710 dictum “correlation does not imply causation” few realize that the converse “causation does not imply correlation” is also true. This conundrum runs counter to deeply ingrained heuristic thinking that is at the basis of modern science. Nature is particularly perverse on this issue by exhibiting mirage correlations (associations between variables that come and go and even switch sign) that can continually cause us to rethink relationships we thought we understood. To address this, here we will examine a minimalist paradigm for studying nature, and a method based on attractor reconstruction that can distinguish causality from correlation. It is a radically different equation-free approach for gaining a mechanistic understanding of nature from time series observations that departs from steady-state classical theory (the way that we typically think). The ideas are intuitive and will be illustrated with examples from genomics and ecology. In the latter case, we find that interactions among species in ecosystems do not occur as we typically model them (as constant averages) but are highly episodic, suggesting a very different paradigm involving occasional excursions and bottlenecks.