Ethan Deyle is a Research Assistant Professor of Biology at the Boston University Marine Program. He is foremost a quantitative ecologist, and his research sits at the intersection of ecological theory, mathematical methods, practical questions, and observational data. There are generally four interrelated and mutually reinforcing branches: (1) general ecological and complex systems theory, (2) practical, applied ecological research to coupled human-natural systems, (3) development of quantitative methods, and (4) studying similar nonlinear/complex systems problems in other domains of biology and natural science. The key instrument of his research has been empirical dynamic modeling—a set of quantitative tools based on using attractor reconstruction to understand and predict nonlinear ecosystems directly from time-series data. The techniques are data-driven and equation-free, and thus have been able to yield insights and find traction where traditional methods like Gaussian statistics or parametric modeling struggle. It is a data science for natural systems, that can be employed to test existing hypotheses and theory from observational data or to do system and hypothesis exploration. Science regularly boils down to questions about causality and mechanism, and thus focusing on time-series approaches to understanding complex or nonlinear interactions in ecosystems has created a framework with remarkable generality across ecosystems and scales. This includes coastal and open-water fisheries, harmful algal blooms, water quality in deep lakes, and coral reef resilience.