 Kellert first focuses on one of the key intuitions driving many views in debates on scientific explanation: Namely, that the sciences provide understanding or insight into phenomena. Chaos explanations, according to Kellert, achieve understanding by constructing, elaborating and applying simple dynamical models. He gives three points of contrast between this approach to understanding and what he takes to be the standard approach to understanding in the sciences. The first is that chaos explanations involve models that are holistic rather than microreductionist. Models of the latter type seek to break systems down into their constituent parts and look for law-like relations among the parts. In contrast, many of the mathematical tools of chaotic dynamics are holistic in that they extract or reveal information about the behavior of the model system as a whole not readily apparent from the nonlinear equations of the model themselves. Methods such as state space reconstruction and sections-of-surface can reveal information implicit in the nonlinear equations. Developing one- and two-dimensional maps from the model equations can also provide this kind of information directly, and are much simpler than the full model equations. 