The problem of understanding natural systems is that they observably change organization and behave by smoothly flowing processes, which are seen changing everywhere at once all the time to do it... That's not like an equation. I found a very productive new kind of diagnostic physics for monitoring their organizational development processes, greatly aided by finding them to normally develop as locally evolving autonomous networks. The great advantage of the approach is that it allows me to separately study nature's own complex processes and the theories we need to help us predict and characterize them. Recognizing those differences is the source of the most productive questions that method generates.
Understanding comes from studying them as whole internalized networks of relationships, much as if individual organisms with energy resource throughputs. They exhibit periods of stable organizational development that go through a natural succession of changing types, typically producing inflection points in the empirical curves reflecting measures of their processes where they transition. That way the method builds on a combination of basic principles of mathematical continuity, the physics of energy conservation and empirical study of the natural successions of organizational development processes. For more detail see my research blog, Reading Nature's Signals, and my research CV, publications list and online bio.