Detecting causality in complex
systems: its application in ecosystem management
Chih-hao Hsieh (National Taiwan
University)
Identifying causal networks is important for effective policy and
management recommendations on climate, epidemiology, financial regulation, and
much else. Here we introduce a method, based on nonlinear state space
reconstruction, that can distinguish causality from correlation. It extends to nonseparable weakly connected dynamic systems (cases not
covered by the current Granger causality paradigm). The approach is illustrated
both by simple models (where, in contrast to the real world, we know the
underlying equations/relations and so can check the validity of our method) and
by application to real ecological systems, including the controversial
sardine-anchovy-temperature problem.