Nonlinearity means that in complex systems, cause and effect are not directly proportional. Small changes in a system’s input can produce disproportionately large or unexpected outcomes, often due to feedback loops and intricate interdependencies among its parts. This makes predicting behavior challenging, as linear relationships—where doubling an input simply doubles the effect—do not apply.