More than the sum of its parts: Self-organized patterns and emergent properties of ecosystems

Abstract

Over the past 30 years, the self-organization theory has effectively explained the regular spatial patterning of ecosystems and has led to a proliferation of studies investigating spatial patterns in ecology and biology. Indeed, the emergent properties generated by this self-organization process are now recognized as critical to ecosystem functioning. Here, we review this important theoretical framework by assessing the definition and development of the concept of self-organization and by evaluating two fundamental theoretical principles of self-organization theory, the Turing principle and the phase separation principle. We further describe the mathematical models of each principle in the context of different, unique ecosystems, and explain the emergent properties of the Turing principle on ecosystem functioning and the phase separation principle on cell functions, respectively. Finally, we propose three promising future developments for ecological self-organization theory: multi-scale self-organization patterns, transient patterns, and individual behavioral self-organization. Our review provides an assessment of this fundamental ecological theory and offers exciting new research directions and applications.