Interactions matter—complexity in landscapes and ecosystems
In this review we argue that theories and methodology arising from the field of complex systems form a new paradigm for ecology. Patterns and processes resulting from interactions between individuals, populations, species and communities in landscapes are the core topic of ecology. These interactions form complex networks, which are the subject of intense research in complexity theory, informatics and statistical mechanics. This research has shown that complex natural networks often share common structures such as loops, trees and clusters. The observed structures contribute to widespread processes including feedback, non-linear dynamics, criticality and self-organisation. Simulation modelling is a key tool in studying complex networks and has become popular in ecology, especially in adaptive management. Important techniques include cellular automata and individual-based models. The complex systems paradigm has led to advances in landscape ecology, including a deeper understanding of the dynamics of spatial pattern formation, habitat fragmentation, epidemic processes, and genetic variation. Network analysis reveals that underlying patterns of interactions, such as small worlds and clusters, in food webs and ecosystems have strong implications for their stability and dynamics. These investigations illustrate how complexity theory and associated methodologies are transforming ecological research, providing new perspectives on old questions as well as raising many new ones.