Complex adaptive systems in the context of "Coupled human–environment system"

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⭐ Core Definition: Complex adaptive systems

A complex adaptive system (CAS) is a system that is complex in that it is a dynamic network of interactions, but the behavior of the ensemble may not be predictable according to the behavior of the components. It is adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events. It is a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure. The Complex Adaptive Systems approach builds on replicator dynamics.

The study of complex adaptive systems, a subset of nonlinear dynamical systems, is an interdisciplinary matter that attempts to blend insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior.

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👉 Complex adaptive systems in the context of Coupled human–environment system

A coupled human–environment system (known also as a coupled human and natural system, or CHANS) characterizes the dynamical two-way interactions between human systems (e.g., economic, social, cultural) and natural (e.g., hydrologic, atmospheric, biological, geological) systems. This coupling expresses the idea that the evolution of humans and environmental systems may no longer be treated as individual isolated systems. The complexity that CHANS research reveals is useful to inform policy decisions regarding environmental sustainability.

CHANS research is a broad field. Some research programs draw from, and build on, the perspectives developed in trans-disciplinary fields such as human ecology, ecological anthropology, environmental geography, economics, as well as others. In contrast, other research programs, such as Critical Zone science, aim to develop a more quantitative theoretic framework focusing on the development of analytical and numerical models, by building on theoretical advances in complex adaptive systems, complexity economics, dynamical systems theory, and the earth sciences. To some extent, all CHANS programs recognize the need to move beyond traditional research methods developed in the social and natural sciences, as these are not sufficient to quantify the highly nonlinear dynamics often present in CHANS. Some research into CHANS emulates the more traditional research programs that tended to separate the social from the ecological sciences.

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