 The adaptive cycle is a heuristic model developed by C.S. Hohling for understanding macro processes of change in ecosystems. However, the adaptive cycle is equally applicable to any complex adaptive system. It can be used to identify structural patterns in both ecosystems as well as social systems as they go through non-linear processes of change. Systems change is about changing complex adaptive systems, i.e. living systems. So understanding these inherent processes of change in living dynamical systems will be of great value. The model describes how complex adaptive systems evolve in terms of four phases, with these four phases being exploitation, conservation, release, and reorganization. The first stage of exploitation is one of a new environment. It is one of growth, a time of expansion and increasing complexity. A system in the exploitation stage has successfully reoriented post-crisis, and there is now plenty of freely available resources for rapid growth and development, a time dominated by positive feedback and self-organizing processes of assembly. This is a period often marked by abundant resources and entrepreneurial leadership, as the environment has plentiful untapped and uncommitted potentiality that are waiting to be reconfigured into new possibilities. Once kick-started along a growth trajectory, many resource flows are available for experimentation. In the R stage, network connections are established and interdependencies are built. At this stage, positive feedback can work to take hold of some emergent pattern and rapidly scale it up, as might be seen with the exponential growth of a startup company, as it rides the positive feedback loop of economies of scale. The conservation stage is a state of equilibrium, is about control development, and this equilibrium is a time of stability. The system has reached a high level of complexity and connection between its parts. A mature system in the conservation stage dynamically performs at a high level of activity and can be seen to be optimal, exhibiting strong stability. At this stage, negative feedback cycles dominate over positive feedback, but as the system settles into a stable configuration, there is the possibility of rigidity forming. Characteristics of a rigid system include very few key nodes with a high concentration of influence and low diversity both in nodes and pathways. Additionally, a rigid system is brittle and vulnerable to disturbance because of reduced diversity and inability to self-organize. This mature act of specialization weakens resilience by permitting systems to become accustomed to and dependent upon their prevailing conditions. In the event of unanticipated shocks, this dependency reduces the ability of the system to adapt to these changes. The system may become rigid and seemingly indestructible, but stagnation and a lack of flexibility may eventually make the system vulnerable to destruction by an external disturbance. The release phase is one of crisis and collapse when the system is destroyed by an external disturbance. Positive feedback generates dramatic change and the system falls apart as it is pushed out of its stability domain. The test of a system in the release state is its capacity to survive in the face of extreme disturbance or disordered collapse. A system must maintain vital functions throughout the crisis. One of the ways that the diversity maintained through small-scale disturbances contributes to the resilience of the system is by cultivating a large stock of resources from which it can pull during a crisis, both in terms of organizations and their relationships, which is essential for leadership to emerge during the release stage. Emergent leadership occurs when actors not tasked with leadership roles informally assume key positions during the crisis. Failure to survive this stage can result in a complete breakdown of the system cycle. Reorganization is a time when the system begins to recover from falling apart. It is a creative time when change can take a variety of possible directions, that is, the system has the possibility of moving into a variety of new stability domains. Chance can be important to the way the system reorganizes, determining which new stability domain it enters. The growth stage that follows reorganization depends on the course initiated during reorganization. To reorient after crisis, the system must reorganize and reconnect these pathways and node relations. The release stage provides opportunities for new elements to enter and become more prominent in the system, be they species, nutrients, individual people, citizen groups, or institutions. At this stage in the cycle, the probability of several alternative future states is high. The complex adaptive system can reorganize and return to its former regime, shift to a different regime with similar structure, but with changes in feedbacks and dominant processes, or transform into a new regime with novel state variables and feedbacks. As novel societal or ecological groups assemble, some succeed and others fail, and the adaptive cycle may then be repeated. The adaptive cycle is a heuristic model that tells us something about the different stages of the process of evolution. We need to understand these inherent dynamics of complex adaptive systems, because this is how we change them. As noted, no one can change such a system. We have to instead work with this adaptive cycle to enable it to evolve in a certain direction. Without understanding these inherent cycles, or where the system might be in, we have little chance of working with those dynamics and will likely exert our resources in the wrong direction, without success.