A resilience-based framework for evaluating adaptive co-management: Linking ecology, economics and society in a complex world

Adaptive co-management brings together collaborative and adaptive approaches in pursuit of sustainable resource use and social-ecological resilience. Enthusiasm for this management approach, however, is countered by recent critiques regarding outcomes. A lack of evidence from consistent evaluation of adaptive co-management further exacerbates this situation. This paper revisits the issue of evaluation in natural resource management and recasts it in light of complex adaptive systems thinking. An evaluative framework for adaptive co-management is developed which directs attention toward three broad components: ecosystem conditions, livelihood outcomes and process and institutional conditions. Scale-specific parameters are offered for each component to facilitate systematic learning from experience and encourage cross-site comparisons. Conclusions highlight the importance of systematically incorporating evaluation into the adaptive co-management process and recognize the challenge for resource agencies and researchers to shift from a conventional to a complex adaptive system perspective.     

A complex systems methodology to transition management

There is a general sense of urgency that major technological transitions are required for sustainable development. Such transitions are best perceived as involving multiple transition steps along a transition path. Due to the path dependent and irreversible nature of innovation in complex technologies, an initial transition step along some preferred path may cut off paths that later may turn out to be more desirable. For these reasons, initial transition steps should allow for future flexibility, where we define flexibility as robustness regarding changing evidence and changing preferences. We propose a technology assessment methodology based on rugged fitness landscapes, which identifies the flexibility of initial transition steps in complex technologies. We illustrate our methodology by an empirical application to 2,646 possible future car systems.

Seven tools for creating adaptive policies

Experience demonstrates that policies crafted to operate within a certain range of conditions are often faced with unexpected challenges outside of that range. The result is that many policies have unintended impacts and do not accomplish their goals. Adaptive policies are designed to function more effectively in complex, dynamic, and uncertain conditions. Based on over a dozen case studies on public policies relating to agriculture and water resources management in Canada and India, we conclude that there are seven tools policymakers should follow to create adaptive policies. Adaptive policies anticipate and plan for the array of conditions that lie ahead: (#1) using integrated and forward-looking analysis; (#2) monitoring key performance indicators to trigger built-in policy adjustments; (#3) undertaking formal policy review and continuous learning; and (#4) using multi-stakeholder deliberation. But not all situations can be anticipated. Unknown unknowns and deep uncertainty will always be part of policymaking. Adaptive policies are able to navigate toward successful outcomes in settings that cannot be anticipated in advance. This can be done by working in concert with certain characteristics of complex adaptive systems and thereby facilitating autonomous actions among stakeholders on the ground. To a degree, adaptive policy tools #3 and #4 can be used toward this purpose, but most directly, such autonomous tools include: (#5) enabling self-organization and social networking; (#6) decentralizing decisionmaking to the lowest and most effective jurisdictional level; and (#7) promoting variation in policy responses. This paper elaborates on these seven tools as a pragmatic guide for policymakers who find themselves working in highly complex, dynamic, and uncertain settings.