Fostering Complexity Thinking in Action Research for Change in Social–Ecological

Complexity thinking is increasingly being embraced by a wide range of academics and professionals as imperative for dealing with today’s pressing social–ecological challenges. In this context, action researchers partner directly with stakeholders (communities, governance institutions, and work resource managers, etc.) to embed a complexity frame of reference for decision making. In doing so, both researchers and stakeholders must strive to internalize not only “intellectual complexity” (knowing) but also “lived complexity” (being and practicing). Four common conceptualizations of learning (explicit/tacit knowledge framework; unlearning selective exposure; conscious/competence learning matrix; and model of learning loops) are integrated to provide a new framework that describes how learning takes place in complex systems. Deep reflection leading to transformational learning is required to foster the changes in mindset and behaviors needed to adopt a complexity frame of reference. We then present three broad frames of mind (openness, situational awareness, and a healthy respect for the restraint/action paradox), which each encompass a set of habits of mind, to create a useful framework that allows one to unlearn reductionist habits while adopting and embedding those more conducive to working in complex systems. Habits of mind provide useful heuristic tools to guide researchers and stakeholders through processes of participative planning and adaptive decision making in complex social–ecological systems.

Complexity, Modeling, and Natural Resource Management

This paper contends that natural resource management (NRM) issues are, by their very nature, complex and that both scientists and managers in this broad field will benefit from a theoretical understanding of complex systems. It starts off by presenting the core features of a view of complexity that not only deals with the limits to our understanding, but also points toward a responsible and motivating position. Everything we do involves explicit or implicit modeling, and as we can never have comprehensive access to any complex system, we need to be aware both of what we leave out as we model and of the implications of the choice of our modeling framework. One vantage point is never sufficient, as complexity necessarily implies that multiple (independent) conceptualizations are needed to engage the system adequately. We use two South African cases as examples of complex systems—restricting the case narratives mainly to the biophysical domain associated with NRM issues—that make the point that even the behavior of the biophysical subsystems themselves are already complex. From the insights into complex systems discussed in the first part of the paper and the lessons emerging from the way these cases have been dealt with in reality, we extract five interrelated generic principles for practicing science and management in complex NRM environments. These principles are then further elucidated using four further South African case studies—organized as two contrasting pairs—and now focusing on the more difficult organizational and social side, comparing the human organizational endeavors in managing such systems.

Addressing communication silo’s using complexity techniques and Social Network Analysis.

A case study published in 2001 by the EU Knowledge Board, where Social Network Analysis was used along with complexity based techniques to assess and improve cross-silo collaboration in a division of a South African bank.

Using Cognitive Edge methods for knowledge creation and collective sense-making

A book chapter about the practical application of Cynefin methodologies on various projects. It forms part of the Hands-on Knowledge Co-creation and Sharing: Practical Methods and Techniques, A book by the KnowledgeBoard Community for the Global Knowledge Community, ISBN: 97895163517