Geoff Syme

The great experiment with devolved NRM governance: lessons from community engagement in Australia and New Zealand since the 1980s

Since the 1980s, natural resource management (NRM) in Australia and New Zealand has been an ambitious experiment with community engagement. Underpinned by theory about public participation, adult education and agricultural extension, but also influenced by neoliberalisms calls for ‘smaller government’, governments embraced engagement as a cost-effective approach to effecting change. Critiques of community engagement are often misguided as they are frequently based on inauthentic or poor engagement practices. Moreover, these critiques have often failed to grasp the nature of the problems being addressed, acknowledge the contributions of engagement or understand the importance of building adaptive capacity to respond to an increasingly complex and uncertain future. The foundations for this commissioned article emerged at a workshop where we reflected and deliberated on our experience as NRM researchers and practitioners over the past 20 years. We begin by identifying the key theories underpinning community engagement and community-based NRM (CBNRM). We then reflect on the experience with community engagement in NRM over the past 20 years and identify key lessons for practitioners and policy makers. Drawing on these insights, and the developing theory around new governance and resilience thinking, we identify opportunities for community engagement under a range of possible futures.

Knowledge that Acts: Evaluating the Outcomes of a Knowledge Brokering Intervention in Western Australia’s Ningaloo Region

Knowledge exchange involves a suite of strategies used to bridge the divides between research, policy and practice. The literature is increasingly focused on the notion that knowledge generated by research is more useful when there is significant interaction and knowledge sharing between researchers and research recipients (i.e., stakeholders). This is exemplified by increasing calls for the use of knowledge brokers to facilitate interaction and flow of information between scientists and stakeholder groups, and the integration of scientific and local knowledge. However, most of the environmental management literature focuses on explicit forms of knowledge, leaving unmeasured the tacit relational and reflective forms of knowledge that lead people to change their behaviour. In addition, despite the high transaction costs of knowledge brokering and related stakeholder engagement, there is little research on its effectiveness. We apply Park’s Manag Learn 30(2), 141–157 (1999); Knowledge and Participatory Research, London: SAGE Publications (2006) tri-partite knowledge typology as a basis for evaluating the effectiveness of knowledge brokering in the context of a large multi-agency research programme in Australia’s Ningaloo coastal region, and for testing the assumption that higher levels of interaction between scientists and stakeholders lead to improved knowledge exchange. While the knowledge brokering intervention substantively increased relational networks between scientists and stakeholders, it did not generate anticipated increases in stakeholder knowledge or research application, indicating that more prolonged stakeholder engagement was required, and/or that there was a flaw in the assumptions underpinning our conceptual framework.

Modeling livelihood indicators and household resilience using Bayesian networks

The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.