Clement, Sarah, Moore, Susan A., Lockwood, Michael, and Morrison, Tiffany H. (2015) A diagnostic framework for biodiversity conservation institutions. Pacific Conservation Biology, 21 (4). pp. 277-290.

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Abstract

Biodiversity loss is a critical issue on the environmental agenda, with species-based approaches failing to stem the decline. Landscape-scale approaches offer promise, but require institutional change. This article describes a novel conceptual framework for assessing institutional arrangements to tackle this persistent problem. In doing so, two critical issues for biodiversity governance are addressed. The first is a need to enrich largely theoretical descriptions of adaptive governance by considering how the practical realities of institutional environments (e.g. public agencies) limit achievement of an adaptive governance 'ideal'. The second is enabling explicit consideration of the unique aspects of biodiversity as a ‘policy problem’ in the analysis of institutional arrangements. The framework contributes to efforts to design more adaptive institutional arrangements, through supporting a more sophisticated and grounded institutional analysis incorporating insights from institutional theory, especially literature on organisational environments and public administration. Concepts from Pragmatism also contribute to this grounding, providing insight into how public agencies can play a more productive role in biodiversity conservation and building public consent for management actions. The diagnostic categories in the framework include the attributes of the biodiversity problem and the involved players; the political context; and practices contributing to both competence and capacity. Guidance on how to apply the framework and an example of its application in Australia illustrate the utility of this tool for institutional diagnosis and design. Development of this diagnostic framework could be further enhanced by empirically informed elaboration of the relationships between its components, and of the nature of, and factors influencing, key concerns for adaptation, particularly learning, self-organising and buffering.

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