Achieving social-ecological fit through bottom-up collaborative governance: an empirical investigation

Abstract

Significant benefits can arise from collaborative forms of governance that foster self-organization and flexibility. Likewise, governance systems that fit with the extent and complexity of the system under management are considered essential to our ability to solve environmental problems. However, from an empirical perspective the fundamental question of whether self-organized (bottom-up) collaborative forms of governance are able to accomplish adequate fit is unresolved. We used new theory and methodological approaches underpinned by interdisciplinary network analysis to address this gap by investigating three governance challenges that relate to the problem of fit: shared management of ecological resources, management of interconnected ecological resources, and cross-scale management. We first identified a set of social-ecological network configurations that represent the hypothesized ways in which collaborative arrangements can contribute to addressing these challenges. Using social and ecological data from a large-scale biodiversity conservation initiative in Australia, we empirically determined how well the observed patterns of stakeholder interactions reflect these network configurations. We found that stakeholders collaborate to manage individual parcels of native vegetation, but not for the management of interconnected parcels. In addition, our data show that the collaborative arrangements enable management across different scales (local, regional, supraregional). Our study provides empirical support for the ability of collaborative forms of governance to address the problem of fit, but also suggests that in some cases the establishment of bottom-up collaborative arrangements would likely benefit from specific guidance to facilitate the establishment of collaborations that better align with the ways ecological resources are interconnected across the landscape. In our case study region, this would improve the capacity of stakeholders to detect both the intended and unintended off-site impacts of management actions. Our approach offers an avenue for empirical evaluations of collaborative governance so that preconditions for effectiveness of environmental programs can be enhanced.

Keywords

• collaborative governance
• Exponential Random Graph Modeling
• networks
• problem of fit
• scales
• social-ecological fit
• social-ecological systems