Identifying governance gaps among interlinked sustainability challenges

Sustainability issues cannot be separated from their social and biophysical context, and collaborative governance responses to interdependent sustainability issues are inherently complex. Governance gaps emerge when responsible actors fail to recognize how multiple issues and actors are interlinked. Closing governance gaps is particularly challenging for sustainability issues that intersect several sectors of society, such as livelihoods, agriculture and biodiversity conservation. This study introduces a new quantitative empirical approach that conceptualizes how governance gaps emerge at the intersection of two networks that are usually studied separately: an actor network and a network of interdependent sustainability issues. We differentiate between (1) integrative gaps that arise when interdependent issues are managed in separation without recognizing their interdependencies, versus (2) collaborative gaps that arise when actors working on common issues do not collaborate. Using data on 60 actors and 38 sustainability issues in southwest Ethiopia, we found comprehensive collaboration networks around, for example, agricultural production and land-use issues, but large collaborative gaps for forest and wildlife issues. While actors actively managed interdependencies around national high-priority issues such as coffee export and family planning, integrative gaps were common for low-profile issues such as access provision of finance, transportation, schools, food and crop markets. In general, smaller specialized actors had a stronger tendency than larger generalist actors to focus their management capacity towards the closing of governance gaps. Surprisingly, greater system complexity did not per se cause governance gaps, except when system interactions were cross-sectoral. Furthermore, our data suggested that integrative system management and collaboration reinforced each other. In conclusion, our network framework advances how governance gaps can be understood and prioritized in different empirical contexts. It enables a theoretically informed empirical identification of the specific sustainability issues for which targeted structural changes are most likely to facilitate improved sustainability outcomes.