The network BiodiversityKnowledge in practice: insights from three trial assessments

Abstract

In order to develop BiodiversityKnowledge, a Network of Knowledge working at the European science–policy interface for biodiversity and ecosystem services, we conducted three trial assessments. Their purpose was to test structure and processes of the knowledge synthesis function and to produce knowledge syntheses. The trial assessments covered conservation and management of kelp ecosystems, biological control of agricultural pests, and conservation and multifunctional management of floodplains. Following the BiodiversityKnowledge processes, we set up expert consultations, systematic reviews, and collaborative adaptive management procedures in collaboration with requesters, policy and decision-makers, stakeholders, and knowledge holders. Outputs included expert consultations, systematic review protocols, a group model and a policy brief. Important lessons learned were firstly that the scoping process, in which requesters and experts iteratively negotiate the scope, scale and synthesis methodology, is of paramount importance to maximize the scientific credibility and policy relevance of the output. Secondly, selection of a broad array of experts with diverse and complementary skills (including multidisciplinary background and a broad geographical coverage) and participation of all relevant stakeholders is crucial to ensure an adequate breath of expertise, better methodological choices, and maximal uptake of outcomes: Thirdly, as the most important challenge was expert and stakeholder engagement, a high visibility and reputation of BiodiversityKnowledge, supported by an incentive system for participation, will be crucial to ensure such engagement. We conclude that BiodiversityKnowledge has potential for a good performance in delivering assessments, but it requires adequate funding, trust-building among knowledge holders and stakeholders, and a proactive and robust interface with the policy and decision making communityPeer reviewe