The case for embedding researchers in conservation agencies

Although protected areas represent a pivotal response to escalating anthropogenic threats, they face many pressures, inside and outside their boundaries. Amid these challenges, effective conservation is guided by evidence-based decision making supported by dynamic processes of learning and knowledge exchange. Although different models promote knowledge exchange, embedding research scientists within conservation agencies is best suited to supporting evidence-based conservation. Based on available literature and our experiences on several continents, we considered the benefits, challenges, and opportunities associated with embedding research scientists within conservation agencies and the research required to better understand the effectiveness of the embedding model for evidence-based conservation. Embedded researchers provide long-term commitment to building social capital among academic and nonacademic stakeholders; act as skilled gatekeepers who increase 2-way flow of knowledge between scientists and managers; attract, coordinate, and support management-relevant external research projects; drive the design and maintenance of long-term monitoring; and align their research with information needs. Notwithstanding the many benefits, research capacity of conservation agencies is declining worldwide. A significant challenge is that the values, structures, functions, and effectiveness of the embedding model of knowledge exchange remain poorly evaluated and documented. Also, embedded researchers have to balance their desire for creativity and flexibility with the standardization and quality control required by their public sector agencies; may be perceived as not credible because they are not truly independent of their agency; and have to couple scientific productivity with skills for transdisciplinary research, social facilitation, and stakeholder engagement. Systematic research on embedding and other models of knowledge exchange, across different world contexts, is required to better understand the benefits, costs, and institutional arrangements associated with different models.