Transparent and feasible uncertainty assessment adds value to applied ecosystem services modeling

Abstract We introduce a special issue that aims to simultaneously motivate interest in uncertainty assessment (UA) and reduce the barriers practitioners face in conducting it. The issue, “Demonstrating transparent, feasible, and useful uncertainty assessment in ecosystem services modeling,” responds to findings from a 2016 workshop of academics and practitioners that identified challenges and potential solutions to enhance the practice of uncertainty assessment in the ES community. Participants identified that one important gap was the lack of a compelling set of cases showing that UA can be feasibly conducted at varying levels of sophistication, and that such assessment can usefully inform decision-relevant modeling conclusions. This article orients the reader to the 11 other articles that comprise the special issue, and which span multiple methods and application domains, all with an explicit consideration of uncertainty. We highlight the value of UA demonstrated in the articles, including changing decisions, facilitating transparency, and clarifying the nature of evidence. We conclude by suggesting ways to promote further adoption of uncertainty analysis in ecosystem service assessments. These include: Easing the analytic workflows involved in UA while guarding against rote analyses, applying multiple models to the same problem, and learning about the conduct and value of UA from other disciplines.