Ecological statistical models are continually becoming more powerful, complex, and integral to conserving biodiversity in a changing world. As statistical methods develop to meet scientific informational needs, however, they often become more difficult to translate into actionable insights for policy-makers and conservation practitioners. For statistical ecological models to be effective conservation tools, conservation practitioners must be able to access model outputs that are immediately understandable and relevant, necessitating that decision support tools be developed collaboratively with practitioners.
Results/Conclusions
We introduce a framework wherein conservation practitioners are included as equal partners in the development of decision support tools that translate complex statistical models to interactive online tools via the open source R Shiny framework. We advocate for an iterative prototyping approach wherein practitioners are included in every stage of tool development, from question formation and model development, to tool interface design. In addition to describing the framework, we provide case study applications to demonstrate an application development pipeline and provide suggestions on optimizing informational value, practitioner engagement, and computational efficiency. Our work demonstrates the value of science-practice partnerships and provides applicable insights for conservation scientists and decision-makers.