Model emulators and complexity management at the environmental science-action interface

As our understanding of the interactions present in socio-ecological systems advance, emulation modeling can help reduce the complexity and required computational resources of the models used to represent these systems. While emulation is commonly used in model meta-analyses and parameterization, it has been less explored in the context of environmental management. In this research, I analyze the reflections of a group of watershed modelers on environmental model emulation. I find that decreased simulation run-times are an important motivation because emulators enable stakeholders to interact directly with the model. However, participants also reported that criteria for an emulator in an environmental management context should also assess its capability to act as a platform for learning and to manage stakeholder perceptions of the modeling process. Further, at the science-action interface, stakeholder perceptions play a significant role in the approach to model emulation through determining acceptable levels complexity in model processes and inputs.