Keywords
climate change; co-production; scenario planning; state-and-transition simulation modelling; rangelands
Start Date
26-6-2018 9:00 AM
End Date
26-6-2018 10:20 AM
Abstract
Managing natural resources is challenging due, in part, to the complex interactions between ecosystems, management actions, and other forcings, such as climate. Participatory modelling is a useful tool for engaging management partners and other stakeholders in resolving these complexities and increasing scientific legitimacy and relevance. Yet despite the utility of these modelling tools, the uncertainty of climate change and its far-reaching impacts remains a substantial hurdle for resource management. Scenario planning is a participatory exercise that accounts for uncertainty by exploring multiple possible futures; however, it oftentimes lacks the quantitative information that stakeholders need or desire. We report on a project that coupled scenario planning with simulation modelling, whereby researchers, resource managers, local subject-matter experts, and climate change adaptation specialists co-produced a state-and-transition simulation model to explore potential effects of climate scenarios and management alternatives on rangeland vegetation in southwest South Dakota. Scenario planning allowed for consideration of a wide range of resources and facilitated open-minded thinking about a small set of divergent and challenging, yet relevant and plausible, climate scenarios and management alternatives. It thereby bracketed the uncertainty associated with climate change and ensured that the most management-relevant uncertainties were addressed in the simulation. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted trade-offs between different management targets. It also identified impactful uncertainties requiring further investigation. Overall, this cooperative study illustrates opportunities for modellers to engage stakeholders through scenario planning.
Engaging Stakeholders in Simulation Modelling Through Scenario Planning
Managing natural resources is challenging due, in part, to the complex interactions between ecosystems, management actions, and other forcings, such as climate. Participatory modelling is a useful tool for engaging management partners and other stakeholders in resolving these complexities and increasing scientific legitimacy and relevance. Yet despite the utility of these modelling tools, the uncertainty of climate change and its far-reaching impacts remains a substantial hurdle for resource management. Scenario planning is a participatory exercise that accounts for uncertainty by exploring multiple possible futures; however, it oftentimes lacks the quantitative information that stakeholders need or desire. We report on a project that coupled scenario planning with simulation modelling, whereby researchers, resource managers, local subject-matter experts, and climate change adaptation specialists co-produced a state-and-transition simulation model to explore potential effects of climate scenarios and management alternatives on rangeland vegetation in southwest South Dakota. Scenario planning allowed for consideration of a wide range of resources and facilitated open-minded thinking about a small set of divergent and challenging, yet relevant and plausible, climate scenarios and management alternatives. It thereby bracketed the uncertainty associated with climate change and ensured that the most management-relevant uncertainties were addressed in the simulation. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted trade-offs between different management targets. It also identified impactful uncertainties requiring further investigation. Overall, this cooperative study illustrates opportunities for modellers to engage stakeholders through scenario planning.
Stream and Session
C5: Participatory Modelling 2.0: Interfaces, Tools, Methods and Approaches for Linking Stakeholders Decisions, and Environmental Modelling