COS 172-4 - RAD storylines: developing ecological scenarios for resource management planning

Abstract: ­Natural resource managers are stewarding ecosystems through rapid environmental changes. An emerging paradigm in management is the Resist, Accept, Direct, or RAD, framework, which is a tool for pro-active and anticipatory decision-making given the potential for ecological transformations. Effective use of the RAD framework relies on the ability to characterize the range of ecological trajectories to understand the potential consequences of accepting ecological change without intervention and to evaluate the opportunities to resist or direct change. However, uncertainties in both future climate and ecological responses hinder our ability to project ecological change. For example, key sources of climate uncertainty include unknown future emissions and uncertain magnitudes of negative and positive climatic feedbacks, while key sources of ecological uncertainty center on how complex ecological systems could respond to novel future conditions, and how stochastic events could shape ecological trajectories. Participatory scenario planning with stakeholders can incorporate uncertainty in future climate by contrasting divergent climate projections that are relevant to specific resources. Yet, although multiple ecological outcomes are possible under a given climate future, ecological impact and vulnerability assessments rarely explore the range of plausible ecological trajectories within each scenario of future climate. Here we present a general framework for developing robust ecological scenarios under divergent climate futures, which we discuss in the context of a case study. We propose integrating multiple sources of information to characterize plausible trajectories of ecological change, including qualitative scenarios and quantitative ecological response modeling. We synthesize statistical and process-based modeling options and their trade-offs in the context of scenario planning. Finally, we outline methods for clustering a large set of ecological scenarios into a representative set that captures divergent but plausible trajectories for use in management planning. By explicitly characterizing uncertainty in ecological responses, this approach can support managers by establishing a range of plausible outcomes and exploring the decision space using the RAD framework. Operationalizing RAD decision-making depends on science support, and we discuss outstanding challenges and next steps in developing robust, broadly applicable workflows for characterizing and communicating ecological scenarios.