Sustainable management of wildlife populations can be aided by building models
that both identify current drivers of natural dynamics and provide near-term predictions of
future states. We employed a Strategic Foresight Protocol (SFP) involving stakeholders to
decide the purpose and structure of a dynamic state-space model for the population dynamics
of the Willow Ptarmigan, a popular game species in Norway. Based on local knowledge of
stakeholders, it was decided that the model should include food web interactions and climatic
drivers to provide explanatory predictions. Modeling confirmed observations from stakeholders
that climate change impacts Ptarmigan populations negatively through intensified outbreaks
of insect defoliators and later onset of winter. Stakeholders also decided that the model
should provide anticipatory predictions. The ability to forecast population density ahead of
the harvest season was valued by the stakeholders as it provides the management extra time to
consider appropriate harvest regulations and communicate with hunters prior to the hunting
season. Overall, exploring potential drivers and predicting short-term future states, facilitate
collaborative learning and refined data collection, monitoring designs, and management priorities.
Our experience from adapting a SFP to a management target with inherently complex
dynamics and drivers of environmental change, is that an open, flexible, and iterative process,
rather than a rigid step-wise protocol, facilitates rapid learning, trust, and legitimacy.
climate change; decision-making; food web; harvesting; near-term forecasting; population
cycles; stakeholders; strategic foresight.
