Guidelines for bridging the divide between ecological forecasts and decision-making

Background/Question/Methods

As the world continues to experience rapid human-induced changes, decision-makers are often pressured to respond to environmental and social challenges in uncertain circumstances. Forecasting models are important analytical tools that can help decision-makers prepare for these challenges and will be increasingly used to address a range of issues from species conservation to resource management to disease outbreaks. Here, we outline general best practices for creating forecasts in decision-making contexts. These best practices were developed through a working group and are based on the experiences of researchers working in academia, government, and industry.

Results/Conclusions

Our best practices encompass strategies for better model development at the science-policy interface. They range from specific technical practices such as quantifying uncertainties, building adaptable models, and creating reusable code, to soft skill practices such as building diverse teams, developing communication techniques, and addressing biases for different audiences. We also categorize strategies based on the time and resources required to implement them, providing first and next steps for researchers desiring to begin or further invest in forecasting. Lastly, we highlight some of the main external obstacles that can prevent good forecasting practices from being adopted in reality. This talk serves as the foundation for this oral session and will provide the benchmarks to evaluate where the forecasting community has most succeeded in integrating forecasting and decision-making, and where future effort should be focused.