Cumulative effects research in SpaDES


Natural resource management decisions benefit from cumulative effects research that efficiently integrates scientific knowledge across multiple disciplines in a timely manner. Unfortunately, researchers frequently encounter barriers to efficient integration, especially when it comes to data, models, and analyses, due to the inaccessibility and non-interoperability of these components, which contributes to disciplinary ‘siloing’ and can delay scientific outputs. Using modern tools to facilitate a continuous and adaptive workflow, I present an overview and results from two recent large scale simulation studies developed using the SpaDES package for R. I reflect on the successes and the challenges of these projects, and highlight key insights from the processes implemented for them.

Oct 25, 2019
Great Lakes Forestry Centre Seminar Series
Sault Ste Marie, ON