Forest ecosystem decision support systems evolved out of a need to apply the results of scientific research to forest management and policy. Initially, these were closed systems, limited by technologies and data availability at the time. The recent availability of large spatial datasets and high-performance computing has enabled creation of new systems-modelling approaches. We examine decision support tools and models used for mountain pine beetle management in B.C. by discussing the advantages and limitations of these historical approaches. Current development of open and scalable modelling platforms seeks to overcome many of the historical limitations and provide cross-disciplinary integration, along with enhanced transparency, accountability, and scientific reproducibility.