Coupling meteorology, plant biology, and economic engineering models within a CyberGIS framework
College: Institute for Genomic Biology
Award year: 2014-2015
Future demand for second-generation biofuel feedstock production will benefit from the synthesis of knowledge across domains. The ability to simultaneously modify assumptions about greenhouse gas emissions that will drive future climate, breeding technologies involved in crop improvement, social drivers of land use for biofuel production, and the costs underlying the economics of the feedstock supply chain are all necessary for both scientific inquiry and decision support. The ability to manage complex computational workflows is a key bottleneck in scientific progress, because it is currently difficult for scientists to share, reproduce, and extend complex analyses. This project will integrate existing models and workflow tools used to simulate weather, bioenergy production, and supply chain optimization within a CyberGIS platform to support scientific investigations into the production and distribution of biofuel feedstocks. This will facilitate cross-domain inquiry and collaboration, increase the scope and precision of scientific inference, and improve the accessibility of complex computational workflows to scientists and decision makers.