Description
Invasive species are a huge threat to lake ecosystems in Minnesota. With over 10,000 water bodies across the state, having up-to-date data and decision support is critical. Researchers at the University of Minnesota have created four complex R and Python models to support lake managers, all pulled together and presented with the most recent infestation data available.
Come along with us to see how we connected these models in the AIS Explorer, a decision support application built in Shiny to help prioritize risks and placing watercraft inspectors, using tools like OCPU and cloud toolings like Lambda, EventBridge and AWS S3.