Across the Pacific, wildfire poses a major threat to biological and cultural resources, and the threat is only predicted to become larger with climate change. In this talk, graduate students Kevin Faccenda and Kelsey Brock discuss a new tool and methodology for predicting the fire risk of invasive species before they enter a region so that management efforts can be focused on the highest risk incipient species.
This tool uses data collected from the primary literature as well as a machine learning model trained on expert survey data to predict fire risk. Their team examined this risk in a spatial context by modeling the distribution of multiple invasive plants and climatic conditions that promote wildfire across the main Hawaiian Islands. Models were created based on current-day climate conditions as well potential conditions at the end of the century to under climate change.