Freshwater systems deliver critical ecological functions for humans and are key habitats for threatened species, but they are now under increasing threat from climate change, invasive species, and pollution.
This project will demonstrate the use of new sensor technologies and AI-supported modelling for the monitoring of lake biodiversity at scale. The effort will use multispectral and other remote sensing data from satellites to characterize the habitat dynamics of lakes US-wide, and, for a selection of Connecticut lakes, validate and extend such measurements using light-weight drones.
We will use these data to measure and predict algal blooms and, leveraging Map of Life datasets and workflows, a suite of freshwater species. The work will provide a key demonstration of novel, affordable, and highly scalable avenues for monitoring and predicting freshwater biodiversity, and it will support regional agency partners for improved prediction and planning of freshwater ecosystem health.
