The new generation of automated acoustic data collection platforms: analysis of vessel avoidance by fish and zooplankton patch structure

Tom Evans, Hannah Blair, Rudstam, Watkins, Suresh Sethi, Kayden Nasworthy (Cornell) Peter Esselman, David Warner, Dan Yule, Tim O’Brien, Mark DuFour, and others at USGS and cooperating agencies. (Funded by USGS) 

This project uses acoustic data collected with automated surface and underwater vehicles to evaluate bias in fisheries surveys to understand the distribution of fish and zooplankton on a whole-lake scale. The work relies upon uncrewed quiet surface vessels powered by wind and solar that collect data continuously for over a month (Saildrone) and a long range autonomous underwater vehicle (LRAUV). The primary objective of the saildrone data is to evaluate fish avoidance of traditional crewed surface vessels used in fisheries surveys. In 2025 we continued analyzing the large amount of data collected from 2021 to 2024. We prepared and plan to submit two papers at the start of 2026, one on acoustic blind zones and one on using drones to conduct a lake-wide acoustic survey. Nasworthy prepared and submitted a manuscript of Mysis developed from these data, which was accepted and will be published in 2026. We worked with Dr. Angus Galloway at the University of Guelph to develop an AI to reduce the amount of processing time needed to analyze the acoustic data. We also prepared and assembled lake-wide data for a colleague to begin working on their own survey questions. Blair and Evans both took new positions in summer 2025.