Project
Unlocking acoustic telemetry datasets using integrated diffusion-advection-taxis modeling
Acoustic tags and the GLATOS network have greatly improved our ability to track fish movement in the Great Lakes, yet much of this information remains difficult to analyze and fully use for management. New movement models can separate fish movement into random motion, passive transport by currents, and active movement toward preferred habitats, providing clearer ecological interpretation when combined with other data. We propose to adapt these methods for Great Lakes acoustic telemetry using Lake Erie Walleye as a case study by modifying the models for fixed receiver arrays, testing them with realistic simulations, and applying them to estimate fishing mortality through time and compare results with current stock assessment models. We will also examine how temperature, currents, harmful algal blooms, and low dissolved oxygen influence Walleye movement and exposure to fishing. This work will improve the value of existing telemetry data and provide practical insights to support fisheries management in the Great Lakes.