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Capturing potential: Leveraging grass carp behavior Ctenopharyngodon idella for enhanced removal

May 23, 2024

Effective management of invasive species benefits from a comprehensive understanding of the species’ behavior and interactions with the invaded system. We investigated temporal dynamics of telemetry detections and the potential utility of a traitor approach for informing response efforts to the invasive grass carp (Ctenopharyngodon idella) population in the Sandusky River, a major tributary to Lake Erie. Telemetered grass carp exhibited heightened activity at night and early morning, suggesting that capture and removal be more effective during these time periods. Analysis of catch per unit effort (CPUE) across different removal methods, trammel nets, electrofishing, and hoop nets. suggested that incorporating the traitor approach could improve capture. Low catchability values (<0.026), based on the number of telemetered grass carp present in the river on a weekly basis and the number of those telemetered fish captured, suggest the species is difficult to capture. Optimizing response effort efficiency is important and refining catchability estimates will lessen errors in population models and improve interpretation of low CPUE data. Results from generalized additive models suggest capture could be improved using telemetry data, night removals, and by attempting exploratory removal efforts in fall and winter months. By incorporating telemetry data and acknowledging the complexities of grass carp behavior and ecology, we found that a multifaceted and data-driven approach to invasive species control could be beneficial, ultimately promoting conservation and sustainability in dynamic ecosystems like Lake Erie.

Publication Year 2024
Title Capturing potential: Leveraging grass carp behavior Ctenopharyngodon idella for enhanced removal
DOI 10.1016/j.jglr.2024.102373
Authors Matthew Ross Acre, Tyler Michael Hessler, Sophia Marie Bonjour, James Roberts, Scott F. Colborne, Travis O. Brenden, Lucas R. Nathan, Dustin Broaddus, Christopher S. Vandergoot, Christine M. Mayer, Song S. Qian, Robert D. Hunter, Ryan E. Brown, Robin Calfee
Publication Type Article
Publication Subtype Journal Article
Series Title Journal of Great Lakes Research
Index ID 70255912
Record Source USGS Publications Warehouse
USGS Organization Columbia Environmental Research Center