Project
Camera monitoring of silver eels
To run eel monitoring programs, local fishermen are contracted to collect data and maintain fyke traps. Due to various reasons, many monitoring locations have disappeared resulting in trend breaks in the time series. This project will test the use of camera monitoring to continue the eel monitoring.
Summary
Silver eel monitoring is important to assess whether eel regulations have an effect on the percentage of migrating silver eel towards the Sargasso Sea. Silver eel monitoring is traditionally executed by fyke traps in collaboration with fishermen. Many fishermen however stop their fisheries activities due to retirement or other work. Since trend monitoring strongly relies on consistent methodology (e.g. location of traps) for year-to-year comparisons, a more robust and consistent monitoring approach is necessary. To anticipate on any further changes in policy and reduced fishermen availability, more robust, future-directed monitoring options need to be explored. Camera trap monitoring using artificial intelligence video recognition software seems a viable alternative. However, so far, video recognition software has not been trained to differentiate between yellow eels and silver eels. In this KB WOT Fisheries project, we will test whether video recognition software can be trained through machine learning to differentiate yellow eels from silver eels in a laboratory environment.