A methodological framework for characterizing fish swimming and escapement behaviors in trawls

Area of Science:

• Marine biology
• Fisheries science
• Animal behavior

Background:

• Underwater cameras offer new insights into fish behavior interacting with fishing gear.
• Existing methodologies need enhancement to handle complex observational data, including censored observations and variable study durations.

Purpose of the Study:

• To develop a methodological framework using a parametric Weibull mixture model to analyze fish escapement behavior.
• To investigate the temporal dynamics of escapement attempts and estimate the probability of escape.
• To test the effects of covariates on escapement success in gadoids interacting with a selective fishing device.

Main Methods:

• Utilized a parametric Weibull mixture model to analyze time-to-event data for fish escapement attempts.
• Applied video data of gadoids interacting with a selective device in a bottom trawl.
• Employed binomial regression to investigate the influence of covariates on escapement success.

Main Results:

• The escapement process in gadoids can be modeled using an exponential law, with a constant instantaneous rate of escape attempts.
• The average time before an escape attempt increases with the number of attempts.
• Over 80% of gadoids attempted to escape through the selective device, with an estimated success probability of approximately 15%.

Conclusions:

• The developed methodology provides a robust framework for analyzing fish behavior and escapement dynamics.
• While over 80% of gadoids attempted to escape, success rates were low (around 15%), indicating potential for gear selectivity improvements.
• Further research with larger datasets is needed to fully understand intrinsic and extrinsic factors influencing gadoid behavior in fishing gear.