Ifremer, LTBH (Laboratory of Fisheries Technology and Biology), Lorient, France.
Center for Nonlinear Phenomena and Complex Systems, Université libre de Bruxelles, Bruxelles, Belgium.
PLoS One. 2020 Dec 11;15(12):e0243311. doi: 10.1371/journal.pone.0243311. eCollection 2020.
Knowledge about fish behavior is crucial to be able to influence the capture process and catch species composition. The rapid expansion of the use of underwater cameras has facilitated unprecedented opportunities for studying the behavior of species interacting with fishing gears in their natural environment. This technological advance would greatly benefit from the parallel development of dedicated methodologies accounting for right-censored observations and variable observation periods between individuals related to instrumental, environmental and behavioral events. In this paper we proposed a methodological framework, based on a parametric Weibull mixture model, to describe the process of escapement attempts through time, test effects of covariates and estimate the probability that a fish will attempt to escape. We additionally proposed to better examine the escapement process at the individual level with regard to the temporal dynamics of escapement over time. Our approach was used to analyze gadoids swimming and escapement behaviors collected using a video set up in front of a selective device known to improve selectivity on gadoids in the extension of a bottom trawl. Comparison of the fit of models indicates that i) the instantaneous rate of escape attempts is constant over time and that the escapement process can be modelled using an exponential law; ii) the mean time before attempting to escape increases with the increasing number of attempts; iii) more than 80% of the gadoids attempted to escape through the selective device; and iv) the estimated probability of success was around 15%. Effects of covariates on the probability of success were investigated using binomial regression but none of them were significant. The data set collected is insufficient to make general statements, and further observations are required to properly investigate the effect of intrinsic and extrinsic factors governing gadoids behavior in trawls. This methodology could be used to better characterize the underlying behavioral process of fish in other parts of a bottom trawl or in relation to other fishing gears.
鱼类行为知识对于能够影响捕捞过程和捕获物种组成至关重要。水下摄像机的快速普及为研究与渔具相互作用的物种在其自然环境中的行为提供了前所未有的机会。这种技术进步将极大地受益于专门方法的平行发展，这些方法考虑了因仪器、环境和行为事件而导致的右删失观测值和个体之间可变的观测期。在本文中，我们提出了一种基于参数 Weibull 混合模型的方法框架，用于描述随时间推移的逃脱尝试过程，检验协变量的影响，并估计鱼类试图逃脱的概率。我们还提出了更好地在个体层面上检查逃脱过程，关注随着时间的推移逃脱的时间动态。我们的方法用于分析使用视频设备在选择性装置前收集的鳕鱼游泳和逃脱行为，该选择性装置已知可以提高底层拖网延伸范围内鳕鱼的选择性。模型拟合度的比较表明：i）逃脱尝试的瞬时率随时间保持不变，并且可以使用指数定律对逃脱过程进行建模；ii）尝试逃脱之前的平均时间随着尝试次数的增加而增加；iii）超过 80%的鳕鱼试图通过选择性装置逃脱；iv）估计的成功概率约为 15%。使用二项式回归研究了协变量对成功概率的影响，但均无显著影响。所收集的数据不足以做出一般性陈述，需要进一步观察才能正确研究内在和外在因素对鳕鱼在拖网中的行为的影响。这种方法可以用于更好地描述底层拖网其他部分或与其他渔具相关的鱼类行为的潜在行为过程。
