Abstract Relative abundance, or CPUE, is a commonly used metric for fisheries conservation and management. Interpreting CPUE data requires understanding the probability that a fish will be caught (catchability) by a particular type of gear and factors that affect catchability. Escape is often not considered in catchability studies, and there is little to no mention of this phenomenon in fisheries textbooks. However, most passive sampling gear, particularly traps, is ‘permeable’, so the number of organisms actually collected will fluctuate based on probability of escapement. Because high or variable escape rates have the potential to bias measures of abundance, the use of passive traps requires recognition and assessment of permeability. To better understand these dynamics, and particularly how they apply to salmonid emergent fry traps, we conducted a series of mesocosm experiments with early-life stage lake trout (Salvelinus namaycush). We assessed entry and exit rates by fitting daily capture data to a hierarchical state-space model. We also evaluated a trap modification and the effect of thiamine deficiency on capture rates; thiamine-deficient fish can be lethargic and unlikely to enter traps, so deficiency in the wild may be underestimated. Results revealed distinct temporal trends, with low initial entry rates that rose around the third week after hatch and remained constant thereafter. Thiamine deficiency decreased entry rates but appeared to have no effect on exit rates. Conversely, a minor trap design change had an unexpectedly large effect on exit rates. We developed a generalizable model for estimating abundance using passive traps based on soak time and entry/exit rates, as well as specific rate estimates for lake trout in emergent fry traps. Such corrections should be performed whenever feasible, as abundance estimates may otherwise be biased by exit-related equilibrium.

中文翻译：

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在中观实验中使用紧急鱼苗陷阱来校正由于渗透性引起的偏差的通用模型

摘要 相对丰度 (CPUE) 是渔业保护和管理的常用指标。解释 CPUE 数据需要了解特定类型的渔具捕获鱼的概率（可捕获性）以及影响可捕获性的因素。捕捞能力研究通常不考虑逃逸，渔业教科书中几乎没有提到这种现象。然而，大多数被动采样装置，尤其是陷阱，是“可渗透的”，因此实际收集的生物体数量会根据逃逸概率而波动。由于高或可变的逃逸率有可能使丰度测量产生偏差，因此使用被动圈闭需要识别和评估渗透率。为了更好地了解这些动态，特别是它们如何应用于鲑鱼紧急鱼苗陷阱，我们对生命早期阶段的湖鳟 (Salvelinus namaycush) 进行了一系列中观实验。我们通过将每日捕获数据拟合到分层状态空间模型来评估进入和退出率。我们还评估了陷阱修改和硫胺素缺乏对捕获率的影响；缺乏硫胺素的鱼可能会昏昏欲睡，不太可能进入陷阱，因此可能低估了野外的缺乏情况。结果显示出明显的时间趋势，低初始进入率在孵化后第三周左右上升，此后保持不变。硫胺素缺乏降低了进入率，但似乎对退出率没有影响。相反，一个微小的陷阱设计变化对退出率产生了意想不到的大影响。我们开发了一个通用模型，用于使用基于浸泡时间和进入/退出率的被动陷阱估计丰度，以及紧急鱼苗陷阱中湖鳟鱼的特定速率估计。只要可行，就应进行此类更正，否则丰度估计可能会因退出相关的平衡而产生偏差。