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首页> 外文期刊>The Open Fish Science Journal >Empirical Estimation of Accumulation-Induced Change in Gill Net Catchability:Mind the Observation Errors
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Empirical Estimation of Accumulation-Induced Change in Gill Net Catchability:Mind the Observation Errors

机译：G网可捕性累积诱发变化的经验估计：注意观察误差

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We analyzed cumulative catches for 24 h gill net exposures divided into 4*6 h, 2*12 h and 1*24 h soak timetreatments to estimate the reduction in its catchability due to accumulation of fish. The effects of loss of catch during netlifting, disturbance effect and fouling were eliminated as far as possible to reveal the true effect of accumulation. First weapplied simple nonparametric and parametric tests in comparison of treatments. As expected, considerable reduction incatchability took place along with the increase in soak time, indicated by significantly lower total 24 h catches fromlonger soaks in comparison with shorter ones. The reduction was more pronounced for roach than for perch. Further, wecompared a functional relationship regression (FRR), admitting correctly observation error variance also in the x-axisvariable, with ordinary least squares regression (OLS) in modelling the relationship between cumulative 24 h catches fordifferent treatments. We estimated the between-replicates proportional observation error variance within a treatment andfound it to be similar in different treatments. Therefore the variance ratio could be assumed to be close to 1 enabling theuse of major axis solution FRR. In this particular case the incorrect use of OLS obviously gives a seriously biased result,exacerbating the negative effect of accumulation for high x-axis values in comparison with FRR. We recommend the useof FRR for any analysis comparing different notoriously low precision fish abundance proxies.
机译：我们分析了24鱼净暴露量（分为4 * 6 h，2 * 12 h和1 * 24 h浸泡时间）的24小时累积渔获量，以估计由于鱼类蓄积而导致其捕获能力下降。尽可能消除网举过程中渔获物损失，扰动效应和结垢的影响，以揭示积累的真实效果。首先，我们在处理方法比较中应用了简单的非参数检验和参数检验。如预期的那样，随着浸泡时间的增加，减少的可吸入性发生了，这表明较长的浸泡与较短的浸泡相比，总的24 h捕获量明显降低。蟑螂的减少比鲈鱼的减少更为明显。此外，我们比较了功能关系回归（FRR），在x轴变量中也正确接受了观察误差方差，而在对不同处理的累积24 h渔获量之间的关系进行建模时，采用了普通最小二乘回归（OLS）。我们估计了治疗中重复之间的比例观察误差方差，发现在不同治疗中相似。因此，可以假定方差比接近1，从而能够使用主轴解FRR。在这种特殊情况下，OLS的不正确使用显然会产生严重偏差的结果，与FRR相比，对于高x轴值，累积的负面影响更加严重。我们建议将FRR用于任何比较不同的众所周知的低精度鱼类丰度代理的分析。

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