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A Bayesian approach to estimating target strength

机译：估计目标强度的贝叶斯方法

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Currently, conventional models of target strength (TS) vs. fish length, based on empirical measurements, are used to estimate fish density from integrated acoustic data. These models estimate a mean TS, averaged over variables that modulate fish TS (tilt angle, physiology, and morphology); they do not include information about the uncertainty of the mean TS, which could be propagated through to estimates of fish abundance. We use Bayesian methods, together with theoretical TS models and in situ TS data, to determine the uncertainty in TS estimates of Atlantic herring (Clupea harengus). Priors for model parameters (surface swimbladder volume, tilt angle, and s.d. of the mean TS) were used to estimate posterior parameter distributions and subsequently build a probabilistic TS model. The sensitivity of herring abundance estimates to variation in the Bayesian TS model was also evaluated. The abundance of North Sea herring from the area covered by the Scottish acoustic survey component was estimated using both the conventional TS-length formula (5.34×10~9 fish) and the Bayesian TS model (mean = 3.17 × 10~9 fish): this difference was probably because of the particular scattering model employed and the data used in the Bayesian model. The study demonstrates the relative importance of potential bias and precision of TS estimation and how the latter can be so much less important than the former.
机译：当前，基于经验测量，目标强度（TS）与鱼类长度的常规模型用于根据综合声学数据估算鱼类密度。这些模型估算出平均TS，将其平均化为可调节鱼类TS的变量（倾斜角，生理和形态）；它们不包括有关平均TS不确定性的信息，可以将其传播到鱼类丰度估计中。我们使用贝叶斯方法，结合理论TS模型和原位TS数据，确定大西洋鲱（Clupea harengus）TS估计中的不确定性。使用模型参数的先验值（表面游泳囊体积，倾斜角和平均TS的s.d.）估计后参数分布，随后建立概率TS模型。还评估了鲱鱼丰度估计值对贝叶斯TS模型变化的敏感性。使用传统的TS长度公式（5.34×10〜9条鱼）和贝叶斯TS模型（平均= 3.17×10〜9条鱼）估算苏格兰声学调查组成部分所覆盖区域的北海鲱鱼的丰度：这种差异可能是由于使用了特定的散射模型以及贝叶斯模型中使用的数据。该研究证明了潜在偏倚和TS估计精度的相对重要性，以及后者如何比前者重要得多。

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