Ohlberger Jan, Staaks Georg, Hölker Franz
Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany.
J Exp Zool A Ecol Genet Physiol. 2007 May 1;307(5):296-300. doi: 10.1002/jez.384.
Tail beat frequency (TBF) was measured for carp (Cyprinus carpio) and roach (Rutilus rutilus), during steady swimming at five different speeds and for fish of various body masses. A multiple stepwise linear regression analysis resulted in models for the prediction of TBFs depending on swimming speed as an independent variable. Speed explained 72 and 86% of the variance in TBF for carp and roach, respectively. By using these data to predict TBF from speed and substituting values into a model from a previous study that predicts active metabolic rates (AMR) from body mass and swimming speed, we can calculate AMR from only fish mass and TBF. Thus, the derived models can be used to estimate the AMR in fish by measuring TBFs in the field using biotelemetry. The approach presented here is a useful and relatively simple tool for estimating the activity metabolism in free-swimming fish. In future studies this method should be applied to a larger and more representative sample size to test the applicability and the validity for a broader range of species.
在稳定游泳状态下,以五种不同速度对鲤鱼(Cyprinus carpio)和拟鲤(Rutilus rutilus)进行了尾鳍摆动频率(TBF)测量,并测量了不同体重的鱼。多元逐步线性回归分析得出了以游泳速度为自变量预测TBF的模型。速度分别解释了鲤鱼和拟鲤TBF变化的72%和86%。通过利用这些数据从速度预测TBF,并将数值代入先前一项研究中根据体重和游泳速度预测活跃代谢率(AMR)的模型,我们仅通过鱼的体重和TBF就能计算出AMR。因此,所推导的模型可用于通过生物遥测技术在野外测量TBF来估计鱼类的AMR。本文提出的方法是一种用于估计自由游动鱼类活动代谢的有用且相对简单的工具。在未来的研究中,应将该方法应用于更大且更具代表性的样本量,以测试其对更广泛物种的适用性和有效性。