Droll Jan, Nagel Christoffer, Pander Joachim, Ebert Sophie, Geist Juergen
Aquatic Systems Biology Unit, TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
J Fish Biol. 2025 Jun;106(6):1714-1723. doi: 10.1111/jfb.16056. Epub 2025 Jan 11.
Animal growth is a fundamental component of population dynamics, which is closely tied to mortality, fecundity, and maturation. As a result, estimating growth often serves as the basis of population assessments. In fish, analysing growth typically involves fitting a growth model to age-at-length data derived from counting growth rings in calcified structures. Additionally, fish growth can be estimated using length-frequency data or data on changes in length derived from mark-recapture events. In our study of the European grayling (Thymallus thymallus L.) in the alpine region of Germany, we utilized all three types of datasets to develop the initial growth model. For the age-at-length data from scales, we applied the traditional von Bertalanffy growth function using both a Bayesian and a frequentist approach. Furthermore, we adopted the mark-recapture data along with the Fabens model for reparametrizing the von Bertalanffy growth model. The electronic length-frequency analysis (ELEFAN) was employed to examine the length-frequency data of the grayling, encompassing multiple sampling events from 2013 to 2022. Our findings indicated that the mark-recapture data, in conjunction with the Fabens model, yielded the most plausible values for both statistical approaches. When the von Bertalanffy growth function was used, the frequentist approach generated unreasonably high values, whereas the Bayesian version produced meaningful results when appropriate priors were applied, suggesting potential issues with the age-at-length data related to ageing. The ELEFAN approach produced the smallest yet reasonable growth parameters, contradicting other studies on the European grayling. The lower values may be attributed to the lack of larger fish in most of the sampling events, resulting in a relatively low asymptotic length and slow growth rate. As demonstrated in this case study on grayling from the River Inn, the use of growth characteristics may be a currently underestimated yet very useful indicator of target species assessment that can nicely complement other population health indicators.
动物生长是种群动态的一个基本组成部分，它与死亡率、繁殖力和成熟度密切相关。因此，估计生长情况通常是种群评估的基础。对于鱼类来说，分析生长情况通常涉及将生长模型拟合到通过计算钙化结构中的生长环得出的体长-年龄数据。此外，鱼类生长情况可以通过体长频率数据或从标记重捕事件中得出的体长变化数据来估计。在我们对德国高山地区欧洲茴鱼（Thymallus thymallus L.）的研究中，我们利用了所有这三种类型的数据集来建立初始生长模型。对于来自鳞片的体长-年龄数据，我们采用传统的冯·贝塔朗菲生长函数，同时使用贝叶斯方法和频率学派方法。此外，我们采用标记重捕数据并结合法本斯模型对冯·贝塔朗菲生长模型进行重新参数化。电子体长频率分析（ELEFAN）被用于研究茴鱼的体长频率数据，涵盖了2013年至2022年的多个采样事件。我们的研究结果表明，标记重捕数据与法本斯模型相结合，在两种统计方法中都产生了最合理的值。当使用冯·贝塔朗菲生长函数时，频率学派方法产生了不合理的高值，而当应用适当的先验时，贝叶斯版本产生了有意义的结果，这表明与年龄测定相关的体长-年龄数据可能存在潜在问题。ELEFAN方法产生了最小但合理的生长参数，这与其他关于欧洲茴鱼的研究结果相矛盾。较低的值可能归因于大多数采样事件中缺乏较大的鱼，导致渐近体长相对较低且生长速度较慢。正如在因河茴鱼的这个案例研究中所表明的，生长特征的使用可能是目前被低估但非常有用的目标物种评估指标，可以很好地补充其他种群健康指标。
