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.
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http://dx.doi.org/10.1111/jfb.16056 | DOI Listing |
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