Ontogenetic and interpopulation differences in otolith shape of the European perch (Perca fluviatilis)
Graphical abstract
Introduction
The discovery of otolith growth increments (Pannella, 1971) paved the way for the use of these calcified structures in life-history and evolutionary studies of fishes (Begg et al., 2005; Campana, 2005; Campana and Neilson, 1985; Campana and Thorrold, 2001; Enberg et al., 2012). Otoliths have been extensively used in recent years for many different aims, which include stock discrimination, habitat use, migration and growth patterns (Campana and Casselman, 1993; Campana and Thorrold, 2001; Secor et al., 1995). Among other applications, otoliths can be used to back-calculate individual size at age to ascertain individual growth patterns at daily and yearly scales and their relationship with the environment. This makes them a perfect tool to study fish growth, which is a key component of many fisheries management and fish ecology studies.
The classical back-calculation and growth studies on fish were developed using fish scales (Fraser, 1916; Lea, 1910; Lee, 1920), but this structure is less precise than otoliths (Robillard and Ellen Marsden, 1996) and they have a poor comparability with otoliths (Muir et al., 2008). New and more precise back-calculation models based on otoliths have emerged in the last decades (Campana, 1990; Morita and Matsuishi, 2001), using different equations to describe the relationship between fish and otolith length. This relationship is crucial to any back-calculation model because it directly affects the model outputs, and consequently the information on fish growth (Ashworth et al., 2017; Günther et al., 2012; Li et al., 2008; Wilson et al., 2009).
The somatic growth patterns in fish are well documented, but the growth patterns of otoliths are poorly known. The shape ontogeny of these calcified structures depends on genetics (Cardinale et al., 2004; Lombarte and Lleonart, 1993; Reichenbacher et al., 2009; Vignon and Morat, 2010), individual sex, age, year class, diet, water depth, temperature and substrate type (Begg and Brown, 2000; Cardinale et al., 2004; Castonguay et al., 1991; Gagliano and McCormick, 2004; Hüssy, 2008; Li et al., 2008; Lombarte and Lleonart, 1993; Mérigot et al., 2007; Vignon, 2018). Given that otolith shape and structure can vary through fish ontogeny (Hare and Cowen, 1995), it is important to account for any changes in the underlying allometries when applying back-calculation models (Günther et al., 2012). Mismatch between the assumptions of the back-calculation models and the ‘true’ fish length-otolith length relationship can result in wrong conclusions about the determination of fish age, growth and the timing of critical reproductive events, which can have important repercussions for the management of fish stocks (Francis, 1990; Hare and Cowen, 1995; Moyano et al., 2020; Thorrold and Hare, 2002).
Complex relationships between individual fish length and otolith size and shape can be particularly important for a species that undergo a conspicuous ontogenetic habitat and diet shift that is dependent on environmental triggers, such as the European perch (Perca fluviatilis) (Allen, 1935; Byström et al., 2012; Dörner et al., 2001; Kratochvil et al., 2008; Persson et al., 2004). Given the environmental conditions heterogeneity among populations and their influence on otolith shape (Vignon, 2012), ontogenetic shifts in the shape of P. fluviatilis otoliths are likely to occur. Despite the knowledge on these processes (Butler, 1989; Hobbs et al., 2007; Laidig et al., 1991; Vigliola et al., 2000), little is known about the inter-population variation on otolith shapes. Therefore, the aim of the present study is to describe how the otolith allometry varies among populations using the European perch as a model species. Specifically we aim I) to describe how the P. fluviatilis otolith shape varies through ontogeny and how this process differs among non-related populations; and II) to compare the fitting of fish-otolith allometry models that are commonly used for the fish length back-calculations.
Section snippets
Studied populations, fish sampling and processing
European perch individuals were captured using the European standard multimesh gillnets (CEN 2005) in 9 different freshwater waterbodies in Czechia (Chabarovice, Lipno, Medard, Most, Římov, Rozkoš, Želivka and Žlutice) and the Netherlands (Honderd en Dertig) from 2010 to 2016 (Fig. 1).
Sagittal otoliths of 1800 individuals were extracted from the cranial cavity after the fish had their standard length (SL) measured to the nearest millimeter (fish < 100 mm of SL) or to the nearest 5 mm (fish >
Results
Individual fish sampled for otoliths (n = 1800) ranged from 78 to 375 mm of SL (mean ± SD = 173.7 ± 61.7 mm) and their mean ± SD age was 2.42 ± 1.63 years (Table 2).
Discussion
Our results show that there are clear ontogenetic and interpopulation differences on the otolith shape of P. fluviatilis. This is probably due to the ontogeny in P. fluviatilis otolith growth. P. fluviatilis otoliths tend to be elongated when fishes are young and old, and more rounded at intermediate ages (3 to 6 years). As a result, allometry models that use a linear or a power relationship between the fish and its otolith length fail to capture fully the ontogeny of P. fluviatilis otoliths.
CRediT authorship contribution statement
A.T. Souza: Conceptualization, Data curation, Formal analysis, Methodology, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. K. Soukalová: Data curation, Investigation. V. Děd: Data curation, Methodology, Software, Validation, Writing - review & editing. M. Šmejkal: Investigation, Writing - review & editing. P. Blabolil: Investigation, Writing - review & editing. M. Říha: Investigation, Writing - review & editing. T. Jůza: Investigation, Writing -
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The authors would like to thank Ivan Jaric and Martina Ilarri for their valuable help in the discussion of the statistical methods and results interpretation. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 677039 project CLIMEFISH and from ERDF/ESF project “Biomanipulation as a tool for improving water quality of dam reservoirs” (No. CZ.02.1.01/0.0/0.0/16_025/0007417). This research was also supported by project
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