Knowl. Manag. Aquat. Ecosyst.
Number 424, 2023
Freshwater ecosystems management strategies
Article Number 22
Number of page(s) 5
Published online 03 August 2023

© I. Kurtul et al., Published by EDP Sciences 2023

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. If you remix, transform, or build upon the material, you may not distribute the modified material.

Dietary analyses provide the basis for understanding the trophic ecology of fishes but are often reliant on destructive sampling, especially where stomach content analyses are used (Sandlund et al., 2016). Stable isotope analysis (SIA) is an alternative method for reconstructing trophic relationships that provides temporally integrated dietary perspectives (Trueman et al., 2012). Dorsal muscle is generally the main tissue analysed in fish SI studies, with its sampling also tending to be destructive, especially in smaller fishes (Hette-Tronquart et al., 2012; Maitland and Rahel, 2021; Boardman et al., 2022). However, other fish tissues (e.g. scale, fin and mucus) can be used non-destructively for SIA (Boardman et al., 2022). These tissues also vary in their rate of stable isotope turnover, being relatively fast in mucus (so SI data provide a short-term dietary perspective, e.g. 4 weeks) and relatively slow in scales (long-term dietary perspective, e.g. 6 months) (Busst and Britton, 2018; Winter et al., 2021). Moreover, when comparing species-specific SI data between studies (e.g. in meta-analyses), data generated from different tissues can be encountered. Providing knowledge is available on the extent to which the SI values vary between the tissues then correction factors and/ or conversion equations can be applied to standardise all values to dorsal muscle equivalents (Maitland and Rahel, 2021; Roberts et al., 2021).

European perch Perca fluviatilis and the pumpkinseed Lepomis gibbosus are species with relatively large native ranges and increasing non-native ranges, where invasive populations of both species can potentially have ecological consequences for native communities (e.g. Almeida et al., 2014; Furlan and Gleeson, 2016). Where the species co-occur, there is also potential for dietary overlap and competition (Fobert et al., 2011), with SIA providing a tool that can investigate the extent of their trophic interactions (Copp et al., 2017). While destructive sampling for the collection of tissues for SIA may be permissible in the invasive range of these fishes, the species can have relatively high fishery values in their native ranges, especially European perch where catch-and-release angling is increasingly practised (Czarkowski and Kapusta, 2019), especially as harvesting by angling can have strong deleterious effects on population abundances (Lyach and Remr, 2019).

To promote the application of a range of different tissues in European perch and pumpkinseed SI studies, including tissues that can be collected non-destructively, the aim here was to test differences in δ13C and δ15N data between dorsal muscle, fin tissue and scales; where significant differences between the tissues were apparent in either species then tissue conversion equations were generated to allow conversion to a standardised dorsal muscle value (SImuscle). The perch (n = 10; mean length ± 95 % CI: 93.6 ± 5.0 mm) and pumpkinseed (n = 18; 102.4 ± 9.4 mm) were sampled from a lentic fish community in Southern England, where the waterbody is used for recreational angling. Due to the non-native status of pumpkinseed in the fishery, the exact location cannot be provided to protect business confidentiality. Fish samples were collected through a combination of rod-and-line angling and baited fish traps in August 2022 (mid-summer in the study area, when water temperatures tend to be in the range of 18–22 °C). Following capture, fish were identified to species, euthanised (anaesthetic overdose, MS-222), with individual fish placed into plastic sample bags and taken to the laboratory, where they were measured (total length (TL), nearest mm) before a sample of dorsal muscle, and fin tissue was excised from all individuals, and up to 3 scales removed. Mucus samples could not be taken as the amounts able to be collected from both species were below the threshold required for SIA.

All muscle, fin and scale samples were then dried to constant weight (60°C for 48 h), before being bulk analysed for δ13C and δ15N in a Thermo Delta V isotope ratio mass spectrometer (Thermo Scientific, USA) interfaced to a NC2500 elemental analyser (CE Elantach Inc., USA). Analytical precision of the δ13C and δ15N sample runs was estimated against an internal standard sample of animal (deer) material every 10 samples, with the overall standard deviation estimated at 0.08 and 0.04‰ respectively. The C:N ratios of the samples were low (mean ± 95% CI: perch 3.25 ± 0.09 (2.91–3.72); pumpkinseed: 3.16 ± 0.06 (2.78–3.71)) and so were not mathematically corrected for lipid content (Post et al., 2007).

In perch, there was a pattern of δ13C enrichment from muscle (mean ± 95% CI: −31.99 ± 0.91‰) to fin: (−30.68 ± 0.97‰) to scale (−29.71 ± 0.68‰), with a pattern of δ15N depletion across these tissues (muscle: 12.98 ± 0.38‰, fin: 12.29 ± 0.37‰. scales: 11.64 ± 0.42‰) (Fig. 1). These patterns were also apparent for pumpkinseed (δ13C: muscle −30.60 ± 0.36‰; fin: −28.96 ± 0.45‰; scale: −27.87 ± 0.35‰; δ15N: muscle: 12.90 ± 0.20‰; fin: 11.70 ± 0.26‰; scales: 11.57 ± 0.23‰) (Fig. 1). Testing for differences in the SI data by tissue and species, using Wilcoxon tests (where data were not normally distributed) and t-tests (data normally distributed), revealed that in both species, there were significant differences in values of muscle SI data versus fin and scales (Tab. 1A). Consequently, linear regression was applied (independent variable: scale or fin tissue SI data; dependent variable: muscle SI data) to generate the regression coefficients a and b for application in equation (1) that enables the standardised dorsal muscle (SImuscle) values to be predicted from scale and fin SI data (SIother) (Tab. 1B; Fig. 1):


To compare inter-species differences in trophic niche sizes between adjusted scale SI data (long isotopic turnover rate) and dorsal muscle data (relatively short isotopic turnover rate) standard ellipse areas (SEA) were calculated that provides an indication of the isotopic niche size, using the SIBER package in R (Jackson et al., 2011, 2012). As the ellipses enclose the core 40% of SI data, they represent the typical resource use of the analysed population (Jackson et al., 2011). A Bayesian estimate of SEA (SEAb) was used due to the small sample sizes; this utilises a Markov chain Monte Carlo simulation (104 iterations per group) and provides 95% confidence limits for the isotopic niche size (Jackson et al., 2011). To quantify trophic niche overlap, the bivariate area shared by both species in isotopic space and percentage of overlap was also calculated using SEAc (subscript ‘c’ indicates a small sample size correction was used) (Jackson et al., 2011, 2012). Values of SEAb were similar for each species and tissue (perch muscle: 7.79 ± 4.12‰2, scale: 7.81 ± 3.99‰2, fin: 9.43 ± 4.77‰2, pumpkinseed muscle: 1.10 ± 0.47‰2, scale: 1.25 ± 0.42‰2, fin: 1.84 ± 0.56‰2). SEAc revealed very similar patterns for all tissues (Supplementary material: Tab. S1 and Fig. S1). In entirety, these results suggest that both the isotopic niche sizes and the resource use of the species (and the extent of inter-specific interactions) were consistent temporally.

The results thus demonstrated that where the trophic relationships of both perch and pumpkinseed are assessed using SIA, the tissue analysed will affect their SI values. Correspondingly, meta-analyses that use SI data from different tissues to assess the spatial and/ or temporal patterns in the trophic relationships of these species can use the information here to generate standardised SI data. The data presented here also enables the collection of fin and/ or scale material from both species using non-destructive methods in their native ranges, promoting the use of sustainable sampling methods.

The SI conversion data for perch were, however, collected from a relatively limited sample size (n = 10), with no fish used above 138 mm. As European perch can attain lengths exceeding 350 mm, with ontogenetic dietary shifts towards piscivory with increasing fish length, then some caution is needed in applying these conversion values beyond the size range analysed. There are other non-lethal tissues to muscle conversion factors available for both species (Tab. 2), with Vollaire et al. (2007) also indicating that the fractionation between perch muscle and a formulated diet was greater for muscle than scales for δ15N (2.88 ± 0.42‰ versus 1.26 ± 0.39‰) but was greater for scales than muscle for δ13C (4.02 ± 0.13‰ versus 5.98 ± 0.20‰). Thus, when researchers apply fin and/ or scales from these and require conversion to standardised muscle values species, they must decide on the conversion factors to use. We argue that our conversion equations provide robust estimates of standardised muscle values. For example, the mean standardised residuals of the predicted SImuscle data versus the observed SI muscle data of both species were significantly smaller using a and b values in Table 1 in equation (1) versus the conversion equations of Hette-Tronquart et al. (2012) (HT) (mean standardised residuals ± 95% CI: δ13C: HT: 1.00 ± 0.37, Tab. 1: 0.41 ± 0.37, ANOVA: F1,54 = 4.93, P = 0.03; δ15N: HT: −0.99 ± 0.37, Tab. 1: 0.00 ± 0.37, ANOVA: F1,54 = 13.89, P < 0.001). Note, however, that the predicted data here were generated from our data that produced the regression coefficients (i.e. it was a circular analysis), so some caution is needed in interpretation. Accordingly, future studies could consider creating their own regression coefficients from a small number of lethally sampled individuals (e.g. n = 10–12 per species) and apply these over their larger dataset generated from non-lethally sampled fish. Finally, we suggest that the provision here of scale to muscle SI values is important, as it provides the opportunity to use historical scale samples of European perch that are more likely to be available for SIA than fin samples across their native range, given their collection in long-term datasets (e.g. Kankaala et al., 2019), where scales are routinely collected for age and growth analyses.

Ethical statement

The study was completed following the gaining of all relevant ethical and legislative approvals (UK Home Office Project Licence P47216841).

Credit authorship contribution statement

Irmak Kurtul: Conceptualization, Writing − review & editing, Formal analysis, Writing − original draft, Visualization. Ali Serhan Tarkan: Conceptualization, Formal analysis, Writing − original draft. J. Robert Britton: Conceptualization, Writing − original draft, Writing − review & editing.


This research was supported by TÜBİTAK BİDEB (2219 Program) with one-year post-doc scholarships for authors both Irmak KURTUL and Ali Serhan TARKAN.

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.

Data Availability

Data will be made available upon reasonable request to the corresponding author.

Supplementary Material

Table 1. Standard ellipse area (SEAb) and corrected standard ellipse area (SEAc) of different tissues in perch and pumpkinseed.

Figure S1. Trophic niche sizes (as the isotopic niches, standard ellipse areas, SEAc) of perch and pumpkinseed for corrected fin and dorsal muscle, and scale.

Access here


We thank to the TÜBİTAK BİDEB (2219 Program), which supported the authors both Irmak KURTUL and Ali Serhan TARKAN with one-year scholarships during their post doc studies at Bournemouth University, the United Kingdom.


  • Almeida D, Merino-Aguirre R, Vilizzi L, Copp GH. 2014. Interspecific aggressive behaviour of invasive pumpkinseed Lepomis gibbosus in Iberian fresh waters. PLoS One 9: e88038. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  • Boardman RM, Pinder AC, Piper AT, Roberts CG, Wright RM, Britton JR. 2022. Non-lethal sampling for the stable isotope analysis of the critically endangered European eel Anguilla anguilla: how fin and mucus compare to dorsal muscle. J Fish Biol 100: 847− 851. [CrossRef] [PubMed] [Google Scholar]
  • Busst GM, Britton JR. 2018. Tissue-specific turnover rates of the nitrogen stable isotope as functions of time and growth in a cyprinid fish. Hydrobiologia 805: 49−60. [CrossRef] [Google Scholar]
  • Cano-Rocabayera O, Maceda-Veiga A, de Sostoa A. 2015. Fish fins and scales as non-lethally sampled tissues for stable isotope analysis in five fish species of north-eastern Spain. Environ Biol Fish 98: 925–932. [CrossRef] [Google Scholar]
  • Copp GH, Britton JR, Guo Z, Ronni Edmonds-Brown V, Pegg J, Vilizzi L, Davison PI. 2017. Trophic consequences of non-native pumpkinseed Lepomis gibbosus for native pond fishes. Biol Invasions 19: 25–41. [CrossRef] [Google Scholar]
  • Czarkowski TK, Kapusta A. 2019. Catch-and-release ice fishing with a mormyshka for roach (Rutilus rutilus) and European perch (Perca fluviatilis). Ribar. Croat J Fish 77: 235–242. [CrossRef] [Google Scholar]
  • Furlan EM, Gleeson D. 2016. Environmental DNA detection of redfin perch, Perca fluviatilis. Conserv Genet Resources 8: 115–118. [CrossRef] [Google Scholar]
  • Fobert E, Fox MG, Ridgway M, Copp GH. 2011. Heated competition: how climate change will affect non-native pumpkinseed Lepomis gibbosus and native perch Perca fluviatilis interactions in the UK. J Fish Biol 79: 1592–1607. [CrossRef] [PubMed] [Google Scholar]
  • Hette-Tronquart N, Mazeas L, Reuilly-Manenti L, Zahm A, Belliard J. 2012. Fish fins as non-lethal surrogates for muscle tissues in freshwater food web studies using stable isotopes. Rapid Comm Mass Spectrom 26: 1603–1608. [CrossRef] [Google Scholar]
  • Jackson MC, Donohue I, Jackson AL, Britton JR, Harper DM, Grey J. 2012. Population-level metrics of trophic structure based on stable isotopes and their application to invasion ecology. PLoS One 7: e31757. [Google Scholar]
  • Jackson AL, Inger R, Parnell AC, Bearhop S. 2011. Comparing isotopic niche widths among and within communities: SIBER-Stable Isotope Bayesian Ellipses in R. J Anim Ecol 80: 595–602. [CrossRef] [PubMed] [Google Scholar]
  • Kankaala P, Arvola L, Hiltunen M, Huotari J, Jones RI, Nykänen H, Ojala A, Olin M, Peltomaa E, Peura S, Rask M. 2019. Ecosystem responses to increased organic carbon concentration: comparing results based on long-term monitoring and whole-lake experimentation. Inland Waters 9: 489–502. [CrossRef] [Google Scholar]
  • Kelly MH, Hagar WG, Jardine TD, Cunjak RA. 2006. Nonlethal sampling of sunfish and slimy sculpin for stable isotope analysis: how scale and fin tissue compare with muscle tissue. N Am H Fish Man 26: 921–925. [CrossRef] [Google Scholar]
  • Lyach R, Remr J. 2019. The effects of environmental factors and fisheries management on recreational catches of perch Perca fluviatilis in the Czech Republic. Aquatic Living Resources 32: 15. [CrossRef] [EDP Sciences] [Google Scholar]
  • Maitland B, Rahel F. 2021. Nonlethal fin sampling of north american freshwater fishes for food web studies using stable isotopes. N Am J Fish Manag 41: 410–420. [CrossRef] [Google Scholar]
  • Post DM, Layman CA, Arrington DA, Takimoto G, Quattrochi J, Montana CG. 2007. Getting to the fat of the matter: models, methods, and assumptions for dealing with lipids in stable isotope analyses. Oecologia 152: 179–189. [CrossRef] [PubMed] [Google Scholar]
  • Roberts K, Lund T, Hayden B, Poesch M. 2021. Season and species influence stable isotope ratios between lethally and non‐lethally sampled tissues in freshwater fish. J Fish Biol 1–13. [Google Scholar]
  • Sandlund OT, Museth J, Øistad S. 2016. Migration, growth patterns, and diet of pike (Esox lucius) in a river reservoir and its inflowing Stock BC, Jackson AL, Ward EJ, Parnell AC. [Google Scholar]
  • Trueman CN, MacKenzie KM, Palmer MR. 2012. Identifying migrations in marine fishes through stable-isotope analysis. J Fish Biol 81: 826–847. [CrossRef] [PubMed] [Google Scholar]
  • Vollaire Y, Banas D, Thomas M, Roch H. 2007. Stable isotope variability in tissues of the Eurasian perch Perca fluviatilis. Comp Biochem Physiol A 148: 504–509. [CrossRef] [Google Scholar]
  • Winter ER, Britton JR. 2021. Individual variability in stable isotope turnover rates of epidermal mucus according to body size in an omnivorous fish. Hydrobiologia 848: 363–370. [CrossRef] [Google Scholar]

Cite this article as Kurtul I, Tarkan AS, Britton JR. 2023. Inter-tissue variability in the stable isotope values of European perch (Perca fluviatilis) and pumpkinseed (Lepomis gibbosus). Knowl. Manag. Aquat. Ecosyst.424, 22.

All Tables

Table 1

(A) Significance of differences in the stable isotope data of different tissues per species, according to Wilcoxon tests and t-tests; (B) results of linear regression of the relationships of dorsal muscle versus fin and scales SI data per species, and the associated regression coefficients of a and b for use in equation (1). P-values are Bonferroni corrected at α 0.05/2 = 0.025 because two sets of tests were derived from the same dataset (or subsets thereof).

Table 2

Comparison of non-lethal tissue − muscle conversion factors for perch and pumpkinseed from across the literature (*combined data for three sunfish species, including pumpkinseed).

All Figures

thumbnail Fig. 1

Comparison of stable isotope data (δ13C, δ15N) of scale (open circle) and fin (filled circle) versus dorsal muscle for pumpkinseed (A, C) and European perch (B, D); solid lines = equality; small dashed line = significant relationship between fin and muscle SI data according to linear regression; long dashed line = significant relationship between fin and muscle SI data according to linear regression.

In the text

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