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Short Communication
Length–weight relations for 19 freshwater fish species (Actinopterygii) from the lowland Elbe River, Germany
expand article infoJanek Simon‡, Wolf-Christian Lewin§, Erik Fladung‡
‡ Potsdam Institute of Inland Fisheries, Potsdam, Germany
§ Thünen Institute of Baltic Sea Fisheries, Rostock, Germany

Corresponding author: Janek Simon ( janek.simon@ifb-potsdam.de )

Academic editor: Rodolfo Reyes
© 2023 Janek Simon, Wolf-Christian Lewin, Erik Fladung.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Simon J, Lewin W-C, Fladung E (2023) Length–weight relations for 19 freshwater fish species (Actinopterygii) from the lowland Elbe River, Germany. Acta Ichthyologica et Piscatoria 53: 1129-135. https://doi.org/10.3897/aiep.53.107199
ZooBank: urn:lsid:zoobank.org:pub:90E2F83A-6AEA-4F4A-8EFB-B59D906A43CB
Open Access

Abstract

Monthly and mean length–weight relations (LWRs) were calculated for 19 freshwater fish species from the middle section of the lowland Elbe River (Germany): Abramis brama (Linnaeus, 1758); Alburnus alburnus (Linnaeus, 1758); Anguilla anguilla (Linnaeus, 1758); Ballerus ballerus (Linnaeus, 1758); Blicca bjoerkna (Linnaeus, 1758); Cobitis taenia Linnaeus, 1758; Esox lucius Linnaeus, 1758; Gobio gobio (Linnaeus, 1758); Gymnocephalus cernua (Linnaeus, 1758); Leuciscus aspius (Linnaeus, 1758); Leuciscus idus (Linnaeus, 1758); Leuciscus leuciscus (Linnaeus, 1758); Lota lota (Linnaeus, 1758); Perca fluviatilis Linnaeus, 1758; Romanogobio albipinnatus (Lukasch, 1933); Rutilus rutilus (Linnaeus, 1758); Sander lucioperca (Linnaeus, 1758); Scardinius erythrophthalmus (Linnaeus, 1758); and Squalius cephalus (Linnaeus, 1758). The values of the exponent b in the LWR W = aTLb ranged from 2.882 (Lota lota) to 3.517 (Cobitis taenia) and the correlation coefficient (r2) was greater than 0.96 for all species except for Cobitis taenia with 0.93. The relations allow for the accurate estimation of weight from length data with reduced handling times of fish in the field while enabling comparisons with other regions and future studies. The calculated LWRs together with species-specific abundance and catch data will be useful for fisheries modeling and estimating population status and related fish species protection, especially for the endangered species in the Elbe River.

Keywords

Elbe River, freshwater fish, Germany, length–weight relation, LWR

Introduction

Fish size is a key variable for several ecological and physiological processes such as sexual maturity, predation, mortality, and ontogenetic diet shifts (Erzini 1994; Wootton 1999; Froese and Binohlan 2000; Evans and Claiborne 2005; Byström et al. 2012) and has important implications for population dynamics (Erzini 1994). Length data are recorded in standard fish sampling programs and essential for studies on growth rates, age structure, and other aspects of fish population dynamics (Kolher et al. 1995). Weight data, in contrast, are collected less frequently in field studies due to the additional technical effort and time required to weigh fish in the field (Martin-Smith 1996; Koutrakis and Tsikliras 2003; Sinovčić et al. 2004). Length–weight relations (LWR) not only allow weight to be estimated from commonly collected length data (Beyer 1991), but also have various applications in fish biology, physiology, ecology, and fisheries assessment. These relations enable seasonal variations in fish growth to be identified and allow a rough assessment of the nutritional status through the calculation of condition indexes, e.g., the mean condition factor (Le Cren 1951; Ricker 1975; Bagenal and Tesch 1978; Richter et al. 2000; Froese 2006). LWRs are also useful to determine whether somatic growth is isometric (weight increases proportionally to length) or allometric (weight does not increase proportionally to length) (Le Cren 1951; Ricker 1975). Furthermore, they allow life history and morphological comparisons between different fish species, or between fish populations of the same species from different habitats and/or regions (Petrakis and Stergiou 1995; Gonçalves et al. 1997; Wootton 1999). Finally, LWRs are also often used in stock assessment models to estimate stock biomass from limited sample sizes, to estimate weight-at-age (Petrakis and Stergiou 1995; Koutrakis and Tsikliras 2003), and to convert growth-in-length to growth-in-weight (Pauly 1993).

LWRs have been estimated for a large number of species. However, since the variation within a species or population is large (Froese et al. 2014), local data and LWRs are likely to be more accurate. Nevertheless, LWRs for European populations of freshwater fish species are relatively rare (Verreycken et al. 2011) and mostly available for fish from lakes (Holubová et al. 2022). To the best of our knowledge, there is no published information on LWRs of fish species in the middle part of the Elbe River in Germany. The intent of this study was therefore to describe the LWRs for freshwater fish in the middle part of a large German river.

Material and methods

The Elbe River has the 4th largest catchment area in central Europe with 148 000 km2, a mean discharge of 861 m3 s–1 at its mouth, and a surface area of about 231 000 ha (Simon et al. 2005). The sampling took place in the middle part of the Elbe River at three sampling sites (stream kilometers 337–350 (52.209314°N, 11.713875°E–52.311094°N, 11.767025°E), 418–423 (52.803450°N, 12.025439°E–52.843850°N, 12.040528°E) and 452–453 (52.974142°N, 11.772764°E). Sampling was performed annually over a four-year period (1997–2000) with fishing campaigns in spring (April–May), summer (July), and early and late autumn (September and November, respectively). Fishes were caught by a combination of DC electrofishing (FEG 5000), seine netting, drift nets, and benthic multi-mesh gillnetting (mesh sizes 6–75 mm). All caught fishes were identified to species level, and total length (TL, to the nearest 0.5 cm) and wet weight (W, measurement accuracy for individuals < 5 g ± 0.1 g and for individuals > 5 g ± 1 g) were measured individually in the field.

The following species were measured and weighed individually: Abramis brama (Linnaeus, 1758); Alburnus alburnus (Linnaeus, 1758); Anguilla anguilla (Linnaeus, 1758); Ballerus ballerus (Linnaeus, 1758); Blicca bjoerkna (Linnaeus, 1758); Cobitis taenia Linnaeus, 1758; Esox lucius Linnaeus, 1758; Gobio gobio (Linnaeus, 1758); Gymnocephalus cernua (Linnaeus, 1758); Leuciscus aspius (Linnaeus, 1758); Leuciscus idus (Linnaeus, 1758); Leuciscus leuciscus (Linnaeus, 1758); Lota lota (Linnaeus, 1758); Perca fluviatilis Linnaeus, 1758; Romanogobio albipinnatus (Lukasch, 1933); Rutilus rutilus (Linnaeus, 1758); Sander lucioperca (Linnaeus, 1758); Scardinius erythrophthalmus (Linnaeus, 1758); and Squalius cephalus (Linnaeus, 1758). Fifteen other species were collected but were excluded from the analyses as they were represented by insufficient numbers.

For sex determination, subsamples of fishes from seven species (Ballerus ballerus, Gobio gobio, Leuciscus aspius, Leuciscus idus, Leuciscus leuciscus, Squalius cephalus, and Lota lota) were killed, frozen, and stored under vacuum at –22°C. Sex was determined visually after thawing, a binocular microscope (WILD M32 Typ S, Fa. Heerbrugg, Germany) was used for smaller fishes.

The collected data was subjected to quality control and defined selection criteria (Froese 2006; Froese et al. 2011; Verreycken et al. 2011). In the final dataset, species-specific LWRs were calculated for every sampled month of the year and all sampled months combined. In addition, for seven species LWRs were calculated separately for each sex. The LWRs were estimated from the formula, W = aTLb, with W being total body weight [g], TL the total length [cm], and a and b the coefficients of the regression.

The parameters a and b of LWRs were estimated by power regression analyses on the non-transformed data, and the association degree between variables (W and TL) was calculated by the coefficient of determination (r2). The standard errors (SE) and 95% confidence intervals (CI) of a and b estimates and the statistical significance level of r2 were also determined.

Linear regression analyses (least-squares method) on log-transformed TL and W data were used to test for the influence of sex on the relation between TL and W. The model fits were assessed by residual diagnostics including the visual inspection of quantile-quantile plots (QQ plots) and residuals vs. fitted plots, accompanied by tests for the residual distribution (Kolmogorov–Smirnov (KS) test), dispersion, and outliers (Hartig 2021). For all statistical hypotheses testing the significance level was set at α < 0.05.

The statistical analyses were performed with R 4.0.5 (R Core Team 2021) and the additional packages “FSA” (Ogle et al. 2021), and “nlstools” (Baty et al. 2015). The package DHARMa (Hartig 2021) was used to assess the model fits of the regression.

Results

During this study, a total of 26 434 fish representing 19 species from seven families were examined. The sample size ranged from 153 for Romanogobio albipinnatus, to 4490 for Abramis brama (Table 1). Depending on the species, the smallest total lengths measured were between 3.5 and 13 cm. The maximum length values for approximately half of the species were close to the maximum lengths observed in Europe (Kottelat and Freyhof 2007; Verreycken et al. 2011; Froese and Pauly 2022).

At the time of data collection, three of the 19 species were classified as critically endangered and six as endangered in the Red List of Fishes in Germany (Bless et al. 1998, Table 1). Furthermore, two species were classified as critically endangered and three species as endangered in the Red List of Fishes of the Federal State of Brandenburg (Knuth et al. 1998). Three of the 19 species are listed in Annex II of the Fauna-Flora-Habitat Directive (EU 1992, Table 1).

Table 1.
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Descriptive statistics and estimated length–weight-relation parameters for 19 freshwater fish species of the lowland Elbe River, Germany between months.

Species Endangered status Month n TL min TL max FishBase TLmax W min W max Length–weight relation parameters
FFH RL BB/D a 95% CI of a b 95% CI of b r²
Anguilla anguilla V/3 May 399 13.0 70.5 2 571 0.001 0.001–0.001 3.285 3.23–3.34 0.979
July 481 13.5 76.5 3 820 0.001 0.001–0.001 3.211 3.17–3.25 0.976
September 520 13.0 72.0 3 805 0.001 0.001–0.001 3.266 3.23–3.31 0.978
November 134 16.5 65.0 7 498 0.001 0.001–0.002 3.102 3.03–3.17 0.983
Total year 1547 13.0 76.5 133.0 2 820 0.0007 0.001–0.001 3.209 3.18–3.24 0.975
Cobitis taenia II 2/2 July 46 6.0 11.5 1 12 0.0007 0.001–0.001 3.926 3.65–4.21 0.950
September 68 6.0 12.0 0.8 10 0.002 0.001–0.004 3.341 3.14–3.55 0.949
Total year 124 6.0 12.0 13.5 0.8 12 0.002 0.001–0.003 3.517 3.33–3.70 0.927
Esox lucius DNE/3 May 82 5.3 78.0 1 3036 0.006 0.004–0.008 3.016 2.93–3.10 0.994
July 244 9.0 75.5 4 2725 0.008 0.007–0.010 2.931 2.88–2.98 0.994
September 170 16.0 75.5 20 2939 0.005 0.004–0.007 3.046 2.98–3.11 0.989
November 126 17.5 82.5 30 3851 0.007 0.005–0.009 2.987 2.93–3.05 0.992
Total year 652 5.3 82.5 137.0 1 3851 0.006 0.006–0.007 3.001 2.97–3.03 0.991
Gobio gobio DNE/CNE May 114 5.0 16.5 0.5 45 0.007 0.005–0.008 3.110 3.03–3.20 0.987
July 127 3.2 16.0 0.2 42 0.004 0.003–0.005 3.285 3.19–3.38 0.982
September 349 3.5 17.0 0.2 38 0.006 0.005–0.007 3.129 3.08–3.18 0.987
November 335 4.2 18.0 0.5 47 0.004 0.003–0.004 3.275 3.23–3.32 0.990
Total year 935 3.2 18.0 21.0 0.2 47 0.005 0.005–0.006 3.189 3.16–3.22 0.985
Romanogobio albipinnatus II G/2 September 70 4.0 11.5 0.3 11 0.003 0.002–0.004 3.364 3.23–3.49 0.975
November 48 5.5 12.5 1 15 0.003 0.002–0.005 3.303 3.08–3.53 0.960
Total year 153 4.0 12.5 13.0 0.3 15 0.004 0.003–0.005 3.234 3.12–3.34 0.964
Abramis brama DNE/CNE May 909 4.0 55.0 0.5 1641 0.011 0.009–0.012 2.985 2.95–3.02 0.985
July 1434 3.8 56.5 0.5 1927 0.014 0.013–0.016 2.910 2.88–2.94 0.982
September 1312 3.8 56.5 0.5 2282 0.01 0.008–0.011 3.010 2.98–3.04 0.979
November 591 4.0 55.5 0.5 1694 0.01 0.008–0.013 2.990 2.94–3.04 0.977
Total year 4490 3.8 56.5 82.0 0.5 2282 0.01 0.010–0.012 2.973 2.95–2.99 0.981
Alburnus alburnus CNE/CNE May 339 4.3 19.5 0.5 48 0.003 0.003–0.004 3.257 3.18–3.34 0.963
July 451 3.5 19.5 0.2 46 0.003 0.003–0.004 3.258 3.18–3.32 0.964
September 545 3.0 19.5 0.1 58 0.003 0.002–0.003 3.307 3.24–3.37 0.973
November 232 3.5 18.5 0.2 48 0.003 0.002–0.004 3.313 3.21–3.42 0.976
Total year 1670 3.0 19.5 25.0 0.1 58 0.003 0.003–0.003 3.288 3.25–3.32 0.969
Ballerus ballerus 3/3 May 189 8.3 45.5 3.5 86 0.002 0.002–0.003 3.355 3.29–3.42 0.989
July 107 6.5 49.0 1 1085 0.004 0.003–0.006 3.200 3.10–3.30 0.989
September 62 15.0 47.0 21 960 0.003 0.002–0.004 3.294 3.18–3.41 0.990
Total year 397 6.5 49.0 40.0 1 1085 0.003 0.002–0.003 3.294 3.25–3.34 0.989
Blicca bjoerkna DNE/CNE May 744 3.5 36.0 0.4 604 0.006 0.005–0.006 3.237 3.20–3.27 0.987
July 779 5.5 34.0 1 566 0.006 0.005–0.006 3.239 3.21–3.27 0.987
September 706 5.5 33.0 1 462 0.006 0.006–0.007 3.188 3.16–3.22 0.983
November 413 4.3 33.5 0.7 432 0.006 0.004–0.007 3.25 3.18–3.32 0.972
Total year 2871 3.3 39.0 45.5 0.2 660 0.006 0.006–0.006 3.227 3.21–3.25 0.982
Leuciscus aspius II DNE/3 May 157 6.0 67.5 1 2398 0.006 0.005–0.009 3.051 2.98–3.13 0.994
July 252 4.0 69.5 0.3 2580 0.007 0.006–0.009 3.032 2.98–3.08 0.994
September 351 4.9 69.0 0.5 2731 0.003 0.003–0.004 3.222 3.17–3.28 0.992
November 173 6.5 71.5 1.5 3351 0.002 0.002–0.003 3.315 3.23–3.40 0.990
Total year 1003 4.0 71.5 120.0 0.3 3351 0.004 0.003–0.004 3.187 3.15–3.22 0.990
Leuciscus idus 3/3 May 721 5.0 49.0 0.7 1699 0.004 0.004–0.004 3.319 3.29–3.35 0.987
July 942 3.0 48.0 0.2 1598 0.004 0.004–0.004 3.306 3.29–3.32 0.994
September 966 4.0 47.0 0.6 1625 0.003 0.003–0.003 3.390 3.37–3.41 0.992
November 403 6.5 47.0 2 1496 0.002 0.002–0.003 3.492 3.43–3.56 0.987
Total year 3134 3.0 49.0 85.0 0.2 1699 0.003 0.003–0.004 3.364 3.35–3.38 0.987
Leuciscus leuciscus 3/3 May 77 3.5 19.5 0.3 74 0.003 0.002–0.003 3.439 3.35–3.52 0.986
July 85 5.5 17.5 1 46 0.004 0.003–0.005 3.313 3.19–3.44 0.978
September 90 4.8 20.0 0.7 75 0.003 0.003–0.004 3.349 3.28–3.42 0.993
November 41 7.5 20.0 2 68 0.003 0.002–0.004 3.356 3.29–3.42 0.995
Total year 297 3.5 20.0 40.0 0.3 75 0.003 0.003–0.004 3.348 3.30–3.40 0.996
Rutilus rutilus DNE/CNE May 779 3.5 29.5 0.3 311 0.004 0.004–0.004 3.347 3.32–3.37 0.988
July 1194 3.2 28.5 0.2 303 0.004 0.004–0.004 3.345 3.32–3.37 0.987
September 1343 3.5 43.5 0.3 1141 0.004 0.004–0.004 3.339 3.33–3.35 0.994
November 573 3.8 36.0 0.4 627 0.003 0.003–0.003 3.448 3.41–3.49 0.987
Total year 4135 3.2 43.5 50.2 0.2 1141 0.003 0.003–0.004 3.390 3.38–3.40 0.990
Scardinius erythrophthalmus DNE/CNE July 61 5.0 28.0 1 259 0.008 0.007–0.009 3.129 3.09–3.17 0.998
September 42 7.0 17.0 3 55 0.007 0.004–0.011 3.194 2.99–3.41 0.970
Total year 144 4.8 28.0 61.7 1 259 0.007 0.006–0.008 3.173 3.14–3.21 0.995
Squalius cephalus CNE/CNE May 295 4.3 42.5 0.6 755 0.012 0.011–0.012 2.962 2.94–2.98 0.995
July 351 5.5 28.5 1 274 0.004 0.005–0.006 3.246 3.22–3.28 0.992
September 385 4.2 39.5 0.5 699 0.005 0.004–0.005 3.263 3.24–3.29 0.991
November 293 4.2 43.0 0.4 1056 0.003 0.003–0.003 3.408 3.39–3.43 0.998
Total year 1350 4.2 43.0 60.0 0.4 1056 0.005 0.005–0.005 3.240 3.22–3.26 0.990
Lota lota 2/2 May 54 3.0 33.0 0.2 282 0.006 0.004–0.014 2.993 2.80–3.19 0.967
July 162 5.7 41.0 1 545 0.007 0.005–0.009 3.024 2.95–3.10 0.975
September 171 8.0 41.5 3 367 0.017 0.013–0.022 2.711 2.63–2.80 0.969
November 107 9.5 38.5 5 381 0.005 0.003–0.007 3.111 3.00–3.22 0.977
Total year 498 3.0 41.5 152.0 0.2 545 0.010 0.008–0.012 2.882 2.83–2.94 0.965
Gymnocephalus cernua DNE/CNE May 74 6.2 16.0 2 52 0.008 0.006–0.011 3.111 2.99–3.23 0.980
July 96 3.7 17.0 0.5 53 0.012 0.009–0.015 2.969 2.86–3.07 0.978
September 194 6.0 18.0 2 87 0.004 0.003–0.004 3.462 3.38–3.54 0.980
November 176 5.5 16.0 1.5 57 0.006 0.005–0.007 3.269 3.18–3.36 0.976
Total year 562 3.7 18.0 25.0 0.5 87 0.006 0.005–0.007 3.272 3.22–3.32 0.974
Perca fluviatilis DNE/CNE May 626 3.3 40.5 0.3 868 0.006 0.005–0.007 3.234 3.20–3.27 0.985
July 933 3.8 43.5 0.4 1230 0.005 0.005–0.005 3.280 3.27–3.29 0.995
September 1279 5.0 43.5 1 1438 0.004 0.003–0.004 3.392 3.37–3.41 0.987
November 564 5.0 40.5 1 970 0.005 0.004–0.005 3.327 3.30–3.35 0.993
Total year 3438 3.3 43.5 60.0 0.3 1438 0.004 0.004–0.004 3.342 3.33–3.35 0.987
Sander lucioperca V/CNE July 50 4.5 71.5 0.5 3313 0.002 0.002–0.003 3.331 3.23–3.43 0.998
September 59 7.5 76.5 2 4184 0.003 0.002–0.004 3.300 3.19–3.42 0.996
November 52 9.0 76.0 4 4551 0.002 0.001–0.002 3.416 3.32–3.52 0.996
Total year 198 4.5 76.5 100.0 0.5 4551 0.002 0.002–0.003 3.316 3.24–3.39 0.993

n = sample size, TL = total length [cm], W = weight [g], min = minimum, max = maximum, a = regression intercept, b = slope of regression line, CI = confidence interval, r² = coefficient of correlation. FFH = FFH Fauna-Flora-Habitat Directive (EU 1992): II = listed in the Annex II Animal and plant species of community interest whose conservation requires the designation of special areas of conservation; RL BB/D = RL-BB Red List of the Federal State of Brandenburg (Knuth et al. 1998); RL-D Red List of Germany (Bless et al. 1998): 2 = critically endangered, 3 = endangered, G = endangered status is assumed, V = declining, Pre-warning list, CNE = currently not considered endangered, DNE = definitely not endangered. Note: Total year can include additional data from other months with fewer individuals than 30 per species that were not separately shown in the table.

The linear regression analyses indicated that there were no significant differences in slopes between males and females in the seven species where this effect could be tested (Table 2).

The power regressions were significant for all species (p < 0.001). The r2 was ≥ 0.99 for seven of the species and was greater than 0.96 for all other species except for Cobitis taenia with 0.93 (Table 1). The regression parameters a (intercept) and b (slope) differed between species. The parameters a and b ranged from 0.0005 ± 0.0001 (mean ± SE) (Anguilla anguilla, May) to 0.017 ± 0.003 (Lota lota, September) and from 2.711 ± 0.044 (Lota lota, September) to 3.926 ± 0.138 (Cobitis taenia, July), respectively. Both parameters varied also between the sampling months with comparably small standard errors in the estimates for a (Table 1). With Rutilus rutilus, for example, the parameter a ranged from 0.003 in November to 0.004 in the other sampling months. The parameter b ranged from 3.339 ± 0.005 in September to 3.448 ± 0.02 in November. The estimates of a for Perca fluviatilis, in contrast, varied between 0.004 in September to 0.006 in May. The b values were lowest in May (3.234 ± 0.017) and highest in September (3.392 ± 0.011). With Esox lucius, the estimates for a were higher and ranged from 0.005 in September to 0.008 in July. The b estimates were slightly lower than those of Rutilus rutilus and Perca fluviatilis and ranged from 2.931 ± 0.025 in July to 3.046 ± 0.034 in September (Table 1).

Table 2.
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Descriptive statistics and estimated length–weight-relation parameters by sex for seven freshwater fish species of the lowland Elbe River, Germany.

Species Sex n TL min TL max W min W max Length–weight relation parameters
a 95% CI of a b 95% CI of b r²
Gobio gobio Male 40 9.5 16.5 6 37 0.009 0.005–0.016 2.972 2.77–3.17 0.964
Female 37 9.5 17.0 7 45 0.005 0.003–0.010 3.183 2.94–3.43 0.964
Both 77 9.5 17.0 6 45 0.007 0.004–0.010 3.094 2.94–3.25 0.963
Ballerus ballerus Male 29 23.0 43.5 88 660 0.005 0.003–0.008 3.149 3.01–3.29 0.991
Female 23 16.5 47.0 27 980 0.004 0.001–0.008 3.236 3.00–3.48 0.988
Both 52 16.5 47.0 27 980 0.004 0.002–0.006 3.209 3.08–3.34 0.989
Leuciscus aspius Male 45 12.5 64.5 13 2175 0.009 0.004–0.018 2.972 2.80–3.15 0.983
Female 49 14.5 66.5 22 2639 0.002 0.001–0.003 3.402 3.26–3.55 0.991
Both 94 12.5 66.5 13 2639 0.004 0.002–0.006 3.216 3.09–3.35 0.984
Leuciscus idus Male 64 11.5 43.5 15 1089 0.005 0.003–0.007 3.258 3.15–3.37 0.991
Female 62 12.5 48.0 15 1699 0.003 0.001–0.006 3.404 3.21–3.61 0.976
Both 126 11.5 48.0 15 1699 0.002 0.001–0.004 3.450 3.31–3.59 0.976
Leuciscus leuciscus Male 24 10.0 19.5 6 74 0.002 0.001–0.003 3.620 3.44–3.80 0.984
Female 30 10.0 20.0 7 75 0.003 0.002–0.005 3.358 3.19–3.53 0.985
Both 54 10.0 20.0 6 75 0.003 0.002–0.004 3.439 3.32–3.56 0.983
Squalius cephalus Male 44 11.0 38.0 12 650 0.004 0.003–0.006 3.312 3.12–3.42 0.994
Female 63 10.5 43.0 9 1056 0.003 0.003–0.004 3.383 3.33–3.44 0.997
Both 107 10.5 43.0 9 1056 0.003 0.003–0.004 3.366 3.32–3.41 0.996
Lota lota Male 26 11.0 38.5 9 381 0.007 0.003–0.017 3.000 2.73–3.27 0.959
Female 37 11.0 37.0 9 404 0.008 0.002–0.028 2.946 2.59–3.31 0.917
Both 63 11.0 38.5 9 404 0.008 0.004–0.016 2.967 2.74–3.20 0.933

n = sample size, TL = total length [cm], W = weight [g], min = minimum, max = maximum, a = regression intercept, b = slope of regression line, CI = confidence interval, r² = coefficient of correlation.

Discussion

Although various studies investigated the fish populations from the Elbe River, LWRs are only available for ten species (Hölker and Hammer 1994; Holubová et al. 2022). To the authors’ best knowledge, this study provides the first references on LWRs for the Romanogobio albipinnatus worldwide, for 15 species in German waters and nine species from the Elbe River (Froese and Pauly 2022; Holubová et al. 2022). Finally, this study shows LWRs of seven fish species whose LWRs exist in fewer than five literature sources in Europe.

Due to the size selectivity of the fishing gear, the majority of samples did not include juveniles or very small individuals. According to Petrakis and Stergiou (1995), the respective LWR should only be used for the size range for which data were available when estimating the linear regression parameters. For this reason, the extrapolating of the relations to fish larvae (Pepin 1995), juveniles (Safran 1992), or immature stages (Bagenal and Tesch 1978) can lead to inaccurate results and is not recommended.

Our samples were always collected in the same four months in four consecutive years. For comparisons with, for example, other ecological regions or future studies, the calculated mean annual values can be considered (Petrakis and Stergiou 1995; Gonçalves et al. 1997). The observed b values of the LWRs in our study were within the limits reported for all fish species (2–4 by Bagenal and Tesch 1978 and 2.5–3.5 by Froese 2006). Despite the different body shapes of the fish species, b is in the majority of fish species larger than 3.0 indicating positive allometric growth (increase in relative body thickness) (Froese 2006; Verreycken et al. 2011). In this study, two species (Abramis brama and Esox lucius) showed isometric growth (b = 3), one species (Lota lota) showed slightly negative allometric growth (b < 3), and the remaining species showed slightly positive to positive allometric growth (b > 3).

Additionally, we have also calculated month-specific LWRs that represent specific seasons of the year. LWRs are not constant throughout the year and can vary depending on factors such as food availability, gonad development, and spawning period (Le Cren 1951; Bagenal and Tesch 1978; Froese 2006; DeWeber et al. 2021). Parameter b is characteristic of the species (Mayrat 1970) and generally does not vary distinctly throughout the year (Le Cren 1951; Bagenal and Tesch 1978; Froese 2006). The small differences in b-values between sampling months within a species found in our study can be attributed to the following factors:

  • differences in the number and size range of specimens examined,
  • effect of the year or season and
  • health and general fish condition (Le Cren 1951; Froese 2006).

The parameter a, however, can vary substantially in days, seasons, and/or habitats (Le Cren 1951; Bagenal and Tesch 1978; Froese 2006). The differences in the parameters between months and years found in our study highlight the importance of considering season and sampling year when calculating and applying LWRs.

Within a fish species, LWRs can significantly differ depending on sex, life stage (larvae, ages 0 and 1 and for sexually mature males and females), and stage of gonadal development (Le Cren 1951; Froese 2006; DeWeber et al. 2021). In the presently reported study, no significant differences between males and females were observed in the seven species that had been caught in sufficient numbers for comparisons (Table 2). This suggests a lack of pronounced sexual dimorphism concerning the LWR for these species, which is similar to the results of Morato et al. (2001) who found significant differences between males and females for only two of 15 coastal fish species of the Azores.

A limitation of the study is that the data and LWRs represent conditions from over 20 years ago which may no longer be representative of the Elbe River. Since conditions including productivity and temperature might have changed in the meantime, the data can be only used as examples for potentially typical LWRs for the studied species in the same ecoregion. These data nevertheless provide the first LWRs for many species of the study region, and future studies can investigate whether the LWRs have changed substantially over time.

Conclusions

The calculated LWRs allow us to dispense with weighing fish in the field during data collection and still get accurate weight estimates for fishes of the middle Elbe River. This allows less and shorter handling, less skin contact with objects, less damage to the mucosa, and minimizes stress, which is especially important for rare and protected fish species and leads to lower costs due to the time saved.

For the Elbe River, data regarding the abundances and biomass composition of catches as well as densities of the individual species in the shore zone and an open water area of groin fields, training walls, and mainstream exists (Fladung 2002a, 2002b). Thus, the additionally calculated LWRs will be useful for fisheries management and the protection of especially the endangered fish species in the Elbe River.

Acknowledgments

We thank Herbert Ebel and Peter Schoppe for their technical assistance and support and the fishermen for their cooperation in collecting samples. We also thank David Ritterbusch and Tyrell DeWeber for helpful discussions on earlier drafts of the manuscript and who kindly improved the English. The work was part of the project “Ökologische Zusammenhänge zwischen Fischgemeinschafts- und Lebensraumstrukturen der Elbe” supported by the Bundesministerium für Bildung, Forschung und Technologie (BMB+F, grant No. 0339578).

References

  • Bagenal TB, Tesch FW (1978) Age and growth. Pp. 101–136. In: Bagenal TB (Ed.) Methods for assessment of fish production in fresh waters. 3rd Edition. IBP Handbook No. 3. Blackwell Scientific Publications, Oxford, UK.
  • Baty F, Ritz C, Charles S, Brutsche M, Flandrois JP, Delignette-Muller ML (2015) A toolbox for nonlinear regression in R: The package nlstools. Journal of Statistical Software 66(5): 1–21. https://doi.org/10.18637/jss.v066.i05
  • Beyer JE (1991) On length–weight relationships. 2. Computing mean weights from length statistics. Fishbyte 9(2): 50–54.
  • Bless R, Lelek A, Waterstraat A (1998) Rote Liste der in Binnengewässern lebenden Rundmäuler und Fische (Cyclostomata & Pisces). Schriftenreihe für Landschaftspflege und Naturschutz 55: 53–59.
  • Byström P, Huss M, Persson L (2012) Ontogenetic constraints and diet shifts in Perch (Perca fluviatilis): Mechanisms and consequences for intra-cohort cannibalism. Freshwater Biology 57(4): 847–857. https://doi.org/10.1111/j.1365-2427.2012.02752.x
  • DeWeber JT, Rösch R, Baer J, Brinker A (2021) Long-term changes in body condition and gillnet selectivity in Lake Constance pelagic spawning whitefish (Coregonus wartmanni). Canadian Journal of Fisheries and Aquatic Sciences 78(7): 841–851. https://doi.org/10.1139/cjfas-2020-0231
  • EU (1992) Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora. Official Journal of the European Union L 206: 22.7.1992, 7–50.
  • Fladung E (2002a) Untersuchungen zum adulten Fischbestand im Hauptstrom (Fahrrinne) der Mittelelbe. Zeitschrift für Fischkunde. Supplementband 1: 121–131.
  • Fladung E (2002b) Der präadulte/adulte Fischbestand in Buhnenfeldern und Leitwerken der Mittelelbe. Zeitschrift für Fischkunde. Supplementband 1: 101–120.
  • Froese R, Binohlan C (2000) Empirical relationships to estimate asymptotic length, length at first maturity and length at maximum yield per recruit in fishes, with a simple method to evaluate length frequency data. Journal of Fish Biology 56(4): 758–773. https://doi.org/10.1111/j.1095-8649.2000.tb00870.x
  • Froese R, Thorson JT, Reyes Jr RB (2014) A Bayesian approach for estimating length–weight relationships in fishes. Journal of Applied Ichthyology 30(1): 78–85. https://doi.org/10.1111/jai.12299
  • Gonçalves JMS, Bentes L, Lino PG, Ribeiro J, Canário AVM, Erzini K (1997) Weight–length relationships for selected fish species of the small-scale demersal fisheries of the south and south-west coast of Portugal. Fisheries Research 30(3): 253–256. https://doi.org/10.1016/S0165-7836(96)00569-3
  • Hölker F, Hammer C (1994) Growth and food of ruffe Gymnocephalus cernuus (L.) in the Elbe Estuary. Archiv für Fischerei- und Meeresforschung 42(1): 47–62.
  • Holubová K, Musilová Z, Horká P (2022) Regression analysis of the length–weight relationships for 17 common European fish in rivers in the Czech Republic. European Journal of Environmental Sciences 12(2): 90–92. https://doi.org/10.14712/23361964.2022.11
  • Knuth D, Rothe U, Zerning M (1998) Rote Liste und Artenliste der Rundmäuler und Fische des Landes Brandenburg (Cyclostomata u. Pisces). Naturschutz und Landschaftspflege Brandenburg, no. 7, Beilage, 19 pp.
  • Kolher N, Casey J, Turner P (1995) Length–weight relationships for 13 species of sharks from the western North Atlantic. Fish Bulletin 93(2): 412–418.
  • Kottelat M, Freyhof J (2007) Handbook of European freshwater fishes. Kottelat, Cornol, Switzerland and Freyhof, Berlin, Germany, 646 pp.
  • Le Cren ED (1951) The length–weight relationship and seasonal cycle in gonad weight and condition in the perch (Perca fluviatilis). Journal of Animal Ecology 20(2): 201–219. https://doi.org/10.2307/1540
  • Mayrat A (1970) Allometric et taxinomie. Revue de Statistique Appliquee 18(4): 47–58.
  • Morato T, Afonso P, Lourinho P, Barreiros JP, Santos RS, Nash RDM (2001) Length–weight relationships for 21 coastal fish species of the Azores, North eastern Atlantic. Fisheries Research 50(3): 297–302. https://doi.org/10.1016/S0165-7836(00)00215-0
  • Pauly D (1993) FishByte section editorial. Naga, ICLARM Quarterly 16, 26 pp.
  • Pepin P (1995) An analysis of the length–weight relationship of larval fish: Limitations of the general allometric model. Fish Bulletin 93(2): 419–426.
  • R Core Team (2021) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
  • Richter HC, Luckstadt C, Focken U, Becker K (2000) An improved procedure to assess fish condition on the basis of length–weight relationships. Archiv für Fischerei- und Meeresforschung 48(3): 255–264.
  • Ricker WE (1975) Computation and interpretation of biological statistics of fish populations. Bulletin of the Fisheries Research Board of Canada 191: 1–382.
  • Simon M, Bekele V, Kulasová B, Maul C, Oppermann R, Řehák P (2005) Die Elbe und ihr Einzugsgebiet – Ein geographisch-hydrologischer und wasserwirtschaftlicher Überblick. Internationale Kommission zum Schutz der Elbe, Magdeburg, 258 pp.
  • Sinovčić G, Franičević M, Zorica B, Čikeš-Keč V (2004) Length–weight and length–length relationships for 10 pelagic fish species from the Adriatic Sea (Croatia). Journal of Applied Ichthyology 20(2): 156–158. https://doi.org/10.1046/j.1439-0426.2003.00519.x
  • Verreycken H, Van Thuyne G, Belpaire C (2011) Length–weight relationships of 40 freshwater fish species from two decades of monitoring in Flanders (Belgium). Journal of Applied Ichthyology 27(6): 1416–1421. https://doi.org/10.1111/j.1439-0426.2011.01815.x
  • Wootton RJ (1999) Ecology of teleost fishes. 2nd edn. Fish and Fisheries Series No. 24, Springer Netherlands, 400 pp.
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