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Article

Influence of Longitudinal Fragmentation on Length–Weight Relationships of Fishes in the Someșul Cald River, Romania

by
Paul Uiuiu
1,2,
Radu Constantinescu
1,2,*,
Tudor Păpuc
1,2,
George-Cătălin Muntean
1,2,
Maria Cătălina Matei-Lațiu
3,
Anca Becze
4,
Daniel Cocan
1,2,
Călin Lațiu
1,2,* and
Cristian Olimpiu Martonoș
5
1
Department of Fundamental Sciences, Faculty of Animal Science and Biotechnologies, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, 3-5 Mănăştur Street, RO-400372 Cluj-Napoca, Romania
2
Fisheries and Aquaculture Research Laboratory, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, 3-5 Mănăștur Street, RO-400372 Cluj-Napoca, Romania
3
Department of Animal Physiology, Faculty of Veterinary Medicine, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, 3-5 Mănăștur Street, RO-400372 Cluj-Napoca, Romania
4
National Institute for Research and Development of Optoelectronics INOE 2000, Research Institute for Analytical Instrumentation, 67 Donath Str., RO-400293 Cluj-Napoca, Romania
5
Department of Biomedical Sciences, Ross University School of Veterinary Medicine, Basseterre P.O. Box 334, Saint Kitts and Nevis
*
Authors to whom correspondence should be addressed.
Fishes 2024, 9(10), 420; https://doi.org/10.3390/fishes9100420
Submission received: 6 September 2024 / Revised: 17 October 2024 / Accepted: 17 October 2024 / Published: 21 October 2024
(This article belongs to the Special Issue Aquatic Biodiversity Challenges in the Third Millennium)

Abstract

:
Romania has a rich hydrographic network, which permitted the construction of over 80 large dams on its water courses, estimating a number between 545 and 674 hydropower plants that were either built or were in a different construction stage on the rivers of Romania in 2021. These hydropower plants were often built outside specific legislation regarding ecological impacts, especially before 1990. Longitudinal fragmentation of rivers causes severe ecological impacts on biodiversity, food chains, and nutrient cycles. Someșul Cald River is the main tributary of Someșul Mic River, the most important water source for the northwestern region of Transylvania. On its course, several dams and reservoirs were built from 1968 to 1980 for electricity production and population freshwater supply. The present study aimed to analyze the length–weight relationships (LWRs) and condition factors occurring in the longitudinally fragmented Someșul Cald River. The LWRs, relative condition factor Kn, and Fulton condition factor K were determined based on total length and wet body weight. Comparisons of LWRs, Kn, and K across river sections constrained by dams showed that some fish species exhibited similar growth patterns and physiological conditions, while others differed significantly. Freshwater fish physiology is altered by longitudinal fragmentation, both natural and artificial. Barriers such as dams influence the energy gradient, limiting feed availability and, consequently, the life history of fish species. Long-term management plans regarding conservation should take into consideration existing fish species population dynamics, along with their physiological and somatic status.
Key Contribution: This paper presents the somatic indices (LWRs) of fishes from Someșul Cald River, which is fragmented into two sections by a large dam.

Graphical Abstract

1. Introduction

Rivers have always been viewed as regenerative sources of water, food, communication, and energy for human societies. However, their exploitation has made them one of the most threatened systems in the world [1]. Lotic ecosystems represent complex structures with a multi-dimensional framework [2]. Water-mediated connectivity has four dimensions: longitudinal (spring to confluence); lateral (minor riverbedmajor riverbedflood plains); vertical (groundwater); and temporal (changes in time of the longitudinal, lateral, and vertical dimensions) [2,3]. Longitudinal fragmentation may cause severe ecological impacts on biodiversity, alteration of food webs, and nutrient cycles. Riverine ecosystems provide an effective carbon cycle and downstream transportation of organic matter and sediments [4]. There is a large body of work documenting the non-beneficial impact of dams and hydropower plants on fish migration and genetic diversity [5,6,7,8]. Mainly, longitudinal fragmentation causes loss of habitat, blocks migration, limits access to suitable breeding habitats, and produces a decrease in native populations and, in some cases, the emergence of invasive species [9,10,11]. Thus, it is important to monitor fish populations in such areas for preventing or taking measures against adverse changes in ichthyofauna.
Continuous surveys of ichthyofauna regarding species composition and growth patterns are essential for creating and implementing proper management plans for aquatic environments. Usually, in the case of water bodies with important roles in the economy such as water supply, hydropower, transportation, commercial fishing, angling/recreational fishing, sport fishing, etc., the ichthyofauna data are based on general observations of the catch from activities such as fishing. However, assessments on ichthyofauna based only on sporadic data from specific fishing activities are subject to biases because of fishing gear and fishing technique selectivity [12]. If there are only a few target species of a specific weight, fishing/angling may be the best sampling instrument as it allows high selectivity. However, when the target is represented by the entire ichthyofauna in an area, angling techniques are not a proper instrument.
A simple, commonly used analysis technique in fisheries management is the length–weight relationship (LWR). In fish, the LWR helps predict weight from length, weight at age, stock assessment, and the well-being of fish populations [13]. Data on biometric relationships such as LWRs and other condition factors (Fulton’s condition factor, K or relative condition factor, Kn) are scarce in catch reports, despite the relatively low cost and effort (length and weight determinations), causing a deficiency in management plans [14]. Moreover, it is important to highlight that both the relative condition factor (Kn) and Fulton’s condition factor (K) are based on the assumption that heavier fish of a given length are in better condition. These indices are widely used in fisheries science to assess the health and nutritional status of fish stocks, as well as to evaluate the impact of parasites and other stressors on aquatic organisms. In addition, measuring fish condition can provide an efficient and straightforward method for assessing the quality of environmental conditions, as variations in fish condition may reflect changes in water quality, food availability, and overall ecosystem health on a local and global scale [15,16].
Romania has a rich hydrographic network, which permitted the construction of over 80 large dams on its water courses [17]. By 2021, an estimate of between 545 and 674 hydropower plants were either built or were being built on the rivers of Romania [18]. However, this number is declining due to high taxes and an infringement procedure started by the European Commission in 2015 [19]. These hydropower plants are often built without regard for their economic and ecological impacts, especially on fish populations [20].
The present study aimed to analyze whether changes in the lengths and weights of fish, changes in the LWRs, and changes in the condition factors occurred in a longitudinally fragmented water body from a mountainous area in Transylvania, Romania.

2. Materials and Methods

2.1. Study Area and Longitudinal Fragmentation

In the present research, we have mapped the Someșul Cald Basin, with a specific focus on its dams, employing advanced geographic information systems (GIS) techniques. This approach has allowed us to delineate [21] the basin’s hydrological features precisely and to assess the impacts of existing dams [22] on water flow, ecosystem health, and local communities. The GIS-based analysis not only provides valuable insights into the spatial distribution [22,23,24,25] and environmental implications [26,27] of these infrastructures but also aids in the strategic planning for future water resource management and conservation efforts within the basin. Someșul Cald River springs from the Bihariei-Vlădeasa massif at an altitude of 1550 m and is the main spring for Someșul Mic River (Someș-Tisza Catchment). Someșul Cald River crosses a large area of the Apuseni Natural Park. It is a highly fragmented water body; on its course occur three dams and reservoirs (Beliș Fântânele, Tarnița, and Someșul Cald) to the confluence with Someșul Rece River (located upstream of the Gilău Dam). The last two dams (Tarnița and Someșul Cald) were built in a cascade and are connected with an artificial canal (less than 1 km).
To assess the influence of longitudinal fragmentation, we classified the river into two sections: (1) T1—the downstream section extending from the inlet of the Tarniţa Reservoir to the Beliș-Fântânele Dam Reservoir; (2) T2—the upstream section extending from the inlet of the Beliș-Fântânele Reservoir to the springs of Someșul Cald River (Figure 1) [28].

2.2. Environmental Characteristics

The main environmental characteristics were determined as follows: water depth (15 determinations per station (measuring rod)); riverbed width (5 determinations per station (measuring tape)); altitude and GPS coordinates (2 determinations, start and end of station (Garmin Etrex 20X GPS device, Garmin, Olathe, KS, USA)) [28]. The main water parameters (dissolved oxygen, pH, conductivity, and temperature) were determined at the time of fish sampling using a Hanna HI-9828 multi-parameter (Hanna Instruments, Cluj-Napoca, Romania) (1 determination per station).

2.3. Fish Sampling and Body Measurements

Fish sampling was performed via backpack electrofishing using a SAMUS 725 MP apparatus (SAMUS Special Electronics, Warsaw, Poland), powered by a 12 V and 24 A rechargeable battery. Water conductivity was tested before electrofishing to adjust the output current at non-lethal frequencies. Fishes were weighted (BW—wet body weight) and measured (TL—total length of fish) to obtain raw data for length–weight relationship (LWRs) analysis, relative condition factor, and Fulton’s condition factor. Total number of samples (species, specimens) and number of samples from each river section/station are presented in Tables S1 and S2.

2.4. LWR, Relative Condition Factor Kn, and Fulton Condition Factor K

LWRs were determined using the formula BW = aTLb, where a and b are the coefficients of the regression between BW (wet body weight) and TL (total length of the fish) [29]. The values of coefficients a and b were determined via least-square linear regression from the log-transformed values of TL and BW using the formula BW = log a + b log TL [30,31,32]. To determine the type of growth for the sampled specimens, values of the b exponent were analyzed as follows: positive allometric growth if b > 3; negative allometric growth if b < 3; and isometric growth if b = 3 [33]. Confidence intervals (CI) at 95% were calculated to determine whether the b values from the linear regressions significantly differed from the isometric value (b = 3), providing a statistical measure of the deviation from expected scaling. In addition, the t-test was used to determine if the obtained b value was significantly different from the isometric value and to establish the growth type. The null hypothesis of isometric growth (H0: b = 3) was tested for α = 0.05 [13]. When s type-II error (defined, in general, as the probability of incorrectly failing to reject the null hypothesis) was encountered, possibly due to the low number of specimens, the growth type was assessed based on the method described by Brown and Vavrek [34], using the suggested term “soft isometry” (s.ISO).
The relative condition factor (Kn) of each individual was determined via the following equation: Kn = Wo/We, where W0 is the observed weight, and We is the expected weight determined from the LWRs [35]. The fish condition can be evaluated as follows: Kn ≥ 1, when the fish growth condition is good; and Kn < 1, when the fish growth condition is poor [29].
Fulton condition factor (K) was determined using the formula K = 100*BW/TL3, where BW is wet body weight and TL is total length [36]. An unpaired t-test was used to determine if statistically significant differences exist in terms of Fulton condition factor K between individuals of the same species from T1 and T2 river stations. Body measurements, calculations, and regression were performed on the combined sexes.

2.5. Statistical Analysis

Statistical analysis was conducted using Microsoft Excel Version 18.2306.1061.0 software and GraphPad Prism 8.0.1. Before statistical testing, data were inspected for normal distribution. Comparisons were performed according to the normal distribution of data and also according to fish species presence, absence, and the number of individuals observed in each section and sections combined (T1, T2, and T1 + T2). Data that had 3 groups and normal distribution was tested using the following parametric tests: one-way ANOVA followed by a post hoc Tukey’s multiple comparison test. When normal distribution was not satisfied, the non-parametric Kruskal–Wallis test, followed by post hoc Dunn’s multiple comparison tests, was used. When data composed of two groups were analyzed, the Mann–Whitney U test was used [37].

3. Results

3.1. Study Area, Longitudinal Fragmentation, and Environmental Characteristics

The study was conducted from August to September 2018. The altitude of the T1 river section ranged from 516 m (N 46°42.413′ E 23°12.932′) to 834 m (N 46°41.959′ E 23°04.825′), and T2 ranged from 999 m (N 46°38.766′ E 22°52.112′) to 1153.5 m (N 46°38.310′ E 22°43.131′). The altitude difference between the upper limit of T1 and the lower limit of T2 (approximately 165 m) was caused by the height of the Beliș-Fântânele Dam (Figure 1). Water depth in T1 ranged from 20.4 cm to 55.8 cm; while in T2, it ranged from 16.4 cm to 42 cm. Riverbed width in T1 ranged from 4.48 m to 9.53 m; while in T2, it ranged from 4.3 m to 24.68 m. Dissolved oxygen in T1 ranged from 10.45 mg/L to 12.07 mg/L; and in T2, it ranged from 9.4 mg/L to 13.32 mg/L. In T1, the pH ranged from 6.12 to 7.23; and in T2, it ranged from 6.94 to 7.33. The water temperature in T1 ranged from 11.3 °C to 14.1 °C; and in T2, it ranged from 10.4 °C to 14.89 °C.

3.2. Fish Sampling (Inclusion and Exclusion Criteria)

A total of 1789 specimens were analyzed (T1: n = 761 vs. T2: n = 1028) and grouped into 12 species and 8 families (Petromyzontidae, Cyprinidae, Leuciscidae, Cobitidae, Nemacheilidae, Salmonidae, Cottidae, and Percidae). A detailed overview of the specimens captured during this research is presented in Table S1. The comparisons for the LWR between the river sections were made based on the presence, absence, and number of individuals. In this sense, four situations were observed:
  • The species was present in both river sections (T1 and T2), and the number of individuals from each river section was ≥3. In this category, six species were observed: Squalius cephalus, Salmo trutta, Phoxinus phoxinus, Eudontomyzon danfordi, Cottus gobio, and Barbus carpathicus.
  • The species was present in both river sections (T1 and T2), and the number of individuals from one of the sections was <3; while in the other station, the number of individuals was >3. In this category, two species were observed: Thymallus thymallus and Barbatula barbatula.
  • The species was present in both river sections, and the number of individuals was <3 in each river section. Also, the sum of individuals (T1 + T2) was <3. In this category, one species was observed: Cobitis elongatoides.
  • The species was present only in one of the river sections, and the number of observed specimens was <3. In this category, three species were observed: Salmo labrax, Rutilius rutilus, and Perca fluviatilis.

3.3. LWRs, Relative Condition Factor Kn, and Fulton’s Condition Factor K

3.3.1. LWRs

According to our study, in the T1 river section (downstream course of the river), three species had isometric growth (E. danfordi, B. carpathicus, and S. trutta), three species had positive allometric growth (P. phoxinus, S. cephalus, and C. gobio), and one species had soft isometric growth (B. barbatula). For two species (T. thymallus and C. elongatoides), the LWRs were not determined due to the small number of specimens. The determined LWRs for the T2 river section (upstream course of the river) showed isometric growth for three species (B. carpathicus, P. phoxinus, and C. gobio). S. cephalus, S. trutta, and T. thymallus showed positive allometric growth. One species presented soft isometric growth (E. danfordi). Due to the small number of specimens, the LWRs for R. rutilus, C. elongatoides, B. barbatula, S. labrax, and P. fluviatilis, were not determined. When the LWRs analysis was performed on fishes from both river sections combined (T1 + T2), four species had isometric growth (E. danfordi, B. carpathicus, P. phoxinus, and C. gobio), three species had positive allometric growth (S. cephalus, S. trutta, and T. thymallus), one species had soft isometric growth (B. barbatula), and for the remaining four species (R. rutilus, C. elongatoides, S. labrax, and P. fluviatilis), LWRs were not determined due to the small number of specimens (Table S1). The similarities and dissimilarities in terms of growth type for the analyzed fish species are presented in Table 1. The growth type of E. dafordi showed isometric growth in T1, soft isometric growth in T2, and isometric growth when T1 and T2 were combined. Barbus carpathicus showed isometric growth in T1, T2, and T1 + T2. Phoxinus phoxinus showed positive allometric growth in T1, isometric growth in T2, and isometric growth in combined samples (T1 + T2). Squalius cephalus showed positive allometric growth in T1, T2, and in combined samples (T1 + T2). For R. rutilus, LWR was not determined due to its absence from T1 and the small number in T2 (n = 1). The LWR for C. elongatoides was not determined due to its small numbers in T1 (n = 1), T2 (n = 1), and T1 + T2 (n = 2). B. barbatula showed soft isometric growth in T1; while in T2, the number of individuals was too small (n = 1) to be analyzed. Soft isometric growth was determined for B. barbatula for the combined river sections (T1 + T2). One specimen of S. labrax and one of P. fluviatilis were observed, and the LWR was not determined. S. trutta showed isometric growth in T1, positive allometric growth in T2, and positive allometric growth when specimens from both river sections were analyzed in combination. The number of T. thymallus was too small to be analyzed in T1 (n = 2); in T2, it showed positive allometric growth; and when specimens from T1 and T2 were combined, it showed positive allometric growth. C. gobio showed positive allometric growth in T1 and isometric growth in T2. When specimens from both river sections were analyzed in combination, isometric growth was observed (Table 1).

3.3.2. Relative Condition Factor Kn

The relative condition factor Kn was determined according to the inclusion and exclusion criteria, influenced by the presence, absence, and number of individuals from each species found in the analyzed river sections (Figure 2).
In the case of S. cephalus, the Kn mean values were >1 in both river sections (T1 = 1.007, T2 = 1.004) and also when combined (T1 + T2 = 1.005). No significant differences were observed among the analyzed groups based on the Kruskal–Wallis test (p = 0.9316). The analyzed S. trutta specimens from both river sections and combined river sections showed Kn mean values > 1 (T1 = 1.007; T2 = 1.015; T1 + T2 = 1.011). Significant differences were observed among groups (p = 0.0154) according to the Kruskal–Wallis test. Statistically significant differences were observed between T1 and T2 specimens based on Dunn’s multiple comparison test (p = 0.0117). The Kn of P. phoxinus showed Kn mean values >1 in both river sections (T1 = 1.014; T2 = 1.026) and in combination (T1 + T2 = 1.021). No significant differences were observed among the analyzed groups based on the Kruskal–Wallis test (p = 0.7799). Eudontomyzon danfordi showed Kn mean values > 1 in both river sections (T1 = 1.278; T2 = 1.002) and also when combined (T1 + T2 = 1.003). Statistically significant differences were determined among groups according to the Kruskal–Wallis test (p < 0.0001). Statistically significant differences appeared between T1 vs. T2 (p = 0.009) and T1 vs. T1 + T2 (p = 0.005) based on Dunn’s multiple comparison test. The analyzed individuals of B. carpathicus showed Kn mean values >1 in both river sections (T1 = 1.048; T2 = 1.004), as well as when river sections were combined (T1 + T2 = 1.005). No significant differences were observed among the analyzed groups based on one-way ANOVA analysis (p = 0.1672). The mean value of Kn determined for C. gobio specimens from T1 was <1 (T1 = 0.937); while in T2, the mean value of Kn was >1 (T2 = 1.009); and combined, T1 + T2 = 1.007. Statistically significant differences were determined among groups based on one-way ANOVA analysis (p < 0.0001). Statistically significant differences were observed between T1 vs. T2 (p = 0.002) and T1 vs. T1 + T2 (p < 0.0001) based on Tukey’s multiple comparison test. T. thymallus showed identical Kn mean values > 1 in T2 and T1 + T2 (1.007). No significant differences were observed between the analyzed groups (T2 vs. T1 + T2, p = 0.9301) based on the Mann–Whitney test. B. barbatula showed Kn mean values >1 in both T1 (1.006) and T1 + T2 (1.036). No significant differences were observed among the analyzed groups based on the Mann–Whitney test (p = 0.4262). For the remaining four species, R. rutilus, C. elongatoides, S. labrax, and P. fluviatilis, Kn was not determined due to the small number of specimens.

3.3.3. Fulton’s Condition Factor K

Fulton’s condition factor K showed statistically significant differences for S. cephalus (p = 0.0322) from the two river sections and combined river sections (T1, T2, and T1 + T2). The differences were observed between T1 and T2 (p = 0.0263). The analyzed specimens from T2 showed a higher mean K value than the specimens from T1 (0.00102 vs. 0.00108).
The Salmo trutta specimens presented statistically significant values for K (p < 0.0001). Differences were determined in all three comparisons (T1 vs. T2—p < 0.0001; T1 vs. T1 + T2—p = 0.0268; and T2 vs. T1 + T2—p = 0.0104) (Figure 3).
In the case of Cottus gobio, one-way ANOVA did not show statistically significant differences (p = 0.0524), but when the post hoc Tukey test was performed, statistically significant differences were observed between T1 vs. T2 specimens (p = 0.0403). A similar situation was observed for Barbus carpathicus. The analysis of variance did not show statistically significant differences among all three groups (T1, T2, and T1 + T2) (p = 0.0547), while the Tukey test showed statistically significant differences between T1 and T2 specimens (p = 0.0424). For species where only one individual was observed, K values were as follows: Perca fluviatilis—0.001214; Rutilus rutilus—0.001082; and Salmo labrax—0.000688.
Fulton’s condition factor did not show statistically significant differences in T1, T2, and T1 + T2 in the case of the remaining species (Supplementary Table S2).

4. Discussion

The differences and similarities of LWRs in the present study (T1 + T1) were compared to data from other studies and FishBase [38].
The analyzed Carpathian lamprey E. danfordi specimens showed similar LWRs to data from FishBase (b = 3.02 (2.81–3.24) vs. b = 2.99 (2.80–3.18)). Other populations found in Romania showed different growth types (b = 2.68 (2.21–3.15)) [39]. The Carpathian barbel B. carpathicus, a species also found in large numbers in Someș River from Tarnița Reservoir to the Dej locality [40], also showed similar LWRs compared to specialty literature: b = 2.96 (2.84–3.08) vs. b = 3.03 (2.86–3.20). In the same river catchment (Becaș River/Someș catchment), the B. carpathicus population showed positive allometric growth (b = 3.16 (3.06–3.26)) according to [41].
The Eurasian minnow P. phoxinus, one of the species widely used as baitfish in Romania, as well as in other European countries [42], showed a similar growth type compared to data found in FishBase: b = 3.09 (2.92–3.23) vs. b = 3.07 (2.97–3.17). The chub S. cephalus, a species found in both lotic and lentic habitats, presented similar LWRs compared to data from FishBase: b = 3.18 (3.10–3.25) vs. b = 3.12 (3.09–3.15). In similar studies, lotic and lentic chub populations could have different growth types: b = 3.26 (Crișul Repede/lotic population) vs. b = 2.95 (Beliș-Fântânele Reservoir/lentic population) [43].
For the roach R. rutilus and uncommon species found at higher altitudes in Romanian waters, the LWRs were not determined due to the low number of specimens observed at the time of fish sampling. They usually spawn from April to May [44,45], but in this case, they migrate from May to June (sometimes July and the start of August) from Beliș-Fântânele Reservoir to Someșul Cald River for spawning, possibly due to higher water temperature and environmental conditions. A similar situation (in terms of abundance of the species) to the case of the roach was observed in the Danubian spined loach C. elongatoides. This species requires further study in terms of habitat adaptations and preferences. The determined LWRs for the stone loach B. barbatula in the present study showed soft isometric growth compared to data reported in the analyzed specialty literature and databases (b = 2.5214 vs. b = 3.04), which show isometric growth [38,46].
The Black Sea salmon or Black Sea trout S. labrax is considered a synonym of Salmo trutta according to some authors [47], a subspecies of Salmo trutta labrax according to others [44], and also a self-standing species [48,49,50]. Only one specimen was observed, and LWRs were not determined. Further studies are necessary (both genetic and morphological) to provide up-to-date information on this species.
The brown trout S. trutta population abundantly present in Someșul Cald River showed different growth types in the T1 river section (b = 3.0178/ISO) and the T2 river section (b = 3.0642/ALLO+). When analyzed as a group (T1 + T2), the species showed positive allometric growth (b = 3.038), highly similar to data analyzed from FishBase (b = 3.03). Other studies determined an even higher b coefficient: b = 3.33 [51].
The European grayling T. thymallus is one of the most affected species in terms of longitudinal fragmentation, and it is considered an indicator species in some cases [52,53]. From the combined river sections (T1 + T2), the obtained data showed positive allometric growth (b = 3.1292), a different b coefficient value compared to FishBase (b = 3.06, probably isometric), as well as to data from Ruscova River (same catchment—Someș-Tisa), where the population showed negative allometric growth, b = 2.8193 [39].
The distribution and migration of bullhead C. gobio, a small-sized fish species, could be limited by longitudinal fragmentation [54]. The determined LWRs for the bullhead showed different growth types in the two river sections (ALLO+ in T1 vs. ISO in T2). Specialty literature data on the species showed different b coefficient values (isometric, allometric positive, and allometric negative): b = 3.18 [38]; b = 2.963; b = 3.001; b = 3.366 [55].
The European perch P. fluviatilis is not very common in mountain streams in general. The LWRs were not determined in this case due to the small number of specimens (n = 1 in T2). According to some authors, the species demonstrated isometric growth, while other authors observed positive and negative allometric growth [38,56].
The limitations of the present study are represented by the low number of individuals observed in some species (e.g., perch, roach, Black Sea trout). A higher number of individuals is desirable, but, in some cases, rare species (vulnerable, threatened, invasive, etc.) are encountered and should be mentioned, along with their wet body weight, total length, and other measurements, which can be used as reference or metadata in future studies.
Fish condition, determined by Fulton’s condition factor, can be affected by environmental conditions such as water quality, food availability, and spawning season [57,58]. Longitudinal connectivity is according to some authors, the main attribute of river ecosystems [59,60]. In terms of somatic condition, determined by Fulton’s condition factor, some of the species inhabiting Someșul Cald River do not seem to be affected by the interrupted connectivity caused by the dams, while others do.

5. Conclusions

Longitudinal fragmentation greatly influences freshwater ichthyofauna by changing species composition and diversity, growth dynamics, and feed availability. Fish species’ life history suffers changes along with the energy gradient modifications caused by dams. Long-term management plans designed for habitat and species conservation should take into consideration the existing fish species population dynamics along with their physiological and somatic status. The present study describes possible relations between habitat alteration and fish welfare expressed through LWRs, relative condition factor Kn, and Fulton’s condition factor K for fish species found in Someșul Cald River, a water body highly fragmented by dam constructions. Comparisons of LWRs, Kn, and K, in terms of river sections (constrained by dams), showed that some fish species had similar growth types and physiological conditions, while some were different. The small number of specimens for some species might represent a narrow sample size, and further studies are required. The present results on the morphological characteristics of fish under anthropization pressure can be used for fishery management and conservation programs.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/fishes9100420/s1: Table S1: The determined LWR for fish species from Someșul Cald River; Table S2: Descriptive statistics for Fulton’s condition factor K and relative condition factor Kn for fish species found in Someșul Cald River.

Author Contributions

Conceptualization, P.U. and C.L.; Data curation, P.U., M.C.M.-L., A.B. and C.L.; Formal analysis, A.B. and C.L.; Investigation, P.U., T.P., G.-C.M., D.C. and C.L.; Methodology, P.U., D.C. and C.L.; Software, P.U. and C.L.; Validation, R.C., D.C. and C.L.; Writing—original draft, P.U. and C.L.; Writing—review and editing, P.U., R.C., T.P., G.-C.M., M.C.M.-L., A.B., D.C., C.L. and C.O.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was approved by the Ethics Committee of the University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, the Approval Code and Date: No. 143/2019.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Someșul Cald River (downstream limit Gilău dam) and Someșul Mic River (upsteream coordinates N 46°38′18.57″, E 22°43′7.85″, downstream coordinates N 47°8′39.80″, E 23°54′47.84″).
Figure 1. Someșul Cald River (downstream limit Gilău dam) and Someșul Mic River (upsteream coordinates N 46°38′18.57″, E 22°43′7.85″, downstream coordinates N 47°8′39.80″, E 23°54′47.84″).
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Figure 2. The relative condition factor Kn (ns p > 0.05; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001; **** p ≤ 0.0001).
Figure 2. The relative condition factor Kn (ns p > 0.05; * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001; **** p ≤ 0.0001).
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Figure 3. Fulton’s condition factor K (ns p > 0.05; * p ≤ 0.05; **** p ≤ 0.0001).
Figure 3. Fulton’s condition factor K (ns p > 0.05; * p ≤ 0.05; **** p ≤ 0.0001).
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Table 1. Growth types of fish species from the analyzed river sections of Someșul Cald River.
Table 1. Growth types of fish species from the analyzed river sections of Someșul Cald River.
FamilySpeciesIndividual River SectionsCombined River Sections
T1T2T1 + T2
PetromyzontidaeE. danfordiISOs. ISOISO
CyprinidaeB. carpathicusISOISOISO
LeuciscidaeP. phoxinusALLO+ISOISO
S. cephalusALLO+ALLO+ALLO+
R. rutilusabsentn too smalln too small
CobitidaeC. elongatoidesn too smalln too smalln too small
NemacheilidaeB. barbatulas. ISOn too smalls. ISO
SalmonidaeS. labraxabsentn too smalln too small
S. truttaISOALLO+ALLO+
T. thymallusn too smallALLO+ALLO+
CottidaeC. gobioALLO+ISOISO
PercidaeP. fluviatilisabsentn too smalln too small
ISO—isometric growth; s. ISO—soft isometric growth; ALLO+—positive allometric growth.
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Uiuiu, P.; Constantinescu, R.; Păpuc, T.; Muntean, G.-C.; Matei-Lațiu, M.C.; Becze, A.; Cocan, D.; Lațiu, C.; Martonoș, C.O. Influence of Longitudinal Fragmentation on Length–Weight Relationships of Fishes in the Someșul Cald River, Romania. Fishes 2024, 9, 420. https://doi.org/10.3390/fishes9100420

AMA Style

Uiuiu P, Constantinescu R, Păpuc T, Muntean G-C, Matei-Lațiu MC, Becze A, Cocan D, Lațiu C, Martonoș CO. Influence of Longitudinal Fragmentation on Length–Weight Relationships of Fishes in the Someșul Cald River, Romania. Fishes. 2024; 9(10):420. https://doi.org/10.3390/fishes9100420

Chicago/Turabian Style

Uiuiu, Paul, Radu Constantinescu, Tudor Păpuc, George-Cătălin Muntean, Maria Cătălina Matei-Lațiu, Anca Becze, Daniel Cocan, Călin Lațiu, and Cristian Olimpiu Martonoș. 2024. "Influence of Longitudinal Fragmentation on Length–Weight Relationships of Fishes in the Someșul Cald River, Romania" Fishes 9, no. 10: 420. https://doi.org/10.3390/fishes9100420

APA Style

Uiuiu, P., Constantinescu, R., Păpuc, T., Muntean, G. -C., Matei-Lațiu, M. C., Becze, A., Cocan, D., Lațiu, C., & Martonoș, C. O. (2024). Influence of Longitudinal Fragmentation on Length–Weight Relationships of Fishes in the Someșul Cald River, Romania. Fishes, 9(10), 420. https://doi.org/10.3390/fishes9100420

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