Floodplains as a Suitable Habitat for Freshwater Fish

[Full title: Floodplains as a Suitable Habitat for Freshwater Fish: The Length–Weight Relationships and Condition Factors of Fish Inhabiting a Danube Floodplain in Croatia]

Citation: Vui´c, N.; Turkovi´c ˇ Cakali´c, I.; Koh, M.; Ergovi´c, V.; Vlaiˇcevi´c, B.; Šag, M.; Rožac, V.; ˇ Cerba, D. Floodplains as a Suitable Habitat for Freshwater Fish: The Length–Weight Relationships and Condition Factors of Fish Inhabiting a Danube Floodplain in Croatia Sustainability 2024 , 16 , 7566. https:// doi.org/10.3390/su 16177566 Academic Editors: Vesna Djikanovi´c and Vera P. Nikoli´c Received: 22 July 2024 Revised: 28 August 2024 Accepted: 29 August 2024 Published: 1 September 2024 Copyright: © 2024 by the authors Licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) sustainability Article Floodplains as a Suitable Habitat for Freshwater Fish: The Length–Weight Relationships and Condition Factors of Fish Inhabiting a Danube Floodplain in Croatia Nera Vui´c 1 , Ivana Turkovi´c ˇ Cakali´c 1 , Miran Koh 1 , Viktorija Ergovi´c 1 , Barbara Vlaiˇcevi´c 1 , Matej Šag 1 , Vlatko Rožac 2 and Dubravka ˇ Cerba 3, * 1 Department of Biology, Josip Juraj Strossmayer University of Osijek, Cara Hadrijana 8/A, 31000 Osijek, Croatia; nera.vuic@biologija.unios.hr (N.V.); iturkovic@biologija.unios.hr (I.T. ˇ C.); miran.koh@biologija.unios.hr (M.K.); viktorija.ergovic@biologija.unios.hr (V.E.); barbara.vlaicevic@biologija.unios.hr (B.V.); msag@biologija.unios.hr (M.Š.) 2 Public Institution Kopaˇcki Rit Nature Park, Mali Sakadaš 1, 31327 Kopaˇcevo, Croatia; vlatko.rozac@pp-kopacki-rit.hr 3 Department of Assessment and Aquatic Ecosystems Research, National Water Reference Laboratory of Slovakia, Water Research Institute, N á br. arm. gen. L. Svobodu 5(7), 81249 Bratislava, Slovakia * Correspondence: dubravka.cerba@vuvh.sk Abstract: When studying the well-being and fitness of ichthyofauna in a specific area, vital information comes from length–weight relationships (LWRs) and condition factor analyses and calculations. Data were collected from 2015 to 2019 in an area important for fish shelter, feeding, and spawning Twenty four species belonging to 10 different families were identified from the total 16,895 of caught individuals, with the most abundant species being Blicca bjoerkna . The calculation of LWRs was possible for 19 species, (R 2 = 0.7049–0.9998 ( p < 0.05)), with the values of the mean coefficient b ranging from 2.6831 to 3.5747, indicating an overall positive allometric growth in the fish population The results of Fulton’s and the relative condition factors showed that a total of eight species were in a relatively good condition, although the species in question varied between the two condition factors. Fulton’s condition factor showed the highest average value for Lepomis gibbosus (1.4956), while Cobitis elongatoides had the lowest (0.4739). Contrarily, the relative condition factor showed the highest average value for Silurus glanis (1.0524), and the lowest for Gymnocephalus cernua (1.0023). The lower values of calculated condition factors in some species could be attributed to sampling being conducted during the colder months of autumn and winter. Future studies should include seasonal sampling in order to achieve a better understanding how various abiotic factors impact the condition factors of these fish species. Nevertheless, this research provided valuable data on the status of the fish population in the floodplain and could be used as a guideline for designing future ichthyofauna studies in this area Keywords: positive allometric growth; Fulton’s factor; relative condition factor; Blicca bjoerkna ; Kopaˇcki Rit; ichthyofauna 1. Introduction When it comes to the assessment of the various biological, physiological, and ecological characteristics of fish, one mode of measurement has proven to be ever present in fishery studies: the length–weight relationship (LWR) measurement [ 1 ]. In fact, data of fish length– weight relationships have been used to monitor fish population dynamics [ 2 ], to compare fish populations in different habitats [ 3 ], to acquire insights into the health [ 4 ] and condition of fish populations [ 5 , 6 ], and even to study the impact of pollutants [ 7 ] and parasitism [ 8 ] on fish health. Furthermore, the values of length–weight relationships can vary depending on the season and can be affected by changes in environmental conditions, as well as Sustainability 2024 , 16 , 7566. https://doi.org/10.3390/su 16177566 https://www.mdpi.com/journal/sustainability

Sustainability 2024 , 16 , 7566 2 of 13 physiological changes such as gonad development [ 9 , 10 ]. The ubiquity of LWR analysis stems partly from its practicality in fieldwork research as it reduces the time and work needed to collect an adequate amount of data on sampled fish by using measured length data to calculate fish weight [ 11 ]. Additionally, LWR data can also be used to calculate fish biomass [ 9 , 11 ], which is useful in fish stock assessments [ 12 ]. Another important biometric tool in fish ecology is the condition factor, which is primarily used to obtain information about the current well-being of individual fish or the species’ population [ 13 ]. It is based on the assumption that heavier fish are in a better physiological condition [ 14 ], i.e., they are able to feed better and accumulate a greater amount of energy reserves compared to lighter fish of the same length [ 15 ]. This kind of logic makes it apparent that fish condition factors are heavily influenced by various biotic and abiotic elements, such as predation, competition, and parasitism, as well as habitat conditions and seasonal fluctuations [ 16 ]. There are several different ways to evaluate the condition of fish, with Fulton’s condition factor (K) being one of the most prominent in fishery studies [ 17 ]. The value of Fulton’s condition factor varies with the changes in the nutritional condition of the fish [ 18 ] and assumes that the shape of the measured fish does not change with its increase in size [ 17 ]. Another type of measurement is the relative condition factor (K n ). It shows the deviation of the observed weight of an individual from the average weight calculated via linear regression of the LWR of a collective population sample [ 10 ]. While Fulton’s condition factor always assumes isometric growth (the fish body shape does not change with growth, but instead follows the cube law), the relative condition factor takes into account the potential deviation of the ideal fish body shape as it increases in size (positive or negative allometric growth) [ 15 , 19 ]. This makes it possible to use the index for comparisons between fish individuals of different lengths and even different species. On the other hand, comparisons between different fish populations are impossible, because a new length–weight regression calculation is needed for every sample of a population within a study [ 20 ]. Fish are known to utilize the unique and nutrient-rich habitats of dynamic floodplain ecosystems as feeding, spawning, and nursery grounds, oftentimes leading to a high diversity of fish species in those areas [ 21 – 23 ]. One such important area in Croatia is found within the Kopaˇcki Rit Nature Park, which, along with being a floodplain of the rivers Drava and Danube, bears characteristics of a wetland and an inner delta [ 24 ]. Kopaˇcki Rit is a well-protected floodplain area in the Danubian basin, and its importance is internationally recognized through its inclusion in Natura 2000, as well as the Ramsar and the Important Bird Areas lists [ 25 – 29 ]. One section of the park is also classified as a Special Zoological Reserve. As expected, numerous ichthyofauna studies have been carried out in Kopaˇcki Rit throughout the years [ 30 – 36 ], with the latest data confirming the presence of over 50 fish species [ 36 ], some of which are classified as endemic to the Danube basin [ 27 ]. Despite the rigorous amount of research put into the analysis of fish biodiversity, little to no effort has been put into research and documentation of the condition factor and length–weight relationships of fish species residing in this important floodplain area Since information on length–weight relationships and condition factors is crucial for assessing fish biology (i.e., growth patterns, physiology, and health status in general) which helps in the monitoring and management of fish populations, the main goal of this study was to document novel information about the length–weight relationships and condition factors of fish residing in the Kopaˇcki Rit Nature Park, along with the additional documentation of fish species and their population numbers 2. Materials and Methods 2.1. Study Area The Kopaˇcki Rit Nature Park is a well-protected floodplain area in the northeastern part of Croatia, situated in-between two large rivers: Drava and Danube (Figure 1 ). The flooding regime of Kopaˇcki Rit is thus determined by these two surrounding rivers, the

Sustainability 2024 , 16 , 7566 3 of 13 Drava and Danube rivers, with the latter having the highest impact on flooding. As such, the inundation area is comprised of various water bodies, some of which are temporarily filled with water, while others, such as shallow lakes, riverside arms, and channels, are permanent [ 27 ]. Most of the lakes and ponds in this area are remnants of the river bed, although some are also products of erosion caused by water withdrawal [ 27 ]. During flooding, water from the Danube river enters the area at two sides: the northern, through the river’s sidearm, Vemeljski Dunavac, and the southern, through the Hulovo channel [ 24 , 25 , 37 ]. A system of natural earth barriers separates the northern and southern parts, but once the Danube river’s water level at the Apatin gauging station increases above 82.50 m a.s.l., the water overflows, connecting the two sides [ 24 ]. The dynamics of flooding and subsequent water withdrawal in this area are responsible for the formation of numerous habitats, able to support more than 2000 recorded species [ 24 ]. In total, the floodplain area covers a surface of around 180 km 2 , making it one of the largest conserved floodplains of the Danube [ 37 ]. Permanent water bodies, located mostly in the southern part within the Special Zoological Reserve, are especially important to fish as they provide suitable spawning areas for individuals residing within the floodplain, and for individuals who migrate from the Drava and Danube rivers [ 27 ]. Sustainability 2024 , 16 , x FOR PEER REVIEW 3 of 14 The Kopa č ki Rit Nature Park is a well-protected fl oodplain area in the northeastern part of Croatia, situated in-between two large rivers: Drava and Danube (Figure 1). The fl ooding regime of Kopa č ki Rit is thus determined by these two surrounding rivers, the Drava and Danube rivers, with the la tt er having the highest impact on fl ooding. As such, the inundation area is comprised of various water bodies, some of which are temporarily fi lled with water, while others, such as shallow lakes, riverside arms, and channels, are permanent [27]. Most of the lakes and ponds in this area are remnants of the river bed, although some are also products of erosion caused by water withdrawal [27]. During fl ooding, water from the Danube river enters the area at two sides: the northern, through the river’s sidearm, Vemeljski Dunavac, and the southern, through the Hulovo channel [24,25,37]. A system of natural earth barriers separates the northern and southern parts, but once the Danube river’s water level at the Apatin gauging station increases above 82.50 m a.s.l., the water over fl ows, connecting the two sides [24]. The dynamics of fl ooding and subsequent water withdrawal in this area are responsible for the formation of numerous habitats, able to support more than 2000 recorded species [24]. In total, the fl oodplain area covers a surface of around 180 km 2 , making it one of the largest conserved fl oodplains of the Danube [37]. Permanent water bodies, located mostly in the southern part within the Special Zoological Reserve, are especially important to fi sh as they provide suitable spawning areas for individuals residing within the fl oodplain, and for individuals who migrate from the Drava and Danube rivers [27]. Figure 1. The sampling area in the Kopa č ki Rit Nature Park fl oodplain. 2.2. Sampling The sampling sites included three di ff erent permanent water bodies within the Kopa č ki Rit Nature Park: Lake Sakadaš and the channels Č onakut and Novi Kanal (Figure 1). These water bodies have been shown to be optimal sampling points in terms of net casting and the diversity of fi sh taxa found, and they have been used in previous ichthyofauna research [34,36,38]. The sampling of the fi sh was conducted in September and December during the period of 2015 to 2019, excluding the December sampling for the years 2018 and 2019 due to the water at the sampling sites being frozen. Water levels within the wetland during these months are not as prone to extreme changes as they are during the early spring and summer months [39], which makes for a stable and optimal time for fi sh sampling. This amounted to a total of eight samples, two samples for each of the years 2015–2017, and one sample for 2018 and 2019, respectively. Gill nets and traditional trap nets of di ff erent sizes/lengths and mesh sizes were used. Each net was positioned at designated locations within the mentioned sampling sites and left overnight for a total of 12 h. Afterwards, the captured fi sh individuals were isolated, counted, and the species were identi fi ed based on their morphological characteristics. Figure 1. The sampling area in the Kopaˇcki Rit Nature Park floodplain 2.2. Sampling The sampling sites included three different permanent water bodies within the Kopaˇcki Rit Nature Park: Lake Sakadaš and the channels ˇ Conakut and Novi Kanal (Figure 1 ). These water bodies have been shown to be optimal sampling points in terms of net casting and the diversity of fish taxa found, and they have been used in previous ichthyofauna research [ 34 , 36 , 38 ]. The sampling of the fish was conducted in September and December during the period of 2015 to 2019, excluding the December sampling for the years 2018 and 2019 due to the water at the sampling sites being frozen. Water levels within the wetland during these months are not as prone to extreme changes as they are during the early spring and summer months [ 39 ], which makes for a stable and optimal time for fish sampling This amounted to a total of eight samples, two samples for each of the years 2015–2017, and one sample for 2018 and 2019, respectively Gill nets and traditional trap nets of different sizes/lengths and mesh sizes were used Each net was positioned at designated locations within the mentioned sampling sites and left overnight for a total of 12 h. Afterwards, the captured fish individuals were isolated, counted, and the species were identified based on their morphological characteristics. Using an ichthyometer, the total length (TL) and standard length (SL) of all fish individuals were measured, while the weight of the fish (m) was measured using a digital scale Sirius electronic scale The taxonomy and nomenclature of all fish sampled in this study were checked using the FishBase database [ 40 ].

Sustainability 2024 , 16 , 7566 4 of 13 2.3. Length–Weight Relationship The measured total length and weight data of the species represented by more than 10 sampled individuals were used to calculate the relationship between the length and weight using the W = a L b equation [ 10 , 41 ]. In the aforementioned formula, the W represents the calculated weight expressed in g, L is the measured total length in cm, while a is the intercept, and b is the slope. The a and b parameters were calculated using a linear regression analysis of the log-transformed formula log (W) = log( a ) + b log(L) [ 10 ]. Following the recommendations of Froese [ 42 ], any of the visible outliers in the length–weight data, whose values did not follow the general trend of the remaining prevalent data, were removed. The species’ length–weight relationship was firstly assessed for each of the sampling seasons, after which the mean value was calculated from all the available a and b parameters (max eight per species). All of the LWR regression calculations were performed using the Microsoft Excel software (Microsoft Office 2016, version 2407) [ 43 ]. The calculated b parameter was further used to determine the growth type of a fish (positive/negative allometric or isometric) by using the confidence intervals (CI) to test whether the calculated b value was significantly different from the predicted b value, indicating isometric growth ( b = 3) where the isometry null hypothesis (H 0: b = 3) was rejected at a 5% significance level The isometric type of growth assumes the fish increases equally in length and weight as it grows. On the other hand, if the fish were to increase more in length than in weight during their growth, they would have a negative allometric growth ( b < 3). If they increased more in weight than in length, a positive allometric growth would be assumed ( b > 3) [ 44 ]. 2.4. Condition Factors Two condition factors were used to evaluate the well-being of fish in this study: Fulton’s condition factor and the relative condition factor. Fulton’s condition factor (K) was calculated using the equation K = (W × 100)/TL 3 , where W is the weight of the fish expressed in g and TL is the measured total length of the fish in cm [ 45 ]. The equation used for the calculation of the relative condition factor (K n ) was K n = W/ a L b [ 10 ], in which W represents the measured weight of the fish in g, and a L b is the predicted weight of the fish in g at a given length ( a and b are the parameters obtained through the assessment of length–weight relationships and L is the measured total length in cm) [ 42 ]. All the condition factor data were tested for homogeneity using the Shapiro–Wilk test and for variance using the parametric F-test or non-parametric Fligner–Kileen test. Furthermore, to compare the calculated mean values of Fulton’s condition factors and relative condition factors with 1, a parametric one-sample t-test or a non-parametric one-sample Wilcoxon signed rank test was used [ 46 ]. 2.5. Statistical Analysis All statistical analyses were conducted in R 4.3.1 version, using the package “stats” 4.0.2. version, and were considered significant at 5 % ( p < 0.05) [ 47 ]. 3. Results During the study period, a total of 16,895 fish individuals were collected, amounting to 698.25 kg. These values varied yearly, with the total weight per sample ranging from a minimum of 56.432 kg to a maximum of 228.955 kg, and the total number of individuals per sample ranging from 1165 to 6727 individuals. In total, 24 fish species belonging to 10 different families were recorded in this study (Table 1 ). With a total of ten species, the family Leuciscidae was represented with the highest diversity, followed by the Percidae and Cyprinidae families, represented with five and two identified species, respectively. Each of the remaining seven families included just one species. The most abundant species was Blicca bjoerkna with 5564 sampled individuals, followed closely by Carassius gibelio (4530), and Alburnus alburnus (3078). On the other hand, only one individual of Chondrostoma nasus was recorded, making it the species with the lowest number of sampled individuals in this study.

Sustainability 2024 , 16 , 7566 5 of 13 Table 1. The minimum, maximum, and mean ± SD of the measured total lengths and weights of all sampled fish species at the three sampling stations in Kopaˇcki Rit from 2015 to 2019 Family Species N Total Length Range [cm] Total Weight Range [g] Min Max Mean Min Max Mean CENTRARCHIDAE Lepomis gibbosus (Linnaeus, 1758) 165 4.5 11.2 6.7 ± 1.2 1.1 26.0 5.1 ± 3.8 COBITIDAE Cobitis elongatoides (B ă cescu and Mayer, 1969) 7 8.6 10.0 9.3 ± 0.5 3.0 6.0 3.9 ± 1.1 CYPRINIDAE Carassius gibelio (Bloch, 1782) 4530 3.5 44.4 9.9 ± 9.1 1.0 1535.0 100.9 ± 274.5 Cyprinus carpio (Linnaeus, 1758) 515 4.0 28.0 9.6 ± 2.9 1.1 305.0 14.0 ± 10.7 GOBIONIDAE Pseudorasbora parva (Temminck and Schlegel, 1846) 899 4.9 11.7 7.8 ± 0.9 1.1 13.0 3.9 ± 1.6 ESOCIDAE Esox lucius (Linnaeus, 1758) 49 23.2 73.2 47.1 ± 9.6 75.0 3000.0 940.4 ± 560.8 ICTALURIDAE Ameiurus nebulosus (Lesueur, 1819) 21 9.6 24.5 18.7 ± 2.4 12.0 214.0 107.9 ± 44.7 LEUCISCIDAE Abramis brama (Linnaeus, 1758) 64 4.8 45.5 10.4 ± 6.1 1.1 1415.0 32.4 ± 182.6 Alburnus albidus (Costa, 1838) 5 11.2 13.2 12.3 ± 0.8 8.2 24.2 16.9 ± 6.2 Alburnus alburnus (Linnaeus, 1758) 3078 5.5 16.6 9.3 ± 1.8 1.0 30.0 5.4 ± 3.7 Leuciscus aspius (Linnaeus, 1758) 335 8.0 69.0 20.1 ± 11.6 3.0 3765.0 192.2 ± 584.8 Blicca bjoerkna (Linnaeus, 1758) 5564 3.0 20.0 8.9 ± 2.3 1.0 97.0 7.9 ± 7.6 Chondrostoma nasus (Linnaeus, 1758) 1 11.8 11.8 11.8 11.0 11.0 11.0 Rutilus sp 4 8.4 15.5 12.5 ± 3.0 5.0 43.0 23.3 ± 15.5 Rutilus pigus (Lacep è de, 1803) 5 10.6 12.6 12.6 ± 0.7 8.7 17.0 17.0 ± 3.3 Rutilus rutilus (Linnaeus, 1758) 521 4.5 26.5 12.5 ± 3.3 1.1 155.0 23.5 ± 25.1 Scardinius erythrophthalmus (Linnaeus, 1758) 106 5.4 28.0 16.2 ± 4.8 1.1 350.0 66.6 ± 31.5 PERCIDAE Gymnocephalus sp 51 5.5 11.5 8.9 ± 1.4 1.1 22.0 9.2 ± 3.9 Gymnocephalus baloni (Holc í k and Hensel, 1974) 45 4.8 14 6.5 ± 1.7 3.0 3.0 3.3 ± 3.5 Gymnocephalus cernua (Linnaeus, 1758) 14 4.9 8.6 7.1 ± 1.3 1.3 7.0 3.9 ± 1.7 Perca fluviatilis (Linnaeus, 1758) 369 5.0 21.9 12.1 ± 3.9 1.1 201.0 30.5 ± 28.7 Sander lucioperca (Linnaeus, 1758) 177 8.5 29.5 18.2 ± 3.4 3.0 200.0 44.4 ± 30.3 XENOCYPRIDIDAE Hypophthalmichthys molitrix (Valenciennes, 1844) 203 9.6 63.5 20.3 ± 7.2 6.0 3145.0 125.8 ± 336.4 SILURIDAE Silurus glanis (Linnaeus, 1758) 167 8.5 40.0 16.9 ± 5.0 2.0 425.0 41.4 ± 45.6

Sustainability 2024 , 16 , 7566 6 of 13 Out of the 24 species recorded in this study, the calculation of length–weight relationships was possible for 19 species, as their sample size exceeded 10 individuals. All calculated linear regressions were significant ( p < 0.05), with the coefficient of determination (R 2 ) ranging from 0.7049 to 0.9998. The values of the mean coefficient a , calculated through the LWR equation, ranged from 0.0020 for Abramis brama to 0.0210 for Gymnocephalus baloni , while the mean coefficient b ranged from 2.6831 for G baloni to 3.5747 for Scardinius erythrophthalmus , with a collective average of 3.2929, indicating an overall positive allometric growth in the fish population. More specifically, 15 species were shown to have positive allometric growth, while two had negative, and two had isometric growth (Table 2 ). The length–weight relationships for each of the growth types are plotted in Figure 2 . The total length of fish documented in this study ranged from 3.0 cm ( Blicca bjoerkna ) to 73.2 cm ( Esox lucius ), while the total weight ranged from 1.0 g ( Alburnus albidus ) to 3765.0 g ( Leuciscus aspius ) Sustainability 2024 , 16 , x FOR PEER REVIEW 6 of 14 Gymnocephalus cernua (Linnaeus, 1758) 14 4.9 8.6 7.1 ± 1.3 1.3 7.0 3.9 ± 1.7 Perca fl uviatilis (Linnaeus, 1758) 369 5.0 21.9 12.1 ± 3.9 1.1 201.0 30.5 ± 28.7 Sander lucioperca (Linnaeus, 1758) 177 8.5 29.5 18.2 ± 3.4 3.0 200.0 44.4 ± 30.3 XENOCYPRIDIDAE Hypophthalmichthys molitrix (Valenciennes, 1844) 203 9.6 63.5 20.3 ± 7.2 6.0 3145.0 125.8 ± 336.4 SILURIDAE Silurus glanis (Linnaeus, 1758) 167 8.5 40.0 16.9 ± 5.0 2.0 425.0 41.4 ± 45.6 Out of the 24 species recorded in this study, the calculation of length–weight relationships was possible for 19 species, as their sample size exceeded 10 individuals. All calculated linear regressions were signi fi cant ( p < 0.05), with the coe ffi cient of determination (R 2 ) ranging from 0.7049 to 0.9998. The values of the mean coe ffi cient a , calculated through the LWR equation, ranged from 0.0020 for Abramis brama to 0.0210 for Gymnocephalus baloni , while the mean coe ffi cient b ranged from 2.6831 for G . baloni to 3.5747 for Scardinius erythrophthalmus , with a collective average of 3.2929, indicating an overall positive allometric growth in the fi sh population. More speci fi cally, 15 species were shown to have positive allometric growth, while two had negative, and two had isometric growth (Table 2). The length–weight relationships for each of the growth types are plo tt ed in Figure 2. The total length of fi sh documented in this study ranged from 3.0 cm ( Blicca bjoerkna ) to 73.2 cm ( Esox lucius ), while the total weight ranged from 1.0 g ( Alburnus albidus ) to 3765.0 g ( Leuciscus aspius ). Figure 2. Length–weight relationships of three species with di ff erent growth types: Abramis brama — positive allometric; Gymnocephalus baloni —isometric; and Silurus glanis —negative allometric. Fulton’s condition factor was calculated for each of the 24 recorded species in this study and was expressed as an average, excluding Chondrostoma nasus, for which the Figure 2. Length–weight relationships of three species with different growth types: Abramis brama — positive allometric; Gymnocephalus baloni —isometric; and Silurus glanis —negative allometric Fulton’s condition factor was calculated for each of the 24 recorded species in this study and was expressed as an average, excluding Chondrostoma nasus, for which the condition data were available from just one individual caught during the whole study. The highest average Fulton’s condition factor was calculated for Lepomis gibbosus (1.4956), while Cobitis elongatoides had the lowest average factor value (0.4739). Condition factors whose values were significantly higher than 1.0 ( p < 0.05) indicated an overall good condition and such values were documented in a total of 8 species in this study, while the remaining 15 species (excluding C nasus due to a lack of data) were proven to be in a poorer condition (Figure 3 ).

Sustainability 2024 , 16 , 7566 7 of 13 Table 2. The calculated values of length–weight parameters and condition factors for species sampled at the three sampling locations in Kopaˇcki Rit from 2015 to 2019 Family Species Length–Weight Relationship Parameters GT Condition Factors n Mean a Mean b CI (b) R 2 Range K K n Centrarchidae Lepomis gibbosus (Linnaeus, 1758) 2 0.0096 3.3016 2.9061–3.6972 0.7244–0.9848 A + 1.4956 1.0226 Cobitidae Cobitis elongatoides (B ă cescu and Mayer, 1969) 0 - - - - - 0.4739 - Cyprinidae Carassius gibelio (Bloch, 1782) 8 0.0072 3.2739 3.2127–3.3350 0.9343–0.9966 A + 1.3213 1.0226 Cyprinus carpio (Linnaeus, 1758) 3 0.0057 3.3296 3.0950–3.5642 0.9207–0.9501 A + 1.0826 1.0224 Gobionidae Pseudorasbora parva (Temminck and Schlegel, 1846) 4 0.0027 3.5573 3.4167–3.6978 0.7049–0.9452 A + 0.7829 1.0171 Esocidae Esox lucius (Linnaeus, 1758) 3 0.0049 3.1517 2.9669–3.3365 0.951–0.9876 A + 0.7246 1.0050 Ictaluridae Ameiurus nebulosus (Lesueur, 1819) 1 0.0049 3.3658 - 0.941 A + 1.4283 1.0050 Leuciscidae Abramis brama (Linnaeus, 1758) 3 0.0020 3.4954 3.3752–3.6155 0.9377–0.9998 A + 0.6181 1.0124 Alburnus albidus (Costa, 1838) 0 - - - - - 0.8769 - Alburnus alburnus (Linnaeus, 1758) 6 0.0024 3.5257 3.2341–3.8172 0.818–0.9877 A + 0.5959 1.0338 Leuciscus aspius (Linnaeus, 1758) 8 0.0052 3.1853 3.0369–3.3338 0.903–0.9987 A + 0.7776 1.0104 Blicca bjoerkna (Linnaeus, 1758) 8 0.0060 3.2385 3.0895–3.3875 0.7316–0.9677 A + 0.8765 1.0227 Chondrostoma nasus (Linnaeus, 1758) 0 - - - - - 0.6695 - Rutilus sp 0 - - - - - 1.0004 - Rutilus pigus (Lacep è de, 1803) 0 - - - - - 0.8501 - Rutilus rutilus (Linnaeus, 1758) 8 0.0048 3.3008 3.1734–3.4282 0.7887–0.9942 A + 0.8809 1.0221 Scardinius erythrophthalmus (Linnaeus, 1758) 5 0.0024 3.5747 3.4465–3.7028 0.9312–0.9976 A + 1.1316 1.0116 Percidae Gymnocephalus sp 1 0.0083 3.1677 - 0.827 I 1.2034 1.0287 Gymnocephalus baloni (Holc í k and Hensel, 1974) 2 0.0210 2.6831 2.5107–2.8555 0.8783–0.9307 I 1.0924 1.0106 Gymnocephalus cernua (Linnaeus, 1758) 2 0.0171 2.7328 2.6480–2.8176 0.955–0.9873 A − 1.0280 1.0024 Perca fluviatilis (Linnaeus, 1758) 5 0.0042 3.4771 3.2185–3.7356 0.8553–0.9942 A + 1.1331 1.0161 Sander lucioperca (Linnaeus, 1758) 4 0.0042 3.2006 3.0260–3.3752 0.8056–0.9853 A + 0.6745 1.0107 Xenocyprididae Hypophthalmichthys molitrix (Valenciennes, 1844) 5 0.0032 3.3847 3.2424–3.5269 0.8496–0.9995 A + 0.7018 1.0205 Siluridae Silurus glanis (Linnaeus, 1758) 3 0.0146 2.8989 2.5191–3.2787 0.908–0.9993 A − 0.6600 1.0524 Note: n = number of calculated LWR; CI = confidence intervals for parameter b ; GT = growth types (A + : positive allometric, A − : negative allometric, I: isometric); K = Fulton’s condition factor; K n = relative condition factor.

Sustainability 2024 , 16 , 7566 8 of 13 Sustainability 2024 , 16 , x FOR PEER REVIEW 7 of 14 condition data were available from just one individual caught during the whole study. The highest average Fulton’s condition factor was calculated for Lepomis gibbosus (1.4956), while Cobitis elongatoides had the lowest average factor value (0.4739). Condition factors whose values were signi fi cantly higher than 1.0 ( p < 0.05) indicated an overall good condition and such values were documented in a total of 8 species in this study, while the remaining 15 species (excluding C . nasus due to a lack of data) were proven to be in a poorer condition (Figure 3). Figure 3. The average values of Fulton’s condition factor for 24 species of fi sh sampled in the Kopa č ki Rit Nature Park fl oodplain from 2015 to 2019. Since the relative condition factor calculation depends on the availability of length– weight regression data, information was available for 19 species in this study (Figure 4). A good condition was noted in eight species, with three being the same species con fi rmed through Fulton’s condition factor, L . gibbosus , Carassius gibelio, and Cyprinus carpio , while the remaining fi ve di ff ered in comparison to the other index. Silurus glanis had the highest recorded average relative condition factor (1.0524), while the lowest average factor was recorded for Gymnocephalus cernua (1.0023) (Table 2). The average values of the Fulton’s condition factors and relative condition factors for each of the fi sh species sampled in this study are shown in Table 2. Figure 3. The average values of Fulton’s condition factor for 24 species of fish sampled in the Kopaˇcki Rit Nature Park floodplain from 2015 to 2019 Since the relative condition factor calculation depends on the availability of length– weight regression data, information was available for 19 species in this study (Figure 4 ). A good condition was noted in eight species, with three being the same species confirmed through Fulton’s condition factor, L gibbosus , Carassius gibelio, and Cyprinus carpio , while the remaining five differed in comparison to the other index Silurus glanis had the highest recorded average relative condition factor (1.0524), while the lowest average factor was recorded for Gymnocephalus cernua (1.0023) (Table 2 ). The average values of the Fulton’s condition factors and relative condition factors for each of the fish species sampled in this study are shown in Table 2 . Sustainability 2024 , 16 , x FOR PEER REVIEW 8 of 14 Figure 4. The average values of the relative condition factor for 19 species of fi sh sampled in the Kopa č ki Rit Nature Park fl oodplain from 2015 to 2019. Table 2. The calculated values of length–weight parameters and condition factors for species sampled at the three sampling locations in Kopa č ki Rit from 2015 to 2019. Family Species Length–Weight Relationship Parameters GT Condition Factors n Mean a Mean b CI ( b ) R 2 Range K K n Centrarchidae Lepomis gibbosus (Linnaeus, 1758) 2 0.0096 3.3016 2.9061–3.6972 0.7244–0.9848 A + 1.4956 1.0226 Cobitidae Cobitis elongatoides (B ă cescu and Mayer, 1969) 0 - - - - - 0.4739 - Cyprinidae Carassius gibelio (Bloch, 1782) 8 0.0072 3.2739 3.2127–3.3350 0.9343–0.9966 A + 1.3213 1.0226 Cyprinus carpio (Linnaeus, 1758) 3 0.0057 3.3296 3.0950–3.5642 0.9207–0.9501 A + 1.0826 1.0224 Gobionidae Pseudorasbora parva (Temminck and Schlegel, 1846) 4 0.0027 3.5573 3.4167–3.6978 0.7049–0.9452 A + 0.7829 1.0171 Esocidae Esox lucius (Linnaeus, 1758) 3 0.0049 3.1517 2.9669–3.3365 0.951–0.9876 A + 0.7246 1.0050 Ictaluridae Ameiurus nebulosus (Lesueur, 1819) 1 0.0049 3.3658 - 0.941 A + 1.4283 1.0050 Leuciscidae Abramis brama (Linnaeus, 1758) 3 0.0020 3.4954 3.3752–3.6155 0.9377–0.9998 A + 0.6181 1.0124 Alburnus albidus (Costa, 1838) 0 - - - - - 0.8769 - Alburnus alburnus (Linnaeus, 1758) 6 0.0024 3.5257 3.2341–3.8172 0.818–0.9877 A + 0.5959 1.0338 Leuciscus aspius (Linnaeus, 1758) 8 0.0052 3.1853 3.0369–3.3338 0.903–0.9987 A + 0.7776 1.0104 Figure 4. The average values of the relative condition factor for 19 species of fish sampled in the Kopaˇcki Rit Nature Park floodplain from 2015 to 2019.

Sustainability 2024 , 16 , 7566 9 of 13 4. Discussion The b coefficient of the length–weight relationships is commonly used as an indicator of fish growth patterns [ 48 ], with Froese [ 42 ] stating that values of this coefficient tend to generally range from 2.5 to 3.5. Similar results are shown in this study, as the calculated means of the b coefficient ranged from 2.6831 for Gymnocephalus baloni , to 3.5747 for Scardinius erythrophthalmus . The presence of b coefficient values that were not within the given range was noted while calculating the separate LWR for each of the sampling seasons, such as 2.3800 for G baloni , 2.4746 for Silurus glanis , and 4.1266 for Alburnus alburnus . The most probable cause for these kinds of results could be due to the lack of a sufficient number of individuals per sample, as smaller sample sizes tend to give more extreme values of the b parameter [ 16 , 49 ]. Nonetheless, the average b coefficient of all recorded species in this study was shown to be above 3 (3.2929, to be exact), indicating overall positive allometric growth. Such results suggest that as the fish grew, they increased more in weight than in length, giving them an overall rounder body shape. The higher values of the b coefficient in this study could have been partly affected by the habitat type, or more specifically, the slow-moving waters of the researched floodplain area. Shukor et al. [ 50 ] stated that lower b values could be found in fish residing in fast-moving waters, while slower-moving waters tend to give fish higher b values. The values of this coefficient can also be influenced by the water temperature, the type of sampling, and the current food availability [ 51 , 52 ]. Since the LWR is known to change in accordance with physiological changes highly dependent on the season, such as spawning [ 53 ], future studies should include the sampling of fish in each of the seasons to obtain a better view of the changes and the overall range of the length–weight relationships for all of the analyzed species Out of the 24 fish species recorded and analyzed in this study, ten belonged to the family Leuciscidae. The morphological and physiological characteristics of species within this group vary considerably, granting the family-wide distribution across the northern parts of Eurasia [ 54 ]. One such species is the Blicca bjoerkna , known to mostly reside in slow-moving waters across the central and northern parts of Europe [ 55 ]. With the nutrientrich, slow-moving waterbodies of Kopaˇcki Rit falling into the similar category of suitable habitats for this species, it had the highest number of sampled individuals in this study, with a total of 5564. The dominance of this species was recorded in other ichthyofauna research conducted in this area [ 32 , 36 ]. Another species with an extremely high number of sampled individuals in this study was the Prussian carp ( Carassius gibelio ). Belonging to the family Cyprinidae, this invasive fish is known to inhabit a wide variety of freshwater ecosystems, increasing in number rapidly via gynogenetic reproduction, making it a strong competitor for native fish species like the Common carp ( Cyprinus carpio ) [ 34 , 56 , 57 ]. Water fluctuation in this floodplain area allows for the constant refreshment of nutrients, allowing a wide variety of fish species to reside in this area [ 24 ], as seen by the number and diversity of fish taxa recorded in the 5 years of sampling in this study. The results of both Fulton’s condition factors and the relative condition factors showed that a total of eight species were in a relatively good condition, although the species in question varied between the two condition factors. More specifically, Fulton’s condition factor showed good condition for the species Lepomis gibbosus , Carassius gibelio , Cyprinus carpio , Ameiurus nebulosus , Scardinus erythrophthalmus , Gymnocephalus sp., G baloni, and G cernua , while the relative condition factor showed good condition for L gibbosus , C gibelio , C carpio , Pseudorasbora parva , Blicca bjoerkna , Rutilus rutilus , Hypophthalmichthys molitrix , and S glanis . The reason for these differences most likely lies in the fact that Fulton’s condition factor always assumes isometric growth for all fish, while the relative condition factor takes into account the potential variations in the type of growth [ 17 ]. For example, in this study, S glanis was a species with a negative allometric type of growth ( b < 3), which, according to Fulton’s condition factor results, was shown to be in a poor condition, with an average value of 0.6600. Contrary to this, the relative condition factor, with an average value of 1.0524, showed good condition A study on three marine fish species by Muchlisin et al. [ 58 ] pointed out that Fulton’s condition factor tends to give lower values for species with negative allometric growth,

Sustainability 2024 , 16 , 7566 10 of 13 meaning that the species with isometric growth had a higher Fulton’s condition factor compared to the two species whose growth showed to be negative allometric The values of fish condition factors can additionally be influenced by various factors, such as water quality [ 3 ], food availability [ 59 ], and parasitism [ 15 ], as well as the fish’s age and sex [ 60 ]. The negative impact of parasitism was successfully detected through the calculation of the Fulton’s condition factor in C gibelio inhabiting waters of the Kopaˇcki Rit Nature Park [ 8 ]. Water temperature also plays a vital role in changes in condition factors [ 61 ], as fish experience physiological changes closely related to seasonal temperature oscillations, most notably through gonadal development and spawning [ 62 ]. In that sense, the condition factor for fish that spawn in the early spring or early summer months (such as esocids and cyprinids) tends to be relatively higher during warmer periods when food is plentiful and the fish have enough time to recover from spawning [ 46 , 63 ]. A decrease in condition factor values is often noted after spawning and during the colder months [ 64 ] when fish feed less and rely on their lipid reserves as a means to survive food scarcity [ 61 ]. Since the sampling in this study was conducted during the colder months of autumn and winter, it can be assumed that the overall condition of most fish species started to slowly decline after its assumed peak during the summer months. Similar to length–weight relationships, future studies should include seasonal sampling in order to better understand how various abiotic factors impact the condition factor of fish species residing in this area. One very important abiotic factor that should be taken into consideration in future research is the impact of climate change on the structure and condition of fish populations in this protected area. Climatological data for this area show an increase in annual mean water and air temperatures [ 24 ], with air temperatures deviating the most during spring and summer months [ 27 ]. Within the Nature Park, these deviations can further be seen as increases in flooding fluctuations, or prolonged drought seasons [ 65 ], which then have the potential to negatively impact the stability of numerous habitats present in the floodplain area, while also contributing to the spread of invasive species [ 66 ]. Besides constant monitoring to ensure the stability of fish populations, more measures should be put in place to minimize the negative effects of illegal and unregulated fishing, as well as to minimize the spread and negative impact of invasive species on the endangered native fish species residing in this area 5. Conclusions The analyzed results indicate that the floodplain area of the Kopaˇcki Rit Nature Park presents an important and suitable habitat for many fish species from the Danube river, providing adequate shelter and food to allow overall positive allometric growth. This research provided the first valuable data on length–weight relationships and condition factors of different fish species in the Special Zoological Reserve in the Kopaˇcki Rit Nature Park, which can be a guideline for establishing future studies of ichthyofauna in floodplain water bodies Author Contributions: Conceptualization, N.V., I.T. ˇ C. and D. ˇ C.; methodology, D. ˇ C., M.K., V.R., I.T. ˇ C., V.E., B.V., M.Š. and N.V.; validation, D. ˇ C., I.T. ˇ C. and N.V.; formal analysis, N.V.; investigation, D. ˇ C., I.T. ˇ C., M.K., V.E., B.V., M.Š., V.R. and N.V.; resources, D. ˇ C. and V.R.; writing—original draft preparation, N.V., I.T. ˇ C. and D. ˇ C.; writing—review and editing, M.K., V.E., B.V., M.Š., V.R., D. ˇ C., I.T. ˇ C and N.V.; visualization, N.V.; supervision, D. ˇ C. and V.R.; funding acquisition, D. ˇ C. All authors have read and agreed to the published version of the manuscript Funding: This research received no external funding Institutional Review Board Statement: Perennial sampling and research have been conducted within the scope of the “Yearly program of protection, management, preservation, promotion and utilization of Kopaˇcki Rit Nature Park”, including ichthyofauna. Collection for research purposes was approved by the Ministry of Environmental Protection and Nature who issued corresponding permits for the research (UP/I-612-07/16-48/141; 517-07-1-1-1-16-4; UP/I-612-07/19-48/158; 517-05-1-1-19-4). We were also obligated to remove all allochthonous and invasive species from the natural environment.

Sustainability 2024 , 16 , 7566 11 of 13 Informed Consent Statement: Not applicable Data Availability Statement: The data presented in this study are available upon request from the corresponding author Acknowledgments: This research was conducted in cooperation with the Public Institution of the Kopaˇcki Rit Nature Park within their perennial monitoring of ichthyocenoses. We would like to thank our colleagues from the PI Kopaˇcki Rit Nature Park for their kind cooperation. Furthermore, the authors would like to thank Ivana Vukši´c, Matija Kresonja, and other colleagues and students for their help in fieldwork activities Conflicts of Interest: The authors declare no conflicts of interest References 1 Santos, M.N.; Gaspar, M.B.; Vasconcelos, P.; Monteiro, C.C. Weight-Length Relationships for 50 Selected Fish Species of the Algarve Coast (Southern Portugal) Fish. Res 2002 , 59 , 289–295. [ CrossRef ] 2 Sultana, R.; Alam, M.S.; Nazrul, K.S.; Mamun, A.; Al Mamun, M.A. Length-Weight Relationship and Population Dynamics Study of the Giant Catfish ( Arius thalassinus ) in the Bay of Bengal Coast of Bangladesh Res. Agric. Livest. Fish 2020 , 6 , 439–444 [ CrossRef ] 3 Stavrescu-Bedivan, M.; Scaeteanu, G.; Madjar, R.M.; Matei, P.; Tob ă , G. Comparative Study of Length-Weight Relationship, Size Structure and Fulton’s Condition Factor for Prussian Carp from Different Romanian Aquatic Ecosystems AgroLife Sci. J 2015 , 4 , 132–139 4 Schneider, J.C.; Laarman, P.W.; Gowing, H. Length-Weight Relationships. In Manual of Fisheries Survey Methods II with Periodic Updates ; James, C., Ed.; Michigan Department of Natural Resources: Ann Arbor, MI, USA, 2000; pp. 1–16 5 Petrakis, G.; Stergiou, K.I. Weight-Length Relationships for 33 Fish Species in Greek Waters Fish. Res 1995 , 21 , 465–469 [ CrossRef ] 6 Stewart, K.M. Changes in Condition and Maturation of the Oreochromis niloticus L. Population of Ferguson’s Gulf, Lake Turkana, Kenya J. Fish Biol 1988 , 33 , 181–188. [ CrossRef ] 7 Rajput, V. The Length-Weight Relationship, Condition Factor and Impact of Fluoride Concentration in Tor tor (Mahasheer) of Lake Bhimtal, India Ribarstvo 2011 , 69 , 63–69 8 Vui´c, N.; Turkovi´c ˇ Cakali´c, I.; Vlaiˇcevi´c, B.; Stojkovi´c Piperac, M.; ˇ Cerba, D. The Influence of Contracaecum Larvae (Nematoda, Anisakidae) Parasitism on the Population of Prussian Carp ( Carassius gibelio ) in Lake Sakadaš, Croatia Pathogens 2022 , 11 , 600 [ CrossRef ] 9 Miller, S.J.; VanGenechten, D.T.; Cichra, C.E. Length-Weight Relationships and an Evaluation of Fish-Size and Seasonal Effects on Relative Condition (Kn) of Fishes from the Wekiva River Florida Sci 2015 , 78 , 1–19. Available online: http://www.jstor.org/ stable/24321839 (accessed on 21 July 2024) 10 Le Cren, E.D. The Length-Weight Relationship and Seasonal Cycle in Gonad Weight and Condition in the Perch ( Perca fluviatilis ) J. Anim. Ecol 1951 , 20 , 201–219. [ CrossRef ] 11 Kimmerer, W.; Avent, S.R.; Bollens, S.M.; Feyrer, F.; Grimaldo, L.F.; Moyle, P.B.; Nobriga, M.; Visintainer, T. Variability in Length–Weight Relationships Used to Estimate Biomass of Estuarine Fish from Survey Data Trans. Am. Fish. Soc 2005 , 134 , 481–495. [ CrossRef ] 12 Evagelopoulos, A.; Batjakas, I.; Koutsoubas, D. Length-Weight Relationships of 9 Commercial Fish Species from the North Aegean Sea Acta Adriat 2017 , 58 , 187–192. [ CrossRef ] 13 De Giosa, M.; Czerniejewski, P.; Rybczyk, A. Seasonal Changes in Condition Factor and Weight-Length Relationship of Invasive Carassius gibelio (Bloch, 1782) from Leszczynskie Lakeland, Poland Adv. Zool 2014 , 2014 , 678763. [ CrossRef ] 14 Abera, L.; Getahun, A.; Lemma, B. Assessment of Length-Weight Relationship, Sex Ratio and Condition Factor of Common Carp ( Cyprinus carpio Linnaeus, 1758) in Lake Ziway, Ethiopia Glob. J. Fish. Aquac 2015 , 3 , 192–197 15 Neff, B.D.; Cargnelli, L.M. Relationships between Condition Factors, Parasite Load and Paternity in Bluegill Sunfish, Lepomis macrochirus Environ. Biol. Fishes 2004 , 71 , 297–304. [ CrossRef ] 16 Famoofo, O.O.; Abdul, W.O. Biometry, Condition Factors and Length-Weight Relationships of Sixteen Fish Species in Iwopin Fresh-Water Ecotype of Lekki Lagoon, Ogun State, Southwest Nigeria Heliyon 2020 , 6 , e 02957. [ CrossRef ] [ PubMed ] 17 Blackwell, B.G.; Brown, M.L.; Willis, D.W. Relative Weight (Wr) Status and Current Use in Fisheries Assessment and Management Rev. Fish. Sci 2000 , 8 , 1–44. [ CrossRef ] 18 Jin, S.; Yan, X.; Zhang, H.; Fan, W. Weight-Length Relationships and Fulton’s Condition Factors of Skipjack Tuna ( Katsuwonus pelamis ) in the Western and Central Pacific Ocean PeerJ 2015 , 3 , e 758. [ CrossRef ] 19 Scott Cone, R. The Need to Reconsider the Use of Condition Indices in Fishery Science Trans. Am. Fish. Soc 1989 , 118 , 510–514 [ CrossRef ] 20 Murphy, B.R.; Willis, D.W.; Springer, T.A. The Relative Weight Index in Fisheries Management: Status and Needs Fisheries 1991 , 16 , 30–38. [ CrossRef ]

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