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Article

Fish of Low Commercial Value in Lakes of Different Trophic Status (Poland)

by
Krystyna Kalinowska
1,
Dariusz Ulikowski
1,
Michał Kozłowski
1,*,
Piotr Traczuk
1,
Maciej Szkudlarek
1,
Konrad Stawecki
2 and
Andrzej Kapusta
2
1
Department of Lake Fisheries, National Inland Fisheries Research Institute, Rajska 2, 11-500 Giżycko, Poland
2
Department of Ichthyology, Hydrobiology and Aquatic Ecology, National Inland Fisheries Research Institute, Oczapowskiego 10, 10-719 Olsztyn, Poland
*
Author to whom correspondence should be addressed.
Diversity 2024, 16(8), 437; https://doi.org/10.3390/d16080437
Submission received: 5 June 2024 / Revised: 10 July 2024 / Accepted: 19 July 2024 / Published: 24 July 2024
(This article belongs to the Special Issue Evaluating the Influence of Environmental Variables on Fish Ecology and Diversity)
Browse Figures
Versions Notes

Abstract

:
In a commercial fishery, some fish are classified as low-value, but their classification varies in different countries. The aim of this study was to determine the abundance, contribution, and dominance of low-value fish species, such as Abramis brama < 1000 g, Alburnus alburnus, Blicca bjoerkna, Gymnocephalus cernua, Perca fluviatilis < 100 g, Rutilus rutilus < 200 g, and Scardinius erythrophthalmus < 200 g, in 145 Polish lakes of different areas, depths, and trophic statuses situated in the northern and central parts of Poland in 2021. Perca fluviatilis and R. rutilus were the most frequent low-value species (100% and 99%, respectively). The contribution of all low-value fish to the total biomass of caught fish was relatively high, ranging from 37% in the mesotrophic lake to 100% in the eutrophic lake (mean of 77 ± 14%). Lakes in which the contribution of low-value species exceeded 90% were relatively numerous (24 lakes, 17% of the studied lakes). Among a total of about 437.5 thousand low-value fish, 261 thousand specimens (60%) had a body weight of below 10 g. All low-value fish species, except for P. fluviatilis and S. erythrophthalmus, were related to the studied environmental variables. The relative biomass of these species increased with increasing lake productivity, while it decreased with the increasing maximum and mean depth of the studied lakes. The high contribution of low-value fish to the total biomass in many lakes indicates the need for the constant monitoring of the abundance and structure of fish communities and the use of appropriate actions (biomanipulation and stocking with piscivorous fish species) to improve the ecological condition of lakes.

1. Introduction

Low-value/trash fish are generally defined as species of low commercial value due to their low quality, small size, and low or even non-existent consumer preference [1,2,3]. Different fish species are regarded as low value, depending on the habitat, season, tradition, and economic situation of different countries [4]. The same fish can be trash for one community but preferred for another, forming the basis of human nutrition, e.g., as in many countries of Southeast Asia and Africa [2,5].
The group of low-value fish is composed of juveniles, by-catch (caught by non-selective fishing gear), trash fishes, accidental catches, and discards [5,6]. Fish of low value are ubiquitous (eurytopic) species, tolerant of large fluctuations in water temperature, salinity, pH, and oxygen content, short-lived (1 to 3 years), low down in the trophic food web, are zooplankton feeders for a large part of their life cycle, and are characterised by their high relative fecundity [7,8].
A characteristic feature of low-value fish is a relatively low content of fat and low calorific value, but a high concentration of protein, omega-3 polyunsaturated fatty acids, amino acids, vitamins, and minerals, such as iodine, iron, zinc, calcium, potassium, and phosphorus [6,9,10,11,12]. All of these compounds play an important role in cerebral development, immune system support, and general health [7]. Minerals are mainly concentrated in the head, bones, and viscera of the fish; therefore, the consumption of the whole small fish can considerably increase its nutritional quality compared to just consuming the muscle tissue, which is much more commonly consumed for larger species [7,13,14,15]. Small species have a low risk of accumulation of mercury, which is observed in fatty fish of higher commercial value [6]. In this context, small fish can play a particularly important role in combating nutritional deficiencies [16].
It should be emphasised that from the ecological point of view, all fish species are an important element of aquatic ecosystems [2,17] and are necessary for their proper functioning. However, the anthropogenic modifications of aquatic ecosystems has meant that some species can adapt well to the changed environmental conditions and in consequence are more numerous than originally. Too many small-bodied fish in aquatic ecosystems can be accompanied by the deterioration of water quality and ecosystem function [18,19]. The intensive fishing of low-value fish can alter the aquatic ecosystem, resulting in the reduction in the number of larger and more commercially important fish species through the loss of food availability [2]. The reduction in the catch efficiency of valuable fish species and the management of low-value fish is the actual problem for the fisheries economy in Poland [20,21].
In Poland, low-value/trash fish are also called “fish weed” [20]. In freshwater ecosystems, this group includes cyprinid (Rutilus rutilus, Alburnus alburnus, Blicca bjoerkna, Abramis brama, Leucaspius delineatus), percid (Perca fluviatilis, Gymnocephalus cernua), and osmerid (Osmerus eperlanus) fish [22]. It may also include alien invasive species due to their negative impact on aquatic ecosystems, i.e., the loss of biodiversity, shifts in the structure of the native fish community, as well as changes in the structure and functioning of the food web [23,24]. They are very common and numerous in aquatic ecosystems but are not the object of intensive commercial or recreational fishing [8]. Currently, the vast majority of inland waters in Poland are subject to the process of fast eutrophication. The increase in lake trophy is accompanied by the disappearance of sensitive fish species, such as Coregonus maraena and C. albula, as well as an increase in the population of fish with lower environmental requirements (B. bjoerkna, A. brama, and R. rutilus) [25,26,27]. The latter species are resistant to deteriorating water quality and may be the dominant component of the fish community in highly eutrophicated lakes [28]. The excessive occurrence of small-bodied fish in lakes is accompanied not only by the deterioration of water quality but also by changes in the structure and functioning of ecosystems [19].
The aim of the present study was to determine the abundance, size structure, dominance, and contribution of low-value fish species (A. brama < 1000 g, A. alburnus, B. bjoerkna, G. cernua, P. fluviatilis < 100 g, R. rutilus < 200 g, and Scardinius erythrophthalmus < 200 g) to the total numbers and biomass of fish in 145 Polish lakes differing in morphometry and trophy. To our knowledge, our study is the first to assess the contribution of low-value fish species in many lakes in Poland.

2. Materials and Methods

2.1. Study Area

The study was conducted in 145 Polish lakes (Figure 1) with an area of 50–791 ha and a maximum depth of 0.4–45.0 m from 5 July to 5 October 2021. The water temperature, dissolved oxygen concentration, and oxygen saturation were measured in situ at 1.0 m depth intervals using a YSI multiparameter probe (Yellow Spring Instruments, OH, USA). Water transparency was measured with a Secchi disc. The trophic state index (TSI) of the lakes was calculated from the Secchi disc depth according to Carlson [29]. It was assumed that lakes with a TSI < 40 are oligotrophic, 40–50 are mesotrophic, 50–70 are eutrophic, and >70 are hypereutrophic. The characteristics of the studied lakes, divided into trophic types, are presented in Table 1. Eutrophic lakes were the most numerous (84 lakes, 57.9% of the studied lakes), while oligotrophic lakes were the least numerous (3 lakes, 2.1% of the studied lakes).

2.2. Fish Sampling

The fish assemblages were sampled according to the European standard for gillnet surveys EN 14757 [30]. The selected lakes were sampled at least once, between 5 July and 5 October 2021. Nordic multi-mesh gillnets were the gillnets used. Benthic gillnets were 30 m long, 1.5 m high, and composed of 12 panels with a length of 2.5 m and a mesh size ranging from 5 to 55 mm. Benthic gillnets consisted of nets of the following mesh sizes: 5, 6.25, 8, 10, 12.5, 15.5, 19.5, 24, 29, 35, 43, and 55 mm. Pelagic gillnets were 27.5 m long, 6 m high, and composed of 11 panels with a mesh size ranging from 6.25 to 55 mm. Depth layers for benthic gillnets were set to 0–2.9, 3–5.9, 6–11.9, 12–19.9, 20–34.9, and 35–49 m. Pelagic gillnets were set from the surface to the bottom at the deepest point of all the lakes with a maximum depth of at least 7.5 m. Depth layers for pelagic gillnets were set to 0–6, 6–12, 12–18, 18–24, 24–30, 30–36, 36–42, and 42–48 m. The fishing time duration was 12 h (between 6 p.m. and 6 a.m.). All of the caught fish were identified [31], counted, and weighed. Individual measurements of the body weight (BW) of caught specimens were determined with an accuracy of 0.1 g. Catch per unit effort was determined as the numbers per unit effort (NPUE) and biomass per unit effort (WPUE), and standardised to gill net area (100 m2). The Ecological Quality Ratio (EQR)—the ratio between the observed value of a biological parameter based on fish for a given lake and the value expected under reference conditions—was calculated. This ratio is expressed as a numerical value between 0 and 1, with a high ecological status represented by values close to one and a poor ecological status represented by values close to zero. The metrics included in the assessment system in Poland take into account the percentage of the total weight of the following fish species: A. alburnus, A. brama, P. fluviatilis, Sander lucioperca, R. rutilus, S. erythrophthalmus, G. cernua, Tinca tinca, and B. bjoerkna [32]. The ecological quality ratio (EQR) was classified as High (1 ≤ EQR ≥ 0.804), Good (0.804 < EQR ≥ 0.557), Moderate (0.557 < EQR ≥ 0.250), Poor (0.250 < EQR ≥ 0.100), and Bad (0.100 < EQR ≤ 0) [33].

2.3. Data Analyses

The relationships between the relative biomass (WPUE) of A. brama < 1000 g, A. alburnus, B. bjoerkna, G. cernua, P. fluviatilis < 100 g, R. rutilus < 200 g, and S. erythrophthalmus < 200 g and the morphometric (area, maximum and mean depth), trophic (TSI), chemical (contribution of the oxygen layer to the entire water column), and ecological quality ratio (EQR) parameters were determined based on Pearson’s linear correlation analysis, a redundancy analysis (RDA), and Monte Carlo tests (999 permutations). Before the analysis, all data were log-transformed. Because response data were compositional and the gradient was 0.7 SD units long, the above linear method (RDA) was appropriate [34]. Statistical analyses (Pearson’s correlation and RDA) were performed using STATISTICA 8.0 (StatSoft, Inc., St Tulsa, USA) and CANOCO 5 (Microcomputer Power, Ithaca, NY, USA), respectively. The coefficient of variation (CV—% standard deviation of the mean) was used to compare the variability of the contribution of the studied fish species to the relative numbers (CVN) and biomass (CVw).

3. Results

3.1. Fish Communities in Lakes of Different Trophic Status

The general characteristics of the fish communities are presented in Table 2. A total of 34 fish species were found in the studied lakes. The number of fish species in lakes ranged from one to 18. Both the lowest and the highest species richness were recorded in hypereutrophic lakes. The total relative numbers (NPUE) and biomass (WPUE) varied in a very wide range. As in the case of the number of species, both the lowest and the highest values of the NPUE and WPUE were recorded in hypereutrophic lakes.

3.2. Low-Value Species Occurrence, Abundance, Contribution, and Dominance

Perca fluviatilis with a body weight of <100 g was present in all of the studied lakes (100% frequency; Table 3) and constituted 8 to 100% of the total biomass of this species. The number of caught individuals in the studied lakes varied between 3 and 8826. The contribution of small-sized P. fluviatilis to the total biomass of all caught fish ranged from 0.2% in the eutrophic lake to 79.2% in the hypereutrophic lake (mean of 19.8 ± 13.0%; Figure 2). It was the dominant species in 34 lakes.
Rutilus rutilus < 200 g were present in 144 lakes (99.3% of the studied lakes; Table 3) and accounted for an important part of the total biomass of the species R. rutilus (>52.7%). The number of individuals ranged from 31 to 4437. Both the lowest and highest values were recorded in the eutrophic lakes. The contribution of R. rutilus to the total biomass of all caught fish varied between 3.3 and 66.3% (mean of 26.2 ± 11.6%; Figure 2). The lowest value was recorded in the highly eutrophic lake and the highest in the oligotrophic lake. This species dominated in 63 lakes.
Abramis brama < 1000 g was found in 137 lakes (94.5% of the studied lakes; Table 3), constituting 8.8 to 100% of the total biomass of this species. The number of individuals ranged from 1 to 1321. Both the lowest and highest values were noted in the eutrophic lakes. The contribution of this low-value species to the total biomass of all caught fish ranged from 0.01 in the eutrophic lake to 47.14% in the highly eutrophic lake (mean of 10.2 ± 9.8%; Figure 2). Abramis brama was the dominant species in 12 lakes.
Gymnocephalus cernua were present in 135 lakes (93.1% of the studied lakes; Table 3). The number of individuals varied between 2 and 798. The contribution of G. cernua to the total biomass of all caught fish ranged from 0.1 to 20.7% (mean of 1.8 ± 2.4%; Figure 2). The lowest contribution was found in the mesotrophic lake while the highest was in the hypereutrophic lake. Gymnocephalus cernua was the dominant species only in one shallow hypereutrophic lake (34.2% of the total numbers).
Alburnus alburnus was caught in 135 lakes (93.1% of the studied lakes; Table 3). The number of individuals varied from 1 to 6548. One individual was caught in four lakes of different trophy. The highest number of specimens was caught in the eutrophic lake. The percentage contribution of this species to the total biomass of the fish community ranged from 0.02 to 49.9% (mean of 8.8 ± 10.0%; Figure 2). Alburnus alburnus dominated in eight lakes.
Blicca bjoerkna was found in 132 lakes (91.0% of the studied lakes; Table 3). The number of individuals varied from 3 in the mesotrophic lakes to 2535 in the hypereutrophic lake. The contribution of this species to the total biomass of all caught fish ranged from 0.2 to 59.4% (mean of 10.1 ± 9.7%; Figure 2). Blicca bjoerkna was a dominant species in 12 lakes.
Scardinius erythrophthalmus < 200 g was present in 122 lakes (84.1% of the studied lakes; Table 3), accounting for 5.8 to 100% of the total biomass of all caught specimens of this species. The number of specimens ranged from 1 to 223. The contribution of this species to the total biomass of the fish community varied between 0.02 and 29.7% (mean of 3.13 ± 4.26%; Figure 2). Both the lowest and highest contributions were recorded in the eutrophic lakes. Scardinius erythrophthalmus was the dominant species in one eutrophic lake only.

3.3. Total Abundance and Contribution of Low-Value Species

The contribution of all low-value fish species to the total biomass of caught fish in the studied lakes varied widely from 36.8% in the mesotrophic lake to 99.9% in the eutrophic lake. The mean contribution was 77.2 ± 13.8%. This indicates that out of 7749 kg caught fish, as much as 5982 kg are low-value fish. In most lakes (50 lakes, 34.5% of the studied lakes), the low-value fish accounted for 80–90%. They were relatively numerous in lakes, in which the contribution of low-value species exceeded 90% (24 lakes, 16.6% of the studied lakes). The dominant species among low-value fish were mainly P. fluviatilis (0.4–100% of the total biomass of low-value fish) and R. rutilus (4.8–84.3% of the total biomass), which dominated in 36 and 73 lakes, respectively. Abramis brama constituted 0.01–87.5% of the total biomass of low-value fish and dominated in 12 lakes. Blicca bjoerkna accounted for 0.17–59.50% of the total biomass and was a dominant species in 14 lakes. Alburnus alburnus, constituting 0.02–58.7% of the total low-value biomass, dominated in 9 lakes. Gymnocephalus cernua accounted only for 0.07–26.8% of the total biomass and was not a dominant species. Scardinius erythrophthalmus, constituting 0.02–44.18% of the total low-value biomass, dominated in one eutrophic lake only.
Taking into account the mean biomass from all lakes, R. rutilus was the most important species, accounting for 33.5% of the total low-value fish biomass (Figure 3). The second most abundant species was P. fluviatilis (25.6% of the total biomass). The contribution of G. cernua and S. erythrophthalmus did not exceed 4%.

3.4. Relationships between Low-Value Fish and Environmental Parameters

The biomass (WPUE) of all low-value fish species, except P. fluviatilis, showed statistically significant negative correlations with the maximum and mean depth of the studied lakes (Table 4). All species, except P. fluviatilis, S. erythrophthalmus, and/or A. brama were positively correlated with the TSI of the studied lakes and oxygen water layer. Four fish species were negatively related to the EQR, while two other species were positively related to the EQR. In most cases, correlations were very close. Redundancy analysis (RDA) showed a close negative relationship between the EQR and TSI (Figure 4). The total relative biomass of low-value fish and the biomass of A. brama were negatively related to the EQR but positively related to TSI. The biomass of A. alburnus was negatively related to the morphometric parameters, while P. fluviatilis were negatively correlated with oxygen levels.

4. Discussion

Around the world, about 490 fish species (70% of the catch) are low-priced and difficult to market due to a lack of demand [6]. Therefore, there is a need to educate communities to improve the processing, handling and acceptability of low-value fish products for direct human consumption [9]. The use of the term “low-value” fish and the size of their catch depend on the years, fishing season and grounds, location, and the efforts of fishermen to sort the catch [2,35]. In Poland, at different times, various species and assortments of fish were/are considered to be of low value [22]. However, the size ranges for A. brama (<1000 g), R. rutilus, and P. fluviatilis (<200 g) were and still are the same [22]. Only the larger individuals of the above species are attractive to the consumer. In this study, S. erythrophthalmus was also included in the low-value fish, in addition to P. fluviatilis, R. rutilus, A. brama, G. cernua, A. alburnus, and B. bjoerkna, due to its bony nature and low economic importance. In the case of P. fluviatilis, individuals below 100 g were considered to be low-value fish, because larger individuals (100–200 g) are quite valuable fish for consumers and relatively attractive objects of angling. Small-sized O. eperlanus was not included in this category because currently this fish has great economic importance and is a gladly consumed fish. In addition, this species is hardly available due to the specific way of catching which is carried out mainly in winter (under ice cover) with the use of towed nets when the fish gather in large shoals. Therefore, in our study, O. eperlanus was caught only in one mesotrophic lake with an area of 765.3 ha and a maximum depth of 45.0 m. In turn, small-bodied L. delineatus has not been included in the low-value fish group, since it is practically impossible to catch this species with typical fishing gear and it is not the target of recreational fisheries. This species is found only in fish monitoring.
The amount of catches of low-value fish and their contribution to the total numbers and biomass of all caught fish depend on the methods used, mainly the type of net and mesh size, the date of catch, and the purpose of the catch (economic, scientific, regulatory, or monitoring). Although fish sampling with multi-mesh gillnets allows for the solid evaluation of the species composition, abundance, biomass, and size structure of fish, it is not entirely satisfactory and should be complemented by the use of nets of a larger mesh size and other gear for catching larger species [36,37,38,39]. Despite the undoubted benefits of using hydroacoustic methods for fish studies (non-invasiveness, speed of research, and low labour requirement), small fish may not be recognised among the disturbances [40]. In this study, data were collected by the use of multi-mesh gillnets according to the European Standard EN 14757. Low-value fish can constitute a large part of the fish caught [6]. The contribution of this group of fish to the total marine catch was 4% in the Philippines, 17% in Bangladesh, 10–20% in India, 31% in Thailand, 36% in Vietnam, and 38% in China see [2]. In Africa, small fish species account for almost three-quarters of the total inland fish catch [7]. Unfortunately, such data are not available for European countries. In Poland, the contribution of low-value fish to total fishing ranged over the years from 6 to 31%, depending on the economic situation of the country [22]. According to Mickiewicz [41] and Krzywiński et al. [42], low-value species constituted 25–40% of the total biomass of catches from fish farms in lakes. In this study, the contribution of low-value fish to the total biomass of caught fish was much higher (37–100%, mean 77%, respectively). Similarly, a relatively high contribution (56–81%) of low-value fish was found in 2003–2018 in dam reservoirs [43].
The reasons for the low contribution of low-value fish to commercial catches are the high costs of fishing with towed gear, their low demand and price, a decrease in the number of fishermen, there being little or no processing capacity, climate change, and anthropopressure [22]. Climate warming may result in changes in fish community structure due to the direct and indirect effects of temperature and the indirect effects of eutrophication, changes in water levels and salinity, biotic interactions, and the geographical distribution [44]. In European lakes, eutrophication stimulates a shift from salmonids to percids and from percids to cyprinids [26]. Monitoring data from 200 Danish lakes collected in late summer (15 August–15 September) during 1989–2006 showed a significant increase in the proportion of small (<10 cm) perch and bream with increasing temperature, although the temperature effect was not found for roach [26]. An increased proportion of small-bodied fish may influence other processes in the lake, such as nutrient dynamics [45].
Catches of low-value fish may contribute to the improvement of the fish community structure in highly eutrophicated lakes [21]. In fishing catches, the dominant species among low-value fish was the A. brama, which in some lakes (Masurian Lakeland, Poland) accounted for 76–94.4% of the total fish biomass [22]. In contrast, our study showed that R. rutilus and P. fluviatilis were the dominant species. In addition, in some lakes, B. bjoerkna and A. brama (14 and 12 lakes, respectively) dominated the biomass.
The numbers of small cyprinid fish, considered to be of low value, increase along a gradient of lake productivity [8]. Lake morphometry (area and depth) is one of the most important factors affecting the composition of fish communities [26,38,46,47]. In this study, all low-value fish species were found in lakes of different trophic status (from oligo- to hypereutrophic) and morphometry (from shallow to deep). The biomass of all low-value fish species, except for P. fluviatilis and S. erythrophthalmus, increased with the increasing trophic state of the lakes and decreased with the increasing maximum depth. While the contribution of low-value fish in fishing catches has decreased quite considerably in recent years from 48.1 to 27.2% [22], in monitoring studies one can expect the opposite trend, mainly due to the rapid eutrophication of lakes, climate change, and anthropopressure. On the other hand, the high food pressure of the cormorant, for which small and numerous fish are the main prey, may to some extent reduce the abundance of low-value fish [48,49].
Our study showed that 67 lakes (46% of the studied lakes) had an ecological status of below Good (EQR < 0.557). According to the Water Framework Directive (WFD) requirements, the ecological condition of the lakes should be at least Good [50]. The condition of Polish lakes obliges us to take action to change the unfavourable situation. Because fish populations may have an important impact on ecosystem functioning, active biomanipulation should be considered. First, planktivorous fish can consume zooplankton, thereby reducing phytoplankton consumption and consequently increasing its biomass [51,52]. Therefore, the reduction in the abundance of zooplankton-feeding fish has been used as a tool to improve lake water quality [53]. Biomanipulation by removing planktivorous fish leads to improved water quality by increasing the consumption of phytoplankton by zooplankton, especially by filter-feeding cladocerans [54,55,56]. Second, macroinvertebrates and omnivorous fish can affect the availability of nutrients for phytoplankton growth [57] through their transfer from sediment to the water column, thereby increasing the internal nutrient load. Also, the reduction in benthic fish abundance may be used as a tool to improve water quality. The decrease in commercial catches and the change in the species structure of catches [22] indicate that biomanipulation goes beyond the area of current fishing activity in lakes. However, biomanipulation may be not effective without the earlier reduction in the external nutrient loading, which is the key method for restoring highly eutrophicated lakes [44]. A combination of biomanipulation with physico-chemical restoration methods (e.g., chemical treatment, hypolimnion oxidation) can result in the most robust and long-lasting effects [55].
The development of methods of using low-value fish and/or support for entities interested in such catches would be a valuable action for lake protection. Still, low-value fish have enormous unexploited economic potential [5]. With the decreasing availability of large-sized fish, small-sized ones can play an important role in eliminating nutritional deficiencies and improving food availability in some countries, and, therefore, efforts should be made to increase the availability, affordability, and consumption of these low-value fish [16]. Low-value fish products are used not only for human consumption but also for livestock/fish [2,4,58], for the pharmaceutical and cosmetic industries, or for biofuel production [59]. These fish are the most common feed used in Asian fish farms, even though they can be a key source of infectious diseases [60]. However, some countries (e.g., Denmark, Norway, and Chile) restricted or even prohibited the use of low-value fish see [60]. In Poland, low-value fish can be the main and additional ingredient of various types of food, such as tinned fish/vegetables and frozen or snack fish products [12,42], a component of feed for other fish species, e.g., Silurus glanis or Salmo sp. [43] and fur animals [41], as well as fertilisers for vegetables and fruit cultivation [61].

5. Conclusions

Low-value fish (P. fluviatilis < 100 g, R. rutilus < 200 g, A. brama < 1000 g, A. alburnus, G. cernua, B. bjoerkna, and S. erythrophthalmus < 200 g) occurred in lakes of various trophic status and morphometry. The highest frequency was noted for P. fluviatilis (100%) and R. rutilus (99.3%). The contribution of low-value fish to the total numbers and biomass of caught fish was relatively high and amounted to 36.0–99.7% (mean of 92.2%) and 36.8–99.9% (mean of 77.2%), respectively. In 111 lakes (76.6% of the studied lakes), low-value fish accounted for more than 90% of the total numbers of fish caught. The dominant species among low-value fish were mainly P. fluviatilis and R. rutilus. Among a total of about 437.5 thousand low-value fish, 261 thousand specimens (59.6%) had a body weight of less than 10 g. The relative abundance (NPUE) and biomass (WPUE) of all low-value fish species, except for P. fluviatilis and S. erythrophthalmus, increased with increasing lake productivity and decreased with increasing maximum depth of the studied lakes. Our results showed that a considerable number of lakes are dominated by small-bodied fish.

Author Contributions

Conceptualization, P.T. and A.K.; methodology, K.K., D.U., M.K., P.T., M.S., K.S. and A.K.; software, K.K. and M.K.; validation, D.U.; investigation, K.K., D.U., M.K., P.T., M.S., K.S. and A.K.; resources, K.K., D.U., M.K., P.T., M.S., K.S. and A.K.; data curation, K.K., D.U., M.K., P.T., K.S. and A.K.; writing—original draft preparation, K.K., A.K. and M.K.; writing—review and editing, D.U., P.T., M.S. and K.S.; project administration, D.U.; funding acquisition, D.U. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financed through the National Inland Fisheries Research Institute within its statutory research activity (topics no. Z-016 and Z-003).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data will be made available on request.

Acknowledgments

We would like to thank the Chief Inspector of Environmental Protection for the permission to use some collected data of the State Environmental Monitoring for the preparation of this work. We thank Agnieszka Wasilewska for creating the map of the sampling lakes. We thank the anonymous reviewer for their valuable comments, which greatly helped us to improve the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Map of Poland showing the geographical distribution of the 145 lakes (black dots) sampled during the study.
Figure 1. Map of Poland showing the geographical distribution of the 145 lakes (black dots) sampled during the study.
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Figure 2. Contribution of low-value fish species to the total biomass of caught fish in 145 lakes (mean values ± standard deviations and ranges).
Figure 2. Contribution of low-value fish species to the total biomass of caught fish in 145 lakes (mean values ± standard deviations and ranges).
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Figure 3. Contribution of individual low-value fish species to the total biomass of low-value fish species in the studied lakes (mean values).
Figure 3. Contribution of individual low-value fish species to the total biomass of low-value fish species in the studied lakes (mean values).
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Figure 4. Redundancy diagram (RDA) showing the relationships between morphometric (area, maximum and mean depth), chemical (oxygen layer), trophic (TSI), and ecological (EQR) parameters of lakes and the relative biomass (WPUE) of individual low-value fish species and the total biomass of this group (Total) in the studied lakes. The cumulative explained variation for the two first axes is 16.5% (13.7 and 2.8%, respectively).
Figure 4. Redundancy diagram (RDA) showing the relationships between morphometric (area, maximum and mean depth), chemical (oxygen layer), trophic (TSI), and ecological (EQR) parameters of lakes and the relative biomass (WPUE) of individual low-value fish species and the total biomass of this group (Total) in the studied lakes. The cumulative explained variation for the two first axes is 16.5% (13.7 and 2.8%, respectively).
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Table 1. Trophic type and morphometric characteristics of the studied lakes.
Table 1. Trophic type and morphometric characteristics of the studied lakes.
TrophyNumber of LakesArea
(ha)		Depth Max
(m)
Oligotrophy383.5–156.16.5–40.5
Mesotrophy3952.0–765.32.6–45.0
Eutrophy8450.0–790.70.4–45.0
Hypertrophy1951.8–461.31.4–23.1
Total14550.0–790.70.4–45.0
Table 2. The number of fish species and the total relative numbers (NPUE) and biomass (WPUE) of fish communities in different trophic types of the studied lakes.
Table 2. The number of fish species and the total relative numbers (NPUE) and biomass (WPUE) of fish communities in different trophic types of the studied lakes.
TrophyNumber of SpeciesNPUE
(inds./100 m2)		WPUE
(kg/100 m2)
Oligotrophy7–1553–3121.2–7.2
Mesotrophy9–1628–5020.7–9.1
Eutrophy6–1723–19261.0–24.1
Hypertrophy1–1816–32370.5–28.9
Total1–1816–32370.5–28.9
Table 3. List of analysed low-value fish species found in the studied lakes, their frequency, relative numbers (NPUE), relative biomass (WPUE), and coefficient of variations in NPUE (CVN) and WPUE (CVW). Mean values ± standard deviations and ranges in parentheses.
Table 3. List of analysed low-value fish species found in the studied lakes, their frequency, relative numbers (NPUE), relative biomass (WPUE), and coefficient of variations in NPUE (CVN) and WPUE (CVW). Mean values ± standard deviations and ranges in parentheses.
SpeciesNumber of LakesFrequency
(%)		NPUE
(inds./100 m2)		CVN
(%)		WPUE
(g/100 m2)		CVW
(%)
Perca fluviatilis145100.0100.1 ± 111.4111974.5 ± 962.099
(0.4–852.8) (8.3–8054.1)
Rutilus rutilus14499.390.2 ± 109.01211477.3 ± 1459.799
(3.9–653.3) (59.8–10,965.1)
Abramis brama13794.526.1 ± 44.4170672.7 ± 1087.4162
(0.1–244.6) (0.2–9819.7)
Alburnus alburnus13593.188.1 ± 212.2241766.4 ± 1678.4219
(0.2–1341.7) (1.5–12,022.4)
Gymnocephalus cernua13593.111.4 ± 18.216088.1 ± 121.4138
(0.2–118.2) (1.2–775.9)
Blicca bjoerkna13291.039.5 ± 74.2188675.6 ± 1244.5184
(0.1–512.1) (7.6–10,764.4)
Scardinius erythrophthalmus12284.14.2 ± 6.2148142.9 ± 195.0137
(0.1–30.6) (0.6–1043.3)
Table 4. Correlation coefficients (n = 145) between abiotic parameters (area, mean and max depth, oxygen), the trophic state index (TSI), and ecological quality ratio (EQR) of the studied lakes and the biomass (WPUE) of low-value fish species. ns—not significant correlation, *—p < 0.05, **—p < 0.01, ***—p < 0.001, ****—p < 0.0001.
Table 4. Correlation coefficients (n = 145) between abiotic parameters (area, mean and max depth, oxygen), the trophic state index (TSI), and ecological quality ratio (EQR) of the studied lakes and the biomass (WPUE) of low-value fish species. ns—not significant correlation, *—p < 0.05, **—p < 0.01, ***—p < 0.001, ****—p < 0.0001.
SpeciesAreaDepth MaxDepth MeanOxygenTSIEQR
Perca fluviatilisnsnsnsnsns0.19 *
Rutilus rutilusns−0.32 ****−0.34 ****0.32 ****0.27 ***ns
Abramis bramans−0.27 **−0.33 ***ns0.31 ***−0.18 *
Alburnus alburnusns−0.31 ***−0.32 ****0.37 ****0.40 ****−0.20 *
Gymnocephalus cernuans−0.24 **−0.25 **0.32 ****0.44 ****−0.35 ****
Blicca bjoerknans−0.28 ***−0.29 ***0.32 ****0.39 ****−0.18 *
Scardinius erythrophthalmusns−0.19 *−0.17 *0.26 **ns0.42 ****
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Kalinowska, K.; Ulikowski, D.; Kozłowski, M.; Traczuk, P.; Szkudlarek, M.; Stawecki, K.; Kapusta, A. Fish of Low Commercial Value in Lakes of Different Trophic Status (Poland). Diversity 2024, 16, 437. https://doi.org/10.3390/d16080437

AMA Style

Kalinowska K, Ulikowski D, Kozłowski M, Traczuk P, Szkudlarek M, Stawecki K, Kapusta A. Fish of Low Commercial Value in Lakes of Different Trophic Status (Poland). Diversity. 2024; 16(8):437. https://doi.org/10.3390/d16080437

Chicago/Turabian Style

Kalinowska, Krystyna, Dariusz Ulikowski, Michał Kozłowski, Piotr Traczuk, Maciej Szkudlarek, Konrad Stawecki, and Andrzej Kapusta. 2024. "Fish of Low Commercial Value in Lakes of Different Trophic Status (Poland)" Diversity 16, no. 8: 437. https://doi.org/10.3390/d16080437

APA Style

Kalinowska, K., Ulikowski, D., Kozłowski, M., Traczuk, P., Szkudlarek, M., Stawecki, K., & Kapusta, A. (2024). Fish of Low Commercial Value in Lakes of Different Trophic Status (Poland). Diversity, 16(8), 437. https://doi.org/10.3390/d16080437

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