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Article

Chironomid Pupal Exuviae Technique in Ecological Research of Man-Made Water Bodies

by
Viktorija Ergović
1,
Dubravka Čerba
2,*,
Natalija Vučković
3 and
Zlatko Mihaljević
3
1
Department of Biology, University of Osijek, Cara Hadrijana 8/a, 31000 Osijek, Croatia
2
Department of Assessment and Aquatic Ecosystems Research, National Water Reference Laboratory of Slovakia, Water Research Institute, Nábr. arm. gen. L. Svobodu 5, 81249 Bratislava, Slovakia
3
Department of Biology, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Water 2024, 16(20), 2917; https://doi.org/10.3390/w16202917
Submission received: 11 September 2024 / Revised: 9 October 2024 / Accepted: 12 October 2024 / Published: 14 October 2024
(This article belongs to the Special Issue Aquatic Ecosystems: Biodiversity and Conservation)
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Abstract

:
Reservoirs serve functional purposes such as irrigation and power generation. However, concerns are raised due to the alterations of the connected riverine ecosystems. Chironomidae (Diptera), a diverse aquatic macroinvertebrate group, are vital to the functioning of ecosystems and serve as water quality indicators. Their holometabolous development includes the pupal stage after four larval stages. The chironomid pupal skin (exuvia) is used in environmental assessments, where the Chironomid Pupal Exuvial Technique (CPET) is a recognized standard. The CPET method is adaptable to different freshwater environments and here was applied in the study of 28 man-made lakes in the Pannonian Lowlands and Dinaric Western Balkan Ecoregion in Croatia to obtain information on chironomid diversity and analyze the potential influence of environmental factors on the chironomid community. The lake surface was skimmed with an exuvial hand net (mesh size of 300 µm) along the lake edge with a transect length of 10 m in the area of accumulated debris of organic and inorganic matter. Individual exuviae were mounted in a Berlese mounting medium and identified by morphological characteristics to the lowest taxonomic level. During the study, 5698 chironomid pupal skins were collected, and 141 taxa (including 97 species) belonging to five subfamilies were identified. The tribe Tanytarsini comprised 40% of the identified taxa, with Paratanytarsus spp. being the most abundant. In the Dinaric ecoregion, Paratanytarsus bituberculatus dominated, while Microchironomus tener and the genus Cricotopus were the dominant taxa in the Pannonian ecoregion. Community structure in the Pannonian ecoregion was influenced by total organic carbon (TOC) and orthophosphates (PO43−), indicating higher anthropogenic pressure compared to the Dinaric ecoregion, where water conductivity influenced Chironomidae assemblages. The research has provided valuable and useful information on the chironomid diversity in man-made and highly altered water bodies, as some of the most vulnerable aquatic habitats to anthropogenic influence. The CPET method could be a useful tool for the ecological studies and bioassessment of water quality in Croatia.

1. Introduction

Artificial lakes, such as reservoirs, are primarily created for the benefit of humans and have various benefits and uses, such as agricultural irrigation, water storage, power generation, or fish farming [1,2]. Today, these lakes are mainly used for relaxation and recreation purposes in/near urban areas. Artificial lakes for wider human use can also be created by excavating gravel or clay, dug as separated fishpond pools, fortified reservoirs for water storage, etc. However, reservoirs are generally built by constructing dams to store water in certain river sections. In Croatia, about 40 reservoirs were built in the last century [3]. Sometimes, the disadvantages of structures such as dams outweigh the benefits mentioned, and there is a need to closely monitor the impact of dams on the entire aquatic ecosystem. Construction alters the existing state of the river [4], leading to significant changes in the hydrological regime and water quality (e.g., increase in water temperature and increase in fluctuations and sedimentation) [5,6,7], and consequently, the biota. The newly formed lake with a higher water temperature may have an increased nutrient uptake, a higher degree of eutrophication, and oxygen deficiency in combination with a lower water transparency [8,9]. All this can lead to shifts in the existing biological communities and changes in their structures and interactions, which affects the functioning of the entire ecosystem [10,11]. According to some researchers, the dominance of tolerant taxa and the loss of sensitive taxa is evident [12,13]. However, Vilenica et al. [14,15,16] proposed that man-made lakes (in Croatia) can be biodiversity hotspots that harbor many species and could even contribute to species conservation.
The Chironomidae (Diptera) are one of the most diverse and abundant taxonomic groups of freshwater macroinvertebrates, occurring at all trophic levels and playing an essential role in food webs, energy flow, and aquatic ecosystem functioning [17,18,19,20,21]. Some chironomid species can even be found in marine (e.g., Halocladius (s.str.) varians (Staeger, 1839) and Thalassosmittia thalassophila (Bequaert and Goetghebuer, 1913)) and terrestrial (e.g., Georthocladius luteicornis (Goetghebuer, 1941)) environments [22]. Chironomidae inhabit heterogeneous microhabitats, including some very specific environments, e.g., glacial brooks [23], hot springs [24], or live as mayfly parasites [25,26]. Chironomidae larvae are known to feed in a variety of ways and are, therefore, often categorized as collectors, grazers, shredders, and predators [27]; some are even known to feed on the hemolymph/blood of aquatic invertebrates or juvenile vertebrates [25,28]. Due to their considerable diversity and high contribution to the biomass of the total macrozoobenthos (both in terms of number of individuals and number of species), they can also be used as water quality indicators in the bioassessment of aquatic environments [17,29,30].
Chironomids are a holometabolous insect group that develops a pupal stage after four larval stages and before the emergence of adults, which can last from a few hours to several days. After emergence, the skin, known as the pupal exuvia, remains on the water surface for up to seven days, depending on water currents, atmospheric conditions, bacterial activity, etc. [17]. The use of chironomid pupal exuviae for the environmental impact assessment of water bodies is increasingly recognized in aquatic environmental studies [31,32,33,34]. The Chironomid Pupal Exuvial Technique (CPET) [35,36] was introduced as the standard method for determining water quality in accordance with the European Union Water Framework Directive [29]. The CPET was initially developed for river biomonitoring [35,37] but is now used in all types of freshwater research [36,38]. CPET is an easy method to use [39,40,41], and its advantages are seen especially in environments with difficult sampling conditions [42]. In a reservoir or lake, the species that are able to maintain a population reflect the physical and chemical characteristics of the sediments and water [43].
This study was part of an extensive project: “Development of a classification system for assessing the ecological potential of artificial and heavily modified surface waters”, with the aim of obtaining ecological data on invertebrate communities in man-made and modified lakes in Croatia. Although water bodies adapted for human utilization can have rather uniform conditions, studied lakes and reservoirs differed in their geographical position, type, degradation level, etc., which could affect biotic communities within in different ways. In Croatia, there was no knowledge of the level of changes in those water bodies from the “natural lake conditions”, nor which are the main parameters influencing the macroinvertebrates. There were no data on the benthic biodiversity in such ecosystems, and studying diversity, especially in the profundal zone, can be quite challenging. By applying the CPET method, we mainly aimed to obtain information on chironomid diversity, detect the presence of non-littoral species, analyze the potential influence of environmental factors on the chironomid community, and also to compare communities between the two different ecoregions. The present study is the first to apply the chironomid pupal exuviae method in man-made lakes in Croatia.

2. Materials and Methods

2.1. Study Area

We analyzed 28 man-made or heavily modified lakes in Croatia (Figure 1). These lakes are mainly reservoirs for irrigation, power generation, and water supply. Some of the lakes are natural but modified water bodies (e.g., Sakadaš Lake, Prološko Blato), and some are gravel pits that are now mainly used for recreational purposes (e.g., Koprivnica Šoderica, Novo Čiče, Rakitje). Hydropower plant artificial lakes (e.g., Dubrava, Varaždin, Čakovec) are lakes with high seasonal water level fluctuations (Table 1).

2.2. Sampling Protocol

Sampling was carried out from July to September 2016 and 2017 on 28 locations. The samples were taken from two ecoregions in Croatia [44]: Dinaric Western Balkan (15 samples) and Pannonian Lowlands (13 samples) (Table 1). The lake surface was sampled once, using a modified Chironomid Pupal Exuvial Technique (CPET) [36] to collect individuals from the studied artificial lakes. Samples were collected using an exuviae hand net with a mesh size of 300 µm along the lake edge with a transect length of 10 m in the area of accumulation of debris and pupal skins. Each sample was preserved in a 4% formaldehyde solution. Further analysis included the separation of the exuviae in the laboratory and the preparation of permanent slides by mounting them in the Berlese mounting medium. The Chironomidae were identified to the lowest taxonomic level using the identification keys of Wiederholm [45] and Langton [46], based on their morphological characteristics.

2.3. Environmental Parameters

The environmental parameters measured at each site with WTW probes were oxygen concentration (oximeter WTW Oxi 330/SET), conductivity (WTW LF 330), and pH (WTW pH 330); water temperature was also measured. Altitude, water level fluctuations, depth of the lake, and consumption of 0.1 M HCl for water hardness were assessed for each lake. Analyses of the water for biological oxygen demand (BOD), chemical oxygen demand (CODMn), total organic carbon (TOC), total nitrogen (TN), nitrate (NO3−), and orthophosphate (PO43−) were carried out according to APHA standard methods (1992) in the Central Water Management Laboratory of Hrvatske Vode (legal entity for water management in Croatia). Land use in the vicinity of the man-made lakes was calculated using the Corine Land Cover classification in the GIS tool [47].

2.4. Data Analyses

Prior to data analysis, identified taxa with only one or two collected individuals (exuviae) were excluded from further calculations, data were transformed using square root transformation (both species and environmental data), and analyses considered the relative abundance of each taxon [48]. Only environmental data matrices were normalized [49].
The similarity of chironomid assemblages between different study sites was calculated using cluster analysis and non-metric multidimensional scaling (nMDS) ordination based on the Bray-Curtis similarity matrix. In this ecological study, nMDS was used for the visualization of multidimensional data of identified species and presenting it in two-dimensional space to identify the gradients and patterns between samples. Euclidean distance was used in the resemblance matrix for environmental data. The statistical software used for data analysis was Primer 6 with Permanova [50]. The same software was used to visualize the data–plots from PCA and dbRDA. PCA was applied to obtain the underlying data structure, and dbRDA was applied to find the connections between species composition with investigated environmental variables to determine key factors that are responsible for shaping community structure or how each environmental variable influences the community. For the ordination of species occurrence in relation to environmental variables, Canonical correspondence analysis (CCA) was performed using CANOCO 5.00 software [51]. A total of 20 environmental variables were tested using the Monte Carlo permutation test with 999 permutations to test the significance of the identified community. Only statistically significant (p < 0.05) environmental variables were considered for data visualization. All recorded taxa were considered for the calculation of the diversity indices.

3. Results

3.1. Chironomidae Assemblages

A total of 5698 chironomid pupal exuviae were collected during the sampling campaign. One hundred forty-one taxa, of which 97 species from five subfamilies, were identified: Tanypodinae (10 taxa), Buchonomyiinae (1 taxon), Diamesinae (1 taxon), Orthocladiinae (40 taxa) and Chironominae–Chironomini (51 taxa), Tanytarsini (38 taxa) (Tables S1 and S2). Tanytarsini accounted for about 40% of all identified taxa, with Paratanytarsus spp. being the most abundant (13.55% of all individuals collected). The most common Tanypodinae species was Procladius choreus (2.51%). Psectrocladius brehmi (4.07%) and Cricotopus sylvestris (2.23%) were the most common Orthocladiinae species, accounting for 26.55% of all individuals collected. The most abundant Chironomini species were Microchironomus tener (9.92%), Tanytarsini Paratanytarsus spp., and Constempellina spp., which accounted for 13.55% and 4.95% of all identified taxa, respectively. The most abundant species was Procladius choreus, which was found at 18 surveyed sites in both ecoregions. Of the 141 taxa, 57 were collected in both ecoregions.
In the Dinaric Western Balkan ecoregion, 3470 exuviae were collected, and 106 taxa were identified, with Paratanytarsus bituberculatus being the most common species. In the Pannonian Lowlands ecoregion, 2228 individuals were collected, and 94 taxa were identified. The most abundant species was Microchironomus tener, followed by the genus Cricotopus. The sites with the highest Shannon-Wiener index were Lokve, Štikada, and Gusić Polje (2.97; 2.89; 2.85) in the Dinaric ecoregion and Čakovec, Varaždin, and Dubrava (3.03; 2.85; 2.84) in the Pannonian ecoregion. The lowest index values were at Ričice (0.63) in the Dinaric and Sakadaš Lake (0.69) in the Pannonian ecoregion.
The nMDS analysis revealed similarities between the sites that are strongly dependent on the ecoregion (Figure 2).
In the Dinaric ecoregion, Prološko Blato had the highest Chironomidae exuviae abundance, while Rakitje was the site where we sampled the highest number of exuviae in the Pannonian ecoregion. Biljsko, Sakadaš, Jošava, Popovac Lake, and Sabljaci were the sites with the lowest abundance of exuviae.

3.2. Environmental and Spatial Drivers

The results of the CCA ordination analysis of the samples and environmental data are shown in Figure 3. Three of the 20 environmental variables tested were statistically significant (p < 0.05). All four axes (eigenvalues of 0.664, 0.588, 0.434, and 0.382) were able to explain a species-environmental correlation of 39.1%. The Monte Carlo permutation test showed that the ordination between exuviae (101 taxa) and environmental variables was significant (first axis F-ratio = 2.26, p = 0.002; overall: trace = 5.295, p = 0.002). Axis 1 was strongly correlated with ecoregion and TOC (total organic carbon), suggesting that these environmental variables are essential for structuring the Chironomidae assemblages (Figure 3).
Conductivity was the only statistically significant environmental parameter influencing Chironomidae assemblages in the Dinaric Western Balkan ecoregion with Cricotopus spp., Psectrocladius sordidelus, and Chironomus plumosus (Figure 4). In the Pannonian ecoregion, the community was structured under the influence of TOC, PO43− (orthophosphate), and altitude. The Jošava, Sakadaš, and Pakra sites correlated most strongly with PO43− values, while TOC had the greatest influence on the community in Popovac and Biljsko Lake (Figure 5a). The species that contributed to the environmental status of these reservoirs are highlighted in Figure 5b.
The Spearman correlation test showed a correlation between O2 (oxygen concentration), conductivity, BOD (biological oxygen demand), TOC, and PO43− with the highest value of 0.568 (p < 0.05). dbRDA results are shown in Figure 6. Together, these five variables could explain 79.12% of the species community data, with TOC being the most significant, with 21.56% of the explained data.
Principal component analysis (PCA) (Figure 7) shows that the ordination of samples in the Dinaric Western Balkan ecoregion correlates negatively with total organic carbon and orthophosphate content.

4. Discussion

The research included 28 artificial water bodies in which 141 Chironomidae taxa, including 97 species, were found. The tribe Tanytarsini comprised about 40% of all identified taxa, mainly Paratanytarsus spp., with a relative abundance of 13.55%. According to Mihaljević et al. [52], the most common chironomid taxa identified in macrozoobenthos samples of studied man-made water bodies belonged to the Tanytarsini (Tanytarsus, Paratanytarsus, and Cladotanytarsus), followed by Tanypodinae and Chironomini. In previous studies on the chironomid assemblages in submerged macrophyte stands in one of the studied water bodies—Sakadaš Lake, Čerba et al. [53,54] recorded 22 and 29 chironomid taxa, respectively, while only two taxa were found in the present study of Sakadaš Lake: Glyptotendipes pallens and Kiefferulus tendipediformis. This mentioned study was focused mainly on the diversity of Chironomidae larvae in connection to the submerged plant species (Myriophyllum spicatum and Ceratophyllum demersum) in Lake Sakadaš, but in recent three-year studies [55], there is no, or very scarce macrophyte community in that lake. Macrophytes are known to represent an important habitat for macroinvertebrates [56], and their absence can potentially be directly linked to the lower number of recorded Chironomidae species in this study.
Species richness of aquatic invertebrates in man-made lakes in Croatia is relatively diverse. In a sampling campaign, Vilenica et al. [15,16] collected 32% of all Croatian Odonata species and 25% of the recorded Croatian mayfly species in man-made lakes. According to Čerba et al. [57], 41% of the total identified Chironomidae species have been recorded in reservoirs. In a study of Chironomidae in European reservoirs conducted on the basis of exuviae samples, the dominant representatives belonged to the Chironominae subfamily [38], with Paratanytarsus spp. being the most abundant taxa. Paratanytarsus is a fairly widespread genus. They are known to favor lentic habitats where they build living tubes and feed on fine organic particles [17,58]. Paratanytarsus bituberculatus, the dominant species in our study, is a species characteristic of stagnant waters [46] but can also be found in slow-flowing streams [59]. This corresponds to the fact that some reservoirs have a short water retention time, which makes them a suitable habitat for this species. The most common Tanypodinae species in our study was Procladius choreus, a species that inhabits lakes and reservoirs in a wide range of trophic states, from oligotrophic to hypertrophic. This highly adaptable species can live in different water quality ranges [60,61]. Interestingly, in samples of macrozoobenthos from man-made lakes, P. choreus was found predominately in littoral sediments at depths between 0.5 and 1 m [52], and the most abundant among Tanypodinae species in the mentioned macrozoobenthos study was Ablablesmyia monilis. Since the sampling of larvae that mainly live in greater depths of lakes rather than littoral zones can be challenging, e.g., Microchironomus tener [62], the CPET method and the collection of pupal exuviae has proven to be a more favorable method for ecological studies [63,64]. Many studies indicate that the CPET method can be used to obtain a relatively high number of species and genera in contrast to the hand-net sampling method of littoral macroinvertebrate fauna [39,41,65]. According to Anderson and Ferrington [40], the CPET method requires 1/3 less time compared to the macrozoobenthos sampling. Another advantage of the CPET method in biomonitoring is that it is a non-invasive method for the environment [66]. Furthermore, it is a cost-effective and more precise method of species identification, resulting in higher species richness in comparison to hand-net sampling [39,66]. An illustration of some of the advantages of this method is given in Table S3.
Croatia is divided into two ecoregions, with each ecoregion having different environmental characteristics, e.g., climate, substrate, water chemistry, precipitation, etc. [44,67,68]. The clustering of reservoirs based on the Chironomidae assemblages is directly related to the spatial drivers defined by the ecoregion. In man-made lakes of the Pannonian Lowlands ecoregion, the species Polypedilum sordens, Glyptotendipes imbecilis, G. pallens, Endochironomus albipennis, Cricotopus intersectus, C. sylvestris, Paratanytarsus inopertus, and Kiefferulus tendipediformis were positively correlated with the concentration of orthophosphates and negatively correlated with increasing depth of the reservoir. These species are typically found in sediments with decaying plants and nutrient-rich waters with good oxygen content; some of them can even live in highly eutrophic waters [28]. Based on the orthophosphate content, the Pannonian ecoregion is exposed to greater anthropogenic pressure than the Dinaric ecoregion. Orthophosphate content alters water quality and ecological status, leading to a decline in biodiversity and assemblage structure [19]. The sites with the highest orthophosphate levels are under greater anthropological pressure; these include Jošava, Biljsko, Čakovec, Varaždin, Koprivnica Šoderica, Dubrava, and Pakra. The first two sampling localities (Jošava and Biljsko Lake) showed poor species diversity. One of the environmental variables that has significantly influenced the Chironomidae assemblage is the maximum depth of lakes. Deeper lakes or reservoirs tend to have smaller littoral areas, with less light passing through along the shoreline. Basin shape changes with connectivity, and scaling relationships can be used to estimate the relative size of the littoral region [69]. In the littoral zone of the lake, the water column is more easily mixed under the influence of the wind and, as such, is, therefore, directly related to the oxygen content in the water [70]. Conductivity and, consequently, water hardness were the only two significant environmental parameters influencing Chironomidae assemblages in the Dinaric ecoregion, reflecting the conditions typical of the karst region [71,72].
Almost all major European rivers are dammed or regulated in some parts [73]. The benefits of damming a river include the utilization of the upstream areas for hydropower and water supply, while the downstream areas are flood protection areas [74]. Such modifications also alter the river flow, which in turn leads to changes in the river bed. These changes affect the physical and chemical properties of the water body, can have a negative impact on water quality, and can potentially cause changes in the biotic communities in the newly created ecosystem (e.g., the structure of the benthic community, preventing fish mobility) [75,76]. Additional high anthropogenic pressure on these habitats (e.g., high organic pollutant or nutrient loads) and differences in water levels, together with low habitat diversity and low nutrient availability, contribute to a lower diversity of biota [15,77,78].

5. Conclusions

Chironomidae pupal exuviae are a good tool for ecological studies on man-made or heavily modified water bodies. In general, CPET assesses the “health” of the aquatic ecosystem and offers advantages over standard macroinvertebrate sampling, such as reduced habitat disruption and more precise species identification. In this case, unlike benthic samples from reservoirs, exuviae provided 69 new species for Croatian chironomid fauna, as a great contribution to the checklist. Even though the sampling in this study was possible only on one occasion during the summer months, this research has provided valuable and useful information on the diversity of the Chironomidae community in the man-made and highly altered water bodies, as some of the most vulnerable aquatic habitats to the anthropogenic influence. Furthermore, clear responses from the “CPET chironomid community” to the environmental parameters indicate that the CPET method could be a useful tool for the ecological studies and bioassessment of water quality in Croatia.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/w16202917/s1, Table S1: Chironomidae taxa recorded in Pannonian Lowlands Ecoregion; Table S2: Chironomidae taxa recorded in Dinaric Western Balkan Ecoregion. Table S3: An overview and comparison of sampling efforts and results between benthic and exuviae methodology.

Author Contributions

Conceptualization, Z.M., V.E. and D.Č.; methodology, Z.M., V.E. and D.Č.; validation, Z.M.; formal analysis, V.E.; investigation, Z.M., V.E., N.V. and D.Č.; resources, Z.M. and D.Č.; writing—original draft preparation, V.E., D.Č. and Z.M.; writing—review and editing, Z.M., V.E., N.V. and D.Č.; supervision, Z.M. and D.Č.; project administration, Z.M.; funding acquisition, Z.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was part of the project: “Development of a classification system for assessing the ecological potential of artificial and heavily modified surface waters”, funded by Central Water Management Laboratory of Hrvatske Vode (legal entity for water management in Croatia). Project number: 10-023/16.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

Authors would like to thank the Central Water Management Laboratory of Hrvatske Vode (legal entity for water management in Croatia) for providing land use and water physicochemical data and Nera Vuić, mag. biol. for assisting with the graphical illustrations.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Positions of the study sites of the 28 man-made lakes (ER 5—Dinaric Western Balkan: 1—Opsenica, 2—Ričice-Zeleno Lake, 3—Prološko Blato, 4—Lokve, 5—Vlačine, 6—Razovac, 7—Pranjčević, 8—Peruča, 9—Štikada, 20—Tribalj, 21—Sabljaci, 22—Lešće, 23—Brljan, 24—Golubić, 28—Gusić Polje; ER 11—Pannonian Lowlands: 10—Rakitje, 11—Novo Čiče, 12—Jarun, 13—Koprivnica Šoderica, 14—Popovac, 15—Pakra, 16—Biljsko Lake, 17—Sakadaš Lake, 18—Jošava, 19—Lapovac, 25—Varaždin, 26—Čakovec, 27—Dubrava).
Figure 1. Positions of the study sites of the 28 man-made lakes (ER 5—Dinaric Western Balkan: 1—Opsenica, 2—Ričice-Zeleno Lake, 3—Prološko Blato, 4—Lokve, 5—Vlačine, 6—Razovac, 7—Pranjčević, 8—Peruča, 9—Štikada, 20—Tribalj, 21—Sabljaci, 22—Lešće, 23—Brljan, 24—Golubić, 28—Gusić Polje; ER 11—Pannonian Lowlands: 10—Rakitje, 11—Novo Čiče, 12—Jarun, 13—Koprivnica Šoderica, 14—Popovac, 15—Pakra, 16—Biljsko Lake, 17—Sakadaš Lake, 18—Jošava, 19—Lapovac, 25—Varaždin, 26—Čakovec, 27—Dubrava).
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Figure 2. Non-metric multidimensional scaling (nMDS) plot shows the distribution of Chironomidae species based on Bray-Curtis resemblance and group-average hierarchical cluster analysis. Samples from two different ecoregions are shown in different colors. The abbreviations of the study sites correspond to those in Table 1.
Figure 2. Non-metric multidimensional scaling (nMDS) plot shows the distribution of Chironomidae species based on Bray-Curtis resemblance and group-average hierarchical cluster analysis. Samples from two different ecoregions are shown in different colors. The abbreviations of the study sites correspond to those in Table 1.
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Figure 3. F1 × F2 plane of Canonical correspondence analysis (CCA) based on 28 samples and 20 environmental variables. Legend: T—water temperature; asl—altitude; FV—water level fluctuation; depth of lake (Dmax and Dmean); P (km2)—surface area of a reservoir; O2—dissolved oxygen concentration; cond—conductivity; °dH—water hardness; BOD—biological oxygen demand; CODMn—chemical oxygen demand; TOC—total organic carbon; TN—total nitrogen; NO3−—nitrate; PO43−—orthophosphate concentration; i-ag—intensive agricultural land use; e-ag—extensive agricultural land use; NAT—natural and near-natural land use. The different ecoregions are labeled with different symbols (ER 5—black circle; ER 11—purple square), and three black arrows represent three statistically significant environmental variables. The abbreviations are as in Figure 1.
Figure 3. F1 × F2 plane of Canonical correspondence analysis (CCA) based on 28 samples and 20 environmental variables. Legend: T—water temperature; asl—altitude; FV—water level fluctuation; depth of lake (Dmax and Dmean); P (km2)—surface area of a reservoir; O2—dissolved oxygen concentration; cond—conductivity; °dH—water hardness; BOD—biological oxygen demand; CODMn—chemical oxygen demand; TOC—total organic carbon; TN—total nitrogen; NO3−—nitrate; PO43−—orthophosphate concentration; i-ag—intensive agricultural land use; e-ag—extensive agricultural land use; NAT—natural and near-natural land use. The different ecoregions are labeled with different symbols (ER 5—black circle; ER 11—purple square), and three black arrows represent three statistically significant environmental variables. The abbreviations are as in Figure 1.
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Figure 4. The CCA analysis shows the effects of environmental data on community structure in the Dinaric Western Balkan ecoregion; the statistically significant variable is marked with a black arrow. The circles represent samples: 1—Opsenica, 2—Ričice-Zeleno Lake, 3—Prološko Blato, 4—Lokve, 5—Vlačine, 6—Razovac, 7—Pranjčević, 8—Peruča, 9—Štikada, 10—Tribalj, 11—Sabljaci, 12—Lešće, 13—Brljan, 14—Golubić, 15—Gusić Polje.
Figure 4. The CCA analysis shows the effects of environmental data on community structure in the Dinaric Western Balkan ecoregion; the statistically significant variable is marked with a black arrow. The circles represent samples: 1—Opsenica, 2—Ričice-Zeleno Lake, 3—Prološko Blato, 4—Lokve, 5—Vlačine, 6—Razovac, 7—Pranjčević, 8—Peruča, 9—Štikada, 10—Tribalj, 11—Sabljaci, 12—Lešće, 13—Brljan, 14—Golubić, 15—Gusić Polje.
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Figure 5. The CCA analysis shows the effects of environmental data on community structure in the Pannonian Lowlands ecoregion: (a) shows the distribution of sampling sites and environmental parameters; (b) shows the distribution of Chironomidae taxa with the highest correlated environmental parameters. The statistically significant variables are marked with a black arrow. The circles represent samples: 1—Rakitje, 2—Novo Čiče, 3—Jarun, 4—Koprivnica Šoderica, 5—Popovac, 6—Pakra, 7—Biljsko Lake, 8—Sakadaš Lake, 9—Jošava, 10—Lapovac, 11—Varaždin, 12—Čakovec, 13—Dubrava). Abbreviation of species: cladlepi—Cladotanytarsus lepidocalcar, cladvire—Cladopelma virescens, cricinte—Cricotopus intersectus, cricsylv—Cricotopus sylvestris, endoalbi—Endochironomus albipennis, glypimbe—Glyptotendipes imbecilis, glyppall—Glyptotendipes pallens, kieftend—Kiefferulus tendipediformis, nanodich—Nanocladius dichromus, paraacul—Parachironomus arcuatus, parainop—Paratanytarsus inopertus, polysord—Polypedilum sordens.
Figure 5. The CCA analysis shows the effects of environmental data on community structure in the Pannonian Lowlands ecoregion: (a) shows the distribution of sampling sites and environmental parameters; (b) shows the distribution of Chironomidae taxa with the highest correlated environmental parameters. The statistically significant variables are marked with a black arrow. The circles represent samples: 1—Rakitje, 2—Novo Čiče, 3—Jarun, 4—Koprivnica Šoderica, 5—Popovac, 6—Pakra, 7—Biljsko Lake, 8—Sakadaš Lake, 9—Jošava, 10—Lapovac, 11—Varaždin, 12—Čakovec, 13—Dubrava). Abbreviation of species: cladlepi—Cladotanytarsus lepidocalcar, cladvire—Cladopelma virescens, cricinte—Cricotopus intersectus, cricsylv—Cricotopus sylvestris, endoalbi—Endochironomus albipennis, glypimbe—Glyptotendipes imbecilis, glyppall—Glyptotendipes pallens, kieftend—Kiefferulus tendipediformis, nanodich—Nanocladius dichromus, paraacul—Parachironomus arcuatus, parainop—Paratanytarsus inopertus, polysord—Polypedilum sordens.
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Figure 6. The dbRDA plot shows environmental variables which had the strongest correlation with species composition. Abbreviations are as in Table 1.
Figure 6. The dbRDA plot shows environmental variables which had the strongest correlation with species composition. Abbreviations are as in Table 1.
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Figure 7. Principal component analysis (PCA) plot with the environmental variables (p < 0.05) with the highest correlation value. Abbreviations are as in Table 1.
Figure 7. Principal component analysis (PCA) plot with the environmental variables (p < 0.05) with the highest correlation value. Abbreviations are as in Table 1.
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Table 1. Study sites with geographical coordinates, altitude, surface area, and depth of man-made lakes. (ER 5—Dinaric Western Balkan: OP—Opsenica, RI—Ričice-Zeleno Lake, PB—Prološko Blato, LO—Lokve, VL—Vlačine, RA—Razovac, PR—Pranjčević, PE—Peruča, ST—Štikada, TR—Tribalj, SA—Sabljaci, LE—Lešće, BR—Brljan, GO—Golubić, GP—Gusić Polje; ER 11—Pannonian Lowland: VZ—Varaždin, CK—Čakovec, DU—Dubrava, RK—Rakitje, NC—Novo Čiče, JA—Jarun, KS—Koprivnica Šoderica, PP—Popovac, PA—Pakra, BL—Biljsko Lake, SL—Sakadaš Lake, JO—Jošava, LA—Lapovac).
Table 1. Study sites with geographical coordinates, altitude, surface area, and depth of man-made lakes. (ER 5—Dinaric Western Balkan: OP—Opsenica, RI—Ričice-Zeleno Lake, PB—Prološko Blato, LO—Lokve, VL—Vlačine, RA—Razovac, PR—Pranjčević, PE—Peruča, ST—Štikada, TR—Tribalj, SA—Sabljaci, LE—Lešće, BR—Brljan, GO—Golubić, GP—Gusić Polje; ER 11—Pannonian Lowland: VZ—Varaždin, CK—Čakovec, DU—Dubrava, RK—Rakitje, NC—Novo Čiče, JA—Jarun, KS—Koprivnica Šoderica, PP—Popovac, PA—Pakra, BL—Biljsko Lake, SL—Sakadaš Lake, JO—Jošava, LA—Lapovac).
EcoregionStudy SiteNEAltitude (m asl)Surface Area (km2)Depth Max (m)Depth Mean (m)
ER 5OP45.3674515.661645750.896.72.9
RI43.4967117.133423871.939.616
PB43.4746617.121612692.115.34
LO45.3685914.706187672.144.733.8
VL44.1567615.426841220.28104
RA45.2049515.7468390.657.55.8
PR43.5627316.719132840.65206.3
PE43.8219116.5531133020.093120.8
ST44.2923215.814085533.346.54.3
TR45.2287614.66736600.4142.7
SA45.2287815.226023201.76.23
LE45.3576915.304441821.4642.521
BR44.0089716.036841870.031810
GO44.0988816.221313070.1763
GP44.9450815.118664300.436.55.4
ER 11VZ46.3921216.163031912.858.75
CK46.3126316.3702116810.513.27
DU46.3248816.6015415016.613.48
RK45.7899715.8441120253
NC45.7117416.103371030.94015
JA45.781615.925211156.474
KS46.2360316.903691281.5208
PP45.637716.87405960.756.52
PA45.4380916.898711042.736.33
BL45.5915318.73839801.2553
SL45.6082818.80041790.1274
JO45.3228118.45246930.791.41
LA45.4802718.112971230.5115
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Ergović, V.; Čerba, D.; Vučković, N.; Mihaljević, Z. Chironomid Pupal Exuviae Technique in Ecological Research of Man-Made Water Bodies. Water 2024, 16, 2917. https://doi.org/10.3390/w16202917

AMA Style

Ergović V, Čerba D, Vučković N, Mihaljević Z. Chironomid Pupal Exuviae Technique in Ecological Research of Man-Made Water Bodies. Water. 2024; 16(20):2917. https://doi.org/10.3390/w16202917

Chicago/Turabian Style

Ergović, Viktorija, Dubravka Čerba, Natalija Vučković, and Zlatko Mihaljević. 2024. "Chironomid Pupal Exuviae Technique in Ecological Research of Man-Made Water Bodies" Water 16, no. 20: 2917. https://doi.org/10.3390/w16202917

APA Style

Ergović, V., Čerba, D., Vučković, N., & Mihaljević, Z. (2024). Chironomid Pupal Exuviae Technique in Ecological Research of Man-Made Water Bodies. Water, 16(20), 2917. https://doi.org/10.3390/w16202917

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