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1 July 2010 Fish community in the chronically polluted middle Elbe River
Pavel Jurajda, Michal Janáč, Zdenka Valová, Georg Streck
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The evaluation of resident fish communities is an important component of the ecological status assessment in aquatic habitats. Despite significant water quality improvement in the Czech Republic in the last decade, several important pollution sources in the Elbe River basin remain. The aim of the study was to evaluate fish community in a chronically polluted part of the channelized lowland Elbe River and its potential indicative capability.

The effluent from both industrial and municipal sewage treatment plant exhibited low pH, high conductivity and wide set of organic compounds (PAH, PCB, DDT etc.). Ecological characteristics of fish communities were obtained by boat electro fishing at selected sites in four inter-weir sections in July 2005 and 2006. Relatively high fish species richness (24 species) was observed in both seasons. Generalists (bleak, roach, chub) form the majority of the fish community in all four sections. There was no significant difference in fish species richness or density among study sections (river segments between weirs) even with a high level of measured organic compounds at the pollution inlet. Significant differences in fish species richness and density were registered among individual sites within study sections. Sites downstream the weirs had significantly higher species richness and density than the other two sites in the middle and upstream weirs. Fish community does not display any indicative remarks concerning water pollution, or in the case of mid-size river, sampling strategy was not efficient to recognize it. Channelization and regulation of the study stretch of the Elbe River seems to be the most important determinant of fish community structure.


Higher level responses at population and community levels to either single or multiple stressors have been well-defined for invertebrates but less well for fishes (Elliott 1994, Walker et al. 1996, Elliott & Hemingway 2002). Stress is defined in this context as the cumulative, quantifiable response to adverse environmental conditions or factors as the result of anthropogenic activities which results in a reduction of fitness to survive at any biological level of organization (cellular, individual, population or community). In addition, certain extreme stressors, such as a loss of habitat (McLusky et al. 1992) or overfishing (Svelle et al. 1997) could have an overarching effect over the lesser stressors, such as pollution and are difficult to detect and quantify.

In communities exposed to chronic pollutant stress, the density of tolerant species may increase, together with the development of resistance as organisms induce the ability to detoxify or sequester pollutants (physiological acclimation and/or genetic adaptation). If the stress remains, then a new equilibrium will develop. Ecosystems where the stress is then removed or reduced will recover through recruitment, recolonisation and/or immigration, although the recovery stages may be transient until a stable system is regained. The ability of any system to withstand and tolerate such changes may be regarded as „environmental homeostasis” (Whitfield & Elliott 2002).

An important component of assessing site-specific toxic hazards in aquatic habitats is to study the resident fish communities as fish represent different levels of the food chain, allow evaluation of longterm accumulation of xenobiotics since they are longlived, and they offer a broad spectrum of relatively well studied toxicological endpoints. The toxic hazards to fish can be assessed at different levels of biological complexity. Community responses are less evaluated especially in river system (Lawrence & Hemingway 2003).

The fish is one of the Biological Quality Elements (BQE) from the Water Framework Directive (WFD) and its function is the notion/assumption that responses to environmental stressors are reflected in fish health and their community composition and distribution (Karr 1981, EU 2000, Breine et al. 2007). The objective of this study was the ecological characterisation of fish communities in the mid-size river in chronically polluted stretch of the Elbe River. Although the Elbe River is one of the largest rivers in Europe, very limited information is available about the structure of fish communities in the main channel (IKSE-MKOL Project 1996, Fuksa 2002).

Material and Methods

Study area

Fish communities were studied in middle Elbe River sites with different suspected levels of chronic chemical pollution near Pardubice town. The sites were selected based on information and data collected within the project MODELKEY and long-term monitoring projects IKSE-MKOL Project (1996) and Project Elbe (Fuksa 2002).

The Elbe River has a total length of 1154 km with 370 km in the Czech Republic (CR). Total basin is 144055 km2, of which 51391 km2 is in CR. Average annual discharge in study area is 56 m3.s-1 (Vlček 1984). Most of the Elbe River is channelized and regulated with two reservoirs, 24 locks and 67 weirs. The stretches from German border upstream to Pardubice (river km 241) are modified and used for navigation.

Despite significant water quality improvement in the last decade, two important pollution sources for the investigated stretches of the Elbe River still persist: Spolana Neratovice and Pardubice industrial zone (e.g. Synthesia Pardubice) (Fuksa 2002). This study comprised a stretch of the Elbe River up- and downstream of the industrial zone of Pardubice. This part of the River Elbe was reported by several authors to be heavily contaminated, e.g. by chloroorganics, aromatic compounds as well as other compounds (Heinisch et al. 2007, Randák et al. 2008).

The study stretch was divided into four sections (downstream ordered) representing inter-weir sections (Table 1, Fig. 1).

Section 1 (Vysoká — Pardubice): partly regulated and unpolluted section (with respect to the Pardubice industrial zone), long riffle stretch, no backwater, 2 tributaries,

Section 2 (Pardubice — Srnojedy): regulated, unpolluted section (with respect to the Pardubice industrial zone), no riffle stretch, 2 backwaters, no tributary,

Section 3 (Srnojedy — Přelouč): regulated and directly polluted hotspot section (with respect to the Pardubice industrial zone), discharge of effluent about 1 m3.s-1, no riffle stretch, no backwaters, no tributary,

Section 4 (Přelouč — Týnec): partly regulated and polluted section (with respect to the Pardubice industrial zone), long riffle stretch, no backwaters, no tributary.

Fig. 1.

Schematic map of study sites. Four sections and 12 sampling sites (open rings) indicated in the Elbe River near Pardubice surveyed in years 2005 and 2006.


Because the different habitat character, three sites were sampled within each section: under weir — with relatively low depth (< 1 m) and stronger current; middle zone — with higher depth (average 2 m) and low current; and above weir — with relatively high depth (up to 6 m) and minimum current (Table 1). It was hypothesized, that the industrial area of Pardubice, with its main effluent in section 3, impaired the fish community. Therefore, the pollution by chemicals mentioned in literature was measured in section 1, serving as reference site, downstream of the effluent and directly in the effluent. Further analysis of the effluent water was carried out to enhance the knowledge about substances released by the outlet.

Chemical characterisation — Elbe River

Semipermeable Membrane Devices (SPMD) were used to collect non-polar compounds (polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), chloropesticides (p,p'-DDT, p,p'-DDE, p,p'-DDD), chlorobenzenes (CB) in the river. These lipophilic compounds were reported to be present in elevated concentrations downstream of Pardubice and originate probably from contamination of factory grounds in the industrial zone (Heinisch et al. 2007). SPMD were first introduced by Huckins et al. (1990) as passive samplers for non-polar compounds. SPMD consist of a neutral lipid (triolein) encapsulated in a layflat lowdensity polyethylene tubing. Compounds in the river water diffuse through the polyethylene membrane and are absorbed by the triolein. Time averaged water concentrations can then be calculated by using uptake rates given in the literature (e.g. Huckins et al. 1990). Further details about the passive sampler itself, principles of sampling procedures and uptake rates can be found elsewhere (Huckins et al. 1990, Luellen & Shea 2002). Three SPMDs were deployed each year (2005 and 2006) for four weeks prior to the fish sampling in section 1, directly into the plume of the effluent from the chemical plant (section 3), and further downstream in section 3. After retrieving the membranes from the river they were cleaned and extracted (Streck et al. 2008). Extracts were purified with gel permeation chromatography (US EPA 1994). Analyses were carried out in the Single Ion Monitoring (SIM) mode with an HP6890 gas chromatograph coupled to an HP5973N mass spectrometer (both Agilent, Sunnyvale, USA).

Table 1.

List of selected sites on the Elbe River surveyed for fish communities in years 2005 and 2006.


Chemical characterisation — effluent

Water released via the effluent form the industrial area of Pardubice (section 3) showed a deep red colour and an aromatic smell. It appeared likely, that at this site other compounds than the reported classical contaminants which were sampled with SPMDs are entering the Elbe River. Therefore, water samples were taken directly from the effluent using brown glass bottles. In order to get information on compounds that are actually released into the Elbe River, a simple screening method was employed. This method consisted of a liquid-liquid extraction of water from the effluent with dichloromethane and a subsequent analysis of the concentrated extract by GC-MS in Scan mode. Substances were identified tentatively using a library of mass spectra (NIST 2005). If standards were available, the identity of the compounds was checked using retention time and mass spectra, and the compounds were quantified.

A simplified scheme for the calculation of the ratio of Predicted No-Effect Concentrations (PNEC) to Predicted Environmental Concentrations (PEC) was used in order to estimate whether the identified and quantified compounds may pose a risk for the fish community. For the River Elbe, PECs were simply calculated by taking dilution of the effluent entering the river into account. Calculations were done using the discharge of the effluent estimated in the field (0.5 m3 s-1) and the low-flow discharge of the River Elbe. The latter value was derived from the average discharge, which is 56.3 m3 s-1 in the middle of section 3, by dividing it by three (EC 2003). Binding to particles and subsequent sedimentation was neglected in order to achieve a conservative estimation of PEC-values. PNECs were calculated using the lowest LC50-values retrieved from the ECOTOX database (US EPA 2008) for the fish species Pimephales promelas or other species, as available, by dividing them by an assessment factor of 1000 (EC 2003).

Fish sampling

Ecological characteristics of fish communities were obtained by classical ichthyologic methods, in accordance with the Water Framework Directive (Fame Consortium 2004). The adult fish (1 year and older) were sampled by boat electro-fishing (type EL63GI, DC 4.5 kW, 12A, 350V) upstream directed along both banks. The caught fish were determined into species and then released back into water. The length of each sampled river stretch (in average 1900 m) was noted and numbers of caught individuals recalculated into density presented as a catch per unit effort (CPUE — individuals per 100 m sampled). The width and depth of the Elbe River channel (in average 40 m and 2 m respectively) in the study sites do not allow the quantitative survey at all. Sampling was undertaken during low flow condition (mean 20 m3.s-1) in 26-29 July 2005 and 17-21 July 2006 in the same sites.

Data analysis

Basic ecological parameters, like species richness, relative community structure (dominance in %), density (CPUE) in adult fish community (1+ and older) were analyzed for particular sampling site and cumulated for each section. Diversity indices (Shannon H′, Simpson) and similarity indices (Jaccard, Renkonen′s Percentage similarity) were calculated (Begon et al. 1990). Ecological and reproductive guilds were analysed (Balon 1975, Schiemer & Waidbacher 1992).

A three-way analysis of variance (ANOVA) was used to determine whether sampled section, site, and year influenced number of fish (log-transformed in order to comply with requirements of ANOVA), number of species and H′.


Species richness and density

A total of 2951 caught adult fish (1+ and older), belonging to 22 fish species, were recorded at twelve river sites (four sections sampled at three river sites each) in the Elbe River in 2005 (Table 2). In the year 2006, a total of 949 adult fish were caught, belonging to 23 species (Table 2). No significant differences in species richness were found between the years nor among sampled sections (ANOVA, both p > 0.05; Fig. 2), though it differed significantly between the sites (ANOVA, p < 0.05), with more species occurring in site 1 (downstream the weirs) than in other two sites (Sheffé post hoc test, p both < 0.05) (Fig. 3). Dominant species were the generalists bleak (Alburnus alburnus) and roach (Rutilus rutilus). These species were the most abundant in all sections studied. Chub (Leuciscus cephalus) was dominant in all sections except section 2. White bream (Abramis bjoerkna) was dominant in section 2 (Table 2).

No significant difference in fish density was found among the studied sections (ANOVA, p < 0.05; Fig. 2). ANOVA found significant differences in fish density (log-transformed) between the years, and among the sites (both p < 0.05), with densities in site 1 (downstream the weirs) being significantly higher than in other two sites (Sheffé post hoc test, p both < 0.05) (Fig. 2 and 3).

Fig. 2.

Species richness (above) and relative density (below) of fish communities in the particular sections on the Elbe River in years 2005 and 2006.


Fig. 3.

Species richness (above) and relative density (below) of fish communities in the particular sites of each section on the Elbe River in years 2005 and 2006.


Diversity indices and ecological guilds

Diversity indices were rather similar in the two years studied. No decrease of diversity was observed in hot spot section 3 (Table 2). Shannon′s index of diversity did not differ among the sections, nor between the years, (ANOVA, both p > 0.05), though it differed among the sites (ANOVA, p < 0.05), with site 1 providing higher values of H′ than site 2 (Scheffé post hoc test, p < 0.05; Table 2).

In both years, the dominant fish species (bleak, roach, white bream) represent the eurytopic guild; they show no preference for running or still waters. Chub belongs to the rheophilic guild, requiring running water at least in some life stages. Higher density of other rheophilic specialists like barbel (Barbus barbus), vimba (Vimba vimba), dace (Leuciscus leuciscus) or gudgeon (Gobio gobio) is limited by the inconvenient habitat of the channelized river. Their occurrence was higher only in section 1 (Table 2). The occurrence of limnophilic species, preferring still water habitat with aquatic vegetation for reproduction is supported by the existence of two large backwaters in section 2. Generalist sensu ecological guild could be considered also as generalist sensu reproductive guild. Except lithophilic chub, all other dominant species belong to the phyto-lithophilic guilds, with low requirements for spawning substrate.

Table 2.

Dominance of adult fish (1 year and older) in four sections (1–4) of the Elbe River in year 2005 and 2006 (in %). (*— species under the stocking program of Czech Anglers union).


Similarity indices

Fish community structure based on species richness was very similar in 2005 and 2006 (total similarity, Jaccard index = 88%) (Table 3). Higher similarity was found in relative composition of fish assemblages between particular sections (Renkonen′s PS index = 93%), due to high density of dominant species and low density of rare species. In 2005, all the sections were relatively highly similar. The highest similarity was found between the section 3 and 4 (Ja 68%, PS 78%). In 2006, the differences between sections were more obvious, with the highest difference found between sections 2 and 3. Higher interannual differences were found in sections 3 and 4 than in sections 1 and 2 (Table 3).

Chemical characterisation — basic parameters

Conductivity, pH, oxygen and temperature data on the Elbe River and the effluent of the chemical plant are given in Table 4. The red coloured effluent, which released an aromatic smell, exhibited a remarkably low pH-value and a high conductivity.

Table 3.

Similarity indices of fish communities in particular sections of the Elbe River in 2005 and 2006.


Table 4.

Basic characterization of the River Elbe in section 3 up- and downstream of the effluent from the chemical plant and of the effluent itself.


Chemical characterisation — SPMDs

For PAHs, only small differences in water concentrations between the sections could be observed (Table 5). Concentrations were below the threshold values defined as environmental quality standards (EQS) in the context of the Water Framework directive. This is also true for chlorobenzenes as well as for DDT and metabolites. No EQS-value exists for PCBs. However, the effluent from the industrial area proved to be a source of chlorobenzenes and PCBs of lower weight, and increased the concentrations of the Elbe River notably (Table 5). While p,p'-DDD and p,p'-DDE were in the same magnitude at both sections (1 and 3), the parent compound p,p'-DDT showed a remarkable increase from below detection limit to 1.2 ng/L in 2005 and even 3.3 ng/L 2006 at the last site (section 3 downstream), indicating a source of fresh DDT in the vicinity of this site.

Chemical characterisation — screening

The screening analysis of the effluent from the industrial area revealed the presence of a vast number of compounds (Table 6). Especially, the waste water contained large amounts of compounds used in the production of explosives, which are produced in Pardubice by Synthesia Semtin a.s.. Toxicity data for fish — LC50-values for Pimephales promelas if available — and PECEffluent/PNEC-values have been included in the table in order to allow a rough evaluation of the findings. LC50-values are only available for a subset of the identified compounds. PECEffluent/PNEC-values were calculated from the concentrations quantified in the effluent, divided by an assessment factor of 1000 and the lowest LC50-values available. Two of the compounds (trinitrotoluene and 1-Chloro-2,4-dinitro-benzene) showed values above one. Furthermore, several other compounds display values close but below one. These results demonstrate that the effluent itself has to be considered as toxic. In order to evaluate the relevance of the concentrations for the fish community in the Elbe River, the dilution of the effluent by the river water has to be taken into account. All PECElbe/PNEC-ratios for the river itself were below one. Values calculated for trinitrotoluene and 1-Chloro-2,4-dinitro-benzene were 0.28 and 0.06, respectively. All in all, it has to be stated that the effluent clearly increases toxicity of the River Elbe, but due to dilution the chemicals do not pose a risk to the fish community. However, these conclusions are based on a very simple risk assessment. Our reflections do not consider mixture toxicity neither that only a subset of compounds released by the effluent could be quantified. Furthermore, they are solely based on data on acute toxicity (Table 6).

Table 5.

Concentrations of chlorobenzenes, PCBs, chloropesticides and PAHs in the River Elbe (in pg/L).



During the two-year study, a total of 24 fish species were registered in the four studied river sections of the Elbe River near Pardubice. Even the Elbe River is one of the most important rivers in the Czech Republic; limited information about the fish community is available only from the large scale monitoring projects IKSE-MKOL Project (1996) and some years of Project Elbe (Fuksa 2002). Fifteen fish species in the two sites (our number 1.II and 3.II) were documented in 1999, with similar dominance of roach, chub and gudgeon (Fuksa 2002). Comparing with our study, bleak was less abundant in survey in 1999. Within the large scale survey of longitudinal profile of the whole Elbe River in years 1991-93 (IKSE-MKOL Project 1996), 24 species were registered in 7 sites, corresponding to our study stretch of the Elbe River. However, only presence-absence data were available in that study (IKSE-MKOL Project 1996). Eleven of the 24 species registered within the study are stocked by the Anglers union. Additionally, five species that were stocked by the Anglers union (Danubian salmon Hucho hucho, grass carp Ctenopharyngodon idella, rainbow trout Oncorhynchus mykiss, brook trout Salvelinus fontinalis, zander Sander lucioperca) were not documented in the field. Nevertheless, including all stocking information increased the total fish diversity to 28 species.

Table 6.

Identified compounds in industrial waste water entering the Elbe River in section 3. The LC50-values have been included for fish species as available. PECElbe/PNEC was calculated from effluent concentration data, dilution by river water and from lowest LC50-values taking an assessment factor of 1000 into account. PECEffluent/PNEC was calculated in the same way without considering a dilution factor.


When comparing species richness and community composition, it is necessary to take into account the lower efficiency of potential sampling methods for channelized medium-size rivers, like the investigated part of the Elbe River. The differences can be influenced by the sampling method as well as by spatiotemporal distribution of fishes within the river channel. Nevertheless, one can gain a rough picture of fish assemblage condition of the studied river stretch from obtained results and the same sampling effort allows the comparison between the sections under study.

Present fish community is not well-balanced. Dominant species are classified as generalists, with wide ecological valence. Roach, bleak and white bream (more common in 2006) are typical eurytopic species (Schiemer & Waidbacher 1992) living both in running and standing water. Chub and gudgeon are rheophilic species requiring running water for particular life stages; nevertheless especially chub is common even in sections without riffle zone or tributaries (section 2 and 3) (Baruš & Oliva 1995). Perch, that is indicated as a fish species typical for channelized rivers and canals (Wolter & Vilcinskas 1997) was not as abundant as expected, according to the river character. Many other species with more specific habitat requirement were registered in low density only (Table 2).

The trend of decreasing CPUE in longitudinal profile of studied sections was apparent, though not significant, in both years, but there were significantly lower CPUE values in all sections in the year 2006 than in the year 2005 (Fig. 2). Decreasing density in longitudinal profile in both years could be affected by the decreasing habitat complexity from section 1 downstream to section 4 (see Study area). The reduction of the CPUE to a half from 2005 to 2006 is difficult to explain. A strong spring flood in 2006 could be a reason. Nevertheless, the composition of the studied river stretch remained relatively unchanged (Ja 88%, PS 93%). Significantly higher fish diversity and density among the sites were documented in sites below the weirs, with diversified habitats and more oxygenated water (IKSE-MKOL Project 1996, Slavík & Bartoš 2001).

There was no straight relationship with the presence of pollutants and ecological descriptors of adult fish community. No significant differences were found between four river sections neither in species richness, CPUE nor in diversity indices. Also species composition in all sections was similar. The elevated water concentrations of PCBs, CBs and DDT in section 3 compared to the upstream sections did not impair the fish community, since concentrations are still below threshold values, e.g. EQS-values. These findings agree well with a recently published survey of body burden and biomarkers in chub in the same stretch of the Elbe River (Randák et al. 2008), which demonstrated an increase of PCBs, HCBs and DDT in chub downstream of the effluent, but couldn't find differences in biomarker response (e.g. ethoxyresorufin-O-deethylase (EROD)) between sites upstream and downstream of section 3.

A lack of adverse effects on fish community was also observed when sampling nearby the outlet from the industrial area. The chemical analysis revealed that waste water released by the effluent contained considerable concentrations of toxic substances, even if PECElbe/PNEC-values calculated from these concentrations and taking dilution by the Elbe River into account indicated no risk to the fish community (Table 6). However, this conclusion might be misleading, since only a small subset of compounds could be identified and quantified, and only acute toxicity was taken into account. Therefore, other explanations of the findings cannot be omitted. E.g., another reason could be a limited efficiency of sampling methods in mid-size channelized rivers to detect fish community differences (Casselman et al. 1990). Furthermore, the size of the effluent's discharge compared to that of the Elbe River should be taken into account as well as that the plume does not mix instantaneously with the river water, leaving space for fish to avoid chemicals released from the effluent. During minimal discharge, water from the effluent will be diluted at least by a factor of 20. Taken altogether, an influence of waste water on the fish community seems to be unlikely.

We therefore conclude that in this study fish community was not a good biological indicator of chemical pollution possible due to insignificant adverse effect of chemicals in concordance with the size of a river (discharge). The main influential factor on the fish community in this study site was most likely geomorphologic and hydrological river character. Fish community presented weak adverse changes in CPUE eight months later in the case of catastrophic poisoning by cyanide in January 2006 in the stretch near the town of Kolín (about 30 km downstream of study stretch) (Křížek et al. 2007).

Fish community is a widely used BQE (WFD), but its indicative value was rarely evaluated, especially in case of chemical pollution (Lawrence & Hemingway 2003). Based on our results in chronically polluted river, fish community is a biological indicator of general ecological river status, including geomorphology of channel, hydrology and water quality. In the case of water quality it seems to be a good indicator only of significantly strong adverse effect accordingly with the river size (Libosvárský et al. 1967). In the mid sized and large rivers, indicative value of fishes in community level is lower owing to insufficient representative sampling efficiency and dilution effect of river.


We thank the Elbe River Authority for the cooperation and the Czech Anglers union in Hradec Králové for fish survey permission in their regions. We are indebted to V. Horák, M. Bialek, J. Cimický, J. Pohl, M. Polačik, J. Huml, M. Dušková, M. Ondračková, M. Wenger for their help in field, two anonymous referee for improving comments and S. White for English and improving of the paper. The present study was funded by 6thFP EU (MODELKEY (511237 GOCE)) and the project Center of Excellence Ministry of Education, Youths and Sports LC522.



Balon E.K. 1975: Reproductive guilds of fishes: a proposal and definition. J. Fish. Res. Board Can. 32: 821–864. Google Scholar


Baruš V. & Oliva O. 1995: [Fauna of CR. Lampreys and fishes I and II]. Academia Praha, Czech Republic . (in Czech with English summary)  Google Scholar


Begon M., Harper J.L. & Townsend C.R. 1990: Ecology. Individuals, populations and communities. Blackwell Science , Oxford, UKGoogle Scholar


Breine J.J., Maes J., Quataert P., Van den Bergh E., Simoens I., Van Thuyne G. & Belpaire C. 2007: A fishbased assessment tool for the ecological quality of the brackish Schelde estuary in Flanders (Belgium). Hydrobiologia 575: 141–159. Google Scholar


Casselman J.M., Penczak T., Carl L., Mann R.H.K., Holčík J. & Woitowich W.A. 1990: An evaluation of fish sampling methodologies for large river systems. Pol. Arch. Hydrobiol. 37: 521–551. Google Scholar


Elliott M. 1994: The analysis of macrobenthic community data. Marine Pollution Bulletin 28: 62–64. Google Scholar


Elliott M. & Hemingway K.L. 2002: Fishes in estuaries. Blackwell Science , Oxford, UKGoogle Scholar


EC (European Commission) 2003: Technical Guidance Document on Risk Assessment (TGD) Part II, European Commission Joint Research Center. Institute for Health and Consumer ProtectionGoogle Scholar


EC (European Commission) 2004: Review report for the active substance benalaxyl. Report of the European Commission. Health & Consumer Protection Directorate General, SANCO/4351/2000Google Scholar


EU (European Union) 2000: Directive 2000/60/EC of the European Parliament and of the Council establishing a framework for the Community action in the field of water policy. The European Parliament and Council, L327/1, 2000Google Scholar


Fame Consortium 2004: Manual for the application of the European Fish Index — EFI. A fish-based method to assess the ecological status of European rivers in support of the Water Framework Directive. Version 1.1, January 2005Google Scholar


Fuksa J. 2002: Biomonitoring of the Czech Elbe — results from years 1993-1996-1999. Research for practices No. 46, VÚV TGM Praha, Czech Republic . (in Czech)  Google Scholar


Heinisch E., Kettrup A., Bergheim W. & Wenzel S. 2007: Persistent chlorinated hydrocarbons (PCHC), source-oriented monitoring in aquatic media — 6. Strikingly high contaminated sites. Fresenius Env. Bull. 15: 1344–1362. Google Scholar


Huckins J.N., Tubergen M.W. & Manuweera G.K. 1990: Semipermeable-membrane devices containing model lipid — a new approach to monitoring the bioavailability of lipophilic contaminants and estimating their bioconcentration potential. Chemosphere 20: 533–552. Google Scholar


IKSE-MKOL Project 1996: Fishes of Elbe. International commission for Elbe protection. Magdeburg, Germany . (in Czech) Google Scholar


Karr J.R. 1981: Assessment of biotic integrity using fish communities. Fisheries 6: 21–27. Google Scholar


Křížek J., Horáček P. & Kava T. 2007: Ichthyocenosis of the Elbe downstream from Kolín after the cyanide poisoning in 2006. Proc. 10th Czech conference of Ichthyology, Praha, Czech Republic : 85–91. Google Scholar


Libosvárský J., Lelek A. & Peňáz M. 1967: Movement and mortality of fish in two polluted brooks. Acta sc. nat. Brno 1: 1– 28. Google Scholar


Lawrence A. & Hemingway K. 2003: Effects of pollution on fish: Molecular effects and population responses. Blackwell Science , Oxford, UKGoogle Scholar


Luellen D.R. & Shea D. 2002: Calibration and field verification of semipermeable membrane devices for measuring polycyclic aromatic hydrocarbons in water. Env. Sci. Technol. 36: 1791–1797. Google Scholar


McLusky D.S., Bryant D.M. & Elliott M. 1992: The impact of land claim on macrobenthos, fish and shorebirds on the forth estuary, Eastern Scotland. Aquat. Conserv. Marine Freshwater Ecosyst. 2: 211–222. Google Scholar


Nationial Institute of Standards (NIST) 2005: NIST/EPA/NIH Mass Spectral Library (NIST 2005). US Department of Commerce , Gaithersburg, USAGoogle Scholar


Randák T., Žlábek V., Pulkrabová J., Kolářová J., Kroupová H., Sirotka Z., Velíšek J., Svobodová Z. & Hajšlová J. 2008: Effects of pollution on chub in the River Elbe, Czech Republic. Ecotox. Environ. Safety. , Google Scholar


Schiemer F. & Waidbacher H. 1992: Strategies for conservation of a Danubian fish fauna. In: Boon P.J. et al. (eds.), River conservation and management. John Wiley & Sons Ltd. , UK : 363–382. Google Scholar


Slavík O. & Bartoš L. 2001: Spatial distribution and temperature variance of fish communities in the channelized and regulated Vltava River (Central Europe). Env. Biol. Fishes 61: 47–55 Google Scholar


Streck G., Schulze T. & Brack W. 2008: Accelerated membrane-assisted clean-up as a tool for the clean-up of extracts from biological tissues. J. Chromatography A 1196–1197: 33–40. Google Scholar


Svelle M., Aarefjord H., Heir H.T. & Øverland S. 1997: Assessment report on fisheries and fisheries related species and habitat issues. Intermediate Ministerial Meeting on the Integration of Fisheries and Environmental Issues, March 13-14 1997, Bergen, Norway. Ministry of Environment , NorwayGoogle Scholar


US EPA (US Environmental Protection Agency) 1994: Method 3640A. Gel-Permeation Cleanup. Washington, DC, USAGoogle Scholar


US EPA (US Environmental Protection Agency) 2008: ECOTOX database. Last access on August 14 2008,  Google Scholar


Vlček V. 1984: Rivers and reservoirs. Geographical lexicon of CSR. Academia Praha, Czech Republic . (in Czech)  Google Scholar


Walker C.H., Hopkin S.P., Sibly R.M. & Peakall D.B. 1996: Principals of ecotoxicology. Taylor & Francis Ltd. , London, UKGoogle Scholar


Whitfield A.K. & Elliott M. 2002: Fishes as indicators of environmental and ecological changes within estuaries — a review of progress and some suggestions for the future. J. Fish Biol. 61 (Suppl. A): 229–250. Google Scholar


Wolter C. & Vilcinskas A. 1997: Perch (Perca fluviatilis) as an indicator species for structural degradation in regulated rivers and canals in the lowlands of Germany. Ecol. Freshwater Fish 6: 174–181. Google Scholar
Pavel Jurajda, Michal Janáč, Zdenka Valová, and Georg Streck "Fish community in the chronically polluted middle Elbe River," Folia Zoologica 59(2), 157-168, (1 July 2010).
Received: 16 February 2009; Accepted: 1 October 2009; Published: 1 July 2010

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