Zooplankton communities are an important component of the pelagic food web, but they are absent on the list of biotic elements to be considered in the assessment of ecological status in Annex V of the Water Framework Directive (2000/60/EC) (Caroni & Irvine 2010). The Directive 2000/60/EC requires the quality of waters to be determined on the basis of biological aspects, with other parameters complementing and supporting such an assessment. The communities of organisms that may be used for this purpose include phytoplankton, macrophytes, phytobenthos, benthos and fish, and these should be supported by a set of chemical and hydromorphological quality data (Annex V, 2000/60/EC) (Jeppesen et al. 2011). The Water Framework Directive does not specify zooplankton as an indicator applicable to water quality assessment, an omission that has attracted trenchant criticism (Moss 2008; Nõges et al. 2009; Jeppesen et al. 2011).
Zooplankton, as an intermediate trophic level in the pelagic food chain of lakes, is important in the assessment of their trophic status. These microscopic organisms are characterized by short life cycles and a relatively high metabolic rate, and such organisms, particularly rotifers and crustaceans, react quickly to changes in environmental conditions (Shurin et al. 2010). Hence, the species composition of rotifers and crustaceans as well as their abundance may be used as biological indicators that reflect changes in water quality. Parameters of the Rotifera community not only indicate the level of water pollution, but also serve to determine general tendencies in the changes of environmental conditions over time (Duggan et al. 2001; Ejsmont-Karabin 2012).
The value of zooplankton as an indicator of ecological conditions results from their position in the food web, between the top-down regulators (fish) and bottom-up factors (phytoplankton). They can thus provide information about the relative importance of the top-down and bottom-up control and their impact on water clarity (Jeppesen et al. 2011).
Danish authors have suggested that zooplankton can be used as an indicator of changes in trophic dynamics and the ecological state of lakes related to changes in nutrient loading and climate (Jeppesen et al. 2000; 2005; 2009; Søndergaard et al. 2005). According to Xu et al. (2001), a set of ecological indicators including structural, functional, and system-level aspects was proposed for the lake ecosystem health assessment, in accordance with the structural, functional, and system-level responses of lake ecosystems to chemical stresses. These indicators include acidification, eutrophication, as well as copper, oil and pesticide contamination. In many countries, zooplankton has been studied as part of lake monitoring (Mäemets 1983; Berzins & Pejler 1989; Matveeva 1991; Karabin 1985; Andronikova 1996; Ejsmont-Karabin 2012; Ejsmont-Karabin, Karabin 2013; Haberman & Haldna 2014), and as part of long-term monitoring of dam reservoirs (Fleituch & Pociecha 2000; Pociecha 2016). In dam reservoirs, zooplankton is rarely examined to determine the trophic indices of these water bodies. However, these artificial reservoirs may be considered lake areas, as there are characterized by environmental conditions similar to those found in natural lakes. For this reason, the zooplankton species composition of dam reservoirs could be used to assess the trophic status.
The objective of this paper was to analyze the usefulness of zooplankton indices based on two groups of zooplankton taxa, Rotifera and Crustacea, and to determine the trophic status of 10 different types of dam reservoir ecosystems, using formulas provided by Ejsmont-Karabin (2013).
In this paper, we demonstrate that zooplankton could be a useful indicator of the structure and function of dam reservoir ecosystems and their ecological status.
Zooplankton samples were collected in 10 dam reservoirs located in five physico-geographic regions of Poland (according to Kondracki 2002) (Fig. 1). All reservoirs differed from each other in the following characteristics: depth, area, catchment and function (Table 1). In order to compare the dam reservoirs in terms of physicochemical parameters, four groups of reservoirs were distinguished: a) reservoirs with a high concentration of PO4 3− in the water (regions: I, II and III); b) reservoirs with high concentrations of Cl−in the water (regions: I, III and IV); c) reservoirs with a high concentration of NO3 − (regions: IV and V); d) reservoirs with a high visibility of the Secchi disc and low conductivity (region V) (Table 2).
Characteristics of the studied dam reservoirs in Poland (nd – no data)
Name of dam reservoir
Łapinskie Nowe Lake
Mylof Dam Reservoir
Koronowskie Lake
Zygmunt August Lake
Siemiatyckie Zalewy Reservoir
Próba Dam Reservoir
Wióry Dam Reservoir
Chańcza Dam Reservoir
Leśniańskie Lake
Lubachowski Dam Reservoir
Location
Kolbudy
Zapora
Koronowo
Czechowizna
Siemiatycze
Próba
Pawłów, Knurów
Chańcza
Leśna
Lubachów
Coordinates
54°17′25″N 18°26′47″E
53°47′38″N 17°40′32″E
53°32′34″N 17°58′01″E
53°27′36″N 22°53′39″E
52°26′12″N 22°52′10″E
51°30′41″N 18°39′24″E
50°56′48″N 21°10′12″E
50°38′40″N 21°03′18″E
51°01′52″N 15°18′10″E
50°45′02″N 16°25′34″E
Year of creation
1925
1848
1960
1559
70’s XX age
2001
1980
1984
1905
1917
River
Radunia
Brda
Brda
Nereśl
Kamionka
Żeglina
Świślina
Czarna Staszowska
Kwisa
Bystrzyca
Area
0.35 km 2
10.5 km 2
13.5 km 2
4.85 km 2
0.33 km 2
0.21 km 2
4. 15 km 2
4.7 km 2
1.4 km 2
0.51 km 2
Capacity
2.5 M m3
16.2 M m3
80. 6 M m3
no data
0. 59 M m3
no data
35 M m3
20.59 M m3
15 M m3
8 M m3
Max depth
15.4 m
12 m
21.2 m
3.5 m
5.1 m
4 m
10 m
11 m
12 m
36 m
Catchment
forest
forest
agroforestry
agriculture
agroforestry
forest
agriculture
forest
forest
forest
Function
retention, energy, fishing
retention, energy, fishing
retention, energy, fishing, recreation
fish farming
retention, fishing, recreation
retention, fishing, recreation
retention, energy, fishing, recreation
retention, energy, fishing, recreation
retention, energy, fishing, recreation
retention, energy, fishing, recreation
Retention time (in days)
nd
12.5
38
nd
nd
nd
nd
218
37.8
54.8
Selected physicochemical parameters of water in the studied dam reservoirs (after Pociecha & Bielańska-Grajner 2015) water temperature (WT), Secchi disk visibility (SD), oxygen concentration (DO), conductivity (EC)
Parameters
Reservoirs (according to order in Fig. 1)
1
2
3
4
5
6
7
8
9
10
SD
m
1.4
3.4
2.7
0.3
1.2
0.8
1.3
1.0
1.6
2.3
WT
°C
12.6
14.8
14.6
19.2
19.2
21.3
21.7
22.4
16.7
16.1
EC
μS cm−1
372
274
326
335
359
376
402
254
135
246
pH
7.7
7.6
7.5
7.6
8.1
8.5
8.0
7.7
5.6
7.8
DO
mg l−1
11.2
8.5
5.9
3.1
14.8
13.1
8.8
14.1
8.2
6.6
No3 −
3.1
0.5
0.5
0.08
0.04
0.03
0.21
0.1
2.05
2.4
po4 3−
0.4
0.3
0.5
0.01
0.03
0.01
0.02
0.02
0.07
0.25
NH4 +
0.04
0.1
0.2
0.03
0.1
0.02
0.28
0.1
0.1
0.06
Cl-
17.3
10.2
12.7
11.9
12.8
31.2
26.7
12.4
8.1
17.6
Mg2+
8.0
4.9
6.8
11.75
10.2
10.2
16.8
6.9
2.65
11.1
Ca2+
62.05
48.9
56.75
55.7
58.1
53.0
45.7
43.6
12.9
28.3
Samples were collected from the central part of the reservoirs in August or September 2012. They were filtered through a plankton net (mesh size of 30 μm). In order to obtain one sample of zooplankton, 10 l of water was filtered, using a 5 l sampler.
All zooplankton samples were examined under a microscope in 0.5 ml chambers, both live and after treatment with 4% fixative solution of formaldehyde. The identification of zooplankton was performed with the use of a light microscope (Nikon H550L) at 40–400× magnification with a Nikon camera and NIS Elements computer software for image analysis. The taxonomical identification of zooplankton was made according to the identification keys (Flössner 2000; Ejsmont-Karabin et al. 2004; Rybak & Błędzki 2010).
Samples from dam reservoirs should be collected in the lake zone/area, and if such a zone cannot be determined, they should be collected from the deepest part of a reservoir, during summer stagnation when the water level does not fluctuate, based on one-time sampling. The thus defined constraints of sampling ensure that the conditions in dams are most similar to those prevailing in lakes.
In order to determine the trophic state of dam reservoirs, indices were calculated on the basis of species density and structure of Rotifera and Crustacea (Table 3). The advantage of the method proposed by Ejsmont-Karabin (2013) is that a single sample is sufficient during summer stagnation. These indices were based on research conducted in lakes.
Numerical trophic state indices for dam reservoirs, irrespective of their trophic type (TSIRot) and (TSICR); the indices use species composition and density of Rotifera and Crustacea (according to Ejsmont-Karabin 2013)
No.
Indices
Regression coefficient
Formulas
1
Number of rotifers (N, ind. l−1)
R2 = 0.60
WSTRot1 = 5.38ln(N) + 19.28
2
Total biomass (B, mg w.w. l−1)
R2 =0.47
WSTRot2 = 5.63ln(B) + 64.47
3
Percentage of bacterivores in the total number (BAC, %)
R2 = 0.34
WSTRot3= 0.23BAC + 44.30
4
Percentage of tecta in the population of
R2 = 0.54
WSTRot4 =0.187TECT + 50.38
5
Ratio of biomass to the number (B:N, mg w.w. l−1: ind. l−1)
R2= 0.50
WSTROt5 = 3.85 (B:N)-0.318
6
Percentage of species indicative of high trophy in the indicative group (IHT, %)
R2= 0.67
WSTRot6 = 0.203 IHT + 40.0
7
Number of Crustacea (N, ind. l−1)
R2= 0.32
WSTCR1 = 25.5N 0.142
8
Biomass of Cyclopoida (B, mg w.w. l−1)
R2= 0.35
WSTCR2 = 57.6B 0.081
9
Percentage of cyclopoid biomass in total biomass of Crustacea (CB,%)
R2= 0.30
WSTCR3 = 40.9CB 0.097
10
Ratio of cyclopoid biomass to Cladocera biomass (CY/CL)
R2= 0.37
WSTCR4= 58.3(CY/CL) 0.071
11
Percentage of species indicative of high trophy in the indicative group (IHT,%)
R2= 0.30
WSTCR5 = 43.8e0.004(IHT)
The trophic state of dam reservoirs was calculated on the basis of the density and species structure of Rotifera and Crustacea communities as proposed by Ejsmont-Karabin 2013 (Table 4).
The trophic state of dam reservoirs corresponding to the value of indices calculated on the basis of density and species structure of Rotifera and Crustacea (after Ejsmont-Karabin 2013)
Zooplankton value of trophic state indices
Trophic state
Below 35
Oligotrophic
From 35 to 45
Mesotrophic
From 45 to 50
Low meso-eutrophic
From 50 to 55
High meso-eutrophic
From 55 to 60
Low eutrophic
From 60 to 65
High eutrophic
Above 65
Polytrophic
Formulas for the trophic state indices based on the structure and density of the zooplankton community were developed using regression equations according to trophic state indices described by Carlson (1977) and the results collected in 74 poly- and dimictic lakes (Ejsmont-Karabin 2012; Ejsmont-Karabin & Karabin 2013).
The zooplankton in the studied dam reservoirs showed significant differences, both in the qualitative and quantitative composition as well as in the density of particular groups of zooplankton. The largest number of zooplankton taxa was found in Lake Koronowskie and the lowest number in Lubachowski Dam Reservoir (Fig. 2). A small number of zooplankton taxa was also observed in Zygmunt August Lake, whose characteristics resemble a breeding pond rather than a typical dam reservoir.
The highest densities of rotifers and crustaceans were observed in Zygmunt August Lake and Próba Dam Reservoir (Fig. 3). The lowest densities of both zooplankton communities were observed in Łapińskie Nowe Lake and Mylof Dam Reservoir (Fig. 3). A very low density of rotifers was also found in two submontane dam reservoirs: Lake Leśniański and Lubachowski Dam Reservoir.
In the most eutrophic dam reservoirs, the dominant species in the zooplankton community were
The dominant zooplankton species were represented by 13 rotifers, 11 cladocerans and 3 copepods. Most species were characteristic of meso- to eutrophic waters. Species characteristic of eutrophic waters, such as
Dominant species of zooplankton (%) in the studied dam reservoirs in 2012
Dominant species
Reservoirs (according to the order in Fig. 1)
1
2
3
4
5
6
7
8
9
10
Rotfera
17
30
12
43
27
41
38
57
14
45
33
24
28
10
15
17
16
22
16
40
13
50
10
16
Cladocera
15
61
76
18
53
73
16
13
10
15
30
25
12
13
26
15
19
10
36
25
18
46
19
50
11
38
15
Copepoda
13
10
17
The indices calculated for the dam reservoirs based on Rotifera and Crustacea communities were very similar. In the case of the Rotifera community, the percentage of the
Indices calculated on the basis of density and species structure of Rotifera in the studied dam reservoirs: A – value after conversion, B – value of the indices
Indices
Reservoirs (according to order in Fig.1)
1
2
3
4
5
6
7
8
9
10
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
Number of rotifers (N, ind. l−1)
152
46
39
39
180
47
3313
63
1455
58
13436
70
2453
61
2641
62
1069
57
818
55
Total biomass (B, mg w.w. l−1)
0.14
53
0.02
42
0.06
49
0.63
62
1.21
65
3
64
1
64
1.2
65
0.2
55
0.1
53
Percentage of bacterivores in total number (BAC, %)
13
47
26
50
54
57
78
62
0.5
44
7
46
41
54
34
52
56
57
90
65
Percentage of tecta in the population of
45
59
12
53
5
51
97
68
4
50
77
65
38
57
86
66
90
67
65
62
Ratio of biomass to the number (B:N, mg w.w. ind.−1)
0.0009
36
0.0005
43
0.0003
49
0.0002
59
0.0008
37
0.0002
53
0.0004
46
0.0004
44
0.0002
58
0.0002
62
Percentage of species indicative of high trophy in the indicative group (IHT, %)
100
60
100
60
57
51
100
60
93
59
100
60
65
53
57
52
96
59
96
59
Indices calculated on the basis of density and species structure of Crustacea in the studied dam reservoirs: A – value after conversion, B – value of the indices
Indices
Reservoirs (according to order in Fig.1)
1
2
3
4
5
6
7
8
9
10
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
Number of Crustacea (N, ind. l−1)
12
36
26
40
154
52
1402
71
197
54
626
64
557
62
207
54
1082
69
135
51
Biomass of Cyclopoida (B, mg w.w. l−1)
0.03
44
0.04
45
1.7
60
7.5
68
1.5
60
4.3
65
2.7
62
3.5
64
7.2
67
1
57
Percentage of cyclopoid biomass in total biomass of Crustacea (CB,%)
35
58
15
53
36
58
65
61
19
54
66
61
33
57
25
56
76
62
12
52
Ratio of cyclopoid biomass to Cladocera biomass (CY/CL)
0.54
56
0.33
54
0.75
57
1.9
61
0.24
51
2
61
1.2
59
0,37
54
0.8
57
0.6
56
Percentage of species indicative of high trophy in the indicative group (IHT,%)
50
53
80
60
58
55
97
64
55
54
90
63
41
52
14
46
18
47
79
60
In the case of one reservoir, Zygmunt August Lake, the index of the trophic state calculated for the Rotifera and Crusacea communities was the same and ranged from highly eutrophic to polytrophic. In the case of other reservoirs, the value of indices indicated mesotrophic to polytrophic state (Table 8).
Trophic state of the studied dam reservoirs corresponding to the value of indices calculated on the basis of density and species structure of Rotifera and Crustacea.
Reservoirs
Rotifera indices of trophic state
Crustacea indices of trophic state
Łapińskie Nowe Lake
low eutrophic
low meso-eutrophic
Mylof Dam Reservoir
high meso-eutrophic
low meso-eutrophic
Koronowskie Lake
high meso-eutrophic
high meso-eutrophic to low eutrophic
Zygmunt August Lake
high eutrophic to polytrophic
high eutrophic to polytrophic
Siemiatyckie Zalewy Reservoir
mesotrophic to high eutrophic
high meso-eutrophic to low eutrophic
Próba Dam Reservoir
high eutrophic to polytrophic
high eutrophic
Wióry Dam Reservoir
high eutrophic
low to high eutrophic
Chańcza Dam Reservoir
high eutrophic to polytrophic
high meso-eutrophic to high eutrophic
Leśniańskie Lake
low to high eutrophic
low eutrophic to polytrophic
Lubachowski Dam Reservoir
low to high eutrophic
low eutrophic
The zooplankton community in freshwater ecosystems contains species identified as aquatic bioindicators. These organisms are very good indicators, because they quickly respond to environmental stress, such as pollution/nutrient enrichment, habitat loss or overexploitation (Adams 2002; Birk et al. 2012). The ecological status of water bodies is defined as the expression of the quality of the structure and functioning of aquatic ecosystems based on biological quality elements (BQEs) (CIS 2003; Jeppesen et al. 2011). When implementing the EU Water Framework Directive (WFD), the Member States must classify the ecological status of surface waters following the standardized procedures (Jeppesen et al. 2011), but zooplankton is not considered useful in this assessment.
Zooplankton is mentioned in the WFD CIS Monitoring Guidance (CIS 2003; Jeppesen et al. 2011) as a “supportive/interpretative parameter” of fish, “often/typically measured or sampled at the same time”. Nevertheless, in many countries, e.g. in Denmark, zooplankton is considered to be useful in studying the ecological state of lakes (Jeppesen et al. 2000; 2005; 2009; Søndergaard et al. 2005). Using mainly examples from Denmark, Estonia and Great Britain, Jeppesen et al. (2011) demonstrated that zooplankton is an important indicator of the ecological state of water, and they discuss straightforward indicators which, with further studies, could be useful indicators of the structure and function of lake ecosystems as well as of their ecological state.
The study of general indicators that would work well in the whole EU is very difficult due to the number of factors that influence the results, including climate, seasons and geographical location of lakes (Moss et al. 2003). Mäemets (1983) demonstrated a clear relationship between zooplankton, the type of lakes and trophic state.
The long-term research of submontane dam reservoirs has shown that the assessment of the trophic status based on the community composition, density and dry weight of zooplankton results in a change of the trophic state of water from eutrophic-mesoeutrophic to mesoeutrophic Pociecha 2016). Moreover, the geographical location of dam reservoirs, as well as reolimnic or limnic characteristics do not affect the determination of the trophic state based on the structure and density of the zooplankton community. In a dam reservoir with a relatively short retention time (below 20 days; Table 1 – Mylof Dam Reservoir and Łapińskie Nowe Lake; Rosnowski and Hajka reservoirs – Pociecha & Heese 2007), the density of zooplankton was low compared to other dam reservoirs studied.
Low density values in reolimnic reservoirs (Łapińskie Nowe Lake and Mylof Dam Reservoir) seem to have no effect on the calculations and results of Rotifera and Crustacea indices of the trophic state (Table 8).
As indicated above, zooplankton indices for Polish lakes studied by Ejsmont-Karabin (2012, 2013) and Ejsmont-Karabin & Karabin (2012) perform very well, not only in natural lakes but also in artificial reservoirs. It is relevant that the selected indices based on Rotifera and Crustacea had similar values in artificial reservoirs. The results of our study show that the indices based on the structure of Rotifera groupings are slightly more sensitive to an increase in trophic conditions compared to the indices based on the structure of Crustacea.
In dam reservoirs, the structure of the zooplankton community with species indicators is similar to that in the lakes (Karabin 1985; Matveeva 1991; Haberman & Haldna 2014). The results of the zooplankton indices used to assess the trophic state of the dam reservoirs confirm the usefulness of these indices for the assessment of the water trophic status of both submontane and lowland dam reservoirs. Our study illustrates that zooplankton is an important indicator of the structure and function of freshwater dam reservoir ecosystems and may reflect the ecological status of water bodies.