For many years, little attention has been paid to the winter ice-covered period in temperate lakes. The reason for this was not only the hard fieldwork conditions and methodological problems with sampling, but mainly the opinion that winter is a dormant season. It was assumed that the metabolic activity of planktonic organisms is reduced or even completely ceased due to low temperature, limited light availability and a short day (reviewed by Bertilsson et al. 2013).
Recent studies showed that aquatic communities can exist under the ice, showing adaptation to hard and unfavorable environmental conditions (Üveges et al. 2012). For example, phytoplankton may form massive under-ice blooms (e.g. Vehmaa & Salonen 2009; Babanazarova et al. 2013; Kalinowska & Grabowska 2016). In turn, the breakdown of phytoplankton blooms may cause extremely high bacterial abundance and biomass (Bižić-Ionescu et al. 2014). Intensive phytoplankton blooms as well as high abundance and activity of heterotrophic bacteria in ice-covered lakes are to a large extent a consequence of climate changes, leading to the decline or absence of ice/snow cover and the reduction of ice duration (Weyhenmeyer et al. 2011). On the other hand, snow, thick ice cover, low primary production and high decomposition of organic materials affect the oxygen depletion, subsequently influencing the winter fish kills and the cascading effect on lake food webs (Balayla et al. 2010; Sayer et al. 2016).
Studies that consider simultaneously all functional groups of aquatic food webs are still very scarce. The results of these studies showed that during the ice-covered period, nanoflagellates, ciliates and rotifers can reach high abundances, while crustaceans are usually few or even absent (Ventelä et al. 1998; Dokulil & Herzig 2009; Twiss et al. 2012; Kalinowska & Grabowska 2016). In addition, literature data show that primary producers can live not only in the water column below the ice cover, but also in liquid water pockets of lake ice sheets, where light conditions are more favorable than in the under-ice water (Kirillin et al. 2012).
It is well documented that winter conditions may significantly affect the functioning and structure of water ecosystems throughout the year (Adrian et al. 1999; Weyhenmeyer et al. 1999; Kirillin et al. 2012; Haberyan 2016), including spring phytoplankton (Yang et al. 2016), thermal regime, the amount of organic carbon production, summer hypoxia (Twiss et al. 2012), metabolic features of freshwater microorganisms, food web development (Bertilsson et al. 2013; Bižić-Ionescu et al. 2014), and dynamics of planktonic organisms (Dokulil & Herzig 2009; Vehmaa & Salonen 2009). According to Haberyan (2016), a single strong climatic anomaly may affect a lake for several years, including a possible increase in winter fish kills (Sayer et al. 2016).
Although the number of studies on temperate ice-covered lakes increased in recent years, much more information about physical, chemical and biological processes is available for perennially ice-covered Arctic and Antarctic lakes than for seasonally ice-covered lakes (Kirillin et al. 2012). Therefore, much more studies of aquatic ecosystems in different parts of the world, focusing on all planktonic communities, are needed to better understand the structure and functioning of under-ice food webs (Twiss et al. 2012; Bertilsson et al. 2013; Bižić-Ionescu et al. 2014).
The aim of this study was to determine the abundance and composition of the microbial (nanoflagellates, ciliates) and classic (phytoplankton, rotifers, crustaceans) food webs’ components in eutrophic Masurian lakes under the ice cover. Because only some species among various taxonomic groups of organisms can adapt to the under-ice conditions, e.g. low temperature and light intensities (Üveges et al. 2012; Bižić-Ionescu et al. 2014), we hypothesized that eutrophic temperate lakes, differing in morphometry and fisheries management, do not differ in abundance and structure of planktonic communities under the ice.
The study was conducted in three eutrophic lakes with different stages of eutrophication (Napiórkowska-Krzebietke et al. 2012; Zakęś et al. 2015), situated in the Masurian Lake District (northeastern Poland). Lake Warniak is a shallow lake with submerged vegetation dominated by charophytes. Two other lakes are deeper and vary in area – Lake Dgał Wielki is a medium-sized lake, while Lake Dgał Mały – a small-sized one. Morphometric characteristics of the lakes are given in Table 1. Historically, all lakes were stocked with seston-filtering and herbivorous fish species –
Morphometric characteristics of the studied Masurian lakes.
Lake
Area (ha)
Max depth (m)
Mean depth (m)
Max length (m)
Max width (m)
Mixing type
Warniak
38.4
3.7
1.2
1000
500
polymictic
Dgat Wielki
93.9
18.8
5.7
1275
1110
dimictic
Dgat Maty
14.4
15.8
4.6
670
295
dimictic
Water samples were collected once a week in February 2016 (four occasions in each lake) from just beneath the ice cover. During the sampling period, the deepest parts of the lakes were not accessible due to thin or brittle and cracked ice. For this reason, our samples were collected from a site about 20 m away from the shore. On each sampling day, the thickness of the ice and snow were measured.
Temperature and oxygen concentrations were measured using an YSI oxygen meter (Model 57).
Total phosphorus (TP) concentrations were determined colorimetrically, after mineralization, using a Shimadzu UV 1601 spectrophotometer (Standard Methods 1999).
Nitrogen and organic carbon concentrations were measured by a Shimadzu TOC-VCSH with a TNM-1 module and automatic sample changer ASI-V using a NDIR detector, according to PN-EN 12260:2004 and PN-EN 1484:1999, respectively. To measure total nitrogen (TN) and total organic carbon (TOC), water samples were homogenized with a magnetic stirrer, while to measure dissolved organic carbon (DOC), water samples were filtered through 0.45-µm pore-size membrane filters. Particulate organic carbon (POC) was calculated as the difference between the TOC and DOC concentrations.
Chlorophyll
Nanoflagellate (NF) samples were fixed with formaldehyde (final concentration 2%), stained with DAPI (Porter & Feig 1980), filtered through 0.8 µm pore size polycarbonate membrane filters (Millipore) and enumerated by epifluorescence microscopy (Nikon Optiphot 2). The NF biovolume was calculated from measurements of cells size and their approximations to simple geometric forms. The carbon content was calculated by multiplying the biovolume with a conversion factor of 200 fg C µm−3 (B⊘rsheim & Bratbak 1987). Autotrophic (ANF) and heterotrophic (HNF) nanoflagellates were differentiated on the basis of chlorophyll
Ciliate samples were fixed with Lugol’s solution and examined under a light microscope (Nikon Eclipse E200). Biovolume was calculated from measurements of cell dimensions and simple geometric shapes and converted to carbon biomass using a conversion factor of 190 fg C µm−3 (Putt & Stoecker 1989). Species identifications of ciliates were based mainly on Foissner et al. (1999).
Phytoplankton samples were fixed with Lugol’s solution and then ethanol, and enumerated by an inverted microscope (Nikon) according to Utermöhl (1958). Biomass was calculated from cell volume measurements, according to standard methods (Napiórkowska-Krzebietke & Kobos 2016). The content of phytoplankton cell carbon was calculated from cell volume according to the formula and coefficients given for freshwater phytoplankton species (Rocha & Duncan 1985). Phytoplankton composition was determined using a Carl Zeiss Jena ”Jenamed” light microscope at 200×, 400× and 1000× magnifications with oil immersion. Taxa identifications followed the newest references (e.g. Huber-Pestalozzi 1983; Krammer & Lange-Bertalot 1986; 1988; 1991; Komárek & Anagnostidis 2005) and currently accepted taxonomic names were confirmed according to Guiry & Guiry (2016).
Rotifers and crustaceans were collected using a 5 l Patalas sampler with five replicates (25 l in total). Samples were concentrated using a 30 µm mesh plankton net and preserved with Lugol’s solution and 96% ethanol. The abundance of zooplankton was quantified using a Sedgwick-Rafter counting cell under an optical microscope. Identification of zooplankton species was based mainly on Flössner (1972), Radwan et al. (2004) and Rybak & Błędzki (2005). Length and length-dry mass relationships were used to determine the biomass of rotifers using Ejsmont-Karabin (1998) and the biomass of crustaceans using Bottrell et al. (1976). The biomass of rotifers and crustaceans was converted to carbon units assuming that carbon content is 45% and 40% of the dry weight, respectively (Latja & Salonen 1978).
Statistical analyses of results were carried out using the STATISTICA software (StatSoft, Inc.). The differences in chemical and biological parameters between the studied lakes were analyzed using the nonparametric analysis of variance. The Kruskal-Wallis test followed by the Mann-Whitney
The studied lakes did not differ statistically (Kruskal-Wallis test,
Dissolved organic carbon (DOC) concentrations were rather low (Table 2) and did not differ significantly between the studied lakes (Kruskal-Wallis test,
Chemical parameters during the ice-covered period in the eutrophic Masurian lakes. Mean values with standard deviations and ranges in parentheses. DOC: dissolved organic carbon; POC: particulate organic carbon; TP: total phosphorus, TN: total nitrogen, Chl
Lake
DOC (mg l−1)
POC (mg l−1)
TP (µg l−1)
TN (mg l−1)
Chl
Warniak
4.78 ± 0.77 (3.75-5.60)
0.23 ± 0.13 (0.10-0.37)
63 ± 7 (56-72)
0.97 ± 0.10 (0.87-1.10)
3.28 ±1.12 (2.46-4.92)
Dgat Wielki
4.81 ± 0.61 (4.31-5.69)
0.34 ± 0.16 (0.19-0.57)
94 ± 19 (75-118)
1.04 ± 0.15 (0.91-1.22)
6.45 ± 1.09 (5.2-7.78)
Dgat Maty
5.71 ± 1.62 (4.23-7.50)
0.45 ± 0.11 (0.29-0.52)
105 ± 19 (81-128)
1.24 ± 0.08 (1.12-1.30)
15.47 ± 8.63 (5.32-24.78)
The studied lakes were characterized by relatively high concentrations of total phosphorus (TP) and nitrogen (TN) (Table 2). The highest mean concentration of TP was recorded in Lake Dgał Mały, a slightly lower value was noted in Lake Dgał Wielki, while the lowest – in Lake Warniak. The mean values of TN in lakes Warniak and Dgał Wielki were similar and clearly lower than in Lake Dgał Mały. Statistical differences in TP and TN were significant between lakes Warniak and Dgał Mały (Kruskal-Wallis test,
The mean concentration of chlorophyll
The mean numbers and biomass of nanoflagellates were clearly higher in Lake Dgał Mały than in lakes Dgał Wielki and Warniak (Fig. 1A, B). However, the differences between the studied lakes, both in the numbers and biomass, were not statistically significant (Kruskal-Wallis test,
The numbers (A) and biomass (B) of nanoflaagellates, with autotrophic (ANF) and heterotrophic (HNF) cells marked, during the ice-covered period in the eutrophic Masurian lakes. Mean values from four sampling datasets with standard deviations for the total numbers and biomass.Figure 1
The ciliate assemblage was characterized by low numbers (Fig. 2A) and particularly low biomass (Fig. 2B). The mean numbers and biomass of ciliates were the highest in Lake Dgał Mały. In lakes Dgał Wielki and Warniak, the mean numbers of ciliates were about two times lower, while the mean biomass – three times lower. Oligotrichs, represented by small species from the genus
The numbers (A) and biomass (B) of ciliates, with taxonomic groups marked, during the ice-covered period in the eutrophic Masurian lakes. Mean values from four sampling datasets with standard deviations for the total numbers and biomass.Figure 2
The numbers (Fig. 3A) and biomass (Fig. 3B) of phytoplankton differed markedly between the studied lakes. The highest mean numbers and biomass were noted in Lake Dgał Mały and about two times lower values were recorded in Lake Dgał Wielki. Lake Warniak was characterized by particularly low numbers and biomass of these organisms. However, statistical analysis revealed significant differences only in the phytoplankton biomass between Lake Warniak and Lake Dgał Mały (Kruskal-Wallis test,
The numbers (A) and biomass (B) of phytoplankton, with taxonomic groups marked, during the ice-covered period in the eutrophic Masurian lakes. Mean values from four sampling datasets with standard deviations for the total numbers and biomass.Figure 3
The numbers (Fig. 4A) and biomass (Fig. 4B) of rotifers were low in the studied lakes. The highest mean numbers was recorded in Lake Dgał Wielki and slightly lower values were noted in Lake Dgał Mały. In contrast, the highest mean rotifer biomass was observed in Lake Dgał Mały. Lake Warniak was characterized by a relatively low numbers and biomass of rotifers. There were no statistical differences in the numbers and biomass of rotifers between the studied lakes (Kruskal-Wallis test,
The numbers (A) and biomass (B) of rotifers, with dominant taxa marked, during the ice-covered period in the eutrophic Masurian lakes. Mean values from three sampling datasets with standard deviations for the total numbers and biomass.Figure 4
The highest mean numbers of crustaceans was noted in Lake Dgał Mały (Fig. 5A). The values were similar in the two other lakes, Warniak and Dgał Wielki, and about two times lower compared to Lake Dgał Mały. The mean biomass of crustaceans was the highest in Lake Warniak, while the slightly lower value was noted in Lake Dgał Mały (Fig. 5B). Lake Dgał Wielki was characterized by extremely low biomass, which was about 6 and 8 times lower compared to two other lakes. The differences in the crustacean biomass between the studied lakes were not statistically significant (Kruskal-Wallis test,
The numbers (A) and biomass (B) of crustaceans, with cladocerans and copepods marked, during the ice-covered period in the eutrophic Masurian lakes. Mean values from three sampling datasets with standard deviations for the total numbers and biomass.Figure 5
Field studies in ice-covered freshwater systems are hazardous, logistically difficult and expensive, especially during the thin ice period or the final phase of ice melting. At that time, the deepest sites of the lakes are usually not accessible either by ship or by car. Samples usually collected from the deepest parts of lakes are treated by hydrobiologists as representative for the whole lake. However, lakes are far from being homogenous in a horizontal plane (Laybourn-Parry 1992). Heterogeneity in the environment and in the distribution of aquatic organisms seems to be particularly evident during the winter when the deepest part of lakes are covered with thick ice, while the parts of lakes closer to the shoreline are without ice or covered with thin ice. However, further studies are needed to confirm this assumption. In this study, we investigated both abiotic and biotic parameters under thin and brittle ice. Similarly to the studies conducted by Kalinowska & Grabowska (2016) in eutrophic Lake Mikołajskie, our samples were collected from a site about 20 m away from the shore. Thus, our results are mainly compared with those noted by the above authors.
Our studies showed low variability (CV < 20%) of chemical parameters, especially TP and TN whereas high variability (CV ranged from 20% to 141%) of biological parameters in all the studied lakes over the short time span. Such large fluctuations, both in the numbers and biomass of all the studied groups of organisms, suggest that winter is a very dynamic period.
The high dissolved oxygen concentrations during the whole ice-covered period suggested good conditions for fish survival in all the studied lakes. Such oxygen conditions in winter were also recorded in 2011-2014, thus, no winter fish kills were observed (Zakęś et al. 2015). The concentrations of dissolved organic carbon (DOC) were relatively low (below 7.5 mg l−1), approximately constant (CV did not exceed 28%) and similar in all the studied lakes. In winter, the vast majority of organic matter in lake waters is of autochthonous origin due to the reduction of dissolved and particulate matter from the atmosphere and the surface runoff from the surrounding watershed by ice cover (Bertilsson et al. 2013). The autochthonous organic matter released by phytoplankton is easily utilized and decomposed by bacteria (Chróst 1986). This fact may explain low DOC concentrations in lake water during winter.
Similarly to the results of other studies (Agbeti & Smol 1995; Toporowska et al. 2010; Babanazarova et al. 2013), we recorded relatively high TP and TN concentrations in all lakes. It seems that such high concentrations of nutrients could be responsible for the massive development of phytoplankton. Another factor contributing to the growth of phytoplankton could be the lack of snow on the ice (Bolsenga & Vanderploeg 1992). Unfortunately, contrary to the results reported by many authors (e.g. Vehmaa & Salonen 2009; Üveges et al. 2012; Babanazarova et al. 2013; Wojciechowska & Lenard 2014; Kalinowska & Grabowska 2016), we did not observe such massive phytoplankton blooms.
The numbers and biomass of phytoplankton did not exceed 16 m ind. l−1 and 4 mg l−1, respectively. Both the maximum and mean phytoplankton numbers were similar to those noted by Kalinowska & Grabowska (2016), while the biomass was about 4 times lower because of nanoplanktonic taxa dominance. However, these maximal values as well as high chlorophyll
As shown by Dokulil & Herzig (2009), if food quality and quantity are good (cryptophytes prevail during winter), some eurythermal rotifer species can quickly reach high densities. In our study, however, both the numbers and biomass of rotifers (maximum of 326 ind. l−1 and 0.2 mg l−1, respectively) were relatively low – about 6-7 times lower than maximal values recorded by Kalinowska & Grabowska (2016). In contrast, the numbers and biomass of crustaceans (maximum of 58 ind. l−1 and 0.82 mg l−1) were much higher compared to values observed by above authors. The dominance of detritophagous
Although the maximum numbers and biomass of ciliates, 10.6 × 103 ind. l−1 and 0.12 mg l−1, were about 2 and 6 times, respectively, lower than those noted by Kalinowska & Grabowska (2016), their taxonomic composition and dominance structure were very similar. Under-ice ciliate communities were mainly represented by small species from the genera
The relationships between abiotic and biotic components based on Principal Component Analysis (PCA). A – ordination diagram, B – classification of samples. Ice – ice cover, DOC, POC, TOC – forms of carbon, TP, TN – total phosphorus and nitrogen, Chl Figure 6
Ecosystem size affects the phytoplankton nutrient status (Guildford et al. 1994), photosynthesis (Fee et al. 1992), distribution (Agbeti et al. 1997) and composition (Borics et al. 2016) and determines food-chain length (Post et al. 2000) in lakes during the ice-free periods. In contrast, the morphometry of lakes does not seem to play an important role in determining the phytoplankton communities during the period of ice cover, with depth being the only determinative factor (Danilov & Ekelund 2001). Information on the effect of lake size on other groups of planktonic organisms under the ice/snow cover is very scarce. That is why in the present study we investigated both microbial and classic food web components in three lakes of almost the same trophic level, but different morphometry. It should be emphasized that only a few studies have so far simultaneously focused on various groups of organisms (Agbeti & Smol 1995; Ventelä et al. 1998; Dokulil & Herzig 2009).
The results of our study showed that the lakes, although similar in the ice cover thickness, differed significantly in the concentrations of TP, TN and chlorophyll
Mean (from three sampling dates) biomass (in µg C l−1) of autotrophic (A) and heterotrophic (H) organisms during the ice-covered period in the eutrophic Masurian lakes.
Organisms
Warniak
%
Dgał Wielki
%
Dgał Mały
%
Autotropic biomass
Phytoplankton
100.7
76.2
255.5
91.5
501.6
82.3
ANF
31.4
23.8
23.6
8.5
107.6
17.7
TOTAL
Heterotrophic biomass
HNF
30.8
16.0
39.8
51.3
40.2
19.6
Ciliates
5.1
2.7
5.7
7.4
13.7
6.7
Rotifers
5.2
2.7
13.9
17.9
36.6
17.8
Crustaceans
151.2
78.6
18.1
23.4
114.8
55.9
TOTAL
A/H biomass ratio
0.7
3.6
3.0
In conclusion, shallow Lake Warniak was characterized by the lowest concentrations of DOC, POC, TP, TN, chlorophyll
The studied lakes were characterized by low organic carbon and chlorophyll