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All issues Volume 30 (2017) Aquat. Living Resour., 30 (2017) 40 Full HTML
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Issue
Aquat. Living Resour.
Volume 30, 2017
Article Number 40
Number of page(s) 9
DOI https://doi.org/10.1051/alr/2017039
Published online 31 October 2017

© EDP Sciences 2017

1 Introduction

In aquatic ecosystems phytoplankton are the principal primary producers form the first trophic level of the aquatic food chain (Nasser and Sureshkumar, 2014). Hence they play an important role in the food webs as they provide food for zooplankton and other aquatic fauna (Jagadeeshappa and Kumara, 2013). Their presence is also essential to support a healthy aquatic ecosystem, and is frequently used as ecological indicator for the ecological health and the stress effects of chemical contaminants in aquatic ecosystems (Xu et al., 1999).

Phytoplankton diversity and dynamics in open lakes is largely dependent on abiotic factors such as nutrient availability, water temperature, light conditions and transparency, along with biotic interactions such as predation and competition (Siddaraju and Deviprasad, 2012; Jiang et al., 2014). Light limitation due to high turbidity is another factor that frequently controls phytoplankton growth over both annual and seasonal cycles (Ariyadej et al., 2004). Moreover, when single groups of organisms like algae compete for nutrients within a uniform environment, the diversity may be lower due to competitive exclusion. However, the biotic interactions between diverse freshwater plankton communities and how this influences overall community composition are highly complex (Siddaraju and Deviprasad, 2012).

Phytoplankton typically also undergo a fairly predictable annual and seasonal cycles (Jiang et al., 2014). The spatial and temporal variation highly influenced by the prevailing physicochemical parameters and these determine their abundance, occurrence and seasonal variations (Rothhaupt, 2000). Plankton respond quickly to environmental changes because of their short life cycle, hence, their species composition and dynamics are more likely to indicate the quality of the water which they are found. The relative abundance of chlorophyll is indicative of productive water (Washington, 1984; Jenkerson and Hickman, 2007). Ecologists have designed a range of indices and models for the measurement of phytoplankton diversity (Warwick, 1992). These diversity indices are applied in water pollution research to evaluate the effects of pollution on species composition (Archibald, 1972; Shashi et al., 2008). The qualitative and quantitative studies of phytoplankton have also been utilized to assess the quality of water (Shashi et al., 2008).

The importance of phytoplankton to trophic systems and overall ecosystem function means that understanding how communities respond to environmental parameters is important. Tropical lakes, particularly those in Africa, are known for their high primary productivity of phytoplankton (Sorokin et al., 2014) and thus present a useful system to study this issue. For example, recent studies on phytoplankton diversity in tropical Africa lakes, particularly in the soda lakes of East Africa, have come up with reports of exceptionally high diversity and photosynthetic activity (Lemma and Desta, 2016). Similarly, a high diversity of aquatic fauna has also been reported in Lake Chamo (Hailemicael and Raju, 2010; Willén et al., 2011). However, there are no clear reports which show phytoplankton diversity and abundance across different seasons in Lake Chamo. Therefore, the primary objective of this research was to assess phytoplankton diversity, abundance and dynamics with physicochemical parameters of Lake Chamo across different seasons.

2 Materials and methods

2.1 Study area

The study took place at Lake Chamo, a tectonic lake and the southernmost lake of the Ethiopian Rift Valley (5°45' N latitude and 37°30' E longitude), which covers an area of 45,000 ha, at an elevation of 1,233 m. It has a maximum known depth of 12.7 m. It is fed by the perennial Kulfo river, Kulfo that enters Lake Chamo from the north and by a number of small but non-perennial rivers including the Rivers Sile and Sego. The lake is characterized by a gently sloping shoreline covered by extensive emergent and submergent vegetation.

2.2 Sample collection sites

Samples were taken from four different sites of the lake, each of which had its own unique characteristics. Site 1 is situated close to the mouth of Kulfo river (N°5.55'05.07", E°37.33'34.8"). Site 2 is considered as the center of the lake (N°5.53'32.1", E°37.34'33.5"). Site 3 is near the mouth of Sile river (N°5.53'45.1", E°37.31'58.3"). Site 4 is located close to the main gate and is characterized by high disturbance (N°5.55'58.1", E°37.32'04.9") (Fig. 1).

thumbnail Fig. 1

Study area and sampling sites.

2.3 Phytoplankton sampling

Sampling took place between December 2013 and November 2014. Winter 2013/14 was considered as season I, spring 2014 season II, summer 2014 season III, and autumn 2014 season IV. Seasonal plankton, with two sampling times for each season, were collected from 4 sites of Lake Chamo using a nylobolt plankton net (No. 25 µm). To do so, two sampling techniques were employed. Firstly, to assess species diversity, phytoplankton were pulled up vertically to the surface. The sample from the net was then placed into a 100 mL bottle. Typically, this process required 2–3 samples to fill the bottle. Secondly, for determining the abundance, phytoplankton were collected using a water sampler (Jagadeeshappa and Kumara, 2013; Jiang et al., 2014). Since the total depth of Lake Chamo is less than 15 m, equal volumes were taken from the surface, mid-depth and bottom regions of the lake (Jagadeeshappa and Kumara, 2013; Jiang et al., 2014). Aliquots from each depth were combined and 1 L of the composite sample was poured into dark plastic bottles and preserved with 2 mL of Lugol's solution per 100 mL of the water for later analysis. For counting, samples were sedimented in glass columns (Welch, 1948) and studied with an inverted microscope. Calculation of phytoplankton abundance (per liter) was based on the cell counts from sub samples. All types of phytoplankton samples were taken to Limnology Laboratory of Addis Ababa University for identification and abundance estimation. Moreover, several special publications from tropical environments and Monographs of Desikachary (1959), (Philipose, 1962; Prescott, 1982), and (Sarode and Kamath, 1984) were consulted.

2.4 Physicochemical parameters measurements

The physicochemical parameters pH, water temperature, specific conductivity, saturation, total dissolved solids, salinity and dissolved oxygen were measured in the field using HQ40D digital multi probes meter (HACH, USA). Chlorophyll-a concentrations and turbidity were measured in the field with a hand-held fluorometer, Aqua Fluor™ (Turner Designs, San Jose, California), and water transparency was also measured using a white and black Secchi disc of 20 cm diameter. All the parameters were measured in three replicats. Water samples were also collected from the surface and stored in a cool box at 4 °C. These samples were later analyzed for total alkalinity (TA), total hardness (TH), total dissolved solid (TDS), chlorides, calcium, magnesium, sulphate, nitrate and total nitrogen (TN) at Arba Minch University Water quality laboratory using standard methods (APHA, 2005).

2.5 Statistical analysis

One-way ANOVA followed by Tukey's honest significant differences test was used to compare the spatial and temporal variation in phytoplankton diversity and physicochemical parameters, and partial correlation analysis was performed with SPSS (IBM©SPSS Statistics ver. 20, New York, USA). PAST programme, Hammer et al. (2001), was used to run Simpson's index, Shannon equitability index, species diversity (Shannon's index, H'), Margalefs Species Diversity (d) (Magurran, 2004) and evenness (Pileou's index, J) in evaluating phytoplankton community structure.

3 Results

3.1 Physicochemical characteristics of Lake Chamo

Water pH ranged from 8.87 ± 0.25 (Mean ± SD) in autumn (site 1) to 9.83 ± 0.79 in summer (site 3. Significant differences in pH were observed across different seasons at site 1 (Tab. 1). Water temperature was highest (30.4 ± 0.21 °C) in spring 2014 at site 3 and lowest 26.0 ± 0.12 °C during summer 2014 at site 2. The mean value of transparency ranged from 12 ± 0.78 cm during summer (site 1) to a 60 ± 0.21 cm in spring 2014 (site 2), and significant differences were also observed across the different seasons and sampling sites. Dissolved oxygen concentrations decreased in summer and autumn, while increased in winter and spring. Transparency remained very low during the rainy season due to increased turbidity. The mean value of electrical conductivity ranged from 1253 ± 1.24 ms/cm at site 1 in the summer to 2127 ± 0.98 ms/cm during spring at site 3.

The mean value of TDS ranged from 595 ± 5.10 mg/L at site 1 during summer to 924 ± 3.65 mg/L at site 3 during spring (Tab. 1). There was significant variation in the value of TDS among the sampling sites and between the seasons (p < 0.05), site 1 having significantly higher value than site 1 and 3. The mean value of TDS at summer season is significantly lower than all the other seasons. The mean value of salinity ranged from 0.6 ± 0.01 ppt at site 1 during summer to 0.93 ± 0.08 ppt at site 3 during spring season and there was not significant variation in the value of salinity among the sampling sites and seasons (p < 0.05).

Table 1

The seasonal and spatial variation of physicochemical variables in Lake Chamo during winter 2013/14 (season I), spring 2014 (season II), summer 2014 (season III), and autumn 2014 (season IV).

3.2 Phytoplankton species composition and abundance

A total of 18 genera belonging to four different taxonomic groups were identified (Tab. 4). The three groups, Cyanophyta, Chlorophyta and Bacillariophyta accounted 96% of the total phytoplankton abundance (Fig. 2). Cyanophyta was the most abundant group representing 46.35% of the total abundance, whilst Chlorophyta (blue green algae) had the highest number of genera, and represented 34.06% of the total abundance. Bacillariophyta (Diatoms) represented 18.42% of the total abundance split between genera. Euglenophyta was the least represented group with only 1.17% of the total.

Phytoplankton species composition and abundance in Lake Chamo showed variation across different seasons and sampling sites during the study period (Fig. 3). During the dry and rainy season, Cyanophyta was the dominant group, followed by Bacillariophyta and Chlorophyta. Dense phytoplankton populations developed during winter and autumn seasons, immediately after the rainy season. Anabaena, Microcystis and Scendesmus species dominated the lake during autumn and winter seasons. Among the Bacillariophyta, Cyclotella and Amphora species were the most abundant during the pre and post rainy season in all sites. Of the Chlorophyta, Pediastrum, Scendesmus and Closterium species showed the highest abundance during the rainy seasons (July to September). Overall, the four seasons exhibit different phytoplankton species composition across different sites.

thumbnail Fig. 2

Seasonal relative abundance of phytoplankton in Lake Chamo 2013–2014.
thumbnail Fig. 3

Seasonal phytoplankton composition in Lake Chamo 2013–2014.

3.3 Diversity indices of phytoplankton across different sampling sites of Lake Chamo

The highest Shannon-Wiener's diversity index (H1 = 2.58 ± 0.14) was recorded at site 4 during winter 2013/14 season, while the lowest (H1 = 1.79 ± 0.08) was recorded at site 2 during autumn 2014 (Tab. 2). Margalefs Species Diversity (d) was highest (2.37 ± 0.27) during autumn at site 1 and lowest at site 2 (1.53 ± 0.01) during winter 2013/14. Highest and lowest Simpsons' index (1/D) of 10.44 ± 0.06 and 2.91 ± 0.23 were recorded at site 4 and site 2, during winter and autumn respectively. Species Evenness was lowest (0.58 ± 0.04) at site 2 during autumn and highest (0.83 ± 0.06) was recorded at site 4 during spring season. The diversity was high during winter season in all sites.

Table 2

Diversity indices measurement of phytoplankton in Lake Chamo during winter 2013/14 (season I), spring 2014 (season II), summer 2014 (season III), and autumn 2014 (season IV).

3.4 Correlation analysis of phytoplankton group with some environmental factors

The results of the partial correlation analysis showed the average Cyanophyta count was positively and non-significantly (p>0.05) correlated with the water temperature and turbidity of the lake (Tab. 3). However, total nitrogen positively and significantly correlated with Cyanophyta count. Positive and significant correlation was also observed between Chlorophyta count and the water temperature of the lake. A non- significant and negative correlation was found between water temperature and, Euglenophyta and Bacillariophyta counts. Total dissolved solids also showed non-significant and positive correlation with these counts.

Table 3

Correlation coefficients found by a partial correlation analysis of phytoplankton group (average count) and various environmental factors in Lake Chamo 2013-2014/15.

4 Discussion

4.1 Physicochemical and phytoplankton conditions

Our current understanding of the seasonal and spatial variation of phytoplankton with environmental factors is insufficient in Lake Chamo. Seasonal variations in phytoplankton are related to a variety of environmental factors in aquatic environments (Cetin and Sen, 2004). Water temperature and transparency are among the most important physical factors affecting the distribution and seasonal variations of phytoplankton (Mosisch et al., 1999). During the study period Lake Chamo water temperature varied between 26.0 ± 0.12 °C to 30.4 ± 0.21 °C. This value is a little higher to the reported values of other Ethiopian Rift Valley Lakes, such as Abijata and Langano 18–27 °C (Kebede et al., 1994; Kumssa and Bekele, 2013); Lakes Ziway 18.5–27.5 °C (Girma, 1988); and Hawassa 20.98–21.33 °C (Abate et al., 2015). The change in water temperature of Lake Chamo affects the phytoplankton diversity and abundance. This result was in agreement with the reports of Richardson et al. (2000) and Lund (1965), in fresh water ecosystem water temperature strongly regulates seasonal variations of phytoplankton. The increase in phytoplankton diversity and abundance during winter and spring seasons in Lake Chamo could also be a result of the increasing water temperature. Similar reports also showed that water temperature of Lake Chamo varied among seasons (Tafa and Assefa, 2014). According to their findings, the water temperature of Lake Chamo increased in January due to the increase in air temperature. Except for site 1 (mouth of Kulfo river), the pH values were not significantly different in all seasons. The pH values recorded in this study were comparable with the results obtained by other researchers, (8.53–9.44) in the same lake (Eyasu, 2004; Tafa and Assefa, 2014; Lemma and Desta, 2016). The pH values were relatively low during the rainy seasons, which may be attributed to the decomposition of organic matter (Tafa and Assefa, 2014). However, the pH values increased after the rainy season. This relatively increases the photosynthetic activities of phytoplankton.

The TDS values of Lake Chamo (924 ± 3.65l to 595 ± 5.10 mg/L) were higher than Lake Hawassa 455.6 mg/L (Abate et al., 2015). But this value is far less than the nearby rift valley lake, Lake Abaya reported a value of 1,522.45 mg/L (Huib and Herco, 2006). This was mainly attributed to the high rate of evaporation and consequent reduction in the water level during spring.

Salinity of Lake Chamo considered to be one of the main factor responsible for the deterioration of the environmental conditions of Lake Chamo and the drop in its phytoplankton and fish diversity (Tafa and Assefa, 2014; Lemma and Desta, 2016). The minimum salinity recorded was 0.6 ± 0.01 ppt at site 1 during summer and the maximum was 0.93 ± 0.08 ppt at site 3 during spring season. The highest salinity during spring season was attributed to the high rate of evaporation in the region, while the lowest may be due to the effect of dilution arises from drainage water from Kulfo, Sile and other rivers during the rainy summer season (Tafa and Assefa, 2014).

Phytoplankton species composition in this study showed a decline at the onset of the rainy season (summer) which corresponded to increased dilution and water turbidity. This result is comparable to the study conducted on Lake Tana (Wondie et al., 2007), who reported that phytoplankton biomass declined during the rainy season as a result of increased turbidity. According to this study the phytoplankton community of Lake Chamo consisted of mainly of Cyanophyta, Chlorophyta, Bacillariophyta and Euglenophyta groups. In line with this, (Golubtsov and Habteselassie, 2010), reported Cyanophyta, Chlorophyta and Bacillariophyta being the main phytoplankton groups in Lake Chamo. The seasonal diversity and abundance of phytoplankton in Lake Chamo is mainly related with the range of physicochemical parameters such as temperature, salinity, alkalinity, nitrate-nitrogen and phosphate. The observed variation in plankton species dominance during the study may be attributed to variations in the optimal conditions for the various species (Jiang et al., 2014; Lemma and Desta, 2016). The variations in phytoplankton cell count across different season have also been reported in other Ethiopian rift valley lakes. For example, Kumssa and Bekele (2013) showed that there were marked variations in phytoplankton population in the Abijata Shala Ethiopian rift valley lake, apparently due to differences in water quality. The finding of this study also showed that Lake Chamo was dominated by Cyanophyta with noticeable changes between seasons. The phytoplankton population changes were characterized by dominance shifts between Cyanophyta and Chlorophyta. The most abundant Cyanophyta was Anabaena sp during autumn and winter, while the dominant Chlorophyta during these seasons were Scendesmus, Cosmarium and Pediastrum species. Of the Bacillariophyta Cyclotella and Amphora species were the most abundant during the dry winter season. Moreover, the highest Shannon-Wiener's diversity index was recorded during the dry winter season, while the lowest was recorded during autumn. This finding agrees with (Jiang et al., 2014), who reported Lake Chaohu was inhabited by different phytoplankton species and dominated by Microcystis viridis, Microcystis flos-aquae, and Anabaena circinalis. These results are also in agreement with Kumssa and Bekele (2013) and Tewodros and Afework (2014), who reported that Bacillariophyta were more dominant during the dry season, especially Cyclotella and Navicula species dominated Abijata- Shalla Lakes (Tab. 2).

5 Conclusion

In this study, a total of 18 genera belonging to four different taxonomic groups were identified, among which Cyanophyta, Chlorophyta and Bacillariophyta accounted 96% of the total phytoplankton abundance. Cyanophyta was the most abundant group representing 46.35% of the total abundance, whilst Chlorophyta had the highest number of genera, and represented 34.06% of the total abundance. Euglenophyta was the least abundant group in the study period. The four seasons exhibit different phytoplankton species composition across different sites, but the overall species diversity was high during winter season in all sampling sites. Moreover, positive and significant correlation was observed between Chlorophyta count and water temperature of the lake. The mean Cyanophyta count was also positively and non-significantly correlated with water temperature and turbidity of the lake. A non- significant and negative correlation was found between water temperature and, Euglenophyta and Bacillariophyta counts.

Appendix

Table 4

Phytoplankton dynamics across different seasons (number of cells/mL).

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Cite this article as: Fekadu A, Chanie S. 2017. A seasonal study on phytoplankton diversity and dynamics of Lake Chamo, Ethiopia. Aquat. Living Resour. 30: 40

All Tables

Table 1

The seasonal and spatial variation of physicochemical variables in Lake Chamo during winter 2013/14 (season I), spring 2014 (season II), summer 2014 (season III), and autumn 2014 (season IV).

In the text
Table 2

Diversity indices measurement of phytoplankton in Lake Chamo during winter 2013/14 (season I), spring 2014 (season II), summer 2014 (season III), and autumn 2014 (season IV).

In the text
Table 3

Correlation coefficients found by a partial correlation analysis of phytoplankton group (average count) and various environmental factors in Lake Chamo 2013-2014/15.

In the text
Table 4

Phytoplankton dynamics across different seasons (number of cells/mL).

In the text

All Figures

thumbnail Fig. 1

Study area and sampling sites.
In the text
thumbnail Fig. 2

Seasonal relative abundance of phytoplankton in Lake Chamo 2013–2014.
In the text
thumbnail Fig. 3

Seasonal phytoplankton composition in Lake Chamo 2013–2014.
In the text

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