Int. J. Aquat. Biol. (2022) 10(5): 349-365 ISSN: 2322-5270; P-ISSN: 2383-0956 Journal homepage: www.ij-aquaticbiology.com © 2022 Iranian Society of Ichthyology Original Article Diatom community structure in relation to physico-chemical factors in a tropical soda Lake Shala and inflowing hot-springs, Ethiopia Solomon Wagaw1,2 Seyoum Mengistou2, Abebe Getahun2, Assefa Wosnie3, Yirga Enawgaw1 1Department of Biology, Wolkite University, Wolkite, Ethiopia. 2Department of Zoological Sciences, Addis Ababa University, Addis Ababa, Ethiopia. 3Department of Biology, Dilla University, Dilla, Ethiopia. s Article history: Received 27 May 2021 Accepted 22 October 2022 Available online 2 5 October 2022 Keywords: Diatom community Lake Shala Hot spring RDA analysis Abstract: Diatoms are highly diverse and versatile, with members growing under different environmental conditions including extreme environments. Although diatom communities in some extreme environments have been investigated recently, little is known about their community structure within the hot springs of soda lakes in Ethiopia. The study aimed to assess the diversity and distribution of diatoms from Lake Shala and inflowing hot springs in relation to physico-chemical variables. Water and diatom samples were collected from Lake Shala and three inflowing hotsprings. The mean pH, temperature, EC, salinity, TDS, DO, NO3-+NO2-, NH3+NH4+, SRP, TP and SiO2 were significantly different among the stations. The significant variations in these factors could be attributed to their heterogeneous geological characteristic and the hydrology of the study area. A total of 45 diatom taxa were identified, with the highest species observed in Shala Hora Mid Hotspring sites (37) and the lowest in Shala Gike Hotspring (29). Diatom community structure was also examined and it was found that the diatom community of Lake Shala and inflowing hotsprings are highly influenced by environmental water conditions. Characteristic taxa including Anomoeoneis sphaerophora, Nitzschia spp., Rhomboids gibberula, R. gibba, R. acuminata, R. operculata, Navicula spp. and Frustulia rhomboids, showed a wide tolerance to pH, salinity, EC, TDS, temperature, nitrogen and phosphate. RDA analysis found a number of discriminating taxa and salinity, conductivity, pH, DO SRP and temperature were key factors that accounted for a significant variation in the diatom community structure. Introduction Soda lakes of the East African Rift Valley are among the world’s most productive ecosystems (Ogato et al., 2016). The Lesser Flamingo (Phoeniconaias minor Geoffroy Saint-Hilaire, 1798) population inhabits these lakes and can gather in flocks of over one million birds when the phytoplankton community of the lake is dominated by Arthrospira fusiformis, their primary food sources (Matagi, 2004; Kumssa and Bekele, 2014). In Ethiopia, the main Flamingo lakes are Abijata, Shala, Metehara, Chitu, and Aranguade, which provide a preferred feeding and breeding habitat for large populations of avifauna (Kumssa and Bekele, 2014). Despite the ecological, economic and scientific research values of these lakes, only a few are Correspondence: Solomon Wagaw DOI: https://doi.org/10.22034/ijab.v10i55.1229 E-mail: wagawsolomon2@gmail.com DOR: 20.1001.1.23830956.2022.10.5.1.2 subjected to active conservation (Matagi, 2004). These ecosystems are highly sensitive to environmental change mainly because of seasonal alterations of hydrological conditions and human‐ induced disturbances, which have been demonstrated to affect biological community structure in Saline lakes (Oduor and Schagerl, 2007a; Krienitz and Kotut, 2010). Saline lakes, especially those in the tropics, remain poorly studied, particularly in the processes controlling species distribution (Mengistou, 2016; Ogato and Kifle, 2017). Diatoms are considered the main component of aquatic ecosystems because they are usually the dominating primary producers (Krienitz and Kotut, 2010) and functionally important in sequestering and transforming many inorganic nutrients into organic https://ij-aquaticbiology.com/index.php/ijab/article/view/1229 350 Wagaw et al./ Diatom community structure in Lake Shala, Ethipoia forms (Krienitz and Kotut, 2010). The benthic diatoms constitute a significant energy source for higher trophic levels (Bate et al., 2002; Carvalho et al., 2002). Despite their ecological importance, the various factors that regulate community distribution and structure are poorly understood compared to pelagic phytoplankton communities (Carvalho et al., 2002). Many studies have reported a wide distribution of benthic diatoms and their tolerance to gradients of diverse environmental variables (Gasse, 1986; Wood and Talling, 1988; Kebede et al., 1994; Oduor and Schagerl, 2007a; Krienitz and Kotut, 2010). Saline Lakes and the nearby hot springs are complex ecosystems in which many environmental factors vary on spatial and/or temporal scales. These factors include geomorphic characteristics, nutrient and ionic concentrations and other physico-chemical properties, manifesting great ecological variability in species composition (Gasse, 1986; Wood and Talling, 1988; Gebre‐Mariam, 2002; Oduor and Schagerl, 2007b; Krienitz and Kotut, 2010). There have been few studies on the ecology of benthic diatom in Ethiopian Rift valley lakes (Gasse, 1986; Woldesenbet, 2019; Wondmagegn, 2019). However, compared with other East African Rift Valley lakes, only a few data are available on diatoms of saline lakes in Ethiopia (e.g. Gasse, 1986). Previous studies on Lake Shala have focused on the primary productivity, algal biomass and water chemistry (Talling et al., 1973; Baumann et al., 1975; Wood and Talling, 1988; Kebede et al., 1994; Gebre-Mariam, 2002) and on the taxonomic identification and classification of the phytoplankton species, with limited studies, i.e., Ogato (2015), focusing on the relationships between physico- chemical variables and phytoplankton. However, the physicochemical variable-dependent diatom distributions have not been well-studied in Lake Shala and associated hot-springs. Accordingly, the present study focuses on patterns of benthic diatom community structure in relation to environmental (chemical and physical) and spatial factors in this alkaline saline environment. Lake Shala is one of the East African Soda ecosystems and is fed by heated groundwater rising from deep aquifers along established fault lines (Grant and Jones, 2016). These hot springs and their drainage channels provide remarkable ecosystems and exhibit spatio-temporal variation in biotics with fascinating gradients of pH, salinity, dissolved oxygen (DO), electrical conductivity (EC) and temperature. The purpose of this work was to answer whether the diatom of Lake Shala and inflowing hot spring habitats differ or not; whereas the lakes are extreme in terms of increased salinity and pH, the hot springs show extreme temperatures. Material and methods Description of the study area: Lake Shala lies between 7°24’-7°33’N and 38°23’-38°39’E at altitudes of approximately 1558 m within the Abijata-Shala Lakes National Park, some 287 km south of Addis Ababa in the main Ethiopian Rift Valley. The lake is volcano-tectonic (WoldeGabriel et al., 2016) and found in the hydrologically closed system of the Ziway-Shala basin. Lake Shala is the deepest among the Ethiopian Rift valley lakes; it has approximately length of 28 km, 12 km width, and an average depth of 87 m (maximum 266 m), with a surface area of around 329 km2 and a vast catchment area (3920 km2) (von Damm and Edmond, 1984; Baxter, 2002). Lake Shala receives its water from River Adabat and Gidu (Baumann et al., 1975; Baxter, 2002). The lake is also surrounded by numerous hot springs of varying salinity, temperature, size and discharge rate, which feed the lake (Baxter, 2002). Lake Shala is characterized by a high pH, saline-alkaline conditions and high phosphate content, but with very low nitrogen levels (Ogato et al., 2014). Its water is rich in sodium (Na+), carbonate (CO3 2-), bicarbonate (HCO3 -) and chloride (Cl-), attributable to their presence in large concentrations in the trachytic and rhyolitic rocks of the Ethiopian Rift (Klemperer and Cash 2007), although they are poor in divalent cations (calcium [Ca2+] and magnesium [Mg2+]) (Ogato et al., 2014). The surface water temperatures 351 Int. J. Aquat. Biol. (2022) 10(5): 349-365 of Lake Shala range from 22 to 26oC (GebreMariyam, 2002). Despite its hostile nature, Lake Shala supports phytoplankton and is dominated by diatoms (Kebede et al., 1994) and cryptophytes (Ogato and Kifle, 2017). Lake Shala also supports sparse zooplankton communities and is dominated by rotifers such as Brachionus dimidiatus, B. pliciatilis and Hexarthra (Mengistou, 2016). The benthic macroinvertebrate community of the lake comprises Tubificidae, Ostracoda and Chironomidae (Tudorancea and Harrison, 1988). The lake supports a rich diversity of avifauna, mainly Pelicans and Lesser Flamingos inhabiting the lake and its volcanic island. Oreochromis niloticus and other small-sized fish such as Aplocheilichthys sp., were reported for the lake in 2002 (Golubtsov et al. 2002). Water physico-chemical analysis: Sampling for physicochemical parameters was carried out at the same time during diatom sampling. Dissolved oxygen, electrical conductivity, pH, and temperature were measured in situ with an HQ40d Hach Lange multi-meter. For nutrient analyses, water samples were filtered through Whatman GF/C) paper. Ammonium (NH4-N) was analyzed by the Indol- phenol blue method, Nitrate (NO3-N) was determined with the sodium-salicylate method and Nitrite (NO2-N) was analyzed based on the reaction between sulphanilamide and N-naphthyl-(1)- ethylendiamin-dihydrochloride (APHA, 1999). Soluble reactive phosphorus (SRP) was determined by the ascorbic acid method, while total phosphorus (TP) was determined by the ascorbic acid method after the persulfate digestion of unfiltered samples. Diatoms data collection: Benthic diatoms were collected from the onshore habitat of Lake Shala and inflowing hot springs during April, May, and July 2018. A total of four sampling sites were selected based on the nature of the lake and inflowing hot springs (Fig. 1). At each sampling station, diatoms were sampled by brushing stones with a toothbrush, following Kelly (2000). At least cobles (5-15 cm) sized stones were brushed and the resulting diatom suspensions were put in a small plastic bottle. The samples were preserved in ethanol (70%) and transported to Addis Ababa University, Limnology Laboratory. At the Laboratory, each diatom sample was acid cleaned with potassium permanganate Figure 1. Map of Lake Shala showing the study sites/sampling points. (Abbreviation: (SL: Shalla Lake; SHH1: Shalla Hora Hot spring 1; SHMH: Shalla Hora Mid Hot spring; SGH: Shalla Gike Hot spring). 352 Wagaw et al./ Diatom community structure in Lake Shala, Ethipoia (KMnO4) and hydrochloric acid (HCl) to oxidize organics and remove the carbonates (Cvetkoska et al., 2018). Diatom were identified to the species or to genus levels, when possible, sub species level using appropriate keys under an inverted Nikon microscope equipped with digital camera at a magnification of 200X and 400CX (Gasse, 1986; Komárek and Kling, 1991; Kelly, 2000; Komárek et al., 2003; Bellinger and Sigee, 2010). Statistical analysis: A nonparametric test, Kruskal- Wallis, analogous to analysis of variance (IBM SPSS Statistics 20) was used to compare means of physico- chemical parameters among the four sampling sites. The association between diatom species distribution and physicochemical variables was evaluated by canonical multivariate analysis using CANOCO for windows 4.5 version software (Ter Braak and Smilauer, 2002). Detrended correspondence analysis (DCA) was employed to check the response of the data, and it was found that the longest gradient (LG) length was 0.859. Therefore, Redundancy analyses (RDA) were used to elucidate the relationships between species assemblages and environmental variables. Diatom species with a total percent abundance <1% were not included in assessing the association between diatom taxa distribution and physicochemical variables. Results Physico-chemical parameters: A summary of spatial variations in physicochemical parameters of Lake Shala and its inflowing hot springs are shown in Figures 2 and 3. The highest mean values of pH (10.17) were recorded at Lake Shala (SL), while the lowest value was recorded at Shala Hora Hot-spring 1 (SHH1) and differences are significant between the stations (P<0.05). Dissolved oxygen (DO) values were within the range of 0.75-8.11 mg L-1 and showed some variability among the studying sites (P<0.05). Electrical conductivity (EC), salinity and total dissolved solids (TDS) across all studying stations were significantly different (P<0.05). EC varied from 26.74±3.8 mS cm-1 in SL to 5.67±7.8 mS cm-1 in SHH1. The highest conductivity mean value was recorded at SL (26.74 mS cm-1) and followed by SHMH (15.85 mS cm-1). Salinity and TDS showed a trend similar to that of conductivity and were significantly different (P<0.05) between the studied sites. Nutrient concentrations along the sampling stations are reported in Figure 3 and their distribution showed spatial heterogeneities with studying stations. NO3 -+NO2 - and NH3+NH4 + concentrations varied from 0 to 2.8 μg L-1 and from 0 to 4.15 μg L- 1, respectively and were insignificantly different among the stations (P>0.05). The mean value of soluble reactive phosphorus (SRP) ranged from 37 μg L-1 to 211.5 μg L-1. In SL, the concentration of SRP was greater and showed a significant difference (P<0.05). The distribution of total phosphate (TP) indicates that the levels of phosphate variations among the studied sites (P<0.05). Highest TP was recorded at SL (8165 μg L-1) and the lowest mean values were documented in SHMH (835 μg L-1). There was a significant difference in dissolved SiO2 between sampling stations (P>0.05). The lowest mean value of dissolved SiO2 (58.75 mg L -1) was recorded at SL and the highest at SGH (124.5 mg L- 1). Diatom composition and their relative abundance: Forty-five (45) identified diatom species from Lake Shala, and its associated hot springs are presented in Table 1. The number of taxa (species richness) among the samples ranges between 29 and 37. Highest taxa were recorded from SHMH (37) (Table 1). The taxa showed a clear gradient along the physicochemical variables and the number decreased to 36, 30 and 29 from SL, SHH1 and SGH, respectively. Dominant species in most of the samples were Anomoeoneis sphaerophora, Frustulia rhomboides, Nitzschia spp., Navicula spp., Epithemia frickei, E. operculata, Rhopalodia gibberula, R. rupestris and Achnanthes spp. Taking into account all samples, 20 (about 44.4%) diatom species such as Amphora spp., A. sphaerophora, Campylodiscus clpeus var bicostata, Cyclotella meneghiniana, Epithemia adnata, E. frickei, E. gibba, E. hyndmanii, 353 Int. J. Aquat. Biol. (2022) 10(5): 349-365 E. operculata, Frustulia rhomboides, Navicula spp., Nitzschia spp., Rhopalodia acuminata, R. acuminate Var. Protracta, R. brebissonii, R. gibberula, R. rupestris and Stephanodiscus spp. were common to the studied water bodies (Table 1, Fig. 4). Species that were exclusive to each sampling site were represented by a few individuals. Species found only in Lake Shala were Campylodiscus hibernicus, Cymatoppleura solea, Encynonema spp., Gomphonema spp. and Pleurosigma spp. While Species found only in Shala Hora Mid Hot spring (SHMH) were as follows: Epithemia turgida var. westermannii, Rhopalodia constrica and R. vermicularis. Distribution of diatom species in relation to physicochemical variables: The RDA showed that the first two axes sufficiently (96.5%) explained the cumulative percentage variance in the diatom species-environmental variables relation in studied sites (Fig. 5, Table 2). Figure 2. Spatial variation of physical environmental variables along the studied stations. (SL: Shalla Lake; SHH1: Shalla Hora Hot spring 1; SHMH: Shalla Hora Mid Hot spring; SGH: Shalla Gike Hot spring; Tep: Temperature; DO: Dissolved Oxygen; TDS: Total Dissolved Solids) (Values with different letters (a, b, c, d) within a column are significantly different at P< 0.05 level (Tukey test is applied)). 354 Wagaw et al./ Diatom community structure in Lake Shala, Ethipoia Figure 4. Venn diagram representing the number of diatoms that are unique and shared between the samples from 4 different sampling sites. (SL: Shalla Lake; SHH1: Shalla Hora Hot spring1; SHMH: Shalla Hora Mid Hot spring; SGH: Shalla Gike Hot spring. Figure 3. Spatial variation of inorganic nutrients along the studied stations. (SL: Shalla Lake; SHH1: Shalla Hora Hot spring 1; SHMH: Shalla Hora Mid Hot spring; SGH: Shalla Gike Hot spring; SRP: Soluble reactive phosphorus; TP: Total phosphorus) (Values with different letters (a, b, c, d) within a column are significantly different at P< 0.05 level (Tukey test is applied)). 355 Int. J. Aquat. Biol. (2022) 10(5): 349-365 The results indicated that pH was the most important environmental variable accounting for species distribution in the first axis. The distribution of diatom species was also positively correlated with EC, Salinity, TDS and DO in axis 1 and contributed 71.8% of the variance. Relative abundance of Anomoeoneis sphaerophora, Rhomboids operculata, Stenopterobia spp., Epithemia argus, Stephanodi- scus spp., E. frickei, E. hyndmanii, E. adnata, Amphora spp., Campylodiscus clpeus var bicostata, Navicula spp., Cyclotella. meneghiniana and Achnanthes spp. had a strong positive association Diatom Species Relative abundances (%) All Stations SL SHH1 SHHM SGH Achnanthes spp. 4.2 - 6 5.8 4.3 Amphora spp. 2.0 1.5 3.5 1.8 1.9 Anomoeoneis sphaerophora 15.7 9.2 15.3 19.9 15.4 A. styriaca (Grunow) Hustedt 0.6 0.6 0.7 0.5 0.7 Campylodiscus clpeus var bicostata W. Sm. 1.7 1.2 1.2 1.2 2.6 C. hibernicus (Ehrenberg) 0.1 0.2 - - - Cyclotella iris Brun & Héribaud 0.7 1.6 2 - - C. meneghiniana Kützing 3.0 3.4 3.2 2 4.8 Cyclotella spp. 2.3 - 4.3 3.6 - Cymatoppleura solea (Brébisson) W. Smith 0.1 0.2 - - - Cymbella spp. 0.3 0.1 0.3 0.3 0.6 Diatoma spp. 0.2 0.2 0.3 0.2 - Epithemia adnata (Kützing) Brébisson 2.5 1.7 3.3 2.6 2.6 E. argus (Ehrenberg) Kützing 1.7 1.3 - 2.3 2.4 E. argus var. alpestris (W. Smith) Grunow 0.2 - - 0.4 - E. frickei Krammer 3.8 2.5 3.3 5 3.3 E. hyndmanii W. Smith 1.7 0.9 0.7 2.7 1.9 E. smithii Carruthers 0.6 0.6 - 1.1 - E. sorex var. gracilis Hustedt 0.2 - - 0.4 0.6 E. turgida (Ehrenberg) Grunow 0.3 - - 0.3 1.3 E. turgida var. westermannii (Ehrenberg) Grunow 0.1 - - 0.3 - Encynonema spp. 0.1 0.2 - - - Encyonopsis microcephala (Grunow) Krammer 0.4 0.9 - 0.4 0.4 Eunotia spp. 0.3 0.4 0.3 0.3 - Frustulia rhomboids (Ehrenberg) De Toni 5.6 3.6 10.4 3.8 8.2 Gomphonema spp. 0.1 0.6 - - - Hantzschia spp. 0.4 0.5 0.5 0.4 - Melosira ambigua (Grun.) Müller 0.5 0.4 1 - 1.7 Navicula spp. 5.4 2 7.3 6.8 4.6 Nitzschia spp. 9.1 18.3 8.5 5.6 4.6 Pinulariaa spp. 0.3 0.4 0.7 - 0.4 Pleurosigma spp 0.1 0.5 - - - Rhopalodia acuminata Krammer 7 9.2 7.1 5.2 8.4 R. acuminate Var. Protracta (Grunow) 2.3 3.1 1.8 2 2.6 R. brebissonii Krammer 1.7 2.8 2.7 0.7 1.5 R. constrica (W. Smith) Krammer 0.1 - - 0.2 - R. gibba (Ehrenberg) O. Müller var. gibba 2.1 2.9 0.7 2.3 1.9 R. gibberula 7.8 13.1 6.8 5.9 5.6 R. operculata (Agardh) Håkansson 7.3 7.4 3.2 7.9 10.4 R. rupestris (W. Smith Krammer) 3.3 5.4 2.3 2.4 3.7 R. vermicularis (O. Müller) 0.1 - - 0.4 - Surirella ovalis Brébisson 0.3 - 0.5 0.3 0.7 Surirella turgida W. Smith 0.7 0.4 - 1 0.9 Stenopterobia spp. 1.4 1.2 0.7 2.3 - Stephanodiscus spp. 1.7 1.5 1.7 1.7 2 Total no. Species 36 30 37 29 Table 1. List of the 45 diatom taxa identified in the Lake Shalla and inflowing hot springs. 356 Wagaw et al./ Diatom community structure in Lake Shala, Ethipoia Figure 5. Redundancy Analyses (RDAs) Triplots showing the relationship between diatoms Communities, environmental parameters and sites (show with different color). Diatom Species Relative abundances (%) All Stations SL SHH1 SHHM SGH Achnanthes spp. 4.2 - 6 5.8 4.3 Amphora spp. 2.0 1.5 3.5 1.8 1.9 Anomoeoneis sphaerophora 15.7 9.2 15.3 19.9 15.4 A. styriaca (Grunow) Hustedt 0.6 0.6 0.7 0.5 0.7 Campylodiscus clpeus var bicostata W. Sm. 1.7 1.2 1.2 1.2 2.6 C. hibernicus (Ehrenberg) 0.1 0.2 - - - Cyclotella iris Brun & Héribaud 0.7 1.6 2 - - C. meneghiniana Kützing 3.0 3.4 3.2 2 4.8 Cyclotella spp. 2.3 - 4.3 3.6 - Cymatoppleura solea (Brébisson) W. Smith 0.1 0.2 - - - Cymbella spp. 0.3 0.1 0.3 0.3 0.6 Diatoma spp. 0.2 0.2 0.3 0.2 - Epithemia adnata (Kützing) Brébisson 2.5 1.7 3.3 2.6 2.6 E. argus (Ehrenberg) Kützing 1.7 1.3 - 2.3 2.4 E. argus var. alpestris (W. Smith) Grunow 0.2 - - 0.4 - E. frickei Krammer 3.8 2.5 3.3 5 3.3 E. hyndmanii W. Smith 1.7 0.9 0.7 2.7 1.9 E. smithii Carruthers 0.6 0.6 - 1.1 - E. sorex var. gracilis Hustedt 0.2 - - 0.4 0.6 E. turgida (Ehrenberg) Grunow 0.3 - - 0.3 1.3 E. turgida var. westermannii (Ehrenberg) Grunow 0.1 - - 0.3 - Table 2. List of the 45 diatom taxa identified in the Lake Shalla and inflowing hot springs. 357 Int. J. Aquat. Biol. (2022) 10(5): 349-365 with pH and positively correlated with EC, salinity, TDS and DO while NO3 -+NO2 -, NH3+NH4 +, SiO2 and TP showed a negative association in axis 1. Nitzschia spp., Rhopalodia gibberula and R. rupestris were strong and positively correlated with pH (0.86), EC (0.99), TDS (0.99), Sal (0.99) DO (1) and TP (0.99) and showed negative association with Tep (-0.98), NO3 -+NO2 - (-0.27), NH3+NH4 + (-0.23) and SiO2 (-0.30) in axis 2 (Table 2). Nitzschia spp., Rhopalodia gibberula, R. rupestris R. acuminata R. acuminata Var Protracta, Cyclotella meneghiniana and R. gibba are representative taxa in Lake Shala abundantly (SL) (Fig. 5). These taxa typically occurred in habitats with high specific EC, salinity, TDS, DO, pH and TP. The diatom assemblage in Shala Hora Mid Hot- spring (SHMH) had intermediate EC, salinity, TDS, DO, pH and TP mean values and was represented by Anomoeoneis sphaerophora, Epithemia frickei, E. hyndmanii, E. argus, E. adnata, Stenopterobia spp, Cyclotella spp, Rhopalodia operculata, Campylodiscus clypeus, Achnanthes spp., Amphora spp., Navicula spp. and Frustulia rhomboids. Discussion Spatial physico-chemical dynamics in Lake Shala and its associated hot springs: There has been significant interest in finding life in extreme environments with high temperatures, salinity and pH like hot springs and soda lakes. Hence, this is the first report on the investigation of diatom diversity and community structure at different physico- chemical factors of Ethiopian Saline-alkaline Lake Shala and inflowing hot springs. This ecological study aimed to examine the influence of the spatial variations in the environmental variables on the diatom distribution within Lake Shala and its inflowing hot springs. The value of high pH, salinity, EC and TDS Diatom Species Relative abundances (%) All Stations SL SHH1 SHHM SGH Encynonema spp. 0.1 0.2 - - - Encyonopsis microcephala (Grunow) Krammer 0.4 0.9 - 0.4 0.4 Eunotia spp. 0.3 0.4 0.3 0.3 - Frustulia rhomboids (Ehrenberg) De Toni 5.6 3.6 10.4 3.8 8.2 Gomphonema spp. 0.1 0.6 - - - Hantzschia spp. 0.4 0.5 0.5 0.4 - Melosira ambigua (Grun.) Müller 0.5 0.4 1 - 1.7 Navicula spp. 5.4 2 7.3 6.8 4.6 Nitzschia spp. 9.1 18.3 8.5 5.6 4.6 Pinulariaa spp. 0.3 0.4 0.7 - 0.4 Pleurosigma spp 0.1 0.5 - - - Rhopalodia acuminata Krammer 7 9.2 7.1 5.2 8.4 R. acuminate Var. Protracta (Grunow) 2.3 3.1 1.8 2 2.6 R. brebissonii Krammer 1.7 2.8 2.7 0.7 1.5 R. constrica (W. Smith) Krammer 0.1 - - 0.2 - R. gibba (Ehrenberg) O. Müller var. gibba 2.1 2.9 0.7 2.3 1.9 R. gibberula 7.8 13.1 6.8 5.9 5.6 R. operculata (Agardh) Håkansson 7.3 7.4 3.2 7.9 10.4 R. rupestris (W. Smith Krammer) 3.3 5.4 2.3 2.4 3.7 R. vermicularis (O. Müller) 0.1 - - 0.4 - Surirella ovalis Brébisson 0.3 - 0.5 0.3 0.7 Surirella turgida W. Smith 0.7 0.4 - 1 0.9 Stenopterobia spp. 1.4 1.2 0.7 2.3 - Stephanodiscus spp. 1.7 1.5 1.7 1.7 2 Total no. Species 36 30 37 29 Table 2. Continued. 358 Wagaw et al./ Diatom community structure in Lake Shala, Ethipoia recorded in the studied Lakes Shala and inflowing hot-springs did reach previously reported in saline alkaline lakes of East Africa (Talling et al., 1973; Melack et al., 1982; Wood and Talling, 1988; Kebede et al., 1994; Talling and Lemoalle, 1998) and inflows hot springs (Mpawenayo and Mathooko, 2004; Owen et al., 2004). Saline alkaline nature of these soda lakes is further influenced by the heterogeneous surficial geology characteristic, climate and hydrology of the region (Legesse et al., 2004). East African Soda lakes are characterized by high concentrations of carbonate salts, especially sodium carbonate and related salt complexes (Wood and Talling, 1988; Kebede et al., 1994). They also contain high concentrations of sodium chloride and other dissolved salts, making them saline-alkaline lakes (Gebre-Mariam, 2002; Klemper and Cash, 2007). During the present investigation, the mean pH values were significantly different over the studied sites. The highest mean values of pH (10.17) were recorded in Lake Shala surface waters, with these high values indicating the influence of potential photosynthetic activity and increased salinity concentrations, both possible causes of alkaline conditions (Talling, 2011). While lower mean pH value recorded in hot springs might be due to less concentration of sodium and carbonate species in the cation and anion-dissolved solutes, respectively. This was supported by the results, which found that the majority of lakes and hot springs of soda lakes in the Kenyan rift valley (Grant and Jones, 2016; Salano et al., 2017). However, the relationship between pH and other factors is complex, being influenced by chemical and biological processes (Hammer, 1986; Williams, 1998). Dissolved oxygen levels were significantly lower in hot spring sites with a mean value ranging between 0.75-3.73 mg L-1. The observed higher amount of DO in the Lake Shala site is probably related to the activities of photosynthetic organisms. Lower oxygen concentrations in hot springs may arise from the high rate of respiration by decomposers such as bacteria and fungi that anchor the gravel and small rocks of the hot springs (Renaut et al., 2008; Grant and Jones, 2016; Salano et al., 2017). Extremely high microbial load within the Great East Africa Rift Valley soda lakes is described by Lanzen et al. (2013) and Grant and Jones (2016). Wood et al. (1984) also suggested the depletion of DO in tropical soda lakes by algal biomass decomposition and high microbial activity. Although salinity, EC and TDS were significantly different across the studied sites, they show considerable strong gradients from hot springs with lower salinity, TDS and EC or diffuse groundwater inflows along the shores towards the lake with higher mean values. High mean values of salinity (14.21 g L-1), EC (26.74 mS cm-1) and TDS (11.7 g L-1) in Lake Shala could be associated with the accumulation of solutes that originate from rain falling directly on the surface of the lake and drainage basin, weathering reactions between runoff and groundwater, hydrothermal fluids and their interactions with subsurface rocks (Baumann et al., 1975; Von Damm and Edmond, 1984; Ayenew and Legesse, 2007). Similarly, East African soda lakes inflowing hot spring water also show considerably lower salinity, EC and TDS than soda lakes; for example, the salinity of Elmentaita and Bogoria hot springs have been recorded between 1.6-2.3 g L-1 and 3.5-3 g L-1, respectively. While in Lake Elmentaita (3.8-4.6 g L-1) and Lake Bogoria (10-20 g L-1), the surface water salinity was higher (Krienitz and Schagerl, 2016). Ogato (2015) also reported the low concentration of salinity (4.5 g L-1) and conductivity (8.2 mS cm-1) of inflowing hot springs around Lake Shala. Concentrations of soluble and largely inorganic forms of the element’s nitrogen, phosphorus and silicon were surveyed and significantly different in the four sampling sites. Nitrogen limitation has been suggested for some other tropical African soda lakes (Melack et al., 1982; Wood and Talling, 1988; Kebede et al., 1994; Talling and Lemoalle, 1998). In the present study, nitrate and ammonia-nitrogen were less and not detected in Lake Shala and inflowing hot springs, which is an indication of 359 Int. J. Aquat. Biol. (2022) 10(5): 349-365 nitrifying bacteria occurrence. High diversity and abundance of ammonia and nitrite-oxidizing organisms are widely distributed and responsible for low nitrogen levels in African soda lakes (Sorokin, 1998; Grant and Jones, 2000; Grant and Jones, 2000; Sorokin et al., 2001; Grant, 2006). However, in SHH1 higher concentration of the NO3 -+NO2 - (2.8 μg L-1) and NH3+NH4 + (4.15 μg L-1) was recorded. The possible reason could be the visitors of livestock around the hot springs which cause considerable inputs of nitrogenous wastes. The concentration of phosphorus was quite high in the lake and inflowing hot springs and was significantly different between sites. High mean soluble reactive phosphate (SRP) and total phosphate (TP) concentrations were recorded in Lake Shala. There is a general trend of increasing phosphate content concentration with increasing salinity and conductivity. This result is nearly comparable with the work done in Ethiopian inland waters by Wood and Telling (1998). The significant variations in these factors could be attributed to the specific abiogenic and biogenic transformations (Wood and Telling, 1998), the predominance of phosphate mineral-rich rocks (Talling and Talling, 1965), and the release from the anoxic water column (Oduor and Schagerl, 2007b). High total phosphate and soluble reactive phosphate concentrations are also reported in East African saline-alkaline lakes (Melack et al., 1982; Kalff, 1983; Oduor and Schagerl, 2007b). In the present study, silicate concentration significantly varied between the sites. Previously the concentration of SiO2 in Lake Shala (56 mg L -1) (Kebede et al., 1994) and the main hot springs located on the shore of Lake Shala (64.8 mg L-1) (Ogato, 2015) were reported. However, the mean concentration SiO2 observed in the present study is remarkably high in hot springs. The contributor could be silicate soils, porous volcanic lavas and the enhanced dissolution of solid silicates in saline waters of high alkalinity and pH (Wood and Telling, 1998). The silicate concentration of Lake Shala in this study (58.75 mg L-1) was comparable with the value (56) reported by Kebede et al. (1994) and (49.55) reported by Gebre-Mariam (2002). The silicate concentration is notably low in Lake Shala, indicating the dominance of diatoms in the lake. Several studies on tropical African lakes (Hecky, 1993; Gebre-Mariam, 2002) reported the association of depletion with the abundance of diatoms. Wood and Talling (1988) and Kebede et al. (1994) suggested that SiO2 could be significantly removed from the solution in Lake Shala, which was dominated by diatoms. Diatom community structure in Lake Shala and hot springs: The extremely inhospitable conditions in alkaline, saline lakes mean that the biodiversity in these systems is limited to organisms with special adaptations to survive such extreme conditions (Matagi, 2004). In the present study, forty-five diatom taxa were identified from Lake Shala and its inflowing hot spring with Rhopalodiaceae (9 taxa) and Epithemiaceae (9) being best represented. The most abundant species were A. sphaerophora, Nitzschia spp., R. acuminata, R. gibberula, R. operculata, Navicula spp. and F. rhomboids. This is in agreement with earlier studies done in alkaline, saline habitat which reported Anomoeoneis, Rhopalodia, Nitzschia and Epithemia to be the most dominant (Hecky and Kilham 1973; Gasse et al., 1983; Mpawenayo and Mathooko, 2004; Owen et al., 2004) in contrast with the reported dominance of algal biomass by Spirulina platensis (Blue-green algae, Cyanobacteria) in alkaline-saline lakes Ethiopia and Kenya (Talling et al., 1973; Harper et al., 2003; Ballot et al., 2004; Oduor and Schagerl, 2007a). The dominance of Anomoeoneis, Rhopalodia, Nitzschia and Epithemia species in these harsh environments can be attributed to their ability to withstand extreme water conditions like very high temperatures, pH and salinity. There was a difference in the taxa number and individual abundance of diatoms among the sampling sites. Low taxon number and individual abundance were recorded in SGH (29) and SHH1 (30). This might be due to the special physical features of the habitat, such as high temperature and 360 Wagaw et al./ Diatom community structure in Lake Shala, Ethipoia low dissolved oxygen; living in such ecosystems has tolerated and adapted to this hostile environment. Owen et al. (2004) also argue that the hot spring’s low diversity values are due to extreme environmental conditions. Contrary, the highest number of diatom species (37) were recorded at SHMH and this might be due to the exchange and contact of the lake organisms with the surrounding hot spring because depending on the Lake Shala water level and wave, this hot spring area can be covered by lake water, which enables direct exchange of organisms. Even minor changes in the lake water level can impact the ecology of the hot springs and adjacent habitats (Renaut et al. 2008, 2013), impacting species diversity (Krienitz et al., 2005). Diatoms have complex spatial dynamics within aquatic ecosystems (Cvetkoska, 2018). Numerous researchers (e.g., Gasse et al., 1983; Hecky and Kilham, 1973; Mpawenayo and Mathooko, 2004; Owen et al., 2004) have demonstrated different diatom assemblages across a range of different alkaline habitats. Differences in diatom community structure among the studding site were investigated and there were dissimilarities in the diatom communities in Lake Shala and its inflowing hot springs. Similarly, Owen et al. (2004) and Mpawenayo and Mathooko (2004) reported variations in the diatom populations in Lake Bogoria, Lake Elmentaita and their inflowing hot springs. During the current investigation, several diatom species, e.g., A. sphaerophora, Nitzschia spp., R. gibberula, R. operculata, R. acuminata, Navicula spp., F. rhomboids, C. meneghiniana, E. adnata and E. frickei, occurred across a range of physico-chemical variables, suggesting that most species have high tolerance ranges of environmental conditions. Distribution of diatom in relation to physico- chemical variables: Numerous studies conducted the influence of physico-chemical and nutrient variables on diatom communities and have shown the importance of water pH and related variables (e.g., salinity, alkalinity, conductivity) as main drivers structuring diatom communities (Gasse et al., 1983; Hecky and Kilham, 1973; Smol and Stoermer, 2010). In the present study, RDA analysis demonstrated that the diatom community structure of Lake Shala and inflowing hot springs was highly influenced by pH and also to some extent by EC, DO, Salinity, TDS and SRP in axis 1, which explained 96.5% of the variance in diatom community composition. Moreover, the analyses indicated strong spatial variability, highlighting the importance of the different environmental factors in structuring the benthic diatom community, which could largely be attributed to variations in physico- chemical features and used as an indicator of lake development, erosion, alkalinization, acidification, salinization, climate change, and especially eutrophication. According to Hecky and Kilham (1973) and Gasse et al. (1983), the distribution of diatom species is essentially influenced by salinity and conductivity. Diatoms in Lake Shala and inflowing hot springs were affected by salinity and nutrients as indicated by the RDA (Fig. 6), with Owen et al. (2004) and Mpawenayo and Mathooko (2004) reporting similar findings. Owen et al. (2004) highlighted the effect of variations in physico-chemical variables of soda lakes and their inflowing hot springs on diatom communities. This result was consistent with a study in East African Soda (e.g. Gasse et al., 1983; Hecky and Kilham, 1973; Mpawenayo and Mathooko 2004; Owen et al., 2004). Conclusion Marked variability in Physico-chemical features was observed among the studying sites in Lake Shala and its inflowing hot springs. This variation was related to inter-site differences in geomorphic and hydrological characteristics, resulting in uneven diatom species distribution. A total of 45 diatom taxa were identified, of which 20 (about 44.4%) diatom species were common across the study area. This indicates that the studied hot springs of soda lakes in Ethiopia are important niches that harbor an unexpectedly high richness of diatom species. The 361 Int. J. Aquat. Biol. (2022) 10(5): 349-365 most abundant species were A. sphaerophora, Nitzschia spp., R. acuminata, R. gibberula, R. operculata, Navicula spp. and F. rhomboids, suggesting high tolerance ranges of environmental conditions. Therefore, the findings in this study will be of high significance in the field of phycology and provide initial insight into the diatom distribution from the soda Lake Shala and hot springs; future studies should expand the spatial and temporal scale by including the whole lake and its hot springs area. References APHA. (1999). Standard methods for the examination of water and waste water, American Public Health Association, American water works Association, Water Environment Federation, Washington, D.C. Ayenew T., Legesse D. (2007). The changing face of Ethiopian rift lakes and their environs: call of the time. Lakes and Reservoirs: Research and Management, 12: 149-165. Ballot A., Krienitz L., Kotut K., Wiegand C., Metcalfe J.S., Codd G.A., Pflugmacher S. (2004). Cyanobacteria and cyanobacterial toxins in three alkaline Rift Valley lakes of Kenya-Lakes Bogoria, Nakuru and Elmenteita. Journal of Plankton Research, 26: 925-935. Bate G.C., Adams J.B., Van Der Molen J.S. (2002). Diatoms as indicators of water quality in South African river systems. WRC Report No 814/1/02.Water Research Commission, Pretoria. Baumann A., Forstner U., Rodhe R. (1975). Lake Shala water chemistry, mineralogy and geochemistry of sediments in an Ethiopian rift lake. Geologische Rundschau, 64: 593-609. Baxter R.M. (2002). Lake morphology and chemistry. In: Tudorancea C, Taylor WD (eds) Ethiopian Rift Valley lakes. Backhuys Publishers, Leiden: 45-60 Borchardt. 1996 p. Bellinger E.G., Sigee D.C. (2010). Freshwater algae: identification and use as bioindicators. John Wiley and Sons, Ltd, Chichester. 118 p. Borchardt M.A. (1996). Nutrients. In: R.J. Stevenson, M.L. Bothwell, R.L. Lowe (Eds.). Algal Ecology. Academic Press, San Diego. pp: 183-227. Carvalho L., Bennion H., Dawson H., Furse M., Gunn I., Hughes R., Johnston A., Maitland P., May L., Monteith D., Luckes S., Taylor R., Trimmer M., Winder J. (2002). Nutrient conditions for different levels of ecological status and biological quality in surface waters (Phase I). R&D Technical Report P2- 260/4. Environmental Agency, Bristol. pp: 8-15. Cvetkoska A., Pavlov A., Jovanovska E., Tofilovska S., Blanco S., Ector L., Cremer C.F., Levkov Z. (2018). Spatial patterns of diatom diversity and community structure in ancient Lake Ohrid. Hydrobiologia, 819: 197-215. Gasse F., Talling J.F., KIlham P. (1983). Diatom assemblages in East Africa: classification, distribution and ecology. Revue d'Hydrobiologie Tropicale (France), 16(1): 3-34. Gebre-Mariam Z. (2002). The effect of wet and dry seasons on the concentrations of solutes and phytoplankton biomass in seven Ethiopian Rift Valley lakes. Limnologica, 32: 169-179. Golubtsov A.S., Dgebuadze Y.Y., Mina M.V. (2002). Fishes of the Ethiopian rift valley. In: Tudorancea C, Taylor WD (eds). Ethiopian rift valley lakes, Biology of inland water series. Backhuys, Leiden. pp: 167-258. Grant W.D. (2006). Alkaline environments and biodiversity. In: Extremophiles (Gerday, E.C. and Glansdorff, N., eds). UNESCO, EOLSS Publishers (http//www.eolss.net), Oxford, UK. Grant W.D., Jones B.E. (2000). Alkaline environments. In: J. Lederberg (Ed.) Encyclopaedia of microbiology, vol 1, 2nd edn. Academic, New York. pp: 126-133. Grant W.D., Jones B.E. (2016). Bacteria, Archaea and Viruses of Soda Lakes. In: M. Schagerl (Ed.). Soda Lakes of East Africa. Springer International Publishing Switzerland. pp: 97-147 Hammer T.U. (1986) Saline Lake ecosystems of the world. Dr. W. Junk, Dordrecht. Harper D.M., Childress R.B., Harper M.M., Boar R.R., Hickley P., Mills S.C., Otieno N., Drane A., Vareschi E., Nasirwa O., Mwatha W.E., Darlington J.P.E.C., Escute Gasulla X. (2003). Aquatic biodiversity and saline lakes: Lake Bogoria, National Reserve, Kenya. Hydrobiologia, 500: 259-276. Hecky R.E. (1993). The eutrophication of Lake Victoria. Limnologie: Verhandlungen, 25(1): 39-48. Hecky R.E., Kilham P. (1973). Diatoms in alkaline, saline lakes: ecology and geochemical implications. Limnology Oceanography, 18: 53-71. Kalff J. (1983). Phosphorus limitation in some tropical African lakes. Hydrobiologia, 100: 101-112. Kebede E., Gebre-Mariam Z., Ahlgren I. (1994). The 362 Wagaw et al./ Diatom community structure in Lake Shala, Ethipoia Ethiopian Rift Valley lakes: chemical characteristics of a salinity-alkalinity series. Hydrobiologia, 288: 1- 12. Kelly M. (2000). Identification of common benthic diatoms in rivers. Field Studies, 9: 583-700. Klemperer S.L., Cash M.D. (2007). Temporal geochemical variation in Ethiopian Lakes Shala, Arenguade, Awasa, and Beseka: possible environmental impacts from underwater and borehole detonations. Journal of Africa Earth Sciences, 48: 174- 198 Komárek J., Kling H.J. (1991). Variation in six planktonic cyanophyte genera in Lake Victoria (East Africa). Algological. Studies, 61: 21- 45. Komárek J., Kling H.J., Komárková J. (2003). Filamentous cyanobacteria. In: D.J. Wehr, R.G. Sheath, (Eds.). Freshwater algae of North America, ecology and classification. Academic Press, Massachusetts. pp: 117-191. Krienitz L., Kotut K. (2010). Fluctuating algal food populations and the occurrence of lesser flamingos (Phoeniconaias minor) in three Kenyan Rift Valley Lakes. Journal of Phycology, 46: 1088-1096. Krienitz L., Mahnert B., Schagerl M. (2016). Lesser Flamingo as a Central Element of the East African Avifauna. In: M. Schagerl (Ed.). Soda Lakes of East Africa. Springer, Switzerland. pp: 259-284. Kumssa T., Bekele A. (2014). Feeding ecology of Lesser Flamingos (Phoeniconaias minor) in Abijata-Shalla Lakes National Park (ASLNP) with special reference to lakes Abijata and Chitu, Ethiopia. Asian Journal of Biological Sciences, 7(2): 57-65. Lanzen A., Simachew A., Gessesse A., Chmolowska D., Jonassen I., Øvreås, L. (2013). Surprising prokaryotic and eukaryotic diversity, community structure and biogeography of Ethiopian soda lakes. PLoS One, 8(8): e72577. Legesse D., Christine V.C., Gasse F.C. (2004). Analysis of the hydrological response of a tropical terminal lake, Lake Abiyata (Main Ethiopian Rift Valley) to changes in climate and human activities. Hydrological Processes, 18(3): 487-504. Matagi S.V. (2004). A biodiversity assessment of the flamingo lakes of eastern Africa. Biodiversity, 5(1): 13-26. Melack J.M., Kilham M.P., Fisher T.R. (1982). Responses of phytoplankton to experimental fertilization with ammonium and phosphate in an African soda lake. Oecologia, 52(3): 321-326. Mengistou S. (2016). Invertebrates of East African soda lakes. In: Soda Lakes of East Africa. Springer. pp: 205-226. Mpawenayo B., Mathooko J.M. (2004). Diatom assemblages in the hotsprings associated with Lakes Elmenteita and Baringo in Kenya. African Journal Ecological, 42: 363-367. Oduor S.O., Schagerl M. (2007a). Phytoplankton photosynthetic characteristics in three Kenyan Rift Valley saline-alkaline lakes. Journal of Plankton Research, 29: 1041-1050. Oduor S.O., Schagerl M. (2007b). Temporal trends of ion contents and nutrients in three Kenyan Rift Valley saline-alkaline lakes and their influence on phytoplankton biomass. Hydrobiologia, 584: 59-68. Ogato T. (2015). Dynamics of phytoplankton and physicochemical features of the Ethiopian soda lakes Chitu and Shala, and evaluation of the potential of their waters for the production of Arthrospira (Spirulina) fusiformis (Cyanophyceae) in laboratory cultures. PhD Thesis, Addis Ababa University, Addis Ababa. 172 p. Ogato T., Kifle D. (2017). Phytoplankton composition and biomass in tropical soda Lake Shala: seasonal changes in response to environmental drivers. Lakes and Reservoirs: Research and Management, 22(2): 168-178. Ogato T., Kifle D., Lemma B. (2016). Algal composition and biomass in the tropical soda lake Chitu with focus on seasonal variability of Arthrospira fusiformis (Cyanophyta). Marine and Freshwater Research, 67(4): 483-491. Ogato T., Kifle D., Fetahi T., Sitotaw B. (2014). Evaluation of growth and biomass production of Arthrospira (Spirulina) fusiformis in laboratory cultures using waters from the Ethiopian soda lakes Chitu and Shala. Journal of Applied Phycology, 26(6): 2273-2282. Owen R.B., Renaut R.W., Hover V.C., Ashley G.M., Muasya A.M. (2004). Swamps, springs and diatoms: wetlands of semi-arid Bogoria-Baringo Rift, Kenya. Hydrobiologia, 518: 59-78. Renaut R.W., Owen R.B., Ego J.K. (2008). Recent changes in geyser activity at Loburu, Lake Bogoria, Kenya Rift Valley. GOSA Transactions, 10: 4-7. Renaut R.W., Owen R.B., Jones B., Tiercelins J.J., Tarits C., Ego J.K., Konhauser K.O. (2013). Impact of lake- 363 Int. J. Aquat. Biol. (2022) 10(5): 349-365 level changes on the formation of thermogene travertine in continental rifts: evidence from Lake Bogoria, Kenya Rift Valley. Sedimentology, 60: 428- 468. Salano O.A., Makonde H.M., Kasili R.W., Nyawira W.L., Nawiri M.P., Boga H.I. (2017). Diversity and distribution of fungal communities within the hot springs of soda lakes in the Kenyan rift valley. African Journal of Microbiology Research, 11(19): 764-775. Smol J.P., Stoermer E.F. (2010). The diatoms. Applications for the environmental and earth sciences, 2nd edn. Cambridge University Press, Cambridge. 667 p. Sorokin D.Y. (1998). Occurrence of nitrification in extremely alkaline natural habitats. Microbiology, 67: 404-408. Sorokin D.Y., Tourova T.P., Schmid M., Wagner M., Koops H.P., Kuenen J.G., Jetten M. (2001). Isolation and properties of obligately chemolithoautotrophic and extremely alkali-tolerant ammonia-oxidizing bacteria from Mongolian soda lakes. Archives of Microbiology, 176(3): 170-177. Talling J.F. (2011). Some distinctive subject contributions from tropical Africa to fundamental science of inland waters. Inland Waters, 1: 61-73. Talling J.F. Lemoalle J. (1998). Ecological dynamics of tropical inland waters. Cambridge University Press, Cambridge. 441 p. Talling J.F., Wood R.B., Prosser M.V., Baxter R.M. (1973). The upper limit of photosynthetic productivity by phytoplankton: evidence from Ethiopian soda lakes. Freshwater Biology, 3: 53-76 Ter Braak C. J., Smilauer P. (2002). CANOCO reference manual and CanoDraw for Windows user's guide: software for canonical community ordination (version 4.5). Wageningen: www. canoco. com. Tudorancea C., Harrison A.D. (1988). The benthic communities of the saline lakes Abijata and Shala (Ethiopia). Hydrobiologia, 158: 117-123. Von Damm K.L., Edmond J.M. (1984). Reverse weathering in the closed-basin lakes of the Ethiopian Rift and Lake Turkana. American Journal of Sciences, 284: 835-862. Williams W.D. (1998). Salinity as a determinant of the structure of biological communities in salt lakes. Hydrobiologia, 381: 191-201. WoldeGabriel G, Olago D., Dindi E., Owor M. (2016). Genesis of the East African Rift System. In: (M. Schagerl (Ed.). Soda Lakes of East Africa. Springer, Switzerland. pp: 25-59. Wood R., Baxter R., Prosser M. (1984). Seasonal and comparative aspects of chemical stratification in some tropical crater lakes, Ethiopia. Freshwater Biology, 14(6): 551-573. Wood R.B., Talling J.F. (1988). Chemical and algal relationships in a salinity series of Ethiopian inland waters. Hydrobiologia, 158: 29-67. Woldesenbet A. (2019). Assessment of the biotic integrity and water quality of Lake Ziway using benthic macroinvertebrate and diatom based multimetric index. Ph.D. Thesis. Addis Ababa University, Addis Ababa, Ethiopia. 196 p. Wondmagegn T. (2019). Water quality assessment of Lake Hawassa, Ethiopia, using macroinvertebrate and diatom based multimetric index. Ph.D. Thesis. Addis Ababa University, Addis Ababa, Ethiopia. 214 p. Material and methods Despite its hostile nature, Lake Shala supports phytoplankton and is dominated by diatoms (Kebede et al., 1994) and cryptophytes (Ogato and Kifle, 2017). Lake Shala also supports sparse zooplankton communities and is dominated by rotifers such as Brac... Water physico-chemical analysis: Sampling for physicochemical parameters was carried out at the same time during diatom sampling. Dissolved oxygen, electrical conductivity, pH, and temperature were measured in situ with an HQ40d Hach Lange multi-meter... Diatoms data collection: Benthic diatoms were collected from the onshore habitat of Lake Shala and inflowing hot springs during April, May, and July 2018. A total of four sampling sites were selected based on the nature of the lake and inflowing hot s... Statistical analysis: A nonparametric test, Kruskal-Wallis, analogous to analysis of variance (IBM SPSS Statistics 20) was used to compare means of physico-chemical parameters among the four sampling sites. The association between diatom species distr... Results Physico-chemical parameters: A summary of spatial variations in physicochemical parameters of Lake Shala and its inflowing hot springs are shown in Figures 2 and 3. The highest mean values of pH (10.17) were recorded at Lake Shala (SL), while the lowe... Nutrient concentrations along the sampling stations are reported in Figure 3 and their distribution showed spatial heterogeneities with studying stations. NO3-+NO2- and NH3+NH4+ concentrations varied from 0 to 2.8 μg L-1 and from 0 to 4.15 μg L-1, res... Diatom composition and their relative abundance: Forty-five (45) identified diatom species from Lake Shala, and its associated hot springs are presented in Table 1. The number of taxa (species richness) among the samples ranges between 29 and 37. High... Distribution of diatom species in relation to physicochemical variables: The RDA showed that the first two axes sufficiently (96.5%) explained the cumulative percentage variance in the diatom species-environmental variables relation in studied sites (... The results indicated that pH was the most important environmental variable accounting for species distribution in the first axis. The distribution of diatom species was also positively correlated with EC, Salinity, TDS and DO in axis 1 and contribute... Discussion Diatom community structure in Lake Shala and hot springs: The extremely inhospitable conditions in alkaline, saline lakes mean that the biodiversity in these systems is limited to organisms with special adaptations to survive such extreme conditions (... Distribution of diatom in relation to physico-chemical variables: Numerous studies conducted the influence of physico-chemical and nutrient variables on diatom communities and have shown the importance of water pH and related variables (e.g., salinity... Conclusion References