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~ 110 ~ International Journal of Fisheries and Aquatic Studies 2020; 8(1): 110-

~ 110 ~ International Journal of Fisheries and Aquatic Studies 2020; 8(1): 110-121 E-ISSN: 2347-5129 P-ISSN: 2394-0506 (ICV-Poland) Impact Value: 5.62 (GIF) Impact Factor: 0.549 IJFAS 2020; 8(1): 110-121 © 2020 IJFAS www.fisheriesjournal.com Received: 19-11-2019 Accepted: 21-12-2019 Lambert Niyoyitungiye (1) Department of Life Science and Bioinformatics, Assam University, Silchar, Assam State, India (2) Department of Environmental Science and Technology, Faculty of Agronomy and Bio Engineering, University of Burundi, Bujumbura, Po Box.2940, Burundi Anirudha Giri Department of Life Science and Bioinformatics, Assam University, Silchar, Assam State, India Bhanu Prakash Mishra Department of Environmental Science, Mizoram University, Aizawl, Mizoram State, India Corresponding Author: Lambert Niyoyitungiye (1) Department of Life Science and Bioinformatics, Assam University, Silchar, Assam State, India (2) Department of Environmental Science and Technology, Faculty of Agronomy and Bio Engineering, University of Burundi, Bujumbura, Po Box.2940, Burundi Quantitative and qualitative analysis of phytoplankton population in relation to environmental factors at the targeted sampling stations on the Burundian littoral of Lake Tanganyika Lambert Niyoyitungiye, Anirudha Giri and Bhanu Prakash Mishra Abstract The present study was conducted at 4 sampling sites of Lake Tanganyika and was intending to identify and estimate the spatial abundance of phytoplankton in relation to physico-chemical attributes. The species composition analysis of the samples has listed 115 species of phytoplanktons belonging to 7families from all sampling sites. The relative diversity index of families has indicated that Bacillariophyceae is the most dominant family in comparison to others families with 50 species (43.4%) followed by the family Chlorophyceae with 31 species (27%). The family Cyanophyceae was found very scarce with 3species (2.6%). Regarding quantitative data, the results of species richness and the Cumulative abundance of the sampling sites showed that phytoplankton species and density were variable among stations. Rumonge site holds first position with 115species which was the maximum of all species identified comprising 3450 individuals per liter followed by Kajaga site with 107species comprising 2482individuals per liter, then Mvugo site with 101species containing 1506individuals per liter and in the last position was Nyamugari site with 86 species comprising1031individuals per liter. Furthermore the results of Canonical Correlation Analysis (CCorA) between the environmental parameters and phytoplankton composition at sampling sites have shown that the abundance and proliferation of some phytoplankton species are negatively or positively affected by the physico-chemical parameters concentration because, some physico-chemical variables were found either inhibitors or accelerators for phytoplankton species growth. Keywords: Phytoplankton, quantitative and qualitative analysis, physico-chemical attributes, Lake Tanganyika 1. Introduction Considered as the basic component of an aquatic food chain, Phytoplanktons are the source of oxygen and the main autochthonous primary producers of all types of water bodies [1]. Phytoplanktons constitute the basis of nutrient cycle of an ecosystem; hence play an important role in maintaining equilibrium between living organisms and abiotic factors [2]. Since phytoplanktons are the primary producers forming the first trophic level of food chain in aquatic system, the qualitative and quantitative studies are of great importance to assess the water quality [3-6]. Their standing crops and their species composition show the water quality in which they are growing [7]. Phytoplanktons are the producers, the basis of the aquatic ecosystem and therefore are sought as the main component of any freshwater system. They play an important role in solving various environmental problems, production of useful substances and understanding the aquatic ecosystem [8]. As species composition of phytoplanktons community changes in response to the environmental variations [9], a thorough knowledge of phytoplankton abundance and its quality in relation to environmental condition is essential for fish culture. The dominance, community structure and seasonality of phytoplankton in tropical wetlands are strongly variable and are depending on nutrient status, morphometry of the underlying substrate, water level and other regional factors [10-12]. Phytoplankton is the main biological elements used to assess the ecological status of surface water bodies and the change in biotic parameters and gives a good indication of energy turnover in aquatic environments, due to its sensitivity to any change in the environment [13, 14], ~ 111 ~ International Journal of Fisheries and Aquatic Studies http://www.fisheriesjournal.com Many authors emphasized the importance of phytoplankton as Bioindictors in different aquatic systems [15-17]. Both the qualitative and quantitative abundance of plankton in a water body are of great importance for imposing sustainable management policies as they vary from location to location and aquatic systems in the same place and with similar ecological conditions [18]. Little or no studies on water quality and phytoplankton diversity and abundance in Lake Tanganyika have been done. Hence the present study was undertaken to assess the phytoplankton community at selected stations of Lake Tanganyika in relations to environmental variables. 2. Materials and Methods 2.1 Study area The data collection on fish species and water sample for laboratory analyses was carried out at 4 sampling sites (Kajaga, Nyamugari, Rumonge and Mvugo) belonging to the Burundian Littoral. The Table1 and Figure1 show the geographical location of the study areas: Table 1: Geographical location of the study sites Study sites Geographical Location Province Commune Longitude-East Latitude-South Altitude Kajaga Bujumbura Rural Buterere 029° 17’ 56’’ 03° 20’ 55’’ 783 m Nyamugari Bujumbura Rural Kabezi 029° 20’ 24’’ 03° 30’ 27’’ 776 m Rumonge Rumonge Rumonge 029° 26’ 03’’ 03° 58’ 23’’ 767 m Mvugo Makamba Nyanza-Lac 029° 34’ 06’’ 04° 17’ 42’’ 810 m Fig 1: Map of the study area showing sampling sites 2.2 Collection of water samples for physico-chemical analysis The field data collection has lasted 3months (January, February and March, 2018). The water sample for Physical and chemical analyzes was collected using plastic containers in the morning time. Temperature, Electrical conductivity, pH and dissolved oxygen have been measured in-situ using electrometric method (conductivity meter and pH-meter) while the remaining parameters were determined in Laboratory using the standard methods [19, 20]. The methods adopted for water quality analysis and the used instruments are listed in the Table2: ~ 112 ~ International Journal of Fisheries and Aquatic Studies http://www.fisheriesjournal.com Table 2: Analytical methods adopted to determine quality of lake water Parameters Methods Equipments Turbidity (NTU) Turbidity tube method Turbiditimeter, Turbidity tube or Nephelometer Temperature Temperature sensitive probe Mercury thermometer Total Dissolved Solids Evaporation method, Electrometric, and Gravimetric method Conductivity meter Transparency Secchi Disk Visibility Method Secchi disk pH, Electrical Conductivity Electrometric Method pH-meter, Conductivity meter Dissolved Oxygen Alsterberg Azide Modification of the Winkler’s Method. Dissolved Oxygen meter Total hardness, Calcium and Magnesium EDTA Titration Method - Chlorides Titration by AgNO3, Mohr’s method. - BOD 5 days incubation at 20 0C followed by titration BOD Incubator Total alkalinity Titration by H2SO4 - COD Digestion followed by titration COD Digestor Total Carbon, Total Nitrogen Titrimetric method - Total.Phosphorous Digestion and ascorbic acid Spectrophotometric Method Spectrophotometer Iron, Lead, Cadmium, Chromium, Copper, Selenium, Arsenic. Atomic Absorption Spectrophotometric Method Spectrophotometer 2.3 Collection of water samples for Phytoplankton identification Water sample was collected from the surface in the morning time. 100 liters of the collected water were filtered through a cloth net of mesh size 63 μm and diameter 16cm. The final volume of the filtered sample was 125ml and was preserved by adding 5ml of 4% formalin solution and kept for 24 hours undisturbed to allow the sedimentation of phytoplankton organisms. After 24 hours, the supernatant was removed carefully using pipette and the final volume of concentrated sample ready for analysis was 50ml. For both qualitative and quantitative analysis, Phytoplanktons were identified by observation under light microscope compounds in species and family level using identification keys as per Mpawenayo [21]. The species belonging to each group were recorded and the number of individuals in each species was counted. The number of organisms was expressed as total organisms per liter using the formula according to Lackey’s drop method. 2.4 Species biodiversity measurement Specific richness (S), Relative diversity index of family, Shannon Wiener Index (H ') (1949) and Pielou's evenness index (1966) (E) have been used for measuring Alpha diversity while Beta diversity was measured using Jaccard Index [22] and Sorensen Index [23]. Indeed: I. The Specific richness (S) is the simplest measure of biodiversity and provides simply the total number of species recorded on a site and its ecological value is therefore limited [24]. Two species richness indices are widely used: Margalef’s diversity index (Dma) = (S-1) / ln N and Menhinick's diversity index (Dme) = S / √N, Where: N = the total number of individuals in the sample, S = the total number of species recorded. II. The relative diversity index of family= 100 * (nef / Nte) and represents the number of species in a family over the total number of species, multiplied by 100. It is expressed as a percentage, Where: nef = number of species in a family; Nte = total number of species in the sample. III. Shannon-Weaver Index (1949) represents the average information provided by a sample on the stand structure from which the sample originates and how individuals are distributed among different species [25]. It is the most commonly used index in ecology [26-29] as it considers both abundance and species richness. It is uploads/Ingenierie_Lourd/ pdf-lambert-memoire-facagro-ub-etude-comparative-de-l-effet-des-systemes-d-elevage-sur-les-performances-zootechniques-des-caprins-de-race-locale-et-croises-boer-dans-la-region-naturelle-de-buyen 1 .pdf