Plankton community structure diversity indices and similarity relationship with reference to industrial wastewater pollution by using correspondence analysis

THAI NGUYEN UNIVERSITY THAI NGUYEN UNIVERSITY OF AGRICULTURE AND FORESTRY ADVANCED EDUCATION PROGRAM TRAN THI MINH HA PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING CORRESPONDENCE ANALYSIS BACHELOR THESIS JANUARY – 2015 THAI NGUYEN UNIVERSITY THAI NGUYEN UNIVERSITY OF AGRICULTURE AND FORESTRY ADVANCED EDUCATION PROGRAM BACHELOR THESIS PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING CORRESPONDENCE ANALYSIS Student Name: Student ID: Year: Tran Thi Minh Ha DTN1053110064 2010 – 2015 Supervisors: Dr.-Phil Arinafril Dr Ho Ngoc Son JANUARY - 2015 TABLE OF CONTENTS I Introduction 1.1 Rationale of the study 1.2 Aims of the study 1.3 Research questions II Literature review 2.1 Introduction to water 2.1.1 The importance of water 2.1.2 Water quality 2.2 Plankton community 2.3 Impact of wastewater in plankton community III Methodology 12 3.1 Collection and sample 14 3.1.1 Place and time 14 3.1.2 Materials and Equipments 14 3.1.3 Plankton samplings 15 3.1.4 Water samplings 15 3.2 Tools and Identification process 15 3.2.1 Tools 15 3.2.2 Identification plankton process 16 3.2.3 Water analysis 16 3.3 Data analysis 19 IV Results and Discussion 20 I 4.1 Results of water analysis in stations 20 4.2 Biodiversity Indices Measurement 25 4.3 Similarity relationship with reference to industrial wastewater pollution by using Correspondence Analysis 32 4.4 Diversity indices 35 V Conclusions and recommendations 40 5.1 Conclusions 40 5.2 Further research 40 II ABBREVIATIONS BOD : Biochemical Oxygen Demand COD : Chemical Oxygen Demand DO : Dissolved Oxygen TSS : Total Suspended Solids SNI : Indonesia national standard PDAM : Drinking Water Company Installation III LIST OF FIGURES Figure 1: Musi River 12 Graph 1: The distribution of planktons on stations in the first observation 34 Graph 2: The distribution of planktons on stations in the second observation 35 IV LIST OF TABLES Table 1: Water analysis in soy sauce industry 20 Table 2: Water analysis in Crumb rubber 21 Table 3: Water analysis in Ship dock 22 Table 4: Water analysis in Drinking Water Company Installation 23 Table 5: Water analysis in Cement Company 24 Table 6: Water analysis in Stock pile 25 Table 7: Planktons in Soy Sauce 26 Table 8: Planktons in Crumb Rubber 26 Table : Planktons in Ship Dock 27 Table10: Planktons in PDAM 28 Table 11: Planktons in Cement Company 29 Table 12: Planktons in Stockpile 29 Table 13: Observation 30 Table 14: Observation 31 Table 15: Diversity Indices 37 Table 13: The first observation Table 14: the second observation V Thai Nguyen University of Agriculture and Forestry Degree Program : Bachelor of Environmental Science and Management Student name: Tran Thi Minh Ha Student ID: DTN 1053110064 Thesis Title: PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING CORRESPONDENCE ANALYSIS Supervisors : Dr.-Phil Arinafril Dr Ho Ngoc Son ABSTRACT Pollution of surface water in any parts of the world becomes one of the most important environmental problems we are facing nowadays Many studies showed that polluted water can deteriorate and degrade water quality and then become limiting factor for the use of water for many purposes Planktons are the main the primary producers which can be easily found in all kinds of water bodies Plankton community is firstly influenced and involved in water pollution As planktons are very sensitive to the chemicals in water, the functions of planktons as the food source for many aquatic animals restrict The present study focused on phytoplankton species composition in Musi River, Palembang, Indonesia, where alongside the river many industries were hosted Two water and plankton samplings were carried out to collect planktons from six selected sites or stations, i.e soy sauce industry, crumb rubber industry, ship dock, regional drinking water company, cement industry and coal stockpile from VI November 7, 2014 to November 16, 2014.The physicochemical parameters were Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), pH and Total Suspended Solids (TSS) The study also included Biochemical Oxygen Demand (BOD5) The result showed that at every station the population community of planktons varied Several planktons were found at one station, and were not found at the other stations For the first observation the number of plankton species found was 22, but for the second observation was 39 species The most abundant planktons found were Ankistrodesmus acicularis (Monoraphidium aciculare) and Ankistrodesmus angustus with 150 individuals and 83 individuals, respectively, for first observation, and Ankistrodesmus acicularis, Striatella interrupta, Koliella Longiseta with 300, 217 and 166 individuals, respectively, for second observation The study concluded that discharged wastewater from industries contributed significant effect on the plankton community Keywords: Planktons; Water Quality, Wastewater, Physicochemical parameters, Biological parameter Number of pages: 50 pages Date of submission: January 15 , 2015 VII PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING CORRESPONDENCE ANALYSIS I Introduction 1.1 Rationale of the study Planktons are composed of phytoplankton and zooplankton which are typically found near the surface in aquatic environments Planktons form the most sensitive components of the ecosystems Phytoplankton plays a vital role in primary production They also play an important role as food for herbivorous animals (Reddy, et al., 2013) Zooplankton plays an essential role in water ecosystems including river The planktonic animals take part in the transformation and circulation of organic matter (Ejsmont-Karabin et al., 2004), regulate the biomass of phytoplankton (Lair, 2005; Kentzer et al., 2010) and provide food for fish, especially for their larval stages and for fish fry (Pourriot et al., 1997) Furthermore, the phytoplankton serves as a producer in the food chain Their productivity depends upon the quality of water Many species of zooplankton are primary consumers and feed on phytoplankton, thus playing an important role in energy and transfer In a water ecosystem, the diversity of phytoplankton can influence the diversity of zooplankton, or vice versa and both can be affected by the environment factors (Chou et al., 2011) Companies which produce goods and directly discharge wastewater to the river are responsible for disturbance and diversity of plankton In fact, water quality is a strong determinate of phytoplankton and zooplankton dynamics, as well as diversity in aquatic system (Nasrollahzadeh et al., 2008; Ramdani et al., 2009) eutrophication levels and resulted in inconsistent and confusing patterns (Arhonditsis et al.,1998) These indices exclusively express the richness and variety of natural ecological communities (diversity indices), the equitability of species abundance in the sample/community (evenness), or emphasize the role of the most important species (dominance) (Washington,1984) Apparently, the multi-component nature of the similarity indices formulations, incorporating most of the above information along with the divergence of these structural characteristics from the baseline conditions, enables the identification of even small quantitative or qualitative differences in the trophic status (Arhonditsis, et al ,2003) The first is the Shannon-Weiner Species Diversity Index is calculated by taking the number of each species, the proportion each species is of the total number of individuals, and sums the proportion times the natural log of the proportion for each species Since this is a negative number, we then take the negative of the negative of this sum The higher the number, the higher is the species diversity In the ideal situation, one should compare populations that are the same size in numbers of individuals (Nolan, et al., 2005) It is explained by the formula: H = -∑ (Pi * ln Pi) where, H = the Shannon diversity index Pi = fraction of the entire population made up of species i (proportion of a species i relative to TOTAL number of species present, not encountered) 36 S = numbers of species encountered On this experiment, Shannon index is a diversity index of species present in the stations in Musi River The second is Berger-Parker’s index This index expresses proportional importance of most abundant species This index was proposed by (Berger and Parker, 1970) and developed by (May, 1975) With simple calculation = d (James and Danoff-Burg, 2003) The formula: d= Nmax/N The reciprocal of Berger-parker Index is commonly used An increase in 1/d corresponds to an increase in diversity and a decrease in dominance (McDonald, et al.,2010) The third is Pileou’s index Species evenness refers to how close in numbers each species in an environment area Mathematically it is defined as a diversity index, a measure of biodiversity which quantifies how equal the community is numerically (Mulder et al., 2004) Table 15: Diversity Indices Station Crumb rubber Soy sauce Ship dock PDAM Cement Stockpile 2 2 2 Individuals 268 117 117 166 67 101 84 353 169 269 68 210 Dominance_D 0.13 0.30 0.30 0.18 0.37 0.33 0.28 0.13 0.12 0.18 0.25 0.12 Shannon _H 2.17 1.28 1.28 1.75 1.05 1.25 1.34 2.32 2.16 1.87 1.39 2.21 Eveness 0.88 0.89 0.89 0.96 0.95 0.87 0.95 0.78 0.97 0.82 0.91 37 Shannon’s index Table 15 showed that in the first observation the highest diversity belonged to Soy sauce with 2.17 and the lowest diversity belonged to ship dock with 1.05 In the second observation the highest diversity belonged to PDAM with 2.32, vice versa was ship dock with 1.25 Indeed, ship dock was a station which was least diversity in all stations To answer this question, water analysis results could show it It was very clearly that Total Suspended Solids (TSS) in ship dock (50.8) exceeded standard compared with PDAM and soy sauce It means water quality in ship dock was dirtier than other stations Ship dock was an area which discharged oil, paints, wastewater with high concentration of heavy metals and some toxins such as lead, iron, etc, this toxic directly affects to planktons and organism in River Berger-Parker’s index Ship dock illustrated dominance of phytoplankton and zooplankton with 37 and 33 percent perspective follow the first and the second observation which most of species could find in this station However, cement was less abundant with approximate 20 percent of species which could find in here Evenness (Pileou’s index) In the first observation, evenness belonged to Stock pile with and it also belonged to Crumb rubber in the second time with 0.97 On 16 November 2014 when the second samples were taken, the night before had a heavy rain, it changed water qualities Some parameters were changed, so evenness was different in times However, in stock pile station, concentration of BOD5 was exceeded in the first observation with 3.25 compared standard and in Crumb Rubber, COD was 15 mg/l compared with 10 mg/l standard COD and BOD5 exceeded that mean 38 concentration of organic and inorganic in water also surpassed standard On this condition, some species had same environmental condition could adapt and develop but the others are not It means all activities in 6stations were caused the different diversity of plankton communities in Musi River 39 V Conclusions and recommendations 5.1 Conclusions From this study it could be concluded that there is relationship between the plankton community structure and water quality parameters based on physicochemical and biochemical parameters The relationship was determined with reference to industrial wastewater pollution Results from the study showed that activities of several industries alongside Musi River influenced the diversity of planktons as the result of deterioration or degradation of water quality The most concentration appearence of Helicostomella sp and Nitzschia brebissonii in PDAM or Diatoma anceps in Cement company showed the different diversity indices of planktons in different stations in Musi River However, the wastewater discharged into the river which was still adapted with existence of planktons The diverse and convergence of the plankton numbers have likely resulted in the observed stations which could have increased pressure factors, such as wastes dumped direct to the river from domestic and industrial wastes without any treatments 5.2 Further research Research was conducted in a short time between November 7, 2014 and November 16, 2014 It could not show differently in plankton community structure in a long time which changes from dry season to rain season Furthermore, parameters were analyzed which were still limitations in BOD5 , COD, TSS, pH and DO The limitation of 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50 Ankistrodesmus angustus 33 B fragillaria crotonensis Stock PDAM Cement 33 0 33 17 0 0 17 17 Diatoma ancepts 0 0 17 Diatoma vulgareR 17 0 0 Gloeotrichia echinulata 0 0 17 Helicostomella sp 0 17 0 Hemidinium nasulum 0 0 17 Koliella longiseta 17 17 0 0 Lobomonas ampla 17 0 0 Melosira granulate 0 17 0 Mesostigma viride 17 0 0 Nitzschia brebissonii 0 33 17 Rhizosolema spp 0 17 17 17 17 0 0 Scenedesmus acuminatus 17 0 0 Skujaella thiebauti 0 0 17 17 Striatella interrupta 0 0 17 17 Synchaeta sp 0 0 17 Tetraedron minimum 33 0 0 33 17 0 0 0 0 33 Species Ankistrodesmus acicularis (Monoraphidium aciculare) Rhodomonas lacustris var nannoplanktica Trachychloron circulate (Xanthophyceae) Trichocerca longiseta Source: fields data pile Table 14: the second observation Stations Species A.fragillaria crotonensis Ankistrodesmis fusiformis Ankistrodesmus acicularis Ankistrodesmus angustus Aphanocapsa grevillei Brachionus calyciflorus Pallas Cerataulina bergonii Chromulina ovalis Diatoma anceps Ditylum brightwellii (West) Douchetia maculate Elakatothrix gelatinosa Euchlanis macrura Eutintinnus sp Gloeotrichia echinulata Gymnodinium lunula Koliella longiseta Mallomonas spp Merismopedia sp Mesostigma viride Netrium digitus Nitzchia acicularis Nitzchia palea Nitzschia brebissonii Ochromonas ludibunda Peridinium sp Pomphyolyx complanata Rhincalanus nasutus Rhizosolema spp Scenedesmus acuminatus Schroederia setigera Stephanomia amphitridis Stichococcus bacillaris Striatella interrupta Synedra acus Synedra utermohlii Synura petersenii Trachychloron circulare Trichocerca longiseta Soy Crumb Ship source rubber dock 0 0 17 17 50 50 33 33 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 17 0 50 33 0 0 33 17 33 0 0 0 17 17 0 0 17 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 33 0 17 50 0 0 0 0 Source: fields data PDAM Cement 0 83 0 17 17 17 33 17 17 0 17 0 17 0 33 17 17 17 50 17 17 100 0 0 17 17 67 0 0 17 0 17 17 17 0 50 17 0 0 67 0 0 0 0 67 0 17 17 Stock pipe 17 17 17 0 33 17 0 0 17 17 33 17 17 0 17 17 17 0 17 0 50 0 0 ... January 15 , 2015 VII PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING CORRESPONDENCE ANALYSIS I Introduction... AGRICULTURE AND FORESTRY ADVANCED EDUCATION PROGRAM BACHELOR THESIS PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING. .. data 31 4.3 Similarity relationship with reference to industrial wastewater pollution by using Correspondence Analysis In each station plankton could not find the same because each plankton has different