(Luận văn) 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 lu an n va p ie gh tn to PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING CORRESPONDENCE ANALYSIS d oa nl w an lu ll u nf va BACHELOR THESIS oi m z at nh z m co l gm @ an Lu JANUARY – 2015 n va ac th si THAI NGUYEN UNIVERSITY THAI NGUYEN UNIVERSITY OF AGRICULTURE AND FORESTRY ADVANCED EDUCATION PROGRAM BACHELOR THESIS lu an n va p ie gh tn to PLANKTON COMMUNITY STRUCTURE, DIVERSITY INDICES, AND SIMILARITY RELATIONSHIP WITH REFERENCE TO INDUSTRIAL WASTEWATER POLLUTION BY USING CORRESPONDENCE ANALYSIS d oa nl w Tran Thi Minh Ha DTN1053110064 2010 – 2015 Student Name: Student ID: Year: ll u nf va an lu Dr.-Phil Arinafril oi m Supervisors: z at nh Dr Ho Ngoc Son z m co l gm @ an Lu n va JANUARY - 2015 ac th si 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 lu an 2.1.1 The importance of water va n 2.1.2 Water quality tn to 2.2 Plankton community gh p ie 2.3 Impact of wastewater in plankton community nl w III Methodology 12 d oa 3.1 Collection and sample 14 lu nf va an 3.1.1 Place and time 14 3.1.2 Materials and Equipments 14 lm ul 3.1.3 Plankton samplings 15 z at nh oi 3.1.4 Water samplings 15 3.2 Tools and Identification process 15 z gm @ 3.2.1 Tools 15 co l 3.2.2 Identification plankton process 16 m 3.2.3 Water analysis 16 an Lu 3.3 Data analysis 19 va IV Results and Discussion 20 n ac th I si 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 lu an n va p ie gh tn to d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th II si 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 lu an n va p ie gh tn to d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th III si 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 lu an n va p ie gh tn to d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th IV si 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 lu an Table 6: Water analysis in Stock pile 25 n va Table 7: Planktons in Soy Sauce 26 tn to Table 8: Planktons in Crumb Rubber 26 gh p ie Table : Planktons in Ship Dock 27 nl w Table10: Planktons in PDAM 28 d oa Table 11: Planktons in Cement Company 29 lu nf va an Table 12: Planktons in Stockpile 29 Table 13: Observation 30 lm ul Table 14: Observation 31 z at nh oi Table 15: Diversity Indices 37 Table 13: The first observation z m co l gm @ Table 14: the second observation an Lu n va ac th V si 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 lu an Supervisors : Dr.-Phil Arinafril va n Dr Ho Ngoc Son tn to ABSTRACT gh p ie Pollution of surface water in any parts of the world becomes one of the most nl w important environmental problems we are facing nowadays Many studies showed d oa that polluted water can deteriorate and degrade water quality and then become lu nf va an 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 lm ul of water bodies Plankton community is firstly influenced and involved in water z at nh oi pollution As planktons are very sensitive to the chemicals in water, the functions of planktons as the food source for many aquatic animals restrict z gm @ The present study focused on phytoplankton species composition in Musi River, co l Palembang, Indonesia, where alongside the river many industries were hosted Two m water and plankton samplings were carried out to collect planktons from six an Lu selected sites or stations, i.e soy sauce industry, crumb rubber industry, ship dock, va regional drinking water company, cement industry and coal stockpile from n ac th VI si 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 lu an were Ankistrodesmus acicularis (Monoraphidium aciculare) and Ankistrodesmus n va angustus with 150 individuals and 83 individuals, respectively, for first observation, tn to and Ankistrodesmus acicularis, Striatella interrupta, Koliella Longiseta with 300, gh p ie 217 and 166 individuals, respectively, for second observation nl w The study concluded that discharged wastewater from industries contributed d oa significant effect on the plankton community nf va an lu Keywords: Planktons; Water Quality, Wastewater, Physicochemical parameters, z at nh oi Number of pages: 50 pages lm ul Biological parameter Date of submission: January 15 , 2015 z m co l gm @ an Lu n va ac th VII si 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 lu sensitive components of the ecosystems Phytoplankton plays a vital role in primary an n va production They also play an important role as food for herbivorous animals tn to (Reddy, et al., 2013) Zooplankton plays an essential role in water ecosystems p ie gh including river The planktonic animals take part in the transformation and circulation of organic matter (Ejsmont-Karabin et al., 2004), regulate the biomass of w oa nl phytoplankton (Lair, 2005; Kentzer et al., 2010) and provide food for fish, d especially for their larval stages and for fish fry (Pourriot et al., 1997) an lu Furthermore, the phytoplankton serves as a producer in the food chain Their nf va lm ul productivity depends upon the quality of water Many species of zooplankton are z at nh oi primary consumers and feed on phytoplankton, thus playing an important role in energy and transfer In a water ecosystem, the diversity of phytoplankton can z influence the diversity of zooplankton, or vice versa and both can be affected by the @ l gm environment factors (Chou et al., 2011) Companies which produce goods and m co directly discharge wastewater to the river are responsible for disturbance and an Lu diversity of plankton In fact, water quality is a strong determinate of phytoplankton and zooplankton dynamics, as well as diversity in aquatic system (Nasrollahzadeh n va et al., 2008; Ramdani et al., 2009) ac th si 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 lu an divergence of these structural characteristics from the baseline conditions, n va enables the identification of even small quantitative or qualitative differences in tn to the trophic status (Arhonditsis, et al ,2003) gh p ie The first is the Shannon-Weiner Species nl w Diversity Index is calculated by taking the number of each species, the proportion d oa each species is of the total number of individuals, and sums the proportion times the lu nf va an 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 lm ul species diversity In the ideal situation, one should compare populations that are the z at nh oi same size in numbers of individuals (Nolan, et al., 2005) It is explained by the formula: z gm @ H = -∑ (Pi * ln Pi) co l where, m H = the Shannon diversity index an Lu Pi = fraction of the entire population made up of species i (proportion of a n ac th 36 va species i relative to TOTAL number of species present, not encountered) si 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 lu an corresponds to an increase in diversity and a decrease in dominance (McDonald, et n va al.,2010) to gh tn The third is Pileou’s index p ie Species evenness refers to how close in numbers each species in an nl w environment area Mathematically it is defined as a diversity index, a measure of d oa biodiversity which quantifies how equal the community is numerically (Mulder et lu nf va an al., 2004) Table 15: Diversity Indices lm ul Station 2 Individuals 268 117 117 166 67 101 Dominance_D 0.13 0.30 0.30 0.18 0.37 0.33 Shannon _H 2.17 1.28 1.28 1.75 1.05 1.25 Eveness 0.88 0.89 0.89 0.96 0.95 0.87 0.95 Stockpile 2 84 353 169 269 68 210 gm Cement 0.13 0.12 0.18 0.25 0.12 1.34 2.32 2.16 1.87 1.39 2.21 0.97 0.82 0.91 @ PDAM z Ship dock z at nh oi Crumb rubber Soy sauce 0.28 m co l 0.78 an Lu n va ac th 37 si 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 lu an was dirtier than other stations Ship dock was an area which discharged oil, paints, n va wastewater with high concentration of heavy metals and some toxins such as lead, tn to iron, etc, this toxic directly affects to planktons and organism in River gh p ie Berger-Parker’s index nl w Ship dock illustrated dominance of phytoplankton and zooplankton with 37 d oa and 33 percent perspective follow the first and the second observation which most lu nf va an of species could find in this station However, cement was less abundant with approximate 20 percent of species which could find in here lm ul Evenness (Pileou’s index) z at nh oi 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 z gm @ when the second samples were taken, the night before had a heavy rain, it changed co l water qualities Some parameters were changed, so evenness was different in m times However, in stock pile station, concentration of BOD5 was exceeded in the an Lu first observation with 3.25 compared standard and in Crumb Rubber, COD was 15 va mg/l compared with 10 mg/l standard COD and BOD5 exceeded that mean n ac th 38 si 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 lu an n va p ie gh tn to d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th 39 si 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 lu an concentration appearence of Helicostomella sp and Nitzschia brebissonii in PDAM n va or Diatoma anceps in Cement company showed the different diversity indices of tn to planktons in different stations in Musi River However, the wastewater discharged gh p ie into the river which was still adapted with existence of planktons The diverse and nl w convergence of the plankton numbers have likely resulted in the observed stations d oa which could have increased pressure factors, such as wastes dumped direct to the lu 5.2 Further research nf va an river from domestic and industrial wastes without any treatments lm ul Research was conducted in a short time between November 7, 2014 and z at nh oi 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, z gm @ parameters were analyzed which were still limitations in BOD5 , COD, TSS, pH and co l DO The limitation of parameters led to the lack of information about water quality m which directly affected to plankton communities So, research needs to open in a an Lu long time or several years and water analysis also need to analyze more parameters n va ac th 40 si References ARHONDITSIS G, KARYDIS M and TSIRTSIS G (2003): Analysis of Phytoplankton Community Structure Using Similarity Indices: A new methodology for discriminating among eutrophication levels in coastal marine ecosystems Department of marine science, University of the 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Environmental Protection Agency, Gulf Breeze, lu an Florida 32561 va n WEHR D.J (2002): Fresh water Algae of North America: Ecology and tn to Classification (pages 613, Institute of Applied Science gh p ie Zooplankton diversity in Philippine Lakes (FERNANDO, 1994, cited by nl w MAMARIL A C pp 81-93) Institute of Biology, College of Science, University d oa of the Philippines Diliman) lu diversity in Philippine Lakes (LAZZARO, 1987, cited by nf va an Zooplankton MAMARIL A C pp 81-93) Institute of Biology, College of Science, University z at nh oi lm ul of the Philippines Diliman) z m co l gm @ an Lu n va ac th 46 si APPENDICES I Images of planktons lu an Fig1.1 Helicostomella sp Fig 1.4 B.fragillaria crotonenis n va p ie gh tn to d oa nl w Fig 1.5 Striatella interrupta nf va an lu Fig 1.2 Nitzschia brebissonii z at nh oi lm ul z m co l gm @ an Lu Fig 1.3 Ankistrodesmus acicularis Fig 1.6 Koliella longiseta n va ac th si Fig 1.7 Ankistrodesmus angustus Fig 1.10 Trichocerca longiseta lu an n va p ie gh tn to d oa nl w nf va an lu lm ul Fig 1.8 Diatoma anceps Fig 1.11 Mesostigma viride z at nh oi z m co l gm @ n va ig 1.9 Gloeotrichia echimulata an Lu F ac th si APPENDICES II Table 13: The first observation Soy Crumb Ship sauce rubber dock 67 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 0 17 0 0 0 17 Koliella longiseta 17 17 0 0 Lobomonas ampla 17 0 0 Stations Melosira granulate 0 17 0 Mesostigma viride 17 0 0 0 0 33 17 0 17 17 17 0 0 0 0 0 0 17 17 0 17 17 0 17 0 0 0 33 Species Ankistrodesmus acicularis (Monoraphidium aciculare) lu an va Helicostomella sp pile n p ie gh tn to Hemidinium nasulum d oa nl w Nitzschia brebissonii Rhodomonas lacustris var 17 lm ul nannoplanktica nf va an lu Rhizosolema spp Striatella interrupta Synchaeta sp 0 Tetraedron minimum 33 33 17 0 0 l Source: fields data gm Trichocerca longiseta @ (Xanthophyceae) z Trachychloron circulate 0 an Lu m Skujaella thiebauti co 17 z at nh oi Scenedesmus acuminatus n va ac th si Table 14: the second observation Stations Species A.fragillaria crotonensis Ankistrodesmis fusiformis Ankistrodesmus acicularis Ankistrodesmus angustus lu an n va Aphanocapsa grevillei Brachionus calyciflorus Pallas Cerataulina bergonii Chromulina ovalis Diatoma anceps Ditylum brightwellii (West) Douchetia maculate Elakatothrix gelatinosa Euchlanis macrura Eutintinnus sp to Gloeotrichia echinulata p ie gh tn Gymnodinium lunula Koliella longiseta Mallomonas spp Merismopedia sp Mesostigma viride Netrium digitus d oa nl w z m co 17 67 0 0 17 0 17 17 17 0 50 17 0 0 67 0 0 0 0 67 0 17 17 an Lu n va ac th 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 l gm @ Synura petersenii Trachychloron circulare Trichocerca longiseta z at nh oi Synedra acus Synedra utermohlii lm ul Striatella interrupta nf va Stichococcus bacillaris 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 PDAM Cement an Nitzschia brebissonii Ochromonas ludibunda Peridinium sp Pomphyolyx complanata Rhincalanus nasutus Rhizosolema spp Scenedesmus acuminatus Schroederia setigera Stephanomia amphitridis lu Nitzchia acicularis Nitzchia palea 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 si