A Limnological Study of Factors Affecting Algal Biodiversity in the Hartbeespoort Dam By

A limnological study of factors affecting algal biodiversity in the Hartbeespoort Dam by

GUSTAVE OLOLO 920303106 MINOR DISSERTATION

Submitted in the partial fulfilment for the requirements for the degree

MAGISTER SCIENTIAE in AQUATIC HEALTH

FACULTY OF SCIENCE

UNIVERSITY OF JOHANNESBURG

Supervisor: Dr. Richard Greenfield Co-Supervisor: Prof. Victor Wepener

OCTOBER 2013

Acknowledgment

I would like to thank God almighty, the provider for everything He makes possible for me along this study period. I also would like to express my heartfelt appreciation to:  Dr. Richard Greenfield, my supervisor, for his assistance, academic guidance and motivational support throughout the duration of my studies.  Prof. Victor Wepener, my co-supervisor for his constant support, his advice, financial support and proof reading of my dissertation.

 The Faculty of Sciences, The Department of Zoology at the University of Johannesburg for the use of facilities and equipment.

 Mrs E. Fisher and Mr B.Rufaro (Spectrum) for their support during this project.

 My Fellow research colleagues, P. Nakarmi, S. Kanga, A. Lesiba, R. Gerber, R.Tate, O.T. Olubambi, V. Maboko, L. Kruger, N. Dumisile and L. Lungile for their help and academic support.  To my Family, for all their continuous support, love and for their belief in me.

 To my Beloved Daughter Avomo Ololo Rebecca Louisia.

 To my Dear Mother Andjolo Marie-Louise.

Table of Contents

Declaration ...... Error! Bookmark not defined.

Acknowledgment ...... 2

Table of Contents ...... 3

List of tables ...... 6

List of figures ...... 7

Abbreviations and Acronyms ...... 9

Glossary ...... 10

Abstract ...... 12

Chapter 1 Introduction ...... 13

1.1 Background ...... 13

1.2 Problem Statement and Hypothesis ...... 14

1.3 Aim and objective of the study ...... 15

Chapter 2 Literature Review ...... 16

2.1 Cyanobacteria ...... 16

2.2 Aquatic macrophytes ...... 18

2.3 Chlorophyll-a ...... 18

2.4 The process of eutrophication ...... 19

2.5 Environmental factors influencing algal bloom formation ...... 19

2.5.1 Temperature ...... 20

2.5.2 pH ...... 20

2.5.3 Turbidity and light penetration ...... 20

2.5.4 Nutrients ...... 21

2.6 The Harbeespoort Dam ...... 21

2.6.1 History, construction and usage ...... 21

2.6.2 Water quality ...... 22

Chapter 3 ...... 24

Materials and Methods ...... 24

3.1 Study area and Sampling points ...... 24

3.2 Physical parameters ...... 26

3.3 Nutrients analysis ...... 26

3.4 Metals in water and total suspended solids (TSS)...... 26

3.5 Chlorophyll-a quantification ...... 26

3.6 Algal identification and quantification ...... 27

3.7 Statistical analysis ...... 27

Chapter 4 Results and Discussion ...... 28

4.1 Physical water quality parameters ...... 28

4.1.1 Temperature ...... 28

4.1.2 Dissolved oxygen (DO)...... 30

4.1.3 Electrical conductivity (EC) ...... 32

4.1.4 Total suspended solids (TSS) ...... 34

4.1.5 pH values ...... 35

4.2 Chemical water quality parameters ...... 36

4.2.1 Total phosphorus ...... 37

4.2.2 Nitrate and nitrite ...... 39

4.2.3 Ammonium ...... 42

4.3 Trace metals ...... 44

4.4 Chlorophyll-a (Chl-a) quantification ...... 47

4.5 Phytoplankton population ...... 49

4.5.1 Cyanophyta (Blue green algae) ...... 50

4.5.1.1 Microcystis aeruginosa ...... 50 4.5.1.2 Anabeana sp...... 50 4.5.1.3 Oscillatoria sp...... 50 4.5.1.4 Arthrospira sp...... 51 4.5.1.5 Cylindrospermopsis sp...... 51 4.5.2 Chrysophyta (Yellow green algae) ...... 51

4.5.2.1 Melosira granulate ...... 51 4.5.2.2 Cyclotella sp...... 51 4.5.3 Chlorophyta (Green algae) ...... 51

4.5.3.1 Oocystis sp...... 51 4.5.3.2 Scenedesmus sp...... 51 4.5.3.3 Sprirogira sp...... 51 4.5.4 Crytophyta (Cryptomonads)...... 52

4.5.5 Pyrrophyta (Dinoflagellates) ...... 52

4.5.5.1 Ceratium sp...... 52 4.5.6 Euglenophyta ...... 52

4.5.6.1 Euglena sp...... 52 4.6 Multivariate statistical analysis for water quality variables ...... 53

4.6.1 Pearson product-moment correlation matrix ...... 53

4.6.2 Canonical Discriminant Functions Analysis (CDFA) ...... 55

Chapter 5 Conclusions and Recommendations ...... 58

5.1 Conclusions ...... 58

5.2 Recommendations ...... 59

References ...... 61

Appendix: ...... 67

List of tables

Table 1: Cyanobacterial toxins of the most dominant species in South Africa, and their functions and mechanisms of action. (Oberholster et al., 2008)...... 17

Table 2: Summary statistics of physical parameters measured in the Hartbeespoort Dam between February 2011 and March 2012...... 28

Table 3: Summary statistics of chemical water parameters and chlorophyll- a measured in the Hartbeespoort Dam between February 2011 and March 2012...... 36

Table 4: Summary statistics of trace metals and the corresponding TWQR values in the Hartbespoort Dam between February 2011 and March 2012...... 44

Table 5: Distribution in percentage of algal divisions and species in the Harbeespoort Dam between February 2011 and March 2012...... 49

Table 6: Pearson 2-tailed correlation matrix for physico-chemical parameters recorded in the Hartbeespoort Dam during the study period...... 54

List of figures

Figure 1: The Hartbeespoort Dam...... 14

Figure 2:Cyanobacteria:A) Anabeana sp.,B) Cylindrospermum sp.,C) Microcystis sp.,D) Oscillatoria sp.( www-cyanosite.bio.perdue.edu/images.html)...... 16

Figure 3: Chemical structure of microcystin-LR. (Carmichael, 1994)...... 18

Figure 4: The nutrient cycle within a water system, indicating the causes and consequences of eutrophication (DWAF, 2002)...... 19

Figure 5: Cyanobacterial bloom and water hyacinth massive growth in the Hartbeespoort Dam. (Venter, 2008)...... 22

Figure 6: Map of Hartbeespoort Dam showing the positions of the six sampling sites...... 25

Figure 7a: Spatial variation in water Temperature based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam...... 29

Figure 7b:Temperatures variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam...... 30

Figure 8a: Spatial variation in water dissolved oxygen based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam...... 31

Figure 8b: Dissolved oxygen variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam...... 32

Figure 9a: Spatial variations in water electrical conductivity based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam...... 33

Figure 9b: Electrical conductivity variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam...... 33

Figure 10: Spatial variations in surface water total suspended solids (TSS) in the Hartbeespoort Dam.34

Figure 11a: Spatial variations in water pH based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam...... 35

Figure 11b: pH variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam...... 36

Figure 12a: Spatial variations in water total phosphorus concentrations based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam...... 38

Figure 12b: Total phosphorus concentrations variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam...... 38

Figure 13a: Spatial variations in water nitrate and nitrite concentrations based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam...... 40

Figure 13b: Nitrate and nitrite concentrations variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam...... 41

Figure 14a: Spatial variations in water ammonium concentrations based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam...... 43

Figure 14b: Ammonium concentrations variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam...... 43

Figure 15: Spatial variations in surface water Chlorophyll-a concentrations in the Hartbeespoort Dam.48

Figure 16: Relationships between dissolved oxygen, temperature and chlorophyll-a variations during period in the Hartbeespoort Dam the study...... 49

Figure 17: Percentage algal groups and species abundances in the Harbeespoort Dam during the study period...... 53

Figure 18a: Temporal Canonical Discriminant Functions Analysis (CDFA1) based on water quality variables measured in the Hartbeespoort Dam...... 56

Figure 18b: Spatial Canonical Discriminant Functions Analysis (CDFA2) based on water quality variables measured in the Hartbeespoort Dam...... 57

Abbreviations and Acronyms AEV Acute effect value

ºC degrees Celsius

DO dissolved oxygen

DWAF Department of Water Affairs and Forestry

EC electrical conductivity km kilometre(s) km2 square kilometre(s) m metre(s) m3 Cubic metre(s) mg/l milligrams per litre ml millilitre(s) mm millimetre(s)

μg/l micro grams per litre

μS/m micro Siemens per meter

TSS total suspended solids

WHO World Health Organisation

WRC Water Research Commission

WW Water Wheel

Glossary:

Acidophilic: Microorganism or plant growing best in acidic conditions.

Alkalopiles: A class of extremophilic microbes capable of survival in alkaline environments, growing optimally around a pH of 10.

Alkalophilic: Microorganism or plant having a strong preference for alkaline conditions.

Aplanospores: Non-sexual spore that do not have motility. They are present in some genus of green algae and some fungi.

Autotrophic: An organism capable of synthesizing its own food from inorganic substances. It does this with the help of light or by using chemical energy

Barophilic: Living organism that grows best in conditions of high atmospheric pressure.

Bryophyta: A division of nonflowering plants characterized by rhizoids rather than true roots and having little or no organized vascular tissue and showing alternation of generations between gamete-bearing forms and spore-bearing forms.

Chlorophyta: A large division of chiefly freshwater eukaryotic algae that possess chlorophyll a and b, store food as starch, and cellulose cell walls.

Chromatophore: The organelle of photosynthesis in photosynthetic bacteria (as the cyanobacteria).

Cyanotoxins: Toxins produced by bacteria called cyanobacteria (also known as blue-green algae)

Epilimnion: The top-most layer in a thermally stratified lake, occurring above the deeper hypolimnion. It is warmer and typically has a higher pH and higher dissolved oxygen concentration than the hypolimnion.

Heterotrophic: An organism capable of exploiting reduced carbon compounds as energy sources, like carbohydrates, fats, and proteins from plants and animals.

Hypertrophic: Dam water condition excessively enriched by phosphate and nitrogen nutrients, where algal growth is.

Hyperscum: Crusted and buoyant cyanobacterial mats that are formed when floating cyanobacterial colonies drift and accumulate.

Hypolimnion: The dense, bottom layer of water in a thermally-stratified lake. It is the layer that lies below the thermocline.

Hypoxic: Condition of low oxygen in water body.

Microcystis: A genus of freshwater cyanobacteria which includes the harmful algal bloom Microcystis aeruginosa

Monomictic: Lakes that mix from top to bottom during one mixing period each year.

Planktonic algae: Floating microscope plants that are normal and essential inhabitants of sunlit surface waters

Psychrophilic: Extremophilic organisms those are capable of growth and reproduction in cold temperatures, ranging from −15°C to +10°C.

Pteridophyta: A division of nonflowering vascular plants that do not bear seeds.

Rhodophyta: A distinct eukaryotic lineage characterized by the accessory photosynthetic pigments phycoerythrin, phycocyanin and allophycocyanins arranged in phycobilisomes, and the absence of flagella and centrioles.

Spermatophyta: Commonly known as the seed plants. The most obvious characteristic shared by all seed plants is the production of seeds.

Thermophilic: An organism, a type of extremophile that thrives at relatively high temperatures, between 45 and 122 C .

Trichomes: Fine outgrowths or appendages on plants and certain protists.

Xanthophyta: Yellow-green algae or xanthophytes are an important group of heterokont algae. Most live in freshwater, but some are found in marine and soil habitats.

Abstract

The relationships between water quality variables and phytoplankton diversity in the Hartbeespoort Dam were assessed spatially and temporally from February 2011 to March 2012 to evaluate the effects of the water quality variables on cyanobacterial bloom (Microcystis aeruginosa) hence aquatic macrophytes growth (Eichhornia crassipes) in the dam. Variables measured using standard methods included; temperature, pH, electrical conductivity, total suspended solids, dissolved oxygen, nitrate, nitrite, total phosphorous , ammonium, trace metals, chlorophyll-a and the phytoplankton community. The physical parameters ranged between: temperature (11.8-28 ºC), electrical conductivity (282-796 µS/cm), dissolved oxygen (0.33-32.2 mg/L), pH (6.95-9.91) and total suspended solids (2-372 mg/L). Chemical variables ranged between; total phosphorous (0.02-3.5 mg/L), nitrate (0.03-21.2 mg/L), nitrite (0.02-0.48 mg/L) and ammonium (0.01-1.58 mg/L), chlorophyll-a (0.13-8693 µg/L), and exceed the TWQR values of the South African Water Quality Guidelines for aquatic ecosystem health health. Metal concentrations in water had the following decreasing order; macro elements: potassium > calcium >sodium > magnesium. Microelements: iron >zinc > aluminium > copper > nickel > manganese > chromium> selenium > lead > silver > arsenic > cadmium. Iron had the highest concentration among microelement of 631.62 µg/L and potassium the highest concentration amongst macro element of 34.49 mg/L. Six Different algal divisions were found in the dam with cyanophyta (cyanobacteria) been the most dominant group (95 %) and M.aeruginosa the most dominant species (69 %). The current study revealed an increase in physical parameters, chlorophyll-a and phytoplankton community and a decrease in chemical parameters in the summer months. An inverse relationship was observed in the winter months at all sites. One-way ANOVA showed a significant differences for physical variables (p <0.05) between months, with no significant differences noted (p > 0.05) between sites and between depths. Chemical variables however, showed a significant differences between months, sites and between depths (p <0.05). A 2-tailed Pearson correlation revealed negative correlations between temperatures and phosphorus, ammonia, nitrate, nitrite, electrical conductivity and iron (r=-0.298;-0.232;-0.099;-0.461;-0.441;-0.260) respectively and positive correlations between temperatures and chlorophyll-a and pH (r= 0.240; 0.609 ;) respectively (p <0.05; p <0.01). Canonical discriminant functions analysis revealed similarities and dissimilarities in water quality variables temporally and spatially with eigenvalues of 84.6 % and 59.1 % respectively. There was an adverse impact of the physico-chemical variables on the phytoplankton community, therefore aquatic macrophytes growth in the dam. The current study revealed that temperature, pH, phosphorous, nitrate and probably iron, copper, zinc and selenium may have contributed to the hypertrophic state of the dam, hence cyanobacterial bloom and growth of aquatic macrophytes.

Keywords: Cyanobacterial bloom, Eichhornia crassipes, Chlorophyll-a, Hartebeespoort Dam, Hypertrophic, Microcystis aeruginosa.

Chapter 1

Introduction

1.1 Background

South Africa encounters an increasing water crisis; posed by the rapidly-worsening quality of our dams (Harding, 2010). This situation is observed in the Crocodile West & Marico Water Management Area, one of the several water stressed catchments in South Africa. This is due to the fact that surface water resources are used expansively, mostly in that catchment, with the main water consumers being agriculture, industry, mining and urban use (DWAF, 2004a). The Hartbeespoort Dam ( Fig.1) is a hypertrophic, warm, monomictic impoundment , located in the North West Province of South Africa within the Crocodile (West) Marico Water Management Area. The dam has a mean depth of 9.6 m and a surface area of 20 km2. The Dam has a maximum capacity of 195 million m3 (Oberholster and Botha, 2010). Hartebeespoort Dam receives water from the 4100 km2 catchment area of Johannesburg and Pretoria, via the Jukskei and Hennops Rivers that flow into the Crocodile River (Oberholster and Botha, 2010). Other smaller direct contributors to the dam are the Magalies River, Leeuwspruit and the Swartspruit. The Hartbeespoort Dam is a severely eutrophied water body receiving a significant external nutrient load (Cukic and Venter, 2012). The dam undergoes severe eutrophication (Fig.1), caused by high phosphate and nitrate concentrations from the Crocodile River, the major inflow. This dam is one of a number of hypertrophic dams in South Africa and has been in this state for some time (DWAF, 2007). In addition, the level of eutrophication in the dam is extreme. The evidence is found in the excessive growth of microscopic algae, cyanobacteria, and macrophytes such as water hyacinth (Eichhornia crassipes) (van Ginkel and Silberbauer, 2007). Eutrophied waters favour bottom dwelling fish, such as carp and catfish that bring nutrients back into the water through remobilisation of sediments (Koekemoer and Steyn, 2005). The bioturbation caused by these fish contributes to the mass development of blue-green algal blooms (cyanobacteria) and other algae.

Figure 1: The Hartbeespoort Dam.

Moreover, cyanobacteria are often associated with the occurrence of blooms the resultant dominance of phytoplankton communities (Quiblier et al., 2008). Wicks and Thlel (1990) said that cyanobacteria bloom formation is stimulated by elevated levels of nutrients especially phosphorus (P), nitrate (NO3) or ammonia

(NH4), water temperatures between 15 ºC and 30 ºC, and a pH between 6 and 9 or higher. This is the result of a combination of high nutrient loading, high incident solar radiation, low wind speeds, and warm water, which make it the ideal environment for the prolific growth of the buoyant blue-green algae, Microcystis aeruginosa (Ashton et al., 1985). Consequently, the Department of Water Affairs (DWA) has initiated the Hartbeespoort Dam Integrated Biological Remediation Programme, referred to as “Harties, Metsi a me - My water”. The purpose of this programme is to deal with the disproportion and damaging biological conditions in the Hartbeespoort Dam (DWAF, 2007). Despite all the effort by the Department of Water Affairs, the dam is still suffering from high ortho-phosphate loads. High ortho-phosphate loading and algal blooms are due mainly to sewage treatment works which do not always comply with 1mg/L phosphate effluent standard ,which is nearly impossible in such an expansive catchment area to monitor (Owuor et al., 2007). There was thus a need to undertake a study to evaluate the appearance pattern and persistence of algal bloom in the dam, and to analyse various aspects that influence phytoplankton growth and persistence in the Hartbeespoort Dam. Those aspects included the complex and dynamic relationships between physico- chemical and biological factors, such as water temperature, pH, oxygen production, and nutrient availability (nitrogen, phosphorus, iron).

1.2 Problem Statement and Hypothesis

The Hartbeespoort Dam is located in the North West Province of South Africa within the Crocodile (West) Marico Water Management Area (WMA) (DWAF, 2007). The Dam is situated on the confluence of the Crocodile and the Magalies Rivers. The two Rivers drain highly populated urban areas, namely Pretoria, Johannesburg and Krugersdorp. The Hartbeespoort Dam has been exposed to algal blooms (M.

auriginosa) (van Ginkel et al., 2001) and massive aquatic weed (E. crassipes) growth. The impoundment was identified as a hyper-eutrophic system and the promulgation of the 1 mg/l Phosphate (P) effluent Standard by the Department of Water Affairs and Forestry in 1980 was to be applied in the catchment (van Ginkel, 2002). This standard was announced in a Government Notice, 1567 of 1980, as follows: “Waste water or effluent produced by or resulting from the use of water for industrial purposes and which drains to any portions of a river mentioned in Schedule 2 or any tributary of such a river within the catchment areas or portions thereof described in the Schedule, shall not contain soluble ortho phosphate (as P) in a higher concentration than 1.0 milligram per litre” (van Ginkel, 2011). Due to financial limitations in the metropolitan areas, sewage treatments works do not always conform to the 1mg/l P effluent standard (Owuor et al., 2007). Likewise, there are also many informal settlements such as Alexandra, Diepsloot, Tembisa, Chartwell and Zandspruit (DWAF, 2004a; Matowanyika, 2010; Cox, 2012) in the catchment, as well as intense farming activities where tobacco, wheat, lucerne, fruit, and flowers are produced. In addition, population growth centred on the Johannesburg and Pretoria metropolitan complex (DWAF, 2004b) results in reduced functioning of the water treatment works which cannot sustain such a population explosion. These factors contribute to the level of eutrophication within the dam (van Ginkel et al., 2001). Accordingly, it is hypothesized that nutrient excess, mainly phosphorus and nitrate in the Hartbeespoort Dam leads to rapid growth of water hyacinth and periodic algal blooms, when environmental conditions are favourable.

1.3 Aim and objective of the study

This study aims to assess the development of algal bloom in the Hartbeespoort Dam, taking into account the complex factors and interrelations that determine their occurrence, abundance and diversity. This comprehensive aim had the subsequent objectives:  To investigate the physico-chemical and biological parameters of the dam and any probable effect to bloom occurrence and persistence ;  To investigate phytoplankton composition with specific reference to Mycrocistis species and their implication in the dam periodic algal bloom.

Chapter 2

Literature Review

2.1 Cyanobacteria

Cyanobacteria, commonly known as blue-green algae, are photosynthetic prokaryotes possessing both bacterial and algal characteristics, (Chorus, 2001). Cyanobacteria are autotrophic organisms which lack internal organelles, a discrete nucleus and the histone proteins associated with eukaryotic chromosomes (Brink, 2011). Their diversity ranges from unicellular, coccoid to branched filaments, nearly colourless to intensely pigmented (Fig.2), autotrophic to heterotrophic, psychrophilic to thermophilic, acidophilic to alkylophilic, planktonic to barophilic, freshwater to marine including hypersaline waters (Owuor et al., 2007).

Figure 2:Cyanobacteria:A) Anabeana sp.,B) Cylindrospermum sp.,C) Microcystis sp.,D) Oscillatoria sp.( www-cyanosite.bio.perdue.edu/images.html).

Cyanobacteria are vital to mankind as they provide them with food, feed, fuel, fertilisers, colorants and produce several secondary metabolites such as vitamins, toxins, enzymes, pharmacological probes and pollution abatements (Thajuddin and Subramanian, 2005). Mycrocystis is one of the dominant

cyanobacteria organisms that is associated with almost permanent blooms in tropical freshwaters that are exposed to constant sunshine, warmth, carbon dioxide, pH and nutrients like phosphate and nitrates (Owuor et al., 2007). Cyanobacteria can produce lethal toxins (Table 1) that can lead to death of domestic and wild animals on consumption of water contaminated by these toxins (Oberholster et al., 2008).

Table 1: Cyanobacterial toxins of the most dominant species in South Africa, and their functions and mechanisms of action. (Oberholster et al., 2008).

Primary target Toxin type organ in mammals Cyanobacteria Taxon Mechanism of toxicity

1. Hepatotoxins Microcystins Liver Microcystis,Oscillatoria, Inhibition of protein Nostoc, Anabaena phosphatase activity, haemorrhaging of the liver Nodularins Liver Nodularia Inhibition of protein phosphatase activity, haemorrhaging of the liver 2. Cytotoxins Cylindrospermopsins Liver,kidney,spleen, Cylindrospermopsis Inhibition of protein intestine,heart,thymus synthesis Neurotoxins Nerve synapse Anabaena, Oscillatoria Blocking of post-synaptic depolarization 3. Anatoxin-a 4. Dermatotoxins Aplysiatoxins Skin Oscillatoria Protein kinase C activators, inflammatory activity 5. Irritant Toxins Lipopolysaccharides Any exposed tissue All Potential irritant and allergen

Blooms of M. aeruginosa are the most common in South Africa (Oberholster et al., 2009). More than 65 microcystins have been isolated to date and they are the most abundant cyanobacterial toxins. Risks to human health may result from prolonged exposure via contaminated water. Microcystins are powerful tumour promoters and inhibitors of protein phosphatase 1 and 2A and are suspected to be involved in the promotion of primary liver cancer in humans (Oberholster et al., 2005). In South Africa, freshwater cyanobacterial blooms and scums of M. aeruginosa have been associated with skin irritations, conjunctivitis and allergic reactions after swimming or water-contact sports in dams (Harding and Paxton, 2001).

The occurrence of cyanobacteria in freshwater is of special importance to the drinking water suppliers as several genera of cyanobacteria can produce offensive taste and odour compounds, as well as cyanotoxins that can affect human health (du Preez et al., 2007). Cyanobacteria (blue-green algae) are known to produce toxins that are directly implicated in livestock and wildlife mortality worldwide (Kellerman et al., 2005). The most toxic freshwater blue-green algae are Microcystis spp., Anabaena spp., and Planktothrix spp., (Hitzfeld et al., 2000), and the most common toxins produced are microcystins, especially microcystin-LR (Fig. 3) (Carmichael, 1994).

Figure 3: Chemical structure of microcystin-LR. (Carmichael, 1994).

Formation of cyanobacteria blooms in fresh water bodies is essentially aided by factors such as nitrogen concentration, phosphorus concentration, temperature, light, micronutrients (iron, molybdenum), pH and alkalinity, buoyancy, hydrologic and meteorological conditions, and the morphology of the impoundment (Hitzfeld et al., 2000)

2.2 Aquatic macrophytes

Aquatic macrophytes are aquatic photosynthetic organisms, large enough to see with the naked eye, that actively grow permanently or periodically submerged below, floating on, or growing up through the water surface. Aquatic macrophytes are represented in seven plant divisions: Cyanobacteria, Chlorophyta, Rhodophyta, Xanthophyta, Bryophyta, Pteridophyta and Spermatophyta (Chambers et al., 2008). Originally from South America, water hyacinth, E. crassipes, is one of the world’s most prevalent invasive aquatic macrophytes (Villamagna and Murphy, 2010), known to cause significant ecological and socio- economic effects. Nutrients and temperature are considered the strongest determinants for water hyacinth growth and reproduction (Wilson et al., 2007).

2.3 Chlorophyll-a

Chlorophyll is a green pigment in all photosynthetic organisms and it exists in three forms, chlorophyll a, b, and c (Mohale, 2011). All green plants contain chlorophyll-a, and planktonic algae owe 1-2 % of its dry weight to chlorophyll-a (Swanepoel et al., 2008). Chlorophyll-a concentrations have been accepted as an indirect measurement of phytoplankton biomass, brought about by various observations on the correlations between algal bio-volume and chlorophyll-a. Estimations of chlorophyll-a concentration are important in the monitoring of water quality of a lake, because it can indicate its trophic state, phytoplankton abundance and biomass (Huang et al., 2010).

2.4 The process of eutrophication

The quality of South Africa’s water resources is becoming increasingly impaired by eutrophication; to the extent that regional crises now prevail (Harding et al., 2009). Eutrophication (Fig.4) is the process of excessive nutrient enrichment of waters that typically results in problems associated with macrophyte, algal or cyanobacteria growth (DWAF, 2002). It is part of the natural ageing process of lakes and is accelerated by human impacts (van Ginkel, 2011). Eutrophication leads to water quality deterioration, algal toxin production, taste and odour problems, oxygen depletion, decline of more desirable fish species, the clogging of waterways, disruption of flocculation and chlorination processes in water treatment plants, and in some cases, excessive loss of water through evapotranspiration (van Ginkel, 2002). The effect of eutrophication in the Hartbeespoort Dam manifests itself through vast and excessive algal blooms, as well as prolific growth of water hyacinth in all areas of the dam (Venter, 2009). Thankfully, in the last decade, the importance and current extent of eutrophication in South African water bodies has been highlighted (van Ginkel et al., 2001; van Ginkel, 2004) and also by the development of an implementation manual for the National Eutrophication Monitoring Programme (DWAF, 2002).

Figure 4: The nutrient cycle within a water system, indicating the causes and consequences of eutrophication (DWAF, 2002).

2.5 Environmental factors influencing algal bloom formation

The formation of cyanobacteria blooms is related to a complex and dynamic relationships between physical, chemical and biological factors (Harding and Paxton, 2001). These factors include water temperature and turbidity, pH, and nutrient availability (nitrogen, phosphorus, iron).

2.5.1 Temperature

All organisms have a temperature range at which optimal growth occurs and their life cycles are directly linked to temperature (Sayed, 2013).Toxic cyanobacteria blooms often occur in eutrophied ecosystems during warm months (Davis et al., 2009). Cyanobacteria have a wide range of temperature tolerance, but rapid growth rates are usually achieved when water temperatures exceed 20 °C (du Preez and van Baalen, 2006). Cyanobacterial bloom formation is stimulated by water temperatures between 15 °C and 30 °C (Wicks and Thlel, 1990). Climatic conditions control the timing and duration of the bloom season for cyanobacteria (van Apeldoorn et al., 2007). In temperate climates, cyanobacterial dominance is often evident during mid-summer to early autumn, though, this dominance may occur any time throughout the year, even under ice during winter (Graham et al., 2008). In subtropical and tropical climates cyanobacteria may dominate at any time. In the Hartbeespoort Dam for example, stable environmental factors such as low rainfall, windless weather and warm water temperatures, which vary from a minimum of 9 to 13 °C during winter periods and a maximum of 24 to 27 °C during summer periods (Owuor et al., 2007), create a suitable growth conditions for cyanobacterial blooms.

2.5.2 pH

This refers to the amount of the acid balance of a solution and it is controlled by the dissolved chemical compounds and biochemical processes in the solution. pH is an important variable in water quality assessment because it influences many biological and chemical processes within a water body and all processes associated with water supply and treatment (Mohale, 2011). Cyanobacteria are distinctive among micro-organism in their incapacity to grow at low pH values (Owuor et al., 2007). Cyanobacterial growth appears to be inhibited completely in habitats with pH values between 4 and 5. They are alkalopiles and their optimal growth pH lies between 7.5 and 10 (Thajuddin and Subramanian, 2005). This preference for alkaline environments reveals that an acid barrier might exist that these micro-organisms have not been able to overcome. The pH of the medium influences algal metabolism directly through enzymatic controls and indirectly through the availability of nutrients, minerals and trace metals (Bachelor et al., 1992).

2.5.3 Turbidity and light penetration

Turbidity (clarity of water) is an important water quality variable. It is affected by zooplankton and phytoplankton densities in the water column, suspended particulate matter such as silt, faecal matter and uneaten feed (MacGibbon, 2008). Lakes and reservoirs are characterized by vertical gradients caused by light and thermal stratification (Graham et al., 2008). Several studies on shallow lakes discussed the effect of turbidity on phytoplankton assemblages. Dokulil (1984) suggested that the most obvious feature of turbid lakes like Lake Neusiediersee was the profound influence that turbidity had on the underwater light intensity. Light intensity was rapidly attenuated and altered in its spectral composition according to the nature of the suspended particles. In turbid underwater environments, algal species with gas vesicles, such as Microcystis, can either move down to avoid the high light intensity at the water surface, or float up when underwater light conditions are poor (Owuor et al., 2007). In water systems where Secchi-depth and suspended solids data showed high turbidity like in Lake Taihu (Chen et al., 2003) or Hartbeespoort Dam, Microcystis spp. generally dominated. Scott et al., (1981) suggested that Microcytis adapts to high lights intensities by reducing the chlorophyll content of the cells while at lower lights intensities and in darkness more chlorophyll is synthesised.

2.5.4 Nutrients

Freshwater algal blooms are the result of an excess of nutrients, and the most important nutrients for algal growth are nitrogen (N) and phosphorus (P) (du Plessis, 2007). A nutrient is a chemical compound or element that can be used by plant cells (algae and aquatic macrophytes) for growth (Wamsley, 2000). In the context of eutrophication, nutrients are mostly inorganic elements that are assimilated by plants and, in conjunction with the process of photosynthesis, are utilised to produce and accumulate organic material in aquatic ecosystems (Owuor et al., 2007). Growth and extra uptake in algal nitrogen content is generally taken to be 9 to 12 % by weight with phosphorus 0.9 to 1.5 % and carbon 35 to 60 % (Bachelor et al., 1992). Phosphorus and nitrogen are the most frequent limiting nutrients in fresh water systems. Increases in the concentrations of these two nutrients in a water body will raise the risk of experiencing eutrophication problems (Owuor et al., 2007). Nitrate plus nitrite concentrations in surface waters give a general indication of the nutrient status and level of organic pollution (Ballance, 1996). Nitrogen occurs in the surface waters in several forms e.g. ammonium, nitrite, nitrate, and urea and nitrogen gas. When taken in the oxidised form, nitrogen must be reduced before it can be incorporated into organic molecules (Bachelor et al., 1992).

Concentrations of phosphates in lakes and reservoirs need to be determined in order to assess the capacity of the water body to carry a cyanobacterial population (Lawton et al. 1999). High concentrations of phosphates can indicate the presence of pollution and are largely responsible for eutrophic conditions (Chapman and Kimstach, 1996). Algae assimilate phosphorus as inorganic phosphate although orthophosphate can be obtained from organic and inorganic polyphosphates of low molecular weight. Orthophosphate is generally considered to be the most immediately available form of phosphorus (Owuor et al., 2007). Other nutrients can be significant, but regularly only under special conditions. Micronutrients such as iron (Fe) are shown to be limited in extremely pristine waters and some marine areas (Wamsley, 2000).

2.6 The Harbeespoort Dam

Hartbeespoort Dam is a valuable water resource in the North West-Gauteng provincial jurisdictions. Hartbeespoort Dam is renowned for its poor water quality and is possibly one of the World’s worst examples of eutrophication, due to the high nutrient loads which enter the system and have overloaded the reservoir basin for decades (Mbukwa et al., 2012). The level of pollution is such that the dam regularly experiences dense blooms of cyanobacterial algae, with associated levels of algal toxins that pose a significant threat to human and animal health. (Harding et al., 2004).

2.6.1 History, construction and usage

Hartbeespoort Dam was constructed across the Crocodile River immediately downstream of its confluence with the Magalies River between 1923 and 1925 (Harding et al., 2004).The dam itself has a circumference when full of about 56 km and holds some 205 million m3 of water. The dam wall is 149.5 m long and 59.4 m high and is built across a valley cutting through the Magaliesberg (WW, 2008).

Hartbeespoort Dam was originally designed for irrigation which is currently its primary use (WW, 2008). The Dam supplies irrigation water through a 544 km long network of canals to 159.76 km2 of farmland.

The farmlands produce tobacco, wheat, lucerne, fruit and flowers. Roughly 80 % of water is used for irrigation with lesser uses for domestic consumption and compensation flows. Today irrigation canals are supplied with 110 - 150 million m3 of water per annum depending on weather conditions (Venter, 2008). Madibeng Local Municipality depends totally on the water from the dam. Inhabitants around the dam and large settlements downstream, including the town of Brits, use purified dam water for drinking (Venter, 2008). Hartbeespoort Dam has become a very popular holiday and weekend resort for the residents of Johannesburg and Pretoria. It is the major water recreation area of northern Gauteng and many forms of water sports are practiced on the dam.

2.6.2 Water quality

The Hartbeespoort Dam is classified as hypertrophic (van Ginkel, 2002) due to high frequency of microcystis algal blooms (Fig. 5), which may occur throughout the year (Gumbo et al., 2010). A technical report from Hartbeespoort Dam Remediation Project phase 1, volume II by Harding et al.,( 2004) confirmed that the dam has been receiving more than 200 metric tons of phosphorus as P for several years.

Figure 5: Cyanobacterial bloom and water hyacinth massive growth in the Hartbeespoort Dam. (Venter, 2008).

In a report in the Water Wheel (2005) by Sophia Dower, it was noted that coupled with other environmental factors such as low rainfall and warm temperature, windless weather, the influx of nutrients generally led to rapid and excessive growth of cyanobacteria and aquatic weeds in this dam. The same report pointed out that excessive nutrient loads (80 to 300 metric tonnes of phosphate (P), originating largely as point source (16 sewage treatment works) are discharged annually into the Crocodile-Jukskei River system that supplies the lake with water, resulting in the reservoir becoming hypertrophic. However, the release of wastewater into catchment areas is a worldwide practice and that with management options and legislation in place under South Africa’s Water Act, this dam should not attract negative publicity as it has generated over the years. It reported further, that the dam has nutrients trapped in the sediments at the bottom and this may remain inactive for extended periods. During summer months, different thermal layers form in the water column of Hartbeespoort Dam causing the deeper thermal water layer to become anaerobic. Under these conditions, phosphorus is released from the sediment which provides optimal

cyanobacterial growth in the lake (Oberholster and Botha, 2010). However, for reasons not yet known, nowhere else in South Africa do these “hyperscums” produce so rapidly or in such quantities than in Hartbeespoort Dam (Dower, 2005). Apart from growth supplies of macronutrients such as phosphorous and nitrates, other abiotic factors such as pH, trace metals are as well essential microelements, which are required by plants. Their occurrence in the dam may impact the growth dynamics of the cyanobacteria present and hence persistence (Owuor et al., 2007). A possibility of any correlations between the presence and levels of trace metals entering this dam; species composition and extent of such bloom formation could exist. Other conditions, such as patterns of wind, sheltering and a semblance of biological structure play an influential role in sustaining acceptable water quality. However, once this semblance of biological structure for example macrophytes or fish population is lost, the balance swings in favour of algal species that are known strategists in dominating nutrient rich environment (Harding et al., 2004). Microcystis aeruginosa is the most common toxic cyanobacteria found in the Hartbeespoort Dam (Harding et al., 2004), and the toxicity of the dam blooms seems to be mainly associated with this species (Oberholster et al., 2008). According to the media release in the Water Wheel 2005, Hartbeespoort Dam suffers from massive seasonal growth of cyanobacteria, which accumulates on the dam surface and rots in the sunlight. It releases offensive odours and often looks and smells like raw sewage- but it is not. The sludge is caused by the natural biodegration of the cyanobacteria and not human excreta. The bloom affects the taste and smell of the water supplied to local residents. Understandably, the residents are up in arms every time such cyanobacteria are rotting starting to which results in smell reports that raw sewage is spilling into the dam (Owuor et al., 2007). This has resulted in management problems for all the stakeholders involved. Those stakeholders include the Hartbeespoort Water Action Group (HWAG), the Department of Water Affairs (DWA) and the general public who reside around the dam. They are trying to find an approach for a solution to this recurrent problem. The re-appearance of algal species in the dam after reported absence during winter has always been a subject of question. Tow (1979) observed that little was known of the fate of M. aeruginosa during absence from the phytoplankton in winter months, only that this species sometimes immediately re-appear and dominate certain water systems. Microcystis aeruginosa break up into individual cells by sloughing off the mucilaginous sheath, settle in the sediments and later, under favourable environmental conditions, redevelop into colonies. Investigation on this phenomenon was therefore necessary for management strategies. In order to rehabilitate and manage this dam, DWAF, as a lead agent has from time to time chosen certain management policies aimed at reducing the nuisance of the phytoplankton. Among such measures included the promulgation of the effluent of phosphate-P standard of 1 mg/L, which was introduced in the catchment of Hartbeespoort Dam in 1985 (Chutter, 1989). A subsequent study (Rossouw and Grobler, 1988) after this initiative, revealed that the standard alone would not be sufficient to reduce the phytoplankton abundance to desirable levels. In addition, due to financial and capacity constraints in the metropolitan areas, sewage treatments works do not always comply with 1 mg/L phosphate effluent standard and enforcement of the standard may not be possible in such an expansive catchment area. Johannesburg Northern Works serving the northern portions of Johannesburg for example, discharge effluents with a concentration of between 4 and 5 mg/L phosphate-phosphorus (Harding et al., 2004). There are also numerous informal settlements that release raw sewage into the catchments, as well as intensive farming activities, all of which contribute to the extent of eutrophication of the dam (van Ginkel et al., 2000).

Chapter 3

Materials and Methods

3.1 Study area and Sampling points

The sampling sites (Fig.6) were considered in consultation with Resource Quality Services (RQS) of Department of Water Affairs based on their sampling site positions in the dam. Sampling trips were conducted for a period of twelve months from February 2011 to March 2012. Six sites along the upper (dam wall), middle and lower (bridge) reaches of the Hartbeespoort Dam were chosen for the study. The sites were positioned within the dam basin as follows: Site 1(S25 43.707; E27 51.020) was at the Dam wall near exit conduits ;Site 2 (S25 44.370; E27 52.717) randomly considered within the basin; Site 3 (S25 45.518; E27 53.309) positioned at the confluence with the Crocodile River; Site 4 (S25 45.551; E27 52.426) and Site 5 (S25 45.389; E27 50.463) positioned at the middle reach of the dam basin and Site 6 (S25 45.559; E27 48.363) positioned at the Bridge, at the confluence with the Magalies River. Water samples for nutrient analysis, chlorophyll-a quantification, metal analysis, suspended particles analysis and algal identification was collected from the six sites by submerging acid-washed polypropylene bottles for surface water only, and using a van Dorn water sampler for samples collection at depths of 5 and 10 metres at each site.

Figure 6: Map of Hartbeespoort Dam showing the positions of the six sampling sites.

3.2 Physical parameters

Conductivity, temperature, pH and dissolved oxygen were recorded in situ from surface water, and at depths of 5 and 10 metres at each of the six sites .A cyberscan con 11 (EUTECH Intrument, Singapore) was used to measure electrical conductivity and temperature. Oxi 320 oximeter (Weilheim, Germany) was used for dissolved oxygen and a pH325 pH-meter (Weilheim, Germany) for pH.

3.3 Nutrients analysis

The water samples were analysed for nutrients using standard spectroquant test-kit techniques on a Merck Spectroquant Pharo100 in the laboratory. The nutrients that were tested for were nitrate, nitrite, ammonium, phosphate. Water quality results were compared to the Target Water Quality Requirement (TWQR) for aquatic ecosystems as set out by DWAF (1996).

3.4 Metals in water and total suspended solids (TSS)

Metal content and total suspended solids of surface water was analysed from the six sites. Water samples were filtered prior metal analysis. 0.45 µm cellulose nitrate filter paper was pre-weighed and placed on a glass fibre filter.100 mL was filtered; the filtrate was acidified with 1.538 mL 65 % suprapure nitric acid and decanted into 15 mL falcon tubes for metal analysis. The metals that were analysed for on the ICP- OES were Ca, K, Mg and Na. The metals that were analysed for on the ICP-MS were Ag, Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Se and Zn. Total suspended solids, were determined by filtering 100mL of water collected from each site, for each sampling period, through a pre-weighed, pre-dried filter membrane (0.45 µm pore size), using a Millipore plastic vacuum filtration system. Once the samples had been filtered, the filter papers were dried at 60 ºC for 48 h, after which they were weighed again. Total suspended solids concentrations were estimated using the weight of residuals on the membrane filters and was expressed as mg/L (Odiyo et al., 2012).

3.5 Chlorophyll-a quantification

Chlorophyll-a concentrations (Chl-a) were determined using a Hitachi 150-20 spectrophotomer (Japan) and according to the method by Sartory (1982). A sample volume of 250 mL was filtered, with the aid of a vacuum pump, through a Whatman GF/C filter. The chlorophyll gathered on the filter was extracted with 10 mL 95 % ethanol in a water bath at 78 ºC for 5 minutes. The samples were removed and left in the dark to cool down. The difference in absorbance of the extract was determined at 665 and 750 nm respectively using 95 % ethanol as the blank. The difference in absorbance of the same sample was again determined 2 minutes after acidification with a drop 0.3 M HCl. The Chlorophyll-a concentration was then calculated using the following equation:

Chlorophyll-a (µg/l) = [(A665-A750) * (A665a-A750a) x 28.66 x extract volume]/volume of sample

Where: A665 = absorbency at 665nm before acidification; A750 = absorbency at 750 nm before acidification; A665a = absorbency at 665 nm after acidification; A750a = Absorbency at 750 nm after acidification; extract volume = 10 mL 95% ethanol; volume of sample = volume of water sample filtered in litres.

3.6 Algal identification and quantification

Water samples for analysis of the phytoplankton population were collected from the surface at each six sampling sites. A semi qualitative and quantitative analysis was performed to identify and quantify the major algae species using visual identification. The counting was completed by means of inverted microscopy with a Zeiss stemi DV4 microscope (Göhingen,Germany) and with the aid of the manual” A guide for identification of microscopic algae in Southern African freshwaters” by van Vuuren et al., 2006. Cells or colonies counted were approximated as percentages in relations to the other species of algae present in the sample (van Vuuren et al., 2006).

3.7 Statistical analysis

A one-way analysis of variance (ANOVA) and multivariate analysis were used to identify differences in water quality parameters among the twelve months of study, six sites and three depths, since samples were collected per parameters temporally and spatially. The level of significance (α) was 0.05 and the p values obtained were referred to as model p in the results section. A model p less than 0.05 indicates that at least two of the months, sites or depths differ in parameters from each other. A multiple post-hoc comparison test was completed to determine where differences lie between specific months, sites or depths (Scheffé test for parametric data or Dunnett’s-T3 test for non-parametric data) at confidence level of p ≤ 0.05. The linking of multivariate data sets containing water quality parameters was computed using a 2-tailed Pearson product-moment correlation (Oberholster, and Botha, 2010) and canonical discriminant functions analysis (Kaselowski and Adams, 2013) to search for relationships and significance there-after between environmental parameters and biological responses spatially and temporally at confidence levels of p ≤ 0.05 and p ≤ 0.01. All statistical calculations were done with the statistical package SPSS (SPSSInc. Chicago, IL, USA) and graphs where generated with GraphPad Prism 5.

Chapter 4

Results and Discussion

Specific water quality variables were discussed comparing mean values at different sites and depths for the months covering the study period along with ranges. Where possible, results were compared to target water quality ranges (TWQR) set out in the water quality guidelines for ecosystem health in South Africa (DWAF, 1996) for appropriate variables.

4.1 Physical water quality parameters

Physical water parameters recorded in the dam are presented in Table 2.

Table 2: Summary statistics of physical parameters measured in the Hartbeespoort Dam between February 2011 and March 2012.

TWQR Minimum Maximum Mean (DWAF 1996) Physical parameters values values ± SD

Temperature (ºC ) 11.58 28 20.70 ± 4.74 - Dissolved Oxygen ±12oo44496 0.33 32.7 6.23 ± 5.19 - (mg/L) Conductivity(µS/cm) 282 796 489.34 ± 74.33 - cm–1 pH 489.346.95 9.91 8.29 ± 0.79 6.5 –9 489.34 Total Suspended Solids 2 372 63.61 ± 67.52 < 100 mg/L (mg/L) SD: Standard deviation.– indicate that TWQR value for aquatic ecosystem health was not available.

4.1.1 Temperature

As can be seen from Table 2, the temperatures of the water samples ranged from 11.58 -28 °C during the study period and were not significantly different among the six sampling sites and the three water depths profile (p > 0.05). There were significant differences among months for temperature as determined by one- way ANOVA (p < 0.05). The lowest temperature value was recorded in August 2011 at surface water level, at site 1 by the dam wall near exit conduits (Appendix-Table A). The highest temperature value was recorded in February 2011 at surface water level, at site 4 positioned at the middle reach of the dam basin (Appendix-Table A). The Dam had an annual mean temperature of 20.70 °C. As can be seen from Fig.7a, the temperatures decreased from April to the end of August 2011. However, there were temperature differences at depths between 5 m and 10 m which indicate stratification (Fig. 7b). These temperature differences decreased gradually from February to August. Almost uniform values were observed in the water column during winter months (June to August). Figure7a again displays surface temperatures below 12 °C during winter period. It also indicates an overturn with almost uniform temperature measurements

recorded from surface to bottom of the dam from May to July. This temperature variation can be attributed to an overturn in the dam that occurred in April 2011. Equally, in Figures 7a & 7b winter months showed almost uniform temperatures values in the water column until the end of August. Figure 7a shows increasing temperature measurements in late September 2011 and the commencement of re-stratification of the dam. In November 2011, the dam had experienced a noticeable stratification below 5 m depth. Higher temperatures during summer months through this study stimulated cyanobacterial blooms in the Hartbeespoort Dam. According to O’Neil et al. (2012), temperatures that approach and exceed 20 °C generally increase the growth rates of many cyanobacteria. A study conducted by Conradie and Barnard (2012), on Hartbeespoort and Roodeplaat Dams confirmed that temperatures especially above 23 °C contributed to the development of cyanobacteria in the form of Microcystis species.

30 Site 1 C  Site 2 20 Site 3 Site 4

10 Site 5 Site 6 Mean Temperatures in Temperatures Mean 0

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Figure 7a: Spatial variation in water temperature based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam.

30 0 m C  5 m 20 10 m

10 Mean Temperatures in Temperatures Mean 0

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Figure 7b: Temperatures variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam.

4.1.2 Dissolved oxygen (DO)

Dissolved oxygen is essential to the respiratory metabolism of most aquatic organisms and its concentration is determined by atmospheric inputs, photosynthesis, respiration and oxidation (Wetzel, 2001). Mean dissolved oxygen concentrations are illustrated in Figs. 8a & 8b. Oxygen concentrations range from 0.33 -32.6 mg/L (Table 2) and were not significantly different among the six sampling sites and among the three water depths profile (p > 0.05). There were significant differences although among sampling months for dissolved oxygen as determined by one-way ANOVA (p < 0.05) (Refer to evidence). The lowest DO (0.33 mg/L) value was recorded in March 2012 at depth of 10 m, at site 6 by the dam bridge, at the confluence with the Magalies River (Appendix-Table A). The highest DO (32.6 mg/L) value was recorded in October 2011 at surface water level, at site 2 randomly considered within the dam basin close to the Crocodile River inflow)(Refer to evidence). This has an annual mean DO value of 6.23 mg/L. Owuor et al. (2007) while investigating the dam recorded oxygen levels ranging from 4 to 6 mg/L in early June of 2003. The dam was well oxygenated at all six sites and three depths during late February, September and October months (Fig. 8b). A pattern of moderately low concentrations of dissolved oxygen was observed during winter months. The moderately low DO concentrations could be ascribed to low photosynthetic activity during winter. A marked anaerobic hypolimnion was visible in late November 2011, early January and March 2012 (Figs. 8a & 8b) where oxygen levels were exceptionally low throughout the dam at all six sites and all three depths profile (0,5,10 m) when the water temperatures were high. A probable reason could be that with more nutrients available, the algae increase in number. As more algae and plants grow, others die and the organic matter produced becomes food for bacteria that decomposes it (Vos and Ross, 2005). With availability in organic matter, the bacteria increase in number and use up the dissolved oxygen (Gazi and Das, 2012) resulting in low concentration of DO in water. Sayed (2013) stated that the depletion of oxygen concentration is due to higher microbial action at elevated temperatures. By late February 2011, however, dissolved oxygen levels increased followed by a declined

in April and May 2011 (Figs. 8a & 8b). An increase in algae may have resulted in an increase in photosynthetic activity leading to an increase in DO level. Dallas and Day, (2004) outlined that an increase in photosynthetic activity is associated with an increase in dissolved oxygen concentrations. The months of September 2011 and October 2011, nevertheless, showed an increase at all six sites and three depths. A possible explanation could have been due to inflow of water from the tributaries as result of spring rains, mixing the water in the dam and therefore increasing DO level. Low temperature in winter months may have also contributed to increased dissolution of molecular oxygen in water. Horne and Goldman (1994) stated that, oxygen is more soluble in colder water than in warmer water.

40 Site 1 30 Site 2 Site 3 20 Site 4 Site 5 Site 6

Mean DO in mg/L in DO Mean 10

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Figure 8a: Spatial variation in water dissolved oxygen based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam.

30 0 m 5 m 10 m 20

Mean DO concentrations in mg/L in concentrations DO Mean 0

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Figure 8b: Dissolved oxygen variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam.

4.1.3 Electrical conductivity (EC)

Electrical conductivity is a measure of the ability of water to pass an electrical current. EC provides an estimate of dissolved ionic matter in the water (Odiyo et al., 2012). In Table 2, the electrical conductivity range from 282 -796 µS/cm and were not significantly different among the six sampling sites and among the three water depths profile (p > 0.05). There were significant differences however among sampling months for EC as determined by one-way ANOVA (p < 0.05) (Refer to evidence). The lowest EC value was recorded in late November 2011 at depth of 10 m, at site 3 at the confluence with the Crocodile River. The highest EC value was recorded in late April 2011 at depth of 5 m at the same site. (Figs. 9a & 9b) The dam had an annual mean electrical conductivity of 489.34 µS/cm. The EC in the impoundments investigated was slightly lower than those recorded by Owuor et al. (2007) in the dam .They recorded EC values ranging from 161 to 573 µS/cm in 2003 and 446 to 587 µS/cm in 2004. High values of electrical conductivity for raw water from Hartbeespoort Dam during the study period could be ascribed to runoffs containing dissolved ionic matters from agricultural land, industrial and domestic wastewater and sewage discharged from the Crocodile and Magalies Rivers. The length of the Magalies River is known for its intensive cultivation and livestock farming (Walsh and Wepener, 2009) and water quality is known to be reduced in the Crocodile River as result of high levels of nutrients received from the Hennops and the Jukskei Rivers (Walsh and Wepener, 2009). Low values of specific conductance are characteristic of oligotrophic impoundment (low nutrients) and high values of specific conductance are observed in eutrophic lakes where nutrients are in greater abundance (Videtich and Erik 2002). A pattern of low mean conductivity levels in summer months, moderate conductivity levels in winter months and high mean conductivity in autumn and spring months was observed in during the study period (Figs. 9a & 9b). These values indicated that major activities that impacted on water in the dam were at their minimum in summer; moderate in winter and at their maximum in spring and autumn months. The high level in EC could be

ascribed to heavy rains during spring and autumn months resulting in increases runoff rich in dissolved ionic matters from the tributaries.

1000 Site 1

800 Site 2

S/cm Site 3  600 Site 4 400 Site 5

Mean EC in EC Mean 200 Site 6

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Figure 9a: Spatial variations in water electrical conductivity based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam.

800 0 m

600 5 m

S/cm 10 m  400

200 Mean EC in EC Mean

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Figure 9b: Electrical conductivity vvariationsariations at different depths based on measurements at six sites (mean ± standard error) in the HartbeespoortHartbeespoort Dam.

4.1.4 Total suspended solids (TSS)

Total suspended solids (TSS) are a water quality parameter which provides an actual weight of the particulate material present in the sample. Only surface water from all the samples was analysed for all sample for TSS. Total suspended solids concentrations in the dam ranged from 2 -372 mg/L as seen in Table 2 and were significantly different among months (p < 0.05). No significant differences among sites were observed (p > 0.05) as determined by one-way ANOVA (Appendix, Table A). The lowest TSS value (2 mg/L) was recorded in late October 2011 at site 2. The highest TSS value (372 mg/L) was recorded in early August at site 5 positioned at the middle reach of the dam basin not far from the dam bridge. There were variations in TSS across all sites during the study period with spring and summer months recording highest TSS at some sites and autumn and winter months recording lowest TSS (Fig. 10). This indicated that the spring and summer rains experienced during the study period had a cumulative effect on TSS in the impoundment. The mean annual TSS value 63.61 mg/L was below the TWQR for aquatic ecosystem health of less than 100 mg/L, therefore TSS caused no harm to the dam overall. High concentrations of suspended solids can lower water quality by absorbing light. Waters then become warmer and lessen the ability of the water to hold oxygen necessary for aquatic life. Since aquatic plants also receive less light, photosynthesis decreases and less oxygen is produced. The combination of warmer water, less light and less oxygen makes it impossible for some forms of life to exist. According to Mvungi et al. (2003), depletion in DO could be indicative of contamination of water by solid waste. In this catchment specifically, suspended solids may result from erosion from urban runoff and agricultural land, industrial wastes, wastewater discharges, bank erosion from Crocodile and Magalies Rivers, the main tributaries of the dam. Modern agriculture is known to be responsible for increases in suspended solids (Skinner et al., 1997). Bottom feeders such as carp and algal growth may have also contributed to the high level of TSS in the impoundment.

Site 1 400 Site 2

300 Site 3 Site 4 200 Site 5

TSS in mg/L in TSS Site 6 100

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Figure 10: Spatial variations in surface water total suspended solids (TSS) in the Hartbeespoort Dam.

4.1.5 pH values pH of water is the measure of the concentration of hydrogen (H+) ions . Together with DO, it directly or indirectly influences other limnological parameters such as transparency, viscosity, total dissolved solids and conductivity (Araoye, 2009). The pH values as shown in Table 2 range between (6.95 and 9.91) which indicated that the dam was somewhat more alkaline during the study period. There were significant differences among sampling months for pH as determined by one-way ANOVA (p < 0.05) (Appendix, Table A). No significant differences between sites and between depths were recorded (p > 0.05). The dam has an annual mean pH of 8.29 (Table 2) which was not different from those recorded by Dörgeloh et al., (1993) (pH = 8.15) and Owuor et al. (2007) (pH = 8.4) in the Hartbeespoort Dam. It was also not different from those found for a number of eutrophic Dams in South Africa, e.g. Gariep Dam (pH = 8.25); Van der Kloof Dam, (pH = 8.0); Loskop Dam, (pH = 8.11) and Roodeplaat Dam, (pH = 8.0) (Dörgeloh et al., 1993). The highest value (pH = 9.91) was recorded in February 2011 at site 3, at the confluence with the Crocodile River, in the surface water and the lowest value (pH = 6.95) in August 2011 at site 2 in the surface water. Harding and Paxton (2001) stated that pH increased with increasing chlorophyll a concentrations and resulting in higher algal biomass, a consequence of elevated photosynthetic activity.

During photosynthesis the algae take up CO2, which lowers carbonic acid in the water and therefore increase the pH (Vos and Roos, 2005). pH values above 8 would then be favourable for algal growth. On average, all the months that cover the study period had pH values above 8 (Figs. 11a & 11b) making the dam alkaline. Figures 11a and 11b also indicated an increase in mean pH values over the 12 months of the study period, which favoured the growth of algae.

15 Site 1 Site 2 Site 3 10 Site 4 Site 5 Site 6 5 Mean pH values pH Mean

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Figure 11a: Spatial variations in water pH based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam.

15 0 m 10 m 10 5 m

5 Mean pH values pH Mean

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Figure 8: pH variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam.

4.2 Chemical water quality parameters

Water chemistry was characterised by spatial and temporal variability in water parameters during the study period and are illustrated in Table 3.

Table 3: Summary statistics of chemical water parameters and chlorophyll- a measured in the Hartbeespoort Dam between February 2011 and March 2012.

TWQR Chemical parameters Minimum values Maximum Mean (DWAF 1996) values ± SD

< 0.025 mg/L Total Phosphorus (T P, mg/L) 0.02 3.50 0.29 ± 0.38* Ammonium (NH4, mg/L) 0.02 1.58 0.22 ± 0.22* < 0.007 mg/L

Nitrate (NO3, mg/L) 0.3 21.2 4.33 ± 3.54 < 10 mg/L Nitrite (NO2, mg/L) 489.34 0.02 0.48 0.14 ± 0.07 < 10 mg/L 0-1 µg /L Chlorophyll a (µg /L) 489.34 0.13 8693 391 ± 1148*

# SD: Standard deviation.* indicate values above the TWQR for aquatic ecosystem health.

4.2.1 Total phosphorus

The total phosphorus concentrations as shown in Table 3 range between 0.02 and 3.50 mg/L. The lowest value (0.02 mg/L) was recorded in February 2011 at site 1 by the dam wall in the surface water and the highest value (3.50 mg/L) in late September 2011 at site 1 by the dam wall at a depth profile of 10 m (Appendix, Table B). Likewise, higher total phosphorus concentrations mean were recorded in winter months with decreases in phosphate levels in summer months (Figs. 12a & 12b). Within this period of study the mean annual total phosphorus concentration of 0.29 mg/L (Table 3) was unacceptably higher by almost tenfold than the acceptable TQWR value (< 0.025 mg/L,DWA,1996). It was revealed that the pooled mean for the current study (0.29 mg/L) was higher than those obtained from earlier studies by Owuor et al. (2007) of 0.038 mg/L. It revealed an increase in total phosphorus in the dam as the data showed significant differences. Many of the values obtained from this study fell within the mesotrophic category (0.005-0.025 mg/L; DWAF 1996) (Figs. 12a & 12b) under which nuisance growth of aquatic plants and cyanobacteria can occur. In water systems like the Hartbeespoort Dam, cyanobacteria often becomes the dominant micro-organism, where surface water becomes enriched with nutrients, like phosphorus from run-off of fertilized agricultural land (Davis et al., 2009). During this study period all sites had stages where the total phosphorous reached the eutrophic (0.025-0.25 mg/L; DWA 1996) level (Fig. 12a) where algae formed toxic bloom. The highest total phosphorus concentration mean was observed in late September by the dam wall at a depth profile of 10 m and the lowest from early January 2011 to early march 2012 almost at all sites and at surface water level (Figs. 12a & 12b). It may have been the result of the bloom mycrocystis sp. which started at these sites in late October and end in March 2012 where algae utilised the orthophosphates available for photosynthesis purposes, therefore growth. Fogg (1980) indicated that during blooms of planktonic algae in freshwater, concentrations of phosphate and nitrogen are at their lowest. This seemed to be the case in Hartbeespoort Dam, where the lowest mean concentration of phosphate in March 2012 coincided with the highest mean concentration of chlorophyll-a (Figs. 12a & 12b and Fig. 15). There were significant differences between months and between sites for total phosphorus concentrations as determined by one-way ANOVA (p < 0.05) (Appendix, Table B). No significant differences between depths (p > 0.05) were observed. High level in mean phosphorus concentrations where recorded at site 1 by the dam wall in September 2011 at surface water level (Appendix, Table B). The causes of high concentrations of phosphorus may due to water effluent from Tributaries Rivers. Wind direction pushed the nutrient load towards the dam wall where it accumulated. Water quality is known to be reduced in the Crocodile River as a result of high levels of nutrients received from the Hennops and Jukskei Rivers (Walsh and Wepener, 2009). Effluent rich in phosphates from the Northern Sewage works which services the extensive urban settlements at Alexandra and Diepsloot (Walsh and Wepener, 2009) also contributed to the high concentration of nutrient in the dam. This condition results in the dam becoming hypertrophic. Hot, dry periods promoted excessive growth of potentially toxic blue-green algae and waterweeds (hyacinths) resulting in users of water being adversely affected by the poor quality water in dam. It also impeded recreational activities and restrained the quality of life around the dam because of the bad smells which occurred during formation of algae hyperscum.

4 Site 1 Site 2 Site 3 3 Site 4 Site 5 2 Site 6 concentrations in mg/L in concentrations - 4 1

Mean PO Mean 0

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Figure 12a: Spatial variations in water total phosphorus concentrations based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam.

2.5 0 m 2.0 5 m 10 m 1.5

1.0 concentrations in mg/L in concentrations - 4 0.5

Mean PO Mean 0.0

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Figure 12b: Total phosphorus concentrations variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam.

4.2.2 Nitrate and nitrite

Nitrate and nitrite levels in natural waters are among the most important indicators of water quality since it gives a general indication of the nutrient status and level of organic pollution (Mohale, 2011). The highest concentration of nitrate (21.22 mg/L) was found at site 5 at a depth of 5 m in February 2011(Appendix, Table B). The lowest nitrate concentration (0.3 mg/L) was found on the surface at site 5 in January 2012 (Table 3). Nitrite concentrations showed the highest concentration in December 2011 (0.48 mg/L) at site 5 and at the depth of 10 m and the lowest in same year and month (0.022 mg/L) at site 2 at the depth of 10 m (Table 3). The annual mean concentrations for nitrate (4.33 mg/L) and nitrite (0.14 mg/L) were below the TWQR range for aquatic ecosystem (0-10 mg/L) (DWAF, 1996). Owuor et al. (2007) recorded a nitrate concentration in the dam that averaged 1.33 mg/L in 2004. It indicated that there has been an increase in nitrate levels in the impoundment over the years. There were significant differences between months for nitrate (p <0.05) and for nitrite concentrations (p < 0.05) as determined by one-way ANOVA (Appendix, Table B). Significant differences were also observed between sites (p <0.05) and between depths (p <0.05) for nitrite concentrations. No significant differences between sites and between depths (p > 0.05) were observed for nitrate. There was also an increase in mean nitrate in winter months of 2011 as opposed to summer months of the same year (Figs. 13a & 13b). Higher nitrate concentrations may signify deterioration in water quality (Owuor et al., 2007). Increased levels of nitrates often indirectly harm the environment by causing huge algae blooms (Yanamadala, 2005). The concentrations of nitrate dropped during March 2012 at all sites and this coincided with the increase in chlorophyll-a concentrations (Fig. 13a and Fig.15).

The depletion in nitrate could be ascribed to its uptake by phytoplankton. van Vuuren and Pieterse (1997) during their study on Vaal River observed that high algal blooms were accompanied by low concentrations of phosphorus and/or nitrogen. Davis et al. (2009) found that nitrates and phosphates significantly increased the growth rate of Microcystis. Low levels of nitrite could be ascribed to nitrification whereby in presence of dissolved oxygen, nitrite is converted into nitrate. Low levels in mean nitrate concentrations in summer months at all sites and at surface water level in the other side could be ascribed to its uptake by algae for photosynthetic activity under good wind conditions and warm temperatures. A pattern of high concentrations in mean nitrate concentrations in the dam were recorded at site 6, at site 1 and at site 3 (Fig. 13a & 13b) in the summer months of February and late November, throughout winter and the spring months. It could be ascribed to intensive cultivation and livestock farming occurring along the length of the Magalies River. The Crocodile River receives effluent from the Northern Sewage works which services the extensive urban settlements at Alexandra and Diepsloot (Walsh and Wepener, 2009). Sewage spillages and industrial discharges into the Hennops Rivers and waste dumps from Alexandra draining into the Jukskei River (Matowanyika, 2010) also contributed to the nutrients overload in the Crocodile River. Photosynthetic activities are reduced in winter due to low temperature, therefore reducing the uptake of nitrate by the algae during winter months. This could explain the steadily high values noted with regard to nitrate in the Hartbeespoort Dam. In addition, increased development in Soweto and inadequate infrastructure is expected to cause these increases in NO3 levels (RHP, 2005). This situation contributes to the hypertrophic condition observed in the dam up to the end of the study period.

Site 1 20 Site 2 Site 3 15 Site 4 Site 5 10 Concentrations in mg/L in Concentrations Site 6 - 3 5

Mean NO Mean 0

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0.5 Site 1 Site 2 0.4 Site 3 Site 4 0.3 Site 5 Site 6 0.2 Concentrations in mg/L in Concentrations - 2 0.1

Mean NO Mean 0.0

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Figure 13a: Spatial variations in water nitrate and nitrite concentrations based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam.

0 m 15 5 m 10 m 10 Concentrations in mg/L in Concentrations - 3 5

Mean NO Mean 0

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0.5

0 m 0.4 5 m 10 m 0.3

0.2 Concentrations in mg/L in Concentrations - 2 0.1

Mean NO Mean 0.0

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Figure 13b: Nitrate and nitrite concentrations variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam.

4.2.3 Ammonium

Ammonium concentration in the dam ranged from 0.02 mg/L in early March 2012, site 5 at dam surface to 1.58 mg/L in mid-January 2012, at site 4, at the depth of 10 m (Table 3). There was significant differences between months and between sites for ammonium (p < 0.05) as determined by one-way ANOVA(Appendix, Table B). No significant differences between depths (p < 0.05) were observed. Within this period of study the mean ammonium concentration of 0.22 mg/L (Table 3) was excessively higher by nearly thirty fold than the acceptable TQWR value (< 0.007 mg/L, DWAF, 1996). This value was close to that obtained by Owuor et al. (2007) of 0.197 mg/L. It indicated that ammonium concentration has remained steady in the impoundment over the years. Figures 14a and 14b indicated that there was a variation in the mean values for ammonium during the period of study, a sign of the occurrence of organic constituents within the dam. Melody and Dodds (2002) stated that the possible fates of ammonium (NH₄⁺) within the system could include biotic uptake, nitrification, volatilisation and absorption. These lower and higher concentrations were observed in the upper surface (0-5 m) (epilimnion) compared to the lower part (hypolimnion) of the dam (10 m) (Figs.14a & 14b). This confirmed that the hypolimnion is a region of reduced chemical species (ammonium), while the epilimnion is dominated by oxidised (nitrate - nitrogen) species. Both oxidised and reduced forms of nitrogen were present interchangeably depending on the level of denitrification, which were possible in a partially anaerobic system like Hartbeespoort Dam. When ammonia volatilises, it is subsequently lost from the water surface and hence a decrease in concentration may be observed in water. The mean ammonium concentrations at site 1 and site 2 in the surface water in June 2011 were higher than the mean ammonium concentrations at the rest of the sites. It indicates the presence of material with a high organic loading at these sites as ammonium accumulates from the decomposition of organic matter from sediments under anaerobic conditions. The Target Water Quality Range (TWQR) for un-ionised ammonia is <= 0.007 mg/L and the Acute Effect Value (AEV) is 0.1 mg/L (DWAF, 1996). Within this period of study the mean ammonium concentration of 0.22 mg/L was twice the AEV. The high temperature combined with the high pH of 8.1(Table 2) present the situation that up to 15 % of the ammonium available is in the toxic free ammonia form (DWAF, 1996). Taking this into consideration, the un-ionised ammonia during late November 2011, early January 2012 and early March 2012 months might have been lethal to the aquatic ecosystem. Fortunately no dead aquatic organism where found during the study period at these specific months. Another major difference in water quality observed during this study was the extent of available oxygen in those specific months. The acute toxicity of ammonia to aquatic organism increases as dissolved oxygen decreases a condition observed in the dam in 1999, where fish were killed (DWAF, 1999).

Site 1 2.0 Site 2 Site 3 1.5 Site 4 Site 5

1.0 Site 6 concentrations in mg/L in concentrations + 4 0.5

Mean NH Mean 0.0

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Figure 14a: Spatial variations in water ammonium concentrations based on measurements at three depths (mean ± standard error) in the Hartbeespoort Dam.

1.5 0 m 5 m 10 m 1.0

concentrations in mg/L in concentrations 0.5 + 4

Mean NH Mean 0.0

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Figure 14b: Ammonium concentrations variations at different depths based on measurements at six sites (mean ± standard error) in the Hartbeespoort Dam.

4.3 Trace metals

Trace metals are part of the vital micronutrients, which by nature are required by plants even though in small or trace quantities (Owuor et al., 2007). Metal levels in water can be either toxic or non-toxic to aquatic organisms, depending on whether the metal concentration and the element are an essential element or not (Greenfield et al., 2012). The occurrence of trace metals together with other factors in this dam could be considered favourable explanation of growth dynamics of the cyanobacteria present and henceforth persistence in the dam (Owuor et al., 2007). Only surface water was considered for trace metal analysis and the results are shown in Table 4.

Table 4: Summary statistics of trace metals and the corresponding TWQR values in the Hartbespoort Dam between February 2011 and March 2012.

Minimum Maximum Mean TWQR Metals values values ±SD (1996)

Ca (mg/L) 1.19 28.80 12.71 ± 4.44 N/A Mg (mg/L) 0.50 11.12 6.04 ± 1.99* 0.05 - 1 mg/L

Na (mg/L) 1.18 23.67 11.06± 4.32 N/A K (mg/L) 13.95 80.33 34.49 ± 12.02 N/A Al (µg/L) 4.48 90.40 19.15 ± 17.19* <10 µg/L (pH < 6.5) µg/L g/L) Mn (µg/L) 0.01 56.57 7.44 ± 8.70 < 180 µg/L

Table 5 continued: Summary statistics of trace metals and the corresponding TWQR values in the Hartbespoort Dam between February 2011 and March 2012.

Cr (µg/L) 1.20 25.35 7.30 ± 4.90 < 12 µg/L Fe (µg/L) 3.75 631.62 144.85 ± 167.49 N/A Ni (µg/L) 0.45 327.41 11.27± 38.15 N/A Cu (µg/L) 0.17 77.32 12.67 ± 15.67* < 1.20 µg/L Zn (µg/L) 1.11 271.29 26.72 ± 37.80* < 2 µg/L As (µg/L) 0.03 24.03 1.39 ± 3.02 < 10 µg/L Se (µg/L) 0.080 12.40 3.75 ± 3.42* < 2 µg/L Ag (µg/L) 0.13 22.76 2.20 ± 2.90 - Cd (µg/L) 0.04 9.19 0.84 ± 1.31* < 0.15 µg/L Pb (µg/L) 0.15 18.43 3.17 ± 4.14* < 1 µg/L

# SD: Standard deviation.* indicate values above the TWQR limits for aquatic ecosystem. N/A means not applicable. - Indicate that TWQR value was not available.

Metal concentrations in water had the following decreasing order: Macro elements: potassium > calcium >sodium > magnesium. Micro elements: iron >zinc > aluminium > copper > nickel > manganese > chromium> selenium > lead > silver > arsenic > cadmium.

Aluminium Aluminium had a mean concentration of 19.15 µg/L (Table 4) and ranged between 4.48 µg/L at site 3 at the confluence with Crocodile River inflow during March 2012 to the highest recorded value of 90.40 µg/L at site 5 in January 2012 (Appendix, Table C1). Arsenic Arsenic had a mean concentration of 1.39 µg/L and ranged from 0.03 µg/L at site 1 in late February 2011 to 24.03 µg/L at site 2 during late August 2011 (Appendix, Table C2). Cadmium Cadmium had a mean concentration of 0.84 µg/L (Table 4).The lowest cadmium concentration of 0.04 µg/L was recorded in early March 2012 at site 6 by the dam bridge at the Magalies River inflow .The highest concentration of 9.19 µg/L was recorded in late November 2011 at site 1 by the dam wall. (Appendix, Table C2). Calcium Calcium had a mean concentration of 12.71 mg/L (Table 4) and ranged between 1.19 mg/L at site 1 by the dam wall of the during June 2011 to the highest recorded value of 28.8 mg/L at site 2 randomly considered within the dam basin and close to the Crocodile River inflow in June 2011(Appendix, Table C1). Chromium Chromium had a mean concentration of 7.44 µg/L and ranged from 1.20 µg/L at site 1 in late February 2011 to 25.35 µg/L at site 2 in December 2011(Appendix, Table C1). Copper Copper had a mean concentration of 12.67 µg/L and ranged from 0.17 µg/L at site 6 in early December 2011 to 77.32 µg/L at site 2 close to Crocodile River inflow during late September 2011 (Appendix, Table C2). The annual mean concentrations for copper in the current study was lower (12.67 µg/L µg/L) compared to the value obtained in by Owuor et al. (2007) of 78 µg/L. Iron Iron concentrations ranged from 3.75 µg/L at site 5, in late September 2011 to 631.62 µg/L at site 4 positioned at the middle reach of the dam basin in early December 2011 (Appendix, Table C1). The mean annual iron concentrations in the dam was 144.85 µg/L. Comparing this value to that obtained in earlier studies by Owuor et al., 2007 (86 µg/L) revealed that the two sets of data had significant difference in mean concentrations. The mean pooled values were higher for the current study. Iron concentrations in the dam have increased over the years. It could be ascribed to the increase in mining activities in the catchment. Lead Lead had a mean concentration of 3.17 µg/L (Table 4).The lowest lead concentration of 0.15 µg/L was recorded in late February 2011 at site 1 by the dam wall. The highest concentration of 18.43 µg/L was recorded in late November 2011 at site 1. (Appendix, Table C2). The mean concentration of lead (3.17 µg/L) was nevertheless lower in the present study than in the study conducted by Scott et al. in 1979 (56 µg/L). Magnesium Magnesium had a mean concentration of 6.04 mg/L and ranged between 0.50 mg/L at site 1 during June 2011 to the highest recorded value of 11.12 mg/L at site 6 by the dam bridge at the confluence with the Magalies River in late February 2011(Appendix, Table C1). Manganese Manganese had a mean concentration of 7.44 µg/L and ranged between 0.01µg/L at site 6 in January 2012 to 56.57µg/L at site 3 in late August 2011 (Appendix, Table C1). The manganese level in the current study is lower than the one obtained by Owuor et al. (2007) in 2004 of 91 µg/L.

Nickel Nickel had a mean concentration of 12.67 µg/L and ranged from 0.45 µg/L at site 3, in March 2012) to 327.52 µg/L during late November 2011at site1 (Appendix, Table C2). Potassium Potassium had a mean concentration of 34.49 mg/L and ranged between 13.95 mg/L at site 1 during June 2011 to recorded value of 80.33 mg/L at site 5 in late May 2011(Appendix, Table C1). Selenium Selenium had a mean concentration of 3.75 µg/L and ranged from 0.080 µg/L at site 1 in late February 2011 to 12.40 µg/L at site 2 during late August 2011 (Appendix, Table C2). The higher levels of selenium experienced may result from erosion caused by urban runoff. The intensive use of pesticides in agricultural practices along the Magalies River and the burning of fossil fuels as an energy source in the cold winter months, in the wide urban informal settlements of Soweto, Alexandra and Diepsloot could have led to the increased selenium levels. Litters directly discharged into the Crocodile River, one of the tributaries of the dam ,could also explain the high level in selenium (Greenfield et al., 2012). Silver Silver had a mean concentration of 2.20 µg/L and ranged from 0.13 µg/L at site 1 in early January 2011 to 22.76 µg/L at site 4 during late May 2011 (Appendix, Table C2). Sodium Sodium had a mean concentration of 11.06 mg/L and ranged between 1.18 mg/L at site 1 during June 2011 to the highest recorded value of 23.67 mg/L at site 5 positioned at the middle reach of the dam basin in late May 2011(Appendix, Table C1). Zinc Zinc had a mean concentration of 26.72 µg/L and ranged from 1.11 µg/L at site 6 in early December 2011 to 271.29 µg/L at site 1 during late September 2011 (Appendix, Table C2). Most of zinc concentrations recorded was above the TWQR of 2 µg/L at all six sites. A study by Owuor et al. (2007) recorded zinc concentrations ranging from 71 µg/L to 86 µg/L in 2004 in the dam. There has been an increase in zinc in the impoundment over the years and it could be ascribed to an increase in mining activities in the catchment.

When the annual trace mean values (Table 4) obtained in this study were compared to the TWQR values for aquatic ecosystem (DWAF, 1996), aluminium, copper, zinc, selenium, cadmium, magnesium and lead had values above the TWQR ranges, except for manganese, chromium and arsenic. There were significant differences between months for iron, copper and lead concentrations (p < 0.05) as determined by one-way ANOVA. No significant differences between sites were observed for iron, aluminium, copper, zinc, selenium, cadmium and lead (p < 0.05). Based on this study, it was not possible to determine any direct relationships between metal levels and phytoplankton growth or their persistence in the dam. However, high concentrations of some trace elements such as iron, aluminium, copper, zinc, selenium, cadmium, magnesium and lead were observed in the dam over the study period ( Appendix Table C (C1; C2)). The ability of algae to survive and reproduce in habitats that are polluted by metal ions may depend on genetic adaptations that they have developed over time (Oberholster et al., 2010). The presence of particular cations affects the accumulation of metals and decreases their toxicity to phytoplankton, probably due to competition and/or complexation and co-precipitation (Oberholster et al., 2010). High concentrations of phosphorus recorded in the dam during the study period could also have decreased the toxicity of a number of heavy metals, whereas extracellular products of algal origin have also been reported to reduce metal toxicity (Reed and Gadd, 1990). Since cyanobacteria depend upon a variety of metal cations to maintain their cellular metabolism (Oberholster et al., 2010), some of these metals, e.g., iron, copper, zinc and selenium which were present in high concentrations may have possibly contributed to phytoplankton growth. Trace metals which are essential for phytoplankton growth are incorporated into essential organic

molecules, particularly a variety of coenzyme factors which are part of the photosynthetic reactions. Of these metals, the concentrations of Fe, Mn, Zn, Cu and Co and sometimes Mo and Se in natural waters may be limiting to algal growth (Brand, 1990).

4.4 Chlorophyll-a (Chl-a) quantification

One of the measures of quantifying phytoplankton abundance is chlorophyll-a concentration (Chutter, 1989). In this study, only surface water was analysed for chl-a and the values are illustrated in Fig.15. As can be seen from Table 3, the chl-a concentration ranged from 0.14 µg/L to 8693 µg/L. The lowest value was recorded in late August 2011 at site 5 and the highest value in March 2012, at site 4 positioned at the middle reach of the dam basin. The dam has mean chlorophyll-a concentration of 391 µg/L (Table 4) and it was higher than the TWQR value for aquatic ecosystem health of < 1 µg/L by almost four hundred fold. Chlorophyll-a values in Hartbeespoort Dam are known to average around 200 µg/L, with values over 1000 µg/L being frequently recorded (Matthews et al., 2012). The mean chl-a concentration was compared to that obtained in earlier studies by Owuor et al. (2007) of 55.78 µg/L. These two means indicated significant differences. The mean chl-a concentration for the current study was sevenfold higher than the concentration obtained by Owuor et al. (2007). This indicated that levels of bloom formation have increased and continued over the years in the dam. There were no significant differences between months (p > 0.05) and between sites (p > 0.05) for chlorophyll-a concentration in the dam as determined by one- way ANOVA. Considerable algal blooms were detected in late September 2011 (3451.86 µg/L) at site1 by the dam wall, near the exit conduits, in late November 2011 (1915.28 µg/L), at site 5 and in January 2012 (1830.73 µg/L) at site 5 positioned at the middle reach of the dam basin (Fig. 15). The highest bloom was observed in March 2012 at site 4 in the middle reach of the dam basin with chlorophyll-a concentrations reaching the level of 8693 µg/L. The highest concentrations of chlorophyll-a recorded in this study coincided with low concentrations of nitrate and phosphorous (Figs. 12a & 12b and Figs. 13a & 13b). The low concentrations of the nutrients together with high chlorophyll-a concentration show that the nutrients were used by phytoplankton for photosynthesis. There were reduced levels of chlorophyll-a concentration observed in May 2011 (0.28 µg/L) at site 3, at the confluence with the Crocodile River, in June 2011 (0.20 µg/L) at site 1 by the dam wall and in late August 2011 (0.22 µg/L) at site 6 by the dam bridge (Fig. 15). Blooms with higher intensities seemed to occur during summer and spring months and bloom with lower intensities during autumn and winter months in the Hartbeespoort Dam. Temperature seemed to be among the significant environmental factors that influenced the bloom therefore increased chlorophyll-a quantity. It is commonly perceived that warm temperatures support cyanobacterial growth (Wood, 1993). A study by Robarts and Zohary (1987) concluded that temperature was the second most important factor affecting the Microcystis bloom in the Hartbeespoort Dam. Higher intensities of algal blooms were regularly detected at sites 1, 4 and 5 during summer months( Appendix Table B). Wind directions toward the dam wall could explain accumulation of chlorophyll-a at site 1. Effluents rich in nutrients such as phosphorus and nitrate from both Magalies and Crocodile Rivers could explain the high chlorophyll-a content at sites 4 and 5 which are not far from Crocodile and Magalies Rivers inflows respectively( Appendix Table B). Nutrients (phosphorus and nitrate) at site 1, 4 and 5 were very low during summer months (Fig. 12a and Fig.13a). Temperature in the other side was above 23 °C on average (Fig. 7a). Those conditions favoured the uptake of nutrients by algae resulting in high chlorophyll-a production. Areas around sites 1, 4 and site 5 in the Hartbeespoort Dam have been identified as some of the historical algae concentration zones due to their locations and conditions that favour massive algal cell aggregations and growth (Zohary.1985) and therefore their proliferation and bloom formation.

10000 Site 1

Site 2 8000 g/L)  Site 3

6000 Site 4 Site 5

4000 Site 6

2000 Chl a concentrations ( a concentrations Chl

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Figure 15: Spatial variations in surface water Chlorophyll-a concentrations in the Hartbeespoort Dam.

Figure 16 below, showed relationships between dissolved oxygen, temperature and chlorophyll-a change. The first relationship indicated that as temperatures of the water increased, the concentrations of chlorophyll-a increased and that of the dissolved oxygen increased as well. An increase in algal concentrations consequently increased photosynthetic activity, therefore release oxygen to the water during some summer months. van Vuuren and Pieterse (1997) reported that in the majority of South African impoundments, maximum chlorophyll-a concentration correspond to high water temperatures. The second relationship indicated that a decrease in temperature was followed by a decrease in chlorophyll-a and subsequently a decrease in DO, mostly during the winter season where photosynthetic activities were very low. The third relationship indicated that as temperatures of the water were extremely high, the concentrations of chlorophyll-a increased and that of the dissolved oxygen decreased. According to Dallas and Day (2004) increased temperatures reduce the solubility of oxygen in water, decreasing the amount that can physically dissolve and hence be available to aquatic organisms. Low chlorophyll-a concentrations was observed after physical removal of algae in the dam, which seemed to have increased with temperature.

30 2.0 Temperature

Chla (mg/L)variations Chla DO 1.5 20 Chla

1.0

C) DO( & mg/L) variations 0.5 

0 0.0 Temps(

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Figure 16: Relationships between dissolved oxygen, temperature and chlorophyll-a variations during period in the Hartbeespoort Dam the study.

4.5 Phytoplankton population

Phytoplankton communities are sensitive to changes in their environment and, therefore, phytoplankton biomass and many phytoplankton species are used as indicators of water quality (Vuorio et al., 2007). Surface water was analysed for Phytoplankton distribution and the results are illustrated in Table 5. Six different algal divisions and 13 macroalgal species were found in the dam during the study period. The number of some singular species although varied in their biovolume percentage counts monthly. Cyanophyta (cyanobacteria) comprised 95 % (5 species) of total species and were dominant. The remaining divisions were Chlorophyta with 2.3 % (3 species), Pyrrophyta with 0.93 % (1 species), Crytophyta with 0.71 % (1 species), Chrysophyta with 0.5 % (2 species) and Euglenophyta with 0.29 % (1 species). M.aeruginosa with 69 % was the most dominant species in the dam (Fig.17).

Table 6: Distribution in percentage of algal divisions and species in the Harbeespoort Dam between February 2011 and March 2012.

Algal divisions Algal species species % Divisions % M.aeruginosa 69 Anabeana sp. 22 Cyanophita Oscillatoria sp. 3.26 95 Anthrospira sp. 0.69 Cylindrospermopsis sp. 0.35 Melosira granulate 0.21 Chrysophyta 0.5 Cyclotella sp. 0.28 Chlorophyta Oocystis sp. 1.25 2.3

Table 7 continued: Distribution in percentage of algal divisions and species in the Harbeespoort Dam between February 2011 and March 2012.

Algal divisions Algal species species % Divisions % Scenedesmus sp. 0.42 Sprirogira sp. 0.63

Crytophyta Cryptomonads sp. 0.71 0.71

Pyrrophyta Ceratium sp. 0.93 0.93

Euglenophyta Euglena sp. 0.29 0.29

Phytoplankton communities were identified as:

4.5.1 Cyanophyta (Blue green algae)

As illustrated in Fig.17, cyanophites accounted for 95 % of the total algal population found in the Hartbeespoort Dam during the study period. The cyanophytes were represented by the following species:

4.5.1.1 Microcystis aeruginosa

The species was found in the Hartbeespoort Dam and arose in the forms of net-shaped colonies of Microcystis aeruginosa forma forma flos aquae (Zohary et al., 1996). Microcystis aeruginosa accounted for 69 % of the total algal composition and was the dominant species almost throughout the sampling period across at all sites. According to Matthews et al., 2012, the phytoplankton assemblages in the Hartbeespoort Dam are known to be near-permanently dominated by the colonial cyanobacterium M. aeruginosa. There was, however a decrease in this species count as compared to previous studies. Hambright and Zohary (2000) recorded 90 %, Owuor et al. (2007) noted 80 % and Oberholster et al. (2010) recorded 80 %. This could be ascribed to mechanical removal of algae from the impoundment as part of Hartbeespoort Dam “me tsi a me “rehabilitation project by the Department of Water Affairs. There was significant differences between months for M. aeruginosa (p < 0.05) as determined by one-way ANOVA. No significant differences between sites (p > 0.05) were observed.

4.5.1.2 Anabeana sp. This species accounted for 22 % (Table 5) of the total algal composition and was observed associated with Microcystis colonies. It had almost uniform presence in the water column. While some of the species had straight trichomes, others had slightly curved trichomes with barrel shaped cells. The species were observed more during late winter but the number decreased as summer approached.

4.5.1.3 Oscillatoria sp. The species accounted for 3.26 % of the total algal composition (Table 5) and was filamentous, elongated and had straight trichomes. When observed in groups, these trichomes were entangled with one another.

They were always observed gliding through in the sample. They were present uniformly in the water column in summer months. No species was however found during winter months.

4.5.1.4 Arthrospira sp. The species accounted for 0.69 % of the total algal composition (Table 5) and has unbranched filaments .They were observed during summer months as solitary and free and floating, or in microscopic mats, more or less screw-like and more or less freely coiled along the whole length, with unchanged or continually changing width of screws.

4.5.1.5 Cylindrospermopsis sp. The species accounted for 0.35 % of the total algal composition (Table 5).They were observed in very small quantity in the dam, only during March 2012. The species was cylindrical with solitary trichomes and appeared blue-green.

4.5.2 Chrysophyta (Yellow green algae)

As illustrated in Fig.17, Chrysophytes accounted for 0.5 % of the total algal population found in the Hartbeespoort Dam during the period of study. The Chrysophytes were represented by the following species:

4.5.2.1 Melosira granulate The species accounted for 0.21 % of the total algal population. The species had cells that were cylindrical and united into long filaments. The lengths of the cells were greater than the breath. The species were greater in winter months than in summer.

4.5.2.2 Cyclotella sp. The species accounted accounted for 0.28 %, of the total algal population (Table 5). The cells were decoid, drum shaped and were either in pairs or solitary (Truter, 1987). This species was frequently present small quantity in winter months. However, no observations were made regarding the species in summer months.

4.5.3 Chlorophyta (Green algae)

As illustrated in Fig.17, Chlorophytes accounted for 2.3 % of the total algal population. The Chlorophytes were represented by the following species:

4.5.3.1 Oocystis sp. This species accounted for 1.25 % (Table 5) and had cells that appeared ovoid with smooth walls. They were present in colonies with few cells. The species were greater in winter months than in summer.

4.5.3.2 Scenedesmus sp. The species accounted for 0.42 % and consisted of flat colonies of a few cells, which were ovoid, fusiform or rectangle in shape. The single chromatophore was parietal in nature. The flat colonies were in most cases ling side by side in double rows. They were irregularly observed during winter months throughout the study period.

4.5.3.3 Sprirogira sp. The species represented 0.63 % of the total phytoplankton community observed in the dam during the study period (Table 5).The species was filamentous and green. Its filamentous thallus consisted of many cylindrical cells which were joined from end to end to form long, unbranched filaments. The species occur in summer months.

4.5.4 Crytophyta (Cryptomonads)

Cryptomonads represented 0.71 % (Fig.17) of the total phytoplankton community observed in the dam during the study period .The species had cells that were oval in shape. Variedly, it had one or two parietal chloroplasts, with broader cells at the anterior end (Truter, 1987). The two flagella were unequal. The species occur in summer months.

4.5.5 Pyrrophyta (Dinoflagellates)

As illustrated in Table 5, Pyrrophyta accounted for 0.93 %( Fig.17) of the total algal population present in the dam during the study period. The Dinoflagellates were represented by the following species:

4.5.5.1 Ceratium sp. The species accounted represented 0.93 % (Table 5) of the total algal population present in the dam during the study period. The species was observed inconsistently throughout the period of study in the water column samples. These are unicellular dinoflagellated motile algae. They had a conspicuous cell wall that bore large spines and elaborate cell wall processes. The species is capable of sexual reproduction, but asexual reproduction occurs by the formation of aplanospores (van Ginkel et al., 2001). The algae were primarily a mid-summer species and were scarce or absent in winter months (Moore 1981; Van Ginkel et al., 2001).

4.5.6 Euglenophyta

As illustrated in Fig.17, Euglenophyta accounted for 0.29 % of the total algal population. The Euglenophytes were represented by the following species:

4.5.6.1 Euglena sp. The species represented 0.29 % of the total algal population present in the dam during the study period (Table 5).The species was not well represented and was only recorded sometimes in the surface water column in winter months. Rarely was this species observed in summer months. The species had cells that were either firm with fine spiral striations or rows of granules or sometimes soft or pliable, changing shape when in movements.

150 60

40 100

Algal % distributions % Algal 20 50 Algal groups % distributions % groups Algal 0 0

MelosiraOocystis CeratiumEuglena Anabeana Cyclotella Spirogyra OscillatoriaAnthrospira Cyanophita Crytophyta Pyrrophyta Chrysophyta Chlorophyta M.aeruginosa ScenedesmusCryptomonads Euglenophyta

Cylindrospermopsis Algal groups Algal species

Figure 17: Percentage algal groups and species abundances in the Harbeespoort Dam during the study period.

4.6 Multivariate statistical analysis for water quality variables

4.6.1 Pearson product-moment correlation matrix

A Pearson product-moment correlation coefficient was computed to assess the relationship between physico-chemical water quality parameters, iron and chlorophyll-a concentrations and is illustrated in Table 6.

Table 8: Pearson 2-tailed correlation matrix for physico-chemical parameters recorded in the Hartbeespoort Dam during the study period.

Variables 1 2 3 4 5 6 7 8 9 10 1.Temperature - - 0.075 0.240* -0.232* -0.099* -0.461** 0.609** -0.441** -.0260* 0.298* 2.Dissolve oxygen 0.075 - -0.109 0.124 0.061 0.304** 0.135 -0.036 0.104 -0.090

3. Chlorophyll-A 0.240* -0.109 - -0.146 0.012 -0.126 -0.179 0.239* -0.166 -0.154

4.Total Phosphorus -0.298* 0.124 -0.146 - 0.102 0.329** 0.241* -0.100 0.044 -0.133 (TPO4)

5.Ammonium (NH4) -0.232* 0.061 0.012 0.102 - 0.236* 0.362** -0.297* 0.222 -0.137

6.Nitrate(NO3) 0.304* 0.329* -0.099* -0.126 0.236* - 0.204 -.008 -0.056 -0.013 * * 7.Nitrite (NO2) -0.461** 0.135 -0.179 0.241* 0.362** 0.204 - -0.262* 0.385** 0.008

8.pH 0.609** -0.036 0.239* -0.100 -0.297* -0.008 -0.262* - -0.282* -0.393**

9.Electrical Conductivity -0.441** 0.104 -0.166 0.044 0.222 -0.056 0.385** -0.282* - -0.004 (EC)

10.Iron (Fe) - - -0.260* -0.154 -0.133 -0.137 -0.013 0.008 -0.004 - 0.090* 0.393** * Correlation is significant at the p < 0.05 level (2-tailed).

**Correlation is significant at the p < 0.01 level (2-tailed).

There was a positive correlation between temperature and chlorophyll-a and pH (r = 0.240; 0.609) respectively, and between chlorophyll-a and pH, r=0.239. Increases in temperature correlated with increase in chlorophyll-a and strong elevation of pH (Table 6). This could be explained by the fact that the high nutrient loads from Hartbeespooort Dam tributaries (Magalies and Crocodile Rivers) are been used when temperatures are reasonably high by the algae for their growth. It results in an increase photosynthetic activity of the algae which influences the DO and pH. Therefore the higher the photosynthetic activity, the higher the DO will be, with a subsequent increase in pH.

There were negative correlations between temperatures and total phosphorus, ammonium, nitrate, nitrite, electrical conductivity and iron (r= -0.298;-0.232;-0.099;-0.461; -0.441,-0260) respectively (Table 6). As temperatures increased, the above mentioned parameters decreased. When temperatures are reasonably high in the dam, available nutrients such as phosphorus and nitrate and some trace metal in the form of iron

are been used by algae for their growth. The decrease in ammonium and nitrite is certainly due to nitrification that occurred in the dam under high temperatures whereby, ammonium is converted into nitrite and subsequently into nitrate.

There was a strong positive correlation between dissolve oxygen and nitrate, r = 0.304. An increase in nitrate concentration led to increase in dissolve oxygen and vice versa. There were positive correlation between total phosphorus and nitrite and strong positive correlation with nitrate (r= 0.241, 0.329) respectively (Table 6). An increase in total phosphorus concentration led to an increase in nitrite, and a considerable increase in nitrate. There were positive correlations between ammonium and nitrate and strong positive correlation between ammonium and nitrite (r= 0.236, 0.362) respectively (Table 6). An increase in ammonium concentration led to an increase in nitrate, and a considerable increase in nitrite. During nitrification, in the presence of dissolved oxygen (DO) ammonia is converted into nitrite and then nitrite into nitrate.

There were negative correlations between ammonium and pH (r= -0.298). An increase in ammonium correlated with a decrease in pH (Table 5). There were negative correlations between pH, nitrite and electrical conductivity (r= -0.262, -0.282) respectively (Table 6). As pH increased there were decreases in nitrite concentrations and electrical conductivity.

There was a strong negative correlation between pH and iron (r=-0.393). An increase in pH led to a considerable decrease in iron and vice versa.

Overall the increase in temperature under favourable wind conditions in the Hartbeespoort Dam resulted in the uptake of nutrients such as phosphate, nitrate, nitrite, some trace element like iron by algae in the dam. It led to production of chlorophyll-a which at the same time increased dissolved oxygen and pH in the dam. Phosphorus and nitrate played the role of limiting nutrients in the dam and their accumulation followed similar patterns during the study period in the dam. Fertilizers, urban runoffs, untreated sewage and acid mine drainage in the catchment through Magalies and Crocodile Rivers might have been the primary sources of high nutrients and trace metals observed. Remobilisation of these nutrients by fish from sediments may have also caused an increase in phosphorus and nitrate in the dam. During winter months as temperature decreased an increase in the phosphorus, ammonium, nitrate, nitrite, DO, EC and iron was observed in the dam due to decrease in in photosynthetic activities of algae.

4.6.2 Canonical Discriminant Functions Analysis (CDFA)

Canonical discriminant functions analysis (Kieslowski and Adams,2013). for all the water quality variables recorded in the Hartbeespoort Dam which showed (dis)similarities spatially and temporally are illustrated in Figs.18a & 18b.

CDFA1 plot (Fig.18a) which represents the relationships between sampling months and water quality variables describes 84.6 % variation in data (eigenvalues). Sampling months 1, 8 and 9 were similar to each other in terms of water quality variables as they corresponded to the period re-stratification of the dam. The water quality variable that best describes the existing grouping and similarities might have been high temperatures and high level of DO therefore high chlorophyll-a concentrations. An increase in dam inflows from rain during those months might also have caused patchiness in water quality variables compared to other months. Sampling months 2 and 3 were similar to each other in terms of water quality variables and matched with the period of overturn that occurred in the dam. The water quality variable that best describes the existing grouping and similarities might have been decreases in temperatures and

moderately low levels of DO and TSS, high EC levels and a decline in chlorophyll-a concentrations. Sampling months 4, 5, and 6 have similarities in water quality variables. They corresponded to the winter season. Similarities between these months as compared to the rest of the sampling months were ascribed to low temperatures, low DO levels, high total phosphorus and nitrates levels and therefore low photosynthetic activities. Sampling months 10, 11, and 12 were analogous to each other in terms of water quality variables and corresponded to summer season. Resemblances between these months as compared to the rest of the sampling months were attributed to high temperatures, low DO levels, low total phosphorus and nitrates levels and therefore high photosynthetic activities. Sampling month 7 which corresponded to spring month described unique pattern in water quality recorded. The water quality variables that best describes water quality recorded during sampling month 7 were increased water temperatures, high DO and TSS levels, moderately high EC, phosphorus, nitrate , ammonium levels and high chlorophyll-a concentrations. It could be assigned to the increase in nutrients content of the dam from heavy spring rains that supported photosynthetic activities of algae at high temperatures. Through the rains, the entering water adds nutrients to the impoundment and it also flushes the system of algae. The dam restarts its ecological cycles of nutrient availability for the algae to take up and increase in numbers (Vos and Roos, 2005).

Figure 18a: Temporal Canonical Discriminant Functions Analysis (CDFA1) based on water quality variables measured in the Hartbeespoort Dam.

*1: 28-February-2011; 2: 29-March-2011; 3: 25-May-2011; 4: 14-June-2011; 5: 02-August- 2011; 6: 24- August-2011; 7: 28-September-2011, 8: 30-October-2011, 9: 23-November-2011; 10: 05-December-2011, 11: 19-January-2012, 12: 05-March-2012.

A CDFA2 ordination of water quality variables for study sites is indicated in Fig. 18b. The plot describes 59.1 % variation in data (eigenvalues). Study sites 5 and 6 close to the Magalies River inflow were similar to each other in terms of water quality variables as they received effluents rich in phosphate and nitrate

from the Magalies River. Referring to specific variables, sites 1 by the dam wall near exit conduits and site 4 in the middle reach of the dam basin varied in water quality parameters in comparison to other sites and indicated spatial variations. Wind direction toward the dam wall could explain accumulation of nutrients therefore phytoplankton and chlorophyll-a at site 1 resulting in disparities in most of the water quality variables recorded. High water retention time at site 4 could explain the dissimilarities from other study sites. Sites 2 and 3 at the inflow of the Crocodile River were very similar in terms their water quality variables as they received effluents rich in phosphate and nitrate from the Crocodile River. The water quality variables that best describes the prevailing grouping and similarities at site 2 and 3 were EC, TSS , trace metals concentrations, phosphorus , nitrate and chlorophyll-a.

Figure 18b: Spatial Canonical Discriminant Functions Analysis (CDFA2) based on water quality variables measured in the Hartbeespoort Dam.

Chapter 5

Conclusions and Recommendations

5.1 Conclusions

This study showed that Hartbeespoort Dam is a hypertrophic impoundment with continuous changes in physico-chemical and biological parameters spatially and temporally. From this study, as illustrated in figures and tables, it can be concluded that while parameters such as pH and electrical conductivity slightly changed spatially and temporally over the study period, there was a noticeable mean increase in dissolved nitrogen as nitrates and phosphate in the winter months and decreased in the summer months (Tables 2, Figures 12a, 12b, 13a and 13b). Statistical analyses also revealed some significant changes spatially and temporally. Those changes also occurred in temperature, DO, EC, TSS, chlorophyll-a and some trace metals such as iron, aluminium, copper, zinc, selenium, cadmium and lead. In addition, warmer conditions with temperatures reaching a maximum of 28 °C in 2011 have led to serious bloom conditions in the Hartbeespoort Dam from 2011 up to the early 2012. Blooms with higher intensities were observed in the summer months and blooms with lower intensities in the winter months. It can be concluded that under favourable wind conditions, phosphorous, nitrate, pH, temperature and probably some trace metals such as iron, copper, zinc and selenium, may have been vital environmental factors that contributed to the massive bloom formation in the dam during this study. Critical concentrations in ammonium where recorded in summer months. The combination of high temperature, pH above 8.1 and low DO might have led to situation of acute toxicity of ammonia to aquatic organisms in the Dam. Fortunately no dead aquatic organism where found during the study period at these specific months.

Another major difference in water quality observed during this study, was the extent of available oxygen. Low dissolved oxygen values either monthly or at various depths were due in part to very low numbers of algae or partly to the consumption of oxygen during decomposition of organic debris (Scott et al., 1979). It was also noted that the availability of inoculums of the cyanobacterial species in the surfaces water created good conditions for algal bloom in the dam. The influence of temperature on DO concentrations in the impoundment was partially masked by the photosynthetic activity of the algae as well as organic matter decomposition. The monthly variations in DO concentrations because of photosynthesis and respiration altered the dam DO profiles. The concentration of DO seemed to be influenced by water temperature, photosynthetic activity of phytoplankton, wind induced mixing and decomposition of organic matter.

There were observable correlations between bloom conditions and the selected physic-chemical parameters and iron in this study. Significantly high concentrations of those parameters were detected as compared to the past studies and may have contributed to the blooms. It is possible to assume that with the current hypertrophic conditions in the dam, those parameters may have triggered bloom formation and growth of aquatic macrophytes. These results also indicated that the Hartbeespoort Dam is highly enriched with nutrients in the form of phosphate and nitrate, and that the highest load was most probably coming through the Crocodile River.

Six different algal divisions were identified as main assemblages present in the dam, although a number of some species were periodic. M. aeruginosa was the dominant phytoplankton species in the Hartbeespoort dam for most of the study period with a percentage distribution of 69 % of the total algal biovolume. There was a remarkable variation in phytoplankton biomass in summer months compared to the rest of the year. Availability in nutrients and warm summer conditions may have contributed to that variation.2011 showed

heavy algal bloom throughout the year with Microcystis species extremely dominating the impoundment for most of the months. This domination was observed at all sampling sites in summer, except in some winter months where Anabaena sp. was the dominant species. Suitable environmental conditions (wind, warm water and availability of nutrients) in the Hartbeespoort Dam enable Microcystis species to form large buoyant colonies (Harding and Paxton, 2001). High species variety merely occurs once green algae and flagellates become more abundant in the spring months. The abundance of cyanobacteria confirmed that Hartbeespoort Dam is an infected and hypertrophic system. Nevertheless, the leading situation perceived might not be the case with the preceding study where blooms of Microcystis disappeared totally and other phytoplankton species e.g. Ceratium emerged and dominated the impoundment for months as cited by van Ginkel et al. (2001). The same study observed that in 1998, from July to November, algal population was dominated by green algae (Oocystis and Coelastrum) while the following year in 1999, the algal population was dominated by Ceratium hirundinella. The size of the colony on aggregation also varied depending on frequency and intensity of the wind (Harding, 1997). During windy conditions smaller colonies were found, as large colonies were easily fragmented (Robarts, 1984), while calm conditions promoted the formation of larger colonies (blooms) at the surface (Robarts, 1984). A similar case occurred in the dam towards the end of the year 2011, whereby dense colonies of patches of several meters were formed at various sites depending on the wind direction in the impoundment. Similarly, some algae disappeared when strong winds blew in other directions. When calm weather prevailed however, the blooms developed into crusted, buoyant mats of several centimetres thick that covered large areas. This thick mat often resulted in serious odours when decomposition took place as witnessed in February 2011. Aquatic macrophytes growth was also observed. This condition rendered the dam hypoxic, a condition with a low dissolved oxygen concentration.

Chlorophyll-a, which is a measure of phytoplankton abundance varied during the study period and reached the extremely high concentrations of 8693 µg/L in March 2012 at site 4, at the middle reach of the Dam basin( Table 3 and Figure 15). The higher chlorophyll-a concentrations always followed increased algal conditions in the dam. The study showed extremely high chlorophyll-a levels in the dam over the study period. The analysis for chlorophyll-a concentrations and algal compositions (Fig. 15 and Fig. 17) indicated that a bloom of M. aeruginosa occurred in the main basin of the Hartbeespoort Dam. Other variables such as temperature variations in 2011 may simply acted as a direct determining environmental factor for bloom formation. Those conditions could be detected by constant monitoring for prediction of casual occurrence of cyanobacterial bloom and aquatic macrophytes growth.

5.2 Recommendations

This study is therefore recommending frequent pragmatic and combined methods to temporally, physically removing algae and aquatic macrophytes. Studies and WHO models in Australia (Burch, 1993), New Zealand, Brazil, Canada, the European Union in and South Africa (du Preez & van Baalen (2006) for Rand Water) have recommended constant monitoring as a practical method for a hypertrophic dam like the Hartbeespoort Dam. Monitoring of the dam should remain, as it supports the tracking of forthcoming algal blooms. Monitoring should also be intensively applied to following subcatchments: Rietvlei River catchment, Hennops River catchment, Jukskei River catchment, Bloubankspruit catchment, Upper Crocodile River catchment and the Magalies and Skeerpoort River catchments, as they directly or indirectly contribute to water quality deterioration in the dam. The monitoring in those subcatchments should be associated with risk assessment every time a warning signs is presented to let appropriate information be processed to the stakeholders regularly. The construction of more sewage treatment works

would help to alleviate the nutrient inflow into the dam, as the existing one cannot support the population growth in the Crocodile West Marico catchment anymore. Education campaigns on pollution for the people in the informal settlements in the catchment should be reinforced and done regularly as to educate the people on domestic pollution, therefore to reduce the load of nutrients into the dam’s tributaries. Mining and agricultural industries operating in the catchment should conform to the 1 mg/l P effluent standard and amended legislation should be reinforced on those industries by the local government. There is also much more potential for community contribution in monitoring schemes, to report on the appearance of blooms and scums as this will help to promote community action and joint responsibility for the causes and cures of cyanobacterial bloom problems (du Preez & van Baaleen, 2006).

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Appendices:

Table A: Physical parameters data recorded in the Hartbeesport Dam during the study period.

TSS Conductivity (mg/ Sampling Temp (ºC ) DO (mg/L) pH (µS/cm) L) 0 5 10 0 0 Periods Sites m m m m 5 m 10 m 0 m 5 m 10 m 0 m 5 m 10 m m 28/02/201 26. 25. 15.4 11.1 9.7 1 S1 1 3 23.5 9 6 11.7 6 9.6 8.4 316 467 469 28 27. 25. 11.1 9.5 9.4 9.4 S2 1 2 24.8 1 8.01 7.8 2 7 2 417 413 421 52 25. 17.3 9.9 9.5 9.5 S3 27 4 25.7 1 4.25 8.3 1 5 6 430 425 429 50 25. 16.8 9.8 9.4 9.3 S4 28 5 25.7 4 6.99 9.22 6 5 4 449 443 450 24 27. 26. 15.0 11.0 11.9 9.7 9.6 S5 1 2 24.8 1 8 6 8 3 8.5 428 430 487 20 26. 24. 13.9 9.6 9.1 8.5 S6 6 9 24.3 8 9.12 2.15 9 3 3 413 433 469 24 29/04/201 20. 7.5 1 S1 8 20 20 2.82 4.4 4.3 2 7.6 7.4 576 578 616 24 20. 20. 7.6 7.7 7.8 S2 5 6 19.3 3.77 4.42 4.7 9 4 2 576 575 575 46 21. 7.1 7.8 8.1 S3 1 20 19.9 5.73 6.02 5.78 2 5 9 584 796 704 34 20. 20. 8.1 8.1 8.0 S4 8 2 20.2 4.37 4.99 5.18 3 2 9 586 589 588 34 20. 20. 8.0 8.0 8.0 S5 4 1 20.1 3.3 4.58 3.79 8 9 6 577 576 574 64 20. 19. 8.2 S6 6 7 19.6 4.48 5.09 5.09 4 8.2 8.2 535 536 536 48 25/05/201 18. 18. 8.1 8.2 8.3 1 S1 2 2 18.1 5.65 5.54 6.27 3 2 1 593 604 599 26 18. 8.3 8.4 8.3 S2 1 18 17.9 5.54 5.83 6.13 1 6 7 602 604 604 34 18. 18. 8.6 8.6 8.6 S3 3 2 18.4 6.32 6.46 6.24 6 9 7 602 605 606 42 18. 18. 8.6 8.6 8.6 S4 6 3 18.4 6.31 6.67 6.67 1 6 5 604 606 611 30 18. 18. 9.0 S5 2 1 18.3 7.52 7.47 7.3 9.1 4 8.8 584 588 590 34 18. 9.0 9.1 9.1 S6 1 18 18 7.48 7.67 7.63 5 3 3 575 575 575 36 14/06/201 14. 14. 7.0 7.4 7.4 1 S1 2 1 14.2 5.21 5.18 5.59 4 6 7 504 517 520 12

14. 14. 7.0 7.2 7.3 S2 1 1 14.1 5.44 5.22 5.52 4 9 7 523 520 517 20 14. 14. 7.3 7.5 7.5 S3 3 2 14.1 6.28 6.41 6.62 1 6 5 524 511 506 16 14. 14. 7.2 7.4 S4 2 6 14.7 6.61 6.65 6.45 5 8 7.5 528 515 515 92 14. 14. 7.1 7.3 7.5 S5 1 2 13.9 5.34 6.19 5.23 7 2 1 523 510 508 50 14. 14. 7.1 7.3 7.4 S6 7 6 14.3 6.04 6.29 6.65 7 2 9 509 507 489 44

02/08/201 11.5 11. 7.5 7.7 7.8 1 S1 8 8 11.6 7.64 8.31 8.3 8 2 4 495 484 482 28 12. 12. 7.9 7.9 S2 4 2 12 6.15 6.55 6.32 9 3 7.9 489 485 490 20 13. 12. 7.4 7.7 7.8 S3 3 4 12.4 7.11 6.8 6.99 8 7 6 508 495 496 148 12. 7.5 7.7 7.9 S4 13 5 13.8 6.02 6.59 6.82 3 6 5 448 487 498 20 13. 12. 7.6 7.8 7.8 S5 7 7 12.3 6.29 6.18 6.28 8 2 7 490 482 483 372 13. 12. 7.6 8.0 8.0 S6 5 5 12.3 7.45 7.45 7.13 5 2 8 467 456 464 144 24/08/201 13. 13. 7.6 7.8 7.9 1 S1 4 3 13.2 5.43 5.46 5.93 5 2 1 494 488 487 30 13. 13. 6.9 7.5 7.5 S2 1 2 13.3 5.8 5.76 5.33 5 6 6 493 491 491 38 15. 15. 7.5 7.8 7.9 S3 6 5 15.4 4 7.46 7.95 7 4 2 500 492 491 38 14. 7.6 7.9 S4 15 9 14.8 4.36 4.43 4.64 1 7.8 2 486 487 488 14 14. 7.9 8.0 8.0 S5 14 3 14.2 4.54 4.81 4.66 9 4 2 491 485 484 26 14. 14. 10.6 11.7 11.9 8.1 8.2 8.2 S6 3 3 14.1 5 4 6 5 5 1 483 473 474 52 28/09/201 22. 21. 8.3 7.4 7.5 1 S1 2 8 18 21.2 22.7 26.1 5 8 1 527 503 512 178 23. 17.7 8.2 7.4 S2 7 19 19.7 23.5 2 18.7 7.6 3 7 528 520 517 62 23. 14.7 12.4 8.4 8.3 7.9 S3 1 20 19.3 21.1 4 6 3 6 8 542 534 534 16 23. 20. 17.3 13.6 12.0 8.3 8.4 8.1 S4 1 7 19.6 6 2 2 5 8 4 519 510 519 104 22. 20. 14.3 12.2 8.5 8.1 S5 5 8 18.4 5 1 9.04 7 8.6 3 521 513 520 90 21. 19. 11.3 10.2 8.5 8.5 8.1 S6 7 7 18.6 4 4 9.01 7 2 1 518 520 521 40

30/10/201 23. 23. 12.6 11.0 8.2 8.7 8.1 1 S1 4 1 20.4 6 3 9.31 4 9 7 510 516 518 178 24. 24. 16.4 10.3 7.4 8.6 8.2 S2 7 3 21.1 32.7 7 4 1 3 6 517 512 522 2 25. 23. 17.7 13.7 8.4 7.8 S3 5 8 22.9 2 8 6.04 2 8.1 7 520 469 560 52 26. 8.0 8.0 7.8 S4 2 25 22.1 9.12 9.31 7.51 3 1 5 475 476 522 44 25. 24. 8.8 8.8 8.2 S5 6 9 22.3 7.96 6.31 5.35 7 2 6 509 518 519 42 25. 8.9 8.6 8.2 S6 8 24 22.8 5.74 4.46 4.1 2 8 9 506 510 520 36 23/11/201 24. 24. 9.1 9.0 8.4 1 S1 3 1 23.1 1.46 1.25 1.34 9 9 8 498 504 514 72 24. 24. 9.1 9.1 8.7 S2 2 2 23.8 1.56 2.15 2.13 5 4 9 504 503 512 60 24. 8.8 8.4 8.8 S3 3 23 22 2.17 2.13 1.85 7 4 6 487 376 282 112 24. 24. 9.2 8.7 8.0 S4 1 4 23.3 1.25 1.3 1.17 3 7 3 490 466 350 120 25. 24. 9.4 9.3 S5 7 9 24.8 1.08 1.23 1.24 9.6 4 3 485 493 497 6 25. 24. 9.6 9.3 S6 5 9 24.9 1.28 1.3 1.29 4 9.5 9 484 493 494 96 05/12/201 22. 22. 7.2 7.1 7.1 1 S1 9 7 22 7.6 3.41 1.27 2 9 7 453 393 429 10 22. 7.1 7.4 7.4 S2 25 7 22.2 7.77 5.47 2.36 1 1 1 378 388 408 10 23. 8.2 7.7 7.7 S3 25 5 23.2 3.37 3.18 1.29 6 5 4 403 303 383 14 24. 23. 7.7 7.7 7.7 S4 1 8 23.5 4.51 3.89 2.09 6 8 8 680 690 685 18 24. 24. 7.2 7.2 S5 5 1 23.4 6.69 4.73 2.39 4 9 7.2 390 420 420 18 25. 24. 7.1 7.1 7.1 S6 5 3 24 7.72 4.99 3.75 1 7 8 320 350 360 50 19/01/201 25. 25. 7.1 7.6 7.9 2 S1 5 1 25 0.76 0.68 0.64 7 8 9 422 429 428 44 25. 25. 7.2 9.7 S2 3 1 24.2 0.78 0.61 0.66 9.6 4 8 426 431 432 16 24. 7.3 7.8 8.0 S3 8 24 23.6 0.61 0.51 0.45 2 2 4 437 440 453 68 25. 24. 9.4 7.2 9.6 S4 1 6 24 0.66 0.59 0.56 4 9 3 426 433 434 290 25. 25. 7.5 7.8 8.0 S5 9 1 25.1 0.8 0.71 0.67 1 7 2 419 429 431 82 S6 26. 25. 25.9 0.95 0.8 0.68 9.3 7.2 8.5 426 422 426 12

8 5 3 05/03/201 26. 25. 9.5 9.5 8.9 2 S1 7 8 24.9 0.89 0.73 0.59 6 1 6 385 397 399 248 27. 9.8 9.7 9.2 S2 2 26 25.2 1.15 0.91 0.66 6 3 9 392 390 402 48 26. 9.5 9.3 9.1 S3 9 25 25.6 0.93 0.76 0.78 4 8 8 392 406 422 94 25. 9.7 9.6 9.5 S4 27 9 25.5 1.15 0.79 0.76 3 1 8 395 392 394 108 26. 25. 9.5 9.4 9.3 S5 8 8 25.1 0.82 0.63 0.56 5 7 6 394 395 394 218 26. 25. 8.9 8.9 8.7 S6 7 1 24.6 0.54 0.38 0.33 8 3 7 407 404 416 108

*Shaded data represent maximum and minimum for each parameter.

Table B: Chemical parameters and chlorophyll-a data recorded in the Hartbeesport Dam during the study period.

Chl-a Total Phosphate Ammonium Nitrate Nitrite (µg/ Sampling (TP,mg/L) (NH4, mg/L) (NO3, mg/L) (NO2, mg/L) L) 10 10 Periods Sites 0 m 5 m m 0 m 5 m m 0 m 5 m 10 m 0 m 5 m 10 m 0 m 0.0 0.0 0.2 0.3 0.0 0.0 0.1 28/02/2011 S1 2 6 0.38 3 1 0.65 6.4 7.6 12.2 6 9 6 278.16 0.6 0.0 0.1 9.6 0.0 0.0 0.0 S2 5 0.6 0.47 3 5 0.3 14.85 5 6.7 9 7 7 33.27 0.6 0.2 0.0 0.1 0.0 0.0 S3 7 8 0.19 8 2 0.04 4.5 5.3 8.5 6 8 0.1 165.85 0.1 0.7 0.1 0.1 12. 0.1 0.1 64.2 S4 8 8 0.59 9 7 0.11 6.3 8 13.9 1 5 0.23 6 0.4 0.2 0.0 0.1 6.8 0.0 0.4 S5 1 4 0.33 2 2 0.83 1.8 5 21.2 0.1 9 4 5.39 0.5 0.4 0.1 0.1 18. 13.4 0.0 0.1 0.1 S6 5 1 0.44 3 7 0.42 20.75 8 5 8 1 9 87.29 0.0 0.1 0.4 0.1 5.3 0.1 0.0 0.1 29/04/2011 S1 9 7 0.22 8 6 0.18 4.15 1 4.36 2 4 4 621.28 0.2 0.2 0.4 0.0 3.8 0.0 0.0 0.2 S2 4 1 0.19 1 9 0.27 4.36 9 1.6 9 7 1 37.82 0.1 0.2 0.2 1.1 0.1 0.0 0.0 S3 9 0.2 0.39 9 6 0.09 2.86 5 2.21 6 5 9 698.99 0.1 0.1 1.6 0.1 0.0 0.0 S4 6 0.2 0.19 0.2 2 0.17 2.39 5 2.9 3 3 9 106.17 0.1 0.1 0.3 0.3 4.4 0.0 0.0 0.0 S5 5 5 0.15 1 6 0.27 2.94 4 3.55 8 7 7 70.39 0.0 0.0 0.2 0.2 2.5 0.0 0.0 0.1 S6 6 7 1.03 1 6 0.09 2.52 5 2.17 3 8 4 2.11 0.1 0.2 0.1 0.1 0.1 0.1 0.1 25/05/2011 S1 2 1 0.35 7 1 0.27 1.1 2.2 2.55 7 8 8 360.59 0.1 0.1 0.4 0.1 0.1 0.1 0.1 S2 7 4 0.37 2 2 0.29 1.45 2.2 3.35 9 5 7 2.25 0.2 0.2 0.2 0.1 3.0 0.1 0.1 0.1 S3 1 3 0.47 5 2 0.24 0.95 5 6.95 5 7 8 0.28 0.3 0.2 0.1 0.1 3.6 0.1 0.1 0.1 S4 1 3 0.34 6 8 0.38 1.85 5 8.35 8 8 8 0.83 0.2 0.3 0.2 0.1 3.5 0.1 0.1 0.1 S5 3 2 0.5 8 2 0.23 2.5 5 4.3 3 8 5 73.33 0.2 0.2 0.1 0.1 0.1 0.0 S6 0.2 1 0.23 8 2 0.36 3.5 5.6 1.1 4 6 6 74.78 0.5 0.3 0.3 0.2 0.1 0.1 14/06/2011 S1 2 5 0.26 1.5 8 0.48 13.8 9.7 3.4 2 5 7 0.2 S2 0.5 0.1 0.2 0.3 1.5 0.39 4.1 3.8 4.4 0.2 0.1 0.2 197.17

5 9 6 5 2 5 1 0.0 0.4 0.4 2.7 0.2 0.2 S3 0.1 8 0.13 1 2 0.42 3.25 5 4.5 1 0.2 2 5.66 0.5 0.0 0.2 0.2 9.8 0.2 0.1 S4 2 5 1.72 9 9 0.29 10.35 5 3.35 0.2 1 9 6.81 1.0 0.0 0.4 4.1 0.2 0.2 0.2 S5 6 7 0.04 5 0.4 0.39 6.3 5 3.3 2 2 2 28.02 0.9 0.0 0.3 5.0 0.1 0.1 S6 8 3 0.07 8 0.3 0.42 10.6 5 2.65 0.2 5 8 15.76 0.0 0.0 2.8 0.1 0.1 0.1 02/08/2011 S1 1.4 0.7 0.17 8 6 0.14 1.35 5 2.7 2 4 5 4.77 0.4 0.1 0.1 0.0 3.2 0.1 0.1 S2 9 7 0.18 3 5 0.12 1.2 5 6.6 5 5 0.2 149.42 0.4 0.2 0.0 0.0 0.1 0.2 S3 2 2 0.29 9 7 0.07 3.7 7.8 5.45 4 7 0.2 5.93 0.2 0.2 0.0 0.0 10. 0.1 0.1 0.1 S4 8 1 0.28 9 8 0.16 11.5 45 9.45 9 7 9 4.65 0.4 0.1 0.1 0.1 5.9 0.1 0.1 0.1 S5 5 2 0.1 8 3 0.09 5.7 5 6.3 6 2 1 9.94 0.0 0.0 0.0 4.2 0.1 0.1 S6 0.1 8 0.05 9 8 0.12 6.3 5 2.6 1 0.1 2 23.9 0.1 0.2 0.3 0.2 3.8 0.1 0.1 0.2 24/08/2011 S1 5 1 0.22 5 4 0.42 3.2 5 4.35 7 5 3 15.57 0.2 0.2 0.2 5.6 0.1 0.2 S2 0.2 1 0.16 3 6 0.31 3.6 7 6.25 0.1 7 3 2.67 0.4 0.4 0.3 0.3 4.6 0.2 0.3 0.4 S3 7 3 0.35 5 3 0.4 4.4 5 5.7 1 5 1 21.77 0.2 0.1 0.1 0.1 3.6 0.1 0.0 0.4 S4 3 8 0.17 9 8 0.18 2.05 5 8.55 8 7 7 0.22 0.1 0.1 0.1 0.1 0.2 0.1 0.2 S5 6 9 0.2 2 7 0.29 5.1 6.6 8.55 6 6 3 0.14 0.0 0.1 3.7 0.1 0.0 0.0 S6 9 0.1 0.09 4 0.2 0.24 4.4 5 2.8 4 8 6 0.22 0.2 0.7 0.0 1.3 0.1 0.1 0.1 3451.8 28/09/2011 S1 5 1.4 3.41 5 8 0.82 5.1 5 6.55 9 2 9 6 0.3 0.3 0.5 0.4 6.6 0.1 S2 7 2 0.34 6 7 0.75 6.45 5 9.8 0.2 0.2 3 545 0.4 0.3 0.6 0.2 7.5 0.2 0.2 S3 7 5 0.39 1 3 0.17 11 5 8.1 0.3 4 5 26.19 0.3 0.3 0.3 0.1 5.9 0.2 0.2 S4 2 4 0.34 3 6 0.51 8.55 5 5.65 1 0.2 1 77.01 0.3 0.3 0.3 0.1 0.1 S5 1 0.3 0.25 3 2 0.37 4.7 7.2 7 8 0.2 7 137.72 0.2 0.3 0.3 0.2 0.1 0.1 0.1 S6 8 6 0.26 2 9 0.1 4.6 6.5 6.9 7 9 6 3.51 0.1 0.0 0.0 0.0 2.0 0.1 0.0 0.1 30/10/2011 S1 8 9 0.14 7 3 0.15 1.45 5 2 5 8 1 11.8

0.1 0.0 0.0 0.1 0.1 0.1 S2 5 0.2 0.13 4 5 0.19 2.3 2.2 6.1 1 9 1 23.05 0.3 0.2 0.0 0.1 4.5 0.1 0.1 S3 9 1 0.15 9 7 0.14 5.55 5 5.5 7 5 0.2 0.19 0.4 0.2 0.1 2.9 0.0 0.1 0.2 S4 9 5 0.43 0.2 7 0.45 2.55 5 3.05 3 8 2 0.92 0.1 0.2 0.0 0.1 0.1 S5 4 1 0.26 4 0.1 0.23 2.7 3.3 4.95 9 0.2 2 41.25 0.1 0.0 0.1 0.2 0.1 0.1 S6 0.1 3 0.09 7 6 0.08 2.4 4.7 7.5 1 5 1 0.27 0.2 0.4 0.2 0.2 0.1 0.1 23/11/2011 S1 5 6 0.37 2 4 0.13 2.05 1.8 1.55 6 5 0.1 991.42 0.1 0.0 3.6 0.0 0.2 1287.5 S2 0.2 7 0.41 0.1 3 0.25 12.6 5 2.15 0.1 5 1 9 0.2 0.6 0.0 0.3 0.1 0.2 0.2 S3 5 1 0.33 6 5 0.45 3.7 2.6 3 1 7 1 133.44 0.3 0.0 0.2 0.3 0.2 S4 8 0.6 0.46 3 2 0.6 2.5 2.8 6.15 0.2 2 9 304.47 0.2 0.3 0.1 0.0 0.1 0.1 0.1 1915.2 S5 4 4 0.33 2 4 0.04 2.7 1.8 1.3 3 1 4 8 0.2 0.2 0.0 1.3 0.1 0.1 0.0 1553.8 S6 7 4 0.31 0.1 4 0.07 2 5 3.9 2 3 6 3 0.1 0.0 0.0 0.0 0.0 05/12/2011 S1 0.1 0.2 0.14 8 2 0.32 2.4 2.6 2.3 9 9 4 43.76 0.0 0.1 0.0 0.0 0.0 0.0 0.0 S2 8 8 0.07 3 5 0.05 2.6 2.8 2.7 2 5 2 89.65 0.2 0.1 0.0 1.5 0.1 0.1 S3 0.2 4 0.18 2 4 0.27 3.5 5 2.05 1 0.1 1 3.03 0.1 0.0 0.0 2.5 0.0 0.0 0.0 S4 5 0.1 0.27 2 5 0.1 4.75 5 3.55 6 4 6 43.82 0.1 0.0 0.0 0.0 0.0 0.4 1011.5 S5 6 9 0.17 7 3 0.18 4.1 1.9 8.55 0.1 5 7 3 0.1 0.0 0.0 0.0 2.1 0.0 0.0 0.0 S6 8 6 0.14 4 4 0.12 1.45 5 2.05 8 7 3 71.89 0.1 0.1 0.1 0.0 2.0 0.0 0.0 0.0 19/01/2012 S1 2 3 0.1 3 9 0.09 1.65 5 2.1 7 9 6 182.51 0.1 0.0 1.9 0.1 0.2 S2 0.6 4 0.28 9 0.1 0.35 3.95 5 1.7 8 0.1 6 17 0.2 0.2 0.3 2.9 0.2 0.2 S3 2 7 0.37 9 0.3 0.44 2.35 5 4.5 4 9 0.3 8.34 0.0 0.1 0.0 0.1 2.1 0.1 0.1 S4 6 7 0.17 7 2 1.58 1.55 5 3.85 0.1 6 9 137.04 0.1 0.0 0.6 0.6 0.0 0.1 0.1 1829.7 S5 2 9 0.12 3 5 0.14 3.9 1.6 1.9 7 2 3 3 0.1 0.1 0.5 1.2 0.0 0.0 0.0 S6 4 3 0.14 5 0.2 0.27 1.3 5 # 3 5 5 117.14 05/03/2012 S1 0.7 0.0 0.15 0.1 0.1 0.17 0.75 0.8 3.1 0.0 0.0 0.1 254.94

7 6 5 5 7 9 6 0.0 0.0 0.1 0.0 0.0 0.0 0.1 1464.3 S2 7 4 0.12 9 6 0.06 0.4 1.6 1.05 8 9 9 2 0.0 0.1 0.0 0.0 2.5 0.0 0.1 0.1 S3 4 1 0.12 3 9 0.13 1.85 5 3.1 9 2 4 244.2 0.1 0.0 0.0 0.0 1.1 0.0 0.0 0.0 8692.9 S4 2 6 0.09 6 9 0.14 0.5 5 1.4 6 6 8 8 0.0 0.0 0.0 0.2 1.0 0.1 0.1 0.0 S5 5 9 0.1 2 5 0.65 2.6 5 2.25 1 9 7 210.21 0.1 0.1 0.5 0.5 0.1 0.1 0.2 S6 4 4 0.24 6 7 0.3 1.7 2.4 0.8 5 5 1 24.15

*Shaded data represent maximum and minimum values for each parameter. #: No value obtained.

Table C (C1; C2): Trace metals data recorded in the Hartbeesport Dam during the study period.

Table C1: Ca , Mg,Na,K,Cr ,Al,Mn & Fe.

Sampling Periods Sites Ca Mg Na K Cr Al Mn Fe 28/02/11 S1 6.45 6.18 6.3 23.02 1.2 20.34 3.91 9.72 S2 6.52 4.52 7.72 27.32 2.27 12.52 2.65 -6.97 S3 4.77 3.68 6.11 21.66 2.15 7.12 1.59 13.37 S4 5.08 6.52 7.39 26.6 4.45 35.98 7.12 91.06 S5 5.08 6.52 7.39 26.6 4.45 35.98 7.12 91.06 S6 9.38 11.12 11.12 36.77 4.85 19.22 3.54 12 29/04/11 S1 6.59 3.48 5.53 21.47 4.34 17.34 6.07 145.34 S2 4.85 3.87 6.14 25.21 2.2 4.95 2.89 -165.11 S3 6.29 4.9 9.08 34.56 5.1 20.03 7.73 72 S4 6.24 3.7 7.96 28.72 3.84 12.21 4.17 174.19 S5 5.27 3.85 6.64 27.49 4.54 8.05 5.95 165.39 S6 4.56 4.38 10.18 31.27 17.8 28.41 4.92 214.51 25/05/11 S1 8.39 5.88 10.32 33.87 7.53 25.63 6.14 10.86 S2 18.43 7.12 15.6 50.23 9.46 51.66 15.42 25.02 S3 7.97 2.99 6.58 20.09 8.54 26.89 4.33 220.53 S4 9.38 3.88 8.08 27.7 2.43 8.17 2.72 27.84 S5 12.59 10.88 23.67 80.33 10.91 37.27 8.71 45.47 S6 17.61 7.45 17.49 55.43 11.44 31.02 11.7 110.31 14/06/11 S1 1.19 0.49 1.18 3.29 # # # # S2 9.99 6.87 11.51 40.53 5.69 34.44 2.46 230.01 S3 11.28 6.37 10.11 35.47 5.36 6.35 1.98 371.8 S4 16.45 5.05 11.58 36.16 6 23.31 4.02 44.71 S5 13.89 7.98 19.23 59.06 13.73 12.62 2.76 371.21 S6 14.02 4.25 8.79 27.84 5.58 26.14 3.23 10.1 02/08/11 S1 12.62 9.02 14.9 44.15 8.82 34.06 8.69 70.13 S2 10.68 7.23 15.75 46.47 10.91 18.34 6.06 20.05 S3 7.78 4.23 6.21 21.23 7.57 11.09 10.81 422.18 S4 11.22 7.25 16.31 46.51 10.48 7.97 10.05 338.27 S5 10.07 4.26 8.5 26.54 5.75 16.28 6.57 395.8 S6 5.85 5.06 13.14 34.81 8.66 18.02 3.13 399.8 24/08/11 S1 16.05 8.5 16.02 45.84 10.24 5.48 15.48 29.16 S2 13.33 6.19 13.21 38.78 12.14 18.97 14.52 33.06 S3 11.87 7.18 9.87 32.18 7.65 10.31 56.57 468.34 S4 13.39 8.19 14.42 40.57 8.1 46.39 16.55 19 S5 13.35 5.77 9.13 29.12 8.47 20.56 9.42 465.29 S6 8.1 6.28 12.15 34.81 9.36 68.61 4.04 499.91 28/09/11 S1 15.59 8.47 12.86 37.85 10.84 20.88 4.57 52.2 S2 24.5 8.47 17.68 47.64 11.51 45.29 13.89 63.8 S3 18.22 7.87 15.4 44.49 12.34 13.98 11.95 18.69

S4 15.54 4.54 7.65 23.56 7.1 8.32 12.46 359.17 S5 15.74 6.59 14.94 40.52 7.97 79.06 9.92 3.75 S6 18.46 6.11 14.28 37.66 7.73 10.52 5.22 341.47 30/10/11 S1 20.75 5.73 13.55 35.56 10.3 15.42 13.12 55.79 S2 16.63 6.69 15.96 43.16 3.7 6.41 4.43 79.7 S3 22.06 9.8 18.75 57.5 1.6 11.88 12.41 22.69 S4 9.79 1.06 1.88 4.8 7.12 16.22 16.22 21.75 S5 19.22 7.84 19.23 51.09 8.71 6.09 3.91 6.05 S6 12.32 6.65 17.17 43.15 13.07 5.38 2.4 90.7 23/11/11 S1 18.36 5.95 10.72 32.33 14.73 9.12 15.4 47.31 S2 28.8 5.62 10.7 28.44 5.71 10.59 10.96 52.92 S3 20.46 6.16 10.85 32.88 2.08 5.86 25.96 21.75 S4 10.94 1.78 3.54 10.19 -5.12 # # # S5 12.63 4.59 6.51 20.97 7.72 6.83 10.98 22.82 S6 23.37 8.51 16.71 47.35 8.73 5.95 1.64 11 05/12/11 S1 10 7.16 10.86 35.32 12.74 18 36.02 194.04 S2 16.61 8.8 8.24 26.91 25.35 15.4 2.22 184.53 S3 18.25 5.94 7.6 34.52 2.9 4.78 12.58 287.02 S4 12.55 6.33 8.27 33.8 11.66 21.36 3.15 631.62 S5 13.15 7.56 13.31 42.19 8.53 11.53 3.29 441.39 S6 19.53 6.79 11.13 35.94 5.9 9.04 1.51 441.64 19/01/12 S1 12.25 6.46 9.46 32.42 4.89 6.45 1.04 444.65 S2 12.46 5.68 9.35 33.18 12.96 11.85 1.08 44.12 S3 20.64 5.87 10.27 33.51 9.64 15.79 2.61 50.85 S4 11.27 5.37 9.14 31.42 14.11 7.62 1.03 335.58 S5 12.66 3.51 6.06 20.18 6.29 90.4 0.89 254.05 S6 13.33 6.12 12.87 38.59 2.59 27.8 0.01 106.61 05/03/12 S1 13.95 5.91 9.58 28.12 2.14 -1.18 -0.27 75.97 S2 9.14 7.29 12.8 41.88 3.41 -0.07 0.19 62.63 S3 10.24 4.27 7.91 24.06 -10.29 4.48 -0.34 45.2 S4 9.6 5.98 10.82 34.26 2.96 -1.67 -0.09 -1.09 S5 11.43 7.09 13.58 42.13 11.59 54.89 3.39 38.94 S6 17.95 5.42 11.58 33.24 4.98 23.1 3.51 74.59

*Shaded data represent maximum and minimum positive values for each metal. # No value obtained. Ca, Mg, Na and K are macro elements analysed on ICP-OES and are in mg/L. Cr, Al, Mn and Fe are microelements analysed on the ICP-MS and are in µg/L.

Table C2: Ni , Cu, Zn, As, Se, Ag, Cd & Pb.

Sampling Periods Sites Ni Cu Zn As Se Ag Cd Pb 28/02/11 S1 3.77 17.11 23.15 0.03 0.51 2.43 0.34 0.15 S2 2.84 7.08 21.64 0.33 0.98 1.98 0.32 1.41 S3 4.06 4.85 13.49 0.35 1.88 2.35 0.43 1.24 S4 5.12 10.98 68.44 0.67 4.61 2.93 0.95 13.79 S5 5.12 10.98 68.44 0.67 4.61 2.93 0.95 13.79 S6 5.22 9.32 32.68 1.05 3.55 3.17 0.24 3.22 29/04/11 S1 3.57 6.15 62.5 0.36 2.48 1.43 0.28 2.81 S2 2.81 2.1 24.81 0.09 1.22 3.35 0.73 1.37 S3 5.26 9.38 19.76 1.06 0.57 1.63 0.41 1.26 S4 4.75 51.09 40.69 0.84 4.19 4.03 0.36 3.51 S5 2.95 7.42 44.65 0.49 2.81 2.63 1.49 1.6 S6 4.81 3.67 32.15 1.13 5.91 0.83 1.14 1.21 25/05/11 S1 3.25 6.48 28.5 1.16 6.7 0.67 0.38 2.5 S2 11.02 5.98 21.58 1.1 1.09 1.34 0.59 1.15 S3 4.33 1.98 16.88 0.47 0.79 0.29 0.17 1.11 S4 2.47 1.82 9.92 0.39 3.43 22.76 -0.28 3.97 S5 11.43 12.39 24.62 2.97 10.64 3 0.72 1.7 S6 11.23 20.34 45.19 2.46 11.28 0.95 1.4 1.6 14/06/11 S1 # # # # # # # # S2 4.72 4.74 13.98 1.53 7.7 2.74 0.89 1.47 S3 3.71 1.66 9.77 0.71 5.49 1.23 0.63 0.95 S4 6.17 2.68 17.5 1.31 0.67 1.57 0.27 1.3 S5 10.52 4.2 11.25 2.73 1.48 3.63 1.17 0.98 S6 4.52 3.25 20.31 1.01 6.03 2.46 1.49 1.33 02/08/11 S1 19.57 5.61 12.98 1.77 7.93 2.63 0.56 1.18 S2 13.15 8.16 22.78 1.68 8.47 0.81 0.68 1.31 S3 4.52 4.98 11.96 0.67 0.54 2.72 0.25 1.04 S4 10.83 7.66 10.62 1.33 1.4 2.15 0.69 0.94 S5 4 4.52 124.43 0.46 2.66 0.36 0.45 0.97 S6 5.66 3.61 31.9 0.83 4.29 1.12 0.77 0.98 24/08/11 S1 14.87 76.97 11.71 1.7 7.7 1.13 0.57 1.11 S2 14.78 24.03 24.03 24.03 1.09 5.85 1.43 1.15 S3 5.91 34.84 9.69 1 0.75 0.78 0.23 0.94 S4 11.93 26.53 14.43 1.61 8.58 0.34 0.37 2.39 S5 3.86 20.67 27.29 0.81 5.78 0.36 0.48 1.07 S6 7.25 16.22 10.73 0.93 0.93 0.88 0.47 1.4 28/09/11 S1 8.19 37.59 271.29 1.71 6.3 0.54 0.57 17.06 S2 7.4 77.32 40.08 1.65 1.42 0.59 -0.25 17.04 S3 11.85 37.55 17.57 1.88 0.92 0.53 0.17 6.48 S4 3.57 17.15 30 0.87 5.46 1.86 0.69 9.42 S5 8.65 31.55 28.85 1.19 7.12 2.78 0.8 3.53 S6 6.28 17.84 13.79 0.92 4.27 2.56 0.32 2.15

30/10/11 S1 11.13 11.24 14.56 0.37 12.4 0.27 0.57 4.34 S2 14.08 28.71 43.8 1 4.87 3.93 2.75 5.82 S3 13.46 30.11 5.58 1.91 0.54 0.7 0.23 9.58 S4 3.37 5.76 24.61 2.08 11.72 0.82 1.98 2.68 S5 11.51 23.15 2.93 1.63 7.57 6.62 0.72 4.99 S6 11.15 19.77 19.78 0.88 4.58 5.81 0.37 3.73 23/11/11 S1 327.41 12.89 18.8 10.23 0.61 0.17 9.19 18.43 S2 22.26 5.7 21.61 0.62 3.38 1.61 0.56 10.02 S3 15.91 8.44 7.48 0.79 0.42 0.54 0.16 7.02 S4 # # # # # # # # S5 2.58 8.35 36.58 0.95 5.78 0.39 1.01 1.15 S6 11.68 18.09 9.9 1.41 6.14 3.59 0.49 1.17 05/12/11 S1 25.01 31.36 141.59 1.6 0.32 0.13 6.43 1.94 S2 2.49 1.94 17.07 1.1 5.67 1.73 0.65 1.59 S3 2.98 0.97 11.14 1.56 8 5.21 0.77 0.88 S4 7.76 2.45 13.42 1.29 6.66 3.29 0.51 1.35 S5 3.05 2.49 21.98 1.43 6.9 0.92 0.53 4.34 S6 2.45 0.17 1.11 1.82 4.19 4.08 1.12 1.03 19/01/12 S1 3.35 2.69 4.64 0.45 0.45 2.64 0.9 1.39 S2 4 1.82 6.25 1.1 3.97 1.04 0.45 1.1 S3 4.56 3.55 15.84 0.84 3.78 2.01 1.59 1.41 S4 5.39 2.5 8.12 1.21 5.91 3.91 1.43 1.21 S5 4.31 1.51 10.59 0.35 2.57 0.69 0.06 0.99 S6 1.34 1.39 4.26 -0.51 0.14 0.38 0.53 0.71 05/03/12 S1 1.19 2.45 2.02 -0.54 -2.11 0.76 0.85 0.63 S2 1.21 0.72 4.14 -0.76 0.08 0.27 0.4 0.8 S3 0.45 0.18 1.78 -1.02 -3.09 0.17 0.76 0.63 S4 1.2 -0.09 1.38 -0.99 -3.86 3.66 0.61 0.77 S5 2.07 4.29 29.7 0.1 3.48 1.49 0.52 2.66 S6 8.74 10.31 37.74 1.15 4.81 3.28 0.04 2.41

*Shaded data represent maximum and minimum positive values for each metal. # No value obtained. Ni , Cu, Zn, As, Se, Ag, Cd & Pb are microelements analysed on the ICP-MS and are in µg/L.

Table D : Percentage distribution of some algae data in the Hartbeesport Dam during the study period.

Chrysophyt Crytoph Pyrro Euglen Cyanophita Chlorophyta Sampli a yta phyta ophyta ng Osc An Ant Cylin Melo Sites Cyc Scen Spi Period M.aeru illat ab hro dros sira Ooc Crypto Cera Euglen lote edes rog s ginosa ori ea spir perm gran ystis monads tium a lla mus yra a na a opsis ulate S1 80 20 0 0 0 0 0 0 0 0 0 0 0 S2 100 0 0 0 0 0 0 0 0 0 0 0 0 28-02- S3 100 0 0 0 0 0 0 0 0 0 0 0 0 2011 S4 100 0 0 0 0 0 0 0 0 0 0 0 0 S5 80 20 0 0 0 0 0 0 0 0 0 0 0 S6 85 15 0 0 0 0 0 0 0 0 0 0 0 S1 70 0 25 0 0 0 0 0 5 0 0 0 0 S2 100 0 0 0 0 0 0 0 0 0 0 0 0 29-04- S3 80 5 15 0 0 0 0 0 0 0 0 0 0 2011 S4 100 0 0 0 0 0 0 0 0 0 0 0 0 S5 70 20 0 0 0 0 0 0 10 0 0 0 0 S6 100 0 0 0 0 0 0 0 0 0 0 0 0 S1 40 0 30 0 0 0 10 5 0 5 0 10 0 S2 40 0 60 0 0 0 0 0 0 0 0 0 0 S3 100 0 0 0 0 0 0 0 0 0 0 0 0 25-05- 10 2011 S4 0 0 0 0 0 0 0 0 0 0 0 0 0 S5 20 0 60 0 0 0 0 0 0 10 0 0 10 S6 20 0 65 0 0 0 0 5 0 5 0 0 5 S1 20 0 80 0 0 0 0 0 0 0 0 0 0 S2 5 0 55 0 0 0 0 20 0 15 0 0 15 14-06- S3 30 0 70 0 0 0 0 0 0 0 0 0 0 2011 S4 10 0 90 0 0 0 0 0 0 0 0 0 0 S5 40 0 60 0 0 0 0 0 0 0 0 0 0 S6 0 0 75 0 0 5 5 5 0 0 5 5 0 S1 40 0 60 0 0 0 0 0 0 0 0 0 0 S2 30 0 45 0 0 5 0 5 10 0 5 0 0 02-08- S3 30 0 70 0 0 0 0 0 0 0 0 0 0 2011 S4 65 0 35 0 0 0 0 0 0 0 0 0 0 S5 40 0 60 0 0 0 0 0 0 0 0 0 0 S6 40 0 20 0 0 10 0 10 10 0 10 0 0 S1 40 0 60 0 0 0 0 0 0 0 0 0 0 S2 45 0 55 0 0 0 0 0 0 0 0 0 0 24-08- S3 30 0 70 0 0 0 0 0 0 0 0 0 0 2011 S4 80 0 20 0 0 0 0 0 0 0 0 0 0 S5 85 0 15 0 0 0 0 0 0 0 0 0 0 S6 60 0 40 0 0 0 0 0 0 0 0 0 0

Table D continued: Percentage distribution of some algae data in the Hartbeesport Dam during the study period.

S1 80 15 0 0 0 0 0 0 0 5 0 0 0 S2 70 15 0 0 0 0 0 10 0 0 0 5 0 28-09- S3 80 5 10 0 0 0 0 0 0 0 0 5 0 2011 S4 90 5 0 0 0 0 0 0 0 5 0 0 0 S5 75 5 15 0 0 0 0 0 0 5 0 0 0 S6 100 0 0 0 0 0 0 0 0 0 0 0 0 S1 80 0 0 0 0 0 0 0 0 0 20 0 0 S2 70 15 0 0 0 0 0 0 0 0 15 0 0 30-10- S3 100 0 0 0 0 0 0 0 0 0 0 0 0 2011 S4 100 0 0 0 0 0 0 0 0 0 0 0 0 S5 70 15 15 0 0 0 0 0 0 0 0 0 0 S6 100 0 0 0 0 0 0 0 0 0 0 0 0 S1 100 0 0 0 0 0 0 0 0 0 0 0 0 S2 75 20 5 0 0 0 0 0 0 0 0 0 0 23-11- S3 90 10 0 0 0 0 0 0 0 0 0 0 0 2011 S4 85 0 15 0 0 0 0 0 0 0 0 0 0 S5 90 0 10 0 0 0 0 0 0 0 0 0 0 S6 80 15 0 0 0 0 0 0 0 5 0 0 0 S1 80 0 20 0 0 0 0 0 0 0 0 0 0 S2 70 0 30 0 0 0 0 0 0 0 0 0 0 05-12- S3 100 0 0 0 0 0 0 0 0 0 0 0 0 2011 S4 90 0 10 0 0 0 0 0 0 0 0 0 0 S5 85 0 15 0 0 0 0 0 0 0 0 0 0 S6 80 0 20 0 0 0 0 0 0 0 0 0 0 S1 75 5 0 0 0 0 0 0 0 0 0 20 0 S2 60 5 20 15 0 0 0 0 0 0 0 0 0 19-01- S3 75 5 5 0 0 0 0 0 0 0 0 15 0 2012 S4 80 0 10 10 0 0 0 0 0 0 0 0 0 S5 100 0 0 0 0 0 0 0 0 0 0 0 0 S6 100 0 0 0 0 0 0 0 0 0 0 0 0 S1 70 10 0 10 5 0 0 5 0 0 0 0 0 S2 80 5 0 5 5 0 0 5 0 0 0 0 0 05-03- S3 70 0 0 5 0 0 0 5 0 0 5 15 0 2012 S4 75 5 0 0 0 0 0 10 0 0 5 5 0 S5 80 0 0 5 15 0 0 0 0 0 0 0 0 S6 100 0 0 0 0 0 0 0 0 0 0 0 0