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Surname, Initial(s). (2012) Title of the thesis or dissertation. PhD. (Chemistry)/ M.Sc. (Physics)/ M.A. (Philosophy)/M.Com. (Finance) etc. [Unpublished]: University of Johannesburg. Retrieved from: https://ujdigispace.uj.ac.za (Accessed: Date).

Aspects of the biological integrity of the Mutale, Mutshindudi and Tshinane Rivers, Limpopo Province

By

ALBERTUS JACOBUS FOURIE

Minor Dissertation Submitted in fulfilment of the requirement for the degree of

MAGISTER SCIENTIAE In AQUATIC HEALTH In the FACULTY OF SCIENCE At the UNIVERSITY OF JOHANNESBURG

Supervisor: Dr J.C. van Dyk

May 2014

A.J. Fourie Page 1

Abstract

Aquatic ecosystems in rural South Africa have been impacted over many years by commercial and subsistence anthropogenic activities (DWAF, 2001). These impacts include commercial and subsistence farming, domestic use (e.g. washing of clothes, cars and bathing) and recreational use (e.g. fishing). In the northern parts of the Limpopo Province of South Africa (Vhembe District) the land use is primarily dominated by various agricultural activities and human settlements. Rivers in this region flow through mixed agricultural use, including commercial agriculture (tea and timber plantations) as well as subsistence farming and housing. Perennial rivers in this region include the Mutale, Mutshindudi and Tshinane rivers. These rivers are located in the Water Management Area 2 (WMA 2 Luvuvhu-Letaba) (Kleynhans, et al., 2007a). They are highland river systems, originating in the nearby Soutpansberg Mountain, and these rivers all form part of the larger drainage system of the Luvuvhu River, a tributary of the Limpopo River. The wetlands in the catchment of these rivers are also heavily utilised by the local communities (Working on Wetlands, 2013) used for grazing, sand mining and subsistence cultivation, thus providing a livelihood for the surrounding communities (SANBI, 2012). The aim of the study was to assess aspects of the biological integrity of the Mutale, Mutshindudi and Tshinane rivers. This study formed part of a larger study that included assessments of both abiotic and biotic aspects of these river systems.

For this study, the focus was on assessing the fish community structure through the application of Fish Response Assessment Index (FRAI), riparian vegetation through the application of Vegetation Response Assessment Index (VEGRAI) and fish health aspects with special reference to liver and gonadal histopathology.

Water quality parameters were found to be within the target water quality range for aquatic ecosystems. The results did however vary between upstream and downstream sampling sites. Similarly, compared to upstream sites, the FRAI showed the Mutale River to improve in fish community structure whereas the Tshinane and Mutshindudi rivers showed a decrease in the FRAI score. The VEGRAI results showed a decrease in EcoCondition in the Mutale and Mutshindudi rivers whereas the Tshinane indicated an increase. This can be attributed to land use change up to the edge of the river systems. Visual observation at the various study sites showed a definite localised impact of human activities on the beds and banks of many parts of the rivers. No histological alterations were identified in any of the gonadal or liver tissue of the Chiloglanis pretoriae (Shortspine suckermouth) (Van der Horst, 1931) and the fish were found to be in a healthy condition according to the selected

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parameters (gonads and livers) assessed. The fish community structure of the three rivers were found to be in a moderately to largely modified condition according to the ecological state categories calculated. However, the fish health assessment showed no histological alterations in the sampled fish. It is proposed that future studies investigate the influence of the domestic use of the rivers as well as attempt to quantify the impact of agriculture on the system.

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TABLE OF CONTENTS

1. Chapter 1: Introduction ...... 12

1.1. Research Aim and Objectives ...... 16

1.2. Hypothesis ...... 16

2. Chapter 2: Background information ...... 17

2.1. Land use ...... 17

2.2. Agricultural impacts ...... 19

2.2.1. Agrochemicals including pesticides ...... 19

2.2.2. Sedimentation ...... 19

2.2.3. Alteration of the beds and banks of rivers ...... 20

2.2.4. Afforestation ...... 21

2.2.5. Buffers and agriculture ...... 21

2.3. Domestic use of water ...... 22

2.3.1. Pathogen pollution in the study sites river systems...... 22

2.3.2. Fishing for human consumption...... 23

2.4. Study area description ...... 23

2.4.1. Ecoregions ...... 24

2.4.2. Vegetation types ...... 26

2.5. Selected study sites ...... 27

2.6. Mutale River ...... 28

2.6.1. Mutale River sampling site description ...... 29

2.7. Mutshindudi River ...... 31

2.7.1. Mutshindudi river sampling site description ...... 31

2.8. Tshinane River ...... 33

2.8.1. Tshinane River sampling site description ...... 33

3. Chapter 3: Methods ...... 35

3.1. Fish population response assessment ...... 35

3.1.1. Step 1: Selection of river for assessment ...... 36

3.1.2. Step 2: Determination of the reference fish assemblage ...... 36

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3.1.3. Step 3: Determination of the present state of drivers ...... 37

3.1.4. Step 4: Selection of representative sampling sites ...... 38

3.1.5. Step 5: Determination of fish habitat condition ...... 38

3.1.6. Step 6: Fish sampling ...... 38

3.1.7. Step 7: Collate and analyse fish sampling data ...... 39

3.1.8. Step 8: Execution of FRAI model ...... 39

3.2. Fish health assessment ...... 40

3.2.1. Target species ...... 40

3.2.2. Necropsy ...... 40

3.2.3. Histopathology ...... 41

3.3. Marginal to terrestrial vegetation assessment ...... 41

4. Chapter 4: Results ...... 43

4.1. Ecological drivers ...... 43

4.1.1. Turbidity or Total Suspended Solids ...... 44

4.1.2. Chemical Oxygen Demand (COD) ...... 44

4.1.3. Nitrates and phosphates ...... 46

4.1.4. pH ...... 47

4.1.5. Ammonium ...... 47

4.1.6. Sulphate ...... 48

4.1.7. Total Dissolved Solids (TDS)/ Electrical Conductivity (EC) ...... 48

4.2. Fish population response assessment ...... 49

4.3. Fish health ...... 50

4.3.1. Necropsy ...... 50

4.3.2. Histopathology ...... 51

4.4. VEGRAI results ...... 53

4.5. Comparisons between the FRAI and VEGRAI results ...... 54

4.5.1. Mutshindudi River ...... 54

4.5.2. Mutale River ...... 55

4.5.3. Tshinane River ...... 56

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5. Chapter 5: Discussion ...... 57

5.1. Ecological Drivers ...... 57

5.1.1. Turbidity ...... 57

5.1.2. Chemical oxygen demand (COD) ...... 57

5.1.3. Nitrates and Phosphates ...... 58

5.1.4. pH ...... 58

5.1.5. Total Dissolved Solids (TDS)/ Electronic conductivity (EC) ...... 58

5.2. Fish Response Assessment Index (FRAI) ...... 59

5.3. Vegetation Response Assessment Index (VEGRAI) ...... 59

5.4. Fish Response Assessment Index (FRAI) and Vegetation Response Assessment Index (VEGRAI) ...... 60

5.5. Fish necropsy and histology ...... 61

6. Chapter 6: Conclusion and recommendations ...... 62

7. Chapter 7: References ...... 64

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FIGURES:

Figure 1: Land use map for the study area (SANBI, 2013) ...... 17 Figure 2: The 1963 aerial image of the area. Note the extensive domestic agriculture in the area (yellow polygon)...... 18 Figure 3: The 2009 Google Earth aerial image of the area. The same areas as in 1963 is still being cultivated, but some areas have been transformed into commercial agriculture areas (yellow polygon)...... 18 Figure 4: Extreme erosion on an ephemeral stream feeding into the Mutale River...... 20 Figure 5: The general location (arrow) of the Mutshindudi, Tshinane and Mutale Rivers within the Luvuvhu-Letaba water management area (WMA2) ...... 24 Figure 6: The catchment data as described by the Department of Water Affairs (DWA, 2012) ...... 25 Figure 7: Vegetation types of the study area (Mucina & Rutherford, 2006) ...... 26 Figure 8: The location of the selected rivers and sampling site location (red=Mutale, green=Tshinane and blue=the Mutshindudi River)...... 27 Figure 9: The National Freshwater Ecosystems Priority Areas (NFEPA) map of the Mutale river. The dark green indicates fish priority areas ...... 29 Figure 10: The Mutale River sampling sites location...... 29 Figure 11: The Mutshindudi River sampling sites location ...... 31 Figure 12: A map showing the location of the three sampling sites in the Tshinane River (t1 – t3) (arrows) ...... 33 Figure 13: A map showing The location of the FROC and reference sites in relation to the sampling sites ...... 36 Figure 14: The selected fish species used in the health assessment study, Chiloglanis pretoriae (Shortspine suckermouth) (Skelton, 2001) ...... 40 Figure 15: Turbidity readings of the water samples collected per site ...... 44 Figure 16: Dissolved Oxygen levels (mg/l) measured in situ during the September, November 2011 and April 2012 sampling surveys. Tshinane 1 and Mutshindudi 2 exceeds the maximum level of measurability (40 mg/l)...... 45 Figure 17: The dissolved Oxygen levels (percentage) measured in situ during the April sampling survey...... 45 Figure 18: Nitrate and phosphate levels measured in water samples collected during the September 2011 sampling survey ...... 46 Figure 19: Nitrate and phosphate levels measured in water samples collected during the april 2012 sampling survey ...... 46

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Figure 20: The pH levels measured in situ at the various sampling sites during the April 2012 sampling survey. the target water quality range is also indicated...... 47 Figure 21: Ammonium levels measured in water samples collected from the various sites during the april 2012 sampling survey. the target water quality range is also indicated ...... 47 Figure 22: Sulphate levels measured in water samples collected from the various sites during the april 2012 sampling survey...... 48 Figure 23: TDS levels measured in situ at the various sites during the april 2012 sampling survey...... 48 Figure 24: The combined FRAI results calculated for the various sampling sites of the three selected rivers ...... 50 Figure 25: The condition factor values calculated for the male and female Chiloglanis pretoriae specimens ...... 51 Figure 26: A low magnification (10x) micrograph showing typical liver parenchyma of C. pretoriae with intrahepatic pancreatic tissue and vasculature clearly visible...... 52 Figure 27: Primary oocytes in the peri-nuclear stage of development in a female specimen 52 Figure 28: Spermatozoa (blue) visible in the seminiferous lobules of a male specimen ...... 53 Figure 29: Level 3 VEGRAI results calculated for the various sites of the three selected rivers ...... 53 Figure 30: The FRAI and VEGRAI results calculated for the sampling sites of the Mutshindudi River ...... 55 Figure 31: The FRAI and VEGRAI results calculated for the sampling sites of the Mutale River ...... 55 Figure 32: The FRAI and VEGRAI results calculated for the sampling sites of the ...... 56

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TABLES:

Table 1: General benefits from buffer adapted from Department of Water Affairs and Forestry, 2000 ...... 21 Table 2: The general characteristics of the Ecoregion II (Kleynhans, et al., 2005) ...... 25 Table 3: The length catchment and origin description of the three rivers of the study area (DWA, 2012) ...... 28 Table 4: The river health rating for the Mutale River (DWAF, 2001) ...... 28 Table 5: Sampling site location in the Mutale river, description and image ...... 30 Table 6: The river health rating for the Mutshindudi River (DWAF, 2001) ...... 31 Table 7: The sampling site description of the Mutshindudi River ...... 32 Table 8: The Tshinane river sample location descriptions ...... 34 Table 9: The eight steps of FRAI as described by Kleynhans, 2007 ...... 35 Table 10: Reference list of expected species for the study sites. A9Muta-School is the reference list for the Mutale River, whereas A9Muts-Phiph is the reference list for the Mutshindudi and Tshinane Rivers (Kleynhans, et al., 2007a)...... 37 Table 11: The Present ecological state category interpretation guide ...... 39 Table 12: The physico-chemical results for the sample surveys (blank blocks is areas where no data is available)...... 43 Table 13: The observed species list for all the sites with abundance ratings ...... 49 Table 14: The mean and standard deviation (±SD) values of the condition factors of the sampled Chiloglanis pretoriae specimens ...... 50 Table 15: The combined FRAI and VEGRAI EcoCondition percentage and classes scores for the three rivers ...... 54

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Abbreviations

DWA Department of Water Affairs DWAF Department of Water Affairs and Forestry EDC Endocrine Disrupting Chemical FAII Fish Assembly Integrity Index FRAI Fish Response Assessment Index FROC Fish Reference of Occurrence H&E Haematoxylin and Eosin NBF Neutrally Buffered Formalin NFEPA National Freshwater Priority Areas NTU Nephelometric Turbidity Units POP Persistent Organic Pollutant RVI Riparian Vegetation Index SASS South African Scoring System TDS Total Dissolved Solids TWQR Target Water Quality Range VEGRAI Vegetation Response Assessment Index WMA Water Management Area WRC Water Research Commission

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Acknowledgements

The writing of this dissertation has been one of the most significant milestones in my life. Without the support, patience and guidance of the following people, this study would not have been possible:

. My wife Ingrid and our children Cameron and Mikayla for supporting and allowing me the time required to complete my studies, . Dr. J.C. van Dyk who undertook to act as my supervisor despite his many other commitments. His knowledge and commitment to the inspired and motivated me, . My mother for her support and prayers, . The Zoology Department at the University of Johannesburg in particular Prof. V. Wepner and Dr. S Bollmohr.

It is to them that I owe my deepest gratitude

Proverbs 16:9 “A man's heart plans his way, But the Lord directs his steps”.

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1. Chapter 1: Introduction

Aquatic ecosystems in rural South Africa have been impacted over many years by commercial and subsistence anthropogenic activities (DWAF, 2001). These impacts include commercial and subsistence farming, domestic use (e.g. washing of clothes, cars and bathing) and recreational use (e.g. fishing). Most of South Africa’s water use is dominated by the agricultural sector (62%) with domestic and urban use estimated at 27%, industrial use at 8% and power generation and forestry at approximately 3% (CSIR, 2010). Hydrological controls in the form of dams and weirs to impound water for irrigation schemes (and by inference agriculture) are widespread in South Africa’s lotic ecosystems and also negatively impact on these ecosystems (Davies & Day, 1998). South Africa has some 569 dams capturing approximately 70% of the country’s mean annual precipitation (Fouche, et al.,

2013). As South Africa is a semi-arid country, it depends greatly on these man-made reservoirs.

The direct abstraction of water from aquatic ecosystems for agriculture, as well as the non- point and point pollution by fertilizers, pesticides and herbicides has a compounding, detrimental effect on lotic ecosystems by reducing water quality and quantity and altering the natural habitat of aquatic biota (WRC, 2013). The effects of poor land cultivation practices also negatively impact on aquatic ecosystems, by becoming sources of sediment pollution (Lorentz, et al., 2013).

Secondary to agriculture, is the direct use of river systems by local populations to provide ecological goods and services. These goods and services are primarily based on the provision of water to wash clothes, bathing, abstraction for domestic use and religious practices. Other goods and services include the use of sand/soil for construction purposes, harvesting of reeds and the collection of fish for human consumption. The provision of water is therefore primary to the financial and economic well-being of the population. If the impact to the system is high, some of the goods and services may be reduced or even lost (DWAF, 2001). Water quality and aquatic habitat of river systems are also negatively impacted by the alteration of river beds and banks through the removal of natural riparian vegetation and increased human and livestock movement to access the water, resulting in increased soil erosion and sedimentation.

In the northern parts of the Limpopo Province of South Africa (Vhembe District) the land use is primarily dominated by various agricultural activities and human settlements. Rivers in this

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region flow through mixed agricultural use, including commercial agriculture (tea and timber plantations) as well as subsistence farming and housing. Perennial rivers in this region include the Mutale, Mutshindudi and Tshinane rivers. These rivers are located in the Water Management Area 2 (WMA 2 Luvuvhu-Letaba) (Kleynhans, et al., 2007a). They are highland river systems, originating in the nearby Soutpansberg Mountain, and these rivers all form part of the larger drainage system of the Luvuvhu River, a tributary of the Limpopo River. The wetlands in the catchment of these rivers are also heavily utilised by the local communities (Working on Wetlands, 2013) used for grazing, sand mining and subsistence cultivation, thus providing a livelihood for the surrounding communities (SANBI, 2012).

The water resource capacity of the Luvuvhu and Mutale catchments is surprisingly large. This is due to the high rainfall frequency in the Soutpansberg Mountains, which results in high yields in both catchments (DWA, 2012). Water requirements in the Luvuvhu catchment is dominated by irrigation and has exceeded the available resource, while the water use in the Mutale catchment, also mostly used for irrigation, is approximately in balance with the resource (DWA, 2004). The recent completion of the Nandoni Dam (completed in 2005 to ensure water security for the towns of Thohoyandou and Louis Trichardt) resulted in a surplus of 37 million m³/a becoming available in the Luvuvhu catchment (Fouche, et al., 2013).

Due to the high utilisation factor by the local communities, the impacts on aquatic ecosystems in this region are twofold: Firstly, there are physical alterations to the ecosystem that includes abstraction of water, habitat destruction, sediment pollution and hydrological alterations. Secondly, there are potential chemical alterations in water quality including physic-chemical parameters but also chemical pollution, and more specifically, agrochemicals in the case of agriculture (Ongley, 1996). A large part of the Vhembe District is also located in a malaria risk area and subsequently Dichlorodiphenyltrichloroethane

(DDT) is used widely for malaria vector control (Marchand, et al., 2008).

In addition to chemical pollution, the use of the rivers and their associated catchments is leading to an increase in sedimentation movement within the systems. The impacts of sedimentation include the reduction of water clarity (turbidity as measured in Nephelometric Turbidity Units NTU) (Harding, et al., 1999). This also impacts on the benthic sediment regime, especially as the river moves from headwaters to middle and lower reaches (Harding, et al., 1999). Negative impacts of sedimentation on fish have been documented before, including a study on Mozambique tilapia, Oreochromis mossambicus (Peters, 1852) where the development of fish was found to be negatively affected in relation to the

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sedimentation load (Smit, et al., 1998). Other impacts included gill and eye damage, as well as behavioural changes including gulping of air, and increased activity. Sedimentation further decreases the habitat suitability for benthic aquatic organisms (Smit, et al., 1998). The decreases in land cover and riparian associated vegetation in catchments is also directly affecting stream biota through the impact on riparian cover (Maloney & Weller, 2011). This is also related to historical and current land use practices.

In recent years, the Vhembe District has experienced increased anthropogenic activities (Gaiger, et al., 2001). Food security in underdeveloped areas is of concern and pressure on natural ecosystems to ensure food security increases. Rivers are seen as a source of goods and services (primarily protein in the form of fish and fresh water) to the community (van der Waal, 2010). To ensure food security from agriculture, the application of pesticides is also increasing (Rickert, 1993).

Traditionally, the monitoring of aquatic ecosystems has involved the measuring of the ecological drivers (physical and chemical assessments of the water column) to determine the condition of the system (DWA, 2013). Attention has moved to the biological responses of the system through bio-monitoring (Dickens & Graham, 2002). Bio-monitoring entails the “monitoring of living organisms, usually as indicators of habitat integrity” (Davies & Day, 1998). In combination with fish, several different biological indicators are used for aquatic bio-monitoring including benthic macro-invertebrates using the South African Scoring System version 5 (SASS 5) (Dickens & Graham, 2002). Diatoms (Periphyton) have also been increasingly used as bio-indicators (van Vuuren, 2007). Their efficacy when used separately has been demonstrated by various studies including Zheng, et al. (2010), van Vuuren (2007) and Harding & Taylor (2011).

Fish are usually a major biological component of riverine ecosystems and contribute to the biological diversity of all systems. The use of a long-living aquatic species such as fish as bio-indicators is useful for the assessment of prolonged or singular impacts to the system. Fish occupy various trophic levels within an aquatic ecosystem and are therefore often used as key indicator species (Brewer 1993) and as part of aquatic health assessment surveys, for example the studies by McHugh et al. (2011; 2013). The structural characteristics of riverine faunal assemblages are measured by the number of fish species and by the spatial and temporal variations in the abundance of those species (Matthews & Heins, 1987). Changes in habitat integrity or water quality can negatively affect the population structure i.e. a decrease in species diversity or the elimination of sensitive or habitat-specific species

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could be observed. In addition to changes in population structure, fish health can also reflect or indicate changes in water quality.

The use of histopathology as a biomarker of pollution in fish is well documented (McHugh, et al., 2011; van Dyk, et al., 2012; McHugh, et al., 2013). The microscopic structure of selected target organs could indicate both long- and short-term exposure to toxic compounds (van Dyk, et al., 2009). A primary target organ used in fish histopathological assessments is the liver. It is the main detoxification organ of the body and studies have shown that fish liver histopathology can be used as a biomarker of aquatic pollution (van Dyk, et al., 2009, van Dyk, et al., 2012). An assessment of gonadal histopathology is equally important, especially when aquatic ecosystems are contaminated with potential endocrine disrupting chemicals (EDC) like DDT and its metabolites. Barnhoorn et al. (2010) showed reproductive abnormalities in the form of testicular oocytes in male Mozambique tilapia from the Luvuvhu River in the Vhembe District.

Studies on the biological integrity of rivers in the Vhembe District have mainly focussed on the Luvuvhu River and its impoundments (Basson & Rossouw, 2003; Bornman, et al., 2010). Previous studies on the biological integrity of the Mutale, Mutshindudi and Tshinane rivers focussed on the fish community structure of these systems and some correlations have been made between the agricultural use of the river and fish population structure. Gaiger et al. (2001) found that fish populations in this region decreased over the past years possibly due to farming practices.

Consequently, a larger, comprehensive study was proposed to further investigate the influence of anthropogenic activities, including agriculture on rural river systems, specifically the Mutale, Mutshindudi and Tshinane rivers in the Vhembe District in the Limpopo Province. As part of this larger study, various aspects of the biological integrity are/were monitored to determine the overall health of the ecosystems. These included: (1) a community survey on pesticide use within this region by Dr. Silke Bollmohr (ongoing); (2) chemical water quality analyses and diatom and aquatic macro-invertebrate assessment (SASS 5) by Ms Leandra Kruger and Ms Zinzi Mboweni (ongoing); and (3) a fish population structure assessment (based on the environmental intolerances and preferences of the fish species (Kleynhans, et al., 2007a) and a fish health assessment. The focus of this mini-dissertation was point (3), as listed above. Through a fish population structure assessment, it was also attempted to ascertain the EcoCondition of the river’s fish population and assign a rating in terms of the terrestrial vegetation component influencing the systems and identifying areas requiring further and future investigations.

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1.1. Research Aim and Objectives

The aim of the study was to assess the fish population structure and fish health aspects of the Mutale, Mutshindudi and Tshinane rivers, Vhembe District, South Africa. To achieve this aim, the following objectives were proposed:

 To perform as fish population response assessment at selected sites using the Fish Response Assessment Index (FRAI);  To assess selected physico-chemical water quality parameters;  To relate the changes in fish community structures to land-use, habitat availability and water quality;  To identify any possible health effects in Chiloglanis pretoriae through a histological assessment of selected target organs;  To determine the marginal and upper marginal habitat quality using the Riparian Vegetation Response Assessment Index (VEGRAI).

1.2. Hypothesis

Anthropogenic activities have a negative impact on the fish population structure and fish health of the Mutale, Mutshindudi and Tshinane rivers.

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2. Chapter 2: Background information

2.1. Land use

Over the past 50 years the land use in the study area has not changed from the current use (Figure 1) but the type of application has. This is due to more areas of subsistence farming being converted to commercial agriculture and is mainly due to the road infrastructure improving in the area as well as the growth in human population. To give an indication of the alteration of the study area in terms of commercial agriculture, historical and current aerial images from the area of the study sites of the Mutale catchment are presented. An image from 1963 (Figure 2) is given in contrast to a Google Earth image from 2013 (Figure 3).

FIGURE 1: LAND USE MAP FOR THE STUDY AREA (SANBI, 2013)

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FIGURE 2: THE 1963 AERIAL IMAGE OF THE AREA. NOTE THE EXTENSIVE DOMESTIC AGRICULTURE

IN THE AREA (YELLOW POLYGON).

FIGURE 3: THE 2009 GOOGLE EARTH AERIAL IMAGE OF THE AREA. THE SAME AREAS AS IN 1963 IS

STILL BEING CULTIVATED, BUT SOME AREAS HAVE BEEN TRANSFORMED INTO COMMERCIAL

AGRICULTURE AREAS (YELLOW POLYGON).

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2.2. Agricultural impacts

Expected impacts in the study area include agrochemical and sedimentation pollution as well as alteration of riparian zones which is increasing due to commercialisation of subsistence farming areas. Expansion of forestation is also increasing the impacts on the aquatic ecosystems. As the pressure for land for subsistence farming increases the buffer zones around aquatic ecosystems also decrease.

2.2.1. Agrochemicals including pesticides

The use of herbicides and pesticides by farmers (both commercial and subsistence) in the catchment of the rivers may lead to the pollution of the rivers and potential bioaccumulation of these chemicals in the aquatic fauna and flora (Barnhoorn, et al., 2010; Bornman, et al., 2010). The use of Dichlorodiphenyltrichloroethane (DDT) for the control of malaria mosquitoes in villages surrounding the study area and the potential pollution of the nearby river systems is therefore of concern. Dichlorodiphenyltrichloroethane is a Persistent Organic Pollutant (POP) and a potential endocrine disrupting chemical (EDC) that is banned from most countries in the world, but some, such as South Africa continues to use the pesticide against the malaria epidemic. Endocrine disrupting chemicals can interact with the physiological systems and cause alterations in the development, growth and reproduction in fish (Bornman, et al., 2010).

2.2.2. Sedimentation

Various land uses including agriculture has led to the siltation of aquatic systems. Many of the South African dams are losing capacity due to high sedimentation loads entering the system, especially the dam systems in the Orange River (Davies & Day, 1998). Van der Waal (1997), reported that Lake Fundudzi is threatened by an increased rate of sedimentation due to anthropogenic activities (especially farming and plantations in the catchment of the system). He was further of the opinion that Lake Fundudzi deserved “national and international conservation status” and that it could “become a valuable ethno- and eco-tourist attraction” if managed and protected properly (van der Waal, 1997). He concluded that the real challenge would be to develop the potential of the area by involving the local community in the eco-tourism potential, while at the same time ensuring the required protection to the lake and its surroundings so as not to disrupt or threaten the traditional ceremonies and rituals (Van der Waal, 1997). The land uses within the catchment area are also sources of sediment pollution, especially if improper land practices are being applied. Figure 4 shows an example of the result of such practices in the catchment of the

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Mutale River. Extreme erosion is due to improper culvert design during road construction, overgrazing of extensive areas and channel straightening of wetlands higher in the catchment of the river.

FIGURE 4: EXTREME EROSION ON AN EPHEMERAL STREAM FEEDING INTO THE MUTALE RIVER.

2.2.3. Alteration of the beds and banks of rivers

The term piosphere effect is used to describe the clearing of natural vegetation around a water source (Biggs, et al., 2003). This is due to trampling and heavy utilisation of the vegetation component around a water source especially during times of drought (Thrash & Derry, 1999). The clearing of the vegetation source increases the erodibility of the soils leading to sedimentation pollution and the altering of the in-stream habitat.

In 2001 the catchment was used for traditional cattle farming, irrigation schemes, orchards (rain fed) and irrigated household vegetable gardens (DWAF, 2001) and in 2011 these activities were observed to be expanding The riparian vegetation is over utilised for many uses including fire wood, fencing, furniture, medicinal purposes and food. As a result of the

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impact on the riparian vegetation, the soils of the area have become unstable and sedimentation is of concern.

2.2.4. Afforestation

The impact of afforestation on the available resource is based on an afforested area of 167 km2. Most of this (134 km2) is in the Luvuvhu catchment, which has a significant impact on the available yield due to its location upstream of the Albasini and Vondo dams. The afforestation in the Mutale catchment is all situated in the high lying area around Lake Fundudzi (DWA, 2004). Unsuitable farming practices and road crossings are the main contributors to degradation (SANBI, 2012).

2.2.5. Buffers and agriculture

Many subsistence farmers who farm in close proximity to the rivers, plant crops up to the edge of the water of the rivers. This opens the banks of the rivers to erosion. The protection that is provided by the fringing vegetation in aquatic ecosystems is very important to reduce the impact that land use activities has on the aquatic ecosystem. Riparian buffer zones provide the following benefits (Table 1) (DWAF, 2000):

TABLE 1: GENERAL BENEFITS FROM BUFFER ADAPTED FROM DEPARTMENT OF WATER AFFAIRS

AND FORESTRY, 2000 o Intercepting sediments/nutrients - Key to counteract eutrophication in downstream lakes and ponds which can be detrimental to aquatic habitats because of large fish kills that occur upon large- scale eutrophication. o Intercepting pesticides - Riparian buffers keep chemicals that can be harmful to aquatic life out of the water. Some pesticides can be Water quality especially harmful if they bio-accumulate in the organism, with the benefits chemicals reaching harmful levels once they are ready for human consumption. o Bank stabilization - This is important because erosion can be a major problem in agricultural regions when cut (eroded) banks can take land out of production. Erosion can also lead to sedimentation and siltation of downstream lakes, ponds, and reservoirs. o Provide habitat - Riparian buffers can act as crucial habitat for a Habitat benefits large number of species, especially those who have lost habitat

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due to agricultural land being put into production. o Increase biodiversity - By adding this vegetated area of land near a water source it becomes a prime location for species that may have left the area due to non-conservation land use to re-establish. With this re-establishment the number of native species and biodiversity in general can be increased. o Buffers acting as corridors - Buffers also serve a major role in wildlife habitat. The habitat provided by the buffers also doubles as corridors for species that have had their habitat fragmented by various land uses. o Shading water - The large trees in the first zone of the riparian buffer provide shade and therefore cooling for the water, increasing productivity (through increased oxygen) and increasing habitat quality for aquatic species. o Increase land value - Often people who purchase land for Economic recreational use are willing to pay more if there is more wooded benefits area located on the land.

2.3. Domestic use of water

The aquatic ecosystems within the study area are used in many ways by the local communities. Piped water is mostly supplied via central stand pipes and the Vhembe District municipality has over the past years improved on the quality of drinking water supplied to the communities. As the communities have to pay for the water, this water is not used for general cleaning (eWISA, 2013). The aquatic ecosystems are primarily used for the washing of clothes and cars, bathing and abstraction for general household chores. This has a twofold effect: firstly the water physico-chemical properties are altered and secondly the banks of the riparian zone (marginal and non-marginal) zones are altered. The rivers are also extensively utilised for recreational use by the communities. The river is a meeting place for the local woman converging on the river to wash their clothes. People also use the river for fishing and swimming (personal observation 2011).

2.3.1. Pathogen pollution in the study sites river systems

The utilisation of the rivers as water source for all the needs of the community has led to the assimilation of pathogens that is a potential risk to the community health. These pathogens include faecal coliforms and the possible sources of contamination of the river water sources

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include human and animal faeces or introduction of micro-organisms by birds and insects. Most of the river sources are reportedly prone to higher bacterial levels due to heightened ecological activities, and may therefore not be suitable for human consumption. These multiple sources of contamination are compounded by limited environmental awareness in rural areas. Some of the pathogens found in the river systems are (Obi, et al., 2002): Mutshindudi River: Escherichia coli, Shigella spp., Vibrio spp., Aeromonas spp., Salmonella spp., Campylobacter spp. Tshinane River: Escherichia coli, Aeromonas spp., Campylobacter spp., Salmonella spp. Mutale River: Shigella spp., Samonella spp., Aeromonas spp. These results indicate that the faecal pollution of the rivers makes the rivers unsuitable for human activities.

2.3.2. Fishing for human consumption

The utilisation of fish in the rivers within the study area has been highlighted by both Bornman, et al. (2010) and van der Waal (1997) as of concern. The use of fine gillnets in (some cases man made) removes even the smallest fish from the system. During the site visit in February 2012 on the Tshinane River, it was observed that people use shirts wrapped between two poles to catch fish, in many cases fish no larger than 50 mm are caught. Utilisation of fish in the Mutshindudi River is high, leading to a low catch effort (18 of the 27 expected species. According to van der Waal (2010), the primary method of fishing is hook and line (84%) with gillnetting 15% and cloth 1%. No specific preference for species exists- fish that were available were consumed.

2.4. Study area description

As mentioned before, the study area is located in the north-eastern corner of the Limpopo Province, in the Vhembe District. The rivers selected for this study all form part of the larger Limpopo River catchment and is located in the Luvuvhu and Letaba water management area (WMA 2) (Figure 5)

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Luvuvhu & Letaba WMA 2

FIGURE 5: THE GENERAL LOCATION (ARROW) OF THE MUTSHINDUDI, TSHINANE AND MUTALE

RIVERS WITHIN THE LUVUVHU-LETABA WATER MANAGEMENT AREA (WMA2)

2.4.1. Ecoregions

The selected rivers are all located within the Ecoregion II- Soutpansberg (Kleynhans, et al., 2005) Figure 6 and are defined by the characteristics as listed in Table 2.

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TABLE 2: THE GENERAL CHARACTERISTICS OF THE ECOREGION II (KLEYNHANS, ET AL., 2005) Characteristic Description Mean annual precipitation Varies from very low to moderate in the east Coefficient of Variation of annual Low to moderate precipitations Drainage density Medium Stream Frequency Medium to high Slopes <5%: 20<% Mean annual temperature Mostly moderate but hot in the east Plains with low relief (limited) Plains moderate relief (Very limited) Terrain morphology Lowlands, hills and mountains (moderate and high relief) Closed hills and mountains (Moderate to high relief)

FIGURE 6: THE CATCHMENT DATA AS DESCRIBED BY THE DEPARTMENT OF WATER AFFAIRS

(DWA, 2012)

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2.4.2. Vegetation types

The study area is classified by the following two vegetation types, Makuleke Sandy Bushveld and Soutpansberg Mountain Bushveld (Mucina & Rutherford, 2006) (Figure 7).

Mutale River

SVI1

SVcb2 1 Tshinane River

Mutshindudi River

FIGURE 7: VEGETATION TYPES OF THE STUDY AREA (MUCINA & RUTHERFORD, 2006)

Makuleke Sandy Bushveld (SVI1) This vegetation type has a variable landscape with low mountains to extremely irregular plains and hills. Tree savannah occurs in deep sands with trees such as Terminalia sericea, Burkea africana, Guibourtia conjugate and Peltophorum africana. The geology of the area is the Soutpansberg group of sandstone with lesser amounts of conglomerate, shale and basalt. Most of the area has deep sands to shallow sandy lithosols. The endemic succulent shrub Euphorbia rowlandii is found in the vegetation type. Approximately 32% of the vegetation type is conserved in the Kruger National Park (Mucina & Rutherford, 2006)

Soutpansberg Mountain Bushveld (SVcb21) This vegetation type occurs in low to high mountains of which the highest is in the west, splitting into increasing numbers of mountain ridges in the east. A dense tree layer with a poorly developed grass layer is characteristic of this vegetation type. The Soutpansberg is orientated from east to west and the vegetation type is found throughout the mountains. Due to the orientation of the ridge, the vegetation changes drastically over the ridge (from south

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to north) resulted from orographic rain on the southern ridges and rain shadow effect on the northern ridges. The main vegetation variations within the Soutpansberg Mountain Bushveld are subtropical moist thickets, mist-belt bush clumps and relatively open savanna sandveld. Reddish or brown sandstone and quartzite, conglomerate, basalt, shale, tuff and siltstone of the Soutpansberg Group constitute the geology of the area. Important endemic taxa include: Combretum vendae, Vangueria soutpansbergensis, Tylophora coddii and Impomoea bisavium. Only approximately 2% of the vegetation type is conserved within the Blouberg Nature Reserve. Portions of the vegetation type incorporate Afromontane Fynbos on the escarpment (Mucina & Rutherford, 2006).

2.5. Selected study sites

Three river systems were chosen as part of a larger study as mentioned in Chapter 1. Two sampling sites were selected along the Mutale River, three along the Mutshindudi River and three along the Tshinane River (Figure 8). The site selection per river was based on the prescribed sampling protocol as described for fish population assessments by Kleynhans (1999; 2007) and for SASS as described by Dickens & Graham (2002). Accessibility was also a deciding factor. As many parts of the rivers (especially the Mutale River) are impounded (weir structures) for the irrigation of agricultural activities, the suitability of the sampling methods is negated (when a river is dammed it reduces the habitat integrity and a thus the fish population assimilation is impacted).

FIGURE 8: THE LOCATION OF THE SELECTED RIVERS AND SAMPLING SITE LOCATION

(RED=MUTALE, GREEN=TSHINANE AND BLUE=THE MUTSHINDUDI RIVER).

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TABLE 3: THE LENGTH CATCHMENT AND ORIGIN DESCRIPTION OF THE THREE RIVERS OF THE

STUDY AREA (DWA, 2012) Secondary Quaternary River Length Origin catchment catchment Mountainous area, Mutshindudi 57 km A9 A91G impounded at the Vondo Dam Tshinane 18 km A9 A91G Mountainous area 121.5 A91A Mutale A9 Lake Fundudzi km A91B

2.6. Mutale River

The Mutale River has been identified in recent years as a system ever increasingly impacted by sedimentation, possibly caused by agriculture (CSIR, 2010). The system originates from Lake Fundudzi (revered by the local Venda population) as a sacred and holy lake and flows to the Luvuvhu River, a tributary of the Limpopo River. The Mutale River flows through large extends of agricultural areas, including commercial and substance farming. In 2001, the River Health Program (RHP) rated the Upper Mutale River (near Lake Fundudzi) health as fair to good (DWAF, 2001) (Table 4).

TABLE 4: THE RIVER HEALTH RATING FOR THE MUTALE RIVER (DWAF, 2001) Health Status SASS Good FAII Good RVI Fair Desired Health Good

A portion of the river is prioritised for conservation by the National Freshwater Priority Areas (NFEPA) for fish species conservation including: Line-spotted barb, Barbus lineomaculatus (Boulenger, 1903); Tigerfish, Hydrocynus vittatus (Castelnau 1861) and Northern barred minnow, Opsaridium peringueyi (Peters 1852) and aquatic ecosystems (river and wetland) (Figure 9) (Nel, et al., 2011).

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Mutale River

NFEPA area

FIGURE 9: THE NATIONAL FRESHWATER ECOSYSTEMS PRIORITY AREAS (NFEPA) MAP OF THE

MUTALE RIVER. THE DARK GREEN INDICATES FISH PRIORITY AREAS

2.6.1. Mutale River sampling site description

The two sampling sites selected in this system were where the most agricultural activities occur within this catchment (Figure 10). Only two sampling sites were chosen because lower down the system becomes impounded and deeper thus not allowing for all aquatic biotypes to be present for sampling (Dickens & Graham, 2002; Kleynhans, 2007c). See Figure 10 for a map of the sample site location and Table 5 for the description of the sample sites .

FIGURE 10: THE MUTALE RIVER SAMPLING SITES LOCATION.

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TABLE 5: SAMPLING SITE LOCATION IN THE MUTALE RIVER, DESCRIPTION AND IMAGE Sampling GPS Description Images site coordinates

MU0 is the higher up in the river and closest to Lake Fundudzi, and is in an area 22°48'20.10"S of relatively low land use for agriculture. Mutale 0 30°25'24.77"E The sampling site is located at the end of a rapid, and is characterised by an alluvial fan deposit at the end of the sampling site.

MU1 is located approximately 3 km downstream from the MU0 sampling site. The site is upstream of a large bridge running through extensive commercial 22°47'33.63"S Mutale 1 agricultural areas. The site has good 30°27'0.03"E representative fish habitat types (Kleynhans, 2007c). The site is impacted on by recreational use as well as cattle drinking and washing of cars.

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2.7. Mutshindudi River

The Mutshindudi River flows from the eastern part of the Soutpansberg Mountains into the man-made Vondo Dam and into the Luvuvhu River. The catchment of this system is extensively utilised for agriculture including tea production and forestry. Activities within this area include subsistence farming (up to 50%) and plantations covering some 17% of the total catchment area (DWAF, 2001). The River Health Program (RHP) rated the Mutshindudi River health as fair to good (DWAF, 2001) (Table 6) in 2001.

TABLE 6: THE RIVER HEALTH RATING FOR THE MUTSHINDUDI RIVER (DWAF, 2001) Present Health SASS Good FAII Fair RVI Fair Desired Health Good

2.7.1. Mutshindudi river sampling site description

Three sampling sites were selected in the Mutshindudi River (Figure 11) including an upstream and a site in the middle reaches as well as a site downstream from agricultural impacts including tea plantations (Table 7).

FIGURE 11: THE MUTSHINDUDI RIVER SAMPLING SITES LOCATION

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TABLE 7: THE SAMPLING SITE DESCRIPTION OF THE MUTSHINDUDI RIVER GPS Sampling site Description Images coordinates

The site is located below the Vondo Dam and is impacted by the frequent use of local residents for 22°57'16.65"S Mutshindudi 1 washing of clothes. A frequently used footpath 30°22'20.21"E leads over the site and the area has been altered by the placement of stones to create a bridge.

Very steep banks lead to the site under a large 22°54'0.42"S bridge. The site is impacted by local residents for Mutshindudi 2 30°31'29.25"E washing of clothes. Due to the slope of the banks, little utilisation of this site is for cattle drinking.

Located just after a bridge and an extensive impounded area. This site is highly impacted by the local community that use it as a washing point 22°51'53.19"S for clothes and cattle drinking. Just upstream of the Mutshindudi 3 30°38'32.39"E site are large areas of agriculture (divided into

plots) located up to the edge of the river. These plots are irrigated with water abstracted from the river.

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2.8. Tshinane River

The Tshinane River is a relatively short river (approximately 18 km) running parallel to the Mutshindudi River and joins the Mutshindudi River further downstream. Although the river is not long, the system is strong flowing. The river flows through areas of tea plantations and tea processing factories. The upper headwaters of the system are extensively used for plantations. This leads to high sediment loads due to the unstable banks of the catchment of the system.

2.8.1. Tshinane River sampling site description

Three sampling sites were selected in the Tshinane River (Figure 12) including an upstream and a site in the middle reaches as well as a site downstream from agricultural impacts including tea plantations (Table 8).

FIGURE 12: A MAP SHOWING THE LOCATION OF THE THREE SAMPLING SITES IN THE TSHINANE

RIVER (T1 – T3) (ARROWS)

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TABLE 8: THE TSHINANE RIVER SAMPLE LOCATION DESCRIPTIONS Sampling GPS Description Images site coordinates

Tshinane 1 The site is located near the origin of the 22°55'9.78"S river, highly utilized by cattle for drinking 30°22'49.68"E as well as for recreational use.

Located downstream from a bridge crossing and small impounded area. Tshinane 2 22°54'44.51"S Large areas of alluvial material 30°26'21.53"E deposition. The site is very dynamic due to the alluvial material movement.

The site is located in a highly eroded Tshinane 3 22°54'38.93"S area just below a bridge. The site has a 30°30'59.57"E fast flowing main channel with good fish habitat.

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3. Chapter 3: Methods

3.1. Fish population response assessment

The Fish population response assessment was done using the Fish Response Assessment Index (FRAI) which consists of 8 steps as described by (Kleynhans, 2007c) (Table 9).

TABLE 9: THE EIGHT STEPS OF FRAI AS DESCRIBED BY KLEYNHANS, 2007 Steps 1-8 Procedure Step 1: Selection of river for As for study requirements and design assessment  Use historical data & expert knowledge  Model: use ecoregions and other environmental Step 2: Determination of the information reference fish assemblage  Use expert fish reference frequency if occurrence database if available  Hydrology  Physico-chemical Step 3: Determination of the present  Geomorphology state of drivers Or  Index of habitat integrity

Step 4: Selection of representative Field survey in combination with other survey activities sampling sites

Step 5: Determination of fish habitat  Assess fish habitat potential condition  Assess fish habitat condition  Sample all velocity depth classes per site if feasible Step 6: Fish sampling  Sample at least three stream sections per site. Step 7: Collate and analyse fish Transform fish sampling data to frequency of occurrence sampling data ratings  Rate the FRAI metrics in each metric group  Enter species reference frequency of occurrence data  Enter species observed frequency of occurrence data Step 8: Execution of FRAI model  Determine weights for metric groups  Obtain FRAI value and category  Present both modelled FRAI and adjusted FRAI

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3.1.1. Step 1: Selection of river for assessment

The selected rivers for this study were the Mutshindudi, Tshinane and Mutale rivers as described in Chapter 2, Section 2.4.

3.1.2. Step 2: Determination of the reference fish assemblage

Fish Response Assessment Index (FRAI) is based on a comparison between historical and in situ fish population assemblage data i.e. a historical list of all fish species present per site compared to a current list of species identified. Two Fish Reference of Occurrence (FROC) lists were used from the WMA 2 Luvuvhu to Letaba FROC list (River Eco-classification: Manual for Ecostatus determination (Version 2) Module D Volume 2) (Kleynhans, et al., 2007a) (Table 10). These lists included the:

 The Mutale (A9Muta-Scho);  The Mutshindudi River (A9Muts-Phiph) (Figure 13).

The Tshinane rivers reference condition was inferred from the Mutshindudi River’s FROC list as the river flows into the Mutshindudi River.

FIGURE 13: A MAP SHOWING THE LOCATION OF THE FROC AND REFERENCE SITES IN RELATION

TO THE SAMPLING SITES

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TABLE 10: REFERENCE LIST OF EXPECTED SPECIES FOR THE STUDY SITES. A9MUTA-SCHOOL IS

THE REFERENCE LIST FOR THE MUTALE RIVER, WHEREAS A9MUTS-PHIPH IS THE REFERENCE LIST

FOR THE MUTSHINDUDI AND TSHINANE RIVERS (KLEYNHANS, ET AL., 2007A). A9 Muta-School A9Muts-Phiph AMOS Anguilla mossambica AURA Amphilius uranoscopus AURA Amphilius uranoscopus BEUT Barbus eutaenia BEUT Barbus eutaenia BMAR Labeobarbus marequensis BLIN Barbus lineomaculatus BUNI Barbus unitaeniatus BMAR Labeobarbus marequensis CGAR Clarias gariepinus BNEE Barbus neefi CPRE Chiloglanis pretoriae BPAU Barbus paludinosus LMAC(E) Lepomis macrochirus BRAD Barbus radiatus MSAL (E) Micopterus salmoides BTRI Barbus trimaculatus OMOS Oreochromis mossambicus BUNI Barbus unitaeniatus TREN Tilapia rendalli BVIV Barbus viviparus TSPA Tilapia sparrmanii CGAR Clarias gariepinus CPRE Chiloglanis pretoriae LCYL Labeo cylindricus LMOL Labeo molybdinus MACU Micralestes acutidens MMAC Marcusenius macrolepidotus MBRE Mesobola brevianalis OPER Opsaridium peringueyi OMOS Oreochromis mossambicus PCAT Petrocephalus wesselsi TREN Tilapia rendalli TSPA Tilapia sparrmanii

3.1.3. Step 3: Determination of the present state of drivers

Water quality parameters were measured during the fish survey in April 2012 as well as in September and November 2011 to coincide with the site visits for the larger study as mentioned in Chapter 1. In situ water quality parameters were measured using the Department of Water Affairs YSI Industries 556 MPS Multimeter. The following parameters were tested for:  Temperature;  pH;  Dissolved oxygen (DO);  Electrical conductivity (EC) and Total Dissolved Solids (TDS).

Parameters not measurable in situ were measured in the laboratory at the University of Johannesburg. For this purpose, one litre plastic bottles were filled on site and the water

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samples were frozen prior to analysis. A Merch Spectroquant Pharo 100 (Photometric Measurement instrument) was used in conjunction with the Merch Spectroquant Reagent Test Kits to test for:  Turbidity;  Chemical oxygen demand;  Nitrates and phosphates;  Ammonium;  Sulphates.

3.1.4. Step 4: Selection of representative sampling sites

Eight sampling sites were selected for this study as described in Chapter 2: Two sampling sites were selected in the Mutale River, and three sites in the Tshinane and Mutshindudi rivers respectively. Refer to section 2.5.

3.1.5. Step 5: Determination of fish habitat condition

Habitat condition was determined according to the FRAI field data sheet per habitat type including the identification and rating of overhanging vegetation, undercut banks and root wads, substrate and aquatic macrophytes. A rating scale of 0 – 5 was used to assess the habitat condition where 0 = absent and 5 = very abundant (Kleynhans, 2007c).

3.1.6. Step 6: Fish sampling

Fish sampling was done in April 2012. Sampling was done through electronarcosis in each habitat type (fast-deep, fast-shallow, slow-deep, slow-shallow) for 15 minutes at each site as described by Kleynhans (2007). Electronarcosis involves the induction of an electric current in the water which renders the fish in close proximity to the electrical field immobile for a short period of time, allowing the collection of fish using a scoop net. The specific equipment used was a Samus 725M electrofisher. This sampling method is in line with the methodology recommended for the FRAI protocol as described by Kleynhans (2007c). Each fish collected was identified to species level and the frequency of occurrence of each species was noted on a pre-prepared FRAI fish data sheet. After identification, fish were returned to the river.

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3.1.7. Step 7: Collate and analyse fish sampling data

Data collected was collated into an occurrence rating. A rating scale of 0 – 5 was used where 0 = absent and 5 = very abundant (Kleynhans, 2007c).

3.1.8. Step 8: Execution of FRAI model

All the data collected from steps 1-7 was important into the FRAI Excel model (Kleynhans, 2007c). A FRAI percentage value and EcoCondition (Present Ecological State (PES)) rating (A-F) was calculated per site (Table 11):

TABLE 11: THE PRESENT ECOLOGICAL STATE CATEGORY INTERPRETATION GUIDE Combined impact Description PES Category score Unmodified, natural. 0-0.9 A Largely natural with few modifications. A slight change in ecosystem processes is 1-1.9 B discernible and a small loss of natural habitats and biota may have taken place. Moderately modified. A moderate change in ecosystem processes and loss of natural habitats has taken place but the 2-3.9 C natural habitat remains predominantly intact Largely modified. A large change in ecosystem processes and loss of natural 4-5.9 D habitat and biota and has occurred.

The change in ecosystem processes and loss of natural habitat and biota is great 6-7.9 E but some remaining natural habitat features are still recognizable. Modifications have reached a critical level and the ecosystem processes have been 8 – 10 F modified completely with an almost complete loss of natural habitat and biota.

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3.2. Fish health assessment

3.2.1. Target species

During the fish population response assessment (as described above), the first 10 short- spine suckermouth Chiloglanis pretoriae (Van der Horst, 1931) (Figure 14) of suitable size (larger fish were favoured over smaller fish) were sampled from the upstream and downstream sites of each of the rivers. The sex of the fish was difficult to determine macroscopically and was not used as a selecting factor. Care was taken not to sample Chiloglanis paratus (Crass, 1960) also occurring in the area (Skelton, 2001; Matlala, et al., 2010).

The genus Chiloglanis includes 45 species of which eight are described from southern Africa (Skelton, 2001). The genus is characterized by jaws and lips that are modified into a sucker or oral disc used for attachment to a variety of substrates and feeding in lotic systems (habitats formed in running water). The suckermouths are typically found in fast flowing waters but over varied substrates and water depths. Chiloglanis pretoriae is not altitude dependant and is abundant where it occurs. Breeding takes place during summer months and eggs are laid between shallow rocks and gravel. The species feed on aquatic- macroinvertebrates such as mayfly nymphs, caddis flies and black fly larvae. The species is a useful indicator species (Skelton, 2001). Chiloglanis spp. is sensitive to flow alterations, and pollutants and are used in the reserve determination and as indicator species to determine the condition of a river system (Matlala, et al., 2010).

FIGURE 14: THE SELECTED FISH SPECIES USED IN THE HEALTH ASSESSMENT STUDY,

CHILOGLANIS PRETORIAE (SHORTSPINE SUCKERMOUTH) (SKELTON, 2001)

3.2.2. Necropsy

Each fish was macroscopically assessed to identify any abnormalities. Fish were measured (total length) and weighed to give an indication of the condition of the fish in relation to the

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population. These measurements were used to calculate a condition factor (CF) for each fish (Carlander, 1969):

3.2.3. Histopathology

Fish were euthanized by severing the spinal cord between the head and the trunk of the fish. Due to the small size of C. pretoriae, the dissection of the fish was not done in the field but left for the laboratory. The small size of the fish also negated the drawing of blood for blood parameter assessment as the volumes of blood would be insufficient.

Tissue samples were processed using standard histopathology methods (Humason, 1979). Fish were fixed whole for 48 hours in 10% neutrally buffered formalin (NBF). Samples were further processed and prepared for light microscopy analyses at the University of Johannesburg. The NBF samples were washed in running tap water for approximately 12 hours. Dehydration of the samples was done in rising concentrations of ethanol (30, 50 and 70%). The process was halted at 70% ethanol and the fish were dissected (the livers and gonads were removed). From there, only the liver and gonads where further dehydrated in rising concentrations of ethanol (80, 90, 96, 100%). Clarification was done using Xylene and the graded infiltration of the samples was done using Histosec® (Merck Millipore) in a temperature-controlled oven in 3 concentration phases. The embedding of the samples was done using L-shaped moulds. The embedded samples were sectioned using a microtome and slides were prepared using albumin and left to dry. The sections were then stained using the haematoxylin and eosin staining (H&E) (van Dyk & Pieterse, 2008) process. The histology sections were assessed using a multi-head Olympus light microscope. Digital images were taken using IM50 Image Manager Software (Pixel IT (Pty) Ltd.).

3.3. Marginal to terrestrial vegetation assessment

The riparian vegetation associated with rivers plays an important role in the prevision of buffering impacts of land uses on aquatic systems especially protecting rivers from non-point source pollution (Qiu & Prato, 1998). Dense buffer vegetation cover on slopes (less than 15%) is most effective for water quality functions (Castelle, et al., 1992).

The South African River Health Program (RHP) under the Department of Water Affairs has developed a suite of programs to allow for the calculation of the ecological category for river and riparian areas. Included in the suite of programs is VEGRAI (Riparian Vegetation

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Response Assessment Index). This is part of the river EcoClassification modelling software as developed by (Kleynhans, et al., 2007b) to determine the condition of riparian and terrestrial vegetation. This program is Microsoft Excel driven, and allows for two levels of calculations. For this study, a level 3 assessment was done as it is more rapid and no in- depth knowledge concerning the identification of the plants is required. The program runs on the premises of comparing the study site to a reference site of similar physiological composition and within the ecoregion. The program does not give an indication on the impacts itself, but rather an indication on the extent of the impacts on the riparian areas.

Visual observations and measurements of the riparian vegetation were made including areas where the alteration of the bed and banks of the river has influenced the riparian vegetation. The alterations were also judged to be either anthropogenically induced, or, due to natural processes. This method was applied at each of the eight sampling sites. The program provides results in ranges and allows for results to be allocated a Present Ecological State (PES) category (Table 11).

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4. Chapter 4: Results

4.1. Ecological drivers

For the interpretation of the water quality results, the Department of Water Affairs and Forestry’s South African Water Quality Guidelines Volume 8 Field guide was used (DWAF, 1996). Table 12 presents all the water quality results for the different sites and various surveys (Refer to section 3.1.3). The average pH was not calculated as pH scale is logarithmic.

TABLE 12: THE PHYSICO-CHEMICAL RESULTS FOR THE SAMPLE SURVEYS (BLANK BLOCKS IS

AREAS WHERE NO DATA IS AVAILABLE).

Turbidity Oxygen Nitrate Phosphate Ammonium Sulphate Site name COD (mg/L) pH Conductivity (ms/M) (NTU) (%) (mg/L) (mg/L) (mg/L) (mg/L) Mutale 0 6 21.30 95.7 4.00 4.91 4.77 57 0.32 <25 Mutale 1 9 29.50 4.30 4.67 0.09 51.00 Mean 7.50 25.40 95.70 4.15 4.79 57.00 0.20 Mutshindudi 1 7 29.90 88.9 4.70 4.74 6.86 42 0.11 186.00 Mutshindudi 2 6 17.60 4.25 5.01 0.11 153.00 Mutshindudi 3 23 40.00 4.15 4.67 0.07 >300 Mean 12.00 29.17 88.90 4.37 4.81 42.00 0.09 169.50 September Tshinane 1 7 40.00 3.60 3.52 0.07 53.00 Tshinane 2 7 37.20 91.4 3.95 1.72 7.20 86 0.08 120.00 Tshinane 3 4 14.40 59 3.95 8.11 109 0.08 207.00 Mean 6.00 30.53 75.20 3.83 2.62 97.50 0.07 126.67 Mutale 0 41 8.90 79.8 0.04 7.65 48 0.04 <25 Mutale 1 23 9.30 50.71 0.10 6.73 49 0.12 55.00 Mean 32.15 9.10 65.26 0.07 48.50 0.08 55.00 Mutshindudi 1 33 11.60 0.52 6.59 47 1.59 <25 Mutshindudi 2 7.42 109 Mutshindudi 3 29 10.60 2.37 0.04 137.00 Mean 31.00 11.10 1.44 78.00 0.81 137.00 November Tshinane 1 85.4 7.51 48 Tshinane 2 23 9.80 3.94 7.09 76 0.13 79.00 Tshinane 3 29 10.90 78.2 5.05 7.73 96 0.34 40.50 Mean 26.00 10.35 81.80 4.50 73.33 0.23 59.75 Mutale 0 4 12.60 89.8 0.01 0.29 7.49 61 0.13 36.00 Mutale 1 4 3.40 83.4 0.01 0.44 6.94 60 0.12 30.00 Mean 4.00 8.00 86.60 0.01 0.36 60.50 0.13 33.00 Mutshindudi 1 4 9.40 72.8 0.01 0.90 7.87 43 0.14 <25 Mutshindudi 2 4 17.20 48.9 0.10 0.53 9.22 111 0.13 125.00 Mutshindudi 3 5 4.50 80.7 0.01 0.51 8.07 111 0.14 50.00 April Mean 4.33 10.37 67.47 0.04 0.65 88.33 0.14 87.50 Tshinane 1 1 <4 90 0.01 0.85 7.92 57 0.12 51.00 Tshinane 1 3 8.90 91.1 0.01 0.60 7.45 53 0.14 <25 Tshinane 3 4 4.20 55.7 0.01 0.84 8.41 114 0.19 29.00 Mean 2.67 6.55 78.93 0.01 0.76 74.67 0.15 40.00 Mean for all 13.96 15.62 71.10 1.38 2.22 68.87 0.21 78.71 trips

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4.1.1. Turbidity or Total Suspended Solids

The turbidity of the water samples varied between sampling sites and surveys. The highest turbidity was observed in November at the Mutale 0 sampling site and the lowest at the Tshinane 1 sampling site during April (Figure 15).

FIGURE 15: TURBIDITY READINGS OF THE WATER SAMPLES COLLECTED PER SITE

4.1.2. Chemical Oxygen Demand (COD)

The chemical oxygen demand for September was higher compared to the other surveys. The oxygen percentage for April was the lowest at the Mutale 1 sampling site and the highest at the Mutshindudi 3 sampling site. The oxygen percentage is only given for April to coincide with the fish sampling (Figure 16 and Figure 17).

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FIGURE 16: DISSOLVED OXYGEN LEVELS (MG/L) MEASURED IN SITU DURING THE SEPTEMBER,

NOVEMBER 2011 AND APRIL 2012 SAMPLING SURVEYS. TSHINANE 1 AND MUTSHINDUDI 2

EXCEEDS THE MAXIMUM LEVEL OF MEASURABILITY (40 MG/L).

FIGURE 17: THE DISSOLVED OXYGEN LEVELS (PERCENTAGE) MEASURED IN SITU DURING THE

APRIL SAMPLING SURVEY.

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4.1.3. Nitrates and phosphates

In September, the relationship between the nitrates and phosphates was similar (mean phosphate level 4.17 mg/L and nitrate level of 4.11 mg/L) (Figure 18). The phosphate levels in the Tshinane River dropped below the Nitrate levels. The April results did not indicate the same similarities (mean phosphate level 0.61 mg/L and nitrate level of 0.31 mg/L) (Figure 19).

FIGURE 18: NITRATE AND PHOSPHATE LEVELS MEASURED IN WATER SAMPLES COLLECTED DURING

THE SEPTEMBER 2011 SAMPLING SURVEY

FIGURE 19: NITRATE AND PHOSPHATE LEVELS MEASURED IN WATER SAMPLES COLLECTED DURING

THE APRIL 2012 SAMPLING SURVEY

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4.1.4. pH

The pH in April at the different sites varied, with the Mutshindudi 2 sampling site exceeding a pH of 9. The lowest pH was measured at the Mutale 1 sampling site (Figure 20).

FIGURE 20: THE PH LEVELS MEASURED IN SITU AT THE VARIOUS SAMPLING SITES DURING THE

APRIL 2012 SAMPLING SURVEY. THE TARGET WATER QUALITY RANGE IS ALSO INDICATED.

4.1.5. Ammonium

The ammonium levels detected in April for the Mutale and Mutshindudi rivers were the same and exceeded the TWQR of 7 mg/L. The Tshinane 1 had the lowest ammonium levels and the Tshinane 3 the highest (Figure 21).

FIGURE 21: AMMONIUM LEVELS MEASURED IN WATER SAMPLES COLLECTED FROM THE VARIOUS

SITES DURING THE APRIL 2012 SAMPLING SURVEY. THE TARGET WATER QUALITY RANGE IS ALSO

INDICATED

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4.1.6. Sulphate

The sulphate levels for April varied between the different rivers. The highest level was measured in the Mutshindudi River, and the lowest in the Mutale and Tshinane rivers. Levels were higher in upstream sites compared to downstream sites (Figure 22).

FIGURE 22: SULPHATE LEVELS MEASURED IN WATER SAMPLES COLLECTED FROM THE VARIOUS

SITES DURING THE APRIL 2012 SAMPLING SURVEY.

4.1.7. Total Dissolved Solids (TDS)/ Electrical Conductivity (EC)

The increases in TDS of all the sites were similar, with increases at the lower sampling sites. The Tshinane River increased substantially from 1 NTU to 4 NTU (Figure 23).

FIGURE 23: TDS LEVELS MEASURED IN SITU AT THE VARIOUS SITES DURING THE APRIL 2012

SAMPLING SURVEY.

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4.2. Fish population response assessment

Table 13 presents the list of observed fish at the different sampling sites for the April 2012 survey. Chiloglanis pretoriae was the only species present at all sampling sites in higher abundance compared to the other species. Of the 24 expected species (FROC list) only 7 was not collected. The Mutale River had the highest species diversity (11 species) compared to only 7 species collected in the Mutshindudi and Tshinane rivers.

TABLE 13: THE OBSERVED SPECIES LIST FOR ALL THE SITES WITH ABUNDANCE RATINGS

Mutale Mutale Tshinane Tshinane Tshinane Mutshindudi Mutshindudi Mutshindud FROC LIST 0 1 1 2 3 1 2 i 3 AMOS ANGUILLA MOSSAMBICA (PETERS 1852) 1 AURA AMPHILIUS URANOSCOPUS (PFEFFER, 1889) 1 1 1 BEUT BARBUS EUTAENIA ( BOULENGER, 1904) 1 BLIN BARBUS LINEOMACULATUS (BOULENGER, 1903) 3 2 BMAR LABEOBARBUS MAREQUENSIS (SMITH, 1841) 2 2 1 2 BNEE BARBUS NEEFI (GREENWOOD, 1962) 2 2 BPAU BARBUS PALUDINOSUS ( PETERS, 1852) BRAD BARBUS RADIATUS (PETERS, 1853) BTRI BARBUS TRIMACULATUS (PETERS, 1852) 2 BUNI BARBUS UNITAENIATUS (GÜNTHER, 1866) 1 1 2 1 BVIV BARBUS VIVIPARUS ( WEBER, 1897) 2 1 CGAR CLARIAS GARIEPINUS (BURCHELL, 1822) 1 CPRE CHILOGLANIS PRETORIAE (VAN DER HORST, 1931) 3 3 3 2 3 2 2 2 LCYL LABEO CYLINDRICUS (PETERS, 1852) LMOL LABEO MOLYBDINUS ( DU PLESSIS, 1963) LROS LABEO ROSAE (STEINDACHNER, 1894) (LABEO ALTEVILIS) 1 MACU MICRALESTES ACUTIDENS (PETERS, 1852) MMAC MARCUSENIUS MACROLEPIDOTUS (PETERS, 1852) 1 MBRE MESOBOLA BREVIANALIS (BOULENGER, 1908) OPER OPSARIDIUM PERINGUEYI (GILCHRIST & THOMPSON, 1913) 2 2 OMOS OREOCHROMIS MOSSAMBICUS (PETERS, 1852) 1 PCAT PETROCEPHALUS WESSELSI (KRAMER & VAN DER BANK, 2000) 1 TREN TILAPIA RENDALLI (BOULENGER, 1896) TSPA TILAPIA SPARRMANII (SMITH, 1840) 2 2 1

Using the observed and expected lists, the EcoStatus (in percentage) of each site was calculated (Figure 24). The Mutale River’s FRAI result was the highest of the three rivers and the Tshinane, site 3, the lowest. Both the Mutshindudi and Tshinane rivers showed a lower FRAI value for the downstream sampling sites compared to the upstream sampling sites. The middle site of the Tshinane River had a higher FRAI value as compared to the middle site of the Mutshindudi River.

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FIGURE 24: THE COMBINED FRAI RESULTS CALCULATED FOR THE VARIOUS SAMPLING SITES OF

THE THREE SELECTED RIVERS

4.3. Fish health

4.3.1. Necropsy

No macroscopic abnormalities were identified for any of the sampled fish (mean total length = 54.5 mm; mean body mass = 1.98 g). Due to the small size of some of the fish, an accurate macroscopic identification of their livers and gonads could not always be done and subsequently samples were only available for light microscopy analysis for 31 fish. The sex ratio of the sampled population was 13% male 18% female. The mean condition factor of the male specimens was higher compared to the female specimens (Table 14 and Figure 25). No differences were identified comparing fish between the sampling sites and thus combined results are presented for the total sample group.

TABLE 14: THE MEAN AND STANDARD DEVIATION (±SD) VALUES OF THE CONDITION FACTORS OF

THE SAMPLED CHILOGLANIS PRETORIAE SPECIMENS N CF Range CF Mean ±SD Male 13 0.76-1.26 1.09 0.15 Female 18 1.04-1.29 0.99 0.14

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FIGURE 25: THE CONDITION FACTOR VALUES CALCULATED FOR THE MALE AND FEMALE

CHILOGLANIS PRETORIAE SPECIMENS

4.3.2. Histopathology

The qualitative histopathological analysis of the liver and gonad tissue did not show any abnormalities across all the sampling sites. The liver samples showed typical fish liver histological structure with hepatocytes, hepatic cords, bile ducts and intra hepatic pancreatic tissue clearly distinguishable. Some mild vacuolation of hepatocytes were identified (Figure 26). The gonadal tissue also showed no microscopic abnormalities. The ovaries of all females were developing in nature with only primary oocytes visible (Figure 27). However, the males were all found to be mature with spermatozoa being the predominant stage of spermatogenesis present (Figure 28).

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Intrahepatic pancreatic tissue

Central vein

Liver parenchyma

Portal vein

FIGURE 26: A LOW MAGNIFICATION (10X) MICROGRAPH SHOWING TYPICAL LIVER PARENCHYMA OF

C. PRETORIAE WITH INTRAHEPATIC PANCREATIC TISSUE AND VASCULATURE CLEARLY VISIBLE.

FIGURE 27: PRIMARY OOCYTES IN THE PERI-NUCLEAR STAGE OF DEVELOPMENT IN A FEMALE

SPECIMEN

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FIGURE 28: SPERMATOZOA (BLUE) VISIBLE IN THE SEMINIFEROUS LOBULES OF A MALE SPECIMEN

4.4. VEGRAI results

The Mutale River had the highest average VEGRAI score (mean of 75.8) with a lower score at the downstream site. The Mutshindudi River had a higher score for the upstream site, with the lowest score for the site in the middle reaches and an increase in score value, or better condition, at the downstream sampling site (63.4%). The Tshinane River had the lowest score for the upstream sampling site and a higher score for the downstream site. The river had a 62.3% average VEGRAI score.

FIGURE 29: LEVEL 3 VEGRAI RESULTS CALCULATED FOR THE VARIOUS SITES OF THE THREE

SELECTED RIVERS A.J. Fourie Page 53

4.5. Comparisons between the FRAI and VEGRAI results

The overall comparison between the VEGRAI and FRAI EcoCondition results showed some similarities with the differences between the two results not exceeding 20% (Table 15).

TABLE 15: THE COMBINED FRAI AND VEGRAI ECOCONDITION PERCENTAGE AND CLASSES

SCORES FOR THE THREE RIVERS FRAI VEGRAI River Site name FRAI EcoCondition VEGRAI EcoCondition Class Class Mutale 0 57.7 D 77 C Mutale Mutale 1 69.4 C 74.6 C Mutshindudi 1 62.9 C 71.7 C Mutshindudi Mutshindudi 2 49.4 D 56.7 D Mutshindudi 3 57.7 C 63.4 C Tshinane 1 45.8 D 60.5 C Tshinane Tshinane 2 51.3 D 58.5 D Tshinane 3 35.4 D 67.7 C

4.5.1. Mutshindudi River

The comparison between the VEGRAI and FRAI results for the Mutshindudi River show similarities. The mean VEGRAI score was 63.9 % and the mean FRAI score 56.6 %. Both scores showed a lower score for the sampling site in the middle reaches of the river (MUT 2) (Figure 30).

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FIGURE 30: THE FRAI AND VEGRAI RESULTS CALCULATED FOR THE SAMPLING SITES OF THE

MUTSHINDUDI RIVER

4.5.2. Mutale River

The FRAI and VEGRAI scores of the Mutale River did not show any similarity between the scores of the same sites. This is due to the VEGRAI score decreasing to the MU 1 sampling site. The FRAI score increased from 57.7 to 69.4 (Figure 31).

FIGURE 31: THE FRAI AND VEGRAI RESULTS CALCULATED FOR THE SAMPLING SITES OF THE

MUTALE RIVER

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4.5.3. Tshinane River

The FRAI and VEGRAI scores of the Tshinane River showed a negative mirror image on the graph. The FRAI score decreased and the VEGRAI score increased towards the downstream site. The FRAI score increased to the highest score at the T2 sampling site, the site that also had the lowest VEGRAI score (Figure 32).

FIGURE 32: THE FRAI AND VEGRAI RESULTS CALCULATED FOR THE SAMPLING SITES OF THE

TSHINANE RIVER

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5. Chapter 5: Discussion

5.1. Ecological Drivers

5.1.1. Turbidity

Most river system’s upper reaches and middle zones area expected to have a high turbidity as a result of the abiotic processes (high water speed and increased channel size) of the systems. No metal analysis results (part of the larger study) are available as yet that could indicate if the turbidity is caused by either dissolved organic or inorganic matter or suspended organic or inorganic matter (Dallas & Day, 2004). All the samples per river indicate an increase in NTU’s between the lower and upper sample sites.

The turbidity of the rivers was much higher for all the rivers during November 2011 compared to the other sampling surveys. Sampling sites such as the Mutshindudi 3 indicated extensive increases in turbidity compared to the other sampling sites. It is difficult to assign the increase turbidity of the Mutshindudi 3 site to a specific cause. It can be noted that the Mutshindudi River leading up to the sampling site is extensively cultivated through subsistence farming and a plot system is used up to the edge of the river with only a small buffer zone left. This is possibly due to sediments being washed from the catchment into the systems after rainfall events. The Mutale River’s upper sampling site had the highest amount of suspended solids for the November survey. During September the Mutshindudi River’s downstream sample site had the highest TSS. This is possibly due to the use of the soils from the river banks at this site for brick making by local residents.

5.1.2. Chemical oxygen demand (COD)

The oxygen percentage of the study sites were within the acceptable range (Dallas & Day, 2004) except for the middle Mutshindudi sampling site. The low level of dissolved oxygen at this site could be attributed to erroneous sampling or to environmental impacts. The sampling site is located just below a bridge culvert structure. The system is highly impounded due to the bridge structure and this could reduce the oxygen concentration in the system. This is due to the deeper water column, reducing the agitation and mixing of the water (for example over riffles) as well as the high respiration of oxygen by the systems fauna and flora in the impounded area. Clear differences between the seasonal results indicate the oxygen demand and production varies with season. Higher water temperature associated with warmer seasons could also reduce the oxygen concentration in the water.

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Dallas & Day (2004) states that acute exposure to low oxygen concentrations (below 80%) will lead to physiological and behavioural stress in aquatic organisms. From the result, most of the site’s oxygen percentage drops below 80%. The Tshinane 3 and Mutshindudi 2 sites are of concern. The Tshinane 3 site has a chronically low rate of oxygenation in the system. This could possibly be as a result of impoundment of the site before it enters the study site.

5.1.3. Nitrates and Phosphates

The September phosphate levels were near, and in some cases in excess of 5 mg/L which indicates oligotrophic conditions (DWAF, 1996). A concentration of phosphorus of less than 5 mg/L is considered to be sufficiently low to reduce the likelihood of algal and other plant growth (Dallas & Day, 2004). Important to note was the differences between the September 2011 and April 2012 sample sets. The mean levels detected during April and September was vastly different indicating changes in the nitrate and phosphate loadings of the system. This is indicative of sampling before and after the rainy season and could be attributed to the application of fertilizers (usually phosphates and nitrates) for the planting season. The results from April could be as a result of photosynthetic production in the systems being high due to the respirational processes using nitrates for the photosynthesis process. The uptake of nitrate and phosphate by aquatic and marginal flora could also be the cause for the low nitrate and phosphate results observed at the Tshinane 2 (T2) sample site during September 2011 and the nitrate results for April 2012.

5.1.4. pH

Only the Mutshindudi 2 site exceeded the maximum pH of 9 (9.22) (DWAF, 1996). The pH levels were generally higher in April possibly due to rainfall events increasing the pH due to increased sediment loads in the system. The low pH at the Mutale 0 site can possibly be attributed to probe error or other elemental aspects in the water (not tested for) reducing the pH.

5.1.5. Total Dissolved Solids (TDS)/ Electronic conductivity (EC)

The TDS was very high and exceeded the maximum value by almost 200 ppm (DWAF, 1996). The EC was very close to the TWQR as set out by DWA (DWAF, 1996). The fact that both the upper and lower sampling sites had high TDS levels shows the water entering this river is already impacted on and the high scores is not due to the activities at the actual

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sampling sites. It is interesting to note that the upstream sampling sites indicated a decrease in the TDS from September to April. The downstream sampling sites all indicated an increase in TDS. This could be attributed to the domestic use of the river systems. The sampling sites are located in areas where the local population wash their clothes and use the rivers extensively. This impacts on the stability of the banks of the rivers as well as on the sediments found within the river as people wade into the river. Water is abstracted from the Mutshindudi and Tshinane rivers for irrigation of agricultural activities. Increases in TDS are a common effect of irrigation as salts are leached from the soil and up in the rivers systems (Davies & Day, 1998). The seasonal impact attributed to rainfall influencing the TDS results. No parameters that could provide information concerning ion loading was tested for.

5.2. Fish Response Assessment Index (FRAI)

The fish response assessment index results indicated that in all three river systems, the fish population assemblage differed between the upstream and downstream sampling sites. It was expected that a lower FRAI would be seen in the downstream sampling sites across the three rivers. This is as the impacts to the rivers increase towards the downstream reaches. Interesting to note was that the Mutale middle sampling site showed an increase in population assemblage in comparison with the upper sampling site. This could be attributed to the following aspects:  The impact from anthropogenic activities was less at the middle sampling site;  The water column was deeper; increasing the fish habitat suitability of the site,  The presence of unique species at this sampling site;

The Tshinane downstream sampling site had the lowest FRAI score. This could be due to the study site being located below a bridge. The selected sampling method was not conjunctive to the habitat types available (mostly slow deep). The utilisation of the site for fishing was of concern and could also have had an impact. The Mutshindudi River’s FRAI score drastically decreased at the middle sampling site, possibly due to the site being heavily utilised for clothes washing. A water purification plant released backwash (containing chlorine, sediments and flocculent) (Dallas & Day, 2004) into this site.

5.3. Vegetation Response Assessment Index (VEGRAI)

The Mutale River results indicated some change in the riparian vegetation composition. This is of concern as the distance between the sampling sites are small (±4 km). This infers the vegetation score will decrease as distance increases (future study needed). The Mutshindudi A.J. Fourie Page 59

River vegetation composition at Mutale 0 was calculated as 71.7 where after the Mutale 1 dropped to 56.7 %. This was possibly due to the extensive agriculture up to the edge of the riparian areas with little or no buffer zone present. The Tshinane River’s VEGRAI score was low due to the extensive cultivation of the riparian area for agriculture. The area was also almost completely transformed by tea plantations. The scores increased at the T3 site due to the lack of recent agriculture activity possibly due to the steep banks of the river precluding it from cultivation. The Mutshindudi River’s VEGRAI results were more stable with a slight decrease at the middle sampling site due to extensive agriculture and clearing of vegetation for access to the river. After the middle sampling site, the system restores to a higher score overall at the downstream study site.

5.4. Fish Response Assessment Index (FRAI) and Vegetation Response Assessment Index (VEGRAI)

The results showed that agriculture most likely have a negative impact on the river systems. The EcoCondition Classes of the study sites showed no great variance within the rivers ranging between C-D (moderately to largely modified) (Table 15). Only the Mutshindudi 2 and Tshinane 2 sampling sites had the same class for both VEGRAI and FRAI. It was found that the heavy utilisation of the river for domestic use (washing of clothes, water abstraction and bathing) coupled with the recreational use (swimming) could be attributed to coinciding with the impact of agriculture on the systems. This is as the areas to the rivers were highly frequented and erosion occurred leading down to the water. The local population also enters the water and wade through the water dislodging sediments and altering the habitat composition of the benthic strata. The washing of clothes is also done with commercial detergents altering the physical and chemical properties of the water. The fish population structure could also be impacted by the heavy fishing for human consumption. Many interviews with the local inhabitants at the communities surrounding the rivers indicated their desire for a sustainable fish population for regular harvesting (personal communication 2011). Highly desirable edible species of fish regularly targeted by the communities include Sharptooth catfish, Clarias gariepinus (Burchell, 1822), African longfin eel, Anguilla mossambica (Peters 1852) and even Bulldog fish, Marcusenius macrolepidotus (Peters 1852). In a recent study funded by the WRC, Fouche, et al. (2013) investigated the suitability of establishing the fishing potential of the nearby Nandoni Dam. They noted a decrease in catch effort due to fishing pressure by the local communities.

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The fish population assessment in the form of the FRAI assessment did not indicate a clear decrease in the fish population due to the impact of agriculture alone. Care was taken to ensure the sampling sites throughout the rivers were similar (in terms of SASS 5 sampling site requirements (for the purpose of the larger study) (Dickens & Graham, 2002) but the impact of river use (including over fishing) rather than agriculture is a possible cause of the decreased FRAI results at the lower study sites. The marginal vegetation assessment in the form of the VEGRAI assessment of the sites did indicate a pattern between the FRAI and VEGRAI except for the T3 sampling site. This is due to a high VEGRAI score in relation to the other VEGRAI results for the river system. Observer bias cannot be ruled out for the high T3 sampling site score.

5.5. Fish necropsy and histology

The absence of abnormalities in the liver and gonads of C. pretoriae from the sampling sites indicated that this species inhabiting these systems were in a good, healthy condition, in terms of the parameters assessed. Bornman, et al. (2010) found that fish from the Luvuvhu River had histological abnormalities, some of which were suspected to be associated with exposure to EDC’s. These included intersex in O. mossambicus (Barnhoorn, et al., 2010). However, no micrsocopic gonadal abnormalilties were identified in C. pretoriae during this study. As O. mossambicus and C. gariepinus were not sampled for a fish health assessment as part of the current study, the health status of other species from the study area is still unknown and needs further investigation. The difference in condition factor of the males versus the females could be attributed to the females not being sexually mature at the time of sampling while all the males were identified to be sexually mature.

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6. Chapter 6: Conclusion and recommendations

With increased pressure from communities requiring natural resources, rivers and the sustainability of aquatic ecosystems will become more relevant as the need for water increases in South Africa (Funke, et al., 2011). Most of the ecological drivers analysed in this study were within the normal range generally accepted for aquatic ecosystems. The sedimentation in the systems was found to be high, and can most likely be attributed to the land use within the area.

As was expected, the Mutale River scored the highest in terms of the FRAI assessment. This is probably due to the sacred nature, as is the belief by the local people, of the main water source of the river, the Lake Fundudzi. Of concern is the sedimentation loading in the Mutshindudi River. The movement of alluvial materials were expected to be high in the Mutale River (SANBI, 2012), but the loads in the river exceeded the Mushindudi River. The fish population’s assemblage in situ is not the same compared to historic population (Fouche, 2009). This could be attributed to overutilisation of fish and the river for natural resources. Only smaller fish was found in the systems, as almost all the larger fish have probably been removed for human consumption. This is of concern as breeding stocks are being reduced and the fecundity of the populations is threatened.

The Tshinane River is highly impacted and most of the river had been altered through the placement of weirs and bridge structures, impounding the system. The extensive use of the river for subsistence and commercial farming (tea plantations) was also altering the river. The removal of the buffer zone between the terrestrial and aquatic systems also alters the river habitat detrimentally and is of concern. The fish populations in the Tshinane River improved towards the downstream reaches. As the river is a relatively short river, the impacts on the river are most likely amplified into the Mutshindudi River.

The assemblages of different fish species in the population were high in comparison with assemblages from other Ecoregions in South Africa (personal observation). The use of agrochemicals and the impact thereof on aquatic organisms is well documented (Davies & Day, 1998, Dallas & Day, 2004, Fouche, et al., 2013, Bornman, et al., 2010 & CSIR, 2010) but during this study the fish health assessment of C. pretoriea did not indicate any abnormalities associated with toxicants, and in this case, most likely agrochemicals. This does not, however, indicate the absence of the chemicals in the systems. Although a quantitative association between the fish population response and the impact of agriculture

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was not investigated as part of this study (this would require comprehensive statistical analysis of multiple and seasonal sampling efforts). It was clear through observations on site that land use activities by local communities, especially subsistence farming and fishing, are altering the habitat and fish population structure within these systems, thus supporting part of the hypothesis of this study that anthropogenic activities most likely have a negative impact on the fish population structure of the Mutale, Mutshindudi and Tshinane rivers. However, no negative health effects were identified in the sampled fish and that part of the hypothesis is therefore rejected. Further, more indepth studies are therefore recommended. Aspects that need investigation include:

 A full assertation to the extent of agricultural practices in the area based on a GIS format needs to be done;

 An investigation into the impact of the Tshinane River on the Mutshindudi River after the confluence needs to be done;

 Further assessment regarding the levels and concentrations of pesticides use in the catchment and the impact on the aquatic ecosystem;

 The impact of the domestic use of the rivers and the effect extensive harvesting has on the fish populations. Further studies into the potential for aquaculture in the areas to coincide with the findings of Fouche, et al. (2013);

 Investigations into the sources and movement of alluvial material in the Mutale, Mutshindudi and Tshinane Rivers.

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7. Chapter 7: References

Barnhoorn, I. E. J., van Dyk, J. C., Pieterse, G. M. & Bornman, M. S., 2010. Intersex in feral indigenous freshwater Oreochromis mossambicus, from various parts of the Luvuvhu River, Limpopo Province, South Africa. Ecotoxicology and Environmental Safety, Volume 73, pp. 1537-1542. Basson, M. S. & Rossouw, J. D., 2003. Luvuvhu and Letaba water management area: overview of water resources availability and utilisation, Pretoria: Department of Water Affairs. Biggs, H. C., Rogers, K. H. & du Toit, J. T., 2003. The Kruger Experience: Ecology and management of Savanna Heterogeneity. 1st ed. Washington: Island Press. Bornman, M. S. Barnhoorn, I E J; Genthe , B; van Vuren, J H; Pieterse, G M; Aneck-Hahn, N H; van Dyk, J C; Marchand, M J; van Zijl, M C; Brink, K A; Patrick, S M; Bremner, K J; & de Jager, C., 2010. DDT for Malaria control: Effects in indicators and health risk, Pretoria: Water Research Commission, Report No. 1674/1/09 Brewer, R., 1993. The Science of Ecology. 2nd ed. Michigan: Saunders College Publishing. Carlander, K., 1969. Handbook of freshwater fishery biology. Iowa: Iowa State University Press. Castelle, A. J., Conolly, M., Emers, E. D., Metz, E. D., Meyer, S.; Witter, M.; Mauermann, S., Erickson, T. & Cooke, S. S., 1992. Wetland Buffers: Use and Effectiveness, Washington: Shore lands and Coastal Zone management program. Council for Scientific and Industrial Research (CSIR), 2010. A CSIR perspective on water in South Africa 2010, Pretoria: Council for Scientific and Industrial Research. Dallas, H. F. & Day, J. A., 2004. Effect of water quality variables on aquatic ecosystems, TT 244-04 Pretoria: Water Research Commission. Davies, B. & Day, J., 1998. Vanishing Waters. Cape Town: University of Cape Town Press. Dickens, C. W. S. & Graham, P. M., 2002. The South African Scoring System (SASS) Version 5 Rapid bioassessment method for rivers. African Journal of Aquatic Science, Volume 27, pp. 1-10. Department of Water Affairs and Forestry (DWAF), 1996. South African Water Quality Guidelines Volume 7: Aquatic Ecosystems, Pretoria: DWAF. Department of Water Affairs and Forestry (DWAF), 2001. River Health Programme. [Online] Available at: http://www.dwa.gov.za/iwqs/rhp/state_of_rivers/letluv_01_toc.html [Accessed 14 09 2013]. Department of Water Affairs (DWA), 2004. Internal Strategic perspective: Luvuvhu/ Letaba water management area, Pretoria: Department of Water Affairs.

A.J. Fourie Page 64

Department of Water Affairs (DWA), 2012. RQS Google Earth Layer Data- Hydrology and Catchment .kml. [Online] Available at: www.dwaf.gov.za/iwqs/ [Accessed 12 October 2013]. Department of Water Affairs (DWA), 2013 [Online] Available at: http://www.dwaf.gov.za/iwqs/rhp/reports/report1/chapter5.pdf [Accessed 20 05 2013]. Electronic Water Institute of South Africa, 2013. eWISA. [Online] Available at: http://www.ewisa.co.za/eWISAWaterworks/misc/MunicipalContacts/defaultLIM_V embe.htm [Accessed 5 October 2013]. Fouche, P. S. O., 2009. Aspects of the ecology and biology of the Lowveld largescale yellowfish (Labeobarbus marequensis, Smith, 1843) in the Luvuvhu River, Limpopo River System, South Africa, s.l.: s.n. Fouche, P. S. O., Vlok, W., Roos, J. C., Luus-Powell, W., & Jooste, A., 2013. Establishing the fishery potential of Lake Nandoni in the Luvuvhu River, Limpopo Province, Pretoria: Water Research Commission Research Report No.1925/1/12. Funke, N., Gooch, G., Nortje, K., Steyn, M. & Rieu-Clarke, A., 2011. Governing Biodiversity conservation and sustainable livelihoods in the Mutale River- an analysis of interplay between laws, policies, institutions and actors. Seventh Framework Program (FP7/2007-2013). Gaiger, I. G., Szubarga, A., Todd, C., van der Waal, T., Weisser, P., van Ree, T., Venter, C., Wood, C., & Fouche, P. S. O., 2001. A Socio-biological study of the aquatic resources and their utilisation in an underdeveloped rural region, the Mutshindudi River catchment, Pretoria: Water Research Commission. Harding, J. S., Young, R G., Hayes, J. W., Shearer, K. A., & Stark, J. D., 1999. Changes in agricultural intensity and river health along a river continuum. Freshwater Biology, Volume 42, pp. 345-357. Harding, W. R.; & Taylor, J. C., 2011. The South African diatom index (SADI) – A preliminary index for indicating water quality in rivers and streams in Southern Africa. Water Research Commission, report no 1707/1/11 Pretoria. Humason, G. L., 1979. Animal tissue techniques 4th edition. W. H. Freeman, New York. Kleynhans, C., 1999. The development of a fish index to assess the biological integrity of South African rivers. WaterSA, 25(3), pp. 265-278. Kleynhans, C. J., Thirion, C., & Moolman, J., 2005. A Level 1 river Ecoregion classification System for South Africa, Lesotho and Swaziland. Department of Water Affairs and Forestry, Pretoria, Resource Quality Services, South Africa, Report no. N/0000/00/REQ0104.

A.J. Fourie Page 65

Kleynhans, C. J., Louw, M. D., & Moolman, J., 2007a. Reference frequency of occurrence of fish species in South Africa. Water Research Commission, Pretoria., Issue TT331/08. Kleynhans, C., MacKenzie, J., & Louw, M., 2007b. Module F: Riparian Vegetation Response Assessment Index in River EcoClassification: Manual for EcoStatus Determination (version 2)., WRC Report No. TT 333/08 ed. s.l. Water Research Commission. Kleynhans, C. J., 2007c. Module D: Fish Response Assessment Index in River EcoClassification: Manual for EcoStatus Determination (version 2). Pretoria: Water Research Commission, Issue WRC Report No. TT330/08. Lorentz, S., Kollongei, N., Snyman, S. R., Berry, W., Jackson, K., Ngaleka; J. J., Pretorius; D., Clark; S., Thornton-Dibb, J. J., le Roux, T., & Germishuyse, A. H. M., 2013. Modelling nutrient and sediment dynamics at the catchment scale, Pretoria: Water Research Commission Research Report No.1516/3/12. Maloney, K. O., & Weller, D. E., 2011. Anthropogenic disturbance and streams: land use and land-use change affect stream ecosystems via multiple pathways. Freshwater Biology, Volume 56, pp. 611-626. Marchand, M. J., Pieterse, G. M., & Barnhoorn, I. E. J., 2008. Preliminary results on sperm motility and testicular histology of two feral species, Oreochromis mossambicus and Clarias gariepinus, from a currently DDT-sprayed area, South Africa. Journal of applied Ichthyology, Volume 24, pp. 423-429. Matlala, M. J., Bills, I. R., Kleynhans, C. J., & Bloomer, P., 2010. Systematics and phylogeography of suckermouth species (Chiloglanis) with emphasis on the Limpopo River system and implications for water management practices, Pretoria: Water Research Commission Research Report No. KV 235-10. Matthews, W. J., & Heins, D. C., 1987. Community and evolutionary ecology of North American stream fishes. 1 st ed. Washington: Washington University. McHugh, K. J., Smit, N. J., Van Vuren, J. H. J., Van Dyk, J. C., Bervoets, L., Covaci, A., & Wepener, V., 2011. A histology-based fish health assessment of the tigerfish, Hydrocynus vittatus from a DDT-affected area. Physics and Chemistry of the Earth, Volume 36, pp. 895-904. McHugh, K. J., Smit, N. J., van Vuuren, J. H. J., & van Dyk, J. C., 2013. Health of sharptooth catfish Clarias gariepinus in Pongolapoort Dam, South Africa: a comprehensive study. African Journal of Aquatic Science, 38(2), pp. 211-219.

A.J. Fourie Page 66

Mucina, L. & Rutherford, M. C., 2006. The vegetation of South Africa, Lesotho and Swaziland. Strelitzia 19. ed. Pretoria: South African National Biodiversity Institute. Nel, J. L., Strydom, W. F., Petersen, C., Hill, L., Roux, D. J., Nienaber, S., van Deventer, H., Swartz, E., & Smith-Adao, L. B., 2011. Atlas of Freshwater Ecosystem Priority Areas in South Africa, Pretoria: Water Research Commission TT500/11. Obi, C. L., Potgieter, N., Bessong, P. O. & Matsaung, G., 2002. Assessment of the microbial quality of river water sources in rural Venda communities in South Africa. Water SA, 28(3), pp. 287-292. Ongley, E. D., 1996. Control of water pollution from agriculture. 55 ed. s.l.: Food and Agriculture Organization of the United Nations. Qiu, Z. & Prato, T., 1998. Economic evaluation of riparian buffers in an agricultural watershed. Journal of the American Water Resources Association, 34(4). Rall, V. E. Engelbrecht, J. S., Musgrave, H., Williams, D. B. G., & Simelane, R., 2010. Bioassays using suitable indigenous freshwater fish species, Pretoria: Water Research Commission Research Report No.1313-2-10. Rickert, D., 1993. Water quality assessment to determine the nature and extent of water pollution by agriculture and related activities. Prevention of Water Pollution by Agriculture and Related Activities. Proceedings of the Food and Agriculture Organisation (FAO): Expert Consultation. Santiago, Chile South African National Biodiversity Institute (SANBI), 2012. Rehabilitation plan for the Mutale, A91G, A92A and A92B Limpopo. Pretoria: South African National Biodiversity Institute. South African National Biodiversity Institute (SANBI), 2013. BGIS SANBI. [Online] Available at: www.bgis.sanbi.org [Accessed 5 October 2013]. Skelton, P., 2001. Freshwater fishes of Southern Africa. 2nd ed. Cape Town: Struik Publishers. Smit, L., du Preeze, H. H., & Steyn, G. J., 1998. Influence of natural silt on the survival of Oreochromis mossambicus yolk sac larvae. Koedoe- African Protected Area Conservation and Science, 41(1), pp. 57-62. Thrash, I., & Derry, J. F., 1999. The nature and modelling of Piosphere: a review. Koedoe- African Protected Area Conservation and Science, 42(2), pp. 73-94. Van der Waal, B. C., 1997. Fundudzi, a unique, sacred and unknown South African lake. Southern African Journal of Aquatic Sciences., 23(1), pp. 42-55. Van der Waal, B. C. W., 2010. Fish as a resource in a rural river catchment in Northern Province, South Africa. African Journal of Aquatic Science, 25(1), pp. 56-70.

A.J. Fourie Page 67

Van Dyk, J. C., Marchand, M. J., Smit, N. J., & Pieterse, G. M., 2009. A histology-based fish health assessment of four commercially and ecologically important species from the Okavango Delta panhandle, Botswana. African Journal of Aquatic Science, 34(3), pp. 273-282. Van Dyk, J.C., Cochrane, M. J., & Wagenaar, G. M., 2012. Liver histopathology of the Sharptooth catfish (Clarias gariepinus) as a biomarker of aquatic pollution. Chemosphere, 87(4): 301–311. Van Dyk, J. C., & Pieterse G. M., 2008. A histo-morphological study of the testis of the Sharptooth catfish (Clarias gariepinus) as reference for future toxicological assessments. Journal of Applied Ichtyology, 24 (4): 415-422 Van Vuuren, L., 2007. Diatoms- A new dimension to water monitoring. WaterWheel, May/June, pp. 12-14. Working on Wetlands, 2013. Working on wetlands. [Online] Available at: http://wetlands.sanbi.org/project_details.php?id=201 [Accessed 26 05 2013]. Water Research Commission, 2013. Study expands SA Knowledge of agricultural non-point source pollution. WaterWheel, March/April, pp. 18-19. Zheng, B., Li, L. & Liu, L., 2010. Biomonitoring and bioindicators used for river ecosystems: Definitions, approaches and trends. Procedia Environmental Sciences volume 2 pg 1510-1524: International Society for Environmental Information Sciences 2010 Annual Conference (ISEIS).

A.J. Fourie Page 68