field studies - ujcontent.uj.ac.za

Chapter 5 – Field Studies

74

CHAPTER 5

FIELD STUDIES

5.1 Introduction

To protect biological recourses depends on the ability to identify and predict the

effects of human actions on these biological systems and to distinguish between

natural and human-induced variation in biological conditions (Karr and Chu,

1999a). Substances that can be potentially toxic, enter the aquatic environment

from a number of different sources. At direct point sources, discharges enter a

water source at a single point, for example discharges of domestic sewages and

industrial effluents. Non-point or diffuse sources where toxic substances enter

surface and underground water through runoff from urban and industrial areas,

leachates from domestic and solid waste disposal sites and mining operations.

Spillage and the release of agricultural chemicals are classified as unquantified

point source discharges; there is little or no data available due to their irregular

discharges (Roux, 1994; Sutton and Oliveira, 1987; Heath and Claassen, 1999).

For the evaluation of the biomarkers under field conditions, a reference site (Rust

de Winter Dam) and two polluted sites, Loskop Dam and Hartebeespoort Dam,

were chosen. During biological assessment, a standard is needed to evaluate

the conditions at one or more sites of interest, against. This standard/reference

condition provides the baseline for site evaluation (Karr and Chu, 1999b).

Reference conditions describe the characteristics of water resources that are

least impaired by human activities. When there are no undisturbed sites, “least

impacted sites” or “best attainable conditions” may be used as reference (Roux,

1994).


75

5.2 Reference site

5.2.1 Rust de Winter Dam

The Elands River is the most westerly tributary of the Olifants River and rises a

few kilometers south of Rayton neat Kaztan, north of the N4-highway. It drains

northwards through hilly country (± 60 km) to the Rust de Winter Dam. From this

point it flows in a westerly direction to the south of the Springbok Flats to its

confluence with the Olifants River, downstream of Marble Hall (Figure 5.3)

(Theron, Prinsloo, Grimsehl & Pullen Inc., 1991a).

The Rust de Winter Dam is the uppermost major dam in the Elands River and is

surrounded by a nature reserve (Figure 5.2). The dam has a catchment area of 1

147 km2 and a total storage capacity of 28.1 x 106 m3. The dam was completed

in 1933 to provide irrigation water to vegetable farms below the dam, but has in

recent years become a popular recreational area for fishing and boating (Figure

5.1) (Butty et al., 1980; Theron, Prinsloo, Grimsehl & Pullen Inc., 1991a).

Rainfall occurs predominantly in the summer months usually between October

and March, with January usually experiencing the heaviest rainfall. There is no

development that can have a major impact on the dam. Irrigation is the dominant

water user from the dam and agriculture is the major land use in the area.

Agricultural activity is restricted to an area close to Zonderwater and to farms

near the impoundment itself. The greatest portion of the catchment is

undeveloped bushveld, which is utilised for cattle ranching (Butty et al., 1980;

Theron, Prinsloo, Grimsehl & Pullen Inc., 1991a). Taking the last statement into

consideration, the RDW dam was thus the best choice as a reference site since it

contains relative little pollution.


76

Figure 5.1 : The Rust de Winter Dam.


77

Figure 5.2 : A map showing the catchment areas, rivers and

urban/industrial developments around the Rust de Winter Dam (A) and

Loskop Dam (B).

(A)

(B)


78

Figure 5.3 : The Rust de Winter Catchment (Buttey et al., 1980).


79

5.3 Polluted sites

5.3.1 Loskop Dam

The Upper Olifants River catchment comprises the drainage areas of the Olifants

River, Klein Olifants River and Wilge River, with tributaries down to the Loskop

Dam (Figure 5.2). The headwaters of these rivers are located along the Highveld

Ridge in the Secunda-Bethal areas and the rivers then flow in a northerly

direction towards the Loskop Dam. The natural rivers and streams have been

extensively dammed with the result that the stream flow is now highly regulated.

The major impoundments upstream of the Loskop Dam include the Witbank

Dam, Middleburg Dam, Bronkhorstspruit Dam and Premiere Mine Dam (BKS

(Pty) Ltd., 1998). In 1990, the population of the Olifants River catchment was

±2.5 x 106. Two thirds of this population lives in rural or semi-urban (settlements)

conditions. Middelburg and Witbank are the largest urban concentrations (Heath

and Claassen, 1999).

Over the past few years, the Olifants River has been systematically impaired

because of an increase in agricultural and mining activities, industrial

development and urbanisation. This river system is often described as one of the

most polluted systems in South Africa and is known as “The Battered River” (Van

Vuren et al., 1999). Along the Olifants River there are intensive and subsistence

agriculture as well as numerous point and diffuse sources of industrial pollution

(Heath and Claassen, 1999).

Loskop Dam was built in 1939, 48 km north of Middelburg and raised in 1977 by

9.1 m. The storage capacity rose from 180 x 106 m3 to 348.1 x 106 m3. The total

catchment area for the dam is 12 261 km2 (SANCOLD, 1978). The total

catchment incorporates the most industrialised region of the Olifants River basin

and the Loskop Dam is the biggest storage unit in the Olifants River catchment

(Figure 5.4) (Theron, Prinsloo, Grimsehl & Pullen Inc., 1991b). Rainfall occurs

mainly in the summer months; with January experiencing the heaviest rain and


80

90% of the water available from the Loskop Dam is used for irrigation (James

and Van Wyk, 1993).

The Loskop Dam has been described as a sink for heavy metals deriving from

the upper catchment and the whole of the Olifants River has been described as

degraded and contaminated with metals and other chemicals. These concerns

have been expressed as a consequence of the large number of agricultural,

industrial and mining activities in the catchment (Grobler et al., 1994). A large

number of mines, predominately coal mines, are located in the Loskop Dam

catchment and are concentrated mainly in the Olifants and Klein Olifants River

catchments upstream of the Witbank and Middelburg Dams respectively (Du

Plessis and Maré, 1999). The most extensive coal mining takes place at the

Witbank Coalfields and Highveld Coalfields. Coalmines provide essential fuel to

local power stations e.g. Arnot, Hendrina, Kriel, Komati, Duhva, Matla and

Kendal, as well as to the domestic and international markets. Coal mining and

industries in the Witbank-Middelburg and Phalaborwa areas also impact the

Olifants River. These mine effluents contain a complex of chemicals, many of

which may have deleterious effects for aquatic systems (Van Vuren et al., 1999).

Water discharges from the mines can originate from various sources, including

sewage treatment plants, seepage from opencast and underground mining

operations. The return flows from sewage treatment plants are released into

natural streams or re-used in mining operations. Return flows are also used for

irrigation purposes. Seepage and decanting from mines can result in serious

water quality related problems (BKS (Pty) Ltd., 1998; Du Plessis and Maré,

1998).

Presently, Loskop Dam supplies domestic, industrial and irrigation water users.

The impoundment mainly supplies the large irrigation schemes downstream of

the dam (BKS (Pty) Ltd., 1998).


81

Figure 5.4 : The Loskop Dam


82

5.3.2 Hartebeespoort Dam

The Hartebeespoort Dam is situated on the Crocodile River, about 16 km

southwest of the town of Brits and 37 km due east of Pretoria (SANCOLD, 1978)

and in the Highveld region of northern South Africa, 250 km south of the tropic of

Capricorn (Figure 5.6) (Hely-Hutchinson and Schumann, 1997). The 5

catchment basins of the dam are, from west to east, the Magalies/Skeerpoort, the

Crocodile, the Jukskei, the Hennops and the Swartspruit basin (Van Riet, 1987).

The Crocodile River is the most intensive irrigation system in South Africa with

numerous point and diffuse sources of domestic and industrial pollution (Figure

5.7) (Heath and Claassen, 1999).

The Hartebeespoort Dam was built in 1923 downstream of the confluence of the

Crocodile River and the Magalies River, and was raised in 1971 with 2.12 m.

The dam has a total storage capacity of 185.49 x 106 m3 and a catchment area of

4 112 km2 (Rossouw, 1992). Rainfall is highly seasonal and occurs mainly

between October and March. Land usage in the Hartebeespoort Dam catchment

can be devided into two categories, namely rural and urban. The commercial,

residential and industrial areas that are associated with the northern suburbs of

Johannesburg and other smaller towns on the Witwatersrand make up the urban

land use, while the rest of the area is used for natural reserves and agriculture

(National Institute for Water Research, 1985) (Figure 5.5).

The rivers that flow into the Hartebeespoort Dam are carrying an ever-increasing

volume of wastewater form a rapidly growing industrial and urban complex

(Aucamp et al., 1987) and Van Riet (1987) stated that the water of the

Hartebeespoort Dam is becoming unsuitable for agriculture, development and

recreation. The upper reaches of the Crocodile River drains the Johannesburg

Northern suburbs and its Hennops tributary drains Kempton Park, Tembisa,

Midrand and Centurion. The Magalies River drains the town of Magaliesburg and

Swartspruit drains the town of Hartebeespoort (Sutton and Oliveira, 1987). Other


83

catchment areas include towns like Clayville, Olifantsfontein, Alexandra and a

part of Atteridgeville and Saulsville (Rossouw, 1992).

Due to the intense urbanisation of this catchment it has the potential to decrease

the water quality of the natural resources due to the dumping of effluents and

solid-waste, mines, industrial activities, etc. There are also the sewerage

treatment plants of Johannesburg, Midrand, Kempton Park, Centurion,

Olifantsfontein, Randfontein, Kurgerdorp and Roordepoort in the catchment area.

Industrial dumping sites include AEK (Pelindaba and Valindaba), AECI-

Modderfontein and the Kelvin power station. There is also the potential

contamination of storm water runoff from industrial areas like Clayville, Isando

and Eastleigh as well as residential areas like Tembisa, Alexandra, Atteridgeville,

etc. The biggest influence on the water quality of the Hartebeespoort Dam is

form the Modderfontein stream that is upstream form the confluence with the

Jukskei River and thus the Crocodile River (Rossouw, 1992).

Figure 5.5 : The Hartebeespoort Dam


84

Figure 5.6 : A map showing the catchment areas, rivers and

urban/industrial areas of the Hartebeespoort Dam.


85

Figu

re 5

.7 :

The

catc

hmen

t are

as o

f the

Har

tebe

espo

ort D

am (B

KS

(Pty

) Ltd

., 19

92).


86

5.4 Materials and Methods

5.4.1 Water Quality

Physical water quality variables such as temperature, pH, conductivity, total

dissolved salts (TDS) and dissolved oxygen were determined at each of the sites

for the summer and winter surveys, using field instruments (Cyberscan DO100

Handheld Dissolved Oxygen Meter; Waterproof pHScan WP2 Tester; Cyberscan

EC-con-300 TDS/Conductivity Meter) (Table 5.1).

5.4.2 Fish sample collection and preservation

Twenty (20) fish were collected in the Rust de Winter Dam (S 24º49.800’; E 027º

29.102’), the Loskop Dam (S 25º14.220’; E 028º30.402’) and the Hartebeespoort

Dam (S 25±º45.678’; E 027º52.656’) during the summer and winter of the year,

2000. Samples were taken seasonally to establish increases and decreases in

biomarker activity. Twenty fish were collected to ensure more reliable results by

reducing variation in the data. The fish were collected using gill nets (70 – 100

mm stretched mesh sizes). The fish were removed from the nets and placed into

a portable holding tank with constant water circulation, till dissection to reduce

handling stress. The standard length (cm), mass (kg) and gender (male/female)

of each fish were recorded as well as other comments such a lesions or cysts on

the skin or liver of the fish, etc. (See Table 5.2 and 5.3)

After the above biological parameters were recorded, blood was drawn from the

caudial vein of the fish with a 2,5 ml pre-heparinised syringe (0,1 ml of 5 000

iu/mΡ sodium heparin) and a 0,6 x 30 mm needle. The blood was transferred to

a 5 ml vacutainer and kept on ice. The fish were then decapitated on a

polythene dissection board using clean, stainless steel tools. The liver was

removed and placed in a cryotube and frozen in liquid nitrogen at -196ºC. After

all 20 fish were dissected, 210 µl of the blood was removed for ALAD analysis

and placed in a clean vacutainer and frozen at -20ºC. The remaining blood was

centrifuged at 3 000 r.p.m. (1 000 g) for 10 min in an automatic refrigerated

centrifuge (Sorvall Superspeed RC2-B) and prepared according to the method of


87

Wittaker (1984) for further analysis. The plasma was placed in a cryotube and

frozen in liquid nitrogen. The red blood cells were kept in the vacutainers and

frozen at -20ºC. At the laboratory the samples were removed from the liquid

nitrogen and kept in a -70ºC freezer.

5.4.3 Method of biomarker analysis

All the protein analyses were done according to the colourimetric method of

Bradford (1976). Table 5.4 shows the different sample preparation and

biomarker analysis methods used during this study.

Table 5.4 : Methods and apparatus used in biomarker analysis of field

samples.

Biomarker Fish tissue

Preparation Method

Preparation Apparatus

Analysis Apparatus

Absorbancy Wavelength

(nm)

Analysis Method

AChE Red blood cells

Wittaker (1984)

Automated Refrigerated Centrifuge (Sorvall Superspeed RC2-B)

See Table 4.8 405 Ellman et al. (1961)

ALAD Whole blood

- Automated Refrigerated Centrifuge (Sorvall Superspeed RC2-B)

SP-8-100 Ultraviolet Spectro- Photometer (PYE Unicam)

555 Schaller and Berlin (1984)

EROD Liver Besselink et al. (1997)

Automated Refrigerated Centrifuge (Sorvall Superspeed RC2-B) Beckman L8-70M Ultracentrifuge

See Table 4.8 Exitation: 510mm Emmision: 586mm

Burke and Mayer (1974)

Glucose Plasma - See Table 4.8 See Table 4.8 546 See Table 4.8

Glycogen Liver - - SP-8-100 Ultraviolet Spectro- Photometer

620 Seifter et al. (1950)

88

Table 5.1 : Physical water qualities of the reference and polluted sites during the summer and winter surveys.

Reference site Polluted sites Variables

Rust de Winter Dam Loskop Dam Hartebeespoort Dam

Date 14/01/00 05/06/00 15/01/00 06/06/00 08/02/00 08/06/00

Time 14:45 15:20 12:10 14:10 16:00 16:25

Temperature (ºC) 25.7 15.5 26.3 18.1 23.1 16.8

pH 8.3 6.3 9.2 8.6 9.3 8.5

Dissolved Oxygen – mg/l 11.1 3.02 12.3 5.2 7.6 3.23

– % 163 30.6 112 56.5 117 34.4

Conductivity(µS/m) 178 136 409 309 511 477

Total dissolved salts (TDS) 88.9 - 203 308 233 -

- = Variables not measured

89

Table 5.2 : Biological variables (standard length, mass and gender) measured of O. mossambicus collected at the

reference and polluted sites during the summer survey.

Reference site Polluted sites Rust de Winter Dam Loskop Dam Hartebeespoort Dam

Fish no.

Standard Length(cm)

Mass (kg)

Gender Comments Standard Length(cm)

Mass (kg)


Mass (kg)

Gender Comments

1 38 1.15 ? - 39 1.25 ? - 23.5 0.30 ? - 2 34 0.65 ? - 38.5 1.20 ? - 24.5 0.35 ? - 3 35 0.75 ? - 38 1.10 ? - 24 0.35 ? - 4 33 0.55 ? One eye

blind 36 0.85 ? - 24.5 0.35 ? -

5 36 0.90 ? - 42 1.55 ? - 24 0.35 ? - 6 41 1.40 ? - 41 1.45 ? - 25.5 0.40 ? - 7 42 1.50 ? - 36 0.90 ? - 25 0.40 ? - 8 35 0.75 ? - 35.5 0.80 ? - 34 0.55 ? - 9 35.5 0.80 ? - 37 1.00 ? - 24 0.30 ? -

10 36 0.90 ? - 37.5 1.00 ? - 26 0.40 ? - 11 42 1.50 ? - 37 1.00 ? - 23 0.30 ? - 12 36 0.90 ? Many

Argulus parasites

35 0.75 ? - 23 0.30 ? -

13 36 0.90 ? - 44 1.75 ? - 24 0.35 ? - 14 39 1.15 ? - 37.5 1.00 ? - 24 0.35 ? - 15 29 0.45 ? - 39 1.30 ? - 24 0.35 ? - 16 28.5 0.50 ? - 35 0.75 ? - - - - - 17 33 0.55 ? - 47 2.10 ? - - - - - 18 36 0.90 ? - 40 1.35 ? - - - - - 19 - - - - 37 1.00 ? - - - - - 20 - - - - 47 2.10 ? - - - - -

90

Table 5.3 : Biological variables (standard length, mass and gender) measured of O. mossambicus collected at the

reference and polluted sites during the winter survey.

Reference site Polluted sites Rust de Winter Dam Loskop Dam Hartebeespoort Dam

Fish no.

Standard Length(cm)

Mass (kg)


Mass (kg)


Mass (kg)

Gender Comments

1 42.5 1.26 ? - 41 1.75 ? - 28.5 0.45 ? Cysts on operculum

2 36 0.77 ? - 36 1.15 ? - 40 1.25 ? One eye blind 3 25 0.23 ? - 41 1.40 ? - 47 1.90 ? - 4 39.5 1.25 ? - 38.5 1.50 ? - 41.5 1.50 ? - 5 38 1.25 ? - 42 1.80 ? Liver dark,

hard with cysts

36.5 1.00 ? -

6 42 1.25 ? - 45.5 2.20 ? - 42 1.50 ? Liver contains cysts

7 36 0.78 ? - 39.5 1.80 ? - 38 1.20 ? - 8 39 1.27 ? - 39.5 1.20 ? - 45.5 1.70 ? - 9 37 0.90 ? - 49 2.40 ? - 42 1.30 ? Bottom lip

deformed 10 35 0.90 ? - 45 2.20 ? - 37 1.10 ? One eye

cataract 11 36.5 1.10 ? - 36.5 1.20 ? - 38 1.25 ? One eye

cataract 12 40 1.25 ? - 43 1.75 ? Liver hard,

with cysts 44.5 1.80 ? -

13 34 0.85 ? One eye blind 45 2.25 ? - 44 1.75 ? - 14 39 1.20 ? - 38.5 1.25 ? - 40 1.40 ?

Liver hard with cysts

15 40 1.05 ? - 39.5 1.50 ? - - - - - 16 42 1.25 ? - 40 1.50 ? - - - - - 17 43 1.60 ? Nematode in

brain cavity 41.5 1.70 ? - - - - -

18 38 1.10 ? - 43 1.90 ? Liver contains cysts

- - - -

19 40.5 1.30 ? - 42 2.00 ? - - - - - 20 35 0.79 ? - 42 1.75 ? - - - - -


91

5.4.4 Statistical Analysis

Statistical analysis was done on the values for the different biomarker

variables measured during the field studies. The statistical analysis was done

by a consultant from STATKON at the Rand Afrikaans University (RAU) by

using the SPSS Computer Systems. The variables were evaluated

statistically with ANOVA. When the ANOVA indicated statistical differences,

Dunnett’s test was employed to test for significance differences between the

reference site (Rust de Winter Dam) and the polluted sites, Loskop and

Hartebeespoort Dam. Significant differences for a dam between the two

seasonal surveys were also determined.

5.5 Results

5.5.1 Physical water quality

The selected physical water quality results for the dams can be seen in Table

5.1.

The variation in temperature for the different dams sampled, is a function of

seasonality. The water temperatures are higher during the summer, and a

drop in water temperature during the winter. All three dams showed a slight

decrease in pH. The Rust de Winter Dam showed the highest dissolved

oxygen content (163% saturation) during the summer, with Loskop and

Hartebeespoort Dam with lower levels of 112 and 117% saturation,

respectively. There was a drop in dissolved oxygen levels in all three dams

during the winter. Conductivity is the ability to conduct an electrical current

due to the presence of ions in the water. Loskop Dam (summer = 409 µS/m;

winter = 309 µS/m) and Hartebeespoort Dam (summer = 511 µS/m; winter =

477 µS/m) showed the highest values for both seasons. Total dissolved salts

(TDS) are a measure of all the salts dissolved in the water and Loskop Dam

and Hartebeespoort Dam showed the highest values during the summer, with

203 and 233 respectively (Table 5.1).


92

5.5.2 Differences between genders

There were no significant differences for the values measured for the different

variables, between the male and female fish collected at the different sites for

both surveys.

5.5.3 Different protein values

Table 5.5 shows the protein values for the different tissues used for the

biomarker analysis. All the biomarker results were expressed in terms of

protein.

Table 5.5 : Protein content of different tissues used for biomarker

analysis.

Tissue protein content (mg/ml )

Dam Season WB RBC Plasma Liver

Summer n

Mean±Sd

Min/max

P

18

63.60±22.81

27.83-108.79

*

16

278.06±200.73

29.90-706.00

-

18

53.39±14.10

27.08-74.71

-

18

29.09±11.24

12.97-61.03

*

RDW

Winter n

Mean±Sd

Min/max

P

19

130.27±35.52

57.93-207.31

*

20

225.12∀27.19

189.60-276.91

-

17

47.15±9.28

30.26-66.96

-

20

43.07±11.85

11.46-66.55

*

Summer n

Mean±Sd

Min/max

P

19

58.36±17.56

20.58-90.90

*

18

474.03±240.45

182.70-897.65

* / <

19

57.10±15.26

21.65-77.00

*

20

34.57±13.01

23.24-84.38

-

LD

Winter n

Mean±Sd

Min/max

P

18

112.03±38.63

25.47-210.69

*

20

259.37±47.97

218.09-412.85

* / <

20

46.27±6.73

37.06-64.47

*

20

34.83±8.87

12.97-52.72

<

Summer n

Mean±Sd

Min/max

P

14

123.35±22.49

84.42-165.60

<

15

184.11±9.27

169.45-204.9

*

14

53.27±16.11

32.02-85.87

*

15

18.78±9.69

10.07-42.79

* / <

HBP

Winter n

Mean±Sd

Min/max

P

13

125.16±45.18

62.81-203.23

-

14

302.12±155.76

195.95-728.69

*

14

42.88±8.05

33.11-64.01

*

14

39.90±9.77

22.30-54.11

*

RDW=Rust de Winter Dam* = Significant difference (p<0.05) between the same dam LD=Loskop Dam different seasonal surveys. HBP=Hartebeespoort Dam < = Significant difference (p<0.05) between the polluted sites WB=Whole Blood (LD/HBP) and the reference site (RDW) during the same RBC=Red Blood Cells survey. - = No significant difference


93

There is a significant difference (p<0.05) between the whole blood protein

levels in the Rust de Winter Dam between the surveys, 63.60 and 130.27

mg/ml for summer and winter respectively. Loskop Dam also showed a

significant difference with 58.36±17.56 and 112.03±38.63 mg/ml for the two

surveys. The Hartebeespoort Dam showed a significant difference with

123.35±22.49 mg/ml and Rust de Winter Dam (63.06±22.81 mg/ml) during

the summer survey.

Rust de Winter Dam showed no significant difference in the red blood cell

protein levels for the two surveys but Loskop Dam did with values of

474.03±240.45 mg/ml for the summer and 259.37±47.49 mg/ml for the winter

survey. Hartebeespoort Dam also showed significant differences (p<0.05) for

the two surveys, with 184.11±9.27 and 302.12±155.76 mg/ml for both the

summer and the winter surveys. The red blood cell protein levels for Loskop

Dam for both summer and winter showed significant differences form the

reference site, Rust de Winter Dam.

The plasma protein content of the Rust de winter Dam showed no significant

differences during the two surveys. Both the Loskop Dam

(summer=57.10±15.26 mg/ml; winter=46.27±6.73 mg/ml) and the

Hartebeespoort Dam (summer=53.27±16.11 mg/ml; winter=42.88±8.05

mg/ml) showed significant differences (p<0.05) for the two surveys. There

were no significant differences between the po lluted sites and the reference

site for the summer and winter surveys.

Both Rust de Winter Dam (summer=29.09±11.24 mg/ml; winter=43.07±11.85

mg/ml) and Hartebeespoort Dam (summer=18.78±9.69 mg/ml;

winter=39.90±9.77 mg/ml) showed significant differences (p<0.05) for the liver

protein content between the two seasonal surveys. Hartebeespoort Dam also

showed a significant difference from the reference site for the summer survey

and Loskop Dam for the winter survey.


94

5.5.4 Different biomarker analysis

Figures 5.8 to 5.12 show the results obtained for the different biomarkers

during the two seasonal surveys.

The Acetylcholinesterase (AChE) enzyme activity (Figure 5.8) for the summer

survey showed inhibition for Loskop Dam (1.59 x 10-4±1.81 x 10-4 OD/min.mg

protein) and induction for Hartebeespoort Dam (5.48 x 10-4±2.57 x 10-4

OD/min.mg protein), but there was no significant difference (p<0.05) between

the reference and polluted sites. There were also no significant differences

between the dams for the winter survey, although there was some inhibition at

the polluted sites. A significant increase was seen in AChE activity in the

Loskop Dam between the two surveys with 1.59 x 10-4±1.81 x 10-4 OD/min.mg

protein for the summer and 4.17 x 10-4±2.66 x 10-4 OD/min.mg protein for the

winter survey.

0.00E+00

2.00E-04

4.00E-04

6.00E-04

8.00E-04

1.00E-03

1

AC

hE

(OD

/min

.mg

pro

tein

)

RDW LD HBP

0.00E+002.00E-044.00E-046.00E-048.00E-041.00E-03

1

AC

hE (O

D/m

in.m

g pr

otei

n)

RDW LD HBP

Figure 5.8 : Acetylcholinesterase (AChE) enzyme activity during the summer

(A) and winter (B) surveys (RDW=Rust de Winter Dam, LD=Loskop Dam, HBP=Hartebeespoort Dam).

A

B


95

05

10152025

1

AL

AD

(U/h

.mg

pro

tein

)

RDW LD HBP

00.5

11.5

22.5

1ALA

D (U

/h.m

g pr

otei

n)

RDW LD HBP

Figure 5.9 : ∗-Aminolevulinic acid dehydratase (ALAD) enzyme activity during

the summer (A) and winter (B) surveys (RDW=Rust de Winter Dam, LD=Loskop Dam, HBP=Hartebeespoort Dam; * = p<0.05).

0

0.5

1

1.5

1

ER

OD

(nM

/min

.mg

prot

ein)

RDW LD HBP

0

0.5

1

1.5

2

1

ER

OD

(nM

/min

.mg

prot

ein)

RDW LD HBP

Figure 5.10 : Ethoxyresorufin-O-deethylase (EROD) enzyme activity during the

summer (A) and winter (B) surveys (RDW=Rust de Winter Dam, LD=Loskop Dam, HBP=Hartebeespoort Dam; * = p<0.05).

A

B

* *

A

B

*

*


96

0.00E+00

1.00E-02

2.00E-02

3.00E-02

4.00E-02

1

Pla

sma

Glu

cose

(mg

g

luco

se/m

g p

rote

in)

RDW LD HBP

0.00E+00

1.00E-02

2.00E-02

3.00E-02

4.00E-02

1

Pla

sma

Glu

cose

(mg

gluc

ose/

mg

prot

ein)

RDW LD HBP

Figure 5.11 : Plasma Glucose content during the summer (A) and winter (B)

surveys (RDW=Rust de Winter Dam, LD=Loskop Dam, HBP=Hartebeespoort Dam; * = p<0.05; **= p<0.1).

0200400600800

100012001400

1

Liv

er G

lyco

gen

(m

g

gly

cog

en/1

00 g

live

r)

RDW LD HBP

0500

1000

15002000

2500

1

Live

r G

lyco

gen

(mg

glyc

ogen

/100

g li

ver)

RDW LD HBP

Figure 5.12 : Liver Glycogen content during the summer (A) and winter (B)

surveys (RDW=Rust de Winter Dam, LD=Loskop Dam, HBP=Hartebeespoort Dam; * = p<0.05).

*

A

B

A

B **


97

Figure 5.9 shows the ALAD enzyme activity for both surveys. Loskop Dam

(5.602 U/h.mg protein) and Hartebeespoort Dam (7.725±3.40 U/h.mg protein)

showed significant differences (p<0.05) in the inhibition of ALAD activity form

Rust de Winter Dam (16.093±7.48 U/h.mg protein) for the summer survey.

There was no significant differences between the dams for the winter survey,

although it looks like inhibition did occur, and all three sites showed significant

decreases in enzyme activity between the two surveys.

EROD synthesis for the three sites is shown in Figure 5.10. Induction did

occur in Loskop Dam (1.011±0.33 nM/min.mg protein) and Hartebeespoort

Dam (1.059±0.28 nM/min.mg protein) during the summer, but not statistical

significant. A significant difference did occur between Loskop Dam

(0.493±0.38 nM/min.mg protein), Hartebeespoort Dam (1.295±0.38

nM/min.mg protein) and Rust de Winter Dam (0.874±0.47 nM/min.mg protein)

for the winter survey with Loskop Dam showing inhibition and Hartebeespoort

Dam, induction. Loskop Dam also showed a significant difference between

the two surveys.

Plasma Glucose levels (Figure 5.11) showed no significant differences for the

summer survey even though Loskop Dam showed a slight increase (2.241 x

10-2±8.00 x 10-3 mg glucose/mg protein) and Hartebeespoort Dam (1.454 x

10-2±9.84 x 10-3 mg glucose/mg protein) a decrease against the reference

site, Rust de Winter Dam. The fish caught at Loskop Dam did show a

significant increase in plasma glucose levels (2.14 x 10-2±7.47 x 10-3 mg

glucose/mg protein) during the winter survey, but there was no difference in

plasma glucose levels between the two surveys. Hartebeespoort Dam (p<0.1;

2.162 x 10-2±6.56 x 10-3 mg glucose/mg protein) showed a significant increase

from Rust de Winter Dam during the winter survey. Rust de Winter Dam did

show a significant decrease in glucose levels for the summer and winter

surveys with 2.147 x 10-2±8.19 x 10-3 mg glucose/mg protein and 1.577 x 10-2

±5.40 x 10-3 mg glucose/mg protein, respectively. Hartebeespoort Dam also

showed a significant increase with glucose levels of 1.454 x 10-2±9.84 x 10-3

mg glucose/mg protein for the summer and 2.162 x 10-2±6.56 x 10-3 mg

glucose/mg protein for the winter surveys.


98

Figure 5.12 shows the liver glycogen content determined during the summer

and winter surveys. Hartebeespoort Dam showed a significant decrease in

values form the reference site. The standard deviation for this survey was

extremely high. There was a significant increase in liver glycogen content for

all three sites form the summer to the winter surveys, with Rust de Winter

Dam increasing from 567.0±634.51 to 1349.864±432.26 mg glycogen/100 g

liver, and Hartebeespoort Dam with 86.0±147.59 to 1569.391±616.88 mg

glycogen/100 g liver. There was no significant difference (p<0.05) between

the sites during the winter survey.

Plasma glucose levels and EROD enzyme activity both showed the smallest

standard deviation and ALAD and AChE enzyme activity and liver glycogen

content the highest. This should be taken into account when choosing a

suitable battery of biomarkers.

5.6 Discussion

Factors such as overpopulation, industrialisation and the improvement in

agricultural practices for better crops production, have all contributed to the

general deterioration of the environment, the same environment that humanity

is completely dependent on for life. Industrial effluents lead to heavy metal

enrichment of the aquatic environment during melting and smelting operations

and these metals can produce various physiological changes in the aquatic

life (Sastry and Shukla, 1994).

The variability of the physical environmental conditions directly affects the

biotic patterns such as abundance of species and micro- and macro-

geographic distribution of all organisms (Roux, 1994). Depending on the

variable, the ambient water quality as well as the organism involved can be

affected. The thermal characteristics of an aquatic ecosystem are reliant on

hydrological, climatical and structural features of its catchment under normal

conditions. Anthropogenic activities can decrease or increase the natural

variation in water temperature negatively. Water temperature as a variable

should be seen as a factor influencing the toxicity of pollutants (Van Vuren et


99

al., 1999) for example, metals like cadmium and zinc increase in toxicity with

an increase in water temperature (DWAF, 1996). The seasonal water

temperature changes, seen in Table 5.1, is still within the tolerance ranges of

Oreochromis mossambicus (Chapter 3).

Geological and atmospheric influences determine the natural pH of a

waterbody (Van Vuren et al., 1999) and the pH range that is not directly lethal

to fish is between 5 and 9. It is however important to remember that the

toxicity of several common toxicants like metals, is affected by pH changes

within this range (Alabaster and Lloyd, 1980).

Dissolved oxygen (DO) is essential for maintaining aquatic life and low oxygen

levels create an increase in the metabolic rate of fish, thereby causing an

increased rate of water pumping over the gills. Thus increasing the amount of

toxin in contact with the gill surface, where it is absorbed (Alabaster and

Lloyd, 1980; Van Vuren et al., 1999). The target range of DO levels are

between 80-120 % saturation (Van Vuren et al., 1999). The drop in oxygen

levels during the winter could be a function of seasonality. Higher inflow of

the rivers around the impoundments takes place because most of the rainfall

occurs during October to March, with January experiencing the most rainfall

for all the sites. Thus during the summer, large amounts of organic matter

enter the water from industrial/domestic wastes and could utilise a large

amount of DO due to microbial respiration (Van Vuren et al., 1999). During

the winter survey the DO levels were extremely low. The high rainfall

experienced during the summer could have caused a large influx of mining

runoff and industrial/domestic waste into the impoundments studied, where

microbial respiration utilised the a large amount of DO. The above-mentioned

as well as a reduction of inflow of the rivers surrounding the impoundments

during the winter could attribute to a decreased DO level.

Total dissolved salts (TDS) concentrations are a measure of the salts

dissolved in the water while the conductivity refers to the water’s ability to

conduct an electrical current due to the presence of ions in the water. The

ions have the ability to carry an electrical charge (CO32-, HCO-, Cl-, SO4

2-,


100

NO3-, Na+, Ca2+, Mg2+). Geological weathering and atmospheric conditions

contribute to the TDS of natural aquatic systems, however domestic and

industrial discharges and surface runoff from urban, industrial and agricultural

areas, together with evaporation can also increase the TDS levels. Natural

fluctuations in TDS could be the dissolution of rocks, soils and decomposing

plant material (Van Vuren et al., 1999). A heavy summer rain season could

enhance the above-mentioned fluctuations. The high conductivity and TDS

values for Loskop Dam could be related to high land usage disturbances such

as mining, and in the case of Hartebeespoort Dam, agricultural runoff and

urban and rural settlement activities, as well as water works (water care

facilities) in the catchment could cause these high levels.

The inhibition of AChE enzyme activity is specific to organophosphorus and

carbamate compounds. These compounds are widely used in pesticides and

the inhibition of AChE has been used for the assessment of

organophosphorus pesticide pollution. Fish can detoxify these compounds

more easily than invertebrates and significant AChE inhibition in fish can only

be detected at relatively high concentrations. Organisms that survived acute

effects of pesticide pollution show a recovery of AChE activity that is slow but

dependant on the spontaneous dephosphorylation of the inhibiton site and on

the synthesis of new AChE (Peakall, 1992; Ibrahim et al., 1998).

Organophosphorus and carbamate compounds may not be the only pollutants

that cause AChE inhibition in fish, chemicals like zinc, mercury, cadmium and

copper can cause some inhibition of AChE, meaning that AChE activity may

not be especially diagnostic for pesticide poisoning (Heath, 1995). The

inhibition of brain AChE activity may remain for several weeks following

exposure to pesticides. The inhibition of blood cholinesterase activity is also

indicative of exposure to a toxicant but the inhibition of enzyme activity is

short-lived and more definitive results are usually obtained with brain AChE

than with blood AChE (Melancon, 1995). The higher the AChE level in a

tissue, the more susceptible it is to inhibition with inhibition the greatest in the

brain, followed by muscle, gill and liver (Heath, 1995). The effectiveness of

using AChE inhibition as an indicator of pollution in field-collected animals

depends on the quality of the reference values so that possible inhibited


101

samples show a significant difference from the control values (Melancon,

1995). For continuous exposure studies, blood sampling has the advantage

that the organism does not have to be killed for sampling and serial samples

may be collected form the same animal. Keeping the above -mentioned in

mind and looking at Figure 5.8, the red blood cell AChE activity was extremely

low for all three sampling sites. The standard deviation was also very high

and in future field surveys; brain AChE activity should be measured for more

accurate results. Blood AChE should not be used as part of a battery of

biomarkers, as it gives unreliable results. However, the possible use of brain

AChE as an indicator of toxicant exposure should be investigated in the

future.

∗-Aminolevulinic acid dehydratase (ALAD) is an important enzyme in the

haem synthesis, converting ∗-Aminolevulinic acid (ALA) to porphobilinogen

and ferrochelatase, and inserting iron into protoporphyrinogen (Nussey,

1994). The ALAD enzyme activity is found in almost every tissue since it also

participate in the synthesis of all other haem proteins. Red blood cells are

formed in the spleen and kidney and an increase in ALAD in the red blood

cells would indicate stimulation of haem synthesis in these two organs

(Nussey, 1994; Westman et al., 1975). The inhibition of ALAD activity is

specific for lead (Wepener, 1990; Johansson-Sjöbeck and Larsson, 1979) and

reduction in the enzyme activity occurs rapidly and can be detected at

exposure concentrations near “no effect” level (Schmitt et al., 1984). Lead is

a naturally occurring heavy metal and is widely distributed by industrial

activities (Ho and Ho, 1997) and the contamination of natural waters by lead is

caused by activities related to increasing mining operations and industrial use

of lead (Tewari et al., 1987). Fish exposed to cadmium, copper, zinc and

mercury showed no erythrocyte ALAD inhibition, indicating that this enzyme is

quite specific to lead (Johansson-Sjöbeck and Larsson, 1979). Mining

activities release a large amount of metals, including lead, into the

environment. The significant decrease (p<0.05) in ALAD enzyme activity

obtained during the field evaluation shows the possibility of high lead

concentrations present in the Loskop Dam catchment. When investigating an


102

area with possible lead contamination, or when conducting lead exposure

experiments in the laboratory, the inhibition of ALAD enzyme activity should

be included in the battery of biomarkers because of the ALAD enzyme

sensitivity to lead.

Ethoxyresorufin-O-deethylase (EROD) is a sensitive indicator of Cytochrome

P1501A and high levels of environmental contaminants by chemicals may

result in an increase in this mixed-function oxidase (MFO) activity in fish

(Chen et al., 1998; Parke, 1981). Organic pollutants like PAHs, PCBs and

dioxins as well as complex mixtures including municipal and industrial

effluents cause the induction of EROD activity (Jimenez and Stegeman,

1990), explaining the induction seen in the Hartebeespoort Dam during the

two surveys. EROD levels from fish caught in the Loskop Dam showed

inhibition of EROD activity during the second survey. It has been reported

that heavy metals have an inhibitory effect on cytochrome P4501A induction

in fish hepatoma cells (Chen et al., 1998; Gagné and Blaise, 1993). Copper

inhibits enzyme activity by binding to SH-residues of the enzymatic proteins of

the MFO system, or as a consequence of the enhancing of lipid peroxidation

of the membranes. This leads to a more general alteration of the structure

and function of the endoplasmic reticulum (Stien et al., 1997). High levels of

PCB congeners and metals such as cadmium also cause inhibition of

cytochrome P4501A mediated catalytic activity (Jakšic et al., 1998).

Environmental variables such as seasonal changes, which are associated

with temperature and sexual factors, age and nutritional status of the fish, are

the most important influences on the MFO activity of fish (Jimenez and

Stegeman, 1990). The EROD enzyme activity proved to be a relative

sensitive biomarker for use in field surveys. By concentrating the enzyme

concentration even more during the preparation stage of the assay, it could be

possible to increase the sensitivity of the assay. Before using EROD enzyme

synthesis as an indicator of pollution, chemical analysis of the river or

impoundment studied, should be carried out to determine the specific

constituents and toxicant levels present in the water. The analysis will explain

the results since liver EROD enzyme activity can be both inhibited and

inducted by pollutants, as mentioned above.


103

In fish, an increase in blood glucose levels and a decrease in liver glycogen

levels, are one of the first signs of stress on the carbohydrate metabolism

(Wepener, 1990). The rise in blood glucose, is the most characteristic general

response to stress, and occurs when the physical activity of the fish exceeds

what is normal (Love, 1980). Blood glucose levels are elevated in fish during

exposure to various pollutants, including pesticides and these stressful stimuli

elicit the rapid secretion of hormones, glucocorticoids and catecholamines,

from the adrenal tissue of fish, producing rapid hyperglycemia (Cerón et al.,

1996). Prolonged hyperglycemia could result in depletion of energy reserves

and an insufficient energy production. Continuous elevated blood glucose

levels cause a shift form aerobic to anaerobic metabolism and increases in

anaerobic metabolism is a response against the depletion of energy caused

by lack of oxygen (Cerón et al., 1996; Solomonson, 1981). Short-term

changes in glucose levels can be induced by handling stress, changes in

temperature, pH, water velocity, hypoxia, or other seasonal variations

(Folmar, 1993). To reduce the possibility of handling stress, all the fish from

the reference as well as the polluted sites were treated equally. The different

blood glucose levels obtained could be attributed to differences in rate and

degree of digestion, absorption and utilisation of glucose, due to an impaired

carbohydrate metabolism (Hilmy et al., 1980). When including plasma glucose

in a battery of biomarkers, it should be remembered that as already

mentioned, elevated blood glucose levels are a general response to stress,

including exposure to toxicants and other environmental changes like water

temperature variations.

Stress response in fish is generally characterised by an increase in adrenalin

causing mobilisation of liver glycogen into blood glucose (Swallow and

Flemming, 1970). The blood glucose levels do not necessarily reflect the

level of glycogen (Love, 1980). The high liver glycogen levels at the polluted

sites for the winter survey showed that the fish at the polluted sites had

greater liver glycogen stores than the reference site. Cortisol lowers the liver

glycogen and an increase in blood glucose with the depletion of liver glycogen

to stress. Metabolic consequence of cortisol impairment may be a reduced


104

capacity to mobilise liver glycogen stores (Hontela et al., 1995). In the field

study, liver glycogen values showed no significant differences between the

reference and polluted sites for both the surveys. High standard deviations

were also obtained (Figure 5.5). When looking at all of the above-mentioned

information, there seems to be a large variation in liver glycogen levels under

normal conditions. It is thus difficult to identify changes in liver glycogen

levels caused by exposure to pollutants. Liver glycogen levels should not be

used as an indicator of pollutants and should not be included in a battery of

biomarkers.

Of the five biomarkers evaluated during this field study, only three biomarkers

showed significant results (p<0.05). ALAD, EROD and plasma glucose levels

can thus be included in a battery of biomarkers to be used as indicators of

exposure to pollutants. Even though these three biomarkers showed

significant results, the biomarkers will be even more accurate and sensitive at

higher levels of pollution. Although erythrocyte AChE and liver glycogen

showed no significant results during this study, it is still possible that these two

biomarkers will show more accurate and significant results at higher pollution

levels. Together with the use of biomarkers as indicators of deteriorating

water quality due to the influx of pollutants, chemical water analysis should

also be carried out. Chemical analysis will show what toxicants/pollutants are

present in the water while the biomarkers will show the level of effect of the

toxicant on the organisms. More reliable results will thus be obtained.


105

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