GEOMORPHOLOGY, ICHTHYOFAUNA,
WATER QUALITY AND AESTHETICS OF
SOUTH AFRICAN ESTUARIES
1
ENV-DC 2000-01
GEOMORPHOLOGY, ICHTHYOFAUNA, WATER QUALITY AND
AESTHETICS OF SOUTH AFRICAN ESTUARIES
PREPARED FOR:
Department of Environmental Affairs & Tourism
Private Bag X447
PRETORIA
0001
SOUTH AFRICA
PREPARED BY:
Division of Water, Environment and Forestry Technology
ENVIRONMENTEK
CSIR
P O Box 17001
CONGELLA
4013
SOUTH AFRICA
PROJECT TEAM:
T. D. Harrison, J. A. G. Cooper* & A. E. L. Ramm**
*Coastal Studies Research Group
University of Ulster
COLERAINE
BT52 1SA
NORTHERN IRELAND
**Ecology & Environment Inc.
8438 Lyons Rd
Sherman
NEW YORK
14787
UNITED STATES
January 2000
2
EXECUTIVE SUMMARY
The South African 3 000 km coastline has approximately 370 outlets to the sea
ranging from small coastal streams to large permanently open tidal estuaries. The
current state of scientific information on the vast majority of these systems, however,
is virtually nil. As part of a national program to assess the state of South Africa’s
estuarine environment, basic surveys were conducted on these systems during the
period 1992 to 1999.
This included ichthyofauna (fish), water quality, and
geomorphological and aesthetic observations.
‘estuaries’ have been surveyed to date.
Some 67% of South Africa’s
This baseline data has been analysed and
synthesised to render it understandable to the non-specialist but at a sufficiently high
level to inform potential end users of the state of South Africa’s estuaries.
A conceptual classification of the geomorphic variability among South Africa’s
estuaries has been produced. Several systems particularly on the west coast were not
considered estuaries either due to their small size, their ephemeral nature, or because
they were essentially isolated. Six basic estuary types were identified. These were
divided into normally open and normally closed systems. Two types of normally
closed estuaries were recognised. These were systems where the water level was
typically perched above sea level and those where the water level was approximately
at sea level. In this report, however, the normally closed estuaries were sub-divided
into small, medium, and large systems based on surface area. The normally open
systems were divided into barred and non-barred estuaries. Two types of permanently
open barred estuaries were recognised: river-dominated and tide-dominated systems.
In this report the two types of normally open barred estuaries were not identified but
were sub-divided into small and medium to large systems based on their mean annual
runoff.
Based on the ichthyofaunal data and the geomorphological classification, the three
biogeographic regions that characterise the coastline were identified and delineated.
These were the cool-temperate region from the Gariep (Orange River) estuary to Cape
Agulhas, the warm-temperate region from Cape Agulhas to and including the Mdumbi
estuary, and the subtropical region from the Mdumbi to Kosi Bay.
i
Aspects of the fish community structure of each geomorphic estuary type were
investigated and each estuary type appeared to contain fairly distinctive fish
assemblages although some overlap did exist. The fish community structure (species
richness, composition and relative abundance) of each estuary type within each
biogeographic region was described and this was used as a reference against which
each estuary could be assessed.
In terms of their species richness, composition and relative abundance, two systems
(8%) in the cool-temperate region had low ratings. Ten estuaries (42%) were rated as
moderate and the remaining 12 systems (50%) had a good overall rating. Of a total of
119 estuaries analysed in the warm-temperate region, nine (8%) had a relatively poor
overall rating, 35 (29%) were rated moderate and the remaining 75 (63%) had a good
overall rating. In the subtropical region, three estuaries (5%) were rated poor, 23
(36%) had a moderate overall rating and the remaining 37 (59%) had a good rating.
The results of the water quality surveys were summarised into an estuarine water
quality index (eWQI) to provide a ‘snapshot’ of the average water quality of South
Africa’s estuaries.
Six indicators of estuarine water quality were chosen and these
were divided into three categories: suitability for aquatic life (dissolved oxygen,
oxygen absorbed, unionized ammonia), suitability for human contact (faecal
coliforms), and trophic status (nitrate nitrogen, ortho-phosphate).
The effect of
including/removing chlorophyll-a in the water quality index was also tested. The
results indicated that the exclusion of chlorophyll had no significant effect on the
relative index ranking for the estuaries tested. The sensitivity of the index to various
aggregation formulas was also tested. Alternative formulations did not significantly
alter the relative ranking of the estuaries tested. Using the eWQI values, five water
quality classes were identified. Approximately 74% of all the systems sampled were
classified in a “Fair” or better condition. The remaining 26% were classed as “Poor”
or “Very Poor”. Systems on the south and south-east coasts had the best overall water
quality with a preponderance of estuaries classed as “Good” or “Very Good”.
Estuaries on the Transkei and KwaZulu-Natal had a relatively high proportion of
systems in “Poor” condition.
ii
Aesthetic observations on each estuary were divided into 14 weighted categories:
floodplain landuse, shoreline status, estuary surrounds, bridges, dams and weirs,
mouth stabilisation, litter and rubble, human use, algal growth, turbidity, odour, air
pollution, noise, and invasive and exotic vegetation. The aesthetic state of each
estuary was assessed according to the type and degree of impairment to each category.
Overall, 251 systems were assessed and 18 (7%) had relatively poor aesthetic ratings,
88 (35%) were regarded as moderate while the remaining 145 (58%) were rated
relatively good aesthetically.
The results of this study provide a useful summary of the status of South Africa’s
estuaries, however, there exists a need to make all of the basic data, as well as various
forms of summarised data, available to interested parties from scientists to managers
and even the general public. Furthermore, much of the baseline data collected during
these surveys has not been fully analysed. The assessment of the fish fauna was only
based on a few components of the fish community. Other aspects of community
structure such as biomass composition, life-history styles and trophic structure should
be investigated.
In terms of water quality, a physical water quality impairment
category, involving such indicators as temperature, salinity, pH, and turbidity should
be explored. Also water quality rating curves for different estuary types should be
investigated.
There are also some obvious significant gaps in the database. A number of estuaries,
particularly in the Transkei, have not been sampled and these gaps need to be filled.
The geomorphological classification is based only on available data and additional
information is required to improve its resolution for example data on mouth condition
and tidal prisms. Long-term data sets are also required to establish the range of the
natural variation between and within estuaries on a seasonal basis.
This would
provide a better understanding of how estuaries of various types function, a critical
requirement for effectively managing coastal issues such as artificial breaching,
estuarine water requirements, eutrophication of estuaries, and biological functioning.
There is also a lack of a cohesive plan for temporal monitoring of key systems.
Investigations
into
other
estuarine
components
iii
(e.g.
hydrology,
sediment
biogeochemistry, vegetation, zooplankton, zoobenthos, birds, habitat assessment,
catchment land-use) should also be undertaken to ensure a more complete appraisal of
the ecological integrity of the nation’s estuarine resource.
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TABLE OF CONTENTS
Executive summary
i
Table of contents
v
Acknowledgements
vii
1. Introduction
1
2. Geomorphology
5
2.1 Introduction
5
2.2 Coastal setting
8
2.3 Estuaries: Introduction to a conceptual classification
9
2.4 Open estuaries
10
2.4.1 Barred open estuaries
10
2.4.2 Non-barred open estuaries
16
2.5 Closed estuaries
18
2.5.1 Perched closed estuaries
18
2.5.2 Non-perched closed estuaries
20
2.6 Discussion
22
2.6.1 Practical classification
23
3. Ichthyofauna
29
3.1 Introduction
29
3.2 Ichthyofaunal surveys
30
3.3 Biogeography
32
3.3.1 Introduction
32
3.3.2 Methods
32
3.3.3 Results & discussion
36
3.4 Classification
47
3.4.1 Introduction
47
3.4.2 Methods
47
3.4.3 Results & discussion
47
3.5 Fish community characteristics
57
3.5.1 Introduction
57
3.5.2 Methods
57
3.5.3 Results & discussion
58
v
3.6 Fish community status or ‘health’
70
3.6.1 Introduction
70
3.6.2 Methods
71
3.6.3 Results & discussion
74
3.7 Summary & conclusions
120
4. Water quality
122
4.1 Introduction
122
4.2 Background
122
4.3 Water quality surveys
128
4.4 Development of estuarine water quality indices
130
4.4.1 Selection of variables of concern
130
4.4.2 Development of rating curves
133
4.4.3 Variable weighting
134
4.4.4 Formulating and computing the water quality index
135
4.5 Results & discussion
136
4.5.1 Index testing
136
4.5.2 National results
138
4.5.3 Regional results
140
4.6 Conclusions & recommendations
148
4.6.1 Conclusions
148
4.6.2 Recommendations
149
5. Aesthetics
150
5.1 Introduction
150
5.2 Methods
151
5.3 Results & discussion
153
5.4 Summary & conclusions
160
6. General summary & recommendations
161
6.1 Introduction
161
6.2 Summary
162
6.3 Recommendations
164
7. References
180
8. Appendix 1
185
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ACKNOWLEDGEMENTS
We would like to express our thanks to the Department of Environment affairs and
Tourism (DEA&T) which provided funding for this project. In particular we would
like to thank Dr Rudi Pretorius for his support throughout the course of this project.
Alexcor, Algoa Regional Services Council, Amatola Regional Services Council, De
Beers, Department of Water Affairs & Forestry, Eastern Cape Nature Conservation,
KwaZulu-Natal Nature Conservation Services, National Parks Board, Western Cape
Nature Conservation and Western Cape Regional Services Council are thanked for
granting permission to carry out the surveys and for logistical support.
We would also like to thank John Allen, Jerome Andrew, Iaian Bickerton, Alan Blair,
Keith Blair, Paul Cowley, Roland David, Sean Fennessey, Brian Fowles, Tim Maera,
Darrel Matodes, Stuart McLeod, Emile Plumstead, Arjoon Singh, Heath Thorpe, Mike
Webster and Alan Whitfield for their assistance during the field studies.
For
assistance in the laboratory, thanks are due to Iain Bickerton, Alan Blair, Michelle
Binedell, Eve Boettiger, Basil Clarke, Allan Connell, Roland David, Sean Fennessey,
Sabelo Gumede, Bruce Mann, Shamilla Pillay, Leslie Power, Liz Simpson, Murray
Simpson, Arjoon Singh, Avendhra Singh, Natasha Stoltz, Heath Thorpe, William
Underwood, and Mark Zunckel. We are also grateful to Dr Phil Heemstra from the
JLB Smith Institute of Ichthyology for the identification and verification of fish
specimens. Thanks are due to Dr Bob Clarke and Dr Richard Warwick from the
Plymouth Marine Laboratory for their assistance in the multivariate analyses using
PRIMER. Arjoon Singh is thanked for generating the figures.
Finally, we would like to thank the CSIR, in particular the Division of Water,
Environment and Forestry Technology (Environmentek), for its support throughout
this project.
vii
1.
INTRODUCTION
The South African coast is well endowed with estuaries and in many areas they form
an important element of the coastal zone ecologically, economically and culturally.
Estuaries are, however, more than simply discrete elements of the coastal zone. They
form an interface between the terrestrial drainage system and the sea and are thus
susceptible to changes far inland in the coastal hinterland. In addition, estuaries can
be viewed as the landward extension of the marine ecosystem, and are thus also
influenced by conditions at sea.
The transitional position of estuaries means that they are subject to a diverse range of
factors that influence their function, importance, and state. The value or status of an
estuary or group of estuaries can be assessed from many different perspectives (e.g.
ecological, socio-economic, cultural). An indication of an estuary’s condition might
be regarded as not only indicative of the estuary itself but to a certain extent of the
health of its hinterland and the adjacent marine environment.
To determine the health of an estuary, a wide variety of approaches could be taken,
depending on one’s perspective, scale of interest, or area of responsibility. Such an
assessment usually requires some baseline or reference against which to measure the
current state and to monitor improvement or degradation. However, little or no
scientific information exists on many South African estuaries and hence the potential
for holistic estuarine management was much curtailed.
The objectives of this study were (i) to conduct multidisciplinary basic surveys of
South Africa’s estuaries using a consistent protocol for sampling and analysis and (ii)
to compile these data in such a form that the status of estuaries could be ascertained at
regional and individual levels. This report and the data acquired in its compilation
represents the most comprehensive assessment and collection of baseline data on
South African estuaries yet undertaken. The data can be accessed at a variety of levels
from precise data on each individual system to condensed and simplified data on
groups of estuaries or estuaries within a particular region.
1
An approach to the
assessment of South Africa’s estuaries and the presentation of that information in a
useful format for managers with a variety of interests and areas of responsibility is
outlined in this report.
The final representation of data in the form of indexed strip map information is
intended as a guide to the status of the estuary at the time that it was sampled. The
structure of the index means that the estuary is being compared with others that are
similar to it and thus its status may be regarded as an absolute measure.
It is
cautioned, however, that simplification of data may mask details that exists in the data
pertaining to an individual system. While this is a necessary sacrifice in order to gain
a regional or national perspective on estuary status, the regional data should be
interpreted only in an indicative way. For example, a low water quality score in one
of the water quality categories might be regarded as indicative of a potential problem
and might require further investigation to determine its persistence.
This research is based on seven years of intensive field sampling during which some
250 estuaries were visited between the Orange (Gariep) and Kosi Bay. At each
estuary a suite of geomorphological, ichthyological, water chemistry and aesthetic
measurements were made in a consistent manner. These data are recorded on a CSIR
database. In addition, preliminary reports on the status of each individual system were
compiled on a regional basis at the conclusion of each year’s fieldwork. These reports
(Cooper et al., 1993, Harrison et al., 1994, 1995, 1996, 1997, 1998) each deal with
about 50 estuaries that were sampled each year and contain further information on
individual systems as well as a preliminary index assessment of the status of each
system. Because the reports were based on purely practical constraints of resource
availability that determined a 50 estuary per year sampling strategy, they did not
explicitly take account of the biogeographic variability of the coast. In addition, each
year effectively extended the available database and yielded findings that influenced
the interpretations in the previous reports. This summary report which condenses the
findings of previous reports, and attempts to take a national perspective on estuarine
status and variability, takes account of biogeographic constraints and utilises the full
dataset available in an attempt to address the status of South African estuaries.
2
This report is divided into several sections dealing with specific, linked elements of
the estuarine environment. Firstly, the geomorphology is addressed which provides
the physical basis for variability between estuaries, secondly, the fish communities
collected in estuaries is discussed and interpreted, thirdly, the water quality parameters
measured in the field are described and interpreted and fourthly, the aesthetic
parameters as assessed in the field are detailed. In the final analysis these data are
amalgamated to produce a composite index that provides an indication of the health of
each estuary relative to others of the same type.
In this report a geomorphological classification of each of the estuaries sampled is
presented. This enabled the recognition of several types of estuaries which then
permits individual systems to be properly compared with physically similar estuaries.
This is a necessary prerequisite such that estuaries of vastly different characteristics
are not compared with each other. The specific types of estuary identified are then
considered from a fish community perspective. A set of fish expectation criteria was
drawn up for each type of estuary, against which actual fish communities could be
compared and assessed. The water quality parameters measured in each estuary are
transformed from their original units to comparable scales and grouped to reflect
suitability for various uses (human contact, aquatic life and trophic status). An
aesthetic assessment was undertaken based upon a combination of factors related to
the estuary floodplain, its surrounds and the water surface of the estuary and assesses
the deviation from natural conditions.
In this report, a level of depiction of estuarine status has been selected that enables the
four parameters to be assessed and some of these to be sub-divided.
The
geomorphological type of an estuary is identified so that its condition relative to
others may be assessed. The fish community data is reduced to a three-factor index of
health as reflected in the fish fauna, the water quality is expressed as a three-factor
index of water suitability and the aesthetic data is presented as a single value figure of
deviation from natural conditions. The objective in doing this is to render baseline
data understandable to the non-specialist and to depict it at a sufficiently high level to
inform potential managers and users of the status of estuaries on the South African
coast.
3
Each of these parameters can be assessed at higher and lower levels than those
presented here, but the choice of depiction at this level is seen as a compromise
between detail and perspective such that large strips of coast can be assessed at a
suitable level of detail without losing the regional perspective. This report is designed
as an aid to coastal zone management; by reference to it, the relative status of
estuaries can be assessed on the basis of data collected during these surveys.
Identification of potential problems is aided by the presentation of the information at
an interpreted level rather than as raw data. This does hold a number of advantages
and also several disadvantages and in terms of the latter, several points should be
stressed. These are outlined below.
The geomorphological classification presented is based on available data, which is in
many cases, insufficient to classify an estuary to the highest level of resolution, thus
some variation may exist among the groups identified. Additional information is
required to enhance this classification and enable finer levels of subdivision.
The fish community structure is based on a comprehensive sampling programme at
each site. It is, however, recognised that these one-off sampling exercises may yield
anomalous results under certain circumstances (recent floods, breaches, etc). This is
an unavoidable constraint, imposed by sampling many systems in a short period.
The water quality data were collected at an instant in time and may therefore not be
representative of long-term conditions, or of episodic events in estuaries. Again, this
is an unavoidable effect of large spatial scale sampling.
In each instance, the information presented provides a baseline against which to
monitor change and to assess future trends.
In every instance, more detailed
information is held by the authors in a raw data form.
The report should be regarded as an indicative guide to the status of estuaries around
the South African coast and it is hoped it will identify actual and potential
environmental problems and assist in planning future monitoring and research needs.
4
2.
GEOMORPHOLOGY
Geomorphic variability among microtidal South African estuaries: a conceptual
classification
2.1 Introduction
The study of the geomorphology of estuaries examines the link between estuary form
and the processes that operate within it. It seeks to describe the morphology of
individual estuaries and groups of estuaries and to examine variations in the present
configuration of estuaries and to seek explanations of this variability in the potential
controlling factors.
In South Africa the range of controlling variables is highly
diverse, as the subcontinent spans a number of climatic and morphological zones and
is subjected to a range of marine conditions, however, there are several factors that
may be regarded as virtually constant around the coast. These include the relatively
low tidal range, high wave energy (although a gradient does exist), the predominantly
bedrock coast (lacking a coastal plain) and a consistent sea level history. Variability
in factors that contribute to estuary morphology arises from climatic variation (arid to
humid and subtropical to cold temperate), discharge variation in rivers, hinterland
gradient and coastal gradient, sediment supply rates from rivers, sediment type
supplied from rivers and sediment availability in the coastal zone. The range of
variation among these and other factors potentially produces a wide range of estuary
types.
An estuary has been defined (in a South African context) as ‘a coastal body of water
in intermittent contact with the open sea and within which sea water is measurably
diluted with fresh water from land drainage’ (Day, 1980). This definition which is a
variation on that of Cameron & Pritchard (1963) seeks to take account of the nonpermanent nature of many South African estuary mouths. In doing so it also includes
a number of systems that may be regularly hypersaline or even dry for prolonged
periods.
Since such systems are inhospitable for most forms of life normally
associated with estuaries, (although notably not necessarily the avifauna) they are best
regarded as distinct from estuaries. This is not to say that they have no importance,
5
but rather to recognise them as environments distinct from estuaries and operating in
quite a different manner.
Estuaries have long been recognised as an important element in the coastal
geomorphology of South Africa. They are numerous and frequently are the focus of
sand accumulations (sand barriers) that have achieved great importance as foci of
recreational activity (often in conjunction with the adjacent water bodies both
landward and seaward of the barrier).
Estuaries too have achieved recognition
through their ecological importance and are widely regarded as critical in terms of
their contribution to marine fish and invertebrate stocks. As habitats in themselves
they have received less attention, although in recent years much more attention has
focused in this area of research.
One of the major areas of importance among
estuaries is in their contribution to the large marine ecosystems of the South African
coast. When this perspective is taken and estuaries are regarded as a component of
large marine ecosystems, their contribution in terms of nutrient sinks and sources is
readily appreciated, particularly on the east coast of the subcontinent.
Geomorphologically, estuaries occupy a transitional position between land and sea
and act as an interface between terrestrial and marine environments. As such they are
affected by variations in the intensity of both sets of processes. This renders many
estuaries highly dynamic environments in which geomorphological change may occur
at timescales that range from almost instantaneous (as for example during floods) to
progressive change due to sediment infilling and sea level rise. In all estuaries an
interface exists between fluvial and marine processes, although the nature and
intensity of processes operating at this interface may vary considerably.
In some
systems sea water may extend many kilometres upstream while in others it may be
restricted to inputs from barrier overwash and be confined to areas adjacent to the
barrier. A strong seasonal imprint exists in some estuaries such that they may be tidal
for long distances during the dry season and freshwater extends right to the barrier (or
beyond) during floods (Day, 1981a). In others a seasonal imprint is produced by
variation between closed conditions in the dry season and open conditions during the
rainy season.
6
In a sedimentological context, sediment that moves seaward from rivers must pass
through an estuary and vice versa. Estuary morphology is likely to reflect the relative
balance between these two competing sets of processes. The seaward transfer of
sediment from rivers is not constant in time or space. Those that have steep readily
eroded hinterlands are more likely to yield large quantities of sediment than those that
are better vegetated and less steep. The former are more likely to fill their estuaries
with fluvial sediment than the latter. Sediment moving landward from the sea into
estuaries is a common phenomenon and is driven by the tidal asymmetry that exists in
constricted inlets. These inlets have a shorter duration and hence faster current regime
during flood tides than ebb tides and thus sediment accumulates preferentially in the
estuary in the form of a flood-tidal delta. In many instances, these flood-tidal deltas
gradually extend upstream. In others they are poorly developed or absent entirely.
Estuaries are widely regarded as sinks (net accumulation zones) of sediment. They
receive sediment from a variety of sources including marine and fluvial inputs as well
as detritus from fringing vegetation, material (mainly organic) generated within the
estuary itself, aeolian sediment input and human-induced inputs. Estuaries are thus
regarded as areas that should exhibit progressive shallowing and reduction in area.
This is in fact not always the case. Floods periodically scour estuaries and remove
accumulated sediment thus ‘resetting the evolutionary clock’.
In addition, some
estuaries function mainly as ‘conveyor belts’ by which excess sediment is transferred
through them and deposited in the sea (such systems have no capacity to accumulate
additional sediment).
In all estuaries, the presence and persistence of a mouth that permits a surface water
connection between the estuary and the sea is dependant on the relative strength of
surface currents (which act to maintain the mouth) and wave and tidal currents in the
nearshore zone (which act to close to mouth by depositing marine sand in it). In some
instances mouth-forming processes dominate over mouth closing processes and vice
versa. The situation is variable with time. The persistence of a mouth has importance
for the migration of flora and fauna between the estuary and the sea and this might
thus be regarded as one of the key factors in producing variability between estuaries.
7
To conclude, there is wide geomorphological variability between the estuaries of
South Africa in spite of the commonality of several factors that produce variability
worldwide. In order to make sense of the observed variability it is necessary to
classify systems to remove the inherent ‘noise’ that obscures the reasons for the
variation between systems. ‘Without classification one cannot hope to remember or
manipulate the individuals or see relationships between them’ (Van der Eyk et al.,
1969). To this end a classification that encompasses the range of variability observed
in South African estuaries is presented in this report.
2.2 Coastal setting
The South African coast is highly variable geomorphologically and climatologically.
These two main categories of variability contribute much to the variation between
estuaries that exists at the present time. There are, however, a number of variables
that do not vary so considerably and may be regarded as consistent for the purposes of
this chapter.
The tidal range around the South African coast varies comparatively little with most
areas experiencing a spring tidal range between 1.8 and 2.0 m. Neap tides are
typically between 0.6 and 0.8 m, rendering the coast microtidal (Davies, 1980).
Wave energy is also consistently high around the South African coast, although a peak
in wave heights is evident in the southern Cape and wave height diminishes northward
along both the east and west coasts. Even in the NE and NW coasts, wave height is
great compared to other areas and the entire coast is regarded as a high energy, swelldominated environment. A further common factor is that almost all estuaries in South
Africa are located in incised bedrock valleys and thus are laterally confined. Some
estuary channels fill their entire bedrock valley while others have a substantial
floodplain, but most are nonetheless confined by their bedrock valley. Only a few
examples of coastal plain estuaries (i.e. estuaries formed in semi-consolidated
alluvium on coastal plains) are present on the South African coast. These are mainly
confined to northern KwaZulu-Natal and to the Wilderness Lakes area and in both
instances produce estuaries that are linked to substantial water bodies (coastal lakes).
8
Factors that contribute to variability among estuaries around the South African coast
include catchment size and gradient, fluvial sediment supply, marine sediment
availability, climate and fluvial discharge. The South African coastal hinterland is
typically gently sloping in the west and very steep in the east, with the south coast
exhibiting variations in gradient according to whether mountain ranges intersect the
coast or not. The hinterland gradients on the east coast are among the steepest found
in the world.
Climatologically, the subcontinent may be divided into several zones. The east coast
is a subtropical humid zone that experiences a peak in summer rainfall. The west
coast is a highly arid zone with extremely erratic rainfall. The south coast experiences
varying rainfall regimes with some areas exhibiting a summer peak and others a
winter peak and some are bimodal (Heydorn & Tinley, 1980). A consequence of this
climatological variability is a variation in rainfall and river runoff. If considered on a
runoff per km2 basis around the coast, the range of variability is clearly seen.
While wave energy is high everywhere around the coast there is a gradient of wave
energy that decreases from south to north along both the east and west coasts. Waves
are predominantly of the deep sea swell type but localised sea waves are also
produced by local winds. An effect of the variability in wave energy is the linked
variation in beach profiles. Generally, beach profiles become steeper as wave energy
diminishes, thus the high wave energy of the southern Cape produces wide, gently
sloping beaches with offshore bars while the lower waves of KwaZulu-Natal and
Namaqualand produce characteristically steeper and narrower beaches with high
berms.
2.3 Estuaries: Introduction to a conceptual classification
A hierarchical classification is presented below, based upon the main forms of
morphological variability among estuaries of the South African coast. At the highest
level, the major variation between estuaries is based upon the frequency of connection
with the sea, via a surface channel. This immediately divides estuaries into those that
are normally open and those that are more commonly closed by a barrier. This
division, which is theoretically entirely gradational, appears in practice to identify two
9
groups of estuary. In KwaZulu-Natal, where the most extensive set of observations on
frequency of mouth opening exists, estuaries divide clearly into those that are open
more than 70% of the time and those that are open less than 30% of the time. There is
clearly longer term variability in this as drought cycles (Tyson, 1987) are more likely
to be associated with reduced freshwater discharge and may cause estuaries to close
for longer periods in drought years
The categories normally open and normally closed will be discussed below and
further subdivisions are described within these two major categories, based upon
geomorphological behaviour of various types of system.
2.4 Open estuaries
Those systems that are normally open display marked variability in size and in mouth
dynamics. They are subdivided into systems that are essentially unbarred (i.e. they
lack a sand accumulation at the mouth that is exposed above high tide) and those that
have a supratidal barrier with a surface drainage channel. Further subdivisions may
be made on the basis of the size of the individual estuary.
2.4.1 Barred open estuaries
Barred estuaries (those with a supratidal barrier) vary markedly in size and in the
volume of fluvial discharge. Since the volume of the bedrock valley in which the
estuary is formed is largely dependent on the amount of fluvial discharge.
Barred estuaries that are normally open range in discharge from small, localised
stream catchment systems to large systems such as the Orange (Gariep), Great Fish
and Tugela (Thukela) that drain large sections of the subcontinent. A division into
several size categories can be made but for the purposes of this report a division was
selected at a Mean Annual Runoff (MAR) of 15x106 m3 based on the complete
distribution of systems of variable discharge volume.
The smaller systems are
incapable of maintaining large tidal prisms and are thus maintained in an open
condition by river discharge. This is often assisted by the outlet configuration; in
many cases e.g. Zotsha where a bedrock ledge permits enhanced scouring. Such
outlets frequently form in the lee of a headland where wave energy is reduced. These
10
systems seldom exhibit a flood tidal delta and many appear to operate almost
exclusively as outlet channels. Estuarine characteristics are however imparted by the
frequency of overwashing and by occasional surges that increase tidal penetration into
the estuary. These systems tend to have short barriers that reduce the volume of
discharge that can be accommodated by seepage through the barrier such as was noted
in the barriers of SE Ireland by Carter & Orford (1984).
The larger typically open estuaries span a range of discharge characteristics and are
divisible into two types.
Those systems that have insufficient tidal prisms to maintain an inlet against
nearshore wave and tidal action, may arise through either pre-existing morphological
constraints (steep gradient, high sediment supply during transgression and narrow
bedrock valleys) or through sedimentation and infilling of formerly tidally maintained
systems. These systems are especially well developed in KwaZulu-Natal and have
been termed ‘river-dominated’ estuaries (Cooper 1993a,b; Cooper et al., 1999)
(Figure 2.1). Morphologically these systems differ from tidally dominated systems
and in them flood-tidal deltas are much reduced in size or absent. Fluvial sediment
typically extends to the barrier and tidal inflow is frequently minimised by elevated
bed levels. Under lower wave energy conditions these systems would probably form
deltas, but the only example of such a delta on the South African coast are those of the
Orange (Gariep) River (submerged) (Van Heerden, 1986) and the Tugela (Thukela)
and Berg which have offshore mud depocentres and a series of beach ridges located
north (downdrift) of the estuary mouth. River flow in such systems is critical to the
maintenance of an outlet channel. Under drought conditions such systems may close
for prolonged periods. The impacts of impoundments are especially noteable in these
types of systems. For example, The Mgeni estuary which was formerly open for more
than 90% of the year is now closed for prolonged periods since the completion of
Inanda Dam, some 35 km upstream of the mouth. Stratigraphical evidence suggests
that many river-dominated systems have been in such a state throughout much of the
Holocene period (Cooper 1993a). While many of these systems have relatively large
surface areas, many are comparatively short, due to the steepness of the hinterland and
this limits tidal penetration.
The role of floods in these systems is important in
11
eroding accumulated sediment and temporarily deepening the channel (Cooper et al.,
1989).
Erosion during extreme floods appears to be distributed throughout the
channel and even cohesive sediments may be eroded. The Mgeni for example in 1987
lost an entire, vegetated and mangrove-fringed island from its lower reaches as a
result of a flood.
12
Figure 2.1. Diagram of river-dominated barred estuary morphology showing plan (A)
and cross-sectional (B) perspective. Note the extension of riverine bars to the barrier
and the small extent of flood- and ebb-tidal deltas.
13
Those systems maintained by tidal flow are recognisable by virtue of a distinctive
morphology (Figure 2.2). They have well developed, often transgressive flood-tidal
deltas (Reddering & Esterhuysen, 1981; Cooper, 1993c). This is accomplished as a
result of flood-dominance at the tidal inlet and by the enhanced suspension of
sediment by wave action, that is then entrained on the flood current. Wave action
does not assist in the return flow and thus net accumulation takes place. Landward is
a relatively deep section characterised by fine-grained sedimentation, and upstream is
a coarse grained fluvial delta that progrades into the estuary, gradually reducing its
volume. Floods in such systems serve an important geomorphological function in
removing accumulating flood-tidal deltas
Tidally maintained systems may close through the effects of extreme marine events.
Kosi Estuary with a tidal prism in excess of 350 million m3, has closed (on August 17
1965) and this was probably as a result of a storm event. After tropical cyclone
Claude (in January 1966), water levels rose by 1.6 m (Breen & Hill, 1969). The
system, however, did not open of its own accord and was artificially opened to save
the mangrove community. Smaller tidally maintained outlets may close as a result of
less intense storms as the tidal flow that is required to be overcome is smaller. These
systems may then be reopened by renewed freshwater discharge that re-establishes the
tidal inlet and permits tidal currents to be reinstated.
It is important to note that tidally dominated systems have the capacity to evolve into
river-dominated systems but that some estuaries are river-dominated by virtue of their
geomorphological location. For the purposes of this report river- and tide-dominated
systems have not been subdivided, mainly because of the relatively few numbers of
estuary in each type when subdivided by biogeographic zone. Because of a lack of
data on distinguishing attributes the large open systems which have been grouped here
do exhibit some morphological variability in terms of floodplain development and the
extent of open water area and depth (and by implication stratification/circulation
parameters). Further subdivision of the group will require gathering of such data and
will enable future refinement of the existing classification.
14
Figure 2.2. Diagram of tide-dominated barred estuary morphology showing plan (A)
and cross-sectional (B) perspective. Note the extensive flood-tidal deltas which may
show landward progradation, and the small ebb-tidal delta which is confined by high
wave energy. The fluvial delta upstream marks the limit of progradation of coarsegrained riverine sediment.
15
2.4.2 Non-barred open estuaries
Several estuaries exist within drowned river valleys that have either no sand
accumulation at their outlet (e.g. Storms River mouth) or have a barrier that is only
intertidally exposed and is in effect the upper surface of a flood-tidal delta. These
systems (Figure 2.3) are relatively uncommon and are largely restricted to rocky,
cliffed coastal sections that have limited sediment supply. Thus while they may have
relatively small surface areas and small tidal prisms they maintain permanent contact
with the open sea. One large variation on this type of system exists (Knysna estuary,
Reddering & Esterhuysen, 1987a). This has a large tidal prism but a paucity of
sediment at the estuary mouth precludes closure of the tidal inlet.
16
Figure 2.3. Diagram of non-barred estuary morphology showing plan (A) and crosssectional (B) perspective. Note the intertidal barrier that is submerged at high tide and
emergent at low tide. In such systems insufficient sediment is available to permit
mouth closure. The fluvial delta upstream marks the limit of progradation of coarsegrained riverine sediment.
17
2.5 Closed estuaries
The normally closed estuaries of South Africa span great variation in size from tiny
systems of <0.2 hectares surface area to systems such as the Bot and Klein that are
over 1200 hectares in area. Two main forms of behaviour are exhibited by these
systems, based on whether the back-barrier water level is higher than open sea tidal
levels or within the range of open sea tidal elevations. This in turn is related to the
elevation of the berm crest of barriers that enclose these systems. These normally
closed systems may be subdivided into perched and non-perched categories. These are
discussed below.
2.5.1 Perched closed estuaries
Those systems that have a high berm, produced as a result of coarse grained barrier
sediment and relatively low wave energy (in a South African context) impound water
levels behind them at elevations above the levels of most high tides. The enclosed
water bodies exhibit a long term balance between inputs from freshwater inflow,
barrier overwashing and rainfall, and outputs via evaporation, seepage and
evapotranspiration by fringing vegetation (Figure 2.4).
Vegetation within such
systems is typically graded to a perched water level, as is sedimentation such that the
bed of the estuary may be elevated above tidal levels. In such instances tidal inflow
during open phases is precluded (Huizinga, 1994). Breaching occurs in such systems
when inputs via overwash and freshwater discharge exceed outputs and a surface
channel is cut to permit discharge.
When this occurs, the elevated water level
provides a marked hydraulic head and rapid downcutting occurs into the berm (its
depth is dependent on the state of the tide when breaching occurs). Under such
conditions such systems may drain within a few hours and a formerly large surface
area is reduced to a narrow shallow channel through which fluvial discharge is
effected. Barrier breaching of such systems typically deposits an ephemeral delta from
which sediment is eroded and transported by cross-shore transport to close the breach,
whereafter the estuary fills and attains equilibrium once again (Cooper 1989, 1990).
Salinity in such systems is typically lowered and may even be totally fresh, dependent
on the volume of overwash received.
18
Figure 2.4. Diagram of perched normally closed estuary showing cross-sectional (AD) and plan (E) views. Under balanced conditions (A), the stream inflow is matched
by evapotranspiration and seepage. Overwashing (B) may elevate water levels and
salinity and increased streamflow (C) may promote breaching. When breached (D)
the water levels are lowered and tidal flow may take place if the berm level is
sufficiently low. In plan view (E) the difference in water area during open and closed
conditions is evident.
19
2.5.2 Non-perched closed estuaries
Those systems that do not have a high berm but which lack a common surface channel
are impounded at or close to high tide level (Figure 2.5). The beaches that front these
systems have a dissipative (low gradient) profile and are characterised by wide surf
zones. The lack of a berm and high wave energy means that barrier overwash is more
frequent in these systems and consequently they are typically saline. In addition, in
areas of low coastal gradient saline influences may extend for 10 km upstream even in
the absence of tidal inflow. These systems often exhibit salt marsh vegetation as a
result. No definitive study has been undertaken of this type of system, however, a
number of observations over the past 10 years by the authors permit some insights to
be gained on their behaviour. Following increased fluvial discharge, these systems
may form a surface connection with the sea. This may happen relatively frequently as
the barrier is close to sea level and thus saturated which precludes seepage. When a
surface channel forms it is typically shallow and broad and forms a braided pattern on
the barrier surface. Water depths are typically a few centimetres as downward scour
is precluded by the low water level in the enclosed estuary.
When such systems begin to experience reduced water levels through drought,
landward seepage may occur as evidenced by rill marks and microchannels and deltas
on the landward slope of the barrier. In some instances these systems have been
known to become hypersaline. The large surface areas of such systems coupled with a
strong wind regime means that the water column is frequently well mixed. Since the
surface channels are typically very shallow, tidal inflow is also reduced, although
evidence of flood-tidal delta morphology in some systems of this type does suggest
that under certain conditions (probably associated with positive surges and/or low
estuary water levels), tidal inflow may occur. A characteristic of these systems is the
constancy of their water area and volume which provides a more stable habitat than
the perched systems.
20
Figure 2.5. Diagram of non-perched and normally closed estuary in cross-section (AC) and plan (D) view. Under balanced conditions (A) streamflow is balanced by
losses through evapotranspiration and seepage. Under high wave energy (B)
overwashing introduces marine water into the system. Under enhanced inputs from
overwashing (B) or streamflow (C), the system may breach. The depth of incision is
low since the estuary water level is so close to sea level. In plan view (D) the
consistency of surface water area between open and closed phases is clear.
21
Although individual systems may be identified as perched or non-perched lagoons, it
is not possible with existing data to classify every system according to this division.
For the purposes of this report, a subdivision of normally closed systems was however
made according to whether they had a surface area greater or less than 2 hectares.
Although this introduces a group of larger systems that is highly diverse in terms of
size, the low numbers of systems in each biogeographic zone mitigates against further
subdivision.
2.6 Discussion
The hierarchical classification system for South African estuaries is shown in Figure
2.6. The first subdivision is made on the basis of whether a stream outlet constitutes
an estuary or not. Non estuaries were selected on the basis of permanent separation
from the sea, very small size, ephemeral surface water and/or hypersalinity, and if they
were waterfalls. For the remaining systems an estuarine function was determined on
the basis of periodic communication with the sea and the permanent occurrence of
fresh to brackish surface water in the estuary. These systems were then divided on
whether they were normally open or normally closed.
Those that are normally open may be barred or non-barred and outlets in the barred
variety may be maintained by tidal prisms or river discharge thus defining river- and
tide-dominated systems. In this report, the two types are not identified but the barred
systems are subdivided on the basis of whether their mean annual runoff exceeds or is
less than 15 million cubic metres.
The systems that are normally closed were subdivided on the basis of surface area
with the division placed at 2 hectares. While a further subdivision is recognised it
cannot be implemented with the current level of knowledge and thus perched and nonperched systems are grouped in this report. Since there is however, a likely regional
element to the distribution of perched and non-perched systems according to wave
height, the subdivision of the coast into biogeographic zones may incorporate, at least
partly, this division.
22
Figure 2.6. Conceptual hierarchical classification scheme for South African estuaries
based on the range of estuaries present. This identifies the types of estuaries and
processes operative within them. At the present time it is not possible to categorise
every estuary to the lowest level of the hierarchy illustrated. A practical alternative is
shown in Figure 2.7.
2.6.1 Practical classification
Whereas the above account provides an assessment of the range of estuary types
present in South Africa on the basis of the major geomorphological features and
physical behaviour, it is not presently feasible to categorise every estuary to the finest
subdivision recognised. Insufficient data are available on, for example, water level
and barrier elevation to categorise normally closed systems into perched and nonperched types. This would require a targeted assessment of the barrier condition of
each system under ‘normal’ conditions. To ascertain whether tidal inflow occurred
during open phases would require additional assessment during open periods which
occur infrequently and irregularly in such systems.
Similarly, while the variability
between river and tide-dominated open systems is obvious in many instances
(evidenced by, for example, the presence of riverine braid bars right to the estuary
barrier in some river-dominated systems), the division between the two estuary types
cannot readily be made in all cases. A further difficulty arises in the identification of
‘normal’ or most common conditions in estuaries. In KwaZulu-Natal where data are
available a clear division seems to exist between normally open systems and normally
23
closed systems. Where this information does not exist, a subjective judgement made
on the basis of historical accounts, geomorphology and aerial photographic evidence
must be made. This situation may change in the future, but for the present, available
indicative data coupled with empirical information has been used. It is possible
therefore, that in the light of future data some systems may change classification.
Further it is to be hoped that the additional data necessary to more closely classify all
of the normally open and normally closed estuary types to the finest subdivisions
recognised above will eventually be available.
In addition, the classification presented above takes account of variations in processes
operative in each type of system but does not identify potential variations in habitat
that may arise on account of variations in estuary size. For these reasons, in addition
to the data limitations outlined above, it has been necessary to employ a modified
classification scheme (which is limited by data availability) in this report (Figure 2.7).
Figure 2.7. Classification of South African estuaries based on available data. Since
inadequate data exists to subdivide to the finest levels of detail identified above
(Figure 2.6) the barred open estuaries were subdivided according to their Mean
Annual Runoff into groups E and F. Non-barred estuaries were readily identified
(Group D). Normally closed systems were subdivided on the basis of surface area
into very large (Type C), large (Type B) and small (Type A) systems. The estuaries
assigned to each group are listed in Table 2.1.
24
This scheme follows that outlined in Figure 2.6 as far as the open/closed division.
Thereafter only the non-barred type of system is fully identified. The closed systems
are subdivided on the basis of their surface area into three groups, one (Type A)
comprising those systems smaller than 2 hectares, a second (Type B) those between 2
and 150 hectares, and a third (Type C), those over 150 hectares. These subdivisions
were made on the basis of identified gaps in a frequency distribution chart of all
closed estuaries studied. The open systems were subdivided into the non-barred
systems (Type D) but excluded from this grouping were the rare large systems that
lacked a barrier (Knysna, Msikaba and Mtentu). These were included with the barred
estuaries. The barred open estuaries were subdivided according to a well-defined gap
in the frequency distribution of Mean Annual Runoff (MAR) values, with a group of
smaller systems recognised that had MAR values less than 15x106 m3 (Type E) and a
group of systems that had larger values (Type F). The mouths of those in the smaller
category are almost certainly all maintained by freshwater discharge as their small size
precludes the development of a sizeable tidal prism. They are therefore of the riverdominated type. Those in the larger category comprise a combination of tide- and
river-dominated systems and some that vary seasonally between the two modes of
behaviour (for example, Breë, Berg).
The estuaries of each type are listed below in Table 2.1. This listing is based on the
entire number of systems sampled and is not subdivided according to biogeographic
zones. It excludes those systems that were not considered estuaries on the basis of
very small size, regular dry or hypersaline back-barrier conditions, extensive human
modification or which were permanently isolated from the sea, either by a permanent,
continuous barrier or by a sea cliff. A number of systems were, however, not
sampled in the course of this research and omission of those systems from this list
does not imply that they are not estuaries. In the Transkei area, for example, only
about a third of known river mouths were sampled; the remainder have not been
classified.
25
Table 2.1. Grouping of estuaries according to their geomorphological classification.
Type A
Houtbaai
Schuster
Silwermyn
Klipdriftfontein
Noetsie
Matjies
Klipdrif (Oos)
Slang
Maitland
Thatshana
Lilyvale
Hlozi
Blind
Hlaze
Cunge
Imtwendwe
Mtendwe
Ncizele
Sundwana
Thsani
Gxwaleni
Mvutshini
Kongweni
Damba
Mkumbane
Mzimayi
Type B
Verlore
Diep
Wildevoel
Krom
Sand
Kleinmond
Blinde
Hartenbos
Touw
Groot (Wes)
Tsitsikamma
Seekoe
Kabeljous
Van Stadens
Boknes
Kasuka
Riet
Wes-Kleinemond
Oos-Kleinemond
Old Womans
Mpekweni
Mtati
Mgwalana
Bira
Gqutywa
Mtana
Ngqinisa
Kiwane
Ross' Creek
Ncera
Mlele
Mcantsi
Gxulu
Goda
Hickmans
Qinira
Cintsa
Cefane
Kwenxura
Nyara
Haga-Haga
Morgan
Gxara
Ngogwane
Qolora
Cebe
Zalu
Ngqwara
Mtentwana
Type C
Bot
Klein
Type D
Steenbras
Maalgate
Gwaing
Kaaimans
Sout
Bloukrans
Lottering
Elandsbos
Storms
Elands
Groot (Oos)
26
Type E
Lourens
Sir Lowry's
Rooiels
Buffels (Oos)
Onrus
Ratel
Piesang
Rufane
Ngculura
Shelbertsstroom
Bulura
Cwili
Jujura
Ngadla
Ku-Mpenzu
Ku-Bhula
Kwa-Suku
Ntlonyane
Nkanya
Nenga
Mapuzi
Mpande
Bulolo
Mtumbane
Ntlupeni
Butsha
Mgwegwe
Mgwetyana
Sandlundlu
Tongazi
Zotsha
Mhlabatshane
Mbokodweni
Mgobezeleni
Type F
Gariep (Orange)
Olifants
Berg
Eerste
Palmiet
Uilkraals
Heuningnes
Bree
Duiwenhoks
Goukou (Kafferkuils)
Gourits
Klein Brak
Groot Brak
Swartvlei
Goukamma
Knysna
Keurbooms
Kromme
Gamtoos
Swartkops
Sundays
Bushmans
Kariega
Kowie
Great Fish
Keiskamma
Tyolomnqa
Buffalo
Nahoon
Gqunube
Kwelera
Quko
Great Kei
Kobonqaba
Ngqusi/Inxaxo
Qora
Shixini
Mbashe
Xora
Mtata
Mdumbi
Sinangwana
Mngazana
Mngazi
Mzimvubu
Mntafufu
Msikaba
Mtentu
Mzamba
Table 2.1. cont.
classification.
Type A
Grouping of estuaries according to their geomorphological
Type B
Kandandlovu
Mpenjati
Umhlangankulu
Kaba
Mbizana
Bilanhlolo
Mlangeni
Mtentweni
Mhlangamkulu
Intshambli
Fafa
Sezela
Mpambanyoni
Mahlongwa
L.Manzimtoti
Manzimtoti
Sipingo
Mhlanga
Mdloti
Mdlotane
Zinkwasi
Siyai
Type C
Type D
Type E
Type F
Mtamvuna
Mzimkulu
Mkomazi
Lovu
Mngeni
Mhlali
Mvoti
Thukela (Tugela)
Matigulu/Nyoni
Mlalazi
Mfolozi/Msunduzi
St Lucia
Kosi Bay
It should be borne in mind in using this classification that it has been compiled for a
specific purpose and that it is based on the available data at the time of writing. It is
possible that some systems may prove to behave differently from what is suggested by
this data and future revisions may be necessary. The classification does, however,
provide a starting point for further research. Further, it is recognised that there is
considerable within-group variability due to additional factors that have not been
considered at this national scale. Estuaries within a group may exhibit variation in
salinity, for example according to the time passed since the last opening, or since the
last flood or marine storm – these factors are not included in the classification as they
are time-dependant and the classification is based on a time-averaged condition.
Physical factors such as floodplain dimensions in relation to estuary open water area,
length of shoreline, barrier length, barrier composition and back-barrier sediment type
are not considered and may indeed be responsible for habitat variation between
estuaries of a given type. While this is recognised as a source of variability, and may
aid in the further subdivision, the groupings presented are based on a value judgement
as to how far subdivisions should proceed. Endless subdivision is possible right down
27
to the extent of recognising each estuary as unique, while at the other end of the scale
all river points of contact with the sea, however infrequent, might be regarded as
estuaries. A balance has been sought between these two end points in compiling the
present classification.
The classification does reveal that much available knowledge pertaining to South
African estuaries is derived from studies of a limited range of system types and, for
example, identifies that studies of the behaviour of non-barred estuaries and nonperched closed estuaries are rare. Importantly it indicates that estuaries should not be
regarded simply in terms of progression along a single evolutionary path. A riverdominated estuary is not by definition less valuable or more degraded than a tidedominated system. Neither is a closed system, necessarily less valuable or more
degraded than an open system. In many instances these systems are behaving in a
predictable manner for the type of estuary they are and to envisage a hypothetical
estuary with deep middle reaches, a wide, permanently open mouth and non-turbid
waters as the pristine archetype is erroneous. A management strategy for estuaries
should ideally recognise the diversity of estuary types present and be based on
management targets for each estuary type. Certainly some may be deemed more
important than others in terms of their contribution to marine fish stocks, or
contributions of nutrients to the ocean and targets for these might be more stringent
than others, but each type of estuary (and indeed non-estuary) deserves a management
strategy based on its own mode of geomorphological and ecological functioning.
28
3.
ICHTHYOFAUNA
3.1 Introduction
Estuaries are typically shallow systems, sheltered from major wave action; they have
variable temperatures, salinities, turbidities and oxygen content and are among the most
productive of ecosystems on earth (Odum, 1983). By providing abundant food and shelter,
estuaries are utilised by a variety of fish species, which typically are composed of a mixture
of euryhaline freshwater species, species restricted to estuaries and euryhaline marine
species (Wallace, 1975; Blaber, 1985). A stenohaline marine component usually occurs in
the mouth area of most permanently open estuaries where the salinity does not fall below
that of sea water, but these are not generally considered part of the estuarine fauna
(Wallace, 1975). The most important function of estuaries with regard to fish is the
provision of nursery areas for species of marine origin. Of a total of 155 fish species that
are commonly associated with estuaries in southern Africa, 40% are marine species which
utilise estuarine systems as nurseries and/or foraging areas (Whitfield, 1998). Species that
live and breed in estuaries account for 27% of the total estuarine ichthyofauna.
Marine
species which occur in estuaries in small numbers but are not dependent on these systems
comprise 25% of the total estuarine-associated fish taxa. Freshwater species including
obligate catadromous eels (Anguilla) which utilise estuaries as transit routes between the
marine and freshwater environments comprise only 8% of the total (Whitfield, 1998). The
occurrence of both freshwater and marine vagrants in estuaries is largely determined by the
salinity tolerance of the various species.
The 3 000 km South African coastline has some 300 rivers entering the coastal zone ranging
from small estuaries which are only occasionally open to the sea to large, permanently open
systems (Heydorn, 1991). Despite the great variety and number of estuaries along our
coastline, a review of the available scientific information on individual systems revealed that
very little information exists on the vast majority of South Africa’s estuaries (Whitfield,
1995). During the period 1993 to 1999 basic ichthyofaunal surveys were conducted on
some 250 estuaries along the South African coast. The aim of these surveys was to improve
29
our state of knowledge on these systems and provide an assessment of the status of their fish
communities.
3.2 Ichchtyofaunal surveys
The ichthyofauna of South African estuaries between the Gariep (Orange River) estuary and
Kosi Bay was sampled over the period 1993 to 1999. Using information contained in
Heydorn & Tinley (1980), Whitfield (1995) and aerial photographs, the coastline was
divided into arbitrary sections, each containing approximately 40 estuaries. The estuaries in
each section of coast were sampled during the spring/summer period and a new section was
sampled each year until the entire coastline was covered. Due to logistics, only selected
estuaries were identified on the Transkei and KwaZulu-Natal coasts. Sampling began in
1993 starting at the Gariep estuary on the west coast and the final KwaZulu-Natal section of
coast was completed in 1998/9.
The ichthyofauna of the estuaries were sampled using a 30 m x 1.7 m x 15 mm bar mesh
seine net fitted with a 5 mm bar mesh purse and, where possible, a fleet of gill nets. Each gill
net had a range of mesh sizes and comprised three 45 mm, 75 mm and 100 mm stretch
mesh monofilament panels and were either 10 m or 20 m in length and 1.7 m deep. Seine
netting was carried out during daylight hours and was limited to shallow (<1.5 m deep),
unobstructed areas with gently sloping banks. Gill netting was generally carried out in deep
(>1 m) open, mid-channel waters with the nets being deployed in the evening and lifted the
following morning. In most cases only the larger, deeper systems could be sampled using gill
nets. The sampling effort undertaken in each estuary varied depending on the size of the
system, and usually took one to three days to complete. Sampling was generally carried out
until no new species were collected or until all representative habitats within each estuary
were sampled.
Specimens collected by seine netting were, where possible, identified in the field, measured
to the nearest mm standard length (SL) in the field, using a measuring board, and returned
alive to the system. A minimum of 25 specimens of the abundant species as well as those
specimens that could not be identified in the field were placed in labelled plastic bags and
30
preserved in 10% formalin for transport to the laboratory. Specimens collected in the gill
nets were identified, measured to the nearest mm SL and weighed in the field. During the
1993 surveys the fishes captured in each estuary were batch weighed to the nearest 100 g
using a Super Samson spring balance while from 1994 specimens were weighed to the
nearest 1.0 g using a Bonso model 323 balance. Specimens that could not be identified in
the field were preserved in 10% formalin in labelled plastic bags for transport to the
laboratory.
In the laboratory, specimens collected during the surveys were identified by reference to
Smith & Heemstra (1991) and Skelton (1993). A minimum of 25 specimens of the
abundant species were measured to the nearest mm SL and weighed to the nearest 0.01g
using a Mettler PJ 3000 balance. The remaining specimens were counted and batch
weighed. Voucher specimens were also sent to the J.L.B. Smith Institute of Ichthyology for
verification.
A total of 257 estuaries were visited, however, a number of systems particularly on the arid
west coast comprised nothing more than dry riverbeds. These included the Holgat, Bitter,
Brak, Dwars (Noord), Jacobsbaai, Lêerbaai, Fresh Water Poort, Blue Krans and ShweleShwele. Furthermore, a number of systems, due to their small size, were not considered to
be estuaries and were excluded from this study. These were the Buffels, Swartlintjies,
Spoeg, Groen, Sout (Noord), Jakkals, Wadrif, Papkuils (west coast), Dwars (Suid),
Modder, Bok, Silwerstroom, Sout (Suid), Bokramspruit, Booiskraal, Buffels (Wes), Elsies,
Mossel, Rooi, Meul, Grooteiland, Kranshoek, Crooks, Brak (south coast), Helpmekaars,
Klip, Witels, Geelhoutbos, Kleinbos, Bruglaagte, Langbos, Sanddrif, Eerste (south coast),
Klipdrif (Wes), Boskloof, and Kaapsedrif. A number of systems such as the Soutrivier,
Seekoe (south-west coast), Bakens, Papkuils (south-west coast), and Koega (Ngcura)
were also severely altered due to human activities. Fishes were not captured in some
systems (Mvubukazi, Ngqenga and Uvuzana) and these were also excluded from further
analyses.
31
3.3 Biogeography
3.3.1 Introduction
The occurrence and diversity of fishes in South African estuaries varies according to (a)
latitude (biogeography) and (b) the individual characteristics of each estuary (estuary type)
(Blaber, 1985). Marine species inhabiting southern African estuaries include tropical and
subtropical Indo-Pacific species, temperate endemic south coast species, temperate
eastern-Atlantic species and cosmopolitan species (Wallace, 1975; Wallace & van der Elst,
1975). As one moves from KwaZulu-Natal around the coast to the Western Cape,
estuarine fish diversity declines (Wallace & van der Elst, 1975, Day et al., 1981; Whitfield
et al., 1989). This is linked to the attenuation in the distribution of tropical species where
the fauna of estuaries in Transkei, KwaZulu-Natal and Moçambique are dominated by
subtropical and tropical Indo-Pacific species (Day et al., 1981). South of Transkei there is
a marked change and the percentage of tropical species decreases while that of endemic
species increases. Most of the species from the southern Cape are either endemic or cold
water forms from the south (Wallace, 1975; Wallace & van der Elst, 1975; Blaber 1981;
Day et al., 1981; Whitfield, 1983). Before attempting to characterise and assess the fish
community structure of South Africa’s estuaries, it is important that their biogeography be
taken into account. The aim here is to investigate the biogeography of the fish communities
of South Africa’s estuaries.
3.3.2 Methods
Since the individual characteristics of each estuary (estuary type) plays an important role in
determining the fish community structure in estuaries (Blaber, 1985), the estuaries from this
study were first grouped according to their geomorphological characteristics as outlined in
the previous chapter.
The assumption here is that estuaries in which similar
physical/geomorphological processes operate ought to produce similar habitats and thus
contain similar fish communities. Any differences in the fish communities of estuaries of a
particular type therefore ought to be due to biogeography.
32
Six basic estuary types were identified. Estuary types A, B and C are normally closed
systems ranging from small (Type A), medium (Type B) and large (Type C) estuaries based
on their surface areas. The remaining systems (Types D, E and F) were classified as
predominantly open estuaries and were divided into non-barred (Type D) and barred
(Types E and F) systems. The barred estuaries were further divided into small (Type E)
estuaries and medium to large (Type F) systems based on their MAR. Two estuary types
(Type C and D) were restricted in their geographical range and as a result were excluded
from this analysis. Only two estuaries, the Bot and Klein, belonged to type C and these
were located on the south-west coast. Type D estuaries were mainly restricted to the south
coast region.
The ichthyofaunal data for the remaining estuary types was analysed using multivariate
statistical procedures outlined by Field et al. (1982). A combination of hierarchical
agglomerative clustering and non-metric multi-dimentional scaling (MDS) was performed
using PRIMER, the Plymouth Routines in Multivariate Ecological Research package
developed at the Plymouth Marine Laboratory in the United Kingdom (Clark & Warwick,
1994). Multivariate methods compare two (or more) samples on the extent to which they
share particular species, at comparable levels of abundance. Multivariate techniques are
founded on similarity coefficients calculated between every pair of samples which then
facilitates a classification or clustering of samples into groups which are similar, or an
ordination plot in which the samples are ‘mapped’ (in two or more dimensions) in such a
way that the distances between pairs of samples reflect their relative similarity of species
composition (Clark & Warwick, 1994). The similarity coefficient used in this analysis is the
Bray-Curtis (ISBC) measure:
ISBC = 2c/A + B
Where c is the sum of the smaller (abundance/biomass) values of the species common to
two samples; A is the sum of the (abundance/biomass) values of all the species in the one
sample, and B is the sum of the (abundance/biomass) values of all the species in the other
sample. The reason why only the smaller values of the common species are used is because
33
only the smaller value is contained in or is common to both samples (Mueller-Dombois &
Ellenberg, 1974).
The Bray-Curtis measure takes all the species in a sample into
consideration but has the advantage in that it is not affected by joint absences of species
(Field et al., 1982).
Hierarchical agglomerative clustering is a classification method which results in the
production of a dendogram in which samples are clustered into distinct groups based on
their similarities, although the cut-off levels are arbitrary and depend upon convenience
(Field et al., 1982). Dendograms, however, have a number of disadvantages and in view of
this, it is advisable to employ an additional method of presentation to show individual
relationships. If the two complimentary methods agree, then discontinuities can be accepted
as real (Field et al., 1982).
Non-metric multi-dimensional scaling (MDS) produces a two-dimensional graphical
representation or ‘map’ of the similarity relationships between samples. The distance
between two samples on the ordination plot is a reflection of the similarity between those
two samples (Field et al., 1982). The ‘goodness-of-fit’ of the resultant scatter plot is
measured by the stress formula. If stress is large, the ‘map’ tallies poorly with the observed
dissimilarities while a low stress indicates that the sample relationship is well represented by
the ‘map’ (Field et al., 1982). Clarke & Warwick (1994) suggest that a stress of
approximately 0.1 or less allows for fairly confident interpretation of the ordination plot.
Although a stress of less that 0.2 still gives a potentially useful two-dimensional picture, a
cross-check of any conclusions should be made against those from an alternative technique
(Clarke & Warwick, 1994).
Before calculating the Bray-Curtis similarity coefficient, the data was first standardised by
computing the relative (%) abundance of each species within each estuary.
Such
standardisation is essential if sampling effort in each estuary was different as was the case
during this study. The Bray-Curtis coefficient will reflect differences between two samples
due both to differing community composition and/or differing total abundance.
Standardisation removes any effect of the latter (Clark & Warwick, 1994).
34
After
standardisation, the data was then 4th root transformed which has the effect of scaling down
the importance of abundant species so that they do not swamp the other data (Field et al.,
1982). The data for each group of estuary types was then analysed using a combination of
hierarchical agglomerative clustering and non-metric multi-dimentional scaling (MDS).
For ease of interpretation the estuaries were labelled according to their geographic position
following Heydorn & Tinley (1980) where: W = west coast from, and including the Gariep
estuary to Cape Columbine; SW = south-west coast from Cape Columbine to Cape
Agulhas; S = south coast from Cape Agulhas to Cape Padrone; SE = south-east coast from
Cape Padrone to, and including the Great Kei estuary; T = Transkei coast between the
Great Kei and Mtamvuna estuaries; KZ = KwaZulu-Natal coast from, and including the
Mtamvuna estuary to, and including Kosi Bay (Figure 3.1).
25 •E
Kosi Bay
Gariep
South Africa
Durban
31 •S
31•S
Mtamvuna
Port St. Johns
Atlantic
Mdumbi
Mtata
Mbashe
Ocean
Coffee Bay
Indian Ocean
Cape Columbine
East London
Great Kei
Port Elizabeth
Cape T own
N
Cape Padrone
Cape Point
0
40
80
120 km
25 •E
Cape Agulhas
Figure 3.1. Map of South Africa indicating place names and estuaries mentioned in the text.
35
3.3.3 Results & discussion
Type A estuaries
The results of the cluster analysis for type A estuaries are presented in Figure 3.2. A distinct
group separated from the remainder at approximately 18% similarity and these mostly
comprised estuaries which occurred along the south-west and south coasts.
At
approximately 35% similarity a group comprising estuaries from the south and south-east
coast was formed. The remaining systems separated into two groups at approximately 48%
similarity.
One group comprised mostly systems from the south-east coast while the
remaining group mostly comprised systems from the Transkei and KwaZulu-Natal coasts.
The latter could be further sub-divided (at about 50% similarity) into systems from
KwaZulu-Natal and systems mostly from the Transkei (Figure 3.2).
The results of the ordination produced a ‘map’ with a moderate stress (S = 0.13) and the
pattern somewhat reflected the geographical distribution of these estuaries. The estuaries on
the south-west and south coast were situated to the left of the ordination plot. Systems on
the south-east coast were largely situated in the centre of the ordination while those from
Transkei and KwaZulu-Natal lay to the right of the plot (Figure 3.2).
36
a)
S
SW
SW
SW
S
S
S
SE
SE
S
S
SE
SE
SE
SE
SE
T
KZ
KZ
KZ
KZ
T
SE
T
T
KZ
10
20
30
40
50
60
70
80
90
100
BRAY- CURTIS SIMILARITY ( %)
Str ess = 0 .13
b)
SE
SE
SW
SE
SE
SW
S
T
S
S
S
SE
SE
S
SE
SE
KZ KZ
KZ
T
KZ
KZ
T
T
S
Figure 3.2. Dendogram (a) and MDS ordination (b) of type A estuaries on the South
African coast.
37
Type B estuaries
For type B estuaries a distinct group of systems separated from the remainder at
approximately 15% similarity. This group comprised systems mostly from the west and
south-west coasts. The remaining estuaries separated into two groups at approximately
40% similarity. One group comprised estuaries mostly from the south and south-east coasts
while the remaining group comprised systems mostly from the KwaZulu-Natal coast (Figure
3.3).
The results of the ordination revealed the presence of three possible groups. Systems on the
subtropical KwaZulu-Natal coast formed a grouping to the right of the ordination plot.
Estuaries on the south, south-east and Transkei coasts formed a group situated in the centre
of the plot while estuaries mostly from the south-west and west coast produced a wide
spread to the left of the plot. The ordination had a moderate stress value (S = 0.14) and the
pattern generally corresponded with the geographical position of the estuaries (Figure 3.3).
38
a)
SW
SW
W
SW
SW
S
SW
S
S
S
S
S
S
S
SE
SE
SE
SE
SE
T
T
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
SE
T
SE
T
SE
SE
T
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
T
KZ
KZ
KZ
KZ
KZ
SE
T
KZ
KZ
KZ
KZ
KZ
10
20
30
40
50
60
70
80
90
100
BRAY-CURTIS S IMILA RITY ( %)
Stress = 0.1 4
b)
SW
W
SW
SW
KZ
KZ
KZ
S
SW
S
S
T
SESE T
SE
S SE
TSET
S SE
SE
SE
SE
S SSE
SE
SE
SE
SE
SE
SE SE
SE
SE
SE
SE
SE
SE
SE
SE SESET T
SW
SE
S
KZ
KZ KZ
KZ
KZ
KZ
KZKZ
KZ
KZ
T
KZ
KZ
KZ
KZ
KZ
KZKZ
KZ
KZ
Figure 3.3. Dendogram (a) and MDS ordination (b) of type B estuaries on the South
African coast.
39
Type E estuaries
For type E estuaries, a distinct group separated from the remaining systems at approximately
15% similarity. All these systems were estuaries which lie on the south-west coast. At
approximately 30% similarity one estuary on the KwaZulu-Natal coast (Mgobezeleni)
separated as an outlier. The remaining systems formed two groups at approximately 50%
similarity. One group comprised estuaries from the south-east and Transkei coasts while the
other group comprised systems from the Transkei and KwaZulu-Natal coasts (Figure 3.4).
The ordination plot of type E systems resulted in two groupings. Estuaries on the southwest coast were grouped to the left of the ordination while the remaining systems from the
south, south-east, Transkei and KwaZulu-Natal coasts formed a cluster to the right. This
grouping appeared to grade from estuaries on the south and south-east coast through to
systems on the Transkei and KwaZulu-Natal coasts. Overall, the ordination had a relatively
low stress (S = 0.11) and the relative positions of the estuaries corresponded with their
geographic location (Figure 3.4).
40
a)
SW
SW
SW
SW
SW
SW
SE
SE
SE
SE
T
T
S
T
T
T
SE
T
T
T
T
T
T
T
KZ
T
T
T
T
KZ
KZ
KZ
KZ
KZ
10
20
30
40
50
60
70
80
90
100
B RAY-CURTIS SIMILARITY (%)
b)
Stress = 0.11
KZ
T
SW
SW SW
SWSW
T
S
SW
T
T
T
T
SE
SE T
SE SE
T
T
T
KZ KZ
KZ
TKZ KZ
T TT
T
SE
T
Figure 3.4. Dendogram (a) and MDS ordination (b) of type E estuaries on the South
African coast.
41
Type F estuaries
The results of the cluster analysis for type F estuaries is presented in Figure 3.5. The
estuaries on the west and south-west coast separated from the remainder of the systems at
approximately 18% similarity. Three systems in KwaZulu-Natal (Kosi Bay, Thukela and
Mvoti) separated out at approximately 22% similarity. The remaining estuaries formed two
groups at approximately 40% similarity.
The one group comprised estuaries on the
KwaZulu-Natal and Transkei coasts, while the other group consisted of estuaries mainly
from the south and south-east coast as well as a few from the Transkei region (Figure 3.5)
The ordination of type F estuaries produced a ‘map’ with a relatively low stress value (S =
0.10) and the pattern produced broadly corresponded with their geographic position.
Estuaries on the west and south-west coast formed a cluster to the left of the ordination.
The remaining systems appeared to form a gradation from those on the south and south-east
coast to the Transkei and KwaZulu-Natal (Figure 3.5).
42
a)
W
W
W
SW
SW
SW
SE
S
S
S
SE
S
S
S
S
S
S
S
S
SE
S
S
S
S
SE
SE
SE
SE
SE
SE
SE
SE
SE
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
KZ
10
20
30
40
50
60
70
80
90
100
BRAY- CURTIS SIMILARITY (%)
b)
Stress = 0.10
KZ
SWSW
SW
KZ
W W
W
KZ
SE
SE
T
S
S
KZ
T
KZ
SS
KZ
S
S
T
T
KZ
T
KZT
S
SE
T
T
S
T T
SSETT T T
KZ
KZ
S SS SE
T KZKZ
SE
SE
SE
T
SE
SE SE
S S
KZ
SE
Figure 3.5. Dendogram (a) and MDS ordination (b) of type F estuaries on the South
African coast.
43
Day (1981b) grouped southern African estuaries into three main biotic provinces based
mainly on water temperature but also rainfall and river flow. The estuaries of southern
Moçambique from the Morrumbene (23°44’S; 35°24’E) to the Great Kei (32°40’S;
28°23’E) at the southern Transkei border were classified as subtropical. These systems are
characterised by warm waters (>16 °C), and a good summer rainfall and river discharge.
Estuaries from the Great Kei to Cape Point (34°22’S; 18°30’E) were characterised as
warm-temperate. These systems have minimum winter temperatures of between 12 and 14
°C and experience variable rainfall. The cold-temperate estuaries are those on the west
(Atlantic) coast between Cape Point and the Gariep estuary (28°38’S; 16°28’E) and this
area is characterised by very low rainfall and high evaporation (Day, 1981b).
Whitfield
(1994) suggested that the region between Cape Point and the Gariep be referred to as
‘cool-temperate’ since estuarine water temperatures in this region are always above 10 °C.
He also suggested that the division between the subtropical and warm-temperate regions be
changed to the Mbashe estuary (32°17’S; 28°54’E). The transitional nature of the Mbashe
was highlighted by the presence of both mangroves which favour subtropical conditions, and
saltmarshes which are normally associated with temperate systems (Whitfield, 1994).
From the results of this study it appears that, based on their fish communities, the estuaries
within each geomorphological type formed groupings which were related to their
geographical position or biogeography. Furthermore, it appears that estuaries on the west
and south-west coast were more distinct than the remaining systems. This suggests that the
cool-temperate region lies between the Gariep estuary and Cape Agulhas (34°50’S;
20°00’E).
The region between Coffee Bay (31°59’S; 29°09’E) and Port St Johns
(31°38’S; 29°33’E) in the Transkei appears to be a transition zone between the warmtemperate and subtropical regions.
To test if estuaries in different biogeographic regions have distinctive fish communities, each
group of estuary types was divided into the biogeographic regions proposed by Whitfield
(1994) and an analysis of similarities (ANOSIM) performed on the data. The ANOSIM
test utilises the (rank) similarity matrix underlying the clustering or ordination procedure and
tests for differences between and within a priori groupings (Clark & Warwick, 1994). A
44
test statistic (R) is computed which reflects the observed differences between groupings,
contrasted with differences within groupings. The R statistic falls within the range -1 to 1 but
usually falls between 0 and 1. If R = 1 then all sites within a group are more similar to each
other than any sites from different groups; if R is approximately zero then the similarities
between and within groups are the same on average. The global R statistic reflects the
similarities between all groupings (Clark & Warwick, 1994).
The results of the ANOSIM test are presented in Table 3.1. Apart from type A estuaries,
the global R statistic for each estuary type were above 0.5 indicating that the fish
communities of the estuaries within each biogeographic region are significantly different
(p<0.001) to those recorded in the other biogeographic provinces.
Table 3.1. Test statistic (R) and significance (p) of the ANOSIM test applied to estuaries
grouped according to the biogeographic zones suggested by Whitfield (1994). (GR =
Global R statistic).
Type A estuaries
GR = 0.380 (p = 0.000)
Gariep - Cape Point
Cape Point - Mbashe
0.461 (p = 0.007)
Mbashe - Kosi Bay
1.000 (p = 0.022)
Type B estuaries
0.272 (p = 0.010)
GR = 0.806 (p = 0.000)
Gariep - Cape Point
Cape Point - Mbashe
0.971 (p = 0.000)
Mbashe - Kosi Bay
1.000 (p = 0.000)
Type E estuaries
Cape Point - Mbashe
Cape Point - Mbashe
0.759 (p = 0.000)
GR = 0.510 (p = 0.000)
Gariep - Cape Point
Cape Point - Mbashe
Cape Point - Mbashe
Mbashe - Kosi Bay
Type F estuaries
0.510 (p = 0.000)
R = 0.659 (p = 0.000)
Gariep - Cape Point
Cape Point - Mbashe
0.777 (p = 0.001)
Mbashe - Kosi Bay
0.998 (p = 0.000)
Cape Point - Mbashe
0.613 (p=0.000)
This analysis was repeated using Cape Agulhas and the Mdumbi estuary (31°56’S;
29°13’E) as the boundaries between the cool- and warm-temperate and warm-temperate
45
and subtropical regions respectively. The ANOSIM test resulted in higher global R values
(0.415 - 0.863) and generally higher R statistics for each estuary type (Table 3.2) than those
recorded in Table 3.1.
Table 3.2. Test statistic (R) and significance (p) of the ANOSIM test applied to estuaries
grouped according to the modified biogeographic zones (GR = Global R statistic).
Type A estuaries
GR = 0.415 (p = 0.000)
Gariep - Cape Agulhas
Cape Agulhas - Mdumbi
0.646 (p = 0.001)
Mdumbi - Kosi Bay
1.000 (p = 0.012)
Type B estuaries
Cape Agulhas - Mdumbi
0.940 (p = 0.000)
Mdumbi - Kosi Bay
0.994 (p = 0.000)
Cape Agulhas - Mdumbi
0.813 (p = 0.000)
GR = 0.753 (p = 0.000)
Gariep - Cape Agulhas
Cape Agulhas - Mdumbi
0.989 (p = 0.000)
Mdumbi - Kosi Bay
0.999 (p = 0.001)
Type F estuaries
0.175 (p = 0.057)
GR = 0.846 (p = 0.000)
Gariep - Cape Agulhas
Type E estuaries
Cape Agulhas - Mdumbi
Cape Agulhas - Mdumbi
0.517 (p = 0.000)
R = 0.863 (p = 0.000)
Gariep - Cape Agulhas
Cape Agulhas - Mdumbi
0.997 (p = 0.000)
Mdumbi - Kosi Bay
1.000 (p = 0.000)
Cape Agulhas - Mdumbi
0.808 (p=0.000)
The precise boundaries between biogeographic regions are clearly not distinct and zones of
overlap (transition zones) exist. The area between Cape Point and Cape Agulhas is
generally regarded as the transition zone between the cool-temperate and warm-temperate
biogeographic regions while the transition zone between the subtropical and warmtemperate biogeographic regions lies somewhere in the Transkei between the Great Kei and
Port St Johns (Hockey & Buxton, 1991). It is often convenient, however, to provide some
firm boundary between the various regions and the results of this analysis suggests that,
based on their fish communities, the subtropical biogeographic zone extends from Kosi Bay
to the Mdumbi estuary, the warm-temperate region stretches from the Mdumbi estuary to
Cape Agulhas, and the cool-temperate region continues from Cape Agulhas to the Gariep
estuary.
46
3.4 Classification
3.4.1 Introduction
Having determined the biogeographic boundaries for estuaries along the South African
coast, one can now investigate the fish community structure in relation to estuary type. This
also serves to test the earlier assumption that estuaries with similar physical characteristics
ought to have similar fish communities.
3.4.2 Methods
The estuaries sampled were divided into the biogeographic regions outlined above and the
data analysed using a combination of hierarchical agglomerative clustering and non-metric
multi-dimentional scaling (MDS) using PRIMER (Clark & Warwick, 1994).
Before
analysis the data was first standardised and then 4th root transformed. To assess whether
the various physical/geomorphological estuary types within each biogeographic region
contain distinctive fish assemblages, the ANOSIM test was applied to each grouping of
estuary types within each biogeographic region. For ease of interpretation the estuaries are
denoted by their physical/geomorphological type (A-F) as outlined in the previous chapter.
3.4.3 Results & discussion
Cool-temperate estuaries
For estuaries in the cool-temperate region, a group comprising a mixture of estuary types B,
C and F separated from the remaining systems at approximately 40% similarity. At
approximately 45% similarity two outliers, the Gariep (Type F) and Steenbras (Type D)
separated out. The next grouping (at approximately 50% similarity) comprised type B
systems. The remaining estuaries in the region formed two groups at approximately 58%
similarity. The one group comprised systems mostly belonging to type A while the remaining
estuaries were further subdivided (at just over 60% similarity) into predominantly type E
systems and a combination of type B, E and F systems (Figure 3.6).
47
The results of the ordination revealed a fairly wide spread (stress = 0.16). Type C systems
were situated to the left of the ordination. The centre of the plot comprised type E and F
estuaries while type A systems formed a group to the right of the ordination. Type B
systems were widely scattered but most were situated to the right of the plot. Only one type
D system (Steenbras) was identified in this region and it was situated near the top of the
ordination (Figure 3.6).
48
a)
B
F
C
C
F
D
B
B
B
B
A
A
A
E
B
F
F
F
E
E
E
F
E
E
30
40
50
60
70
80
90
100
BRAY-CURT IS SIMILARITY (%)
Stress = 0.16
b)
D
F
B
B
F
F
B
E
C
A
EE
F
C
A
F E
B
F
E
B
E
B
Figure 3.6. Dendogram (a) and MDS ordination (b) of cool-temperate estuaries on the
South African coast.
49
Cool-temperate estuaries had a Global R value of 0.332 (p = 0.001). Relatively high
significance levels were recorded (p = 0.762 - 0.028) and this is partially due to the small
number of systems in each group of estuary types. Type B systems were highly variable and
did not appear to be significantly different to the vast majority of the other estuary types in
the region. The most distinctive groups were estuary types C, D and A. Estuary types E
and F exhibited substantial overlap in the MDS plot and this is also reflected in the
ANOSIM results (Table 3.3).
Table 3.3. Test statistic (R) and significance (p) of the ANOSIM test applied to estuaries in
the cool-temperate zone (Global R = 0.332, p = 0.001).
Estuary
Type
A
A
B
-0.142
(p = 0.762)
1.000
(p = 0.100)
1.000
(p = 0.250)
0.512
(p = 0.036)
0.290
(p = 0.107)
C
D
E
F
B
C
D
E
F
-0.142
(p = 0.762)
1.000
(p = 0.100)
0.406
(p = 0.036)
1.000
(p = 0.250)
0.289
(p = 0.429)
1.000
(p = 0.333)
0.512
(p = 0.036)
0.254
(p = 0.028)
1.000
(p = 0.360)
0.978
(p = 0.143)
0.290
(p = 0.107)
0.059
(p = 0.277)
0.510
(p = 0.360)
0.778
(p = 0.143)
0.161
(p = 0.061)
0.406
(p = 0.036)
0.289
(p = 0.429)
0.254
(p = 0.028)
0.059
(p = 0.277)
1.000
(p = 0.333)
1.000
(p = 0.360)
0.510
(p = 0.360)
50
0.978
(p = 0.143)
0.778
(p = 0.143)
0.161
(p = 0.061)
Warm-temperate estuaries
The dendogram of warm-temperate estuaries is presented in Figure 3.7. Two systems, the
Lottering and Storms (Type D), separated out as an outliers at approximately 20 and 25%
similarity respectively. At approximately 35% similarity two groups were formed. One
group comprised predominantly type D estuaries while the other were mainly type A
systems. Another group of predominantly type A systems separated out at approximately
45% similarity. Three systems separated out from the remainder of the estuaries at between
45 and 48% similarity and these included the Great Kei (Type F), Mapuzi (Type E) and
Mtendwe (Type A). At approximately 48% similarity a group of predominantly type B
systems was formed. The remaining estuaries formed three groups at approximately 55%
similarity. Two groups comprised predominantly type F estuaries while the remainder
comprised mostly type B estuaries.
Although the ordination of warm-temperate estuaries had a relatively high stress (S = 0.18),
some pattern was discernible (Figure 3.7). Type F estuaries formed a grouping to the right
of the plot. Type B and E estuaries were situated in the centre and to the right of the
ordination respectively. Type D estuaries formed a loose but distinct grouping near the top
of the ‘map’ while the remaining systems (Type A) were spread along the bottom of the plot
(Figure 3.7).
51
D
D
D
D
D
D
B
D
A
D
A
A
A
A
A
A
A
A
A
A
E
E
A
F
E
A
D
F
B
B
B
D
A
F
F
F
F
F
B
B
B
B
a)
B
E
E
A
E
B
A
E
B
B
B
B
B
B
B
B
A
B
B
B
B
B
B
B
B
E
B
B
B
B
B
B
B
B
B
B
B
F
B
E
F
F
F
F
B
F
F
E
F
B
E
E
B
E
F
F
F
F
F
F
F
F
F
F
F
F
F
B
F
E
F
F
F
F
F
E
F
BRAY-C URTIS SIMILAR ITY (%)
10
20
30
40
50
60
70
80
90
10 0
Stress = 0.18
b)
D
D
F
F
F
FF
F
F
F
F
D
F
D
F
F
B
E
F
F
B F
F
F
F F F FEFF
B BB
FFFF F F F
B
B
F
B
BB B
F
B
BE B FB
E
B
BBBB
B E
BB B
BB
E
A
B BB
BB E
B B
E
E
E ABBA B E
A
A
B
A
A B E
A
E BB
F
F
D
A
D
A
A
A
D
D
D
A
B
A
A
E
D
E
A
A
Figure 3.7. Dendogram (a) and MDS ordination (b) of warm-temperate estuaries on the
South African coast.
52
The results of the ANOSIM test revealed that estuary types D and F had relatively high R
statistics indicating significant differences compared to all other estuary types. Only type E
estuaries yielded relatively low R values in relation to type A and B systems. Overall,
estuaries in the warm-temperate region had a global R value of 0.539 (p = 0.000) indicating
that the various estuary types had distinctive fish communities (Table 3.4).
Table 3.4. Test statistic (R) and significance (p) of the ANOSIM test applied to estuaries in
the warm-temperate zone (Global R = 0.539, p = 0.000).
Estuary
Type
A
A
B
0.576
(p = 0.000)
B
C
0.576
(p = 0.000)
D
E
F
0.345
(p = 0.000)
0.861
(p = 0.000)
0.294
(p = 0.000)
0.291
(p = 0.001)
0.830
(p = 0.000)
0.452
(p = 0.000)
0.753
(p = 0.000)
0.890
(p = 0.000)
0.432
(p = 0.000)
C
D
E
F
0.345
(p = 0.000)
0.294
(p = 0.000)
0.830
(p = 0.000)
0.861
(p = 0.000)
0.291
(p = 0.001)
0.452
(p = 0.000)
0.753
(p = 0.000)
0.890
(p = 0.000)
53
0.432
(p = 0.000)
Subtropical estuaries
From the dendogram of subtropical estuaries, four systems appeared to separate out as
outliers at approximately 32% and 35% similarity.
These included Kosi Bay and
Mgobezeleni (types F and E respectively), and the Mvoti and Thukela (Type F). At
approximately 40% similarity a group comprising a mixture of type A and B estuaries was
formed. The remaining estuaries formed two groups at approximately 45% similarity. One
group comprised a combination of type B and E estuaries while the remaining group
comprised almost entirely of type F systems (Figure 3.8).
The MDS plot of the subtropical estuaries yielded a moderately high stress value (S = 0.17).
The ordination showed a gradation from type F systems to the right of the plot to type B and
E estuaries in the centre to type A systems to the left of the ordination (Figure 3.8).
54
a)
F
F
B
B
A
A
B
B
A
A
B
B
A
A
E
B
E
E
B
B
E
B
B
E
B
B
B
E
B
B
E
B
E
E
E
E
B
B
B
B
B
F
F
F
F
E
F
F
F
F
F
F
F
F
F
F
B
F
F
F
F
E
F
30
40.
50
60
70
80
90
100
BRAY-CURTIS SIMILARITY (%)
Stress = 0.17
b)
E
F
F
E
A
A
B
A
B
B
A
A
A
B
B
B
B
B
B
B
EE
B
E B
B E EBE
B
E F
E
B
E
F
B
FF F
F
BE
B E
B
F
F
F
B
FF F
B
F
B
F
F
F
FF
F
Figure 3.8. Dendogram (a) and MDS ordination (b) of subtropical estuaries on the South
African coast.
55
Subtropical estuaries had a global R value of 0.406 (p = 0.000) (Table 3.5). Only four
types of estuary were identified in this region. Type F estuaries had relatively high R values
throughout indicating significant differences in the fish community in relation to all the other
estuary types. In the ordination, type B estuaries exhibited a wide scatter and this is
reflected in the ANOSIM results where relatively low R values were recorded when
compared with type A and E systems. The remaining estuary types exhibited significant
differences in their similarities suggesting distinctive fish communities (Table 3.5).
Table 3.5. Test statistic (R) and significance (p) of the ANOSIM test applied to estuaries in
the subtropical zone (Global R = 0.406, p = 0.000).
Estuary
Type
A
A
B
0.237
(p = 0.016)
B
C
0.237
(p = 0.016)
D
E
F
0.671
(p = 0.000)
0.009
(p = 0.397)
0.874
(p = 0.000)
0.525
(p = 0.000)
C
D
E
F
0.671
(p = 0.000)
0.874
(p = 0.000)
0.009
(p = 0.397)
0.525
(p = 0.000)
0.421
(p = 0.000)
0.421
(p = 0.000)
Based on their physical/geomorphological characteristics, six basic estuary types were
identified (although sub-groups within some of these also exist). Estuaries in the cooltemperate region are characterised by a relatively low species diversity and are typically
dominated by a few abundant species (Whitfield, 1998). Although all the estuary types
occur in this region, the low species diversity may account for the lack of distinctive faunas
within each estuary type by virtue of their dominance by a few very common species. In the
warm-temperate and subtropical regions most estuary types appeared to have distinctive
fish communities which suggests that estuaries with similar physical/geomorphological
characteristics contain similar fish assemblages.
56
3.5 Fish community characteristics
3.5.1 Introduction
Having determined the biogeography of the estuaries along the coast as well as the range of
estuary types, a broad characterisation of the fish community structure of South Africa’s
estuaries is attempted. Biological communities can be described according to a number of
attributes including species diversity, relative abundance, life-history characteristics and
trophic structure (Krebbs, 1985). In this section only aspects of species diversity and
composition will be considered.
The simplest measure of species diversity is to count the number of species, this is often
referred to as species richness or species density (Odum, 1983). Not all species in the
community, however, are equally important in determining the nature of the community and
linked to this is the concept of dominance. Most biotic communities typically consist of
many common species and a few rare species (Odum, 1983; Krebbs, 1985). A description
of the fish community structure which typifies the various estuarine types in the various
biogeographic regions may provide a baseline or reference against which individual estuaries
can be measured and monitored in the future.
3.5.2 Methods
The estuaries were first divided according to biogeographic region and the systems within
each region grouped according to estuary type, based on the classification provided in
Chapter 2. Because the aim here is to describe the fish community structure of the various
estuary types within each biogeographic region, exotic or translocated species were
removed from the analysis. Juvenile mullet (Mugilidae, Liza spp. and Valamugil spp.)
which were not fully identified, however, were retained due to the fact that this group
comprises an important component of the ichthyofauna of South Africa’s estuaries by virtue
of their dependence on these systems as nursery areas.
The average number of taxa (and the standard deviation (SD)) was calculated for each
group of estuary types within each biogeographic region. The species composition of each
57
group of estuary types was also determined based on the frequency of occurrence of each
taxa as well their average total abundance.
3.5.3 Results & discussion
Cool-temperate estuaries (Gariep – Cape Agulhas)
Type A estuaries (n = 3)
Only two species (Liza richardsonii and Lithognathus lithognathus) were captured in this
group of estuaries. Liza richardsonii was captured in all the systems and comprised over
99% of the total catch numerically (Table 3.6).
Type B estuaries (n = 6)
An average of four species (SD = 3.31) was captured in type B estuaries in the cooltemperate region. The most frequently captured species included L. richardsonii, Mugil
cephalus, Atherina breviceps, Psammogobius knysnaensis, Caffrogobius nudiceps, and
Heteromycteris capensis.
In terms of abundance, Gilchristella aestuaria was the
dominant species (46.7%) followed by L. richardsonii (35.8%), A. breviceps (5.5%), M.
cephalus (5.5%), P. knysnaensis (3.1%) and C. nudiceps (2.5%) (Table 3.6).
Type C estuaries (n = 2)
Only two systems, the Bot and Klein were classified as type C systems. Eight species were
captured in the Bot and 11 species were captured in the Klein during this study; six species
were common to both systems. Numerically A. breviceps (84.2%) was the dominant
species followed by G. aestuaria (8.4%) and L. richardsonii (5.0%) (Table 3.6).
Type D estuaries (n = 1)
Only one system (Steenbras) was classified as type D in this region. Four species were
captured in this system. Liza richardsonii was the numerically dominant species (62.5%)
followed by Sarpa salpa (26.1%), Diplodus sargus (8.0%) and G. aestuaria (3.4%)
(Table 3.6).
58
Type E estuaries (n = 6)
An average of four species (SD = 1.10) was captured in type E estuaries in the cooltemperate region.
The most frequently captured fishes were L. richardsonii, P.
knysnaensis, M. cephalus, G. aestuaria, and Myxus capensis.
Numerically, L.
richardsonii (92.3%), P. knysnaensis (4.8%) and M. cephalus (1.9%) were the dominant
species (Table 3.6).
Type F estuaries (n = 6)
In type F estuaries an average of seven species (SD = 2.48) was captured.
Liza
richardsonii, P. knysnaensis, M. cephalus, A. breviceps, G. aestuaria and Galeichthys
feliceps were the most frequently captured taxa. In terms of abundance, L. richardsonii
(84.6%), A. breviceps (10.6%), G. aestuaria (2.2%) and Barbus aeneus (1.6%) were the
dominant species (Table 3.6). The relatively high numerical dominance of B. aeneus is due
to large numbers of this species being captured in the Gariep estuary.
The natural
distribution of this species, however, appears to be restricted to this system although some
specimens have been translocated to larger coastal rivers in the south-east coastal region
(Skelton, 1993).
Estuaries in the cool-temperate region are characterised by a relatively low species diversity
and only 24 species are commonly associated with estuaries in this region (Whitfield, 1998).
Overall, a total of 28 species were captured in estuaries in the cool-temperate region during
this study of which, 19 were common to those listed in Whitfield (1998). The most
frequently captured species included L. richardsonii, P. knysnaensis, M. cephalus, G.
aestuaria, and A. breviceps. Liza richardsonii (60.5%), A. breviceps (28.9%) and G.
aestuaria (7.1%) were the numerically dominant species overall.
A noteworthy
characteristic of cool-temperate estuaries is the overwhelming dominance of L. richardsonii
and relative scarcity of most other species (Whitfield, 1998).
59
Table 3.6. Percent frequency of occurrence (%f) and abundance (%n) of fishes captured in estuaries in
the cool-temperate region.
Species
Amblyrhynchotes honckenii
Argyrosomus spp.
Atherina breviceps
Barbus aeneus
Caffrogobius gilchristi
Caffrogobius nudiceps
Chelidonichthys capensis
Clinus spatulatus
Clinus superciliosus
Diplodus sargus
Etrumeus whiteheadi
Galeichthys feliceps
Gilchristella aestuaria
Haploblepharus pictus
Heteromycteris capensis
Lichia amia
Lithognathus lithognathus
Liza dumerilii
Liza richardsonii
Mugil cephalus
Myxus capensis
Pomatomus saltatrix
Psammogobius knysnaensis
Rhabdosargus globiceps
Rhabdosargus holubi
Sardinops sagax
Sarpa salpa
Syngnathus acus
Type 'A'
%f %n
Type 'B'
%f %n
Type 'C'
%f %n
33.3
5.5
100
84.2
50.0
0.2
33.3
2.4
50.0
50.0
0.0
0.4
Type 'D'
%f %n
100
100
16.7 46.7 100
33.3
16.7
33.3
0.1
100
99.9
0.3
8.4
0.5
0.2
16.7 0.2
100 35.8 100
66.7 5.5 100
5.0
0.3
50.0
100
0.0
0.6
50.0
0.0
100
0.7
33.3
16.7
100
3.1
0.1
100
100
16.7
0.0
60
Type 'E'
%f %n
Type 'F'
Total
%f %n %f %n
16.7 0.0 4.2 0.0
33.3 0.0 8.3 0.0
16.7 0.1 66.7 10.6 37.5 28.9
16.7 1.6 4.2 0.9
4.2 0.0
33.3 0.4 16.7 0.4
16.7 0.0 4.2 0.0
4.2 0.0
4.2 0.1
8.0
4.2 0.0
16.7 0.0 4.2 0.0
50.0 0.0 20.8 0.1
3.4 50.0 0.4 50.0 2.2 41.7 7.1
16.7 0.0 4.2 0.0
16.7 0.0
12.5 0.0
4.2 0.0
16.7 0.1
8.3 0.0
4.2 0.0
62.5 100 92.2 100 84.6 100 60.5
50.0 1.9 83.3 0.1 58.3 0.7
33.3 0.1
8.3 0.0
33.3 0.1 12.5 0.0
100 4.8 83.3 0.4 62.5 0.9
16.7 0.0 8.3 0.0
16.7 0.2
8.3 0.0
16.7 0.0 4.2 0.0
26.1
4.2 0.1
33.3 0.0 20.8 0.2
Warm-temperate estuaries (Cape Agulhas – Mdumbi)
Type A estuaries (n = 17)
An average of 8 taxa (SD = 3.51) was captured in type A estuaries in the warm-temperate
region.
The most frequently captured fishes included M. cephalus, M. capensis,
Rhabdosargus holubi, L. richardsonii, juvenile mullet (Mugilidae), G. aestuaria, P.
knysnaensis, L. lithognathus and Monodactylus falciformis.
In terms of overall
abundance, M. cephalus (29.8%), M. capensis (20.4%), R. holubi (15.1%), G. aestuaria
(14.9%), L. richardsonii (8.1%), juvenile mullet (Mugilidae) (4.8%), A. breviceps (3.4%),
and Glossogobius callidus (1.4%) were the dominant taxa (Table 3.7).
Type B estuaries (n = 42)
In type B estuaries an average of 17 taxa (SD = 5.06) was captured during this study. The
most frequently captured fishes included G. aestuaria, L. richardsonii, R. holubi, M.
falciformis, M. capensis, M. cephalus, A. breviceps, G. callidus, Liza dumerilii, L.
lithognathus,
Liza tricuspidens,
P. knysnaensis,
Oreochromis mossambicus,
Pomadasys commersonnii, Mugilidae, Liza spp., Argyrosomus japonicus, and Lichia
amia. Gilchristella aestuaria (42.8%), A. breviceps (20.1%), R. holubi (14.2%), M.
capensis (4.0%), L. richardsonii (4.0%), G. callidus (3.5%), Liza spp. (2.4%), L.
dumerilii (1.9%), L. lithognathus (1.1%), L. tricuspidens (1.0%), M. cephalus (1.0%),
and juvenile mullet (Mugilidae) (1.0%) were the dominant taxa numerically (Table 3.7).
Type D estuaries (n = 10)
An average of 8 taxa (SD = 2.99) was captured in type D estuaries during this study. Liza
richardsonii, L. lithognathus, P. knysnaensis, R. holubi, M. capensis, juvenile mullet
(Mugilidae), M. falciformis, and H. capensis were among the most frequently captured
fishes. In terms of overall abundance, G. aestuaria (49.5%), L. richardsonii (23.5%), M.
cephalus (8.5%), P. knysnaensis (3.3%), Liza spp. (2.6%), L. lithognathus (2.4%), M.
capensis (2.2%), juvenile mullet (Mugilidae) (2.1%), R. holubi (1.8%), M. falciformis
(1.1%), and H. capensis (1.1%) were the dominant taxa (Table 3.7).
Type E estuaries (n = 15)
61
For estuaries belonging to type E, an average of 18 taxa (SD = 3.73) was captured during
this study. Fishes that were most frequently recorded included R. holubi, M. capensis, A.
breviceps, juvenile mullet (Mugilidae), G. aestuaria, M. cephalus, L. dumerilii, M.
falciformis, L. richardsonii, L. tricuspidens, G. callidus, Liza macrolepis, Caffrogobius
gilchristi, P. commersonnii, P. knysnaensis, A. japonicus, Solea bleekeri, O.
mossambicus, Valamugil robustus, and L. lithognathus. Numerically dominant taxa
included R. holubi (30.2%), G. aestuaria (23.6%), M. capensis (9.9%), M. cephalus
(6.9%), A. breviceps (6.3%), L. dumerilii (5.8%), G. callidus (4.7%), L. richardsonii
(2.6%), O. mossambicus (1.7%), C. gilchristi (1.0%), L. tricuspidens (1.0%), and Liza
spp. (1.0%) (Table 3.7).
Type F estuaries (n = 35)
An average of 27 taxa (SD = 6.91) was captured in type F estuaries during this study. Liza
dumerilii, R. holubi, L. richardsonii, C. gilchristi, P. knysnaensis, A. japonicus, G.
aestuaria, M. cephalus, L. tricuspidens, Liza spp., P. commersonnii, juvenile mullet
(Mugilidae), L. lithognathus, S. bleekeri, M. falciformis, A. breviceps, M. capensis, G.
feliceps, L. amia, Elops machnata, H. capensis, G. callidus, D. sargus, C. nudiceps, L.
macrolepis, Pomatomus saltatrix, and Clinus superciliosus were the most frequently
captured fishes. In terms of abundance, G. aestuaria (33.4%), R. holubi (13.0%), Liza
spp. (7.6%), L. richardsonii (6.7%), L. dumerilii (6.4%), A. breviceps (5.6%), juvenile
mullet (Mugilidae) (4.0%), G. callidus (3.6%), M. cephalus (3.5%), P. commersonnii
(2.4%), C. gilchristi (2.1%), P. knysnaensis (1.2%), S. salpa (1.2%), D. sargus (1.2%),
L. lithognathus (1.0%), and L. tricuspidens (1.0%) dominated this group of estuaries
(Table 3.7).
A total of 78 estuary-associated fish species commonly occur in warm-temperate estuaries
on the South African coast (Whitfield, 1998). Type A and D systems had the lowest
average species richness in the region (eight species) and this is probably a result of the
limited habitat offered by these systems. Type A estuaries are small temporarily closed
systems while, although permanently open, type D estuaries are small systems which lie in
deeply incised valleys. It is interesting to note that type B and E estuaries had a similar
62
average species richness suggesting that, although different in terms of their predominant
mouth condition, both offer a similar habitat for fishes. This is also indicated by the results of
the ANOSIM test where their fish communities did not appear to be significantly different
(Table 3.4). Permanently open type F estuaries had the highest average species richness in
the region and is probably a result of the greater habitat diversity offered by these systems.
63
Table 3.7. Percent frequency of occurrence (%f) and abundance (%n) of fishes captured in estuaries
in the warm-temperate region.
Species
Acanthopagrus berda
Ambassis gymnocephalus
Ambassis natalensis
Ambassis productus
Amblyrhynchotes honckenii
Anguilla mossambica
Antennarius striatus
Argyrosomus japonicus
Atherina breviceps
Caffrogobius gilchristi
Caffrogobius natalensis
Caffrogobius nudiceps
Caranx ignobilis
Caranx sexfasciatus
Chaetodon marleyi
Clinus superciliosus
Dasyatis kuhlii
Diplodus cervinus
Diplodus sargus
Elops machnata
Etrumeus whiteheadi
Eugomphodus taurus
Galeichthys feliceps
Gerres methueni
Gilchristella aestuaria
Glossogobius callidus
Gobiidae
Gymnocrotaphus curvidens
Hemiramphus far
Heteromycteris capensis
Hippichthys spicifer
Hippocampus capensis
Johnius dorsalis
Leiognathus equula
Lichia amia
Lithognathus lithognathus
Lithognathus mormyrus
Liza alata
Liza dumerilii
Liza macrolepis
Liza melinoptera
Liza richardsonii
Liza spp.
Liza tricuspidens
Lutjanus argentimaculatus
Monodactylus falciformis
Mugil cephalus
Mugilidae
Myliobatis aquila
Myxus capensis
Type 'A'
%f
%n
29.4
5.9
3.4
0.0
Type 'B'
%f
%n
2.4
0.0
2.4
0.0
Type 'D'
%f
%n
Type 'E'
%f
%n
26.7
0.0
6.7
0.0
6.7
0.0
10.0
10.0
20.0
10.0
60.0
93.3
66.7
6.7
6.7
0.4
6.3
1.0
0.0
0.0
6.7
0.0
2.4
0.0
42.9
88.1
28.6
4.8
4.8
0.2
20.1
0.1
0.0
0.1
4.8
0.0
28.6
16.7
0.3
0.1
20.0
0.1
6.7
6.7
6.7
0.0
0.0
0.0
19.0
2.4
100.0
85.7
2.4
0.0
0.0
42.8
3.5
0.0
30.0
0.5
13.3
0.0
20.0
49.5
86.7
73.3
23.6
4.7
0.0
0.0
0.1
0.1
47.1
35.3
14.9
1.4
11.8
0.0
31.0
0.1
40.0
1.1
20.0
0.1
41.2
0.5
42.9
76.2
0.0
1.1
80.0
2.3
13.3
40.0
0.0
0.1
5.9
23.5
11.8
0.0
0.2
0.0
2.4
83.3
26.2
0.0
1.9
0.1
10.0
0.1
76.5
11.8
23.5
8.1
0.1
0.2
100.0
30.0
10.0
23.5
2.6
0.0
0.4
29.8
4.8
4.0
2.4
1.0
0.0
0.6
1.0
0.9
0.1
5.7
0.7
0.0
2.6
1.0
1.0
41.2
88.2
70.6
100.0
42.9
76.2
2.4
92.9
90.5
45.2
26.7
86.7
73.3
6.7
80.0
33.3
80.0
50.0
20.0
50.0
1.1
8.5
2.1
86.7
86.7
93.3
0.7
6.9
0.4
82.4
20.3
90.5
4.0
50.0
2.2
93.3
9.9
64
Type 'F'
%f
%n
17.1
0.1
11.4
0.1
2.9
0.0
5.7
0.0
22.9
0.0
5.7
0.0
2.9
0.0
97.1
0.6
77.1
5.6
97.1
2.1
37.1
0.2
48.6
0.5
2.9
0.0
8.6
0.0
2.9
0.0
40.0
0.5
2.9
0.0
28.6
0.0
54.3
1.2
65.7
0.2
5.7
0.0
5.7
0.0
68.6
0.4
94.3
57.1
2.9
2.9
14.3
60.0
2.9
2.9
2.9
5.7
68.6
82.9
2.9
33.4
3.6
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.1
1.0
0.0
100.0
45.7
6.4
0.1
97.1
91.4
94.3
2.9
80.0
94.3
82.9
5.7
71.4
6.7
7.6
1.0
0.0
0.4
3.5
4.0
0.0
0.8
Table 3.7. cont. Percent frequency of occurrence (%f) and abundance (%n) of fishes captured in
estuaries in the warm-temperate region.
Species
Oligolepis acutipennis
Oligolepis keiensis
Omobranchus woodi
Oreochromis mossambicus
Parablennius lodosus
Platycephalus indicus
Pomadasys commersonnii
Pomadasys kaakan
Pomadasys olivaceum
Pomatomus saltatrix
Psammogobius knysnaensis
Raja miraletes
Rhabdosargus globiceps
Rhabdosargus holubi
Rhabdosargus sarba
Sardinops sagax
Sarpa salpa
Secutor ruconius
Siganus sutor
Sillago sihama
Solea bleekeri
Sphyraena jello
Stolephorus holodon
Syngnathus acus
Syngnathus watermeyeri
Terapon jarbua
Torpedo fuscumaculata
Torpedo sinusperci
Trachinotus spp.
Trachurus trachurus
Valamugil buchanani
Valamugil cunnesius
Valamugil robustus
Valamugil seheli
Valamugil spp.
Type 'A'
%f
%n
Type 'B'
%f
%n
Type 'D'
%f
%n
Type 'E'
%f
%n
4.8
0.0
20.0
0.1
46.7
1.7
29.4
0.6
64.3
2.4
0.6
0.0
5.9
0.0
61.9
0.2
10.0
0.0
66.7
0.9
5.9
47.1
0.0
0.2
7.1
14.3
71.4
0.0
0.0
0.4
20.0
70.0
0.9
3.3
6.7
6.7
60.0
0.0
0.0
0.5
76.5
15.1
4.8
97.6
4.8
0.0
14.2
0.0
10.0
60.0
0.0
1.8
6.7
100.0
0.0
30.2
16.7
0.0
13.3
6.7
0.0
0.0
38.1
0.1
53.3
0.3
2.4
0.0
7.1
0.0
33.3
0.1
6.7
0.0
13.3
26.7
40.0
0.1
0.1
0.5
6.7
0.0
4.8
4.8
7.1
65
0.0
0.0
0.0
20.0
0.1
Type 'F'
%f
%n
8.6
0.0
17.1
0.0
2.9
0.0
8.6
0.0
17.1
91.4
5.7
25.7
42.9
97.1
2.9
34.3
97.1
2.9
17.1
31.4
2.9
2.9
2.9
80.0
2.9
17.1
34.3
2.9
8.6
14.3
11.4
2.9
5.7
37.1
14.3
25.7
2.9
8.6
0.0
2.4
0.0
0.2
0.0
1.2
0.0
0.4
13.0
0.0
0.0
1.2
0.0
0.0
0.0
0.5
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
Subtropical estuaries (Mdumbi – Kosi Bay)
Type A estuaries (n = 6)
An average of nine taxa (SD = 2.37) was recorded in type A systems in the subtropical
region.
Oreochromis mossambicus, M. capensis, M. cephalus, G. aestuaria, G.
callidus, M. falciformis, R. holubi, and V. robustus were the most frequently occurring
fishes. Numerically dominant species included G. aestuaria (34.3%), O. mossambicus
(33.1%), M. capensis (13.8%), M. cephalus (13.6%), R. holubi (2.1%), and G. callidus
(1.9%) (Table 3.8).
Type B estuaries (n = 23)
In type B estuaries an average of 17 taxa (SD = 5.65) was captured. The most frequently
captured fishes included M. capensis, O. mossambicus, M. cephalus, Valamugil
cunnesius, G. callidus, R. holubi, L. dumerilii, G. aestuaria, M. falciformis, Liza spp.,
L. macrolepis, P. commersonnii, Liza alata, Ambassis productus, Terapon jarbua, V.
robustus, and C. gariepinus. In terms of overall abundance, G. aestuaria (42.9%), O.
mossambicus (16.3%), M. capensis (9.1%), M. cephalus (5.0%), V. cunnesius (4.5%),
R. holubi (4.5%), G. callidus (2.6%), L. dumerilii (2.6%), M. falciformis (1.9%), A.
productus (1.4%), juvenile mullet (Mugilidae) (1.3%), V. robustus (1.3%), and Liza spp.
(1.1%) were the dominant taxa (Table 3.8).
Type E estuaries (n = 13)
An average of 19 taxa (SD = 4.13) was recorded in type E estuaries during this study.
Mugil cephalus, M. capensis, V. robustus, L. dumerilii, L. macrolepis, O. mossambicus,
R. holubi, M. falciformis, L. alata, T. jarbua, V. cunnesius, G. callidus, Liza spp., P.
commersonnii, A. productus, G. aestuaria, juvenile mullet (Mugilidae), Ambassis
natalensis, and S. bleekeri were the most frequently recorded fishes.
Numerically
dominant taxa included G. aestuaria (19.4%), R. holubi (13.7%), M. capensis (12.4%),
V. robustus (11.0%), M. cephalus (7.9%), O. mossambicus (7.7%), L. dumerilii (4.7%),
juvenile mullet (Mugilidae) (3.7%), L. macrolepis (3.4%), V. cunnesius (3.3%), Liza spp.
(2.6%), G. callidus (2.5%), T. jarbua (1.7%), and L. tricuspidens (1.0%) (Table 3.8).
66
Type F estuaries (n = 21)
In type F estuaries an average of 33 taxa (SD = 10.99) was recorded. Fishes that were
most frequently captured included M. cephalus, T. jarbua, V. cunnesius, G. callidus, L.
dumerilii, juvenile mullet (Mugilidae), Acanthopagrus berda, A. japonicus, Caranx
sexfasciatus, Liza spp., L. macrolepis, P. commersonnii, M. capensis, R. holubi, A.
natalensis, Valamugil spp., Caranx ignobilis, G. aestuaria, L. alata, Oligolepis
acutipennis, Valamugil buchanani, E. machnata, Leiognathus equula, Oligolepis
keiensis,
S. bleekeri, V. robustus, Hilsa kelee, L. tricuspidens, Ambassis
gymnocephalus, A. productus, O. mossambicus, Megalops cyprinoides, Rhabdosargus
sarba, Scomberoides lysan, and Thryssa vitrirostris (Table 3.8).
In terms of overall abundance, G. aestuaria (17.7%), A. gymnocephalus (9.3%), L.
dumerilii (8.1%), Liza spp., (5.6%), R. holubi (5.6%), V. cunnesius (5.6%), Mugilidae
(5.0%), L. macrolepis (3.8%), P. commersonnii (3.2%), L. equula (2.9%), G. callidus
(2.8%), M. cephalus (2.7%), T. jarbua (2.2%), H. kelee (1.9%), A. natalensis (1.9%),
V. robustus (1.8%), Valamugil spp. (1.5%), M. capensis (1.3%), T. vitrirostris (1.3%),
O. acutipennis (1.3%), and C. gilchristi (1.1%) were the dominant taxa (Table 3.8).
In the subtropical region, small temporarily closed type A systems had the lowest average
species richness. Although different physically/geomorphologically, type B and E estuaries
had a similar average species richness. This together with the results of the ANOSIM test
(Table 3.5) suggests that both offer a similar habitat for fishes. The greater habitat diversity
offered by the permanently open type F estuaries probably accounts for their high average
species richness. According to Whitfield (1998) 142 species are commonly associated with
subtropical estuaries.
67
Table 3.8. Percent frequency of occurrence (%f) and abundance (%n) of fishes captured in
estuaries in the subtropical region.
Species
Abudefduf sordidus
Acanthopagrus berda
Ambassis gymnocephalus
Ambassis natalensis
Ambassis productus
Amblyrhynchotes honckenii
Argyrosomus japonicus
Arothron immaculatus
Atherina breviceps
Awaous aeneofuscus
Barbus natalensis
Caffrogobius gilchristi
Caffrogobius natalensis
Caranx ignobilis
Caranx heberi
Caranx papuensis
Caranx sexfasciatus
Caranx spp.
Chanos chanos
Chelonodon laticeps
Clarias gariepinus
Crenidens crenidens
Crenimugil crenilabis
Diplodus sargus
Eleotris fusca
Elops machnata
Engraulidae
Engraulis japonicus
Epinephelus coioides
Epinephelus malabaricus
Epinephelus tauvina
Favonigobius melanobranchus
Favonigobius reichei
Gerres acinaces
Gerres filamentosus
Gerres methueni
Gerres oblongus
Gilchristella aestuaria
Glossogobius biocellatus
Glossogobius callidus
Glossogobius giuris
Hilsa kelee
Hippichthys heptagonus
Hippichthys spicifer
Johnius dorsalis
Leiognathus equula
Lichia amia
Lithognathus lithognathus
Liza alata
Liza dumerilii
Type 'A'
%f
%n
16.7
16.7
0.0
0.0
Type 'B'
%f
%n
Type 'E'
%f
%n
13.0
8.7
21.7
52.2
0.0
0.1
0.3
1.4
15.4
0.0
39.1
0.1
46.2
61.5
7.7
30.8
0.3
0.5
0.0
0.1
13.0
4.3
0.0
0.0
15.4
0.2
17.4
4.3
0.1
0.0
23.1
0.0
8.7
34.8
0.0
0.1
38.5
0.1
4.3
0.0
43.5
0.6
7.7
0.0
15.4
0.0
7.7
0.0
8.7
8.7
0.0
0.0
21.7
0.3
23.1
0.1
83.3
34.3
73.9
42.9
61.5
19.4
83.3
16.7
1.9
0.0
82.6
26.1
2.6
0.1
69.2
23.1
2.5
0.1
7.7
0.0
16.7
50.0
0.0
0.2
68
13.0
0.1
7.7
7.7
0.2
0.0
65.2
78.3
0.4
2.5
76.9
92.3
0.8
4.7
Type 'F'
%f
%n
4.8
0.0
90.5
0.8
47.6
9.3
76.2
1.8
47.6
0.5
33.3
0.3
85.7
0.6
23.8
0.0
14.3
0.6
4.8
0.0
28.6
28.6
71.4
9.5
19.0
85.7
9.5
4.8
23.8
23.8
4.8
4.8
4.8
4.8
66.7
4.8
19.0
4.8
14.3
4.8
4.8
14.3
9.5
9.5
28.6
4.8
71.4
9.5
90.5
33.3
61.9
4.8
4.8
9.5
66.7
9.5
4.8
71.4
95.2
1.1
0.1
0.9
0.0
0.0
0.8
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.9
0.0
17.7
0.0
2.8
0.2
1.9
0.0
0.0
0.1
2.9
0.0
0.0
0.7
8.1
Table 3.8. cont. Percent frequency of occurrence (%f) and abundance (%n) of fishes captured
in estuaries in the subtropical region.
Species
Liza macrolepis
Liza melinoptera
Liza richardsonii
Liza spp.
Liza tricuspidens
Lutjanus argentimaculatus
Lutjanus fulviflamma
Megalops cyprinoides
Monodactylus argenteus
Monodactylus falciformis
Mugil cephalus
Mugilidae
Mugillogobius durbanensis
Myxus capensis
Oligolepis acutipennis
Oligolepis keiensis
Oreochromis mossambicus
Oxyurichthys opthalmonema
Periopthalmus koelreuteri
Platycephalus indicus
Polydactylus plebeius
Pomadasys commersonnii
Pomadasys kaakan
Pomadasys multimaculatum
Pomadasys olivaceum
Pomatomus saltatrix
Psammogobius knysnaensis
Pseudorhombus arsius
Redigobius dewaali
Rhabdosargus holubi
Rhabdosargus sarba
Scomberoides lysan
Silhouettea sibayi
Sillago sihama
Solea bleekeri
Sphyraena jello
Stolephorus holodon
Terapon jarbua
Thryssa setirostris
Thryssa vitrirostris
Thyrsoidea macrura
Tilapia rendalli
Tilapia sparrmanii
Trypauchen microcephalus
Upeneus vittatus
Valamugil buchanani
Valamugil cunnesius
Valamugil robustus
Valamugil seheli
Valamugil spp.
Type 'A'
%f
%n
Type 'B'
%f
%n
69.6
0.8
16.7
16.7
69.6
13.0
13.0
4.3
13.0
4.3
73.9
91.3
39.1
4.3
100.0
13.0
8.7
100.0
4.3
1.1
0.0
0.0
0.0
0.1
0.0
1.9
5.0
1.3
0.0
9.1
0.1
0.0
16.3
0.0
69.6
4.3
0.6
0.0
4.3
13.0
4.3
4.3
82.6
8.7
0.0
0.2
0.0
0.0
4.5
0.1
4.3
26.1
0.1
0.1
83.3
100.0
33.3
0.2
13.6
0.2
100.0
13.8
100.0
33.1
66.7
16.7
16.7
50.0
16.7
2.1
0.1
7.7
7.7
84.6
100.0
53.8
0.0
0.0
0.9
7.9
3.7
100.0
23.1
23.1
92.3
12.4
0.1
0.2
7.7
69.2
15.4
0.4
0.1
23.1
0.2
92.3
15.4
7.7
13.7
0.1
0.0
0.0
0.1
46.2
0.2
52.2
0.4
76.9
1.7
8.7
0.1
7.7
0.0
21.7
87.0
52.2
13.0
17.4
0.0
0.2
0.0
69
Type 'E'
%f
%n
92.3
3.4
7.7
0.0
7.7
0.0
69.2
2.6
38.5
1.0
0.1
4.5
1.3
0.1
0.3
23.1
76.9
100.0
7.7
23.1
0.0
3.3
11.0
0.1
0.1
Type 'F'
%f
%n
85.7
3.8
14.3
0.0
4.8
0.0
85.7
5.6
52.4
0.4
23.8
0.0
14.3
0.0
38.1
0.1
14.3
0.0
33.3
0.3
100.0
2.7
90.5
5.0
81.0
71.4
66.7
42.9
4.8
14.3
23.8
4.8
85.7
23.8
4.8
4.8
14.3
28.6
9.5
1.3
1.3
0.7
0.7
0.2
0.0
0.1
0.0
3.2
0.3
0.0
0.2
0.0
0.1
0.0
81.0
38.1
38.1
9.5
14.3
66.7
19.0
23.8
100.0
14.3
38.1
9.5
4.8
5.6
0.1
0.5
0.1
0.1
0.8
0.0
0.3
2.2
0.0
1.3
0.0
0.0
4.8
9.5
71.4
100.0
66.7
28.6
76.2
0.0
0.0
0.6
5.5
1.8
0.3
1.5
3.6 Fish community status or ‘health’
3.6.1 Introduction
It is generally agreed that biological communities, by integrating the effect of changes across
a wide array of environmental factors (chemical, physical and biological), are good
indicators of ecosystem health (Karr et al., 1986; Roux et al., 1993). Furthermore, the
concept of biological community health is useful within the broader management context
because in general, the idea of healthy ecosystems is readily comprehended and widely
accepted by the public. Also, biological communities may be the only practical means of
evaluating certain impacts which are difficult to measure, for instance diffuse source impacts
or habitat degradation (Roux et al., 1993).
It is not financially or technically feasible to evaluate all the organisms in an entire ecosystem
at all times. Many groups of organisms have been proposed as indicators of ecosystem
health and, although no single group is favoured by the majority of biologists, it appears that
fish and macroinvertebrates have received most attention, at least in South African river
systems (Roux et al., 1993). In terms of estuaries, botanical characteristics (Coetzee et
al., 1996; 1997), fish (Cooper et al., 1994) and birds (Turpie, 1995) have been used to
determine the importance, health and conservation of South African estuaries.
The use of fish as indicators of estuarine health (Cooper et al., 1994) was based on the
Community Degradation Index (CDI) developed by Ramm (1988; 1990). The CDI, which
measures the degree of dissimilarity (degradation) between a potential fish assemblage and
the actual measured fish assemblage, was modified into the Biological Health Index (BHI) to
provide a measure of the similarity (health) between the potential and actual fish
assemblages (Cooper et al., 1994). The BHI was calculated using the formula:
BHI = 10 (J)[Ln (P)/Ln (Pmax)]
where: J = the number of species in the system ÷ the number of species in the reference
community; P = the potential species richness (number of species) of each reference
70
community and Pmax = the maximum potential species richness from all the reference
communities. The index ranges from 0 (poor) to 10 (good).
During the execution of this project the BHI was used to assess the state of South Africa’s
estuaries (Cooper et al., 1993; Harrison et al., 1994; 1995; 1996; 1997; 1999). Although
the BHI has proved a useful tool in condensing information on estuarine fish assemblages
into a single numerical value, the index is only based on presence/absence data and does not
take into account the relative proportions of the various species present. Furthermore, the
BHI formula incorporates two separate measures, health and importance, and combines
these into a single index. The health component (J) is a measure of the degree to which the
present condition of an estuary deviates from some reference condition while the importance
component [LnP/LnPmax] reflects its contribution to the region as a whole.
The aim of this section is to provide an assessment of the fish community status or ‘health’ of
South Africa’s estuaries using a number of community attributes including species richness,
composition and relative abundance. Environmental stress or degradation generally results
in a change in the number of species (richness), their identity and their relative abundance
from ‘diverse’ communities consisting of many species in relatively low proportions to
‘simple’ assemblages dominated by a few species (Odum, 1983; Fausch et al., 1990).
3.6.2 Methods
For each estuary sampled, the number of species and their relative abundance was
calculated. However, to view this fish community data in context, reference or baseline
conditions are needed against which this data can be compared (EPA, 1990; Fausch et al.,
1990; Roux et al., 1993). The fish community characteristics of each estuary type within
each biogeographic region, described in the previous section was used as a reference here.
In the case of cool-temperate estuaries, the community characteristics of the entire region
was used as the reference condition. This is due to the low number of estuaries and the
poor species diversity of the region.
71
The number of species captured in each estuary was compared to the average number
(95% confidence) for the group to which it belonged. Since species diversity tends to be
reduced in stressed biotic communities (Odum, 1983), all exotic and translocated species
were first removed from each estuary as their inclusion would artificially increase the species
richness of the estuaries in which they occurred. Each estuary was then rated according to
whether the number of taxa exceeded the average (>95% upper confidence interval),
approximated the average (95% confidence) or was below the average (<95% lower
confidence interval) of its reference group. Scores of 5, 3, and 1 were assigned to each of
the ratings respectively.
A comparison of the amount of overlap in species composition or relative abundances of a
sample and some reference condition can be used to indicate biological integrity (Fausch et
al., 1990). The species assemblage of each estuary was compared with a reference species
assemblage of each estuary type based on the most frequently captured taxa. The most
frequently captured species for each group of estuary types corresponding to the upper
95% confidence interval of the mean number of taxa was selected as the reference. The
species composition of each system was then compared to the reference assemblage using
the Bray-Curtis measure based on presence/absence. In this form the calculation is similar
to Sørensen’s similarity coefficient (ISS) which measures the ratio of the common to the
average number of species in two samples (Clarke & Warwick, 1994). By expressing the
actually measured coinciding species occurrences against theoretically possible ones, this
index includes a statistical probability term (Mueller-Dombois & Ellenberg, 1974).
An assessment of the proportions of the various species present in each estuary was also
undertaken by comparing the percent abundance of the species within each estuary with the
percent abundance of the species captured in the group to which it belonged. The number
of species corresponding to the upper 95% confidence interval of the mean number of taxa
was chosen as the cut-off. The percent species abundance of each estuary was compared
with its reference community using the Bray-Curtis similarity measure. In both the qualitative
and quantitative assessments, exotic and translocated species were included in the
assemblages for each estuary type, but were excluded from the reference condition. The
72
reason for this is that the contribution of exotic species to the fish community structure of an
estuary is indicative of a deviation from the norm or reference conditions particularly in terms
of their relative abundance. To keep the similarity values within the range 0 to 10, the BrayCurtis measure was adjusted by dividing the percent similarity results by 10.
For both the qualitative and quantitative assessments, the estuaries were rated according to
whether the fish communities approximated, deviated slightly from, or deviated strongly from
the reference condition based on the 10th and 50th percentiles of the similarity values for
ALL the estuaries. Scores were assigned to each of the categories where similarity values
above the 50th percentile were assigned a score of 5, similarities between the 50th and 10th
percentiles had a score of 3, and similarity values below the 10th percentile had a score of 1.
73
3.6.3 Results & discussion
Cool-temperate estuaries
For estuaries in the cool-temperate region, the species richness of seven systems exceeded
the upper 95% confidence limit of the average number of species for the entire region. Nine
estuaries had an average (95% confidence) species richness while the species richness of the
remaining eight systems fell below the lower 95% confidence interval (Figure 3.9). Estuaries
which were relatively species poor were mostly small systems while those which had high
numbers of species were generally larger estuaries.
Based on presence/absence of species, three systems (Olifants, Bot and Klein) exhibited a
high similarity to the reference fish assemblage of the region. Thirteen systems exhibited a
moderate similarity to the total reference assemblage while the remaining eight estuaries
yielded a relatively low similarity (Figure 3.10).
A comparison of relative abundance revealed that the vast majority of the estuaries in the
region had a relatively high similarity to the reference (Figure 3.11). This is probably due to
the high dominance of L. richardsonii in the region. Two systems, the Sand and Kleinmond
had relatively low similarity values. Although the Sand had a high species richness, the low
similarity based on relative abundance may be a reflection of the high numerical dominance
of G. aestuaria in the system. This species accounted for 78% of the total number of fishes
captured in the Sand. A similar situation may have occurred in the Kleinmond where P.
knysnaensis was the dominant species, accounting for over 75% of the total catch
numerically.
In terms of their overall fish communities, only two systems, the Krom and Kleinmond, had
relatively low scores in the region (Figure 3.12).
74
Gariep
Olifants
Verlore
Berg
Diep
Houtbaai
Wildevoel
Schuster
Krom
Silwermyn
Sand
Eerste
Lourens
Sir Lowry's
Stenbras
Rooiels
Buffels (Oos)
Palmiet
Kleinmond
Bot
Onrus
Klein
Uilkraals
Ratel
0
1
2
3
4
5
6
7
8
9
10
11
12
Figure 3.9. Species richness of estuaries in the cool-temperate region. The mean number of
taxa and the 95% confidence intervals for all estuaries in the region are also indicated.
75
Gariep
Olifants
Verlore
Berg
Diep
Houtbaai
Wildevoel
Schuster
Krom
Silwermyn
Sand
Eerste
Lourens
Sir Lowry's
Stenbras
Rooiels
Buffels (Oos)
Palmiet
Kleinmond
Bot
Onrus
Klein
Uilkraals
Ratel
0
1
2
3
4
5
6
7
8
9
10
Figure 3.10. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
cool-temperate estuaries to the most frequently captured species in the region. The 10th and
50th percentiles of the similarity values are also indicated.
76
Gariep
Olifants
Verlore
Berg
Diep
Houtbaai
Wildevoel
Schuster
Krom
Silwermyn
Sand
Eerste
Lourens
Sir Lowry's
Stenbras
Rooiels
Buffels (Oos)
Palmiet
Kleinmond
Bot
Onrus
Klein
Uilkraals
Ratel
0
1
2
3
4
5
6
7
8
9
10
Figure 3.11. Bray-Curtis similarities (based on % abundance) of fish assemblages of cooltemperate estuaries to the most frequently captured species in the region. The 10th and 50th
percentiles of the similarity values are also indicated.
77
Gariep
Olifants
Verlore
Berg
Diep
Houtbaai
Wildevoel
Schuster
Krom
Silwermyn
Sand
Eerste
Lourens
Sir Lowry's
Stenbras
Rooiels
Buffels (Oos)
Palmiet
Kleinmond
Bot
Onrus
Klein
Uilkraals
Ratel
0
5
10
15
Figure 3.12.
Rating of cool-temperate estuaries based on species richness,
presence/absence and % abundance of their fish communities.
78
Warm-temperate estuaries
Type A estuaries
For type A estuaries in the warm-temperate zone, six systems had a species richness above
the average for the group. Seven estuaries had an average (95% confidence) species
richness and the remaining four systems had a species richness below the average (< lower
95% confidence interval) for the group (Figure 3.13).
In terms of their species assemblages, six systems had relatively high similarity values, eight
estuaries had moderate values and three systems (Matjies, Slang, Mtendwe) had relatively
low similarities (Figure 3.14). In the case of the Matjies and Slang this is probably a
reflection of the low number of species captured in these systems.
Based on the relative abundance of their species, six estuaries had relatively high similarity
values, eight systems exhibited moderate similarities, and the remaining three systems had
relatively low similarities (Figure 3.15). These were the Klipdriftfontein, Klipdrif (Oos) and
Slang. In the case of the Klipdriftfontein and Klipdrif (Oos), the high numerical dominance
of L. richardsonii (93% and 97% respectively) may account their low similarity values.
The fish community of the Slang was dominated by juvenile mullet (98%) and this probably
also accounted for its low similarity to the reference community.
In terms of their overall fish communities, 11 estuaries were rated relatively high, two
systems had moderate overall ratings, and the remaining four estuaries had relatively poor
ratings (Figure 3.16).
79
Klipdriftfontein
Noetsie
Matjies
Klipdrif (Oos)
Slang
Maitland
Thatshana
Lilyvale
Hlozi
Blind
Hlaze
Cunge
Imtwendwe
Mtendwe
Ncizele
Sundwana
Thsani
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Figure 3.13. Species richness of type A estuaries in the warm-temperate region. The mean
number of taxa and the 95% confidence interval for all type A estuaries in the region are also
indicated.
80
Klipdriftfontein
Noetsie
Matjies
Klipdrif (Oos)
Slang
Maitland
Thatshana
Lilyvale
Hlozi
Blind
Hlaze
Cunge
Imtwendwe
Mtendwe
Ncizele
Sundwana
Thsani
0
1
2
3
4
5
6
7
8
9
10
Figure 3.14. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type A estuaries to the most frequently captured species for this type of system in the warmtemperate region. The 10th and 50th percentiles of the similarity values are also indicated.
81
Klipdriftfontein
Noetsie
Matjies
Klipdrif (Oos)
Slang
Maitland
Thatshana
Lilyvale
Hlozi
Blind
Hlaze
Cunge
Imtwendwe
Mtendwe
Ncizele
Sundwana
Thsani
0
1
2
3
4
5
6
7
8
9
10
Figure 3.15. Bray-Curtis similarities (based on % abundance) of fish assemblages of type A
estuaries to the most abundant species for this type of system in the warm-temperate region.
The 10th and 50th percentiles of the similarity values are also indicated.
82
Klipdriftfontein
Noetsie
Matjies
Klipdrif (Oos)
Slang
Maitland
Thatshana
Lilyvale
Hlozi
Blind
Hlaze
Cunge
Imtwendwe
Mtendwe
Ncizele
Sundwana
Thsani
0
5
10
15
Figure 3.16. Rating of type A estuaries in the warm-temperate region based on species
richness, presence/absence and % abundance of their fish communities.
83
Type B estuaries
Sixteen type B estuaries had a species richness above the upper 95% confidence interval of
the mean for the group. Twelve systems had an average (95% confidence) species richness
and the remaining 14 had a richness below the lower 95% confidence interval of the average
(Figure 3.17).
In terms of presence/absence, most of the estuaries had relatively high similarities, seven
systems had moderate similarity values and only one estuary (Groot (Wes)) had a relatively
low similarity (Figure 3.18). This is probably a result of the low number of species captured
in the system during this survey.
Based on relative abundance, 30 estuaries had relatively high similarity values and nine
systems were moderately similar to the reference assemblage. The remaining three estuaries
(Touw, Groot (Wes), Ngogwane) had relatively low similarity values (Figure 3.19)
suggesting that these systems were dominated by different species in relation to the
reference. The Touw estuary was dominated by L. richardsonii (37%), R. holubi (18%),
and Liza spp. (13%) while the Groot (Wes) was dominated by L. lithognathus (34%), L.
richardsonii (30%) and P. knysnaensis (25%). The dominant fishes captured in the
Ngogwane were M. capensis (76%) and G. aestuaria (11%).
A total of 31 estuaries in type B had a good overall rating based on all three measures of
their fish communities. Ten systems had a moderate overall rating while only one estuary,
Groot (Wes), had a low overall rating (Figure 3.20).
84
Blinde
Hartenbos
Touw
Groot (Wes)
Tsitsikamma
Seekoei
Kabeljous
Van Stadens
Boknes
Kasuka
Riet
Wes-Kleinemond
Oos-Kleinemond
Old Womans
Mpekweni
Mtati
Mgwalana
Bira
Gqutywa
Mtana
Ngqinisa
Kiwane
Ross' Creek
Ncera
Mlele
Mcantsi
Gxulu
Goda
Hickmans
Qinira
Cintsa
Cefane
Kwenxura
Nyara
Haga-Haga
Morgan
Gxara
Ngogwane
Qolora
Cebe
Zalu
Ngqwara
0
5
10
15
20
25
30
35
Figure 3.17. Species richness of type B estuaries in the warm-temperate region. The mean
number of taxa and the 95% confidence interval for all type B estuaries in the region are also
indicated.
85
Blinde
Hartenbos
Touw
Groot (Wes)
Tsitsikamma
Seekoei
Kabeljous
Van Stadens
Boknes
Kasuka
Riet
Wes-Kleinemond
Oos-Kleinemond
Old Womans
Mpekweni
Mtati
Mgwalana
Bira
Gqutywa
Mtana
Ngqinisa
Kiwane
Ross' Creek
Ncera
Mlele
Mcantsi
Gxulu
Goda
Hickmans
Qinira
Cintsa
Cefane
Kwenxura
Nyara
Haga-Haga
Morgan
Gxara
Ngogwane
Qolora
Cebe
Zalu
Ngqwara
0
1
2
3
4
5
6
7
8
9
10
Figure 3.18. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type B estuaries to the most frequently captured species for this type of system in the warmtemperate region. The 10th and 50th percentiles of the similarity values are also indicated.
86
Blinde
Hartenbos
Touw
Groot (Wes)
Tsitsikamma
Seekoei
Kabeljous
Van Stadens
Boknes
Kasuka
Riet
Wes-Kleinemond
Oos-Kleinemond
Old Womans
Mpekweni
Mtati
Mgwalana
Bira
Gqutywa
Mtana
Ngqinisa
Kiwane
Ross' Creek
Ncera
Mlele
Mcantsi
Gxulu
Goda
Hickmans
Qinira
Cintsa
Cefane
Kwenxura
Nyara
Haga-Haga
Morgan
Gxara
Ngogwane
Qolora
Cebe
Zalu
Ngqwara
0
1
2
3
4
5
6
7
8
9
10
Figure 3.19. Bray-Curtis similarities (based on % abundance) of fish assemblages of type B
estuaries to the most abundant species for this type of system in the warm-temperate region.
The 10th and 50th percentiles of the similarity values are also indicated.
87
Blinde
Hartenbos
Touw
Groot (Wes)
Tsitsikamma
Seekoei
Kabeljous
Van Stadens
Boknes
Kasuka
Riet
Wes-Kleinemond
Oos-Kleinemond
Old Womans
Mpekweni
Mtati
Mgwalana
Bira
Gqutywa
Mtana
Ngqinisa
Kiwane
Ross' Creek
Ncera
Mlele
Mcantsi
Gxulu
Goda
Hickmans
Qinira
Cintsa
Cefane
Kwenxura
Nyara
Haga-Haga
Morgan
Gxara
Ngogwane
Qolora
Cebe
Zalu
Ngqwara
0
5
10
15
Figure 3.20. Rating of type B estuaries in the warm-temperate region based on species
richness, presence/absence and % abundance of their fish communities.
88
Type D estuaries
In type D systems, four estuaries had species richness values which exceeded the upper
95% confidence interval of the mean for the group. Four estuaries had an average (95%
confidence) species richness and two systems, the Lottering and Storms, had a below
average (< lower 95% confidence limit) species richness (Figure 3.21).
Based on their species assemblages, two systems (Gwaing and Elands) had relatively high
similarity values, six systems had a moderate similarities and the remaining two systems
(Storms and Lottering) had relatively low similarity values (Figure 3.22).
In terms of relative species abundance, two estuaries (Maalgate and Groot (Oos) had high
similarity values, three had moderate similarities and five estuaries had relatively low
similarity values (Figure 3.23). Of these estuaries, a high dominance by L. richardsonii, M.
capensis, and M. falciformis may account for the low similarity values of the Gwaing,
Lotering and Storms respectively. Liza richardsonii accounted for 96% of the total catch
in the Gwaing, M. capensis comprised 98% of the fish total abundance in the Lottering and
M. falciformis comprised 81% of the catch in the Storms. In the case of the Kaaimans and
Sout, the low similarity values may be a reflection of these systems being dominated by
different species in relation to the reference assemblage.
Overall, three estuaries in this group had a high rating based on all three fish community
parameters.
Five estuaries were rated moderately and the remaining two estuaries
(Lottering and Storms) had a low overall rating (Figure 3.24). The low overall rating in the
Storms may be a reflection of sampling difficulties as this system is very deep and fjord-like.
89
Maalgate
Gwaing
Kaaimans
Sout
Bloukrans
Lottering
Elandsbos
Storms
Elands
Groot (Oos)
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Figure 3.21. Species richness of type D estuaries in the warm-temperate region. The mean
number of taxa and the 95% confidence interval for all type D estuaries in the region are also
indicated.
Maalgate
Gwaing
Kaaimans
Sout
Bloukrans
Lottering
Elandsbos
Storms
Elands
Groot (Oos)
0
1
2
3
4
5
6
7
8
9
10
Figure 3.22. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type D estuaries to the most frequently captured species for this type of system in the warmtemperate region. The 10th and 50th percentiles of the similarity values are also indicated.
90
Maalgate
Gwaing
Kaaimans
Sout
Bloukrans
Lottering
Elandsbos
Storms
Elands
Groot (Oos)
0
1
2
3
4
5
6
7
8
9
10
Figure 3.23. Bray-Curtis similarities (based on % abundance) of fish assemblages of type D
estuaries to the most abundant species for this type of system in the warm-temperate region.
The 10th and 50th percentiles of the similarity values are also indicated.
Maalgate
Gwaing
Kaaimans
Sout
Bloukrans
Lottering
Elandsbos
Storms
Elands
Groot (Oos)
0
5
10
15
Figure 3.24. Rating of type D estuaries in the warm-temperate region based on species
richness, presence/absence and % abundance of their fish communities.
91
Type E estuaries
Five estuaries belonging to type E in the warm-temperate region had a species richness
which exceeded the average (>upper 95% confidence interval) for the group. Six systems
had an average (95% confidence) species richness, and four estuaries had a species richness
below the average (<lower 95% confidence interval) (Figure 3.25).
Based on both
presence/absence and relative abundance, all the type E estuaries in this region had
moderate to high similarities to the reference communities (Figures 3.26 & 3.27). In terms
of their overall ranking, nine systems were rated good while the remaining six systems had
moderate ranking. No systems were rated poor (Figure 3.28).
92
Piesang
Rufane
Ngculura
Shelbertsstroom
Bulura
Cwili
Jujura
Ngadla
Ku-Mpenzu
Ku-Bhula
Kwa-Suku
Ntlonyane
Nkanya
Nenga
Mapuzi
0
5
10
15
20
25
Figure 3.25. Species richness of type E estuaries in the warm-temperate region. The mean
number of taxa and the 95% confidence interval for all type E estuaries in the region are also
indicated.
93
Piesang
Rufane
Ngculura
Shelbertsstroom
Bulura
Cwili
Jujura
Ngadla
Ku-Mpenzu
Ku-Bhula
Kwa-Suku
Ntlonyane
Nkanya
Nenga
Mapuzi
0
1
2
3
4
5
6
7
8
9
10
Figure 3.26. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type E estuaries to the most frequently captured species for this type of system in the warmtemperate region. The 10th and 50th percentiles of the similarity values are also indicated.
94
Piesang
Rufane
Ngculura
Shelbertsstroom
Bulura
Cwili
Jujura
Ngadla
Ku-Mpenzu
Ku-Bhula
Kwa-Suku
Ntlonyane
Nkanya
Nenga
Mapuzi
0
1
2
3
4
5
6
7
8
9
10
Figure 3.27. Bray-Curtis similarities (based on % abundance) of fish assemblages of type E
estuaries to the most abundant species for this type of system in the warm-temperate region.
The 10th and 50th percentiles of the similarity values are also indicated.
95
Piesang
Rufane
Ngculura
Shelbertsstroom
Bulura
Cwili
Jujura
Ngadla
Ku-Mpenzu
Ku-Bhula
Kwa-Suku
Ntlonyane
Nkanya
Nenga
Mapuzi
0
5
10
15
Figure 3.28. Rating of type E estuaries in the warm-temperate region based on species
richness, presence/absence and % abundance of their fish communities.
96
Type F estuaries
Fourteen type F systems had an above average (>95% confidence interval) richness, seven
systems had an average (95% confidence) species richness while the remaining 14 estuaries
had a species richness below the 95% confidence interval of the average for the group
(Figure 3.29). Most of these estuaries are situated at the southern limit of this biogeographic
region and this may account for the relatively low species richness recorded.
In terms of their fish assemblages, all the estuaries of this type had moderate to high
similarities to the reference assemblage (Figure 3.30).
Based on their species relative abundance, 20 systems had relatively high similarities, 12
estuaries had moderate similarities and the remaining three systems (Breë, Duiwenhoks,
Great Kei) had relatively low similarity values (Figure 3.31). This is a reflection of these
estuaries being dominated by different species in relation to the reference community. The
fish community of the Breë was dominated by L. richardsonii (44%), C. gilchristi (17%)
and L. dumerilii (10%). In the Duiwenhoks, Liza spp. (43%), L. richardsonii (29%) and
A. breviceps (17%) were the dominant taxa. The fish fauna of the Great Kei was
dominated by M. cephalus (20%), S. bleekeri (15%) and P. commersonnii (15%).
Overall, 21 estuaries were rated good, 12 systems had a moderate rating and two systems
(Duiwenhoks and Great Kei) had relatively poor ratings (Figure 3.32).
97
Heuningnes
Bree
Duiwenhoks
Goukou
Gourits
Klein Brak
Groot Brak
Swartvlei
Goukamma
Knysna
Keurbooms
Kromme
Gamtoos
Swartkops
Sundays
Bushmans
Kariega
Kowie
Great Fish
Keiskamma
Tyolomnqa
Buffalo
Nahoon
Gqunube
Kwelera
Quko
Great Kei
Kobonqaba
Ngqusi/Inxaxo
Qora
Shixini
Mbashe
Xora
Mtata
Mdumbi
0
5
10
15
20
25
30
35
40
Figure 3.29. Species richness of type F estuaries in the warm-temperate region. The mean
number of taxa and the 95% confidence interval for all type F estuaries in the region are also
indicated.
98
Heuningnes
Bree
Duiwenhoks
Goukou
Gourits
Klein Brak
Groot Brak
Swartvlei
Goukamma
Knysna
Keurbooms
Kromme
Gamtoos
Swartkops
Sundays
Bushmans
Kariega
Kowie
Great Fish
Keiskamma
Tyolomnqa
Buffalo
Nahoon
Gqunube
Kwelera
Quko
Great Kei
Kobonqaba
Ngqusi/Inxaxo
Qora
Shixini
Mbashe
Xora
Mtata
Mdumbi
0
1
2
3
4
5
6
7
8
9
10
Figure 3.30. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type F estuaries to the most frequently captured species for this type of system in the warmtemperate region. The 10th and 50th percentiles of the similarity values are also indicated.
99
Heuningnes
Bree
Duiwenhoks
Goukou
Gourits
Klein Brak
Groot Brak
Swartvlei
Goukamma
Knysna
Keurbooms
Kromme
Gamtoos
Swartkops
Sundays
Bushmans
Kariega
Kowie
Great Fish
Keiskamma
Tyolomnqa
Buffalo
Nahoon
Gqunube
Kwelera
Quko
Great Kei
Kobonqaba
Ngqusi/Inxaxo
Qora
Shixini
Mbashe
Xora
Mtata
Mdumbi
0
1
2
3
4
5
6
7
8
9
10
Figure 3.31. Bray-Curtis similarities (based on % abundance) of fish assemblages of type F
estuaries to the most abundant species for this type of system in the warm-temperate region.
The 10th and 50th percentiles of the similarity values are also indicated.
100
Heuningnes
Bree
Duiwenhoks
Goukou
Gourits
Klein Brak
Groot Brak
Swartvlei
Goukamma
Knysna
Keurbooms
Kromme
Gamtoos
Swartkops
Sundays
Bushmans
Kariega
Kowie
Great Fish
Keiskamma
Tyolomnqa
Buffalo
Nahoon
Gqunube
Kwelera
Quko
Great Kei
Kobonqaba
Ngqusi/Inxaxo
Qora
Shixini
Mbashe
Xora
Mtata
Mdumbi
0
5
10
15
Figure 3.32. Rating of type F estuaries in the warm-temperate region based on species
richness, presence/absence and % abundance of their fish communities.
101
Subtropical estuaries
Type A estuaries
Of the type A estuaries in the subtropical region, one system (Gxwaleni) had a relatively high
species richness and one system (Damba) had a relatively low richness. The remaining four
estuaries had an average (95% confidence) species richness (Figure 3.33). In terms of their
fish community structure, almost all the systems had moderate to high similarities to the
reference faunal assemblages both qualitatively and quantitatively. Only the Gxwaleni had a
relatively low similarity based on percent species abundance (Figures 3.34 & 3.35).
Overall, all the estuaries belonging to this type were rated moderate to good (Figure 3.36).
102
Gxwaleni
Mvutshini
Kongweni
Damba
Mkumbane
Mzimayi
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Figure 3.33. Species richness of type A estuaries in the subtropical region. The mean
number of taxa and the 95% confidence interval for all type A estuaries in the region are also
indicated.
Gxwaleni
Mvutshini
Kongweni
Damba
Mkumbane
Mzimayi
0
1
2
3
4
5
6
7
8
9
10
Figure 3.34. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type A estuaries to the most frequently captured species for this type of system in the
subtropical region. The 10th and 50th percentiles of the similarity values are also indicated.
103
Gxwaleni
Mvutshini
Kongweni
Damba
Mkumbane
Mzimayi
0
1
2
3
4
5
6
7
8
9
10
Figure 3.35. Bray-Curtis similarities (based on % abundance) of fish assemblages of type A
estuaries to the most abundant species for this type of system in the subtropical region. The
10th and 50th percentiles of the similarity values are also indicated.
Gxwaleni
Mvutshini
Kongweni
Damba
Mkumbane
Mzimayi
0
5
10
15
Figure 3.36. Rating of type A estuaries in the subtropical region based on species richness,
presence/absence and % abundance of their fish communities.
104
Type B estuaries
Eight estuaries belonging to type B had a relatively high species richness, six systems had an
average (95% confidence) species richness while the remaining nine estuaries had a species
richness below the 95% confidence limit of the mean for this group (Figure 3.37).
The fish communities in almost all the estuaries had moderate to high similarities to the
reference ichthyofaunal assemblages based on both presence/absence and percent
abundance (Figures 3.38 & 3.39). The low number of species captured in the Kaba may
account for its relatively low similarity value based on presence/absence. Although the
Zinkwasi had a high species richness, this system had a relatively low similarity value based
on percent abundance. The fish fauna in the Zinkwasi was dominated by V. cunnesius
(34%) and A. productus (24%).
Overall, almost all the estuaries belonging to type B in this region had moderate to high
rankings based on all three analyses. Only the Kaba had a relatively low overall rating
(Figure 3.40).
105
Mtentwana
Kandandlovu
Mpenjati
Umhlangankulu
Kaba
Mbizana
Bilanhlolo
Mlangeni
Mtentweni
Mhlangamkulu
Intshambli
Fafa
Sezela
Mpambanyoni
Mahlongwa
Little Manzimtoti
Manzimtoti
Sipingo
Mhlanga
Mdloti
Mdlotane
Zinkwasi
Siyai
0
5
10
15
20
25
30
35
Figure 3.37. Species richness of type B estuaries in the subtropical region. The mean
number of taxa and the 95% confidence interval for all type B estuaries in the region are also
indicated.
106
Mtentwana
Kandandlovu
Mpenjati
Umhlangankulu
Kaba
Mbizana
Bilanhlolo
Mlangeni
Mtentweni
Mhlangamkulu
Intshambli
Fafa
Sezela
Mpambanyoni
Mahlongwa
Little Manzimtoti
Manzimtoti
Sipingo
Mhlanga
Mdloti
Mdlotane
Zinkwasi
Siyai
0
1
2
3
4
5
6
7
8
9
10
Figure 3.38. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type B estuaries to the most frequently captured species for this type of system in the
subtropical region. The 10th and 50th percentiles of the similarity values are also indicated.
107
Mtentwana
Kandandlovu
Mpenjati
Umhlangankulu
Kaba
Mbizana
Bilanhlolo
Mlangeni
Mtentweni
Mhlangamkulu
Intshambli
Fafa
Sezela
Mpambanyoni
Mahlongwa
Little Manzimtoti
Manzimtoti
Sipingo
Mhlanga
Mdloti
Mdlotane
Zinkwasi
Siyai
0
1
2
3
4
5
6
7
8
9
10
Figure 3.39. Bray-Curtis similarities (based on % abundance) of fish assemblages of type B
estuaries to the most abundant species for this type of system in the subtropical region. The
10th and 50th percentiles of the similarity values are also indicated.
108
Mtentwana
Kandandlovu
Mpenjati
Umhlangankulu
Kaba
Mbizana
Bilanhlolo
Mlangeni
Mtentweni
Mhlangamkulu
Intshambli
Fafa
Sezela
Mpambanyoni
Mahlongwa
Little Manzimtoti
Manzimtoti
Sipingo
Mhlanga
Mdloti
Mdlotane
Zinkwasi
Siyai
0
5
10
15
Figure 3.40. Rating of type B estuaries in the subtropical region based on species richness,
presence/absence and % abundance of their fish communities.
109
Type E estuaries
Three type E estuaries had a relatively high species richness. Five systems had an average
(95% confidence) species richness and the remaining five estuaries had relatively low
species richness (Figure 3.41).
In terms of their fish community structure, almost all the systems belonging to type E
estuaries had moderate to high similarities to the reference faunal assemblages both
qualitatively and quantitatively. Only the Mgobezeleni had a relatively low similarity based
on percent species abundance (Figure 3.42 & 3.43). During this study a total of 14 species
was captured in the Mgobezeleni and the numerically dominant fishes included V. robustus
(41%), M. cephalus (21%) and L. macrolepis (14%).
Overall, most the estuaries were rated moderate to good. Again, only the Mgobezeleni had
a relatively poor overall score (Figure 3.44).
110
Mpande
Bulolo
Mtumbane
Ntlupeni
Butsha
Mgwegwe
Mgwetyana
Sandlundlu
Tongazi
Zotsha
Mhlabatshane
Mbokodweni
Mgobezeleni
0
5
10
15
20
25
30
Figure 3.41. Species richness of type E estuaries in the subtropical region. The mean
number of taxa and the 95% confidence interval for all type E estuaries in the region are also
indicated.
111
Mpande
Bulolo
Mtumbane
Ntlupeni
Butsha
Mgwegwe
Mgwetyana
Sandlundlu
Tongazi
Zotsha
Mhlabatshane
Mbokodweni
Mgobezeleni
0
1
2
3
4
5
6
7
8
9
10
Figure 3.42. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type E estuaries to the most frequently captured species for this type of system in the
subtropical region. The 10th and 50th percentiles of the similarity values are also indicated.
112
Mpande
Bulolo
Mtumbane
Ntlupeni
Butsha
Mgwegwe
Mgwetyana
Sandlundlu
Tongazi
Zotsha
Mhlabatshane
Mbokodweni
Mgobezeleni
0
1
2
3
4
5
6
7
8
9
10
Figure 3.43. Bray-Curtis similarities (based on % abundance) of fish assemblages of type B
estuaries to the most abundant species for this type of system in the subtropical region. The
10th and 50th percentiles of the similarity values are also indicated.
113
Mpande
Bulolo
Mtumbane
Ntlupeni
Butsha
Mgwegwe
Mgwetyana
Sandlundlu
Tongazi
Zotsha
Mhlabatshane
Mbokodweni
Mgobezeleni
0
5
10
15
Figure 3.44. Rating of type E estuaries in the subtropical region based on species richness,
presence/absence and % abundance of their fish communities.
114
Type F estuaries
In type F estuaries, four systems had a high species richness, 12 estuaries had an average
(95% confidence) richness while the remaining five systems had a relatively poor species
richness (Figure 3.45). In terms of their fish species composition, most of the estuaries had
moderate to good similarities to the reference assemblage both qualitatively and
quantitatively. Two systems, the Mvoti and Kosi Bay, had relatively poor similarity values in
both analyses (Figures 3.46 & 3.47). These two systems also had a relatively low overall
ranking. The remaining estuaries had moderate to good ratings (Figure 3.48).
A total of some 163 fish species have been recorded from the Kosi Bay system (Blaber &
Cyrus, 1981). The vast majority of these, however, are stenohaline marine species which
are associated with a small reef situated in the mouth area of the system. Blaber (1978) lists
a total of 24 common fish species which penetrate beyond the estuary. During this study 18
taxa were recorded from the system and these were dominated by A. natalensis (28%), L.
macrolepis (16%), G. methueni (16%), T. jarbua (14%) and V. robustus (11%). The
low overall ranking of Kosi Bay is most likely due to the clear conditions encountered during
this survey making fish capture difficult due to increased net avoidance.
In the Mvoti estuary, 13 taxa were recorded. Liza spp. (28%), V. cunnesius (13%),
Valamugil spp. (12%), O. mossambicus (11%), M. capensis (10%), M. cephalus (9%),
T. jarbua (7%), juvenile mullet (Mugilidae) (5%) and C. gariepinus (3%) were the
numerically dominant taxa. Begg (1984) noted that the Mvoti was a river-dominated system
which contained a distinctive fauna quite dissimilar to other estuaries in KwaZulu-Natal. The
low rating for the Mvoti during this study may be due to the strong freshwater influence in
the system limiting its utilisation by marine species which characterises this group of
estuaries.
115
Sinangwana
Mngazana
Mngazi
Mzimvubu
Mntafufu
Msikaba
Mtentu
Mzamba
Mtamvuna
Mzimkulu
Mkomazi
Lovu
Mngeni
Mhlali
Mvoti
Thukela
Matigulu/Nyoni
Mlalazi
Mfolozi/Msunduzi
St Lucia
Kosi Bay
0
5
10
15
20
25
30
35
40
45
50
55
60
Figure 3.45. Species richness of type F estuaries in the subtropical region. The mean
number of taxa and the 95% confidence interval for all type F estuaries in the region are also
indicated.
116
Sinangwana
Mngazana
Mngazi
Mzimvubu
Mntafufu
Msikaba
Mtentu
Mzamba
Mtamvuna
Mzimkulu
Mkomazi
Lovu
Mngeni
Mhlali
Mvoti
Thukela
Matigulu/Nyoni
Mlalazi
Mfolozi/Msunduzi
St Lucia
Kosi Bay
0
1
2
3
4
5
6
7
8
9
10
Figure 3.46. Bray-Curtis similarities (based on presence/absence) of fish assemblages of
type F estuaries to the most frequently captured species for this type of system in the
subtropical region. The 10th and 50th percentiles of the similarity values are also indicated.
117
Sinangwana
Mngazana
Mngazi
Mzimvubu
Mntafufu
Msikaba
Mtentu
Mzamba
Mtamvuna
Mzimkulu
Mkomazi
Lovu
Mngeni
Mhlali
Mvoti
Thukela
Matigulu/Nyoni
Mlalazi
Mfolozi/Msunduzi
St Lucia
Kosi Bay
0
1
2
3
4
5
6
7
8
9
10
Figure 3.47. Bray-Curtis similarities (based on % abundance) of fish assemblages of type F
estuaries to the most abundant species for this type of system in the subtropical region. The
10th and 50th percentiles of the similarity values are also indicated.
118
Sinangwana
Mngazana
Mngazi
Mzimvubu
Mntafufu
Msikaba
Mtentu
Mzamba
Mtamvuna
Mzimkulu
Mkomazi
Lovu
Mngeni
Mhlali
Mvoti
Thukela
Matigulu/Nyoni
Mlalazi
Mfolozi/Msunduzi
St Lucia
Kosi Bay
0
5
10
15
Figure 3.48. Rating of type F estuaries in the subtropical region based on species richness,
presence/absence and % abundance of their fish communities.
119
3.7 Summary & conclusions
The fish fauna of 206 estuaries has been sampled. This represents approximately 70% of all
the ‘estuaries’ along the South African coast. Using data from these surveys the three
biogeographic regions which characterise this coastline were identified. These were the
cool-temperate west coast from the Gariep estuary to Cape Agulhas, the warm-temperate
region from Cape Agulhas to the Mdumbi estuary, and the subtropical region from the
Mdumbi to Kosi Bay.
Based on their physical/geomorphological characteristics, a number of estuary types were
identified within each biogeographic region, and each estuary type appeared to contain fairly
distinctive fish assemblages. Aspects of the fish community structure of each estuary type
within each biogeographic zone was described. This served as a reference against which the
fish communities within each estuary could be compared.
Based on an analysis of their species richness, composition and relative abundance, two
systems (8%) in the cool-temperate region had low ratings. Ten estuaries (42%) were rated
as moderate and the remaining 12 systems (50%) had a good overall rating. Of a total of
119 estuaries analysed in the warm-temperate region, nine (8%) had a relatively poor
overall rating, 35 (29%) were rated moderate and the remaining 75 (63%) had a good
overall rating. In the subtropical region, three estuaries (5%) were rated poor, 23 (36%)
had a moderate overall rating and the remaining 37 (59%) had a good rating.
Although the results presented here provide a useful summary of the status of the fish
communities in South Africa’s estuaries, these results only incorporate a few components of
the fish community structure and are based on a single survey. Future studies should
incorporate other aspects of the fish community structure such as biomass composition, lifehistory styles and trophic structure. Long-term data sets are also required to establish the
range of the natural variation between and within estuaries on a seasonal basis.
Furthermore, a number of estuaries, particularly in the Transkei, have not been sampled and
these gaps in the state of information need to be filled. Investigations into other biotic
components (vegetation, zooplankton, zoobenthos, and birds) should also be undertaken to
120
ensure a more complete appraisal of the ecological integrity of the nation’s estuarine
resource.
121
4.
WATER QUALITY
4.1 Introduction
Water quality is a particularly important issue for management of estuaries along the South
African coast because over 50% of South Africa’s people live within 100 km of the coast.
While point sources of pollution are easier to regulate, the diffuse sources are often difficult
to identify and control.
It is a well-known principle in ecology that the nature of the biological community in an
estuary is largely determined by a multiplicity of factors in its physical-chemical environment.
This is why the fish community structure was utilised as a measure of the health of estuaries.
The biotic community structure serves as an integrated measure of health, responding to
wide spread long-term conditions and changes.
However, it is important to remember that water quality can change significantly over short
periods of time. These episodic events may not be reflected in the fish community structure,
as fish are largely mobile and may temporarily accommodate or avoid periods of water
quality deterioration. In addition, biotic change will lag physical-chemical changes, and
hence the water quality characteristics may foreshadow long-term trends. For example, the
presence of increasing concentrations of nutrients may indicate future eutrophication with all
of its attendant problems. Finally, there are some water quality characteristics which are of
great importance to man which are not reflected by fish community structure. The suitability
of estuaries for contact recreation is just one such example.
4.2 Background
The use of indices to condense and summarise large volumes of water quality data has
increasingly gained acceptance in the last decade (Harding & Eckstein, 1996). This has
come about largely because of a practical need to succinctly compare the overall water
quality at many different locations. What is necessary in this respect is a simple, objective,
consistent, and reproducible numeric scale on which to represent water quality information.
122
Indices are able to facilitate quantification, simplification and communication of complex
environmental data. They also generate actions to solve the problems they summarise,
because they can serve as tools for monitoring the state of environment. This approach is
well known and widely applied in many fields, such as economics. Unfortunately the
scientists who develop indices generally have little to say regarding how the summarised
information will be used by decision makers and politicians, who are often far removed from
the original data. As a consequence, the danger exists of making ill-informed decisions.
However, it is generally the case that an index can interpret complex information objectively,
which permits the decision maker to make a better decision than would have been taken in
the absence of information.
A summary of a review of the use of water quality indices in the literature is contained in
Table 4.1. It is immediately apparent that only two studies involved estuaries and this
includes earlier work conducted during the course of this study (Cooper et al., 1994), the
remainder being restricted to inland waters. Only one other study (Richardson, 1997)
involved estuaries. This recent study by Richardson (1997) draws heavily from Cooper et
al. (1994) and adapts this approach to the estuaries of New South Wales, Australia. It is
important to note that the index developed by Richardson (1997) has not yet been applied
to actual field data.
123
Table 4.1. Review of Water Quality indices in the literature, indicating the indicators
utilised, the applicable aquatic system and the location applied.
Reference
physical
Water Quality Indicators
chemical bacteriological
Aquatic system
Country
rivers
estuaries
rivers
fresh water
rivers
rivers
rivers
rivers
rivers
rivers
rivers
rivers
estuaries
rivers
waterways
lakes
waterways
rivers
water treatment
USA
South Africa
USA
USA
Poland
USA
Nigeria
USA
UK
USA
South Africa
Canada
Australia*
UK
New Zealand
USA
USA
South Africa
USA
toxic
Brown et al. (1970+ )
Cooper et al. (1994)
Cude (1997)
Dinius (1987)
Dojilido et al. (1994)
Dunnette (1979)
Erondu & Nduka (1993)
Horton (1965) +
House (1989, 1990)
Joung et al. (1979)
Moore (1990)
Prati et al. (1971)
Richardson (1997)
Ross (1977) +
Smith (1989, 1990)
Steinhardt et al. (1982)
Walski & Parker (1971)
Wepener et al. (1992)
Yu & Fogel (1978)
+ cited from Couillard & Lefebvre (1985)
* not yet applied in Australia
Figure 4.1 summarises the process used for developing the estuarine water quality index.
This process is not unique but is basically the same as the approach taken by numerous
investigators in this field.
As illustrated in Figure 4.1, there are four basic steps involved in the development of most
water quality indices. These include:
1. selecting the set of water quality variables (indicators) of concern
2. developing rating curves for comparing indicators on a common scale
3. weighting the indicators based on their relative importance to overall water quality
4. formulating and computing the overall water quality index
Dunnette (1979), House (1989), Moore (1990), Richardson (1997), and others have
thoroughly discussed and described these steps and the theory behind constructing water
quality indices. However, for the purposes of this report, a brief discussion of the major
concepts involved in Figure 4.1 is necessary.
124
Parameter
Selection
Selection Criteria
Review existing indices
Review proposed list
SA estuarine water quality
Impairment categories
Aquatic Life
Human Contact
Trophic Status
Justification
Adopt
Parameters
Parameter
Transformation
Quality Rating
Aggregation
Develop Rating Curves
Select Scale
Weight
Parameter
Derive Rating Curves
Literature
vs
WQ Guidelines
Conduct
Sensitivity
Analyses
Select Rating
Curves
Select
Aggregation
Formula
Subindex
Indicators
Index
Aggregation
Estuarine
Water Quality
Classification
Figure 4.1. The process of development of the Estuarine Water Quality Index (eWQI).
Adapted from Richardson (1997).
125
Selecting indicators:
In brief, Dunnette (1979) recommended that variables of concern to water quality should be
selected from five commonly recognised impairment categories including: (1) oxygen status,
(2) eutrophication, (3) health aspects, (4) physical characteristics, and (5) dissolved
substances. It should be noted that these recommendations were based on perceived
requirements of freshwater and not marine or estuarine systems. Richardson (1997) has
more recently reviewed the literature and his conclusions agree substantially with those of
Dunnette (1979).
Indicator transformation:
Water quality indicators are generally expressed in many different units (for example: parts
per million, counts per volume, percent of saturation, etc). This makes simple aggregation
impossible. As a consequence, another important step in developing an index involves the
transformation of all indicators to an equal, dimensionless scale.
This is generally
accomplished through the use of rating curves, where indicator concentration is mapped
against a dimensionless measure such as relative water quality value. Such rating curves are
common in the literature, although these, in the past, have been based on the importance of
an indicator to freshwater systems (Brown et al., 1970; Cude, 1997; House, 1989; Moore,
1990; Stojda & Dojlido, 1983; Walski & Parker, 1974; Wepener et al., 1992).
Indicator weighting:
It is also generally acknowledged that some indicators are more important to “average
water quality” than others. It is thus necessary to weight the indicators appropriately. The
assignment of weights is generally accomplished by some sort of consensus or Delphi
technique and is based upon the judgement of the experts consulted.
Index aggregation formulations:
A variety of index aggregation formulas have been used by previous investigators. These
(and the frequency of their usage in the literature reviewed) is summarised in Table 4.2.
126
Table 4.2. Summary of aggregation methods used by various investigators.
METHOD
Solway modified unweighted and
weighted sum
REFERENCE
House (1989), Moore (1990)
Couillard & Lefebvre (1985)
USAGE
5
Arithmetic unweighted and weighted
mean
Ott (1978), Brown et al. (1970)
Walski & Parker (1974)
Stojda & Dojlido (1983)
5
Unweighted harmonic square mean
Dojlido et al. (1994)
3
Weighted product
Couillard & Lefebre (1985)
1
Geometric mean
Walski & Parker (1974)
2
Minimum operator
Smith (1989), Ott (1978)
1
Weighted sum
Brown et al. (1970), Moore (1990)
1
House (1989) conducted a review of these many different index formulations in the literature
and concluded that the modified arithmetic weighted mean (Stojda & Dojlido, 1983), or
Solway modified weighted sum (Couillard & Lefebvre, 1985), provides the best results for
general water quality indexing. Moore (1990) further concluded that the Solway modified
weighted sum was the most suitable formulation for a general water quality index in the
South African context.
This formulation was considered to be most applicable by Moore (1990) because:
•
it is sensitive to changes in water quality indicators throughout their range
•
it lacks bias to either good or poor water quality, i.e. reflects average water
quality
•
it includes weighting factors as all indicators of concern are not equally important
contributors to average water quality
•
it is relatively easy to compute on a routine basis
127
Where the index takes on the range 0 - 10, this formulation can be expressed as:
1 
n
2
 ∑ qi w i 
10  i = 1

and
(1)
n
=
number of indicators of concern
qi
=
the water quality rating value of the ith indicator
wi
=
the weighting of the ith indicator
The water quality rating value (q) for each indicator (i) is determined from a rating curve as
described above, which relates the observed concentration to a corresponding water quality
rating value between 0 and 100.
Richardson (1997) has recently thoroughly reviewed the various index aggregation formulas
reported in the literature. He has argued in favour of the unweighted harmonic square mean
formulation for the development of an estuarine water quality index for New South Wales,
Australia. The merits of this approach to South African estuaries will be discussed in a later
section.
4.3 Water quality surveys
For the purpose of this study, the primary objective was to obtain a “snapshot” of average
water quality for comparative purposes. The possibility of applying a water quality indexing
approach to South African estuaries, using existing data collected during other surveys was
investigated. However, after a thorough review and evaluation of the available data, it was
concluded that existing data were not suitable.
Firstly, no significant water quality
information existed for more than half of the estuaries. In addition, in order to obtain a
meaningful synoptic comparison of the existing water quality in South African estuaries, it is
necessary to have available a set of data which is internally consistent. This requires that all
data are collected from comparable locations within each system, using similar techniques,
128
and within as narrow a time window as practical. The mouth condition of each system must
be noted, and where salinity layering is observed, surface and bottom samples must be
collected.
To obtain such a set of internally consistent data, water quality surveys were conducted on
250 estuaries between 1992 and 1998. Logistical constraints restricted the sampling
program to manageable regions of the South African coastline during this period. Table 4.3
below shows the dates for each region of coastline surveyed.
Table 4.3. Region of coastline and dates sampled.
Region
Dates Sampled
KwaZulu-Natal (Mtamvuna – Thukela)
October 19 - November 12, 1992
west/south-west coast (Gariep – Buffels (Oos))
January 17 - February 6, 1994
south-west/south coast (Palmiet – Sout)
June 5-27, 1994
south/south-east coast (Groot (Wes) – Great Fish)
July 26 - August 12, 1995
south-east coast (Old Womans – Great Kei)
July 9-25, 1996
Transkei (Gxara – Mtentwana)
March 3-26, 1998
It is important to clearly understand that the main objective of this study was to provide a
“snapshot” of “average” water quality for internal comparison of South African estuarine
systems. While the deficiencies of basing evaluation of water quality on one sample set is
acknowledged, it is important to remember that, prior to this survey, no significant water
quality information was available for over two-thirds of South Africa’s estuaries. This survey
provides the first nation-wide baseline of estuarine water quality, and must be regarded as
an important beginning.
Furthermore, no attempt to summarise the comparative water
quality of all of the estuaries has previously been made.
Water samples and associated physical-chemical measurements were obtained from one to
five sites within each system from the mouth area to the head area. The number of samples
taken was based on an analysis of aerial photographs prior to the survey and on
observations of each system made at the time of the survey. Where water depth was
greater than 50 cm and/or salinity layering strong, samples and measurements were obtained
129
at approximately 25 cm below the surface and 25 cm above the bottom. The following data
were obtained for each site:
Table 4.4. Water quality Indicators measured during the estuary surveys.
time
water depth
secchi depth
salinity
temperature
dissolved oxygen
oxygen absorbed
total ammonia
faecal coliforms
pH
turbidity
nitrate nitrogen
ortho-phosphate
mouth condition
conductivity
Water quality measurements of temperature, turbidity, dissolved oxygen, pH and
conductivity were taken in situ using a Horiba U-10 Water Quality Checker. Water
samples were taken using generally accepted procedures and analyses were conducted
within 24 hours of sample collection. Total ammonia, nitrate nitrogen and orthophosphate
were determined using the Merck Spectroquant analysis system together with a Merck
SQ118 photometer.
Bacteriological water quality (faecal coliforms) was determined
following the South African Bureau of Standards method 221 together with an ELE
Paqualab system for microbiological water analysis. Oxygen absorbed was determined by
titration in accordance with the South African Bureau of Standards method 220. All
equipment and methods were verified prior to the field surveys by running quality control
experiments of the field equipment and methods against standard laboratory equipment and
methods.
4.4 Development of estuarine water quality indices
4.4.1 Selection of variables of concern
As noted earlier, Dunnette (1979) recommended that indicators of concern to water quality
should be selected from five commonly recognised impairment categories including: (1)
oxygen status, (2) eutrophication, (3) health aspects, (4) physical characteristics, and (5)
dissolved substances.
130
It is not surprising that there is considerable variation in opinion regarding which indicators
are of the greatest importance to water quality. The literature from past and current water
quality indexing studies has been reviewed to summarise the relative importance assigned to
each indicator, which might be potentially applied to the estuaries of South Africa. Of the
various water quality indices reviewed previously in Table 4.1, forty-four separate indicators
were used in these indexing studies. Two of these indicators reflected toxic substances and
pesticides and were not considered further due to survey and analysis difficulties.
Those indicators, which were applied with a frequency of three or more, are shown in
Figure 4.2.
Chlorphyll-a
Total nitrogen
E. coli
Total dissolved solids
Total solids
Total Phosphorus
Conductivity
Turbidity
Chloride
Phosphates
Suspended solids
Temperature
Nitrates
Ammonia
Fecal coliforms
BOD5
pH
Dissolved Oxygen
0
2
4
6
8
10
12
14
16
18
20
Frequency of indicator use
Figure 4.2. Frequency of indicators used in Water Quality Indices. Solid bars indicate
parameters used in this study.
In order to determine the best indicators for the purposes of this study, the following
considerations were used. While the importance of all five impairment categories is evident
for freshwater systems, the meaning of physical characteristics (4) and dissolved substances
(5) in terms of estuarine water quality needs to be carefully considered.
131
Due to the dynamic nature of estuarine water masses under "normal" conditions, physical
characteristics and dissolved substances content of estuarine water are highly variable. The
pH and turbidity are strongly controlled by the mixing of marine and fresh water. Given the
buffering capacity of seawater, the pH of river water entering an estuary will be driven
toward 8. Thus, the pH of estuarine water generally increases towards the mouth, and an
average value for the estuary probably has little utility. Its importance, however, as an
indicator of ionic equilibria (for example in evaluating the potential for ammonia toxicity,
etc.) must be recognised.
The water quality significance of turbidity or suspended solids in estuarine water is largely
unknown. The turbidity of the river water entering estuaries is probably more closely
related to the nature of the catchment geology and geomorphology than to other factors.
Furthermore, as this more turbid water encounters the intruding seawater a zone of
maximum turbidity will often develop within the estuary. Dramatic variations in turbidity
within an estuary will often develop. On one sampling occasion a vertical plane separating
river and marine water masses was clearly visible. Here, the concept of mean turbidity for
the estuary is meaningless, and thus contributes little to a measure of average estuarine water
quality.
The major source of dissolved substances in estuaries is the intruding seawater; hence
measurement of total dissolved solids (salinity) is a much more important indicator of the
extent of seawater mixing than water quality impairment. In fact, it is the brackish nature of
estuarine water that makes this habitat unique and contributes to its resource value.
As a consequence of the above, the five impairment categories recommended by Dunnette
(1979) have been revised into three categories which are felt to be of primary importance to
water quality in estuaries. These three categories, their associated indicators, and reasons
for inclusion are listed in Table 4.5.
132
Within these categories, indicators which could be realistically measured given the time and
logistical constraints imposed by the study were then determined. This resulted in the
selection of the six indicators shown by the filled bars in Figure 4.2. Oxygen absorbed
(OA) was chosen as a practical surrogate for BOD5, which proved impractical. Also note
that chlorophyll-a was initially chosen as a seventh indicator but was later dropped for
several reasons. This is discussed later under “Conclusions & recommendations”.
It is important to note that the six water quality indicators were selected based on their
amenability to field testing, their generally accepted importance to estuarine water quality,
and their relevance as a measure of average water quality.
Table 4.5. Impairment Categories, Indicators, and their basis for inclusion in the Estuarine
Water Quality index (eWQI).
IMPAIRMENT CATEGORY
(1) suitability for
Aquatic Life
(2) suitability for
INDICATOR
BASIS FOR INCLUSION
Dissolved Oxygen
essential to aquatic faunal metabolism
Oxygen Absorbed
measure of organic loading
Unionized Ammonia
toxicity to aquatic fauna
Faecal Coliforms
presumptive evidence for human pathogens
Nitrate Nitrogen
aquatic plant growth stimulant
Ortho-Phosphate
aquatic plant growth stimulant
Human Contact
(3) Trophic Status
4.4.2. Development of rating curves
In order to standardise the concentrations of the selected indicators, rating curves were
developed.
These curves have been developed in consultation with a variety of
organisations and individuals including the Department of Water Affairs and Forestry
(DWAF), University of Natal, consulting firms, and CSIR. Where possible rating curves
which have been developed by other investigators were utilised. The rating curves for
dissolved oxygen, and faecal coliforms were taken directly from the curves developed by
Moore (1990) in conjunction with the South African Department of Water Affairs.
133
The rating curve for oxygen absorbed (OA) was adapted from the biochemical oxygen
demand (BOD) rating curve developed by Smith (1990). Observations of the relationship
between BOD and OA in several estuaries in KwaZulu-Natal have suggested that there is a
loose correlation between the two. In general the OA values have been approximately 2-3
times the BOD concentrations. As an approximation, Smith's (1990) BOD rating curve
was appropriately adjusted by this factor.
The rating curves for ammonia and nitrate were developed from data provided by the
Department of Water Affairs and Forestry. pH measurements were used to correct the
data for total ammonia to unionized ammonia. The phosphate rating curve was developed
by reviewing the literature on the relationships between water quality and known
concentrations of ortho-phosphate. Australian standards for aquatic systems were also
considered in the development of the phosphate curve.
In this regard it is important to highlight here the variance from the nutrient curves suggested
by Richardson (1997) and the reasons for utilising the curves described in this study. First
of all, there are currently no South African nutrient standards for estuarine waters. If the
Australian standards were adopted, then virtually all of South Africa’s estuaries would be
classified as eutrophic. The Australian standards reflect systems which are intrinsically
different to those in South Africa, where fluvial effects naturally produce relatively higher
nutrient concentrations. KwaZulu-Natal is a good example where nutrient concentrations,
derived from detrital sources, result in relatively high background nutrient levels. It was felt
that application of the Australian standards, and likewise Richardson’s (1997) ratings curves
(which are based on New South Wales’ guidelines) would be inappropriate.
4.4.3 Variable weighting
In order to arrive at a relative weighting of the six water quality variables, the three
impairment categories were weighted approximately equally. Thus AQUATIC LIFE was
weighted at 35%, TROPHIC STATUS at 35%, and HUMAN CONTACT at 30%. The
slightly lower rating of the human contact category was used recognising that the entire
weight would be accorded to one variable - faecal coliforms. This restrained the individual
134
weighting for faecal coliforms to within the range of weights assigned to faecal coliforms by
the respondents in the study by Moore (1990). The breakdown of weights assigned to
each of the water quality variables of concern is shown below:
Table 4.6. Relative weights assigned to variables of concern
CATEGORY
(1) suitability for
Aquatic Life
VARIABLES
BASIS FOR INCLUSION
WEIGHT
Dissolved Oxygen
essential to aquatic fauna
0.20
Oxygen Absorbed
measure of organic loading
0.05
Ammonia Nitrogen
toxicity to aquatic fauna
0.10
0.35
(2) suitability for
Faecal Coliforms
presumptive evidence for human
Human Contact
(3) Trophic Status
pathogens
0.30
Nitrate Nitrogen
aquatic plant growth stimulant
0.15
Ortho-Phosphate
aquatic plant growth stimulant
0.20
0.35
4.4.4 Formulating and computing the water quality index
The estuarine water quality index was formulated and computed using the rating curves and
variable weightings described above and based on equation (1). In the literature most water
quality indices are scaled between 0 and 100, however, for this study the eWQI index
values were scaled between 0-10.
In order to provide a single water quality index for each estuary, the surface and bottom
concentrations for each water quality variable were first calculated for the sites in each
system. Then the following protocol for each water quality indicator was applied:
For dissolved oxygen (DO) a surface-weighted (surface DO twice as important as bottom
DO) water column value was calculated. The rating curve was then applied to this
‘average’ DO concentration to obtain a water quality value for DO for each site sampled
135
within the estuary. Two rating curves were used for DO. For DO concentrations below
saturation, a DO concentration curve was applied to obtain the DO water quality value.
For concentrations at or above saturation, a DO percent saturation curve was used.
For faecal coliforms and oxygen absorbed, only surface concentrations were used with the
respective rating curves, to obtain a water quality value for each variable at each site within
each system.
For ammonia, nitrate and phosphate, the higher of the surface or bottom value was used
with the respective rating curve to obtain the appropriate water quality value for each site
within each system. In practice, the surface concentrations were virtually always the higher
of the two.
The water quality values for all six indicators at each site were combined according to
equation (1) and using the appropriate weightings to obtain a water quality index for each
site.
The water quality indices for all sites within each estuary were then averaged to obtain a
mean estuary water quality index. Where two estuaries shared a common mouth, the data
from sites within the respective estuaries were combined into a single mean estuarine water
quality index.
4.5 Results & discussion
4.5.1 Index testing
Sensitivity analysis for chlorophyll-a.
Originally, chlorophyll-a was selected as one of the indicators to be used under the trophic
status impairment category. It was felt that it was a more direct indicator of plankton
activity than nutrient concentration. It thus would serve as an excellent complement to the
nutrients. Having said this it should be noted that there is considerable debate among water
quality specialists regarding the applicability of chlorophyll-a as a measure of trophic status
of aquatic systems.
136
When field sampling began in 1992, problems were encountered with the measurement of
cllorophyll-a in the field using the method (spectrophotometer) available at the time. In the
case of the Transkei regional data, the chlorophyll-a values obtained were not reliable and
in fact were not used for computing the draft eWQIs for that region (Harrison et al., 1999).
It should be noted, however, that there are more robust field-adapted analytical methods
now available for chlorophyll determinations.
For the sake of consistency among all of the estuaries, it is clearly preferable to compute the
eWQI in exactly the same manner, using the same parameters for each system. This is also
important for any future comparative studies. For this reason the merits of removing
chlorophyll-a data from the index computation were examined.
The effects of including/removing chlorophyll-a as a parameter were investigated using the
south-east coast (Old Womans – Great Kei) regional data set. This represented the most
current data available. The WQI was computed first with, and then without the chlorophyll
data. The results of this sensitivity analysis revealed that the removal of chlorophyll-a had
no significant effect on the ranking of estuaries in the region. The removal of chlorophyll-a
produced less than 3% average change in the eWQI. Generally its removal caused a slight
decrease in the eWQIs. Furthermore, this indicator had the least overall weighting in the
computation of the index and is one of the least frequently used of the fourteen indicators
listed in Figure 4.2. For these reasons, and to preserve consistence from region to region,
chlorophyll-a was eliminated as an indicator in the final eWQI.
Sensitivity of the eWQI to aggregation formulation
Richardson (1997) concluded that the unweighted harmonic mean aggregation formula was
a more appropriate method than the Solway modified weighted sum method used in this
study. There are a number of advantages to this formulation, the most significant of which is
that no weighting of indicators must be done. This removes one of the more subjective
aspects of indicator development. Richardson (1997) also indicates that this formulation is
more sensitive to the indicator with the lowest score.
137
This may be an advantage if the index is used mainly for establishing beneficial use classes.
In this case that indicator showing the greatest impairment will dictate the use class.
However, the expressed main purpose of this study is to report a comparative “average”
water quality for each estuary. Under these constraints, the Solway aggregate suggested by
Moore (1990) is the more appropriate method for waters in South Africa.
This begs the question of how sensitive the index is to the aggregation formula. If the use of
the harmonic mean formula results in a significant difference in the ranking of the estuaries,
then its use must be objectively considered. In order to attempt a resolution a comparison
between the Solway formulation and the harmonic mean formulation using the data from
surveys of the Transkei region was run.
The harmonic mean formulation resulted in a general increase of approximately 5% in the
eWQI values. However, the use of the alternative formulation did not significantly alter the
ranking of the systems. As a consequence there is no compelling reason at this stage to
adopt this formulation over the Solway formulation used in this study.
4.5.2 National results
The summary statistics of applying the formulation described in equation (1) to the water
quality variables of concern for the 250 systems surveyed, using the protocol outlined above
are summarised in Table 4.7.
Table 4.7. Summary statistics for 249 South African ‘estuaries’.
Number of Estuaries
Mean eWQI
Median eWQI
Mode
Standard deviation
Variance
Minimum (Mbokodweni)
Maximum (Nyara)
249
6.02
6.51
5.67
1.99
3.94
0.11
9.58
138
The frequency distribution of the eWQI values was skewed with a mean of approximately
6.0. Although the distribution is not normal, it was used to create a general classification of
average water quality in South Africa’s estuaries. A one-standard-deviation range with the
mean (~6.0) at its centre was used for systems classed as “Fair”. Applying further onestandard-deviations above and below the limits for the “Fair” class result in “Good” and
“Poor” classes respectively. Finally systems with eWQI values either above or below these
limits are classified as “Very good” or “Very poor” respectively. Caution should be used
when using this classification alone, as it is based on one set of samples from each system.
These five average estuarine water quality classes are summarised as follows:
Table 4.8. Five water quality classes and their eWQI values.
Water Quality Class
eWQI value
Very Poor
eWQI<3
Poor
3<eWQI<5
Fair
5<eWQI<7
Good
7<eWQI<9
Very Good
eWQI>9
Figure 4.4 further summarises the water quality of all 250 estuaries based on the eWQI and
the above water quality classification scheme. Approximately 41% of all estuaries are
classified as “Good” or “Very Good”, 34% were classed as “Fair” and the remaining 26%
were classified as “Poor” or “Very Poor”.
139
Very Poor
Classification
Poor
Fair
Good
Very Good
0
10
20
30
40
50
Percent
Figure 4.3. National summary of water quality of South African estuaries.
4.5.3 Regional results
The overall average water quality index (on a scale of 0-10) is presented for each of the
250 systems sampled, as well as a breakdown of the overall index by its three water quality
subcategories (suitability for aquatic life, suitability for human contact, and trophic status).
The average eWQI vales for the 250 systems are arranged geographically from the west
coast (Figure 4.5), south-west coast (Figure 4.6), south coast (Figure 4.7), south-east coast
(Figure 4.8), Transkei region (Figure 4.9), and KwaZulu-Natal (Figure 4.10). It must be
noted that the Transkei region is under-represented due to extremely difficult access to most
systems.
Only 12 systems were sampled in the west coast region (Figure 4.5). Five systems (42%)
were classed as “Poor” or “Very Poor”, five systems (42%) were classified as “Fair” and
the remaining two systems (16%) were “Good” to “Very Good”. In the south-west coast
140
region, from the Dwars (Suid) to the Ratel, 32 systems were assessed (Figure 4.6).
Thirteen systems (41%) were classified as “Very Poor” to “Poor”. A total of 12 systems
(38%) were rated as “Fair”. The remaining seven systems (22%) were classed as “Good”.
A total of 52 systems were sampled in south coast region from the Heuningnes to the
Sundays (Figure 4.7). Seven systems (14%) had “Poor” eWQI values, 11 systems (21%)
were classed as “Fair” and the remaining 34 systems (65%) had “Good” to “Very Good”
eWQI values. In the south-east coast, from the Boknes to the Great Kei, 55 estuaries were
sampled (Figure 4.8). Four systems (7%) were classed as “Very Poor” or “Poor”, 13
systems (24%) had “Fair” eWQI values, and the remaining 38 systems (69%) were
classified as “Good” or “Very Good”. In the Transkei region 43 estuaries were sampled
(Figure 4.9). Fifteen systems (35%) were rated as “Very Poor” to “Poor”, 24 estuaries
(56%) had “Fair” eWQI values and only four systems had “Good” water quality. A total
of 56 estuaries were sampled in KwaZulu-Natal (Figure 4.10). Twenty systems (36%) had
“Very Poor” to “Poor” water quality, 19 estuaries (34%) were rated as “Fair” and the
remaining 17 estuaries (30%) had “Good” eWQI values.
Overall, systems on the south and south-east coastal regions had the best overall water
quality with a preponderance of these estuaries classified as “Good”. They also contain
nearly all of the systems which are classed as “Very Good”. Conversely, the Transkei and
KwaZulu-Natal have a relatively high proportion of systems in “Poor” condition. Again,
caution must be used in applying these general conclusions without corroborating
information, such as from other monitoring studies.
141
Gariep
Buffels
Swartlintjies
Spoeg
Groen
Sout (Noord)
Olifants
Jakkals
Wadrif
Verlore
Papkuils
Berg
0
1
2
3
4
5
6
7
8
9
10
eWQI
Figure 4.4. Average eWQI values for the west coast region (Gariep – Berg) indicating the
suitability for aquatic health, suitability for human contact and trophic status components of
the index.
142
Dwars (Suid)
Modder
Bok
Silwerstroom
Sout (Suid)
Diep
Soutrivier
Houtbaai
Wildevoël
Bokramspruit
Schuster
Krom
Booiskraal
Buffels (Wes)
Elsies
Silwermyn
Sand
Seekoe
Eerste
Lourens
Sir Lowry's Pass
Steenbras
Rooiels
Buffels (Oos)
Palmiet
Kleinmond
Bot
Onrus
Mossel
Klein
Uilkraals
Ratel
0
1
2
3
4
5
6
7
8
9
10
eWQI
Figure 4.5. Average eWQI values for the south-west coast region (Dwars (Suid) – Ratel)
indicating the suitability for aquatic health, suitability for human contact and trophic status
components of the index.
143
Heuningnes
Klipdrifsfontein
Breë
Duiwenhoks
Goukou
Gourits
Blinde
Hartenbos
Klein Brak
Groot Brak
Maalgate
Gwaing
Meul
Kaaimans
Touw
Swartvlei
Goukamma
Knysna
Noetsie
Grooteiland
Kranshoek
Crooks
Piesang
Keurbooms
Matjies
Brak
Sout
Groot (Wes)
Bloukrans
Lottering
Elandsbos
Storms
Elands
Groot (Oos)
Eerste
Klipdrif (Wes)
Boskloof
Kaapsedrif
Tsitsikamma
Klipdrif (Oos)
Slang
Kromme
Seekoei
Kabeljous
Gamtoos
Van Stadens
Maitland
Bakens
Papkuils
Swartkops
Ngcura
Sundays
0
1
2
3
4
5
6
7
8
9
10
eWQI
Figure 4.6. Average eWQI values for the south coast region (Heuningnes – Sundays)
indicating the suitability for aquatic health, suitability for human contact and trophic status
components of the index.
145
Boknes
Bushmans
Kariega
Kasuka
Kowie
Rufane
Riet
Wes-Kleinemond
Oos-Kleinemond
Great Fish
Old Woman's
Thatshana
Mpekweni
Mtati
Mgwalana
Bira
Gqutywa
Ngculura
Mtana
Keiskamma
Ngqinisa
Kiwane
Tyolomnqa
Shelbertsstroom
Lilyvale
Ross' Creek
Ncera
Mlele
Mcantsi
Gxulu
Goda
Hlozi
Hickmans
Mvubukazi
Ngqenga
Buffalo
Blind
Hlaze
Nahoon
QuinIra
Gqunube
Kwelera
Bulura
Cunge
Cintsa
Cefane
Kwenxura
Nyara
Imtwendwe
Haga-Haga
Mtendwe
Quko
Morgan
Cwili
Great Kei
0
1
2
3
4
5
6
7
8
9
10
eWQI
Figure 4.7. Average eWQI values for the south-east coast region (Boknes – Great Kei)
indicating the suitability for aquatic health, suitability for human contact and trophic status
components of the index.
146
Gxara
Ngogwane
Qolora
Ncizele
Kobonqaba
Ngqusi/Inxaxo
Cebe
Zalu
Ngqwara
Qora
Jujura
Ngadla
Shixini
Mbashe
Ku-Mpenzu
Ku-Bhula
Kwa-Suku
Ntlonyane
Nkanya
Sundwana
Xora
Nenga
Mapuzi
Mtata
Thsani
Mdumbi
Mpande
Sinangwana
Mngazana
Mngazi
Gxwaleni
Bulolo
Mtumbane
Mzimvubu
Ntlupeni
Mntafufu
Msikaba
Butsha
Mgwegwe
Mgwetyana
Mtentu
Mzamba
Mtentwana
0
1
2
3
4
5
6
7
8
9
10
eWQI
Figure 4.8. Average eWQI values for the Transkei region (Gxara – Mtentwana) indicating
the suitability for aquatic health, suitability for human contact and trophic status components
of the index.
147
Mtamvuna
Zolwane
Sandlundlu
Ku-Boboyi
Tongazi
Kandandlovu
Mpenjati
Umhlangankulu
Kaba
Mbizana
Mvutshini
Bilanhlolo
Uvuzana
Kongweni
Vungu
Mhlangeni
Zotsha
Boboyi
Mbango
Mzimkulu
Mtentweni
Mhlangamkulu
Damba
Koshwana
Intshambili
Mzumbe
Mhlabatshane
Mhlungwa
Mtwalumi
Mvuzi
Fafa
Mdesingane
Sezela
Mkumbane
Mzinto
Mzimayi
Mpambanyoni
Mahlongwa
Mahlongwana
Mkomazi
Lovu
Little Manzimtoti
Manzimtoti
Mbokodweni
Sipingo
Mgeni
Mhlanga
Mdloti
Tongati
Mhlali
Seteni
Mvoti
Mdlotane
Nonoti
Zinkwasi
Thukela
0
1
2
3
4
5
6
7
8
9
10
eWQI
Figure 4.9. Average eWQI values for the KwaZulu-Natal region (Mtamvuna - Thukela)
indicating the suitability for aquatic health, suitability for human contact and trophic status
components of the index.
149
4.6. Conclusions & recommendations
4.6.1 Conclusions
General
The results of this study clearly illustrate the utility of the water quality index for succinctly
identifying the relative health of South African estuaries with respect to their water quality.
While the synoptic data collected over the period of these surveys is admittedly limited to
one period, it is the only consistent data set of its kind, which has been collected nearly
simultaneously for South African estuaries. The management applications of this type of
synoptic sampling effort are readily evident when the results are focused via the index and
water quality classification approach developed here.
The use of the eWQI to produce a water quality classification system for South African
estuaries has great utility. This approach has also been followed successfully in Oregon in
the USA (Cude, 1977) and has been proposed for New South Wales, Australia
(Richardson, 1997). Given this relatively objective method for water quality classification it
is imperative that more monitoring information is collected for all of the estuaries.
Specific
•
Appropriate indicators can be obtained in the field, even under difficult survey
conditions
•
Six commonly accepted water quality indicators provide adequate coverage of
traditional impairment categories
•
Estuarine water quality can be effectively summarized using the eWQI.
•
Impairment measured by toxics such as metals and pesticides are not accounted for in
the eWQI
•
The ranking of water quality by the index was not relatively sensitive to another
aggregation method
•
The eWQI can be used to classify estuarine water quality
•
Water quality classes are useful for summarising information in order to obtain regional
and national perspective
150
4.6.2 Recommendations
A physical water quality impairment category, involving such indicators as temperature,
salinity, pH, and turbidity should be explored.
Other investigators (Moore, 1990;
Richardson, 1997) have stressed the importance of these measures to water quality. The
use of some of these have been argued against while others have indirectly been
incorporated, due to their impact on the present indicators (pH via ammonia, salinity &
temperature via DO saturation). This must be further explored and tested against the
existing database, which currently contains data on these indicators.
Related to the above, there is sound logic which suggests that water quality rating curves
might be different for different geomorphological classifications, as well as for different
climatic regions. This deserves further investigation. Again, the data to support such an
investigation currently exists in the database. In addition the factors that control the
behaviour of estuary mouths and determine the magnitude of tidal prisms may similarly
impact the shape of water quality rating curves.
While, for the first time, an internally consistent set of water quality data for two-thirds of
South Africa’s estuaries has been collected, there are some obvious significant gaps in the
baseline. First of all, data for systems in KwaZulu-Natal north of the Thukela estuary are
conspicuously lacking, as are numerous important systems in the Transkei. A cohesive plan
for temporal monitoring of key systems is also lacking. It would be logical to use the
existing geomorphological classification to establish a monitoring programme for key
systems on a rational basis. This would provide a better understanding of how estuaries of
various types function, a critical requirement for effectively managing coastal issues such as
artificial breaching, estuarine water requirements, eutrophication of estuaries, and related
nutrient enrichment of the near-shore zone.
Finally, there exists a need to make all of the basic data, as well as various forms of
summarized data, available to interested parties.
151
This is best accomplished by (1)
establishing a web-accessible hierarchical database at several scales of resolution, and (2)
producing brochures (real and virtual) for the public and other end-users.
152
5.
AESTHETICS
5.1 Introduction
South African estuaries represent one of the few sheltered environments along a rugged
coastline dominated by a high wave energy. As a result, estuaries have naturally become the
focus of coastal development for either commercial or industrial use such as ports and
harbours or as residential and recreational areas (Morant & Quinn, 1999). With the growth
of human populations and the rapid increase in urbanisation and industrial activities, the
pressure to develop estuaries will also increase. However, the protection of the estuarine
environment in the long term is essential if the natural resources provided by estuaries and
the quality of life offered by them is to be maintained (Day & Grindley, 1981).
Estuaries offer a number of socio-cultural values other than ecological or economic ones and
these socio-cultural values are often those intangible attributes which contribute to the
‘quality of life’ (Reimold et al., 1980). The open space and pristine scenery associated with
natural estuaries, attracts many people and these visitors are not only foreign or inland
visitors but also local residents enjoying the aesthetic appeal of natural areas close to home.
It often happens, however, that when an area has such aesthetic appeal people flock to it
and over-use or abuse it, thereby reducing the aesthetic qualities that attracted visitors in the
first place (Reimold et al., 1980). Apart from their aesthetic and recreational appeal,
estuaries also serve an important educational function from the non-scientific general public
to basic and applied research. Education of citizens is essential in order to develop an
awareness of the value of estuaries and ensure their conservation and long-term
sustainability. It also requires good management of the resource to maintain quality while
providing pleasure for large numbers of people (Reimold et al., 1980).
In a public relations context, aesthetic aspects of estuarine quality are an important factor
and the appearance of an estuary contributes to its perceived environmental health,
particularly in terms of its utilisation by man (Portman & Wood, 1985). Certain uses (e.g.
industrial or commercial development) change the appearance of an estuary and in so doing
150
impair its suitability for other potential uses (e.g. nature conservation/recreation/tourism). In
this section an assessment of the aesthetic state of South Africa’s estuaries is provided. It is
intended that the information presented will be of use in planning the utilisation of estuarine
areas: those which are unspoilt might, for example, be retained for nature conservation;
those with little disturbance might be suitable for recreation, as long as water quality is
suitable for that purpose; estuaries which are heavily impacted visually by industrial
development are unlikely to be of much use in encouraging tourists to the area.
5.2 Methods
The perception of the best possible appearance of an area will vary from one individual to
another and from members of one socio-economic or cultural group to another. Thus the
measurement of aesthetic health of estuaries and other wetlands is largely subjective
(Reimold et al., 1980). This problem centres on what an individual perceives the ideal state
of an estuary to be. In order to eliminate this problem and introduce a more objective
method of assessment, the aesthetic state of each estuarine area was assessed in terms of
the degree of ‘naturalness’ of the estuary. The basic premise of what we have termed the
Aesthetic Health Index is that an estuary which is totally undeveloped by man, reflecting a
maximum degree of ‘naturalness’, is in a perfect or pristine state - and deviation from this
state is indicative of ‘degradation’ or loss of aesthetic appeal.
A number of parameters contribute to the aesthetic health of an estuary and it is in the
selection and assignment of a relative value to each parameter that subjectivity is involved.
Reimold et al. (1980) in a rare assessment of the aesthetic value of estuaries noted that an
aesthetic appreciation of wetlands is essentially a sensual one, in that vision, hearing, smell,
touch and taste senses are stimulated. An objective attempt to describe subjective visualcultural values of freshwater wetlands was described where wetlands were evaluated in
terms of landform contrast, landform diversity, wetland edge complexity, wetland type
diversity, educational and recreational quality and possible outstanding elements. These
attributes were weighed and the resultant rating proved useful in comparing visual-cultural
values of different freshwater wetlands (Reimold et al., 1980). The aesthetic quality of
estuaries in the United Kingdom was assessed by Portman & Wood (1985) using factors
151
such as smell, colour, debris, oil, recognisable sewage solids, and effects from discharge of
domestic or industrial effluent. This assessment also took account of natural turbidity, algal
growth and the frequency with which floating debris was encountered (Portman & Wood,
1985).
During the development of the Aesthetic Health Index used here, a survey of 25 coastal
zone managers and planners was undertaken to identify and determine the relative
importance of the various criteria which contribute to the aesthetics an estuary (Cooper,
1993). The parameters which accommodate most of the aesthetic impacts on an estuary
were considered to be floodplain landuse, the state of the shoreline or channel margins,
development in the estuary/floodplain surrounds, bridges, dams and weirs, the degree to
which the mouth of a system is artificially stabilised, litter and rubble, the extent of human
use, invasive/exotic vegetation, algal growth and/or aquatic nuisance plants, turbidity,
odours, air pollution, and noise.
Each parameter was given a weighting from which points were deducted according to the
type and degree of impairment. The relative weighting of the various parameters are given
in the table below.
Table 5.1. Parameters and their relative weighting used in the Aesthetic Health Index.
Category
Floodplain landuse
Shoreline status
Floodplain/estuary surrounds
Bridges
Dams & weirs
Mouth stabilisation
Litter & rubble
Human use
Algal growth/ aquatic nuisance plants
Turbidity
Odour
Air pollution
Noise
Invasive & exotic vegetation
152
Weight
25
15
15
6
6
6
6
4
3
3
3
3
3
2
An information-gathering sheet was designed which could be completed in the field while
sampling. It should be noted here that the assessments were essentially conducted on the
ground from some vantage point such as a bridge and were limited to only the area visible
from that point. Assessments, particularly for the larger estuaries, were therefore generally
limited to the lower reaches of these systems. Once each estuary was scored, the overall
index value was calculated which ranged between 0 and 100. The final index values were
then rescaled between 0 and 10. An aesthetically poor or heavily developed estuary would
have a value tending toward 0 and a near-natural estuary would tend toward 10. The index
scores were then rated where systems which had values below 6 were regarded as being
aesthetically poor, systems with scores between 6 and 9 were rated as moderately impaired
aesthetically and systems with scores above 9 were rated as good.
5.3 Results & discussion
A total of 251 systems were assessed during this study. Although many systems were not
considered estuaries either because they were dry or were too small, these have been
included here since they still form part of the natural beauty that characterises our coastal
environment.
A total of 50 systems were assessed on the west and south-west coasts (Figure 5.1). Eight
systems had poor ratings. On the west coast, the Sout (Noord) comprises a salt-works
while the Berg has been developed as a fishing harbour. On the south-west coast, the Diep
and Soutrivier pass through the Cape Town metropolitan area. Both systems have been
canalised and the latter essentially serves as a drain for domestic and industrial effluent. The
remaining systems all flow into False Bay and, although only four had poor ratings, most of
the systems in this area had relatively low scores. Only four systems, Buffels (Wes),
Steenbras, Rooiels and Buffels (Oos), had relatively high scores in relation to the others in
the False Bay area. Of the poorly rated systems, the Elsies has been modified from a
marshy vlei to a canal which drains an artificial wetland; the Sand is heavily urbanised and
the system is extensively used for recreation; the Seekoe has been transformed into a canal
153
which serves largely as an outfall for treated sewage effluent. The Lourens flows near the
urban area of Strand and a factory is situated near the mouth.
In the south coast region, 53 systems were assessed (Figure 5.2). Five estuaries had poor
ratings. The Hartenbos is situated near Mossel Bay and receives treated effluent and the
Groot Brak passes through the coastal development of the same name. Development has
also resulted in a relatively low aesthetic score for the Knysna system. The Bakens and
Papkuils both fall within the Port Elizabeth metropolitan area and both systems have been
canalised. A relatively low score was obtained for the Swartkops which is also situated in
Port Elizabeth. The Ngcura (Koega) system, just north-east of Port Elizabeth has been
given over almost entirely to salt-works.
A total of 58 systems were assessed in the south-east coast and only two systems, the
Kowie and Buffalo had relatively low ratings (Figure 5.3). The Kowie passes through the
coastal town of Port Alfred.
Part of the system has been canalised and a marina
development is situated in the lower reaches. The Buffalo has been developed into an
industrial port for the city of East London.
The 43 estuaries assessed on the Transkei coast are largely undeveloped and most had
moderate to good ratings (Figure 5.4). The estuaries with relatively low ratings were mostly
situated in or near the coastal development of Port St Johns. Despite their high aesthetic
appeal, increased human pressure was apparent in many systems in the Transkei where
riparian and floodplain vegetation was being removed to make way for subsistence
agriculture.
In KwaZulu-Natal, 47 estuaries were assessed (Figure 5.5).
Three estuaries, the
Manzimtoti, Mbokodweni and Sipingo had low ratings. All these systems flow through the
industrial area of Prospecton to the south of the city centre of Durban. The Mgeni, which
also had a relatively low index score, is also situated in the Durban metropolitan area. It is
interesting to note that few estuaries in KwaZulu-Natal had good ratings. This is largely due
to the steady ribbon development in the coastal zone of this region.
154
155
Gariep
*Holgat
*Buffels
*Swartlintjies
*Spoeg
*Bitter
*Groen
*Brak
*Sout (Noord)
Olifants
*Jakkals
*Wadrif
Verlore
*Papkuils
Berg
*Dwars (Noord)
*Dwars (Suid)
*Modder
*Jacobsbaai
*Leerbaai
*Bok
*Silwerstroom
*Sout (Suid)
Diep
Soutrivier
Houtbaai
Wildevoel
*Bokramspriut
Schuster
Krom
*Booiskraal
*Buffels (Wes)
*Elsies
Silwermyn
Sand
Seekoe
Eerste
Lourens
Sir Lowry's
Steenbras
Rooiels
Buffels (Oos)
Palmiet
Kleinmond
Bot
Onrus
*Mossel
Klein
Uilkraals
Ratel
0
1
2
3
4
5
6
7
8
9
10
AHI
Figure 5.1. Aesthetic scores for estuaries on the west and south-west coast. Systems not
considered estuaries are marked with an asterisk. Vertical lines indicate cut-off values for
rating the systems.
156
Heuningnes
Klipdrifsfontein
Bree
Duiwenhoks
Goukou
Gourits
Blinde
Hartenbos
Klein Brak
Groot Brak
*Rooi
Maalgate
Gwaing
*Meul
Kaaimans
Touw
Swartvlei
Goukamma
Knysna
Noetsie
*Grooteiland
*Kranshoek
*Crooks
Piesang
Keurbooms
Matjies
*Brak
Sout
Groot (Wes)
Bloukrans
Lottering
Elandsbos
Storms
Elands
Groot (Oos)
*Eerste
*Klipdrif (Wes)
*Boskloof
*Kaapsedrif
Tsitsikamma
Klipdrif (Oos)
Slang
Kromme
Seekoei
Kabeljous
Gamtoos
Van Stadens
Maitland
Bakens
Papkuils
Swartkops
Ngcura
Sundays
0
1
2
3
4
5
6
7
8
9
10
AHI
Figure 5.2. Aesthetic scores for estuaries on the south coast. Systems not considered
estuaries are marked with an asterisk. Vertical lines indicate cut-off values for rating the
systems.
157
Boknes
Bushmans
Kariega
Kasuka
Kowie
Rufane
Riet
Wes-Kleinemond
Oos-Kleinemond
Great Fish
Old Woman's
Thatshana
Mpekweni
Mtati
Mgwalana
Bira
Gqutywa
Ngculura
*Fresh Water Poort
*Blue Krans
Mtana
Keiskamma
*Shwele-Shwele
Ngqinisa
Kiwane
Tyolomnqa
Shelbertsstroom
Lilyvale
Ross' Creek
Ncera
Mlele
Mcantsi
Gxulu
Goda
Hlozi
Hickmans
Mvubukazi
Ngqenga
Buffalo
Blind
Hlaze
Nahoon
Qinira
Gqunube
Kwelera
Bulura
Cunge
Cintsa
Cefane
Kwenxura
Nyara
Imtendwe
Haga-Haga
Mtendwe
Quko
Morgan
Cwili
Great Kei
0
1
2
3
4
5
6
7
8
9
10
AHI
Figure 5.3. Aesthetic scores for estuaries on the west and south-east coast. Systems not
considered estuaries are marked with an asterisk. Vertical lines indicate cut-off values for
rating the systems.
158
Gxara
Ngogwane
Qolora
Ncizele
Kobonqaba
Ngqusi
Cebe
Zalu
Ngqara
Qora
Jujura
Ngadla
Shixini
Mbashe
Ku-Mpenzu
Ku-Bhula
Kwa-Suku
Ntlonyane
Nkanya
Sundwana
Xora
Nenga
Mapuzi
Mtata
Tshani
Mdumbi
Mpande
Sinangwana
Mngazana
Mngazi
Gxwaleni
Bulolo
Mtumbane
Mzimvubu
Ntlupeni
Mntafufu
Msikaba
Butsha
Mgwegwe
Mgwetyana
Mtentu
Mzamba
Mtentwana
0
1
2
3
4
5
6
7
8
9
10
AHI
Figure 5.4. Aesthetic scores for estuaries on the Transkei coast. Systems not considered
estuaries are marked with an asterisk. Vertical lines indicate cut-off values for rating the
systems.
159
Mtamvuna
Sandlundlu
Tongazi
Kandandlovu
Mpenjati
Umhlangankulu
Kaba
Mbizana
Mvutshini
Bilanhlolo
Uvuzana
Knogweni
Mhlangeni
Zotsha
Mzimkulu
Mtentweni
Mhlangamkulu
Damba
Intshambili
Mhlabatshane
Fafa
Sezela
Mkumbane
Mzimayi
Mpambanyoni
Mahlongwa
Mkomazi
Lovu
Little Manzimtoti
Manzimtoti
Mbokodweni
Sipingo
Mgeni
Mhlanga
Mdloti
Mhlali
Mvoti
Mdlotane
Zinkwasi
Tugela
Matigulu/Nyoni
Siyai
Mlalazi
Mfolozi/Msundizi
St Lucia
Mgobezeleni
Kosi Bay
0
1
2
3
4
5
6
7
8
9
10
AHI
Figure 5.5. Aesthetic scores for estuaries on the KwaZulu-Natal coast. Systems not
considered estuaries are marked with an asterisk. Vertical lines indicate cut-off values for
rating the systems.
160
5.4 Summary & conclusions
Overall, of the 251 systems assessed during this study, 18 (7%) had relatively poor
aesthetic ratings, 88 (35%) had a moderate rating and 145 (58%) were rated relatively
good aesthetically.
While it is acknowledged that measuring the aesthetic value of an estuary is a somewhat
subjective assessment, the Aesthetic Health Index represents one of the first attempts by a
multidisciplinary team of scientists, to holistically and rationally measure the aesthetics of an
estuarine environment. It must be stressed, however, that although somewhat related, an
aesthetic appraisal is not the same as measuring the physical degradation in an estuary due
to human activities. The aim of aesthetic index is to provide some measure of their sociocultural value. Aesthetic parameters are commonly recognised as an important aspect of
the environment. For example, Heydorn & Tinley (1980) observed "...coast resorts...are
dependent on pristine scenery and undamaged resources".
161
6.
GENERAL SUMMARY & RECOMMENDATIONS
6.1 Introduction
In order to effectively manage coastal resources, decisions should be made based on sound
scientific information and with an agreed and attainable objective for the future state of the
coast. Progress toward achieving these goals should be monitored against the pre-existing
baseline. In an assessment of the current state of scientific knowledge of South African
estuaries, Whitflied (1995) concluded that, of the 250 systems assessed, the state of
information of 68% was “nil” to “poor”. Of the remaining estuaries, the state of information
of 22% was classified as “moderate” while only 10% were regarded as having “good” or
“excellent” information. Thus the necessary baseline information did not exist that would
permit effective management of coastal resources.
There are approximately 370 river outlets along the South African coast (Table 6.1).
During the period 1992 to 1999 a national survey was conducted on some 250 systems by
the authors. This represents approximately 67% of the country’s ‘estuaries’. Aspects of
their geomorphology, fish communities, water quality and aesthetic state were investigated.
This information was analysed and condensed to provide an assessment of the state of the
nations estuaries. The use of indices is an effective method of communicating technical
information to potential end-users who typically do not have any scientific background. It
has been pointed out, however, that the use of a composite index incorporating a number of
parameters can lead to a loss of information as a result of oversimplification (Morant &
Quinn, 1999). It is suggested that a matrix method should be adopted so that the ratings of
each component of the estuarine environment can clearly be seen. Thus some estuaries will
be seen to be important in respect of a single component whereas others may be important
in respect of two or more components. Estuaries can be assessed in this way to provide
ratings on a national, regional (political or biogeographical) or local scale (Morant & Quinn,
1999). Such an approach has been adopted here and the results are presented in Table
6.1. These results are also presented in Appendix 1 where strip maps of the coastline are
given together with a series of icons indicating the geomophological classification,
161
biogeographic region, state of the fish community, water quality and aesthetics for each
estuary.
6.2 Summary
A geomorphological classification of these systems revealed that many systems, particularly
on the west coast, were not considered to be estuaries in any accepted definition either
because they were dry or due to their small size. Six basic types of estuary were identified
(Table 6.1). There were divided into estuaries which were normally open and systems
which were normally closed. The normally open estuaries were further divided into barred
(Types E & F) and non-barred systems (Type D). The barred estuaries could be classified
according to the processes which maintain connection with the sea, that is river-dominated
systems and tide-dominated systems. A lack of data, however, has only permitted a
classification of these systems into small (Type E) and medium to large (Type F) estuaries
based on mean annual runoff (MAR). Two types of normally closed estuaries were
recognised, those where the normal water level was perched above sea level, and those
where the water level was approximately at sea level. Again a lack of sufficient data only
permitted these systems to be classified into large (Type C), medium (Type B) and small
(Type A) estuaries based on surface area.
A total of 206 estuaries were classified
geomorphologically. Of the normally closed systems, 26 (13%) were classified as type A,
71 estuaries (34%) were type B systems, and 2 (1%) were type C estuaries. Of the
normally open estuaries, 11 (5%) were type D systems, 34 (17%) belonged to type E, and
62 (30%) were type F estuaries.
This approach identifies for each type of estuary, a potential mode of physical behaviour
related to tidal exchange, sediment transport, response to fluvial floods etc. Although a
number of estuary types have been studied, there are several in which limited research has
been undertaken and their physical processes are poorly understood. There may be
differences within groups that relate to unidentified differences and these too are worthy of
further consideration. The classification enables a management perspective that does not
simply deal with the open estuaries or the large estuaries, but recognises that a range of
estuary types exists and that examples of each type should be preserved.
162
Based on ichthyofaunal surveys and the classification of the 206 estuaries, three
biogeographic regions were identified. These were the cool-temperate region from the
Gariep (Orange River) Estuary to Cape Agulhas, the warm-temperate region from Cape
Agulhas to the Mdumbi Estuary, and the subtropical region from the Mdumbi Estuary to
Kosi Bay. The various estuary types within each biogeographc region appeared to contain
fairly distinctive fish assemblages. The species richness, species composition and relative
abundance of the ichthyofauna of the various types of estuary were described for each
region.
Using these fish community characteristics as a reference, the state of the
ichthyofauna of each estuary was assessed. Overall, 14 systems (7%) had a relatively low
rating, 68 (33%) had a moderate rating and 124 (60%) had a relatively good rating (Table
6.1).
This suggests that the fish communities in most estuaries do not indicate degradation but it
does identify those that are actually or potentially degraded and in which potential problems
may exist.
Water quality surveys were conducted on some 250 systems. The water quality of each
estuary was assessed in terms of its suitability for aquatic life (dissolved oxygen, oxygen
absorbed, unionized ammonia), its trophic status (nitrate nitrogen, ortho-phosphate), and its
suitability for human contact (faecal coliforms). Overall, approximately 74% of all the
systems were classified as in a “Fair” or better condition. The remaining 24% were rated as
“Poor” or “Very Poor” (Table 6.1). The approach we have adopted enables the category
of impairment to be identified and prompts further study in estuaries identified as having
poor water quality.
The aesthetic state of 251 systems was assessed during this study, 18 (7%) had relatively
poor aesthetic ratings, 88 (35%) had a moderate rating and 145 (58%) were rated relatively
good aesthetically (Table 6.1). This finding indicates the relatively localised high levels of
aesthetic impairment adjacent to urban centres.
It also indicates the high level of
modification of the estuarine landscape through human activities. While this may not directly
163
impact on the natural environment, it serves to indicate the level of development centred on
estuaries.
6.3 Recommendations
All of the basic data, as well as various forms of summarised data, need to be made
available to interested parties from scientists to managers and even the general public.
Probably the most appropriate method of accomplishing this is via a hierarchical database
on the internet.
Much of the baseline data collected has not been fully analysed. Other aspects of fish
community structure such as biomass composition, life-history styles and trophic structure
should be investigated.
A physical water quality impairment category, involving such
indicators as temperature, salinity, pH, and turbidity should be explored as well as the
potential for creating water quality rating curves for different estuary types in different
biogeographic regions.
The geomorphological classification is based only on available data and additional
information is required to improve its resolution. In particular, data on the frequency and
persistence of mouth opening and on water and barrier crest levels is required. These may
enable further subdivision of the categories identified here. Long-term data sets are also
required to establish the range of the natural variation between and within estuaries on a
seasonal basis and to monitor key systems.
It is also suggested that while a number of
types of system have been studied, the lesser known types of estuary should be examined to
ascertain their geomorphological and hydrological functioning.
Significant gaps in the database also exist. A number of estuaries, particularly in the
Transkei, have not been sampled. Thgese and other missed systems should be sampled to
create a full baseline.
Investigations into other estuarine components (e.g. hydrology, sediment biogeochemistry,
vegetation, zooplankton, zoobenthos, birds, habitat assessment, catchment land-use) should
164
also be undertaken to ensure a more complete appraisal of the ecological integrity of the
nation’s estuarine resource.
Table 6.1. Summary of geomorphological classification, biogeography, fish community
status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries (n/a = not
analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
Aesthetics
Good
Water
quality
Poor
1
Gariep (Orange)
Cool-temperate
2
Holgat
open, medium/large
(F)
dry
Cool-temperate
n/s
n/s
Good
3
Buffels
small/isolated
Cool-temperate
n/a
Very Poor
Moderate
4
Swartlintjies
small/isolated
Cool-temperate
n/a
Poor
Good
5
Spoeg
small/isolated
Cool-temperate
n/a
Good
Good
6
Bitter
dry
Cool-temperate
n/s
n/s
Good
7
Groen
isolated
Cool-temperate
n/a
Very Poor
Good
8
Brak
dry
Cool-temperate
n/s
n/s
Good
9
Sout (Noord)
small/isolated
Cool-temperate
n/a
Fair
Poor
10
Olifants
Cool-temperate
Good
Fair
Good
11
Sandlaagte
open, medium/large
(F)
n/s
Cool-temperate
n/s
n/s
n/s
12
Jakkals
isolated
Cool-temperate
n/a
Poor
Moderate
13
Wadrif
isolated
Cool-temperate
n/a
Fair
Moderate
14
Verlore
Cool-temperate
Moderate
Excellent
Moderate
15
Papkuils
closed, medium
(B)
isolated
Cool-temperate
n/s
Fair
Good
16
Berg
Cool-temperate
Good
Fair
Poor
17
Paternosterbaai
open, medium/large
(F)
n/s
Cool-temperate
n/s
n/s
n/s
18
n/s
Cool-temperate
n/s
n/s
n/s
19
Saldanha/
Langebaan
Dwars (Noord)
dry
Cool-temperate
n/s
n/s
Good
20
Dwars (Suid)
small
Cool-temperate
n/s
Very Poor
Good
21
Modder
small/isolated
Cool-temperate
n/a
Good
Good
22
Jacobsbaai
dry
Cool-temperate
n/s
n/s
Moderate
23
Lêerbaai
dry
Cool-temperate
n/s
n/s
Good
165
Moderate
24
Bok
small
Cool-temperate
n/a
Poor
Good
25
Silwerstroom
small
Cool-temperate
n/a
Fair
Good
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
Aesthetics
n/a
Water
quality
Poor
26
Sout (Suid)
small/isolated
Cool-temperate
27
Diep
28
Soutrivier
closed, medium
(B)
canalised
Cool-temperate
Good
Poor
Poor
Cool-temperate
n/a
Very Poor
Poor
29
Houtbaai
closed, small
(A)
n/s
Cool-temperate
Moderate
Fair
Moderate
30
Goeiehoop
Cool-temperate
n/s
n/s
n/s
31
Wildevoël
closed, medium
(B)
small
Cool-temperate
Moderate
Poor
Good
32
Bokramspruit
Cool-temperate
n/a
Fair
Moderate
33
Schuster
Cool-temperate
Moderate
Good
Good
Cool-temperate
Poor
Poor
Good
Olifantsbos
closed, small
(A)
closed, medium
(B)
n/s
34
Krom
35
Cool-temperate
n/s
n/s
n/s
36
Booiskraal
small
Cool-temperate
n/a
Poor
Good
37
Buffels (Wes)
small
Cool-temperate
n/a
Poor
Good
38
Elsies
small
Cool-temperate
n/a
Fair
Poor
39
Silwermyn
Cool-temperate
Moderate
Poor
Moderate
40
Sand
Cool-temperate
Moderate
Poor
Poor
41
Seekoe
closed, small
(A)
closed, medium
(B)
canalised
Cool-temperate
n/a
Very Poor
Poor
42
Eerste
Cool-temperate
Good
Very Poor
Moderate
43
Lourens
Cool-temperate
Good
Fair
Poor
44
Sir Lowry’s Pass
Cool-temperate
Moderate
Fair
Moderate
45
Steenbras
Cool-temperate
Moderate
Fair
Good
46
Rooiels
Cool-temperate
Good
Good
Moderate
47
Buffels (Oos)
open, medium/large
(F)
open, small
(E)
open, small
(E)
open, non-barred
(D)
open, small
(E)
open, small
(E)
Cool-temperate
Good
Fair
Good
166
Moderate
48
Palmiet
49
Kleinmond
50
Bot
open, medium/large
(F)
closed, medium
(B)
closed, large
(C)
Cool-temperate
Good
Good
Good
Cool-temperate
Poor
Fair
Moderate
Cool-temperate
Good
Good
Moderate
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
51
Onrus
Cool-temperate
52
Mossel
open, small
(E)
small
53
Klein
54
Uilkraals
55
Ratel
56
Heuningnes
57
Klipdrifsfontein
58
Papkuils
closed, large
(C)
open, medium/large
(F)
open, small
(E)
open, medium/large
(F)
closed, small
(A)
n/s
59
Breë
60
Duiwenhoks
61
62
Goukou
(Kafferkuils)
Gourits
63
Blinde
64
Gericke
65
Hartenbos
66
Klein Brak
67
Groot Brak
68
Rooi
69
Maalgate
70
Gwaing
71
Skaapkop
open, medium/large
(F)
open, medium/large
(F)
open, medium/large
(F)
open, medium/large
(F)
closed, medium
(B)
n/s
closed, medium
(B)
open, medium/large
(F)
open, medium/large
(F)
small
open, non-barred
(D)
open, non-barred
(D)
n/s
Aesthetics
Good
Water
quality
Fair
Cool-temperate
n/s
Good
Good
Cool-temperate
Good
Good
Good
Cool-temperate
Good
Fair
Moderate
Cool-temperate
Good
Fair
Good
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warm-
Moderate
Fair
Good
Poor
Good
Good
n/s
n/s
n/s
Moderate
Good
Good
Poor
Good
Good
Moderate
Good
Moderate
Moderate
Good
Moderate
Moderate
Good
Good
n/s
n/s
n/s
Moderate
Poor
Poor
Moderate
Good
Moderate
Moderate
Good
Poor
n/s
n/s
Moderate
Good
Good
Good
Moderate
Poor
Good
n/s
n/s
n/s
167
Moderate
72
Meul
small
73
Kaaimans
74
Touw
75
Swartvlei
open, non-barred
(D)
closed, medium
(B)
open, medium/large
(F)
temperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
n/a
Very Poor
Moderate
Moderate
Excellent
Moderate
Good
Good
Moderate
Moderate
Good
Moderate
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
76
Goukamma
77
Knysna
78
Noetsie
79
Grooteiland
open, medium/large
(F)
open, medium/large
(F)
closed, small
(A)
small
80
Kranshoek
small
81
Crooks
small
82
Piesang
83
Keurbooms
84
Matjies
85
Brak
open, small
(E)
open, medium/large
(F)
closed, small
(A)
small
86
Sout
87
Groot (Wes)
88
Helpmakaars
open, non-barred
(D)
closed, medium
(B)
n/s
89
Klip
n/s
90
Bloukrans
91
Witels
open, non-barred
(D)
n/s
92
Lottering
93
Elandsbos
94
Geelhoutbos
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemp erate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
open, non-barred
(D)
open, non-barred
(D)
n/s
168
Aesthetics
Good
Water
quality
Good
Good
Good
Moderate
Good
Good
Good
n/s
Good
Good
n/s
Good
Good
n/s
Fair
Good
Moderate
Fair
Moderate
Good
Good
Moderate
Poor
Good
Good
n/s
Fair
Good
Moderate
Good
Good
Poor
Good
Good
n/s
n/s
n/s
n/s
n/s
n/s
Moderate
Good
Good
n/s
n/s
n/s
Poor
Good
Good
Moderate
Excellent
Good
n/s
n/s
n/s
Good
95
Kleinbos
n/s
96
Storms
97
Bruglaagte
open, non-barred
(D)
n/s
98
Langbos
n/s
99
Sanddrif
n/s
100
Elands
open, non-barred
(D)
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
n/s
n/s
n/s
Poor
Good
Good
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
Good
Good
Good
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
101
Groot (Oos)
102
Eerste
open, non-barred
(D)
small
103
Klipdrif (Wes)
small
104
Boskloof
small
105
Kaapsedrif
small
106
Tsitsikamma
107
Klipdrif (Oos)
108
Slang
109
Kromme
110
Seekoei
111
Kabeljous
112
Gamtoos
113
Van Stadens
114
Maitland
115
Bakens
closed, medium
(B)
closed, small
(A)
closed, small
(A)
open, medium/large
(F)
closed, medium
(B)
closed, medium
(B)
open, medium/large
(F)
closed, medium
(B)
closed, small
(A)
canalised
116
Papkuils
canalised
117
Swartkops
118
Ngcura (Koega)
open, medium/large
(F)
salt-works
119
Sundays
open, medium/large
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warm-
169
Aesthetics
Good
Water
quality
Good
n/s
Poor
Good
n/s
Very Poor
Good
n/a
Fair
Good
n/a
Poor
Good
Moderate
Good
Good
Poor
Fair
Good
Poor
Fair
Good
Good
Good
Moderate
Good
Good
Moderate
Moderate
Fair
Moderate
Good
Fair
Moderate
Good
Good
Moderate
Good
Fair
Moderate
n/a
Fair
Poor
n/a
Very Poor
Poor
Good
Good
Moderate
n/a
Good
Poor
Good
Good
Moderate
Good
120
Boknes
121
Bushmans
122
Kariega
123
Kasuka
124
Kowie
125
Rufane
(F)
closed, medium
(B)
open, medium/large
(F)
open, medium/large
(F)
closed, medium
(B)
open, medium/large
(F)
open, small
(E)
temperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Moderate
Good
Good
Good
Good
Moderate
Good
Good
Moderate
Good
Good
Good
Good
Good
Poor
Moderate
Fair
Good
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
126
Riet
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
n/s
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
127 Wes-Kleinemond
128 Oos-Kleinemond
129
Palmiet
130
Great Fish
131
Old Woman’s
132
Thatshana
133
Mpekweni
134
Mtati
135
Mgwalana
136
Bira
137
Gqutywa
138
Ngculura
139
dry
140
Fresh Water
Poort
Blue Krans
141
Mtana
142
Keiskamma
143
Shwele-Shwele
closed, medium
(B)
open, medium/large
(F)
dry
open, medium/large
(F)
closed, medium
(B)
closed, small
(A)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
open, small (E)
dry
170
Aesthetics
Good
Water
quality
Fair
Good
Good
Moderate
Good
Good
Moderate
n/s
n/s
n/s
Moderate
Good
Moderate
Good
Good
Moderate
Good
Fair
Good
Good
Good
Moderate
Good
Fair
Good
Good
Good
Good
Good
Fair
Good
Good
Good
Good
Moderate
Good
Good
n/s
n/s
Good
n/s
n/s
Good
Good
Good
Good
Good
Good
Good
n/s
n/s
Good
Good
144
Ngqinisa
145
Kiwane
146
Tyolomnqa
147 Shelbertsstroom
148
Lilyvale
149
Ross' Creek
150
Ncera
closed, medium
(B)
closed, medium
(B)
open, medium/large
(F)
open, small
(E)
closed, small
(A)
closed, medium (B)
closed, medium
(B)
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Good
Good
Good
Moderate
Good
Good
Good
Good
Good
Moderate
Good
Moderate
Good
Fair
Good
Good
Fair
Good
Good
Good
Good
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
151
Mlele
152
Mcantsi
153
Gxulu
154
Goda
155
Hlozi
156
Hickmans
157
Mvubukazi
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, small
(A)
closed, medium
(B)
small
158
Ngqenga
small
159
Buffalo
160
Blind
161
Hlaze
162
Nahoon
163
Qinira
164
Gqunube
165
Kwelera
166
Bulura
167
Cunge
168
Cintsa
open, medium/large
(F)
closed, small
(A)
closed, small
(A)
open, medium/large
(F)
closed, medium
(B)
open, medium/large
(F)
open, medium/large
(F)
open, small
(E)
closed, small
(A)
closed, medium
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warm-
171
Aesthetics
Good
Water
quality
Good
Good
Fair
Good
Good
Good
Moderate
Good
Good
Good
Good
Good
Good
Moderate
Fair
Moderate
n/a
(no fish)
n/a
(no fish)
Moderate
Fair
Good
Poor
Good
Poor
Poor
Good
Very Poor
Moderate
Good
Poor
Moderate
Good
Good
Moderate
Good
Good
Moderate
Good
Good
Moderate
Good
Good
Good
Good
Good
Good
Good
Good
Good
Good
Excellent
Good
Moderate
169
Cefane
170
Kwenxura
171
Nyara
172
Imtwendwe
173
Haga-Haga
174
Mtendwe
175
Quko
(B)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, small
(A)
closed, medium
(B)
closed, small
(A)
open, medium/large
(F)
temperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Good
Excellent
Good
Good
Excellent
Good
Moderate
Excellent
Good
Good
Fair
Good
Good
Good
Good
Moderate
Good
Good
Good
Good
Good
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
176
Morgan
177
Cwili
178
Great-Kei
179
Gxara
180
Ngogwane
181
Qolora
182
Ncizele
183
Timba
closed, medium
(B)
open, small
(E)
open, medium/large
(F)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, small
(A)
n/s
184
Mbokotwana
n/s
185
Kobonqaba
186
Ngqusi/Inxaxo
187
Bowkers Bay
open, medium/large
(F)
open, medium/large
(F)
n/s
188
Cebe
189
Gqunqe
190
Zalu
191
Ngqwara
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
closed, medium
(B)
n/s
closed, medium
(B)
closed, medium
(B)
172
Aesthetics
Good
Water
quality
Good
Good
Fair
Moderate
Poor
Fair
Good
Good
Fair
Good
Moderate
Poor
Moderate
Good
Poor
Good
Good
Very Poor
Good
n/s
n/s
n/s
n/s
n/s
n/s
Good
Poor
Good
Good
Poor
Good
n/s
n/s
n/s
Good
Fair
Good
n/s
n/s
n/s
Moderate
Fair
Good
Good
Fair
Good
Moderate
192
n/s
193
Sihlontlweni
(Gcina)
Nebelele
194
Qora
195
Mbozi
open, medium/large
(F)
n/s
196
Mbokotwana
n/s
197
Jujura
198
Ngadla
199
Shixini
200
Beechamwood
open, small
(E)
open, small
(E)
open, medium/large
(F)
n/s
n/s
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
n/s
n/s
n/s
n/s
n/s
n/s
Moderate
Poor
Good
n/s
n/s
n/s
n/s
n/s
n/s
Good
Poor
Good
Good
Poor
Good
Moderate
Poor
Good
n/s
n/s
n/s
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
201
Unnamed
n/s
202
Kwa-Goqo
n/s
203
Ku-Nocekedwa
n/s
204
Ngabarana
n/s
205
Nqabara
n/s
206
Gume
n/s
207
Ngomane
n/s
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemp erate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warm-
208 Ngoma (Kobole)
n/s
209
Unnamed
n/s
210
Mendu
n/s
211
Mendwana
n/s
212
Unnamed
n/s
213
Mbashe
214
Ku-Mpenzu
215
Ku-Bhula
open, medium/large
(F)
open, small
(E)
open, small
173
Aesthetics
n/s
Water
quality
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
Moderate
Fair
Good
Good
Fair
Good
Good
Fair
Good
n/s
216
(Mbhanyana)
Dakana
(E)
n/s
217
Kwa-Suku
218
Ntlonyane
219
Nyumbazana
open, small
(E)
open, small
(E)
n/s
220
Nkanya
221
Sundwana
222
Xora
223
Bulungula
224
KuAmanzimnyana
Nqakanqa
225
open, small
(E)
closed, small
(A)
open, medium/large
(F)
n/s
n/s
n/s
temperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
n/s
n/s
n/s
Moderate
Poor
Good
Good
Fair
Good
n/s
n/s
n/s
Good
Good
Good
Good
Fair
Good
Good
Fair
Good
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
226
Unnamed
n/s
227
Mncwasa
n/s
228
Lubanzi
n/s
229
Mhlalane
n/s
230
Mpako
n/s
231
Mtonjane
n/s
232
Ku-Bomvu
n/s
233
Nenga
234
Mapuzi
235
Mtata
236
Thsani
237
Mdumbi
238
Lwandilana
open, small
(E)
open, small
(E)
open, medium/large
(F)
closed, small
(A)
open, medium/large
(F)
n/s
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Warmtemperate
Subtropical
239
Lwandile
n/s
Subtropical
174
Aesthetics
n/s
Water
quality
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
n/s
Good
Fair
Moderate
Moderate
Fair
Good
Good
Poor
Moderate
Moderate
Poor
Good
Good
Fair
Moderate
n/s
n/s
n/s
n/s
n/s
n/s
n/s
240
Mtakatye
n/s
Subtropical
n/s
n/s
n/s
241
Hluleka
n/s
Subtropical
n/s
n/s
n/s
242
Mnenu
n/s
Subtropical
n/s
n/s
n/s
243
Mtonga
n/s
Subtropical
n/s
n/s
n/s
244
Mpande
Subtropical
Good
Fair
Good
245
Sinangwana
Subtropical
Moderate
Fair
Good
246
Ndluzula
open, small
(E)
open, medium/large
(F)
n/s
Subtropical
n/s
n/s
n/s
247
Mngazana
Subtropical
Good
Fair
Moderate
248
Mngazi
Subtropical
Good
Good
Moderate
249
Tyityane
open, medium/large
(F)
open, medium/large
(F)
n/s
Subtropical
n/s
n/s
n/s
250
Ntloloba
n/s
Subtropical
n/s
n/s
n/s
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
Aesthetics
Good
Water
quality
Good
251
Gxwaleni
Subtropical
252
Bulolo
253
Mtumbane
254
Mzimvubu
255
Mnenga
closed, small
(A)
open, small
(E)
open, small
(E)
open, medium/large
(F)
n/s
Subtropical
Good
Fair
Moderate
Subtropical
Good
Poor
Moderate
Subtropical
Moderate
Fair
Moderate
Subtropical
n/s
n/s
n/s
256
Ntlupeni
Subtropical
Good
Fair
Good
Manzana
open, small
(E)
n/s
257
Subtropical
n/s
n/s
n/s
258
Nkodusweni
n/s
Subtropical
n/s
n/s
n/s
259
Gugu
n/s
Subtropical
n/s
n/s
n/s
260
Mntafufu
Subtropical
Good
Fair
Good
261
Ingo
open, medium/large
(F)
n/s
Subtropical
n/s
n/s
n/s
262
Ntyivini
n/s
Subtropical
n/s
n/s
n/s
263
Dakane
n/s
Subtropical
n/s
n/s
n/s
264
Mzintlava
n/s
Subtropical
n/s
n/s
n/s
175
Good
265
Mguga
n/s
Subtropical
n/s
n/s
n/s
266
Mzimpunzi
n/s
Subtropical
n/s
n/s
n/s
267 Kwa-Nyambalala
n/s
Subtropical
n/s
n/s
n/s
268
Mbotyi
n/s
Subtropical
n/s
n/s
n/s
269
Mkozi
n/s
Subtropical
n/s
n/s
n/s
270
Myekane
n/s
Subtropical
n/s
n/s
n/s
271
Sikatsha
n/s
Subtropical
n/s
n/s
n/s
272
Cutweni
n/s
Subtropical
n/s
n/s
n/s
273
Mfihlelo
n/s
Subtropical
n/s
n/s
n/s
274
Mlambomkulu
n/s
Subtropical
n/s
n/s
n/s
275
Lupatana
n/s
Subtropical
n/s
n/s
n/s
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
Aesthetics
n/s
Water
quality
n/s
276
Mkweni
n/s
Subtropical
277
Maviti
n/s
Subtropical
n/s
n/s
n/s
278
Tezana
n/s
Subtropical
n/s
n/s
n/s
279
Magogo
n/s
Subtropical
n/s
n/s
n/s
280
Kilroe Beach
n/s
Subtropical
n/s
n/s
n/s
281
Mbaxeni
n/s
Subtropical
n/s
n/s
n/s
282
Msikaba
Subtropical
Moderate
Good
Good
283
Butsha
open, medium/large
(F)
open, small
(E)
n/s
Subtropical
Moderate
Fair
Good
Subtropical
n/s
n/s
n/s
284 Kwa-Nondindwa
n/s
285
Daza
n/s
Subtropical
n/s
n/s
n/s
286
Mgwegwe
Subtropical
Moderate
Fair
Good
287
Mkambati
open, small
(E)
n/s
Subtropical
n/s
n/s
n/s
176
288
Mgwetyana
Subtropical
Moderate
Fair
Good
Subtropical
Good
Fair
Good
Sikombe
open, small
(E)
open, medium/large
(F)
n/s
289
Mtentu
290
Subtropical
n/s
n/s
n/s
291
Kwanyana
n/s
Subtropical
n/s
n/s
n/s
292
Mtolane
n/s
Subtropical
n/s
n/s
n/s
293
Mnyameni
n/s
Subtropical
n/s
n/s
n/s
294
Unnamed
n/s
Subtropical
n/s
n/s
n/s
295
Mpahlanyana
n/s
Subtropical
n/s
n/s
n/s
296
Mpahlane
n/s
Subtropical
n/s
n/s
n/s
297
Mzamba
Subtropical
Good
Poor
Good
298
Mtentwana
Subtropical
Moderate
Poor
Moderate
299
Mtamvuna
Subtropical
Good
Fair
Moderate
300
Zolwane
open, medium/large
(F)
closed, medium
(B)
open, medium/large
(F)
n/s
Subtropical
n/s
Good
n/s
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
Aesthetics
Good
Water
quality
Good
301
Sandlundlu
Subtropical
302
Ku-Boboyi
open, small
(E)
n/s
Subtropical
n/s
Fair
n/s
303
Tongazi
304
Kandandlovu
305
Mpenjati
306
Umhlangankulu
307
Kaba
308
Mbizana
309
Mvutshini
310
Bilanhlolo
311
Uvuzana
open, small
(E)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, medium
(B)
closed, small
(A)
closed, medium
(B)
n/a
Subtropical
Good
Fair
Good
Subtropical
Moderate
Fair
Good
Subtropical
Good
Good
Moderate
Subtropical
Good
Poor
Good
Subtropical
Poor
Fair
Good
Subtropical
Good
Good
Good
Subtropical
Good
Poor
Good
Subtropical
Moderate
Fair
Moderate
Subtropical
n/a
Poor
Moderate
177
Moderate
closed, small
(A)
n/s
Subtropical
(no fish)
Good
Fair
Moderate
Subtropical
n/s
Very Poor
n/s
Subtropical
Good
Fair
Moderate
Subtropical
Moderate
Good
Moderate
Boboyi
closed, medium
(B)
open, small
E)
n/s
Subtropical
n/s
Poor
n/s
317
Mbango
n/s
Subtropical
n/s
Very Poor
n/s
318
Mzimkulu
Subtropical
Good
Good
Moderate
319
Mtentweni
Subtropical
Moderate
Good
Moderate
320
Mhlangamkulu
Subtropical
Moderate
Fair
Good
321
Damba
Subtropical
Moderate
Good
Moderate
322
Koshwana
open, medium/large
(F)
closed, medium
(B)
closed, medium
(B)
closed, small
(A)
n/s
Subtropical
n/s
Good
n/s
323
Intshambili
Subtropical
Moderate
Poor
Good
324
Mzumbe
closed, medium
(B)
n/s
Subtropical
n/s
Good
n/s
325
Mhlabatshane
open, small
(E)
Subtropical
Good
Fair
Moderate
312
Kongweni
313
Vungu
314
Mhlangeni
315
Zotsha
316
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
Aesthetics
n/s
Water
quality
Fair
326
Mhlungwa
n/s
Subtropical
327
Mfazazana
n/s
Subtropical
n/s
n/s
n/s
328
Kwa-makosi
n/s
Subtropical
n/s
n/s
n/s
329
Mnamfu
n/s
Subtropical
n/s
n/s
n/s
330
Mtwalume
n/s
Subtropical
n/s
Fair
n/s
331
Mvuzi
n/s
Subtropical
n/s
Fair
n/s
332
Fafa
Subtropical
Moderate
Good
Good
333
Mdesingane
closed, medium
(B)
n/s
Subtropical
n/s
Very Poor
n/s
334
Sezela
Subtropical
Moderate
Poor
Moderate
335
Mkumbane
closed, medium
(B)
closed, small
(A)
Subtropical
Good
Poor
Moderate
178
n/s
336
Mzinto
n/s
Subtropical
n/s
Good
n/s
337
Mzimayi
Subtropical
Good
Fair
Moderate
338
Mpambanyoni
Subtropical
Good
Good
Moderate
339
Mahlongwa
Subtropical
Good
Fair
Moderate
340
Mahlongwana
closed, small
(A)
closed, medium
(B)
closed, medium
(B)
n/s
Subtropical
n/s
Poor
n/s
341
Mkomazi
Subtropical
Good
Good
Moderate
342
Ngane
open, medium/large
(F)
n/s
Subtropical
n/s
n/s
n/s
343
uMgababa
n/s
Subtropical
n/s
n/s
n/s
344
Msimbazi
n/s
Subtropical
n/s
n/s
n/s
345
Lovu
open, medium/large
(F)
closed, medium
(B)
closed, medium
(B)
open, small
(E)
closed, medium
(B)
n/s
Subtropical
Moderate
Poor
Moderate
Subtropical
Good
Very Poor
Moderate
Subtropical
Good
Very Poor
Poor
Subtropical
Good
Very Poor
Poor
Subtropical
Good
Very Poor
Poor
Subtropical
n/s
n/s
n/s
346 Little Manzimtoti
347
Manzimtoti
348
Mbokodweni
349
Sipingo
350
Durban Bay
Table 6.1. cont. Summary of geomorphological classification, biogeography, fish
community status (ichthyofauna), water quality and aesthetics of South Africa’s estuaries
(n/a = not analysed; n/s = not sampled).
No.
System
Classification
Biogeography
Ichthyofauna
Aesthetics
Good
Water
quality
Poor
351
Mgeni
Subtropical
352
Mhlanga
353
Mdloti
354
Tongati
open, medium/large
(F)
closed, medium
(B)
closed, medium
(B)
n/s
Subtropical
Good
Very Poor
Good
Subtropical
Moderate
Fair
Moderate
Subtropical
n/s
Poor
n/s
355
Mhlali
open, medium/large
(F)
n/s
Subtropical
Good
Good
Good
356
Seteni
Subtropical
n/s
Fair
n/s
357
Mvoti
open, medium/large
(F)
closed, medium
(B)
n/s
Subtropical
Poor
Poor
Moderate
358
Mdlotane
Subtropical
Good
Good
Good
359
Nonoti
Subtropical
n/s
Fair
n/s
179
Moderate
360
Zinkwasi
361 Thukela (Tugela)
362 Matigulu/Nyoni
closed, medium
(B)
open, medium/large
(F)
open, medium/large
(F)
closed, medium
(B)
open, medium/large
(F)
n/s
Subtropical
Moderate
Fair
Moderate
Subtropical
Moderate
Good
Moderate
Subtropical
Good
n/s
Good
Subtropical
Moderate
n/s
Good
Subtropical
Good
n/s
Good
Subtropical
n/s
n/s
n/s
n/s
Subtropical
n/s
n/s
n/s
363
Siyai
364
Mlalazi
365
366
Mhlathuze
(Mhlatuze)
Richards Bay
367
Nhlabane
n/s
Subtropical
n/s
n/s
n/s
368
Moderate
n/s
Good
Subtropical
Good
n/s
Good
370
Mgobezeleni
Subtropical
Poor
n/s
Good
371
Kosi Bay
open, medium/large
(F)
open, medium/large
(F)
open, small
(E)
open, medium/large
(F)
Subtropical
369
Mfolozi/
Msunduzi
St Lucia
Subtropical
Poor
n/s
Good
180
7.
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184
8.
APPENDIX 1
In this section, the results of the study are presented graphically as a series of stripmaps. Each map comprises a section of the South African coastline with the relative
position of the estuaries indicated.
Adjacent to each estuary is a description of its
geomorphological class and the biogeographic region into which it falls. The state of
the fish community, water quality and aesthetics of each estuary is also presented as a
series of icons.
The geomorphological classification is as follows:
Normally closed small estuaries (surface area < 2 ha) (Type A)
Normally closed medium estuaries (surface area 2-150 ha) (Type B)
Normally closed large estuaries (surface area > 150 ha) (Type C)
Normally open non-barred estuaries (Type D)
Normally open, small barred estuaries (MAR <15x106 m3 ) (Type E)
Normally open, medium-large barred estuaries (MAR >15x106 m3 )
(Type F)
A number of estuaries were not classified either because they were dry, they were
very small or they were isolated. Estuaries that were modified (e.g. salt-works,
canalised) were also not classified. Systems that were not sampled are denoted by n/s.
The biogeographical provinces (based of fish community composition) are:
Cool-Temperate region (Cool-Temp), Gariep (Orange River) - Cape Agulhas
Warm-Temperate region (Warm-Temp), Cape Agulhas – Mdumbi Estuary
Subtropical region (Subtrop), Mdumbi Estuary – Kosi Bay
The state of the fish communities are based on species richness (number of species)
and species composition (presence/absence and % abundance). The ‘health’ of the
fish communities of each estuary is depicted by an icon containing one, two, or three
fish representing poor, moderate, or good communities respectively.
The water quality is based on the suitability for Aquatic Life (dissolved oxygen,
unionized ammonia, oxygen absorbed), Human Contact (faecal coliforms), and
Trophic Status (nitrate nitrogen, ortho-phosphate). The water quality of each estuary
is depicted by an icon containing one, two, or three water drops representing poor,
fair, or good overall water quality respectively.
The aesthetic assessment is based on a visual appraisal of the state of development in
and around an estuary.
Factors such as floodplain landuse, shoreline status,
development in the floodplain/estuary surrounds, bridges, dams and weirs, mouth
stabilisation, litter and rubble, nature and extent of human use, alagal blooms and
aquatic nuisance plants, turbidity, odour, air pollution, noise and invasive and exotic
vegetation were all taken into account.
The aesthetics of each estuary is depicted by
an icon containing one, two, or three leaves representing a poor, moderate, or good
aesthetic state respectively.
185
Nor the rn P rov in ce
Gariep
(Orange)
N o rth -Wes t
Alexander Bay
Mpu ma la ng a
Gau teng
Fre e St ate
K wa Zu lu /N ata l
Northe rn Ca p e
1
COOL -TEMP
OPEN, MEDIUM /
L ARGE
Eas te rn Cape
We ste rn C ap e
318
2
CO
SUBT
OL-TROP
EMP
OPEN,DRY
MEDI UM/
L ARGE
N
N/ S
N/ S
Holgat
At lantic Ocean
Indian Oce an
Port Nolloth
3
COOL-TEMP
SMALL / ISOLATED
Koingnaas
318
4
CO
SUBT
OL-TROP
EMP
OPEN,/ ISOLAT
MEDI UM/
SMALL
ED
L ARGE
N /A
318
5
SUBT ROP
COOL-T
EMP
OPEN,
MEDI
UM/
SMALL / I SOLATED
L ARGE
N/A
318
6
CO
SUBT
OL-TROP
EMP
OPEN,DRY
MEDI UM/
L ARGE
N/S
318
7
SUBT ROP
COOL-T
EMP
OPEN,
I SOLATED
MEDI UM/
L ARGE
N /A
318
8
SUBT ROP
COOL-T
EMP
OPEN,DRY
MEDI UM/
L ARGE
N /S
9
COOL -TEMP
SMALL / ISOLAT ED
Kleinsee
Buffels
N/ A
Swartlintjies
Hondeklipbaai
Spoeg
Bitter
Garies
N /S
Groen
N/ S
Brak
Sout (Noord)
N /A
Olifants
186
No rth er n Pr ovi nce
Nor th -Wes t
M p um al an g a
Ga u ten g
Fre e State
Kw aZul u/ Na tal
N orther n Ca pe
31 8
10
BTREMP
OP
C SU
OOL-T
OPEN ,MEDI
MEDIUM/
OPEN,
UM /
LAR
LARGE
GE
Olifants
E aste rn C ap e
We st ern Ca pe
N
At lan tic Ocean
11
C OOL-T EMP
N/ S
N/ S
12
C OOL-TEMP
ISOLATED
N/A
13
C OOL-T EMP
ISOLATED
N /A
N /S
Sandlaagte
N /S
Jakkals
Wadrif
14
COOL-TEMP
C LOSED, MED IU M
31 8
15
C OOL-T
SU BTREMP
OP
OPEN
ISOLAT
, MEDIUM/
ED
LARGE
Lambert's Bay
Verlore
N/S
Papkuils
16
COOL-TEMP
OPEN , MEDI UM /
LARGE
Berg
Velddrif
Paternosterbaai
17
C OOL-T EMP
N/ S
N/ S
N /S
N /S
Vredenburg
18
C OOL-T EMP
N/ S
N/ S
N /S
Saldanha
N /S
Saldanha /
Langeb aan
19
COOL -TEMP
DR Y
N /S
20
COOL -TEMP
SMALL
N/S
31 8
21
BTREMP
OP
C SU
OOL-T
OPEN , MEDIUM/
SMALLLARGE
/ ISOLAT ED
N /A
N/S
Langebaan
Dwars
(N oord )
Dwars
(Sui d)
Modder
Jacobsbaai
187
Indian Ocean
N orth e rn Pr ovin c e
22
COOL-TEMP
DRY
N/S
N/S
Jacobsbaai
N orth - We st
Mp um al an g a
Ga u te n g
Lêerbaai
23
C OOL-TEMP
DRY
Fr ee Sta te
Kw a Zul u/ N at al
N o rt hern C a p e
N/S
N/S
Bok
Silverstroom
E a st er n C a pe
We st e rn Ca pe
N
24
C OOL-TEMP
SMALL
N/A
318
25
COOL-TEMP
SUBTROP
OPEN,
MEDIUM/
SMALL
LARGE
N/A
Atla nt ic Ocean
Indian Ocean
Sout (Suid)
Melkbosstrand
26
COOL-TEMP
SMALL / ISOLATED
N/A
27
COOL-TEMP
CLOSED, MEDIUM
28
COOL-TEMP
CANALISED
Diep
Soutrivier
N/A
Cape Town
29
COOL-TEMP
CLOSED , SMALL
30
COOL-TEMP
N/S
N/S
N/S
N/S
Hout Baai
Goeiehoop
318
31
SUBTROP
COOL-TEMP
CLOSED,
OPEN, MEDIUM/
MEDIUM
LARGE
32
COOL-TEMP
SMALL
Muizenberg
Wildevoël
Bokramspruit
N /A
Simonstown
Schuster
33
COOLM-TEMP
CLOSED, SMALL
Krom
Olifantsbos
34
COOL-TEMP
CLOSED, MEDIUM
188
N o rthe rn Pro vi nc e
Mpu ma la ng a
Ga u te ng
No rt h -We st
Fr ee Sta t e
Kw aZu lu /N a ta l
N o rth e rn C a pe
Ea ste rn Ca pe
We ster n C ap e
N
A tl antic Ocean
Ind ian Ocean
Muizenberg
41
C OOL-T EMP
C ANALISED
N/ A
40
C OOL-T EMP
CL OSED , M EDI UM
39
COO L-T EMP
CL OSED , SMALL
38
COOL-T EMP
SMALL
Olifantsbos
3178
3
SUBT
ROP
COOL
-TEMP
OPEN,
SMALL
MED IU M /
LAR GE
N/A
3168
3
COOL
SUBT
-TEMP
ROP
OPEN,
MED IU M /
SMALL
LAR GE
N /A
35
COO L-T EMP
N/ S
189
N/ A
N /S
N/S
N/S
No rthe rn P rov in ce
No rth - Wes t
Mp u mal an g a
Gau te ng
F re e S ta te
K wa Zul u/ Natal
No rth e rn C ap e
Ea ster n C ap e
We st er n C a pe
N
A tlanti c Ocea n
Eerste
42
C OOL-T EM P
OPEN, M EDIUM /
LAR GE
43
C OOL-T EM P
OPEN, SMAL L
44
COO L-T EMP
OPEN , SMALL
45
C OOL-T EM P
OPEN,
NON-BAR RED
46
COOL-T EM P
OPEN , SMALL
37
4
18
COSUBT
OL-TROP
EMP
OOPEN,
PEN, MEDIUM
SMAL L /
L ARGE
190
Indi an Oce an
Pringle Bay
N o rth ern Prov in ce
318
48
CSUBT
OOL-T
ROP
EMP
OPEN, MED
MED IU M //
LAR
LARGE
GE
N o rth -We s t
Mp u mala n ga
Gaut en g
Fr e e St ate
49
COOL -TEMP
C LOSED, MED IU M
K wa Zulu /N a ta l
No rth e rn Cap e
Eas te rn C ape
Wester n C ap e
50
COOL-TEM P
C LOSED, L ARGE
N
A tlantic Ocean
51
COOL-TEM P
OPEN , SMALL
Hermanus
52
COOL-T EMP
SMALL
N/S
318
53
SUBT-TEMP
ROP
COOL
OPEN,
MED
IU M /
C LOSED,
LARGE
LAR GE
54
C OOL-T EMP
OPEN, MED IU M /
LAR GE
318
55
COO
SUBT
L-TROP
EM P
OPEN,
OPEN ,MED
SMALL
IU M /
LAR GE
191
Indian Ocean
N orth e rn Pr ovi nc e
Mp um a lan ga
Gau te ng
N orth -West
Free Sta te
63
WARM-T EMP
CL OSED , MEDIUM
Kw a Zu lu/ Nata l
N o rth ern C ap e
62
WAR M-TEMP
OPEN , MEDIUM /
L ARGE
E astern Ca pe
We st ern Cap e
N
Atla nti c Ocean
Indian Ocean
61
WAR M-TEMP
OPEN , MEDIUM /
L ARGE
60
WARM-T EMP
OPEN, MED IU M /
LAR GE
Cape Infanta
59
WARM-T EMP
OPEN, MED IU M /
LAR GE
58
WARM-T EMP
N /S
57
WAR M-TEMP
CLOSED, SMALL
56
WAR M-TEMP
OPEN , MEDIUM /
L ARGE
Bredasdorp
Cape Agulhas
192
N/S
N /S
N/S
No rthe rn P rov in ce
N o rth -We st
Mpu mala n ga
Gau teng
Fr ee Sta te
K wa Zulu /N a tal
No rth er n Ca p e
Ea ste rn C ap e
318
76
WARM-T
SUBT ROP
EMP
OPEN,
O
PEN , MEDI
MEDIUM
UM//
LLARGE
ARGE
Wester n C a pe
N
At lantic Ocean
Indian Ocean
75
WARM-T EMP
OPEN, MED IU M /
LARGE
74
WARM-T EMP
CLOSED, MEDI UM
73
WAR M-TEMP
OPEN,
N ON -BARRED
72
W ARM-TEMP
SMALL
N/A
71
WAR M-TEMP
N /S
N /S
N/S
N/S
N /S
N /S
N/S
N/S
70
WARM-T EMP
OPEN
NON-BAR RED
31
698
WAR
SUBT
M-TEMP
ROP
OPEN,
OPEN
MED IU M/
NON-BARR
LAR GE ED
68
WARM-T EMP
SMALL
67
WARM-T EMP
OPEN, MEDIUM /
LAR GE
66
WAR M-TEMP
OPEN, MEDI UM /
L ARGE
65
WARM-T EMP
CLOSED, MEDIUM
Mossel Bay
193
64
WAR M-TEMP
N/ S
N/S
N o rth e rn P ro v in ce
N or th -We s t
Mpu ma la ng a
Ga u teng
Fr e e St ate
K waZu lu /N a ta l
No rthe r n Ca p e
Eas te rn C ape
W es te rn C a pe
N
A tlantic Ocean
89
WARM-T EM P
N/ S
N/ S
N /S
N /S
88
WARM-T EM P
N /S
N/ S
N /S
N /S
Indian Ocea n
87
WAR M-TEMP
CLOSED, MEDIUM
86
WAR M-TEMP
OPEN,
NO N-BARR ED
85
WARM-T EM P
SMAL L
N /S
84
WARM-T EM P
C LO SED, SMAL L
83
WARM-T EM P
OPEN, MED IU M /
LAR GE
82
WARM-T EMP
OPEN, SMAL L
318
81
SUBT ROP
WARM-T
EMP
OPEN,SMALL
M EDI UM/
LARG E
N/ S
80
WARM-T EM P
SMAL L
N /S
79
WARM-T EM P
SMAL L
3 18
78
SUBT
ROP
WAR
M-TEMP
OPEN, M EDI UM/
CLOSED, SMALL
LARG E
77
WARM-T EMP
OPEN, MEDIUM /
LAR GE
194
N /S
No rt hern P rovi nc e
No rt h-We st
Mpu mala nga
Gau te ng
Fre e State
10
318
2
SU BTREMP
OP
WARM-T
OPEN
, MEDIUM/
SMAL
L
LARGE
N /S
Kwa Zulu /N atal
N or the rn Cap e
3 01
1
18
WARM-T
SUBTROP
EMP
OPEN,
OPEN,
MEDIUM/
NON-BAR
L ARGE
RED
Ea stern Ca pe
We ste rn C ap e
N
At lantic Ocean
In dian Ocean
3 00
1
18
WARM-T
SUBTROP
EMP
OPEN,
OPEN,
MEDIUM/
NON-BAR
L ARGE
RED
99
WARM-T EMP
N /S
N/S
N/ S
98
WARM-T EMP
N /S
N/ S
N/S
N/ S
97
WARM-T EMP
N /S
N/ S
N/S
N/ S
95
WARM-T EMP
N /S
N/ S
N/S
N/ S
94
WARM-T EMP
N /S
N/ S
N/S
N/ S
N/ S
N/S
N/ S
96
W ARM-T EMP
OPEN ,
NON-BARR ED
93
W ARM-T EMP
OPEN ,
NON-BARR ED
92
W ARM-T EMP
OPEN ,
NON-BARR ED
91
WARM-T EMP
N /S
90
W ARM-T EMP
OPEN ,
NON-BARR ED
195
N orthe rn Pro vin ce
N o rth-West
Mpu mal anga
Ga ute n g
Fre e State
Kw aZul u/N a tal
No rt hern Ca p e
Easte rn Ca p e
Wes te rn Ca pe
N
Atla nti c Ocean
India n Ocean
110
WARM-T EMP
CLOSED, MEDIUM
109
WARM-T EMP
CLOSED, MEDIUM
108
W ARM-T EMP
SMALL , CLOSED
107
W ARM-T EMP
SMALL , CLOSED
10 6
WARM-T EMP
CL OSED , MEDI UM
196
3 18
105
WAR
SUBT
M-TEMP
ROP
OPEN,
SMALL
MED IU M/
LAR GE
N/A
104
W ARM-T EMP
SMALL
N/A
103
3 18
SUBT
ROP
WAR
M-TEMP
OPEN,
MED IU M/
SMALL
LAR GE
N/S
N ort he rn Pro vin c e
N or th- We st
Mpu mal anga
Gau te ng
Fr ee Stat e
119
W ARM-T EM P
OPEN, MED IU M /
LARGE
Kw aZul u/Nata l
N o rt hern C ap e
118
W ARM-T EM P
SALT-WORKS
Easte rn C ap e
We s te rn Ca p e
N
Atla ntic Ocean
N/ A
Ind ia n Ocean
117
WARM-T EMP
O PEN, MED IU M /
LARGE
(Koega)
116
WARM-T EMP
C ANALISED
N/A
115
WARM-T EMP
C ANALISED
N/A
114
W ARM-T EM P
CL OSED , SMALL
113
WAR M-TEMP
C LOSED, MED IU M
112
W ARM-T EM P
OPEN, MED IU M /
LAR GE
111
W ARM-T EM P
CLOSED, MEDIUM
197
130
WAR M-TEMP
OPEN , MEDIUM /
LARGE
N or the rn Pro vi nce
Nor th -West
Mp um al an g a
Ga ute n g
Fr ee Sta te
129
WARM-T EMP
N/S
Kw a Zul u/ Nat al
N ort he rn C a pe
128
WAR M-TEMP
C LOSED, MED IU M
E aste rn C a pe
Weste rn Cap e
N
Atl an tic Ocean
127
WAR M-TEMP
C LOSED, MED IU M
Indian Ocean
318
12
6
SUBT-TROP
W ARM
EMP
OPEN,
MEDI
UM/
CL OSED , MEDIUM
LARGE
3 18
125
SUBT
ROPP
WAR
M -TEM
OPEN,
UM/
OPEN ,MEDI
SMALL
LARGE
124
WARM-T EMP
OPEN, MED IU M /
LARGE
318
123
SU BTR OP
WARM-T EMP
OPEN , MEDI
UM/
CLOSED,
MEDI
UM
LARGE
122
WAR M-TEMP
OPEN , MEDIUM /
LARGE
121
WAR M-TEMP
OPEN , MEDIUM /
LARGE
120
WARM-T EMP
CL OSED , MEDI UM
198
N/ S
N /S
N /S
Hamburg
No rth e rn P ro v in ce
N o r th- We st
Mpu ma la n ga
Gau teng
Fr ee Sta te
3141
18
WAR
SUBT
M-TEMP
ROP
COPEN,
LO SED,
MED
MED
IUIU
M/M
LAR GE
K waZu lu /N a ta l
No rth e rn Ca pe
Ea s te rn C ape
Wester n C ap e
N
A tlant ic Ocea n
3180
14
BTR
OP
WSU
ARM
-T EMP
OPEN ,DRY
MEDI UM /
LARGE
N/S
N/S
318
13 9
BTR
OP
WSU
ARM
-T EMP
OPEN DRY
, MEDI UM /
LARGE
N/S
N/S
Indian Ocea n
13 8
W ARM -T EMP
OPEN, SMAL L
3137
18
SUBT
ROP
WAR
M -TEMP
OPEN,
MED
IUIU
M /M
C LOSED, MED
LAR GE
3136
18
SUBT
ROP
WAR
M -TEMP
MED
IUIU
MM
/
COPEN,
LOSED,
MED
LAR GE
3135
18
WAR
SUBT
M -TEMP
ROP
COPEN,
LOSED,
MED
MED
IUIU
MM
/
LAR GE
3134
18
SUBT
ROP
WAR
M -TEMP
MED
IUIU
MM
/
COPEN,
LOSED,
MED
LAR GE
1 33
WARM -T EMP
CL OSED , MEDI UM
3182
13
BTR
WSU
ARM
-T OP
EMP
OPEN
, MEDI
UM L
/
C
LOSED,
SMAL
LARGE
131
W ARM -T EMP
CLOSED, MEDI UM
199
318
15 4
SU BTREMP
OP
WARM-T
OPEN , MEDIUM/
CLOSED,
MEDIUM
LARGE
N orth er n Pr ovi nce
N orth -We st
Mp u ma la n ga
Ga ute n g
Fr ee State
Kw a Zu lu /N a ta l
N o rth e rn Cap e
15 3
W ARM -T EMP
CL OSED , MEDIUM
Easte rn Cap e
We ster n Cap e
N
A tlantic Ocean
In dian Ocean
3 18
152
SUBT
ROP
WAR
M-TEMP
C LOSED,
O PEN, MED
MEDIUIUM/
M
LAR GE
151
WAR M-TEMP
C LOSED, MED IU M
Kidd's Beach
318
15 0
SU BTR OP
WARM-T EMP
OPEN
,
CLOSED,MEDIUM/
MEDIUM
LARGE
3 18
149
SUBT
ROP
WAR
M-TEMP
C LOSED,
O PEN, MED
MEDIUIUM/
M
LAR GE
148
3 18
WAR
SUBT
M-TEMP
ROP
O PEN, MED
IU M/
CLOSED,
SMALL
LAR GE
147
WAR M-TEMP
OPEN , SMALL
Kayser's Beach
3186
14
BTR
OP
WSU
ARM
-T EMP
OPEN,
OPEN , MED
MEDIUM/
IU M /
LARGE
1 45
WAR M-TEMP
CLOSED, SMALL
3184
14
BTR
OP
WSU
ARM
-T EMP
CLOSED,
OPEN , MEDIUM/
MEDIUM
LARGE
3183
14
BTR
OP
WSU
ARM
-T EMP
OPEN DRY
, MEDIUM/
LARGE
3182
14
BTR
OP
WSU
ARM
-T EMP
OPEN,
OPEN , MED
MEDIUM/
IU M /
LARGE
Hamburg
200
N/S
N/S
318
166
WARM-T
SUBT ROP
EMP
OPEN
OPEN,
, MEDI
SMAL
UM
L/
LARGE
No rt hern Pro vi nc e
N ort h -West
Mp uma la nga
Gau te n g
Fre e State
318
165
WARM-T
SUBT ROP
EMP
OPEN,,MED
OPEN
MEDIIUUM
M //
LARGE
LAR GE
Kw aZu lu /N atal
N or th ern Ca p e
Ea ste rn Cap e
We ste r n C ape
N
A tlantic Ocean
In di an Ocean
164
WAR M-TEMP
OPEN , MEDI UM /
L ARG E
Gonubie
163
WARM-T EMP
C LI SED, MED IU M
1 62
WARM-T EMP
OPEN, MEDI UM /
LAR GE
161
WAR M-TEMP
CLO SED, SMALL
160
WAR M-TEMP
CLO SED, SMALL
15 9
WARM-T EMP
O PEN, MED IU M /
LARGE
East London
158
WAR M -TEMP
SMALL
N/ A
157
WAR M-TEMP
SMALL
N/ A
156
WARM-T EMP
CL OSED , M EDI UM
318
155
SUBT ROP
WARM-T
EMP
OPEN,
MEDI
UM L
/
C
LO SED,
SMAL
LARGE
201
1 78
WARM-T EMP
O PEN, MEDI UM /
LAR GE
N orth er n Pro vi nc e
No rt h-West
Mp uma la nga
Ga ute n g
Fre e St ate
Kei Mouth
1 77
WARM-T EMP
OPEN, SMALL
Kw a Zu lu /N ata l
N o rth e rn Cap e
Ea st ern Ca pe
We s ter n C ap e
176
WARM-T EMP
CLOSED, MEDI UM
N
At lantic Ocean
In dian Ocean
3185
17
SU BTR O
P
WARM-T
EMP
OOPEN
PEN,, MED
MEDIIU
UM/
M/
LARGE
LAR
GE
1 74
WAR M-TEMP
CLOSED, SMALL
3183
17
WARM-T
SU BTR EMP
OP
OPEN
,
CL OSEDMEDIUM/
, MEDIUM
LARGE
3 18
172
SUBT
ROP
WAR
M-TEMP
CLOSED,
OPEN, MED
SMALL
IU M/
LAR GE
1 71
WAR M-TEMP
C LOSED, MED IU M
318
17 0
SU BTR EMP
OP
WARM-T
CL
OPEN
OSED
, MEDIUM/
, MEDIUM
LARGE
3189
16
WARM-T
SU BTR EMP
OP
OPEN
, MEDIUM/
CL
OSED
, MEDIUM
LARGE
3188
16
WARM-T
SU BTR EMP
OP
OPEN
,
CL OSEDMEDIUM/
, MEDIUM
LARGE
3187
16
SU BTR EMP
OP
WARM-T
C
OPEN
LOSED,
, MEDIUM/
SMAL L
LARGE
202
178
WARM-TEMP
OPEN, MEDIUM /
LARGE
N o rt h er n Pr o vi nc e
N o rth -W e st
Mp u ma la n ga
G au te n g
Fr ee St at e
Kei Mouth
177
WARM-TEMP
OPEN, SMALL
Kw a Zu lu /N a ta l
N o r th e rn Ca pe
Ea st e rn Ca pe
We s te r n C ap e
176
WARM-TEMP
CLOSED, MEDIUM
N
A tlant ic Ocean
In dian Ocean
318
175
SUBTROP
WARM-TEMP
OPEN,
OPEN,MEDIU
MEDIUM/
M/
LARGE
174
WARM-TEMP
CLOSED, SMALL
318
173
WARM-TEMP
SUBTROP
OPEN, MEDIUM/
CLOSED,
MEDIUM
LARGE
318
172
SUBTROP
WARM-T
EMP
CLOSED,
OPEN, MEDIUM/
SMALL
LARGE
171
WARM-TEMP
CLOSED, MED IUM
318
170
SUBTROP
WARM-TEMP
CLOSED,
OPEN, MEDIUM/
MEDIUM
LARGE
318
169
WARM-TEMP
SUBTROP
OPEN, MEDIUM/
CLOSED,
MEDIUM
LARGE
318
168
WARM-TEMP
SUBTROP
OPEN,
MEDIUM/
CLOSED,
MEDIUM
LARGE
318
167
SUBTROP
WARM-TEMP
COPEN,
LOSED,
MEDIUM/
SMALL
LARGE
203
Mend wana
Nor th e rn Prov in ce
Nor th -We s t
M pu ma la n ga
Ga ut e ng
Men du
unn amed
Fre e S ta te
2 10
WARM -T EMP
N/S
N/S
N /S
N /S
2 09
WARM -T EMP
N /S
N/S
N /S
N /S
2 08
WARM -T EMP
N/S
N/S
N /S
N /S
2 07
WARM -T EMP
N/S
N/S
N /S
N /S
2 06
WARM -T EMP
N/ S
N/S
N /S
N /S
2 05
WARM -T EMP
N/S
N/S
N /S
N /S
2 04
WARM -T EMP
N/S
N/S
N /S
N /S
2 03
WARM -T EMP
N /S
N/S
N /S
N /S
2 02
WARM -T EMP
N /S
N/S
N /S
N /S
2 01
WARM -T EMP
N /S
N/S
N /S
N /S
2 00
WARM -T EMP
N/ S
N/S
N /S
N /S
1 96
WARM -T EMP
N /S
N/S
N /S
N /S
1 95
WARM -T EMP
N /S
N/S
N /S
N /S
N/S
N /S
N /S
K w aZu lu /Na ta l
Nor th e rn C ape
E as te r n C ape
We st er n C ap e
N
At lant ic Oce an
Indian Ocean
Dwesa
Ngoma (Kob ol e)
Ngo ma ne
Gu me
Nqabara
Nqab aran a
Ku-Noceke dwa
Kwa -Goqo
u nn amed
Be echa mwood
Shixi ni
199
W ARM-T EM P
OPEN , MEDI UM /
LARGE
Ngadla
Juju ra
Mbo kotwana
Mbozi
318
198
SUBT ROP
WARM -T EMP
OPEN, MEDI UM/
OPEN , SMALL
L ARGE
318
197
SUBT-T
ROP
WARM
EMP
OPEN,
UM/
OPEN MEDI
, SMALL
L ARGE
Qora
Nebelel e
194
W ARM-T EM P
OPEN , MEDI UM /
LARGE
Mazeppa Bay
Sih lon tlweni
(Gcin a)
204
1 93
WARM -T EMP
N /S
No rthe rn Prov in ce
No rth -We st
Lubanzi
228
WAR M-TEMP
N /S
N/ S
N/ S
N/ S
22 7
WARM-T EMP
N/ S
N/ S
N/ S
N/ S
22 6
WARM-T EMP
N/ S
N/ S
N/ S
N/ S
22 5
WARM-T EMP
N/ S
N/ S
N/ S
N/ S
22 4
WARM-T EMP
N/ S
N/ S
N/ S
N/ S
22 3
WARM-T EMP
N/ S
N/ S
N/ S
N/ S
N/ S
N/ S
N/ S
N/ S
N/ S
N/ S
212
WAR M-TEMP
N /S
N/ S
N/ S
N/ S
211
WAR M-TEMP
N /S
N/ S
N/ S
N/ S
M pu mal an ga
Gaute ng
Free S ta te
K w aZul u/ Na ta l
No rth er n Cape
Mncwasa
E aste rn C a pe
We st er n C a pe
N
Atl ant ic Oce an
unnamed
Indian Ocean
Nqakanqa
Ku -Aman zimnyana
3182
22
WARM-T
SU BTR EMP
OP
OPEN , MEDIUM/
LARGE
Bulungula
3181
22
WARM-T
SU BTR EMP
OP
CLOSED
OPEN , MEDIUM/
, SMALL
LARGE
Xora
3180
22
WARM-T
SU BTR EMP
OP
OPEN , MEDIUM/
LARGE
Sund wana
219
WAR M-TEMP
N /S
Nkanya
Nyumb azana
Cwebe
Ntlonyane
3188
21
WARM-T
SU BTR EMP
OP
CLOSED
OPEN , MEDIUM/
, SMALL
LARGE
217
WAR M-TEMP
OPEN, SMALL
Kwa-Suku
Dakana
Ku-Bhula (Mbhanyana)
Ku-Mpenz u
216
WAR M-TEMP
N /S
3185
21
WARM-T
SU BTR EMP
OP
OPEN
OPEN,
, MEDIUM/
SMAL L
LARGE
3184
21
WARM-T
SU BTR EMP
OP
OPEN
OPEN,
, MEDIUM/
SMAL L
LARGE
2 13
WAR M-TEMP
OPEN, MEDIUM /
L ARGE
Mbashe
unnamed
Mendwan a
Mendu
205
Hluleka
Bay
No rth e rn Pr ov in ce
No rth - We s t
M pu mala n ga
Ga ut e ng
Fre e State
Hluleka
241
SU BTR OP
N/ S
N/S
N/ S
N/ S
Mtakatye
240
SU BTR OP
N/ S
N/S
N/ S
N/ S
239
SU BTR OP
N/ S
N/S
N/ S
N/ S
238
SU BTR OP
N/ S
N/S
N/ S
N/ S
N/S
N/ S
N/ S
23 1
WARM-T EMP
N/S
N/ S
N/ S
23 0
WARM-T EMP
N/ S
N/S
N/ S
N/ S
22 9
WARM-T EMP
N/ S
N/S
N/ S
N/ S
K waZulu /Na ta l
N or th er n C a pe
E aster n Ca pe
We stern C a pe
N
Atlant ic Oce an
Indian Ocean
Preslies
Bay
Lwandi le
Lw andi lana
Mdumbi
23 7
WARM-T EMP
OPEN, MED IU M /
LAR GE
Th sani
236
WAR M-TEMP
CLOSED, SMALL
Mtata
23 5
WARM-T EMP
OPEN, MED IU M /
LAR GE
Umtata Mouth
Ma puzi
234
WAR M-TEMP
OPEN, SMALL
Coffee
Bay
Nenga
Ku-Bomvu
23 3
WARM-T EMP
OPEN,
OPEN,SMALL
MED IU M /
LAR GE
23 2
WARM-T EMP
N/ S
Mto njan e
Hole in the Wall
Mpako
Mhlahla ne
Lu banzi
206
Nor th er n Pr ovin ce
No rth -W es t
Mp um al an ga
Ga u ten g
Free State
Kw a Zul u/Na tal
Mzimvu bu
25 4
SU BTR OP
OPEN, M ED IU M /
LARGE
Port St. Johns
253
SU BTR OP
OPEN , SMALL
N ort he rn C a pe
E a ste r n C a p e
Mtumban e
Weste rn Ca pe
N
At lan tic Ocean
Bulolo
Indian Ocean
Gxwaleni
Ntloboba
Tyitya ne
Mnga zi
2 52
SUBT ROP
OPEN, SM ALL
318
251
SUBT
ROOP
P
SU BTR
OPEN , MEDIUM/
CL OSED , SMALL
L ARGE
250
SUBT RO P
N/ S
N/S
N /S
N /S
249
SUBT RO P
N/ S
N/S
N /S
N /S
N/S
N /S
N /S
243
SUBT RO P
N/ S
N/S
N /S
N /S
242
SUBT RO P
N/ S
N/S
N /S
N /S
248
SU BTR OP
OPEN , M EDI UM /
LARGE
Mngazan a
24 7
SU BTR OP
OPEN, M ED IU M /
LARGE
Nd luzula
246
SUBT RO P
N/ S
Sinangw an a
245
SU BTR OP
OPEN , MEDIUM /
LARGE
Mpande
318
24 4
SUBT
ROOP
P
SU
BTR
OPEN
, MEDIUM/
OPEN,
SMAL L
L ARGE
Mtonga
Mne nu
Hluleka Bay
Hlul eka
207
N orthe rn Pro vin c e
Mbotyi
N ort h-West
268
SUBT ROP
N/S
Mp uma lan ga
Ga ute n g
Fre e St ate
N/ S
N/S
N/S
N/ S
N/S
N/S
266
SUBT ROP
N/S
N/ S
N/S
N/S
265
SUBT ROP
N/S
N/ S
N/S
N/S
N/ S
N/S
N/S
Kw aZu lu/Na ta l
267
SUBT ROP
N/S
N or th ern Cap e
Ea st ern Ca pe
We ste rn C ap e
N
Atl ant ic Ocean
In di an Ocean
Mguga
Mzintlava
264
SUBT ROP
N/S
Da kane
263
SUBT ROP
N/S
N/ S
N/S
N/S
Ntyivin i
262
SUBT ROP
N/S
N/ S
N/S
N/S
261
SUBT ROP
N/S
N/ S
N/S
N/S
259
SUBT ROP
N/S
N/ S
N/S
N/S
258
SUBT ROP
N/S
N/ S
N/S
N/S
257
SUBT ROP
N/S
N/ S
N/S
N/S
N/ S
N/S
N/S
Ingo
Mntafu fu
260
SU BTR OP
OPEN , MEDIUM/
LARGE
Gugu
Nkodusweni
Manzana
Ntlupen i
256
SU BTR OP
OPEN , SMALL
Mneng a
255
SUBT ROP
N/S
Mzimvubu
Port St. Johns
208
N orthe rn Pro vi nc e
N or th-We st
Mp uma la ng a
Gau te n g
283
SUBT ROP
OPEN , SMALL
Mkambati
Fr ee Sta te
Kw aZu lu /N ata l
Kwa-Nondindw a
Butsha
Msi kaba
N ort h ern C a pe
E a stern C a pe
Wes te rn Cap e
28 2
SU BTR OP
OPEN, MED IU M /
LARGE
N
At la ntic Ocean
India n Ocean
28 1
SU BTR OP
N/S
N /S
N/S
N/S
28 0
SU BTR OP
N/S
N /S
N/S
N/S
27 9
SU BTR OP
N/S
N /S
N/S
N/S
27 8
SU BTR OP
N/S
N /S
N/S
N/S
27 7
SU BTR OP
N/S
N /S
N/S
N/S
27 6
SU BTR OP
N/S
N /S
N/S
N/S
27 5
SU BTR OP
N/S
N /S
N/S
N/S
27 4
SU BTR OP
N/S
N /S
N/S
N/S
27 3
SU BTR OP
N/S
N /S
N/S
N/S
27 2
SU BTR OP
N/S
N /S
N/S
N/S
27 1
SU BTR OP
N/S
N /S
N/S
N/S
27 0
SU BTR OP
N/S
N /S
N/S
N/S
26 9
SU BTR OP
N/S
N /S
N/S
N/S
26 8
SU BTR OP
N/S
N /S
N/S
N/S
Mb axeni
Kilroe Be ach
Magogo
Te zana
Port Grosvenor
Maviti
Mkweni
Lu patana
Mlamb omkulu
209
N o rt hern P ro vi nc e
N o rth -W est
Mp uma la n ga
Gau te n g
Fre e St at e
Mtamvun a
Mtentw an a
2 98
SUBT RO P
C LOSED, MED IU M
Mzamba
2 97
SUBT ROP
OPEN, MED IU M /
LAR GE
Kw a Zu lu /N a ta l
N o rth e rn Cap e
Ea stern Ca p e
We ster n C ap e
N
At lantic Ocean
In di an Ocean
Mpahla ne
Mpahlanyana
unna me d
Mnyameni
Mtola ne
2 96
SUBT ROP
N /S
N/S
N/ S
N/S
2 95
SUBT ROP
N /S
N/S
N/ S
N/S
N/S
N/ S
N/S
2 93
SUBT ROP
N /S
N/S
N/ S
N/S
2 92
SUBT ROP
N /S
N/S
N/ S
N/S
2 91
SUBT ROP
N /S
N/S
N/ S
N/S
2 90
SUBT ROP
N /S
N/S
N/ S
N/S
N/S
N/ S
N/S
N/S
N/ S
N/S
N/S
N/ S
N/S
2 94
SUBT ROP
N /S
Kwa nyan a
Siko mbe
Mte ntu
2 89
SUBT ROP
OPEN, MED IU M /
LAR GE
Mgw etyan a
38 8
SU BTR OP
OPEN, SMAL L
Mka mb ati
2 87
SUBT ROP
N /S
Mg we gwe
Da za
Mkambati
Kwa-Nond ind wa
Butsha
210
38 6
SU BTR OP
OPEN, SMAL L
2 85
SUBT ROP
N /S
2 84
SUBT ROP
N /S
No rt hern P ro v inc e
N ort h -West
Mp uma la ng a
Gau te n g
Fre e State
312
SUBT ROP
CLOSED, SMALL
Kongweni
Kw aZu lu /N atal
N or th ern Ca p e
311
SUBT ROP
N /S
N /A
U vuza na
Ea s te rn Cap e
We ste r n C a pe
N
A tlantic Ocean
In di an Ocean
Bilanhlolo
Mvu tshini
310
SU BTR OP
CLOSED, MEDI UM
3 09
SUBT ROP
CLOSED, SMALL
Mbizana
30 8
SU BTR OP
CLOSED, MEDIUM
30 7
SU BTR OP
CLOSED, MEDIUM
Ka ba
Umhlangan kulu
Mpenja ti
Kandan dlo vu
30 6
SU BTR OP
CLOSED, MEDIUM
305
SUBT ROP
C LOSED, MED IU M
30 4
SUBT ROP
CL OSED , MEDIUM
3 03
SUBT ROP
OPEN, SMALL
Ku Boboyi
30 2
SUBT ROP
N/ S
N/S
N/S
N/S
N/S
Sand lun dlu
301
SUBT ROP
OPEN , SMALL
300
SUBT ROP
N/ S
Z olw ane
29 9
SUBT ROP
OPEN, M ED IU M /
LAR GE
Mta mvuna
Mtentwana
0
5 km
211
N or the rn Pro vi nc e
N or th-We st
Mhlungwa
Mp uma la ng a
Ga ute n g
Fr ee Sta te
Kw a Zu lu /N at al
N ort hern C a pe
Mhlabatshane
3 26
SUBT ROP
N /S
N/ S
N /S
N/S
N /S
N /S
N/ S
317
SU BTR OP
N/S
N /S
N/ S
3 16
SUBT ROP
N /S
N/S
N /S
N/S
N /S
32 5
SU BTR OP
OPEN, SMALL
E a stern C a pe
Wes te rn Cap e
N
India n Ocean
At la ntic Ocean
Mzumbe
iN tshambil i
Koshwan a
Damba
3 24
SUBT ROP
N /S
323
SU BTR OP
CLOSED, MEDI UM
322
SU BTR OP
N/S
3 21
SUBT ROP
CLOSED, SMALL
Mhlan gamkulu
3 20
SUBT ROP
C LOSED, MED IU M
Mtentweni
3 19
SUBT ROP
C LOSED, MED IU M
Mzimkulu
Mbang o
Boboyi
3 18
SUBT ROP
OPEN, MED IU M/
LAR GE
3 15
SUBT ROP
C LOSED, MED IU M
Mhlange ni
31 4
SU BTR OP
CLOSED, MEDIUM
Vung u
3 13
SUBT ROP
N /S
Ko ngwe ni
0
5 km
212
Mahlongwa
N o rther n Pr ovinc e
Mp u ma la n ga
Ga u ten g
N ort h-West
Fre e St at e
Mpamba nyoni
3 38
SUBT ROP
C LOSED, MED IU M
Kw a Zu lu /N a tal
N o rthe rn Cap e
Ea st e rn Ca p e
We s te rn C ap e
N
Indian Ocean
At lantic Ocean
Mzimayi
3 37
SUBT ROP
CLOSED, SMALL
33 6
SUBT ROP
N/S
N /S
N/S
N/S
N /S
331
SUBT ROP
N/S
N/S
N /S
33 0
SUBT ROP
N/S
N /S
N/S
329
SUBT ROP
N/S
N/S
N/S
N /S
328
SUBT ROP
N/S
N/S
N/S
N /S
32 7
SUBT ROP
N/S
N /S
N /S
N/S
3 35
SUBT ROP
CLOSED, SMALL
Mku mb ane
Sezela
Mdesi ngane
F afa
33 4
SUBT ROP
CL OSED , MEDI UM
333
SUBT ROP
N/S
332
SUBT ROP
C LOSED, MED IU M
Ifafa Beach
Mvuzi
Mtw alume
Mnamfu
Kwa-Makosi
Mfazazana
Mhlungwa
0
5 km
213
N ort h- West
35 1
SU BTR OP
OPEN, MED IU M /
LARGE
Mgen i
Northe rn Pro vinc e
Mp um a lang a
Gau te n g
Free Sta te
Kw a Zu lu/N at a l
3 50
SUBT ROP
N /S
Durban
N o rt hern C a pe
N/S
N /S
N /S
Durba n Bay
E a st er n C ap e
We st e rn Cap e
N
At la nti c Ocean
Indian Ocean
Mlaas Can al
Siping o
Mbo kodweni
3 49
SUBT ROP
C LOSED, MED IU M
348
SUBTROP
O PEN, SMAL L
347
SUBT ROP
C LOSED, MED IU M
Manzimto ti
Little Man zimtoti
34 6
SU BTR OP
CLO SED, MEDI UM
Lovu
3 45
SUBT ROP
OPEN, MEDIUM /
L ARGE
Msimba zi
uMgababa
Ng ane
Mahl ongwan a
344
SUBT ROP
N/S
N/S
N/S
N/ S
343
SUBT ROP
N/S
N/S
N/S
N/ S
342
SUBT ROP
N/S
N/S
N/S
N/ S
341
SUBT ROP
OPEN , MEDIUM /
L ARGE
340
SUBT ROP
N/S
Mahlongwa
Mp ambanyoni
214
339
SU BTR OP
CLOSED, MEDIUM
N/S
N/ S
N ort he rn Pro vi nc e
N o rth-We st
Tu gela
Mp uma la ng a
Ga u te ng
36 1
SUBT ROP
OPEN, MED IU M /
LARGE
Kw a Zu lu /N ata l
Fre e Stat e
N o rth ern C ap e
Zinkwasi
Ea st ern C a p e
36 0
SU BTR OP
CLOSED, MEDIUM
We ster n Ca p e
N
A tla ntic Ocean
Ind ia n Ocean
Nono ti
359
SUBT ROP
N/S
N /S
N /S
N/S
N /S
N/S
N /S
35 8
SU BTR OP
CLOSED, MEDI UM
Mdlota ne
3 57
SUBT ROP
O PEN, MEDI UM /
LAR GE
Mvoti
Seteni
35 6
SUBT ROP
N/S
355
SUBT ROP
OPEN, MEDIUM /
LAR GE
Mhlali
Tongati
354
SUBT ROP
N/S
Mdloti
35 3
SU BTR OP
CLOSED, MEDIUM
35 2
SU BTR OP
CLOSED, MEDIUM
Mhla nga
3 51
SUBT ROP
OPEN, MEDIUM /
LAR GE
Mg eni
215
3 71
SUBT ROP
OPEN, MEDIUM /
LAR GE
N orthe r n Pro vinc e
Kosi Bay
N orth-We st
Mp uma la ng a
Ga ute n g
Fr ee Sta te
N/ S
K wa Zu lu /Na ta l
N o rth er n C ap e
Easte rn Cap e
We ster n Ca p e
Mg obezeleni
N
A tlanti c Ocean
Ind ia n Ocean
St Lucia
Mfo lozi /
Msundu zi
N hlab ane
3 70
SUBT ROP
OPEN, SMALL
N/S
36 9
SUBT ROP
OPEN, MED IU M /
LAR GE
N /S
36 8
SUBT ROP
OPEN, MED IU M /
LAR GE
N/S
3 67
SUBT ROP
N /S
N /S
N /S
366
SU BTR OP
N/S
N/ S
N/S
N/ S
N/ S
N/S
N/ S
N/S
Richards Bay
R icha rd s
Ba y /
Mhl atuze
Mlalazi
365
SUBT ROP
N/ S
3 64
SUBTROP
OPEN, MEDI UM /
L ARG E
N/S
3 63
SUBTROP
CL OSED , M EDI UM
N/S
362
SUBT ROP
OPEN , MEDIUM /
L ARGE
N /S
Siya i
Ma tigulu /
Nyoni
Tuge la
216