Long-term monitoring of vegetation dynamics in the Goegap

Long-term monitoring of vegetation dynamics in the Goegap
Long-term monitoring of vegetation dynamics in the Goegap
Nature Reserve, Namaqualand, South Africa
by
NADINE LIDA BROODRYK
Submitted in partial fulfilment of the requirements for the degree
MAGISTER SCIENTIAE
Department of Plant Science
School of Biological Sciences
In the Faculty Natural and Agricultural Sciences
University of Pretoria
Pretoria
Supervisor: Prof. M. W. van Rooyen
April 2010
© University of Pretoria
I declare that the thesis/dissertation, which I hereby submit for the degree Magister Scientiae at
the University of Pretoria, is my own work and has not previously been submitted by me for a
degree at this or any other tertiary institution.
SIGNATURE: ………………………………..
DATE: ………April 2010………………….…
TABLE OF CONTENTS
ABSTRACT ............................................................................................ vi
ACKNOWLEDGEMENTS ......................................................................... vii
CHAPTER 1
INTRODUCTION .......................................................... 1
CHAPTER 2
LITERATURE REVIEW.................................................. 4
2.1
Introduction ..................................................................................... 4
2.2
Long-term monitoring
2.2.1
2.2.2
2.2.3
2.2.4
2.2.5
2.2.6
2.2.7
2.2.8
2.2.9
2.3
......................................................................... 4
Introduction ............................................................................. 4
Defining long-term ecological monitoring/research ................................... 5
The importance of long-term studies in environmental science ...................... 5
Systematic approaches to long-term studies (LTS) .................................. 7
Long-term study requirement .......................................................... 7
Phenomena addressed by long-term studies (LTS) .................................. 9
Advantages of long-term studies (LTS) .............................................. 11
Alternative approaches to long-term studies (LTS) .................................. 12
Concluding remarks on long-term monitoring ........................................ 13
2.3.6
......................................................................... 13
Introduction ............................................................................ 13
The traditional concept of succession ................................................ 14
Terminology ............................................................................ 16
Documenting succession.............................................................. 17
Modelling and succession ............................................................. 17
Vegetation dynamics and plant community management ........................... 18
2.3.7
Implications of vegetation change for range or veld management in arid and
Vegetation dynamics
2.3.1
2.3.2
2.3.3
2.3.4
2.3.5
semi-arid rangelands ................................................................ 18
2.3.8
2.3.9
............................................. 22
Concluding remarks on vegetation dynamics ........................................ 22
Sustainability and productivity modeling
i
2.4
Veld management ............................................................................. 23
2.4.4
............................................................................ 23
Carrying capacity and succession .................................................... 23
Ecological carrying capacity versus economic carrying capacity ................... 24
Veld condition assessment ............................................................ 25
2.4.5
Comparison of the ecological index method (EIM) and the degradation
2.4.1
2.4.2
2.4.3
Introduction
gradient method (DGM) ............................................................. 29
2.4.6
2.5
Concluding remarks on veld condition................................................ 31
Mechanism of plant species survival ....................................................... 31
2.5.1
Life form classification ................................................................. 31
2.5.2
The annual species – evasion ........................................................ 32
2.5.3
The succulent species – tolerance
2.5.4
CHAPTER 3
................................................... 34
Concluding remarks on plant life history strategies .................................. 35
STUDY AREA ............................................................. 36
3.1
Introduction .................................................................................... 36
3.2
Goegap Nature Reserve ...................................................................... 38
3.3
Background .................................................................................... 38
3.4
Climate .......................................................................................... 39
3.5
Wildlife .......................................................................................... 40
3.6
Vegetation ...................................................................................... 41
3.7
Geology and soils ............................................................................. 42
3.8
Management units............................................................................. 46
3.9
The line transects
............................................................................. 47
ii
CHAPTER 4
METHODS ................................................................. 50
............................................................................ 50
4.1
Field methodology
4.2
Data analyses .................................................................................. 55
4.2.1
Vegetation cover and diversity ........................................................ 55
4.2.2
Life forms............................................................................... 55
4.2.3
Range condition and carrying capacity ............................................... 57
4.2.4
Ordination .............................................................................. 57
CHAPTER 5
5.1
5.1.2
5.1.3
5.1.4
5.1.5
........................................................................... 72
Rainfall ................................................................................. 72
Frequency of occurrence of annual and perennial species ......................... 72
Species and life form diversity ........................................................ 74
Species composition .................................................................. 76
Grazing capacity ....................................................................... 83
Bluemine Mountain
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5
5.3
............................................................................... 59
Rainfall ................................................................................. 59
Frequency of occurrence of annual and perennial species ......................... 59
Species and life form diversity ........................................................ 60
Species composition .................................................................. 65
Grazing capacity ....................................................................... 71
Bleshoek Plains
5.1.1
5.2
RESULTS AND DISCUSSION ....................................... 59
Goegap Plains ................................................................................. 84
5.3.1
Rainfall ................................................................................. 84
5.3.2
Frequency of occurrence of annual and perennial species
5.3.3
5.3.4
5.3.5
......................... 84
Species and life form diversity ........................................................ 86
Species composition .................................................................. 88
Grazing capacity ....................................................................... 96
iii
5.4
Jaleeg Plains ................................................................................... 97
5.4.1
Rainfall ................................................................................. 97
5.4.2
......................... 97
Species and life form diversity ........................................................ 99
Species composition ................................................................ 101
Grazing capacity ..................................................................... 108
5.4.3
5.4.4
5.4.5
5.5
Koperberg Plains ............................................................................ 109
5.5.1
Rainfall ............................................................................... 109
5.5.2
Frequency of occurrence of annual and perennial species
5.5.3
5.5.4
5.5.5
5.6
....................... 109
Species and life form diversity ...................................................... 111
Species composition ................................................................ 114
Grazing capacity ..................................................................... 120
T’ganagas Plains ............................................................................ 121
5.6.1
Rainfall ............................................................................... 121
5.6.2
Frequency of occurrence of annual and perennial species
5.6.3
5.6.4
5.6.5
5.7
Frequency of occurrence of annual and perennial species
....................... 121
Species and life form diversity ...................................................... 122
Species composition ................................................................ 124
Grazing capacity ..................................................................... 130
Zebrawater Foothills ........................................................................ 131
5.7.1
Rainfall ............................................................................... 131
5.7.2
Frequency of occurrence of annual and perennial species
5.7.3
5.7.4
5.7.5
....................... 131
Species and life form diversity ...................................................... 133
Species composition ................................................................ 136
Grazing capacity ..................................................................... 143
iv
DISCUSSION AND CONCLUSIONS ............................. 144
CHAPTER 6
6.1
Introduction .................................................................................. 144
6.2
Vegetation trends
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5
6.2.6
6.2.7
........................................................................... 144
Bleshoek Plains ...................................................................... 144
Bluemine Mountain .................................................................. 145
Goegap Plains ....................................................................... 145
Jaleeg Plains ......................................................................... 146
Koperberg Plains .................................................................... 147
T’ganagas Plains .................................................................... 147
Zebrawater Foothills ................................................................. 148
...................................................................... 148
6.3
Long-term monitoring
6.4
Vegetation dynamics
6.5
Mechanisms of plant species survival.................................................... 150
6.6
Veld condition
6.7
Conclusions and veld management recommendations ................................ 151
....................................................................... 149
............................................................................... 150
CHAPTER 7
REFERENCE LIST .................................................... 152
CHAPTER 8
APPENDIX ............................................................... 163
v
ABSTRACT
Long-term monitoring of vegetation dynamics in the Goegap Nature Reserve,
Namaqualand, South Africa
by
NADINE LIDA BROODRYK
Supervisor: Prof. M.W. van Rooyen
DEPARTMENT OF PLANT SCIENCE
MAGISTER SCIENTIAE
Namaqualand is a semi-desert area situated in the winter rainfall region of South Africa hosting
the world’s richest succulent flora, and is one of only two arid areas to classify as a global hotspot
of biodiversity. The Goegap Nature Reserve, east of Springbok, lies in the Upland Succulent
Karoo. After all the livestock were removed and the reserve fenced in 1969, a long-term
monitoring project was initiated to record possible vegetation changes under the reduced grazing
pressure. The first monitoring was done in 1974 when two line transects, of 1 km each, were
surveyed. These surveys have been repeated annually covering a period of more than 30 years.
When the reserve was enlarged in 1990, five additional line transects were set out in highly
degraded areas. The main aim of this study was therefore to determine whether any changes in
the vegetation in terms of species composition, species richness and life form richness in the
monitored line transects could be detected. Rainfall as possible force driving these changes was
also examined. It was found that changes did indeed take place in the vegetation. The species
composition revealed notable changes over the entire monitored period, specifically in the two
longest established line transects, whereas in the case of the species richness changes were
also detected, but to a lesser extent and not notable in terms of an overall increase or decrease in
the number of species. These changes are referred to as fluctuations. Rainfall can be regarded
as a definite environmental driving force, with the time, intensity and duration of importance,
specifically to the annual species composition. Overall, the veld condition improved and
continuous monitoring of the line transects on a regular basis should take place to improve our
understanding of the complex dynamics of this ecosystem. Because the changes in species
composition are reflected in changes in grazing capacity the results are of direct importance to
the management of the wildlife on the reserve.
vi
ACKNOWLEDGEMENTS
I thank my Heavenly Father for His wisdom, grace and love He bestowed upon me throughout
this project. I would also like to express my sincere gratitude towards the following persons and
institutes for their support and interest:
Professor M.W. (Gretel) van Rooyen who I truly admire for being such an incredible
supervisor.
Helga van der Merwe and Annelise le Roux for sharing their immense knowledge of the
study area.
Northern Cape Department of Environment and Nature Conservation, as well as the
Goegap Nature Reserve management for making use of their facilities.
The Department of Plant Science, University of Pretoria, for making use of their facilities
and the University’s financial support.
The German Federal Ministry of Education and Research (BMBF) through the BIOTA
South Project, for their financial support.
The National Research Foundation for their financial support, under grant number 61277.
The Council for Geoscience, Pretoria, for the complimentary electronic data.
Magda Nel, as well as the National Botanical Institute, for the help with the herbarium work.
The following persons for their help with the field work: Annelise le Roux, Prof. Gretel van
Rooyen, Prof. Noël van Rooyen, Helga van der Merwe, Christopher Rakuambo, Helene
Fotouo, Betsie le Roux, Lizandé Kellerman, Conrad Geldenhuys, Ronel Mulder, Retief
Grobler and Angelique Kritzinger.
Many thanks to all my friends for always being interested and willing to help.
My whole family, for all their interest, patience and encouragement, especially my parents
and grandmother - you are truly synonymous to love…
vii
CHAPTER 1
INTRODUCTION
The Succulent Karoo is a global biodiversity hotspot located in southern Africa and is globally one
of a few places to be so biologically distinct (Mucina & Rutherford 2006). A ‘hotspot’ refers to an
area with a high concentration of endemic species and which is also threatened by habitat loss or
alteration (Van Wyk & Smith 2001). Hotspots contain at least 1 500 endemic plant species and
have already lost 75% or more of their original vegetation. Although these hotspots globally
include less than 2% of the earth’s land surface-area, they contribute to 44% of all vascular plant
species and 38% of birds, mammals, reptiles and amphibians (Hilton-Taylor 1996, Van Wyk &
Smith 2001).
This biome hosts a high concentration of leaf-succulent shrubs. It is characterised by low winter
rainfall, extreme summer aridity and lime-rich, weakly developed soils. Rainfall varies between 50
and 350 mm per annum, and the maximum summer temperatures vary between 30ºC and 40ºC.
The species richness, mostly succulents, is much higher than for any other arid area of this size
elsewhere in the world (Mucina & Rutherford 2006). Little information is available on the fauna of
the Succulent Karoo (Low & Rebelo 1998, Le Roux & Van Rooyen 1999).
Although the plant species of the Succulent Karoo Biome are specialised to survive under harsh
climatic conditions any human induced change in their surroundings could affect them adversely.
One of the overriding problems in the region is land degradation due to inappropriate veld
management practices such as overstocking. In a desert ecosystem, seedlings are sought-after
forage. Severe grazing can reduce vegetation cover, resulting in the decrease and disappearance
of shade and protection for the germination and survival of seedlings of various shrub species.
Thus, some species may disappear due to overgrazing or grazing during an inappropriate time of
the year such as the dry summer months and can result in diminishing a whole seedling crop.
Trampling due to overgrazing can also destroy entire colonies of plants e.g. stone plants (family
Aizoaceae) even if they are unpalatable. The result of overgrazing in arid areas leads to
desertification, defined as the irreversible reduction of the biological potential of land (Cowling et
al. 1999b, Le Roux & Van Rooyen 1999). An increase in abundance of certain indigenous plant
species (such as Galenia africana and Psilocaulon spp.) indicates that the vegetation is
overutilised and therefore grazing should be reduced to the minimum and effective management
1
applied (Le Roux & Van Rooyen 1999). A study conducted by Steinschen et al. (1996) on
whether the invasion of grasses threatens the annual species in Namaqualand, indicated that the
greatest threat to these indigenous plant species was severe grazing.
Arable land, productive soils, indigenous vegetation, water resources and biodiversity are all
decreasing due to human impact (South African Environmental Observatory Network 2004).
Humans are furthermore, an important threat to the Succulent Karoo Biome, especially with
regards to the collection of rare and endangered plant species. Many small succulents easily
exceed ages of 50 years and recruitment occurs only once or twice during their entire lifetime.
Effective resource management programmes are needed to address these problems (South
African Environmental Observatory Network 2004). Fortunately, alien invasive plant species do
not pose a large threat in the region. According to Le Roux and Van Rooyen (1999) there are only
a few alien invasive plant species in the Succulent Karoo Biome (such as Nerium oleander,
Nicotiana glauca and Fumaria muralis) that threaten the native vegetation of this biome.
Conservation in the Succulent Karoo Biome is challenging due to the high diversity of plant
species and also the large variation in habitats. Lombard et al. (1999) stated that it is difficult to
conserve all the plant species occurring in the Succulent Karoo Biome within a formal nature
reserve system, due to its highly variable species richness together with high compositional
species turnover. Ideally, conservation would include the design of a reserve network
representing the enormous biodiversity of the Succulent Karoo vegetation (Cowling et al. 1999a).
Even though it is impossible to exactly predict the impacts of global warming, there is little doubt
that climate change will add another layer of complexity to effective veld management and
conservation. Both plant and animal species will react to climate change by migration, extinction
and speciation. It is very important to ensure that a conservation area will persist in the face of
predicted climate change (Cowling et al. 1999a, 1999b). However, conservation outside protected
areas is also very important (Hendricks et al. 2005). Protected areas in the country will have to
integrate parts of existing rangelands and will therefore be challenged to reduce numbers of
livestock in the communal livestock production system (Hendricks et al. 2007).
Arid and semi-arid environments frequently display complex non-equilibrium dynamics involving
non-linear and stochastic event-driven behaviour (Westoby et al. 1989a, 1989b). Vegetation
changes occur unpredictably, in the short-term, in response to the inter-annual variation in
rainfall, and episodically in the long-term (several decades) in response to rare events as well as
grazing pressure, changes in climate, altered disturbance regimes, or a combination of these
factors (Behnke & Schoones 1993, Illius & O’Connor 1998, Ward 2006). This complicates the
complete understanding of long-term dynamics, because it is difficult to observe rare events.
2
Long-term ecological monitoring is required in order to increase the understanding of vegetation
dynamics in arid areas (Wiegand & Jeltsch 2000, Ward 2006). The objectives of long-term
ecological monitoring are to examine and document changes in essential assets of biological
communities, while monitoring is also necessary for evaluating the progress of the management
objectives of any project. In spite of the importance of long-term monitoring of the natural
environment, ‘monitoring’ is often regarded as a low-grade science adding little to our
understanding of the functioning of environmental systems (Burt 1994).
The Goegap Nature Reserve, approximately 15 000 ha in size, is situated in Namaqualand, in the
Succulent Karoo Biome (Rösch 2001b). The Hester Malan Nature Reserve was established in
1966 (Le Roux 1984), and in 1969 the reserve was fenced and excluded the livestock that
previously grazed freely in the reserve. In 1990, land from the neighbouring farm Goegap was
added to the reserve and it was declared as the Goegap Nature Reserve. At that stage, this
newly added section was much more heavily grazed than the Hester Malan section. It was only in
2002 that the fence dividing the Hester Malan section from the Goegap section was removed,
after a survey showed that the vegetation on the Goegap part had recovered substantially (Rösch
2001a).
The fencing of the reserve and removal of livestock created an opportunity of investigating
vegetation recovery after severe overgrazing. Firstly, it was of importance to investigate whether
the veld condition improved since the removal of the livestock. Secondly, because wildlife were
reintroduced into the reserve and started increasing in numbers it was important to prevent
overgrazing, therefore degrading of the veld condition. To examine these issues, line transect
surveys were established throughout the Goegap Nature Reserve to monitor the changes in
vegetation, and some of these line transects have been monitored for more than 30 years
already.
To improve our understanding of the vegetation dynamics of the Succulent Karoo it is vital to
have knowledge of the way in which plant species respond to the climate and disturbance
regimes as well as to have knowledge of the life history traits of the species that enable these
responses. Therefore, the main aim of this study was to assess the changes in the vegetation, in
terms of species composition, species richness and life form richness, in seven long-term
monitoring transects in the Goegap Nature Reserve. Because the changes in species
composition are reflected in changes in grazing capacity the results are of direct importance to
the management of the wildlife on the reserve.
3
CHAPTER 2
LITERATURE REVIEW
2.1
Introduction
The objectives of this chapter are to give a broad overview of different concepts to be discussed
further on throughout the study. The importance of long-term monitoring is firstly discussed
because it forms the fundamentals for this long-term study. Thereafter the concepts of vegetation
dynamics and the development of different models applicable to arid regions are considered
because these models can help with interpretation of the vegetation composition changes. Since
carrying capacity and the changes in carrying capacity were determined throughout the monitored
years, a short description of veld management and the essentials of carrying capacity
determination are also given. Lastly, an overview on adaptations of plant species occurring in the
Succulent Karoo, with special reference to life forms is provided, because changes in life form
composition throughout the monitored period was also investigated.
2.2
Long-term monitoring
2.2.1
Introduction
Environmental change is a persistent feature occurring all over the world. A few millennia ago,
lush vegetation, as well as elephant and antelope dominated the North African region, now known
as the Sahara Desert. Early explorers documented rivers in Botswana that have since
disappeared. Preserved ice cores found in Antarctica and Greenland are evidence for extreme
climatic changes that can take place within a short time. Frequently asked questions are: How will
the changes affect precipitation? Will deserts spread or close up? How will our national parks and
other protected areas be affected by such change? These questions can only be answered
through the use of information obtained over a long period of time; therefore with long-term
environmental research (Pickett 1989, South African Environmental Observatory Network 2004).
The value of long-term monitoring has only been recognised relatively recently. There are,
however, a few monitoring experiments that have run for over a century and a well-known
example is the Broadbalk Experiment in Rothamsted which has been in operation for over 150
years. Long-term experiments provide exceptionally valuable information by answering questions
not even considered during the original set up of the experiment (Beard et al. 1999).
4
2.2.2
Defining long-term ecological monitoring/research
Long-term research can be practically defined as the persistence of studies of the environment
beyond the usual limits of funding cycles, completion of a graduate degree, or the length of time
’interesting’ ideas remain trendy (Pickett 1989). Most modern research projects have a life-span
of two to five years (masters or PhD) and therefore past environmental research has been limited
mostly to this short time span. These studies yield important results, however, for the efficient
conservation of our ecosystems another approach, long-term ecological research, is necessary.
In some cases environmental monitoring has extended over longer periods, but rarely in such a
way that cause-effect relationships could be established, thus proper experimental approaches
that include adequate experimental controls were lacking. Research therefore has focused on
small-scale questions, rather than big-scale issues that must be addressed for dynamic national
and global management of the human environment (South African Environmental Observatory
Network 2001, 2002, 2004, Krug et al. 2006).
2.2.3
The importance of long-term studies in environmental science
In spite of the importance of long-term monitoring of the natural environment, ‘monitoring’ is often
regarded as a low-grade science adding little to our understanding of the functioning of
environmental systems (Burt 1994). The objectives of long-term ecological monitoring are to
examine and document changes in essential assets of biological communities. Monitoring is also
necessary for evaluating the progress of management objectives of any project. Monitoring of the
vegetation structure and dynamics has to be done in a scientifically accurate way, while being
cost-effective and widely understandable. Monitoring methods can be limited by the expense,
training requirements and poor repeatability. Therefore, it is essential to identify an appropriate
group of rapid, repeatable and cost-effective methods that reflect various processes and functions
(Havstad & Herrick 2003).
The past has an influence on the present and future course of an ecosystem. Long-term studies
(LTS) document the effects of the past conditions on continuous processes (Figure 2.1).
Therefore, the aim of LTS is to document the changing environmental influences and conditions
before lost to the historical record (Pickett 1989, Burt 1994).
5
Figure 2.1
The various influences on an ecological process or system through time.
In Figure 2.1 the large horizontal arrow indicates the course of a system through time. The small
boxes enclosed represent specific system states whose order can influence the outcome of the
process. The vertical line separating the head from the body of the arrow represents the present,
with the past on the left and the future on the right.
Methods used to gather information for management decisions on a seasonal or annual time
frame are called short-term monitoring and provide data on vegetation status at specific sites.
Methods used to gather information that create a ‘trend-record’ are called long-term monitoring.
Short and long-term monitoring programmes can be integrated in order to achieve management
objectives (Havstad & Herrick 2003). Short-term studies are often misleading and without longterm data there is a lack of interpretation. However, ecologists often appear insensitive to the vital
role of LTS in formulating and testing basic ecological concepts. Thus, long-term data sets are
fundamental for testing most theoretical constructs or concepts central to ecology, but most of
these concepts are not tested because they require systematic, long-term observations. The
organisms studied are usually selected either because they are suited for studies limited in time
and space or they are likely to confirm the theoretical construct. There is consequently an
unacknowledged excess of unanswered questions in ecology, and hypotheses of which the
validity is not known. Most scientists are only interested in new and intriguing ideas and not in
supporting long-term testing. The problem is that concepts are accepted and rejected with little
experimental foundation. In addition, the need to examine spatial and temporal validity, or the
application of a process, structure or mechanism, once recognized, has barely any support
among ecologists. Most scientists have been working on long-term programmes of abiotic rather
than biotic factors. This may be because numerous parameters address social needs (such as
weather) and the greater ease in standardising methods (Franklin 1989). Just as LTS are vital to
ecological sciences, they are also important to identify and resolve social issues, such as the
sustained productivity of forests, agricultural lands and fisheries.
6
2.2.4
Systematic approaches to long-term studies (LTS)
An extensive and systematic approach to LTS is necessary. It is firstly important to note what are
the vital issues that deserve the energy and cost associated with LTS. Experiments need to be
included, where appropriate, to provide contrasting treatments, and need to be kept simple and
straightforward (KISS principle: keep-it-simple-stupid). The design needs to foresee unpredicted
modifications. Non-manipulative observations of processes in natural ecosystems are necessary
in most cases and systematic examination of how processes and structures vary in time and
space is crucial. Therefore, to develop proper designs for long-term research monitoring and
programmes is complex (Franklin 1989). Furthermore LTS should include comparative studies of
processes across and within biomes. Care should be taken not to view ecological mechanisms as
being mutually exclusive (Franklin 1989).
It is important that more research includes different organisational levels, i.e. population,
community, ecosystem and landscape. Most natural resource issues such as biodiversity
conservation necessitate combined knowledge on all levels, from the genetic to the landscape.
Detailed and specific information is required to make crucial decisions on biological resources as
well as to formulate ecological hypotheses (Franklin 1989).
Procedural considerations include methodology and data management. A well-planned
experimental design and exploitation of best current technology are important in monitoring
programmes. The data documentation and management procedures need to be detailed although
the documentation of initial conditions can be problematic. Nonetheless, data need to be
available and easy accessible whenever required (Franklin 1989).
2.2.5
Long-term study requirement
According to Pace and Cole (1989) LTS are required when:
Changes of an ‘unknown’ type are monitored. Although some changes may be
expected, the nature of the change may be unclear.
Studying the dynamics of certain ecological systems where no surrogate methods are
available.
Many ecological phenomena fall under these two categories. Monitoring (Figure 2.2) plays an
important role in LTS, and if carefully designed may reveal the scales of variability in an
ecological system. It provides the vital data for evaluating indirect methods, such as models or
remote sensing.
7
The role of long-term monitoring in policy and management
assessment
Survey
Research
Monitoring
Prediction
How will it change?
Assessment
Is
policy/management
working?
Policy/Management
Figure 2.2
Monitoring, research and modelling are required to detect and manage
environmental change, and are interconnected actions (Parr et al. 2003).
Pace and Cole (1989) suggested the following with regards to monitoring:
a) Monitoring is the most effective when combined with experimental manipulation;
b) Archiving is essential for future developments in analytical techniques, re-evaluation of
existing ideas, as well as development of new questions and
c) A monitoring programme must be relatively inexpensive and comprise only a small
percentage, about 10%, of the resources of a LTS.
Monitoring, however, requires substantial time allocation. It is suggested that technology and
methods should be improved to reduce time and expenses of monitoring programmes. In any
case it is important that the time used for monitoring should be acknowledged as valuable and
vital even when the monitoring does not result in longer term studies (Pace & Cole 1989).
Ecological monitoring is based on collection, analysis and interpretation of data, designed to
investigate biophysical phenomena outside project or programme cycles. The objective of
ecological monitoring is to predict environmental trends to prevent disastrous consequences.
8
Indicators (or benchmarks) are used to help provide concise answers to the monitoring question
(Abbot & Guijt 1998).
The following are examples of issues that have vital long-term components (Franklin 1989):
Ecosystem changes associated with succession;
Predator-prey interactions which tend to be complex with long-term cycles, specifically for
large vertebrates;
Productivity controls, for example, the effect of herbivory on short- and long-term
productivity of terrestrial ecosystems;
Geomorphic processes including weathering of parent materials and erosion;
Ecosystem responses to atmospheric inputs, including pollutants and changes in key
biogeochemical cycles;
The effects of climatic change;
Genetically engineered organisms and
Biodiversity losses.
2.2.6
Phenomena addressed by long-term studies (LTS)
Slow phenomena
Many environmental processes happen over a much longer period of time than the time for a
research degree. One such process for an example is succession. If one required reliable
conclusions, long-term studies would be needed to examine succession. For long-lived species
important life history events happen over long periods of time.
In these cases LTS are
fundamental to document population dynamics and their influence on ecosystems. LTS are also
necessary to identify the factors controlling the recruitment or mortality of populations when these
are intermittent (Pace & Cole 1989). Additional examples include soil development and wood
decay (Franklin 1989, Pickett 1989, Burt 1994).
Transient occurrences are often misinterpreted by short-term studies. It was found that 70% of
ecological experiments lasted less than one year (Pickett 1989, Burt 1994). The predicament with
the short time frame of most ecological experiments is the variation in outcome due to the
variability in the environment. Experiments done in different years often yield different results.
Differences in initial conditions as well as changing boundary conditions may be of importance.
Some differences may occur due to repeating studies at different times without a persistent
priority system. Therefore, LTS are a reliable way to determine slow processes (Pickett 1989).
9
Episodic phenomena (rare events)
Rare events are the second main type of process amenable to LTS. This category includes any
ecological event with a return time of more than a few years. The only way to learn the frequency
and ecological significance of such phenomena is to observe them over long periods and only
then will some be discovered. Rare events may, to some extent, be predictable (El Nino events in
the eastern Pacific) or unpredictable (floods, fire, volcanic eruptions) or periodic. Rare events that
are to some degree predictable can possibly be captured by short-term studies. Periodic
recruitment, periodic mortality or small gap disturbance may also be open to short-term studies.
An extreme type of rare event is unique, unprecedented and unrepeatable, such as the invasion
of an exotic species or the outbreak of a disease and these are only accessible through LTS.
Reproductive patterns for long-lived organisms are an example of this class of event. Many
species are episodic reproducers as a consequence of environmental variables, seed production
or disturbance patterns, and these are specifically evident in marginal or stressful environments.
Rare events have an impact on ecosystems even if at intermediate frequencies (Franklin 1989,
Pickett 1989, Burt 1994).
Rare events, such as a spatially extensive event (e.g. drought) or localised event (e.g. tornado)
are better observed via long-term studies. However, even so, a LTS network will probably
overlook local events too. If an event has extensive effects continued LTS will show this in
records. Thus, without LTS these events’ importance in ecosystem development and life cycles of
organisms go unnoticed (Franklin 1989, Burt 1994).
Subtle and complex phenomena
Subtle and complex phenomena require LTS in order to separate pattern (trend) from ‘noise’
(non-trend). Subtle processes change over time but the year-to-year variance is large compared
to the magnitude of the trend. Complex phenomena include various interacting features. LTS are
needed to investigate these events to sort out the relative contribution of multiple factors through
acquiring an adequate statistical sample (Franklin 1989).
Subtle processes will not be noticed unless a long record is present because subtle processes
are embedded in a variable matrix. Even if a clear outline does exist, high frequency variation will
obscure this and short-term studies will fail to notice it. Systems or processes strongly influenced
by climate are examples of this. LTS can reveal what the multiple factors contributing to, for
example, climate change are, whereas without LTS it is difficult to attribute these fluctuations to
certain processes (Pickett 1989, Burt 1994).
10
Complex processes have multiple causes. A system must be observed for long enough to include
periods when different causes dominate its structure or function. For systems that are replicated
sufficiently in space, a comparative method may be useful. Population regulation is the possible
paradigm of a multivariate issue. Populations are controlled by various factors including predation and
herbivory, competition and dispersal. Competitive interactions have been studied, almost exclusively,
via short-term studies and it is vital to address the role of these interactions over long periods. It is
clear that there can be noteworthy changes in consequences over time, for example relationships can
shift from competitive to mutualistic. Interactions, initially regarded as unimportant may turn out to be
vital, or interactions initially regarded as essential may turn out to be irrelevant (Franklin 1989, Pickett
1989).
Several ecological processes reveal high levels of year-to-year variability, for example productivity in
deserts which is strongly linked to the level of precipitation. Thus, biological phenomena are strongly
related to physical parameters (Franklin 1989). However, in moderate environments high annual
variability also occurs, for example the litter-fall in mature deciduous hardwood forests (Gosz et al.
1972 in Franklin 1989). Ecologists should frequently assess and publish data on inter-annual high
variability when conducting LTS and monitoring programmes (Pace & Cole 1989).
2.2.7
Advantages of long-term studies (LTS)
Only LTS reveal the existence of trends, cycles and rare events and provide hypotheses for
scientists to explain, whereas short-term experimentation may test the hypothesis, but only
once it is formulated. It takes long to build up a dataset in ecology for the development of
useful hypotheses, because the natural ecosystems are so complex (Burt 1994).
Long-term datasets test hypotheses not formulated and thought of with the initial set-up.
For
example, the Rothamsted classical experiments began in 1843. The original aim was to
determine which elements most limited plant growth. This aim was already achieved by the
1860s and with the continuation of these experiments even until today, many new questions
have been investigated.
Through LTS it becomes clear what significant changes have a negative impact on both the
ecosystem and humans. It is important for long-term monitoring networks to carefully select
indicator variables and species, to provide significant information on future changes, on local,
regional and global scale, and to allow new vital questions to be formulated (Burt 1994).
Although LTS are essential, there still are limitations. Network sites may be subjectively selected and
there may be an insufficient number of sampling sites. One problem area that has been identified is
that successful projects need a dedicated leader, an opportunity (site and idea) and funding (often
11
from various sources) (Franklin 1989). Above all there needs to be consistency and commitment in a
LTS network (Burt 1994).
2.2.8
Alternative approaches to long-term studies (LTS)
Short-term experiments
LTS are more costly, time consuming and difficult than shorter term studies (Pace & Cole 1989).
The most effective LTS are those interacting with short-term experimentation. Without LTS, shortterm studies are often not interpretable, because of the complexity of natural ecosystems. The
cause-and-effect relationships are, however, better understood via short-term studies and these
are used to supplement LTS (Burt 1994).
Modelling
A simulation model forecasts future behaviour by using current knowledge. These models
simulate the result of a combination of processes and thereby predict possible outcomes. LTS are
logistically difficult and scientists need to be patient while collecting data. Therefore the idea of
predicting changes is attractive, specifically for experimentalists who want to evaluate the
consequences of land management changes, or potential climate change before it is too late to
avoid negative consequences. However, no model is superior to the assumptions and data it
depends on. LTS information provides the means for model calibration as well as verification.
Thus, LTS and modelling complement each other (Burt 1994).
Space-time substitution (chronosequence)
Ecosystem change testing, with relation to succession, has been limited principally to
chronosequence analysis. This is the most common approach for studying community and
ecosystem succession but can often be misleading (Franklin 1989, Pickett 1989). The ergodic
hypothesis implies that under certain conditions, sampling in space can be comparable to
sampling through time, and that space-time transformations are possible. Thus, the assumption is
made that the statistical properties of a time series are basically the same as thát of the
observations of the same phenomenon taken in space. Spatial comparison may, however, not be
matching like with like. Ergodic reasoning ignores process and spatial variation within and
between sites (Burt 1994). LTS and space-time substitution may be regarded as complementary
(Franklin 1989, Pickett 1989, Burt 1994).
12
The use of palaeo-environmental data
Analysis of palaeo-environmental data has lead to useful information on environmental change.
Such studies provide information on slow processes (over centuries or millennia) and rare events
can be identified. It may, however, be that they provide data too coarse-grained to be compared
with LTS. Both approaches are needed (Burt 1994).
Mobile study teams
This includes the set up of a study group that is mobile and can rely on routine surveys,
retrospective records or spatial comparisons to investigate changes caused by unique events.
This may be difficult to maintain, but it is likely that at least some members on the team remain
keen to record some extreme events (Burt 1994).
2.2.9
Concluding remarks on long-term monitoring
Some events are best addressed via LTS although this is an expensive route in terms of time,
money and energy. It is therefore important to determine when LTS are necessary and when not
for answering important ecological questions (Pace & Cole 1989). Long-term studies provide an
invaluable basis for the development of environmental science (Burt 1994).
After the World Summit for Sustainable Development, it was seen that LTS and the related longterm ecological networks and programmes such as Environmental Observatories Network (EON)
and Long-term Ecological Research (LTER) are crucial (Biggs et al. 1999, Henschel & Pauw,
2002, Henschel et al. 2003).
2.3
Vegetation dynamics
2.3.1
Introduction
The scientific study of succession began at the end of the nineteenth century and the concept of
plant succession was initiated primarily in North America during the first two decades of the
twentieth century (Glenn-Lewin et al. 1992). Succession can be defined as directional change
over time in community composition. Succession begins when a disturbance is followed by
colonisation of the disturbed site by plants (Mueller-Dombois & Ellenberg 1974, Connel & Slatyer
1977, Gurevitch et al. 2002). The study of succession aims at establishing the patterns and
causes of succession.
13
2.3.2
The traditional concept of succession
Clements (1916 in Connell & Slatyer 1977) offered a rigid view of plant succession, and noted the
following subcomponents in succession, referred to as relay floristics, in which one stage prepared
the way for the next:
Nudation by which novel surfaces are exposed;
Migration is the arrival of disseminules;
Ecesis includes germination, establishment, growth and reproduction;
Competition which may result in replacement of species;
Reaction whereby the species change the habitat and
Final stabilisation as the climax.
Clements’s views (1916 in Connell & Slatyer 1977) on the causes of succession dominated the
literature on the topic for many years. In contrast to Clements, Gleason (1917 in Tainton 1999)
suggested that succession was much less ordered. He believed that successional communities
were incohesive groups and that the nature of any change was largely dependent on the availability
of seed and a favourable environment.
According to Barbour et al. (1987) if there is some directional, cumulative, non-random change in a
community over 1–500 years, the community is a successional (seral) community. However, if no
significant changes occur over the given period, the community is said to be a mature or climax
community. The climax community is said to be in a state of dynamic equilibrium. An apparent
climax, is actually an earlier seral stage maintained by disturbance and is called a disclimax.
Succession, in the traditional sense, leads to a climax community. However, the climax is the most
challenged concept in ecology (Niering 1987, Krohne 2001). Already in 1954 Egler suggested that
the term vegetation change rather than succession should be used. Vegetation change refers to all
kinds of temporal alterations within and between communities. The terms ‘steady state’ or ‘relative
stability’ instead of climax, are more appropriate when looking at fairly stable conditions in any biotic
system (Niering 1987). Such a view of community stability leads to the concept of dynamic
equilibrium. Four stages of species equilibrium were defined by Mueller-Dombois and Ellenberg
(1974):
Non-interactive species equilibrium applies mainly to pioneer plant communities.
Interactive species equilibrium is found when interactive species share the same niche and
form ecological groups. Pioneer communities are replaced by communities consisting of
non-interactive together with interactive species.
Assertive species equilibrium is the consequence of interaction among species which leads
to the formation of long-lived combinations.
14
Evolutionary species equilibrium is the final stage of community development and the
species are adapted genetically to each other and to the environment.
Connell and Slatyer (1977) proposed three other alternative models (the facilitation, tolerance and
inhibition models) to elucidate the mechanisms of successional change after a perturbation. The
models differ with regards to how new species arrive later in the succession sequence.
The early successional species in the facilitation model modify the physical environment in such a
way as to facilitate colonisation by later-successional species. This continues until the occupier
species no longer modify the site to facilitate invasion of other species (Connell & Slatyer 1977,
Krohne 2001). Evidence for this model for autotrophs comes from primary succession on newly
exposed surfaces (Connell & Slatyer 1977, Van Hulst 1992, Gurevitch et al. 2002).
In the tolerance model succession is also driven by changes in the physical environment caused
by species. The early occupiers in this model, however, do not increase or reduce the later
colonists’ growth and invasion. The species’ sequence of appearance is determined only by their
life-history traits. The species appearing later have propagules dispersed more slowly and their
progeny grows more slowly. They grow despite the presence of the early successors. In active
tolerance the presence of one species lowers the growth rate of others by reducing the availability
of resources, whereas in passive tolerance, the change is the result of individual resource
requirement differences of the species involved (Connell & Slatyer 1977, Krohne 2001). The
evidence for this model is that late successional plant species are often capable of establishing
without any preparation of the area by earlier species. This model applies to most secondary
succession. The view of this model suggests that succession leads to a community composed of
the most efficient species in exploiting resources, each specialised on different kinds or quantities
of resources (Connell & Slatyer 1977, Gurevitch et al. 2002).
The inhibition model, suggests that earlier colonists inhibit the invasion of succeeding colonists or
suppress the growth of those already present and prevent any further succession. Thus, the main
element determining the outcome of succession is the nature of the initial colonisation. In this model
the species replacing a dying inhabitant need not have life-history traits different from the original
inhabitant, and the tolerance of late-succession species is of importance, allowing late species to
survive through long suppression periods. Evidence for this pathway is obtained from observations
revealing that later species need no site preparation by earlier species in order to establish; early
species suppress the establishment of later ones, inhibit their growth and reduce their survival.
Even though this may be the case, the earlier species eventually die and are replaced. This model
also applies to most secondary succession (Connell & Slatyer 1977, Gurevitch et al. 2002). In the
15
inhibition model the early colonists are killed by disturbances caused by abiotic or biotic factors
(natural enemies).
The models of Connell and Slatyer (1977) are conceptual models and do not effectively describe
successional changes because they were never designed to do that. They explain only one aspect
of succession and that is the net effect of an earlier species on a later one. Various other aspects
such as seed viability, weather, floods, and herbivore abundance were not included in these models
(Connell et al. 1987).
2.3.3
Terminology
A multitude of terms have been proposed to describe succession:
Primary succession. This is the establishment of vegetation on land not previously
vegetated. The time-scale involved here may be centuries up to thousands of years. On
such a long time-scale evolutionary changes are significant and cannot be ignored. The
establishment on a wet substrate is termed hydrarch primary succession and on a dry
surface xerarch primary succession (Mueller-Dombois & Ellenberg 1974, Burrows 1990,
Barbour et al. 1987, Gurevitch et al. 2002).
Secondary succession. This includes all the non-phenological vegetation changes
occurring in established ecosystems. Secondary succession initiates after a partial
disturbance by either man or nature. An example of an extreme case of secondary
succession is old-field succession that initiates after agricultural cropland was abandoned.
In general, the vegetation changes happen quite fast. However, in some cases it may take
almost as long as primary succession. The extent of change that the disturbance causes
depends on the intensity of the disturbance (Mueller-Dombois & Ellenberg 1974, Barbour et
al. 1987, Burrows 1990, Tainton 1999, Gurevitch et al. 2002).
Autogenic succession. Autogenic succession is driven by factors resulting from the
community or its constituent organisms (biotic forces). Interactions include factors such as
competition, shade generation and soil modification by plants (‘internal’ forces). “Third
party” effects refer to a plant or animal species or microorganism that change the success
of establishment of two species. In the presence of the third party the second species will
be more successful in colonising (Glenn-Lewin et al. 1992).
Allogenic succession: This refers to vegetation change due to environmental conditions
(‘external’ forces). An example of this is long-term vegetation response to climate. GlennLewin and Van der Maarel (1992) suggest that even though it might be possible to label
individual processes as auto- or allogenic, it is misleading and not useful to label an entire
successional pathway as either.
16
Progressive succession: This refers to species enrichment related to increased structural
complexity and biomass. This often leads to habitats that are progressively more mesic.
Regressive (retrogressive) succession: This is the loss of species and is related to
decreased structural complexity. This kind of succession leads to a simpler community with
fewer species which is either more hydric (wet) or xeric (dry).
It is important to distinguish between succession and non-directional vegetation change.
Phenological changes as well as year-to-year or long-term environmental variations (fluctuations)
are two other styles of vegetation change (Burrows 1990). Phenological changes (e.g. leaf
emergence, flowering, fruiting, leaf-shedding) in plants are correlated with the seasons and do not
generally result in changes in plant populations. Environmental variation such as those resulting
from climatic variation cause changes in seed production, seedling establishment and survival, or in
gross productivity or reproduction by mature plants. These changes are called fluctuations.
2.3.4
Documenting succession
Vegetation change can be investigated through various ways including studies on the same area
and side-by-side comparisons. The first type of study is more reliable. Studies on the same area
are based on permanent plots, containing marked individuals, exclosure studies, aerial photographs
taken at different times, historical records and evidence of change in populations (Mueller-Dombois
& Ellenberg 1974, Burrows 1990). However, few accurate, long-term records, in numerical data
form, exist.
2.3.5
Modelling and succession
Modelling expresses vegetation dynamics by means of symbolic logic and mathematics. Models
simplify the process, although current models can be relatively complex. The use and importance of
modelling is increasing because of improved technology and are useful for ecological forecasting
and conservation and management. Although models exhibit properties of generality, precision or
reality they never exhibit all three simultaneously (Glenn-Lewin & Van der Maarel 1992). The main
problem in modelling is the validation of the model. Models that include spatial variation and the
nature of changes over time are needed for consistent prediction of vegetation dynamics. The
following are examples of successional models:
Analytical models are simple theoretical and explanatory expressions based on principles
resulting from ecosystem observations;
Statistical models are stochastic expressions where the parameters are probabilities of
events and are useful for probabilistic predictions of vegetation dynamics and
successional events;
17
Lottery models are a form of statistical model and are used for prediction of succession;
Simulation models are real and precise, but not general. They can be used for prediction
and sensitivity analysis and attempt to duplicate the true behaviour of phenomena (GlennLewin & Van der Maarel 1992).
2.3.6
Vegetation dynamics and plant community management
Vegetation dynamics and management are interconnected and understanding the processes
involved in vegetation change, is vital for proper management. In wildlife management large areas
of land are managed to maintain a diversity of vegetation types to favour a diversity of animal
populations. Succession and climax are therefore two concepts often used by wildlife managers.
2.3.7
Implications of vegetation change for range or veld management in arid and semiarid rangelands
Rangeland management is organised around models as to how ecosystems function. A brief
discussion on some models for research and management on rangelands follows.
The range succession model
This model is also called the directional model (Milton & Hoffman 1994) and is derived from the
Clementsian ideas of plant ecology and suggests that a given rangeland has a stable state (climax)
in the absence of grazing. Succession towards the climax is a steady process with grazing pressure
causing changes, retrogressive to the successional tendency. The grazing pressure therefore
produces an equilibrium in the vegetation at a set stocking density. All possible vegetation states
can be assorted on a single continuum which ranges from heavily grazed vegetation in an early
successional, poor condition to ungrazed, climax, vegetation in an excellent condition. The aim of
management is to choose the correct stocking density that establishes a long-term balance
between the grazing pressure and the successional tendency. The model can incorporate rainfall
by assuming that drought affects vegetation in a similar way to grazing. Management should
therefore respond to drought by reducing grazing pressure because the joint pressure of drought
and grazing should vary as little as possible (Westoby et al. 1989a).
However, evidence reveals that this model’s assumptions are not appropriate in all cases. The
following mechanisms have been identified in rangelands that conflict with model predictions
(Westoby et al. 1989a, 1989b):
Demographic inertia - some plant communities only establish after a rare event, but after
this event the population may persist for long periods.
18
Grazing catastrophe - plant abundance may change discontinuously and irreversibly in
response to changes in stocking density.
Priority in competition - mature plants have a competitive advantage above the seedlings of
other species.
Fire positive feedback - some vegetation types promote fire and are also promoted by fire.
Soil change – a change in soil condition due to vegetation change may be irreversible.
In spite of all the criticism to the range succession model it is still in use in many rangelands. Some
of the limitations of this approach are as follow (Friedel 1991):
Climax is not always the most desirable condition;
Pristine conditions for a site may not be the actual climax;
No allowance for exotic species is made and
It is not well studied in woodland and forests.
Because of the limitations of the range succession model various attempts have been made to
broaden the theoretical basis of the model. In contrast with the Clementsian view, current ecological
theories suggest alternative stable states, discontinuous and irreversible transitions, event-driven
systems, non-equilibrium dynamics and stochastic effects in succession. Limitations of the range
succession model are most obvious in arid and semi-arid rangelands, where rare events are
important and where effects of grazing and intrinsic vegetation change operate irregularly. The
state-and-transition model, discussed next, copes with these features (Westoby et al. 1989b, Ward
2006).
The state-and-transition model
A set of ‘states’ of vegetation and a set of ‘transitions’, triggered by natural events or management
actions, between the states may in many cases describe rangeland dynamics (Westoby et al.
1989a, 1989b, Laycock 1991). Transitions may occur very quickly and the system does not come to
rest halfway through a transition. Transitions are also often referred to by the concept of thresholds.
The threshold is the boundary in space and time between two states (such as grassland and shrubinvaded grassland), and the initial shift across the boundary to a new domain is not reversible on a
practical time scale without considerable involvement by the range manager (Friedel 1991).
To develop a state-and-transition model the information on rangelands should be stated in the
following form (Westoby et al. 1989a, 1989b):
A catalogue of potential alternative states of the system;
A catalogue of potential transitions from one state to another. Information on the conditions
inducing transitions (climatic conditions together with grazing or fire) for each entry;
19
The above entries should be expressed as opportunities, i.e. climatic conditions under
which management, fire and grazing can produce a favourable transition, or hazards, i.e.
climatic conditions with heavy grazing which can produce unfavourable conditions.
The state-and-transition model is a stochastic model and in contrast to the range succession model,
aims to foresee the opportunities and hazards and consequently to seize the opportunities and to
evade the hazards as far as possible. This model emphasises the research on estimating the
probabilities of the climatic conditions relevant to the particular transitions and thus the emphasis is
on timing and flexibility. This model provides a practical way of organising information for
management and incorporates cyclic and successional processes as well as stochastic reactions of
vegetation to climatic or biotic disturbances.
In studies conducted in the Karoo where the state-and-transition model was applied the following
conclusions were made (Milton & Hoffman 1994):
There were five constraints on passive transitions between vegetative states – competition,
seed availability, microsites, soil properties and keystone processes;
Knowledge on the effects of the size of an area on its prediction for recovery is lacking;
The model can be improved by adding a temporal dimension to passive and active
transitions and
The economics of actively managing various transitions needs to be examined.
The state-and-transition model therefore forecasts which vegetation states can be manipulated by
livestock withdrawal and which can be changed by active management, and it can be used to guide
management decisions for the conservation of biodiversity and wildlife management in arid and
semi-arid environments (Milton & Hoffman 1994).
Non-equilibrium models of grazing systems
Equilibrium is reached between animal populations and forage resources under constant weather
conditions. Disequilibrium is established when climatic variability disturbs the system. Nonequilibrium happens when the population dynamics are disconnected from the resources not
associated with main factors (such as productive dry season grazing) that determine survival of the
animal population over the season of plant dormancy (Richardson et al. 2005). Persistent nonequilibrium, as explained by Briske et al. 2003, is similar to this. The other two types of nonequilibrium are presented by threshold and state-and-transition models. Both these represent
changes over time in vegetation composition. The state-and-transition model was designed for
rangeland systems characterised by event-driven vegetation dynamics.
20
The standard successional models cannot be used to understand the patterns in vegetation
changes in rangelands in disequilibrium. These models imply that plant and animal populations
fluctuate in response to natural oscillations in abiotic factors (for example rainfall seasonality or
quantity), or biotic factors such as facilitation and competition. Most of these models suggest that
herbivory has less impact on the composition of the vegetation than climatic conditions or plant
interactions (Milton & Hoffman 1994). In non-equilibrium grazing systems the physical conditions
supporting plant growth fluctuate widely and the consumption by animals does not control plant
biomass because the same physical factors controlling plant population growth control the animal
population. Grazing systems in equilibrium, on the other hand, suggest that consumption by
herbivores controls plant growth, the food availability regulates growth of herbivores and that the
physical conditions are relatively unvarying. Given the climatic patterns in arid and semi-arid South
Africa, non-equilibrium, event-driven grazing systems may occur. The productivity of arid
rangelands may be unstable in the short-term but resilient in long term (Behnke & Schoones 1993,
Illius & O’Connor 1998, Ward 2006).
The simplified model, as explained by Richardson et al. 2005, acts as an equilibrium model when
soil moisture is consistent, however, when vegetation responds to differences in rainfall between
years, the model imitates a system at disequilibrium. Arid rangeland systems exhibits complex
dynamics and neither the equilibrium nor non-equilibrium theories can propose this, however, their
standard model imitates such a system.
Cyclic models
In cyclic models species a is replaced with species b, and then later species b will again be
replaced by species a. Shrub-dominated communities often display cyclic succession as indicated
in a study done, on open areas within desert scrub in Texas, by Yeaton (1978 in Barbour et al.
1987). Cyclic succession also occurs in the Succulent Karoo bearing in mind the short turn-over
rates (Yeaton & Esler 1990, Jürgens et al. 1999).
Competitive hierarchy model
In this model of Horn (1981 in Glenn-Lewin et al. 1992), plants occurring later in succession are
increasingly dominant by virtue of their competitive success above early successional species.
However, the late successional species may invade the earlier stages of succession. The outcome
of competition among the species determines the replacement patterns. In a changing environment,
the competitive relationships of species change and the result of succession by these specific
mechanisms cannot be predicted. The competitive hierarchy model can be seen as the primary-
21
secondary continuum with non-invasible initial floristics as one extreme and the other extreme is the
initial composition with few species that are quickly replaced (Glenn-Lewin et al. 1992).
Vital attributes model
Succession requires understanding of life histories of species and therefore the vital attributes
model is used to model succession. This model is based upon a small number of vital life traits,
such as propagule persistence, dispersal, age at first reproduction and longevity or life span. Each
life history trait is classified into a few elements. This results into a set of species with certain
dynamic properties that come into action at specific times or conditions after a perturbation. This
model is useful in natural area management (Glenn-Lewin et al. 1992).
2.3.8
Sustainability and productivity modelling
Within-year management decisions on the production of milk and meat are evaluated through a
short-term mechanistic model (Richardson & Hahn 2007) and this model is also used to develop
equation-sets and rules for long-term models. Long-term models are then used to investigate the
effects of different strategies on the sustainability of the ecosystem over many years. Factors such
as the amount and distribution of rainfall, range condition and time of birth and death of animals
within the year are also recognised.
Therefore, the short-term model is used to study inter-relations between rainfall, stocking rate and
productivity. It shows that the timing of rainfall also influences birth and death rates. The long-term
model is used to study long-term effects of the stocking rate strategies. This model shows that
when moderately degraded rangeland is stocked with a recommended upper limit level, the land is
unable to recover to less degraded states over 100 years (Richardson et al. 2007).
2.3.9
Concluding remarks on vegetation dynamics
It is vital to understand vegetation dynamics and develop a predictive understanding of the structure
and function of the Succulent Karoo ecosystem in order to apply proper vegetation management
together with sustained animal production. Vegetation change may be a slow process in an arid
ecosystem due to the high inter-annual rainfall variation and therefore the variation in plant
abundance and presence (Wiegand & Milton 1996, Cowling et al. 1999a, Ward 2006). The means
of analysing the vegetation dynamics data include descriptive methods, multivariate analysis,
experimental studies and modelling. Models incorporating spatial and temporal variation (gradients
of changes over time) are ultimately needed for reliable prediction of vegetation dynamics (GlennLewin et al. 1992).
22
One needs to understand that arid and semi-arid environments frequently display complex nonequilibrium dynamics involving non-linear and stochastic event-driven behaviour in order to apply
effective vegetation management. Vegetation changes occur unpredictably, in the short-term, in
response to the inter-annual variation in rainfall, and episodically in the long-term (several decades)
in response to rare events as well as grazing pressure, changes in climate, altered disturbance
regimes, or a combination of these factors. This complicates the complete understanding of longterm dynamics, because it is difficult to observe rare events. Long-term ecological monitoring is
required to study the interaction between the rainfall, geology and ecology in order to increase the
understanding of long-term dynamics in arid areas (Wiegand & Jeltsch 2000, Ward 2006).
No technology can yet reverse the extreme damage of degradation in arid and semi-arid
ecosystems, and therefore long-term ecological monitoring integrated with other fields such as
socio-economics and social and ethical issues must be used to maintain options for future
generations (Wiegand & Jeltsch 2000).
2.4.
Veld management
2.4.1
Introduction
The key component of managing wildlife populations in dynamic systems is correct habitat
management (Behnke & Scoones 1993, Bothma et al. 2004). Veld management is defined as the
management of natural vegetation for specific objectives related to different forms of land use. A
comprehensive assessment of the veld condition is an absolute necessity for a successful veld
management program. A generally accepted principle is that as the area for wildlife decreases,
management must become more intensive (Trollope 1990).
The term “veld condition” refers to the condition of the vegetation in relation to several functional
characteristics. These characteristics include the production of sustained forage and the veld’s
resistance to soil erosion. The concept of veld condition is valuable to evaluate the present
condition of the rangeland and for devising veld management programmes such as the stocking
density, rotational grazing, rotational resting and veld burning (Trollope et al. 1989).
2.4.2
Carrying capacity and succession
Rangeland management has adapted plant succession theory into grazing systems. In general, it is
believed that grazing pushes the successional sequence back to a sub-climax stage. It is therefore
important to balance the grazing pressures with the regenerative powers of plants. The carrying
23
capacity concept aims to set the stocking density at the level where this balance is maintained. In
practice, managers use indicator species which are sensitive to grazing, to observe the extent to
which grazing has altered and is altering the climax vegetation. This approach therefore has the
potential to act as a warning of range deterioration. The biggest shortcoming of the approach is that
it does not incorporate non-equilibrium dynamics (see section 2.3.7 above).
The idea of carrying capacity was at first developed for domestic grazers and did not make
provision for the broad range of diets found in wild African herbivores. However, methods have
been developed that deal with plant resource variation and distinguishes between grazing and
browsing. By separating these components in the wildlife diet for stocking density calculation, the
diversity in the vegetation resources is optimally utilized (Bothma et al. 2004).
2.4.3
Ecological carrying capacity versus economic carrying capacity
Wildlife managers distinguish between ecological and economical carrying capacity (Figure 2.3).
Where wildlife occurs at a high density animals are often not in a good condition and under these
circumstances the vegetation will often also not be in a good state. An improved vegetation state
and healthier animals will be obtained when fewer animals are maintained. This can be achieved
by hunting (wild animals) or culling (domestic stock and wildlife). The point of maximum sustained
yield lies half way to two thirds of the stocking density at ecological carrying capacity and is termed
economic carrying capacity (Figure 2.3). As the population of animals grows beyond the economic
carrying capacity, the off-take rate starts to fall and returns to zero.
Figure 2.3
The relationship between plant and animal populations in a grazing system
(Behnke & Scoones 1993).
24
2.4.4
Veld condition assessment
Veld condition assessments make comparisons between plant communities possible and provide a
way to (a) quantify and (b) observe spatial and temporal changes within a specific vegetation type.
The three main objectives for assessing veld condition are:
Veld condition evaluation relative to its potential in that ecological zone;
Evaluation of current management effects on veld condition and monitoring changes over
time and
Classifying and quantifying the different vegetation types (Tainton 1999).
Very little formalised research was conducted on methods of assessing veld condition before the
early 1970s in southern Africa, but currently a range of techniques are available.
Southern African grasslands’ range condition assessments are based on the estimation of
proportional species composition. The wheel-point apparatus and the nearest plant method or
modifications thereof are used for estimations of species composition. The species composition data
are manipulated in various ways to fulfil the objectives of the grazing capacity determination and the
monitoring of a range condition index (Hurt & Bosch 1991).
Thus, various plant survey methods can be used for the gathering of vegetation data. Vorster (1982)
did a thousand point survey with the chain method, and recorded all basal, crown and canopy spread
strikes in his study to develop the ecological index method. Mentis (1981) evaluated the wheel-point
and step-point methods of veld condition assessment. He concluded that the step-point method is
used in preference to the wheel-point method, although there may be exceptions, because it saves in
equipment and manpower. However, the step-point method does not provide an estimate of basal
cover and should rather not be used in bushy veld or uneven terrain. If an estimate of basal cover is
required, a modified wheel-point apparatus may be used.
Methods for veld condition assessment can either be based on agronomic principles or on ecological
principles. Humphrey (1949, 1962) in Tainton (1999) stated that a veld condition assessment should
not be restrained by ecological concepts, and that the maximum forage production for the livestock
type being grazed should be the only criterion used to estimate the veld condition.
Methods based on ecological principles score veld condition according to the response of the
vegetation to biotic and abiotic environmental impacts. The frequency and intensity of defoliation
(such as grazing and fire) are major environmental variables and it is assumed that the defoliation
regime can be designed to change the vegetation state to that most suited to the management
25
objectives. It is also assumed that soil and climatic factors, specifically rainfall, influence the veld
condition (Tainton 1999).
Weighted palatability composition method (WPCM)
The weighted palatability composition method (WPCM) is an example of a method based on
agronomic principles and assigns palatable ratings to species. For classifying grassland species
the following classes were described: Class I – Highly palatable, Class II – Intermediate, and Class
III – Unpalatable (Tainton, 1999).
Ecological index method
The ecological index method (EIM) was developed by Vorster (1982) for veld condition assessment
in the Karoo areas. It was a refinement of the method used in the Karoo region by Van den Berg
and Roux (1974 in Vorster 1982). The technique is based on the principle that veld in a certain
topographical unit, in a homogeneous area, is compared to a veld benchmark on a similar
topographical unit in the same area. A veld benchmark for a topographical unit reflects the potential
botanical composition and cover for that unit. It is, however, difficult to find benchmark sites in the
Karoo, and the “best” site in respect of botanical composition and cover is often used to present the
veld benchmark (Vorster 1982).
The ecological index method classifies plant species into different ecological groups viz.
decreasers, increasers and invaders (Vorster 1982):
i.
Decreasers: Species that are dominant in veld in excellent condition and that
decrease in number as the veld is under- or overutilised. The climax grass species
will be classified in this group.
ii.
Increasers 1: Species that occur naturally in veld, but increase when veld is
selectively utilised or underutilised.
iii.
Increasers 2a: Species that are rare in veld in excellent condition but increase when
veld is moderately overgrazed during the long-term. These species usually increase
as the Decreaser species decrease. The Karoo bushes and taller shrubs will belong
to this group, as well as sub-climax grass species.
iv.
Increasers 2b: These species are rare in veld in excellent condition but increase
when the veld is heavily overgrazed over the long-term. The species include
moderately hardy, less palatable Karoo bushes and taller shrubs and perennial
pioneer grasses.
v.
Increasers 2c: These species are rare in veld in excellent condition and increase
when veld is excessively overgrazed over the long-term. This group consists of the
26
rain-dependent annual grasses, ephemerals, hardy unpalatable Karoo bushes and
taller shrubs and the poisonous plant species.
vi.
Invaders: Plant species belonging to this group can be described as foreign to a
plant community and also increase quickly in number when the veld is in an agroecologically deprived state (Vorster 1982).
To calculate a range condition score a grazing value is assigned to each of the ecological groups
(Vorster 1982, Bothma et al. 2004) as follows:
i.
Decreasers = 10
ii.
Increasers 1 = 7
iii.
Increasers 2a = 4
iv.
Increasers 2b = 4
v.
Increasers 2c = 1
vi.
Invaders = 1
This weighting presents both an agro-ecological and an agronomic scale because of the close
relation between the ecological status and agronomic value of the species (Taiton 1999).
The EIM differs from the other methods because the ecological group contribution is expressed in
terms of actual cover and not relative cover or nearest plant data whereas most other veld condition
assessment techniques use botanical composition and cover as two separate indicators. An
advantage is that fewer calculations need to be done (Vorster 1982).
If grazing capacity norms are related to veld condition it may be advantageous to use canopy
spread in the calculation rather than basal cover. If for example two identical sites were compared
where the one has undergone severe grazing and the other not, the veld condition index value of
the severely grazed site would be lower when using canopy spread. There may, however, be only a
small difference between the relative botanical composition (Vorster 1982).
Problems can occur with the classification of a species into the correct ecological group in the
absence of sufficient quantitative data. One of the important factors when classifying a plant
species into a ecological group is the region of occurrence. Through the experience of specialists,
such as pasture scientists, this problem may be overcome. The use of other quantitative techniques
may also be of help. Furthermore, the benchmark is prone to dynamic changes, due to short-term
seasonal rainfall fluctuations, which is a problem. It is therefore necessary to re-characterise such
benchmarks every five to ten years. If the benchmark has progressed new values are taken. Veld
that is not in an excellent condition is especially affected by this problem (Vorster 1982).
27
Key species method (KSM)
This method was developed by Mentis (1983 cited in Tainton 1999) because not all species in the
grassland show the typical Decreaser/Increaser response to utilisation intensity. He stated that
only species that respond sensitively to the grazing gradient should be used to determine the veld
condition. Individual or groups of species that react similarly to a specific grazing management
treatment represent key species (Tainton 1999). The previous grazing history of a certain sample
site is reflected by the key species method (Hurt & Bosch 1991).
Weighted key species method (WKSM)
This method by Heard et al. (1986) in Hurt & Bosch (1991) and Tainton (1999) is a modified
approach of the key species method. It is used to derive a condition index from weighted key
species abundances. The final score gives an exact indication of the sample site position along
the grazing gradient (Hurt & Bosch 1991, Tainton 1999). Thus, the method monitors temporal
changes in species composition (Hurt & Bosch 1991).
Degradation gradient method (DGM)
This is another modification of the key species method (Hurt & Bosch 1991, Tainton 1999). It was
developed in the climatic-climax grasslands using multivariate procedures. The vegetation
condition is quantified along a degradation gradient, thus a model describing long-term vegetation
and habitat changes from under-utilised to severely over-utilised rangeland. Establishment of a
degradation gradient for each ecological zone is vital for interpretation of the condition
assessment. Data on species composition are collected, from veld in various stages of
degradation, in each ecological unit. These data are obtained from long-term grazing trials,
obvious variations in the pastoral impact on vegetation, and species composition sampling at
different distances from well established points of animal concentrations (example watering
points) (Hurt & Bosch 1991, Tainton 1999).
The gradients are described in terms of (i) floristic composition and (ii) soil factors. The gradient
is subdivided into five classes:
a) Under-utilised;
b) Under-grazed;
c) Moderately grazed;
d) Moderately to severely degraded and
e) Severely degraded (Tainton 1999).
28
This approach does not include a single benchmark for a given area against which a particular
sample of veld can be rated. By applying the degradation model the sample site position can be
quantified on the degradation gradient and thereby provides an index of its condition. Only the
species acting as significant indicators of grazing conditions are used (Tainton 1999). These
models are therefore used as basis for objective and quantitative condition assessments of new
sites. This is done by integration of the new sites into the old ordinations (Hurt & Bosch 1991).
Grazing index method (GIM)
This method is based on the ecological index method (EIM) and was proposed by Du Toit (1996)
for Karoo veld, and according to the author is a more direct evaluation of the veld grazing value
than the EIM. For this method the descending point method is used and a 200-point survey is
carried out to obtain the botanical species composition. Species abundance values are multiplied
by their Grazing Index Value (GIV). A combined grazing index value for the studied community is
then derived. The relationship between the grazing index method score and grazing capacity is
determined by comparison with a benchmark.
The grazing index method is basically similar to ecological index method, with the exception that
the Ecological Index Values (EIVs) of species are replaced by the Grazing Index Values (GIVs).
The grazing index method is believed to result in more reliable range condition scores and therefore
more accurate grazing capacity determinations than the ecological index method because the
Grazing Index Values of species take more properties of the species into consideration (Du Toit
1995, 2000). The following factors were subjectively scored for the Grazing Index Values:
The acceptable dry matter production;
Forage value of this dry matter during the growing season;
Forage value of this dry matter during the dormant season;
How easy the plant material can be grazed (e.g. presence of thorns);
The degree to which the species is perennial and
The apability of a species to defend the soil against erosion.
The parameters were selected to avoid bias as far as possible (Du Toit 1995, 2003).
2.4.5
Comparison of the ecological index method (EIM) and the degradation gradient
method (DGM)
The ecological index method and the degradation gradient method were developed with different
objectives in mind. The ecological index method is primarily a method the establish veld condition
and to use the veld condition index to estimate a grazing capacity. The degradation gradient
method aims at describing and understanding vegetation dynamics within a theoretical framework.
29
An objective range condition assessment technique, which can be used to monitor veld condition
must be sensitive to detect spatial and temporal changes. According to a study done by Hurt &
Bosch (1991), both the EIM and the DGM appeared to be relatively sensitive techniques.
However, the EIM uses all species to calculate a condition index, and includes a subjective
allocation of species into the decreaser and increaser categories. These two categories are
problematic especially in semi-arid areas where most species react strongly to other dynamic
forces such as moisture stress. Thus, grazing-induced changes may be concealed (Hurt & Bosch
1991).
For the DGM selected species are used for interpretation. According to Hurt and Bosch (1991)
The EIM does therefore not provide such a sensitive measure of change as the DGM and it is not
recommended to use this method for monitoring range trend. If it is necessary to determine the
grazing capacity it is important to include all the species with their different grazing values. Where
grazing-induced changes in the composition of the species are of importance, then only species
affected by grazing intensity should be included in the condition index calculations (Hurt & Bosch
1991).
The assessment of veld condition needs to be ecologically interpretable and needs to provide the
basis for the description of management strategies. In order to obtain the wanted ecological
interpretation, it is important to have information and knowledge on features such as species
responses to grazing, community dynamics in the studied biome, and vegetation and habitat
degradation relations. The DGM provides this knowledge whereas the EIM does not. The DGM
provides information on whether the degradation trend is reversible via normal rangeland
management practices, or if physical reclamation methods are needed to restore the land
productivity. Thus, the DGM predicts the recovery potential of vegetation degraded to various
extents. The EIM is not based on a gradient that can be associated with changes in habitat
conditions, and does not identify multiple benchmarks. The DGM has the advantage of placing a
sample site objectively along a degradation gradient. The DGM also tests the appropriateness of
the degradation model for the condition assessment by using residual analysis. The objective
selection of key species and the relatively homogenous vegetation areas on which the DGM is
based, guarantees that ecotypical variation is reduced within species. The EIM principally uses
subjective species classification; species are categorised as decreasers and increasers and thus
are subjected to errors during the condition index calculations (Hurt & Bosch 1991).
To develop gradients, large numbers of vegetation samples are needed. The DGM could be
criticised as being time consuming and cost-inefficient, but Hurt and Bosch (1991) do not see this
as a problem. Throughout the grassland biome, many range assessments have been conducted
and sufficient data for gradient construction should be available. The same arguments do
30
however, not apply to the Succulent Karoo. Furthermore, “marker sites” must be included in the
database for objective identification of a grazing gradient (Hurt & Bosch 1991).
2.4.6
Concluding remarks on veld condition
Veld condition data are important in veld management, and when the trends in veld condition are
monitored over time these can be used to evaluate and modify veld management practices. It is
vital to monitor the veld in a game ranch or conservation area on a regular basis because these
form part of a dynamic ecosystem. Data from grass and shrub surveys will provide the basis for
adjusting the browser and grazer stocking density, the rotational resting program and the veldburning program (Trollope 1990).
The DGM provides a technique to test the degradation model’s appropriateness as the basis for
assessment and does not focus on carrying capacity but rather on the dynamics and theory. The
EIM and GIM, on the other hand, are not as sensitive in measuring changes as the DGM and are
not based on a gradient associated with changes in habitat conditions. Conversely, they are more
practical methods and focused to give you an answer regarding carrying capacity. Both the EIM
and GIM use all species to calculate veld condition (Hurt & Bosch 1991).
2.5.
Mechanisms of plant species survival
Plants growing in arid and unpredictable environments, such as the Succulent Karoo, face stress
from drought and heat. Rainfall in arid areas is unpredictable in time, space and amount and is a
strong selective force shaping the life-history patterns and affecting all the life cycle stages of
annuals. The soil water availability is a principal factor of long-term dynamics in arid regions. Two
main survival strategies of plants growing in such conditions are drought tolerance (succulence)
and drought avoidance or evasion (ephemerals). Drought evasion is a strategy common among
annual species (short-lived species). They complete their life cycle in one year and their root and
shoot systems die after seed production. Annual plants are divided into growing plants and
dormant seeds, where the dormant percentage is the far greater of the two. Succulence is mainly
displayed by perennial species (Le Roux & Van Rooyen 1999, Van Rooyen 1999, Ward 2006).
2.5.1
Life form classification
The life form classification of Raunkiaer (1934 in Mueller-Dombois & Ellenberg 1974) was
developed to show the relationship between plant form and climate. Raunkiaer believed that the
relationship between plant form and climate could best be reflected by the position of the
perennating bud. He classified plants into the following main groups:
31
Phanerophytes (P)
Chamaephytes (Ch)
Hemicryptophytes (H)
Lianes
Annuals (Therophytes)
Geophytes (Cryptophytes)
Raunkiaer’s classification system was applied in this study to establish whether there were
changes in the life form spectrum across the monitored years. Further detail and definitions of the
life forms are provided in the Chapter 3.
2.5.2
The annual species – evasion
A high percentage of plant species in Namaqualand are drought evading and display a large
degree of plasticity in their growth rate, size and phenology (Van Rooyen et al. 1990). The floristic
composition of annual vegetation in Namaqualand is determined by the interaction between
temperature, and the timing and intensity of rainfall. The duration of the rainfall is also important;
since a soft rainfall shower is more effective than a cloudburst yielding the same amount of rain
(Milton et al. 1997, Le Roux & Van Rooyen 1999, Van Rooyen 1999, Wiegand & Jeltsch 2000,
Ward 2006). Annual species show a number of adaptations to accomplish their drought evading
behaviour.
Dormancy
Delayed seed germination is an evolutionary stable strategy in short-lived but not in long-lived
plants in environments that are variable, such as in the Succulent Karoo. The abundance of
dormant seeds in the soil is inversely related to the dominant plant species’ life expectancy.
Dormancy prevents germination in unsuitable habitat conditions where establishment may not
take place. Three types of seed dormancy are described namely (Fenner & Thompson 2005):
Innate dormancy:
Seeds that are innately (primary) dormant are incapable of
germination directly after dispersal even if conditions are suitable for growth.
Enforced dormancy: This happens when the seed is deprived of its requirements for
germination (absence of sufficient moisture, light or temperature). Ecologically, it is useful
to identify factors in the environment preventing germination in situ at any period
(Murdoch & Ellis 2000).
Induced dormancy: Innate dormancy does not occur in many species’ newly dispersed
seeds. If they fail to meet suitable conditions for germination however, they attain an
induced (secondary) dormancy. It is an acquired condition of inability to germinate
caused by some experience after ripening (Harper 1977).
32
Annual and pauciennial succulents show staggered seed germination whereas germination of
perennial succulents seldom shows innate seed dormancy (Milton et al. 1997). Increased seed
dormancy occurs in increasingly unpredictable environments (greater seed carryover from year to
year takes place) (Van Rooyen 1999). Dormancy is an adaptation to prevent seeds from
responding to unpredictable rainfall in the dry season that do not supply the seeds with enough
moisture for establishment and growth (Baskin & Baskin 1989, Fenner & Thompson 2005).
The Succulent Karoo seed banks show a high degree of spatial heterogeneity. The seed bank
size varies over an order of magnitude on a geographical scale. Most of the annual species in
Namaqualand have persistent seed banks that are large when compared to the annual seed
additions and losses. Seed banks are important for annual plants because they may produce an
age structure in the adult population (Van Rooyen 1999). Large seed banks are expected in
frequently disturbed or very arid sites where annuals or pauciennials predominate. This general
pattern is confirmed by the seed-bank dynamics of Succulent Karoo plant assemblages. Largeseeded, non-succulent Karoo shrubs with long life spans do not maintain dormant seed banks
(Milton et al. 1997).
Polymorphism
Polymorphism occurs when developmentally or morphologically different seeds differ in innate
dormancy. These seeds are produced on the same or on different plants of a species (Murdoch
& Ellis 2000). Seeds from the same plant can vary in size, seed coat anatomy, morphology or
mechanism and timing of release. This influences the dispersal, and the germination behaviour
and growth (Esler 1999). Polymorphism is an adaptation increasing the survival chances of plants
in unpredictable environments (disturbed habitats and arid) environments, such as the Karoo (van
Rooyen 1999). Polymorphic seeds occur in many Succulent Karoo species (Esler 1999). It
enables adaptation to two strategies: an escape in space and an escape in time (van Rooyen
1999).
Polymorphism for germination requirements has been observed for several ephemerals in
Namaqualand. Some seeds from the annual Mesembryanthemaceae species (vygies) germinate
very quickly while others from the same seed capsule take a longer time to germinate. Thus, it is
suggested that the seed populations consist out of fast-germinating seeds, making maximum use
of the short growing period, and of slowly germinating seeds that avoid the drought risk (Esler
1999).
33
Flowering
Desert annuals are able to flower over a wide seasonal range in photoperiod and temperature if
efficient moisture is available, due to the facultative nature of both photo-induction and thermoinduction of flowering. In an unpredictable growing season environment, this flexibility enhances the
probability of successful reproduction. Thus, ephemerals are able to flower and reproduce
irrespective of whether the rainfall season starts in the autumn or winter. During early autumn rains,
plants germinate and flower initiation occurs only during the decreased temperatures during the
winter, and if favourable conditions occur during the rest of the season, the plants become large
and produce many flowers in the spring after the temperatures have increased. If rain starts in the
mid-winter, however, the temperatures are low and the juvenile phase is shortened, resulting in
early flowering. Water stress also affects the lifespan and flowering period of the ephemerals (Van
Rooyen et al. 1991 & 1992, Steyn et al. 1996a&b).
In summary, the annual plant species complete their life cycles in the short periods when climatic
conditions are favourable. They germinate and grow during the wet winter and flower and set seed
during the spring. They vanish and survive the dry season as seeds. The annual species in
Namaqualand have adaptations to counteract the year-to-year variability in their environmental
conditions, such as the production of seed banks. Most of these seeds are dormant and this
prevents the instantaneous germination of all the seeds. Different species are favoured under
different environmental conditions in different years, depending on the first rainfall (Le Roux & Van
Rooyen 1999).
2.5.3
The succulent species – tolerance
Succulents utilise the water they stored in their leaves and stems during times of drought. They
have evolved various strategies in order to maintain optimal moisture conditions. These include a
thick cuticle and few stomata to prevent excess water loss. Some succulents use the CAM
(Crassulacean Acid Metabolism) photosynthetic pathway where carbon dioxide is taken in during
the cooler night time, therefore preventing water loss through open stomata (Le Roux & Van
Rooyen 1999).
The vygies, a dominant succulent group, have a highly specialised dispersal device, associated
with rain. Precipitation causes dispersal to take place and water is available for germination. The
seeds are enclosed in capsules that open up in moist conditions, allowing the dispersal of the
seeds by raindrops, and close in dry conditions. In more primitive species, the seeds are ejected by
a splash-cup action; however, in the more evolved species the seeds do no not lie fully exposed
and are covered by an elastic membrane at the top of the locule in the capsule. Only a few seeds
34
are ejected at a time, but over a greater distance. Thus, this adaptation enhances dispersal in
space, but inhibits it in time (Le Roux & Van Rooyen 1999).
Some plants do not grow higher than the soil level, with only one or a few leaves per individual
(such as the Lithops species and other windowplants, family Mesembryanthemaceae). These
plants withdraw the water from the exposed leaves into the subsequent year’s leaves, sheltered
underground, when drought conditions dominate. Old dry leaves protect the following year’s
leaves and also reflect the sun. Some plant species of Namaqualand maximise their solar energy
balance during the cooler winter months (when the solar energy is low and the day length short)
by orientating their leaves northwards. Windowplants, withdrawn underground, leave only a
‘window’ on the surface of the soil for the intake of sunlight. The leaf ‘windows’ are nonpigmented zones that allow deep penetration of the sunlight to chlorophyllous tissue. Another
method of maximising radiation during the winter season is found on large leaves of geophytes
lying on the ground (Cowling et al. 1999a, Le Roux & Van Rooyen 1999).
Succulent-dominated communities in Namaqualand are exceptional in the sense that most of the
perennials are relatively short-lived shrubs. In Namaqualand, plants die and are replaced
constantly, resulting in significant compositional change of the perennial component over
decades, thus, the age structure of the succulents are uneven (Cowling et al. 1999a).
Non-succulent dwarf shrubs have small leaves to limit transpiration, or large leaves which are
shed during the dry season. Some plant species have no leaves and rather green stems for
photosynthesis and this reduces transpiration. Geophytes are both evasive and tolerant because
they survive the dry period underneath the soil surface as bulbs, corms, rhizomes or tubers.
2.5.4
Concluding remarks on plant life history strategies
Knowledge of life history traits of plant species is essential to understanding plant responses to
climate and disturbance regimes. Without this knowledge vegetation dynamics in arid
environments cannot be fully understood.
It is therefore important to appreciate the significance of long-term studies and the role that longterm monitoring fulfils in ecological studies, especially in arid regions. Because the area of study
is a conservation area, sound veld management practices are crucial. Therefore veld condition
assessments are needed to assess the impact of possible overutilisation by mammalian
herbivores on vegetation and to provide recommendations on the carrying capacity for the
Goegap Nature Reserve.
35
CHAPTER 3
STUDY AREA
3.1
Introduction
Namaqualand is a semi-desert of unique plant wealth situated in the Succulent Karoo Biome in the
northwestern corner of South Africa (Figure 3.1). Synonymous with impressive wild flower displays
of annual plant species in the spring season, Namaqualand exhibits many features that are not
shared by the rest of the semi-deserts of the world. It is one of only two entirely arid areas to
classify as a global hotspot of biodiversity. This hotspot, together with the Horn of Africa
(www.conservation.org), hosts the world’s richest semi-desert flora. Namaqualand contains about
3 500 plant species (Cowling et al. 1999a, Le Roux & Van Rooyen 1999, Desmet 2007).
Namaqualand
Goegap Nature Reserve
Figure 3.1 Map of the Succulent Karoo Biome (shaded in green) (Mucina & Rutherford 2006).
36
Human population growth, habitat degradation and other features of global climate change are
threatening the existence of desert ecosystems. Namaqualand has been compared to numerous
other deserts throughout the world because of its high plant diversity occurring in its desert climate.
Many of these comparative studies, in e.g. Esler and Rundel (1999), Esler et al. (1999) and
Whitford (1999), indicate that no other desert in the world has such high levels of endemism as
Namaqualand (Cowling et al. 1999a). The species richness of the Namaqualand flora exceeds the
number of species occurring in similar-sized areas of winter rainfall deserts in America, North Africa
and the Middle East.
Namaqualand differs from other winter rainfall deserts mainly in two ways (Cowling et al. 1999a):
(a) the higher predictability of rainfall between years and (b) the mild winter and early spring
temperatures. These factors allow growth of perennials and annuals to continue throughout winter
to reproductive maturity during late winter and early spring. Fog, usually occurring along the coast,
is a vital source of moisture in the Strandveld where the annual rainfall is below 100 mm. Hot,
desiccating bergwind conditions can occur throughout the year and may cause an abrupt end to
flowering when they occur in spring (Hilton-Taylor 1996, Desmet & Cowling 1999).
According to Mucina and Rutherford (2006) the Succulent Karoo is divided into six bioregions
namely the Richtersveld, Namaqualand Hardeveld, Namaqualand Sandveld, Namaqualand
Knersvlakte, Trans-escarpment Succulent Karoo and the Rainshadow Valley Karoo. Namaqualand
is divided into four geographical regions namely the Richtersveld, Sandveld, the hills and
mountains of the Kamiesberg Range (Namaqualand Hardeveld) and the Knersvlakte. Three of the
five centres of endemism in the Succulent Karoo Biome (Van Wyk & Smith 2001) also form part of
the Namaqualand geographical region (Le Roux & Van Rooyen 1999). They are the Gariep Centre
of Endemism, the Knersvlakte Centre of Endemism and the Hantam-Roggevled Centre of
Endemism (Van Wyk & Smith 2001). A total of 135 plant families and 724 genera have been
recorded in Namaqualand of which approximately 25% of this flora is endemic (Cowling et al.
1999a&b, Le Roux & Van Rooyen 1999, Desmet 2007). The diverse plant life occurring here is
dominated
mainly
by
low,
often
minute,
leaf-succulent
shrubs
including
the
families
Mesembryanthemaceae (vygies) Crassulaceae (stonecrops), Asteraceae and an enormous bulb
flora (Low & Rebelo 1998, Cowling et al. 1999a&b).
The conserved areas in Namaqualand are divided into three main nature reserves or national
parks. They are the (a) Richtersveld National Park (162 455 hectares), (b) Goegap Nature Reserve
(14 865 hectares) and (c) the Namaqua National Park which incorporates the 930 hectare Skilpad
Wildflower Reserve (more than 110 000 ha in total). Most people tend to take this desert area for
granted and although Namaqualand’s flower heritage has been abused for many years, nowadays
it has acquired much wider botanical recognition (Cowling et al. 1999b, Le Roux & Van Rooyen
1999).
37
3.2
Goegap Nature Reserve
The Goegap Nature Reserve is situated between 29° 34’ 24” S and 29° 43’ 24” S and 17° 54’ 40” E
and 18° 07’ 20 E” about 15 km east of Springbok, Northern Cape Province (Rösch 2001b) and
covers an area of approximately 15 000 ha (Figure 3.2).
According to Acocks’s (1988) classification the reserve straddles the Namaqualand Broken Veld
and the False Succulent Karoo whereas Low & Rebelo (1998) classify the reserve as being located
partly in the Upland Succulent Karoo and partly in the Bushmanland vegetation types. According to
Mucina et al. (2005) the reserve lies within the Namaqualand Blomveld and Namaqualand
Klipkoppe Shrubland vegetation types (Namaqualand Hardeveld Bioregion), with a small part in the
east lying in the Bushmanland Arid Grassland (Bushmanland Bioregion).
Figure 3.2 Map of Namaqualand indicating (by the blue arrow) the locality of the Goegap Nature
Reserve (travel.iafrica.com).
3.3.
Background
The Hester Malan Nature Reserve was established in 1966 (Le Roux 1984). In 1969 the reserve
was fenced and thus excluded the livestock that previously grazed freely in the reserve. In 1990,
38
bordering land was added to the reserve and it was declared as the Goegap Nature Reserve
(Rösch 2001b). At that stage the Goegap Nature Reserve comprised of two parts: the western
section, formerly known as the Hester Malan Nature Reserve which was approximately 7 000
hectares in size, and the eastern section, formerly known as the farm Goegap, about 8 000
hectares in size. Initially, the veld on the Goegap farm was in a much worse condition than the veld
on the Hester Malan section of the reserve and it was decided not to remove all the fences dividing
the two sections (Rösch 2003). The result of a field survey in 2000 (Rösch 2001a) showed that the
vegetation on the Goegap part of the reserve had recovered substantially, and that sustainable
grazing could be achieved. Therefore, in 2002 the fence dividing the two sections of the reserve
was finally removed.
3.4
Climate
The climate of the Goegap Nature Reserve can be described as warm and dry, with large
fluctuations in the daily and seasonal temperature (Table 3.1). The reserve occurs within a winter
rainfall region and receives soft, erratic and uncertain, though effective rainfall (Table 3.2). Rainfall
data were gained from the long-term climate and rainfall data of the reserve (Table 3.3) and the
South African Weather Service ([email protected]). The annual rainfall is relatively low
(varying between 100 and 350 mm) with the highest percentage of rainfall received mainly during
winter from April to September. More summer rainfall is received in the eastern side of the reserve
because it is situated in the transition zone between the winter and summer rainfall areas (Rösch
2003). Temperature extremes vary from about -10ºC in the winter, to 41ºC in the summer.
Table 3.1 The monthly maximum and minimum temperatures (in °C) of Springbok, Namaqualand,
from 1973 to 2007 (electronic data supplied by the South African Weather Bureau)
Month
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
MONTHLY MAX (°C)
Range
Lowest
Highest
29.7
26.9
32.0
30.0
28.3
32.2
28.8
26.2
31.5
25.1
21.6
27.7
20.8
18.6
24.3
17.4
14.3
21.0
17.1
14.9
20.7
17.9
14.2
20.7
21.1
16.5
25.4
24.1
19.3
26.6
26.3
22.6
30.5
28.1
25.3
31.2
Mean
MONTHLY MIN (°C)
Mean
Range
Lowest
Highest
16.1
13.5
18.4
17.0
14.6
20.6
16.5
13.3
19.0
14.0
11.6
16.8
10.9
8.10
13.8
8.40
6.50
11.1
7.70
5.40
10.3
7.60
5.40
11.4
9.50
7.40
14.0
11.3
8.20
15.8
12.8
9.20
16.0
14.5
12.2
16.8
39
Table 3.2 The mean monthly rainfall (in mm) of Springbok, Namaqualand, from 1973 to 2007
(electronic data supplied by the South African Weather Bureau)
MONTHLY RAINFALL (mm)
Mean
Range
Lowest
Highest
7.50
0.00
56.80
7.70
0.00
65.50
11.60
0.00
70.50
18.60
0.00
78.90
27.40
0.00
95.50
33.30
0.00
111.20
30.10
0.20
100.10
28.70
0.00
102.80
14.60
0.00
70.60
13.50
0.00
39.70
8.900
0.00
52.00
6.500
0.00
50.70
Month
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
Table 3.3 Coordinates (degrees, minutes and seconds) of six rain meters in the Goegap Nature
Reserve (data supplied by the Northern Cape Department of Environment and Nature
Conservation)
Number
1
3
5
6
8
9
3.5
Line Transect
Koperberg and T'ganagas Plains
Zebrawater Foothills
Bluemine Mountain
Jaleeg Plains
Bleshoek Plains
Goegap Plains
S
29 39 53.7
29 36 37.2
29 37 16.5
29 42 22.8
29 41 18.1
29 41 31.0
E
17 59 53.5
17 58 31.9
18 00 36.8
18 05 8.10
17 55 49.6
17 58 45.8
Wildlife
Although the Goegap Nature Reserve is situated in an arid region, it is home to 45 mammal
species, 25 reptile species, three amphibian species and 94 bird species. The dominant wildlife
includes the Hartmann’s mountain zebra (Equus zebra hartmannae), gemsbok (Oryx gazella),
springbok (Antidorcas marsupialis), klipspringer (Oreotragus oreotragus), duiker (Sylvicapra
grimmia) and steenbok (Raphicerus campestris) (Northern Cape Nature Conservation Services
undated).
40
3.6
Vegetation
Approximately 581 plant species have been recorded in the Goegap Nature Reserve (Northern
Cape Nature Conservation Services undated). For only a few weeks each year the flowers (mainly
the annual plant species) transform the veld into a flower paradise. Perennial plants are mainly
summer deciduous or evergreen dwarf shrubs of which many have succulent leaves for the
conservation of water during the drier periods.
According to Rösch (2001b) the vegetation of the Goegap Nature Reserve can be divided into two
major phytosociological units:
A.
The vegetation on the rocky hills and
B.
The vegetation on the plains.
The vegetation occurring predominantly on the rocky hills includes the following plant communities:
1)
Helichrysum obtusum dwarf open shrubland
2)
Searsia undulata tall sparse shrubland
a. Nenax namaquensis – Searsia undulata tall sparse shrubland
b. Diospyros ramulosa – Searsia undulata tall sparse shrubland
3)
Leipoldtia schultzei short open shrubland
c.
Dyerophytum africanum – Hermbstaedtia glauca – Leipoldtia schultzei short open
shrubland
d. Pteronia divaricata – Tetragonia microptera – Leipoldtia schultzei short open
shrubland
e. Ruschia species (HRSK 17) – Leipoldtia schultzei short open shrubland
f.
Eriocephalus microphyllus – Leipoldtia schultzei short open shrubland
g. Euphorbia decussata – Leipoldtia schultzei short open shrubland
h. Ruschia robusta – Leipoldtia schultzei short open shrubland
The vegetation dominating the plains of the reserve includes the following communities:
1)
Stipagrostis namaquensis short closed grassland
2)
Ruschia brevibracteata short sparse shrubland
3)
Stipagrostis obtusa short closed grassland
4)
Stipagrostis brevifolia short sparse shrubland
5)
Drosanthemum otzenianum low closed shrubland
6)
Psilocaulon junceum – Drosanthemum hispidum low sparse shrubland
7)
Mesembryanthemum guerichianum dwarf sparse shrubland
a. Galenia sarcophylla – Mesembryanthemum guerichianum dwarf sparse shrubland
b. Drosanthemum hispidum – Mesembryanthemum guerichianum dwarf sparse
shrubland
8)
Tripteris sinuata short open shrubland
a.
Galenia meziana – Tripteris sinuata short sparse shrubland
41
b.
Stipagrostis brevifolia –Tripteris sinuata short open shrubland
c.
Leipoldtia schultzei –Tripteris sinuata short open shrubland
d. Aptosimum spinescens – Tripteris sinuata short open shrubland
9)
Psilocaulon junceum – Zygophyllum retrofractum low sparse shrubland
10)
Psilocaulon junceum low sparse shrubland
3.7
Geology and soils
The reserve includes the distinctive koppies and sandy plains characteristic of Namaqualand
(Northern Cape Nature Conservation Services undated). The reserve’s geology consists mainly of
gneisses and granite of the Namaqualand Metamorphic Complex (Figures 3.3 & 3.4) covered with
early tertiary to more recent deposits of sands (Marais et al. 2001). The granite and gneiss are
approximately 1 100 million years old. The soil of the reserve includes red, deep soil as well as
land covered with exposed rock (Land Type Survey Staff 1987). The koppies generally consist of
granite boulders on the crests and midslopes, whereas the footslopes and valleys comprise the
Hutton soil type.
Figure 3.3
A simplified representation of the metamorphic zonation in western Namaqualand
(Robb et al. 1999).
42
The Goegap Nature Reserve includes four land types (Land Type Survey Staff 1987): Ae80, Ae85,
Ib127 and Ib129 (Figure 3.5). Map unit Ae indicates red, high base status soils deeper than 300
mm and dunes are absent. Map unit Ib refers to land covered 60 – 80% with rock, stones or
boulders. The land types are described as follow (Land Type Survey Staff 1987):
1) Ae80: granites and gneisses of the Okiep Group of the Namaqualand Metamorphic Complex.
The soil type dominating this land type is the Hutton soil type, and occurs specifically along the
footslopes and valleys (80% of the land type);
2) Ae85: gneissic granite of the Namaqualand Metamorphic Complex covered with early tertiary
to more recent deposits of sands. This land type includes the deep soil (more than 1 200 mm)
of the Hutton soil form;
3) Ib127: gneissic granite of the Namaqualand Metamorphic Complex. This land type is covered
67% with rock. Granite boulders dominate on the crests and midslopes whereas the footslopes
and valleys are dominated by Hutton soils;
4) Ib129: this land type (on the eastern side of the reserve) includes boulders of granite and
gneisses of the Okiep Group of the Namaqualand Metamorphic Complex. The reserve
boundary fence is situated at the base of these boulders.
Arid areas are usually characterised by shallow soils. The dominant soils are red and yellow
reflecting weathering in a well-drained, oxidizing environment. The soils occurring on the plains of
the reserve are generally deeper than the soils occurring on the ‘koppies’, which usually have a
slightly darker colour. The soil formation is dependent on the environmental conditions of the arid
area and includes factors such as climate, drainage, and age as well as biotic factors. The abiotic
environmental factors (such as strong wind, low rainfall and long periods of drought) as well as the
nature of the parent material are of more importance with regards to soil formation than the biotic
factors (such as trampling and the burrowing of animals) (Le Roux 1984, Watkeys 1999).
The soil at the base of the solid rock domes is more humus-rich than on other parts of the reserve
because water flows down the steep rocky sides and gathers at the base of the rocks. Thus,
shrubs occur here in higher densities because of the higher moisture level in the soil (Le Roux
1984).
43
Figure 3.4 Map indicating the geology of the Goegap Nature Reserve (Geological vector data was supplied by the Council or Geoscience, Pretoria) together
with the positions of the line transects.
44
Figure 3.5 Map indicating the land types of the Goegap Nature Reserve and the positions of the line transects.
45
3.8
Management units
Rösch (2001a) stated that the effective management of the Goegap Nature Reserve is of extreme
importance. Using various factors including plant communities and land types, management units
were identified (Rösch 2001b). These ten management units (Figure 3.6) form the basis for the
management and monitoring programs.
Figure 3.6 The management units identified on the Goegap Nature Reserve (Rösch 2001b).
46
3.9
The line transects
From 1974 two line transects (named the Zebrawater Foothills and Bluemine Mountain) were
established by the Department of Agriculture. These line transects were monitored and field data
recorded on a yearly basis, each time more or less at the end of August. In 1990 the number of
line transects was increased to seven (Figure 3.7), three on the old part of the nature reserve
(Hester Malan Nature Reserve part) and four on the new section (Goegap farm). Three of the five
new line transects (named the Goegap, Bleshoek and Jaleeg Plains) have been monitored since
1991, whereas the Koperberg and T’ganagas Plains line transects have been monitored only
since 1997. These five new line transects are currently also monitored on a yearly basis together
with the two older ones (Rösch 1997).
The management units represented by the line transects and a summary of the environmental
features of the seven line transects reported on in study are provided in Tables 3.4 and 3.5.
Table 3.4 The line transects in the different management units. The management units were
identified by Rösch (2001b)
Line transect
Management Unit
Bleshoek Plains
3
Bluemine Mountain
10
Goegap Plains
5
Jaleeg Plains
7
Koperberg Plains
2
T’ganagas Plains
4
Zebrawater Foothills
8/10
47
a.
b.
Figure 3.7 The Goegap Nature Reserve a) indicating the location of the long-term monitoring
transects
and
b)
the
transects
in
relation
48
to
the
topography
of
the
reserve.
Table 3.5 The altitude, land type, geology and soil of the seven line transects
Line transect
Altitude (m)
Land type
Geology
Soil
Main vegetation
communities
Galenia sarcophylla –
Mesembryanthemum
guerichianum dwarf sparse
BLESHOEK
PLAINS
903.5
Ae80
Nababeep gneisses
Sand, rubble and soil
Hutton soil
(coarse, sandy)
shrubland subcommunity
and the Psilocaulon junceum
– Zygophyllum retrofractum
low sparse shrubland
Searsia undulata tall sparse
BLUE MINE
MOUNTAIN
GOEGAP PLAINS
1080.6
941.0
Ib127
Ib127
Kweekfontein granite
(granite boulders on the
crest)
Nababeep gneiss
Hutton soils
Nababeep gneiss (No
rock cover)
Sand, rubble and soil
Hutton soils
(coarse, sandy)
shrubland and
Leipoldtia schultzei short
open shrubland
Tripteris sinuata short open
shrubland
Drosanthemum hispidum –
Mesembryanthemum
guerichianum dwarf sparse
JALEEG PLAINS
959.3
Ae85
Nababeep gneiss
Sand, rubble and soil
Hutton soil (deep shrubland subcommunity,
form, > 1 200
Psilocaulon junceum low
mm)
sparse shrubland and
Stipagrostis brevifolia short
sparse shrubland
Psilocaulon junceum –
Drosanthemum hispidum low
KOPERBERG
PLAINS
850.9
Ae80
Sand, rubble and soil
Hutton soil
(sandy, high in
salt
concentration)
sparse shrubland and
Galenia sarcophylla –
Mesembryanthemum
guerichianum dwarf sparse
shrubland subcommunity
Drosanthemum hispidum –
T’GANAGAS
PLAINS
950.9
Ae80
Nababeep gneiss
Sand, rubble and soil
Mesembryanthemum
Hutton soil
guerichianum dwarf sparse
shrubland subcommunity
Drosanthemum hispidum –
Mesembryanthemum
guerichianum dwarf sparse
ZEBRAWATER
FOOTHILLS
1075.8
Ae80/Ib127
Kweekfontein granite
(granite boulders on
crest)
Nababeep gneiss
shrubland subcommunity,
Hutton soils
Searsia undulata tall sparse
shrubland and
Leipoldtia schultzei short
open shrubland
49
CHAPTER 4
METHODS
4.1.
Field methodology
The field methodology involved the annual monitoring of line transects on the Goegap Nature
Reserve. Seven line transects (Table 4.1, Figures 4.1 – 4.7) were investigated in the reserve. The
Zebrawater Foothills and Bluemine Mountain line transects have been monitored for the longest
period. These line transects were established and have been monitored annually since 1974. Three
line transects (Goegap Plains, Bleshoek Plains and Jaleeg Plains) were established and monitored
since 1991 and two line transects (Koperberg Plains and T’ganagas Plains) monitored since 1997.
Table 4.1 Coordinates (degrees, minutes and seconds) of the starting and ending points of seven
line transects in the Goegap Nature Reserve
Line transects
Bleshoek Plains
Starting point
S
29 41 31.0
E
17 58 45.9
End point
S
29 41 06.3
E
17 58 21.7
Zebrawater Foothills
29 37 12.0
17 57 48.9
29 37 39.7
17 57 47.7
Koperberg Plains
29 40 34.1
17 58 25.0
29 40 58.7
17 57 59.9
Bluemine Mountain
29 37 54.0
18 00 33.1
29 37 25.7
18 00 23.4
Goegap Plains
29 40 57.8
18 01 08.1
29 41 28.5
18 00 56.5
T’ganagas Plains
29 40 41.1
18 00 03.5
29 40 15.2
17 59 42.0
Jaleeg Plains
29 41 12.6
18 05 22.8
29 41 39.1
18 05 44.7
These seven line transects have been surveyed annually at the end of August or beginning of
September. The vegetation surveys are conducted during this time of the year, the main flowering
period, because the annual species are present during spring time and because the species are more
easily identified then, than any other time of the year (Rösch 2003).
The descending point method (Roux 1963, Mentis 1981) with 1 000 points per survey was used to
determine the species composition and vegetation cover (Rösch 2003). Each line transect was one
kilometre (1 000 m) in length, and was marked at 100 m intervals with droppers. A 100 m rope,
marked at 1 m intervals, was spread between each pair of droppers and straightened with both ends
hooked to a dropper. The line was walked from the beginning to the second dropper and at each 1 m
interval, a thin rod was released and the species recorded if it qualified as a strike. When arriving
50
Figure 4.1
The Bleshoek Plains line transect in the Goegap Nature Reserve in the spring of
2006.
Figure 4.2
The Bluemine Mountain line transect in the Goegap Nature Reserve in the spring
of 2006.
51
Figure 4.3
The Goegap Plains line transect in the Goegap Nature Reserve in the spring of
2006.
Figure 4.4
The Jaleeg Plains line transect in the Goegap Nature Reserve in the spring of 2006
52
Figure 4.5
The Koperberg Plains line transect in the Goegap Nature Reserve in the spring of
2006.
Figure 4.6
The T’ganagas Plains line transect in the Goegap Nature Reserve in the spring of
2006.
53
Figure 4.7
The Zebrawater Foothills line transect in the Goegap Nature Reserve in the spring of
2006.
at the second dropper the rope was detached and moved to the next two droppers. This procedure
was repeated ten times at each line (Rösch 1997).
The descending point method included the following data recorded at each 1 m interval (Rösch
1997):
first strike – plant species first touched by the rod;
second strike – plant species growing beneath the first plant species and also touched by
the rod;
dead woody individuals – the rod touched dead woody plant material of a plant that was still
anchored;
seedlings – plant species still in seedling phase touched by the rod and
rocks or stones were noted for the line transects at Zebrawater Foothills and Bluemine
Mountain.
54
4.2.
Data analysis
4.2.1
Vegetation cover and diversity
The following were calculated for each line transect:
The species richness (S) or number of species recorded per transect was obtained with the
PC-ORD computer package (PC-ORD version 4, MjM Software Design, Gleneden Beach,
Oregon, USA).
Species evenness (E) was computed by means of the PC-ORD computer package using the
equation (McCune & Mefford 1999):
E
=
H/ln (S)
Where H
=
Shannon’s index of diversity.
ln (S)
=
natural logarithm of the number of species per transect.
Shannon’s index of diversity (H) was computed by means of the PC-ORD computer package
using the equation (McCune & Mefford 1999):
H
=
-∑(Pi*ln(Pi))
Where Pi
=
the importance probability of species i.
ln (Pi)
=
the natural logarithm of the importance probability of species i.
Simpson’s diversity index for infinite populations (D) was computed by means of the PC-ORD
computer package using the equation (McCune & Mefford 1999):
D
=
1 – sum (Pi*Pi)
where Pi refers to the importance probability in the element i.
This is the complement of the original Simpson’s diversity index.
The number of first strikes and seedlings was expressed as a percentage of the total number
of possible strikes (1 000). This value represented the vegetation cover.
The number of second strikes was likewise expressed as a percentage of the total number of
possible strikes (1 000).
The number of dead strikes was expressed as a percentage of the total number of possible
strikes (1 000).
4.2.2
Life forms
To obtain a measure of the functional diversity of the vegetation each recorded species was assigned
to a life form category according to the life form classification of Mueller-Dombois & Ellenberg (1974).
Only the categories relevant to this study are mentioned in the outline below:
Phanerophytes (P) – autotrophic, kormophytes, woody or herbaceous evergreen perennial
plants that grow taller than 50 cm, or whose shoots do not die back periodically to that height
limit:
Dwarf trees less than 2 m tall – Nanophanerophytes (N P scap).
Normal-sized shrubs (< 2 m) – Nanophanerophytes (N P caesp).
55
Chamaephytes (Ch) – Autotrophic, kormophytes, woody or herbaceous evergreen
perennial plants that remain perennially within 50 cm above ground surface or if they grow
taller than 50 cm, their shoots die back periodically to that height limit:
Woody (up to branch tips) dwarf shrubs, frutescent (Ch frut).
Semi-woody (woodiness restricted to base of shoot system) dwarf shrubs, suffrutescent
(Ch suff).
All herbaceous perennial forbs, grasses and ferns that do not grow taller than 1 m or die
back periodically to a shoot system that remains green at least 25 cm above ground
surface (Ch herb).
All succulents that grow up to 50 cm, except those that die back to a remnant portion at the
soil surface (hemicryptophytes) or within the soil (geophytes) (Ch succ):
Stem succulents (Ch st succ) and
Leaf succulents (Ch l succ).
Hemicryptophytes (H) – Perennial herbaceous plants with periodic shoot reduction to a
remnant shoot system that lies flat on the ground surface:
Caespitose hemicryptophytes (H caesp).
Reptant hemicryptophytes (creeping or matted) (H rept).
Rosette hemicryptophytes (H ros).
Lianas – Plants growing by supporting themselves on other plants, but that still germinate
on the ground and maintain contact with the soil.
Annuals (Therophytes) – Plants completing their whole life cycle in one year and whose
shoot and root system dies after seed production.
Geophytes (Cryptophytes) – Perennial herbaceous plants with periodic shoot reduction of
the entire shoot system to storage organs in the soil.
The total number of first strikes and seedlings of all the different life forms (i.e. perennials, annuals,
geophytes and lianas) encountered were also calculated as a percentage of the total number of
possible strikes. The frequency of the total number of these first strikes and seedlings was also
expressed as the percentage contribution made to the vegetation cover. The frequency of strikes
(%) of the annuals and all perennials combined was plotted versus the annual rainfall of the
Springbok weather station and the rainfall data collected on the Goegap Nature Reserve.
The life form data were used to calculate the following diversity indices:
Life form richness;
Life form evenness;
56
Shannon index of life form diversity and
Simpson’s index of life form diversity.
The indices were calculated in two different ways. In the first instance the number of species in a life
form was used as a measure of its abundance and in the second instance the sum of all strikes of the
species in a particular life form was used as a measure of its abundance.
4.2.3
Range condition and carrying capacity
Because the area of study is under protection, it is important to assess the impact of possible
overutilisation by mammalian herbivores on vegetation; thus, to conduct a veld condition assessment
and provide recommendations on the carrying capacity for the Goegap Nature Reserve. The veld
condition was assessed with the use of GIV (grazing index values) of species (Du Toit 2003, Rösch
2003).
The first step in formulating a veld management program is to determine the veld condition in every
homogenous vegetation unit in the given area. The seven line transects investigated in this study
represent seven of the 10 management units of the Goegap Nature Reserve (see Chapter 3). One
technique often used to determine the veld condition is the Ecological Index Method (EIM) (Bothma
2000). The technique has been shown to provide reliable results in the karoo environment (Vorster
1982). The grazing index method (GIM) is a refinement of the EIM and was proposed by Du Toit
(1996, 1998) specifically for the karoo veld. Each species has a unique grazing index value allocated
to them, and the cover of each species is then multiplied by its grazing index value. Thίs product
corresponds to the condition index of that species in the specific veld under survey. Therefore, when
all the condition indices of the individual species are added together, the sum represents the veld
condition index (or veld condition score) of that specific veld. The veld condition index is then
compared with the veld condition index of the benchmark. The veld condition index of the benchmark
is divided by the veld condition index of the veld sample (Du Toit 2003). The veld condition score
(VCS) of 650 was taken as the highest possible score (Lloyd 1996). This answer is the grazing
capacity of the sample in morgan per small stock unit (morgan/SSU). A correction factor of 7.14 is
applied to convert the grazing capacity to large-stock unit (LSU) per hectare (Du Toit 2002). This
value can be compared to the grazing capacity norm appropriate to the area under study (Du Toit
2003, Rösch 2003).
4.2.4
Ordination
According to Kent and Coker (2001) ordination means to “set in order”, and here ordering means
vegetation sample arrangement in relation to each other, in terms of their species composition and/or
their associated environmental control similarity. Individual samples or species and their degree of
similarity to each other, and the correlation of the individuals with underlying environmental factors,
are determined. The techniques of ordination and gradient analysis are also methods for data
reduction and exploration that lead to hypothesis formulation. Two types of gradient analysis are
57
defined, namely direct, for example canonical correspondence analysis (CCA), and indirect
ordination, for example correspondence analysis (CA).
s
The CANOCO computer software package (CANOCO version 4.5, Microcomputer Power. Ithaca, NY,
USA) (Ter Braak & Smilauer 2003) was used to investigate the species composition changes. Firstly,
detrended correspondence analysis (DCA) was used to find out if a linear or a unimodal context must
be applied (Leps & Smilauer 2003). The unimodal method was used (and not the linear method of
ordination) because the gradient value was long (>4 SD). Correspondence analysis (CA) was used to
do an indirect gradient analysis and canonical correspondence analysis (CCA) was used to do a
direct gradient analysis. The perennial species were analysed with regard to the progress throughout
the monitored years separately from the annual species. Perennial species do not react notably to the
rainfall whereas annual species do react to rainfall.
CANOCO can be applied to most methods of ordination and is designed for data analysis in
community ecology. Ordination deals not primarily with classes, as in classification, but is an essential
technique of gradient analysis. The plant species occurring in the line transects can be arranged in
sequence by their positions along an environmental gradient or axis, and any change in these plant
species are related to changes in the environment (Whittaker 1978b, Ter Braak & Smilauer 2003). To
make use of this method, quantitative data are needed, though replications are unnecessary
(qualitative data can be used but it is difficult to derive a gradient from this).
The rainfall data, obtained from different rain meters situated in the reserve, were analysed in six
different ways:
First quarter rainfall: the sum of rainfall in January, February and March (late summer
rainfall);
Second quarter rainfall: the sum of rainfall in April, May and June (early and partly mid-winter
rainfall);
Summer rainfall: the sum of rainfall in October, November and December of the previous
year and the rainfall in January, February and March of the current year;
Winter rainfall: the rainfall in April, May, June, July and August of the current year (the rainfall
having an influence on the current year’s flowering) (September rainfall is excluded because
this is when field work is done);
Previous winter rainfall: the sum of rainfall of April, May, June, July, August and September of
the previous year and
Annual rainfall: the rainfall throughout the year (from January up to December) of the current
year.
Thus, the rainfall can be divided into different groups related mainly to the seasons (winter and
summer) and by using CANOCO the annual species will be placed in relation to the different rainfall
groups.
58
CHAPTER 5
RESULTS
5.1
Bleshoek Plains
5.1.1
Rainfall
Figure 5.1 shows the large fluctuations in the rainfall at the Bleshoek Plains line transect during the
monitored years. The annual rainfall varied approximately threefold from 105.5 mm up to 303.8 mm
rain. Such highly variable rainfall is typical for semi-arid and arid environments (Low & Rebelo 1998,
Le Roux & Van Rooyen 1999, Mucina & Rutherford 2006). The winter rainfall received was much
higher than the summer rainfall, indicating that the area was situated in a winter rainfall region.
350
300
Rainfall (mm)
250
Winter
200
Summer
150
Total
100
50
0
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Tme (years)
Figure 5.1 The rainfall during the monitored years at the Bleshoek Plains line transect. Summer =
rainfall in the summer months (January to March and October to December of the current year),
Winter = rainfall in the winter months (April to September), and Total = the total annual rainfall
(January to December).
5.1.2
Frequency of occurrence of annual and perennial species
The frequency of occurrence of the perennial species did not reveal any changes in a specific
direction at the Bleshoek Plains line transect over time (Figure 5.2). In contrast, the frequency of the
annual species showed a clear relationship with the winter rainfall (Figure 5.3). It should be noted
that in Figures 5.2 and 5.3 the summer rainfall refers to the rainfall from October to December of the
previous year and January to March of the current year, therefore this value represents the summer
59
period preceding the current winter growing season. The winter rainfall refers to the rainfall from
300
60
250
50
200
40
150
30
100
20
50
10
0
Frequency (%)
Rainfall (mm)
April to August of the current year.
0
1991
1993 1994
1995
1997
1998 1999
2000
2001 2002
2003
2004
2005 2006
2007
Time (years)
Rainfall (Winter)
Rainfall (Summer)
Annuals
Perennials
Figure 5.2 The frequency of strike of the annual and perennial species and the winter and summer
rainfall during the monitored years for the Bleshoek Plains line transect. The blue line represents the
percentage frequency of the perennial species, whereas the red line represents the annual species.
The summer rainfall stretches from October to December of the previous year and January to March
of the current year, whereas the winter rainfall includes the rainfall from April to August of the current
year.
It is clear that except in the very dry years, the frequency of strikes of the annual species exceeded
that of the perennial species. The vegetation at this line transect therefore comprised mostly annual
vegetation.
5.1.3
Species and life form diversity
The following four measures of diversity were calculated for each year for the Bleshoek Plains line
transect by means of the PC-ORD computer package (PC-ORD version 4, MjM Software Design,
Gleneden Beach, Oregon USA) (McCune & Mefford 1999, Chapter 4):
The species richness (S) or number of species
Species evenness (E)
Shannon’s index of diversity (H)
Simpson’s diversity index
60
70
y = 0.2284x + 2.6105
R2 = 0.6065
60
Frequency (%)
50
40
30
20
10
0
0
50
100
150
200
250
300
Rainfall (m m )
Figure 5.3 The regression of the winter rainfall against the frequency of annual species for the
Bleshoek Plains line transect.
To obtain a measure of the functional diversity of the vegetation each recorded species was
assigned to a life form category (Mueller-Dombois & Ellenberg 1974). The life form data were then
used to calculate the same diversity indices as for the species data. The life form indices were
calculated in two different ways. In the first instance the number of species in a life form was used as
a measure of its abundance and in the second instance the sum of all strikes of the species in a
particular life form was used as a measure of its abundance.
Richness
The species richness records the total number of species without reference to the distribution of
individuals among the species (Krohne 2001). The species richness of the perennial species (Figure
5.4) did not reveal any definite changes in a specific direction, and therefore showed no specific
increase or decrease during the past monitored years. The species richness of the annual species
2
revealed large fluctuations. There was a significant positive correlation (r = 0.20) between the
species richness of the annual species and the rainfall but this relation was not found with the
perennial species richness. There was a strong correlation between the frequency of occurrence of
the annual species and annual species richness (Figure 5.5).
Table 5.1 shows that the most prevalent life forms for the Bleshoek Plains line transect were the
therophytes and the chamaephytes.
61
Table 5.1 Number of species per life form occurring at the Bleshoek Plains line transect
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
1991
0
0
0
8
2
0
0
6
4
2
3
3
0
0
0
22
2
1993
0
0
0
8
1
0
0
7
5
2
3
3
0
0
0
31
3
1994
0
0
0
8
2
0
0
6
4
2
4
4
0
0
0
28
1
1995
0
0
0
7
1
0
0
6
4
2
4
4
0
0
0
23
1
1997
0
0
0
8
2
0
0
6
4
2
4
4
0
0
0
23
2
1998
0
0
0
10
2
0
0
8
6
2
4
4
0
0
0
13
1
1999
0
0
0
7
2
0
0
5
4
1
3
3
0
0
0
3
3
62
2000
0
0
0
8
3
0
0
5
3
2
4
4
0
0
0
13
3
2001
0
0
0
7
2
0
0
5
3
2
3
3
0
0
0
20
1
2002
0
0
0
7
2
0
0
5
3
2
3
3
0
0
0
21
2
2003
0
0
0
6
2
0
0
4
3
1
3
3
0
0
0
2
0
2004
0
0
0
7
1
0
0
6
5
1
3
3
0
0
0
12
3
2005
0
0
0
8
2
0
0
6
5
1
3
3
0
0
0
9
1
2006
0
0
0
8
3
1
0
4
3
1
4
4
0
0
0
25
2
2007
0
0
0
7
2
0
0
5
4
1
3
3
0
0
0
22
3
Species number
50
40
30
20
10
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Annuals
Perennials
Total
Figure 5.4 The species richness of annual and perennial species as well as total species richness
during the past monitored years for the Bleshoek Plains line transect.
35
y = 0.4091x + 5.7387
R2 = 0.7882
30
Species richness
25
20
15
10
5
0
0
10
20
30
40
50
60
Frequency (%)
Figure 5.5 The regression of the frequency of strike for the annual species against the annual
species richness for the Bleshoek Plains line transect.
Diversity measures
The evenness (E) and Simpson’s index of diversity (D) remained almost unchanged over the
monitoring period whereas the Shannon index (H) mirrored the total species richness trends (Figure
5.6a). Where the number of species was used as a measure of the abundance of growth forms
(Figure 5.6b) the diversity increased in the years with a low winter rainfall. The opposite trend was
observed where the number of strikes was used as a measure of the abundance of the growth forms
(Figure 5.6c). In all three graphs (Figure 5.6a-c) the changes were not directional but depended
primarily on the amount of winter rainfall.
63
a.
3.5
Index value
3
2.5
2
1.5
1
0.5
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Tim e (years)
E
Index value
b.
H
D
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Tim e (years)
E
c.
H
D
1.4
Index value
1.2
1
0.8
0.6
0.4
0.2
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Tim e (years)
E
H
D
Figure 5.6 The diversity measures in the Bleshoek Plains line transect, using (a) the first strikes of
all species, (b) the number of species in the different life forms and (c) the number of strikes in the
different life forms. E = species/life form evenness, H = Shannon’s diversity index and D =
Simpson’s diversity index.
64
5.1.4
Species composition
Individual species
The most abundant perennial species at Bleshoek Plains line transect was Leipoldtia schultzei
(Appendix 8.1). This succulent species showed a slight increase in frequency of occurrence over the
2
monitored years (r = 0.38; Figure 5.7a). In contrast, Ruschia robusta, another succulent species
2
showed a marked decline (r = 0.25) in the last few years. The two palatable grass species,
2
2
Stipagrostis obtusa and S. brevifolia, also showed a marked decline (r = 0.60; r = 0.44) over the
monitored years (Figure 5.7b).
12
a.
Frequency (%)
10
8
y = 0.1518x + 7.8924
R2 = 0.3766
6
4
2
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
4
b.
3.5
y = -0.0696x + 2.6838
R2 = 0.2501
Frequency (%)
3
2.5
2
y = -0.1086x + 1.7752
R2 = 0.6035
1.5
1
0.5
y = -0.0643x + 1.2476
R2 = 0.4428
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Ruschia robusta
Stipagrostis brevifolia
Stipagrostis obtusa
Figure 5.7 Changes in frequency of selected perennial species at Bleshoek Plains line transect; (a)
Leipoldtia schultzei; and (b) Ruschia robusta, Stipagrostis obtusa and S. brevifolia.
65
4
3.5
3
Frequency (%)
2.5
2
y = -0.1929x + 2.5829
2
R = 0.5177
1.5
1
0.5
0
-0.5
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
-1
Time (years)
Figure 5.8 Changes during the past 15 years in an unpalatable annual species, Leysera tenella,
occurring in the Bleshoek Plains line transect.
In general, the annual species showed large fluctuations in abundance. Leysera tenella showed a
2
decreasing trend (r = 0.52) in the Bleshoek Plains line transect (Figure 5.8). This change is an
indication of veld recovery. However, the decrease of the perennial grass species showed the
opposite trend.
Community composition
The changes in the species composition were illustrated by the use of Correspondence Analysis
(CA) in the computer programme CANOCO. The scatter diagram of data of all species in the
Bleshoek Plains line transect reveals that changes did occur (Figure 5.9a). There is no clear
directional trend, although the progression seems to go from the top of the ordination space to the
bottom.
Perennial species composition
When only the perennial species were used in the CA ordination (Figure 5.10) there is a clear
progression in the years from the left to the right on the scatter diagram as indicated by the arrow in
Figure 5.11.
Annual species composition
The change in the annual species composition was analysed by Canonical Correspondence
Analysis with regards to the rainfall because rain gives rise to changes in short-lived vegetation.
Rainfall was expressed in different ways: the first quarter rainfall (1Q), second quarter rainfall (2Q),
summer rainfall (Summer), winter rainfall (Winter), rainfall of the previous winter (Prev winter), and
annual rainfall (Annual).
66
0.8
a.
97
Zalu gil
94
Chei den
Trip hyo
Manu che
95
Dimo sin
Stip cil
Zalu ben
Apto spi
Hirp ech
Dide car
98
Grie hum
Heli cor
Gymn lin
Crot hum
Leys ten
Phyl occ
Stip obt
Pent air
Poly sel
Rusc bre
Iflo glo
Feli nam
Phar dic
Gale fru
Trac spp
Cras thu
91
00
99
Mese gue Trip sin
Gaza ten
Psil jun
Oste pin
Stip bre
Dimo pol
Manu ben
Wahl pro
Fove dic
93
04
Sals kal
Oxal spp
Tetr fru
Rusc rob
Dros his
Less dif
Gaza lic
Zygo ret
Pela red
Peli vir
Leip sch
Trib ter
Hype sal
Gale sar
05
Glad sp.
Ehrh lon
Sene are
Euph dec
Schm kal
Karr sch
Geop
Heli leo
Onco suf
Lyci cin
03
Tetr mic Arct fas
Sene car
Trip amp
Loto bra
02
Erod sp.
Onco gra
01
Heli var
Dyer afr
Poly col
Ehrh cal
Rusc eli
Heli ses
Heli lac
Blep mac
06
-0.8
07
-0.6
b.
.
Axes :
Eigenvalues :
1.0
1
2
3
4
0.272
0.216
0.158
0.127
23.6
42.5
56.2
67.2
Total inertia
1.150
Cumulative percentage
Variance of species data :
Sum of all eigenvalues :
1.150
Figure 5.9 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of all species (75 species) relative to the monitored years for the Bleshoek Plains line
transect. The red x-marks represent the years and the blue crosses the species. (b) Details of the
CA ordination.
67
1.0
00
06
Gale fru
a.
Blep mac
Dyer afr
Ehrh cal
Peli vir
94
01
97
Trip sin
Chei den
Hype sal
Zygo ret
98
99 Lyci cin
Stip obt
Psil jun
Stip bre
Tetr fru
Leip sch
Rusc rob
Euph dec
Apto spi
93
03
05
Rusc bre
02
Dros his
Rusc eli
07
91
Stip cil
95
-1.0
04
-1.0
b.
1.0
Axes :
Eigenvalues :
1
2
3
4
0.051
0.029
0.022
0.014
31.3
49.1
62.6
71.0
Total inertia
0.162
Cumulative percentage
Variance of species data :
Sum of all eigenvalues :
0.162
Figure 5.10 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of perennial species (22 species) relative to the monitored years for the Bleshoek Plains
line transect where the red x-marks represent the years and the blue crosses the species. (b) Details
of the CA ordination.
68
1.0
00
94
97
06
01
99
98
93
03
05
02
07
91
95
-1.0
04
-1.0
1.0
Figure 5.11 Scatter diagram produced by a Correspondence Analysis (CA) ordination showing the
position of the monitored years for the Bleshoek Plains line transect with the arrow indicating the
direction of vegetation change.
The annual species showed no directional trend in species composition over the monitored years
(Figure 5.12). However, there were fluctuations in the annual species composition because these
species react towards the rainfall. A few species, such as Tribulus terrestris, Galenia sarcophylla,
Gymnodiscus linearifolia and Polycarena selaginoides were associated with high values for summer
and first quarter rainfall. In contrast, most annual species were associated with the winter rainfall and
second quarter rainfall axes. Heliophila lactea and H. variabilis were prominent in years with high
winter rainfall values and species such as Dimorphotheca sinuata and Lessertia diffusa were more
often encountered in years with less winter rainfall. There was a low (near to zero) correlation of
summer rainfall with the winter and second quarter rainfall.
69
0.8
97 Zalu gil
a.
Summer
Dide car
99
95
Crot hum
Zalu ben
Dimo sin
04
Phyl occ
Cras thu
1Q
98
Leys ten
Heli cor
Trip hyo
94
Grie hum
Less dif
Gymn lin
Sals kal
Trib ter
05
00
Mese gue
Poly sel
Gaza ten
Iflo glo
Wahl pro
Manu che
Ehrh lon
Schm kal 93
Hirp ech
Manu ben
Oste pin
Feli nam 91
Fove dic
Phar dic
Pela red
Pent air
Sene are
Dimo pol
Karr sch
Gaza lic
Gale sar
Heli leo
Prev Win
Onco suf
Sene car
02
Erod sp.
Trip amp
Onco gra
Tetr mic
Heli ses
07
Loto bra
Heli var
Poly col
Arct fas
03
2Q
01
Heli lac
Annual
06
-0.8
Winter
-0.6
1.0
b. Axes :
1
2
3
4
Total inertia
Eigenvalues :
0.395
0.253
0.136
0.108
1.576
Species-environment correlations :
0.973
0.966
0.929
0.852
of species data :
25.1
41.1
49.8
56.6
of species-environment relation :
40.8
66.8
80.9
92.1
Cumulative percentage variance
Sum of all eigenvalues :
1.576
Sum of all canonical eigenvalues :
0.970
Figure 5.12
(a) Scatter diagram produced by a Canonical Correspondence Analysis (CCA)
ordination showing the position of the annual species (49 species) relative to the years and rainfall in
the Bleshoek Plains line transect. The red x-marks represent the years and the blue crosses the
species. 1Q = rainfall from January to March of the current year, 2Q = rainfall from April to June of
the current year, Summer = rainfall from October to December of the previous year and January to
March of the current year, Winter = rainfall from April to August of the current year, Prev Win =
rainfall from April to September of the previous year and Annual = the annual rainfall of the current
year. (b) Details of the CCA ordination.
70
5.1.5
Grazing capacity
The grazing index method (GIM) as proposed by Du Toit (1996) for the Karoo veld was applied to
calculate the grazing capacity of the vegetation on the Bleshoek Plains line transect. The method
involves calculating the veld condition score and by comparing this value with a benchmark with a
known grazing capacity, the grazing capacity of the range under consideration can be calculated.
In general, the grazing capacity was lowest in the years with a low winter and total annual rainfall
and highest in years with a high winter as well as annual rainfall. The fluctuations in grazing capacity
2
Crazing capacity score (ha/LSU)
did not show directional trends (r = 0.10; Figure 5.13).
y = 2.3745x + 81.678
R2 = 0.1019
180
160
140
120
100
80
60
40
20
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Figure 5.13 The grazing capacity (ha/LSU) throughout the monitored years for the the Bleshoek
Plains line transect.
71
5.2
Bluemine Mountain
5.2.1
Rainfall
Figure 5.14 shows the fluctuation in the rainfall at the Bluemine Mountain line transect with an
increase in total annual rainfall during the last three monitored years. The annual rainfall varied
approximately fivefold from 65.30 mm up to 334.90 mm rain. The fluctuations in rainfall agree with
the rainfall trends for semi-arid and arid environments (Le Roux & Van Rooyen 1999, Van Rooyen
1999, Ward 2006). The winter rainfall was much higher than the summer rainfall, indicating that the
area was situated in a winter rainfall region.
400
350
Rainfall (mm)
300
250
Winter
200
Summer
150
Total
100
50
0
74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Figure 5.14
The rainfall during the monitored years at the Bluemine Mountain line transect.
Summer = rainfall in the summer months (January to March and October to December of the current
year), winter = rainfall in the winter months (April to September) and Total = the total annual rainfall
(January to December).
5.2.2
Frequency of occurrence of annual and perennial species
The frequency of occurrence of the perennial species revealed a slight increase at the Bluemine
Mountain line transect over time (Figure 5.15). In contrast, the frequency of the annual species
2
showed some relationship (r = 0.43) with the winter rainfall (Figure 5.16). In Figure 5.15 the summer
rainfall refers to the rainfall from October to December of the previous year and January to March of
the current year. The winter rainfall refers to the rainfall from April to August of the current year.
72
300
50
45
250
40
Rainfall (mm)
30
150
25
20
100
Frequency (%)
35
200
15
10
50
5
0
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Rainfall (Winter)
Rainfall (Summer)
Annuals
Perennials
Figure 5.15 The frequency of strike of the annual and perennial species and the winter and summer
rainfall during the monitored years for the Bluemine Mountain line transect. The blue line represents
the perennial species, whereas the red line represents the annual species. The summer rainfall
stretches from October to December of the previous year and January to March of the current year,
whereas the winter rainfall includes the rainfall from April to August of the current year.
It is clear that the frequency of strikes of the perennial species exceeded that of the annual species.
The vegetation at this line transect therefore comprised mostly perennial vegetation.
y = 0.0798x - 3.6191
R2 = 0.4319
30
25
Frequency (%)
20
15
10
5
0
0
50
100
150
200
250
300
-5
Rainfall (mm)
Figure 5.16 The regression of the winter rainfall against the frequency of annual species for the
Bluemine Mountain line transect.
73
5.2.3
Species and life form diversity
Richness
The species richness of the perennial species (Figure 5.17) did not reveal any definite changes in a
specific direction, and therefore showed no specific increase or decrease during the monitored
years. The species richness of the annual species revealed large fluctuations. In general, the
correlation between the species richness of the annual species and the total annual rainfall was
2
2
more positive (r = 0.3709) than that of perennial species richness and total annual rainfall (r =
2
0.2824). There was a strong correlation (r = 0.73) between the frequency of occurrence of the
annual species and annual species richness (Figure 5.18).
80
Species number
70
60
50
40
30
20
10
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Annuals
Perennials
Total
Figure 5.17 The species richness of annual and perennial species as well as total species richness
during the past monitored years for the Bluemine Mountain line transect.
Table 5.2 shows that the most prevalent life forms for the Bluemine Mountain Line Transect were the
therophytes and the chamaephytes.
Diversity measures
The evenness and Simpson’s index of diversity remained almost unchanged over the monitoring
period whereas the Shannon index mirrored the total species richness trends (Figure 5.19a). Where
the number of species was used as a measure of the abundance of growth forms (Figure 5.19b) the
diversity measures showed a decrease in the years with a low rainfall. A different trend was
observed when the number of strikes was used as a measure of the abundance of the growth forms
(Figure 5.19c) in which case there seems to be a gradual decline in diversity. In Figure 5.19a and
5.19b the changes were not directional but depended primarily on the amount of winter rainfall.
74
Table 5.2 Number of species per life form occurring at the Bluemine Mountain line transect
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
1974
4
1
3
25
12
0
1
12
10
2
1
1
0
0
0
10
1
1993
3
0
3
30
15
1
0
14
12
2
1
1
0
0
0
23
1
1975
2
0
2
26
14
0
1
11
9
2
1
1
0
0
0
16
2
1994
3
0
3
30
12
1
0
17
14
3
1
1
0
0
0
10
1
1976
2
0
2
38
18
2
1
17
14
3
2
1
0
1
0
17
0
1995
3
0
3
34
18
0
0
16
14
2
2
1
0
1
0
16
1
1977
3
0
3
30
15
0
0
15
12
3
3
2
1
0
0
16
0
1996
3
0
3
26
15
0
0
11
10
1
2
1
0
1
0
9
1
1978
2
0
2
26
13
0
1
12
11
1
2
1
0
1
0
2
0
1997
4
0
4
37
19
0
1
17
16
1
4
2
1
1
1
15
1
1979
3
0
3
25
12
0
0
13
12
1
1
1
0
0
0
3
0
1998
3
0
3
31
16
0
1
14
13
1
0
0
0
0
0
2
0
1980
3
0
3
24
12
0
0
12
10
2
0
0
0
0
0
8
0
1999
3
0
3
31
17
0
0
14
13
1
2
2
0
0
0
9
0
75
1982
2
0
2
24
10
0
0
14
11
3
1
1
0
0
0
2
0
2000
3
0
3
26
16
0
0
10
9
1
3
1
1
1
0
12
1
1984
3
0
3
31
15
0
0
16
13
3
1
1
0
0
0
2
0
2001
3
0
3
30
18
0
0
12
11
1
3
1
1
1
0
19
1
1985
3
0
3
30
16
0
0
14
11
3
1
1
0
0
0
1
0
2002
3
0
3
32
18
0
1
13
12
1
3
2
1
0
0
18
1
1986
3
0
3
27
11
0
0
16
13
3
2
1
1
0
0
3
0
2003
3
0
3
30
18
0
0
12
11
1
0
0
0
0
0
1
0
1987
3
0
3
28
11
0
0
17
14
3
1
1
0
0
0
2
0
2004
3
0
3
28
13
0
0
15
13
2
3
1
1
1
0
10
2
1989
3
0
3
30
15
1
1
13
11
2
1
1
0
0
0
1
0
2005
3
0
3
29
16
0
0
13
12
1
3
2
0
1
0
16
2
1990
3
0
3
35
16
2
1
16
14
2
1
1
0
0
0
1
0
2006
4
0
4
32
16
1
0
15
14
1
4
2
1
1
1
29
3
1991
3
0
3
30
15
1
0
14
13
1
4
2
1
1
0
14
1
2007
4
0
4
31
19
1
0
11
10
1
5
3
1
1
0
23
1
y = 0.9944x + 4.4565
R2 = 0.7348
35
Species richness
30
25
20
15
10
5
0
0
5
10
15
20
25
30
Frequency (%)
Figure 5.18 The regression of the frequency of strike for the annual species against the annual
species richness for the Bluemine Mountain line transect.
5.2.4
Species composition
Individual species
The most abundant perennial species at Blue Mine Mountain were Eriocephalus microphyllus and
Tripteris sinuata (Appendix 8.2) and Ruschia elineata. The former two species are both palatable
2
2
species and revealed an increase (r = 0.29; r = 0.76) over the monitored years (Figure 5.20a),
2
whereas Ruschia elineata, an unpalatable species, showed a decrease (r = 0.56) over the
monitored years (Figure 5.20b). In general, the annual species showed large fluctuations in
abundance. The most abundant annual species at this line transect was Galenia sarcophylla
(Appendix 8.2), a species with a low grazing index value (Du Toit 2003), which showed a decreasing
2
trend (r = 0.39) over the monitored years (Figure 5.20c).
Community composition
The changes in the species composition were detected by the use of Correspondence Analysis (CA)
in the computer programme CANOCO. The scatter diagram of data at the Bluemine Mountain line
transect indicated most of the early years towards the centre and slightly towards the left of the
ordination space and the later years progressively more towards the right of the ordination space.
Therefore in the ordination of the total floristic data of this line transect a weak gradient in direction
could be observed (Figure 5.21a).
76
a.
4
3.5
Index value
3
2.5
2
1.5
1
0.5
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
1974
0
Tim e (years)
E
D
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1974
Index value
b.
H
Tim e (years)
E
H
D
c.
1.6
1.4
Index value
1.2
1
0.8
0.6
0.4
0.2
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
1974
0
Tim e (years)
E
H
D
Figure 5.19. The diversity measures at the Bluemine Mountain line transect, using (a) the first
strikes of all species, (b) the number of species in the different life forms and (c) the number of
strikes in the different life forms. E = species evenness, H = Shannon’s diversity index and D =
Simpson’s diversity index.
77
a. 9
y = 0.0648x + 4.8655
R2 = 0.2862
8
Frequency (%)
7
6
5
4
3
y = 0.1046x + 0.529
R2 = 0.7593
2
1
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Eriocephalus microphyllus
b.
Tripteris sinuata
1.2
Frequency (%)
1
0.8
0.6
y = -0.022x + 0.5614
R2 = 0.5597
0.4
0.2
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
-0.2
Time (years)
Ruschia elineata
c.
2
Frequency (%)
1.5
y = -0.0443x + 1.3469
R 2 = 0.3895
1
0.5
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Tim e (years)
Galenia sarcophylla
Figure 5.20 Changes in frequency of selected (a) palatable and (b) unpalatable perennial species
and (c) an annual species at Bluemine Mountain.
78
1.0
76
a.
Anti mie
Sene cin
Trip hyo
Ursi cak
Trip amp
Euph mau
Zygo foe
01
Arct fas
Mese gue
05
Cras mus
Loto bra
74
Fove dic
Tetr mic
Pent air Zalu ben
Feli nam
Iflo
Home sp.
06 Wahl ann
Heli var
Manu che
Iflo kor Erio 2
02
Plan caf
75
Gale sar
77
Mano alb
Rusc eli
Otho arb
Onco suf
Leip sch Erio mic .93
Rusc rob
Sene car Karr sch
Lamp
god
Rusc vir Tetr fru
Leys ten
Lyci cin
Euph dec
Dias nam
78 79
04
99
82 89
95 Lebe ser
Oxal spp
Peli vir
.80 98
90
86 84
87 96 94 03 97
Herm mar
Dide spi
85
Heli leo
00
91
Cotu bar
Nena sp.
Arid noc
Gale sec Phar con
Psil jun
Heli lat
Ehrh cal
Leip Tie
Feli 1jr
Oste pin
Lasi mic
Herm cun
07
Heli
mee
Otho sp.
Iflo reg Manu gil
Pter glo
-0.6
Zalu ste
-0.4
b.
Axes :
Eigenvalues :
0.8
1
2
3
4
Total inertia
0.238
0.160
0.121
0.059
1.019
23.3
39.1
50.9
56.8
Cumulative percentage
variance of species data :
Sum of all eigenvalues :
1.019
Figure 5.21 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of all species (the most important 66 species of the total 154 species) relative to the
monitored years for the Bluemine Mountain line transect. The red x-marks represent the years and
the blue crosses the species. (b) Details of the CA ordination.
79
0.6
a.
02
01
Heli tin
03 Plin kar
Feli fil
Eury dre
Vygi spp
00
Ceph ebr
99
Erio bre
Cras mus
95
04
Pter cil
05
97
Gaza het
Herm mar
Eury mul
06
Feli bre
Melo can
Zygo ret
Trip sin
94 98
Lebe ser
Chry cil
Leip sch Pter inc
Otho cyl
93 Hirp ali
96
Gale afr
Amph tom
Rusc rob
91
Nena cin
Tetr fru
.89
87
Deve aph
90 84
Rusc vir
Arid noc
74
Otho arb
Psil jun
86
76 Rusc eli
85
80 Euph mau
79
82
Peli vir
Gale sec
Phar con
Dide spi
Leip Tie
Ehrh cal
Otho sp.
Pter glo
Heli mee 07
Herm cun
78
77
-0.4
75
-0.2
b.
Axes :
Eigenvalues :
1.0
1
2
3
4
0.162
0.066
0.030
0.027
31.2
44.1
49.9
55.1
Total inertia
0.518
Cumulative percentage
variance of species data :
Sum of all eigenvalues :
0.518
Figure 5.22 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of the perennial species (the 44 most important species of the 91 species) relative to the
monitored years for the Bluemine Mountain line transect. The red x-marks represent the years and
the blue crosses the species. (b) Details of the CA ordination.
80
0.8
02
01
03
00
05
99
95
97
04
98
06
-0.4
94
96
93
89
91
84
74
90 87
76
85
86
80 79
82 75
78
77
07
-0.5
2.0
Figure 5.23 Scatter diagram produced by a Correspondence Analysis ordination of the floristic data
of the perennial species indicating the change occurring over the monitoring period, where the
arrows indicates the progress in years, in the Bluemine Mountain line transect.
Perennial species composition
When the floristic data of only the perennial species (Figures 5.22) was used in the ordination the
direction of the vegetation change was more apparent than when all species were used in the
ordination. The direction of the change from the earlier years to the more recent years has been
indicated by arrows in Figure 5.23. Many species were associated with the earlier years whereas the
more recent years were associated with only a few species such as Pteronia glomerata and
Hermannia cuneifolia (Figure 5.22). The vegetation occurring during the earlier years contained a
larger component of unpalatable species left after the heavy grazing by livestock until 1969, than the
more recent years.
Annual species composition
The change in the annual species composition was analysed by Canonical Correspondence
Analysis with regards to the rainfall because of the relationship between rainfall and short-lived
vegetation. Rainfall was expressed in different ways: the first quarter rainfall (1Q), second quarter
rainfall (2Q), summer rainfall, winter rainfall, rainfall of the previous winter, and annual rainfall.
Most of the annual species occurring on the Bluemine Mountain line transect did not show a strong
association with a high winter rainfall (Figure 5.24). The annual species also showed no directional
trend in species composition over the monitored years. However, there were fluctuations in the
annual species composition because these species react towards the timing and quantity of the
rainfall and consequently years with similar rainfall patterns were grouped together. There was a low
(near to zero) correlation between summer rainfall and the winter and second quarter rainfall.
81
1.0
86
a.
79
78
77
98
84
00
80
87 Iflo par
Cler pap
Atri lin
Wahl pro
04
Phyl sp.
Cotu lax
Poac
99
Brom pec
Manu ben
Cotu nau 91
95
85
Grie hum
Cras thu
Gale sar
93
82
03
89
Heli lat
02
97
Leys ten
Iflo glo
05
Hirp ech
Ehrh del
Disc spi
Pent air
Mese gue
Ursi cak
75
Fove dic Gyna sed
Erod cic
Manu che
74
94 Gaza ten
Cotu bar
Feli nam
Heli var
Onco suf
Arct fas
Ursi cal
Sene car
Dimo sin
90
01
Zalu gil
Ursi nan
Poly col
96
Lasi bra
Karr sch
Heli leo
Zalu ben
Plan caf
Loto bra
Tetr mic
Dias nam
Summer
Trip hyo
Trip amp
1Q
76
Iflo kor
Prev Win
06 Iflo
Wahl ann
Nena sp.
Oste pin
2Q
07
Feli 1jr
Zalu ste
Manu gil
Lasi mic
Iflo reg
Winter
-1.0
Annual
-0.4
b.
1.0
Axes :
1
2
3
4
Eigenvalues :
0.363
0.207
0.162
0.088
Species-environment correlations :
0.953
0.786
0.835
0.868
of species data :
11.9
18.7
24.0
26.9
of species-environment relation:
39.2
61.5
79.0
88.5
Total inertia
3.056
Cumulative percentage variance
Sum of all eigenvalues :
3.056
Sum of all canonical eigenvalues :
0.928
Figure 5.24
(a) Scatter diagram produced by a Canonical Correspondence analysis (CCA)
ordination showing the position of the annual species (58 species) relative to the years and rainfall at
the Bluemine Mountain line transect. The red x-marks represent the years and the blue crosses the
species. 1Q = rainfall from January to March of the current year, 2Q = rainfall from April to June of
the current year, Summer = rainfall from October to December of the previous year plus January to
March of the current year, Winter = rainfall from April to August of the current year, Prev Win =
rainfall from April to September of the previous year and Annual = the annual rainfall of the current
year. (b) Details of the CCA ordination.
82
5.2.5
Grazing capacity
Changes in palatable and unpalatable species for the Bluemine Mountain line transect were
examined. The palatability of the plant species was determined by using the subjective grazing index
values as indicated by Du Toit (1996, 2003). To calculate the grazing capacity by the grazing index
method (GIM) of Du Toit (1996) the veld condition score was comparing with a benchmark with a
known grazing capacity.
The veld condition score showed a steady increase over time and this was reflected by the
2
improvement (r = 0.53) in the grazing capacity (Figure 5.25).
60
Grazing capacity score (ha/LSU)
y = -0.5256x + 48.465
2
R = 0.5347
50
40
30
20
10
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
1974
0
Time (years)
Figure 5.25
The grazing capacity (ha/LSU) throughout the monitored years for the vegetation
occurring in the Bluemine Mountain line transect. LSU = Large Stock Unit.
83
5.3
Goegap Plains
5.3.1
Rainfall
Figure 5.26 shows the fluctuation in the rainfall at the Goegap Plains line transect with an increase in
rainfall during the last three monitored years. The annual rainfall varied approximately threefold from
102 mm up to 303.8 mm rain. Such fluctuations in annual rainfall are a common occurrence for
semi-arid and arid environments (Le Roux & Van Rooyen 1999, Van Rooyen 1999, Ward 2006). The
winter rainfall was much higher than the summer rainfall in most years.
350
300
Rainfall (mm)
250
Winter
200
Summer
Total
150
100
50
0
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Figure 5.26 The rainfall during the monitored years at the Goegap Plains line transect. Summer =
rainfall in the summer months (January to March and October to December of the current year),
Winter = rainfall in the winter months (April to September) and Total = the total annual rainfall
(January to December).
5.3.2
Frequency of occurrence of annual and perennial species
The frequency of occurrence of the perennial species at the Goegap Plains line transect ranged
from 3.2% in 2003 to 20.6% in 2000, but did not reveal any changes in a specific direction over time
(Figure 5.27). In contrast, the frequency of the annual species showed a relationship with the winter
2
rainfall (r = 0.58; Figure 5.28). The frequency of the annuals ranged from 0.9% in 2003 to 34.7% in
1993. It was clear that the frequency of strikes of the annual species exceeded that of the perennial
species during the wet years, although the opposite was true for years with a low winter rainfall
when perennial species had a higher frequency of occurrence than the annual species.
84
300
40
35
250
Rainfall (mm)
25
150
20
15
100
Frequency (%)
30
200
10
50
5
0
0
1991
1993
1994
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Rainfall (Winter)
Rainfall (Summer)
Annuals
Perennials
Figure 5.27 The frequency of strike of the annual and perennial species and the winter and summer
rainfall during the monitored years for the Goegap Plains line transect. The blue line represents the
perennial species, whereas the red line represents the annual species. The summer rainfall
stretches from October to December of the previous year and January to March of the current year,
whereas the winter rainfall includes the rainfall from April to August of the current year.
40
y = 0.1275x - 0.9306
R2 = 0.576
35
Frequency (%)
30
25
20
15
10
5
0
0
50
100
150
200
250
300
Rainfall (mm)
Figure 5.28 The regression of the winter rainfall against the frequency of annual species for the
Goegap Plains line transect.
85
5.3.3
Species and life form diversity
Species number
Species richness
40
35
30
25
20
15
10
5
0
1991 1993 1994 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Annuals
Perennials
Total
Figure 5.29 The species richness of annual and perennial species as well as total species richness
during the past monitored years for the Goegap Plains line transect.
The species richness of the perennial species (Figure 5.29) did not reveal any definite changes in a
specific direction, and therefore showed no specific increase or decrease during the past monitored
years. The species richness of the annual species revealed large fluctuations. In general, the
correlation between the species richness of the annual species and the total annual rainfall was
2
2
more positive (r = 0.2807) than that of perennial species richness and total annual rainfall (r =
2
0.0027). There was a strong correlation (r = 0.72) between the frequency of occurrence of the
annual species and annual species richness (Figure 5.30).
Table 5.3 indicates that the most prevalent life forms for the Goegap Plains line transect were the
therophytes and the chamaephytes.
86
Table 5.3 Number of species per life form occurring at the Goegap Plains line transect
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
1991
0
0
0
7
3
0
0
4
3
1
1
1
0
0
0
16
2
1993
1
0
1
7
3
0
0
4
3
1
3
3
0
0
0
27
3
1994
1
0
1
6
2
0
0
4
3
1
3
3
0
0
0
15
3
1997
1
0
1
11
5
1
0
5
4
1
5
5
0
0
0
19
3
1998
1
0
1
8
4
1
0
3
2
1
3
3
0
0
0
6
3
1999
1
0
1
7
3
1
0
3
2
1
2
2
0
0
0
2
2
2000
1
0
1
9
5
1
0
3
2
1
4
4
0
0
0
16
3
87
2001
1
0
1
8
5
0
0
3
2
1
4
4
0
0
0
14
2
2002
1
0
1
8
4
0
0
4
3
1
3
3
0
0
0
14
2
2003
1
0
1
8
4
1
0
3
2
1
2
2
0
0
0
2
2
2004
1
0
1
6
4
0
0
2
2
0
2
2
0
0
0
15
2
2005
0
0
0
9
5
0
0
4
3
1
4
3
0
1
0
16
2
2006
1
0
1
9
3
1
0
5
4
1
3
3
0
0
0
17
1
2007
1
0
1
8
4
1
0
3
2
1
2
2
0
0
0
22
2
y = 0.5399x + 6.1425
R2 = 0.7184
30
Species richness
25
20
15
10
5
0
0
5
10
15
20
25
30
35
40
Frequency (%)
Figure 5.30 The regression of the frequency of strike for the annual species against the annual
species richness for the Goegap Plains line transect.
Diversity measures
The evenness (E) and Simpson’s index of diversity (D) remained almost unchanged over the
monitoring period whereas the Shannon index (H) mirrored the species richness trends (Figure
5.31a). Where the number of species was used as a measure of the abundance of growth forms
(Figure 5.31b) the diversity measures showed an increase in the years with a low winter rainfall. A
different trend was observed when the number of strikes was used as a measure of the abundance
of the growth forms (Figure 5.31c) in which case the evenness and Simpson’s index of diversity
stayed mostly unchanged but there seemed to be a gradual decline in the Shannon index of
diversity during the last couple of monitored years. In Figure 5.31a and 5.31b the changes were not
directional but depended primarily on the amount of winter rainfall.
5.3.4
Species composition
Individual species
The most abundant perennial species at the Goegap Plains line transect were Aptosimum
spinescens, Drosanthemum hispidum and Psilocaulon junceum. Drosanthemum hispidum
2
(Appendix 8.3) did not reveal any decrease or increase over the monitored years (r = 0.0045;
Figure 5.32a), However, Aptosimum spinescens and Psilocaulon junceum, both unpalatable
2
2
species, showed a decreasing trend (r = 0.51; r = 0.55) in the Goegap plains line transect (Figure
5.32b).
In general the annual species showed large fluctuations in abundance. The most abundant annual
species at this line transect were all unpalatable species, namely Galenia sarcophylla, Atriplex
88
lindleyi subsp. inflata, Foveolina dichotoma and Osteospermum pinnatum. Galenia sarcophylla did
2
not reveal any notable change in direction throughout the monitored years (r = 0.06; Figure 5.33a)
whereas Atriplex lindleyi subsp. inflata, Foveolina dichotoma and Osteospermum pinnatum showed
2
2
2
a decreasing trend (r = 0.8; r = 0.1; r = 0.19) throughout the monitored years (Figure 5.33b). This
change is an indication of veld recovery.
a.
3.5
3
Index value
2.5
2
1.5
1
0.5
0
1991 1993 1994
1997 1998 1999 2000
2001 2002 2003
2004 2005 2006 2007
Time (years)
E
Index value
b.
H
D
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
E
Index value
c.
H
D
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1991 1993 1994 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
E
H
D
Figure 5.31 The diversity measures in the Goegap Plains line transect, using (a) the first strikes of
all species, (b) the number of species in the different life forms and (c) the number of strikes in the
different life forms, E = species evenness, H = Shannon’s diversity index and D = Simpson’s
diversity index.
89
a.
12
Frequency (%)
10
8
y = -0.0453x + 5.111
R2 = 0.0045
6
4
2
0
1991
1993
1994
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Drosanthemum hispidum
b.
4
3.5
Frequency (%)
3
y = -0.1886x + 2.4429
R2 = 0.5493
2.5
2
1.5
y = -0.0602x + 1.3516
R2 = 0.5093
1
0.5
0
-0.5
1991
1993
1994
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Aptosimum spinescens
Psilocaulon junceum
Figure 5.32 Changes in frequency of (a) a selected palatable perennial species and (b) selected
unpalatable perennial species at Goegap Plains line transect.
90
a.
14
Frequency (%)
12
10
y = 0.2521x + 1.9022
R 2 = 0.0569
8
6
4
2
0
1991
1993
1994
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Galenia sarcophylla
4.5
b.
4
y = -0.1275x + 2.0132
Frequency (%)
3.5
R2 = 0.1889
3
y = -0.0765x + 1.4593
R2 = 0.1048
2.5
2
1.5
y = -0.1055x + 1.5198
R2 = 0.8041
1
0.5
0
1991
1993 1994
1997
1998
1999
2000 2001
2002
2003
2004
2005 2006
2007
Time (years)
Atriplex lindleyi subsp. inflata
Foveolina dichotoma
Osteospermum pinnatum
Figure 5.33 Changes in frequency of selected annual species at Goegap Plains line transect. (a)
Galenia sarcophylla and (b) Atriplex lindleyi subsp. inflata, Foveolina dichotoma and Osteospermum
pinnatum.
Community composition
The changes in the composition of all species combined were detected by the use of
Correspondence Analysis (CA) in the computer programme CANOCO. The scatter diagram of the
floristic data of all the species in the Goegap Plains line transect revealed that some directional
change did occur (Figure 5.34a) with the general direction of the trend indicated by the arrow in
Figure 5.34c.
91
1.0
a.
Erod mos Amel str
Pent air Zalu gil Mora sch
Phar dic
Manu ben
93
Cras thu
91
Phyl occ
Wahl pro
Unid spe
Manu che
Plan caf
Karr sch
Heli var
Hirp ech
Fove dic
Coni elo
Auge cap
Orni sec
Sene are
Psil jun
Arid noc
02
Wahl ann
Oste pin
Heli leo
94
Heli tin
Oxal spp
Atri lin
Peli vir
Onco suf
Dimo sin
Apto spi
Heli ses
Iflo reg
07
Crot hum
Babi sp.
Sals aph
Loto
fal Mora min
Herm sp.
Onco gra
Lasi mic
Leys ten
Stip cil
Trac bul
Pter sca 01
Dimo pol
Hype sal
98
Grie hum
Zygo
ret
Gale sar
Erio mic
Poly col
Sene niv
Loto bra
Stip bre
Herm cun Gaza lic Pela red
97
Stip obt
Aizo can
Less dif
Dros his
Lyci cin
Iflo par
99
04
Geop
Mese gue
03
00
Sals tub
Stip zey
06
Jame alb
-0.6
Apto ind
Thes lin
Trip amp 05
-0.6
1.0
b.
Axes :
Eigenvalues :
1
2
3
4
0.303
0.253
0.228
0.151
23.3
42.8
60.4
72.0
Total inertia
1.297
Cumulative percentage
variance of species data :
Sum of all eigenvalues :
1.297
Figure 5.34 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of all species (74 species) relative to the monitored years for the Goegap Plains line
transect. The red x-marks represent the years and the blue crosses the species. (b) Details of the
CA ordination. (c) (On next page) The Correspondence Analysis (CA) scatter diagram with the
arrow indicating the direction of change at the Goegap Plains line transect.
92
1.0
c.
93
91
94
02
97
04
07
98
01
99
03
00
06
-1.0
05
-1.0
1.5
Figure 5.34 (continued)
Perennial species composition
The perennial species of the Goegap Plains line transect (Figure 5.35a) did not reveal a clear
gradient as time proceeded.
Annual species composition
The change in the annual species composition was analysed by Canonical Correspondence
Analysis (CCA) with regards to the rainfall. The annual species occurring in the Goegap Plains line
transect also showed no directional trend in species composition over the monitored years. Most of
the annual species occurring in this line transect did not show a strong association with a high winter
rainfall (Figure 5.36). However, there were some annual species that preferred a high value for
summer or first quarter (1Q) rainfall, such as Aizoon canariense, Mesembryanthemum guerichianum
and Tripteris amplectens. There was a low (near to zero) correlation between summer rainfall and
the winter and second quarter rainfall.
93
1.0
03
a.
04
99
Stip bre
Sene niv
Erio mic
07
Herm cun
01
00
Herm sp.
Stip cil
Zygo ret
Stip obt
98
Sals tub
Stip zey
06
Sals aph
Pter sca
97
Lyci cin
Apto spi
Dros his
Jame alb
Arid noc
Heli tin
Hype sal
02
Psil jun
Peli vir
Coni elo
Thes lin
05
94
Apto ind
Auge cap
91
-0.6
93
-0.4
b.
Axes :
Eigenvalues :
1.0
1
2
3
4
Total inertia
0.373
0.105
0.087
0.059
0.747
49.9
64.0
Cumulative percentage
variance of species data :
Sum of all eigenvalues :
75.7 83.5
0.747
Figure 5.35 (a) Scatter diagram produced by a Correspondence analysis (CA) ordination showing
the position of the perennial species (25 species) relative to the monitored years for the Goegap
Plains line transect. The red x-marks represent the years and the blue crosses the species. (b)
Details of the CA ordination.
94
1.0
Phar dic
a.
93
Pent air
Zalu gil
Erod mos
Amel str
Cras thu
99
Manu ben
Heli var
Wahl pro
Hirp ech
Wahl ann
98
02
04
Plan caf
Fove dic
97
Oste pin
Babi sp.
Karr sch
Sene are
Unid spe
Atri lin
Dimo sin
Iflo par
Heli leo
Grie hum
Onco gra
Gale sar
Dimo pol
Loto bra
Aizo can
01
Gaza lic
Manu che
Phyl occ
2Q
91
94
Poly col
Leys ten
Onco suf
Mese gue
Summer
Heli ses
06
Prev Win
Winter
Less dif
Pela red
05
03
Trip amp
1Q
Lasi mic
Iflo reg
Annual
Crot hum
07
Loto fal
-1.0
00
-1.0
1.0
b. Axes
1
2
3
4
Eigenvalues :
0.360
0.240
0.125
0.088
Species-environment correlations :
0.974
0.883
0.913
0.913
of species data :
26.8
44.6
53.9
60.4
of species-environment relation:
39.3
65.5
79.1
88.7
Total inertia
1.345
Cumulative percentage variance
Sum of all eigenvalues :
1.345
Sum of all canonical eigenvalues :
0.917
Figure 5.36
(a) Scatter diagram produced by a Canonical Correspondence Analysis (CCA)
ordination showing the position of the annual species (43 species) relative to the years and rainfall in
the Goegap Plains line transect. The red x-marks represent the years and the blue crosses the
species. 1Q = rainfall from January to March of the current year, 2Q = rainfall from April to June of
the current year, Summer = rainfall from October to December of the previous year plus January to
March of the current year, Winter = rainfall from April to August of the current year, Prev Win =
rainfall from April to September of the previous year and Annual = the annual rainfall of the current
year. (b) Details of the CCA ordination.
95
5.3.5
Grazing capacity
The grazing index method (GIM) as proposed by Du Toit (1996) for the Karoo veld was applied to
calculate the grazing capacity of the vegetation on the Goegap Plains. The method involves
calculating the veld condition score and by comparing this value with a benchmark with a known
grazing capacity, the grazing capacity of the range under consideration can be calculated.
The fluctuations in veld condition score and consequently grazing capacity did not show directional
2
trends (r = 0.04; Figure 5.37) and no improvement in grazing capacity could be demonstrated. The
exceptionally low grazing capacity in 2003 was the result of the winter rainfall for that year being low
and occurring at the end of the growing season.
400
Grazing capacity score (ha/LSU
350
300
y = 4.3217x + 76.895
R 2 = 0.0397
250
200
150
100
50
0
1991 1993 1994 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Figure 5.37
The grazing capacity (ha/LSU) throughout the monitored years for the vegetation
occurring in the Goegap Plains line transect. LSU = Large Stock Unit.
96
5.4
Jaleeg Plains
5.4.1
Rainfall
Figure 5.38 shows the fluctuation in the rainfall at the Jaleeg Plains line transect with an increase in
rainfall during the last two monitored years. The annual rainfall varied approximately fivefold from
62.9 mm up to 303.8 mm rain. The winter rainfall was much higher than the summer rainfall,
indicating that the area would qualify as a winter rainfall region.
350
300
Rainfall (mm)
250
200
Winter
150
Summer
Total
100
50
0
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Figure 5.38 The rainfall during the monitored years at the Jaleeg Plains line transect. Summer =
rainfall in the summer months (January to March and October to December of the current year),
Winter = rainfall in the winter months (April to September) and Total = the total annual rainfall
(January to December).
5.4.2
Frequency of occurrence of annual and perennial species
The frequency of occurrence of the perennial species at the Jaleeg Plains line transect revealed an
upward trend over time (Figure 5.39). In contrast, the frequency of the annual species showed a
2
weak relationship (r = 0.37) with the winter rainfall (Figure 5.40). In general, the frequency of strikes
of the perennial species was less than that of the annual species, except in years with a low rainfall.
The vegetation at this line transect therefore comprises mostly annual vegetation.
97
60
250
50
200
40
150
30
100
20
50
10
0
Frequency (%)
Rainfall (mm)
300
0
1991
1993
1994
1995
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Rainfall (winter)
Rainfall (summer)
Annuals
Perennials
Figure 5.39 The frequency of strike of the annual and perennial species and the winter and summer
rainfall during the monitored years for the Jaleeg Plains line transect. The blue line represents the
perennial species, whereas the red line represents the annual species. The summer rainfall
stretches from October to December of the previous year and January to March of the current year,
whereas the winter rainfall includes the rainfall from April to August of the current year.
60
y = 0.1374x + 9.6295
R2 = 0.3699
Frequency (%)
50
40
30
20
10
0
0
50
100
150
200
250
300
Rainfall (mm)
Figure 5.40 The regression of the winter rainfall against the frequency of annual species for the
Jaleeg Plains line transects.
98
5.4.3
Species and life form diversity
Species richness
The species richness of the perennial species (Figure 5.41) did not reveal any definite changes in a
specific direction, and therefore showed no specific increase or decrease during the past monitored
years. The species richness of the annual species revealed large fluctuations. The correlation
2
between the species richness of the annual species and the total annual rainfall was positive (r =
0.3346) whereas there was no relationship between the perennial species richness and total annual
2
rainfall (r = 0.0019). There was a strong correlation between the frequency of occurrence of the
2
Species numbers
annual species and annual species richness (r = 0.76; Figure 5.42).
50
45
40
35
30
25
20
15
10
5
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Annuals
Perennials
Total
Figure 5.41 The species richness of annual and perennial species as well as total species richness
during the past monitored years for the Jaleeg Plains line transect.
Table 5.4 shows that the most prevalent life forms for the Jaleeg Plains line transect were the
therophytes and the chamaephytes.
Diversity measures
The evenness (E) and Simpson’s index of diversity (D) remained almost unchanged over the
monitoring period whereas the Shannon index (H) mirrored the species richness trends (Figure
5.43a). Where the number of species was used as a measure of the abundance of growth forms
(Figure 5.43b) the diversity measures showed an increase in the years with a low winter rainfall. The
opposite trend was observed when the number of strikes was used as a measure of the abundance
of the growth forms (Figure 5.43c). In all three graphs (Figure 5.43a-c) the changes were not
directional but depended primarily on the amount of winter rainfall.
99
Table 5.4 Number of species per life form occurring at the Jaleeg Plains line transect
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
1991
0
0
0
8
1
1
1
5
2
3
1
1
0
0
0
18
1
1993
1
0
1
5
0
0
0
5
2
3
1
1
0
0
0
28
2
1994
0
0
0
5
2
0
0
3
1
2
1
1
0
0
0
16
1
1995
1
0
1
3
0
0
0
3
1
2
1
1
0
0
0
20
2
1997
0
0
0
7
1
0
1
5
3
2
2
2
0
0
0
19
3
1998
0
0
0
8
2
0
0
6
4
2
1
1
0
0
0
0
0
1999
0
0
0
7
1
0
1
5
3
2
1
1
0
0
0
11
1
100
2000
0
0
0
11
2
2
1
6
3
3
1
1
0
0
0
8
0
2001
0
0
0
9
2
0
1
6
3
3
3
2
1
0
0
23
1
2002
0
0
0
8
1
2
1
4
2
2
2
2
0
0
0
16
2
2003
0
0
0
5
1
0
0
4
2
2
1
1
0
0
0
2
2
2004
0
0
0
7
1
1
0
5
2
3
1
1
0
0
0
11
1
2005
0
0
0
7
1
1
1
4
2
2
1
1
0
0
0
10
0
2006
0
0
0
10
1
2
1
6
3
3
1
1
0
0
0
34
1
2007
0
0
0
7
2
1
0
4
2
2
1
1
0
0
0
23
1
40
y = 0.5019x + 3.9235
R2 = 0.7624
Species richness
35
30
25
20
15
10
5
0
0
10
20
30
40
50
60
Frequency (%)
Figure 5.42 The regression of the frequency of strike for the annual species against the annual
species richness for the Jaleeg Plains line transect.
5.4.4
Species composition
Individual species
Changes in palatable and unpalatable species for the Jaleeg Plains line transect were examined,
and palatability of the plant species was determined by using the subjective grazing-index values as
indicated by Du Toit (2003).
The most abundant perennial species at the Jaleeg Plains line transect were Ruschia robusta and
Stipagrostis brevifolia (Appendix 8.4). Stipagrostis brevifolia, a palatable species, revealed an
2
increase in frequency (r = 0.62) throughout the monitored years (Figure 5.44a). In general, the
annual species showed large fluctuations in abundance. The most abundant annual species at this
line transect were Dimorphotheca sinuata, Foveolina dichotoma and Galenia sarcophylla. Both
Dimorphotheca sinuata and Foveolina dichotoma, unpalatable species, showed a decreasing trend
2
2
(r = 0.37; r = 0.11; Figure 5.44b).
Community composition
The Correspondence Analysis scatter diagram of data of all the species in the Jaleeg Plains line
transect reveals that changes did occur (Figure 5.45). The general direction of the trend is indicated
by the arrow in Figure 5.46 with most of the early years found to the lower left side of the ordination
space and the later years progressively more towards the upper part and to the right.
101
a.
3
Index value
2.5
2
1.5
1
0.5
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Tim e (years)
E
Index value
b.
H
D
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Tim e (years)
E
H
D
c.
1.4
Index value
1.2
1
0.8
0.6
0.4
0.2
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Tim e (years)
E
H
D
Figure 5.43 The diversity measures of (a) the first strikes of all species, using (b) the number of
species in the different life forms and (c) the number of strikes in the different life forms, in the
Jaleeg Plains line transect. E = species evenness, H = Shannon’s diversity index and D = Simpson’s
diversity index.
102
a.
14
Frequency (%)
12
10
y = 0.4589x + 5.5886
R2 = 0.6249
8
6
4
2
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Stipagrostis brevifolia
b.
25
y = -0.9771x + 13.677
R2 = 0.3695
Frequency (%)
20
15
y = -0.2379x + 4.8495
R2 = 0.1145
10
5
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
-5
Time (years)
Foveolina dichotoma
Dimorphotheca sinuata
Figure 5.44 Changes in frequency of (a) a selected perennial species and (b) two annual species at
Jaleeg Plains line transect.
103
1.0
07
Feli 1jr
Ligh pla
a.
Zalu ste
Sond
Lasi mic
Sene car
Wahl ann
Gale mez
01 Scel sp.
Heli lac
Lasi bra
02
Gymn lin
Ursi cal
Onco gra
Aspa sp.
Lach sp.
Heli leo
Heli tin
Herm dis
Hype sal
Zalu ben
Sond ten
Pela red
Cras thu
Heli var
Cras nik
Karr sch Pent air
Wahl pro
Leys ten
Trip sin
Sene are
Heli ses
Rusc rob
99 Lyci cin
Onco suf
Ursi cak 93
Dimo pol
Manu ben
Aizo can
Arct fas
Trac fal Grie hum
Phar dic
Feli nam
Sarc sal
Tetr fru
Zalu gil
Dias nam
Stip nam
Phyl occ
Heli cor Oste pin
91
Mese gue
Gale sar
Dimo sin
Herm tom
Coni elo
Trac tor
Lyci fer
Zalu pus
Tetr mic
Rusc bre
03 Geop
Stip bre
Psil jun
Disc spi
98
04
Wahl thu
Euph dec
Gaza lic
Fove dic
Zygo ret
Loto bra
Oxal spp
Phar cro
06 Hebe (li
Herm tom
Euph mau
Manu che Trip amp
Bulb den
Less dif
Hirp ech
95
Gale afr
Heli lat
97
Phar con
Iflo glo
00
05
Unid spe
-1.0
94
-1.0
b.
1.0
Axes :
Eigenvalues :
1
2
3
4
Total inertia
0.320 0.168 0.145
0.121
1.046
30.6
72.0
Cumulative percentage
Variance of species data :
Sum of all eigenvalues :
46.6
60.5
1.046
Figure 5.45 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of all species (88 species) relative to the monitored years for the Jaleeg Plains line
transect. The red x-marks represent the years and the blue crosses the species. (b) Details of the
CA ordination.
104
0.8
07
01
02
06
04
99
03 98
91
93
95
00
97
-0.6
05
94
-1.0
Figure 5.46
1.0
The Correspondence Analysis (CA) scatter diagram with the arrow indicating the
direction of change at the Jaleeg Plains line transect.
Perennial species composition
The composition of the perennial species of the Jaleeg Plains line transect (Figure 5.47a) did not
reveal a clear gradient as time proceeded.
Annual species composition
The Canonical Correspondence Analysis (CCA) of the annual species occurring on the Jaleeg
Plains line transect with regards to the rainfall showed that some annual species had a strong
association with high values of winter rainfall, e.g. Heliophila lactea, Gymnodiscus linearifolia and
Zaluzianskya benthamiana (Figure 5.48). Those species associated with high values for summer
rainfall were Galenia sarcophylla, Mesembryanthemum guerichianum and Dimorphotheca polyptera.
The annual species occurring in the Jaleeg Plains line transect, however, showed no directional
trend in species composition over the monitored years. There was a low (near to zero) correlation of
summer rainfall and first quarter rainfall with the winter and second quarter rainfall.
105
1.0
a.
02
Aspa sp.
97
Heli tin
Stip nam
01
Gale mez
Coni elo
Scel sp.
Psil jun
00
Gale afr
Phar con
99
Lyci cin
Herm dis
Euph dec
Herm tom
Cras nik
Euph mau
06
Rusc rob
Zygo ret
Stip bre
Wahl thu
Tetr fru
98
Sarc sal
Rusc bre
91
Herm tom
95
03
Lyci fer
94
05
Trip sin
04
07 93
-0.6
Ligh pla
-0.4
1.0
b.
Axes :
Eigenvalues :
1
2
3
4
Total inertia
0.075 0.044 0.028
0.025
0.251
29.9
68.9
Cumulative percentage
Variance of species data :
Sum of all eigenvalues :
47.6
58.8
0.251
Figure 5.47 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of the perennial species (26 species) relative to the monitored years for the Jaleeg
Plains line transect. The red x-marks represent the years and the blue crosses the species. (b)
Details of the CA ordination.
106
1.0
a.
Annual
Winter
Prev Win
2Q
07
Bulb den
Phar cro
Hebe (li
Hype sal
06
Manu che Trip amp
Heli lac
Sene car
Feli 1jr
Sond
Zalu ste Lasi mic
Gymn lin
Zalu ben
Heli leo
03
Wahl ann
Heli var
Less dif
Pela red
Onco gra
Heli ses
Sene are
01
Loto bra
Disc spi
Gaza lic
Lasi bra
Summer
Sond ten
Cras thu
95
Tetr mic
Heli lat
Gale sar
Pent air
Fove dic
Wahl pro
Karr sch
Arct fas
Leys ten
Unid spe
Zalu pus
Dimo sin
04
Zalu gil
00
Dimo pol
05
94
1Q
Grie hum
Mese gue
Iflo glo
Phyl occ
Hirp ech
97
Oste pin
Phar dic
Ursi cal
02
Heli cor
99
Manu ben
-0.6
Ursi cak
Dias nam
Feli nam
93 Onco suf
91
Aizo can
-0.6
b.
1.0
Axes :
1
2
3
4
Total inertia
Eigenvalues :
0.367
0.172
0.101
0.066
1.230
Species-environment correlations :
0.946
0.914
0.878
0.660
of species data :
29.8
43.8
52.0
57.4
of species-environment relation :
48.2
70.9
84.1
92.8
Cumulative percentage variance
Sum of all eigenvalues :
1.230
Sum of all canonical eigenvalues :
0.760
Figure 5.48
(a) Scatter diagram produced by a Canonical Correspondence Analysis (CCA)
ordination showing the position of the annual species (57 species) relative to the years and rainfall in
the Jaleeg Plains line transect. The red x-marks represent the years and the blue crosses the
species. 1Q = rainfall from January to March of the current year, 2Q = rainfall from April to June of
the current year, Summer = rainfall from October to December of the previous year plus January to
March of the current year, Winter = rainfall from April to August of the current year, Prev Win =
rainfall from April to September of the previous year and Annual = the annual rainfall of the current
year. (b) Details of the CCA ordination.
107
5.4.5
Grazing Capacity
The veld condition score fluctuated, but overall showed an upward trend (Appendix 8.4). The
2
improvement in veld condition (r = 0.37) was reflected in the improvement of the grazing capacity
over the monitored years (Figure 5.49).
90
Grazing capacity score (ha/LSU)
80
y = -2.0019x + 69.648
70
R2 = 0.3731
60
50
40
30
20
10
0
1991 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Figure 5.49 The grazing capacity over the monitored years for the vegetation occurring in the
Jaleeg Plains line transect. LSU = Large Stock Unit.
108
5.5
Koperberg Plains
5.5.1
Rainfall
Figure 5.50 shows the fluctuation in the rainfall at the Koperberg Plains line transect illustrating an
increase in rainfall during the last three monitored years. The annual rainfall varied approximately
threefold from 95 mm up to 304 mm rain. The area is clearly a winter rainfall region with the amount
of winter rainfall exceeding that of the summer rainfall.
350
Rainfall (mm)
300
250
Winter
200
Summer
150
Total
100
50
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Figure 5.50 The rainfall during the monitored years at the Koperberg Plains line transect. Summer
= rainfall in the summer months (January to March and October to December of the current year),
Winter = rainfall in the winter months (April to September) and Total = the total annual rainfall
(January to December)
5.5.2
Frequency of occurrence of annual and perennial species
The frequency of occurrence of the perennial species did not reveal any changes in a specific
direction at the Koperberg Plains line transect over time (Figure 5.51). In contrast, the frequency of
2
the annual species showed a relationship with the winter rainfall (r = 0.58; Figure 5.52). It was clear
that except in the very wet years, the frequency of strikes of the perennial species exceeded that of
the annual species. The vegetation at this line transect therefore comprised mostly perennial
vegetation.
109
30
250
25
200
20
150
15
100
10
50
5
0
Frequency (%)
Rainfall (mm)
300
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Rainfall (Winter)
Rainfall (Summer)
Annuals
Perennials
Figure 5.51 The frequency of strike of the annual and perennial species and the winter and summer
rainfall during the monitored years for the Koperberg Plains line transect. The blue line represents
the perennial species, whereas the red line represents the annual species. The summer rainfall
stretches from October to December of the previous year and January to March of the current year,
whereas the winter rainfall includes the rainfall from April to August of the current year.
30
y = 0.0983x - 1.2491
R2 = 0.5764
Frequency (%)
25
20
15
10
5
0
0
50
100
150
200
250
300
Rainfall (mm)
Figure 5.52 The regression of the winter rainfall against the frequency of annual species for the
Koperberg Plains line transect.
110
5.5.3
Species diversity
Species richness
The species richness of the perennial species (Figure 5.53) did not reveal any definite changes in a
specific direction, and therefore showed no specific increase or decrease during the past monitored
years. The species richness of the annual species revealed large fluctuations. The correlation
between the species richness of the annual species and the total annual rainfall was more positive
2
2
(r = 0.375) than that of perennial species richness and total annual rainfall (r = 0.295). There was a
strong correlation between the frequency of occurrence of the annual species and annual species
richness (Figure 5.54).
Table 5.5 indicates that the most prevalent life forms for the Koperberg Plains line transect were the
therophytes and the chamaephytes.
Diversity measures
The evenness (E) and Simpson’s index of diversity (D) remained almost unchanged over the
monitoring period whereas the Shannon index (H) mirrored the species richness trends (Figure
5.55a). Where the number of species was used as a measure of the abundance of growth forms
(Figure 5.55b) the diversity measures showed an increase in the years with a low winter rainfall. A
different trend was observed when the number of strikes was used as a measure of the abundance
of the growth forms (Figure 5.55c) in which case there seems to be a gradual decline in diversity. In
Figure 5.55a and b the changes were not directional but depended primarily on the amount of winter
rainfall.
111
Table 5.5 Number of species per life form occurring at the Koperberg Plains line transect
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
1997
1
0
1
9
1
0
0
8
7
1
0
0
0
0
0
11
2
1998
1
0
1
7
1
0
0
6
5
1
0
0
0
0
0
4
0
1999
1
0
1
6
1
0
0
5
4
1
0
0
0
0
0
2
1
2000
2
0
2
6
1
0
0
5
4
1
0
0
0
0
0
2
0
2001
1
0
1
6
1
0
0
5
4
1
0
0
0
0
0
10
1
2002
1
0
1
7
1
0
0
6
5
1
0
0
0
0
0
14
0
2003
1
0
1
6
0
0
0
6
5
1
0
0
0
0
0
2
1
112
2004
1
0
1
8
1
1
0
6
5
1
0
0
0
0
0
1
0
2005
1
0
1
8
1
1
0
6
5
1
0
0
0
0
0
12
0
2006
2
0
2
8
1
0
0
7
6
1
0
0
0
0
0
14
0
2007
2
0
2
7
1
0
0
6
5
1
0
0
0
0
0
10
1
Species numbers
30
25
20
15
10
5
0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Annuals
Perennials
Total
Figure 5.53 The species richness of annual and perennial species as well as total species richness
during the past monitored years for the Koperberg Plains line transect.
y = 0.4507x + 2.7716
R2 = 0.6522
16
Species richness
14
12
10
8
6
4
2
0
0
5
10
15
20
25
30
Frequency (%)
Figure 5.54 The regression of the frequency of strike for the annual species against the annual
species richness for the Koperberg Plains line transect.
113
5.5.4
Species composition
Individual species
The most abundant perennial species at the Koperberg plains were Zygophyllum retrofractum and
Salsola tuberculata (Appendix 8.5). Neither of these species revealed any decrease or increase over
2
2
the monitored years (r = 0.05; r = 0.03; Figure 5.56a). In general, the annual species showed large
fluctuations in abundance. The most abundant annual species at this line transect was Atriplex
2
lindleyi subsp. inflata, an unpalatable pioneer species, which showed a decreasing trend (r = 0.30)
across the monitored years (Figure 5.56b).
Community composition
The changes in the species composition were investigated by the use of Correspondence Analysis
(CA) in the computer programme CANOCO. The scatter diagram of data of all the species in the
Koperberg Plains line transect did not reveal a strong directional trend (Figure 5.57).
Perennial species composition
Although the perennial species composition of the Koperberg Plains line transect showed changes
in composition over the monitored years a clear directional trend was not apparent as time
proceeded (Figure 5.58a).
Annual species composition
The change in the annual species composition was analysed by Canonical Correspondence
Analysis with regards to the rainfall because of the relationship between rainfall and short-lived
vegetation. Most of the annual species occurring on the Koperberg Plains line transect were not
strongly association with a high winter rainfall (Figure 5.59). The annual species in this transect also
showed no directional trend in species composition over the monitored years. There was a low (near
to zero) correlation of summer rainfall with the winter and second quarter rainfall.
114
a.
3
Index value
2.5
2
1.5
1
0.5
0
1997
1998
1999 2000
2001
2002
2003
2004 2005
2006
2007
2006
2007
Time (years)
E
b.
H
D
1.8
1.6
Index value
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
Tim e (years)
E
c.
H
D
1.4
1.2
Index value
1
0.8
0.6
0.4
0.2
0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
E
H
D
Figure 5.55 The diversity measures of (a) the first strikes of all species, using (b) the number of
species in the different life forms and (c) the number of strikes in the different life forms, in the
Koperberg Plains line transect. E = species evenness, H = Shannon’s diversity index and D =
Simpson’s diversity index.
115
a.
7
6
y = 0.0509x + 4.3945
R2 = 0.0528
Frequency (%)
5
4
3
2
y = 0.0227x + 2.4909
R2 = 0.0342
1
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Tim e (years)
Salsola tuberculata
Zygophyllum retrofractum
7
6
Frequency (%)
5
y = -0.2327x + 4.3873
R2 = 0.3011
4
3
2
1
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Figure 5.56 Changes in frequency of (a) selected perennial species and (b) an annual species
(Atriplex lindleyi subsp. inflata) at Koperberg Plains line transect.
116
1.0
Sals kal 06
Loto fal
05
a.
Aizo can
Less dif
Manu che
Gale sec
Gale sar
Loto bra
Gaza lic
Herm tom
97 Chei den
Coni elo
Tetr mic
Mese gue
Onco gra
Oste pin
Dros his
Trac spp
Atri lin
Psil sub
Tetr fru
Sals tub
Zygo ret
Dros bos
01
Geophyte
Dros otz
98
99
04
Fove dic
Dimo sin
Sals aph
Lyci cin Arid noc
Sene are
00
Oxal spp
03
Sene car
Karr sch
Leys ten
02
Heli var
Zalu ben
Amellus
07
-1.0
Trip hey
-1.0
b.
Axes :
Eigenvalues :
1.0
1
2
3
4
Total inertia
0.637
0.291
0.128
0.085
0.036
45.8
65.8
79.2
84.8
Cumulative percentage
Variance of species data :
Sum of all eigenvalues :
0.637
Figure 5.57 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of all species (40 species) relative to the monitored years for the Koperberg Plains line
transect. The red x-marks represent the years and the blue crosses the species. (b) Details of the
CA ordination.
117
1.0
97
a.
Coni elo
Dros his
07
06
Gale sec
Sals aph
00
Psil sub
Tetr fru
Zygo ret
Dros bos
Chei den
98
Arid noc
Lyci cin
Sals tub
01
Dros otz
02
05
99
Herm tom
03
-1.0
04
-1.0
b. Axes :
Eigenvalues :
1.0
1
2
3
4
Total inertia
0.060
0.049
0.020
0.011
0.160
37.2
67.6
80.3
87.0
Cumulative percentage
Variance of species data :
Sum of all eigenvalues :
0.160
Figure 5.58 (a) Scatter diagram produced by a CA ordination showing the position of the perennial
species (14 species) relative to the monitored years for the Koperberg Plains line transect. The red
x-marks represent the years and the blue crosses the species. (b) Details of the CA ordination.
118
0.8
Summer
a.
Loto fal 05
Aizo can
Less dif
Manu che
Annual
06
1Q
Sals kal
Gale sar
2Q
Loto bra
Winter
Tetr mic
Gaza lic
Oste pin
Mese gue
Onco gra
97
Fove dic
Atri lin
Dimo sin
99
00
Sene are
01
98
Trip hey
Amel lus
Sene car
Karr sch
07
Heli var
02 Leys ten
04
-0.6
Zalu ben
Prev Win
03
-1.0
b.
1.0
Axes :
1
2
3
4
Total inertia
0.886
Eigenvalues :
0.330
0.201
0.112
0.029
Species-environment correlations :
0.903
0.990
0.968
0.886
Variance of species data :
37.2
59.9
72.6
75.8
of species-environment relation :
46.9
75.4
91.4
95.5
Cumulative percentage
Sum of all eigenvalues :
0.886
Sum of all canonical eigenvalues :
0.704
Figure 5.59
(a) Scatter diagram produced by a Canonical Correspondence Analysis (CCA)
ordination showing the position of the annual species (23 species) relative to the years and rainfall in
the Koperberg Plains line transect. The red x-marks represent the years and the blue crosses the
species. 1Q = rainfall from January to March of the current year, 2Q = rainfall from April to June of
the current year, Summer = rainfall from October to December of the previous year plus January to
March of the current year, Winter = rainfall from April to August of the current year, Prev Win =
rainfall from April to September of the previous year and Annual = the annual rainfall of the current
year. (b) Details of the CCA ordination.
119
5.5.5
Grazing Capacity
The grazing index method (GIM) as proposed by Du Toit (1996) for the Karoo veld was applied to
calculate the grazing capacity of the vegetation on the Koperberg Plains line transect. The method
involves calculating the veld condition score and compares this value with a benchmark with a
known grazing capacity, to calculate the grazing capacity of the range under consideration.
The fluctuations in veld condition score and consequently grazing capacity did not show directional
2
trends (Figure 5.60). No improvement in grazing capacity (r = 0.0073) could be demonstrated.
y = -0.4278x + 80.331
R 2 = 0.0073
Grazing capacity (ha/LSU)
120
100
80
60
40
20
0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Figure 5.60
The grazing capacity (ha/LSU) throughout the monitored years for the vegetation
occurring in the Koperberg Plains line transect where LSU = Large Stock Unit.
120
5.6
T’ganagas Plains
5.6.1
Rainfall
The rainfall at the T’ganagas Plains line transect is the same as that of the Koperberg Plains and is
illustrated in Figure 5.50. The annual rainfall showed the increase in rainfall during the last two
monitored years and an approximately threefold range from 95 mm up to 304 mm rain.
5.6.2
Frequency of occurrence of annual and perennial species
The frequency of occurrence of the perennial species was low throughout and did not reveal any
changes in a specific direction at the T’ganagas Plains line transect over time (Figure 5.61). In
contrast, the frequency of the annual species showed a very clear relationship with the winter rainfall
(Figure 5.62). It was clear that the frequency of strikes of the annual species far exceeded that of the
perennial species. The vegetation at this line transect therefore comprises mostly annual vegetation.
300
90
80
250
200
60
50
150
40
100
30
Frequency (%)
Rainfall (mm)
70
20
50
10
0
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Winter
Summer
Annual
Perennial
Figure 5.61 The frequency of strike of the annual and perennial species and the winter and summer
rainfall during the monitored years for the T’ganagas Plains line transect. The blue line represents
the perennial species, whereas the red line represents the annual species. The summer rainfall
stretches from October to December of the previous year and January to March of the current year,
whereas the winter rainfall includes the rainfall from April to August of the current year.
121
100
y = 0.3218x + 6.2268
R2 = 0.6819
90
80
Frequency (%)
70
60
50
40
30
20
10
0
0
50
100
150
200
250
300
Rainfall (mm)
Figure 5.62 The regression of the winter rainfall against the frequency of annual species for the
T’ganagas Plains line transects.
5.6.3
Species and life form diversity
Species richness
The species richness of the perennial species (Figure 5.63) did not reveal a directional change
during the monitored years. The species richness of the annual species revealed large fluctuations.
2
There was a weak correlation (r =0.252) between the species richness of the annual species and
the total annual rainfall, but no relationship between perennial species richness and total annual
2
rainfall (r = 0.078). There was a strong correlation between the frequency of occurrence of the
2
annual species and their richness (r = 0.65; Figure 5.64).
Table 5.6 indicates that the most prevalent life forms for the T’ganagas Plains line transect were the
therophytes and the chamaephytes.
Diversity measures
The Shannon index (H) mirrored the species richness trends (Figure 5.65a). Where the number of
species was used as a measure of the abundance of growth forms (Figure 5.65b) the diversity
measures showed an increase in the years with a low winter rainfall. A different trend was observed
when the number of strikes was used as a measure of the abundance of the growth forms (Figure
5.65c) in which case there seems to be a decline in diversity. In Figure 5.65a and b the changes
were not directional but depended primarily on the amount of winter rainfall. However, in Figure
5.65c there appeared to be a decline in the diversity parameters over time.
122
Table 5.6 Number of species per life form occurring at the T’ganagas Plains line transect
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
1997
0
0
0
2
0
0
0
2
1
1
1
1
0
0
0
23
3
1998
0
0
0
4
1
0
0
3
2
1
2
2
0
0
0
10
2
1999
0
0
0
2
0
1
0
1
0
1
1
1
0
0
0
3
2
2000
0
0
0
3
0
1
0
2
1
1
2
2
0
0
0
12
2
2001
0
0
0
3
0
1
0
2
1
1
2
2
0
0
0
20
2
2002
0
0
0
4
0
1
0
3
2
1
2
2
0
0
0
14
1
2003
0
0
0
1
0
0
0
1
0
1
1
1
0
0
0
1
3
123
2004
0
0
0
1
0
0
0
1
0
1
1
1
0
0
0
16
3
2005
0
0
0
1
0
0
0
1
0
1
2
2
0
0
0
11
1
2006
0
0
0
2
1
0
0
1
0
1
1
1
0
0
0
23
2
2007
0
0
0
3
2
0
0
1
0
1
1
1
0
0
0
20
2
30
Species number
25
20
15
10
5
0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Time (years)
Annuals
Perennials
Total
Figure 5.63 The species richness of annual and perennial species as well as total species richness
during the past monitored years for the T’ganagas Plains line transect.
25
Species richness
20
y = 0.212x + 4.5161
15
R2 = 0.6471
10
5
0
0
20
40
60
80
100
Frequency (%)
Figure 5.64 The regression of the frequency of strike for the annual species against the annual
species richness for the T’ganagas Plains line transect.
5.6.4
Species composition
Individual species
The most abundant perennial species at the T’ganagas Plains line transect was Psilocaulon
2
junceum (Appendix 8.6). This unpalatable species revealed a decrease (r = 0.42) over the
monitored years (Figure 6.66a). In general the annual species showed large fluctuations in
abundance (Figure 6.66b).
124
a.
2.5
Index value
2
1.5
1
0.5
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Tim e (years)
E
b.
H
D
1.6
1.4
1.2
Index value
1
0.8
0.6
0.4
0.2
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
E
c.
H
D
1.4
1.2
Index value
1
0.8
0.6
0.4
0.2
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
E
H
D
Figure 5.65 The diversity measures of (a) the first strikes of all species, using (b) the number of
species in the different life forms and (c) the number of strikes in the different life forms, in the
T’ganagas Plains line transect. E = species evenness, H = Shannon’s diversity index and D =
Simpson’s diversity index.
125
a.
7
Frequency (%)
6
5
4
y = -0.5173x + 5.94
R2 = 0.4175
3
2
1
0
1998
1997
1999
2000
2001
2002
2003
2004
2005
2006
2007
Tim e (years)
Psilocaulon junceum
b.
35
30
y = 1.1045x + 0.8273
R2 = 0.2246
Frequency (%)
25
y = -0.5818x + 16.973
R2 = 0.0182
20
y = 0.4855x + 2.1691
R2 = 0.0651
15
10
5
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Time (years)
Galenia sarcophylla
Heliophila sesselifolia
Lotononis brachyloba
Figure 5.66 Changes in frequency of (a) Psilocaulon junceum and (b) selected annual species at
2
2
T’ganagas Plains line transect (Galenia sarcophylla, r = 0.07; Heliophila sesselifolia, r = 0.22;
2
Lotononis brachyloba, r = 0.02).
Community composition
The Correspondence Analysis (CA) scatter diagram of data of all the species in the T’ganagas
Plains line transect revealed that changes did occur (Figure 5.67), however it was difficult to detect a
clear direction in the changes in the total species composition for the monitored years.
Perennial species composition
The perennial species of the T’ganagas Plains line transect (Figure 5.68a) did not reveal a clear
gradient as time proceeded.
126
1.0
05
a.
Aizo can
Trib zey
Mese gue
99
Herm dis
Dros his
Hype sal
98
Gale sar
Manu gil Heli tin
Phyl occ
02 Sene car
07
Onco gra Gaza lic
Zalu ben
04
Less dif
Lyci cin
Heli ses
Heli 1jr 06
Wahl pro Cler pap
Oxal spp
Manu che
Sene are
Leys ten
Psil jun
Karr sch Cras thu
Gale nam Herm tom
Fove dic
Sute tri
Poly col Arct fas Hirp ech
Dimo sin
Geop
00
Coni elo
Dimo pol Gymn lin
Trac bul
Gaza ten
Loto bra
Pela red 97
Grie hum
Phar dic 01
Oste pin
Bulb suc
-1.0
03
-0.6
0.6
b. Axes :
1
Eigenvalues :
2
0.502 0.291
3
4
Total inertia
0.135
0.108
1.323
70.1
78.3
Cumulative percentage
Variance of species data :
Sum of all eigenvalues
38.0
:
59.9
1.323
Figure 5.67 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of all species (47 species) relative to the monitored years for the T’ganagas Plains line
transect. The red x-marks represent the years and the blue crosses the species. (b) Details of the
CA ordination.
127
1.0
07
Lyci cin
a.
04
Herm dis
02
Heli tin
Dros his
Psil jun
01
Coni elo
Herm tom
98
03
97
00
Hype sal
05
Gale nam
-0.2
06
99
-0.4
b.
Axes :
Eigenvalues :
1.0
1
2
3
4
0.345 0.282 0.194 0.147
Total inertia
1.058
Cumulative percentage
Variance of species data :
32.6
59.2
Sum of all eigenvalues :
77.6
91.5
1.058
Figure 5.68 (a) Scatter diagram produced by a Correspondence Analysis (CA) ordination showing
the position of the perennial species (9 species) relative to the monitored years for the T’ganagas
Plains line transect. The red x-marks represent the years and the blue crosses the species. (b)
Details of the CA ordination.
Annual species composition
The Canonical Correspondence Analysis indicated that most of the annual species occurring on the
T’ganagas Plains line transect showed a strong association with the winter rainfall (Figure 5.69). The
annual species occurring in this line transect, however, showed no directional trend in species
composition over the monitored years. There were fluctuations in the annual species composition
because these species react towards the rainfall. There was a low (near to zero) correlation of
summer rainfall with the winter and second quarter rainfall.
128
1.0
05
a.
Aizo can
1Q
Trib zey
Mese gue
99
98
Summer
Annual
2Q
04
Manu gil
Phyl occ
Cler pap
Gale sar
Less dif
02
Prev Win
Wahl pro 07
Zalu ben
Karr sch
Gaza lic
Onco gra
Winter
Heli 1jr
Sene car
06 Manu che
Leys ten
Sene are
Gymn lin
Heli ses
Poly col
Fove dic
Cras thu
Dimo pol Arct fas
Dimo sin
Hirp ech
Sute tri
Gaza ten
00
Oste pin
Grie hum
Loto bra
Phar dic
97
Pela red
-0.6
01
03
-0.8
b.
b.
Axes :
0.6
1
2
3
4
Eigenvalues :
0.526 0.302
0.098
0.054
Species-environment correlations :
0.997 0.993
0.973
0.965
of species data :
45.9
72.2
80.8
85.5
of species-environment relation:
50.8
80.0
89.5
94.6
Total inertia
1.145
Cumulative percentage variance
Sum of all eigenvalues :
1.145
Sum of all canonical eigenvalues :
1.034
Figure 5.69 (a) Canonical Correspondence Analysis (CCA) scatter diagram showing the position of
34 annual species relative to the years and rainfall in the T’ganagas Plains line transect. The red xmarks represent the years and the blue crosses the species. 1Q = rainfall from January to March of
the current year, 2Q = rainfall from April to June of the current year, Summer = rainfall from October
to December of the previous year plus January to March of the current year, Winter = rainfall from
April to August of the current year, Prev Win = rainfall from April to September of the previous year
and Annual = the annual rainfall of the current year. (b) Details of the CCA ordination.
129
5.6.5
Grazing Capacity
The grazing index method (GIM) was applied to calculate the grazing capacity of the vegetation on
the T’ganagas plains (Du Toit 1996). The method involves calculating the veld condition score and
by comparing this value with a benchmark with a known grazing capacity, the grazing capacity of the
range under consideration can be calculated. The fluctuations in grazing capacity did not show
2
directional trends (r = 0.0973; Figure 5.70) and no improvement in grazing capacity could be
demonstrated, however, a sudden decrease took place in 1999.
3000
Grazing Capacity (ha/LSU)
2500
2000
1500
y = -70.487x + 768.68
1000
R 2 = 0.0973
500
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
-500
Time (years)
Figure 5.70
The grazing capacity (ha/LSU) throughout the monitored years for the vegetation
occurring in the T’ganagas Plains line transect. LSU = Large Stock Unit.
130
5.7
Zebrawater Foothills
5.7.1
Rainfall
Figure 5.71 shows the fluctuation in the rainfall at the Zebrawater Foothills line transect with an
increase in rainfall during the last three monitored years. The annual rainfall varied approximately
sevenfold from 53.50 mm up to 334.90 mm rain. Fluctuations in annual rainfall are a common
feature in semi-arid and arid environments. The winter rainfall was much higher than the summer
rainfall, indicating that the area was situated in a winter rainfall region.
400
350
Rainfall (mm)
300
250
Winter
200
Summer
Total
150
100
50
0
74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Figure 5.71
The rainfall during the monitored years at the Zebrawater Foothills line transect.
Summer = rainfall in the summer months (January to March and October to December of the current
year), Winter = rainfall in the winter months (April to September) and Total = the total annual rainfall
(January to December)
5.7.2
Frequency of occurrence of annual and perennial species
The frequency of occurrence of the perennial species revealed an increasing trend at the
Zebrawater Foothills line transect over time, except in the last year of surveying (Figure 5.72).
Unfortunately, the recording of annual species did not take place in the Zebrawater Foothills line
transect from 1984 to 1989 and hence the relationship between the frequency of the annual species
with the winter rainfall did not included those years (Figure 5.73).
131
300
50
45
250
40
Rainfall (mm)
30
150
25
20
100
Frequency (%)
35
200
15
10
50
5
0
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Rainfall (winter)
Rainfall (summer)
Annuals
Perrenials
Figure 5.72 The frequency of strike of the annual and perennial species and the winter and summer
rainfall during the monitored years for the Zebrawater Foothills line transect. The blue line
represents the perennial species, whereas the red line represents the annual species. The summer
rainfall stretches from October to December of the previous year and January to March of the
current year, whereas the winter rainfall includes the rainfall from April to August of the current year.
Except in the last year (2007), the frequency of strikes of the perennial species exceeded that of the
annual species and the vegetation at this line transect therefore comprised mostly perennial
vegetation.
y = 0.0711x - 4.3832
R2 = 0.3835
35
30
Frequency (%)
25
20
15
10
5
0
0
50
100
150
200
250
300
-5
Rainfall (mm)
Figure 5.73 The regression of the winter rainfall against the frequency of annual species for the
Zebrawater Foothills line transects.
132
5.7.3
Species and life form diversity
Species richness
The species richness of the perennial species (Figure 5.74) did not reveal clear changes in a
specific direction. The species richness of the annual species revealed large fluctuations. In general,
the correlation between the species richness of the annual species and the total annual rainfall was
2
2
more positive (r = 0.2152) than that of perennial species richness and total annual rainfall (r =
0.1595). There was a strong correlation between the frequency of occurrence of the annual species
2
and annual species richness (r = 0.67; Figure 5.75).
Table 5.7 shows that the most prevalent life forms for the Zebrawater Foothills line transect were the
therophytes and the chamaephytes.
Diversity measures
The evenness (E) and Simpson’s index of diversity (D) remained almost unchanged over the
monitoring period whereas the Shannon index (H) mirrored the species richness trends (Figure
5.76a). A similar trend for the Shannon index of diversity was observed when the number of strikes
was used as a measure of the abundance of the growth forms (Figure 5.76c). Where the number of
species was used as a measure of the abundance of growth forms (Figure 5.76b) the diversity
measures showed a slight increase in the years with a low winter rainfall. In all three graphs (Figures
6a-c) the changes were not directional but depended primarily on the amount of winter rainfall.
133
Table 5.7 Number of species per life form occurring at the Zebrawater Footfills line transect
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
Phanerophytes (P)
NP scap
NP caesp
Chamaephytes (Ch)
Ch frut
Ch suff
Ch herb
Ch succ
Ch l succ
Ch st succ
Hemicryptophytes (H)
H caesp
H rept
H ros
Liana (L)
Therophytes (T)
Geophytes (G)
1974
0
0
0
14
6
0
0
8
6
2
0
0
0
0
0
3
0
1994
0
0
0
23
8
1
0
14
11
3
3
3
0
0
0
6
3
1975
2
0
2
17
8
1
0
8
6
2
2
2
0
0
0
15
0
1995
1
0
1
25
10
1
0
14
11
3
4
3
1
0
0
16
1
1976
2
0
2
21
9
1
0
11
9
2
5
4
1
0
0
20
1
1996
2
0
2
23
10
1
0
12
9
3
3
3
0
0
0
7
1
1977
1
0
1
21
8
1
0
12
9
3
3
2
0
1
0
20
1
1997
2
0
2
25
11
0
0
14
11
3
2
2
0
0
0
4
2
1978
2
0
2
18
8
1
0
9
8
1
1
1
0
0
0
0
0
1998
1
0
1
21
9
0
0
12
9
3
1
1
0
0
0
3
0
1979
0
0
0
22
10
0
0
12
10
2
0
0
0
0
0
2
1
1999
3
0
3
21
10
0
0
11
9
2
1
1
0
0
0
6
0
1980
0
0
0
18
9
0
0
9
7
2
1
1
0
0
1
15
0
2000
2
0
2
19
9
1
0
9
7
2
0
0
0
0
0
4
0
134
1982
0
0
0
18
7
0
0
11
8
3
1
1
0
0
0
1
0
2001
2
0
2
23
12
1
0
10
8
2
2
2
0
0
0
13
2
1984
1
0
1
21
9
0
0
12
9
3
2
1
1
0
0
0
0
2002
2
0
2
24
10
1
0
13
10
3
3
2
1
0
0
14
1
1985
3
0
3
19
7
0
0
12
9
3
0
0
0
0
0
0
0
2003
2
0
2
20
5
0
0
15
12
3
1
1
0
0
0
1
1
1986
2
0
2
22
10
0
0
12
9
3
3
1
1
1
0
0
0
2004
2
0
2
21
7
1
0
13
11
2
2
2
0
0
0
3
1
1987
1
0
1
19
9
0
0
10
7
3
1
1
0
0
1
0
0
2005
2
0
2
21
8
1
0
12
10
2
1
1
0
0
0
13
1
1989
2
0
2
23
9
1
0
13
10
3
1
1
0
0
0
0
0
2006
2
0
2
21
10
0
0
11
9
2
4
3
1
0
0
21
1
1990
1
0
1
22
10
0
0
12
9
3
2
1
1
0
0
1
0
2007
1
0
1
19
11
0
0
8
6
2
2
2
0
0
1
25
1
60
Species numbers
50
40
30
20
10
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Years (time)
Annual
Perennial
Total
Figure 5.74 The species richness of annual and perennial species as well as total species
richness during the past monitored years for the Zebrawater Foothills line transect.
40
y = 1.0946x + 4.1835
2
R = 0.6725
Species richness
35
30
25
20
15
10
5
0
0
5
10
15
20
25
30
35
Frequency (%)
Figure 5.75 The regression of the frequency of strike for the annual species against the annual
species richness for the Zebrawater Foothills line transect.
135
5.7.4
Species composition
Individual species
The most abundant species at the Zebrawater Foothills were the perennial plant species
Eriocephalus microphyllus, Ruschia brevibracteata, Ruschia elineata and Tripteris sinuata
(Appendix 8.7). Ruschia brevibracteata and Ruschia elineata, both unpalatable species, showed
2
2
a decreasing trend in frequency (r = 0.33; r = 0.79) over the monitored years (Figure 5.77a),
whereas Eriocephalus microphyllus and Tripteris sinuata, both palatable species, revealed an
2
2
increasing trend (r = 0.51; r = 0.66; Figure 5.77b-c). This change is an indication of veld
recovery. In general the annual species showed large fluctuations in abundance.
Community composition
The Correspondence Analysis (CA) scatter diagram of data of all the species in the Zebrawater
Foothills line transect revealed that changes did occur (Figure 5.78). The ordination of the total
species composition of the Zebrawater Foothills line transect showed that most of the monitored
years were clustered, and most of the species were associated with these years. No progression
with time in a particular direction was present although a gradient stretched from the top at 1976
downwards, and another one from the 1970s to the right. The outstanding years were 1976, 2006
and 2007 each with only a few species associated with them. Two gradients were therefore
present, one along the X- and one along the Y-axis. The high rainfall in 1976 and the
exceptionally high summer rainfall component could possibly explain the position of this year
along the Y-axis. The exceptionally high winter rainfall component in 2006 and 2007 could
possibly explain their position along the X-axis.
136
a.
3.5
3
Index value
2.5
2
1.5
1
0.5
2007
2006
2005
2004
2003
2002
2001
2000
1998
1998
1999
1997
1997
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
1974
0
Time (years)
E
b.
H
D
2
1.8
1.6
Index value
1.4
1.2
1
0.8
0.6
0.4
0.2
2007
2006
2005
2004
2003
2002
2001
2000
1999
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
1974
0
Tim e (years)
E
c.
H
D
1.6
1.4
Index value
1.2
1
0.8
0.6
0.4
0.2
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
1974
0
Time (years)
E
H
D
Figure 5.76 The diversity measures of (a) the first strikes of all species, (b) the number of
species in the different life forms and (c) the number of strikes in the different life forms, in the
Zebrawater Foothills line transect. E = species evenness, H = Shannon’s diversity index and D =
Simpson’s diversity index.
137
a.
2.5
2
y = -0.0252x + 0.771
R2 = 0.3275
Frequency (%)
1.5
y = -0.051x + 1.4377
R2 = 0.7938
1
0.5
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
-0.5
Time (years)
Ruschia brevibracteata
b.
Ruschia elineata
2
y = 0.0321x + 0.5791
R2 = 0.6592
1.8
Frequency (%)
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Tripteris sinuata
c.
y = 0.1171x + 2.8752
R2 = 0.5062
8
7
Frequency (%)
6
5
4
3
2
1
0
74 75 76 77 78 79 80 82 84 85 86 87 89 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07
Time (years)
Eriocephalus microphyllus
Figure 5.77
Changes in frequency of selected (a) unpalatable perennial species and (b&c)
palatable species at Zebrawater Foothills line transect.
138
1.0
a.
Chae inv 76 Sela div
Aizo can
Grie hum
Gale sar
Trip amp
Arct fas
Ursi cal
Heli cor
Loto bra
Ursi nan
Disc spi
Trip hyo
Dimo sin
Phar aur
Leys ten
Ehrh cal
Ehrh bar
Herm tri
75
77
Lamp god
06
Manu che
Heli var
Rusc eli
Cype kle
Iflo reg
Heli leo
Lasi mic
Ehrh del
Wahl ann
Manu gil Cotu nud
Apto spi
Cyph sp.
Brom jap 07 Heli blo
Wahl an2
-0.2
Tetr fru
Wahl pro
Hirp ali
80
Feli nam
Gale
afr
Erio mic
Rusc bre
Oxal
spp
05
95
Cras sub
Euph mau
93
Pent air
Pent inc
Leip sch
Zalu ben
Hemi rac
78 Rusc rob
Euph
dec Karr sch Tyle wal
74
89
Trip sin
Sene car
Cras thu
84 86
01 02
Onco suf
Psil jun
Cras mus Herm dis
90
03 94 96
98
Lebe ser 91
97 04
87 99 00
82 79 85
-0.2
b.
1.0
Axes :
Eigenvalues :
1
2
3
4
Total inertia
0.296
0.187
0.107
0.076
1.093
27.1
44.2
54.0
61.0
Cumulative percentage
Variance of species data :
Sum of all eigenvalues :
Figure 5.78
1.093
(a) Scatter diagram produced by a Correspondence analysis (CA) ordination
showing the position of 63 most important species, of the total 137 species relative to the
monitored years, for the Zebrawater Foothills line transect. The red x-marks represent the years
and the blue crosses the species. (b) Details of the CA ordination.
139
Perennial species composition
When only the floristic data of the perennial species was used in the Correspondence Analysis
(Figure 5.79) directional changes in species composition over the monitored years were evident.
The changes occurred from the upper left side of the ordination space to the lower centre of the
ordination space as indicated by the arrow in Figure 5.80. Many species can be associated with
0.6
the earlier years whereas the more recent years are only correlated with a few species.
93
a.
77
78
Pter div
Apto ind
Chry cil
Heli tin
75
76
Chae inv
Sela div
80
74
Phar aur
Rusc bre
Othe uni
Rusc eli
Ehrh bar
84
Peli vir
95
Scir nod
86 87
Zygo
foe
82
Lyci
cin
79
rob
89 Rusc
Ceph ebr
85
94
Pent inc Euph mau
Lamp god 90 Tetr fru
91
Gale afr
Chei den
Tyle wal
Gale nam
Leip sch
Erio mic
Herm dis
Wibo mon
Trip sin 98
Euph dec
96
00
Lebe ser
01
Cras sub
97
Lyci oxy
Zygo sp.
99
Cype kle
-0.6
03
05
07
Pren pal
Dros bos
Cype
06
02
Groe vyg
Apto spi
Vygi vet
04
-0.6
1.0
b.
Axes :
Eigenvalues :
1
2
3
4
Total inertia
0.078
0.060
0.041
0.033
0.402
19.4
34.4
44.7
52.9
Cumulative percentage
variance of species data :
Sum of all eigenvalues :
0.402
Figure 5.79 (a) Scatter diagram produced by a Correspondence Analyis (CA) ordination showing
the position of the 42 most important perennial species (of the total 68 perennial species) relative
to the monitored years for the Zebrawater Foothills line transect. The red x-marks represent the
years and the blue crosses the species. (b) Details of the CA ordination.
140
0.6
93
77
78
75
74 80
76
79
84 87 89
86
82
85
90
91
95
02
94
98
96
00
97
99
06
01
05
07
03
-0.6
04
-0.6
1.2
Figure 5.80 Scatter diagram produced by a Correspondence Analysis (CA) ordination indicating
the change occurring over the monitoring period, where the arrow indicates the progress in years,
in the Zebrawater Foothills line transect.
Annual species composition
Most of the annual species occurring on the Zebrawater Foothills line transect did not show a
strong association with the winter rainfall (Figure 5.81). The annual species occurring in the
Zebrawater Foothills line transect also showed no directional trend in species composition over
the monitored years. However, there were fluctuations in the annual species composition
because these species react towards the rainfall. There was a low (near to zero) correlation of
summer rainfall with the winter and second quarter rainfall. Several annual species such as
Wahlenbergia annularis, Cotula sp., Bromus japonicus, Heliophila sp. and Manulea gilioides had
a strong correlation with the winter rainfall and were also associated with 2007, a year with
exceptionally high winter rainfall.
141
1.0
79
a.
80
Heli ses
Sile cap
03
Cler pap
82
Hirp ech
Tetr mic
00
77
Less dif
01
04
74
99
Dias nam
Ursi cak
98
Aden glo
Doro bel
Iflo par
Cotu lep
Hemi rac
Phyl occ Mese gue
Brom pec
Heli cor
Cras
thu
Otho per 93
Plan caf
Iflo glo Fove dic
75
90
Karr sch
95
Dimo sin
Poly col
02
Leys ten
91 Manu che
96
05
Feli nam
Zalu gil
Pent air
Loto fal
Heli var 94
Disc spi Trib utr
Onco suf
Ehrh lon
Sene car Wahl pro
Zalu ben
Lasi mic
Heli leo
Arct fas
06
Cotu gee
Trip hyo
Onco gra
Loto bra
Ehrh del
Summer
Ursi nan Ursi cal
Iflo reg
Wahl ann
Cotu gee
Brom jap
Heli blo
Wahl an2 07
Manu gil
Trip amp
97
Grie hum
Aizo can
76
Gale sar
1Q
Winter
2Q
Prev Win
-1.0
Annual
-0.6
Axes
b.
1.0
:
1
2
3
4
Eigenvalues :
0.486 0.363
0.213
0.145
Species-environment correlations :
0.964 0.927
0.795
0.765
variance of species data :
11.6
20.3
25.3
28.8
of species-environment relation :
36.2
63.3
79.1
89.9
Total inertia
4.191
Cumulative percentage
Sum of all eigenvalues :
4.191
Sum of all canonical eigenvalues :
1.342
Figure 5.81 (a) Canonical Correspondence Analysis (CCA) scatter diagram showing the position of
60 annual species relative to the years and rainfall in the Zebrawater foothills line transect. The red xmarks represent the years and the blue crosses the species. 1Q = rainfall from January to March of
the current year, 2Q = rainfall from April to June of the current year, Summer = rainfall from October
to December of the previous year plus January to March of the current year, Winter = rainfall from
April to August of the current year, Prev Win = rainfall from April to September of the previous year
and Annual = the annual rainfall of the current year. (b) Details of the CCA ordination.
142
5.7.5
Grazing Capacity
The grazing capacity showed a general increase over the monitored years, with the exception of
2007 where the grazing capacity showed a sudden decline (Figure 5.82). This improvement in
2
grazing capacity (r = 0.49) supported the general trends observed by the increase in palatable
species and decrease in unpalatable species (Figure 5.77).
Grazing capacity score (ha/LSU)
80
y = -0.7763x + 59.719
2
R = 0.4903
70
60
50
40
30
20
10
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1991
1990
1989
1987
1986
1985
1984
1982
1980
1979
1978
1977
1976
1975
1974
0
Time (years)
Figure 5.82
The veld condition score throughout the monitored years for the vegetation
occurring in the Zebrawater Foothills line transect where LSU = Large Stock Unit.
143
CHAPTER 6
DISCUSSION AND CONCLUSIONS
6.1
Introduction
Overgrazing is believed to have degraded as much as two-thirds of the Succulent Karoo
(http://www.skep.org) and is one of the largest threats to this global hotspot of biodiversity (Hendricks
et al. 2005, 2007). Understanding the process of natural vegetation recovery after severe
overstocking, and the rate at which it occurs may assist in developing techniques that could enhance
the natural recovery process. The current study in the Goegap Nature Reserve therefore set out to
assess the changes in the vegetation, in terms of species composition, species richness and life form
richness, in seven long-term monitoring transects. Of prime importance was to answer the question
whether the veld condition had improved since the removal of the livestock. However, because the
wildlife that had been reintroduced into the reserve had increased in numbers, concern was being
expressed that wildlife were now overutilising the vegetation and causing a deterioration in condition.
The study therefore also intended to provide practical management recommendations on stocking
density of wildlife on the reserve.
6.2
Vegetation trends
6.2.1
Bleshoek Plains
The Bleshoek Plains line transect is located in the Galenia sarcophylla – Mesembryanthemum
guerichianum dwarf sparse shrubland sub-community and the Psilocaulon absimile – Zygophyllum
retrofractum low sparse shrubland community (Rösch 2001a) and represents management unit 3. Up
to 1990, it was part of the neighbouring Goegap farm and was grazed heavily by livestock. From 1990
to 2002 the fence between the old reserve section (Hester Malan) and the Goegap section was kept
intact and no wildlife grazed in the area. The line transect was established in 1991 since when it has
been regularly monitored.
In general, the perennial component of the vegetation showed little changes in the frequency of
occurrence and the species richness. The annual component, on the other hand, showed large
fluctuations depending on the timing and the amount of rainfall. These fluctuations were evident in
terms of the frequency of occurrence, species richness and composition. Some species showed a
clear preference for summer rainfall but most species were associated with winter rainfall and second
quarter rainfall. The perennial species composition revealed directional change as the years
144
progressed, where the unpalatable species Ruschia robusta decreased in the last few years. This
change is an indication of veld recovery. However, the decrease of some of the palatable perennial
grass species (Stipagrostis obtusa and S. brevifolia) showed the opposite trend, specifically after the
fence was removed. During the last four years when the wildlife was still excluded, the grazing
capacity improved. However, in the year after the fence was removed, it worsened. The removal of
the fence coincided with the years with very low winter rainfall as the only rain that occurred was at
the end of the growing season in spring. Changes in the life form diversity were not directional but
depended mainly on the winter rainfall, with the Shannon index of the life forms increasing with a low
winter rainfall. However, the opposite trend appeared for the number of strikes.
6.2.2
Bluemine Mountain
The Bluemine Mountain line transect is located in the Searsia undulata tall sparse shrubland and
Leipoldtia schultzei short open shrubland communities and represents management unit 10. This line
transect formed part of the older, Hester Malan section, and was heavily grazed by livestock until
1969 when the reserve was fenced and the livestock excluded. This line transect was established in
1974 since when it has been regularly monitored.
The perennial component of the vegetation showed a slight increase in the frequency of occurrence
but did not reveal definite changes in species richness. As was the case for the Bleshoek Plains line
transect, the annual component showed fluctuations in frequency of occurrence, species richness
and composition. Most species did not show a preference for high winter rainfall. Although most
annual species did not show a clear preference for high winter rainfall, more annual species were
associated with the winter rainfall than with the summer rainfall. There was a directional change from
the earlier to the more recent years in the perennial species composition, with only a few species
associated with the more recent years, indicating that the vegetation occurring during the earlier
years contained a larger component if unpalatable species left after the heavy grazing by livestock
until 1969. The increase in several palatable species and the decrease in several unpalatable species
are an indication of veld recovery. The veld condition score therefore revealed a steady increase, and
indicates improvement in the grazing capacity. Changes in the life form diversity were not directional
but depended mainly on the winter rainfall, with the Shannon index of the life forms decreased with a
low winter rainfall. However, a different trend appeared for the number of strikes for the life forms,
where there seemed to be a gradual decline in diversity.
6.2.3
Goegap Plains
The Goegap Plains line transect is located in the Tripteris sinuata short open shrubland community
and represents management unit 5. Up to 1990, it was part of the neighbouring Goegap farm and
was grazed heavily by livestock. From 1990 to 2002 the fence between the old reserve section
145
(Hester Malan) and the Goegap section was kept intact and no wildlife grazed in the area. The line
transect was established in 1991 since when it has been regularly monitored.
Similar to the Bleshoek Plains line transect, the perennial component of the vegetation showed little
changes in the frequency of occurrence and the species richness. The annual species component, on
the other hand, showed large fluctuations depending on the timing and the amount of rainfall. As was
the case for the Bluemine Mountain line transect, most species did not show a preference for high
winter rainfall. Some species, however, preferred high summer or first quarter rainfall. The perennial
species composition did not indicate a change in direction as time proceeded, neither did the veld
condition show any trend in a specific direction and therefore no improvement in grazing capacity
could be demonstrated. The low grazing capacity during 2003 was due to the low winter rainfall at the
end of the growing season. However, several unpalatable species showed a decreasing trend, this
indicating veld recovery. Changes in the life form diversity were not directional but depended mainly
on the winter rainfall, where the Shannon index of diversity of the life forms (based on the number of
species) increased with a low winter rainfall. However, a different trend appeared for the number of
strikes, where the Shannon index of diversity showed a gradual decline throughout the last couple of
monitored years.
6.2.4
Jaleeg Plains
The Jaleeg Plains line transect is situated in the Drosanthemum hispidum – Mesembryanthemum
guerichianum dwarf sparse shrubland subcommunity, Psilocaulon junceum low sparse shrubland and
Stipagrostis brevifolia short sparse shrubland and represents management 7. Up to 1990, it was part
of the neighbouring Goegap farm and was grazed heavily by livestock. From 1990 to 2002 the fence
between the old reserve section (Hester Malan) and the Goegap section was kept intact and no
wildlife grazed in the area. The line transect was established in 1991 since when it has been regularly
monitored.
Similar to the Bluemine Mountain line transect, the perennial component of the vegetation revealed
an upward trend in the frequency of occurrence over time, however, no definite changes were
revealed in the species richness. The frequency of the annual species showed a weak relationship
with the winter rainfall, and no directional trend in composition, however, large fluctuations were
revealed in the annual species richness. The perennial species composition did not reveal directional
change as time proceeded. The improved veld condition gradually throughout the monitored years,
therefore the grazing capacity improved. As was the case for the Bleshoek Plains line transect, the
changes in the life form diversity were not directional but depended mainly on the winter rainfall,
where the Shannon index of diversity of the life forms increased with a low winter rainfall. However,
the opposite trend appeared for the number of strikes for the life forms.
146
6.2.5
Koperberg Plains
The Koperberg Plains line transect is situated in the Psilocaulon junceum – Drosanthemum hispidum
low sparse shrubland and Galenia sarcophylla – Mesembryanthemum guerichianum dwarf sparse
shrubland subcommunity and represents management 2. This severe degraded piece of land forms
part of the reserve since establishment of the Hester Malan Nature Reserve in 1966. It is situated
adjacent to the tailings of the Carolusberg copper mine and the soil is covered with a layer of dust
which has been blown from the tailings. There is also a dry river course running through the area and
as a result it was severely overgrazing before being incorporated into the reserve. The line transect
was established in 1997 since when it has been regularly monitored.
Similar to the Bleshoek and Goegap Plains line transects, in general, the perennial component of the
vegetation showed little changes in the frequency of occurrence and the species richness. The
annual component, on the other hand, showed large fluctuations depending on the timing and the
amount of rainfall. These fluctuations were evident in terms of the frequency of occurrence, species
richness and composition. As was the case for the Bluemine Mountain and Goegap Plains line
transect, most species did not show a preference for high winter rainfall. Some species, however,
preferred high summer rainfall. The perennial species composition revealed directional change as the
years progressed, however no improvement in veld condition and consequently grazing capacity
could be demonstrated. Changes in the life form diversity were not directional but depended mainly
on the winter rainfall, where the Shannon index of diversity of the life forms increased with a low
winter rainfall. However, a different trend appeared for the number of strikes, where the diversity
showed a gradual decline.
6.2.6
T’ganagas Plains
The T’ganagas Plains line transect is situated in the Drosanthemum hispidum – Mesembryanthemum
guerichianum dwarf sparse shrubland community and represents management 4. This line transect is
situated in the original Hester Malan Nature Reserve and was cultivated many years before the
reserve was proclaimed. Since proclamation of the Hester Malan Nature Reserve is has been one of
the preferred sites of gemsbok and springbok, especially during the summer. It has also carried large
numbers of small mammals. The line transect was established in 1997 since when it has been
regularly monitored.
Similar to the Bleshoek and Goegap Plains line transect, in general, the perennial component of the
vegetation showed little changes in the frequency of occurrence and the species richness. The
annual component, on the other hand, showed large fluctuations depending on the timing and the
amount of rainfall. These fluctuations were evident in terms of the frequency of occurrence, species
richness and composition. Some species showed a clear preference for summer and first quarter
147
rainfall but most species were associated with winter and second quarter rainfall. The perennial
species composition revealed directional change as the years progressed, where the unpalatable
species Psilocaulon junceum decreased in the last few years. This change is an indication of veld
recovery although no improvement in grazing capacity could be demonstrated, however, a sudden
decrease took place in 1999. As was the case for the Koperberg Plains line transect, changes in the
life form diversity were not directional but depended mainly on the winter rainfall, where the Shannon
index of diversity of the life forms increased with a low winter rainfall. However, a different trend
appeared for the number of strikes, where the diversity showed a gradual decline.
6.2.7
The
Zebrawater Foothills
Zebrawater
Foothills
line
transect
is
located
in
the
Drosanthemum
hispidum
–
Mesembryanthemum guerichianum dwarf sparse shrubland subcommunity, Searsia undulata tall
sparse shrubland and Leipoldtia schultzei short open shrubland communities and represents
management unit 8 and 10. Up to 1990, it formed part of the, older, Hester Malan section, and was
heavily grazed by livestock until 1969 when the reserve was fenced and the livestock excluded. This
line transect was established in 1974 since when it has been regularly monitored.
Similar to the Bluemine Mountain and the Jaleeg Plains line transects, the frequency of occurrence of
the perennial species component revealed an increasing trend (except in the last year of surveying).
As was the case for the other line transects, the annual component showed fluctuations in frequency
of occurrence, species richness and composition. Similar to the Bluemine Mountain line transect,
most annual species did not show a preference for high winter rainfall. There was a directional
change from the earlier to the more recent years in the perennial species composition, with only a few
species associated with the more recent years. An investigation of the species composition indicated
that the vegetation occurring during the earlier years contained a larger component of unpalatable
species left after the heavy grazing by livestock until 1969. The increase in several palatable species
and the decrease in several unpalatable species are an indication of veld recovery. The veld
condition score therefore revealed a steady increase, and indicates improvement in the grazing
capacity. The Shannon’s index of diversity when the number of strikes was used as a measurement
of abundance of life forms mirrored the species richness trends. The diversity measures for the
number of species for the life forms showed a slight increase with low winter rainfall years. Changes
for the diversity were not directional but depended mainly on the amount of winter rainfall.
6.3
Long-term monitoring
Long-term ecological monitoring is generally the preferred method for detecting changes of slow
phenomena, subtle and complex phenomena and episodic or rare events (Pickett 1989, Franklin
1989, Pace & Cole 1989, Burt 1994). The current study could conclusively show that because the
148
vegetation changes occurring in the Goegap Nature Reserve take place so slowly and over such a
long period that for the efficient conservation of the reserve in this invaluable ecosystem, long-term
ecological research is necessary. It is only then that vegetation changes can be detected and causeeffect relationships can be established (Pace & Cole 1989, South African Environmental Observatory
Network 2002, 2004, Krug et al. 2006). The long time span over which long-term monitoring records
have been gathered at the Goegap Nature Reserve has ensured that both exceptionally wet and
exceptionally dry years have been incorporated in the period. The long-term monitoring of the line
transects has improved our understanding of the functioning of this ecosystem, enabling us to create
a ‘trend-record’, and has the ability to recognise chronic and detrimental ecosystem change (natural
and anthropogenic). This improved the ecological warning capabilities, and must be used for
management and decision making on ecological issues (Van Jaarsveld & Biggs 2000). The
descending point method, that was used for monitoring each year, proved to be a rapid, repeatable
and cost-effective method (Havstad & Herrick 2003) and provided data to analyse and to reflect
various processes and functions.
The results clearly showed that the longest established, and therefore longest monitored line
transects (the Bluemine Mountain and Zebrawater Foothills line transects), gave the best indication of
directional change, demonstrating that change take place slowly in arid environments (although
degradation can happen in a short time) confirming Pickett’s statement (1989) that long-term studies
are a reliable way to determine slow processes. High levels of year-to-year variability in the
productivity (strongly linked to the precipitation level) were also revealed, showing biological
phenomena are strongly related to physical parameters (Franklin 1989). Because this ecosystem is
complex, it took long to build up a dataset for the development of useful hypotheses. It also became
evident with the use of long-term data what significant changes have an impact on the nature reserve,
such as the removal of livestock and the addition of wildlife.
6.4
Vegetation dynamics
The directional change notable in the perennial community composition over the monitored years in
several of the line transects was evidence of the occurrence of succession (Burrows 1990, GlennLewin et al. 1992, Barbour et al. 1987, Gurevitch et al. 2002). However, it is not implied that
succession proceeds on a predetermined trajectory and reaches a single climax state as traditional
succession theory predicts (Niering 1987, Krohne 2001). The results showed that non-directional
change also occurred, especially in the annual community composition and the life form diversity.
These changes are referred to as fluctuations and correlate with the rainfall, and did not result in
directional changes in plant populations. These fluctuations in rainfall lead to complex dynamics
(Richardson et al. 2005, 2007) and the dynamics are often described as being event-driven (Westoby
et al. 1989a, 1989b) or nonequilibrium/disequilibrium (Behnke & Schoones 1993, Illius & O’Connor
1998, Ward 2006).
149
Because vegetation dynamics and management are interconnected, understanding these processes
is critical to develop effective vegetation management together with sustained animal production.
Vegetation change may be a slow process in an arid ecosystem due to the high inter-annual rainfall
variation and therefore the variation in plant abundance and presence (Wiegand & Milton 1996,
Cowling et al. 1999a, Todd & Hoffman 1999, Ward 2006). The results also showed that the effects of
grazing and essential vegetation change operated irregularly (as supported by the state-andtransition model).
Therefore, the results showed, in accordance with Wiegand and Jeltsch (2000) and Ward (2006), that
the vegetation changes occurred, over the short-term, unpredictably in response to the inter-annual
variation in rainfall, and episodically, over several decades due to rare events, as well as grazing
pressure, changes in climate, altered disturbance regimes, or a combination of these factors.
6.5
Mechanisms of plant species survival
The results clearly showed that the unpredictable rainfall, in time, amount and space, is a strong
selective force influencing the life-history patterns and life cycle stages of the annual vegetation
component. The most prevalent life forms for all the line transect were the therophytes and the
chamaephytes. Drought evasion is a strategy common among these short-lived species, showing a
large degree of flexibility in their growth rate, size and phenology (Van Rooyen et al. 1990) whereas
succulence occurs mainly in perennial species.
6.6
Veld condition
The veld condition was determined with the use of the GIV (Grazing Index Values) of the plant
species according to the method developed by Du Toit (1995, 1996, 2000, 2002, 2003). This method
is a refinement of the method originally proposed for Karoo veld by Vorster (1982) and provided good
comparative estimates of grazing capacity. For the Bluemine Mountain and the Zebrawater Foothills
line transects, that had been monitored for more than 30 years, it was evident that the frequency of
perennial species increased, and that the direction of vegetation change was from a larger
component of unpalatable species in the early years to a larger component of palatable species in the
more recent years. This indicated that removal of the livestock did have a positive effect on the veld
condition and this was reflected in an improved carrying capacity. An improvement in the veld
condition could also be demonstrated at Jaleeg Plains, but not in the case of the Goegap, Bleshoek,
Koperberg and T’ganagas Plains line transects (where no directional change could be demonstrated).
Although a decrease in several unpalatable species throughout the monitored years was detected at
Koperberg Plains and T’ganagas Plains, this was not reflected in the veld condition assessment.
These line transects have only been monitored since 1997 and the period could be too short to detect
150
directional trends. The Goegap Plains, and to a lesser extent Bleshoek Plains, contains a large
component of grasses in the vegetation and is therefore an area favoured by wildlife. At both sites the
decrease in the contribution of the grass component was detected.
6.7
Conclusions and veld management recommendations
Human activities are having a major impact on the biodiversity and functioning of ecosystems in
southern Africa. The consequences of these impacts have focused attention on the need to
understand the processes of vegetation degradation but also of vegetation recovery. This study
investigated the natural vegetation recovery process after the cessation of overgrazing by livestock.
Overall, the recovery process proceeded very slowly and was primarily detected in the perennial
component of the vegetation, with the annual component reacting to rainfall.
Long-term monitoring of the line transects has provided valuable information for the management of
the Goegap Nature Reserve. Although an improvement in the carrying capacity at some sites was a
positive sign, the lack of improvement at some of the preferred sites such as Goegap Plains,
indicated that management intervention was needed. Results of the annual monitoring are indeed at
present feeding into the regulation of stocking density on the reserve.
Managers should therefore use, as indicated by Bothma et al. (2004), indicator species (sensitive to
grazing) to monitor the effect of grazing on the vegetation. It is vital to continue these developments in
veld condition in order to evaluate and adjust veld management practices. As suggested by Hurt and
Bosch (1991) the Ecological Index Method (EIM) and the Grazing Index Method (GIM), the results
indicated these are practical methods and to give answers concerning the carrying capacity.
Continuous monitoring of the line transects on a regular basis should take place, forming part of the
complex dynamics of this ecosystem.
151
CHAPTER 7
REFERENCE LIST
ABBOT, J. & GUIJT, I. 1998. Changing views on change: participatory approaches to monitoring
the environment. South African Radio League (SARL) Discussion Paper 2: 11 – 17.
ACOCKS, J.P.H. 1988. Veld Types of South Africa. Memoirs of the Botanical Survey of South
Africa 57: 1 – 145.
BARBOUR, M.G., BURK, J.H. & PITTS, W.D. 1987. Terrestrial Plant Ecology. Benjamin/
Cummings, California.
BASKIN, J.M. & BASKIN, C.C. 1989. Physiology of dormancy and germination in relation to seed
bank ecology. In: M.A. Leck, V.T. Parker & R.L. Simpson (eds) Ecology of soil seed banks.
pp. 53 – 66. Academic Press, San Diego.
BEARD,
G.R.,
SCOTT,
W.A.
&
ADAMSON,
J.K.
1999.
The
value
of
consistent
methodology in long-term environmental monitoring. Environmental Monitoring and
Assessment 54: 239 – 258.
BEHNKE, JR., R.H. & SCOONES, I. 1993. Rethinking range ecology: implications for rangeland
management in Africa. In: R.H. Behnke, I. Schoones & C. Kerven (eds) Range ecology at
disequilibrium: new models of natural variability and pastoral Adaptations in African
Savannas. pp.1 – 31. Overseas Development Institute, London.
BIGGS, H.C., KERLEY, G.I.H. & TSHIGUVHO, T. 1999. A South African long-term ecological
research network: a first for Africa? South African Journal of Science 95: 244 – 246.
BOTHMA, J. DU P. 2000. Wildplaasbestuur. Nuwe uitgebreide uitgawe. J.L. van Schaik
Uitgewers, Pretoria.
BOTHMA, J. DU P., VAN ROOYEN, N. & VAN ROOYEN M.W. 2004. Using diet and plant
resources to set wildlife stocking densities in African savannas. Wildlife Society Bulletin 32:
840 – 851.
152
BRISKE, D.D, FUHLENDORF, S.D. & SMEINS, F.E. 2003. Vegetation dynamics on rangelands:
a critique of the current paradigms. Journal of Applied Ecology 40: 601 – 614.
BURROWS, C.J. 1990. Processes of vegetation change. Chapman & Hall, London.
BURT, T.P. 1994. Long-term study of the natural environment – perceptive science or mindless
monitoring? Progress in Physical Geography 18: 475 – 496.
CONNELL, J.H., NOBLE, I.R. & SLATYER, R.O. 1987. On the mechanism producing
successional change. Oikos 50: 136 – 137.
CONNELL, J.H. & SLATYER, R.O. 1977. Mechanisms of succession in natural communities and
their role in community stability and organisation. American Naturalist 111: 1119 – 1144.
COUNCIL FOR GEOSCIENCE. Geological Vector Data 1:250 000 for the Goegap Nature
Reserve. Council for Geoscience, Pretoria.
COWLING, R.M., ESLER, K.J. & RUNDEL, P.W. 1999a. Namaqualand, South Africa – an
overview of a unique winter-rainfall desert ecosystem. Plant Ecology 142: 3 – 21.
COWLING, R.M., PIERCE, S.M. & PATERSON-JONES, C. 1999b. Namaqualand: A Succulent
Desert. Fernwood Press, South Africa.
DESMET, P.G. 2007. The diamonds of Namaqualand: an introduction to the environment and
floral diversity. Journal of Arid Environments 70: 570 – 587.
DESMET, P.G. & COWLING, R.M. 1999. The climate of the karoo – a functional approach. In:
W.R.J. Dean & S.J. Milton (eds) The Karoo. Ecological patterns and processes. pp. 3 – 16.
Cambridge University Press, Cambridge.
DU TOIT, P.V.C. 1995. The grazing index method of range condition assessment. African Journal
of Range and Forage Science 12(2): 61 – 67.
DU TOIT, P.V.C. 1996. Development of a model to estimate grazing index values for Karoo plant
species. Ph.D. thesis. University of Pretoria, Pretoria.
153
DU TOIT, P.V.C. 1998. Description of a method for assessing veld condition in the Karoo. African
Journal of Range and Forage Science 14(3): 90 – 93.
DU TOIT, P.V.C. 2000. Estimating grazing index values for plants from arid regions. Journal of
Range Management 53: 529 – 536.
DU TOIT, P.V.C. 2002. Boesmankop grazing capacity benchmark for the Nama-Karoo.
Grootfontein Agric 5: 1 – 6.
DU TOIT, P.C.V. 2003. Veld evaluation. Department of Agriculture. Grootfontein Agriculture
Development Institute.
EGLER, F.E. 1954. Vegetation science concept. I. Initial floristic composition – a factor in old-field
vegetation development. Vegetatio 4: 412 – 417.
ESLER, K.J. 1999. Plant reproductive ecology. In: W.R.J. Dean & S.J. Milton (eds) The Karoo:
ecological patterns and processes. pp. 123 – 144.
Cambridge University Press,
Cambridge.
ESLER, K.J. & RUNDEL, P.W. 1999. Comparative patterns of phenology and growth form
diversity in two winter rainfall deserts: the Succulent Karoo and Mojave Desert ecosystems.
Plant Ecology 142: 97 – 104.
ESLER, K.J., RUNDEL, P.W. & COWLING, R.M. 1999. The Succulent Karoo in a global context:
plant structural and functional comparison with North American winter-rainfall deserts. In:
W.R.J. Dean & S.J. Milton (eds) The Karoo. Ecological patterns and processes. pp. 303 –
313. Cambridge University Press, Cambridge.
FENNER, M, & THOMPSON, K. 2005. The Ecology of Seeds. Cambridge University Press,
Cambridge.
FRANKLIN, J.F. 1989. Importance and justification of long-term studies in ecology. In: G.E.
Likens (ed.) Long-term studies in ecology: approaches and alternatives. pp. 3 – 19.
Springer-Verlag, New York.
FRIEDEL, M.H. 1991. Range condition assessment and the concept of thresholds: a viewpoint.
Journal of Range Management 44: 427 – 433.
154
GLENN-LEWIN, D.C., PEET, R.K. & VEBLEN, T.T. 1992. Prologue. In: D.C. Glenn-Lewin, R.K.
Peet & T.T. Veblen (eds) Plant succession – theory and prediction. pp. 1 – 10. Chapman &
Hall, London.
GLENN-LEWIN, D.C. & VAN DER MAAREL. 1992. Patterns and processes of vegetation
dynamics. In: D.C. Glenn-Lewin, R.K. Peet & T.T. Veblen (eds) Plant succession – theory
and prediction. pp. 11 – 43. Chapman & Hall, London.
GUREVITCH, J., SCHEINER, S.M. & FOX, G.A. 2002. The Ecology of Plants. Sinauer,
Massachusetts, U.S.A.
HARPER, J.L. 1977. Population biology of plants. Academic Press, New York.
HAVSTAD, K.M. & HERRICK, J.E. 2003. Long-term ecological monitoring. Arid Land Research
and Management 17: 389 – 400.
HENDRICKS, H.H., BOND, W.J., MIDGLEY, J.J. & NOVELLIE, P.A. 2005. Plant species richness
and composition along livestock grazing intensity gradients in a Namaqualand (South
Africa) protected area. Plant Ecology 176: 19 – 33.
HENDRICKS, H.H., BOND, W.J., MIDGLEY, J.J. & NOVELLIE, P.A. 2007. Biodiversity
conservation and pastoralism – reducing herd size in a communal livestock production
system in Richtersveld National Park. Journal of Arid Environments 70: 718 – 727.
HENSCHEL, J.R.
& PAUW, J. 2002. Environmental observatories. LTER a-la-Africa. In: H.
Baijnath & Y. Singh (eds) Rebirth of science in Africa: a shared vision for life and
environmental sciences. pp.149 – 159. Umdaus Press, Pretoria.
HENSCHEL, J., PAUW, J., BANYIKWA, F., BRITO, R., CHABWELA, H., PALMER, T.,
RINGROSE, S., SANTOS, L., SITOE, A. & VAN JAARSVELD, A. 2003. Developing the
Environmental Long-term Observatories Network of South Africa (ELTOSA). South African
Journal of Science 99: 100 – 108.
HILTON-TAYLOR, C. 1996. Patterns and characteristics of the flora of the Succulent Karoo
Biome, southern Africa. In L.J.G. Van der Maeson, X.M. Van der Burgt & J.M. Van
Medenbach de Rooy (eds) Biodiversity of succulents and African arid regions. pp. 58 – 72.
Kluwer, Netherlands.
155
HURT, C.R. & BOSCH, O.J.H. 1991. A comparison of some range condition assessment
techniques used in southern African grasslands. Proceedings of the Grassland Society of
South Africa 8: 131 – 136.
ILLIUS, A.W. & O’CONNOR, T.G. 1998. On the relevance of non-equilibrium concepts to arid and
semi-arid grazing systems. Ecological Applications 9: 798 – 813.
JÜRGENS, N., GOTZMANN, I.H. & COWLING, R.M. 1999. Remarkable medium-term dynamics
of leaf-succulent Mesembryanthema (Aizoaceae)
in the
winter-rainfall desert of
northwestern Namaqualand, South Africa. Plant Ecology 142: 87 – 96.
KENT, M. & COKER, P. 2001. Vegetation description and analysis. A Practical Approach. John
Wiley & Sons Ltd, West Sussex.
KROHNE, D.T. 2001. General Ecology 2
nd
edn. Brooks/Cole, USA.
KRUG, C.B., ESLER. K.J., HOFFMAN M.T., HENSCHEL J., SCHMIEDEL U. & JUERGENS N.
2006. North-South cooperation through Biodiversity Monitoring Transect Analysis in South
Africa (BIOTA Southern Africa): An interdisciplinary research programme in arid and semiarid southern Africa. South African Journal of Science 102: 187 – 190.
LAND TYPE SURVEY STAFF. 1987. Land types of the maps 2816 Alexander Bay, 2818
Warmbad, 2916 Springbok, 2918 Pofadder, 3017 Garies and 3018 Loeriesfontein. Memoirs
on the Agricultural Natural resources of South Africa 9: 1 – 538.
LAYCOCK, W.A. 1991. Stable states and thresholds of range condition on North American
rangelands – a viewpoint. Journal of Range Management 44: 422 – 426.
LEPS, J. & SMILAUER, P. 2003. Multivariate analysis of ecological data using CANOCO.
Cambridge University Press, Cambridge.
LE ROUX, A. & VAN ROOYEN, M.W. 1999. Succulent Karoo. In: J. Knobel (ed.) The magnificent
natural heritage of South Africa. pp. 94 – 107. Sunbird Publishing, Llandudno.
LE ROUX, A. 1984. ‘n Fitososiologiese studie van die Hester Malan-Natuurreservaat. MSc.
Dissertation. University of Pretoria, Pretoria.
156
LLOYD, W. 1996. An assessment of the veld condition potential of Goegap Nature Reserve.
Northern Cape Nature Conservation Services, Departmental Report.
LOMBARD, A.T., HILTON-TAYLOR, C., REBELO, A.G., PRESSEY, R.L., & COWLING, R.M.
1999. Reserve selection in the Succulent Karoo, South Africa: coping with high
compositional turnover. Plant Ecology 142: 35 – 55.
LOW, A.B. & REBELO T.G. 1998. Vegetation of South Africa, Lesotho and Swaziland.
Department of Environmental Affairs & Tourism, Pretoria.
MARAIS, J.A.H., AGENBACHT, A.L.D., PRINSLOO, M. & BASSON, W.A. 2001. The geology of
the Springbok area. Council for Geoscience, South Africa.
McCUNE, B. & MEFFORD, M.J. 1999. PC-ORD. Multivariate Analysis of Ecological Data,
Version 4. MjM Software Design, Gleneden Beach, Oregon, USA.
MENTIS, M.T. 1981. Evaluation of the wheel-point and step-point methods of veld condition
assessment. Proceedings of the Grassland Society of South Africa. 16: 89 – 94.
MILTON, S.J. & HOFFMAN, M.T. 1994. The application of state-and-transition models to
rangeland research and management in arid succulent and semi-arid grassy Karoo, South
Africa. African Journal of Range and Forage Science 11(1): 18 – 26.
MILTON, S.J., YEATON, R.I., DEAN, W.R.J. & VLOK, J.H.J. 1997. Succulent Karoo. In: R.M.
Cowling, D.M. Richardson & S.M. Pierce (eds) Vegetation of southern Africa. pp. 131 –
161. Cambridge University Press, Cambridge.
MUCINA, L. & RUTHERFORD, M.C. (eds) 2006. The vegetation of South Africa, Lesotho and
Swaziland. Strelitzia 19. South African National Biodiversity Institute, Pretoria.
MUCINA, L., RUTHERFORD, M.C. & POWRIE L.W. 2005. Vegetation Map of South Africa,
Lesotho and Swaziland, 1:1 000 000 scale sheet maps. South African National Biodiversity
Institute, Pretoria.
MUELLER-DOMBOIS, D. & ELLENBERG, H. 1974. Aims and methods of vegetation ecology.
John Wiley & Sons, New York.
157
MURDOCH, A.J. & ELLIS, R.H. 2000. Longevity, viability and dormancy. In: Fenner (ed.) Seeds:
the ecology of regeneration in plant communities. Chapter 8. CAB International,
Wallingford.
NIERING, W.A. 1987. Vegetation dynamics (succession and climax) in relation to plant
community management. Conservation Biology 1: 287 – 325.
NORTHERN CAPE NATURE CONSERVATION SERVICES. Undated. Goegap Nature Reserve:
Information Guide. Northern Cape Nature Conservation Services, Kimberley.
PACE, M.L. & COLE, J.J. 1989. What questions, systems or phenomena warrant long-term
ecological study? In: G.E. Likens (ed.) Long-term studies in ecology: approaches and
alternatives. pp. 183 – 185. Springer-Verlag, New York.
PARR, T.W., SIER, A.R.J., BATTARBEE, R.W., MACKAY, A. & BURGESS, J. 2003. Detecting
environmental change: science and society – perspectives on long-term research and
st
monitoring in the 21 century. The Science of the Total Environment 310: 1 – 8.
PICKETT, S.T.A. 1989. Long-term studies: past experience and recommendations for the future.
In: P.G. Risser (ed.) Long-term ecological research: an international perspective. pp. 71 –
88. Scientific Committee on Problems of the Environment (SCOPE) 47. Wiley, Chichester.
RICHARDSON, F.D., HAHN, B.D. & HOFFMAN, M.T. 2005. On the dynamics of grazing systems
in the semi-arid Succulent Karoo: The relevance of equilibrium and non-equilibrium
concepts to the sustainability of semi-arid pastoral systems. Ecological Modelling 187: 491
– 512.
RICHARDSON, F.D. & HAHN, B.D. 2007. A short-term mechanistic model of forage and livestock
in the semi-arid Succulent Karoo: 1. Description of the model and sensitivity analyses.
Agricultural Systems 95: 49 – 61.
RICHARDSON, F.D., HAHN, B.D. & HOFFMAN, M.T. 2007. Modelling the sustainability and
productivity of the pastoral systems in the communal areas of Namaqualand. Journal of
Arid Environments 70: 701 – 717.
158
ROBB, L.J., ARMSTRONG, R.A. & WATERS, D.J. 1999. The History of Granulite-Facies
Metamorphism
and
Crustal
Growth
from
Single
Zircon
U-Pb
Geochronology:
Namaqualand, South Africa. Journal of Petrology 40: 1747 – 1770.
RÖSCH, H. 1997. Preliminary results of the 1997 line transects at Goegap Nature Reserve.
Scientific
Services
Section.
Northern
Cape
Conservation
Service,
Unpublished
Departmental Report, Calvinia.
RÖSCH, H. 2001a. Quantification of the herbaceous component on Goegap Nature Reserve –
Year 2000. Northern Cape Nature Conservation Service, Unpublished Departmental
Report, Calvinia.
RÖSCH, H. 2001b. The identification and description of the management units of the Goegap
Nature Reserve. Koedoe 44: 17 – 30.
RÖSCH, H. 2003. Veld condition assessment on Goegap Nature Reserve – Year 2002. Scientific
Services Section. Northern Cape Conservation Service, Unpublished Departmental Report,
Calvinia.
ROUX, P.W. 1963. The descending point method of vegetation survey. A point sampling method
for the measurement of semi-open grasslands and Karoo vegetation in South Africa. South
African Journal of Agricultural Science 5: 273 – 288.
South African Environmental Observatory Network (SAEON). 2001. South African Environmental
Observatory Network and associated Research Thrust for South Africa: Proposal. National
Research Foundation, Pretoria.
South African Environmental Observatory Network (SAEON). 2002. South African Environmental
Observatory Network and associated Research Thrust for South Africa: Proposal. National
Research Foundation, Pretoria.
South African Environmental Observation Network (SAEON). 2004. South African Environmental
Observation Network Review: An eye on our changing world. National Research
Foundation, Pretoria.
159
STEINSCHEN, A.K., GÖRNE, A. & MILTON, S.J. 1996. Threats to the Namaqualand flowers:
outcompeted by grass or exterminated by grazing? South African Journal of Science 92:
237 – 242.
STEYN, H.M., VAN ROOYEN, N., VAN ROOYEN, M.W. & THERON, G.K.
1996a. The
phenology of Namaqualand ephemeral species: the effect of sowing date. Journal of Arid
Environments 32: 407 – 420.
STEYN, H.M., VAN ROOYEN, N., VAN ROOYEN, M.W. & THERON, G.K. 1996b. The phenology
of Namaqualand ephemeral species. The effect of water stress. Journal of Arid
Environments 33: 49 – 62.
TAINTON,
N.M.
1999.
Veld
management
in
South
Africa.
Natal
University
Press,
Pietermaritzburg.
TER BRAAK, C.J.F. & SMILAUER, P. 2003. CANOCO Reference manual and CanoDraw for
Windows User’s guide: Software for Canonical Community Ordination (version 4.5).
Microcomputer Power. Ithaca, NY, USA.
TODD, S. & HOFFMAN, M.T. 1999. Effects of heavy grazing on plant species diversity and
community composition in a communally managed semi-arid shrubland, Namaqualand,
South Africa. Plant Ecology 142: 169 – 178.
TROLLOPE, W.S.W. 1990. Veld management with specific reference to game ranching in the
grassland and savanna areas of South Africa. Koedoe 33: 77 – 87.
TROLLOPE, W.S.W., POTGIETER, A.L.F. & ZAMBATIS, N. 1989. Assessing veld condition in
the Kruger National Park using key grass species. Koedoe 32: 67 – 93.
VAN HULST, R. 1992. From population dynamics to community dynamics: modelling succession
as a species replacement process. In: D.C. Glenn-Lewin, R.K. Peet & T.T. Veblen (eds)
Plant succession – theory and prediction. pp. 188 – 211. Chapman & Hall, London.
VAN JAARSVELD, A.S. & BIGGS, H.C. 2000. Broad participation enhances steps towards a
South African ecosystem observatory system (LTER). South African Journal of Science 96:
66.
160
VAN ROOYEN, M.W. 1999. Functional aspects of short-lived plants. In: W.R.J. Dean & S.J.
Milton (eds) The Karoo: ecological patterns and processes. pp. 107 – 122. Cambridge
University Press, Cambridge.
VAN ROOYEN, M.W., GROBBELAAR, N., THERON, G.K. & VAN ROOYEN, N. 1992. The
ephemerals of Namaqualand: effect of germination date on parameters of growth analysis
of three species. Journal of Arid Environments 22: 117 – 136.
VAN ROOYEN, M.W., THERON, G.K. & GROBBELAAR, N. 1990. Life form and dispersal
spectra of the flora of Namaqualand, South Africa. Journal of Arid Environments 19: 133 –
145.
VAN ROOYEN, M.W., GROBBELAAR, N., THERON, G.K. & VAN ROOYEN, N. 1991. The
ephemerals of Namaqualand: effects of photoperiod, temperature and moisture stress on
development and flowering of three species. Journal of Arid Environments 20: 15 – 29.
VAN WYK, A.E. & SMITH, G.F. 2001. Regions of floristic endemism in southern Africa: a review
with emphasis on succulents. Umdaus Press, Pretoria.
VORSTER, M. 1982. The development of the ecological index method for assessing veld
condition in the Karoo. Proceedings of the Grassland Society of South Africa 17: 84 – 89.
WARD, D. 2006. Long-term effects of herbivory on plant diversity and functional types in arid
ecosystems. In: K. Danell, R. Bergström, P. Ducan, J. Pastor (eds) Large herbivore
ecology, ecosystem dynamics and conservation. pp. 142 – 169. Cambridge University
Press, Cambridge.
WATKEYS, M.K. 1999. Soils of the arid south-western zone of Africa. In: W.R.J. Dean & S.J.
Milton (eds) The Karoo. Ecological patterns and processes. pp. 17 – 25. Cambridge
University Press, Cambridge.
WESTOBY, M., WALKER, B., & NOY-MEIR, I. 1989a. Range management on the basis of a
model which does not seek to establish equilibrium. Journal of Arid Environments. 17: 235
– 239.
WESTOBY, M., WALKER, B., & NOY-MEIR, I. 1989b. Opportunistic management for rangelands
not at equilibrium. Journal of Range Management. 37: 266 – 273.
161
WHITFORD, W.G. 1999. Comparison of ecosystem processes in the Nama-karoo and other
deserts. In: W.R.J. Dean & S.J. Milton (eds) The Karoo. Ecological patterns and processes.
pp. 291 – 302. Cambridge University Press, Cambridge.
WHITTAKER, R.H. 1978a. Classification of Plant Communities. Junk Publishers, The Hague,
Boston.
WHITTAKER, R.H. 1978b. Ordination of Plant Communities. Junk Publishers, The Hague,
Boston.
WIEGAND, T. & JELTSCH, F. 2000. Long-term dynamics in arid and semiarid ecosystems –
synthesis of a workshop. Plant Ecology 150: 3 – 6.
WIEGAND, T. & MILTON, S.J. 1996. Vegetation change in semiarid communities. Simulating
probabilities and time scales. Vegetatio 125(2): 169 – 183.
YEATON, R.I., & ESLER, K.J. 1990. The dynamics of Succulent Karoo vegetation. Vegetatio 88:
103 – 113.
162
CHAPTER 8
APPENDIX
Table 8.1
Species
Aptosimum spinescens
Arctotis fastuosa
Blepharis cf. macra
Cheiridopsis denticulata
Crassula thunbergiana
Crotalaria humilis
Didelta carnosa
Dimorphotheca polyptera
Dimorphotheca sinuata
Drosanthemum hispidum
Dyerophytum africanum
Ehrharta calycina
Ehrharta longiflora
Erodium sp.
Euphorbia decussata
Felicia namaquana
Foveolina dichotoma
Galenia cf. fruticosa
Galenia sarcophylla
Gazania lichtensteinii
Gazania tenuifolia
Geophyte
Gladiolus sp.
Grielum humifusum
Gymnodiscus linearifolia
Helichrysum leontonyx
Heliophila coronopifolia
Heliophila lacteal
Heliophila sessilifolia
Heliophila variabilis
Hirpicium echinus
Hypertelis salsoloides
Ifloga glomerata
Karroochloa schismoides
Species
Total species and the frequency of strike for the Bleshoek Plains line transect
1991
0.1
0.1
0.0
0.0
0.1
0.0
0.0
0.1
0.6
0.0
0.0
0.0
0.0
0.0
0.3
0.3
3.7
0.0
0.0
0.0
0.0
0.0
0.0
2.4
0.0
0.6
0.6
0.0
0.0
0.0
0.0
0.2
0.0
10.9
1991
1993
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.6
1.0
0.1
0.0
0.0
0.2
0.0
0.2
0.1
8.5
0.0
4.9
0.3
0.0
0.0
0.1
0.4
0.0
0.4
0.0
0.0
0.0
0.7
0.0
1.0
0.4
12.4
1993
1994
0.1
0.7
0.0
0.1
0.1
0.0
0.0
0.2
4.3
0.0
0.0
0.0
0.0
0.0
0.4
0.1
4.3
0.0
0.4
0.3
0.2
0.0
0.0
5.5
0.0
0.0
1.0
0.0
0.0
0.0
0.4
1.0
0.2
4.2
1994
1995
0.0
0.0
0.0
0.0
0.1
0.4
0.0
0.0
4.4
0.1
0.0
0.0
0.0
0.0
0.4
0.0
4.4
0.0
0.2
0.5
0.1
0.0
0.0
1.2
0.0
0.2
1.3
0.0
0.0
0.0
0.0
0.2
0.0
6.5
1995
1997
0.0
0.0
0.0
0.0
2.3
6.4
0.4
0.0
8.1
0.0
0.0
0.0
0.0
0.0
0.2
0.0
2.0
0.0
5.9
0.6
0.3
0.0
0.0
2.7
0.0
0.0
0.1
0.0
0.0
0.0
0.0
1.0
0.0
0.4
1997
1998
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.1
0.0
2.3
0.6
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
0.2
1998
163
1999
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
0.0
1999
2000
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.1
11.1
0.0
0.0
0.1
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.8
0.0
0.1
2000
2001
0.0
0.8
0.0
0.0
0.0
0.7
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.3
0.0
4.4
0.0
2.2
0.3
0.3
0.0
0.0
1.3
0.0
0.1
0.0
0.0
0.0
0.2
0.0
1.8
0.0
4.6
2001
2002
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
1.0
0.0
0.0
0.0
0.0
0.3
0.8
0.1
3.0
0.0
0.8
0.1
0.2
0.1
0.0
0.1
0.0
0.0
0.3
0.0
0.0
2.1
0.0
0.7
0.0
13.6
2002
2003
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.8
2003
2004
0.0
0.1
0.0
0.0
0.0
1.8
0.0
0.0
0.3
0.1
0.0
0.0
0.0
0.0
0.3
0.0
2.0
0.0
0.1
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.5
0.0
4.6
2004
2005
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.4
0.0
0.1
0.0
6.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.8
0.0
0.0
2005
2006
0.0
1.3
0.1
0.0
0.1
0.0
0.1
0.1
0.5
0.0
0.1
0.1
0.0
0.0
0.4
0.0
1.4
0.0
10.4
0.8
0.0
0.1
0.0
0.4
0.0
0.1
0.0
0.5
0.0
2.2
0.0
1.2
0.0
2.6
2006
2007
0.0
0.0
0.0
0.0
0.9
1.5
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.4
0.0
3.4
0.0
0.0
0.0
0.0
0.1
0.0
0.4
0.0
0.6
0.0
0.4
2.5
0.8
0.1
0.3
0.0
8.3
2007
Leipoldtia schultzei
Lessertia diffusa
Leysera tenella
Lotononis brachyloba
Lycium cinereum
Manulea benthamiana
Manulea cheiranthus
Mesembryanthemum guerichianum
Oncosiphon grandiflorum
Oncosiphon suffruticosum
Osteospermum pinnatum
Oxalis spp.
Pelargonium redactum
Peliostomum virgatum
Pentaschistis airoides
Pharnaceum dichotomum
Phyllobolus occulatus
Polycarena collina
Polycarena selaginoides
Psilocaulon junceum
Ruschia elineata
Ruschia brevibracteata
Ruschia robusta
Salsola kali
Schmidtia kalahariense
Senecio arenarius
Senecio cardaminifolius
Stipagrostis brevifolia
Stipagrostis ciliata
Stipagrostis obtusa
Tetragonia fruticosa
Tetragonia microptera
Trachyandra spp.
Tribulus terrestris
Tripteris amplectens
Tripteris hyoseroides
Tripteris sinuata
Wahlenbergia prostrata
Zaluzianskya benthamiana
Zaluzianskya gilioides
Zygophyllum retrofractum
Total
7.2
0.0
2.1
0.0
0.0
0.8
0.4
0.9
2.8
0.0
0.4
0.2
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.1
2.3
0.0
0.0
1.8
0.1
0.8
0.0
1.2
0.0
0.2
0.3
0.0
0.0
0.0
0.1
0.3
0.0
0.0
0.2
42.8
9.4
0.4
2.2
4.6
0.0
2.8
0.1
1.4
4.2
0.9
0.9
0.2
2.0
0.0
0.0
0.0
0.2
0.0
0.0
0.2
0.0
0.0
2.0
0.1
0.1
2.5
0.0
1.5
0.0
1.5
0.1
0.2
0.7
0.6
0.5
0.0
0.1
0.3
0.0
0.0
0.4
72.1
7.2
0.1
3.5
2.1
0.0
0.3
1.0
0.9
1.0
0.0
1.5
0.1
0.7
0.1
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
1.8
0.0
0.0
2.6
0.0
1.3
0.0
1.4
0.0
0.2
0.0
0.0
0.0
0.1
0.3
0.1
0.0
0.0
0.3
50.3
8.7
0.1
2.0
0.9
0.0
0.0
0.0
0.9
2.1
0.1
0.9
0.0
1.9
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
2.0
0.0
0.0
4.4
0.0
1.3
0.1
1.4
0.0
0.1
0.2
0.0
0.0
0.0
0.1
0.0
2.0
0.0
0.5
49.9
9.4
0.5
3.0
4.1
0.1
0.0
0.0
0.8
1.4
0.0
0.5
0.2
0.5
0.1
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.1
2.9
0.0
0.0
0.5
0.0
0.9
0.0
1.6
0.0
0.0
2.2
0.0
0.2
0.0
0.6
0.4
0.0
0.1
0.6
61.3
8.8
0.1
0.8
0.3
0.1
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.1
3.4
0.1
0.0
0.0
0.0
0.6
0.0
1.2
0.1
0.0
0.2
0.0
0.0
0.1
0.3
0.0
0.0
0.0
0.4
22.5
164
7.9
0.3
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
2.6
0.0
0.0
0.0
0.0
0.2
0.0
0.4
0.0
0.0
0.1
0.1
0.0
0.0
0.4
0.0
0.0
0.0
0.6
14.3
9.7
0.3
0.0
1.4
0.1
0.0
0.0
2.1
0.3
0.0
0.0
0.1
0.1
0.2
0.0
0.0
0.0
0.0
0.3
0.1
0.0
0.0
2.4
0.0
0.0
0.0
0.0
0.6
0.0
1.9
0.0
0.0
0.5
1.3
0.0
0.0
0.6
0.0
0.0
0.0
0.7
37.2
10.0
0.1
0.0
16.6
0.1
0.0
0.0
0.5
5.8
0.0
0.8
0.0
2.3
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
2.0
0.0
0.0
0.3
0.0
0.9
0.0
1.0
0.0
1.9
0.5
0.0
0.3
0.0
0.2
0.0
0.0
0.0
0.3
61.4
10.7
0.0
0.6
0.3
0.1
0.0
0.0
0.5
10.3
0.0
0.1
0.0
0.3
0.0
0.0
0.1
0.0
0.2
0.0
0.2
0.0
0.0
2.6
0.0
0.0
1.1
0.0
1.1
0.0
1.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.5
53.3
8.9
0.0
0.0
0.0
0.1
0.0
0.0
0.0
3.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.1
0.0
0.0
0.0
0.0
0.5
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.2
17.5
8.4
0.0
0.2
0.4
0.1
0.0
0.0
0.0
3.1
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
1.8
0.0
0.0
0.4
0.0
0.1
0.0
0.6
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
26.7
9.6
0.0
0.0
3.4
0.1
0.0
0.0
1.6
1.1
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
1.8
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.0
0.0
0.0
3.1
0.2
0.0
0.2
0.0
0.0
0.0
0.6
29.8
10.8
0.2
0.4
19.8
0.2
0.0
0.0
0.2
11.8
0.3
0.5
0.1
0.4
0.2
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
1.4
0.0
0.0
0.5
0.0
0.6
0.0
0.0
0.0
0.2
0.0
0.0
0.8
0.0
0.2
0.0
0.0
0.0
0.7
71.9
9.9
0.3
0.8
3.8
0.2
0.0
0.0
0.0
20.7
0.3
0.3
0.1
0.1
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.1
0.0
0.8
0.0
0.0
6.7
0.1
0.4
0.0
0.1
0.0
0.0
0.4
0.0
0.0
0.0
0.2
0.4
0.0
0.0
0.4
66.9
Table 8.2
Species
Amphiglossa tomentosa
Anthospermum tricostatum
Antizoma miersiana
Aptosimum indivisum
Arctotis fastuosa
Aridaria noctiflora
Atriplex lindleyi subsp. inflata
Bromus pectinatus
Cephalophyllum ebracteatum
Cheiridopsis denticulata
Chrysocoma ciliata
Cleretum papulosum
Cotula barbata
Cotula laxa
Cotula nudicaulis
Crassula muscosa subsp. muscosa
Crassula subaphylla
Crassula thunbergiana
Deverra aphylla
Diascia namaquana
Didelta spinosa
Dimorphotheca sinuata
Diospyros austro-africana
Dischisma spicatum
Drosanthemum sp. (shrub)
Drosanthemum hispidum
Ehrharta calycina
Ehrharta delicatula
Eriocephalus brevifolius
Eriocephalus microphyllus
Erodium cicutarium
Euphorbia decussata
Euphorbia mauritanica
Euryops dregeanus
Euryops multifidus
Felicia sp.
Felicia brevifolia
Felicia filifolia
Felicia cf. namaquana
Foveolina dichotoma
Galenia africana
Total species and the frequency of strike for the Bluemine Mountain line transect
1974 1975 1976 1977 1978 1979 1980 1982 1984 1985 1986 1987 1989 1990 1991 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.7
0.0
0.0
0.0
0.0
0.0
0.1
0.0
3.8
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.0
0.2
0.0
0.0
0.0
6.1
0.1
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.4
1.1
0.6
0.1
0.0
0.1
0.0
0.3
0.0
0.0
0.0
0.1
1.0
0.3
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.3
0.0
0.0
0.0
0.6
0.0
0.0
0.0
4.4
0.0
0.5
0.4
0.0
0.0
0.0
0.2
0.0
0.2
0.9
1.2
0.0
0.1
0.0
0.0
0.0
0.1
0.2
0.0
0.0
0.7
0.2
0.0
0.2
0.0
0.0
0.0
0.0
0.7
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.8
0.0
0.0
0.0
4.9
0.0
0.7
0.2
0.0
0.0
0.0
0.1
0.0
0.0
0.8
0.9
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.9
0.2
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
5.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.1
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.4
0.0
0.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.5
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
5.0
0.0
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
4.5
0.0
0.7
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.8
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.3
0.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
5.3
0.0
0.4
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.9
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.5
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.8
0.0
0.6
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
1.1
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.5
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
4.8
0.0
0.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.3
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.7
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
5.5
0.0
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.5
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
5.9
0.0
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
165
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.2
0.5
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
6.2
0.0
0.9
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.4
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.7
0.4
0.0
0.6
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.0
5.5
0.0
0.7
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.5
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.2
0.0
0.4
0.0
0.0
0.0
0.2
0.5
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.6
0.2
0.0
0.0
8.0
0.0
0.6
0.0
0.0
0.0
0.0
0.3
0.0
0.4
0.9
0.9
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.5
0.7
0.0
0.1
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
7.7
0.0
0.7
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.2
0.6
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.2
0.4
0.4
0.0
0.2
0.0
0.0
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.0
6.2
0.0
0.8
0.0
0.1
0.1
0.0
0.3
0.0
0.1
1.1
0.6
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.2
0.0
0.3
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
7.1
0.0
0.7
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.3
0.7
0.3
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.7
0.6
0.0
0.3
0.3
0.0
0.1
0.1
0.7
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.6
0.0
0.0
0.0
7.4
0.0
0.7
0.0
0.0
0.0
0.0
0.8
0.0
0.6
0.3
1.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.6
0.7
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
6.6
0.0
0.9
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
1.2
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.3
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.8
0.0
0.7
0.0
0.0
0.1
0.0
0.1
0.0
0.1
0.1
1.3
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.9
0.2
0.1
0.1
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.4
6.7
0.0
1.0
0.0
0.1
0.0
0.0
0.0
0.5
0.0
0.1
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.6
0.3
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.0
7.8
0.0
0.7
0.0
0.0
0.1
0.0
0.4
0.0
0.8
0.9
0.8
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.3
0.8
0.4
0.0
0.7
0.0
0.1
0.4
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.5
6.3
0.0
0.8
0.0
0.1
0.1
0.0
0.0
0.2
1.1
0.4
0.9
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.7
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
6.2
0.0
0.9
0.0
0.1
0.0
0.0
0.3
0.0
0.0
0.0
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
6.4
0.0
0.4
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.9
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.6
0.4
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.8
5.9
0.0
0.2
0.0
0.0
0.1
0.0
0.1
0.0
0.1
0.1
1.0
0.2
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.1
0.5
0.3
0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.1
0.1
0.1
0.0
0.3
0.0
0.5
0.0
0.0
0.1
4.6
0.0
0.8
0.0
0.0
0.1
0.1
0.4
0.0
1.3
0.6
1.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.6
0.0
0.9
0.0
0.0
0.0
0.0
0.6
0.0
0.1
0.1
0.2
0.0
0.0
0.0
0.3
0.3
0.0
0.4
6.2
0.0
0.8
0.0
0.0
0.1
0.8
0.2
0.0
0.0
0.3
1.5
Species
Galenia meziana
Galenia namaensis
Galenia sarcophylla
Gazania heterochaeta
Gazania tenuifolia
Geophyte
Grielum humifusum
Gynandriris setifolia
Hallianthus planus
Helichrysum asperum
Helichrysum leontonyx
Helichrysum sp. (perennial)
Helichrysum tinctum
Heliophila thunbergii var. macrostylis
Heliophila variabilis
Hermannia cuneifolia
Hermannia disermifolia
Hermannia marginata
Hermannia trifurca
Hirpicium alienatum
Hirpicium echinus
Homeria sp.
Hypertelis salsoloides
Ifloga glomerata
Karroochloa schismoides
Lampranthus godmanniae
Lasiopogon micropoides
Lasiospermum brachyglossum
Lebeckia sericea
Leipoldtia schultzei
Leipoldtia sp. (Tierhoek)
Leysera gnaphalodes
Leysera tenella
Lotononis brachyloba
Lycium cinereum
Manochlamys albicans
Manulea benthamiana
Manulea cheiranthus
Manulea gilioides
Melolobium adenodes
Melolobium candicans
Mesembryanthemum guerichianum
Montinia caryophyllacea
Moraea sp.
1974 1975 1976 1977 1978 1979 1980 1982 1984 1985 1986 1987 1989 1990 1991 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
0.0
0.1
1.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.4
0.0
0.5
1.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
1.6
0.0
0.0
0.0
0.0
0.3
0.1
0.0
0.2
0.0
0.0
0.1
0.3
0.1
0.0
0.0
0.3
1.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.6
0.0
0.2
0.0
0.4
0.3
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
1.1
0.0
0.0
0.1
0.0
0.3
0.1
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.2
1.8
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.7
0.0
0.5
0.0
0.1
1.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
2.2
0.0
0.0
0.4
0.2
0.2
0.1
0.0
0.1
0.0
0.0
0.1
0.2
0.0
0.0
0.1
0.4
1.4
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.0
0.0
0.5
0.0
0.4
0.0
0.5
1.1
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
2.1
0.0
0.0
0.8
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.3
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.1
0.4
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.7
0.0
0.1
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.5
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
2.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.3
0.9
0.0
0.0
0.0
0.0
0.1
0.4
0.0
0.0
0.2
2.7
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.0
0.6
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
3.1
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.2
0.4
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
4.1
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
4.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
1.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.7
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.1
5.3
0.0
0.0
0.0
0.0
0.5
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.7
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.4
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.4
4.9
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
1.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.2
0.6
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.2
5.5
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
166
0.0
0.0
1.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.0
0.1
0.5
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.3
4.6
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.4
0.2
0.0
0.0
0.0
0.0
0.0
0.0
1.1
0.0
0.0
0.0
0.3
0.0
0.3
0.1
0.0
0.7
0.0
0.0
0.0
0.0
0.3
0.4
0.0
0.0
0.4
5.4
0.0
0.0
1.2
0.0
0.3
0.1
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.9
0.0
0.0
0.0
0.1
0.0
0.0
0.0
2.9
0.0
0.0
0.0
1.7
0.0
0.1
0.0
0.2
0.7
0.0
0.0
0.0
0.1
0.1
0.3
0.0
0.0
0.5
4.7
0.0
0.0
1.1
0.0
0.4
0.0
0.3
0.5
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.7
0.0
0.1
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.1
0.5
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.4
4.0
0.0
0.0
0.6
0.0
0.2
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.4
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.8
0.0
0.6
0.0
0.2
0.0
0.1
0.7
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.3
5.1
0.0
0.0
0.4
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.1
0.4
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.4
4.5
0.0
0.0
0.2
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.3
0.2
0.9
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.6
0.0
0.2
0.2
0.5
0.1
0.2
0.5
0.0
0.0
0.0
0.1
0.0
0.4
0.0
0.0
0.4
4.7
0.0
0.0
1.4
0.0
0.4
0.1
0.0
0.0
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.3
0.0
0.2
0.7
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.2
5.3
0.0
0.0
0.1
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.1
0.0
0.2
0.0
0.3
0.0
0.3
0.3
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.3
4.4
0.0
0.0
0.0
0.0
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.1
0.1
1.3
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.3
5.3
0.0
0.0
0.2
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.0
0.1
0.1
0.3
0.3
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
8.5
0.0
0.1
0.0
0.2
0.8
0.0
0.0
0.0
0.0
0.5
0.2
0.0
0.1
0.2
4.7
0.0
0.0
0.7
0.5
0.3
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.1
0.0
8.3
0.0
0.2
0.1
0.0
1.0
0.0
0.0
0.0
0.0
0.5
0.5
0.0
0.0
0.5
4.9
0.0
0.0
0.5
0.0
0.3
0.1
0.0
0.1
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.0
0.4
0.0
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.4
4.5
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.1
0.1
0.2
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
1.1
0.0
0.4
0.0
0.2
0.8
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.4
4.0
0.0
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.4
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
3.8
0.0
0.4
0.0
0.4
1.1
0.0
0.1
0.0
0.1
0.1
0.2
0.0
0.0
0.1
5.1
0.0
0.0
0.3
0.3
0.4
0.1
0.0
0.2
0.0
0.3
0.0
0.4
0.0
0.0
0.0
0.1
0.7
0.1
0.0
0.3
0.0
0.0
0.0
0.0
3.4
0.0
0.0
0.0
6.0
0.0
0.4
0.1
0.2
1.7
0.0
0.1
0.0
0.1
0.5
0.0
0.0
0.0
0.5
2.7
1.6
0.0
1.1
1.2
0.1
0.1
0.0
1.2
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
3.5
0.3
0.0
0.1
2.5
0.2
0.2
0.1
0.2
1.4
0.0
0.0
0.0
0.0
0.7
0.4
0.1
0.0
0.4
0.0
5.6
0.0
1.2
0.0
0.3
0.0
0.0
0.0
0.4
0.0
0.1
0.0
0.0
0.0
Species
Nenax cinerea
Oncosiphon suffruticosum
Orbea namaquensis
Osteospermum pinnatum
Othonna arbuscula
Othonna cylindrica
Oxalis spp.
Pelargonium carnosum
Pelargonium grandicalcaratum
Peliostomum virgatum
Pentaschistis airoides
Pentzia incana
Pharnaceum aurantium
Phyllobolus sp.
Plantago caffra
Plinthus karooicus
Poaceae
Polycarena collina
Psilocaulon junceum
Pteronia ciliata
Pteronia divaricata
Pteronia glabrata
Pteronia glomerata
Pteronia incana
Searsia undulata
Ruschia brevibracteata
Ruschia cymosa
Ruschia elineata
Ruschia robusta
Ruschia viridifolia
Scirpus nodosus
Senecio cardaminifolius
Senecio cinerascens
Senecio niveus
Stipagrostis brevifolia
Stipagrostis namaquensis
Tetragonia fruticosa
Tetragonia microptera
Thesium lineatum
Trachyandra falcata
Trichogyne paronychioides
Tripteris amplectens
Tripteris hyoseroides
Tripteris oppositifolia
1974 1975 1976 1977 1978 1979 1980 1982 1984 1985 1986 1987 1989 1990 1991 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
0.0 0.1 0.3
0.4 0.2 0.3
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.6 0.4
0.1 0.2 0.8
0.3 0.1 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.1 0.1
0.1 0.1 0.4
0.0 0.0 0.1
0.0 0.0 0.1
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.2 0.1 0.6
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
1.3 1.4 1.2
0.3 0.3 0.4
0.3 0.0 0.3
0.0 0.0 0.0
0.5 1.1 0.4
9.5 10.4 11.7
0.0 0.0 0.1
0.0 0.0 0.0
0.0 0.5 0.0
0.0 0.0 0.2
0.0 0.0 0.0
0.0 0.0 0.0
0.3 0.5 0.1
0.4 0.6 0.4
0.0 0.0 0.0
0.2 0.1 0.1
0.0 0.1 0.0
0.0 0.0 0.0
1.6 0.7 4.9
0.0 0.0 5.3
0.0 0.0 0.0
0.5
0.4
0.0
0.0
0.8
0.4
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.6
0.2
0.1
0.0
0.3
14.8
0.3
0.0
0.2
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.3
0.9
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.7
0.3
0.6
0.0
0.6
11.6
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.5
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.5
0.3
0.0
0.3
13.7
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.2
0.0
0.0
0.0
0.2
0.4
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.4
0.2
0.1
0.5
12.5
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.3
0.0
0.0
0.0
0.3
0.5
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.5
0.4
0.1
0.0
0.7
13.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.2
0.4
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.7
0.2
0.0
0.0
0.0
1.1
0.2
0.2
0.0
0.1
14.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.5
0.5
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.2
0.0
0.0
0.0
0.6
0.2
0.1
0.0
0.3
17.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.6
0.6
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.6
0.2
0.0
0.0
0.4
17.8
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.4
0.5
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.1
0.0
0.0
0.0
0.5
0.3
0.1
0.0
0.1
15.5
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.2
0.3
0.0
0.0
0.0
0.0
0.0
0.6
0.1
0.0
0.0
0.0
0.0
0.0
0.9
0.1
0.0
0.0
0.0
0.7
0.4
0.1
0.0
0.0
13.9
0.2
0.0
0.0
0.0
0.0
0.0
0.1
1.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
167
0.3
0.0
0.0
0.0
0.7
0.4
0.0
0.0
0.0
0.0
0.0
0.3
0.2
0.0
0.0
0.0
0.0
0.0
0.5
0.1
0.0
0.0
0.0
0.6
0.3
0.3
0.0
0.1
15.4
0.1
0.0
0.0
0.0
0.3
0.0
0.2
0.6
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.3
0.0
0.0
0.4
0.6
0.5
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.9
0.3
0.2
0.0
0.1
15.4
0.2
0.0
0.8
0.0
0.1
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
1.5
0.0
0.0
0.1
0.7
0.3
0.0
0.0
0.0
0.3
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.8
0.2
0.1
0.0
0.1
13.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.1
0.5
0.0
0.0
0.0
0.1
0.1
0.0
0.4
0.6
0.3
0.0
0.0
0.0
0.0
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
1.2
0.3
0.3
0.0
0.2
15.1
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.5
0.0
0.0
0.2
0.2
0.1
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.0
1.2
0.2
0.4
0.0
0.1
17.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.3
0.0
0.0
0.0
0.5
0.1
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.9
0.2
0.2
0.0
0.1
14.7
0.3
0.0
0.5
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.3
0.0
0.0
0.0
1.0
0.9
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
1.5
0.4
0.2
0.0
0.1
16.0
0.1
0.1
0.1
0.0
0.0
0.0
0.1
0.4
0.0
0.1
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
1.0
0.4
1.1
0.0
0.3
14.7
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.3
0.1
0.0
0.0
0.0
0.7
0.0
0.0
0.1
0.0
0.0
0.3
0.0
0.0
0.0
0.4
0.0
0.1
0.0
0.1
0.0
0.0
0.0
1.2
0.1
0.1
0.0
0.2
10.9
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
1.2
0.4
0.2
0.0
0.0
11.3
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.2
0.0
0.0
0.0
0.1
0.0
0.0 0.1 0.0
1.3 2.3 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
1.1 0.9 0.9
0.4 0.3 0.0
0.0 0.0 0.0
0.0 0.0 0.1
0.0 0.0 0.0
0.0 0.0 0.0
0.3 0.3 0.4
0.1 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.2 0.1 0.5
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.1 0.1 0.2
0.1 0.0 0.0
0.1 0.0 0.0
0.0 0.0 0.0
1.0 2.7 1.0
0.4 0.4 0.4
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
9.8 11.5 10.7
0.0 0.0 0.0
0.0 0.0 0.0
1.5 1.2 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.0 0.1 0.0
0.1 0.3 0.6
0.1 0.0 0.0
0.1 0.0 0.0
0.0 0.0 0.0
0.0 0.0 0.0
2.5 0.1 0.0
0.0 0.0 0.0
0.0 0.0 0.0
0.3
0.0
0.0
0.0
0.0
1.0
0.4
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.3
0.0
0.0
0.0
1.1
0.4
0.2
0.0
0.0
9.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.4
0.2
0.0
0.0
0.1
0.9
0.0
0.0
0.0
0.2
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
1.1
0.4
0.2
0.0
0.0
8.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
1.3
0.0
0.6
1.5
0.0
0.0
0.0
0.9
1.1
0.0
0.0
0.1
0.2
0.6
0.1
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.5
0.3
0.4
0.0
0.0
9.2
0.0
0.0
1.6
0.0
0.0
0.1
0.0
0.2
0.1
0.0
0.0
0.3
1.6
0.4
0.0
0.3
1.4
0.0
0.1
0.1
1.2
1.5
0.0
0.0
0.2
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
1.5
0.3
0.2
0.0
0.0
9.3
0.0
0.0
1.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.1
0.0
0.0
0.0
Species
Tripteris sinuata
Tylecodon wallichii
Ursinia cakilefolia
Ursinia calenduliflora
Ursinia nana
Viscum capense
Aizoaceae
Wahlenbergia annularis
Wahlenbergia prostrata
Zaluzianskya benthamiana
Zaluzianskya giliodes
Zygophyllum foetidum
Zygophyllum retrofractum
Zygophyllum sp. nov.
Total
1974 1975 1976 1977 1978 1979 1980 1982 1984 1985 1986 1987 1989 1990 1991 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
0.8
0.1
0.0
1.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.5
0.0
32.0
1.0
0.1
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
34.2
1.8
0.1
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.0
0.0
51.5
1.3
0.0
0.8
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
41.0
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
28.9
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
31.1
0.7
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
28.7
1.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
31.6
1.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
35.1
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
36.9
1.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
41.0
0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
37.9
2.3
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
38.9
168
1.7
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
39.1
1.9
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
45.8
1.9
0.1
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.0
51.3
2.3
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
42.0
1.8
0.1
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.0
0.2
0.0
45.7
1.6
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
38.5
3.4
0.1
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
52.7
3.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
41.9
3.3
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.0
35.3
3.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
39.5
3.5
0.0
0.2
0.0
0.1
0.0
0.0
0.0
0.0
0.5
1.0
0.0
0.3
0.0
56.8
3.5
0.1
0.0
1.2
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.2
0.1
59.0
3.9
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.2
0.1
38.2
3.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.1
0.0
34.5
2.5
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.2
0.0
42.0
4.4
0.1
0.0
0.7
0.0
0.1
0.0
0.2
0.0
0.7
0.0
0.0
0.1
0.0
61.7
3.5
0.1
0.0
0.7
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.1
0.0
54.9
Table 8.3
Species
Aizoon canariense
Amellus strigosus
Aptosimum indivisum
Aptosimum spinescens
Aridaria noctiflora
Atriplex lindleyi subsp. inflata
Augea capensis
Babiana sp.
Conicosia elongata
Crassula thunbergiana
Crotolaria humilis
Dimorphotheca sinuata
Dimorphotheca polyptera
Drosanthemum hispidum
Eriocephalus microphyllus
Erodium moschatum
Foveolina dichotoma
Galenia sarcophylla
Gazania lichtensteini
Geophyte
Grielum humifusum
Helichrysum leontonyx
Helichrysum tinctum
Heliophila sesselifolia
Heliophila variabilis
Hermannia cuneifolia
Hermannia sp.
Hirpicium echinus
Hypertelis salsoloides
Jamesbrittania albiflora
Karroochloa schismoides
Lasiopogon micropoides
Lessertia diffusa
Leysera tenella
Lotononis brachyloba
Lotononis falcata
Lycium cinereum
Manulea benthamiana
Manulea cheiranthus
Total species and the frequency of strike for the Goegap Plains line transect
1991
0.0
0.0
0.0
0.8
0.0
1.7
0.0
0.0
0.2
0.0
0.0
0.0
0.1
2.3
0.0
0.0
1.8
1.4
0.0
0.0
0.0
1.2
0.0
1.6
0.0
0.0
0.0
0.0
2.5
0.0
3.9
0.0
0.0
0.6
0.0
0.0
0.5
0.1
0.2
1993
0.5
0.1
0.0
1.2
0.0
1.4
0.4
0.0
0.1
1.8
0.0
0.0
0.1
4.5
0.0
0.1
3.0
6.5
0.0
0.0
0.0
0.6
1.4
0.0
1.0
0.0
0.0
0.1
3.5
0.0
5.4
0.0
0.4
0.3
1.6
0.0
0.4
0.6
0.0
1994
0.0
0.0
0.0
1.2
0.0
1.1
0.2
0.0
0.0
0.0
0.0
0.2
0.0
5.4
0.0
0.0
0.5
3.0
0.0
0.0
0.1
0.0
0.1
0.3
0.0
0.0
0.0
0.0
3.6
0.0
1.1
0.0
0.0
0.0
0.0
0.0
0.8
0.0
0.1
1997
0.1
0.0
0.0
1.4
0.0
1.2
0.2
0.1
0.1
0.0
0.0
0.2
0.0
9.0
0.0
0.0
0.8
5.2
0.2
0.0
0.1
0.0
0.2
0.0
0.8
0.1
0.3
0.1
3.6
0.0
0.1
0.0
0.1
1.0
0.7
0.0
0.3
0.0
0.0
1998
0.0
0.0
0.0
0.9
0.0
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.1
5.9
0.0
0.0
0.0
1.6
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
2.4
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.4
0.0
0.0
169
1999
0.0
0.0
0.0
1.1
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.2
0.0
0.0
0.0
0.3
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
2.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.7
0.0
0.0
2000
0.3
0.0
0.0
1.5
0.0
0.8
0.0
0.0
0.0
0.0
0.0
0.2
0.1
10.3
0.1
0.0
0.1
5.6
0.0
0.3
0.1
0.0
0.1
0.1
0.0
0.1
0.0
0.0
4.8
0.0
0.0
0.0
1.3
0.1
1.1
0.0
0.8
0.0
0.0
2001
0.0
0.0
0.0
1.1
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.1
0.1
0.0
1.0
1.9
0.1
0.0
0.0
0.0
1.7
0.8
0.0
0.1
0.0
0.0
2.1
0.0
0.2
0.0
0.3
0.7
5.3
0.0
0.2
0.0
0.0
2002
0.0
0.0
0.0
0.7
0.1
0.3
0.0
0.0
0.0
0.0
0.0
0.2
0.0
3.5
0.1
0.0
2.7
0.0
0.4
0.0
0.0
0.0
8.2
2.1
0.0
0.0
0.0
0.0
0.6
0.0
0.6
0.0
0.0
1.7
0.0
0.0
0.5
0.0
0.0
2003
0.0
0.0
0.0
0.7
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
2004
0.0
0.0
0.0
0.6
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.3
0.1
0.0
1.3
0.2
0.0
0.1
0.1
0.0
0.9
2.7
0.1
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.6
0.0
0.0
2005
1.8
0.0
0.6
0.5
0.0
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.3
3.9
0.1
0.0
0.2
12.7
0.4
0.1
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
6.8
0.0
0.3
0.0
2.2
2.4
1.8
0.0
0.1
0.0
0.0
2006
0.0
0.0
0.0
0.5
0.0
0.4
0.1
0.0
0.1
0.0
0.0
0.0
0.1
5.8
0.0
0.0
0.6
13.2
0.6
0.0
0.1
0.3
0.0
2.4
0.0
0.0
0.0
0.0
6.0
0.1
0.5
0.0
1.2
2.7
5.4
0.0
0.6
0.0
0.0
2007
0.0
0.0
0.0
0.4
0.0
0.1
0.0
0.0
0.0
0.1
0.2
0.0
0.0
7.4
0.1
0.0
0.4
1.5
0.2
0.0
0.0
0.6
0.0
11.3
0.0
0.0
0.0
0.0
2.3
0.0
1.8
0.2
0.4
3.6
0.3
0.5
0.7
0.0
0.0
Species
Mesembryanthemum guerichianum
Moraea minuata
Moraea schlechterii
Oncosiphon grandiflorum
Oncosiphon suffruticosum
Ornithogalum secundum
Osteospermum pinnatum
Oxalis spp.
Pelargonium redactum
Peliostomum virgatum
Pentaschistis airoides
Pharnaceum dichotomum
Phyllobolus occulatus
Plantago caffra
Polycarena collina
Psilocaulon junceum
Pteronia scariosa
Salsola aphylla
Salsola tuberculata
Senecio arenarius
Senecio niveus
Stipagrostis brevifolia
Stipagrostis ciliata
Stipagrostis obtusa
Stipagrostis zeyheri
Thesium lineatum
Trachyandra bulbinifolia
Trichogyne paronychioides
Tripteris amplectens
Unidentified species
Wahlenbergia annularis
Wahlenbergia prostrata
Zaluzianskya gilioides
Zygophyllum retrofractum
Total
1991
0.0
0.0
0.0
0.3
0.0
0.4
0.5
0.3
0.0
0.0
0.0
0.0
0.1
0.0
0.0
2.3
0.2
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.0
0.2
0.0
0.5
25.0
1993
0.2
0.0
0.2
0.2
0.1
0.2
4.2
0.8
0.0
0.1
0.1
1.3
0.0
0.1
0.0
3.4
0.2
0.1
0.0
1.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
2.8
0.5
0.0
51.2
1994
0.1
0.0
0.0
0.0
0.0
0.4
0.9
0.2
0.0
0.1
0.0
0.0
0.0
0.1
0.0
2.8
0.0
0.1
0.0
1.2
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.2
0.0
0.4
0.0
0.6
25.1
1997
0.0
0.0
0.0
1.1
0.0
0.6
2.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.7
0.2
0.0
0.2
0.2
0.1
0.3
0.1
0.0
0.0
1.5
0.0
0.0
0.1
0.0
0.3
0.0
0.5
35.0
1998
0.0
0.0
0.0
0.3
0.0
0.0
0.4
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.3
0.3
0.2
0.0
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.4
16.2
170
1999
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.4
9.8
2000
1.0
0.0
0.0
0.6
0.0
0.0
1.1
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.8
0.6
0.1
0.0
0.1
0.1
0.2
0.0
0.1
0.0
0.0
7.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
40.8
2001
0.0
0.0
0.0
2.2
0.1
0.0
2.6
0.3
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.6
1.0
0.1
0.0
0.2
0.0
0.1
0.0
0.1
0.0
0.0
4.8
0.0
0.0
0.0
0.0
0.0
0.0
0.8
33.9
2002
0.1
0.0
0.0
1.5
0.4
0.0
1.8
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.5
0.2
0.0
0.4
0.0
0.1
0.0
0.0
0.0
0.0
5.9
0.1
0.0
0.0
0.1
0.0
0.0
0.4
33.6
2003
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.5
0.1
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.8
6.2
2004
0.7
0.0
0.0
1.6
0.0
0.0
0.5
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
2.2
0.0
0.0
0.0
0.0
0.0
0.0
0.7
14.8
2005
1.8
0.0
0.0
0.7
0.0
0.1
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.7
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.8
40.3
2006
0.1
0.0
0.0
2.5
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.5
0.5
0.0
0.1
0.6
0.0
0.0
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
46.7
2007
0.0
0.1
0.0
3.0
1.1
0.0
0.7
0.4
0.5
0.1
0.0
0.0
0.0
0.0
0.1
0.6
0.3
0.2
0.0
0.5
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.2
0.0
1.3
41.7
Table 8.4
Species
Aizoon canariense
Arctotis fastuosa
Asparagus sp.
Bulbostylis densa
Conicosia elongata
Crassula thunbergiana
Diascia namaquana
Dimorphotheca polyptera
Dimorphotheca sinuata
Dischisma spicata
Euphorbia decussata
Euphorbia mauritanica
Felicia namaquana
Foveolina dichotoma
Galenia africana
Galenia meziana
Galenia sarcophylla
Gazania lichtensteini
Geophyte
Grielum humifusum
Gymnodiscus linearifolius
Hebenstretia cf. linearis
Helichrysum leontonyx
Helichrysum tinctum
Heliophila coronopifolia
Heliophila lacteal
Heliophila thunbergii var. macrostylis
Heliophila sesselifolia
Heliophila variabilis
Hermannia disermifolia
Hermannia tomentosa
Hermannia cf. tomentosa
Hirpicium echinus
Hypertelis salsoloides
Ifloga glomerata
Karroochloa schismoides
Lachenalia sp.
Lasiopogon micropoides
Lasiospermum brachyglossum
Lessertia diffusa
Leysera tenella
Total species and the frequency of strike for the Jaleeg Plains line transect
1991
0.1
0.0
0.0
0.0
0.1
0.4
0.0
0.0
3.3
0.0
0.2
0.0
0.0
3.3
0.0
0.0
4.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.2
0.3
0.0
0.0
0.0
0.0
0.0
0.0
2.5
0.0
0.0
0.0
0.1
0.1
1993
0.0
0.3
0.0
0.0
0.0
1.0
0.1
0.1
14.8
0.1
0.2
0.0
0.2
10.6
0.0
0.0
3.1
0.1
0.0
0.3
0.0
0.0
0.2
0.0
2.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
8.2
0.0
0.0
0.0
0.1
1.7
1994
0.0
0.3
0.0
0.0
0.0
0.1
0.0
0.0
22.8
0.0
0.1
0.0
0.0
6.6
0.0
0.0
0.8
0.4
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.3
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.5
0.0
0.0
0.0
0.0
1.4
1995
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
14.0
0.2
0.2
0.0
0.0
4.6
0.0
0.0
1.1
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.2
2.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.7
0.0
0.0
0.0
0.0
2.0
1997
0.0
0.1
0.0
0.0
0.1
0.3
0.0
0.0
15.3
0.0
0.4
0.0
0.0
1.8
0.0
0.0
6.4
0.7
0.0
0.0
0.0
0.0
0.0
0.2
0.2
0.0
0.0
0.9
0.2
0.0
0.0
0.0
0.1
0.0
0.2
0.4
0.0
0.0
0.0
0.0
4.4
1998
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
171
1999
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.0
0.0
0.2
0.0
0.0
0.9
0.0
0.0
2.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
0.0
0.0
0.0
1.7
2000
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.4
0.0
0.4
0.0
0.0
0.2
0.1
0.0
14.4
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.9
2001
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.3
3.9
0.0
0.5
0.0
0.0
3.9
0.0
0.1
0.6
0.2
0.0
0.1
0.0
0.0
0.0
0.3
0.6
0.0
0.0
0.8
0.6
0.1
0.0
0.0
0.0
0.0
0.0
6.1
0.1
0.0
0.1
0.4
6.8
2002
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
3.1
0.0
0.5
0.0
0.0
1.5
0.0
0.0
1.6
0.1
0.0
0.0
0.0
0.0
0.0
0.8
0.1
0.0
0.0
0.1
0.7
0.0
0.0
0.0
0.0
0.0
0.0
3.4
0.0
0.0
0.0
0.0
6.7
2003
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
2004
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.4
0.0
0.0
0.2
0.0
0.0
1.3
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.1
1.6
2005
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
15.9
0.3
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
1.2
2006
0.0
0.2
0.0
0.1
0.0
0.1
0.0
0.0
2.8
0.3
0.1
0.2
0.0
4.1
0.0
0.0
11.9
1.3
0.0
0.1
0.1
0.1
1.4
0.0
0.0
0.7
0.0
0.0
2.2
0.0
0.0
0.1
0.0
0.2
0.0
1.7
0.0
0.1
0.0
0.5
1.7
2007
0.0
0.0
0.0
0.0
0.0
1.5
0.0
0.0
4.1
0.0
0.5
0.0
0.1
6.5
0.0
0.0
0.1
0.5
0.0
0.0
0.1
0.0
2.1
0.0
0.0
0.7
0.0
2.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.7
0.0
0.3
0.0
0.1
3.6
Species
Lotononis brachyloba
Lycium cinereum
Lycium ferocissimum
Manulea benthamiana
Manulea cheiranthus
Mesembryanthemum guerichianum
Oncosiphon grandiflorum
Oncosiphon suffruticosum
Osteospermum pinnatum
Oxalis spp.
Pelargonium redactum
Pentaschistis airoides
Pharnaceum confertum
Pharnaceum croceum
Pharnaceum dichotomum
Phyllobolus occulatus
Psilocaulon junceum
Ruschia brevibracteata
Ruschia robusta
Sarcocaulon salmoniflorum
Sceletium sp.
Senecio arenarius
Senecio cardaminifolius
Sonderina tenuis
Sonderina tenuis
Stipagrostis brevifolia
Stipagrostis namaquensis
Tetragonia fruticosa
Tetragonia microptera
Trachyandra falcata
Trachyandra tortilis
Tripteris amplectens
Tripteris sinuata
Unidentified species
Ursinia cakilefolia
Ursinia calenduliflora
Wahlenbergia annularis
Wahlenbergia prostrata
Wahlenbergia thunbergiana
Zaluzianskya pusilla
Zaluzianskya benthamiana
Zaluzianskya gilioides
Zygophyllum retrofractum
Total
1991
0.0
0.1
0.0
0.3
0.0
0.3
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.3
0.0
3.6
0.1
0.0
0.2
0.0
0.0
0.0
6.4
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
27.9
1993
0.1
0.0
0.2
0.0
0.0
0.2
0.0
3.4
0.3
0.3
0.0
0.3
0.0
0.0
0.5
0.2
0.3
0.0
3.7
0.1
0.0
1.8
0.0
0.0
0.0
7.6
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
3.1
0.0
0.1
0.0
0.1
0.0
66.4
1994
0.0
0.2
0.0
0.0
0.0
0.1
0.8
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
3.8
0.0
0.0
2.2
0.0
0.0
0.0
6.5
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
48.9
1995
0.2
0.0
0.3
0.0
0.0
0.0
0.1
0.0
0.0
0.5
0.1
0.0
0.0
0.0
0.3
0.0
0.7
0.0
4.5
0.0
0.0
1.4
0.0
0.0
0.0
5.9
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.3
0.2
0.1
0.0
40.9
1997
0.5
0.4
0.0
0.0
0.0
0.6
1.3
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
2.0
0.0
6.5
0.0
0.0
0.1
0.0
0.0
0.0
6.5
0.3
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.1
50.7
1998
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.2
6.2
0.0
0.0
0.0
0.0
0.0
0.0
6.7
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
14.8
172
1999
0.1
0.3
0.0
0.0
0.0
0.3
1.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.0
6.3
0.0
0.0
0.0
0.0
0.0
0.1
8.1
0.3
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
27.2
2000
0.0
0.3
0.0
0.0
0.0
0.5
0.3
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
1.8
0.0
6.4
0.1
0.0
0.0
0.0
0.0
0.0
12.0
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
40.3
2001
0.5
0.4
0.0
0.0
0.0
0.3
6.3
0.0
0.0
0.0
0.2
0.3
0.0
0.0
0.1
0.0
1.4
0.0
6.5
0.1
0.2
0.8
0.0
0.0
0.0
13.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.1
0.3
56.5
2002
0.1
0.2
0.0
0.0
0.0
0.0
3.9
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.1
1.0
0.0
6.5
0.0
0.0
0.2
0.0
0.0
0.3
9.3
0.3
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.1
0.0
0.0
0.0
0.2
41.5
2003
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
6.4
0.0
0.0
0.0
0.0
0.0
0.0
10.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
19.2
2004
0.0
0.2
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
5.9
0.1
0.0
0.0
0.0
0.0
0.0
11.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.3
23.3
2005
0.1
0.4
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
6.1
0.0
0.0
0.0
0.0
0.0
0.0
12.6
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
38.7
2006
1.7
0.2
0.0
0.0
0.2
0.2
3.3
0.0
0.1
0.1
0.1
0.2
0.0
2.2
0.0
0.1
1.7
0.0
7.1
0.0
0.0
1.0
0.1
0.0
0.4
12.4
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.5
1.6
0.0
0.6
0.0
0.3
64.5
2007
0.0
0.1
0.0
0.0
0.0
0.0
6.5
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
6.0
0.0
0.0
3.7
0.2
0.3
0.0
10.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.3
2.0
0.1
0.0
0.4
0.5
0.2
57.6
Table 8.5
Total species and the frequency of strike for the Koperberg Plains line transect
Species
Aizoon canariense
Amellus strigosus
Aridaria noctiflora
Atriplex lindleyi subsp. inflata
Geophyte
Cheiridopsis denticulata
Conicosia elongata
Dimorphotheca sinuata
Drosanthemum sp. (shrub)
Drosanthemum hispidum
Drosanthemum cf. otzenianum
Foveolina dichotoma
Galenia sarcophylla
Galenia cf. fruticosa
Gazania lichtensteinii
Heliophila variabilis
Hermannia tomentosa
Karroochloa schismoides
Lessertia diffusa
Leysera tenella
Lotononis brachyloba
Lotononis falcata
Lycium cinereum
Manulea cheiranthus
Mesembryanthemum guerichianum
Oncosiphon grandiflorum
Osteospermum pinnatum
Oxalis spp.
Psilocaulon subnodosum
Salsola aphylla
Salsola kali
Salsola tuberculata
Senecio arenarius
Senecio cardaminifolius
Tetragonia fruticosa
Tetragonia microptera
Trachyandra spp.
Tripteris hyoseroides
Zaluzianskya benthamiana
Zygophyllum retrofractum
Total
1997
0.0
0.0
1.7
4.5
0.0
0.0
0.1
0.5
1.2
0.2
0.2
1.1
0.4
0.0
1.3
0.0
0.0
0.1
0.0
0.0
0.2
0.0
0.1
0.0
0.2
0.5
0.5
0.2
3.5
0.0
0.0
2.4
0.6
0.0
0.2
0.0
0.1
0.0
0.0
3.9
23.7
1998
0.0
0.0
2.0
5.8
0.0
0.1
0.0
0.0
1.1
0.0
0.2
0.0
0.2
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
2.1
0.0
0.0
2.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.5
20.2
1999
0.0
0.0
2.3
2.3
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.6
0.0
0.0
2.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.5
12.7
173
2000
0.0
0.0
1.3
3.2
0.0
0.0
0.0
0.0
0.7
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.7
0.6
0.0
2.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.3
13.3
2001
0.0
0.0
1.3
1.7
0.0
0.0
0.0
0.0
0.8
0.0
0.2
0.5
0.1
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.1
0.0
1.6
0.0
0.0
2.3
0.2
0.2
0.0
0.5
0.1
0.0
0.0
4.3
14.3
2002
0.0
0.0
2.6
4.3
0.0
0.0
0.0
0.2
2.3
0.0
0.2
7.6
0.3
0.0
0.0
0.1
0.0
0.5
0.0
0.1
0.0
0.0
0.1
0.0
0.1
0.1
0.9
0.0
2.1
0.0
0.0
3.4
6.8
0.2
0.1
0.1
0.0
0.0
0.1
5.8
38.0
2003
0.0
0.0
1.1
1.8
0.0
0.0
0.0
0.0
0.8
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.3
0.0
0.0
2.9
0.0
0.0
0.1
0.0
0.0
0.0
0.0
4.4
12.1
2004
0.0
0.0
1.2
1.3
0.0
0.0
0.0
0.0
1.1
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
2.5
0.0
0.0
0.1
0.0
0.0
0.0
0.0
3.4
10.3
2005
0.1
0.0
1.2
3.1
0.0
0.0
0.0
0.0
0.9
0.0
0.1
2.5
4.0
0.0
0.4
0.0
0.1
0.2
0.2
0.0
0.0
0.1
0.1
0.0
0.4
0.0
1.3
0.0
1.1
0.0
0.0
3.2
1.1
0.0
0.1
0.4
0.0
0.0
0.0
5.2
25.8
2006
0.0
0.0
1.3
3.1
0.0
0.1
0.0
0.1
0.7
0.1
0.0
4.5
7.4
0.1
0.4
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
0.1
0.1
1.5
0.0
1.3
0.6
0.1
2.7
6.3
0.1
0.1
0.4
0.0
0.0
0.0
5.3
36.7
2007
0.0
0.1
1.6
1.8
0.0
0.0
0.0
0.2
0.6
0.1
0.0
6.3
1.1
0.0
0.0
0.0
0.0
1.5
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
1.8
0.2
1.2
0.8
0.0
2.2
12.0
0.5
0.2
0.0
0.0
0.2
0.0
5.1
37.6
Table 8.6
Total species and the frequency of strike for the T’ganagas Plains line transect
Species
Aizoon canariense
Arctotis fastuosa
Bulbine succulenta
Cleretum papulosum
Conicosia elongata
Crassula thunbergiana
Dimorphotheca polyptera
Dimorphotheca sinuata
Drosanthemum hispidum
Foveolina dichotoma
Galenia namaensis
Galenia sarcophylla
Gazania lichtensteinii
Gazania tenuifolia
Geophyte
Grielum humifusum
Gymnodiscus linearifolia
Helichrysum leontonyx
Helichrysum tinctum
Heliophila sesselifolia
Hermannia disermifolia
Hermannia tomentosa
Hirpicium echinus
Hypertelis salsoloides
Karroochloa schismoides
Lessertia diffusa
Leysera tenella
Lotononis brachyloba
Lycium cinereum
Manulea cheiranthus
Manulea gilioides
Mesembryanthamum guerichianum
Oncosiphon grandiflorum
Osteospermum pinnatum
Oxalis spp.
Pelargonium redactum
Pharnaceum dichotomum
Phyllobolus occulatus
Polycarena collina
Psilocaulon junceum
Senecio arenarius
Senecio cardaminifolius
Sutera tristis
Trachyandra bulbinifolia
Tribulus zeyheri
Wahlenbergia prostrata
Zaluzianskya benthamiana
Total
1997
0.1
0.8
0.1
0.0
0.9
0.1
0.1
0.2
0.0
7.5
6.9
0.0
0.0
0.1
0.0
1.2
1.7
0.0
0.0
7.7
0.0
0.0
0.1
0.2
0.1
0.7
3.5
25.4
0.0
0.0
0.0
0.7
2.2
0.1
0.2
0.0
0.1
0.0
5.5
2.0
0.0
0.1
0.0
5.0
0.1
0.0
0.0
73.4
1998
0.0
0.2
0.0
0.0
0.3
0.0
0.0
0.0
0.2
0.0
3.0
0.0
0.0
0.0
0.1
0.0
0.3
0.0
0.2
0.7
0.4
0.0
0.0
0.6
0.0
0.0
0.4
0.1
0.0
0.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
0.0
4.7
0.4
0.0
0.3
0.0
0.4
0.2
0.0
0.0
13.5
1999
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.2
0.0
0.4
0.0
0.1
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.3
0.3
0.0
0.0
3.4
174
2000
1.6
0.2
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.7
5.7
0.0
0.2
0.0
0.3
0.0
0.0
0.0
0.2
0.0
0.0
1.2
0.0
0.8
0.0
0.3
0.0
29.6
0.0
0.0
0.0
3.2
0.0
0.0
0.0
0.0
0.0
0.0
5.6
0.1
0.0
0.2
0.1
0.1
1.4
0.0
0.0
51.7
2001
0.0
6.9
0.1
0.0
0.1
0.0
0.1
0.1
0.0
5.2
6.3
0.0
1.5
0.0
0.4
0.3
0.8
0.0
1.0
9.9
0.0
0.2
0.0
0.2
1.0
0.3
1.0
31.0
0.0
0.0
0.0
0.2
4.1
0.0
0.0
0.3
0.0
0.3
5.7
1.8
0.0
0.1
0.0
0.0
0.1
0.0
0.0
79.0
2002
0.0
2.6
0.0
0.0
0.1
0.0
0.0
0.1
0.2
3.5
1.5
0.0
1.8
0.0
0.1
0.0
0.9
0.0
5.0
17.9
0.0
0.2
0.0
0.2
3.1
0.0
3.0
0.0
0.0
0.1
0.0
0.0
11.7
0.0
0.0
0.0
0.0
0.0
6.3
4.2
0.0
0.1
0.0
0.0
0.0
0.2
0.0
62.8
2003
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
30.6
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
1.3
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
32.5
2004
0.0
1.0
0.0
1.0
0.0
0.0
0.1
0.0
0.0
1.1
0.1
0.0
0.1
0.0
0.2
0.0
0.0
0.0
0.6
11.8
0.0
0.0
0.0
0.0
1.8
0.1
1.2
1.6
0.0
0.1
0.0
0.2
4.4
0.0
0.2
0.0
0.0
0.2
0.1
1.7
0.0
0.0
0.0
0.6
0.0
0.0
0.0
28.2
2005
4.4
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
12.3
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.8
0.0
0.3
0.1
2.8
0.0
0.0
0.0
4.9
0.8
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.1
0.0
0.2
2.7
0.0
0.0
30.8
2006
0.0
6.5
0.0
0.2
0.0
0.0
0.0
0.0
0.0
1.7
20.0
0.1
1.8
0.1
0.4
0.0
0.4
1.2
0.0
11.3
0.0
0.0
0.2
1.0
1.9
0.2
1.4
24.6
0.0
0.0
0.1
0.2
7.4
0.0
0.2
0.0
0.0
0.6
1.0
1.0
0.2
0.2
0.0
0.0
0.1
0.1
0.0
84.1
2007
0.0
0.2
0.0
0.0
0.0
0.1
0.1
0.2
0.0
12.0
0.1
0.0
0.5
0.0
0.5
0.0
1.2
0.3
0.0
21.5
0.1
0.0
0.0
0.1
8.4
0.2
1.5
2.6
0.1
0.0
0.0
0.0
26.7
0.0
0.2
0.0
0.0
0.1
0.1
7.6
0.3
0.0
0.0
0.0
0.0
0.7
0.2
85.6
Table 8.7
Species
Total species and the frequency of strike for the Zebrawater Foothills line transect
1974
1975
1976
1977
1978
1979
1980
1982
1984
1985
1986
1987
1989
1990
1991
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Adenogramma glomerata
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
Aizoon canariense
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Aptosimum indivisum
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Aptosimum spinescens
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
Arctotis fastuosa
0.1
0.1
1.6
0.1
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Asparagus fasciculatus
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Bromus pectinatus
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
Bulbine succulenta
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Cephalophyllum ebracteatum
0.1
0.1
0.1
0.1
0.2
0.1
0.0
0.0
0.4
0.1
0.0
0.0
0.2
0.0
0.1
0.2
0.1
0.2
0.2
0.1
0.1
0.2
0.1
0.0
0.1
0.1
0.1
0.0
0.1
0.0
Chaetobromus involucratus subsp. dregeanus
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Cheiridopsis denticulate
0.0
0.5
0.4
0.2
0.4
0.2
0.5
0.3
0.2
0.1
0.2
0.2
0.2
0.3
0.0
0.8
0.3
0.3
0.2
0.5
0.5
0.6
0.4
0.4
0.5
0.5
0.5
0.5
0.4
0.3
Chlorophytum crassinerve
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Chrysocoma ciliata
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Cleretum papulosum
0.0
0.0
0.0
0.3
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
Cotula nudicaulis
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
1.3
Cotula leptalea
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.7
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Crassula muscosa subsp. obtusifolia
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Crassula muscosa subsp. muscosa
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.1
0.1
0.0
0.1
0.1
0.0
0.1
0.2
0.0
0.1
0.1
0.1
0.0
0.1
0.1
0.1
0.1
0.0
0.1
0.0
Crassula subaphylla
0.0
0.0
0.1
0.1
0.0
0.1
0.0
0.1
0.0
0.1
0.1
0.0
0.1
0.1
0.0
0.3
0.1
0.2
0.3
0.2
0.0
0.0
0.0
0.1
0.6
0.6
0.1
0.8
0.6
0.8
Crassula thunbergiana
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.2
0.0
0.0
0.1
0.1
0.3
0.1
0.1
0.3
0.2
0.0
0.0
0.0
0.0
0.2
Cyanella orchidiformis
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Cyperaceae
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
Cyphia sp.
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
Diascia namaquana
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
Dimorphotheca sinuata
0.0
0.5
0.4
0.3
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
Dischisma spicata
0.0
0.1
0.5
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Dorotheanthus bellidiformis subsp. hestermalanensis
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Drosanthemum sp. (shrub)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.2
0.0
0.0
Ehrharta barbinodis
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Ehrharta calycina
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.0
Ehrharta delicatula
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
Ehrharta longiflora
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
Eriocephalus brevifolius
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
1.5
0.0
0.2
0.2
0.0
0.0
0.0
0.0
0.0
Eriocephalus microphyllus
3.1
2.7
4.7
3.9
3.0
3.3
2.5
3.3
2.9
3.0
3.8
3.7
4.2
5.1
5.0
5.5
6.1
5.2
5.8
6.1
6.2
5.2
6.3
6.9
3.7
7.2
5.7
7.3
5.8
3.5
Euphorbia decussata
0.9
0.7
1.3
0.8
0.0
1.3
0.9
2.2
2.3
1.9
2.2
2.5
2.7
2.5
2.6
2.4
2.7
2.4
2.9
3.4
3.2
3.0
3.5
3.3
3.4
3.8
3.1
3.6
4.1
2.9
Euphorbia mauritanica
0.2
0.5
0.3
0.5
0.4
0.4
0.3
0.6
0.5
0.4
0.9
0.9
0.8
0.9
1.0
0.5
0.7
0.9
0.7
0.6
0.9
0.8
0.8
0.7
0.5
0.4
0.2
0.1
0.1
0.3
Felicia brevifolia
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Felicia namaquana
0.0
0.3
0.2
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.7
0.0
0.7
0.1
0.0
0.0
0.1
0.0
0.1
0.2
0.0
0.0
0.0
0.1
1.2
Foveolina dichotoma
0.0
0.8
0.2
0.6
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.8
1.3
0.5
1.2
0.6
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.1
Galenia africana
3.7
3.8
3.9
4.4
4.7
1.5
0.9
2.1
2.5
2.5
3.5
3.4
4.4
3.1
2.6
2.7
3.0
2.9
2.7
3.0
3.7
2.8
4.0
3.2
3.0
3.1
2.8
2.3
2.2
2.6
Galenia meziana
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
Galenia namaensis
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.1
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
Galenia sarcophylla
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Gazania heterochaeta
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Geophyte
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
Grielum humifusum
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
175
1974
1975
1976
1977
1978
1979
1980
1982
1984
1985
1986
1987
1989
1990
1991
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Mesembryanthemaceae
Species
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
Helichrysum leontonyx
0.0
0.2
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.2
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
1.0
3.4
13.1
Helichrysum tinctum
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.8
0.2
1.4
0.4
0.2
0.0
0.0
0.0
0.5
2.5
0.0
0.1
0.0
0.0
0.0
Heliophila coronopipfolia
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
Heliophila sesselifolia
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Heliophila variabilis
0.1
0.8
1.4
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
1.0
0.0
0.7
0.2
0.2
0.0
0.0
0.0
1.0
1.9
0.6
0.3
0.9
3.3
3.3
Hemimeris racemosa
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
Hermannia disermifolia
0.0
0.1
0.1
0.1
0.2
0.1
0.1
0.1
0.2
0.1
0.4
0.4
0.5
0.4
0.1
0.5
0.4
0.4
0.4
0.5
0.4
0.3
0.6
0.4
0.6
0.6
0.3
0.4
0.3
0.2
Hermannia trifurca
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.2
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
Hirpicium alienatum
0.0
0.4
0.6
0.8
0.2
0.6
0.4
0.1
0.3
0.4
0.4
0.4
0.3
0.2
0.4
0.4
0.5
0.2
0.1
0.3
0.3
0.2
0.3
0.3
0.3
0.3
0.2
0.7
1.0
0.6
Hirpicium echinus
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Hypertelis salsoloides
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Ifloga glomerata
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.1
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Indigofera sp. (HR84)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
Karroochloa schismoides
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.3
0.1
Lachenalia sp.
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Lampranthus godmanniae
0.0
0.0
0.8
0.6
0.3
0.1
0.1
0.2
0.0
0.1
0.2
0.3
0.8
0.1
0.0
0.2
0.3
0.2
0.4
0.4
0.0
0.0
0.0
0.0
0.0
0.3
0.2
0.4
0.0
0.2
Lapeirousia silenoides
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Lasiopogon micropoides
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
Lebeckia sericea
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.2
0.0
0.1
0.2
0.1
0.2
0.2
0.0
0.1
0.3
0.2
0.4
0.1
0.2
0.2
0.3
0.3
0.3
0.2
0.3
0.4
Leipoldtia plana
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.8
0.3
1.5
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.7
0.0
0.0
Leipoldtia schultzei
9.1
7.4
8.8
5.3
8.5
9.8
9.7
11.6
11.8
12.6
14.2
10.7
11.5
9.1
12.9
12.1
13.6
12.8
13.4
13.7
16.2
12.9
13.9
17.5
16.5
17.9
14.3
15.8
12.8
7.9
Lessertia diffusa
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
Leysera tenella
0.0
0.3
1.0
1.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.5
Lotononis brachyloba
0.0
0.0
1.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
1.4
0.0
Lotononis falcata
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
Lycium cinereum
0.3
0.2
0.1
0.0
0.2
0.3
0.2
0.2
0.0
0.5
0.4
0.5
0.3
0.2
0.2
0.4
0.2
0.3
0.3
0.3
0.2
0.0
0.1
0.1
0.2
0.0
0.0
0.1
0.2
0.3
Lycium oxycarpum
0.0
0.1
0.2
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.2
0.4
0.1
0.0
0.0
Manochlamys albicans
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
Manulea cheiranthus
0.0
0.1
0.1
0.1
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
1.1
0.0
Melolobium candicans
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Mesembryanthemum guerichianum
0.6
0.3
0.1
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.3
0.2
0.1
0.4
0.0
0.2
0.4
0.6
0.0
0.0
0.1
0.9
0.0
0.0
Microloma sagittatum
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Oncosiphon grandiflorum
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Oncosiphon suffruticosum
0.0
0.0
0.0
0.2
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.4
0.2
0.3
0.3
0.0
0.1
0.0
0.1
0.3
0.9
0.0
0.2
0.0
0.9
2.5
Other unidentified species
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Othonna perfoliata
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Oxalis spp.
0.0
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.8
0.3
0.3
0.3
0.2
0.1
0.0
0.0
0.0
0.8
0.4
0.0
0.3
0.1
0.9
1.2
Pelargonium carnosum
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Pelargonium ramosissimum
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.0
0.0
0.2
0.1
0.0
0.0
Peliostomum virgatum
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
Pentaschistis airoides
0.0
0.3
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
0.3
0.5
Pentzia incana
0.3
0.2
0.3
0.2
0.2
0.5
0.2
0.3
0.2
0.0
0.3
0.3
0.3
0.2
0.3
0.2
0.1
0.3
0.3
0.3
0.4
0.3
0.5
0.3
0.3
0.0
0.2
0.2
0.1
0.1
Pharnaceum aurantium
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
Phyllobolus occulatus
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.1
0.0
0.0
Plantago cafra
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Polycarena collina
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
Prenia pallens
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
Psilocaulon junceum
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.2
0.2
0.2
0.2
0.1
0.2
0.2
0.2
0.2
0.4
0.2
0.3
0.4
0.3
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
176
2007
1974
1975
1976
1977
1978
1979
1980
1982
1984
1985
1986
1987
1989
1990
1991
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Pteronia divaricata
Species
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Pteronia incana
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.2
0.0
0.0
0.2
0.1
0.1
0.0
0.0
0.0
0.2
0.0
Pteronia paniculata
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Pteronia undulata
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Ruschia brevibracteata
0.5
0.0
0.5
0.6
1.9
0.3
0.7
0.6
0.8
0.1
0.9
0.5
0.5
0.5
0.4
0.4
0.3
0.6
0.2
0.1
0.2
0.2
0.4
0.0
0.1
0.1
0.0
0.0
0.0
0.0
Ruschia elineata
1.2
2.0
1.5
1.3
1.1
0.7
1.2
0.7
1.2
1.3
0.8
0.6
0.9
0.6
0.6
0.2
0.5
0.5
0.4
0.2
0.3
0.2
0.2
0.4
0.2
0.2
0.1
0.3
0.0
0.0
Ruschia robusta
5.0
4.4
5.4
12.3
6.1
6.1
6.1
6.8
7.0
7.3
7.0
7.5
6.2
7.1
7.0
6.3
7.4
6.4
4.4
7.4
8.5
7.1
6.3
6.2
6.2
6.8
4.7
4.3
4.5
2.2
Ruschia sp.
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
Ruschia viridifolia
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Scirpus nodosus
0.0
0.1
0.1
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.1
0.1
0.0
0.0
0.1
0.1
0.1
0.1
0.2
0.1
0.2
0.1
0.0
0.0
0.1
0.3
0.2
0.1
0.0
0.1
Searsia undulata
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Selago divaricata
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Senecio cardaminifolius
0.0
0.3
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
0.5
0.4
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.6
0.0
0.0
0.0
0.6
2.1
Silene capense
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Tetragonia fruticosa
0.0
0.2
0.6
0.3
0.1
0.2
0.3
0.1
0.3
0.2
0.3
0.0
0.5
0.2
0.2
0.2
0.6
0.1
0.0
0.1
0.3
0.2
0.1
0.3
0.1
0.1
0.2
0.1
0.3
0.0
Tetragonia microptera
0.0
0.0
0.0
0.2
0.0
0.0
1.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.1
0.2
0.0
Thesium lineatum
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Tribolium utriculosum
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
Trichogyne paronychioides
0.0
0.0
0.1
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.5
Tripteris amplectens
0.0
0.1
4.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.2
0.0
Tripteris hyoseroides
0.0
0.0
0.6
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.6
0.2
Tripteris sinuata
0.6
0.6
1.0
0.7
0.7
1.0
0.8
0.8
0.7
0.7
1.2
0.9
1.1
0.9
1.2
1.0
0.9
1.1
1.0
1.4
1.3
0.9
1.2
1.6
0.9
1.6
1.4
1.4
1.8
1.9
Tylecodon wallichii
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.1
Ursinia cakilefolius
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Ursinia calenduliflora
0.0
0.4
1.7
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.3
0.2
Ursinia nana
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
Aizoaceae (vygie, groen vetblaar)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.1
1.2
0.0
0.0
0.0
Wahlenbergia annularis
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
Wahlenbergia prostrata
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.2
Wiborgia monoptera
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.1
0.0
0.3
0.0
0.1
0.1
0.0
0.1
0.1
0.4
0.1
0.2
0.3
0.1
0.0
0.4
0.3
0.0
0.0
0.4
0.1
0.2
Zaluzianskya benthamiana
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.3
0.4
0.9
Zaluzianskya gilioides
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.6
Zygophyllum divaricatum
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
Zygophyllum foetidum
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
Zygophyllum sp. nov.
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
Total
26.0
29.1
47.6
39.5
28.7
27.3
29.0
30.8
32.4
32.2
38.3
33.5
36.5
32.5
44.0
48.9
41.2
45.0
37.6
43.1
45.1
38.4
40.1
48.2
47.6
46.5
37.7
45.0
51.3
55.3
177
Was this manual useful for you? yes no
Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Download PDF

advertisement