Succulent Karoo Ecosystem Plan: Technical Report - bgis-sanbi

Cape Conservation Unit, Report No CCU 1/03 

Botanical Society of South Africa 

March 2003 

Succulent Karoo Ecosystem Plan 

BIODIVERSITY COMPONENT 

TECHNICAL REPORT 

Amanda Driver 

Philip Desmet 

Mathieu Rouget 

Richard Cowling 

Kristal Maze

Acknowledgements 

Our grateful thanks go to the many people who participated in numerous ways in the 

SKEP Biodiversity Component. 

In particular we would like to thank 

• Sarah Frazee (Conservation International) 

• Daphne Hartney (Eco-Africa) 

• Glynnis Barodien (Botanical Society of South Africa) 

• Benis Egoh (IPC, UCT) 

• Zuziwe Jonas (IPC, UCT) 

• Wendy Paisley (Botanical Society of South Africa) 

• Tessa Mildenhall (Conservation International) 

• Penny Waterkeyn (freelance graphic designer) 

• Members of the SKEP Biodiversity Advisory Group (see Section 19) 

• Those individuals and organisations who generously provided data (see Sections 

8 & 14) 

• The expert mappers (see Section 8) 

• The SKEP sub-regional champion teams 

• All those who participated in the SKEP Biodiversity Component Workshops 

SKEP Biodiversity Component Technical Report, March 2003 Page i

Contents 

Part A: Context and Background...................................................................................1 

1. Introduction .........................................................................................................1 

2. The Succulent Karoo Biome...............................................................................3 

3. Conservation Planning Methodology .................................................................5 

Part B: Technical Process.............................................................................................8 

4. Overview of the Technical Steps in the Conservation Planning Process..........8 

5. Planning Domain ..............................................................................................11 

Defining the planning domain....................................................................................11 

Finalising the sub-regional divisions ..........................................................................12 

Overlapping planning domains between SKEP and other projects ...............................13 

6. Digital Elevation Model .....................................................................................15 

Why a DEM is important ...........................................................................................15 

Error estimation........................................................................................................15 

Comparison of the DEMs available for the South African part of the planning domain ...17 

Creating the SKEP DEM...........................................................................................18 

Limitations of the SKEP DEM....................................................................................19 

7. Vegetation Map.................................................................................................20 

Why the vegetation map is important .........................................................................20 

Constraints on the development of a SKEP vegetation map........................................21 

Methods ..................................................................................................................22 

Interpretation and limitations .....................................................................................25 

8. Expert Mapping.................................................................................................27 

Why expert mapping?...............................................................................................27 

Expert mapping methodology ....................................................................................27 

Assessment of the expert mapping exercise ..............................................................30 

9. Species Distribution Data .................................................................................32 

How species distribution data were used ...................................................................32 

Data collection .........................................................................................................32 

Data analysis and results..........................................................................................35 

Interpretation and limitations .....................................................................................41 

10. Spatial Components of Ecological and Evolutionary Processes .....................43 

Why spatial components of processes are important ..................................................43 

How the process layer was developed.......................................................................44 

Limitations of the process layer .................................................................................49 

11. Land Use and Habitat Transformation .............................................................51 

Why land use and habitat transformation are important ...............................................51 

What needs to be mapped ........................................................................................51 

Data sources ...........................................................................................................52 

Methods ..................................................................................................................53 

Limitations of the land-use layers ..............................................................................59 

12. Protected Areas ................................................................................................61 

Why a protected area layer is important .....................................................................61 

Data sources and constraints ....................................................................................61 

Categories of protected areas ...................................................................................61 

Limitations of the protected area layer .......................................................................62 

SKEP Biodiversity Component Technical Report, March 2003 Page ii

13. Planning Units...................................................................................................64 

What are planning units? ..........................................................................................64 

How the planning unit layer was developed................................................................64 

Limitations of the planning unit layer ..........................................................................64 

14. Conservation Targets .......................................................................................66 

The role of targets ....................................................................................................66 

Targets in CAPE ......................................................................................................67 

Targets in SKEP ......................................................................................................68 

Interpretation and limitations of species-accumulation targets .....................................73 

15. Identifying Geographic Priorities ......................................................................74 

Irreplaceability map (conservation options) ................................................................74 

Framework for action map ........................................................................................75 

Nine geographic priority areas ...................................................................................80 

Part C: Organisational Process...................................................................................82 

16. Why Write Up the Process?.............................................................................82 

17. SKEP Components and Structures..................................................................84 

18. Biodiversity Team .............................................................................................89 

19. Biodiversity Advisory Group .............................................................................92 

20. Biodiversity Component Workshop 1...............................................................94 

21. Acquisition of Biological Data ...........................................................................96 

22. Land-Use Data Acquisition through Sub-Regional Champions.......................98 

Stakeholder mapping methodology ............................................................................98 

Assessment of the stakeholder mapping exercise ......................................................99 

23. Focus Group on Ecological Processes..........................................................101 

24. Targets Workshop ..........................................................................................102 

25. Biodiversity Component Workshop 2.............................................................103 

26. Action Planning Workshops............................................................................106 

Developing products for Action Planning Workshops ................................................106 

Assessment of products at Action Planning Workshops ............................................107 

Part D: Tables and References.................................................................................109 

27. Additional Tables ............................................................................................109 

28. References......................................................................................................143 

Part E: Appendices (available as a separate document)..........................................147 

SKEP Biodiversity Component Technical Report, March 2003 Page iii

List of Figures 

Figure 1: The Succulent Karoo biome ................................................................................ 3 

Figure 2: The SKEP planning domain showing sub-regions ................................................13 

Figure 3: Overlapping planning domains of the CAPE, STEP and SKEP projects ................14 

Figure 4: Geographic extent of the four DEMs used to compile the SKEP DEM ...................16 

Figure 5: SKEP expert map ..............................................................................................31 

Figure 6: Classification of SKEP QDS into Succulent Karoo and non-succulent Karoo, 

geographic priority areas (top right) and SKEP sub-regions (bottom left)......................34 

Figure 7: Flow diagram illustrating the steps involved in preparing the summary species 

distribution databases for analysis.............................................................................36 

Figure 8: Steps involved in determining endemicity of species recorded in the Succulent 

Karoo ......................................................................................................................37 

Figure 9: The relationship between collecting intensity (i.e. the number of records per QDS) 

and the number of species recorded in a QDS for plants.............................................38 

Figure 10: The overlap between conservation priorities based on the number of endemic 

plants per QDS versus areas mapped by experts .......................................................39 

Figure 11: The distribution of plant collecting records, number of species and number of 

endemic plants in the Succulent Karoo. .....................................................................40 

Figure 12: Spatial components of ecological processes in the SKEP planning domain .........50 

Figure 13: Topographic regions in the SKEP planning domain............................................50 

Figure 14: Frequency distribution of current irreversible habitat transformation (urban, 

cropping, and mining; i.e. area not available for conservation) among the Succulent 

Karoo vegetation types .............................................................................................54 

Figure 15: Map of habitat transformation showing the different land-use categories .............55 

Figure 16: Spatial patterns of the likelihood of mining, urban development, crop agriculture 

and ostrich farming in the next ten years ....................................................................58 

Figure 17: Spatial pattern of vulnerability to future land-use pressure in the SKEP planning 

domain ....................................................................................................................59 

Figure 18: Protected areas in the SKEP planning domain...................................................63 

Figure 19: Planning units for the SKEP planning domain ....................................................65 

Figure 20: How targets relate to the division of the landscape and possible land-uses 

compatible with each zone ........................................................................................67 

Figure 21: The location of survey points within the SKEP planning domain..........................70 

Figure 22: Species-accumulation curves for 17 SKEP vegetation types...............................71 

Figure 23: Irreplaceability values in the SKEP planning domain, based on targets set for 

vegetation types and expert-identified areas ..............................................................75 

Figure 24: An irreplaceability-vulnerabilty graph.................................................................76 

Figure 25: SKEP Framework for Action for Namaqualand ..................................................78 

Figure 26: Overlay of ecological processes for Namaqualand (to be used with the framework 

for action map) .........................................................................................................79 

Figure 27: Geographic priority areas for conservation in the Succulent Karoo biome ............80 

Figure 28: Organogram of SKEP structures .......................................................................85 

Figure 29: Timeline for the planning phase of SKEP, showing the work of the Biodiversity 

Component ..............................................................................................................88 

Figure 30: Summarised breakdown of the Biodiversity Component budget ..........................91 

SKEP Biodiversity Component Technical Report, March 2003 Page iv

List of Tables 

Table 1: Technical steps in the conservation planning process ............................................ 6 

Table 2: Summary of the four DEMs used to compile the SKEP DEM .................................15 

Table 3: Summary statistics comparing the CM, ARC and a XY shifted ARC DEMs to the spot 

height information for three regions in Namaqualand ..................................................18 

Table 4: Classes generated for each environmental layer in the development of the Namibian 

broad habitat map ....................................................................................................25 

Table 5: QDS species distribution datasets used in SKEP..................................................33 

Table 6: Number of database records used to compile the biodiversity statistics for the 

Succulent Karoo.......................................................................................................34 

Table 7: Summary of endemicity status of Succulent Karoo plant species ...........................35 

Table 8: Summary statistics at the order level for Amphibian, Bees, Termites, Mammals, 

Scorpions and Reptiles that occur in the Succulent Karoo ...........................................41 

Table 9: Key ecological and evolutionary processes for maintaining biodiversity in the 

Succulent Karoo (modified from Cowling et al. 1999a) ................................................44 

Table 10: Spatial components of ecological and evolutionary processes identified in the SKEP 

planning domain.......................................................................................................45 

Table 11: Classification of edaphic interfaces based on unique combination of parent material, 

according to the potential for species movement ........................................................47 

Table 12: Extent of habitat transformation within Succulent Karoo and the SKEP planning 

domain ....................................................................................................................55 

Table 13: Criteria used to derive the likelihood of mining in the next ten years .....................56 

Table 14: Rules used to summarise the likelihood of mining for each planning unit ..............56 

Table 15: Criteria used to derive the likelihood of urban development in the next ten years ..57 

Table 16: Rules used to summarise the likelihood of urban development for each planning 

unit..........................................................................................................................57 

Table 17: Criteria used to derive likelihood of crop agriculture in the next ten years..............57 

Table 18: Criteria used to derive likelihood of ostrich farming in the next ten years ...............58 

Table 19: Summary of vulnerability index for each planning unit .........................................59 

Table 20: Area conserved in Category 1 and 2 reserves in the Succulent Karoo..................62 

Table 21: Planning units used for SKEP............................................................................64 

Table 22: Sources of phytosociological survey data used in the SKEP project .....................69 

Table 23: The scale used to set targets for expert-identified areas ......................................72 

Table 24: Biodiversity Advisory Group members ................................................................92 

Table 25: The subdivision of South African vegetation types for SKEP..............................109 

Table 26: A list of the sand movement corridors identified in SKEP and their component 

SKEP vegetation units ............................................................................................115 

Table 27: Combinations of environmental classes and rules used to develop the broad habitat 

unit map ................................................................................................................117 

Table 28: A summary of the number of plant families, genera and species found in the 

Succulent Karoo.....................................................................................................121 

Table 29: Summary statistics for the 431 bird species that have been recorded in the 

Succulent Karoo.....................................................................................................122 

Table 30: A list of duplicate species numbers encountered in the bird database.................126 

Table 31: Summary statistics at the generic level for Amphibians, Bees, Termites, Mammals, 

Scorpions and Reptiles that occur in the Succulent Karoo .........................................127 

Table 32: Summary statistics at the class level for Amphibian, Bees, Termites, Mammals, 

Scorpions and Reptiles that occur in the Succulent Karoo .........................................132 

Table 33: Targets set for vegetation types .......................................................................133 

Table 34: Targets set for expert -identified areas ..............................................................138 

SKEP Biodiversity Component Technical Report, March 2003 Page v

Part A: Context and Background 

1. Introduction 

The Succulent Karoo biome is one of 25 internationally recognised biodiversity 

hotspots, and is the world’s only arid hotspot. Yet only 3.5% of the biome’s 

116 000 km 2 area is formally conserved, and the Succulent Karoo’s biodiversity is 

under pressure from a range of sources (discussed further in Section 2). 

In this context, the goal of the Succulent Karoo Ecosystem Plan (SKEP) is to provide 

an overarching framework to guide conservation efforts in the Succulent Karoo. 

The planning phase of the SKEP project ran from January to August 2002, and was 

led by Conservation International’s Southern Africa Hotspots Programme. 1 It aimed 

to: 

• provide a hierarchy of priority actions to guide conservation efforts and donor 

investment in the biome (both on and off formal reserves); 

• build human resource capacity to implement the plan by including training and 

mentorship activities as part of the planning process; 

• generate the institutional and government support required to ensure its effective 

implementation. 

The planning phase of SKEP was structured as four distinct but related components, 

dealing with: 

• biodiversity; 

• socio-political issues; 

• resource economics; 

• institutional issues. 

The Botanical Society of South Africa, in partnership with South Africa’s National 

Botanical Institute (NBI), was contracted by Conservation International to undertake 

the Biodiversity Component of SKEP. Another partner in the Biodiversity Component 

of SKEP was the Institute for Plant Conservation (IPC) at the University of Cape 

Town. 

The goal of the Biodiversity Component of SKEP was to identify broad-scale 

geographic priorities for terrestrial biodiversity conservation in the Succulent Karoo 

biome, using a systematic conservation planning approach. Systematic conservation 

planning is explained in greater detail in Section 3. 

Because the Succulent Karoo is a large area spanning two countries and three 

provinces within South Africa, and incorporating diverse habitats and socio-economic 

systems, the area was divided into four sub-regions: 

• Namibia-Gariep; 

1 Conservation International, established in 1987, is an international NGO based in the United States and working in 

over 30 countries. CI’s work focuses on 25 global biodiversity hotspots – the richest and most threatened reservoirs 

of plant and animal life on earth. The Hotspots approach to the conservation of threatened ecosystems and species 

is a highly targeted strategy for tackling the overwhelming problem of biodiversity loss at the global level. For more 

information visit www.conservation.org. 

SKEP Biodiversity Component Technical Report, March 2003 Page 1

• Namaqualand; 

• Hantam-Tanqua-Roggeveld; 

• Southern Karoo. 

SKEP champions were appointed in each of these sub-regions as part of the work of 

the Socio-Political Component. The champions were people working in existing 

organisations in each of the sub-regions. Each champion had a full-time assistant 

funded by SKEP. The Biodiversity Team worked closely with the sub-regional 

champion teams at various stages of the project. The structure and functioning of the 

Biodiversity Component and the champion teams is explained in greater detail in 

Section 17. 

The Succulent Karoo hotspot has been idenitified as a priority for investment by the 

Critical Ecosystem Partnership Fund (CEPF). 2 One of the products of the planning 

phase of SKEP was an Ecosystem Profile that was submitted to CEPF. On the basis 

of this profile, the CEPF Donor Council generously approved an $8 million grant for 

the Succulent Karoo Hotspot, to be invested over a five-year period. However, the 

aims and scope of SKEP went beyond securing a CEPF grant and implementing 

CEPF-funded projects. It is hoped that local and regional stakeholders, and other 

donors and investors in the Succulent Karoo, will be guided by the priorities identified 

by SKEP. SKEP has already moved into the implementation phase, and sub-regional 

co-ordinators have been established to facilitate this process. 

This report is structured in three parts: 

• Part A introduces the Succulent Karoo, SKEP, and the systematic conservation 

planning approach used by the Biodiversity Component of SKEP. 

• Part B explains the technical aspects of the conservation planning process 

undertaken for SKEP and presents the results. 

• Part C discusses how the Biodiversity Component of SKEP was managed as a 

project, including the organisational structures and processes involved. 

Part A is structured as follows: 

• Section 2 explains why the Succulent Karoo is worthy of its status as a global 

biodiversity hotspot. 

• Section 3 outlines the systematic conservation planning approach used in SKEP. 

This report is available in electronic format from www.botanicalsociety.org.za/ccu. 

Other SKEP products that are publicly available include: 

• Selected GIS layers and images produced by the Biodiversity Component 

(available from the Conservation Planning Unit at http://cpu.uwc.ac.za); 

• The Succulent Karoo Ecosystem Profile (available at www.cepf.net or 

www.dlist.org); 

• The SKEP Twenty Year Strategy (available at www.cepf.net or www.dlist.org); 

• The SKEP First Phase Report, sub-regional reports and other documentation 

(available at the SKEP kiosk at www.dlist.org). 

2 CEPF is a joint initiative of Conservation International, the Global Environment Facility, the Government of Japan, 

the MacArthur Foundation and the World Bank. CEPF aims to dramatically advance conservation of earth's 

biodiversity hotspots by providing support to non-government, community and grassroots organisations. A 

fundamental goal is to ensure civil society is engaged in biodiversity conservation. For further information, visit 

www.cepf.net. 


2. The Succulent Karoo Biome 

The Succulent Karoo biome, shown in Figure 1, extends from the south-west through 

the north-western areas of South Africa and into southern Namibia. This region’s 

levels of plant diversity and endemism rival those of rain forests, making the 

Succulent Karoo an extraordinary exception to the low diversity typical of arid areas, 

and the only arid ecosystem to be recognised as a global biodiversity hotspot. Nearly 

one third of the plant species of the region are endemic and the region boasts the 

richest variety of succulent flora in the world (just under a third of the Succulent 

Karoo’s flora are succulents). In addition to its floral diversity, the biome is a centre of 

diversity for reptiles and many groups of invertebrates. 

Figure 1: The Succulent Karoo biome 

The rich biodiversity of the Succulent Karoo is due to an extensive and complex array 

of habitat types derived from topographical and climatic diversity in the region’s 

rugged mountains, semi-arid shrublands, and coastal dunes. The hallmark of the 

Succulent Karoo is its exceptionally diverse and endemic-rich flora, especially 

succulents and bulbs. The 116 000 km 2 biome is home to 6356 plant species, 40% of 

which are endemic 3 and 936 (17%) of which are Red Data Listed. 4 This biodiversity is 

due to massive speciation of an arid-adapted biota in response to unique climatic 

conditions and high environmental heterogeneity. The high regional plant richness is 

the result of high compositional change of species-rich communities along these 

environmental and geographical gradients. Many species are extreme habitat 

specialists, mainly related to soil-type, of limited range size. Local endemism (i.e. the 

3 6 356 species in 1 002 genera and 168 families. Approximately 29% of the flora are succulent plants and 18% 

geophytes. 1630 (26%) species are strict endemics and 905 (14%) are near-endemics (i.e. centre of distribution in 

the Succulent Karoo). 80 genera are endemic, mostly succulent and bulb genera. These figures include ferns. 

4 Previous figures (now updated by SKEP): 4 849 plant species in 730 genera, of which 1 940 species (40%) and 67 

genera endemic; 851 Red Data List species (Hilton-Taylor 1996). 


estriction of species to extremely small ranges of less than 50 km 2 ) is most 

pronounced among succulents, especially Mesembryanthemaceae, and bulbs. (See 

Appendix 1, “Magical Mesembs: Floral Fantasies of a Parched Paradise”, for more 

on Mesembryanthemaceae. 5 ) Similar patterns of compositional change along 

gradients have been observed for certain groups of invertebrates. In addition to 

invertebrates, faunal diversity and endemism is high for reptiles, amphibians and 

some mammal taxa. 

The spectacular diversity and endemism of the Succulent Karoo biota is 

comprehensively described in numerous articles and books. See, for example, Dean 

and Milton (1999), Low and Rebelo (1996), and Milton et al. (1997). 

In spite of its extraordinary levels of biodiversity, the conservation status of the 

Succulent Karoo is poor. Only 3.5% of the biome is formally conserved. This 

protected area system, like most others in the world, is not representative of the 

region’s biodiversity; consequently many biodiversity features have no protection 

status. In particular, the protected area system has not been designed to 

accommodate the ecological and evolutionary processes that maintain and generate 

the Succulent Karoo’s biodiversity. 

In spite of low population densities, the Succulent Karoo’s biodiversity is under 

extreme pressure from human impacts, especially mining, crop agriculture, ostrich 

farming, overgrazing, illegal collection of fauna and flora, and anthropogenic climate 

change. 

However, irreversible land transformation in the Succulent Karoo is not extensive. 

Although a substantial portion of the biome is at risk from overgrazing, only 5% has 

been irreversibly transformed. Pervasive aridity, low irrigation potential and 

inaccessible mountain areas have limited the expansion of agriculture, invasive 

species, and urban development pressures that have transformed so much of the 

adjacent Cape Floristic Kingdom. In fact, as a result of the demise of the historical 

herds of springbok that once grazed the area, livestock grazing, a land-use that 

dominates 90% of the Succulent Karoo, is compatible with biodiversity conservation if 

managed properly. Well-managed livestock-grazing regimes can help maintain 

niches for plant diversity. 

Low levels of irreversible habitat transformation, opportunities for biodiversity-friendly 

forms of land use in many areas, together with low population density and low 

opportunity costs of conservation in most of the region, mean that there are still many 

options for conserving the Succulent Karoo’s biodiversity in and off protected areas. 

5 Thanks to Gideon Smith of the National Bota nical Institute (and a member of the Biodiversity Advisory Group) for 

writing this short piece for SKEP. 


3. Conservation Planning Methodology 

The goal of the Biodiversity Component of SKEP was to identify broad-scale spatial 

priorities for terrestrial biodiversity conservation in the Succulent Karoo biome, using 

a systematic conservation planning approach. 

Conservation planning is a branch of conservation biology that seeks to identify 

spatially explicit options and priorities for the conservation of biodiversity. This is 

important given the limited resources, human and financial, available for conservation 

efforts. It makes sense to channel those limited resources to areas and activities that 

will have the greatest impact in terms of conserving biodiversity. 

The starting point for conservation planning is that we should be strategic in our 

conservation efforts. We should aim to conserve: 

• a representative sample of all ecosystems and species (the principle of 

representiveness; Austin and Margules 1986); 

• ecological and evolutionary processes that enable ecosystems to persist over 

time (the principle of persistence; Soulé 1987, Cowling and Pressey 2001). 

To be most effective, conservation planning should be systematic. Systematic 

approaches to conservation planning share the following features: They are: 

• data-driven; 

• target-based (see below); 

• efficient (in terms of the land area identified to achieve targets); 

• transparent and repeatable (assumptions are made explicit); 

• flexible (the results give options for achieving targets). 

For more detail on the systematic conservation planning approach, see Margules and 

Pressey (2000). 

A characteristic of systematic conservation planning that sets it apart from other 

approaches to conservation planning, is the setting of explicit conservation targets 

(Pressey et al. 2003). Historically, conservation action has tended to focus on the 

creation and expansion of formal protected areas, driven by factors such as the 

availability of cheap land for incorporation into protected areas and scenic quality 

(Pressey et al. 1996). This means that, all over the world, well-conserved habitats 

tend to be those that are not suitable for other land uses, while habitats suitable for, 

for example, agriculture, mining or urban expansion, tend to be poorly conserved 

(Rouget et al. 2003c). Systematic conservation planning counteracts this problem of 

ad hoc conservation efforts by setting conservation targets for all biodiversity 

features, including ecological and evolutionary processes (Margules and Pressey 

2000). 

There is ongoing debate amongst conservation planners about the most effective 

framework or protocol for conservation planning. There is general agreement 

amongst South African conservation planners that an operational framework for 

conservation planning that is geared towards implementation is needed, rather than 

simply a technical framework that guides the technical aspects of conservation 

planning. In SKEP, the broad operational framework was provided by the four 

components of the project introduced in Section 1 (and discussed further in Section 


17). In addition, the SKEP project was guided by the principles of planning for 

implementation and focused stakeholder involvement (see Section 16). 

The work of the Biodiversity Component fitted into this broad operational framework. 

Within this framework, the work was guided by a technical protocol adapted from the 

CAPE project, which undertook a systematic conservation plan for the Cape Floristic 

Region (Cowling et al. 1999b, Cowling et al. 2003a) (Table 1). 

Table 1: Technical steps in the conservation planning process 

Step 

1 

2 

3 

Action Relevant 

Section(s) in 

Compile data on biodiversity pattern (must include a 

continuous data layer e.g. of vegetation types) 

Compile data on ecological and evolutionary processes, 

and represent spatially where possible 

Identify areas where natural habitat has been 

transformed 

4 Identify types, patterns and rates of future land-use 

pressures, and represent spatially where possible 

5 

6 

7 

Identify areas that are already protected 12 

Set targets for the representation of biodiversity pattern 

and ecological processes 

Lay out options for achieving targets and identify 

geographic priorities for conservation action 

Part B 

7, 8, 9 

Note that some conservation plans involve a further eighth step, in which a protected 

area network that achieves the conservation targets is explicitly designed. This step, 

usually called “reserve design”, results in one possible configuration of a protected 

area network – there are almost always many possible configurations of protected 

areas that achieve conservation targets. In the SKEP planning phase, the aim was 

not to design a protected area network for the Succulent Karoo, but simply to identify 

broad-scale priority areas for conservation action. There was thus no reserve design 

step. Reserve design within each of the priority areas would require finer scale 

systematic conservation planning, which could be undertaken in the implementation 

phase of SKEP. 

Also note that when we talk about “conservation action”, we do not mean simply the 

establishment or extension of formal protected areas. Conservation action includes 

activities and projects related to formal protected areas, but should not be limited to 

these. In the case of the Succulent Karoo, conservation action should include 

working with private landowners (such as farming communities and mining 

companies) to encourage conservation-friendly land-management practices, and 

working with land-use decision-making agencies (such as municipalities and 

departments of agriculture) to encourage land-use decisions that protect biodiversity 

in priority areas. A conservation plan needs to recognise competing land uses and 

development needs. Conservation action also includes ensuring that economic 

benefits from the Succulent Karoo’s biodiversity are realised and flow to local 

SKEP Biodiversity Component Technical Report, March 2003 Page 6 

10 

11 

11 

14 

15

communities, and building awareness of the Succulent Karoo’s biodiversity among 

the public, locally, regionally and internationally. 

Each of the steps in Table 1 is outlined briefly in Section 4, and then explained in 

detail in the rest of Part B. 


Part B: Technical Process 

4. Overview of the Technical Steps in the Conservation 

Planning Process 

As explained in Section 3, the Biodiversity Component of SKEP used the systematic 

conservation planning approach to identify broad-scale geographic priorities for 

conservation action in the Succulent Karoo biome. This involved several technical 

steps, shown in Table 1 on page 6, undertaken within the broader operational 

framework provided by the SKEP project as a whole. 

The technical steps listed in Table 1 are described briefly below. 

• In Step 1 data on biodiversity pattern are compiled. This usually involves 

compiling a layer of vegetation types or habitat units. It is important that this 

step results in a continuous data layer – in other words, a layer that covers the 

entire planning domain (the area for which the conservation plan is being done). 

This continuous layer provides the basic set of biodiversity features for which 

conservation targets must be set. In addition to the continuous layer of vegetation 

types or habitat units, further information about biodiversity pattern, such as 

species distribution data, may be collected. 

• In Step 2, ecological and evolutionary processes are identified, and spatial 

components of these processes are mapped where possible. The focus is on 

landscape-scale processes rather than small-scale processes. Small-scale 

processes will be “captured” within each of the vegetation types or habitat units 

identified in Step 1. 

• In Step 3, areas where the natural habitat has been transformed, for example by 

urban development, agriculture or mining, are identified and mapped. 

• In Step 4, likely future land-use pressures are identified, and mapped where 

possible. 

• In Step 5, areas that are already protected are identified and mapped. Protected 

areas are usually divided into different categories depending on the degree of 

protection they confer. 

• In Step 6, conservation targets are set for biodiversity features identified in 

Steps 1 and 2. 

• Step 7 brings all this information together to produce a map of conservation 

options, i.e. options for achieving conservation targets. Conservation planning 

software called C-Plan was used to assist with this step in SKEP. The resulting 

conservation options map, or irreplaceability map (see below), can be interpreted 

together with spatial information on expected land-use pressures, to provide 

direction on geographic priorities for conservation action. 

Because the SKEP conservation plan is for the whole Succulent Karoo biome, an 

area of 116 000 km 2 spanning two countries, the spatial scale of the conservation 

plan was broad. Most spatial data were gathered at 1:250 000 scale, and all spatial 

outputs are at 1:250 000 scale. The outputs are not intended for decision-making 

about individual pieces of land at the local scale (although they provide a useful 

regional context for such local decisions), but rather to indicate broad-scale priority 

areas for conservation action. 


Steps 1 to 5 rely heavily on the use of a Geographic Information System (GIS). We 

used the ESRI suite of GIS products (chiefly ArcView 3.2 and ArcInfo 8.2). Step 7 

was undertaken with the help of GIS-linked conservation planning software C-Plan 

(Ferrier et al. 2000; http://www.ozemail.com.au/~cplan). This conservation planning 

tool was developed by the New South Wales National Parks and Wildlife Service to 

assist conservation planners to identify and evaluate spatial options for the 

development of conservation systems. 

C-Plan prioritises parcels of land (e.g. farms or other planning units) based on a 

computed measure of conservation value, termed irreplaceability (Ferrier et al. 

2000). The irreplaceability index is a measure assigned to a land parcel that reflects 

the importance of that area, in the context of the planning domain, for the 

achievement of the regional conservation targets for selected biological features. 

Features can be vegetation types, habitats, species or spatial surrogates for 

processes. 

Site irreplaceability is a function of how much of each target is achieved by a 

particular land parcel or planning unit. Thus irreplaceability can be viewed in two 

ways: 

• The potential contribution of any site to a conservation goal or the likelihood of 

that site being required to achieve the goal. 

• The extent to which the options for achieving a system of conservation areas that 

is representative (achieves all the targets) are reduced if that site is lost or made 

unavailable. 

Irreplaceability values range from 0 to 1. Sites with a high irreplaceability value are 

essential for achieving conservation targets (i.e. if these sites are not included in the 

protected area system then it is unlikely or impossible that targets will be achieved). 

Low site irreplaceability means that there is flexibility in terms of which sites can be 

chosen to achieve the target. An irreplaceability value of zero indicates that the target 

has already been achieved in the existing protected area network. 

It is important not to confuse C-Plan with the systematic conservation planning 

process. C-Plan is a software tool that can assist in Step 7 of the systematic 

conservation planning process (and in the subsequent reserve design step if it is 

undertaken). Systematic conservation planning does not rely on C-Plan, and, 

depending on the scale of the plan and the nature of the landscape being analysed, 

C-Plan may not be the most helpful tool available. For SKEP it was a highly 

appropriate tool. 

The structure of this part of the report is as follows: 

• Section 5 explains how the planning domain was decided on; 

• Section 6 explains how a digital elevation model was compiled; 

• Section 7 explains how the vegetation map that provided the basic layer of 

biodiversity features was compiled; 

• Section 8 describes how expert knowledge was used to map additional 

biodiversity features; 

• Section 9 explains the collection and role of species distribution data; 

• Section 10 describes how the layer of spatial components of ecological and 

evolutionary processes was developed; 

• Section 11 describes how spatial information on habitat transformation and landuse 

was gathered; 


• Section 12 describes how the protected area layer was compiled; 

• Section 13 explains the role and nature of planning units; 

• Section 14 explains how conservation targets were set for biodiversity features; 

• Section 15 explains how the data layers were analysed to produce an 

irreplaceability map and a framework for action map, and interpreted to identify 

nine broad geographic priority areas for conservation action. 


5. Planning Domain 

Defining the planning domain 

The Succulent Karoo biome, as defined by Low and Rebelo (1996) for South Africa 

and the biome map supplied by the Namibian Atlas Project, provided the starting 

point for defining a planning domain for the SKEP project. 6 

The SKEP planning domain consisted of the Succulent Karoo biome plus adjacent 

habitats. The planning domain extended beyond the Succulent Karoo biome for two 

main reasons: 

• to include ecological gradients and processes; 

• to include outliers of Succulent Karoo vegetation. 

There was some confusion amongst those involved in the various components of 

SKEP about the distinction between the Succulent Karoo biome and the SKEP 

planning domain, so we circulated the short explanation in the box below to clarify. 

Defining a Biologically Meaningful Boundary for the SKEP Project 

The focus of SKEP is the Succulent Karoo biome. When defining a boundary of this study it is important not to 

consider the Succulent Karoo (SK) in isolation, but rather view the SK as part of an environmental continuum. 

In essence, the SK is an ecotone biome. An ecotone is an ecological boundary across which there is a change 

from one state to the next (e.g. vegetation type or climatic zone). The SK occupies the arid interface or ecotone 

between the winter rainfall and the summer rainfall systems of southern Africa. As a result the biodiversity shares 

elements of both systems (Fynbos and Nama Karoo) along with a unique suite of elements restricted to the SK 

that make it such an endemic rich biome. 

With any conservation planning exercise one needs to consider not only species or habitats, but also the 

ecological processes that allow those species and habitat to survive and evolve. In order for biodiversity to persist 

we need to conserve ecological processes as much as we need to conserve ecological patterns. Thus when 

defining the boundaries for SKEP one not only has to include the entire SK, but also significant parts of the 

neighbouring biological systems in order to explicitly consider key processes. One only needs to think of the great 

springbok migrations that impacted so heavily on the SK. This process transcended the boundary of the SK into 

the Nama Karoo. Likewise sister species that lie either side of the summer/winter rainfall divide are evidence of an 

important evolutionary gradient that needs to be considered. 

The proposed boundary for the SKEP study comprises the SK as presently defined in the literature plus a 

significant amount of neighbouring biomes (both Fynbos and Nama Karoo) as we feel that including these areas is 

important for including ecological gradients and processes. The ultimate focus of SKEP will be the core SK 

biome. However, should it be necessary areas from adjoining biomes will be highlighted in order to 

achieve explicit conservation targets for ecological processes. 

SKEP planning domain = Succulent Karoo biome + adjacent habitats 

6 The SKEP project has resulted in a new definition of the Succulent Karoo biome, which differs slightly from this 

starting point. Figure 1 shows the new SKEP definition of the Succulent Karoo biome. The Low and Rebelo (1996) 

definition of the Succulent Karoo is shown in Appendix 1 in Part E. 


Low and Rebelo (1996) identify four sub-types of Succulent Karoo vegetation, all of 

which were included in the planning domain: 

• Strandveld Succulent Karoo; 

• Upland Succulent Karoo; 

• Lowland Succulent Karoo; 

• Little Succulent Karoo. 

Two non-Succulent Karoo vegetation types identified by Low and Rebelo (1996) 

were also included in the planning domain: 

• Great Nama Karoo; 

• Central Lower Nama Karoo. 

At the initial stakeholder discussion meeting about SKEP in September 2001, some 

stakeholders motivated strongly that there are significant patches of Succulent Karoo 

vegetation within these predominantly Nama Karoo habitats, and that they should be 

included in the planning domain. However, these patches or outliers of Succulent 

Karoo vegetation have not been mapped. 

The consequences of including these large areas of Nama Karoo vegetation in the 

planning domain were significant. On the one hand, it was important to be inclusive in 

the definition of the planning domain, and not to leave out significant outliers of 

Succulent Karoo vegetation. On the other hand, because these particular outliers 

have never been mapped, and because time and budget constraints did not allow for 

new vegetation mapping as part of the SKEP project, they could not be included in 

the analysis. 

At 257 000km 2 , the SKEP planning domain was more than twice the size of the 

116 000km 2 Succulent Karoo biome. 

Finalising the sub-regional divisions 

As explained in Section 1, four sub-regions were identified at the start of the SKEP 

project, and champions were appointed for each sub-region as part of the work of the 

Socio-Political Component of SKEP. The Biodiversity Team had the task of finalising 

the boundaries of the four sub-regions within the SKEP planning domain. This was 

done in consultation with the sub-regional champion teams. The sub-regional 

boundaries were, where possible, aligned with local or district municipal boundaries. 

Alignment with administrative boundaries streamlined the work of the champion 

teams, for example in information gathering. 

Appendix 2 in Part E (The SKEP Planning Domain: Documentation of the Decision 

Process, March 2002), explains the four stages of finalising the SKEP planning 

domain in detail. Figure 2 shows the final SKEP planning domain and the SKEP subregions. 


Figure 2: The SKEP planning domain showing sub-regions 

Overlapping planning domains between SKEP and other projects 

The SKEP planning domain overlaps substantially with the planning domains of two 

other biome-wide conservation planning projects: CAPE (Cape Action for People and 

the Environment) in the Cape Floristic Region, and STEP (Subtropical Thicket 

Ecosystem Plan) in the Thicket biome. The domains of all three projects are shown in 

Figure 3. The overlaps reflect the reality that the boundaries between the vegetation 

types involved are not neat. For example, the Little Karoo area is characterised by a 

mixture of fynbos, thicket and succulent karoo vegetation. 

The need to co-ordinate outputs from CAPE, STEP and SKEP resulted in a separate 

project in the last quarter of 2002, led by the Botanical Society in partnership with the 

Conservation Planning Unit at Western Cape Nature Conservation Board. The 

project examined, among other issues, how to produce a single integrated 

conservation planning product for municipalities in which two or more of the CAPE, 

STEP and SKEP plans apply. 


Figure 3: Overlapping planning domains of the CAPE, STEP and SKEP projects 


6. Digital Elevation Model 

Why a DEM is important 

The digital elevation model (DEM) forms an integral part of modern GIS-assisted 

landscape ecological analyses. Many topographic and hydrological variables can 

only be calculated from a DEM. In addition, abiotic environmental factors, such as 

climatic and soil variables, can also be modeled and made spatially explicit with the 

aid of a DEM. Although not used directly in C-Plan analysis, the DEM is an essential 

piece of basic spatial information that is used in many stages of the project from 

initial ecological analyses/modelling through to presentation of results. This section 

describes the development of a 100m DEM for SKEP. 

Knowledge of a DEM’s accuracy is a necessary prerequisite for any GIS modeling or 

analyses. DEM error places minimum bounds on the spatial resolution of any model 

outputs. The DEM developed for the SKEP project is a mosaic of four different DEMs 

(see Table 2). Each DEM was developed from different source data using different 

techniques with varying degrees of pre- and post-interpolation data correction. Figure 

4 illustrates the geographic coverage of each of the four DEMs. 

Table 2: Summary of the four DEMs used to compile the SKEP DEM 

Name of DEM 

Original 

Grid 

resolution 

Source 

Original 

contour 

data scale 

Maximum 

vertical 

error 

Maximum 

horizontal 

error 

Namaqualand DEM 100m Computamaps 1:50 000 25m 39m 

ARC DEM 100m unknown 1:50 000 35m >39m 

Namibia DEM 100 100m Computamaps 1:250 000 40m 195m 

Namibia DEM 500 500m Computamaps unknown unknown unknown 

SKEP -DEM 100m

difference between the observed and spot height altitude values (Table 3), this 

error is assumed to be approximately 10m. 

Figure 4: Geographic extent of the four DEMs used to compile the SKEP DEM 

Horizontal error 

Horizontal or planimetric error is a result of deviation in the raw contour data from its 

true geographic position. This value is supplied by the Surveyor General and is 39m 

of the 1:50 000 maps and 195m for the 1: 250 000 maps. There is additional error 

due to inaccurate projection. This error is variable across the landscape and can be 

as great as 50m; however, this is not factored in here. 

Additional error 

There are additional errors or “defects” in the DEM relating to the vagaries of the 

interpolation process. These are only found on the ARC DEM, which appears not to 

have undergone any post-interpolation data correction. These errors are noticeable 

as the following defects in the DEM: 

• Banding can be observed in very flat areas; 

• The coastline is more convoluted than in reality; 


• Unexplained straight “lines” with data values unexpectedly different to 

neighboring cells. Two lines can be detected in the SKEP DEM in the 

Riviersonderend Mountains and in the Noorsveld. 

Comparison of the DEMs available for the South African part of the 

planning domain 

As noted in Table 2, the SKEP project had available to it two 100m grid resolution 

DEMs with which to perform analyses for the South African part of the planning 

domain. These two DEMs were acquired from different sources. One was sourced 

from a Cape Town-based GIS consulting firm, Computamaps (CM), and the other 

from the Agricultural Research Council (ARC). Although they were developed from 

the same original source data (the 1:50 000 map contour lines supplied by the 

Surveyor General), different interpolation methods were used to interpolate the two 

grids. This section compares the two DEMs to one another and to control spot height 

points from the 1:50 000 maps to determine confidence levels for the respective 

grids. 

The CM DEM was developed from the 1:50 000 map sheets contour lines supplied 

by the Surveyor General in Mowbray. There are two sources of error in this raw data. 

The first relates to error due to incorrect projection from the Clarke 1880 to WGS84 

datum. The second relates to error as a result of the original trigonometric 

triangulation of the country whereby triangulation errors were pushed to the least 

populated part of the country, the north-western Cape. The CM DEM addressed the 

first error in the raw data by reprojecting the contour lines to WGS84 map datum. The 

contours and drainage lines from these corrected maps were used as input into the 

interpolation algorithm. The interpolation algorithm used was a modification of the 

ArcInfo Topogrid command. The modifications were made by Mike Hutchins who 

originally developed Topogrid for ESRI. The interpolation method is a form of 

minimum curvature spline with drainage enforcement. Grids interpolated at the 20m 

resolution have a vertical RMS error between 2-7m. Grids interpolated at the 100m 

resolution have a vertical RMS error between 7-15m. Added to this error is the 

vertical error on the original contour maps of one-half a contour interval or 10m. 

Thus, the CM 100m DEM has a maximum vertical error of approximately 25m (J. 

Hyland pers. comm.). 

The ARC DEM was developed from the Surveyor General supplied 1:50 000 contour 

data using the ArcInfo version of Topogrid (D. Fairbanks pers. comm.). Little other 

information is known about this DEM. Error present in the supplied contour data due 

to inaccurate WGS84 transformation of the spatial data, as much as 50m 

horizontally, was not to our knowledge addressed in this dataset. 

The CM and ARC DEMs were compared to spot height information obtained from the 

Surveyor General for three areas in Namaqualand where the DEMs overlap. In 

additional to these two DEMs, the ARC DEM was shifted by 100m west and south in 

an effort to improve the overlap with the underlying spot heights. The results of these 

comparisons are presented in Table 3. 

Difference between the two compared DEMs shows an interesting pattern that is 

most likely related to the interpolation method used. On steep convex slopes the 

difference (i.e. Computamaps – ARC) is generally >20m. Conversely, on steep 

concave slopes this difference is generally

gradients (i.e. level or gently undulating ground) and on even slopes the difference 

between the between two DEMs is generally less than 20m positive or negative. 

Table 3: Summary statistics comparing the CM, ARC and a XY shifted ARC 

DEMs to the spot height information for three regions in Namaqualand 

Kamiesberg 

CM ARC XY 

Mean 3.714844 19.957031 13.710938 

Total N 256 256 256 

Std Dev. 65.516296 75.215573 70.218220 

LCL Mean -6.912090 7.756847 2.321338 

UCL Mean 14.341777 32.157216 25.100537 

Skewness -13.192518 -8.239083 -9.961208 

Kurtosis 193.731564 105.254203 134.393807 

Coast 

CM ARC XY 

Mean 1.3888889 10.4259259 9.3827160 

Total N 162 162 162 

Std Dev. 5.4101928 10.2009655 9.3091392 

LCL Mean 0.2808677 8.3367424 7.4761808 

UCL Mean 2.4969101 12.5151095 11.2892513 

Skewness -6.2927551 -0.3571527 -0.3662793 

Kurtosis 64.0537359 2.8758994 3.0296505 

Plains 

CM ARC XY 

Mean 0.47887324 -11.07042254 -11.33802817 

Total N 71 71 71 

Std Dev. 2.06230907 7.01493090 6.78431734 

LCL Mean -0.16920422 -13.27485380 -13.46998947 

UCL Mean 1.12695070 -8.86599127 -9.20606687 

Skewness 0.08127335 0.01391489 -0.03361135 

Kurtosis 7.92513707 -0.74997227 -0.72729851 

Overall, the CM DEM appears to be a better reflection of the observed data than the 

ARC DEM with a mean difference between DEMs close to zero in all three test 

areas. Error across the ARC DEM is not equal and deviates significantly from zero. 

This deviation is probably the result of both triangulation and projection error. 

Although the XY shifted ARC DEM improved the overlap of the DEM and the spot 

heights, without control points from the southern and eastern parts of the DEM it is 

difficult to determine if this shift improves or worsens the overlap in these areas. 

Considering that the north-west of South Africa was a triangulation error repository, 

this error is probably not equal across the ARC DEM. 

Creating the SKEP DEM 

For the purposes of the SKEP DEM, the original ARC DEM was used with the 

Namaqualand portion of the study area being replaced with the CM DEM for this 

area. 

The Namibian 100 DEM comprising the merged 100m and 500m (interpolated to 

100m) DEMs was supplied by Computamaps. This DEM was clipped along the 

Orange River. The Namaqualand grid was kept as is and the ARC DEM was clipped 


along the boundary of the Namaqualand DEM (approximately 20E and 32S) allowing 

a 1km overlap area. The three DEMs were merged using the merge command in 

ArcView. The merge command smoothes the overlap zone between grids using a 

weighted averages smoothing algorithm creating a seamless join. For all DEMs, 

values less than zero were converted to NO DATA values in the resultant grid. 

Limitations of the SKEP DEM 

The SKEP DEM comprises a mosaic of four different DEMs of differing spatial 

extents, resolution and accuracy. Over the majority of this DEM vertical error is less 

than 40m and horizontal less than 50m. Variability in these error estimates depends 

on the region and the underlying DEM used. Users of the SKEP DEM need to be 

aware of the variable accuracy of the DEM as well as the interpolation “glitches” 

present in the southern and eastern parts of the DEM, and the limits these impose on 

analyses and model predictions made using this DEM. 


7. Vegetation Map 

Why the vegetation map is important 

Systematic conservation planning aims to develop plans of action or frameworks that 

most effectively conserve a region’s biodiversity in the context of on-going human 

use and transformation of that region (Pressey and Cowling 2001). This requires that 

there is some form of biodiversity information about every part of the landscape. The 

manner in which biodiversity can be represented will vary depending on the nature of 

the data source (e.g. vegetation unit, species home range, point locality species 

records, quarter degree grid museum record, etc.). However, all biodiversity data 

layers that are eventually used in such planning exercises need to have one 

characteristic in common – they need to be spatially explicit. In other words this 

biodiversity information must be attached to some point or area in geographic space. 

With conservation and land-use plans decisions are made about units of land based 

on the biological and other attributes of that land and its neighbors. Hence the 

importance of spatially explicit information. 

As decisions are made about all areas of land, at least some of the biodiversity 

information used in the conservation plan needs to comprise continuous information 

surfaces across the entire landscape. Continuous information layers are not a 

prerequisite for conservation or land-use planning; however, in the systematic 

planning approach decisions cannot be made about the value of areas for which 

there is no biodiversity data, albeit rudimentary data. Implicit in the development of 

such biodiversity information surfaces is that these surfaces act as surrogates for 

biodiversity. This is because biologists have not sampled, and are never likely to 

sample, every inch of a landscape. When mapping biodiversity, understanding of the 

distribution of the biodiversity feature being mapped is extrapolated to areas in 

geographic space that have never been surveyed. 

Traditionally, vegetation maps are seen as reasonable surrogates for biodiversity at a 

range of taxonomic and ecological spatial and hierarchical scales. This “coarse-filter” 

approach assumes that by protecting a portion of each vegetation type, all or most of 

the biodiversity in these habitats is preserved (Noss et al. 1997). Thus, the 

development of a vegetation map for SKEP was essentially the primary biodiversity 

layer, continuous across the entire planning domain. The vegetation map ensured 

that there was at least some biodiversity information for every part of the SKEP 

planning domain. Another attribute of this continuous information surface is that the 

mapped features, i.e. vegetation units, are mutually exclusive – they do not overlap 

one another. Thus, at any point in space there is only one vegetation unit 

represented. This also means that if the area of a planning unit (see Section 13) is x, 

then the sum of areas of the vegetation units that occur in this planning unit is also x. 

The SKEP vegetation map provided the primary layer of biodiversity features for the 

systematic conservation planning exercise. To summarise, a vegetation map is 

appropriate for this task for two main reasons: 

• Vegetation types are good surrogates for species localities at a wide range of 

spatial scales. Using vegetation types or land classes as surrogates for 

biodiversity is thus a widespread practice in conservation planning. 


• A vegetation map is continuous across the entire planning domain. In the 

systematic conservation planning approach, decisions cannot be made about the 

conservation value of areas for which there are no biodiversity data. The 

vegetation map ensured that for every part of the SKEP planning domain there 

was at least some biodiversity information. 

The vegetation map provided a better primary biodiversity feature layer than species 

distribution data, for at least two reasons. 

• Most of the available species distribution data were stored at a scale too crude 

for the SKEP assessment. These data were provided at the quarter degree scale 

(QDS), which is too crude for planning and implementation at the 1:250 000 

scale. A quarter degree square measures approximately 24 by 27km. (Even if 

species distribution data are stored with point localities, they are not always 

publicly available in this form, often for good reason – there is concern about, for 

example, locality data falling into the hands of illegal collectors.) 

• The available species distribution data did not comprise presence-absence sets 

(and almost never does, even for exceptionally well-collected taxa). In other 

words, sampling across all QDS was not comprehensive, resulting in many false 

absences for species records. This will inevitably bias the selection of priority 

sites in favour of those with records, and consequently may miss sites with 

unique or rich species complements. 

A lesson from CAPE on using species distribution data versus vegetation types 

in conservation planning 

The CAPE project provided an important lesson for SKEP regarding the use of species localities versus 

vegetation types in conservation planning. The CAPE conservation plan used a combination of land classes 

and species distribution data. Lombard et al. (2003) showed that when targets were set for each of 364 

species of Proteaceae, comprising a massive 183 181 point locality records, this taxon was not very 

effective in achieving targets for vegetation types – it was a poor surrogate. The reason for this was that 

Proteaceae do not grow in all of the vegetation types found in the Cape Floristic Region. However, 

achieving targets for vegetation types also achieved targets for all but a small subset of extremely rare 

Proteaceae. Vegetation types or land classes were thus a good surrogate for Proteaceae, but the reverse 

was not true – Proteaceae were not a good surrogate for land classes. 

Note that the Proteaceae data set was compiled over ten years at a cost of approximately R2.5 million (in 

1991-2001 Rands), not including the in-kind contributions of hundreds of volunteers (Rebelo 2002). Given 

the urgency of identifying conservation priorities, and the scarce resources available for conservation 

assessments, the simultaneous collection of presence-absence data sets for an effective array of indicator 

taxa (i.e. those taxa associated with the full array of environments in a planning domain) is unrealistic. The 

time and cost involved made this an impossible task for all three bioregional conservation plans in southern 

Africa (CAPE, SKEP and STEP), and would also make it impossible in most other biologically rich 

bioregions in the developing world. 

Constraints on the development of a SKEP vegetation map 

There were several constraints on the development of a vegetation map for the 

SKEP planning domain: 

• The short time framework dictated the use of existing mapping with minor 

additions or amendments based on expert knowledge. 


• It was important not to impinge negatively upon other mapping initiatives already 

underway, and to work together with existing initiatives where possible. 

• Dealing with two countries increased the effort required to obtain exisitng 

mapping. 

• There is tradeoff between data accuracy and spatial resolution. Given the coarse 

spatial scale of the SKEP project (1:250 000), improving the spatial accuracy of 

the vegetation map to a finer scale would not lead to a significant improvement in 

the accuracy of the project outputs. 

Methods 

The SKEP vegetation map is comprised of two principal sources. For the South 

African part of the planning domain, the new South African Vegetation Map (SA Veg 

Map) was used. For the Namibian part of the planning domain, a new vegetation map 

was developed from a combination of satellite image classification, grad-sect 

environmental modelling and existing very broad-scale vegetation maps for the 

region. 

South African part of the vegetation map 

The National Botanical Institute (NBI) has been tasked by the national Department of 

Environmental Affairs and Tourism with the development of a new vegetation map for 

South Africa. The vegetation map currently in use (Low and Rebelo 1996) identifies 

68 vegetation types across the country at 1:1 000 000 scale. It does not provide 

sufficient detail for biome-level a conservation planning project such as SKEP (only 

four types of Succulent Karoo vegetation are identified). 

The new SA Veg Map, which will be published during 2003, identifies approximately 

380 vegetation types across the country, including approximately 170 in the South 

African part of the SKEP planning domain. At a scale of 1:250 000, it gives much 

more detail and matches the scale of the SKEP project. Permission was granted to 

use a pre-peer review copy of the new SA Veg Map, clipped to the SKEP planning 

domain. 7 

This SKEP portion of the draft SA Veg Map was modified in four ways: 

• Where the SA Veg Map overlapped with the STEP vegetation map in the south 

east of the planning domain, 8 polygons that had “no data” in the SA Veg Map 

were classified either by merging with neighbouring SA Veg Map polygons or by 

labelling using STEP vegetation names (see Table 25 in Section 27 (Part D)). 

• Some new SA Veg Map units were subdivided to reflect the location of: 

regions of extensive quartz patches; 

regions of quartzite mountains outside of the Cape Fold Belt geological 

province. 

Regions with quartz patches or quartzite mountians are known to harbour 

significant numbers of endemic species within the Succulent Karoo. Whilst the 

matrix vegetation is generally similar to neighbouring areas that do not have 

these two broad habitat types, their association with high numbers of endemic 

7 Thanks to Mike Rutherford of the NBI (and member of the SKEP Biodiversity Advisory Group) for agreeing to this. 

8 The Sub-tropical Thicket Ecosystem Planing (STEP) project, which commenced in 2001, mapped all thicket 

vegetation. The STEP planning domain overlaps substantially with the SKEP planning domain, as shown in Figure 3 

in Section 5. 


species warrants these regions being mapped as distinct biodiversity features. 

This is a key element of selecting biodiversity features for systematic planning. 

The features used must represent the basic patterns of biodiversity within a 

region. 

The resultant breakdown of 175 SA Veg Map vegetation units into 200 SKEP 

vegetation units is summarised in Table 25 in Section 27 (Part D). This was the 

most extensive modification of the SA Veg Map. 

• In addition to this subdivision, the SKEP vegetation units were classified to reflect 

the location of sand movement corridors. The names of these corridors and their 

component vegetation units are summarised in Table 26 in Section 27 (Part D). 

These corridors are not explicitly reflected in SKEP vegetation unit names. They 

were used in the development of the data layer showing spatial components of 

ecological processes (see Section 8). 

• The new SA Veg Map coverage was cleaned to remove sliver polygons and 

gaps, and the topology was checked. 

Namibian part of the vegetation map 

The object of the Namibian vegetation mapping exercise was to develop a vegetation 

map that was of comparable spatial resolution to that developed for the South African 

part of the planning domain, as explained above. There was no equivalent map to 

use as a starting point for the Namibian part of the planning domain. The scale of the 

existing Namibian vegetation map was approximately 1:1 000 000. 

The basic approach consisted of delimiting units using a basic GIS-based grad-sect 

technique of remotely derived environmental variables (Austin and Heyligers 1989; 

Wessels et al. 1998) and then classifying units based on the existing Namibian 

vegetation map whilst integrating available vegetation descriptions of the region. The 

resultant mapped units can best be described as “broad habitat units” rather than 

true vegetation types, i.e. they are based on habitat classes that were predicted 

rather than on observed vegetation discontinuities. The grad-sect approach was 

chosen over other more accurate modelling techniques primarily because of lack of 

point biodiversity-community data. A second constraint was the time available for 

performing these more involved mapping approaches. 

The basic philosophy of the modelling approach is that at the landscape level, 

vegetation patterns are determined primarily by: 

• broad substrate type (rock, dune or sandy plain); 

• rainfall seasonality; 

• altitude influence on climate amelioration. 

Thus for the grad-sect process these three basic environmental covers were 

required. 

Broad substrate type (Landform) 

The spatial accuracy of available landscape-type and geological maps for Namibia 

was not compatible with the resolution required for this mapping exercise. Thus, a 

broad substrate type map was developed from an available satellite image mosaic for 

the SKEP planning domain. 


The satellite image used was a LANDSAT 5 mosaic created by EARTHSAT for 

NASA (TM bands 742 [RGB] Orthorectified mosaic; ca. 1990 [range from 1987 to 

1993]; UTM projection, WGS84 datum; 28.5 metre pixel size [spatial resolution]) 

obtained for this project from Western Cape Nature Conservation Board. The false 

colour processing of this image performed by the developer was optimised for 

geological features (Justin Hyland, Computamaps, pers. comm.). In an arid 

landscape where vegetation cover is low and which is sensitive to broad geological 

classes makes this image ideally suited to develop a regional-scale vegetation map. 

eCognition image analysis software was used to produce "object primitives". This 

software was provided free of charge on a trial basis for this project by the South 

African distributor MSS (Pty) Ltd in Johannesburg. The object primitives are areas of 

uniform colour and texture on the satellite image and the assumption was made that 

these represent uniform geological features on the ground. Thus, this image analysis 

process reduced the satellite image from several million pixels to around 100 000 

image objects. These image objects were then manually classified into rock, sandy 

plains or dunes. The advantage of this technique is that it removes the requirement 

to digitise these features manually and the spatial accuracy of resultant boundaries is 

high. These three basic substrate classes were then classified into 12 regional 

classes (see 

Table 4). 

Rainfall seasonality layer (Winter) 

A rainfall seasonality layer (percentage winter rainfall) was developed using Centre 

for Computational Water Research climate data for the region, a DEM and a 

stepwise regression model. Three variables were used in the model: altitude, latitude 

and distance from the coast. The following equation was developed using the 

regression analysis: 

% winter rainfall = -81.8973 – 9.6022(latitude) + 0.0103(altitude) – 51.6745(Log10(distance to 

coast)) 

r 2 = 0.8831, p

Table 4: Classes generated for each environmental layer in the development of 

the Namibian broad habitat map 

Landform 

Winter 

(% winter rainfall) 

Altitude 

(m a.m.s.l.) 

1 Luderitz 0 0 

2 Bushmanland dunes 10 300 

3 Coastal hummock dunes 30 600 

4 Coastal sandy plains 40 900 

5 Red dunes 50 1300 

6 Red sand 1700 

7 Rock 2000 

8 Sandy flats 

9 White sand 

10 Namib sand erg 

11 Namib coastal mega-linear dunes 

12 Namib inland mega-linear dunes 

Limitations of and omissions from the Namibian broad habitat map 

The grad-sect stratification technique did not take explicit cognisance of the 

occurrence of fog in the southern Namib. This is recognised as an important biotic 

determinant in the region (Desmet and Cowling, 1998). Quartz and lichen fields are 

not captured in the resultant map. These are key habitats for unique biotic diversity in 

the Succulent Karoo and are captured to a degree in the South African vegetation 

map. Most importantly, the grad-sect intervals are based on the author’s 

understanding of vegetation patterns in the Southern African arid zone. The 

delimitation of these classes is not scaled based on objective biological data, an 

important shortcoming of this technique. As a result of the type satellite image 

analysis used, the boundaries between dunes, sand and rock are generally quite 

accurate (

is conducted with finer spatial resolution, the boundaries and units in this map will 

change to reflect this increase in knowledge. 

The SKEP vegetation map has not been ground-truthed beyond informal expert 

comment on the spatial accuracy of boundaries. For boundaries where the 

discontinuity between vegetation units is discrete, i.e. related to a change in 

underlying substrate (such as between sandveld and hardeveld), the boundaries can 

be assumed to have an error of less than 1km. In most cases the boundary error is 

less than this. Where boundaries between vegetation units are “fuzzy” or not 

discrete, i.e. biogeographic boundaries relating to change in rainfall (such as 

Bushmanland plains); or, where the mapped feature is patchy thus a general area is 

mapped rather than the physical boundary (such as with regions containing quartz 

patches), the error around the mapped boundary can range from 1 km to several 

kilometres. These errors need to be borne in mind when applying this map to finerscale 

planning studies. 


8. Expert Mapping 

Why expert mapping? 

Systematic conservation planning and expert-driven conservation planning are often 

seen as opposing or contradictory approaches. However, it is possible and usually 

necessary to incorporate expert knowledge into systematic conservation planning. 

Although systematic conservation planning is data-driven and target-driven, rather 

than expert-driven, it can draw substantially on expert knowledge. (See Cowling et al. 

(2003b) for suggestions on incorporating expert knowledge into systematic 

conservation planning.) 

In the case of SKEP, expert knowledge was important in formulating the vegetation 

map (see Section 6), the layer of spatial components of processes (see Section 8) 

and the land-use and habitat transformation layers (see Section 11). 

Further, to supplement the data on biodiversity features provided by the SKEP 

vegetation map and the spatial components of processes, experts in different 

taxonomic groups were asked to map centres of endemism and species richness, 

unique habitats, and key areas for maintenance of biological processes. 

The Succulent Karoo is a relatively small hotspot, in terms of its geographic area, 

and has been well surveyed by experts in the field (with the exception of parts of the 

Sperrgebiet). There was thus confidence that an expert mapping exercise could 

result, in this hotspot, in a reasonably comprehensive spatial picture of the area. 

Because of tight time and budget constraints, the exercise was conducted on a 

limited scale, with only 20 experts involved. 

The initial aim was to compare the results of the expert mapping exercise with the 

results of the systematic approach, and to explore whether expert mapping added 

value and how one might use such data. As explained in Section 14 and 15, the 

decision was subsequently made to incorporate the expert mapping layer directly in 

the analysis of conservation options and priorities, rather than to use it simply as a 

context layer. 

A formal comparison of the results of the expert mapping exercise with the results of 

the systematic approach was not part of the terms of reference of the Biodiversity 

Component, and there was not time to undertake such a comparison. However, this 

could be undertaken as a separate project, for example for postgraduate research. 

This section explains how the expert mapping exercise was conducted, and 

assesses its strengths as well as problems associated with it. 

Expert mapping methodology 

The expert mapping methodology was based strongly on the methodology developed 

earlier in the SKEP project for land-use mapping by stakeholders (explained in 

Section 12). It involved several steps: 

• deciding on taxonomic groups; 

• identifying experts in each group, and invite them to participate; 


• preparing base maps and overlays for mapping; 

• developing a data form; 

• conducting mapping in small groups; 

• digitising mapped polygons on overlays; 

• capturing data forms; 

• cleaning and linking the data. 

The following taxonomic groups were used for expert mapping: 

• amphibians; 

• birds; 

• fish; 

• invertebrates; 

• plants; 

• reptiles; 

• small mammals. 

These groups cover all the larger life forms except for large mammals, which are not 

a feature of the Succulent Karoo. 

Experts were identified based on the following criteria: 

• widely recognised expertise within their field; 

• knowledge of their taxonomic group within all or a significant part of the Succulent 

Karoo biome; 

• proximity to Cape Town (we were able to fund a limited number of people to 

travel to Cape Town for this exercise, but for the most part had to rely on experts 

who were Cape Town-based, bearing in mind the need to cover the Namibian 

part of the planning domain as well as the South African part); 

• availability within the project schedule. 

The aim was to use at least two experts for each taxonomic group (this was possible 

in six of the seven taxa). For plants there were eight expert mappers, since plant 

species richness and endemism is the outstanding feature of the Succulent Karoo 

and most well known. In cases where it was not clear who the best person or people 

were for a particular taxonomic group, advice was asked from people in that field of 

expertise with whom the Biodiversity Team were in contact. The extensive network 

and knowledge of biological specialists that existed among certain members of the 

Biodiversity Team and the Biodiversity Advisory Group, made the task of identifying 

expert mappers relatively straightforward. 

Some of the experts identified had had previous contact with the SKEP project (for 

example, at the first Biodiversity Component Workshop held in January 2002 – see 

Section 20). Others had no previous contact with SKEP. 

Appendix 3 in Part E includes a list of the expert mappers involved, and a copy of the 

standard invitation sent to them. 

The mapping methodology involved drawing polygons on tracing paper overlaid on a 

base map, and filling in a data form for each polygon drawn. Topographic maps at 

1:250 000 scale, from the Surveyor-General, were used as the base maps. Twentytwo 

of these cover the entire SKEP planning domain (17 for the South African part 

and five for the Namibian part). The tracing paper overlays were printed on inkjet 

tracing paper, showing just the outline of the 1:250 000 map and the map number, so 


that the right overlay could be matched up with the right base map and accurately 

aligned with it. 

Experts were given an overview map showing the SKEP planning domain and the 22 

map sheets. This was useful for keeping track of which overlays had been completed 

and which not. With 22 large sheets spread out in a room and different people 

working on different ones, it is easy to loose track. If an expert drew no polygons on a 

particular map sheet, the person was asked to indicate on the overview map whether 

this was because of lack of knowledge of the area, or because there was nothing that 

required mapping in that area. A copy of the overview sheet is included in Appendix 3 

in Part E. 

The data form is a critical part of the expert mapping exercise. It needs to be filled in 

for each and every polygon drawn, and correctly matched with the relevant map 

sheet and polygon using a clear labelling system. An example of the data form 

developed for the SKEP expert mapping exercise is included in Appendix 3 in Part E. 

It included the following questions. 

• attributes of the area: 

centres of endemism, 

local centres of biotic diversity, 

unique habitats / biotic community types, 

key areas for maintenance of biological processes, 

areas threatened with transformation; 

• important or focal taxa; 

• number of endemic or rare and endangered taxa; 

• land-use pressures facing the area. 

The actual mapping exercise was conducted in small groups. The original intention 

was to get all expert mappers to attend a singe one-day mapping session. However, 

because of constraints on people’s availability, several mapping sessions were run 

over a period of two weeks. If we were to do the exercise again, we would stick to 

this arrangement. Small groups of expert mappers worked well, especially where 

experts from the same field of expertise worked together and could confer. 

Some initial explanation and guidance by a member of the Biodiversity Team was 

required. However, because the people involved were scientists and generally 

understood the nature of GIS and the need for clear data, ongoing supervision 

throughout the mapping exercise was not required. (This was not the case for 

stakeholder mapping of land use and habitat transformation, as will be discussed in 

Section 11). 

Polygons for all taxonomic groups were drawn on a single set of overlays. The 

overlay sheets were secured with cellotape to laminated base maps, and not 

removed in between mapping sessions. Fine felt tip pens worked well for drawing on 

the tracing paper overlays. Different experts used different colours to help distinguish 

their polygons (in addition to individualised labels). 

One of the Namibian-based experts conducted the mapping exercise remotely. He 

was able to digitise the required areas on-screen. The Namibian Atlas Project also 

also provided data on important plant areas. However, these data were not included 

as they were spatially too coarse and did not add to the information already mapped 

by other plant experts. 


Figure 5 shows the final expert map. The left-hand map shows the polygons for 

different taxonomic groups in different colours. The right-hand map shows the 

number of polygon overlaps in different shades. 

The expert who mapped areas for fish, Dean Impson, also provided a detailed report 

on freshwater fishes of the Succulent Karoo, co-authored with two colleagues. See 

Appendix 4 for a copy of the report. 

Sections 14 and 15 deals with how the expert map was incorporated into the analysis 

of conservation priorities in the Succulent Karoo. 

Assessment of the expert mapping exercise 

Strengths of expert mapping include the following: 

• The scope of the exercise is flexible: the number of experts involved can be 

tailored to the project timeframe and budget. 

• Results are quick, visual and easy to relate to, even for a layperson. 

• It provides an opportunity for active involvement in the conservation planning 

process by a range of scientists in different fields. This can generate support for 

and greater understanding of the conservation planning process. 

• If experts map in groups, with people from the same taxonomic field mapping 

together, it gives them a chance to share knowledge. Most of the expert mappers 

seemed to have gained something from the exercise and were pleased to have 

participated. 

Potential problems with expert mapping include the following: 

• In the case of SKEP, some experts were able to map areas of significance for 

biodiversity with a high degree of precision, while others mapped much less 

precisely. This was the result of two factors: 

For some taxonomic groups the degree of precision was related to mobility of 

the organisms concerned. For example, it is easier to pinpoint a precise 

centre of endemism for plants or for amphibians than it is for mammals or for 

birds. 

For all taxonomic groups the degree of precision was related to the underlying 

knowledge base. For example, research on invertebrates in the Succulent 

Karoo is much is more limited than research on reptiles. As a general rule, 

better-known groups were better mapped, e.g. plants vs insects. 

The result is a set of polygons that vary in size from less than 20 ha to in excess 

of 1 000 000 ha, and cannot all be viewed or interpreted in the same way. 

(Section 15 explains how this was dealt with in the analysis.) 

• The expert mapping exercise as conducted for SKEP results in a clear spatial 

product. However, it does not capture the “decision rules” used by the experts in 

deciding where to indicate areas of significance for biodiversity. The expert 

mapping process would need to be managed differently if the aim was to record 

these decision rules in addition to the mapped areas. 

• The expert mapping process needs to be closely managed to ensure uniformity 

of the mapping process between different experts. 

• Because the expert map is in some ways “easier to relate to” than the 

irreplaceability map or the framework for action map (see Section 15), there is a 

risk that it could be relied on more heavily by potential users of SKEP outputs for 

guidance on spatial conservation priorities in the Succulent Karoo. It needs to be 


made clear that the expert map is not a map of conservation priorities in the 

Succulent Karoo. It is simply one input into the analysis of these priorities. 

• In any expert mapping exercise, there are biases associated with incomplete 

knowledge, and a possibility that charismatic species receive disproportionate 

attention. Some features are likely to be left out. 

Figure 5: SKEP expert map 


9. Species Distribution Data 

How species distribution data were used 

Species distribution data comprises species occurrence records from museum and 

herbarium specimens or atlas projects. For southern Africa, these data have typically 

been collected at the quarter degree scale (QDS) (a quarter degree square 

measures approximately 24 by 27km). Although some of these data have been used 

in a previous region-wide priority setting study (Lombard et al. 1999), they were too 

coarse to use as biodiversity features in the SKEP conservation planning process. 

Species distibution data were nonetheless important for developing an overview of 

broader patterns of taxonomic diversity within the Succulent Karoo. For most 

taxonomic groups this was the only spatial biodiversity data available for the region. 

The aims of collating species distribution data for SKEP were: 

• to assess the number and availability of biological inventory data for the 

Succulent Karoo; 

• to develop a set of baseline biodiversity statistics for the Succulent Karoo to 

assist in determining research priorities for the region. 

The baseline biodiversity statistics included global speices lists with endemicity 

rankings. The SKEP global plant list includes 6 356 species in 1 002 genera and 168 

families. Approximately 29% of the flora are succulent plants and 18% geophytes. 

Twenty-six percent (1630) are strict endemics and 14% (905) are near-endemics (i.e. 

their centre of distribution is in the Succulent Karoo). Eighty genera are endemic, 

mostly succulent and bulb genera. Seventeen percent (936) of Succulent Karoo plant 

species are Red Data Listed. Global lists were also compiled for amphibians (17 

species including 5 (29%) strict endemics), bees and termites (177 including 68 

(38%) strict endemics), scorpions (70 including 18 (26%) strict endemics), mammals 

(68 including 6 (9%) strict endemics), reptiles (121 including 24 (20%) strict 

endemics) and birds (431 including 1 (

The QDS databases obtained for these analyses are listed in Table 5. 

Table 5: QDS species distribution datasets used in SKEP 

Taxonomic 

Group 

Contact Person Organisation 

Frogs James Harrison Avian Demography Unit, UCT 

Mike Griffith National Museum of Namibia 

Insects Mervin Mansell 

(Termites) 

Plant Protection Research Institute 

Connal Eardley 

(Bees) 

Plant Protection Research Institute 

Plants Gideon Smith PRECIS South Africa 

Patricia Craven PRECIS Namibia 

Ted Oliver SABONET 

Philip Desmet Institute for Plant Conservation 

Small mammals Mike Griffith National Museum of Namibia 

Marion Burger Northern Flagship Institute 

Andrew Turner Western Cape Nature Conservation Board 

Scorpions Lorenzo Prendrini UCT/New York Museum of Natural History 

Birds James Harrison Avian Demography Unit 

Fish Dean Impson Western Cape Nature Conservation Board 

Reptiles Marion Burger Northern Flagship Institute 

Andrew Turner Western Cape Nature Conservation Board 

Important databases that were requested, but not available within the project 

timeframe and hence not used in these analyses, were: 

Database Contact Person Organisation 

Succulent Karoo global 

plant species list 

Craig Hilton-Taylor IUCN, formerly NBI 

Reptiles QDS Bill Branch Bay World, Port Elizabeth 

Data extraction instructions were provided to the curator of each dataset. A Microsoft 

Access tutorial was developed to help institutions extract the data required for this 

project (see Appendix 9 in Part E). The basic request submitted to all databases was 

the following: 

• Extract all records that fall within the SKEP QDS area (489 QDS). 

• For each species extracted in the above request, extract all distribution records 

from the database. 

This not only gives us a list of species that occur in the SKEP area, but step two 

gives us an idea of the global distribution of each species and hence enables us to 

calculate levels of endemism for the Succulent Karoo. 

The initial data request asked for information on 489 QDS within the SKEP planning 

domain. This is an area much larger than the Succulent Karoo; however, at the 

outset it was decided to be inclusive rather than exclusive in defining the planning 

domain (see Section 5). When the core Succulent Karoo was defined later in the 

project (308 QDS), it was easier to refine the existing requested data rather than 

asking the data providers to supply information on additional QDS included in the 

definition of the Succulent Karoo (see Figure 6 below). 


Figure 6 shows the classification of SKEP QDS into Succulent Karoo (308 QDS) and 

non-Succulent Karoo (top right), and into the four SKEP sub-regions (bottom left). 

The top-right map also shows the QDS in each of the nine geographic priority areas 

identified as an outcome of the SKEP conservation planning exercise (see Section 

15). 

Figure 6: Classification of SKEP QDS into Succulent Karoo and non-succulent 

Karoo, geographic priority areas (top right) and SKEP sub-regions (bottom left) 

Table 6 provides a basic summary of the information used to compile the biodiversity 

statistics for the Succulent Karoo. Although QDS information for reptiles was 

provided, this was not used as recent nomenclatural changes in the group provided a 

significant source of error in the data. The results for the various taxonomic groups 

are presented in the table below. The results are presented in three sections based 

on the three databases assembled for analysis presented in Table 6. 

Table 6: Number of database records used to compile the biodiversity 

statistics for the Succulent Karoo 

Taxonomic Group 

Total number of records in 

each database 

Succulent Karoo records 

only 

1. Plants 287 386 46 068 

2a. Amphibian, Bees, Termites, 

Fish, Mammals, Scorpions 

11 479 5 916 

2b. Reptiles 

Composite species list for 

Succulent Karoo 

- 

3. Birds Summary QDS data provided - 


Data analysis and results 

The protocol for amalgamating databases and extracting the summary information for 

the global species lists and endemicity analyses is illustrated in Figure 7. Figure 8 

illustrates the steps involved in determining levels of endemicity. Three summary 

databases were developed, based on the size and type of input data, for: 

• plants; 

• birds; 

• all other taxonomic groups. 

Information related to these summary databases follows. Additional tables with 

further details can be found in Part D. 

Summary information for plants 

Table 28 in Part D provides a summary of the number of plant families, genera and 

species found in the Succulent Karoo. There are 168 families, 1002 genera and 6356 

species according to the results of this analysis. 

There are two methods of ranking plant endemicity status in the Succulent Karoo. 

Endemicity class is based on the number of QDS where a species has been 

recorded that fall within the Succulent Karoo relative to the total number of QDS in 

which a species has been recorded. Distribution range is based on the percentage of 

QDS where a species has been recorded that fall within the Succulent Karoo. 

Endemicity classes are defined as follows: 

1 = Endemic to the Succulent Karoo (i.e. occurs only within the SKEP QDS area). 

2 = Occurs in Succulent Karoo and only in 1-3 other QDS outside the SKEP QDS 

area (i.e. near-endemic). 

3 = Occurs in Succulent Karoo and 4-10 other QDS outside the Succulent Karoo. 

4 = Occurs in Succulent Karoo and in >10 other QDS outside the Succulent Karoo. 

Table 7 summarises the results according to these four classes. 

Table 7: Summary of endemicity status of Succulent Karoo plant species 

Endemicity Total number of % of total Distribution Total number of % of total 

class species species range species species 

1 1630 26 < 50% in SK 3647 57 

2 909 14 50 to 75% in 772 12 

3 975 15 75 to 99% in 262 4 

4 2842 45 100% in SK 1630 26 

Alien 45 1 

Grand Total 6356 100 6356 100 


Figure 7: Flow diagram illustrating the steps involved in preparing the summary species distribution databases for analysis 


Figure 8: Steps involved in determining endemicity of species recorded in the Succulent Karoo 


A complete global plant species list for the Succulent Karoo, developed by the SKEP 

Biodiversity Component, is available in electronic form together with electronic copies 

of this report (see Section 1). Species are arranged according to the PRECIS 

numbering system. Information given in the species list includes family, endemicity 

status and occurrence in each of the four SKEP planning regions. 

Figure 9 illustrates the relationship between collecting intensity (i.e. the number of 

records per QDS) and the number of species recorded in a QDS for plants. There is 

a significantly positive relationship between collecting intensity and species diversity 

in the Succulent Karoo. Using only collection data to guide conservation decisions is 

biased in favour of areas that have been well collected. There may be other areas 

with significantly high levels of diversity that are not identified using these data. 

Compare, for example, the outcome of the QDS distribution data versus the expert 

mapping outcomes. If the number of endemic plants is used as a simple surrogate for 

conservation importance, the QDS data match the expert information at a very broad 

scale (see Figure 10). However, at the scale at which SKEP is working, many of the 

details of the expert areas and also smaller mapped areas are not elucidated in the 

QDS data. A question worth asking is whether Springbok is really the most endemic 

rich QDS in the Succulent Karoo or whether this is a function of the town being one 

of the oldest urban settlements in the biome. 

Figure 9: The relationship between collecting intensity (i.e. the number of 

records per QDS) and the number of species recorded in a QDS for plants 

SKEP Biodiversity Component Technical Report, March 2003 

Page 38

Figure 10: The overlap between conservation priorities based on the number of 

endemic plants per QDS versus areas mapped by experts 

Figure 11 shows the distribution of the total number of plant records per QDS for the 

whole SKEP planning domain, and the number of Succulent Karoo plants species 

and endemic plant species (Categories 1&2, Table 21) per QDS in the Succulent 

Karoo part of the planning domain. The distribution of total plant records shows that 

there are some major data gaps in the plant distribution database. This supports the 

assertion made with Figure 9 and Figure 10 that using species distribution data in 

conservation planning is biased towards areas where there are collection data. The 

distribution of endemic plants is centred along the axis of the western escarpment 

mountains and western Little Karoo basin. Broad centres of endemism are congruent 

with the nine geographic priorities identified by SKEP (see Figure 27 in Section 15). 


Page 39

Figure 11: The distribution of plant collecting records, number of species and 

number of endemic plants in the Succulent Karoo. 

Summary information for birds 

Four hundred and thirty-one bird species (379 genera, 92 families, 25 orders) have 

been recorded in the Succulent Karoo according to the SKEP analysis. Table 29 in 

Part D gives summary statistics for these species. Bird endemicity was not analysed 

as only one species, Barlow’s Lark, is a strict Succulent Karoo endemic. There are, 

however, eight species strictly endemic to southern Africa’s arid zone (viz. Succulent 

and Nama Karoo, Vernon 1999). 

Of the 431 bird species recorded from the Succulent Karoo, six have duplicate 

numbers in the bird database (i.e. species that have been split subsequent to the 

advent of the Bird Atlas Project in southern Africa, e.g. ADU number 502 = Karoo 

Lark as well as Barlow’s Lark). There are potentially a further six species that should 

be included in the summary information. These species are listed in Table 30 in 

Part D. 

Summary data for Amphibians, Bees, Termites, Mammals, Scorpions 

and Reptiles 

Summary data for these taxa is presented at three different levels. Table 31 and 

Table 32 in Part D give summary statistics at the generic level and the class level 


Page 40

espectively. Table 8 below gives summary statistics at the order level. All three 

tables include endemicity status. 

Table 8: Summary statistics at the order level for Amphibian, Bees, Termites, 

Mammals, Scorpions and Reptiles that occur in the Succulent Karoo 

Endemicity Classes (Status): 

1= Occurs only in the Succulent Karoo area (i.e. 100% of known distribution is in the Succulent Karoo). 

2= Between 50 and 100% of distribution of species in the Succulent Karoo OR at least 25% or m ore of 

distribution if species known from 4 QDS or fewer. 

4= less than 50% of known range in the Succulent Karoo. Known from 5 or more QDS. 

(Note: Fish do not appear in this table because no fish fall into these endemicity classes.) 

CLASS Status 

Total 

Species % of Class 

Amphibia 1 5 29 

2 8 47 

4 4 24 

Amphibia Total 17 100 

Aranaea 1 18 26 

2 20 29 

4 32 46 

Aranaea Total 70 100 

Insecta 1 86 49 

2 74 42 

4 17 10 

Insecta Total 177 100 

Mammalia 1 6 9 

2 11 16 

4 51 75 

Mammalia Total 68 100 

Reptilia 1 24 20 

4 97 80 

Reptilia Total 121 100 

Grand Total 453 

For more information about fish in the Succulent Karoo, see the report in Appendix 4 

(Freshwater Fishes of the Succulent Karoo Biome: Distribution, Conservation Status, 

Hotspots and Associated Conservation Issues, by N.D. Impson, A. Abrahams and A. 

Turner.). 

Interpretation and limitations 

As stated at the beginning of this section, the aim of collecting species distribution 

data was primarily to provide a biome-wide overview of the distribution of biodiversity 

in the Succulent Karoo and a set of baseline statistics. No prescriptive conclusions 

about conservation priorities in the region are drawn based on these data, and the 

data were not used in the analysis of geographic conservation priorities presented in 

Section 15. The results can also be seen as a preliminary step towards identifying 

priorities for future inventory and taxonomic research. 

The number of available biodiversity inventory datasets for the region limits the 

analyses presented. The availability of this data is a direct function of the number of 

taxonomists working in the relevant fields as well as funding available for the 


Page 41

collection and curation of such data. Although the quantity of collection data for the 

Succulent Karoo is probably better than for most terrestrial regions in the world, it is 

nonetheless biased in favour of taxa and regions that have been well collected, are 

better known, or are the focus of the institution or person who provided the data. The 

data collection deficiencies demonstrated for plants (see Figure 9 above) are 

mirrored for all taxonomic groups looked at. Interpretation of these data needs to 

mindful of these deficiencies. 

In the short term some of these deficiencies can be addressed by accessing other 

available data. For example, the plant dataset is lacking data from the two flagship 

herbaria for the Succulent Karoo, namely the Bolus Herbarium and dicotyledons from 

the Compton Herbarium. Adding this information would more than double the size of 

the plant database and fill many of the collecting gaps identified. However, there are 

some genuine data gaps where there has been very little information collecting of 

any sort. The most glaring is the Sperregebiet. These gaps can only be addressed 

through further collecting. 

Nevertheless, broad patterns of biodiversity in the Succulent Karoo can be distilled 

from the data. Centres of biotic diversity are congruent with the nine geographic 

priorities identified in the SKEP process (see Figure 27 in Section 15). 


Page 42

10. Spatial Components of Ecological and Evolutionary 

Processes 

Why spatial components of processes are important 

Conservation planning aims to ensure the representation and the persistence of 

biodiversity indefinitely (Terborgh and Soulé 1999, Margules and Pressey 2000). The 

goal of biodiversity representation has been expressed in many different ways from 

protecting species occurrences to conserving entire ecosystems (e.g. Franklin 1993, 

Noss and Cooperrider 1994, Rebelo 1997). The goal of biodiversity persistence 

requires the consideration not only of biodiversity patterns, but also of the processes 

that maintain, sustain and generate this biodiversity (Balmford et al. 1998, Cowling et 

al. 1999a, Margules and Pressey 2000). Ensuring that protected areas represent 

biodiversity pattern will not necessarily guarantee their persistence. Ecological and 

evolutionary processes should be directly incorporated into conservation planning by 

identifying the spatial requirements of these processes (Balmford et al. 1998). 

The most common and long-standing approach to addressing processes in 

conservation planning has been to consider generic design criteria such as the size, 

shape and connectivity of conservation areas (Shafer 1990, Noss et al. 1997). 

Although it is generally true that more natural processes will continue in larger 

conservation areas (Cowling et al. 1999a, Pressey et al. 2003), the persistence of 

other processes will hinge on conservation of their particular spatial components 

(Cowling et al. 1999a, Cowling and Pressey 2001, Desmet et al. 2002, Moritz 2002, 

Cowling et al. 2003a, Rouget et al. 2003a). Spatial components are defined here as 

the physical features of a region with which particular ecological and evolutionary 

processes are associated. These can be identified in many ways. They might include 

drought refugia (Morton et al. 1995), climatic refugia (Noss 2001), ecotones (Smith et 

al. 1997) and unusual geologies associated with endemic species (Coleman and 

Kruckeberg 1999). 

In the Succulent Karoo, distinct processes have been associated with with surface 

geology and soils, climate, topography, drainage systems, and the configuration of 

remaining native vegetation. These features could be missed or only partly 

incorporated into conservation plans unless they are specifically identified and 

targeted (Cowling and Pressey 2001, Mortiz 2002, Cowling et al., 2003a). 

Ideally, areas maintaining adaptive diversification (e.g. environmental gradients, 

ecotones) or containing historically isolated populations should be identified and 

protected (Moritz 2002, Rouget et al. 2003a). The spatial dimensions of ecological 

processes such as drought refugia also need to be determined and such insights 

incorporated in conservation planning. Finally, connectivity within these areas should 

be ensured to maintain species migration and gene flow. 

However, the spatial components of processes have rarely been considered in 

conservation planning. Although the literature on ecological and evolutionary 

processes is huge, very little is relevant to conservation planning because most of 

the studies have failed to identify the spatial dimensions of these processes. 


Page 43

This section describes the spatial components of key processes that maintain 

biodiversity in the Succulent Karoo and explains how they were mapped in order to 

be incorporated in the conservation plan. 

How the process layer was developed 

Our approach is based on the earlier study of the Succulent Karoo by Cowling et al. 

(1999a). This was the first study to systematically address ecological and 

evolutionary processes in the Succulent Karoo and develop to spatial components for 

these processes. Given the regional scale of the SKEP project, the focus was on 

medium- to large-scale processes only. 

At the first SKEP Biodiversity Component Workshop (22 January 2002, see 

Section 20), the processes listed in Table 9 were recognised as being important for 

maintaining biodiversity. Processes identified in Cowling et al. (1999a) were used as 

a starting point. Preliminary spatial components were identified and were refined 

later, partly through a focus group meeting held with experts in this field (see Section 

23). 

Table 9: Key ecological and evolutionary processes for maintaining 

biodiversity in the Succulent Karoo (modified from Cowling et al. 1999a) 

Process Spatial component 

1. Viable populations of endemic species Small conservation areas (

Table 10: Spatial components of ecological and evolutionary processes 

identified in the SKEP planning domain 

Spatial component Ecological or evolutionary process Method of identification 

Spatially fixed 

Sand movement 

corridors 

Inland movement of marine sands 

and associated soil development 

Riverine corridors Migration and exchange between 

inland and coastal biota 


Functional corridor comprising intact 

source and sink areas 

250m buffer of untransformed habitat 

along riverine systems linking coastal 

and inland subregions 

Edaphic interfaces Diversification of plant species 500m buffer of untransformed habitat 

along vegetation types of contrasting 

substrates 

Quartz patches Diversification of plant species Remote sensing and expert 

knowledge 

Spatially flexible 

Upland-lowland 

gradients 

Macroclimatic 

gradients 

Sand movement corridors 

Ecological diversification of plant and 

animal lineages; migration of biota 

Geographic diversification of plant 

and animal lineages; migration of 

biota in response to climate change 

Only directions were indicated 

Only directions were indicated 

Sand movement corridors are living systems in constant motion. They are important 

habitats for many reptiles, amphibians, birds, small mammals and invertebrates, and 

are sensitive to transformation. Sand movement corridors are large interconnected 

landscapes “units” that are dependent on the other parts of the unit for their 

existence. Disrupting the mobility of these corridors has serious knock-on effects for 

human activities. 

In more formal terms, the movement of marine sediments represents a dynamic 

process that drives ecosystem functioning and determines biodiversity patterns. 

Sand deposits create a complex sequence of sediments of various ages associated 

with unique plant species assemblages (Desmet 1996, Cowling et al. 1999a). 

Sand movement corridors were mapped from satellite image, and reflected in the 

SKEP vegetation map (see Section 7). Only functional sand movement corridors 

were included in the process layer. Sand movement corridors were considered 

functional if less than 50% of the area had been transformed by agriculture and 

urban development, and if no major road traversed them. 

Twenty-one functional sand movement corridors were identified in the SKEP 

planning domain. They are shown in Figure 12. 

Riverine corridors 

Riverine corridors are important channels for plant and animal species movement, 

partly because they link different valleys and mountain ranges. They are also 

important as a source of water for human use. Vegetation on riverbanks needs to be 

Page 45

maintained in order for rivers themselves to remain healthy, thus the focus is not just 

on rivers themselves but on riverine corridors. 

In more formal terms, riverine ecosystems support structurally and functionally 

heterogeneous assemblages (Milton et al. 1997). They are associated with several 

ecological processes. Riverine corridors facilitate animal movement and plant 

dispersal by linking the major topographic regions of the Succulent Karoo: the coastal 

lowland, the escarpment, and the interior basin and mountains. There is evidence 

that migration of plant species along riverine corridors has resulted in species 

diversification (Bayer 1999). Owing to their topographic and climatic heterogeneity, 

riverine corridors also act as refugia from drought and have provided refugia for 

mesic and xeric species during major climatic events in the past (Cowling et al. 

1999a). 

Inter-basin riverine corridors were defined as those that link two of the three major 

topographic regions (coastal lowland, escarpment, interior basin and mountains) (see 

Figure 13). Riverine corridors that were identified in CAPE (Cape Action Plan for the 

Environment) and that fall into the SKEP planning domain were also selected (see 

Rouget et al. 2003a). In Namaqualand and Namibia, all rivers can act as riverine 

corridors for at least two reasons: 

• all estuaries are important bird areas; 

• all areas are highly susceptible to climate change and species migration is mostly 

confined along rivers. 

A buffer of 500m on each side of the riverbank was used. Only untransformed areas 

(based on current land use) within the buffer were considered suitable for maintaining 

ecological processes. 

Twenty-five riverine corridors were identified in the SKEP planning domain. They are 

shown in Figure 12. In Namibia, only 1% of the total length of these riverine corridors 

has been transformed by agriculture, mining and urban development; in South Africa 

25% has been transformed. 

Edaphic interfaces 

Vegetation types with similar substrates (geology or soil type) have soft edaphic 

interfaces. These interfaces are important for plant species migration – they allow 

species to move. Hard edaphic interfaces, between vegetation types with different 

substrates, are important for species diversification. Selection and subsequent 

diversification needs to take place in order for plant species to cross these 

boundaries. 

In more formal terms, habitat specialisation plays an important role in plant 

diversification in the Succulent Karoo. Ecological diversification of poorly dispersed 

lineages generally occurs in areas of contrasting edaphic types (Desmet and Cowling 

1999). Such areas can be identified on the basis of edaphic interfaces (sharp 

edaphic discontinuities preventing species migration) or on the basis of edaphic and 

topographic diversity in a given area. 

To identify edaphic interfaces, unique combinations of vegetation types were 

classified based on their underlying parent material. Unique combinations were 

coded as hard, semi or soft interfaces according to the potential for species to move 

across these edaphic boundaries (Table 11). Hard interfaces were considered to 


Page 46

promote ecological diversification. A buffer of 500m was used on each side of the 

hard interfaces. Only untransformed areas (based on current land use) within the 

buffer were considered to be suitable for maintaining ecological diversification. 

Table 11: Classification of edaphic interfaces based on unique combination of 

parent material, according to the potential for species movement 

SOIL 1 2 3 4 5 6 7 8 9 

Acid Sand (1) 

Colluvium (2) Hard 

Granite (3) Semi Semi 

Granite & Colluvium (4) Semi Soft Soft 

Quartzite (5) Semi Semi Semi Semi 

Quartzite & Colluvium (6) Semi Soft Semi Semi Soft 

Quartzite & Shale (7) Semi Semi Semi Semi Soft Soft 

Sand (8) Semi Semi Semi Semi Semi Semi Semi 

Shale (9) Hard Hard Hard Hard Hard Hard Soft Hard 

Alkali Sand Hard Soft Hard Soft Hard Soft Hard Semi Hard 

Fourteen different categories of edaphic interfaces were identified (see Table 11). 

Almost 15 % of their total area has been transformed by urban development, mining, 

and crop agriculture and cannot therefore maintain processes associated with the 

edaphic interfaces. 

Edaphic interfaces are the most widespread of the process components mapped for 

the Succulent Karoo. They are too dense to show in a biome-wide map printed at the 

size allowed by this report, and are not included in Figure 12. Figure 26 in Section 26 

shows edaphic interfaces for Namaqualand (along with other ecological processes in 

Namaqualand). 

Drainage basins associated with quartz patches 

Quartz patches are unique to the Succulent Karoo biome. These extraordinary 

biodiversity features are centres of endemism and species diversification, and are 

especially important habitats for the dwarf succulents that are a hallmark of the 

Succulent Karoo. Quartz patches are delicate systems, extremely sensitive to 

transformation. 

Quartz patches form when colluvial or alluvial soils deposited in a valley bottom are 

eroded by water. The fine soil material is washed away, leaving behind a lag of 

quartz pebbles on the soil surface. Quartz patches are invariably associated with the 

valley bottoms and also specific drainage basins that have the right parent material, 

i.e. quartz-rich bedrock. Depending on the geological history of the drainage basin, 

quartz patches in one basin may be in a more advanced state of development than 

another basin in a river catchment next door. Moreover, once plants colonise the 

quartz patches they tend to be restricted to quartz patches within one drainage basin 

system, as these patches are isolated from neighbouring systems by the non-quartz 

patch habitats that comprise the drainage basin catchment. 

Drainage basins are assumed to represent evolutionary fronts of currently speciating 

taxa – the Mesembryanthemaceae in particular (Desmet et al. 1998). Each of these 

drainage basins comprises a distinct evolutionary front, including both ancestral and 

young species (Cowling et al. 1999a). To promote biodiversity persistence, entire 


Page 47

drainage basins should be targeted in conservation planning. Several adjoining 

drainage basins can capture several unique systems of plant diversification. 

Large drainage basins were mapped using the DEM and quartz patches from the 

satellite image and available knowledge of their distribution. They were incorporated 

into the vegetation map (see Section 7). 

Over 590 000ha of drainage basins and associated quartz fields were identified in the 

SKEP planning domain. They are shown in Figure 12. 

Island patches of special habitats 

Special habitats comprise inselbergs, quartz patches and “stepping stones”. Bedrock 

outcrops might promote ecological divergence in the Succulent Karoo. These hard 

surfaces also provide stepping stones for the flora to migrate. Spatial dimensions for 

these special habitats were not identified as quartz patches – the most important 

ones – were already captured by drainage basins. 

Upland-lowland gradients 

Upland-lowland gradients and climatic gradients are important for species migration 

and species diversification in response to climate change. Temperature and rainfall 

change along these gradients. Keeping natural habitat intact along the length of 

these gradients allows them to continue playing their ecological role. 

In the past, seasonal movements of large mammals used to occur along a gradient 

from the uplands (summer grazing) to the coastal lowland (winter grazing). These 

gradients are important for the migration of biota in general as well as small-scale 

adjustments to climate change and should be considered in conservation planning 

(Rouget et al. 2003a). However, the precise migration route is not well defined as 

such process can persist in various spatial configurations. These processes might be 

best addressed in designing protected area networks by ensuring that uplandlowland 

links exist within protected area networks. Gradients, which are constrained 

by habitat transformation, should take the shortest possible route. 

The directions of the gradients were indicated but specific spatial dimensions were 

not identified for them, as shown in Figure 12. For the Namaqualand and Namibia- 

Gariep subregions, gradients should run from the coastal plain to the escarpment, 

and from the escarpment to the highveld (and vice-versa). For Hantam-Tankwa- 

Roggeveld, gradients should run from the interior basin to the escarpment (and viceversa). 

For the Southern Karoo, gradients should run north-south through the interior 

basin. (Figure 13 shows these major topographic regions.) 

Macroclimatic gradients 

Recent studies by the National Botanical Institute have indicated that the impacts of 

climate change in the Succulent Karoo are likely to be severe (see 

www.nbi.ac.za/frames/researchfram.htm). Species level analysis has indicated that 

species composition is likely to change, and could even lead to major structural 

changes in the biome’s vegetation. The majority of the centres of species endemism 

in South Africa may show significant deterioration of bioclimate, with more than half 

predicted to experience bioclimatic conditions completely unlike those of today 


Page 48

(Midgley et al. 2001). Conservation areas are also likely to experience a complete 

alteration of climate. 

This means that it is important for the protected area network to maximise the ability 

of species to move in response to climatic change. Macro-climatic gradients are 

particularly important for allowing species migration in response to climate change. 

As for the upland-lowland gradients, the direction of the macro-climatic gradients is 

indicated without specifying their exact route. 

Major climatic gradients run east-west in the Southern Karoo and Hantam-Tankwa- 

Roggeveld sub-regions, and north-south in Namaqualand and Namibia-Gariep subregions, 

as shown in Figure 12. 

Limitations of the process layer 

The spatial components of processes were defined at a broad scale and within the 

constraints of a short project timeframe. Much more information is required to define 

their spatial dimensions more fully and accurately. 

Firstly, generic spatial components of processes were identified, in other words these 

are not taxa-specific and their role in maintaining biodiversity might differ between 

taxa. Secondly, the configuration of spatial components might be too narrow in some 

cases to sustain ecological diversification or to allow species migration. Lastly, given 

the complexity of geological types, numerous edaphic interfaces were identified as 

spatial components of species diversification but not all might enable speciation. Very 

little is known about species diversification in the Succulent Karoo. Although the 

detailed mechanisms of speciation in the SK are still largely unknown, the hypothesis 

of speciation due to edaphic diversification remains the most probable (Cowling et al. 

1999a; Desmet et al. 2002). 

Despite these limitations, there is an urgent need to incorporate the spatial 

components of processes into systematic conservation planning. This is the only way 

to explicitly target evolutionary and ecological processes, and thus to ensure 

persistence of biodiversity over time. Spatial components will differ between different 

biogeographic zones and for different lineages, and it may not be possible to collect 

all of the data required to identify the spatial components in a rigorous way. 

Conservation planning must proceed before results of all ongoing research are 

available. The only short-term solution, especially in data-poor areas, is to use expert 

knowledge of population, community and landscape ecologists and evolutionary 

biologist, to make informed estimates of spatial dimensions. 


Page 49

Figure 12: Spatial components of ecological processes in the SKEP planning 

domain 

Figure 13: Topographic regions in the SKEP planning domain 


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11. Land Use and Habitat Transformation 

Why land use and habitat transformation are important 

The formulation of an effective strategic plan for biodiversity conservation in the 

Succulent Karoo required an assessment of the current situation with regard to 

habitat transformation, and an explicit framework for predicting the likelihood of 

remaining habitat (i.e. that potentially available for conservation) being transformed. 

Although the loss of habitat through land-use practices has been recognised as the 

major threat to biodiversity (Wilcove et al. 1998), the emphasis in conservation 

planning has largely been on identifying biodiversity features. Less attention has 

been given to identifying, in spatially explicit terms, the factors that threaten 

biodiversity now, and how these are likely to change in the future. Most of the 

conservation planning literature that does deal with threats to biodiversity has 

focused on identifying threats to biodiversity at the species level (Rebelo 1992, Sisk 

et al. 1994, Flather et al. 1998). Conservation decisions seldom incorporate 

estimates of future changes in land use (Menon et al. 2001, Rouget et al. 2003b). 

Detailed knowledge of land-use pressures on biodiversity should be an essential 

component of conservation planning for two main reasons: 

• Firstly, current land-use and likely future land-use changes constrain 

conservation planning (transformed land usually has very low conservation value, 

and areas with high transformation potential are problematic for incorporating in 

protected area networks). 

• Secondly, the spatial dimensions of habitat transformation (current and predicted) 

have implications for implementing conservation strategies (Margules and 

Pressey 2000, Pressey and Cowling 2001). Transformed or highly fragmented 

habitats with many competing land-use pressures require different forms of 

conservation action than those relatively free of human activities because the 

latter are to some extent self-protected by their harsh environmental 

characteristics (e.g. mountainous areas on unfertile soils – factors that have 

limited human development). Moreover, habitats susceptible to be transformed in 

future should receive priority in conservation action. 

Over the last decades, several models of land-use change have been developed to 

project and quantify future land use and cover (see review in Veldkamp and Lambin 

2001). This section outlines the approach used in SKEP for assessing current land 

use and deriving spatial predictions of future land-use change in the Succulent 

Karoo. Mapping by local and regional stakeholders played an important part in the 

approach. This section should be read together with Section 22 in Part C, which 

describes how the stakeholder mapping exercise was undertaken in more detail. 

What needs to be mapped 

For the SKEP project, we wanted to map areas that had already been transformed by 

various land uses, as well as the likelihood of future transformation of habitat. 


Page 51

Current habitat transformation 

Transformation of natural habitats can be classified in various categories from 

outright loss of vegetation (e.g. in built-up urban areas) to change in vegetation cover 

or structure (e.g. as a result of grazing). For conservation planning, a spatial layer 

showing the extent and configuration of “natural”, restorable and irreversibly 

transformed areas in the domain is needed. Areas categorised as “natural” are 

normally considered as suitable for achieving conservation targets (see Section 14). 

Restorable areas would be considered if conservation targets for some features 

could not be achieved in areas of natural habitat. Irreversibly transformed areas such 

as urban areas do not generally contribute to conservation targets. 

Outright loss of natural habitat (e.g. urban and cultivated areas) can easily be 

identified using remote sensing. However, it is extremely difficult to map gradients of 

alteration such as grazing intensity. In the Succulent Karoo where grazing is the most 

extensive land use, quantitative and spatially explicit information of grazing intensity 

is required. 

Future land-use pressures 

Habitat likely to be transformed in future should receive priority for conservation 

action. In the Succulent Karoo, future pressures on biodiversity are likely to come 

from new mining development, expansion of crop agriculture and ostrich farming, 

unsustainable use of natural resources, overgrazing by sheep and goats, and to a 

certain extent urban development. 

Complex spatial modelling which integrates socio-economic factors, together with 

adequate data layers on currently transformed areas, would be required to derive an 

accurate layer for each of these land-use pressures. This was not possible given the 

timeframe and resources of the SKEP project, so a combination of stakeholder 

knowledge, expert knowledge and some basic spatial data layers was used. The 

planning horizon was ten-years, in other words the likelihood of habitat 

transformation in the next ten years was considered. 

Data sources 

Large amounts of data currently exist which describe current land use practises in 

the Succulent Karoo. However, few are spatially explicit. Following the first 

Biodiversity Component Workshop on 22 January 2002 (see Section 20), all possible 

sources of land use data were listed. Due to the limitations of most datasets in terms 

of geographic coverage, two main sources for identifying the spatial dimensions of 

current land use were used, namely the National Land Cover (NLC) for South Africa 

and the stakeholder mapping dataset (explained below). 

The NLC was derived from classification of satellite imagery collected from 1994 to 

1996 (Fairbanks et al. 2000). Satellite image interpretation is the most widely used 

technique for depicting spatial patterns of habitat transformation. The NLC contains 

the following land-use categories: improved grassland (pastures), forest plantations 

(by non-indigenous trees), degraded vegetation (due to overgrazing and fuel wood 

collection), cultivated lands (permanent/temporary, irrigated/dryland), urban 

(residential, commercial, industrial) and, mines and quarries. The NLC database was 

designated for 1:250 000 scale mapping applications (25 ha minimum mapping unit) 

and is appropriate for this study. 


Page 52

The use of the NLC raised two issues: 

• Firstly, remote-sensing techniques fail to accurately identify land degradation 

(e.g. overgrazing, erosion), especially in arid ecosystems. 

• Secondly, the NLC is geographically limited to South Africa and no information 

was available at this scale for the Namibian section. 

To compensate for these two shortcomings, stakeholder knowledge of current landuse 

practices was used. Stakeholder mapping workshops were organised by the 

sub-regional champions to complement existing information from the NLC for the 

following land-use sectors: 

• agriculture; 

• mining; 

• tourism; 

• conservation; 

• communal areas. 

In this document, this dataset is referred to as the stakeholder mapping data. 

Participants were asked to map current and future land use practices on 1:250 000 

topography maps. Data forms were completed for each feature mapped (see 

Appendix 11 in Part E). Although this exercise stimulated enormous participation in 

SKEP, the quality of the data gathered was uneven among sub-regions, which limited 

its use for this analysis. However, the information was captured as a potential basis 

for other studies. (Note that the stakeholder mapping of conservation areas was not 

used in the current land-use layer but was incorporated into the protected area layer 

(see Section 12). Stakeholder mapping of communal areas provided data that were 

too incomplete and uneven across the planning domain to use for SKEP.) 

Spatial patterns of future land-use pressure in the SKEP planning domain were 

derived using a combination of expert knowledge, stakeholder knowledge, basic 

spatial data layers (such as mining licences) and simple models. 

Methods 

Current habitat transformation 

The extent and configuration of the current land-use in the Succulent Karoo was first 

assessed using the NLC. The 20-30 NLC categories (depending on the province) 

were reclassified into the following categories: cultivated crops (including forestry 

plantations), degraded areas (due to erosion/overgrazing), mines and quarries, urban 

areas, waterbodies, and “natural” (areas of natural habitat). 

The stakeholder mapping data were separately digitized for each of the five sectors 

(see above). The resolution of the mapping was quite variable. Data mapped at the 

cadastral level were excluded because of scale incompatibility with the NLC data 

(25m resolution). 

Both layers (NLC and champions) were combined to derive a composite layer of 

habitat transformation. The addition of the stakeholder mapping did not provide 

adequate information on the overgrazing status of the Succulent Karoo because of 

the lack of a common definition of overgrazing among all sub-regions and the 

intrinsic difficulty of mapping overgrazing. Although the stakeholder mapping data 


Page 53

provided good maps of overgrazed areas for the Hantam-Tankwa-Roggeveld region, 

the information was not consistent throughout the biome, especially for 

Namaqualand. This was compensated for by a map of overgrazed areas for 

Namaqualand based on a combination of expert knowledge of the region and 

interpretation of the SKEP satellite image. Manual interpretation of the satellite image 

was used to map overgrazing in Namaqualand as large areas with lower than 

expected vegetation cover can be detected by comparing color patterns along fence 

lines. 

Over 11 million hectares (5%) of the Succulent Karoo biome has been transformed 

by crop agriculture, urban development and mining and is no longer available for 

conservation (Table 12). Almost half of the Succulent Karoo vegetation types (61) 

have not been affected by urban development, crop agriculture or mining, and only 

five vegetation types have 50% or more of their original area transformed (Figure 14). 

The extent of habitat transformation is uneven in the Succulent Karoo biome with 

Namaqualand and the Southern Karoo being the two sub-regions most affected 

(Table 12). 

no of veg. types 

70 

60 

50 

40 

30 

20 

10 

0 

0 0-5 5-25 25-50 50-75 75-100 

% transformed 

Figure 14: Frequency distribution of current irreversible habitat transformation 

(urban, cropping, and mining; i.e. area not available for conservation) among 

the Succulent Karoo vegetation types 


Page 54

Figure 15: Map of habitat transformation showing the different land-use 

categories 

Table 12: Extent of habitat transformation within Succulent Karoo and the 

SKEP planning domain 

Region Area (ha) Crop (%) Mines (%) Urban (%) Total transf (%) 

• Namaqualand 3621866 4.34 1.79 0.08 6.21 

• Namibia-Gariep 2895118 0.10 4.27 0.07 4.44 

• Hantam-Tankwa- 

Roggeveld 3232802 2.00 0.02 0.03 2.04 

• Southern Karoo 1533603 5.97 0.01 0.23 6.20 

SK Biome 11283388 2.80 1.68 0.08 4.56 

Non SK Biome 14364581 2.97 0.15 0.06 3.18 

Total SKEP domain 25647970 2.90 0.82 0.07 3.79 


Page 55

Future habitat transformation: vulnerability 

Spatial estimates of future land-use pressures were derived for the following land-use 

categories: mining, urban development, crop agriculture, and ostrich farming. These 

spatial estimates were derived simplistically and provide only broad guidelines. The 

likelihood of each land-use in the next ten years was scored high (H), medium (M), 

unknown (U), low (L), or none (N) and was summarised at the scale of a planning 

unit (sixteenth degree square, see Section 13). 

Mining 

The likelihood of mining in the next ten years was based on mineral occurrence, 

prospecting and mining licences, combined with expert assessment of the likelihood 

of exploitation based on knowledge of the economic viablility of the mineral deposits 

involved and market conditions. Mining licence data were linked to parent parcels, 

and no differentiation was made between prospecting and mining licences. The 

likelihood of mining was scored high, medium, unknown, or none according to the 

criteria listed in Table 13. The likelihood of mining was assigned to each planning unit 

based on the rules listed in Table 14. More than 80% of the planning units have no 

likelihood of mining in the next ten years. 

Table 13: Criteria used to derive the likelihood of mining in the next ten years 

Likelihood of Criteria 

mining 

High (H) Parent parcel with licence application for high-return mineral 

Mineral deposit for high-return mineral likely to be exploited in 10 

years 

Medium (M) Parent parcel with licence application but exploitation of this mineral is 

uncertain 

Mineral deposit for mineral likely to be exploited in 20 years 

Unknown (U) Parent parcel with licence for mineral unlikely to be exploited 

None (N) Everywhere else 

Table 14: Rules used to summarise the likelihood of mining for each planning 

unit 

Likelihood of Rules No of planning 

mining 

units 

High H > 50% of planning unit area 698 

Medium M > 75% of planning unit area 

(H+M) > 25% of planning unit area 

489 

Unknown U > 50% of planning unit area 217 

Low M > 5% of planning unit area 49 

None Everything else 6130 

Urban development 

The likelihood of urban development was calculated based on distance from existing 

towns and topography. It was scored high, medium, or none according to the criteria 

listed in Table 15. The likelihood of urban development was assigned to each 

planning unit based on the rules listed in Table 16. More than 90% of the planning 

units have no likelihood of urban development while 3% have a high likelihood of 

urban development according to this model. 


Page 56

Table 15: Criteria used to derive the likelihood of urban development in the 

next ten years 

Urban potential Criteria 

Town (T) Existing towns 

High (H) Flat areas (= 8°) within 5 km of existing towns 

Medium (M) Steep areas (> 8°) within 5 km of existing towns 

None (N) Everywhere else 

Table 16: Rules used to summarise the likelihood of urban development for 

each planning unit 


urban dev 

units 

High H > 50% of planning unit area 236 

Medium M > 75% of planning unit area 

(H+M) > 25% of planning unit area 

172 

Low M > 5% of planning unit area 165 

None Everything else 6970 

Crop agriculture 

For each planning unit, the likelihood of crop agriculture was estimated based on 

existing cropping practises, water availability and topography. The likelihood of crop 

agrictulture was scored high, unknown, or none according to the criteria listed in 

Table 17. 

Table 17: Criteria used to derive likelihood of crop agriculture in the next ten 

years 


crop agric 

units 

High Sufficient water availability and flat topography 449 

None Insufficient water availability and/or rough 

topography 

6062 

Unknown Everything else 1032 

Ostrich farming 

For each planning unit, the likelihood of ostrich farming in the next ten years was 

estimated. The criterion for high likelihood was proximity to existing ostrich farming or 

lucerne fields (a key resource for ostrich farming). The criterion for medium likelihood 

was based on togography and proximity to roads, as ostriches are hardy birds that 

can be farmed more or less anywhere where the land is flat and where food can be 

trucked in. Likelihood of ostrich farming was scored high, low, or unknown according 

to the criteria listed in Table 18. 


Page 57

Table 18: Criteria used to derive likelihood of ostrich farming in the next ten 

years 

Ostrich farming Rules No of planning 

potential 

units 

High Near existing ostrich farming or lucerne fields 1019 

Medium 

Low 

Flat areas close to major roads 

Everything else 

5587 

None Category 1 and 2 conservation areas 937 

Figure 16 shows the spatial patterns of likelihood of mining, urban development, crop 

agriculture and ostrich farming. 

Figure 16: Spatial patterns of the likelihood of mining, urban development, 

crop agriculture and ostrich farming in the next ten years 

Overall vulnerability index 

For each planning unit, these four future land-use pressures were summarised into a 

single index of vulnerability. This represents the likelihood of further habitat 

transformation within the next ten years. The vulnerability index was scored high, 

medium, unknown, low, or none based on the highest score among the four 

categories of future land-use pressure. The following ranking order was used: None 

(lowest score) – Low – Unknown – Medium – High (highest score). Figure 17 shows 

the result. 


Page 58

Twenty-four percent of the planning units across the planning domain have a high 

vulnerability index, 6% medium, and 10% unknown. Only 9% have a vulnerability 

ranking of none. Of the 51% of planning units with a low vulnerability ranking, many 

fall outside the Succulent Karoo biome (see Table 19). This vulnerability index was 

incorporated in the framework for action map which was used for identifying 

geographic priorities for conservation action (see Section 15). 

Table 19: Summary of vulnerability index for each planning unit 

Vulnerability No of planning 

units 

High 1793 

Medium 489 

Unknown 730 

Low 3875 

None 656 

Figure 17: Spatial pattern of vulnerability to future land-use pressure in the 

SKEP planning domain 

Limitations of the land-use layers 

Given the available data and the time constraints, the spatial patterns of current and 

future habitat transformation show some limitations. It was not possible to spatially 

quantify grazing impact in a consistent way across the entire planning domain. As 

livestock farming is the most common land use practices in the Succulent Karoo, this 


Page 59

has considerably reduced the estimates of habitat transformation. As new data on 

grazing impacts become available, such estimates should be revised. The models of 

future land-use pressures rely on some relatively simple assumptions, and more 

complex models could be developed. 

Despite these limitations, the approach successfully identified areas not available for 

conservation due to complete habitat transformation. It also provided reasonable 

estimates of the areas most likely to be transformed in the near future. 


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12. Protected Areas 

Why a protected area layer is important 

Only 3.5% of the Succulent Karoo is formally protected, and the locations of formal 

protected areas mean that they do not represent the wide array of environmental 

heterogeneity, biodiversity patterns and processes in the region. Knowledge of the 

spatial location of currently protected areas is needed to assess the contribution of 

existing protected areas to meeting conservation targets (see Sections 14) and to 

identify gaps in the protected area network. 

Data sources and constraints 

No dataset of protected areas, currently available in GIS format for South Africa and 

Namibia, is entirely up to date. SKEP primarily relied on datasets provided by 

conservation agencies and government to build a GIS database of existing protected 

areas. Data from the Namibian Atlas Project and the South African Environmental 

Potential Atlas (ENPAT) were also used. Finally, the sub-regional champions 

provided recent information on the location and status of protected areas through the 

stakeholder mapping exercise (see Sections 11 and 22). 

The exact configuration and the status of protected areas sometimes differed 

according to the data source. In most cases, this was rectified by consulting the 

relevant conservation agency. 

All data supplied were combined into a single layer of protected areas. The 

boundaries were adjusted to cadastral boundaries when possible. This dataset was 

also used to develop the planning unit layer (see Section 13). 

Categories of protected areas 

Conservation planning exercises generally distinguish between different types of 

protected areas, according to the degree of protection of biodiversity provided. A 

common distinction made is between statutory and non-statutory reserves. Statutory 

reserves are supported by strong legal and institutional structures, while nonstatutory 

reserves represent varying degrees of legal protection and institutional 

capacity that are consistently weaker than statutory protected areas. For SKEP, 

protected areas were categorised based on a combination of legal status and 

management objectives. Two major classes of protected areas were identified: 

• Category 1 reserves: These are statutory reserves managed primarily for 

biodiversity conservation. They include National Parks; Department of Water 

Affairs and Forestry (DWAF) Nature Reserves and Provincial Nature Reserves. 

• Category 2 reserves: These are statutory and non-statutory reserves managed 

for biodiversity conservation and/or other land uses. So, for example, a statutory 

reserve managed for biodiversity conservation and other land uses would be 

classified as a Category 2 reserve rather than a Category 1 reserve. This is the 

case with the Richtersveld National Park, a contractual national park in which 

both conservation and other land uses occur. Other Category 2 reserves include 

local authority (municipal) reserves, Protected Natural Environments; Mountain 


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Catchment Areas; Conservancies; Natural Heritage Sites; Private Nature 

Reserves, DWAF Demarcated Forests; and Private Demarcated Forests). 

Table 20 gives a breakdown of the area conserved in Category 1 and Category 2 

reserves in the Succulent Karoo biome and in the SKEP planning domain. Over 

650 000 ha are under some form of protection, 60% of which is in Category 1 

reserves. Figure 18 shows the location of protected areas in the SKEP planning 

domain. 

Table 20: Area conserved in Category 1 and 2 reserves in the Succulent Karoo 

Class Type Area in ha (%) 

SK SKEP 

Category 1 National Parks 326393 797544 

Provincial Nature Reserves 64134 145519 

DWAF Nature Reserves 474 250082 

Sub-total 1 391001 (3.5) 1193146 (4.6) 

Category 2 Conservancies 86899 342934 

Local authority (municipal) reserves 4025 11010 

Mountain Catchment Areas 1619 277891 

Natural Heritages Sites 1346 2857 

Private Nature Reserves 53339 78831 

National Park * 


106700 162906 

Unknown 5608 45366 

Sub-total 2 259536 (2.3) 921795 (3.6) 

TOTAL 650537 (5.7) 2114941 (8.2) 

Limitations of the protected area layer 

This dataset is only suitable for analysis at 1:250 000 scale due to spatial 

inaccuracies. There may be conservancies and private nature reserves that have not 

been recorded, and the non-statutory status of those that have been recorded means 

that their designation may change. 

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Figure 18: Protected areas in the SKEP planning domain 


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13. Planning Units 

What are planning units? 

Planning units (also called selection units) subdivide the planning domain into many 

small units which are used for identifying geographic priorities for conservation action 

(and for designing a system of reserves if reserve design is undertaken). For each 

planning unit, data on biodiversity features and transformation of natural habitat is 

compiled. The contribution of each unit to achieving conservation targets (see below) 

is then assessed (see Section 4). 

How the planning unit layer was developed 

SKEP planning units consisted of sixteenth degree squares (average size 3 900 ha) 

and protected areas. Protected areas were obtained from various sources (see 

Section 12). 

Sixteenth degree squares were derived for the entire SKEP planning domain (6 638 

sixteenth degree squares). These match exactly with planning units used for the 

CAPE conservation plan. Category 1 and Category 2 protected areas were then 

integrated with the sixteenth degree squares (see Section 12 for definitions of these 

protected area categories). The exact configuration of Category 1 protected areas 

was used as planning units, i.e. each Category 1 protected area became a single 

planning unit. Category 2 protected areas (which provide weaker protection of 

biodiversity) were intersected with the sixteenth degree squares. This enabled 

selection of only parts of these relatively large areas to contribute to conservation 

targets. 

The planning unit layer consisted of 7 512 planning units including 6 585 sixteen 

degree squares (representing 86% of the available area) (see Table 21 and Figure 

19). 

Table 21: Planning units used for SKEP 

Type Area in km 2 (% SKEP) Number 

Sixteenth-degree squares 136895 (86) 6585 

Category 1 protected areas 15286.3 (10) 44 

Category 2 protected areas 5929.1 (4) 883 

Limitations of the planning unit layer 

The average size of a planning unit was 2 100 ha. All information regarding its 

biodiversity and land use status was summarised to the planning unit (i.e. the spatial 

location of features within each planning unit was lost). Therefore, outcomes based 

on this layer (e.g. the framework for action, see Section 15) can only be interpreted at 

a broad scale. 


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Figure 19: Planning units for the SKEP planning domain 


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14. Conservation Targets 

The role of targets 

As explained in Section 3, systematic conservation planning involves setting explicit 

targets for conservation of biodiversity pattern and process. A target might be, for 

example, 500 ha of a particular vegetation type, or a defined area of a particular 

riverine corridor. The success of the systematic approach relies on setting 

conservation targets in a consistent and transparent manner. Targets underpin the 

effectiveness of subsequent stages in the planning process. 

Targets need to use the best available ecological information to interpret the 

conservation goals as explicit, quantitative targets for biological features. Naturally, 

interpretation of the goals is constrained by the availability of both quantitative and 

expert biodiversity information. Also, targets require periodic revision as better 

information comes to light. 

To be effective, conservation targets must meet the following three criteria: 

• they must be comprehensive, i.e. they must cover all biodiversity features; 

• they must be quantitative; 

• they must be adequate and must not be constrained downwards by lack of 

quantitative or expert knowledge. 

Different types of targets can be distinguished: 

• baseline targets; 

• retention targets; 

• process targets. 

These are introduced briefly and then discussed further in the sub-sections that 

follow. 

If one wishes to conserve all biological diversity, one requires the whole landscape. 

In conservation planning a trade-off is made between the short- to medium-term 

needs of humans, and the need to conserve as much biological diversity as possible. 

Baseline targets are aimed at setting aside the minimum amount of land required to 

represent the biodiversity that occurs there (Pressey et al. 2003). Landscapes are 

generally composed of repeating units of the same biodiversity features (e.g. patches 

of the same vegetation type or populations of the same species). Thus, conserving 

one occurrence of a vegetation type might suffice for achieving the baseline or 

representation target. However, for this biodiversity to persist through time requires 

that the processes responsible for maintaining that patch of vegetation are 

maintained. Over and above the baseline target a process target is required as well. 

The relation of these targets to overall land-use is illustrated in Figure 20. 

Retention targets are used in some conservation plans to take account of the 

expected rate of future habitat transformation. As explained below, retention targets 

were not used in SKEP. 


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Figure 20: How targets relate to the division of the landscape and possible 

land-uses compatible with each zone 

Targets in CAPE 

There are different methods for setting conservation targets. Here the method used 

in CAPE is explained. The method developed for SKEP is then presented. 

In CAPE, targets for Broad Habitat Units (BHUs) were set by determining a baseline 

representation target for each BHU and then adding a retention target based on the 

extent of transformation in each BHU and the predicted rate of future transformation 

(Pressey et al. 2003), Equation 1. 

Equation 1: TARGET = BASELINE + RETENTION 

Baseline targets 

The baseline target is designed to capture biological heterogeneity between 

biodiversity feature classes (i.e. BHU, veg types), and is expressed as a percentage 

of total area. The BHU (or any vegetation map unit) is viewed here as an adequate 

surrogate for finer-scale patterns of diversity in plants as well as other taxonomic 

groups (e.g. insects or animals). 

Before setting baseline targets, there are two approaches for constructing 

biodiversity feature classes for the purpose of planning and setting baseline targets. 

Either assign different targets according to between-class biodiversity heterogeneity, 

or create homogeneous classes of biodiversity features and assign them the same 

target. Biological heterogeneity is defined as variation in abiotic and/or biotic factors 

(which are related to species diversity) within a given class. This implies that one has 

some indication of the biological variation between features classes. Alternatively, 

biodiversity feature classes can be defined as homogeneous 

environmental/biological units or as units with similar patterns of species diversity. 

This removes the need to scale targets according to the differential diversity between 

classes. For SKEP, the vegetation map is of the first type – feature classes or 


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vegetation types show different patterns of biological diversity. An adequate target for 

one class will not necessarily conserve the same proportional diversity in another 

class. 

The CAPE BHUs are also of the first type of biodiversity feature – classes are not 

equal in their biodiversity. In CAPE, a basic target of 10% was set for BHUs and then 

this target was weighted according to the observed heterogeneity of BHUs in 

different biogeographic regions of the planning domain. To the west of the Breede 

River there is double the species diversity than to the east. Also, uplands have more 

species than lowlands. Thus, for homogeneous BHUs, a baseline target of 10% was 

set, for moderately heterogeneous 15% and heterogeneous 25%. 

Retention targets 

The retention target was developed to take account of different levels of vulnerability 

to future transformation (high levels of vulnerability would mean a higher retention 

target) and also as a precautionary measure (if a biodiversity feature was likely to be 

lost it would receive a higher target). In CAPE, the retention target was added to the 

baseline target if the BHU was likely to disappear through future land use pressures. 

In KwaZulu-Natal, a vegetation type fragmentation index was used to develop a 

retention target. 

The use of retention targets means that the irreplaceability map reflects a 

combination of biological information (captured in the baseline target) and information 

about vulnerability to future transformation (captured in the retention target). 

Vulnerability is thus directly included in the irreplaceability map. This is one way to 

identify priority areas. However, if one does this, irreplaceability and vulnerability are 

no longer independent. It is more appropriate to consider vulnerability separately 

from irreplaceability. Vulnerability to future transformation should be taken into 

account in scheduling implementation of conservation action, not in determining 

conservation worthiness. Retention targets were thus not used in SKEP. Baseline 

targets should be all that is required. Naturally, this requires that one has a good 

means of developing baseline targets. 

Targets in SKEP 

In SKEP, a novel approach to setting baseline targets was developed, based on the 

original species-area relationship explored by ecologists in the 1960s and 70s. This 

seminal work partly provided the foundation for the currently accepted IUCN baseline 

conservation target of 10%. From examination of many species area accumulation 

curves a general observation was made – if you sample 10% of an area you sample 

approximately 50% of species represented. In species rich regions like the Succulent 

Karoo, characterised by high levels of beta and gamma diversity, this general rule 

needs to be adapted to accommodate the higher levels of biodiversity, as one would 

need to sample proportionately more area to observe the same given proportion of 

total species. The decision also needs to be made whether 50% of species is an 

adequate target. 

For SKEP phytosociological survey plots were used to explore the species-area 

relationship within vegetation types in the Succulent Karoo and then set targets 

based on the observed patterns of diversity. 

Targets were set for vegetation types and expert-identified areas. As the expertidentified 

areas are fundamentally a different type of biodiversity feature data, the 


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protocol for setting targets for vegetation types and expert areas differed. These are 

discussed under the methods section. Targets for expert-identified areas were 

included as these areas: 

• incorporate expert knowledge not captured in the vegetation map; 

• cover taxonomic groups besides plants; 

• are an alternative type of biodiversity surrogate. 

Targets for vegetation types 

For SKEP phytosociological survey plots were used to explore the species-area 

relationship within vegetation types in the Succulent Karoo. Sources of survey data 

are presented in Table 22 and the location of these survey sites is illustrated in 

Figure 21. 

Table 22: Sources of phytosociological survey data used in the SKEP project 

Project 

Code 

Source of Data 


Number 

of Plots 

5 Annelise le Roux surveys of Namaqualand 22 








14 Helga Rosch PhD Goegap Nature Reserve 284 

15 Ute Schmiedel PhD data on quartz patches in SA 1 593 

16 Philip Desmet MSc project on strandveld 118 

17 Philip Desmet species list from Kleinzee Nature Reserve 1 

18 Philip Desmet survey of DeBeers Buffels River Nuttabooi 

mining area 9 

19 Philip Desmet survey of DeBeers Buffels River Staanhoek 

mining area 6 

20 Domatilla Raimondo Honours project survey of Strandveld at 

Groen River mouth 19 

21 Philip Desmet assessment of the Strandveld at Strandfontein 3 

22 Philip Desmet assessment of Kookfontein for SANP/WWF 26 

23 Philip Desmet Gamsberg EIA 84 

24 Tania Anderson Gamsberg EIA 5 

25 Philip Desmet IDC Silicone Mine EIA Nuwerus 22 

26 Norbert Juergens Namaqualand phytosociological dataset 1 421 

27 Laco Mucina data from Bauer 14 

28 Laco Mucina data from Sue Milton 115 

29 Laco Mucina data from Francine Reubin 98 

30 Bruce Bayer data from Chris Stokes 1 494 

Total number of plots 5 491 

Total number of species occurrences 47 641 

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Figure 21: The location of survey points within the SKEP planning domain 

For vegetation types where more than 50 survey plots were located, species-area or 

accumulation curves were constructed. Naturally, these plots do not sample all of a 

vegetation types species and simply using the observed accumulation curve would 

result in an under estimate of area required to represent all species. To counter this 

problem simulated species-area curves that use a variety of statistical methods were 

simulated to estimate the true species accumulation curve for an area. The software 

package EstimateS developed by R. Colwell was used. 9 EstimateS computes 

randomized species accumulation curves, statistical estimators of true species 

richness (S), and a statistical estimator of the true number of species shared 

between pairs of samples, based on species-by-sample (or sample-by-species) 

incidence or abundance matrices. EstimateS is freely available from the website 

listed below. 

The resultant species accumulation curves for 17 SKEP vegetation types are 

presented in Figure 22. All six methods of computing species accumulation curves 

available in EstimateS were plotted and compared by standardizing the x- and yaxes. 

This allows one to compare the shapes of the estimated curves. A target of 

conserving at least 75% of species in any vegetation type was set, i.e. the horizontal 

solid red lines in Figure 22. The resultant area required to observe this proportion of 

species is obtained by dropping a vertical line from where this line intersects the 

curve down to the x-axis. The value on the x-axis is interpreted as being the 

percentage area required to conserve 75% of species. This visual approach provides 

9 Version 6.0b1, March 2001, Department of Ecology and Evolutionary Biology, University of Connecticut; Email: 

colwell@uconnvm.uconn.edu, Es timateS; Website: http://viceroy.eeb.uconn.edu/estimates 


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the same result if one were to fit a power curve to the estimated curves and then 

calculate the area required based on the proportion of total species targeted and the 

slope of the curve. 

Using targets higher than 90% would require that almost all area would be required 

to conserve species. This is a result of the high numbers of rare and range-restricted 

species that occur in the Succulent Karoo. A large proportion of the regional 

biodiversity is composed of species with very small distributions (Lombard et al. 

1999). For most vegetation types conserving 10% of the area, i.e. the IUCN target, 

conserves approximately 50% of species. There are two vertical red lines on each 

graph in Figure 22. This is because the six estimated curves vary in the manner in 

which they estimate the accumulation of species. The left and right-hand vertical 

lines specify a lower and upper baseline target respectively (Table 33). There are not 

sufficient phytosociological survey data to produce species-accumulation curves for 

all SKEP vegetation types. Vegetation types without data were grouped with a 

vegetation type for which there was data and given the same target. This grouping 

was based on expert interpretation of the higher-order phytosociological grouping of 

vegetation types. 

Figure 22: Species-accumulation curves for 17 SKEP vegetation types 

The horizontal red line is the target of the area required to capture at least 75% of species recorded in a 

vegetation type. Key to legend: (1) Sobs – the observed species accumulation curve; (2-6) estimated 

curves. 

Table 33 in Part D gives the results of the target-setting exercise using species 

accumulation curves. The actual target in hectares for each SKEP vegetation type is 

listed. 


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Using the species-area curve to derive conservation targets is discussed in more 

detail in Desmet and Cowling (in prep). 

Targets for expert-identified areas 

Different targets were set for different sized expert-identified areas using a sliding 

scale shown in Table 23. 

For areas less than 4 000 ha the target was 100%. Generally such areas are smaller 

than the average cadastral unit in the region, and conserving part of the area would 

be difficult and could compromise the integrity of the feature being targeted – e.g. a 

kloof (gorge) or perennial spring. For larger expert areas a lower target was set that 

incorporates two types of expected error, one related to capturing mapped data (data 

capture error) and one related to the nature of the mapping process (mapping error). 

The first type of error relates to capturing the data, i.e. digitising the polygons drawn 

by experts. For example, an 8 000 ha expert area might be a square measuring 8 by 

10 km. Expert areas were mapped on 1:250 000 scale topographical maps using a 

marker pen which draws a line 2 mm wide, making this line 500m wide on the 

ground. When the polygon is digitised, an error of approximately 500m can be 

expected. If the boundary was mapped accurately by the expert, i.e. if there was no 

mapping error, then the data capture error would amount to about 2 000 ha or 25% of 

the polygon area. Thus we could set a target of 75% in order to capture the entire 

area minus data capture errors. 

As expert polygons increase in size, the data capture error remains constant but 

decreases as a proportion of polygon size. However, the second type of error – 

mapping error – increases, as the boundaries of polygons drawn by experts are not 

necessarily accurate. Larger polygons become increasingly ellipsoid. This is really a 

function of experts extrapolating their knowledge in larger areas. In small areas it is 

easy to determine exact boundaries whereas in larger areas this task in more difficult 

as experts cannot conceivably visit every corner of the landscape. Mapping errors 

may translate into inaccuracies of several kilometres on the ground. 

Table 23: The scale used to set targets for expert-identified areas 

Target Size of expert-identified areas 

(% of area) 

(ha) 

100 128 001 

Table 34 in Part D gives the results of the target setting exercise for expert-identified 

areas using this scale. The actual target in hectares for each expert-identified area is 

listed. 


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Targets for spatial components of processes 

Spatial components of ecological and evolutionary processes require, by definition, a 

100% target – if part of the habitat in the spatial component is transformed, the whole 

ecological or evolutionary process is compromised. As explained in Section 15, the 

process layer was not incorporated into the C-Plan analysis for SKEP. This means 

that the 100% target set for spatial components of proceses is not reflected in the 

SKEP irreplaceability map – it remains an implicit target rather than an explicit one. 

Process features were used as thematic information layers in the prioritisation 

process, and processes must be seen as a crucial context layer in the absence of 

explicit process targets. 

Interpretation and limitations of species-accumulation targets 

Setting targets was limited by availability of phytosociological data. Despite the large 

number of survey plots (5 491 sites) in the dataset, only 17 vegetation types had 

sufficient plots to perform the analyses (i.e. >50 plots). In addition there were no 

phytosociological data for Namibia. 

Generally, however, all targets appear to be in the same range of values between 

15% and 50%. Differences in targets for vegetation types are not necessarily a 

function of overall species diversity, but the overall heterogeneity of the mapped 

vegetation type. Thus, vegetation types with very high targets should probably be 

mapped as two or more vegetation types. 

The species accumulation curves in Figure 22 support the IUCN 10% target, i.e. that 

10% of the area conserves 50% of the species. This broad relationship is upheld for 

almost all vegetation types analysed. The real debate is whether conserving 50% of 

species is sufficient. This common pattern suggests that in all vegetation types at 

least half the species present are common and occur throughout the vegetation type. 

The distribution patterns of the remainder of species differ. For vegetation types with 

low targets, there are few range-restricted species whereas for vegetation types with 

larger targets there are more such species that flatten the accumulation curve and 

push up the target. One must remember, however, that this pattern is combined with 

the differential heterogeneity of mapped vegetation types pattern mentioned above. 

Teasing the two apart will require further work. 

A precautionary note about baseline targets: The species accumulation curve is 

certainly a good approach to incorporating available survey data into setting 

adequate baseline targets for a vegetation type. However, this curve tells us nothing 

about where this biodiversity is located in the landscape. In a perfect world where the 

location of every species is known and where there are no constraints to protected 

area planning, a protected area network that conserves 75% of species in the area 

specified in the baseline target could be laid out. In reality such an optimal outcome 

can never be achieved. One may find that simply to achieve the species 

representation target, the baseline target plus an additional target is required to make 

up for inefficiency. This is partly why the precautionary principle was applied by using 

the upper target value in C-Plan rather than a mean between the upper and lower or 

the lower. 


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15. Identifying Geographic Priorities 

Sections 5 to 14 have dealt with each of the data layers and the other major pieces of 

information (such as conservation targets) needed for a systematic conservation 

plan. This section describes how these input layers and targets were analysed and 

interpreted to produce three successive products: 

• an irreplaceability map (or map of conservation options) for the SKEP planning 

domain; 

• a “framework for action” map for each of the SKEP sub-regions; 

• a map of nine geographic priority areas for conservation action in the Succulent 

Karoo. 

Each of these is discussed below. 

Irreplaceability map (conservation options) 

In Section 4, the term irreplaceability was introduced. Irreplaceability values are 

calculated for all planning units in the planning domain. The irreplaceability value of a 

planning unit indicates how important that planning unit is for achieving conservation 

targets. Planning units with a high irreplaceability value are essential for achieving 

conservation targets (i.e. if these sites are not included in the protected area system 

then it is unlikely or impossible that targets will be achieved). Low irreplaceability 

values mean that there is flexibility in terms of which sites can be chosen to achieve 

the target. An irreplaceability value of zero indicates that the targets for features 

included in that planning unit have already been achieved in the existing protected 

area network. 

A map of irreplaceability values is a map of conservation options: in areas of 

high irreplaceability, all or most of the extant habitat is required to achieve targets; in 

areas of low irreplaceability, there is greater flexibility in the array of available sites 

required to achieve conservation targets (Pressey 1999). 

Irreplaceability values for SKEP planning units were calculated based on a formula 

involving: 

• the target for each biodiversity feature, in hectares; 

• the extant (i.e. untransformed) area of each feature, in hectares; 

• the area of each feature already included in a Category 1 protected area, in 

hectares. 

Targets can only be met using untransformed areas. Areas already included in 

Category 1 protected areas are considered to have already contributed to meeting 

targets. 

Irreplaceability values based just on vegetation type targets were low on the whole, 

reflecting the generally low levels of irreversible transformation of habitat in the 

Succulent Karoo (as discussed in Section 11). If it had been possible to develop a 

spatial layer of overgrazing, and thus to take partial habitat transformation as a result 

of overgrazing into account, irreplaceabilility values based simply on vegetation 


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targets would have been more useful. As it was, they gave a misleading (overgenerous) 

picture of conservation options in the Succulent Karoo. 

Instead, irreplaceability was calculated based on the targets set for vegetation types 

and for expert-identified areas. Figure 23 shows the results. Clusters of high 

irreplaceability values occur around centres of biotic diversity (i.e. with many 

biodiversity features) and areas where there are relatively greater levels of habitat 

transformation, reflecting the combined use of targets for expert-identified areas and 

targets for vegetation types. 

This irreplaceability map, together with the map of spatial components of ecological 

processes and the map of vulnerability to future land-use pressures, was to develop 

the spatial products discussed below: the framework for action map and the nine 

geographic priority areas. 

Figure 23: Irreplaceability values in the SKEP planning domain, based on 

targets set for vegetation types and expert-identified areas 

Framework for action map 

As explained in Section 14, the targets set for biodiversity features in SKEP (whether 

vegetation types or expert-identified areas) related purely to biological 

characteristics. There was no attempt to capture in the targets any information 

related to land-use pressure or vulnerability to future habitat transformation. This 


Page 75

means that the irreplaceability map (Figure 23) does not contain any measure or 

indication of vulnerability. 

Priorities for conservation action should reflect a combination of irreplaceability and 

vulnerability to future habitat transformation. These two measures can be shown on a 

graph or matrix, as in Figure 24. On the whole, one can say that geographic areas 

falling in Quadrant 2 have the highest priority for conservation action, while 

geographic areas falling in Quadrant 4 have the lowest. It is less clear whether 

Quadrant 1 or 3 is of greater priority for conservation action. 

Irreplaceability 

1 2 

4 

High Irr 

Low Vuln 

Low Irr 

Low Vuln 

High Irr 

High Vuln 

Low Irr 

High Vuln 

Vulnerability 

Figure 24: An irreplaceability-vulnerabilty graph 

Figure 23 shows the final irreplaceability map for SKEP. Figure 17 in Section 11 

shows the final vulnerability map for SKEP (reflecting combined vulnerability to 

transformation from mining, crop agriculture, ostrich farming and urban 

development). 

It was important to find a way to represent these two maps – the irreplaceability map 

and the vulnerability map – as a single product, to give the equivalent information 

shown by an irreplaceability-vulnerability graph but in a spatial form. In addition, this 

product needed to be simple enough for a layperson to understand, so that it could 

be used as an input to discussions about priority conservation actions by local and 

regional stakeholders at sub-regional Action Planning Workshops (see Section 26). 

Participants at the second Biodiversity Component Workshop held in June 2002 were 

asked to advise on how best to do this (see Section 25). They gave excellent 

suggestions, which were incorporated into “framework for action” maps for each of 

the SKEP sub-regions following consultation with the SKEP Technical Working 

Group. 

Key features of the framework for action map include: 

• The term “conservation options” is used instead of “irreplaceability”; 

• Three categories of conservation options or irreplaceability are represented 

(rather than the usual ten): 


3 

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purple 10 indicates irreplaceability of between 0.75 and 1 – few or no options 

for meeting conservation targets, 

orange indicates irreplaceability of between 0.25 and 0.75 – several options 

for meeting conservation targets, 

green represents irreplaceability of between 0 and 0.25 – many options for 

meeting conservation targets; 

• Vulnerability to future land-use pressure is represented by shading: 

a dark shade indicates high vulnerability, 

a medium shade indicates medium vulnerability, 

a pale shade indicates low vulnerability, 

hatching indicates unknown vulnerability; 

• Spatial components of ecological and evolutionary processes are shown as a 

transparent overlay that should be used in conjunction with the framework for 

action map. 

The framework for action map thus summarises information on conservation options 

(irreplaceability) and vulnerability to future land-use pressure. A dark purple planning 

unit represents an area that falls in Quadrant 2 of the irreplaceability-vulnerability 

graph, while a light green planning unit represents an area that would fall in 

Quadrant 4 of the irreplaceability-vulnerability graph. 

A framework for action map and an overlay of ecological processes were produced 

for each sub-region. Figure 25 shows the framework for action poster for 

Namaqualand. Figure 26 shows the overlay of ecological processes for 

Namaqualand. The overlay was printed on tracing paper and laminated, and could be 

clipped over the framework for action poster (both produced at A0 size). Appendix 14 

in Part E contains A4 versions of the framework for action posters developed for 

each sub-region. 

10 Participants at the second Biodiversity Component Workshop advised that red is not a good colour to use to 

represent high irreplaceability values because it has negative connotations. 


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Figure 25: SKEP Framework for Action for Namaqualand 


Figure 26: Overlay of ecological processes for Namaqualand (to be used with the framework for action map) 


Nine geographic priority areas 

A complementary product, produced for the Biome-Wide Action Planning Workshop 

(see Section 26), shows nine broadly defined priority areas for conservation action 

across the biome, based on interpretation of the framework for action map. These 

are shown in Figure 27. Areas were delimited based on the aggregation of high 

irreplaceability planning units (few conservation options), medium to high land-use 

pressures experienced in the area, and the incorporation of spatial components of 

key ecological processes. Where the priority areas border one another the 

boundaries were defined on the basis of biotic discontinuities, e.g. fundamental 

differences between the biota of the sandy coastal plain compared to the granite 

Namaqualand uplands. 

Appendix 5 in Part E includes a description of each of the nine priority areas. Finer 

scale conservation planning within each of these priority areas could be undertaken 

as part of the implemetation phase of SKEP. 

Figure 27: Geographic priority areas for conservation in the Succulent Karoo 

biome 

These nine geographic priority areas are broadly congruent with priority areas for 

conservation identified for the Succulent Karoo by a previous study (Lombard et al. 

1999). 11 This study identified priorities using data on Red Data Book plant species at 

11 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(1-2): 35-55. 


the QDS scale. Lombard et al.’s (1999) analysis has several shortcomings as a 

stand-alone assessment: 

• The planning units (QDS) are too crude for effective delimitation of priority areas 

for implementation. 

• The assessment failed to identify the Sperrgebiet and the Roggeveld portion of 

the Bokkeveld-Hantam-Roggeveld priority areas, owing almost certainly to the 

false absence of records of many unique species in these under-collected areas. 

This confirms the value of SKEP’s approach of targeting vegetation types as 

surrogates for species, together with expert-identified areas. 

• The planning domain for this study did not include the Bushmanland Inselbergs 

priority region identified by SKEP. 

A further strength of the SKEP conservation plan was the involvement of a broad 

range of local and regional stakeholders in the planning process. This, together with 

the recent Critical Ecosystem Partnership Fund grant for the Succulent Karoo biome 

(see www.cepf.net), dramatically increases the likelihood that the planning outcomes 

will translate into conservation action on the ground. 


Part C: Organisational Process 

16. Why Write Up the Process? 

A technical report on a conservation planning project clearly needs to record the 

“hard science” of the conservation planning exercise – what data were used, how the 

analysis was performed, and so on. This was dealt with extensively in Part B. We felt 

it was also important to record and discuss how we did what we did, not just from a 

technical point of view but from the point of view of organising and running the project 

– the “soft stuff”. The soft stuff is not often reported on, yet it is often the key to a 

successful project, and is not self-evident. This is the topic of Part C. 

There are many different ways to undertake a conservation planning project. The 

SKEP planning phase was characterised by three interrelated features that 

influenced how the Biodiversity Component undertook its work: 

• Short timeframe 

Conservation planning projects at a similar spatial scale in southern Africa, such 

as CAPE and the Subtropical Thicket Ecosystem Plan (STEP), have been 

conducted over two years or more. The SKEP planning phase, in contrast, was 

an eight-month project. 12 

• Planning for implementation 

The SKEP team was committed to ensuring that the ecosystem planning exercise 

was not simply a desktop exercise which had to be sold, after the fact, to people 

and organisations living and working in the Succulent Karoo in order to be 

implemented. This required stakeholder involvement in the planning process, and 

at least some institutional continuity between the planning phase and the 

implementation phase. The network of sub-regional champions (see Section 17) 

was thus set up with a view not simply to facilitating stakeholder participation, but 

also with a view to: 

facilitating institutional continuity between the planning phase and the 

implementation phase; 

building capacity for implementation during the planning phase. 

The work of the Biodiversity Component needed to support these aims. 

• Focused stakeholder involvement 

As noted above, stakeholder involvement was crucial for building ownership of 

the planning process and its outcomes among people and organisations in the 

Succulent Karoo. The nature of stakeholder involvement in SKEP was 

deliberately focused. We did not aim for full public participation, but rather cast 

the stakeholder net more narrowly. For example, workshop invitations were 

generally not open but went to specific people. This targeted approach to 

stakeholder involvement characterised the work of the Biodiversity Component. 

Although it was partly imposed by time and budget constraints, we believe that 

this approach was ultimately more effective than a broad public participation 

approach. 

12 The planning phase of SKEP ran from January to August 2002 – an eight-month period. However, the final 

products of the Biodiversity Component had to be completed by the end of July 2002, to be used in Action Planning 

Workshops over the period 29 July to 18 August. The technical part of the conservation planning process was thus 

completed within seven months. 


The Biodiversity Component interacted with two main constituencies over the course 

of the project: 

• the scientific community, based both in academic institutions and in the 

conservation agencies in the region; 

• the sub-regional champion teams in the four SKEP sub-regions, and through 

them with further local and regional stakeholders. 

Through the course of various workshops and other project events, discussed in the 

sections that follow, we engaged with these two constituencies both separately and 

together. 

In reading this part of the report, please bear in mind that in a retrospective write-up 

of the SKEP project it is easy to give the impression that the progression of the 

project over the eight months was neat and predictable. In fact, at many points we 

were acutely aware that we were trying something new and ambitious, and that we 

were feeling our way through challenges and obstacles. Often these were heightened 

by the rapid pace of the project and the deadlines involved. Not only were we 

attempting to complete a biome-wide systematic conservation plan in record time, we 

were also doing it with unprecedented levels of direct stakeholder participation in the 

planning process, using a brand new organisational model of champion teams. 

Without a great deal of vision and commitment from the SKEP Co-ordinator, a strong 

central co-ordination team, and highly experienced conservation planners in the 

Biodiversity Team, this would not have been possible. 

Part C of the report is structured as follows: 

• Section 17 outlines the four SKEP components and discusses the relationship of 

the Biodiversity Component to the other components. 

• Section 18 explains how the Biodiversity Team was structured. 

• Section 19 discusses the role of the Biodiversity Advisory Group. 

• Section 20 deals with the first Biodiversity Component Workshop. 

• Section 21 discusses issues related to collection of biological data. 13 

• Section 22 discusses issues related to the collection of land-use data through the 

sub-regional champion network. 

• Section 23 reviews a focus group meeting held on spatial components of 

ecological processes. 

• Section 24 reviews a workshop held on conservation targets. 

• Section 25 deals with the second Biodiversity Component Workshop. 

• Section 26 discusses the role of the Biodiversity Team in the Action Planning 

Workshops that marked the end of the planning phase of the SKEP project. 

Sections 17 to 19 deal with project structures, while Sections 20 to 26 follow more or 

less the chronological order of project activities and milestones. 

13 Not including the expert mapping exercise, which is discussed in detail in Section 8 in Part A. 


17. SKEP Components and Structures 

As explained briefly in Section 1, SKEP was led by Conservation International. Sarah 

Frazee, Programme Director of Conservation International’s Southern Africa 

Hotspots Programme, played the role of SKEP Co-ordinator. The SKEP project was 

divided into four distinct but related components, dealing with: 

• biodiversity; 

• socio-political issues; 

• resource economics; 

• institutional issues. 

A Technical Working Group and a Co-ordination Team integrated the work of the four 

components. 

This section gives a brief overview of the four components and their relationships to 

each other, before we go into more detail on the structure and work of the 

Biodiversity Component. 

Figure 10, an organogram of SKEP structures, shows the different components and 

sub-regions. 

The Biodiversity Component of SKEP was undertaken by the Cape Conservation 

Unit of the Botanical Society of South Africa, in partnership with South Africa’s 

National Botanical Institute (NBI) and the Institute for Plant Conservation (IPC) at 

UCT, and advised by Richard Cowling of the Terrestrial Ecology Research Unit 

(TERU) at UPE. 

The partnership arrangement was based on the complementary expertise and 

resources of the organisations. The Botanical Society had experience in coordinating 

conservation planning projects, and wished to further this experience 

through involvement in a rapid biome-wide conservation plan. 14 The NBI was able to 

provide office space and other practical resources such as computer equipment, IT 

support and data at a reduced fee. Scientists based at the IPC provided specialist 

conservation planning expertise, and expertise on the Succulent Karoo biome. 

The composition of the Biodiversity Team is discussed in Section 18. 

The Socio-Political Component of SKEP was contracted to Eco-Africa, a sociallyminded 

environmental consulting firm. 15 The component was supervised by Francois 

Odendal (Director of Eco-Africa) and co-ordinated by Daphne Hartney (an Eco-Africa 

consultant). As mentioned in earlier sections, the SKEP planning domain was divided 

into four sub-regions: 16 

14 The Cape Conservation Unit of the Botanical Society works chiefly in the Greater Cape Floral Kingdom, including 

the fynbos and succulent karoo hotspots. The Cape Conservation Unit’s five-year strategic plan identifies four 

strategic directions for the unit’s work: conservation planning, implementation of conservation plans, policy and 

legislation, and advocacy and education. The SKEP project fitted clearly within the unit’s geographic and strategic 

focus. 

15 Eco-Africa is dedicated to the skilled management of Southern African habitats, the upliftment of rural areas along 

ecologically and financially sound lines, and the preservation and management of areas with endangered species. 

For more information visit www.ecoafrica.co.za. 

16 For more detail on how these sub-regions were decided on, see “The SKEP Planning Domain: Documentation of 

the Decision Process, March 2002” in Appendix 1 in Part E. 


Sub-region: 

Hantam-Tanqua 

Biodiversity Advisory Group 

TERU, NBI, NMET, WCNCB, NCNC, 

IPC, SANP 

Sub-region: 

Namibia-Gariep 

NCNC Sutherland 

Karas Regional SPP 

Asst 

Rep-more 

socioeconomic 

focus 

Planner 

Asst 

Asst 

NAM Parks 

MET 

Institutional 

Component 

Sub-region: 

Namaqualand 

Eco-Africa 

SANP 

Advises 

Figure 28: Organogram of SKEP structures 

• Namibia-Gariep; 

• Namaqualand; 

• Hantam-Tanqua-Roggeveld; 

• Southern Karoo. 

Biological 

Component 

BotSoc 

SKEP-TWG 

CI co-ord 

Advises 

Economic 

Component 

IPC 

The Socio-Political Component established a network of champions in the SKEP 

sub-regions. The champions were people based in the sub-regions, with full-time 

positions in existing organisations or institutions. Their contribution of time and 

energy to SKEP was voluntary. Each sub-region had two champions, one with a 

biodiversity background or focus, and one with a socio-economic background or 

focus. 17 SKEP funded a full-time assistant for each champion. Together, the 

champions and assistants formed champion teams in each of the sub-regions. Their 

tasks included: 

• Information gathering, for example on land-use and existing conservation 

initiatives in the relevant sub-region; 

• Informing local stakeholders in different sectors about SKEP; 

• Organising and running stakeholder workshops, to gather information and to 

communicate the outputs of SKEP, and to engage stakeholders in identifying 

conservation priorities; 

• Writing sub-regional reports; 

• Publicising the Succulent Karoo and SKEP. 

17 The Southern Karoo sub-region was an exception, with only one champion. 

Socio- 

Political 

Component 

Eco-Africa 

Socio- 

Political 

Advisory 

Group 

Sub-region: 

Southern Karoo 

WCNCB Agriculture 

Asst 

Asst 

Asst Asst 


Building the capacity of the individuals involved to continue to contribute to 

conservation in the Succulent Karoo beyond the planning phase of SKEP was a 

focus of the work of the Socio-Political component. 

The Resource Economics Component of SKEP was undertaken by the IPC. 18 It 

was supervised by Timm Hoffman (Director of the IPC), and co-ordinated by Ivor 

James. The component took the form of a case study of one of the SKEP subregions, 

Namaqualand. It was based on an existing IPC project that aimed to assess 

and model the major land-use practices in Namaqualand, and to test a methdology 

for building an ecological-economic model of Namaqualand that could be used as a 

land-use decision-making tool. The private agriculture, communal agriculture, mining, 

conservation and tourism sectors were examined. Members of the Biodiversity Team 

participated in a ten-day workshop in Kamieskoon in April 2002, at which part of the 

modelling exercise was undertaken. Although the model developed was quantitative, 

it was not spatially explicit. It was thus not possible to link the outputs of the 

economic model directly to the spatial outputs from C-Plan. 

The Institutional Component of SKEP was not contracted to a specific 

organisation, but both the NBI’s Bioregional Policy and Planning Directorate and the 

Ministry of Environment and Tourism in Namibia guided the SKEP team to focus 

throughout the project on institutional arrangements needed to ensure the longerterm 

life of SKEP. This included: 

• establishing and building the capacity of the champion teams; 

• building relationships between Namibian and South African organisations 

working in the Succulent Karoo; 

• appointing a SKEP co-ordinator who would be able to take the project into its 

next phase after the approval of a CEPF grant for the Succulent Karoo (see 

Section 1). 

A Technical Working Group, chaired by Sarah Frazee of Conservation 

International, oversaw the SKEP project and ensured that the work of the four 

components was integrated. Members of the Technical Working Group included the 

Supervisors and Co-ordinators of each of the Components, the sub-regional 

champions, and the two special advisors to the SKEP project, Richard Cowling and 

Amanda Younge. The Technical Working Group met four times over the course of 

the project. 

In addition to the Technical Working Group, a smaller Co-ordination Team, 

consisting of Sarah Frazee and the co-ordinators of the Biodiversity, Socio-Political 

and Economics Components, met more regularly (usually once a week). 

For more detailed information about the Socio-Political, Resource Economics and 

Institutional Components of SKEP, see the SKEP First Phase Report and other 

SKEP resouces available at the SKEP kiosk at www.dlist.org. 

18 The Institute for Plant Conservation was established in 1992 as a result of a generous donation to the University of 

Cape Town by Mr Leslie Hill. The institute undertakes research, extension and post-graduate teaching directed at 

improving the conservation status of the Cape Floristic Region. For more information visit www.uct.ac.za/depts/ipc. 


Relationship of the Biodiversity Component to other components of 

SKEP 

The Biodiversity Component interacted with the other components of SKEP both 

formally and informally. 

Formal interaction took place through the Technical Working Group and the Coordination 

Team. The Technical Working Group provided a good forum for taking 

stock of the SKEP project as a whole, and for contact between members of the 

Biodiversity Team and all the champion teams. 

The smaller Co-ordination Team provided for vital communication on day-to-day 

management and co-ordination issues. In addition to formal weekly or fortnightly 

meetings, there was regular phone and email contact between the Biodiversity Coordinator, 

the Socio-Political Co-ordinator and the SKEP Co-ordinator. Strong 

working relationships between these three people in particular were essential to the 

success of the SKEP project. 

Timeline for the SKEP project 

Figure 29 shows a timeline for the planning phase of the SKEP project. The work of 

the Biodiversity Team occurred chiefly over the period January to August 2002, 

shaded in grey. The main activities of the Biodiversity Component’s work in this 

period are reflected. 


Prep 

Planning 

Write-up & final 

products 

Move into 

implemen 

tation 

Month Main Activity Key Meetings 

Sep 01 Calitzdorp discussion meeting 

… 

Dec 01 

Jan 02 

Feb 02 

Data gathering 

TWG 1 

Biod Comp Workshop 1 

Mar 02 

Apr 02 

Data analysis 

TWG 2 

BAG 1 

May 02 TWG 3 

BAG 2 

Jun 02 

Biod Comp Workshop 2 

BAG 3 

Jul 02 

Interpretation of results & 

products for action 

Aug 02 

Sep 02 

planning Action Planning Workshops 

TWG 4 

Oct 02 

Nov 02 

Dec 02 

Jan 03 

onwards 

Figure 29: Timeline for the planning phase of SKEP, showing the work of the 

Biodiversity Component 


18. Biodiversity Team 

This section discusses the structure and functioning of the team that undertook the 

Biodiversity Component of SKEP. The five-person Biodiversity Team consisted of: 

• Kristal Maze (Supervisor, Botanical Society); 

• Mandy Driver (Co-ordinator, Botanical Society); 

• Philip Desmet (Conservation Planning Specialist, IPC); 

• Mathieu Rouget (Conservation Planning Specialist, IPC); 

• Glynnis Barodien (GIS Technician, Botanical Society). 

Kristal Maze (MSc), Manager of the Cape Conservation Unit of the Botanical Society, 

spent approximately 15% of her time on SKEP over the period January to September 

2002. Kristal brought to the team experience in co-ordinating conservation planning 

projects at different spatial scales, contacts with networks of specialists, as well as 

general project management experience. Kristal, together with Philip and Mathieu, 

was involved in project planning and recruitment during November and December 

2001. 

Mandy Driver (MA, MBA) was appointed on a full-time contract to co-ordinate the 

Biodiversity Component of SKEP. Although she had no previous background in 

conservation planning, she brought project management and regional economic 

development expertise to the team. 

Philip Desmet (MSc), a PhD student at the IPC, spent approximately 180 days on 

SKEP over the period January to September 2002. Philip’s extensive knowledge of 

the Succulent Karoo, contacts with networks of specialists, as well as his expertise in 

conservation planning and C-Plan were crucial to the success of SKEP. 

Mathieu Rouget (PhD), a post-doctoral fellow at the IPC, spent approximately 90 

days on SKEP over the period January to September 2002. Mathieu’s experience 

with dealing with land-use and transformation in conservation planning as well as his 

general expertise in conservation planning and C-Plan were crucial to the success of 

SKEP. 

Glynnis Barodien (MSc) was appointed on a full-time contract to the SKEP 

Biodiversity Component for the duration of the project. She brought approximately 

three years of experience in GIS consulting work to the team. Although she was new 

to conservation planning, she had worked on a range of GIS projects in different 

contexts. 

Professor Richard Cowling of the Terrestrial Ecology Research Unit at the University 

of Port Elizabeth was an overall advisor to the SKEP project. Members of the 

Biodiversity Team interacted with him frequently over the course of the project in 

relation to strategic decisions about the direction of the team’s work. 

In addition to the core team, we involved postgraduate students at the IPC in the 

work of the Biodiversity Component. We outsourced GIS work to Benis Egoh (an 

intern) and Zuziwe Jonas (a Masters student). We were able to offer Zuziwe a oneyear 

bursary towards her Masters degree which deals with land-use patterns in the 

Succulent Karoo biome. 


Penny Waterkeyn, a freelance designer, provided invaluable assistance with the 

production of posters and other products for Action Planning Workshops, working 

closely with Mandy and Glynnis. 

The Biodiversity Team worked effectively. Reasons for this related both to the 

structure and to the functioning of the team. In terms of the team’s functioning, 

strengths included: 

• clear workplan and project milestones, established at the outset; 

• regular team meetings (every week or fortnight during most of the project); 

• regular reviews of the workplan, and an adaptive management approach; 

• thorough preparation by the whole team for workshops and presentations; 

• strong working relationship between the co-ordinator and supervisor; 

• exceptionally strong conservation planning and C-Plan expertise; 

• exceptionally committed conservation planning scientists who remained calm 

under pressure; 

• two team field trips (linked to workshops) to familiarise the team with the biome – 

these provided team-building opportunities; 

• good relationships between team members (partly explained by the above points, 

and partly just good luck!); 

Weaknesses and difficulties in the team’s functioning included: 

• Although all the team members were based in Cape Town, the conservation 

planners were not co-located with the GIS technician, resulting in lack of clarity 

on the day-to-day management of the GIS technician. The GIS technician was 

physically based at the Botanical Society, which made day-to-day management 

of her work by the conservation planning scientists based at the IPC impractical. 

• Underestimation of the amount of mapmaking involved in the project. Mapmaking 

was undertaken by the GIS technician, but did not play to her skills or utilise them 

effectively. A specialised mapmaker may be a useful person to contract in to a 

project such as this. The co-ordinator would need to have direct access to such a 

person. 

• Limited in-house data. 

Overall we felt that the team structure was effective. To do a successful conservation 

plan, one does not need in-house C-Plan expertise – it makes sense to contract this 

out to independent specialist consultants. However, we would recommend an inhouse 

full-time co-ordinator. Depending on this person’s experience with 

conservation planning projects, a supervisor or mentor can play a crucial role (over 

and above the role of an Advisory Group, which is more distant and not accessible 

on a daily or weekly basis). A GIS technician with relatively high-level GIS skills is 

important. Especially in a rapid conservation planning project, there is no time to train 

someone with low-level GIS skills. This person could be based in the same 

organisation as the co-ordinator or could work more directly with the conservation 

planning scientists. If the GIS technician is not physically co-located with the 

conservation planning scientists, responsibilities for day-to-day management of the 

technician need to be clearly and explicitly worked out. In addition, as we have noted 

above, mapmaking skills are required. However, a full-time mapmaker is not justified 

– it is not obvious how such skills should most effectively be brought into the project. 

The total budget for the Biodiversity Component of SKEP, including all workshops 

and the production of final products after August 2002, was approximately R650 000. 

Figure 30 shows a summarised breakdown of how this was spent. 


9% 

9% 

5% 6% 

37% 

34% 

Personnel: specialists & GIS 

Personnel: co-ordination 

Workshops 

Admin & running 

Travel & accom 

Data & software 

Figure 30: Summarised breakdown of the Biodiversity Component budget 


19. Biodiversity Advisory Group 

An Advisory Group was established to guide the work of the Biodiversity Component. 

Members included people in key conservation implementing agencies and people 

with expertise in systematic conservation planning and/or knowledge of the 

Succulent Karoo biome. They are listed in Table 24. This section outlines the role of 

the Biodiversity Advisory Group and assesses its effectiveness. 

Table 24: Biodiversity Advisory Group members 

Member Organisation 

Ernst Baard Western Cape Nature Conservation Board 

Phoebe Barnard Ministry of Environment and Tourism, Namibia 

Hugo Bezuidenhout South African National Parks 

Antje Burke EnviroScience, Namibia 

Richard Cowling Terrestrial Ecology Research Unit, UPE 

Helen de Klerk Western Cape Nature Conservation Board 

Sarah Frazee Conservation International 

Timm Hoffmann Institute for Plant Conservation, UCT 

Patrick Lane Ministry of Environment and Tourism, Namibia 

Annelise Le Roux Western Cape Nature Conservation Board 

Guy Midgley National Botanical Institute 

Sue Milton Stellenbosch University 

Helga Rosch Northern Cape Nature Conservation Services 

Mike Rutherford National Botanical Institute 

Colleen Seymour Conservation Planning Unit, Western Cape 

Nature Conservation Board 

Gideon Smith National Botanical Institute 

Jan Vlok Consultant 

Amanda Younge Consultant 

Advisory Group members were requested to: 

• attend three Advisory Group meetings over the course of the project; 

• attend two SKEP Biodiversity Component Workshops (see Sections 20 and 25); 

• comment on selected SKEP products in draft form (different members had 

expertise relating to different products); 

• provide input on the perspective of the institution they represent with regard to 

the progress and implications of the SKEP project; 

• promote awareness of SKEP within and beyond their institutions. 

The Advisory Group met three times over the course of the project, and played a 

significant role in reaching and endorsing decisions. Discussion at the first Advisory 

Group meeting, held on 19 March 2002, focused on decisions and progress with 

respect to data collection. At the second Advisory Group meeting, on 20 May 2002, 

we presented draft data layers for discussion. The third Advisory Group meeting, on 

26 June 2002, took place the day after the second Biodiversity Component 

Workshop. The workshop had raised many issues relating to data analysis, and the 

Advisory Group meeting provided a useful opportunity to discuss these further. 

Appendix 6 in Part E contains agendas and minutes of Advisory Group meetings. 


Although attendance at Advisory Group meetings was generally limited, these 

meetings were valuable to the Biodiversity Team for several reasons: 

• setting the dates of the meetings early on helped to provide clear deadlines to 

work towards; 

• having to report to the Advisory Group helped us to consolidate and document 

our progress; 

• the meetings provided a valuable forum for reflection and discussion – this was 

particularly important in a project that was moving at such a rapid pace; 

• members of the Advisory Group helped facilitate access to some datasets; 

• the meetings provided an opportunity to keep key stakeholders abreast of SKEP 

progress. 


20. Biodiversity Component Workshop 1 

On 22 January 2002, we held the first SKEP Biodiversity Component Workshop. The 

purpose of the workshop was to introduce SKEP to the scientific community and to 

identify possible sources of data for the systematic conservation planning exercise. 

This section explains what we did at the workshop and assesses its effectiveness. 

The workshop invitation explained that, “A workshop is being organised to identify the 

types and sources of biodiversity and land-use information that will be used in this 

project. This invitation has been sent to all organisations that have an interest in the 

biodiversity of the Succulent Karoo, specifically those which can contribute to the 

development of either the biodiversity information and/or the land-use information 

and which can potentially contribute data for the development of these information 

layers. Please could you forward this invite to the most appropriate person/s from 

your organisation.” A limited budget was available to assist people from out of town 

to get to the workshop. 

Approximately 40 people attended the workshop. There was strong attendance by 

biological scientists from conservation agencies and academic institutions. 

Attendance from social scientists, whose inputs were sought on land-use data, was 

more limited – more about this later in the section. 

Preparation for the workshop was substantial, and involved the whole Biodiversity 

Team. It included developing a SKEP Biodiversity Data Form for participants to fill in, 

and instructions and other material for small group work. 

Follow-up phone calls were made to people whose attendance we felt was important 

but who had not responded to the invitation. Those who expressed interest in 

contributing but were unable to attend, received an electronic version of the data 

form to fill in and return to us. 

At the workshop we introduced SKEP and systematic conservation planning, and 

explained the nature of data required. We then asked participants to work in small 

groups to identify and record possible sources of data. Groups were organised 

around major categories of data, and participants allocated themselves to groups 

according to their area of expertise or interest. 

All datasets identified by workshop participants were captured in a database by the 

SKEP GIS Technician. This database provided a valuable tool for the data gathering 

effort over the next several months (see Section 21). The resulting data directory is 

one of the products of the SKEP Biodiversity Component. 

The workshop was a success from the point of view of the Biodiversity Team: 

• It provided a team-building opportunity for us – preparing for and running the 

workshop was our first major team undertaking. 

• It provided a good introduction to SKEP and to systematic conservation planning 

for a relatively large group of people, including people in conservation 

implementing agencies. 

• Participation in the workshop was characterised by enthusiasm and a spirit of 

collaboration. Our assessment is that one-on-one interactions with people to get 

information about available datasets, in addition to being more time consuming, 


would not have been as effective. The workshop generated a sense of purpose 

around contributing data to the SKEP project. 

• In addition to being useful for us, the workshop provided an unusual opportunity 

for scientists to work together in groups and share information with each other 

about datasets. 

• The workshop revealed that there was lack of clarity on data needed to delineate 

spatial components of ecological processes in the Succulent Karoo, which 

prompted us to organise a specific focus group discussion on this issue (see 

Section 23). 

• We provided an excellent lunch that was much appreciated by participants, who 

had contributed their time so willingly. 

In retrospect, the main weakness of the workshop related to the relative lack of focus 

on land-use data. If we were to run the workshop again we would: 

• Make more effort to ensure that social scientists with knowledge of land-use 

patterns and information in the Succulent Karoo were invited and attended. (The 

relative focus on biological scientists was partly a reflection of the networks of 

members of the Biodiversity Team, so this would have involved substantial extra 

work to identify the right people.) 

• Run parallel small group sessions on biological and land-use data (rather than a 

set of small groups in the morning on biological data and another set of small 

groups in the afternoon on land-use data). 

The discussion we needed to have about land-use data at this early stage of the 

project was not simply about “who has the data we need”, but rather about: 

• which land-use patterns and trends in the Succulent Karoo are the most 

important ones to identify for a broad-scale conservation planning project; 

• how can these be pinned down spatially in a useful and feasible way, given time 

and data constraints? 

Appendix 7 in Part E contains the workshop invitation, the agenda, the data forms 

and instructions for small group work, the workshop minutes, and a list of 

participants. 


21. Acquisition of Biological Data 

The next major step in the work of the Biodiversity Team was to gather the spatial 

datasets that would underpin the systematic conservation planning exercise. These 

included: 

• satellite images; 

• digital elevation models; 

• vegetation map; 

• data on spatial components of ecological processes; 

• data on land-use and habitat transformation; 

• data on protected areas; 

• plot and releve data to develop species-area curve targets. 

In addition, species distribution data were collected in order to produce global 

species lists and endemicity rankings for the Succulent Karoo biome. 

One important challenge was that data would be useful only if we could acquire them 

at more or less the same scale for the whole planning domain, so we had to get 

equivalent data for Namibia and South Africa. A visit to Namibia by the Biodiversity 

Co-ordinator early in the project was useful. The staff of the Namibian Atlas Project, 

based in the Ministry of Environment and Tourism in Windhoek, were especially 

helpful. They provided a CD with many of the basic data layers required for the 

Namibian part of the planning domain. 

Another challenge was that we had a limited budget for acquiring data. This meant 

that we could not throw money at the problem in the event of problems accessing 

data, but rather had to come up with creative solutions. In some cases we managed 

to negotiate reduced prices for data. 

Lastly, issues of confidentiality of data were important. We developed a SKEP data 

agreement, assuring data owners that their data would be used only for SKEP and 

would not be available to anyone beyond the project team. See Appendix 9 in Part E 

for a copy of the data agreement. 

The sourcing of data for the digital elevation model, the vegetation map, the 

protected area layer and spatial components of processes was dealt with in Part B. 

Section 22 discusses the collection of land-use data in detail. The comments below 

refer particularly (but not only) to the collection of plot data and species distribution 

data, both of which came from multiple sources (see Table 5 in Section 8 and Table 

22 in Section 14). See Appendix 10 for a data dictionary reflecting all data obtained. 

Initially we had planned an ambitious method to derive a biodiversity features layer, 

rather than using the new SA veg map. This had to be reviewed when there were 

hiccups getting some of the necessary data inputs. Plot data and species distribution 

data would have been some of the inputs for modelling a biodiversity feature layer. In 

the end, plot data were used only to develop species-area curve targets, and species 

distribution data were used only to develop global species lists. 

For species distribution data we developed a data request and a data extraction 

tutorial, which clearly expressed our requirements. This was important if the data 

were to be useful for producing global lists and endemicity rankings. It was also 


important that data were extracted in a standard format, to avoid large amounts of 

time being spent cleaning and interpreting data we received. See Appendix 9 in Part 

E for a copy of the data request and the data extraction tutorial. 

A note about species distribution data: Even though these data do not form an 

integral part of the systematic conservation planing exercise, gathering this sort of 

data is worthwhile as it provides a basis for understanding the biodiversity of the 

system – without these data we would have very little idea of what biodiversity is out 

there. It also gives many researches an opportunity to contribute to the conservation 

planning process and provides a sound rationale to motivate for the acquisition of 

funds to manintain, update and add to these databases. 

Issues that arose in the data collection process included the following: 

• Some data owners were only too happy to provide their data and to see the data 

being used. Others were reluctant. Reasons for reluctance included: 

Unwillingness to release data that are not perfect; 

Fear that data would end up being distributed more widely than the SKEP 

project in spite of assurances to the contrary. 

• Some data owners were happy to contribute their data for free. Others required 

payment. There was not always a correlation between quality of data and size of 

payment expected. 

• In some cases there was an unrealistic expectation that SKEP had resouces to 

contibute to capturing and/or cleaning and/or collecting more data. 

• Significant effort was invested in building relationships and developing trust with 

data owners. In some cases this required substantial patience and repeated 

discussions. 

The main lesson learned in the process was that acquiring datasets can be time 

consuming and costly. It is important to plan for this. Often it is difficult to predict 

exactly where and with whom the obstacles and delays will occur, so one needs an 

adaptive management approach. A team with significant conservation planning 

experience is needed to come up with creative “Plan B” solutions. 


22. Land-Use Data Acquisition through Sub-Regional 

Champions 

Early on in the SKEP project we recognised that we had an opportunity to experiment 

with a new method of collecting data on land-use, both current and expected. As 

explained in Section 11, we had land-use data from the National Land Cover but 

wanted to supplement it. The Biodiversity Team worked with the overall SKEP Coordinator 

and the Co-ordinator of the Socio-Political Component to develop a 

methodology for involving local and regional stakeholders in mapping current and 

expected land-use. This section explains and assesses the methodology. 

Stakeholder mapping methodology 

We identified five major land-use (or potential land-use) categories in the Succulent 

Karoo for which we wanted to collect additional data: 

• agriculture; 

• mining; 

• tourism; 

• communal areas; 

• conservation. 

For each SKEP sub-region, we produced a set of tracing paper overlays for 

1:250 000 map sheets. The tracing paper overlays showed selected categories of 

NLC information (cultivated crops, mines and quarries, urban areas, degraded areas 

and waterbodies, as explained in Section 11). The overlays also showed the SKEP 

planning domain, with areas outside the relevant sub-region greyed out. 

We decided that each land-use category should be mapped on a separate overlay (to 

prevent confusion and messy results that would be difficult to digitise), and that 

current and future land use should be mapped on separate overlays. More than 250 

overlays were needed altogether. The physical task of producing these overlays was 

enormous. 

For each land-use catgory we asked stakeholders to add to or change the existing 

NLC data. For each polygon, line or point added to the NLC data, a data form 

needed to be filled in by the stakeholder. (Initially we thought we could use a table on 

one sheet of paper to list all the polygons on a given tracing paper overlay but this 

would have been unworkable, because of the numbers of people involved in the 

mapping exercise and because it would have been too squashed.) Keeping track of 

the data forms, and making sure correct labelling was used so we could link them to 

the correct map afterwards, was important. 

A different data form was developed for each sector, and for current and future landuse, 

so there were ten different data forms altogether. Appendix 11 in Part E contains 

examples of all the data forms. We hoped to use the data forms to gather further 

information about the land-uses represented in the NLC data (for example, 

information about what type of crop agriculture or what type of mining occurred in a 

particular area, or about the numbers of people employed in a mine or numbers of 

visitors to a tourist facility). 


At least one member of the Biodiversity Team attended each of the sub-regional 

information gathering workshops held in February and March 2002. Stakeholders at 

these workshops were asked to work in groups to map what they knew about landuse 

in the relevant sub-region. Champion teams were coached in the mapping 

methodology (for example, the need to draw neat lines and closed polygons, and to 

fill in a data form for every line/polygon). We developed a short mapping 

methodology document for the champion teams, included in Appendix 11 in Part E. 

Champion teams also did follow-up work in some cases to get additional 

stakeholders to add to the maps after the information gathering workshops. 

Once the stakeholder mapping exercise was completed, spatial data from the tracing 

paper overlays were digitised, the data forms were captured, and the data were 

cleaned and linked. This was a massive task, which took approximately 70 person 

days. Over 170 overlays were returned, and over 1300 polygons were digitised from 

these overlays. Appendix 11 in Part E includes a more detailed report on this process 

(Benis Egoh & Mathieu Rouget, “SKEP Champion Data: Compiling Land-Use 

Information from Local Knowledge”, October 2002). 

As explained in Section 11, the quality of the data collected varied greatly across the 

planning domain, and was in many cases weak from a scientific point of view. This 

meant that it was of limited value for the systematic conservation planning exercise. 

Assessment of the stakeholder mapping exercise 

The stakeholder mapping exercise generated a sense of involvement in the 

conservation planning process by many stakeholders across the planning domain, 

and was valuable from this point of view. 

However, the exercise absorbed an enormous amount of time, both of the champion 

teams and of the Biodiversity Team. The effort put in exceeded the ultimate 

usefulness of the data obtained. There may be other less time consuming and costly 

ways of achieving the sense of involvement generated by the exercise. 

The stakeholder mapping exercise required intense involvement from both the 

Biodiversity Component and the Socio-Political Component of SKEP. In retrospect, 

we can see that the needs and expectations of the two components differed in 

relation to the mapping exercise. Also, the division of roles and responsibilities 

between the two components was not always clear in relation to the mapping 

exercise, partly because we were figuring out the nature of the task as we went, and 

partly because the extent of the task was not fully appreciated at the outset. 

Stakeholder mapping should be approached with caution. If it is attempted, important 

lessons that emerged from the SKEP process include: 

• Expectations about the type of data that it is possible to collect need to be 

realistic, and the ultimate uses of the data need to be clearly established at the 

outset. 

• Working one-on-one with an identified individual (or a small group of people) with 

expert on-the-ground knowledge, results in much better data than mapping in a 

big stakeholder workshop. (This happened in one sub-region and resulted in 

much higher quality data.) 

• Intense supervision of the entire mapping process is required by a member of the 

technical team. 


• One person needs to take overall responsibility for co-ordinating the process from 

start to finish. 

As discussed in Section 8, the expert mapping exercise which we undertook to 

develop a layer of expert-identified areas of species richness and endemism in the 

SKEP planning domain, was highly successful. The basic methodology was the 

same as the methodology used for the stakeholder mapping exercise described 

above (and indeed was based on it). However, key differences were the numbers of 

mappers involved at one time, the level of expertise of the mappers, and the fact that 

most of the mappers understood the nature of a GIS and the resultant requirements 

of the data they were providing (for example, in terms of accuracy and 

completeness). 


23. Focus Group on Ecological Processes 

At the first Biodiversity Component Workshop on 22 January 2002 (see Section 20) 

the lack of clarity on spatial components of ecological processes in the Succulent 

Karoo became apparent. The small group dealing with this issue had valuable 

discussion, but did not get further than identifying a tentative list of processes, and in 

many cases was unable to identify spatial components of those processes or 

datasets that would be required to delineate them. The Biodiversity Team undertook 

to organise a follow-up workshop, involving a more focused group of people with 

specific expertise in this area, to take the discussion further. 

The aim of the focus group discussion, held on 4 April 2002, was to decide which 

spatial components of which ecological and evolutionary processes to use to develop 

the process layer for SKEP. We held the half-day discussion in Port Elizabeth, 

following directly on from a STEP workshop that fortuitously involved many of the 

same people. 19 

We used the spatial components of ecological processes identified in a previous 

study of the Succulent Karoo (Cowling et al. 1999a) as a starting point, together with 

those identified at the first Biodiversity Component Workshop. Guy Midgley of the 

National Botanical Institute did a presentation on climate change, which is one of the 

major ecological processes impacting on the Succulent Karoo. For a record of the 

discussion, please see Appendix 12 in Part E. For a list of the spatial components of 

ecological processes that were finally used in SKEP, see Section 8. 

The focus group on discussion on ecological processes was useful for two main 

reasons: 

• As noted in Section 8, the incorporation of ecological processes into conservation 

planning is relatively new. The focus group discussion thus provided a valuable 

opportunity to think through some of the complex issues involved in identifying 

broad-scale ecological processes and in mapping spatial components of these, 

not just for the SKEP Biodiversity Team but also for the other participants. 

• The discussion generated new ideas and insights, and contributed directly to the 

development of the process layer for SKEP, confirming that a small, focused 

group of people was the right forum for holding this discussion. 

19 An added benefit was that members of the Biodiversity Team were able to attend the STEP workshop, which 

turned out to be a valuable learning experience. It exposed us to the detail of another biome-wide conservation 

planning project that was dealing with some similar conceptual issues, although within a very different project 

structure. 


24. Targets Workshop 

As explained in Section 14, different conservation planning projects have set 

conservation targets using different methods. We identified the need for a workshop 

to discuss and decide on the most appropriate method for SKEP. 

The targets workshop was held in Cape St Francis on 3-4 June 2002. It involved a 

small, focused group of people with direct experience in the technical aspects of 

systematic conservation planning projects, and included people working on 

concurrent projects that were facing similar decisions (such as STEP). 

The history of target setting was presented, and new approaches were discussed 

and evaluated. The workshop was informal, and discussion was wide-ranging – not 

limited simply to target setting in SKEP. For example, we used the opportunity to 

review different project approaches. 20 We did not capture a formal record of the 

proceedings. 

The main decision made in relation to SKEP was to use species accumulation curves 

to set targets for vegetation types. This was explained in much more detail in 

Section 14. 

At the time the workshop was held, the SKEP expert mapping exercise was in 

progress, and the expert mapping results had not been captured. At that stage, we 

imagined that the expert-identified areas would provide purely a context layer. Later, 

we explored the idea of setting targets for expert-identified areas, and made the 

decision to do so. Although we were able to discuss this with the Biodiversity 

Advisory Group, it would have been valuable to have the discussion at the targets 

workshop as well. 

20 We were struck at this workshop by the value of the opportunity for conservation planners working on different 

projects to meet and reflect on technical and other project issues. Partly as a result of this, the Botanical Society 

subsequently hosted an extremely valuable workshop on “Lessons Learned in Conservation Planning in South 

Africa” in November 2002. The idea of the Lessons Learned workshop came out of this targets workshop. 


25. Biodiversity Component Workshop 2 

The first Biodiversity Component Workshop, held in January 2002, focused on data 

requirements and availability for the SKEP project (see Section 20). The second 

Biodiversity Component Workshop was held several months later, on 24-25 June 

2002. Its purpose was to report back on the development of data layers for SKEP, to 

present our approach to target setting, and to discuss the format of spatial products 

for Action Planning Workshops. 

Invitations went to all those who attended the first workshop, as well as additional 

people. A limited budget was available to assist participants from out of town to get to 

the workshop. About 60 people attended the workshop, including champions and 

assistants, people from conservation implementing agencies, academics, and people 

from NGOs active in the SKEP region. The audience included a mixture of people 

with knowledge of the Succulent Karoo but little knowledge of conservation planning, 

people with quite high-level knowledge of the science of conservation planning. 

Addressing this mixed audience was challenging. 

The first day of the workshop focused on presenting and discussing the data layers 

developed for SKEP (including the planning domain, planning units, vegetation map, 

spatial components of processes, habitat transformation and future land-use 

pressures). The second day focused on presenting and discussing conservation 

targets and an initial irreplaceability map. We then asked participants for input on the 

most useful way to present the final spatial outputs to stakeholders at the upcoming 

sub-regional Action Planning Workshops in July and August 2002. 

The workshop was highly interactive. In particular, participants gave valuable input 

on the draft layers dealing with future land-use pressures. These were some of the 

most challenging data layers to derive because of the lack of suitable spatial data. 

We had divided future land-use pressure into four categories: 

• urban development; 

• mining; 

• crop suitability; 

• grazing sensitivity. 

Discussion on the draft mining, crop suitability and grazing sensitivity layers that we 

presented was heated, and many useful suggestions were made. On the evening of 

Day 1, the Biodiversity Team and Richard Cowling had further discussions and came 

up with a new proposed method for developing these layers, which we presented to 

the workshop on the morning of Day 2, and which formed the basis for the layers as 

they were eventually compiled (see Section 11). 

A major breakthrough that was made as a result of discussions at this workshop was 

to distinguish between ostrich farming and sheep and goat grazing. We had been 

trying to deal with all grazing, including ostrich, sheep and goat grazing, in the same 

spatial layer. It became clear that this was not useful or appropriate. “Ostrich grazing” 

is actually a euphemism – ostriches are mainly farmed in pens, at densities that 

irreversibly transform the areas of land involved, with no possibility of recovery of the 

vegetation. In contrast, even severe overgrazing by sheep or goats leaves the 

possibility of recovery of the vegetation if grazing ceases. 


It also became clear at this workshop that to predict future grazing pressure by sheep 

and goats in a spatially explicit way was not a feasible undertaking, so overgrazing 

was removed from the future land-use pressure layer. (We had already decided not 

to map existing overgrazed areas for the SKEP project.) Ostrich farming (rather than 

overgrazing) was used as one of the categories of future land-use pressure. 

Another insight from the workshop was the need for layers dealing with future landuse 

pressures to reflect a combination of, on the one hand, the inherent “suitability” 

of an area (for example, for crop agriculture or mining), and on the other hand, the 

market and other conditions governing whether that inherent suitability is likely to be 

exploited in practice. We used expert input to assist in deriving layers that reflected 

this combination of considerations. 

Day 2 of the workshop then went on with a discussion of the new target setting 

method developed for SKEP (see Section 14), which proved uncontroversial. 

Finally, we asked participants to work in small groups to advise us on how best to 

present the irreplaceability map combined with vulnerability to future land-use 

pressure, to stakeholders at the upcoming sub-regional Action Planning Workshops. 

We gave participants mock-ups of an irreplaceability map (including processes) and 

a vulnerability layer, for a sub-region-sized area, printed on tracing paper so that they 

could experiment with different ways of combining the layers. We asked them to think 

about how best to present this information as a single map, including the terminology 

and colours. We also asked them to think about accompanying information that 

would be useful to explain and interpret the new single combined irreplaceability and 

vulnerability map. They presented their proposals to the plenary in the form of 

posters (rather than giving just verbal report backs). The results of these small group 

discussions and poster presentations were exceptionally valuable for the Biodiversity 

Team, and fed directly into the development of the Framework for Action maps for 

the sub-regions and supporting posters (see Sections 15 and 26). 

The second Biodiversity Component Workshop was ambitious, for at least two 

reasons: 

• the audience was wide-ranging, as noted above; 

• some of the data layers and analysis we were presenting were hot off the press – 

the Biodiversity Team had not had time to digest and refine what we presented. 

In retrospect, and with more time, it may have been better to hold two separate 

workshops – one for people with knowledge of and interest in the science of 

conservation planning, the other for people with a more direct interest in conservation 

action in the Succulent Karoo. Also, it would have been ideal to have spent more 

time refining some of the data layers (such as the future land-use pressure layers) 

and analysis before we presented them. However, circumstance dictated that we go 

ahead with a single workshop as scheduled. On the positive side, we felt that the 

amount of debate and energetic participation engendered by the presentation of 

some less than fully resolved data layers, was good for SKEP. It made for a 

memorable workshop that challenged people to engage with the material presented 

and to think creatively. The mixed audience provided opportunities for mutual 

learning. 

Immediately after the workshop, we had a small, separate meeting just with the five 

Namibians who had attended the workshop, to clarify how we had developed the 

vegetation map (or habitat units) for Namibia, and to get Namibia-specific input on 


some of the other data layers. This was a valuable opportunity to build our 

relationship with the Namibian stakeholders. 

Appendix 13 in Part E includes the workshop invitation, list of participants, and small 

group instructions. 


26. Action Planning Workshops 

Action Planning Workshops in each of the SKEP sub-regions followed close on the 

heels of the second Biodiversity Component Workshop. This section discusses the 

role of the Biodiversity Component in these Action Planning Workshops. 

The purpose of the Action Planning Workshops was: 

• to present the results of the systematic conservation plan to stakeholders in the 

sub-regions; 

• to identify priority conservation actions in each sub-region. 

The sub-regional champion teams organised the workshops, and invited 

stakeholders from a range of sectors including: 

• agriculture (private and communal); 

• tourism; 

• mining; 

• conservation; 

• government (including municipalities). 

The dates of the sub-regional Action Planning Workshops were as follows: 

• 29-30 July 2002 – Namibia-Gariep workshop in Keetmanshoop 

• 1-2 August 2002 – Hantam-Tanqua-Roggeveld workshop in Calvinia 

• 7-8 August 2002 – Southern Karoo workshop in Oudtshoorn 

• 12-13 August 2002 – Namaqualand workshop in Springbok 

The sub-regional Action Planning Workshops were followed by a Biome-Wide Action 

Planning Workshop on 19 August 2002, which represented the culmination of the 

planning phase of SKEP. Results from the sub-regional workshops fed into the 

biome-wide workshop, which identified biome-wide priority conservation actions. 

The role of the Biodiversity Team in relation to the Action Planning Workshops was: 

• to produce a set of products showing the results of the systematic conservation 

planning exercise; 

• to attend the workshops and assist in facilitation. 21 

Developing products for Action Planning Workshops 

We had a month between the second Biodiversity Component Workshop and the first 

Action Planning Workshop to finalise the SKEP data layers and develop and produce 

posters to present at the workshops. We wanted the posters to be displayed for the 

duration of each workshop, and to be available to the champions to keep and display 

afterwards, not just to be flashed up on a screen during a presentation. Another 

reason for producing hard copies of posters was that not all the sub-regions would 

have data projectors at their workshops. 

21 Kristal and/or Mandy attended all the workshops, rather than the whole Biodiversity Team. 


Two days after the second Biodiversity Component Workshop we presented the 

proposed framework for action map (based on the advice synthesised from small 

groups at the Biodiversity Component Workshop) to the Technical Working Group for 

discussion. The following day we met with the champion teams to finalise the set of 

products we would produce for the Action Planning Workshops. 

Some of the champion teams were concerned that there was not enough purple (i.e. 

areas with few options for meeting conservation targets) on the framework for action 

map for their sub-region. A perception that green areas in the framework for action 

map are “not important” needed to be counteracted. Rather, these areas should be 

seen as areas where there is flexibility and opportunity. Green means many options 

for meeting conservation targets, which means many opportunities. 

The task of designing the set of ten posters with the help of a graphic designer, and 

then printing and laminating two sets for each sub-region, was not small. The ten 

posters were: 

• SKEP vegetation map (A0) 

• Vegetation map legend (A1) 

• Transformed and degraded areas (A1) 

• Protected areas (A1) 

• Expert mapping (A1) 

• Gap analysis of vegetation types (A1) 

• Framework for action map (per sub-region) (A0) 

• Process overlay (per sub-region) (A0) 

• How to develop a framework for action (A0) 

• Input layers for the framework for action (A0) 

Appendix 14 in Part E contains an A4 version of each of these posters. 

Assessment of products at Action Planning Workshops 

The Action Planning Workshops were successful in involving local and regional 

stakeholders in thinking strategically about conservation priorities in the Succulent 

Karoo. Participants worked in sector-related groups, such as tourism, agriculture and 

conservation, to identify priority actions and possible projects. A record of the Action 

Planning Workshops is available at the SKEP kiosk at www.dlist.org. 

The aim here is not to assess the workshops as a whole but just how the products 

from the Biodiversity Component were used. The crucial insight that we gained from 

watching the champion teams and the workshops participants interact with our 

products over the course of the four sub-regional Action Planning Workshops, was 

how difficult it is for people to relate to the spatial outputs of a systematic 

conservation plan. 

We had put a lot of energy into producing a set of posters that we hoped was 

accessible and easy to understand. We had tried to simplify the “raw” outputs of 

C-Plan, and to accompany them with explanatory material (such as the poster on 

How to Develop a Framework for Action). While there was definite interest in the 

posters, people were simply not able to absorb the bulk of what was presented. 

The small group sessions at the Action Planning Workshops were organised around 

thematic groups. The spatial products did not feed directly into the discussions on 


project-level activites. If one wanted to achieve this, more thinking would have to go 

into developing a workshop methodology that combined thematic priorities and 

spatial priorities. 

The lesson we took away with us is that an irreplaceability map (or an irreplaceability 

and vulnerability map) – simplified or not – should not be seen as the final output of a 

conservation plan. There is a need for an additional step to interpret the 

irreplaceability and vulnerability maps. Depending on the audience and the purpose 

of the product, different forms of interpretation would be appropriate. For example, 

the interpretation ideally needed for Action Planning Workshops would be different 

from the interpretation needed to produce a useful product for a municipal land-use 

planner or a manager in a conservation agency. 

Between the last sub-regional Action Planning Workshop and the Biome-Wide Action 

Planning Workshop, the Biodiversity Team had time to interpret the framework for 

action map for SKEP to identify nine broad geographic priority areas (or corridors in 

CEPF terms) within the Succulent Karoo. These are shown in Figure 27 in Section 

15. These nine geographic priority areas were presented at the Biome-Wide Action 

Planning Workshop, and have provided the basis for subsequent planning by the 

SKEP sub-regional teams. They will, we predict, be a more widely used product than 

the framework for action maps on which they are based. 

The need for interpretation of irreplaceability maps to produce designed conservation 

planning products is being taken forward in several Botantical Society projects and in 

other conservation planning projects in South Africa. 


Part D: Tables and References 

27. Additional Tables 

Table 25: The subdivision of South African vegetation types for SKEP 

Draft SA Veg Map Name Final SKEP Name 

Agter-Sederberg Succulent Scrub Agter-Sederberg Succulent Karoo 

Albany Succulent Thicket Albany Succulent Thicket 

Alexander Bay Coastal Dunes Alexander Bay Gravel Patches 

Aliwal North Dry Grassland Aliwal North Dry Grassland 

Altimontane Fynbos Altimontane Fynbos 

Anenous Plateau Shrubland Anenous Plateau Renosterveld 

Harras Quartzite Succulent Karoo 

Arid Coastal Salt Marshes Arid Coastal Salt Marshes 

Augrabies Mountains Succulent Scrub Aughrabies Mountain Succulent Karoo 

Augrabies Sandveld Grassland Augrabies Sandveld Grassland 

Baviaansklook-Gamtoos Thicket Baviaansklook-Gamtoos Thicket 

Bokkeveld Sand Fynbos Bokkeveld Sand Fynbos 

Boland Granite Fynbos Boland Granite Fynbos 

Breede Alluvium Fynbos Breede Alluvium Fynbos 

Breede Alluvium Renosterveld Breede Alluvium Renosterveld 

Breede Quartzitic Fynbos Breede Quartzitic Fynbos 

Breede Sand Fynbos Breede Sand Fynbos 

Breede Shale Fynbos Breede Shale Fynbos 

Breede Shale Renosterveld Breede Shale Renosterveld 

Bushmanland Arid Grassland Bushmanland Arid Grassland 

Eastern Bushmanland Quartz And Gravel Patches 

Kliprand Gravel Patches 

Moreskadu Quartz Patches 

Western Bushmanland Quartz and Gravel Patches 

Bushmanland Basin Bushmanland Basin 

Bushmanland Vloere Bushmanland Vloere 

Camdebo Succulent Thicket Camdebo Succulent Thicket 

Camdebo-Aberdeen Karoo Camdebo-Aberdeen Karoo 

Cederberg Sandstone Fyn Cederberg Sandstone Fynbos 

Cederberg Sandstone Fynbo Cederberg Sandstone Fynbos 

Cederberg Sandstone Fynbos Cederberg Sandstone Fynbos 

Cederberg Shale Communities Shale Renosterveld Communities 

Central Karroid Koppies Central Karroid Koppies 

Central Knersvlakte Plains Central Knersvlakte Lowland Succulent Karoo 

Rooiberg Quartzite Succulent Karoo 

Central Little Karoo Calitzdorp Quartz Patches 

Central Little Karoo 

Oudtshoorn Quartz Patches 

Central Mountain Renosterveld Central Mountain Renosterveld 

Central Richtersveld Succulent Scrub Central Richtersveld Succulent Karoo 

Ceres Alluvium Fynbos Ceres Alluvium Fynbos 

Ceres Renosterveld Ceres Renosterveld 

Ceres Shale Renos terveld Ceres Shale Renosterveld 



Coastal Granite Fynbos Coastal Granite Fynbos 

Coastal Granite Renosterveld Coastal Granite Renosterveld 

Dams Dams 

Die Plate Succulent Scrub Die Plate Succulent Karoo 

Doring River Succulent Karoo Doring River Succulent Karoo 

Eastern Gwarrieveld Eastern Gwarrieveld 

Steytlerville River Terraces 

Eastern Little Karoo Eastern Little Karoo 

Eastern Lower Karoo Eastern Lower Karoo 

Eastern Renosterveld Eastern Renosterveld 

Eastern Upper Karoo Eastern Upper Karoo 

Elgin Shale Fynbos Elgin Shale Fynbos 

Gariep Desert Plains Eastern Bushmanland Quartz And Gravel Patches 

Gariep Desert Plains 

Gariep Stony Desert Eastern Bushmanland Quartz And Gravel Patches 

Gariep Stony Desert 

Goariep Mountain Succulent Scrub Goariep Mountain Succulent Karoo 

Gouritz Valley Thicket Gouritz Valley Thicket 

Graafwater Sandstone Fynbos Graafwater Sandstone Fynbos 

Grassy Fynbos Grassy Fynbos 

Great Karoo Great Karoo 

Grootrivier Quartzite Fynbos Grootrivier Quartzite Fynbos 

Hantam Karoo Hantam Karoo 

Hantam Plateau Renosterveld Hantam Plateau Renosterveld 

Hellskloof Desert Nababiepsberge Desert 

Hex Sandstone Fynbos Hex Sandstone Fynbos 

Hottentots Holland Sandstone Fynbos Hottentots Holland Sandstone Fynbos 

Kaiing Bushmanland Basin 

Kamiesberg Mountain Fynbos Kamiesberg Mountain Fynbos 

Kamiesberg Mountain Shrubland Kamiesberg Mountain Brokenveld 

Kango Fynbos Kango Fynbos 

Kango Renosterveld Kango Renosterveld 

Karroid Mountain Grassland Karroid Mountain Grassland 

Kleinpoort Mountain Karoo Camdebo Succulent Thicket 

Knersvlakte Dolorites Knersvlakte Dolorites 

Troe-Troe River Quartz Patches 

Knersvlakte Quartzfields Knersvlakte Quartzfields 

Koekenaap Quartz Patches 

Nuwerus Quartzite Succulent Karoo 


Knersvlakte Shales Knersvlakte Shales 

Koa River Duneveld Eastern Bushmanland Quartz And Gravel Patches 

Koa River Dunes 

Western Bushmanland Quartz and Gravel Patches 

Kouebokkeveld Shale Fynbos Kouebokkeveld Shale Fynbos 

Kouga-Kamanassie Sandstone Fynbos Kouga-Kamanassie Sandstone Fynbos 

Laingsburg-Touws Succulent Karoo Laingsburg-Touws Succulent Karoo 

Lamberts Bay Sand Strandveld Lamberts Bay Strandveld 

Langeberg Sandstone Fynbos Langeberg Sandstone Fynbos 

Langeberg Shale Fynbos Langeberg Shale Fynbos 

Langkloof Shale Renosterveld Langkloof Shale Renosterveld 

Leipoldtville Sand Fynbos Leipoldtville Sand Fynbos 



Little Karoo Western Little Karoo 

Lower Koerougab Sheet Wash Plains Northern Richtersveld Lowland Succulent Karoo 

Lower Orange River Alluvia Lower Orange River Alluvia 

Matjiesfontein Quartzite Fynbos Matjiesfontein Quartzite Fynbos 

Matjiesfontein Shale Fynbos Matjiesfontein Shale Fynbos 

Matjiesfontein Shale Renosterveld Matjiesfontein Shale Renosterveld 

Moist Mountain Grassland Moist Mountain Grassland 

Montagu Shale Renosterveld Montagu Shale Renosterveld 

Mossel Bay Shale Renosterveld Mossel Bay Shale Renosterveld 

Muscadel Alluvia Calitzdorp Quartz Patches 

Muscadel Alluvia 


Vanwyksdorp Quartz Patches 

Nababiepsberge Desert Nababiepsberge Desert 

Namaqualand Alluvia Arid Coastal Salt Marshes 

Namaqualand Alluvia 

Namaqualand Lowland Succulent Karoo 

Olifants River Quartz Patches 

Namaqualand Arid Grasslands Namaqualand Arid Grasslands 


Namaqualand Coastal Dunes Alexander Bay Gravel Patches 

Namaqualand Coastal Dunes 

Namaqualand Klipkoppe Eenriet Quartzite Succulent Karoo 


Knersvlakte Quartzfields 

Koingnaas Quartzite Succulent Karoo 

Namaqualand Klipkoppe 


Riethuis Quartzfields 


Springbok Quartzite Succulent Karoo 

Namaqualand Klipkoppe Flats Koingnaas Quartzite Succulent Karoo 

Namaqualand Klipkoppe Flats 


Platbakkies Quartz and Gravel Patches 

Springbok Quartzite Succulent Karoo 

Namaqualand Northern Strand Alexander Bay Gravel Patches 

Namaqualand Northern Strandveld 

Namaqualand Pans Namaqualand Pans 

Namaqualand Red Sand Plains Aughrabies Mountain Succulent Karoo 

Buffels River Quartz And Gravel Patches 


Namaqualand Red Sand Plains 

Naroegas Quartzite Succulent Karoo 

Namaqualand Renosterveld Namaqualand Renosterveld 

Namaqualand Sand Fynbos Koingnaas Quartzite Succulent Karoo 

Namaqualand Sand Fynbos 

Namaqualand Sandveld Dunes Namaqualand Sandveld Dunes 

Namaqualand Southern Strand Namaqualand Southern Strandveld 

Namaqualand Spinescent Grasslands Namaqualand Spinescent Grasslands 

Namaqualand Succulent Veld Buffels River Quartz And Gravel Patches 





Kotzerus Quartz Patches 




Riethuis Quartzfields 

Namaqualand White Sand Plains Namaqualand White Sand Plains 

Niewoudtville Dolerite Renosterveld Niewoudtville Dolerite Renosterveld 

no data Camdebo Succulent Thicket 

Langkloof Shale Renosterveld 

Sundays Succulent Thicket 

Noams Mountain Desert Noams Mountain Desert 

Noorsveld Noorsveld 

Northern Knersvlakte Plains Northern Knersvlakte Lowland Succulent Karoo 


Northern Richtersveld Scorpionstailveld Lekkersing Quartz Patches 

Northern Richtersveld Lowland Succulent Karoo 

Northern Richtersveld Yellow Duneveld Alexander Bay Gravel Patches 

Northern Richtersveld Yellow Dunes 

Olifants Sandstone Fynbos Olifants Sandstone Fynbos 

Outeniqua Sandstone Fynbos Outeniqua Sandstone Fynbos 

Prince Albert Succulent Karoo Prince Albert Succulent Karoo 

Richtersberg Mountain Desert Richtersberg Mountain Desert 

Richtersveld High Mountain Shrubland Richtersveld Renosterveld 

Richtersveld Red Duneveld Lekkersing Quartz Patches 

Richtersveld Red Dunes 

Richtersveld Southwestern Foothills Richtersveld Southwestern Foothills Succulent Karo 

Richtersveld Western Foothills Lekkersing Quartz Patches 

Richtersveld Western Foothills Succulent Karoo 

Richtersveld White Duneveld Alexander Bay Gravel Patches 

Richtersveld White Dunes 

Riethuis Quartzfields Riethuis Quartzfields 

Robertson Karoo Robertson Karoo 

Roggeveld Karoo Roggeveld Karoo 

Roggeveld Renosterveld Roggeveld Renosterveld 

Rooiberg Quartz Fields Rooiberg Quartz Fields 

Southeastern Richtersveld Desert 

Rosyntjieberge Succulent Mountain Scrub Rosyntjieberge Succulent Karoo 

Ruens Shale Renosterveld Ruens Shale Renosterveld 

Ruschia Spinosa Plains Eenriet Quartzite Succulent Karoo 

Ruschia Spinosa Plains 

Scorpionstalveld Plain Northern Richtersveld Lowland Succulent Karoo 

Sonderend Sandstone Fynbos Sonderend Sandstone Fynbos 

Southeastern Karoo Kalkveld Southeastern Karoo Kalkveld 

Southeastern Montane Fynbos Southeas tern Montane Fynbos 

Southeastern Richtersveld Desert Southeastern Richtersveld Desert 

Southeastern Richtersveld Quartzites 

Southeastern Richtersveld Succulent Scrub Southeastern Richtersveld Succulent Karoo 

Southern Karoo Alluvia Southern Karoo Alluvia 


Southern Knersvlakte Plains Southern Knersvlakte Lowland Succulent Karoo 

Southern Nababiepsberge Mountain Desert Kristalberge Mountain Desert 



Southeastern Richtersveld Desert 

Southern Richtersveld Inselbergs Aughrabies Mountain Succulent Karoo 



Southern Richtersveld Inselbergs 

Southern Richtersveld Red Sandveld Dunes Lekkersing Quartz Patches 

Southern Richtersveld Red Dunes 

Southern Richtersveld Scorpionstailveld Aughrabies Mountain Succulent Karoo 



Southern Richtersveld Lowland Succulent Karoo 

Southern Richtersveld Yellow Duneveld Southern Richtersveld Yellow Dunes 

Southern Richtersveld Yellow Loam Sandveld Southern Richtersveld Yellow-Loam Dunes 

Southwestern Richtersveld Mountain Scrub Southwestern Richtersveld Mountain Succulent Karoo 

Springbokvlakte East Gariep Desert Plain Springbokvlakte East Gariep Desert Plains 

Springbokvlakte Mountain Desert Richtersberg Mountain Desert 

Steinkopf Plateau Shrubland Steinkopf Plateau Renosterveld 

Steytlerville Karoo Steytlerville Karoo 


Stinkfonteinberge Eastern Footplains Stinkfonteinberge Lowland Succulent Karoo 

Sundays Thicket Steytlerville River Terraces 

Sundays Succulent Thicket 

Swartberg Conglomerate Fynbos Swartberg Conglomerate Fynbos 

Swartberg Mesic Sandstone Fynbos Swartberg Mesic Sandstone Fynbos 

Swartberg Sandstone Fynbos Swartberg Sandstone Fynbos 

Swartberg Shale Renosterveld Swartberg Shale Renosterveld 

Swartruggens Quartzite Fynbos Swartruggens Quartzite Fynbos 

Swartruggens Sandstone Karoo Swartruggens Sandstone Karoo 

Swellendam Silcrete Fynbos Swellendam Silcrete Fynbos 

Tanqua Karoo Southern Tanqua Karoo 

Southern Tanqua Mountain Succulent Karoo 

Tanqua Karoo 

Tanqua Sheet Wash Plains Southern Tanqua Karoo 

Tanqua Sheet Wash Plains 

Tatasberg Mountain Desert Richtersberg Mountain Desert 

Umdaus Mountains Succulent Scrub Oernoep River Quartz Patches 

Umdaus Quartzite Succulent Karoo 

Uniondale Renosterveld Uniondale Renosterveld 

Unnamed Agter-Sederberg Succulent Karoo 

Camdebo Succulent Thicket 

Camdebo-Aberdeen Karoo 

Hantam Karoo 

Karroid Mountain Grassland 

Knersvlakte Shales 

Mossel Bay Shale Renosterveld 

Namaqualand Coastal Dunes 


Namaqualand Sand Fynbos 

Northern Knersvlakte Lowland Succulent Karoo 

Nuweveld Escarpment Karoo 

Western Karoo Hardeveld 

Upper Annisvlakte Succulent Scrub Upper Annisvlakte Succulent Karoo 



Vanrhynsdorp Shale Renosterveld Vanrhynsdorp Shale Renosterveld 

Vanwyksdorp Gwarrieveld Vanwyksdorp Gwarrieveld 


Villiersdorp Shale Renosterveld Villiersdorp Shale Renosterveld 

Volcanic Fynbos Volcanic Fynbos 

West Gariep Desert West Gariep Desert 

West Gariep Gravel Plains Alexander Bay Gravel Patches 

West Gariep Gravel Plains 

West Gariep Lowlands Alexander Bay Gravel Patches 

West Gariep Lowlands 

Western Karoo Hardeveld Western Karoo Hardeveld 

Western Little Karoo Anysberg Quartz Patches 

Langeberg Quartz Patches 


Warmwaterberg Quartz Patches 

Western Little Karoo 

Western Spekboomveld Calitzdorp Quartz Patches 


Western Spekboomveld 

Western Upper Karoo Western Upper Karoo 

Winterhoek Sandstone Fynbos Winterhoek Sandstone Fynbos 

Total SA Veg Map vegetation units: 175 Total SKEP vegetation units: 272 


Table 26: A list of the sand movement corridors identified in SKEP and their 

component SKEP vegetation units 

Sand Movement Corridor SKEP Vegetation Type 

Total area 

(ha) 

Alexander Bay Sand Corridor Alexander Bay Gravel Patches 22633 

Alexander Bay Sand Corridor Sum 22633 

Bitter River Active Dunes Namaqualand Coastal Dunes 5929 

Bitter River Active Dunes Sum 5929 

Bitter River Coast Dunes Namaqualand Southern Strandveld 383 

Namaqualand White Sand Plains 4910 

Bitter River Coast Dunes Sum 5293 

Brandsebaai Coastal Dunes Namaqualand Red Sand Plains 1020 

Namaqualand Southern Strandveld 88 

Brandsebaai Coastal Dunes Sum 1108 

Breede River Northern Sand Corridor Breede Alluvium Renosterveld 340 

Breede Quartzitic Fynbos 106 

Breede Sand Fynbos 338 

Breede Shale Renosterveld 82 

Robertson Karoo 75 

Breede River Northern Sand Corridor Sum 941 

Breede River Southern Sand Corridor Breede Alluvium Renosterveld 185 

Breede Sand Fynbos 337 

Breede River Southern Sand Corridor Sum 522 

Buffels-Holgat Active Dunes Namaqualand Coastal Dunes 28030 


Southern Richtersveld Red Dunes 22483 

Southern Richtersveld Yellow Dunes 7718 

Buffels-Holgat Active Dunes Sum 59961 

Groen River Active Dunes Namaqualand Coastal Dunes 102 

Groen River Active Dunes Sum 102 

Groen River Inland Dunes Namaqualand Red Sand Plains 10827 


Namaqualand White Sand Plains 1055 

Groen River Inland Dunes Sum 12142 

Groen-Speog Inland Dunes Namaqualand Coastal Dunes 8571 

Namaqualand Lowland Succulent Karoo 3445 

Namaqualand Sand Fynbos 21938 

Namaqualand Sandveld Dunes 3480 


Groen-Speog Inland Dunes Sum 37672 

Holgat-Boegoeberg Active Dunes Namaqualand Coastal Dunes 3930 

Namaqualand Northern Strandveld 165 

Richtersveld White Dunes 10938 

Holgat-Boegoeberg Active Dunes Sum 15033 

Knersvlakte Inland Dunes Namaqualand Spinescent Grasslands 29745 

Knersvlakte Inland Dunes Sum 29745 

Koa River Bushmanland Arid Grassland 37714 

Gariep Desert Plains 6612 

Koa River Dunes 130930 

Koa River Sum 175255 

Koingnaas -Komaggas Inland Dunes Namaqualand Red Sand Plains 12854 


Sand Movement Corridor SKEP Vegetation Type 

Total area 

(ha) 

Namaqualand Sand Fynbos 16523 

Koingnaas -Komaggas Inland Dunes Sum 29377 

Namib Erg Luderitz-Pomona Rock Outcrops & Gravel Plains 3735 

Namib Desert Erg 160905 

Namib Erg Sum 164640 

Namib Inland Erg Namib Desert Erg Inland Dunes 40915 

Namib Desert Erg Linear Dunes 62831 

Namib Desert Inland Red Dune 1835 

Namib Inland Erg Sum 105581 

Haalenberg Active Dunes Namib Coastal Red Dunes 10271 

Haalenberg Active Dunes Sum 10271 

Obibberg Active Dunes Namib Coastal Red Dunes 29472 

West Gariep Desert 904 

Obibberg Active Dunes Sum 30376 

Hohenfels -Roter Kamm Active Dunes Namib Coastal Mobile Dune Strandveld 53346 

Namib Coastal Red Dunes 122444 

Namib Coastal Strandveld 7373 

Namib Inland Strandveld 5156 

Namib Red Sandy Plains 24094 

Hohenfels -Roter Kamm Active Dunes Sum 212414 

Boegoeberg Active Dunes Namib Coastal Mobile Dune Strandveld 6448 

Namib Coastal Strandveld 191990 

Boegoeberg Active Dunes Sum 198439 

Swartlintjies -Buffels River Active Dunes Namaqualand Coastal Dunes 20039 

Namaqualand Red Sand Plains 29934 


Swartlintjies -Buffels River Active Dunes Sum 51416 


Table 27: Combinations of environmental classes and rules used to develop 

the broad habitat unit map 

Vegetation Landform Winter Altitude 

No. of 

polygons 

Arid (valley) transitional nama karoo rock 30 0 1 

300 90 

600 438 

Arid mountain succulent karoo rock 40 0 18 

300 200 

600 608 

Central red sands red sand 10 900 1 

1300 1 

30 600 8 

900 67 

1300 33 

1700 1 

Coastal mountain succulent karoo rock 0 0 3 

300 4 

50 0 1 

300 178 

600 73 

Coastal red dunes fields red dunes 30 300 5 

600 9 

900 4 

40 300 8 

600 49 

900 35 

1300 1 

50 300 6 

600 8 

Escarpment nama karoo rock 10 900 29 

1300 312 

1700 208 

High escarpment nama karoo rock 10 2000 31 

Hight altitude succulent karoo rock 40 1700 50 

2000 2 

Hottentots Bay rock outcrops & gravel plains rock 0 0 5 

300 7 

40 0 2 

300 1 

50 300 2 

Inland red dune fields red dunes 0 900 28 

1300 13 

10 600 4 

900 34 

1300 20 

30 600 4 

900 16 

1300 11 

40 900 2 

Karas arid grassland sandy flats 10 600 10 

900 8 

30 600 10 

900 30 

1300 9 

Karas arid grasslands sandy flats 10 600 5 



No. of 

polygons 

900 138 

1300 72 

Karas arid savanna sandy flats 10 300 7 

600 77 

900 284 

1300 255 

1700 115 

30 300 7 

600 23 

900 19 

Karas dune arid grassland bushmanland dunes 10 600 3 

900 5 

30 600 3 

900 8 

1300 1 

Karas nama karoo rock 10 300 44 

600 222 

900 618 

Karas sandy flats sandy flats 10 300 15 

600 39 

900 32 

1300 5 

30 300 10 

600 28 

900 56 

1300 4 

40 300 4 

600 7 

900 3 

Karas upland nama karoo rock 10 1300 349 

1700 17 

Luderitz-Pomona rock outcrops & gravel 

plains 

Ludertiz 0 0 43 

300 89 

40 0 5 

300 10 

600 7 

50 0 31 

300 34 

Mesic mountain succulent karoo rock 40 1300 148 

Mesic transitional nama karoo rock 30 1700 165 

2000 11 

Mountain succulent karoo rock 40 900 293 

Namib Erg namib sand erg 0 0 13 

300 16 

600 6 

30 300 3 

600 7 

900 6 

40 0 2 

300 15 

600 16 

50 300 2 

rock 0 0 2 

300 2 

40 300 1 



No. of 

polygons 

Namib Erg inland dunes namib inland megali 

0 600 19 

900 17 

10 600 13 

900 4 

Namib Erg linear dunes namib coastal 

mega-l 

0 600 2 

10 600 4 

30 300 2 

600 7 

900 1 

NE red sands red sand 10 900 3 

1300 20 

1700 13 

30 1300 6 

1700 16 

NE sandy plains sandy flats 0 600 1 

900 4 

1300 11 

10 600 49 

900 77 

1300 96 

1700 124 

30 300 4 

600 31 

900 27 

Orange River nama karoo 1 rock 10 300 25 

600 65 

Southern Namib coastal hummock dunes coastal hummocks 0 0 76 

300 100 

50 0 56 

300 45 

coastal sand 0 0 7 

50 0 1 

Southern Namib coastal mobile dune 

strandveld 

white dunes 0 0 4 

300 8 

40 300 4 

600 2 

50 0 2 

300 36 

600 19 

Southern Namib coastal strandveld coastal sand 0 300 7 

30 300 14 

40 300 79 

50 300 81 

Southern Namib inland mobile dune 

strandveld 

white dunes 40 300 16 

600 13 

900 24 

50 300 6 

600 1 

Southern Namib inland strandveld coastal sand 30 600 20 

40 600 156 

900 37 

50 600 68 



No. of 

polygons 

Southern Namib Inselberg nama karoo 2 rock 10 600 109 

900 131 

1300 178 

1700 72 

Succulent karoo sandy plains sandy flats 30 300 9 

600 53 

900 111 

1300 170 

1700 28 

40 0 19 

300 18 

600 61 

900 117 

1300 25 

1700 6 

50 300 18 

600 10 

SW red-sandveld karoo red sand 40 0 19 

300 8 

600 54 

900 96 

1300 34 

1700 10 

50 300 1 

600 10 

Transitional nama karoo rock 30 900 700 

1300 354 

Grand Total 

1 Only along the Orange river 

2 Only inselbergs on the coastal plain 

10044 


Table 28: A summary of the number of plant families, genera and species 

found in the Succulent Karoo 

Species 

Genera 

Genera 

Genera 

Family Name Family Name 

Mesembryanthemaceae 108 1132Capparaceae 

Family Name 

5 13Icacinaceae 2 2 

Asteraceae 108 777Anthericaceae 2 12Juncaginaceae 1 2 

Iridaceae 29 408Convolvulaceae 4 10Myricaceae 1 2 

Scrophulariaceae 39 349Alliaceae 2 9Ophioglossaceae 1 2 

Fabaceae 57 315Verbenaceae 3 9Orthotrichaceae 1 2 

Poaceae 84 297Bryaceae 3 8Pedaliaceae 2 2 

Crassulaceae 5 202Urticaceae 3 8Penaeaceae 2 2 

Hyacinthaceae 22 172Viscaceae 1 8Primulaceae 2 2 

Asphodelaceae 8 149Loranthaceae 5 7Resedaceae 1 2 

Euphorbiaceae 13 140Apocynaceae 3 6Ruppiaceae 1 2 

Asclepiadaceae 31 130Fumariaceae 4 6Unknown 2 2 

Geraniaceae 5 126Funariaceae 3 6Vitaceae 1 2 

Aizoaceae 18 124Grimmiaceae 4 6Zamiaceae 1 2 

Amaryllidaceae 15 100Melianthaceae 1 6Zannichelliaceae 2 2 

Oxalidaceae 1 96Oleaceae 3 6Anemiaceae 1 1 

Chenopodiaceae 10 83Sapindaceae 6 6Aponogetonaceae 1 1 

Sterculiaceae 3 82Tecophilaeaceae 2 6Araceae 1 1 

Cyperaceae 17 70Bartramiaceae 4 5Archidiaceae 1 1 

Brassicaceae 11 69Burseraceae 1 5Azollaceae 1 1 

Acanthaceae 12 56Neuradaceae 2 5Blechnaceae 1 1 

Orchidaceae 14 55Proteaceae 4 5Brachytheciaceae 1 1 

Eriospermaceae 1 54Araliaceae 1 4Bryobartramiaceae 1 1 

Zygophyllaceae 7 51Bruniaceae 3 4Cactaceae 1 1 

Polygalaceae 3 49Droseraceae 1 4Codoniaceae 1 1 

Restionaceae 11 48Fissidentaceae 1 4Davalliaceae 1 1 

Apiaceae 22 47Flacourtiaceae 3 4Dipsacaceae 1 1 

Campanulaceae 5 47Illecebraceae 2 4Encalyptaceae 1 1 

Thymelaeaceae 4 45Loganiaceae 2 4Equisetaceae 1 1 

Rutaceae 8 44Nyctaginaceae 3 4Fabroniaceae 1 1 

Asparagaceae 1 40Onagraceae 3 4Lauraceae 1 1 

Rhamnaceae 4 39Periplocaceae 3 4Lentibulariaceae 1 1 

Santalaceae 3 39Tiliaceae 1 4Linaceae 1 1 

Anacardiaceae 4 36Aytoniaceae 3 3Loasaceae 1 1 

Colchicaceae 5 36Commelinaceae 2 3Lythraceae 1 1 

Solanaceae 6 36Dioscoreaceae 1 3Malpighiaceae 1 1 

Lamiaceae 10 34Ditrichaceae 2 3Marsileaceae 1 1 

Boraginaceae 14 32Frankeniaceae 1 3Meliaceae 1 1 

Caryophyllaceae 7 31Haemodoraceae 2 3Montiniaceae 1 1 

Rubiaceae 8 31Haloragaceae 3 3Myoporaceae 1 1 

Ericaceae 1 30Menispermaceae 2 3Myrsinaceae 1 1 

Pottiaceae 15 29Moraceae 1 3Myrtaceae 1 1 

Portulacaceae 5 27Papaveraceae 2 3Phytolaccaceae 1 1 

Ebenaceae 2 26Plantaginaceae 1 3Piperaceae 1 1 

Lobeliaceae 4 26Potamogetonaceae 1 3Polytrichaceae 1 1 

Ricciaceae 1 24Ptychomitriaceae 2 3Ptaeroxylaceae 1 1 

Cucurbitaceae 9 23Ranunculaceae 2 3Rafflesiaceae 1 1 

Malvaceae 8 23Salicaceae 1 3Salvadoraceae 1 1 

Rosaceae 3 21Vahliaceae 1 3Sapotaceae 1 1 

Celastraceae 8 20Aspleniaceae 2 2Schizaeaceae 1 1 

Pteridaceae 3 18Bignoniaceae 1 2Selaginellaceae 1 1 

Plumbaginaceae 4 16Dicranaceae 2 2Sphaerocarpaceae 1 1 

Gentianaceae 2 15Dryopteridaceae 1 2Stilbaceae 1 1 

Polygonaceae 4 15Elatinaceae 1 2Tamaricaceae 1 1 

Amaranthaceae 8 14Gigaspermaceae 2 2Targioniaceae 1 1 

Hypoxidaceae 3 14Hydnoraceae 1 2Typhaceae 1 1 

Juncaceae 1 14Hydrophyllaceae 1 2Ulmaceae 1 1 

Grand Total: 168 families, 1002 genera, 6356 species 


Species 

Species

Table 29: Summary statistics for the 431 bird species that have been recorded 

in the Succulent Karoo 

Order Family Genus Total 

Anseriformes Anatidae Alopochen 1 

Anas 6 

Dendrocygna 2 

Netta 1 

Oxyura 1 

Plectropterus 1 

Sarkidiornis 1 

Tadorna 1 

Thalassornis 1 

Apodiformes Apodidae Apus 7 

Cypsiurus 1 

Caprimulgiformes Caprimulgidae Caprimulgus 4 

Charadriiformes Burhinidae Burhinus 2 

Charadriidae Charadrius 8 

Pluvialis 1 

Vanellus 2 

Glareolidae Cursorius 2 

Smutsornis 1 

Haematopodidae Haematopus 2 

Jacanidae Actophilornis 1 

Laridae Catharacta 1 

Chlidonias 3 

Hydroprogne 1 

Larus 4 

Stercorarius 1 

Sterna 7 

Phalaropodidae Phalaropus 1 

Recurvirostridae Himantopus 1 

Recurvirostra 1 

Rostratulidae Rostratula 1 

Scolopacidae Actitis 1 

Arenaria 1 

Calidris 4 

Gallinago 1 

Limosa 2 

Numenius 2 

Philomachus 1 

Tringa 5 

Xenus 1 

Ciconiiformes Ardeidae Ardea 4 

Ardeola 1 

Bubulcus 1 

Butorides 1 

Casmerodius 1 

Egretta 2 

Ixobrychus 2 

Nycticorax 1 

Ciconiidae Ciconia 3 

Leptoptilos 1 

Mycteria 1 



Plataleidae Bostrychia 1 

Platalea 1 

Plegadis 1 

Threskiornis 1 

Scopidae Scopus 1 

Coliiformes Coliidae Colius 2 

Urocolius 1 

Columbiformes Columbidae Aplopelia 1 

Columba 3 

Oena 1 

Streptopelia 3 

Turtur 2 

Coraciiformes Bucerotidae Tockus 2 

Coraciidae Coracias 1 

Halcyonidae Alcedo 2 

Ceryle 2 

Halcyon 1 

Meropidae Merops 2 

Phoeniculidae Phoeniculus 1 

Rhinopomastus 1 

Upupidae Upupa 1 

Cuculiformes Cuculidae Centropus 1 

Chrysococcyx 2 

Clamator 2 

Cuculus 4 

Falconiformes Accipitridae Accipiter 4 

Aquila 3 

Buteo 3 

Circaetus 2 

Circus 2 

Elanus 1 

Gyps 2 

Haliaeetus 1 

Hieraaetus 1 

Melierax 1 

Micronisus 1 

Milvus 1 

Polemaetus 1 

Polyboroides 1 

Stephanoaetus 1 

Torgos 1 

Falconidae Falco 7 

Polihierax 1 

Pandionidae Pandion 1 

Sagittariidae Sagittarius 1 

Galliformes Numididae Numida 1 

Phasianidae Coturnix 1 

Francolinus 4 

Gruiformes Gruidae Anthropoides 1 

Otididae Ardeotis 1 

Eupodotis 2 

Neotis 2 

Rallidae Amaurornis 1 



Fulica 1 

Gallinula 1 

Porphyrio 1 

Porzana 1 

Rallus 1 

Sarothrura 1 

Turnicidae Turnix 1 

Musophagiformes Musophagidae Tauraco 1 

Passeriformes Alaudidae Ammomanes 1 

Calandrella 1 

Certhilauda 4 

Chersomanes 1 

Eremalauda 1 

Eremopterix 2 

Galerida 1 

Mirafra 3 

Spizocorys 2 

Campephagidae Campephaga 1 

Coracina 1 

Corvidae Corvus 3 

Dicruridae Dicrurus 1 

Estrildidae Amadina 1 

Estrilda 2 

Lagonosticta 2 

Ortygospiza 1 

Fringillidae Emberiza 4 

Pseudochloroptila 1 

Serinus 10 

Hirundinidae Delichon 1 

Hirundo 7 

Psalidoprocne 1 

Riparia 3 

Laniidae Lanius 3 

Malaconotidae Dryoscopus 1 

Laniarius 1 

Nilaus 1 

Tchagra 1 

Telophorus 2 

Motacillidae Anthus 5 

Macronyx 1 

Motacilla 4 

Muscicapidae Batis 3 

Melaenornis 2 

Muscicapa 2 

Sigelus 1 

Stenostira 1 

Terpsiphone 1 

Trochocercus 1 

Nectariniidae Anthreptes 1 

Nectarinia 7 

Oriolidae Oriolus 2 

Paridae Parus 2 

Ploceidae Amblyospiza 1 



Euplectes 2 

Passer 4 

Petronia 1 

Philetairus 1 

Plocepasser 1 

Ploceus 4 

Quelea 1 

Sporopipes 1 

Promeropidae Promerops 1 

Pycnonotidae Andropadus 1 

Phyllastrephus 1 

Pycnonotus 2 

Remizidae Anthoscopus 1 

Sturnidae Creatophora 1 

Lamprotornis 2 

Onychognathus 2 

Spreo 1 

Sturnus 1 

Sylviidae Acrocephalus 4 

Apalis 2 

Bradypterus 3 

Camaroptera 1 

Cisticola 8 

Eremomela 2 

Euryptila 1 

Malcorus 1 

Parisoma 2 

Phragmacia 1 

Phylloscopus 2 

Prinia 2 

Sphenoeacus 1 

Sylvietta 1 

Turdidae Cercomela 4 

Chaetops 1 

Cossypha 1 

Erythropygia 3 

Monticola 3 

Myrmecocichla 1 

Oenanthe 2 

Saxicola 1 

Thamnolaea 1 

Turdus 1 

Viduidae Vidua 2 

Zosteropidae Zosterops 1 

Pelecaniformes Anhingidae Anhinga 1 

Pelecanidae Pelecanus 1 

Phalacrocoracidae Phalacrocorax 5 

Sulidae Morus 2 

Phoenicopteriformes Phoenicopteridae Phoeniconaias 1 

Phoenicopterus 1 

Piciformes Capitonidae Lybius 1 

Pogoniulus 1 

Trachyphonus 1 



Tricholaema 1 

Indicatoridae Indicator 3 

Prodotiscus 1 

Picidae Campethera 2 

Dendropicos 1 

Geocolaptes 1 

Mesopicos 1 

Podicipediformes Podicipedidae Podiceps 2 

Tachybaptus 1 

Procellariiformes Diomedeidae Diomedea 3 

Oceanitidae Hydrobates 1 

Oceanites 1 

Procellariidae Daption 1 

Macronectes 2 

Procellaria 1 

Pterodroma 1 

Puffinus 1 

Psittaciformes Psittacidae Agapornis 1 

Pterocliformes Pteroclididae Pterocles 2 

Sphenisciformes Spheniscidae Spheniscus 1 

Strigiformes Strigidae Asio 1 

Bubo 2 

Otus 1 

Strix 1 

Tytonidae Tyto 1 

Struthioniformes Struthionidae Struthio 1 

Trogoniformes Trogonidae Apaloderma 1 

No data 1 3 

Total number of species 431 

1 No data in database for R126 YellowBilled Kite, Budgerrigar and Mallard 

Table 30: A list of duplicate species numbers encountered in the bird database 

Species greyed out were excluded from the final species list for the Succulent Karoo. 

ADU 

No 

Common Name Species Name Order Family 

126Yellowbilled Kite Milvus migrans parasitus Falconiformes Accipitridae 

126Black Kite Milvus migrans migrans Falconiformes Accipitridae 

239Whitewinged Black Korhaan Eupodotis afraoides Gruiformes Otididae 

239Black Korhaan Eupodotis afra Gruiformes Otididae 

391Burchell's Coucal Centropus burchellii Cuculiformes Cuculidae 

391Whitebrowed Coucal Centropus superciliosus Cuculiformes Cuculidae 

502Karoo Lark Certhilauda albescens Passeriformes Alaudidae 

502Barlow's Lark Certhilauda barlowi Passeriformes Alaudidae 

657Bleating Warbler Camaroptera brachyura Passeriformes Sylviidae 

657Greybacked Warbler Camaroptera brevicaudata Passeriformes Sylviidae 

686Karoo Prinia Prinia maculosa Passeriformes Sylviidae 

686Spotted Prinia Prinia hypoxantha Passeriformes Sylviidae 


Table 31: Summary statistics at the generic level for Amphibians, Bees, 

Termites, Mammals, Scorpions and Reptiles that occur in the Succulent Karoo 


1= Occurs only in the Succulent Karoo area (I.e. 100% of known distribution is in the Succulent Karoo. 

2= Between 50 and 100% of distribution of species in the Succulent Karoo OR at least 25% or more of 


4= less than 50% of known range in the Succulent Karoo. Known from 5 or more QDS. 


CLASS ORDER FAMILY GENUS 

Total 

Status Species 

Amphibia Anura Bufonidae Bufo 1 1 

2 2 

4 1 

Microhylidae Breviceps 1 1 

2 1 

Phrynomantis 1 1 

Pipidae Xenopus 2 1 

Ranidae Afrana 2 1 

4 1 

Cacosternum 1 1 

2 1 

4 1 

Strongylopus 1 1 

2 1 

Tomopterna 2 1 

4 1 

Amphibia Total 17 

Aranaea Buthidae Hottentotta 2 1 

Karasbergia 4 1 

Parabuthus 1 2 

2 1 

4 9 

Uroplectes 2 2 

4 5 

Ischnuridae Hadogenes 2 2 

4 3 

Opisthacanthus 2 1 

4 1 

Scorpionidae Opistophthalmus 1 16 

2 13 

4 13 

Aranaea Total 70 

Insecta Hymenoptera (Apoidea) Afranthidium 1 1 

2 1 

Allodape 2 5 

4 1 

Allodapula 2 1 

4 1 

Amegilla 1 1 

2 2 

4 2 

Anthidium 1 2 



Total 


2 1 

Anthophora 1 4 

2 6 

4 1 

Braunsapis 1 1 

2 1 

4 1 

Ceratina 1 4 

2 2 

4 1 

Chalicodoma 1 4 

2 2 

Coelioxys 1 4 

Colletes 1 1 

Creightoniella 1 1 

Ctenoceratina 2 1 

4 1 

Eoanthidium 1 1 

Epeolus 2 2 

Fidelia 1 2 

2 1 

Halterapis 1 1 

Haplomelitta 2 1 

Heriades 1 1 

Megachile 2 3 

Melittidae 1 1 

Nomada 2 1 

Osmia 1 1 

Pachymelus 1 2 

Patellapis 1 2 

Pleisanthidium 1 1 

Protosmia 1 1 

2 1 

Pseudapis 2 1 

Pseudoanthidium 2 1 

Pseudodichroa 1 1 

Scrapter 1 9 

2 11 

4 1 

Seladonia 1 2 

2 1 

4 1 

Sphecodopsis 1 3 

2 2 

Spinanthidium 1 4 

2 2 

Tetraloniella 1 2 

2 2 

Thyreus 1 1 

2 2 

4 2 

Xylocopa 1 2 



Total 


2 5 

4 3 

Xyloxopa 2 1 

Isoptera Barbibucca 1 1 

Capophanes 1 1 

Centroclisis 2 1 

Crambomorphus 2 1 

Creoleon 1 1 

Cueta 1 1 

2 2 

Cymothales 1 1 

2 1 

Golafrus 2 1 

Isonemurus 1 2 

Kimochrysa 1 1 

Laurhervasia 1 1 

Melambrotus 1 1 

Myrmeleon 1 3 

2 1 

Nannoleon 2 1 

Nemeura 1 1 

Nemia 1 4 

Nesoleon 2 1 

4 1 

Neuroleon 1 1 

Palparellus 2 1 

Palpares 2 3 

4 1 

Pamares 1 3 

Pamexis 1 2 

2 1 

Pseudoproctarrelabris 1 1 

Strixomyia 2 1 

Tricholeon 1 1 

Insecta Total 177 

Mammalia Artiodactyla Bovidae Oreotragus 4 1 

Pelea 4 1 

Raphicerus 4 2 

Sylvicapra 4 1 

Taurotragus 2 1 

Carnivora Canidae Canis 4 1 

Otocyon 4 1 

Vulpes 4 1 

Felidae Felis 4 2 

Panthera 4 1 

Hyaenidae Hyaena 4 1 

Mustelidae Aonyx 4 1 

Ictonyx 4 1 

Mellivora 4 1 

Poecilogale 4 1 

Protelidae Proteles 4 1 

Viverridae Galerella 4 1 



Total 


Genetta 4 1 

Suricata 1 1 

4 1 

Chiroptera Molossidae Tadarida 2 2 

Nycteridae Nycteris 4 1 

Pteropodidae Rousettus 2 1 

Rhinolophidae Rhinolophus 4 1 

Vespertilionida Eptesicus 2 1 

4 1 

Laephotis 2 1 

Miniopterus 2 1 

Myotis 1 1 

4 1 

Hyracoidea Procavidae Procavia 4 1 

Insectivora Chrysochloridae Chrysochloris 4 1 

Soricidae Crocidura 4 1 

Myosorex 4 1 

Suncus 2 1 

Lagomorpha Leporidae Lepus 4 1 

Pronolagus 4 1 

Macroscelidea Macroscelididae Elephantulus 4 2 

Macroscelides 4 1 

Perissodactyl Equidae Equus 1 1 

Rhinocerotidae Diceros 2 1 

Primates Cercopithecidae Cercopithecus 4 1 

Papio 4 1 

Rodentia Gliridae Graphiurus 1 1 

4 1 

Hystricidae Hystrix 4 1 

Muridae Acomys 4 1 

Aethomys 4 2 

Desmodillus 4 1 

Gerbillurus 4 1 

Mus 1 1 

Otomys 2 1 

4 2 

Parotomys 4 2 

Petromyscus 2 1 

Rhabdomys 4 1 

Saccostomus 4 1 

Tatera 1 1 

4 1 

Petromuridae Petromus 4 1 

Sciuridae Xerus 4 1 

Mammalia Total 68 

Reptilia Scincidae Acontias 1 3 

4 2 

Mabuya 4 5 

Scelotes 1 1 

4 3 

Typhlosaurus 1 3 

4 1 



Total 


Gekkonidae Afroedura 1 1 

Afrogecko 4 1 

Chondrodactylus 4 2 

Goggia 1 2 

4 2 

Lygodactylus 4 1 

Narudasia 4 1 

Pachydactylus 1 3 

4 14 

Palmatogecko 4 1 

Phelsuma 1 1 

Ptenopus 4 1 

Agamidae Agama 1 1 

4 4 

Elapidae Aspidelaps 4 1 

Homoroselaps 4 1 

Naja 4 2 

Viperidae Bitis 4 7 

Chamaeleonidae Bradypodion 4 2 

Chamaeleo 4 1 

Gerrhosauridae Cordylosaurus 4 1 

Gerrhosaurus 4 1 

Cordylidae Cordylus 1 4 

4 4 

Platysaurus 1 1 

Colubridae Dasypeltis 4 1 

Dipsina 4 1 

Lamprophis 4 3 

Philothamnus 4 1 

Prosymna 4 3 

Psammophis 4 4 

Psammophylax 4 1 

Pseudaspis 4 1 

Telescopus 4 2 

Leptotyphlopidae Leptotyphlops 4 2 

Lacertidae Meroles 1 1 

4 4 

Nucras 4 2 

Pedioplanis 4 5 

Typhlopidae Rhinotyphlops 4 2 

Varanidae Varanus 4 2 

Chelonia Testudinidae Chersina 4 1 

Geochelone 4 1 

Homopus 1 2 

4 1 

Psammobates 1 1 

4 1 

Pelomedusidae Pelomedusa 4 1 

Reptilia Total 121 



Table 32: Summary statistics at the class level for Amphibian, Bees, Termites, 

Mammals, Scorpions and Reptiles that occur in the Succulent Karoo 


1 = Occurs only in the Succulent Karoo area (i.e. 100% of known distribution is in the Succulent Karoo. 

2 = Between 50 and 100% of distribution of species in the Succulent Karoo OR at least 25% or more of 


4 = less than 50% of known range in the Succulent Karoo. Known from 5 or more QDS. 


Total % of 

CLASS ORDER Status Species Order 

Amphibia Anura 1 5 29 

2 8 47 

4 4 24 

Amphibia Total 17 100 

Aranaea 1 18 26 

2 20 29 

4 32 46 

Aranaea Total 70 100 

Insecta Hymenoptera (Apoidea) 1 60 45 

2 59 44 

4 15 11 

Total Hymenoptera 134 100 

Isoptera 1 26 60 

2 15 35 

4 2 5 

Total Isoptera 43 100 

Insecta Total 177 

Mammalia Artiodactyla 2 1 1 

4 5 7 

Carnivora 1 1 1 

4 15 22 

Chiroptera 1 1 1 

2 6 9 

4 4 6 

Hyracoidea 4 1 1 

Insectivora 2 1 1 

4 3 4 

Lagomorpha 4 2 3 

Macroscelidea 4 3 4 

Perissodactyl 1 1 1 

2 1 1 

Primates 4 2 3 

Rodentia 1 3 4 

2 2 3 

4 16 24 

Mammalia Total 68 100 

Reptilia 1 21 17 

4 92 76 

Chelonia 1 3 2 

4 5 4 

Reptilia Total 121 100 



Table 33: Targets set for vegetation types 

Column “1” = percent low target, column “2” = percent high target 

SKEP Vegetation Type Name Vegetation Group 1 2 

Total 

Area 


(ha) 

Area 1 

(ha) 

Area 2 

(ha) 

Arid Coastal Salt Marshes azonal 15 35 3738 561 1308 

Muscadel Alluvia azonal 20 35 36723 7345 12853 

Namaqualand Alluvia azonal 20 35 56868 11374 19904 

Augrabies Sandveld Grassland desert grassland 20 35 12330 2466 4316 

Namaqualand Arid Grasslands desert grassland 20 35 65482 13096 22919 

Namaqualand Spinescent Grasslands desert grassland 20 35 49462 9892 17312 

Kamiesberg Mountain Fynbos fynbos 30 50 3692 1108 1846 

Namaqualand Sand Fynbos fynbos 20 35 93696 18739 32794 

Central Knersvlakte Lowland Succulent 

Karoo 

lowland succulent karoo 20 35 16753 3351 5864 

Central Little Karoo lowland succulent karoo 20 35 68846 13769 24096 

Eastern Little Karoo lowland succulent karoo 20 35 24500 4900 8575 

Grillenthal Coastal Inselbergs and Gravel 

Plains 


Hottentots Bay Rock Outcrops & Gravel 

Plains 


Knersvlakte Dolorites lowland succulent karoo 25 40 2639 660 1055 

Knersvlakte Shales lowland succulent karoo 15 35 83414 12512 29195 

Luderitz-Pomona Rock Outcrops & Gravel 

Plains 


Namaqualand Klipkoppe Flats lowland succulent karoo 20 35 302920 60584 106022 

Namaqualand Lowland Succulent Karoo lowland succulent karoo 20 35 226120 45224 79142 

Northern Knersvlakte Lowland Succulent 



Northern Richtersveld Lowland Succulent lowland succulent karoo 20 35 23955 4791 8384 


Prince Albert Succulent Karoo lowland succulent karoo 10 20 223061 22306 44612 

Robertson Karoo lowland succulent karoo 20 40 61257 12251 24503 

Southeastern Richtersveld Desert lowland succulent karoo 20 35 62527 12505 21884 

Southeastern Richtersveld Succulent Karoo lowland succulent karoo 20 35 52147 10429 18251 

Southern Knersvlakte Lowland Succulent 



Southern Richtersveld Lowland Succulent lowland succulent karoo 20 35 72296 14459 25303 


Southern Tanqua Karoo lowland succulent karoo 20 35 125141 25028 43799 

Springbokvlakte East Gariep Desert Plains lowland succulent karoo 20 35 9677 1935 3387 

Steytlerville Karoo lowland succulent karoo 10 20 16167 1617 3233 

Stinkfonteinberge Lowland Succulent Karoo lowland succulent karoo 20 35 4552 910 1593 

Tanqua Karoo lowland succulent karoo 15 35 595871 89381 208555 

Tanqua Sheet Wash Plains lowland succulent karoo 15 35 162805 24421 56982 

Upper Annisvlakte Succulent Karoo lowland succulent karoo 20 35 19180 3836 6713 

Vanwyksdorp Gwarrieveld lowland succulent karoo 20 35 73353 14671 25674 

West Gariep Lowlands lowland succulent karoo 15 35 46028 6904 16110 

Western Little Karoo lowland succulent karoo 20 35 335057 67011 117270 

Agter-Sederberg Succulent Karoo mountain succulent karoo 20 35 221903 44381 77666 

Aughrabies Mountain Succulent Karoo mountain succulent karoo 20 35 7968 1594 2789 

Aurusberg Succulent Karoo mountain succulent karoo 20 35 15925 3185 5574 

Boegoeberg Succulent Karoo mountain succulent karoo 20 35 37069 7414 12974 

Central Richtersveld Succulent Karoo mountain succulent karoo 25 40 100381 25095 40153 

Die Plate Succulent Karoo mountain succulent karoo 20 35 12756 2551 4465 

Doring River Succulent Karoo mountain succulent karoo 20 35 21889 4378 7661 

Eenriet Quartzite Succulent Karoo mountain succulent karoo 20 35 11132 2226 3896


Total 

Area 


(ha) 

Area 1 

(ha) 

Area 2 

(ha) 

Fish River Mountain Succulent Karoo mountain succulent karoo 15 35 5621 843 1967 

Goariep Mountain Succulent Karoo mountain succulent karoo 20 35 17077 3415 5977 

Harras Quartzite Succulent Karoo mountain succulent karoo 20 35 17810 3562 6233 

Klinghardberg Succulent Karoo mountain succulent karoo 20 35 23464 4693 8213 

Koingnaas Quartzite Succulent Karoo mountain succulent karoo 20 35 22440 4488 7854 

Nababiepsberge Desert mountain succulent karoo 15 35 137903 20685 48266 

Namaqualand Klipkoppe mountain succulent karoo 30 50 797444 239233 398722 

Namus Mountain Succulent Karoo mountain succulent karoo 20 35 47622 9524 16668 

Naroegas Quartzite Succulent Karoo mountain succulent karoo 20 35 26694 5339 9343 

Noams Mountain Desert mountain succulent karoo 20 35 171470 34294 60014 

Nuwerus Quartzite Succulent Karoo mountain succulent karoo 20 35 63877 12775 22357 

Richtersberg Mountain Desert mountain succulent karoo 20 35 51912 10382 18169 

Richtersveld Southwestern Foothills 

Succulent Karo 

mountain succulent karoo 20 35 33109 6622 11588 

Richtersveld Western Foothills Succulent mountain succulent karoo 20 35 11129 2226 3895 


Rooiberg Quartzite Succulent Karoo mountain succulent karoo 20 35 16585 3317 5805 

Rosh Pinah Mountain Succulent Karoo mountain succulent karoo 20 35 91442 18288 32005 

Rosyntjieberge Succulent Karoo mountain succulent karoo 20 35 5995 1199 2098 

Southeastern Richtersveld Quartzites mountain succulent karoo 20 35 60050 12010 21017 

Southern Richtersveld Inselbergs mountain succulent karoo 20 35 12867 2573 4503 

Southern Tanqua Mountain Succulent Karoo mountain succulent karoo 20 40 205015 41003 82006 

Southwestern Richtersveld Mountain mountain succulent karoo 20 35 15810 3162 5534 

Succulent Karoo 

Springbok Quartzite Succulent Karoo mountain succulent karoo 20 35 22253 4451 7789 

Swartruggens Sandstone Karoo mountain succulent karoo 20 35 60032 12006 21011 

Umdaus Quartzite Succulent Karoo mountain succulent karoo 20 35 40166 8033 14058 

West Gariep Desert mountain succulent karoo 15 35 142850 21427 49997 

Alexander Bay Gravel Patches quartz-gravel succulent karoo 15 35 26341 3951 9219 

Anysberg Quartz Patches quartz-gravel succulent karoo 20 35 26526 5305 9284 

Buffels River Quartz And Gravel Patches quartz-gravel succulent karoo 20 35 15686 3137 5490 

Calitzdorp Quartz Patches quartz-gravel succulent karoo 20 35 10390 2078 3636 

Concordia Quartz Patches quartz-gravel succulent karoo 20 35 832 166 291 

Eastern Bushmanland Quartz And Gravel quartz-gravel succulent karoo 20 35 165586 33117 57955 

Patches 

Eastern Richtersveld Quartz Patches quartz-gravel succulent karoo 20 35 24 5 8 

Gamoep Quartz and Gravel Patches quartz-gravel succulent karoo 20 35 55217 11043 19326 

Kamma River Quartz Patches quartz-gravel succulent karoo 20 35 8610 1722 3013 

Kliprand Gravel Patches quartz-gravel succulent karoo 20 35 117533 23507 41136 

Knersvlakte Quartzfields quartz-gravel succulent karoo 25 40 122376 30594 48950 

Koekenaap Quartz Patches quartz-gravel succulent karoo 25 40 1597 399 639 

Komkans Quartz Patches quartz-gravel succulent karoo 20 35 27295 5459 9553 

Kotzerus Quartz Patches quartz-gravel succulent karoo 20 35 4303 861 1506 

Langeberg Quartz Patches quartz-gravel succulent karoo 20 35 23799 4760 8330 

Lekkersing Quartz Patches quartz-gravel succulent karoo 20 35 53675 10735 18786 

Loeriesfontein Gravel Patches quartz-gravel succulent karoo 20 35 56944 11389 19931 

Moreskadu Quartz Patches quartz-gravel succulent karoo 20 35 8372 1674 2930 

Oernoep River Quartz Patches quartz-gravel succulent karoo 25 40 22643 5661 9057 

Olifants River Quartz Patches quartz-gravel succulent karoo 25 40 21546 5386 8618 

Oudtshoorn Quartz Patches quartz-gravel succulent karoo 20 35 10972 2194 3840 

Platbakkies Quartz and Gravel Patches quartz-gravel succulent karoo 20 35 38441 7688 13454 

Remhoogte Quartz Patches quartz-gravel succulent karoo 20 35 3336 667 1168 

Riethuis Quartzfields quartz-gravel succulent karoo 25 40 23257 5814 9303 

Steytlerville River Terraces quartz-gravel succulent karoo 20 35 32383 6477 11334 

Troe-Troe River Quartz Patches quartz-gravel succulent karoo 20 35 5018 1004 1756 

Vanwyksdorp Quartz Patches quartz-gravel succulent karoo 20 35 20919 4184 7322 

Warmwaterberg Quartz Patches quartz-gravel succulent karoo 20 35 39956 7991 13984


Total 

Area 

(ha) 

Area 1 

(ha) 


Area 2 

(ha) 

West Gariep Gravel Plains quartz-gravel succulent karoo 15 35 3909 586 1368 

Western Bushmanland Quartz and Gravel 

Patches 

quartz-gravel succulent karoo 20 35 25632 5126 8971 

Anenous Plateau Renosterveld renosterveld 20 35 17816 3563 6236 

Central Mountain Renosterveld renosterveld 25 35 132678 33169 46437 

Hantam Plateau Renosterveld renosterveld 25 40 74958 18740 29983 

Namaqualand Renosterveld renosterveld 30 50 71447 21434 35723 

Richtersveld Renosterveld renosterveld 20 35 7679 1536 2688 

Roggeveld Renosterveld renosterveld 25 40 274116 68529 109646 

Steinkopf Plateau Renosterveld renosterveld 20 35 13695 2739 4793 

Namaqualand Red Sand Plains sandveld 20 35 351439 70288 123003 

Namaqualand Sandveld Dunes sandveld 20 35 34706 6941 12147 

Namib Coastal Red Dunes sandveld 20 35 171363 34273 59977 

Namib northern Sandy Plains sandveld 20 35 228869 45774 80104 

Namib Red Sandy Plains sandveld 20 35 190622 38124 66718 

Namib Southern Sandy Plains sandveld 20 35 85608 17122 29963 

Northern Richtersveld Yellow Dunes sandveld 20 35 54675 10935 19136 

Richtersveld Red Dunes sandveld 20 35 30805 6161 10782 

Southern Richtersveld Red Dunes sandveld 20 35 22483 4497 7869 

Southern Richtersveld Yellow Dunes sandveld 20 35 33343 6669 11670 

Southern Richtersveld Yellow-Loam Dunes sandveld 20 35 27958 5592 9785 

Lamberts Bay Strandveld strandveld 20 35 38063 7613 13322 

Namaqualand Coastal Dunes strandveld 20 35 82130 16426 28745 

Namaqualand Northern Strandveld strandveld 20 35 176 35 61 

Namaqualand Pans strandveld 15 30 7068 1060 2121 

Namaqualand Southern Strandveld strandveld 20 35 10292 2058 3602 

Namaqualand White Sand Plains strandveld 20 35 47875 9575 16756 

Namib Coastal Hummock Dunes strandveld 10 10 6848 685 685 

Namib Coastal Mobile Dune Strandveld strandveld 20 35 120309 24062 42108 

Namib Coastal Strandveld strandveld 20 35 292134 58427 102247 

Namib Inland Mobile Dune Strandveld strandveld 20 35 60368 12074 21129 

Namib Inland Strandveld strandveld 20 35 101498 20300 35524 

Richtersveld White Dunes strandveld 20 35 10938 2188 2880 

Kamiesberg Mountain Brokenveld thicket 30 50 212396 63719 106198 

Hantam Karoo upland succulent karoo 15 35 718883 107832 251609 

Laingsburg-Touws Succulent Karoo upland succulent karoo 15 35 254745 38212 89161 

Roggeveld Karoo upland succulent karoo 15 35 593609 89041 207763 

Ruschia Spinosa Plains upland succulent karoo 15 35 19109 2866 6688 

Non-Succulent Karoo Vegetation Types 

Dams azonal 10 10 1882 188 0 

Lower Orange River Alluvia azonal 10 10 3255 326 326 

Bushmanland Arid Grassland desert grassland 10 10 870107 87011 87011 

Karas Arid Grasslands desert grassland 10 10 159375 15937 15937 

Karas Dune Arid Grassland desert grassland 10 10 16009 1601 1601 

Karroid Mountain Grassland desert grassland 10 10 111319 11132 11132 

Koa River Dunes desert grassland 10 10 154072 15407 15407 

Namib Central Red Sands desert grassland 10 10 88340 8834 8834 

Altimontane Fynbos fynbos 10 10 7294 729 729 

Bokkeveld Sand Fynbos fynbos 10 10 134712 13471 13471 

Boland Granite Fynbos fynbos 10 10 402 40 40 

Breede Alluvium Fynbos fynbos 10 10 22435 2243 2243 

Breede Quartzitic Fynbos fynbos 10 10 9772 977 977 

Breede Sand Fynbos fynbos 10 10 9360 936 936 

Breede Shale Fynbos fynbos 10 10 9582 958 958 

Cederberg Sandstone Fynbos fynbos 10 10 80036 8004 8004 

Ceres Alluvium Fynbos fynbos 10 10 6150 615 615


Total 

Area 


(ha) 

Area 1 

(ha) 

Area 2 

(ha) 

Coastal Granite Fynbos fynbos 10 10 1542 154 154 

Elgin Shale Fynbos fynbos 10 10 408 41 41 

Graafwater Sandstone Fynbos fynbos 10 10 3936 394 394 

Grassy Fynbos fynbos 10 10 35928 3593 3593 

Grootrivier Quartzite Fynbos fynbos 10 10 19474 1947 1947 

Hex Sandstone Fynbos fynbos 10 10 26587 2659 2659 

Hottentots Holland Sandstone Fynbos fynbos 10 10 14690 1469 1469 

Kango Fynbos fynbos 10 10 31118 3112 3112 

Kouebokkeveld Shale Fynbos fynbos 10 10 5914 591 591 

Kouga-Kamanassie Sandstone Fynbos fynbos 10 10 113907 11391 11391 

Langeberg Sandstone Fynbos fynbos 10 10 180199 18020 18020 

Langeberg Shale Fynbos fynbos 10 10 7545 754 754 

Leipoldtville Sand Fynbos fynbos 10 10 51032 5103 5103 

Matjiesfontein Quartzite Fynbos fynbos 10 10 123233 12323 12323 

Matjiesfontein Shale Fynbos fynbos 10 10 9958 996 996 

Olifants Sandstone Fynbos fynbos 10 10 29 3 3 

Outeniqua Sandstone Fynbos fynbos 10 10 37076 3708 3708 

Sonderend Sandstone Fynbos fynbos 10 10 47779 4778 4778 

Southeastern Montane Fynbos fynbos 10 10 135504 13550 13550 

Swartberg Conglomerate Fynbos fynbos 10 10 37817 3782 3782 

Swartberg Mesic Sandstone Fynbos fynbos 10 10 5048 505 505 

Swartberg Sandstone Fynbos fynbos 10 10 279704 27970 27970 

Swartruggens Quartzite Fynbos fynbos 10 10 165225 16523 16523 

Swellendam Silcrete Fynbos fynbos 10 10 11651 1165 1165 

Volcanic Fynbos fynbos 10 10 906 91 91 

Winterhoek Sandstone Fynbos fynbos 10 10 6984 698 698 

Aliwal North Dry Grassland mesic grassland 10 10 68308 6831 6831 

Moist Mountain Grassland mesic grassland 10 10 14856 1486 1486 

Bushmanland Basin nama karoo 10 10 425458 42546 42546 

Bushmanland Vloere nama karoo 10 10 43842 4384 4384 

Camdebo-Aberdeen Karoo nama karoo 10 10 690377 69038 69038 

Central Karroid Koppies nama karoo 10 10 1397 140 140 

Eastern Gwarrieveld nama karoo 10 20 181700 18170 36340 

Eastern Lower Karoo nama karoo 10 10 243001 24300 24300 

Eastern Upper Karoo nama karoo 10 10 111170 11117 11117 

Gariep Desert Plains nama karoo 10 10 86621 8662 8662 

Gariep Stony Desert nama karoo 10 10 186346 18635 18635 

Great Karoo nama karoo 10 10 2014000 201400 201400 

Huib Hoch Escarpment Nama Karoo nama karoo 10 10 88656 8866 8866 

Huib Hoch Mountain Desert nama karoo 10 10 145286 14529 14529 

Huib Hoch Plateau Nama Karoo nama karoo 10 10 786029 78603 78603 

Karas Nama Karoo nama karoo 10 10 643397 64340 64340 

Karas Sandy Plains nama karoo 10 10 134254 13425 13425 

Karas Stony Desert nama karoo 10 10 431993 43199 43199 

Karas Upland Nama Karoo nama karoo 10 10 178425 17843 17843 

Kristalberge Mountain Desert nama karoo 10 10 16947 1695 1695 

Noorsveld nama karoo 10 10 4518 452 452 

Northeastern Gwarrieveld nama karoo 10 10 139981 13998 13998 

Nuweveld Escarpment Karoo nama karoo 10 10 159332 15933 15933 

Southeastern Karoo Kalkveld nama karoo 10 10 132314 13231 13231 

Southern Karoo Alluvia nama karoo 10 10 526127 52613 52613 

Swartkloofberg Desert nama karoo 10 10 54307 5431 5431 

Western Karoo Hardeveld nama karoo 10 10 170634 17063 17063 

Western Upper Karoo nama karoo 10 10 233865 23387 23387 

Namib Desert Erg namib desert 10 10 160950 16095 16095 

Namib Desert Erg Inland Dunes namib desert 10 10 40934 4093 4093 

Namib Desert Erg Linear Dunes namib desert 10 10 62861 6286 6286


Total 

Area 


(ha) 

Area 1 

(ha) 

Area 2 

(ha) 

Namib Desert Inland Red Dune namib desert 10 10 204817 20482 20482 

Namib Desert Inselbergs and Gravel Plains namib desert 10 10 211582 21158 21158 

Namib Desert Red Sands namib desert 10 10 21963 2196 2196 

Namib Desert Sandy Plains namib desert 10 10 647084 64708 64708 

Breede Alluvium Renosterveld renosterveld 10 10 62316 6232 6232 

Breede Shale Renosterveld renosterveld 10 10 87275 8728 8728 

Ceres Renosterveld renosterveld 10 10 1536 154 154 

Ceres Shale Renosterveld renosterveld 10 10 17275 1727 1727 

Coastal Granite Renosterveld renosterveld 10 10 1923 192 192 

Eastern Renosterveld renosterveld 10 10 8524 852 852 

Kango Renosterveld renosterveld 10 10 47741 4774 4774 

Langkloof Shale Renosterveld renosterveld 10 10 62794 6279 6279 

Matjiesfontein Shale Renosterveld renosterveld 10 10 195494 19549 19549 

Montagu Shale Renosterveld renosterveld 10 10 125792 12579 12579 

Mossel Bay Shale Renosterveld renosterveld 10 10 3438 344 344 

Niewoudtville Dolerite Renosterveld renosterveld 10 10 11822 1182 1182 

Ruens Shale Renosterveld renosterveld 10 10 4395 440 440 

Shale Renosterveld Communities renosterveld 10 10 21996 2200 2200 

Swartberg Shale Renosterveld renosterveld 10 10 35206 3521 3521 

Uniondale Renosterveld renosterveld 10 10 71003 7100 7100 

Vanrhynsdorp Shale Renosterveld renosterveld 10 10 84273 8427 8427 

Villiersdorp Shale Renosterveld renosterveld 10 10 273 27 27 

Karas Arid Savanna savanna 10 10 253444 25344 25344 

Albany Succulent Thicket thicket 10 10 3451 345 345 

Baviaansklook-Gamtoos Thicket thicket 10 10 23748 2375 2375 

Camdebo Succulent Thicket thicket 10 10 483339 48334 48334 

Gouritz Valley Thicket thicket 10 10 2103 210 210 

Sundays Succulent Thicket thicket 10 10 203025 20302 20302 

Western Spekboomveld thicket 10 10 211459 21146 21146

Table 34: Targets set for expert-identified areas 

Expert Area Taxonomic Total Area Target Target 

Unique ID Group (ha) 

(%) (ha) 

ao8 amphibian 6717 75 5037 

ao4 amphibian 30284 25 7571 

ao9 amphibian 34452 12 4134 

ao2 amphibian 55495 12 6659 

ao10 amphibian 67795 6 4067 

ao5 amphibian 88611 6 5316 

ao7 amphibian 138275 3 4148 

ao3 amphibian 210799 3 6323 

ao6 amphibian 327837 3 9835 

ao1 amphibian 504847 3 15145 

b12 birds 3421 100 3421 

b10 birds 3677 100 3677 

b11 birds 3882 100 3882 

b1 birds 6591 75 4943 

b22 birds 9106 50 4553 

b17 birds 15544 50 7772 

b7 birds 17172 25 4293 

b5 birds 24980 25 6245 

b19 birds 44992 12 5399 

b13 birds 45895 12 5507 

b15 birds 68174 6 4090 

b3 birds 97668 6 5860 

b8 birds 126307 6 7578 

b4 birds 133136 3 3994 

b14 birds 158593 3 4757 

b18 birds 203040 3 6091 

b16 birds 235518 3 7065 

b21 birds 246568 3 7397 

b20 birds 357791 3 10733 

b2 birds 385147 3 11554 

b6 birds 2089605 3 62688 

f4 fish 1255 100 1255 

f9 fish 2521 100 2521 

f10 fish 5855 75 4391 

f7 fish 14173 50 7086 

f2 fish 16430 50 8215 

f3 fish 18550 25 4637 

f5 fish 27073 25 6768 

f8 fish 39462 12 4735 

f11 fish 56014 12 6721 

f12 fish 58834 12 7060 

f1 fish 92727 6 5563 

f6 fish 97593 6 5855 

ig2 insects 35022 12 4202 

ig8 insects 135090 3 4052 

ig14 insects 191289 3 5738 

ig10 insects 191299 3 5738 

ig13 insects 198554 3 5956 

ig19 insects 215446 3 6463 




(%) (ha) 

ig18 insects 269415 3 8082 

ig7 insects 294886 3 8846 

ig12 insects 326561 3 9796 

ig9 insects 439779 3 13193 

ig11 insects 451376 3 13541 

ig1 insects 463247 3 13897 

ig17 insects 525048 3 15751 

ig6 insects 1008513 3 30255 

ig20 insects 1239843 3 37195 

ig16 insects 1798329 3 53949 

JI33 invertebrates 16 100 16 







































Mg5 Mammals 1783 100 1783 

Mg7 Mammals 2864 100 2864 

Mg6 Mammals 3260 100 3260 




(%) (ha) 

Mg8 Mammals 25946 25 6486 

Mg3 Mammals 38385 12 4606 

Mg2 Mammals 89343 6 5360 

Mg10 Mammals 1365008 3 40950 

Mg9 Mammals 2307204 3 69216 

Mg1 Mammals 3817568 3 114527 

gw5 plants 429 100 429 

gw15 plants 558 100 558 

pgd40 plants 833 100 833 

gw6 plants 926 100 926 

ms6 plants 990 100 990 

gw10 plants 1199 100 1199 

gw9 plants 1499 100 1499 

gw21 plants 1703 100 1703 

pgd23 plants 1876 100 1876 

pgd10 plants 2126 100 2126 

vp5 plants 2184 100 2184 

pgd4 plants 2267 100 2267 

pgd1 plants 2366 100 2366 

vp2 plants 2886 100 2886 

pgd41 plants 3732 100 3732 

gw13 plants 4016 75 3012 

gw7 plants 4125 75 3093 

vp6 plants 4331 75 3248 

ms2 plants 4402 75 3301 

gw17 plants 4484 75 3363 

pgd35 plants 4780 75 3585 

vp27 plants 5202 75 3901 

pgd12 plants 5461 75 4095 

pgd28 plants 5595 75 4196 

ms4 plants 5647 75 4235 

ms5 plants 5772 75 4329 

pgd25 plants 5833 75 4374 

pgd33 plants 6080 75 4560 

pgd5 plants 6187 75 4640 

pgd3 plants 6525 75 4893 

vp23 plants 6607 75 4955 

vp10 plants 6741 75 5055 

vp19 plants 6940 75 5205 

pgd18 plants 7019 75 5264 

pgd8 plants 7367 75 5525 

vp4 plants 7455 75 5591 

vp20 plants 7801 75 5850 

pgd34 plants 7988 75 5991 

pgd32 plants 8051 50 4025 

pgd29 plants 8076 50 4038 

pgd7 plants 8194 50 4097 

pgd6 plants 8571 50 4285 

ms9 plants 8761 50 4380 

vp25 plants 8817 50 4408 

pgd39 plants 8962 50 4481 

ms1 plants 9146 50 4573 




(%) (ha) 

pgd9 plants 9479 50 4739 

pgd16 plants 10027 50 5013 

gw19 plants 10201 50 5100 

vp24 plants 11270 50 5635 

pgd17 plants 11307 50 5653 

vp8 plants 11417 50 5708 

pgd26 plants 11826 50 5913 

vp15 plants 12270 50 6135 

vp3 plants 12484 50 6242 

pgd36 plants 12567 50 6283 

vp22 plants 12806 50 6403 

gw18 plants 13859 50 6929 

pgd37 plants 14193 50 7096 

ms7 plants 14956 50 7478 

gw12 plants 15133 50 7566 

ms3 plants 15477 50 7738 

gw2 plants 16431 50 8215 

gw11 plants 16491 50 8245 

vp14 plants 16513 50 8256 

gw20 plants 17264 25 4316 

pgd13 plants 17734 25 4433 

pgd30 plants 19675 25 4918 

gw4 plants 19784 25 4946 

gw3 plants 21467 25 5366 

gw1 plants 21751 25 5437 

pgd38 plants 22245 25 5561 

pgd2 plants 22553 25 5638 

vp18 plants 24218 25 6054 

vp1 plants 24302 25 6075 

gw16 plants 24307 25 6076 

vp7 plants 25350 25 6337 

pgd31 plants 26896 25 6724 

pgd27 plants 27450 25 6862 

gw8 plants 27806 25 6951 

pgd11 plants 28096 25 7024 

vp21 plants 31421 25 7855 

ms8 plants 32591 25 8147 

pgd15 plants 33734 12 4048 

vp11 plants 35092 12 4211 

pgd20 plants 36267 12 4352 

vp16 plants 37195 12 4463 

pgd22 plants 44411 12 5329 

vp9 plants 45102 12 5412 

pgd21 plants 45239 12 5428 

nam8 plants 50334 12 6040 

nam5 plants 56211 12 6745 

vp12 plants 58462 12 7015 

nam2 plants 58673 12 7040 

nam1 plants 62680 12 7521 

nam4 plants 65907 6 3954 

pgd19 plants 66795 6 4007 

ms10 plants 68711 6 4122 




(%) (ha) 

pgd24 plants 75443 6 4526 

nam6 plants 76127 6 4567 

vp26 plants 97104 6 5826 

vp17 plants 109334 6 6560 

pgd14 plants 165337 3 4960 

ms11 plants 193053 3 5791 

nam3 plants 199413 3 5982 

nam7 plants 220209 3 6606 

vp13 plants 227178 3 6815 

r14 reptiles 3609 100 3609 

r7 reptiles 3642 100 3642 

r2 reptiles 11526 50 5763 

r11 reptiles 18480 25 4620 

r3 reptiles 18646 25 4661 

r1 reptiles 25386 25 6346 

r12 reptiles 25855 25 6463 

r10 reptiles 27617 25 6904 

r5 reptiles 42955 12 5154 

r4 reptiles 56033 12 6723 

r18 reptiles 58756 12 7050 

r8 reptiles 70519 6 4231 

r6 reptiles 94035 6 5642 


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Part E: Appendices 

THESE ARE AVAILABLE IN A SEPARATE DOCUMENT 

• Appendix 1: Magical Mesembs: Floral Fantasies of a Parched Paradise, by 

Gideon Smith 

• Appendix 2: The SKEP Planning Domain: Documentation of the Decision 

Process, March 2002 

• Appendix 3: Expert mapping 

• Appendix 4: Freshwater Fishes of the Succulent Karoo Biome: Distribution, 

Conservation Status, Hotspots and Associated Conservation Issues, by N.D. 

Impson, A. Abrahams and A. Turner. 

• Appendix 5: Descriptions of the nine geographic priority areas for conservation 

action identified by SKEP 

• Appendix 6: Biodiversity Advisory Group agendas and minutes 

• Appendix 7: Biodiversity Component Workshop 1, 22 January 2002 

• Appendix 8: SKEP data acquisition table 

• Appendix 9: SKEP data request, data extraction tutorial and data agreement 

• Appendix 10: SKEP data dictionary 

• Appendix 11: Stakeholder mapping 

• Appendix 12: SKEP Process Focus Group Proceedings, 4 April 2002 

• Appendix 13: Biodiversity Component workshop 2, 24-25 June 2002 

• Appendix 14: Products for Action Planning Workshops

Succulent Karoo Ecosystem Plan: Technical Report - bgis-sanbi

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