Picking up the pieces: a biosphere reserve frameworkfor a fragmented landscape ± The Coastal Lowlandsof the Western Cape, South Africa

C.E. HEIJNIS1;�, A.T. LOMBARD2, R.M. COWLING2 and P.G. DESMET2

1Percy FitzPatrick Institute for African Ornithology, Zoology Department, University of Cape Town,

Rondebosch 7701, South Africa; 2Institute for Plant Conservation, Botany Department, University of

Cape Town, Rondebosch 7701, South Africa; � Present address: Institute for Plant Conservation,

Botany Department, University of Cape Town, Rondebosch 7701, South Africa

Received 21 April 1998; accepted in revised form 8 July 1998

Abstract. The coastal lowlands of the Western Cape (CLWC) form part of the fynbos biome, an

area renowned for its high levels of plant diversity and endemism. The vegetation of the CLWC has

been severely reduced and fragmented, and is currently impacted on by agricultural, pastoral,

coastal resort and urban development, as well as alien plant spread. Furthermore, most of the

vegetation communities are under-represented within existing protected areas. In response to this

urgent need for increased conservation e�orts, an initiative to establish a UNESCO-MAB bio-

sphere reserve in the area has been launched. The aim of this project was to use biological criteria to

identify areas that could potentially contain the core areas and bu�er zones of a biosphere reserve.

A reserve selection algorithm was chosen which provides a ¯exible tool for selecting representative

areas for protection. The algorithm is a step-wise heuristic, which has rules for including mandatory

polygons, forcing adjacency, including desirable (e.g. Red Data Book plant species) and excluding

undesirable features (e.g. bisection by major roads). Farm boundaries (cadastral units) were used as

selection units, resulting in a total of 1 717 parcels. The selection process was conducted three times

with target areas set at 10% , 25% and 50% of the original extent of each vegetation type within the

study area. Areas of 62 834ha, 121 199ha and 242 397ha, respectively, or 36% , 49% and 76% of

the available land in the study area being selected. It is recommended that the area identi®ed as the

50% target area be considered the future site of core areas and bu�er zones for the proposed

biosphere reserve. The algorithm successfully maintained a high degree of connectivity between

selected areas. This is important considering the high levels of plant beta diversity associated with

edaphic gradients. Rather than presenting a de®nitive reserve system, this study provides a tool

allowing biological criteria to be included explicitly within the negotiation process. As the biosphere

reserve is assembled, priorities can be re-assessed.

Key words: conservation planning, fragmented landscape, fynbos, South Africa

Introduction

The coastal lowlands of the Western Cape (CLWC) form part of the Cape

Floristic Region (CFR) (Bond and Goldblatt 1984). The CFR has one of the

highest plant species densities and levels of endemism for any temperate or

tropical continental region (Linder 1985; Major 1988; Cowling et al. 1989;

Biodiversity and Conservation 8: 471±496, 1999.Ó 1999 Kluwer Academic Publishers. Printed in the Netherlands.

Cowling and Holmes 1992). It is recognised as one of the world's hottest `hot-

spots' of plant diversity and endemism (Myers 1990). Agricultural, pastoral,

coastal resort and urban development, as well as the rapid spread of alien plant

species constitute the major threats to biodiversity in the CLWC (McDonald

1988; Azorin 1992; Deacon et al. 1992; Rebelo 1992; Richardson et al. 1992).

These factors have already caused extensive fragmentation of the natural

vegetation, and consequently, much of the remaining natural vegetation exists

in the form of habitat remnants (Boucher 1981; Cowling et al. 1986; Rebelo

1996a). The CLWC have high potential for the generation of income from

ecotourism, but this requires that the area is managed properly and that a

representative protected area system is established (Siegfried 1989).

The urgent need for timely conservation action in the CLWC has been

acknowledged by landowners, conservation bodies, local and provincial

administrative bodies and other stakeholders alike. In 1996, Cape Nature

Conservation, the statutory body responsible for environmental management

and conservation in the Western Cape Province, made a policy decision to

adopt the biosphere reserve approach to in situ conservation advocated by the

UNESCO Man and the Biosphere (MAB) Programme. This approach incor-

porates ecosystem management and human development into a regional con-

text. It advocates the establishment of a multiple use network of areas,

including one or more strictly delineated and protected core areas, surrounded

by less strictly protected bu�er zones, both enveloped within a series of

transitions zones (see UNESCO 1984; 1995; Batisse 1986; Vernhes 1987;

Wells and Brandon 1993; McNeely 1994; Rojas and McNeely 1995). Cape

Nature Conservation is attempting to establish one such reserve in a portion of

the CLWC.

The key question that arises is the siting of the biosphere reserve within

the CLWC, and more speci®cally, the position and relative sizes of the zones

that comprise a biosphere reserve. Thus, the objectives of this study were

twofold. First, to develop a set of databases and a unifying methodology which

could be used by nature conservationists and planners for negotiations,

planning and establishment of the biosphere reserve, and its future manage-

ment. Then to use these tools to identify a system of areas which could form

the bu�er zones and core areas of the proposed biosphere reserve on biological

grounds, which would: (i) adequately conserve the major habitats (vegetation

types); (ii) maintain contiguity between and within vegetation types;

(iii) preclude tracts of land invaded by high density alien plant species, trans-

formed land and small isolated reserves where possible; (iv) conserve as many

rare and endemic plant species as possible, and (v) provide ¯exibility for

the development of new conservation priorities as the biosphere reserve

develops.

472

Methods

Study area

The study area comprises 4 854 km2 or some 40% of the coastal lowlands of the

Western Cape (Figure 1). The physiography of the area is relatively simple

consisting of a low-lying (<200m), gently undulating coastal plain broken in

the south-east by a series of low granitic hills (<700m). Soils found at the

coast are recent, calcareous and coarse-grained sands derived from recent

marine sediments, grading to older, more acidic, ®ne-grained sands inland

(Lambrechts 1981; Rebelo 1996a). Ancient (pre-Cape) meta-sedimentary shales

of the Malmesbury group underlie most of the eastern (inland) part of the

study area. Soils derived from these rocks are duplex (sandy loams over clay),

base-saturated and clayey (Lambrechts 1981; Rebelo 1996b). The area has a

mediterranean-type climate with mild (ca. 12 �C) wet winters and warm (ca.

24 �C) dry summers (Nieman 1981). Rainfall ranges between 150mm á y)1 in

the north to 400mm á y)1 in the south (Nieman 1981). As a result of this

relatively steep moisture gradient (ca. 2.5mm á kmÿ1) and the high diversity of

soil types, the area supports a high diversity of vegetation types and plant

species (Jarman 1986; Boucher 1987). Further details on the geology, geo-

morphology, hydrology and soils of the coastal lowlands of the Western Cape

are given in Rogers (1981), Deacon et al. (1983), Lambrechts et al. (1986),

Boucher (1987) and King (1988).

Three main vegetation types occur in the study area: Dune Thicket, Sand

Plain Fynbos (West Coast), and West Coast Renosterveld. Dune Thicket in the

study area occurs in a coastal strip on recent calcareous dune sands, calcretes

and Tertiary limestones, while Sand Plain Fynbos, a sclerophyllous, ®re-prone

shrubland, is found predominantly on old (early Pleistocene to Tertiary), ®ne-

grained acidic soils. West Coast Renosterveld is con®ned largely to the ®ne-

textured soils derived from the Malmesbury Group Shales, Cape Granite Suite

and Klipheuwel Formation Shales (Tansley 1982; Rebelo 1996a). Only 6% of

Renosterveld and 14% of fynbos in the CLWC were untransformed in 1981

(Boucher 1981). Renosterveld is currently the most poorly protected with

<10% of extant vegetation or <5% of its original extent in both the west and

south-western Cape being conserved (Rebelo 1992). The conservation status of

Dune Thicket in the Western Cape is slightly better, with 14% falling within

current protected areas. Only 1% of Sand Plain Fynbos in the Western Cape

falls within existing protected areas (Rebelo 1996a). These main vegetation

types comprise eight sub-categories in the study area (Figure 2). These sub-

categories, delineated on the basis of an unpublished map prepared by

C. Boucher (University of Stellenbosch) ca. 1970, di�erentiate between plant

communities occurring on di�erent substrata, at di�erent altitudes and along

473

Figure 1. Indigenous vegetation types, including undi�erentiated water-bodies (wetlands, vleis,

lakes and pans) in the study area. The key describes the vegetation type and its code. The insert

shows the location of the study area within the Cape Floristic Region and South Africa.

474

Figure 2. Land use and alien plant density in the study area.

475

di�erent points of hydrological gradients (Boucher 1987, 1997 and R.M.

Cowling pers. com.). As such, these sub-categories are more representative of

plant biodiversity in the area than using the three undi�erentiated vegetation

types, and provide an adequate surrogate for ¯oristic variation. These vege-

tation categories are detailed in Appendix 1 and will henceforth be referred to

as vegetation types.

Data

Thirteen themes of spatial data were used in the study: the nine vegetation

types and undi�erentiated waterbodies (i.e. dams, ¯ood-plain-areas, pans and

vleis) (Figure 1); alien vegetation and land use (Figure 2); endemic Proteaceae

and Red Data plant species, current farm parcels (cadastral units), protected

areas and state-owned land (Figure 3); magisterial districts; railways and

roads. The data comprising the vegetation types theme were digitised from a

1 : 100 000 map prepared by C. Boucher ca. 1970, ground-truthed by one of us

(PGD) in 1997. The alien vegetation and land use were delineated on 1 : 50 000

topographic maps (Chief Directorate: Surveys and Land Information) and

digitised into a geographic information system (GIS: ARC/INFO versions

3.4D+ and 6.1.1). The boundaries of these themes were identi®ed using

photographs taken from a light aircraft during the course of this study. Where

cover of the area was not absolute, older aerial and orthophotographs were

also used. These photographs were used at two scales, 1 : 50 000 and 1 : 10 000.

The degree of alien plant infestation was rated as either low (scattered), me-

dium or high (closed canopy). Cape Nature Conservation supplied digital in-

formation detailing the location and extent of all municipal, provincial and

national reserves in the area. The extent and location of all private reserves in

the area augmented this data set. The latter data were obtained separately from

Cape Provincial Administration and delineated on 1 : 50 000 topographical

maps and digitised as detailed above. The main portion of the themes com-

prising water-bodies, railways and roadways, state-owned land and magisterial

districts were purchased in digital format at a scale of 1 : 50 000 from the Chief

Directorate: Surveys and Land Information, but were also augmented by

digitising relevant features from the topographical maps listed above. Addi-

tional information concerning state-owned land was obtained from the Cape

Town City Council, delineated on 1 : 50 000 maps and digitised. Records of the

distribution of Red Data plant species in the study area were provided by Cape

Nature Conservation. The place names of these records were transposed onto

1 : 50 000 topographical maps as point localities and digitised into the GIS.

Additional information regarding species distributions was obtained from

R.M. Cowling, J. Manning and P. Goldblatt. Records of Proteiod species were

obtained from the Protea Atlas Project at the University of Cape Town,

476

Figure 3. Cadastral units (farm boundaries), endemic Red Data and Proteaceae plant species,

protected areas and state-land in the study area.

477

through A.G. Rebelo of the National Botanical Institute. Henceforth, both

data sets will be referred to collectively as the plant species theme. The ca-

dastral units theme was purchased in digital format at a scale of 1 : 50 000 from

the Chief Directorate: Surveys and Land Information, but was augmented with

data obtained from the south-western Cape ENPAT (Environmental Potential

Atlas) digital database prepared by the Department of Environmental A�airs

and Tourism (1996).

Cadastral units (current farm parcels) were chosen as selection units for area

prioritisation. Where no cadastral data were available, in the south, part of the

Greater Cape Town Metropolitan area, a 2:5� 3 km grid was generated and

inserted (this size corresponded to the mean size of farms in the area). The

study area comprised a total of 1 717 cells with a mean size of 2.8 km2. Five

cadastral unit themes (alien vegetation, land use, protected areas, state land,

vegetation types and water bodies) were used to classify each cadastral unit,

according to the features they represent. Thus, each cadastral unit was desig-

nated a value for alien plant density, land-use type, protected area status, state-

land status and vegetation type corresponding to the identity of the majority of

each feature within the unit. The magisterial districts, railways, rivers, roads,

water bodies and the plant species themes were contained in four separate

digital maps as lines, a separate polygon-form and point-form digital map,

respectively. A Gause Conformal Conic projection centred on 18� longitude

was used for all analyses which were performed using either Arc View V3, or

Arc/INFO versions 3.4D+ and 6.1.1. (Environmental Systems Research

Institute, Redlands, California).

Core area and bu�er zone selection

The total extent of the study area was 485 410 ha. All cultivated or developed

land was considered unavailable for conservation. However, cultivated land in

protected areas or state-owned land was considered restorable and therefore

available for consideration. All land under low or medium density alien plants

was also considered restorable (Azorin 1992; Holmes and Cowling 1997). Land

under high density alien plants was considered non-restorable since these areas

were most likely to have the longest history of invasion (cf. Holmes and

Cowling 1997). Again, land invaded by high density alien plants within pro-

tected areas or state-owned land was considered available for conservation as

these are usually priorities in clearing programmes (D.M. Richardson pers.

comm.). All areas considered unsuitable for conservation, and thus unavailable

according to these criteria, were excluded from the database (the remaining set

formed the base from which speci®c core areas and bu�er zones were selected).

The available set comprised 170 361 ha or 35% of the study area, after it was

`split' into cadastral units and 177 546 ha or 37% of the study area when no

478

cadastral units were considered (Figures 4a and b, respectively). Unless oth-

erwise indicated, results were obtained considering the area in terms of ca-

dastral units. Cultivated land accounted for 56% of the excluded area, while

developed areas and high density aliens accounted for 2% and 7%, respec-

tively. For each vegetation type Figure 5 details the proportions of available,

cultivated, developed land; land invaded by high density alien plants; and land

currently owned by the state or included in protected areas. Salvia Lowland

Sand Plain Fynbos (LPSPF) had the highest proportion of available land (88%

of total area), while West Coast Renosterveld (WCR) had the lowest (3% of

total area). Proteoid Lowland Sand Plain Fynbos (PLSPF) had the highest

proportion of high density alien plant species (15%), closely followed by Dune

Thicket±Lowland Fynbos Transitional Veld (DT-LF) (14%) and Dune

Thicket on mobile to semi-mobile sand (DTS) (13%).

To expedite the process of establishing reserve systems, setting explicit tar-

gets for conservation requires negotiation and compromise between all stake-

holders (Pressey in press). Historically, particularly in South Africa, decisions

have been either the providence of the political or the conservation lobbies,

resulting in dissatisfaction whatever the outcome. This project is one of the ®rst

in the country that is attempting to unite the two often mutually exclusive

demands into a compromise acceptable to both. Consequently, three targets of

10%, 25% and 50%, of the original extent of each vegetation type in the study

area were decided upon (Table 1). While these may seem excessively high, it is

imperative to remember that the study area comprises only some 40% of the

CLWC. Thus 40% of this area actually only amounts to some 20±30% of the

original extent of the total lowlands. This complies with the minimum of 10%

suggested by Myers (1979) and subsequently endorsed by Rebelo (1997).

To achieve the targets for each vegetation class, speci®c areas (polygons

made up of cadastral units) were prioritised. Area prioritisation was conducted

using a simple heuristic algorithm based on iterative selection algorithms

commonly found in the literature (Vane-Wright et al. 1991; Bedward et al.

1992; Rebelo and Siegfried 1992; Margules and Meyers 1993, Nicholls and

Margules 1993; Pressey et al. 1995; Willis et al. 1996). The algorithm was a

stepwise heuristic comprising a series of rules designed to represent the nom-

inated target area for each vegetation class in the smallest possible area of

contiguous cadastral units. Areas were selected according to the following

objectives (after Lombard et al. 1997): (i) that the total area prioritised within

each vegetation class was the smallest possible (within the constraints of the set

targets); (ii) that it included as many contiguous vegetation types as possible

(thereby maximising regional-scale plant species diversity ± see Cowling 1990);

(iii) that as few undesirable (e.g. roads, towns) and as many desirable features

(e.g. rivers, wetlands) as possible were included; and (iv) that as many known

recorded populations of endemic plant species were included. To simplify the

479

Figure 4. Land available for conservation in the study area both (a) with and (b) without `splitting'

the area into cadastral units. `Available' land is the area remaining in the study area after the

exclusion of areas infested with high density alien plants and all developed land not in protected

areas nor state-land.

480

heuristic procedure and maintain ecosystem integrity within each of the veg-

etation types, the selection procedure was performed separately for each veg-

etation type.

The algorithm had the following rules, the choice and application of which

are explained below:

Rule 1: mandatory cadastral units(s);

Rule 2: cadastral unit(s) adjacent to mandatory cadastral units;

Rule 3: cadastral unit(s) adjacent to other available cadastral unit(s) of the

same vegetation type;

Rule 4: cadastral unit(s) adjacent to available cadastral unit(s) of other

vegetation type(s);

Rule 5: exclude cadastral unit(s) less than 5 ha in size surrounded by un-

available land;

Rule 6: cadastral unit(s) adjacent to the coast;

Rule 7: cadastral unit(s) with the next underrepresented unique features;

Rule 8: exclude cadastral unit(s) adjacent to unavailable land;

Rule 9: exclude cadastral unit(s) bisected by major road(s) or railway(s);

Rule 10: exclude cadastral unit(s) bisected by lines delimiting magisterial

districts.

Cadastral units comprising either protected areas or state-land were considered

mandatory for three reasons: (i) state-land is often not used by the general

public and usually forms the basis for future reserve sites (C. Burgers pers.

Figure 5. Original areas of vegetation types within the study area, showing the proportion of each

type which is available for conservation, has been developed or infested by high density alien plants

and is currently within protected areas and/or state-land. Vegetation codes are described in Table 1

and Appendix 1.

481

Table

1.Areaselectiontargetsfortheeightvegetationtypes

inthecoastallowlandsoftheWestern

Cape.Target

areasare

given

aspercentages

oftheoriginal

extentofthevegetationtypes

within

thestudyarea.Bold

target

areasindicate

vegetationtypes

wheretheselectionalgorithm

could

beapplied.Italicised®gures

indicate

wherethetarget

areafellwithin

existingprotected

areasorstate-land.Allareasare

reported

inhaandapply

tothestudyarea`split'into

cadastral

units.

Vegetationtype

Vegetation

code

Totalareain

thestudyarea

Totalareaavailable

forconservation

Areain

state-land

and/orprotected

areas

10%

Target

area

25%

Target

area

50%

Target

area

DuneFields(M

obilesands)

DF

4834

2347

1719

483

1208

2417

WestCoast

DuneThicket

(Strandveld)

DT

88999

42193

19295

8899

22249

44499

WestCoast

DuneThicket

(Strandveld)

DTG

32095

5642

1400

3209

8023

16047

WestCoast

DuneThicket

(Strandveld)±Lowland

FynbosTransitionalVeld

DT-LF

42970

37367

13556

4296

10742

21484

WestCoast

DuneThicket

(Strandveld)onmobileto

semi-mobilesandorSouth

Coast

DuneStrandveld

DTS

15884

12026

6175

1588

3971

7942

ProteiodLowlandSandPlain

Fynbos

PLSPF

79871

15996

155

7987

19967

39935

Salvia

LowlandSandPlain

Fynbos

SLSPF

56191

49794

4627

5619

14047

28095

WestCoast

Renosterveld

WCR

164566

4995

4005

16457

41142

82283

Totals

485410

170361

50934

48538

121349

242702

482

comm.); (ii) it is essential to incorporate existing protected areas within the

selected set; and (iii) the status or quality of the vegetation contained within

protected areas or state-land is often far superior to that outside. These

mandatory cadastral units provided the starting point for the algorithm. All

subsequent rules were applied in sequence, with rules lower in the list being

used only as needed, either to resolve ties or to obtain selected areas within 2%

of target limits.

In order to maximise the contiguity of the resulting protected area system and

to minimise the number of isolated cadastral units selected, adjacency was one

of the primary underlying tenets of the algorithm. To facilitate application of the

adjacency rules (rules 2±4, 6 and 8), each cadastral unit in the available set was

coded on the basis of the features of the cadastral units adjacent to it. Features

used were: coast; protected areas, other vegetation types; same vegetation type;

state-land; and, unavailable land (cultivated and developed areas, and those

infested with high density alien plants). Rules 2±4 acted as ®lters, narrowing the

action of subsequent rules to adjacent cadastral units wherever possible. Rule 5

ensured that very small (<5 ha) or isolated cadastral units were excluded from

the ®nal selection. Rule 6 was used only where applicable, i.e. where vegetation

types abutted the coast. Rule 7 served to select cadastral units with unique

features, including the presence of endemic plant species, and the presence of

rivers, vleis, or wetlands from the group chosen by rules 1±5. These features were

used in a stepwise fashion. Three additional exclusion rules ± rules 8, 9 and 10

were used a posteriori to modify the design of the resultant set of cadastral units.

As conservation of small reserves in South Africa usually becomes the respon-

sibility of the local authorities, rule 10 serves to minimise the number of po-

tential administering bodies. Once chosen, a site was considered nominally

conserved as were its features and was removed from the subsequent analyses

along with its attributes, so that selected areas complemented each other.

The size of the area available for consideration precluded the use of sensi-

tivity analyses usually conducted as part of reserve selection procedures (e.g.

Bedward et al. 1992; Pressey et al. 1994; Willis et al. 1996; Lombard et al.

1997). The algorithm devised was speci®cally designed to prioritise areas in a

highly fragmented landscape for inclusion within a contiguous protected area

system. Consequently, the number of outcomes of the selection procedure was

restricted as was its ¯exibility (Pressey et al. 1993). Although it is often in-

structive to compare selection procedures run with and without including ex-

isting reserve systems as mandatory cells or cadastral units (e.g. Pressey and

Nicholls 1989, 1991; Nicholls and Margules 1993), such an exercise would have

been of little value here owing to the paucity of land available for conservation

in the study area.

483

Results

The area systems identi®ed with the 10%, 25% and 50% targets are given in

Figures 6a, b and c, respectively. With a 10% target, areas selected comprised

a total of 62 834 ha (248 cadastral units), encompassing 36% of the available

land in the study area (Figure 6a, Tables 2 and 3). DT formed the bulk of the

selected area (19 295 ha or 31%), while DF contributed the smallest proportion

(1 720 ha or 3%). The selected system contained 60 of the 83 Red Data Book

plant species and 661 of the 1 791 Red Data Book plant species' occurrences.

SLSPF (Salvia Lowland Sand Plain Fynbos) had the highest density of species

and species' occurrences per unit area (30 and 364, respectively), while DF had

the lowest (1 and 3, respectively). The areas identi®ed for the 25% and 50%

targets comprised 121 199 ha (419 cadastral units) and 242 397 ha (610 cadas-

tral units), respectively (Figures 6b and c, Table 2). That is 49% and 76% of

the available land in the study area. Again, DT formed the bulk of these areas,

comprising 27% and 33% of the area selected with the 25% and 50% targets

respectively. Similarly, DF had the least area selected in both target area sce-

narios, with 1 720 ha and 2 347 ha, or 1% and 2% identi®ed, respectively. With

a target of 25% of the original extent of the vegetation types in the study area,

66 species and 808 species occurrences are included. With targets set at 50% of

the original extent of the vegetation types in the study area, this increased to 75

and 977, respectively. The 50% target exclusively included greater than 50% of

the total species occurrences, while representing 90% of actual species. In both

cases, SLSPF had the largest proportion of species and species occurrences,

and DF the lowest.

The 10% target area fell within protected areas and/or state-land for ®ve of

the vegetation types (DT, DF, DTS and DT-LF). With the 25% target, three of

the vegetation types fell within existing protected areas and/or state-land (DF,

DTS, and DT-LF). No attempt was made to select cadastral units for vege-

tation types where existing protected areas or state-land exceeded the target

areas. The 10% target area was larger than the available land for one of the

vegetation types, WCR. This increased to three (DTG, PLSPF and WCR) for

the 25% target area and ®ve (DT, DTG, DF, PLSPF and WCR) for the 50%

target area. For each of the three target scenarios where the selection procedure

was applied, areas selected within each vegetation type fell within 5% of the

target area speci®ed (Table 2). The e�ciency of the selection procedure and the

use of cadastral units as selection units are summarised in Table 3. Generally,

e�ciency of the selection procedure tended to increase with an increase in

target percent and to decrease when the area selected was considered as a

proportion of the total available land in the study area (without cadastral

units). This holds particularly for those vegetation types which existed mainly

as habitat fragments, such as WCR (Figure 4b, Table 3). This becomes

484

Figure 6. Areas selected by the selection procedure with (a) 10% target area, (b) 25% target area,

and (c) 50% target area. Percentages refer to the original extent of the vegetation within the study

area.

485

Table

2.Resultsoftheareaselectionprocess

usingthreetargetpercentages

forthecoastallowlandsoftheWestern

Cape.Bold

®guresindicate

vegetationtypes

wheretheselectionalgorithm

could

beapplied.Italicised®guresindicate

wheretarget

areasfellwithin

existingprotected

areasorstate-land.Allareasare

reported

inha.No.speciesrefers

toplantspecies.Negativenumbersindicate

under-representationandpositivenumbersover-representation.Vegetationcodes

areaare

explained

inTable

1andAppendix

1.

Target

Vegetation

code

Area

selected

Areaover/under

representation

%Total

areaselected

Algorithm

rules

applied

No.

polygonsselected

Meansize

of

selected

polygons

No.ofspecies

No.species

occurrences

10%

DF

1720

1236

36

±4

429

13

DT

19295

10395

22

±11

137

141

18

DTG

3185

)25

10

1±7

9353

34

DT-LF

13556

9259

32

±26

521

16

78

DTS

6175

4587

39

±22

280

33

PLSPF

8247

)260

10

1±8

18

458

25

106

SLSPF

5661

)42

10

1±9

10

566

30

364

WCR

4995

11462

3±

18

227

26

85

Totals

62834

13

248

60

661

25%

DF

1720

511

36

±4

429

13

DT

22393

)143

25

1±5

183

122

17

41

DTG

5642

)2382

18

±108

52

57

DT-LF

13556

2814

32

±26

521

16

76

DTS

6175

2204

39

±22

280

33

PLSPF

15996

)397k

20

±35

457

45

221

SLSPF

13615

)433

24

1±3

23

591

33

372

WCR

4995

36147

3±

18

277

26

85

Totals

121199

17

419

66

808

50%

DF

2347

)70

49

±9

260

13

DT

42194

)2306

47

±336

125

28

74

DTG

5642

)1046

18

±108

52

57

DT-LF

22313

)829

52

1±8

41

544

19

92

DTS

8179

)236

51

1±8

20

408

48

PLSPF

15996

)23940

20

±35

457

45

221

SLSPF

28488

)392

51

1±8

43

662

49

490

WCR

4995

)77288

3±

18

277

26

85

Totals

242397

27

610

75

977

486

Table

3.Areasselected

foreach

vegetationtypeunder

threetarget

scenarios(10,25and50%

)asafunctionoftheavailable

landin

thestudyareaboth

with

andwithoutcadastralunits.

Italicised®guresindicate

wherethetarget

areafellwithin

existingprotected

areasorstate-land.Allareasare

reported

inha.

Vegetationcodes

are

explained

inTable

1.

Target

Vegetationcode

Areaselected

Available

landwith

cadastralunits

Areaselected

as%

ofavailable

land

withcadastralunits

Totalavailable

land

instudyarea

Areaselected

as%

ofthetotalavailable

landin

thestudyarea

10%

DF

1720

2347

73

4325

40

DT

19295

42194

46

43344

45

DTG

3185

5642

56

9646

33

DT-LF

13556

37367

36

35457

38

DTS

6175

12026

51

13526

46

PLSF

8247

15996

52

16381

50

SLSPF

5661

49794

11

45067

13

WCR

4995

4995

100

9790

51

Totals

62834

170361

37

177546

35

25%

DF

1720

2347

73

4325

40

DT

22393

42194

53

43344

52

DTG

5642

5642

100

9646

58

DT-LF

13556

37367

36

35457

38

DTS

6175

12026

51

13526

46

PLSF

15996

15996

100

16381

98

SLSPF

13615

49794

27

45067

30

WCR

4995

4995

100

9790

41

Totals

84092

170361

49

177546

47

50%

DF

2347

2347

100

4325

54

DT

42194

42194

100

43344

97

DTG

5642

5642

100

9646

58

DT-LF

22313

37367

60

35457

63

DTS

8179

12026

68

13526

60

PLSF

15996

15996

100

16381

98

SLSPF

28488

49794

57

45067

52

WCR

4995

4995

100

9790

41

Totals

130153

170361

76

177546

73

487

particularly relevant for this vegetation type as the use of cadastral units de-

creases the proportion of fragments included within the available land set.

Discussion

This study combines both coarse- and ®ne-®lter approaches (Noss 1987;

Hunter et al. 1988). It has identi®ed an appropriate area from which core areas

and bu�er zones should be selected for inclusion within a biosphere reserve. In

addition, it has attempted to outline a speci®c system of priority areas, which

should comprise these core areas and bu�er zones. The e�ciency of the pro-

cedure in sampling the range of remaining natural diversity and therefore the

representativeness of the resulting prioritised areas, its explicitness, its use of

the principle of complementarity and its requirements for clear goals o�er

signi®cant advantages over the ad hoc approaches to reserve selection usually

applied in southern Africa.

Adequacy of areas selected

The heuristic algorithm used in this study was designed to accommodate the

high degree of fragmentation of the Western Cape coastal lowlands by using a

core of adjacency rules and precluding cadastral units containing land mostly

transformed by agriculture, pastoral or urban development, or containing high

densities of alien plant species. The selected areas under the three target sce-

narios (Figures 6a, b and c) included large tracts of Sand Plain Fynbos, which

harbours a rich and unusual neoendemic ¯ora that is inadequately conserved

outside the study area (Cowling and Holmes 1992; Rebelo and Siegfried 1992).

They include between 36% and 76% of the remaining West Coast Renoster-

veld that has long been recognised as a conservation priority (Cowling et al.

1986; Jarman 1986; Rebelo 1992; Rebelo and Tansley 1993). They also in-

corporate between 40% and 80% of West Coast Dune Thicket in South Africa

and large tracts of riparian vegetation along the lower reaches of the Berg

River. This latter vegetation type is highly productive, structurally diverse and

supports a particularly rich avifauna (MacDowell 1993; Hockey 1993).

The classi®cation and methodology used here for the assessment of con-

servation status and area selection are based solely on plant data. This is

because what little information is available on faunal distributions in the area is

mostly at the quarter-degree scale and hence too coarse for inclusion (Rebelo

1992). While the fauna per se is not considered, it is hoped that adequate

protection of habitats will also conserve animal species. Similar assumptions

have been made by numerous authors working within the CFR (e.g. Rebelo

488

and Siegfried 1992; Lombard et al. 1997). Each of the three vegetation types

found in the study area support a distinct avifauna and a rich invertebrate

fauna with high levels of endemism (Siegfried 1981; Tansley 1982). The pro-

posed system also includes many habitats suitable for the conservation of the

coastal lowland fauna. The inclusion of Langebaan Lagoon, a proclaimed

RAMSAR site, and the lower reaches of the Berg River, protects an area with a

high diversity of aquatic bird species (Hockey 1993; Shaw et al. 1996). Other

important sites are the Darling Hills and other granitic outcrops which also

support rich bird species assemblages (Siegfried 1989). Several endemic species

of amphibians are also found in many of the vleis in the selected area system

(Greig 1981). In a national-wide study, Lombard (1995) identi®ed ®ve quarter-

degree squares within the study area as representing hotspots for frogs, birds,

tortoises, snakes and mammals.

Fragmentation

The algorithm used was successful in maintaining a high degree of connectivity

between selected polygons. The degree of connectivity increased as the target

area percent increased. With a target of 10% the degree of connectivity both

within and between vegetation types was much less than with a target of 50%.

Inclusion of contiguous vegetation types accommodated for the high beta di-

versity of many of the vegetation types associated with habitat change in the

lowlands of the CFR (Cowling 1990; Cowling and Holmes 1992). The selected

areas included steep edaphic gradients, particularly in the Hope®eld, Darling

and Atlantis areas, which ensured that much of the region's plant diversity was

captured (see also Lombard et al. 1997). For example, the majority of the

selected area for SLSPF lies in an east-west, rather than a north-south orien-

tation, which captures a major edaphic gradient associated with increasing

sediment age. However, some of the edaphic gradients have not been included

because of the paucity of available land in the study area. The greater the target

area percent, the more edaphic gradients are captured. Edaphically heteroge-

neous sites conserve diverse species-rich assemblages of plants and provide

environmental gradients for future migration and speciation especially in the

event of climatic change (Graham 1988; Cowling et al. 1992; Peters and

Lovejoy 1992; Lombard et al. 1997). Edaphic speciation is regarded as an

important mode of diversi®cation in the lowlands of the CFR (Cowling et al.

1992; Willis et al. 1996).

Implementation and ¯exibility

No speci®c di�erentiation has been made between core areas and bu�er zones

in this study. The demarcation of core areas vs. bu�er zones requires a detailed

489

knowledge of all aspects of the area under consideration. While biological

considerations constitute a large portion of these, it is imperative that socio-

economic factors are also taken into account, e.g. landownership, access rights,

future development frameworks, public goodwill and co-operation and, most

importantly, the exact amount of funding available immediately and in the

foreseeable future. From a biological point of view, the principle of irre-

placeability (Pressey et al. 1993) becomes vitally important when identifying

actual reserve areas within the broad-scale area identi®ed in this study. The

high proportion of local endemics within each vegetation type (Rebelo 1992)

indicates that a single reserve within each of the identi®ed vegetation types

would not adequately conserve endangered or vulnerable plant species. Core

areas within the areas identi®ed should not only be carefully selected with

regard to location, number and connectivity, but also with particular consid-

eration for the total area and adjacent habitats. Inclusion of adjacent undis-

turbed habitats and diverse soil types will enhance the overall species richness

of the resultant reserve system owing to the exceptionally high soil-related beta

diversity in lowland fynbos regions (Cowling 1990). The extreme fragmentation

of some of the vegetation types e.g. WCR (Figures 4a and b) would require

some form of o�-core management and protection to maintain these remnants

in a matrix of agricultural land and so increase the overall level of protection.

Kemper et al. (submitted) suggest that for South Coast Renosterveld (200 km

to the south of the study area) these fragments are instrumental in conserving

the biodiversity of this vegetation type and should be conserved by some form

of contractual agreement with landowners if it is not possible to conserve each

remnant formally. The high degree of fragmentation will also have implications

as to the eventual management of the resulting biosphere reserve. It is

imperative that fragments of natural vegetation not represented by available

cadastral units (compare Figures 4a and b) are investigated and the option of

including them as very small core areas within either the transition zone or

bu�er area is considered.

It is recommended that the area identi®ed under the auspices of the 50%

target area be considered the future site of core areas and bu�er zones for the

proposed biosphere reserve. This is the last possible and practical site for the

conservation of the vegetation types inherent to the CLWC and the 50% target

area was set with regard to the study area alone (only some 40% of the

CLWC). Prioritisation of areas should consider both the indispensability and

the vulnerability of vegetation types (Pressey 1997): Indispensability of a site is

indicative of the extent to which options for achieving conservation goal(s) are

lost if the area is lost, while vulnerability refers to the susceptibility of an area

to destruction or alteration in the future. Figure 7 shows a scatter-plot of

indices of vulnerability vs. indispensability, a proxy measure for indispens-

490

ability, for each vegetation type at the 50% target. The indispensability index

(ind) for each vegetation type was calculated as a function of the percentage of

available land needed to achieve the 50% target. The vulnerability index (vul)

is a composite of three threats: alien infestation, development or cultivation

and loss of biodiversity due to fragmentation, ameliorated by the percentage of

the vegetation type currently in protected areas. The threat components of

vulnerability were calculated as a function of the extent to which the vegetation

types have already been reduced and fragmented as a result of each of these

threats. In order to give equal weighting to each of the three factors, values

were reduced to a scale of between 1 and 10, summed and then reduced by the

proportion of area currently in protected areas to give a total vulnerability

index. The marked di�erence between WCR and the other vegetation types in

terms of indispensability highlights the extreme reduction and fragmentation of

the vegetation type. This factor also di�erentiates it from the equally vulner-

able vegetation type, PLSPF. WCR was the vegetation type with the highest

combination of indispensability and vulnerability (irr 20, vul 1647), while

SLSPF had the lowest (irr 5, vul 56). This suggests that WCR is the vegetation

type with the highest priority and SLSPF the lowest. Those vegetation types

falling within the top right-hand corner of the scatter-plot have higher priority

than those in the bottom left.

Figure 7. Scatter plot of indispensability vs. vulnerability indices for each vegetation type in the

study area. The vulnerability index is a composite of three threats: alien infestation, development

and loss of fragmentation, the e�ects of which are modi®ed by the proportion of area already in

protected areas. The indispensability index for each vegetation type was the percent of available

land needed to achieve a 50% of the remnant extent of each of the vegetation types. Vegetation

codes are described in Table 1 and Appendix 1.

491

Where possible, existing protected areas should form the starting points for

core areas and attempts should be made to provide links or corridors between

these. It is recommended that core areas and bu�er zones be identi®ed in an

atmosphere of negotiation between all stakeholders. The establishment of a

biosphere reserve is a process that requires that all interested parties be con-

sidered. Rather than presenting a de®nitive reserve system, this study provides

a tool that allows for biological criteria to be included explicitly within that

negotiation process. As the biosphere reserve is assembled, priorities can be re-

assessed in an iterative manner.

Acknowledgements

We are grateful to A. Plos for technical assistance and to Dr B.M. Clark for

useful discussion and comments on drafts of this report. Special thanks go to

D. Gerneke without whose expertise in light aircraft aviation, the collection of

additional data may not have been possible. We would like to express our

gratitude to C. Burgers, R. Poole, A. le Roux and B. de Wet of Cape Nature

Conservation for data contributed and useful discussion. Similarly, Dr A.G.

Rebelo and the Protea Atlas Project, Dr J. Manning, Dr P. Goldblatt and Dr

A.B. Low are thanked for their contributions. Thanks are also due to Dennis

Moss & Associates, Cape Town City Council, The Darling Wild Flower As-

sociation, The West Coast Biosphere Reserve Committee and The West Coast

Regional Services Council. This project would not have been possible without

the funding supplied by WWF-SA, The Ubuntu Trust and the Institute for

Plant Conservation, which are all gratefully acknowledged.

Appendix 1. Nine sub-categories of vegetation types occurring in the study area (after Boucher

1987).

Vegetation

name Abbreviation

Phytosociological

nomenclature Description

Dune ®elds

(Mobile sand)

DF ± ±

West Coast Dune

Thicket (Strandveld)

DT Euclea racemosa ±

Zygophyllum

morgsana Alliance

Short closed to tall open

shrubland and tall closed

restioland on stable lime-rich

sands.

West Coast Dune

Thicket (Strandveld)

on dry granite

DTG Euclea racemosa ±

Zygophyllum

morgsana Alliance

Hillside closed dwarf and dense

shrubland on granite

outcrops. Dominant plant

communities incl. Galenia

crystallina ± Senecio ¯oribunda

hillside-closed dwarf

shrubland; and Eharta erecta ±

Maurocenia frangularia

hillside dense shrub-land.

492

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