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Biogeographic patterns in rocky intertidalcommunities in KwaZulu-Natal, South AfricaKJ Sink , GM Branch & JM HarrisPublished online: 08 Jan 2010.

To cite this article: KJ Sink , GM Branch & JM Harris (2005) Biogeographic patterns in rocky intertidal communities inKwaZulu-Natal, South Africa, African Journal of Marine Science, 27:1, 81-96, DOI: 10.2989/18142320509504070

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African Journal of Marine Science 2005, 27(1): 81–96Printed in South Africa — All rights reserved

Copyright © NISC Pty LtdAFRICAN JOURNAL OF

MARINE SCIENCEISSN 1814–232X

On the east coast of southern Africa, marine biogeo-graphic boundaries have previously been unresolved.This paper analyses large-scale patterns of communitystructure of rocky intertidal shores along the whole ofthe KwaZulu-Natal coast, based on abundance datacovering 220 macroalgal and invertebrate species at 39sites and using hierarchical cluster analyses andmultidimensional scaling to define biogeographicregions. ANOSIM showed that rocky shores in thenorthernmost region, termed Maputaland, were signi-ficantly different from those in three other regions tothe south, which fall within a single biogeographicregion termed the Natal Province. A clear biogeographicbreak between these two provinces was identified atCape Vidal Point, with >65% Bray Curtis dissimilarityin community structure between Maputaland and Natal.This break was detectable in both the low and midshore, but in the high and top shore, communitiesconverged and there was no regional differentiation for

these zones. There was no evidence of a previouslysuggested biogeographic break near Durban. The majorspecies distinguishing Maputaland and Natal wereidentified using SIMPER analyses and correspond withpreviously described differences between Moçambiqueand KwaZulu-Natal. Species characteristic of Maputa-land have tropical affinities and it is proposed that thisregion forms part of the tropical Indo-West PacificProvince. Natal appears sufficiently distinctive to berecognised as a subtropical biogeographic provincedifferent from Maputaland, and possibly different fromthe warm-temperate South Coast Agulhas Province. Thevirtual absence of representative unexploited shores inthe Natal Province and the occurrence of subsistenceharvesting on almost all rocky shores in Maputaland(including those in theoretically protected areas), con-stitute obvious gaps in the biodiversity conservationstrategy of KwaZulu-Natal.

Biogeographic patterns in rocky intertidal communities in KwaZulu-Natal, South Africa

KJ Sink1*, GM Branch1 and JM Harris2

1 Marine Biology Research Institute, Department of Zoology, University of Cape Town, Rondebosch 7701, South Africa2 Ezemvelo KZN Wildlife, Private Bag X3, Congella 4013, South Africa* Corresponding author, e-mail: skink@mweb.co.za

Introduction

Biogeography is defined as the study of biological life ina spatial and temporal context and is concerned with thedescription and explanation of patterns of distribution (Coxand Moore 1998). One of its major applications is thegeneration of knowledge necessary to achieve adequateand representative conservation of biodiversity. In thespecific context of coastal marine systems, representativeprotected areas need to be established within eachprincipal biogeographic region if marine biodiversity is tobe conserved (Hockey and Buxton 1989, Attwood et al.1997a, Hockey and Branch 1997, Roberts 2003a, 2003b).A prerequisite to achieving this goal is, however, a secureknowledge of where biogeographic regions begin and end.

In South Africa, concern has been expressed that notall biogeographic areas are adequately protected (Hockeyand Buxton 1989). In particular, representative habitats inthe southern section of the East Coast (including southern

KwaZulu-Natal) are very poorly represented in fully protectedmarine protected areas (Attwood et al. 1997b). Identifyingbiogeographic breaks along the East Coast has, however,been difficult, because the entire KwaZulu-Natal coastlinehas not previously been well represented in biogeographicsurveys. The early work of Stephenson (1939, 1944, 1947)did not extend north of Cape Vidal (Figure 1) and a recentsurvey of biomass patterns around the entire coast of SouthAfrica included only two KwaZulu-Natal sites, Ballito andCape Vidal (Bustamante and Branch 1996). Bolton andStegenga (2002) highlight the lack of information coveringseaweed distribution and marine vegetation communitiesalong the East Coast. In response to these needs, the presentstudy provides detailed information about species distributionand abundance of invertebrates and macroalgae based onequal sampling effort at a large number of KwaZulu-Natalrocky shores.

Keywords: algae, biodiversity, biogeography, biological community structure, intertidal rocky shores, marine protected areas,Perna perna

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The pioneering intertidal research of Stephenson (1939,1944, 1947) indicated that the South African intertidal areacomprises three sections: (a) the cool-temperate WestCoast, (b) the warm-temperate South Coast and (c) thesubtropical East Coast. Subsequent intertidal work by Brownand Jarman (1978), Emanuel et al. (1992) and Bustamanteand Branch (1996) recognised three biogeographicprovinces (Figure 1). Turpie et al. (2000) showed that thedistribution of coastal fishes also reflects three biogeographicprovinces: the West, South and East Coast provinces. Ananalysis of seaweed distributions in South Africa (Bolton1986) suggested only two provinces, a warm-temperateprovince (with West and South Coast components) and asubtropical East Coast province. However, recent analyseshave consistently defined the South Coast as anindependent province (Stegenga and Bolton 1992, Emanuelet al. 1992, Bustamante and Branch 1996).

Emanuel et al. (1992) divided the West Coast ofsouthern Africa into two separate cool-temperate provin-ces, the Namaqua and Namib provinces, with a divisionnear Lüderitz (Figure 1). On the basis of seaweed flora,a third division is even recognised on the southern portion

of the Cape West Coast (Engledow et al. 1992, Bolton andAnderson 1997, Figure 1). This is termed the South-WesternCape Sub-province and is more species-rich in terms ofseaweeds than the Namib Province or the northern part ofthe Namaqua Province (Engledow et al. 1992, Bolton andAnderson 1997). This division is also reflected in the inverte-brate fauna (Emanuel et al. 1992). A tropical West Coastprovince north of southern Angola and a tropical East Coastprovince north of central Moçambique have also beenrecognised (Penrith and Kensley 1970, Kensley and Penrith1973, Bolton and Anderson 1997).

There is an area of overlap between the cool-temperateWest Coast and the warm-temperate South Coast AgulhasProvince (Stephenson and Stephenson 1972). This overlapextends from Cape Point to Cape Agulhas, with a rapidreduction of West Coast species between Hermanus andArniston (Stephenson 1947, Jackelman et al. 1991, Emanuelet al. 1992, Stegenga and Bolton 1992). The East Coasthas been less studied and there is no consensus regardingthe position of an overlap region or the eastern limit of theAgulhas Province (Emanuel et al. 1992, Bolton andAnderson 1997). Stephenson (1947) identified an eastern

Figure 1: Southern Africa, showing the previously proposed marine biogeographic provinces and biogeographic breaks identified on thebasis of patterns in the distribution of intertidal fauna and flora

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African Journal of Marine Science 2005, 27(1): 81–96 83

overlap area between East London and Durban on theKwaZulu-Natal coast, with an important break near Port StJohns. Emanuel et al. (1992) proposed that the divisionbetween the East Coast and South Coast was south of PortSt Johns. Turpie et al. (2000) reported that coastal fishesdo not reflect a clear biogeographic break between the Eastand South Coast provinces, with gradual species turnovereast of Cape Point. The Transkei region in the Eastern Capewas, however, more similar to the South Coast than theEast Coast, and the East Coast province was consideredto extend northwards from the southern border of KwaZulu-Natal. Hommersand (1986) noted that the KwaZulu-Natalflora is poorly studied, but reported that the East Coast florareflects an eastwardly decreasing number of Agulhasspecies, replaced largely by tropical Indo-West Pacificspecies. Bolton and Anderson (1997) did not recognise asubtropical province as such, but considered the easternoverlap to extend from around East London to Durban andregarded the area north of Durban as part of the TropicalIndo-West Pacific Province.

Within KwaZulu-Natal, two main biogeographic breakshave been proposed (Figure 1). First, in an analysis of thepresence or absence of intertidal and nearshore inverte-brates, Emanuel et al. (1992) described a break just northof Durban. Second, Jackson (1976) identified differencesin intertidal fauna and flora between (1) Maputaland, runningfrom the border of Moçambique to Leven Point, just northof Cape Vidal, (2) southern Zululand, extending from LevenPoint to Durnford Point, and (3) Natal, stretching fromDurnford Point to Port Edward (Figure 1). Jackson arguedthat there is a distinct break north of Cape Vidal and somechange in the vicinity of Port Durnford, just south of RichardsBay. She viewed communities in Maputaland as being themost distinct, with communities in southern Zululand beingmore similar to those in Natal than Maputaland. In Jackson’sopinion, the subtropical province extended from a southernboundary between Port St Johns and Qolora in the Transkeito a northern boundary between Cape Vidal and Mabibi.Stephenson and Stephenson (1972) considered the EastCoast province to extend all the way from Moçambique toPort St Johns. Emanuel et al. (1992) found no further breaksnorth of Durban to at least as far as Ponta da Barra Falsain Moçambique. There is therefore confusion about theprecise position, or even existence, of a biogeographicbreak between tropical and subtropical provinces on theKwaZulu-Natal coast. In this study, large-scale patterns incommunity structure (species composition and abundance)were sought along the whole of the approximately 560-kmcoastline of the political province of KwaZulu-Natal (Figure1). The principal aim of this research was to identify andcharacterise differences in intertidal community structure ata large scale (spanning hundreds of kilometres) along theKwaZulu-Natal coast. More specific objectives were: (1) toidentify any biogeographic breaks along the KwaZulu-Natalcoast, by using descriptive techniques and objectivesimilarity analyses to test for differences in communitystructure between regions; (2) to examine whether anyobserved biogeographic patterns conform to previouslyproposed biogeographic provinces or sub-provinces; and (3)to identify characteristic and distinguishing species that ac-count for similarities within and differences between regions.

Biogeographic patterns are thus explored in a quantitativemanner for the entire KwaZulu-Natal coast. Such biogeo-graphical analyses are critical for the establishment ofsensible strategies for the conservation and managementof biodiversity and resources. The data gathered for thisanalysis are the first to allow broad-scale quantification ofspecies abundance for rocky shores in this region, and differfrom previous analyses in several respects. First, they allowseparate analyses of different zones on the shore. Second,the spatial intervals and numbers of sites sampled allow amuch more fine-scale examination of patterns than has beenpossible in the past. Third, they are based on the quantitativeabundance of species rather than presence-or-absence data,as has been the case for most previous surveys.

Material and Methods

Biological sampling design

The KwaZulu-Natal (KZN) coast was divided into four pre-defined regions termed Maputaland, Zululand, Central KZNand Southern KZN, each c. 140km long. In total, 39 siteswere sampled from these regions (Figure 2). The boundariesof the regions were selected to test for significant differencesin community structure between previously describedbiogeographic regions or subregions, as proposed byJackson (1976) and Emanuel et al. (1992).

Using distance, the intertidal area was divided into fourequally-sized zones (the low, mid, high and top shore), andrandom replicate 1m X 0.5m quadrats were sampled in thecentre of each zone. Pools and gullies were excluded. Thelow shore was surveyed at 39 sites, the mid shore at 27sites, and the high and top shore at 22 and 13 sitesrespectively. Effort was greater low on the shore, becausediversity was greatest there and because human harvestingis concentrated there (Lasiak 1999). Only 13 sites weresurveyed on the top shore because of the continual presenceof deep sand (>20cm) in this zone at many sites. Sites weresurveyed during the summer of 1996/1997 (low and midshore) and autumn 1997 (high and top shore) and all surveystook place during spring-low tides.

A pilot study based on species-richness curves wasundertaken to determine appropriate replication within sites(Sink 2001). Sample sizes were chosen to include at least95% of the species recorded. On these grounds, 20quadrats were selected as sufficient replication for the lowand mid shore, and 10 quadrats for the high and top shore.

In each quadrat, percentage cover of all sessile species,counts of visible mobile species, and mean sizes of mobilespecies were recorded in the field. For the low, mid andhigh shore, counts of mobile organisms were converted topercentage cover estimates using mean size. For the topshore, counts of mobile organisms were not converted,because few sessile species were recorded in this zoneand bare rock dominated.

Data analysis

Each of the four zones on the shore was analysed separately.PRIMER (Plymouth Routines in Multivariate EcologicalResearch, Version 4.0) was used for analysis of species

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Figure 2: Map of the KwaZulu-Natal coast showing all rocky shore sites (closed squares) surveyed during the biogeographic study andthe pre-defined regions that were tested for significant differences in community structure. All sites are recreationally exploited except forthose that are fully protected (*), inaccessible (Island Rock) or subject to subsistence harvesting (underlined). The positions of currentmarine protected areas and the types of harvesting occurring in different areas are shown

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African Journal of Marine Science 2005, 27(1): 81–96 85

composition and abundance (Clarke and Warrick 1994).Biological data were root-transformed to upweight thecontribution of less abundant species. Hierarchical cluste-ring analysis using Bray-Curtis coefficients and multi-dimensional scaling (MDS; Kruskal and Wish 1978) wereused to compare community structure between sites andregions. Within each zone, the average Bray-Curtis similaritybetween sites was used as a measure of community conver-gence. As the number of sites sampled differed between thezones, this was done in two ways: first by using the data forall sites sampled, and then by standardising the number ofsites analysed per zone (n = 13) to ensure that differencesin sample size did not bias the result. For the latter approach,analyses were restricted to the 13 sites at which all fourzones were sampled.

Differences in community structure between pre-definedregions were tested using one-way ANOSIM analyses (Clarkeand Green 1988, Clarke 1993). Mean percentage covers ofall species from replicate sites within each region werecompared. For those regions that differed significantly,characteristic and distinguishing species between regionswere then identified using similarity percentage breakdownanalyses (SIMPER). Species were only considered if theycontributed >2% to the overall similarity or dissimilarity, orwere among those that cumulatively accounted for at least80% of the overall similarity or dissimilarity within andbetween regions. On these grounds, abundance estimatesfor 220 species (91 invertebrates and 129 algae) were usedin the analysis.

Results

Biogeographic breaks and regional differences incommunity structure

ANOSIM tests between the four pre-defined regions detectedsignificant differences in community structure betweenregions in the low and mid shore (Global r = 0.479, p <0.01, n = 39 and r = 0.55, p < 0.01, n = 27 respectively),but not in the high and top shore (r = 0.027, p = 0.33, n =22 and r = 0.197, p = 0.13, n = 13 respectively).

Comparing individual regions, the low-shore communitystructure in Maputaland was significantly different from thatof Zululand, Central KZN and Southern KZN (Table 1). There

were, however, no significant differences in low-shorecommunity structure between Zululand, Central KZN andSouthern KZN. In the mid-shore, community structure inMaputaland was similarly significantly different from that ofZululand, Central KZN and Southern KZN. Mid-shorecommunity structure in Zululand was also significantlydifferent to that of Central KZN and Southern KZN, but therewas no difference between Central and Southern KZN.

Hierarchical cluster analyses and two-dimensional MDSordination plots were used to explore the similarity of siteswithin each of the four zones on the shore. The dendrogramfor the low-shore sites (Figure 3a) showed that two sites(one from Central KZN and one from Southern KZN) wereoutliers, >75% dissimilar to all other sites. Apart from thesetwo sites, all the Maputaland sites, along with one Zululandsite (Cape Vidal Point) and one site from Southern KZN(Umfazazana), formed a discrete cluster, >70% dissimilar tosites in the rest of KwaZulu-Natal. Sites from Zululand,Central KZN and Southern KZN did not separate out intoregional groups, sites from different regions often being moresimilar than sites from the same region. The MDS plot(Figure 3b) also indicated that Maputaland low-shore siteswere different from those of the rest of KwaZulu-Natal. CapeVidal Point again grouped with the Maputaland sites, andUmfazazana, a site in Southern KZN where subsistenceharvesting is undertaken, was also more similar to theMaputaland sites than to other Southern KZN or CentralKZN sites.

In the mid shore (Figure 4a), three sites (two fromZululand and one from Central KZN), were outliers >80%dissimilar to all other sites. All the Maputaland sites wereagain grouped in a cluster, >70% dissimilar to the remainingsites, and sites from the three other regions did not separateout into regional groups. Cape Vidal Point grouped with thesites from Central and Southern KZN. The MDS plot (Figure4b) also indicated that the Maputaland sites were distinct.

In the high-shore sites, there was no distinct clusteringof sites into their respective regions (Figure 5). Similarly, inthe top-shore sites, hierarchical cluster analysis and MDSshowed that there was no separation between regions(Figure 6).

The differences in the low- and mid-shore sites evidentbetween Maputaland and the three other regions indicatethat there are only two distinct biogeographic regions in

Table 1: Results of one-way ANOSIM tests for differences between regions in low- and mid-shore community structure in KwaZulu-Natal.Tests based on Bray-Curtis similarity measures derived from root-transformed estimates of mean percentage cover of 220 species fromreplicate sites within each pre-defined region

ANOSIM test of significanceRegion Zululand Central KwaZulu-Natal Southern KwaZulu-NatalMaputaland Low shore; r = 0.783 (p < 0.01*) Low shore; r = 0.727 (p < 0.01*) Low shore; r = 0.810 (p < 0.01*)

Mid shore; r= 0.889 (p < 0.01*) Mid shore; r = 0.754 (p < 0.01*) Mid shore; r = 0.760 (p = 0.01*)

Zululand Low shore; r = 0.248 (p = 0.10) Low shore; r = 0.368 (p = 0.07)Mid shore; r = 0.467 (p = 0.006*) Mid shore; r = 0.402 (p = 0.013*)

Central KwaZulu-Natal Low shore; r = 0.081 (p = 0.20)Mid shore; r = 0.041 (p = 0.068)

* = Significant difference (p < 0.05)

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KwaZulu-Natal. Sites north of Cape Vidal fall in a regionhereafter termed ‘Maputaland’, whereas all sites south ofCape Vidal can be considered as belonging within a singleregion, previously termed Natal (Jackson 1976).

Considering differences among sites, there was greatervariability (lower similarity) in the low and mid shore than inthe top and high shore, as reflected in the average Bray-Curtis similarity for each zone (Table 2). Along the entire

KwaZulu-Natal coast, the mid shore had the greatestvariability in community structure between sites (S = 40.51%,n = 13 or S = 33.29%, n = 27). There was also substantialbetween-site variability in the low shore (S = 51.46%, n =13 or S = 41.82%, n = 39), but less in the high shore (S =54.95%, n = 13 or S = 48.23%, n = 22). Highest similarity(S = 72.79%, n = 13) was recorded in the top shore, indi-cating convergence of community structure.

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Figure 3: (a) Dendrogram of the hierarchical cluster analysis and(b) MDS plot (stress = 0.14) for the low shores of 39 sites withinfour pre-defined regions: M = Maputaland, Z = Zululand, C =Central KwaZulu-Natal, S = Southern KwaZulu-Natal

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Figure 4: (a) Dendrogram of hierarchical cluster analysis and (b)MDS plot (stress = 0.16) for the mid shores of 27 sites within fourpre-defined regions: M = Maputaland, Z = Zululand, C = CentralKwaZulu-Natal, S = Southern KwaZulu-Natal

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Figure 5: (a) Dendrogram of hierarchical cluster analysis and (b)MDS plot (stress = 0.12) for the high shores of 22 sites withinfour pre-defined regions: M = Maputaland, Z = Zululand, C =Central KwaZulu-Natal, S = Southern KwaZulu-Natal

Average similarity (S%)Zone Entire Coast Entire Coast Maputaland NatalLow shore 51.46 (n = 13) 41.82 (n = 39) 47.36 (n = 10) 51.14 (n = 29)Mid shore 40.51 (n = 13) 33.29 (n = 27) 49.73 (n = 6) 39.00 (n = 21)High shore 54.95 (n = 13) 48.23 (n = 22) 0– 0–Top shore 72.79 (n = 13) 72.79 (n = 13) 0– 0–

Table 2: Average similarity (S%) between sites for each zone on the shore, as determined by SIMPER analysis. For the entire coast ofKwaZulu-Natal, comparable estimates between zones are indicated for a standardised sample size (n = 13 sites) and for all surveyedsites. Sample sizes are indicated in parentheses. Separate average similarities were determined within Maputaland and Natal for the lowand mid shores only, because no biogeographic differences in community structure were evident in the high and top shores

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Figure 6: (a) Dendrogram of hierarchical cluster analysis and (b)MDS ordination (stress = 0.05) for the top shores of 13 sites withinfour pre-defined regions: M = Maputaland, Z = Zululand, C =Central KwaZulu-Natal, S = Southern KwaZulu-Natal

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Characteristic species

Low shoreFor the low shores in Maputaland, 80% of the similaritybetween sites was accounted for by 19 taxa (Table 3). Thefour most characteristic taxa were algae: Sargassum elegans,Cheilosporum sagittatum, encrusting coralline algae and

Caulerpa racemosa, cumulatively accounting for 31.82% ofthe similarity. The brown mussel Perna perna and the ascidianPyura stolonifera were the next most important species,explaining an additional 11.29% of the group similarity. Themost characteristic mobile species was the limpet Scutellastrapica. C. racemosa, P. stolonifera and the barnacle Tetraclitasquamosa rufotincta were the most consistently characteristic

Maputaland NatalCharacteristic species %Av Si Si/SD(Si) ΣSI% Characteristic species %Av Si Si/SD(Si) ΣSI%

Low shore (n = 10 sites; S = 47.36%) Low shore (n = 29 sites; S = 51.14%)Sargassum elegans 13.06 09.69 1.40 09.69 Perna perna 51.24 30.13 1.86 30.13Cheilosporum sagittatum 17.84 08.99 0.98 18.67 Hypnea spicifera 07.34 06.90 1.25 37.03Encrusting corallines 05.33 06.64 2.00 25.31 Cheilosporum sagittatum 05.75 06.28 1.36 43.31Caulerpa racemosa 04.87 06.50 2.53 31.82 Encrusting corallines 03.30 06.22 1.99 49.53Perna perna 11.58 06.44 1.19 38.26 Ralfsia sp. 02.18 05.09 1.79 54.62Pyura stolonifera 04.70 04.85 2.16 43.10 Jania verrucosa 02.58 04.73 1.61 59.35Tetraclita squamosa 02.16 04.20 2.11 47.31 Plocamium corallorhiza 01.93 04.36 1.29 63.71Ralfsia sp. 01.83 04.00 1.76 51.30 Hypnea intricata 03.82 04.21 1.01 67.92Chamaedoris delphinii 01.95 03.96 1.37 55.26 Spyridia hypnoides 01.46 02.73 1.37 70.65Sargassum crassifolium 03.27 03.88 1.29 59.14 Bare rock 01.39 02.49 1.67 73.14Laurencia glomerata 05.23 03.32 0.74 62.46 Octomeris angulosa 01.00 02.24 0.89 75.38Idanthyrsus pennatus 07.19 03.17 0.67 65.63 Scutellastra aphanes 00.68 01.90 1.03 77.27Bare rock 00.91 02.62 1.24 68.25 Sand 02.10 01.69 0.62 78.96Valonia macrophysa 01.29 02.41 1.00 70.66 Arthrocardia sp. 00.99 01.50 1.00 80.46Unidentified green ascidian 02.08 02.40 1.00 73.06Jania adhaerens 01.55 02.27 0.86 75.34Hymeniacedon sp. 01.09 02.16 1.66 77.50Unidentified sandy ascidian 01.03 01.99 1.30 79.49Scutellastra pica 00.72 01.71 1.36 81.20

Mid shore (n = 6 sites; S = 49.73%) Mid shore (n = 21 sites; S = 39.00%)Tetraclita squamosa 27.35 22.52 2.33 22.52 Octomeris angulosa 23.76 15.90 0.73 15.900Bare rock 15.43 18.05 4.19 40.57 Jania verrucosa 20.10 14.86 0.76 30.76Hymeniacedon sp. 07.19 08.71 1.43 49.28 Bare rock 13.30 14.71 1.100 45.47Encrusting corallines 11.03 08.45 1.19 57.73 Ralfsia sp. 05.01 07.56 0.88 53.03Palythoa nelliae 10.16 07.56 1.16 65.29 Palythoa nelliae 12.63 05.28 0.43 58.31Dendropoma tholia 05.67 03.74 0.90 69.03 Tetraclita serrata 02.70 05.16 0.84 63.48Ralfsia sp. 00.79 0 3.700 3.50 72.72 Perna perna 00.68 03.900 1.52 67.37Idanthyrsus pennatus 04.84 03.01 0.97 75.74 Encrusting corallines 02.32 03.36 0.96 70.73Cellana capensis 00.67 02.92 2.23 78.65 Pomatoleios kraussii 02.10 02.91 0.61 73.64Perna perna 00.73 0 2.30 0 1.32 80.95 Zoanthus natalensis 02.72 02.85 0.48 76.49Ulva sp. 00.31 02.07 2.54 83.01 Saccostrea cuccullata 00.79 02.75 0.79 79.25

Gelidium foliaceum 01.11 02.45 0.73 81.700Gelidium reptans 00.68 02.32 0.75 84.01Scutellastra natalensis 00.49 02.14 0.700 86.15

High shore (n = 22 sites; S = 48.23%)Bare rock 37.59 19.3 1.81 40.07Saccostrea cuccullata 34.47 16.1 1.27 73.45Chthalamus dentatus 03.05 03.2 0.92 80.08Brown ephemeral alga 11.02 01.9 0.31 83.95

Top shore (n = 13 sites; S = 72.79%)Bare rock 51.32 37.3 4.63 51.32 Afrolittorina africana (32.02) 23.3 2.51 83.34 Afrolittorina natalensis (14.13) 10.3 1.22 97.47 Littoraria glabrata 0(2.00) 01.5 0.99 99.48

Table 3: Characteristic species for low, mid, high and top shores in KwaZulu-Natal, as determined by SIMPER analyses. Maputaland andNatal were analysed separately for the low and mid shores because significant differences in community structure were revealed betweenregions in these zones. The ranking is determined by Si, the average contribution of each species to the overall similarity of the zone ineach region. %Av indicates the average percentage cover of each species from all sites. Figures in parentheses for the top shore aredensities m–2, not % cover. Si/SD(Si) is the ratio between Si and SD(Si), the standard deviation of Si. This ratio reflects how consistently thespecies abundance varied within each region. ΣSI% is the cumulative percentage contribution of each species to the overall similarity (S)

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species, as reflected by their high ratios of Si/SD(Si).In Natal, 80% of the low-shore group similarity was

explained by 14 taxa (Table 3) with P. perna accounting for30.13%. Other important characteristic taxa were the algaeHypnea spicifera, C. sagittatum, encrusting algae (crustosecorallines and Ralfsia expansa) and Jania verrucosa.Scutellastra aphanes was the most characteristic mobilespecies. Encrusting coralline algae and P. perna were thetwo most consistent characteristic taxa.

Mid shoreWithin Maputaland, 10 taxa accounted for 80% of the mid-shore group similarity (Table 3). The top two taxa, i.e. thebarnacle T. squamosa rufotincta and the sponge Hymenia-cedon sp., together with the proportion of bare rockexplained 50% of the group similarity. R. expansa, Ulva, T.squamosa rufotincta and the limpet Cellana capensis werethe most consistently typical taxa.

In Natal, 11 taxa accounted for 80% of the overall groupsimilarity, with four taxa explaining 50% (Table 3). The principalcharacteristic species were Octomeris angulosa, J. verrucosaand R. expansa. P. perna was the most consistently charac-teristic species. The most important characteristic mobilespecies was Scutellastra natalensis.

High shoreHigh-shore sites were treated as a unit covering the wholeKwaZulu-Natal coast because no biogeographic break wasidentified within this zone. In all, three taxa accounted for80% of the average similarity in the high shore (Table 3).The most consistent and most characteristic species wasthe sun oyster Saccostrea cuccullata, which, together withbare rock, accounted for >70% of the overall similarity. Thebarnacle Chthalamus dentatus and an unidentifiedephemeral brown alga were also characteristic.

Top shoreTop-shore sites were similarly treated as a unit coveringthe entire KwaZulu-Natal coast because no biogeographicbreaks were identified in that zone. Bare rock and threelittorinid snails accounted for 99% of the overall similarity(Table 3). Afrolittorina africana was the most consistentlycharacteristic and abundant species.

Species distinguishing between regions

Low shoreMaputaland low-shore sites were on average 70.04% dissi-milar to those in Natal, with 44 taxa accounting for 80% ofthis dissimilarity (Table 4). P. perna was the top-rankingdistinguishing species, accounting for 8.36% of the dissi-milarity, with an average cover of only 11.58% in Maputa-land, but 51.25% in Natal. T. squamosa rufotincta and P.perna constituted the most consistent distinguishingspecies.

Only 13 species contributed >2% each to the averagedissimilarity between Maputaland and Natal. After P. perna,most of these were algal species that were more commonin Maputaland than Natal, e.g. S. elegans, C. sagittatum,S. crassifolium, Laurencia glomerata and Caulerpa race-mosa (Figure 7). Two species of algae, Hypnea spicifera

and H. intricata, were, however, almost absent fromMaputaland but were characteristic species in Natal. Threeother invertebrate species were characteristic of Maputa-land low shores: the ascidian Pyura stolonifera, thepolychaete Idanthyrsus pennatus and the barnacle T.squamosa rufotincta.

Mid shoreThere was a 74% dissimilarity between Maputaland andNatal, and Table 4 summarises the 30 species thatcumulatively contributed to 80% of the dissimilarity. In all,12 taxa individually accounted for >2% of the overalldissimilarity. Among these, barnacles were importantdistinguishing species. T. squamosa rufotincta was domi-nant in Maputaland, whereas Octomeris angulosa andTetraclita serrata were prevalent in Natal (Figure 7). T.squamosa rufotincta and the alga Dictyosphaeria versluysii,both characteristic of the mid-shore sites in Maputaland,were the most consistent distinguishing species (Table 4).The articulated coralline alga, J. verrucosa, was moreabundant in Natal and was the most important disting-uishing alga (Figure 7).

Discussion

Biogeographic breaks and regional differences incommunity structure

The substantial quantitative differences in low- and mid-shore community structure between Maputaland sites andthose from the three pre-defined regions farther southjustify the division of the KwaZulu-Natal coast into at leasttwo biogeographic regions. The differences betweenMaputaland and Natal suggested by Jackson (1976), whoidentified the area between Mabibi and Cape Vidal as theboundary between a tropical province and a subtropicalarea farther south, are thus confirmed by this study. Thelow shore of Cape Vidal Point clustered with shores fromMaputaland, whereas the mid shore of this site clusteredwith sites from Natal. Cape Vidal Point is thereforeconsidered as the boundary between the two biogeo-graphic regions. These two regions will hereafter bereferred to as Maputaland (extending from Cape Vidal toat least the Moçambique border) and Natal (Cape Vidalto at least Port Edward), whereas KwaZulu-Natal refersto the entire coastline examined (Moçambique border toPort Edward, Figure 2).

In the high and top shore there were no significantdifferences identified between Maputaland and Natal but,from a biogeographic perspective, less emphasis shouldbe placed on these zones for two reasons. First, only aminority of the species occurred in high and top shore (22and 46 respectively out of a total of 220 species in thepresent surveys). Second, average similarity between siteswas also much greater in the high, and particularly thetop shore, compared with the low and mid shore, reflectingconvergence of community structure in the upper zones,as reported in several other studies (Stephenson andStephenson 1972, Lubchenco et al. 1984, McGuinness1990). This pattern suggests that the communities in theupper shore are constrained by relatively uniform stresses

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such as desiccation and high temperatures (Bustamante etal. 1997). Lower on the shore, diverging abiotic conditions(such as wave action and sand inundation), greater diversityand stronger biological interactions (e.g. competition andpredation) may lead to greater dissimilarities between sitesand regions.

The zoogeographic analysis of Emanuel et al. (1992)divided the subtropical East Coast into two distinct sub-provinces with a transition just north of Durban. Both theresults presented here and Jackson’s (1976) study failed

to detect a change in intertidal community structure nearDurban, although Stephenson (1944) traced a gradualreduction of intertidal species southwards from thesubtropical East Coast towards the cool-temperate WestCoast, recording the subtraction of 11 species betweenDurban and Port Edward. Jackson (1976) attributed herfailure to detect this trend to disproportionate sampling effortin different areas. The results presented here are, however,based on equal sampling efforts and still fail to identify anybreak near Durban or any difference in community structure

Av% Av% Di/ Av% Av% Di/Distinguishing species (Map) (Nat) SD(Di) ΣDI% Distinguishing species (Map) (Nat) SD(Di) ΣDI%

Low shore (D = 70.04%) Mid shore (D = 74.08%) Perna perna 11.58 51.24 1.72 08.36 Tetraclita squamosa 27.35 00.44 2.69 09.71Sargassum elegans 13.06 02.31 1.42 13.09 Octomeris angulosa 00.59 23.76 1.16 17.03Cheilosporum sagittatum 17.84 05.75 1.22 17.74 Jania verrucosa 00.10 20.10 1.01 23.92Hypnea spicifera 00.28 07.34 1.42 21.28 Palythoa nelliae 10.16 12.63 1.31 29.58Laurencia glomerata 05.23 00.00 0.96 24.21 Hymeniacedon sp. 07.19 00.04 1.61 34.25Caulerpa racemosa 04.87 00.55 1.49 27.01 Encrusting corallines 11.03 02.32 1.24 38.72Pyura stolonifera 04.70 00.32 1.26 29.73 Bare rock 15.43 13.30 1.43 43.01Idanthyrsus pennatus 07.19 00.16 0.79 32.40 Dendropoma tholia 05.67 00.01 0.98 46.39Sargassum crassifolium 03.27 00.15 1.27 34.87 Idanthyrsus pennatus 04.84 00.03 0.84 49.28Hypnea intricata 00.35 03.82 1.30 37.30 Ralfsia sp. 00.79 05.01 1.38 52.01Tetraclita squamosa 02.16 00.03 1.89 39.46 Jania adhaerens 05.59 00.25 0.63 54.63Chamaedoris delphinii 01.95 00.06 1.62 41.53 Tetraclita serrata 00.00 02.70 1.15 57.09Palythoa nelliae 03.61 00.14 0.85 43.58 Zoanthus natalensis 00.77 02.72 1.06 59.28Jania verrucosa 00.67 02.58 1.42 45.52 Pomatoleios kraussii 00.04 02.10 0.91 61.11Encrusting corallines 05.33 03.30 1.33 47.44 Gelidium 00.79 01.11 1.04 62.76Unidentified green ascidian 02.08 00.00 1.13 49.29 Laurencia pumilla 00.93 00.65 1.12 64.29Plocamium corallorhiza 00.32 01.93 1.59 51.07 Neomeris sp. 0 01.87 00.34 0.58 65.800Jania adhaerens 01.55 00.03 1.27 52.70 Gelidium reptans 00.84 00.68 1.17 67.15Valonia macrophysa 01.29 00.01 1.28 54.31 Arthrocardia sp. 00.01 01.59 0.65 68.46Sand 00.46 02.10 0.95 55.89 Padina boryana 00.81 00.09 1.17 69.72Laurencia pumilla 02.15 00.00 0.74 57.42 Dictyosphaeria versluysii 00.49 00.00 1.62 70.89Caulerpa filiformis 00.00 02.99 0.65 58.91 Saccostrea cuccullata 00.18 00.79 1.27 72.06Hymeniacedon sp. 01.09 00.01 1.15 60.29 Ulva spp. 00.31 01.20 0.78 73.200Unidentified sandy ascidian 01.03 00.00 1.19 61.66 Cellana capensis 00.67 00.14 1.500 74.25Octomeris angulosa 00.03 01.00 1.18 62.99 Scutellastra natalensis 00.00 00.49 1.100 75.300Spyridia hypnoides 00.20 01.46 1.20 64.28 Perna perna 00.73 00.68 1.200 76.33Ralfsia sp. 01.83 02.18 1.41 65.56 Laurencia glomerata 01.78 00.00 0.43 77.33Arthrocardia sp. 00.76 00.99 1.06 66.80 Brown ephemeral algae 00.51 00.11 0.79 78.23Bare rock 00.91 01.39 0.90 68.04 Hypnea intricata 00.00 01.22 0.44 79.09Arthrocardia carinata 00.05 01.63 0.68 69.16 Laurencia natalensis 00.00 00.46 0.67 79.91Scutellastra pica 00.72 00.02 1.18 70.22 Zoanthus parvus 00.21 00.40 0.69 80.69Chondria armata 00.65 00.06 1.16 71.26Scutellastra aphanes 00.06 00.68 1.06 72.24Laurencia natalensis 00.18 00.56 1.09 73.14Gelidium abbottiorum 00.00 01.27 0.56 74.01Byssus threads 00.52 00.16 0.88 74.81Unidentified algae 00.77 00.07 0.58 75.60Champia compressa 00.40 00.17 0.99 76.37Cladophora rugulosa 00.00 00.44 0.77 77.07Halimeda cuneata 00.13 00.37 1.03 77.75Polysiphonia sp. 00.10 00.47 0.64 78.41Callithamnion stuposum 00.21 00.28 0.97 79.05Ulva spp. 00.06 00.41 0.72 79.69Dictyota humifusa 00.27 00.03 1.02 80.29

Table 4: Major species distinguishing between Maputaland and Natal in the low and mid shores, as determined by SIMPER analyses.The ranking is determined by Di, the average contribution of each species to the overall dissimilarity between regions (D). Species areranked in order of importance. Av% indicates the average percentage cover of each species at sites within Maputaland (Map) and Natal (Nat).Di/SD(Di) is the ratio between Di and SD(Di), the standard deviation of Di. This ratio reflects how consistently the species abundance varieswithin each region. ΣDI% is the cumulative percentage contribution of each species to the overall dissimilarity. Only taxa accounting for 80%of the cumulative dissimilarity are shown

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between sites in Zululand, Central KZN and Southern KZN.Unlike the analysis of Emanuel et al. (1992), whichexamined both intertidal and shallow subtidal invertebrates(at depths <30m), the present study and Jackson’s analysiswere based on intertidal species only, but did include bothinvertebrates and algae. Marine biogeographical analysesare strongly influenced by the ocean depth to which theanalysis extends (Brown and Jarman 1978, Millard 1978,Turpie et al. 2000) and the greater range of depths includedin the analysis of Emanuel et al. (1992) may have exertedan appreciable influence on the observed biogeographicpattern. More importantly, the analysis of Emanuel et al.(1992) was conducted at a time when few surveys hadbeen undertaken in Maputaland, so the data available fortheir analysis were less reliable than now.

The >70% dissimilarity between Maputaland and Natal

recorded here was substantially greater than the 45%dissimilarity reported by Jackson (1976). This differencemost likely reflects different sampling techniques andanalyses. The present study was based on equal samplingeffort at all sites, whereas Jackson devoted disproportionateamounts of collecting time in different areas and samplingeffort varied between sites. Jackson (1976) included poolsin her study, but pools and gullies were excluded in thepresent study. Nevertheless, despite these differences inmethods, a similar biogeographic pattern was observed.

Emanuel et al. (1992) used presence or absence dataat 100-km intervals. Jackson (1976) used semi-quantitativemeasures to sample 10 sections of coast with one or moresites visited per section, relying on abundance ratings fora checklist of 53 species. The present analysis was basedon quantitative data from replicated samples incorporating

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Figure 7: Mean percentage cover for species distinguishing between Maputaland and Natal in (a) low and (b) mid-shore site pairs. Datafor less abundant taxa have been multiplied (x3)

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220 species. The central conclusion, that there is a clearbiogeographic break at Cape Vidal but none south of there(at least as far as Port Edward), is therefore likely to berobust.

Species characterising and distinguishing regions

The most important species contributing to the dissimilaritybetween Maputaland and Natal was P. perna, which waspresent in both regions but at much lower densities in thenorth (Figure 7). Other workers have also noted the reducedabundance of P. perna in Maputaland. Jackson (1976) ratedmussels as occasional (2/5 on her rating system) to frequent(3/5) in Maputaland, but abundant (4/5) or exceptionallyabundant (5/5) in Natal. Fielding et al. (1991) reported thatmussels occurred only as individuals or in small clumps inMaputaland, whereas dense mussel beds occurred farthersouth. In the present study, high mussel densities were,however, recorded at Island Rock, a Maputaland siteinaccessible to harvesters, and intermediate mussel coverwas found at two ‘no-take’ Maputaland sites, Cape VidalPoint and Sodwana Point. Stephenson and Stephenson(1972) compared Natal shores with those of Inhaca Islandin Moçambique on the basis of descriptions by Kalk (1958,1959) and Isaac (1956) and cited reduced mussels atInhaca as a principal distinguishing feature. Studiescomparing recent and abandoned shell middens inMoçambique report recent local extinction of P. perna onInhaca Island, allegedly as a result of subsistenceharvesting (de Boer 2000).

Other invertebrates that played a prominent role indistinguishing the low-shore communities of Maputalandfrom Natal were the solitary ascidian P. stolonifera and asessile polychaete Idanthyrsus pennatus (Figure 7). Highercover of I. pennatus at Inhaca was cited as an importantdistinguishing feature between Moçambique and Natal(MacNae 1962, Stephenson and Stephenson 1972). P.stolonifera was on average almost 15 times more abundantin Maputaland than in Natal, despite being an importantfood source for subsistence collectors in Maputaland (Kyleet al. 1997). P. stolonifera extends from Namibia rightaround the southern African coast into tropical waters insouthern Moçambique (Day 1974, Berry 1982) and P.stolonifera beds are a characteristic and dominant featureof the very low shore and shallow subtidal on the SouthCoast (Stephenson and Stephenson 1972). Therefore,dense cover of P. stolonifera in the low shore is not uniqueto temperate shores. Large areas of Pyura have also beenrecorded at Inhaca Island (Stephenson and Stephenson1972). Genetic sequencing of P. stolonifera should beundertaken to test whether these tropical and temperatepopulations are different species. The taxonomy of Pyurais poorly understood (Clarke et al. 1999).

Several algae were also important distinguishing speciesbetween the two biogeographic regions. H. spicifera is thedominant low-shore alga in Natal, but was almost absentin Maputaland and is absent from Inhaca (Stephenson andStephenson 1972). It has, however, been recorded inKenya, Madagascar and Mauritius (Silva et al. 1996). S.elegans was more abundant in Maputaland than Natal and

has been reported as replacing H. spicifera in Maputaland(Jackson 1976). Other algae that characterised the lowshore in Maputaland (and which have also been reportedin Moçambique) were S. crassifolium and Chamaedorisdelphinii (Stephenson and Stephenson 1972).

In the mid shore, three species of barnacles wereimportant in distinguishing between regions, conforming toJackson’s (1976) observations. Tetraclita squamosa wasthe top ranking, most consistent distinguishing species, onlybeing recorded in any numbers in Maputaland in both thepresent and Jackson’s studies. This species is consideredtropical and has been recorded at Dar es Salaam, Aldabra,Seychelles, Mauritius and in the Red Sea (Hartnoll 1976).T. serrata has previously been recorded in South Africa andMadagascar (Hartnoll 1976) and was characteristic of Natal,along with Octomeris angulosa. Stephenson and Stephen-son (1972) also documented O. angulosa and T. serrataas characteristic of shores in Natal. Several speciescharacterising Maputaland are therefore tropical, extendingwidely into East Africa and the tropical Indo-West Pacific,whereas those characterising Natal have temperatesouthern African affinities.

Biogeographic affinities

The observed differences in intertidal species compositionand abundance between Maputaland and Natal areconsistent with previously described differences betweenMoçambique and Natal (Stephenson and Stephenson1972). The top five distinguishing low-shore speciesidentified by the present study (Figure 7) were also listedas key species distinguishing Natal and Inhaca Island(Stephenson and Stephenson 1972). The similarity betweenthe low and mid shores of Maputaland and tropical shoresfarther north (e.g. Moçambique and Tanzania) suggest thatMaputaland falls within the tropical Indo-West PacificProvince, a large biogeographic region that spans half theglobe, extending from East Africa to eastern Australia(Lüning 1990), although it may form a distinct sub-provincethat extends to some (as yet undetermined) extent intosouthern Moçambique. The species complement of algaein Maputaland reflects these tropical affinities, whereasspecies composition in Natal is more subtropical and hasaffinities with that of the warm-temperate South Coast(Hommersand 1986, Silva et al. 1996). Quantitative intertidalsurveys north of the Moçambican border are required toestablish the relationship between shores in Maputalandand tropical shores to the north. As the central and northernMoçambique coast is sheltered from wave action, Jackson(1976) suggested the exposed East Coast of Madagascaras an appropriate tropical area with which to compareKwaZulu-Natal shores. This would provide more informationabout the tropical affinities of Maputaland and Natal shores.

Bolton and Anderson (1997) have argued against theexistence of a subtropical province in KwaZulu-Natal,because the flora reflects an eastwardly decreasing numberof temperate South Coast Agulhas Province species,replaced largely by Indo-West Pacific species. On thesegrounds, the biogeographic province of Natal could beregarded as an extended eastern overlap between the

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South Coast Agulhas Province and the Indo-West PacificProvince. Bolton and Anderson (1997) suggested that thisoverlap extends from East London to Moçambique,including the entire KwaZulu-Natal coast. However, theresults presented here suggest that Natal does constitutea separate subtropical province, as advocated by Jackson(1976), because there is >70% dissimilarity between it andMaputaland. However, quantitative surveys need to beundertaken between Port Edward and East London toassess whether there is a clear distinction in intertidalcommunity structure similar to that found at Cape Vidal. Ifsuch a distinction is identified, this would justify theclassification of a discrete subtropical Natal Province andpinpoint its southern boundary. There is evidence from otherstudies that Natal may be different from the warm-temperateSouth Coast Agulhas Province when the distribution andabundance of both intertidal invertebrates and algae aretaken into account (Stephenson 1948, Emanuel et al. 1992,Bustamante and Branch 1996). One limpet species that isabundant on the temperate South Coast Agulhas Province,Scutellastra cochlear (Stephenson 1944, Field and Griffiths1991, Bustamante and Branch 1996), is absent except atthe most southern sites in KwaZulu-Natal. This supportsthe contention that Natal rocky shores differ in speciescomposition from those in the temperate South CoastAgulhas Province and comprise a discrete subtropicalprovince. Surveys between Port Edward and East Londonare currently underway.

The present study was based on abundance data andnot presence/absence data. The clear biogeographic patternthat emerged indicates the value of examining relativeabundance when resolving biogeographic patterns. The fourmost important low-shore species and the 11 most importantmid-shore species distinguishing between Maputaland andNatal were not absent from either region, but had large andconsistent differences in abundance between regions.However, there were also species that were confined toonly one of these biogeographic regions. Laurenciaglomerata, L. pumilla, Dictyosphaeria versluysii and twounidentified ascidians were found only in Maputaland.Conversely, T. serrata, S. natalensis, Hypnea intricata andLaurencia natalensis were absent from Maputaland. Weconsider the community approach to have wide applicationin conservation planning. In meeting conservation targets,representative areas including different biologicalcommunities and viable populations (not isolated records)of resource species need to be set aside in marine reserves.Studies based on presence/absence data do not allowmanagers to assess the abundance of any taxa within amarine reserve. Regional differences in abundance of sometaxa may also reflect important ecological differences suchas contrasting trophic patterns that may indicate differentecosystem processes that need to be considered inconservation planning. A drawback of the methodsemployed in this study is that patterns are based ondominant taxa and meiofuna and rare species are notexplicitly considered. However, inclusion of differentmacroalgal or macrofaunal assemblages in marine reservesshould cover distinct microalgal or meiofaunal communitiesthey support.

Determinants of large-scale patterns

The distribution and abundance of species on largegeographic scales is governed by large-scale dispersal andinfluenced by oceanographic conditions (Druehl 1981,Raffaelli and Hawkins 1996, Menge and Branch 2001). Mostinvertebrates have a planktonic larval phase that will bestrongly affected by the physical oceanographic environ-ment (Connolly and Roughgarden 1999). Large-scaledifferences in structure and abundance of intertidal commu-nities have been linked to nearshore oceanographicconditions, including phytoplankton concentration, produc-tivity and water temperature (Bustamante et al. 1995, Mengeet al. 1997a, 1997b, 1999).

The boundaries of the biogeographic provinces in SouthAfrica correspond closely with oceanographic conditions.The West Coast is influenced by the cold, relatively slowBenguela Current that drifts northwards, and upwelling ischaracteristic along that coast (Brown and Jarman 1978,Branch and Griffiths 1988). On the East Coast, the warmAgulhas Current is a well-defined, intense jet approximately100km wide and more than a kilometre deep, which movesrapidly down the South-East Coast (Shannon 1985,Schumann 1998). Upwelling on the West Coast and itsvirtual absence on the East Coast has resulted in aproductivity gradient around southern Africa (Shannon 1985,Brown and Cochrane 1991, Brown et al. 1991). Large-scalevariations in biomass and community composition along theSouth African coast have been linked to these gradients ofprimary production and nutrient concentrations (Bustamanteet al. 1995). Wave action has also been implicated as apotential determinant underlying biogeographic patterns(Jackson 1976, McClurg 1988). Near-shore oceanographyhas been poorly studied in KwaZulu-Natal and future studiesin this field are likely to improve understanding of large-scale patterns.

The role of environmental factors in establishing theobserved biogeographic patterns in KwaZulu-Natal intertidalcommunities needs to be investigated. This is particularlyimportant because regional differences in humanexploitation could be contributing to differences in thecomposition of biota between Maputaland and Natal. Mostshores in Maputaland are subject to intensive subsistenceharvesting, whereas Natal shores are exploited byrecreational collectors who harvest far less (Kyle et al.1997, Tomalin and Kyle 1998). Umfazazana, the onlydocumented subsistence-exploited site in Natal, proved tobe more similar to subsistence-exploited sites fromMaputaland than to any other sites in Natal. An importantresource species, P. perna, was the most obvious speciesdistinguishing between regions, being much less abundantin Maputaland where shores are intensively exploited.Therefore, the role of subsistence harvesting in determininglarge-scale patterns in community structure warrantsinvestigation. The potential determinants of the observedbiogeographic pattern and in particular the extent thatharvesting contributes to regional differences in communitystructure has been examined (Sink 2001).

The other important intertidal resource species targetedin KwaZulu-Natal, redbait Pyura stolonifera, is more abundant

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in Maputaland than farther south, despite higher exploitationin Maputaland (Kyle et al. 1997). However, there are threesites in Maputaland that are not subject to exploitation, andthese have high densities of P. stolonifera that bias the overallabundance estimate for the region. P. stolonifera is acommon bait organism and its exploitation in Natal by anglersmay account for its low abundance there. There is, however,some evidence that P. stolonifera competes with P. perna(Berry 1982), so its relative scarcity in Natal may be onaccount of the abundance of P. perna. Distinguishingbetween the roles of abiotic factors, biological interactionsand human exploitation on the abundance of these species(and hence biogeographic patterns) is a priority.

Implications for conservation

All biogeographic regions should be represented in ‘no-take’marine reserves (Hockey and Branch 1994, 1997, Robertset al. 2003a, 2003b). Jackson (1976) proposed two marinereserves along the KwaZulu-Natal coast, one in Maputalandand one in Natal. Currently, approximately 150km of the560km-long KwaZulu-Natal coastline lies in marineprotected areas, with 144km of this falling in Maputaland,i.e. north of Cape Vidal (Figure 2). Only 4.8km (including2km of rocky shore) is conserved in Natal, i.e. in theTrafalgar Marine Reserve (Mann et al. 1998). The Maputa-land and St Lucia Marine Reserves include only rockyshores typical of the Maputaland biogeographic region. TheTrafalgar Marine Reserve in Natal was established toconserve intertidal fossils. However, it is wave-sheltered(Sink 2001) and not representative of the coast as a whole,although it does host extensive subtidal seaweedcommunities (Mann et al. 1998). The intertidal resourcesthat are most heavily exploited in Natal (P. perna and P.stolonifera) are not present at Trafalgar, so they receive noprotection anywhere in the Natal biogeographic region.

Although Maputaland shores between Kosi Mouth andMabibi fall within the Maputaland Marine Reserve, subsis-tence harvesters have exploited all the shores there forgenerations, and continue to do so except at Island Rock,which is protected by virtue of its inaccessibility. In theadjacent St Lucia Marine Reserve, approximately 20km ofshore (including about 4km of rocky ledge) is managed asa sanctuary and is completely unexploited. At all othershores, including the Maputaland, St Lucia and TrafalgarMarine Reserves, shore-angling is permitted. In the absenceof representative habitats closed to all forms of fishing andharvesting, the effects of harvesting and shore-angling inKwaZulu-Natal cannot be unambiguously assessed.

Another important result that emerged from the presentstudy is the extent of the between-site differences incommunity structure. Such smaller-scale patterns incommunity structure need to be understood and incor-porated into marine protected areas to ensure adequatecoverage of the full spectrum of habitat and biologicaldiversity in KwaZulu-Natal.

In conclusion, there is a distinct biogeographic break inKwaZulu-Natal between Maputaland to the north and Natalto the south. The biota in Maputaland shows affinities withthe large tropical Indo-West Pacific Province. Natal is a

subtropical region extending south into Transkei. KwaZulu-Natal urgently requires additional marine reserves in theNatal Province. Furthermore, the practice of allowingintensive subsistence harvesting throughout the MaputalandMarine Reserve, a component of the World Heritage Site,the Greater St Lucia Wetland Park, and inshore fishingalong most of KwaZulu-Natal, should be re-evaluated.Without benchmark studies in fully protected ‘no-take’ areas,harvesting impacts cannot be assessed and the issue ofwhether harvesting is sustainable or optimal can never beadequately resolved.

Acknowledgements — Financial support and running costs for thisresearch were received from a doctoral bursary via a South AfricanNetwork for Coastal and Oceanographic Research and NationalResearch Foundation Grant to GMB, funds from the MellonFoundation and a Pew Fellowship awarded to JMH. Ezemvelo KZNWildlife is thanked for logistical support.

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Manuscript received February 2003; accepted August 2003

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