Surveys of white sharks (Carcharodon carcharias) off bathing beaches in Algoa Bay, South Africa

Surveys of white sharks (Carcharodon carcharias) offbathing beaches in Algoa Bay South Africa

M L DickenAB and A J BoothA

ADepartment of Ichthyology and Fisheries Science Rhodes University PO Box 94 Grahamstown

6140 South AfricaBCorresponding author Email raggedtoothsharkbayworldcoza

Abstract The present study provides information on the existence of a possible inshore nursery area for white sharks(Carcharodon carcharias) in Algoa Bay South Africa In total 43 flights were conducted using a Robinson R22

helicopter between October 2010 and March 2012 A total of 50 white sharks was sighted with a maximum sighting rateof seven sharks per hour in October 2010 The majority (960) of sharks observed were less than 25m in lengthimmature and sighted between October and March (980) A hurdle model comprising a logistic regression to modelpresencendashabsence and a log-normal generalised linearmodel for abundance showed thatwater temperature and barometric

pressure explained the sightings of sharks peaking in mid-December The sighting of sharks was best explained bybarometric pressure month and year A total of 58 white shark catches was recorded from key informant interviews withshore anglers between July 2009 and December 2011 Sharks ranged in size from 15 to 25m in total length with young-

of-the-year sharks (175m) accounting for 690of the catch Defining key habitats for young-of-the-year and juvenilesis critical for the management and conservation of white sharks worldwide

Additional keywords aerial juvenile nursery area shore angling

Received 27 November 2012 accepted 10 February 2013 published online 24 April 2013

Introduction

The white shark Carcharodon carcharias is a wide-rangingspecies with a cosmopolitan distribution in temperate andtropical waters worldwide (Compagno 2001) In South Africa

its regional centre of abundance extends along the eastern coastfrom False Bay in the Western Cape to KwaZulundashNatal (KZN)in the north-east (Bass et al 1975 Compagno 2001) Existing

white-shark research both in South Africa (Martin et al 2005aLaroche et al 2007 Martin et al 2009 Fallows et al 2012) andinternationally (Pyle et al 1996 Goldman and Anderson 1999

Robbins 2007 Domeier and Nasby-Lucas 2008 Skomal et al2012) has focused primarily on adult sharks (35m) at island-based pinniped colonies Although these studies have begun toelucidate the biology of adult and subadult white sharks little is

known about the movements and habitat preferences of juvenile(25m) sharks particularly in South Africa (Dudley 2012)

Although little research has been conducted on white sharks

in the Eastern Cape young-of-the-year and juvenile whitesharks have been recorded by anglers (Smith 1951 Dicken2008) and in Algoa Bay scavenging from a whale carcass

(Dicken 2008) Ferreira and Ferreira (1996) using unpublishedcatch data noted that Algoa Bay has the highest number ofrecorded catches for small (160 cm) sharks within South

Africa On the basis of these observations it has been suggestedthat the inshore waters of Algoa Bay may be a white-sharknursery ground (Cliff et al 1996 Dicken 2008)

Electronic-tagging studies (Dewar et al 2004 Weng et al

2007 Bradford et al 2012 Bruce and Bradford 2012) andincidental catches (Bruce 2008 Santana-Morales et al 2012)have shown that young-of-the-year and juveniles are found

mainly in near-shore waters Their proximity close inshore forextended periods of time not only makes them vulnerable toby-catch in commercial and recreational fisheries (Casey and

Pratt 1985 Klimley 1985 Malcolm et al 2001 Weng et al

2007) but also potentially increases the chance of humanndashsharkinteractions This is of particular concern because the number of

white shark attacks both in South Africa (Cliff 2006) as well asworldwide (Burgess and Callahan 1996 Curtis et al 2012) hasbeen gradually increasing Although unprovoked attacks bywhite sharks are infrequent there is a growing pressure on local

governments to implement mitigating measuresAerial surveys using a helicopter or a fixed-wing aircraft can

be an effective method to detect the presence of individuals that

are sparsely distributed over large areas (Quang andBecker 1996Nishi and Buckland 2000 Pollock et al 2006) Marine aerialsurveys have focused primarily onmammals that spend a consid-

erable amount of time at the surface such as dolphins whalesdugongs and turtles (Barlow et al 1988Marsh and Sinclair 1989Cockcroft et al 1992 Cardona et al 2005 Pollock et al 2006

OrsquoDonoghue et al 2010) Although sharks spend less time at thesurface and do not usually aggregate aerial surveys have beensuccessfully employed to detect whale sharks (Rhincodon typus)

CSIRO PUBLISHING

Marine and Freshwater Research

httpdxdoiorg101071MF12336

Journal compilation CSIRO 2013 wwwpublishcsiroaujournalsmfr

basking sharks (Cetorhinus maximus) (Wilson 2004 Burks et al2005 Cliff et al 2007 Rowat et al 2009) and lemon sharks

(Negaprion brevirostris) (Gruber et al 1988)When present white sharks are commonly visible in the surf

zone within a few hundred metres from shore This behaviour

renders them easily visible from the air and thus easily countedduringaerial surveysAerial surveys ofhigh-risk beach areas havebeen used intermittently in bothAustralia and theUnited States to

inform beachgoers of the presence of potentially dangerousspecies such as white sharks tiger sharks (Galeocerdo curvier)and bull sharks (Carcharhinus leucas) (Curtis et al 2012)

Anecdotal reports from shore-based anglers suggest that the

number of white sharks at certain beaches within Algoa Bayhave increased in recent years Recreational shore-basedangling is a form of linefishing where fish are caught using a

hook and line and comprises both a social as well as a moreformal organised competitive sector (van der Elst 1989) It is oneof the most popular sport and outdoor recreational activities in

South Africa with an estimated 412 000 fishers (McGrath et al1997) Although white sharks are a threatened species and fullyprotected in South Africa (Compagno 1991) they are occasion-ally caught incidentally while fishing for other large species of

shark such as raggedtooth (Carcharias taurus) dusky (Carch-arhinus obscurus) and bronze whaler (Carcharhinus bra-

chyurus) sharks (Dicken et al 2012)

Incidental catches have been effectively used to determinethe spatial distribution and ecology of juvenile white sharks inthe near-shore environment (Klimley 1985 Clua and Seret

2010 Santana-Morales et al 2012 Lowe et al 2012) Informa-tion on white-shark catches from shore anglers provides useful

information that can augment data obtained from aerial surveysIt also provides an important insight into fishery interactions thatcould potentially be used to assist in developing strategies to

minimise fishery-induced mortalityUsing a combination of aerial and shore angling surveys the

current paper presents the first quantitative study on the seasonal

occurrence and size of white sharks off beaches within AlgoaBay and indeed anywhere in South Africa The occurrence ofsharks is compared to various environmental parameters toelucidate factors influencing their near-shore use This informa-

tion is critical not only tominimise the risk of encounter betweensharks and people but also in identifying important nursery-areahabitat for juvenile white sharks

Materials and methods

Study area

Algoa Bay is a wide relatively shallow (depth70m) eastward-facing bay (Schumann et al 2005) The bay coastline extendsfor 90 km between the headlands of Cape Recife in the west and

Woody Cape in the east (Fig 1) Two large perennial rivers theSwartkops and Sundays Rivers flow into the bay The Islands ofthe Cross comprising St Croix Brenton and Jahleel are located

1ndash3 km offshore between the Swartkops and Sundays riversystems A second island group comprising Bird Seal Stagand Black Rocks is located8 km offshore fromWoody Cape

SwartkopsRiver

PE harbour

Cape Recife

Ngquraharbour

Jahleel

2

3

CapeTown

PortElizabeth

Durban

Brenton

St Croix15

15

20

15

15

1

4

5

20

2030

2020

Flight path

White shark aerialsightings 2010ndash2012

White shark catches

4 4 Kilometers2 0

30

3015

15

50

50

30

20

1515

20

Fig 1 Location of the Algoa Bay study area indicating the zone of aerial survey shark sighting and shore-angling catches Map

insert shows the location of Algoa Bay in relation to the South African coastline

B Marine and Freshwater Research M L Dicken and A J Booth

This group of islands is a known winter (May to October)aggregation site for white sharks (Dicken et al 2013)

Algoa Bayrsquos physical oceanographic conditions are influ-enced by the Agulhas Current that brings warm water from thetropics southward along the eastern coast (Shannon 1989)

Although surface water temperatures generally range between168C and 208C (Schumann et al 2005) the bay is subject tointermittent wind-induced coastal upwelling that can reduce

water temperatures to below 128C (Schumann et al 1982Beckley 1983) The shoreline is dominated by sandy beacheswhich are subject to high-energy swells and wave heights thatmay exceed 5m during storm conditions Within the bay local

bathymetry and weather systems result in varied oceanographicconditions over spatial scales of kilometres and over time scalesof days (Schumann et al 2005)

Aerial surveys

Aerial surveys were conducted from a Robinson R22 helicopter

The aircrew consisted of a pilot and an observer both of whomwere experienced in aerial survey techniques The sameobserver was used on every survey to exclude the possibility ofobserver bias Fixed line transects of approximately 1-h

endurance were flown from Cape Recife to St Croix Island andback covering a distance of 80 km (Fig 1) The flight path wasconducted300m from the shoreline at an average altitude and

speed of 300m and 90 kmh1 respectively This provided atransect width of 600m within which individual animals15m in total length could be reliably observed (Marsh and

Sinclair 1989 Robbins et al 2012) The water depth within thesurveyed transect was less than 15m (Bremner 1991) The fly-ing speed and altitude used in the study were selected to reduce

the probability of perception error (Marsh and Sinclair 1989Redfern et al 2002 Pollock et al 2006) and are more conser-vative than those commonly employed for other marine taxa(McClellan 1996 McDaniel et al 2000 Shelden and Laake

2002 Rowat et al 2009)Between two and four surveys were flown in every month of

the study period Surveys were conducted only when environ-

mental conditions were suitable for sharks to be observed in thenear-shore environment The ability to see sharks depends on theangle of the sun and glare sea-surface state water clarity swell

size cloud cover andwind speed and direction (Ross et al 1989Pollock et al 2006) As a result surveys were conductedbetween 1000 hours and 1200 hours (CAT) and only in windconditions below Beaufort Scale 3 that provided an acceptable

sea-surface state to detect sharks (Marsh and Sinclair 1989Shelden and Laake 2002 Pollock et al 2006) Swell height hadto be less than 15m and the cloud ceiling above 300m with no

rain Water clarity and percentage cloud cover were estimatedby the onboard observer Water clarity was estimated using ascale of 3 where 1frac1410m 2frac14 5ndash10m and 3 =5m Air

temperature barometric pressure and tidal height for eachsurvey were provided by the South African Weather ServiceFraction of the moon illuminated (lunar phase) was obtained

from the website (httpaausnonavymildatadocsMoonFrac-tionphp accessed October 2012) Sea temperature wasrecorded using an lsquoOnset Hoborsquo water-temperature logger(Onset Computer Corporation Cape Cod MA) which was

permanently deployed at a depth of 15m at St Croix Island

Water temperature at this depth is considered to be representa-tive of the upper mixed surface layer (Schumann et al 2005)

When a white shark was spotted the helicopter was allowedto temporarily deviate from the survey path and circle or hoverto confirm its identity and where possible take photographs

A GPS waypoint was taken for each shark sighted the directionof flight path together with the time of sighting its size (totallength) distance from beach swim direction the number of

sharks present and the presence of any fish schools or otheranimals If a shark was observed on both the outbound andinbound flight within 200m of the original sighting and was of asimilar size it was considered a duplicate and was not included

in any analysisThe life-history stage of sharks sighted was defined accord-

ing to the definitions of Bruce and Bradford (2012) and

included the following young-of-the-year (YOY) sharks(175m in total length TL) juvenile sharks (175ndash30min TL) subadult sharks (30ndash36m in TL for males and

30ndash48m in TL for females) and adult sharks (36m inTL for males and 48m in TL for females)

Statistical analysis

Preliminary analysis revealed that sighting-rate data from aerialsurveys were zero-inflated with 896 of data consisting ofzeros (Fig 2) Different statistical approaches have beendeveloped to account for this excess of zeros and can be cate-

gorised into mixture or two-part conditional models Mixturemodels or zero-inflated models (ZI) account for the zeroobservations as both lsquotruersquo zeros and lsquofalsersquo zeros (Lambert

1992) lsquoTruersquo zeros are accounted for by one of several discreteprobability distributions such as a Poisson or negative binomialhence the abbreviations ZIP or ZINB whereas an additional

binomial distribution accounts for the additional lsquofalsersquo zeros Inthe case of presencendashabsence or abundance data lsquotruersquo zeros arethose samples where no organisms were sampled because theywere actually absent whereas lsquofalsersquo zeros are those samples

where sampling bias or inexperience resulted in no organismsbeing sampled despite them being present at the samplinglocality An extension for presencendashabsence data is the zero-

inflated binomial (ZIB) (Hall 2000 Martin et al 2005b) modelthat includes an additional parameter to separate the probabilityof an organism being present at a site even if it was not observed

All ZImodels however require count data and in the case of the

0

01

02

03

04

05

06

07

08

09

10

0 1 2 3 4 5 6 7

Sighting rate

Fre

quen

cy

Fig 2 Frequency of aerial white-shark sighting rates

Surveys of white sharks (Carcharodon carcharias) Marine and Freshwater Research C

ZIB model they also require repeated measurements at specificlocalities Two-part models by contrast assume that all

observed zeros are lsquotruersquo and model the zeros as a binomialprocess and positive observations as a truncated probabilitydistribution Two-part models are also called hurdle zero-

altered or delta models (Aitchison 1955 Pennington 1983Maunder and Punt 2004) because the lsquohurdlersquo of a value beingnon-zero must be overcome before the positive observations

conditional on at least one non-zero observation can be mod-elled Hurdle models can be applied to data that are either dis-crete or continuous on [0N] such as a log-normal or gammadistribution The general form of the hurdle model is

PrethY j x yTHORNfrac14pethxTHORN y frac14 0

eth1 pethxTHORNTHORN f ethyTHORN1 f eth0THORNTHORN y gt 0

(

where x denotes a random binary variable with 0 and 1 assignedto the positive and zero observations respectively and f(y)denotes the probability distribution chosen to describe the pos-

itive observations In hurdle models logistic regression modelszero sighting rates whereas positive values aremodelledwith anappropriate discrete or continuous generalised linear model

To account for zero inflation in these data a hurdle modelwas used to model the effect of environmental and temporalcovariates on both probability of presencendashabsence and abun-

dance (sharks hndash1) of white sharks A log-normal distributionwas considered because it is one of the most frequently assumeddistributions for positive catch rates (Myers and Pepin 1990 Ye

et al 2001 Fletcher et al 2005)The expected mean of the hurdle model with log-normally

distributed positive observations is

EethyTHORN frac14 eth1 pTHORN exp mthorn s2

2

where m and s are themean and standard deviation respectively

of the natural logarithm-transformed positive observations(Fletcher et al 2005)

Year sea temperature air pressure wind speed and directionair temperature tidal height fraction of the moon cloud cover

sea state and water clarity at the time of the surveys wereincluded in both models In addition seasonality (month) wasincluded in the logistic regression by including both the sine and

cosine angular-transformed month-of-the-year because it wasnoticed that the presencendashabsence of sharks was seasonal(Beamish et al 2005)Variables were selected using a stepwise

procedure using Akaikersquos information criterion (AIC) (Akaike1972) The most parsimonious of either the zero or the positivemodels had the lowest AIC

Model fit was assessed using a pseudo-R2 (McFadden 1974)calculated as 1 ndash LLreducedLLnull where LLreduced and LLnulldenote the log-likelihoods from the reduced model (that has themost parsimonious combination of variables) and the null model

(with only an intercept term) respectively

White-shark shore catches

Random sampling of white-shark catches from a defined list of

anglers within Algoa Bay was not possible for several reasons

First few anglers catch white sharks or have little knowledgeabout where or when to catch them Second it is illegal to target

white sharks and catches are rarely recorded and third there isno complete list of all anglers who fish within the Bay As aresult key-informant interviews were conducted with local

lsquoexpertsrsquo who were deemed to be the most knowledgeable andwilling to provide information on white-shark catches

Snowball sampling (Biernacki and Waldorf 1981 Babbie

1989 Salganik and Heckathorn 2004) in which respondentswere asked to identify other anglers who may perhaps haveknowledge of white-shark catches was used to generate anincreasing set of interviews through a referral process This is a

useful sampling technique to obtain rare information which isunevenly distributed within the target population and concen-trated within a small group of individuals (Neis et al 1999

Aswani and Lauer 2006)In total eight anglers were identified and interviewed every 2

months from October 2009 to August 2012 to provide informa-

tion on any white sharks they had either caught themselves orhad heard about Four of the anglers interviewed had beenfishing in Algoa bay for more than 40 years They were askedwhere and when the sharks had been caught how many sharks

had been caught and their sizes Given the relatively smallsample size and the limits of snowball sampling it was notpossible to use inferential statistics to estimate the total number

of white sharks caught within Algoa Bay The informationcollected however does provide useful background knowledgeon the seasonal timing and occurrence of white sharks which

can be used to augment the data collected from the aerialsurveys The data also provides an insight into current fishingpractices and the potential susceptibility of white sharks to

fishing mortality

Results

Aerial surveys

Forty-three surveys were conducted between October 2010 andMarch 2012 During 2317min of aerial survey time a total of 50

white sharks was observed (Fig 3) Shark sightings per hour

Fig 3 Aerial photo of juvenile white shark 2m in total length

swimming 100m from the shoreline in Algoa Bay

D Marine and Freshwater Research M L Dicken and A J Booth

varied within months among months and among years Apartfrom a single shark observed in May 2011 all of them weresighted in the spring and summer months between October and

March (Fig 4) The maximum sighting rate on a single surveywas 7 h1 in October 2010 Average monthly water tempera-tures between October and March in 20102011 were markedly

lower than those in 20112012 (by 018C to 758C) andcorresponded to a higher sighting rate of sharks (Fig 4)

All of the sharks observed were locatedmore than 4 km north

of the Port Elizabeth harbour with 820 being within 6 kmnorth and south of the Port of Ngqura (Fig 1) Sharks weresighted in the same areas in both study years Sharks wereobserved between 20m and 500m of the shoreline with the

majority (780) within 100m Direction of movement alongthe coast was varied with most sharks moving either north(400) or inshore (300) Sharks ranged in size from 15 to

4m with themajority (960) either YOY or juveniles (25min TL) Only four (80) of the sharks observed were within100m of a fish school

Other shark species observed during the surveys includedsmooth hound sharks (Mustelus mustleus) smooth hammerheadsharks (Sphyrna zygaena) whale sharks (Rhincodon typus) and

bull sharks (Carcharhinus leucas)

Generalised linear modelling (GLM)

Water temperature and barometric pressure were significantenvironmental variables in modelling the probability of observ-

ing a zero sighting rate (Table 1) with lower water temperaturesand higher barometric pressures increasing the probability ofobserving a shark Peak shark presence was predicted to be in

mid-December (Fig 5) for both 2010 and 2011 which was 2months later than what was actually observed This lag is areflection of average peak abundance over 2 years The binomial

GLM explained 29 of the variability within the data Baro-metric pressure month and year explained the highest abun-dances with an R2 of 041 although the only significant variable

was year with a steady decrease in catch rates over the studyperiod The combined model had a joint fit of R2frac14 034 (Fig 5)

White-shark catches

In total 58 white shark catches were recorded from the shore-angling survey Sharks ranged in size from 15 to 25m in TL

with YOY sharks (175m) accounting for 690 of the catchUnfortunately there was no information on the sex of the sharkscaught Almost all of the sharks (948) were caught in spring

and summer between themonths of September andMarch withmost sharks (621) being caught in October and November(spring) Although shark catches were recorded from five pri-

mary sites within the study area more sharks were caught atSites 1 (121) 2 (362) and 3 (414) located north of thePort Elizabeth harbour than at Sites 4 (86) and 5 (17) to thesouth (Fig 1) All of the sharks recorded in the survey were

released aliveMore sharks were caught in 2009 (nfrac14 24) and 2010 (nfrac14 26)

than in 2011 (nfrac14 8) This trend is similar to that of the declining

aerial sighting ratesobservedbetween2010and2011 Interviewed

0

1

1

3

33

32

2 2 2 2 2 2 2 2

3

3

2

4

2

3

4

5

6

7

8

Oct

Nov

Dec Jan

Feb

Mar

Apr

May

June

July

Aug

Sep

t

Oct

Nov

Dec Jan

Feb

Mar

Month

Sig

htin

g ra

te (

shar

ks h

1 )

0

50

100

150

200

250

Tem

pera

ture

(C

)

Fig 4 Mean monthly sighting rates (sharks h1) of white sharks between October 2010 and March

2012 as observed from Cape Recife to St Croix Island and average monthly water temperatures

Vertical lines represent standard error of the mean and inserted values the number of surveys conducted

in that month

Table 1 Estimated model coefficients for a delta model that regressed

sighting rate presence and absence (zero model) and magnitude (posi-

tives)ofwhite sharkagainst several environmentalandseasonalvariables

Data were collected from aerial surveys between October 2010 and March

2012 observed from Cape Recife to St Croix Island

Coefficient Estimate se P(t)

Zero model

Intercept 268132 157197 009

Water temperature 051 021 002

Barometric pressure 013 006 004

Year 126 078 011

R2 029

Positive model

Intercept 203016 57244 001


CosMonth 056 027 006

Year 102 028 001

R2 041

Combined model R2 034

Surveys of white sharks (Carcharodon carcharias) Marine and Freshwater Research E

anglers some of whom had been fishing for over 40 years statedthat before 2009 white sharks were rarely caught from the shore

Discussion

Aerial sightings and shore-angling catches indicated that both

YOY and juvenile white sharks occur close inshore at certainsites within Algoa Bay during the spring and summer In SouthAfrica inshore summer sightings of sharks have also been

observed at Mossel Bay Gansbaai and False Bay (Kock andJohnson 2006 Kock et al 2012 2013) These sharks howeverconsisted of both juveniles25m in TL and adults4m in TLHeupel et al (2007) defined a shark nursery area on the basis of

the following three criteria (1) neonate and small juvenilesharks are more commonly encountered in the area than they arein other areas (2) sharks have a tendency to remain or return for

extended periods and (3) the area or habitat is repeatedly usedacross years Although the results from the present study metCriteria 1 and 3 further research is required to establish whether

sharks are resident or simply on route to another area Thepresence of small sharks in Algoa Bay over time howeversuggests that parts of the bay are important spring and summer

habitat and core activity zones for YOY and juvenile whitesharks Elsewhere in the world inshore spring and summernursery grounds for white sharks have been identified insouthern California (Dewar et al 2004Weng et al 2007 Lowe

et al 2012) Mexico (Weng et al 2007 Santana-Morales et al2012) and the eastern coast of Australia (Bradford et al 2012Bruce and Bradford 2012 Werry et al 2012)

Previous research has suggested that the primary character-istics of a nursery area are predator avoidance (Holland et al

1993 Merson and Pratt 2001 Heupel and Hueter 2002) and an

abundant food source (Branstetter 1990 Castro 1993 Simpfen-dorfer andMilward 1993) The inshore distribution of YOY andjuvenile white sharks during the spring and summer separates

them from larger sharks commonly found within Algoa Bay atBird Island (Dicken et al 2013) It also separates them from themain component of the adult population in the Southern andWestern Capes In addition warmer waters and an abundance of

prey species in Algoa Bay would satisfy their energetic require-ments for growth For example a variety of elasmobranch

species including blue rays (Dasyatis chrysonota) sand sharks(Rhinobatos annulatus) and dusky sharks (Carcharhinusobscurus) pup close inshore from October to December espe-

cially at Sites 1ndash3 (Rossouw 1984 Ebert and Cowley 2003Dicken 2011) Juvenile white sharks may time their movementinshore to feed on these seasonally abundant species all of

which are commonly recorded from the stomach contents ofjuvenile great white sharks (Cliff et al 1989 Hussey et al

2012) Predictable seasonal events such as prey availability havealso been suggested to influence the occupancy of white shark

nursery areas in Australia (Bruce and Bradford 2012) and theinshore movement of white sharks in False bay South Africa(Kock et al 2013)

More white sharks were recorded in both the aerial and shore-angling surveys to the north than to the south of the Port Elizabethharbour Currents and rip-tides north of the harbour are much

stronger than to the south (Schumann et al 2005 Roberts 2010)These currents together with nutrient inputs from both theSwartkops and Sundays Rivers may increase the near-shoreproductivity of the area resulting in a greater abundance of

available prey Unfortunately there are no published studies onspatial and seasonal variations of primary production withinAlgoa Bay Current ongoing research however has indicated

that nutrient concentrations and primary production increase inthe vicinity of both the Swartkops and Sundays Rivers along theAlexandria Coastal Dunefield (through groundwater input) and

typically occur in the higher-rainfall period between June andOctober (T Bornman SouthAfrican Environmental ObservationNetwork pers comm) This may be a contributing factor

leading to the presence of more prey and hence more sharks atthis time of year The beaches in these areas are also closer todeeper water a factor considered by Krogh (1994) to be favour-able tohigher numbers ofwhite sharks alongbeaches inAustralia

Interestingly all of the sharks observed in the aerial surveysand the majority of sharks caught in the angler survey were frombeaches with an eastndashnorth orientation This is the same orienta-

tion as the Recife Bird Ridge a discontinuous and steep seawarddipping ridge considered the dividing line between Algoa Bayand the adjacent continental shelf (Bremner 1991) This orienta-

tion would be in line with the directed movement of sharks bothfrom the north and the south into Algoa Bay Beach orientationhas been suggested to increase the likelihood of temporaryresidency of sharks along the eastern coast of Australia (Werry

et al 2012)The rate of aerial sightings of white sharks was significantly

related to higher barometric pressures and lower water tempera-

tures The role that barometric pressure plays in influencing theabundance of white sharks close inshore however is unclearand may have been biased by the fact that more flights were

conducted on fine weather days which would typically havehigher barometric pressures It should also be noted that baro-metric pressure as well as water temperature may be indirect

controlling factors and that sharks are being influenced by oneor more other variables that are closely associated with themsuch as the availability of prey Although sharks were observedon days when the water temperature was as low as 118C themajority were observed in water temperatures ranging from

0

10

20

30

40

50

60

70

80

0

Oct

Dec

Feb Apr

Jun

Aug Oct

Dec

Feb

31 59 76 103 137 174 223 264 307 350 374 412 466 501

Julian days

Sig

htin

g ra

te (

shar

ks h

1 )

Observed sighting rate

Predicted sighting rate

Fig 5 Observed and delta model-predicted sighting rates (sharks h1) of

white sharks betweenOctober 2010 andMarch 2012 as observed fromCape

Recife to St Croix Island

F Marine and Freshwater Research M L Dicken and A J Booth

168C to 1758C This is similar to the preferred temperaturerange exhibited by YOY and juvenile white sharks in other

studies (Dewar et al 2004 Weng et al 2007 Bruce andBradford 2012)

Sighting submerged marine animals is difficult with a high

proportion of under-reporting (Barlow et al 1988 Ross et al1989 Robbins et al 2012) that would result in lsquofalsersquo zerosAnimals within sighting distance of observers will be missed if

they are swimming too deep or are inwater conditions thatmasktheir presence Robbins et al (2012) concluded that aerialobservers have limited ability to detect the presence of sharksdeeper than 25m or more than 300-m distant from the flight

path of the aircraft YOY and juvenile white sharks spend aconsiderable amount of time at the surface (0ndash5m) (Dewar et al2004Weng et al 2007 Bruce andBradford 2012) Despite this

however it is likely that some sharks remained undetectableduring the aerial surveys conducted in the present study andowing to the continuous nature of the data the probability of

accounting for the lsquofalsersquo zeros could not be determinedSatellite tracking of white sharks in Australia has revealed

that juveniles regularly move in and out of the surf zoneoccupying coastal waters to a depth of 120m (Bruce and

Bradford 2012) As a result the numbers of white sharksobserved during any given survey of the surf zone are only aproportion of those present in the nursery area This fact

together with detection bias and the high temporal variabilityin sighting rates precludes an estimation of the population sizeof sharks from the survey data The data do however provide a

useful index of the relative abundance and seasonal occurrenceof sharks which can be used as a reference point in monitoringfuture population trends

Several sources of bias are also inherent in the collection ofinformation regarding white-shark catches from shore anglersFirst some catches will not have been recorded during thesurvey leading to an underestimate in the number of sharks

caught Second the size of sharks caught from the shore will bebiased by the tackle used by anglers which prevents them fromlanding large sharks Despite these biases information on the

size seasonality and occurrence of sharks supports the findingsobtained from the aerial surveys strengthening the argumentspresented in the current paper Catch information also provides a

useful insight into the susceptibility of this species to potentialfishing mortality

It is unclear as to why shore anglers suddenly started catchingwhite sharks from 2009 onwards Anglers have always targeted

large sharks there has been no major shift in the type of tackleused and fishing effort for sharks has if anything declined sincethe vehicle beach ban in 2002 (Dicken et al 2006 Mann et al

2008 Dicken et al 2012) There is also no significant trend inannual or seasonal water temperatures or correlations betweenwater temperatures and ENSO events in the Port Elizabeth region

between 1982 and 2009 (Rouault et al 2010) Whether theincreased catch per unit effort reflects a greater number of sharkspupped as a result of a redistribution or recovery of the white-

shark population or is simply a product of favourable environ-mental conditions such as prey availability remains unclear

White sharks have been implicated as one of themain speciesinvolved in shark attacks both in South African (Cliff 2006) and

international waters (Burgess and Callahan 1996 Curtis et al

2012) The abundance of juvenile white sharks close to beachesinAlgoaBaymay increase the risk of encounter withwater users

and hence the chance of an attack Despite numerous reportedencounters however there have been no confirmed attacksleading to injury at any of the inshore sites surveyed in the

present studyHigh abundance of juvenile sharks and an absenceof shark attacks have also been observed at popular bathingbeaches in Australia (Bruce and Bradford 2012) These findings

suggest that the presence of sharks alone is a poor indicator ofattack risk On the eastern coast of Australia shark attacksappear to be more common at beaches where juvenile whitesharks exhibit transitory rather than resident behaviour in

nursery areas (Werry et al 2012) This may be a result of sharksbeing less selective when seeking prey during transit (Werryet al 2012)

To conclude the present study is the first in South Africa toprovide information on the existence of a possible inshorenursery area for white sharks Defining key habitats for YOY

and juvenile white sharks is critical to their conservation inSouth Africa and improves our understanding of white-sharkdistribution and biology It also provides critical informationnecessary to minimise the risk of encounter between sharks and

people as well as for managing human impacts on white sharksclose inshore

Acknowledgements

This work would not have been possible without the financial support of the

Nelson Mandela Metropolitan Municipality the African Coelacanth Eco-

system Project and a National Research Foundation Professional Develop-

ment Programme Post-doctoral Fellowship award Logistical support was

provided by the South African Environmental Observation Network

(Elwandle Node) and research permits from Oceans and Coast We also

thank the South African Weather Service and Dr Wayne Goschen for sup-

plying environmental data and Trade Motto Oceans Fresh Gary Hook and

Quick Cool (especially Francois van Zyl) for bait Special thanks go to John

Huddlestone and Christo Janse van Rensburg for conducting the aerial

surveys We also gratefully acknowledge the Director and staff of the Port

Elizabeth Museum at Bayworld for their support and infrastructure

Administration of funding by Bayworld Centre for Research and Education

is gratefully acknowledged

References

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a discrete probability mass at the origin Journal of the American

Statistical Association 50 901ndash908

Akaike H (1972) Information theory as an extension of the maximum

likelihood principle In lsquoSecond International Symposium on Informa-

tion Theoryrsquo (Eds B N Petrov and F Csaki) pp 267ndash281 (Akademiai

Kiado Budapest)

Aswani S and Lauer M (2006) Benthic mapping using local aerial photo

interpretation and resident taxa inventories for designing marine pro-

tected areas Environmental Conservation 33 263ndash273 doi101017

S0376892906003183

Babbie E (1989) lsquoThe Practice of Social Researchrsquo 5th edn (Wadsworth

Belmont CA)

Barlow J Oliver C W Jackson T D and Taylor B L (1988) Harbor

porpoise Phocoena phocoena abundance estimation for California

Oregon and Washington II Aerial surveys Fish Bulletin 86 433ndash444

BassA JDrsquoAubrey JD andKistnasamyN (1975)Sharksof the east coast

of southern Africa IV The families Odontaspididae Scapanorhynchidae

Isuridae Cetorhinidae Alopiidae Orectolobidae and Rhiniodontidae

Surveys of white sharks (Carcharodon carcharias) Marine and Freshwater Research G

Investigative Report of the Oceanographic Research Institute Durban 39

1ndash102

Beamish C A Booth A J and Deacon N (2005) Age growth and

reproduction of largemouth bass Micropterus salmoides in Lake

Manyame Zimbabwe African Zoology 40 63ndash69

Beckley L E (1983) Sea-surface temperature variability around Cape

Recife South Africa South African Journal of Science 79 436ndash438

Biernacki P and Waldorf D (1981) Snowball sampling problems and

techniques of chain referral sampling SociologicalMethodsampResearch

10 141ndash163

Bradford RW Hobday A J andBruce BD (2012) Identifying juvenile

white shark behavior from electronic tag data In lsquoGlobal Perspectives on

the Biology and Life History of the White Sharkrsquo (Ed M L Domeier)

pp 255ndash270 (CRC Press Boca Raton FL)

Branstetter S (1990) Early life-history implications of selected carcharhi-

noid and lamnoid sharks of the northwest Atlantic NOAA Technical

Report National Marine Fisheries Service 90 17ndash28

Bremner J M (1991) The bathymetry of Algoa Bay Bulletin of the

Geological Survey South Africa 100 3ndash18

Bruce B D (2008)White sharks The biology and ecology ofCarcharodon

carcharias In lsquoSharks of the Open Oceanrsquo (Eds E Pikitch and M

Camhi) pp 69ndash81 (Blackwell Scientific Oxford UK)

Bruce B D and Bradford RW (2012) Habitat use and spatial dynamics of

juvenile white sharks Carcharodon carcharias in Eastern Australia In

lsquoGlobal Perspectives on theBiology and LifeHistory of theWhite Sharkrsquo

(Ed M L Domeier) pp 225ndash253 (CRC Press Boca Raton FL)

Burgess G H and Callahan M (1996) Worldwide patterns of white shark

attacks on humans In lsquoGreatWhite Sharks the Biology ofCarcharodon

carchariasrsquo (Eds A P Klimley and D G Ainley) pp 457ndash469

(Academic Press San Diego CA)

Burks CM DriggersW B III andMullin K D (2005) Abundance and

distribution of whale sharks (Rhinocodon typus) in the northern Gulf of

Mexico Fish Bulletin 104 579ndash584

Cardona L Revelles M Carreras C San Felix M Gazo M and

Aguilar A (2005) Western Mediterranean immature loggerhead tur-

tles habitat use in spring and summer assessed through satellite tracking

and aerial surveysMarine Biology 147 583ndash591 doi101007S00227-

005-1578-9

Casey J G and Pratt H L Jr (1985) Distribution of the white shark

Carcharodon carcharias in the western North Atlantic Southern

Californian Academy of Sciences Memoirs 9 2ndash14

Castro J I (1993) The shark nursery of Bulls Bay South Carolina with a

review of the shark nurseries of the southeastern coast of the United

States Environmental Biology of Fishes 38 37ndash48 doi101007

BF00842902

Cliff G (2006) A review of shark attacks in False Bay and the Cape

Peninsula between 1960 and 2005 In lsquoFinding a Balance White Shark

Conservation and Recreational Safety in the Inshore Waters of Cape

Town South Africarsquo (Eds D C Nel and T P Peschak) pp 20ndash31

WWF South Africa Report Series ndash 2006Marine001 (WWF South

Africa Cape Town South Africa)

Cliff G Anderson-Reade M D Aitken A P Charter G E and

Peddemors VM (2007) Aerial census of whale sharks on the Northern

KwaZulundashNatal coast South Africa Fisheries Research 84 41ndash46

doi101016JFISHRES200611012

Cliff G Dudley S F J and Davis B (1989) Sharks caught in the

protective gill nets off Natal South Africa 2 The great white shark

Carcharodon carcharias (Linnaeus) South African Journal of Marine

Science 8 131ndash144 doi10298902577618909504556

Cliff G Dudley S F J and Jury M (1996) Catches of white sharks

in KwaZulundashNatal South Africa and environmental influences In

lsquoGreat White Sharks the Biology of Carcharodon carchariasrsquo (Eds

A P Klimley and D G Ainley) pp 351ndash362 (Academic Press

San Diego CA)

Clua E and Seret B (2010) Unprovoked fatal shark attack in Lifou Island

(Loyalty Islands New Caledonia South Pacific) by a great white shark

Carcharodon carcharias The American Journal of Forensic Medicine

and Pathology 31 281ndash286 doi101097PAF0B013E3181EC7CB8

Cockcroft V G Ross G J B Peddemors V M and Borchers D L

(1992) Estimates of abundance and undercounting of bottlenose dol-

phins off northern Natal South Africa South African Journal of Wildlife

Research 22 102ndash109

Compagno L J V (1991) Government protection for the great white shark

(Carcharodon carcharias) in South Africa South African Journal of

Science 87 284ndash285

Compagno L J V (2001) lsquoFAO Species Catalogue Sharks of the World

An Annotated and Illustrated Catalogue of Shark Species Known to

Date Vol 1 Part 2 Bullhead Mackerel and Carpet Sharks (Hetero-

dontiformes Lamniformes and Orectolobiformes)rsquo Food and Agricul-

ture Organization species catalogue for fishery purposes (FAO Rome)

Curtis TH Bruce BD Cliff G Dudley S F J Klimley A P KockA

Lea RN LoweCGMcCosker J E Skomal GBWerry JM and

West J G (2012) Responding to the risk of white shark attack updated

statistics prevention control methods and recommendations In lsquoGlobal

Perspectives on theBiology and LifeHistory of theWhite Sharkrsquo (EdM

L Domeier) pp 477ndash510 (CRC Press Boca Raton FL)

Dewar H DomeierM andNasby-Lucas N (2004) Insights into young of

the year white sharks (Carcharodon carcharias) behavior in the South-

ern California Bight Environmental Biology of Fishes 70 133ndash143

doi101023BEBFI0000029343540276A

Dicken M L (2008) First observations of young of the year and juvenile

great white sharks (Carcharodon carcharias) scavenging from a whale

carcass Marine and Freshwater Research 59 596ndash602 doi101071

MF07223

Dicken M L (2011) Population size of neonate and juvenile dusky sharks

(Carcharhinus obscurus) in the Port of Ngqura South Africa African

Journal of Marine Science 33 255ndash261 doi1029891814232X2011

600299

DickenM L SmaleM J and Booth A J (2006) Shark fishing effort and

catch of the raggedtooth shark (Carcharias taurus) in the South African

competitive shore angling fisheryAfrican Journal ofMarine Science 28

589ndash601 doi10298918142320609504209

Dicken M L Smale M J and Booth A J (2012) Long-term catch and

effort trends in Eastern Cape Angling Week competitions African


709961

Dicken M L Smale M J and Booth A J (2013) White sharks

Carcharodon carcharias at Bird Island Algoa Bay South Africa

African Journal of Marine Science in press

Domeier M L and Nasby-Lucas N (2008) Migration patterns of white

sharks Carcharodon carcharias tagged at Guadalupe Island Mexico

and identification of an eastern Pacific shared foraging area Marine

Ecology Progress Series 370 221ndash237 doi103354MEPS07628

Dudley S F J (2012) A review of research on the white shark Carchar-

odon carcharias (Linnaeus) in southern Africa In lsquoGlobal Perspectives

on the Biology and Life History of the White Sharkrsquo (Ed M L

Domeier) pp 511ndash533 (CRC Press Boca Raton FL)

Ebert D A and Cowley P D (2003) Diet feeding behaviour and habitat

utilisation of the blue stingray Dasyatis chrysonota (Smith 1828) in

South African waters Marine and Freshwater Research 54 957ndash965

doi101071MF03069

Fallows C Martin R A and Hammerschlag N (2012) Comparisons

between white shark-pinniped interactions at Seal Island (South Africa)

with other sites in California In lsquoGlobal Perspectives on the Biology and

Life History of the White Sharkrsquo (Ed M L Domeier) pp 105ndash117

(CRC Press Boca Raton FL)

Ferreira C A and Ferreira T P (1996) Population dynamics of white

sharks in South Africa In lsquoGreat White Sharks the Biology of

H Marine and Freshwater Research M L Dicken and A J Booth

Carcharodon carchariasrsquo (Eds A P Klimley and D G Ainley) pp

381ndash391 (Academic Press San Diego CA)

Fletcher D MacKenzie D and Villoutas E (2005) Modelling skewed

data with many zeros a simple approach combining ordinary and

logistic regression Environmental and Ecological Statistics 12

45ndash54 doi101007S10651-005-6817-1

GoldmanK J andAnderson S D (1999) Space utilization and swimming

depth of white sharks Carcharodon carcharias at the South Farallon

Islands central California Environmental Biology of Fishes 56

351ndash364 doi101023A1007520931105

Gruber S H Nelson D R andMorrissey J F (1988) Patterns of activity

and space utilization of lemon sharks Negaprion brevirostris in a

shallow Bahamian lagoon Bulletin of Marine Science 43 61ndash76

Hall D B (2000) Zero-inflated Poisson binomial regression with random

effects a case study Biometrics 56 1030ndash1039 doi101111J0006-

341X200001030X

Heupel M R and Hueter R E (2002) Importance of prey density in

relation to the movement patterns of juvenile blacktip sharks (Carch-

arhinus limbatus) within a coastal nursery areaMarine and Freshwater

Research 53 543ndash550 doi101071MF01132

Heupel M R Carlson J K and Simpfendorfer C A (2007) Shark nursery

areas concepts definition characterization and assumptions Marine


Holland K N Wetherbee B M Peterson J D and Lowe C G (1993)

Movements and distribution of hammerhead shark pups on their natal

grounds Copeia 1993 495ndash502 doi1023071447150

Hussey N E McCann HM Cliff G Dudley S F J Wintner S P and

Fisk A T (2012) Size-based analysis of diet and trophic position of the

white shark (Carcharodon carcharias) in South African waters In

lsquoGlobal Perspectives on the Biology and Life History of the White

Sharkrsquo (Ed M L Domeier) pp 27ndash49 (CRC Press Boca Raton FL)

Klimley A P (1985) The areal distribution and autoecology of the white

shark Carcharodon carcharias off the west coast of North America

Southern Californian Academy of Science Memoirs 9 15ndash40

Kock A and Johnson R (2006) White shark abundance not a causative

factor in numbers of shark bite incidents In lsquoFinding a Balance White

Shark Conservation and Recreational Safety in the Inshore Waters of

Cape Town South Africarsquo (Eds D C Nel and T P Peschak) pp 1ndash19



Kock A Titleyn S PetersenW Sikweyiya M Davids P Tsotsobe S

Colenbrander D Gold H and Oelofse G (2012) Shark spotters a

pioneering shark safety program in Cape Town South Africa In lsquoGlobal

Perspectives on the Biology and Life History of the White Sharkrsquo


Kock A OrsquoRiain M J Mauff K Meyer M Kotze D and Griffiths C

(2013) Residency habitat use and sexual segregation of white sharks

Carcharodon carcharias in False Bay South Africa PLoS ONE 8(1)

e55048 doi101371JOURNALPONE0055048

Krogh M (1994) Spatial seasonal and biological analysis of sharks caught

in the New South Wales protection beach meshing programme Austra-

lian Journal ofMarine andFreshwater Research 45 1087ndash1106 doi10

1071MF9941087

Lambert D (1992) Zero-inflated Poisson regression with an application to

defects in manufacturing Technometrics 34 1ndash14 doi1023071269547

Laroche R K Kock A A Dill L M and Oosthuizen W H (2007)

Effects of provisioning ecotourism activity on the behaviour of white

sharks Carcharodon carcharias Marine Ecology Progress Series 338

199ndash209 doi103354MEPS338199

Lowe CG BlasiusM E Jarvis E TMason T J GoodmanloweGD

and OrsquoSullivan J B (2012) Historic fishery interactions with white

sharks in the southern California Bight In lsquoGlobal Perspectives on the

Biology and Life History of the White Sharkrsquo (Ed M L Domeier)


MalcolmH Bruce B D and Stevens J D (2001)A review of the biology

and status of white sharks in Australian waters In lsquoReport to Environ-

ment Australia Marine Species Protection Programrsquo pp 1ndash113 CSIRO

Marine Research Hobart

Mann B Q Nanni G and Pradervand P (2008) A monthly aerial survey

of the KwaZulundashNatal marine shore fishery ORI Unpublished Report

No 264 Oceanographic Research Institute Durban South Africa

Marsh H and Sinclair D F (1989) An experimental evaluation of dugong

and sea turtle aerial survey techniques Australian Wildlife Research 16

639ndash650 doi101071WR9890639

Martin R A Hammerschlag N Collier R S and Fallows C (2005a)

Predatory behaviour of white sharks (Carcharodon carcharias) at Seal

Island SouthAfrica Journal of theMarine Biological Association of the

United Kingdom 85 1121ndash1135 doi101017S002531540501218X

Martin T GWintle B A Rhodes J R Kuhnert PM Field S A Low-

Choy S J Tyre A J and Possingham H P (2005b) Zero tolerance

ecology improving ecological inference bymodelling the source of zero

observations Ecology Letters 8 1235ndash1246 doi101111J1461-0248

200500826X

Martin R A Rossmo D K and Hammerschlag N (2009) Hunting

patterns and geographic profiling of white shark predation Journal of

Zoology 279 111ndash118 doi101111J1469-7998200900586X

Maunder M N and Punt A (2004) Standardizing catch and effort data a

review of recent approaches Fisheries Research 70 141ndash159


McClellan D (1996) Aerial surveys for sea turtles marine mammals and

vessel activity along the southeast Florida coast 1992ndash1996 Report No

390NationalOceanic andAtmospheric Administration NationalMarine

Fisheries Service ndash Southeast Fisheries Science Centre Miami Florida

McDaniel C J Crowder L B and Priddy J A (2000) Spatial dynamics

of sea turtle abundance and shrimping intensity in the US Gulf of

Mexico Conservation Ecology 4 15

McFadden D (1974) The measurement of urban travel demand Journal of

Public Economics 3 303ndash328 doi1010160047-2727(74)90003-6

McGrathM D Horner C CM Brouwer S L Lamberth S J Mann B

Q Sauer W H H and Erasmus C (1997) An economic valuation of

the South African linefishery South African Journal of Marine Science

18 203ndash211 doi102989025776197784161171

Merson R R and Pratt H L (2001) Distribution movements and growth

of young sandbar sharksCarcharhinus plumbeus in the nursery grounds

of Delaware Bay Environmental Biology of Fishes 61 13ndash24

doi101023A1011017109776

Myers R A and Pepin P (1990) The robustness of lognormal-based

estimators of abundanceBiometrics 46 1185ndash1192 doi1023072532460

Neis B Schneider D C Felt L Haedrich R L Fischer J and

Hutching J A (1999) Fisheries assessment what can be learned from

interviewing resource usersCanadian Journal of Fisheries and Aquatic

Sciences 56 1949ndash1963

Nishi J S and Buckland L (2000) An aerial survey of caribou on western

Victoria Island (5ndash17 June 1994) Department Of Resources Wildlife

and Economic Development Government of The Northwest Territories

Canada

OrsquoDonoghue S H Drapeau L and Peddemors V M (2010) Broad-scale

distribution patterns of sardine and their predators in relation to remotely

sensed environmental conditions during the KwaZulundashNatal sardine run

African Journal of Marine Science 32 279ndash291 doi1029891814232X

2010501584

Pennington M (1983) Efficient estimators of abundance for fish and

plankton surveys Biometrics 39 281ndash286 doi1023072530830

Pollock K H Marsh H D Lawler I R and Alldredge M W (2006)

Estimating animal abundance in heterogeneous environments an appli-

cation to aerial surveys for dugongs The Journal of Wildlife Manage-

ment 70 255ndash262 doi1021930022-541X(2006)70[255EAAIHE]20

CO2

Surveys of white sharks (Carcharodon carcharias) Marine and Freshwater Research I

Pyle P Anderson S D Klimley A P and Henderson R P (1996)

Environmental factors affecting the occurrence and behavior of white

sharks at the Farallon Islands California In lsquoGreat White Sharks the

Biology of Carcharodon carchariasrsquo (Eds A P Klimley and D G

Ainley) pp 281ndash291 (Academic Press San Diego CA)

Quang P X andBecker E F (1996) Line transect sampling under varying

conditions with application to aerial surveys Ecology 77 1297ndash1302

doi1023072265601

Redfern J V Viljoen P C Kruger JM andGetzWM (2002) Biases in

estimating population size from an aerial census a case study in the

Kruger National Park South Africa South African Journal of Science 98

455ndash761

Robbins R L (2007) Environmental variables affecting the sexual segre-

gation of great white sharks Carcharodon carcharias at the Neptune

Islands South Australia Journal of Fish Biology 70 1350ndash1364

doi101111J1095-8649200701414X

RobbinsWD Peddemors VM andKennelly S J (2012) Assessment of

shark sighting rates by aerial beach patrols Fisheries Final Report Series

No 132 NSW Department of Primary Industries Jervis Bay NSW

Roberts M J (2010) Coastal currents and temperatures along the eastern

region of Algoa Bay South Africa with implications for transport and

shelf-bay water exchange American Journal of Science 32 145ndash161

Ross G J B Cockcroft V G Melton D A and Butterworth D S

(1989) Population estimates for bottlenose dolphins Tursiops truncatus

inNatal andTranskei waters South African Journal ofMarine Science 8

119ndash129 doi10298902577618909504555

Rossouw G J (1984) Age and growth of the sand shark Rhinobatos

annulatus in Algoa Bay South Africa Journal of Fish Biology 25

213ndash222 doi101111J1095-86491984TB04868X

Rouault M Pohl B and Penven P (2010) Coastal oceanic climate change

and variability from1982 to 2009 around SouthAfricaAfrican Journal of

Marine Science 32 237ndash246 doi1029891814232X2010501563

Rowat D Gore M Meekan M G Lawler I R and Bradshaw C J A

(2009) Aerial survey as a tool to estimate whale shark abundance trends

Journal of Experimental Marine Biology and Ecology 368 1ndash8

doi101016JJEMBE200809001

Salganik M J and Heckathorn D D (2004) Sampling and estimation in

hidden populations using respondent-driven sampling Sociological

Methodology 34 193ndash240 doi101111J0081-1750200400152X

Santana-Morales O Sosa-Nishizaki O Escobedo-Olvera M A Onate-

Gonzalez E C OrsquoSullivan J B and Cartamil D (2012) Incidental

catch and ecological observations of juvenile white sharks (Carcharodon

carcharias) in BajaCaliforniaMexico and its conservation implications

In lsquoGlobal Perspectives on the Biology and Life History of the White

Sharkrsquo (EdM L Domeier) pp 187ndash198 (CRCPress Boca Raton FL)

Schumann E H Perrins L A and Hunter I T (1982) Upwelling along

the south coast of the Cape Province South Africa South African

Journal of Science 78 238ndash242

Schumann E H Churchill J R S and Zaayman H J (2005) Oceanic

variability in the western sector of Algoa Bay South Africa African

Journal ofMarine Science 27 65ndash80 doi10298918142320509504069

Shannon L V (1989) The physical environment In lsquoOceans of Life off

Southern Africarsquo (Eds A I L Payne and R J M Crawford) pp 12ndash27

(Vlaeberg Cape Town South Africa)

Shelden K E W and Laake J L (2002) Comparison of the offshore

distribution of southboundmigrating graywhales from aerial survey data

collected off Granite Canyon California 1979ndash96 The Journal of

Cetacean Research and Management 4 53ndash56

Simpfendorfer C A and Milward N E (1993) Utilisation of a tropical

bay as a nursery area by sharks of the families Carcharhinidae and

SphyrnidaeEnvironmental Biology of Fishes 37 337ndash345 doi101007

BF00005200

Skomal G B Chisholm J and Correia S J (2012) Implications of

increasing pinniped populations on the diet and abundance of white

sharks off the coast of Massachusetts In lsquoGlobal Perspectives on the



Smith J L B (1951) A juvenile of theman-eaterCarcharodon carcharias

Annals and Magazine of Natural History 12 729ndash736

van der Elst R P (1989) Marine recreational angling in South Africa

In lsquoOceans of Life off Southern Africarsquo (Eds A I L Payne and

R J M Crawford) pp 164ndash176 (Vlaeberg Publishers Cape Town

South Africa)

Weng K C Boustany A M Pyle P Anderson S D Brown A and

Block B A (2007) Migration and habitat of white sharks (Carchar-

odon carcharias) in the eastern Pacific Ocean Marine Biology 152

877ndash894 doi101007S00227-007-0739-4

Werry J M Bruce B Sumpton W Reid D and Mayer D G (2012)

Beach areas preferred by juvenile white sharkCarcharodon carcharias

in eastern Australia from long-term catch-per-unit-effort and movement

data In lsquoGlobal Perspectives on the Biology and Life History of the

White Sharkrsquo (Ed M L Domeier) pp 271ndash286 (CRC Press Boca

Raton FL)

Wilson S G (2004) Basking sharks (Cetorhinus maximus) schooling in the

southern Gulf of Maine Fisheries Oceanography 13 283ndash286

doi101111J1365-2419200400292X

Ye Y Al-Husaini M and Al-Baz A (2001) Use of generalized linear

models to analyze catch rates having zero values the Kuwait driftnet

fishery Fisheries Research 53 151ndash168 doi101016S0165-7836(00)

00287-3

wwwpublishcsiroaujournalsmfr

J Marine and Freshwater Research M L Dicken and A J Booth

basking sharks (Cetorhinus maximus) (Wilson 2004 Burks et al2005 Cliff et al 2007 Rowat et al 2009) and lemon sharks

(Negaprion brevirostris) (Gruber et al 1988)When present white sharks are commonly visible in the surf

zone within a few hundred metres from shore This behaviour

renders them easily visible from the air and thus easily countedduringaerial surveysAerial surveys ofhigh-risk beach areas havebeen used intermittently in bothAustralia and theUnited States to

inform beachgoers of the presence of potentially dangerousspecies such as white sharks tiger sharks (Galeocerdo curvier)and bull sharks (Carcharhinus leucas) (Curtis et al 2012)

Anecdotal reports from shore-based anglers suggest that the

number of white sharks at certain beaches within Algoa Bayhave increased in recent years Recreational shore-basedangling is a form of linefishing where fish are caught using a

hook and line and comprises both a social as well as a moreformal organised competitive sector (van der Elst 1989) It is oneof the most popular sport and outdoor recreational activities in

South Africa with an estimated 412 000 fishers (McGrath et al1997) Although white sharks are a threatened species and fullyprotected in South Africa (Compagno 1991) they are occasion-ally caught incidentally while fishing for other large species of

shark such as raggedtooth (Carcharias taurus) dusky (Carch-arhinus obscurus) and bronze whaler (Carcharhinus bra-

chyurus) sharks (Dicken et al 2012)

Incidental catches have been effectively used to determinethe spatial distribution and ecology of juvenile white sharks inthe near-shore environment (Klimley 1985 Clua and Seret

2010 Santana-Morales et al 2012 Lowe et al 2012) Informa-tion on white-shark catches from shore anglers provides useful

information that can augment data obtained from aerial surveysIt also provides an important insight into fishery interactions thatcould potentially be used to assist in developing strategies to

minimise fishery-induced mortalityUsing a combination of aerial and shore angling surveys the

current paper presents the first quantitative study on the seasonal

occurrence and size of white sharks off beaches within AlgoaBay and indeed anywhere in South Africa The occurrence ofsharks is compared to various environmental parameters toelucidate factors influencing their near-shore use This informa-

tion is critical not only tominimise the risk of encounter betweensharks and people but also in identifying important nursery-areahabitat for juvenile white sharks

Materials and methods

Study area

Algoa Bay is a wide relatively shallow (depth70m) eastward-facing bay (Schumann et al 2005) The bay coastline extendsfor 90 km between the headlands of Cape Recife in the west and

Woody Cape in the east (Fig 1) Two large perennial rivers theSwartkops and Sundays Rivers flow into the bay The Islands ofthe Cross comprising St Croix Brenton and Jahleel are located

1ndash3 km offshore between the Swartkops and Sundays riversystems A second island group comprising Bird Seal Stagand Black Rocks is located8 km offshore fromWoody Cape

SwartkopsRiver

PE harbour

Cape Recife

Ngquraharbour

Jahleel

2

3

CapeTown

PortElizabeth

Durban

Brenton

St Croix15

15

20

15

15

1

4

5

20

2030

2020

Flight path

White shark aerialsightings 2010ndash2012

White shark catches

4 4 Kilometers2 0

30

3015

15

50

50

30

20

1515

20

Fig 1 Location of the Algoa Bay study area indicating the zone of aerial survey shark sighting and shore-angling catches Map

insert shows the location of Algoa Bay in relation to the South African coastline

B Marine and Freshwater Research M L Dicken and A J Booth






Aerial surveys
































0

01

02

03

04

05

06

07

08

09

10

0 1 2 3 4 5 6 7

Sighting rate

Fre

quen

cy









(








2
























fishing mortality

Results

Aerial surveys





















White-shark catches








0

1

1

3

33

32

2 2 2 2 2 2 2 2

3

3

2

4

2

3

4

5

6

7

8

Oct

Nov

Dec Jan

Feb

Mar

Apr

May

June

July

Aug

Sep

t

Oct

Nov

Dec Jan

Feb

Mar

Month

Sig

htin

g ra

te (

shar

ks h

1 )

0

50

100

150

200

250

Tem

pera

ture

(C

)




in that month







Zero model

Intercept 268132 157197 009



Year 126 078 011

R2 029

Positive model

Intercept 203016 57244 001



Year 102 028 001

R2 041




Discussion

































0

10

20

30

40

50

60

70

80

0

Oct

Dec

Feb Apr

Jun

Aug Oct

Dec

Feb

31 59 76 103 137 174 223 264 307 350 374 412 466 501

Julian days

Sig

htin

g ra

te (

shar

ks h

1 )






































Acknowledgements















References







Kiado Budapest)




S0376892906003183


Belmont CA)









1ndash102








10 141ndash163




























005-1578-9







BF00842902



















San Diego CA)


























doi101023BEBFI0000029343540276A




MF07223




600299




589ndash601 doi10298918142320609504209




709961















doi101071MF03069














45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3








Aerial surveys
































0

01

02

03

04

05

06

07

08

09

10

0 1 2 3 4 5 6 7

Sighting rate

Fre

quen

cy









(








2
























fishing mortality

Results

Aerial surveys





















White-shark catches








0

1

1

3

33

32

2 2 2 2 2 2 2 2

3

3

2

4

2

3

4

5

6

7

8

Oct

Nov

Dec Jan

Feb

Mar

Apr

May

June

July

Aug

Sep

t

Oct

Nov

Dec Jan

Feb

Mar

Month

Sig

htin

g ra

te (

shar

ks h

1 )

0

50

100

150

200

250

Tem

pera

ture

(C

)




in that month







Zero model

Intercept 268132 157197 009



Year 126 078 011

R2 029

Positive model

Intercept 203016 57244 001



Year 102 028 001

R2 041




Discussion

































0

10

20

30

40

50

60

70

80

0

Oct

Dec

Feb Apr

Jun

Aug Oct

Dec

Feb

31 59 76 103 137 174 223 264 307 350 374 412 466 501

Julian days

Sig

htin

g ra

te (

shar

ks h

1 )






































Acknowledgements















References







Kiado Budapest)




S0376892906003183


Belmont CA)









1ndash102








10 141ndash163




























005-1578-9







BF00842902



















San Diego CA)


























doi101023BEBFI0000029343540276A




MF07223




600299




589ndash601 doi10298918142320609504209




709961















doi101071MF03069














45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3









(








2
























fishing mortality

Results

Aerial surveys





















White-shark catches








0

1

1

3

33

32

2 2 2 2 2 2 2 2

3

3

2

4

2

3

4

5

6

7

8

Oct

Nov

Dec Jan

Feb

Mar

Apr

May

June

July

Aug

Sep

t

Oct

Nov

Dec Jan

Feb

Mar

Month

Sig

htin

g ra

te (

shar

ks h

1 )

0

50

100

150

200

250

Tem

pera

ture

(C

)




in that month







Zero model

Intercept 268132 157197 009



Year 126 078 011

R2 029

Positive model

Intercept 203016 57244 001



Year 102 028 001

R2 041




Discussion

































0

10

20

30

40

50

60

70

80

0

Oct

Dec

Feb Apr

Jun

Aug Oct

Dec

Feb

31 59 76 103 137 174 223 264 307 350 374 412 466 501

Julian days

Sig

htin

g ra

te (

shar

ks h

1 )






































Acknowledgements















References







Kiado Budapest)




S0376892906003183


Belmont CA)









1ndash102








10 141ndash163




























005-1578-9







BF00842902



















San Diego CA)


























doi101023BEBFI0000029343540276A




MF07223




600299




589ndash601 doi10298918142320609504209




709961















doi101071MF03069














45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3


















White-shark catches








0

1

1

3

33

32

2 2 2 2 2 2 2 2

3

3

2

4

2

3

4

5

6

7

8

Oct

Nov

Dec Jan

Feb

Mar

Apr

May

June

July

Aug

Sep

t

Oct

Nov

Dec Jan

Feb

Mar

Month

Sig

htin

g ra

te (

shar

ks h

1 )

0

50

100

150

200

250

Tem

pera

ture

(C

)




in that month







Zero model

Intercept 268132 157197 009



Year 126 078 011

R2 029

Positive model

Intercept 203016 57244 001



Year 102 028 001

R2 041




Discussion

































0

10

20

30

40

50

60

70

80

0

Oct

Dec

Feb Apr

Jun

Aug Oct

Dec

Feb

31 59 76 103 137 174 223 264 307 350 374 412 466 501

Julian days

Sig

htin

g ra

te (

shar

ks h

1 )






































Acknowledgements















References







Kiado Budapest)




S0376892906003183


Belmont CA)









1ndash102








10 141ndash163




























005-1578-9







BF00842902



















San Diego CA)


























doi101023BEBFI0000029343540276A




MF07223




600299




589ndash601 doi10298918142320609504209




709961















doi101071MF03069














45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3




Discussion

































0

10

20

30

40

50

60

70

80

0

Oct

Dec

Feb Apr

Jun

Aug Oct

Dec

Feb

31 59 76 103 137 174 223 264 307 350 374 412 466 501

Julian days

Sig

htin

g ra

te (

shar

ks h

1 )






































Acknowledgements















References







Kiado Budapest)




S0376892906003183


Belmont CA)









1ndash102








10 141ndash163




























005-1578-9







BF00842902



















San Diego CA)


























doi101023BEBFI0000029343540276A




MF07223




600299




589ndash601 doi10298918142320609504209




709961















doi101071MF03069














45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3


































Acknowledgements















References







Kiado Budapest)




S0376892906003183


Belmont CA)









1ndash102








10 141ndash163




























005-1578-9







BF00842902



















San Diego CA)


























doi101023BEBFI0000029343540276A




MF07223




600299




589ndash601 doi10298918142320609504209




709961















doi101071MF03069














45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3




1ndash102








10 141ndash163




























005-1578-9







BF00842902



















San Diego CA)


























doi101023BEBFI0000029343540276A




MF07223




600299




589ndash601 doi10298918142320609504209




709961















doi101071MF03069














45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3








45ndash54 doi101007S10651-005-6817-1




351ndash364 doi101023A1007520931105






341X200001030X





































1071MF9941087






199ndash209 doi103354MEPS338199















639ndash650 doi101071WR9890639









200500826X



















18 203ndash211 doi102989025776197784161171




doi101023A1011017109776










Canada





2010501584







CO2









doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3










doi1023072265601




455ndash761




doi101111J1095-8649200701414X










119ndash129 doi10298902577618909504555



213ndash222 doi101111J1095-86491984TB04868X







doi101016JJEMBE200809001


























BF00005200











South Africa)




877ndash894 doi101007S00227-007-0739-4






Raton FL)



doi101111J1365-2419200400292X




00287-3



Documents

Surveys of white sharks (Carcharodon carcharias) off bathing beaches in Algoa Bay, South Africa