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First Estimates of Mortality and Population Size of White Sharks on the South African Coast

  • KwaZulu-Natal Sharks Board
Carcharodon carcharias
David G. Ainley
Academic Press
An Imprint oj
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First Estimates of Mortality and
Population Size of White Sharks on
the South African Coast
Sharks Board
South Africa
Oceanographic Research
South Africa
South Africa
Oceanographic Research
South Africa
The white shark
Carchnrodou carcharias
occurs along
the entire South African coast, but the center of its
distribution is the temperate waters of the Western
Cape (Bass et al., 1975). The species' range extends
into Namibia and possibly southern Mozambique
(Compagno et al., 1989).
This species has bitten humans in Cape waters and
also in KwaZulu-Natal, where a gill-netting pro-
gram, introduced in 1952, has reduced the incidence
of shark attack (Davies, 1964; Wallett, 1983;
At present, 40 km of nets, maintained by the
Natal Sharks Board (NSB), catches an average of 1354
sharks per year, including 39 white sharks (see Chap-
ter 32, by Cliff et al.). Initially, all potentially danger-
ous sharks found alive in the nets were killed. Since
however, most live sharks, including danger-
ous ones, have been released and, whenever pos-
tagged (Cliff and Dudley, 1992b).
Other sources of fishing mortality of white sharks
are big-game angling, spear fishing, and incidental
catches in commercial fisheries in Western Cape wa-
None of these mortalities has been quantified,
although one angler captured 18 white sharks in False
Bay over a 4-year period (Wallett, 1983). Some spear
fishermen carry a "powerhead,'' that is, a rifle bullet
modified to fit over the end of the spear, which is
fired at any threatening shark. The considerable com-
mercial value of the jaws and teeth may lead to in-
creased targeting and possible overexploitation
(Compagno, 1991). In South Australia, fishermen and
divers claim that the species has undergone a serious
decline in recent years (Bruce, 1992).
In South Africa, research has been carried out on
white sharks caught in the shark nets (Bass et al.,
Cliff ct al., 1989, Chapter 32). In 1990, the Shark
Research Center of the South African Museum initi-
ated research into the movements, habitat use, be-
havior, abundance, and population structure of the
species (Compagno, 1991).
In the absence of information about the status of
the stock, government protection was granted to C.
carcharias in April 1991, making it illegal to "catch or
kill any white shark except on the authority of a per-
mit issued by the Director-General of Environment
Affairs'' (Compagno, 1991).
Clearly, there is an urgent need to investigate the
population dynamics of white sharks to assess the
validity and effectiveness of this preemptive legisla-
The Biology of Carcharodon carcharias 393 Copyright © 1996 by Academic Press, Inc.
All rights of reproduction in any form reserved.
tion. The tagging of white sharks under the auspices
of a national marine fish tagging program, initiated
by the Oceanographic Research Institute (ORI) in
has provided this opportunity. The mark-and-
recapture study described in this chapter is a first
attempt at quantifying the stock of white sharks along
a large section of the South African coast.
Materials and Methods
Tagging and Shark Capture
Each dart tag had a stainless steel head and a plastic
streamer, at first red (Floy Tag), but lately yellow (Hall-
print) (van der Elst, 1990). The latter tag also was used
by Bruce (1992), and a tag of similar design has been
used extensively by the U.S. National Marine Fisheries
Service (Casey, 1985). Shark lengths used in the text
are precaudal measurements (PCLs). Details about the
white sharks tagged and recaptured are given in Table I.
The shark nets are distributed along 325 km of
KwaZulu-Natal coast (Fig. 1), Richards Bay being the
northernmost location. Mean monthly sea-surface
temperature (SST) ranges from 19.9°C in August to
25.3°C in February (Cliff and Dudley, 1991a). Specifi-
cations of the nets and the manner in which they are
deployed and serviced have been given by Wallett
(1983) and Cliff et al. (1988a).
In 1990, one of the authors (T.K.W.), a commercial
line fisherman, started tagging white sharks in the
vicinity of Struis Bay (Fig. 1), 6 km east of Cape
Agulhas, the southernmost point on the African con-
tinent. The mean monthly SST there ranges from
15°C in July to 21°C in January (Greenwood and
Taunton-Clark, 1992). The sharks were caught on rod
and 40-kg line, using small live sharks as bait. SST
was measured (by T.K.W.) when most white sharks
were tagged.
Estimating Population Size
A modified Petersen estimate (Seber, 1982) was
used to calculate the population size, N, at the end of
time interval / as
_ (M, + 1) (n, + 1)
+ 1) 1 (1)
where m, is the number of marked animals recap-
tured in the total catch, ri of white sharks, and M, is
the number of marked animals alive at the end of
interval /.
In this study, the tagging and recapture of white
sharks were undertaken concurrently over a 5-year
period. This period was split into five
and a Petersen estimate was obtained for each year.
The total population size of white sharks, N, was
estimated as
N= 2^'
1) (2)
where s is the number of samples.
In applying the Petersen estimate, it was assumed
that all tagging took place at the beginning of time
interval / and that all recaptures occurred at the end.
Allowance was made for the rerelease of tagged
sharks upon recapture and the loss of a constant frac-
tion of tagged animals, 1 - a, either through immedi-
ate tag shedding or death from capture stress. As-
suming that mo animals are marked at the start of a
time interval, / = 0, then the number effectively
tagged. Mo, is
Mo = amo (3)
The number surviving to the next time interval, / =
is equal to
M, am^^e^ Z) (4)
TABLE I Details of Tagged and Recaptured White Sharks
Marina Beach
Struis Bay
Struis Bay
Struis Bay
Precaudal length
Algoa Bay
Struis Bay
Struis Bay
Time free
Distance travelled
"Localities shown in Figure 1.
''Abbreviations: F, female; M, male.
off South Africa
False Bay
^ Kenton on Sea
Algoa Bay
Struis Bay
15°E 20°E 25°E
FIGURE 1 The southern African distribution of the white shark (after Compagno et ai, 1989). The shark-netted region in
KwaZulu-Natal and the localities at which white sharks were tagged or recaptured are indicated.
where Z is the instantaneous rate of total mortality,
taken to be constant. If, at this time, a further m^
animals are tagged and released or if recaptured ani-
mals are rereleased, then the number surviving to the
next time interval, M,, is
Ml = a(me
+ m, + W,) (5)
where W, is the number of marked animals re-
released. In general,
M, = M, + «(»/,,, + W,^,) (6)
In order to apply the Petersen estimate, we need to
know the total annual catch, Uj, which comprises a
known component, Kj (the sum of the catch in the
shark nets and that of T.K.W.), and an unknown com-
ponent, Uj (the sum of trawl net catches and those
made by spear fishermen and other big-game an-
such that
= Kj + Uj.
Estimating Mortality
Using the Baranov catch equation (Ricker, 1975),
the estimated number of tag recaptures, K that are
reported, assuming that all such recaptures are re-
ported, is
= M, J (1 ') (7)
where F is the instantaneous fishing mortality rate,
taken to be constant throughout the experiment.
Hilborn (1990) has shown that the sampling distribu-
tion of the tag recoveries can be approximated by the
Poisson distribution. The likelihood of the expected
number of recoveries, R given the observed number
of tag recoveries, r is
I Tj)
= exp (-•RA
" r,! (8)
ET At.
The total likelihood of observing all r given the cor-
responding R^ is therefore the product of all the indi-
vidual likelihoods:
TABLE II Mark-Recapture Statistics
off the South African Coast
L{R \r) = U exp (-K,) ^ (9)
For computational convenience, the negative of the
log likelihood was calculated, and this equation
formed the quantity to be minimized:
-In lLi(x,F,Z)] = -2 In (exp (-R,) ^ (10)
Given the number of animals that are marked and
recaptured in each time interval, three parameters (a,
f, and Z) need to be estimated to determine the size
of the white shark population, N. Initial trials indi-
cated that there was insufficient contrast in the data
to estimate all the parameters. We therefore fixed a
while allowing free estimation of F and Z. The model
was set up in a spreadsheet that was programmed to
perform a nonlinear optimization routine.
Estimating Parameter Variances and
Confidence Intervals
A bootstrap technique (Efron, 1981; Punt and But-
terworth, 1993) was used to estimate variances for the
parameters F, Z, N and N. A large number of arti-
ficially generated recapture data sets were randomly
drawn from a Poisson distribution using the proce-
dure described in the book by Press ct al. (1986). The
procedure requires, as input, the expected mean
number of recoveries in each interval (observed
mean, 1) (Table II). The number of rereleases of white
sharks in each time interval, /, was calculated as
0.6(G,), where G, is the random deviate from a Poi-
sson distribution of mean value = 1, and 0.6 repre-
sents the average number of recaptured white sharks
that have been rereleased (Table II). To each pseu-
dodata set a new set of parameters and derived quan-
tities (such as the N/s) are estimated. The standard
error of a parameter or derived quantity, Q, is then
obtained from
SE.Ql^VSS^ (11)
where Q" is the value of Q from the n\h data set and
Q is the mean of the Q"'s. The 95% confidence inter-
vals were calculated using the percentile method.
Rei x^leases.
, Unknown,
"Not used in the analyses.
Sharks Tagged
Between 1978 and 1993, 97 (15.7%) of 616 white
sharks caught in the nets were found alive. Initially,
these sharks were killed, but in 1989 the first of 22 live
sharks (11.8% of the white shark catch) was released
from the nets after being marked with a dart tag. Three
free-swimming sharks, one of which was tagged
twice, were marked while they fed on a dead whale off
Durban. Of the 25 sharks tagged, 13 were females and
11 were males. The males ranged from 130 to 370 cm
PCL, with a mode of 200 cm; the two largest males, 320
and 370 cm, were both feeding on the whale carcass.
The females ranged from 150 to 265 cm PCL, with a
mode of 180-200 cm (Fig. 2).
In the Struis Bay area, 46 were tagged (by T.K.W.).
They included 32 females (range, 150-450 cm; mode,
300 cm) and 8 males (range, 250-350 cm; mode, 350
cm) (Fig. 2). These sharks were tagged in water where
the average SST was 18.6°C (range, 16.2-21.8°C; N =
A 180-cm unsexed specimen was tagged by a com-
mercial angler off Kenton-on-Sea, and a 158-cm fe-
male was tagged and released from a beach seine net
in False Bay. In total, between 1989 and 1993, 73 white
sharks were tagged along the south and east coasts of
South Africa (excluding sharks tagged by members of
the White Shark Research Institute, Cape Town).
Six sharks (8.2% of those tagged) were recaptured
(Table I). The mean distance traveled while at liberty
36. Population Size off South Africa 397
^ 6
100 140 180 220 260 300 340 380 420 460
PCL (cm)
FIGURE 2 Size-frequency distribution of female (F) and male (M) white sharks tagged in
KwaZulu-Natal (N) and in the western Cape (C). Sharks of unrecorded sex are excluded, PCL,
Precaudal length.
was 365 km (SE = 244; range, 0-1409 km), and the
mean time at liberty was 275 days (SE = 86; range, 1-
527 days). Three of the 22 sharks released from the
shark nets were recaptured. One traveled 4 km in 1
day and was rereleased. Another, of 150 cm, was
recaptured in the same shark net installation at Glen-
more 366 days later; it had grown by 15 cm. It was
also released. A third shark, of 180 cm, traveled 774
km from Ballito to Algoa Bay in 27 days, a rate of at
least 28.7 km/day.
Three sharks tagged in the western Cape (by
T.K.W.) were recaptured, two at the same locality
(Struis Bay) after 357 and 373 days, respectively; both
sharks were released. The third shark was recaptured
in the Durban shark nets, having traveled 1409 km in
527 days.
Estimate of Mortality and Population Size
The number of sharks tagged, the number recap-
tured, the number of recaptures rereleased, and the
known and assumed unknown catches are shown
annually for the 5-year period 1989-1993 (Table III).
The shark that was recaptured 1 day after release was
excluded from the analysis, because the time at liber-
ty was too short to assume complete mixing of
marked and unmarked white sharks. Given a surviv-
al factor, a ^ 0.9 (see Discussion), the computed val-
TABLE III White Shark Population Estimates
off the South African Coast, 1989-1993
Total Catch,
716 (147-591)'
676 (350-1582)
2227 (718-2772)
1279 (839-1843)
CV, Coefficient of variation.
"See Eq. 8 in the text.
''See Eq. 1 in the text.
confidence limits of the population estimate are given in
ues for instantaneous rates of mortality were Z = 0.53
and f = 0.055 year~i. of these two parameters, Z
was a better estimate than f, as shown by the lower
coefficient of variation (Table IV). Assuming that the
average annual unknown catch was 50 for the years
1989 and 1990, and 10 in the years 1991-1993 (T. Fer-
reira, personal communication), then the annual pop-
ulation estimate ranged from 377 (1992) to 2227
sharks (1993) (Table III). The overall estimate for the
5-year study period was 1279, with a coefficient of
variation of 24%.
The sharks tagged in KwaZulu-Natal were smaller
than those in Cape waters (see Chapter 35, by Fer-
reira and Ferreira). Although two sharks >300 cm
PCL were tagged while feeding on a whale carcass off
Durban and four mature males were recently caught
in the shark nets (see Chapter 32, by Cliff et al.), it
would appear that white sharks >250 cm are not as
common as smaller individuals in the netted region.
The high recapture rate (13.6%) of white sharks
released from the nets is encouraging. Murru (1990)
regards gill nets as the most stressful means of catch-
ing elasmobranchs, and therefore survival must be
low. The lower recapture rate (6.5%) of sharks tagged
by T.K.VV. may be due to the ban on angling for this
species in 1991.
The overall white shark recapture rate of 8.2% was
similar to or slightly higher than that of other large
coastal sharks marked in the ORI tagging program,
van der Elst and Bullen (1992) reported the following
recaptures: 7.3% of 96 tiger sharks
6.8% of 88 bull sharks Carcharhinus leucas, 3.5% of
1122 raggedtooth sharks Carcharias taurus, and 1.6%
of 252 broadnose sevengill cowsharks Notorynchus
Our white shark recapture rate (8.2%) was lower
than that in South Australia, where 13.6% of 22 white
sharks tagged were recaptured, with traveling dis-
tances of 18-220 km and times at liberty of 30-78 days
(Bruce, 1992). The higher recapture rate and lower
mean time at liberty (60 days) suggest that South Aus-
tralian white sharks may incur a higher fishing mor-
tality, which is understandable, as no legislation pro-
hibits angling for this species. Only two of a small but
TABLE IV Parameters in White Shark Mortality
Estimates off the South African Coast
0.9 (fixed)
CV (%)
L (95%)
R (95%)
CV, Coefficient of variation; L, left (lower) 95% confidence limit
of estimate; R, right (upper) 95% confidence limit of estimate.
unspecified number of white sharks tagged on the
East Coast of the United States have been recaptured,
one of which traveled 614 km during 1.3 years at
liberty (Casey et al., 1991).
In the present study, four recaptures were made in
the same area; three of the four occurred close to 1
year later. This pattern of sharks returning to fixed
localities at yearly intervals has been suggested by
research in California (Ainley et al, 1985; Klimley and
Anderson, Chapter 33). In South Australia, there is
also a high degree of site fidelity, with 36% of the 58
marked sharks resighted, all at their original locations
(Strong ^f a/., 1992).
The large distances (774 and 1409 km) covered by
two of the recaptured sharks indicate that the animals
are also highly mobile in South African waters. Al-
though these long-distance movements were farther
than those reported in Australia or the United States,
they, too, were coastwise. The low incidence of white
sharks near islands in the Pacific and Indian oceans
indicates that there may be limited transoceanic
movement, and the warm tropical surface waters
may act as a barrier to regular transequatorial move-
ment of white sharks. Although the population of
white sharks along the southern African coast may
not be geographically isolated, there may be little re-
cruitment from other centers of abundance, high-
lighting the need for local legislation to prevent pos-
sible overexploitation. Genetic studies are being
conducted to compare white sharks from different
regions (see Chapter 6, by Martin).
Several assumptions, some of which were dis-
cussed by Ricker (1975), were made in using the Pe-
tersen estimate to determine the size of the white
shark population.
Instantaneous mortality rates, Z and f, are con-
stant. The assumption of constant natural mortality
may not be unreasonable, given that the duration of
the study is relatively short compared to the life span
of white sharks. Furthermore, the sharks tagged com-
prised few very small animals, which may be more
prone to predation, and no very large sharks, which
were approaching the end of their life span. On the
other hand, fishing mortality would be affected by
any change in fishing effort during the study period.
The largest components of this effort are the shark
which remained constant, and big-game an-
gling, whose effort was heavily curtailed by the pro-
tective legislation introduced in 1991. There were no
reports of any change in effort in the trawl fishery
and by spear fishermen. The extent of the reduction
in f is unknown.
There is a 10% instantaneous tag shedding and
tag-induced mortality. Tags inserted into sharks
36. Population Size off South Africa 399
caught in the nets were checked to ensure that they
were firmly embedded before the animals were re-
leased. Due to the stress of capture on a baited line or
in a gill net, some mortality is likely. Telemetry may
provide an assessment of capture mortality. In this
study, we assumed that 90% of tagged animals sur-
vived the stress of capture, hence a = 0.9.
There is no long-term tag shedding. The good
condition of the tag in a shark recaptured after 527
days indicates good tag retention. Tag shedding is
therefore thought to be low. A large bull shark re-
tained its dart tag for 11 years in captivity before be-
ing released. Double-tagging experiments on white
sharks may provide more information on long-term
tag shedding rates.
All recaptures of tagged sharks are reported. All
recaptures in the shark nets should be reported; how-
ever, following the introduction of protective legisla-
tion, recaptures by big-game anglers may be unre-
ported for fear of prosecution. Some spear fishermen
are known to shoot sharks that threaten them. Any
tagged sharks killed in this way may pass unnoticed
by the diver, and hence may not be reported.
The distribution of tagged fish or the fishing
effort is random. Despite the high degree of site fidel-
ity discussed earlier, the average time to recapture of
0.754 year is ample time to allow for the mixing of
tagged and untagged sharks. The recapture of a shark
1 day after release was excluded from the popula-
tion analyses, because there was insufficient time for
mixing. Fishing effort is not random, as the nets are
permanently installed at fixed localities, while the
efforts of T.K.W. are concentrated in the Struis Bay
6. Recruitment or emigration is negligible. Recruit-
ment of newborn white sharks to the fishery may be
balanced by a combination of natural mortality and
inaccessibility of particularly large specimens. Tag-
ging occurred between Richards Bay, KwaZulu-Na-
and Struis Bay, Western Cape, or only part of the
shark's southern African range. There will be consid-
erable movement of sharks into and out of the tag-
ging region, resulting in a gradual reduction in the
proportion of tagged animals in the study area.
The Petersen estimate of 1279 sharks (Table III) ap-
plies only to the region between Richards Bay and
Struis Bay and excludes all the northern and much of
the western Cape coasts, where the many colonies of
South African fur seal Arctocephalus piisillus pusilliis
(Oosthuizen and David, 1988) may attract a large
number of white sharks. The estimate is fairly insen-
sitive to decreased values of the unknown compo-
nent of the annual catch, which, when halved, results
in a 14% decline in the population, that is, to 1098
sharks. The coefficient of variability (24%) of the esti-
mate is low, considering the small sample sizes.
In this study, F - 0.055, Z = 0.53, and Z - f - 0.48
year"^ which represents the sum of M and U, where
M is the instantaneous rate of natural mortality and U
is the sum of the instantaneous rate of emigration and
long-term tag shedding. M is unknown, but is likely
to be low for this apex predator, with its apparent
slow growth and low fecundity. In the porbeagle
shark Lamna nasus, another member of the family
Lamnidae, M = 0.18 year^^ (Aasen, 1963). M is un-
likely to exceed this value in white sharks of the size
range tagged in this study. This results in U = 0.3
year '. As mentioned above, long-term tag loss is
likely to be low, and emigration, whereby tagged
white sharks move out of the study region, is the
major component of U.
A possible yardstick in assessing the validity of
protective legislation is to ensure that fishing mortal-
ity, now mainly that due to shark nets, does not ex-
ceed natural mortality. In this study, f is considerably
lower than the sum of M and U. Many of the sharks
caught in this study were released alive; conse-
quently, the real F may be lower than 0.055 year '
and, in our opinion, does not represent overfishing of
white shark stocks. Improved estimates of mortality
and emigration are needed, however, before relax-
ation of the current protective legislation can be con-
The ORI Tagging Programme tagged 73 white
sharks C. carcharias in South African waters between
January 1989 and December 1993. Anglers in temper-
ate Cape waters tagged 48 (66%) of the sharks; the
remainder were tagged by the NSB. Cape specimens
were larger than those from KwaZulu-Natal; most of
the sharks were 150-400 cm PCL. Six of the sharks
(8.2%) were recaptured within a mean of 275 days
(range, 1-527 days) and a mean distance traveled of
365 km (range, 0-1409 km). A modified Petersen esti-
mate was used to determine the size of the white
shark population for each of the 5 years of the study.
Allowance was made for capture-induced mortality
and the rerelease of tagged sharks that were recap-
tured. Fishing mortality was assumed to be constant,
despite the introduction of protective legislation in
The overall estimate was 1279 sharks (95% con-
fidence limits, 839-1843) for the region Richards Bay
in KwaZulu-Natal to Struis Bay in Western Cape.
Mortality rates were estimated as f = 0.055 year '
confidence limits, 0.015-0.10) and Z = 0.53
year^^ (95% confidence limits, 0.42-0.66). Improved
estimates of mortality are needed before any relax-
ation of the protective legislation can be considered.
We are indebted to the members of the ORI Tagging Pro-
gramme, particularly the field staff of the NSB, who have tagged
white sharks. The financial support of Stellenbosch Farmers Win-
ery and the Southern Africa Nature Foundation, sponsors of the
tagging program, is gratefully acknowledged. A. E. Punt, L. Beck-
ley, S. F. J. Dudley, and V. Peddemors commented on the manu-
script. The senior author (G.C.) thanks the National Audubon Soci-
ety and the Steinhart Aquarium, California Academy of Sciences,
for financial assistance in attending the symposium.
... Capture−recapture studies are widely used to estimate the size of wildlife populations and have been conducted in other areas where white sharks aggregate (Cliff et al. 1996, Strong et al. 1996, Sosa-Nishizaki et al. 2012, Towner et al. 2013, Andreotti et al. 2016, Becerril-García et al. 2020. These approaches are based on reconstructing encounter histories over time and require that individuals are 'marked' in some way that makes them distinguishable from other individuals in the population. ...
... These approaches are based on reconstructing encounter histories over time and require that individuals are 'marked' in some way that makes them distinguishable from other individuals in the population. Early white shark capture−recapture surveys used conventional fisheries dart tags to mark individuals (Cliff et al. 1996, Strong et al. 1996, but the realization that individual sharks could be identified by their unique coloration and dorsal fin profiles revolutionized researchers' ability to efficiently and noninvasively obtain encounter history data (Klimley & Anderson 1996, Strong et al. 1996, Domeier & Nasby-Lucas 2007. Photographic identification (hereafter photo-ID) surveys have been used to monitor and estimate the size of white shark aggregations in the eastern North Pacific and Indian oceans , Sosa-Nishizaki et al. 2012, Towner et al. 2013, Andreotti et al. 2016, but the appropriateness of the analytical approaches used to do so has become the subject of some debate. ...
... We conducted a seasonal photo-ID survey in the nearshore waters along the Atlantic coast of Cape Cod, known locally as the 'Outer Cape' (Fig. 1). Unlike previous capture-recapture surveys of white shark populations (Cliff et al. 1996, Strong et al. 1996, Towner et al. 2013, Andreotti et al. 2016), we employed active rather than passive (i.e. attracting sharks with baits) sampling techniques. ...
Full-text available
The present study provides the first estimate of abundance for the white shark at a new aggregation site in the western North Atlantic, which required the development of a novel modeling framework to accommodate the species’ migratory behavior. Estimates of abundance are needed to evaluate the performance of existing conservation measures for white shark populations worldwide but have historically been infeasible to obtain in the region. Following the recent emergence of Cape Cod, Massachusetts, USA, as a seasonal aggregation site, we conducted a photographic capture-recapture survey and identified 393 individual white sharks from 2015-2018. As conventional capture-recapture models do not adequately represent the species’ migratory behavior, we extended an existing open spatial capture-recapture framework to allow for movements into and out of the surveyed area and accommodate variation in residency and habitat use among individuals. Using simulations, we demonstrated that failing to account for these processes resulted in biased estimates of abundance that would be misleading if used as the basis for management advice. We applied the model developed to describe the seasonal dynamics of the Cape Cod aggregation site and estimated a superpopulation size of 800 (393-1286) individuals, which provides an important baseline for this species of conservation concern. Because it directly links changes in abundance over time to the demographic processes underpinning them, the model described provides a more mechanistic understanding of the dynamics of white shark aggregations and improves the applied relevance of the results for the conservation and management of the species.
... The South African population of white sharks has five main coastal aggregation sites (from west to east: False Bay, Gansbaai, Struisbaai, Mossel Bay and Algoa Bay). These aggregations are not genetically distinct (Andreotti et al. 2016), with sharks migrating between them, and further along the South African coast to KwaZulu-Natal (KZN), Mozambique and the Western Indian Ocean (Cliff et al. 1996;Ferreira and Ferreira 1996;Bonfil et al. 2005;Jewell et al. 2011). Some segregation by shark size is apparent between the sites, with average size typically increasing from west to east (Cliff et al. 1989(Cliff et al. , 1996Ferreira and Ferreira 1996;Dicken 2008;Kock et al. 2013;Towner et al. 2013;Hewitt 2014;Ryklief et al. 2014). ...
... These aggregations are not genetically distinct (Andreotti et al. 2016), with sharks migrating between them, and further along the South African coast to KwaZulu-Natal (KZN), Mozambique and the Western Indian Ocean (Cliff et al. 1996;Ferreira and Ferreira 1996;Bonfil et al. 2005;Jewell et al. 2011). Some segregation by shark size is apparent between the sites, with average size typically increasing from west to east (Cliff et al. 1989(Cliff et al. , 1996Ferreira and Ferreira 1996;Dicken 2008;Kock et al. 2013;Towner et al. 2013;Hewitt 2014;Ryklief et al. 2014). With the exception of Struisbaai, these locations are characterised by the presence of pinniped colonies (Dudley 2012). ...
... Christiansen et al. (2015) suggested multiple reasons why South Africa's young white sharks show such diversity in isotopic signatures, including individual variation, spatial segregation, and maternal influences. In the case of smaller sharks at the Gansbaai aggregation, temporal variation could also play a strong role in their isotopic diversity, representing a function of the time since they undertook the westerly coastal migration for the first time (Cliff et al. 1989(Cliff et al. , 1996Ferreira and Ferreira 1996;Dicken 2008;Kock et al. 2013;Towner et al. 2013;Hewitt 2014;Ryklief et al. 2014). Kelp detritus contributes significantly to the coastal food web of South Africa (Bustamante and Branch 1996;Miller and Page 2012), and recorded variation in δ 13 C values of kelp could also partially explain the variation in SIBER niches between juveniles and larger sharks as juveniles make comparatively more use of coastal habitat as opposed to the pelagic or tropical habitats utilised by larger individuals (Cliff et al. 2000;Zuffa et al. 2002;Bonfil et al. 2005;Hussey et al. 2012b;Smale and Cliff 2012;OCEARCH 2016). ...
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Demographic differences in resource use are key components of population and species ecology across the animal kingdom. White sharks (Carcharodon carcharias) are migratory, apex predators, which have undergone significant population declines across their range. Understanding their ecology is key to ensuring that management strategies are effective. Here, we carry out the first stable isotope analyses of free-swimming white sharks in South Africa. Biopsies were collected in Gansbaai (34.5805°S, 19.3518°E) between February and July 2015. We used Stable Isotope Bayesian Ellipsis in R and traditional statistical analyses to quantify and compare isotopic niches of male and female sharks of two size classes, and analyse relationships between isotopic values and shark length. Our results reveal cryptic trophic differences between the sexes and life stages. Males, but not females, were inferred to feed in more offshore or westerly habitats as they grow larger, and only males exhibited evidence of an ontogenetic niche shift. Lack of relationship between δ13C, δ15N and female shark length may be caused by females exhibiting multiple migration and foraging strategies, and a greater propensity to travel further north. Sharks < 3 m had much wider, and more diverse niches than sharks > 3 m, drivers of which may include individual dietary specialisation and temporal factors. The differences in migratory and foraging behaviour between sexes, life stages, and individuals will affect their exposure to anthropogenic threats, and should be considered in management strategies.
... These events were also described by other authors along the coast of South Africa. Annual catch rates of white sharks C. carcharias in shark nets, set along the KwaZulu-Natal coast, varied considerably from 1966 to 1993 (Cliff et al. 1996) and those authors observed that a cyclical trend peaked with 4-6 years intervals. The similar peak year interval is not surprising, as most white sharks that are part of Gansbaai aggregations also move into KZN shark netted areas (Ocearch accessed, 2013;Towner et al. 2013b). ...
... Most of the white sharks sighted undergo a change of diet from piscivorous to marine mammals (Tricas & McCosker 1984) and it cannot be excluded that the presence of other prey (bony fish or other sharks) influences the presence of C. carcharias in the area. As evidence of the absence of correlation between the availability of young fur seals and the presence of sharks, the trend in the Kwazulu-Natal area is similar, despite the absence of colonies of seals (Cliff et al. 1996). However, it would take several decades of sightings to statistically confirm the existence of peaks. ...
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In Gansbaai (South Africa), at Dyer Island Nature Reserve, a large White shark population is present and can be observed due to the support of local ecotourism operators authorised to reach the field observation sites. Between 2009 and 2019, it was possible to create a database including information about each individual observed. In total, 423 white sharks were sighted during 462 direct observation hours from the boat, that included 220 hours from the diving "cage". The mean sighting rate was 0.91 (range 0.18-1.53) sharks per hour and sighting rates dramatically declined in the last three years of the study period. Ninety-nine unique Photo-Ids of the dorsal fin were collected and only five re-sightings occurred, which indicate a transient behaviour for the Gansbaai White shark population. The sex ratio showed that females were always prevalent over males throughout the duration of the observations: the ratios were 1:2.2:0.8 for males, females, and unsexed sharks, respectively, and showed the prevalence of immature female individuals (immature: 51 males, 201 females, and 40 unsexed; adults: 49 males, 14 females, and 1 unsexed; undefined maturity: 5 males, 19 females, and 43 unsexed sharks). The predominance of immatures only applies to the females; there were as many immature males (51) as mature (49). The total length for all the individuals was between 150 cm and 500 cm (mean 308 cm, n = 423) with few young-of-the-year and adults recorded, indicating that Gansbaai Area is not a nursery area nor an adult aggregation site, but a seasonal feeding ground. The interannual sighting trend showed a consistent long-term increasing peak (ca. 4-5 years) and this could confirm that, in Gansbaai, the White shark frequency is not affected by ecotourism but, since 2017, a consistent loss of sightings was also due to recorded transient killer whales' unusual fatal attacks.
... Two Petersen-Bailey estimates were obtained for the population size of G. cirratum in RA, referring to the first and second expeditions and second and third expeditions. Once these calculations were done, the total N was calculated as the average of the two previous values as in Cliff et al. (1996) (i.e., N is the average of N estimates). So: ...
The Atlantic nurse shark, Ginglymostoma cirratum , was recently listed as Vulnerable by IUCN Red List, however, as highlighted, little is known about its populations in the Southwestern Atlantic. Therefore, population studies are essential to propose status evaluations and new conservation measures. Natural marks present on the animals' bodies are used as an alternative non‐invasive method rather than the usual tagging system for individual identification, thus avoiding the need for animal handling. This study aimed to evaluate the population size trend of G. cirratum at the Rocas Atoll Marine Biological Reserve, the only atoll located in the South Atlantic. Data were collected through underwater filming, photo‐identification, and visual censuses. Three expeditions were carried out in 2018 and the abundance of sharks was sampled in the inner part of Rocas Atoll Marine Biological Reserve. Sharks were identified individually with the aid of the software Interactive Identification System – Contour (I3S). Based on the re‐sightings of identified animals, two capture–recapture estimators of population size were used (Petersen–Bailey; Jolly–Seber). The estimates were then compared to the only previous estimate made 20 years before, which employed the same number of expeditions and estimators. A total of 139 sharks were identified from 444 sightings in 63 h of diving effort. Population estimates varied from 200 to 205 sharks, which are significantly lower than the previous estimate (339–368 sharks) made 20 years ago, suggesting a demographic decline in Southwestern Atlantic populations. Population studies and movement of G. cirratum are essential to inform the implementation of additional protective measures, including the establishment of protected corridors between marine protected areas and the recovery of G. cirratum populations. It is crucial to consider that the distribution of individuals may extend beyond the borders of the non‐take marine protected area. Therefore, the observed decline in the local population could potential indicate a broader decline across the Southwestern Atlantic.
... Although large numbers of BRUVS videos were analysed (>500) and a large number of individually identifiable sharks recorded, the numbers of individuals re-sighted on successive campaigns were too low for open population mark-recapture models to be employed, such as the Schnabel and Jolly-Seber methods which we have applied to basking shark in Scotland [25]. However, the numbers of re-sightings in the Cayman Islands for six surveys over three years were high enough for successive population estimates of two species to be made using the Chapman derivative of the basic Lincoln-Peterson estimator [43,44], which is more robust for small sample sizes [45]. For each "re-capture" occasion t, the population size N t was calculated where n t = the number of sharks sighted on sample occasion t, r t = the number of marked sharks re-sighted in sample n t , and m t = the number of marked sharks at the beginning of sample occasion t: ...
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Baited Remote Underwater Video Stations (BRUVS) are widely used for monitoring relative abundances of fishes, especially sharks, but only the maximum number of individuals seen at any one time (MaxN) is usually recorded. In both the Cayman Islands and the Amirante Islands, Seychelles, we used photo-ID to recognise individual sharks recorded on BRUVS videos. This revealed that for most species the actual numbers of separate individuals (IndN) visiting the BRUVS were significantly higher than MaxN, with, for example, ratios of IndN to MaxN being 1.17 and 1.24 for Caribbean reef, Carcharhinus perezi, and nurse, Ginglymostoma cirratum, sharks in the Cayman Islands, and 2.46 and 1.37 for blacktip reef, C. melanopterus, and grey reef, C. amblyrhynchos, sharks, respectively, in the Amirantes. Further, for most species, increasing the BRUVS deployment period beyond the 60 min normally used increased the observed IndN, with more than twice as many individuals in the Cayman Islands and >1.4 times as many individuals in the Amirantes being recorded after 120 min as after 60 min. For most species, MaxN and IndN rose exponentially with time, so data from different deployment periods cannot reliably be compared using catch-per-unit-effort (CPUE) calculated as catch-per-unit-time. In both study areas, the time of first arrival of individuals varied with species from <1 min to >2 h. Individually identifiable sharks were re-sighted after up to 429 days over 10 km away in the Cayman Islands and 814 days over 23 km away in the Amirantes, demonstrating that many individuals range over considerable distances. Analysis of Cayman re-sightings data yielded mean population estimates of 76 ± 23 (SE) and 199 ± 42 (SE) for C. perezi and G. cirratum, respectively. The results demonstrate that, for sharks, the application of both photo-identification and longer deployment periods to BRUVS can improve the precision of abundance estimates and provide knowledge of population size and ranging behaviour.
... However, the first long-term fish tagging initiative in the region got under way in 1976, when the KwaZulu-Natal Sharks Board (KZNSB) began tagging elasmobranchs captured in their bather protection nets and by fishing in adjacent areas (Cliff and Dudley 1991a, b, Cliff and Dudley 1992a, b, Dudley and Cliff 1993, Cliff et al. 1996, Allen and Cliff 2000). This project remains in operation and to date more than 6200 elasmobranchs have been tagged with a 9.8% recapture rate (S. ...
... Some studies have extrapolated results to provide regional population estimates 11,12 , but extrapolating site-specific estimates to regional levels can be compromised by sharks' site fidelity, life-history-specific habitat use and factors impacting the probability of recording and re-sighting an individual 9,10,13 . Two studies have attempted population estimates based on conventional tag-recapture 14,15 , but these have similar challenges in addition to issues around tag loss and low sample sizes. Establishing current status and trends in marine populations generally requires long-term, standardized, historical records or other suitable abundance indices. ...
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Conservation concerns exist for many sharks but robust estimates of abundance are often lacking. Improving population status is a performance measure for species under conservation or recovery plans, yet the lack of data permitting estimation of population size means the efficacy of management actions can be difficult to assess, and achieving the goal of removing species from conservation listing challenging. For potentially dangerous species, like the white shark, balancing conservation and public safety demands is politically and socially complex, often leading to vigorous debate about their population status. This increases the need for robust information to inform policy decisions. We developed a novel method for estimating the total abundance of white sharks in eastern Australia and New Zealand using the genetic-relatedness of juveniles and applying a close-kin mark-recapture framework and demographic model. Estimated numbers of adults are small (ca. 280–650), as is total population size (ca. 2,500–6,750). However, estimates of survival probability are high for adults (over 90%), and fairly high for juveniles (around 73%). This represents the first direct estimate of total white shark abundance and survival calculated from data across both the spatial and temporal life-history of the animal and provides a pathway to estimate population trend.
... Maestría en Ciencias: Biología de Sistemas y Recursos Acuáticos. blanco, Carcharadon carcharias;(Geremy et al. 1996), donde se encontró que la mortalidad natural (M) no es dependiente de la longitud máxima (L∞) (R 2 de M vs. L∞ = 0.164), ni de la tasa de crecimiento individual (K) (R 2 de M vs. K =0.4077), sino de un conjunto de factores asociados, que en muchos casos son casi imposible de ser estimados de manera convencional(Vetter, 1988), añadidos a las respuestas adaptativas de cada especie o población a tratar de mantenerse en equilibrio frente a presiones pesqueras o de catástrofes, y que se observa por lo general en la disminución de las tallas de madurez, longevidad y fecundidad(Daimond, 1989).Contra lo que muchos autores recomiendan se debe de evitar la estimación únicamente por el método deHoening (1983), ya que continuamente se observa que se rompen marcas de captura en las pesquerías(Sparre et al. 1989), el valor puede ser subestimado frecuentemente, lo que ocasionaría graves consecuencias para el stock, si dependiera de este parámetro el incremento de la flota pesquera.El valor obtenido en este trabajo es muy similar al encontrado por Chen y Liu (1997) para la misma especie en las aguas de Taiwan (M=0.3), de la misma manera que en la costa michoacana, la estructura de edad en las capturas es muy similar en Taiwan(Chen et al, 1990), pudiendo quizá aplicar una estrategia de pesca similar a las dos poblaciones.En este trabajo, el parasitismo se observa como una causa indirecta de mortalidad, debido a que aumenta la susceptibilidad a la depredación y/o desnutrición grave, como se puede ver en ...
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Este trabajo se basó en el análisis de 4692 tiburones martillo (Sphyrna lewini) recolectados durante 11 años (junio de 1987 a febrero de 1998) procedentes de la pesca artesanal de la costa michoacana. Paralelo a esta costa existen tres zonas de segregación social de estos tiburones, siendo la más importante el área de refugio y crianza, donde las crías se reclutan cerca del Río Nexpa. Un indicio de la reducción de la edad reproductiva como mecanismo de regulación frente a la presión pesquera, es que las edades estimadas de primera madurez y de maduración del 50% de la población, no presentaron diferencias significativas (P>0.0001). La gestación dura aproximadamente 10 meses, los partos presentan un promedio de 30 crías con una proporción 1.2:1 de hembras contra machos, los ciclos de partos masivos son trianuales. Estos tiburones son ictiófagos con una alta preferencia por batoideos, diferenciándose las hembras por preferir presas pelágicas, llegando a incluir en su dieta al delfín manchado (Stenella attenuata), sin que se pueda diferenciar si esta observación corresponde a la depredación o carroñeo. Los tiburones martillo juveniles, de 110 a 160 cm, ejercen canibalismo sobre las crías, como depredadores importantes de juveniles del tiburón martillo se encuentran el tiburón volador (Carcharhinus limbatus) y el pargo colmillón (Lutjanus novemfasciatus). Las relaciones de la ictiofauna acompañante en la captura, se definen principalmente por depredadores y presas, además de la competencia interespecífica expresada por la preferencia alimenticia, depredación y uso del espacio. Los índices de mortalidad natural (M) y por pesca (F) presentan valores de 0.32 y 0.61 respectivamente, mientras que los rendimientos por recluta (Y/R) muestran una especie que encuentra en sus máximos valores al tener edades de entrada a la pesquería y promedio de captura cercanas a la madurez sexual. Los valores demográficos obtenidos fueron Ro = 11.8 y r = 0.32, por su comportamiento en diferentes escenarios, el primer índice representa la resistencia y el segundo la elasticidad del stock frente a la pesca de esta región. En las condiciones actuales de pesca Ro desciende hasta 5.5% mientras que la r se vuelve negativa.
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Understanding movement patterns underlies effective management and conservation measures. The current study summarises the main findings from a tagging program of Western Australian sharks to provide insights into the movement patterns of the main commercial shark species: dusky (Carcharhinus obscurus), sandbar (C. plumbeus), gummy (Mustelus antarcticus) and whiskery (Furgaleus macki) sharks. Between 1993 and 2020, >12 000 individuals from 52 taxonomic groups were implanted with conventional tags in Western Australia, of which 8.5% were recaptured. Most of the tagged (74.5%) and recaptured (95.8%) individuals belong to the four main commercial shark species. Recaptured individuals of these species, as well as tiger (Galeocerdo cuvier) and bronze whaler (C. brachyurus) sharks showed displacements of >1000 km and rates of movement (ROMs) of >10 km day–1, with the exception of whiskery sharks, which showed much slower ROMs (<3 km day–1). Despite tagged dusky and sandbar sharks being predominately small individuals and gummy and whiskery sharks being large individuals, dusky and sandbar sharks had faster ROMs and a greater proportion of recaptures outside the release zone. Our study provided the information required for estimating movement rates across different fishing zones and therefore defining the spatial scale for managing these shark species.
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