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Abundance and degree of residency of humpback dolphins Sousa plumbea in Mossel Bay, South Africa

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DOI: 10.2989/1814232X.2015.1083477
Abstract
Indian Ocean humpback dolphins Sousa plumbea inhabit nearshore waters from South Africa to eastern India. Humpback dolphins are vulnerable to conservation threats due to their naturally small population sizes and use of nearshore habitats, where human activities are highest. We investigated the abundance and residency of this species inhabiting Mossel Bay, South Africa, using photographic mark-recapture. Data were collected during 81 surveys in Mossel Bay between 2011 and 2013. Open population modelling using the POPAN parameterisation produced a ‘super-population’ estimate of 125 individuals (95% CI: 61–260) and within-year estimates of between 33 and 86 individuals (2011: 71 [95% CI: 30–168]; 2012: 33 [15–73], 32 [15–70]; 2013: 46 [20–108]). Although less appropriate, closed capture models were also run for comparison with previous studies in the region and generated similar, but slightly smaller, population estimates within each year. We compared our catalogue with opportunistic data collected from East London, Plettenberg Bay, De Hoop and Gansbaai. The only catalogue matches attained were between Plettenberg Bay (n = 44 identified) and Mossel Bay (n = 67 identified), separated by 140 km. Population exchange was moderate, with nine individuals resighted in multiple years between these two areas. This study supports previous findings of long-range movements for this species and provides a baseline from which to assess future impacts on the population.
African Journal of Marine Science 2015, 37(3): 383–394
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AFRICAN JOURNAL OF
MARINE SCIENCE
ISSN 1814-232X EISSN 1814-2338
http://dx.doi.org/10.2989/1814232X.2015.1083477
African Journal of Marine Science is co-published by NISC (Pty) Ltd and Taylor & Francis
Indo-Pacific humpback dolphins Sousa spp. inhabit warm,
shallow, coastal waters (<30 m deep) of the Indo-Pacific
region between South Africa in the west and Australia and
China in the east (Reeves et al. 2008). The western limit
of the species’ range is currently considered to be False

Africa, with further range extension being constrained by
the cold waters of the Benguela Current (Findlay et al. 1992;
Jefferson and Karczmarski 2001; Best 2007). A global study
of the genus (Mendez et al. 2013) reported strong genetic
and morphometric variation, suggesting three extant species
of Indo-Pacific humpback dolphins. The new nomenclature
described them as the Indian Ocean humpback dolphin
S. plumbea, Indo-Pacific humpback dolphin Sousa chinensis
(with the boundary between them occurring in the region of
the Bay of Bengal, India), and Australian humpback dolphin
S. sahulensis off northern Australia (Reeves et al. 2008;
Jefferson and Rosenbaum 2014). We have thus chosen to
follow this new species designation and hereafter refer to the
study species (and all previous literature pertaining to the
plumbea ‘form’) as S. plumbea.
Available abundance estimates indicate there may
be <10 000 individuals of S. chinensis and S. plumbea
combined, worldwide (Reeves et al. 2008), and <1 000
S. plumbea are thought to occupy the entire South
African coastline (Karczmarski 1996). Its low abundance,
discontinuous distribution and high exposure to human
impacts, including coastal fisheries, shipping, pollution,
entanglement in bather protection nets, and coastal
development throughout its global range, categorise
S. plumbea (reported as the plumbea-type of S. chinensis)
as Vulnerable on the IUCN Red List of Threatened Species
(Reeves et al. 2008). During the most recent update of
the South African National Red List Assessment (June
2014), S. plumbea was recognised as Endangered based
on a number of criteria, primarily its small range, popula-
tion fragmentation and low population size (Endangered
B1 ab (ii iii v)/Vulnerable D1) (Atkins et al. in press). Sousa
plumbea was the only marine mammal in South Africa to
be moved to a higher category of conservation concern
and the only dolphin listed as Endangered (Atkins et al.
in press). It is one of the better-studied cetacean species
on the southern African coastline; however, the majority of
studies are over 10 years old (Elwen et al. 2011). Given the
national and international recognition of the conservation
status of this species, it is imperative that information on the
status of the species in South African waters is updated.
Mark-recapture using photographic identification is a
powerful and versatile technique widely used to assess the
abundance, residency, social interactions and individual
behaviours of a number of cetacean species (Calambokidis
and Barlow 2004; Baird et al. 2009; Barendse et al.
Abundance and degree of residency of humpback dolphins Sousa plumbea
in Mossel Bay, South Africa
BS James
1,2
, MN Bester
1
, GS Penry
1
, E Gennari
2,3
and SH Elwen
1
*
1
Mammal Research Institute, University of Pretoria, Hatfield, South Africa
2
Oceans Research, Mossel Bay, South Africa
3
South African Institute for Aquatic Biodiversity, Grahamstown, South Africa
* Corresponding author, e-mail: simon.elwen@gmail.com
Indian Ocean humpback dolphins Sousa plumbea inhabit nearshore waters from South Africa to eastern India.
Humpback dolphins are vulnerable to conservation threats due to their naturally small population sizes and use
of nearshore habitats, where human activities are highest. We investigated the abundance and residency of this
species inhabiting Mossel Bay, South Africa, using photographic mark-recapture. Data were collected during 81
surveys in Mossel Bay between 2011 and 2013. Open population modelling using the POPAN parameterisation
produced a ‘super-population’ estimate of 125 individuals (95% CI: 61–260) and within-year estimates of between
33 and 86 individuals (2011: 71 [95% CI: 30–168]; 2012: 33 [15–73], 32 [15–70]; 2013: 46 [20–108]). Although less
appropriate, closed capture models were also run for comparison with previous studies in the region and generated
similar, but slightly smaller, population estimates within each year. We compared our catalogue with opportunistic
data collected from East London, Plettenberg Bay, De Hoop and Gansbaai. The only catalogue matches attained
were between Plettenberg Bay (n = 44 identified) and Mossel Bay (n = 67 identified), separated by 140 km.
Population exchange was moderate, with nine individuals resighted in multiple years between these two areas. This
study supports previous findings of long-range movements for this species and provides a baseline from which to
assess future impacts on the population.
Keywords: mark-recapture, open population modelling, photo-identification, Plettenberg Bay, POPAN, Sousa chinensis
Introduction
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James, Bester, Penry, Gennari and Elwen
384
2010; Reisinger and Karczmarski 2010). Photographic
mark-recapture studies assessing S. plumbea abundance
and residency patterns have been conducted in four
locations in southern Africa: on the east coast in Maputo

KwaZulu-Natal (KZN) coastline, with a focus on Richards
        
Keith et al. 2002); and on the Cape south coast in Algoa

       
Jobson 2006) (Figure 1). In all cases, population estimates
were <600 individuals and mostly <200 individuals, and
population connectivity between these study sites is not well
understood.
In South African waters, S. plumbea is concentrated in
two main areas, the KZN north coast and the Cape south
coast (Figure 1). Off the KZN coast, S. plumbea is more
common in the shallow waters of the Thukela Bank area
(which extends roughly 60 km north and 80 km south
of Richards Bay), where it appears to be associated with
the four major river mouths in the area (Durham 1994).
The species is rare along the southern KZN and Transkei
(i.e. northern part of the Eastern Cape) coastline as is
evident from the low encounters (Durham 1994; Keith et al.
2002), low number of strandings (Findlay et al. 1992), low
sightings during aerial surveys (Ross et al. 1989) and low
captures in bather protection nets (Atkins et al. 2013). This
hiatus in distribution appears to functionally separate South
Africa’s east and south coast populations. This is supported
further by (i) a lack of matches found during a comparison
of photo-identification catalogues from Algoa Bay and KZN,
which are 1 060 km apart (Karczmarski et al. 1999) and
(ii) the existence of two distinct mitochondrial DNA (mtDNA)
haplotypes from individuals sampled on the northern KZN
coast and the Cape south coast, including Algoa Bay
and False Bay (Smith-Goodwin 1997), although sample
size from the Cape south coast was limited. Therefore, it
appears that the populations of S. plumbea on the Cape
south coast and on the KZN coast are essentially separate
(Figure 1).
Despite being adjacent to a populated and accessible
stretch of coastline with relatively high numbers of whale-
AFRICA
South
Africa
SOUTH AFRICA
Cape south coast
East coast
Local Sousa plumbea range
20° E
22°15 E
30° E
34° S
34°11 S
0 175 350 km
0 5 10 km
Western
Cape
Eastern
Cape
KwaZulu-
Natal
Study area
Dedicated surveys
CTD surveys
50 m
30 m
20 m
15 m
Figure 1: Map of the study area, Mossel Bay, and the names and locations of sites mentioned in the text. Also shown are the typical tracks for
dedicated and oceanographic CTD surveys conducted between 20 April 2011 and 14 November 2013. The range of Sousa plumbea in South
African waters is shown
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African Journal of Marine Science 2015, 37(3): 383–394
385
watching companies and research organisations, the Cape
south coast population of S. plumbea is particularly poorly
studied. There are few published data for the approximately
1 000 km of coastline between East London and False Bay,
other than from Algoa Bay, which was the subject of a multi-
year study in the early 1990s (Karczmarski and Cockcroft
1998; Karczmarski 1999; Karczmarski et al. 1999). In the
current study we provide a mark-recapture estimate of

which represents the most westerly abundance estimate
available for S. plumbea (500 km from the known western
limit of the species). Further, we investigate individual
movement patterns by comparing the photo-identification
data collected in this study with opportunistic dorsal fin
photographs available from four sites along the southern
South African coastline. For purposes of compari son,
wherever possible we have used the same or similar defini-
tions and methods used in earlier studies in the region.
This study thus provides important baseline information
on the population that uses Mossel Bay, which may be
useful for broader species conservation and management
initiatives.
Material and methods
Data collection
Data were collected a minimum of once per month from
2011 to 2013 in Mossel Bay, except in August 2011 when
no surveys were undertaken due to logistical constraints
(Table 1). Mossel Bay is a large semi-enclosed embayment
on the south coast of South Africa (Figure 1). The bay is
shallow, with the 20 m depth contour ~1.2 km from the
shore, and is moderately sheltered from the prevailing
westerly wind and swell by the Cape St Blaize peninsula
to the west of the bay. The sea floor is characterised by
areas of both sandy bottom and exposed nearshore reefs
(Jackson and Lipschitz 1984). The small Seal Island, on
the western side of the bay, is occupied by a rookery of
Cape fur seals Arctocephalus pusillus pusillus (Johnson et
al. 2009). Three rivers enter the bay; the Klein Brak River
mouth was permanently open during the study period, the
Hartenbos River was closed by a large sandbar (described
by Swartz et al. 2000) and the Groot Brak River was
opened mechanically (by bulldozer) between September
and April each year (Anchor Environmental 2012).
Boat-based surveys were conducted from a 6-m
fibreglass catamaran-type skiboat with two 90-HP
two-stroke engines. Data were collected during (i) dedicated
photo-identification surveys and (ii) line-transect surveys
conducted for the collection of physical oceanographic data
(conductivity, temperature and depth), hereafter referred
to as CTD surveys. Both survey types covered a similar
search area between the Groot Brak River mouth and the
Mossel Bay Harbour (Figure 1). Dolphins were approached
and photographed in the same manner during both survey
types, allowing for the compilation of a single catalogue.
Dedicated photo-identification surveys were conducted
in both directions between the limits of the search area
(Figure 1). A searching speed of 7 knots was maintained,
with a minimum of three observers searching continuously
using the naked eye and binoculars.
During CTD surveys, data collection began in the Groot
Brak area and ended at the Mossel Bay Harbour, following
a predefined inshore–offshore zigzag route between
200 and 1 000 m from the shore (Figure 1). During these
surveys, the boat came to a complete stop at the end of
each transect line to collect CTD data. A single observer
conducted continuous 360° scans during the CTD deploy-
ment, as well as when the boat was in transit between
sampling stations. If any cetaceans were sighted between
stations, the animals would immediately be approached.
However, if animals were sighted while on station, they
would be approached only after the completion of the CTD
data collection.
On both types of survey, standard data collected
were as follows: (i) time and location of the encounter;
(ii) estimates of group size (minimum, best and maximum);
(iii) group composition (calves, juveniles and adults)
and (iv) behaviour. A group was defined as a number of
Month
Number
of
surveys
Number
of
encounters
Total
survey
time (h)
Number
of
photos
Number

photos
2011
April 1 1 5.2 382 274
May 3 1 19.5 358 257
June 6 2 22.8 1 545 838
July 3 0 7.5 0 0
Aug. 0 0 0.0 0 0
Sept. 1 1 5.6 109 95
Oct. 1 0 7.3 0 0
Nov. 3 1 11.6 75 42
Dec. 3 0 12.1 0 0
2012
Jan. 1 0 5.5 0 0
Feb. 3 2 18.1 272 176
Mar. 4 3 28.2 1 014 764
April 1 0 5.0 0 0
May 1 0 5.0 0 0
June 2 0 13.8 0 0
July 1 1 8.5 123 99
Aug. 4 2 31.1 102 30
Sept. 2 1 13.3 127 14
Oct. 3 1 23.0 64 30
Nov. 2 0 8.8 0 0
Dec. 3 2 18.4 371 206
2013
Jan. 3 1 15.5 28 7
Feb. 4 1 21.7 528 467
Mar. 3 2 23.0 278 226
April 4 3 29.0 551 335
May 3 1 21.7 28 9
June 2 1 13.8 36 12
July 5 1 26.5 26 16
Aug. 3 1 24.6 15 5
Sept. 3 1 23.1 3 0
Oct. 1 1 9.0 151 133
Nov. 2 1 12.5 6 2
Total 81 32 490.7 6 192 4 037
Table 1: Summary of survey effort in Mossel Bay between 2011
and 2013, including number of surveys and encounters, survey
time, number of photographs of Sousa plumbea and those of

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James, Bester, Penry, Gennari and Elwen
386
individual S. plumbea, observed together at the same
time, often engaged in the same or a similar behaviour
(Karczmarski 1999). Dolphin groups were approached
slowly and from behind to minimise disturbance. We
attempted to photograph all individuals in the group, regard-
less of markings or age. Photographs were taken using
a digital SLR camera equipped with a 70–300 mm zoom
lens and polarising filter. Individuals encountered more than
once on the same day were recorded as a single encounter.
Residency of animals within Mossel Bay was explored for
all animals in the catalogue, with those animals encoun-
tered at least four times during the study period consid-
ered asresident’, those seen only once classified as
‘transient’ and the remainder classified as ‘semi-resident’,
following the definitions of Keith et al. (2002). Seasonality
of presence was investigated by determining the number of
individuals encountered during each survey day within the
two defined seasons; winter (May–October) and summer
(November–April), following Karczmarski et al. (1999).
Opportunistic photographs of S. plumbea were available
from locations to the east and west of Mossel Bay. These
were collected from commercial whale-watching boats
        


during aerial patrols in the De Hoop Marine Protected Area

Data selection and processing
Photographs were graded for quality (Q) on a scale of 1–6
(Q1 being the worst and Q6 the best), based on the level
of focus, exposure of the dorsal fin and hump, lighting,
and angle to the camera (Elwen et al. 2009). Using only
photographs with a grade of Q3 or higher, individuals were
then graded on a distinctiveness (D) scale of 1–5, D1 being
not distinctive and D5 very distinctive (Elwen et al. 2009).
Individual identification was determined using several
criteria, including: (i) dorsal fin tears, (ii) nicks and notches,
(iii) deformities, (iv) colouration, (v) scratches, (vi) scars and
wounds, and (vi) distinctive fin shapes (Karczmarski and
Cockcroft 1998; Wilson et al. 1999; Mansur et al. 2011).
Multiple dorsal-edge marks and body scars were used to
identify or confirm the identity of catalogued individuals,
and all matches were confirmed by at least two authors
(BSJ and SHE). On account of the small group sizes and
high frequency of markings (body and dorsal markings), it
was possible to distinguish all individuals on any given day.
However, not all individuals were sufficiently distinctive to
allow for confident resighting between days or over longer
time-periods. Calves and juveniles were defined based
on their sizes and the closeness of their associations with
adults that were assumed to be their mothers (Karczmarski
1999). Only a small proportion of calves and juveniles had
distinguishing body marks that enabled confirmation of their
identity. Although adult individuals in Q3 photographs were
included in the photo-identification catalogue, only individ-
uals of distinctiveness D3D5 in photographs of quality
Q4 and above were used in mark-recapture analyses
to ensure consistent identification between encounters.
Opportunistic photographs were evaluated in the same
-
fiable individual placed into a working catalogue for each of
the four locations (East London, Plettenberg Bay, De Hoop
and Gansbaai). Individuals were then compared between
each catalogue and that of Mossel Bay, with all catalogues

Of the 69 animals identified in the various locations, only

areas. For all locations, individuals photographed in close
association with a calf on three or more sampling occasions
were assumed to be female (Karczmarski 1999; Keith et al.
2002).
Estimating abundance of marked individuals
Capture histories for each individual were compiled using
survey days on which S. plumbea was encountered as
the capture period. A visual inspection of the discovery
curve of newly captured individuals was used to investi-
gate whether the population could be considered openor
‘closed’ relative to the study area and period (Williams et al.
2002). The presence of an asymptote would indicate that
most animals had been captured and the population could
effectively be treated as closed, whereas the absence of an
asymptote would indicate that a relatively large number of
individuals in the population were yet to be captured, so the
population should be treated as open (e.g. Keith et al. 2002;
Williams et al. 2002; Reisinger and Karczmarski 2010).
To enable comparability with previous studies in the region,
we analysed our mark-recapture data using both open and
closed population models. The different assumptions and
Table 2: Summary of unpublished, opportunistic photo-identification data for Sousa plumbea from various locations along the South African
coast and from different sources
Location
Number of
photographs
Time-
period
Number
of surveys
Total number of
dolphins identified
Source
East London 115 2012 1 6 GSP (pers. obs.)
Plettenberg Bay 622 2006–2010, 2013 15 44 GSP (pers. obs.); ORCA
Foundation (2009, 2010; http://
orcafoundation.com)
De Hoop MPA
1
22 2007 3 8 P Chadwick (African
Conservation Photography;
www.peterchadwick.co.za)
Gansbaai 62 2007, 2008 7 11 Dyer Island Conservation Trust
1

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African Journal of Marine Science 2015, 37(3): 383–394
387
analytical methods employed by the two approaches (Jolly
1965; Otis et al. 1978; Chao 2001; Chao and Huggins 2005;
Cooch and White 2012) mean that the results are not directly
comparable, but using both can provide a more comprehen-
sive assessment of the number of S. plumbea in the study
area and also allows for direct comparisons to other studies
where closed models have been used. Here, we have
used both closed and open population models to estimate
annual abundance for each of the three consecutive years
(2011–2013). Closed models provide an estimate of the
number of individuals using the study area during each of
the three years whereas open population models provide an
estimate of the super-population for the entire study period,
which accounts for births and deaths occurring within that
period and also assume that some animals may be outside
the area (immigration and emigration) during the period.
Given that the mark-recapture estimates apply only to the
proportion of the population that is distinctively marked (see
below), it must further be assumed that the behaviour and
capture probability of the marked individuals is representative
of the entire population (Cooch and White 2012). Calves and
juveniles were excluded from the mark-recapture analysis
due to the low incidence of permanent/reliable dorsal fin
markings on young animals (Hammond et al. 1990). Our
abundance estimates therefore are representative of the
adult population. All mark-recapture analyses in our study
were conducted in the programme MARK (White and
Burnham 1999; Cooch and White 2012) using the RMark
interface (Laake 2013).
Closed population models
Annual estimates of abundance of S. plumbea in Mossel
Bay were calculated for 2011, 2012 and 2013, respectively,
by means of a series of closed capture models using the
Huggins log-likelihood method (Huggins 1989, 1991). Model
fit was compared using the penalised Akaike information
criterion (AICc) value to determine the best-fitting model in
each model set, with AICc values >2 regarded as signifi-
cant (Burnham and Anderson 2002). We implemented
models that allowed for variations in capture probability over
time and for differences in capture probability (heteroge-
neity) within the population using a two-mixture approach
(Pledger 2000). For models that included capture heteroge-
neity, the probability that an individual occurs in a specific
mixture () was fixed at a value of 0.475, based on a series
of successful model runs, to improve model convergence.
We did not include models that investigated a behavioural
response to capture (as might occur when animals are
trapped or physically captured) and set initial capture
probability equal to subsequent recapture probability (p c).
Open population models
Open population modelling was conducted using the
POPAN parameterisation (Schwarz and Arnason 1996)
in the Jolly–Seber (JS) framework (Jolly 1965; Seber
1965). Parameters calculated were the super-population
size (defined here as N
s
), apparent survival (), capture
probability (p) and the probability of entry from the super-
population (b) (Cooch and White 2012). Additionally, open
population models were also run for each year and were
compared with annual abundance estimates produced
using closed models. Because only adults were used
in analyses, no estimates of birth rate or recruitment
were available. Model fit was compared using the quasi-
penalised Akaike information criterion (QAICc) (Cooch and
White 2012).
Goodness-of-fit testing
Goodness-of-fit testing was performed to produce a
variance inflation factor (), which would indicate whether
the data were over- or underdispersed compared to a fully
time-dependent Cormack–Jolly–Seber model with perfect
fit (Cormack 1964; Jolly 1965; Seber 1965), and by how
much the data violate the model assumptions (Cooch and
White 2012). The factor was then used to produce a QAICc
to provide a means for model selection. For this study,
was determined using 1 000 simulations in a bootstrap
goodness-of-fit test in the program MARK and using the
standalone program RELEASE (Burnham et al. 1987).
RELEASE also provided results of TEST 2, TEST 3.SR and
TEST 3.Sm which test for capture homogeneity, survival
homogeneity and potential variation in survival over time,
respectively. Values of larger than 1.0 indicate overdisper-
sion in the data. To be conservative, the greatest value
produced by means of these tests was used to correct the
AICc prior to model selection using the QAICc for all open
population models (Cooch and White 2012).
Estimating total population size
To account for the poorly marked individuals not used in the
mark-recapture analysis, the mark-recapture estimates (N
ˆ
)
from both closed and open population models were extrap-
olated upwards to calculate the total population size (N
total
),
with variance calculated using the Delta method (Wilson
et al. 1999). The proportion of marked individuals () was

in good-quality photographs (Q4–Q6, n 1 321) expressed
as a proportion of the number of animals identified during
each survey, averaged over all surveys.
Results
In all, 491 hours of boat-based surveys, during 81 survey
days, were conducted between 20 April 2011 and 14
November 2013 (66 dedicated photo-identification surveys
and 15 CTD surveys). Sousa plumbea individuals were
encountered on 32 surveys (26 dedicated, 6 CTD) and
successfully photographed on 31 of them. The total time
spent with the dolphins during all encounters was 30
hours. During this time, 6 661 photographs were taken,
of which 1 321 (20%) were of acceptable quality (Q4 and
above) for use in mark-recapture analyses. Nine individ-
uals were rated with a distinctiveness of D2, 11 of D3, 33
of D4 and 14 of D5, with no adult individuals rated as D1
(unidentifiable) in reasonable-quality photographs. In all,
67 distinctive animals were identified and used to develop
a photo-identification catalogue (with 87% of catalogued

Of the catalogued individuals, 44% were encoun-
tered within the first three months of the study. About half
(n 33, 49%) were encountered only once, with only two
being encountered more than 10 times (Figure 2). Most
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James, Bester, Penry, Gennari and Elwen
388
individuals (n 44, 66%) were present in only a single
year; some (n 20, 33%) were present in two years and
only three (1%) were present in all three years of the study.
Group sizes varied between one and 15 (mean 4.9 ind. [SD
3.5]), with only four encounters of lone adults. Larger group
sizes were observed in 2011 than during other years, and
groups tended to be larger in summer (Figure 3).
Abundance estimate: closed population models
Closed capture models corrected by the proportion of
marked individuals in the population produced the following
within-year population estimates (N
total
): 2011 – 71 ind. (95%
CI: 30–167); 2012 35 ind. (14–86) and 28 ind. (14–55);
and 2013 43 ind. (19–98) and 54 ind. (19154). For
2011, the best-fitting model allowed for variation in capture
probability with time. In 2012, the null model and the model
allowing for capture heterogeneity fitted the data equally
well. In 2013, the model allowing for variation in capture
probability over time and the model allowing for capture
probability to vary both over time and with heterogeneity
were the best-fitting models (Table 3). Model averaging
of the real parameter value of p was undertaken for the
two best-fitting models in 2012 and 2013, respectively,
but no significant difference was found between model
results (Student’s t-test), and results from both models are
presented for each year.
Abundance estimate: open population models
Goodness-of-fit testing suggested slight overdispersion
in the super-population data, with 1.197 based on
bootstrapping in MARK and 1.04 in RELEASE based
on TEST 2 and TEST 3 (Table 4). The more conservative
value of (1.197) was used to correct the AICc for model
selection. The best model (QAICc 399.1) produced a
super-population abundance estimate (N
total
) of 125 ind.
(95% CI: 112–140) and included time-dependent survival,
constant capture probability and time-dependent probability
of entrance of an animal from the super-population into
the population {(t)p(.)b(t)N
s
(.)} (Table 5). Open popula-
tion estimates (N
total
) were fairly consistent between models
and varied between 104 ind. for the model with constant
survival and recapture probabilities and constant entrance
into the super-population {(.)p(.)b(.)N
s
(.)} and 127 ind.
for the model that included constant survival and capture
1 2 3 4 5 6 7 8 9 10 11 12
NUMBER OF SIGHTINGS
NUMBER OF DOLPHINS
10
20
30
All grades, all qualities
Grade D3, quality Q4
Figure 2: Frequency distribution of sightings of Sousa plumbea of
all distinctiveness grades in photographs of all qualities, and only
         
Mossel Bay between April 2011 and November 2013
20 Apr
2011
02 May 2011
22
Jun 2011
22 Feb 2012
24 Apr
2013
29 May 2013
20 Jun 2013
24 Jul
2013
23 Aug 2013
26 Sep 2013
29 Oct
2013
28 Feb 2012
23 Mar 2012
29
Mar 2012
18 Jul 2012
10 Aug 2012
30
Aug 2012
11 Sep
2012
10 Oct
2012
13 Dec 2012
14 Nov
2013
26 Dec
2012
27 Jun
2011
08 Jul
2011
08 Jan 2013
12 Feb
2013
17 Mar 2013
22 Mar 2013
03 Apr
2013
11 Apr
2013
11 Sep
2011
18 Nov 2011
SURVEY DATE
5
10
15
20
NUMBER OF INDIVIDUALS
IDENTIFIED PER SURVEY
20
40
60
80
100
120
140
CUMULATIVE TOTAL AND NEW INDIVIDUALS
0 0
Discovery curve
Entire study period
2011
2012
2013
Ind. per survey
Figure 3:

November 2013)
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African Journal of Marine Science 2015, 37(3): 383–394
389
probabilities with time dependent entrance into the super-
population {(.)p(.)b(t)N
s
(.)} (Table 5). Open population
modelling was also conducted within each year. The best
model for 2011 (QAICc 85.1) produced an abundance
estimate of 71 ind. (95% CI: 30–168) and included
time-dependent survival, constant recapture probability and
entrance into the population. For 2012, two models fitted
the data equally well (QAICc 94.5 and 95.2), producing
population estimates of 33 ind. (95% CI: 15–73) and 32
ind. (95% CI: 15–70), respectively. Both models included
constant survival and recapture probabilities but the models
differed in time dependence and constant entrance into the
super-population respectively. For 2013, the best-fitting
model (QAICc 99.1) produced an abundance estimate
of 46 ind. (95% CI: 20–108) and included time-dependent
survival, constant recapture probability and time-dependent
entrance into the super-population. Model selection for each
year was based on corrected AICc values using the more
conservative values (Table 4).
Residence
The time between resightings varied from five days to 22
months. Very few animals (n 7, or 10% of the population)
were resident’ in Mossel Bay during the study period, as
defined by Keith et al. (2002). Of those considered resident,
five were female (based on repeated close association
with a calf), of which two were seen more frequently when
they were accompanied by a small calf and less frequently
when the calf was older. Half of the animals identified in
Mossel Bay would be classified as ‘transient’ and 40% as
‘semi-resident’.
Seasonality
There were no consistent seasonality patterns in Mossel
Bay in terms of either number of animals encountered or
individual presence. Within each year there were multiple
months when no new individuals were captured. More
groups and more individuals were encountered during April
and June 2011 (summer and winter), March and December
Table 3: Huggins full heterogeneity closed model outputs including: number of parameters (N
par
); penalised Akaike information criterion
(AICc); difference between the selected candidate model and the top ranked model (AICc); the model’s deviation from a perfect fit
(Deviance); relative support for the model (Weight); estimate of the number of marked animals (N
ˆ
); standard error (SE); lower and upper
limits of the 95% confidence interval (LCL and UCL); and estimated total population (N
total
). The proportion of marked individuals () was
n 1 321) expressed as a proportion of
the number of individuals identified during each survey within each year, resulting in values of 0.85, 0.80 and 0.99 for 2011, 2012 and 2013,
respectively
Model*
Model selection criteria Marked population Total population
N
par
AICc AICc Deviance Weight N
ˆ
SE LCL UCL N
total
SE LCL UCL
2011
(.)p(t)c() 6 160.3 0.0 179.9 0.9 60 15 42 106 71 33 30 167
(.)p(.)c() 1 170.0 9.7 200.0 0.0 65 17 44 116 76 35 32 182
2012
(.)p(.)c() 1 153.7 0.0 150.1 0.5 22 4 19 35 35 17 14 86
(.)p(mix)c() 2 153.7 0.1 148.1 0.5 28 8 20 57 28 10 14 55
(.)p(t + mix)c() 11 159.0 5.3 133.7 0.0 28 8 20 56 35 17 14 84
(.)p(t)c() 10 159.4 5.7 136.4 0.0 22 3 18. 33 27 9 14 53
2013
(.)p(t)c() 8 178.8 0.0 176.3 0.6 43 8 33 68 43 19 19 98
(.)p(t + mix)c() 9 179.6 0.8 174.9 0.4 53 18 35 115 54 31 19 154
(.)p(.)c() 1 188.4 9.7 200.6 0.0 45 9 34 73 45 20 20 105
(.)p(mix)c() 2 189.2 10.5 199.4 0.0 57 20 36 128 57 34 19 169
* The parameters used to build the models in these sets are: the probability of being captured initially (p); the probability of recapture given
that the animal has been captured before (c), which for our models was set equal to p; and the probability that an animal occurs in a
specific mixture (). Each parameter may be designated as time dependent (t) or constant over time (.). Mixture (mix) was included as a
heterogeneity parameter to determine if capture probability varies between individuals with set at 0.475 for these models
Test
Super-population 2011 2012 2013
2
df p
2
df p
2
df p
2
df p
Test 2 + Test 3 1.04 34.27 33 0.41 0.55 1.64 3 0.65 1.02 6.12 6 0.41 0.22 1.32 6 0.97
Test 2 1.61 29.04 18 0.05 0.55 1.64 3 0.65 1.32 3.97 3 0.26 0.33 1.32 4 0.86
Test 3 0.35 5.24 15 0.99 NA NA NA NA 0.72 2.15 3 0.54 0.0 0.0 2 1.0
Test 3.SR 0.25 2.27 9 0.99 NA NA NA NA 1.08 2.15 2 0.34 0.0 0.0 2 1.0
Test3.Sm 0.50 2.97 6 0.81 NA NA NA NA 0.0 0.0 1 1.0 0.0 0.0 0 1.0
Table 4: Program RELEASE goodness-of-fit test results of the fully time-dependent Cormack–Jolly–Seber model within a POPAN
parameterisation in the program MARK, of sighting histories of Sousa plumbea in Mossel Bay during the period April 2011 to November 2013
for the super-population and for each year. Parameters for goodness-of-fit testing are designated as follows: variance inflation factor (),
Chi-squared statistic (
2
), degrees of freedom (df) and statistical significance (p-value). NA denotes no data
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James, Bester, Penry, Gennari and Elwen
390
2012 (summer) and April and October 2013 (summer and
winter) compared to other times of the year (Figure 3).
Population links
The catalogue of S. plumbea identified in Mossel Bay was
compared to images taken opportunistically at four locations
over a 7-year period (2006–2013; Table 2). No individ-
uals identified at East London, De Hoop or Gansbaai were
common to any of the other locations, whereas nine (15%)
individuals from 58 used to evaluate movement between
areas were found to be common to both Mossel Bay
and Plettenberg Bay. Four of the nine were observed in
multiple years in Mossel Bay but during only a single year
in Plettenberg Bay, and one individual was seen during
multiple years in both locations (Table 6). Two individuals
were seen during multiple years in Plettenberg Bay and in
only a single year in Mossel Bay. Two individuals were seen
during only a single year in both locations. The only year in
which data were collected at both locations was 2013. Five
identified individuals were determined to be female, based
on close association with a calf on three or more occasions,
with three of these individuals common to Mossel Bay and
Plettenberg Bay.
Discussion
This study presents the most westerly published abundance
estimate for S. plumbea and the first within southern Africa
Individual ID Sex
Plettenberg Bay Mossel Bay
2006 2007 2008 2009 2010 2013 2011 2012 2013
MB_Sp_026/PB_Sp_006 Unknown 0 1 0 0 0 0 1 0 1
MB_Sp_027/PB_Sp_029 Unknown 0 0 0 0 0 1 1 0 1
MB_Sp_034/PB_Sp_024 Unknown 0 0 1 1 0 0 1 0 0
MB_Sp_043/PB_Sp_013 Female 0 1 0 0 0 0 0 1 1
MB_Sp_048/PB_Sp_050 Unknown 0 0 0 1 0 0 0 1 0
MB_Sp_050/PB_Sp_010 Female 0 1 0 0 1 0 0 1 1
MB_Sp_053/PB_Sp_027 Female 0 0 0 0 0 1 0 1 1
MB_Sp_055/PB_Sp_014 Unknown 0 1 0 0 0 1 0 0 1
MB_Sp_059/PB_Sp_054 Unknown 0 0 0 0 0 1 0 0 1
Table 6: Catalogued Sousa plumbea found in both Mossel Bay (MB; 2011–2013) and Plettenberg Bay (PB; 2006–2013, excluding 2011 and
2012). A value of 1 represents a year in which an individual was captured in a surveyed area and 0 when that individual was not seen
Table 5: Open population (POPAN) model outputs for the super-population and for each year, including: number of parameters (N
par
); quasi-
penalised Akaike information criterion (QAICc); difference between the selected candidate model and the top ranked model (QAICc); indication
Sousa plumbea (N
ˆ
); standard
N
total
). The QAICc and Qdev
 values of 1.197 (super-population), 1.039 (2011), 1.235
(2012) and 1.0 (2013). The proportion of marked individuals (
photographs (Q4–Q6, n  value of
0.872, 0.85, 0.80 and 0.99 (over the 3-year period and in 2011, 2012 and 2013, respectively)
Model
Model selection criteria Marked population Total population
N
par
QAICc QAICc Qdev Weight N
ˆ
SE LCL UCL N
total
SE LCL UCL
Super-population
(t)p(.)b(t)N
s
(.) 9 399.1 0.0 68.7 9.8
–1
109 19 73 146 125 48 61 260
(t)p(.)b(.)N
s
(.) 8 407.3 8.2 79.3 1.6
–2
94 11 72 116 108 35 58 200
(.)p(.)b(t)N
s
(.) 8 414.2 15.1 86.2 5.2
–4
111 20 72 150 127 50 60 269
(.)p(.)b(.)N
s
(.) 4 416.2 17.0 97.2 2.0
–4
91 11 70 112 104 33 56 192
2011
(t)p(.)b(.)N
s
(.) 3 85.1 0.0 0.0 9.5
–1
60 15 31 90 71 33 30 168
(.)p(.)b(.)N
s
(.) 3 93.4 8.2 0.0 1.5
–2
72 20 33 110 84 41 34 206
(.)p(.)b(t)N
s
(.) 6 93.4 8.3 0.0 1.5
–2
74 20 35 112 86 41 36 210
(.)p(t)b(.)N
s
(.) 8 94.9 9.8 0.0 7.7
–3
68 24 20 116 79 44 29 219
2012
(.)p(.)b(t)N
s
(.) 6 94.5 0.0 23.3 4.4
–1
27 6 15 38 33 14 15 73
(.)p(.)b(.)N
s
(.) 4 95.2 0.7 30.0 3.1
–1
26 5 15 37 32 13 15 70
(t)p(.)b(t)N
s
(.) 8 97.0 2.5 18.6 1.3
–1
26 6 15 38 32 14 14 71
(t)p(.)b(.)N
s
(.) 6 97.0 2.6 25.8 1.2
–1
26 5 16 36 32 13 15 69
2013
(t)p(.)b(t)N
s
(.) 10 99.1 0.0 0.0 8.2
–1
45 10 27 64 46 21 20 108
(t)p(.)b(.)N
s
(.) 6 103.4 4.3 0.0 9.8
–2
46 9 28 65 47 21 20 108
(t)p(t)b(.)N
s
(.) 11 104.0 4.9 0.0 7.1
–2
38 6 27 50 39 15 19 80
(.)p(.)b(t)N
s
(.) 6 109.6 10.5 0.0 4.3
–3
68 20 30 107 69 37 26 184
Downloaded by [Bridget James] at 23:30 23 November 2015
African Journal of Marine Science 2015, 37(3): 383–394
391
in over 11 years. Here we applied closed and open popula-
tion models to generate within-year abundance estimates
of S. plumbea using Mossel Bay over three consecutive
years, and open population models to determine the size
of the super-population over a 3-year period. Additionally,
we explored individual movement patterns over a 1 000-km
stretch of coastline using photographs collected opportun-
istically. During the study period, 67 individuals were identi-
fied in Mossel Bay, and mark-recapture analysis yielded
an open population estimate of <130 individuals. The
confidence intervals in this study were large as a result of
the low number of resightings of animals. However, even
the upper confidence limit was below the abundances
estimated for other populations on the Cape south coast,
namely Algoa Bay and Plettenberg Bay (see below).
Certain individuals were observed in both Mossel Bay and
Plettenberg Bay (140 km apart), suggesting that abundance
estimates for these populations cannot be treated in
isolation. We discuss below the limitations and implications
of our results and place them within the context of what is
known about S. plumbea biology in southern Africa.
Photo-identification is a widely used research technique
and full rationalisation of assumptions of this approach to
studying dolphins has been discussed in detail elsewhere
(e.g. Wilson et al. 1999; Read et al. 2003; Elwen et al.
2009). Briefly, to assess abundance or survival rates
accurately, both closed and open population mark-recapture
models are reliant on the fulfilment of several key assump-
tions, namely, that marks are unique, do not change
between sampling periods, and are correctly identified,
and that marking does not affect the capture probability
of the individual. Additionally, sufficient time must pass
between sampling periods to allow for complete mixing
of the population, sampling periods should be instant-
aneous, and all animals must have an equal chance of
being captured (Cooch and White 2012). The frequency
of our surveys and the use of multiple marks for individual
recognition reduced the probability of a mismatch occurring
as a result of marks changing. The relatively high number
of animals that were encountered only once, and the lack
of a complete asymptote in the discovery curves for 2012
and 2013, suggest that some animals spend the majority
of their time outside the study area. Although this does not
necessarily violate the assumptions of closed population
models, provided their use of the study area is effectively
random, it reduces the probability of recapturing individuals
and can reduce model accuracy and precision. We included
closed models primarily to improve comparability with other
studies along the South African coastline that have used
these models (Durham 1994; Atkins and Atkins 2002; Keith
et al. 2002; Jobson 2006), and because they allow hetero-
geneity of capture probability to be accounted for analyt-
ically (Pledger 2000). Ultimately, the abundance estimates
obtained using both open and closed models within each
year were very similar, lending confidence to the results and
confirming the low number of animals using Mossel Bay.
Mark-recapture methods have been used to estimate the
abundance of Sousa plumbea in seven previous studies
at four other sites along the southern African coast (see
Table 7). All were similar to the current study in spatial extent
(except that of Durham [1994] that investigated almost the
Study site
Duration of
study
(months)
Number
of
surveys
Number
of
encounters
Group size
(ind.; range
[mean])
Max. individual
distance
travelled
(km)
Catalogue
size
(ind.)
Animals seen
more than once
(ind.)
Distinct
animals
(%)
Closed model
abundance
estimate
(ind. [95% CI])
Open model
abundance
estimates
(ind. [95% CI])
Reference
MapB 24 146 37 2–25 (14.9) NA 52 23 52 NA 105 (31–151) 1
KZN (entire) 18 136 56 1–18 (6.7) 120 96 45 68 165 (134–229) 161 (81–240) 2
RB 18 41 30 1–20 (5.1) 70 45 23 31 NA 38 (19–56) 2
7 73 56 1–20 140 24 (181 KZN) 56 76 NA 74 (60–88) 3
25 125 NA NA NA 92 56 54 244 (217–287) 170 (112–230) 4
AB 36 60 104
§
3–24 (7) 110 70 37 92 NA 466 (447–485) 5, 6
PB 24 87 35 2–20 (mode 5) 32 63 36 77 112 (75–133) 727 7
MossB 32 81 31 1–15 (4.9) 139 67 34 94 46* (38–56) 125 (112–140) 8
§
The high number of encounters made in Algoa Bay compared to other studies can be attributed to differences in survey methods, as the research boat was launched only in response to
shore-based sightings of S. plumbea (Karczmarski et al. 1999).
* Mean closed population size
References: 1 Guissamulo and Cockcroft (2004), 2 Durham (1994), 3 Keith et al. (2002), 4 Atkins and Atkins (2002), 5 Karczmarski (1996), 6 Karczmarski et al. (1999), 7
Jobson (2006), 8 – Current study
Table 7: Summary of study design and mark-recapture results obtained from previous studies on Sousa plumbea in southern Africa: Maputo Bay (MapB,
1
1992 and 1995–1997), KwaZulu-
Natal (KZN,
2
1991–1993), Richards Bay (RB,
3
1998,
4
1998–2000), Algoa Bay (AB,
5,6
1991–1994), and Plettenberg Bay (PB,
7
2002 and 2003) and in the present study in Mossel Bay (MossB,
8
2011–2013). Values not reported are shown as NA
Downloaded by [Bridget James] at 23:30 23 November 2015
James, Bester, Penry, Gennari and Elwen
392
entire KZN coastline) and duration, and applied either open
population models only or a combination of both open and
closed models (Table 7). Slight differences in the methods
used among the studies make direct comparisons of results
difficult, but there are several marked similar ities. For most
studies, estimates of abundance were ~100 individuals
using each study area, although open population models
generated higher estimates for Algoa Bay (465 km to the
east of Mossel Bay; Karczmarski et al. 1999) and Plettenberg
Bay (140 km to the east of Mossel Bay; Jobson 2006) on the
Cape south coast (Table 7). These generally low estimates
are supported by the small number of animals identi-
fied in each location, ranging from 52 ind. in Maputo Bay
(Guissamulo and Cockcroft 2004) to 181 ind. in KZN (Keith et
al. 2002). Low encounter rates in most studies (Table 7), lack
of complete asymptotes in discovery curves where available
(Durham 1994; Karczmarski et al. 1999; Keith et al. 2002;
Jobson 2006), and high proportions of individuals seen only
once, collectively suggest that these studies represent only a
proportion of the range of the population(s) under study, with
many individuals spending at least some time outside of the
areas under study. From a conservation and management
perspective, it is valuable to know to which area or popula-
tion an estimate applies, and whether there is any popula-
tion overlap between estimates from adjacent areas. Hence
it is important to determine individual ranging patterns and
population structure within southern African waters.
The definition of resident or transient individuals in studies
of Sousa plumbea is somewhat arbitrary and typically is
based on the number of times animals are photographed
successfully, rather than a known behavioural distinction,
as observed in some bottlenose dolphin populations (e.g.
Conn et al. 2011). Given that the number of times individ-
uals will be photographed depends heavily on the level of
survey effort and the area searched, it is difficult to compare
these parameters directly between studies. Within South
Africa, most S. plumbea appear to be transient within either
the Thukela Bank region of KZN (Durham 1994; Keith et
al. 2002) or on the Cape south coast, including in Algoa
Bay, Plettenberg Bay and Mossel Bay (Karczmarski et al.
1999; Jobson 2006; this study). The relative proximity of
locations on the Cape south coast suggests there is likely
to be some degree of population overlap between study
areas. However, data on alongshore movements of S.
plumbea in southern Africa is limited. The longest stretch
of southern African coastline that has been surveyed in a
single study on humpback dolphins to date is the 550 km
of the KZN coastline (Durham 1994). Multiple launch sites
along the coast were used to cover the area. The longest
movement by an individual detected during that study was
120 km. However, 59% of individuals (and 80% of identi-
fied mothers) were always sighted within the vicinity of
their first sighting (i.e. in the same ‘search area’), with
maximum recorded alongshore movements of between 17
and 70 km, suggesting high site fidelity within the popula-
tion (Durham 1994). A more recent study supports these
findings, with 181 individuals identified off KZN but only a
single long-distance movement of 150 km detected (from
Durban to Richards Bay) (Keith et al. 2002). On the Cape
south coast, all individuals identified from two surveys of St
Francis Bay were resighted in the adjacent Algoa Bay, some
100 km away; however, only 10% of the identified population
was seen frequently, with females comprising 80% of these
animals (Karczmarski et al. 1999). Of animals identified in
Plettenberg Bay, three individuals were also seen in Buffalo
Bay, approximately 32 km to the west (Jobson 2006).
In the current study, we found matches between Mossel
Bay and Plettenberg Bay (140 km away), the closest site
from which data were available and also the site with the
largest quantity of data. Several of the nine individuals
identified in both bays were identified in multiple years
and they were found to move in both directions. These
nine individuals represent 13% of the animals in the
Mossel Bay catalogue and 20% of the 44 animals identi-
fied opportunistically in Plettenberg Bay, suggesting a
moderate degree of overlap between these two sites and
supporting previous suggestions that humpback dolphins on
the Cape south coast probably form one large population
(Karczmarski 1996). It has been suggested that mother–
calf pairs would have higher site fidelity to an area (Durham
1994; Karczmarski et al. 1999); however, three of the nine
animals seen to undertake these long-distance movements
were females with calves. The movement of individuals
back and forth between multiple locations over a number
of years suggests that both areas are within the home
range of these animals and that this is not an artefact of a
seasonal movement or gradual shift in range over time.
In Mossel Bay, a peak in relative abundance of S. plumbea
was observed in the number of individuals encountered
during the summers (November–April) of 2011–2012 and
2012–2013, although the largest groups were seen in winter
(May–October) of 2011. In Algoa Bay, the population of S.
plumbea exhibited strong seasonal fluctuations with higher
abundance during summer and late winter (Karczmarski et
al. 1999), whereas in Plettenberg Bay, Jobson (2006) found
humpback dolphins were present year-round (Jobson 2006).
The observed seasonality, combined with the resightings
between these study sites, is consistent with the notion of
a single continuous population that exhibits some level of
alongshore seasonal movement, westward from Algoa Bay
at the end of summer/beginning of autumn and eastward
from Mossel Bay towards Algoa Bay during mid-winter, with
Plettenberg Bay being a core-use area.
Previous studies reported higher resightings of female
than male animals, suggesting that high residency to
localised areas was possibly a result of females adjusting
their travelling speed and distances to the capacity of the
calf (Durham 1994; Keith et al. 2002). In our study, only
two of five identified resident females were seen more
frequently when accompanied by a small calf, while at least
three were observed moving between Mossel Bay and
Plettenberg Bay, including a single animal photographed
in Mossel Bay with a calf and then in Plettenberg Bay five
months later (from where no photograph of the calf was
available). These observations suggest that this pattern of
higher female site fidelity may not hold for all study areas.
Conclusion
The abundance estimates produced in this study represent
the most westerly population data available for Sousa
plumbea and indicate that a small number of these dolphins
Downloaded by [Bridget James] at 23:30 23 November 2015
African Journal of Marine Science 2015, 37(3): 383–394
393
use Mossel Bay and the adjacent coast. Although both
closed and open population models were used in this study
to improve comparability to earlier work, the wide-ranging
nature of the animals suggest that open population models
are more appropriate for this species along the South
African coast. Placing our estimated numbers within the
context of the entire Cape south coast is confounded by
the lack of good data on the alongshore range of individ-
uals and on any possible sex- or age-related differences. To
date, almost all studies of S. plumbea in southern African
waters have been conducted in relatively small survey
areas (10s of km long) and, when comparisons have been
made with studies from other locations, they have often
relied on older or limited data. In order to address this gap
in the data and to determine accurately the total popula-
tion size and structure of S. plumbea along the Cape
south coast, we recommend that a wide-scale, multi-site,
mark-recapture study be undertaken. Ideally such a study
should include a genetic component, and pollutants and
other threats should be investigated. Although satellite
telemetry would be a powerful tool, consideration should
be given to ethical issues associated with the use of an
invasive technique on this potentially endangered popula-
tion. If such a wide-scale estimate of the entire Cape south
coast population can be achieved, it would allow for a
thorough regional threat assessment to be conducted, such
as the one undertaken for the critically endangered bottle-
nose dolphin Tursiops truncatus population in Doubtful
Sound, New Zealand (Currey et al. 2009). Until this can
be achieved, the available information suggests that the
S. plumbea population of the Cape south coast is small,
numbering in the hundreds to low thousands at most. Also,
it is largely isolated from populations farther east, making
the population particularly vulnerable to further impacts.
Acknowledgements We thank Oceans Research for the provision
of logistical support by way of volunteers, boats, running costs and
skippers. A special thank you to Oceans Research skippers, Rob
Lewis, Dorien Schröder, Riley Elliott, Dylan Irion, Andre Faul, John
Wiley, Mike Barron, Chris Henderson, Dan Dawson, Jeremy Frimond,
Natalie Graham, Dave van Beuningen and Curtis Young. Thanks
are also due to the following: Monica Betts for providing additional
humpback dolphin photographs from Mossel Bay, taken between
May and November 2013; Renae Logston who helped with photog-
raphy during 2011 and 2012 and allowed us additional boat time
during her CTD surveys; the volunteers that helped in data collec-
tion and the sorting of photographs during 2011, 2012 and 2013;
the Centre for Dolphin Studies and Tracey Meintjies of the ORCA
Foundation in Plettenberg Bay; Dyer Island Conservation Trust in
Gansbaai and Peter Chadwick, African Conservation Photography,
for providing additional photographs of humpback dolphins. Tess
Gridley, Dr Pedro Fruet and an anonymous reviewer provided useful
and valuable comments on an earlier draft of this manuscript. This
research was conducted under a series of permits issued to the
Mammal Research Institute, Department of Zoology and Entomology,
University of Pretoria, by the Department of Environmental Affairs.
The methods used were approved by the Animal Ethics Committee of
the University of Pretoria (ec061-09, ec019-12).
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Manuscript received August 2014, revised February 2015, accepted June 2015
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November 2017 · Aquatic Conservation Marine and Freshwater Ecosystems · Impact Factor: 2.14
    The Indian Ocean humpback dolphin was recently uplisted to 'Endangered' in the recent South African National Red List assessment. Abundance estimates are available from a number of localized study sites, but knowledge of movement patterns and population linkage between these sites is poor. A national research collaboration, the SouSA project, was established in 2016 to address this key... [Show full abstract]
    Article
    April 2012 · PLoS ONE · Impact Factor: 3.23
      Determining the residency of an aquatic species is important but challenging and it remains unclear what is the best sampling methodology. Photo-identification has been used extensively to estimate patterns of animals' residency and is arguably the most common approach, but it may not be the most effective approach in marine environments. To examine this, in 2005, we deployed acoustic... [Show full abstract]
      Article
      January 2009 · Marine Mammal Science · Impact Factor: 1.94
        Heaviside's dolphins, Cephalorhynchus heavisidii, are endemic to southwestern Africa, where they are exposed to unknown levels of anthropogenic threats, including inshore set netting. Using photo-ID data collected over 3 yr on the west coast of South Africa, we calculated Chapman's-modified Petersen estimates of the number of distinctive individuals at three spatial scales. Sample sizes were... [Show full abstract]
        Article
        January 2010 · Marine Mammal Science · Impact Factor: 1.94
          This study estimates the population size of Indo-Pacific bottlenose dolphins (Tursiops aduncus) in the Algoa Bay region on the Eastern Cape coast of South Africa. Mark-recapture analyses were performed on photo-identification data collected on 54 occasions during a 3-yr-study period. Using a photographic data set of over 10,000 ID-images, 1,569 individuals were identified, 131 of which were... [Show full abstract]
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