ArticlePDF Available

Large-scale tropical movements and diving behavior of white sharks Carcharodon carcharias tagged off New Zealand

Authors:
  • El Colegio de la Frontera Sur – Unidad Chetumal
  • Auckland War Memorial Museum

Abstract and Figures

Recent advances in our understanding of the spatial behavior of white sharks have been based on only 3 geographical areas: the waters off Australia, southern Africa, and the northeast Pacific Ocean. Here we report results from the first study in New Zealand waters using satellite tags to study sharks. We attached pop-up archival tags to 4 white sharks Carcharodon carcharias at the Chatham Islands, New Zealand, during April 2005. One tag released prematurely, but 3 others showed long-distance northward movements of 1000 to 3000 km across the open ocean, with 2 sharks moving to the tropical islands of New Caledonia and Vanuatu. Our results are similar to recent findings elsewhere of fast oceanic travel and well oriented navigation. Circumstantial information suggests that some of these movements could be part of a regular foraging migration where white sharks visit humpback whale wintering grounds to feed on carcasses and prey on newborn calves. Before embarking on large-scale movements, all sharks remained over the continental shelf near the Chatham Islands for 2.6 to 5.0 mo, rarely swimming deeper than 100 m. In contrast, during oceanic large-scale movements, they spent most of their time in the top 1 m of water, showing periodic dives to depths over 900 m. The diving behavior in combination with the large-scale movements from temperate to tropical waters results in the sharks experiencing a very wide range of water temperatures.
Content may be subject to copyright.
AQUATIC BIOLOGY
Aquat Biol
Vol. 8: 115–123, 2010
doi: 10.3354/ab00217 Published online January 12
INTRODUCTION
The white shark Carcharodon carcharias (also known
as the great white shark) is a globally distributed
apex predator, with reported centers of abundance in
temperate and sub-tropical waters (Compagno 2001).
Negative abundance trends and rapid population de-
clines reported in several range states have high-
lighted the need for improved knowledge of this
species (Malcolm et al. 2001, Soldo & Jardas 2002,
Anonymous 2004), and have led to its protection in a
number of countries as well as its inclusion on Appen-
dix II of the Convention for International Trade in
Endangered Species of Animals and Plants (CITES)
and Appendices I and II of the Convention on the Con-
servation of Migratory Species of Wild Animals (CMS).
As recently as 2001, the white shark was considered
to be chiefly an inhabitant of continental and insular
shelves, and its migratory habits were virtually
unknown (Compagno 2001). However, recent research
through satellite-linked tags has demonstrated that
besides spending extended periods of time in pre-
ferred coastal areas, white sharks commonly venture
thousands of kilometers into the open ocean (Boustany
et al. 2002) and undertake regular long-distance
coastal migrations, often returning to sites to which
they show a high degree of fidelity (Bonfil et al. 2005,
Bruce et al. 2006, Weng et al. 2007a,b). One white
© Inter-Research 2010 · www.int-res.com*Email: ramon.bonfil@gmail.com
Deceased
Large-scale tropical movements and diving
behavior of white sharks Carcharodon carcharias
tagged off New Zealand
R. Bonfil1,*, M. P. Francis2, C. Duffy3, M. J. Manning2,†, S. O’Brien4
12233 Caton Ave. 5C, Brooklyn, New York 11226, USA
2National Institute of Water and Atmospheric Research, 301 Evans Bay Parade, Greta Point, Wellington 6021, New Zealand
3Department of Conservation, Private Bag 68908, Newton, Auckland 1145, New Zealand
4School of Aquatic & Fishery Sciences, University of Washington, 1122 NE Boat St., Seattle, Washington 98105, USA
ABSTRACT: Recent advances in our understanding of the spatial behavior of white sharks have been
based on only 3 geographical areas: the waters off Australia, southern Africa, and the northeast
Pacific Ocean. Here we report results from the first study in New Zealand waters using satellite tags
to study sharks. We attached pop-up archival tags to 4 white sharks Carcharodon carcharias at the
Chatham Islands, New Zealand, during April 2005. One tag released prematurely, but 3 others
showed long-distance northward movements of 1000 to 3000 km across the open ocean, with 2 sharks
moving to the tropical islands of New Caledonia and Vanuatu. Our results are similar to recent find-
ings elsewhere of fast oceanic travel and well oriented navigation. Circumstantial information sug-
gests that some of these movements could be part of a regular foraging migration where white sharks
visit humpback whale wintering grounds to feed on carcasses and prey on newborn calves. Before
embarking on large-scale movements, all sharks remained over the continental shelf near the
Chatham Islands for 2.6 to 5.0 mo, rarely swimming deeper than 100 m. In contrast, during oceanic
large-scale movements, they spent most of their time in the top 1 m of water, showing periodic dives
to depths over 900 m. The diving behavior in combination with the large-scale movements from tem-
perate to tropical waters results in the sharks experiencing a very wide range of water temperatures.
KEY WORDS: Great white shark .Archival satellite tags .Southwest Pacific Ocean
Resale or republication not permitted without written consent of the publisher
O
PEN
PEN
A
CCESS
CCESS
Aquat Biol 8: 115– 123, 2010
shark made an impressive and fast transoceanic return
migration, covering more than 22 000 km in less than
9 mo (Bonfil et al. 2005). White sharks also display dif-
ferent diving behaviors during oceanic versus shelf
residence, and Bonfil et al. (2005) and Weng et al.
(2007a) speculated that celestial clues are used during
oceanic navigation.
White sharks are common in New Zealand waters
and were recently protected within its Territorial Sea
and Exclusive Economic Zone, but in this part of their
range, there has been little research on their biology,
including movements. Here we present data on the
meso- and macro-scale movements and diving behav-
ior of 3 white sharks tagged with archival satellite tags
at the Chatham Islands, New Zealand.
MATERIALS AND METHODS
Satellite tagging. Four white sharks (3 females, 1
male) were tagged with pop-up archival transmitting
tags (PAT4 tags; Wildlife Computers) during April 2005
at Star Keys, Chatham Islands, New Zealand (175°
59.16’ W, 44° 13.40’S; Table 1). All sharks were tagged
free-swimming, following the procedure described in
Bonfil et al. (2005). Tagged sharks were sexed visually
from diving cages or from the surface as they passed
close to the boat. Shark size was estimated visually by
at least 2 experienced observers and ranged between
ca. 350 and 450 cm in total length (TL; Table 1). Tags
were deployed for 3 to 6 mo (Table 1) and programmed
to record depth, temperature, and light measurements
at 60 s intervals. Limits for depth bins are shown in
Fig. 4; upper limits for temperature bins were 4, 6, 8,
10, 12, 14, 16, 18, 20, 23, 26, and 60°C. Archival data
were transmitted to Argos satellites in 6 h bins (starting
at 00:00, 06:00, 12:00, and 18:00 h local time).
Data analysis. Daily shark positions were estimated
from ambient light-level data collected by PAT4 tags
using the geolocation algorithms implemented in
software available from www.wildlifecomputers.com
(WC-AMP 1.01.009, WC-GPE 1.01.0005). To reduce
the inherent uncertainty of these estimates (Musyl et
al. 2001, Itoh et al. 2003, Wilson et al. 2007), revised
‘most-probable’ daily positions were estimated by
Kalman filter analysis. The model assumed was the
Nielsen et al. (2006) extension of the model of Sibert et
al. (2003) incorporating sea-surface temperature (SST);
the ‘solstice’ error model was assumed in all fits.
The number of data points fitted to each track is
listed in Table 2. Days for which PAT-measured
SST data were implausible (observed SST above 35°C)
were omitted from the analysis. The deployment and
pop-up positions (Table 1) were assumed by the
Kalman filter fitting routine to be known without error.
Longitude and SST bias were not estimated, and lati-
tude bias was estimated in all fits. Composite SST field
data on a 1° longitude ×1° latitude grid for the dates
and area of interest and averaged over consecutive
8 d periods were downloaded from the online NMFS
atlas deposited at the University of Hawaii and used
in the model fits as described by Nielsen et al. (2006).
Most-probable position estimates and surrounding
confidence regions (within 2 SE) were extracted from
the fitted model object for each track.
Approximate departure dates from the Chatham
Islands were estimated by simultaneous examination
of temporal changes in longitude, depth, and tempera-
ture. Missing data prevented exact determination of
the departure dates, but errors were probably minimal
(~± 2 d). Oceanic travel swimming speeds were esti-
mated based on great circle distances traveled from
the Chatham Islands to the pop-up points and time
spent traveling.
For days with no PAT4 depth-temperature (PDT)
profile data in the transmitted data summaries, we con-
servatively estimated these values from the 6 h bin
data where they existed: minimum depths and temper-
116
Table 1. Carcharodon carcharias. Details of tag deployments on white sharks at the Star Keys, Chatham Islands, New Zealand. Speed
estimates are for oceanic traveling, and are not based on the entire deployment time period. Dates are in Universal Time. F: female;
M: male; Est. TL: estimated total length; n/a: not available
Tag no. Sex Est. TL (m) Tagging date Pop-up date Pop-up Argos pop-up Distance Deployment (d) Speed
(2005) (2005) location location class traveled (km) Programmed Actual (km h–1)
57033 F 4.2 to 4.5 7 Apr 5 Jul 172° 02.1’W 1 1036 89 89 5.4
35° 25.4’ S
57034 F 3.5 9 Apr 14 Apr 176°17.4’ W n/a n/a 120 5 n/a
43° 45.6’ S
57035 F 4.0 9 Apr 5 Sep 167° 09.3’E 1 2847 149 149 3.7
22° 45.3’ S
57036 M 3.2 to 3.5 8 Apr 5 Oct 169° 38.7’E 2 2884 180 181 4.3
21° 11.2’ S
Bonfil et al.: Tropical movements of NZ white sharks
atures were estimated as the upper (deeper, warmer)
bound of the lowest bin in each 24 h period, and maxi-
mum depths and temperatures were estimated as the
lower (shallower, cooler) bound of the highest bin in
each 24 h period. This procedure allowed approximate
temporal interpolation between daily PDT estimates
but at the expense of underestimating the maxima and
overestimating the minima.
RESULTS
We successfully tracked 3 sharks for periods of 89,
149, and 181 d (Table 1). Summary data transmitted for
each tag via the Argos system comprised time-at-depth
data, time-at-temperature data, depth-temperature pro-
file data, and geolocation estimates of longitude and
latitude based on light readings.
Geographic movements
A 3.8 to 4.0 m TL female white shark (Tag 57034,
programmed for a 4 mo deployment) prematurely shed
its tag 5 d after tagging. This tag reported to the Argos
system from ~70 km north of the tagging site, but the
tag may have drifted from elsewhere before transmit-
ting (it was programmed to detach and transmit after
168 h at a constant depth).
A second female white shark, 4.2 to 4.5 m TL (Tag
57033, a 3 mo deployment) traveled to the Louisville
Seamount Chain, 1036 km northeast of the Chatham
Islands (Table 1). The pop-up region has no shallow
water: most of the sea floor is at depths >4000 m,
although several seamounts within 55 to 90 km rise to
depths of 2400 to 3700 m. A third female white shark,
ca. 4.0 m TL (Tag 57035, a 5 mo deployment) traveled
to the southern shelf of New Caledonia, 2847 km
northwest of the Chatham Islands. The fourth shark, a
3.2 to 3.5 m TL male (Tag 57036, a 6 mo deployment)
moved to southern Vanuatu, having traveled 2884 km
from the tagging site (Fig. 1).
The Kalman filter-corrected tracks suggest that the
sharks traveled directionally to pop-up locations (Fig. 2).
Numerical results of the Kalman model fits are pro-
vided in Table 2. Sharks 57035 and 57036 visited the
northeastern coast of New Zealand before continuing
on a direct route to the tropical waters of New Caledo-
nia and Vanuatu. The estimated routes and swimming
speeds suggest that these sharks did not stop in coastal
waters of mainland New Zealand during their large-
scale movements.Estimated speeds during ocean travel-
ing were 89 to 130 km d–1 (3.7 to 5.4 km h–1; Table 1).
The 3 white sharks we tracked remained in the vicin-
ity of the Chatham Islands for 2.6 to 5.0 mo before
embarking on oceanic large-scale movements. They
left the Chatham Islands in late June (57033), early
July (57035), and early September (57036; Fig. 3).
Sharks 57035 and 57036 arrived in tropical waters in
early August and early October, respectively.
Vertical distribution
While at the Chatham Islands, all 3 sharks remained
in shallow water, rarely venturing below 75 m (Figs. 3
& 4). Most time (mean of 3 sharks = 81.8%) was spent
between 2 m and 50 m depth. The modal depth range
was slightly greater for shark 57035 (26 to 50 m) than
for the other 2 sharks (11 to 25 m).
During their ocean traveling phase, the vertical dis-
tribution of the sharks changed dramatically. All 3
sharks spent most time (mean 61.6%) at the surface
(0 to 1 m depth band) but made periodic deep dives.
Sharks 57033 and 57036 both dove to at least 901 m
(maximum PDT depths for both sharks were shallower
than the shallow limit of the deepest depth bin occu-
pied), and shark 57035 dove to at least 748 m (Fig. 3).
The vertical distribution pattern was bimodal, but this
effect is exaggerated by the unequal depth-bin sizes.
117
Table 2. Carcharodon carcharias. Numerical results of Kalman filter model fits. N: number of observations fitted to in each track;
LL: model log-likelihood; p: number of model free parameters; Est.: model parameter estimate; SD: model parameter standard de-
viation; u, v, and D: movement parameters from the Kalman transition equation; blong, blat, bSST, σlong, σlat, and σSST: bias and SD
parameters; a0and b0: solstice error model parameters from the measurement equation. See Nielsen et al. (2006) for a description
of model parameters and their derivation
Model parameters
Tag N LL puvDb
long blat bSST σlong σlat σSST a0b0
57033 59 –274.998 9 Est. 3.78 10.40 429.36 0 0.18 0 0.18 1.70 0.24 0.03 25.56
SD 0.83 0.97 82.04 0.45 0.17 0.30 0.03 0.02 5.11
57035 90 – 446.223 9 Est. 5.10 8.20 556.83 0 0.01 0 0.45 1.63 0.25 0.05 26.89
SD 1.15 0.86 74.72 0.36 0.08 0.27 0.03 0.02 4.27
57036 79 – 455.196 9 Est. 4.69 8.37 764.04 0 5.82 0 0.28 2.81 0.35 0.01 9.68
SD 1.08 1.81 91.34 0.52 0.07 0.28 0.02 0.01 3.03
Aquat Biol 8: 115– 123, 2010
After grouping the depth bins into equal 200 m inter-
vals, the mean percentages of time spent by the 3
sharks in each depth range were 76.7% at 0 to 200 m,
4.6% at 201 to 400 m, 8.3 % at 401 to 600 m, 9.2 % at
601 to 800 m, and 1.1% at 801 to 1000 m. The bimodal
pattern persisted, and had a minimum at 201 to 400 m,
indicating that the sharks traversed these depths rela-
tively quickly. The percentage of time spent by indi-
vidual sharks deeper than 400 m was 11 to 30% (mean
18.7%) and deeper than 600 m was 6 to 18 % (mean
10.4%; Fig. 4).
It was not possible to determine the frequency or
duration of deep dives because of the coarse temporal
resolution of the data (6 h time bins) and frequent gaps
in the data series because of incomplete transmission.
However, Shark 57033 made at least 2 dives deeper
than 800 m, Shark 57035 made at least 5 dives deeper
than 600 m, and Shark 57036 made at least 4 dives
deeper than 600 m (Fig. 3). Shark 57035 displayed a
third vertical distribution pattern in New Caledonian
waters, intermediate between those from the Chatham
Islands and while ocean traveling (Fig. 3). She spent
most of her time (74.0%) shallower than 100 m, but
with large amounts of time between 101 and 200 m
(12.6%) and 201 and 400 m (12.1 %). Only 1.2 % of her
time was spent deeper than 400 m.
Temperature ranges
While at the Chatham Islands, all 3 sharks experi-
enced similar, steadily declining water temperatures
as winter approached (Fig. 3). Maximum and minimum
temperatures differed little, consistent with the sharks
inhabiting the shallow mixed layer. Water temperature
was near 15°C when tags were deployed in April and
declined to about 12°C in late June to early July when
Sharks 57033 and 57035 departed, and about 11°C in
early September when Shark 57036 departed.
After departure from the Chatham Islands, maxi-
mum temperatures increased rapidly as the sharks
headed northwards into subtropical and tropical
118
Fig. 1. Southwest Pacific Ocean showing the tagging site (star) and other locations mentioned in the text. 1: Vanuatu; 2: New
Caledonia; 3: Louisville Seamount Chain; 4: Chatham Islands; 5: Campbell Island; A: Chatham Island; B: Star Keys; 100 m bathy-
metric contours are overlaid on the inset
Bonfil et al.: Tropical movements of NZ white sharks
waters. Shark 57035 reached a plateau of about 22°C,
and a maximum of 23.8°C in New Caledonian waters,
and Shark 57036 reached 23.4°C at the end of his
track in southern Vanuatu. During the ocean traveling
phase, minimum temperatures experienced by the
sharks fluctuated markedly in concert with their div-
ing behavior (Fig. 3). All sharks experienced tem-
peratures less than 8°C, with Sharks 57036 and 57033
recording the lowest values at 6.6°C and 6.4°C, respec-
tively.
As a result of their movement from temperate
to tropical latitudes and deep diving behavior, our
sharks experienced a wide range of temperatures (6.4
to 23.8°C). Temperature variations of 10 to 12°C were
often experienced in a single day by Sharks 57035
and 57036 (Fig. 3).
DISCUSSION
Geographic movements
The 3 white sharks successfully tracked
during this study appear to have remained at
the Chatham Islands for several months after
tagging and then made rapid, directed move-
ments to subtropical and tropical locations.
This is consistent with studies conducted
elsewhere describing white shark behaviors
ranging from site fidelity to trans-oceanic
migrations (Strong et al. 1992, Goldman &
Anderson 1999, Boustany et al. 2002, Bonfil
et al. 2005, Bruce et al. 2006, Weng et al.
2007a,b, Domeier & Nasby-Lucas 2008).
While our data do not provide unequivocal
evidence for residency because light-based
geolocation estimates are subject to error
particularly for latitude (Musyl et al. 2001,
Itoh et al. 2003), the most-probable position
estimates for the 3 sharks have relatively
small confidence regions and are tightly
grouped around the islands (Fig. 2). Addition-
ally, the steady decline in tag-recorded tem-
peratures as winter approached, and the
relatively shallow depths recorded during
this period are also consistent with the sharks
remaining in the vicinity of the Chatham
Islands for 2.6 to 5.0 mo after tagging.
The Chatham Islands sharks all made ex-
tensive oceanic movements, whereas most
other white sharks tagged in the Southern
Hemisphere have largely remained within
shelf waters when moving from temperate to
lower latitudes (Bonfil et al. 2005, Bruce et al.
2006). The most notable exceptions to this are
the trans-oceanic return migration of an im-
mature female white shark between South
Africa and Western Australia (Bonfil et al. 2005) and the
movement of a subadult female white shark between
South Australia and the northwest coast of New Zealand
(Bruce et al. 2006). The important difference between
these studies and ours is that in both southern Africa and
Australia, the continental shelf is continuous between
tropical and temperate regions, but the Chatham Islands
are in a temperate region where the continental shelf is
separated from subtropical and tropical shelves by ex-
tensions of the continental slope and submarine ridges.
Seasonal migration to subtropical and tropical latitudes
is a common white shark behavior elsewhere (Boustany
et al. 2002, Bonfil et al. 2005, Bruce et al. 2006, Weng et
al. 2007a, Domeier & Nasby-Lucas 2008), so it is not sur-
prising that white sharks inhabiting New Zealand waters
make long-distance, northward, oceanic movements.
119
Fig. 2. Carcharodon carcharias. ‘Most-probable’ tracks for tagged white
sharks; confidence regions (2 SE) surrounding each point are shown (orange)
Aquat Biol 8: 115– 123, 2010
Swimming speed
Chatham Island white sharks maintained high swim-
ming speeds (3.7 to 5.4 km h–1) during ocean crossings.
Previous estimates of white shark swimming speeds
maintained for several hours or longer are mainly
within the range of 2.9 to 4.5 km h–1 (Carey et al. 1982,
Strong et al. 1992, Boustany et al. 2002, Klimley et al.
120
Fig. 3. Carcharodon carcharias. Depth ranges traversed by 3 tagged white sharks and ambient water temperatures recorded by
the tags. Data represent minimum and maximum values recorded within a 6 h time interval. Vertical dashed lines indicate the
approximate date of departure of each shark from the Chatham Islands. The vertical dotted line in B indicates the approximate
time of arrival of shark 57035 at New Caledonia. Missing data mean that depth and temperature plots do not always correspond
with each other
Bonfil et al.: Tropical movements of NZ white sharks
2002, Bruce et al. 2006). However, a speed of 4.7 km
h–1was recorded during an ocean transit of ca.11100 km
in 99 d (Bonfil et al. 2005), and a maximum speed of
5.0 km h–1 was recorded for a shark tracked in the
northeast Pacific (Weng et al. 2007b). Fur-
thermore, Domeier & Nasby-Lucas (2008)
recorded a maximum speed of 8.0 km h–1
over a 24 h period for a white shark in the
northeast Pacific. Thus, white sharks can
make extended migrations at sustained
speeds of about 5 km h–1, or 120 km d–1. In
an analysis of 4 satellite-tracked Aus-
tralian sharks (1.8 to 3.6 m TL), Bruce et
al. (2006) found that swimming speed was
independent of shark length. In compari-
son, salmon sharks Lamna ditropis also
swim at relatively high speeds during
oceanic travel; Weng et al. (2008) reported
maximum swimming speeds of 4.29 km
h–1 for salmon sharks in the North Pacific.
Motivation for large-scale movements
Although the motivation for white shark
migrations is unknown, archival satellite
tag records from the northeast Pacific
suggest they may be related to foraging
(Weng et al. 2007a, Domeier & Nasby-
Lucas 2008). However, foraging chances
are likely to be higher in the areas to
which our white sharks are traveling from
New Zealand than in the vast oceanic
region to where northeast Pacific white
sharks are traveling. In our case, the tag
release points and pop-up dates coin-
cide with seasonal aggregations of large
whales, particularly humpback whales
Megaptera novaeangliae in tropical areas
(Gaskin 1976, Garrigue & Gill 1994,
Richards 2002, Garrigue & Russell 2004).
Data collected by Clua & Séret (in
press) indicate that white sharks occur
sporadically but consistently in New
Caledonian waters. They reported more
than 20 occurrences in the last 30 yr.
White sharks are known to scavenge on
whale carcasses (Carey et al. 1982, Long
& Jones 1996, Dudley et al. 2000) and
have also been observed to attack dis-
tressed juvenile southern right whales
Eubalaena australis (S. Burnell pers.
comm.). Most white shark records from
the Hawaiian Islands coincided with the
humpback whale calving season (Novem-
ber to May; Taylor 1985, Boustany et al. 2002, Weng et
al. 2007a, Domeier & Nasby-Lucas 2008), and similar
patterns are evident in Australia (Paterson & Paterson
1989, Bruce et al. 2006) and New Caledonia (Garrigue
121
Fig. 4. Carcharodon carcharias. Time spent by 3 white sharks at different
depths while at the Chatham Islands, ocean traveling, and (for Shark 57035
only) New Caledonia. N: sample sizes (number of days with data records) for
Chatham Islands, ocean traveling, and New Caledonia
Aquat Biol 8: 115– 123, 2010
& Gill 1994, Clua & Séret in press). The correlation of
white shark movements with those of large cetaceans
in different parts of the world suggests that white
sharks might travel to areas frequented by whales to
exploit windfall feeding opportunities.
More research, including further satellite tagging
and the development of techniques to remotely record
feeding events of sharks, needs to be carried out
before we can determine whether our preliminary
results of white shark large-scale movements are
indeed aimed at feeding on whales, whether they
return to the Chatham Islands after these large-scale
movements to the tropics, and whether such patterns
of spatial behavior are indeed seasonal, predictable,
and constitute part of a migration.
Vertical behavior
The 3 white sharks we tracked displayed a unimodal
depth distribution with a preference for depths of 2 to
50 m while at the Chatham Islands. They rarely dove
deeper than 75 m, although depths exceeding 100 m
exist within 9 km of the Star Keys tagging site. Prefer-
ences for depths shallower than 50 m have also been
displayed by white sharks near pinniped colonies else-
where (Strong et al. 1992, Goldman & Anderson 1999,
Boustany et al. 2002, Bruce et al. 2006, Hammerschlag
et al. 2006, Weng et al. 2007b).
This behavior pattern changed abruptly after the
sharks left the Chatham Islands. During ocean travel-
ling, the Chatham Islands sharks spent most of their
time at the surface (mean 62% at 0 to 1 m depth),
punctuated by dives below 600 m depth. The bimodal
depth distribution exhibited by the Chatham Islands
sharks during oceanic travel (Fig. 4) is essentially the
same as that shown by white sharks during oceanic
travel in the northeast Pacific and Indian Oceans
(Boustany et al. 2002, Bonfil et al. 2005, Weng et al.
2007a, Domeier & Nasby-Lucas 2008). These results,
and the regular receipt of satellite fixes from dorsal fin
tags that transmit when the aerial breaks the sea sur-
face (e.g. Bruce et al. 2006), indicate that white sharks
moving in oceanic waters travel mainly at the surface.
Diving to depths greater than 500 m is also a feature in
all of these studies, suggesting that surface migration
interspersed with deep diving is a routine behavioral
pattern for white sharks during ocean travel. Oscilla-
tory swimming behavior is common in large pelagic
fishes, including sharks, and may serve a variety of
functions in addition to foraging. These include ther-
moregulation (Carey & Scharold 1990), energy conser-
vation (Weihs 1973), and navigation using geomag-
netic and/or celestial cues (Klimley et al. 2002, Bonfil
et al. 2005).
Further research is required to understand the func-
tion of bimodal depth oceanic swimming behavior and
the mechanisms used by white sharks to navigate during
oceanic travel, and to determine whether white sharks
that leave New Zealand make return large-scale move-
ments such as those reported elsewhere (Bonfil et
al. 2005, Weng et al. 2007a). Such research could also
help elucidate population connectivity between the
Chatham Islands, mainland New Zealand, tropical is-
lands in the region, and Australia. The limited amount of
existing information on white shark movements in this
region suggests at least some movement between Aus-
tralia and the main islands of New Zealand (Pardini et al.
2001, Bruce et al. 2006). Despite the sparse and infre-
quent records of white sharks from the tropical islands of
the southwest Pacific, our data suggest that white sharks
may regularly travel there from New Zealand, possibly
drawn to humpback whale wintering and calving
grounds.
Acknowledgements. We thank T. and S. Gregory-Hunt, G.
King, and K. Scollay for their invaluable assistance in finding
and tagging of sharks; and C. Garrigue (Opération Cétacés,
Nouméa) for providing information on humpback whale
distribution and migration around New Caledonia and the
tropical South Pacific. The Wildlife Conservation Society, The
Roe Foundation, the New Zealand Foundation for Research
Science and Technology, and the New Zealand Department
of Conservation provided financial support for this project.
LITERATURE CITED
Anonymous (2004) Inclusion of Carcharodon carcharias
(white shark) on CITES Appendix II, including an annota-
tion that states that a zero annual export quota is estab-
lished for this species. Consideration of Proposals for
Amendment of Appendices I and II. Convention for Inter-
national Trade on Endangered Species of Flora and
Fauna, 13th Conference of the Parties, Bangkok, Thailand,
October 2004. Available at: www.cites.org/eng/cop/13/
raw_props.shtml
Bonfil R, Meÿer M, Scholl MC, Johnson R and others (2005)
Transoceanic migration, spatial dynamics and population
linkages of white sharks. Science 310:100– 103
Boustany AM, Davis SF, Pyle P, Anderson SD, Le Boeuf BJ,
Block BA (2002) Expanded niche for white sharks. Nature
415:35– 36
Bruce BD, Stevens JD, Malcolm H (2006) Movements and
swimming behavior of white sharks (Carcharodon car-
charias) in Australian waters. Mar Biol 150:161–172
Carey FG, Scharold JV (1990) Movements of blue sharks
(Prionace glauca) in depth and course. Mar Biol 106:
329– 342
Carey FG, Kanwisher JW, Brazier O, Gabrielson G, Casey JG,
Pratt HL Jr (1982) Temperature and activities of a white
shark, Carcharodon carcharias. Copeia 1982:254 260
Clua E, Séret B (in press) Unprovoked fatal shark attack in
Lifou island (Loyalty Islands, New Caledonia, South
Pacific) by a great white shark, Carcharodon carcharias.
Am J Forensic Med Pathol
Compagno LJV (2001) Sharks of the world. An illustrated and
122
Bonfil et al.: Tropical movements of NZ white sharks
annotated catalogue of shark species known to date. Vol.
2. Bullhead, mackerel and carpet sharks (Heterodontif-
ormes, Lamniformes and Orectolobiformes). FAO Species
Catalogue for Fishery Purposes 1. FAO, Rome
Domeier ML, Nasby-Lucas N (2008) Migration patterns of
white sharks Carcharodon carcharias tagged at Guada-
lupe Island, Mexico, and identification of an eastern
Pacific shared offshore foraging area. Mar Ecol Prog Ser
370:221–237
Dudley SFJ, Anderson-Reade MD, Thompson GS, McMullen
PB (2000) Concurrent scavenging off a whale carcass by
great white sharks, Carcharodon carcharias, and tiger
sharks, Galeocerdo cuvier. Fish Bull 98:646– 649
Garrigue C, Gill PC (1994) Observations of humpback whales
Megaptera novaeangliae in new Caledonian waters dur-
ing 1991–1993. Biol Conserv 70:211– 218
Garrigue C, Russell K (2004) Vanuatu. In: Rep 5th Annu Meet
South Pac Whale Res Consortium, 2–6 April 2004, Byron
Bay, NSW, Australia: regional updates. For consideration
by The Scientific Committee of The International Whaling
Commission, Sorrento. Sc/55/Sh7. Available at: www.
whaleresearch.org/update_006.htm
Gaskin DE (1976) The evolution, zoogeography and ecology
of Cetacea. Oceanogr Mar Biol Annu Rev 14:247– 346
Goldman KJ, Anderson SD (1999) Space utilization and swim-
ming depth of white sharks, Carcharodon carcharias, at
the South Farallon Islands, central California. Environ Biol
Fishes 56:351– 364
Hammerschlag N, Martin RA, Fallows C (2006) Effects of
environmental conditions on predator prey interactions
between white sharks (Carcharodon carcharias) and Cape
fur seals (Arctocephalus pusillus pusillus) at Seal Island,
South Africa. Environ Biol Fishes 76:341– 350
Itoh T, Tsuji T, Nitta A (2003) Migration patterns of young
Pacific bluefin tuna (Thunnus orientalis) determined with
archival tags. Fish Bull 101:514–534
Klimley AP, Beavers SC, Curtis TH, Jorgensen SJ (2002)
Movements and swimming behavior of three species of
sharks in La Jolla Canyon, California. Environ Biol Fishes
63:117–135
Long DL, Jones RE (1996) White shark predation and scav-
enging on cetaceans in the eastern North Pacific Ocean.
In: Klimley AP, Ainley DG (eds) Great white sharks. The
biology of Carcharodon carcharias. Academic Press, San
Diego, CA, p 293– 307
Malcolm H, Bruce BD, Stevens JD (2001) A review of the biol-
ogy and status of white sharks in Australian waters. Report
to Environment Australia, Marine Species Protection Pro-
gram, CSIRO Marine Research, Hobart
Musyl M, Brill RW, Curran DS, Gunn JS and others (2001)
Ability of electronic archival tags to provide estimates of
geographical position based on light intensity. In: Sibert
JR, Nielsen JL (eds) Electronic tagging and tracking in
marine fisheries. Kluwer Academic Publishers, Dordrecht,
p 343– 368
Nielsen A, Bigelow KA, Musyl MK, Sibert JR (2006) Im-
proving light-based geolocation by including sea surface
temperature. Fish Oceanogr 15:314–325
Pardini AT, Jones CS, Noble LR, Krieser B and others (2001)
Sex-biased dispersal of great white sharks. Nature 412:
139– 140
Paterson R, Paterson P (1989) The status of the recovering
stock of humpback whales Megaptera novaeangliae in
east Australian waters. Biol Conserv 47:33–48
Richards R (2002) Southern right whales: a reassessment of
their former distribution and migration routes in New
Zealand waters, including on the Kermadec Grounds. J R
Soc N Z 32:355– 377
Sibert JR, Muysl MK, Brill RW (2003) Horizontal movements
of bigeye tuna (Thunnus obesus) near Hawaii determined
by Kalman filter analysis of archival tagging data. Fish
Oceanogr 12:141–151
Soldo A, Jardas I (2002) Occurrence of great white shark, Car-
charodon carcharias (Linnaeus, 1758) and basking shark,
Cetorhinus maximus (Gunnerus 1765) in the Eastern
Adriatic and their protection. Period Biol 104:195–201
Strong WR, Murphy RC, Bruce BD, Nelson DR (1992) Move-
ments and associated observations of bait-attracted white
sharks, Carcharodon carcharias: a preliminary report.
Aust J Mar Freshw Res 43:13–20
Taylor L (1985) White sharks in Hawaii: historical and con-
temporary records. Mem South Calif Acad Sci 9:41 48
Weihs D (1973) Mechanically efficient swimming techniques
for fish with negative buoyancy. J Mar Res 31:194–209
Weng KC, Boustany AM, Pyle P, Anderson SD, Brown A,
Block BA (2007a) Migration and habitat of white sharks
(Carcharodon carcharias) in the eastern Pacific Ocean.
Mar Biol 152:877– 894
Weng KC, O’Sullivan JB, Lowe CG, Winkler CE, Dewar H,
Block BA (2007b) Movements, behavior and habitat
preferences of juvenile white sharks in the eastern Pacific
as revealed by electronic tags. Mar Ecol Prog Ser 338:
211–224
Weng KC, Foley DG, Ganong JE, Perle C, Shillinger GL,
Block B (2008) Migration of an upper trophic level preda-
tor, the salmon shark Lamna ditropis, between distant
ecoregions. Mar Ecol Prog Ser 372:253 –264
Wilson SG, Stewart BS, Polovina JJ, Meekan MG, Stevens JD,
Galuardi B (2007) Accuracy and precision of archival tag
data: a multiple-tagging study conducted on a whale shark
(Rhincodon typus) in the Indian Ocean. Fish Oceanogr
16:547– 554
123
Editorial responsibility: Brent Stewart,
San Diego, California, USA
Submitted: September 8, 2007; Accepted: December 4, 2009
Proofs received from author(s): January 1, 2010
... Zealand have traveled to the tropical waters of New Caledonia, Vanuatu, and Tonga in the South Pacific (Bonfil et al. 2010;Duffy et al. 2012). Satellite tracking studies have also revealed trans-oceanic migrations in white sharks, such as the case of an adult white shark tagged off the coast of South Africa conducting a fast, trans-oceanic return migration spanning the entire Indian Ocean to the west coast of Australia (Bonfil et al. 2005). ...
... The year 2021 was particularly cold given the strong La Niña event recorded, with SST around the ENSO 1 + 2 region registering an anomality of − 0.81 °C and − 1.53 °C for November and December, respectively, based on NOAA's NOAA OI SST V2 High Resolution Dataset (Huang et al. 2021) (Fig. 2). The endothermic capacity of white sharks plays a central role in their ability to predate and inhabit colder habitats (Bernvi 2016), and it has been hypothesized to play an important role in trans-oceanic migrations to foraging areas and for conducting drift diving behaviors into deep and colder waters (Boustany et al. 2002;Bonfil et al. 2010). ...
Article
The occurrence of white sharks, Carcharodon carcharias, in Ecuadorian waters has been based on informal reports and questionable circumstantial evidence. We reviewed unique video evidence from a commercial tuna purse seiner and confirmed the first record for this apex predator within Ecuadorian waters and one of the few available for the Tropical Eastern Pacific. It is hypothesized that the oceanography resulting from the 2021 La Niña ENSO event may be related to this unusual sighting. We propose a vagrant status for the Galapagos Islands until further evidence can confirm residency.
... The waters surrounding eastern Australia and New Zealand harbour a single population of white sharks [17], hereafter referred to as eastern Australasian (EA) white sharks. Juvenile and sub-adult (hereafter referred to immature) individuals of this population regularly frequent coastal habitats along the Australian east coast [6,[18][19][20][21][22][23][24][25]. Movements of this population have been relatively well studied, yet most tagging studies have focused on horizontal rather than vertical patterns, paying little attention to the 3-dimensional nature of the marine environment. ...
... Movements of this population have been relatively well studied, yet most tagging studies have focused on horizontal rather than vertical patterns, paying little attention to the 3-dimensional nature of the marine environment. Satellite and acoustic tracking data revealed complex spatial dynamics comprising an inshore continental-shelf phase as well as extensive oceanic travel, resulting in connectivity across their entire Australasian range [6,[18][19][20][21][22][23][24][25]. Vertical movements in coastal habitats were typically concentrated in the upper 100 m of the water column [6,21,25]. ...
Article
Full-text available
Knowledge of the 3-dimensional space use of large marine predators is central to our understanding of ecosystem dynamics and for the development of management recommendations. Horizontal movements of white sharks, Carcharodon carcharias, in eastern Australian and New Zealand waters have been relatively well studied, yet vertical habitat use is less well understood. We dual-tagged 27 immature white sharks with Pop-Up Satellite Archival Transmitting (PSAT) and acoustic tags in New South Wales coastal shelf waters. In addition, 19 of these individuals were also fitted with Smart Position or Temperature Transmitting (SPOT) tags. PSATs of 12 sharks provided useable data; four tags were recovered, providing highly detailed archival data recorded at 3-s intervals. Horizontal movements ranged from southern Queensland to southern Tasmania and New Zealand. Sharks made extensive use of the water column (0–632 m) and experienced a broad range of temperatures (7.8–28.9 °C). Archival records revealed pronounced diel-patterns in distinct fine-scale oscillatory behaviour, with sharks occupying relatively constant depths during the day and exhibiting pronounced yo-yo diving behaviour (vertical zig-zag swimming through the water column) during the night. Our findings provide valuable new insights into the 3-dimensional space use of Eastern Australasian (EA) white sharks and contribute to the growing body on the general ecology of immature white sharks.
... Southern-Western Australian and Eastern Australian and New Zealand) or from the Northwest Pacific subpopulation, it is further uncertain as to why, how frequently, and for what duration they are utilizing these tropical waters. It is not uncommon for C. carcharias to utilize tropical waters as they have a global distribution in temperate, subtropical, and tropical seas (Bonfil et al., 2005(Bonfil et al., , 2010Duffy et al., 2012;Skomal et al., 2017). However, research illustrates that C. carcharias movement patterns have been suggested to be correlated with a variety of both biotic and abiotic variables, including reproductive behaviour (e.g. ...
Article
In 2013 and 2019, two separate encounters with a white shark (Carcharodon carcharias) were documented within Indonesian waters. Of particular importance was ca. 6.0 m male C. carcharias that was captured in Lombok, Indonesia in 2013, where an upper lateral tooth was retained. Using the D-loop sequences of the mitochondrial DNA (mtDNA) associated with this captured white shark, the mtDNA was compared to the available mtDNA sequences in GenBank® associated with the Northwest Pacific and Australian (i.e. Southern-Western and Eastern) C. carcharias subpopulations to determine its point of origin. Results from the mtDNA analyses suggest that the point of origin for this captured C. carcharias is from one of the Australian subpopulations. When compared to primary literature, this migration presents a northerly range extension for this species; however, since it is unclear what Australian subpopulation this shark was from it is uncertain what subpopulation this range extension applies to. Although C. carcharias presence within Indonesian waters is likely a rare occurrence, being that Indonesia represents the largest shark fin exporter in the world, the utilization of these waters and potential unsustainable exploitation poses a definitive threat to this highly migratory top predator. Therefore, further research investigating the purpose and site fidelity of C. carcharias within these waters is critical to future multijurisdictional protection of this top predator.
... More specifically, YOY/juveniles typically inhabit discrete inshore nursery areas [10,12], enabling more effective location-based management practices (e.g., in United States Territorial Waters) [13]. Carcharodon carcharias has a global distribution in both temperate and subtropical seas, and occasionally utilizes tropical waters [11,[14][15][16]. This species is characterized by having low fecundity, producing an average of 2-14 pups per litter [17,18], slow growth [19,20], and late sexual maturity, which is estimated to be >360 cm total length (TL) for males and >480 cm TL for females [10]. ...
Article
Full-text available
The white shark (Carcharodon carcharias) is a globally distributed top predator. Due to its ecological importance, increasing knowledge through continued research can enhance management measures. One such facet of biological knowledge is the identification of shark nursery areas, as protection of these regions is critical to species survival. Presently, there are two known C. carcharias nursery areas in association with the Eastern Australian subpopulation; however, a nursery area associated with the Southern-Western Australian C. carcharias subpopulation has yet to be identified. Herein, we report opportunistic laser photogrammetry, stereo-photogrammetry, and baited remote underwater video systems (BRUVS) data that resulted in the identification of sixteen young-of-the-year (YOY)-juvenile C. carcharias from two separate regions (i.e., Salisbury Island and Daw Island) in South-West Australia. Additionally, anecdotal bycatch data associated with two YOY C. carcharias (i.e., 1.40 and 1.70 m total length) from another location within the Great Australian Bight are reported. While it is premature to conclude that these sites represent discrete or an expansive interconnected nursery area, the sightings success in this study is indicative that future research may want to consider implementing a study during a similar time period (i.e., February–March) while using a similar attractant methodology (i.e., bottom-set BRUVS baited with squid [Sepioteuthis australis]) to help elucidate the unique life-history characteristics of this C. carcharias subpopulation.
... Marine megafauna utilize dynamic and variable movement patterns to obtain resources (Goldbogen, 2006;Laidre et al., 2007), mates (Bonfil et al., 2005), and evade predators in the three-dimensional ocean environment where encounter rates are highly spatially and temporally dependent (Sims et al., 2008). Numerous studies have demonstrated that many species drastically alter their movement strategies from location to location (Hays et al., 2006;Bonfil et al., 2010;Campana et al., 2011) and on temporal scales from minutes to years Johnston et al., 2005;Dewar et al., 2008;Andrzejaczek et al., 2019a). Movement pattern diversity is exhibited in many ways from altering swimming depth (Wilson et al., 2006;Weng et al., 2007), diel vertical migrations (Sims et al., 2005), diving geometry (Gleiss et al., 2011a), or foraging behavior (Bruce et al., 2006;Graham et al., 2006). ...
Article
Full-text available
Diving behavior in basking sharks, the largest obligate ram filter feeding planktivore, is highly dependent on their location. In the Bay of Fundy, where basking sharks congregate in the boreal summer and autumn, the sharks’ copepod prey are located deep in the water column, below 100 m, in dense but scattered patches. We used time-depth recorders to examine how the vertical movements of basking sharks adapt to such a prey field and captured 4,138 hours of diving behavior from 42 sharks in the boreal summer from 2008 to 2020. Using finite mixture models, we split the time series into surface and subsurface movement blocks and used dynamic time-warping to cluster subsurface movements into seven modes based on their shapes and lengths, with mostly V-shaped subsurface movements (85%) and a minority that were U-shaped (14%). Across sharks, five overall strategies of vertical movement behavior were identified. The strategies split broadly by the ratio of V-shaped movements to U-shaped movements in a deployment and whether the majority of subsurface movements were above or below 100 m. A majority of basking sharks (64%) were reverse diel vertical migrators but none altered their time-allocation across tidal periods. During more thermal stratification, sharks dove deeper, longer, and less frequently while during less thermal stratification sharks dove shallower, shorter, and more frequently. Overall, we show that basking sharks exhibit considerable inter- and intra-individual variability in their diving behavior, and therefore presumably also in foraging modes. Some of this variability relates to time of year and tidal phase, unsurprising in this highly tidally-driven system; however, the majority of the variability remains unexplained without more information on the distribution, composition, and abundance of the copepod prey field. The technique presented is extendable to other species and, unlike many dive classification techniques, requires few subjective delineations of diving behavior.
Article
This study used a novel approach combining stable isotope data and condensed multivariate fatty acid data to define comparative niche space and overlap of six sympatric sharks from the south‐west Indian Ocean: Galeocerdo cuvier , Sphyrna zygaena , Sphyrna lewini , Carcharias taurus , Carcharodon carcharias and Carcharhinus obscurus . G. cuvier had the smallest fatty acid niche space but exhibited the largest range in δ ¹³ C, suggestive of foraging across multiple environments (habitat generalist) but on nutritionally similar prey in a narrow trophic band (nutritional specialist). The remaining five species had comparatively higher δ ¹⁵ N, pelagic‐based fatty acids and larger fatty acid niche spaces, suggesting they are nutritional generalists with a preference for higher trophic level prey. Niche space was not associated with conservation status despite declining populations for half of the species studied. This suggests that resource availability is not a limiting factor for these species and that their mobile nature provides them access to diverse habitats and resources, while exposing them to a broad range of anthropogenic threats, muting the relationship between conservation status and resource use. The combined approach allowed for a comprehensive representation of niche space, distinguishing species based on trophic level, basal carbon sources and pelagic and coastal prey consumption. The presented integrated approach provides greater detail and resolution of elasmobranch trophic ecology that could not be achieved with either fatty acid or stable isotope analysis alone.
Article
Ontogenetic habitat shifts are a common feature of many marine species, including sharks, which face conservation threats when their distributions overlap with human resource extraction and habitat modification. White sharks Carcharodon carcharias , for example, exhibit a distinctly coastal phase as juveniles, with a limited distribution compared to the basin-scale range of adults. Using an unoccupied aerial vehicle (UAV), we studied a coastal aggregation site within a Southern California Bight nursery area to determine how fine-scale temporal and oceanographic factors affect white sharks at different developmental stages. White shark density, as measured via UAV, was highly variable across time of day and day of year, with modest variation across years. Typically, more sharks were observed in the late afternoon hours. Sharks, especially those <3 m total length, were observed more often during periods of colder seafloor temperatures, potentially reflecting avoidance of these colder, deeper waters by more cold-intolerant smaller white sharks. Alternate models incorporating sea surface temperature showed a very small but significant association between surface temperatures and <3 m total length white sharks for the months we surveyed, but no such association for larger sharks. There were no or only modest effects of visibility, swell height, chl a levels, sea state, and tidal height on UAV-observed shark density. Understanding how temporal patterns and oceanographic predictors of density change over time as well as how shark ontogeny interacts with these factors can help us to better understand how this species uses coastal habitats and predict when they may be more likely to share marine space with humans.
Chapter
The quintessential example of evolutionary convergence is that between the shark, ichthyosaur, and dolphin. Although not closely related, the three exemplar taxa have independently evolved adaptations in morphology, physiology, and behavior that result in concomitant levels of performance that meet the requirements associated with operating in a dense, viscous, and thermally conductive marine environment. These apex marine predators display a remarkable amount of homoplasy. All three taxa have developed streamlined fusiform bodies to reduce drag when swimming. The position, type, and morphology of the control surfaces (i.e., fins, flippers, flukes) are similar for the convergent taxa. The control surfaces have different internal support structures, but function similarly to generate lift forces for stability and maneuverability. The main departure in control surface design among the three taxa is that dolphins lack pelvic fins. For dolphins, the loss of pelvic appendages is directly related to the possession of horizontally oriented caudal flukes, which perform double duty as a propulsive device and posterior stabilizer for trim control. The flukes of dolphins and caudal fins of ichthyosaurs and sharks have a lunate shape that function as an oscillating wing to generate high efficiency, lift-based thrust for high-speed swimming. The three convergent taxa are homeothermic, with a body temperature above that of the water in which they live. The advantages of an elevated body temperature are the attainment of higher maximum swimming speeds, longer and faster sustained swimming speeds, improved digestion, brain heating, and enhanced visual acuity. The convergence of the shark, ichthyosaur, and dolphin with respect to morphology, physiology, and locomotor performance reflects similar selective pressures imposed by the physical fluid environment that have dictated the independent evolutionary trajectories of these high-performance marine predators.
Preprint
Full-text available
Many large pelagic predators, including shark, tuna, and billfish, periodically dive to deep oceanic layers, connecting the surface and mesopelagic ecosystems. However, the patterns and drivers of deep dives across species remain poorly understood. To close this gap, we conduct a meta-analysis of the diving behavior of 24 pelagic predator species from the global ocean, resulting in 671 independent diving depth estimates from 87 tagging studies. Our analysis reveals consistent large-scale patterns in diving depths, with predators diving deeper offshore and during the day, and shallower closer to the coast and during the night. Deep diving species show similar diving depths during the night, with deeper dives for sharks, and shallower dives for tuna and swordfish. These patterns are reversed during the day, widening the gap between day and night vertical ranges for these groups. In contrast, shallow diving species show smaller variations between day and night dives, with sharks diving slightly deeper on average, followed by tuna and billfish. Correlations with co-located environmental variables suggest an important predictive role for proxies of prey abundance and light availability, as well as variables that influence physiology, such as oxygen and temperature. These relationships are more robust for deep divers during the day, and shallow divers at night. Our analysis highlights the value of tagging observations for the development of a mechanistic, quantitative characterization of vertical habitat use of large marine predators and its environmental constraints.
Article
Full-text available
Opportunistic in‐water and aerial surveys in South Africa and the analysis of contributed citizen science data have extended the known range of reef manta rays Mobula alfredi along the eastern coast of Africa by 140 km (to Mdumbi Beach) and verified the first transboundary movements for the species. Additionally, six new long‐range dispersal records have provided evidence of connectivity with the M. alfredi population off the Inhambane coastline of Mozambique. Five of these records captured one‐way movements, the longest of which was an individual that travelled 505 km from Praia do Tofo to Sodwana Bay with 301 days between sightings. A single individual made a return trip between Závora, Mozambique and Sodwana Bay, South Africa (a total distance of ~870 km). These findings support the Convention on Migratory Species listing for the species, suggesting regional transboundary management units are warranted for this wide‐ranging elasmobranch.
Article
Full-text available
Purpose: Among 29 different species of sharks reported in the Adriatic, the great white shark and the basking shark are included as very rare species. These two species, like other sharks, have life history characteristics, such as slow growth, delayed ages at maturity, low fecundity and long gestation periods, that make them particularly vulnerable to overfishing. A number of studies carried out throughout the world indicate that numbers of these two species decline. Methods: This paper gives collected data of records of these two species in the Eastern Adriatic, based on bibliographical research and collaboration with numerous persons and institutions. Conclusion: Since 19th century 61 records of the great white shark and 27 records of the basking shark have been collected in the Eastern Adriatic. According to obtained results, a proposal of their protection in the same area has been presented.
Chapter
Full-text available
We tested the ability of archival tags and their associated algorithms to estimate geographical position based on ambient light intensity by attaching six tags (three tags each from Northwest Marine Technologies [NMT] and Wildlife Computers [WC]) at different depths to a stationary mooring line in the Pacific Ocean (approx. 166º42'W, 24º00'N), for approximately one year (29- Aug-98 to 16-Aug-99). Upon retrieval, one tag each from the two vendors had malfunctioned: from these no data (NMT) or only partial data (WC) could be downloaded. An algorithm onboard the NMT tag automatically calculated geographical positions. For the WC tags, three different algorithms were used to estimate geographical positions from the recorded light intensity data. Estimates of longitude from all tags were significantly less variable than those for latitude. The mean absolute error for longitude estimates from the NMT tags ranged from 0.29 to 0.35º, and for the WC tags from 0.13 to 0.25º. The mean absolute error in latitude estimates from the NMT tags ranged from 1.5 to 5.5º, and for the WC tags from 0.78 to 3.50º. Ambient weather conditions and water clarity will obviously introduce errors into any geoposition algorithm based on light intensity. We show that by applying objective criteria to light level data, outliers can be removed and the variability of geographical position estimates reduced. We conclude that, although archival tags are suitable for questions of ocean basin-scale movements, they are not well suited for studies of daily fine scale movement patterns because of the likely magnitude of position estimate errors. For studies of fine scale movements in relation to specific oceanographic conditions, forage densities and distance scales of 100 km or less, other methods (e.g. acoustic tracking) remain the tool of choice.
Article
We investigated the migration and behavior of young Pacific bluefin tuna (Thunnus orientalis) using archival tags that measure environmental variables, record them in memory, and estimate daily geographical locations using measured light levels. Swimming depth, ambient water temperature, and feeding are described in a companion paper. Errors of the tag location estimates that could be checked were -0.54° ±0.75° (mean ±SD) in longitude and -0.12° ±3.06° in latitude. Latitude, estimated automatically by the tag, was problematic, but latitude, estimated by comparing recorded sea-surface temperatures with a map of sea-surface temperature, was satisfactory. We concluded that the archival tag is a reliable tool for estimating location on a scale of about one degree, which is sufficient for a bluefin tuna migration study. After release, tagged fish showed a normal swimming behavioral pattern within one day and normal feeding frequency within one month. In addition, fish with an archival tag maintained weight-at-length similar to that of wild fish; however, their growth rate was less than that of wild fish. Of 166 fish released in the East China Sea with implanted archival tags, 30 were recovered, including one that migrated across the Pacific Ocean. Migration of young Pacific bluefin tuna appears to consist of two phases: a residency phase comprising more than 80% of all days, and a traveling phase. An individual young Pacific bluefin tuna was observed to cover 7600 km in one traveling phase that lasted more than two months (part of this phase was a transpacific migration completed within two months). Many features of behavior in the traveling phase were similar to those in the residency phase; however the temperature difference between viscera and ambient temperature was larger, feeding was slightly more frequent, and dives to deeper water were more frequent.
Article
Geolocation data were recovered from archival tags applied to bigeye tuna near Hawaii. A state-space Kalman filter statistical model was used to estimate geolocation errors, movement parameters, and most probable tracks from the recovered data. Standard deviation estimates ranged from 0.5� to 4.4� latitude and from 0.2� to 1.6� longitude. Bias estimates ranged from )1.9� to 4.1� latitude and from )0.5� to 3.0� longitude. Estimates of directed movement were close to zero for most fish reaching a maximum magnitude of 5.3 nm day)1 for the one fish that moved away from its release site. Diffusivity estimates were also low, ranging from near zero to 1000 nm2 day)1. Low values of the estimated movement parameters are consistent with the restricted scale of the observed movement and the apparent fidelity of bigeye to geographical points of attraction. Inclusion of a time-dependent model of the variance in geolocation estimates reduced the variability of latitude estimates. The statespace Kalman filter model appears to provide realistic estimates of in situ geolocation errors and movement parameters, provides a means to avoid indeterminate latitude estimates during equinoxes, and is a potential bridge between analyses of individual and population movements.