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ARTICLE
Decline of coastal apex shark populations
over the past half century
George Roff 1, Christopher J. Brown 2, Mark A. Priest 1& Peter J. Mumby1
Overexploitation of large apex marine predators is widespread in the world’s oceans, yet the
timing and extent of declines are poorly understood. Here we reconstruct a unique fisheries-
independent dataset from a shark control programme spanning 1760 km of the Australian
coastline over the past 55 years. We report substantial declines (74–92%) of catch per unit
effort of hammerhead (Sphyrnidae), whaler (Carcharhinidae), tiger shark (Galeocerdo cuvier)
and white sharks (Carcharodon carcharias). Following onset of the program in the 1960s, catch
rates in new installations in subsequent decades occurred at a substantially lower rate,
indicating regional depletion of shark populations over the past half a century. Concurrent
declines in body size and the probability of encountering mature individuals suggests that
apex shark populations are more vulnerable to exploitation than previously thought. Ongoing
declines and lack of recovery of vulnerable and protected shark species are a cause for
concern.
https://doi.org/10.1038/s42003-018-0233-1 OPEN
1School of Biological Sciences, University of Queensland, Brisbane QLD 4072, Australia. 2Australian Rivers Institute, Griffith University, Nathan QLD 4111,
Australia. Correspondence and requests for materials should be addressed to G.R. (email: g.roff@uq.edu.au)
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Through hunting and widespread habitat modification, top-
level predators have been depleted throughout the world’s
continents, rivers and oceans1, driving widespread ecolo-
gical change2. While losses of apex predators and the con-
sequences for ecosystems have been well documented in
terrestrial ecosystems1, the extent and magnitude of decline in
apex predators in the marine environment is less well
understood3,4. Coastal ecosystems in particular have experienced
widespread trophic downgrading, having lost many of their top-
level predators through overfishing5. Throughout the 20th cen-
tury, increasing human-shark interactions in coastal ecosystems
lead to the public perception that sharks are dangerous to people,
resulting in near extirpation of some coastal shark species
through hunting6. Despite widespread evidence for historical
exploitation of coastal sharks, historical baselines for population
sizes are largely unknown7. The absence of baselines is particu-
larly problematic for conservation of endangered and threatened
shark populations, and the extent to which targeting shark
populations reduces interaction rates with humans in coastal
ecosystems is contentious8.
Here we report on long-term changes in shark catches from the
Queensland Shark Control Program (QSCP) adjacent to the
Great Barrier Reef World Heritage Area (GBRWHA). The QSCP
has been operating since 1962 using a system of mesh nets and
baited drumlines (Supplementary Figure 1) with an aim to
“minimise the threat of shark attack on humans”9by reducing the
local populations of large sharks to minimise the probability of
encounters between sharks and swimmers10. The programme
started in Cairns in 1962, and has since expanded to 11 regions in
Queensland, spanning tropical and sub-tropical coastal ecosys-
tems across 1760 km of the eastern Australian coastline11 (Fig. 1a,
Supplementary Figure 2). To date, nearly 50,000 sharks have been
caught by the QSCP (Fig. 1). From the onset of the programme in
1962, increasing numbers of baited drumlines were installed in
place of nets (Fig. 1b) due to logistical constraints and issues of
bycatch (predominantly turtles and dugongs11).
Results
Species identification and taxonomic composition of shark
catch. Analysis of the QSCP catch data reveals a diverse range of
sharks (45 spp.) spanning multiple trophic levels (Supplementary
Table 1), ranging from small (~ 80 cm maximum total length
[TL
max
]) low trophic level sharks (e.g. Heterodontus portusjack-
soni) to large (> 600 cm TL
max
) apex sharks such as tiger sharks
(Galeocerdo cuvier) and white sharks (Carcharodon carcharias).
Although the QSCP has been in operation since 1962 (Fig. 1c),
records relating to species identification are considered reliable
only from ~1996 onwards following a systematic review of the
programme9. Shark catches from the long-term data set
(1962–2017) were therefore grouped into five broad categories
based on reliably identifiable characteristics: (1) hammerhead
sharks (Sphyrnidae, 23% of total catch, predominantly Sphyrna
mokarran &Sphyrna lewini), (2) tiger sharks (Galeocerdo cuvier,
26% of total catch), (3) whaler sharks (requiem sharks of the
family Carcharhinidae, 45% of total catch), (4) white sharks
(Carcharodon carcharias, 2% of total catch) and (5) other sharks
(4% of total catch, Supplementary Table 1).
Long-term changes in CPUE of shark populations. Bayesian
negative binomial mixed effects models revealed substantial
declines in catch per unit effort (CPUE) of large apex sharks over
the past five decades (Supplementary Table 2). In 1962, an
average of 9.5 hammerheads were recorded per net per year,
which declined by 92% to 0.8 hammerheads in 2016 (Fig. 2a).
These declines did not appear to follow a latitudinal gradient and
were consistent among regions (Supplementary Figure 3). Ham-
merhead sharks are more vulnerable to capture in nets owing to
their unique hammer shaped cephalofoil that easily becomes
entangled11,12 (Supplementary Figure 3). Drumline catch
declined from an average of 0.25 hammerheads per drum per year
in 1962 to 0.02 in 2016 (Fig. 2a). Whaler sharks (Carcharinidae)
also exhibited large declines in CPUE: in 1962, catches averaged
18.3 individuals per net per year declining by 82% to 3.23 indi-
viduals per net per year by 2016, while catch rates of drumlines
declined from 2.3 individuals per drum per year in 1962 to 0.4 in
2016 (Fig. 2b). Declines in hammerheads and whalers were
exceptionally rapid following the deployment of nets in the early
1960s (Fig. 1b), exceeding an exponential rate of decline (Fig. 2a,
b). By the mid 1970s, average hammerhead catch rates were
45–55% lower than the previous decade, and CPUE continued to
decline, reaching ~ 75% of historical baselines by the mid 1990s.
Coinciding with decreasing catch rates, the estimated annual
zero-catch probability (catching no hammerhead sharks at any
given beach within a region per year) increased by 4.8-fold
between 1962 and 2016 (Fig. 2a), while the annual zero-catch
probability of whalers increased by 6.9-fold in the same time-
period (Fig. 2b). These trends were broadly consistent across all
regions (Supplementary Figure 4). As whaler sharks encompass a
broad group of sharks within the Carcharinidae family (26 spp.,
Supplementary Table 1), the lack of species-resolution in the
long-term dataset renders it unclear as to whether the 1962–2016
decline in catch rates represents an even decline among whalers,
or masks long-term shifts in species composition among mem-
bers of the Carcharinidae.
In contrast to hammerheads and whalers, catch rates of tiger
sharks were relatively stable between the early 1960s and early
1990s, prior to a 74% decline in CPUE over the past 25 years
(Fig. 2b). Catches of 1.4 individuals per drum per year in 1962
declined to 0.4 individuals in 2016, while catches in nets declined
from 2.3 individuals per net per year in 1962 to 0.6 individuals in
2016 (Fig. 2c). Coinciding with ongoing declines in numbers of
tiger sharks in nets and drumlines, the annual zero-catch
probability of tiger sharks increased by 1.7-fold (Fig. 2c). The
strongest declines in tiger shark CPUE were recorded at high
latitude regions (Supplementary Figure 5), where tiger sharks
undergo seasonal migrations in warmer summer months13. Such
a result is broadly consistent with previous observations of
geographic range constriction commensurate with population
declines in pelagic predators14.
While relatively uncommon (~ 2% of total catch), white sharks
are considered ‘high risk’and are actively targeted by the QSCP11,
despite being listed as ‘vulnerable’under the Australian Environ-
ment Protection and Biodiversity Conservation Act (EPBC) in
1999. CPUE of white sharks in the QSCP declined by 92% over
the past five decades from 0.7 white sharks per net per year in
1962 to 0.05 individuals in 2015, and 0.1 white sharks per drum
per year in 1962 to 0.008 individuals in 2015 (Fig. 2d). These
declines are ongoing in 8 out of 9 regions (Supplementary
Figure 5) despite a complete ban of commercial and recreational
fishing of white sharks since 1999 under the environment
protection and biodiversity conservation act and the enactment of
a 2002 recovery plan by the federal government15.
As is common when reconstructing historical baselines16, some
degree of uncertainty exists in the accuracy of effort records in the
early years of the QSCP. Prior to the review and standardisation
of the programme in 1992, exact setting of nets may have varied
among regions, and differences in hook types and bait on the
drumlines may have occurred among regions and through time.
Similarly, the accuracy of catch records may be questioned as
historical data has been collected by contracted commercial
fisherman prior to standardised training in shark species
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identification from 1992 onwards. While minor gear variation
may have occurred, declines in CPUE were spatially consistent
among regions in the early years of the programme along nearly
1800 km of coastline (Fig. 1), and analysis of temporal trends in
bycatch revealed no clear evidence of changes in gear types in the
early years of the programme coinciding with rapid declines in
shark catches17–20. Further, it is unlikely that changes in drumline
gear and bait types would have a substantial effect on CPUE as
Cairns (1962)
Townsville (1963)
Bundaberg (1973)
Capricorn Coast (1969)
Gold Coast (1962)
Mackay (1973)
Nth Stradbroke (1974)
Rainbow Beach (1974)
Sunshine Coast (1962)
Gladstone (1983)
Australia
Gold Coast, 3rd November 1963
a
Cumulative effort (nets)
Drumlines
Nets
1960 1970 1980 1990 2000 2010 2020
1960 1970 1980 1990 2000 2010 2020
0
10,000
20,000
30,000
40,000
50,000
Cumulative catch
Queensland
Cumulative effort (drumlines)
c
b
14°S
18°S
22°S
26°S
140°E 144°E 148°E
10°S
0
10
20
30
40
50
0
100
200
300
400
Fig. 1 Regional setting and historical changes in catch and effort for the Queensland Shark Control Program. a Timing of the establishment of shark
control programmes across the Queensland coastline (map created under Creative Commons Attribution 4.0 International from Geoscience Australia).
bCumulative effort for nets and drumlines and catch between 1962 and 2017. cHistorical photograph of contractors measuring sharks removed from
QSCP nets on the Gold Coast in the early years of the programme (3 November 1963), reprinted from Paterson (1990) Biological Conservation, 52(2),
147–159 (ref. 17) with permission from Elsevier
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large sharks are omnivorous and opportunistic12,21,22, and likely
do not exhibit strong preference for fish or shark flesh as bait. In
addition, changes in hook types during by-catch reduction trials
have no measurable effect on shark catches23, and declines were
consistent in both nets and drumlines (Supplementary Figure 3).
Notes from contractors during the early years of the programme
provide insight into changing shark dynamics and support the
observed decline in CPUE: in some regions nets were installed
shortly after the programme initiated to cope with “increase(s) in
large shark catches”(contractor notes), while the number of
drumlines in some regions were reduced in the 1990s due to
declining catch rates of sharks. Patterson17 notes that “When net
catches were high in earlier years, reliance on lines was
unnecessary to achieve satisfactory results but as net catches
declined lines were used more assiduously in some regions, with a
consequent increase in tiger shark catches”.
While some uncertainty exists with the historical data, analysis
of the detailed contemporary catch data since standardisation of
nets and drumlines throughout the region and following formal
training of contractors in shark species identification (1992–2017)
reveals ongoing declines over the past 25 years (Supplementary
Figure 6). CPUE of hammerheads declined by 68%, whalers by
69%, tigers by 69% and white sharks by 42%, while the probability
of catching no sharks at any given beach within a region increased
through time (Supplementary Figure 6). While ongoing declines
are a cause for concern, historical data from the long-term dataset
(1962–2017) suggest that the historical baselines for populations
may be substantially higher than that based on contemporary
data. This represents a classic case of shifting baseline
syndrome5,24, and implies that studies of sharks declines in the
region in recent decades12,25,26 may be predicated on a
substantially shifted baseline.
Regional depletions of shark populations. Shark control pro-
grams operate with the intent of depleting local populations of
sharks, yet the spatial scale at which these depletions occur is not
well understood. Following the initial deployment of shark nets in
Cairns and the Gold Coast in 1962 (Fig. 1), the programme
expanded along the Queensland coastline to include additional
beaches and additional regions between 1962 and 1998 (Supple-
mentary Figure 2). To quantify the spatial scale of population
declines, we explored changes in initial catch rates (calculated as
the average CPUE for the first five years) following the installa-
tion of gear at new beaches. Within regions, CPUE varied sub-
stantially among beaches within years, consistent with differential
habitat preferences and environmental drivers of shark distribu-
tions that operate over relatively small spatial scales27,28. Despite
such small-scale variability in CPUE, initial catch rates in newly
installed beaches were consistently similar to that of established
beaches within regions (Supplementary Figure 7). At regional
scales, initial CPUE in new net and drumline installations in
recent decades occurred at a lower rate than earlier installations
for hammerhead, whaler and white sharks (Fig. 3). Analysis of
this trend using Bayesian mixed effects models indicates a decline
in initial CPUE between 1963 and 1998 of 78% for hammerheads,
47% for whalers and 92% for white sharks (Fig. 3). Decline in
initial catch rate was considerably smaller for tiger sharks (−4%,
1960 1970 1980 1990 2000 2010 2020
0
5
10
15
20
1960 1970 1980 1990 2000 2010 2020 1960 1970 1980 1990 2000 2010 2020 1960 1970 1980 1990 2000 2010 2020
0
0.25
0.50
0.75
1.00
1960 1970 1980 1990 2000 2010 2020
0
1
2
3
1960 1970 1980 1990 2000 2010 2020 1960 1970 1980 1990 2000 2010 2020 1960 1970 1980 1990 2000 2010 2020
0
0.1
0.2
0.3
1960 1970 1980 1990 2000 2010 2020
0
0.25
0.50
0.75
1.00
1960 1970 1980 1990 2000 2010 20201960 1970 1980 1990 2000 2010 2020 1960 1970 1980 1990 2000 2010 2020
0
0.25
0.50
0.75
1.00
Carcharhinidae
–92% –82% –74% –92%
CPUE net–1 year–1
CPUE drumline–1 year–1
Annual probability of zero catch
4.8 fold increase
Carcharodon carchariasGaleocerdo cuvier
Hammerhead sharks Whaler sharks Tiger shark White shark
Sphyrnidae
6.9 fold increase 1.7 fold increase 1.3 fold increase
Fig. 2 Catch per unit effort (CPUE) in nets and drumlines with fits from Bayesian negative binomial generalised additive mixed effects models (± 95%
credibility intervals), and the annual zero-catch probability (± 95% credibility intervals). Percentages represent the % decline over the 1962–2017 dataset.
Photographs courtesy of Juan Oliphant (http://oneoceandiving.com/)
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Fig. 3), which is consistent with relatively stable CPUE of tiger
sharks between 1960 and ~1990 prior to region-wide declines
CPUE in the late 1990s (Supplementary Figure 6).
From a management perspective, assessing the status of stocks
through fisheries data can be problematic, as CPUE may be
decoupled from abundance due to a range of behavioural and
operational factors that can affect catch rates29. The initial
declines in CPUE have been theorised to reflect depletions of local
populations, with subsequent catches comprising an influx of
sharks from adjacent regions30. Such a response would result in
hyperdepletion, a phenomena by which CPUE declines more
rapidly than population abundance31. The impact of shark
control programs upon populations will vary among species, and
is likely dependant on both movement patterns, habitat use and
the degree of philopatry32. In theory, hyperdepletion would be
more likely to occur in whaler sharks that exhibit small-scale
movements and site attachment within bays on the Queensland
coastline33 than larger apex species that undergo large-scale
transoceanic migrations34 and whose populations cover entire
ocean basins35. Nevertheless, the advent of satellite tracking of
sharks presents an emerging picture that even apex species that
undergo long distance movements (>1000 km), including tiger36,
hammerhead37 and white sharks38,39, can exhibit patterns of
residency or site-attachment (see ref. 40 for a concise review),
rendering them susceptible to localised depletion in shark control
programs. Indeed, declines in the early years of the programme
and increases in the probability of annual zero catches for these
taxa may represent selective depletion of site attached or resident
individuals from the regional population. However, the aseasonal
migration of sharks to coastal nursery areas adjacent to the
QSCP12,39 would favour patterns of hyperstability (e.g. ref. 41.)
rather than hyperdepletion. The ongoing reduction in initial
CPUE as the programme expanded implies that the scale of
declines extend beyond local beaches where the shark control
programme operates, and points to serial depletion of large apex
sharks throughout the wider region over the past five decades.
Dynamics population models should now be developed to
explore the causes of declines and policy options for reversing
them (e.g. refs. 42,43).
Long-term changes in size structure. Life-history characteristics,
such as growth, longevity and fecundity are largely correlated
with body size in sharks44,45. Size is also strongly linked to trophic
position4,45, and size-structuring in communities can be a strong
determinant of the strength of competitive and predatory inter-
actions45. Coinciding with substantial declines in CPUE over the
long-term dataset (1962–2015), the average size of hammerhead
sharks (Sphyrnidae) increased over the past five decades by 5%
(210–221 cm, Supplementary Table 3). As ‘Sphyrnidae’encom-
passes both the large great hammerhead (Sphyrna mokkaran,
TL
max
=610 cm46) and the smaller scalloped hammerhead
(Sphyrna lewini,TL
max
=430 cm46), it is unclear whether the
increase in size through time reflects a shift in the proportion of
scalloped vs great hammerheads, or alternatively reflects selective
declines of neonate and juvenile scalloped hammerhead sharks
from adjacent coastal nursery grounds12 in the early years of the
programme. For the past two decades where species-specific data
are available (1997–2017), the average size of great hammerheads
declined significantly by 22% (274–215 cm) and scalloped ham-
merheads by 16% (204–177 cm, Supplementary Table 4).
The average size of tiger sharks declined significantly by 21%
(272–215 cm) over the past five decades, a pattern that was
consistent among males and females (Supplementary Figure 8).
The average size of whalers also declined significantly by 9%
between 1962 and 2017 (193–166 cm). Long-term declines in the
whaler group may reflect an overall intraspecific reduction in size
over the past five decades, and/or shifts in species composition
towards smaller species of whalers. While our results provide
insight into long-term changes in size structure of large apex
shark populations, a degree of uncertainty exists in historical
records in the early years of the programme. In the early years
prior to 1990, a bounty system was in place for large sharks over
two metres in size, which may have provided an incentive to
exaggerate the sizes of smaller sharks by contractors for monetary
gain. While the extent to which this occurred is unclear,
significant declines in size among hammerhead, whaler and tiger
sharks have continued over the past 20 years following the
removal of bounties and review of the QSCP (1997–2017), and
the rate of decline in the size of tiger sharks across the long-term
Initial CPUE nets
Hammerhead sharks Whaler sharks Tiger shark White shark
Carcharhinidae (Galeocerdo cuvier)(Carcharodon carcharias)Sphyrnidae
Initial CPUE drumlines
1960 1970 1980 1990 2000 2010 2020
0
10
20
30
40
50
1960 1970 1980 1990 2000 2010 2020
0
10
20
30
50
1960 1970 1980 1990 2000 2010 2020
0
2
4
6
10
1960 1970 1980 1990 2000 2010 2020
0
1
2
4
1960 1970 1980 1990 2000 2010 2020
0.0
0.5
1.0
1.5
1960 1970 1980 1990 2000 2010 2020
0
1
2
3
4
5
1960 1970 1980 1990 2000 2010 2020
0
1
2
3
4
5
1960 1970 1980 1990 2000 2010 2020
0.0
0.2
0.4
0.6
YearYearYearYear
1960 1970 1980 1990 2000 2010 2020
0
5
10
15
20
0.0
0.1
0.2
1960 1970 1980 1990 2000 2010 2020
0
5
10
15
20
25
0.0
0.3
0.6
1.2
1.5
1960 1970 1980 1990 2000 2010 2020
0
1
2
3
4
0.0
0.4
0.8
1.2
1.6
1960 1970 1980 1990 2000 2010 2020
0.0
0.5
1.0
1.5
2.0
0.0
0.05
0.1
0.15
0.2
–92%–4%–47%–78%
Initial CPUE nets
Initial CPUE drumlines
Bundaberg
Cairns
Capricorn Coast
Gladstone
Gold Coast
Mackay
North Stradbroke Island
Rainbow Beach
Sunshine Coast North
Sunshine Coast North
Townsville
Regions
0.9
0.15
0.05
40 83
Fig. 3 Initial catch per unit effort (defined as the average CPUE of the first five years of operation) for each beach within regions, and model fits from
Bayesian generalised additive mixed effects models (± 95% credibility intervals) for nets and drumlines. Symbols courtesy of the Integration and
Application Network (ian.umces.edu/symbols/)
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dataset 55-year dataset (10.4 cm per decade, Fig. 4), is similar to
that occurring over the past 20 years (8.6 cm per decade).
From a demographic perspective, species with large maximum
sizes, low growth coefficients, low fecundity, and higher size at
maturity specifically targeted by the QSCP (Supplementary Figure 9)
areparticularlyvulnerabletooverfishing44. We used previously
published estimates of sizes at maturity of shark populations from
local studies27,47,48 to quantify changes in the probability of maturity
in hammerhead and tiger shark catches in the QSCP over the past
twodecades.Whileourestimatesassumethatsizeatmaturityis
fixed over time, sharks are unlikely to exhibit rapid shifts in maturity
due to their K-selected life-history strategies44.Ourresultsindicate
significant and substantial declines in the probability of recording
mature male and female scalloped hammerheads over the past 20
years (Fig. 3d). Most notably, the probability of recording mature
females of scalloped hammerheads declined from 54% in 1997 to
14% in 2017, while probability of mature males declined from 82 to
55% over the same time-period (Supplementary Table 5). Significant
declines were also recorded for female great hammerheads (85% in
1997 to 59% in 2017, Fig. 3d), although no declines were observed
for male great hammerheads. Over the past 50 years, the probability
of recording sexually mature female tiger sharks declined from 43%
in 1962 to 23% in 2017, while the probability of recording mature
males declined from 34 to 9%. In contrast to other sharks caught by
the QSCP, most white sharks were juveniles and sub-adults, and
very few (<1% of females and 7% males) were of mature size.
Considering that the QSCP selectively targets larger sharks (> 1.5
m11), the ongoing decline in the probability of catching mature
hammerheads and tiger sharks is of concern, as declines in the
number of sharks reaching maturity can strongly influence
population dynamics and inhibit recovery rates44.
Causes of declines in coastal shark populations. With wide-
spread depletions of sharks throughout the world’s oceans, con-
servation and management of shark populations is becoming
increasingly important49. Given the multi-jurisdictional nature of
apex shark movement50 and paucity of historical records, causes
of declines at regional scales can often be hard to pinpoint, and
vary substantially among species. The rate and magnitude of
declines in CPUE across multiple taxa strongly implicate fishing
as the primary cause of long-term declines, and precludes alter-
native hypothesis such as environmental drivers or shifting prey
dynamics (Supplementary Table 6). To assess the potential role of
fisheries in the timing of decline of coastal shark populations, we
compiled available records of local and regional commercial and
recreational fisheries from the mid-20th century (Supplementary
Table 7). As nets and baited drumlines are highly efficient in
catching sharks, the QSCP is likely to have exerted localised
impacts on coastal shark populations in regions where gear has
been deployed. Indeed, shark control programmes are considered
effective because they systematically target and reduce popula-
tions of large sharks that are believed to be dangerous9.At
regional scales, considering the widespread movement patterns of
large apex sharks (Fig. 5) and genetic evidence for population
connectivity among Australian waters and throughout the Indo-
Pacific35,39,51,52, the serial declines in shark populations recorded
by the QSCP likely also reflects ongoing population depletion by
recreational, and commercial fisheries in Queensland and adja-
cent jurisdictions, although the absence of historical fisheries data
from the 1960s and 1970s makes the early causes of declines
difficult to pinpoint. The rapid initial declines indicate that apex
sharks may be susceptible to even relatively low levels of fishing
pressure3,44. While the annual regional catch of whalers and
Great hammerhead (Sphyrna mokkoran) Scalloped hammerhead (Sphyrna lewini) Tiger (Galeocerdo cuvier)
(Carcharhinidae)
ab
de
c
Whaler
1960 1970 1980 1990 2000 2010 2020
0
1
2
3
4
5
1995 2000 2005 2010 2015 2020
0
1
2
3
4
5
1960 1970 1980 1990 2000 2010 2020
0
1
2
3
4
5
YearYear
YearYear
1960 1970 1980 1990 2000 2010 2020
0
1
2
3
4
5
(Galeocerdo cuvier)
Tiger
Great hammerhead
Scalloped hammerhead
Hammerhead
(Sphyrnidae)
***
***
***
***
***
1960 1980 2000
0.2
0.4
0.6
0.8
1.0
2000 2005 2010 20151995
2000 2005 2010 20151995 2000 2005 2010 20151995
2000 2005 2010 20151995 1970 1990 2010
1960 1980 20001970 1990 2010
Freq mature Freq immature
0
80
160
160
80
0
0
0.2
0.4
0.6
0.8
1.0
0
0
20
40
40
20
0
0
15
30
30
15
0
Freq mature Freq immature Freq mature Freq immature
0.2
0.4
0.6
0.8
1.0
0.2
0.4
0.6
0.8
1.0
0
0.2
0.4
0.6
0.8
1.0
0.2
0.4
0.6
0.8
1.0
0
0.2
0.4
0.6
0.8
1.0
0
P (maturity)
P (maturity)P (maturity)
P (maturity)P (maturity)
P (maturity)
0.2
0.4
0.6
0.8
1.0
0
0
10
20
20
10
0
0
10
20
20
10
0
Freq mature Freq immature Freq mature Freq immature
Male
***
***
Female
Male
Female
***
***
Female
Male
*
ns
Yea rYea r
Yea r
Length (m)
Length (m)
Length (m)
Freq mature Freq immature
0
90
180
180
90
0
(Sphyrna lewini)
(Sphyrna mokkoran)
Fig. 4 Long-term changes in size structure and sexual maturity. Linear regressions (± 95% confidence intervals) for change in size for ahammerheads
(1962–2017, shading indicates period in which species specific data are available), great and scalloped hammerheads (Sphyrna mokarran and Sphyrna lewini,
1997–2017), bwhaler sharks (Carcharhinidae, 1962–2015), ctiger sharks (Galeocerdo cuvier, 1962–2017), and binomial probability models for sexual
maturity in male and female, dgreat and scalloped hammerheads (S. mokarran and S. lewini, 1997–2017) and etiger sharks (G. cuvier, 1962–2017). ns not
significant. ***p< 0.001, **p< 0.01, *p< 0.05. Symbols courtesy of the Integration and Application Network (ian.umces.edu/symbols/)
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1
10
100
1000
10,000
Maximum distance (km)
c
b
Carcharhinus leucas
C.amblyrhynchos
C.sorrah
C.tilstoni
C.brevipinna
C.amboinensis
Rhizoprionodon taylori
Carcharias taurus
Galeocerdo cuvier
Carcharodon carcharias
Whaler Tiger White Other
New
Zealand
Fiji
Vanuatu
New
Caledonia
Papua New Guinea
Solomon Islands
Tasman Sea
10°S
20°S
30°S
40°S
140°E 150°E 160°E 170°E
Queensland
Coral Sea
180°E
White shark
(Carcharodon carcharias)
New
Zealand
Fiji
Vanuatu
New
Caledonia
Papua New Guinea
Solomon Islands
Tasman Sea
Pacific Ocean
Pacific Ocean
10°S
20°S
30°S
40°S
140°E 150°E 160°E 170°E
Queensland
Coral Sea
180°E
a
Tiger shark
(Galeocerdo cuvier)
Bull shark
(Carcharhinus leucas)
0500 1000 1500 2000 km
Fig. 5 Regional movement patterns among coastal and oceanic ecosystems. Representative movement tracks derived from satellite and acoustic tracking
studies of sharks adjacent to the eastern Australian coastline for atiger sharks (Galeocerdo cuvier,n=10) and bull sharks (Carcharhinus leucas,n=17),
bwhite sharks (Carcharodon carcharias,n=6), and cmaximum distance derived from movement studies for whaler sharks (Carcharhinidae), tiger sharks
(G. cuvier), and white sharks (C. carcharias) caught in the QSCP program
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hammerheads in Queensland net fisheries in recent years exceeds
the annual catch in the QSCP by nearly an order of magnitude
(Supplementary Figure 10), the targeting of both neonate and
juvenile life stages and selective removal of large individuals in
recreational and commercial fisheries (Supplementary Table 7)
coinciding with the expansion of shark control programs in QLD
and adjacent New South Wales53 is likely to have had a sub-
stantial impact on sharks with low population growth rates.
As tiger sharks are not generally considered a target species by
fisheries within the region (Supplementary Table 7), the initial
stability in CPUE may reflect either a lack of fishing pressure in
the early years of the programme, or alternatively may reflect
shifts in the species composition of shark assemblages in response
to overall population declines54. The ongoing declines in CPUE,
increase in probability of zero catch and reduction in size of tiger
sharks that started in the 1990s coincides with a near doubling in
the number of baited drumlines in 8 of the 11 regions
(Supplementary Figure 2). Additional increases in recreational
and commercial fisheries for tiger sharks over the past 20 years
indicates that current fishing pressure of these sharks may be
unsustainable25. As a consequence of local and regional
exploitation, large apex sharks that were once historically
abundant are now considered ‘Endangered’and ‘Vulnerable’
under the IUCN Red Listing (Supplementary Table 1). Critically,
white sharks are now increasingly rare in QSCP catch, having
undergone a 92% decline over the past five decades. The apparent
lack of recovery of protected white shark populations despite a
complete ban on commercial and recreational fishing in
Queensland and neighbouring New South Wales over two
decades ago15 is a cause for concern, and implicates ongoing
catches in shark control programs on the eastern Australian
coastline and fisheries bycatch as drivers of population declines.
Regional movements and connectivity of shark populations.As
top-level consumers, apex sharks exhibit widespread movements
throughout the world’s oceans4,40,50. Thus, population declines in
coastal habitats may have cascading effects in adjacent coastal and
pelagic ecosystems. To quantify the scale of shark movements and
potential for connectivity among coastal habitats, we synthesised
biotelemetry and tagging data from previous studies along
Queensland coastline (n=436 sharks, Supplementary Table 8).
Movement patterns of great and scalloped hammerhead shark
species on the Queensland coastline are currently unknown.
Genetic evidence supports connectivity of scalloped hammer-
heads along the continental shelf between Australia and Indo-
nesia52, and although speculative, analysis of population structure
suggests that adult females may migrate from Australia to
Indonesia and Papua New Guinea55. Evidence from tagging
studies in the Atlantic indicate that while great hammerheads
undergo large-scale (> 3000 km) oceanic migrations, they also
exhibit seasonal residency to coastal and coral reef ecosystems
and long-term site fidelity37. Most species of whaler sharks for
which data are available exhibited varying patterns of residency,
dispersal and connectivity among coastal environments on the
Queensland coastline (Fig. 5), long-range migrations and multiple
habitat use among coastal and coral reef ecosystems was observed
in bull sharks (Carcharhinus leucas56).
Satellite tracking data from tiger sharks on the Queensland
coast indicate smaller scale resident behaviour36 coupled with
widespread movement along the eastern Australian coastline (23°
S–40°S, Supplementary Table 8). Tiger sharks have been reported
to migrate to higher latitudes in warmer months for foraging36,
and tracking studies provide evidence of long-distance migrations
(>1000 km) from the Queensland coast to tropical coral reef
regions of New Caledonia and Papua New Guinea (Fig. 5). Such
widespread movement patterns are consistent with recent studies
indicating population connectivity spanning among eastern and
western Australia, and Hawaii, resulting in a single large Indo-
Pacific population of tiger sharks35,51. Tracking data for white
sharks indicate that while movements are predominantly linked
to nearshore waters along the eastern Australian coastline (23°
S–39°S, Supplementary Table 8), large-scale (> 3000 km) transo-
ceanic excursions were recorded from subtropical Queensland to
temperate New Zealand waters (Fig. 5). Such widespread
movement patterns of large apex sharks among coastal and
pelagic ecosystems indicates a degree of connectivity among
habitats (sandy beaches, coral reefs, seagrass beds, kelp forests)
along the eastern coastline of Australia and throughout Oceania
(Fig. 5). Depletion of shark populations recorded on the
Queensland coastline over the past 50 years may have had
cascading effects on broad-scale nutrient transfer and cross-
ecosystem linkages among adjacent food webs throughout the
region57,58.
Discussion
In terrestrial ecosystems, habitat loss and hunting have been the
primary drivers of decline in large vertebrate species1,2. The
removal of large carnivores in terrestrial systems has substantial
impacts at ecosystem scales1,2, which is often at direct odds with
conservation objectives59. Hunting to reduce conflict is prevalent
in terrestrial ecosystems, yet the extent to which it occurs in
marine ecosystems is largely undocumented. While the efficacy of
shark control programs remains controversial, a general percep-
tion is that recovering shark populations are to blame for recent
increases in unprovoked shark incidents in Queensland and New
South Wales8. By providing unique insight into past coastal
ecosystem states, the QSCP data imply that increases in
human–shark interactions are occurring at a time when shark
populations are severely depleted compared to historical base-
lines. The timing of these observed declines precede previously
reported collapses of coastal and pelagic apex sharks by several
decades, and the magnitude of decline is either equal to or
exceeding rates reported in coastal oceans elsewhere in the
world3,4,60. Thus, shark populations within Australian coastlines
may be predicated on a substantially shifted baseline. Promising
signs of recovery have been reported from coastal shark popu-
lations that have undergone a history of severe exploitation in the
Atlantic61, yet ongoing serial depletions of large sharks under the
QSCP may impact upon local recovery of vulnerable and
endangered coastal shark populations.
Methods
Historical reconstructions of fishing effort and shark catches. The Queensland
Shark Control Program (QSCP) employs a series of baited drumlines and mesh
nets adjacent to coastal beaches. The QSCP actively targets ‘dangerous’and
‘potentially dangerous’sharks17, specifically certain species of whalers (Carch-
arhinidae), tiger sharks (Galeocerdo cuvier), white sharks (Carcharodon carcharias)
and hammerhead sharks (Sphyrnidae). As a historical record of shark catches, the
QSCP is unique in that it represents a continuous documented long-term effort,
and that both size and identity of sharks have been recorded since the onset of the
programme. Data were accessed from the Queensland Shark Control Program
(QSCP) from the State of Queensland, Australia through the Department of
Agriculture and Fisheries (https://www.daf.qld.gov.au/fisheries/shark-control-
program).
The QSCP initially used nets, although due to high levels of bycatch
(predominantly turtles and dugongs11) and declines in the number of sharks
caught in nets17, they were increasingly replaced with drumlines (Supplementary
Figure 2). Nets are considered a passive way of capturing sharks moving across
beaches, whereas baited drumlines actively target feeding sharks11. However,
evidence suggests that nets may actively target sharks, as bycatch trapped in nets
attract feeding sharks17. Previous studies indicate that different gear types select for
different sharks: hammerhead sharks and rays were particularly vulnerable to net
capture, whereas higher catch rates of tiger sharks were observed for drumlines11.
Increases in sea surface temperatures 1962–2016 within regions is shown in
Supplementary Figure 11.
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Since the initiation of the QSCP in 1962, contractors have recorded the total
length, sex, species and status (dead/alive) of each captured shark. Gear types have
been standardised and largely unchanged since around 199211. Nets (186 m in
length, 6 m drop and 50 cm stretched mesh size11) are predominantly set parallel,
and ~500–1000 m, from shore (water depth 7–12 m) depending on local
bathymetric conditions (Supplementary Figure 1). Drumlines are positioned
500–1000 m from the shore and hooks (single 14/0 J hook11) are baited with either
shark flesh (pre-2002) or mullet (post-2002). Nets and drumlines are checked by
contractors 15–20 days each month11 (Supplementary Figure 1).
Species identification is generally considered unreliable prior to 1996, while data
on species identification following a review of the QSCP in 1997 is considered more
robust9. For long-term analysis (1962–2017) we selected four readily identifiable
groups: (i) hammerheads (Sphyrinidae, readily identifiable by their flattened and
laterally extended cephalofoil shaped head), (ii) requiem whaler sharks
(Carcharhinidae), (iii) tiger sharks (Galeocerdo cuvier, readily identifiable by their
large vertical body stripes and blunt head shape), and (iv) white sharks
(Carcharodon carcharias, readily identifiable by their robust, large, conical snout
and countershading, with a white underside and a grey dorsal area).
Effort data in the form of total number of nets and drumlines was reconstructed
using historical records from contractor’s logbooks between 1962 and 2017
(Supplementary Figure 2). Historical effort records account for seasonal lifting of
gear and swapping of gear between beaches during seasons to avoid bycatch of
turtles and whales, and annual effort was adjusted to reflect these changes. Catch
data was standardised by effort at each site to calculate catch per unit effort
(CPUE62) for both gear types. Where catch records were unclear or uncertainty
existed regarding number of drumlines or nets, beaches were excluded from the
analysis. Similarly, with size data, individuals were excluded where contractors
appeared to have recorded measurements in imperial units, or where sizes exceeded
the maximum total length (TL
max
) for each group46. Prior to standardization of the
programme in 1996, in some minor instances, gear type was recorded as ‘unknown’
where exact records were not kept (2.41% of total catch data). In these instances,
catch from the ‘unknown’category was assigned to either drumline or net gear
types in proportion to the odds ratio of catch by drumlines or nets for each species
by region combination.
Statistical analysis. We modelled spatial and temporal variation in shark catches
under the QSCP between 1962 and 2017. We used Bayesian generalised linear
mixed models to model temporal change in catch as a function of time with nested
random effects of region and sites within regions. As catch rates peaked during the
warmer austral summer months (November to February), time was modelled
following financial years (e.g. July 1962 to June 1963). Time was also treated as a
random effect and its effect on catch was modelled with an order two random walk,
which is equivalent to a cubic spline63. Gear (net, drumlines) was included in the
model as a fixed effect, to account for differences in catchability between gear types.
Catch was modelled with a negative binomial distribution, which was found to
adequately account for over-dispersion in catch data. We included effort as an
offset in the GLMM, thus the model’s predictions were for CPUE. Each group
(hammerheads, whalers, tigers and white sharks) was modelled separately. Models
were fit using the integrated nested Laplace approximations (INLA)64 in the R
package ‘INLA’65.
Prior parameters for the random walk component were specified using the
penalized complexity method which controls over-fitting of the temporal trend66.
We used prior parameters of 0.1 and 0.01, though none of the models’WAICs
changed considerably with different choices. All other parameters were given vague
(broad) priors. For each group two models were fitted, the first allowed the random
walk to vary by regions (though the random walk component for all regions shared
the same hyper-parameters), whereas the second had only an additive regional
effect and a shared global random walk. We compared the two models using the
WAIC67. We calculated annual zero-catch probability as the probability of catching
no sharks at a given site per year. Initial catch rates were defined as the average
CPUE for the first five years following the installation of gear at new beaches. To
quantify the spatial scale of population declines, we explored changes in initial
catch rates across all beaches between 1962 and 1998. We used Bayesian
generalised linear mixed models with a random effect of region. Effort as an offset
in the GLMM as above, and catch was modelled with a Poisson distribution.
Long-term changes in size structure. Changes in the size of sharks over the long-
term dataset (1962–2017) were explored for the four major groups (hammerheads,
whalers, tigers and white sharks), and for short-term data for scalloped hammer-
heads and great hammerheads (1992–2017) using linear mixed effects models with
gear and sex as fixed effects and site and region as nested random effects. We used
previously published estimates of sizes at maturity of shark species from local
studies27,47 to quantify changes in the probability of maturity in shark catches in
the QSCP over the past two decades. While our estimates assume that size at
maturity is fixed over time, we argue that this is a reasonable assumption in that
sharks are less likely to exhibit rapid shifts in maturity due to their K-selected life-
history strategies. Changes in the probability of catching mature individuals were
assessed for either sex using binomial general linear models with site and region as
nested random effects. Generalised linear models and GLMMs for maturity were fit
using the package lme468 and base package in R69.
Regional movement patterns of coastal sharks. To assess potential large spatial
scale effects of Queensland shark declines, we reviewed existing literature for shark
movement data that included movements recorded within the Queensland coast-
line for shark species recorded in the QSCP catch. We then extracted a distance
metric to represent the maximum movement recorded by an individual of each
species. For both satellite and acoustic telemetry this comprised the shortest in-
water distance between the furthest points of a minimum convex polygon for the
widest-ranging tagged individual. For conventional mark-recapture (or re-sighting,
in the case of photographic identification) studies using external tags, the greatest
distance between initial capture and recapture point among individuals of each
species was used. While the greatest distance moved by an individual of each
species appears a relatively liberal representation of a species movement, we con-
sider this metric to be somewhat conservative for a number of reasons. First,
sample sizes in satellite tagging studies are generally small and deployments short.
Therefore, only the longest tracks are more likely to accurately capture any seasonal
movements undertaken by migratory species. Second, acoustic telemetry is limited
by receiver placement and any movements beyond the range of receiver arrays are
unknown. Third, mark-recapture studies are limited by spatial and temporal extent
of recapture effort, and finally, we limited our search to movement data that was
only within and/or overlapped the QSCP study areas.
Data availability
Use of the Shark Control Program data is by courtesy of the State of Queensland,
Australia through the Department of Agriculture and Fisheries (https://www.daf.
qld.gov.au/fisheries/shark-control-program).
Received: 26 May 2018 Accepted: 13 November 2018
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Acknowledgements
C.J.B. was supported by a Discovery Early Career Researcher Award (DE160101207)
from the Australian Research Council, M.A.P. was supported by an Australian Gov-
ernment Research Training Program Scholarship. Use of the Shark Control Program
data is by courtesy of the State of Queensland, Australia through the Department of
Agriculture and Fisheries. We sincerely thank Wayne Sumpton and George Leigh for
invaluable discussions and critical insight into the QSCP.
Author contributions
G.R. and M.A.P. conceived the study, G.R. and C.J.B. analysed the CPUE and size data,
G.R. and M.A.P. analysed the movement data, G.R. wrote the first draft of the manu-
script, C.J.B., M.A.P. and P.J.M. contributed to the final draft of the manuscript.
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