Residency and spatial distribution of bull sharks (Carcharhinus leucas) in and
around Reunion Island MPA
Marc Soria1*¶, Michael R. Heithaus2,Antonin Blaison3¶, Estelle Crochelet4¶, Fabien Forget5, Pascale
1 MARBEC, University Montpellier, CNRS, Ifremer, IRD, Sète, France
2Center for Coastal Oceans Research, Marine Sciences Program, Florida International University, North
Miami, FL 33181
3 MARBEC, University Montpellier, CNRS, Ifremer, IRD, Sète, France
4ARBRE - Agence de Recherche pour la Biodiversité à la Réunion, 18 rue des Seychelles, Lotissement
Horizon, 97436 Saint-Leu, La Réunion.
5MARBEC, University Montpellier, CNRS, Ifremer, IRD, Sète, France
6UMR 9220 ENTROPIE, IRD, La Réunion, France
* Corresponding author
E-mail: email@example.com , +33767173453 (MS)
A sudden increase in the shark attacks rates on humans in Reunion Island has been blamed by some on
the implementation of a Marine Protected Area (MPA) along the Island’s West Coast where attacks,
primarily by bull sharks (Carcharhinus leucas), were concentrated. We used passive acoustic telemetry
to investigate the spatial distribution of bull sharks (N = 36) by quantifying their residency and their
frequentation of the MPA and compared it to outside of the MPA. Over the study duration of 17 months,
18 sharks were detected in the acoustic receiver array, most of which were detected more frequently
outside the MPA (N = 148; mean ± SD = 41.5 ± 56.4 visits month-1and 17.6 ± 30.5 hrs month-1
respectively) than inside the MPA (N = 218; mean = 21.4± 28.1 visits month-1 and 7.2 ± 15.2 hrs month-
1). There was, however, individual variation in sharks’ use of the MPA. Thirteen sharks spent more time
outside the MPA than inside the MPA while five sharks (all females) spent significantly more time
inside the MPA. These results suggest that the spatial distribution of bull sharks does not appear to be
primarily centered in the MPA along the west coast of Reunion island. There are, however, specific
locations where bull shark encounter probabilities are relatively high during particular times of the year.
Such higher risk areas could be targeted as part of the risk management strategy for changes in human
uses in order to reduce the risks of negative shark-human interactions observed during the past decade.
Keywords: bull shark, marine protected area, human-shark conflict, acoustic telemetry
Despite of the substantial global shark populations decline (e.g. Ferretti et al. 2010), with approximately
25% of shark and ray populations threatened by extinction (Dulvy et al. 2014), some areas around the
world have seen shark populations stabilize or even begin to increase (e.g. Carlson et al. 2012). In some
areas this has raised concerns about the potential for negative shark-human interactions including
increased rates of depredation of fisheries (Gilman et al. 2008, MacNeil et al. 2009) or even shark bites
on humans (Taglioni & Guiltat 2015). Despite the low probability of shark bites on ocean users at a
global scale (https://www.floridamuseum.ufl.edu/shark-attacks/), the rate of shark-human interactions
offshore of Reunion Island in the Southwest Indian Ocean has increased over the past decade
(Lagabrielle et al. 2018). Off Reunion Island, the incidence of shark bites rose from 1.2 bites yearly
between 1980 and 2010 to an average of 3.7 bites yearly between 2011 and 2015 (Taglioni & Guiltat
2015). Following these authors, the majority of incidents involved bull sharks (Carcharhinus leucas)
and people practicing board sports (e.g. surfing). When correcting for the total number of surfing hours,
the increase in incidents represents a 23-fold increase from 2005-2016 (Lagabrielle et al. 2018). Shark-
human incidents peak in winter and appear to have shifted from being distributed randomly around the
island before 2010 to the island’s west coast, the hub of Reunion’s coastal water activities (Lemahieu et
Increasing shark-human incident rates, concentrated on one part of the island, has exacerbated conflicts
among ocean-users and has led to great interest in understanding potential causes for these patterns.
Previous analyses have suggested that seasonal patterns of shark abundance and the total numbers of
ocean users may drive some of observed patterns of shark-human incidents (Ferretti et al. 2015,
Chapman & McPhee 2016). Another factor that could potentially contribute to the increased incident
rates could be the rapid tourism development of the west coast over the past 20 years. Such
developments may have increased freshwater runoff to the coast, expanding habitat for juvenile bull
sharks. It is also possible that increased fishing pressure on reef sharks have reduced their populations
but there are not convincing data on this fishing activity. Tourism development has resulted in
eutrophication of the reef waters and over-exploitation of resources leading to declines in living coral
cover and fish biomass (McClanahan et al. 2007, Hughes et al. 2010, Naim et al. 2013) as well as
erosion of coral beaches (Mahabot 2016). Recognizing this, a Marine Protected Area (MPA) was
established in 2007 to restore and protect reef zones.
The creation of the MPA has been controversial with some ocean users. They consider that reduced
human uses combined with increased fish biomass in the MPA have attracted sharks towards the coastal
waters where ocean activities, especially surfing, occur. To address these concerns associated with
increasing shark-human incidents (Yemane et al. 2009), the CHARC (Connaissance de l’HAbitat des
Requins Côtiers de la Réunion) program was launched in October 2011 (FEDER convention of 28 June
2012; French State convention Bop 113 n°2012/03 and Region Reunion convention ref. POLENV
n°20120257). The aim of this broader project was to use acoustic telemetry to investigate spatiotemporal
patterns in the occurrence and residence times of bull and tiger (Galeocerdo cuvier) sharks that had been
implicated in incidents (Blaison 2017). In this study, we investigate the degree of residency and spatial
distribution of bull sharks in and out of Reunion Island’s MPA.
2. MATERIALS AND METHODS
2.1. Study species
Bulls sharks are large carcharhinids that frequent warm coastal waters worldwide. Bull sharks in the
Indian Ocean are larger than those of the Atlantic Ocean, and can reach lengths exceeding 400 cm total
length (McCord & Lamberth 2009). Bull sharks are viviparous, with neonates generally occupying
coastal rivers, mangroves and estuaries for the first several years of life before moving to coastal waters
(Cruz-Martínez et al. 2004, Simpfendorfer et al. 2005). Large bull sharks are capable of taking large-
bodied prey and have broad diets that include cephalopods, crustaceans, teleosts, elasmobranchs and
marine mammals (Daly et al. 2013, Trystram et al. 2016). Larger individuals can restrict their
movements to particular areas along coasts (Yeiser et al. 2008, Carlson et al. 2010), however some
individuals are also known to undertake long distance movements or seasonal migrations depending on
location (Daly et al. 2014, Lea et al. 2015, Espinoza et al. 2016).
2.2. Study site
Reunion Island is a relatively young volcanic island (3 Ma) in the southern hemisphere (21°07’S /
55°32’E), located 700 km east of Madagascar in the southwest Indian Ocean (Fig. 1). The island is 2512
km2 and has 217 km of coastline. Like most volcanic islands, Reunion is characterized by its lack of
insular plateau (except in the north at Saint-Paul, and in the south at Saint-Pierre). Beyond this plateau,
the underwater slopes are very steep (ca. 10-20%) to a depth of 2,000 m (Piton & Taquet 1992). The
coastal ecosystems of Reunion include sandy and rocky bottoms as well as coral reefs. Fringing reefs
stretch over 25 km along the west and south-west coast, from Saint-Gilles to Saint-Pierre (Montaggioni
& Faure 1980). They form a natural coral barrier that bounds the reef flats and back-reef depressions,
and lie no further than 500 m from the beach. In February 2007, a 35 km2 marine protected area (MPA)
was established that extends ca. 36 km from Cap La Houssaye (Saint-Paul) to La Pointe aux Oiseaux
(Etang-Salé). Much of the existing reef habitat is included in the MPA (Letourneur et al. 2004, Fig. 1).
Our study was focused primarily along the western coast (leeward coast), from Saint-Paul’s Bay to
Saint-Pierre, and was centered around the MPA (Fig. 1).
Fig. 1 The study site along the west coast of Reunion Island. The MPA is colored differently according
to the different levels of protections ( low level, medium level, sanctuary). Shark release locations
are labeled with stars () and the position of the receivers with closed circles ().Receivers with “I” in
the receiver ID are considered inside the MPA and those with an “O” are outside the MPA.
2.3. Field methods
Occurrence and residence times of bull shark were assessed using passive acoustic telemetry (Heupel et
al., 2018). Sharks were captured along the west coast of Reunion Island between September 2012 and
March 2013, using horizontal drifting long-lines that were 0.2 to 1 km long and equipped with 20 to 200
baited 16/0 circle hooks (Blaison 2017). Most fishing occurred at dusk or overnight and soak times were
fixed at 3 hrs to minimize mortality. The CPUE (catch per unit effort), expressed as the number of
sharks per 100 hooks per hour, averaged 0.35 ± 1.07, 0-6.25, N = 115 sharks (Blaison et al. 2015). The
fishing effort was higher on the north-west coast (70% of the fishing effort was done in Saint-Paul’s Bay
and offshore from the harbor of Saint-Gilles and 30% in the south offshore from the harbor of Saint-
Pierre). CPUE were not significantly different between the different sites (N = 115; Kruskal-Wallis test,
H = 11,8, P = 0,07; i.e. Blaison et al. 2015).
Once captured, sharks were brought alongside a tagging vessel, they were measured and the sex was
recorded. Sharks were then inverted and, once they entered a state of tonic immobility (Henningsen
1994), transmitters (Vemco V16TP-4H, transmission interval 40-80 s, power output 158 db, estimated
battery life 845 days, N = 13, or V16-5H, transmission interval 40-80 s, power output 162 db, estimated
battery life of 482 days, N = 5) were implanted through a mid-ventral incision. Two independent
absorbable sutures were made to close the wound. All the fieldwork and protocols of handling and
tagging the sharks were approved by the Ethics Committee (n° 114) of the CYROI (Cyclotron Réunion
Océan Indien) in Reunion Island.
The array of acoustic receivers consisted of 36 Vemco VR2W receivers, deployed on average ca. 2 km
apart and 700 m from shore at depths of 10-60 m (Fig. 1). Detection ranges are known to vary with
environmental characteristics such as depth, sea conditions, surrounding noise and the presence of
thermoclines (Mathies et al. 2014). Therefore, 13 range tests were conducted in the study site. The range
to 50% detection probability was on average of 190 ± 80 m (N = 6) for the receivers placed less than 400
m from the shore (22% of the acoustic network and evenly distributed inside and outside the MPA) and
in average of 390 ± 90 m (N =7) for the receivers further offshore (78% of the acoustic network). We
can therefore presume that the detection ranges are comparable throughout the network, inside and
outside the MPA.
2.4. Data analysis
Data analysis was restricted to the period between the 1st of January 2013 and the 25th of May 2014.
During this period, all receivers were operational;14 receivers were deployed along roughly 27 km of
coastline outside of the MPA, and 22 receivers were deployed along the 36 km of coastline of the MPA
(Fig. 1). During the analysis period, 36 sharks were detected in the receiver array. We calculated the
proportion of time within the study zone by dividing the proportion of time a shark was within the
monitoring array (defined as having been detected on any receiver during a 60 min window) divided by
the total number of monitored hours (the time between tagging and either the end of the study period or
the estimated tag lifetime). The proportion of detection time inside MPA was calculated by dividing the
number of hours inside the MPA by the number of hours in the study zone.
To determine whether sharks used the MPA differently than areas outside of the MPA, we calculated the
number of visits each shark made to individual receivers as well as the duration of these visits. The
duration of a visit to a receiver was defined as the time between first being detected and when it was last
detected on that receiver before an absence (maximum blanking period; MBP) of more than one hour
(Ohta & Kakuma 2005, Capello et al. 2015). This period of absence from a receiver overestimates the
amount of time spent within the detection range of the receiver. Moreover, sharks that return within this
interval of one hour would have remained within the MPA or outside the MPA during this relatively
short absence. To ensure that results were not biased by the selection of a 60 min MBP, we analyzed the
effect of the MBP duration on the presence estimated inside and outside the MPA. This effect was tested
for MBPs of 1, 3 and 6 hrs. The number of times sharks returned to specific receivers (i.e. the number of
distinct visits) decreased by 50% (2326 to 1161) for a 3 hrs MBP and by 68% (2326 to 727) for a MBP
of 6 hr. The duration of presence per visit increased by 72% when increasing the MBP from 1 hr to 3 hrs
(0.38 ± 0.75 hr and 0.65 ± 1.50 hr, respectively) and more than 100% when increasing MBP from 1 hr to
6 hrs (0.91 ± 2.22 hr). While MBP affected the number and duration of visits, there was no difference in
the increase between receivers inside and outside the MPA [Kruskal-Wallis test: H (2, N = 441) = 0.045,
P = 0.977; Siegel post hoc test: Z1hr,3hr = 0.148, Z1hr.6hr = 0.205, Z3hr,6hr = 0.0567]. Therefore, MBP does
not affect the nature of our results. Results presented, use a MBP of 1 h.
The home-range of bull sharks inside the study zone was estimated by using the adehabitatHR R
package v0.4.15 (Calenge 2006). The home range for each shark was computed in order to visualize
their activity area within the receiver array and to determine the importance of the MPA in the spatial
distribution of sharks. If the MPA is attractive to sharks it can be expected that the latter plays an
important role in their spatial distribution. The function kernelUD estimates the utilization distribution
(UD) of each shark by considering that the animal’s use of space can be described by a bivariate
probability density function. The 90% home range was calculated from the UD estimates. The UD gives
the probability density to relocate the sharks at any place according to the coordinates (x, y) of the 36
receivers deployed in the study zone. The kernel estimation of the UD at a given point coordinate is
where h is a smoothing parameter, n is the number of relocations, and di is the distance of the
ith observation from the x, y coordinate. We determined kernel bandwidth h, by numerical optimization
using the optimal h (hopt) for a standard multivariate normal distribution (Horne & Garton 2006).
Since the number of receivers were not the same inside and outside the MPA, the duration of presence
and the number of visits per month, per shark and per receiver were weighted by the densities of
receivers in each area [with a factor of 1 inside the MPA, 1.32 outside the MPA in the north (4 receivers
along 9.8 km of coastline), and 1.05 outside the MPA in the south (10 receivers along 17.6 km of
coastline)]. The sums and means of the duration of presence and of the number of visits inside or outside
MPA were then calculated per month, for each shark or for each receiver. Only adult shark detected
during more than 2 months were included in the analyses (with the exception of two sharks that were
detected during four months but with less than 2 detections per month and were excluded of the
Presence times were Log and Box-Cox transformed and visits were Box-Cox transformed. These
transformations were appropriate (Chi-square test X12 = 12.8, P = 0.38 and X8 = 11.03, P = 0.20
respectively). We also did not detect differences in variances between data inside and outside the reserve
(Levene tests F (1,318) = 0.67, P = 0.41, and F (1,318) = 3.10, P = 0.08 respectively). Therefore, our
data met the assumptions of parametric tests.
We used mixed ANOVA models to determine first, whether the release sites (i.e. whether sharks were
captured inside or outside the MPA) could impact on the proportion of detection time and number of
visits inside the MPA and secondly whether the monthly presence of sharks varied between areas (i.e.
inside or outside the MPA). Area, month and interactions were fixed-effect factors, and we included the
individual identity of sharks as a random factor.
To group the sharks relative to their MPA use, we conducted a hierarchical cluster analysis (HCA) on
the monthly proportions of time spent in the MPA, using Ward's minimum variance method and
Manhattan distance which has the advantage of both having triangular inequality and offering better data
contrast than Euclidean distance. Tukey's HSD was used to correct for multiple comparisons.
Seasonality of presence by group was described following the marine seasons in Reunion island
(Conand et al. 2008). All statistical tests were carried out in Statistica 12.0 (StatSoft Inc.) or using
specific R packages. Results are presented as mean ± SD (min-max, N = x), unless otherwise indicated.
Of the 36 tagged sharks, 24 were caught and tagged inside the MPA and 12 outside the MPA. Only 18
were detected frequently enough to be included in analyses (i.e. during more than 2 months). Of the 18
sharks that were not included in the analysis, eight sharks were never detected and ten were detected too
rarely and sporadically (i.e. during only few months).
The final database contains 10804 visits from 103170 detections. The 18 individuals monitored on the
west coast of Reunion island included six males and 12 females, with two individuals detected in all 17
months, four detected during 14-16 months, seven detected during 9-12 months, and five sharks during
Table 1 Presence time and number of visits at receivers inside and outside the MPA between Jan 2013 - May 2014. Monthly mean presence time was
estimated from the sum of time of presence by month. Receiver codes with an I were located inside the MPA and those with an O were outside.
± SD (hour)
Mean visits ±
presence time ±
± SD (by
I1 1600 9 53.7 6 ± 7.6 122 13.6 ± 10.6 O1 400 7 15.3 2.2 ± 1.4 101 14.4 ± 8.3
1 ± 0.7
4.3 ± 2.4
36.5 ± 31.6
56.2 ± 38.5
0.2 ± 0.1
1.2 ± 0.4
22.8 ± 22.6
39.8 ± 28.9
I4 1050 6 95.6 15.9 ± 13.1 278 46.3 ± 34.6 O4 950 12 190.7 15.9 ± 15.2 434 36.2 ± 21.5
17.8 ± 24.5
33.4 ± 37.8
11.7 ± 13.3
54.4 ± 51.8
I6 1400 12 465.9 38.8 ± 43.3 698 58.2 ± 57.2 O6 400 12 517.9 43.2 ± 42.7 1373 114.5 ± 93
I7 850 12 22.1 1.8 ± 2.3 107 8.9 ± 8.3 O7 290 11 757.9 68.9 ± 61.5 1373 124.9 ± 95.8
1.6 ± 1.9
7.3 ± 4.1
5.3 ± 5.5
27.4 ± 23.8
I9 810 12 34.3 2.9 ± 2.9 69 5.8 ± 4.1 O9 460 12 32.8 2.7 ± 4.2 144 12 ± 11.3
I10 430 10 42.9 4.3 ± 3.8 149 14.9 ± 10.2 O10 630 12 128.3 10.7 ± 14.4 363 30.2 ± 28.3
4 ± 3.7
22.9 ± 17.3
3.7 ± 3.5
7.3 ± 5.5
I12 540 9 42.7 4.7 ± 10.7 34 3.8 ± 2.9 O12 730 5 5.7 1.1 ± 1 43 8.7 ± 5.1
I13 540 11 10.7 1 ± 0.9 59 5.4 ± 3.2 O13 520 10 10.2 1 ± 0.7 34 3.4 ± 1.4
8.7 ± 8.6
31.7 ± 17.1
4.9 ± 3.6
15.4 ± 9.1
I15 910 12 7.4 0.6 ± 0.4 44 3.7 ± 1.8
I16 700 12 106.8 8.9 ± 9.3 521 43.4 ± 33.8
3.5 ± 4
13.9 ± 9.8
I18 300 12 85.9 7.2 ± 6 568 47.3 ± 39
5 ± 5.5
10.9 ± 9.9
4 ± 3.4
17.6 ± 13.1
I21 850 11 87.3 7.9 ± 12.1 302 27.5 ± 35.1
5.8 ± 3.3
25.9 ± 13.3
7.2 ± 15.2
21.4 ± 28.1
17.6 ± 30.5
41.5 ± 56.4
Table 2 Summary statistics of the 18 bull sharks from January 2013 to May 2014. The asterisks denote the sharks whose presences inside and outside the MPA
are significantly different (Tukey’s HSD test). ♀: female; ♂: male. I code is for receivers inside the MPA and O code for those outside.
General informations Inside MPA Outside MPA
time ± SD (in
± SD (by
time ± SD (in
± SD (by
1 ♀ *
41.5 ± 37.8
66.4 ± 58.5
0.4 ± 0.4
4.2 ± 4.4
42.6 ± 58.7
88 ± 89.4
4.6 ± 3.2
18.9 ± 14.2
24.5 ± 23.6
67 ± 54
2.9 ± 1.3
11.2 ± 6.4
4 ♀ *
12.2 ± 7.4
47.1 ± 28.8
4.2 ± 3.4
18.5 ± 11.6
5 ♀ *
5.7 ± 5.7
22 ± 18.4
1.4 ± 1.2
5.4 ± 4.2
16.1 ± 12.3
56.9 ± 40
23.3 ± 16.8
46.6 ± 22.7
6.6 ± 5
43 ± 34
6.4 ± 3.9
19.4 ± 10.2
8.4 ± 3.9
31 ± 6
16.9 ± 5.9
65.1 ± 10.3
4.3 ± 3.3
21.9 ± 15
10 ± 9.1
36.9 ± 17.2
13.2 ± 14.8
24.2 ± 23.5
29 ± 36.8
51.4 ± 47.2
1.7 ± 2
10 ± 10.7
1.8 ± 1.5
7.8 ± 5.6
12 ♀ *
7.3 ± 9.8
21.2 ± 21.7
19.3 ± 21.6
38.9 ± 28.5
13 ♂ *
4.8 ± 5.3
22.2 ± 20.9
16 ± 14.4
38 ± 25.8
14 ♀ *
10 ± 12.6
36 ± 41.6
25.4 ± 26.5
61.4 ± 42
15 ♀ *
4.1 ± 8.3
10.2 ± 18.5
16.5 ± 14.1
36 ± 25.4
3.9 ± 2.5
29 ± 29.7
20.1 ± 26.8
59.2 ± 81.5
17 ♀ *
2.7 ± 2.7
14.7 ± 14.6
10.6 ± 8.6
19 ± 10.6
18 ♂ *
0.8 ± 0.8
6.1 ± 4
19.2 ± 24.7
46.7 ± 48.4
10.8 ± 17.3
32 ± 35.6
15 ± 19.5
35.3 ± 33.2
3-6 months. These sharks spent between 2.3% - 29.3% of their time in range of at least one receiver
(mean = 11.5% ± 7.0, N = 18).
Overall, sharks made more visits and spent longer times within the range of receivers found outside the
MPA than inside (Table 1).
Fig. 2 90% Kernel home-range densities of sharks that were detected in the array of acoustic receivers.
Green boxes indicate the latitudinal extent of the MPA. Shark release locations are denoted by stars
().Shark codes are indicated in each box. Inset indicates (shaded rectangle) the localization of the
study zone relative to Reunion Island. Red shark codes denotes sharks that spent more time within the
MPA (Group 1, see Table 1 and Fig. 3).
Based on Kernel home range estimates, 12 of 18 sharks that entered the array moved over extensive
areas of the coast and ranges extended over the entire study zone (Fig. 2). Two sharks had a restricted
occupancy, one (N°1) in the north part of the MPA, the other north of the MPA (N° 10). Two other
individuals (N° 17 and 18) occupied two areas outside the MPA area (in North and South of the study
zone) but did not enter coastal waters of the MPA (Fig. 1, 2 and Table 2).
Sharks released within the MPA spent approximately equal amounts of time (in hour month-1) around
receivers inside and outside the MPA [13.08 ± 21.07 h (0.05-109.95), N = 81 and 13.28 ± 20.91 h (0.04-
103.90), N = 87 respectively; ANOVA F (1,166) = 0.02, P = 0.89], while those that were tagged outside
the MPA spent considerably more time at receivers outside the reserve than inside [16.62 ± 17.93 h
(0.10-111.32), N = 87 and 8.00 ± 10.27 h (0.05-42.27), N = 65 respectively; ANOVA F (1,150) = 19.05,
P = 0.001]. Sharks in the latter category also were detected for longer overall proportions of time as
The amount of time sharks spent at receivers varied significantly with the interaction : area x shark
identity and the main effects of area, month, and shark identity (Table 3). In general, sharks spent more
time outside the MPA with small but significant variation across months. Individual sharks varied in the
duration of time they spent in the study zone and inside versus outside the reserve (Table 3).
Table 3 Results of the ANOVA mixed model for effects of MPA, month and shark on the presence time
of tagged bull sharks in the study zone.
Factors Effect df
df error MS
error F p-value
Area x Month
Area x Shark
Month x Shark
Area x Month x Shark
Fig. 3 Hierarchical clustering dendrogram of sharks (cf. shark codes in Table 1) based on the proportion
of time spent in the MPA.
The hierarchical cluster analysis revealed two groups. The Group 1 (Fig. 3, Table 2) was composed of
five individuals (N° 1, 2, 3, 4, 5), all females, which spent more time (>70% of the total presence time)
in the MPA and visited it more often (Table 4).
Table 4 Total and monthly mean presence time and number of visits at receivers inside and outside the
MPA for two behavior types resolved by hierarchical cluster analysis. P values are based on ANOVA.
Group MPA N Total presence
± SD (h)
Mean visits ±
22.0 ± 28.9
51.8 ± 47.6
2.6 ± 2.7
11.4 ± 10.4
7.6 ± 10
26.2 ± 29
17.6 ± 20.5
40.4 ± 34.2
However, the difference between areas was significant for only three sharks (N°1, 4 and 5; Table 2).
Except for the shark N°1, these sharks ranged widely (see home-ranges Fig. 2). Four sharks of five (1, 2,
3 and 5, Table 2) in Group 1 spent more time at the three receivers offshore of Saint-Gilles harbor (I4, I5
and I6, Fig. 1) than at the others receivers, inside the MPA [9.7 ± 14.2 h month-1 receiver-1 (0.05-55.34),
N= 55 and 0.7 ± 1.2 h month-1 receiver-1 (0.03-7.84), N= 257 respectively; ANOVA, F (1,310) = 94.34,
P= 0.001]. In addition, these sharks were observed mainly between April and June when water
temperatures are dropping (Fig. 4).
Fig. 4 Proportion of time individual sharks were detected across seasons (from Jan-Mar : Summer, from
Apr-Jun: Cooling, from Jul-Sep: Winter and from Oct-Dec: Warming).
Group 2 (Fig. 3 and Table 2) was composed of thirteen individuals (from N°6 to N°18) which spent
more time outside the MPA than inside and made more visits to receivers outside the MPA (Table 4).
Post hoc analyses indicated that presence times were significantly different inside and outside the MPA
for six of thirteen individuals (Table 2). In general these sharks were widely dispersed in the study zone
with the exception of two individuals (N° 10 and 18) that were detected mostly outside the MPA (Fig.
2). Outside the MPA, they occupied mostly receivers on either side of the MPA: O2, O3 and O4 in
Saint-Paul’s Bay and O5, O6, O7 in Saint-Louis’s Bay (see Fig. 1) than the other receivers outside the
MPA (4.6 ± 14.2 h month-1 receiver-1 (0.03-82.28), N = 477 and 1.0 ± 1.9 h month-1 receiver-1 (0.03-
18.26), N = 327 respectively; ANOVA, F (1,802) = 153.04, P = 0.001). Except for two sharks,
exclusively observed in summer (N° 8 and 16), these sharks were present throughout the year and did
not display marked seasonality (Fig. 4).
Given the high rate of bull shark-human incidents and increasing public concern, it is important to
understand whether MPA affect the spatial distribution of bull sharks. In the absence of movement data
prior the implementation of the MPA and in the absence of knowledge on the habitat quality for bull
sharks inside and outside the MPA, it is impossible to pinpoint whether the MPA implementation
modified the movements and residency of bull shark along the west coast of Reunion island.
Nonetheless, we found that 50% of the tagged sharks (18 individuals) were never detected in the coastal
network and most of the 18 sharks that remained within the acoustic array spent more time outside than
inside the MPA. Generally, their home-ranges appear to extend along the coast of the study area. Finally,
only 5 (21%) of the 24 individuals tagged inside the MPA regularly frequented this area. This suggests
that tagging location did not appear to have an effect on the sharks’ movements and that bull sharks were
not using the MPA more heavily than surrounding areas.
Reunion Island’s MPA was created in 2007 in order to restore coral reef biodiversity and augment fish
stocks by managing the human activities taking place within it. For coastal sharks, such as the bull shark,
this could provide them with an opportunity to find feeding sites if prey resources recovered (Garla et al.
2006, Knip et al. 2012a). While MPAs in other areas have been shown to result in rebounds in shark
numbers fairly quickly (Knip et al. 2012b, Edgar et al. 2014), this pattern seems not verified for bull
sharks off Reunion. Indeed, our tracking data do not suggest that bull sharks preferentially select areas
within the MPA. This difference could be due to the continued presence of extractive fishing in the
Reunion MPA and relatively low biomass of potential prey within the MPA. Indeed, from 2008 to 2014,
fish biomass in the reserve increased from ca 400 to 500 kg ha-1, but only in the full sanctuary zones of
the MPA (Bigot et al. 2016) that represent ca 5% of the reserve’s area (see Fig. 1). This small increase in
biomass is unlikely to be sufficient to drive shifts in shark numbers. Moreover, biomass on Reunion’s
reefs is generally low (~500 kg ha-1) compared to biomass levels observed on other Indian Ocean coral
reefs (McClanahan et al. 2011, Chabanet et al. 2016) and may represent only a modest attraction for
large-bodied predators like bull sharks. Shark use of the MPA was spatially heterogeneous. The one
location where shark activity was concentrated inside the MPA was offshore of Saint-Gilles, where
professional and recreational fishing are authorized. In the perspective of implementing an efficient
strategy of warning and prevention in Reunion island, this further suggests to focus more on the habitat
use, movements and site fidelity of sharks than on the impact of MPA which is unlikely a cause of
Sharks often exhibit inter-individual variation in behaviors [e.g. (Heithaus et al. 2002, Matich et al.
2011)]. Here, we found that individuals varied considerably in their use of the MPA and temporal
patterns of occurrence. Broadly, sharks could be grouped into those that were present virtually year-
round and used waters outside or at the boundaries of the MPA more than those inside and another
smaller group of female sharks that occurred primarily Apr-Jun, when waters temperatures are dropping,
and used waters off Saint-Gilles more often than other individuals.
Variation in the abundance and behavior of bull sharks has been attributed to several factors including
temperature (Carlson et al. 2010, Brunnschweiler et al. 2010, Matich & Heithaus 2012, Drymon et al.
2014), dissolved oxygen levels (Heithaus et al. 2009), salinity (Simpfendorfer et al. 2005, Curtis 2008)
and water turbidity (Cliff & Dudley 1991, Taylor 2007, Froeschke et al. 2010).
At Reunion Island several factors could be responsible for the increase in shark-human interactions
including benthic substrate, sea temperature and period of day (Lagabrielle et al. 2018), turbidity and
swell height (Taglioni et al., 2018). Multiple rivers and ravines provide freshwater inputs to the coastal
waters. During rainfall events, turbid outflow waters rich in organic matter (Piper & Normark 2009)
would not only reduce visibility in coastal waters but also reduce water salinity, conditions that might be
attractive to bull sharks (Werry et al. 2018). Over the recent decades, the fast expansion of the urban
zones on the west coast of the island might have increased the soil sealing and by consequence the rate
and quantity of stormwater runoff flowing to the sea (Shuster et al. 2014). Consistent with this
hypothesis is the finding that the highest occurrence of sharks outside the MPA was in the two bays
located at the mouths of the two largest rivers of the west coast (Fig. 1), on both sides of the MPA
(receivers O2, O3 and O4 in Saint-Paul’s bay and O5, O6, O7 in Saint-Louis’s Bay).
Overexploitation of stocks of coastal and deep-sea demersal fish in Reunion observed since the early
2000’s (Le Manach et al. 2015) may have reduced the availability of potential prey for bull sharks,
inducing them to forage over wider areas and nearer to the coast irrespective of the presence of the
MPA. Anthropogenic changes to the environment could also influence shark behavior and habitat use
(Wong & Candolin 2015, Hays et al. 2016). For example, the presence of the harbor of Saint-Gilles,
where fish carcasses are discarded regularly (Loiseau, pers comm) would offer feeding opportunities and
could attract sharks (Hazin et al. 2008, Papastamatiou et al. 2011). Consistent with this hypothesis is the
finding that the three receivers in the MPA with the greatest presence were offshore of Saint-Gilles
harbor (I4, I5 and I6, see Fig. 1). Another hypothesis is that the preferred use of the Saint-Gilles site by
four adult females during April to June is linked to reproduction. Indeed, this period overlaps with the
apparent mating period of bull sharks in the intertropical zone [March -June; (Stevens & McLoughlin
1991, Espinoza et al. 2016)]. Recently, Pirog et al. 2019 reported that the mating period in Reunion
island should occur during the cold season (June-September). The hypothesis stated above suggests that
a pre-spawning shark aggregation could occur near Saint-Gilles harbor before the mating period. In
addition to external factors like turbidity, swell height and human activity (Taglioni et al. 2018),
localized movements might influence the occurrence of attacks. For example, the site of Saint-Gilles,
where four of the five sharks observed in the MPA were mainly present, is one of the most popular surf
spot of Reunion island. Therefore, a high level of shark-human interactions could be expected on this
site. Specific analysis on fine-scale movements along the coast related to biotic and abiotic factors could
help to test this hypothesis.
While passive acoustic telemetry is an important tool in studies of elasmobranch habitat use, it has
limitations (e.g.Kessel et al. 2014, Heupel et al. 2018). The first challenge is detection area within the
network of receivers. For example, sharks can spend a considerable portion of their time outside of a
monitoring array as was the case for most of the sharks tagged in this study. In our study at Reunion
Island, the receivers only covered ca. 40% of the coastal zone of the study area and did not extend far
into offshore waters where sharks likely spend considerable time. It also did not extend along the coast
further away from the MPA. However, the array was optimized to determine whether individuals were
spending extended periods of time nearshore where shark-human interactions might occur both inside
and outside the MPA.
With a highly mobile species like bull sharks, and relatively large detection ranges, movements along
the coastline have a high probability of being detected by receivers. Importantly, this design is unlikely
to bias results towards greater use of waters inside or outside the reserve. The weighting factors used to
take into account the difference of the densities of receivers inside and outside the MPA should not have
influenced the results. A second challenge is the number of tagged sharks that could be analyzed in our
study. Of the 36 sharks tagged, only 18 were detected enough times to warrant inclusion in analyses.
This sample, however, is large enough to gain insights into general patterns of visitation and residence
times for individuals using coastal waters and provides evidence that sharks are not using MPA waters
more often than those outside the MPA. Finally, spatial or temporal variations in detection ranges of the
receivers might confound data analysis. While the potential impact of such variation is difficult to fully
quantify, the design of the array and range testing suggest that patterns were unlikely to have been
driven by variation in detection ranges of receivers. Indeed, receivers were deployed in acoustically
similar environments inside and outside the MPA and only eight receivers of 36 (22%) were situated
near the coastline and the coral reefs where background noise could reduce detection ranges.
Nevertheless, these nearshore’s receivers were evenly distributed inside and outside the MPA. Lastly,
receiver recoveries were performed every 4-5 months to reduce the potential effects of biofouling
(Heupel et al. 2008).
In summary, our results suggest that although some sharks may use specific areas inside the MPA during
limited time periods, they do not seem to use more the habitat in the MPA than around the MPA. Indeed,
sharks generally were not detected in coastal waters after release or spent more time in waters outside
the MPA than inside the MPA. Concerning the influence of release positions on residence time in or out
of the MPA, we are currently studying the relationship between fine scale individual movements and
potential social interactions amongst sharks. Further studies that employ additional field and analytical
methods, increase sample sizes, extend the temporal period of observation and integrate data on
environmental and biotic factors will provide further insights into the factors driving bull shark habitat
use along the coast of Reunion Island. Together with biological and ecological studies, social science
studies on the perception by the different ocean users of the wildlife as both carrier of damages and
fascination (Dickman 2010) are also necessary to develop policies that could reduce shark-human
We are grateful to all members of the institutions and associations involved in the shark program (IRD,
CRPMEM, University of Reunion Island, Globice, Kélonia, ARVAM, Squal’Idées, RNMR, Ifremer), as
well as all volunteers who assisted with shark fishing and tagging and made our work possible. Finally,
we thank anonymous reviewers and the guest editor for their comments and advice, which helped to
improve this paper. This study received financial support from the European Union (convention FEDER
ref. 2012-dossier Presage n° 33021), the French government (BOP 113 n°2012/03) and the Regional
Council of Reunion Island (POLENV n°20120257). Research grants provided to the second author by
the Regional Council of Reunion Island. The funders had no role in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.
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