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Low abundance of sharks and rays
in baited remote underwater video
surveys in the Arabian Gulf
Rima W. Jabado
1,2, Shamsa M. Al Hameli1, Edwin M. Grandcourt1 & Shaikha S. Al Dhaheri1
Data on the diversity and relative abundance of elasmobranchs (sharks and rays) in the Arabian Gulf
have been limited to shery-dependent monitoring of landing sites. Understanding the diversity and
abundance of sharks and rays is, however, crucial to inform policy and management plans. Baited
Remote Underwater Video Surveys (BRUVS) were conducted in 2015–2016 across the United Arab
Emirates Arabian Gulf waters encompassing a range of depths and habitat types. Data from 278 BRUVS
(757 hours soak time) were analysed to gather information on diversity, relative abundance, species
distribution, and habitat associations. Surveys recorded 213 individuals from 20 species of sharks and
rays at 129 stations. The frequency of occurrence of species usually discarded by shers such as the
Arabian carpetshark (Chiloscyllium arabicum) and stingrays (Himantura spp.) was high, accounting for
60.5% of observed elasmobranchs. Despite the large survey area covered and extensive sampling eort,
the relative abundance of sharks and rays was low at 0.28 elasmobranchs per hour, 0.13 sharks per hour,
and 0.15 rays per hour. This CPUE was reduced to one of lowest recorded abundance on BRUVS from
around the world when removing the two discarded species from the analysis (0.11 elasmobranchs per
hour). These results likely reect the intense shing pressure and habitat loss contributing to population
declines of many elasmobranchs in the Arabian Gulf. Findings provide a baseline for future work and can
support the design of conservation strategies for sharks and rays in the UAE.
Populations of many species of elasmobranchs (sharks and rays) have drastically declined worldwide due to over-
shing and habitat loss leading to growing concerns over their long-term sustainability1,2. Our understanding of
population trends and ecology of these species largely relies on a combination of shery-dependent sources (catch
per unit eort (CPUE)) or extractive shery-independent techniques (e.g., trawl, gillnet, and longline surveys) to
estimate relative abundance3. ese methods form the basis of sheries management but can result in abundance,
catchability, and size selectivity biases4,5. Furthermore, these approaches have a limited ability to survey high
complexity habitats such as coral reefs, do not provide accurate information on non-target species of the various
sheries sampled (i.e., bycatch), and oen fail to record rare and threatened species4–6.
Beyond the range of commercial and recreational sheries, fundamental information pertaining to diversity,
distribution, and abundance estimates of sharks and rays is crucial for the development of eective management
and conservation initiatives7,8. However, data collection for these species is especially dicult because most are
highly mobile, have ontogenetic shis in habitat preferences, and have broad geographic ranges9,10. Although
there are limited resources and funding to undertake such large scale sampling, the prioritisation of these data is
critical to sheries management and to evidence-based conservation planning7.
A growing number of studies have considered alternative methods to independently assess elasmobranch pop-
ulations and reduce current data gaps6,11. e baited remote underwater video system (BRUVS) technique is now
established as a cost-eective, non-extractive means of providing a standardized, non-invasive, non-extractive,
and non-destructive shery-independent sampling method to (1) estimate the relative abundance of elasmo-
branchs across geographically wide areas as well as a range of habitats and depths that might otherwise be inac-
cessible; (2) provide estimates of species richness; (3) analyse species-specic behaviours; and (4) determine
size and biomass when using stereo-cameras4,5,8,11–16. is method uses bait to attract individuals into the eld
of view of a camera so that species can be identied and individuals counted. is approach oen complements
other traditional methods to enhance the scope and capability of monitoring and stock assessment programs13.
1Environment Agency - Abu Dhabi, P.O. Box 45553, Al Mamoura Building, Murour Road, Abu Dhabi, United Arab
Emirates. 2Gulf Elasmo Project, P.O. Box, 29588, Dubai, United Arab Emirates. Correspondence and requests for
materials should be addressed to R.W.J. (email: rimajabado@hotmail.com)
Received: 4 April 2018
Accepted: 28 September 2018
Published: xx xx xxxx
OPEN
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Indeed, studies indicate that BRUVS produce similar relative abundance estimates and species composition to
other shery-independent techniques such as longline surveys5, even though a greater amount of replicates and
amount of time might be required12.
e Arabian Sea and its adjacent waters has recently been highlighted as one of the regions with the most
threatened shark and ray populations in the world17. Much of the data available from the region, and particularly
in the Arabian Gulf, stem from shery-dependent trawl research surveys or monitoring of landings at various
sites (e.g.,18,19). Here, we report on the results from the rst BRUVS to be deployed in the Arabian Gulf waters
of the United Arab Emirates (UAE) with the aim to (1) assess the relative abundance of sharks and rays across
UAE Gulf waters using shery-independent methods; (2) collect data on shark and ray distribution patterns and
habitat associations; and (3) investigate how factors such as season, depth, habitat, and geographic stratum can
inuence the presence of sharks and rays.
Results
Fisheries Resource Assessment Surveys (FRAS) (see Methods for details) were undertaken in May-June 2015,
April to June 2016, and October to December 2016. A total of 283 BRUVS were deployed during this period. Of
these, 278 sites were used in the analysis (Fig.1a); four were discarded due to inadequate visibility (<1.5 m) and
one BRUVS unit was stolen (Fig.2). e total number of video hours was 757.2 hours with a minimum of 64 min-
utes, a maximum of 3.2 hours, and a mean deployment time of 2.1 hours (±0.44 hours SD). All deployments were
spread throughout daylight hours from 06.55–18.15 hrs. Deployment site depths ranged from 1 to 41 m, with a
mean sampling depth of 16.6 m (±8.5 m SD). Details of deployments based on the various factors used in the
analysis are provided in Table1.
Species richness and diversity. Two-hundred and thirteen individual sharks and rays were observed in
which 99 sharks and 114 rays were recorded (Fig.1, Table2). From the 278 deployments, sharks and rays were
observed on 129 (46.4%) of the BRUVS with 64 deployments (23%) recording sharks, and 88 (31.6%) recording
rays. Of the identied individuals (82.4% of individuals observed), a total of 20 shark and ray species, belonging
to eight families from 15 genera were recorded (Fig.3). ese included nine species of sharks from two families
and ve genera and 11 species of rays from six families and 10 genera (Table2). is represents 29.4% of elasmo-
branch species known to occur in Arabian Gulf waters (32 shark species of which 28.1% were observed and 36
ray species of which 30.5% were observed). e cumulative curve indicates that aer approximately 300 hours of
soak time, we had adequately sampled species richness and few additional species were recorded in the remaining
survey time (Fig.4).
e frequency of occurrence of most species was low except for Chiloscyllium arabicum and Himantura spp.
that dominated during the surveys. ese were the most frequently observed species accounting for 60.5% of all
elasmobranchs, 49.5% of identied sharks, and 70.1% of identied rays, respectively. Additional dominant shark
species observed included the whitecheek shark (Carcharhinus dussumieri) (17.2% of identied individuals and
the highest MaxN recorded of 3 sharks in one video frame) and the spottail shark (C. sorrah) (16.2% of identied
individuals). For rays, H. leoparda and Pastinachus spp. accounted for 6.1% and 5.3% of identied rays, respec-
tively. Most species were only recorded once throughout the surveys including the pigeye shark (C. amboinensis),
sharptooth lemon shark (Negaprion acutidens), Halavi guitarsh (Glaucostegus halavi), and the blotched fantail
ray (Taeniurops meyeni). A total of 16 sharks and rays recorded could not be identied due to their distance from
the BRUVS unit.
It was not possible to accurately estimate lengths of individual sharks and rays, especially if these were
observed in the distance. However, at proximity, the majority of sharks (97.9%) were notably smaller than the bait
arm (1.5 m). e majority of Himantura spp. for which we were able to record an estimate of size (n = 68) were
between 50 cm and 100 cm DW (76.4%) with 8.8% larger than 100 cm DW, 76.4% between 50 cm and 100 cm
DW, and 5.8% smaller than 50 cm DW. e largest shark recorded was C. amboinensis at over 150 cm TL while
the largest ray was a smoothnose wedgesh (Rhynchobatus laevis) estimated at over 200 cm TL. e smallest rays
were estimated at around 50 cm TL. Sex could only be determined for 56 Himantura spp. of which 60.7% were
male and 39.3% were female.
Analysis of tapes showed there was no apparent relationship between soak time and the probability of a shark
or ray appearing in the video. Individuals were sighted from the second minute (2.6 mins) of deployment and
until 160.5 mins had elapsed with a mean number of 59.1(±41.4 SD)minutes elapsed to rst sighting.
CPUE. Overall, the CPUE obtained by BRUVS surveys was relatively low (0.28 elasmobranchs per hour, 0.13
sharks per hour, and 0.15 rays per hour) (Fig.5). is CPUE was signicantly reduced when excluding obser-
vations of C. arabicum and Himantura spp. from the analysis (0.11 elasmobranchs per hour and 0.06 sharks per
hour and 0.04 rays per hour respectively). Dierences in the relative abundance of elasmobranchs, sharks, rays,
C. arabicum and Himantura spp. based on Season, Depth, Habitat, and Strata are presented in Fig.6(a–e) and
Table3.
is CPUE recorded for the southern Arabian Gulf was between one to two orders of magnitude lower than
published estimates obtained from reef systems in French Polynesia, Australia, Fiji, the Bahamas, and Indonesia
(Fig.7).
Discussion
is survey is the rst to estimate the relative abundance of sharks and rays using BRUVS in the Arabian Gulf and
across the whole of UAE Gulf waters. It allowed a cost-eective and rapid means to sample across a broad spatial
scale and range of habitats. Results clearly indicate a low relative abundance of elasmobranchs across the south-
ern Arabian Gulf with CPUE levels up to two orders of magnitude lower than those recorded using comparable
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BRUVS techniques in other regions of the world (e.g., Maldives20, French Polynesia6, Western Australia5, and
Sudan21). When removing C. arabicum and Himantura spp. from our analysis, species known to be discarded
by shers in the UAE18,22, our CPUE is reduced by more than half and ranges closer to the alarmingly low CPUE
results from the northern Saudi Arabian Red Sea21. While there are few historical baselines of elasmobranch
abundance from the Arabian Gulf, several studies have already highlighted the increasing shing pressure on
these species in the region with population declines as well as changes in the species composition and sizes of
individuals landed (e.g.18,19). Overshing is the most plausible explanation for the almost complete absence of
large sharks during these surveys and the overall low diversity of species. ese ndings are consistent with the
hypothesis that sharks and rays in the Arabian Gulf and broader Arabian Sea and adjacent waters region are
amongst the most threatened in the world17. Despite the UAE having developed legislation to regulate shark
shing (including species-specic protections), most species (especially sharks) are still landed as bycatch due to
an overlap between the seasonal shark shing ban and open gillnet shing season22. Unsustainable shing and
overexploitation of elasmobranch resources, coupled with weak enforcement of shing policies, are widespread
in the region and these low CPUE numbers are likely a reection of stocks that have been depleted from over two
decades of overshing21,23.
Only 29.4% of elasmobranch species known from sheries-dependent surveys to occur in Arabian Gulf waters
were recorded using BRUVS17,24,25. Other surveys along the Great Barrier Reef in Australia, Indonesia, and South
Africa also recorded less than 50% of known elasmobranch diversity15,26,27. is low diversity in BRUVS could be
due to several factors including the behavior of animals in the presence of bait, or environmental variables such
Figure 1. Map of the United Arab Emirates showing locations of (a) stations (n = 278) where baited remote
underwater video surveys were deployed = ●, (b) location of shark = and ray = sightings, and (c) location
of Arabian carpetshark Chiloscyllium arabicum = and stingray Himantura spp. = sightings.
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as depth gradients or habitats surveyed15,26. Firstly, our BRUVS recorded during the day and some elasmobranch
species exhibit diel changes in behavior and activity28,29. For example, many shark species are less active during
the day than at night when shers set various shing gear (e.g., gillnets or longlines) and catch large quantities of
sharks22,29,30. Furthermore, shers tend to have much longer soak times (oen over 12 hours) and cover large areas
and therefore are more likely to capture sharks and rays during foraging trips27. Also, BRUVS might be biased
towards species attracted to the bait15, while net shing captures individuals that are not bait-dependent27. We do
however recognize that of the 16 unidentied animals recorded on our BRUVS, 14 were rays, highlighting that
the species richness of rays could be higher than what is reported here.
Figure 2. Baited Remote Underwater Video Survey unit with GoPro Hero 4 mounted, bait arm, and bait bag.
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Vessel and logistical constraints during FRAS prevented us from sampling inshore shallow lagoons and
mangrove forests, thus potentially underestimating the abundance of species occurring in these areas. Several
ray species have been observed in shallow water lagoons within UAE waters31 while some shark species utilize
mangroves as nursery areas in other regions of the world (e.g.,32). Nevertheless, we sampled across the depths
gradients of UAE waters (1 to 41 m), in many shallow areas, as well as structurally complex habitats (seagrass
beds, so-sediment inter-reef habitats, macro-algae), areas that also likely provide ideal habitats for many elas-
mobranch species. We found no signicant dierences in the abundance of elasmobranchs for each of these
variables. It is unlikely that depth inuenced the abundance of sharks, a result that is consistent with those from16
and33 who suggest that the lack of dierence in abundance with depth could be due to their attraction to the bait
along with their capability to disperse between dierent depths. Furthermore, several studies have shown that
sharks are oen more common at oshore sites than in inshore coastal habitats (e.g.,15). In the UAE, shers have
conrmed they travel to deeper waters to catch sharks as they have practically disappeared from inshore waters
and it is unlikely that the limited sampling in inshore habitats would have signicantly changed our CPUE results
for sharks22. Less information is available on habitat preferences of ray species occurring in UAE waters. Further
Survey period n BRUVS
Depth Habitat Strata
≤10 m >10 m Mud Sand Other West Central East
Spring 2015 26 26 0 0 2 24 26 0 0
Spring/Summer 2016 134 49 85 58 38 38 107 23 4
Fall/Winter 2016 118 50 68 51 51 16 30 53 35
Tot a l 278 125 153 109 91 78 163 76 39
Table 1. Summary of the number of Baited Remote Underwater Surveys (n BRUVS) completed in 2015 and
2016 by Depth, Habitat and Strata.
Common name Species name Σ MaxN % Occurrence Depth Habitats (MaxN) Seasons (MaxN) Size range
SHARKS
Carcharhinidae
Pigeye shark Carcharhinus amboine nsis 1 0.5 11 M (1) FW (1) >150 TL
Whitecheek shark Carcharhinus dussumie ri 17 8 11–24 M (3), S (2), O (1) SS (1)– FW (3) <100 TL
Blacktip shark Carcharhinus limbatus 6 2.8 9–24 M (2), O (1) SS (1) – FW (2) <100 TL
Blacktip reef shark Carcharhinus melanopte rus 2 0.9 1–6 O (1) SS (1) <100 TL
Spottail shark Carcharhinus sorrah 16 7.5 3–30 M (2), S (2), O (1) SS (2) – FW (2) <100 TL
Sliteye shark Loxodon macror hinus 3 1.4 13–20 M (1), S (1), O (1) SS (1)- FW (1) <100 TL
Sharptooth lemon shark Negaprion acutidens 1 0.5 6 O (1) SS (1) >100 TL
Milk Shark Rhizoprionodon acutus 4 1.9 13–20 M (1) SS (1)- FW (1) <100 TL
Whaler shark Carcharhinus sp. 2 0.9 20–22 M (1), O (1) FW (1) <100 TL
Hemiscyllidae Arabian carpetshark C hiloscyllium arabicum 49 23 3–23 M (2), S (1), O (3) SS (3) – FW (2) <100 TL
Total sharks 99 47.3
RAYS
Aetobatidae Spotted eagle ray Aetobatus ocellatus 6 2.8 4–20 S (1), O (1) SS (1) n/a
Dasyatidae
Leopard whipray Himantura leoparda 7 3.3 11–22 M (1), S (1), O (1) SS (1) – FW (1) 80–100 DW
Reticulate whipray Himantura uarn ak 67 31.5 5–37 M (2), S (3), O (2) SS (2) – FW (3) 40–>100 DW
Pink whipray Pateobati s fai 2 0.9 17–29 M (1) FW (1) 40–100
Cowtail ray Pastinachus sp. 6 2.8 5–13 M (1), S (1), O (1) SS (1) – FW (1) 40–100
Blotched fantail ray Taeniurops meyeni 1 0.5 19 S (1) SS (1) 60–80 DW
Glaucostegidae Halavi guitarsh Glaucostegus halavi 1 0.5 22 M (1) SS (1) >100 TL
Gymnuridae Longtail buttery ray Gy mnura poecilura 1 0.5 17 S (1) SS (1) 30–40 DW
Rhinidae
Bowmouth guitarsh Rhina ancylostoma 1 0.5 14 0 (1) SS (1) >100 TL
Smoothnose wedgesh Rhynchobatus laevis 2 0.9 17–25 S (1) SS (1) >200 TL
Wedgesh Rhynchobatus sp. 1 0.5 21 M (1) FW (1) 100–200 TL
Rhinopteridae Cownose ray Rhinoptera sp. 3 1.4 5–14 O (2) SS (2) 40–100 DW
Unidentied Himantura s p. 14 6.6 5–37 M (1), S (1), O (2) SS (2) – FW (1) n/a
Total rays 114 52.7
TOTALS 213 100
Table 2. Summary of results of Baited Remote Underwater Video Surveys (BRUVS) with a summary of shark
and ray species observed during deployments, abundance (sum (Σ) of MaxN and % MaxN), depth ranges (m),
habitat associations (S – Sand, M – Mud, O – Other; and MaxN by type), seasons (SS – Spring/Summer, FW –
Fall/Winter; and MaxN for each), and estimated size ranges (cm) as total length (TL) or Disc Width (DW). n/a
indicates individuals did not approach the bait arm to allow for size estimates.
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research in these shallow inshore habitats is warranted to determine which are critical sites for elasmobranchs
including breeding aggregation, mating, and nursery areas.
While gear selectivity or environmental variables could also be a reason for not sampling the overall diversity
of species in UAE waters, we argue that the core reason many species were not present in our surveys is due of their
current low abundance in these waters. Indeed, while the relative abundance of shark species varied from that
recorded during shery-dependent surveys in the UAE, except for C. arabicum, species diversity was consistent
with dominant species landed by shers across the country. Interviews with shers, as well as landing site surveys
conrm that carpet sharks are not targeted by shing activity in the UAE and are usually discarded18,22. In the UAE,
over 90% of landings consist of the spottail (C. sorrah), milk (Rhizoprionodon acutus), common blacktip shark
(C. limbatus), whitecheek shark (C. dussumieri) and slit-eye shark (Loxodon macrorhinus) sharks, all of which
Figure 3. Images of elasmobranchs captured by the baited remote underwater video systems in the Arabian
Gulf, (a) spottail shark Carcharhinus sorrah, (b) leopard whipray Himantura leoparda, (c) smoothnose
wedgesh Rhynchobatus laevis.
Figure 4. Cumulative number of elasmobranchs (➖), sharks ( ), and rays ( ) recorded for each 50-hour
soak time interval on the baited remote underwater video systems in the Arabian Gulf.
Figure 5. Mean relative abundance (MaxN h−1 ± SE) of Elasmobranchs, Sharks, Rays, Arabian carpetshark
Chiloscyllium arabicum, and stingrays Himantura spp. determined by baited underwater video surveys.
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were observed in this study and therefore conrming their prevalence in these waters18. Indeed, because BRUVS
use baits that attract sharks, they probably sample those species likely to be most aected by shing activity16.
On the other hand, the diversity and abundance of ray species recorded here were dierent than those recorded
during landing site surveys. Landings data indicate that the most abundant taxa are the cownose rays (Rhinoptera
spp.) (59.4% of ray landings), eagle rays (Aetomylaeus spp.) (20.6%), and wedgeshes, Rhynchobatus spp. (10.5%)34
(Jabado, unpubl. data). While several species of rays were recorded, Himantura spp. clearly dominated in our
survey. is dierent species composition could be due to the fact that shers generally discard ray catches in the
UAE unless they are netted in large numbers22. is indicates that BRUVS have the potential to provide a better
indication of diversity and abundance than shery-dependent surveys for unwanted and discarded catch.
An understanding of habitat associations at the species level and over large spatial gradients can be a valuable
approach to detect important areas for elasmobranch conservation, as well as reveal complex ecological processes
such as connectivity within and across ecosystems15. Due to the low abundance of most species observed, it was
dicult to identify spatial, seasonal, or habitat association patterns and this information was only discerned for C.
arabicum and Himantura spp. Chiloscyllium arabicum sharks exhibited a strong association with shallow waters of
the western region where complex habitats such as coral assemblages and seagrass beds are most prevalent. On the
other hand, Himantura spp. were more common in the deeper waters of the eastern zone characterized by areas
of sand and mud with little structurally complex habitats. ese results are likely due to the habitat preferences
of these two species groups which is oen due to the availability of feeding and refuge sites for prey species25,35.
Further studies are needed in the Arabian Gulf to elucidate habitat associations and use for the majority of spe-
cies occurring in these waters. ese data can then support assessments of the risk of species to shing and/or
habitat degradation.
Figure 6. Mean relative abundance (MaxN h−1 ± SE) of Elasmobranchs, Sharks, Rays, Arabian carpetshark
Chiloscyllium arabicum, and stingrays Himantura spp. determined by baited underwater video surveys in
relation to Season (SS: Spring/Summer, FW: Fall/Winter), Depth (Shallow: ≤10 m, Deep: >10 m), Habitat (Sand,
Mud, Other), and Strata (West, Central, East). * Indicates a signicant dierence (p < 0.05) between groups.
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e species-level identication of individuals and the determination of sizes and sex using BRUVS are chal-
lenging and common limitations5,12,15,27,36. On some occasions animals did not approach the camera and we were
therefore only able to identify 82.4% of observed individuals. is was particularly challenging with some species
of rays that need closer morphological examination to separate between similar species. Furthermore, while clasp-
ers of mature males are usually visible, discerning the sex of females or sub-adult males was challenging since it
depends on the behavior of the animals in front of the camera12. e large majority of the animals observed here
were small-bodied species with maximum total lengths or disc widths of less than 100 cm (e.g., C. arabicum,
R. acutus, C. dussumieri, and longtailed buttery ray G. poecilura)24,25,35 and it was therefore not possible to determine
maturity levels. For some of the larger-bodied animals (e.g., C. sorrah, C. limbatus, H. uarnak, R. laevis), even though
the depth of view of horizontal look-outward systems does not provide a good reference for measurements, the
length of the bait arm provided a point of perspective as a scale bar allowing for coarse estimations of sizes13. In future
studies, we recommend the use of stereo-video techniques to examine relative abundance at an intra-species resolu-
tion as they can provide accurate length and biomass estimates12,37,38. Indeed, the use of length-frequency estimates
for selected commercially important species can provide an additional useful metric for long-term monitoring.
It is important to note that there are a number of biases associated with comparing BRUVS studies from
around the world including the sampling design and deployment of units (i.e., time of day, depths), the type
and quantity of bait used, and soak times6,21. ese can highly inuence estimates of relative abundance and
species richness. While this BRUVS study was not eectively designed to investigate the occurrence and distribu-
tion of sharks and rays, deployment times, type and amount of bait, and survey time frames generally exceeded
those reported for elasmobranchs from around the world5,12,16,21,27,30. One study39 shows that sampling precision
is improved with increasing soak times as it likely enhances the probability of the bait plume intersecting indi-
viduals as they move around and attracts them to the BRUVS unit. Overall, an optimal 60-minute deployment
time is proven to provide an accurate representation of species assemblages and is adequate to record 95% of
species14,37, although sightings can continue to increase until aer 180 mins of deployment21. It has been sug-
gested that it takes longer for sharks to appear in the video when their abundance is low4. In our study, soak time
df X2pdf X2pdf X2p df X2pdf X2p
Season (SS × FW) 1 4.322 0.038 1 4.421 0.036 1 0.242 0.623 1 0.702 0.000 1 12.513 0.402
Depth (S × D) 1 0.355 0.551 1 1.772 0.183 1 6.526 0.011 1 7.194 0.007 1 9.047 0.003
Habitat (S × M × O) 2 0.755 0.686 2 8.968 0.011 2 2.250 0.325 2 12.809 0.002 2 6.947 0.031
Strata (W × C × E) 2 1.109 0.574 2 15.327 0.000 2 5.556 0.062 2 13.940 0.001 2 9.161 0.010
Pairwise tests UpUpUpUpUp
Habitat
(S × M) 4685 0.533 4337 0.038 4548 0.280 4831 0.689 4743 0.594
(S × O) 3306 0.401 2848 0.002 3175 0.157 2927 0.003 2954 0.010
(M × O) 4122 0.788 3918 0.305 4075 0.639 3526 0.004 3646 0.030
Strata
(W × C) 5987 0.651 5417 0.044 5336 0.035 5431 0.018 5155 0.005
(W × E) 2940 0.422 2274 0.000 2753 0.104 2515 0.002 2724 0.049
(C × E) 1318 0.289 1261 0.022 1472 0.946 1365 0.073 1455 0.849
Table 3. Results of ANOVA testing the eect of Season (SS: Spring/Summer, FW: Fall/Winter), Depth (Shallow:
≤10 m, D eep: >10 m), Habitat (S: Sand, M: Mud, O: Other), and Strata (W: West, C: Central, E: East) on the
relative abundance of Elasmobranchs, Sharks, Rays, the Arabian carpetshark (Chiloscyllium arabicum) and
stingrays (Himantura spp.); df = degrees of freedom; bold p values denotes signicance at p < 0.05.
Figure 7. Comparison of mean relative abundance (MaxN h−1) published from BRUVS studies from around
the world for sharks in shed areas (black), sharks in no-take zones (light grey), and elasmobranchs in shed
areas (dark grey). For the UAE, the dark grey column represents the CPUE of sharks and rays aer removing the
Arabian carpetshark (Chiloscyllium arabicum) and stingrays (Himantura spp.) from the analysis.
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varied between a minimum of one hour and up to over 3 hours, and our cumulative species curve shows that few
new species were recorded aer 300 hours of soak time, indicating that we adequately sampled abundance and
species diversity in southern Arabian Gulf waters. We do acknowledge that water quality and visibility is likely
the greatest limitation to BRUVS13,15. While lack of visibility due to lighting at depth is oen not an issue in the
shallow waters of the Arabian Gulf, the vast majority of this body of water is characterized by muddy substrates40.
is aected visibility at certain sites when large quantities of teleost sh aggregated and created a ‘mud’ plume.
Several stations had to be removed from this study due to the inability to see the bait bag (1.5 m from the camera).
Some results show that there is a marginal, non-signicant eect of underwater visibility on the performance of
BRUVS with performance dropping only at the lowest visibility (about 1 m)41. erefore, even though visibility
might have been variable, there were no signicant dierences in CPUE between sand and mud habitats and
visibility is unlikely to have aected our overall CPUE. Overcoming this limitation in Arabian Gulf waters might
require the development of li-bag systems or sampling using cameras from above.
In conclusion, this study has provided valuable data to complement existing sheries-dependent information
available in the UAE. It conrms that the BRUVS sampling technique is useful to examine the diversity, relative
abundance, and habitat associations of elasmobranchs across broad spatial scales, especially in areas where the
use of conventional sheries-independent sampling tools would be dicult to implement. ere is scope for the
future use of this data as a baseline to monitor changes in the relative abundance of species while allowing the
examination of changes in species diversity and composition over time in response to natural and anthropogenic
drivers. However, combining dierent techniques for monitoring, including shery-dependent and independent
methods, will prove more appropriate to fully dene species richness and assemblages in waters where shing
pressure is intense, sheries discards are prevalent (e.g., carpet sharks and rays), or where rare species are known
to occur. Finally, as highlighted from results in Australia29, if management strategies were to be developed and
implemented to reverse stock declines in the Arabian Gulf, BRUVS can allow measurements of species-specic
recovery patterns and demonstrate the ecacy of management strategies.
Methods
Study area. e Arabian Gulf is a sub-tropical and semi-enclosed basin characterized by a wide range of habitats
including coral reefs, mangroves, sandy bays, seagrass beds, and so-sediment habitats40,42. is shallow sea, con-
nected to the Indian Ocean through the narrow Strait of Hormuz, is unique in its extreme environmental conditions.
With an average depth of 35 m, salinity levels are high and oen exceed 45 parts per thousand, while sea surface
temperatures can uctuate between 12 °C in winter to over 36 °C in summer40. e UAE is a coastal country located
on the southern side of the Arabian Gulf with an Exclusive Economic Zone (EEZ) of 58,292 km2. It has a coastline of
approximately 650 km facing the Arabian Gulf, and approximately 70 km bordering the Sea of Oman (Fig.1).
Sampling technique. e BRUVS dataset used here was not collected specically to examine shark and
ray diversity and abundance patterns. ese surveys were conducted as a component of the Fisheries Resources
Assessment Survey (FRAS) to assess the abundance and status of demersal sheries resources in UAE Gulf waters.
BRUVS were deployed from surface vessels during daytime hours at randomly generated stations (New Zealand
National Institute of Water and Atmospheric Research (NIWA) Random Station Generator) across UAE Gulf
waters. To avoid issues with maritime boundaries, surveys considered a 12 nautical mile (nm) exclusion zone
inside of the UAE Exclusive Economic Zone and extended to 15 nm around the island of Abu Musa (Fig.1a).
Additionally, several restricted locations were excluded from the sampling (e.g., oilelds and concession areas,
major shipping lanes and channels) as well as shallow lagoon areas or mangrove forests occurring at depths of
1–3 m that could not be accessed with FRAS vessels.
BRUVS were tted with a GoPro Hero 4 + black high denition camera, set to the standard settings of high
denition video quality (1080), super-wide frame and 25 frames per second) to ensure a full view of the seaoor,
enclosed in a frame and mounted on a steel rod of 1.2 m height (Fig.2). A weighed down (with 2 kg of dive weight
on each side) 1 × 1 m piece of thick mesh (mesh dimension 2.5 × 2.5 cm) was used as a base frame for each
BRUVS unit to stabilize it and ensure a consistent eld of view. A bait arm made of two crossed 25 mm diameter
PVC pipes was placed 1.5 m away from the center of the mesh. e bait consisted of 2 kg of fresh Indian oil sar-
dines (Sardinella longiceps) in a wire mesh bag, chopped to maximize dispersal of the sh oil. BRUVS units were
lowered to the sea bed from the boat using a rope with a buoy placed at the surface to facilitate manual retrieval.
Cameras were set to record continuously for at least a 60 minute period.
Video and data analysis. Species richness and relative abundance estimates of sharks and rays were recorded
during the review of the video footage using Apple Quicktime by the rst two authors. e start time of the video
was recorded when BRUVS landed on the seaoor and settled in one location. To avoid repeat counts of individual
sharks and rays continuously re-entering the eld of view, the maximum number of individuals of the same species
appearing at the same time (MaxN) was used as a relative abundance measure43. MaxN is a conservative estimate
of abundance in high density areas43,44 and was recorded for ve categories: Elasmobranchs (sharks and rays com-
bined), Sharks, Rays, Arabian carpetshark (Chiloscyllium arabicum), and stingrays (Himantura spp.) which consisted
of the reticulated whipray (H. uarnak) and the leopard whipray (H. leoparda). Deployment time, species, sex (if vis-
ible), time of rst sighting, time of each subsequent sighting, MaxN, time of MaxN, and benthos type were recorded
in all videos. Depth was determined using built-in vessel depth sounders at each site. Samples were discarded from
analysis if horizontal visibility was low (<1.5 m), estimated by means of visibility of the bait bag.
Species were identied to the lowest possible taxon. If identication could not be condently conrmed, then
individuals were recorded under the closest genus or family name. For example, this occurred for individuals of
the genus Pastinachus and Rhinoptera, where two look-alike species of each occur in Arabian Gulf waters and
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SciEntific RepoRts | (2018) 8:15597 | DOI:10.1038/s41598-018-33611-8
need close morphological examination in order to separate them. Furthermore, in some cases, sharks or rays
made distant passes, making it dicult to identify to a family level. No attempts at measurements of individuals
were made but coarse estimates of the total length (TL) or disc width (DW) of each individual were noted to
thenearest 50 cm increment by comparing them with the length of the PVC pipe on the bait arm and individ-
uals were classied as ‘adult’ or ‘juvenile’, based on their size compared to known maturity estimates from the
region24,25.
All statistical analysis was conducted using SPSS (version 23). e catch per unit eort (CPUE), used as a rel-
ative abundance index, was calculated as Max N/hr−1 for each species and category. Relative abundance was com-
pared for four factors: Season (Spring/Summer and Fall/Winter), Depth (shallow: 10 m or less and deep, over 10 m),
Geographic strata (West, Central, and East), and Habitat type (Mud (unconsolidated sediment), Sand (consolidated
sand), and Other (other habitats including seagrass, macro-algae, and coral assemblages)) using Kruskal-Wallis
non-parametric rank tests (ANOVA) as CPUE data was found to deviate signicantly from a normal distribu-
tion due to the abundance of 0 values within the data set. Signicant dierences among the groups were further
explored using post-hoc Mann-Whitney U tests. A Bonferroni correction was not applied, given the radical low-
ering of statistical power and increased likelihood of Type II errors associated with this type of correction12,45,46.
e relationship between soak time and the number of species of elasmobranchs, sharks, and rays observed
was evaluated by plotting a species cumulative curve against each 50-hour soak time interval. Finally, the CPUE
was graphically compared to published estimates obtained using similar BRUVS approaches in terms of camera
orientation (vertical to substrate), number of cameras (one at a time), bait type (pilchards or sardines), soak time
(at least 60 mins), and video metrics used (MaxN), from dierent regions around the world6,12,15,16,20,21,26,27,33.
Where more than one study has been conducted in the same region (i.e., Northwest Australia and Indonesia), the
average of all published estimates was depicted21.
Data Availability
e data that support the ndings of this study are available from the Environment Agency–Abu Dhabi but re-
strictions apply to the availability of these data, which were used under license for the current study, and so are
not publicly available. Data are however available from the authors upon reasonable request and with permission
of the Environment Agency – Abu Dhabi.
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Acknowledgements
e authors would like to thank Environment Agency – Abu Dhabi Management for supporting and funding
the Fisheries Resources Assessment Survey. We gratefully acknowledge the support and involvement of the New
Zealand National Institute of Water and Atmospheric Research team, especially Neil Bagley, Rosemary Hurst,
Keith Michael, Peter Marriott, Bilal Bjeirmi, Peter Mc Millan, Darren Stevens, Warrick Lyon, Darren Parsons, and
Dan MacGibbon in the design of the baited underwater video survey units and their deployment. anks also
go to the crew of RV ‘Bahith I’ and ‘Bahith II’ for their assistance with the eld work. A special thank you to Will
White for conrming the identication of Himantura uarnak and H. leoparda individuals recorded on the videos
and to Maitha M. Al Hameli for providing GIS assistance.
Author Contributions
S.S.A.D. acquired the funding for this project. E.M.G. and S.S.A.D. were in charge of project administration and
provided logistical support. S.M.A.H. and R.W.J. completed the video analysis. R.W.J. wrote the main manuscript
text. R.W.J. and S.M.A.H. prepared all gures. E.D.G. and R.W.J. undertook the statistical analyses. All authors
reviewed and edited the manuscript.
Additional Information
Competing Interests: e authors declare no competing interests.
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