Grey Reef Shark (Carcharhinus
amblyrhynchos)
Supplementary Information for Carcharhinus amblyrhynchos
Colin Simpfendorfer1, Demian Chapman2, Euan Harvey3, Michael Heithaus2, Michelle
Heupel4, Aaron McNeil5, Mark Meekan6
1
James Cook University, Queensland, Australia
Florida International University, Florida, USA
3
Curtin University, Western Australia, Australia
4
Australian Institute of Marine Science, Queensland, Australia
5
Dalhousie University, Nova Scotia, Canada
6
Australian Institute of Marine Science, Western Australia, Australia
2
To estimate the global status of the Grey Reef Shark, we estimated population reduction
using data from the Global Finprint project, which is a global scale initiative to assess the
spatial variation in status of sharks and rays on coral reefs. From 2015 to 2018, it
sampled over 400 reefs as well as accessed legacy data from other research programs
(www.globalfinprint.org).
Finprint sampling of coral reefs used Baited Underwater Video Stations (BRUVS).
BRUVS consisted of a weighted metal frame holding a compact high resolution video
camera (typically a GoPro) and an arm holding a bait bag containing 1 kg of crushed oily
fish 1 m in front of the camera. Where possible, at least 50 BRUVS were deployed at a
reef (defined as a single isolated reef, or a patch of a large reef ~10 km2). Four to eight
BRUVS were deployed simultaneously at a reef, with all BRUVS set at least 500 m from
each other. BRUVS were deployed for 60 minutes, although some deployments were
longer for logistical reasons. This deployment time was sufficient to adequately sample
the core coral reef shark and ray species (Currey-Randall et al. 2020). All videos were
read by trained annotators using either Event Measure
(https://www.seagis.com.au/event.html) or the Finprint Annotator
(https://github.com/GlobalFinPrint/Finprint-Annotator). All sharks and rays observed were
identified to the lowest possible taxon (mostly to species), and the time they entered the
video frame and the maximum number of each species in a single frame (MaxN) in each
video was recorded. MaxN is a conservative measure of relative abundance that
ensures individuals are not double counted (Sherman et al. 2018).
We estimated status using all sampled reefs at which Grey Reef Sharks were formerly
known to occur. This involved searching published information on the species, including
historic accounts. We consulted with local experts where questions remained about the
historic occurrence of the species at individual reefs. For each reef within the species’
THE IUCN RED LIST OF THREATENED SPECIES™
known range, the mean MaxN value was estimated using a general linear model suited
to zero-inflated data (function glm.nb in the R package MASS provided a glm with a
negative binomial link function). There were significant differences in the mean MaxN of
small oceanic reefs compared to those on continental shelves or adjacent to large
islands. Thus, levels of depletion were analysed separately for these types of reefs.
Since there are large differences in the potential carrying capacity of individual reefs for
sharks and rays (Nadon et al. 2012) we used the median of all positive MaxN values as
the reference level for no depletion (i.e. if a reef’s estimated mean MaxN value from the
model was > the median of non-zero mean MaxN values then depletion was assumed to
be zero). We considered this to be a conservative measure, and so expect that it may
under-estimate levels of depletion.
The level of depletion of Grey Reef Sharks (scale 0-1) for each reef was calculated by
(1-[reef MaxN/reference MaxN for no depletion]). Reef depletion levels greater than one
were converted to one. Depletion levels by jurisdiction were calculated by taking the
mean of all reefs within that jurisdiction. Standard error of the means was also calculated
and used to produce confidence intervals for depletion levels. Jurisdictions were typically
nations, but in some instances were remote territories considered separately (e.g. U.S.
Pacific Territories, Australian and French Indian Ocean and Pacific territories) to account
for spatial variation. To estimate an overall global depletion level for Grey Reef Sharks
we weighted the jurisdictional values by the percentage of the world’s coral reefs in their
waters and produced a weighted mean depletion. Percentages of coral reefs by
jurisdiction were taken from the “World Atlas of Coral Reefs” (Spalding et al. 2001).
The extinction risk of the global Grey Reef Shark population was assessed by applying
Criteria A (population size reduction) of the IUCN Red List Categories and Criteria over
the past three generation lengths (43.5 years). We assume a reference date of 2018
(when the last Global Finprint samples were collected), making the start of the period for
assessing reduction of Grey Reef Shark over the past three generation lengths (43.5
years) 1974. The depletion estimated with the Global Finprint data do not provide
timeframes, however, pressure on most shark populations increased from approximately
1980 when demand for shark fins increased (Dent and Clarke 2015). For example,
Ferretti et al. (2018) showed that catches of coral reef species in the British Indian
Ocean Territories increased dramatically from the mid-1970s to the early 1980s, and
these are some of the more remote reefs in the world. Thus, we assumed that all, or the
vast majority, of the declines described here have occurred during the past three
generation lengths of this species.
Results
11,615 BRUVS deployments at 254 reefs in 40 jurisdictions (of 29 nations) were used in
the analysis of depletion and Red List status of Grey Reef Shark. In total, Finprint
sampled jurisdictions that covered 88.2% of the world’s coral reefs. Grey Reef Shark
depletion estimates were based on jurisdictions that contained 88.6% of the coral reefs
within its known range. Figure 1 shows the depletion estimate by reef. Consistent levels
of depletion were observed across south and southeast Asia, and the east coast of
Africa. Depletion levels at oceanic islands and reefs in the Pacific were highly variable.
The coral reef area weighted population depletion level for Grey Reef Sharks was 59.2%
(standard error 51.9 – 66.5%). Estimated depletion by jurisdiction are shown in Figure 2.
Assuming that this depletion occurred over the past three generation lengths (43.5
years), this equated to an estimated population reduction of 59.2% (standard error 51.9
– 66.5%) meeting Endangered A2b. The error estimates include only the Endangered
category. Given this, and that the estimate is likely to be an under-estimate of the
reduction, and due to levels of exploitation, we conclude that the most suitable category
for Grey Reef Sharks is Endangered A2bd.
References
Currey-Randall, L. M., Cappo, M., Simpfendorfer, C.A., Farabaugh, N.F., Heupel, M.R.
2020. Optimal soak times for Baited Remote Underwater Video Station surveys of
reef-associated elasmobranchs. PLoS ONE 15:e0231688.
Dent, F., Clarke, S.C. 2015. State of the global market for shark products. FAO Fisheries
and Aquaculture Technical Paper 590:1-187.
Ferretti, F., Curnick, D., Liu, K., Romanov, E.V., Block, B.A.. 2018. Shark baselines and
the conservation role of remote coral reef ecosystems. Science Advances
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Nadon, M. O., Baum, J.K., Williams, I.D., McPherson, J.M., Zgliczynski, B.J., Richards,
B.L., Schroeder, R.E., Brainard, R.E. 2012. Re-creating missing population
baselines for Pacific reef sharks. Conservation Biology 26:493-503.
Sherman, C. S., Chin, A., Heupel, M.R., Simpfendorfer, C.A. 2018. Are we
underestimating elasmobranch abundances on baited remote underwater video
systems (BRUVS) using traditional metrics? Journal of Experimental Marine Biology
and Ecology 503:80-85.
Spalding, M. D., Ravilious, C., Green, E.P. 2001. World Atlas of Coral Reefs. University
of California Press, Berkeley.
Figure 1. Estimated reef level depletion of Grey Reef Sharks from Global Finprint data.
Figure 2. Estimated depletion of Grey Reef Sharks by jurisdiction from Global Finprint
data. Error bars represent standard error. Red solid line indicates the global coral reef
weighted depletion estimate, red dashed lines represent standard error.