Overfishing and Climate Change Elevate Extinction Risk of Endemic Sharks and Rays in the Southwest Indian Ocean Hotspot and Adjacent Waters

Abstract

The southwest Indian Ocean (SWIO) is a hotspot of endemic and evolutionarily distinct sharks and rays. We summarise the extinction risk of the sharks and rays endemic to coastal, shelf, and slope waters of the SWIO and adjacent waters (Namibia to Kenya, including SWIO islands). Thirteen of 70 species (19%) are threatened: one is Critically Endangered, five are Endangered, and seven are Vulnerable. A further seven (10%) are Near Threatened, 33 (47.1%) are Least Concern, and 17 (24.2%) are Data Deficient. While the primary threat is overfishing, there are the first signs that climate change is contributing to elevated extinction risk through habitat reduction and inshore distributional shifts. By backcasting their status, few species were threatened in 1980, but this changed soon after the emergence of targeted shark and ray fisheries. South Africa has the highest national conservation responsibility, followed by Mozambique and Madagascar. Yet, while fisheries management and enforcement have improved in South Africa over recent decades, drastic improvements are urgently needed elsewhere. To avoid extinction and ensure robust populations of the region’s endemic sharks and rays and maintain ecosystem functionality, there is an urgent need for the strict protection of Critically Endangered and Endangered species and sustainable management of Vulnerable, Near Threatened, and Least Concern species, underpinned by species-level data collection and reduction of incidental catch.

Full text

Overshing and Climate Change Elevate Extinction
Risk of Endemic Sharks and Rays in the Southwest
Indian Ocean Hotspot
Riley Pollom (  rpollom@indyzoo.com )
Simon Fraser University, British Columbia
Jessica Cheok
Simon Fraser University, British Columbia
Nathan Pacoureau
Simon Fraser University, British Columbia
Katie S. Gledhill
University of Technology Sydney
Peter M. Kyne
Charles Darwin University
David A. Ebert
Moss Landing Marine Laboratories
Rima W. Jabado
Elasmo Project
Katelyn B. Herman
Georgia Aquarium
Rhett H. Bennett
South African Institute for Aquatic Biodiversity
Charlene Silva
Department of Agriculture, Forestry and Fisheries, South Africa
Stela Fernando
National Institute of Fishery Research
Baraka Kuguru
Tanzania Fisheries Research Institute (TAFIRI)
Robin Leslie
Department of Agriculture, Forestry and Fisheries, South Africa
Meaghen E. McCord
South African Institute for Aquatic Biodiversity
Melita Samoilys
CORDIO East Africa
Henning Winker

Department of Agriculture, Forestry and Fisheries, South Africa
Sean Fennessy
Oceanographic Research Institute
Caroline M. Pollock
IUCN Red List Unit
Cassandra L. Rigby
James Cook University
Nicholas K. Dulvy
Simon Fraser University, British Columbia
Research Article
Keywords: marine conservation, Convention on Biological Diversity, elasmobranch, IUCN Red List Index,
biodiversity indicator, Sustainable Development Goals
Posted Date: November 11th, 2021
DOI: https://doi.org/10.21203/rs.3.rs-984080/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License. 
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Overfishing and climate change elevate extinction risk 1
of endemic sharks and rays in the southwest Indian 2
Ocean hotspot 3
4
Riley A. Pollom*1,2, Jessica Cheok1, Nathan Pacoureau1, Katie S. Gledhill3,4,5, Peter M. 5
Kyne6, David A. Ebert7,8, Rima W. Jabado9, Katelyn B. Herman10, Rhett H. Bennett8,11, 6
Charlene da Silva12, Stela Fernando13, Baraka Kuguru14,15, Robin Leslie12, Meaghen E. 7
McCord8, Melita Samoilys15, Henning Winker12, Sean Fennessy16, Caroline M. Pollock17, 8
Cassandra L. Rigby18, Nicholas K. Dulvy1 9
10
11
1Earth to Ocean Research Group, Department of Biological Sciences, Simon Fraser University, Burnaby, 12
British Columbia, Canada, V5A 1S6 13
14
2IUCN SSC Global Center for Species Survival, Indianapolis Zoo, 1200 West Washington Street, 15
Indianapolis, Indiana, USA 16
17
3Fish Ecology Lab, School of the Environment, University of Technology Sydney, PO Box 123, Broadway 18
2007, NSW, Australia 19
20
4Molecular Breeding and Biodiversity Research Group, Stellenbosch University, Private Bag X1, 21
Stellenbosch 7602, South Africa 22
23
5South African Shark Conservancy, Old Harbour Museum, Hermanus 7200 South Africa 24
25
6Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT 0909, 26
Australia 27
28
7Pacific Shark Research Center, Moss Landing Marine Laboratories, Moss Landing, CA 95039, USA 29
30
8South African Institute for Aquatic Biodiversity, Private Bag 1015, Grahamstown, 6140, South Africa 31
32
9Elasmo Project, PO Box 29588, Dubai, United Arab Emirates 33
34
10Georgia Aquarium, 225 Baker Street Northwest, Atlanta, Georgia, USA, 30313 35
36
11Wildlife Conservation Society, Villa Ifanomezantsoa, Soavimbahoaka, PO Box 8500, Antananarivo 101, 37
Madagascar 38
39
12Department of Agriculture, Forestry and Fisheries; Branch: Fisheries Research and Development, 40
Foretrust Building, Martin Hammerschlag Way, Foreshore, Cape Town, 8000, South Africa 41
42
13National Institute of Fishery Research, PO Box 389, Maputo, Mozambique 43
44
14 Tanzania Fisheries Research Institute (TAFIRI), PO Box 9750, Dar es Salaam, Tanzania 45
46
15CORDIO East Africa, PO Box 10135, Mombasa 80101, Kenya 47
48
16Oceanographic Research Institute, Durban, South Africa 49
50
17IUCN Red List Unit, The David Attenborough Building, Pembroke Street, Cambridge, UK CB2 3QZ 51
52

18College of Science and Engineering, James Cook University, 1 James Cook Drive, Douglas, Queensland 53
4811, Australia 54
55
Abstract 56
57
The southwest Indian Ocean (SWIO) is a hotspot of endemic and evolutionarily distinct 58
sharks and rays. We summarise the extinction risk of the sharks and rays endemic to 59
coastal, shelf, and slope waters of the SWIO (Namibia to Kenya, including SWIO islands). 60
Thirteen of 70 species (19%) are threatened: one is Critically Endangered, five are 61
Endangered, and seven are Vulnerable. A further seven (10%) are Near Threatened, 33 62
(47.1%) are Least Concern, and 17 (24.2%) are Data Deficient. While the primary threat 63
is overfishing, there are the first signs that climate change is contributing to elevated 64
extinction risk through habitat reduction and inshore distributional shifts. By backcasting 65
their status, few species were threatened in 1980, but this changed soon after the 66
emergence of targeted shark and ray fisheries. South Africa has the highest national 67
conservation responsibility, followed by Mozambique and Madagascar. Yet, while 68
fisheries management and enforcement have improved in South Africa over recent 69
decades, drastic improvements are urgently needed elsewhere. To avoid extinction and 70
ensure robust populations and future food security, there is an urgent need for the strict 71
protection of Critically Endangered and Endangered species and sustainable 72
management of all species, underpinned by species-level data collection and bycatch 73
reduction. 74
75
Keywords: marine conservation, Convention on Biological Diversity, elasmobranch, 76
IUCN Red List Index, biodiversity indicator, Sustainable Development Goals. 77
78
79
80
81
82
83
84

Introduction 85
Anthropogenic pressures are mounting in the global oceans, and extinction risk appears 86
to be increasing mainly through overfishing. There are nearly 1,400 marine species 87
threatened globally; over one-quarter of these are threatened due to overfishing, more 88
than double the risk caused by the next most-cited threat1. The international community 89
has formally agreed through the Convention on Biological Diversity that extinctions need 90
to be prevented. Although society failed to meet the 2020 marine targets, namely Aichi 91
Targets 6 (fisheries sustainability), 11 (avoiding extinction risk), and 14 (life under water), 92
work is well underway to establish a more effective post-2020 Global Framework for 93
Biodiversity with goals for 2030 and beyond. The IUCN Red List of Threatened Species 94
provides a robust view of fisheries sustainability and extinction risk, especially when 95
tracked over time through the Red List Index. To date, the only marine Red List Index 96
available to report on the status of marine life is that for the hard stony corals (Family 97
Scleractinia), which are threatened primarily by global climate change2. There is, 98
therefore, a need to expand the Red List Index for marine species that are threatened by 99
overfishing, which is the primary cause of population reductions in the oceans3. 100
101
Marine taxa particularly threatened by fisheries include the sharks and rays (subclass 102
Elasmobranchii), many of which are captured incidentally as bycatch in fisheries targeted 103
at more productive species or are directly targeted4. Sharks and rays represent an ancient 104
lineage of over 400 million years of evolution5. Further, they often function as apex and 105
mesopredators in pelagic, benthic, and nearshore environments6. Understanding how 106
changes in fisheries management are affecting sharks and rays through the Red List 107
Index is crucial to gauging progress towards international biodiversity targets. The first 108
comprehensive assessment of this unique radiation of fishes, published in 2014, 109
estimated that over one-quarter are threatened7; recent work reflecting new information 110
reveals that over one third are in fact threatened4. Globally, some progress has been 111
made with taxonomic and regional species subsets to track change through 112
reassessment and Red List Index development8,9,10. 113
114

The southwest Indian Ocean and the adjacent Benguela Current (hereafter SWIO) have 115
one of the most distinctive shark and ray faunas globally, comprised of high richness and 116
endemicity with a large number of evolutionarily distinct species11,12. This area exhibits a 117
rich diversity of over 250 species from at least 47 families, in part due to the variety of 118
habitats, including warm-water tropical coral reefs, kelp and mangrove forests, and warm-119
temperate and cool-water rocky reefs and sand flats12,13. This biogeography is influenced 120
in the south by the unique ecological conditions created by the confluence of the warm 121
southward-flowing Agulhas Current along the east and south coasts of South Africa and 122
the cold northward-flowing Benguela Current on the west coast of South Africa and 123
Namibia14. 124
125
Coastal regions of the SWIO are under considerable fishing pressure. Approximately one-126
quarter of the human population lives within 100 km of the coast; population growth is 127
among the highest worldwide, with a projected doubling of the human population by 128
205015. Coastal communities in the region are heavily dependent on fisheries as the 129
primary source of protein, livelihoods, and food security. The pressure and scale of 130
artisanal fisheries are significant and could pose an equivalent if not greater threat than 131
industrialized fleets to sharks in the region. For example, in Mozambique, the total small-132
scale fisheries catch is estimated to be as much as three times that of the industrial 133
sector16. Several nations in the SWIO face significant socio-economic challenges and 134
rank in the lowest quartile of the Human Development Index (HDI)17, limiting their ability 135
to manage marine resources effectively. This includes sharks and rays, which are subject 136
to generally unregulated take in parts of the SWIO, particularly in artisanal fisheries. 137
138
Here, we provide an assessment of extinction risk status of 70 sharks and rays endemic 139
to the SWIO. Specifically, we: (1) assess the extinction risk of these sharks and rays using 140
the IUCN Red List Categories and Criteria, (2) compare the change in extinction risk over 141
~40 years against a retrospective assessment for 1980 using the Red List Index, and (3) 142
determine the countries with the most significant national conservation responsibility. 143
Finally, we propose some general policies that, if implemented, will help to safeguard 144
shark and ray populations in the SWIO. 145

146
RESULTS 147
148
Taxonomic diversity and species richness 149
150
This study comprised 70 endemic species (38 sharks and 32 rays, the latter comprising 151
guitarfishes, electric rays, and skates) from 7 orders, 20 families, and 39 genera (Table 152
1). Families with the highest species richness were Rajidae (hardnose skates, n = 12, 153
17.1% of all species) and Pentanchidae (deepwater catsharks, n = 15, 21.4%), 154
collectively comprising more than a third (38.5%) of the regional endemic fauna. Species 155
richness was greatest along the South African and southern Mozambican coastlines, with 156
a maximum number of 19 species occurring in each country (Fig. 1a). The richness of 157
threatened (Critically Endangered, CR; Endangered, EN; or Vulnerable, VU) shark and 158
ray species also suggested an inverse latitudinal gradient (n = 13; Fig. 1b). The high 159
concentration of threatened endemics in South Africa is driven by the threatened sharks 160
(n = 8), whereas threatened rays (n=5) were more disparately distributed across the 161
region (Fig. 1c & d). 162
163
Taxonomic patterns in extinction risk 164
165
Nearly one-fifth (n = 13, 19%) of assessed endemic sharks and rays in the region are 166
threatened with extinction (Table 1). One species, the Shorttail Nurse Shark 167
(Pseudoginglymostoma brevicaudatum), is CR and at an extremely high risk of extinction. 168
It is assessed under Criterion A2cd as it has undergone a suspected population reduction 169
of >80% over the past three generations (30 years) due to a decline in habitat quality and 170
actual and potential levels of exploitation. Five species (7%) are EN and face a very high 171
risk of extinction, and seven species (10%) are VU, facing a high risk of extinction (Table 172
1). A further seven species (10%) are Near Threatened (NT), indicating they may become 173
threatened soon if countries don’t implement management and conservation. 174
175
Most threatened and NT species were assessed as such using Criterion A (population 176
reduction). For example, the Tiger Catshark (Halaelurus natalensis) declined by 39% in 177
the commercially fished area in the last 27 years, consistent with a population reduction 178

of 56.5% (CI: -97.3, 83.3) in 3 GL (60 years); however, there has been an expected range 179
shift away from trawl grounds reducing catchability in the surveys, and experts agreed 180
that the appropriate Category for this species is VU. The Twin-eye Skate (Raja ocellifera) 181
declined by 65.5% in the commercially fished area in the last 27 years, consistent with a 182
population reduction of 65.5% (CI: -89.2, -17.1) in 3 GL (27 years) and is EN (Fig. 2). 183
184
There were two cases of small-range species, found in few locations and undergoing a 185
continuing decline, which met threatened categories under criterion B: the Natal Shyshark 186
(Haploblepharus kistnasamyi) and the Flapnose Houndshark (Scylliogaleus quecketti), 187
are assessed as VU. 188
189
Nearly half of species showed slight increases or did not decrease substantially enough 190
to meet the thresholds to be assessed as threatened or NT and were thus assigned a 191
status of Least Concern (LC; n = 33, 47%) (Table 2). For example, the Softnose Skate 192
(Bathyraja smithii) occurs primarily in Namibia, where fishing pressure is low. The 193
Whitecheek Lanternshark (Etmopterus alphus) occurs between 472 and 792 m depth 194
along a narrow strip of the Mozambique coastline, and it has refuge at depth in the 195
absence of fishing deepwater fishing activities. There were eight species for which indices 196
of abundance were available and revealed either stability or an increase in population 197
index (Fig. 2, left column) and these are assessed as LC. 198
199
Finally, almost a quarter of species are Data Deficient (DD; n = 17, 24%) because there 200
is insufficient information to accurately assess their extinction risk (i.e., data are so sparse 201
for these species that assessors were not able to determine whether they are CR, LC, or 202
somewhere between). Three of the six species of guitarfishes from the family 203
Rhinobatidae require further information to assign a risk category. One of five endemic 204
scyliorhinid catsharks and three of 15 pentanchid catsharks are DD. There are fewer data 205
available regarding the status of rays overall, and nearly one-third are DD (10 of 32 206
species). Three species previously assessed as DD are now LC due to new information: 207
the Saldanha Catshark (Apristurus saldanha), the Black Legskate (Indobatis ori), and the 208
Whitespotted Smoothhound (Mustelus palumbes). 209

210
All changes in Red List status since the previous assessments are non-genuine changes 211
except for the Shorttail Nurse Shark (which had its population further reduced since the 212
2005 assessment). These non-genuine changes are due to new information becoming 213
available since the previous assessments. This new knowledge can be used to 214
retrospectively correct previously published assessments for the development of a Red 215
List Index. Thus, the newly stated retrospective statuses can be considered more 216
accurate than the previously published assessments (Table 1). 217
218
Key threats 219
Red List assessments for all 13 threatened and seven NT species reported ‘Biological 220
Resource Use’ and, more specifically, ‘Fishing and Harvesting Aquatic Resources’ as 221
threatening processes, while other threats (habitat loss and degradation, pollution) 222
caused reductions or a continuing decline in population size in fewer species (Fig. 3). We 223
include climate change in the threat rationale of seven threatened and NT species. 224
Although not the leading cause of population reductions, it has induced a significant 225
distributional shift in the populations of six of these seven species18 (grey bar, Fig. 3). 226
Coastal development and pollution contributed to localized extinction risk for three 227
species, but overfishing is the primary threat for all of them. 228
229
Overfishing is the main threat 230
Overfishing is the primary threat to all threatened elasmobranchs in the SWIO region 231
through targeted and incidental catches (bycatch), including commercial, recreational, 232
and artisanal fisheries using fishing gears such as gillnets, longlines, handlines, trawls, 233
and seine nets. Furthermore, all 20 threatened and NT species are exposed to overfishing 234
through incidental catches, where fisheries target other species such as teleost fishes or 235
shrimps but catch and retain other valuable species such as sharks and rays. 236
237
Overfishing is compounded by climate change 238
There are two impact pathways by which climate change may be elevating extinction risk 239
of sharks and rays. Firstly, the increasing frequency and severity of coral bleaching are 240

implicated in the elevated extinction risk of the Shorttail Nurse Shark. This tropical shark 241
has declined significantly over the past 15 years, resulting in a genuine change in status 242
from VU to CR. This population reduction is suspected to be caused by a combination of 243
overfishing, destructive fishing practices, and a continuing decline in habitat quality due 244
to coral bleaching and rising sea temperatures. Live capture for the aquarium trade may 245
further exacerbate risk. Secondly, there has been a north-easterly shift in the distribution 246
of thermal habitat across the southern Cape of South Africa. This shift has resulted in 247
simultaneous northeastward shifts of many teleost and elasmobranch species 248
distributions toward the narrower shelf area off the Eastern Cape and KwaZulu-Natal18. 249
Three species undergoing notable range shifts are the Lesser Guitarfish (Acroteriobatus 250
annulatus), Bluntnose Spurdog (Squalus acutipinnis), and Twin-eye Skate (Raja 251
ocellifera) (Fig. 4). 252
253
In addition to fishing pressure and climate change, habitat degradation from coastal 254
development and pollution further exacerbates overfishing for two South African endemic 255
catsharks. The Brown Shyshark (Haploblepharus fuscus) and the Natal Shyshark both 256
inhabit nearshore waters at depths of less than 50 m. They are endemic to South Africa 257
near several large urban centers (Port Elizabeth, East London, and Durban) and are thus 258
subject to the associated localised urban development and pollution. 259
260
The Red List Index and national conservation responsibilities 261
262
Almost all species were retrospectively assessed as LC (n = 52) or DD (n = 17) in 1980 263
(Table 1), except one NT species (Natal Sleeper Ray Heteronarce garmani), resulting in 264
a regional Red List Index (RLI) value of 0.996 (where a value of 1 represents all assessed 265
species being LC; Fig. 5a). The regional RLI decreased slightly to 0.917 by 2005 and 266
further to 0.849 in the most recent assessment (2020) presented here. This decreasing 267
trend in RLI results from the increased numbers of species in threatened and NT 268
categories by 2005 and 2020 (13 and 20, respectively; Table 1). When disaggregating 269
the RLI down to country-level, the most significant decline in RLI is from 1980 to 2005 in 270
Madagascar (a decline from 0.999 to 0.672; Fig. 5b). Between 2005 and 2020, the 271

greatest decline in country-level RLI occurred in Madagascar (0.672 to 0.558; Fig. 5c). 272
Nine range countries bear some responsibility for conserving the 70 endemic SWIO 273
species that have been assessed using the IUCN Red List Categories and Criteria (Table 274
3). Consistent with the inverse latitudinal richness trend, South Africa had the highest 275
national conservation responsibility (NCR) of all nine range countries (NCR = 1), followed 276
by relatively high responsibilities for Mozambique (NCR = 0.442) and Madagascar (NCR 277
= 0.407; Fig. 6). Collectively, these three countries represent 93% of all conservation 278
responsibility in the region. 279
280
Discussion 281
Here, we provide the first comprehensive reassessment of extinction risk in sharks and 282
rays that are endemic to waters of the SWIO. Of 70 species herein assessed for the IUCN 283
Red List, nearly one-fifth are threatened and thus have a high to extremely high risk of 284
extinction (1 CR, 5 EN, 7 VU). Despite a lack of data from parts of the region, it is clear 285
that excessive fishing activity and limited management capacity are substantial barriers 286
to ensuring robust shark and ray populations into the future. A further quarter of species 287
are DD and could potentially be listed as threatened as additional data become available. 288
Furthermore, this assessment of endemic species belies the overall status of sharks and 289
rays in the region. If we include the wider-ranging coastal, pelagic, and deepwater 290
species, there are 75 additional globally threatened sharks and rays that occur in the 291
region, including 26 that are EN and 12 that are CR. Including these groups would also 292
add another 21 DD species. We next (1) compare these findings to threat patterns globally 293
and in other regions, and identify measures to (2) avoid extinctions, (3) ensure 294
sustainability, (4) maintain robust functional populations, (5) drive down data deficiency 295
gaps, and (6) cope with prevalent and emerging threats. 296
297
The percentage of threatened endemic species in this region (19%) is considerably lower 298
than that observed globally (37%)1. At the regional level, 42% of species (n=50) are 299
threatened or predicted to be threatened in the Northwest Atlantic and two-thirds of 300
species (67%, n=48) in the Mediterranean Sea9. A regional assessment (including all 301
species, not only endemics) of the Arabian Sea and its adjacent waters region found 302

50.9% of species are threatened19. Although we find extinction risk in SWIO to be lower 303
than in these regions, many of the most threatened families found in this region are not 304
included in this assessment, including the sawfishes, wedgefishes, hammerheads, and 305
thresher sharks 8,10,20,21, and if non-endemics are included, there are 82 of 227 species 306
(36% threatened). In any case, there are at least six endemic species that are endangered 307
(EN or CR) and require urgent conservation action to prevent further declines and 308
extinction. 309
310
The most severe and prevalent threat to the endemic species assessed in this region is 311
heavy fishing pressure and bycatch mortality, resulting in population reductions for 312
threatened and NT species22. This threat is particularly problematic for species inhabiting 313
shallow inshore and continental shelf waters to approximately 200 m depth, such as the 314
Shorttail Nurse Shark (the only CR species), and the Happy Eddie Catshark 315
(Haploblepharus edwardsii), Greyspot Guitarfish (Acroteriobatus leucospilus), and Twin-316
eye Skate (all EN). In the specific case of the Shorttail Nurse Shark, extensive landings 317
surveys in Madagascar (2007–2012)23 have not recorded any individuals, and only one 318
individual has been observed there in 270 hours of baited remote underwater video 319
(BRUV) surveys24. Sightings of this species have also not been reported from extensive 320
visual census surveys in Tanzania, Mozambique, or Madagascar (2009–2015)25, 321
although since this assessment, its range has been extended to include Mozambique26. 322
323
We recommend that governments implement management interventions for CR and EN 324
species without delay. These interventions should involve strict prohibitions on landings 325
where they are not yet in place and capacity for enforcement of laws. Highly impactful 326
fishing gears, such as large-mesh (shark-directed) gillnets and longlines, should be 327
regulated, and legislation against destructive fishing practices such as reef nets and blast 328
fishing, which damage habitats such as coral reefs, should be enforced to ensure the 329
continued presence of these threatened species in the wild. If threats are not mitigated 330
rapidly, species such as the Shorttail Nurse Shark could become extinct in the very near 331
future. This situation could follow that of at least one, possibly two, sawfish species which 332
are already considered locally extinct in South Africa (Largetooth Sawfish Pristis pristis 333

and Green Sawfish P. zijsron). Although they are the first rays protected in the region, 334
protection was implemented too late, two years before the last sighting of a sawfish27. 335
336
For species in this region that are VU due to small geographic range sizes, occurring in 337
few locations, and inferred to have declining populations (e.g., Flapnose Houndshark 338
Scylliogaleus quecketti, Natal Shyshark), there is an opportunity to implement spatial 339
closures of important habitat to complement catch and fishing effort reduction 340
approaches. Establishing closures will require the identification of overlap between the 341
existing protected area network and key habitat features and understanding movement 342
behaviour and potential aggregation sites28,29. Marine Protected Areas might prove to be 343
a suitable approach for conserving threatened endemic sharks30. Even a modest 344
expansion of the protected areas network has significant potential to contribute to the 345
conservation of these species31. 346
347
Madagascar, South Africa, and Seychelles are the only nations to implement a National 348
Plan of Action for the Conservation and Management of Sharks, although most countries 349
in the region are developing these32,33. From our analyses, Mozambique and Madagascar 350
had the most significant national conservation responsibility after South Africa, with these 351
three nations representing 93% of all responsibility in the region. These should be priority 352
nations to effectively implement National Plans of Action to set the stage for sustainable 353
catch of species in their national waters. Further, such plans should include legislative 354
mechanisms for protection of CR and EN species, explicit actions on catch limits for VU 355
or NT species, strategies for managing bycatch in fisheries and, where needed, actions 356
on protecting habitats or areas known as important during critical life stages32. Increased 357
efforts to accurately assess fishing pressure are also paramount. Underreporting and 358
discrepancies in fisheries data are prevalent in reports provided to Regional Fisheries 359
Management Organisations (RFMOs) and the Food and Agriculture Organization of the 360
United Nations (FAO). Furthermore, where data are collected, discards are not reported, 361
and post-release mortality is unknown, even in South Africa, where data collection is 362
relatively robust32. 363
364

Encouragingly, almost half of the species assessed here are LC, which means their 365
populations are stable or declining slowly such that population reduction thresholds are 366
not triggered. In many cases, these species are not exposed to the pressures to which 367
threatened species are. For example, the geographic or bathymetric ranges of some 368
species mean they are sparsely or never fished. Even when such a species is fished, 369
resilience to this pressure is indicated by relatively stable population trends over time. For 370
example, the Whitespotted Smoothhound Mustelus palumbes has shown a modest 371
estimated increase of 8% over 27 years across the South African hake trawl grounds (Fig. 372
2). Whitespotted Smoothhounds are caught in trawl, line, and demersal shark longline 373
fisheries, but given their increase in abundance, they appear robust to moderate levels of 374
fishing activity (< 50 t per annum), although further management measures will be needed 375
to ensure sustainability if catches increase. Some other targeted or retained bycatch 376
species (e.g., Bluntnose Spurdog, Slime Skate Dipturus pullopunctatus) also exhibit some 377
level of resilience to fishing pressure. However, it is essential that these LC species be 378
monitored in terms of abundance and catch to maintain robust, ecologically functional 379
populations that yield ecosystem services to humanity and contribute to food security. 380
381
A quarter of the species assessed had insufficient data available for an accurate 382
assessment and were evaluated as DD. Many countries are still reporting catches as 383
“sharks”, and species-level monitoring of rays has been particularly neglected in the 384
region. Catch reconstructions reveal serious discrepancies where reported catches are 385
far lower than the reconstructions, around 200% in Madagascar and Mauritius34,35, and 386
>75% in Tanzania36. While there has been progress in assessing the species composition 387
and monitoring of fisheries, there remains a lack of species-specific population trend and 388
time-series data, particularly in countries other than South Africa. The lack of species-389
specific fisheries data means that declines in sensitive species (e.g., angelsharks, 390
guitarfishes) could go unnoticed27,37. More information may reveal other species that are 391
threatened. Further, more detailed information will be needed to provide effective spatial 392
planning and fisheries management while minimizing impacts and conflicts with resource 393
users. 394
395

Emerging threats in this region include the expansion of deepwater fisheries and climate 396
change impacts on sharks and rays. Two deepwater species affected by fishing pressure 397
are EN catsharks: the Honeycomb Izak Catshark (Holohalaelurus favus) and the African 398
Spotted Catshark (H. punctatus), which occur in waters greater than 200 m. Despite the 399
potential for refuge at depth, populations of these deepwater catsharks are suspected of 400
having undergone reductions of more than 50% over the past three generations due to 401
deepwater trawl and longline fisheries operating within their ranges. These declines will 402
continue if deepwater fisheries are further developed in the absence of management38. 403
We caution that as deepwater fisheries increase, particularly in Mozambique, 404
Madagascar, and Tanzania, including fishing by distant water nations, many of the 405
deepwater LC species may be at greater risk of extinction39. Monitoring fisheries 406
expansions into deeper or more remote waters overlapping with the geographic ranges 407
of deepwater LC species will be important (along with species-level catch data). 408
409
Although declines in VU species are mainly due to fishing, one of these species, the Tiger 410
Catshark is unique in that it has undergone a population reduction (including a reduction 411
in area of occupancy) that is at least partially related to an ecological shift in currents due 412
to climate change18,40. For this catshark, mortality due to fisheries does not appear 413
substantial enough to be the only factor causing this reduction, highlighting the 414
importance of considering climate change in future Red List assessments of sharks and 415
rays. As species distribution models for sharks and rays become available41, future 416
assessments could consider using climate projections. Trait-based approaches are 417
already available to evaluate the potential risk of climate change and will be helpful for 418
future reassessment42,43. 419
420
Conclusion 421
Here, we find that 13 of the 70 (19%) endemic shark and ray species in the SWIO are 422
threatened with an elevated risk of extinction. There is thus a need for a collaborative 423
regional improvement in shark and ray conservation to reduce risk for these endemic 424
species. However, this limited species sample belies the actual risk to the elasmobranch 425
fauna in the SWIO region, as some of the most highly threatened cosmopolitan 426
elasmobranch groups, including sawfishes, wedgefishes, and hammerhead sharks, are 427

not endemic to this region and were thus not included in this study (the vast majority of 428
which are CR globally). There is a great urgency to act to avoid further extinctions, ensure 429
sustainability, maintain robust functional populations, reduce data deficiency, and secure 430
livelihoods and food security for coastal people. On-going monitoring and data collection 431
at the species level are essential, particularly for threatened and NT species. Species-432
specific annual fisheries-independent population monitoring needs to take place. In the 433
absence of such data, species-specific monitoring of catches and landings (taking into 434
account fishing effort) can provide a reliable index of the trend in abundance. Although 435
there has been an improvement in fisheries management in South Africa, this has not yet 436
resulted in improved conservation status, but it may well have maintained populations 437
and prevented more severe declines than those observed. Many other countries in the 438
region have a long way to go to effectively monitor, manage, and protect their shark and 439
ray species and play their part to ensure the global viability of elasmobranch fauna. 440
Nations are currently negotiating new biodiversity and sustainability targets to bend the 441
curve on biodiversity to halt and reverse declines in populations and minimize 442
extinctions44,45. This study provides evidence that extinction risk has increased in the 443
SWIO region due to overfishing and climate change and that action is needed to bend the 444
curve for elasmobranchs there. 445
446
Methods 447
We first describe the geographic and taxonomic scope of the regional endemic 448
elasmobranch extinction risk assessment, followed by the application of the IUCN Red 449
List Categories and Criteria, species mapping and spatial analyses, and the calculation 450
of a Red List Index. 451
452
Geographic and taxonomic scope. We focus on the assessment of extinction risk in 453
endemic sharks and rays of the SWIO that inhabit the continental and insular shelves and 454
slopes off Africa from the Angola–Namibia border, around the Cape of Good Hope, and 455
east and north to the Kenya–Somalia border. The region also includes Madagascar and 456
the islands of the southwest Indian Ocean. The geographic scope thus comprised nine 457
range countries: Namibia, South Africa, Mozambique, Tanzania, Kenya, Madagascar, 458

Comoros, Seychelles, and Mauritius). The Namibia–Angola border was chosen as the 459
western boundary of the region because of the oceanographic and faunal break at the 460
interface between the Benguela and Guinea Currents14. The Kenya–Somalia border was 461
chosen as the northeastern-most limit of this assessment as it abuts the boundary of the 462
Arabian Sea and its adjacent waters region, the subject of a separate recent extinction 463
risk assessment19. Reunion is not included here because no regionally endemic sharks 464
or rays exist there. 465
466
A comprehensive list of all elasmobranch species known to occur in the region was based 467
on the work of Ebert and van Hees46. We evaluated 70 shark and ray species considered 468
endemic to the region and did not include those that inhabit wider-ranging coastal, 469
pelagic, or deepwater areas. For nomenclature and taxonomy, we followed the online 470
electronic version of the Catalog of Fishes47 for sharks and Rays of the World48 for rays. 471
472
Application of the IUCN Red List Categories and Criteria. We assessed species at the 473
global level by applying the IUCN Red List Categories and Criteria (Version 3.1) and the 474
associated guidelines49,50. Existing data and information on each species, including 475
taxonomy, geographic distribution, population trends, habitat and ecology, significant 476
threats, and conservation measures were compiled by the IUCN Species Survival 477
Commission Shark Specialist Group (SSG) and regional experts. Information was 478
obtained from published peer-reviewed scientific literature, government reports, 479
unpublished fisheries data, grey literature, anecdotal information, and expert 480
observations and data. 481
482
A four-day workshop was convened at the National Research Foundation’s South African 483
Institute for Aquatic Biodiversity (SAIAB) in Grahamstown in April 2018, facilitated by the 484
SSG. Workshop participants included regional fisheries, biodiversity, and taxon-specific 485
experts, including representatives of non-governmental organizations, fisheries agencies, 486
and government staff from countries across the region. During the workshop, participants 487
shared data, reports, and anecdotal information for each species and threats from the 488
region. This group systematically assessed 70 species against each of five quantitative 489

IUCN Red List Criteria A–E: A, population reduction; B, geographic range; C, small 490
population size and decline; D, very small or restricted population; and, E, quantitative 491
analysis50. 492
493
Each species was assigned to one of the following Red List Categories: Extinct (EX), 494
Extinct in the Wild (EW), Critically Endangered (CR), Endangered (EN), Vulnerable (VU), 495
Near Threatened (NT), Least Concern (LC), or Data Deficient (DD) (for definitions, see49). 496
The categories CR, EN, and VU are collectively termed ‘threatened’ categories. A species 497
qualifies for one of the three threatened categories by meeting the quantitative threshold 498
for that category within one of the five criteria (A–E). The NT category is applied to species 499
that come close to, but do not meet, a threshold for a threatened category. The LC 500
category is applied to species that have been assessed against the Red List criteria but 501
do not qualify for CR, EN, VU, or NT. There were two ways species were assessed as 502
LC: i) data show that the species has a stable or increasing population size over 3 GL, or 503
ii) because they inhabit remote or deepwater areas that are not subject to threats and 504
therefore it can be inferred that the population is not undergoing reduction. The DD 505
category is applied to a species when there is inadequate information to make a direct or 506
indirect assessment of the risk of extinction based on its distribution and/or population 507
status50. The Red List assessment process includes a structured approach to classifying 508
threats into 11 primary classes, such as human intrusions and disturbance, pollution, 509
biological resource use, and climate change and severe weather51 and appropriate 510
threats were selected for each species. 511
512
Red List Criterion A uses a set of quantitative thresholds to classify population reduction 513
scaled over three generation lengths (3 GL)49. One primary source of long-term 514
abundance data for 17 species was demersal research trawl surveys conducted in South 515
Africa during summer along the west coast and autumn and spring along the south coast 516
by the Fisheries Branch of the South African Department of Agriculture, Fisheries and 517
Forestry52. All datasets underwent extensive checks before analyses, and their reliability 518
was reviewed by experts during the workshop. Annual density estimates (kg per nm2 area 519
swept) were estimated using the geostatistical delta-generalized linear mixed model 520

(GLMM) developed by Thorson et al.53. Applications of the delta-GLMM to South African 521
trawl survey index standardization have been described elsewhere18,54 and the spatial 522
patterns in density over time are shown for species for which there were data available. 523
Although demersal trawl surveys commenced in 1984, we only considered the period 524
from 1991 onwards due to improvements in species identification following the initial 525
survey years. For the analysis, each survey season was treated as an individual index i. 526
To analyze trend data, we used a Bayesian population state-space model designed 527
specifically for IUCN Red List assessments (Just Another Red List Assessment, 528
JARA)20,55, which builds on the Bayesian state-space tool for averaging relative 529
abundance indices56 and is available open-source on GitHub (www.github.com/henning-530
winker/JARA). Each relative abundance index (or time-series) was assumed to follow an 531
exponential growth defined through the state process equation: 532   533
where  is the logarithm of the expected abundance in year t, and  is the normally 534
distributed annual rate of change with mean , the estimable mean rate of change for a 535
time-series, and process variance . We linked the logarithm of the observed relative 536
abundance indices to the logarithm of the true expected population trend using the 537
observation equation (eqn. 16) from Winker et al.56. We used a non-informative normal 538
prior for , and an approximately uniform prior on the log scale for the process 539
variance 
. 540
541
We ran two Monte Carlo Markov chains for each dataset with different initial values. Each 542
Markov chain was initiated by assuming a prior distribution on the initial condition centred 543
around the first data point in each abundance time-series. In each chain, the first 1,000 544
iterations were discarded (‘burn-in’), and of the remaining 10,000 iterations, 5,000 were 545
selected for posterior inference (‘thinning rate’ = 2). Thus, posterior distributions were 546
estimated from 20,000 iterations. Convergence was diagnosed using Geweke’s 547
diagnostic57 with thresholds of p = 0.05 via the ‘coda’ library (v0.19-1)58. Analyses were 548
performed using R Statistical Software v3.5.059 and via the interface from R (‘R2jags’ 549
package v0.5-7)60 to JAGS (‘Just Another Gibbs Sampler’ v4.3.0)61. The Highest 550
Posterior Density interval was used as the interval estimator of 95% credible intervals. 551

552
While there are many demographic approaches to calculating generation length50, these 553
are generally data-intensive and have been applied to relatively few sharks and rays. 554
Therefore, to derive generation length (GL), a simple measure that requires only female 555
age-at-maturity and maximum age was used: 556
GL = maximum age+([maximum age – age-at-maturity]*z)), 557
where z depends on the mortality rate of adults and is typically around 0.3 for mammals 558
but we assume z is 0.5 to account for the truncation of age-structure due to overfishing 559
and underestimateion of age in chondrichthyans. This value represents the median age 560
of parents of the current cohort. To derive population reduction over 3 GL, the 561
proportional decline over the x years of available catch rate or landings datasets was 562
calculated, and this was used to calculate annual proportional change, which was then 563
scaled across the 3 GL period. 564
565
If a species qualified for a change in conservation status from a previously published 566
assessment (a ‘downlisting or ‘uplisting’ in status), changes were classified as either 567
Genuine or non-genuine changes. Genuine changes are assigned due to actual 568
increases or decreases in the level of extinction risk that a species faces based on change 569
in the threatened processes. In contrast, non-genuine changes are assigned due to new 570
information, taxonomic changes, and/or errors in the application of criteria or incorrect 571
data used in the previous assessment50. 572
573
Assessments were drafted after the workshop's conclusion and the category and criteria 574
and the assessment rationale sections were initially sent to all workshop participants to 575
solicit feedback before circulation to the full membership of the SSG comprising 177 576
members from 55 countries for their input. Each assessment was peer-reviewed by at 577
least two experts with knowledge of the species and the IUCN Red List categories and 578
criteria. Completed assessments were submitted to the IUCN Red List Unit in Cambridge, 579
UK, for final review and publication on the IUCN Red List1. 580
581

Species distribution mapping. Draft species range maps were primarily based on the 582
original maps published in the previous Red List assessments augmented by revised 583
distributions from those in Sharks of the World62 and Rays of the World48 and maps were 584
reviewed and validated by regional experts and taxonomists. The final distribution maps 585
were prepared using ArcGIS 10.6. The ranges of each species were clipped to their 586
known depth range based on the highest-resolution bathymetry dataset available across 587
the region (15 arc seconds)63. One species, Kaja’s Sixgill Sawshark (Pliotrema kajae), 588
was excluded from all spatial analyses, as it was not possible to map its range due to a 589
lack of data. 590
591
Red List Index. We derived retrospective assessments for two earlier periods, 2005 and 592
1980 (with the current assessments set at 2020), in order to calculate a Red List Index 593
(RLI)64. Before this current reassessment, all except 15 newly described species had 594
assessments published on the IUCN Red List. All changes in Red List category except 595
one were considered non-genuine changes due to new information50. In other words, if 596
what is currently understood was known during the previous assessments, the assigned 597
status of those species would likely have been different. For example, if a species was 598
assessed as DD in 2005 but is now LC in the current assessment, the older status would 599
be retrospectively corrected to be LC. For species assessed as NT or in one of the 600
threatened categories, ‘backcasting’ was undertaken by retrospectively assigning status 601
based on current understanding of the spatial and temporal pattern of coastal human 602
population growth, the development of general fishing pressure, the availability of fishing 603
gear capable of capturing sharks and rays, and the development of the international trade 604
demand for shark and shark-like ray fins7. 605
606
The RLI for all 70 endemic species was also disaggregated to each of the nine SWIO 607
range countries. The disaggregation of RLI to country level, which considers the relative 608
proportions of all species’ ranges occurring in each country, allows a more nuanced 609
understanding of which range countries contribute most to the change in Red List 610
statuses across all species and the region. This is an important consideration because 611
different range countries can potentially contain highly differing proportions of an 612

individual species’ distribution range, impacting driving or preventing extinction risk in this 613
species. For calculating country-specific RLI values, the equation is amended such that: 614
 


 615
where  is the year of assessment,  is the country and  is the Red List threat at 616
year  for each species, multiplied by 
, representing the proportion of each species’ 617
total range found within the Exclusive Economic Zone (EEZ) of each country65. This is 618
summed across all species that occur in each country’s EEZ and divided by the maximum 619
threat score (), multiplied by the sum of proportional species’ ranges. The final 620
country-specific RLI value is derived by subtracting from 1. Higher RLI values indicate 621
fewer negative changes in Red List status across species and vice versa (as with the 622
global RLI). Finally, we calculated national conservation responsibilities for all range 623
countries, which are based on the sum of all threat scores across species within a country, 624
multiplied by each of the species’ proportional ranges for that country45. 625
626
Acknowledgements 627
The assessment workshop was graciously hosted by the South African Institute for 628
Aquatic Biodiversity (SAIAB), and organizers are particularly indebted to Angus Paterson 629
and Sally Schramm for their support during the workshop. The authors would like to 630
acknowledge Kerry Sink and Megan van der Bank from SANBI for attending the workshop 631
and providing valuable insight. Tracey Fairweather from South Africa’s Department of 632
Agriculture, Forestry and Fisheries (now Department of Environment, Forestry and 633
Fisheries) and Gareth Jordaan and Bruce Mann from the Oceanographic Research 634
Institute of South Africa (ORI) provided data and insight into assessments. Benedict Kiilu, 635
Andrew Temple, Jeremey Kiszka, and Sabine Wintner also provided input into species 636
assessments. Wade J. VanderWright provided assistance with data collation. 637
638
Author Contributions 639
RAP, PMK, and NKD designed the study and organized and led the workshop. RAP, 640
KSG, and NKD wrote the manuscript. JC, NP, and NKD analyzed the data and produced 641

the figures. KSG, DAE, RWJ, KBH, RHB, CDS, SF, BK, RL, MEM, MS, and HW attended 642
the workshop and provided valuable insight into Red List assessments. KBH provided 643
mapping support. SF provided data and insight electronically. CLR and CMP reviewed 644
Red List assessments. All authors reviewed the manuscript and provided critical insight. 645
Funding 646
This contribution is part of the IUCN SSC Shark Specialist Group’s Global Shark Trends 647
Project and was funded by the Shark Conservation Fund, a philanthropic collaborative 648
that pools expertise and resources to meet the threats facing the world’s sharks and rays. 649
The Shark Conservation Fund is a project of Rockefeller Philanthropy Advisors. 650
651
PMK was supported by the Marine Biodiversity Hub, a collaborative partnership 652
supported through funding from the Australian Government’s National Environmental 653
Science Program (NESP). 654
655
DAE was supported by the South African Institute for Aquatic Biodiversity, Save Our Seas 656
Foundation, and the South African Shark and Ray Protection Project, implemented by the 657
WILDTRUST and funded by the Shark Conservation Fund. 658
659
RHB was supported by a grant (FED/2016/382-097/SVC-019 BIS) from the Indian Ocean 660
Commission 661
662
CDS and HWK were supported by DAFF SA and funded by the Marine Living Resources 663
Fund 664
665
NKD was supported by Discovery and Accelerator grants from Natural Science and 666
Engineering Research Council and a Canada Research Chair. 667
668
The National Research Foundation South African Institute for Aquatic Biodiversity 669
provided in-kind support for the assessment workshop. 670
671

Figure Captions 672
673
Figure 1. Endemic species richness of (a) sharks and rays (n = 70), (b) threatened (Critically Endangered, Endangered or 674
Vulnerable, according to the IUCN Red List Categories) sharks and rays (n = 13), (c) threatened sharks (n = 8), and (d) 675
individual distributions of threatened rays (n = 5) across the SWIO region. 676
677
Figure 2. Species population time-series (expressed as a proportion) modelled from demersal research trawl surveys in 678
commercially fished areas (line) and shore-based research angling surveys (dashed line) off the west and south coasts of 679
South Africa. Lines and dashed lines denote the mean, and shaded regions represent the 95% credible intervals. Time-680
series are divided by their initial values and start at one. Silhouette colours indicate Red List status: dark green is Least 681
Concern, light green is Near Threatened, yellow is Vulnerable, orange is Endangered. 682
683
Figure 3. Count of reported threat categories in the 20 threatened (Critically Endangered, Endangered and Vulnerable) and 684
Near Threatened SWIO shark and ray species. 685
686
Figure 4. Spatial and temporal change in density (ln kg per km-2) between 20°E and 27°E longitude for 1991 and 2016 for 687
(a) Lesser Guitarfish (Acroteriobatus annulatus; Vulnerable), (b) Bluntnose Spurdog (Squalus acutipinnis; Near 688
Threatened), and (c) Twin-eye Skate (Raja ocellifera; Endangered). 689
690
Figure 5. Red List Index (RLI) for Sub-equatorial Africa endemic sharks and rays (n = 70). (a) The decline in RLI across 691
assessment years 1980, 2005, and 2020. Country-specific declines in RLI from (b) 1980—2005 and (c) 2005—2020. 692
Calculations of RLI exclude Data Deficient (DD) species. 693
694
Figure 6. National conservation responsibility of nine range countries for all 70 endemic shark and ray species in the SWIO 695
region for which Red List Status is known. 696
697
698
699
700
701
702
703
704

Tables 705
Table 1. Original, retrospectively backcasted (for years 1980 and 2005), and current assessments of IUCN Red List categories for all 706
endemic shark and ray species of the sub-equatorial Africa region (n = 70). Differences in original past assessments and backcast 707
assessments arise due to new information about a species’ status from the better informed, more recent assessments. (CR, Critically 708
Endangered; EN, Endangered; VU, Vulnerable; NT, Near Threatened; LC, Least Concern; DD, Data Deficient). Species marked with 709
* have been recently described for which previously published assessments do not exist. 710
711
ORDER: Family
Common name
Original IUCN Red List status
Red List status for RLI
Species name
2000
Mid-2000s
Late-2010s
1980
2005
2020
SHARKS
PRISTIOPHORIFORMES:
Pristiophoridae
Sawsharks
Pliotrema annae*
Anna’s Sixgill Sawshark
DD2020
DD
DD
DD
Pliotrema kajae*
Kaja’s Sixgill Sawshark
DD2020
DD
DD
DD
Pliotrema warreni*
Warren’s Sixgill
Sawshark
LC2019
LC
LC
LC
SQUATINIFORMES: Squatinidae
Angel Sharks
Squatina africana
African Angelshark
DD2004
NT2017
LC
LC
NT
SQUALIFORMES: Centrophoridae
Gulper Sharks
Centrophorus seychellorum
Seychelles Gulper Shark
DD2008
LC2018
LC
LC
LC
SQUALIFORMES: Squalidae
Houndsharks
Squalus acutipinnis*
Bluntnose Spurdog
NT2019
LC
LC
NT
Squalus bassi*
African Longnose
Spurdog
LC2019
LC
LC
LC
Squalus lalannei
Seychelles Spurdog
DD2008
LC2018
LC
LC
LC
SQUALIFORMES: Etmopteridae
Lantern Sharks
Etmopterus alphus*
Whitecheek Lanternshark
LC2018
LC
LC
LC
Etmopterus compagnoi*
Brown Lanternshark
LC2018
LC
LC
LC

ORDER: Family
Common name
Original IUCN Red List status
Red List status for RLI
Species name
2000
Mid-2000s
Late-2010s
1980
2005
2020
Etmopterus sculptus*
Sculpted Lanternshark
LC2018
LC
LC
LC
Etmopterus sentosus*
Thorny Lanternshark
LC2006
LC2018
LC
LC
LC
ORECTOLOBIFORMES:
Ginglymostomatidae
Nurse Sharks
Pseudoginglymostoma brevicaudatum
Shorttail Nurse Shark
VU2004
CR2018
LC
VU
CR
ORECTOLOBIFORMES:
Hemiscylliidae
Longtailed Carpetsharks
Chiloscyllium caeruleopunctatum*
Bluespotted
Bambooshark
DD2019
DD
DD
DD
CARCHARHINIFORMES:
Pentanchidae
Deepwater Catsharks
Apristurus saldanha
Saldanha Catshark
LC2004
LC2018
LC
LC
LC
Bythaelurus clevai
Broadhead Catshark
DD2004
DD2018
DD
DD
DD
Bythaelurus lutarius*
Mud Catshark
DD2018
DD
DD
DD
Bythaelurus tenuicephalus*
Narrowhead Catshark
LC2018
LC
LC
LC
Halaelurus lineatus
Lined Catshark
DD2004
LC2018
LC
LC
LC
Halaelurus natalensis
Tiger Catshark
DD2004
VU2018
LC
NT
VU
Haploblepharus edwardsii
Happy Eddie Catshark
NT
NT2008
EN2019
LC
NT
EN
Haploblepharus fuscus
Brown Shyshark
NT
VU2008
VU2019
LC
VU
VU
Haploblepharus kistnasamyi
Natal Shyshark
CR2008
VU2019
LC
NT
VU
Haploblepharus pictus
Dark Shyshark
LC2008
LC2018
LC
LC
LC
Holohalaelurus favus
Honeycomb Izak
Catshark
EN2008
EN2019
LC
EN
EN
Holohalaelurus grennian
Grinning Izak Catshark
DD2008
DD2019
DD
DD
DD
Holohalaelurus melanostigma
Crying Izak Catshark
DD2006
LC2019
LC
LC
LC
Holohalaelurus punctatus
African Spotted Catshark
EN2008
EN2019
LC
EN
EN

ORDER: Family
Common name
Original IUCN Red List status
Red List status for RLI
Species name
2000
Mid-2000s
Late-2010s
1980
2005
2020
Holohalaelurus regani
Izak Catshark
LC2007
LC2019
LC
LC
LC
CARCHARHINIFORMES:
Scyliorhinidae
Catsharks
Cephaloscyllium sufflans
Balloon Shark
LC2004
NT2019
LC
LC
NT
Poroderma africanum
Pyjama Shark
NT
NT2005
LC2019
LC
LC
LC
Poroderma pantherinum
Leopard Catshark
DD2004
LC2019
LC
LC
LC
Scyliorhinus capensis
Yellowspotted Catshark
NT
NT2004
NT2019
LC
LC
NT
Scyliorhinus comoroensis
Comoro Catshark
DD2007
DD2018
DD
DD
DD
CARCHARHINIFORMES:
Proscylliidae
Finback Catsharks
Eridacnis sinuans
African Ribbontail
Catshark
LC2004
LC2018
LC
LC
LC
CARCHARHINIFORMES: Triakidae
Houndsharks
Mustelus palumbes
Whitespot Smoothhound
DD2006
LC2019
LC
LC
LC
Scylliogaleus quecketti
Flapnose Houndshark
VU
VU2005
VU2018
LC
NT
VU
Triakis megalopterus
Spotted Gully Shark
NT
NT2005
LC2019
LC
LC
LC
RAYS
RAJIFORMES: Anacanthobatidae
Legskates
Anacanthobatis marmorata
Spotted Legskate
DD2004
NT2019
LC
LC
NT
Indobatis ori
Black Legskate
DD2004
LC2019
LC
LC
LC
RAJIFORMES: Arhynchobatidae
Softnose Skates
Bathyraja smithii
Softnose Skate
DD2008
LC2019
LC
LC
LC
RAJIFORMES: Gurgesiellidae
Pygmy Skates
Cruriraja durbanensis
Smoothnose Pygmy
Skate
DD2008
DD2018
DD
DD
DD
Cruriraja hulleyi
Hulley’s Pygmy Skate
LC2007
LC2018
LC
LC
LC

ORDER: Family
Common name
Original IUCN Red List status
Red List status for RLI
Species name
2000
Mid-2000s
Late-2010s
1980
2005
2020
Cruriraja parcomaculata
Roughnose Pygmy Skate
DD2007
LC2018
LC
LC
LC
Fenestraja maceachrani
Madagascar Pygmy
Skate
DD2008
DD2018
DD
DD
DD
RAJIFORMES: Rajidae
Hardnose Skates
Dipturus campbelli
Blackspot Skate
NT2004
NT2019
LC
LC
NT
Dipturus crosnieri
Madagascar Skate
VU2006
VU2018
LC
VU
VU
Dipturus lanceorostratus
Rattail Skate
DD2004
DD2018
DD
DD
DD
Dipturus pullopunctatus
Slime Skate
LC2004
LC2019
LC
LC
LC
Dipturus stenorhynchus
Prownose Skate
DD2004
DD2018
DD
DD
DD
Leucoraja compagnoi
Tigertail Skate
DD2004
DD2018
DD
DD
DD
Leucoraja wallacei
Yellowspotted Skate
LC2008
VU2019
LC
LC
VU
Neoraja stehmanni
South African Dwarf
Skate
DD2004
LC2018
LC
LC
LC
Okamejei heemstrai
Narrow Skate
DD2004
LC2018
LC
LC
LC
Raja ocellifera
Twineye Skate
EN2019
LC
VU
EN
Rajella caudaspinosa
Munchkin Skate
NT2004
LC2018
LC
LC
LC
Rajella paucispinosa
Sparsethorn Skate
LC2018
LC
LC
LC
TORPEDINIFORMES: Narkidae
Sleeper Rays
Electrolux addisoni
Ornate Sleeper Ray
CR2008
LC2018
LC
LC
LC
Heteronarce garmani
Natal Sleeper Ray
VU2007
NT2019
NT
NT
NT
Narke capensis
Cape Sleeper Ray
DD2007
LC2018
LC
LC
LC
TORPEDINIFORMES: Torpedinidae
Torpedo Rays
Tetronarce cowleyi*
South African Torpedo
LC2018
LC
LC
LC
Torpedo fuscomaculata
Blackspotted Torpedo
DD2004
DD2018
DD
DD
DD
TORPEDINIFORMES: Narcinidae
Numbfishes

ORDER: Family
Common name
Original IUCN Red List status
Red List status for RLI
Species name
2000
Mid-2000s
Late-2010s
1980
2005
2020
Narcine insolita
Madagascar Numbfish
DD2004
DD2018
DD
DD
DD
RHINOPRISTIFORMES:
Rhinobatidae
Guitarfishes
Acroteriobatus annulatus
Lesser Guitarfish
LC2006
VU2019
LC
NT
VU
Acroteriobatus blochii
Bluntnose Guitarfish
LC2006
LC2018
LC
LC
LC
Acroteriobatus leucospilus
Greyspot Guitarfish
DD2008
EN2018
LC
VU
EN
Acroteriobatus ocellatus
Speckled Guitarfish
DD2008
DD2018
DD
DD
DD
Rhinobatos austini
Austin’s Guitarfish
DD2018
DD
DD
DD
Rhinobatos holcorhynchus
Slender Guitarfish
DD2008
DD2018
DD
DD
DD
MYLIOBATIFORMES: Gymnuridae
Butterfly Rays
Gymnura natalensis
Diamond Ray
DD2006
LC2018
LC
LC
LC
712

Table 2. Endemic SWIO shark and ray species and their observed and projected (over 3 GL) population trends (observed change in 713
% in fisheries trawl surveys and shore-based research angling surveys off the west and south coasts of South Africa), for which JARA 714
has been used as a decision-support tool to undertake extinction risk assessments based on the IUCN Red List Categories and Criteria. 715
716
Species
Common Name
RL
Survey
Years
GL
Population trend (%)
Category
Observed
3GL
Acroteriobatus
annulatus
Lesser
Guitarfish
VU
trawl surveys
1991–2017
5
-87
-34.1 (-76.7, 62.7)
angling surveys
1998–2017
5
26
16.7 (-26.3, 75.6)
Dipturus
pullopunctatus
Slime Skate
LC
trawl surveys
1991–2017
11.5
71
110.1 (10.2, 288.6)
Halaelurus
natalensis
Tiger Catshark
VU
trawl surveys
1991–2017
20
-39
-56.5 (-97.3, 83.3)
Haploblepharus
edwardsii
Happy Eddie
EN
trawl surveys
1991–2017
20
-59
-74.8 (-98.9, 36.2)
angling surveys
1996–2017
20
-72
-92.3 (-99.6, -60.0)
Haploblepharus
fuscus
Brown Shyshark
VU
angling surveys
1996–2017
20
-21
32.4 (-99.3, 550.6)
Holohalaelurus
regani
Izak Catshark
LC
trawl surveys
1991–2017
20
39
78.4 (-42.6, 199.4)
Leucoraja wallacei
Yellowspotted
Skate
VU
trawl surveys
1991–2017
12
-37
-40.4 (-78.6, 32.4)
Mustelus palumbes
Whitespot
Smoothhound
trawl surveys
1991–2017
14
15
26.7 (-36.8, 108.4)
Pliotrema warreni
Warren’s Sixgill
Sawhark
LC
trawl surveys
1991–2017
11
84
96.3 (-55.3, 405.4)
Poroderma
africanum
Pyjama
Catshark
LC
angling surveys
1996–2017
25
30
172.8 (-91.4, 702.0)
Poroderma
pantherinum
Leopard
Catshark
LC
angling surveys
1996–2017
18
64
332.6 (-87.4, 1425.1)
Raja ocellifera
Twineye Skate
EN
trawl surveys
1991–2017
9
-70
-65.5 (-89.2, -17.1)
Scyliorhinus
capensis
Yellowspotted
Catshark
NT
trawl surveys
1991–2017
21
-28
-36.3 (-93.4, 115.5)
Squalus acutipinnis
Bluntnose
Spurdog
NT
trawl surveys
1991–2017
23.5
-12
-21.3 (-78, 95.5)

Species
Common Name
RL
Survey
Years
GL
Population trend (%)
Category
Observed
3GL
Squalus bassi
African
Longnose
Spurdog
LC
trawl surveys
1991–2017
23.5
124
146.3 (-33.7, 370.7)
Triakis
megalopterus
Spotted Gully
Shark
LC
angling surveys
1996–2017
20
64
117.7 (55.8, 195.7)
717

30
Table 3. Nine range countries in the southwest Indian Ocean and their national conservation
responsibilities for all 70 endemic shark and ray species across the region, where Red List
statuses are known. Responsibility for each country is calculated based on the numbers of
species occurring in the country’s Exclusive Economic Zone (EEZ), the most recent Red List
assessment category, and the proportion of each species’ range area occurring in the EEZ
(values were normalized to range from 0 to 1).
Country
National Conservation
Responsibility
South Africa
1.000
Mozambique
0.442
Madagascar
0.407
Tanzania
0.057
Namibia
0.053
Kenya
0.014
Mauritius
0.002
Comoros
0.001
Seychelles
0.000
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Figures
Figure 1
Species richness of (a) all endemic shark and ray species (n = 70), (b) all threatened endemic shark and
ray species (n = 13), (c) threatened sharks (n = 8), and (d) individual distributions of threatened rays (n =
5) across the SWIO region. Countries are labeled with their respective ISO country codes.

Figure 2
Species population time-series modeled from demersal research trawl surveys in commercially shed
areas (line) and shore-based research angling surveys (dashed line). Lines and dashed lines denote the
mean and shaded regions the 95% credible intervals. Time-series are divided by their initial values and
start at one. Silhouette colors indicate Red List status: dark green is Least Concern, light green is Near
Threaten, yellow is Vulnerable, orange is Endangered.

Figure 3
Count of threat categories in the Red List assessments for 20 Threatened and Near Threatened
elasmobranch species in the SWIO region.

Figure 4
Two decades of spatial and temporal change in density (ln kg per km-2) on the South African shelf
between 1991–2016 for (a) Lesser Guitarsh (Acroteriobatus annulatus), (b) Bluntnose Spurdog
(Squalus acutipinnis), and (c) Twin-eye Skate (Raja ocellifera).

Figure 5
Red List Index (RLI) for Sub-equatorial Africa endemic sharks and rays (n = 70). (a) Decline across
assessment years 1980, 2005, and 2020. Country-specic declines in Red List Index for each SWIO
country from (b) 1980—2005, and (c) 2005—2020. Calculations of RLI exclude Data Decient (DD)
species.฀

Figure 6
National conservation responsibilities of range countries for all shark and ray endemics in the SWIO
region, where Red List statuses are known.