ArticlePDF Available

Extinction risk and conservation of the world's sharks and rays

  • Save Our Seas Foundation

Abstract and Figures

The rapid expansion of human activities threatens ocean-wide biodiversity. Numerous marine animal populations have declined, yet it remains unclear whether these trends are symptomatic of a chronic accumulation of global marine extinction risk. We present the first systematic analysis of threat for a globally distributed lineage of 1,041 chondrichthyan fishes-sharks, rays, and chimaeras. We estimate that one-quarter are threatened according to IUCN Red List criteria due to overfishing (targeted and incidental). Large-bodied, shallow-water species are at greatest risk and five out of the seven most threatened families are rays. Overall chondrichthyan extinction risk is substantially higher than for most other vertebrates, and only one-third of species are considered safe. Population depletion has occurred throughout the world's ice-free waters, but is particularly prevalent in the Indo-Pacific Biodiversity Triangle and Mediterranean Sea. Improved management of fisheries and trade is urgently needed to avoid extinctions and promote population recovery.
Content may be subject to copyright.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 1 of 34
Extinction risk and conservation of the
world’s sharks and rays
Nicholas K Dulvy1,2*, Sarah L Fowler3, John A Musick4, Rachel D Cavanagh5, Peter
M Kyne6, Lucy R Harrison1,2, John K Carlson7, Lindsay NK Davidson1,2, Sonja V
Fordham8, Malcolm P Francis9, Caroline M Pollock10, Colin A Simpfendorfer11,12,
George H Burgess13, Kent E Carpenter14,15, Leonard JV Compagno16, David A
Ebert17, Claudine Gibson3, Michelle R Heupel18, Suzanne R Livingstone19,
Jonnell C Sanciangco14,15, John D Stevens20, Sarah Valenti3, William T White20
1IUCN Species Survival Commission Shark Specialist Group, Department of Biological
Sciences, Simon Fraser University, Burnaby, Canada; 2Earth to Ocean Research Group,
Department of Biological Sciences, Simon Fraser University, Burnaby, Canada; 3IUCN
Species Survival Commission Shark Specialist Group, NatureBureau International,
Newbury, United Kingdom; 4Virginia Institute of Marine Science, College of William and
Mary, Gloucester Point, United States; 5British Antarctic Survey, Natural Environment
Research Council, Cambridge, United Kingdom; 6Research Institute for the Environment
and Livelihoods, Charles Darwin University, Darwin, Australia; 7Southeast Fisheries Science
Center, NOAA/National Marine Fisheries Service, Panama City, United States; 8Shark
Advocates International, The Ocean Foundation, Washington, DC, United States;
9National Institute of Water and Atmospheric Research, Wellington, New Zealand; 10Global
Species Programme, International Union for the Conservation of Nature, Cambridge,
United Kingdom; 11Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook
University, Townsville, Australia; 12School of Earth and Environmental Sciences, James
Cook University, Townsville, Australia; 13Florida Program for Shark Research, Florida
Museum of Natural History, University of Florida, Gainsville, United States; 14IUCN Species
Programme Species Survival Commission, Old Dominion University, Norfolk, United
States; 15Conservation International Global Marine Species Assessment, Old Dominion
University, Norfolk, United States; 16Shark Research Center, Iziko, South African Museum,
Cape Town, South Africa; 17Pacific Shark Research Center, Moss Landing Marine
Laboratories, Moss Landing, United States; 18School of Earth and Environmental Sciences,
Australian Institute of Marine Science, Townsville, Australia; 19Global Marine Species
Assessment, Biodiversity Assessment Unit, IUCN Species Programme, Conservation
International, Arlington, United States; 20Marine and Atmospheric Research,
Commonwealth Scientific and Industrial Research Organisation, Hobart, Australia
Abstract The rapid expansion of human activities threatens ocean-wide biodiversity. Numerous
marine animal populations have declined, yet it remains unclear whether these trends are symptomatic
of a chronic accumulation of global marine extinction risk. We present the first systematic analysis of
threat for a globally distributed lineage of 1,041 chondrichthyan fishes—sharks, rays, and chimaeras.
We estimate that one-quarter are threatened according to IUCN Red List criteria due to overfishing
(targeted and incidental). Large-bodied, shallow-water species are at greatest risk and five out of the
seven most threatened families are rays. Overall chondrichthyan extinction risk is substantially higher
than for most other vertebrates, and only one-third of species are considered safe. Population depletion
has occurred throughout the world’s ice-free waters, but is particularly prevalent in the Indo-Pacific
Biodiversity Triangle and Mediterranean Sea. Improved management of fisheries and trade is
urgently needed to avoid extinctions and promote population recovery.
DOI: 10.7554/eLife.00590.001
*For correspondence: dulvy@
Competing interests: The
authors declare that no
competing interests exist.
Funding: See page 27
Received: 29 January 2013
Accepted: 05 December 2013
Published: 21 January 2014
Reviewing editor: Ian T Baldwin,
Max Planck Institute for Chemical
Ecology, Germany
This is an open-access article,
free of all copyright, and may be
freely reproduced, distributed,
transmitted, modified, built
upon, or otherwise used by
anyone for any lawful purpose.
The work is made available under
the Creative Commons CC0
public domain dedication.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 2 of 34
Research article
Populations and species are the building blocks of the communities and ecosystems that sustain humanity
through a wide range of services (Mace et al., 2005; Díaz et al., 2006). There is increasing evidence that
human impacts over the past 10 millennia have profoundly and permanently altered biodiversity on land,
especially of vertebrates (Schipper et al., 2008; Hoffmann et al., 2010). The oceans encompass some of
the earth’s largest habitats and longest evolutionary history, and there is mounting concern for the increas-
ing human influence on marine biodiversity that has occurred over the past 500 years (Jackson, 2010). So
far our knowledge of ocean biodiversity change is derived mainly from retrospective analyses usually
limited to biased subsamples of diversity, such as: charismatic species, commercially-important fisheries,
and coral reef ecosystems (Carpenter et al., 2008; Collette et al., 2011; McClenachan et al., 2012;
Ricard et al., 2012). Notwithstanding the limitations of these biased snapshots, the rapid expansion of
fisheries and globalized trade are emerging as the principal drivers of coastal and ocean threat (Polidoro
et al., 2008; Anderson et al., 2011b; McClenachan et al., 2012). The extent and degree of the global
impact of fisheries upon marine biodiversity, however, remains poorly understood and highly contentious.
Recent insights from ecosystem models and fisheries stock assessments of mainly data-rich northern
hemisphere seas, suggest that the status of a few of the best-studied exploited species and ecosystems
may be improving (Worm et al., 2009). However, this view is based on only 295 populations of 147 fish
species and hence is far from representative of the majority of the world’s fisheries and fished species,
especially in the tropics for which there are few data and often less management (Sadovy, 2005; Newton
et al., 2007; Branch et al., 2011; Costello et al., 2012; Ricard et al., 2012).
Overfishing and habitat degradation have profoundly altered populations of marine animals
(Hutchings, 2000; Lotze et al., 2006; Polidoro et al., 2012), especially sharks and rays (Stevens et al.,
2000; Simpfendorfer et al., 2002; Dudley and Simpfendorfer, 2006; Ferretti et al., 2010). It is not
clear, however, whether the population declines of globally distributed species are locally reversible or
symptomatic of an erosion of resilience and chronic accumulation of global marine extinction risk
(Jackson, 2010; Neubauer et al., 2013). In response, we evaluate the scale and intensity of overfishing
through a global systematic evaluation of the relative extinction risk for an entire lineage of exploited
marine fishes—sharks, rays, and chimaeras (class Chondrichthyes)—using the Red List Categories and
Criteria of the International Union for the Conservation of Nature (IUCN). We go on to identify, (i) the life
eLife digest Ocean ecosystems are under pressure from overfishing, climate change, habitat
destruction and pollution. These pressures have led to documented declines of some fishes in some
places, such as those living in coral reefs and on the high seas. However, it is not clear whether
these population declines are isolated one-off examples or, instead, if they are sufficiently
widespread to risk the extinction of large numbers of species.
Most fishes have a skeleton that is made of bone, but sharks and rays have a skeleton that is
made of cartilage. A total of 1,041 species has such a skeleton and they are collectively known as
the Chondrichthyes. To find out how well these fish are faring, Dulvy et al. worked with more than
300 scientists around the world to assess the conservation status of all 1,041 species.
Based on this, Dulvy et al. estimate that one in four of these species are threatened with extinction,
mainly as a result of overfishing. Moreover, just 389 species (37.4% of the total) are considered to be
safe, which is the lowest fraction of safe species among all vertebrate groups studied to date.
The largest sharks and rays are in the most peril, especially those living in shallow waters that are
accessible to fisheries. A particular problem is the ‘fin trade’: the fins of sharks and shark-like rays
are a delicacy in some Asian countries, and more than half of the chondrichthyans that enter the fin
trade are under threat. Whether targeted or caught by boats fishing for other species, sharks and
rays are used to supply a market that is largely unmonitored and unregulated. Habitat degradation
and loss also pose considerable threats, particularly for freshwater sharks and rays.
Dulvy et al. identified three main hotspots where the biodiversity of sharks and rays was particularly
seriously threatened—the Indo-Pacific Biodiversity Triangle, Red Sea, and the Mediterranean Sea—
and argue that national and international action is needed to protect them from overfishing.
DOI: 10.7554/eLife.00590.002
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 3 of 34
Research article
history and ecological attributes of species (and taxonomic families) that render them prone to extinction,
and (ii) the geographic locations with the greatest number of species of high conservation concern.
Chondrichthyans make up one of the oldest and most ecologically diverse vertebrate lineages: they
arose at least 420 million years ago and rapidly radiated out to occupy the upper tiers of aquatic food
webs (Compagno, 1990; Kriwet et al., 2008). Today, this group is one of the most speciose lineages
of predators on earth that play important functional roles in the top-down control of coastal and oce-
anic ecosystem structure and function (Ferretti et al., 2010; Heithaus et al., 2012; Stevens et al.,
2000). Sharks and their relatives include some of the latest maturing and slowest reproducing of all
vertebrates, exhibiting the longest gestation periods and some of the highest levels of maternal
investment in the animal kingdom (Cortés, 2000). The extreme life histories of many chondrichthyans
result in very low population growth rates and weak density-dependent compensation in juvenile sur-
vival, rendering them intrinsically sensitive to elevated fishing mortality (Musick, 1999b; Cortés, 2002;
García et al., 2008; Dulvy and Forrest, 2010).
Chondrichthyans are often caught as incidental, but are often retained as valuable bycatch of fish-
eries that focus on more productive teleost fish species, such as tunas or groundfishes (Stevens et al.,
2005). In many cases, fishing pressure on chondrichthyans is increasing as teleost target species
become less accessible (due to depletion or management restrictions) and because of the high, and in
some cases rising, value of their meat, fins, livers, and/or gill rakers (Fowler et al., 2002; Clarke et al.,
2006; Lack and Sant, 2009). Fins, in particular, have become one of the most valuable seafood
commodities: it is estimated that the fins of between 26 and 73 million individuals, worth US$400-550
million, are traded each year (Clarke et al., 2007). The landings of sharks and rays, reported to the
Food and Agriculture Organization of the United Nations (FAO), increased steadily to a peak in 2003
and have declined by 20% since (Figure 1A). True total catch, however, is likely to be 3–4 times greater
than reported (Clarke et al., 2006; Worm et al., 2013). Most chondrichthyan catches are unregulated
and often misidentified, unrecorded, aggregated, or discarded at sea, resulting in a lack of species-
specific landings information (Barker and Schluessel, 2005; Clarke et al., 2006; Iglésias et al., 2010;
Bornatowski et al., 2013). Consequently, FAO could only be ‘hopeful’ that the catch decline is due to
improved management rather than being symptomatic of worldwide overfishing (FAO, 2010). The
reported chondrichthyan catch has been increasingly dominated by rays, which have made up greater
than half of reported taxonomically-differentiated landings for the past four decades (Figure 1B).
Chondrichthyan landings were worth US$1 billion at the peak catch in 2003, since then the value has
dropped to US$800 million as catch has declined (Musick and Musick, 2011). A main driver of shark
fishing is the globalized trade to meet Asian demand for shark fin soup, a traditional and usually
expensive Chinese dish. This particularly lucrative trade in fins (not only from sharks, but also of shark-
like rays such as wedgefishes and sawfishes) remains largely unregulated across the 86 countries and
territories that exported >9,500 mt of fins to Hong Kong (a major fin trade hub) in 2010 (Figure 1C).
Red List status of chondrichthyan species
Overall, we estimate that one-quarter of chondrichthyans are threatened worldwide, based on the observed
threat level of assessed species combined with a modeled estimate of the number of Data Deficient spe-
cies that are likely to be threatened. Of the 1,041 assessed species, 181 (17.4%) are classified as threat-
ened: 25 (2.4%) are assessed as Critically Endangered (CR), 43 (4.1%) Endangered (EN), and 113 (10.9%)
Vulnerable (VU) (Table 1). A further 132 species (12.7%) are categorized as Near Threatened (NT).
Chondrichthyans have the lowest percentage (23.2%, n = 241 species) of Least Concern (LC) species of all
vertebrate groups, including the marine taxa assessed to date (Hoffmann et al., 2010). Almost half (46.8%,
n = 487) are Data Deficient (DD) meaning that information is insufficient to assess their status (Table 1).
DD chondrichthyans are found across all habitats, but particularly on continental shelves (38.4% of 482
species in this habitat) and deepwater slopes (57.6%, Table 2). Of the 487 DD species for which we
had sufficient maximum body size (n = 396) and geographic distribution data (n = 378), we were able
to predict that at least a further 68 DD species are likely to be threatened (Table 3, Supplementary
file 1). Accounting for the uncertainty in threat levels due to the number of DD species, we estimate
that more than half face some elevated risk: at least one-quarter (n = 249; 24%) of chondrichthyans are
threatened and well over one-quarter are Near Threatened (Table 1). Only 37% are predicted to be
Least Concern (Table 1).
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 4 of 34
Research article
Drivers of threat
The main threats to chondrichthyans are overexploitation through targeted fisheries and incidental
catches (bycatch), followed by habitat loss, persecution, and climate change. While one-third of threat-
ened sharks and rays are subject to targeted fishing, some of the most threatened species (including
sawfishes and large-bodied skates) have declined due to incidental capture in fisheries targeting other
species. Shark-like rays, especially sawfishes, wedgefishes and guitarfishes, have some of the most valu-
able fins and are highly threatened. Although the global fin trade is widely recognized as a major driver
of shark and ray mortality, demand for meat, liver oil, and even gillrakers (of manta and other devil rays)
also poses substantial threats. Half of the 69 high-volume or high-value sharks and rays in the global
fin trade are threatened (53.6%, n = 37), while low-value fins often enter trade as well, even if meat
demand is the main fishery driver (Supplementary file 2A). Coastal species are more exposed to the
combined threats of fishing and habitat degradation than those offshore in pelagic and deepwater
ecosystems. In coastal, estuarine, and riverine habitats, four principal processes of habitat degradation
(residential and commercial development, mangrove destruction, river engineering, and pollution)
jeopardize nearly one-third of threatened sharks and rays (29.8%, n = 54 of 181, Supplementary file 2B).
The combined effects of overexploitation and habitat degradation are most acute in freshwater, where
over one-third (36.0%) of the 90 obligate and euryhaline freshwater chondrichthyans are threatened.
Figure 1. The trajectory and spatial pattern of chondrichthyan fisheries catch landings and fin exports. (A) The landed catch of chondrichthyans reported to
the Food and Agriculture Organization of the United Nations from 1950 to 2009 up to the peak in 2003 (black) and subsequent decline (red). (B) The rising
contribution of rays to the taxonomically-differentiated global reported landed catch: shark landings (light gray), ray landings (black), log ratio [rays/sharks],
(red). Log ratios >0 occur when more rays are landed than sharks. The peak catch of taxonomically-differentiated rays peaks at 289,353 tonnes in 2003.
(C) The main shark and ray fishing nations are gray-shaded according to their percent share of the total average annual chondrichthyan landings reported to
FAO from 1999 to 2009. The relative share of shark and ray fin trade exports to Hong Kong in 2010 are represented by fin size. The taxonomically-differenti-
ated proportion excludes the ‘nei’ (not elsewhere included) and generic ‘sharks, rays, and chimaeras’ category.
DOI: 10.7554/eLife.00590.003
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 5 of 34
Research article
Their plight is exacerbated by high habitat-specificity and restricted geographic ranges (Stevens et al.,
2005). Specifically, the degradation of coastal, estuarine and riverine habitats threatened 14% of sharks
and rays: through residential and commercial development (22 species, including river sharks Glyphis
spp.); mangrove destruction for shrimp farming in Southeast Asia (4 species, including Bleeker’s varie-
gated stingray Himantura undulata); dam construction and water control (8 species, including Mekong
freshwater stingray Dasyatis laosensis), and pollution (20 species). Many freshwater sharks and rays
suffer multiple threats and have narrow geographic distributions, for example the Endangered
Roughnose stingray (Pastinachus solocirostris) that is found only in Malaysian Borneo and Indonesia
(Kalimantan, Sumatra and Java). Population control of sharks, in particular due to their perceived risk
to people, fishing gear, and other fisheries has contributed to the threatened status of at least 12 species
(Supplementary file 2B). Sharks and rays are also threatened due to capture in shark control nets
(e.g. Dusky shark Carcharhinus obscurus), and persecution to minimise: damage to fishing nets
(e.g. Green sawfish Pristis zijsron); their predation on aquacultured molluscs (e.g. Estuary stingray
Dasyatis fluviorum); interference with spearfishing activity (e.g. Grey nurse shark Carcharias taurus),
and the risk of shark attack (e.g. White shark Carcharodon carcharias). So far the threatened status of
only one species has been directly linked to climate change (New Caledonia catshark Aulohalaelurus
kanakorum, Supplementary file 2B). the climate-sensitivity of some sharks has been recognized (Chin
et al., 2010) and the status of shark and ray species will change rapidly in climate cul-de-sacs, such
as the Mediterranean Sea (Lasram et al., 2010).
Correlates and predictors of threat
Elevated extinction risk in sharks and rays is a function of exposure to fishing mortality coupled with
their intrinsic life history and ecological sensitivity (Figures 2–6). Most threatened chondrichthyan
species are found in depths of less than 200 m, especially in the Atlantic and Indian Oceans, and the
Western Central Pacific Ocean (79.6%, n = 144 of 181, Figure 2). Extinction risk is greater in larger-bodied
Table 1. Observed and predicted number and percent of chondrichthyan species in IUCN Red List categories
number (%)
species number (%) CR EN VU NT LC DD
Skates and rays 539 (51.8) 107 (19.9) 14 (1.3) 28 (2.7) 65 (6.2) 62 (6.0) 114 (11.0) 256 (24.6)
Sharks 465 (44.7) 74 (15.9) 11 (1.1) 15 (1.4) 48 (4.6) 67 (6.4) 115 (11.0) 209 (20.1)
Chimaeras 37 (3.6) 0 0 0 0 3 (0.3) 12 (1.2) 22 (2.1)
All observed 1041 181 (17.4) 25 (2.4) 43 (4.1) 113 (10.9) 132 (12.7) 241 (23.2) 487 (46.8)
All predicted 249 (23.9) 312 (29.9) 389 (37.4) 91 (8.7)
CR, Critically Endangered; EN, Endangered; VU, Vulnerable; NT, Near Threatened; LC, Least Concern; DD, Data Deficient. Number threatened is the
sum total of the categories CR, EN and VU. Species number and number threatened are expressed as percentage of the taxon, whereas the percentage
of each species in IUCN categories is expressed relative to the total number of species.
DOI: 10.7554/eLife.00590.004
Table 2. Number and percent of chondrichthyans in IUCN Red List categories by their main habitats
Habitat Species (%) Threatened (%) CR (%) EN (%) VU (%) NT (%) LC (%) DD (%)
Coastal and continental
482 (46.3) 127 (26.3) 20 (4.1) 26 (5.4) 81 (16.8) 73 (15.1) 97 (20.1) 185 (38.4)
Neritic and
39 (3.7) 17 (43.6) 0 3 (7.7) 14 (35.9) 13 (33.3) 5 (12.8) 4 (10.3)
Deepwater 479 (46.0) 25 (5.2) 2 (0.4) 6 (1.3) 17 (3.5) 45 (9.4) 133 (27.8) 276 (57.6)
Mesopelagic 8 (0.8) 0 0 0 0 0 4 (50.0) 4 (50.0)
Freshwater (obligate
species only)
33 (3.2) 12 (36.4) 3 (9.1) 8 (24.2) 1 (3.0) 1 (3.0) 2 (6.1) 18 (54.5)
Totals 1041 181 (17.4) 25 (2.4) 43 (4.1) 113 (10.9) 132 (12.7) 241 (23.2) 487 (46.8)
CR, Critically Endangered; EN, Endangered; VU, Vulnerable; NT, Near Threatened; LC, Least Concern; DD, Data Deficient.
DOI: 10.7554/eLife.00590.005
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 6 of 34
Research article
species found in shallower waters with narrower depth distributions, after accounting for phyloge-
netic non-independence (Figures 3 and 4). The traits with the greatest relative importance (>0.95) are
maximum body size, minimum depth, and depth range. In comparison, geographic range (measured
as Extent of Occurrence) has a much lower relative importance (0.79, Figure 3), and in the predictive
models it improved the variance explained by 2% and the prediction accuracy by 1% (Table 3). The prob-
ability that a species is threatened increases by 1.2% for each 10 cm increase in maximum body length,
and decreases by 10.3% for each 50 m deepening in the minimum depth limit of species. After ac-
counting for maximum body size and minimum depth, species with narrower depth ranges have a
1.2% greater threat risk per 100 m narrowing of depth range. There is no significant interaction
between depth range and minimum depth limit. Geographic range, measured as the Extent of
Occurrence, varies over six orders of magnitude, between 354 km2 and 278 million km2 and is positively
correlated with body size (Spearman’s
= 0.58), and hence is only marginally positively related to
extinction risk over and above the effect of body size. Accounting for the body size and depth effects,
the threat risk increases by only 0.5% for each 1,000,000 km2 increase in geographic range (Table 4).
The explanatory and predictive power of our life history and geographic distribution models increased
with complexity, though geographic range size contributed relatively little additional explanatory
power and a high degree of uncertainty in the parameter estimate (Tables 3 and 4). The maximum
variance explained was 69% (Table 4) and the predictive models (without controlling for phylogeny)
explained 30% of the variance and prediction accuracy was 77% (Table 3).
By habitat, one-quarter of coastal and continental shelf chondrichthyans (26.3%, n = 127 of 482) and
almost half of neritic and epipelagic species (43.6%, n = 17 of 39) are threatened. Coastal and continental
shelf and pelagic species greater than 1 m total length have a more than 50% chance of being threatened,
compared to 12% risk for a similar-sized deepwater species (Figure 5). While deepwater chondrichthyans,
due to their slow growth and lower productivity, are intrinsically more sensitive to overfishing than their
shallow-water relatives (García et al., 2008; Simpfendorfer and Kyne, 2009) for a given body size they are
less threatened—largely because they are inaccessible to most fisheries (Figure 5).
As a result of their high exposure to coastal shallow-water fisheries and their large body size, sawfishes
(Pristidae) are the most threatened chondrichthyan family and arguably the most threatened family of
marine fishes (Figure 6). Other highly threatened families include predominantly coastal and continental
shelf-dwelling rays (wedgefishes, sleeper rays, stingrays, and guitarfishes), as well as angel sharks and
thresher sharks; five of the seven most threatened families are rays. Least threatened families are com-
prised of relatively small-bodied species occurring in mesopelagic and deepwater habitats (lanternsharks,
catsharks, softnose skates, shortnose chimaeras, and kitefin sharks, Figure 6, Figure 6—source data 1).
Geographic hotspots of threat and conservation priority by habitat
Local species richness is greatest in tropical coastal seas, particularly along the Atlantic and Western
Pacific shelves (Figure 7A). The greatest uncertainty, where the number of DD species is highest, is
centered on four areas: (1) Caribbean Sea and Western Central Atlantic Ocean, (2) Eastern Central
Atlantic Ocean, (3) Southwest Indian Ocean, and (4) the China Seas (Figure 7B). The megadiverse
China Seas face the triple jeopardy of high threat in shallow waters (Figure 7CD), high species richness
(Figure 7A), and a large number of threatened endemic species (Figure 8), combined with high risk
due to high uncertainty in status (large number of DD species, Figure 7B). Whereas the distribution of
Table 3. Summary of predictive Generalized Linear Models for life history and ecological correlates of IUCN status
Model structure
and hypothesis
Degrees of
freedom, k
likelihood AICcΔAIC
(AUC) R2
1maximum length 2 −227.479 459 43.67 0.000 0.678 0.139
2 …+ minimum depth 3 −210.299 426.7 11.34 0.003 0.746 0.243
3 …+…+ depth range 4 −204.703 417.5 2.19 0.25 0.762 0.276
4 …+…+…+ geographic range 5 −202.578 415.3 0 0.748 0.772 0.298
Species were scored as threatened (CR, EN, VU) = 1 or Least Concern (LC) = 0 for n = 367 marine species. AICc is the Akaike information criterion
corrected for small sample sizes and ΔAIC is the change in AICc. The models are ordered by increasing complexity and decreasing AIC weight (largest
ΔAIC to lowest), coefficient of determination (R2), and prediction accuracy (measured using Area Under the Curve, AUC).
DOI: 10.7554/eLife.00590.006
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 7 of 34
Research article
Figure 2. IUCN Red List Threat status and the depth distribution of chondrichthyans in the FAO Fishing Areas of the
Atlantic, Indian and Pacific Oceans, and Polar Seas. Each vertical line represents the depth range (surface-ward minimum
to the maximum reported depth) of each species and is colored according to threat status: CR (red), EN (orange), VU
(yellow), NT (pale green), LC (green), and DD (gray). Species are ordered left to right by increasing median depth. The
depth limit of the continental shelf is indicated by the horizontal gray line at 200 m. The Polar Seas include the following
FAO Fishing Areas: Antarctic–Atlantic (Area 48), Indian (Area 58), Pacific (Area 88), and the Arctic Sea (Area 18).
DOI: 10.7554/eLife.00590.007
Figure 2. Continued on next page
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 8 of 34
Research article
threat in coastal and continental shelf chondrichthyans is similar to the overall threat pattern across
tropical and mid-latitudes, the spatial pattern of threat varies considerably for pelagic and deepwater
species. Threatened neritic and epipelagic oceanic sharks are distributed throughout the world’s
oceans, but there are also at least seven threat hotspots in coastal waters: (1) Gulf of California,
(2) southeast US continental shelf, (3) Patagonian Shelf, (4) West Africa and the western Mediterranean
Sea, (5) southeast South Africa, (6) Australia, and (7) the China Seas (Figure 7D). Hotspots of deepwater
threatened chondrichthyans occur in three areas where fisheries penetrate deepest: (1) Southwest
Atlantic Ocean (southeast coast of South America), (2) Eastern Atlantic Ocean, spanning from Norway to
Namibia and into the Mediterranean Sea, and (3) southeast Australia (Figure 7E).
Hottest hotspots of threat and priority
Spatial conservation priority can be assigned using three criteria: (1) the greatest number of threatened
species (Figure 7A), (2) greater than expected threat (residuals of the relationship between total number
of species and total number of threatened species per cell, Figure 9), and (3) high irreplaceability—high
numbers of threatened endemic species (Figure 8). Most threatened marine chondrichthyans (n =
135 of 169) are distributed within, and are often
endemic to (n = 73), at least seven distinct threat
hotspots (e.g., for neritic and pelagic species
Figure 7D). With the notable exception of the US
and Australia, threat hotspots occur in the waters
of the most intensive shark and ray fishing and
fin-trading nations (Figure 1C). Accordingly
these regions should be afforded high scientific
and conservation priority (Table 5).
The greatest number of threatened species
coincides with the greatest richness (Figure 7A
vs 7C–E); by controlling for species richness we
can reveal the magnitude of threat in the pelagic
ocean and two coastal hotspots that have a
greater than expected level of threat: the Indo-
Pacific Biodiversity Triangle and the Red Sea.
Throughout much of the pelagic ocean, threat is
greater than expected based on species richness
alone, species richness is low (n = 30) and a high
percentage (86%) are threatened (n = 16) or Near
Threatened (n = 10). Only four are of Least Concern
(Salmon shark Lamna ditropis, Goblin shark
Mitsukurina owstoni, Longnose pygmy Shark
Heteroscymnoides marleyi, and Largetooth
cookiecutter shark Isistius plutodus) (Figure 9). The
Indo-Pacific Biodiversity Triangle, particularly the
Gulf of Thailand, and the islands of Sumatra, Java,
Borneo, and Sulawesi, is a hotspot of greatest
residual threat especially for coastal sharks and
rays with 76 threatened species (Figure 9). Indeed,
the Gulf of Thailand large marine ecosystem has
The following figure supplements are available for figure 2:
Figure supplement 1. Map of Food and Agriculture Organization of the United Nations Fishing Areas and their
codes: 18, Arctic Sea; 21, Atlantic, Northwest; 27, Atlantic, Northeast; 31, Atlantic, Western Central; 34, Atlantic,
Eastern Central; 37, Mediterranean and Black Sea; 41, Atlantic, Southwest; 47, Atlantic, Southeast; 48, Atlantic,
Antarctic; 51, Indian Ocean, Western; 57, Indian Ocean, Eastern; 58, Indian Ocean, Antarctic and Southern; 61,
Pacific, Northwest; 67, Pacific, Northeast; 71, Pacific, Western Central; 77, Pacific, Eastern Central; 81, Pacific,
Southwest; 87, Pacific, Southeast; and, 88, Pacific, Antarctic.
DOI: 10.7554/eLife.00590.008
Figure 2. Continued
Figure 3. Standardized effect sizes with 95% confidence
intervals from the two best explanatory models of life
histories, geographic range and extinction risk in
chondrichthyans. The data were standardized by
subtracting the mean and dividing by one standard
deviation to allow for comparison among parameters.
The relative importance is calculated as the sum of the
Akaike weights of the models containing each variable.
Chondrichthyans were scored as threatened (CR, EN,
VU) = 1 or Least Concern (LC) = 0 for n = 367 marine
species. Threat status was modeled using General
Linear Mixed-effects Models, with size, depth and
geography treated as fixed effects and taxonomy
hierarchy as a random effect to account for phyloge-
netic non-independence.
DOI: 10.7554/eLife.00590.009
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 9 of 34
Research article
the highest threat density with 48 threatened
chondrichthyans in an area of 0.36 million km2.
The Red Sea residual threat hotspot has 29 threat-
ened pelagic and coastal species (Figure 9).
There are 15 irreplaceable marine hotspots that
harbor all 66 threatened endemic species (Figure 8;
Supplementary file 2C).
In a world of limited funding, conservation priori-
ties are often based on immediacy of extinction,
the value of biodiversity and conservation oppor-
tunity (Marris, 2007). In this study, we provide
the first estimates of the threat status and hence
risk of extinction of chondrichthyans. Our system-
atic global assessment of the status of this lineage
that includes many iconic predators reveals a risky
combination of high threat (17% observed and
23.9% estimated), low safety (Least Concern, 23%
observed and >37% estimated), and high uncer-
tainty in their threat status (Data Deficient, 46%
observed and 8.7% estimated). Over half of spe-
cies are predicted to be threatened or Near
Threatened (n = 561, 53.9%, Table 1). While no
species has been driven to global extinction—
as far as we know—at least 28 populations of
sawfishes, skates, and angel sharks are locally
or regionally extinct (Dulvy et al., 2003; Dulvy
and Forrest, 2010). Several shark species have
not been seen for many decades. The Critically
Endangered Pondicherry shark (Carcharhinus
hemiodon) is known only from 20 museum speci-
mens that were captured in the heavily-fished
inshore waters of Southeast Asia: it has not been
seen since 1979 (Cavanagh et al., 2003). The
now ironically-named and Critically Endangered
Common skate (Dipturus batis) and Common angel
shark (Squatina squatina) are regionally extinct
from much of their former geographic range in
European waters (Cavanagh and Gibson, 2007;
Gibson et al., 2008; Iglésias et al., 2010). The
Largetooth sawfish (Pristis pristis) and Smalltooth
sawfish (Pristis pectinata) are possibly extinct
throughout much of the Eastern Atlantic, particu-
larly in West Africa (Robillard and Séret, 2006;
Harrison and Dulvy, 2014).
Our analysis provides an unprecedented un-
derstanding of how many chondrichthyan species
are actually or likely to be threatened. A very high
percentage of species are DD (46%, 487 species);
that is one of the highest rates of Data Deficiency
of any taxon to date (Hoffmann et al., 2010). This
high level of uncertainty in status further elevates
risk and presents a key challenge for future assess-
ment efforts. We outline a first step through our
estimation that 68 DD species are likely to be
Figure 4. Life history sensitivity, accessibility to fisheries
and extinction risk. Probability that a species is
threatened due to the combination of intrinsic life
history sensitivity (maximum body size, cm total length,
TL) and accessibility to fisheries which is represented as
minimum depth limit, depth range, and geographic
range size (Extent of Occurrence). The lines represent
the variation in body size-dependent risk for the upper
quartile, median, and lower quartile of each range
metric. The examplar species are all of similar maximum
body length and the difference in risk is largely due to
differences in geographic distribution. Chondrichthyans
were scored as threatened (CR, EN, VU) = 1 or Least
Concern (LC) = 0 for n = 366 marine species. The lines
are the best fits from General Linear Mixed-effects
Models, with maximum body size and geographic
Figure 4. Continued on next page
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 10 of 34
Research article
threatened based on their life histories and distribu-
tion. Numerous studies have retrospectively
explained extinction risk, but few have made a
priori predictions of risk (Dulvy and Reynolds,
2002; Davidson et al., 2012). Across many taxa,
extinction risk has been shown to be a function of
an extrinsic driver or threat (Jennings et al.,
1998; Davies et al., 2006) and the corresponding
life history and ecological traits: large body size (low
intrinsic rate of population increase, high trophic level), small geographic range size, and ecological spe-
cialization. Maximum body size is an essential predictor of threat status, we presume because of the close
relationship between body size and the intrinsic rate of population increase in sharks and rays (Smith
et al., 1998; Frisk et al., 2001; Hutchings et al., 2012). Though we note that this proximate link may
be mediated ultimately through the time-related traits of growth and mortality (Barnett et al., 2013;
Juan-Jordá et al., 2013). Our novel contribution is to show that depth-related geographic traits are more
important for explaining risk than geographic range per se. The shallowness of species (minimum
depth limit) and the narrowness of their depth range are important risk factors (Figure 3). We hypoth-
esize that this is so because shallower species are more accessible to fishing gears and those with
narrower depth ranges have lower likelihood that a proportion of the species distribution remains
beyond fishing activity. For example, the Endangered Barndoor skate (Dipturus laevis) was elimi-
nated throughout much of its geographic range and depth distribution due to bycatch in trawl fish-
eries, yet may have rebounded because a previously unknown deepwater population component lay
beyond the reach of most fisheries (Dulvy, 2000; Kulka et al., 2002; COSEWIC, 2010). We find that
geographic range (measured as Extent of Occurrence) is largely unrelated to extinction risk. This is in
marked contrast to extinction risk patterns on land (Jones et al., 2003; Cardillo et al., 2005; Anderson
et al., 2011a) and in the marine fossil record (Harnik et al., 2012a, 2012b), where small geographic
range size is the principal correlate of extinction risk. We suggest that this is because fishing activity is
now widespread throughout the world’s oceans (Swartz et al., 2010), and even species with the larg-
est ranges are exposed and often entirely encompassed by the footprint of fishing activity. By contrast,
with a few exceptions (mainly eastern Atlantic slopes, Figure 7E), fishing has a narrow depth pene-
tration and hence species found at greater depths can still find refuge from exploitation (Morato et
al., 2006; Lam and Sadovy de Mitcheson, 2010).
The status of chondrichthyans is arguably among the worst reported for any major vertebrate lineage
considered thus far, apart from amphibians (Stuart et al., 2004; Hoffmann et al., 2010). The percentage
and absolute number of threatened amphibians is high (>30% are threatened), but a greater percentage
are Least Concern (38%), and uncertainty of status is lower (32% DD) than for chondrichthyans. Our
discovery of the high level of threat in freshwater chondrichthyans (36%) is consistent with the
emerging picture of the intense and unmanaged extinction risk faced by many freshwater and estuarine
species (Darwall et al., 2011).
Our threat estimate is comparable to other marine biodiversity status assessments, but our findings
caution that ‘global’ fisheries assessments may be underestimating risk. The IUCN Global Marine Species
Assessment is not yet complete, but reveals varying threat levels among taxa and regions (Polidoro
et al., 2008, 2012). The only synoptic summary to-date focused on charismatic Indo-Pacific coral reef
ecosystem species. Of the 1,568 IUCN-assessed marine vertebrates and invertebrates, 16% (range:
12–34% among families) were threatened (McClenachan et al., 2012). This is a conservative estimate
of marine threat level because although they may be more intrinsically sensitive to extinction drivers,
charismatic species are more likely to garner awareness of their status and support for monitoring and
conservation (McClenachan et al., 2012). The predicted level of chondrichthyan threat (>24%) is dis-
tinctly greater than that provided by global fisheries risk assessments. These studies provide modeled
estimates of the percentage of collapsed bony fish (teleost) stocks in both data-poor unassessed fish-
eries (18%, Costello et al., 2012) and data-rich fisheries (7–13%, Branch et al., 2011). This could be
because teleosts are generally more resilient than elasmobranchs (Hutchings et al., 2012), but in
addition we caution that analyses of biased geographic and taxonomic samples may be underesti-
mating risk of collapse in global fisheries, particularly for species with less-resilient life histories.
Our work relies on consensus assessments by more than 300 scientists. However, given the
uncertainty in some of the underlying data that inform our understanding of threat status, such as
distribution traits treated as fixed effects and taxonomy
hierarchy as a random effect to account for phylogenetic
non-independence. Each vertical line in each of the
‘rugs’ represents the maximum body size and Red List
status of each species: threatened (red) and LC (green).
DOI: 10.7554/eLife.00590.010
Figure 4. Continued
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 11 of 34
Research article
fisheries catch landings data, it is worth consid-
ering whether these uncertainties mean our
assessments are downplaying the true risk.
While there are methods of propagating uncer-
tainty through the IUCN Red List Assessments
(Akcakaya et al., 2000), in our experience this
approach was uninformative for even the best-
studied species, because it generated confidence
intervals that spanned all IUCN Categories. Instead
it is worth considering whether our estimates of
threat are consistent with independent quantita-
tive estimates of status. The Mediterranean Red
List Assessment workshop in 2005 prompted
subsequent quantitative analyses of catch landings,
research trawl surveys, and sightings data.
Quantitative trends could be estimated for five
species suggesting they had declined by 96% to
>99.9% relative to their former abundance sug-
gesting they would meet the highest IUCN Threat
category of Critically Endangered (Ferretti et al.,
2008). By comparison the earlier IUCN regional
assessment for these species, while suggesting
they were all threatened, was more conservative
for two of the five species: Hammerhead sharks
(Sphyrna spp.)—Critically Endangered, Porbeagle
shark (Lamna nasus)—Critically Endangered,
Shortfin mako (Isurus oxyrinchus)—Critically
Endangered, Blue shark (Prionace glauca)
Vulnerable, and Thresher shark (Alopias
We can also make a complementary comparison
to a recent analysis of the status of 112 shark and
ray fisheries (Costello et al., 2012). The median
biomass relative to the biomass at Maximum
Sustainable Yield (B/BMSY) of these 112 shark and
ray fisheries was 0.37, making them the most
overfished groups of any of the world’s unassessed
fisheries. Assuming BMSY occurs at 0.3 to 0.5 of
unexploited biomass then the median biomass of
shark and ray fisheries had declined by between
81% and 89% by 2009. These biomass declines
would be sufficient to qualify all of these 112
shark and ray fisheries for the Endangered IUCN
category if they occurred within a three-generation
time span. By comparison our results are consider-
ably more conservative. Empirical analyses show
that an IUCN threatened category listing is trig-
gered only once teleost fishes (with far higher den-
sity-dependent compensation) have been fished
down to below BMSY (Dulvy et al., 2005; Porszt et
al., 2012). Hence, our findings are consistent
with only around one-quarter of chondrichthyan
species having been fished down below the BMSY
target reference point. While there may be con-
cern that expert assessments may overstate
declines and threat, it is more likely that our con-
Figure 5. Life history, habitat, and extinction risk in
chondrichthyans. IUCN Red List status as a function of
maximum body size (total length, TL cm) and accessibility
to fisheries in marine chondrichthyans in three main
habitats: coastal and continental shelf <200 m
(‘Continental shelf’); neritic and oceanic pelagic <200 m
(‘Pelagic’); and, deepwater >200 m (‘Deepwater’),
n = 367 (threatened n = 148; Least Concern n = 219).
The upper and lower ‘rug’ represents the maximum
Figure 5. Continued on next page
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 12 of 34
Research article
servative consensus-based approach has under-
stated declines and risk in sharks and rays.
For marine species, predicting absolute risk of
extinction remains highly uncertain because, even
with adequate evidence of severe decline, in many
instances the absolute population size remains
large (Mace, 2004). There remains considerable un-
certainty as to the relationship between census and
effective population size (Reynolds et al., 2005). Therefore, Red List categorization of chondrichthyans
should be interpreted as a comparative measure of relative extinction risk, in recognition that unmanaged
steep declines, even of large populations, may ultimately lead to ecosystem perturbations and eventually
biological extinction. The Red List serves to raise red flags calling for conservation action, sooner rather
than later, while there is a still chance of recovery and of forestalling permanent biodiversity loss.
Despite more than two decades of rising awareness of chondrichthyan population declines and
collapses, there is still no global mechanism to ensure financing, implementation and enforcement of
chondrichthyan fishery management plans that is likely to rebuild populations to levels where they
would no longer be threatened (Lack and Sant, 2009; Techera and Klein, 2011). This management
shortfall is particularly problematic given the large geographic range of many species. Threat increased
only slightly when geographic range is measured as the Extent of Occurrence; however, geographic
range becomes increasingly important when it is measured as the number of countries (legal jurisdic-
tions) spanned by each species. The proportion of species that are threatened increases markedly with
geographic size measured by number of Exclusive Economic Zones (EEZs) spanned; one-quarter of
threatened species span the EEZs of 18 or more countries (Figure 10). Hence, their large geographic
ranges do not confer safety, but instead exacerbates risk because sharks and rays require coherent,
effective international management.
With a few exceptions (e.g., Australia and USA), many governments still lack the resources, expertise,
and political will necessary to effectively conserve the vast majority of shark and rays, and indeed many
body size and Red List status of each species: threat-
ened (upper rugs) and Least Concern (lower rugs). The
lines are best fit using Generalized Linear Mixed-effects
Models with 95% confidence intervals (Table 9).
DOI: 10.7554/eLife.00590.011
Figure 5. Continued
Figure 6. Evolutionary uniqueness and taxonomic conservation priorities. Threat among marine chondrichthyan families varies with life history sensitivity
(maximum length) and exposure to fisheries (depth distribution). (A) Proportion of threatened data sufficient species and the richness of each taxonomic
family. Colored bands indicate the significance levels of a one-tailed binomial test at p=0.05, 0.01, and 0.001. Those families with significantly greater
(or lower) than expected threat levels at p<0.05 against a null expectation that extinction risk is equal across families (35.6%). (B) The most and least
threatened taxonomic families. (C) Average life history sensitivity and accessibility to fisheries of 56 chondrichthyan families. Significantly greater
(or lower) risk than expected is shown in red (green).
DOI: 10.7554/eLife.00590.012
The following source data are available for figure 6:
Source data 1. Number and IUCN Red List status of chondrichthyan species in IUCN Red List categories by family (alphabetically within each order).
DOI: 10.7554/eLife.00590.013
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 13 of 34
Research article
other exploited organisms (Veitch et al., 2012). More than 50 sharks are included in Annex I (Highly
Migratory Species) of the 1982 Law of the Sea Convention, implemented on the high seas under the
1992 Fish Stocks Agreement, but currently only a handful enjoy species-specific protections under the
world’s Regional Fishery Management Organizations (Table 6), and many of these have yet to be
implemented domestically. The Migratory Sharks Memorandum of Understanding (MoU) adopted by
the Parties to the Convention on Migratory Species (CMS) so far only covers seven sharks, yet there
may be more than 150 chondrichthyans that regularly migrate across national boundaries (Fowler,
2012). To date, only one of the United Nations Environment Programme’s Regional Seas Conventions,
the Barcelona Convention for the Conservation of the Mediterranean Sea, includes chondrichthyan
fishes and only a few of its Parties have taken concrete domestic action to implement these listings.
Despite two decades of effort, only ten sharks and rays had been listed by the Convention on
International Trade in Endangered Species (CITES) up to 2013 (Vincent et al., 2014). A further seven
species of shark and ray were listed by CITES in 2013—the next challenge is to ensure effective imple-
mentation of these trade regulations (Mundy-Taylor and Crook, 2013). OSPAR (the Convention for
the Protection of the marine Environment of the North-East Atlantic) lists many threatened shark and
ray species, but its remit excludes fisheries issues. Many chondrichthyans qualify for listing under CITES,
CMS, and various regional seas conventions, and should be formally considered for such action as a
complement to action by Regional Fisheries Management Organizations (RFMOs) (Table 6).
Bans on ‘finning’ (slicing off a shark’s fins and discarding the body at sea) are the most widespread
shark conservation measures. While these prohibitions, particularly those that require fins to remain
attached through landing, can enhance monitoring and compliance, they have not significantly
reduced shark mortality or risk to threatened species (Clarke et al., 2013). Steep declines and the high
threat levels in migratory oceanic pelagic sharks suggest raising the priority of improved management
of catch and trade through concerted actions by national governments working through RFMOs
as well as CITES, and CMS (Table 7).
A high proportion of catch landings come from nations with a large number of threatened chon-
drichthyans and less-than-comprehensive chondrichthyan fishery management plans. Future research
is required to down-scale these global Red List assessments and analyses to provide country-by-country
diagnoses of the link between specific fisheries and specific threats to populations of more broadly
distributed species (Wallace et al., 2010). Such information could be used to focus fisheries management
and conservation interventions that are tailored to specific problems. There is no systematic global
monitoring of shark and ray populations and the national fisheries catch landings statistics provide
invaluable data for tracking fisheries trends in unmanaged fisheries (Newton et al., 2007; Worm
et al., 2013). However, the surveillance power of such data could be greatly improved if collected at
greater taxonomic resolution. While there have been continual improvements, catches are under-
reported (Clarke et al., 2006), and for those that are reported only around one-third is reported at the
Table 4. Summary of explanatory Generalized Linear Mixed-effect Models of the life history and
geographic distributional correlates of IUCN status
Model structure
and hypothesis
Degrees of
freedom, k
likelihood AICcΔAIC
of fixed
effects only
of fixed
and random
maximum length 5 −197.06 404.3 28.31 0.000 0.32 0.58
…+ minimum
6 −187.013 386.3 10.29 0.005 0.48 0.65
…+…+ depth
7 −182.139 378.6 2.62 0.212 0.49 0.66
geographic range
8 −179.785 376.0 0 0.784 0.69 0.80
Species were scored as threatened (CR, EN, VU) = 1 or Least Concern (LC) = 0 for n = 367 marine species. AICc is
the Akaike information criterion corrected for small sample sizes; ΔAIC is the change in AICc. The models are
ordered by increasing complexity and decreasing AIC weight (largest ΔAIC to lowest). R2GLMM(m) is the marginal
R2 of the fixed effects only and R2GLMM(c) is the conditional R2 of the fixed and random effects.
DOI: 10.7554/eLife.00590.014
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 14 of 34
Research article
species level (Fischer et al., 2012). To comple-
ment improved catch landings data, we recom-
mend the development of repeat regional
assessments of the Red List Status of chondrich-
thyans to provide an early warning of adverse
changes in status and to detect and monitor the
success of management initiatives and inter-
ventions. Aggregate Red List Threat indices
for chondrichthyans, like those available for
mammals, birds, amphibians, and hard corals
(Carpenter et al., 2008) would provide one
of the few global scale indicators of progress
toward international biodiversity goals (Walpole
et al., 2009; Butchart et al., 2010).
Our global status assessment of sharks and
rays reveals the principal causes and severity of
global marine biodiversity loss, and the threat
level they face exposes a serious shortfall in the
conservation management of commercially-
exploited aquatic species (McClenachan et al.,
2012). Chondrichthyans have slipped through
the jurisdictional cracks of traditional national and
international management authorities. Rather
than accept that many chondrichthyans will inevi-
tably be driven to economic, ecological, or bio-
logical extinction, we warn that dramatic changes
in the enforcement and implementation of the
conservation and management of threatened
chondrichthyans are urgently needed to ensure
a healthy future for these iconic fishes and the
ecosystems they support.
IUCN Red List Assessment process
and data collection
We applied the Red List Categories and Criteria
developed by the International Union for
Conservation of Nature (IUCN) (IUCN, 2004) to
1,041 species at 17 workshops involving more
than 300 experts who incorporated all available
information on distribution, catch, abundance,
population trends, habitat use, life histories,
threats, and conservation measures.
Some 105 chondrichthyan fish species had been
assessed and published in the 2000 Red List of
Threatened Species prior to the initiation of the
Global Shark Red List Assessment (GSRLA). These
assessments were undertaken by correspondence
and through discussions at four workshops
(1996—London, UK, and Brisbane, Australia;
1997—Noumea, New Caledonia, and 1999—
Pennsylvania, USA). These assessments applied earlier versions of the IUCN Red List Criteria and, where
possible, were subsequently reviewed and updated according to version 3.1 Categories and Criteria
during the GSRLA. The IUCN Shark Specialist Group (SSG) subsequently held a series of 13 regional and
thematic Red List workshops in nine countries around the world (Table 8). Prior to the workshops, each
Figure 7. Global patterns of marine chondrichthyan
diversity, threat and knowledge. (A) Total chondrichthyan
richness, (B) the number of Data Deficient and threat
by major habitat: (C) coastal and continental shelf
(<200 m depth), (D) neritic and epipelagic (<200 m
depth), and (E) deepwater slope and abyssal plain
(>200 m) habitats. Numbers expressed as the total
number of species in each 23,322 km2 cell. The
numbers are hotspots refereed to in the text.
DOI: 10.7554/eLife.00590.015
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 15 of 34
Research article
participant was asked to select species for assessment based on their expertise and research areas.
Where possible, experts carried out research and preparatory work in advance, thus enabling more syn-
thesis to be achieved during each workshop. SSG Red List-trained personnel facilitated discussion and
consensus sessions, and coordinated the production of global Red List Assessments for species in each
region. For species that had previously been assessed, participants provided updated information and
assisted in revised assessments. Experts completed assessments for some wide-ranging, globally distrib-
uted species over the course of several workshops. In total, 302 national, regional, and international
experts from 64 countries participated in the GSRLA workshops and the production of assessments. All
Red List Assessments were based on the collective knowledge and pooled data from dedicated experts
Figure 9. Spatial variation in the relative extinction risk of marine chondrichthyans. Residuals of the relationship
between total number of data sufficient chondrichthyans and total number of threatened species per cell, where
positive values (orange to red) represent cells with higher threat than expected for their richness alone.
DOI: 10.7554/eLife.00590.017
Figure 8. Irreplaceability hotspots of the endemic threatened marine chondrichthyans. Endemics were defined as
species with an Extent of Occurrence of <500,000 km2 (n = 66). Irreplaceable cells with the greatest number of
small range species are shown in red, with blue cells showing areas of lower, but still significant irreplaceability.
Irreplaceability is the sum of the inverse of the geographic range sizes of all threatened endemic species in the cell.
A value of 0.1 means that on average a single cell represents one tenth of the global range of all the species
present in the cell. The numbers are hotspots referred to in the text.
DOI: 10.7554/eLife.00590.016
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 16 of 34
Research article
Table 5. Scientific and conservation priority according to threat, knowledge and endemicity by FAO Fishing Area
FAO Fishing Area
(ranked priority)
species (% of
total, n = 181)
Data Deficient
species (% of
total, n = 487)
Number of endemic
species (threatened
endemics) Threatened endemic species
(1) Indian, Eastern 67 (37.0) 69 (14.2) 58 (5) Atelomycterus baliensis, Himantura fluviatilis, Zearaja maugeana, Trygonorrhina melaleuca,
Urolophus orarius
(2) Pacific, Western Central 76 (42.0) 81 (16.6) 51 (14) Glyphis glyphis, Aulohalaelurus kanakorum, Hemitriakis leucoperiptera, Brachaelurus
colcloughi, Hemiscyllium hallstromi, H. strahani, Himantura hortlei, H. lobistoma, Pastinachus
solocirostris, Aptychotrema timorensis, Rhinobatos jimbaranensis, Rhynchobatus sp. nov. A,
Rhynchobatus springeri, Urolophus javanicus
(3) Pacific, Northwest 48 (26.5) 116 (23.8) 80 (6) Benthobatis yangi, Narke japonica, Raja pulchra, Squatina formosa, S. japonica, S. nebulosa
(4) Indian, Western 61 (33.7) 104 (21.4) 62 (8) Carcharhinus leiodon, Haploblepharus kistnasamyi, H. favus, H. punctatus, Pseudoginglymostoma
brevicaudatum, Electrolux addisoni, Dipturus crosnieri, Okamejei pita
(5) Atlantic, Western Central 32 (17.7) 81 (16.6) 62 (4) Diplobatis colombiensis, D. guamachensis, D. ommata, D. pictus
(6) Pacific, Southwest 34 (18.8) 49 (10.1) 28
(7) Atlantic, Southwest 52 (28.7) 52 (10.7) 37 (19) Galeus mincaronei, Schroederichthys saurisqualus, Mustelus fasciatus, M. schmitti, Atlantoraja
castelnaui, A. cyclophora, A. platana, Rioraja agassizii, Sympterygia acuta, Benthobatis kreffti,
Dipturus mennii, Gurgesiella dorsalifera, Rhinobatos horkelii, Zapteryx brevirostris, Rhinoptera
brasiliensis, Squatina argentina, S. guggenheim, S. occulta, S. punctata
(8) Atlantic, Southeast 37 (20.4) 51 (10.5) 13
(9) Atlantic, Eastern Central 42 (23.2) 44 (9.0) 6
(10) Pacific, Southeast 26 (14.4) 67 (13.8) 32 (3) Mustelus whitneyi, Triakis acutipinna, T. maculata
(11) Pacific, Eastern Central 20 (11.0) 52 (10.7) 19 (2) Urotrygon reticulata, U. simulatrix
(12) Atlantic, Northeast 33 (18.2) 23 (4.7) 8
(13) Atlantic, Northwest 22 (12.2) 17 (3.5) 3 (1) Malacoraja senta
(14) Mediterranean & Black Sea 34 (18.8) 16 (3.3) 3 (1) Leucoraja melitensis
(15) Pacific, Northeast 9 (5.0) 11 (2.3) 0
(16) Indian, Antarctic 1 (0.6) 4 (0.8) 2
(17) Atlantic, Antarctic 1 (0.6) 4 (0.8) 2
(18) Pacific, Antarctic 0 3 (0.6) 0
(19) Arctic Sea 0 0 0
Endemics were defined as those species found only within a single FAO Fishing Area. FAO Fishing Areas were ranked according to greatest species richness, percent threatened species, percent Data
Deficient species, number of endemic species and number of threatened endemic species.
DOI: 10.7554/eLife.00590.018
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 17 of 34
Research article
Figure 10. Elevated threat in chondrichthyans with
the largest geographic ranges, spanning the
greatest number of national jurisdictions. Frequency
distribution of number of jurisdictions spanned by all
chondrichthyans (black, n = 1,041) and threatened
species only (red, n = 174), for (A) country EEZs, and
(B) the overrepresentation of threatened species
spanning a large number of country EEZs, shown by
the log ratio of proportion of threatened species
over the proportion of all species. The proportion of
threatened species is greater than the proportion of
all species where the log ratio = 0, which corre-
sponds to range spans of 16 and more countries.
DOI: 10.7554/eLife.00590.019
across the world, ensuring global consultation
and consensus to achieve the best assessment for
each species with the knowledge and resources
available (‘Acknowledgements’). Any species
assessments not completed during the workshops
were finalized through subsequent correspondence
among experts.
The SSG evaluated the status of all described
chondrichthyan species that are considered to
be taxonomically valid up to August 2011 (see
“Systematics, missing species and species cov-
erage” below). Experts compiled peer-reviewed
Red List documentation for each species, including
data on: systematics, population trends, geo-
graphic range, habitat preferences, ecology, life
history, threats, and conservation measures. The
SSG assessed all species using the IUCN Red List
Categories and Criteria version 3.1 (IUCN, 2001).
The categories and their standard abbreviations
are: Critically Endangered (CR), Endangered (EN),
Vulnerable (VU), Near Threatened (NT), Least
Concern (LC), and Data Deficient (DD). Experts
further coded each species according to the
IUCN Habitats, Threats and Conservation Actions
Authority Files, enabling analysis of their habitat
preferences, major threats and conservation action
requirements. SSG Program staff entered all data
into the main data fields in the IUCN Species
Information Service Data Entry Module (SIS DEM)
and subsequently transferred these data into
the IUCN Species Information Service (SIS) in
Systematics, missing species and
species coverage
The SSG collated data on order, family, genus,
species, taxonomic authority, commonly-used
synonyms, English common names, other common
names, and taxonomic notes (where relevant).
For taxonomic consistency throughout the spe-
cies assessments, the SSG followed Leonard J V
Compagno’s 2005 Global Checklist of Living
Chondrichthyan Fishes (Compagno, 2005), only deviating from this where there was extensive
opposing consensus with a clear and justifiable alternative, as adjudicated by the IUCN SSG’s Vice
Chairs of Taxonomy, David E Ebert and William T White.
Keeping pace with the total number of chondrichthyans is a challenging task, especially given the
need to balance immediacy against taxonomic stability. One-third of all species have been described
in the past thirty years. Scientists have described a new chondrichthyan species, on average, almost
every 2–3 weeks since the 1970s (Last, 2007; White and Last, 2012). Since Leonard V J Compagno
completed the global checklist in 2005, scientists have recognized an additional 140 species (mostly
new) living chondrichthyan species. This increase in the rate of chondrichthyan descriptions in recent
years is primarily associated with the lead up to the publication of a revised treatment of the entire
chondrichthyan fauna of Australia (Last and Stevens, 2009), requiring formal descriptions of previ-
ously undescribed taxa. In particular, three CSIRO special publications published in 2008 included
descriptions of 70 previously undescribed species worldwide (Last et al., 2008a, 2008b, 2008c). The
number of new species described in 2006, 2007 and 2008 was 21, 23, and 81, respectively, with all but
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 18 of 34
Research article
nine occurring in the Indo–West Pacific. Additional nominal species of chondrichthyans are also
included following resurrection of previously unrecognized species such as the resurrection of
Pastinachus atrus for the Indo–Australian region, previously considered a synonym of P. sephen (Last
and Stevens, 1994). Scientists excluded some nominal species of dubious taxonomic validity from
this assessment. Thus, the total number of chondrichthyan species referred to in this paper (1,041)
does not include all recent new or resurrected species, which require future work for their inclusion in
the GSRLA.
Many more as yet undescribed chondrichthyan species exist. The chondrichthyan faunas in several
parts of the world (e.g., the northern Indian Ocean) are poorly known and a large number of species
are likely to represent complexes of several distinct species that require taxonomic resolution, for
example some dogfishes, skates, eagle rays, and stingrays (Iglésias et al., 2010; White and Last,
2012). Many areas of the Indian and Pacific Oceans are largely unexplored and, given the level of
micro-endemism documented for a number of chondrichthyan groups, it is likely that many more
species will be discovered in the future (Last, 2007; Naylor et al., 2012). For example, recent surveys
of Indonesian fish markets revealed more than 20 new species of sharks out of the approximately 130
recorded in total (White et al., 2006; Last, 2007; Ward et al., 2008).
Distribution maps
SSG experts created a shapefile of the geographic
distribution for each chondrichthyan species with
GIS software using the standard mapping protocol
for marine species devised by the IUCN GMSA
team ( The map shows
the Extent of Occurrence of the species cut to
one of several standardized basemaps depending
on the ecology of the species (i.e., coastal and
continental shelf, pelagic and deepwater). The
distribution maps for sharks are based on orig-
inal maps provided by the FAO and Leonard JV
Compagno. Maps for some of the batoids were
originally provided by John McEachran. New maps
for recently described species were drafted
where necessary. The original maps were updated,
corrected, or verified by experts at the Red List
workshops or out-of-session assessors and SSG
staff and then sent to the GMSA team who mod-
ified the shapefiles and matched them to the dis-
tributional text within the assessment.
Occurrence and habitat preference
SSG assessors assigned countries of occurrence
from the ‘geographic range’ section of the Red
List documentation and classified species to the
FAO Fishing Areas (
technical-documents/data-organization) in which
they occur (Figure 2—figure supplement 1).
Each species was coded according to the IUCN
Habitats Authority File (http://www.iucnredlist.
habitats-classification-scheme-ver3). These cate-
gorizations are poorly developed and often irrel-
evant for coastal and offshore marine animals.
For the purposes of analysis presented here we
assigned chondrichthyans to five unique habi-
tat-lifestyle combinations (coastal and continental
shelf, pelagic, meso- and bathypelagic, deepwater,
Table 6. Progress toward regional and
international RFMO management measures
for sharks and rays
1. Bans on ‘finning’ (the removal of a shark’s fins and
discarding the carcass at sea) through most RFMOs
(Fowler and Séret, 2010);
2. North East Atlantic Fisheries Commission (NEAFC)
bans on directed fishing for species not actually
targeted within the relevant area (Spiny dogfish
[Squalus acanthias], Basking shark [Cetorhinus
maximus], Porbeagle shark [Lamna nasus]) (NEAFC,
3. Convention on the Conservation of Antarctic Marine
Living Resources bans on ‘directed’ fishing for skates
and sharks and bycatch limits for skates (CCMLR,
4. A Northwest Atlantic Fisheries Organization (NAFO)
skate quota (note: this has consistently been set higher
than the level advised by scientists since its
establishment in 2004) (NAFO, 2011);
5. International Commission for the Conservation of
Atlantic Tunas (ICCAT) bans on retention,
transshipment, storage, landing, and sale of Bigeye
Thresher (Alopias superciliosus), and Oceanic whitetip
shark (Carcharhinus longimanus), and partial bans
(developing countries excepted under certain
circumstances) on retention, transshipment, storage,
landing, and sale of most hammerheads (Sphyrna spp.),
and retention, transshipment, storage, and landing (but
not sale) of Silky shark (Carcharhinus falciformis) (Kyne
et al., 2012);
6. An Inter-American Tropical Tuna Commission (IATTC)
ban on retention, transshipment, storage, landing, and
sale of Oceanic whitetip sharks (IATTC, 2011);
7. An Indian Ocean Tuna Commission (IOTC) ban on
retention, transshipment, storage, landing, and sale of
thresher sharks-with exceptionally low compliance and
reportedly low effectiveness (IOTC, 2011); and,
8. A Western and Central Pacific Fisheries Commission
ban on retention, transshipment, storage, and landing
(but not sale) of Oceanic whitetip sharks (Clarke et al.,
DOI: 10.7554/eLife.00590.020
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 19 of 34
Research article
and freshwater) mainly according to depth distri-
bution and, to a lesser degree, position in the
water column. The pelagic group includes both
neritic (pelagic on the continental shelf) and epi-
pelagic oceanic (pelagic in the upper 200 m of
water over open ocean) species. Species habitats
were classified based on the findings from the
workshops combined with a review of the pri-
mary literature, FAO fisheries guides and field
guides (Cavanagh et al., 2003; Cavanagh and
Gibson, 2007; Cavanagh et al., 2008; Gibson
et al., 2008; Camhi et al., 2009; Kyne et al.,
2012). Species habitat classifications tended to
be similar across families, but for some species
the depth distributions often spanned more than
one depth category and for these species habitat
was assigned according to the predominant loca-
tion of each species throughout the majority of its
life cycle (Compagno, 1990). This issue was mainly
confined to coastal and continental shelf species
that exhibited distributions extending down the
continental slopes (e.g., some Dasyatis, Mustelus,
Rhinobatos, Scyliorhinus, Squalus, and Squatina).
We caution that some of the heterogeneity in
depth distribution or unusually large distributions
may reflect taxonomic uncertainty and the exist-
ence of species complexes (White and Last,
2012). We defined the deep sea as beyond the
continental and insular shelf edge at depths greater
than or equal to 200 m. Coastal and continental
shelf includes predominantly demersal species
(those spending most time dwelling on or near
the seabed), and excluded neritic chondrichthy-
ans. Pelagic species included macrooceanic and
tachypelagic ocean-crossing epipelagic sharks
with circumglobal distributions as well as sharks
suspected of ocean-crossing because they exhibit
circumglobal but disjunct distributions, for example
Galapagos shark (Carcharhinus galapagensis).
Our classification resulted in a total of 33 obli-
gate freshwater and 1,008 marine and euryhaline
chondrichthyans of which 482 species were found
predominantly in coastal and continental shelf, 39
in pelagic, 479 in deepwater, and eight in meso-
and bathypelagic habitats. To evaluate whether
the geographic patterns of threat are robust to
alternate unique or multiple habitat classifications
we considered two alternate classification schemes,
one where species were classified into a single
habitat and another where species were classified
in one or more habitats. The alternate unique
classification scheme yielded 42 pelagic (Camhi
et al., 2009), and 452 deepwater chondrichthyans
(Kyne and Simpfendorfer, 2007), leaving 517
coastal and continental shelf and 33 obligate
freshwater species (totaling 1,044, based on an
Table 7. Management recommendations: the
following actions would contribute to rebuilding
threatened chondrichthyan populations and
properly managing associated fisheries
Fishing nations and regional fisheries management
organizations (RFMOs) are urged to:
1. Implement, as a matter of priority, scientific advice
for protecting habitat and/or preventing overfishing of
chondrichthyan populations;
2. Draft and implement Plans of Action pursuant to
the International Plan Of Action (IPOA–Sharks), which
include, wherever possible, binding, science-based
management measures for chondrichthyans and their
essential habitats;
3. Significantly increase observer coverage,
monitoring, and enforcement in fisheries taking
4. Require the collection and accessibility of
species-specific chondrichthyan fisheries data, including
discards, and penalize non-compliance;
5. Conduct population assessments for
6. Implement and enforce chondrichthyan fishing
limits in accordance with scientific advice; when
sustainable catch levels are uncertain, set limits based
on the precautionary approach;
7. Strictly protect chondrichthyans deemed
exceptionally vulnerable through Ecological Risk
Assessments and those classified by IUCN as Critically
Endangered or Endangered;
8. Prohibit the removal of shark fins while onboard
fishing vessels and thereby require the landing of sharks
with fins naturally attached; and,
9. Promote research on gear modifications, fishing
methods, and habitat identification aimed at mitigating
chondrichthyan bycatch and discard mortality.
National governments are urged to:
10. Propose and work to secure RFMO management
measures based on scientific advice and the
precautionary approach;
11. Promptly and accurately report species-specific
chondrichthyan landings to relevant national and
international authorities;
12. Take unilateral action to implement domestic
management for fisheries taking chondrichthyans,
including precautionary limits and/or protective status
where necessary, particularly for species classified by
IUCN as Vulnerable, Endangered or Critically
Endangered, and encourage similar actions by other
Range States;
13. Adopt bilateral fishery management agreements
for shared chondrichthyan populations;
14. Ensure active membership in Convention on
International Trade in Endangered Species (CITES),
Convention for the Conservation of Migratory
Species (CMS), RFMOs, and other relevant regional
and international agreements;
15. Fully implement and enforce CITES
chondrichthyan listings based on solid non-detriment
findings, if trade in listed species is allowed;
Table 7. Continued on next page
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 20 of 34
Research article
older taxonomic scheme). When species were
classified in more than one habitat this resulted in
513 species in the coastal and continental shelf,
564 in deepwater, 54 in pelagic, and 13 meso-
and bathypelagic habitats. We found the geo-
graphic pattern of threat was robust to the choice
of habitat classification scheme, and we present
only the unique classification (482 coastal and
continental shelf, 39 pelagic, 479 deepwater hab-
itat species).
Major threats
SSG assessors coded each species according to
the IUCN Major threat Authority File (http://www.
We coded threats that appear to have an important impact, but did not describe their relative impor-
tance for each species.
The term ‘bycatch’ and its usage in the IUCN Major threat Authority File do not capture the
complexity and values of chondrichthyan fisheries. Some chondrichthyans termed ‘bycatch’ are actually
caught as ‘incidental or secondary catch’ as they are used to a similar extent as the target species or
are sometimes highly valued or at least welcome when the target species is absent. ‘Unwanted bycatch’
refers to cases where the chondrichthyans are not used and fishers would prefer to avoid catching
them (Clarke, S personal communication, Sasama Consulting, Shizuoka, Japan). If the levels of unwanted
bycatch are severe enough, chondrichthyans can be actively persecuted to avoid negative and costly
gear interactions—such as caused the near extirpation of the British Columbian population of Basking
shark (Cetorhinus maximus) (Wallace and Gisborne, 2006).
Red List Assessment
We assigned a Red List Assessment category for each species based on the information above using
the revised 2001 IUCN Red List Categories and Criteria (version 3.1;
documents/categories-and-criteria). We provided a rationale for each assessment justifying the classi-
fication along with a description of the relevant criteria used in the designation. Data fields also present
the reason for any change in Red List categories from previous assessments (i.e., genuine change in
status of species, new information on the species available, incorrect data used in previous assessments,
change in taxonomy, or previously incorrect criteria assigned to species); the current population trend
(i.e., increasing, decreasing, stable, unknown); date of assessment; names of assessors and evaluators
(effectively the peer-reviewers); and any notes relevant to the Red List category. The Red List docu-
mentation for each species assessment is supported by references to the primary and secondary literature
cited in the text.
Data entry, review, correction, and consistency checking
Draft regional Red List Assessments and supporting data were collated and peer-reviewed during the
workshops and through subsequent correspondence to produce the global assessment for each
species. At least one member of the SSG Red List team was present at each of the workshops to facilitate
a consistent approach throughout the data collection, review and evaluation process. Once experts
had produced draft assessments, SSG staff circulated summaries (comprised of rationales, Red List
Categories and Criteria) to the entire SSG network for comment. As the workshops took place over a
>10-year period, some species assessments were reviewed and updated at subsequent workshops or
by correspondence. Each assessment received a minimum of two independent evaluations as a part of
the peer-review process, either during or subsequent to the consensus sessions (a process involving
65 specialists and experts across 23 participating countries) prior to entry into the database and
submission to the IUCN Red List Unit.
SSG Red List-trained personnel undertook further checks of all assessments to ensure consistent
application of the Red List Categories and Criteria to each species, and the then SSG Co-chair Sarah
L Fowler, thoroughly reviewed every assessment produced from 1996 to 2009. Following the data
review and evaluation process, all species assessments were entered in the Species Information Service
database and checked again by SSG Red List Unit staff. IUCN Red List Program staff made the final
16. Propose and support the listing of additional
threatened chondrichthyan species under CITES and
CMS and other relevant wildlife conventions;
17. Collaborate on regional agreements and the CMS
migratory shark Memorandum of Understanding (CMS,
2010), with a focus on securing concrete conservation
actions; and,
18. Strictly enforce chondrichthyan fishing and
protection measures and impose meaningful penalties
for violations.
DOI: 10.7554/eLife.00590.021
Table 7. Continued
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 21 of 34
Research article
check prior to the acceptance of assessments in the Red List database and publication of assessments
and data online (
Subpopulation and regional assessments
We included only global species assessments in this analysis. In many cases, subpopulation and
regional assessments were developed for species before a global assessment could be made. For very
wide-ranging species, such as the oceanic pelagic sharks, a separate workshop was held to combine
these subpopulation or regional assessments (Table 8). A numerical value was assigned to each threat
category in each region where the species was assessed, and where possible these values were then
averaged to calculate a global threat category (rdenfors et al., 2001). Hence, the Red List categories
of some species may differ regionally; for example, porbeagle shark (Lamna nasus) is classified as VU
globally, but CR in the Northeast Atlantic and Mediterranean Sea. Often population trends were not
available across the full distribution of a species. In these cases, the degree to which the qualifying
threshold was met was modified according to the degree of certainty with which the trend could be
extrapolated across the full geographic range of a species. The calculation of the overall Red List cat-
egory for globally distributed species is challenging, particularly when a combination of two or more
of the following issues occurs: (1) trend data are available only for a part of the geographic range;
(2) regional trend data or stock assessments are highly uncertain; (3) the species is data-poor in some
other regions; (4) the species is subject to some form of management in other regions; and, (5) the
species is moderately productive (Dulvy et al., 2008). This situation is typified by the Blue shark
(Prionace glauca) that faces all of these issues. The best abundance trend data come from the
Atlantic Ocean, but the different time series available occasionally yield conflicting results; surveys
of some parts of the Atlantic exhibit declines of 53–80% in less than three generations (Dulvy et al.,
2008; Gibson et al., 2008), while a 2008 stock assessment conducted for the International Commission
for the Conservation of Atlantic Tuna (ICCAT) indicate, albeit with substantial uncertainty, that the
North Atlantic Blue shark population biomass is still larger than that required to generate Maximum
Sustainable Yield (BMSY) (Gibson et al., 2008). The Blue shark is one of the most productive of the
oceanic pelagic sharks, maturing at 4–6 years of age with an annual rate of population increase of
28% per year and an approximate BMSY at 42% of virgin biomass, B0 (Cortés, 2008; Simpfendorfer
et al., 2008). While the available data may support the regional listing of the Atlantic population
of this species in a threatened category, the assessors could not extrapolate this to the global
distribution because the species may be subject to lower fishing mortality in other regions. Hence
the Blue shark was listed as NT globally. Further details on this issue and additional data require-
ments to improve the assessment and conservation of such species are considered elsewhere
(Gibson et al., 2008; Camhi et al., 2009).
Red Listing marine fishes
We assessed most threatened chondrichthyans (81%, n = 148 of 181) using the Red List popula-
tion reduction over time Criterion A. Only one of the threatened species, the Skate (Dipturus) was
assessed under the higher decline thresholds of the A1 criterion, where ‘population reduction in
the past, where the causes are clearly reversible AND understood AND have ceased’. The remaining
threatened species were assessed using the IUCN geographic range Criterion B (n = 29) or the
small population size and decline Criterion C (n = 4: Borneo shark Carcharhinus borneensis,
Colclough’s shark Brachaelurus colcloughi, Northern river shark Glyphis garricki, and Speartooth
shark Glyphis glyphis). The Criterion A decline assessments were based on statistical analyses and
critical review of a tapestry of local catch per unit effort trajectories, fisheries landings trajectories
(often at lower taxonomic resolution), combined with an understanding of fisheries selectivity and
development trajectories.
We assessed most chondrichthyans using the Red List criterion based on population reduction
over time (Criterion A). The original thresholds triggering a threatened categorization were
Criterion A1: VU 20%; EN 50%; and CR 80% decline over the greater of the past (A1) or future (A2)
10 years or three generations (IUCN Categories and Criteria version 2.3). IUCN raised these
thresholds in 2001 to VU, 30%; EN, 50%; and CR, 80% decline over the greater of 10 years or
three generations in the past (A2), future (A3) and ongoing (A4), and changed A1 to a reduction
over the past 10 yrs or 3 generations of VU 50%; EN 70%; CR 90%, where the causes of reduction
are understood AND have ceased AND are reversible. This was in response to concerns that the
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 22 of 34
Research article
original thresholds were too low for managed populations that are being deliberately fished down
to MSY (typically assumed to be 50% of virgin biomass under Schaeffer logistic population growth)
(Reynolds et al., 2005). This revision was designed to improve consistency between fisheries limit
reference points and IUCN thresholds reducing the likelihood of false alarms—where a sustainably
exploited species incorrectly triggers a threat listing (Dulvy et al., 2005; Porszt et al., 2012).
Empirical testing shows that this has worked and demonstrates that a species exploited at fishing
mortality rates consistent with achieving MSY (FMSY) would lead to decline rates that would be
unlikely to be steep enough to trigger a threat categorization under these new thresholds (Dulvy
et al., 2005).
It is incontrovertible that a species that has declined by 80% over the qualifying time period is
at a greater relative risk of extinction than another that declined by 40% (in the same period).
Regardless, there may be a wide gap in the population decline trajectory between the point at
which overfishing occurs and the point where the absolute risk of extinction becomes a real con-
cern (Musick, 1999a). In addition, fisheries scientists have expressed concern that decline criteria
designed for assessing the extinction risk of a highly productive species may be inappropriate for
species with low productivity and less resilience (Musick, 1999a), although this was addressed
with the use of generation times to rescale decline rates to make productivity comparable (Reynolds
et al., 2005; Mace et al., 2008). In response to concerns that IUCN decline thresholds are too low
and risk false alarms, the American Fisheries Society (AFS) developed alternate decline criteria
(Musick, 1999a) to classify North American marine fish populations (Musick et al., 2000). This
approach only categorizes species that have undergone declines of 70–99% over the greater of
three generations or 10 years. Nonetheless, most of the species so listed by AFS also appear on
the relevant IUCN Specialist Group lists and vice versa, although the risk categories are slightly
different. The reason for the concordance is that in most instances the decline had far exceeded
50% over the appropriate timeframe long before it was detected. Consequently, SSG scientists
generally agreed in assigning threat categories to species that had undergone large declines, but
many were reluctant to assign a VU classification to species that were perceived to be at or near
50% virgin population levels and presumably near BMSY
. In practice, the latter were usually classified as
NT unless other circumstances (highly uncertain data, combined with widespread unregulated
fisheries) dictated a higher level of threat according to the precautionary principle.
Table 8. The locations, dates, number of participants and the number of countries represented at
each of the SSG Red List workshops, along with unique totals
Red List workshop Location Date Participants Countries
Australia and Oceania Queensland, Australia March 2003 26 5
South America Manaus, Brazil June 2003 25 8
Sub-equatorial Africa Durban, South Africa September 2003 28 9
Mediterranean San Marino October 2003 29 15
Deep sea sharks Otago Peninsula,
New Zealand
November 2003 32 11
North and Central
Florida, USA June 2004 55 13
Batoids (skates and
Cape Town, South Africa September 2004 24 11
Expert Panel Review Newbury, UK March 2005 12 5
Northeast Atlantic Peterborough, UK February 2006 25 9
West Africa Dakar, Senegal June 2006 25 12
Expert Panel Review Newbury, UK July 2006 9 12
Pelagic sharks Oxford, UK February 2007 18 11
Northwest Pacific/
Southeast Asia
Batangas, Philippines June/July 2007 23 13
Totals 227 57
DOI: 10.7554/eLife.00590.022
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 23 of 34
Research article
Statistical analysis
Modeling correlates of threat
Vulnerability to population decline or extinction is a function of the combination of the degree to
which intrinsic features of a species’ behavior, life history and ecology (sensitivity) may reduce the
capacity of a species to withstand an extrinsic threat or pressure (exposure). We tested the degree to
which intrinsic life histories and extrinsic fishing activity influenced the probability that a chondrichthyan
species was threatened. Threat category was modeled as a binomial response variable; with LC
species assigned a score of 0, and VU, EN & CR species assigned a 1. We used maximum body length
(cm), geographic range size (Extent of Occurrence, km2), and depth range (maximum–minimum depth,
m) as indices of intrinsic sensitivity, and minimum depth (m) and mean depth (maximum–minimum
depth/2) as a measure of exposure to fishing activity. All variables were standardized to z-scores by
subtracting the mean and dividing by the standard deviation to minimize collinearity (variance inflation
factors were less than 2). Mean depth was not included in model evaluation as it was computed from,
and hence, correlated to minimum depth (Spearman’s
= 0.52). We fitted Generalized Linear Mixed-
effect Models with binomial error and a logit link to model the probability of a species being threatened,
using taxonomic structure as a nested random effect (e.g., order/family/genus) to account for phylo-
genetic non-independence. The probability of a species i being threatened was assumed to be binomially
distributed with a mean pi, such that the linear predictor of pi was:
0 , , , ,
log = ,
i j i j i k i k
pX X
 
 
β β β
+ +
i,j and
i,k are the fitted coefficients for life history or geographic range traits j and k, and Xi,j and
Xi,k are the trait values of j and k for species i (Tables 4 and 9). The effect of a one standard deviation
increase in the coefficient of interest was computed as:
( )
( )
( )
( )
0 1 0 1
1/ 1 exp 1/ 1 ( ,)exp * 2
β β β β
+ + + +
following (Gelman and Hill, 2006). Models were fitted using the lmer function in the R package lme4
(Bates et al., 2011). The amount of variance explained by the fixed effects only and the combined
fixed and random effects of the binomial GLMM models was calculated as the marginal R2GLMM(m)
and conditional R2GLMM(c), respectively, using the methods described by Nagakawa and Schlielzeth
Estimating the proportion of potentially threatened DD species
We predicted the number of Data Deficient species that are potentially threatened based on the
maximum body size and geographic distribution traits (Table 3; Supplementary file 1). Specifically,
based on the explanatory models described above, all variables were log10 transformed and we
fitted generalized linear models of increasing complexity assuming a binomial error and logit link
(Equation 2; Table 3). Model performance was evaluated using Receiver Operating Characteristics
by comparing the predicted probability that the species was threatened p(THR) against the true
observed status (Least Concern = 0, and threatened [VU, EN & CR] = 1) (Sing et al., 2005; Porszt
et al., 2012). The prediction accuracy was calculated as the Area Under the Curve (AUC) of the
relationship between false positive rates and true positive rates, where a false positive is a model
prediction of 0.5 and true observed status is 0 (or <0.5 and 1) and a true positive is a prediction of
0.5 and true observed status is 1 (or <0.5 and 0). True and false positive rates, and accuracy (AUC)
were calculated using the R package ROCR (Sing et al., 2005). The probability that a DD species
was threatened p(THR)DD was predicted based on the available life history and distributional traits.
DD species with p(THR)DD 0.5 were classified as threatened and <0.5 as Least Concern. This
optimum classification threshold was confirmed by comparing accuracy across the full range of possible
thresholds (from 0 to 1). We fitted models using the gls function and calculated pseudo-R2 using the
package rms.
With these models we can estimate the number and proportion of species in each category
(Table 1). We estimated that 68 of 396 DD species are potentially threatened, and hence the
remainder (396–68 = 328) is likely to be either Least Concern or Near Threatened. Assuming these
species are distributed between these categories according to the observed ratio of NT:LC species of
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 24 of 34
Research article
0.5477 this results in a total of 312 (29.9%) Near Threatened species (132 known + 180 estimated)
and 389 (37.4%) Least Concern species (241 known +148 estimated). After apportioning the DD
species among threatened (68), NT (312), and LC (389), only 91 (8.7%; 487–396) are likely to be
Data Deficient (Table 1).
Spatial analysis
The SSG and the GMSA created ArcGIS distribution maps as polygons describing the geographical
range of each chondrichthyan depending on the individual species’ point location and depth informa-
tion. Pelagic species distribution maps were digitized by hand from the original map sources. For spatial
analyses, we merged all species maps into a single shapefile. We mapped species using a hexagonal grid
composed of individual units (cells) that retain their shape and area (23,322 km2) throughout the globe.
Specifically, we used the geodesic discrete global grid system, defined on an icosahedron and projected
to the sphere using the inverse Icosahedral Snyder Equal Area (ISEA) (Sahr et al., 2003). A row of cells
near longitude 180°E/W was excluded, as these interfered with the spatial analyses (Hoffmann et al.,
2010). Because of the way the marine species range maps are buffered, the map polygons are likely
to extrapolate beyond known distributions, especially for any shallow-water, coastal species, hence
not only will range size itself likely be an overestimate, but so will the number of hexagons.
We excluded obligate freshwater species from the final analysis as their distribution maps have yet
to be completed. The maps of the numbers of threatened species represent the sum of species that
have been globally assessed as threatened, in IUCN Red List categories VU, EN or CR, existing in each
23,322 km2 cell. We caution that this should not be interpreted to mean that species existing within
that grid cell are necessarily threatened in this specific location, rather that this location included species
that are threatened, on average, throughout their Extent of Occurrence. The number of threatened
species was positively related to the species richness of cells (F1, 14,846 = 1.5 e5, p<0.001, r2 = 0.91). To
remove this first-order effect and reveal those cells with greater and lower than expected extinction
risk, we calculated the residuals of a linear regression of the number of threatened species on the
number of non-DD species (referred to as data sufficient species). Cells with positive residuals were
mapped to show areas of greater than expected extinction risk compared to cells with equal or
negative residuals. Hexagonal cell information was converted to point features and smoothed across
neighboring cells using ordinary kriging using a spherical model in the Spatial Analyst package of ArcView.
Such smoothing can occasionally lead to contouring artefacts, such as the yellow wedge west of southern
Africa in Figure 7D, and we caution against over-interpreting marginal categorization changes.
We identified hotspots of threatened endemic chondrichthyans to guide conservation priorities. To
describe the potential cost of losing unique chondrichthyan faunas, we calculated irreplaceability
scores for each cell. Irreplaceability scores were calculated for each species as the reciprocal of its area
of occupancy measured as the number of cells occupied. For example, for a species with an Extent of
Occurrence spanning 100 hexagons, each hexagon in its range would have an irreplaceability 1/100 or
0.01 in each of the 100 hexagons of its Extent of Occurrence. The irreplaceability of each cell was
calculated by averaging log10 transformed irreplaceability scores of each species in each cell. Averaging
irreplaceability scores controls for varying species richness across cells. We calculated irreplaceability
both for all chondrichthyans and for threatened species only. Irreplaceability was also calculated using
only endemic threatened species, whereby endemicity was defined as species having an Extent of
Occurrence of <50,000, 100,000, 250,000 or 500,000 km2. Different definitions of endemicity gave
similar patterns of irreplaceability and we present the results of only the largest-scale definition of
endemicity. Hence the irreplaceability of threatened species and particularly the threatened endemic
chondrichthyans represents those locations or ‘hotspots’ (Myers et al., 2000) at greatest risk of losing
the most unique chondrichthyan biodiversity.
Fisheries catch landings and shark fin exports to Hong Kong
We extracted chondrichthyan landings reported to FAO by 146 countries and territories from a total
of 128 countries (as some chondrichthyan fishing nations are overseas territories, unincorporated
territories, or British Crown Dependencies) from FishStat (FAO, 2011). We categorized landings into
153 groupings, comprised of 128 species-specific categories (e.g., angular roughshark, piked dogfish,
porbeagle, Patagonian skate, plownose chimaera, small-eyed ray, etc) and 25 broader nei (nei = not
elsewhere included) groupings (e.g., such as various sharks nei, threshers sharks nei, ratfishes nei, raja
rays nei). For each country, all chondrichthyan landings in metric tonnes (t) were averaged over the decade
2000–2009. Landings reported as ‘<0.5’ were assigned a value of 0.5 t. Missing data reported as ‘.’ were
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 25 of 34
Research article
Table 9. Continued on next page
Table 9. Parameter estimates for General Linear Mixed-effects Models testing the probability that a
species is threatened p(THR) given either categorical habitat class or continuous measure of depth
distribution and maximum size
(A) Habitat category
p(THR) = maximum length + habitat category, random effect = Order/Family/Genus
Fixed effects Standardized coefficient Standard error p-value
Intercept (Coastal and
continental shelf)
0.27 0.33 0.4
Deepwater −2.01 0.39 <0.001
Pelagic −0.46 0.94 0.62
Maximum length 2.59 0.69 <0.001
marginal R2GLMM(m) of fixed effects only = 0.40.
conditional R2GLMM(c) of fixed and random effects = 0.60.
ΔAIC without taxonomic inclusion = −18.7.
ΔAIC for differing threat metrics: binomial THR (CR + EN + VU + NT) = −165.7; categorical = −975.6.
(B) Minimum depth
p(THR) = maximum length + minimum depth, random effect = Order/Family/Genus
Fixed effects Standardized coefficient Standard error p-value
Intercept −0.74 0.31 0.015
Minimum depth −2.73 0.78 <0.001
Maximum length 2.46 0.61 0.002
marginal R2GLMM(m) of fixed effects only = 0.48.
conditional R2GLMM(c) of fixed and random effects = 0.64.
ΔAIC without taxonomic inclusion = −12.9.
ΔAIC for differing threat metrics: binomial THR (CR + EN + VU + NT) = −153.4; categorical = −985.8.
(C) Maximum depth
p(THR) = maximum depth + maximum length, random effect = Order/Family/Genus
Fixed effects Standardized coefficient Standard error p-value
Intercept −0.60 0.28 <0.001
Maximum depth −2.35 0.54 <0.001
Maximum length 3.03 0.63 <0.001
marginal R2GLMM(m) of fixed effects only = 0.45.
conditional R2GLMM(c) of fixed and random effects = 0.63.
ΔAIC without taxonomic inclusion = −17.2.
ΔAIC for differing threat metrics: binomial THR (CR + EN + VU + NT) = −156.7; categorical = −981.7.
(D) Depth range
P(THR) = median depth + maximum length, random effect = Order/Family/Genus
Fixed effects Standardized coefficient Standard error p-value
Intercept −0.51 0.26 0.002
Depth range −1.82 0.50 <0.001
Maximum length 3.17 0.64 <0.001
marginal R2GLMM(m) of fixed effects only = 0.42.
conditional R2GLMM(c) = 0.62.
ΔAIC without taxonomic inclusion = −22.3.
ΔAIC for differing threat metrics: binomial THR (CR + EN + VU + NT) = −158.7; categorical = −982.3.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 26 of 34
Research article
assigned a zero. Total annual chondrichthyan landings are underestimated as data are not reported for
1,522 out of a total count of 13,990 entries in the dataset. Therefore, 11% of chondrichthyan landings
reported to the FAO over the 10-year period are ‘data unavailable, unobtainable’. We mapped FAO
chondrichthyan landings as the national percent share of the average total landings from 2000 to 2009.
For the analysis of landings over time we removed the aggregate category ‘sharks, rays, skates, etc’
and all nine of the FAO chimaera reporting categories. The ‘sharks, rays, skates, etc’ FAO reported
category comprised 15,684,456 tonnes of the reported catch from all countries during 1950–2009,
which is a total of 45% of the total reported catch for this time period. However, the proportion of
catch in this category has declined from around 50% of global catch to around 35%, presumably due to
better reporting of ray catch and as sharks have declined or come under stronger protection (Figure 1).
The nine chimaera categories make up a small fraction of the global catch, 249,404.5 tonnes from
1950 to 2009, representing 0.72% of the total catch.
Hong Kong has long served as one of the world’s largest entry ports for the global shark fin trade.
While fins are increasingly being exported to Mainland China where species-specific trade data is more
difficult to obtain, each year (from 1996 to 2001) Hong Kong handled around half of all fin imports
(Clarke et al., 2006). Data on shark fin exports to Hong Kong were requested directly from the Hong
Kong Census and Statistics Department (Hong Kong Special Administrative Region Government,
2011). We mapped exports to Hong Kong as the proportion of the summed total weight of the four
categories of shark fin exported to Hong Kong in 2010: (1) shark fins (with or without skin), with cartilage,
dried, whether or not salted but not smoked (trade code: 3055950), (2) shark fins (with or without skin),
without cartilage, dried, whether or not salted but not smoked (3055930), (3) shark fins (with or without
skin), without cartilage, salted or in brine, but not dried, or smoked (3056940), and (4) shark fins (with or
without skin), with cartilage, salted or in brine, but not dried or smoked (3056930). We could not correct
the difference in weight due to product type. To identify the threat classification of the chondrichthyan
species in the fin trade, we included records of the most numerous species used in the Hong Kong fin
trade as well as those species with the most-valued fins (Clarke et al., 2006, 2007; Clarke, 2008).
We thank the UN Food and Agriculture Organization and John McEachran for providing distribution
maps. We thank all SSG staff, interns and volunteers for logistical and technical support: Sarah
Ashworth, Gemma Couzens, Kendal Harrison, Adel Heenan, Catherine McCormack, Helen Meredith,
Kim O’Connor, Rachel Kay, Charlotte Walters, Lindsay MacFarlane, Lincoln Tasker, Helen Bates and
Rachel Walls. We thank Rowan Trebilco, Wendy Palen, Cheri McCarty, and Roger McManus for their
comments on the manuscript, and Statzbeerz and Shinichi Nagakawa for statistical advice. Opinions
expressed herein are of the authors only and do not imply endorsement by any agency or institution
associated with the authors.
Table 9. Continued
(E) Geographic range (Extent of Occurrence)
p(THR) = geographic range + maximum length, random effect = Order/Family/Genus
Fixed effects Standardized coefficient Standard error p-value
Intercept −0.50 0.52 0.33
Geographic range 5.22 3.7 0.12
Maximum length 2.16 0.75 0.004
marginal R2GLMM(m) of fixed effects only = 0.65.
conditional R2GLMM(c) = 0.81.
ΔAIC without taxonomic inclusion = −25.8.
ΔAIC for differing threat metrics: binomial THR (CR + EN + VU + NT) = −156.5; categorical = −982.9.
The improvement of model fit by inclusion of phylogenetic random effect was calculated as the difference in AIC
(ΔAIC) between the GLMM (with phylogenetic random effect) and a GLM as ΔAIC = AIC(GLMM)-AIC(GLM). p(THR)
was binomially distributed assuming species that were CR, EN or VU were threatened (1) and LC species were not
(0). We present ΔAIC for two other threat classifications, assuming: THR also includes NT species, or THR was a
continuous categorical variable ranging from LC = 0 to CR = 5.
DOI: 10.7554/eLife.00590.023
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 27 of 34
Research article
Assessing species for the IUCN Red List relies on the willingness of dedicated experts to contribute
and pool their collective knowledge, thus allowing the most reliable judgments of a species’ status
to be made. Without their enthusiastic commitment to species conservation, this work would not be
possible. We therefore thank all of the SSG members, invited national, regional and international experts
who have attended Regional, Generic and Expert Review SSG Red List workshops, and all experts
who have contributed data and their expertise by correspondence. A total of 209 SSG members and
invited experts participated in regional and thematic workshops and a total of 302 scientists and
experts were involved in the process of assessing and evaluating the species assessments. We express
our sincere thanks and gratitude to the following people who have contributed to the GSRLA since 1996.
We ask forgiveness for any names that may have been inadvertently omitted or misspelled.
Acuña E, Adams W, Affronte M, Aidar A, Alava M, Ali A, Amorim A, Anderson C, Arauz R, Arfelli C,
Baker J, Baker K, Baranes A, Barker A, Barnett L, Barratt P, Barwick M, Bates H, Batson P, Baum J, Bell
J, Bennett M, Bertozzi M, Bethea D, Bianchi I, Biscoito M, Bishop S, Bizzarro J, Blackwell R, Blasdale T,
Bonfil R, Bradaï MN, Brahim K, Branstetter S, Brash J, Bucal D, Cailliet G, Caldas JP, Camara L, Camhi M,
Capadan P, Capuli E, Carlisle A, Carocci F, Casper B, Castillo-Geniz L, Castro A, Charvet P, Chiaramonte G,
Chin A, Clark T, Clarke M, Clarke S, Cliff G, Clò S, Coelho R, Conrath C, Cook S, Cooke A, Correia J,
Cortés E, Couzens G, Cronin E, Crozier P, Dagit D, Davis C, de Carvalho M, Delgery C, Denham J,
Devine J, Dharmadi, Dicken M, Di Giácomo E, Diop M, Dipper F, Domingo A, Doumbouya F, Drioli M,
Ducrocq M, Dudley S, Duffy C, Ellis J, Endicott M, Everett B, Fagundes L, Fahmi, Faria V, Fergusson I,
Ferretti F, Flaherty A, Flammang B, Freitas M, Furtado M, Gaibor N, Gaudiano J, Gedamke T, Gerber L,
Gledhill D, Góes de Araújo ML, Goldman K, Gonzalez M, Gordon I, Graham K, Graham R, Grubbs R,
Gruber S, Guallart J, Ha D, Haas D, Haedrich R, Haka F, Hareide N-R, Haywood M, Heenan A, Hemida F,
Henderson A, Herndon A, Hicham M, Hilton–Taylor C, Holtzhausen H, Horodysky A, Hozbor N, Hueter R,
Human B, Huveneers C, Iglésias S, Irvine S, Ishihara H, Jacobsen I, Jawad L, Jeong C-H, Jiddawi N,
Jolón M, Jones A, Jones L, Jorgensen S, Kohin S, Kotas J, Krose M, Kukuev E, Kulka D, Lamilla J,
Lamónaca A, Last P, Lea R, Lemine Ould S, Leandro L, Lessa R, Licandeo R, Lisney T, Litvinov F, Luer C,
Lyon W, Macias D, MacKenzie K, Mancini P, Mancusi C, Manjaji Matsumoto M, Marks M, Márquez-Farias J,
Marshall A, Marshall L, Martínez Ortíz J, Martins P, Massa A, Mazzoleni R, McAuley R, McCord M,
McCormack C, McEachran J, Medina E, Megalofonou P, Mejia-Falla P, Meliane I, Mendy A, Menni R,
Minto C, Mitchell L, Mogensen C, Monor G, Monzini J, Moore A, Morales M.R.J, Morey G, Morgan A,
Mouni A, Moura T, Mycock S, Myers R, Nader M, Nakano H, Nakaya K, Namora R, Navia A, Neer J,
Nel R, Nolan C, Norman B, Notarbartolo di Sciara G, Oetinger M, Orlov A, Ormond C, Pasolini P,
Paul L, Pegado A, Pek Khiok A.L, Pérez M, Pérez-Jiménez J.C, Pheeha S, Phillips D, Pierce S, Piercy A,
Pillans R, Pinho M, Pinto de Almeida M, Pogonoski J, Pollard D, Pompert J, Quaranta K, Quijano S,
Rasolonjatovo H, Reardon M, Rey J, Rincón G, Rivera F, Robertson R, Robinson L, J.R, Romero M, Rosa
R, Ruίz C, Saine A, Salvador N, Samaniego B, San Martín J, Santana F, Santos Motta F, Sato K,
Schaaf-DaSilva J, Schembri T, Seisay M, Semesi S, Serena F, Séret B, Sharp R, Shepherd T, Sherrill-
Mix S, Siu S, Smale M, Smith M, Snelson, Jr, F, Soldo A, Soriano-Velásquez S, Sosa-Nishizaki O, Soto
J, Stehmann M, Stenberg C, Stewart A, Sulikowski J, Sundström L, Tanaka S, Taniuchi T, Tinti F, Tous
P, Trejo T, Treloar M, Trinnie F, Ungaro N, Vacchi M, van der Elst R, Vidthayanon C, Villavicencio-
Garayzar C, Vooren C, Walker P, Walsh J, Wang Y, Williams S, Wintner S, Yahya S, Yano K, Zebrowski
D & Zorzi G.
Additional information
Funder Author
Conservation International Sarah L Fowler
Packard Foundation Sarah L Fowler
Save Our Seas Foundation Nicholas K Dulvy
UK Department of Environment and Rural Affairs Sarah L Fowler
US State Department Nicholas K Dulvy,
Sarah L Fowler
US Department of Commerce Nicholas K Dulvy
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 28 of 34
Research article
Funder Author
Marine Conservation Biology Institute Sarah L Fowler
Pew Marine Fellows Program Sarah L Fowler
Mohamed bin Zayed Species Conservation Foundation Nicholas K Dulvy
Zoological Society of London Nicholas K Dulvy
Canada Research Chairs Program Nicholas K Dulvy
Natural Environment Research Council, Canada Nicholas K Dulvy
Tom Haas and the New Hampshire Charitable Foundation Sarah L Fowler
Oak Foundation Sarah L Fowler
Future of Marine Animal Populations, Census of Marine Life Sarah L Fowler
IUCN Centre for Mediterranean Cooperation Sarah L Fowler
UK Joint Nature Conservation Committee Sarah L Fowler
National Marine Aquarium, Plymouth UK Sarah L Fowler
New England Aquarium Marine Conservation Fund Sarah L Fowler
The Deep, Hull, UK Sarah L Fowler
Blue Planet Aquarium, UK Sarah L Fowler
Chester Zoo, UK Nicholas K Dulvy,
Sarah L Fowler
Lenfest Ocean Program Sarah L Fowler
WildCRU, Wildlife Conservation Research Unit,
University of Oxford, UK
Sarah L Fowler
Institute for Ocean Conservation Science,
University of Miami
Sarah L Fowler
Flying Sharks Nicholas K Dulvy
The funders had no role in study design, data collection and interpretation, or the
decision to submit the work for publication.
Author contributions
NKD, SLF, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting
or revising the article, Contributed unpublished essential data or reagents; JAM, CG, Acquisition of
data, Drafting or revising the article; RDC, Conception and design, Acquisition of data, Analysis and
interpretation of data, Drafting or revising the article; PMK, LRH, SV, Acquisition of data, Analysis and
interpretation of data, Drafting or revising the article; JKC, LNKD, MPF, GHB, SRL, Analysis and inter-
pretation of data, Drafting or revising the article; SVF, JCS, JDS, Analysis and interpretation of data,
Drafting or revising the article, Contributed unpublished essential data or reagents; CMP, Acquisition
of data, Analysis and interpretation of data; CAS, Conception and design, Analysis and interpretation
of data, Drafting or revising the article; KEC, Analysis and interpretation of data, Contributed unpub-
lished essential data or reagents; LJVC, Acquisition of data, Drafting or revising the article, Contributed
unpublished essential data or reagents; DAE, MRH, WTW, Drafting or revising the article, Contributed
unpublished essential data or reagents
Additional files
Supplementary files
• Supplementary le 1. The Data Decient chondrichthyan species that are potentially threatened.
DOI: 10.7554/eLife.00590.024
Supplementary le 2. (A) IUCN Red List status of chondrichthyans in the fin trade, including
(i) families with the most-valued fins, and (ii) the most prevalent species utilized in the Hong Kong fin trade.
(B) Chondrichthyan species threatened by (i) control measures, and (ii) habitat destruction and degradation,
pollution or climate change with the corresponding IUCN threat classification (Salafsky et al., 2008).
(C) Irreplaceable: the 66 threatened endemic sharks and rays ordered in decreasing irreplaceability.
DOI: 10.7554/eLife.00590.025
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 29 of 34
Research article
Major datasets
The following dataset was generated:
Author(s) Year Dataset title Dataset ID and/or URL
Database, license,
and accessibility
The International Union for
Conservation of Nature
2013 The IUCN Red List of
Threatened Species Publicly available.
Akcakaya HR, Ferson S, Burgman MA, Keith DA, Mace GM, Todd CR. 2000. Making consistent IUCN classifications
under uncertainty. Conservation Biology 14:1001–1013. doi: 10.1046/j.1523-1739.2000.99125.x.
Anderson SC, Farmer RG, Ferretti F, Houde ALS, Hutchings JA. 2011a. Correlates of vertebrate extinction risk in
Canada. Bioscience 61:538–549. doi: 10.1525/bio.2011.61.7.8.
Anderson SC, Flemming JM, Watson R, Lotze HK. 2011b. Serial exploitation of global sea cucumber fisheries.
Fish and Fisheries 12:317–339. doi: 10.1111/j.1467-2979.2010.00397.x.
Barker MJ, Schluessel V. 2005. Managing global shark fisheries: suggestions for prioritizing management
strategies. Aquatic Conservation: Marine and Freshwater Ecosystems 15:325–347. doi: 10.1002/aqc.660.
Barnett LAK, Winton MV, Ainsley SM, Cailliet GM, Ebert DA. 2013. Comparative demography of skates:
life-history correlates of productivity and implications for management. PLOS ONE 8:e65000. doi: 10.1371/
Bates D, Maechler M, Bolker B. 2011. lme4: linear mixed-effects models using S4 classes. R package version
Bornatowski H, Braga RR, Vitule JRS. 2013. Shark mislabeling threatens biodiversity. Science 340:923.
doi: 10.1126/science.340.6135.923-a.
Branch TA, Jensen OP, Ricard D, Ye Y, Hilborn R. 2011. Contrasting global trends in marine fishery status
obtained from catches and from stock assessments. Conservation Biology 25:777–786. doi: 10.1111/j.1523-
Butchart SHM, Walpole M, Collen B, van Strien A, Scharlemann JPW, Almond REA, Baillie JEM, Bomhard B,
Brown C, Bruno J, Carpenter KE, Carr GM, Chanson J, Chenery AM, Csirke J, Davidson NC, Dentener F,
Foster M, Galli A, Galloway JN, Genovesi P, Gregory RD, Hockings M, Kapos V, Lamarque JF, Leverington F,
Loh J, McGeoch MA, McRae L, Minasyan A, Morcillo MH, Oldfield TEE, Pauly D, Quader S, Revenga C, Sauer JR,
Skolnik B, Spear D, Stanwell-Smith D, Stuart SN, Symes A, Tierney M, Tyrrell TD, Vie JC, Watson R. 2010.
Global biodiversity: indicators of recent declines. Science 328:1164–1168. doi: 10.1126/science.1187512.
Camhi MD, Valenti SV, Fordham SV, Fowler SL, Gibson C. 2009. The conservation status of pelagic sharks and
rays: Report of the IUCN shark specialist group pelagic shark red list workshop. Newbury, UK: IUCN Species
Survival Commission Shark Specialist Group. p. 78.
Cardillo M, Mace GM, Jones KE, Bielby J, Binida-Edmonds ORP, Sechrest W, Orme CDL, Purvis A. 2005.
Multiple causes of high extinction risk in large mammal species. Science 309:1239–1241. doi: 10.1126/
Carpenter KE, Abrar M, Aeby G, Aronson RB, Banks S, Bruckner A, Chiriboga A, Cortes J, Delbeek JC,
DeVantier L, Edgar GJ, Edwards AJ, Fenner D, Guzman HM, Hoeksema BW, Hodgson G, Johan O, Licuanan
WY, Livingstone SR, Lovell ER, Moore JA, Obura DO, Ochavillo D, Polidoro BA, Precht WF, Quibilan MC,
Reboton C, Richards ZT, Rogers AD, Sanciangco J, Sheppard A, Sheppard C, Smith J, Stuart S, Turak E, Veron
JEN, Wallace C, Weil E, Wood E. 2008. One-third of reef-building corals face elevated extinction risk from
climate change and local impacts. Science 321:560–563. doi: 10.1126/science.1159196.
Cavanagh RD, Fowler SL, Camhi MD. 2008. Pelagic sharks and the FAO international plan of action for the
conservation and management of sharks. In: Camhi MD, Pikitch EK, Babcock EA, editors. Sharks of the open
ocean. Biology, fisheries and conservation. Oxford: Blackwell. p. 478–492.
Cavanagh RD, Gibson C. 2007. Overview of the conservation status of cartilaginous fishes (Chondrichthyans) in
the Mediterranean Sea. Gland, Switzerland and Malaga, Spain: IUCN Species Survival Commission Shark
Specialist Group. p. 42.
Cavanagh RD, Kyne PM, Fowler SL, Musick JA, Bennett MB. 2003. The conservation status of Australasian
chondrichthyans: Report of the IUCN shark specialist group Australia and Oceania regional red list workshop.
Brisbane, Australia: The University of Queensland, School of Biomedical Sciences. p. 170.
CCMLR. 2011. Conservation Measure 41-10 (2010) Limits on the exploratory fishery for Dissostichus spp. in
Statistical Subarea 88.2 in the 2010/11 season. Commission on the Conservation of Antarctic Marine Living
Resource. Hobart, Tasmania. p. 3.
Chin A, Kyne PM, Walker TI, McAuley RB. 2010. A new integrated risk assessment for climate change: analysing
the vulnerability of sharks and rays on Australia’s Great Barrier Reef. Global Change Biology 16:1936–1953.
doi: 10.1111/j.1365-2486.2009.02128.x.
Clarke SC. 2008. Use of shark fin trade data to estimate historic total shark removals in the Atlantic Ocean.
Aquatic Living Resources 21:373–381. doi: 10.1051/alr:2008060.
Clarke SC, Harley SJ, Hoyle SD, Rice JS. 2013. Population trends in Pacific oceanic sharks and the utility of
regulations on shark finning. Conservation Biology 27:197–209. doi: 10.1111/j.1523-1739.2012.01943.x.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 30 of 34
Research article
Clarke SC, McAllister MK, Milner-Gulland EJ, Kirkwood GP, Michielsens CGJ, Agnew DJ, Pikitch EK, Nakano H,
Shivji MS. 2006. Global estimates of shark catches using trade records from commercial markets. Ecology
Letters 9:1115–1126. doi: 10.1111/j.1461-0248.2006.00968.x.
Clarke SC, Milner-Gulland EJ, Bjørndal T. 2007. Social, economic and regulatory drivers of the shark fin trade.
Marine Resource Economics 22:305–327.
CMS. 2010. Memorandum of understanding on the conservation of migratory sharks. United nations environment
programme, convention on migratory species.
Collette BB, Carpenter KE, Polidoro BA, J Jorda MJ, Boustany A, Die DJ, Elfes C, Fox W, Graves J, Harrison L,
McManus R, Minte-Vera CV, Nelson RJ, Restrepo V, Schratwieser J, Sun C-L, Amorim A, Brick Peres M, Canales
C, Cardenas G, Chang S-K, Chiang W-C, de Oliveira Leite JN, Harwell H, Lessa R, Fredou FL, Oxenford HA,
Serra R, Shao K-T, Sumaila R, Wang S-P, Watson R, Yáñez E. 2011. High value and long-lived - double jeopardy
for tunas and billfishes. Science 333:291–292. doi: 10.1126/science.1208730.
Compagno LJV. 1990. Alternative life-history styles of cartilaginous fishes in time and space. Environmental
Biology of Fishes 28:33–75. doi: 10.1007/BF00751027.
Compagno LJV. 2005. Checklist of living chondrichthyan fishes. In: Fowler SL, Cavanagh R, Camhi M, Burgess
GH, Caillet GM, Fordham S, Simpfendorfer CA, Musick JA, editors. Sharks, Rays and Chimaeras: the Status of
the Chondrichthyan Fishes. Gland, Switzerland: IUCN/SSC Shark Specialist Group. p. 401–423.
Cortés E. 2000. Life history patterns and correlations in sharks. Reviews in Fisheries Science 8:299–344.
Cortés E. 2002. Incorporating uncertainty into demographic modelling: application to shark populations and
their conservation. Conservation Biology 18:1048–1062. doi: 10.1046/j.1523-1739.2002.00423.x.
Cortés E. 2008. Comparative life history and demography of pelagic sharks. In: Camhi MD, Pikitch EK,
Babcock EA, editors. Sharks of the Open Ocean. Biology, Fisheries and Conservation. Oxford: Blackwell.
p. 309–322.
COSEWIC. 2010. COSEWIC assessment and status report on the Barndoor skate (Dipturus laevis) in Canada.
Committee on the Status of Endangered Wildlife in Canada. Ottawa, Canada. p. xiii + 71.
Costello C, Ovando D, Hilborn R, Gaines SD, Deschenes O, Lester SE. 2012. Status and solutions for the world’s
unassessed fisheries. Science 338:517–520. doi: 10.1126/science.1223389.
Darwall WRT, Holland RA, Smith KG, Allen D, Brooks EGE, Katarya V, Pollock CM, Shi YC, Clausnitzer V,
Cumberlidge N, Cuttelod A, Dijkstra KDB, Diop MD, Garcia N, Seddon MB, Skelton PH, Snoeks J, Tweddle D,
Vie JC. 2011. Implications of bias in conservation research and investment for freshwater species. Conservation
Letters 4:474–482. doi: 10.1111/j.1755-263X.2011.00202.x.
Davidson AD, Boyer AG, Kim H, Pompa-Mansilla S, Hamilton MJ, Costa DP, Ceballos G, Brown JH. 2012. Drivers
and hotspots of extinction risk in marine mammals. Proceedings Of the National Academy Of Sciences Of the
United States Of America 109:3395–3400. doi: 10.1073/pnas.1121469109.
Davies RG, Orme CDL, Olson V, Thomas GH, Ross SG, Ding TS, Rasmussen PC, Stattersfield AJ,
Bennett PM, Blackburn TM, Owens IPF, Gaston KJ. 2006. Human impacts and the global distribution
of extinction risk. Proceedings of the Royal Society B-Biological Sciences 273:2127–2133. doi: 10.1098/
Díaz S, Fargione J, Chapin FS III, Tilman D. 2006. Biodiversity loss threatens human well-being. PLOS Biology
4:1300–1305. doi: 10.1371/journal.pbio.0040277.
Dudley SFJ, Simpfendorfer CA. 2006. Population status of 14 shark species caught in the protective gillnets off
KwaZulu-Natal beaches, South Africa, 1978-2003. Marine and Freshwater Research 57:225–240. doi: 10.1071/
Dulvy NK. 2000. Dipturus [Raja] laevis, Mitchill, 1818. IUCN, Gland, Switzerland.
Dulvy NK, Baum JK, Clarke S, Compagno LJV, Cortés E, Domingo A, Fordham S, Fowler S, Francis MP, Gibson C,
Martínez J, Musick JA, Soldo A, Stevens JD, Valenti S. 2008. You can swim but you can’t hide: the global status
and conservation of oceanic pelagic sharks. Aquatic Conservation: Marine and Freshwater Ecosystems 18:459–482.
doi: 10.1002/aqc.975.
Dulvy NK, Forrest RE. 2010. Life histories, population dynamics, and extinction risks in chondrichthyans. In: Carrier JC,
Musick JA, Heithaus MR, editors. Sharks and their relatives II: biodiversity, adaptive physiology, and conservation.
Boca Raton: CRC Press. p. 635–676.
Dulvy NK, Jennings SJ, Goodwin NB, Grant A, Reynolds JD. 2005. Comparison of threat and exploitation status
in Northeast Atlantic marine populations. Journal of Applied Ecology 42:883–891. doi: 10.1111/j.1365-2664.
Dulvy NK, Reynolds JD. 2002. Predicting extinction vulnerability in skates. Conservation Biology 16:440–450.
doi: 10.1046/j.1523-1739.2002.00416.x.
Dulvy NK, Sadovy Y, Reynolds JD. 2003. Extinction vulnerability in marine populations. Fish and Fisheries
4:25–64. doi: 10.1046/j.1467-2979.2003.00105.x.
FAO. 2010. The state of world fisheries and Aquaculture 2010. Food and Agriculture organization of the United
nations. Rome. p. 197.
FAO. 2011. FishSTAT capture production (1950-2009) database. Food and Agriculture organization of the United
nations. Rome.
Ferretti F, Myers RA, Serena F, Lotze HK. 2008. Loss of large predatory sharks from the Mediterranean sea.
Conservation Biology 22:952–964. doi: 10.1111/j.1523-1739.2008.00938.x.
Ferretti F, Worm B, Britten GL, Heithaus MR, Lotze HK. 2010. Patterns and ecosystem consequences of shark
declines in the ocean. Ecology Letters 13:1055–1071. doi: 10.1111/j.1461-0248.2010.01489.x.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 31 of 34
Research article
Fischer J, Erikstein K, D‘Offay B, Barone M, Guggisberg S. 2012. Review of the implementation of the international
plan of action for the conservation and management of sharks. Food and Agriculture organization of the United
nations. Rome, C1076. p. 125.
Fowler S, Séret B. 2010. Shark fins in Europe: Implications for reforming the EU finning ban. European
Elasmobranch Association and IUCN Shark Specialist Group. p. 27.
Fowler SL. 2012. Background paper on the conservation status of migratory sharks. Convention on migratory
species. Bonn, Germany. p. 22.
Fowler SL, Reed TM, Dipper FA. 2002. Elasmobranch Biodiversity, Conservation and Management. Gland,
Switzerland and Cambridge, UK: IUCN Species Survival Commission Shark Specialist Group.
Frisk MG, Miller TJ, Fogarty MJ. 2001. Estimation and analysis of biological parameters in elasmobranch fishes: a
comparative life history study. Canadian Journal of Fisheries and Aquatic Sciences 58:969–981. doi: 10.1139/f01-051.
García VB, Lucifora LO, Myers RA. 2008. The importance of habitat and life history to extinction risk in sharks,
skates, rays and chimaeras. Proceedings of the Royal Society B-Biological Sciences 275:83–89. doi: 10.1098/
Gärdenfors U, Hilton-Taylor C, Mace GM, Rodríguez JP. 2001. The application of IUCN Red List Criteria regional
levels. Conservation Biology 15:1206–1212. doi: 10.1046/j.1523-1739.2001.00112.x.
Gelman A, Hill J. 2006. Data analysis using regression and multilevel/hierarchial models. Cambridge: Cambridge
University Press.
Gibson C, Valenti SV, Fowler SL, Fordham SV. 2008. The conservation status of Northeast Atlantic chondrichthy-
ans. Report of the IUCN shark specialist group Northeast Atlantic red list workshop. Newbury, UK: IUCN
species survival Commission shark specialist group. p. 76.
Harnik PG, Lotze HK, Anderson SC, Finkel ZV, Finnegan S, Lindberg DR, Liow LH, Lockwood R, McClain CR,
McGuire JL, O’Dea A, Pandolfi JM, Simpson C, Tittensor DP. 2012a. Extinctions in ancient and modern seas.
Trends in Ecology & Evolution 27:608–617. doi: 10.1016/j.tree.2012.07.010.
Harnik PG, Simpson C, Payne JL. 2012b. Long-term differences in extinction risk among the seven forms of rarity.
Proceedings of the Royal Society B-Biological Sciences 279:4969–4976. doi: 10.1098/rspb.2012.1902.
Harrison LR, Dulvy NK. 2014. Sawfish: a global Strategy for conservation. Vancouver, British Columbia, Canada:
International Union for the Conservation of Nature Species Survival Commission’s Shark Specialist Group. ISBN:
978-0-9561063-3-9. p. 112.
Heithaus MR, Wirsing AJ, Dill LM. 2012. The ecological importance of intact top-predator populations: a
synthesis of 15 years of research in a seagrass ecosystem. Marine and Freshwater Research 63:1039–1050.
doi: 10.1071/MF12024.
Hoffmann M, Hilton-Taylor C, Angulo A, Bohm M, Brooks TM, Butchart SHM, Carpenter KE, Chanson J, Collen B,
Cox NA, Darwall WRT, Dulvy NK, Harrison LR, Katariya V, Pollock CM, Quader S, Richman NI, Rodrigues ASL,
Tognelli MF, Vie J-C, Aguiar JM, Allen DJ, Allen GR, Amori G, Ananjeva NB, Andreone F, Andrew P, Ortiz ALA,
Baillie JEM, Baldi R, Bell BD, Biju SD, Bird JP, Black-Decima P, Blanc JJ, Bolanos F, Bolivar-G W, Burfield IJ,
Burton JA, Capper DR, Castro F, Catullo G, Cavanagh RD, Channing A, Chao NL, Chenery AM, Chiozza F,
Clausnitzer V, Collar NJ, Collett LC, Collette BB, Fernandez CFC, Craig MT, Crosby MJ, Cumberlidge N,
Cuttelod A, Derocher AE, Diesmos AC, Donaldson JS, Duckworth JW, Dutson G, Dutta SK, Emslie RH, Farjon
A, Fowler S, Freyhof J, Garshelis DL, Gerlach J, Gower DJ, Grant TD, Hammerson GA, Harris RB, Heaney LR,
Hedges SB, Hero J-M, Hughes B, Hussain SA, Icochea MJ, Inger RF, Ishii N, Iskandar DT, Jenkins RKB, Kaneko Y,
Kottelat M, Kovacs KM, Kuzmin SL, La Marca E, Lamoreux JF, Lau MWN, Lavilla EO, Leus K, Lewison RL,
Lichtenstein G, Livingstone SR, Lukoschek V, Mallon DP, McGowan PJK, McIvor A, Moehlman PD, Molur S,
Muñoz Alonso A, Musick JA, Nowell K, Nussbaum RA, Olech W, Orlov NL, Papenfuss TJ, Parra-Olea G, Perrin
WF, Polidoro BA, Pourkazemi M, Racey PA, Ragle JS, Ram M, Rathbun G, Reynolds RP, Rhodin AG, Richards SJ,
Rodríguez LO, Ron SR, Rondinini C, Rylands AB, Sadovy de Mitcheson Y, Sanciangco JC, Sanders KL, Santos-
Barrera G, Schipper J, Self-Sullivan C, Shi Y, Shoemaker A, Short FT, Sillero-Zubiri C, Silvano DL, Smith KG,
Smith AT, Snoeks J, Stattersfield AJ, Symes AJ, Taber AB, Talukdar BK, Temple HJ, Timmins R, Tobias JA,
Tsytsulina K, Tweddle D, Ubeda C, Valenti SV, van Dijk PP, Veiga LM, Veloso A, Wege DC, Wilkinson M,
Williamson EA, Xie F, Young BE, Akçakaya HR, Bennun L, Blackburn TM, Boitani L, Dublin HT, da Fonseca GA,
Gascon C, Lacher TE Jnr, Mace GM, Mainka SA, McNeely JA, Mittermeier RA, Reid GM, Rodriguez JP,
Rosenberg AA, Samways MJ, Smart J, Stein BA, Stuart SN. 2010. The impact of conservation on the status of
the world’s vertebrates. Science 33:1503–1509. doi: 10.1126/science.1194442.
Hong Kong Special Administrative Region Government. 2011. Census and statistics Department. Hong Kong
special Administrative region government. Hong Kong.
Hutchings JA. 2000. Collapse and recovery of marine fishes. Nature 406:882–885. doi: 10.1038/35022565.
Hutchings JA, Myers RA, Garcia VB, Lucifora LO, Kuparinen A. 2012. Life-history correlates of extinction risk and
recovery potential. Ecological Applications 22:1061–1067. doi: 10.1890/11-1313.1.
IATTC. 2011. Resolution on the conservation of oceanic whitetip sharks caught in association with fisheries in the
Antigua convention area. Inter-American Tropical Tuna Commission (IATTC). La Jolla, USA, C-11-10. p. 2.
Iglésias SP, Toulhout L, Sellos DP. 2010. Taxonomic confusion and market mislabelling of threatened skates:
Important consequences for their conservation status. Aquatic Conservation - Marine and Freshwater
Ecosystems 20:319–333. doi: 10.1002/aqc.1083.
IOTC. 2011. Report of the Fourteenth session of the IOTC scientific Committee. Indian ocean tuna Commission.
Mahé, Seychelles. p. 33.
IUCN. 2001. IUCN red list categories and criteria: version 3.1. IUCN Species Survival Commission. Gland
Switzerland and Cambridge, UK. p. 38.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 32 of 34
Research article
IUCN. 2004. Guidelines for using the IUCN red list categories and criteria. IUCN Species Survival Commission.
Gland, Switzerland. p. 87.
Jackson JBC. 2010. The future of the oceans past. Philosophical Transactions of the Royal Society B: Biological
Sciences 365:3765–3778. doi: 10.1098/rstb.2010.0278.
Jennings S, Reynolds JD, Mills SC. 1998. Life history correlates of responses to fisheries exploitation. Proceedings
of the Royal Society B-Biological Sciences 265:333–339. doi: 10.1098/rspb.1998.0300.
Jones KE, Purvis A, Gittleman JL. 2003. Biological correlates of extinction risk in bats. American Naturalist
161:601–614. doi: 10.1086/368289.
Juan-Jordá MJ, Mosqueira I, Freire J, Dulvy NK. 2013. Life in 3-D: life history strategies of tunas, bonitos and
mackerels. Reviews in Fish Biology and Fisheries 23:135–155. doi: 10.1007/s11160-012-9284-4.
Kriwet J, Witzmann F, Klug S, Heidtke UHJ. 2008. First direct evidence of a vertebrate three-level trophic chain in the
fossil record. Proceedings of the Royal Society B-Biological Sciences 275:181–186. doi: 10.1098/rspb.2007.1170.
Kulka DW, Frank KT, Simon JE. 2002. Barndoor skate in the northwest Atlantic off Canada: distribution in relation
to temperature and depth based on commercial fisheries data. Department of Fisheries and Oceans, Canadian
Science Advisory Secretariat Research Document, 2002/073. p. 17.
Kyne PM, Carlson JK, Ebert DA, Fordham SV, Bizzarro JJ, Graham RT, Kulka DW, Tewes EE, Harrison LR, Dulvy
NK. 2012. The Conservation Status of North American, Central American, and Caribbean chondrichthyans.
IUCN Species Survival Commission Shark Specialist Group. Vancouver, Canada. p. 148.
Kyne PM, Simpfendorfer CA. 2007. A collation and summarization of available data on deepwater chondrichthyans:
biodiversity, life history and fisheries. IUCN Species Survival Commission Shark Specialist Group. Newbury,
England. p. 137.
Lack M, Sant G. 2009. Trends in global shark catch and recent developments in management. TRAFFIC
International. Cambridge. p. 33.
Lam VYY, Sadovy de Mitcheson Y. 2010. The sharks of South East Asia – unknown, unmonitored and unmanaged.
Fish and Fisheries 12:51–74. doi: 10.1111/j.1467-2979.2010.00383.x.
Lasram FBR, Guilhaumon FO, Albouy C, Somot S, Thuiller W, Mouillot D. 2010. The Mediterranean Sea as a
‘cul-de-sac’ for endemic fishes facing climate change. Global Change Biology 16:3233–3245. doi: 10.1111/j.1365-
Last PR. 2007. The state of chondrichthyan taxonomy and systematics. Marine and Freshwater Research 58:7–9.
doi: 10.1071/MF07003.
Last PR, Stevens JD. 1994. Sharks and rays of Australia, CSIRO, Division of Fisheries. Hobart, Australia.
Last PR, Stevens JD. 2009. Sharks and rays of Australia, CSIRO, Division of Fisheries. Hobart, Australia.
Last PR, White WT, Pogonoski J. 2008a. Descriptions of new Australian chondrichthyans. CSIRO Marine and
Atmospheric Research Paper. Hobart, Australia, 22. p. 368.
Last PR, White WT, Pogonoski J. 2008b. Descriptions of new dogfishes of the genus Squalus (Squaloidea:
Squalidae). CSIRO Marine and Atmospheric Research Paper. Hobart, Australia, 14. p. 136.
Last PR, White WT, Pogonoski J, Gledhill DC. 2008c. Descriptions of new Australian skates (Batoidea: Rajoidea).
CSIRO Marine and Atmospheric Research Paper. Hobart, Australia, 21. p. 187.
Lotze HK, Lenihan HS, Bourque BJ, Bradbury RH, Cooke RG, Kay MC, Kidwell SM, Kirby MX, Peterson CH,
Jackson JBC. 2006. Depletion, degradation, and recovery potential of estuaries and coastal seas. Science
312:1806–1809. doi: 10.1126/science.1128035.
Mace G, Masundire H, Baillie J, Ricketts T, Brooks T. 2005. Biodiversity. In: Hassan R, Scholes R, Ash N, editors.
Ecosystems and human well-being: current state and trends: findings of the condition and trends working group.
Washington DC: Island Press. p. 77–122.
Mace GM, Collar NJ, Gaston KJ, Hilton-Taylor C, Akcakaya HR, Leader-Williams N, Milner-Gulland EJ, Stuart SN.
2008. Quantification of extinction risk: IUCN’s system for classifying threatened species. Conservation Biology
22:1424–1442. doi: 10.1111/j.1523-1739.2008.01044.x.
Mace PM. 2004. In defence of fisheries scientists, single species models and other scapegoats: confronting the
real problems. Marine Ecology Progress Series 274:285–291.
Marris E. 2007. Conservation priorities: what to let go. Nature 450:152–155. doi: 10.1038/450152a.
McClenachan L, Cooper AB, Carpenter KE, Dulvy NK. 2012. Extinction risk and bottlenecks in the conservation
of charismatic marine species. Conservation Letters 5:73–80. doi: 10.1111/j.1755-263X.2011.00206.x.
Morato T, Watson R, Pitcher TJ, Pauly D. 2006. Fishing down the deep. Fish and Fisheries 7:24–34. doi: 10.1111/j.1467-
Mundy-Taylor V, Crook V. 2013. Into the Deep: Implementing CITES measures for commercially-valuable sharks
and manta rays. TRAFFIC. Cambridge. p. 106.
Musick JA. 1999a. Criteria to define extinction risk in marine fishes. Fisheries 24:6–14. doi: 10.1577/1548-
Musick JA. 1999b. Ecology and conservation of long-lived marine animals. In: Musick JA, editor. Life in the slow
lane: ecology and conservation of long-lived marine animals. Bethesda, Maryland: American Fisheries Society
Symposium. p. 1–10.
Musick JA, Harbin MM, Berkeley SA, Burgess GH, Eklund AM, Findley L, Gilmore RG, Golden JT, Ha DS,
Huntsman GR, McGovern JC, Parker SJ, Poss SG, Sala E, Schmidt TW, Sedberry GR, Weeks H, Wright SG.
2000. Marine, estuarine, and diadromous fish stocks at risk of extinction in North America (exclusive of Pacific
salmonids). Fisheries 25:6–30.
Musick JA, Musick S. 2011. Sharks (Special Topics C3), in review of the state of the world Marine fishery
resources. Food and Agriculture organization of the United nations, Rome, Italy, 569. p. 245–254.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 33 of 34
Research article
Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J. 2000. Biodiversity hotspots for conservation
priorities. Nature 403:853–858. doi: 10.1038/35002501.
NAFO. 2011. NAFO conservation and enforcement measures. North Atlantic fisheries Organisation. http://www.
Nakagawa S, Schielzeth H. 2012. A general and simple method for obtaining R2 from generalized linear
mixed-effects models. Methods in Ecology and Evolution 4:133–142. doi: 10.1111/j.2041-
Naylor GJP, Caira JN, Jensen K, Rosana KAM, White WT, Last PR. 2012. A DNA sequence-based approach to
the identification of shark and ray species and its implications for global elasmobranch diversity and parasitology.
Bulletin of the American Museum of Natural History 367:1–262. doi: 10.1206/754.1.
NEAFC. 2009. Fisheries (High seas fishing Notifications—North East Atlantic fisheries Commission) Notice 2009.
Neubauer P, Jensen OP, Hutchings JA, Baum JK. 2013. Resilience and recovery of overexploited marine
populations. Science 340:347–349. doi: 10.1126/science.1230441.
Newton K, Côté IM, Pilling GM, Jennings S, Dulvy NK. 2007. Current and future sustainability of island coral reef
fisheries. Current Biology 17:655–658. doi: 10.1016/j.cub.2007.02.054.
Polidoro BA, Brooks T, Carpenter KE, Edgar GJ, Henderson S, Sanciangco J, Robertson DR. 2012. Patterns of
extinction risk and threat for marine vertebrates and habitat-forming species in the Tropical Eastern Pacific.
Marine Ecology-Progress Series 448:93–104. doi: 10.3354/meps09545.
Polidoro BA, Livingstone SR, Carpenter KE, Hutchinson B, Mast RB, Pilcher NJ, Sadovy de Mitcheson Y, Valenti
SV. 2008. Status of the world’s marine species. In: Vié J-C, Hilton-Taylor C, Stuart SN, editors. Wildlife in a
changing world: an analysis of the 2008 IUCN Red List of threatened species. Gland, Switzerland: International
Union for Conservation of Nature. p. 55–65.
Porszt E, Peterman RM, Dulvy NK, Cooper AB, Irvine JR. 2012. Reliability of indicators of declines in abundance.
Conservation Biology 26:894–904. doi: 10.1111/j.1523-1739.2012.01882.x.
Reynolds JD, Dulvy NK, Goodwin NB, Hutchings JA. 2005. Biology of extinction risk in marine fishes.
Proceedings of the Royal Society B-Biological Sciences 272:2337–2344. doi: 10.1098/rspb.2005.3281.
Ricard D, Minto C, Jensen OP, Baum JK. 2012. Examining the knowledge base and status of commercially
exploited marine species with the RAM Legacy Stock Assessment Database. Fish and Fisheries 13:380–398.
doi: 10.1111/j.1467-2979.2011.00435.x.
Robillard M, Séret B. 2006. Cultural importance and decline of sawfish (Pristidae) populations in West Africa.
Cybium 30:23–30.
Sadovy Y. 2005. Trouble on the reef: the imperative for managing vulnerable and valuable fisheries. Fish and
Fisheries 6:167–185. doi: 10.1111/j.1467-2979.2005.00186.x.
Sahr K, White D, Kimerling AJ. 2003. Geodesic discrete global grid systems. Cartography and Geographic
Information Science 30:121–134. doi: 10.1559/152304003100011090.
Salafsky N, Salzer D, Stattersfield AJ, Hilton-Taylor C, Neugarten R, Butchart SHM, Collen B, Cox N, Master LL,
O’Connor S, Wilkie D. 2008. A standard lexicon for biodiversity conservation: unified classifications of threats
and actions. Conservation Biology 22:897–911. doi: 10.1111/j.1523-1739.2008.00937.x.
Schipper J, Chanson JS, Chiozza F, Cox NA, Hoffmann M, Katariya V, Lamoreux J, Rodrigues ASL, Stuart SN,
Temple HJ, Baillie J, Boitani L, Lacher TE Jnr, Mittermeier RA, Smith AT, Absolon D, Aguiar JM, Amori G,
Bakkour N, Baldi R, Berridge RJ, Bielby J, Black PA, Blanc JJ, Brooks TM, Burton JA, Butynski TM, Catullo G,
Chapman R, Cokeliss Z, Collen B, Conroy J, Cooke JG, da Fonseca GAB, Derocher AE, Dublin HT, Duckworth JW,
Emmons L, Emslie RH, Festa-Bianchet M, Foster M, Foster S, Garshelis DL, Gates C, Gimenez-Dixon M,
Gonzalez S, Gonzalez-Maya JF, Good TC, Hammerson G, Hammond PS, Happold D, Happold M, Hare J, Harris RB,
Hawkins CE, Haywood M, Heaney LR, Hedges S, Helgen KM, Hilton-Taylor C, Hussain SA, Ishii N, Jefferson TA,
Jenkins RKB, Johnston CH, Keith M, Kingdon J, Knox DH, Kovacs KM, Langhammer P, Leus K, Lewison R,
Lichtenstein G, Lowry LF, Macavoy Z, Mace GM, Mallon DP, Masi M, McKnight MW, Medellin RA, Medici P,
Mills G, Moehlman PD, Molur S, Mora A, Nowell K, Oates JF, Olech W, Oliver WRL, Oprea M, Patterson BD,
Perrin WF, Polidoro BA, Pollock C, Powel A, Protas Y, Racey P, Ragle J, Ramani P, Rathbun G, Reeves RR,
Reilly SB, Reynolds JE III, Rondinini C, Rosell-Ambal RG, Rulli M, Rylands AB, Savini S, Schank CJ, Sechrest W,
Self-Sullivan C, Shoemaker A, Sillero-Zubiri C, De Silva N, Smith DE, Srinivasulu C, Stephenson PJ, van Strien N,
Talukdar BK, Taylor BL, Timmins R, Tirira DG, Tognelli MF, Tsytsulina K, Veiga LM, Vié JC, Williamson EA, Wyatt SA,
Xie Y, Young BE. 2008. The status of the world’s land and marine mammals: diversity, threat, and knowledge.
Science 322:225–230. doi: 10.1126/science.1165115.
Simpfendorfer CA, Cortés E, Heupel MR, Brookes E, Babcock EA, Baum JK, McAuley R, Dudley SFJ, Stevens JD,
Fordham S, Soldo A. 2008. An integrated approach to determining the risk of over-exploitation for data-poor
pelagic Atlantic sharks. International Commission for the Conservation of Atlantic Tunas, Madrid, 2008/138/140.
p. 1–14.
Simpfendorfer CA, Hueter RE, Bergman U, Connett SMH. 2002. Results of a fishery-independent survey
for pelagic sharks in the western North Atlantic, 1977-1994. Fisheries Research 55:175–192. doi: 10.1016/
Simpfendorfer CA, Kyne PM. 2009. Limited potential to recover from overfishing raises concerns
for deep-sea sharks, rays and chimaeras. Environmental Conservation 36:97–103. doi: 10.1017/
Sing T, Sander O, Beerenwinkel N, Lengauer T. 2005. ROCR: visualizing classifier performance in R. Bioinformatics
21:3940–3941. doi: 10.1093/bioinformatics/bti623.
Dulvy et al. eLife 2014;3:e00590. DOI: 10.7554/eLife.00590 34 of 34
Research article
Smith SE, Au DW, Show C. 1998. Intrinsic rebound potentials of 26 species of Pacific sharks. Marine and
Freshwater Research 49:663–678. doi: 10.1071/MF97135.
Stevens JD, Bonfil R, Dulvy NK, Walker P. 2000. The effects of fishing on sharks, rays and chimaeras
(Chondrichthyans), and the implications for marine ecosystems. ICES Journal of Marine Science 57:476–494.
doi: 10.1006/jmsc.2000.0724.
Stevens JD, Walker TI, Cook SF, Fordham S. 2005. Threats faced by chondrichthyan fishes. In: Fowler SL,
Cavanagh R, Camhi M, Burgess GH, Caillet GM, Fordham S, Simpfendorfer CA, Musick JA, editors. Sharks, rays
and chimaeras: the status of the Chondrichthyan fishes. Gland, Switzerland and Cambridge, UK: IUCN Species
Survival Commission Shark Specialist Group. p. 48–57.
Stuart SN, Chanson JS, Cox NA, Young BE, Rodrigues ASL, Fischman DL, Waller RA. 2004. Status and
trends of amphibian declines and extinctions worldwide. Science 306:1783–1786. doi: 10.1126/
Swartz W, Sala E, Tracey S, Watson R, Pauly D. 2010. The spatial expansion and ecological footprint of fisheries
(1950 to Present). PLOS ONE 5:e15143. doi: 10.1371/journal.pone.0015143.
Techera EJ, Klein N. 2011. Fragmented governance: reconciling legal strategies for shark conservation and
management. Marine Policy 35:73–78. doi: 10.1016/j.marpol.2010.08.003.
Veitch L, Dulvy NK, Koldewey H, Lieberman S, Pauly D, Roberts CM, Rogers AD, Baillie JEM. 2012. Avoiding
empty ocean commitments at Rio +20. Science 336:1383–1385. doi: 10.1126/science.1223009.
Vincent ACJ, Sadovy de Mitcheson Y, Fowler SL, Lieberman S. 2014. The role of CITES in the conservation of
marine fishes subject to international trade. Fish and Fisheries (In Press). doi: 10.1111/faf.12035.
Wallace BP, DiMatteo AD, Hurley BJ, Finkbeiner EM, Bolten AB, Chaloupka MY, Hutchinson BJ, Abreu-Grobois FA,
Amorocho D, Bjorndal KA, Bourjea J, Bowen BW, Dueñas RB, Casale P, Choudhury BC, Costa A, Dutton PH,
Fallabrino A, Girard A, Girondot M, Godfrey MH, Hamann M, López-Mendilaharsu M, Marcovaldi MA, Mortimer JA,
Musick JA, Nel R, Pilcher NJ, Seminoff JA, Troëng S, Witherington B, Mast RB. 2010. Regional management
units for marine turtles: a novel framework for prioritizing conservation and research across multiple scales.
PLOS ONE 5:e15465.
Wallace S, Gisborne B. 2006. Basking sharks: the slaughter of BC’s gentle giants. Vancouver: New Star Books.
Walpole M, Almond REA, Besancon C, Butchart SHM, Campbell-Lendrum D, Carr GM, Collen B, Collette L,
Davidson NC, Dulloo E, Fazel AM, Galloway JN, Gill M, Goverse T, Hockings M, Leaman DJ, Morgan DHW,
Revenga C, Rickwood CJ, Schutyser F, Simons S, Stattersfield AJ, Tyrrell TD, Vie JC, Zimsky M. 2009. Tracking
progress toward the 2010 biodiversity target and beyond. Science 325:1503–1504. doi: 10.1126/
Ward RD, Holmes BH, White WT, Last PR. 2008. DNA barcoding Australasian chondrichthyans: results and
potential uses in conservation. Marine and Freshwater Research 59:57–71. doi: 10.1071/MF07148.
White WT, Last PR. 2012. A review of the taxonomy of chondrichthyan fishes: a modern perspective. Journal of
Fish Biology 80:901–917. doi: 10.1111/j.1095-8649.2011.03192.x.
White WT, Last PR, Stevens JD, Yearsley GK, Dharmadi F. 2006. Economically important sharks and rays of
Indonesia, Australian Centre for international Agricultural research. Canberra.
Worm B, Davis B, Kettemer L, Ward-Paige CA, Chapman D, Heithaus MR, Kessel ST, Gruber SH. 2013. Global
catches, exploitation rates, and rebuilding options for sharks. Marine Policy 40:194–204. doi: 10.1016/j.
Worm B, Hilborn R, Baum JK, Branch TA, Collie JS, Costello C, Fogarty MJ, Fulton EA, Hutchings JA, Jennings S,
Jensen OP, Lotze HK, Mace PM, McClanahan TR, Minto C, Palumbi SR, Parma AM, Ricard D, Rosenberg AA,
Watson R, Zeller D. 2009. Rebuilding global fisheries. Science 325:578–585. doi: 10.1126/science.1173146.
... Despite advances in this area, there is still a marked lack of quantitative information on bycatches and discard rates (Kelleher 2008). Even, the extent and degree of the global impact of fisheries on marine biodiversity remains poorly understood and highly contentious (Dulvy et al. 2014). Moreover, studies on bycatch provide an opportunity to characterize the fish composition of a region and they allowed determining possible associations or "species assemblages" defined as geographical areas that are characterized by a particular species composition relatively homogeneous and persistent. ...
... The proposed analyzes should be complemented with abundance data of the species by fleet since the bycatch rates are different in each fleet. The quantification of the bycatch is a valuable data to assess the real impact of the bycatch since among the species mentioned some of them have conservation issues, such as, the group of cartilaginous fishes (Dulvy et al. 2014) and the rocky reef fishes (Venerus et al. 2014), and others are rare species that could be affected by bycatches in this type of fisheries (Stobutski et al. 2001). ...
... Elasmobranchs are currently facing a multitude of threats, including overfishing, chemical pollution, habitat destruction, and climate change effects, resulting in global conservation concerns [21]. In this sense, the above-mentioned shifts in marine microbiota composition and diversity comprise a significant health effect factor that may negatively influence elasmobranch health and immune responses, potentially increasing their susceptibility to infections and diseases, increasing conservation concerns. ...
Full-text available
Yeast infections have gained significant attention in the field of marine biology in recent years. Among the broad diversity of marine organisms affected by these infections, elasmobranchs (sharks and rays) have emerged as highly susceptible, due to climate change effects, such as increasing water temperatures and pollution, which can alter the composition and abundance of fungal communities. Additionally, injuries, or compromised immune systems resulting from pollution or disease may increase the likelihood of fungal infections in elasmobranchs. Studies are, however, still lacking for this taxonomic group. In this context, this study aimed to screen yeast species in cell cultures obtained from the brain of artisanally captured Pseudobatos horkelii, a cartilaginous fish that, although endangered, is highly captured and consumed worldwide. Fungi were isolated during an attempt to establish primary cultures of elasmobranch neural cells. Culture flasks were swabbed and investigated using morphological, phenotypic, and molecular techniques. Two isolates of the emerging opportunistic pathogen Trichosporon japonicum were identified, with high scores (1.80 and 1.85, respectively) by the MALDI-ToF technique. This is the first report of the basidiomycetous yeast T. japonicum in Pseudobatos horkelii in Brazil. This finding highlights the need for further research to determine the potential impact on elasmobranch health, ecology, as well as on commercial fisheries.
... The significant decline in global biodiversity in the past decades can be considered the sixth mass extinction event on Earth, with land vertebrates considered the most threatened group (Cowie, Bouchet & Fontaine, 2022;del Monte-Luna et al., 2023). Despite that, some marine groups, such as elasmobranchs, face comparable threat levels (Dulvy et al., 2014). Within elasmobranchs, Batoidea (skates and rays) comprise the most threatened group, with 36% of species assigned to one of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species threat categories (Dulvy et al., 2021). ...
Molecular analysis is a powerful tool for assessing and developing conservation strategies for endangered species. Elasmobranchs comprise one of the most threatened groups of vertebrates, with about one‐third of the species subject to some degree of threat. This is the case for Pseudobatos horkelii , the Brazilian guitarfish, which has suffered severe population reductions (>80%) in recent decades, mainly through coastal overfishing. Understanding the genetic diversity of this species is paramount to applying adequate management and conservation strategies. In this context, the present study evaluated the genetic diversity of P. horkelii , employing single‐nucleotide polymorphism (SNP) nuclear markers obtained by double‐digest restriction site‐associated DNA sequencing (ddRADseq). Samples collected in three areas along the Brazilian Coast (Rio de Janeiro, São Paulo, and Rio Grande do Sul) provided an average of 1,565,339 reads and 2,846 SNPs. The results indicate the presence of at least two genetically distinct populations along the Brazilian Coast, with molecular diversity differences noted among clusters. The heterozygosity excess observed in all populations is likely the result of a bottleneck, probably resulting from overfishing and habitat fragmentation. Moreover, the upwelling phenomenon in Cabo Frio, in the state of Rio de Janeiro, may have a significant influence over the observed genetic structure. The gene flow between the clusters was estimated and was noted as asymmetric between the populations studied. The observed patterns may be the result of the combination of biological characteristics and overfishing pressure in the past decades. The evidence of structured populations presenting genetic diversity differences provides insightful information for the development of stock management and conservation strategies for the Brazilian guitarfish.
... The main cause of the shark's decline is the exploitation of excess both by-catch and as the main target (Worm et al., 2013). Other causes of the decline of sharks such as climate change and habitat destruction (Dulvy et al., 2014). Indonesia is included as one of the countries that utilize the largest shark resources in the world. ...
Full-text available
Research on the types of sharks traded at the Southwest Aceh fish landing site was conducted in September 2022. The purpose of this study is to analyze the morphology and genetic analysis of sharks. Sampling uses purposive sampling techniques, for morphological analysis refers to shark identification books, while genetic analysis uses the Sanger method used at the sequencing stage. Morphological data analysis using Image-j software, for genetic analysis, using Mega 6 (Molecular Evolutionary Genetic Analysis). Morphological analysis was carried out at the Laboratory of Biosystematics and Marine Genetics, Faculty of Fisheries and Marine Sciences, Teuku Umar University. Genetic analysis was carried out at the Denpasar Biodiversity Laboratory, Bali. The results of this study found two species of sharks with a total of 8 individuals from the genus Carcharinus
... Shark-like batoids are highly vulnerable elasmobranchs (Dulvy et al., 2014;Moore, 2017;Jabado, 2018;Purushottama et al., 2018). Regional elasmobranch fisheries are highly dynamic and always change pattern according to consumer demand, export value, abundance of species, availability and price (Akhilesh et al., 2011;Nair et al., 2013).Therefore, studying the types of species of shark-like batoids that are landed and their biological traits are necessary prerequisite for formulating conservation measures for these species in India. ...
Scarce information exists on the life history of the bowmouth guitarfish Rhina ancylostomus (=R. ancylostoma) landed by trawlers and gillnetters that operate in the eastern Arabian Sea off Karnataka, on the south-west coast of India. This study was carried out to update information on this species by analysing the size distribution, sex ratio, length-at-maturity (Lm50%), length–weight relationship and diet using data collected during 2016-2019. Three hundred and sixty-nine individuals were collected with a total length (TL) range of 44.0 to 295 cm and total weight (TW) range of 0.2 to 127 kg. The length-weight relationship (LWR) of females and males did not differ significantly and therefore, a common equation was derived as TW = 0.006604TL 3.027504(r2=0.979). The length-at-maturity (Lm50%) for females and males were estimated to be 183.0 and 164.0 cm TL, respectively. R. ancylostoma has two functional ovaries and the ovarian cycle and gestation run concurrently. The number of embryos ranged from 2 to 8 and size at-birth was estimated to range between 44.0 and 50.0 cm TL. Overall sex ratio indicated dominance of females. Dietary analysis of stomach contents (%IRI) revealed that R. ancylostomus fed primarily on teleosts (73.3%), crustaceans (20.5%) and molluscs (6.2%). Gravid females enter coastal waters possibly for parturition and feeding in some seasons, where they become vulnerable to trawl and gillnets used along Karnataka coast. The species is categorised in IUCN Red List as “Critically Endangered” and the present study revealed the urgent need to construct an effective management plan to conserve this species in the region.Keywords: Bycatch, Elasmobranchs, Life history, Shark ray
... By-catch from commercial fisheries (i.e., where catch is sold) has been a major driver of this decline in shark populations, whereby pelagic longlines and seine nets incidentally catch non-target shark species [20,41]. Direct targeting of sharks for the fin trade and recreational sports fisheries has contributed to further declines in shark stocks [17,24]. Low intrinsic population growth rates and long generation times make sharks inherently susceptible to over-exploitation [30,46]. ...