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The process of understanding the rapid global decline of sawfishes (Pristidae) has revealed great concern for their relatives, the wedgefishes (Rhinidae) and giant guitarfishes (Glaucostegidae), not least because all three families are targeted for their high-value and internationally-traded ‘white’ fins.The objective of this study was to assess the extinction risk of all 10 wedgefishes and 6 giant guitarfishes by applying the International Union for Conservation of Nature (IUCN) Red List Categories and Criteria, and to summarise their biogeography and habitat, life history, exploitation, use and trade, and population status.Wedgefishes and giant guitarfishes have overtaken sawfishes as the most imperilled marine fish families globally, with all but one of the 16 species facing an extremely high risk of extinction due to a combination of traits – limited biological productivity, presence in shallow waters overlapping with some of the most intense and increasing coastal fisheries in the world, and over-exploitation in target and bycatch fisheries driven by the need for animal protein and food security in coastal communities and trade in meat and high-value fins.Two species with very restricted ranges, the Clown Wedgefish (Rhynchobatus cooki) of the Indo-Malay Archipelago and the False Shark Ray (Rhynchorhina mauritaniensis) of Mauritania may be very close to extinction.Only the Eyebrow Wedgefish (Rhynchobatus palpebratus) is not assessed as Critically Endangered, due to it occurring primarily in Australia where fishing pressure is low, and some management measures are in place. Australia represents a ‘lifeboat’ for the three wedgefish and one giant guitarfish species occurring there.To conserve populations and permit recovery, a suite of measures will be required which will need to include species protection, spatial management, bycatch mitigation, and harvest and international trade management, all of which will be dependent on effective enforcement.

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

SummarySharks and rays are possibly the most threatened Class of marine fishes and their declines can be halted if protected areas are optimised to benefit these species. We identify spatial priorities for all 63 endemic sharks and rays in the marine biodiversity hotspot, the Western Indian Ocean (WIO). Collectively, while the WIO nations currently surpass the 10% Aichi ocean protection target, this amounts to a dismal protection of only 1.57% of each species’ distribution range. We show that the entire ranges of all endemics can be achieved by protecting 11% of EEZs of WIO nations, well within reach of the new 30% of oceans by 2030 target. Regional management bodies exist, which if taken advantage of to implement shark and ray management, provide opportunities to implement more efficient management across the region. We recommend key management actions to implement and explicit incentivisation of international cooperation in the post-2020 biodiversity framework.Science for SocietyThe past decade has seen massive growth in the establishment of marine protected areas (MPAs), driven by the Aichi biodiversity target of protecting 10% of all ocean areas. This expansion of MPAs, however, has largely occurred in areas residual to extractive uses, often coinciding with less threatened areas of lower conservation value. This coming decade will see a further push to ensure 30% of the oceans are protected by 2030. It is important to understand how existing and future MPAs should be placed to benefit threatened biodiversity. Currently this is unclear for sharks and rays, comprising a species group that is the most evolutionarily distinct vertebrate radiation in the world and also one of the most threatened. We identify both regional and national conservation priorities for expanding marine protected areas to benefit all 63 endemic sharks and rays occurring in the Western Indian Ocean region. We find that the region has already exceeded the 10% ocean protection target, but this amounts to an average of only 1.57% protection of the distribution ranges of these species. We show that protecting the top 10% priority sites will conserve almost half of the geographic range of each species yet require only 1.16% of the total EEZ – a tiny fraction of the 30% by 2030 target. We also show that regional collaboration among all nations can result in more spatially efficient conservation priorities. We recommend that the post-2020 biodiversity framework needs to explicitly incentivise regional cooperation between nations to efficiently achieve urgent targets and maximise benefits to biodiversity.

Many important areas identified for conservation priorities focus on areas of high species richness, however, it is unclear whether these areas change depending on what aspect of richness is considered (e.g. evolutionary distinctiveness, endemicity, or threatened species). Furthermore, little is known of the extent of spatial congruency between biodiversity measures in the marine realm. Here, we used the distribution maps of all known marine sharks, rays, and chimaeras (class Chondrichthyes) to examine the extent of spatial congruency across the hotspots of three measures of species richness: total number of species, evolutionarily distinct species, and endemic species. We assessed the spatial congruency between hotspots considering all species, as well as on the subset of the threatened species only. We consider three definitions of hotspot (2.5%, 5%, and 10% of cells with the highest numbers of species) and three levels of spatial resolution (1°, 4°, and 8° grid cells). Overall, we found low congruency among all three measures of species richness, with the threatened species comprising a smaller subset of the overall species patterns irrespective of hotspot definition. Areas of congruency at 1° and 5% richest cells contain over half (64%) of all sharks and rays and occurred off the coasts of: (1) Northern Mexico Gulf of California, (2) USA Gulf of Mexico, (3) Ecuador, (4) Uruguay and southern Brazil, (5) South Africa, southern Mozambique, and southern Namibia, (6) Japan, Taiwan, and parts of southern China, and (7) eastern and western Australia. Coarsening resolution increases congruency two-fold for all species but remains relatively low for threatened measures, and geographic locations of congruent areas also change. Finally, for pairwise comparisons of biodiversity measures, evolutionarily distinct species richness had the highest overlap with total species richness regardless of resolution or definition of hotspot. We suggest that focusing conservation attention solely on areas of high total species richness will not necessarily contribute efforts towards species that are most at risk, nor will it protect other important dimensions of species richness.

Spatial data characteristics have the potential to influence various aspects of prioritising bio-diversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors-planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs-on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs.