Effective ocean management and conservation of highly migratory species depends onresolving overlap between animal movements and distributions, and fishing effort.However, this information is lacking at a global scale. Here we show, using a big-data approach that combines satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space-use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively), and were also associated with significant increases in fishing effort.We conclude that pelagic sharks have limited spatial refuge from current levels of fishing effort in marine areas beyond national jurisdictions (the high seas). Our results demonstrate an urgent need for conservation and management measures at high-seas hotspots of shark space use, and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real-time, dynamic management.Industrialised fishing is a major source of mortality for large marine animals (marine megafauna) 1-6 . Humans have hunted megafauna in the open ocean for at least 42,000 years 7 , but international fishing fleets targeting large, epipelagic fishes did not spread into the high seas (areas beyond national jurisdiction) until the 1950s 8 . Prior to this, the high seas constituted a spatial refuge largely free from exploitation as fishing pressure was concentrated on continental shelves 3,8 . Pelagic sharks are among the widest ranging vertebrates, with some species exhibiting annual ocean-basin-scale migrations 9 , long term trans-ocean movements 10 , and/or fine-scale site fidelity to preferred shelf and open ocean areas 5,9,11 . These behaviours could cause extensive spatial overlap with different fisheries from coastal areas to the deep ocean. On average, large pelagic sharks account for 52% of all identified shark catch worldwide in target fisheries or as bycatch 12 . Regional declines in abundance of pelagic sharks have been reported 13,14 , but it is unclear whether exposure to high fishing effort extends across ocean-wide population ranges and overlaps areas in the high seas where sharks are most abundant 5,13 .Conservation of pelagic sharkswhich currently have limited high seas management 12,15,16would benefit greatly from a clearer understanding of the spatial relationships between sharks' habitats and active fishing zones. However, obtaining unbiased estimates of shark and fisher distributions is complicated by the fact that most data on pelagic sharks come from catch records and other fishery-dependent sources 4,15,16 .Here, we provide the first global estimate of the extent of space use overlap of sharks with industrial fisheries. This is based on the analysis of the movements of pelagic sharks tagged with satellite transmitters in the Atlantic, Indian and Pacific oceans, together with fishing vessel movements m...

Summary Fine‐scale predator movements may be driven by many factors including sex, habitat and distribution of resources. There may also be individual preferences for certain movement strategies within a population which can be hard to quantify. Within top predators, movements are also going to be directly related to the mode of hunting, for example sit‐and‐wait or actively searching for prey. Although there is mounting evidence that different hunting modes can cause opposing trophic cascades, there has been little focus on the modes used by top predators, especially those in the marine environment. Adult white sharks (Carcharhodon carcharias) are well known to forage on marine mammal prey, particularly pinnipeds. Sharks primarily ambush pinnipeds on the surface, but there has been less focus on the strategies they use to encounter prey. We applied mixed hidden Markov models to acoustic tracking data of white sharks in a coastal aggregation area in order to quantify changing movement states (area‐restricted searching (ARS) vs. patrolling) and the factors that influenced them. Individuals were re‐tracked over multiple days throughout a month to see whether state‐switching dynamics varied or if individuals preferred certain movement strategies. Sharks were more likely to use ARS movements in the morning and during periods of chumming by ecotourism operators. Furthermore, the proportion of time individuals spent in the two different states and the state‐switching frequency, differed between the sexes and between individuals. Predation attempts/success on pinnipeds were observed for sharks in both ARS and patrolling movement states and within all random effects groupings. Therefore, white sharks can use both a ‘sit‐and‐wait’ (ARS) and ‘active searching’ (patrolling) movements to ambush pinniped prey on the surface. White sharks demonstrate individual preferences for fine‐scale movement patterns, which may be related to their use of different hunting modes. Marine top predators are generally assumed to use only one type of hunting mode, but we show that there may be a mix within populations. As such, individual variability should be considered when modelling behavioural effects of predators on prey species.

White sharks, Carcharodon carcharias, are often described as elusive, with little information available due to the logistical difficulties of studying large marine predators that make long-distance migrations across ocean basins. Increased understanding of aggregation patterns, combined with recent advances in technology have, however,

South Africa is reputed to host the world’s largest remaining population of white sharks, yet no studies have accurately determined a population estimate based on mark-recapture of live individuals. We used dorsal fin photographs (fin IDs) to identify white sharks in Gansbaai, South Africa, from January 2007 – December 2011. We used the computer programme DARWIN to catalogue and match fin IDs of individuals; this is the first study to successfully use the software for white shark identification. The programme performed well despite a number of individual fins showing drastic changes in dorsal fin shape over time. Of 1682 fin IDs used, 532 unique individuals were identified. We estimated population size using the open-population POPAN parameterisation in Program MARK, which estimated the superpopulation size at 908 (95% confidence interval 808–1008). This estimated population size is considerably larger than those described at other aggregation areas of the species and is comparable to a previous South African population estimate conducted 16 years prior. Our assessment suggests the species has not made a marked recovery since being nationally protected in 1991. As such, additional international protection may prove vital for the long-term conservation of this threatened species.

Background: Many marine species are difficult to study because components of their lifecycles occur solely or partially outside of the observable realm of researchers. Advances in biologging tags have begun to give us glimpses into these unobservable states. However, many of these tags require rigid attachment to animals, which normally requires catching and restraining the animals. These methods become prohibitive with large, dangerous, or rare species, such as large predatory sharks, and can have significant consequences for individual survival and behavior. Therefore, there is a need for methods and hardware to non-invasively and rigidly attach biologging tags to large predatory sharks that presents limited effects on the animals and researchers. Here we test a clamp tag and methods to non-invasively and rigidly attach biologging tags to white sharks (Carcharodon carcharias) in Gansbaai, South Africa.

We present 15 individual cases of sub-adult white sharks that were SPOT tagged in South Africa from 2003–2004 and have been re-sighted as recently as 2011. Our observations suggest SPOT tags can cause permanent cosmetic and structural damage to white shark dorsal fins depending on the duration of tag attachment. SPOT tags that detached within 12–24 months did not cause long term damage to the dorsal fin other than pigmentation scarring. Within 12 months of deployment, tag fouling can occur. After 24 months of deployment permanent damage to the dorsal fin occurred. A shark survived this prolonged attachment and there seems little compromise on the animal's long term survival and resultant body growth. This is the first investigation detailing the long term effects of SPOT deployment on the dorsal fin of white sharks.

Manual acoustic telemetry was used to describe core habitat use of white sharks in the complex marine landscape of the Dyer Island and Geyser Rock system near Gansbaai, South Africa. We compared home range estimates and swimming pattern analyses to those established at Mossel Bay, another white shark aggregation area roughly 300 km to the east. Traditional home range estimates used in Mossel Bay did not account for movement or barriers, and were thus biased towards areas with very little shark movement (i.e. potential resting areas). We found that adapting a Movement-based Kernel Density Estimate (MKDE) could account for movement and barriers, resolving these issues. At Dyer Island and Geyser Rock, daytime shark habitat use was adjacent to the seal colony, with low rates of movement, non-linear swimming patterns and small activity areas. At night, rates of movement and linearity increased as sharks travelled further from the islands into deeper waters. MKDEs revealed 4 focal areas of habitat use: a channel between the 2 islands, an area to the south of the seal colony, another area near a kelp feature to the southwest of the seal colony and a reef system to the northwest. These results differed significantly from the habitat use at Mossel Bay, where focal areas occurred adjacent to the seal colony during the hours of dawn and dusk. We discuss possible explanations for these differences. This study is the first to make use of MKDEs in a complex marine landscape and highlights important differences in habitat use of a threatened species between 2 separate aggregation areas.

The seasonal occurrence of white sharks visiting Gansbaai, South Africa was investigated from 2007 to 2011 using sightings from white shark cage diving boats. Generalized linear models were used to investigate the number of great white sharks sighted per trip in relation to sex, month, sea surface temperature and Multivariate El Niño/Southern Oscillation (ENSO) Indices (MEI). Water conditions are more variable in summer than winter due to wind-driven cold water upwelling and thermocline displacement, culminating in colder water temperatures, and shark sightings of both sexes were higher during the autumn and winter months (March–August). MEI, an index to quantify the strength of Southern Oscillation, differed in its effect on the recorded numbers of male and female white sharks, with highly significant interannual trends. This data suggests that water temperature and climatic phenomena influence the abundance of white sharks at this coastal site. In this study, more females were seen in Gansbaai overall in warmer water/positive MEI years. Conversely, the opposite trend was observed for males. In cool water years (2010 to 2011) sightings of male sharks were significantly higher than in previous years. The influence of environmental factors on the physiology of sharks in terms of their size and sex is discussed. The findings of this study could contribute to bather safety programmes because the incorporation of environmental parameters into predictive models may help identify times and localities of higher risk to bathers and help mitigate human-white shark interactions.