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.