Shark interactions with water users can, on rare occasions, lead to shark bites. The sporadic nature of these events and their rarity has complicated efforts to understand the underlying causes, with many contributing factors implicated. Understanding shark presence and movement patterns near beaches is critical to developing a better appraisal of risk for shark bites. Recent advancements in Unmanned Aerial Vehicle (UAV, or drones) technology has provided new opportunities to observe and monitor sharks in coastal areas, offering real-time safety benefits and research insights. This research uses four years of data from the Queensland SharkSmart drone trial to investigate shark presence and movement behaviour at three beaches in Southeast Queensland. The research aimed to evaluate high-resolution shark tracks to analyse key metrics including proximity to shore and water users, time spent in the area and signs of active foraging. By bringing these and other data together, the study sought to develop a risk assessment matrix to inform risk to water users at these beaches and provide criteria to assist drone pilots decide when to evacuate beaches when risk is higher. Results showed that shark species, total length, proximity to water users and prey presence were key aspects determining the risk to water users associated with shark sighting events. Areas with abundant prey or near river mouths were more likely to attract potentially dangerous sharks. Understanding shark patterns at these beaches will facilitate predictions of higher-risk shark occurrences, thereby contributing to risk management and improvement of SharkSmart education for water users.

Context Coastal beach environments provide habitats for marine megafauna, including turtles, rays, marine mammals and sharks. However, accessing these variable energy zones has been difficult for researchers by using traditional methods. Aims This study used drone-based aerial surveys to assess spatio-temporal variation of marine megafauna across south-eastern Queensland, Australia. Methods Drones were operated at five south-eastern Queensland beaches. Megafauna sightings and key variables including location, month and turbidity were analysed to assess variation across locations. Key results Overall, 3815 individual megafauna were detected from 3273 flights. There were significant differences in the composition of megafauna assemblages throughout the year and among beaches, with megafaunal sightings in >80% of flights conducted off North Stradbroke Island. Conclusions Strong temporal presence was found that is congruent with other studies examining seasonality. This supports the use of drones to provide ecological data for many hard-to-study megafauna species and help inform long-term sustainable management of coastal ecosystems. Implications Results indicated that environmental conditions can influence the probability of sighting marine megafauna during aerial surveys.

Tag-recapture programs to monitor the movements of fish populations are among some of the longest-running citizen-science datasets to date. Here, using half a century of yellowtail kingfish (Seriola lalandi, Carangidae) tag-recapture data collected through citizen-science projects, we report novel insights into population connectivity in Australia and New Zealand (NZ). Despite the importance of kingfish in commercial and recreational fisheries, substantial knowledge gaps about their stock structure and connectivity between jurisdictions hinder current management efforts. Between 1974 and 2022, 63,432 releases and 4636 recaptures (7.3%) of tagged kingfish were collected in Australia and NZ. Most tagged individuals (51.4%) were recaptured within 10 km of their original release location up to 14 years post-release (mean: 225 days), indicating some degree of site fidelity. However, 656 (14.2%) kingfish were recaptured over 100 km from their release location, with one fish travelling at least 2834 km in 702 days. Seasonal variability was evident for releases and recaptures, with more releases occurring in summer and autumn in most jurisdictions. Network analysis of recaptures revealed no connectivity between tagged kingfish from western and eastern Australia, supporting genetic delineation. By contrast, extensive connectivity exists across eastern Australia and NZ, with 87 kingfish moving between five Australian state jurisdictions, 316 individuals travelling across 15 bioregions and six kingfish moving between Australia and NZ. Our findings provide important new insights into the structure and connectivity of the eastern Australia kingfish stock and suggest increased collaboration between state and international fisheries jurisdictions may support improved stock assessment and management.

Background Acoustic telemetry has become a fundamental tool to monitor the movement of aquatic species. Advances in technology, in particular the development of batteries with lives of > 10 years, have increased our ability to track the long-term movement patterns of many species. However, logistics and financial constraints often dictate the locations and deployment duration of acoustic receivers. Consequently, there is often a compromise between optimal array design and affordability. Such constraints can hinder the ability to track marine animals over large spatial and temporal scales. Continental-scale receiver networks have increased the ability to study large-scale movements, but significant gaps in coverage often remain. Methods Since 2007, the Integrated Marine Observing System's Animal Tracking Facility (IMOS ATF) has maintained permanent receiver installations on the eastern Australian seaboard. In this study, we present the recent enhancement of the IMOS ATF acoustic tracking infrastructure in Queensland to collect data on large-scale movements of marine species in the northeast extent of the national array. Securing a relatively small initial investment for expanding receiver deployment and tagging activities in Queensland served as a catalyst, bringing together a diverse group of stakeholders (research institutes, universities, government departments, port corporations, industries, Indigenous ranger groups and tourism operators) to create an extensive collaborative network that could sustain the extended receiver coverage into the future. To fill gaps between existing installations and maximise the monitoring footprint, the new initiative has an atypical design, deploying many single receivers spread across 2,100 km of Queensland waters. Results The approach revealed previously unknown broad-scale movements for some species and highlights that clusters of receivers are not always required to enhance data collection. However, array designs using predominantly single receiver deployments are more vulnerable to data gaps when receivers are lost or fail, and therefore "redundancy" is a critical consideration when designing this type of array. Conclusion Initial results suggest that our array enhancement, if sustained over many years, will uncover a range of previously unknown movements that will assist in addressing ecological, fisheries, and conservation questions for multiple species.

Fisher-shark conflict is occurring at Lord Howe Island, Australia due to high levels of Galapagos shark (Carcharhinus galapagensis) depredation (where sharks consume hooked fish) and bycatch. Depredation causes costly loss of target catch and fishing gear and increased mortality of target species, and sharks can be injured or killed when bycaught. This study applied acoustic telemetry and vessel tracking from 2018 to 2021 to identify; (1) how the movements of 30 tagged sharks and activity of six fishing vessels overlapped, and (2) where key ‘hotspots’ of overlap occurred. Fisher surveys were also conducted to collect information about mitigating shark interactions. Residency index analysis indicated that three sharks tagged at a fish waste dumping site had markedly higher residency. Core home ranges of sharks overlapped with higher fishing activity at four ‘hotspots’. Statistical modelling indicated positive linear effects of fishing activity and bathymetric complexity on shark detections and tagged sharks were present for 13

The black jewfish (Protonibea diacanthus) occurs in tropical coastal waters throughout the central Indo‐Pacific. It has long been valued as an important recreational and artisanal fishery species but has become increasingly targeted by commercial fisheries due to demand for its large swim bladder. To better understand how changes in fishing pressure may impact the sustainable exploitation of P. diacanthus populations throughout Eastern Australia, we evaluated the reproductive biology of the species across two management regions in Central Queensland. Reproductive characteristics studied included the size at maturity, fecundity, spawning mode, and season. Spawning periodicity was evaluated throughout the two major management regions and revealed an increase in the gonadosomatic index during the early austral spring, followed by evidence of spawning occurring from September through March with a peak from September to November. Females were found to produce ∼4.5 million ± 1.4 million oocytes (mean ± SE) per batch. Spawning periodicity did not vary latitudinally but was found to differ from other regions in northern Australia. The present study provides reliable maturity and fecundity information to improve future assessment and sustainable management of P. diacanthus.

Shark depredation is a complex social-ecological issue that affects a range of fisheries worldwide. Increasing concern about the impacts of shark depredation, and how it intersects with the broader context of fisheries management, has driven recent research in this area, especially in Australia and the United States. This review synthesises these recent advances and provides strategic guidance for researchers aiming to characterise the occurrence of depredation, identify the shark species responsible, and test deterrent and management approaches to reduce its impacts. Specifically, the review covers the application of social science approaches, as well as advances in video camera and genetic methods for identifying depredating species. The practicalities and considerations for testing magnetic, electrical, and acoustic deterrent devices are discussed in light of recent research. Key concepts for the management of shark depredation are reviewed, with recommendations made to guide future research and policy development. Specific management responses to address shark depredation are lacking, and this review emphasizes that a “silver bullet” approach for mitigating depredation does not yet exist. Rather, future efforts to manage shark depredation must rely on a diverse range of integrated approaches involving those in the fishery (fishers, scientists and fishery managers), social scientists, educators, and other stakeholders.

Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been tested at Queensland beaches. To determine effectiveness, it is necessary to understand how environmental and operational factors affect the ability of drones to detect sharks. To assess this, we utilised data from the Queensland SharkSmart drone trial, which operated at five southeast Queensland beaches for 12 months in 2020–2021. The trial conducted 3369 flights, covering 1348 km and sighting 174 sharks (48 of which were >2 m in length). Of these, eight bull sharks and one white shark were detected, leading to four beach evacuations. The shark sighting rate was 3% when averaged across all beaches, with North Stradbroke Island (NSI) having the highest sighting rate (17.9%) and Coolum North the lowest (0%). Drone pilots were able to differentiate between key shark species, including white, bull and whaler sharks, and estimate total length of the sharks. Statistical analysis indicated that location, the sighting of other fauna, season and flight number (proxy for time of day) influenced the probability of sighting sharks.

We developed and applied a method to quantify spearfisher effort and catch, shark interactions and shark depredation in a boat-based recreational spearfishing competition in the Great Barrier Reef Marine Park in Queensland. Survey questions were designed to collect targeted quantitative data whilst minimising the survey burden of spearfishers. We provide the first known scientific study of shark depredation during a recreational spearfishing competition and the first scientific study of shark depredation in the Great Barrier Reef region. During the two-day spearfishing competition, nine vessels with a total of 33 spearfishers reported a catch of 144 fish for 115 h of effort (1.25 fish per hour). A subset of the catch comprised nine eligible species under competition rules, of which 47 pelagic fish were weighed. The largest fish captured was a 34.4 kg Sailfish (Istiophorus platypterus). The most common species captured and weighed was Spanish Mackerel (Scomberomorus commerson). The total weight of eligible fish was 332 kg and the average weight of each fish was 7.1 kg. During the two-day event, spearfishers functioned as citizen scientists and counted 358 sharks (115 h effort), averaging 3.11 sharks per hour. Grey Reef Sharks (Carcharhinus amblyrhynchos) comprised 64% of sightings. Nine speared fish were fully depredated by sharks as spearfishers attempted to retrieve their catch, which equates to a depredation rate of 5.9%. The depredated fish included four pelagic fish and five reef fish. The shark species responsible were Grey Reef Shark (C. amblyrhynchos) (66%), Bull Shark (Carcharhinus leucas) (11%), Whitetip Reef Shark (Triaenodon obesus) (11%) and Great Hammerhead (Sphyrna mokarran) (11%). There were spatial differences in fish catch, shark sightings and rates of depredation. We developed a report card that compared average catch of fish, sightings of sharks per hour and depredation rate by survey area, which assists recreational fishers and marine park managers to assess spatio-temporal changes. The participating spearfishers can be regarded as experienced (average 18 days a year for average 13.4 years). Sixty percent of interviewees perceived that shark numbers have increased in the past 10 years, 33% indicated no change and 7% indicated shark numbers had decreased. Total fuel use of all vessels was 2819 L and was equivalent to 6.48 tons of greenhouse gas emissions for the competition.

Shark depredation, whereby hooked fish are partially or completely consumed before they can be retrieved, occurs globally in commercial and recreational fisheries. Depredation can damage fishing gear, injure sharks, cause additional mortality to targeted fish species and result in economic losses to fishers. Knowledge of the mechanisms behind depredation is limited. We used a 13 yr dataset of fishery-dependent commercial daily logbook data for the Mackerel Managed Fishery in Western Australia, which covers 15° of latitude and 10000 km of coastline, to quantify how fishing effort and environmental variables influence depredation. We found that shark depredation rates were relatively low in comparison with previous studies and varied across the 3 management zones of the fishery, with 1.7% of hooked fish being depredated in the northern Zone 1, 2.5% in the central Zone 2 and 5.7% in the southern Zone 3. Generalized additive mixed models found that measures of commercial fishing activity and a proxy for recreational fishing effort (distance from town centre) were positively correlated with shark depredation across Zones 1 and 2. Depredation rates increased during the 13 yr period in Zones 2 and 3, and were higher at dawn and dusk, suggesting crepuscular feeding in Zone 1. This study provides one of the first quantitative assessments of shark depredation in a commercial fishery in Western Australia, and for a trolling fishery globally. The results demonstrate a correlation between fishing effort and depredation, suggesting greater fishing effort in a concentrated area may change shark behaviour, leading to high rates of depredation.

A Combat Management System (CMS) is the computers and software of a naval platform which integrates the sensors, weapons, displays, data and other equipment, enabling the naval platform to operate efficiently and effectively to achieve mission success.In a hostile environment where threats may be fast moving, hard to detect, large in number, or all of the above, a crewed naval surface vessel requires a CMS that not only acts at the behest of the crew, but can also act autonomously when required.The capacity of the CMS to utilise data, respond autonomously, provide information to the crew and respond to crew commands significantly impacts the ability of the platform to achieve its mission.Modelling and simulation of not just the ship's sensors and weapons, but also the CMS, is therefore critical if we aim to thoroughly evaluate the capability of the platform in combat scenarios.Such studies can reveal the strengths and weaknesses of a platform, capability gaps and areas of opportunity, providing an evidence base to improve tactics and strategy, force structure and acquisition decisions.As of 2021, the Royal Australian Navy surface fleet includes three Hobart Class guided missile destroyers, each employing the Lockheed Martin developed Aegis CMS.The Royal Australian Navy also comprises eight Anzac Class frigates employing the Saab developed 9LV CMS.Later this decade the Anzac Class frigates will begin to be replaced by nine Hunter Class frigates with an Aegis CMS and 9LV tactical interface.Understanding the capability and limitations of these ships requires an understanding of how their respective CMS installations will perform.Based on references of the Aegis CMS, we have constructed, and continue to develop, a highly configurable CMS model called Comet, which is capable of interfacing with other models in constructive simulation environments to enable naval combat analysis studies.The architecture and functionality of Comet are presented in this paper.Comet has been utilised in combat analysis studies to evaluate the performance of surface naval platforms against a variety of missile threats.The Find, Fix, Track, Target, Engage, Assess (F2T2EA) kill chain summarises the sequence of processes which occur in the detection, engagement and intercept of a threat.By evaluating the F2T2EA kill chain, the performance capabilities and limitations of a platform are identified and opportunities for improvement in the engagement kill chain are discovered.Alternative tactics, strategy, equipment configurations and/or new procurements can be modelled and analysed to discover if they improve capability.Comet can be executed in two different modes: the CMS Emulation mode or the System Level Analytical Baseline (SLAB) mode.The SLAB mode is a cut-down version of the Comet Fire Control System developed to provide an efficient and comprehensive evaluation of threat engageability and interceptability at each point in time, whereas the CMS Emulation mode represents how a real CMS will engage the threat, wait for the intercept attempt to complete and then reengage if necessary.The analytical use cases of Comet are presented here in the context of analysing the air and missile defence capability of naval surface vessels.

The volume of the olfactory bulbs (OBs) relative to the brain has been used previously as a proxy for olfactory capabilities in many vertebrate taxa, including fishes. Although this gross approach has predictive power, a more accurate assessment of the number of afferent olfactory inputs and the convergence of this information at the level of the telencephalon is critical to our understanding of the role of olfaction in the behaviour of fishes. In this study, we used transmission electron microscopy to assess the number of first-order axons within the olfactory nerve (ON) and the number of second-order axons in the olfactory peduncle (OP) in established model species within cartilaginous (brownbanded bamboo shark, Chiloscyllium punctatum [CP]) and bony (common goldfish, Carassius auratus [CA]) fishes. The total number of axons varied from a mean of 18.12 ± 7.50 million in the ON to a mean of 0.38 ± 0.21 million in the OP of CP, versus 0.48 ± 0.16 million in the ON and 0.09 ± 0.02 million in the OP of CA. This resulted in a convergence ratio of approximately 50:1 and 5:1, respectively, for these two species. Based on astroglial ensheathing, axon type (unmyelinated [UM] and myelinated [M]) and axon size, we found no differentiated tracts in the OP of CP, whereas a lateral and a medial tract (both of which could be subdivided into two bundles or areas) were identified for CA, as previously described. Linear regression analyses revealed significant differences not only in axon density between species and locations (nerves and peduncles), but also in axon type and axon diameter (p < 0.05). However, UM axon diameter was larger in the OPs than in the nerve in both species (p = 0.005), with no significant differences in UM axon diameter in the ON (p = 0.06) between species. This study provides an in-depth analysis of the neuroanatomical organisation of the ascending olfactory pathway in two fish taxa and a quantitative anatomical comparison of the summation of olfactory information. Our results support the assertion that relative OB volume is a good indicator of the level of olfactory input and thereby a proxy for olfactory capabilities.

Baited video systems have been widely used to assess the relative abundance and diversity of sharks in locations around the world, however they provide limited information on behaviour. We developed and pilot tested a novel experimental approach to investigate whether repeated deployments of baited video systems in the same location could generate quantitative data on shark behavioural patterns, in the context of shark depredation (where sharks consume hooked fish). Specifically, we sought to test whether repeated exposure to boats and food in the same location would lead to a change in the arrival time and first feeding time of sharks, over a short timescale. We used the Ningaloo Marine Park (NMP) in Western Australia, a location where higher shark depredation rates have been identified in consistently fished areas, as a case study. A modified Baited Remote Underwater Video (BRUV) system was repeatedly deployed at two fished sites and two sites within a no-take marine reserve in the NMP, over six consecutive days, to mimic repeated recreational fishing and the availability of hooked fish for sharks to depredate. This approach was designed to investigate and disentangle the potential role of changes in behaviour versus variation in shark abundance, as a mechanism for how and why shark depredation can occur. Here, we report preliminary results from this methodological approach, where time of arrival and time of first feeding declined markedly in the fished site over 6 days of BRUV deployments, compared to the control site in the no-take marine reserve. A greater number of individuals from four carcharhinid species were observed at the fished site, compared to only three individuals from two species in the no-take marine reserve. The preliminary results from pilot testing of this novel experimental approach suggest that, with further modifications to identify individual sharks, and a greater spatial and temporal replication of sampling, it may be possible to identify behavioural changes occurring in sharks in the context of shark depredation. Understanding this mechanism can bring important benefits for fishers and managers, as it can lead to modifications in fishing methods designed at reducing the occurrence of behavioural changes in sharks, and thus mitigating shark depredation.

Shark depredation, whereby a shark consumes an animal caught by fishing gear, can cause higher mortality for target species, injury to sharks and the loss of catch and fishing gear. A critical first step towards potential mitigation is understanding this behaviour and the shark species involved, because the identity of depredating shark species is unknown in many fisheries, and behavioural dynamics of shark interactions with fishing gear are not well understood. We used line-mounted video cameras in a recreational fishery in the Ningaloo region of Western Australia to: (1) identify shark species responsible for depredation, (2) investigate behavioural interactions with fishing gear, (3) identify the prevalence of retained fishing gear in sharks and (4) quantify the influence of environmental variables and fishing methods on shark abundance during demersal fishing at 92 locations. The shark depredation rate was 9.1 %, and sicklefin lemon Negaprion acutidens, blacktip/Australian blacktip Carcharhinus limbatus/tilstoni, grey reef C. amblyrhynchos and spottail C. sorrah sharks were observed depredating lethrinid and epinephelid fishes. Five additional shark species from 4 families were recorded but were not responsible for depredation. Sharks frequently investigated baited hooks and other fishing gear components and were observed following the fishing gear as it was retrieved. The relative abundance of sharks at each fishing location was influenced by longitude, sea surface temperature and total number of fish hooked. By identifying the shark species responsible for depredation, and investigating their behavioural interactions with fishing gear, this study provides important insights that have broader significance to other fisheries, particularly for understanding impacts on sharks and for developing effective deterrents to mitigate shark depredation.

Shark depredation, where a shark consumes a hooked fish before it can be retrieved to the fishing vessel, can occur in recreational fisheries. This may cause higher mortality rates in target fish species, injuries to sharks from fishing gear and negatively impact the recreational fishing experience. This study quantified spatial variation and frequency of shark depredation in a recreational fishery in the Ningaloo Marine Park and Exmouth Gulf, Western Australia, by surveying 248 fishing boats at west coast boat ramps and 155 boats at Exmouth Gulf boat ramps from July 2015 to May 2016. Shark depredation occurred on 38.7% of fishing trips from west coast boat ramps and 41.9% of trips from Exmouth Gulf boat ramps. The mean (+/- 95% CI) shark depredation rate per trip was 13.7 +/- 3.3% for demersal fishing (n = 185) and 11.8 +/- 6.8% for trolling (n = 63) for west coast boat ramps, compared to 11.5 +/- 2.8% (n = 128) and 7.2 +/- 8.4% (n = 27) for Exmouth Gulf ramps. Depredation rates varied spatially, with higher depredation in areas which received greater fishing pressure. A novel application of Tweedie generalised additive mixed models indicated that depth, the number of other boats fishing within 5 km and survey period influenced depredation rates for fishing trips from west coast boat ramps. For the Exmouth Gulf ramps, fishing pressure and decreasing latitude positively affected the number of fish depredated. These results highlight the important influence of spatial variation in fishing pressure. The occurrence of higher depredation rates in areas which receive greater fishing pressure may indicate the formation of a behavioural association in the depredating sharks. This study is the first quantitative assessment of shark depredation in an Australian recreational fishery, and provides important insights that can assist recreational fishers and managers in reducing depredation.

Shark depredation, where a shark partially or completely consumes an animal caught by fishing gear before it can be retrieved to the fishing vessel, occurs in commercial and recreational fisheries worldwide, causing a range of negative biological and economic impacts. Despite this, it remains relatively understudied compared to other fisheries issues. This is the first review of the literature relating to shark depredation, which also includes an overview of the potential mechanisms underlying its occurrence and options for mitigation. Furthermore, this review highlights key research gaps that remain to be investigated, thereby providing impetus for future research. In total, 61 studies have been published between 1955 and 2018, which include information on shark depredation. These studies recorded quantitative rates of depredation between 0.9 and 26% in commercial and recreational fisheries and during research fishing, identified 27 shark species from seven families that were responsible for depredation and discussed potential factors influencing its occurrence. Information from research into bycatch mitigation and the testing of shark deterrent approaches and technologies is also presented, in the context of applying these approaches to the reduction of shark depredation. This review presents an holistic overview of shark depredation in fisheries globally and, in doing so, provides a central resource for fisheries researchers and managers focusing on this topic to stimulate further collaborative research on this important fisheries issue.

The effect of environmental variables on blue shark Prionace glauca catch per unit effort (CPUE) in a recreational fishery in the western English Channel, between June and September 1998-2011, was quantified using generalized additive models (GAMs). Sea surface temperature (SST) explained 1·4% of GAM deviance, and highest CPUE occurred at 16·7° C, reflecting the optimal thermal preferences of this species. Surface chlorophyll a concentration (CHL) significantly affected CPUE and caused 27·5% of GAM deviance. Additionally, increasing CHL led to rising CPUE, probably due to higher productivity supporting greater prey biomass. The density of shelf-sea tidal mixing fronts explained 5% of GAM deviance, but was non-significant, with increasing front density negatively affecting CPUE. Time-lagged frontal density significantly affected CPUE, however, causing 12·6% of the deviance in a second GAM and displayed a positive correlation. This outcome suggested a delay between the evolution of frontal features and the subsequent accumulation of productivity and attraction of higher trophic level predators, such as P. glauca.