The Drone Revolution of Shark Science: A Review

Novel pre-copulatory behavior in basking sharks observed by drone

Basking sharks (Cetorhinus maximus) seasonally aggregate in coastal surface waters of the North Atlantic, providing opportunities for visual observation. While putative courtship displays have been observed, actual copulation has not been documented. Here we examine video collected by an unmanned aerial vehicle ("drone") of novel behavioral interactions between basking sharks in Cape Cod Bay, Massachusetts in May 2021. The behaviors, including close following and tight concentric circling, are consistent with pre-copulatory behavior observed in other shark species. These observations provide new insights into the pre-copulatory behavior of basking sharks.

Predicting whaler shark presence and interactions with humans in southern Queensland, Australia

The Queensland Shark Control Program (QSCP) started in 1962 to reduce the number of shark-human incidents by deploying nets and drumlines across the most popular beaches. The program targets large shark species (white, tiger and bull sharks) that are potentially hazardous to bathers. However, this strategy is lethal for other sharks and marine wildlife, including threatened and endangered species. Thus, finding non-lethal strategies is a priority. To better manage shark-human interactions, establishing a better understanding of the factors that drive shark movement is key. Here we used sea surface temperature (SST), rainfall and distance to rivers as environmental variables to predict the presence of whaler sharks in southern Queensland based on 26 years of catch data from the QSCP. We found that SST is positively corelated to sharks caught by drumlines, while rainfall was associated with the number of sharks captured in shark nets. In addition, more sharks were captured by nets and drumlines further away from rivers, and nets captured roughly 10 times more sharks than drumlines over the period of study. In contrast to tiger sharks, the catch data indicate the number of whalers has not declined over the past 26 years. Our findings suggest that environmental variables can be used to predict the movement of large sharks and by incorporating this knowledge into management plans and public education programs, may ultimately reduce shark-human incidents.

Risks of Drone Use in Light of Literature Studies

This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning of the research, conducting a systematic review of the literature, proposing a classification framework corresponding to contemporary research trends related to the risk of drone applications, and compiling the characteristics of the publications assigned to each of the highlighted thematic groups. This systematic literature review used the PRISMA method. A total of 257 documents comprising articles and conference proceedings were analysed. On this basis, eight thematic categories related to the use of drones and the risks associated with their operation were distinguished. Due to the high content within two of these categories, a further division into subcategories was proposed to illustrate the research topics better. The conducted investigation made it possible to identify the current research trends related to the risk of drone use and pointed out the existing research gaps, both in the area of risk assessment methodology and in its application areas. The results obtained from the analysis can provide interesting material for both industry and academia.

Shifts in the incidence of shark bites and efficacy of beach-focussed mitigation in Australia

Shark-human interactions are some of the most pervasive human-wildlife conflicts, and their frequencies are increasing globally. New South Wales (Australia) was the first to implement a broad-scale program of shark-bite mitigation in 1937 using shark nets, which expanded in the late 2010s to include non-lethal measures. Using 196 unprovoked shark-human interactions recorded in New South Wales since 1900, we show that bites shifted from being predominantly on swimmers to 79 % on surfers by the 1980s and increased 2-4-fold. We could not detect differences in the interaction rate at netted versus non-netted beaches since the 2000s, partly because of low incidence and high variance. Although shark-human interactions continued to occur at beaches with tagged-shark listening stations, there were no interactions while SMART drumlines and/or drones were deployed. Our effect-size analyses show that a small increase in the difference between mitigated and non-mitigated beaches could indicate reductions in shark-human interactions. Area-based protection alone is insufficient to reduce shark-human interactions, so we propose a new, globally transferable approach to minimise risk of shark bite more effectively.

Utility of Spectral Filtering to Improve the Reliability of Marine Fauna Detections from Drone-Based Monitoring

Monitoring marine fauna is essential for mitigating the effects of disturbances in the marine environment, as well as reducing the risk of negative interactions between humans and marine life. Drone-based aerial surveys have become popular for detecting and estimating the abundance of large marine fauna. However, sightability errors, which affect detection reliability, are still apparent. This study tested the utility of spectral filtering for improving the reliability of marine fauna detections from drone-based monitoring. A series of drone-based survey flights were conducted using three identical RGB (red-green-blue channel) cameras with treatments: (i) control (RGB), (ii) spectrally filtered with a narrow 'green' bandpass filter (transmission between 525 and 550 nm), and, (iii) spectrally filtered with a polarising filter. Video data from nine flights comprising dolphin groups were analysed using a machine learning approach, whereby ground-truth detections were manually created and compared to AI-generated detections. The results showed that spectral filtering decreased the reliability of detecting submerged fauna compared to standard unfiltered RGB cameras. Although the majority of visible contrast between a submerged marine animal and surrounding seawater (in our study, sites along coastal beaches in eastern Australia) is known to occur between 515-554 nm, isolating the colour input to an RGB sensor does not improve detection reliability due to a decrease in the signal to noise ratio, which affects the reliability of detections.

The biology and ecology of the basking shark: A review

Here we review the literature on the basking shark (Cetorhinus maximus, Gunnerus, 1765), well known as the second largest extant shark (and fish) species globally. Previous reviews were published by Kunzlik in 1988 and Sims in 2008, but in the last 15 years modern electronic and DNA sequencing technologies have resulted in considerable advances in our knowledge of the species' behaviour and ecology. Basking sharks are planktivores and under appropriate conditions spend prolonged periods at the ocean surface feeding on copepod prey that primarily make up their diet, the behaviour that gave rise to their common name. In general, they are migratory and move into higher latitude waters during the summer months, when loose surface-feeding aggregations may form at favoured sites, the best known of which at present occur at hotspots on the west coasts of Britain and Ireland. The species is found circumglobally in temperate waters, but they are also now known on occasion to migrate at depth between northern and southern hemispheres, as well as across oceans within the northern hemisphere. In the past basking shark were more abundant across much of their range, but, consequent on targeted fisheries and in some places intentional eradication, became everywhere scarce, with recent population recovery in the north-east Atlantic being the result of protective measures initiated in the 1990s. Despite their charismatic nature, some of their most fundamental biological processes including copulation, gestation and birth remain largely unknown, due to their migratory and often deep-water lifestyle. In contrast, the deployment of small-scale archival and satellite tags has revealed the details of both broadscale migratory movements and horizontal and vertical foraging behaviours. Recent genetic studies support evidence suggesting a degree of site fidelity in relation to seasonal feeding grounds, which likely explains why in the past local populations have collapsed following periods of intensive fishing. Other recent research using aerial drones and towed cameras has revealed within loose feeding aggregations elements of social behaviour that may have a courtship function as well as enhance feeding efficiency.

Bull Shark (Carcharhinus leucas) Occurrence along Beaches of South-Eastern Australia: Understanding Where, When and Why

Unprovoked shark bites have increased over the last three decades, yet they are still relatively rare. Bull sharks are globally distributed throughout rivers, estuaries, nearshore areas and continental shelf waters, and are capable of making long distance movements between tropical and temperate regions. As this species is implicated in shark bites throughout their range, knowledge of the environmental drivers of bull shark movements are important for better predicting the likelihood of their occurrence at ocean beaches and potentially assist in reducing shark bites. Using the largest dataset of acoustically tagged bull sharks in the world, we examined the spatial ecology of 233 juvenile and large (including sub-adult and adult) bull sharks acoustically tagged and monitored over a 5.5-year period (2017-2023) using an array of real-time acoustic listening stations off 21 beaches along the coast of New South Wales, Australia. Bull sharks were detected more in coastal areas of northern NSW (<32° S) but they travelled southwards during the austral summer and autumn. Juveniles were not detected on shark listening stations until they reached 157 cm and stayed north of 31.98° S (Old Bar). Intra-specific diel patterns of occurrence were observed, with juveniles exhibiting higher nearshore presence between 20:00 and 03:00, whilst the presence of large sharks was greatest from midday through to 04:00. The results of generalised additive models revealed that large sharks were more often found when water temperatures were higher than 20 °C, after >45 mm of rain and when swell heights were between 1.8 and 2.8 m. Understanding the influence that environmental variables have on the occurrence of bull sharks in the coastal areas of NSW will facilitate better education and could drive shark smart behaviour amongst coastal water users.

The genetics-morphology-behavior trifecta: Unraveling the single greatest limitation affecting our understanding of chondrichthyan evolution

Sharks, rays, and chimaera form the clade Chondrichthyes, an ancient group of morphologically and ecologically diverse vertebrates that has played an important role in our understanding of gnathostome evolution. Increasingly, studies seek to investigate evolutionary processes operating within the chondrichthyan crown group, with the broad aim of understanding the driving forces behind the vast phenotypic diversity observed among its constituent taxa. Genetic, morphological, and behavioral studies have all contributed to our understanding of phenotypic evolution yet are typically considered in isolation in the context of Chondrichthyes. In this viewpoint, I discuss why such isolation is prevalent in the literature, how it constrains our understanding of evolution, and how it might be overcome. I argue that integrating these core fields of organismal biology is vital if we are to understand the evolutionary processes operating in contemporary chondrichthyan taxa and how such processes have contributed to past phenotypic evolution. Despite this, the necessary tools to overcome this major limitation already exist and have been applied to other taxa.

A content analysis of 32 years of Shark Week documentaries

Despite evidence of their importance to marine ecosystems, at least 32% of all chondrichthyan species are estimated or assessed as threatened with extinction. In addition to the logistical difficulties of effectively conserving wide-ranging marine species, shark conservation is believed to have been hindered in the past by public perceptions of sharks as dangerous to humans. Shark Week is a high-profile, international programming event that has potentially enormous influence on public perceptions of sharks, shark research, shark researchers, and shark conservation. However, Shark Week has received regular criticism for poor factual accuracy, fearmongering, bias, and inaccurate representations of science and scientists. This research analyzes the content and titles of Shark Week episodes across its entire 32 years of programming to determine if there are trends in species covered, research techniques featured, expert identity, conservation messaging, type of programming, and portrayal of sharks. We analyzed titles from 272 episodes (100%) of Shark Week programming and the content of all available (201; 73.9%) episodes. Our data demonstrate that the majority of episodes are not focused on shark bites, although such shows are common and many Shark Week programs frame sharks around fear, risk, and adrenaline. While criticisms of disproportionate attention to particular charismatic species (e.g. great whites, bull sharks, and tiger sharks) are accurate and supported by data, 79 shark species have been featured briefly at least once. Shark Week's depictions of research and of experts are biased towards a small set of (typically visual and expensive) research methodologies and (mostly white, mostly male) experts, including presentation of many white male non-scientists as scientific experts. While sharks are more often portrayed negatively than positively, limited conservation messaging does appear in 53% of episodes analyzed. Results suggest that as a whole, while Shark Week is likely contributing to the collective public perception of sharks as bad, even relatively small alterations to programming decisions could substantially improve the presentation of sharks and shark science and conservation issues.

Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia

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.

The Relative Abundance and Occurrence of Sharks off Ocean Beaches of New South Wales, Australia

There is still limited information about the diversity, distribution, and abundance of sharks in and around the surf zones of ocean beaches. We used long-term and large-scale drone surveying techniques to test hypotheses about the relative abundance and occurrence of sharks off ocean beaches of New South Wales, Australia. We quantified sharks in 36,384 drone flights across 42 ocean beaches from 2017 to 2021. Overall, there were 347 chondrichthyans recorded, comprising 281 (81.0%) sharks, with observations occurring in <1% of flights. Whaler sharks (Carcharhinus spp.) had the highest number of observations (n = 158) recorded. There were 34 individuals observed for both white sharks (Carcharodon carcharias) and critically endangered greynurse sharks (Carcharias taurus). Bull sharks (Carcharhinus leucas), leopard sharks (Stegostoma tigrinum) and hammerhead species (Sphyrna spp.) recorded 29, eight and three individuals, respectively. Generalised additive models were used to identify environmental drivers for detection probability of white, bull, greynurse, and whaler sharks. Distances to the nearest estuary, headland, and island, as well as water temperature and wave height, were significant predictors of shark occurrence; however, this varied among species. Overall, we provide valuable information for evidence-based species-specific conservation and management strategies for coastal sharks.

UAV remote sensing applications in marine monitoring: Knowledge visualization and review

With the booming development of information technology and the growing demand for remote sensing data, unmanned aerial vehicle (UAV) remote sensing technology has emerged. In recent years, UAV remote sensing technology has developed rapidly and has been widely used in the fields of military defense, agricultural monitoring, surveying and mapping management, and disaster and emergency response and management. Currently, increasingly serious marine biological and environmental problems are raising the need for effective and timely monitoring. Compared with traditional marine monitoring technologies, UAV remote sensing is becoming an important means for marine monitoring thanks to its flexibility, efficiency and low cost, while still producing systematic data with high spatial and temporal resolutions. This study visualizes the knowledge domain of the application and research advances of UAV remote sensing in marine monitoring by analyzing 1130 articles (from 1993 to early 2022) using a bibliometric approach and provides a review of the application of UAVs in marine management mapping, marine disaster and environmental monitoring, and marine wildlife monitoring. It aims to promote the extensive application of UAV remote sensing in the field of marine research.

Diving into the vertical dimension of elasmobranch movement ecology

Knowledge of the three-dimensional movement patterns of elasmobranchs is vital to understand their ecological roles and exposure to anthropogenic pressures. To date, comparative studies among species at global scales have mostly focused on horizontal movements. Our study addresses the knowledge gap of vertical movements by compiling the first global synthesis of vertical habitat use by elasmobranchs from data obtained by deployment of 989 biotelemetry tags on 38 elasmobranch species. Elasmobranchs displayed high intra- and interspecific variability in vertical movement patterns. Substantial vertical overlap was observed for many epipelagic elasmobranchs, indicating an increased likelihood to display spatial overlap, biologically interact, and share similar risk to anthropogenic threats that vary on a vertical gradient. We highlight the critical next steps toward incorporating vertical movement into global management and monitoring strategies for elasmobranchs, emphasizing the need to address geographic and taxonomic biases in deployments and to concurrently consider both horizontal and vertical movements.

Warm beach, warmer turtles: Using drone-mounted thermal infrared sensors to monitor sea turtle nesting activity

For decades sea turtle projects around the world have monitored nesting females using labor-intensive human patrolling techniques. Here we describe the first empirical testing of a drone-mounted thermal infrared sensor for nocturnal sea turtle monitoring; on the Osa peninsula in Costa Rica. Preliminary flights verified that the drone could detect similar sea turtle activities as identified by on-the-ground human patrollers – such as turtles, nests and tracks. Drone observers could even differentiate tracks of different sea turtle species, detect sea turtle hatchlings, other wildlife, and potential poachers. We carried out pilot flights to determine optimal parameters for detection by testing different thermal visualization modes, drone heights, and gimbal angles. Then, over seven nights, we set up a trial to compare the thermal drone and operators’ detections with those observed by traditional patrollers. Our trials showed that thermal drones can record more information than traditional sea turtle monitoring methods. The drone and observer detected 20% more sea turtles or tracks than traditional ground-based patrolling (flights and patrols carried out across the same nights at the same time and beach). In addition, the drone operator detected 39 other animals/predators and three potential poachers that patrollers failed to detect. Although the technology holds great promise in being able to enhance detection rates of nesting turtles and other beach activity, and in helping to keep observers safer, we detail challenges and limiting factors; in drone imagery, current cost barriers, and technological advances that need to be assessed and developed before standardized methodologies can be adopted. We suggest potential ways to overcome these challenges and recommend how further studies can help to optimize thermal drones to enhance sea turtle monitoring efforts worldwide.

The Future of Artificial Intelligence in Monitoring Animal Identification, Health, and Behaviour

Simple Summary

Due to climate change and human interference, many species are now without habitats and on the brink of extinction. Zoos and other conservation spaces allow for non-human animal preservation and public education about endangered species and ecosystems. Monitoring the health and well-being of animals in care, while providing species-specific environments, is critical for zoo and conservation staff. In order to best provide such care, keepers and researchers need to gather as much information as possible about individual animals and species as a whole. This paper focuses on existing technology to monitor animals, providing a review on the history of technology, including recent technological advancements and current limitations. Subsequently, we provide a brief introduction to our proposed novel computer software: an artificial intelligence software capable of unobtrusively and non-invasively tracking individuals’ location, estimating position, and analyzing behaviour. This innovative technology is currently being trained with orangutans at the Toronto Zoo and will allow for mass data collection, permitting keepers and researchers to closely monitor individual animal welfare, learn about the variables impacting behaviour and provide additional enrichment or interventions accordingly.

Abstract

With many advancements, technologies are now capable of recording non-human animals’ location, heart rate, and movement, often using a device that is physically attached to the monitored animals. However, to our knowledge, there is currently no technology that is able to do this unobtrusively and non-invasively. Here, we review the history of technology for use with animals, recent technological advancements, current limitations, and a brief introduction to our proposed novel software. Canadian tech mogul EAIGLE Inc. has developed an artificial intelligence (AI) software solution capable of determining where people and assets are within public places or attractions for operational intelligence, security, and health and safety applications. The solution also monitors individual temperatures to reduce the potential spread of COVID-19. This technology has been adapted for use at the Toronto Zoo, initiated with a focus on Sumatran orangutans (Pongo abelii) given the close physical similarity between orangutans and humans as great ape species. This technology will be capable of mass data collection, individual identification, pose estimation, behaviour monitoring and tracking orangutans’ locations, in real time on a 24/7 basis, benefitting both zookeepers and researchers looking to review this information.

Drones can reliably, accurately and with high levels of precision, collect large volume water samples and physio-chemical data from lakes

The rapid development and application of drone technology has included water sampling and collection of physiochemical data from lakes. Previous research has demonstrated the significant potential of drones to play a future pivotal role in the collection of such data from lakes that fulfil requirements of large-scale monitoring programmes. However, currently the utilisation of drone technology for water quality monitoring is hindered by a number of important limitations: i) the low rate of successful sample captured; ii) the relatively low volume of water sample retrieved for analyses of multiple water chemistry parameters; and critically iii) differences between water chemistry parameters when using a drone versus samples collected by boat. Here we present results comparing the water chemistry results of a large number of parameters (pH, dissolved oxygen concentration, temperature, conductivity, alkalinity, hardness, true colour, chloride, silica, ammonia, total oxidised nitrogen, nitrite, nitrate, ortho-phosphate, total phosphorous and chlorophyll) sampled via drone with samples collected by boat in a number of lakes. The drone water sampling method used here is the first to collect a sufficiently large volume of water to meet the monitoring requirements of large scale water monitoring programmes, 2 L, at a 100% success rate and most crucially, with water chemistry variables that are not significantly different to those taken using traditional boat water sampling. This study therefore shows that drone technology can be utilised to collect water chemistry data and samples from lakes in a reliable, more rapid and cost effective manner than traditional sampling using boats, that is safer for personnel and poses less of a biosecurity risk.

Using Drones to Assess Volitional Swimming Kinematics of Manta Ray Behaviors in the Wild

Drones have become increasingly popular tools to study marine megafauna but are underutilized in batoid research. We used drones to collect video data of manta ray (Mobula cf. birostris) swimming and assessed behavior-specific kinematics in Kinovea, a semi-automated point-tracking software. We describe a ‘resting’ behavior of mantas making use of strong currents in man-made inlets in addition to known ‘traveling’ and ‘feeding’ behaviors. No significant differences were found between the swimming speed of traveling and feeding behaviors, although feeding mantas had a significantly higher wingbeat frequency than traveling mantas. Resting mantas swam at a significantly slower speed and wingbeat frequency, suggesting that they were continuously swimming with the minimum effort required to maintain position and buoyancy. Swimming speed and wingbeat frequency of traveling and feeding behaviors overlapped, which could point to other factors such as prey availability and a transitional behavior, influencing how manta rays swim. These baseline swimming kinematic data have valuable applications to other emerging technologies in manta ray research.

The emergence of marine recreational drone fishing: Regional trends and emerging concerns

Online evidence suggests that there has been an increase in interest of using unmanned aerial vehicles or drones during land-based marine recreational fishing. In the absence of reliable monitoring programs, this study used unconventional publicly available online monitoring methodologies to estimate the growing interest, global extent, catch composition and governance of this practice. Results indicated a 357% spike in interest during 2016 primarily in New Zealand, South Africa and Australia. From an ecological perspective, many species targeted by drone fishers are vulnerable to overexploitation, while released fishes may experience heightened stress and mortality. From a social perspective, the ethics of drone fishing are being increasingly questioned by many recreational anglers and we forecast the potential for increased conflict with other beach users. In terms of governance, no resource use legislation specifically directed at recreational drone fishing was found. These findings suggest that drone fishing warrants prioritised research and management consideration.

How Big Is That Manta Ray? A Novel and Non-Invasive Method for Measuring Reef Manta Rays Using Small Drones

This study explores the application of small, commercially available drones to determine morphometric the measurements and record key demographic parameters of reef manta rays (Mobula alfredi) in Raja Ampat, Indonesia. DJI Mavic 2 Pro drones were used to obtain videos of surface-feeding M. alfredi with a floating, known-length PVC pipe as a reference scale—thus avoiding the need to utilize altitude readings, which are known to be unreliable in small drones, in our photogrammetry approach. Three dimensions (disc length (DL), disc width (DW), and cranial width (CW)) from 86 different individuals were measured. A hierarchical multivariate model was used to estimate the true measurements of these three dimensions and their population-level multivariate distributions. The estimated true measurements of these dimensions were highly accurate and precise, with the measurement of CW more accurate than that of DL and, especially, of DW. Each pairing of these dimensions exhibited strong linear relationships, with estimated correlation coefficients ranging from 0.98–0.99. Given these, our model allows us to accurately calculate DW (as the standard measure of body size for mobulid rays) using the more accurate CW and DL measurements. We estimate that the smallest mature M. alfredi of each sex we measured were 274.8 cm (males, n = 30) and 323.5 cm DW (females, n = 8). We conclude that small drones are useful for providing an accurate “snapshot” of the size distribution of surface-feeding M. alfredi aggregations and for determining the sex and maturity of larger individuals, all with minimal impact on this vulnerable species.

Social networks and the conservation of fish

Despite our critical dependence on aquatic wildlife, we lack a complete understanding of the drivers of population stability and structure for most fish species. Social network analysis has been increasingly used to investigate animal societies as it explicitly links individual decision-making to population-level processes and demography. While the study of social structure is of great ecological interest, it is also potentially important for species of economic value or of conservation concern. To date however, there has been little focus on how social processes are likely to influence the conservation of fish populations. Here we identify applications for how a social network approach can help address broad fish conservation themes such as population structure, biological invasions or fisheries management. We discuss the burgeoning opportunities offered and challenges still faced by current technologies to integrate social network approaches within fish conservation.

Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground

Getting maternal milk through nursing is vital for all newborn mammals. Despite its importance, nursing has been poorly documented in humpback whales (Megaptera novaeangliae). Nursing is difficult to observe underwater without disturbing the whales and is usually impossible to observe from a ship. We attempted to observe nursing from the calf's perspective by placing CATS cam tags on three humpback whale calves in the Sainte Marie channel, Madagascar, Indian Ocean, during the breeding seasons. CATS cam tags are animal-borne multi-sensor tags equipped with a video camera, a hydrophone, and several auxiliary sensors (including a 3-axis accelerometer, a 3-axis magnetometer, and a depth sensor). The use of multi-sensor tags minimized potential disturbance from human presence. A total of 10.52 h of video recordings were collected with the corresponding auxiliary data. Video recordings were manually analyzed and correlated with the auxiliary data, allowing us to extract different kinematic features including the depth rate, speed, Fluke Stroke Rate (FSR), Overall Body Dynamic Acceleration (ODBA), pitch, roll, and roll rate. We found that suckling events lasted 18.8 ± 8.8 s on average (N = 34) and were performed mostly during dives. Suckling events represented 1.7% of the total observation time. During suckling, the calves were visually estimated to be at a 30-45° pitch angle relative to the midline of their mother's body and were always observed rolling either to the right or to the left. In our auxiliary dataset, we confirmed that suckling behavior was primarily characterized by a high average absolute roll and additionally we also found that it was likely characterized by a high average FSR and a low average speed. Kinematic features were used for supervised machine learning in order to subsequently detect suckling behavior automatically. Our study is a proof of method on which future investigations can build upon. It opens new opportunities for further investigation of suckling behavior in humpback whales and the baleen whale species.

Optimal Navigation of an Unmanned Surface Vehicle and an Autonomous Underwater Vehicle Collaborating for Reliable Acoustic Communication with Collision Avoidance

This paper focuses on safe navigation of an unmanned surface vehicle in proximity to a submerged autonomous underwater vehicle so as to maximise short-range, through-water data transmission while minimising the probability that the two vehicles will accidentally collide. A sliding mode navigation law is developed, and a rigorous proof of optimality of the proposed navigation law is presented. The developed navigation algorithm is relatively computationally simple and easily implementable in real time. Illustrative examples with extensive computer simulations demonstrate the effectiveness of the proposed method.

The use of an unoccupied aerial vehicle to survey shark species over sand and rocky-reef habitats in a marine protected area

Cabo Pulmo National Park was established in 1995 and has since seen a large increase in fish biomass. An unoccupied aerial vehicle (UAV) was used to survey shallow coastal habitat in which lemon sharks (Negaprion brevirostris), bull sharks (Carcharhinus leucas) and Pacific nurse sharks (Ginglymostoma unami) were recorded. Sharks were more common in the afternoon, potentially using warmer shallow areas to behaviourally thermoregulate. This study highlights UAV surveying to be a viable tool for species identification, a limitation of previous terrestrial surveys conducted in the area.

Going Batty: The Challenges and Opportunities of Using Drones to Monitor the Behaviour and Habitat Use of Rays

The way an animal behaves in its habitat provides insight into its ecological role. As such, collecting robust, accurate datasets in a time-efficient manner is an ever-present pressure for the field of behavioural ecology. Faced with the shortcomings and physical limitations of traditional ground-based data collection techniques, particularly in marine studies, drones offer a low-cost and efficient approach for collecting data in a range of coastal environments. Despite drones being widely used to monitor a range of marine animals, they currently remain underutilised in ray research. The innovative application of drones in environmental and ecological studies has presented novel opportunities in animal observation and habitat assessment, although this emerging field faces substantial challenges. As we consider the possibility to monitor rays using drones, we face challenges related to local aviation regulations, the weather and environment, as well as sensor and platform limitations. Promising solutions continue to be developed, however, growing the potential for drone-based monitoring of behaviour and habitat use of rays. While the barriers to enter this field may appear daunting for researchers with little experience with drones, the technology is becoming increasingly accessible, helping ray researchers obtain a wide range of highly useful data.