Operational Protocols for the Use of Drones in Marine Animal Research

Rapid surveying of benthopelagic ecosystems with a towed mini-ROV

Surveying benthic communities has historically relied on snorkel or SCUBA, but these methods are labour-intensive, inefficient (∼1000 m2 per day covered for one dive pair) and depth-limited (<30 m depth). Here we detail a remote method using a towed mini-ROV that combines the depth capabilities and endurance of towed cameras with the flexibility and manoeuvrability of SCUBA and snorkel. Towed mini-ROV allows over 10 km of transects or 38,000 m2 of benthic surveys per day, produces data that can be geo-referenced, allows measurement of organisms using orthomosaics, can include physical data such as depth and temperature, and can operate from depths of 2-60 m without any gear changes. This setup requires only modest modifications of readily available equipment, and is relatively low-cost given the time and labour efficiencies gained. We provide some examples of the types of data that can be produced (video, imagery, spatial layer), as well as the sort of coverage that is realistic using real survey data obtained from the Great Barrier Reef, Australia. Results demonstrate this approach could be used on a large scale to rapidly survey benthic environments. It could be further improved by using a more hydrodynamic ROV design, and a more streamline pipeline that integrates data sources. Use of underwater positioning systems could improve spatial parameters, lasers could improve measurement accuracy, and additional cameras could increase spatial coverage, but at the cost of added complexity and hydrodynamic drag.

Closing the air gap: the use of drones for studying wildlife ecophysiology

Techniques for non-invasive sampling of ecophysiological data in wild animals have been developed in response to challenges associated with studying captive animals or using invasive methods. Of these, drones, also known as Unoccupied Aerial Vehicles (UAVs), and their associated sensors, have emerged as a promising tool in the ecophysiology toolkit. In this review, we synthesise research in a scoping review on the use of drones for studying wildlife ecophysiology using the PRISMA-SCr checklist and identify where efforts have been focused and where knowledge gaps remain. We use these results to explore current best practices and challenges and provide recommendations for future use. In 136 studies published since 2010, drones aided studies on wild animal body condition and morphometrics, kinematics and biomechanics, bioenergetics, and wildlife health (e.g. microbiomes, endocrinology, and disease) in both aquatic and terrestrial environments. Focal taxa are biased towards marine mammals, particularly cetaceans. While conducted globally, research is primarily led by institutions based in North America, Oceania, and Europe. The use of drones to obtain body condition and morphometric data through standard colour sensors and single camera photogrammetry predominates. Techniques such as video tracking and thermal imaging have also allowed insights into other aspects of wildlife ecophysiology, particularly when combined with external sampling techniques such as biologgers. While most studies have used commercially available multirotor platforms and standard colour sensors, the modification of drones to collect samples, and integration with external sampling techniques, have allowed multidisciplinary studies to integrate a suite of remote sensing methods more fully. We outline how technological advances for drones will play a key role in the delivery of both novel and improved wildlife ecophysiological data. We recommend that researchers prepare for the influx of drone-assisted advancements in wildlife ecophysiology through multidisciplinary and cross-institutional collaborations. We describe best practices to diversify across species and environments and use current data sources and technologies for more comprehensive results.

Harbour Porpoises Are Flexible Predators Displaying Context-Dependent Foraging Behaviours

Opportunistic mobile predators can adapt their behaviour to specific foraging scenarios, allowing them to target diverse prey resources. An interesting example is the harbour porpoise (Phocoena phocoena), a marine mammal with a huge energy demand feeding on a large variety of fish, squid and shrimps. Little is known about the foraging behaviour of harbour porpoises, as observations of wild specimens are notoriously difficult to obtain. In this study, foraging was identified in almost 60% of videos from UAV recordings in Danish coastal waters during daylight hours. Observations reveal them to be flexible predators, foraging on both single fish and schools of fish, as well as individually and in groups of varying sizes. We argue that some of the observed behavioural adaptations and context-dependent strategies for prey capture are based on information transfer and social learning. Our results provide unprecedented insights into the foraging behaviour of an opportunistic mammalian predator. Furthermore, this study highlights the importance of porpoises having access to coastal areas for energy acquisition, where they are in conflict with anthropogenic disturbances such as fisheries with the risk of bycatch.

On the move: Influence of animal movements on count error during drone surveys

The use of remote sensing to monitor animal populations has greatly expanded during the last decade. Drones (i.e., Unoccupied Aircraft Systems or UAS) provide a cost- and time-efficient remote sensing option to survey animals in various landscapes and sampling conditions. However, drone-based surveys may also introduce counting errors, especially when monitoring mobile animals. Using an agent-based model simulation approach, we evaluated the error associated with counting a single animal across various drone flight patterns under three animal movement strategies (random, directional persistence, and biased toward a resource) among five animal speeds (2, 4, 6, 8, 10 m/s). Flight patterns represented increasing spatial independence (ranging from lawnmower pattern with image overlap to systematic point counts). Simulation results indicated that flight pattern was the most important variable influencing count accuracy, followed by the type of animal movement pattern, and then animal speed. A  awnmower pattern with 0% overlap produced the most accurate count of a solitary, moving animal on a landscape (average count of 1.1 ± 0.6) regardless of the animal's movement pattern and speed. Image overlap flight patterns were more likely to result in multiple counts even when accounting for mosaicking. Based on our simulations, we recommend using a lawnmower pattern with 0% image overlap to minimize error and augment drone efficacy for animal surveys. Our work highlights the importance of understanding interactions between animal movements and drone survey design on count accuracy to inform the development of broad applications among diverse species and ecosystems.

Directional swimming patterns in jellyfish aggregations

Having a profound influence on marine and coastal environments worldwide, jellyfish hold significant scientific, economic, and public interest.1,2,3,4,5 The predictability of outbreaks and dispersion of jellyfish is limited by a fundamental gap in our understanding of their movement. Although there is evidence that jellyfish may actively affect their position,6,7,8,9,10 the role of active swimming in controlling jellyfish movement, and the characteristics of jellyfish swimming behavior, are not well understood. Consequently, jellyfish are often regarded as passively drifting or randomly moving organisms, both conceptually2,11 and in process studies.12,13,14 Here we show that the movement of jellyfish is modulated by distinctly directional swimming patterns that are oriented away from the coast and against the direction of surface gravity waves. Taking a Lagrangian viewpoint from drone videos that allows the tracking of multiple adjacent jellyfish, and focusing on the scyphozoan jellyfish Rhopilema nomadica as a model organism, we show that the behavior of individual jellyfish translates into a synchronized directional swimming of the aggregation as a whole. Numerical simulations show that this counter-wave swimming behavior results in biased correlated random-walk movement patterns that reduce the risk of stranding, thus providing jellyfish with an adaptive advantage critical to their survival. Our results emphasize the importance of active swimming in regulating jellyfish movement and open the way for a more accurate representation in model studies, thus improving the predictability of jellyfish outbreaks and their dispersion and contributing to our ability to mitigate their possible impact on coastal infrastructure and populations.

Spatial prioritization of dugong habitats in India can contribute towards achieving the 30 × 30 global biodiversity target

Indian coastal waters are critical for dugong populations in the western Indian Ocean. Systematic spatial planning of dugong habitats can help to achieve biodiversity conservation and area-based protection targets in the region. In this study, we employed environmental niche modelling to predict suitable dugong habitats and identify influencing factors along its entire distribution range in Indian waters. We examined data on fishing pressures collected through systematic interview surveys, citizen-science data, and field surveys to demarcate dugong habitats with varying risks. Seagrass presence was the primary factor in determining dugong habitat suitability across the study sites. Other variables such as depth, bathymetric slope, and Euclidean distance from the shore were significant factors, particularly in predicting seasonal suitability. Predicted suitable habitats showed a remarkable shift from pre-monsoon in Palk Bay to post-monsoon in the Gulf of Mannar, indicating the potential of seasonal dugong movement. The entire coastline along the Palk Bay-Gulf of Mannar region was observed to be at high to moderate risk, including the Gulf of Mannar Marine National Park, a high-risk area. The Andaman Islands exhibited high suitability during pre- and post-monsoon season, whereas the Nicobar Islands were highly suitable for monsoon season. Risk assessment of modelled suitable areas revealed that < 15% of high-risk areas across Andaman and Nicobar Islands and Palk Bay and Gulf of Mannar, Tamil Nadu, fall within the existing protected areas. A few offshore reef islands are identified under high-risk zones in the Gulf of Kutch, Gujarat. We highlight the utility of citizen science and secondary data in performing large-scale spatial ecological analysis. Overall, identifying synoptic scale 'Critical Dugong Habitats' has positive implications for the country's progress towards achieving the global 30 × 30 target through systematic conservation planning.

Can denticle morphology help identify southeastern Australian elasmobranchs?

Elasmobranchs are covered in scale-like structures called dermal denticles, comprising dentine and enameloid. These structures vary across the body of an individual and between species, and are frequently shed and preserved in marine sediments. With a good understanding of denticle morphology, current and historical elasmobranch diversity and abundance might be assessed from sediment samples. Here, replicate samples of denticles from the bodies of several known (deceased) shark species were collected and characterized for morphology before being assigned morphotypes. These data were used to expand the established literature describing denticles and to investigate intra- and interspecific variability, with the aim of increasing the viability of using sediment samples to assess elasmobranch diversity and abundance. Denticle morphology was influenced more by life-history traits than by species, where demersal species were largely characterized by generalized function and defense denticles, whereas pelagic and benthopelagic species were characterized by drag-reduction denticles. Almost all species possessed abrasion strength or defense denticles on the snout, precluding their utility for separating species. In a separate manipulative experiment, samples of denticles were collected from sediments in two aquaria with known elasmobranchs to determine their utility for reliably separating species. Visual examination of denticles, morphometric measurements, scaled photographs, and reference collections allowed for some precise identification, but not always to the species level. Ongoing work to develop denticle reference collections could help to identify past and present families and, in some cases, species.

Skinny dolphins: Can poor body condition explain population decline in Indo-Pacific humpback dolphins (Sousa chinensis)?

Indo-Pacific humpback dolphins (IPHDs) who form resident populations along the Chinese coastline are facing a wide range of anthropogenic disturbances including intense fishing and some populations have been shown to experience a severe decline. Body condition is thought to be a good indicator of health since it is linked to survival and reproductive success. In order to better understand population trends, we investigated whether the body condition of IPHDs is poorer in populations whose status is alarming than in other populations. UAV flights were conducted from 2022 to 2023 in four locations (i.e., Sanniang Bay, Leizhou Bay, Jiangmen, and Lingding Bay) in the northern South China Sea. Body ratios were calculated using the body length and widths of IPHDs and were used to analyze differences among seasons, locations, and demographic parameters. A PCA was then used to obtain a detailed picture of the body condition composition of dolphins at each location. Results showed that dolphins from Leizhou Bay and Jiangmen were in better body condition than those from Sanniang Bay and Lingding Bay. Since populations inhabiting Sanniang Bay and Lingding Bay have been shown to experience a sharp decline, it can be hypothesized that poor body condition may have played a role in such a trend. Further investigations of the factors impacting IPHDs' body condition are needed, including monitoring of prey density, contaminant concentration, stress levels, and impacts of human activities on dolphins' behavior. In addition, the creation of a robust scoring method would allow for regular monitoring of IPHDs' body condition to inform conservation measures.

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.

Underwater sound of three unoccupied aerial vehicles at varying altitudes and horizontal distances

Unoccupied aerial vehicles (UAVs), or "drones," are increasingly used as a tool for cetacean research, but knowledge about how these tools contribute to underwater sound is lacking. In this study, underwater sound levels of three commonly used UAV models (Mavic Pro Platinum, Phantom 4 Pro v2.0, Inspire 1 Pro) were recorded. For each model, three replicate flights were conducted at 36 positions at standardized horizontal (0-30 m) and vertical (2-40 m) distances from a hydrophone (1 m depth). Median broadband received levels of the Inspire were highest at 96.5 dBrms 141-17 783 Hz re 1 μPa2, followed by the Phantom (92.4 dBrms 141-17 783 Hz re 1 μPa2) and Mavic, which was quietest (85.9 dBrms 141-17 783 Hz re 1 μPa2). Median ambient sound levels in the absence of an UAV were 82.7 dBrms 141-17 783 Hz re 1 μPa2. Significant increases in ambient sound levels associated with UAV flights occurred at higher altitudes than previously reported, and received levels decreased more with increasing horizontal distance of the UAV than with altitude. To minimize potential noise impacts on sensitive marine animal subjects, we recommend increasing horizontal distance to the animal, rather than altitude, and choosing the quietest UAV feasible.

Deployment of biologging tags on free swimming large whales using uncrewed aerial systems

Suction-cup-attached biologging tags have led to major advances in our understanding of large whale behaviour. Getting close enough to a whale at sea to safely attach a tag is a major limiting factor when deploying these systems. Here we present an uncrewed aerial system (UAS)-based tagging technique for free-swimming large whales and provide data on efficacy from field testing on blue (Balaenoptera musculus) and fin (B. physalus) whales. Rapid transit speed and the bird's-eye view of the animal during UAS tagging contributed to the technique's success. During 8 days of field testing, we had 29 occasions when a focal animal was identified for attempted tagging and tags were successfully attached 21 times. The technique was efficient, with mean flight time of 2 min 45 s from launch to deployment and a mean distance of 490 m from the launch vessel to tagged animal, reducing potential adverse effects resulting from close approaches for tagging. These data indicate that UAS are capable of attaching biologging tags to free-swimming large whales quickly and from large distances, potentially increasing success rates, decreasing attempt times, and reducing animal disruption during tagging.

A pilot study to estimate the population size of endangered Galápagos marine iguanas using drones

BACKGROUND

Large-scale species monitoring remains a significant conservation challenge. Given the ongoing biodiversity crisis, the need for reliable and efficient methods has never been greater. Drone-based techniques have much to offer in this regard: they allow access to otherwise unreachable areas and enable the rapid collection of non-invasive field data. Herein, we describe the development of a drone-based method for the estimation of population size in Galápagos marine iguanas, Amblyrhynchus cristatus. As a large-bodied lizard that occurs in open coastal terrain, this endemic species is an ideal candidate for drone surveys. Almost all Amblyrhynchus subspecies are Endangered or Critically Endangered according to the IUCN yet since several colonies are inaccessible by foot, ground- based methods are unable to address the critical need for better census data. In order to establish a drone-based approach to estimate population size of marine iguanas, we surveyed in January 2021 four colonies on three focal islands (San Cristobal, Santa Fe and Espanola) using three techniques: simple counts (the standard method currently used by conservation managers), capture mark-resight (CMR), and drone-based counts. The surveys were performed within a 4-day window under similar ambient conditions. We then compared the approaches in terms of feasibility, outcome and effort.

RESULTS

The highest population-size estimates were obtained using CMR, and drone-based counts were on average 14% closer to CMR estimates-and 17-35% higher-than those obtained by simple counts. In terms of field-time, drone-surveys can be faster than simple counts, but image analyses were highly time consuming.

CONCLUSION

Though CMR likely produces superior estimates, it cannot be performed in most cases due to lack of access and knowledge regarding colonies. Drone-based surveys outperformed ground-based simple counts in terms of outcome and this approach is therefore suitable for use across the range of the species. Moreover, the aerial approach is currently the only credible solution for accessing and surveying marine iguanas at highly remote colonies. The application of citizen science and other aids such as machine learning will alleviate the issue regarding time needed to analyze the images.

Design and fabrication of a stereo-video camera equipped unoccupied aerial vehicle for measuring sea turtles, sharks, and other marine fauna

The recent commercialization of unoccupied aerial vehicles (UAVs) has facilitated their incorporation into a variety of ecological studies. While UAVs are able to provide accurate visual data of marine species from an aerial perspective, these devices have some limitations that make measuring marine animals below the surface challenging. Many marine organisms are often visible from the air, but are deeper in the water column, and current methods cannot measure animals below the surface. Here, we developed and tested a stereo-video camera (SVC) system that was mounted onto a commercially-available UAV. We used the SVC-UAV to conduct remote body-size measurements for two marine species: the green sea turtle (Chelonia mydas) and the nurse shark (Ginglymostoma cirratum). When comparing SVC measurements to those taken by hand, the SVC-UAV had a mean absolute error (MAE) of 4.44 cm (n = 6; mean percent error (MPE) = 10.6%) for green sea turtles and 7.16 cm absolute error (n = 1; PE = 3.6%) for the nurse shark. Using a linear model, we estimated the slope of the SVC versus hand measurements for green sea turtles to be 1.085 (±0.099 SE), and accounting for the standard error, a measurement bias was not apparent. Using model selection, based on a global model predicting MAE from animal distance to the SVC and body size, the top ranked model was the intercept-only model. This indicates that neither animal distance nor body size strongly influenced measurement error. Incorporating SVC systems into UAVs can allow for relatively accurate measurements of near surface-dwelling marine species. To our knowledge, there is no other stand-alone SVC for UAVs available that offers similar accuracy and utility.

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.

Remote sensing techniques for automated marine mammals detection: a review of methods and current challenges

Marine mammals are under pressure from multiple threats, such as global climate change, bycatch, and vessel collisions. In this context, more frequent and spatially extensive surveys for abundance and distribution studies are necessary to inform conservation efforts. Marine mammal surveys have been performed visually from land, ships, and aircraft. These methods can be costly, logistically challenging in remote locations, dangerous to researchers, and disturbing to the animals. The growing use of imagery from satellite and unoccupied aerial systems (UAS) can help address some of these challenges, complementing crewed surveys and allowing for more frequent and evenly distributed surveys, especially for remote locations. However, manual counts in satellite and UAS imagery remain time and labor intensive, but the automation of image analyses offers promising solutions. Here, we reviewed the literature for automated methods applied to detect marine mammals in satellite and UAS imagery. The performance of studies is quantitatively compared with metrics that evaluate false positives and false negatives from automated detection against manual counts of animals, which allows for a better assessment of the impact of miscounts in conservation contexts. In general, methods that relied solely on statistical differences in the spectral responses of animals and their surroundings performed worse than studies that used convolutional neural networks (CNN). Despite mixed results, CNN showed promise, and its use and evaluation should continue. Overall, while automation can reduce time and labor, more research is needed to improve the accuracy of automated counts. With the current state of knowledge, it is best to use semi-automated approaches that involve user revision of the output. These approaches currently enable the best tradeoff between time effort and detection accuracy. Based on our analysis, we identified thermal infrared UAS imagery as a future research avenue for marine mammal detection and also recommend the further exploration of object-based image analysis (OBIA). Our analysis also showed that past studies have focused on the automated detection of baleen whales and pinnipeds and that there is a gap in studies looking at toothed whales, polar bears, sirenians, and mustelids.

Drone Observations of Marine Life and Human–Wildlife Interactions off Sydney, Australia

Drones have become popular with the general public for viewing and filming marine life. One amateur enthusiast platform, DroneSharkApp, films marine life in the waters off Sydney, Australia year-round and posts their observations on social media. The drone observations include the behaviours of a variety of coastal marine wildlife species, including sharks, rays, fur seals, dolphins and fish, as well as migratory species such as migrating humpback whales. Given the extensive effort and multiple recordings of the presence, behaviour and interactions of various species with humans provided by DroneSharkApp, we explored its utility for providing biologically meaningful observations of marine wildlife. Using social media posts from the DroneSharkApp Instagram page, a total of 678 wildlife videos were assessed from 432 days of observation collected by a single observer. This included 94 feeding behaviours or events for fur seals (n = 58) and dolphins (n = 33), two feeding events for white sharks and one feeding event for a humpback whale. DroneSharkApp documented 101 interactions with sharks and humans (swimmers and surfers), demonstrating the frequent, mainly innocuous human–shark overlap off some of Australia’s busiest beaches. Finally, DroneSharkApp provided multiple observations of humpback and dwarf minke whales with calves travelling north, indicating calving occurring well south of traditional northern Queensland breeding waters. Collaboration between scientists and citizen scientists such as those involved with DroneSharkApp can greatly and quantitatively increase the biological understanding of marine wildlife data.

Beached and Floating Litter Surveys by Unmanned Aerial Vehicles: Operational Analogies and Differences

The abundance of litter pollution in the marine environment has been increasing globally. Remote sensing techniques are valuable tools to advance knowledge on litter abundance, distribution and dynamics. Images collected by Unmanned Aerial Vehicles (UAV, aka drones) are highly efficient to map and monitor local beached (BL) and floating (FL) marine litter items. In this work, the operational insights to carry out both BL and FL surveys using UAVs are detailly described. In particular, flight planning and deployment, along with image products processing and analysis, are reported and compared. Furthermore, analogies and differences between UAV-based BL and FL mapping are discussed, with focus on the challenges related to BL and FL item detection and recognition. Given the efficiency of UAV to map BL and FL, this remote sensing technique can replace traditional methods for litter monitoring, further improving the knowledge of marine litter dynamics in the marine environment. This communication aims at helping researchers in planning and performing optimized drone-based BL and FL surveys.

QuadNet: A Hybrid Framework for Quadrotor Dead Reckoning

Quadrotor usage is continuously increasing for both civilian and military applications such as surveillance, mapping, and deliveries. Commonly, quadrotors use an inertial navigation system combined with a global navigation satellite systems receiver for outdoor applications and a camera for indoor/outdoor applications. For various reasons, such as lighting conditions or satellite signal blocking, the quadrotor’s navigation solution depends only on the inertial navigation system solution. As a consequence, the navigation solution drifts in time due to errors and noises in the inertial sensor measurements. To handle such situations and bind the solution drift, the quadrotor dead reckoning (QDR) approach utilizes pedestrian dead reckoning principles. To that end, instead of flying the quadrotor in a straight line trajectory, it is flown in a periodic motion, in the vertical plane, to enable peak-to-peak (two local maximum points within the cycle) distance estimation. Although QDR manages to improve the pure inertial navigation solution, it has several shortcomings as it requires calibration before usage, provides only peak-to-peak distance, and does not provide the altitude of the quadrotor. To circumvent these issues, we propose QuadNet, a hybrid framework for quadrotor dead reckoning to estimate the quadrotor’s three-dimensional position vector at any user-defined time rate. As a hybrid approach, QuadNet uses both neural networks and model-based equations during its operation. QuadNet requires only the inertial sensor readings to provide the position vector. Experimental results with DJI’s Matrice 300 quadrotor are provided to show the benefits of using the proposed approach.

A simple tool for linking photo-identification with multimedia data to track mammal behaviour

Identifying individual animals is critical to describe demographic and behavioural patterns, and to investigate the ecological and evolutionary underpinnings of these patterns. The traditional non-invasive method of individual identification in mammals—comparison of photographed natural marks—has been improved by coupling other sampling methods, such as recording overhead video, audio and other multimedia data. However, aligning, linking and syncing these multimedia data streams are persistent challenges. Here, we provide computational tools to streamline the integration of multiple techniques to identify individual free-ranging mammals when tracking their behaviour in the wild. We developed an open-source R package for organizing multimedia data and for simplifying their processing a posteriori—“MAMMals: Managing Animal MultiMedia: Align, Link, Sync”. The package contains functions to (i) align and link the individual data from photographs to videos, audio recordings and other text data sources (e.g. GPS locations) from which metadata can be accessed; and (ii) synchronize and extract the useful multimedia (e.g. videos with audios) containing photo-identified individuals. To illustrate how these tools can facilitate linking photo-identification and video behavioural sampling in situ, we simultaneously collected photos and videos of bottlenose dolphins using off-the-shelf cameras and drones, then merged these data to track the foraging behaviour of individuals and groups. We hope our simple tools encourage future work that extend and generalize the links between multiple sampling platforms of free-ranging mammals, thereby improving the raw material needed for generating new insights in mammalian population and behavioural ecology.

Incorporating Geographical Scale and Multiple Environmental Factors to Delineate the Breeding Distribution of Sea Turtles

Temperature is often used to infer how climate influences wildlife distributions; yet, other parameters also contribute, separately and combined, with effects varying across geographical scales. Here, we used an unoccupied aircraft system to explore how environmental parameters affect the regional distribution of the terrestrial and marine breeding habitats of threatened loggerhead sea turtles (Caretta caretta). Surveys spanned four years and ~620 km coastline of western Greece, encompassing low (<10 nests/km) to high (100–500 nests/km) density nesting areas. We recorded 2395 tracks left by turtles on beaches and 1928 turtles occupying waters adjacent to these beaches. Variation in beach track and inwater turtle densities was explained by temperature, offshore prevailing wind, and physical marine and terrestrial factors combined. The highest beach-track densities (400 tracks/km) occurred on beaches with steep slopes and higher sand temperatures, sheltered from prevailing offshore winds. The highest inwater turtle densities (270 turtles/km) occurred over submerged sandbanks, with warmer sea temperatures associated with offshore wind. Most turtles (90%) occurred over nearshore submerged sandbanks within 10 km of beaches supporting the highest track densities, showing the strong linkage between optimal marine and terrestrial environments for breeding. Our findings demonstrate the utility of UASs in surveying marine megafauna and environmental data at large scales and the importance of integrating multiple factors in climate change models to predict species distributions.

Comparison of UAV and Boat Surveys for Detecting Changes in Breeding Population Dynamics of Sea Turtles

Surveying the breeding population of a given species can be difficult for many logistic reasons. Marine turtles are a challenging taxon for the study of reproductive ecology and breeding strategies, because turtles aggregate off-shore and males remain exclusively at sea. For successful management of sea turtle populations, determining operational sex ratios (OSRs) on a continuing basis is critical for determining long-term population viability, particularly in the context of changing hatchling sex ratios due to temperature-dependent sex determination in a warming climate. To understand how survey technique and stage of the breeding season might influence the ability to detect turtles and determine OSRs, we surveyed the presence and identified the sex of adult male and female green sea turtles (Chelonia mydas) using a boat and small commercial unoccupied/unmanned aerial vehicle (UAV), at the start (October) and peak (December) of a nesting season at an important breeding site at Heron Island, Great Barrier Reef, Australia. The ratio of males to females within the breeding ground detected by both survey methods changed from being male-biased in October to heavily female-biased in December, indicating that most males cease their reproductive effort and depart before the peak of the nesting season. Surveying with a UAV more than doubled the rate of turtles seen per minute of survey effort compared with surveying solely from the boat and allowed surveys to be conducted at times and/or places unsafe or inaccessible for boats. The sex of a slightly greater proportion of turtles seen could not be identified by observers using a UAV versus a boat, although more turtles were detected using the UAV. The departure of many males during the peak of the nesting season is likely due to an increasing biological cost of residency in the area because males encounter fewer receptive females as the season progresses and the limited foraging opportunity is insufficient to support the number of males present. Overall, we found that UAVs are an effective tool for studying important but difficult to observe aspects of sea turtle biology.

COVID-19 disruption reveals mass-tourism pressure on nearshore sea turtle distributions and access to optimal breeding habitat

Quantifying the extent to which animals detect and respond to human presence allows us to identify pressure (disturbance) and inform conservation management objectively; however, obtaining baselines against which to compare human impact is hindered in areas where human activities are already well established. For example, Zakynthos Island (Greece, Mediterranean) receives around 850,000 visitors each summer, while supporting an important loggerhead sea turtle rookery (~300 individuals/season). The coronavirus (COVID-19)-driven absence of tourism in May-June 2020 provided an opportunity to evaluate the distribution dynamics of this population in the absence (2020) vs. presence (2018 and 2019) of visitors using programmed unmanned aerial system (UAS) surveys. Ambient sea temperature transitioned from suboptimal for breeding in May to optimal in late June, with turtle distribution appearing to shift from shallow (to benefit from waters 3-5°C above ambient) to deeper waters in 2018 and 2019, but not 2020. The 2020 data set demonstrated that increased tourism pressure, not temperature, drives turtles offshore. Specifically, >50% of turtles remained within 100 m of shore at densities of 25-50 visitors/km, even when sea temperature rose, with 2018 and 2019 data supporting this trend. Reduced access to warmer, nearshore waters by tourism could delay the onset of nesting and increase the length of the egg maturation period between nesting events (internesting interval) at this site. A coastal refuge zone could be delimited in May-June where touristic infrastructure is minimal, but also where turtles frequently aggregate. In conclusion, sea turtles appear capable of perceiving changes in the level of human pressure at fine spatial and temporal scales and adjusting their distribution accordingly.

Behavioural and physiological responses of captive Antillean manatees to small aerial drones

Abstract Context Unmanned aerial vehicles or drones are powerful tools for wildlife research. Identifying the impacts of these systems on target species during operations is essential to reduce risks of disturbance to wildlife, to minimise bias in behavioural data, and to establish better practices for their use. Aims We evaluated the responses of captive Antillean manatees to the overhead flight of a small aerial drone. Methods We used aerial and ground videos to compare manatee activity budgets and respiration rates in three 15-min sampling periods: ‘before’, ‘during’ and ‘after’ flights with a DJI Phantom 3 Advanced. The drone was hovered stationary for 3 min at five altitudes (100 m, 40 m, 20 m, 10 m, 5 m) to determine whether manatees display behavioural responses compared with the control period, and whether they respond more at lower altitudes. Only one flight was performed per manatee group to avoid bias owing to habituation to the drone. Key results Manatees responded to drone flights by (1) increasing their activity levels during and after flights, therefore signalling after effects; (2) decreasing their respiration rate during flights; and (3) displaying behavioural reactions including grouping, tail-kicking, fleeing from their original position and moving under submerged structures. From the 11 individuals displaying behavioral reactions, 9 reacted in the first ~2 min of flight, preventing assessments of altitude effects and suggesting manatees responded to the drone sound at take-off. Conclusions Behavioural changes of responding manatees were similar to previous reports of disturbance responses to boats and drones in this species. Our use of a control period showed shifts in respiration rates and activity budgets that persisted after flights. Several manatees reacted to the drone from the time of take-off and first minutes of flight, indicating that the sound of the electric rotors could be a strong negative stimulus to manatee and highlighting the importance of establishing safe distances for take-off. Implications Future studies should consider that drones could elicit conspicuous and inconspicuous responses in manatees. Our results emphasise the need for control data on animal behaviour to better assess the impact of drones on wildlife and to design non-invasive protocols.

Using Drones to Measure Jellyfish Density in Shallow Estuaries

Understanding jellyfish ecology and roles in coastal ecosystems is challenging due to their patchy distribution. While standard net sampling or manned aircraft surveys are inefficient, Unmanned Aerial Vehicles (UAVs) or drones represent a promising alternative for data collection. In this technical report, we used pictures taken from a small drone to estimate the density of Aurelia sp. in a shallow fjord with a narrow entrance, where the population dynamic is well-known. We investigated the ability of an image processing software to count small and translucent jellyfish from the drone pictures at three locations with different environmental conditions (sun glare, waves or seagrass). Densities of Aurelia sp. estimated from semiautomated and manual counts from drone images were similar to densities estimated by netting. The semiautomated program was able to highlight the medusae from the background in order to discard false detections of items unlikely to be jellyfish. In spite of this, some objects (e.g., seagrass) were hardly distinguishable from jellyfish and resulted in a small number of false positives. This report presents a preview of the possible applications of drones to observe small and fragile jellyfishes, for which in situ sampling remains delicate. Drones may represent a noninvasive approach to monitoring jellyfish abundance over time, enabling the collection of a large amount of data in a short time. Software development may be useful for automatically measuring jellyfish size and even population biomass.

Accuracy and precision of citizen scientist animal counts from drone imagery

Repeated counts of animal abundance can reveal changes in local ecosystem health and inform conservation strategies. Unmanned aircraft systems (UAS), also known as drones, are commonly used to photograph animals in remote locations; however, counting animals in images is a laborious task. Crowd-sourcing can reduce the time required to conduct these censuses considerably, but must first be validated against expert counts to measure sources of error. Our objectives were to assess the accuracy and precision of citizen science counts and make recommendations for future citizen science projects. We uploaded drone imagery from Año Nuevo Island (California, USA) to a curated Zooniverse website that instructed citizen scientists to count seals and sea lions. Across 212 days, over 1,500 volunteers counted animals in 90,000 photographs. We quantified the error associated with several descriptive statistics to extract a single citizen science count per photograph from the 15 repeat counts and then compared the resulting citizen science counts to expert counts. Although proportional error was relatively low (9% for sea lions and 5% for seals during the breeding seasons) and improved with repeat sampling, the 12+ volunteers required to reduce error was prohibitively slow, taking on average 6 weeks to estimate animals from a single drone flight covering 25 acres, despite strong public outreach efforts. The single best algorithm was ‘Median without the lowest two values’, demonstrating that citizen scientists tended to under-estimate the number of animals present. Citizen scientists accurately counted adult seals, but accuracy was lower when sea lions were present during the summer and could be confused for seals. We underscore the importance of validation efforts and careful project design for researchers hoping to combine citizen science with imagery from drones, occupied aircraft, and/or remote cameras.

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.

The Drone Revolution of Shark Science: A Review

Over the past decade, drones have become a popular tool for wildlife management and research. Drones have shown significant value for animals that were often difficult or dangerous to study using traditional survey methods. In the past five years drone technology has become commonplace for shark research with their use above, and more recently, below the water helping to minimise knowledge gaps about these cryptic species. Drones have enhanced our understanding of shark behaviour and are critically important tools, not only due to the importance and conservation of the animals in the ecosystem, but to also help minimise dangerous encounters with humans. To provide some guidance for their future use in relation to sharks, this review provides an overview of how drones are currently used with critical context for shark monitoring. We show how drones have been used to fill knowledge gaps around fundamental shark behaviours or movements, social interactions, and predation across multiple species and scenarios. We further detail the advancement in technology across sensors, automation, and artificial intelligence that are improving our abilities in data collection and analysis and opening opportunities for shark-related beach safety. An investigation of the shark-based research potential for underwater drones (ROV/AUV) is also provided. Finally, this review provides baseline observations that have been pioneered for shark research and recommendations for how drones might be used to enhance our knowledge in the future.

Volitional Swimming Kinematics of Blacktip Sharks, Carcharhinus limbatus, in the Wild

Recent work showed that two species of hammerhead sharks operated as a double oscillating system, where frequency and amplitude differed in the anterior and posterior parts of the body. We hypothesized that a double oscillating system would be present in a large, volitionally swimming, conventionally shaped carcharhinid shark. Swimming kinematics analyses provide quantification to mechanistically examine swimming within and among species. Here, we quantify blacktip shark (Carcharhinus limbatus) volitional swimming kinematics under natural conditions to assess variation between anterior and posterior body regions and demonstrate the presence of a double oscillating system. We captured footage of 80 individual blacktips swimming in the wild using a DJI Phantom 4 Pro aerial drone. The widespread accessibility of aerial drone technology has allowed for greater observation of wild marine megafauna. We used Loggerpro motion tracking software to track five anatomical landmarks frame by frame to calculate tailbeat frequency, tailbeat amplitude, speed, and anterior/posterior variables: amplitude and frequency of the head and tail, and the body curvature measured as anterior and posterior flexion. We found significant increases in tailbeat frequency and amplitude with increasing swimming speed. Tailbeat frequency decreased and tailbeat amplitude increased as posterior flexion amplitude increased. We found significant differences between anterior and posterior amplitudes and frequencies, suggesting a double oscillating modality of wave propagation. These data support previous work that hypothesized the importance of a double oscillating system for increased sensory perception. These methods demonstrate the utility of quantifying swimming kinematics of wild animals through direct observation, with the potential to apply a biomechanical perspective to movement ecology paradigms.

Autonomous Deployment of Underwater Acoustic Monitoring Devices Using an Unmanned Aerial Vehicle: The Flying Hydrophone

Unmanned aerial vehicles (UAV) are increasingly becoming a popular tool in the observation and study of marine mammals. However, the potential capabilities of these vehicles regarding autonomous operations are not being fully exploited for passive underwater acoustic monitoring in marine mammal research. This article presents results from the development of a UAV system equipped with an underwater acoustic recorder aimed at assisting with the monitoring of harbour porpoises in Special Areas of Conservation in the United Kingdom. The UAV is capable of autonomous navigation, persistent landing, take-off and automatic data acquisition at specified waypoints. The system architecture that enables autonomous UAV flight including waypoint planning and control is described. A bespoke lightweight underwater acoustic recorder (named the PorpDAQ) capable of transmitting the results of fast Fourier transforms (FFT) applied to incoming signals from a hydrophone was also designed. The system's operation is successfully validated with a combination of outdoor experiments and indoor simulations demonstrating different UAVs capable of autonomously navigating and landing at specific waypoints while recording data in an indoor tank. Results from the recorder suggest that lightweight, relatively low-cost systems can be used in place of heavier more expensive alternatives.