Seabird species vary in behavioural response to drone census

An interspecific foraging association with polar bears increases foraging opportunities for avian predators in a declining Arctic seabird colony

Interspecific foraging associations (IFAs) are biological interactions where two or more species forage in association with each other. Climate-induced reductions in Arctic sea ice have increased polar bear (Ursus maritimus) foraging in seabird colonies, which creates foraging opportunities for avian predators. We used drone video of bears foraging within a common eider (Somateria mollissima) colony on East Bay Island (Nunavut, Canada) in 2017 to investigate herring gull (Larus argentatus) foraging in association with bears. We recorded nest visitation by gulls following n = 193 eider flushing events from nests during incubation. The probability of gulls visiting eider nests increased with higher number of gulls present (β = 0.14 ± 0.03 [SE], p < .001) and for nests previously visited by a bear (β = 1.14 ± 0.49 [SE], p < .02). In our model examining the probability of gulls consuming eggs from nests, we failed to detect statistically significant effects for the number of gulls present (β = 0.09 ± 0.05 [SE], p < .07) or for nests previously visited by a bear (β = -0.92 ± 0.71 [SE], p < .19). Gulls preferred to visit nests behind bears (χ2 = 18, df = 1, p < .0001), indicating gulls are risk averse in the presence of polar bears. Our study provides novel insights on an Arctic IFA, and we present evidence that gulls capitalize on nests made available due to disturbance associated with foraging bears, as eiders disturbed off their nest allow gulls easier access to eggs. We suggest the IFA between gulls and polar bears is parasitic, as gulls are consuming terrestrial resources which would have eventually been consumed by bears. This finding has implications for estimating the energetic contribution of bird eggs to polar bear summer diets in that the total number of available clutches to consume may be reduced due to avian predators.

Airborne imagery does not preclude detectability issues in estimating bird colony size

Aerial images obtained by drones are increasingly used for ecological research such as wildlife monitoring. Yet detectability issues resulting from animal activity or visibility are rarely considered, although these may lead to biased population size and trend estimates. In this study, we investigated detectability in a census of Malagasy pond heron Ardeola idae colonies on the island of Mayotte. We conducted repeated drone flights over breeding colonies in mangrove habitats during two breeding seasons. We then identified individuals and nests in the images and fitted closed capture-recapture models on nest-detection histories. We observed seasonal variation in the relative abundance of individuals, and intra-daily variation in the relative abundance of individuals-especially immature birds-affecting the availability of nests for detection. The detection probability of nests estimated by capture-recapture varied between 0.58 and 0.74 depending on flyover days and decreased 25% from early to late morning. A simulation showed that three flyovers are necessary to detect a 5-6% decline in colonies of 50 to 200 nests. These results indicate that the detectability of nests of forest-canopy breeding species from airborne imagery can vary over space and time; we recommend the use of capture-recapture methods to control for this bias.

Drone Observation for the Quantitative Study of Complex Multilevel Societies

Unmanned aerial vehicles (drones) have recently been used in various behavioral ecology studies. However, their application has been limited to single groups, and most studies have not implemented individual identification. A multilevel society refers to a social structure in which small stable "core units" gather and make a larger, multiple-unit group. Here, we introduce recent applications of drone technology and individual identification to complex social structures involving multiple groups, such as multilevel societies. Drones made it possible to obtain the identification, accurate positioning, or movement of more than a hundred individuals in a multilevel social group. In addition, in multilevel social groups, drones facilitate the observation of heterogeneous spatial positioning patterns and mechanisms of behavioral propagation, which are different from those in a single-level group. Such findings may contribute to the quantitative definition and assessment of multilevel societies and enhance our understanding of mechanisms of multiple group aggregation. The application of drones to various species may resolve various questions related to multilevel societies.

Using drone imagery to obtain population data of colony-nesting seabirds to support Canada’s transition to the global Key Biodiversity Areas program

Identifying of global or national biodiversity ‘hotspots’ has proven important for focusing and prioritizing conservation efforts worldwide. Canada has nearly 600 Important Bird and Biodiversity Areas (IBAs) identified by quantitative criteria to help guide avian conservation and management. Marine IBAs capture critical waterbird habitats such as nesting colonies, foraging sites, and staging areas. However, due to their remote locations, many lack recent population counts. Canada has begun transitioning IBAs into the global Key Biodiversity Areas (KBA) program; KBAs identify areas that are important for the persistence of biodiversity and encompass a wider scope of unique, rare, or vulnerable taxa. Assessing whether IBAs qualify as KBAs requires current data – as will future efforts to manage these biologically important sites. We conducted a pilot study in the Chain Islets and Great Chain Island IBA, in British Columbia, to assess the effectiveness of using drones to census surface-nesting seabirds in an IBA context. This IBA was originally designated for supporting a globally significant breeding colony of Glaucous-winged Gulls (Larus glaucescens). Total nest counts derived from orthomosaic imagery (1012 nesting pairs) show that this site now falls below the Global and National IBA designation criterion threshold, a finding consistent with regional declines in the species. Our trial successfully demonstrates a flexible and low cost approach to obtaining population data at an ecologically sensitive KBA site. We explore how drones will be a useful tool to assess and monitor species and habitats within remote, data-deficient IBAs, particularly during the transition to KBAs.

Using computer vision, image analysis and UAVs for the automatic recognition and counting of common cranes (Grus grus)

Long-term monitoring of wildlife numbers traditionally uses observers, which are frequently inefficient and inaccurate due to their variable experience/training, are costly and difficult to sustain over time. Furthermore, there are other inhibiting factors for wildlife counting, such as: inhabiting inaccessible areas, fear of humans, and nocturnal behavior. There is a need to develop new technologies that will automatically identify and count wild animals in order to determine the appropriate management protocol. In this study, an advanced and accurate method for automatically calculating the number of cranes (Grus grus), using thermal cameras at night and visible light (RGB) cameras during the day onboard unmanned aerial vehicles (UAVs), based on image analysis and computer vision, was developed. The cranes congregate at night in a large communal roost, making it possible to count the birds while they are relatively static and all together. Each bird was counted individually by creating a standardized tool to determine population numbers for management, using image analysis and automatic processing. A dedicated algorithm was developed that aimed to identify the cranes based on their spectral characteristics (typical temperature, shape, size) and to effectively separate the cranes from the typical background. The automatic segmentation and counting of roosting common cranes using UAV nighttime thermal images had an Overall Accuracy (OA) of 91.47%, User's Accuracy (UA) of 99.68%, and Producer's Accuracy (PA) of 91.74%. The computer vision and machine learning algorithm based on the YOLO v3 platform of daytime RGB UAV images of common cranes at the feeding station yielded an overall loss accuracy level of 2.25%, with a mean square error of 1.87, OA of 94.51%, UA of 99.91%, PA of 94.59%. These results are highly encouraging, and although the algorithms were developed for the purpose of counting cranes, they could be adapted for other counting purposes for wildlife management.

A colonial-nesting seabird shows no heart-rate response to drone-based population surveys

Aerial drones are increasingly being used as tools for ecological research and wildlife monitoring in hard-to-access study systems, such as in studies of colonial-nesting birds. Despite their many advantages over traditional survey methods, there remains concerns about possible disturbance effects that standard drone survey protocols may have on bird colonies. There is a particular gap in the study of their influence on physiological measures of stress. We measured heart rates of incubating female common eider ducks (Somateria mollissima) to determine whether our drone-based population survey affected them. To do so, we used heart-rate recorders placed in nests to quantify their heart rate in response to a quadcopter drone flying transects 30 m above the nesting colony. Eider heart rate did not change from baseline (measured in the absence of drone survey flights) by a drone flying at a fixed altitude and varying horizontal distances from the bird. Our findings suggest that carefully planned drone-based surveys of focal species have the potential to be carried out without causing physiological impacts among colonial-nesting eiders.

Monitoring Colonies of Large Gulls Using UAVs: From Individuals to Breeding Pairs

Measuring success or failure in the conservation of seabirds depends on reliable long-term monitoring. Traditionally, this monitoring has been based on line transects and total or point counts, all of which are sensitive to subjective interpretation. Such methods have proven to consistently record fewer individuals than intensive efforts, while requiring many hours of fieldwork and resulting in high disturbance. New technologies, such as drones, are potentially useful monitoring tools, as they can cover large areas in a short time, while providing high-resolution data about bird numbers and status. This study conducted two types of Uncrewed Aerial Vehicle (UAV) surveys in a big colony of multispecies breeding gulls. From a 25 m height, we photographed 30 circle plots where nests were also counted on the ground, showing that the number of occupied nests/breeding pairs could be estimated accurately by multiplying the number of counted individuals with a 0.7 conversion factor. A fixed-wing UAV was used to photograph the entire island to compare drone counts with counts conducted by traditional methods, were we counted a higher number of breeding pairs than the traditional count (1.7-2.2 times more individuals). It was concluded that UAVs provided improved estimates of colony size with much reduced monitoring effort.

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.

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.

Behavioral responses of blue-winged teal and northern shoveler to unmanned aerial vehicle surveys

Unmanned aerial vehicles (UAVs) have become a popular wildlife survey tool. Most research has focused on detecting wildlife using UAVs with less known about behavioral responses. We compared the behavioral responses of breeding blue-winged teal (Spatula discors) (n = 151) and northern shovelers (Spatula clypeata) (n = 46) on wetlands flown over with a rotary DJI Matrice 200 quadcopter and control wetlands without flights. Using a GoPro camera affixed to a spotting scope, we conducted focal individual surveys and recorded duck behaviors for 30 minutes before, during, and 30 minutes after UAV flights to determine if ducks flushed or changed in specific activities. We also conducted scan surveys during flights to examine flushing and movement on the entire wetland. Between 24 April and 27 May 2020, we conducted 42 paired (control and flown) surveys. Both teal and shovelers increased proportion of time engaged in overhead vigilance on flown wetlands from pre-flight to during flight (0.008 to 0.020 and 0.006 to 0.032 of observation time, respectively). Both species left the wetland more frequently during flights than ducks on control wetlands. Despite similarities between species, we observed marked differences in time each species spent on active (e.g., feeding, courtship, swimming), resting, and vigilant behaviors during flights. Overall, teal became less active during flights (0.897 to 0.834 of time) while shovelers became more active during this period (0.724 to 0.906 of time). Based upon scan surveys, ducks flushed in 38.1% of surveys while control wetlands only had a single (2.4%) flush during the flight time. We found launch distance was the most important predictor of whether ducks swam for cover or away from the UAV which could result in inaccurate counts. Ducks appear aware of UAVs during flights, but minimal behavioral shifts suggest negative fitness consequences are unlikely.

Drones, automatic counting tools, and artificial neural networks in wildlife population censusing

The use of a drone to count the flock sizes of 33 species of waterbirds during the breeding and non-breeding periods was investigated.In 96% of 343 cases, drone counting was successful. 18.8% of non-breeding birds and 3.6% of breeding birds exhibited adverse reactions: the former birds were flushed, whereas the latter attempted to attack the drone.The automatic counting of birds was best done with ImageJ/Fiji microbiology software - the average counting rate was 100 birds in 64 s.Machine learning using neural network algorithms proved to be an effective and quick way of counting birds - 100 birds in 7 s. However, the preparation of images and machine learning time is time-consuming, so this method is recommended only for large data sets and large bird assemblages.The responsible study of wildlife using a drone should only be carried out by persons experienced in the biology and behavior of the target animals.

Sociability strongly affects the behavioural responses of wild guanacos to drones

Drones are being increasingly used in research and recreation but without an adequate assessment of their potential impacts on wildlife. Particularly, the effect of sociability on behavioural responses to drone-associated disturbance remains largely unknown. Using an ungulate with complex social behaviour, we (1) assessed how social aggregation and offspring presence, along with flight plan characteristics, influence the probability of behavioural reaction and the flight distance of wild guanacos (Lama guanicoe) to the drone's approach, and (2) estimated reaction thresholds and flight heights that minimise disturbance. Sociability significantly affected behavioural responses. Large groups showed higher reaction probability and greater flight distances than smaller groups and solitary individuals, regardless of the presence of offspring. This suggests greater detection abilities in large groups, but we cannot rule out the influence of other features inherent to each social unit (e.g., territoriality) that might be working simultaneously. Low flight heights increased the probability of reaction, although the effect of drone speed was less clear. Reaction thresholds ranged from 154 m (solitary individuals) to 344 m (mixed groups), revealing that the responsiveness of this guanaco population to the drone is the most dramatic reported so far for a wild species.

Applications of Uncrewed Aerial Vehicles (UAV) Technology to Support Integrated Coastal Zone Management and the UN Sustainable Development Goals at the Coast

Data and information obtained from low-cost uncrewed aerial vehicles (UAVs), commonly referred to as 'drones', can be used to support integrated coastal zone management (ICZM) and sustainable development at the coast. Several recent studies in various disciplines, including ecology, engineering, and several branches of physical and human geography, describe the applications of UAV technology with practical coastal management potential, yet the extent to which such data can contribute to these activities remains underexplored. The main objective of this paper is to collate this knowledge to highlight the areas in which UAV technology can contribute to ICZM and can influence the achievement of the UN Sustainable Development Goals (SDGs) at the coast. We focus on applications with practical potential for coastal management activities and assess their accessibility in terms of cost, ease of use, and maturity. We identified ten (out of the 17) SDGs to which UAVs can contribute data and information. Examples of applications include surveillance of illegal fishing and aquaculture activities, seaweed resource assessments, cost-estimation of post-storm damages, and documentation of natural and cultural heritage sites under threat from, for example, erosion and sea-level rise. An awareness of how UAVs can contribute to ICZM, as well as the limitations of the technology, can help coastal practitioners to evaluate their options for future management activities.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12237-021-01001-5.

Evaluation of the use of drones to monitor a diverse crocodylian assemblage in West Africa

Context West African crocodylian populations are declining and in need of conservation action. Surveys and other monitoring methods are critical components of crocodile conservation programs; however, surveys are often hindered by logistical, financial and detectability constraints. Increasingly used in wildlife monitoring programs, drones can enhance monitoring and conservation efficacy. Aims This study aimed to determine a standard drone crocodylian survey protocol and evaluate the drones as a tool to survey the diverse crocodylian assemblage of West Africa. Methods We surveyed crocodile populations in Benin, Côte d’Ivoire, and Niger in 2017 and 2018, by using the DJI Phantom 4 Pro drone and via traditional diurnal and nocturnal spotlight surveys. We used a series of test flights to first evaluate the impact of drones on crocodylian behaviour and determine standard flight parameters that optimise detectability. We then, consecutively, implemented the three survey methods at 23 sites to compare the efficacy of drones against traditional crocodylian survey methods. Key results Crocodylus suchus can be closely approached (>10 m altitude) and consumer-grade drones do not elicit flight responses in West African large mammals and birds at altitudes of >40–60 m. Altitude and other flight parameters did not affect detectability, because high-resolution photos allowed accurate counting. Observer experience, field conditions (e.g. wind, sun reflection), and site characteristics (e.g. vegetation, homogeneity) all significantly affected detectability. Drone-based crocodylian surveys should be implemented from 40 m altitude in the first third of the day. Comparing survey methods, drones performed better than did traditional diurnal surveys but worse than standard nocturnal spotlight counts. The latter not only detected more individuals, but also a greater size-class diversity. However, drone surveys provide advantages over traditional methods, including precise size estimation, less disturbance, and the ability to cover greater and more remote areas. Drone survey photos allow for repeatable and quantifiable habitat assessments, detection of encroachment and other illegal activities, and leave a permanent record. Conclusions Overall, drones offer a valuable and cost-effective alternative for surveying crocodylian populations with compelling secondary benefits, although they may not be suitable in all cases and for all species. Implications We propose a standardised and optimised protocol for drone-based crocodylian surveys that could be used for sustainable conservation programs of crocodylians in West Africa and globally.

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.

Fewer bat passes are detected during small, commercial drone flights

Advances in technological capabilities, operational simplicity and cost efficiency have promoted the rapid integration of unmanned aerial vehicles (UAVs) into ecological research, providing access to study taxa that are otherwise difficult to survey, such as bats. Many bat species are currently at risk, but accurately surveying populations is challenging for species that do not roost in large aggregations. Acoustic recorders attached to UAVs provide an opportunity to survey bats in challenging habitats. However, UAVs may alter bat behaviour, leading to avoidance of the UAV, reduced detection rates and inaccurate surveys. We evaluated the number of bat passes detected with and without the presence of a small, commercial UAV in open habitats. Only 22% of bat passes were recorded in the presence of the UAV (0.23 ± 0.09 passes/min) compared to control periods without the UAV (1.03 ± 0.17 passes/min), but the effect was smaller on the big brown bat/silver-haired bat (Eptesicus fuscus/Lasionycteris noctivagans) acoustic complex. Noise interference from the UAV also reduced on-board bat detection rates. We conclude that acoustic records attached to UAVs may inaccurately survey bat populations due to low and variable detection rates by such recorders.

Eave and swarm collections prove effective for biased captures of male Anopheles gambiae mosquitoes in Uganda

BACKGROUND

Traditional malaria vector sampling techniques bias collections towards female mosquitoes. Comprehensive understanding of vector dynamics requires balanced vector sampling of both males and females. Male mosquito sampling is also necessary for population size estimations by male-based mark-release-recapture (MRR) studies and for developing innovations in mosquito control, such as the male-targeted sterile insect technique and other genetic modification approaches. This study evaluated a range of collection methods which show promise in providing a more equal, or even male-biased, sex representation in the sample.

RESULTS

Swarms were found at all study sites and were more abundant and larger at the peak of the wet season. Swarm sampling caught the most males, but when man/hour effort was factored in, sampling of eaves by aspiration was the more efficient method and also provided a representative sample of females. Grass-roofed houses were the most productive for eave collections. Overall few mosquitoes were caught with artificial resting traps (clay pots and buckets), although these sampling methods performed better at the start of the wet season than at its peak, possibly because of changes in mosquito ecology and an increased availability of natural resting sites later in the season. Aspiration of bushes was more productive at the peak of the wet season than at the start.

CONCLUSIONS

The results of this study demonstrate that eave aspiration was an efficient and useful male mosquito collection method at the study sites and a potentially powerful aid for swarm location and MRR studies. The methods evaluated may together deliver more sex-balanced mosquito captures and can be used in various combinations depending on the aims and ecological parameters of a given study.

Un-crewed aerial vehicle population survey of three sympatrically breeding seabird species at Signy Island, South Orkney Islands

Surveying seabirds in polar latitudes can be challenging due to sparse human populations, lack of infrastructure and the risk of disturbance to wildlife or damage to habitats. Counting populations using un-crewed aerial vehicles (UAVs) is a promising approach to overcoming these difficulties. However, a careful validation of the approach is needed to ensure comparability with counts collected using conventional methods. Here, we report on surveys of three Antarctic bird species breeding on Signy Island, South Orkney Islands; Chinstrap (Pygoscelis antarctica) and Gentoo (Pygoscelis papua) Penguins, and the South Georgia Shag (Leucocarbo atriceps georgianus). We show that images from low-altitude UAV surveys have sufficient resolution to allow separation of Chinstrap Penguins from contiguously breeding Adélie Penguins (Pygoscelis adéliae), which are very similar in appearance when viewed from overhead. We compare data from ground counts with manual counts of nesting birds on images collected simultaneously by low-altitude aerial photography from multi-rotor UAVs at the same colonies. Results at this long-term monitoring site confirmed a continued population decline for Chinstrap Penguins and increasing Gentoo Penguin population. Although both methods provided breeding pair counts that were generally within ~ 5%, there were significant differences at some locations. We examine these differences in order to highlight potential biases or methodological constraints that should be considered when analysing similar aerial census surveys and comparing them with ground counts.

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.

Remotely Piloted Aircraft System (RPAS)-Based Wildlife Detection: A Review and Case Studies in Maritime Antarctica

Simple Summary

Remotely piloted aircraft systems (RPAS) have been successfully applied in wildlife monitoring with imaging sensors to improve or to supplement conventional field observations. To effectively utilize this technique, we reviewed previous studies related to wildlife detection with RPAS. First, this study provides an overview of the applications of RPAS for wild animal studies from the perspective of individual detection and population surveys as well as behavioral studies. In terms of the RPAS payload, applying thermal-imaging sensors was determined to be advantageous in detecting homeothermic animals due to the thermal contrast with background habitat using case studies detecting southern elephant seal (Mirounga leonina) using RGB and thermal imaging sensors in King George Island, maritime Antarctica.

Abstract

In wildlife biology, it is important to conduct efficient observations and quantitative monitoring of wild animals. Conventional wildlife monitoring mainly relies on direct field observations by the naked eyes or through binoculars, on-site image acquisition at fixed spots, and sampling or capturing under severe areal constraints. Recently, remotely piloted aircraft systems (RPAS), also called drones or unmanned aerial vehicles (UAV), were successfully applied to detect wildlife with imaging sensors, such as RGB and thermal-imaging sensors, with superior detection capabilities to those of human observation. Here, we review studies with RPAS which has been increasingly used in wildlife detection and explain how an RPAS-based high-resolution RGB image can be applied to wild animal studies from the perspective of individual detection and population surveys as well as behavioral studies. The applicability of thermal-imaging sensors was also assessed with further information extractable from image analyses. In addition, RPAS-based case studies of acquisition of high-resolution RGB images for the purpose of detecting southern elephant seals (Mirounga leonina) and shape property extraction using thermal-imaging sensor in King George Island, maritime Antarctica is presented as applications in an extreme environment. The case studies suggest that currently available cost-effective small-sized RPAS, which are capable of flexible operation and mounting miniaturized imaging sensors, and are easily maneuverable even from an inflatable boat, can be an effective and supportive technique for both the visual interpretation and quantitative analysis of wild animals in low-accessible extreme or maritime environments.

Operational Protocols for the Use of Drones in Marine Animal Research

The use of drones to study marine animals shows promise for the examination of numerous aspects of their ecology, behaviour, health and movement patterns. However, the responses of some marine phyla to the presence of drones varies broadly, as do the general operational protocols used to study them. Inconsistent methodological approaches could lead to difficulties comparing studies and can call into question the repeatability of research. This review draws on current literature and researchers with a wealth of practical experience to outline the idiosyncrasies of studying various marine taxa with drones. We also outline current best practice for drone operation in marine environments based on the literature and our practical experience in the field. The protocols outlined herein will be of use to researchers interested in incorporating drones as a tool into their research on marine animals and will help form consistent approaches for drone-based studies in the future.

Measuring disturbance at swift breeding colonies due to the visual aspects of a drone: a quasi-experiment study

There is a growing body of research indicating that drones can disturb animals. However, it is usually unclear whether the disturbance is due to visual or auditory cues. Here, we examined the effect of drone flights on the behavior of great dusky swifts Cypseloides senex and white-collared swifts Streptoprocne zonaris in 2 breeding sites where drone noise was obscured by environmental noise from waterfalls and any disturbance must be largely visual. We performed 12 experimental flights with a multirotor drone at different vertical, horizontal, and diagonal distances from the colonies. From all flights, 17% caused <1% of birds to temporarily abandon the breeding site, 50% caused half to abandon, and 33% caused more than half to abandon. We found that the diagonal distance explained 98.9% of the variability of the disturbance percentage and while at distances >50 m the disturbance percentage does not exceed 20%, at <40 m the disturbance percentage increase to > 60%. We recommend that flights with a multirotor drone during the breeding period should be conducted at a distance of >50 m and that recreational flights should be discouraged or conducted at larger distances (e.g. 100 m) in nesting birds areas such as waterfalls, canyons, and caves.

Thermal Imaging of Beach-Nesting Bird Habitat with Unmanned Aerial Vehicles: Considerations for Reducing Disturbance and Enhanced Image Accuracy

Knowledge of temperature variation within and across beach-nesting bird habitat, and how such variation may affect the nesting success and survival of these species, is currently lacking. This type of data is furthermore needed to refine predictions of population changes due to climate change, identify important breeding habitat, and guide habitat restoration efforts. Thermal imagery collected with unmanned aerial vehicles (UAVs) provides a potential approach to fill current knowledge gaps and accomplish these goals. Our research outlines a novel methodology for collecting and implementing active thermal ground control points (GCPs) and assess the accuracy of the resulting imagery using an off-the-shelf commercial fixed-wing UAV that allows for the reconstruction of thermal landscapes at high spatial, temporal, and radiometric resolutions. Additionally, we observed and documented the behavioral responses of beach-nesting birds to UAV flights and modifications made to flight plans or the physical appearance of the UAV to minimize disturbance. We found strong evidence that flying on cloudless days and using sky-blue camouflage greatly reduced disturbance to nesting birds. The incorporation of the novel active thermal GCPs into the processing workflow increased image spatial accuracy an average of 12 m horizontally (mean root mean square error of checkpoints in imagery with and without GCPs was 0.59 m and 23.75 m, respectively). The final thermal indices generated had a ground sampling distance of 25.10 cm and a thermal accuracy of less than 1 °C. This practical approach to collecting highly accurate thermal data for beach-nesting bird habitat while avoiding disturbance is a crucial step towards the continued monitoring and modeling of beach-nesting birds and their habitat.

Drone Surveys Do Not Increase Colony-wide Flight Behaviour at Waterbird Nesting Sites, But Sensitivity Varies Among Species

The popularity of using unmanned aerial vehicles (UAVs) to survey colonial waterbirds has increased in the past decade, but disturbance associated with this bourgeoning technology requires further study. Disturbance was investigated by conducting aerial surveys with a consumer-grade quadcopter (DJI Phantom 3), while concurrently recording behavioural reactions on video. Surveys of mixed-species waterbird colonies (1-6 species per colony) were flown in horizontal transects at heights of 122, 91, 61, and 46 m, which is a typical range for collecting aerial imagery and producing high-resolution mosaicked orthophotos of nesting bird sites. An upper limit of 122 m was used due to local regulations prohibiting higher-altitude flights without federal authorization. Behavioural reactions were tallied every minute and a disturbance score was calculated for each sampling period. When compared to control periods, we found no evidence that colony-wide escape (i.e., flight) behaviour increased during drone flights, at any altitude flown. However, disturbance score increased significantly by 53% for surveys at 46 m. Some species were more sensitive to surveys than others. Laughing Gulls, in particular, exhibited a significant (125%) increase in escape behaviour for surveys at 91 m. Our results indicate when used in a capacity to gather high-resolution imagery for estimating breeding pairs, UAV surveys affected some species more than others, but severe reactions did not appear to increase for mixed-species colonies as a whole. Further study on safe operating thresholds is essential, especially at local and regional scales.

Who's better at spotting? A comparison between aerial photography and observer-based methods to monitor floating marine litter and marine mega-fauna

Pollution by marine litter is raising major concerns due to its potential impact on marine biodiversity and, above all, on endangered mega-fauna species, such as cetaceans and sea turtles. The density and distribution of marine litter and mega-fauna have been traditionally monitored through observer-based methods, yet the advent of new technologies has introduced aerial photography as an alternative monitoring method. However, to integrate results produced by different monitoring techniques and consider the photographic method a viable alternative, this 'new' methodology must be validated. This study aims to compare observations obtained from the concurrent application of observer-based and photographic methods during aerial surveys. To do so, a Partenavia P-68 aircraft equipped with an RGB sensor was used to monitor the waters off the Spanish Mediterranean coast along 12 transects (941 km). Over 10000 images were collected and checked manually by a photo-interpreter to detect potential targets, which were classified as floating marine macro-litter, mega-fauna and seabirds. The two methods allowed the detection of items from the three categories and proved equally effective for the detection of cetaceans, sea turtles and large fish on the sea surface. However, the photographic method was more effective for floating litter detection and the observer-based method was more effective for seabird detection. These results provide the first validation of the use of aerial photography to monitor floating litter and mega-fauna over the marine surface.

Response of colonial Peruvian guano birds to flying UAVs: effects and feasibility for implementing new population monitoring methods

Background

Drones are reliable tools for estimating colonial seabird numbers. Although most research has focused on methods of improving the accuracy of bird counts, few studies have evaluated the impacts of these methods on bird behavior. In this study, we examined the effects of the DJI Phantom 3 drone approach (altitude, horizontal and vertical descent speeds) on changes in the intensity of behavioral response of guano birds: guanay cormorants (Phalacrocorax bougainvilli), Peruvian boobies (Sula variegata) and Peruvian pelicans (Pelecanus thagus). The breeding and non-breeding condition was also evaluated.

Methods

Eleven locations along the Peruvian coast were visited in 2016–2017. Drone flight tests considered an altitude range from 5 to 80 m from the colony level, a horizontal speed range from 0.5 to 15 m/s, and a vertical descent speed range from 0.5 to 3 m/s. The intensity of the behavioral response of birds was scored and categorized as: 0-no reacting, 1-head pointing to the drone (HP), 2-wing flapping (WF), 3-walking/running (WR) and 4-taking-off/flying (TK). Drone noise at specific altitudes was recorded with a sound meter close to the colony to discriminate visual from auditory effects of the drone.

Results

In 74% of all test flights (N = 507), guano birds did not react to the presence of the drone, whereas in the remaining flights, birds showed a sign of discomfort: HP (47.7%, N = 130), WF (18.5%), WR (16.9%) and TK (16.9%). For the drone approach tests, only flight altitude had a significant effect in the intensity of the behavioral response of guano birds (intensity behavioral response <2). No birds reacted at drone altitudes above 50 m from the colony. Birds, for all species either in breeding or non-breeding condition, reacted more often at altitudes of 5 and 10 m. Chick-rearing cormorants and pelicans were less sensitive than their non-breeding counterparts in the range of 5–30 m of drone altitude, but boobies reacted similarly irrespective of their condition. At 5 m above the colony, cormorants were more sensitive to the drone presence than the other two species. Horizontal and vertical flights at different speeds had negligible effects (intensity behavioral response <1). At 2 m above the ground, the noise of the cormorant colony was in average 71.34 ± 4.05 dB (N = 420). No significant differences were observed in the drone noise at different flight altitudes because the background noise of the colony was as loud as the drone.

Conclusions

It is feasible to use the drone DJI Phantom 3 for surveys on the guano islands of Peru. We recommend performing drone flights at altitudes greater than 50 m from guano bird colonies and to select take-off spots far from gulls. Likewise, this study provides a first step to develop guidelines and protocols of drone use for other potential activities on the Peruvian guano islands and headlands such as surveys of other seabirds and pinnipeds, filming and surveillance.

A Population Census of Large Herbivores Based on UAV and Its Effects on Grazing Pressure in the Yellow-River-Source National Park, China

Using the Yellow-River-Source National Park (YRSNP) as a study site, an unmanned aerial vehicle (UAV) remote sensing and line transect method was used to investigate the number of wild herbivorous animals and livestock, including the kiang (Equus kiang) and Tibetan gazelle (Procapra picticaudata). A downscaling algorithm was used to generate the forage yield data in YRSNP based on a 30-m spatial resolution. On this basis, we estimated the forage–livestock balance, which included both wild animals and livestock, and analyzed the effects of functional zone planning in national parks on the forage–livestock balance in YRSNP. The results showed that the estimates of large herbivore population numbers in YRSNP based on population density in the aerial sample strips, which were compared and validated with official statistics and warm season survey results, indicated that the numbers of kiangs and Tibetan gazelles in the 2017 cold season were 12,900 and 12,100, respectively. The numbers of domestic yaks, Tibetan sheep, and horses were 53,400, 76,800, and 800, respectively, and the total number of sheep units was 353,200. The ratio of large wild herbivores and livestock sheep units was 1:5. Large wild herbivores have different preferences for functional zones, preferring ecological restoration areas consisting mainly of sparse grassland. The grazing pressure indices of the core reserve areas and ecological restoration areas were 0.168 and 0.276, respectively, indicating that these two regions still have high grazing potential. However, the grazing pressure index of the traditional utilization areas was 1.754, indicating that these grasslands are severely overloaded. After the planning and implementation of functional zones, the grazing pressure index of YRSNP was 1.967. Under this measure, the number of livestock was not reduced and the grazing pressure nearly doubled, indicating that forage–livestock conflict has become more severe in YRSNP.

Terrestrial mammalian wildlife responses to Unmanned Aerial Systems approaches

Unmanned Aerial Systems (UAS) are increasingly being used recreationally, commercially and for wildlife research, but very few studies have quantified terrestrial mammalian reactions to UAS approaches. We used two Vertical Take-off and Landing (VTOL) UAS to approach seven herbivore species in the Moremi Game Reserve, Botswana, after securing the relevant permissions. We recorded responses to 103 vertical and 120 horizontal approaches, the latter from three altitudes above ground level (AGL). We ran mixed logistic regressions to identify factors triggering (i) any response and (ii) an evasive response. We included effects of activity, altitude, direction of approach, distance, habitat, herd type, herd size, other species, target species, time, VTOL type and wind strength. Response triggers were linked to altitude, distance, habitat and target species. Elephant (Loxodonta africana), giraffe (Giraffa camelopardalis), wildebeest (Connochaetes taurinus) and zebra (Equus quagga) were most affected by VTOL approach, impala (Aepyceros melampus) and lechwe (Kobus leche) were least responsive, and tsessebe (Damaliscus lunatus) displayed intermediate sensitivity. VTOLs flown lower than 60 m AGL and closer than 100 m horizontal distance from target animals triggered behavioural responses in most species. Enforced regulations on recreational UAS use in wildlife areas are necessary to minimise disturbance to terrestrial mammals.

Bears habituate to the repeated exposure of a novel stimulus, unmanned aircraft systems

Unmanned aircraft systems (UAS; i.e. 'drones') provide new opportunities for data collection in ecology, wildlife biology and conservation. Yet, several studies have documented behavioral or physiological responses to close-proximity UAS flights. We experimentally tested whether American black bears (Ursus americanus) habituate to repeated UAS exposure and whether tolerance levels persist during an extended period without UAS flights. Using implanted cardiac biologgers, we measured heart rate (HR) of five captive bears before and after the first of five flights each day. Spikes in HR, a measure of stress, diminished across the five flights within each day and over the course of 4 weeks of twice-weekly exposure. We halted flights for 118 days, and when we resumed, HR responses were similar to that at the end of the previous trials. Our findings highlight the capacity of a large mammal to become and remain habituated to a novel anthropogenic stimulus in a relatively short time (3-4 weeks). However, such habituation to mechanical noises may reduce their wariness of other human threats. Also, whereas cardiac effects diminished, frequent UAS disturbances may have other chronic physiological effects that were not measured. We caution that the rate of habituation may differ between wild and captive animals: while the captive bears displayed large initial spikes in HR change (albeit not as large as wild bears), these animals were accustomed to regular exposure to humans and mechanical noises that may have hastened habituation to the UAS.

Social responses of travelling finless porpoises to boat traffic risk in Misumi West Port, Ariake Sound, Japan

Anthropogenic effects have created various risks for wild animals. Boat traffic is one of the most fatal risks for marine mammals. Individual behavioral responses of cetaceans, including diving behavior such as changing swimming direction and lengthing inter-breath interval, to passing boats is relatively well known; however, the social function of cetacean responses to boat traffic in a natural setting remains poorly understood. We focused on describing the behavioral responses of single and aggregated finless porpoises to boats passing at Misumi West Port, Ariake Sound, Japan, by using a drone characterized with a high-precision bird's-eye angle. During the study period, we collected 25 episodes of finless porpoise responses to boats passing by. A mean (± SEM) of 5.1 ± 1.0 individuals were observed for each episode. The primary response to passing boats was avoidance by dive, which implies boat traffic is a substantial disturbance to finless porpoises that travel along the seawater surface daily. The diving duration decreased significantly with an increase in the number of aggregated individuals. The diving and floating reaction times were 10.9 ± 2.3 s and 18.7 ± 5.0 s, respectively. There was no significant difference between the reaction times indicating that each individual was motivated to keep the group cohesion consistent when floating even after the risk had dissolved, which is comparable to the behavior of porpoises that dive when riskier conditions are present, such as when a boat approaches an aggregation. Our findings provide new insights on the sociality of finless porpoises even though there were limitations, like an inability to identify a specific individual. The drone enabled us to observe the social behavior of finless porpoises and other cetaceans at an unprecedented resolution, which may lead to a better understanding of the evolutionary diversity of intelligence and sociality and the bridge to human evolution.

Can drones count gulls? Minimal disturbance and semiautomated image processing with an unmanned aerial vehicle for colony-nesting seabirds

Accurate counts of wild populations are essential to monitor change through time, but some techniques demand specialist surveyors and may result in unacceptable disturbance or inaccurate counts. Recent technological developments in unmanned aerial vehicles (UAVs) offer great potential for a range of survey and monitoring approaches. They literally offer a bird's-eye view, but this increased power of observation presents the challenge of translating large amounts of imagery into accurate survey data. Seabirds, in particular, present the particular challenges of nesting in large, often inaccessible colonies that are difficult to view for ground observers, which are commonly susceptible to disturbance. We develop a protocol for carrying out UAV surveys of a breeding seabird colony (Lesser Black-backed Gulls, Larus fuscus) and subsequent image processing to provide a semiautomated classification for counting the number of birds. Behavioral analysis of the gull colonies demonstrated that minimal disturbance occurred during UAV survey flights at an altitude of 15 m above ground level, which provided high-resolution imagery for analysis. A protocol of best practice was developed using the expertise from both a UAV perspective and that of a dedicated observer. A GIS-based semiautomated classification process successfully counted the gulls, with a mean agreement of 98% and a correlation of 99% with manual counts of imagery. We also propose a method to differentiate between the different gull species captured by our survey. Our UAV survey and analysis approach provide accurate counts (when comparing manual vs. semi-automated counts taken from the UAV imagery) of a wild seabird population with minimal disturbance, with the potential to expand this to include species differentiation. The continued development of analytical and survey tools whilst minimizing the disturbance to wild populations is both key to unlocking the future of the rapid advances in UAV technology for ecological survey.

Drone Monitoring of Breeding Waterbird Populations: The Case of the Glossy Ibis

Waterbird communities are potential indicators of ecological changes in threatened wetland ecosystems and consequently, a potential object of ecological monitoring programs. Waterbirds often breed in largely inaccessible colonies in flooded habitats, so unmanned aerial vehicle (UAV) surveys provide a robust method for estimating their breeding population size. Counts of breeding pairs might be carried out by manual and automated detection routines. In this study we surveyed the main breeding colony of Glossy ibis (Plegadis falcinellus) at the Doñana National Park. We obtained a high resolution image, in which the number and location of nests were determined manually through visual interpretation by an expert. We also suggest a standardized methodology for nest counts that would be repeatable across time for long-term monitoring censuses, through a supervised classification based primarily on the spectral properties of the image and a subsequent automatic size and form based count. Although manual and automatic count were largely similar in the total number of nests, accuracy between both methodologies was only 46.37%, with higher variability in shallow areas free of emergent vegetation than in areas dominated by tall macrophytes. We discuss the potential challenges for automatic counts in highly complex images.

Recording animal vocalizations from a UAV: bat echolocation during roost re-entry

Unmanned aerial vehicles (UAVs) are rising in popularity for wildlife monitoring, but direct recordings of animal vocalizations have not yet been accomplished, likely due to the noise generated by the UAV. Echolocating bats, especially Tadarida brasiliensis, are good candidates for UAV recording due to their high-speed, high-altitude flight. Here, we use a UAV to record the signals of bats during morning roost re-entry. We designed a UAV to block the noise of the propellers from the receiving microphone, and report on the characteristics of bioacoustic recordings from a UAV. We report the first published characteristics of echolocation signals from bats during group flight and cave re-entry. We found changes in inter-individual time-frequency shape, suggesting that bats may use differences in call design when sensing in complex groups. Furthermore, our first documented successful recordings of animals in their natural habitat demonstrate that UAVs can be important tools for bioacoustic monitoring, and we discuss the ethical considerations for such monitoring.