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Bottom row: a iStock. Unmanned aerial vehicles UAVs currently provide the most affordable and flexible imaging platforms for obtaining an aerial perspective in the field. In addition to greatly expanding the simultaneous field of view afforded by stationary cameras, UAVs provide the ability to adjust camera positioning on the fly and at distances up to several kilometres from the operator. This capability facilitates truly non-invasive filming of collective animal behaviour when following 'best practices' outlined in [ 40 , 41 ] and when combined with computer vision techniques e.

[] Inference of Causal Information Flow in Collective Animal Behavior

For example, Torney et al. Figure 4. Still frame from a UAV video sequence demonstrating ability to automatically track unique individuals and species e. Still frame was reproduced with permission from Colin J. Figure 5. Combining bio-logging with UAV imagery enables investigation of how the environment shapes collective movement in wild animal groups. Coloured lines show trajectories for the majority of baboons within a single troop obtained using GPS collars , and background image shows 3D point cloud rendering of their habitat obtained from UAV imagery.

White lines show scale each line extends 50 m. Adapted from [ 10 ]. In addition, a growing commercial market is continually increasing the utility and affordability of UAVs by offering a wide range of airframe designs, payload capacities, and technical configurations to suit the needs and budget of most academic research programmes [ 44 , 45 ].


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Alternatively, a thriving DIY community offers limitless opportunities for researchers needing bespoke solutions at low cost. The inability to film animals through dense canopy or turbid water, or to resolve smaller species less than about 30 kg at appropriate altitude is currently the largest limitation of UAVs for studies of collective animal behaviour. However, thermal infrared and increasingly compact, high-resolution cameras are rapidly expanding future possibilities for filming under these conditions.

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Limited battery life presents an additional challenge, though significant gains stand to be made from utilizing alternative airframes. For example, fixed-wing UAVs afford significantly longer flight times than compact, multi-rotor designs i. However, a multi-rotor system affords the advantage of hovering in place without the need to circle continuously as required by a fixed-wing aircraft.

In addition, many low-cost commercial systems can produce stimuli perceived to be threatening by many species i. Furthermore, there is some evidence that UAVs may cause physiological changes in study animals i. Alternatively, non-motorized platforms i.

Understanding collective animal behavior may be in the eye of the computer

Of course, these gains come at the cost of manoeuvrability, though this may be partially mediated by use of a remote controlled camera gimbal, or increased altitude. Finally, depending on the study area, UAVs may present a multitude of legal challenges, which will generally require advance permitting and licensing at a minimum, and partial to total restriction of flights at a maximum.

Thus, it is essential to work with local stakeholders and law enforcement agencies during the early phases of project planning to clarify procedures and ensure compliance prior to beginning work. Commercial satellite companies maintain the largest collection of archived images with the resolution appropriate for identifying individual animals 30 cm [ 50 ] to 50 cm [ 50 , 51 ] , but the random and disparate temporal distribution of coverage generally limits the use of archived images for studies of collective movement.

While there is some promise for using new, commissioned images to capture time series of large animal groups moving across the landscape, this will require future increases in satellite availability for civilian use coupled with a significant decrease in cost. Obtaining such high-resolution, high-frequency satellite imagery presents a first opportunity to study entire herds of large animals e. Animal-mounted sensors or bio-loggers present another promising and complementary approach to image-based studies of collective behaviour.

Acknowledgements

Such on-board sensors—including GPS, accelerometers, magnetometers, pressure sensors and acoustic recorders, among others—are opening up new directions in a range of biological disciplines, as they allow data to be collected continuously and directly at the location of the study animal, irrespective of changes in accessibility or visibility of the animal, and without need for re-identifying the same individual repeatedly.

For studying collective behaviour in particular, on-board sensors allow animal position, movement and behaviour to be monitored with increasing resolution and across a range of habitats and contexts [ 55 , 56 ]. In addition, many tags now include multiple types of sensors integrated with one another, making it possible to test how the movements, vocalizations, behaviours and social interactions of freely-moving animals influence one another [ 57 ]. However, the utility of bio-loggers is limited by the need to affix sensors to each monitored animal, a process that usually requires capture for collars, backpacks or glue attachment or close range physical interaction for suction cup or dart attachments.

Additionally, the need for animals to carry devices imposes strong weight and size restrictions, thereby limiting the sensor payload and battery size, and resulting in trade-offs between sensor sampling rate, duty cycling, and battery life. Retrieving data can also present challenges.

In some cases, it may be possible to download data remotely from tags, while in others, tags must be retrieved either through recapturing animals or by having a remote drop-off system to offload data. Another complication that is especially relevant to studies of collective behaviour is the need to deploy many devices simultaneously. If instrumentation happens over an extended period of time, tags need a pre-programmed start time to maximize simultaneous recording time.


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  7. Additionally, the internal clocks of independent tags will drift over time, and thus tags that do not include a GPS sensor will need a system for intermittently synchronizing tags. Lastly, on-board sensors are typically expensive, so deploying many tags may become cost-prohibitive for some research projects. Despite these challenges, continued advances in technology have reduced the size and cost of on-board sensors while also increasing their spatial and temporal resolution.

    Owing to these advances, their use in behavioural biology is rapidly growing, and they are becoming an increasingly powerful tool for studying collective animal behaviour. We explore these advances and associated challenges in greater detail below. Modern GPS tags are capable of monitoring animal locations at sub-second rates, and with spatial resolution that can achieve sub-metre precision. These advances mean that data can now be collected at the temporal and spatial scales necessary for studying fine-scale social interactions within groups [ 55 ].

    Collecting movement data via GPS tags has a number of advantages. First and foremost, it is possible to monitor animals in areas where visual observation is impossible. Moreover, animals can be tracked over multiple spatial scales from local interactions within groups to long-range collective migrations [ 63 ] and with an adjustable temporal rate. Such high-density data can allow estimation of individual interaction rules and leadership [ 64 ], differences in relative position within a group that are related to individual differences or personality traits [ 65 , 66 ], or tracking fine-scale interactions with the local environment [ 10 , 63 ].

    GPS sensors require a relatively large amount of power, but recent low-power GPS tags now allow for multi-week continuous 1 Hz position updates tracking of medium-sized animals such as baboons [ 59 ]. However, this increased spatial or temporal resolution may not be high enough to resolve fine-scale movements and social interactions for some systems and contexts.

    Therefore, these methods are most appropriate for groups that are dispersed over at least tens of metres, or for addressing interactions that take place over such distances. In contrast to overhead imaging, there are no limits to maximum separation distance so it is more feasible to study social dynamics of fluid groups on the move. For smaller animals or more compact group interactions, high-resolution imaging from either stationary cameras or UAVs is likely a better approach to differentiating interactions.

    For marine animals or other systems where a significant component of movement takes place vertically, cheap and power-efficient pressure sensors can monitor the depth of a tagged animal. Tags with pressure sensors generally store and transmit summary data or store raw depth measurements.


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    This information can provide data on dive and foraging behaviour, and can be merged with Argos positions i. GPS locations from Argos satellite system to provide detailed data on foraging ecology of deep-diving animals [ 67 ]. Although it is possible to use pressure sensors to quantify dive initiation and other characteristics of leadership, so far this technology has only been used to a limited extent for studies of collective behaviour [ 68 ]. This is in part due to problems with separating lack of coordination from lack of horizontal cohesion, and in part due to inevitable clock drift between independently sampling tags.

    Novel approaches to solve these two issues are therefore needed, such as synchronization pulses or incorporation of GPS or fast-lock GPS technology with accurate timing information. Even when precise positions are not known, information on the presence or proximity of animals to one another, or to fixed geographical locations, can still provide a useful quantification of social structure and interactions.

    Probabilistic models of individual and collective animal behavior

    Such methods can be particularly important for species whose size, environment or behaviour makes continuous monitoring impractical or impossible, or for processes that span longer time scales, such as social learning. A range of active and passive transponder systems have been used to obtain such data so far, and are thought to be increasingly important to future work [ 69 ].

    Passive integrated transponder PIT tags are extremely small, lightweight and inexpensive devices that carry a unique barcode and are typically implanted internally in animals. PIT tags do not require an internal power source so they can usually remain with an animal for its entire lifetime and are well suited to automated set-ups. While PIT tag systems do not monitor position continuously, they are well suited to systems in which animals spend time at specific locations such as nests and foraging patches, or to monitor their movements through specific movement corridors such as rivers e.

    Arrays of transponder readers can also give more detailed information on animal positions and movement directions [ 70 ], and co-occurrences at specific locations can be used to infer social structure [ 71 ]. A limitation of PIT tags is that their detection range is very short, typically on the order of a few metres or less. In the context of collective behaviour, PIT tags have been used to monitor decision-making, social network structure, and information transfer in populations of wild birds [ 17 , 72 , 73 ], bats Myotis bechsteinii [ 74 ] and house mice Mus musculus [ 75 ], among others.

    Active transponder tags, including VHF radio beacons or acoustic transponders that contain their own power source for signal generation, can provide a longer-range alternative, though these also require deployed receiving stations.

    Several lakes have recently been instrumented with relatively dense arrays of acoustic receivers to track active transponders implanted in multiple species of fish, allowing a detailed perspective into interactions both within and between species in an ecosystem [ 69 , 76 ]. Proximity sensors are active transponder tags that can themselves receive information from other transponders and store information on time and ID of encountered tags [ 77 ].

    Tags can be tuned either to record signals above a certain threshold or to record signals and signal strength, where the latter can be used to infer encounter distance [ 78 ]. These tags have been used to automatically map association patterns and investigate social learning in free-ranging New Caledonian crows Corvus moneduloides [ 79 ] and to investigate social dynamics of zebras Equus quagga [ 80 ] and sharks Carcharhinus galapagensis [ 81 , 82 ].

    A full understanding of how animal groups coordinate movement will require data, not just on where animals are, but on the sensory information they are taking in and the behaviours that they are engaging in. Recent laboratory studies of animal groups have begun to incorporate sensory information, such as the visual field of each individual in a school of fish [ 9 , 35 , 83 ], to build more predictive and biologically motivated models of collective motion [ 84 ].

    Onboard inertial sensors such as accelerometers, magnetometers and gyroscopes provide an opportunity to obtain detailed behavioural information for animal groups in the wild, even when they cannot be directly observed by humans, and may also provide the means for tracking body orientation and gaze direction of animals within moving groups. Both accelerometers and magnetometers are commonly used in bio-logging tags since they are compact, cheap and power efficient [ 85 , 86 ].

    Gyroscopes have some advantages when measuring energetics and body posture, but have seen only limited use in bio-logging tags owing to their higher power consumption, drift and complex data processing [ 87 ]. Tri-axial accelerometers measure both static acceleration caused by the gravitational field of the Earth and dynamic acceleration caused by acceleration of the animal and thereby the sensor itself along three dimensions.

    Depending on sensor placement, dynamic acceleration can be related to the movement of the animal itself, and various proxies for energy expenditure or activity level using tri-axial accelerometers have been developed as a result ODBA [ 88 ]; veDBA [ 89 ]; MSA [ 90 ]. Accelerometers may also be used to estimate body orientation, often quantified as the pitch, roll and heading of an animal.

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    To measure all three axes of body orientation, an accelerometer and magnetometer are needed, and magnetic heading must be corrected for the magnetic inclination and declination at the study site. Magnetometers are seldom used by themselves because they cannot fully specify the orientation of the tag owing to rotational ambiguity around the magnetic field vector. However, with triaxial accelerometers and magnetometers, time series of body orientation can be used to quantify the gait of an animal over time [ 91 ].