Bio-acoustic tracking and localization using heterogeneous, scalable microphone arrays.

Microphone arrays are an essential tool in the field of bioacoustics as they provide a non-intrusive way to study animal vocalizations and monitor their movement and behavior. Microphone arrays can be used for passive localization and tracking of sound sources while analyzing beamforming or spatial filtering of the emitted sound. Studying free roaming animals usually requires setting up equipment over large areas and attaching a tracking device to the animal which may alter their behavior. However, monitoring vocalizing animals through arrays of microphones, spatially distributed over their habitat has the advantage that unrestricted/unmanipulated animals can be observed. Important insights have been achieved through the use of microphone arrays, such as the convergent acoustic field of view in echolocating bats or context-dependent functions of avian duets. Here we show the development and application of large flexible microphone arrays that can be used to localize and track any vocalizing animal and study their bio-acoustic behavior. In a first experiment with hunting pallid bats the acoustic data acquired from a dense array with 64 microphones revealed details of the bats' echolocation beam in previously unseen resolution. We also demonstrate the flexibility of the proposed microphone array system in a second experiment, where we used a different array architecture allowing to simultaneously localize several species of vocalizing songbirds in a radius of 75 m. Our technology makes it possible to do longer measurement campaigns over larger areas studying changing habitats and providing new insights for habitat conservation. The flexible nature of the technology also makes it possible to create dense microphone arrays that can enhance our understanding in various fields of bioacoustics and can help to tackle the analytics of complex behaviors of vocalizing animals.

Out of the laboratory, into the field: perspectives on social, ethical and regulatory challenges in UK wildlife research.

Drawing on insights from qualitative social science research, this paper aims to prompt reflection on social, ethical and regulatory challenges faced by scientists undertaking invasive animal research in the field and propose ways of addressing these challenges to promote good care for animals and environments. In particular, we explore challenges relating to the management of (i) relationships with publics and stakeholders, who may be present at field sites or crucial to research success; (ii) ethical considerations not present in the laboratory, such as the impacts of research on populations and ecosystems; (iii) working under an array of regulations, which may operate in accordance with competing ethical principles or objectives; and (iv) relationships with regulators (especially vets), which may involve disagreements over ethics and expertise, especially because regulators may be more accustomed to overseeing research in the laboratory than the field. We argue that flexibility-at a personal and policy level-and respect for others' expertise emerged as two key ways of negotiating ethical challenges, fostering positive working relationships and promoting good care for individual animals and broader ecosystems. While our analysis focuses on the UK, we propose that many of these lessons are broadly applicable to international contexts. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.

A Comparison of Focal and Opportunistic Sampling Methods when Studying Chimpanzee Facial and Gestural Communication.

Researchers frequently use focal individual sampling to study primate communication. Recent studies of primate gestures have shown that opportunistic sampling offers benefits not found in focal individual sampling, such as the collection of larger sample sizes. What is not known is whether the opportunistic method is biased towards certain signal types or signalers. Our goal was to assess the validity of the opportunistic method by comparing focal individual sampling to opportunistic sampling of facial and gestural communication in a group of captive chimpanzees (Pan troglodytes). We compared: (1) the number of observed facial and gestural signals per signal type and (2) the number of observed facial and gestural signals produced by each signaler. Both methods identified facial signals, gesture signals, and gesture signalers at similar relative rates, but the opportunistic sampling method yielded a more even distribution of signalers and signal types than the focal individual sampling method. In addition, the opportunistic sampling method resulted in larger sample sizes for both facial and gestural communication. However, the opportunistic method did not allow us to calculate the signals per time for each individual, which is easily done with the focal individual method. These results suggest that the opportunistic sampling method is (1) comparable to the focal individual sampling method in multiple important measures, (2) associated with additional sampling benefits, and (3) limited in measuring some variables. Thus, we recommend that future studies use a mixed-methods approach, as focal individual and opportunistic sampling have distinct strengths that complement each other's limitations.

Action detection using a neural network elucidates the genetics of mouse grooming behavior.

Automated detection of complex animal behaviors remains a challenging problem in neuroscience, particularly for behaviors that consist of disparate sequential motions. Grooming is a prototypical stereotyped behavior that is often used as an endophenotype in psychiatric genetics. Here, we used mouse grooming behavior as an example and developed a general purpose neural network architecture capable of dynamic action detection at human observer-level performance and operating across dozens of mouse strains with high visual diversity. We provide insights into the amount of human annotated training data that are needed to achieve such performance. We surveyed grooming behavior in the open field in 2457 mice across 62 strains, determined its heritable components, conducted GWAS to outline its genetic architecture, and performed PheWAS to link human psychiatric traits through shared underlying genetics. Our general machine learning solution that automatically classifies complex behaviors in large datasets will facilitate systematic studies of behavioral mechanisms.

Behavior is one of the ultimate and most complex outputs of the body's central nervous system, which controls movement, emotion and mood. It is also influenced by a person's genetics. Scientists studying the link between behavior and genetics often conduct experiments using animals, whose actions can be more easily characterized than humans. However, this involves recording hours of video footage, typically of mice or flies. Researchers must then add labels to this footage, identifying certain behaviors before further analysis. This task of annotating video clips ­ similar to image captioning ­ is very time-consuming for investigators. But it could be automated by applying machine learning algorithms, trained with sufficient data. Some computer programs are already in use to detect patterns of behavior, however, there are some limitations. These programs could detect animal behavior (of flies and mice) in trimmed video clips, but not raw footage, and could not always accommodate different lighting conditions or experimental setups. Here, Geuther et al. set out to improve on these previous efforts to automate video annotation. To do so, they used over 1,250 video clips annotated by experienced researchers to develop a general-purpose neural network for detecting mouse behaviors. After sufficient training, the computer model could detect mouse grooming behaviors in raw, untrimmed video clips just as well as human observers could. It also worked with mice of different coat colors, body shapes and sizes in open field animal tests. Using the new computer model, Geuther et al. also studied the genetics underpinning behavior ­ far more thoroughly than previously possible ­ to explain why mice display different grooming behaviors. The algorithm analyzed 2,250 hours of video featuring over 60 kinds of mice and thousands of other animals. It found that mice bred in the laboratory groom less than mice recently collected from the wild do. Further analyses also identified genes linked to grooming traits in mice and found related genes in humans associated with behavioral disorders. Automating video annotation using machine learning models could alleviate the costs of running lengthy behavioral experiments and enhance the reproducibility of study results. The latter is vital for translating behavioral research findings in mice to humans. This study has also provided insights into the amount of human-annotated training data needed to develop high-performing computer models, along with new understandings of how genetics shapes behavior.

TRex, a fast multi-animal tracking system with markerless identification, and 2D estimation of posture and visual fields.

Automated visual tracking of animals is rapidly becoming an indispensable tool for the study of behavior. It offers a quantitative methodology by which organisms' sensing and decision-making can be studied in a wide range of ecological contexts. Despite this, existing solutions tend to be challenging to deploy in practice, especially when considering long and/or high-resolution video-streams. Here, we present TRex, a fast and easy-to-use solution for tracking a large number of individuals simultaneously using background-subtraction with real-time (60 Hz) tracking performance for up to approximately 256 individuals and estimates 2D visual-fields, outlines, and head/rear of bilateral animals, both in open and closed-loop contexts. Additionally, TRex offers highly accurate, deep-learning-based visual identification of up to approximately 100 unmarked individuals, where it is between 2.5 and 46.7 times faster, and requires 2-10 times less memory, than comparable software (with relative performance increasing for more organisms/longer videos) and provides interactive data-exploration within an intuitive, platform-independent graphical user-interface.

The ZE-Tunnel: An Affordable, Easy-to-Assemble, and User-Friendly Benchtop Zebrafish Swim Tunnel.

The popularity of zebrafish in both basic biological and biomedical research has led to an increased need for understanding their behavior. Locomotor behavior is an important outcome of different factors, such as specific genotypes or external stimuli that influence the nervous and musculoskeletal system. Locomotion can be studied by forced swimming in a swim tunnel, a device capable of generating a laminar water flow at different speeds in a chamber where zebrafish can be placed. However, commercially available swim tunnels are relatively expensive and in-house built systems are mostly presented without clear building instructions or proper validation procedures. In this study, we developed an alternative, cheap (<250 euro), and user-friendly, but customizable benchtop swim tunnel, called the "Zebrafish exercise-tunnel" (ZE-Tunnel). Detailed step-by-step instructions on how to construct the tunnel components, including the frame, mechanical, and electric components are given. The ZE-Tunnel was reliably used to exercise fish for prolonged periods and its performance was successfully validated by replicating previously published experiments on critical speed testing in zebrafish. Finally, implementation of behavioral video analysis using freely available motion-tracking software showed differences in swimming dynamics in the Chihuahua skeletal zebrafish mutant.

A Matlab-based toolbox for characterizing behavior of rodents engaged in string-pulling.

String-pulling by rodents is a behavior in which animals make rhythmical body, head, and bilateral forearm as well as skilled hand movements to spontaneously reel in a string. Typical analysis includes kinematic assessment of hand movements done by manually annotating frames. Here, we describe a Matlab-based software that allows whole-body motion characterization using optical flow estimation, descriptive statistics, principal component, and independent component analyses as well as temporal measures of Fano factor, entropy, and Higuchi fractal dimension. Based on image-segmentation and heuristic algorithms for object tracking, the software also allows tracking of body, ears, nose, and forehands for estimation of kinematic parameters such as body length, body angle, head roll, head yaw, head pitch, and path and speed of hand movements. The utility of the task and software is demonstrated by characterizing postural and hand kinematic differences in string-pulling behavior of two strains of mice, C57BL/6 and Swiss Webster.

Standardized ethograms and a device for assessing amphibian thermal responses in a warming world.

Most predictions of how populations and species of ectotherms will respond to global warming are based on estimates of the temperature at which organisms lose motor control (i.e., CTmax - the Critical Thermal Maximum). Here, we describe a non-lethal protocol and ethograms to estimate the relative tolerance of amphibians to increasing temperatures. These methods-suitable for field or laboratory conditions-are replicable, inexpensive and applicable to both post-metamorphic stages and organisms with direct development. We illustrate the use of this standardized protocol for four amphibians from a tropical cloud forest in Veracruz, Mexico with contrasting life histories: a lungless salamander (Aquiloeurycea cafetalera: Plethodontidae), a leaf-litter frog (Craugastor rhodopis: Craugastoridae), a semiaquatic frog (Lithobates berlandieri: Ranidae), and a tree frog (Rheohyla miotympanum: Hylidae). We identified four behavioral responses preceding CTmax for all amphibians included in this study: 1) Optimal Activity Range, 2) Supra-optimal Activity Range, 3) Heat Stress Range, and 4) Involuntary Movements Range. Additionally, we identified a fifth parameter associated with resilience to heat shock: 5) Recovery Stage after reaching CTmax. We conclude that the behavioral responses preceding the Critical Thermal Maximum are as informative as CTmax. Using behavioral responses to estimate thermal tolerance has the additional advantage of reducing the risk of injury or death of amphibians during physiological experiments.

MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology.

Fast object tracking in real time allows convenient tracking of very large numbers of animals and closed-loop experiments that control stimuli for many animals in parallel. We developed MARGO, a MATLAB-based, real-time animal tracking suite for custom behavioral experiments. We demonstrated that MARGO can rapidly and accurately track large numbers of animals in parallel over very long timescales, typically when spatially separated such as in multiwell plates. We incorporated control of peripheral hardware, and implemented a flexible software architecture for defining new experimental routines. These features enable closed-loop delivery of stimuli to many individuals simultaneously. We highlight MARGO's ability to coordinate tracking and hardware control with two custom behavioral assays (measuring phototaxis and optomotor response) and one optogenetic operant conditioning assay. There are currently several open source animal trackers. MARGO's strengths are 1) fast and accurate tracking, 2) high throughput, 3) an accessible interface and data output and 4) real-time closed-loop hardware control for for sensory and optogenetic stimuli, all of which are optimized for large-scale experiments.

Validation of alternative behavioral observation methods in young broiler chickens.

Continuous sampling provides the most complete data set for behavioral research; however, it often requires a prohibitive investment of time and labor. The objectives of this study were to validate behavioral observation methods of young broiler chickens using 1) 7 scan sampling intervals (0.5, 1, 3, 5, 10, 15, and 30 min) and 2) an automated tracking software program (EthoVision XT 14) compared to continuous behavioral observation, considered the gold standard for behavior observation. Ten 19-day-old Ross 708 broiler cockerels were included in this study. All behavior was video recorded over an 8-h period, and data were collected using a continuous sampling methodology. The same video files were utilized for analysis for scan sampling and automated tracking software analysis. For both analyses, the following criteria were used to identify which method accurately reflected the true duration and frequency for each behavior, as determined by continuous observation: R2 ≥ 0.9, slope was not different from 1 (P > 0.05), and intercept was not different from 0 (P > 0.05). Active, eating, drinking, and maintenance behaviors were accurately estimated with 0.5-min scan sample intervals. Active, inactive, eating, and maintenance behaviors were accurately estimated with 1-min scan sample intervals. Inactive behavior was accurately estimated with 5-min scan sample intervals. The remainder of sampling intervals examined did not provide accurate estimates, and no scan sampling interval accurately estimated the number of behavior bouts. The automated tracking software was able to accurately detect true duration of inactive behavior but was unable to accurately detect activity. The results of this study suggest that high-frequency behaviors can be accurately observed with instantaneous scan sampling up to 1-min intervals. Automated tracking software can accurately identify inactivity in young broiler chickens, but further behavior identification will require refinement.

La eficacia en la detección canina en el ámbito de las fuerzas armadas: propuesta de un estándar de evaluación / Effectiveness in dog detection in the military: proposal for an evaluation standard

El uso de perros detectores está ampliamente implantado entre las Fuerzas Armadas y Policiales de todo el mundo. Pero cada país, e incluso a menudo cada rama de los ejércitos, tienen un sistema de entrenamiento diferente para estos animales, lo que dificulta la tarea de establecer un estándar con el que medir sus resultados al desarrollar dicha práctica. A través de una revisión bibliográfica de estudios de etología canina, el autor trata de dirimir cuál es el mínimo porcentaje de detección que podemos esperar de un perro para decir que está correctamente entrenado, a fin de que se convierta en un estándar válido y eficaz por el que puedan medirse los resultados de los perros detectores de las Fuerzas Armadas

The use of detector dogs is widely implanted among the Armed Forces and Police around the world. But each country, and even often each branch of the military, has a different training system for these animals, making it difficult to establish a standard against which to measure their performance in developing such a practice. Through a literature review of canine ethology studies, the author attempts to determine what is the minimum percentage of detection we can expect from a dog to say that it is properly trained, so that it becomes a valid and effective standard by which to measure the results of detection dogs in the Armed Forces

Kinematic signatures of prey capture from archival tags reveal sex differences in killer whale foraging activity.

Studies of odontocete foraging ecology have been limited by the challenges of observing prey capture events and outcomes underwater. We sought to determine whether subsurface movement behavior recorded from archival tags could accurately identify foraging events by fish-eating killer whales. We used multisensor bio-logging tags attached by suction cups to Southern Resident killer whales (Orcinus orca) to: (1) identify a stereotyped movement signature that co-occurred with visually confirmed prey capture dives; (2) construct a prey capture dive detector and validate it against acoustically confirmed prey capture dives; and (3) demonstrate the utility of the detector by testing hypotheses about foraging ecology. Predation events were significantly predicted by peaks in the rate of change of acceleration ('jerk peak'), roll angle and heading variance. Detection of prey capture dives by movement signatures enabled substantially more dives to be included in subsequent analyses compared with previous surface or acoustic detection methods. Males made significantly more prey capture dives than females and more dives to the depth of their preferred prey, Chinook salmon. Additionally, only half of the tag deployments on females (5 out of 10) included a prey capture dive, whereas all tag deployments on males exhibited at least one prey capture dive (12 out of 12). This dual approach of kinematic detection of prey capture coupled with hypothesis testing can be applied across odontocetes and other marine predators to investigate the impacts of social, environmental and anthropogenic factors on foraging ecology.

A Review of Freely Available, Open-Source Software for the Automated Analysis of the Behavior of Adult Zebrafish.

The analysis of behavior in animal models is an important objective in many research fields, including neuroscience, psychology, toxicology, and neuropsychopharmacology. Animal models have been used for many years, and several behavioral paradigms, such as locomotor activity, social interactions, and cognitive behavior, have been studied in animal models to correlate the behaviors with pharmacological or environmental interventions and with molecular, biochemical, and physiological findings. We reviewed the literature looking for open-source, freely available software to analyze animal behavior and found 12 freely available programs: ToxTrack, EthoWatcher, Mouse Behavior Tracker, Mouse Move, JAABA, wrMTrck, AnimalTracker, idTracker, Ctrax, Mousetracker, VideoHacking, and Cowlog, which were developed with different programs, work on different platforms, and have particular types of inputs and outputs and analysis capabilities. We reviewed some examples of their use, tested some of them, and provided several recommendations for the future development of programs for the automated analysis of behavior in animal models. In conclusion, we show freely available software for the automated analysis of behavior in animal models such as adult zebrafish and provide information for researchers and students looking for quick, easy-to-implement, and inexpensive behavior analysis alternatives.

Head-mounted sensors reveal visual attention of free-flying homing pigeons.

Gaze behavior offers valuable insights into attention and cognition. However, technological limitations have prevented the examination of animals' gaze behavior in natural, information-rich contexts; for example, during navigation through complex environments. Therefore, we developed a lightweight custom-made logger equipped with an inertial measurement unit (IMU) and GPS to simultaneously track the head movements and flight trajectories of free-flying homing pigeons. Pigeons have a limited range of eye movement, and their eye moves in coordination with their head in a saccadic manner (similar to primate eye saccades). This allows head movement to act as a proxy for visual scanning behavior. Our IMU sensor recorded the 3D movement of the birds' heads in high resolution, allowing us to reliably detect distinct saccade signals. The birds moved their head far more than necessary for maneuvering flight, suggesting that they actively scanned the environment. This movement was predominantly horizontal (yaw) and sideways (roll), allowing them to scan the environment with their lateral visual field. They decreased their head movement when they flew solo over prominent landmarks (major roads and a railway line) and also when they flew in pairs (especially when flying side by side, with the partner maintained in their lateral visual field). Thus, a decrease in head movement indicates a change in birds' focus of attention. We conclude that pigeons use their head gaze in a task-related manner and that tracking flying birds' head movement is a promising method for examining their visual attention during natural tasks.

A machine vision system for zooplankton behavioural studies: a case study on the phototactic behaviour of sea lice (Lepeophtheirus salmonis) during sound and ultrasound stimuli.

Machine vision represents an accurate and easily verifiable method for observing live organisms and this technology is constantly evolving in terms of accessibility and cost. Motivated by the complexity of observing small-sized aquatic organisms in experimental systems, and the difficulties related to real-time observation, sampling and counting without interfering with the organisms, we here present a new method for observing behaviour and dispersion of non-sessile zooplankton organisms using a custom-made tank with an associated machine vision system. The system was used in an experiment where the aim was to assess the effect of sound and ultrasound on the phototactic behaviour of copepodite stages of the salmon louse (Lepeophtheirus salmonis). The experimental set-up is described, including a triangular test tank designed to create a sound pressure gradient, a mechanized camera movement system and a vision system with dedicated image processing software.

Re-wilding Collective Behaviour: An Ecological Perspective.

The earliest studies of collective animal behaviour were inspired by and conducted in the wild. Over the past decades much of the research in this field has shifted to the laboratory, combining high-resolution tracking of individuals with mathematical simulations or agent-based models. Today we are beginning to see a 're-wilding' of collective behaviour thanks to technological advances, providing researchers with the opportunity to quantify and model the heterogeneity that exists within the social groupings they study and within the environments in which these groups live. The perspective we present here aims to inspire and steer this research toward answering fundamental and outstanding behavioural and ecological questions, while also tackling pertinent conservation challenges.

Collective movement in ecology: from emerging technologies to conservation and management.

Recent advances in technology and quantitative methods have led to the emergence of a new field of study that stands to link insights of researchers from two closely related, but often disconnected disciplines: movement ecology and collective animal behaviour. To date, the field of movement ecology has focused on elucidating the internal and external drivers of animal movement and the influence of movement on broader ecological processes. Typically, tracking and/or remote sensing technology is employed to study individual animals in natural conditions. By contrast, the field of collective behaviour has quantified the significant role social interactions play in the decision-making of animals within groups and, to date, has predominantly relied on controlled laboratory-based studies and theoretical models owing to the constraints of studying interacting animals in the field. This themed issue is intended to formalize the burgeoning field of collective movement ecology which integrates research from both movement ecology and collective behaviour. In this introductory paper, we set the stage for the issue by briefly examining the approaches and current status of research in these areas. Next, we outline the structure of the theme issue and describe the obstacles collective movement researchers face, from data acquisition in the field to analysis and problems of scale, and highlight the key contributions of the assembled papers. We finish by presenting research that links individual and broad-scale ecological and evolutionary processes to collective movement, and finally relate these concepts to emerging challenges for the management and conservation of animals on the move in a world that is increasingly impacted by human activity.This article is part of the theme issue 'Collective movement ecology'.

Ethoscopes: An open platform for high-throughput ethomics.

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.

Urban primate ranging patterns: GPS-collar deployments for Macaca fascicularis and M. sylvanus.

The global increase in urbanization is leading to heavier interface between humans and wildlife. Within these anthropogenic landscapes, little is known about ranging patterns, particularly with regard to urban primates. Here we present the results of the first long-term deployment of multiple GPS collars on two species of macaques to investigate the impacts of urbanization on urban primate ranging patterns in Singapore and Gibraltar. Collars data acquisition were excellent with respect to the amount, quality, and accuracy of data collected; however, remote connectivity and drop-off functionality was poor across all deployments. Analyses highlighted high variability in ranging patterns between individuals within each species that aligned with access to human food resources and patterns of tourism. Individuals from troops with less access to human food had much larger home, core, and day ranges relative to those with regular provisioning or raiding opportunities. Almost no temporal range overlap was observed between any focal individuals at either site and spatial overlap was low for all but two troops at each site. We found no relationship between anthropogenic schedules and changes in ranging patterns. Significant seasonal variation existed for daily path length and day range size for both the Singapore long-tailed and the Gibraltar Barbary macaques, with long-tailed macaques increasing their range during the equatorial monsoon season and Barbary macaques increasing their range during drier, summer months. This study highlights how the behavioral plasticity found within the genus Macaca is reflected in ranging pattern variability within urban environments.

Mechanical Conflict System: A Novel Operant Method for the Assessment of Nociceptive Behavior.

A new operant test for preclinical pain research, termed the Mechanical Conflict System (MCS), is presented. Rats were given a choice either to remain in a brightly lit compartment or to escape to a dark compartment by crossing an array of height-adjustable nociceptive probes. Latency to escape the light compartment was evaluated with varying probe heights (0, .5, 1, 2, 3, and 4 mm above compartment floor) in rats with neuropathic pain induced by constriction nerve injury (CCI) and in naive control rats. Escape responses in CCI rats were assessed following intraperitoneal administration of pregabalin (10 and 30 mg/kg), morphine (2.5 and 5 mg/kg), and the tachykinin NK1 receptor antagonist, RP 67580 (1 and 10 mg/kg). Results indicate that escape latency increased as a function of probe height in both naive and CCI rats. Pregabalin (10 and 30 mg/kg) and morphine (5 mg/kg), but not RP 67580, decreased latency to escape in CCI rats suggesting an antinociceptive effect. In contrast, morphine (10 mg/kg) but not pregabalin (30 mg/kg) increased escape latency in naive rats suggesting a possible anxiolytic action of morphine in response to light-induced fear. No order effects following multiple test sessions were observed. We conclude that the MCS is a valid method to assess behavioral signs of affective pain in rodents.