Slowness and acceleration: a new method to quantify the activity budget of chelonians (original) (raw)
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The deployment of an ever-evolving array of animal-borne telemetry and data logging 16 devices is rapidly increasing our understanding of the movement, behaviour and 17 physiology of a variety species and the complex, and often highly dynamic, 18 environments they use and respond to. The rapid rate at which new technologies, 19 improvements to current technologies and new analytical techniques are being 20 developed has meant that movements, behaviour and physiological processes are 21 being quantified at finer spatial and temporal scales than ever before. The Fourth 22
Simulation-based validation of activity logger data for animal behavior studies
Animal Biotelemetry
Bio-loggers are widely used for studying the movement and behavior of animals. However, some sensors provide more data than is practical to store given experiment or bio-logger design constraints. One approach for overcoming this limitation is to utilize data collection strategies, such as non-continuous recording or data summarization that may record data more efficiently, but need to be validated for correctness. In this paper we address two fundamental questions—how can researchers determine suitable parameters and behaviors for bio-logger sensors, and how do they validate their choices? We present a methodology that uses software-based simulation of bio-loggers to validate various data collection strategies using recorded data and synchronized, annotated video. The use of simulation allows for fast and repeatable tests, which facilitates the validation of data collection methods as well as the configuration of bio-loggers in preparation for experiments. We demonstrate this metho...
Frontiers Ecology and Evolution, 2020
Many details of the behavior, life history and eco-physiology of animals, even among intensively-studied species, remain unknown. Direct observation is a laborious process only amenable for accessible and non-cryptic species, whereas traditional radio telemetry does not directly provide information on the diversity and complexity of animal physiology and behavior. Further, both methods are laborious and/or expensive, and may lead to biased data when physiology and/or behaviors are altered by marking or tracking (Boyer-Ontl and Pruetz, 2014; Nowak et al., 2014; Welch et al., 2018; see also Le Grand et al.). Ultimately, these methods provide only a fragmentary overview of animal behavior patterns during periods when individuals can be readily detected and surveyed while leaving activities during other times obscured. However, the ongoing miniaturization, sensor development, and increased affordability of data logging and advanced telemetric devices offers the potential for continuous and intensive data collection, thereby potentially allowing researchers to more rigorously investigate both physiology and behavior of animals that are difficult to study using traditional observational methods. Owing to these new technologies, we are at the cusp of a truly revolutionary opportunity to address important and longstanding knowledge gaps in animal eco-physiology. To that end, the special section entitled Ecology and Behaviour of Free-Ranging Animals Studied by Advanced Data-Logging and Tracking Techniques includes 22 papers that report on and quantify otherwise hidden aspects of the biology of a variety of mammals, birds, and even invertebrates, across diverse environments including land, water, and air. The highlighted studies focus on fields ranging from basic animal behavior and ecology to eco-physiology; several papers adopt an integrative approach, providing a rather comprehensive understanding of individual time budgets and their implications. Ultimately and collectively, these contributions serve as testament to the drastic improvement in the level of ecological inference that can be derived from research studies involving the use of data-logging and tracking devices that are currently available.
Observing the unwatchable through acceleration logging of animal behavior
Animal Biotelemetry, 2013
Behavior is an important mechanism of evolution and it is paid for through energy expenditure. Nevertheless, field biologists can rarely observe animals for more than a fraction of their daily activities and attempts to quantify behavior for modeling ecological processes often exclude cryptic yet important behavioral events. Over the past few years, an explosion of research on remote monitoring of animal behavior using acceleration sensors has smashed the decades-old limits of observational studies. Animal-attached accelerometers measure the change in velocity of the body over time and can quantify fine-scale movements and body postures unlimited by visibility, observer bias, or the scale of space use. Pioneered more than a decade ago, application of accelerometers as a remote monitoring tool has recently surged thanks to the development of more accessible hardware and software. It has been applied to more than 120 species of animals to date. Accelerometer measurements are typically collected in three dimensions of movement at very high resolution (>10 Hz), and have so far been applied towards two main objectives. First, the patterns of accelerometer waveforms can be used to deduce specific behaviors through animal movement and body posture. Second, the variation in accelerometer waveform measurements has been shown to correlate with energy expenditure, opening up a suite of scientific questions in species notoriously difficult to observe in the wild. To date, studies of wild aquatic species outnumber wild terrestrial species and analyses of social behaviors are particularly few in number. Researchers of domestic and captive species also tend to report methodology more thoroughly than those studying species in the wild. There are substantial challenges to getting the most out of accelerometers, including validation, calibration, and the management and analysis of large quantities of data. In this review, we illustrate how accelerometers work, provide an overview of the ecological questions that have employed accelerometry, and highlight the emerging best practices for data acquisition and analysis. This tool offers a level of detail in behavioral studies of free-ranging wild animals that has previously been impossible to achieve and, across scientific disciplines, it improves understanding of the role of behavioral mechanisms in ecological and evolutionary processes.
2020
The use of miniature accelerometer (ACT) data-loggers for remote and continuous recording of animal movement behavior is becoming increasingly common. Until recently, size constraints limited most animal-borne ACT applications to large-bodied species. We capitalized on the ongoing miniaturization and advancement of these technologies and associated computational techniques to develop a framework for long-term, low-frequency ACT monitoring of activity in small and secretive terrestrial species. We achieved this by internally implanting coupled radio transmitters and tri-axial ACTs in rattlesnakes (Crotalus atrox). Periodic field-validation observations of behavior were used to train and test supervised learning models (Random Forest, RF; Generalized Linear Elastic Net, GLMNET) for activity classification. The best performing RF model classified periods of movement and immobility in rattlesnakes with high accuracy (movement = 96%, immobile = 99%), and was applied to extensive ACT fiel...
Animal Biotelemetry, 2023
Background Biologgers have contributed greatly to studies of animal movement, behaviours and physiology. Accelerometers, among the various on-board sensors of biologgers, have mainly been used for animal behaviour classification and energy expenditure estimation. However, a general principle for the combined sampling duration and frequency for different taxa is lacking. In this study, we evaluated whether Nyquist-Shannon sampling theorem applies to accelerometer-based classification of animal behaviour and energy expenditure approximation. To evaluate the influence of accelerometer sampling frequency on behaviour classification, we annotated accelerometer data from seven European pied flycatchers (Ficedula hypoleuca) freely moving in aviaries. We also used simulated data to systematically evaluate the combined effect of sampling duration and sampling frequency on the performance of estimating signal frequency and amplitude.
An activity-data-logger for monitoring free-ranging animals
Applied Animal Behaviour Science, 1996
A small (16 cm X 15 cm X 21 cm) solar powered activity-data-logger (ADL) has been developed as a suitable instrument for recording the presence and movements of free-ranging animals. Locomotor activity is recorded by a passive infrared detector (PID). At fixed intervals the signals picked up by the PID are condensed automatically and stored in the ADL. This database can be transferred for further use onto a lap-top or PC. The ADL can store information for up to 80 days and thereafter this information has to be tranferred in order to use the ADL further. A solar-generated accumulator serves as the power supply.
Diving into the analysis of time – depth recorder and behavioural data records: A workshop summary
Directly observing the foraging behavior of animals in the marine environment can be extremely challenging, if not impossible, as such behavior often takes place beneath the surface of the ocean and in extremely remote areas. In lieu of directly observing foraging behavior, data from time-depth recorders and other types of behavioral data recording devices are commonly used to describe and quantify the behavior of fish, squid, seabirds, sea turtles, pinnipeds, and cetaceans. Often the definitions of actual behavioral units and analytical approaches may vary substantially which may influence results and limit our ability to compare behaviors of interest across taxonomic groups and geographic regions. A workshop was convened in association with the Fourth International Symposium on Bio-logging in Hobart, Tasmania on 8 March 2011, with the goal of providing a forum for the presentation, review, and discussion of various methods and approaches that are used to describe and analyze time-depth recorder and associated behavioral data records. The international meeting brought together 36 participants from 14 countries from a diversity of backgrounds including scientists from academia and government, graduate students, post-doctoral fellows, and developers of electronic tagging technology and analysis software. The specific objectives of the workshop were to host a series of invited presentations followed by discussion sessions focused on (1) identifying behavioral units and metrics that are suitable for empirical studies, (2) reviewing analytical approaches and techniques that can be used to objectively classify behavior, and (3) identifying cases when temporal autocorrelation structure is useful for identifying behaviors of interest. Outcomes of the workshop included highlighting the need to better define behavioral units and to devise more standardized processing and analytical techniques in order to ensure that results are comparable across studies and taxonomic groups.