Review of GPS collar deployments and performance on nonhuman primates

Dore, Kerry M.; Hansen, Malene Friis; Klegarth, Amy R.; Fichtel, Claudia; Koch, Flávia; Springer, Andrea; Kappeler, Peter M.; Parga, Joyce A.; Humle, Tatyana; Colin, Christelle; Raballand, Estelle; Huang, Zhi‐Pang; Qi, Xiao-Guang; Fiore, Anthony Di; Link, Andrés; Stevenson, Pablo R.; Stark, Danica J.; Tan, Noeleen; Gallagher, Christa A.; Anderson, C. Jane; Campbell, Christina J.; Kenyon, Marina; Pebsworth, Paula A.; Sprague, David S.; Jones‐Engel, Lisa; Fuentes, Agustín

doi:10.1007/s10329-020-00793-7

Cited by 34 publications

(39 citation statements)

References 55 publications

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“…This includes species whose social activities are not yet well known. Location information has become more reliable and scalable thanks to recent developments in biologging technology, such as GPS (Dore et al., 2020; Fehlmann & King, 2016; Gelardi et al., 2020; Heupel et al., 2006; King et al., 2018; Rutz et al., 2012; Rutz & Hays, 2009). However, naively measuring the Euclidean distance between individuals and treating pairs with a smaller distance as socially related is not necessarily reasonable.…”

Section: Introductionmentioning

confidence: 99%

Nonparametric analysis of inter‐individual relations using an attention‐based neural network

et al. 2021

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1. Social network analysis, widely adopted in animal studies over the past decade, enabled the revelation of global characteristic patterns of animal social systems from pairwise inter-individual relations.2. Animal social networks are typically drawn based on geometric proximity and/or frequency of social behaviors (e.g., grooming), but the appropriate metric for inter-individual relatedness is not clear especially when prior knowledge on the species/data is limited.3. In this study, the researchers explored a non-parametric analysis of inter-individual relations using a neural network with the attention mechanism, which plays a central role in natural language processing.4. The high interpretability of the attention mechanism and the flexibility of the entire neural network allow automatic detection of inter-individual relations included in raw data, without requiring prior knowledge/assumptions about what modes/types of relations are included in the data. 5. For these case studies, three-dimensional location data collected from simulated agents and real Japanese macaques were analyzed.6. The proposed method successfully recovered the latent relations behind the simulated data and discovered female-oriented relations in the real data that are in accordance with previous generalizations about macaque social structure.

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Section: Introductionmentioning

confidence: 99%

Nonparametric analysis of inter‐individual relations using an attention‐based neural network

et al. 2021

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“…Biolog data are systematic, fine-grained, and large-scale compared to traditional ecological observations. Therefore, they are ideal for machine learning-based and other data-scientific analyses [9][10][11]. Besides measuring the extent of overall behavioral changes upon isolation, we also investigated whether isolation intensifies or diminishes the macaques' individuality reflected in their movement, performing individual recognition based on the location trajectories [12].…”

Section: Introductionmentioning

confidence: 99%

Effects of short-term isolation on social animals’ behavior: an experimental case study of Japanese macaque

Morita

Toyoda

Aisu

et al. 2021

Preprint

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One of the goals in animal socioecology is to understand the functions and dynamics of group living. While observations of free-ranging animals are a crucial source of information, an experimental investigation that manipulates the size or composition, or both, of animal groups in captivity can also bring complementary contributions to the research inquiry. When paired with an automatic data collection by biologging technology, experimental studies on captive animals also allow for big data analyses based on recent machine learning techniques. As an initial exploration of this research paradigm, the present study inquired to what extent isolation of captive Japanese macaques (Macaca fuscata) changed their movement patterns. Using three-dimensional location trajectories of the macaques that were systematically collected via Bluetooth Low Energy beacons and a deep neural network, we estimated the identifiability of whether a macaque was behaving in isolation or in group. We found that the neural network identified the isolation vs. in-group conditions with more than 90% accuracy from a five-minute location trajectory, suggesting that the isolation caused notable changes from the canonical group-living behaviors. In addition, the isolation made each individual more identifiable from one another based on their location trajectories.

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“…This approach has led to broad applications, including examination of home ranges [6,7], migratory routes [8][9][10], habitat use [11,12], resource allocation [13,14], activity budgets [15][16][17] as well as social interactions [18]. Since their inception, animal-borne GPS's have reduced considerably in mass and size, whilst data storage capacity, battery longevity and affordability have improved [5,19,20]. Consequently, scientists can now track animals as small as ca.…”

Section: Introductionmentioning

confidence: 99%

Decision rules for determining terrestrial movement and the consequences for filtering high-resolution GPS tracks – A case study using the African Lion (Panthera leo)

Gunner

Wilson

Holton

et al. 2021

Preprint

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The combined use of Global Positioning System (GPS) technology and motion sensors within the discipline of movement ecology has increased over recent years. This is particularly the case for instrumented wildlife, with many studies now opting to record parameters at high (infra-second) sampling frequency. However, the detail with which GPS loggers can elucidate fine-scale movement depends on the precision and accuracy of fixes, with accuracy (specifically, location error and fix success rate) being affected by signal reception. We hypothesised that animal behaviour was the main factor affecting fix inaccuracy (particularly for collar-mounted tags sampling at high frequency). In conjunction to this, inherent GPS positional noise (‘jitter’), would be most apparent during GPS fixes for non-moving locations, thereby producing disproportionate error during rest periods. A Movement Verified Filtering (MVF) protocol was constructed to compare GPS-derived speed data to dynamic body acceleration (DBA). This was collected by a simultaneously deployed tri-axial accelerometer, to provide a computationally quick method for identifying genuine travelling movement. This method was tested on 11 free-ranging lions ( Panthera leo ) within the Kgalagadi Transfrontier park in the Kalahari Desert, fitted with collar-mounted GPS units and tri-axial motion sensors (Daily Diary; DD) recording at 1 and 40 Hz, respectively. The findings support the hypothesis and show that distance moved estimates were, on average, overestimated by > 80 % prior to GPS screening. We present the conceptual and mathematical protocols for screening fix inaccuracy within high resolution GPS datasets. We demonstrate the importance that MVF has for avoiding inaccurate and biased estimates of movement and caution the accuracy of findings from previous studies that employed minimal GPS pre-processing . Throughout, we address the applicability of comparing fine-scale indices of GPS- and motion sensor-borne data in tandem to qualify animal behaviour.

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Review of GPS collar deployments and performance on nonhuman primates

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Cited by 34 publications

References 55 publications

Nonparametric analysis of inter‐individual relations using an attention‐based neural network

Nonparametric analysis of inter‐individual relations using an attention‐based neural network

Effects of short-term isolation on social animals’ behavior: an experimental case study of Japanese macaque

Decision rules for determining terrestrial movement and the consequences for filtering high-resolution GPS tracks – A case study using the African Lion (Panthera leo)

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