High-resolution Tracking Data Research Articles

Relative telencephalon size does not affect collective motion in the guppy (Poecilia reticulata).

Collective motion is common across all animal taxa, from swarming insects to schools of fish. The collective motion requires intricate behavioral integration among individuals, yet little is known about how evolutionary changes in brain morphology influence the ability for individuals to coordinate behavior in groups. In this study, we utilized guppies that were selectively bred for relative telencephalon size, an aspect of brain morphology that is normally associated with advanced cognitive functions, to examine its role in collective motion using an open-field assay. We analyzed high-resolution tracking data of same-sex shoals consisting of 8 individuals to assess different aspects of collective motion, such as alignment, attraction to nearby shoal members, and swimming speed. Our findings indicate that variation in collective motion in guppy shoals might not be strongly affected by variation in relative telencephalon size. Our study suggests that group dynamics in collectively moving animals are likely not driven by advanced cognitive functions but rather by fundamental cognitive processes stemming from relatively simple rules among neighboring individuals.

Smarter foragers do not forage smarter: a test of the diet hypothesis for brain expansion.

A leading hypothesis for the evolution of large brains in humans and other species is that a feedback loop exists whereby intelligent animals forage more efficiently, which results in increased energy intake that fuels the growth and maintenance of large brains. We test this hypothesis for the first time with high-resolution tracking data from four sympatric, frugivorous rainforest mammal species (42 individuals) and drone-based maps of their predominant feeding trees. We found no evidence that larger-brained primates had more efficient foraging paths than smaller brained procyonids. This refutes a key assumption of the fruit-diet hypothesis for brain evolution, suggesting that other factors such as temporal cognition, extractive foraging or sociality have been more important for brain evolution.

Self-reported and tracked nighttime smartphone use and their association with overweight and cardiometabolic risk markers

Nighttime smartphone use is associated with sleep problems, which in turn have a bidirectional association with overweight. We aim to investigate whether nighttime smartphone use and sleep are related to overweight and metabolic dysfunction in adult populations. We used data from three population samples (aged 16–89) from the SmartSleep Study, which included survey data (N = 29,838), high-resolution tracking data (N = 3446), follow-up data (N = 1768), and cardiometabolic risk markers (N = 242). Frequent self-reported nighttime smartphone use was associated with 51% higher odds (95% CI: 1.32; 1.70) of overweight compared with no use. Tracked nighttime smartphone use was also associated with overweight. Similar results were found for obesity as an outcome. No consistent associations were found between nighttime smartphone use and cardiometabolic risk markers in a small subsample of healthy young women. Poor sleep quality (vs. good sleep quality) was associated with overweight (OR = 1.19, 85% CI: 1.10; 1.28). Overall, frequent nighttime smartphone use was consistently associated with overweight and a higher BMI across diverse population samples. The bidirectional interplay between nighttime smartphone use, sleep, and overweight may create a vicious circle of metabolic dysfunction over time. Therefore, nighttime smartphone use may be a potential target point for public health interventions to reduce overweight at the population level.

Multi-scale movement syndromes for comparative analyses of animal movement patterns

BackgroundAnimal movement is a behavioral trait shaped by the need to find food and suitable habitat, avoid predators, and reproduce. Using high-resolution tracking data, it is possible to describe movement in greater detail than ever before, which has led to many discoveries about the behavioral strategies of particular species. Recently, enough data been become available to enable a comparative approach, which has the potential to uncover general causes and consequences of variation in movement patterns, but which must be scale specific. MethodsHere we introduce a new multi-scale movement syndrome (MSMS) framework for describing and comparing animal movements and use it to explore the behavior of four sympatric mammals. MSMS incorporates four hierarchical scales of animal movement: (1) fine-scale movement steps which accumulate into (2) daily paths which then, over weeks or months, form a (3) life-history phase. Finally, (4) the lifetime track of an individual consists of multiple life-history phases connected by dispersal or migration events. We suggest a series of metrics to describe patterns of movement at each of these scales and use the first three scales of this framework to compare the movement of 46 animals from four frugivorous mammal species.ResultsWhile subtle differences exist between the four species in their step-level movements, they cluster into three distinct movement syndromes in both path- and life-history phase level analyses. Differences in feeding ecology were a better predictor of movement patterns than a species’ locomotory or sensory adaptations.ConclusionsGiven the role these species play as seed dispersers, these movement syndromes could have important ecosystem implications by affecting the pattern of seed deposition. This multiscale approach provides a hierarchical framework for comparing animal movement for addressing ecological and evolutionary questions. It parallels scales of analyses for resource selection functions, offering the potential to connect movement process with emergent patterns of space use.

Cohort profile: The SmartSleep Study, Denmark, combining evidence from survey, clinical and tracking data

PurposeThe SmartSleep Study is established to comprehensively assess the impact of night-time smartphone use on sleep patterns and health. An innovative combination of large-scale repeated survey information, high-resolution sensor-driven smartphone...

Super-resolution in brain positron emission tomography using a real-time motion capture system

Super-resolution (SR) is a methodology that seeks to improve image resolution by exploiting the increased spatial sampling information obtained from multiple acquisitions of the same target with accurately known sub-resolution shifts. This work aims to develop and evaluate an SR estimation framework for brain positron emission tomography (PET), taking advantage of a high-resolution infra-red tracking camera to measure shifts precisely and continuously. Moving phantoms and non-human primate (NHP) experiments were performed on a GE Discovery MI PET/CT scanner (GE Healthcare) using an NDI Polaris Vega (Northern Digital Inc), an external optical motion tracking device. To enable SR, a robust temporal and spatial calibration of the two devices was developed as well as a list-mode Ordered Subset Expectation Maximization PET reconstruction algorithm, incorporating the high-resolution tracking data from the Polaris Vega to correct motion for measured line of responses on an event-by-event basis. For both phantoms and NHP studies, the SR reconstruction method yielded PET images with visibly increased spatial resolution compared to standard static acquisitions, allowing improved visualization of small structures. Quantitative analysis in terms of SSIM, CNR and line profiles were conducted and validated our observations. The results demonstrate that SR can be achieved in brain PET by measuring target motion in real-time using a high-resolution infrared tracking camera.

Night-time smartphone use, sleep duration, sleep quality, and menstrual disturbances in young adult women: A population-based study with high-resolution tracking data.

To explore the relationship among night-time smartphone use, sleep duration, sleep quality, and menstrual disturbances in young adult women. Women aged 18-40 years were included in the SmartSleep Study in which they objectively tracked their smartphone use via the SmartSleep app between self-reported sleep onset and offset times (n = 764) and responded to a survey (n = 1068), which included background characteristics, sleep duration, sleep quality (Karolinska Sleep Questionnaire), and menstrual characteristics (International Federation of Gynecology and Obstetrics' definitions). The median tracking time was four nights (interquartile range: 2-8). Higher frequency (p = .05) and longer duration (p = .02) of night-time smartphone use were associated with long sleep duration (≥9 h), but not with poor sleep quality or short sleep duration (<7 h). Short sleep duration was associated with menstrual disturbances (OR = 1.84, 95% confidence interval [CI] = 1.09 to 3.04) and irregular menstruation (OR = 2.17, 95% CI = 1.08 to 4.10), and poor sleep quality was associated with menstrual disturbances (OR = 1.43, 95% CI = 1.19 to 1.71), irregular menstruation (OR = 1.34, 95% CI = 1.04 to 1.72), prolonged bleedings (OR = 2.50, 95% CI = 1.44 to 4.43) and short-cycle duration (OR = 1.40, 95% CI = 1.06 to 1.84). Neither duration nor frequency of night-time smartphone use was associated with menstrual disturbances. Night-time smartphone use was associated with longer sleep duration, but not with menstrual disturbances in adult women. Short sleep duration and sleep quality were associated with menstrual disturbances. Further investigation of the effects of night-time smartphone use on sleep and female reproductive function in large prospective studies is needed.

WATLAS: high-throughput and real-time tracking of many small birds in the Dutch Wadden Sea

Tracking animal movement is important for understanding how animals interact with their (changing) environment, and crucial for predicting and explaining how animals are affected by anthropogenic activities. The Wadden Sea is a UNESCO World Heritage Site and a region of global importance for millions of shorebirds. Due to climate change and anthropogenic activity, understanding and predicting movement and space-use in areas like the Wadden Sea is increasingly important. Monitoring and predicting animal movement, however, requires high-resolution tracking of many individuals. While high-resolution tracking has been made possible through GPS, trade-offs between tag weight and battery life limit its use to larger species. Here, we introduce WATLAS (the Wadden Sea deployment of the ATLAS tracking system) capable of monitoring the movements of hundreds of (small) birds simultaneously in the Dutch Wadden Sea. WATLAS employs an array of receiver stations that can detect and localize small, low-cost tags at fine spatial (metres) and temporal resolution (seconds). From 2017 to 2021, we tracked red knots, sanderlings, bar-tailed godwits, and common terns. We use parts of these data to give four use-cases revealing its performance and demonstrating how WATLAS can be used to study numerous aspects of animal behaviour, such as, space-use (both intra- and inter-specific), among-individual variation, and social networks across levels of organization: from individuals, to species, to populations, and even communities. After describing the WATLAS system, we first illustrate space-use of red knots across the study area and how the tidal environment affects their movement. Secondly, we show large among-individual differences in distances travelled per day, and thirdly illustrate how high-throughput WATLAS data allows calculating a proximity-based social network. Finally, we demonstrate that using WATLAS to monitor multiple species can reveal differential space use. For example, despite sanderlings and red knots roosting together, they foraged in different areas of the mudflats. The high-resolution tracking data collected by WATLAS offers many possibilities for research into the drivers of bird movement in the Wadden Sea. WATLAS could provide a tool for impact assessment, and thus aid nature conservation and management of the globally important Wadden Sea ecosystem.

High-resolution tracking data highlight the importance of fallow land during a seasonal habitat bottleneck for a steppe-land specialist

Farmland ecosystems are seasonally dynamic habitats shaped by meteorological fluctuations and anthropogenic land-use changes. Farmland birds may be seasonally constrained with limited foraging and breeding resources (so-called “resource bottlenecks”), especially when there is a loss of natural and semi-natural habitats. During spring, the growth of cereal crops makes a large proportion of arable land unsuitable for specialist steppe birds with narrow vegetation structure requirements. We investigated the existence of a seasonal bottleneck of suitable habitats for steppe birds using the endangered Pin-tailed sandgrouse (Pterocles alchata) as a model species. We used for first time lightweight GPS tags to study habitat selection and movement patterns throughout the cereal crop cycle during three years in north-eastern Spain. We also evaluated if conservation measures promoting suitable vegetation structures for steppe birds (Targeted Fallow Management, TFM) influenced habitat selection. Sandgrouse avoided cereal crops when cereal vegetation was high, resulting in a 30% reduction of suitable habitat area at the start of the breeding season. This proved the existence of a spring habitat bottleneck when sandgrouse only selected open natural habitats and fallows. Sandgrouse similarly selected TFM and conventionally managed fallows during and after the bottleneck, possibly because of their similar vegetation structure and the scarcity of alternative suitable habitats. Halting the ongoing loss of fallow land is paramount for the conservation of steppe birds like sandgrouse because they constitute a key refuge to buffer the impacts of seasonal habitat bottlenecks.

Nighttime smartphone use and changes in mental health and wellbeing among young adults: a longitudinal study based on high-resolution tracking data

Frequent nighttime smartphone use can disturb healthy sleep patterns and may adversely affect mental health and wellbeing. This study aims at investigating whether nighttime smartphone use increases the risk of poor mental health, i.e. loneliness, depressive symptoms, perceived stress, and low life satisfaction among young adults. High-dimensional tracking data from the Copenhagen Network Study was used to objectively measure nighttime smartphone activity. We recorded more than 250,000 smartphone activities during self-reported sleep periods among 815 young adults (university students, mean age: 21.6 years, males: 77%) over 16 weekdays period. Mental health was measured at baseline using validated measures, and again at follow-up four months later. Associations between nighttime smartphone use and mental health were evaluated at baseline and at follow-up using multiple linear regression adjusting for potential confounding. Nighttime smartphone use was associated with a slightly higher level of perceived stress and depressive symptoms at baseline. For example, participants having 1–3 nights with smartphone use (out of 16 observed nights) had on average a 0.25 higher score (95%CI:0.08;0.41) on the Perceived stress scale ranging from 0 to 10. These differences were small and could not be replicated at follow-up. Contrary to the prevailing hypothesis, nighttime smartphone use is not strongly related to poor mental health, potentially because smartphone use is also a social phenomenon with associated benefits for mental health.

Using the VEMCO Positioning System (VPS) to explore fine-scale movements of aquatic species: applications, analytical approaches and future directions

Recent advancements in telemetry have redefined our ability to quantify the fine-scale movements of aquatic animals and derive a mechanistic understanding of movement behaviours. The VEMCO Positioning System (VPS) is a fine-scale commercial positioning system used to generate highly accurate semi-continuous animal tracks. To date, VPS has been used to study 86 species, spanning 25 taxonomic orders. It has provided fine-scale movement data for critical life stages, from tracking day-old turtle hatchlings on their first foray into the sea to adult fish returning to natal rivers to spawn. These high-resolution tracking data have improved our understanding of the movements of species across environmental gradients within rivers, estuaries and oceans, including species of conservation concern and commercial value. Existing VPS applications range from quantifying spatio-temporal aspects of animal space use and key aspects of ecology, such as rate of movement and resource use, to higher-order processes such as interactions among individuals and species. Analytical approaches have seen a move towards techniques that incorporate error frameworks such as autocorrelated kernel density estimators for home range calculations. VPS technology has the potential to bridge gaps in our fundamental understanding of fine-scale ecological and physiological processes for single and multi-species studies under natural conditions. Through a systematic review of the VPS literature, we focus on 4 principle topics: the diversity of species studied, current ecological and ecophysiological applications and data analysis techniques, and we highlight future frontiers of exploration.

Investigating avoidance and attraction responses in lesser black-backed gulls Larus fuscus to offshore wind farms

Movements through or use of offshore wind farms by seabirds while commuting or foraging may increase the potential for collision with turbine blades. Collision risk models provide a method for estimating potential impacts of wind farms on seabird populations, but are sensitive to input parameters, including avoidance rates (ARs). Refining understanding of avoidance through the use of high-resolution empirical movement data has the potential to inform assessments of the collision impacts of offshore wind farms on seabird populations. We assessed the movements of GPS-tagged lesser black-backed gulls Larus fuscus from a breeding colony in northwest England to estimate the species’ AR and avoidance/attraction index (AAI) to nearby offshore wind farms. To investigate both macro- (0-4 km) and meso-scale (0-200 m) responses to wind turbines, we used calculations of AR and AAI based on simulated vs. observed tracks. We found that birds exhibited an AR of -0.15 (95% CI: -0.44 to 0.06), indicating a degree of attraction within 4 km of the wind farms. However, AAI values varied with distance from wind farm boundaries, with a degree of avoidance displayed between 3 and 4 km, which weakened as distance bands approach wind farm boundaries. Meso-scale avoidance/attraction was assessed with regard to the nearest individual turbine, and flight height relative to the rotor height range (RHR) of the nearest turbine. We found attraction increased below the RHR at distances &lt;70 m, while avoidance increased within the RHR at distances approaching the turbine. We explore how high-resolution tracking data can be used to improve our knowledge of L. fuscus avoidance/attraction behaviour to established wind farms, and so inform assessments of collision impacts.

Simultaneous Monitoring of the Same Animals with PIT Tags and Sensor Nodes Causes No System Interference

Recent technological advances have multiplied the variety of biologgers used in wildlife research, particularly with small-bodied animals. Passive integrated transponders (PIT) have been used for decades to log visits of tagged animals at reader-equipped artificial feeders or roost boxes. More recently, novel miniaturized sensor nodes can collect data on social encounters among tagged individuals in any location. Combining these systems allows researchers to gather high-resolution tracking data on certain individuals from their long-term PIT-tagged animal populations. However, there can be a risk of interference among tracking systems. Here we tested whether placing an additional biologging sensor on top of a PIT tag might attenuate the magnetic field reaching the PIT tag and, in turn, hamper reading success of the radio-frequency identification (RFID) reader. We also evaluated data transmission by a digital sensor node in the presence of a magnetic field created by the RFID antenna. The combination of this RFID system and wireless biologging sensors works without error, suggesting that the simultaneous use of PIT tags and other digital biologgers, e.g., miniaturized GPS-loggers, should also work together properly when communication channels do not overlap. The combination of long-term monitoring with PIT tags and short-term tracking with biologging sensor nodes creates exciting new opportunities to gather rich social data when individuals are not present at RFID reader stations.

Effects of multiple stressors on fish shoal collective motion are independent and vary with shoaling metric

Collective movement is critical to the survival of some animals. Despite substantial progress in understanding animal collectives such as fish shoals and bird flocks, it is unknown how collective behaviour is affected by changes in multiple environmental conditions that can interact as stressors. Using a fully factorial repeated-measures design, we tested the independent and combined effects of darkness and acoustic noise on the collective motion of three-spined sticklebacks, Gasterosteus aculeatus, quantified using high-resolution tracking data from video. Corresponding to the importance of vision in shoaling behaviour, darkness increased nearest-neighbour distances and reduced coordination, measured as speed correlations and differences in directional heading between nearest neighbours. Although individual swimming speeds were not impacted by darkness, the group's centre of mass was slower, an emergent effect of reduced polarisation (i.e. greater group disorder) in darkness. While additional acoustic noise had no detectable effect on these variables, it altered group structure, with fish being more likely to be found side by side one another. Fish were also further from the arena wall (i.e. showed reduced wall following) when there was additional acoustic noise. There was only weak evidence for additive or interactive effects of the two stressors. Across the different environmental contexts, there were consistent, repeatable differences between groups (i.e. group personality variation) in the speed, turning angle and distance from the arena wall of individuals, but the only collective behaviour that was repeatable was group polarization. Our study demonstrates that multiple stressors can have independent effects that impact different aspects of behaviour and highlights the need for empirical studies on multiple stressors as their effects can be unpredictable.

Passive acoustic methods for tracking the 3D movements of small cetaceans around marine structures.

A wide range of anthropogenic structures exist in the marine environment with the extent of these set to increase as the global offshore renewable energy industry grows. Many of these pose acute risks to marine wildlife; for example, tidal energy generators have the potential to injure or kill seals and small cetaceans through collisions with moving turbine parts. Information on fine scale behaviour of animals close to operational turbines is required to understand the likely impact of these new technologies. There are inherent challenges associated with measuring the underwater movements of marine animals which have, so far, limited data collection. Here, we describe the development and application of a system for monitoring the three-dimensional movements of cetaceans in the immediate vicinity of a subsea structure. The system comprises twelve hydrophones and software for the detection and localisation of vocal marine mammals. We present data demonstrating the systems practical performance during a deployment on an operational tidal turbine between October 2017 and October 2019. Three-dimensional locations of cetaceans were derived from the passive acoustic data using time of arrival differences on each hydrophone. Localisation accuracy was assessed with an artificial sound source at known locations and a refined method of error estimation is presented. Calibration trials show that the system can accurately localise sounds to 2m accuracy within 20m of the turbine but that localisations become highly inaccurate at distances greater than 35m. The system is currently being used to provide data on rates of encounters between cetaceans and the turbine and to provide high resolution tracking data for animals close to the turbine. These data can be used to inform stakeholders and regulators on the likely impact of tidal turbines on cetaceans.

Interactions between angler movement behaviour and an invasive seaweed with ecosystem engineering properties in a marine recreational fishery

The establishment of non-native, habitat-forming seaweeds into new areas may trigger changes in ecosystem functioning, including the spatial redistribution of native biodiversity. These changes can in turn affect socio-economic systems. We studied the question whether the spatial behaviour of marine anglers is altered by the presence of a non-native seaweed using a novel image-based method to measure fisher movements. A Hidden Markov Model (HMM) was applied to high resolution tracking data of marine recreational boat anglers exploiting a coastal fishery half covered by a recently introduced tropical seaweed, Halimeda incrassata. We then examined if the presence of the non-native seaweed affected the transition probability between two key behavioural states of the anglers: searching and fishing. The analysis revealed a significant effect of the seaweed presence at site-level on angler movement behaviour, but in the opposite direction that we predicted: the presence of the non-native seaweed led a decrease in the use of invaded patches although these patches are known to host an increased fish abundance. Invaded sites thus were attractive to the target fishes, but not for anglers, leading to repulsion. We conclude that, at the patch level non-native habitat forming seaweeds can exert substantial impacts on fisher behaviour in marine recreational fisheries. We discuss future studies needed to shed light to the social-economic impact of H. incrassata for local temperate recreational fisheries.

Spatial ecology of male hippopotamus in a changing watershed

The obligate dependency of the common hippopotamus, Hippopotamus amphibius, on water makes them particularly vulnerable to hydrological disturbances. Despite the threats facing this at-risk species, there is a lack of information regarding H. amphibius spatial ecology. We used high-resolution tracking data of male H. amphibius to assess home range size, movement mode (e.g. residency and migratory movements), and resource selection patterns. We compared these results across seasons to understand how hydrological variability influences H. amphibius movement. Our study watershed has been severely impacted by anthropogenic water abstraction causing the river to stop flowing for prolonged periods. We observed H. amphibius movements to be highly constrained to the river course with grassy floodplains being their preferred habitat. Dominant and small sub-adult males displayed year-round residency in/near river pools and had smaller home ranges compared to large sub-adults. During the dry season, large sub-adult males made significant (~15 km) upstream movements. The larger home range size of large sub-adults can be attributed to the elevated levels of migratory and exploratory activities to limit conspecific aggression as the river dries. Our observations provide insight into how future changes in water flow may influence male H. amphibius movements and populations through density-dependent effects.

GPS telemetry for small seabirds: using hidden Markov models to infer foraging behaviour of Common Diving Petrels (Pelecanoides urinatrix urinatrix)

ABSTRACTCommon Diving Petrels (Pelecanoides urinatrix urinatrix) are distributed widely around coastal New Zealand and breed primarily on predator-free offshore islands. Despite their ubiquity, little is known of their at-sea foraging movement, as their small size and frequent diving behaviour have presented logistic challenges to obtaining high-resolution tracking data that reflect detailed movement patterns. We present the first attempt to collect detailed (5 min/fix) movement trajectories of Common Diving Petrels, using miniaturised global positioning system (GPS) loggers. Adult breeding Common Diving Petrels were tracked for single foraging trips from Tiritiri Matangi Island near Auckland, New Zealand. We applied a hidden Markov model to infer behavioural states from the movement data, and a kernel density estimation on the GPS fixes of area-restricted behaviour to characterise feeding hotspots. We found that Common Diving Petrels in the Hauraki Gulf are local foragers during their breeding season, and the model results indicated that foraging accounted for two-thirds of all behaviour states. At-sea foraging activities of the birds were concentrated in areas up to 30 km from their colony. Our findings reveal the utility of combining GPS tracking with behavioural models to infer the foraging behaviours and space-use patterns of small seabird taxa.

Identification of Griffon Vulture\u2019s Flight Types Using High-Resolution Tracking Data

Being one of the most frequently killed raptors by collision with wind turbines, little is known about the Griffon vulture’s flight strategies and behaviour in a fine scale. In this study, we used high-resolution tracking data to differentiate between the most frequently observed flight types of the Griffon, and evaluated the performance of our proposed approach by an independent observation during a period of 4 weeks of fieldwork. Five passive flight types including three types of soaring and two types of gliding were discriminated using the patterns of measured GPS locations. Of all flight patterns, gliding was classified precisely (precision = 88%), followed by linear and thermal soaring with precision of 83 and 75%, respectively. The overall accuracy of our classification was 70%. Our study contributes a baseline technique using high-resolution tracking data for the classification of flight types, and is one step forward towards the collision management of this species.

Repeatable group differences in the collective behaviour of stickleback shoals across ecological contexts.

Establishing how collective behaviour emerges is central to our understanding of animal societies. Previous research has highlighted how universal interaction rules shape collective behaviour, and that individual differences can drive group functioning. Groups themselves may also differ considerably in their collective behaviour, but little is known about the consistency of such group variation, especially across different ecological contexts that may alter individuals' behavioural responses. Here, we test if randomly composed groups of sticklebacks differ consistently from one another in both their structure and movement dynamics across an open environment, an environment with food, and an environment with food and shelter. Based on high-resolution tracking data of the free-swimming shoals, we found large context-associated changes in the average behaviour of the groups. But despite these changes and limited social familiarity among group members, substantial and predictable behavioural differences between the groups persisted both within and across the different contexts (group-level repeatability): some groups moved consistently faster, more cohesively, showed stronger alignment and/or clearer leadership than other groups. These results suggest that among-group heterogeneity could be a widespread feature in animal societies. Future work that considers group-level variation in collective behaviour may help understand the selective pressures that shape how animal collectives form and function.