Movement-based Methods Research Articles

Evaluating movement-based methods for estimating the frequency and timing of parturition in mule deer

BackgroundInformation on reproduction of harvested species such as mule deer (Odocoileus hemionus) is vital for conservation and management. Furthermore, parturition in ungulates may be detected using patterns of movement logged by GPS transmitters. Several movement-based methods have been developed to detect parturition in ungulates including the Peterson method, behavioral change point analysis (BCPA), rolling minimum convex polygons (rMCP), individual-based method (IBM), and population-based method (PBM). Our objectives were to (1) test the accuracy and the precision of each previously described method and (2) develop an improved method optimized for mule deer that incorporated aspects of the other methods.MethodsWe determined parturition timing and status for female mule deer fitted with GPS collars and implanted with vaginal implant transmitters (VITs). We used movement patterns before and after parturition to set movement thresholds for each movement-based method. Following model training, we used location and birth date data from an external dataset to test the effectiveness of each movement-based method. Additionally, we developed a novel method for detecting parturition called the analysis of parturition indicators (API). We used two regression analyses to determine the accuracy and precision of estimates generated by each method.ResultsThe six methods we employed varied in accuracy, with the API, rMCP, and BCPA being most accurate. Precision also varied among methods, with the API, rMCP, and PBM generating the most precise estimates of parturition dates. The API and the rMCP performed similarly and better overall than any of the other existing methods.ConclusionsWe found that movement-based methods could be used to accurately and precisely detect parturition in mule deer. Further, we determined that the API and rMCP methods had the greatest overall success at detecting parturition in mule deer. The relative success of the API and rMCP may be attributed to the fact that both methods use home range size to detect parturition and are validated using known parturition dates of collared deer. We present the API as an efficient method of estimating birth status and timing of parturition of mule deer fitted with GPS transmitters, as well as affirm the effectiveness of a previously developed method, rMCP.

Novel Movement-Based Methods for the Calibration of Colocated Multiple-Input Multiple-Output Radars

Novel Movement-Based Methods for the Calibration of Colocated Multiple-Input Multiple-Output Radars

Are opportunistic captures of neonate ungulates biasing relative estimates of litter size?

The capture of neonate ungulates allows for the collection of valuable ecological data, including estimates of litter size. However, varied methods used to capture neonate ungulates can result in sampling biases. Our objective was to determine if opportunistic captures of neonate ungulates (i.e., locating neonates by visually scanning for adult females displaying postpartum behaviors) bias relative estimates of litter size and investigate potential causes if a bias does exist. We analyzed data from 161 litters of mule deer (Odocoileus hemionus) sampled using three different capture methods during 2019–2021 in Utah, USA. Estimates of litter size derived from opportunistic captures were smaller than estimates derived from movement-based captures or captures completed with the aid of vaginal implant transmitters (VITs). Age at capture was inversely related to estimates of litter size and likely influenced the detection bias associated with opportunistic captures. Neonates captured opportunistically were not older than neonates captured using movement-based methods, but were older than neonates captured with the aid of VITs. Distance between neonates from the same litter did not influence estimates of litter size. Researchers should be aware of the biases associated with different capture methods and use caution when interpreting data among multiple capture methods. Estimates of litter size derived from opportunistic captures should not be compared to estimates of litter size derived from alternative capture methods without accounting for the detection bias we observed.

Mind the gap: The 4M Bridge Between 4E-Cognition and Movement-Based Design

Along with technology trends like extended reality, wearables, IoT, and exergames, new design approaches have emerged, focusing on full-body interactions by actively working with the lived body’s capacity to sense, feel, and create. Thus, designers are recommended to use movement as part of the design activity when designing for and of movement, regardless of the targeted application domain. However, designing for bodily experiences is challenging. We have identified a gap of no movement-based design framework available, including the moving body as the centre part and core material of the design processes. We recognise the human body is more than a physical object in the world, but a feeling, perceptualising body, that creates meaning in interaction with the environment. It thus frustrates and challenges us to reach a bodily grounded design process embracing the lived body. A common framework informed by the theoretical aspect of embodied cognition and the practical element of movement design can be a starting point for embodied design research. Recognising these challenges, we see a need for creating a bridge between practice and theory. Based on the bridging concept from Dalsgaard and Dindler, this paper presents a movement-based design framework to bridge the abstract idea of embodied cognition theory with the 4E perspectives of embodied, embedded, enactive and extended and concrete movement-based design practices. We created a movement-based design framework structuring the movement-based methods of different perspectives. The 4M model we propose contains three types of facilitator-mediated methods: 1) Mood-setters stimulating a creative body being, 2) Movement-based design methods for creating immersion in creative bodily activities, and 3) Movement concepts as knowledge and evidence for developing and validating movement artefacts. Besides the facilitator cards, the participants have access to Modifiers that can be used in conjunction with the other methods as creative inspiration for exploring, trying, or performing new movement possibilities.

Using low-fix rate GPS telemetry to expand estimates of ungulate reproductive success

BackgroundPopulation parameters such as reproductive success are critical for sustainably managing ungulate populations, however obtaining these data is often difficult, expensive, and invasive. Movement-based methods that leverage Global Positioning System (GPS) relocation data to identify parturition offer an alternative to more invasive techniques such as vaginal implant transmitters, but thus far have only been applied to relocation data with a relatively fine (one fix every < 8 h) temporal resolution. We employed a machine learning method to classify parturition/calf survival in cow elk in southeastern Kentucky, USA, using 13-h GPS relocation data and three simple movement metrics, training a random forest on cows that successfully reared their calf to a week old.ResultsWe developed a decision rule based upon a predicted probability threshold across individual cow time series, accurately classifying 89.5% (51/57) of cows with a known reproductive status. When used to infer status of cows whose reproductive outcome was unknown, we classified 48.6% (21/38) as successful, compared to 85.1% (40/47) of known-status cows.ConclusionsWhile our approach was limited primarily by fix acquisition success, we demonstrated that coarse collar fix rates did not limit inference if appropriate movement metrics are chosen. Movement-based methods for determining parturition in ungulates may allow wildlife managers to extract more vital rate information from GPS collars even if technology and related data quality are constrained by cost.

Eye Movement-Based Methods for Human-System Interaction. A Comparison of Different Approaches

The paper focuses on utilizing eye movements for controlling computer programs. Four different approaches were considered, including gazing at an element, blinking, and two solutions for eye gestures. The methods were implemented in a simple photo viewer. However, the developed functionalities can be utilized in other applications (switching e-book pages or on-screen keyboard elements). Various sizes for gazed components were verified, as well as the time required for performing particular actions, the number of unwanted element choices, and needed gesture repetitions. The methods were also assessed by the participants of the experiments. Based on the obtained results, it may be reasoned that components of size 200px are convenient for the application control. The users’ opinions and the experiments’ outcomes revealed that the gaze-based method and gestures based on joining points are satisfactory solutions.

Reptiles on the wrong track? Moving beyond traditional estimators with dynamic Brownian Bridge Movement Models

BackgroundAnimal movement expressed through home ranges or space-use can offer insights into spatial and habitat requirements. However, different classes of estimation methods are currently instinctively applied to answer home range, space-use or movement-based research questions regardless of their widely varying outputs, directly impacting conclusions. Recent technological advances in animal tracking (GPS and satellite tags), have enabled new methods to quantify animal space-use and movement pathways, but so far have primarily targeted mammal and avian species.MethodsMost reptile spatial ecology studies only make use of two older home range estimation methods: Minimum Convex Polygons (MCP) and Kernel Density Estimators (KDE), particularly with the Least Squares Cross Validation (LSCV) and reference (href) bandwidth selection algorithms. These methods are frequently applied to answer space-use and movement-based questions. Reptile movement patterns are unique (e.g., low movement frequency, long stop-over periods), prompting investigation into whether newer movement-based methods –such as dynamic Brownian Bridge Movement Models (dBBMMs)– apply to Very High Frequency (VHF) radio-telemetry tracking data. We simulated movement data for three archetypical reptile species: a highly mobile active hunter, an ambush predator with long-distance moves and long-term sheltering periods, and an ambush predator with short-distance moves and short-term sheltering periods. We compared traditionally used estimators, MCP and KDE, with dBBMMs, across eight feasible VHF field sampling regimes for reptiles, varying from one data point every four daylight hours, to once per month.ResultsAlthough originally designed for GPS tracking studies, dBBMMs outperformed MCPs and KDE href across all tracking regimes in accurately revealing movement pathways, with only KDE LSCV performing comparably at some higher frequency sampling regimes. However, the LSCV algorithm failed to converge with these high-frequency regimes due to high site fidelity, and was unstable across sampling regimes, making its use problematic for species exhibiting long-term sheltering behaviours. We found that dBBMMs minimized the effect of individual variation, maintained low error rates balanced between omission (false negative) and commission (false positive), and performed comparatively well even under low frequency sampling regimes (e.g., once a month).ConclusionsWe recommend dBBMMs as a valuable alternative to MCP and KDE methods for reptile VHF telemetry data, for research questions associated with space-use and movement behaviours within the study period: they work under contemporary tracking protocols and provide more stable estimates. We demonstrate for the first time that dBBMMs can be applied confidently to low-resolution tracking data, while improving comparisons across regimes, individuals, and species.

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue

Introduction: Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices. Method: This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.

Exploring how material cues drive sensorimotor prediction across different levels of autistic-like traits

Recent research proposes that sensorimotor difficulties, such as those experienced by many autistic people, may arise from atypicalities in prediction. Accordingly, we examined the relationship between non-clinical autistic-like traits and sensorimotor prediction in the material-weight illusion, where prior expectations derived from material cues typically bias one’s perception and action. Specifically, prediction-related tendencies in perception of weight, gaze patterns, and lifting actions were probed using a combination of self-report, eye-tracking, motion-capture, and force-based measures. No prediction-related associations between autistic-like traits and sensorimotor control emerged for any of these variables. Follow-up analyses, however, revealed that greater autistic-like traits were correlated with reduced adaptation of gaze with changes in environmental uncertainty. These findings challenge proposals of gross predictive atypicalities in autistic people, but suggest that the dynamic integration of prior information and environmental statistics may be related to autistic-like traits. Further research into this relationship is warranted in autistic populations, to assist the development of future movement-based coaching methods.

Movement-based methods to infer parturition events in migratory ungulates

Long-distance migrations by ungulate species are a globally imperiled natural phenomenon and conservation of them requires monitoring population vital rates. Satellite telemetry tracking is widely used for understanding the spatial distribution and movement of animals, especially migratory animals in remote environments. Recently, analytical methods have been developed to infer parturition events from movement data in multiple species that calve in isolation, but to date such methods have not been tested on animals that both migrate and spatially aggregate during calving. We applied two movement-based methods developed to infer parturition in nonmigratory woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)) to 241 reproductive seasons spanning 6 years of GPS data from migratory barren-ground caribou (Rangifer tarandus granti J.A. Allen, 1902). We compared results from both methods to data from aerial surveys of collared females during the calving period. We found that each movement-based method had ∼80% overall accuracy to identify calving events, with interannual variation ranging from 61% to 100%. When we considered instances when the two analytical methods agreed on parturition outcome, the accuracy increased to 89% with an annual range of 73%–100%. Using these methods, we identified marked interannual differences in peak calving dates and higher parturition rates than previously reported for this caribou herd. The successful application of these analyses to a migratory, gregarious ungulate suggests a broader applicability of the methodology.

Going through the motions: incorporating movement analyses into disease research.

Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at the population scale, especially for wildlife diseases. In simplifying the contact process, we ignore the heterogeneities in host movements that complicate the real world, and overlook their impact on spatiotemporal patterns of disease burden. Movement ecology offers a set of tools that help unpack the transmission process, letting researchers more accurately model how animals within a population interact and spread pathogens. Analytical techniques from this growing field can also help expose the reverse process: how infection impacts movement behaviours, and therefore other ecological processes like feeding, reproduction, and dispersal. Here, we synthesise the contributions of movement ecology in disease research, with a particular focus on studies that have successfully used movement-based methods to quantify individual heterogeneity in exposure and transmission risk. Throughout, we highlight the rapid growth of both disease and movement ecology and comment on promising but unexplored avenues for research at their overlap. Ultimately, we suggest, including movement empowers ecologists to pose new questions, expanding our understanding of host-pathogen dynamics and improving our predictive capacity for wildlife and even human diseases.

Inferring parturition and neonate survival from movement patterns of female ungulates: a case study using woodland caribou

Analyses of animal movement data have primarily focused on understanding patterns of space use and the behavioural processes driving them. Here, we analyzed animal movement data to infer components of individual fitness, specifically parturition and neonate survival. We predicted that parturition and neonate loss events could be identified by sudden and marked changes in female movement patterns. Using GPS radio-telemetry data from female woodland caribou (Rangifer tarandus caribou), we developed and tested two novel movement-based methods for inferring parturition and neonate survival. The first method estimated movement thresholds indicative of parturition and neonate loss from population-level data then applied these thresholds in a moving-window analysis on individual time-series data. The second method used an individual-based approach that discriminated among three a priori models representing the movement patterns of non-parturient females, females with surviving offspring, and females losing offspring. The models assumed that step lengths (the distance between successive GPS locations) were exponentially distributed and that abrupt changes in the scale parameter of the exponential distribution were indicative of parturition and offspring loss. Both methods predicted parturition with near certainty (>97% accuracy) and produced appropriate predictions of parturition dates. Prediction of neonate survival was affected by data quality for both methods; however, when using high quality data (i.e., with few missing GPS locations), the individual-based method performed better, predicting neonate survival status with an accuracy rate of 87%. Understanding ungulate population dynamics often requires estimates of parturition and neonate survival rates. With GPS radio-collars increasingly being used in research and management of ungulates, our movement-based methods represent a viable approach for estimating rates of both parameters.

Dynamic Approach to Space and Habitat Use Based on Biased Random Bridges

BackgroundAlthough habitat use reflects a dynamic process, most studies assess habitat use statically as if an animal's successively recorded locations reflected a point rather than a movement process. By relying on the activity time between successive locations instead of the local density of individual locations, movement-based methods can substantially improve the biological relevance of utilization distribution (UD) estimates (i.e. the relative frequencies with which an animal uses the various areas of its home range, HR). One such method rests on Brownian bridges (BBs). Its theoretical foundation (purely and constantly diffusive movements) is paradoxically inconsistent with both HR settlement and habitat selection. An alternative involves movement-based kernel density estimation (MKDE) through location interpolation, which may be applied to various movement behaviours but lacks a sound theoretical basis.Methodology/Principal FindingsI introduce the concept of a biased random (advective-diffusive) bridge (BRB) and show that the MKDE method is a practical means to estimate UDs based on simplified (isotropically diffusive) BRBs. The equation governing BRBs is constrained by the maximum delay between successive relocations warranting constant within-bridge advection (allowed to vary between bridges) but remains otherwise similar to the BB equation. Despite its theoretical inconsistencies, the BB method can therefore be applied to animals that regularly reorientate within their HRs and adapt their movements to the habitats crossed, provided that they were relocated with a high enough frequency.Conclusions/SignificanceBiased random walks can approximate various movement types at short times from a given relocation. Their simplified form constitutes an effective trade-off between too simple, unrealistic movement models, such as Brownian motion, and more sophisticated and realistic ones, such as biased correlated random walks (BCRWs), which are too complex to yield functional bridges. Relying on simplified BRBs proves to be the most reliable and easily usable way to estimate UDs from serially correlated relocations and raw activity information.