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49 results for “tracking movements”
Fig. 4. Most-probable tracks for sailfish I, II in Short-term movements and habitat preferences of sailfish, Istiophorus platypterus (Istiophoridae), along the southeast coast of Brazil
Fig. 4. Most-probable tracks for sailfish I, II, III, and IV fitted with Kalman Filter State-Space Model.
Movement data from a Malayan krait (Bungarus candidus) tracked in the Sakaerat Biosphere Reserve, Nakhon Ratchasima province, Thailand
<p>Movement data gained through radio-telemetry of a single adult male Malayan krait (<em>Bungarus candidus</em>) among a protected forest of the Sakaerat Biosphere Reserve in Nakhon Ratchasima province, Thailand for a period of 103 days (with 90 location fixes/datapoints).</p> <p> </p> <p>BUCA40_movement_data.csv file column headings:</p> <p>track_ID: number corresponding to the location check datapoint</p> <p>animal_ID: <em>B. candidus</em> identifier number from the Sakaerat tracking project</p> <p>datetime: Date and time when the snake was located (mm/dd/yyyy hh:mm)</p> <p>easting: UTM easting (UTM Zone 47N; Datum WGS84)</p> <p>northing: UTM northing (UTM Zone 47N; Datum WGS84)</p> <p>utm_zone: Universal Transverse Mercator zone (47N World Geodetic System 84)</p> <p>GPS_accuracy: GPS location accuracy in meters (m)</p> <p>behavior: The animal’s behavior observed during the location check (e.g. sheltering, foraging, moving, or feeding)</p> <p>shelter_type: Identified selected shelter type</p> <p>habitat_type: Land-use type where the snake was located </p>
Plastid and peroxisome movement tracks in the root cells of Arabidopsis thaliana
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Upper-body movements: precise tracking of human motion using inertial sensors
<p>The <em>Upper-body movements: precise tracking of human motion using inertial sensors</em> is a dataset composed of 11 participants' IMU data (5 women + 6 men). This collection is divided into 6 motion sets containing different motions for the upper-body.</p> <p><strong>Folder Structure</strong></p> <p>subject -> set -> IMU position -> file</p> <p>e.g. subject01 -> set6 -> forearm -> Accelerometer.txt</p> <p><strong>IMU placement </strong></p> <p>For data collection participants wore 4 IMUs:</p> <ul> <li>1 on the chest</li> <li>1 on the right arm</li> <li>1 on the right forearm</li> <li>1 on the right hand.</li> </ul> <p><strong>Sets</strong></p> <p>Each set includes:</p> <ul> <li> set1 - flexion/extension of the forearm; abduction/adduction of the arm; anatomical position</li> <li> set2 - flexion/extension of the wrist; radial/ulnar deviation of the wrist; anatomical position</li> <li> set3 - flexion/extension and lateral flexion of the torso; anatomical position</li> <li> set4 - flexion/extension of the arm; flexion/extension of the torso; anatomical position</li> <li> set5 - flexion/extension of the arm; anatomical position; anatomical position</li> <li> set6 - flexion/extension of the torso; flexion/extension of the arm; anatomical position</li> </ul> <p><strong>Annotations</strong></p> <p>This dataset is accompanied by the<em> annotations.csv</em> file.<br> Each file row present "Set,Subject,Category,Segment,Type,Init,End":</p> <ul> <li>Set - sets 1-6</li> <li>Subject - participant ID</li> <li>Category - relative or absolute. Refers to the joint angle.</li> <li>Absolute if the angle is obtained considering an anatomical plane as reference.</li> <li>Relative if the angle is obtained from one segment in relation to another.</li> <li>Type - segment at action (torso; right_arm_forearm; wrist; right_arm_sagittal)</li> <li>Init/End - time in seconds, describing the begin and end of the motion, respectively.</li> </ul> <p> </p>
LRP predicts smooth pursuit eye movement onset during the ocular tracking of self-generated movements
<p>Dataset relative to the following publication:</p> <p>Chen, J., Valsecchi, M. & Gegenfurtner, K.R. (2016). LRP predicts smooth pursuit eye movement onset during the ocular tracking of self-generated movements. <em>Journal of Neurophysiology, </em>in press</p> <p>Each folder contains the data relative to one experiment and the script that was used to generate them. Please refer to "Description on data format.txt" for the usage of the data.</p> <p>Additional information can be deducted from the experimental scripts.</p>
Role of motor execution in the ocular tracking of self-generated movements
<p>Dataset relative to the following publication:</p> <p>Chen, J., Valsecchi, M. & Gegenfurtner, K.R. (2016). Role of motor execution in the ocular tracking of self-generated movements. <em>Journal of Neurophysiology, </em>DOI: 10.1152/jn.00574.2016</p> <p>Please refer to "data description.txt" for details about the data. Additional information can be deducted from the experimental scripts.</p>
Tracking movements in an endangered capercaillie population using DNA-tagging
<p>Knowing the location and movements of individuals at various temporal and spatial scales is an important facet of behavior and ecology. In threatened populations, movements that would ensure gene flow and population viability are often challenged by habitat fragmentation. Also in those endangered populations capturing and handling individuals to tag them, or to obtain tissue samples, can present additional challenges. DNA tagging, i.e. non-invasive individual identification of samples, can reveal movement patterns. We used fecal material genetically assigned to individuals to indirectly track movements of a large-bodied, endangered forest bird, Cantabrian capercaillie (<em>Tetrao urogallus cantabricus</em>). We wanted to know how the birds were using the fragmented forest landscape, and whether they showed fidelity to display areas. We used multi-event capture-recapture models to estimate fidelity to display areas among three consecutive mating seasons. We identified 127 individuals, and registered movements of 22 females and 48 males. Most observed movements were as expected relatively short, concentrated around display areas. We did not find differences in movement distances between females and males within mating seasons, or between them. Fidelity to display areas among seasons was 0.62 (± 0.12 SE) for females and 0.77 (± 0.07 SE) for males. The best CR model suggested no sex or season effects. Several longer movements, up to 9.9 km, linked distant display areas, demonstrating that Cantabrian capercaillies were able to move between different parts of the study area, complementing previous studies on gene flow. Those longer movements may be taking birds out of the study area, and into historical capercaillie territories, which still include substantial forest cover. The non-invasive DNA tagging approach provided a much larger sample size than would have been feasible with direct tracking. Lack of information on the social status of individuals and timing of movements are some disadvantages of DNA tagging.</p>
DATASET: Tracking microbial movement in saturated media with spectral induced polarization
<p>Dataset for Tracking microbial movement in saturated media with spectral induced polarization by Saneiyan et al. </p> <p> </p> <p><em>Abstract</em></p> <p>Pathogenic microorganisms in the subsurface can contaminate the soil and water supplies potentially posing great danger to human health. Early contamination detection routines rely on sparse direct sampling which is spatiotemporally limited. Thus, the path of microorganisms in the subsurface remains ambiguous and this can cause delays in detection of biohazardous threats. The geophysical spectral induced polarization (SIP) technique, sensitive to microbe’s presence and activity in porous media, is a promising method to monitor microbial transport pathways. Here we evaluated the efficiency of SIP in monitoring the chemotactic movement of Sporosarcina pasteurii in saturated porous media. A cylindrical sample holder was packed with Ottawa sand and saturated with sterile KCl solution to allow free movement of the microbes. The sample holder was oriented vertically and S. pasteurii was introduced at the bottom, allowing the movement of the microbes against gravity, towards a carbon source available at the top of the column. Temporal SIP measurements were collected at 3 regions of the sample holder: bottom (microbial injection point), middle and top (carbon source). Both the real (σ') and the imaginary (σ'') conductivity parts of the SIP signal increased over time with the σ^'' showing a peak signal magnitude following the upward movement of the microbes. We repeated the experiment excluding the carbon source in experiment 2 and omitting microbial injection in experiment 3. Unlike experiment 1, we did not observe any significant SIP signal changes in these two experiments. Our study is indicating there is a strong SIP signal correlation with microbial chemotaxis.</p> <p> </p>
GPS tracking data for: Male mating season range expansion results from an increase in scale of daily movements for a polygynous-promiscuous bird
<p>Males of species with promiscuous mating systems are commonly observed to use larger ranges during the mating season relative to non-mating seasons, which is often attributed to a change in movements related to reproductive activities. However, few studies link seasonal range sizes to variations in daily space use patterns to provide insight into the behavioral mechanisms underlying mating season range expansion. We studied 20 GPS-tagged male wild turkeys (<em>Meleagris gallopavo</em>), a large upland gamebird, during the mating and summer non-mating seasons to test the hypothesis that larger mating season ranges resulted from male wild turkeys expanding the scale of daily movement activities to locate and court females. We delineated mating and non-mating seasons based on the intensity of gobbling, a vocalization tied to courtship behavior, recorded by autonomous recording units distributed across the study area. Mating season ranges were significantly larger than non-mating season ranges. Daily ranges were larger in the mating season, as were distances between roost sites used on consecutive nights. Variance in daily range size was greater in the mating season, but low temporal autocorrelation suggested considerable daily variability in both seasons. We found no evidence that male wild turkeys changed how they distributed daily movements within seasonal ranges, or differences in habitat use, suggesting larger mating season ranges result from male wild turkeys increasing the scale of their daily movements, rather than a systematic shift to a nomadic movement strategy. Likely, the distribution of females is more dynamic and ephemeral compared to other resources, prompting males to traverse larger daily ranges during the mating season to locate and court females. Our work illustrates the utility of using daily movement to understand the behavioral process underlying larger space use patterns.</p>
Analysis of Smooth Pursuit Eye Movements in Clinical Context by Tracking the Target and Eyes
<p>Eyemove dataset obtained at Teikyo University.</p> <p>If you use the dataset, please state clearly that you have used our data.</p> <p>The mp4 files are the video of the examination.<br> Excel files are the position of the optic disc analyzed by SSD and the ocular position data analyzed by VOG.</p>
Fig. 2 in Movement and activity pattern of a brown bear (Ursus arctos L.) tracked in Central Balkan Mountain, Bulgaria
Fig. 2. Minimum, maximum and average speed of the bear in different habitats.
A glimpse into the foraging and movement behavior of Nyctalus aviator: a complementary study by acoustic recording and GPS tracking
<p>Species of open-space bats that are relatively large, such as bats from the genus <em>Nyctalus</em>, are considered as high-risk species for collisions with wind turbines. However, important information on their behavior and movement ecology, such as the locations and altitudes at which they forage, is still fragmentary, while crucial for their conservation in light of the increasing threat posed by progressing wind turbine construction. We adopted two different methods of microphone array recordings and GPS-tracking capturing data from different spatio-temporal scales in order to gain a complementary understanding of the echolocation and movement ecology of <em>Nyctalus aviator</em>, the largest open-space bat in Japan. Based on microphone-array recordings, we found that echolocation calls during natural foraging are adapted for fast-flight in open space optimal for aerial-hawing. In addition, we attached a GPS tag that can simultaneously monitor feeding buzz occurrence and confirmed that foraging occurred at 300 m altitude and that the flight altitude in mountainous areas is consistent with the turbine conflict zone. Thus, our acoustic GPS survey clearly identified<em> N. aviator</em> as a high-risk species in Japan.</p>
Multi-colony tracking of two pelagic seabirds with contrasting flight capability illustrates how windscapes shape migratory movements at an ocean-basin scale
<p>Migration is a common trait among many animals allowing the exploitation of spatiotemporally variable resources. It often implies high energetic costs to cover large distances, for example between breeding and wintering grounds. For flying or swimming animals, the adequate use of winds and currents can help reduce the associated energetic costs. Migratory seabirds are good models because they dwell in habitats characterized by strong winds while undertaking very long migrations. We tested the hypothesis that seabirds migrate through areas with favourable winds. To that end, we used a multi-colony geolocator tracking dataset of two North Atlantic seabirds with contrasting flight capabilities, the black-legged kittiwake (<em>Rissa</em> <em>tridactyla</em>) and the Atlantic puffin (<em>Fratercula</em> <em>arctica</em>), and wind data from the ERA5 climate reanalysis model. Both species had on average positive wind support during migration. Their main migratory routes were similar and followed seasonally prevailing winds. The general migratory movement had a loop-shape at the scale of the North Atlantic, with an autumn route (southward) along the east coast of Greenland, and a spring route (northward) closer to the British Isles. While migrating, both species had higher wind support in spring than in autumn. Kittiwakes migrated farther and benefited from higher wind support than puffins on average. The variation in wind conditions encountered while migrating was linked to the geographical location of the colonies. Generally, northernmost colonies had better wind support in autumn while the southernmost colonies had a better wind support in spring, with some exceptions. Our study helps in understanding how the physical environment shapes animal migration, which is crucial to further predict how migrants will be impacted by ongoing environmental changes.</p>
Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems
<p>Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems</p><p>Please read the README.txt file before working with the data.</p>
Tracking movements in an endangered capercaillie population using DNA-tagging
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Grid cells accurately track movement during path integration-based navigation despite switching reference frames
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Data from: Seasonality in daily movement patterns of mandrills revealed by combining direct tracking and camera traps
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A glimpse into the foraging and movement behavior of Nyctalus aviator: a complementary study by acoustic recording and GPS tracking
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GPS tracking data for: Male mating season range expansion results from an increase in scale of daily movements for a polygynous-promiscuous bird
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Multi-colony tracking of two pelagic seabirds with contrasting flight capability illustrates how windscapes shape migratory movements at an ocean-basin scale
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.