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559 results for “Track data”
Northern elephant seal tracking and diving – raw and curated data
Open the record for dataset details and reuse information.
Northern elephant seal tracking and diving – processed data
Open the record for dataset details and reuse information.
Data from: Novel track morphotypes from new tracksites indicate increased Middle Jurassic dinosaur diversity on the Isle of Skye Scotland
<p>Dinosaur fossils from the Middle Jurassic are rare globally, but the Isle of Skye (Scotland, UK) preserves a varied dinosaur record of abundant trace fossils and rare body fossils from this time. Here we describe two new tracksites from Rubha nam Brathairean (Brothers' Point) near where the first dinosaur footprint in Scotland was found in the 1980s. These sites were formed in subaerially exposed mudstones of the Lealt Shale Formation of the Great Estuarine Group and record a dynamic, subtropical, coastal margin. These tracksites preserve a wide variety of dinosaur track types, including a novel morphotype for Skye: <i>Deltapodus</i> which has a probable stegosaur trackmaker. Additionally, a wide variety of tridactyl tracks shows evidence of multiple theropods of different sizes and possibly hints at the presence of large-bodied ornithopods. Overall, the new tracksites show the dinosaur fauna of Skye is more diverse than previously recognized and give insight into the early evolution of major dinosaur groups whose Middle Jurassic body fossil records are currently sparse.</p>
Data from: Spatiotemporal variation in disturbance impacts derived from simultaneous tracking of aircraft and shorebirds
<p>1. Assessing impacts of disturbance over large areas and long time periods is crucial for nature management, but also challenging since impacts depend on both wildlife responses to disturbance and on the spatiotemporal distribution of disturbance sources. Combined tracking of animals and disturbance sources enables quantification of wildlife responses as a function of the distance to a disturbance source. We provide a framework to derive such distance-response curves and combine those with disturbance source presence data to quantify energetic costs of disturbance at a landscape scale. 2. We tracked 90 Eurasian Oystercatchers Haematopus ostralegus and all aircraft in a military training area in the Dutch Wadden Sea. We quantified distance-response curves estimating flight probability and additional displacement for five types of aircraft activities, by comparing bird movement prior to aircraft presence with movement during aircraft presence. We then used the distance-response curves to map mean and variation in additional daily energy expenditure due to cumulative aircraft disturbance across the landscape for a 700-day period. 3. Flight probability and displacement responses differed strongly among aircraft activities and decreased from transport airplanes, through bombing jets, helicopters, jets to small civil airplanes. Since the most disturbing aircraft activities were also the rarest ones, mean additional daily energy expenditure did not exceed 0.25%. However, days with substantial (>1%) additional expenditure occurred between 0.1% and 3.7% of all days across high tide roosts in the tidal basin. Notably, expenditure particularly spiked on days with transport airplane activity (up to 8.5%). 4. Synthesis and applications. Cumulative energetic flight costs due to aircraft disturbance are low and unlikely to impact survival of oystercatchers in our study area. Our results provide evidence that the legal minimum flight height of 450m for small civil airplanes effectively limits disturbance of oystercatchers. Mitigation should focus on limiting the number of days when disturbance has a high impact by reducing rare but highly disturbing activities, especially transport airplanes. Our approach can be applied to other species and disturbance sources that are automatically tracked, e.g. boats and walkers, ultimately to quantify the entire anthropogenic disturbance landscape.</p>
Analysis of migration patterns of western marsh harriers using GPS tracking data
<p>This repository contains analysis code for Vansteelant et al. (2020, <a href="https://doi.org/10.1007/s10336-020-01785-6">https://doi.org/10.1007/s10336-020-01785-6</a>). See the <code>README.md</code> for more information.</p>
Data for: Performance of a high-frequency (180 kHz) acoustic array for tracking juvenile Pacific salmon in the coastal ocean
<p><b>Background</b></p> <p>Acoustic telemetry is now a key research tool used to quantify juvenile salmon survival, but transmitter size has limited past studies to larger smolts (>130 mm fork length). New, smaller, higher-frequency transmitters ("tags") allow studies on a larger fraction of the smolt size spectrum (>95 mm); however, detection range and study duration are also reduced, introducing new challenges. The potential cost implications are not trivial. With these new transmitters in mind, we designed, deployed, and tested the performance of a dual-frequency receiver array design in the Discovery Islands region of British Columbia, Canada. We double-tagged 50 juvenile steelhead (<i>Oncorhynchus mykiss</i>) with large 69 kHz tags (VEMCO model V9-1H) and small 180 kHz tags (model V4-1H). The more powerful 69 kHz tags were used to determine fish presence in order to estimate the detection efficiency (DE) of the 180 kHz tags. We then compared the standard error of the survival estimate produced from the tracking data using the two tag types which has important implications for array performance and hypothesis testing in the sea.</p> <p><b>Results</b></p> <p>Perfect detection of the 69 kHz tags allowed us to determine the DE of the 180 kHz tags. Although the 180 kHz tags began to expire during the study, the estimated DE was acceptable at 76% (SE = 9%) when we include single detections. However, confidence intervals on steelhead survival (64%) were 1.5x larger for the 180 kHz tags (47-85% vs. 51-77% for 69 kHz) because of the reduced DE.</p> <p><b>Conclusions</b></p> <p>The array design performed well; however, single detections of the 180 kHz tags indicates that under slightly different circumstances the DE could have been compromised, emphasizing the need to carefully consider the interaction of animal migration characteristics, study design, and tag programming when designing telemetry arrays. To increase DE and improve the precision of 180 kHz-based survival estimates presented here requires either an increase in receiver density, an increase in tag sample size (and modified transmitter programming), or both. The optimal solution depends on transmitter costs, array infrastructure costs, annual maintenance costs, and array use (i.e., contributors). Importantly, the use of smaller tags reduces potential tag burden effects and allows early marine migration studies to be extended to Pacific salmon populations that have been previously impossible to study.</p>
Eye-tracking (EOG) Data
<p>Dataset taken from https://sites.google.com/site/consensusmotifs/</p> <p>Stored on Zenodo as backup for Stumpy Consensus Motif Search</p>
Data from: Tracking temperate fish reveals their relevance for plant seed dispersal
<p>Seed dispersal is a fundamental process for plant communities, especially now that our changing world demands rapid colonization of new habitats. Long-distance dispersal is especially important for plant population persistence and range expansions.</p> <p>The contribution of fishes to plant seed dispersal in aquatic ecosystems (ichthyochory) has long been overlooked. Although we know fish disperse seeds, it is largely unknown where, when and how far – especially in temperate regions. Here we studied the potential of fish to disperse seeds locally and over long distances, specifically hypothesizing that i) dispersal by fish depends on the season, ii) individual fish contribute differently to seed dispersal, and iii) water regulating structures (barriers) inhibit seed dispersal.</p> <p>We tested our hypotheses by acoustically tracking 71 common carp (Cyprinus carpio) with 21 hydrophones in a 38km-long study system for >2 years in the Netherlands. We calculated potential seed dispersal throughout this system by combining nearly 1.5 million location registrations with experimentally assessed retention times of seeds after ingestion (i.e. time between ingestion and egestion).</p> <p>Seed dispersal on local scales was quantitatively most important during summer and autumn, with high dispersal potential in a range of four kilometres from the location of seed ingestion. Long-distance dispersal up to 16 km was possible at low probabilities in spring. In winter, most seeds were egested within two km. Maximum and median dispersal distances varied widely among individuals, emphasizing variation in effectiveness among individual fish for seed dispersal. Less than two percent of all fish movements reached beyond sluices and weirs, indicating that anthropogenic barriers in freshwater systems strongly reduced the potential of common carp to disperse seeds to these areas.</p> <p>This study shows that common carp can locally disperse plant seeds with high probabilities, and over distances up to 16 km with low probabilities throughout temperate ecosystems. This can contribute to restoration and maintenance of plant community diversity. However, this ecosystem function of fish to plants requires intact fish populations – because not all individual fish contribute equally to dispersal – and unrestricted connectivity throughout aquatic ecosystems.</p>
A comparative usability analysis of eye-tracking and mouse click data taken from digital libraries
<p>This dataset is the result of a study, in which we analyzed parallels and differences between clicks as well as eye movements on two different digital library homepages. For this analysis we used diverse tracking tools for mouse clicks and eye tracking data that where further studied with respect to specific areas of interest (AOI). </p> <p>The dataset contains two screenshots indicating the areas of interest (AOIs; entitled “AreasOfInterest_Kartenportal.jpg and AreasOfInterest_Webportal.jpg), which separate the homepages into analyzable parts. It also contains eight screenshots of the homepages containing the total amount of collected clicks (each name starting with “clicks”) and two screenshots with the eye tracking heat maps (starting with “Heatmap”). The screenshots have directly been extracted from the click and eye tracking tools and matched with the before mentioned AOIs in order to gain the total count of clicks and views as well as the view duration the concerned area.</p> <p>All data are synthesized in a document containing three sheets with different tables: a first one with the initial data compilation for all AOIs of the two analyzed homepages (entitled “Data”), a second one with a more visual compiled data analysis for both homepages and all AOIs (entitled “Data2) and last one with the duration of the view as well as the duration of the fixation and the compiled click data (entitled « Eye tracking study data »).</p>
FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure
<p>This upload contains the FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure.</p> <p>If you use the datasets, we would be grateful if you cited the following paper:</p> <p>Zou, C., Zhang, Y., Ouyang, Z. (2016) HSA: integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure. Genome Biology, 17: 40.</p>
Best track data
<p>Best track data of fitow, downloaded from http://0205konami.blog.163.com/blog/static/663188852011191057583/</p>
Multilingual Bottle-Neck Feature Learning from Untranscribed data for track 1 in zerospeech2017 (system 1 -- without VTLN)
<p>We investigate the extraction of bottle-neck features (BNFs) for multiple languages without access to manual transcription. Multilingual BNFs are derived from a multi-task learning deep neural network which is trained with unsupervised phoneme-like labels. The unsupervised phoneme-like labels are obtained from language-dependent Dirichlet process Gaussian mixture models separately trained on untranscribed speech of multiple languages.</p>
Whale shark tracking data from the eastern tropical Pacific
<p>These two data files contain Argos position data and subsurface time-at-temperature data from whale sharks tagged at Darwin's Arch, Galapagos during 2011 - 2012.</p>
Experimental data for "Spot-On: robust model-based analysis of single-particle tracking experiments"
<p><strong>Overview of experimental spaSPT data</strong></p> <p>To comprehensively test Spot-On over many different conditions, we conducted 1064 spaSPT experiments. The raw data is freely available and the purpose of this ReadMe file is to describe the organization, acquisition parameters and format of the data. The data is for 4 different cell lines imaged over 15 different conditions yielding a total of 60 different conditions. The four cell lines were:</p> <ul> <li> <p>U2OS C32 Halo-CTCF</p> </li> <li> <p>U2OS H2B-Halo-SNAP</p> </li> <li> <p>U2OS Halo-3xNLS</p> </li> <li> <p>mESC (JM8.N4) C3 Halo-Sox2</p> </li> </ul> <p>The cell lines were constructed in different ways. U2OS C32 Halo-CTCF was made by homozygous endogenous N-terminal tagging of CTCF in human osteosarcoma U2OS cells using CRISPR/Cas9-mediated genome-editing as described (C32 refers to clone number 32)<sup>1</sup>. We note the CTCF is an essential gene and that N-terminal tagging did not appear to affect CTCF function or expression level according to a series of control experiments<sup>1</sup>. Moreover, C32 Halo-CTCF has been authenticated using Short Tandem Repeat (STR) profiling (performed by Dr. Alison N. Killilea at the UC Berkeley Cell Culture Facility) against the following loci: THO1, D5S818, D13S317, D7S820, D16S539, CSF1PO, AMEL, vWA and TPOX. The C32 Halo-CTCF cell line showed a 100% match with U2OS.</p> <p>U2OS H2B-Halo-SNAP was made through random integration of a H2B-HaloTag-SNAP-Tag transgene expressed using the EF1a promoter with an IRES-NeoR gene for drug selection. After transfection, cells were selected using G418 until a pure cell population was obtained. This cell line has also been described previously<sup>1</sup>. The wild-type U2OS cell line used to make this cell line was also authenticated using STR profiling against the same loci as C32 and also showed a 100% match with U2OS.</p> <p>U2OS Halo-3xNLS was made through random integration of a FLAG-Halo-3xNLS (3x SV40 NLS: PKKKRKV) transgene expressed using the EF1a promoter. NeoR for drug selection was separately expressed using an SV40 promoter. After transfection, cells were selected using G418 until a pure cell population was obtained. This cell line has also been described previously<sup>1</sup>. The wild-type U2OS cell line used to make this cell line was also authenticated using STR profiling against the same loci as C32 and also showed a 100% match with U2OS.</p> <p>mESC C3 Halo-Sox2 was made through homozygous N-terminal tagging of Sox2 in JM8.N4<sup>2</sup> mouse embryonic stem cells using CRISPR/Cas9-mediated genome editing as previously described (C3 refers to clone number 3)<sup>3</sup>. The functionality of the C3 Halo-Sox2 knock-in was validated through control experiments and pluripotency through teratoma assays as described previously<sup>3</sup>.</p> <p>Each file contains single-molecule trajectories from a single cell imaged over 30,000 frames. Localization and tracking was performed using a custom-written Matlab implementation of the MTT-algorithm<sup>4</sup> and the following settings: Localization error: 10<sup>-6.25</sup>; deflation loops: 0; Blinking (frames): 1; max competitors: 3; max <em>D</em> (m<sup>2</sup>/s): 20.</p> <p>The same 15 conditions were used for each of the 4 cell lines.</p> <p><strong>ExpA PA-JF549</strong></p> <p>The purpose of this experiment was to test the effect of “motion-blurring” on the Spot-On estimated <em>D</em><sub>FREE</sub> and <em>F</em><sub>BOUND</sub>. 5 different experimental conditions were considered. Full details are given in the Methods section. Briefly, cells were grown overnight on plasma-cleaned 25 mm circular coverslips either directly (U2OS) and MatriGel coated as described<sup>1</sup>. Cell were labeled with 5-50 nM PA-JF549<sup>5</sup> for around 15-30 min, washed twice and medium exchanged to phenol-red free medium. 30,000 frames were collected at a camera exposure time (Andor iXon Ultra 897; frame-transfer mode; vertical shift speed: 0.9 μs; -70C) of 9.5 ms which together with a ~447 μs camera integration time gave a frame rate of ~100 Hz. PA-JF549 dyes were photo-activated during the ~447 μs camera integration time using 405 nm pulses and the 405 nm pulse intensity optimized to achieve a mean density of 1 molecule per frame per nucleus. The JF549 dye was excited using a 561 nm laser and the total number of excitation photons kept constant but either delivered during a 1 ms pulse, a 2 ms pulse, a 4 ms pulse, a 7 ms pulse or with constant illumination.</p> <p>For each cell line and condition, 4 replicates were performed. We count a replicate as an independent experiment performed on a different day. For each replicate around 5 cells were imaged. Occasionally, fewer than 5 cells are available. To avoid tracking errors, we removed cells with too high a localization density from the analysis. All of this information is available in the file name. For example, “U2OS_C32_Halo-CTCF_PA-JF549_1ms-561nm_100Hz_rep2_cell03” refers to the third cell imaged in the second replicate of U2OS C32 Halo-CTCF using a 1 ms excitation pulse of 561 nm laser at a frame rate of 100 Hz. Similarly, “U2OS_C32_Halo-CTCF_PA-JF549_cont-561nm_100Hz_rep4_cell01” refers to the first cell imaged in the fourth replicate of U2OS C32 Halo-CTCF using constant 561 nm laser at a frame rate of 100 Hz.</p> <p>The five ExpA_PAJF549 conditions are separated by cell line such that each cell line is provided in a separate directory. E.g. the directory “U2OS_H2B_ExpA_PAJF549” contains all data for the U2OS H2B-Halo-SNAP cell line.</p> <p><strong>ExpA PA-JF646</strong></p> <p>This experiment was exactly identical to the “ExpA_PA-JF549” experiment except cell were labeled with PA-JF646<sup>5</sup> and excited using a 633 nm laser. The file names and data organization was otherwise the same and the same five excitation conditions were considered.</p> <p><strong>ExpB PA-JF646</strong></p> <p>The purpose of this experiment was to test if the Spot-On estimated <em>D</em><sub>FREE</sub> and <em>F</em><sub>BOUND</sub> values would depend on the frame rate. In particular, all four proteins exhibit some levels of apparent anomalous diffusion, which could cause a dependence on the frame rate. Cells were labeled with PA-JF646 and grown and imaged as described above. Photo-activation took place during the ~447 μs camera integration time and JF646 dyes were excited using 1 ms stroboscopic 633 nm excitation pulses. To change the frame rate, the camera exposure time was set to 4.5 ms (~201 Hz), 5.5 ms (~167 Hz), 7 ms (~134 Hz), 13 ms (~74 Hz) and 19.5 ms (~50 Hz) when also counting the ~447 μs camera integration time. All of this information is available in the file name. For example, “U2OS_Halo-3xNLS_PA-JF646_1ms-633nm_74Hz_rep2_cell04” refers to the fourth cell imaged in the second replicate of U2OS Halo-3xNLS using a 1 ms excitation pulse of 633 nm laser at a frame rate of 74 Hz. Similarly, “mESC_C3_Halo-Sox2_PA-JF646_1ms-633nm_201Hz_rep1_cell03” refers to the third cell imaged in the first replicate of mESC Halo-Sox2 using a 1 ms excitation pulse of 633 nm laser at a frame rate of 201 Hz.</p> <p><strong>Data format</strong></p> <p>All data is available in two different formats: CSV-files and Matlab MAT-files. Both file formats are readable by the web-version of Spot-On. The Matlab version of Spot-On is only able to read the MAT-files. The CSV format consists of comma-separated values and contains headers. If opened with Microsoft Excel, it should appear as shown:</p> <p>Here the “frame” column contains the frame number in which the molecule was detected. The “t” column contains the timestamp. The “trajectory” column contains the trajectory number. For example, trajectory number 1 was only detected in frame 13 after which it disappeared. In contrast, trajectory number 4 was detected in frames 20, 21 22, 23 and 24. Finally, the “x” and “y” columns contain the x,y coordinates of the localization in units of micrometers (μm).</p> <p>The MAT-files contain a structure array named “trackedPar”. trackedPar contains three variables:</p> <ul> <li> <p>trackedPar.xy: “xy” is a matrix with 2 columns and a number of rows corresponding to the number of localizations in that trajectory. The first column is the x-coordinate and the second column is the y-coordinate. The units are micrometers (μm).</p> </li> <li> <p>trackedPar.Frame: “Frame” is a column vector where each element is the frame where the particle was localized.</p> </li> <li> <p>trackedPar.TimeStamp: “TimeStamp” is a column vector where each element is the timepoint where the particle was localized.</p> </li> </ul> <p>Each element in the structure array “trackedPar” correspond to a different trajectory.</p>
Simulated data for "Spot-On: robust model-based analysis of single-particle tracking experiments"
<p><strong>Generation of simulated data</strong></p> <p>To systematically evaluate the performance of Spot-On as well as other common analysis tools such as MSD<sub>i</sub> and vbSPT, we considered a comprehensive set of 3480 realistic SPT simulations spanning the range of plausible dynamics. The simulations were performed using simSPT, which is freely available at GitLab: https://gitlab.com/tjian-darzacq-lab/simSPT. The simulation methods are described in detail at GitLab. A full description of the parameters which allows exact reproduction of the simulations is available together with the data (see Data Availability section). Briefly, we parameterized simSPT to consider that particles diffuse inside a sphere (the nucleus) of 8 µm diameter illuminated using HiLo illumination (assuming a HiLo beam width of 4 µm), with an axial detection range of ~700 nm, centered at the middle of the HiLo beam. Molecules are assumed to have a half-life of 4 frames (when inside the HiLo beam) and of 40 frames when outside the HiLo beam. The localization error was set to 25 nm and the simulation was run until 100000 in-focus trajectories were recorded. More specifically, the effect of the exposure time (1 ms, 4 ms, 7 ms, 13 ms, 20 ms), the free diffusion constant (from 0.5 µm²/s to 14.5 µm²/s in 0.5 µm²/s increments) and the fraction bound (from 0 % to 95 % in 5 % increments) were investigated, yielding a dataset consisting of 3480 simulations. The advantage of simulations is that the ground truth is known. This allows a quantitative assessment of which method works the best.</p> <p><strong>Content of the archives:</strong></p> <ol> <li>170718_simSPT_simulations.zip the code and instructions to reproduce the simulations</li> <li>4um.tar.bz2 simulated data inside a 4 µm nucleus</li> <li>20um.tar.bz2 simulated data inside a 20 µm nucleus, in which virtually no confinement occurs.</li> <li>subsampled.tar.bz2 is a set of subsampled datasets, containing either 99999, 30000, 10000, 3000, 1000, 300, 100 or 30 trajectories. Each subsampling was done 50 times, yielding 50 files per subsmpling.</li> </ol> <p><strong>Formats:</strong></p> <p>The data is provided both in CSV and .mat formats. .mat files are provided in the following dataset: 10.5281/zenodo.835541</p>
Raw sequencing data and ngsfilters for snow track eDNA samples
<p>Continued advancements in environmental DNA (eDNA) research have made it possible to access intraspecific variation from eDNA samples, opening new opportunities to expand non-invasive genetic studies of wildlife populations. However, the use of eDNA samples for individual genotyping, as typically performed in non-invasive genetics, still remains elusive. We present the first successful individual genotyping of eDNA obtained from snow tracks of three large carnivores: brown bear (<em>Ursus</em> <em>arctos</em>), European lynx (<em>Lynx</em> <em>lynx</em>) and wolf (<em>Canis</em> <em>lupus</em>). DNA was extracted using a protocol for isolating water eDNA and genotyped using amplicon sequencing of short tandem repeats (STR) and, for brown bear, a sex marker, on a high-throughput sequencing platform. Individual genotypes were obtained for all species, but genotyping performance differed among samples and species. The proportion of samples genotyped to individuals was higher for brown bear samples (5/7) than for wolf (7/10) and lynx (4/9), but locus genotyping success was greater for brown bear (0.88). Results for three species show that reliable individual genotyping, including sex identification, is now possible from eDNA in snow tracks, underlining its vast potential to complement the non-invasive genetic methods used for wildlife. To fully leverage the application of snow track eDNA, improved understanding of the ideal species- and site-specific sampling conditions, as well as laboratory methods promoting genotyping success are needed. This will also inform efforts to retrieve and type nuclear DNA from other eDNA samples, thereby advancing eDNA–based individual and population-level studies.</p>
Particle tracking data in idealized and realistic estuary models
<p>Particle tracking data in the realistic North River estuary model, Delaware estuary model, and idealized estuary models with different channel dimensions.</p>
Data for: Tracking hybrid viability across life-stages in a natural avian contact zone
<p><span>Hybrid inviability is an important post-zygotic reproductive barrier between species, but emerging signs of reduced viability can be difficult to study across the lifespan of natural hybrids.</span><span> We use a combination of long-term monitoring, extra-pair paternity and mitochondrial DNA identification in a natural hybrid zone of <em>Ficedula </em>flycatchers to detect emerging signs of intrinsic hybrid inviability across their entire lifespan. We evaluate possible evidence of Darwin's corollary to Haldane's rule, predicting asymmetries in inviability between hybrids resulting from reciprocal crosses, due to incompatible genetic factors with sex-specific inheritance patterns. We found higher hatching failure among mixed-species pairs, possibly indicating early developmental impairments associated with specific parental genetic combinations. Adult hybrids had a higher basal mortality rate than both parental species, and different age-specific mortality trajectories. There were signs of differences in age-independent mortality rates between the reciprocal hybrid crosses: hybrids with a pied flycatcher mother experienced slightly increased mortality later in life. Using an exceptional dataset with many natural hybrids tracked across life stages, we provide evidence for several emerging signs of reduced hybrid viability. Incompatibilities between alleles located on autosomes and uniparentally inherited factors such Z-linked and/or mitochondrial genes are strong candidates underlying intrinsic hybrid dysfunction in this system.</span></p>
Data from: Larval diet and temperature alter mosquito immunity and development: using body size and developmental traits to track carry-over effects on longevity
<p><span><strong>Background</strong>:</span><span> Estimating arbovirus transmission potential requires a mechanistic understanding of how environmental factors influence the expression of adult mosquito traits. While preimaginal exposure to environmental factors can have profound effects on adult traits, tracking and predicting these effects remains challenging. </span></p> <p><span><strong>Methods</strong>:</span><span> Using <em>Aedes albopictus</em> and a structural equation modelling approach, we explored how larval nutrition and temperature jointly affect development rate and success, body size, and whether these metrics capture carry-over effects on adult longevity. Additionally, we investigated how larval diet and temperature affect the baseline expression of ten immune genes. </span></p> <p><span><strong>Results</strong>:</span><span> We found that larval development </span><span>success</span><span> was primarily determined by diet, while temperature and diet both affected development rate, pupal wet weight, and wing length. Effects of diet on both morphometric measures and their relationships to adult longevity were asymmetrical, with wing length having a positive association and pupal weight a negative association. Larval diet indirectly affected adult longevity, and the time to pupation was negatively correlated with longevity. </span><span>The</span><span> expression of </span><span>eight </span><span>immune genes from Toll, </span><span>JAK-STAT, and Imd pathways </span><span>was enhanced in mosquitoes with higher nutrition. </span></p> <p><span><strong>Conclusions</strong>:</span><span> Our results highlight deficiencies from using a single body size measure to capture carry-over effects on adult traits. Further studies of larval development rate under varying environmental conditions and its potential for tracking carry-over effects on vectorial capacity are warranted. </span></p>
Col de la Croix 1988 autumn survey radar tracking data
<p>Individual tracks of free flying nocturnal migrants recorded by a military tracking radar (see Bruderer 1997):</p><p><i>Bruderer, B. The Study of Bird Migration by Radar Part 1: The Technical Basis*. Naturwissenschaften <strong>84</strong>, 1–8 (1997). </i><a href="https://doi.org/10.1007/s001140050338"><i>https://doi.org/10.1007/s001140050338</i></a><i> </i></p><p> </p><p><strong>Description of variables </strong></p><p>Code site code (C88: Col de la Croix)</p><p>FNr Track number starting each day at 00:00 with 1</p><p>Z mean flight altitude (m above radar)</p><p>Rg mean flight direction (°)</p><p>Ra mean heading (°, body axis)</p><p>Vg mean ground speed (cm/s)</p><p>Va mean airspeed (cm/s)</p><p>Vz mean climb rate (cm/s)</p><p>FieldClass Echo class 1-9 based on wingbeat pattern, see description below</p><p> </p><p><strong>description of variable FieldClass</strong> </p><p>Code description</p><p>1 wader-type large (continuous wingbeats)</p><p>2 wader-type small (continuous wingbeats)</p><p>3 passerine-type large (regular phases of wingbeats and pauses => bounding flight)</p><p>4 passerine-type small (regular phases of wingbeats and pauses => bounding flight)</p><p>5 swift-type (irregular phases of wingbeats and pauses => flap-gliding flight)</p><p>6 raptor (visually identified)</p><p>7 single bird large (partly visually identified)</p><p>8 flock of unidentified birds</p><p>9 unknown bird</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.