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389 results for “lifetime”
Honeybee lifetime tracking data 2019
<p>Data from barcode-based tracking of honeybees during summer of 2019, taken in an observation hive located at University of Konstanz, Germany.</p> <p>See <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2019data">table of experiments and manipulations performed</a></p> <p>Associated GitHub repositories:<br> <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2019data">https://github.com/jacobdavidson/bees_lifetimetracking_2019data</a><br> <a href="https://github.com/jacobdavidson/bees_drones_2019data">https://github.com/jacobdavidson/bees_drones_2019data</a></p> <p>Data usage example is on <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2019data/blob/main/Data%20usage%20example%20-%20updated.ipynb">Github</a></p> <p><strong>File contents: </strong></p> <p><strong><a href="https://zenodo.org/record/7298798/files/2019_Quantity_Dates_Cohorts_DaysLived.xlsx?download=1">2019_Quantity_Dates_Cohorts_DaysLived.xlsx</a></strong></p> <p>List and description of quantities contained in the single-day summary metrics, and the metrics calculated at shorter intervals (hour, 5 minute, 1 minute). Also lists day number definitions, cohort birthdates, and estimated days lived per bee.</p> <p><strong><a href="https://zenodo.org/record/7298798/files/trajectories_000-019.zip?download=1">trajectories_000-019.zip</a>, <a href="https://zenodo.org/record/7298798/files/trajectories_020-039.zip?download=1">trajectories_020-039.zip</a>, <a href="https://zenodo.org/record/7298798/files/trajectories_040-059.zip?download=1">trajectories_040-059.zip</a>, <a href="https://zenodo.org/record/7298798/files/trajectories_060-079.zip?download=1">trajectories_060-079.zip</a>, <a href="https://zenodo.org/record/7298798/files/trajectories_080-099.zip?download=1">trajectories_080-099.zip</a>, <a href="https://zenodo.org/record/7298798/files/trajectories_100-114.zip?download=1">trajectories_100-114.zip</a></strong></p> <p>Single-day hdf files, each containing x-y trajectory data in the form:</p> <table> <thead> <tr> <th>daynum</th> <th>framenum</th> <th>uid</th> <th>x</th> <th>y</th> <th>camera</th> <th>theta</th> </tr> </thead> </table> <ul> <li>daynum: the day number of the observation period. See 'Day numbers' sheet in <a href="https://zenodo.org/record/7298798/files/2019_Quantity_Dates_Cohorts_DaysLived.xlsx?download=1">2019_Quantity_Dates_Cohorts_DaysLived.xlsx</a></li> <li>framenum: using the camera frame rate of 3fps, the frame number with respect to that particular day</li> <li>uid: the Unique ID of each bee</li> <li>x,y: pixel coordinate values of each bee. Conversion is 80 pixels/cm</li> <li>camera: which camera the bee was detected on: 0=exit side (with dance floor - shown at right in comb map images), 1=back side (show at left in comb map images)</li> <li>theta: orientation of the bee in the hive </li> </ul> <p><strong><a href="https://zenodo.org/record/7298798/files/comb-contents-images2019.zip?download=1">comb-contents-images2019.zip</a></strong></p> <p>Comb content color-coded png image files, as well as pkl files for using the comb data type (see <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2019data/blob/main/Data%20usage%20example%20-%20updated.ipynb">Data Usage Example</a>)</p> <p><strong><a href="https://zenodo.org/record/7298798/files/daydatamat.csv?download=1">daydatamat.csv</a></strong></p> <p>Summary behavioral metrics calculated for each tracked bee on each day of the experiment. See 2018_Quantity_Descriptions.xlsx for full list and detail of quantities. Data is in the form:</p> <table> <thead> <tr> <th>Age</th> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th><metric1></th> <th><metric2></th> <th>...</th> </tr> </thead> </table> <p><strong><a href="https://zenodo.org/record/7298798/files/df_day1min.zip?download=1">df_day1min.zip</a>, <a href="https://zenodo.org/record/7298798/files/df_day5min.zip?download=1">df_day5min.zip</a>, <a href="https://zenodo.org/record/7298798/files/df_dayhour.zip?download=1">df_dayhour.zip</a></strong></p> <p>Behavioral metrics calculated over different time intervals: 1 minute, 5 minute, or 1 hour divisions. See 2018_Quantity_Descriptions.xlsx for full list and detail of quantities. Files are organized as a single .hdf file for each day. Each file contains data in the form:</p> <p>Per-hour data:</p> <table> <thead> <tr> <th>Age</th> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th>Hour</th> <th><metric1></th> <th><metric2></th> <th>...</th> </tr> </thead> </table> <p>5-minute or 1-minute data: </p> <table> <thead> <tr> <th>Age</th> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th>timedivision</th> <th><metric1></th> <th><metric2></th> <th>...</th> </tr> </thead> </table> <p><strong><a href="https://zenodo.org/record/7298798/files/dfxy_dayhour.zip?download=1">dfxy_dayhour.zip</a></strong></p> <p>x-y histogram data, calculated by using a 2cmx2cm grid and binning for each hour of each day. One file per day, and each file contains data in the form:</p> <table> <thead> <tr> <th>Day number</th> <th>Bee unique ID</th> <th>Cohort ID</th> <th>Hour</th> <th>hist0</th> <th>hist1</th> <th>...</th> <th>hist1434</th> </tr> </thead> </table> <p>Convert the flattened histogram structure into a shape of [41,35] in order to view as shown in the paper or in the <a href="https://github.com/jacobdavidson/bees_lifetimetracking_2019data/blob/main/Data%20usage%20example%20-%20updated.ipynb">Data Usage Example</a></p>
Why do parents produce small broods of offspring that have lower body mass, survival, and lifetime reproductive success? A case study in a long-lived bird
<p class="MsoNormal"><span>Numerous studies have </span><span>examined the correlation between offspring </span><span>quantity</span><span> and quality</span><span>, and many have found that the most common brood size is often smaller than broods with the highest offspring quality or production. However, the reasons why these small broods with lower offspring quality are produced, are still poorly explained. Using data spanning 29 years, we investigated the effects of brood size on nestlings' body mass and the lifetime fitness for those offspring as adults (as proxies of offspring quality) in the Crested Ibis (<em>Nipponia nippon</em>). We also examined the temporal variation of brood size. We found that overall offspring quality increases with brood size and that individuals from broods of three had the highest quality, as quantified by larger body mass, higher adult survival, and lifetime reproductive success. Furthermore, brood size of an individual pair significantly varied across years, and the proportion of broods containing two offspring increased while broods of three decreased after 2000 when the population dispersed to low-quality habitat. These findings indicate that spatiotemporal variation in resources may impact variation in brood size and subsequent fitness consequences, and that small broods are more common in resource-poor years or low-quality habitats. In contrast, parents with access to high-quality resources produce larger broods of nestlings that achieve higher body mass and subsequently experience higher adult survival and lifetime fitness. This study highlights how variation in life history traits can be influenced by resource condition, and provides an insight into particular habitat that need conservation for Crested Ibis.</span></p>
Code and data for "Costly lifetime maternal investment in killer whales"
<p>R code and data necessary to reproduce all analyses from the manuscript "Costly lifetime maternal investment in killer whales." Included is reproductive history data on 40 southern resident killer whale females, the R code to fit Bayesian regression models, code to produce the plots in the manuscript, and code to perform sensitivity analysis for fixed effect priors.</p>
Comparison between ozone column depths and methane lifetimes computed by 1-D and 3-D models at different atmospheric O2 Levels
<p>Recently, Cooke et al. (2022) used a 3-D coupled chemistry-climate model (WACCM6) to calculate ozone column depths at varied atmospheric O<sub>2</sub> levels. They argued that previous 1-D photochemical model studies, e.g., Segura et al. (2003), may have overestimated the ozone column depth at low pO<sub>2</sub>, and hence also overestimated the lifetime of methane. We have compared new simulations from an updated version of the Segura et al. model with those from WACCM6, together with some results from another 1-D and 3-D model. The discrepancy in ozone column depths is likely due to multiple interacting parameters, including lower boundary conditions, vertical and meridional transport rates, and different chemical mechanisms, especially the treatment of O<sub>2</sub> photolysis in the Schumann-Runge (SR) bands (175-205 nm). The discrepancy in tropospheric OH concentrations and methane lifetime between WACCM6 and the 1-D model at low pO<sub>2</sub> is reduced when absorption from CO<sub>2</sub> and H<sub>2</sub>O in this wavelength region is included in WACCM6. Including scattering in the SR bands may further reduce this difference. Resolving these issues can be accomplished by developing an accurate parameterization for O<sub>2</sub> photolysis in the SR bands and then repeating these calculations in the various models. Work is already underway to this end.</p>
Variation among strains of Borrelia burgdorferi in host tissue abundance and lifetime transmission determine the population strain structure in nature
<p class="MsoNormal">Pathogen life history theory assumes a positive relationship between pathogen load in host tissues and pathogen transmission. Empirical evidence for this relationship is surprisingly rare due to the difficulty of measuring transmission for many pathogens. The comparative method, where a common host is experimentally infected with a set of pathogen strains, is a powerful approach for investigating the relationships between pathogen load and transmission. The validity of such experimental estimates of strain-specific transmission is greatly enhanced if they can predict the pathogen population strain structure in nature.</p> <p class="MsoNormal"><em>Borrelia burgdorferi</em> is a multi-strain, tick-borne spirochete that causes Lyme disease in North America. This study used 11 field-collected strains of <em>B. burgdorferi</em>, a rodent host (<em>Mus musculus, </em>C3H/HeJ) and its tick vector (<em>Ixodes scapularis</em>) to determine the relationship between pathogen load in host tissues and lifetime host-to-tick transmission (HTT). Mice were experimentally infected via tick bite with 1 of 11 strains. Lifetime HTT was measured by infesting mice with <em>I. scapularis </em>larval ticks on 3 separate occasions. The prevalence and abundance of the strains in the mouse tissues and the ticks were determined by qPCR. We used published databases to obtain estimates of the frequencies of these strains in wild <em>I. scapularis</em> populations.</p> <p>Spirochete loads in ticks and lifetime HTT varied significantly among the 11 strains of <em>B. burgdorferi</em>. Strains with higher spirochete loads in the host tissues were more likely to infect feeding larvae, which molted into nymphs with a higher probability of <em>B. burgdorferi</em> infection (<em>i.e.</em>, higher HTT). Our laboratory-based estimates of lifetime HTT were predictive of the frequencies of these strains in wild <em>I. scapularis</em> populations. For <em>B. burgdorferi</em>, the strains that establish high abundance in host tissues and that have high lifetime transmission are the strains that are most common in nature.</p>
Data for the publication: "Development and In-Vivo Validation of a Portable Phosphorescence Lifetime-Based Fiber-Optic Oxygen Sensor"
<p>This data set contains all raw data for the publication “Development and In-Vivo Validation of a Portable Phosphorescence Lifetime-Based Fiber-Optic Oxygen Sensor”:</p> <p>- Raw sensor data</p> <p>- Python scripts</p> <p>- particle photon scripts</p> <p>- CAD Drawings</p> <p>- PCB Designs</p>
1-D Model Files for Martian atmospheric chemistry of HCl: implications for the lifetime of atmospheric methane
<p>File containing 1-D model [netCDF] files used in the JGR: Planets manuscript "Martian atmospheric chemistry of HCl: implications for the lifetime of atmospheric methane".</p> <p><strong>MCD-model.zip</strong></p> <p>Contains data files where the 1-D model is driven using Mars Climate Database v5.3 standard climatological profiles of dust and ice aerosols and H2O. readme.txt provides details of the subdirectory structure.</p> <p><strong>TGO-model.zip</strong></p> <p>Contains data files where the 1-D model is driven using dust and ice aerosol profiles retrieved by the ACS TIRVIM and H2O profiles retrieved by either the NOMAD spectrometer or ACS NIR channel. readme.txt provides details of the directory structure.</p> <p><strong>matching_orbits.txt</strong></p> <p>Spatio-temporal details of the 77 ACS MIR HCl retrievals that we aim to reproduce, including the details of the approximately co-located ACS TIRVIM aerosol and NOMAD/ACS NIR H2O retrievals used to drive the 1-D model.</p>
Lifetime wolf breeder data
<p>Data for male and females wolves where we knew both the start and end of their breeding tenure. </p>
Ziprasidone in Bipolar Disorder With Comorbid Lifetime Panic or Generalized Anxiety Disorder(GAD)
ClinicalTrials.gov study NCT01172652. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Data from: MHC class II supertypes affect survival and lifetime reproductive success in a migratory songbird
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Variation among strains of Borrelia burgdorferi in host tissue abundance and lifetime transmission determine the population strain structure in nature
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Data from: Counting chicks before they hatch: Extending the observed lifetime to better characterise evolutionary processes in the wild
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The facultative intracellular symbiont Lariskella is neutral for lifetime fitness and spreads through cytoplasmic incompatibility in the leaffooted bug, Leptoglossus zonatus
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Data from: Parameterizing the robust design in the BUGS language: lifetime carry‐over effects of environmental conditions during growth on a long‐lived bird
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Data from: Lifetime trajectories of male mating effort under reproductive conflict in a cooperatively breeding mammal
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Data from: The social formation of fitness: Lifetime consequences of prenatal nutrition and postnatal care in a wild mammal population
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Data from: Sex-specific performances, trade-offs and trait repeatability across the lifetime of the world's largest semelparous mammal (Dasyurus hallucatus)
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Comparison between ozone column depths and methane lifetimes computed by 1-D and 3-D models at different atmospheric O2 Levels
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Wide-field fluorescence lifetime imaging of neuron spiking and sub-threshold activity in vivo
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Why do parents produce small broods of offspring that have lower body mass, survival, and lifetime reproductive success? A case study in a long-lived bird
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