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2,121 results for “trapping”
DoeDat Camera Trap Project 1935738 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
DoeDat Camera Trap Project 690594 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
DoeDat Camera Trap Project 315295 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
DoeDat Camera Trap Project 1062399 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
DoeDat Camera Trap Project 625456 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
Figure 3 in Seasonal changes in the population structure of dominant planktonic copepods collected using a sediment trap moored in the western Arctic Ocean
Figure 3. Seasonal changes in sea ice concentration, surface chl. a (from satellite) and total mass flux (a), and daylight hours (b) at St. NAPt from October 2010 to September 2012.
Figure 8 in Seasonal changes in the population structure of dominant planktonic copepods collected using a sediment trap moored in the western Arctic Ocean
Figure 8. Seasonal changes in sea ice concentration, daylight hours, chl. a, and total mass flux from January to December (upper panel). The ecological characteristics of the five dominant copepods (lower panel). The open and solid bars indicate the high abundance and reproductive periods for each species, respectively.
DoeDat Camera Trap Project 6171471 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
DoeDat Camera Trap Project 6496641 (Meise Botanic Garden)
A project on the <a href="https://www.doedat.be">DoeDat platform</a> of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>. Footage of camera traps is offered to volunteers for identification of the animals visible, if any. This deposition is an archive of the images in this project as well as the transcription results formatted in Darwin Core.
Vortex input files -- Ashe et al., "Minding the data-gap trap: predicting the dynamics of abundant dolphin species under uncertainty"
<p>Vortex input file used for analyses presented in:<br> "Minding the data-gap trap: predicting the dynamics of abundant dolphin species under uncertainty", <br> by Erin Ashe, Rob Williams, Christopher Clark, Christine Erbe, Leah Gerber, Ailsa Hall, Philip Hammond, Robert C. Lacy, Randall Reeves, & Nicole Vollmer<br> </p>
Indistinguishable photons from a trapped-ion quantum network node
<p>Dataset of measurements for "Indistinguishable photons from a trapped-ion quantum network node"</p>
Data from: Continuous-time spatially explicit capture-recapture models, with an application to a jaguar camera-trap survey
<ol> <li>Many capture-recapture surveys of wildlife populations operate in continuous time but detections are typically aggregated into occasions for analysis, even when exact detection times are available. This discards information and introduces subjectivity, in the form of decisions about occasion definition.</li> <li>We develop a spatio-temporal Poisson process model for spatially explicit capture-recapture (SECR) surveys that operate continuously and record exact detection times. We show that, except in some special cases (including the case in which detection probability does not change within occasion), temporally aggregated data do not provide sufficient statistics for density and related parameters, and that when detection probability is constant over time our continuous-time (CT) model is equivalent to an existing model based on detection frequencies. We use the model to estimate jaguar density from a camera-trap survey and conduct a simulation study to investigate the properties of a CT estimator and discrete-occasion estimators with various levels of temporal aggregation. This includes investigation of the effect on the estimators of spatio-temporal correlation induced by animal movement.</li> <li>The CT estimator is found to be unbiased and more precise than discrete-occasion estimators based on binary capture data (rather than detection frequencies) when there is no spatio-temporal correlation. It is also found to be only slightly biased when there is correlation induced by animal movement, and to be more robust to inadequate detector spacing, while discrete-occasion estimators with binary data can be sensitive to occasion length, particularly in the presence of inadequate detector spacing.</li> <li>Our model includes as a special case a discrete-occasion estimator based on detection frequencies, and at the same time lays a foundation for the development of more sophisticated CT models and estimators. It allows modelling within-occasion changes in detectability, readily accommodates variation in detector effort, removes subjectivity associated with user-defined occasions, and fully utilises CT data. We identify a need for developing CT methods that incorporate spatio-temporal dependence in detections and see potential for CT models being combined with telemetry-based animal movement models to provide a richer inference framework.</li> </ol>
FIGURE 5 in Review of the Ulopella leafhopper genus group (Auchenorrhyncha, Cicadellidae, Ulopinae) with description of a new genus and species collected from pitfall traps in Zambia
FIGURE 5. Kivulopa hovana (holotype), external features and genitalia; a, dorsal habitus, Scale bar: 1 mm., b, lateral habitus, c, face, d, distal segment of right subgenital plate and fused basal segments of right and left subgenital plates together with dorsal plate of same (arrowed), ventral view, e, right subgenital plate (arrow indicates dorsal plate of basal segment), lateral view, f, style, g, aedeagus lateral view, h, aedeagus ventral view, i, connective ventral view, j, connective left lateral view. See Material and methods for details of imaged specimen.
FIGURE 2 in Review of the Ulopella leafhopper genus group (Auchenorrhyncha, Cicadellidae, Ulopinae) with description of a new genus and species collected from pitfall traps in Zambia
FIGURE 2. Kafulopa bicolor, external features and genitalia: a, face; b, right fore leg, lateral view; c, right fore tibia, in cross section near apex; d, right hind femur (apex to top); e, right hind leg, dorsal view; f, right hind leg, ventral view; g, right hind tibia, in cross section at midlength; h – j, male genital capsule, h, lateral view, i, dorsal view, j, ventral view (arrow indicates fused basal lobes of subgenital plates); k, aedeagus, lateral view; l, apex of aedeagus, ventral view; m, second valvulae lateral view; n, first valvulae, lateral view (Abbreviations: AD: anterior dorsal, AV: anterior ventral, PD: posterior dorsal, PV: posterior ventral).
FIGURE 1 in Review of the Ulopella leafhopper genus group (Auchenorrhyncha, Cicadellidae, Ulopinae) with description of a new genus and species collected from pitfall traps in Zambia
FIGURE 1. Kafulopa bicolor: a, dorsal habitus (holotype) scale bar 1 mm; b, lateral habitus (holotype); c, face (paratype), d, apex of female abdomen in ventral view (paratype).
Supplementary material 5: Bombus spp trapped in Palmer Alaska, 2009 from: Bumble Bees (Hymenoptera: Apidae: Bombus spp.) of Interior Alaska: Species Composition, Distribution, Seasonal Biology, and Parasites - Biodiversity Data Journal 3: e5085 (08 May 2015) https://doi.org/10.3897/BDJ.3.e5085
1040 specimens of fourteen species trapped using Blue Vane pollinator traps with counts of queens, workers, and males by date.
Supplementary material 3: Bombus spp trapped in Fairbanks Alaska, 2009 from: Bumble Bees (Hymenoptera: Apidae: Bombus spp.) of Interior Alaska: Species Composition, Distribution, Seasonal Biology, and Parasites - Biodiversity Data Journal 3: e5085 (08 May 2015) https://doi.org/10.3897/BDJ.3.e5085
2,131 specimens of fifteen species trapped using Blue Vane pollinator traps with counts of queens, workers, and males by date.
Supplementary material 2: Bombus spp trapped in Delta Junction Alaska, 2010 from: Bumble Bees (Hymenoptera: Apidae: Bombus spp.) of Interior Alaska: Species Composition, Distribution, Seasonal Biology, and Parasites - Biodiversity Data Journal 3: e5085 (08 May 2015) https://doi.org/10.3897/BDJ.3.e5085
1812 specimens of sixteen species trapped using Blue Vane pollinator traps with counts of queens, workers, and males by date.
Supplementary material 1: Bombus spp trapped in Delta Junction Alaska, 2009 from: Bumble Bees (Hymenoptera: Apidae: Bombus spp.) of Interior Alaska: Species Composition, Distribution, Seasonal Biology, and Parasites - Biodiversity Data Journal 3: e5085 (08 May 2015) https://doi.org/10.3897/BDJ.3.e5085
2,446 specimens of sixteen species trapped using Blue Vane pollinator traps with counts of queens, workers, and males by date.
Supplementary material 4: Bombus spp trapped in Fairbanks Alaska, 2010 from: Bumble Bees (Hymenoptera: Apidae: Bombus spp.) of Interior Alaska: Species Composition, Distribution, Seasonal Biology, and Parasites - Biodiversity Data Journal 3: e5085 (08 May 2015) https://doi.org/10.3897/BDJ.3.e5085
57 specimens of seven species trapped using Blue Vane pollinator traps with counts of queens, workers, and males by date.
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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.