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1,630 results for “Occupations”
Leopard (Panthera pardus) occupancy in the Chure range of Nepal
<p><span>Conservation of large carnivores like leopards requires large and interconnected habitats. Despite the wide geographic range of the leopard globally, only 17% of their habitat is within protected areas. Leopards are widely distributed in Nepal but their population status and occupancy is poorly understood. We carried out the sign-based leopard occupancy survey across the entire Chure range (~19,000 km<sup>2</sup>)to understand the habitat occupancy along with the covariates affecting their occupancy. Leopard signs were obtained from in 70 out of 223 grids surveyed, with a naïve leopard occupancy of 0.31. The model-averaged leopard occupancy was estimated to be 0.5732 (SE 0.0082) with a replication level detection probability of 0.2554 (SE 0.1142). The top model shows the additive effect of wild boar, ruggedness, presence of livestock and human population density positively affecting the leopard occupancy. The detection probability of leopard was higher outside the protected areas, less in the high NDVI (normalized difference vegetation index) areas, and higher in the areas with livestock presence. Presence of wild boar was strong predictor of leopard occupancy followed by presence of livestock, ruggedness and human population density. Leopard occupancy was higher in west Chure (0.70±SE 0.047) having five protected areas compared to east Chure (0.46 ±SE0.043) with no protected areas. Protected areas and prey species had positive influence on leopard occupancy in west Chure range. Similarly in the east Chure, the leopard occupancy increased with prey, NDVI, and terrain ruggedness. Enhanced law enforcement and mass awareness activities are necessary to reduce poaching/killing of wild ungulates and leopards in the Chure range to increase leopard occupancy. In addition, maintaining the sufficient natural prey base can contribute to minimize the livestock depredation and hence, decrease the human-leopard conflict in the Chure range. </span></p>
Figure 1 in Occupation dynamics and nesting behaviours of Xylocopa frontalis (Olivier) (Hymenoptera: Apidae) in artificial shelters
Figure 1. Temporal variation of the number of Xylocopa frontalis nesting females and the number of brood cells produced in the shelters at the Panga Ecological Station (PES) and at the Água Limpa Experimental Farm (ALEF) from April 2012 to March 2013.
Human recreation impacts seasonal activity and occupancy of American black bears (Ursus americanus) across the urban-wildlife interface
<p>The datasets used for all analyses throughout the study that are downloaded from the Yooper Wildlife Watch Project found on Zooniverse. </p>
Collaboration for conservation: assessing country-wide carnivore occupancy dynamics from sparse data
<p><strong>Aim:</strong> Assessing the distribution and persistence of species across their range is a crucial component of wildlife conservation. It demands data at adequate spatial scales and over extended periods of time, which may only be obtained through collaborative efforts, and the development of methods that integrate heterogeneous datasets. We aimed to combine existing data on large carnivores to evaluate population dynamics and improve knowledge on their distribution nationwide.</p> <p><strong>Location:</strong> Botswana</p> <p><strong>Methods:</strong> Between 2010 – 2016, we collated data on African wild dog, cheetah, leopard, brown and spotted hyaena, and lion gathered with different survey methods by independent researchers across Botswana. We used a multi-species, multi-method dynamic occupancy model to analyse factors influencing occupancy, persistence, and colonisation, while accounting for imperfect detection. Lastly, we used the gained knowledge to predict the probability of occurrence of each species countrywide.</p> <p><strong>Results:</strong> Wildlife areas and communal rangelands had similar occupancy probabilities for most species. Large carnivore occupancy was low in commercial farming areas and where livestock density was high, except for brown hyaena. Lion occupancy was negatively associated with human density; lion and spotted hyena occupancy was high where rainfall was high, while the opposite applied to brown hyaena. Lion and leopard occupancy remained constant countrywide over the study period. African wild dog and cheetah occupancy declined over time in the south and north, respectively, whereas both hyaena species expanded their ranges. Countrywide predictions identified the highest occupancy for leopards and lowest for the two hyaena species.</p> <p><strong>Main Conclusions:</strong> We highlight the necessity of data sharing and propose a generalisable analytical method that addresses the challenges of heterogeneous data common in ecology. Our approach, which enables a comprehensive multi-species assessment at large spatial and temporal scales, supports the development of data-driven conservation guidelines and the implementation of evidence-based management strategies nationally and internationally.</p>
Automated bird sound classifications of long-duration recordings produce occupancy model outputs similar to manually annotated data
<p>Occupancy modeling is used to evaluate avian distributions and habitat associations, yet it typically requires extensive survey effort because a minimum of three repeat samples are required for accurate parameter estimation. Autonomous recording units (ARUs) can reduce the need for surveyors on site, yet ARUs utility were limited by hardware costs and the time required to manually annotate recordings. Software that identifies bird vocalizations may reduce expert time needed, if classification is sufficiently accurate. We assessed the performance of BirdNET – an automated classifier capable of identifying vocalizations from >900 North American and European bird species – by comparing automated to manual annotations of recordings of 13 breeding bird species collected in northwestern California. We compared the parameter estimates of occupancy models evaluating habitat associations supplied with manually annotated data (9 min recording segments) to output from models supplied with BirdNET detections. We used three sets of BirdNET output to evaluate the duration of automatic annotation needed to approach manually annotated model parameter estimates: 9-min, 87-min, and 87-min of high-confidence detections. We incorporated 100 3-sec manually validated BirdNET detections per species to estimate true and false positive rates within an occupancy model. BirdNET correctly identified 90% and 65% of the bird species a human detected when data were restricted to detections exceeding a low or high confidence score threshold, respectively. Occupancy estimates, including habitat associations, were similar regardless of method. Precision (proportion of true positives to all detections) was >0.70 for 9 of 13 species, and a low of 0.29. However, processing of longer recordings was needed to rival manually annotated data. We conclude that BirdNET is suitable for annotating multispecies recordings for occupancy modeling when extended recording durations are used. Together, ARUs and BirdNET may benefit monitoring and, ultimately, conservation of bird populations by greatly increasing monitoring opportunities. </p>
Allegheny Woodrat occupancy across Western Virginia, United States
<p>The Allegheny woodrat (<em>Neotoma magister</em>), a rock outcrop habitat specialist, has suffered drastic reductions in geographic range over the past 40 years. Previous research has examined habitat characteristics at varying spatial scales, but none have used occupancy modeling to examine trends over time. Therefore, we used presence/absence data from live trapping to assess environmental variables likely to influence Allegheny woodrat occupancy and detection patterns at a regional scale across western Virginia, USA, from 2009 to 2011. We observed a shift in occupancy and detection rates across years with a peak in 2009, a decline in 2010, and an apparent recovery in 2011. We found significant isolation by distance effect influencing woodrat occupancy across the region, with occupancy linked to sites in closer proximity to other occupied locations. Occupancy increased in oak and hickory forests, suggesting woodrat occurrence increases in forest types with a higher abundance of hard and soft mast-producing species. We found variable effects of elevation over time, with higher occupancy at higher elevations in 2009 but at lower elevations in 2010, which may be explained by variation in winter severity and mast abundance across years. Allegheny woodrat management should include activities to promote and retain mast-producing species at higher elevations to offset potential subpopulation contractions during harsh winters.</p>
Long-term monitoring in endangered woodlands shows effects of multi-scale drivers on bird occupancy
<p>Occupancy predictor data, detection predictor data, and species detections from sites in remnant Box Gum Grassy Woodland patches in south-eastern Australia. Only sites, species, and predictors used in our statistical analysises included. For privacy, predictors have been standardised (mean = 0, standard deviation = 1) and latitude and longitude have been offset by random vectors.</p>
Replication package for: Hours Constraints, Occupational Choice, and Gender: Evidence from Medical Residents
<p>This is the replication package for:</p> <p>Wasserman, Melanie (forthcoming) "Hours Constraints, Occupational Choice, and Gender: Evidence from Medical Residents" Review of Economic Studies</p> <p>It contains:</p> <ul> <li>README file</li> <li>do files to reproduce the main tables and figures</li> <li>data files for all reproducible analyses</li> <li>all reproducible results</li> </ul>
Indoor Positioning Simulation For Examination And Correction Of Occupancy Limits In Architectural Design
<p>Dataset that contains the images of scenarios used for the analysis and the analysis itself.</p>
Occupancy modeling of habitat use by white-tailed deer after more than a decade of exclusion in the boreal forest
<p>The exclusion of herbivores in forest areas is a strategy used to reduce the impact of selective browsing and increase the regeneration of desired plant species. On Anticosti Island (Québec, Canada), selective browsing by white-tailed deer prevents the regeneration of balsam fir – white birch forests leading to their conversion into white spruce forests. Large deer exclosures were established for ca . 10 to 12 years in clear-cuts with patches of residual forest from 2001 to 2006 to assist in the natural regeneration of fir stands and to provide shelter and food resources for deer. Our objective was to assess how deer use exclosures after the removal of fences according to their spatial configuration and habitat composition. We randomly distributed automatic cameras for periods of 14 days during summer in six exclosures ranging from 3.1 to 11.2 km2 (n=25 cameras per exclosure) from which deer were reduced for 10 to 12 years. We compared candidate occupancy models that included spatial configuration and food resource variables while simultaneously controlling for variables affecting detection probability. We obtained weak evidence that deer habitat use increased by 19% when forage resources, represented by the cover of <em>Cornus canadensis</em>, increased from 0 to 100%. None of the other variables (distance between the border of exclosures and cameras and distance between forest patches and cameras) was retained, suggesting that the use of regenerating forests by deer in summer after a period of exclusion is related to forage availability and therefore, any forest management that improves food production during summer should help maintain or increase habitat use by deer.</p>
Sponge species identity and morphology shape occupancy patterns of a Caribbean sponge-dwelling goby (Elacatinus horsti)
<p>An R studio project that includes original transect survey data files used to examine the influence of sponge species and morphology on resident fish (goby) occupancy. Associated R code in Script folders 1-3 used to test for differences in goby-occupied sponge abundance across different sites, and test for the effects of different sponge characteristics on goby occupancy and group size. </p> <p> </p>
Sierra Nevada Barred Owl Occupancy Data 2017-2018
<p>Do not use without author's permission.</p>
Dataset: Occupancy Detection, Tracking, and Estimation Using a Vertically Mounted Depth Sensor [Sample Dataset]
<p>[Sample Dataset File.]</p> <p>Occupancy detection, tracking, and estimation has a wide range of applications including improving building energy efficiency, safety, and security of the occupants. As depth sensors are getting cheaper, they offer a viable solution to estimate occupancy accurately in a non-privacy invasive manner. Even though there are publicly available depth datasets, they do not consider placing the sensor in the ceiling looking downwards to estimate occupancy. We deployed four Kinect for XBOX One in four CMU classrooms and conference rooms for a period of four weeks in 2017 and collected over 6 TB of depth data. We annotate this huge dataset by labelling bounding boxes around occupants and release the annotated dataset. </p>
Occupational Differences in Parental Perspectives on the Family's Role in Preventing Gender-Based Violence
<p><strong><em><span>Occupational Differences in Parental Perspectives on the Family's Role in Preventing Gender-Based Violence</span></em></strong></p>
FIG. 4 in Staggered-Entry Analysis of Breeding Phenology and Occupancy Dynamics of Arizona Toads from Historically Occupied Habitats of New Mexico, USA
FIG. 4. Estimated detection probability from the simple multi-season model fitted with calling data from historical and control sites, based on the relationship between detection and Julian date from the simple multi-season occupancy model. Julian values represent only the values present in our data set and range from 1 March to 30 May (Julian days 60–150).
FIG. 3 in Staggered-Entry Analysis of Breeding Phenology and Occupancy Dynamics of Arizona Toads from Historically Occupied Habitats of New Mexico, USA
FIG. 3. Estimated probabilities of yearly occupancy (y-axis; 6 95% CI) from the historically occupied (orange) and control (blue) sites for the (A) staggered-entry model (SE) and the (B) simple multi-season (SMS) model. Dotted error bars represent years when surveys were not conducted.
FIG. 2 in Staggered-Entry Analysis of Breeding Phenology and Occupancy Dynamics of Arizona Toads from Historically Occupied Habitats of New Mexico, USA
FIG. 2. Estimated probabilities of Arizona Toads entering sites between subsequent surveys (orange), given that they have not previously entered, based on the estimated relationship between entry and Julian date. Estimated probabilities of Arizona Toad departing sites between subsequent surveys (blue), given that they are already present, based on the estimated relationship between departure and Julian date. Yellow points show the probabilities that toads were available to be detected for each day. Julian values range from 1 March to 30 May.
FIG. 1 in Staggered-Entry Analysis of Breeding Phenology and Occupancy Dynamics of Arizona Toads from Historically Occupied Habitats of New Mexico, USA
FIG. 1. Study area in southwestern New Mexico showing historically occupied (n ¼ 86; red circles) and control (n ¼ 59; blue triangles) waterbodies sampled during the 2013–2016 and 2019 breeding seasons for the Arizona Toads (Anaxyrus microscaphus). Filled shapes represent sites where we detected toads at least once, and open shapes represent sites where we never detected toads. Basemap by Stamen Design, under CC BY 3.0.
Data from larval habitat occupancy and habitat attribute surveys.
Open the record for dataset details and reuse information.
Figure 2 in Density, occupancy and detectability of tortoise species (Chelonoidis spp.) in the Atlantic Forest: implications for conservation and management
Figure 2. Relationship between the probability of detection of Chelonoidis denticulatus (A) and Chelonoidis carbonarius (B) with the accumulated rainfall of the day before sampling (previous rainfall) in the Vale Natural Reserve, Brazil.
ScienceDex guides
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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.