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585 results for “Camera trap”

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dryad36/100

A novel camera trapping method for individually identifying pumas by facial features

Camera traps (CTs), used in conjunction with capture-mark-recapture analyses (CMR; photo-CMR), are a valuable tool for estimating abundances of rare and elusive wildlife. However, a critical requirement of photo-CMR is that individuals are identifiable in CT images (photo-ID). Thus, photo-CMR is generally limited to species with conspicuous pelage patterns (e.g., stripes or spots) using lateral-view images from CTs stationed along travel paths. Pumas (Puma concolor) are an elusive species for which CTs are highly effective at collecting image data, but their suitability to photo-ID is controversial due to their lack of pelage markings. For a wide range of taxa, facial features are useful for photo-ID, but this method has generally been limited to images collected with traditional handheld cameras. Here we evaluate the feasibility of using puma facial features for photo-ID in a CT framework. We consider two issues: 1) the ability to capture puma facial images using CTs, and 2) whether facial images improve human ability to photo-ID pumas. We tested a novel CT accessory that used light and sound to attract the attention of pumas, thereby collecting face images for use in photo-ID. Face captures rates increased at CTs that included the accessory (n = 208, χ2 = 43.23, P ≤ 0.001). To evaluate if puma faces improve photo-ID, we measured the inter-rater agreement of 5 independent assessments of photo-ID for 16 of our puma face capture events. Agreement was moderate to good (Fleiss' kappa = 0.54, 95% CI = 0.48–0.60), and was 92.90% greater than a previously published kappa using conventional CT methods. This study is the first time such a technique has been used for photo-ID, and we believe a promising demonstration of how photo-ID may be feasible for an elusive but unmarked species.

opencc-zeroJan 2023View details →

zenodo36/100

Image dataset for training of an insect detection model for the Insect Detect DIY camera trap

This dataset contains images of an artifical flower platform with different insects sitting on it or flying above it. All images were automatically recorded with the <a href="https://maxsitt.github.io/insect-detect-docs/">Insect Detect DIY camera trap</a>, a hardware combination of the Luxonis OAK-1, Raspberry Pi Zero 2 W and PiJuice Zero pHAT for automated insect monitoring (<a href="https://doi.org/10.1101/2023.12.05.570242">bioRxiv preprint</a>).<h2>Classes</h2>The following object classes were annotated in this dataset:<ul><li>wasp (mostly Vespula sp.)</li><li>hbee (Apis mellifera)</li><li>fly (mostly Brachycera)</li><li>hovfly (various Syrphidae, e.g. Episyrphus balteatus)</li><li>other (all Arthropods with insufficient occurences, e.g. various Hymenoptera, true bugs, beetles)</li><li>shadow (shadows of the recorded insects)</li></ul>View the <a href="https://universe.roboflow.com/maximilian-sittinger/insect_detect_detection/health">Health Check</a> for more info on class balance.<h2>Versions</h2><ul><li><a href="https://universe.roboflow.com/maximilian-sittinger/insect_detect_detection/dataset/4">v4 insect_detect_416_1class</a><ul><li>squashed to square (aspect ratio 1:1)</li><li>downscaled to 416x416 pixel</li><li>all classes merged into one class ("insect")</li></ul></li><li><a href="https://universe.roboflow.com/maximilian-sittinger/insect_detect_detection/dataset/5">v5 insect_detect_raw_4K</a><ul><li>original images in 4K resolution (3840x2160 pixel)</li></ul></li><li><a href="https://universe.roboflow.com/maximilian-sittinger/insect_detect_detection/dataset/7">v7 insect_detect_320_1class</a><ul><li>squashed to square (aspect ratio 1:1)</li><li>downscaled to 320x320 pixel</li><li>all classes merged into one class ("insect")</li></ul></li></ul><h2>Deployment</h2>You can use this dataset as starting point to train your own insect detection models. Check the <a href="https://maxsitt.github.io/insect-detect-docs/modeltraining/train_detection/">model training instructions</a> for more information.Open source Python scripts to deploy the trained models can be found at the <a href="https://github.com/maxsitt/insect-detect">insect-detect GitHub repo</a>.

opencc-by-4.0Mar 2023View details →

dryad36/100

Mammalian Camera Trap Data; Northwest Arkansas

The human footprint is rapidly expanding, and wildlife habitat is continuously being converted to human residential properties. Surviving wildlife that reside in developing areas are displaced to nearby undeveloped areas. However, some animals can co-exist with humans and acquire the necessary resources (food, water, shelter) within the human environment. This may be particularly true when development is low intensity, as in residential suburban yards. Yards are individually managed "greenspaces" that can provide a range of food (e.g., bird feeders, compost, gardens), water (bird baths and garden ponds), and shelter resources (e.g., brush-piles, outbuildings) and are surrounded by varying landscape cover. To evaluate which residential landscape and yard features influence the richness and diversity of mammalian herbivores and mesopredators; we deployed wildlife game cameras in 46 residential yards in summer 2021 and 96 yards in summer 2022. We found that mesopredator diversity had a negative relationship with fences and was positively influenced by the number of bird feeders present in a yard. Mesopredator richness increased with the amount of forest within 400m of the camera. Herbivore diversity and richness were positively correlated to the area of forest within 400m surrounding yard and by garden area within yards, respectively. Our results suggest that while landscape does play a role in the presence of wildlife in a residential area, homeowners also have agency over the richness and diversity of mammals occurring in their yards based on the features they create or maintain on their properties.

opencc-zeroApr 2023View details →

zenodo36/100

Adapting camera-trap placement based on animal behaviour for rapid detection: a focus on the Endangered, white-bellied pangolin (Phataginus tricuspis)

Table containing detection data of species using two camera trap placement strategies (log vs non-log)

opencc-by-4.0Apr 2023View details →

dryad36/100

Camera trap grey squirrel photograph data

Effective wildlife population management requires an understanding of the abundance of the target species. In the UK, the increase in numbers and range of the non-native invasive grey squirrel Sciurus carolinensis poses a substantial threat to the existence of the native red squirrel S. vulgaris, to tree health, and to the forestry industry. Reducing the number of grey squirrels is crucial to mitigate their impacts. Camera traps are increasingly used to estimate animal abundance, and methods have been developed that do not require the identification of individual animals. Most of these methods have been focussed on medium to large mammal species with large range sizes and may be unsuitable for measuring local abundances of smaller mammals that have variable detection rates and hard-to-measure movement behaviour. The aim of this study was to develop a practical and cost-effective method, based on a camera trap index, that could be used by practitioners to estimate target densities of grey squirrels in woodlands to provide guidance on the numbers of traps or contraceptive feeders required for local grey squirrel control. Camera traps were deployed in ten independent woods of between 6 and 28 ha in size. An index, calculated from the number of grey squirrel photographs recorded per camera per day had a strong linear relationship (R2 = 0.90) with the densities of squirrels removed in trap and dispatch operations. From different time filters tested, a 5 minute filter was applied, where photographs of squirrels recorded on the same camera within 5 minutes of a previous photograph were not counted. There were no significant differences between the number of squirrel photographs per camera recorded by three different models of camera, increasing the method's practical application. This study demonstrated that a camera index could be used to inform the number of feeders or traps required for grey squirrel management through culling or contraception. Results could be obtained within six days without requiring expensive equipment or a high level of technical input. This method can easily be adapted to other rodent or small mammal species, making it widely applicable to other wildlife management interventions.

opencc-zeroMay 2023View details →

zenodo36/100

Data from: Evaluating predator control using two non-invasive population metrics: a camera trap activity index and density estimation from scat genotyping

Includes datasets from the Wimmera and Mallee, Victoria, Australia: - Fox camera trap data used to model activity - Fox scat SECR capture and trap files used to model density

opencc-by-4.0Feb 2022View details →

dryad36/100

Data from: Using camera traps to estimate habitat preferences and occupancy patterns of vertebrates in boreal wetlands

Wetlands are a critical habitat for boreal mammals and birds that rely on them for breeding, foraging, and resting. However, wetlands in boreal regions are increasingly experiencing natural and human pressures. These impacts can lead to a reduction in the availability of wetland habitats for boreal mammals and birds that rely on wetlands for breeding, foraging, and resting. To inform management and conservation, camera traps provide an opportunity to survey mammals and birds to investigate their habitat preferences. We aimed to evaluate the effect of habitat features on the occupancy of mammals and birds in boreal wetlands. We used a multispecies occupancy model to estimate the habitat associations of 11 mammals and 45 avian species detected at 50 sampling ponds during the summers of 2018 and 2019 in Northern Quebec. Our results indicate that certain mammals, such as Red Fox and River Otters, and birds including the American Pipit, Common Raven, Hooded Merganser, and Greater Yellowlegs showed a preference for peatland ponds, whereas the Common Grackle preferred beaver ponds. We found few effects of distance to roads, and no effect of amount of forest cover on species occupancy. The occupancy of 27% of mammals and 24% of birds decreased with increasing latitude. These findings offer valuable insights for informing conservation initiatives focused on the preservation of wetlands in northern Quebec. By discerning the specific types of ponds preferred by each species, conservationists can strategically ensure the preservation and proper management of these habitats, thereby enhancing their conservation efforts.

opencc-zeroOct 2023View details →

dryad36/100