A permanent security post for camera trapping

2013 ◽  
Vol 35 (1) ◽  
pp. 123 ◽  
Author(s):  
Paul D. Meek ◽  
Guy-Anthony Ballard ◽  
Peter J. S. Fleming
Keyword(s):  
Wildlife Management ◽  
Camera Trap ◽  
Camera Traps ◽  
Camera Trapping ◽  
Private Enterprises ◽  
Government Agencies ◽  
Animal Activity

As the use of camera traps in wildlife management in Australia rapidly increases, government agencies, private enterprises, universities and individuals are investing considerable amounts of money in camera trap technology for research, monitoring and recreation. Often camera traps need to be placed along vehicle tracks or in obvious locations to detect animal activity. Consequently, units are frequently highly visible and therefore easily located by would-be thieves. We describe a field-tested security post design that increases security for both camera traps and data, whilst also offering a means of standardising placement.

More haste, less speed: pilot study suggests camera trap detection zone could be more important than trigger speed to maximise species detections

2018 ◽  
Vol 40 (1) ◽  
pp. 118 ◽  
Author(s):  
Bronwyn A. Fancourt ◽  
Mark Sweaney ◽  
Don B. Fletcher
Keyword(s):  
Pilot Study ◽  
Wildlife Management ◽  
Detection Probability ◽  
Field Trials ◽  
Camera Trap ◽  
Camera Traps ◽  
Detection Zone ◽  
Trigger Time ◽  
Management Actions ◽  
Context Specific

Camera traps are being used increasingly for wildlife management and research. When choosing camera models, practitioners often consider camera trigger speed to be one of the most important factors to maximise species detections. However, factors such as detection zone will also influence detection probability. As part of a rabbit eradication program, we performed a pilot study to compare rabbit (Oryctolagus cuniculus) detections using the Reconyx PC900 (faster trigger speed, narrower detection zone) and the Ltl Acorn Ltl-5310A (slower trigger speed, wider detection zone). Contrary to our predictions, the slower-trigger-speed cameras detected rabbits more than twice as often as the faster-trigger-speed cameras, suggesting that the wider detection zone more than compensated for the relatively slower trigger time. We recommend context-specific field trials to ensure cameras are appropriate for the required purpose. Missed detections could lead to incorrect inferences and potentially misdirected management actions.

Camera Trapping

2014 ◽  
Keyword(s):  
Wildlife Management ◽  
Camera Traps ◽  
Camera Trapping ◽  
Biological Knowledge ◽  
Design Standards ◽  
Future Directions ◽  
Private And Public ◽  
Selection Of ◽  
Sydney Australia

Camera trapping in wildlife management and research is a growing global phenomenon. The technology is advancing very quickly, providing unique opportunities for collecting new biological knowledge. In order for fellow camera trap researchers and managers to share their knowledge and experience, the First International Camera Trapping Colloquium in Wildlife Management and Research was held in Sydney, Australia. Camera Trapping brings together papers from a selection of the presentations at the colloquium and provides a benchmark of the international developments and uses of camera traps for monitoring wildlife for research and management. Four major themes are presented: case studies demonstrating camera trapping for monitoring; the constraints and pitfalls of camera technologies; design standards and protocols for camera trapping surveys; and the identification, management and analyses of the myriad images that derive from camera trapping studies. The final chapter provides future directions for research using camera traps. Remarkable photographs are included, showing interesting, enlightening and entertaining images of animals 'doing their thing', making it an ideal reference for wildlife managers, conservation organisations, students and academics, pest animal researchers, private and public land managers, wildlife photographers and recreational hunters.

Camera Trapping Technology and Related Advances: into the New Millennium

2020 ◽  
Vol 40 (3) ◽  
pp. 392-403 ◽  
Author(s):  
Paul D. Meek ◽  
Guy Ballard ◽  
Greg Falzon ◽  
Jaimen Williamson ◽  
Heath Milne ◽  
...  
Keyword(s):  
Wildlife Management ◽  
Survey Methods ◽  
Camera Traps ◽  
Camera Trapping ◽  
Engineering Statistics ◽  
The Usa ◽  
Computational Sciences ◽  
Processing And Storage ◽  
Methods Analytical ◽  
Analytical Tools

Camera trapping has advanced significantly in Australia over the last two decades. These devices have become more versatile and the associated computer technology has also progressed dramatically since 2011. In the USA, the hunting industry drives most changes to camera traps; however the scientific fraternity has been instrumental in incorporating computational engineering, statistics and technology into camera trap use for wildlife research. New survey methods, analytical tools (including software for image processing and storage) and complex algorithms to analyse images have been developed. For example, pattern and texture analysis and species and individual facial recognition are now possible. In the next few decades, as technology evolves and ecological and computational sciences intertwine, new tools and devices will emerge into the market. Here we outline several projects that are underway to incorporate camera traps and associated technologies into existing and new tools for wildlife management. These also have significant implications for broader wildlife management and research.

Animal detections vary among commonly used camera trap models

2017 ◽  
Vol 44 (4) ◽  
pp. 291 ◽  
Author(s):  
Michael M. Driessen ◽  
Peter J. Jarman ◽  
Shannon Troy ◽  
Sophia Callander
Keyword(s):  
Camera Trap ◽  
Camera Traps ◽  
Substantial Proportion ◽  
Multiple Camera ◽  
Animal Activity ◽  
Bait Station ◽  
Animal Images ◽  
A Site ◽  
Expensive Model ◽  
Better Than

Context Understanding how different camera trap models vary in their ability to detect animals is important to help identify which cameras to use to meet the objectives of a study. Aims To compare the efficacy of four camera trap models (representing two commonly used brands of camera, Reconyx and Scoutguard) to detect small- and medium-sized mammals and birds. Methods Four camera models were placed side by side, focused on a bait station, under field conditions, and the numbers of triggers and visits by mammals and birds were compared. Trigger=camera sensor is activated and records an image of an animal. Visit=one or a sequence of triggers containing one or more images of a species, with no interval between animal images greater than 5min. Key results The Scoutguard 530V camera recorded fewer than half of the triggers and visits by all animals that the Reconyx H600, Scoutguard 560K and Keepguard 680V cameras recorded. The latter three cameras recorded similar numbers of visits by mammals, but the Reconyx H600 recorded fewer triggers by medium-sized mammals than the Keepguard 680V. All camera models failed to detect a substantial proportion of the total known triggers and visits by animals, with a greater proportion of visits detected (14–88%) than triggers (5–83%). All camera models recorded images with no animals present (blanks), with Reconyx H600 recording the fewest blank images. Conclusions Camera trap models can vary in their ability to detect triggers and visits by small- and medium-sized mammals and birds. Some cheaper camera models can perform as well as or better than a more expensive model in detecting animals, but factors other than cost may need to be considered. Camera traps failed to detect a substantial proportion of known triggers and visits by animals. Number of visits is a more useful index of animal activity or abundance than number of triggers. Implications Variation in camera performance needs to be taken into consideration when designing or comparing camera surveys if multiple camera models are used, especially if the aim is to compare animal activity or abundance. If maximising the number of animal visits recorded at a site is important, then consideration should be given to using two or more cameras.

Can camera trapping be used to accurately survey and monitor the Hastings River mouse (Pseudomys oralis)?

2016 ◽  
Vol 38 (1) ◽  
pp. 44 ◽  
Author(s):  
Paul D. Meek ◽  
Karl Vernes
Keyword(s):  
Small Mammals ◽  
Small Mammal ◽  
Survey Methods ◽  
Camera Trap ◽  
Camera Traps ◽  
Camera Trapping ◽  
Common Element ◽  
Computer Assisted ◽  
Survey Tool ◽  
Wide Range

Camera trapping is increasingly recognised as a survey tool akin to conventional small mammal survey methods such as Elliott trapping. While there are many cost and resource advantages of using camera traps, their adoption should not compromise scientific rigour. Rodents are a common element of most small mammal surveys. In 2010 we deployed camera traps to measure whether the endangered Hastings River mouse (Pseudomys oralis) could be detected and identified with an acceptable level of precision by camera traps when similar-looking sympatric small mammals were present. A comparison of three camera trap models revealed that camera traps can detect a wide range of small mammals, although white flash colour photography was necessary to capture characteristic features of morphology. However, the accurate identification of some small mammals, including P. oralis, was problematic; we conclude therefore that camera traps alone are not appropriate for P. oralis surveys, even though they might at times successfully detect them. We discuss the need for refinement of the methodology, further testing of camera trap technology, and the development of computer-assisted techniques to overcome problems associated with accurate species identification.

The history of wildlife camera trapping as a survey tool in Australia

2015 ◽  
Vol 37 (1) ◽  
pp. 1 ◽  
Author(s):  
Paul D. Meek ◽  
Guy-Anthony Ballard ◽  
Karl Vernes ◽  
Peter J. S. Fleming
Keyword(s):  
Quantitative Research ◽  
Reaction Times ◽  
Historical Review ◽  
Camera Trap ◽  
Recent Change ◽  
Camera Traps ◽  
Camera Trapping ◽  
Survey Tool ◽  
Trapping Methods ◽  
Effective Models

This paper provides an historical review of the technological evolution of camera trapping as a zoological survey tool in Australia. Camera trapping in Australia began in the 1950s when purpose-built remotely placed cameras were used in attempts to rediscover the thylacine (Thylacinus cynocephalus). However, camera traps did not appear in Australian research papers and Australasian conference proceedings until 1989–91, and usage became common only after 2008, with an exponential increase in usage since 2010. Initially, Australian publications under-reported camera trapping methods, often failing to provide fundamental details about deployment and use. However, rigour in reporting of key methods has increased during the recent widespread adoption of camera trapping. Our analysis also reveals a change in camera trap use in Australia, from simple presence–absence studies, to more theoretical and experimental approaches related to population ecology, behavioural ecology, conservation biology and wildlife management. Practitioners require further research to refine and standardise camera trap methods to ensure that unbiased and scientifically rigorous data are obtained from quantitative research. The recent change in emphasis of camera trapping research use is reflected in the decreasing range of camera trap models being used in Australian research. Practitioners are moving away from less effective models that have slow reaction times between detection and image capture, and inherent bias in detectability of fauna, to more expensive brands that offer faster speeds, greater functionality and more reliability.

scholarly journals Applying camera traps to detect and monitor introduced mammals on oceanic islands

Oryx ◽  
2020 ◽  
pp. 1-8
Author(s):  
Lucas Lamelas-López ◽  
Iván Salgado
Keyword(s):  
Introduced Species ◽  
Large Scale ◽  
Camera Trap ◽  
Oceanic Islands ◽  
Camera Traps ◽  
Camera Trapping ◽  
Sampling Effort ◽  
Terrestrial Mammals ◽  
Management Actions ◽  
Survey Technique

Abstract The introduction of mammal predators has been a major cause of species extinctions on oceanic islands. Eradication is only possible or cost-effective at early stages of invasion, before introduced species become abundant and widespread. Although prevention, early detection and rapid response are the best management strategies, most oceanic islands lack systems for detecting, responding to and monitoring introduced species. Wildlife managers require reliable information on introduced species to guide, assess and adjust management actions. Thus, a large-scale and long-term monitoring programme is needed to evaluate the management of introduced species and the protection of native wildlife. Here, we evaluate camera trapping as a survey technique for detecting and monitoring introduced small and medium-sized terrestrial mammals on an oceanic island, Terceira (Azores). Producing an inventory of introduced mammals on this island required a sampling effort of 465 camera-trap days and cost EUR 2,133. We estimated abundance and population trends by using photographic capture rates as a population index. We also used presence/absence data from camera-trap surveys to calculate detection probability, estimated occupancy rate and the sampling effort needed to determine species absence. Although camera trapping requires large initial funding, this is offset by the relatively low effort for fieldwork. Our findings demonstrate that camera trapping is an efficient survey technique for detecting and monitoring introduced species on oceanic islands. We conclude by proposing guidelines for designing monitoring programmes for introduced species.

scholarly journals Improving Terrestrial Squamate Surveys with Camera-Trap Programming and Hardware Modifications

Animals ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 388 ◽  
Author(s):  
D. J. Welbourne ◽  
A. W. Claridge ◽  
D. J. Paull ◽  
F. Ford
Keyword(s):  
Focal Length ◽  
Time Lapse ◽  
Camera Trap ◽  
Camera Traps ◽  
Camera Trapping ◽  
Infrared Sensor ◽  
Vertebrate Fauna ◽  
The World ◽  
Lens Focal Length

Camera-traps are used widely around the world to census a range of vertebrate fauna, particularly mammals but also other groups including birds, as well as snakes and lizards (squamates). In an attempt to improve the reliability of camera-traps for censusing squamates, we examined whether programming options involving time lapse capture of images increased detections. This was compared to detections by camera-traps set to trigger by the standard passive infrared sensor setting (PIR), and camera-traps set to take images using time lapse in combination with PIR. We also examined the effect of camera trap focal length on the ability to tell different species of small squamate apart. In a series of side-by-side field comparisons, camera-traps programmed to take images at standard intervals, as well as through routine triggering of the PIR, captured more images of squamates than camera-traps using the PIR sensor setting alone or time lapse alone. Similarly, camera traps with their lens focal length set at closer distances improved our ability to discriminate species of small squamates. With these minor alterations to camera-trap programming and hardware, the quantity and quality of squamate detections was markedly better. These gains provide a platform for exploring other aspects of camera-trapping for squamates that might to lead to even greater survey advances, bridging the gap in knowledge of this otherwise poorly known faunal group.

scholarly journals A picture is worth a thousand words: the application of camera trapping to the study of birds

2008 ◽  
Vol 18 (S1) ◽  
pp. S144-S162 ◽  
Author(s):  
Timothy G. O'Brien ◽  
Margaret F. Kinnaird
Keyword(s):  
Finite Mixture Models ◽  
Camera Trap ◽  
Camera Traps ◽  
Camera Trapping ◽  
Individual Identification ◽  
Nest Defence ◽  
Primary Forest ◽  
Sampling Effort ◽  
Observation Process ◽  
Capture Recapture

AbstractThis study reviews the use of remotely triggered still cameras, known as camera traps, in bird research and suggests new methods useful for analyzing camera trap data. Camera trapping may be most appropriate for large, ground-dwelling birds, such as cracids and pheasants. Recent applications include documentation of occurrence of rare species and new species records, nest predation studies and behavioural studies including nest defence, frugivory, seed dispersal, and activity budgets. If bird postures are analyzed, it may be possible to develop behavioural time budgets. If birds are marked or individually identifiable, abundance may be estimated through capture-recapture methods typically used for mammals. We discourage use of relative abundance indices based on trapping effort because of the difficulty of standardizing surveys over time and space. Using the Great Argus Pheasant Argus argusianus, a cryptic, terrestrial, forest bird as an example, we illustrate applications of occupancy analysis to estimate proportion of occupied habitat and finite mixture models to estimate abundance when individual identification is not possible. These analyses are useful because they incorporate detection probabilities < 1 and covariates that affect the sample site or the observation process. Results are from camera trap surveys in the 3,568 km2 Bukit Barisan Selatan National Park, Indonesia. We confirmed that Great Argus Pheasants prefer primary forest below 500 m. We also find a decline in occupancy (6–8% yr−1). Point estimates of abundance peak in 2000, followed by a sharp decline. We discuss the effects of rarity, detection probability and sampling effort on accuracy and precision of estimates.

scholarly journals A First Step Towards Automated Species Recognition from Camera Trap Images of Mammals Using AI in a European Temperate Forest

2021 ◽  
pp. 299-310
Author(s):  
Mateusz Choiński ◽  
Mateusz Rogowski ◽  
Piotr Tynecki ◽  
Dries P. J. Kuijper ◽  
Marcin Churski ◽  
...  
Keyword(s):  
Data Processing ◽  
Large Scale ◽  
Species Recognition ◽  
Population Monitoring ◽  
Camera Trap ◽  
Camera Traps ◽  
Camera Trapping ◽  
Classification Model ◽  
Wildlife Monitoring ◽  
Species Classification

AbstractCamera traps are used worldwide to monitor wildlife. Despite the increasing availability of Deep Learning (DL) models, the effective usage of this technology to support wildlife monitoring is limited. This is mainly due to the complexity of DL technology and high computing requirements. This paper presents the implementation of the light-weight and state-of-the-art YOLOv5 architecture for automated labeling of camera trap images of mammals in the Białowieża Forest (BF), Poland. The camera trapping data were organized and harmonized using TRAPPER software, an open-source application for managing large-scale wildlife monitoring projects. The proposed image recognition pipeline achieved an average accuracy of 85% F1-score in the identification of the 12 most commonly occurring medium-size and large mammal species in BF, using a limited set of training and testing data (a total of 2659 images with animals).Based on the preliminary results, we have concluded that the YOLOv5 object detection and classification model is a fine and promising DL solution after the adoption of the transfer learning technique. It can be efficiently plugged in via an API into existing web-based camera trapping data processing platforms such as e.g. TRAPPER system. Since TRAPPER is already used to manage and classify (manually) camera trapping datasets by many research groups in Europe, the implementation of AI-based automated species classification will significantly speed up the data processing workflow and thus better support data-driven wildlife monitoring and conservation. Moreover, YOLOv5 has been proven to perform well on edge devices, which may open a new chapter in animal population monitoring in real-time directly from camera trap devices.

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