Towards a best‐practices guide for camera trapping: assessing differences among camera trap models and settings under field conditions

ResumenEn el estado de Guanajuato se confirmó la presencia de tlalcoyote (Taxidea taxus) mediante fototrampeo. Estos registros se localizan en la zona de influencia de la Reserva de la Biosfera Sierra Gorda de Guanajuato (RBSGG) y complementan ellistado de mamíferos reportados en la reserva. Los registros más cercanos de tlalcoyote se localizan a 90 km al noroeste en el estado de San Luis Potosíy a 105 km al suroeste del registro colectado en Silao, Guanajuato por Alfredo Dugès en 1874. Es fundamental incluir al tlalcoyote dentro del plan de manejo de la rbsgg con el fin de implementar acciones para su monitoreo y conservación a largo plazo, así como confirmar si en la región puede existir una población establecida y que no se trate de individuos errantes.Palabras clave: cámaras trampa, matorral xerófilo, mustelidae, Sierra Gorda, tejón norteamericano.AbstractIn Guanajuato state is confirmed the presence of tlalcoyote (Taxidea taxus) by camera trapping. These records are located in the influence area of the Sierra Gorda of Guanajuato Biosphere Reserve (RBSGG) and complement the list of mammals reported for the reserve. The nearest tlalcoyote records are located 90 km at northwest in San Luis Potosí state and 105 km at southwest from the recordcollected in Silao, Guanajuato by Alfredo Dugès in 1874. Is essential to include the tlalcoyote within the management plan of the rbsgg to implement actions of monitoring and conservation and confirm that in the region there may be an established population and it’s are not of errant individuals.Key words: American Badger, camera trap, mustelidae, Sierra Gorda, xerophytic scrub.

Download Full-text

Counting Sunda clouded leopards with confidence: incorporating individual heterogeneity in density estimates

Oryx ◽

10.1017/s0030605318001503 ◽

2019 ◽

pp. 1-10 ◽

Cited By ~ 5

Author(s):

Azlan Mohamed ◽

Rahel Sollmann ◽

Seth Timothy Wong ◽

Jürgen Niedballa ◽

Jesse F. Abrams ◽

...

Keyword(s):

Population Density ◽

Large Scale ◽

Null Model ◽

Camera Trap ◽

Camera Trapping ◽

Individual Heterogeneity ◽

Sampling Effort ◽

Density Estimates ◽

Clouded Leopard ◽

Forest Reserves

AbstractEven with intensive sampling effort, data often remain sparse when estimating population density of elusive species such as the Sunda clouded leopard Neofelis diardi. An inadequate number of recaptures can make it difficult to account for heterogeneity in detection parameters. We used data from large-scale camera-trapping surveys in three forest reserves in Sabah, Malaysian Borneo, to (1) examine whether a high-density camera-trap network increases the number of recaptures for females, which tend to be more difficult to detect, thus improving the accuracy of density estimates; (2) compare density estimates from models incorporating individual heterogeneity in detection parameters with estimates from the null model to evaluate its potential bias; and (3) investigate how the size of the camera-trap grid affects density and movement estimates. We found that individual heterogeneity could not be incorporated in the single-site data analysis and only conservative null model estimates could be generated. However, aggregating data across study sites enabled us to account for individual heterogeneity and we estimated densities of 1.27–2.82 individuals/100 km2, 2–3 times higher than estimates from null models. In light of these findings, it is possible that earlier studies underestimated population density. Similar densities found in well-managed forest and recently selectively logged forest suggest that Sunda clouded leopards are relatively resilient to forest disturbances. Our analysis also revealed that camera-trapping grids for Sunda clouded leopard density estimations should cover large areas (c. 250 km2), although smaller grids could be appropriate if density or detectability are higher.

Download Full-text

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

Australian Mammalogy ◽

10.1071/am15016 ◽

2016 ◽

Vol 38 (1) ◽

pp. 44 ◽

Cited By ~ 10

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.

Download Full-text

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

Australian Mammalogy ◽

10.1071/am14021 ◽

2015 ◽

Vol 37 (1) ◽

pp. 1 ◽

Cited By ~ 28

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.

Download Full-text

Best practices for reporting individual identification using camera trap photographs

Global Ecology and Conservation ◽

10.1016/j.gecco.2020.e01294 ◽

2020 ◽

Vol 24 ◽

pp. e01294

Author(s):

Yan Ru Choo ◽

Enoka P. Kudavidanage ◽

Thakshila Ravindra Amarasinghe ◽

Thilina Nimalrathna ◽

Marcus A.H. Chua ◽

...

Keyword(s):

Best Practices ◽

Camera Trap ◽

Individual Identification

Download Full-text

Camtrap DP: A frictionless data exchange format for camera trapping data

Biodiversity Information Science and Standards ◽

10.3897/biss.5.73188 ◽

2021 ◽

Vol 5 ◽

Author(s):

Peter Desmet ◽

Jakub Bubnicki ◽

Ben Norton

Keyword(s):

Data Management ◽

Data Exchange ◽

Species Recognition ◽

Camera Trap ◽

Camera Trapping ◽

Essential Information ◽

Data Exchange Format ◽

Exchange Format ◽

Darwin Core ◽

Biodiversity Information

Camera trapping is one of the most important technologies in conservation and ecological research and a well-established, non-invasive method of collecting field data on animal abundance, distribution, behaviour, temporal activity, and space use (Wearn and Glover-Kapfer 2019). Collectively, camera trapping projects are generating a massive and continuous flow of data, consisting of images and videos (with and without animal observations) and associated identifications (Scotson et al. 2017, Kays et al. 2020). In recent years, significant progress has been made by the global camera trapping community to resolve the challenges this brings, from the development of specialized data management tools and analytical packages, to the application of cloud computing and artificial intelligence to automate species recognition (Tabak et al. 2018). However, to effectively exchange camera trap data between infrastructures and to (automatically) harmonize data into large-scale wildlife datasets, there is a need for a common data exchange format—one that captures the essential information about a camera trap study, allows expression of different study and identification approaches, and aligns well with existing biodiversity standards such as Darwin Core (Wieczorek et al. 2012). Here we present Camera Trap Data Package (Camtrap DP), a data exchange format for camera trap data. It is managed by the Machine Observations Interest Group of Biodiversity Information Standards (TDWG) and developed publicly, soliciting community feedback for every change. Camtrap DP is built on Frictionless Standards, a set of generic specifications to describe and package (tabular) data and metadata. Camtrap DP extends these with specific requirements and constraints for camera trap data. By building on an existing framework, users can employ existing open source software to read and validate Camtrap DP formatted data. Validation especially is useful to automatically check if provided data meets the requirements set forth by Camtrap DP, before analysis or integration. Supported by the major camera trap data management systems e.g. Agouti, TRAPPER, eMammal, and Wildlife Insights, Camtrap DP is reaching its first stable version. The first Camtrap DP dataset was published on Zenodo (Cartuyvels et al. 2021b). This dataset was also published to the Global Biodiversity Information Facility (GBIF) (Cartuyvels et al. 2021a), demonstrating the ability and limitations of transforming the data to the Darwin Core standard.

Download Full-text

Best practices and software for the management and sharing of camera trap data for small and large scales studies

Remote Sensing in Ecology and Conservation ◽

10.1002/rse2.54 ◽

2017 ◽

Vol 3 (3) ◽

pp. 158-172 ◽

Cited By ~ 14

Author(s):

Lorraine Scotson ◽

Lisa R. Johnston ◽

Fabiola Iannarilli ◽

Oliver R. Wearn ◽

Jayasilan Mohd-Azlan ◽

...

Keyword(s):

Best Practices ◽

Camera Trap

Download Full-text

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

Oryx ◽

10.1017/s0030605319001364 ◽

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.

Download Full-text

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

Animals ◽

10.3390/ani9060388 ◽

2019 ◽

Vol 9 (6) ◽

pp. 388 ◽

Cited By ~ 3

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.

Download Full-text

Ocelot Leopardus pardalis in Belize: the impact of trap spacing and distance moved on density estimates

Oryx ◽

10.1017/s0030605307000518 ◽

2007 ◽

Vol 41 (4) ◽

pp. 469-477 ◽

Cited By ~ 99

Author(s):

Adam Dillon ◽

Marcella J. Kelly

Keyword(s):

Camera Trap ◽

Pine Forest ◽

Camera Trapping ◽

Buffer Size ◽

Size Analysis ◽

Wet Season ◽

Density Estimates ◽

Leopardus Pardalis ◽

Broad Leaf ◽

The Impact

AbstractWe used remote cameras to obtain information on an elusive species and to examine the effects of different camera trapping methodologies on abundance estimates. We determined activity pattern, trail use, trap success, and density of ocelot Leopardus pardalis in seven camera-trap surveys across two habitat types in western Belize: tropical broad-leaf rainforest and tropical pine forest. Ocelots in the rainforest were active mostly at night, in particular immediately after sunset, and they travelled on low-use roads (especially in the wet season) and high-use roads (especially in the dry season) more than established and newly cut trails. Trap success was relatively high in the rainforest (2.11–6.20 captures per 100 trap nights) and low in the pine forest (0.13–0.15 captures per 100 trap nights). Camera trapping combined with mark-recapture statistics gave densities of 25.82–25.88 per 100 km2 in the broad-leaf versus 2.31–3.80 per 100 km2 in the pine forest. Density estimates increased when animals repeatedly captured at the same camera (zero-distance moved animals) were included in the buffer size analysis. Density estimates were significantly negatively correlated with distance between cameras. We provide information on ocelot population status from an unstudied portion of its range and advise that camera trap methodologies be standardized to permit comparisons across sites.

Download Full-text