scholarly journals Optimising camera trap height and model increases detection and individual identification rates for a small mammal, the numbat (Myrmecobius fasciatus)

2020 ◽  
Author(s):  
Anke Seidlitz ◽  
Kate A. Bryant ◽  
Nicola J. Armstrong ◽  
Michael Calver ◽  
Adrian F. Wayne
Keyword(s):  
Small Mammal ◽  
Camera Trap ◽  
Individual Identification ◽  
Trap Height

Spot on: using camera traps to individually monitor one of the world’s largest lizards

2020 ◽  
Vol 47 (4) ◽  
pp. 326 ◽  
Author(s):  
Harry A. Moore ◽  
Jacob L. Champney ◽  
Judy A. Dunlop ◽  
Leonie E. Valentine ◽  
Dale G. Nimmo
Keyword(s):  
Activity Patterns ◽  
Image Data ◽  
Dorsal Surface ◽  
Camera Trap ◽  
Camera Traps ◽  
Identification Accuracy ◽  
Individual Identification ◽  
Lizard Species ◽  
Late Afternoon ◽  
Large Animals

Abstract ContextEstimating animal abundance often relies on being able to identify individuals; however, this can be challenging, especially when applied to large animals that are difficult to trap and handle. Camera traps have provided a non-invasive alternative by using natural markings to individually identify animals within image data. Although camera traps have been used to individually identify mammals, they are yet to be widely applied to other taxa, such as reptiles. AimsWe assessed the capacity of camera traps to provide images that allow for individual identification of the world’s fourth-largest lizard species, the perentie (Varanus giganteus), and demonstrate other basic morphological and behavioural data that can be gleaned from camera-trap images. MethodsVertically orientated cameras were deployed at 115 sites across a 10000km2 area in north-western Australia for an average of 216 days. We used spot patterning located on the dorsal surface of perenties to identify individuals from camera-trap imagery, with the assistance of freely available spot ID software. We also measured snout-to-vent length (SVL) by using image-analysis software, and collected image time-stamp data to analyse temporal activity patterns. ResultsNinety-two individuals were identified, and individuals were recorded moving distances of up to 1975m. Confidence in identification accuracy was generally high (91%), and estimated SVL measurements varied by an average of 6.7% (min=1.8%, max=21.3%) of individual SVL averages. Larger perenties (SVL of >45cm) were detected mostly between dawn and noon, and in the late afternoon and early evening, whereas small perenties (SVL of <30cm) were rarely recorded in the evening. ConclusionsCamera traps can be used to individually identify large reptiles with unique markings, and can also provide data on movement, morphology and temporal activity. Accounting for uneven substrates under cameras could improve the accuracy of morphological estimates. Given that camera traps struggle to detect small, nocturnal reptiles, further research is required to examine whether cameras miss smaller individuals in the late afternoon and evening. ImplicationsCamera traps are increasingly being used to monitor reptile species. The ability to individually identify animals provides another tool for herpetological research worldwide.

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.

scholarly journals Best practices for reporting individual identification using camera trap photographs

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

scholarly journals PAQUETE camtrapR PARA GESTIONAR DATOS DE FOTO-TRAMPEO: APLICACIÓN EN LA RESERVA DE LA BIOSFERA TEHUACÁN-CUICATLÁN

2017 ◽  
Vol 1 (2) ◽  
pp. 13
Author(s):  
Eva López-Tello ◽  
Salvador Mandujano
Keyword(s):  
Technological Development ◽  
Biosphere Reserve ◽  
R Package ◽  
Camera Trap ◽  
Individual Identification ◽  
Data Set ◽  
Organization And Management ◽  
R Packages ◽  
Visualization Of Data ◽  
Short Time

ResumenEl empleo de cámaras trampa es un método que se ha popularizado en la última década debido al desarrollo tecnológico que ha hecho más accesible la adquisición de este equipo. Una de las ventajas de este método es que podemos obtener mucha información en poco tiempo de diferentes especies. Sin embargo, existen pocos programas que faciliten la organización y extracción de la información de una gran cantidad de imágenes. Recientemente se ha puesto disponible libremente el paquete R llamado camtrapR, el cual sirve para extraer los metadatos de las imágenes, crear tablas de registros independientes, registros de presencia/ausencia para ocupación, y gráficos espaciales. Para comprobar la funcionalidad del programa en este artículo presentamos seis ejemplos de las principales funciones de camtrapR. Para esto se utilizó un conjunto de imágenes obtenidas con 10 cámaras-trampa en una localidad de la Reserva de la Biosfera Tehuacán-Cuicatlán. camtrapR se aplicó para probar los siguientes objetivos: organización y manejo de las fotos, clasificación por especie, identificación individual, extracción de metadatos por especie y/o individuos, exploración y visualización de datos, y exportación de datos para análisis de ocupación. Está disponible libre el código R utilizado en este trabajo. De acuerdo a los resultados obtenidos se considera que camtrapR es un paquete eficiente para facilitar y reducir el tiempo de extracción de los metadatos de las imágenes; así mismo es posible obtener los registros independientes sin errores de omisión o duplicación de datos. Además, permite crear archivos *.csv que después pueden ser analizados con otros paquetes R o programas para otros propósitos.Palabras clave: base de datos, historias de captura, metadatos, R. AbstractThe camera-trap is a method that has become popular in the last decade due to the technological development that has made the acquisition of this equipment more accessible. One of the advantages of this method is that we can get a lot of information in a short time for different species. However, there are few programs that facilitate the organization and extraction of information from large number of images. Recently, the R package called camtrapR has been made freely available, which serves to extract the metadata from the images, create independent record tables, occupation presence/absence registers and spatial graphics. To check the functionality of this package, in this article we present six examples of how to use the main functions of camtrapR. For this purpose, we used a data set of images obtained with 10 cameras in the location of the Tehuacán-Cuicatlán Biosphere Reserve. camtrapR was applied to test the following objectives: organization and management of the photos, classification by species, individual identification, extraction of metadata by species and individuals, exploration and visualization of data, and export of data for analysis of occupation. The R code used in this work is available freely in line. According to our results, camtrapR is an efficient package to facilitate and reduce the extraction time of the metadata of the images; it is also possible to obtain the independent records without errors of omission or duplication of data. In addition, it allows to create * .csv files that can then be analyzed with other R packages or programs for different objectives.Key words: capture histories, database, metadata, organization, R.

scholarly journals Chimp&See: an online citizen science platform for large-scale, remote video camera trap annotation of chimpanzee behaviour, demography and individual identification

2016 ◽  
Author(s):  
Mimi Arandjelovic ◽  
Colleen R Stephens ◽  
Maureen S McCarthy ◽  
Paula Dieguez ◽  
Ammie K Kalan ◽  
...  
Keyword(s):  
Citizen Science ◽  
General Public ◽  
Large Scale ◽  
Video Camera ◽  
Camera Trap ◽  
Scientific Data ◽  
Individual Identification ◽  
Community Size ◽  
Data Set ◽  
Effective Manner

The Pan African Programme: The cultured chimpanzee (PanAf) is a large-scale research project across the chimpanzee (Pan troglodytes) range which aims to better understand and model the socioecological and demographic drivers of chimpanzee diversity. As part of the PanAf, over 350,000 1-minute camera trap videos have been recorded. To annotate this large data set and ascertain individual chimpanzee identifications from 39 different temporary and collaborative chimpanzee research sites, we developed the web-based citizen science platform Chimp&See (www.chimpandsee.org) in collaboration with the Zooniverse. Chimp&See allows members of the general public to view the PanAf videos online and annotate which species are present and the behaviours they exhibit in each video. These citizen scientists also watch and discuss videos to determine unique chimpanzee individuals and match them from different video clips. Each video is viewed by up to 15 unique users, allowing us to obtain a confidence score based on the number of consensus matches for each identification. In this poster, we compare the accuracy and efficiency achieved by the general public on this platform to automated facial detection software and expert scientific annotators. We also evaluate whether citizen science and video camera trapping is a way forward for assessing chimpanzee age/sex structure, density and community size in a cost and time effective manner. Finally, we discuss the balance between maintaining user engagement and obtaining detailed and accurate scientific data from citizen scientists.

scholarly journals The selfie trap: A novel camera trap design for accurate small mammal identification

2018 ◽  
Vol 20 (2) ◽  
pp. 156-158 ◽  
Author(s):  
Ana Gracanin ◽  
Vanja Gracanin ◽  
Katarina M. Mikac
Keyword(s):  
Small Mammal ◽  
Camera Trap ◽  
Trap Design

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 Chimp&See: an online citizen science platform for large-scale, remote video camera trap annotation of chimpanzee behaviour, demography and individual identification

2016 ◽  
Author(s):  
Mimi Arandjelovic ◽  
Colleen R Stephens ◽  
Maureen S McCarthy ◽  
Paula Dieguez ◽  
Ammie K Kalan ◽  
...  
Keyword(s):  
Citizen Science ◽  
General Public ◽  
Large Scale ◽  
Video Camera ◽  
Camera Trap ◽  
Scientific Data ◽  
Individual Identification ◽  
Community Size ◽  
Data Set ◽  
Effective Manner

The Pan African Programme: The cultured chimpanzee (PanAf) is a large-scale research project across the chimpanzee (Pan troglodytes) range which aims to better understand and model the socioecological and demographic drivers of chimpanzee diversity. As part of the PanAf, over 350,000 1-minute camera trap videos have been recorded. To annotate this large data set and ascertain individual chimpanzee identifications from 39 different temporary and collaborative chimpanzee research sites, we developed the web-based citizen science platform Chimp&See (www.chimpandsee.org) in collaboration with the Zooniverse. Chimp&See allows members of the general public to view the PanAf videos online and annotate which species are present and the behaviours they exhibit in each video. These citizen scientists also watch and discuss videos to determine unique chimpanzee individuals and match them from different video clips. Each video is viewed by up to 15 unique users, allowing us to obtain a confidence score based on the number of consensus matches for each identification. In this poster, we compare the accuracy and efficiency achieved by the general public on this platform to automated facial detection software and expert scientific annotators. We also evaluate whether citizen science and video camera trapping is a way forward for assessing chimpanzee age/sex structure, density and community size in a cost and time effective manner. Finally, we discuss the balance between maintaining user engagement and obtaining detailed and accurate scientific data from citizen scientists.

scholarly journals Accessing camera trap survey feasibility for estimating Blastocerus dichotomus (Cetartiodactyla, Cervidae) demographic parameters

2017 ◽  
Vol 107 (0) ◽  
Author(s):  
Pedro Henrique F. Peres ◽  
Maxihilian S. Polverini ◽  
Márcio L. Oliveira ◽  
José Maurício B. Duarte
Keyword(s):  
Distance Sampling ◽  
Cost Benefit ◽  
Camera Trap ◽  
Camera Traps ◽  
Biological Information ◽  
Individual Identification ◽  
Conservation Strategies ◽  
Observation Data ◽  
Demographic Information ◽  
Blastocerus Dichotomus

ABSTRACT Demographic information is the basis for evaluating and planning conservation strategies for an endangered species. However, in numerous situations there are methodological or financial limitations to obtain such information for some species. The marsh deer, an endangered Neotropical cervid, is a challenging species to obtain biological information. To help achieve such aims, the study evaluated the applicability of camera traps to obtain demographic information on the marsh deer compared to the traditional aerial census method. Fourteen camera traps were installed for three months on the Capão da Cruz floodplain, in state of São Paulo, and ten helicopter flyovers were made along a 13-kilometer trajectory to detect resident marsh deer. In addition to counting deer, the study aimed to identify the sex, age group and individual identification of the antlered males recorded. Population estimates were performed using the capture-mark-recapture method with the camera trap data and by the distance sampling method for aerial observation data. The costs and field efforts expended for both methodologies were calculated and compared. Twenty independent photographic records and 42 sightings were obtained and generated estimates of 0.98 and 1.06 ind/km², respectively. In contrast to the aerial census, camera traps allowed us to individually identify branch-antlered males, determine the sex ratio and detect fawns in the population. The cost of camera traps was 78% lower but required 20 times more field effort. Our analysis indicates that camera traps present a superior cost-benefit ratio compared to aerial surveys, since they are more informative, cheaper and offer simpler logistics. Their application extends the possibilities of studying a greater number of populations in a long-term monitoring.

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