scholarly journals How many giraffes are there? A comparison of abundance estimators at Ongava Game Reserve, Namibia

2021 ◽  
Author(s):  
Christophe Bonenfant ◽  
Ken Stratford ◽  
Stephanie Periquet
Keyword(s):  
Population Size ◽  
Detection Probability ◽  
Wildlife Conservation ◽  
Camera Trap ◽  
Biological Data ◽  
Camera Traps ◽  
Population Abundance ◽  
Visit Frequency ◽  
Game Reserve ◽  
Capture Recapture

Camera-traps are a versatile and widely adopted tool to collect biological data in wildlife conservation and management. If estimating population abundance from camera-trap data is the primarily goal of many projects, what population estimator is suitable for such data needs to be investigated. We took advantage of a 21 days camera-trap monitoring on giraffes at Onvaga Game Reserve, Namibia to compare capture-recapture (CR), saturation curves and N-mixture estimators of population abundance. A marked variation in detection probability of giraffes was observed in time and between individuals. Giraffes were also less likely to be detected after they were seen at a waterhole with cameras (visit frequency of f = 0.25). We estimated population size to 119 giraffes with a Cv = 0.10 with the best CR estimator. All other estimators we a applied over-estimated population size by ca. -20 to >+80%, because they did not account for the main sources of heterogeneity in detection probability. We found that modelling choices was much less forgiving for N-mixture than CR estimators. Double counts were problematic for N-mixture models, challenging the use of raw counts at waterholes to monitor giraffes abundance.

scholarly journals The wildcat Felis silvestris in northern Turkey: assessment of status using camera trapping

Oryx ◽  
2011 ◽  
Vol 45 (1) ◽  
pp. 112-118 ◽  
Author(s):  
Özgün Emre Can ◽  
İrfan Kandemi̇r ◽  
İnci̇ Togan
Keyword(s):  
Population Size ◽  
Camera Traps ◽  
Sampling Effort ◽  
Felis Silvestris ◽  
Forest Patch ◽  
Western Turkey ◽  
Lack Of Information ◽  
The Status ◽  
Capture Recapture ◽  
Estimate Population Size

AbstractThe wildcat Felis silvestris is a protected species in Turkey but the lack of information on its status is an obstacle to conservation initiatives. To assess the status of the species we interviewed local forestry and wildlife personnel and conducted field surveys in selected sites in northern, eastern and western Turkey during 2000–2007. In January–May 2006 we surveyed for the wildcat using 16 passive infrared-trigged camera traps in Yaylacı k Research Forest, a 50-km2 forest patch in Yenice Forest in northern Turkey. A total sampling effort of 1,200 camera trap days over 40 km2 yielded photo-captures of eight individual wildcats over five sampling occasions. Using the software MARK to estimate population size the closed capture–recapture model M0, which assumes a constant capture probability among all occasions and individuals, best fitted the capture history data. The wildcat population size in Yaylacı k Research Forest was estimated to be 11 (confidence interval 9–23). Yenice Forest is probably one of the most important areas for the long-term conservation of the wildcat as it is the largest intact forest habitat in Turkey with little human presence, and without human settlements, and with a high diversity of prey species. However, it has been a major logging area and is not protected. The future of Yenice Forest and its wildcat population could be secured by granting this region a protection status and enforcing environmental legislation.

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.

scholarly journals A Spatially Explicit Capture–Recapture Model for Partially Identified Individuals When Trap Detection Rate Is Less than One

2019 ◽  
Vol 71 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Soumen Dey ◽  
Mohan Delampady ◽  
K. Ullas Karanth ◽  
Arjun M. Gopalaswamy
Keyword(s):  
Detection Probability ◽  
Credible Interval ◽  
Camera Traps ◽  
Spatially Explicit ◽  
Panthera Tigris ◽  
Partial Identity ◽  
Proposed Model ◽  
Estimation Problems ◽  
Capture Recapture ◽  
Future Work

Spatially explicit capture–recapture (SECR) models have gained enormous popularity to solve abundance estimation problems in ecology. In this study, we develop a novel Bayesian SECR model that disentangles two processes: one is the process of animal arrival within a detection region, and the other is the process of recording this arrival by a given set of detectors. We integrate this complexity into an advanced version of a recent SECR model involving partially identified individuals (Royle JA. Spatial capture-recapture with partial identity. arXiv preprint arXiv:1503.06873, 2015). We assess the performance of our model over a range of realistic simulation scenarios and demonstrate that estimates of population size N improve when we utilize the proposed model relative to the model that does not explicitly estimate trap detection probability (Royle JA. Spatial capture-recapture with partial identity. arXiv preprint arXiv:1503.06873, 2015). We confront and investigate the proposed model with a spatial capture–recapture dataset from a camera trapping survey of tigers (Panthera tigris) in Nagarahole study area of southern India. Detection probability is estimated at 0.489 (with 95% credible interval (CI) [0.430, 0.543]) which implies that the camera traps are performing imperfectly and thus justifying the use of our model in real world applications. We discuss possible extensions, future work and relevance of our model to other statistical applications beyond ecology. AMS classification codes: 62F15, 92D40

scholarly journals FoxMask: a new automated tool for animal detection in camera trap images

2019 ◽  
Author(s):  
Eric Devost ◽  
Sandra Lai ◽  
Nicolas Casajus ◽  
Dominique Berteaux
Keyword(s):  
Moving Objects ◽  
Data Extraction ◽  
Cost Effective ◽  
Camera Trap ◽  
Biological Data ◽  
Camera Traps ◽  
Computer Assisted ◽  
List Type ◽  
Background Estimation ◽  
Animal Detection

SUMMARYCamera traps now represent a reliable, efficient and cost-effective technique to monitor wildlife and collect biological data in the field. However, efficiently extracting information from the massive amount of images generated is often extremely time-consuming and may now represent the most rate-limiting step in camera trap studies.To help overcome this challenge, we developed FoxMask, a new tool performing the automatic detection of animal presence in short sequences of camera trap images. FoxMask uses background estimation and foreground segmentation algorithms to detect the presence of moving objects (most likely, animals) on images.We analyzed a sample dataset from camera traps used to monitor activity on arctic fox Vulpes lagopus dens to test the parameter settings and the performance of the algorithm. The shape and color of arctic foxes, their background at snowmelt and during the summer growing season were highly variable, thus offering challenging testing conditions. We compared the automated animal detection performed by FoxMask to a manual review of the image series.The performance analysis indicated that the proportion of images correctly classified by FoxMask as containing an animal or not was very high (> 90%). FoxMask is thus highly efficient at reducing the workload by eliminating most false triggers (images without an animal). We provide parameter recommendations to facilitate usage and we present the cases where the algorithm performs less efficiently to stimulate further development.FoxMask is an easy-to-use tool freely available to ecologists performing camera trap data extraction. By minimizing analytical time, computer-assisted image analysis will allow collection of increased sample sizes and testing of new biological questions.

scholarly journals Fauna diversity in the southern part of the Kon Ka Kinh National Park, Gia Lai province

2021 ◽  
Vol 43 (4) ◽  
pp. 139-151
Author(s):  
Nguyen Ai Tam ◽  
Nguyen Van Tay ◽  
Nguyen Thi Kim Yen ◽  
Ha Thang Long
Keyword(s):  
National Park ◽  
Wildlife Conservation ◽  
Animal Species ◽  
Infrared Camera ◽  
Camera Trap ◽  
Iucn Red List ◽  
Camera Traps ◽  
Survey Results ◽  
Set Up ◽  
First Time

Kon Ka Kinh National Park (KKK NP) is a priority zone for biodiversity protection in Vietnam as well as ASEAN. In order to survey the current fauna species diversity in the southern part of the KKK NP, we conducted camera trapping surveys in 2017, 2018, and 2019. 28 infrared camera traps were set up on elevations between 1041 to 1497 meters. In total, there were 360 days of survey using camera trap. As result, we recorded a total of 27 animal species of those, five species are listed in the IUCN Red List of Threatened Species (IUCN, 2020). The survey results showed a high richness of wildlife in the southern park region, and it also revealed human disturbance to wildlife in the park. The first-time camera trap was used for surveying wildlife diversity in the southern region of the KKK NP. Conducting camera trap surveys in the whole KKK NP is essential for monitoring and identifying priority areas for wildlife conservation in the national park.

scholarly journals An assessment of carnivore relative abundance and density in the eastern rainforests of Madagascar using remotely-triggered camera traps

Oryx ◽  
2010 ◽  
Vol 44 (2) ◽  
pp. 219-222 ◽  
Author(s):  
Brian Gerber ◽  
Sarah M. Karpanty ◽  
Charles Crawford ◽  
Mary Kotschwar ◽  
Johnny Randrianantenaina
Keyword(s):  
Relative Abundance ◽  
National Park ◽  
Camera Trap ◽  
Camera Traps ◽  
Domestic Dog ◽  
Likelihood Method ◽  
Ranomafana National Park ◽  
Carnivore Species ◽  
Cryptoprocta Ferox ◽  
Capture Recapture

AbstractDespite major efforts to understand and conserve Madagascar’s unique biodiversity, relatively little is known about the island’s carnivore populations. We therefore deployed 43 camera-trap stations in Ranomafana National Park, Madagascar during June–August 2007 to evaluate the efficacy of this method for studying Malagasy carnivores and to estimate the relative abundance and density of carnivores in the eastern rainforest. A total of 755 camera-trap nights provided 1,605 photographs of four endemic carnivore species (fossa Cryptoprocta ferox, Malagasy civet Fossa fossana, ring-tailed mongoose Galidia elegans and broad-striped mongoose Galidictus fasciata), the exotic Indian civet Viverricula indica and the domestic dog Canis familiaris. We identified 38 individual F. fossana and 10 individual C. ferox. We estimated density using both capture-recapture analyses, with a buffer of full mean-maximum-distance-moved, and a spatially-explicit maximum-likelihood method (F. fossana: 3.03 and 2.23 km-2, respectively; C. ferox: 0.15 and 0.17 km-2, respectively). Our estimated densities of C. ferox in rainforest are lower than published estimates for conspecifics in the western dry forests. Within Ranomafana National Park species richness of native carnivores did not vary among trail systems located in secondary, selectively-logged and undisturbed forest. These results provide the first assessment of carnivore population parameters using camera-traps in the eastern rainforests of Madagascar.

scholarly journals Horizontal or vertical? Camera trap orientations and recording modes for detecting potoroos, bandicoots and pademelons

2014 ◽  
Vol 36 (1) ◽  
pp. 60 ◽  
Author(s):  
Brendan D. Taylor ◽  
Ross L. Goldingay ◽  
John M. Lindsay
Keyword(s):  
Detection Probability ◽  
New South ◽  
Population Monitoring ◽  
Camera Trap ◽  
Probability Of Detection ◽  
Camera Traps ◽  
North East ◽  
South Wales ◽  
Detection Probabilities ◽  
The Stability

Camera traps can detect rare and cryptic species, and may enable description of the stability of populations of threatened species. We investigated the relative performance of cameras oriented horizontally or vertically, and recording mode (still and video) to detect the vulnerable long-nosed potoroo (Potorous tridactylus) as a precursor to population monitoring. We established camera traps for periods of 13–21 days across 21 sites in Richmond Range National Park in north-east New South Wales. Each camera trap set consisted of three KeepGuard KG680V cameras directed at a bait container – one horizontal and one vertical camera in still mode and one horizontal camera in video mode. Potoroos and bandicoots (Perameles nasuta and Isoodon macrourus) were detected at 14 sites and pademelons (Thylogale stigmatica and T. thetis) were detected at 19 sites. We used program Presence to compare detection probabilities for each camera category. The detection probability for all three taxa groups was lowest for the vertical still and similar for the horizontal cameras. The detection probability (horizontal still) was highest for the potoroos (0.43) compared with the bandicoots (0.16) and pademelons (0.25). We estimate that the horizontal stills camera could achieve a 95% probability of detection of a potoroo within 6 days compared with 8 days using a vertical stills camera. This suggests that horizontal cameras in still mode have great potential for monitoring the dynamics of this potoroo population.

scholarly journals The impacts of camera placement on species detectability in an Indonesian terrestrial community

2021 ◽  
Author(s):  
Eric Van Dam
Keyword(s):  
Body Size ◽  
Data Collection ◽  
Study Design ◽  
Detection Probability ◽  
Camera Trap ◽  
Camera Traps ◽  
Camera Placement ◽  
Species Detection ◽  
Animal Populations ◽  
Selective Placement

<p>Ecologists have increasingly favoured the use of camera traps in studies of animal populations and their behaviour. Because camera trap study design commonly implements non-random selective placement, we must consider how this placement strategy affects the integrity of our data collection. Selective placement of camera traps have the benefits of 1) maximizing the probability of encounter events by sampling habitats or microhabitats of known significance to a focus or closely-related species and 2) reducing data collection and maintenance effort in the field by situating cameras along more easily-accessible landscape features. Introducing a non-random survey method, such as selective placement, into a project studying a species or community that also expresses non-random habitat use may lead to unintentionally biased data and inaccurate results. By using a paired on-trail/off-trail camera-trap study design, my aim is to investigate potential differences in popular ecological indices, species detection probability (p) using multi-method occupancy models, and intraspecific temporal activity for a terrestrial community in Gunung Palung National Park in Indonesian Borneo. Differences in detection probability between on and off-trail cameras were compared against species characteristics (including body size, diet, and taxonomic group) to find potential correlations. While several species exhibited a significant difference in detection probability between cameras placed on foot trails and those placed randomly off-trail, there was no measured community trend. This stresses my conclusion further that a non-random study design leaves results open to bias from unknown patterns in detection due to underlying variation in behaviour and microhabitat use. Selective placement may be effective for increasing detection probability for some species but can also lead to substantial bias if the features selected for are not explicitly taken into account within the analysis or balanced with a control in the study design. In addition, a positive interactive effect was found between on trail species detection and body size for the terrestrial omnivore guild, and three species presented significant variation in temporal activity between camera placement types. This provides evidence that camera placement not only affects species state parameters and indices but has a noticeable impact on behavioural observations that require accountability as well.</p>

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 The impacts of camera placement on species detectability in an Indonesian terrestrial community

2021 ◽  
Author(s):  
Eric Van Dam
Keyword(s):  
Body Size ◽  
Data Collection ◽  
Study Design ◽  
Detection Probability ◽  
Camera Trap ◽  
Camera Traps ◽  
Camera Placement ◽  
Species Detection ◽  
Animal Populations ◽  
Selective Placement

<p>Ecologists have increasingly favoured the use of camera traps in studies of animal populations and their behaviour. Because camera trap study design commonly implements non-random selective placement, we must consider how this placement strategy affects the integrity of our data collection. Selective placement of camera traps have the benefits of 1) maximizing the probability of encounter events by sampling habitats or microhabitats of known significance to a focus or closely-related species and 2) reducing data collection and maintenance effort in the field by situating cameras along more easily-accessible landscape features. Introducing a non-random survey method, such as selective placement, into a project studying a species or community that also expresses non-random habitat use may lead to unintentionally biased data and inaccurate results. By using a paired on-trail/off-trail camera-trap study design, my aim is to investigate potential differences in popular ecological indices, species detection probability (p) using multi-method occupancy models, and intraspecific temporal activity for a terrestrial community in Gunung Palung National Park in Indonesian Borneo. Differences in detection probability between on and off-trail cameras were compared against species characteristics (including body size, diet, and taxonomic group) to find potential correlations. While several species exhibited a significant difference in detection probability between cameras placed on foot trails and those placed randomly off-trail, there was no measured community trend. This stresses my conclusion further that a non-random study design leaves results open to bias from unknown patterns in detection due to underlying variation in behaviour and microhabitat use. Selective placement may be effective for increasing detection probability for some species but can also lead to substantial bias if the features selected for are not explicitly taken into account within the analysis or balanced with a control in the study design. In addition, a positive interactive effect was found between on trail species detection and body size for the terrestrial omnivore guild, and three species presented significant variation in temporal activity between camera placement types. This provides evidence that camera placement not only affects species state parameters and indices but has a noticeable impact on behavioural observations that require accountability as well.</p>

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