First photographic records of bush dogs (Speothos venaticus) from camera-traps in Guyana

Mammalia ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Matthew T. Hallett ◽  
Anthony Roberts ◽  
Ashley P. Holland ◽  
Angus Jackman
Keyword(s):  
Camera Trap ◽  
Camera Traps ◽  
Individual Study ◽  
Detection Rates ◽  
Detailed Measurement ◽  
Scale Modelling ◽  
In The Wild ◽  
Bush Dog ◽  
Speothos Venaticus ◽  
Photographic Records

AbstractThe bush dog (Speothos venaticus) is rare, elusive, and difficult to study in the wild. Guyana contains a wealth of intact tropical forest (∼18.4 million ha) and savanna (1.6 million ha) habitats, but management of this species is hindered by a lack of data. We present two photographic records (consisting of nine individuals) of bush dogs from camera-traps set in the Kanuku Mountains Protected Area (KMPA) – the first of this species in Guyana. These records highlight the importance of Guiana Shield forests and Guyana’s expanding protected areas system to the conservation of these wide-ranging carnivores. Additionally, we recommend that detailed measurement and reporting of site variables become standard, as it will improve the efficacy of camera-trap studies of bush dogs and allow for broad-scale modelling of space use not otherwise possible due to the low detection rates at the scale of each individual study.

scholarly journals Long-term monitoring of margays (Leopardus wiedii): Implications for understanding low detection rates

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247536
Author(s):  
Bart J. Harmsen ◽  
Nicola Saville ◽  
Rebecca J. Foster
Keyword(s):  
Detection Rate ◽  
Camera Trap ◽  
Wide Distribution ◽  
Camera Traps ◽  
Detection Rates ◽  
Terrestrial Mammals ◽  
Exclusive Territories ◽  
Carnivore Species ◽  
Density Population

Population assessments of wide-ranging, cryptic, terrestrial mammals rely on camera trap surveys. While camera trapping is a powerful method of detecting presence, it is difficult distinguishing rarity from low detection rate. The margay (Leopardus wiedii) is an example of a species considered rare based on its low detection rates across its range. Although margays have a wide distribution, detection rates with camera traps are universally low; consequently, the species is listed as Near Threatened. Our 12-year camera trap study of margays in protected broadleaf forest in Belize suggests that while margays have low detection rate, they do not seem to be rare, rather that they are difficult to detect with camera traps. We detected a maximum of 187 individuals, all with few or no recaptures over the years (mean = 2.0 captures/individual ± SD 2.1), with two-thirds of individuals detected only once. The few individuals that were recaptured across years exhibited long tenures up to 9 years and were at least 10 years old at their final detection. We detected multiple individuals of both sexes at the same locations during the same survey, suggesting overlapping ranges with non-exclusive territories, providing further evidence of a high-density population. By studying the sparse annual datasets across multiple years, we found evidence of an abundant margay population in the forest of the Cockscomb Basin, which might have been deemed low density and rare, if studied in the short term. We encourage more long-term camera trap studies to assess population status of semi-arboreal carnivore species that have hitherto been considered rare based on low detection rates.

Effects of different attractants and human scent on mesocarnivore detection at camera traps

2020 ◽  
Vol 47 (4) ◽  
pp. 338
Author(s):  
Bracy W. Heinlein ◽  
Rachael E. Urbanek ◽  
Colleen Olfenbuttel ◽  
Casey G. Dukes
Keyword(s):  
Fatty Acid ◽  
Castor Oil ◽  
Camera Trap ◽  
Camera Traps ◽  
Individual Species ◽  
Detection Rates ◽  
Capture Success ◽  
Affect Detection ◽  
Species Specific

Abstract ContextCamera traps paired with baits and scented lures can be used to monitor mesocarnivore populations, but not all attractants are equally effective. Several studies have investigated the efficacy of different attractants on the success of luring mesocarnivores to camera traps; fewer studies have examined the effect of human scent at camera traps. AimsWe sought to determine the effects of human scent, four attractants and the interaction between attractants and human scent in luring mesocarnivores to camera traps. Methods We compared the success of synthetic fermented egg (SFE), fatty acid scent (FAS) tablets, castor oil, and sardines against a control of no attractant in luring mesocarnivores to camera traps. We deployed each attractant and the control with either no regard to masking human scent or attempting to restrict human scent for a total of 10 treatments, and replicated treatments eight to nine times in two different phases. We investigated whether: (1) any attractants increased the probability of capturing a mesocarnivore at a camera trap; (2) not masking human scent affected the probability of capturing a mesocarnivore at a camera trap; and (3) any attractants increased the probability of repeat detections at a given camera trap. We also analysed the behaviour (i.e. speed and distance to attractant) of each mesocarnivore in relation to the attractants. Key resultsSardines improved capture success compared with the control treatments, whereas SFE, castor oil, and FAS tablets had no effect when all mesocarnivores were included in the analyses. Masking human scent did not affect detection rates in the multispecies analyses. Individually, the detection of some species depended on the interactions between masking (or not masking) human scent and some attractants. ConclusionsSardines were the most effective as a broad-based attractant for mesocarnivores. Mesocarnivores approached traps baited with sardines at slower rates, which allows for a higher success of capturing an image of the animal. ImplicationsHuman scent may not need to be masked when deploying camera traps for multispecies mesocarnivore studies, but researchers should be aware that individual species respond differently to attractants and may have higher capture success with species-specific attractants.

The effect of camera-trap viewshed obstruction on wildlife detection: implications for inference

2020 ◽  
Vol 47 (2) ◽  
pp. 158 ◽  
Author(s):  
Remington J. Moll ◽  
Waldemar Ortiz-Calo ◽  
Jonathon D. Cepek ◽  
Patrick D. Lorch ◽  
Patricia M. Dennis ◽  
...  
Keyword(s):  
Image Data ◽  
Camera Trap ◽  
Camera Traps ◽  
Mammal Species ◽  
Ecological Processes ◽  
Detection Rates ◽  
Management Application ◽  
Efficiency And Effectiveness ◽  
Steep Slopes ◽  
Wildlife Detection

Abstract ContextCamera traps are one of the most popular tools used to study wildlife worldwide. Numerous recent studies have evaluated the efficiency and effectiveness of camera traps as a research tool. Nonetheless, important aspects of camera-trap methodology remain in need of critical investigation. One such issue relates to camera-trap viewshed visibility, which is often compromised in the field by physical obstructions (e.g. trees) or topography (e.g. steep slopes). The loss of visibility due to these obstructions could affect wildlife detection rates, with associated implications for study inference and management application. AimsWe aimed to determine the effect of camera-trap viewshed obstruction on wildlife detection rates for a suite of eight North American species that vary in terms of ecology, commonness and body size. MethodsWe deployed camera traps at 204 sites throughout an extensive semi-urban park system in Cleveland, Ohio, USA, from June to September 2016. At each site, we quantified camera-trap viewshed obstruction by using a cover-board design. We then modelled the effects of obstruction on wildlife detection rates for the eight focal species. Key resultsWe found that detection rates significantly decreased with an increasing viewshed obstruction for five of the eight species, including both larger and smaller mammal species (white-tailed deer, Odocoileus virginianus, and squirrels, Sciurus sp., respectively). The number of detections per week per camera decreased two- to three-fold as visibility at a camera site decreased from completely free of obstruction to mostly obstructed. ConclusionsThese results imply that wildlife detection rates are influenced by site-level viewshed obstruction for a variety of species, and sometimes considerably so. ImplicationsResearchers using camera traps should address the potential for this effect to ensure robust inference from wildlife image data. Accounting for viewshed obstruction is critical when interpreting detection rates as indices of abundance or habitat use because variation in detection rate could be an artefact of site-level viewshed obstruction rather than due to underlying ecological processes.

scholarly journals New camera-trap records for bush dog (Speothos venaticus) in Colombia

2017 ◽  
Vol 29 ◽  
pp. 19-22 ◽  
Author(s):  
Paola Rodríguez-Castellanos ◽  
Germán Garrote ◽  
Fernando Trujillo
Keyword(s):  
Camera Trap ◽  
Bush Dog ◽  
Speothos Venaticus

scholarly journals Diet and habitat associations of bush dogs Speothos venaticus in the Interior Atlantic Forest of eastern Paraguay

Oryx ◽  
2005 ◽  
Vol 39 (1) ◽  
pp. 86-89 ◽  
Author(s):  
Gerald L. Zuercher ◽  
Philip S. Gipson ◽  
Osvaldo Carrillo
Keyword(s):  
Atlantic Forest ◽  
Small Mammals ◽  
Iucn Red List ◽  
Red List ◽  
Habitat Associations ◽  
Fruit Consumption ◽  
In The Wild ◽  
Bush Dog ◽  
Grassland Habitats ◽  
Speothos Venaticus

The diet and habitat associations of bush dogs Speothos venaticus, categorized as Vulnerable on the IUCN Red List, are virtually unknown in the wild. In eastern Paraguay, bush dogs occur in the Reserva Natural del Bosque Mbaracayú. The Reserve contains one of the largest remaining fragments of the Interior Atlantic Forest in Paraguay as well as cerrado and grassland habitats. We analysed bush dog faeces to determine their diet. Bush dogs in the Reserve mostly ate vertebrates. Although small mammals (marsupials and rodents) were the most numerically dominant foods, agoutis Dasyprocta azarae and pacas Cuniculus paca represented 90.5% of biomass consumed. Cecropia fruit was also present in the diet. This is the first documentation of fruit consumption by bush dogs. Signs of bush dogs were detected in all habitats, with the greatest proportion in high forest.

scholarly journals How rare is rare? Quantifying and assessing the rarity of the bush dog Speothos venaticus across the Amazon and other biomes

Oryx ◽  
2016 ◽  
Vol 52 (1) ◽  
pp. 98-107 ◽  
Author(s):  
Tadeu G. de Oliveira ◽  
Fernanda Michalski ◽  
André L. M. Botelho ◽  
Lincoln J. Michalski ◽  
Armando M. Calouro ◽  
...  
Keyword(s):  
Central America ◽  
Relative Abundance ◽  
Habitat Structure ◽  
Field Data ◽  
Brazilian Amazon ◽  
Camera Trap ◽  
Population Parameters ◽  
The Mean ◽  
Bush Dog ◽  
Speothos Venaticus

AbstractThe bush dog Speothos venaticus is a medium-sized Neotropical canid. It is considered to be rare and its biology and population parameters are still poorly understood. The Amazon is one of the main strongholds of this species and is important for maintaining viable populations, as the region still holds extensive tracts of pristine habitat. We gathered field data from camera-trap studies throughout the Brazilian Amazon to estimate the relative abundance of the species and gain an understanding of its rarity, and how this compares with estimates from other vegetative formations and for sympatric hypercarnivores. We focused on three pristine or partially disturbed sites and one fragmented site. The estimated relative abundance of the species was 0.060–0.185 individuals per 100 trap-days, confirming that the species is rare. The bush dog's abundance in the Amazon is equivalent to that in all other areas outside the Basin. The mean group size recorded was c. 2.5 individuals. There were no differences in group sizes between forests in the Amazon and in other regions of Central America; however, there were significant differences between forests and open habitats. A combination of competition/predation, habitat structure/integrity, and disease may be acting synergistically in determining the abundance and rarity of bush dogs.

scholarly journals Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning

2018 ◽  
Vol 115 (25) ◽  
pp. E5716-E5725 ◽  
Author(s):  
Mohammad Sadegh Norouzzadeh ◽  
Anh Nguyen ◽  
Margaret Kosmala ◽  
Alexandra Swanson ◽  
Meredith S. Palmer ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Data Extraction ◽  
High Volume ◽  
Camera Trap ◽  
Camera Traps ◽  
Deep Convolutional Neural Networks ◽  
Manual Task ◽  
In The Wild

Having accurate, detailed, and up-to-date information about the location and behavior of animals in the wild would improve our ability to study and conserve ecosystems. We investigate the ability to automatically, accurately, and inexpensively collect such data, which could help catalyze the transformation of many fields of ecology, wildlife biology, zoology, conservation biology, and animal behavior into “big data” sciences. Motion-sensor “camera traps” enable collecting wildlife pictures inexpensively, unobtrusively, and frequently. However, extracting information from these pictures remains an expensive, time-consuming, manual task. We demonstrate that such information can be automatically extracted by deep learning, a cutting-edge type of artificial intelligence. We train deep convolutional neural networks to identify, count, and describe the behaviors of 48 species in the 3.2 million-image Snapshot Serengeti dataset. Our deep neural networks automatically identify animals with >93.8% accuracy, and we expect that number to improve rapidly in years to come. More importantly, if our system classifies only images it is confident about, our system can automate animal identification for 99.3% of the data while still performing at the same 96.6% accuracy as that of crowdsourced teams of human volunteers, saving >8.4 y (i.e., >17,000 h at 40 h/wk) of human labeling effort on this 3.2 million-image dataset. Those efficiency gains highlight the importance of using deep neural networks to automate data extraction from camera-trap images, reducing a roadblock for this widely used technology. Our results suggest that deep learning could enable the inexpensive, unobtrusive, high-volume, and even real-time collection of a wealth of information about vast numbers of animals in the wild.

Quantifying imperfect camera-trap detection probabilities: implications for density modelling

2020 ◽  
Vol 47 (2) ◽  
pp. 177 ◽  
Author(s):  
T. McIntyre ◽  
T. L. Majelantle ◽  
D. J. Slip ◽  
R. G. Harcourt
Keyword(s):  
Population Density ◽  
Surface Temperature ◽  
Ambient Temperature ◽  
Population Level ◽  
Camera Trap ◽  
Camera Traps ◽  
Imperfect Detection ◽  
Detection Rates ◽  
Detection Probabilities ◽  
Density Modelling

Abstract ContextData obtained from camera traps are increasingly used to inform various population-level models. Although acknowledged, imperfect detection probabilities within camera-trap detection zones are rarely taken into account when modelling animal densities. AimsWe aimed to identify parameters influencing camera-trap detection probabilities, and quantify their relative impacts, as well as explore the downstream implications of imperfect detection probabilities on population-density modelling. MethodsWe modelled the relationships between the detection probabilities of a standard camera-trap model (n=35) on a remotely operated animal-shaped soft toy and a series of parameters likely to influence it. These included the distance of animals from camera traps, animal speed, camera-trap deployment height, ambient temperature (as a proxy for background surface temperatures) and animal surface temperature. We then used this detection-probability model to quantify the likely influence of imperfect detection rates on subsequent population-level models, being, in this case, estimates from random encounter density models on a known density simulation. Key resultsDetection probabilities mostly varied predictably in relation to measured parameters, and decreased with an increasing distance from the camera traps and speeds of movement, as well as heights of camera-trap deployments. Increased differences between ambient temperature and animal surface temperature were associated with increased detection probabilities. Importantly, our results showed substantial inter-camera (of the same model) variability in detection probabilities. Resulting model outputs suggested consistent and systematic underestimation of true population densities when not taking imperfect detection probabilities into account. ConclusionsImperfect, and individually variable, detection probabilities inside the detection zones of camera traps can compromise resulting population-density estimates. ImplicationsWe propose a simple calibration approach for individual camera traps before field deployment and encourage researchers to actively estimate individual camera-trap detection performance for inclusion in subsequent modelling approaches.

Searching for rare and secretive snakes: are camera-trap and box-trap methods interchangeable?

2020 ◽  
Vol 47 (6) ◽  
pp. 476 ◽  
Author(s):  
Dalton B. Neuharth ◽  
Wade A. Ryberg ◽  
Connor S. Adams ◽  
Toby J. Hibbitts ◽  
Danielle K. Walkup ◽  
...  
Keyword(s):  
Life Histories ◽  
Detection Rate ◽  
Temporal Trends ◽  
Habitat Type ◽  
Camera Trap ◽  
Camera Traps ◽  
Similar Data ◽  
Detection Rates ◽  
Snake Species ◽  
Snake Detection

Abstract ContextAdvancements in camera-trap technology have provided wildlife researchers with a new technique to better understand their study species. This improved method may be especially useful for many conservation-reliant snake species that can be difficult to detect because of rarity and life histories with secretive behaviours. AimsHere, we report the results of a 6-month camera-trapping study using time lapse-triggered camera traps to detect snakes, in particular the federally listed Louisiana pinesnake (Pituophis ruthveni) in eastern Texas upland forests in the USA. MethodsSo as to evaluate the efficacy of this method of snake detection, we compared camera-trap data with traditional box-trapping data collected over the same time period across a similar habitat type, and with the same goal of detecting P. ruthveni. Key resultsNo differences in focal snake species richness were detected across the trap methods, although the snake-detection rate was nearly three times higher with camera traps than with the box traps. Detection rates of individual snake species varied with the trapping method for all but two species, but temporal trends in detection rates were similar across the trap methods for all but two species. Neither trap method detected P. ruthveni in the present study, but the species has been detected with both trap methods at other sites. ConclusionsThe higher snake-detection rate of the camera-trap method suggests that pairing this method with traditional box traps could increase the detection of P. ruthveni where it occurs. For future monitoring and research on P. ruthveni, and other similarly rare and secretive species of conservation concern, we believe these methods could be used interchangeably by saturating potentially occupied habitats with camera traps initially and then replacing cameras with box traps when the target species is detected. ImplicationsThere are financial and logistical limits to monitoring and researching rare and secretive species with box traps, and those limits are far less restrictive with camera traps. The ability to use camera-trap technologies interchangeably with box-trap methods to collect similar data more efficiently and effectively will have a significant impact on snake conservation.

scholarly journals Sunda clouded leopard Neofelis diardi densities and human activities in the humid evergreen rainforests of Sumatra

Oryx ◽  
2020 ◽  
pp. 1-8
Author(s):  
Iding Haidir ◽  
David W. Macdonald ◽  
Matthew Linkie
Keyword(s):  
Conservation Planning ◽  
Forest Edge ◽  
Camera Trap ◽  
Camera Traps ◽  
Spatially Explicit ◽  
Clouded Leopard ◽  
Wild Felids ◽  
The Status ◽  
In The Wild ◽  
Capture Recapture

Abstract Most species of wild felids are threatened, but for many little is known about their status in the wild. For the cryptic and elusive Vulnerable Sunda clouded leopard Neofelis diardi, key metrics such as abundance and occupancy have been challenging to obtain. We conducted an intensive survey for this species on the Indonesian island of Sumatra. We deployed camera traps across four study areas that varied in elevation and threats, for a total of 28,404 trap nights, resulting in 114 independent clouded leopard photographs, in which we identified 18 individuals. Using a Bayesian spatially explicit capture–recapture analysis, we estimated clouded leopard density to be 0.8–2.4 individuals/100 km2. The highest predicted occurrence of people was at lower altitudes and closer to the forest edge, where we categorized more than two-thirds of people recorded by camera traps as bird poachers, 12.5% each as ungulate/tiger poachers and non-timber collectors, and < 2% as fishers. Our findings provide important insights into the status of this little known species in Sumatra. We recommend that the large volume of camera-trap data from other Sumatran landscapes be used for an island-wide assessment of the clouded leopard population, to provide up-to-date and reliable information for guiding future conservation planning.

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