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Durbach, I., Borchers, D., Sutherland, C., Sharma, K. (2020). Fast, flexible alternatives to regular grid designs for spatial
capture–recapture..
Abstract: Spatial capture–recapture (SCR) methods use the location of
detectors (camera traps, hair snares and live-capture traps) and the locations at which animals were detected (their spatial capture histories) to estimate animal density. Despite the often large expense and effort involved in placing detectors in a landscape, there has been relatively little work on how detectors should be located. A natural criterion is to place traps so as to maximize the precision of density estimators, but the lack of a closed-form expression for precision has made optimizing this criterion computationally demanding. 2. Recent results by Efford and Boulanger (2019) show that precision can be well approximated by a function of the expected number of detected individuals and expected number of recapture events, both of which can be evaluated at low computational cost. We use these results to develop a method for obtaining survey designs that optimize this approximate precision for SCR studies using count or binary proximity detectors, or multi-catch traps. 3. We show how the basic design protocol can be extended to incorporate spatially varying distributions of activity centres and animal detectability. We illustrate our approach by simulating from a camera trap study of snow leopards in Mongolia and comparing estimates from our designs to those generated by regular or optimized grid designs. Optimizing detector placement increased the number of detected individuals and recaptures, but this did not always lead to more precise density estimators due to less precise estimation of the effective sampling area. In most cases, the precision of density estimators was comparable to that obtained with grid designs, with improvement in some scenarios where approximate CV(¬D) < 20% and density varied spatially. 4. Designs generated using our approach are transparent and statistically grounded. They can be produced for survey regions of any shape, adapt to known information about animal density and detectability, and are potentially easier and less costly to implement. We recommend their use as good, flexible candidate designs for SCR surveys when reasonable knowledge of model parameters exists. We provide software for researchers to construct their own designs, in the form of updates to design functions in the r package oSCR. |
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Koju. N. P,, Bashyal, B., Pandey, B. P., Shah, S. N., Thami, S., Bleisch, W. V. (2020). First camera-trap record of the snow leopard Panthera uncia in Gaurishankar Conservation Area, Nepal. Oryx, , 1–4.
Abstract: The snow leopard Panthera uncia is the flagship species of the high mountains of the Himalayas. There is po- tentially continuous habitat for the snow leopard along the northern border of Nepal, but there is a gap in information about the snow leopard in Gaurishankar Conservation Area. Previous spatial analysis has suggested that the Lamabagar area in this Conservation Area could serve as a transbound- ary corridor for snow leopards, and that the area may con- nect local populations, creating a metapopulation. However, there has been no visual confirmation of the species in Lamabagar. We set !! infrared camera traps for " months in Lapchi Village of Gaurishankar Conservation Area, where blue sheep Pseudois nayaur, musk deer Moschus leucogaster and Himalayan tahr Hemitragus jemlahicus, all snow leopard prey species, had been observed. In November #$!% at &,!$$ m, ' km south-west of Lapchi Village, one camera recorded three images of a snow leopard, the first photographic evidence of the species in the Conservation Area. Sixteen other species of mammals were also recorded. Camera-trap records and sightings indicated a high abun- dance of Himalayan tahr, blue sheep and musk deer. Lapchi Village may be a potentially important corridor for snow leopard movement between the east and west of Nepal and northwards to Quomolongma National Park in China. However, plans for development in the region present in- creasing threats to this corridor. We recommend develop- ment of a transboundary conservation strategy for snow leopard conservation in this region, with participation of Nepal, China and international agencies.
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Sharma, K., Fiechter, M., George, T., Young, J., Alexander, J.
S., Bijoor, Suryawanshi, K., Mishra, C. (2020). Conservation and people: Towards an ethical code of conduct for
the use of camera traps in wildlife research. Ecological Solutions and Evidence, , 1–6.
Abstract: 1. Camera trapping is a widely employed tool in wildlife
research, used to estimate animal abundances, understand animal movement, assess species richness and under- stand animal behaviour. In addition to images of wild animals, research cameras often record human images, inadvertently capturing behaviours ranging from innocuous actions to potentially serious crimes. 2. With the increasing use of camera traps, there is an urgent need to reflect on how researchers should deal with human images caught on cameras. On the one hand, it is important to respect the privacy of individuals caught on cameras, while, on the other hand, there is a larger public duty to report illegal activity. This creates ethical dilemmas for researchers. 3. Here, based on our camera-trap research on snow leopards Panthera uncia, we outline a general code of conduct to help improve the practice of camera trap based research and help researchers better navigate the ethical-legal tightrope of this important research tool. |
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Zhang, L., Lian, X., Yang, X. (2020). Population density of snow leopards (Panthera Uncia) in the Yage Valley Region of the Sanjiangyuan National Park: Conservation Implications and future directions. Artic, Antartic and Alpine Research, 52(1), 541–550.
Abstract: Population-based studies on snow leopard (Panthera uncia) are of theoretical and practical sig- nificance for the conservation of alpine ecosystems, though geographic remoteness and isolation hinder surveys in many promising regions. The Sanjiangyuan National Park on the Tibetan Plateau is acknowledged as a main snow leopard habitat, but most of the region remains unexplored and unknown. We adopted a combined approach of route survey and camera trapping survey to explore the population density of snow leopard in the Yage Valley region of the Sanjiangyuan National Park. Results indicated that (1) large populations of blue sheep contributed to the major food supply for snow leopards, along with diverse prey species as dietary supplementations, and (2) a population density of four to six snow leopards per 100 km2 on the north bank was estimated, and nine to fourteen individuals within the valley core areas were identified. We also argue that under the potential impacts of hydropower dams, this valley ecosystem should be symbolized as a conservation hotspot and therefore merits prioritized conservation. We recommend further surveys combined with novel methods/techniques and advocate a sustainable ecotourism model for the first V-shaped valley along the Yangtze mainstream.
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