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.

Abstract: The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List. It is the least well-known of the large felids because of its shy and elusive nature and the inaccessible terrain it inhabits across the mountains of Central and South Asia. We report the first photographic record of the snow leopard in Kishtwar High Altitude National Park, India. During our camera-trapping surveys, conducted using a grid-based design, we obtained eight photographs of snow leopards, the first at 3,280 m altitude on 19 September 2022 and subsequent photographs over 3,004-3,878 m altitude. We identified at least four different individuals, establishing the species’ occurrence in Kiyar, Nanth and Renai catchments, with a capture rate of 0.123 ± SE 0.072 captures/100 trap-nights. ghts. We also recorded the presence of snow leopard prey species, including the Siberian ibex Capra sibirica, Himalayan musk deer Moschus leucogaster, long-tailed marmot Marmota caudata and pika Ochotona sp., identifying the area as potential snow leopard habitat. Given the location of Kishtwar High Altitude National Park, this record is significant for the overall snow leopard conservation landscape in India. We recommend a comprehensive study across the Kishtwar landscape to assess the occupancy, abundance, demography and movement patterns of the snow leopard and its prey. In addition, interactions between the snow leopard and pastoral communities should be assessed to understand the challenges facing the conservation and management of this important high-altitude region.

Abstract: Abstract There is a need for simple and robust techniques for assessment and monitoring of populations of the Endangered snow leopard Panthera uncia to inform the de- velopment of action plans for snow leopard conservation. We explored the use of occupancy modelling to evaluate the influence of environmental and anthropogenic features on snow leopard site-use patterns. We conducted a camera trap survey across &#63284;&#63288;&#63280; km&#63282; in Gansu Province, China, and used data from &#63286;&#63280; camera traps to estimate probabilities of site use and detection using the single season occupancy model. We assessed the influence of three covariates on site use by snow leopards: elevation, the presence of blue sheep Pseudois nayaur and the presence of human disturb- ance (distance to roads). We recorded &#63287;&#63286; captures of snow leopards over &#63282;,&#63289;&#63280;&#63286; trap-days, representing a mean capture success of &#63282;.&#63286;&#63282; captures per &#63281;&#63280;&#63280; trap-days. Elevation had the strongest influence on site use, with the probability of site use increasing with altitude, whereas the influence of presence of prey and distance to roads was relatively weak. Our findings indicate the need for practical and robust tech- niques to appraise determinants of site use by snow leo- pards, especially in the context of the limited resources available for such work.

Abstract: Understanding the impact of livestock on native
wildlife is of increasing conservation relevance. For the
Vulnerable snow leopard Panthera uncia, wild prey reduction,
intensifying human&#65533;wildlife conflicts and retaliatory
killings are severe threats potentially exacerbated by the
presence of livestock. Elucidating patterns of co-occurrence
of snow leopards, wild ungulate prey, and livestock, can be
used to assess the compatibility of pastoralism with conservation.
We used camera trapping to study the interactions of
livestock, Siberian ibex Capra sibirica and snow leopards in
a national park in the Altai mountains, Mongolia. We obtained
&#63284;&#63289;&#63284; detections of wild mammals and &#63289;&#63281;&#63282; of domestic
ungulates, dogs and humans. Snow leopards and Siberian
ibex were recorded &#63281;&#63284; and &#63283;&#63283; times, respectively. Co-occurrence
modelling showed that livestock had a higher estimated
occupancy (&#63280;.&#63286;&#63285;) than ibex, whose occupancy was
lower in the presence of livestock (&#63280;.&#63281;&#63281;) than in its absence
(&#63280;.&#63283;&#63284;&#65533;&#63280;.&#63283;&#63285; depending on scenarios modelled). Snow leopard
occupancy did not appear to be affected by the presence of
livestock or ibex but the robustness of such inference was
limited by uncertainty around the estimates. Although our
sampling at presumed snow leopard passing sites may have
led to fewer ibex detections, results indicate that livestock
may displace wild ungulates, but may not directly affect
the occurrence of snow leopards. Snow leopards could still
be threatened by livestock, as overstocking can trigger
human&#65533;carnivore conflicts and hamper the conservation
of large carnivores. Further research is needed to assess
the generality and strength of our results.