Abstract: This study was undertaken in the Phu valley of Manang district in the Annapurna Conservation Area, Nepal,
Spring, 2004 and 2005. I used the Snow Leopard Management Information System (“second order” survey technique), to determine
the relative abundance of snow leopards in delineated areas in Phu valley. Transects routes were plotted by
randomly selected feasible landforms such as along ridgelines, cliff bases and river bluffs where snow
leopards sign is likely to be found. Altogether, 16 transects (total length of 7.912 km) were laid down (mean
transect length=0.495 km). They revealed, 54 sign sites (both relic and non-relic) and altogether 88 signs (72
scrapes, 11 feces, 3 scent mark, 2 pugmarks and 1 hair) were recorded (6.8 site/km and 11.1 signs/km). There
were 61.1% non-relic and 38.9% relic sites. The density of snow leopards in Phu Valley may be 4-5 snow
leopards/100 kmý.It was found that the Ghyo block had the highest sign density (13.6 mean sign item/km)
and Phu block (9.8 mean sign item/km) and the lowest in Ngoru block (3.9 mean sign item/km.). For blue sheep, direct count method was applied from different appropriate vantage points (fixed-point
count). I counted total individuals in each herd and classified all individuals whenever possible, using 8 X24
binocular and 15-60x spotting scope. A total 37 blue sheep herds and 1209 individuals were observed in
192.25 kmý of the study area (blue sheep density, 6.3 kmý). Average herd size was 32.68. Herd size varied
from 1 to 103 animals (the largest so far recorded). The average sex ratio male to female for the entire survey
area was 0.67. Recruitment rate was 47.13. The ratio of yearlings to adult female was 0.45. In Ghyo block
had total 168 blue sheep (area, 44.08 km2 or 3.8/ km2 i.e. 137.2 kg/ kmý). Blue sheep density in Ngoru block
showed 4.7/km2 (area, 65.47 km2). Highest density of blue sheep among three blocks was recorded in Phu
block, 8.9/km2 (or 320 kg/km2) in its 82.70 km2 area. A standard questionnaire was designed, and interviews conducted for relevant information was collected on
livestock depredation patterns (total household survey). Out of 33 households surveyed, 30 reported that they
had livestock depredation by the snow leopard in 2004. Altogether 58 animals were reportedly lost to snow
leopards (3.1% of the total mortality). Out of the estimated standing available biomass (1, 83,483kg) in the
Phu valley at least 2220 kg or 1.3% of the total livestock biomass was consumed by snow leopards in the
year of our study (2004). It was estimated that in the Phu valley annually 1.8 animals were lost per household
to snow leopards. This means approx. Rs.413560 (US$ 5,908) is lost annually in the valley (US$
179/household/annum). Ghyo block, had the highest animals loss (53.4%), followed by Phu block (36.2%)
and Ngoru block (10.3%) to snow leopards. There is positive correlation among the densities of blue sheep, relative abundance of the snow leopard and
livestock depredation. Blue sheep is the main prey species of the snow leopard in Phu valley and its
conservation therefore matters to reduce livestock depredation. A general patterns appears here that shows
that blue sheep (prey) abundance determine snow leopard (predator) abundance and that livestock
depredation by snow leopards may be minimal where there is good population of blue sheep, and vice versa.

Abstract: This study was carried out in the Kangchenjunga Conservation Area (KCA), Eastern Nepal from Feb – Nov 2007. We used the Snow Leopard Information Management System, SLIMS (second order survey technique) to determine the relative abundance of snow leopard in the upper part of KCA. Altogether, 36 transects (total length of 15.21 km) were laid down in the major three blocks of KCA. 104 Signs (77 scrapes, 20 feces, 2 Scent mark, 3 Pugmarks and 2 hairs) were recorded. Fixed-point count method was applied for blue sheep from appropriate vantage points. We counted total individual in each herd using 8x42 binocular and 15-60x spotting scope. A total of 43 herds and 1102 individuals were observed in the area. The standard SLIMS questionnaire was conducted to find out relevant information on livestock depredation patterns. Out of 35 households surveyed in KCA, 48% of herders lost livestock due to snow leopards. A total of 21 animals were reportedly lost due to snow leopards from August to September 2007.

Abstract: Predators have significant ecological impacts on the region's prey-predator dynamic and community structure through their numbers and prey selection. During April-December 2007, I conducted a research in Sagarmatha (Mt. Everest) National Park (SNP) to: i) explore population status and density of wild prey species; Himalayan tahr, musk deer and game birds, ii) investigate diet of the snow leopard and to estimate prey selection by snow leopard, iii) identify the pattern of livestock depredation by snow leopard, its mitigation, and raise awareness through outreach program, and identify the challenge and opportunities on conservation snow leopard and its co-existence with wild ungulates and the human using the areas of the SNP. Methodology of my research included vantage points and regular monitoring from trails for Himalayan tahr, fixed line transect with belt drive method for musk deer and game birds, and microscopic hair identification in snow leopard's scat to investigate diet of snow leopard and to estimate prey selection. Based on available evidence and witness accounts of snow leopard attack on livestock, the patterns of livestock depredation were assessed. I obtained 201 sighting of Himalayan tahr (1760 individuals) and estimated 293 populations in post-parturient period (April-June), 394 in birth period (July -October) and 195 November- December) in rutting period. In average, ratio of male to females was ranged from 0.34 to 0.79 and ratio of kid to female was 0.21-0.35, and yearling to kid was 0.21- 0.47. The encounter rate for musk deer was 1.06 and density was 17.28/km2. For Himalayan monal, the encounter rate was 2.14 and density was 35.66/km2. I obtained 12 sighting of snow cock comprising 69 individual in Gokyo. The ratio of male to female was 1.18 and young to female was 2.18. Twelve species (8 species of wild and 4 species of domestic livestock) were identified in the 120 snow leopard scats examined. In average, snow leopard predated most frequently on Himalayan tahr and it was detected in 26.5% relative frequency of occurrence while occurred in 36.66% of all scats, then it was followed by musk deer (19.87%), yak (12.65%), cow (12.04%), dog (10.24%), unidentified mammal (3.61%), woolly hare (3.01%), rat sp. (2.4%), unidentified bird sp. (1.8%), pika (1.2%), and shrew (0.6%) (Table 5.8 ). Wild species were present in 58.99% of scats whereas domestic livestock with dog were present in 40.95% of scats. Snow leopard predated most frequently on wildlife species in three seasons; spring (61.62%), autumn (61.11%) and winter (65.51%), and most frequently on domestic species including dog in summer season (54.54%). In term of relative biomass consumed, in average, Himalayan tahr was the most important prey species contributed 26.27% of the biomass consumed. This was followed by yak (22.13%), cow (21.06%), musk deer (11.32%), horse (10.53%), wooly hare (1.09%), rat (0.29%), pika (0.14%) and shrew (0.07%). In average, domestic livestock including dog were contributed more biomass in the diet of snow leopard comprising 60.8% of the biomass consumed whilst the wild life species comprising 39.19%. The annual prey consumption by a snow leopard (based on 2 kg/day) was estimated to be three Himalayan tahr, seven musk deer, five wooly hare, four rat sp., two pika, one shrew and four livestock. In the present study, the highest frequency of attack was found during April to June and lowest to July to November. The day of rainy and cloudy was the more vulnerable to livestock depredation. Snow leopard attacks occurred were the highest at near escape cover such as shrub land and cliff. Both predation pressure on tahr and that on livestock suggest that the development of effective conservation strategies for two threatened species (predator and prey) depends on resolving conflicts between people and predators. Recently, direct control of free – ranging livestock, good husbandry and compensation to shepherds may reduce snow leopard – human conflict. In long term solution, the reintroduction of blue sheep at the higher altitudes could also “buffer” predation on livestock.

Abstract: The main purpose of this work was to study the use of infrared trapping cameras to estimate Snow Leopard population size in a specific study area. This is the first time a study of this nature has taken place in China. During 71 days of field work, a total of 36 cameras were set up in Muzat Valley adjacent to the Tomur Nature Reserve in Xinjiang Province. We expended approximately 2094 trap days total. At least 32 pictures of Snow Leopards, 22 pictures of other wild species and 72 pictures of livestock were taken in the Muzat Valley. Meanwhile, 20 transects were run and 31 feces sample were collected. We also observed the behavior of ibex for 77.3 hours and found a total of approximately 264 ibexes in the research area.

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.