Abstract: Monitoring Techniques Forest leopards have never been systematically surveyed in African forests, in spite of their potentially vital ecological role as the sole large mammalian predators in these systems. Because leopards are rarely seen in this habitat, and are difficult to survey using the most common techniques for assessing relative abundances of forest mammals, baseline knowledge of leopard ecology and responses to human disturbance in African forests remain largely unknown. This technical handbook sums up the experience gained during a two-year study of leopards by Philipp Henschel in the Lop‚ Reserve in Gabon, Central Africa, in 2001/2002, supplemented by additional experience from carnivore studies conducted by Justina Ray in southwestern Central African Republic and eastern Congo (Zaire) . The main focus of this effort has been to develop a protocol that can be used by fieldworkers across west and central Africa to estimate leopard densities in various forest types. In developing this manual, Henschel tested several indirect methods to assess leopard numbers in both logged and unlogged forests, with the main effort devoted to testing remote photography survey methods developed for tigers by Karanth (e.g., Karanth 1995, Karanth & Nichols 1998; 2000; 2002), and modifying them for the specific conditions characterizing African forest environments. This handbook summarizes the results of the field testing, and provides recommendations for techniques to assess leopard presence/absence, relative abundance, and densities in African forest sites. We briefly review the suitability of various methods for different study objectives and go into particular detail on remote photography survey methodology, adapting previously developed methods and sampling considerations specifically to the African forest environment. Finally, we briefly discuss how camera trapping may be used as a tool to survey other forest mammals. Developing a survey protocol for African leopards is a necessary first step towards a regional assessment and priority setting exercise targeted at forest leopards, similar to those carried out on large carnivores in Asian and South American forests.

Abstract: Solitary felids like tigers and snow leopards are notoriously difficult to enumerate, and indirect techniques like pugmark surveys often produce ambiguous information that is difficult to interpret because many factors influence marking behavior and frequency (Ahlborn & Jackson 1988). Considering the snow leopard's rugged habitat, it is not surprising then that information on its current status and occupied range is very limited. We adapted the camera-trapping techniques pioneered by Ullas Karanth and his associates for counting Bengal tigers to the census taking of snow leopards in the Rumbak watershed of the India's Hemis High Altitude National Park (HNP), located in Ladakh near Leh (76ø 50' to 77ø 45' East; 33ø 15' to 34ø 20'North).

Abstract: The secretive nature of snow leopards (Uncia uncia) makes them difficult to monitor, yet conservation efforts require accurate and precise methods to estimate abundance. We assessed accuracy of Snow Leopard Information Management System (SLIMS) sign surveys by comparing them with 4 methods for estimating snow leopard abundance: predator:prey biomass ratios, capture-recapture density estimation, photo-capture rate, and individual identification through genetic analysis. We recorded snow leopard sign during standardized surveys in the SaryChat Zapovednik, the Jangart hunting reserve, and the Tomur Strictly Protected Area, in the Tien Shan Mountains of Kyrgyzstan and China. During June-December 2005, adjusted sign averaged 46.3 (SaryChat), 94.6 (Jangart), and 150.8 (Tomur) occurrences/km. We used
counts of ibex (Capra ibex) and argali (Ovis ammon) to estimate available prey biomass and subsequent potential snow leopard densities of 8.7 (SaryChat), 1.0 (Jangart), and 1.1 (Tomur) snow leopards/100 km2. Photo capture-recapture density estimates were 0.15 (n = 1 identified individual/1 photo), 0.87 (n = 4/13), and 0.74 (n = 5/6) individuals/100 km2 in SaryChat, Jangart, and Tomur, respectively. Photo-capture rates
(photos/100 trap-nights) were 0.09 (SaryChat), 0.93 (Jangart), and 2.37 (Tomur). Genetic analysis of snow leopard fecal samples provided minimum population sizes of 3 (SaryChat), 5 (Jangart), and 9 (Tomur) snow leopards. These results suggest SLIMS sign surveys may be affected by observer bias and environmental variance. However, when such bias and variation are accounted for, sign surveys indicate relative abundances similar to photo rates and genetic individual identification results. Density or abundance estimates based on capture-recapture or ungulate biomass did not agree with other indices of abundance. Confidence in estimated densities, or even detection of significant changes in abundance of snow leopard, will require more effort and better documentation.

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: From September to November 2004 we conducted surveys of snow leopard Uncia uncia signs in three major valleys in Sagarmatha (Mount Everest) National Park in Nepal using the Snow Leopard Information Management System, a standardized survey technique for snow leopard research. We walked 24 transects covering c. 14 km and located 33 sites with 56 snow leopard signs, and 17 signs incidentally in other areas. Snow leopards appear to have re-inhabited the Park, following their disappearance c. 40 years ago, apparently following the recovery of Himalayan tahr Hemitragus jemlahicus and musk deer Moschus chrysogaster populations. Taken together the locations of all 73 recent snow leopard signs indicate that the species is using predominantly grazing land and shrubland/ open forest at elevations of 3,000-5,000 m, habitat types that are also used by domestic and wild ungulates. Sagarmatha is the homeland of c. 3,500 Buddhist Sherpas with .3,000 livestock. Along with tourism and associated developments in Sagarmatha, traditional land use practices could be used to ensure coexistence of livestock and wildlife, including the recovering snow leopards, and ensure the wellbeing of the Sherpas.

Abstract: Nepal's snow leopards (Uncia uncia) are mostly found along the northern border with Tibet (China). The largest populations are in Dolpa, Mugu, Manang, and Myagdi Districts. Potential habitat totals about 30,000 square kilometers. Numbers are estimated at 300-500, but surveys are urgently needed to confirm this rough guess. Like elsewhere, the primary threats center on poaching, depletion of natural prey, livestock depredation and resultant retributive killing of snow leopards by herders, and the lack of public awareness and support for conserving snow leoaprds, especially among local herders.

Abstract: Habitat selection of Snow Leopard ( Unica unica) in Beita Mountain of the Altay Mountain system in northeast Xinjiang was conducted from September to October 2004. Six habitat features of 59 sites used by Snow Leopard and 30 random plots were measured by locating 15 transects surveys in the study area . Vanderploge and Scaviaps selectivity index was used to assess Snow Leopardps selection for the different habitat parameters. Principal Component Analysis was used as the primary factor . The results indicated that Snow Leopard preferred the altitude between 2000 – 2 200 m and avoided 2 600 – 3 000 m ; selected cliff base , ridgeline and avoided hillside and valley bottom ; utilized the shrub and rejected the forest ; selected the nongrazing area and avoided the slightly broken region ; preferred north orientation and rejected the south orientation. The results show that grazing status , vegetation type , topography and the ruggedness are the primary factors for the habitat selection of Snow Leopard.