Abstract: When densities of large carnivores fall below certain thresholds, dramatic ecological effects
can follow, leading to oversimplified ecosystems. Understanding the population status of
such species remains a major challenge as they occur in low densities and their ranges are
wide. This paper describes the use of non-invasive data collection techniques combined
with recent spatial capture-recapture methods to estimate the density of snow leopards
Panthera uncia. It also investigates the influence of environmental and human activity indicators
on their spatial distribution. A total of 60 camera traps were systematically set up during
a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve,
Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trapdays,
representing an average capture success of 2.62 captures/100 trap-days. We identified
a total number of 20 unique individuals from photographs and estimated snow leopard
density at 3.31 (SE = 1.01) individuals per 100 km2. Results of our simulation exercise indicate
that our estimates from the Spatial Capture Recapture models were not optimal to
respect to bias and precision (RMSEs for density parameters less or equal to 0.87). Our
results underline the critical challenge in achieving sufficient sample sizes of snow leopard
captures and recaptures. Possible performance improvements are discussed, principally by
optimising effective camera capture and photographic data quality.

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: 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: The protection of Snow Leopards in the remote and economically disadvantaged Northern Areas of Pakistan needs local people equipped with the skills to gather and present information on the number and range of individual animals in their area. It is important for the success of a conservation campaign that the people living in the area are engaged in the conservation process. Snow Leopards are elusive and range through inhospitable terrain so direct study is difficult. Consequently the major goals for this project were twofold, to gather information on snow leopard distribution in this area and to train local university students and conservation management professionals in the techniques used for locating snow leopards without the need to capture or even see the animals. This project pioneered the use of DNA testing of field samples collected in Pakistan to determine the distribution of snow leopards and to attempt to identify individuals. These were collected in and around that country's most northerly national park, the Kunjurab National Park, which sits on the Pakistan China border. Though the Northern Areas is not a well developed part of Pakistan, it does possess a number of institutions that can work together to strengthen snow leopard conservation. The first of these is a newly established University with students ready to be trained in the skills needed. Secondly WWF-Pakistan has an office in the main town and a state of the art GIS laboratory in Lahore and already works closely with the Forest Department who manage the national park. All three institutions worked together in this project with WWF providing GIS expertise, the FD rangers, and the university students carrying out the laboratory work. In addition in the course of the project the University of the Punjab in Lahore also joined the effort, providing laboratory facilities for the students. As a result of this project maps have been produced showing the location of snow leopards in
two areas. Preliminary DNA evidence indicates that there is more than one animal in this
relatively small area, but the greatest achievement of this project is the training and
experience gained by the local students. For one student this has been life changing. Due to
the opportunities provided by this study the student, Nelofar gained significant scientific
training and as a consequence she is now working as a lecturer and research officer for the
Center for Integrated Mountain Research, New Campus University of the Punjab, Lahore
Pakistan

Abstract: Conservation and management of snow leopards (Uncia uncial) has largely relied on anecdotal evidence and presence-absence data due to their cryptic nature and the difficult terrain they inhabit. These methods generally lack the scientific rigor necessary to accurately estimate population size and monitor trends. We evaluated the use of photography in capture-mark-recapture (CMR) techniques for estimating snow leopard population abundance and density within Hemis National Park, Ladakh, India. We placed infrared camera traps along actively used travel paths, scent-sprayed rocks, and scrape sites within 16-30 kmý sampling grids in successive winters during January and March 2003-2004. We used head-on, oblique, and side-view camera configurations to obtain snow leopard photographs at varying body orientations. We calculated snow leopard abundance estimates using the program CAPTURE. We obtained a total of 66 and 49 snow leopard captures resulting in 8.91 and 5.63 individuals per 100 trap nights during 2003 and 2004, respectively. We identified snow leopards based on the distinct pelage patters located primarily on the forelimbs, flanks, and dorsal surface of the tail. Capture probabilities ranged from 0.33 to 0.67. Density estimates ranged from 8.49 (SE+0.22) individuals per 100 kmý in 2003 to 4.45 (SE+0.16) in 2004. We believe the density disparity between years is attributable to different trap density and placement rather than to an actual decline in population size. Our results suggest that photographic capture-mark-recapture sampling may be a useful tool for monitoring demographic patterns. However, we believe a larger sample size would be necessary for generating a statistically robust estimate of population density and abundance based on CMR models.

Abstract: Animal-borne tracking devices have generated a wealth of new knowledge, allowing us to better understand, manage and conserve species. Fitting such tracking devices requires that animals are captured and often chemically immobilized. Such procedures cause stress and involve the risk of injuries and loss of life even in healthy individuals. For telemetry studies to be justifiable, it is vital that capture operations are planned and executed in an efficient and ethical way. Project objectives must be clearly articulated to address well-defined knowledge gaps, and studies designed to maximize the probability of achieving those goals. We provide guidelines for how to plan, design, and implement telemetry studies with a special emphasis on snow leopards that are typically captured using foot snares. We also describe the necessary steps to ensure that captures are conducted safely, and with minimal stress to animals.

Abstract: Abundance estimation of large carnivores is essential for their effective conservation planning, yet estimating population size is challenging due to their elusive and wide-ranging nature. China is estimated to encompass 60% of the snow leopard Panthera uncia habitat, making it a crucial pillar for global snow leopard conservation. However, no large-scale population assessment has been conducted despite scattered survey effort accumulating rapidly in recent years. This study combined and standardized existing camera trap sur-
vey data from 12 sites collected by four organizations during 2015 ~ 2021 to estimate snow leopard population in an area of 360,000 ­ km2 on the Tibetan Plateau, China. The representativeness of existing survey was evaluated based on two habitat stratification approaches to achieve less biased population assessment. Spatially explicit capture-recapture (SECR) models were applied for snow leopard density estimation and the top-ranked model showed a significant positive correlation between conservation priority strata and density. An average snow leopard density of 0.90 /100 ­ km2 (95% CI: 0.68 ~ 1.21 /100 ­ km2) and a population size of 1,002 (95% CI: 755 ~ 1,341) individuals was estimated for the defined snow leopard habitat. Two more conservative estimates of 971 (95% CI: 732 ~ 1,287) and 978 (95% CI: 737 ~ 1,267) individuals were generated within two defined survey regions, in which our data had higher representativity. This study presents a practical approach to synthesize existing population survey data for large-scale population assessments of individually identifiable species. The estimated number represents 11 ~ 21% of the global snow leopard population, indicating high conservation value of this region.

Abstract: The main purpose of this work was to study the use of infrared trapping cameras to estimate snow leopard Uncia uncia 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 five different small vales of the Muzat Valley adjacent to the Tomur Nature Reserve in Xinjiang Province, E80ø35' – 81ø00' and N42ø00' – 42ø10', elevation 2'300 – 3'000 m, from 18th October to 27th December 2005. We expended approximately 2094 trap days and nights total (c. 50'256 hours). At least 32 pictures of snow leopards, 22 pictures of other wild species (e.g. chukor, wild pig, ibex, red fox, cape hare) and 72 pictures of livestock were taken by the passive Cam Trakker (CT) train monitor in about 16 points of the Muzat Valley. The movement distance of snow leopard was 3-10 km/day. And the capture rate or photographic rate of snow leopard was 1.53%. Meanwhile, 20 transects were run and 31 feces sample were collected. According to 32 photos, photographic rate and sign survey after snowing on the spot, were about 5-8 individuals of snow leopards in the research area, and the minimum density of snow leopard in Muzat Valley was 2.0 – 3.2 individuals/100 km2. We observed the behavior of ibex for 77.3 hours, and found about 20 groups and a total of approximately 264 ibexes in the research area.

Abstract: The snow leopard Panthera uncia is an elusive and globally-threatened apex predator occurring in the mountain ranges of central Asia. As with other large carnivores, gaps in data on its distribution and abundance still persist. Moreover, available density estimates are often based on inadequate sampling designs or analytical approaches. Here, we used camera trapping across a vast mountainous area (area of the sampling frame 850 km2; analysed habitat extent 2600 km2) and spatially-explicit capture-recapture (SECR) models to provide, to our knowledge, the first robust snow leopard population density estimate for the Altai Mountains. This region is considered one of the most important conservation areas for snow leopards, representing a vast portion of suitable habitat and a key ecological corridor. We also provide estimates of the scale parameter (σ) that reflects ranging behaviour (activity range) and baseline encounter probability, and investigated potential drivers of density and related parameters by assessing their associations with anthropogenic and environmental factors. Sampling yielded 9729 images of snow leopards corresponding to 224 independent detections that belonged to a minimum of 23 identified adult individuals. SECR analysis resulted in an overall density of 1.31 individuals/100 km2 (1.15%–1.50 95% CI), which was positively correlated with terrain slope. This estimate falls within the mid-values of the range of density estimates for the species globally. We estimated significantly different activity range size for females and males (79 and 329 km2, respectively). Base- line encounter probability was negatively associated with anthropogenic activity. Our study contributes to on-going efforts to produce robust global estimates of population abundance for this top carnivore.