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: Snow leopard ecology, distribution and abundance in Mongolia were studied between 1993 and 1999. I placed VHF and satellite radio-collars on 4 snow leopards, 2 males and 2 females, to determine home ranges, habitat use, movements, and activity. Home ranges of snow leopards in Mongolia were substantially larger than reported elsewhere. Males ranged over 61 – 142 km2 and female 58 to 1,590 km2. Cats had crepuscular activity patterns with daily movements averaging 5.1 km. Intraspecific distances averaged 1.3 km for males to 7.8 km for males. Leopards selected moderately to very-broken habitat with slopes > 20o, in areas containing ibex. Leopard distribution and abundance was determined using sign surveys. Leopard range in Mongolia is approximately 103,000 km2 but cats are not uniformly distributed within that range. High-density areas include the eastern and central Transaltai Gobi and the northern Altai ranges. Relative leopard densities compared well with relative ibex densities on a regional basis. A snow leopard conservation plan was drafted for Mongolia that identifies problems and threats, and provides an action plan. Wild Bactrian camels occur in the Great Gobi National Park (GGNP) and are thought to be declining due to low recruitment. I surveyed camels by jeep and at oases, observing 142 (4.2% young) and 183 (5.3% young) in 1997 and 1998. Current range was estimated at 33,300 km2. Some winter and calving ranges were recently abandoned. Track sizes and tooth ages from skulls were used to assess demographics. A deterministic model was produced that predicts camel extinction within 25 to 50 years under current recruitment rates and population estimates. Gobi brown bears are endemic to Mongolia and may number less than 35. Three population isolates may occur. I collected genetic material from bears at oases using hair traps. Microsatellite analyses of nuclear DNA determined sixteen unique genotypes, only two of which occurred at more than one oases. Genetic diversity was very low with expected heterozygosity = 0.32, and alleles per locus = 2.3. Mitochondrial DNA sequences were compared to other clades of brown bear and found to fall outside of all known lineages.

Abstract: China, the world's most populous country, also contains the largest number of Snow Leopards of any country in the world. But the survey and research of the snow leopard had been very little for the second half of the 20th century. Until recent years, the members of Xinjiang Snow Leopards Group (XSLG/SLT/XFC) , the Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences have been tracking down the solitary animal. The journal reporter does a face-to-face interview with professor Ma Ming who is a main responsible expert of the survey team. By the account of such conversation, we learn the achievements, advances and difficulty of research of snow leopards in the field, Tianshan and Kunlun, Xinjiang, the far west China, and we also know that why the team adopt the infrared camera to capture the animals. Last but not least professor talked about the survival menace faced by the Snow Leopards in Xinjiang.