|
Zhenhuang, S. (1964). Economic Fauna of China. China: Academia Sinica Press.
|
|
Zhirjakov, V. A. (1990). On the ecology of the snow leopard in the Zailisky-Alatau (Northern Tien Shan). Int Ped Book of Snow Leopards, 6, 25–30.
|
Zhirnov L.V. (1978). Rare and endangered species of the USSR.
Abstract: A description of snow leopard number, distribution, reproductive biology, death reasons, and conservation measures in the USSR, where northern and north-western border of its habitat runs, is given. The population of snow leopard in the USSR is 500 1,000 animals. In the Inner Tien Shan, 400 snow leopards were caught 1936 through 1970. The maximum of 120 skins was purchased in Pamir in 1956 1958. Population of snow leopard directly correlates with population of ibex, a fact being verified by data collected on a long-term basis. Moreover, snow leopard was for a long time considered as a harmful animal, shooting of which was encouraged by premiums and resulted in reduction of snow leopard population.
|
Zhirnov, L., & Ilyinsky, V. (1986). The Great Gobi National Park – a refuge for rare animals of the Central Asian deserts. Moscow: Centre for International Projects, GKNT.
Abstract: Discusses snow leopard distribution in Great Gobi National Park
|
Zhiryakov V.A. (2002). Ecology and behavior of the Snow leopard in Kazakhstan (Vol. N 1-4.).
Abstract: The data on spreading, numbers and population density of snow leopard in Kazakhstan are given in this article. The total number of the snow leopard in Kazakhstan is evaluated in 100-110 individuals. The everywhere occurred numbers' reduction under the influence of the anthropogenic factors is observed. The snow leopard' inhabitation area varies from 20 to 120 square kilometers depending on its regions. Sex and composition of the population and its aggregative behavior are given. The dynamics of numbers and mortality are estimated.
|
Zimina R.P. (1964). Biology and biotopical distribution of mammals. Predators. Distribution of mammals by vertical zones.
Abstract: Fauna of the Issyk-Kul depression and the surrounding ridges consists of heterogeneous elements different in their ecologic features and origin. In highlands, more common are species of Central Asia's origin (gray marmot, snow leopard, dhole, ibex, argali, etc.). Snow leopard is met in Terskey-Alatau. Each year hunters catch/shoot one to three snow leopards in the Chon-Kizilsu river basin. In the Djeti-Oguz district, up to five eight snow leopards are caught each winter. Snow leopard is also caught/shot in the river basins Chon-Kizilsu, Karabatkak, Ortok, Archtor, Tekeletor, and Shatly.
|
Zong-Yi, W., & Sung, W. (1986). Distribution and recent status of the Felidae in China. In D.S.Miller, &.D.D.Everett (Eds.), (pp. 201–209).
Abstract: Thirteen of the 37 existing species of the family Felidae have been recorded in China. These species are widely distributed throughout the country and inhabit a variety of life zones. Over the past several decades, the populations of most species of cats in China have declined due to overharvest and habitat destruction. China has a Protected Wildlife Species List which was initiated in 1962. Some cat species in China are now endangered or may already be extinct while other species or subspecies are threatened. The authors use limited data on the distribution of cats in China to summarize the staus of each species and the problems facing each. Recomendations for new measures to protect cats in China are made.
|
Anonymous. (2001). Snow leopard in Mongolia. Ulaanbaatar, Mongolia.
Abstract: This documents contains a review of the snow leopard's distribution, status and habitat in Mongolia, describes threats and conservation needs of the species, and outlines presently implemented actions. Five major threats are identified: 1) Poaching 2) loss of prey 3) degradation, fragmentation and loss of habitat 4) conflict with herders 5) lack of public awareness. Actions to mitigate the five major threats are recommended and future conservation priorities are set.
|
Han, X. M., D. G., Zhang, E., Jones, M., and Jin, T.. (2001). Far eastern leopard and Siberian tiger conservation measures. (pp. 102–103). Harbin: Widlife Conservation Society.
Abstract: Workshop to develop a recovery plan for the wild north China tiger population. October 20th to 23th, 2000, Harbin.
Like the Siberian Tiger, the Far Eastern Leopard is one of China's largest Felidae and lives mainly in the eastern mountains of Jilin Province. The number of leopards is very low and it is even more endangered than the tiger. There is a very close relationship between leopard and tiger conservation, especially in areas where overlap occurs. In these areas, special emphasis has to be placed on each of the species' specific conservation needs. There is urgent need to step up our efforts to study and monitor leopard populations and to develop a conservation strategy. This document contains information of the status and main threats of the Far Eastern leopard and makes recommendations on needed conservation measures.
Keywords: CCT, conservation, conservation needs, conservation strategy, distribution, Jilin Province, leopard, monitoring, Panthera pardus, Panthera tigris, poaching, recovery, Recovery plan, snow
|
LI. J, W. A. N. G. D., YIN. H, ZHAXI. D, JIAGONG. Z, SCHALLER. G. B, MISHRA. C, MCCARTHY. T. M, WANG. H, WU. L, XIAO. L, BASANG. L, ZHANG. Y, ZHOU. Y, LU. Z. (2013). Role of Tibetan Buddhist Monasteries in Snow Leopard Conservation. Conservation Biology, 00, 1–8.
Abstract: The snow leopard (Panthera uncia) inhabits the rugged mountains in 12 countries of Central Asia,
including the Tibetan Plateau. Due to poaching, decreased abundance of prey, and habitat degradation, it was listed as endangered by the International Union for Conservation of Nature in 1972. Current conservation strategies, including nature reserves and incentive programs, have limited capacities to protect snow leopards. We investigated the role of Tibetan Buddhist monasteries in snow leopard conservation in the Sanjiangyuan region in China’s Qinghai Province on the Tibetan Plateau. From 2009 to 2011, we systematically surveyed snow leopards in the Sanjiangyuan region. We used the MaxEnt model to determine the relation of their presence to environmental variables (e.g., elevation, ruggedness) and to predict snow leopard distribution. Model results showed 89,602 km2 of snow leopard habitat in the Sanjiangyuan region, of which 7674 km2 lay within Sanjiangyuan Nature Reserve’s core zones. We analyzed the spatial relation between snow leopard habitat and Buddhist monasteries and found that 46% of monasteries were located in snow leopard habitat and 90% were within 5 km of snow leopard habitat. The 336 monasteries in the Sanjiangyuan region could protect more snow leopard habitat (8342 km2) through social norms and active patrols than the nature reserve’s core zones. We conducted 144 household interviews to identify local herders’ attitudes and behavior toward snow leopards and other wildlife. Most local herders claimed that they did not kill wildlife, and 42% said they did not kill wildlife because it was a sin in Buddhism. Our results indicate monasteries play an important role in snow leopard conservation. Monastery-based snow leopard conservation could be extended to other Tibetan Buddhist regions that in total would encompass about 80% of the global range of snow leopards.
|
Holt, C. D. S., Nevin, O. T., Smith, D., Convery, I. (2018). Environmental niche overlap between snow leopard and four prey species in Kazakhstan. Elsevier, (48), 97–103.
Abstract: The snow leopard Panthera uncia has declined due to habitat loss, habitat fragmentation and human persecution. Predator distribution is heavily dependent on prey species availability and distribution. With increasing pressures from farming practices encroaching into native species range and persecution of snow leopards in response to livestock depredation, it is vital to assess current predator and prey species distribution to highlight sensitive areas of overlap for protection. This study uses MaxEnt, a presence-only Species Distribution Model (SDM) to assess snow leopard and four prey species habitat suitability along
the southern and eastern borders of Kazakhstan using environmental data. This area is considered an important corridor between snow leopard populations in the north and south of their range. Each of the five SDM's produced models of �good� discriminating abilities. We then compared the potential niche overlap between snow leopard and four prey species using ENMTools to highlight areas of important niche overlap within the corridor. The results indicated a very high degree of overlap between snow leopard and Siberian ibex and high degrees Capra sibirica with red deer Cervus elaphus, argali Ovis ammon and urial Ovis orientalis. The snow leopard population in this region is also found to be using forested areas below 2500 m, much lower than recorded in other areas of their range. The results highlight areas needed for protection but also pose additional conservation questions regarding the importance of prey species to transitory individuals.
|
Karnaukhov, A. S., Malykh, S. V., Korablev, M. P., Kalashnikova, Y. M., Poyarkov, A. D., Rozhnov, V. V. (2018). Current Status of the Eastern Sayan Snow Leopard (Panthera uncia) Grouping and Its Nutritive Base. Biology Bulletin, 45(9), 1106–1115.
Abstract: A field survey of snow leopard (Panthera uncia) habitats was carried out in the southeastern part of
the Eastern Sayan Mountains (Okinskii and Tunkinskii districts of the Republic of Buryatia and the Kaa-
Khemskii district of Tuva Republic). Seven or eight adult snow leopards were observed as constant inhabitants
of the Tunkinskie Gol'tsy, Munku-Sardyk, and Bol'shoi Sayan mountain ridges. The presence of eight
snow leopards was confirmed using DNA-based analyses of scats collected in 2014 – 2016. The main prey species
of the snow leopard in Eastern Sayan is the Siberian ibex (Capra sibirica), but its abundance has steadily
decreased over the past 20 years. The red deer (Cervus elaphus) and the wild boar (Sus scrofa), which were
some of the most numerous ungulates in the survey area, are replacing the Siberian ibex in the snow leopard's
diet. In addition, the mountain hare (Lepus timidus) is also of importance to the snow leopard's diet.
|
Singh, R., Krausman, P. R., Pandey, P., Maheshwari, A., Rawal,
R. S., Sharma, S., Shekhar, S. (2020). Predicting Habitat Suitability of Snow Leopards in the Western
Himalayan Mountains, India. Biology bulletin, 47(6), 655–664.
Abstract: The population of snow leopard (Panthera uncia) is declining
across their range, due to poaching, habitat fragmentation, retaliatory
killing, and a decrease of wild prey species. Obtaining information on
rare and cryptic predators living in remote and rugged terrain is
important for making conservation and management strategies. We used the
Maximum Entropy (MaxEnt) ecological niche modeling framework to predict
the potential habitat of snow leopards across the western Himalayan
region, India. The model was developed using 34 spatial species
occurrence points in the western Himalaya, and 26 parameters including,
prey species distribution, temperature, precipitation, land use and land
cover (LULC), slope, aspect, terrain ruggedness and altitude. Thirteen
variables contributed 98.6% towards predicting the distribution of snow
leopards. The area under the curve (AUC) score was high (0.994) for the
training data from our model, which indicates pre- dictive ability of
the model. The model predicted that there was 42432 km2 of potential
habitat for snow leop- ards in the western Himalaya region. Protected
status was available for 11247 km2 (26.5%), but the other 31185 km2
(73.5%) of potential habitat did not have any protected status. Thus,
our approach is useful for predicting the distribution and suitable
habitats and can focus field surveys in selected areas to save
resources, increase survey success, and improve conservation efforts for
snow leopards.
|
Atzeni, L., Cushman, S. A., Bai, D., Wang, J., Chen, P., Shi,
K., Riordan, P. (2020). Meta-replication, sampling bias, and multi-scale model selection:
A case study on snow leopard (Panthera uncia) in western China. Ecology and Evolution, , 1–27.
Abstract: Replicated multiple scale species distribution models (SDMs)
have become increasingly important to identify the correct variables
determining species distribution and their influences on ecological
responses. This study explores multi-scale habitat relationships of the
snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan
Plateau of western China. Our primary objectives were to evaluate the
degree to which snow leopard habitat relationships, expressed by
predictors, scales of response, and magnitude of effects, were
consistent across study areas or locally landcape-specific. We coupled
univariate scale optimization and the maximum entropy algorithm to
produce multivariate SDMs, inferring the relative suitability for the
species by ensembling top performing models. We optimized the SDMs based
on average omission rate across the top models and ensembles’ overlap
with a simulated reference model. Comparison of SDMs in the two study
areas highlighted landscape-specific responses to limiting factors.
These were dependent on the effects of the hydrological network,
anthropogenic features, topographic complexity, and the heterogeneity of
the landcover patch mosaic. Overall, even accounting for specific local
differences, we found general landscape attributes associated with snow
leopard ecological requirements, consisting of a positive association
with uplands and ridges, aggregated low-contrast landscapes, and large
extents of grassy and herbaceous vegetation. As a means to evaluate the
performance of two bias correction methods, we explored their effects on
three datasets showing a range of bias intensities. The performance of
corrections depends on the bias intensity; however, density kernels
offered a reliable correction strategy under all circumstances. This
study reveals the multi-scale response of snow leopards to environmental
attributes and confirms the role of meta-replicated study designs for
the identification of spatially varying limiting factors. Furthermore,
this study makes important contributions to the ongoing discussion about
the best approaches for sampling bias correction.
|
