Wahlberg, C. (1980). Autopsy findings and causes of death in captive snow leopards (Panthera uncia): a preliminary report. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards (Vol. 2, pp. 205–217). Helsinki: Helsinki Zoo.
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Knowles, J. (1982). Snow leopards (Panthera uncia) at Marwell Zoological Park. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards, Vol. 3 (Vol. 3, pp. 59–62). Helsinki: Helsinki Zoo.
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Blomqvist, L. (1979). The 1978 register for the captive population of snow leopards, Panthera uncia. International Zoo News, 26(7-8), 17–23.
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Blomqvist, L. (1989). Status of the captive snow leopard (Panthera uncia) in 1987.
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Freeman, H. (1974). A preliminary study of the behaviour of captive snow leopards (Panthera uncia). In International Zoo Yearbook (Vol. 15, pp. 217–222).
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Rana, B. S. (1997). Distinguishing kills of two large mammalian predators in Spiti Valley Himachal Pradesh. J.Bombay Nat.Hist.Soc, 94(3), 553.
Abstract: The author studied livestock killed by predators in the Spiti Valley, India, to determine what species had killed yaks, horses, donkeys, and other domestic animals. Eleven of the kills examined were made by snow leopards and six by the Tibetan wolf. Wolves were involved in surplus killings, while snow leopards kill as food is needed. lgh
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Suryawanshi, K. R., Bhatnagar, Y. V. B., Redpath, S., Mishra, C. (2013). People, predators and perceptions: patterns of livestock depredation by snow leopards and wolves. Journal of Applied Ecology, 50, 550–560.
Abstract: 1. Livestock depredation by large carnivores is an important conservation and economic concern
and conservation management would benefit from a better understanding of spatial variation
and underlying causes of depredation events. Focusing on the endangered snow leopard
Panthera uncia and the wolf Canis lupus, we identify the ecological factors that predispose
areas within a landscape to livestock depredation. We also examine the potential mismatch
between reality and human perceptions of livestock depredation by these carnivores whose
survival is threatened due to persecution by pastoralists.
2. We assessed the distribution of the snow leopard, wolf and wild ungulate prey through field
surveys in the 4000 km2 Upper Spiti Landscape of trans-Himalayan India. We interviewed local
people in all 25 villages to assess the distribution of livestock and peoples’ perceptions of the risk
to livestock from these carnivores. We monitored village-level livestock mortality over a 2-year
period to assess the actual level of livestock depredation. We quantified several possibly influential
independent variables that together captured variation in topography, carnivore abundance
and abundance and other attributes of livestock. We identified the key variables influencing livestock
depredation using multiple logistic regressions and hierarchical partitioning.
3. Our results revealed notable differences in livestock selectivity and ecological correlates of
livestock depredation – both perceived and actual – by snow leopards and wolves. Stocking
density of large-bodied free-ranging livestock (yaks and horses) best explained people’s threat
perception of livestock depredation by snow leopards, while actual livestock depredation was
explained by the relative abundance of snow leopards and wild prey. In the case of wolves,
peoples’ perception was best explained by abundance of wolves, while actual depredation by
wolves was explained by habitat structure.
4. Synthesis and applications. Our results show that (i) human perceptions can be at odds
with actual patterns of livestock depredation, (ii) increases in wild prey populations will intensify
livestock depredation by snow leopards, and prey recovery programmes must be accompanied
by measures to protect livestock, (iii) compensation or insurance programmes should
target large-bodied livestock in snow leopard habitats and (iv) sustained awareness
programmes are much needed, especially for the wolf.
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Mishra, C., Young, J. C., Fiechter, M., Rutherford, B., Redpath, S. M. (2017). Building partnerships with communities for biodiversity conservation: lessons from Asian mountains. Journal of Applied Ecology, , 1–9.
Abstract: Applied ecology lies at the intersection of human societies and natural systems. Consequently, applied ecologists are constantly challenged as to how best to use ecological knowledge to influence the management of ecosystems (Habel et al. 2013). As Hulme (2011) has pointed out, to do so effectively we must leave our ivory towers and engage with stakeholders. This engagement is especially important and challenging in areas of the world where poverty, weak institutions and poor governance structures conspire to limit the ability of local communities to contribute to biodiversity conservation. These communities often bear disproportionate costs in the form of curtailed access to natural resources, ecosystem services, and developmental
programmes, and also suffer wildlife-caused damage, including injuries or loss of human life, and economic
and psychological impacts (Madhusudan & Mishra 2003). It is well-recognized that conservation efforts in large parts of the world historically have been perceived to be discriminatory by local people (Mishra 2016). The need for engagement with local communities is therefore embedded in the 2020 Aichi biodiversity targets and is widely thought to be critical to the success of conservation efforts. However, although the need for engagement is clear, as ecologists and practitioners we often have little formal training in how we should engage with local communities and how we can recognize the pitfalls and opportunities provided by developing genuine partnerships. The practical challenges of achieving effective engagement are considerable (Agrawal & Gibson 1999; Waylen et al. 2010, 2013), and such forays are fraught with difficulties and ethical considerations (Chan et al. 2007). When they are done badly, conservation interventions
can damage relationships and trust, and lead to serious injustice to local people and setbacks for ecological
outcomes (Duffy 2010). Much has been written on knowledge exchange and participatory research approaches (e.g. Reed et al. 2014 and references therein). This Practitioner’s Perspective
seeks to focus on the next logical step: the elements that practitioners and researchers need to consider when
engaging with communities to effect conservation. Engagement around the management of protected areas
has been discussed and formalized (e.g. Dudley 2008). Considerable literature has also emerged, particularly
from Africa, on the use and co-management of natural resources, commonly referred to as community-based natural resource management or CBNRM (e.g. Fabricius 2004; Roe, Nelson & Sandbrook 2009; Child & Barnes
2010). There have been attempts to draw general principles for CBNRM (e.g. Thakadu 2005; Gruber 2010). In
the related field of community-based conservation, however, while there have been efforts to draw lessons (e.g. Berkes 2004), little exists in terms of frameworks or guidelines for effectively working with local communities to effect biodiversity conservation in multi-use landscapes
(Mishra 2016). The eight principles for community-based conservation outlined here (Fig. 1) build on ideas developed in fields as diverse as applied ecology, conservation and natural
resource management, community health, social psychology, rural development, negotiation theory, and ethics
(see Mishra 2016). They have been developed, challenged and tested through 20 years of community experience andour own research on the endangered snow leopard Panthera uncia and its mountain ecosystems, in South and Central Asia. We suspect that with contextual adaptations, their relevance for applied ecologists and practitioners may be universal.
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Oli, M. (1994). Snow leopards and blue sheep in Nepal: Densities and predator: Prey ratio (Vol. 75).
Abstract: I studied snow leopards (Panthera uncia) and blue sheep (Pseudois nayaur) in Manang District, Annapurna Conservation Area, Nepal, to estimate numbers and analyze predatorprey interactions. Five to seven adult leopards used the 105-km2 study area, a density of 4.8 to 6.7 leopards/100 km2. Density of blue sheep was 6.6-10.2 sheep/km2, and biomass density was 304 kg/km2. Estimated relative biomass consumed by snow leopards suggested that blue sheep were the most important prey; marmots (Marmota himalayana) also contributed significantly to the diet of snow leopards. Snow leopards in Manang were estimated to harvest 9-20% of total biomass and 11-24% of total number of blue sheep annually. Snow leopard :blue sheep ratio was 1 :1 14-1 :159 on a weight basis, which was considered sustainable given the importance of small mammals in the leopard's diet and the absence of other competing predators.
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Xiao, C., Bai, D., Lambert, J. P., Li, Y., Cering, L., Gong, Z., Riordan, P., Shi, K. (2022). How Snow Leopards Share the Same Landscape with Tibetan Agro-pastoral Communities in the Chinese Himalayas. Journal of Resources and Ecology, 13(3), 483–500.
Abstract: The snow leopard (Panthera uncia) inhabits a human-altered alpine landscape and is often tolerated by residents in regions where the dominant religion is Tibetan Buddhism, including in Qomolangma NNR on the northern side of the Chinese Himalayas. Despite these positive attitudes, many decades of rapid economic development and population growth can cause increasing disturbance to the snow leopards, altering their habitat use patterns and ultimately impacting their conservation. We adopted a dynamic landscape ecology perspective and used multi-scale technique and occupancy model to better understand snow leopard habitat use and coexistence with humans in an 825 km2 communal landscape. We ranked eight hypothetical models containing potential natural and anthropogenic drivers of habitat use and compared them between summer and winter seasons within a year. HABITAT was the optimal model in winter, whereas ANTHROPOGENIC INFLUENCE was the top ranking in summer (AICcw≤2). Overall, model performance was better in the winter than in the summer, suggesting that perhaps some latent summer covariates were not measured. Among the individual variables, terrain ruggedness strongly affected snow leopard habitat use in the winter, but not in the summer. Univariate modeling suggested snow leopards prefer to use rugged land in winter with a broad scale (4000 m focal radius) but with a lesser scale in summer (30 m); Snow leopards preferred habitat with a slope of 22° at a scale of 1000 m throughout both seasons, which is possibly correlated with prey occurrence. Furthermore, all covariates mentioned above showed inextricable ties with human activities (presence of settlements and grazing intensity). Our findings show that multiple sources of anthropogenic activity have complex connections with snow leopard habitat use, even under low human density when anthropogenic activities are sparsely distributed across a vast landscape. This study is also valuable for habitat use research in the future, especially regarding covariate selection for finite sample sizes in inaccessible terrain.
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