Co-occurrence of snow leopard, wolf and Siberian ibex under livestock encroachment into protected areas across the Mongolian Altai

2021 ◽  
Vol 261 ◽  
pp. 109294
Author(s):  
Marco Salvatori ◽  
Simone Tenan ◽  
Valentina Oberosler ◽  
Claudio Augugliaro ◽  
Philippe Christe ◽  
...  
PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0228832
Author(s):  
Shoaib Hameed ◽  
Jaffar ud Din ◽  
Hussain Ali ◽  
Muhammad Kabir ◽  
Muhammad Younas ◽  
...  

Pakistan’s total estimated snow leopard habitat is about 80,000 km2 of which about half is considered prime habitat. However, this preliminary demarcation was not always in close agreement with the actual distribution—the discrepancy may be huge at the local and regional level. Recent technological developments like camera trapping and molecular genetics allow for collecting reliable presence records that could be used to construct realistic species distribution based on empirical data and advanced mathematical approaches like MaxEnt. The current study followed this approach to construct an accurate distribution of the species in Pakistan. Moreover, movement corridors, among different landscapes, were also identified through circuit theory. The probability of habitat suitability, generated from 98 presence points and 11 environmental variables, scored the snow leopard’s assumed range in Pakistan, from 0 to 0.97. A large portion of the known range represented low-quality habitat, including areas in lower Chitral, Swat, Astore, and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber, Broghil, and Central Karakoram represented high-quality habitats. Variables with higher contributions in the MaxEnt model were precipitation during the driest month (34%), annual mean temperature (19.5%), mean diurnal range of temperature (9.8%), annual precipitation (9.4%), and river density (9.2). The model was validated through receiver operating characteristic (ROC) plots and defined thresholds. The average test AUC in Maxent for the replicate runs was 0.933 while the value of AUC by ROC curve calculated at 0.15 threshold was 1.00. These validation tests suggested a good model fit and strong predictive power. The connectivity analysis revealed that the population in the Hindukush landscape appears to be more connected with the population in Afghanistan as compared to other populations in Pakistan. Similarly, the Pamir-Karakoram population is better connected with China and Tajikistan, while the Himalayan population was connected with the population in India. Based on our findings we propose three model landscapes to be considered under the Global Snow Leopard Ecosystem Protection Program (GSLEP) agenda as regional priority areas, to safeguard the future of the snow leopard in Pakistan and the region. These landscapes fall within mountain ranges of the Himalaya, Hindu Kush and Karakoram-Pamir, respectively. We also identified gaps in the existing protected areas network and suggest new protected areas in Chitral and Gilgit-Baltistan to protect critical habitats of snow leopard in Pakistan.


2021 ◽  
Vol 2 ◽  
Author(s):  
Dechen Lham ◽  
Gabriele Cozzi ◽  
Stefan Sommer ◽  
Phuntsho Thinley ◽  
Namgay Wangchuk ◽  
...  

The snow leopard (Panthera uncia) is one of the world's most elusive felids. In Bhutan, which is one of the 12 countries where the species still persists, reliable information on its distribution and habitat suitability is lacking, thus impeding effective conservation planning for the species. To fill this knowledge gap, we created a country-wide species distribution model using “presence-only” data from 420 snow leopard occurrences (345 from a sign survey and 77 from a camera-trapping survey) and 12 environmental covariates consisting of biophysical and anthropogenic factors. We analyzed the data in an ensemble model framework which combines the outputs from several species distribution models. To assess the adequacy of Bhutan's network of protected areas and their potential contribution toward the conservation of the species, we overlaid the output of the ensemble model on the spatial layers of protected areas and biological corridors. The ensemble model identified 7,206 km2 of Bhutan as suitable for the snow leopard: 3,647 km2 as highly suitable, 2,681 km2 as moderately suitable, and 878 km2 as marginally suitable. Forty percent of the total suitable habitat consisted of protected areas and a further 8% of biological corridors. These suitable habitats were characterized by a mean livestock density of 1.3 individuals per hectare, and a mean slope of 25°; they closely match the distribution of the snow leopard's main wild prey, the bharal (Pseudois nayaur). Our study shows that Bhutan's northern protected areas are a centre for snow leopard conservation both at the national and regional scale.


2020 ◽  
Author(s):  
Shoaib Hameed ◽  
Jaffar ud Din ◽  
Hussain Ali ◽  
Muhammad Kabir ◽  
Muhammad Younas ◽  
...  

AbstractPakistan’s total estimated snow leopard habitat is about 80,000 km2 of which about half is considered prime. However, this preliminary demarcation was not always in close agreement with the actual distribution—the discrepancy may be huge at the local and regional level. Recent technological developments like camera trapping and molecular genetics allow for collecting reliable presence records that could be used to construct realistic species distribution based on empirical data and advanced mathematical approaches like MaxEnt. Current study followed this approach to construct accurate distribution of the species in Pakistan. Moreover, movement corridors, among different landscapes, were also identified through the circuit theory. The habitat suitability map, generated from 384 presence points and 28 environmental variables, scored the snow leopard’s assumed range in Pakistan, from 0 to 0.97. A large shear of previously known range represented low-quality habitat, including areas in lower Chitral, Swat, Astore and Kashmir. Conversely, Khunjerab, Misgar, Chapursan, Qurumber, Broghil, and Central Karakoram represented high-quality habitats. Variables with higher contribution in the MaxEnt model were precipitation of driest month (34%), annual mean temperature (19.5%), mean diurnal range of temperature (9.8%), annual precipitation (9.4%) and river density (9.2). The validation texts suggest a good model fit, and strong prediction power.The connectivity analysis revealed that the population in the Hindukush landscape appears to be more connected with the population in Afghanistan as compared to other populations in Pakistan. Similarly, the Pamir-Karakoram population is better connected with China and Tajikistan, while the Himalayan population was with the population in India.Current study allows for proposing three model landscapes to be considered under GSLEP agenda as regional priority areas, to safeguard safeguard future of the species in the long run. These landsacpes fall in mountain ranges of the Himalaya, Hindu Kush and Karakoram-Pamir, respectively. We also identified gaps in existing protected areas network, and suggest new protected areas in Chitral and Gilgit-Baltistan to protect critical habitats of snow leopard in Pakistan.


2018 ◽  
Vol 10 (8) ◽  
pp. 12086
Author(s):  
Rinzin Phunjok Lama ◽  
Tashi R. Ghale ◽  
Madan K. Suwal ◽  
Rishi Ranabhat ◽  
Ganga Ram Regmi

The Snow Leopard Panthera uncia is a rare top predator of high-altitude ecosystems and insufficiently surveyed outside of protected areas in Nepal.  We conducted a rapid camera-trapping survey to assess the presence of Snow Leopard in the Limi valley of Humla District.  Three individuals were recorded in two camera locations offering the first photographic evidence of this elusive cat outside the protected area network of Nepal. In addition to Snow Leopard, the Blue Sheep Pseudois nayaur, Beech Marten Martes foina, Pika Ochotona spp. and different species of birds were also detected by camera-traps.  More extensive surveys and monitoring are needed for reliably estimating the population size of Snow Leopard in the area.  The most urgent needs are community-based conservation activities aimed at mitigating immediate threats of poaching, retaliatory killing, and rapid prey depletion to ensure the survival of this top predator in the Himalaya. 


Author(s):  
Miha Krofel ◽  
Claudio Groff ◽  
Valentina Oberosler ◽  
Claudio Augugliaro ◽  
Francesco Rovero

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
AFSHAN ANJUM BABA ◽  
SYED NASEEM UL-ZAFAR GEELANI ◽  
ISHRAT SALEEM ◽  
MOHIT HUSAIN ◽  
PERVEZ AHMAD KHAN ◽  
...  

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.


2016 ◽  
Vol 548 ◽  
pp. 263-275 ◽  
Author(s):  
RE Lindsay ◽  
R Constantine ◽  
J Robbins ◽  
DK Mattila ◽  
A Tagarino ◽  
...  

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