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Hameed, S. |
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Title |
Population status of the snow leopard and its conflict with local people in laspur valley, Chitral, Pakistan |
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2010 |
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1-77 |
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The present study was designed to determine the status of snow leopard in Laspur valley, Chitral (Khyber Pakhtunkhawa) by using multiple census methods. |
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Master's thesis |
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Pakistan |
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English |
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M.Phil Thesis, Pir Mehr Ali Shah (PMAS) – Arid Agriculture University |
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yes |
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SLN @ rana @ |
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1327 |
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Ahmad, S., Ali, H., Asif, M., Khan, T, Din, N., Rehman, E. U., Hameed, S., Din, J. U., Nawaz, M. A. |
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Title |
Spatial density pattern of Himalayan Ibex (Capra sibirica) in Pakistan |
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Journal Article |
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Year |
2022 |
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Global Ecology & Conservation |
Abbreviated Journal |
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39 |
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e02288 |
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1-12 |
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Himalayan ibex, Population, Hindu Kush, Himalaya, Karakoram, Pakistan |
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Mountain ungulates perform a key role in maintaining the balance of ecosystems as they are the primary consumers of vegetation and prey for large predators. The mountain ranges of northern Pakistan are home to six species of mountain ungulates, and the Himalayan ibex (Capra sibirica), hereafter ibex, is the most abundant among them. This study was conducted in three administrative regions of northern Pakistan, viz. Gilgit-Baltistan (GB), Azad Jammu and Kashmir (AJK), and Khyber Pakhtunkhwa (KP), to generate a range-wide density pattern map of ibex. A double-observer survey was conducted in 25 study sites during 2018–2021 across the ibex distribution range, covering an area of about 35,307 km2, by walking transects totaling 1647 km. Within the ibex range where the survey was not conducted due to financial and logistical constraints, we obtained species population information from local wildlife departments’ most recent annual survey data. The aim was to generate a density map for the entire ibex range. Using the BBRe-capture package in program R, we estimated an ibex population of 7639 (95 % CI) with a mean density of 0.21/km2 in the surveyed area. Combining with the secondary data from un-surveyed areas, the total population estimate for the country came to 10,242 ibex. The largest population densities were observed in four valleys (Shimshal, Gulkin-Hussaini, Khyber, and Khunjerab) of the Karakoram-Pamir range, followed by the Hindu Kush range (Chitral Wildlife Division [WD]). The central and eastern parts of the Karakoram range had moderate to low densities, while the Himalayan range (e.g., Astore Valley) supported a small population. The mean herd size was 15 individuals (range: 5–41), and the average detection probability of observers A and B was 0.69 and 0.48, respectively. The average male and young ratios per 100 females were estimated to be 75 and 81, respectively. The range-wide density map developed during the study provided an evidence for the impact of trophy hunting programs and an objective tool for range-wide conservation planning of the species. |
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SLN @ rakhee @ |
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1699 |
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Bischof, R.,Hameed, S.,Ali, H.,Kabir, M.,Younas, M.,Shah, K. A.,Din, J. U.,Nawaz, M. A. |
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Using time-to-event analysis to complement hierarchical methods when assessing determinants of photographic detectability during camera trapping |
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2013 |
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Methods in Ecology and Evolution |
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Cox proportional hazards model, cumulative incidence, Martes foina, Panthera Uncia, survival anaalysis, Vulpes Vulpes, weighted observations |
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1. Camera trapping, paired with analytical methods for estimating occupancy, abundance and other ecological parameters, can yield information with direct consequences for wildlife management and conservation. Although ecological information is the primary target of most camera trap studies, detectability influences every aspect from design to interpretation.
2. Concepts and methods of time-toevent analysis are directly applicable to camera trapping, yet this statistical field has thus far been ignored as a way to analyze photographic capture data. to illustrate the use to time-to-event statistics and to better understand how photographic evidence accumulates, we explored patterns in tow related measure of detectability: Detection probability and time to detection. We analyzed camera trap data for three sympatric carnivores ( snow Leopard, red fox and stone marten) in the mountains of northern Pakistan and tested predictions about patterns in detectability across species, sites and time.
3. We found species-specific differences in the magnitude of detectability and the factors influencing it, reinforcing the need to consider determinants of detectability in study design and to account for them during analysis. Photographic detectability of snow leopard was noticeably lower than that of red fox, but comparable to detectability of stone marten. Site-specific attributes such as the presence of carnivore sign ( snow Leopard), terrain ( snow leopard and red fox) and application for lures ( red fox) influenced detectability. For the most part, detection probability was constant over time.
4. Species- specific differences in factors determining detectability make camera trap studies targeting multiple species particularly vulnerable to misinterpretation if the hierarchical origin of the data is ignored. Investigators should consider not only the magnitude of detectability, but also the shape of the curve describing the cumulative process of photographic detection, as this has consequences for both determining survey effort and the election of analytical models. Weighted time-to -event analysis can complement occupancy analysis and other hierarchal methods by providing additional tools for exploring camera trap data and testing hypotheses regarding the temporal aspect of photographic evidence accumulation. |
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1405 |
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Din, J. U., Bari, F., Ali, H., Rehman, E. U., Adli, D. S. H., Abdullah, N. A., Norma-Rashid, Y., Kabir, M., Hameed, S., Nawaz, D. A., Nawaz, M. A. |
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Title |
Drivers of snow leopard poaching and trade in Pakistan and implications for management |
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2022 |
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Nature Conservation |
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46 |
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49-62 |
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conflict, illegal trade, northern Pakistan, pelt, poaching; retaliatory killing |
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The snow leopard is one of the highly valued species from high-altitude mountain ecosystems of Central and Southeast Asia, including Pakistan. This keystone species is facing a myriad of conventional and emerging threats, including poaching and trade, that are poorly documented in Pakistan. To understand the dynamics and drivers of the poaching and trading of snow leopards in Pakistan, we investigated the issue in depth through a multifaceted survey in the snow leopard range of the country. We recorded 101 snow leopard poaching incidences from 11 districts during 2005–2017. The reported poaching incidences varied spatially (‒x = 9 ± 2.6 [95% Cl: 3–15]) and temporally (‒x = 7.8 ± 1.09) and accounted for 2–4% annual population loss (n = 200–420) in a period of 13 years. Poaching and trade together constituted 89% of the total incidence reported and animals were mostly shot (66%), poisoned (12%), snared (12%) and captured (4%), respectively. Only a fraction (3%) of the incidences were reported to the relevant law enforcement agencies. Trade routes included large cities and neighbouring countries, even the Middle East and Europe. The average base and end prices for each item were 245 ± 36 USD and 1,736 ± 520 USD, respectively, while maximum monetary fines set as per the law were 275 USD. Our results establish the need for developing multi-stakeholder coordination mechanisms at regional, national and international levels and information sharing to curb this menace. Improving the existing laws and surveillance system, while taking the local communities onboard, will further help to this end. |
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SLN @ rakhee @ |
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1672 |
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Hameed, S., Din, J. U., Ali, H., Kabir, M., Younas, M., Rehman,
E. U., Bari, F., Hao, W., Bischof, R., Nawaz, M. A. |
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Identifying priority landscapes for conservation of snow
leopards in Pakistan |
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Journal Article |
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2020 |
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Plos One |
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1-20 |
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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
Afghani- stan 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. |
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1617 |
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