Habitat suitability models are useful to understand species distribution and to guide management and conservation strategies. The grey wolf (Canis lupus) has been extirpated from most of its historic range in Pakistan primarily due to its impact on livestock and livelihoods. We used non-invasive survey data from camera traps and genetic sampling to develop a habitat suitability model for C. lupus in northern Pakistan and to explore the extent of connectivity among populations. We detected suitable habitat of grey wolf using a maximum entropy approach (Maxent ver. 3.4.0) and identified suitable movement corridors using the Circuitscape 4.0 tool. Our model showed high levels of predictive performances, as seen from the values of area under curve (0.971±0.002) and true skill statistics (0.886±0.021). The main predictors for habitat suitability for C. lupus were distances to road, mean temperature of the wettest quarter and distance to river. The model predicted ca. 23,129 km2 of suitable areas for wolf in Pakistan, with much of suitable habitat in remote and inaccessible areas that appeared to be well connected through vulnerable movement corridors. These movement corridors suggest that potentially the wolf range can expand in Pakistan’s Northern Areas. However, managing protected areas with stringent restrictions is challenging in northern Pakistan, in part due to heavy dependence of people on natural resources. The habitat suitability map provided by this study can inform future management strategies by helping authorities to identify key conservation areas.

Summary1. 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-to-event analysis are directly applicable to camera trapping, yet this statistical field has thus far been ignored as a way to analyse photographic capture data. To illustrate the use of time-toevent statistics and to better understand how photographic evidence accumulates, we explored patterns in two related measures of detectability: detection probability and time to detection. We analysed 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 of 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 selection of analytical models. Weighted time-to-event analysis can complement occupancy analysis and other hierarchical methods by providing additional tools for exploring camera trap data and testing hypotheses regarding the temporal aspect of photographic evidence accumulation.

ABSTRACT. Pastoralism and predation are two major concomitantly known facts and matters of concern for conservation biologists worldwide. Pastoralist-predator conflict constitutes a major social-ecological concern in the Pamir mountain range encompassing Afghanistan, Pakistan, and Tajikistan, and affects community attitudes and tolerance toward carnivores. Very few studies have been conducted to understand the dynamics of livestock predation by large carnivores like snow leopards (Panthera uncia) and wolves (Canis lupus), owing to the region's remoteness and inaccessibility. This study attempts to assess the intensity of livestock predation (and resulting perceptions) by snow leopards and wolves across the Afghani, Pakistani, and Tajik Pamir range during the period January 2008-June 2012. The study found that livestock mortality due to disease is the most serious threat to livestock (an average 3.5 animal heads per household per year) and ultimately to the rural economy (an average of US$352 per household per year) as compared to predation (1.78 animal heads per household per year, US$191) in the three study sites. Overall, 1419 (315 per year) heads of livestock were reportedly killed by snow leopards (47%) and wolves (53%) in the study sites. People with comparatively smaller landholdings and limited earning options, other than livestock rearing, expressed negative attitudes toward both wolves and snow leopards and vice versa. Education was found to be an effective solution to dilute people's hatred for predators. Low public tolerance of the wolf and snow leopard in general explained the magnitude of the threat facing predators in the Pamirs. This will likely continue unless tangible and informed conservation measures like disease control and predation compensation programs are taken among others.

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Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan’s mountain ungulates.