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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Competition may lead to changes in a species’ environmental niche in areas of sympatry and shifts in the niche of weaker competitors to occupy areas where stronger ones are rarer. Although mainland Mediterranean (Rhinolophus euryale) and Mehely’s (R. mehelyi) horseshoe bats mitigate competition by habitat partitioning, this may not be true on resource-limited systems such as islands. We hypothesize that Sardinian R. euryale (SAR) have a distinct ecological niche suited to persist in the south of Sardinia where R. mehelyi is rarer. Assuming that SAR originated from other Italian populations (PES) – mostly allopatric with R. mehelyi – once on Sardinia the former may have undergone niche displacement driven by R. mehelyi. Alternatively, its niche could have been inherited from a Maghrebian source population. We: a) generated Maxent Species Distribution Models (SDM) for Sardinian populations; b) calibrated a model with PES occurrences and projected it to Sardinia to see whether PES niche would increase R. euryale’s sympatry with R. mehelyi; and c) tested for niche similarity between R. mehelyi and PES, PES and SAR, and R. mehelyi and SAR. Finally we predicted R. euryale’s range in Northern Africa both in the present and during the Last Glacial Maximum (LGM) by calibrating SDMs respectively with SAR and PES occurrences and projecting them to the Maghreb. R. mehelyi and PES showed niche similarity potentially leading to competition. According to PES’ niche, R. euryale would show a larger sympatry with R. mehelyi on Sardinia than according to SAR niche. Such niches have null similarity. The current and LGM Maghrebian ranges of R. euryale were predicted to be wide according to SAR’s niche, negligible according to PES’ niche. SAR’s niche allows R. euryale to persist where R. mehelyi is rarer and competition probably mild. Possible explanations may be competition-driven niche displacement or Maghrebian origin. [ABSTRACT FROM AUTHOR]