Snow leopards ( Panthera uncia ) serve as an umbrella species whose conservation benefits their high-elevation Asian habitat. Their numbers are believed to be in decline due to numerous anthropogenic threats; however, their conservation is hindered by numerous knowledge gaps. In particular, the dearth of genetic data, unique among all big cat species, hinders a full understanding of their population structure, historical population size, and current levels of genetic diversity. Here, we use whole-genome sequencing data for 41 snow leopards (37 newly sequenced) to offer insights into these unresolved aspects of snow leopard biology. Among our samples, we find evidence of a primary genetic divide between the northern and southern part of the range around the Dzungarian Basin—as previously identified using landscape models and fecal microsatellite markers—and a secondary divide south of Kyrgyzstan around the Taklamakan Desert. Most noteworthy, we find that snow leopards have the lowest genetic diversity of any big cat species, likely due to a persistently small population size throughout their evolutionary history rather than recent inbreeding. We also find that snow leopards have significantly less highly deleterious homozygous load compared to numerous Panthera species, suggesting effective purging during their evolutionary history at small population sizes. Without a large population size or ample standing genetic variation to help buffer them from any forthcoming anthropogenic challenges, snow leopard persistence may be more tenuous than currently appreciated.

The Turkestan lynx (Lynx lynx isabellina Blyth, 1847) is a rare and understudied subspecies of the Eurasian lynx occupying the mountains of Central and South Asia. This elusive felid’s northwestern range includes the Tien Shan and Zhetisu Alatau mountains in the border region of Kazakhstan, China, Kyrgyzstan, and Uzbekistan. As the first step to conserve this vulnerable carnivore, we have conducted the first full-scale research from 2013 until 2022 on its distribution in this region. Using 132 environmental predictors of 359 lynx sightings, we have created species habitat distribution models across the lynx’s northwestern range using machine learning approaches (Maximum Entropy—MaxEnt). Additionally, we created species distribution forecasts based on seven bio-climatic environmental predictors with each three different future global climate model scenarios. To validate these forecasts, we have calculated the changes in the lynx distribution range for the year 2100, making the first species distribution forecast for the Turkestan lynx in the area. Additionally, it provides insight into the possible effects of global climate change on this lynx population. Based on these distribution models, the lynx population in the Northern and Western Tien Shan and Zhetisu Alatau plays a significant role in maintaining the stability of the whole subspecies in its northwestern and global range, while the distribution forecast shows that most lynx distribution ranges will reduce in all future climate scenarios, and we might face the Turkestan lynx’s significant distribution range decline under the ongoing and advancing climate change conditions. For a future (year 2100) warming scenario of 3 deg. C (GCM IPSL), we observe a decrease of 35% in Kazakhstan, 40% in Kyrgyzstan, and 30% in China as the three countries with the highest current predicted distribution range. For a milder temperature increase of 1.5–2 deg. C. (GCM MRI), we observe an increase of 17% Kazakhstan, decrease of 10% in Kyrgyzstan, and 57% in China. For a cooling scenario of approx. 1–1.5 deg. C (GCM MIROC), we observe a decrease of 14% Kazakhstan, increase of 11% in Kyrgyzstan, and a decrease of 13% in China. These modeled declines indicate the necessity to create new and expand the existing protected areas and establish ecological corridors between the countries in Central and South Asia.

The saiga antelope (Saiga tatarica), a keystone migratory species of the Central Asian steppes and deserts, is increasingly threatened by habitat fragmentation due to the rapidly expanding transport infrastructure in Kazakhstan, which hosts approximately 95% of the species’ global population. This study provides a spatial assessment of railway and road infrastructure across the contemporary ranges of the Betpaqdala, Ustyurt, and Ural saiga populations. Using the literature and our field data from the 1980s to the present day, combined with geographic information system (GIS)-based analysis of 80,427 km of roads and 4021 km of railways, we have quantified infrastructure densities and identified critical barriers to saiga migration using kernel density and minimum convex polygons (MCP) estimations. The results reveal a negative connection between infrastructure density and occurrences of saiga herds, particularly in the Ustyurt population, where a high railway density coincides with severely reduced migratory activity and a reduction in this population’s winter range by 79.84% since 2015. Major railways such as Sekseuildi–Zhezqazgan, Zhezqazgan–Zharyk, and Shalqar–Beineu intersect essential migratory pathways and have contributed to significant range contraction, subpopulation isolation, and northward shifts in seasonal habitats. In contrast, the Ural population (subject to minimal railway infrastructure interference) has shown robust demographic recovery. While roads are more widespread, their impact is less severe due to greater permeability. However, upcoming projects such as the China–Europe transit corridor and the “Center–West” regional development corridor could amplify future threats. We recommend immediately implementing wildlife-friendly infrastructure, including overpasses and ecological corridors, to preserve the connectivity of saiga ranges and support the long-term conservation of this ungulate species.

Saiga antelope and Turkmenian kulans are considered critically endangered and near threatened, respectively, by the International Union for Conservation of Nature (IUCN). Due to these species’ fragile status, it is important to understand the pathogens infecting their remaining populations. A total of 496 faecal samples were collected from Ural saiga antelope in western Kazakhstan during June, September, and November of 2021 and May and August of 2022 and 149 faecal samples were collected from kulans in the Altyn-Emel nature reserve in south-eastern Kazakhstan from June to August of 2021. Additionally, endo- and ecto-parasites were collected from 17 saiga that were found deceased due to natural causes. Nine helminths (3 cestodes, 6 nematodes) and two protozoans were found in Ural saiga antelope. In addition to intestinal parasites, one case of cystic echinococcosis due to Echinococcus granulosus infection and one case of cerebral coenurosis due to Taenia multiceps infection was identified on necropsy. None of the collected ticks (all Hyalomma scupense) were found positive for Theileria annulate (enolase gene) or Babesia spp. (18 S ribosomal RNA gene) via PCR. Three intestinal parasites (Parascaris equorum, Strongylus sp., and Oxyuris equi) were found in kulans. All identified parasites, in both saiga and kulans, are also found in domesticated livestock, suggesting a need for better understanding of how parasites are maintained within and between regional wild and domestic ungulate populations.