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.

This article provides insight into the distribution, elevational occurrence, and habitat associations of three species in the Kazakh part of the Tien Shan Mountains: the Turkestan lynx (Lynx lynx isabellinus), Asiatic wildcat (Felis lybica ornata), and Pallas’s cat (Otocolobus manul). From January 2012 until July 2025, we compiled 221 records based on camera trapping, visual observations, snow tracking, and questionnaire data, classified according to SCALP criteria. Research results revealed the Turkestan lynx to be the most widely distributed species, occurring across all the main river valleys and gorges of the Western and Northern Tien Shan and occupying various altitudinal zones and habitat types, with a predominance of coniferous forests and shrubs. The Asiatic wildcat was primarily associated with foothills, river valleys, riparian forests, and shrublands, but obtained camera-trap records indicate residence and stable population within the forest belt. Pallas’s cat was observed mainly in the Northern Tien Shan with isolated records in the Karatau Mountains, and occupied low mountains with smooth slopes, low hills, cliffs and rock outcrops. Maintaining habitat integrity and conducting long-term monitoring will be essential for assessing population dynamics and maintaining species diversity of Felidae under environmental change.

Background. The saiga antelope (Saiga tatarica) remains exposed to recurrent mass mortality, and a bank of viable somatic cells can insure its genetic diversity. Vitrification of saiga cells has not been studied. Aim. To establish fibroblast lines from neonatal saiga calves and to compare three vitrification solutions under two cooling regimens. Methods. Ear skin explants from 50 calves (25 males, 25 females) aged up to two weeks from the Betpak-Dala region were cultured in DMEM. Cells were loaded stepwise with 20% dimethyl sulfoxide (DMSO), 20% ethylene glycol (EG) or 20% DMSO + 20% EG, each with 0.5 M sucrose, and cooled in 0.25 mL straws either in liquid nitrogen (−196 °C) or in subcooled nitrogen at −205 °C (super-cooling ultra-rapid vitrification, SCURV). Viability was assessed by trypan blue exclusion (n = 50 lines per group). Results. Cell outgrowth began on days 6–10 of culture. Two-way ANOVA showed effects of both the cooling regimen (p < 0.001; η² = 0.19) and the solution (p < 0.001; η² = 0.04), without interaction. SCURV increased viability by 6.1 percentage points (95% CI 4.7–7.5), and the DMSO + EG mixture by 3.1 points relative to either single agent (p = 0.001); DMSO and EG did not differ. The highest viability, 53.9 ± 5.9%, was obtained with DMSO + EG under SCURV. Conclusions. The DMSO + EG mixture combined with ultra-rapid cooling at −205 °C was the most effective vitrification protocol. Samples of all 50 calves were added to the saiga somatic cell cryobank.

Background. The saiga antelope (Saiga tatarica) has recovered numerically in Kazakhstan, but its populations remain exposed to mass mortality events that can remove a large share of a population within weeks. Viable somatic cell banking can insure genetic diversity, yet no cryopreservation protocol had been reported for saiga cells. Aim. To establish primary fibroblast cultures from saiga ear skin and to compare post-thaw survival after passive and controlled-rate slow freezing. Methods. Ear skin biopsies were collected from 50 adult saigas of the Betpak-Dala and Ustyurt populations. Fibroblasts obtained by explant culture were frozen at passage 2 either passively in cryovials with 10% dimethyl sulfoxide (DMSO; ≈ −1 °C/min to −70 °C) or in 0.5 mL straws with 1.5 M DMSO or 1.5 M ethylene glycol (EG) after 2 h equilibration at 5 °C, using a programmable freezer. Viability was assessed by trypan blue exclusion. Results. Cell outgrowth began on days 6–10 of culture. Passive freezing reduced viability from 97.6% to 44.5% (p < 0.001), with high inter-individual variability (9–77%; CV 30%). Controlled-rate freezing yielded 52.8 ± 1.1% viable cells with DMSO and 62.1 ± 1.0% with EG versus 85.8 ± 0.8% in fresh controls (p < 0.001); EG exceeded DMSO by 9.3 percentage points and gave 27% more viable cells per straw. Both controlled-rate treatments outperformed passive freezing and showed 2.9–3.5-fold lower variance. Conclusions. Controlled-rate slow freezing with 1.5 M EG was the most effective protocol and was adopted for the first somatic cell cryobank of the saiga in Kazakhstan.

The snow leopard (Panthera uncia) is a Vulnerable felid, and cryobanking of its somatic cells is a practical way to preserve the genetic diversity of the Kazakhstan population. We compared the post-thaw viability of snow leopard skin fibroblasts after two slow-freezing protocols. Primary fibroblast lines were established from ear-skin biopsies of 16 animals and cryopreserved at passage 5. In experiment 1, cells were frozen passively in cryovials placed in a polystyrene block at −70 °C (about 1 °C/min) in fetal bovine serum with 10% dimethyl sulfoxide (DMSO). In experiment 2, cells were frozen in 0.5 mL straws in a programmable freezer with 1.5 M DMSO or 1.5 M ethylene glycol (EG). Viability was assessed by trypan blue exclusion. Passive freezing reduced viability from 98.5 ± 0.3% to 43.7 ± 12.5% (p < 0.001). Controlled-rate freezing yielded 57.9 ± 9.4% viable cells with DMSO and 62.9 ± 8.9% with EG; the difference between the two cryoprotectants was not significant (p = 0.13). Both controlled-rate variants outperformed passive freezing, by 14.2 and 19.2 percentage points (one-way ANOVA, F(2,45) = 14.7, p < 0.001; Tukey test, p ≤ 0.001). Thawed cells reattached, proliferated and reached confluence within 7 days. Controlled-rate freezing in straws is recommended for the snow leopard somatic cell bank, and DMSO and EG can be used interchangeably. The resulting fibroblast collection forms the first somatic cell cryobank of snow leopards in Kazakhstan.