One of the most extensive natural plague centers, or foci, is located in Central Asia, in particular, the Zhambyl region in Southern Kazakhstan. Here, we conducted plague surveillance from 2000 to 2020 in the Zhambyl region in Kazakhstan and confirmed 3,072 cases of infected wild animals. We used Species Distribution Modeling by employing MaxEnt, and identified that the natural plague foci are primarily located in the Moiynqum, Betpaqdala, and Tauqum Deserts. The Zhambyl region's central part, including the Moiynqum and Sarysu districts, has a high potential risk of plague outbreak for the rural towns and villages. Since the phenomenon of climate change has been identified as a determinant that affects the rodent populations, thereby elevating the likelihood of an outbreak of plague, we investigated the potential dissemination routes of the disease under the changing climate conditions, thus creating Species Distribution Forecasts for the rodent species in southern part of Kazakhstan for the year 2100. By 2100, in case of increasing temperatures, the range of host species is likely to expand, leading to a higher risk of plague outbreaks. The highest risk of disease transmission can be expected at the outer limits of the modeled total distribution range, where infection rates are high, but antibody presence is low, making many species susceptible to the pathogen. To mitigate the risk of a potential plague outbreak, it is necessary to implement appropriate sanitary‐epidemiological measures and climate mitigation policies.

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.

A forward-looking review of innovative bridge materials enabling wildlife crossings, integrating engineering resilience with saiga migration conservation needs.

Water resources in the semi-arid agricultural landscapes of Northern Kazakhstan are under intense stress from climatic, ecological, and socioeconomic issues, which increase the human–wildlife conflict. In this study, the Extended Livelihood Vulnerability Index (ELVI) was developed to assess farm holdings’ water-related vulnerability and climate change adaptive capacity for saiga antelope (Saiga tatarica) recovery. The framework integrates 13 components and 63 indicators covering climate and natural hazards, human–wildlife coexistence, water resources issues, natural and land resources, agriculture, infrastructure, socioeconomic conditions, and livelihood strategies. The assessment combines hydroclimatic data from 1961–2024, field surveys, questionnaires, official statistics, spatial information, and saiga migration data from Naurzum and Auliekol Districts of Kostanay Region. Overall ELVI values were 0.481 in Naurzum (ND) and 0.416 in Auliekol (AD). Natural Resources availability indexes showed the highest component score (0.972 in ND and 0.957 in AD), followed by Climate Change and Natural Disasters (0.719 in ND and AD), and Human–Wildlife Coexistence (0.695 in ND and 0.603 in AD). Climate analysis revealed significant warming (0.28 °C per decade) without a significant long-term precipitation trend. The project findings demonstrate that water resources availability stress is a cross-cutting dimension of rural vulnerability, while saiga recovery creates an additional pathway of socio-ecological complexities through competition for water, pasture, and agricultural lands.

This article is dedicated to studying the complex ecology of the Volga-Ural saiga population in Kazakhstan, providing comprehensive information about its current state and dynamics. Extensive field studies were conducted in key locations such as calving sites, summer pastures, and wintering grounds to understand habitat conditions, ecological characteristics, and relationships with other animal species. The increasing population of Volga-Ural saigas has led to conflicts of interest with agricultural producers, which have been examined alongside proposed measures for resolution. Currently, this population is the world`s largest, uniquely positioned in the border area between Kazakhstan and the Russian Federation. In recent years, saigas have been observed crossing the borders of these countries in the west and northwest of the West Kazakhstan region during spring, seeking calving sites. Fluctuation in saiga numbers from perilous lows to record highs within several years, raise concerns about sustainable long-term development. The author`s research seeks to address these questions and aligns with other researchers advocating for population regulation through controlled reduction necessary to manage the rapidly increasing saiga population effectively. Furthermore, this article serves as a valuable resource for conservation stakeholders, including those interested in saiga protection and regional agriculture development. It significantly contributes to understanding the intricate ecosystem dynamics along the right bank of the Ural River, emphasizing the importance of sustainable natural resource management for saiga conservation and overall biodiversity in the region. Key words: saiga, population, epizootic, migration, habitat, predators