Land is a limited yet vital resource, which is fundamental for food security and national stability. Ensuring its effective use requires modern tools to support informed decision making. This study evaluates land suitability for irrigation in the Kyzylorda region of Kazakhstan, with the objective of identifying areas appropriate for crop expansion. A multidimensional approach was employed, integrating soil properties, topography, proximity to water sources, and existing land use patterns, with suitability classes defined according to the Food and Agriculture Organization’s framework. The Analytic Hierarchy Process, based on pair-wise comparisons and Saaty’s scale, was used to assign weights to each factor. The findings reveal that 30% of highly suitable land and 80% of suitable land remain uncultivated. Conversely, 10% of the current cropland is located in marginally suitable area—likely a result of historical land use decisions or the limited availability of optimal land. This research responds to the specific challenges of arid climates and water scarcity by providing a decision-support tool that promotes sustainable land use, strengthens food security, and encourages responsible land management.

Scientific labour organization is becoming relevant in the context of the rapidly changing requirements of the modern market, especially in the growing human interaction with robotic systems and artificial intelligence. The purpose of this study is to conduct a bibliometric and content analysis of scientific labour organization in agriculture, with a focus on the integration of remote sensing technologies and precision farming. The methodological basis of the work included bibliometric and content analysis of scientific articles selected from the Web of Science database for the period 1992-2025, using clusterization (CiteSpace 6.3.R1). The results showed a steady increase in publication activity: since 2017, the number of papers has increased to four per year, and the peak of citations occurred in 2022. Cluster analysis revealed two dominant areas: “Industry 4.0” (77 articles, the average publication year is 2016, S = 0.99) and “Precision Agriculture” (34 articles, the average year is 2014, S = 1.0). These clusters have shown that sustainable land use technologies and precision farming innovations are changing the organization of labor and management of agricultural enterprises. The results demonstrate the growing interest in the problems of labor organization in the context of the digitalization of the agricultural sector, the strengthening of interdisciplinary ties and the expansion of the range of applied research. In the future, it is advisable to expand databases for analysis, include more intersectoral research and develop organizational models that take into account the social and ethical aspects of the introduction of new technologies.

This study aims to identify challenges in the training of scientific personnel in the field of social sciences and humanities at the doctoral level in Kazakhstan. It proceeds from the assumption that successful completion of a Ph.D. program is conditioned by internal and external factors that influence the educational process and may lead to challenges in Ph.D. thesis defense. The study employs an explanatory-sequential approach within a mixed-methods design, incorporating economic-statistical, regression, and content analysis. Data were gathered through questionnaires from 61 current students and graduates of Ph.D. programs in the social sciences and humanities. Findings indicate that having a job made it more challenging for respondents to study and complete their Ph.D. programs, as employment requires time and effort; however, the additional monthly income besides scholarship helped reduce financial stress, thereby supporting their academic progress. Women found studying easier than men, while married respondents experienced fewer challenges than single ones. Although 36.1% of respondents expressed high satisfaction with Ph.D. training quality, the majority reported challenges, with 65.65% noting issues in the educational process, 52.5% identifying problems in scientific supervision, 33% raising concerns about teacher qualifications, and 25% highlighting infrastructure needs. Key factors influencing Ph.D. completion rates included an unstable study environment, characterized by frequent changes in regulations, and students’ difficulties in meeting government-imposed requirements, especially publication in a Scopus database journal. The study’s practical value is developing measures to enhance Ph.D. thesis defense rates by improving admission requirements, restricting external employment, increasing supervisor accountability, and adjusting publication standards. Acknowledgments This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP19680246 “Building up highly intelligent human resources in the conditions of digitalization of the economy of Kazakhstan: problems and prospects”, 2023–2025) and supported the Oxus Society for Central Asian Affairs (program “Advancing data-driven solutions by strengthening partnerships between the scientific, academic and civil sectors in Central Asia”, 2023–2024).

Understanding the interactions among mountain snow resources, river discharge, and irrigated agriculture is essential for sustainable water management in transboundary river basins of Central Asia. This study evaluated the relationships among high-elevation snow conditions, hydroclimatic factors, summer river discharge, and agricultural vegetation dynamics in the transboundary Chu River Basin during 2001–2025 using MODIS snow-cover, snow-persistence, and NDVI products together with meteorological and hydrological observations. The results showed that snow cover was widespread during winter but declined substantially during spring, while the Mann–Kendall analysis indicated that no statistically significant trend predominated across most of the high-elevation snow zone, although significant decreases in snow persistence occurred across 12.83% of the analyzed area. For summer cropland NDVI, 61.15% of the analyzed area showed no significant trend, while significant decreases and increases occurred across 26.24% and 12.62%, respectively. Spring temperature exhibited a significant negative correlation with snow persistence (r = −0.64, p < 0.001), indicating the sensitivity of mountain snow resources to warming conditions. Summer river discharge was strongly correlated with summer precipitation (r = 0.77, p < 0.0001), vegetated cropland area (r = 0.76, p < 0.0001), and mean summer NDVI (r = 0.69, p < 0.001). In addition, snow persistence showed a significant positive relationship with summer river discharge (r = 0.63, p < 0.001), vegetated cropland area (r = 0.52, p = 0.008), and mean summer NDVI (r = 0.42, p = 0.036), suggesting a linkage between high-elevation snow conditions, seasonal water availability, and downstream agricultural vegetation. Canonical correlation analysis further revealed a strong multivariate association between hydroclimatic and hydroagricultural variables (Rc = 0.900, Rc² = 0.810). Overall, the findings indicate significant statistical linkages among climate conditions, snow resources, river discharge, and irrigated agriculture, providing a scientific basis for water-resource management and climate-change adaptation in transboundary mountain-fed basins.

Shared mental models are a compelling concept that highlights the importance of shared understanding among team members to achieve improved team performance. This study aimed to extract individual mental models from social media posts and explore differences in the shared mental models of successful and unsuccessful teams on example of the FIBA 3x3 Basketball World Cup 2023. Mental models were derived through semantic network analysis employing the textual analytical software Automap. The sample consisted of 368 posts from 39 team members, collected from platforms such as Facebook, X and Instagram. Significant disparities between successful and unsuccessful teams were uncovered, with the former displaying a greater number of concepts and statements, having larger shared cognitive maps. Additionally, the analysis offered insights into gender specific team sharedness, revealing that even though male team members were less verbal, they exhibited a higher degree of sharedness compared to their female counterparts. This study demonstrates the potential of social media data for constructing shared mental models and offers two key contributions: 1) It provides empirical evidence to the literature, and 2) it highlights the viability of social media as a tool for evaluating shared mental models, opening new avenues for research in the field.

Sustainable expansion of irrigated agriculture requires the identification of areas with favorable biophysical conditions while also considering water-resource and infrastructure constraints. This study assessed the biophysical land suitability for potential irrigation development within the Ertis Water Management Basin (WMB), Kazakhstan, using an integrated remote sensing, geographic information system (GIS), and Analytic Hierarchy Process (AHP) framework. Four criteria—slope, normalized difference vegetation index (NDVI), land use/land cover (LULC), and soil texture—were standardized into five suitability classes and integrated using an AHP-based weighted overlay. The derived weights were 0.51 for slope, 0.26 for NDVI, 0.14 for LULC, and 0.09 for soil texture, with a consistency ratio of approximately 1%. The resulting assessment classified approximately 10% of the basin as highly suitable (S1), 43% as suitable (S2), 18% as moderately suitable (S3), 2% as marginally suitable (S4), and 27% as not suitable (NS), indicating that approximately 53% of the basin falls within the two highest suitability classes. Regional analysis showed that substantial shares of suitable land are concentrated in Pavlodar and Abay Regions, while suitable areas were identified across a wide range of distances from the river network. These findings indicate considerable biophysical potential for irrigation development across the Ertis WMB, with suitable areas occurring both near and farther from the river network. The resulting suitability map provides a spatial basis for identifying areas where more detailed assessments of water availability, irrigation infrastructure, and development feasibility can subsequently be undertaken.