Kanat Kulymbet

The rare Central Asian plant Acanthophyllum gypsophiloides occurs in environmentally contrasting mountain and foothill localities of the Syrdarya Karatau. We evaluated whether three populations—Sayasu, Kuyik, and Birlik—are associated with contrasting profile-level edaphic conditions within a shared regional climatic background, and whether these locality-level contrasts are accompanied by differences in population demographic configuration and local vegetation greenness. The three sampled soil profiles differed markedly in their physicochemical characteristics. Sayasu and Kuyik were dominated by coarse-textured material with low fine-fraction contents, whereas the Birlik profile contained a substantially greater < 0.01 mm fraction but showed the lowest humus and total macronutrient concentrations, the highest pH (8.55–8.69), and markedly greater carbonate content (CO₂, 4.91–7.04%). Both WorldClim and CHELSA indicated long-term warming during 1980–2019, although the estimated rates differed between products, whereas precipitation patterns were more dataset-dependent. Population density and ontogenetic structure also differed among the three localities. Sentinel-2 NDVI values extracted at the population locations were 46.3%, 59.5%, and 61.0% lower in 2025 than the corresponding 2016 values at Sayasu, Kuyik, and Birlik, respectively; these observations represent pixel-scale vegetation greenness rather than species-specific population performance. Overall, the three localities were differentiated primarily by contrasting sampled soil-profile conditions within a common regional warming context, while demographic structure and local vegetation greenness provided complementary ecological evidence. These co-occurring patterns identify locality-specific environmental contrasts relevant to conservation monitoring but do not establish causal relationships among soil conditions, climate, vegetation greenness, and population dynamics.

Long-term soil organic carbon (SOC) monitoring provides a rare opportunity to test the performance of process-based models against real data. We evaluated RothC using 20 georeferenced soil profiles sampled in 2004 and 2024 in the semi-arid steppe of Central Kazakhstan. We used the 2004 SOC stocks for equilibrium initialization, whereas independently measured 2024 stocks were used for endpoint evaluation. A baseline-conditioned, endpoint-uncalibrated forward simulation (S1) was driven by profile-specific climate, NPP-scaled plant-C inputs, vegetation cover, and reconstructed management; a constrained inverse analysis (S2) estimated the non-negative effective C-input multiplier required to reproduce the observed endpoint, and a zero-input simulation (S3) defined the lower feasibility boundary. S1 preserved the broad between-profile variation in absolute 2024 SOC stocks (R² = 0.692), but agreement for the observed 2004–2024 SOC change was negligible (R² < 0.001; Lin’s CCC = 0.002). The direction of SOC change was reproduced at 9 of the 20 profiles, with an RMSE of 12.49 Mg C ha⁻¹ and a mean bias of −4.41 Mg C ha⁻¹. We obtained physically admissible inverse solutions for 17 profiles, with M_required ranging from 0.42 to 4.62 (mean = 2.04; median = 1.96). Profiles 295, 299, and 313 remained below the zero-input boundary under all management-timing scenarios. Together, these results show that adjusting plant-C input can reconcile modeled and observed SOC at most profiles. However, no non-negative adjustment of plant-C input could reproduce some observed endpoints. These cases indicate that other processes or sources of uncertainty should be considered.

Wild plant populations in mountain ecosystems often depend on specific combinations of soil, vegetation and microsite conditions. Alcea nudiflora (Lindl.) Boiss. is a poorly studied Malvaceae species in Central Asia, and its population structure across different soil and vegetation conditions in the Trans-Ili Alatau remains insufficiently documented. We assessed three natural populations of A. nudiflora along an elevational gradient in the Trans-Ili Alatau, Kazakhstan: P1 at 900 m a.s.l., P2 at 1438 m a.s.l. and P3 at 1620 m a.s.l. Floristic composition, vegetation structure, ontogenetic stages and soil physicochemical properties were analysed using field surveys, 10 × 10 m plots, soil descriptions, laboratory analyses and exploratory ordination. P1 occurred in relatively open meadow–shrub vegetation and showed the strongest coenotic expression of A. nudiflora, with 62 individuals recorded within the 100 m² vegetation plot and a broad representation of major ontogenetic stages. In P2, A. nudiflora remained a regular component of shrub–meadow and forest-edge vegetation, whereas in P3, the species occurred sparsely and was restricted to meadow openings, forest-edge gaps, and local microsites. Surface soil properties varied among habitats. In the upper horizon, P1 had 3.67% humus, 95.2 mg kg⁻¹ readily hydrolysable N, 36.0 mg kg⁻¹ available P₂O₅, 610 mg kg⁻¹ available K₂O, pH 8.41 and 4.28% CO₂; P2 had 3.72% humus, 39.2 mg kg⁻¹ readily hydrolysable N, 44.8 mg kg⁻¹ available P₂O₅, 450 mg kg⁻¹ available K₂O, pH 8.23 and 0.54% CO₂. PCA explained 37.1%, 33.8% and 9.4% of variance on PC1–PC3, summarizing gradients of nutrients, texture, carbonates and alkalinity. The results indicate that population status is associated with surface soil conditions, vegetation structure and microsite availability rather than elevation alone.

Accurate assessment of long-term soil organic carbon (SOC) change requires repeated field measurements and explicit treatment of temporal differences in soil mass. We quantified the net 2004–2024 SOC stock difference at 20 permanent monitoring sites in the semi-arid chestnut-soil zone of Central Kazakhstan using fixed-depth (FD) and equivalent soil mass (ESM) calculations, together with Landsat NDVI and hydroclimatic summaries. At 0–50 cm, FD SOC stock increased from 69.70 ± 17.43 to 79.39 ± 25.00 Mg C ha⁻¹, giving a mean paired difference of +9.69 Mg C ha⁻¹ (95% CI: 2.78 to 16.60; p = 0.008). After ESM adjustment to the site-specific 2004 reference soil mass, the 2024 mean was 75.43 ± 25.24 Mg C ha⁻¹ and the paired difference was +5.73 Mg C ha⁻¹ (95% CI: −0.78 to 12.25; p = 0.081). None of the five depth-specific FD comparisons remained significant after Holm adjustment. Positive annual-composite NDVI slopes occupied approximately 94.7% of the mapped area, but the site-level association between ΔNDVI and ESM-corrected ΔSOC was weak and non-significant (Pearson r = 0.259, R² = 0.067, p = 0.270; Spearman ρ = 0.241, p = 0.307). Mean aridity index declined from 0.345 in 2004–2008 to 0.308 in 2020–2024 and was interpreted as hydroclimatic context rather than a demonstrated driver of SOC change. Management–soil combinations were examined only as an exploratory site-level comparison because most combinations were unreplicated. These results show that ESM correction materially affects inference and that a two-date resampling design supports interpretation of net endpoint differences rather than continuous SOC change.

Solonetz and Solonetzic rangelands are widespread in arid regions of Central Kazakhstan, where pasture degradation is often difficult to assess because surface vegetation patterns do not always reflect subsurface soil constraints. This study aimed to evaluate degradation patterns in Solonetz pasture ecosystems of the Ulytau region by integrating field soil-profile descriptions, laboratory analyses, vegetation observations, forage productivity data and Sentinel-2A-derived MSAVI. Ten monitoring soil profiles were examined for particle-size distribution, soluble salts, ionic composition, exchangeable cations, available N, P and K, vegetation cover and forage yield. USDA textural classification, salt-distribution analysis, Pearson correlation, PCA, RDA and MSAVI-based mapping were used to link soil-profile properties with vegetation and spectral response. The first two PCA axes explained 65.5% of the total variance, while selected soil profile constrains accounted for 58% of the variation in vegetation cover, forage yield and MSAVI in the RDA analyses. The results showed strong profile heterogeneity, with clay enrichment, subsurface salt accumulation, alkalinity and Na- or Mg-related exchange–complex imbalance associated with several degradation pathways. Surface horizons were often weakly saline, whereas deeper layers contained stronger chemical and physical limitations. MSAVI values were low across the monitoring sites and reflected vegetation–soil surface conditions rather than salinity or sodicity directly. MSAVI ranged from 0.0888 to 0.2148, with a mean value of 0.1248. Combining soil-profile diagnostics with Sentinel-2A MSAVI improved the reliability of interpreting spatial degradation patterns and provides a practical framework for monitoring spatially heterogeneous Solonetz rangelands, supporting sustainable rangeland management under arid conditions.

Post-mining phosphorite landscapes in semi-arid regions often retain physical constraints that limit vegetation establishment and slow soil recovery. We assessed soil physical recovery at the Zhanatas phosphorite deposit (southern Kazakhstan) by comparing three site types: (i) a reclaimed dump (technical reclamation in 2012, biological reclamation in 2013; ~2 ha; ~50 cm loam substrate; 70–75% plant establishment), (ii) a dump undergoing passive selfrecovery since mine closure in 1984 with sparse vegetation cover (~9.5–10%), and (iii) an undisturbed reference soil. During May–September 2025, three soil profiles were excavated per site and sampled by genetic horizons. Across sites, materials were sand-dominated, but the fine fraction (<0.01 mm) differed strongly among recovery pathways. The reclaimed site showed stable near-surface texture (<0.01 mm = 31.97–34.93% at 0–40 cm), comparable to the upper horizons of the naturally revegetated dump (28.60–30.34% at 0–70 cm). In contrast, a deep layer of the naturally revegetated dump (70–110 cm) was extremely coarse (sand 89.89%; <0.01 mm 8.87%), indicating a persistent textural discontinuity. The undisturbed soil had the highest fine fraction (<0.01 mm = 34.57–45.05%). Moisture ranged from 2.09% (reclaimed 0–10 cm) to 11.69% (dump 70–110 cm). PCA differentiated site types and revealed the greatest heterogeneity in the naturally recovering dump. Reclamation improved near-surface physical conditions, but full convergence to reference soil remains incomplete due to strong textural contrasts within the profile.

Solonetz and Solonetzic rangelands are widespread in arid regions of Central Kazakhstan, where pasture degradation is often difficult to assess because surface vegetation patterns do not always reflect subsurface soil constraints. This study aimed to evaluate degradation mechanisms in Solonetz pasture ecosystems of the Ulytau region by integrating field soil-profile descriptions, laboratory analyses, vegetation observations, forage productivity data and Sentinel-2A-derived MSAVI. Ten monitoring soil profiles were examined for particle-size distribution, soluble salts, ionic composition, exchangeable cations, available N, P and K, vegetation cover and forage yield. USDA textural classification, salt-distribution analysis, Pearson correlation, PCA, RDA and MSAVI-based mapping were used to link soil-profile properties with vegetation and spectral response. The results showed strong profile heterogeneity, with clay enrichment, subsurface salt accumulation, alkalinity and Na- or Mg-related exchange-complex imbalance forming several degradation pathways. Surface horizons were often weakly saline, whereas deeper layers contained stronger chemical and physical limitations. MSAVI values were low across the monitoring sites and reflected vegetation–soil surface conditions rather than salinity or sodicity directly. Combining soil-profile diagnostics with Sentinel-2A MSAVI improved the interpretation of degradation patterns and provides a practical framework for monitoring spatially heterogeneous Solonetz rangelands in arid pasture systems.

Soil salinization poses a persistent threat to irrigated agroecosystems, yet remote sensing-based salinity assessment remains predominantly calibrated against bulk electrical conductivity without fully integrating crop physiological variability. This review examines the evolution of remote sensing approaches for soil salinity mapping (1994–2024), with particular emphasis on the role of crop salt tolerance in shaping spectral interpretation and mapping accuracy. A systematic synthesis of 58 peer-reviewed studies retrieved from the Scopus database was conducted using bibliometric analysis and structured full-text thematic classification to evaluate methodological trends and conceptual integration across soil, crops, and spectral domains. The results reveal substantial technological advancement, including multispectral and hyperspectral sensing, machine learning frameworks, and multi-source data integration. However, most approaches remain surface-oriented and statistically calibrated, with limited operationalization of crop-specific tolerance thresholds, root-zone salinity dynamics, and hydrochemical variability. The findings indicate that crop salt tolerance functions as a mediating factor within the soil–plant–spectral continuum, influencing the stability and transferability of spectral–salinity relationships. Integrating physiological tolerance parameters and subsurface processes into modeling frameworks is essential for improving agronomic interpretability and supporting more reliable salinity management in irrigated systems.

The genus Trollius L. remains insufficiently studied in Kazakhstan, necessitating comprehensive monitoring of its distribution and population status assessments. In Kazakhstan, this genus is represented by the following five species: T. asiaticus, T. altaicus, T. dschungaricus, T. lilacinus and T. komarovii. Of those, T. altaicus and T. dschungaricus are the most widely distributed. This study focuses on analyzing the population structure of Trollius altaicus and Trollius dschungaricus in relation to varying ecological and geographical conditions within Kazakhstan, along with conducting a comprehensive morphometric assessment. To study plant communities with Trollius L. species, classical geobotanical methods were applied, including the route-reconnaissance method to determine the species’ range and carry out a detailed population survey which involved the assessment of the age structure of populations and species composition of associated vegetation. Population structure analysis showed that the majority of T. altaicus plants were in the generative stage, with the right skewed age spectrum suggesting a decline in population size. Meanwhile, populations of T. dschungaricus were dominated by juvenile and virginal individuals, with the left skewed age spectrum suggesting a high regenerative potential. The morphometric analysis revealed high variability of plant height, number of leaves, flower diameter, diameter of generative bushes, number of basal leaves, and leaf length and width. The obtained results can serve as a basis for developing effective conservation and management strategies for T. altaicus and T. dschungaricus under ongoing climate change and anthropogenic impact. This research demonstrates that a detailed assessment of phenotypic characteristics is vital for formulating preservation frameworks and managing biological resources sustainably.

Maize production in semi–arid irrigated systems depends on soil fertility and an active rhizosphere. We hypothesized that vermiculite enriched with humic substances (HS) or Chlorella vulgaris (CV) would outperform vermiculite alone by improving soil fertility, maize nutrition, and rhizosphere-associated microbial indicators. A field experiment was conducted in southern Kazakhstan under medium–loam sierozem using a randomized block design with three replicates and seven treatments: control, vermiculite at 1 and 2 t ha⁻¹, vermiculite + HS at 1 and 2 t ha⁻¹, and vermiculite + CV at 1 and 2 t ha⁻¹. Amendments were incorporated before sowing, and soil, plant, and microbial measurements were taken before sowing, at V6–V8, and after harvest. Compared with the control, all amendments improved early maize growth, leaf area development, biomass accumulation, and nutrient status, and increased grain yield. The strongest response was obtained with vermiculite + HS at 2 t ha⁻¹, which increased grain yield from 6.48 to 10.24 t ha⁻¹ (+58%). Microbial indicators differed between bulk soil and the rhizosphere, while Pearson correlation and PCA revealed coordinated soil–plant–microbe responses and productivity–linked variables across treatments. Taken together, these results indicate that enriched vermiculite, especially HS–enriched vermiculite at 2 t ha⁻¹, is a promising amendment for improving maize productivity and rhizosphere functioning in semi–arid irrigated systems.