Search Results (1,005)

The ecological restoration of degraded sandy land in the Yarlung Zangbo River Valley is constrained by the metabolic functions of soil microorganisms. This study investigates the dynamic mechanisms of microbial elemental use efficiency in walnut plantations, with a focus on seasonal variations in soil chemical stoichiometry, extracellular enzyme activity, and microbial nutrient efficiency in rhizosphere and bulk soils. This paper explores the effects of conventional organic fertilizer (CF) and organic–inorganic compound fertilizer (OIF) on microbial nutrient use strategies and their seasonal dynamics. The results showed significant seasonal fluctuations in soil active nutrients and microbial biomass, while the total nutrient content remained stable. OIF enhanced microbial chemical stoichiometric homeostasis but simultaneously triggered a “carbon–phosphorus metabolic trade-off”, leading to a restraint of microbial carbon use efficiency (CUE) during the growing season. Microbial elemental use efficiency (EUE) exhibited clear seasonal differentiation: CUE was higher in summer, promoting biomass accumulation, whereas NUE and PUE increased in winter and spring, reflecting a nutrient conservation strategy. The EUE pathways were decoupled between rhizosphere and non-rhizosphere microenvironments. The rhizosphere was more directly driven by soil chemical stoichiometry and microbial biomass, while the non-rhizosphere was influenced by nutrient limitation states, represented by vector characteristics. This study provides insights into the seasonal adaptability and microenvironmental heterogeneity of microbial metabolism during the restoration of cold sandy land. It is suggested that future ecological management should focus on N-P balanced fertilization and consider the differential responses between rhizosphere and non-rhizosphere zones to enhance ecosystem productivity and soil carbon, nitrogen, and phosphorus sequestration potential. Full article

Hippophae gyantsensis Lian is an important native tree species in the “One River, Two Streams” valley of Tibet, valued for its ecological restoration potential and nutrient-rich fruits. However, this species has several limitations, including a long fruiting cycle (3–5 years to flowering and 10–15 years to reach peak fruit production), small fruit size, and numerous branch thorns. These traits hinder large-scale cultivation and mechanized harvesting, creating an urgent need for improved varieties with larger fruit and higher yield. In this study, we established an efficient Agrobacterium-mediated genetic transformation system for H. gyantsensis using hypocotyls as explants. Under optimized conditions (OD₆₀₀ = 0.5, AS = 200 μmol/L, infection time = 15 min), the transformation efficiency reached 36.67% (calculated as the number of PCR-positive plants divided by the total number of explants initially inoculated with Agrobacterium). A rooting rate of 12.5% was achieved using 100 mg/L rooting powder (ABT1) for 40 min, resulting in an overall success rate of approximately 4–5%. Furthermore, we identified and cloned two fruit-size-related genes, Hgfw2.2 and Hgfw3.2, from H. gyantsensis. Heterologous expression of Hgfw2.2 and Hgfw3.2 in tomato decreased and increased fruit size, respectively, consistent with their regulatory roles in fruit development. Given the positive regulatory effect of Hgfw3.2, this gene was further transformed into H. gyantsensis. This study represents the first report of a stable genetic transformation platform for H. gyantsensis, providing a robust technical foundation for future molecular breeding and the development of improved, large-fruited varieties. Full article

This article presents the results of a field study conducted in 2022 on groundwater outflows located at the edge of the Kashubian Lake District and the Reda-Łeba Proglacial Stream Valley in northern Poland. The recharge of numerous springs was found to occur from the first aquifer, locally supported by a deeper aquifer connected to the first one near the bowl of Lubowidzkie Lake. Groundwater drainage occurs by gravity. It is relatively abundant for young glacial areas and averages 82 dm³·s⁻¹, making the springs capable of acting as a drinking water reservoir. This assessment is based on major ions and nutrients only; microbiological and trace-organic/metal analyses are required before any drinking-water designation. Spring water is important in the lake’s supply, accounting for 18.0% of the total inflow to the basin. The hydrochemical characteristics of these waters keep the lake in ecological balance. The waters from the springs are characterized by little variation in chemical composition, with the Ca-HCO₃ hydrochemical type. They represent young infiltration waters associated with direct recharge from precipitation (the average age of the water is 60 years). Currently, low nitrate and chloride suggest limited agricultural and urban influence, but phosphate levels and observed human activities warrant caution. Forest management is gradually developing in its catchment, which may result in a reduction of the spring yield and a deterioration of their quality in the future. This may result in a disturbance of the hydrological balance of structures hydraulically connected to spring recharge and to groundwater inflow (river, lake). Although the springs studied are local hydrological phenomena, their functioning and the need for protection are closely linked to global challenges in the field of sustainable development. This primarily concerns the protection of groundwater-dependent ecosystems and, more broadly, water security and increased resilience to climate change. Full article

Under the dual pressures of global climate change and rapid urbanization, the spatial contradiction between urban expansion and flash flood disasters in mountainous dam areas is increasingly evident. However, the mechanisms by which the multi-dimensional characteristics of urban expansion affect regional flash flood susceptibility (FFS) remain unclear, limiting scientific guidance for source-level disaster prevention. This study uses Zhaotong City, a flash flood-prone area in the lower Jinsha River basin of southwestern China, as a case study. Using land use and multi-source remote sensing data from 2000 and 2025, we identify urban expansion patterns and morphological characteristics, apply the XGBoost-SHAP model to evaluate flash flood susceptibility and determine dominant factors, and employ the generalized additive model (GAM) to quantify the nonlinear responses of expansion dimensions to FFS. Results show the following: (1) Urban expansion in Zhaotong City is primarily edge (51%) and leapfrog (46%), clustering along river valleys, dam areas, and transportation corridors. (2) The XGBoost model performs well (AUC = 0.877). Elevation, slope, normalized difference vegetation index (NDVI), and precipitation are the primary natural factors influencing FFS. About 15.66% of the city falls within the high/very high FFS zones, mainly in the Zhaolu Dam area, riverbanks of main and tributary streams, and the urban built-up area. (3) Urban expansion-related indicators explain 28.6% of the spatial variation in FFS, with leapfrog expansion as the primary driver (contribution rate 32.75%). Disorderly urban growth and morphological imbalance significantly increase flash flood susceptibility. This study provides a scientific basis for spatial planning, flash flood prevention and control, and climate-adaptive urban development in similar mountainous dam areas in Southwest China and Asia, supporting regional sustainable development goals. Full article

Tourism safety in high altitude destinations is strongly affected by the combined effects of environmental constraints, tourism exposure, and safety support capacity. The Qinghai–Tibet Plateau (QTP), characterized by high altitude, complex terrain, sparse settlements, and limited emergency accessibility in remote areas, provides a representative case for tourism risk assessment in extreme plateau environments. To predict and interpret the spatial pattern of tourism risk on the QTP, this study constructs an assessment framework based on “Hazard–formative factors + Risk exposure + Safety security” and integrates XGBoost with SHAP interpretable machine learning. Eleven indicators representing environmental conditions, tourism exposure, and safety support capacity were used to model tourism risk at a 1 km × 1 km spatial resolution. The optimized XGBoost model achieved an AUC of 0.877, indicating good predictive performance. The results show that tourism risk on the QTP presents a spatial pattern of “high in the northwest and low in the southeast”. High risk and relatively high risk areas account for approximately 74.98% of the study area and are mainly distributed in remote hinterlands and northwestern plateau regions, whereas low risk areas are concentrated around southeastern river valleys, towns, mature scenic areas, and major transport corridors. SHAP analysis indicates that Distance to towns is the most important factor influencing predicted tourism risk, followed by Reception facility kernel density, Relief degree of land surface, and Scenic spot kernel density. Nonlinear and interaction analyses further suggest that remoteness, tourism facilities, terrain relief, and scenic area concentration jointly shape the predicted risk pattern. The findings provide spatial evidence for differentiated tourism risk management, including regular tourism development in relatively safe urban and scenic nodes, controlled management of medium risk tourism corridors, and stricter access management in remote high risk areas. Full article

Numerical simulations quantify the transient impacts of implementing green infrastructure (GI) grass swales on unconfined aquifer storage and groundwater-surface water interactions around the Red Butte Creek (RBC) of Utah, USA. The Red Butte Creek Watershed (RBCW) transitions from undeveloped mountainous National Forest land to downstream urbanized areas within Salt Lake Valley (SLV). This reconnaissance-level study demonstrates that increasing stormwater infiltration in urbanized areas during the rainy months (April-June) can, until at least the subsequent March, (a) enhance aquifer recharge and support sustainable groundwater yields; and (b) improve surface water availability. Simulations predict hydrologic impacts of aquifer recharge resulting from hypothetical grass-swale implementation within a 704-acre area located around RBC. The employed model, HyperRBC, is an adaptation of a United States Geological Survey (USGS) transient numerical flow, MODFLOW, model implementation for SLV. Adaptations involved (a) uniformly refined horizontal discretization of seven aquifer layers within a sub-area encompassing parts of RBCW and an adjacent watershed; (b) updated input data; and (c) MODFLOW’s Streamflow-Routing (SFR) package to simulate RBC flow and aquifer-stream seepage. Model predictions indicated that by the end of next March: (a) about 3% of the GI-induced recharge would remain within the unconfined aquifer in the HyperRBC area; (b) 66.6% of the recharge would flow northward into the downgradient continuation of the unconfined aquifer; and (c) 30.3% would discharge to nearby stream and river. In summary, predicted hydrologic changes due to the short-term GI-induced recharge highlight increased groundwater availability within and outside the study area for at least the subsequent 12 months, including high-water-demand summer. These findings show the importance of GI in interim environmental management and in enhancing the effective use of water resources. Full article

The Ili River Valley is a typical seasonally frozen region in which slope instability frequently occurs during the warm frozen-soil stage, generally at temperatures ranging from approximately −1.5 to 0 °C. In this context, changes in unfrozen water content play an important role in controlling the pore structure and mechanical behavior of warm frozen soil, yet the links among these factors remain insufficiently understood. This study investigates warm frozen soil from the Ili River Valley, with particular emphasis on the role of unfrozen water content in regulating pore-structure characteristics and mechanical response under low-temperature conditions. Low-field nuclear magnetic resonance (NMR), low-temperature triaxial shear tests, scanning electron microscopy (SEM), and quantitative image analysis were employed to examine the relationships between unfrozen water content, pore structure, and macroscopic mechanical properties under different temperatures, initial water contents, and confining pressures. The results show that unfrozen water content decreases markedly with decreasing temperature, especially within the range of −1.5 to −5 °C, and increases with increasing initial water content. These changes are accompanied by significant variations in porosity, pore abundance, and pore fractal dimension, reflecting freezing-induced reorganization of the pore system. Lower temperatures and higher initial water contents promote ice-crystal growth and the formation of larger ice-cemented aggregates, thereby modifying the pore framework. Meanwhile, peak strength and cohesion increase with decreasing temperature and increasing initial water content, whereas the internal friction angle shows a decreasing trend. In addition, porosity, pore abundance, and pore fractal dimension are closely correlated with peak strength and cohesion. The results indicate that unfrozen water content governs the freezing-induced reorganization of pore structure, which in turn controls the strength evolution of warm frozen soil. These findings improve understanding of the role of unfrozen water in low-temperature soil structure and strength evolution and provide a basis for evaluating slope instability in the Ili River Valley. Full article

As a mountain–water city in the upper Yangtze River region, Chongqing is characterized by complex river-valley terrain, dense riverside development, extreme summer heat, high humidity, and frequent calm-wind conditions. Existing studies on waterfront thermal comfort mainly focus on plain cities, whereas mountainous riverside parks remain insufficiently understood. This study investigated summer thermal comfort in three riverside parks in Chongqing—Jiulongtan Park, Coral Park, and Jiangtan Park—through field measurements of air temperature, black globe temperature, wind speed, relative humidity, and Thermal Radiation, combined with thermal sensation vote (TSV) and thermal comfort vote (TCV) surveys. Results showed that the maximum air temperature reached 43.7 °C and the maximum black globe temperature reached 61.6 °C. The hydrophilic layer recorded the highest wind speed (1.64 ± 0.39 m/s), while the elastic layer showed high PET values (36.00–46.10 °C). Regression analysis indicated neutral PET values of 32.49–35.74 °C. Correlation analysis showed that PET, mean thermal sensation vote (MTSV), and mean thermal comfort vote (MTCV) were positively correlated with air temperature, black globe temperature, mean radiant temperature (T_mrt), and relative humidity. In contrast, PET was negatively correlated with wind speed. This study reveals the coupled effects of river-valley terrain, elevation stratification, waterfront microclimate, and landscape elements on outdoor thermal comfort, providing a scientific basis for optimizing shading, ventilation, and hydrophilic spaces in hot-humid mountain–water cities. Full article

Accurate landslide susceptibility assessment remains challenging in mountainous regions with complex terrain, heterogeneous geology, and clustered landslide inventories. This study develops a slope–unit–based landslide susceptibility assessment framework for Tongren County, Qinghai Province, China, using a landslide inventory of 217 events, multi–source environmental data, Certainty Factor (CF)–based conditioning–factor analysis, and machine learning models. Eighteen conditioning factors derived from remote sensing, geological survey, and meteorological datasets were extracted at the slope–unit scale, and their collinearity was evaluated using Pearson’s correlation and the Variance Inflation Factor (VIF). Eight models—Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), AdaBoost, Decision Tree (DT), XGBoost, K–Nearest Neighbors (KNN), and Convolutional Neural Network (CNN)—were evaluated under a 70:30 train/test split. The results show clear performance differences among the tested models: SVM achieved the best overall balance between discrimination and landslide detection (AUC = 0.9489; recall = 0.879). The tested CNN baseline showed relatively weak performance under the current slope–unit–based tabular–data setting. Susceptibility zoning results showed that high– and very–high–susceptibility zones were mainly concentrated along the Longwu River and its tributaries, where middle–elevation dissected terrain, weak lithological materials, river–valley erosion, and human engineering activities spatially coincide. These results provide a practical basis for slope monitoring and land–use planning in Tongren County. Full article

As a typical mountain ecosystem in the western Tianshan Mountains, the Ili River Valley possesses abundant vegetation resources. Soil nematodes are effective biological indicators for evaluating soil micro-food webs. Nevertheless, the response mechanisms of nematode community structure to distinct vegetation types, especially native trees and forest-edge shrubs, remain poorly understood in this region. In this study, two dominant tree species (Picea schrenkiana and Malus sieversii) and two forest-edge shrub species (Berberis heteropoda and Berberis sibirica) were investigated. We analyzed the composition, diversity, and energy structure of rhizosphere soil nematodes and further compared their differences among plant species. The results indicated that tree rhizospheres had significantly higher amounts of nitrate nitrogen ($\mathrm{N}{\mathrm{O}}_3^{-}$-N and microbial biomass carbon (MBC), along with a lower amount of extractable organic carbon/extractable total nitrogen (EOC:ETN) than shrub rhizospheres (p < 0.05). Picea schrenkiana (PS) exhibited greater root carbon storage, higher root biomass, and a higher root carbon-to-nitrogen ratio (RC:RN) than Berberis heteropoda (BH) and Berberis sibirica (BS) (p < 0.05). The genus Chiloplacus dominated the nematode community across all four woody plants. The relative abundance of omnivore-predatory nematodes was markedly higher in shrubs (BH and BS) than in trees (PS and MS). The soil food webs of PS and MS were degraded, whereas shrub food webs were in a transitional state between structured and degraded habitats. Shrubs presented a higher maturity index, structural metabolic footprint, and energy flux of omnivore-predatory nematodes, but a lower energy flux of bacterivorous nematodes. Additionally, PS had the highest nematode carbon use efficiency (NCUE) and the lowest energy flux uniformity (U). $\mathrm{N}{\mathrm{O}}_3^{-}$-N extractable total nitrogen (ETN), soil organic carbon (SOC), and root traits were the primary factors driving variations in nematode communities and carbon indicators. Therefore, nematode carbon indicators closely associated with soil carbon and nitrogen cycling have the potential to serve as sensitive auxiliary biological metrics for evaluating material cycling and energy flow in pure forests and shrub ecosystems. This study provides empirical support for the assessment of regional ecosystem stability. Full article

Revealing the spatial differentiation patterns of cultivated land multifunctionality contributes to the improvement of cultivated land protection policies. This study investigated the spatiotemporal differentiation characteristics and functional zoning of cultivated land multifunctionality in Alpine Valley Area from a topographic gradient perspective. An evaluation index system for cultivated land multifunctionality in Alpine Valley Area was constructed across four dimensions: production (PF), social (SF), ecological (EF), and landscape (LF) functions. Using Yulong County, Yunnan Province, as a case study, methods including kernel density analysis, standard deviation ellipse theory, topographic gradient analysis, and hierarchical clustering were employed to quantify the horizontal and topographic gradient characteristics of the multifunctionality of cultivated land from 2010 to 2020, thereby delineating functional zones. Results indicated: (1) Cultivated land multifunctionality shows clear topographically-dependent spatial differentiation: PF concentrates in central basins and northwest specialty agricultural zones, SF overlaps with production but with more dispersed high/low values, EF follows a “high in the center, low on the lateral areas” pattern, and LF remains relatively stable; (2) Significant hierarchical differences in cultivated land functions were observed along the elevation, slope, and terrain niche index (TNI) gradients. PF, EF, and LF generally decreased with increasing elevation, slope, and TNI, whereas the dominance of SF exhibited an inverted-V-shaped distribution along the gradient. (3) The study area was divided into five zones: Flat-Basin Agritourism Zone (FAZ), River-Valley Eco-Agriculture Zone (REZ), Sub-Alpine Specialty Agricultural Production Zone (SSAPZ), Sub-Alpine Steep Slope Integrated Management Zone (SSIMZ), and Mid-Mountain Steep Slope Ecological Conservation Zone (MSECZ), with differentiated strategies proposed for each. This study innovatively integrates a topographic gradient perspective, TNI, and hierarchical clustering to systematically evaluate the cultivated land multifunctionality in Alpine Valley Area, providing a new methodological framework for similar mountainous regions. Full article

Transmission lines in Southwestern China are highly exposed to compound hazards induced by extreme winds and ice and snow conditions. This study assesses future changes in extreme wind hazards and their spatial overlap with baseline ice susceptibility under the SSP2-4.5 emission scenario, using high-resolution dynamically downscaled climate projections. Compared to the historical period (1995–2014), the results indicate a marked intensification of extreme spring wind events over northwestern Southwestern China and the transitional zone between the Sichuan Basin and the Hengduan Mountains during 2041–2060. The occurrence frequency of wind speeds exceeding historical 50-year return levels is projected to increase by 5–10 times in complex terrain, particularly along the Golmud–Qaidam belt. The Comprehensive Extreme Wind Index (CEWI) identifies the Golmud–Wulanwusu–Qaidam river basin belt as the region of highest wind hazard amplification. Meanwhile, analysis of historical observations reveals that icing-prone conditions occur on more than 25 days each spring in the Nyenchentanglha Mountains and southeastern Tibetan Plateau valleys, establishing a baseline map of ice susceptibility. Due to methodological limitations in projecting future icing, this susceptibility map is used as a static indicator of ice-prone areas. By superimposing projected wind intensification onto the baseline ice susceptibility map, four relative hazard exposure categories are delineated. Regions of highest potential exposure are concentrated in the Bayan Har Mountains and portions of the western Hengduan Mountains, whereas northwestern basins are dominated by high wind risk alone. These results reveal pronounced spatial heterogeneity in the relative amplification of compound hazards under future warming and provide a scenario-informed scientific basis for prioritizing regions in disaster risk reduction and resilient planning of transmission infrastructure in mountainous regions. Full article

(1) Pholidoptera griseoaptera (De Geer, 1773) (Orthoptera, Tettigoniidae) is a common and widespread inhabitant of forest edges in Europe and may therefore serve as a suitable model species for understanding past and future changes in forest wildlife. (2) We recorded the presence or absence of the species in 189 forest and forest-edge plots within the Kaluga Region using acoustic observations and pitfall trapping, and analysed the data using logistic regression. (3) Across the region, the main positive factor affecting species presence was the dominance of nemoral herbs in the herb layer. The main negative factors were habitat isolation caused by physical barriers and location within moraine plains formed during the late stage of the Moscow glaciation. The presence of coniferous tree species and spatial autocovariation were also significant factors, although their contributions were relatively small. The abundance of Ph. griseoaptera was higher in forests located within river valleys. Within Kaluga, the long-term persistence of tree vegetation and habitat isolation were the main significant factors affecting species occurrence. The smallest urban habitat occupied by the species covered approximately 13 ha, whereas the total area of unmown patches within this habitat was only about 0.2 ha. (4) Ph. griseoaptera may be used as an indicator of the long-term persistence of broadleaved deciduous (nemoral) forests. Under conditions of high urbanization, however, the species may become threatened. Full article

Landslides are widespread and highly destructive geological hazards that pose serious threats to infrastructure and densely populated areas. Conducting scientific and accurate predictions of landslide spatial distribution is therefore of great practical importance for supporting landslide prevention, risk management, and the reduction in casualties and economic losses. Landslides are driven by multiple variables, including elevation, road distance, river distance, slope and land use, with complex nonlinear interactions that traditional linear models cannot accurately capture. This study adopts a Categorical Boosting model (CatBoost) as the base prediction model, which demonstrates strong performance in capturing interactions among multiple variables and achieves relatively robust landslide spatial distribution predictions without complex feature engineering. However, CatBoost is highly sensitive to hyperparameters and difficult to manually optimize. Based on the Nutcracker Optimization Algorithm (NOA), which features an efficient search strategy, a multi-level improved Nutcracker Optimization Algorithm (COLNOA) is proposed to optimize its hyperparameters. The proposed algorithm integrates Circle Chaotic Mapping into the initial population construction of the NOA to generate two distinct populations and enables information exchange between them during the evolutionary process, thereby enhancing global search capability. In addition, Opposition-Based Learning and lateral mutation strategies are introduced to update inferior individuals in each iteration, improving their search capability. Based on these improvements, a COLNOA-CatBoost prediction model is developed. The proposed model is applied to a case study in Wanzhou District, Chongqing, China. The results show that the proposed model achieves a recall of 0.863, an F1-score of 0.860, and an accuracy of 0.865, outperforming baseline models such as decision trees. Compared with the original CatBoost model, recall, F1-score, and accuracy are improved by 34.8%, 35.0%, and 35.1%, respectively. The spatial prediction results indicate that high-risk landslide areas in Wanzhou District are mainly concentrated in regions such as Zouma Town, medium-risk areas in Xintian Town, low-risk areas in Fenshui Town, and very low-risk areas in Longju Town. Further analysis of terrain and landforms indicates that the high-risk areas for landslides in Wanzhou District are mainly related to steep slopes, deep river valleys, exposed or cut slopes at the foot of the slope, runoff convergence, and road excavation slopes. The extremely low and low-risk areas are mostly distributed in the middle and low mountain and hilly areas with relatively flat terrain, weak river cutting and engineering disturbance. This is consistent with the previous correlation analysis that the number of landslides increases with increasing slope and decreases with increasing elevation, distance from rivers, and distance from roads. Overall, the proposed model provides an effective approach for landslide spatial distribution prediction. Full article

To elucidate the mechanisms of nutrient cycling in rhizosphere soil and microbial metabolism during the prolonged continuous cropping of lavender, this study examined the rhizosphere soil of lavender with different continuous cropping years (1, 4, 7, 10, 15, and 20 years) in the Ili River Valley of Xinjiang, China, measuring physicochemical properties, microbial biomass C/N/P, and eight extracellular enzyme activities. Microbial carbon use efficiency (CUE) and nutrient limitation were quantified using vector analysis, threshold elemental ratios (TERs), and two derived indices (TER_EEA and TER_L). Soil properties exhibited distinct nonlinear patterns: SOC peaked at 4 years (p < 0.05), TN was highest at 20 years, and TP was lowest at 4–7 years. MBC and MBN peaked at 20 years, whereas MBP was significantly lower than in 1-, 4-, and 10-year fields (p < 0.05). EEC and EEN were highest at 20 years, while EEP was lowest at 4 years (p < 0.05). The activity of carbon-related acquisition enzymes increases from 134.81 μmol/g·h in the first year to 393.86 μmol/g·h in the 20th year, an increase of 192%; the activity of nitrogen acquisition enzymes increases from 686.11 μmol/g·h in the first year to 1430.58 μmol/g·h in the 20th year, an increase of 108%. This indicates that the decomposition of organic matter and the nutrient cycling capacity continue to enhance. Vector analysis showed a mean VA of 46° and VL of 0.25, with VA > 45° (P limitation) at 1–4 years shifting to VA < 45° (N limitation) at 20 years. Critically, TEREEA and TERL produced opposite dominant limitations due to differing normalization frameworks—TEREEA scales by microbial biomass stoichiometry—while TERL normalizes against enzyme-derived thresholds. CUET and CUEE ranged from 0.42 to 0.56, with the minimum at 10 years and relatively high values at 15–20 years (p < 0.05). RDA identified CBH (26.2%) and NO₃⁻–N (19.8%) as primary drivers, with extractable phosphorus exhibiting the strongest regulatory effect (pseudo-F = 26.0). These results demonstrate that multi-model stoichiometric assessment is essential, as single indices may yield contradictory diagnoses. These results demonstrate that multi-model stoichiometric assessment is essential, as single indices may yield contradictory diagnoses, and the observed nonlinear shifts in dominant limitation type provide a mechanistic basis for targeted nutrient management in sustainable lavender cultivation. Full article