Oases in arid regions are crucial for sustaining agricultural production and ecological stability, yet few studies have simultaneously examined the coupled dynamics of land use/cover change (LUCC), carbon emissions, and ecosystem service value (ESV) at the oasis–agricultural scale. This gap limits our understanding of how different land use trajectories shape trade-offs between carbon processes and ecosystem services in fragile arid ecosystems. This study examines the spatiotemporal interactions between land use carbon emissions and ESV from 1990 to 2020 in the Wensu Oasis, Northwest China, and predicts their future trajectories under four development scenarios. Multi-period remote sensing data, combined with the carbon emission coefficient method, modified equivalent factor method, spatial autocorrelation analysis, the coupling coordination degree model, and the PLUS model, were employed to quantify LUCC patterns, carbon emission intensity, ESV, and its coupling relationships. The results indicated that (1) cultivated land, construction land, and unused land expanded continuously (by 974.56, 66.77, and 1899.36 km²), while grassland, forests, and water bodies declined (by 1363.93, 77.92, and 1498.83 km²), with the most pronounced changes occurring between 2000 and 2010; (2) carbon emission intensity increased steadily—from 23.90 × 10⁴ t in 1990 to 169.17 × 10⁴ t in 2020—primarily driven by construction land expansion—whereas total ESV declined by 46.37%, with water and grassland losses contributing substantially; (3) carbon emission intensity and ESV exhibited a significant negative spatial correlation, and the coupling coordination degree remained low, following a “high in the north, low in the south” distribution; and (4) scenario simulations for 2030–2050 suggested that this negative correlation and low coordination will persist, with only the ecological protection scenario (EPS) showing potential to enhance both carbon sequestration and ESV. Based on spatial clustering patterns and scenario outcomes, we recommend spatially differentiated land use regulation and prioritizing EPS measures, including glacier and wetland conservation, adoption of water-saving irrigation technologies, development of agroforestry systems, and renewable energy utilization on unused land. By explicitly linking LUCC-driven carbon–ESV interactions with scenario-based prediction and evaluation, this study provides new insights into oasis sustainability, offers a scientific basis for balancing agricultural production with ecological protection in the oasis of the arid region, and informs China’s dual-carbon strategy, as well as the Sustainable Development Goals.

Quantifying the impacts and contributions of nitrogen (N), phosphorus (P), and potassium (K) fertilizer management on the annual and cutting cycle yields of alfalfa can provide guidance for alfalfa cultivation. In this study, 597 sets of alfalfa yield data from the arid and semi-arid regions of China were collected and grouped according to the N, P, K, and NPK rates. Statistical and meta-analyses were employed to explore the response of alfalfa yield to fertilization management. The results indicated that the annual and cutting cycle yields of alfalfa increased and then decreased as the N rate increased; meanwhile, the annual yield increased with the P and K rates, and the cutting cycle yield decreased with increased cutting cycles under P and K treatments. The alfalfa yield at the first cutting cycle was about 30% of the annual yield in the arid and semi-arid regions of China. Moreover, the annual yield increased and then decreased as the NPK rate increased. The Aggregated Boosted Tree (ABT) algorithm-based analysis showed that the NPK rate had the greatest contribution to the annual yield (37.61%), followed by the application rates of P (24.50%), N (22.55%), and K (15.34%). The impacts of the P/NPK, N/NPK, and K/NPK ratios on the annual yield were 38.64%, 31.71%, and 27.65%, respectively. Additionally, an NPK amount > 225–310 kg/ha and ratios of N, P, and K of 14.28–27.72%, 36.36–50%, and below 25%, respectively, resulted in the highest increase in alfalfa yield. This is recommended as the optimal fertilization practice to obtain high alfalfa yields and improve fertilizer use efficiency in the arid and semi-arid regions of China.

To investigate the effects of long-term cultivation on soil physicochemical properties, cotton production and soil quality dynamics in the oases of southern Xinjiang, uncultivated and unfertilized wasteland was used as the control (CK), and cotton fields with cultivation durations of 7, 12, 21, 30 and 40 years were selected in the Tailan River oasis. Soil physicochemical properties (0–200 cm) and cotton production indicators were measured. A minimum dataset (MDS) and soil quality index (SQI) were constructed, and obstacle-factor diagnosis, partial least-squares structural equation modelling (PLS-SEM), the Mantel test and multiple linear regression were used to identify key drivers. The results indicated that the SQI in the 0–40 cm soil layer showed an increase-then-decrease pattern with different cultivation histories. Organic matter (OM), available phosphorus (AP), pH and electrical conductivity (EC) were identified as major obstacle factors for SQI improvement. PLS-SEM indicated a strong positive association between soil nutrients and SQI, whereas salinity and alkalinity were negatively associated with SQI; cultivation duration was indirectly associated with SQI through its positive association with soil nutrients. Soil nutrients also had the strongest positive association with cotton yield, whereas salinity and alkalinity were negatively associated with yield. Reproductive organs’ dry weight (RDW), available potassium (AK) and OM were the most important predictors of cotton yield. In summary, the SQI showed an increase-then-decrease pattern across sampled fields with different cultivation histories, with the highest mean in 30-year fields and a lower mean in 40-year fields. Insufficient soil nutrient supply emerged as the primary obstacle to SQI and yield in long-term cultivated fields. Synergistic improvements in cotton yield and SQI can be achieved through measures such as optimising the combined application of nitrogen and phosphorus, regulating water and salinity, increasing the application of organic fertiliser and implementing appropriate crop rotation, thereby providing a reference for soil quality management and sustainable agricultural development in arid regions.

Silage maize is an important forage crop in China and globally. Applied nitrogen (N) is crucial for increasing the harvest yield (aboveground dry matter) of silage maize. However, there is a lack of information on how nitrogen rate affects the harvest yield of silage maize in different planting regions and under different climatic and soil conditions in China. A meta-analysis was conducted to quantify and evaluate the effects of N rate on the harvest yield and N fertilizer contribution rate of silage maize in China and different planting regions in the country based on research published from 2000 to 2025. The effects of mean annual temperature, annual precipitation, soil properties, planting density, and cultivar used on the maize yield response were also investigated via subgroup analysis. The means of the N rate, harvest yield, and N contribution rate for silage maize in China were 211 kg ha⁻¹, 20,117 kg ha⁻¹, and 27%, respectively. In the southwest hilly and mountainous region, silage maize exhibited the highest harvest yield-change rate (55.41%) under a N rate of >0–100 kg ha⁻¹. In Northern China, the Huang-Huai Plain region, and the southern hilly region, the maximum harvest-yield-change rates for silage maize (31.42%, 54.11%, and 42.66%) were observed at a N rate of >200–300 kg ha⁻¹. In northwest inland China, the maximum harvest-yield-change rate (50.76%) of silage maize occurred at a N rate of >300 kg ha⁻¹. Furthermore, the aggregated boosted tree algorithm was adopted to quantify the relative contribution of N rate, annual mean temperature, annual precipitation, soil pH, soil organic matter, soil type and texture, cultivar selected, and planting density to the harvest yield and N contribution rate of silage maize. Soil type made the greatest contribution to the yield of silage maize in China, accounting for 41.36%, followed by cultivar (40.28%) and planting density (5.97%), and the total contribution of the three factors reached 87.61%. Soil type exhibited the highest contribution (26.35%) to the N contribution rate of silage maize in China, followed by cultivar (22.36%) and planting density (15.11%). The combined contribution of the three factors was 63.82%. Based on the dual criteria of maximizing harvest yield and the N contribution rate, the optimal N rates found for silage maize were 173–300, 110–200, 311–395, 168–270, and 92–270 kg ha⁻¹ for Northern China, the Huang-Huai Plain region, northwest inland China, the southern hilly region, and the southwest hilly and mountainous region, respectively. Meanwhile, in Northern China, the Huang-Huai Plain region, northwest inland China, the southern hilly region, and the southwest hilly and mountainous region, the increase in the yield of silage maize at harvest reached its maximum, and the corresponding silage maize cultivars were Yayu 8, Baimaya, Xinyu 9, Aoyu 5102, and Yuqingyu 3, respectively. This study provides reasonable guidance on suitable N rates for improving the yield and N contribution rate of silage maize in China and various other planting regions.