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This study investigates the novel approach of synergizing desert vegetation with shelter forests to enhance windbreak efficiency in a transitional zone between the Korla oasis and the Taklimakan Desert, northwest China. Through an extensive field survey and experimental setup, we evaluated the impact of different shelterbelt configurations on wind speed reduction. Three types of shelter forests were examined: multi-row Poplar (Populus alba), single-row Jujube (Ziziphus jujube), and a mixed-species layout combining one row of Jujube and two rows of Poplar trees. Wind speed measurements were recorded at multiple heights across three zones—open field, between desert vegetation and shelterbelt, and leeward of the shelterbelt—over a three-month period (April to June, 2023). The findings reveal a significant reduction in wind speed, particularly on the leeward side, with multi-row and mixed-species configurations proving the most effective. The highest synergistic efficiency, observed in the mixed-species shelter forest, showed a windbreak efficiency improvement of over 20% compared to desert vegetation alone. This study provides new insights into the combined effectiveness of desert vegetation and shelter forests, offering a strategic framework for designing shelterbelts in arid environments. These results underscore the critical role of diverse, structured vegetation arrangements in combating wind erosion and contribute to the development of sustainable ecological management practices for desert regions worldwide. [ABSTRACT FROM AUTHOR]

The Altay Mountains' forests are vital to Xinjiang's terrestrial ecosystem, especially water regulation and conservation. This study evaluates vegetation evapotranspiration (ET) from 2000 to 2017 using temperature, precipitation, and ET data from the China Meteorological Data Sharing Service. The dataset underwent quality control and was interpolated using the inverse distance weighted (IDW) method. Correlation analysis and climate trend methodologies were applied to assess the impacts of temperature, precipitation, drought, and extreme weather events on ET. The results indicate that air temperature had a minimal effect on ET, with 68.34% of the region showing weak correlations (coefficients between −0.2 and 0.2). Conversely, precipitation exhibited a strong positive correlation with ET across 98.91% of the area. Drought analysis, using the standardized precipitation evapotranspiration index (SPEI) and the Temperature Vegetation Dryness Index (TVDI), showed that ET was significantly correlated with the SPEI in 96.47% of the region, while the TVDI displayed both positive and negative correlations. Extreme weather events also significantly influenced ET, with reductions in the Simple Daily Intensity Index (SDII), heavy precipitation days (R95p, R10), and increases in indicators like growing season length (GSL) and warm spell duration index (WSDI) leading to variations in ET. Based on the correlation coefficients and their significance, it was confirmed that the SII (precipitation intensity) and R95p (heavy precipitation) are the main factors causing vegetation ET increases. These findings offer crucial insights into the interactions between meteorological variables and ET, essential information for sustainable forest management, by highlighting the importance of optimizing water regulation strategies, such as adjusting species composition and forest density to enhance resilience against drought and extreme weather, thereby ensuring long-term forest health and productivity in response to climate change. [ABSTRACT FROM AUTHOR]

Taitema Lake, situated at the terminus of the Tarim River Basin in Northwest China, represents a crucial ecological resource impacted by climate variability and anthropogenic interventions. In this study, we investigate the dynamic changes in Taitema Lake's area and water quality resulting from the implementation of an ecological water transfer project in 2000. Leveraging Landsat remote sensing data and comprehensive water quality monitoring, we analyzed the relationship between lake area variations and shifts in water quality parameters. Notably, our findings reveal a significant increase in Taitema Lake's area from 9.4 km2 in 2000 to 320 km2 in 2013. Concurrently, water quality indicators exhibited marked fluctuations, with total salt content ranging from 45,323.6 mg/L in 2000 to 970.4 mg/L in 2010 before increasing to 14,586.3 mg/L by 2014. Furthermore, a linear regression analysis highlights the moderate positive correlation between lake area and mineralization (R2 = 0.506) and sodium levels (R2 = 0.4907). Additionally, chloride (R2 = 0.5681) and sulfate (R2 = 0.6213) concentrations demonstrated a strong negative correlation with the lake area, indicative of a dilution effect. Furthermore, a comparison of water quality indicators between the years of minimum (2008) and maximum (2013) lake area underscores improvements in pH, chemical oxygen demand, and anionic surfactant concentrations as the lake area increased. Our study provides valuable insights into the effectiveness of ecological water management strategies in restoring and maintaining the ecological health of Taitema Lake, thereby informing evidence-based decision-making for the sustainable management of freshwater resources in arid environments. [ABSTRACT FROM AUTHOR]

The Taklimakan Desert in northwest China stands as a significant contributor to dust storms, with its fringe oases already designated as ecologically fragile due to the severe impacts of these storms. This study focuses on Moyu County, situated on the southwest edge of the Taklimakan Desert, examining the origin and transport pathways of dust storms from 2004 to 2021. The classification involves utilizing a 36 h backward trajectory model and the k-means clustering technique, resulting in three clusters displaying distinct transport pathways and entry directions. Air pollutant concentrations at the study site corresponding to each cluster are analyzed to elucidate the contribution of dust storms from different directions. The results categorize 1952 dusty days into three categories: NE-SE (cluster 1), N-N (cluster 2), and NW-W (cluster 3). The highest frequency of dust storms, accounting for 64% of the total suspended dust weather, originates from the northeast and southeast direction (NE-SE category), with relatively weak intensity, mainly as suspended dust (71.5%). Strong sand storms predominantly occur from the northwest direction (57.8%). Cluster 1 (the southeast direction) exhibits a higher concentration of SO2, NO2, and CO, mainly associated with its pathway over anthropogenically polluted areas. Conversely, Cluster 3 (northwest direction) shows higher PM10 and PM2.5 concentrations due to increased wind speed and stronger dust storm intensity. The study develops dust storm early warning schemes based on 15-day advance predictions, utilizing an 18-year trajectory model and local monitoring data. This proposed warning scheme serves as a predictive tool for potential dust storm events and air pollution levels, aiding in both scientific research and policy formulation for dust storm mitigation and adaptation. The data obtained also hols relevance for conducting further scientific research in this field. [ABSTRACT FROM AUTHOR]