Search Results (4)

Eurasian drylands are vital for the global climate and ecological balance. Quantifying spatiotemporal variations in surface soil moisture (SSM) is essential for monitoring water, energy, and carbon cycles. The suitability of recent global-scale surface soil moisture datasets for Eurasian arid and semi-arid regions has not been comprehensively evaluated. This study investigates spatiotemporal trends of five SSM products—MERRA-2, ESACCI, GLEAM, GLDAS, and ERA5—from 1980 to 2023. The performance of these products was evaluated using in situ station data and the three-cornered hat (TCH) method, followed by partial correlation analysis to assess the influence of environmental factors, including mean annual temperature (MAT), mean annual precipitation (MAP), potential evapotranspiration (PET), vapor pressure deficit (VPD), and leaf area index (LAI), on SSM from 1981 to 2018. The results showed consistent SSM patterns: higher values in India, the North China Plain, and Russia, and lower values in the Arabian Peninsula, the Iranian Plateau, and Central Asia. Regionally, MAT, PET, VPD, and LAI increased significantly (0.04 °C yr⁻¹, 1.66 mm yr⁻¹, 0.004 kPa yr⁻¹, and 0.003 m² m⁻² yr⁻¹, respectively; p < 0.05), while MAP rose non-significantly (0.29 mm yr⁻¹). ERA5 exhibited the strongest correlation with in situ station data (R² = 0.42), followed by GLEAM (0.37), ESACCI (0.28), MERRA2 (0.19), and GLDAS (0.17). Additionally, ERA5 showed the highest correlation (correlation = 0.72), while GLEAM had the lowest bias (0.03 m³ m⁻³) and ESACCI exhibited the lowest ubRMSE (0.03 m³ m⁻³). The three-cornered hat method identified ERA5 and GLDAS as having the lowest uncertainties (<0.03 m³ m⁻³), with ESACCI exceeding 0.05 m³ m⁻³ in northern regions. Across land cover types, cropland had the lowest uncertainty among the five SSM products, while forest had the highest. Partial correlation and dominant factor analysis identified MAP as the primary driver of SSM. This study comprehensively evaluated SSM products, highlighting their strengths and limitations. It underscored MAP’s crucial role in SSM dynamics and provided insights for improving SSM datasets and water resource management in drylands, with broader implications for understanding the hydrological impacts of climate change. Full article

Eurasian dryland ecosystems consist mainly of cropland and grassland, and their changes are driven by both natural factors and human activities. This study utilized the normalized difference vegetation index (NDVI), gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) to analyze the changing characteristics of vegetation activity in Eurasia over the past two decades. Additionally, we integrated the mean annual temperature (MAT), the mean annual precipitation (MAP), the soil moisture (SM), the vapor pressure deficit (VPD) and the terrestrial water storage (TWS) to analyze natural factors’ influence on the vegetation activity from 2003 to 2022. Through partial correlation and residual analysis, we quantitatively described the contributions of both natural and human factors to changes in vegetation activity. The results indicated an overall increasing trend in vegetation activity in Eurasia; the growth rates of vegetation greenness, productivity and photosynthetic capacity were 1.00 × 10⁻³ yr⁻¹ (p < 0.01), 1.30 g C m⁻² yr⁻² (p < 0.01) and 1.00 × 10⁻³ Wm⁻²μm⁻¹sr⁻¹yr⁻¹ (p < 0.01), respectively. Furthermore, we found that soil moisture was the most important natural factor influencing vegetation activity. Human activities were identified as the main driving factors of vegetation activity in the Eurasian drylands. The relative contributions of human-induced changes to NDVI, GPP and SIF were 52.45%, 55.81% and 74.18%, respectively. These findings can deepen our understanding of the impacts of current natural change and intensified human activities on dryland vegetation coverage change in Eurasia. Full article

Identifying the changes in dryland functioning and the drivers of those changes are critical for global ecosystem conservation and sustainability. The arid and semi-arid regions of northern China (ASARNC) are located in a key area of the generally temperate desert of the Eurasian continent, where the ecological conditions have experienced noticeable changes in recent decades. However, it is unclear whether the ecosystem functioning (EF) in this region changed abruptly and how that change was affected by natural and anthropogenic factors. Here, we estimated monthly rain use efficiency (RUE) from MODIS NDVI time series data and investigated the timing and types of turning points (TPs) in EF by the Breaks For Additive Season and Trend (BFAST) family algorithms during 2000–2019. The linkages between the TPs, drought, the frequency of land cover change, and socioeconomic development were examined. The results show that 63.2% of the pixels in the ASARNC region underwent sudden EF changes, of which 26.64% were induced by drought events, while 55.67% were firmly associated with the wetting climate. Wet and dry events were not detected in 17.69% of the TPs, which might have been caused by human activities. TP types and occurrences correlate differently with land cover change frequency, population density, and GDP. The improved EF TP type was correlated with the continuous humid climate and a reduced population density, while the deteriorated EF type coincided with persistent drought and increasing population density. Our research furthers the understanding of how and why TPs of EF occur and provides fundamental data for the conservation, management, and better decision-making concerning dryland ecosystems in China. Full article

In Asian deserts environmental and anthropomorphic dust is a significant health risk to rural populations. Natural sources in dry landscapes are exacerbated by human activities that increase the vulnerability to dust and dust-borne disease vectors. Today in Central and Inner Asian drylands, agriculture, mining, and rapid development contribute to dust generation and community exposure. Thorough review of limited dust investigation in the region implies but does not quantify health risks. Anthropogenic sources, such as the drying of the Aral Sea, highlight the shifting dust dynamics across the Central EurAsian steppe. In the Gobi Desert, our case study in Khanbogd, Mongolia addressed large-scale mining’s potential dust risk to the health of the local population. Dust traps showed variable exposure to particulates among herder households and town residents; dust density distribution indicated that sources beyond the mine need to be considered when identifying particulate sources. Research suggests that atmospheric dust from multiple causes may enhance human particulate exposure. Greater awareness of dust in greater Central Asia reflects community concern about related health implications. Future human well-being in the region will require more thorough information on dust emissions in the changing environment. Full article