TXTao Xie

Tao Xie

*This is an algorithmically generated author record based on publicly available information.

Tao Xie has a total of 9 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Spatiotemporal Variability and Driving Factors of Vegetation Net Primary Productivity in the Yellow River Basin (Shaanxi Section) from 2000 to 2022

    by Qiuman Liu, Du Lyu, Tao Xie, Lu Cui, Yifan Ma, Yunfeng Zhang

    Net primary productivity (NPP) is a key metric for assessing ecosystem functionality and sustainability. This study utilized MOD17A3 NPP data in conjunction with trend analysis, a gravity center model, and the Geodetector method to examine the spatiotemporal evolution and driving mechanisms of NPP across the Yellow River Basin (Shaanxi section) from 2000 to 2022. Results revealed: (1) The average NPP over the study period was 353.01g C m−2 with an upward trend of 9.7 g C m−2yr−1; spatially, NPP increased from north to south, with significant variability in northern Shaanxi and a 17.89 km northeastward shift in NPP’s gravity center. (2) Areas exhibiting significant NPP increases (slope > 0, p < 0.01) comprised 97.83% of the region, while declines were mainly observed in Guanzhong. (3) Normalized Difference Vegetation Index (NDVI) was the dominant factor, with the strongest synergistic, nonlinear interaction with land use type reflecting human activities (q = 0.831), indicating that the combined influence of climate factors, land surface factors, and human activities amplifies the explanatory effect on NPP variability. The study demonstrates an overall improvement in NPP, although local declines occurred, and its spatial distribution was influenced by a combination of natural and human factors. These findings will provide data support for the high-quality development of the Yellow River Basin.

  • Open Access

    Analyzing the Spatiotemporal Dynamics and Driving Forces of Ecological Environment Quality in the Qinling Mountains, China

    by Jiachen Liu, Tao Xie, Du Lyu, Lu Cui, Qiuman Liu

    The Qinling Mountains serve as a vital ecological barrier for China, needing regular monitoring for sustainable progress. The present study analyzed the Qinling Mountains (sections in Shaanxi province) via the Google Earth Engine (GEE) and Landsat images, constructing a Remote Sensing Ecological Index (RSEI) for quantitatively analyzing the spatiotemporal evolution of the ecological environment quality from 1990 to 2020. Additionally, this study integrated geodetector and multiscale geographically weighted regression (MGWR) to discern the driving factors influencing ecological quality. The results indicated the following: (1) over the 30 years, the RSEI in the study area initially declined (1990–2005) and then began to improve (2005–2020), demonstrating an overall upward trend; (2) RSEI varied with topography: lower values corresponded to lower elevations (20°); and (3) NDVI, DEM, land use, and the presence of protected areas emerged as the main driving forces of ecological quality. The interaction between ecological conservation policies and socioeconomic factors enhanced the explanatory strength for the differentiation in ecological environment quality. In conclusion, factors like increased vegetation cover and the establishment of protected areas have significantly promoted the improvement of ecological environment quality in the Qinling region, making this study a scientific reference for providing ecological environment protection and promoting high-quality development.


  • Open Access

    Impacts of Different Types of Vegetation Restoration on the Physicochemical Properties of Sandy Soil

    by Du Lyu, Qiuman Liu, Tao Xie, Yahui Yang

    Understanding the integrated effects of vegetation types on the physicochemical properties and quality of sandy soils is crucial for guiding vegetation reconstruction and ecological restoration in desertified areas. This study selected three vegetation types at the southern edge of the Mu Us sandy land, including fenced Leymus secalinus Tzvel. grassland (LS), natural Hedysarum mongolicum Turcz (HM) forest land, and Salix cheilophila Schneid. (SC) forest land, as well as sandy land as a control (SD). The differences in the soil physicochemical properties were investigated by collecting soils from three layers within 0–60 cm. The soil quality index (SQI) was calculated using principal component analysis to comprehensively evaluate the soil quality. This study found that the soil physicochemical properties differed significantly among the plots and layers, and the soil properties exhibited a vertical distribution, with chemical indicators concentrated in the surface layer. As depth increased, differences in soil properties between the vegetation and control plots diminished, with vegetation influence mainly in the 0–20 cm layer. Among all the sample sites, the 0–20 cm layer of LS had the highest organic matter content (5.98 g/kg), which was 2.25, 2.28, and 4.71 times that of HM, SC, and SD, respectively. Moreover, LS had the lowest bulk density (1.35 g/cm3), which was 0.89, 0.91, and 0.86 times lower than that of HM, SC, and SD, respectively. The effects of different vegetation restoration types on the comprehensive quality of soil were different, as shown in LS (0.15) > HM (0.11) > SC (0.10) > SD (0.08). In conclusion, all three vegetation restoration types significantly affected the soil physicochemical properties and led to different degrees of variability of soil indexes in the vertical profile, and the fenced grassland restoration type may be preferable for ecological restoration and reconstruction in this region.