您选择的条件: BAO Yuhai
  • Grazing alters sandy soil greenhouse gas emissions in a sand-binding area of the Hobq Desert, China

    分类: 环境科学技术及资源科学技术 >> 环境科学技术基础学科 提交时间: 2022-06-13 合作期刊: 《干旱区科学》

    摘要: Abstract: Deserts are sensitive to environmental changes caused by human interference and are prone to degradation. Revegetation can promote the reversal of desertification and the subsequent formation of fixed sand. However, the effects of grazing, which can cause the ground-surface conditions of fixed sand to further deteriorate and result in re-desertification, on the greenhouse gas (GHG) fluxes from soils remain unknown. Herein, we investigated GHG fluxes in the Hobq Desert, Inner Mongolia Autonomous Region of China, at the mobile (desertified), fixed (vegetated), and grazed (re-desertified) sites from January 2018 to December 2019. We analyzed the response mechanism of GHG fluxes to micrometeorological factors and the variation in global warming potential (GWP). CO2 was emitted at an average rate of 4.2, 3.7, and 1.1 mmol/(m2h) and N2O was emitted at an average rate of 0.19, 0.15, and 0.09 mol/(m2h) at the grazed, fixed, and mobile sites, respectively. Mean CH4 consumption was as follows: fixed site (2.9 mol/(m2h))>grazed site (2.7 mol/(m2h))>mobile site (1.1 mol/(m2h)). GHG fluxes varied seasonally, and soil temperature (10 cm) and soil water content (30 cm) were the key micrometeorological factors affecting the fluxes. The changes in the plant and soil characteristics caused by grazing resulted in increased soil CO2 and N2O emissions and decreased CH4 absorption. Grazing also significantly increased the GWP of the soil (P

  • Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau

    分类: 地球科学 >> 地理学 提交时间: 2021-04-30 合作期刊: 《干旱区科学》

    摘要: Snow cover is an important water source for vegetation growth in arid and semi-arid areas, and grassland phenology provides valuable information on the response of terrestrial ecosystems to climate change. The Mongolian Plateau features both abundant snow cover resources and typical grassland ecosystems. In recent years, with the intensification of global climate change, the snow cover on the Mongolian Plateau has changed correspondingly, with resulting effects on vegetation growth. In this study, using MOD10A1 snow cover data and MOD13A1 Normalized Difference Vegetation Index (NDVI) data combined with remote sensing (RS) and geographic information system (GIS) techniques, we analyzed the spatiotemporal changes in snow cover and grassland phenology on the Mongolian Plateau from 2001 to 2018. The correlation analysis and grey relation analysis were used to determine the influence of snow cover parameters (snow cover fraction (SCF), snow cover duration (SCD), snow cover onset date (SCOD), and snow cover end date (SCED)) on different types of grassland vegetation. The results showed wide snow cover areas, an early start time, a late end time, and a long duration of snow cover over the northern Mongolian Plateau. Additionally, a late start, an early end, and a short duration were observed for grassland phenology, but the southern area showed the opposite trend. The SCF decreased at an annual rate of 0.33%. The SCD was shortened at an annual rate of 0.57 d. The SCOD and SCED in more than half of the study area advanced at annual rates of 5.33 and 5.74 DOY (day of year), respectively. For grassland phenology, the start of the growing season (SOS) advanced at an annual rate of 0.03 DOY, the end of the growing season (EOS) was delayed at an annual rate of 0.14 DOY, and the length of the growing season (LOS) was prolonged at an annual rate of 0.17 d. The SCF, SCD, and SCED in the snow season were significantly positively correlated with the SOS and negatively correlated with the EOS and LOS. The SCOD was significantly negatively correlated with the SOS and positively correlated with the EOS and LOS. The SCD and SCF can directly affect the SOS of grassland vegetation, while the EOS and LOS were obviously influenced by the SCOD and SCED. This study provides a scientific basis for exploring the response trends of alpine vegetation to global climate change.