Long-term vegetation restoration increases deep soil carbon storage in the Northern Loess Plateau

Abstract

Afforestation plays an important role in soil carbon storage and water balance. However, there is a lack of information on deep soil carbon and water storage. The study investigates the effect of returning farmland to the forest on soil carbon accumulation and soil water consumption in 20-m deep soil profile in the hilly and gully region of the Chinese Loess Plateau. Four sampling sites were selected: Platycladus orientalis (Linn.) Franco forest (PO: oriental arborvitae), Pinus tabulaeformis Carr. Forest (PT: southern Chinese pine), apple orchard (AO) and farmland (FL, as a control). Soil organic carbon (SOC) and soil inorganic carbon (SIC) content were measured in 50-cm sampling intervals of 20-m soil profiles, as well as the associated factors (e.g. soil water content). The mean SOC content of PT was the highest in the 1–5 m layer and that of FL was the lowest (p < 0.05). Compared with FL, the SOC storages of PO, PT and AO increased by 2.20, 6.33 and 0.90 kg m−2 (p > 0.05), respectively, in the whole profile. The SIC content was relatively uniform throughout the profile at all land-use types and SIC storage was 9–10 times higher than SOC storage. The soil water storage of PO, PT and AO was significantly different from that of FL with a decrease of 1169.32, 1161.60 and 1139.63 mm, respectively. After the 36-yrs implementation of the “Grain for Green” Project, SOC in 20 m soil profiles increased as a water depletion cost compared with FL. Further investigation is still needed to understand the deep soil water and carbon interactions regarding ecological restoration sustainability in the Northern Loess Plateau.

Energy Use Greenization, Carbon Dioxide Emissions, and Economic Growth: An Empirical Analysis Based in China

“…Energy use directly and/or indirectly contributes to economic growth (Wu et al, 2021). Conversely, other studies showed that energy use is determined by economic growth and not vice versa (Lan et al, 2021); several studies also found that both true GDP and energy use are interdependent, and there is bidirectional causality between them (Bekun et al, 2021c). However, some studies found that there is no causal relationship between energy use and economic development (Bekun et al, 2021b;Fang et al, 2022).…”

Application of a Novel Hybrid Machine Learning Algorithm in Shallow Landslide Susceptibility Mapping in a Mountainous Area

“…NDVI can show surface reflectance of the area and yield quantitative estimates of the vegetation biomass and growth ; Liu et al, 2022), which can influence landslides. TWI, SPI, TPI, VRM, and valley depth are the secondary DEM products that have been widely used for landslide prediction modeling (Li and Zhang, 2008;Zhang et al, 2019a;Dou et al, 2019b;Lan et al, 2021;. We incorporated the mean annual rainfall data from 2001 to 2019 to generate a rainfall map using the inverse distance weighted (IDW) method (Chao et al, 2021;de Jesus et al, 2021).…”

Analysis of the recent trends in vegetation dynamics and its relationship with climatological factors using remote sensing data for Caspian Sea watersheds in Iran

“…Vegetation cover is often used as a climate impact indicator in climate change studies. Also, because of the vital role of vegetation changes in the hydrological and biochemical cycles of the climate and its influence on the atmospheric energy balance, it must be considered in such studies (Olafsson and Rousta, 2021;Lan et al, 2021).…”