Identification of driving forces for windbreak and sand fixation services in semiarid and arid areas: A case of Inner Mongolia, China

Abstract

Soil wind erosion is a global problem that leads to increasingly serious regional land degradation, where the need for windbreak and sand fixation services (WSFS) is substantial. Inner Mongolia plays an important role in global semiarid and arid areas and the severe land degradation resulting from soil wind erosion warrants an urgent solution. However, the mechanism of influence of various driving factors on windbreak and sand fixation services is still not fully studied. In this paper, the revised wind erosion equation (RWEQ) model was used to synthesize the monthly spatiotemporal dynamics of soil wind erosion modulus (SWEM) and WSFS in Inner Mongolia from January 2000 to February 2020 from a semi-monthly scale. The influencing factors of WSFS were examined from both natural and anthropogenic aspects. Results show that over the past 20 years, the average SWEM in Inner Mongolia was 118.06 t ha−1 yr−1, the areas with severe wind erosion were mainly concentrated in the desert areas in the southwest of Inner Mongolia, and the forests in the northeast suffered less soil wind erosion. Meanwhile, the average WSFS was 181.11 × 108 t yr−1, with the high-value areas mainly located in major deserts, sandy land, and the area bordering Mongolia in the north and the low-value areas mainly located in the densely forested northeast and the Gobi Desert in the northwest. Both SWEM and WSFS showed a clear downward trend and a certain periodicity over the past 20 years. WSFS showed two peaks a year (April and October). Among the natural factors, precipitation and NDVI showed a significant correlation with WSFS and were identified as the main driving factors of WSFS, whereas temperature had no significant correlation. Among the anthropogenic factors, farming and animal husbandry intensity and GDP showed a positive correlation with WSFS, whereas population showed a negative correlation. These four types of factors were identified as socio-economic factors that drive WSFS. Meanwhile, WSFS did not show any significant correlation with the administrative area. Land use change contributed to a large proportion of WSFS change, thereby suggesting that the intensity of human activities is another central driver of WSFS.